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==== Front Mol Diagn Ther Mol Diagn Ther Molecular Diagnosis & Therapy 1177-1062 1179-2000 Springer International Publishing Cham 633 10.1007/s40291-022-00633-y Acknowledgement to Referees Acknowledgement to Referees 12 12 2022 13 © Springer Nature Switzerland AG 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. ==== Body pmcDear Reader, We would like to take this opportunity to thank all who have contributed to ensuring the journal has thrived despite the extraordinary circumstances that the science community, and the world in general, has faced in the past couple of years. Firstly, I would like to thank the authors of the articles published in Molecular Diagnosis & Therapy over the course of 2022. The willingness and enthusiasm of our authors to contribute content to the journal are crucial for its continued success. We are also very grateful to the members of the journal’s Honorary Editorial Board, who have acted as peer reviewers and authors, and have provided guidance on journal content, policy and processes. The high quality of the content published in Molecular Diagnosis & Therapy has been reflected in the most recent impact factor of 4.476, a record high for the journal and a CiteScoreTM of 6.9. Further, Molecular Diagnosis & Therapy has published content in a timely manner, with an average time from submission to first decision of 17 days and from acceptance to online publication of 30 days. The quality of published articles is also testament to the diligence of the peer reviewers, whose willingness to share their expertise ensures that the journal’s content is held to the highest standard. We would like to acknowledge the following individuals who acted as reviewers for Molecular Diagnosis & Therapy in the last 12 months: Hoda Abdallah, Egypt Hamid M. Abdolmaleky, USA James B. Adams, USA Walter Adriani, Italy Trevor E. Angell, USA Luca Antonioli, Italy Xiaomin Bao, USA Christian Barro, USA Alakananda Basu, USA Sabina Baumgartner-Parzer, Austria Carla Boccaccio, Italy Yurii S. Borovikov, The Russian Federation Camille Boulagnon-Rombi, France Renáta Bozó, Hungary Erwin Brosens, The Netherlands María José Buitrago, Spain Emil Bulatov, The Russian Federation Oscar Campuzano, Spain Fabio Candotti, Switzerland S.C. Carneiro, Brazil Gabriella Castoria, Italy Lindsay J. Celada, USA Nishant Chakravorty, India Som S. Chatterjee, USA Max Chernesky, Canada Elaine Y.Y. Cheung, Australia Javier Chinen, USA Peter Choi, USA Andrew J. Colebatch, Australia Niall Corcoran, Australia Elena De Vita, UK Charles R. Dean, USA Selami Demirci, USA Silvano Dragonieri, Italy Shangming Du, Germany Shiwei Duan, China Reinhard Dummer, Switzerland Thomas Eggermann, Germany Jakub P. Fichna, Poland Claudio Fiocchi, USA Robert J. Fontana, USA Renato Franco, Italy Anja Gäckler, Germany Maria Galindo, Spain Yu-Zhen Gao, China Eleni Gavriilaki, Greece Éloïse Giabicani, France Roberta Giordo, United Arab Emirates Heather L. Glasgow, USA Andrey S. Glotov, The Russian Federation Yoel Gofin, USA Svetlana Gorokhova, France Aleksandra Grela-Wojewoda, Poland Scott D. Grosse, USA Jian-Long Guan, China Fen Guo, USA Xu-Guang Guo, China Peter Hagedorn, Denmark Tristan Hardy, Australia Atif A. Hashmi, Pakistan Beate Haugk, UK Rong He, USA Robert L. Hendren, USA Daniel L. Hertz, USA Daniel Hilger, Germany Matthew I. Hiskens, Australia Daniel J. Hodson, UK Christopher L. Holley, USA Jason Howitt, Australia Susan Hsiao, USA Chao-Kai Hsu, Taiwan, Republic of China Fabien Hubert, France Cristiane Ida, USA Chukwuemeka V. Ikpeazu, USA Gino In, USA Tadeusz Issat, Poland Christopher M. Jackson, USA Hartmut Jaeschke, USA Aditi Jain, USA Biljana Jekic, Serbia Scott D. Jewell, USA Ivana Joksic, Serbia Anna Kablak-Ziembicka, Poland Jennifer Kalish, USA Alexandra Kalogeraki, Greece Murat Karaoğlan, Turkey Olga Karpicheva, The Russian Federation Nasibeh Karimi, USA Anna Kawiak, Poland Melissa A. Kelly, USA Vanessa Kennedy, USA Narae Kim, Japan Eddy Kizana, Australia Indu Kohaar, USA Ciaran Kohli-Lynch, USA Antonis Kourtidis, USA Valentyna Kryklyva, The Netherlands Canan Kuscu, USA Michaela Lackner, Austria Volker Lauschke, Sweden Dimitri Lavillette, China Carsten W. Lederer, Cyprus Loic Lemonnier, France Maria Levkova, Bulgaria Ka Keat Lim, UK Meng Lin, USA Shijie Liu, USA Jose A. Lopez-Escamez, Spain Chia-Feng Lu, Taiwan, Republic of China Andrea Lunardi, Italy Yafeng Ma, Australia Thomas T. MacDonald, UK Anil K. Madugundu, USA Marina Marini, Italy Steven B. Marston, UK Robert McWilliams, USA Michael L. Merchant, USA Sven Michel, Germany Shuji Momose, Japan Kevin Moreau, UK Axel Muendlein, Austria A. Mukhopadhyay, India Vanja Nagy, Austria Ken Natsuga, Japan Irene Netchine, France Ainsley J. Newson, Australia Monika Oldak, Poland Diego Ortega-Del Vecchyo, Mexico Raymond Owens, UK Despina Papakosta, Greece Jai N. Patel, USA Reuben J. Pengelly, UK Germán R. Perez, Argentina Carmen Pheiffer, South Africa Leonardo Z. Pipek, Brazil Federico Prefumo, Italy Mirja Puolakkainen, Finland Sudarshan Rajagopal, USA Sivaprakash Ramalingham, India Marie Ranson, Australia Peter J. Riegman, The Netherlands Carrie Ris-Stalpers, The Netherlands Helen Rizos, Australia Alessandro Rizzo, Italy Jürgen Rödel, Germany Analiz Rodriguez, USA Fausto J. Rodriguez, USA Paul Roepman, The Netherlands Leonardo Roever, Brazil Maria Rossing, Denmark Florence I. Roullet, Canada Somak Roy, USA Rani Sachdev, Australia Lydia Sagath, Finland Fabian Sanchis-Gomar, Spain Gijs W.E. Santen, The Netherlands Roland Schmitz, Germany Roberto Schreiber, Brazil Matthias Schwab, Germany Akansha Shah, USA Jingzhe Shang, China Liming Shen, China Sergey Sidorenko, The Russian Federation Dario Siniscalco, Italy Abay Sisay, Ethiopia Lillian L. Siu, Canada Maria J. Stasia, France Maher A. Sughayer, Jordan Qing Sun, China Dorothy M. Supp, USA Akifumi Takaori-Kondo, Japan Rajkumar P. Thummer, India Xun Tian, China Elena Tirrò, Italy Sara Tomei, Qatar Emina E. Torlakovic, Canada Victor Trevino, Mexico Jan Trøst Jørgensen, Denmark Natalia Trpchevska, Sweden Hin Fung Tsang, Hong Kong, China Shlomo Tsuriel, Israel Hēth R. Turnquist, USA Sony Tuteja, USA Jop van Berlo, USA Mieke Van Bockstal, Belgium Paul van der Leest, The Netherlands Gerardus P.J. van Hout, The Netherlands Rita Verma, USA Tijl Vermassen, Belgium Maria T. Vietri, Italy Cristina Villena, Spain Jun Wang, China Yun Wang, China Joanna Wardlaw, UK Jonathon K. Watts, USA Jesper Wengel, Denmark Michelle M. Williams, USA Jana Wittig, Germany John Woodford, USA Peizeng Yang, China Takahito Yasuda, Japan Xin Yuan, China Elena Zaklyazminskaya, The Russian Federation Shenghong Zhang, China Fusheng Zhou, China Weimin Zhou, China Ying S. Zou, USA I am constantly looking for innovative ways to help improve the discoverability of the work published in the journal. Last year we have launched journal collections (https://link.springer.com/journal/40291/collections) and we now have five topical collections focused on dermatology, diagnosis of COVID-19, droplet digital PCR, brain tumours and breast cancer. I hope that you have found the articles published throughout 2022 to be both interesting and informative. I have appreciated the high quality of content contributed to the journal this year and look forward to keeping you up to date with topical issues in molecular diagnosis and therapy in 2023. With best wishes, Alison Fitches
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==== Front J Comp Physiol A Neuroethol Sens Neural Behav Physiol J Comp Physiol A Neuroethol Sens Neural Behav Physiol Journal of Comparative Physiology. A, Neuroethology, Sensory, Neural, and Behavioral Physiology 0340-7594 1432-1351 Springer Berlin Heidelberg Berlin/Heidelberg 36508004 1596 10.1007/s00359-022-01596-5 Review Effect of natural abiotic soil vibrations, rainfall and wind on anuran calling behavior: a test with captive-bred midwife toads (Alytes obstetricans) De Luca Jacopo [email protected] 1 Zaffaroni-Caorsi Valentina 23 Bosch Jaime 45 Llusia Diego 678 Beltrán Juan Francisco 9 Márquez Rafael 10 1 grid.8509.4 0000000121622106 Dipartimento Di Scienze, Università Degli Studi Roma Tre, Viale Guglielmo Marconi, 446, Rome, Italy 2 grid.8532.c 0000 0001 2200 7498 Departamento de Zoologia, Instituto de Biociências, Universidade Federal Do Rio Grande Do Sul, Avenida Bento Gonçalves, 9500, Prédio 43435, Bairro Agronomia, Porto Alegre, Rio Grande Do Sul 91501-970 Brazil 3 grid.11696.39 0000 0004 1937 0351 University of Trento, (C3A Centro Agricoltura, Alimenti E Ambiente), Trento, Italy 4 grid.10863.3c 0000 0001 2164 6351 IMIB-Biodiversity Research Institute, University of Oviedo-CSIC-Principality of Asturias, Gonzalo Gutiérrez Quirós S/N, 33600 Mieres, Spain 5 Centro de Investigación, Seguimiento Y Evaluación, Parque Nacional de La Sierra de Guadarrama, Cta. M-604, Km 27.6, 28740 Rascafría, Spain 6 grid.5515.4 0000000119578126 Department of Ecology, Terrestrial Ecology Group, Universidad Autónoma de Madrid, Madrid, Spain 7 grid.5515.4 0000000119578126 Centro de Investigación en Biodiversidad y Cambio Global, Universidad Autónoma de Madrid, Madrid, Spain 8 grid.411195.9 0000 0001 2192 5801 Departamento de Ecologia, Laboratório de Animal, Universidade Federal de Goiás, Av. Esperança, S/N, Goiânia, Goiás Brazil 9 grid.9224.d 0000 0001 2168 1229 Department of Zoology, University of Seville, Avenida Reina Mercedes, S/N, 41012 Seville, Spain 10 grid.420025.1 0000 0004 1768 463X Departamento de Biodiversidad y Biología Evolutiva, Fonoteca Zoológica, Museo Nacional de Ciencias Naturales (CSIC), José Gutiérrez Abascal 2, 28006 Madrid, Spain Handling editor: Peter M. Narins. 12 12 2022 19 29 4 2022 16 11 2022 17 11 2022 © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Anurans are known to detect vibrations, but few studies explore relationships between vibrations and resultant behaviors. We studied the reaction of calling captive-bred male midwife toads (Alytes obstetricans) to the randomized playback of a vibrational crescendo stimulus train. We considered two sources of natural abiotic vibrational stimuli: rainfall and wind. Rainfall was expected to induce calling and wind was expected to inhibit it. Playback experiments with two synthetic tones (200 Hz and 300 Hz) tested the sensitivity to pure tones and could possibly reveal a hearing sensitivity trend between these frequencies. The toads did not increase call rate in response to rainfall vibrations and only one of the five wind stimulus levels caused a significant decrease in call rate. This limited response could be explained, because the tested toads came from a captive population, where emergence may not be mediated by rainfall vibrations. We found that A. obstetricans is highly sensitive to very low frequencies, which could explain the sensitivity observed to vibrational stimuli. Playback of a random crescendo stimulus train proves to be a valid approach for addressing behavioral questions. However, the use of a captive population may have been a limitation in the clarity of the results. Supplementary Information The online version contains supplementary material available at 10.1007/s00359-022-01596-5. Keywords Seismic signals Biotremology Communication Behavior Hearing http://dx.doi.org/10.13039/501100009880 Regione Lazio Torno Subito Internship De Luca Jacopo ==== Body pmcIntroduction Anurans have an exquisite seismic sensor for the detection of vibrations (Narins and Lewis 1984). The anuran hearing system has been well-studied in recent years (Gerhardt and Huber 2002; Ryan 2001). However, comparatively little is known about behavioral responses to sensed substrate vibrations (Narins and Lewis 1984; Narins et al. 2007). The inner ear of anurans has a receptor organ for acoustic stimuli generally above 1000 Hz, the basilar papilla, that is homologous to that found in the hearing system of other higher vertebrates, such as birds and mammals. In addition to the basilar papilla, there are at least two other sensory organs in the anuran inner ear: the amphibian papilla and the sacculus (Simmons et al. 2006; Schoffelen et al. 2009). The amphibian papilla, an organ found exclusively in amphibians, is tuned to frequencies between 50 and 1000 Hz, whereas the sacculus is tuned to low frequencies between 20 and 300 Hz. These two organs are known to sense substrate-borne vibrations (Christensen Dalsgaard and Narins 1993; Lewis and Narins 1985) that may be related to behaviors of high selective value (Márquez et al. 2016)⁠. This vibrational sensory system has been reported in a variety of contexts (Hill 2009), e.g., intra-specific signalling (Lewis and Narins 1985; Caldwell et al. 2010; Narins et al. 2018), prey detection (Solano 2016), predator avoidance (Warkentin 2005; Warkentin et al. 2017; Cohen et al. 2019), and detection of environmental cues (Halfwerk et al. 2016; Márquez et al. 2016). In the latter category, the authors showed that vibrations from wind and rain affected the behavior of species exposed to it. This means that, like other animals (Ben-Ari and Inbar 2014; Hill 2001), anurans use vibrational senses to process their surroundings (Halfwerk et al. 2016). Given the importance of the hearing system in amphibian anurans, whose reproduction and survival depend on communication and the perception of the environment, abiotic vibrations could act not only by masking essential pieces of information but also in decision making. We choose as model species the midwife toads (Alytes obstetricans), because we have already evaluated their sensitivity to certain frequencies like the anthropogenic ones (Caorsi et al. 2019), so these further tests will allow us to better understand their vibrational hearing. In particular, we studied the effect of abiotic vibrational noise (wind and rainfall) on the midwife toads using playback experiments to examine if they influence one of the most fundamental activities of anurans reproduction, the calling activity. Furthermore, we tested two synthetic tones (200 Hz and 300 Hz) derived from the peak frequencies of wind and rainfall. These playback stimuli allow us to explore the sensitivity of the toads to pure tones and to possibly detect a hearing sensitivity trend within these frequencies. We expect the wind to be an inhibitor of calling activity as active toads are less active on windy nights, possibly due to the desiccating effect of wind on toads (Oseen and Wassersug 2002; Steelman and Dorcas 2010; Brown 2013); while rainfall, on the other hand, is known to act as a trigger of emergence and activity in some species (Márquez et al. 2016) and is thus expected not to inhibit calling activity and eventually even increase calling rate in the study species. Materials and methods Location and study species The playback experiments were completed between in June and July 2020 in the Amphibian Recovery Center of the Sierra de Guadarrama National Park, where a captive population of midwife toads (Alytes obstetricans, Alytidae) is established for the reintroduction of the toads in their natural habitats (Martín-Beyer et al. 2011). This anuran species is widespread across Europe but has suffered substantial declines throughout its range and population size, especially due to chytridiomycosis and ranavirosis (e.g., Bosch et al. 2001, 2021). The genus is known for its remarkable reproductive behavior, with males carrying the eggs entwined around their hind legs on land for about a month, from fertilization to hatching. Males typically call in open spaces, while tending occurs mainly underground. During this period the eggs are kept under adequate temperature and moisture conditions, away from predation or infection by fungi, and finally, the mature egg masses are released at the shore of a body of water (Márquez and Verrell 1991; Márquez 1995; Márquez and Bosch 1995). We tested a total of 15 male radio-tagged individuals that were temporarily housed in the outdoor enclosure of the Center. Animals are housed indoors in winter to avoid low temperatures and to allow them to breed year-round and are kept in outdoor enclosures from May to September. After each complete experiment, the tested animal was identified and returned to its indoor terrarium. This population was selected for testing, because travel between regions was forbidden in Spain during the 2020 field season due to the COVID-19 pandemic and the captive population was within the limits of the region of Madrid. We verified that every animal was healthy by observation when measuring its length and weight after the test. We ensured that every animal had the minimum stress possible, minimizing handling and transportation times. Every individual tested was left 24 h in the open enclosure before testing. Experiments started after sunset and the emission of stimuli started when the focal male seemed at the peak of its vocal activity. Playback stimuli For the experiments, we constructed a set of 9 playback crescendo stimuli trains: rainfall, wind in five different intensities (5 km/h, 6 km/h, 7 km/h, 8 km/h, 9 km/h), a pure tone of 200 Hz, a pure tone of 300 Hz, and a silence stimulus (control). All stimuli lasted 2 min and were modified by applying a linear ‘fade-in’ amplitude filter from 0% to 100%, using Audacity 2.0.2 (SourceForge, Carnegie Mellon University, Pittsburgh, PA, USA) Before applying the ‘fade-in’ amplitude filter, the stimuli were peak normalized to 100% with some exceptions: the amplitude of the 5 wind stimuli was scaled, so that the highest wind level (9 km/h) was peak normalized at 100% but the rest kept their relatively lower amplitudes. Therefore, the highest peaks of the 4 lower wind stimuli did not reach 100%. The advantage of using fade-in stimuli is that only the maximum intensity of each stimulus had to be adjusted to the conditions when re-cording in the field. This was adjusted using exactly the same equipment and recording level in the playbacks as was used in the recording of the wind playback and ensuring recording level did not saturate. As for rainfall the maximum level was adjusted to the maximum level of the higher wind speed. Rainfall vibrations were recorded in Puente Ajolí, (5 m.a.s.l. El Rocío, Doñana, Huelva 37º08′01862 N 6º27′44.98″W) in 2012 with an Oyo ONE geophone vertically protected by a foam-covered structure to prevent the direct impact of the drops on the geophone. The stimulus was the same that was used in Márquez et al. (2016). To obtain the spectral components of the rainfall vibration, recordings, FFTs (1,024 points, sampling rate 48 kHz, 61.9 Hz bandwidth) were made using Audacity 2.0.2 and Raven Pro 2.5 (Lab of Ornithology, Cornell University, Ithaca, NY, USA). The recordings obtained had slightly irregular flat spectra toward the lower end of the spectrum. Based on this acoustic signature, a 2-min synthetic vibration stimulus was generated with Audacity 2.0.2 by low-pass filtering broadband noise (100% amplitude). Wind vibrations were recorded in Puerto de Morcuera (1700 masl 40º50′32.76″N, 3º50′10.912 W, Madrid) in July 2020 in a mountain grassland habitat similar to the habitat of the extant natural population of midwife toads in Peñalara, and in the near vicinity. Vibrations were recorded with an Oyo ONE geophone protected (vertically and laterally) by a foam-covered structure to prevent the direct impact of the wind on the geophone, while the wind speed was monitored with a Bresser (model 7002510) portable weather station. Both for rainfall and wind vibrations, the geophone was connected to a custom-made amplifier which in turn was connected to the input of a Sound Devices 744 T recorder. The pure tones of 200 and 300 Hz were included to test if there was a detection bias in the range considered. 200 Hz was an approximate central frequency for the wind stimuli and 300 Hz was an approximate central frequency for the rainfall stimuli. Synthetic stimuli were synthesized with Audacity software, and natural stimuli were edited and played back with the same software too. An online randomizer (https://www.random.org/lists/) was used to generate the random sequence of the stimuli. A single rainfall track was used and a single wind track was used for each of the five wind intensity levels. Experimental design Experiments were carried out for 15 days during male calling activity, starting from 10 p.m., from the 8th of June to the 20th of July 2020. Alytes obstetricans males were calling in an open-air enclosure area with a small accumulation of bricks on a corner, which the toads used as a refuge and from which they called. Toads were individually marked with radio tags. Each toad was only tested once and was returned to its indoor terrarium after reading the tag after the test. One experiment was completed per night. One to three toads were housed in the enclosure but tests were started when only one individual was calling. Occasionally a second non-focal toad would start calling during the test. This was noted and considered in the statistical analyses. Playback vibrations were generated with a portable computer connected to a Kenwood KAC-5205 amplifier (with all filters switched off) and a “Clark Synthesis TST429 Platinum tactile-sound transducer” buried 10 cm below ground 1.5 m away from the bricks. To monitor the intensities of vibrations reaching the toads we placed an Oyo ONE geophone about 10 cm from the refuge that housed the animals during the experiment. The geophone was connected to a custom-made amplifier with a fixed gain of 30db. To record the intensities and number of calls of the toads we used a microphone (Audio Technica AT3032) placed approximately 2 m away from the calling male. The microphone and geophone were connected to a Sound Devices 744 T recorder with 4 channels. Playback was not equalized. The spectral components of the recorded signals by the geophone were only visually inspected at the time of playback and were compared to the emitted natural stimuli to verify that they were no major spectral degradation effects. The emitted stimuli were well within the ranges of the emission equipment (transducer and amplifier). The experimenters were located 4.5 m away from the enclosure, remaining motionless during the playback (Fig. 1).Fig. 1 Experimental setup in the field. The enclosure was 4.8 × 2.5 m wide. The microphone was placed 2 m away from the tested individual and the geophone was placed 10 cm away from it. The transducer was placed at a variable distance, but always more than 1.5 m away from the focal calling individual. Observers were located 4,5 m away from the enclosure Test Protocol Our test was based on the observation of a single calling toad before and during the emission of a crescendo stimulus train, a random sequence of stimuli separated by silence with each stimulus being linearly increasing in amplitude (“crescendo”, or Fade-in 0–100), similar to the technique used in Caorsi et al. (2019), Fig. 2. We emitted a playback train with 9 different stimuli to every individual (a total of 38 min). Every experiment started at 10 pm (sunset time, approximately). Each stimulus was 2 min long, with 2 min of silence before (pre-stimulus) and after (post-stimulus). The stimuli were presented in random order being different for each toad. Before each trial, we measured the temperature and the relative humidity.Fig. 2 Playback scheme (crescendo stimulus train) showing the 9 playback stimuli (total 38 min) presented to each animal in random order. Triangles indicate the increase of the amplitude of the vibration emission within the 2-min treatment Data extraction For every stimulus, pre-stimulus and post-stimulus we measured the following acoustic characteristics and measurements: total number of calls, mean dominant frequency of the last 5 calls, and mean fundamental frequency of the last 5 calls. In addition, we determined for each experiment: the total number of specimens in the enclosure, the total number of specimens calling in the enclosure, background noise, time before hearing the first specimen singing, duration of a call of a specimen before turning silent during the playback of a stimulus, duration of the 1° call group defined as a regular calling, duration of the 2° call group defined as a regular calling, duration of the 3° call group defined as a regular calling and mean duration of all regular call groups. We define regular calling an interrupted call group using Koehler et al. (2017) terminology. These variables represent the duration of the calling bouts of the calls during playback tests. They were recorded to spot toads with low calling activity in case they should not be included in the analyses but we did not exclude any test based on these parameters. The analysis was carried out with the software Raven Pro on an Acer Nitro 5 notebook. The FFT window size used was 2048, passband filter 0.5–10 kHz. Statistical analysis To test the effect of vibration stimuli on the calling activity of the focal individuals, we used a general linear mixed-effects model (LMM, Baayen 2008), as the experiment followed a repeated measured design within individuals. Thus, we included the type of playback stimulus (9 levels) as fixed factor, and individual (15 levels) as random factor. Since environmental temperature and the presence of other calling males may influence the calling activity of the focal males, we included two additional factors as covariates to account for these effects, namely, air temperature (measured every time at the beginning of any experiment) and the maximum number of non-focal males exhibiting calling activity during the playback test. The air temperature was previously z-transformed to be centred and scaled. The response variable of the LMM was estimated as the difference in call rate (number of calls per minute) between the 2-min experimental period (stimulus) and an average of five 2-min silence periods (pre-stimulus and post-stimulus of a given treatment and the entire silence stimulus of a given individual). This variable represents the behavioral response of the focal males to the vibration stimuli in comparison with their behavior during periods without stimuli. The response variable follows a symmetric distribution and hence we fitted a LMM with Gaussian error structure and identity link using the function lmer of the R package lme4 (Bates et al. 2014). The interaction terms and random slopes were not included to reduce model complexity. To test the effect of the stimulus order regardless the kind of vibration, we fitted a similar LMM but replacing type of stimulus by the position of every stimulus in each experimental sequence as fixed effect. The model structure and fitting procedure remained identical. Visual diagnostics (Q–Q plots, residuals plotted against fitted values, etc.) revealed no obvious deviations from the canonical assumptions of linearity, normally distributed and homogenous residuals, and the absence of influential observations in both LMMs. Variance inflation factor (Field 2005) was applied to a standard linear model (excluding the random effect) using the function vif of the R package car (Fox and Weisberg 2011) and indicated no collinearity (VIF < 1.29). The LMMs were fitted using the Maximum Likelihood (rather than Restricted Maximum Likelihood; Bolker et al. 2008) and model inference established by full-null model comparisons (null model comprising without the fixed effect) with a likelihood ratio test using the R function anova (test = “Chisq”; Dobson 2002; Forstmeier and Schielzeth 2011). The effect of covariates was based on additional likelihood ratio tests, comparing the full with respective reduced models using the R function drop1 (Barr 2013). Confidence intervals for model estimates and fitted values were derived using the function bootMer of the R package lme4, using 1000 parametric bootstraps and bootstrapping over the random effects. These intervals were used for post-hoc pairwise comparisons. Finally, we calculated conditional and marginal coefficients of determination with the function r.squaredGLMM of the R package MuMIn (Barton 2022). Significance level was set at 5%. All statistical analysis and figures were performed using R v 3.6.3 (R Core Team 2020). Results The full-null model comparison showed that the type of stimulus significantly influenced the call rate of the focal males (χ2 = 27.1, df = 7, p < 0.001). Specifically, calling activity increased with synthetic vibrations of 200 and 300 Hz, whereas it decreased when males were exposed to vibration stimuli associated with intense wind (7–9 km/h; Fig. 3). However, wide confidence intervals prevent us from establishing clear differences among stimuli. According to the model estimates, only pure tones of 200 and 300 Hz elicited a consistent (positive) response (Table 1). According to a visual inspection using predicted (fitted) values, only wind stimuli at higher intensity (7–9 km/h) showed a consistent (negative) response, with wind stimuli at 7 and 8 km/h evoking a significantly different shift in call rate than pure tone of 300 Hz (Fig. 3). No evidence of rainfall and weak wind vibrations having an effect on call rate was found, as indicated by their 95% confidence intervals including zero (Table 1; Fig. 3). Similarly, temperature and neighbour calling males did not influence calling behavior of the focal males (χ2 = 1.95, df = 1, p = 0.16; χ2 = 1.56, df = 1, p = 0.21, respectively).Fig. 3 Effect of vibrational stimuli on call rate, measured as difference in number of calls per minute between the 2-min experimental period (stimulus) and an average of five 2-min silence periods (pre-stimulus and post-stimulus of a given treatment and the entire silence stimulus of a given individual). Points are mean predicted (fitted) values of shift in call rate, corresponding to the additive effect of each coefficient when taking into account the covariates included in the model. Bars represent 95% confidence intervals for each type of stimulus as obtained with the R function bootMer applied on the fitted regression model. The dashed line indicates no change in the call rate. We considered the effect of a stimulus in call rate as significant if the estimate and corresponding 95% confidence interval did not include zero. Shifts in call rate larger than 0 represent a positive effect (i.e., stimulus increasing calling activity). Shifts in call rate below 0 indicate a negative effect (i.e., stimulus decreasing calling activity). In addition, using confidence intervals for post-hoc pairwise comparisons, we considered the effect of a stimulus as significantly different from another stimulus if their confidence intervals did not overlap Table 1 Model estimates of the effect of the vibration stimuli on call rate of the midwife toad Fixed effects Estimate SE CI.lb CI.ub (intercept) Rainfall  –4.414 3.393  –11.818 1.789 Wind 5 km/h 6.107 3.810  –0.900 13.754 Wind 6 km/h 5.606 3.813 –2.105 13.391 Wind 7 km/h  –3.634 3.813  –10.977 4.197 Wind 8 km/h  –4.213 3.810  –11.541 3.839 Wind 9 km/h  –1.480 3.810  –8.848 5.826 Synthetic 200 Hz 8.587 3.810 1.353 16.549 Synthetic 300 Hz 10.267 3.810 2.685 18.553 Nb, calling males 3.087 2.385  –1.461 8.000 Temperature  –3.106 2.117  –7.049 1.054 The standard error of the estimates (“SE”) and the lower and upper bounds of the 95% confidence intervals (“CI.lb” and “CI-ub”) are shown The fixed factors explained less than a quarter of the total variance (R2m = 0.234), while both fixed and random factors of the model accounted for less than half (R2c = 0.459). The largest proportion of the variability on the response variable that was not explained by fixed factors is due to the “residual variance” (71%), meaning that the differences among the focal individuals (“random variance”, 29%) were less relevant, and factors other than individuals and/or our predictor and covariates should account for this unexplained variability in call rate. Regardless of the type of vibration, the order of stimuli within the experimental sequence had no effect on calling activity of the focal males (χ2 = 8.3, df = 8, p = 0.40), with all stimulus orders showing no significantly different shifts in call rate (Fig. 4). The actual distribution of the order of presentation of the randomly chosen sequences during the experiments indicated that some stimuli, such as rainfall and wind 8 km/h, were presented at the onset of the experiment more often than other stimuli.Fig. 4 Effect of the order of presentation of the stimuli on call rate. Points are mean predicted (fitted) values of shift in call rate, and bars are 95% confidence intervals for each stimulus order. The dashed line indicates no change in the call rate (see further details in Fig. 3) Discussion Among the environmental stimuli, the only significant observed effect on calling rate is limited to the stimulus two of the high levels of wind (7 and 8 km/h) which, as predicted, inhibits calling behavior and thus alters its call rate. The remaining high wind speed (9 km/h) also inhibits the calling rate but the effect is not significant (Table 1 and Fig. 3). The two lighter wind speeds (5 km/h and 6 km/h) increased slightly, not significantly, calling rate. The toads did not react to rainfall vibrations by increasing their call rate. Contrary to expectations, it could be related to the fact that the tested toads came from a captive population, where emergence to the surface is not mediated by rainfall vibrations. This effect has been observed in other species in their natural habitat (Márquez et al. 2016). The vibrations were presented in random order to the toads. Each test had its specific sequence. The random sequences used presented rainfall in the first position on several occasions (3 of 15 toads) but the first stimulus presented did not have a substantially larger inhibitory effect (Fig. 4). On the other hand, the single frequency vibrations (pure tones) increased call rate significantly. This result was not expected and opens many questions about how wide the frequency band of the stimulus has to be to elicit call inhibition and whether airborne stimulation (auditory) may play a role. Anuran auditory neurons have a clear frequency selectivity that characterizes many frog species by their neural tuning curves, or frequency-threshold curves (Dijk et al. 2011; Zakon and Wilczynski 1988). In the focal species, a study measured the sensitivity of the torus semicircularis auditory midbrain to frequencies from 100 to 5000 Hz. It revealed regions of high sensitivity in the low-frequency range, between approximately 100–500 Hz and, in the high-frequency range, between approximately 1200–2400 Hz. The best thresholds in the lower frequency range reached values of approximately 40 dB SPL, occurring at the lowest audio frequency tested (100 Hz), whereas those in the high-frequency range were between 40 and 50 dB SPL (Mohneke and Schneider 1979; Penna et al. 2015). Thus, A. obstetricans is highly sensitive to very low frequencies, which could explain the sensitivity observed to vibrational stimuli (10 Hz and 100 Hz) in previous experiments in nature (Caorsi et al. 2019), and, to a lesser extent, in the present study. The experimental setup of the playback of the crescendo stimulus trains appears to be a valid approach for addressing behavioral questions. The limitation to one exemplar of each natural stimulus may affect the power of the statistical tests applied but it is difficult to increase the number of exemplars per test without increasing excessively the duration of the playback test. Based on the natural calling pattern of the species, the first 2 h after sunset are the best time window to run the tests. On the other hand, the lack of an effect of presentation order (Fig. 4) appears to support this approach. The use of a captive population which is kept in an environment with a high level of anthropogenic vibrations (terrarium maintenance and feeding, aerators of adjacent aquaria and vibration from a nearby road), may have affected the response of the toads to the stimuli if there is habituation. This may explain the limitation in the clarity of the results, although the model used yielded results with factors that explained a sizeable percentage of the variance. If naturally occurring populations of toads tested in the field respond differently, this remains to be demonstrated. Supplementary Information Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 151 KB) Acknowledgements Access and study permits were granted by Parque Nacional de la Sierra de Guadarrama, Spain. We are grateful to Dr. Richard G. Bowker who reviewed the English version of the manuscript and to two anonymous reviewers who provided valuable comments on the study. We thank Roger Mundry for providing R functions to compute GLMM confidence intervals and model assumptions. DL also acknowledges a postdoctoral grant provided by Comunidad de Madrid (2020-T1/AMB-20636, Programa de Atracción de Talento investigador, Spain). Author contributions RM and JFB conceptualized the study. JL and RM collected data and wrote the main manuscript text. VZ-C prepared figures 1 and 2. DL and JB made the statistical analysis and made figures 3, 4 and 5. All authors reviewed the manuscript. All authors contributed to the preparation of the tests. Funding Partial financial support was received from “Torno Subito” scholarship from Lazio Region in Italy (JDL). Data availability The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials. Declarations Conflict of interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Baayen RH Analyzing linguistic data 2008 Cambridge Cambridge University Press Barr DJ Random effects structure for testing interactions in linear mixed-effects models Front Psychol 2013 4 328 10.3389/fpsyg.2013.00328 23761778 Barton K (2022) MuMIn: multi-model inference. R package version 1.46.0. R-Forge. https://CRAN.R-project.org/package=MuMIn. Accessed 12 Oct 2022 Bates D Mächler M Bolker B Walker S Fitting linear mixed-effects models using lme4 J Stat Softw 2014 67 1 1 48 10.18637/jss.v067.i01 Ben-Ari M Inbar M Aphids link different sensory modalities to accurately interpret ambiguous cues Behav Ecol 2014 25 3 627 632 10.1093/beheco/aru033 Bolker BM Brooks ME Clark CJ Geange SW Poulsen JR Stevens MHH White JSS Generalized linear mixed models: a practical guide for ecology and evolution Trends Ecol Evol 2008 24 127 135 10.1016/j.tree.2008.10.008 Bosch J Martínez-Solano I García-París M Evidence of a chytrid fungus infection involved in the decline of the common midwife toad (Alytes obstetricans) in protected areas of Central Spain Biol Conserv 2001 97 331 337 10.1016/S0006-3207(00)00132-4 Bosch J Mora-Cabello de Alba A Marquínez S Price SJ Thumsová B Bielby J Long-term monitoring of amphibian populations of a national park in Northern Spain reveals negative persisting effects of Ranavirus, but not Batrachochytrium dendrobatidis Front Vet Sci 2021 8 64549 10.3389/fvets.2021.645491 Brown DJ Predictive models for calling and movement activity of the endangered Houston toad Am Midl Nat 2013 169 303 321 10.1674/0003-0031-169.2.303 Caldwell MS Johnston GR McDaniel JG Warkentin KM Vibrational signaling in the agonistic interactions of red-eyed treefrogs Curr Biol 2010 20 1012 1017 10.1016/j.cub.2010.03.069 20493702 Caorsi V Guerra V Furtado R Llusia D Miron L Borges-Martins M Both C Narins P Meenderink S Márquez R Anthropogenic substrate-borne vibrations impact anuran calling Sci Rep 2019 10.1038/s41598-019-55639-0 Christensen Dalsgaard J Narins PM Sound and vibration sensitivity of VIIIth nerve fibers in the frogs Leptodactylus albilabris and Rana pipiens pipiens J Comp Physiol A 1993 172 653 662 10.1007/BF00195391 8350283 Cohen KL Piacentino ML Warkentin KM Two types of hatching gland cells facilitate escape-hatching at different developmental stages in red-eyed treefrogs, Agalychnis callidryas (Anura: Phyllomedusidae) Biol J Linn Soc Lond 2019 126 751 767 10.1093/biolinnean/bly214 Dijk P van Mason MJ Schoffelen RLM Narins PM Meenderink SWF Mechanics of the frog ear Hear Res 2011 273 46 58 10.1016/j.heares.2010.02.004 20149854 Dobson AJ An introduction to generalized linear models 2002 Boca Raton Chapman & Hall/CRC Field A Discovering Statistics using SPSS 2005 London Sage Publications Forstmeier W Schielzeth H Cryptic multiple hypotheses testing in linear models: overestimated effect sizes and the winner’s curse Behav Ecol Sociobiol 2011 65 1 47 55 10.1007/s00265-010-1038-5 21297852 Fox J Weisberg S An R companion to applied regression 2011 Thousand Oaks Sage Publications Gerhardt HC Huber F Acoustic communication in insects and anurans. Common problems and diverse solutions 2002 Chicago University of Chicago Press Halfwerk W Ryan MJ Wilson PS Wind- and rain-induced vibrations impose different selection pressures on multimodal signaling Am Nat 2016 188 279 288 10.1086/687519 27501086 Hill PSM Vibration and animal communication: a review Am Zool 2001 41 5 1135 1142 10.1093/icb/41.5.1135 Hill PSM How do animals use substrate-borne vibrations as an information source? Sci Nat 2009 96 1355 1371 10.1007/s00114-009-0588-8 Koehler J Jansen M Rodriguez A Kok PJ Toledo LF Emmrich M Vences M The use of bioacoustics in anuran taxonomy: theory, terminology, methods and recommendations for best practice Zootaxa 2017 4251 1 1 124 10.11646/ZOOTAXA.4251.1.1 28609991 Lewis ER Narins PM Do frogs communicate with seismic signals? Science 1985 227 187 LP 189 10.1126/science.227.4683.187 17843077 Márquez R Female choice in the midwife toads (Alytes obstetricans and A. cisternasii) Behavior 1995 132 1–2 151 161 10.1163/156853995X00342 Márquez R Bosch J Advertisement calls of the midwife toads Alytes (Amphibia, Anura, Discoglossidae) in continental Spain J Zool Syst Evol Res 1995 33 3–4 185 192 10.1111/j.1439-0469.1995.tb00224.x Márquez R Verrell P The courtship and mating of the Iberian midwife toad Alytes cisternasii (Amphibia: Anura: Discoglossidae) J Zool 1991 225 1 125 139 10.1111/j.1469-7998.1991.tb03806.x Márquez R Beltrán JF Llusia D Penna M Narins PM Synthetic rainfall vibrations evoke toad emergence Curr Biol 2016 26 24 R1270 R1271 10.1016/j.cub.2016.11.005 27997835 Martín-Beyer B, Fernández-Beaskoetxea S, García G, Bosch J (2011) Re-introduction program for the common midwife toad and Iberian frog in the Natural Park of Peñalara in Madrid, Spain: can we defeat chytridiomycosis and trout introductions? Digital.CSIC. https://digital.csic.es/handle/10261/124177. Accessed 10 Oct 2021 Mohneke R Schneider H Effect of temperature upon auditory thresholds in two anuran species, Bombina v. variegata and Alytes o. obstetricans (Amphibia, Discoglossidae) J Comp Physiol A 1979 130 9 16 10.1007/BF02582969 Narins PM Lewis ER The vertebrate ear as an exquisite seismic sensor J Acoust Soc Am 1984 76 1384 1387 10.1121/1.391455 6512101 Narins PM Feng AS Fay RR Popper AN Hearing and sound communication in amphibians 2007 New York Springer Narins PM Meenderink SWF Tumulty JP Cobo-Cuan A Márquez R Plant-borne vibrations modulate calling behavior in a tropical amphibian Curr Biol 2018 28 R1333 R1334 10.1016/j.cub.2018.10.056 30513326 Oseen KL Wassersug RJ Environmental factors influencing calling in sympatric anurans Oecologia 2002 133 616 625 10.1007/s00442-002-1067-5 28466161 Penna M Velásquez NA Bosch J Dissimilarities in auditory tuning in midwife toads of the genus Alytes (Amphibia: Anura) Biol J Linn Soc Lond 2015 116 41 51 10.1111/bij.12563 R Core Team R: a language and environment for statistical computing 2020 Vienna R foundation for statistical computing Ryan MJ Recent advances in anuran communication 2001 Washington Smithsonian Institution Press Schoffelen RLM Segenhout JM Dijk P Tuning of the tectorial membrane in the basilar papilla of the northern leopard frog J Assoc Res Otolaryngol 2009 10 309 320 10.1007/s10162-009-0167-x 19488819 Simmons DD Sebastiaan WF Pantelis NV Anatomy, physiology, and function of auditory end-organs in the frog inner ear Hearing and sound communication 2006 NewYork Springer Solano LAR Foraging behavior with possible use of substrate-borne vibrational cues for prey localization in Atelopus laetissimus (Ruiz-Carranza, Ardila-Robayo, and Hernández-Camacho, 1994) Herpetol Notes 2016 9 191 195 Soorae PS Global re-introduction perspectives: more case studies from around the globe 2011 Abu Dhabi IUCN/SSC re-introduction specialist group and environment agency Steelman CK Dorcas ME Anuran calling survey optimization: developing and testing predictive models of anuran calling activity J Herpetol 2010 44 61 68 10.1670/08-329.1 Warkentin KM How do embryos assess risk? Vibrational cues in predator-induced hatching of red-eyed treefrogs Anim Behav 2005 70 59 71 10.1016/j.anbehav.2004.09.019 Warkentin KM Diaz JC Güell BA Jung J Kim SJ Cohen KL Developmental onset of escape-hatching responses in red-eyed treefrogs depends on cue type Anim Behav 2017 129 103 112 10.1016/j.anbehav.2017.05.008 Zakon HH Wilczynski W The evolution of the amphibian auditory system 1988 New York Wiley
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==== Front Potato Res Potato Res Potato Research 0014-3065 1871-4528 Springer Netherlands Dordrecht 9607 10.1007/s11540-022-09607-3 Article Determinants Influencing Selection of Potato Varietal Technology and the Role of Gender in Farm Decisions in Bhutan http://orcid.org/0000-0001-9091-6706 Rai Pradeep [email protected] http://orcid.org/0000-0001-9822-2581 Bajgai Yadunath [email protected] grid.473381.a Department of Agriculture, Ministry of Agriculture and Forests, National Potato Program, National Center for Organic Agriculture (NCOA), Thimphu, Bhutan 12 12 2022 119 27 3 2022 23 11 2022 © The Author(s), under exclusive licence to European Association for Potato Research 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Potato is a primary food and cash crop in Bhutan. The adoption of new varieties has faced some challenges. To address this situation, farmers’ needs and priorities were investigated through varietal demonstration and a field survey in seven of the main potato-growing districts of Bhutan. The role of gender in farm decisions and operations in relation to potato farming was also assessed. Nine quality determinants significantly (χ2 = 376.54, P < 0.001) influenced farmers’ selection of potato varieties. These determinants, in order of their relative preference, were as follows: high productivity (15.5% by weight of mean rank), high market value (13.4%), red-skinned (12.7%), marketability (11.6%), large tubers (11.3%), late-blight resistant (11.3%), micronutrient content (8.8%), short-duration (8.3%) and good taste (7.2%). Potato productivity (yield) and preference vote data were significantly correlated (R = 0.395, P < 0.01) for female farmers but not for male farmers. Similarly, the involvement of female farmers in farm decision-making processes was significantly (P < 0.001) higher than when compared with their male counterparts. However, both genders were equally involved in physical farm operations. Bhutanese potato cropping is highly driven by commercially driven (market) preferences such as yield, colour and size as opposed to subsistence preferences such as micronutrient content. Understanding farmers’ priorities during the development of new potato variety is critical for varietal selection for adoption. Furthermore, understanding the role of women in farm decision-making processes is crucial for adoption of new varietal technology in potato production. These findings may serve as an evidence-based insight to guide research and policy interventions in Bhutan and in similar agroecologies. Keywords Farm operations Farmers’ choice Technology diffusion Varietal technology Women farmers ==== Body pmcIntroduction Potatoes are the fourth most important crop after wheat, rice and maize globally (Campos and Oscar 2020). Cultivation occurs on an estimated 19 million hectares with a total yearly production of 378 million tons (Devaux et al. 2020). Bio-fortified potato varieties have been developed to supplement micronutrients such as Fe, Zn and vitamin C, particularly for subsistence purposes in developing countries (Burgos et al. 2020). Potatoes have gained prominence in addressing food and nutrition insecurity, especially in the global south (Raymundo et al. 2018). Varietal development and release now cater for the needs of the farmers to combat climate change and to suit many geographic locations (Gatto et al. 2018). New agricultural technologies have transformed lives of small-scale farmers in developing countries where the majority of the population depends on agriculture for their livelihood (Rola-Rubzen et al. 2020). Simultaneous climate change and diversified agricultural production practices have increasingly generated heterogeneous cultivation conditions (Boubennec 2019) challenging the technologies. In order to combat this, diverse agricultural innovations and delivery have been the mainstay of the country’s agricultural production systems. Varietal innovations are one of the major components of agricultural adaptation to global changes (Boubennec 2019). While varietal innovations and delivery have been successful in increasing productivity and alleviate poverty (Kapalasa 2019; Mendola 2007), these can be undermined by low technology adoption and acceptance by the farmers (Adesina and Baidu-Forson 1995). Despite enormous benefits, not every technology developed by researchers is adopted by the farmers (Adesina and Baidu-Forson 1995; Just and Zilberman 1988). Guerin and Guerin (1994) revealed that the problem of non-adoption is multifactorial and farmers tend to select packages of practices that are consistent with their local needs and priorities, socio-economic status and attitude toward new practices. Moreover, adoption also depends upon the nature and characteristics of the newly developed technology itself (Mgumia et al. 2015). Roder (2009) and Upadhyay et al. (2020) reported that the adoptability of a new variety is not merely a linear process but also depends on vagaries of other factors such as colour, shape, consumer demand, marketability and market value than the aspect of yield alone. Hence, identification of farmer’s priorities and participatory decision-making may be more relevant in achieving maximum technology diffusion (Kolech et al. 2015; Thompson and Scoones 2009). Furthermore, Jha et al. (2020) revealed that underlying factors such as farmers’ perceived behaviour and attitudes differ between technologies and that farmers are constantly challenged by their own local surroundings and needs. A gender gap in technology adoption for agricultural technologies has been a pertinent issue in many farming communities of the world (Theis et al. 2018), increasing the already recognized gendered productivity gap in agriculture. Women’s agricultural productivity is largely constrained by their limited access to agricultural technology (Peterman et al. 2010). We consider it essential to understand the role of women and their engagement in agricultural technology adoption for many reasons. These include their constant association with household farming and, often, as a primary care-taker of the family (Spangler and Christie 2020). Globally, 43% of women are actively involved in agriculture sector (Doss 2011), in various agricultural operations ranging from land preparation to seed sowing and farm operations to crop harvest (Rasheed et al. 2020). Agriculture technologies that are inclusive of gender perspectives and responsive to the concerns of women were found to result in rapid adoption of high-benefit new technologies such as improved varieties achieving better livelihood outcomes (Rola‐Rubzen et al. 2020). Moreover, agriculture technology that is used in a way that considers women participation (in the right context) results in a significant increase in productivity, production and farm economies (Tambo and Mockshell 2018). Because women are more concerned about immediate family welfare and benefit (Christinck et al. 2017), researchers need to consider the gender-sensitivities and subtleties involved. Similar gender-sensitive approaches have resulted in better adoption of varieties, for examples of potatoes in Tanzania (Mudege et al. 2020) and maize in Ethiopia (Gebre et al. 2019). Around 62% of Bhutanese people live in rural areas and depend on agriculture for their livelihood (NSB 2017). Of these, 56% and 44% practice crop-based and livestock-based farming, respectively (RSD 2019b). Potatoes have been an important component of crop-based farming and have resulted in an indelible impact on the lives of Bhutanese households since their introduction in the 1770s (Roder et al. 2008). Of the total 76,688 ha arable land in Bhutan, 4187 ha are under potato cultivation (RSD 2019a, b, 2020b), engaging 21% of the country’s farming households who directly depend on agriculture for their livelihood (DOA 2017; NSB 2017). Furthermore, potatoes are an emerging (export) market-oriented crop for Bhutan (Roder et al. 2007) generating over ngultrums (Nu.) 709 million (1US$ ≈ Nu.72) in revenue surpassing the combined revenue earned by other horticulture commodities in 2019 (RSD 2020a). In light of the crop’s increasing relevance in supporting livelihoods and as an export revenue-generator, the Department of Agriculture in Bhutan has released several potato varieties. Prior to distribution, new varieties were field-tested and distributed among potato producers in different regions of the country to test adaptation to specific climatic conditions (Rai et al. 2021). Unfortunately, two potato varieties (Khangma Kaap and Kufri Jyoti), with moderate productivity, have been de-notified due to a poor receptiveness by the farmers recently. This probably indicates that varietal acceptability and adoption differ across Bhutan. There are various reasons why lower adoption might occur in Bhutan. For example, movement is difficult through the country’s rugged topography, settlement is highly scattered, there is a relatively poor network of motorable roads, and technology adoption could be challenged as farmers lack awareness and are more hesitant to risk growing new varieties. Furthermore, while Bhutan is often considered both a matriarchal and patriarchal society, the role of gender in farm decisions and operations is not well understood. In addition, the food security was reported to be significantly lower among the female-headed households as compared to the male-headed households in a nationally representative study in Bhutan (Aryal et al. 2019). Therefore, we hypothesized that the factors responsible for the selection of potato varieties to be adopted and grown also differed and included a gendered role in farm decisions and operations. Accordingly, the objectives of this paper were (1) to determine the relative importance of the factors influencing farmers’ selection of potato varieties for adoption and (2) to determine the role of gender in farm decisions and operations. Materials and Methods Research Sites Seven major potato growing districts in Bhutan were selected for the study (Fig. 1). The research comprised two parts. The first part involved the establishment of demonstration plots with new potato varieties from 2017 to 2019 in five districts (Bumthang, Chukha, Gasa, Haa and Wangdue). These plots were used to assess the gender preference for new potato varieties. The second part involved a semi-structured questionnaire-based field survey of six districts (Bumthang, Chukha, Gasa, Mongar, Tashigang and Wangdue) (Fig. 1). Due to insufficient seeds of new potato varieties, we could not demonstrate in Mongar and Tashigang; however, we included them for the survey as they are also the main potato growing districts. Haa was left out for the survey because of COVID-19 restrictions at the time of data collection. This questionnaire assessed factors that influence farmers in selection of a potato variety for adoption. These six districts study sites were located at an elevation ranging from 1500 to 2600 m above sea level and characterized by warm temperate climate with mean daily temperature ranging from 2.5 to 22.8 °C and a mean annual rainfall of 1649.9 mm (NCHM 2018; RSD 2019a).Fig. 1 Study sites showing five districts of potato varietal demonstrations and six districts of field survey Assessment of Gender Preferences through Field Demonstrations of New Potato Varieties Demonstration plots consisting of three potato varieties, Nasephey Kewa Kaap (NKK), Yusi Maap and Desiree (the standard check/control) (Table 1), were established in the five districts (Bumthang, Chukha, Gasa, Haa and Wangdue) as part of the technology dissemination and production assessment programme. Plots of each of the three varieties were established adjacent to each other and managed by farmers (Rai et al. 2021). The location of these sites was sequentially changed from 2017 to 2019 within the district in order to showcase varietal performance to different communities. The yield of each variety was recorded at harvest at each site in the district, and an average yield per variety per district was calculated.Table 1 Demonstration plots consisting of three potato varieties, Nasephey Kewa Kaap (NKK), Yusi Maap and Desiree Potato variety Accession number Release year Tuber colour Days to maturity Resistance to late-blight Yusi Maap CIP392797.22 2017 Red 130–140 Moderate NKK CIP393077.159 2014 White 160–180 High Desiree CIP800048 1988 Red 130–140 Susceptible NKK Nasphey Kewa Kaap Farmers’ choices were assessed using Participatory Variety Selection approach consistently across the five districts over 3 years (Bajgai et al. 2018; Haan et al. 2019). Harvested potato tubers of the three varieties were displayed and farmers casted votes for their preferences. Farmers’ choices were captured following a gender-responsive technique, where men casted their preference votes using six maize grains while women with six bean grains. Each farmer was asked to cast three votes (three grains) for the most preferred variety, two for the moderate and one for the least preferred one (Haan et al. 2019; Rai et al. 2021). The preference votes received by each variety was segregated by gender and recorded in all five districts over 2017 to 2019. Field Survey A semi-structured questionnaire-based field survey was conducted in the six districts of Bumthang, Chukha, Gasa, Mongar, Tashigang and Wangdue (Fig. 1) to assess the relative importance of factors that influenced farmers’ selection of a potato variety. The survey was undertaken by a team of researchers including the local agriculture extension agents from October to December 2020. Prior to the implementation of the questionnaire survey, a sampling frame of the potato growing households in each district was constructed. Purposive sampling was employed as this approach allowed a random selection of households without bias (Baarda and Hidajattoellah 2014). The surveyor staff were briefed and trained to ensure uniformity in administration of the survey. In each district, 40 randomly selected potato farmers were interviewed, which exceeded the required 5% sample size recommended for representative research (Bartlett 2001), resulting in 240 samples across the six districts. A point score analysis was used as a simple and flexible way of collecting data of farmers’ perceptions (Beckford 2002). Based on an extensive review of literature, the experiences of the Participatory Varietal Selection processes in the districts and a pre-survey, factors such as ‘good taste’, ‘high market value’, ‘large tubers’, ‘marketability’, ‘micronutrient content’, ‘high productivity’, ‘red-skinned’, ‘late-blight resistant’ and ‘short duration’ were listed. These nine factors will be referred to as quality traits throughout this paper. The survey responses for the quality traits were coded on a Likert scale (strongly disagree = 1, disagree = 2, neither agree nor disagree = 3, agree = 4, strongly agree = 5) to quantify the qualitative responses received for statistical analysis (Joshi et al. 2015; Sullivan and Artino 2013). The same approach was used to gather data on female farmers’ involvement in farm decisions and operations as compared to their male counterparts at the household level. Furthermore, in order to synthesize the related findings from the demonstration plots and the survey, we compared the gender preferences for three varieties with that of gender roles in farm decision-making and operations. Household socio-demographic indicators of literacy level, age range, family size and land holdings were also captured. The minimum age of a respondent was set at 20 years to ensure that the responses were more reliable. We also assessed the relationship between the gender influence in the household, farm and location characteristics with respect to quality traits. Statistical Analyses Since the data generated in this study were non-parametric in nature (besides not fulfilling the assumptions of ANOVA), Spearman’s correlation and the Kruskal–Wallis and Mann–Whitney U tests were used for statistical data analyses using the IBM SPSS Statistics (Version 22) predictive analytics software. These methodologies are more appropriate and commonly used to analyze non-parametric or ordinal data by scholars and academia (Delmo and Refugio 2018; McKight and Najab 2010). While different years were considered as temporal replications, the pooled data of potato yields and the preference votes (by gender) over 3 years in the five districts were analysed using Spearman’s correlation to establish the relationship between productivity and gender. The data collected on the quality traits were assessed using a boxplot and then subjected to the Kruskal–Wallis test by ranks (equivalent to one-way ANOVA for parametric data) to infer the differences among the quality traits and further to decipher the influence of location (districts), household and farm characteristics on the quality traits. We categorized households into four categories: 1–2 members (20.42% of the surveyed households), 2–4 members (27.92%), 5–6 members (27.92%) and ≥ 7 members (23.75%) for statistical analysis. Similarly, farm characteristics (farm sizes) were also categorized into four categories; 0–0.4 ha (43.33% of the households), 0.4–0.82 ha (23.33%), 0.83–1.22 ha (12.50%) and > 1.22 ha (20.83%). Accordingly, a post hoc analysis was conducted to segregate the significantly different mean ranks using the Dunn test in SPSS. Data on whether or not female farmers were more involved in farm decisions and operations than their male counterparts was analyzed using the Mann–Whitney U test (equivalent to unpaired t-test) which tests two independent samples. The plots were generated using the MS Excel and R statistical software, version 3.1. Among the R packages, we used ‘xlsx’, ‘ggplot2’, ‘dplyr’ and ‘tidyverse’ for manipulation and visualization of the data (R Core Team 2018). Result Demographic Profile of Surveyed Respondents There were a total of 240 farmers comprising of 65.83% female and 34.17% male farmers who took part in the survey across the six districts. A majority of farmers (75.00%) were aged between 31 and 60 years; the remainder were either younger than 31 (12.08%) or older than 60 years (12.92%) of age. The average family size was 6.48 members per household, and the average land holding was 1.08 ha per household. A majority of the respondents were illiterate (59.17%), and only 0.42% had diploma or higher qualifications. The remainder fell under the following highest education categories: non formal education — 18.33%, finished primary school — 15.83%, finished high school — 5% and obtained certificate and vocational level education — 1.25%. Factors Influencing the Selection of New Potato Varieties The nine quality traits influencing the adoption of potato varieties were good taste, high market value, large tubers, marketability, micronutrient content, high productivity, red-skinned, resistance to late-blight and short duration. The chi-square (χ2) values for the districts and the pooled data across the districts of these quality traits were ≥ 71.1694 (Table 2) indicating high levels of significant difference. The quality traits for selection of the three potato varieties were significantly different (P < 0.05), both at the district level (Table 3) and on the pooled data of the six districts (Fig. 2).Table 2 Summary of the Kruskal–Wallis test by ranks of the factors influencing farmers on selection of potato varieties District/overall n Df χ2 value /test statistic P-value 1 Bumthang 40 8 81.1415  < 0.001 2 Chukha 40 8 117.5284  < 0.001 3 Gasa 40 8 92.9841  < 0.001 4 Mongar 40 8 96.0673  < 0.001 5 Tashigang 40 8 71.1694  < 0.001 6 Wangdue 40 8 82.4475  < 0.001 7 Overall (pooled) 240 8 376.542  < 0.001 Table 3 Mean ranks by the Kruskal–Wallis test of factors influencing selection of potato varieties in six districts Factors Bumthang Chukha Gasa Mongar Tashigang Wangdue 1 Good taste 183.64ab   80.49e   95.90e   87.65e 110.12d 126.11d 2 High market value 214.82ab 220.96ab 224.45ab 207.90abc 188.68bc 255.35a 3 Large tubers 195.64ab 177.69bc 202.62abc 185.05bcd 193.25bc 155.98bcd 4 Marketability 163.15b 206.75bc 189.12bc 200.72abc 154.68c 212.28ab 5 Micronutrient content 154.45b 123.39d 147.65 cd 125.94d 154.62c 144.70 cd 6 High productivity 236.50a 275.25a 264.95a 267.48a 267.00a 209.80ab 7 Red-skinned 180.82ab 221.97ab 170.75c 218.29ab 228.72ab 225.05a 8 Resistance to late-blight 214.82ab 172.38bcd 202.18abc 159.94 cd 160.85c 189.40abc 9 Short duration   80.65c 145.62 cd 126.88de 171.54bcd 166.57c 107.24d Quality traits with same letters are not significant at P < 0.05 within a district (column) Fig. 2 Overall mean ranks of determining quality traits in selecting potato varieties in the six study districts. Quality traits with same letters are not significant at P < 0.05 High productivity generally scored the highest mean rank ranging from 209.80 to 275.25, followed by high market value (188.68–255.35) and marketability (154.68–212.28) across the six districts (Table 3). Short duration scored the lowest rank ranging from 80.65 to 171.54, followed by good taste (80.49–183.64) and micronutrient content (123.39–154.62). Other quality traits such as red-skinned, resistance to late-blight and large tubers were given intermediate quality ranks (Table 3). High productivity was rated 5 (strongly agree) by 63% of the respondents while 0% rated 1 (strongly disagree) across the districts. Similarly, high market value and marketability were rated 5 by 44 and 31% of the respondents, respectively, and 0% rated 1 for both the factors (Fig. 3). However, short duration and good taste were rated 5 by only 14 and 12% of the respondents, respectively, while 3 and 8% rated these quality traits as 1, respectively, across the six districts (Fig. 3).Fig. 3 Overall farmer’s responses (ranking) expressed in terms of % in the surveyed six districts Examining the quality traits within and across the districts revealed varied and inconsistent results (Table 3). For instance, a more detailed evaluation of the quality traits for Bumthang revealed that the ranking between good taste, high market value, large tubers, red-skinned and resistance to late-blight were not significantly different, but were significant in other districts (Table 3). In Chukha, the ranking between high market value, red-skinned, large tubers and marketability were not significantly different, but the ranking between other quality traits was significantly different (Table 3). Conversely, in Gasa, there was a significant difference between the ranking among all quality traits except for large tuber size, resistance to late-blight, good taste and short duration. In Mongar, large tubers, short duration, high market value and marketability were not significant, and in Tashigang, all the quality traits except for good taste, high productivity and red-skinned were not significantly different to each other. Lastly, only the quality traits of large tubers and resistance to late-blight were significantly different to some of the quality traits for Wangdue. Since there was inconsistency across the districts on the level of significance between quality traits, we assessed the pooled data from across the six districts to get a comprehensive understanding of these quality traits (Fig. 2). The most important quality trait was high productivity with the mean rank of 1510, followed by high market value (1301) and red-skinned (1236). High productivity was rated 5 (strongly agree) by 63% of the respondents while 0% rated it 1 (strongly disagree) across the districts. Similarly, high market value and marketability were rated 5 by 44 and 31% of the respondents, respectively and 0% rated 1 for both the factors (Fig. 3). However, short duration and good taste were rated 5 by 14 and 12% of the respondents, respectively, while 3 and 8% of them rated 1, respectively, across the six districts (Fig. 3). The mean rank of high productivity was significantly (P < 0.05) higher than that of the other eight quality traits (Fig. 2). The least important quality traits were good taste with the mean rank of 696, followed by short duration (803) then micronutrient content (855). Furthermore, the mean rank of short duration was significantly (P < 0.05) lower than that of the other eight traits (Fig. 2). The three intermediate quality traits of large tubers, marketability and resistance to late-blight were not statistically different from each other. Role of Household and Farm Characteristics in the Quality Traits The relationship between the four household categories (2–4, 5–6 and ≥ 7 members) and quality traits were not significantly different to each other (χ2 = 7.1728, P = 0.067) and therefore the quality traits were not further evaluated. In contrast, the relationship between the four land categories (0–0.4, 0.4–0.82, 0.83–1.22 and > 1.22 ha) were significantly (χ2 = 62.0955, P < 0.001) different indicating the influence of farm sizes on quality traits. Generally, the post hoc analysis showed more numbers of significant pairs at lower size categories and fewer at higher land size categories (five in 0–0.4, four in 0.42–0.82, three in > 1.22 and two in 0.83–1.22 ha categories) (Table 4). Those farmers classed in the 0–0.4-ha land category had highest mean rank values for quality traits followed by those farmers classed in the 0.42–0.82 ha, and the lowest quality rank values were observed in those farmers classed in the 0.83–1.22 ha. Within the 0–0.4-ha category, the quality traits of high productivity and high market value were generally significantly different to the other seven quality traits; however, they did not differ with each other (Table 4). Furthermore, within the same category, the quality trait of good taste was significantly different to high market value, large tubers, marketability, red-skinned and resistant to late-blight while it did not differ with short duration. Whereas, for the 0.42–0.82-ha category, good taste and micronutrient content were significantly different to the rest of the quality traits, but they did not differ with each other. However, high market value, large tubers, marketability, red-skinned and resistant to late-blight differed with other four traits while they did not differ among each other. Within the 0.83–1.22-ha category, good taste, large tubers, marketability, micro nutrient-content, resistant to late-blight and short duration were significantly different with the other three traits while not differing among themselves. Lastly, good taste, high productivity and short duration significantly differed with other six quality traits in the > 1.22-ha category (Table 4).Table 4 Mean ranks by Kruskal–Wallis test of quality traits based on farm characteristic (farm sizes) of households Quality traits Farm sizes (land holdings) in ha 0–0.4 (n = 104) 0.42–0.82 (n = 56) 0.83–1.22 (n = 30)  > 1.22 (n = 50) Good taste 273.42e 145.39d   93.92b 182.44c High market value 567.96ab 314.86ab 168.70a 254.71ab Large tubers 505.33b 253.61bc 136.83ab 208.49bc Marketability 485.93b 252.57bc 135.92ab 249.39ab Micronutrient content 382.28 cd 190.29 cd 100.42b 180.68bc High productivity 672.67a 352.29a 185.50a 303.51a Red-skinned 521.09b 296.21ab 168.70a 255.35ab Resistance to late-blight 461.55bc 250.30bc 134.13ab 252.37ab Short duration 346.27de 216.98c   95.38b 142.56c Potato Productivity and Gender Preferences Under Field Demonstrations in Five Districts The mean productivity of the new varieties, NKK and Yusi Maap were 24.09 and 26.18 t/ha, respectively, with the mean difference of 2.09 t/ha across the districts (Fig. 4). The mean productivity of Desiree across the districts was 18.04 t/ha and was consistently lower than that of NKK and Yusi Maap. The mean productivity of Yusi Maap was 31.02 and 7.9% greater than Desiree and NKK, respectively (Fig. 4). Desiree exhibited both its highest yield (21.6 t/ha) in Bumthang and the lowest yield (14.77 t/ha) in Haa despite these areas being of similar altitude and agroecology zone. Yusi Maap yielded highest (29.3 t/ha) at lower elevation of Chukha and the least (21.4 t/ha) at higher elevation of Haa. Generally, the yield performance of all the varieties in Haa district showed comparatively lower yield than in other locations (districts) (Fig. 4).Fig. 4 Mean productivity of three potato varieties over 3 years, error bars are standard deviation of means Similarly, the overall preference votes casted by farmers for Yusi Maap were 43.9 and 23.0% greater than for Desiree and NKK, respectively. It was intriguing to note that, although the mean productivity difference between Yusi Maap and NKK was as minimal at 7.9%, the difference in preferential votes was as high as 23.0%. When the mean productivity data and vote data were correlated by gender, there was a positive and significant relationship (R = 0.395, P < 0.01) between the mean productivity (yields) and votes for female farmers (Fig. 5A), but this was not significant (R = 0.193, P = 0.202) for male farmers (Fig. 5B).Fig. 5 Relationship between potato productivity and female farmers’ votes (a) and those of male farmers’ (b) for three potato varieties in the five study districts from 2017 to 2019. Shaded region shows the standard deviation of the linear correlation Role of Gender in Farm Decisions and Operations The result of the Mann–Whitney U test for two independent samples showed that the female farmers were significantly (test statistic = 8218.50, P < 0.001) more involved in farm decision-making process than their male counterparts, illustrated with a different median in the boxplot (Fig. 6A). However, the female farmers were not significantly (test statistic = 7210, P = 0.1345) more involved in farm operations than their male counterparts, as indicated by the same median value (Fig. 6B). Hence, female farmers were significantly more involved in farm decision-making, but were equally involved in physical farm operations. In addition, there was significant negative relationship (R =  − 0.1765, P < 0.05) between farm household size and women’s involvement in farm decision-making, whereas the relationship on farm operations was not significant (R =  − 0.1243, P = 0.1197). Furthermore, positive and significant relationship (R = 0.1558, P < 0.05) was observed between land holding size and women’s involvement in farm decision-making, whereas the relationship on farm operations was negative and significant (R =  − 0.1243, P < 0.01).Fig. 6 Boxplots displaying the data to indicate that the female farmers were more involved in decision-making (A) and equally involved in farm operations (B) as their male counterparts from the six districts. Y-axis has point scale or a Likert scale; 1 strongly disagree, 2 disagree, 3 neither agree nor disagree, 4 agree, 5 strongly agree Discussion Factors Influencing the Selection of New Potato Varieties Quality traits for the choice of a potato variety in order of their relative preference were: high productivity (15.5% by weight of mean rank), high market value (13.4%), red-skinned (12.7%), marketability (11.6%), large tubers (11.3%), late-blight resistant (11.3%), micronutrient content (8.8%), short-duration (8.3%) and good taste (7.2%). These quality traits varied across the six study districts (Table 3), a result that is consistent with the previous studies by Roder (2009) and Upadhyay et al. (2020). This variation could be a reflection of district-specific contexts as farmers are governed by their own requirements and priorities from region to region in terms of technology adoption or diffusion (Ghimire et al. 2015). In general, quality traits such as high productivity, high market value and marketability were ranked high in all six districts, which indicated the importance placed by farmers on these qualities which translated into the generation of food or cash income for their livelihoods. Across the districts, the most influential quality trait was high productivity as the combination of ratings 5 (strongly agree) and 4 (agree) which constituted 98% of the respondents (Fig. 3). The findings were consistent to a similar study in Indian state of Gujarat, which revealed that 98.5% of the farmers rated productivity or the yield as the most determining factor for adoption of potato varieties over heat-tolerance and late-blight resistance quality traits (Rana et al. 2010). Similarly, high productivity was also reported as the most preferred and the deciding factor over other quality traits such as shape, size, maturity, price, colour and disease resistance by the farmers in their adoption of potato varieties in such diverse places as Nepal, Malawi and Bangladesh (Gairhe et al. 2017; Kapalasa 2019; Khalil et al. 2013). Additionally, productivity was the most important market preference expressed by farmers in the Andes for the adoption of potato varieties (Ortiz et al. 2020). While productivity was the most preferred trait in Bhutan, other quality traits such as high market value, red-skinned and marketability were also considered important, although degree of preference for each of these traits varied among the districts. High market value and marketability were rated 5 by 44 and 31% of the respondents, respectively and 0% rated 1 (strongly disagree) for both the factors (Fig. 3). The trait high market value is intricately linked to colour of the tubers and marketability because the red-skinned potatoes fetch higher prices than the white-skinned potatoes in Bhutan (Bajgai et al. 2018; Roder et al. 2007). This could be a credible reason why the red-skinned Desiree variety is so popular with most Bhutanese farmers despite consistently yielding low in the field (Rai et al. 2021). A similar study in Nepal reported that farmers across all regions were more receptive to red-skinned varieties than white-skinned due to the higher market demand, eventually fetching higher prices (Upadhyay et al. 2020). Most of the Bhutanese potatoes are exported to India and the market value or price is usually determined by Indian-centric factors. This means that slight fluctuations and aberrations in potato production in India have severe and direct implications in the price of Bhutanese potatoes (Roder et al. 2007). In contrast, socio-economic factors that result in uncertainties in potato prices demotivate growers, even in the presence of desired varieties, in Pakistan (Hussain and Sadozai 2006). Tuber colour (red) and size (large) enhances salability, whereas other quality factors such as late-blight resistance reduce crop loss, a possible reason for ranking this quality trait to be of moderate preference. On the other hand, short duration and good taste were rated 5 by only 14 and 12% of respondents, while 3 and 8% of them rated 1, respectively, across the six districts (Fig. 3). These traits were least preferred by the farmers and rated low because they did not contribute directly to their livelihood. This is due to the fact that potato farming in Bhutan is more commercially oriented than subsistence alone, and the quality traits are market-driven. Hence, quality traits of micronutrient content and good taste were least preferred as they are more of consumption-related trait than other more obvious market attributes. It is important to balance both commercial (marketability/sales)- and subsistence (nutritional)-level attributes during the process of new variety development. Farm sizes had a significant role in determining the quality traits of a potato variety across the six districts. Similarly, Bajracharya and Sapkota (2017) found that the farm and field characteristics such as farm sizes, locations (e.g., low lands) and draft animal-power were key factors influencing the likelihood of adopting new rice variety in Nepal. However, the number of family members residing in the households showed an insignificant relationship with that of quality traits, possibly due to availability of off-farm income sources, especially for male farmers of the household. Role of Gender in Farm Decisions and Operations Once the factors influencing selection of potato varieties were established, it was of interest to delve into the role of gender in the Bhutanese context because gender-sensitive approaches have resulted in better adoption of crop varieties (Gebre et al. 2019; Mudege et al. 2020). A significant correlation (R = 0.395) between potato productivity and preference by women (in a pooled data from five districts over three years) reflected the close association of women with household farming. This is in agreement with the previous study by Spangler and Christie (2020), where the authors found that women increasingly took control of obtaining the knowledge of integrated pest management in vegetable production leading to increased yield. Similarly, women potato farmers in Nepal were reported to be more engaged in farm decision-making since it resulted in better accessibility to food and livelihood (FAO 2019). The significant association of preference votes and potato productivity could be further supported by the perception data. The result from the perception data showed that the female farmers were significantly (P < 0.001) more involved in farm decision-making than the male farmers, explicating the women’s affinity and concerns for household food security in the Bhutanese context. The finding illustrates that the females have a higher participation rate in a number of decision-making domains in comparison to the male farmers in Bhutan (Sariyev et al. 2020). This result also reflects women’s concerns for household food and income (Anderson et al. 2017; Mudege et al. 2020), where Bhutanese women were relatively more forthright than men in decision-making processes related to household’s food security and family’s welfare along with other farm concerns (Sariyev et al. 2020). The higher decision-making role of women in Bhutan could also be associated with the matrilineal resource endowment tradition, in which daughters inherit parental resources, and hence the family responsibilities (Aphichoke 2013). This tradition empowers women with at least equal or greater access to decision-making processes unlike in many other neighbouring countries in the South-Asian region. However, the negative correlation observed between farm household size and women’s involvement in farm decision-making could be due to the fact that responsibilities of women increase as household size decreases, possibly because in larger households, decision-making is shared with other household members. Similar gender differences in terms of household food security have been reported in a recent study (Aryal et al. 2019), and the differences reported were due to both observable and unobservable features of the households in Bhutan. In contrast, the female farmers were found to be equally involved in the physical farm operations as the male ones. According to Moktan et al. (2015), the division of work between male and female depends upon the arduous nature of the given tasks and the types of crops cultivated. Furthermore, female farmers (61.7%) were found to outnumber male ones, indicating the feminization trend of Bhutanese agriculture (NSB 2019; RSD 2019a). The positive but weak correlation (R = 0.193) between the preference votes and potato productivity for men could indicate their major involvement in off-farm activities. Similarly, a significant relationship between land holding size and women’s involvement in farm decision-making was observed which is in concurrence with a past study conducted in Bhutan (Sariyev et al. 2020). Conclusion Selection of a potato variety by farmers in Bhutan is predominantly influenced by quality traits such as high productivity, high market value and red-skinned. This suggests that the process of generating a new potato variety necessitates understanding farmers’ needs and production practices as they relate to variety selection and adoption. Moreover, these quality traits, besides being determinants for selection and adoption by farmers, are also more market-driven than consumption-related as indicated by the lower ratings for good taste and micronutrient content. Furthermore, this study also suggests that potato farming has considerable potential for large-scale commercialization in Bhutan when the farmers’ preferential choice for quality traits such as high productivity, high market value and red-skinned are considered. Farm size had a significant role in determining the quality traits while family size did not. Women’s role in farm decision-making processes can be crucial for adoption of new varietal technology in potato production in Bhutan. The findings from this study provide insight and guidance for research and policy interventions for potato industry in Bhutan and other similar agroecologies. Acknowledgements The authors are grateful and extend their appreciation to the logistical support provided by the District Agriculture Officers (DAOs) and Block agriculture staff in Bumthang, Chukha, Gasa, Haa, Mongar, Tashigang and Wangdue. We are also thankful to all participating farmers for their participation and input. We are indebted to NCOA, Yusipang (former ARDC, Yusipang) and above all to the Department of Agriculture for support and conducive environment. We are highly indebted to Dr. Stephen Johnson of the NSW Department of Primary Industries, Australia for editing and improving the paper. Lastly, we would also like to express our gratitude to colleagues from the National Potato Program for their support in data collection and field work. Funding The following financed the research: (1) Food Security and Agriculture Productivity Project (FSAPP) funded by Global Agriculture and Food Security Program (GAFSP) and managed by World Bank, and 2) ITPGRFA/FAO/EU: Biodiverse and Nutritious Potato Improvement across Peru, Nepal and Bhutan through International Potato Centre (CIP), Lima. Data Availability All the analyzed data for this study will be available and transparent. Declarations Competing Interests The authors declare no competing interests. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Pradeep Rai and Yadunath Bajgai contributed equally to this research work. ==== Refs References Adesina AA, Baidu-Forson J (1995) Farmers’ perceptions and adoption of new agricultural technology: evidence from analysis in Burkina Faso and Guinea, West Africa. Agricult Econ 13(1), 1-9. 10.1016/0169-5150(95)01142-8 Anderson CL Reynolds TW Gugerty MK Husband and wife perspectives on farm household decision-making authority and evidence on intra-household accord in rural Tanzania World Dev 2017 90 169 183 10.1016/j.worlddev.2016.09.005 28163352 Aphichoke K (2013) Bhutan gender policy note. Retrieved from http://documents.worldbank.org/curated/en/960591468017989867/Bhutan-gender-policy-note. Accessed 21 Jan 2021 Aryal JP, Mottaleb KA, Rahut Dil B (2019) Untangling gender differentiated food security gaps in Bhutan: an application of exogenous switching treatment regression. 23(2), 782–802. 10.1111/rode.12566 Baarda B Hidajattoellah D Research. This is it! : guidelines how to design, perform and evaluate quantitative and qualitative research 2014 2 Groningen Noordhoff Uitgevers bv Bajgai Y, Dochen T, Wangchuk P, Kadian SK, Felde TZ, Lefebvre M, . . . Wangdi N (2018) Participatory varietal selection of potato and agronomic performance with farmers’ feedback on new varieties. Bhutanese J Agricult 1(1), 1-12 Bajracharya M Sapkota M Profitability and productivity of potato (Solanum tuberosum) in Baglung district Nepal Agricult Food Secur 2017 6 1 47 10.1186/s40066-017-0125-5 Boubennec A Varietal innovation for high quality sweet cherry production Italus Hortus 2019 26 21 24 10.26353/j.itahort/2019.1.2124 Bartlett JE, Kotrlik JW, Higgins CC (2001) Organizational research: Determining appropriate sample size in survey research. Inf Technol Learn Perform J 19: 43–50 Beckford CL (2002) Decision–making and innovation among small–scale yam farmers in central Jamaica: a dynamic, pragmatic and adaptive process. 10.1111/1475-4959.00052 Burgos G, Felde T, Andre C, Kubow S (2020) The potato and its contribution to the human diet and health. In (pp. 37–74) Campos H, Oscar O (eds) (2020) The potato crop, its agricultural, nutritional and social contribution to humankind. Lima, Peru: International Potato Center. 10.1007/978-3-030-28683-5 Christinck A, Weltzien E, Rattunde F, Ashby J (2017) Gender differentiation of farmer preferences for varietal traits in crop improvement: Evidence and issues. Working Paper No. 2. CGIAR Gender and Agriculture Research Network; CGIAR System Management Office and International Center for Tropical Agriculture (CIAT). Cali, pp 38  Delmo J, Refugio C (2018) Empirical research on Mann-Whitney U-test. Statistics Class Project. 10.13140/RG.2.2.11899.36649 Devaux A, Goffart JPP, Athanasios, Kromann P, Gatto M, Okello J, Suarez V, Hareau G (2020) Global food security, contributions from sustainable potato agri-food systems. In the potato crop. Its agricultural, nutritional and social contribution to human kind. Lima, Peru: International Potato Center, pp 3–35. 10.1007/978-3-030-28683-5_1 DOA (2017) Agriculture statistics. RNR statistics division, ministry of agriculture and forests, royal government of Bhutan, Thimphu Doss C (2011) The role of women in agriculture. Retrieved from http://www.fao.org/economic/esa. Accessed 18 Jan 2021 FAO (2019) Country gender assessment of agriculture and the rural sector in Nepal. Retrieved from https://www.fao.org/publications. Accessed 21 Jan 2021 Gairhe S Gauchan D Timsina K Adoption of improved potato varieties in Nepal J Nepal Agricult Res Council 2017 3 38 44 10.3126/jnarc.v3i1.17274 Gatto M, Hareau G, Pradel W, Suárez V, Qin J (2018) Release and adoption of improved potato varieties in Southeast and South Asia. 10.4160/9789290605010 Gebre GG Isoda H Rahut DB Amekawa Y Nomura H Gender differences in the adoption of agricultural technology: the case of improved maize varieties in southern Ethiopia Women's Studies International Forum 2019 76 102264 10.1016/j.wsif.2019.102264 Ghimire R Wen-chi H Shrestha RB Factors affecting adoption of improved rice varieties among rural farm households in Central Nepal Rice Sci 2015 22 1 35 43 10.1016/j.rsci.2015.05.006 Guerin L Guerin T Constraints to the adoption of innovations in agricultural research and environmental management: a review Aust J Exp Agric 1994 34 4 549 571 10.1071/EA9940549 Haan S, Salas E, Fonseca C, Gastelo M, Amaya N, Bastos C, Bonierbale M (2019) Participatory varietal selection of potato using the mother & baby trial design: a gender-responsive trainer's guide produced by international potato center citation. 10.4160/9789290605386 Hussain A, Sadozai K (2006) Production and marketing constraints of potato in Shiger Valley of Gilgit-Baltistan 22 173-178 Jha S, Kaechele H, Lana M, Amjath-Babu TS, Sieber S (2020) Exploring farmers’ perceptions of agricultural technologies: a case study from Tanzania. Sustainability 12(3). 10.3390/su12030998 Joshi A Kale S Chandel S Pal D Likert scale: explored and explained British J Appl Sci Technol 2015 7 396 403 10.9734/BJAST/2015/14975 Just RE Zilberman D The effects of agricultural development policies on income distribution and technological change in agriculture J Dev Econ 1988 28 2 193 216 10.1016/0304-3878(88)90058-2 Kapalasa E Assessing factors influencing farmers adoption of improved potato varieties in Malawi Int J Econ Energy Environ 2019 4 1 10.11648/j.ijeee.20190401.11 Khalil I Haque M Hoque M Adoption of BARI recommended potato (Solanum tuberosum) varieties by the potato farmers of Bangladesh The Agriculturists 2013 11 2 79 86 10.3329/bjar.v39i1.20145 Kolech SA Halseth D Perry K De Jong W Tiruneh FM Wolfe D Identification of farmer priorities in potato production through participatory variety selection Am J Potato Res 2015 92 6 648 661 10.1007/s12230-015-9478-0 McKight PE, Najab J (2010) Kruskal-wallis test. The corsini encyclopedia of psychology 1:1–10. 10.1002/9780470479216.corpsy0491 Mendola M Agricultural technology adoption and poverty reduction: a propensity-score matching analysis for rural Bangladesh Food Policy 2007 32 3 372 393 10.1016/j.foodpol.2006.07.003 Mgumia AH Mattee AZ Kundi BAT Characteristics of agriculture technology and application of an agricultural innovation system in Tanzania Afr J Sci Technol Innov Dev 2015 7 2 73 83 10.1080/20421338.2015.1023651 Moktan M, Norbu L, Choden K, Forest T, Bhutan (2015) Can community forestry contribute to household income and sustainable forestry practices in rural area? A case study from Tshapey and Zariphensum in Bhutan. Forest Policy Econ 62. 10.1016/j.forpol.2015.08.011 Mudege NN, Escobar SS, Polar V (2020) Gender topics on potato research and development. In: Campos H, Ortiz O (eds) The potato crop: its agricultural, nutritional and social contribution to humankind. Springer International Publishing, Cham, pp 475–506 NCHM (2018) Climate data book of Bhutan. Weather and climate services division, national center for hydrology and meteorology, royal government of Bhutan, Thimphu NSB (2017) Population and Housing Census of Bhutan. Thimphu: Royal Government of Bhutan Retrieved from www.nsb.gov.bt NSB (2019) Labour force survey report of Bhutan. Retrieved from Thimphu, Bhutan: https://www.nsb.gov.bt. Accessed 17 Jul 2020 Ortiz O, Thiele G, Nelson R, Bentley J (2020) Participatory research (PR) at CIP with potato farming systems in the Andes: evolution and prospects. In The Potato Crop (pp. 451–473) Peterman A, Behrman J, Quisumbing A (2010) A review of empirical evidence on gender differences in nonland agricultural inputs, technology, and services in developing countries. 10.1007/978-94-017-8616-4_7 R Core Team (2018) A language and environment for statistical computing. , Austria. Vienna, Austria Rai P Bajgai Y Lhadon T Lobzang L Sangay S Productivity and preferences of new potato varieties and their relationships in five districts of Bhutan Bhutanese J Agricult 2021 4 1 11 27 10.55925/btagr.21.4102 Rana R, Sharma N, Kadian MS, bh G, Arya S, Campilan D, Thiele G (2010) Assessing potato farmers’ perceptions on abiotic stresses and implications for crop improvement research in heat-prone Gujarat, India: International Potato Center, P.O.Box 1558, Lima 12, Peru Rasheed A Mwalupaso G Abbas Q Tian X Waseem R Women participation: a productivity strategy in rice production Sustainability 2020 12 2870 10.3390/su12072870 Raymundo R, Asseng S, Robertson R, Petsakos A, Hoogenboom G, Quiroz R, . . . Wolf J (2018) Climate change impact on global potato production. Eur J Agronomy, 100, 87-98. 10.1016/j.eja.2017.11.008 Roder W Are mountain farmers slow to adopt new technologies? Mt Res Dev 2009 34 114 118 10.1659/0276-4741(2004)024[0114:AMFSTA]2.0.CO;2 Roder W, Nidup K, Chettri GB (2008) The potato in Bhutan: Bhutan potato development program, department of agriculture, ministry of agriculture and forests Roder W, Nidup K, Wangdi S (2007) Marketing Bhutanese potato - experiences, challenges and opportunities. Bhutan potato development program, department of agriculture, Semtokha, Thimphu. CIP/CFC/BPDP, Working Paper No 4 Rola-Rubzen MF Paris T Hawkins J Sapkota B Improving gender participation in agricultural technology adoption in Asia: from rhetoric to practical action Appl Econ Perspect Policy 2020 42 1 113 125 10.1002/aepp.13011 RSD (2019a) Bhutan RNR statistics, Ministry of Agriculture and Forests, Thimphu. Accessed 11 Apr 2020 RSD (2019b) RNR Census of Bhutan. Thimphu: Ministry of Agriculture and Forests, Thimphu RSD (2020a) Major crops auctioned by FCBL in 2019. Research and Statistics Division, Ministry of Agriculture and Forests Retrieved from www.moaf.gov.bt RSD (2020b) RNR Statistical Release (RNR-SR), Agriculture land use statistics for effective decision making. Thimphu Sariyev O Loos TK Zeller M Gurung T Women in household decision-making and implications for dietary quality in Bhutan Agricultural and Food Economics 2020 8 1 13 10.1186/s40100-020-00158-0 Spangler K Christie ME Renegotiating gender roles and cultivation practices in the Nepali mid-hills: unpacking the feminization of agriculture Agric Hum Values 2020 37 2 415 432 10.1007/s10460-019-09997-0 Sullivan G Artino A Analyzing and interpreting data from Likert-type scales J Grad Med Educ 2013 5 541 542 10.4300/JGME-5-4-18 24454995 Tambo JA Mockshell J Differential impacts of conservation agriculture technology options on household income in sub-Saharan Africa Ecol Econ 2018 151 95 105 10.1016/j.ecolecon.2018.05.005 Theis S, Lefore N, Meinzen-Dick R, Bryan E (2018) What happens after technology adoption? Gendered aspects of small-scale irrigation technologies in Ethiopia, Ghana, and Tanzania. Agricult Human Values, 35. 10.1007/s10460-018-9862-8 Thompson J Scoones I Addressing the dynamics of agri-food systems: an emerging agenda for social science research Environ Sci Policy 2009 12 386 397 10.1016/j.envsci.2009.03.001 Upadhyay N Ghimire Y Acharya Y Sharma B Adoption of improved potato varieties in Nepal Journal of Southeast European and Black Sea Studies 2020 3 139 145
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==== Front Curr Radiol Rep Curr Radiol Rep Current Radiology Reports 2167-4825 Springer US New York 407 10.1007/s40134-022-00407-8 Cardiovascular Imaging (Hamid Chalian, Section Editor) Machine Learning in Cardiovascular Imaging: A Scoping Review of Published Literature Rouzrokh Pouria 12 Khosravi Bardia 12 Vahdati Sanaz 12 Moassefi Mana 12 Faghani Shahriar 12 Mahmoudi Elham 12 Chalian Hamid 3 http://orcid.org/0000-0001-7926-6095 Erickson Bradley J. [email protected] 12 1 grid.66875.3a 0000 0004 0459 167X Artificial Intelligence Laboratory, Mayo Clinic, Rochester, MN 55905 USA 2 grid.66875.3a 0000 0004 0459 167X Radiology Informatics Laboratory, Department of Radiology, Mayo Clinic, 200 1st Street, SW, Rochester, MN USA 3 grid.34477.33 0000000122986657 Department of Radiology, Cardiothoracic Imaging, University of Washington, Seattle, WA USA 12 12 2022 112 17 11 2022 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Purpose of Review In this study, we planned and carried out a scoping review of the literature to learn how machine learning (ML) has been investigated in cardiovascular imaging (CVI). Recent Findings During our search, we found numerous studies that developed or utilized existing ML models for segmentation, classification, object detection, generation, and regression applications involving cardiovascular imaging data. We first quantitatively investigated the different aspects of study characteristics, data handling, model development, and performance evaluation in all studies that were included in our review. We then supplemented these findings with a qualitative synthesis to highlight the common themes in the studied literature and provided recommendations to pave the way for upcoming research. Summary ML is a subfield of artificial intelligence (AI) that enables computers to learn human-like decision-making from data. Due to its novel applications, ML is gaining more and more attention from researchers in the healthcare industry. Cardiovascular imaging is an active area of research in medical imaging with lots of room for incorporating new technologies, like ML. Supplementary Information The online version contains supplementary material available at 10.1007/s40134-022-00407-8. Keywords Scoping review Cardiovascular imaging Artificial intelligence Machine learning Deep learning Radiology Cardiology ==== Body pmcIntroduction The use of artificial intelligence (AI) in healthcare has exploded in recent years. Since 1995, the output of AI publications on healthcare has increased by an average of 17.02% per year, and the growth rate of research papers in this field has significantly accelerated to 45.15% from 2014 to 2019 [1]. AI is a general term for any technique that enables computers to mimic human-like behavior [2]. Machine learning (ML) is a subset of AI that can learn human-like decision-making from data. Deep learning (DL) is a subset of ML that incorporates artificial neural network algorithms. Conventional ML, on the other hand, refers to the subfield of ML that does not involve neural networks (Fig. 1). Tree-based models, support vector machines, and K-nearest neighbors are famous examples of conventional ML algorithms.Fig. 1 An arbitrary framework to describe artificial intelligence, machine learning, deep learning, and conventional machine learning Most ML algorithms can be thought of as parametric models that produce one or more quantities as their outputs while using data as their input variables [3]. During an iterative process known as model training, ML algorithms gradually encounter a carefully compiled set of data and discover the most optimal parameter values that can explain that dataset. ML algorithms can be distinguished from each other based on their mathematical expressions (a.k.a. architectures), input variables, and parameters. One can theoretically train many valid ML algorithms for the same task and on the same data, and this is what makes ML both an esthetic and scientific area. Aligned with the conventional routines, we hereafter use the word “model” to denote ML and DL algorithms in this report. The major distinction between DL and conventional ML is their respective computational complexity [4]. In contrast to conventional ML models, which have a limited potential for data-driven learning, DL models are more complicated and can have millions of parameters. This increased capacity lets DL models learn more as they are exposed to additional data. However, the intricacies of DL models necessitate training them with larger datasets and more sophisticated hardware technology, such as graphics processing units. The learning process of ML models is described as supervised when their training data are labeled. This strategy could be exemplified by a DL model that has been trained on chest X-ray (CXR) data from both normal and pneumonia patients and has similarly learned to label any CXR it encounters for the first time as normal or pneumonia indicating. While supervised learning is the most common strategy for training ML models, other strategies like unsupervised, semi-supervised, and self-supervised learning also exist and have diverse applications. Using only unlabeled training data, for instance, an unsupervised ML model can learn to cluster CXRs into arbitrary but still meaningful classes [5]. Another perspective for classifying ML models is based on their applications. Computer vision is a subset of ML that deals with imaging data. As illustrated in Fig. 2, computer vision models may be used for various tasks, the most common of which are as follows [6]:Classification an input image is labeled with one or more categorical labels, e.g., to distinguish input CXRs based on whether they are presented with cardiomegaly or normal hearts. Regression an input image is labeled with one or more quantitative labels, e.g., to predict the age of a patient by looking at input CXRs. Semantic segmentation the entire surface areas or volumes of some objects of interest are delineated in an input image, e.g., to segment the entire heart area in input CXRs. Object detection the locations of some objects of interest are approximated in an input image using key points or bounding boxes, e.g., to localize the heart in input CXRs. Generation synthetic but realistic-looking imaging data is generated, e.g., to inpaint covered parts of input CXRs as if those parts came from real radiographs. Fig. 2 An illustration of different machine learning tasks on an arbitrary chest X-ray (CXR) example. A An example classifier model can learn to distinguish CXRs presenting with pneumonia from normal-appearing CXRs; B a regressor model can learn to predict a patient’s age by looking at their CXR; C an example segmentation model can learn to segment the heart on an input CXR; D an example object detector model can learn to localize the heart on an input CXR using a bounding box; E an example generator (inpainting) model can learn to inpaint a covered area of a CXR as if it came from a real radiograph Cardiovascular imaging (CVI) is a rapidly expanding subspecialty of medical imaging that has made substantial contributions to translational research, risk assessment, diagnosis, prognosis, and therapeutic planning studies in structural and functional cardiovascular diseases [7]. In recent years, advanced medical imaging technologies have paved the way for improved phenotyping of cardiovascular pathologies. Given this context and the daily expansion of AI applications in healthcare, one can anticipate an increase in the incorporation of AI into CVI [8]. To comprehend the scope of AI applications in CVI, we conducted a scoping review of the available peer-reviewed literature. Our report attempts to provide an overview of ML research in CVI and to set the stage for future research in this field. Methods In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews [9], we designed a scoping review to answer two overarching research questions: (1) How are ML models used to analyze CVI? And (2) what is the quality of the research used to develop and report these models? To answer the aforementioned questions, we combed through peer-reviewed original studies indexed in MEDLINE from January 1, 2012 to May 31, 2022, which examined the application of ML in CVI. Studies on non-human subjects, non-radiological data (e.g., histology data), fetal cardiovascular topics, non-peer-reviewed articles, non-English articles, review articles, and book chapters were excluded. The search was conducted using the PubMed search engine and a search term comprised MeSH terms and keywords related to cardiovascular organs, radiology imaging, and ML (Supplements 1). Following an initial check for duplicate removal, six reviewers (PR, BK, SF, MM, SV, and EM) independently reviewed the titles and abstracts of the captured search results based on the inclusion and exclusion criteria stated previously. To make this process more reliable, 50 random studies were initially selected, and their data elements were charted by the authors and discussed in a focus group discussion to level their understanding of the required fields. The full text of all eligible articles was then retrieved and revisited by reviewers for final evaluation and data extraction. Due to the lack of appropriate bias assessment tools for ML studies and the desire to maximize the inclusion of relevant articles, no assessment of the risk of bias was performed at this stage. A database of included studies was created, and several aspects of the study characteristics, data handling, model development, and performance evaluation of each article were extracted based on reviewer consensus. The detailed data elements which were charted in each of these categories are introduced in Table 1.Table 1 Detailed data elements extracted from the eligible studies during the data charting phase Category Data elements Study characteristics Publication year Country of the corresponding author Study design Clinical application Studied organs Studied pathologies Data handling Studied imaging modalities The use of multi-modality models Dataset size Model development Machine learning tasks The use of deep learning, conventional machine learning, or both The source of transfer learning (if any) The use of a standardized checklist for model development Performance evaluation The use of cross-validation The use of external validation The provision of interpretation maps for deep learning models The provision of uncertainty measures for deep learning models Due to the heterogeneous scopes, applications, and methodologies of the included articles, no meta-analysis was conducted. Instead, the review results were reported using descriptive statistics. We also offered a narrative synthesis of the statistical findings to help non-technical readers better interpret our analyses. Results A systematic search of the scientific literature yielded 845 distinct papers (no duplicates), of which 215 were excluded after assessing their titles and abstracts. The full text of 41 studies was unavailable with our institutional access, yielding 589 eligible studies for final data extraction (Table 2). A database of all eligible articles and their extracted items is provided in Supplement 2.Table 2 Number of excluded articles in the current report based on their reason for exclusion Reasons for exclusion Number (%) of excluded studies Not radiology study 113 (44.1%) No full-text available 41 (16.0%) Not cardiovascular study 34 (13.3%) No human subject 34 (13.3%) Not machine learning study 25 (9.8%) Not original study 9 (3.5%) Out of 845 identified studies, 256 were excluded, yielding a final pool of 589 eligible articles for data extraction Study Characteristics Figure 3 depicts the distribution of publication years for the collected articles. The number of published articles exhibits a consistent annual increase, with almost 69% of all articles published since 2020. The USA and China contributed the most publications among all countries. The geographic distribution of all published manuscripts is depicted in Fig. 4. The frequency of study designs, clinical applications, studied organs, and studied diseases is depicted in Table 3.Fig. 3 The distribution of publication year across all eligible studies included in our review. The number of published articles exhibits a consistent annual increase, with almost 69% of all articles published since 2020 Fig. 4 The geographic distribution of the corresponding countries for all studies included in the final review pool. The intensity of color for each country correlates with the number of publications from that country Table 3 The frequency of study designs, clinical applications, studied organs, and studied diseases across all eligible articles Category Data elements Number (%) of included studies Study design Observational 510 (86.5%) Retrospective 50 (8.5%) cohort 18 (3.0%) Prospective cohort 7 (1.2%) Case–control Trial 4 (0.7%) Clinical application Informatics 270 (45.8%) Diagnosis 223 (37.9%) Prognosis 26 (4.4%) Primary prevention 25 (4.2%) Treatment 24 (4.1%) Education 1 (0.2%) Combined 16 (2.7%) Others 4 (0.7%) Studied organ Heart 413 (70.1%) Coronary vasculature 120 (20.4%) Aorta 24 (4.1%) Pulmonary vasculature 9 (1.5%) Pericardial fat 6 (1.0%) Conduction system 1 (0.2%) Combined 16 (2.7%) Studied pathology No Pathology 192 (33.2%) Atherosclerosis 109 (18.9%) Valvular disorders 34 (5.9%) Heart failure 28 (4.8%) Ischemic heart disease 22 (3.8%) Arrhythmia 17 (2.9%) Cardiomyopathy 16 (2.9%) Cancer or mass 12 (2.0%) Multiple pathologies 103 (17.8%) Other pathologies 45 (7.8%) While the majority of included studies (510 [86.5%]) were observational, trials were the least common study design (4 [0.7%]). Only 24 (4.1%) of the articles focused on treatment-related applications, while 223 (37.9%) developed ML models for diagnostic purposes. The uses of ML models with no direct clinical application (e.g., for segmenting organs to construct an atlas or for generating synthetic imaging data) were categorized as informatic in 270 (45.8%) of the papers. The heart and atherosclerosis were the most researched organs and pathologies, respectively. Data Handling Table 4 illustrates the distribution of included publications based on the researched imaging modality. In the majority of articles (244 [41.5%]), Magnetic Resonance Imaging (MRI) was the most studied modality, while Single-photon Emission Computed Tomography (SPECT) received the least amount of attention (8 [1.4%]). Only 79 (13.4%) of the included studies presented a multimodal ML method. Table 4 illustrates the distribution of dataset sizes for all articles. Most assessed publications developed their models using 100–1000 examinations.Table 4 The distribution of imaging modalities and dataset size (number of reported examinations) across all eligible studies Category Data elements Number of included studies Imaging modality MRI 244 (41.4%) Echocardiography/Ultrasound 102 (17.3%) CT-angiography 77 (13.1%) Chest CT 41 (6.7%) Cardiac CT 36 (6.2%) Coronary angiography 15 (2.6%) Chest x-ray 11 (1.9%) OCT 9 (1.6%) SPECT 8 (1.4%) Combined 41 (7.0%) Others 5 (0.8%) Dataset size  < 100 138 (23.4%) 100–1000 219 (37.2%) 1000–10,000 122 (20.7%) 10,000–100,000 45 (7.6%) 100,000–1,000,000 9 (1.6%)  > 1,000,000 2 (0.3%) Not Reported 54 (9.2%) Model Development A total of 60 (10.2%) articles did not develop an ML model. Of the remaining articles, the majority (393 [67.1%]) developed a DL model, whereas 102 (17.4%) only developed conventional ML techniques and 31 (5.3%) employed a combination of both approaches. Segmentation tasks were the most common across all studies (224 [42.6%]), followed by classification (115 [21.9%]), a combination of tasks (80 [15.2%]), generation (58 [11.0%]), regression (35 [6.6%]), and object detection (14 [2.7%]). Only 3 (0.5%) of the included studies reported adherence to a standard checklist or protocol when building and (or) evaluating their ML models. Sixty-three (11.9%) articles reported using transfer learning to train their ML models, 36 (57.1%) of which used models pretrained on clinical data. Performance Evaluation A total of 196 (32.7%) of the articles tested their ML models in a cross-validation scenario, and external validation of ML models was reported by 63 (10.6%) of all publications. Only 17 (17.7%) of the studies that utilized classification and regression DL models (96 articles) offered interpretation maps of their performance, and only 29 (4.9%) reported uncertainty measures for their algorithms. Synthesis Study Characteristics CVI is a medical imaging domain with enormous potential for ML application. The yearly growth in the number of publications reviewed demonstrates an increasing interest in conducting such interdisciplinary research. Although the bulk of articles was published by scientific institutes in developed nations, the constraints of conducting ML research in underprivileged locations are quickly diminishing. On the one hand, ML requires less advanced on-site technology than it once did, and many ML operations can be conveniently executed via cloud services [10]. On the other hand, more public medical datasets are made available every day, which can enable ML research in locations that lack access to extensive institutional data [11]. Most ML studies with direct clinical applications had an observational setup with a diagnostic focus. This was not unexpected given that observational studies are the most viable study design, and classification is the most prevalent application of ML. However, we should stress the avenues of research that can leverage other study types or focus on outcomes other than diagnosis. For example, Commandeur et al. designed a prospective ML study to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium, and epicardial adipose tissue [12]. Their study is a good example of applying ML for primary prevention and also in a prospective setting. As another example, Lee et al. applied conventional ML to non-invasive measurements from Computed Tomography (CT) images and electrocardiograms (ECGs) to predict patients’ responses to cardiac resynchronization therapy. Their work exemplifies how ML models could help with different therapeutic planning scenarios [13]. Lastly, we observed a significant amount of research in areas like segmenting heart chambers, quantifying epicardial fat, and coronary artery calcium scoring by applying ML to various imaging modalities. Despite the undeniable significance of such topics, we strongly encourage ML researchers to investigate other study fields as well. In light of this proposal, we can provide an example of an innovative study by Pyrros et al., which applied ML to CXRs to analyze racial/ethnic and socioeconomic differences in the prevalence of atherosclerotic vascular disease [14]. Even among diagnostic studies, innovation and high-impact research are not rare. Recent research by Liebig et al. demonstrates that collaboration between ML models and radiologists improves the performance of mammography-based breast cancer screening compared to relying solely on radiologists’ decisions [15]. They endorsed a novel retrospective interventional design for their investigation, which could be replicated in CVI studies. Data Handling Most of the examined papers focused on MRIs and echocardiograms. AI can provide many solutions for image acquisition, reconstruction, and analysis of cardiac MRI studies [16]. Echocardiography, on the other hand, has various limitations (such as a longer process duration, high operator subjectivity, and vast observation ranges) that could be ameliorated by artificial intelligence [17]. Apart from these two modalities, chest CT scans are commonly ordered for a variety of thoracic diseases, including lung diseases. Automated ML models that can evaluate the heart and circulation on chest CT scans are therefore excellent candidates for opportunistic cardiovascular disease screening. Examples of such applications could be a study by Commandeur et al., which leveraged DL to quantify epicardial fat on non-contrast chest CT scans of asymptomatic individuals [18], and another study by Aquino et al., which measured the size of the left atrium on chest CT scans for prediction of cardiovascular outcomes [19]. We found a few publications that built and assessed multimodal ML models. Multi-modal (or fusion) models are a group of models that comprise data from multiple imaging modalities or any non-imaging data (e.g., clinical variables or textual data) in addition to imaging data [20]. ML models and, in particular, DL models can simultaneously analyze numerous kinds of data, much like human medical experts who frequently rely on multiple pieces of data from a single patient to reach a diagnostic or therapeutic conclusion. Input data to ML models may be distinct imaging modalities; for instance, Puyol-Anton et al. created a DL model to predict patients’ responses to cardiac resynchronization therapy using 2D echocardiography and cardiac MRI [21]. A blend of imaging and non-imaging data can also be used to train multimodal ML models. For instance, Huang et al. developed a DL model capable of detecting pulmonary embolisms in CT Pulmonary Angiography examinations while also leveraging information from the patient’s electronic health records [22]. They demonstrated that the performance of their multimodal model was superior to that of an identical model trained just on CT imaging. The number of examinations utilized by the eligible articles for training or evaluating their ML models varied considerably. Aside from the differences in the actual size of the data researchers had access to, this variability could be attributed to two other factors: (1) the reviewed articles did not share their dataset size in a consistent manner. While some articles simply reported the number of examinations used, many others only reported the number of patients included in their study (without clarifying how many exams had been obtained from each patient). Furthermore, a few instances described the size of their datasets using inaccurate terms, such as subjects or scans. Such terms may refer to both the number of patients and the number of images, which might confuse the reader. (2) Terms like scan, image, and imaging are not used consistently in the medical imaging literature. In addition to referring to a single two-dimensional (2D) image, these words can also imply a three-dimensional (3D) volume. As a best practice, we encourage ML researchers to always supply separate patient and examination numbers for their research. The terminology used to describe 2D and 3D imaging data in research should also be clarified. These tips can considerably improve the reproducibility of ML research and lessen its susceptibility to bias [23•]. Finally, we would like to emphasize the significance of considering publicly accessible medical datasets when undertaking ML research in medical imaging. Multiple free public datasets are available to ML researchers for various medical imaging modalities [11]. Therefore, researchers who lack sufficient internal data to train their models may find comparable data from other institutions. Using data from such an external source will not only increase the training size of ML models but also make them more generalizable. The EchoNet-Dynamic dataset of more than 10,000 echocardiograms [24], the Lung Image Database Consortium image collection (LIDC-IDRI) dataset of more than 1000 chest CT scans [25], the ImageTBAD dataset of more than 100 CT angiographies with type-B aortic dissection [26], and the Cardiac Atlas Project (CAP) dataset of more than 80 cardiac MRIs [27] are among the public datasets that were introduced in different articles we reviewed. However, this is not an exhaustive list of available datasets, and we encourage researchers to seek appropriate public datasets before conducting any study. ML competition websites such as Kaggle are also an excellent place to hunt for public data, although using such datasets in ML research should be undertaken with extreme caution [23•]. Model Development As previously noted, DL models are much more complicated than conventional ML models and have a higher learning capacity. This explains why DL models have been more popular than conventional ML methods in the reviewed articles. However, DL is not always the go to option in ML research and selecting the appropriate ML model is more task specific. Although DL models are widely regarded as state-of-the-art computer solutions for automated decision-making in many different fields, there are some circumstances where conventional ML models or a combination of DL and conventional ML methods offer higher performance or are more affordable than DL methods [4, 28]. In a study by Gao et al., for instance, tree-based traditional ML techniques such as gradient boosting machines outperformed neural networks for vessel segmentation on X-ray coronary angiography [29]. It is also commonly believed that, when applied to tabular data, the same tree-based models are frequently superior to or on par with DL approaches [30]. Segmentation and classification were the most researched ML applications across all studies. Nonetheless, ML has additional intriguing uses in CVI. Among the least investigated ML tasks were object detection methods. Similar to segmentation models, these models pinpoint items of interest in input images while requiring less annotation effort (one draws rectangles around target objects rather than paints over all their pixels). For instance, Nizar et al. introduced an object detection technique for real-time aortic valve detection on echocardiography [31]. Another interesting area of research in medical imaging is image generation. Although current research efforts have utilized generative DL for objectives, such as removing artifacts from imaging data [32], raising the resolution of imaging [33], producing synthetic imaging datasets [34, 35], and improving segmentation outcomes [36], and the capabilities of generative models are far broader. It has been demonstrated that generative models can convert two biplanar CXRs to a natural-looking chest CT scan and even incorporate synthetic tumoral lesions into normal imaging data [37, 38]. Transfer learning is the technical term for when a DL model is first trained (pretrained) on a different dataset and its parameters are then fine-tuned on the dataset of interest [39]. This technique enables DL models to be trained more quickly (assuming the time to train the pretrained model is not included), with less training data, and with greater generalizability to unseen data [40]. The quality and similarity of the initial dataset that the model was pretrained on are a significant factor in determining the efficiency of transfer learning. Transfer learning is more beneficial for DL models when the original dataset is large and has imaging features similar to those of the dataset of interest. Surprisingly, several of the examined articles did not disclose whether or not they used transfer learning. A few of those who reported employing transfer learning had pretrained their models using non-medical imaging datasets, such as ImageNet. Medical images, however, are fundamentally different from natural photographs, and pretraining DL models on natural photographs may not be the best transfer learning choice for medical images. Pretraining DL models using public medical image datasets is a more effective technique. Ankenbrand et al. illustrate this strategy by transferring weights from a DL model pretrained on a public medical image dataset to train their DL model for segmenting the heart on cardiac MRI data [41]. Almost none of the examined research acknowledged developing their ML models using a systematic checklist like the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) [42•]. While many aspects of ML studies, including but not limited to model development, are susceptible to systematic biases [23•, 43•, 44•], documenting study adherence to a set of predefined standards helps reassure both researchers and their audience about the validity and reliability of a model's performance. In addition, publicly sharing the code, datasets, and weights of the trained ML models can further improve the repeatability of the researchers’ work, but we recognize that such public disclosures may not always be possible due to institutional policies that hold sway. Performance Evaluation It is typical in ML to sequester a random subset of data as the test set and train the ML models on the remaining data with or without validation sets). This allows the trained model to be evaluated against an untouched test set. When datasets are small or very imbalanced, this typical method of data partitioning is not the most effective. Instead, cross-validation approaches can provide a more accurate evaluation of a model’s performance under such conditions [23•]. Even though many medical datasets are either small or highly imbalanced, few of the examined articles utilized cross-validation strategies. This is a crucial shortcoming that diminishes confidence in their reported performance. We should note, though, that we also identified a few studies that employed more sophisticated and reliable kinds of cross-validation, such as nested cross-validation [45, 46]. Similar to cross-validation, few studies documented external validation of their ML models. External validation is a valuable performance measure as it helps to demonstrate a model’s generalizability to unseen data [47]. For example, assume that a DL model performs well on internal test data, but its performance declines significantly when applied to data from other institutions. A likely explanation for this observation could be the discrepancy in medical imaging devices and vendors across different institutions. A well-trained ML model should have minimal (or acceptable) sensitivity to the vendor-specific characteristics of the input imaging data and be able to extract relevant signals from that data regardless of its acquisition properties. Even if the internal and external performance of a DL model is exceptional, there is no assurance that these models have learned to pick relevant and meaningful imaging signals. For instance, the apparent superior performance of a DL model in identifying pneumonia may be attributable to its attention to radiology markers present in CXR imaging [48]. Even though DL models are commonly referred to as black boxes, there are ways to visualize the regions of the imaging data to which they contribute the most when making predictions. This is called DL interpretation (or explanation) mapping [49]. Despite its uttermost importance, the majority of research employing DL classifier or regressor models did not report interpretation mapping for their models. Although interpretation maps have limitations [50], they can often shed more light on what a DL model has learned and whether or not it appears valid to human experts. Finally, DL models could have uncertain performance due to their inherent properties or when they encounter data points that were not adequately represented in their training data [51•]. For example, a classifier designed to distinguish between non-COVID-19 and COVID-19 viral pneumonia on the CXR may be unreliable when used on a CXR presenting with bacterial pneumonia. Even though neither label could be accurate, this classifier will still predict a label for this CXR and without adequate uncertainty quantification, a naive user may accept that prediction. Although several techniques exist for uncertainty quantification of DL models, they have not been thoroughly studied for medical purposes and therefore, it is not surprising that only a small number of studies in our pool have employed such techniques (52). The need to quantify the uncertainty of DL models, however, will likely become more and more important to healthcare researchers. Discussion CVI is a rapidly growing area of medical imaging with ample opportunities for ML study. In this report, we presented the findings of a recent scoping review describing the applications of ML in CVI. Our findings must be evaluated in light of two significant limitations. First, due to feasibility concerns, we limited our search to the MEDLINE database and English peer-reviewed manuscripts. Searching other databases, adding non-English and gray literature, and applying broader search terms would increase the number of articles eligible for inclusion. Despite this limitation, we believe that our combined pool of articles were sufficient to describe the broad trends in ML research for CVI. Second, we did not conduct a bias assessment of the individual articles included in our review. We considered this limitation acceptable because our objective was not to perform any meta-analyses on the results of the review but rather to assemble a more thorough list of factors that might make included studies more susceptible to bias. In conclusion, we used quantitative statistics and qualitative synthesis to summarize four major aspects of ML research in CVI (study characteristics, data handling, model development, and performance evaluation) and attempted to sketch the big picture of current research gaps and future directions for similar studies. Supplementary Information Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 7 KB) Supplementary file2 (XLSX 694 KB) Acknowledgements We thank Dr. Hani Abujudeh for reviewing the manuscript. Funding N.A. Data Availability All data analyzed during this study are provided in the supplementary materials. Declarations Conflict of interest The authors declare that they have no conflict of interest. Research Involving Human and Animals Rights This article does not contain any studies with human or animal subjects performed by any of the authors. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Pouria Rouzrokh and Bardia Khosravi have contributed equally to this work. ==== Refs References Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance 1. Guo Y Hao Z Zhao S Gong J Yang F Artificial intelligence in health care: bibliometric analysis J Med Internet Res 2020 22 7 e18228 10.2196/18228 32723713 2. Secinaro S Calandra D Secinaro A Muthurangu V Biancone P The role of artificial intelligence in healthcare: a structured literature review BMC Med Inform Decis Mak 2021 21 1 125 10.1186/s12911-021-01488-9 33836752 3. •Weinan E. Machine Learning and Computational Mathematics. arXiv [math.NA]. 2020. http://arxiv.org/abs/2009.14596. This reference is a nice introduction to machine learning and their mathematical background. 4. •Chauhan NK, Singh K. A Review on Conventional Machine Learning vs Deep Learning. 2018 International Conference on Computing, Power and Communication Technologies (GUCON). 2018. p. 347–352. This reference is a nice introduction to deep learning and how it stands differently from conventional machine learning methods. 5. •King B, Barve S, Ford A, Jha R. Unsupervised Clustering of COVID-19 Chest X-Ray Images with a Self-Organizing Feature Map. 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS). 2020. p. 395–398. This reference provides an interesting example of unsupervised learning in medical imaging. 6. •Elyan, Vuttipittayamongkol. Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward. Artif Cells Blood Substit Immobil Biotechnol. https://rgu-repository.worktribe.com/output/1631673/computer-vision-and-machine-learning-for-medical-image-analysis-recent-advances-challenges-and-way-forward. This reference highlights the most recent applications of machine learning in medical image analysis. 7. Di Carli MF Geva T Davidoff R The future of cardiovascular imaging Circulation 2016 133 25 2640 2661 10.1161/CIRCULATIONAHA.116.023511 27324360 8. Esteva A Chou K Yeung S Deep learning-enabled medical computer vision NPJ Digit Med 2021 4 1 5 10.1038/s41746-020-00376-2 33420381 9. Page MJ McKenzie JE Bossuyt PM The PRISMA 2020 statement: an updated guideline for reporting systematic reviews Rev Esp Cardiol 2021 74 9 790 799 10.1016/j.recesp.2021.06.016 34446261 10. Agavanakis KN Karpetas GE Taylor M Practical machine learning based on cloud computing resources AIP Conf Proc 2019 2123 1 020096 10.1063/1.5117023 11. ••Li J, Zhu G, Hua C, et al. A Systematic Collection of Medical Image Datasets for Deep Learning. arXiv [eess.IV]. 2021. http://arxiv.org/abs/2106.12864. It introduces multiple public datasets for training deep learning models on medical imaging data. 12. Commandeur F Slomka PJ Goeller M Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium, and epicardial adipose tissue: a prospective study Cardiovasc Res 2020 10.1093/cvr/cvz321 13. Lee AWC Razeghi O Solis-Lemus JA Non-invasive simulated electrical and measured mechanical indices predict response to cardiac resynchronization therapy Comput Biol Med 2021 138 104872 10.1016/j.compbiomed.2021.104872 34598070 14. Pyrros A Rodríguez-Fernández JM Borstelmann SM Detecting racial/ethnic health disparities using deep learning from frontal chest radiography J Am Coll Radiol 2022 19 1 Pt B 184 191 10.1016/j.jacr.2021.09.010 35033309 15. Leibig C Brehmer M Bunk S Byng D Pinker K Umutlu L Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis Lancet Digit Health 2022 4 7 e507 e519 10.1016/S2589-7500(22)00070-X 35750400 16. Fotaki A Puyol-Antón E Chiribiri A Botnar R Pushparajah K Prieto C Artificial intelligence in cardiac MRI: is clinical adoption forthcoming? Front Cardiovasc Med 2021 8 818765 10.3389/fcvm.2021.818765 35083303 17. Zhou J Du M Chang S Chen Z Artificial intelligence in echocardiography: detection, functional evaluation, and disease diagnosis Cardiovasc Ultrasound 2021 19 1 29 10.1186/s12947-021-00261-2 34416899 18. Commandeur F Goeller M Betancur J Deep learning for quantification of epicardial and thoracic adipose tissue from non-contrast CT IEEE Trans Med Imaging 2018 37 8 1835 1846 10.1109/TMI.2018.2804799 29994362 19. Aquino GJ Chamberlin J Mercer M Deep learning model to quantify left atrium volume on routine non-contrast chest CT and predict adverse outcomes J Cardiovasc Comput Tomogr 2022 16 3 245 253 10.1016/j.jcct.2021.12.005 34969636 20. Huang S-C Pareek A Seyyedi S Banerjee I Lungren MP Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines NPJ Digit Med 2020 3 136 10.1038/s41746-020-00341-z 33083571 21. Puyol-Antón E Sidhu BS Gould J A multimodal deep learning model for cardiac resynchronisation therapy response prediction Med Image Anal 2022 79 102465 10.1016/j.media.2022.102465 35487111 22. Huang S-C Pareek A Zamanian R Banerjee I Lungren MP Multimodal fusion with deep neural networks for leveraging CT imaging and electronic health record: a case-study in pulmonary embolism detection Sci Rep 2020 10 1 22147 10.1038/s41598-020-78888-w 33335111 23. •Rouzrokh P, Khosravi B, Faghani S, et al. Mitigating Bias in Radiology Machine Learning: 1. Data Handling. Radiology: Artificial Intelligence. Radiological Society of North America; 2022;4(5):e210290. This paper discusses how bias can happen and be mitigated during model development of machine learning models in medicine. 24. Ouyang D He B Ghorbani A Video-based AI for beat-to-beat assessment of cardiac function Nature 2020 10.1038/s41586-020-2145-8 25. Armato SG 3rd McLennan G Bidaut L The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans Med Phys 2011 38 2 915 931 10.1118/1.3528204 21452728 26. Yao Z Xie W Zhang J ImageTBAD: A 3D computed tomography angiography image dataset for automatic segmentation of type-B aortic dissection Front Physiol 2021 12 732711 10.3389/fphys.2021.732711 34646158 27. Fonseca CG Backhaus M Bluemke DA The Cardiac Atlas Project—an imaging database for computational modeling and statistical atlases of the heart Bioinformatics. Oxford Academic 2011 27 16 2288 2295 10.1093/bioinformatics/btr360 28. Lai Y A comparison of traditional machine learning and deep learning in image recognition J Phys Conf Ser. IOP Publishing 2019 1314 1 012148 10.1088/1742-6596/1314/1/012148 29. Gao Z Wang L Soroushmehr R Vessel segmentation for X-ray coronary angiography using ensemble methods with deep learning and filter-based features BMC Med Imaging 2022 22 1 10 10.1186/s12880-022-00734-4 35045816 30. •Grinsztajn L, Oyallon E, Varoquaux G. Why do tree-based models still outperform deep learning on tabular data? arXiv [cs.LG]. 2022. http://arxiv.org/abs/2207.08815. This reference lists several reasons for why conventional machine learning approaches like tree-based models are sometimes better in interpreting tabular data than deep learning models. 31. Nizar MHA Chan CK Khalil A Yusof AKM Lai KW Real-time detection of aortic valve in echocardiography using convolutional neural networks Curr Med Imaging Rev 2020 16 5 584 591 10.2174/1573405615666190114151255 32. Nezafat M El-Rewaidy H Kucukseymen S Hauser TH Fahmy AS Deep convolution neural networks based artifact suppression in under-sampled radial acquisitions of myocardial T 1 mapping images Phys Med Biol 2020 65 22 225024 10.1088/1361-6560/abc04f 33045693 33. Mahapatra D Bozorgtabar B Garnavi R Image super-resolution using progressive generative adversarial networks for medical image analysis Comput Med Imaging Graph 2019 71 30 39 10.1016/j.compmedimag.2018.10.005 30472408 34. Sun Y Vixege F Faraz K A pipeline for the generation of synthetic cardiac color doppler IEEE Trans Ultrason Ferroelectr Freq Control 2022 69 3 932 941 10.1109/TUFFC.2021.3136620 34986095 35. Prakosa A Sermesant M Delingette H Generation of synthetic but visually realistic time series of cardiac images combining a biophysical model and clinical images IEEE Trans Med Imaging 2013 32 1 99 109 10.1109/TMI.2012.2220375 23014716 36. Xu C Xu L Ohorodnyk P Roth M Chen B Li S Contrast agent-free synthesis and segmentation of ischemic heart disease images using progressive sequential causal GANs Med Image Anal 2020 62 101668 10.1016/j.media.2020.101668 32276185 37. •Ying, Guo, Ma, Wu, Weng. X2CT-GAN: reconstructing CT from biplanar X-rays with generative adversarial networks. Proc Estonian Acad Sci Biol Ecol. http://openaccess.thecvf.com/content_CVPR_2019/html/Ying_X2CT-GAN_Reconstructing_CT_From_Biplanar_X-Rays_With_Generative_Adversarial_Networks_CVPR_2019_paper.html. This reference introduces an interesting deep learning model that can build a three-dimensional CT scan from a two-dimensional Chest X-ray. 38. •Wolleb J, Sandkühler R, Bieder F, Cattin PC. The Swiss Army Knife for Image-to-Image Translation: Multi-Task Diffusion Models. arXiv [cs.CV]. 2022. http://arxiv.org/abs/2204.02641. This paper introduces different applications of diffusion models, including a couple of interesting applications in medicine. 39. Kim HE Cosa-Linan A Santhanam N Jannesari M Maros ME Ganslandt T Transfer learning for medical image classification: a literature review BMC Med Imaging 2022 22 1 69 10.1186/s12880-022-00793-7 35418051 40. •Iman M, Rasheed K, Arabnia HR. A Review of Deep Transfer Learning and Recent Advancements. arXiv [cs.LG]. 2022. http://arxiv.org/abs/2201.09679. This paper introduces transfer learning, a deep learning technique that enables new models leverage the knowledge of the already trained models. 41. Ankenbrand MJ Lohr D Schlötelburg W Reiter T Wech T Schreiber LM Deep learning-based cardiac cine segmentation: transfer learning application to 7T ultrahigh-field MRI Magn Reson Med 2021 86 4 2179 2191 10.1002/mrm.28822 34002412 42. •Mongan J, Moy L, Kahn CE Jr. Checklist for Artificial Intelligence in Medical Imaging (CLAIM): A Guide for Authors and Reviewers. Radiol Artif Intell. 2020;2(2):e200029. This paper introduces a checklist for standard development of machine learning models in medicine. 43. •Zhang K, Khosravi B, Vahdati S, et al. Mitigating Bias in Radiology Machine Learning: 2. Model Development. Radiology: Artificial Intelligence. Radiological Society of North America; 2022;e220010. This paper discusses how bias can happen and be mitigated during model development of machine learning models in medicine. 44. •Faghani S, Khosravi B, Zhang K, et al. Mitigating Bias in Radiology Machine Learning: 3. Performance Metrics. Radiology: Artificial Intelligence. Radiological Society of North America; 2022;e220061. This paper discusses how bias can happen and be mitigated in during the performance evaluation of machine learning models in medicine. 45. Larroza A Materka A López-Lereu MP Monmeneu JV Bodí V Moratal D Differentiation between acute and chronic myocardial infarction by means of texture analysis of late gadolinium enhancement and cine cardiac magnetic resonance imaging Eur J Radiol 2017 10.1016/j.ejrad.2017.04.024 46. Kotu LP Engan K Borhani R Cardiac magnetic resonance image-based classification of the risk of arrhythmias in post-myocardial infarction patients Artif Intell Med 2015 64 3 205 215 10.1016/j.artmed.2015.06.001 26239472 47. Yu AC Mohajer B Eng J External validation of deep learning algorithms for radiologic diagnosis: a systematic review Radiol Artif Intell 2022 4 3 e210064 10.1148/ryai.210064 35652114 48. Zech JR Badgeley MA Liu M Costa AB Titano JJ Oermann EK Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: a cross-sectional study PLoS Med 2018 15 11 e1002683 10.1371/journal.pmed.1002683 30399157 49. Ayyar MP Benois-Pineau J Zemmari A Review of white box methods for explanations of convolutional neural networks in image classification tasks JEI 2021 30 5 050901 50. •Saporta, Gui, Agrawal, Pareek, Truong. Deep learning saliency maps do not accurately highlight diagnostically relevant regions for medical image interpretation. MedRxiv. This reference explains how saliency maps, that are often used for explaining how deep learning models work, could be biased and how they should be interpreted with caution. 51. •Abdar M, Pourpanah F, Hussain S, et al. A review of uncertainty quantification in deep learning: Techniques, applications and challenges. Inf Fusion. 2021;76:243–297. This article discusses different applications of uncertainty quantification in deep learning. 52. Loftus TJ Shickel B Ruppert MM Uncertainty-aware deep learning in healthcare: a scoping review PLOS Digit Health 2022 1 8 0000085 10.1371/journal.pdig.0000085
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==== Front Iran J Sci Technol Trans A Sci Iran J Sci Technol Trans A Sci Iranian Journal of Science and Technology. Transaction A, Science 1028-6276 2364-1819 Springer International Publishing Cham 1387 10.1007/s40995-022-01387-2 Research Paper An INAR(1) Time Series Model via a Modified Discrete Burr–Hatke with Medical Applications http://orcid.org/0000-0002-8061-4672 Shirozhan Masoumeh [email protected] 1 Mamode Khan Naushad Ali [email protected] 2 Bakouch Hassan S. [email protected] [email protected] 34 1 Water and Wastewater Company, Ardabil, Ardabil Province Iran 2 grid.45199.30 0000 0001 2288 9451 Department of Economics and Statistics, University of Mauritius, Moka, Mauritius 3 grid.412602.3 0000 0000 9421 8094 Department of Mathematics, College of Science, Qassim University, Buraydah, Saudi Arabia 4 grid.412258.8 0000 0000 9477 7793 Department of Mathematics, Faculty of Science, Tanta University, Tanta, Egypt 12 12 2022 116 6 3 2022 10 11 2022 © The Author(s), under exclusive licence to Shiraz University 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. This paper introduces a flexible discrete transmuted record type discrete Burr–Hatke (TRT-DBH) model that seems suitable for handling over-dispersion and equi-dispersion in count data analysis. Further to the elegant properties of the TRT-DBH, we propose, in the time series context, a first-order integer-valued autoregressive process with TRT-DBH distributed innovations [TRBH-INAR(1)]. The moment properties and inferential procedures of this new INAR(1) process are studied. Some Monte Carlo simulation experiments are executed to assess the consistency of the parameters of the TRBH-INAR(1) model. To further motivate its purpose, the TRBH-INAR(1) is applied to analyze the series of the COVID-19 deaths in Netherlands and the series of infected cases due to the Tularaemia disease in Bavaria. The proposed TRBH-INAR(1) model yields superior fitting criteria than other established competitive INAR(1) models in the literature. Further diagnostics related to the residual analysis and forecasting based on the TRBH-INAR(1) model are also discussed. Based on modified Sieve bootstrap predictors, we provide integer forecasts of future death of COVID-19 and infected of Tularemia. Keywords Transmuted record type INAR(1) model Modified empirical likelihood COVID-19 disease Tularemia disease ==== Body pmcIntroduction Count data are commonly encountered in everyday life phenomena, including insurance, economics, social sciences, medicines, transport and among an unlimited number of areas. In these applications, the count observations are normally expressed as positive integers that are collected on a daily, weekly, or monthly sequential basis. Hence, such repeated observations are more likely serially correlated. On the other side, these series of counts are commonly over-dispersed due to some outliers or presence of physical or latent effects and, in some cases, can be equi-dispersed or under-dispersed as well. Thus, there is an important need to appropriately model the series of counts via the suitable distribution that can accommodate as fully as possible different statistical features. The prevalent probability models in the literature include the geometric, Poisson, Poisson mixtures (Karlis and Xekalaki 2005), Conway–Maxwell Poisson (Shmueli et al. 2005; Sellers and Shmueli 2010; Sellers et al. 2012) distributions. However, owing to the complex nature and some unique properties of the natural phenomena, such as skewness, dispersion, monotone or unimodal failure rate, inflation or deflation, these conventional density functions may not be fully relevant, as similarly argued in El-Morshedy et al. (2020), Eliwa and El-Morshedy (2021) and the references therein. This leads to introducing some other more flexible distributions for positive counts that emerge from discretizing some continuous functions. Examples of such distributions have been comprehensively studied by Gómez-Déniz and Calderín-Ojeda (2011), Chakraborty and Chakravarty (2012), Nekoukhou et al. (2013), Bakouch et al. (2014), Hussain et al. (2016), Bahti and Bakouch (2019), Altun (2020) and references therein. In this same sense, this paper introduces a modified discrete Burr–Hatke (BH) model, based on the transmuted record type (TRT) constructor introduced by Shakil and Ahsanullah (2011). The discrete version of BH model has been recently proposed by El-Morshedy et al. (2020) to model count events exhibiting huge over-dispersion with various skewness features. The discrete version of BH stands out as a main competitor to the traditional count models as it yields far more superior fitting criteria. This paper focuses on the TRT construction strategy because it leads to skewed distributions and is compatible with one side long-tailed data. The transmuted distributions are special cases of extremal distributions (Kozubowski and Podgórski 2016). Further to the choice of the probability model, there is a need to investigate the relevant time series structures related to the counts of correlated nature. For repeated count observations, McKenzie (1986), McKenzie (1988) and Al-Osh and Alzaid (1987) introduced the thinning-based INAR(1) processes. The classical INAR(1) model consists of two important components: a survival part that relates the current observation with its previous lagged via the thinning, in particular, the binomial thinning operation (Steutel and van Harn 1979) and a random innovation or error component. In the original INAR(1) model, the innovation was allowed to follow the benchmark Poisson, while the binomial thinning was defined with the fixed or random coefficient. Over the years, in view of obtaining better fitting criteria or information criteria in severely over-dispersed or zero inflated data series, several authors have proposed a vast number of alterations to either the innovation terms. The INAR(1) model based on the geometric innovations was introduced by Jazi et al. (2012), which can handle the over-dispersed count data sets. The INAR(1) model with the binomial thinning operator and Poisson–Lindley innovation was established by Lívio et al. (2018), and several estimation methods, including the conditional least squares, Yule–Walker and conditional maximum likelihood, were used for estimating the parameters. Recently, to cover some unique properties of real data sets, other distributions were designated for innovation of the IANR(1) models, such as power series (Bourguignon and Vasconcellos 2015), Poisson-transmuted exponential (Altun and Mamode Khan 2021) and Bell (Huang and Zhu 2021). Borges et al. (2017) introduced a new operator called ρ-negative binomial thinning operator and provided a new INAR(1) process with geometric marginals that can be applied for phenomena with excess zeros. Liu and Zhu (2021) introduced a new flexible thinning operator named extended binomial that has two parameters. Considering the extended binomial operator, they defined a new INAR(1) model and estimated the unknown parameters through the two-step conditional least squares and conditional maximum likelihood methods. Ristić et al. (2013) were the first to propose the INAR(1) process having a dependent count series. Shirozhan et al. (2019) combined the Pegram operator with the dependent thinning operator. A new dependent negative binomial thinning operator based on the inflated geometric counting series is introduced by Shamma et al. (2020). In classical models, the counting series are expected to be independent, which is not often the case in real-world situations like contagious diseases. Also, the binomial thinning operator is not suitable for zero inflated demands. After an outbreak has gone, we occasionally come across data sets with too many zeros. As a result, we need a count model that can deal with zero inflation. All earlier drawbacks stimulate us to introduce a new INAR(1) model based on the generalized negative binomial (GNB) thinning operator with flexible discrete innovations. The most notable feature of the utilized thinning operator is that it may be used for data sets with additional observations. The principal aim of this paper is devoted to introducing an INAR(1) model with dependent counting series with flexible innovations, where the dependency of the count series makes the thinning operator more suitable for modeling practical count data sets. Some clinical data sets demonstrate the applicability of the suggested model. The following is the outline of the paper. Section 2 introduces a distribution using the TRT approach and the discrete BH baseline distribution. Also, the survival, hazard rate, probability generating functions and non-central moments of the proposed distribution are provided. The GNB thinning operator is reviewed in Sect. 3. With the proposed discrete innovations, the INAR(1) process is developed, which is based on the GNB thinning operator, and some properties of the process are investigated, including the conditional mean and variance. Several parametric and nonparametric estimation methods for the proposed INAR(1) process are reported in Sect. 4. Finally, in Sect. 5, two real-life count data are utilized to analyze the application of the introduced INAR(1) model, demonstrating our model’s suitability in contrast to several relevant INAR(1) models. A Modified Version of Discrete Burr–Hatke Distribution In this section, we provide a modified discrete distribution based on transmuted record type method and discrete Burr–Hatke baseline distribution. The survival and hazard rate function, along with some statistical properties of the distribution, are also given. First, we consider the DBH distribution, which is introduced by El-Morshedy et al. (2020). The cumulative distribution function (CDF) and probability mass function (PMF) of DBH distribution are represented, respectively, asHY(y,λ)=1-λy+1y+2,0<λ<1,y=0,1,2,…,hY(y,λ)=(1y+1-λy+2)λy. Now, we review the TRT method, which is defined asZ=dYU(1)w.p.1-γYU(2)w.p.γ,0<γ<1, where YU(1) and YU(2) are, respectively, the first and second upper records [for more details, see Shakil and Ahsanullah (2011)]. Hence, the CDF of TRT distribution is shown asFZ(z,λ,γ)=HY(z)+γ(1-HY(z))ln(1-HY(z)), where HY(z) is an arbitrary CDF baseline distribution. Consider the DBH baseline distribution, the CDF of the proposed distribution is represented asFZ(z,λ,γ)=1-λz+1z+2+γ(λz+1z+2)ln(λz+1z+2)=1-λz+1z+2[1-γln(λz+1z+2)], and the PMF isfZ(z,λ,γ)=FZ(z,λ,γ)-FZ(z-1,λ,γ)=λz[1z+1-λz+2-γ(1z+1ln(λzz+1)-λz+2ln(λz+1z+2))]. We call this distribution as the transmuted record type-discrete Burr–Hatke. The survival and hazard rate functions (HRF) of the TRT-DBH are demonstrated as belowS(z,λ,γ)=λz+1z+2[1-γln(λz+1z+2)],HRF(z,λ,γ)=fZ(z,λ,γ)S(z-1,λ,γ)=1-λ(z+1)(1-γln(λz+1z+2))(z+2)(1-γln(λzz+1)). The PMF and HRF plots of TRT-DBH distribution are depicted in Figs. 1 and 2, for different combinations of the parameters.Fig. 1 The PMF plots for TRT-DBH distribution with different combinations of parameters (λ,γ) Fig. 2 The HRF plots for TRT-DBH distribution with different combinations of parameters (λ,γ) It is clear that the HRF of TRT-DBH distribution has different shapes, including decreasing and unimodal, which dedicate the capability of TRT-DBH distribution to model different types of data sets. Some Statistical Properties of TRT-DBH Distribution Now, some properties of the TRT-DBH distribution are investigated, such as the probability generating function, r-th non-central moments, and so on. Let Z follow the TRT-DBH distribution with the parameters (λ,γ), then its probability generating function is obtained as followsGZ(s)=E(SZ)=∑z=0∞sz[λzz+1-λz+1z+2]-γ∑z=0∞sz[λzz+1ln(λzz+1)-λz+1z+2ln(λz+1z+2)]=1Sλ(1-1s)∑z=0∞(sλ)z+1z+1+1s-γln(λ)(1-1s)∑z=0∞(1-1z+1)(Sλ)z+γ(1-1s)∑z=0∞ln(z+1)(sλ)zz+1=(1-1s){-1sλln(1-sλ)-γln(λ)[11-sλ-1sλln(1-sλ)]-γSλΦ′(sλ,1,2)}+1s,|s|<1 where Φ(a,b,c)=∑n=0∞an(n+c)b,|a|<1 is the LerchPhi function and we denote its derivative asΦ′(a,b,c)=∂∂bΦ(0,1,0)(a,b=b0,c)∣b=b0. Noted that both λ and s are restricted (0<λ<1,|s|<1); hence, the condition of the LerchPhi function is satisfied. The r-th non-central moments of TRT-DBH distribution are represented asE(Zr)=∑z=0∞zrfZ(z,λ,γ)=∑z=0∞(zr-(z-1)r)λzz+1-γ∑z=0∞(zr-(z-1)r)λzz+1ln(λzz+1). It is concluded that the first and second moments of the TRT-DBH distribution are as follows1 μZ=E(Z)=-1-ln(1-λ)λ-γ[ln(λ)(11-λ+ln(1-λ)λ)+λΦ′(λ,1,2)],E(Z2)=3-λ1-λ+3ln(1-λ)λ-γln(λ)(5λ-3(1-λ)2-3ln(1-λ)λ)-γ(2Φ′(λ,0,1)-3λΦ′(λ,1,2)). Accordingly, based on the first and second moments, the variance of TRT-DBH distribution can be obtained in closed form. The Fisher dispersion index (FDI) is defined as the variance to mean ratio, which indicates whether a certain distribution is suitable for under or over-dispersed data sets. If FDI <(>)1, the distribution is under-dispersed (over-dispersed). The numerical mean, variance, skewness, kurtosis and FDI of TRT-DBH distribution are provided in Table 1, for different combinations of the parameters. Based on Table 1, the mean and variance of TRT-DBH are increased by increasing values of parameters λ and γ. Also, for small values of λ and large values of γ, the FDI measure is near to one, which indicates the equi-dispersion of TRT-DBH distribution. For other combinations of (λ,γ), the FDI measure is more than one, so the TRT-DBH distribution is over-dispersion. The TRT-DBH distribution is severely skewed to right and leptokurtic. So, TRT-DBH distribution also has a perfect fit for right long-tailed data. Based on Fig. 3, the values of Var(Z)-E(Z) are always positive, which confirms the results of Table 1 and the over-dispersion nature of the TRT-DBH model.Table 1 Some statistical properties of the TRT-DBH distribution Measures (λ,γ) (0.1, 0.1) (0.1, 0.5) (0.1, 0.9) (0.5, 0.1) (0.5, 0.5) (0.5, 0.9) (0.9, 0.1) (0.9, 0.5) (0.9, 0.9) Mean 0.07072 0.13916 0.20761 0.46341 0.77189 1.08036 1.86500 3.09126 4.31753 Variance 0.07830 0.15151 0.21535 0.87540 1.49050 1.91528 14.5526 27.2993 37.0385 Skewness 4.34336 3.03405 2.34709 3.05341 2.39579 1.98291 4.55818 3.60665 3.07481 Kurtosis 26.2771 15.3736 11.2771 23.3821 20.0279 20.3337 47.7409 35.8777 32.8224 FDI 1.10723 1.08872 1.03728 1.88904 1.93099 1.77282 7.80303 8.83112 8.57865 Fig. 3 The Var(Z)-E(Z) plots for TRT-DBH distribution with different combinations of parameters (λ,γ) Formulation of the INAR(1) Model with TRT-DBH Innovation The purpose of this section is to introduce an INAR(1) time series model based on the TRT-DBH distribution. First, we review the definition of the GNB thinning operator defined by Shamma et al. (2020), and then, an INAR(1) model with TRT-DBH innovation is constructed. Definition 1 (Shamma et al. 2020) Consider a sequence of independent identically distributed (iid) geometric random variables {Vi}i∈N with parameter θ1+θ and Bernoulli random variable W with parameter αθ, 0≤α≤θ≤1, where Vi and W are independent for all i∈N. Define a sequence of dependent random variables {Ui}i∈N as Ui=ViW,i∈N. It can be verified Ui has a mixture distribution as follows2 P(Ui=u)=1-α1+θu=0(αθ)θu(1+θ)u+1u=1,2,…, denoted as zero inflated geometric distribution (ZIG(1-αθ,θ1+θ)). Also,E(Ui)=α,Var(Ui)=α(2θ-α+1),Cov(Ui,Uj)=α(θ-α),i≠j. The random variable ∑i=1nUi is a mixture of zero and negative binomial (n,θ1+θ) distributed random variables with proportions 1-αθ and αθ, respectively, and the zero inflated negative binomial distribution is the name given to it. Definition 2 (GNB thinning operator) Let X be a non-negative integer valued random variable and Ui,i∈N as noted above by (2). The operator “α∗θ”,0≤α≤θ≤1, defined as α∗θXt-1=∑i=1Xt-1Ui,t is called the GNB thinning operator. Shamma et al. (2020) outlined the properties of the GNB thinning operator The Proposed INAR(1) Model The following recursive equation introduces the proposed stationary INAR(1) process {Xt} as3 Xt=α∗θXt-1+Zt,α<θ<1,t≥1, where “∗θ” is the GNB thinning operator, {Zt} be a sequence of TRT-DBH random variables with parameters (λ,γ) and given Xt-1, the random variables α∗θXt-1 and Zt are independent of each other. We shall refer to this model as TRBH-INAR(1). The one-step transition probabilities areP0j=PXt=j|Xt-1=0=P(Zt=j), and for i≥1, we get4 Pij=PXt=j|Xt-1=i=(1-αθ)P(Zt=j)+αθ∑k=0ji-1i+k-1θk(1+θ)i+kP(Zt=j-k), whereP(Zt=j)=λj[1j+1-λj+2-γ(1j+1ln(λjj+1)-λj+2ln(λj+1j+2))]. This model may be fitted to infectious illness data and can be used to describe the disease’s transmission as follows: In the case of the INAR(1) model, if Xt-1 represents the number of new patients throughout the time span (t-2,t-1], α∗θXt-1 will be the number of surviving patients from the previous month, which may stimulate new patients or likely cure, and {Zt} will be the number of new patients infected in the current period. Remark 1 Shamma et al. (2020) provided several properties of the GNB thinning operator as follows (i) Eα∗θX∣X=αX, (ii) Varα∗θX∣X=α(θ-α)X+α(θ+1)X, (iii) Eα∗θX=αE(X), (iv) Eα∗θX=α(θ-α)E2(X)+α(θ+1)E(X)+αθVar(X). The expectation and variance of the process {Xt} is obtained asE(X)=μZ1-α,Var(X)=αμZ(1+θ)(1-α)(1-αθ)+α(θ-α)μZ2(1-α)2(1-αθ)+σZ21-αθ, where μZ and σZ2 are the mean and variance of TRT-DBH distribution, respectively. Proposition 1 The Fisher dispersion index of {Xt} is obtained asIX=Var(X)E(X)=α(θ-α)μZ2+α(θ+1)(1-α)μZ+(1-α)2σZ2(1-αθ)(1-α)μZ. This readily demonstrates that IX is more than one and obviously is over-dispersed. Proof In order to confirm IZX≥1, it is required to show Var(X)-E(X)≥0. Hence, we show the following inequality always holdsα(θ-α)μZ2+(1-α)(2αθ-1+α)μZ+(1-α)2σZ2≥0, which can be rewritten asα(θ-α)μZ2+(1-α)2(σZ2-μZ)+2αθ(1-α)μZ≥0. Since the TRT-DBH model is over-dispersed or equi-dispersed, so IZ>1 (i.e., σZ2-μZ≥0), and the proof is concluded. □ Proposition 2 Suppose {Xt} is a stationary process defined by (3), then for α<θ<1 and t≥1, (i) The conditional expectation is 5 EXt∣Xt-k=αkXt-k+1-αk1-αμZ. When k→∞, then limk→∞EXt∣Xt-k=μZ1-α, which is the process’s unconditional expectation. (ii) The conditional variance is 6 Var(Xt∣Xt-1)=α(θ-α)Xt-12+α(θ+1)Xt-1+σZ2, and VarXt∣Xt-k=αkθk-αkXt-k2+αk(1+θ)(1-θk)1-θXt-k+2μZαk(1-θk1-θ-1-αk1-α)Xt-k+αμZ(1+θ)1-θ(1-αk-11-α-θ(1-(αθ)k-1)1-αθ)+μZ2(1-(αθ)k-11-αθ-1-α2k-21-α2)+2αμZ2[θ1-θ(α(1-αk-1)1-α-αθ(1-(αθ)k-1)1-αθ)-α1-α(α(1-αk-1)1-α-αθ(1-α2k-2)1-α2)]+σZ21-(αθ)k1-αθ. hence, limk→∞VarXt∣Xt-k=αμZ(1+θ)(1-α)(1-αθ)+α(θ-α)μZ2(1-α)2(1-αθ)+σZ21-αθ, which is the process’s unconditional variance. (iii) The autocorrelation function of the process Xt is represented as ρ(k)=Corr(Xt,Xt-k)=αk. Proof See Appendix A. □ Different Estimation Method The conditional maximum likelihood, modified conditional least square, modified maximum empirical likelihood, and Yule–Walker estimation procedures for the parameters of the TRBH-INAR(1) model are discussed in this section. Conditional Maximum Likelihood Estimation The log-likelihood function is maximized in terms of the model parameters δ= (α,θ,λ,γ) in order to produce conditional maximum likelihood (CML) estimators. The log-likelihood function for sample observation X1,…,Xn from the TRBH-INAR(1) model can be written asℓδ=logLδ∣X2,…,Xn=∑t=2nlogPXt=j∣Xt-1=i, where PXt=j∣Xt-1=i is transition probability given by (4). The CML estimator of the unknown parameters are numerically obtained by maximizing the log-likelihood function with commands “nlm” or “optim” from statistical package “R”. Modified Conditional Least Square Estimation The modified conditional least squares (MCLS) estimators of the parameters α,μZ are found by minimizing the expression below7 Q(α,μZ)=∑t=2nXt-E(Xt∣Xt-1)2=∑t=2nXt-αXt-1-μZ2, where μZ is a function of the parameters (λ,γ). The estimators are given byα^MCLS=(n-1)∑t=2nXtXt-1-∑t=2nXt∑t=2nXt-1(n-1)∑t=2nXt-12-(∑t=2nXt-1)2, andμ^Z,MCLS=∑t=2nXt-α^MCLS∑t=2nXt-1n-1. It is worth mention that the MCLS estimation of parameters (λ,γ) is obtained by finding the root of the equation (1) equal to the estimation of the μ^Z,MCLS. The one-step conditional expectation of the process depends only on the parameters α and μZ and is not possible to use it for the estimation of the parameter θ. Hence, the parameter θ can be estimated under the modified method proposed by Karlsen and Tjøstheim (1988). The parameter θ can be estimated by minimizing the following expression8 T(θ)=∑t=2nVt-Var(Xt|Xt-1)2, whereVt=(Xt-E(Xt|Xt-1))2=Xt-α^MCLSXt-1-μ^Z,MCLS2, and Var(Xt|Xt-1) is defined in (6) with estimated values of the parameters (α,λ,γ) as belowVar(Xt∣Xt-1)=α^MCLS(θ-α^MCLS)Xt-12+α^MCLS(θ+1)Xt-1+σ^Z,MCLS2, where σZ2 is a function of the parameters (λ,γ) and can be estimated easily by (λ^MCLS,γ^MCLS). Modified Maximum Empirical Likelihood Estimation The nonparametric modified empirical likelihood (MEL) technique for the TRBH-INAR(1) model is discussed in this section, which comprises two phases. In the first step, we obtain the maximum MEL estimators for the parameters α and μZ as follows. By taking the derivative of Q(α,μZ) defined in (7) with respect to β=(α,μZ), we have the estimating equation-12∂Q(β)∂β=∑t=2nmt(β)=0, where mt(β)=(m1,t(β),m2,t(β))′ with m1,t(β)=Xt-1(Xt-αXt-1-μZ), m2,t(β)=Xt-αXt-1-μZ. Following Qin and Lawless (1994), we can define the log MEL function asLME(β)=∑t=1nlog(1+d′(β)mt(β)), where d(β) satisfies1n∑t=1nmt(β)1+d′(β)mt(β)=0. The maximum MEL estimator (MMELE) for the parameter β is defined by minimizing the above equation, i.e.,β^mmel=argminβLME(β). The MMEL estimation of the parameters (λ,γ) can be easily obtained based on the μ^Z,mmel and finding the root of the Eq. (1). The maximum MEL estimator for the parameter θ is obtained in the second phase. By considering the function T(θ) which is defined in (8), we have-12∂T(θ)∂θ=∑t=2nmt(θ), where mt(θ)=α^mmelXt-1(Xt-1+1)[Vt-α^mmel(θ-α^mmel)Xt-12-α^mmel(θ+1)Xt-1-σ^Z,mmel2], and Vt=Xt-α^mmelXt-1-μ^Z,mmel2. The MMELE for the parameter θ will be obtained by minimizing log MEL function. Yule–Walker Estimation The Yule–Walker (YW) estimators of the unknown vector δ are obtained as follows. Using the fact that E(Xt)=μZ1-α and Corr(Xt,Xt-1)=α, the YW estimations of the parameters (α,μZ) are generated using the sample mean and sample autocorrelation function as follows:α^YW=∑t=2n(Xt-X¯)(Xt-1-X¯)∑t=1n(Xt-X¯)2,μ^Z,YW=X¯(1-α^YW). Similarly, the YW estimation of the parameters (λ,γ) is performed using the μ^Z,mmel, and finding the equation’s root (1). We utilize the second moment of the procedure to estimate the parameter θ as follows:E(Xt2)=αθE(Xt2)+α(1+θ)E(Xt)+E(Zt2)+2αμZE(Xt)=α(1+θ)1-αθE(Xt)+E(Zt2)1-αθ+2αμZE(Xt)1-αθ, which is obtained based on Remark 1. Let X2¯=1n∑t=1nXt2, then9 X2¯=α^YW(1+θ)1-α^YWθX¯+μ^Z,YW2+σ^Z,YW1-α^YWθ+2α^YWμ^Z,YWX¯1-α^YWθ, as a result, estimate of the parameter θ is determined by computing the root of the Eq. (9) numerically. Simulation Approach We examine the efficiency of the parameter estimate approaches for the TRBH-INAR(1) model using Monte Carlo simulation, under different sample sizes n=(100,200,500,1000) over h=1000 iterations. Two distinct parameter combinations are evaluated as α,θ,λ=0.4,0.8,0.7,0.3 and 0.2,0.4,0.9,0.6. We use the mean squared error (MSE) metric to assess the estimators’ performance. The results are summarized in Tables 2 and 3, where represent that all estimates of the parameters are convergent to their actual values. Furthermore, when the sample size grows larger, the MSE decreases. Among different kinds of estimation methods, the CML and MMEL provide better performance than MCLs and YW estimations, since they have small MSE for all parameters. In comparison among the CML and MMEL methods, we provide the computer running time (R.time), which indicates that the MMEL method is faster than CML and as well as CML in MSE measure. As a result, the nonparametric MMEL technique outperforms other methods of estimation.Table 2 Results of simulations of the TRBH-INAR(1) model’s parameter estimations n CML MMEL α^ θ^ λ^ γ^ R.Time α^ θ^ λ^ γ^ R.Time α,θ,λ,γ=0.4,0.8,0.7,0.3    100 0.43075 0.81661 0.76381 0.28297 134.69 0.41534 0.77461 0.69378 0.31683 97.01    MSE (0.01358) (0.03378) (0.00858) (0.00355) (0.01301) (0.03197) (0.00928) (0.00232)    200 0.42209 0.82608 0.74652 0.31603 311.03 0.41129 0.78035 0.70572 0.31138 153.86    MSE (0.00874) (0.01564) (0.00618) (0.00309) (0.00975) (0.01652) (0.00839) (0.00187)    500 0.42182 0.81377 0.72775 0.30616 857.82 0.41028 0.81293 0.70374 0.30929 493.41    MSE (0.00312) (0.00602) (0.00509) (0.00219) (0.00428) (0.00943) (0.00625) (0.00138)    1000 0.41721 0.80927 0.70715 0.30123 2115.21 0.41112 0.79797 0.69651 0.30199 652.44    MSE (0.00218) (0.00259) (0.00477) (0.00166) (0.00235) (0.00479) (0.00439) (0.00104) α,θ,λ,γ=0.2,0.4,0.9,0.6    100 0.23824 0.45879 0.89641 0.61591 112.15 0.23941 0.36262 0.94042 0.63544 65.74    MSE (0.00799) (0.03091) (0.00082) (0.03401) (0.00952) (0.04456) (0.00398) (0.04425)    200 0.22906 0.44981 0.89978 0.60062 266.47 0.25133 0.37088 0.93545 0.62737 124.34    MSE (0.00527) (0.01183) (0.00036) (0.02152) (0.00553) (0.03457) (0.00259) (0.01327)    500 0.22899 0.43896 0.90223 0.59378 763.11 0.22391 0.42868 0.92714 0.62215 460.02    MSE (0.00356) (0.00559) (0.00014) (0.01337) (0.00526) (0.01953) (0.00189) (0.00761)    1000 0.21661 0.41588 0.90277 0.60904 1932.19 0.21868 0.41706 0.91664 0.61247 557.86    MSE (0.00275) (0.00354) (0.00071) (0.01015) (0.00331) (0.01366) (0.00092) (0.00285) Table 3 Results of simulations of the TRBH-INAR(1) model’s parameter estimations n MCLS YW α^ θ^ λ^ γ^ R.Time α^ θ^ λ^ γ^ R.Time α,θ,λ,γ=0.4,0.8,0.7,0.3    100 0.34643 0.76204 0.80737 0.30327 273.25 0.38488 0.76703 0.78856 0.28814 60.14    MSE (0.02229) (0.37431) (0.01459) (0.00854) (0.01532) (0.28766) (0.01158) (0.00813)    200 0.36568 0.78433 0.75426 0.29853 420.77 0.39773 0.76522 0.77414 0.29876 102.7    MSE (0.012535) (0.10733) (0.01279) (0.00822) (0.00978) (0.01932) (0.01058) (0.00769)    500 0.38148 0.78581 0.72288 0.29787 847.28 0.39588 0.79944 0.75931 0.29683 199.61    MSE (0.00591) (0.03619) (0.01158) (0.00726) (0.00441) (0.01024) (0.01088) (0.00621)    1000 0.39085 0.79011 0.71332 0.295236 1324.41 0.39865 0.80364 0.75087 0.29504 258.23    MSE (0.00299) (0.01821) (0.01136) (0.00602) (0.00379) (0.00823) (0.01009) (0.00589) α,θ,λ,γ=0.2,0.4,0.9,0.6    100 0.26071 0.32083 0.91666 0.63862 218.46 0.23588 0.36791 0.91948 0.56604 56.23    MSE (0.01159) (0.05267) (0.00919) (0.06116) (0.01272) (0.06227) (0.00721) (0.07331)    200 0.24713 0.34577 0.91059 0.62406 387.89 0.21343 0.44966 0.92816 0.55631 94.93    MSE (0.00761) (0.05147) (0.00825) (0.06111) (0.00628) (0.05396) (0.00606) (0.06303)    500 0.22984 0.35921 0.91424 0.62141 756.62 0.20261 0.43879 0.91098 0.54532 128.81    MSE (0.00685) (0.05224) (0.00717) (0.05103) (0.00587) (0.03977) (0.00402) (0.06297)    1000 0.20334 0.36305 0.92775 0.59396 1251.96 0.19814 0.43378 0.93276 0.53304 160.28    MSE (0.00649) (0.04271) (0.00623) (0.04092) (0.00558) (0.02375) (0.00294) (0.04302) Application of Real-World Data In this section, we investigate the application of the TRBH-INAR(1) process by using two types of clinical count data. The first data set is devoted to daily counts of death from the COVID-19 disease, reported from Netherland and consists of 46 observations, from second July until 16-th August at 2021, by the World Health Organization (https://covid19.who.int). The second data set represents the weekly counts of Tularemia disease, reported from Bavaria, and it consists of 48 observations, from first week until 48-th week on 2020, from the Robert Koch Institute: SurvStat@RKI 2.0 (https://survstat.rki.de) site.Fig. 4 The sample path, ACF and PACF of both data sets Figure 4 depicts the sample path, autocorrelation function (ACF), and partial autocorrelation function (PACF) of the two data series, indicating that the data sets should be modeled using a first-order autoregressive model. Furthermore, the augmented Dickey–Fuller test is used to justify stationarity of the two clinical data sets, where the p-value of augmented Dickey–Fuller test for COVID-19 data is less than 0.01 and for Tularemia data is equal 0.022, which confirm the stationarity of both data sets. The mean, variance and autocorrelation of the two data sets are (3.565, 7.717, 0.557) and (2.125, 5.047, 0.310), respectively. Both data series are empirically over-dispersed with dispersion indices I^X=(2.164,2.375), respectively. We compare the TRBH-INAR(1) model to some competitive INAR(1) models as: PINAR(1) (Al-Osh and Alzaid 1987), GINAR(1) (Alzaid and Al-Osh 1988), NBIINAR(1) (Al-Osh and Aly 1992), GPQINAR(1) (Alzaid and Al-Osh 1993), NBRCINAR(1) (Weiß 2008), NGINAR(1) (Ristić et al. 2009), DCGINAR(1) (Ristić et al. 2013), NDCINAR(1) (Miletić Ilić 2016), ρ-NGINAR(1) (Borges et al. 2017), GADCINAR(1) (Nastić et al. 2017) and GNBINAR(1) (Shamma et al. 2020). We reported the CML estimates, the information criterion (IC) statistics as AIC, BIC, HQIC and CAIC, and the root mean squares of differences of observations and predicted values (RMS) for each INAR model. Tables 4 and 5 show the results for two different data series. Regarding Tables 4 and 5, the values of the IC and RMS are the smallest for the TRBH-INAR(1) model. Therefore, we can conclude that the TRBH-INAR(1) model provides the best loss information among other competitive INAR(1) models.Table 4 The CML estimates and some IC measures of COVID-19 data Model CML AIC BIC HQIC CAIC RMS PINAR(1) λ^=2.13186,α^=0.40172 211.27 214.92 212.64 213.84 2.34 GINAR(1) p^=0.73919,α^=0.35818 218.04 221.69 219.41 220.61 2.41 NGINAR(1) p^=4.16264,α^=0.95784 204.74 208.41 206.11 207.31 2.55 NBRCINAR(1) n^=3.60698,p^=0.50657,ρ^=0.47929 203.32 208.81 205.38 206.29 2.32 NBIINAR(1) n^=3.07621,p^=1.86301,ρ^=0.53645 201.83 207.32 203.89 204.81 2.31 GPQINAR(1) λ^=1.43165,θ^=0.25134,ρ^=0.4607 204.38 209.86 206.43 207.35 2.48 NDCINAR(1) α^=0.34853,θ^=0.99957,μ^=3.70577 213.90 219.38 215.95 214.47 2.38 ρ-NGINAR(1) α^=0.68822,ρ^=3.73767,μ^=0.29627 200.14 205.62 202.19 200.71 2.58 DCGINAR(1) α^=0.51582,θ^=0.66611,μ^=3.10469 210.16 215.65 212.22 210.73 2.32 GADCINAR(1) α^=0.44552,θ^=0.80996,μ^=3.56932 207.75 213.24 209.81 208.32 2.33 GNBINAR(1) α^=0.92765,θ^=0.96184,μ^=3.98312 201.61 207.09 203.66 202.17 2.52 TRBH-INAR(1) α^=0.58847,θ^=0.80592,λ^=0.66448, 196.94 204.26 199.68 200.44 2.27 γ^=0.53178 Table 5 The CML estimates and some IC measures of Tularemia data Model CML AIC BIC HQIC CAIC RMS PINAR(1) λ^=1.54083,α^=0.27962 195.36 199.11 196.78 197.91 2.13 GINAR(1) p^=0.64816,α^=0.34085 184.05 187.80 185.47 186.60 2.14 NGINAR(1) p^=2.15417,α^=0.54857 180.33 184.07 181.75 182.88 2.18 NBRCINAR(1) n^=2.42637,p^=0.52029,ρ^=0.38773 183.13 188.74 185.25 186.06 2.13 NBIINAR(1) n^=1.84523,p^=1.60513,ρ^=0.46674 181.54 187.15 183.66 184.47 2.15 GPQINAR(1) λ^=1.07131,θ^=0.26666,ρ^=0.35176 183.52 189.14 185.65 186.46 2.18 NDCINAR(1) α^=0.77226,θ^=0.99999,μ^=13.75551 237.51 243.12 239.63 238.05 3.48 ρ-NGINAR(1) α^=1.19804,ρ^=8659.928,μ^=0.31496 177.04 182.65 179.16 177.58 4.41 DCGINAR(1) α^=0.62351,θ^=0.53917,μ^=2.10281 178.49 184.11 180.61 179.04 2.23 GADCINAR(1) α^=0.37802,θ^=0.39667,μ^=1.93569 185.42 191.03 187.54 185.96 2.14 GNBINAR(1) α^=0.34240,θ^=0.41512,μ^=2.04136 182.49 188.11 184.61 183.04 2.13 TRBH-INAR(1) α^=0.33436,θ^=0.48157,λ^=0.58878 173.45 180.94 176.28 176.88 2.08 γ^=0.79411 The Clinical Data Sets’ Residual Analysis We provide the results of a residual analysis of clinical data sets, which confirmed the suitability of the proposed model. The Pearson residuals are defined aset=Xt-E(Xt∣Xt-1)Var(Xt∣Xt-1), where E(Xt∣Xt-1) and Var(Xt∣Xt-1) are defined in (5) and (6), respectively. Note that, estimation of the parameters of the TRBH-INAR(1) model are substituted in each E(Xt∣Xt-1) and Var(Xt∣Xt-1) to compute the Pearson residuals. The Pearson residuals ACF of both data sets is shown in Fig. 5. The residuals are non-correlated, as shown in Fig. 5, and the results are supported by the Ljung-Box test p-values (0.679, 0.935). Figure 6 shows the Pearson residuals cumulative periodogram, which shows how residuals are distributed randomly and without trend. Figure 7 shows the result of the parametric re-sampling method. First, 5000 data sets with bootstrap sample size n=(46,48) are obtained using the fitted TRBH-INAR(1) model (with CML estimates of the parameters of each data set). Second, using the bootstrap samples, the ACF of each specific lag is calculated. The acceptance bounds 100(0.975)% and 100(0.025)% quantiles are shown as “+”, and the samples ACF are presented by “∙” symbols, in Fig. 7. According to Fig. 7, all of the sample autocorrelations were assigned between the acceptance boundaries, indicating that the model was adequate.Fig. 5 The Pearson residuals ACF for the two data sets Fig. 6 The Pearson residuals cumulative periodogram for the two data sets Fig. 7 The acceptance areas and the bootstrap ACF Methods of Forecasting To test the TRBH-INAR(1) model’s appropriateness and predictability, we present forecasts of the specified data sets using both the traditional and modified Sieve bootstrap approaches. The k-step ahead classical predictor of the TRBH-INAR(1) model is represented asX^t=EXt∣Xt-k=αkXt-k+1-αk1-αμZ, where unknown parameters α and μZ are substituted by the related CML estimates. Modified Sieve Bootstrap Approach The integer nature of the count data is not preserved by the classical predictor, despite the fact that the count time series is an integer. The Sieve bootstrap technique is a distribution-free predictor that preserves the integer nature of the count data. Hence, we modified the bootstrap approach proposed by Pascual et al. (2004) to apply for the TRBH-INAR(1) model via the following steps. Since α∗θα∗θX≠dα2∗θX, we can only provide the one-step modified Sieve bootstrap prediction. The thinning parameters (α,θ) are estimated based on the YW estimation approach. Compute residuals Z^t=Xt-α^Xt-1, for t=2,...,n. The empirical distribution of the modified residuals Z~t is provided, where Z~t=Z^t, and [·] shows the nearest integer value. The bootstrap series Xtb is given by Xtb=α^∗θ^Xt-1b+Ztb,b=1,…,B, where B is the bootstrap sample size that was chosen to be B=500, and Ztb is generated from the empirical distribution in step 3, for t=1,2,...,n. The YW estimation of the parameters (α^YW,θ^YW) is obtained by inserting the sample mean, variance, and solving the following equations EXt(1-α)=EZtVar(Xt)=α(θ-α)μZ2(1-α)2(1-αθ)+α(θ+1)μZ(1-α)(1-αθ)+σZ21-αθ. Based on the sample means α^=1B∑i=1Bα^i,YW and θ^=1B∑i=1Bθ^i,YW, the parameters α,θ are estimated. The recursion method is used to acquire future bootstrap observations by the expression X^t+1b=α^∗θ^Xtb+Zt+1b. The traditional and modified Sieve bootstrap predictions of the relevant data series, for which we know the observed values, are provided in Table 6 as a result of evaluating two prediction approaches. When there are zero or near-zero data demands, the symmetric mean absolute percent error (SMAPE) is applied to compare the forecast systems. The less SMAPE value leads to a better forecasting scheme. According to Table 6, the modified Sieve bootstrap predictors’ SMAPE values are lower than classical, and the modified Sieve bootstrap predictors are integers, which are consistent with the nature of actual data.Table 6 The k-step ahead predictions of clinical data series k COVID-19 Tularemia Actual data Bootstrap Classical Actual data Bootstrap Classical 1 8 10 7.75761 1 1 2.28751 2 9 10 5.99219 2 2 1.61879 3 2 0 6.58066 3 1 1.95315 4 2 2 2.46137 2 1 2.28751 5 7 7 2.46137 3 7 1.95315 6 9 7 5.40372 2 1 2.28751 7 7 6 6.58066 12 13 1.95315 8 6 4 5.40372 3 2 5.29675 9 6 5 4.81525 4 4 2.28751 10 3 3 4.81525 5 3 2.62187 SMAPE 0.33131 0.43131 0.41133 0.52701 Conclusions We provide a first-order integer-valued autoregressive [INAR(1)] time series model based on the transmuted record type-discrete Burr–Hatke (TRT-DBH) distribution, which is a more flexible version of the discrete Burr–Hatke distribution. The TRT-DBH distribution is proved to over-dispersed, asymmetric and leptokurtic. The hazard rate function of the proposed distribution has different shapes as monotone and unimodal. The applicability of the TRT-DBH distribution is demonstrated in time series modeling based on an INAR(1) model with TRT-DBH distributed innovations. Properties of the model are studied as well as different estimation approaches for the model parameters. The assessment of the properties and estimation approaches is conducted via some simulation studies. The adequacy of fit of the proposed INAR(1) model is checked via two clinical data sets, including the Covid-19 series and is compared with other competitive models. For both clinical data sets, we perform the residual analysis (Pearson residuals), as well as traditional and modified Sieve bootstrap forecasting methods. Appendix A: The Proof of Proposition 2 (i) The model’s conditional expectation is calculated as follows: E(Xt∣Xt-1)=αXt-1+μZ,E(Xt∣Xt-2)=E(E(Xt∣Xt-1)∣Xt-2)=α2Xt-2+(1+α)μZ. So, it is induced via the induction that E(Xt∣Xt-k)=αkXt-k+(1-αk)μZ1-α, which is a linear function of Xt. (ii) Based on Remark 1, the conditional variance of the TRBH-INAR(1) process is computed as VarXt∣Xt-1=Varα∗θXt-1∣Xt-1+Var(Zt)=α(θ-α)Xt-12+α(θ+1)Xt-1+σZ2, and VarXt∣Xt-2=EVarXt∣Xt-1∣Xt-2+VarEXt∣Xt-1∣Xt-2=α(θ-α)E(Xt-12∣Xt-2)+α(θ+1)E(Xt-1∣Xt-2)+σZ2+α2VarXt-1∣Xt-2=αθVarXt-1∣Xt-2+α(θ-α)E2(Xt-1∣Xt-2)+α(θ+1)E(Xt-1∣Xt-2)+σZ2=α2(θ2-α2)Xt-22+α2(θ+1)2Xt-2+2α2(θ-α)μZXt-2+α(θ+1)μZ+α(θ-α)μZ2+(1+αθ)σZ2, subsequently VarXt∣Xt-3=α3(θ3-α3)Xt-32+α3(θ+1)(1+θ+θ2)Xt-3+2α3((θ-α)+(θ2-α2))μZXt-3+α(θ+1)(1+α(1+θ))μZ+[α(θ-α)+α2(θ2-α2)]μZ2+2α2(θ-α)μZ2+(1+αθ+α2θ2)σZ2. By induction, we can conclude that Var(Xt∣Xt-k)=αkθk-αkXt-k2+αk(1+θ)∑i=0k-1θiXt-k+2μZαk∑i=0k-1(θi-αi)Xt-k+μZ(1+θ)∑i=1k-1αi∑j=0i-1θj+μZ2∑i=0k-1αi(θi-αi)+2αμZ2∑i=1k-1αi∑j=1i(θj-αj)+σZ2∑i=0k-1(αθ)i. After some elementary calculations, the proof is complete. (iii) The proof is unimportant and may be ignored. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Declarations Conflict of Interest The authors have no relevant financial or non-financial interests to disclose. ==== Refs References Al-Osh MA Aly EEAA First order autoregressive time series with negative binomial and geometric marginals Commun Stat-Theory Methods 1992 21 2483 2492 10.1080/03610929208830925 Al-Osh MA Alzaid AA First-order integer-valued autoregressive (INAR(1)) process J Time Ser Anal 1987 8 261 275 10.1111/j.1467-9892.1987.tb00438.x Altun E A new generalization of geometric distribution with properties and applications Commun Stat-Simul Comput 2020 49 3 793 807 10.1080/03610918.2019.1639739 Altun E Mamode Khan N Modelling with the Novel INAR(1)-PTE Process Methodol Comput Appl Probab 2021 10.1007/s11009-021-09878-2 Alzaid AA Al-Osh MA First-order integer-valued autoregressive (INAR(1)) process: distributional and regression properties Stat Neerl 1988 42 53 61 10.1111/j.1467-9574.1988.tb01521.x Alzaid AA Al-Osh MA Some autoregressive moving average processes with generalized Poisson marginal distributions Ann Inst Stat Math 1993 45 223 232 10.1007/BF00775809 Bahti D Bakouch HS A new infinitely divisible discrete distribution with applications to count data modeling Commun Stat-Theory Methods 2019 48 1401 1416 10.1080/03610926.2018.1433847 Bakouch HS Jazi AM Nadarajah S A new discrete distribution Statistics 2014 48 200 240 10.1080/02331888.2012.716677 Borges P Bourguignon M Molinares FF A generalized NGINAR(1) process with inflated parameter geometric counting series Aust N Z J Stat 2017 59 137 150 10.1111/anzs.12184 Bourguignon M Vasconcellos KLP First order non-negative integer valued autoregressive processes with power series innovations Braz J Probab Stat 2015 29 1 71 93 10.1214/13-BJPS229 Chakraborty S Chakravarty D Discrete gamma distribution: properties and parameter estimation Commun Stat-Theory Methods 2012 41 3301 3324 10.1080/03610926.2011.563014 Eliwa MS El-Morshedy M A one-parameter discrete distribution for over-dispersed data: statistical and reliability properties with applications J Appl Stat 2021 10.1080/02664763.2021.1905787 El-Morshedy M Eliwa MS Altun E Discrete Burr–Hatke distribution with properties, estimation methods and regression model IEEE Access 2020 8 74359 74370 10.1109/ACCESS.2020.2988431 Gómez-Déniz E Calderín-Ojeda E The discrete Lindley distribution: properties and applications J Stat Comput Simul 2011 81 11 1405 1416 10.1080/00949655.2010.487825 Huang J Zhu F A new first-order integer-valued autoregressive model with Bell innovations Entropy 2021 323 713 10.3390/e23060713 Hussain T Aslam M Ahmad M A two parameter discrete Lindley distribution Rev Colomb Estadíst 2016 39 1 45 61 10.15446/rce.v39n1.55138 Jazi MA Jones G Lai CD Integer valued AR(1) with geometric innovations J Iran Stat Soc 2012 11 173 190 Karlis D Xekalaki E Mixed Poisson distributions Int Stat Rev 2005 73 1 35 58 10.1111/j.1751-5823.2005.tb00250.x Karlsen H, Tjøstheim D (1988) Consistent estimates for the NEAR(2) and NLAR(2) time series models. J R Stat Soc. Ser B (Methodol), 50(2), 313–320 Kozubowski TJ Podgórski K Transmuted distributions and random extrema Stat Probab Lett 2016 116 6 8 10.1016/j.spl.2016.04.001 Liu Z Zhu F A new extension of thinning-based integer-valued autoregressive models for count data Entropy 2021 23 1 62 10.3390/e23010062 Lívio T Mamode Khan N Bourguignon M Bakouch SH An INAR(1) model with Poisson–Lindley innovations Econ Bull 2018 38 3 1505 1513 McKenzie E Autoregressive moving-average processes with negative binomial and geometric distributions Adv Appl Probab 1986 18 679 705 10.2307/1427183 McKenzie E Some ARMA models for dependent sequences of Poisson counts Adv Appl Probab 1988 20 822 835 10.2307/1427362 Miletić Ilić AV A geometric time series model with a new dependent Bernoulli counting series Commun Stat-Theory Methods 2016 45 6400 6415 10.1080/03610926.2014.895840 Nastić AS Ristić MM Miletić Ilić AV A geometric time series model with an alternative dependent Bernoulli counting series Commun Stat-Theory Methods 2017 46 2 770 785 10.1080/03610926.2015.1005100 Nekoukhou V Alamatsaz MH Bidram H Discrete generalized exponential distribution of a second type Statistics 2013 47 4 876 887 10.1080/02331888.2011.633707 Pascual L Romo J Ruiz E Bootstrap predictive inference for ARIMA processes J Time Ser Anal 2004 25 4 449 65 10.1111/j.1467-9892.2004.01713.x Qin J Lawless J Empirical likelihood and general estimating equations Ann Stat 1994 22 1 300 325 10.1214/aos/1176325370 Ristić MM Bakouch HS Nastić AS A new geometric first-order integer-valued autoregressive (NGINAR(1)) process J Stat Plan Inference 2009 139 2218 2226 10.1016/j.jspi.2008.10.007 Ristić MM Nastić SA Miletić Ilić VA A geometric time series model with dependent Bernoulli counting series J Time Ser Anal 2013 34 4 423 516 10.1111/jtsa.12023 Sellers KF Shmueli G A flexible regression model for count data Ann Appl Stat 2010 4 2 943 961 10.1214/09-AOAS306 Sellers KF Borle S Shmueli G The COM-Poisson model for count data: a survey of methods and applications Stat Qual, Ind Technol 2012 28 2 104 116 Shakil M Ahsanullah M Record values of the ratio of Rayleigh random variables Pak J Stat 2011 27 307 325 Shamma N Mohammadpour M Shirozhan M A time series model based on dependent zero inflated counting series Comput Stat 2020 35 1737 1757 10.1007/s00180-020-00982-4 Shirozhan M Mohammadpour M Bakouch HS A new geometric INAR(1) model with mixing Pegram and generalized binomial thinning operators Iran J Sci Technol, Trans A: Sci 2019 43 1011 1020 10.1007/s40995-017-0345-3 Shmueli G Minka TP Kadane JB Borle S Boatwright P A useful distribution for fitting discrete data: revival of the Conway–Maxwell–Poisson distribution J Appl Stat 2005 54 127 142 Steutel FW van Harn K Discrete analogues of self-decomposability and stability Ann Probab 1979 7 893 899 10.1214/aop/1176994950 Weiß CH Thinning operations for modeling time series of count—a survey AStA Adv Stat Anal 2008 92 319 341 10.1007/s10182-008-0072-3
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==== Front Jpn J Ophthalmol Jpn J Ophthalmol Japanese Journal of Ophthalmology 0021-5155 1613-2246 Springer Japan Tokyo 36508060 969 10.1007/s10384-022-00969-2 Clinical Investigation Recent trends in anti-vascular endothelial growth factor intravitreal injections: a large claims database study in Japan http://orcid.org/0000-0002-7944-6923 Hashimoto Yohei [email protected] 12 Okada Akira 3 Matsui Hiroki 1 Yasunaga Hideo 1 Aihara Makoto 2 Obata Ryo 2 1 grid.26999.3d 0000 0001 2151 536X Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033 Japan 2 grid.26999.3d 0000 0001 2151 536X Department of Ophthalmology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan 3 grid.26999.3d 0000 0001 2151 536X Department of Prevention of Diabetes and Lifestyle-Related Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan 12 12 2022 110 6 5 2022 20 10 2022 © Japanese Ophthalmological Society 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Purpose To clarify recent trends in the use of intravitreal injections of anti-vascular endothelial growth factor (VEGF) in Japan. Study design Retrospective cohort study. Methods We used the DeSC database, a large-scale claims database for Japan, for entries between April 2014 and March 2021. We counted the number of anti-VEGF drug injections (aflibercept, ranibizumab, brolucizumab, and pegaptanib) administered every year, calculated the sex- and age-adjusted injection rates, and stratified these rates according to sex, age categories, anti-VEGF drugs, and diagnoses. We also calculated the number of injections administered within one year after the first injection according to the diagnoses. Results In total, 164,451 cases of anti-VEGF injections were identified. The sex- and age-adjusted rates of anti-VEGF injections per 1000 person-years increased from 7.9 in 2014 to 16.1 in 2020. Men were approximately twice as likely to receive anti-VEGF injections than women. The 70–79, 80–89, and ≥90 age categories had the highest rates, accounting for approximately 80%. Neovascular age-related macular degeneration had the highest rate, accounting for 60–70% over the study period. Aflibercept was the most commonly used drug, accounting for approximately 80% over the study period. The average number of injections within one year after the first injection was 4.4 for neovascular age-related macular degeneration, 2.7 for branch retinal vein occlusion, 3.1 for central retinal vein occlusion, and 3.5 for diabetic macular edema in 2020. Conclusion These findings can be used as a benchmark for the clinical practice of anti-VEGF therapy. Supplementary Information The online version contains supplementary material available at 10.1007/s10384-022-00969-2. Keywords Anti-vascular endothelial growth factor Age-related macular degeneration Retinal vein occlusion Diabetic macular edema Myopic choroidal neovascularization http://dx.doi.org/10.13039/501100003478 Ministry of Health, Labour and Welfare 21AA2007 Yasunaga Hideo Ministry of Education, Culture, Sports, Science and Technology, Japan20H03907 Yasunaga Hideo ==== Body pmcIntroduction Many randomized controlled studies show that intravitreal injections of anti-vascular endothelial growth factors (VEGF) provide notable benefits for patients with neovascular age-related macular degeneration (nAMD) [1], branch retinal vein occlusion (BRVO) [2, 3], central retinal vein occlusion (CRVO) [2, 4], diabetic macular edema (DME) [5–8], myopic choroidal neovascularization (mCNV) [9, 10], neovascular glaucoma (NVG) [11], and retinopathy of prematurity (ROP) [12, 13]. Trends in the use of anti-VEGF are reported in various countries, the US [14, 15], the UK [16], and Italy [17]. A large claims’ database study was conducted in Japan [18], in which the age of the participants ranged from 21–75 years. Considering the aging population in Japan and the high prevalence of diseases such as nAMD and RVO in the elderly [19, 20], it is necessary to include all ages to understand the details of the trends. We aimed to investigate more recent trends (2014–2021) in the use of anti-VEGF medication in Japan by using a large claims database containing information regarding all ages. Subjects and methods Data source We used the DeSC database (DeSC Healthcare Inc.) for entries between April 2014 and March 2021. This database was developed in 2021 and comprises health insurance claims’ data from multiple types of health insurers: (1) health insurance for employees of large companies (Kempo), (2) the National Health Insurance for unemployed (Kokuho), and (3) the Advanced Elderly Medical Service System for elderly individuals aged ≥75 years (Koki Koreisha Iryo Seido). Thus, the DeSC database covers young, middle-aged, and elderly individuals. The individual-level data on outpatients and inpatients are anonymously stored. The information stored is as follows: (1) unique identifier; (2) age and sex; (3) diagnoses based on the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes; (4) procedures; (5) drugs dispensed based on the Anatomical Therapeutic Chemical Classification System; and (6) period from start to end of insurance. The DeSC database reportedly contains the information of 2,220,702 individuals, including 824,516 individuals from Kempo, 1,095,713 individuals from Kokuho, and 300,473 individuals from Koki Koreisha Iryo Seido, between December 2019 and November 2020 [21]. Contrastingly, the Ministry of Health, Labour and Welfare, Japan, report that 78 million, 27 million, and 18 million individuals were enrolled in Kempo, Kokuho, and Koki Koreisha Iryo Seido, respectively, as of March 2020 [22]. Therefore, the DeSC database has a higher proportion of individuals from Kokuho than from the entire population. This study was conducted in accordance with the tenets of the Declaration of Helsinki. This study was approved by the Institutional Review Board of the University of Tokyo. The requirement for informed consent was waived due to the anonymous nature of the database. Outcomes The number of anti-VEGF injections and patients receiving anti-VEGF injections We defined intravitreal anti-VEGF injections as the prescription of anti-VEGF drugs, such as aflibercept, ranibizumab, brolucizumab, and pegaptanib. The codes used to identify these drugs are shown in Online Resource 1. We counted the number of anti-VEGF injections stratified according to the fiscal year. The fiscal year is defined as the period from April to March (hereafter, the year refers to the fiscal year). If an individual received two or more injections in the same month, they were counted separately. We subsequently stratified the number of injections according to the sex, age category (≤39, 40–49, 50–59, 60–69, 70–79, 80–89, and ≥90 years), anti-VEGF drugs (aflibercept, ranibizumab, brolucizumab, and pegaptanib), and diagnoses (nAMD, BRVO, CRVO, DME, mCNV, NVG, ROP, multiple diagnoses, and unspecified). The diagnoses were identified based on the recorded diagnoses in the same year and month as the prescription of drugs. The codes used to identify these drugs are shown in Online Resource 2. The multiple diagnoses group included cases that had two or more diagnoses amongst nAMD, BRVO, CRVO, DME, mCNV, NVG, and ROP in the same year and month as the use of anti-VEGF drugs. The unspecified group was defined as cases that did not have any of the abovementioned diagnoses. The use of anti-VEGF drugs before or without approval was included. For example, we included cases in which only NVG was registered, and aflibercept was simultaneously administered before 2019. The approval timings for the anti-VEGF drugs are shown in Online resource 3. We also counted the number of unique patients receiving anti-VEGF injections in each fiscal year and stratified this number according to sex and age category. The rate of anti-VEGF injections The total number of injections depends on the number of beneficiaries enrolled in the DeSC database. Thus, we calculated the injection rates by year, using the number of injections as the numerator and the total person-years at risk for all the beneficiaries in the same year as the denominator. These rates were expressed as the number of injections per 1000 person-years, as in previous studies [15]. Furthermore, we stratified the injection rates according to sex, age category, anti-VEGF drugs, diagnoses, and drugs and diagnoses. We adjusted the rates by sex and age using the direct standardization method [20, 23], with reference to the population in the DeSC database in 2020. We also calculated the distribution of the age category stratified by diagnosis in 2020. The annual number of anti-VEGF injections after the first injections We investigated the number of anti-VEGF injections per person within one year after the first injection. First, we identified the date of the first injection for each patient. We only included patients with more than one year of observation period after the first injections. We then included patients who received anti-VEGF injections for a single diagnosis among the abovementioned diagnoses within one year after the first injections (Online Resource 4). We subsequently counted the number of anti-VEGF injections within one year after the first injection. We used the years and diagnoses of the first injection dates to stratify the number of injections. Finally, we standardized the number of injections per person within one year after the first injection with reference to the population who underwent anti-VEGF injections at least once in 2020. Comparison between the DeSC database and the whole population in Japan Lastly, we investigated the representativeness of the DeSC database. We compared the number of anti-VEGF injections in the current study with that in the NDB open data for 2019 [24]. We used the statistical programming language R (version 3.5.0) for data cleaning, making graphs, and calculating the standardized rates. Results In total, 164,451 anti-VEGF injections were administered between 2014 and 2020. The total number of injections increased from 2221 in 2014 to 60,229 in 2020, with an increase in the total person-years (the denominator of the injection rate) from 516,350 to 3,753,480 (Table 1). The number of patients receiving anti-VEGF injections increased from 947 in 2014 to 20,145 in 2020.Table 1 Person-years of the beneficiaries, the number of anti-VEGF injections, and the number of patients receiving anti-VEGF injections in the DeSC database and NDB open data. variable Fiscal year (from April to March) NDB open data (2019)a 2014 2015 2016 2017 2018 2019 2020 Total Person-years  Total 516350 (100) 1215966 (100) 1409297 (100) 1612964 (100) 3172481 (100) 3314128 (100) 3753480 (100) 14994666 (100) – Sex  Female 258970 (50) 595674 (49) 687324 (49) 787612 (49) 1712632 (54) 1794855 (54) 2051417 (55) 7888484 (53) –  Male 257381 (50) 620293 (51) 721973 (51) 825352 (51) 1459849 (46) 1519274 (46) 1702063 (45) 7106185 (47) Age category  ≤39 171291 (33) 448472 (37) 488450 (35) 534071 (33) 560030 (18) 539650 (16) 518390 (14) 3260354 (22) –  40–49 77493 (15) 196495 (16) 220168 (16) 239594 (15) 255765 (8) 253284 (8) 242238 (6) 1485037 (10) –  50–59 53218 (10) 156411 (13) 181014 (13) 213395 (13) 244496 (8) 253266 (8) 255047 (7) 1356847 (9) –  60-69 49604 (10) 248055 (20) 329623 (23) 372224 (23) 443126 (14) 423432 (13) 391591 (10) 2257655 (15) –  70–79 58949 (11) 57316 (5) 78365 (6) 138801 (9) 775907 (24) 895404 (27) 1100742 (29) 3105484 (21) –  80–89 85446 (17) 87481 (7) 88432 (6) 90277 (6) 723919 (23) 761754 (23) 990885 (26) 2828194 (19) –  ≥90 20348 (4) 21737 (2) 23246 (2) 24602 (2) 169238 (5) 187339 (6) 254588 (7) 701098 (5) – Injections  Total 2221 (100) 3822 (100) 4880 (100) 6832 (100) 40389 (100) 46078 (100) 60229 (100) 164451 (100) 735060 (100) Sex  Female 787 (35) 1472 (39) 1964 (40) 2763 (40) 16876 (42) 19552 (42) 24824 (41) 68238 (41) 294306 (40)  Male 1434 (65) 2350 (61) 2916 (60) 4069 (60) 23513 (58) 26526 (58) 35405 (59) 96213 (59) 429590 (58) Age category  ≤39 7 (0) 12 (0) 35 (1) 55 (1) 41 (0) 64 (0) 82 (0) 296 (0) 2374 (0)  40–49 17 (1) 86 (2) 111 (2) 177 (3) 196 (0) 236 (1) 281 (0) 1104 (1) 16006 (2)  50–59 71 (3) 239 (6) 387 (8) 490 (7) 646 (2) 755 (2) 768 (1) 3356 (2) 46625 (6)  60–69 220 (10) 1183 (31) 1692 (35) 2344 (34) 3289 (8) 3344 (7) 3372 (6) 15444 (9) 127609 (17)  70–79 657 (30) 801 (21) 1097 (22) 1932 (28) 14699 (36) 17691 (38) 23189 (39) 60066 (37) 289077 (39)  80–89 1106 (50) 1275 (33) 1337 (27) 1579 (23) 18510 (46) 20533 (45) 28026 (47) 72366 (44) 210813 (29)  ≥90 143 (6) 226 (6) 221 (5) 255 (4) 3008 (7) 3455 (7) 4511 (7) 11819 (7) 31392 (4) Drug  Aflibercept 1476 (66) 2846 (74) 3922 (80) 5323 (78) 31161 (77) 35716 (78) 46504 (77) 126948 (77) 551378 (75)  Ranibizumab 735 (33) 952 (25) 946 (19) 1503 (22) 9160 (23) 10339 (22) 12128 (20) 35763 (22) 183682 (25)  Brolicizumab – – – – – – 1597 (3) 1597 (1) –  Pegaptanib 10 (0) 24 (1) 12 (0) 6 (0) 68 (0) 23 (0) 0 (0) 143 (0) – Diagnosis  Age-related macular degeneration 1453 (65) 2117 (55) 2550 (52) 3276 (48) 24991 (62) 27914 (61) 36496 (61) 98797 (60) –  Branch retinal vein occlusion 270 (12) 579 (15) 768 (16) 1150 (17) 5006 (12) 5986 (13) 7384 (12) 21143 (13) –  Central retinal vein occlusion 153 (7) 267 (7) 355 (7) 501 (7) 2378 (6) 2593 (6) 3550 (6) 9797 (6) –  Diabetic macular edema 66 (3) 217 (6) 401 (8) 714 (10) 2264 (6) 2728 (6) 3859 (6) 10249 (6) –  Myopic choroidal neovascularization 14 (1) 26 (1) 45 (1) 58 (1) 289 (1) 289 (1) 348 (1) 1069 (1) –  Neovascular glaucoma 3 (0) 26 (1) 37 (1) 37 (1) 41 (0) 40 (0) 159 (0) 343 (0) –  Retinopathy of prematurity – – – – – 1 (0) 2 (0) 3 (0) –  Multiple diagnoses 181 (8) 319 (8) 389 (8) 592 (9) 3688 (9) 4447 (10) 6108 (10) 15724 (10) –  Unspecified 81 (4) 271 (7) 335 (7) 504 (7) 1732 (4) 2080 (5) 2323 (4) 7326 (4) – Patients receiving injections  Total 947 (100) 1572 (100) 2020 (100) 2651 (100) 14166 (100) 15884 (100) 20145 (100) 57385 (100) – Sex  Female 378 (40) 648 (41) 857 (42) 1136 (43) 6266 (44) 7065 (44) 8728 (43) 25078 (44) –  Male 569 (60) 924 (59) 1163 (58) 1515 (57) 7900 (56) 8819 (56) 11417 (57) 32307 (56) – Age category  ≤39 5 (1) 8 (1) 20 (1) 26 (1) 21 (0) 30 (0) 40 (0) 150 (0) –  40–49 7 (1) 37 (2) 49 (2) 73 (3) 86 (1) 97 (1) 102 (1) 451 (1) –  50–59 26 (3) 108 (7) 147 (7) 201 (8) 260 (2) 298 (2) 292 (1) 1332 (2) –  60–69 101 (11) 460 (29) 689 (34) 879 (33) 1224 (9) 1194 (8) 1178 (6) 5725 (10) –  70–79 282 (30) 336 (21) 467 (23) 733 (28) 5245 (37) 6117 (39) 7715 (38) 20895 (36) –  80–89 470 (50) 538 (34) 553 (27) 640 (24) 6298 (44) 6943 (44) 9266 (46) 24708 (43) –  ≥90 56 (6) 85 (5) 95 (5) 99 (4) 1032 (7) 1205 (8) 1552 (8) 4124 (7) – Data are presented as N (%). < 400 cannot be made public in the NDB open data. aThe sum of the values for each category does not correspond to the total as the cells with N The crude injection rates per 1,000 person-years were 5.0 (2014), 3.1 (2015), 3.5 (2016), 4.2 (2017), 12.7 (2018), 13.9 (2019), and 16.1 (2020) in fiscal years (Fig. 1). The sex- and age-adjusted rates of the injections per 1,000 person-years increased from 7.9 in 2014 to 16.1 in 2020 (Fig. 2), increasing by 104 % (2.04-fold) over 7 years.Fig. 1 Crude rates and sex- and age-adjusted rates of the total injections Fig. 2 Age-adjusted rates stratified according to sex The injection rates for men increased from 11.6 to 20.8, and for women from 4.9 to 12.1, from 2014 to 2020. (Fig. 2). Men accounted for approximately 60–70% of the total injections over the period. All age categories show increases in the injection rates from 2014–2020, with the rate for individuals in their 80s increasing by 111% (2.11-fold) from 13.4 to 28.3, 70s increasing by 87 % (1.87-fold) from 11.3 to 21.1, and people ≥90 years of age increasing by 133% (2.33-fold) from 7.6 to 17.7 (Fig. 3). These three age categories were most likely to receive injections, accounting for approximately 80%.Fig. 3 Sex-adjusted rates stratified according to age category All diagnoses (excluding NVG and ROP) show increases in the injection rates from 2014 to 2020, with the rate of nAMD increasing by 83% (1.83-fold) from 5.3 to 9.7, BRVO by 122% (2.22-fold) from 0.9 to 2.0, CRVO by 73% (1.73-fold) from 0.55 to 0.95, DME by 442 % (5.42-fold) from 0.19 to 1.03, and mCNV by 80% (1.80-fold) from 0.05 to 0.09 (Fig. 4). The nAMD group shows the highest rate, accounting for 60–70% over the study period, followed by the BRVO group. Although CRVO and DME ranked third and fourth from 2014 to 2019, this order was reversed in 2020.Fig. 4 Sex- and age-adjusted rates stratified according to diagnosis. nAMD neovascular age-related macular degeneration, BRVO branch retinal vein occlusion, CRVO central retinal vein occlusion, DME diabetic macular edema, mCNV myopic choroidal neovascularization, NVG neovascular glaucoma Over the study period, the rate of aflibercept increased by 130% (2.30-fold) from 5.4 to 12.4, and of ranibizumab increased by 28 % (1.28-fold) from 2.5 to 3.2 (Fig. 5). Pegaptanib peaked in 2015 at a rate of 0.06 but gradually decreased thereafter and finally was eliminated by 2020. The rate of brolucizumab was 0.43 in 2020. Aflibercept was the most commonly used drug, accounting for approximately 80% of the total injections over the study period.Fig. 5 Sex- and age-adjusted rates stratified according to drug Analysis stratified according to the drug and diagnosis shows that aflibercept gained popularity for use in nAMD, BRVO, and DME from 2014 to 2020, and the increase in the use of aflibercept and ranibizumab was similar for CRVO and mCNV (Fig. 6).Fig. 6 Sex- and age-adjusted rates stratified according to drug and diagnosis. nAMD neovascular age-related macular degeneration, BRVO branch retinal vein occlusion, CRVO central retinal vein occlusion, DME diabetic macular edema, mCNV myopic choroidal neovascularization, NVG neovascular glaucoma On stratifying the analysis according to the age category and diagnosis in 2020, the age category accounting for the majority was 80–89 years (51%) for nAMD, 70–79 years (43%) for BRVO, 80–89 years (47%) for CRVO, 70–79 years (48%) for DME, 70–79 years (50%) for mCNV, 70–79 years (49%) for NVG, and ≤39 years (100%) for ROP (Online Resource 5). The average number of injections per person within one year after the first injection tended to increase for all diseases except NVG (Fig. 7). The number of injections for nAMD increased from 3.4 to 4.4, BRVO from 2.1 to 2.7, CRVO from 2.7 to 3.1, DME from 2.8 to 3.5, and mCNV from 2.4 to 2.9, over the study period.Fig. 7 Annual number of anti-VEGF injections after the first injections according to diagnosis. nAMD neovascular age-related macular degeneration, BRVO branch retinal vein occlusion, CRVO central retinal vein occlusion, DME diabetic macular edema, mCNV myopic choroidal neovascularization, NVG neovascular glaucoma Comparing the number of injections in the DeSC database with that in the NDB open data, the age distribution of the DeSC database was somewhat biased toward older individuals (the furthest right column in Table 1). Injections administered to individuals aged ≥70 years accounted for 90% in the DeSC database, whereas they accounted for 72% in the whole population. The distribution of sex and drugs was similar in the DeSC database and NDB open data. Discussion Here we clarify the recent trends in the use of anti-VEGF drugs using a large-scale claims database. The total injection rate in 2020 was approximately 16 per 1000 person-years. The injections were most commonly administered to men to people in their 80s, and those with nAMD. Aflibercept was the most commonly used drug. These trends were observed over the period between 2014 and 2020. The total sex- and age-adjusted injection rates increased by 104% between 2014 and 2020. The possible reasons for this increase include (1) the approval of the use of ranibizumab and aflibercept for the treatment of BRVO, CRVO, and DME between 2013 and 2015. The pivotal clinical trials after 2014 demonstrating the effectiveness of anti-VEGF drugs may have accelerated anti-VEGF use [3, 4, 8]. Previous surveys show that the proportion of ophthalmologists choosing anti-VEGF injections as the first choice therapy for DME increased from 73% in 2015 to 81% in 2016–2017 [25, 26] in Japan. Although only one survey investigated the preference regarding the treatment of RVO in Japan [27], 100% of ophthalmologists chose anti-VEGF injections as the first therapy; (2) the spread of spectral-domain optical coherence tomography (OCT) in Japan between 2014 and 2020. OCT can detect even the slightest lesions, such as subretinal fluid and intraretinal fluid; it has become the current standard in ophthalmic clinical practice [28]. This spread may have lowered the threshold for the administration of anti-VEGF drugs; and (3) the changes in the guiding criteria for the retreatment of nAMD. The criteria initially consisted of quantitative measures, such as OCT-measured central retinal thickness [29, 30]; however, qualitative measures, such as evidence of the presence of fluid on OCT, are now indicated [31]. This may have contributed to the increase in anti-VEGF injections. According to the current study men were more likely to receive injections than women. A possible reason is that most of the diagnoses were nAMD. Two previous population-based studies conducted in Japan showed that the prevalence of nAMD was higher among men than that among women, and this trend was the opposite of that observed in caucasians [32, 33]. This sex gap may be due to the following characteristics unique to Japan: (1) a higher proportion of smokers among men, (2) a high prevalence of polypoidal choroidal vasculopathy, a type of nAMD more likely to develop in men than in women, and (3) differences in the genetic composition of nAMD, such as the complement factor H gene [33]. The elderly were more likely to receive injections than the middle-aged and young. This may be related to the prevalence of the diseases. Older age is a significant risk factor for AMD [19] and RVO [20]. These two diseases accounted for the majority of the population in the current study; thus, the proportion of the elderly aged 70–79, 80–89, and ≥90 years were larger than other age categories. The injection rates for nAMD, BRVO, CRVO, and DME increased during the study period. Among all the diagnoses, except for unspecified diagnoses, the highest rate was observed for nAMD, followed by BRVO, DME, and CRVO in 2020. This order was consistent with a previous study that used a claims database in Japan from 2008 to 2015 [18]. However, previous population-based cohort studies in Japan report that, among people aged ≥50 years the prevalence of nAMD was 0.7% in 1998 [32] and 0.6% in 2000–2002 [19], that of BRVO was 2.4% in 1998 [20], and of CRVO was 0.2% in 1998 [20]. Furthermore, a survey conducted in 2019 reports that the prevalence of DM was 19.7% in men and 10.8% in women (approximately 15% of the total population) [34], whereas a meta-analysis showed that the estimated prevalence of DME was 7.4% among patients with DM [35]; thus, the prevalence of DME in the general population would be approximately 1.1% (= 0.15*0.074), signifying that nAMD was not the highest. This difference between the injection rates and prevalence may be attributed to the different levels of necessity to treat the diseases. Almost all nAMD patients should be treated with anti-VEGF injections regularly because nAMD is vision-threatening, and anti-VEGF is usually the first choice of treatment, as established by the AMD guidelines [36]. In contrast, only 5–15% of BRVO develop macular edema [37]. Furthermore, alternative therapies, such as laser photocoagulation and vitrectomy, can be used in the treatment of RVO [27]. Alternative therapies for DME, such as sub-Tenon's corticosteroid and vitrectomy, would lower the injections’ rates farther than in nAMD [38]. Our analysis reveals that the number of injections within one year after the first injection was higher for nAMD (4.4) compared with BRVO (2.7) and DME (3.5) in 2020. The injection rates for DME continued to increase and surpassed those of CRVO in 2020. Since the number of cases of diabetes mellitus in Japan was stable between 2010 and 2019 [34], there is a possibility that the treatment pattern of DME has been gradually changing. This is supported by surveys that report a recent preference for anti-VEGF therapy over other treatments, such as sub-Tenon’s corticosteroid and laser photocoagulation, in the treatment of DME [25, 26]. Specifically, the proportion of ophthalmologists choosing anti-VEGF injections as the first therapy has increased from 73% in 2015 to 81% in 2016–2017 [25, 26]. The analysis stratified according to drugs shows the popularity of aflibercept compared with ranibizumab in the treatment of nAMD, BRVO, and DME. Ranibizumab binds to VEGF-A, whereas aflibercept traps VEGF-A, VEGF-B, and placental growth factor [39, 40]. This difference in their pharmacological function may be associated with the following clinical superiorities of aflibercept over ranibizumab. First, some studies report a higher possibility of polyp regression with the administration of aflibercept compared with ranibizumab for polypoidal choroidal vasculopathy [41, 42]. Since the prevalence of polypoidal choroidal vasculopathy is high among Asians, the effectiveness of aflibercept may have contributed to its popularity. Second, aflibercept can decrease choroidal thickness to a greater extent than ranibizumab [43]. Third, one study reports that nAMD cases with choroidal vascular hyperpermeability had better visual outcomes when treated with aflibercept than with ranibizumab [44]. The second and third results imply that aflibercept can suppress the exudative tendency of the choroid more potently than ranibizumab. Furthermore, in terms of cost, aflibercept was cheaper than ranibizumab (JPY 137, 292 vs. JPY 160,698 as of March 2021). The abovementioned reasons likely contributed to the popularity of aflibercept in the treatment of nAMD. The Diabetic Retinopathy Clinical Research Network Protocol T study reports that visual acuity at one year was better in patients treated with aflibercept than in those treated with ranibizumab whenever their baseline visual acuity was < 20/50 [45]. The superiority of aflibercept over ranibizumab disappeared at two years, but from the perspective of the area under the curve [46], some ophthalmologists may have preferred aflibercept for the treatment of DME. There is no clear evidence of the superiority of aflibercept over ranibizumab in treating RVO. For example, a recent randomized controlled study (LEAVO study) did not show the superiority of aflibercept over ranibizumab in the treatment of macular edema secondary to CRVO [47]. Hence, why aflibercept is more likely to be chosen for the treatment of RVO in recent years remains unknown. The current study had several limitations. First, not all diagnoses were accurately identified because some patients had multiple diagnoses in the same year and month as the injections or because they did not have any of the abovementioned diagnoses. We may have to develop algorithms to predict the true diagnoses from the data of diagnoses, drugs, and procedures of adjacent months. Second, the claims data are subject to coding errors and omissions. Third, we did not account for the influence of the COVID-19 pandemic. This may influence -patients’ behaviour whenever there is a need to consult a doctor; However, an increasing trend in injection rates was observed in 2020. Fourth, when interpreting the current results we must consider the age distribution of the DeSC database as the proportion of older individuals in the DeSC database was higher than that in the whole population in Japan. One of the strengths of the current study is that it includes a large number of people using large-scale claims’ data. This enabled us to estimate the injection rates with small variance. Another strength is that the DeSC database includes all ages, including >75 years, in addition to information on the diagnoses (unlike the NDB open data). Since the prevalence of nAMD and RVO is strongly associated with older age [32, 33], it is essential to include the elderly to provide all the details of the anti-VEGF injections administered. In conclusion, the current study clarifies the recent trends in anti-VEGF injections in Japan using a large claims’ database. The total injection rate increased by 104% between 2014 and 2020. Men, the elderly aged ≥70 years, nAMD, and aflibercept had a large share in the stratified analyses according to sex, age category, diagnosis, and drug use. The current findings help understand the details of the use of anti-VEGF drugs in recent Japanese clinical practice and can become a benchmark for anti-VEGF drug injections. Supplementary Information Below is the link to the electronic supplementary material.Supplementary file1 (PDF 469 KB) This work was supported by grants from the Ministry of Health, Labour and Welfare, Japan (H30-Policy-Designated-004 and H29-ICT-General-004) and the Ministry of Education, Culture, Sports, Science and Technology, Japan (17H04141). The sponsor or funding organization had no role in the design or conduct of this study. Data availability We used de-identified, individual-level data obtained from the DeSC Claims Database (Tokyo, Japan). The address of their HP is https://desc-hc.co.jp. Data may be obtained from the Inc. and are not publicly available. Declarations Conflict of interest Y. Hashimoto, None; A. Okada, None; H. Matsui, None; H. Yasunaga, None; M. Aihara, Grants or contracts (Santen, Senju, Alcon, Novartis, Pfizer, Kowa, Otsuka, Wakamoto, Johnson & Johnson, Glaukos, TOMEY, Ono, CREWT Medical Systems, Sato), Consulting fees (Santen, Senju, Alcon, Pfizer, Kowa, Otsuka, Wakamoto, HOYA, Glaukos, IRIDEX, Astellas), Payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events (Santen, Senju, Alcon, Novartis, Pfizer, Kowa, Otsuka, Johnson & Johnson, HOYA, Glaukos, TOMEY, IRIDEX, CREWT Medical Systems, Canon, ZEISS, Sato), Participation on a Data Safety Monitoring Board or Advisory Board (Santen, Senju, HOYA, Kowa), Receipt of equipment, materials, drugs, medical writing, gifts or other services (Kowa, Santen); R. Obata, Payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events (Novartis, Bayer, Santen, Senju, Alcon). Corresponding Author: Yohei Hashimoto Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Rofagha S Bhisitkul RB Boyer DS Sadda SR Zhang K Seven-year outcomes in ranibizumab-treated patients in ANCHOR, MARINA, and HORIZON Ophthalmology 2013 120 2292 2299 10.1016/j.ophtha.2013.03.046 23642856 2. Varma R Bressler NM Suñer I Lee P Dolan CM Ward J Improved vision-related function after ranibizumab for macular edema after retinal vein occlusion: results from the bravo and cruise trials Ophthalmology 2012 119 2108 2118 10.1016/j.ophtha.2012.05.017 22817833 3. Clark WL Boyer DS Heier JS Brown DM Haller JA Vitti R Intravitreal aflibercept for macular edema following branch retinal vein occlusion: 52-week results of the vibrant study Ophthalmology 2016 123 330 336 10.1016/j.ophtha.2015.09.035 26522708 4. Ogura Y Roider J Korobelnik J-F Holz FG Simader C Schmidt-Erfurth U Intravitreal aflibercept for macular edema secondary to central retinal vein occlusion: 18-month results of the phase 3 GALILEO study Am J Ophthalmol 2014 158 1032 8.e2 10.1016/j.ajo.2014.07.027 25068637 5. Massin P Bandello F Garweg JG Hansen LL Harding SP Larsen M Safety and efficacy of ranibizumab in diabetic macular edema (resolve study): a 12-month, randomized, controlled, double-masked, multicenter phase II study Diabetes Care 2010 33 2399 2405 10.2337/dc10-0493 20980427 6. Nguyen QD Brown DM Marcus DM Boyer DS Patel S Feiner L Ranibizumab for diabetic macular edema: results from 2 phase III randomized trials: RISE and RIDE Ophthalmology 2012 119 789 801 10.1016/j.ophtha.2011.12.039 22330964 7. Elman MJ Aiello LP Beck RW Bressler NM Bressler SB Diabetic Retinopathy Clinical Research Network Randomized trial evaluating ranibizumab plus prompt or deferred laser or triamcinolone plus prompt laser for diabetic macular edema Ophthalmology 2010 117 1064 77.e35 10.1016/j.ophtha.2010.02.031 20427088 8. Heier JS Korobelnik J-F Brown DM Schmidt-Erfurth U Do DV Midena E Intravitreal aflibercept for diabetic macular edema Ophthalmology 2016 123 2376 2385 10.1016/j.ophtha.2016.07.032 27651226 9. Ikuno Y Ohno-Matsui K Wong TY Korobelnik J-F Vitti R Li T Intravitreal aflibercept injection in patients with myopic choroidal neovascularization Ophthalmology 2015 122 1220 1227 10.1016/j.ophtha.2015.01.025 25745875 10. Wolf S Balciuniene VJ Laganovska G Menchini U Ohno-Matsui K Sharma T RADIANCE: a randomized controlled study of ranibizumab in patients with choroidal neovascularization secondary to pathologic myopia Ophthalmology 2014 121 682 92.e2 10.1016/j.ophtha.2013.10.023 24326106 11. Inatani M Higashide T Matsushita K Miki A Ueki M Iwamoto Y Intravitreal aflibercept in Japanese patients with neovascular glaucoma: the VEGA randomized clinical trial Adv Ther 2021 38 1116 1129 10.1007/s12325-020-01579-5 33330958 12. Stahl A Lepore D Fielder A Fleck B Reynolds JD Chiang MF Ranibizumab versus laser therapy for the treatment of very low birthweight infants with retinopathy of prematurity (RAINBOW): an open-label randomised controlled trial The Lancet 2019 394 1551 1559 10.1016/S0140-6736(19)31344-3 13. Stahl A Krohne TU Eter N Oberacher-Velten I Guthoff R Meltendorf S Comparing alternative ranibizumab dosages for safety and efficacy in retinopathy of prematurity: a randomized clinical trial JAMA Pediatr 2018 172 278 10.1001/jamapediatrics.2017.4838 29309486 14. Berkowitz ST Sternberg P Feng X Chen Q Patel S Analysis of anti–vascular endothelial growth factor injection claims data in US medicare part B beneficiaries from 2012 to 2015 JAMA Ophthalmol. 2019 137 921 10.1001/jamaophthalmol.2019.1971 31219520 15. Parikh R Ross JS Sangaralingham LR Adelman RA Shah ND Barkmeier AJ Trends of anti-vascular endothelial growth factor use in ophthalmology among privately insured and medicare advantage patients Ophthalmology 2017 124 352 358 10.1016/j.ophtha.2016.10.036 27890437 16. Chopra R Preston GC Keenan TDL Mulholland P Patel PJ Balaskas K Intravitreal injections: past trends and future projections within a UK tertiary hospital Eye Lond Engl 2022 36 1373 8 17. Perrone V Dovizio M Veronesi C Citraro R De Francesco A Dell’Orco S Retrospective analysis of the pharmaco-utilization of VEGF inhibitors and health care costs among patients with wet age-related macular degeneration and other ocular diseases in Italy Int J Environ Res Public Health 2022 19 2548 10.3390/ijerph19052548 35270241 18. Kawasaki R Bauer M Bezlyak V Ogura Y Treatment patterns for retinal diseases in patients newly-treated with anti-VEGF agents: a retrospective analysis of claims data from the Japan medical data center database Jpn J Ophthalmol 2021 65 215 226 10.1007/s10384-020-00802-8 33420855 19. Kawasaki R Wang JJ Ji G Taylor B Oizumi T Daimon M Prevalence and risk factors for age-related macular degeneration in an adult Japanese population: the Funagata study Ophthalmology 2008 115 1376 81.e2 10.1016/j.ophtha.2007.11.015 18222000 20. Yasuda M Kiyohara Y Arakawa S Hata Y Yonemoto K Doi Y Prevalence and systemic risk factors for retinal vein occlusion in a general Japanese population: the hisayama study Investig Opthalmology Vis Sci. 2010 51 3205 10.1167/iovs.09-4453 21. Okada A Yasunaga H Prevalence of noncommunicable diseases in Japan using a newly developed administrative claims database covering young, middle-aged, and elderly people JMA J 2022 5 190 198 35611228 22. Ministry of Health, Labour and Welfare, Japan. Universal health insurance system. https://www.mhlw.go.jp/bunya/iryouhoken/iryouhoken01/dl/01a.pdf. Accessed 7 Sep 2022 (in Japanese) 23. Fay MP Feuer EJ Confidence intervals for directly standardized rates: a method based on the gamma distribution Stat Med 1997 16 791 801 10.1002/(SICI)1097-0258(19970415)16:7<791::AID-SIM500>3.0.CO;2-# 9131766 24. Ministry of Health, Labour and Welfare, Japan. NDB open data. https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000177182.html. Accessed 7 Sep 2022 (in Japanese) 25. Sugimoto M Tsukitome H Okamoto F Oshika T Ueda T Niki M Clinical preferences and trends of anti-vascular endothelial growth factor treatments for diabetic macular edema in Japan J Diabetes Investig. 2019 10 475 483 10.1111/jdi.12929 26. Ogura Y Shiraga F Terasaki H Ohji M Ishida S Sakamoto T Clinical practice pattern in management of diabetic macular edema in Japan: survey results of Japanese retinal specialists Jpn J Ophthalmol 2017 61 43 50 10.1007/s10384-016-0481-x 27722786 27. Ogura Y Kondo M Kadonosono K Shimura M Kamei M Tsujikawa A Current practice in the management of branch retinal vein occlusion in Japan: survey results of retina specialists in Japan Jpn J Ophthalmol 2019 63 365 373 10.1007/s10384-019-00685-4 31428900 28. Fujimoto J Swanson E The development, commercialization, and impact of optical coherence tomography Investig Opthalmol Vis Sci. 2016 57 1 13 10.1167/iovs.16-19963 29. Holz FG Amoaku W Donate J Guymer RH Kellner U Schlingemann RO Safety and efficacy of a flexible dosing regimen of ranibizumab in neovascular age-related macular degeneration: the SUSTAIN study Ophthalmology 2011 118 663 671 10.1016/j.ophtha.2010.12.019 21459217 30. Lalwani GA Rosenfeld PJ Fung AE Dubovy SR Michels S Feuer W A variable-dosing regimen with intravitreal ranibizumab for neovascular age-related macular degeneration: year 2 of the PrONTO study Am J Ophthalmol 2009 148 43 58.e1 10.1016/j.ajo.2009.01.024 19376495 31. Martin DF Maguire MG Ying G Grunwald JE Fine SL CATT Research Group Ranibizumab and bevacizumab for neovascular age-related macular degeneration N Engl J Med 2011 364 1897 1908 10.1056/NEJMoa1102673 21526923 32. Oshima Y Ishibashi T Murata T Tahara Y Kiyohara Y Kubota T Prevalence of age related maculopathy in a representative Japanese population: the Hisayama study Br J Ophthalmol 2001 85 1153 1157 10.1136/bjo.85.10.1153 11567955 33. Kawasaki R Wang JJ Rochtchina E Taylor B Wong TY Tominaga M Cardiovascular risk factors and retinal microvascular signs in an adult japanese population: the funagata study Ophthalmology 2006 113 1378 1384 10.1016/j.ophtha.2006.02.052 16877076 34. Ministry of Health, Labour and Welfare, Japan. National health and nutrition survey (2019). https://www.mhlw.go.jp/content/10900000/000687163.pdf. Accessed 9 Apr 2022 (in Japanese). 35. Yau JWY Rogers SL Kawasaki R Lamoureux EL Kowalski JW Bek T Global prevalence and major risk factors of diabetic retinopathy Diabetes Care 2012 35 556 564 10.2337/dc11-1909 22301125 36. Takahashi K Ogura Y Ishibashi T Shiraga F Yuzawa M Treatment guidelines for age-related macular degeneration Nippon Ganka Gakkai Zasshi 2012 116 1150 1155 23379205 37. Rogers SL McIntosh RL Lim L Mitchell P Cheung N Kowalski JW Natural history of branch retinal vein occlusion: An evidence-based systematic review Ophthalmology 2010 117 1094 101.e5 10.1016/j.ophtha.2010.01.058 20430447 38. Moulin TA Adjei Boakye E Wirth LS Chen J Burroughs TE Vollman DE Yearly treatment patterns for patients with recently diagnosed diabetic macular edema Ophthalmol Retina. 2019 3 362 370 10.1016/j.oret.2018.11.014 31014689 39. Papadopoulos N Martin J Ruan Q Rafique A Rosconi MP Shi E Binding and neutralization of vascular endothelial growth factor (VEGF) and related ligands by VEGF Trap, ranibizumab and bevacizumab Angiogenesis 2012 15 171 185 10.1007/s10456-011-9249-6 22302382 40. Fogli S Del Re M Rofi E Posarelli C Figus M Danesi R Clinical pharmacology of intravitreal anti-VEGF drugs Eye (Lond) 2018 32 1010 1020 10.1038/s41433-018-0021-7 29398697 41. Cho HJ Kim KM Kim HS Han JI Kim CG Lee TG Intravitreal aflibercept and ranibizumab injections for polypoidal choroidal vasculopathy Am J Ophthalmol 2016 165 1 6 10.1016/j.ajo.2016.02.019 26921806 42. Hosokawa M Shiraga F Yamashita A Shiragami C Ono A Shirakata Y Six-month results of intravitreal aflibercept injections for patients with polypoidal choroidal vasculopathy Br J Ophthalmol 2015 99 1087 1091 10.1136/bjophthalmol-2014-305275 25712826 43. Gharbiya M Cruciani F Mariotti C Grandinetti F Marenco M Cacace V Choroidal thickness changes after intravitreal antivascular endothelial growth factor therapy for age-related macular degeneration: ranibizumab versus aflibercept J Ocul Pharmacol Ther 2015 31 357 362 10.1089/jop.2014.0160 26133059 44. Hata M Oishi A Tsujikawa A Yamashiro K Miyake M Ooto S Efficacy of intravitreal injection of aflibercept in neovascular age-related macular degeneration with or without choroidal vascular hyperpermeability Invest Ophthalmol Vis Sci 2014 55 7874 7880 10.1167/iovs.14-14610 25395483 45. Wells JA Glassman AR Ayala AR Jampol LM Bressler NM Bressler SB Aflibercept, bevacizumab, or ranibizumab for diabetic macular edema: two-year results from a comparative effectiveness randomized clinical trial Ophthalmology 2016 123 1351 1359 10.1016/j.ophtha.2016.02.022 26935357 46. Gross JG Glassman AR Jampol LM Inusah S Aiello LP Writing Committee for the Diabetic Retinopathy Clinical Research Network Panretinal photocoagulation vs intravitreous ranibizumab for proliferative diabetic retinopathy: a randomized clinical trial JAMA 2015 314 2137 10.1001/jama.2015.15217 26565927 47. Hykin P Prevost AT Sivaprasad S Vasconcelos JC Murphy C Kelly J Intravitreal ranibizumab versus aflibercept versus bevacizumab for macular oedema due to central retinal vein occlusion: the LEAVO non-inferiority three-arm RCT Health Technol Assess 2021 25 1 196 10.3310/hta25380
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==== Front Innov Syst Softw Eng Innov Syst Softw Eng Innovations in Systems and Software Engineering 1614-5046 1614-5054 Springer London London 510 10.1007/s11334-022-00510-1 S.i. : Intelligence for Systems and Software Engineering Mental health issues assessment using tools during COVID-19 pandemic Rao Hamnah 1 Gupta Meenu 2 http://orcid.org/0000-0002-7297-335X Agarwal Parul [email protected] 1 Bhatia Surbhi [email protected] 3 Bhardwaj Rajat 4 1 grid.411816.b 0000 0004 0498 8167 Jamia Hamdard, Hamdard Nagar, New Delhi-58, India 2 grid.448792.4 0000 0004 4678 9721 Chandigarh University, Punjab, India 3 grid.412140.2 0000 0004 1755 9687 Department of Information systems, college of computer science and information technology, King Faisal University, Al Hasa, Saudi Arabia 4 grid.428245.d 0000 0004 1765 3753 Chitkara University, Punjab, India 12 12 2022 112 17 6 2022 22 11 2022 © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. COVID-19 has brought distress among people as pandemic has impacted the globe not only economically or physically, but also psychologically by degrading their mental health. Several research were done in the past which tried to capture these issues but post-covid situation needs to be critically handled and analyzed so that corrective measures for cure and support can be taken. The current work is an attempt to observe the mental health issues (anxiety and depression) that occurred during the lockdown by combining a few pre-designed questionnaires. The online survey included 244 respondents (females = 126, males = 118) and when we thoroughly examined gender, age group, and occupational activity as three main factors, the results showed that female students aged 21–35 were affected more than male students of the same age group. In this study, we used a 4-item Geriatric Depression Scale (GDS-4) as a depression screening instrument and discovered that 225 out of total respondents were depressed. Using the Generalized Anxiety Disorder (GAD-7), a self-administered anxiety tool, we found 103 responders with mild, 87 with moderate, 12 with severe, and 42 with no anxiety symptoms. Patient Health Questionnaire (PHQ-9) showed the symptoms of mental disorders where 68 individuals had mild, 85 had moderate, 37 had moderately severe, 12 had severe, and 42 had no symptoms. With the help of multiple linear regression analysis, demographic data were evaluated, and later results were compared between GDS-4, GAD-7, and PHQ-9 using correlation coefficients. This will help practitioners and individuals to focus on their physiological health and adopt diagnostic measures. Keywords Anxiety Depression Mental health Mental disorders Psychological tools ==== Body pmcIntroduction CoronaVirus that emerged in the late 2019 from Wuhan, China, has become a global epidemic which is an infectious disease caused by the SARS-COV-2 virus [1], although the initial source of viral transmission to human remains unknown [2]. As it rapidly sweeps across the world, people were shut like prisoners in their houses during lockdown causing an enormous degree of fear, worry and anxiety [3]. Livelihood affected in every possible manner; on one side, people’s usual activities and routines were disturbed, and on the other side, the productivity was paused, and businesses were closed causing severe impact on global economy [4]. While the work-from-home policy and online education mode [5] were implemented in the upper classes, tens of millions of people were still living in poverty and fighting to meet their fundamental necessities. Health care was also one of the key aspects affected by COVID-19 and people become lazier due to fewer physical activities, which has a detrimental influence on one’s physical health. The major psychological impact on public mental health was seen as an increased level of anxiety, stress, and depression [6]. Loneliness, sadness, harmful alcohol and drug use, self-harm, or suicide conduct, and sleeping issues are also likely to grow [7]. Mental illness is rarely addressed seriously, which has resulted in major issues and many tragic scenarios. It can make you feel miserable and be harmful to your everyday life at your job, school, or in managing decent relationships [8]. In most cases, symptoms can be managed with a combination of medications and talk therapy called psychotherapy [9]. Detecting mental health issues by finding the difference in behavior is not an easy task as there is no direct test to find one’s mental and emotional health [10]. You can do it by daily analyzing the person closely or checking his changed behavior in actions and thoughts [11]. Our work will give you some idea about mental illness, but you must know that every illness has a specific combination of symptoms. Some signs which are commonly seen in people with mental illness are given below:Unnecessarily worrying. Mood swings (mostly negative). Feeling sad all the time. Power of learning and concentration is lost. Avoid being social and participating in social activities. Anger issues are raised. Sleeping and eating disorders. In some cases, increased use of drugs and alcohol. Always lost in the imaginary world away from reality. Stressed in performing daily basic activities. Avoid talking about their problem (believing it is not a problem). Anxiety is defined by the World Health Organization as the fear of a future threat, feelings of tension, anxious thoughts, and physical changes such as elevated blood pressure and heart rate [12]. Depression is a severe kind of anxiety characterized by persistent sadness and a lack of interest in one’s favorite activities. People suffering from depression are frequently fatigued, as well as disruptions in sleeping and eating patterns have been monitored [13]. The global population is already vulnerable to depression, anxiety, and a variety of other mental health issues, which have been proved to be stressful in pre-covid phase. Over 264 million people are depressed all over the world, and due to fear of the disease, many cases of suicidal attempts were reported by ‘The Hindustan Times’ (2020) [14]. This paper aims to make people understand that talking about mental health and its issues is normal and that mental illness is as common as a fever [15]. Major contribution This research sheds light on significant components for public mental health and mental health care management systems. To demonstrate the need for growth in mental health awareness, assessment tools have utilized. This study identifies the evaluation of scores and the importance of psychological tools; hence, GDS-4, GAD-7, and PHQ-9 helped us in analyzing the levels of depression, anxiety, and other common mental health disorders. Prospective research is investigated using various statistical methods, such as mean, standard deviation, linear multiple regression analysis, and correlation coefficients, based on the stated parameters. For future work, it is recommended to evaluate different parameters to find more realistic results. Organization of the paper Open discussion on mental health awareness specially post-covid phase will help people take necessary actions if needed based on their physiological health. Section 2 contains the literature review which helps the researcher to know earlier work done on this topic and used for better understanding and gathering data for future references. Methodology is discussed in Sect. 3 which has been subdivided into few headings explaining the data sets and tools used in questionnaire for the data collection. Section 4 contains experimental result analysis which has subgroups evaluating the result tables based on different tools GDS-4, GAD-7, and PHQ-9. Discussion on the results is shown in Sect. 5 where the results on the mean, standard deviation, linear multiple regression analysis, and correlation coefficients using statistical tools were defined. Summary and future scope of the research are concluded in Sect. 6. Literature review Some relatable papers have been reviewed to know the work done on mental health, and a small description is written that helps in future reference A better understanding of the topic and gathering all the informative knowledge help to know the research questions and gaps more accurately as shown in Table 1.Table 1 Literature Review S no. References Methodology used Result analysis 1 [14] Reading and collecting newspaper report about suicide during COVID, purposive sampling is used method This study is based on media articles and explains why there were so many suicide incidents during COVID-19. There is a demand for a nationwide tele-mental health service 2 [16] A descriptive analysis was performed using the data from Depression Anxiety Stress Scale (DASS-42) and a questionnaire for coping techniques tool Analysis of the DASS-42 indicated male and female individuals varied considerably in mental health and quality of life, but no significant differences in coping mechanisms were detected 3 [17] To make inferences, data were analyzed using SPSS v21, and t test, ANOVA test, and correlational analysis were used According to research, because of their greater levels of psychological discomfort, students and health professionals require specific care. Find out how people in India experienced sadness, anxiety, tension, and familial impact during the lockdown 4 [18] Data analysis and data visualization techniques, bar graphs, and methodology diagrams were employed in the analysis and statistical format Describes the psychological status of people in Bangladesh who have been affected by COVID-19 in their daily lives. Based on the depression scale, Internet use, and psychological change, male and female scores were compared 5 [19] Variable descriptive statistics, correlation coefficients, and regression analysis were performed on the data In a report published during the new coronavirus outbreak, the importance of individual characteristics as predictors of quality of life and the influence of group-related variables are discussed. Individual and group characteristics both had a substantial impact on QoL, according to the findings 6 [20] In the cross-sectional investigation, the DASS-21 and IES scales were employed. The data were analyzed using Cronbach’s alpha, GLM, and the R statistical software package The study’s goal was to look at the psychological effects of COVID-19 on university students. The findings show that preventative action should be taken, as well as the provision of a psychological specialist to the institution in the situation of a future epidemic. Students outperform university personnel on every metric 7 [21] The data were analyzed using median-absolute detection, descriptive statistics, Pearson’s correlation, t test, and ANOVA The association between personality traits, mental health, and creativity was investigated in this study. The propensity for isolation, as well as personality factors from the Big Five, was significantly predicted the same 8 [22] They calculated descriptive statistics and logistic regression The goal of this study was to find the occurrence of psychological health problems before and during the COVID-19 pandemic. This research highlights the urgent need to increase global mental health promotion and preventive efforts During the COVID-19 epidemic, [23] found related variables in physicians’ anxiety, stress, and depression levels in both clinical and general settings. SPSS-v25, Pearson’s correlation, descriptive statistics, t test, ANOVA, and multiple linear regression were used to evaluate the data. In the USA, [24] researchers tried to uncover variables linked to depression, anxiety, and PTSD symptomatology. These criteria offer preliminary advice on how to treat COVID-19-related mental health issues in the clinic. PHQ-8 was used to measure depression, GAD-7 was used to measure anxiety, and PCL-C was used to measure PTSD symptoms. In the study, [25] investigated the consequences of loneliness and behavior on mental health, as well as the moderating and mediating effects of biopsychosocial factors. Loneliness and fear were significant factors tinning mentality and behavioral issues during the COVID-19 lockdown, according to the research. In [26], researchers talked about the mental health issues that came up because of the disease’s morbidity, mortality, and mitigation actions during the pandemic. According to the findings on mental health, substance abuse, and suicide thoughts, a few strategies were proposed. In [27], researchers discovered the GPS symptoms score, GAD median score, PHQ total median score, ISI median score, and PSS total score median in the Italian population. And they concluded that Italy needed to keep a close watch on mental health measures to reduce the outbreak’s impact on mental health. The researchers in [28] conducted a research to look at the mental health of Greek university students. According to the findings, students are at a greater risk of developing depression and suicidality because of the COVID-19 pandemic. In [29], COVID-19 has been linked to an increase in risk factors such as social isolation, child abuse, intimate partner violence, unemployment, housing and economic stress, workplace trauma, and sorrow and loss, according to the researchers. To ‘flatten the curve’ and avoid a spike in mental illness, an emphasis on primary prevention is particularly vital. In [30], the authors investigated the relationship between COVID-19 fear and social vulnerabilities as well as mental health effects in individuals in the USA. They witnessed a people that areas concerned, afraid, and unsure about COVID-19 and the implications it would have for themselves, their families, their communities, and their country. The researchers in [31] employed a longitudinal dataset that linked biometric and survey data from multiple cohorts of young individuals before and during the COVID-19 pandemic to demonstrate significant changes in physical activity, sleep, time usage, and mental health. They use the Center for Epidemiologic Studies Depression Scale (CES-D) and the GAD-7 to examine data for depression and anxiety symptoms. In [32], they stated from the point of view of military medical planners to present information about the prevalence of mental health issues and conditions from the last few pandemics including COVID-19. Psychological needs of people affected and the harmful impacts of isolation, especially anxiety and distress, and post-traumatic stress symptoms. The researchers in [33] examined how job loss affected the mental health of people in South Africa during an epidemic. Adults who kept paid jobs throughout the lockdown had much lower depression levels than those who lost their jobs; according to the research in [34], they examined the economic costs, as well as the effects on everyday life and delays in academic pursuits, most of which were correlated to anxiety symptoms. Social support, on the other hand, was shown to be adversely connected to anxiety. [35] focused on primarily tele-mental health services, to see if they were feasible and acceptable for patients, relatives, and health practitioners during the epidemic. Psychological therapy and support may help to alleviate the burden of chronic mental health issues and to ensure the well-being of people who are harmed. The researchers in [36] demonstrate the prevalence and related risk factors of mental health problems among Bangladeshi students, mainly anxiety, depression, and stress. The DASS-21, GAD-7, PHQ-9, HADS, and CES-D-R-10 scales were adopted in seven cross-sectional online survey-based investigations. A study by [37] looked at the influence of a recent mental disorder—such as attention deficit hyperactivity disorder (ADHD), bipolar disorders, depression, and schizophrenia—on the probability of COVID-19 infection, as well as related mortality and hospitalization rates. The researchers in [38] evaluated the reported mental health effect and coping, as well as changes in depressive symptoms, anxiety, concern, and loneliness before and during the COVID-19 epidemic between those with and without lifelong depression, anxiety, or obsessive–compulsive disorders. The researchers in [39] wanted to see how the pandemic affected individuals with diverse psychiatric problems who were hospitalized for treatment. More than half of those surveyed said their symptoms had worsened, and 40% said they needed more therapeutic help. The study [40] focuses on the prevalence as well as predictors of general mental illnesses as evaluated by the questionnaire GHQ-12 and the occurrence of loneliness in the United Kingdom during COVID-19. This study examines the psychological impact of broader members of society during COVID-19, including general mental problems and loneliness, as well as the underlying socioeconomic inequalities. [41] conducted a comprehensive review to synthesize existing evidence of the impact of COVID-19 on psychosocial symptoms in the overall population and related risk factors. The COVID-19 pandemic is linked to extremely high levels of psychological discomfort, which, in many cases, would fulfill the clinical relevance criteria. The researchers [42] wanted to see how isolation affected sufferers in Residential Rehab Communities when compared with healthy controls. On the variables of anxiety, stress, worry, and risk perception, there were substantial differences between mental patients and controls. When compared to healthy controls, mentally ill patients ranked lower on stress but higher on anxiety, estimated risk of COVID-19 infection, and worry about an emergency scenario. A few algorithms on brain signal activity [43] were conducted to improve the precision of stress and other mental health concerns utilizing the EEG signals [44, 45]. Researchers suggest a fuzzy contrast-based approach that categorizes text written by mentally ill patients into different symptoms by using an attention network for positionally weighted words [46]. To address the ambiguity and imprecision inherent in the input data and for calculating the relationships between psychological variables, they applied fuzzy logic modeling to data [47]. Methodology Data set Online survey has been circulated among people on social networking sites like WhatsApp, Facebook, Instagram, and e-mails from 15 November to 15 December 2021. A survey was sent to further connections of different people to find mental health problems faced by them; the questionnaire contains a total of 24 questions and four sections in which all questions were compulsory and three pre-designed tools were used. Section one contains basic information reading the demographic factors such as gender, age group and occupational activities as described in Table 2.Table 2 Characteristics of participants (N = 244) Variables Level Frequency (n) N (%) Age Groups Below 20 62 25.41 21–35 124 50.82 36–50 43 17.62 Above 50 15 6.15 Gender Female 126 51.64 Male 118 48.36 Occupational activity Student 114 46.72 Employed 84 34.43 Unemployed 46 18.85 Tools used in the questionnaire Section 2 has a 4-item Geriatric Depression Scale (GDS), a depression assessment tool, simple and quick to perform, with high specificity and sensitivity, and has limited clinical value used in primary care [48]. It is a short version of the original GDS which contains 30 questions. 2-point scale is used to find if you have depression (2–4 = Depression, 1-Uncertain, 0 = Not depression) [49] As shown in Table 3, questions are also attached.Table 3 Results of questions based on the 4-item Geriatric Depression Scale (GDS) GDS-4 YES (%) NO (%) N = 244 Q1 139 (57) 105 (43) Q2 175 (72) 69 (28) Q3 162 (66) 82 (34) Q4 179 (73) 65 (27) Q1 Are you satisfied with your life after covid hit globally? Q2 Do you feel that your life is empty during covid lockdowns? Q3 Are you afraid that something bad is going to happen to you like fear to getting infection during this pandemic? Q4 Do you feel happy most of the time before and after COVID-19? Section 3 GAD-7 (Generalized Anxiety Disorder Assessment) is a simple self-administered patient questionnaire used as a screening tool to measure anxiety disorder scores from 0 to 3 that are assigned to categories ‘not at all,’ ‘several days,’ ‘more than half the days,’ ‘nearly every day,’ respectively. These results for seven questions were added, and cutoff thresholds for mild, moderate, and severe anxiety were 5, 10, and 15, respectively [50]. Questions based on the GDS-4 are also included in the Table 4. Table 4 Results of questions based on Generalized Anxiety Disorder Assessment GAD-7 GAD-7 N = 244 NOT AT ALL = 0 % SEVERAL DAYS = 1 % MORE THAN HALF DAYS = 2 % NEARLY EVERY DAY = 3 % Q1 54 22 117 48 40 16 33 14 Q2 73 30 93 38 48 20 30 12 Q3 69 28 101 41 43 18 31 13 Q4 67 27 99 41 43 18 35 14 Q5 74 30 88 36 52 21 30 12 Q6 59 24 84 34 52 21 49 20 Q7 56 23 98 40 57 23 33 14 Q1 Feeling nervous, anxious or on edge due to covid and its negative impact? Q2 Not being able to stop or control worrying about covid infection? Q3 Worrying too much about different things related to virus? Q4 Trouble relaxing? Q5 Being so restless that it is hard to sit still? Q6 Becoming easily annoyed or irritable? Q7 Feeling afraid as if something awful might happen? Section 4 contains PHQ-9 (Patient Health Questionnaire) which is a self-administered version of the PRIME-MD diagnostic tool for common mental disorders. Scores ranging from 0 to 3 correspond to the categories ‘not at all,’ ‘several days,’ ‘more than half the days,’ ‘and nearly every day,’ respectively. Hence, when nine questions are added together, we get scores as 0–4 for none, 5–9 for mild, 10–14 for moderate, 15–19 for moderately severe and 20–27 for severe mental disorders [51] as shown in Table 5.Table 5 Results of questions based on Patient Health Questionnaire PHQ-9 PHQ-9 N = 244 NOT AT ALL = 0 % SEVERAL DAYS = 1 % MORE THAN HALF DAYS = 2 % NEARLY EVERYDAY = 3 % Q1 59 24 96 39 58 24 31 13 Q2 86 35 88 36 32 13 38 16 Q3 65 27 99 41 49 20 31 13 Q4 55 23 92 38 65 27 32 13 Q5 68 28 91 37 58 24 27 11 Q6 89 36 79 32 43 18 33 14 Q7 82 34 79 32 48 20 35 14 Q8 102 42 83 34 38 16 21 9 Q9 106 43 72 30 41 17 25 10 Q1 Little interest or pleasure in doing things? Q2 Feeling down, depressed, or hopeless? Q3 Trouble falling or staying asleep, or sleeping too much? Q4 Feeling tired or having little energy? Q5 Poor appetite or overeating? Q6 Feeling bad about yourself—or that you are a failure or have let yourself or your family down? Q7 Trouble concentrating on things, such as reading the newspaper or watching television? Q8 Moving or speaking so slowly that other people could have noticed? Or the opposite—being so fidgety or restless that you have been moving around a lot more than usual? Q9 Thoughts that you would be better off dead, or of hurting yourself in some way? Experimental results analysis A total of 244 responses are recorded and shown in Table 2, and pie charts are shown to explain the distribution of data based on gender, age group, and occupational activities. From total of 244 respondents, 126(51.64%) were female and 118(48.36%) were male recorded in Fig. 1.Fig. 1 Gender distribution in data Furthermore, when distribution is calculated, 62(25.41%) of the respondents were below 20 years, 124(50.82%) were between 21 and 35 years, 43(17.62%) were between 36 and 50 years and 15(6.15%) were above 50 years when davidite in age groups recorded in Fig. 2.Fig. 2 Age group division in data When seen by occupational activities, 114(46.72%) respondents were students, 84(34.43%) were employed, i.e., working remotely from their homes and 46(18.85%) were unemployed during the days of COVID-19 lockdown due to lack of facilities and work which cannot be done remotely like workers from manufacturing industries and many others which is recorded in Fig. 3.Fig. 3 Occupational activities in data 4-item geriatric depression scale Analysis of the GDS-4 item tool revealed that on average, 163 people from 244 answered “Yes,” and on an average, 80.25 answered “No.” We found out that 119 females and 106 males were “Depressed.” And 7 females and 12 males were found in ca condition which was “Uncertain” according to the GDS-4 item scale. Surprisingly, not even a single person was “Not Depressed as” shown in Fig. 4. Their mean and standard deviation are also seen in Table 6.Fig. 4 Identifying depression Table 6 Description of participants based on gender of GDS-4 item scale with their mean and standard deviation Variables Gender N Mean SD Depression Male 106 2.9 0.74 Female 119 2.8 0.72 No depression Male 0 – – Female 0 – – Uncertain Male 12 1 – Female 7 1 – Generalized anxiety disorder assessment Analysis of the GAD-7 tool revealed that on average, 64.57 people answered, “Not at All,” 97.14 answered “Several days,” 47.86 answered “More Than Half Days,” and 34.43 answered “Nearly Every day” from a total of 244 respondents. By adding the scores of each question, we found that 56 males and 47 females have “Mild Anxiety,” 53 males and 44 females have “Moderate Anxiety,” and five males and seven females have “Severe Anxiety” and only 14 males and 28 females were there who have “no anxiety” shown in Fig. 5. Mean and standard deviation are also calculated from their scores shown in Table 7.Fig. 5 Identifying anxiety Table 7 Description of participants based on gender of GAD-7 scale with their mean and standard deviation Variables Gender N Mean SD Mild Male 56 7.69 1.23 Female 47 6.91 1.23 Moderate Male 43 11.51 1.6 Female 44 11.9 1.54 Severe Male 5 17.2 2.17 Female 7 17.14 1.35 No anxiety Male 14 1.64 1.55 Female 28 2.57 1.26 Patient health questionnaire Analysis of the PHQ-9 tool revealed that on average, 79.11 people answered, “Not at All,” 86.55 answered “Several days,” 48.0 answered “More Than Half Da and ys,” 30.33 answered “Nearly Every day” from 244 respondents. By adding the scores of each question, we found that 33 males and 35 females have “Mild mental disorders,” 50 males and 29 females have “Moderate,” and 10 males and 26 females have “Moderately Severe” and only five males and six females have “severe mental disorders” but only 12 males and 30 females were there who have fewer scores and hence no mental disorders shown in Fig. 6. Mean and the standard deviation are also calculated of the scores shown in Table 8.Fig. 6 Identifying mental disorder Table 8 Description of participants based on gender of PHQ-9 scale with their mean and standard deviation Variables Gender N Mean SD Mild Male 33 8.03 1.16 Female 35 6.77 1.37 Moderate Male 56 11.5 1.34 Female 29 11.86 1.48 Moderately severe Male 11 16.1 1.29 Female 26 16.92 1.44 Severe Male 6 23.25 3.36 Female 6 23.4 1.97 None Male 12 1.17 1.53 Female 30 2.17 1.34 Table 9 shows us the results of the t test performed based on gender difference and scores of the tools; mean and the standard deviation are calculated, and we found out that males and female are not significantly different with GDS-4 (t = 0.256, p = 0.99 > 0.05) but significantly different with GAD-7 and PHQ-9 (t = 0.92, p = 0.02 < 0.05 and t = 1.178, p = 0.0001 < 0.05, respectively).Table 9 Gender differences Tools Gender N Mean SD T Sig GDS-4 Male 118 2.67 .943 0.256 0.99 Female 126 2.70 .813 – – GAD-7 Male 118 8.75 3.846 0.920 0.02 Female 126 8.26 4.340 – – PHQ-9 Male 118 10.53 4.930 1.178 0.00 Female 126 9.68 6.133 – – Multiple linear regression analysis was performed from data using the demographic data gender (male, female), age groups (below 20, 21–35, 36–50, above 50), occupation activities (students, employed, unemployed) on the total scores of the standardized tools (Table 10). Additionally, R which tells simple correlation and R square(R2) which tells total variation in dependent variables (scores of tools) given by independent variables (demographic variables) are 0.40 and 0.002 for GDS-4 with a significance of 0.943, R and R2 are 0.140 and 0.20 for GAD-7 with the significance of 0.192, R and R2 are 0.112 and 0.012 for PHQ-9 with the significance of 0.388, respectively.Table 10 Multiple Regression Analysis on GDS-4 ITEM, GAD-7, PHQ-9 total cores in the overall sample Model B SE Beta (β) t Sig 95% CI Lower Bound Upper Bound GDS-4 Gender − 0.042 .115 − 0.024 − 0.363 .717 − 0.269 .186 Age Group .002 .005 .023 .313 .754 − 0.008 .011 Occupational activities .024 .083 .021 .292 .770 − 0.139 .187 GAD-7 Gender .291 .536 .035 .542 .588 − 0.766 1.347 Age Group .017 .023 .056 .771 .441 − 0.027 .062 Occupational activities .508 .384 .094 1.323 .187 − 0.248 1.264 PHQ-9 Gender .710 .732 .064 .970 .333 − 0.732 2.153 Age Group .004 .031 .008 .117 .907 − 0.057 .064 Occupational activities .580 .524 .079 1.107 .270 − 0.453 1.613 B Unstandardized Coefficients, SE Standard Error, Beta(β) Standardized Coefficients, CI Confidence Interval Table 11 indicates the correlation coefficients between GDS-4, GAD-7, and PHQ-9, and hence, negative correlation between GDS with GAD and PHQ is 0.055 and 0.131, respectively, implying that as one variable’s value increases, the value of the other variable drops or vice versa. GAD and PHQ have a positive correlation of 0.623; hence, the values of both the variables will change together which means either value will increase for both or decrease.Table 11 Correlation coefficients GDS GAD PHQ GDS Pearson Correlation Sig. (2-tailed) GAD Pearson Correlation − 0.055 Sig. (2-tailed) 0.395 PHQ Pearson Correlation − 0.131* 0.623** Sig. (2-tailed) .041 0.000 *Correlation is significant at the 0.05 level (2-tailed) **Correlation is significant at the 0.01 level (2-tailed) Discussion As the world came to a pause during the pandemic, and the infection’s rapid spread, along with its high severity, prompted widespread terror [52]. But thing that had never stopped was human brains, which never stopped thinking, although some minds were healthy and productive, others were unhappy and depressed, thinking negatively [53]. This research was started to tell the psychological distress using the standardize tools in different gender, age group, and occupational activities. By calculating the score, we find out that more than 80% people are suffering from mental health issues. As a greater number of females responded on our survey in comparison with males, females were likely to have more distress [54]. GDS-4 item tool tells there was not even one who came under the category of no depression and over 90% were having symptoms of depression. More than 50% people lie in the category of mild and moderate anxiety and mental disorders when seen the severity according to GAD-7 scores and PHQ-9 scores, respectively. We found the mean and standard deviation by the formulas shown in Eqs. (1) and (2), respectively.1 x¯=sumofobservationsno.ofobservations 2 σ=∑i=1nxi-x¯2n-1 We performed independent t test to find the significance difference means of male and female which is related by score of the tools. The value of t is found as 0.256, 0.920, 1.178, and the significance value is 0.99, 0.02, 0.0001 for the tools as GDS-4, GAD-7, PHQ-9, respectively. Hence, GAD-7 and PHQ-9 are significantly different when seen the means of males and females. The evaluated scores offer a way for theoretical and empirical social media-based mental health investigations [55]. Utilizing this work can help specialists to find people who needs awareness regarding the issue which will increase the standards and quality of life on the planet [56]. Multiple regression analysis is performed, and the result shows that the Unstandardized Coefficient is denoted by B, Standard Error as SE, Standardized Coefficients as Beta (β), Confidence Interval for B is denoted as CI which is 95% with upper bound and lower bound values. Also, the values of R, R2, error in R(Δ), and in regression table sum of squares, degree of freedom, mean square, F, and significance are also observed. Correlation coefficients are used to find how strong is the relationship between the variables and we check the relationship between GDS-4, GAD-7 and PHQ-9 tool to find how these are related when calculated for the same respondents. Positive correlation implies when values of one variable increase; then, the value of second variable also increases and same in case of decreasing value of both variables together. And the value of one variable increases, while other variable’s value decreases or vice versa; the negative correlation is observed. And a correlation can be zero when there is no relation between the two variables. Conclusion and future scope The current study demonstrated that the effects of COVID-19 during pandemic and post-lockdown period generate significant level of mental health issues based on the cut scores. When people transitioned to the new standards of covid, substantial level of anxiety, depressive symptoms, and poor mental health care were evaluated. When we thoroughly considered gender, age group, and occupational activity as three primary determinants, the results revealed that female students aged 21–35 were influenced more than male students. GDS-4 was utilized as a depression screening instrument in this study and determined that 92.22% respondents were depressed, 7.78% were uncertain, whereas no-depressive scale remains null. We detected that responders’ anxiety levels as 42.22% contains mild, 35.65% moderate, 4.9% severe, and 17.2% with no symptoms of anxiety using the GAD-7. PHQ-9 symptoms such as mild, moderate, severely moderate, severe and no sickness were examined as 27.8%, 34.83%, 15.1%, 4.9%, and 17.2% respectively to generalize the level of common psychological issues. This work can finally enable the patients and professionals to focus on preventing the consequences and to apply diagnostic measures for their physiological health after post-covid phase. Since a sizeable portion of population was missing from the dataset, we were incapable of achieving intended outcomes. For further research, it is recommended that comparing other parameterized variables such as individual’s location, impact of isolation and daily routine analysis can be used to expand the understanding of how these factors have been affected during and after enactment of the lockdown on public mental health. Funding No funding was received for conducting this study. Data availability The data shall be made available on request to the corresponding author. Declarations Conflict of interest No competing interest directly or indirectly related to the work submitted for publication exists. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Ding X Clifton D Ji N Lovell NH Bonato P Chen W Yu X Xue Z Xiang T Long X Xu K Wearable sensing and telehealth technology with potential applications in the coronavirus pandemic IEEE Rev Biomed Eng 2020 14 48 70 10.1109/RBME.2020.2992838 2. Zhao J Cui W Tian BP The potential intermediate hosts for SARS-CoV-2 Front Microbiol 2020 11 580137 10.3389/fmicb.2020.580137 33101254 3. WHO, "Mental health and COVID-19," [Online]. Available: https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/publications-and-technical-guidance/mental-health-and-covid-19 4. Ahnquist J Wamala SP Economic hardships in adulthood and mental health in Sweden. The Swedish national public health survey BMC Public Health 2009 11 1 1 1 5. Khattar A, Jain PR, Quadri SMK (2020) Effects of the disastrous pandemic COVID 19 on learning styles, activities, and mental health of young Indian students-a machine learning approach. In: 2020 4th international conference on intelligent computing and control systems (ICICCS), pp 1190–1195. IEEE 6. Cullen W Gulati G Kelly BD Mental health in the COVID-19 pandemic QJM Int J Med 2020 113 5 311 2 10.1093/qjmed/hcaa110 7. Sano A, Phillips AJ, Amy ZY, McHill AW, Taylor S, Jaques N, Czeisler CA, Klerman EB, Picard RW (2015) Recognizing academic performance, sleep quality, stress level, and mental health using personality traits, wearable sensors, and mobile phones. In: 2015 IEEE 12th international conference on wearable and implantable body sensor networks (BSN), pp 1–6). IEEE 8. Pfeffer B North CS Mental health and the Covid-19 pandemic N Engl J Med 2020 383 6 510 512 10.1056/NEJMp2008017 32283003 9. Clinic M "Mental illness," [Online]. Available: https://www.mayoclinic.org/diseases-conditions/mental-illness/symptoms-causes/syc-20374968 10. Felman (2020) "What is mental health?," 2020 [Online]. Available: https://www.medicalnewstoday.com/articles/154543 11. Banerjee D The COVID-19 outbreak: Crucial role the psychiatrists can play Asian J Psychiatry 2020 50 102014 10.1016/j.ajp.2020.102014 12. Peteet JR COVID-19 anxiety J Relig Health 2020 59 2203 2204 10.1007/s10943-020-01041-4 32415426 13. Teles A, Rodrigues I, Viana D, Silva F, Coutinho L, Endler M, Rabêlo R, (2019) Mobile mental health: a review of applications for depression assistance. In: 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS), pp 708–713. IEEE 14. DsouzaD D Quadros S Hyderabadwala JZ Aggregated COVID-19 suicide incidences in India: Fear of COVID-19 infection is the prominent causative factor Psychiatry Res 2020 290 113145 10.1016/j.psychres.2020.113145 32544650 15. Jain R Gupta M Taneja S Hemanth DJ Deep learning based detection and analysis of COVID-19 on chest X-ray images Appl Intell 2021 51 3 1690 1700 10.1007/s10489-020-01902-1 16. Sameer AS Khan MA Nissar S Banday MZ "Assessment of mental health and various coping strategies among general population living under imposed COVID-lockdown across world: a cross-sectional study Ethics Med Public Health 2020 15 100571 10.1016/j.jemep.2020.100571 32838000 17. Rehman U Shahnawaz MG Khan NH Kharshiing KD Khursheed M Gupta K Kashyap D Uniyal R Depression, anxiety and stress among Indians in times of Covid-19 lockdown Community Mental Health J 2021 57 1 42 48 10.1007/s10597-020-00664-x 18. Rahman MM Saifuzzaman AM Ahmed F Mahin M Shetu SF Impact of COVID-19 on mental health: a quantitative analysis of anxiety and depression based on regular life and internet use Current Res Behav Sci 2021 2 100037 10.1016/j.crbeha.2021.100037 19. Kharshiing KD Kashyap KD Gupta M Khursheed G Shahnawaz M Khan NH Rehman U Quality of life in the COVID-19 pandemic in India: Exploring the role of individual and group variables Community Mental Health J 2021 57 1 70 78 10.1007/s10597-020-00712-6 20. Odriozola-González P Planchuelo-Gómez A Irurtia JM de Luis-García R Psychological effects of the COVID-19 outbreak and lockdown among students and workers of a Spanish university Psychiatry Res 2020 290 113108 10.1016/j.psychres.2020.113108 32450409 21. Michinov E, Michinov N (2021) Stay at home! When personality profiles influence mental health and creativity during the COVID-19 lockdown. Current Psychology, 1–12 22. Winkler P Formanek T Mlada K Kagstrom A Mohrova Z Mohr P Csemy L Increase in prevalence of current mental disorders in the context of COVID-19: analysis of repeated nationwide cross-sectional surveys Epidemiol Psychiatr Sci 2020 10.1017/S2045796020000888 23. Elbay RY Kurtulmuş A Arpacıoğlu S Karadere E Depression, anxiety, stress levels of physicians and associated factors in Covid-19 pandemics Psychiatry Res 2020 290 113130 10.1016/j.psychres.2020.113130 32497969 24. Liu CH Zhang FE Wong GT Hyun S Factors associated with depression, anxiety, and PTSD symptomatology during the COVID-19 pandemic: clinical implications for US young adult mental health Psychiatry Res 2020 290 113172 10.1016/j.psychres.2020.113172 32512357 25. Megalakaki O Kokou-Kpolou CK Effects of biopsychosocial factors on the association between loneliness and mental health risks during the COVID-19 lockdown Current Psychol 2021 41 11 8224 8235 10.1007/s12144-021-02246-w 26. Czeisler MÉ Lane RI Petrosky E Wiley JF Christensen A Njai R Rajaratnam SMW Mental health, substance use, and suicidal ideation during the COVID-19 Pandemic—United States, June 24–30, 2020 MMWR. Morb Mortal Wkly Rep 2020 69 32 1049 1057 10.15585/mmwr.mm6932a1 32790653 27. Rossi R Socci V Talevi D Mensi S Niolu C Pacitti F Di Lorenzo G COVID-19 pandemic and lockdown measures impact on mental health among the general population in Italy Front Psych 2020 11 790 10.3389/fpsyt.2020.00790 28. Patsali ME Mousa DPV Papadopoulou EV Papadopoulou KK Kaparounaki CK Diakogiannis I Fountoulakis KN University students’ changes in mental health status and determinants of behavior during the COVID-19 lockdown in Greece Psychiatry Res 2020 292 113298 10.1016/j.psychres.2020.113298 32717710 29. Carbone SR Flattening the curve of mental ill-health: the importance of primary prevention in managing the mental health impacts of COVID-19 Mental Health Prev 2020 19 200185 10.1016/j.mhp.2020.200185 30. Fitzpatrick KM Harris C Drawve G Fear of COVID-19 and the mental health consequences in America Psychol Trauma: Theory, Res Pract Policy 2020 12 S1 S17 10.1037/tra0000924 31. Giuntella O Hyde K Saccardo S Sadoff S Lifestyle and mental health disruptions during COVID-19 Proc Nat Acad Sci 2021 10.1073/pnas.2016632118 32. Han RH Schmidt MN Waits WM Bell A Planning for mental health needs during COVID-19 Current Psychiatry Rep 2020 22 12 1 10 10.1007/s11920-020-01189-6 33. Posel D Oyenubi A Kollamparambil U Job loss and mental health during the COVID-19 lockdown: evidence from South Africa PloS one 2021 16 3 e0249352 10.1371/journal.pone.0249352 33784339 34. Cao W Fang Z Hou G Han M Xu X Dong J Zheng J The psychological impact of the COVID-19 epidemic on college students in China Psychiatry Res 2020 287 112934 10.1016/j.psychres.2020.112934 32229390 35. Zhou X Snoswell CL Harding LE Bambling M Edirippulige S Bai X Smith AC The role of telehealth in reducing the mental health burden from COVID-19 Telemed e-Health 2020 26 4 377 379 10.1089/tmj.2020.0068 36. Al Mamun F Hosen I Misti JM Kaggwa M Kaggwa MM Mamun MA Mental disorders of Bangladeshi students during the COVID-19 pandemic: a systematic review Psychol Res Behav Manag 2021 14 645 10.2147/PRBM.S315961 34104010 37. Wang Q Xu R Volkow ND Increased risk of COVID19 infection and mortality in people with mental disorders: analysis from electronic health records in the United States Psychiatry 2021 20 1 124 130 38. Pan KY Kok AA Eikelenboom M Horsfall M Jörg F Luteijn RA Penninx BW The mental health impact of the COVID-19 pandemic on people with and without depressive, anxiety, or obsessive-compulsive disorders: a longitudinal study of three Dutch case-control cohorts Lancet Psychiatry 2021 8 2 121 129 10.1016/S2215-0366(20)30491-0 33306975 39. Favreau M Hillert A Osen B Gärtner T Hunatschek S Riese M Voderholzer U Psychological consequences and differential impact of the COVID-19 pandemic in patients with mental disorders Psychiatry Res 2021 302 114045 10.1016/j.psychres.2021.114045 34126461 40. Li LZ Wang S Prevalence and predictors of general psychiatric disorders and loneliness during COVID-19 in the United Kingdom Psychiatry Res 2020 291 113267 10.1016/j.psychres.2020.113267 32623266 41. Xiong J Lipsitz O Nasri F Lui LM Gill H Phan L McIntyre RS Impact of COVID-19 pandemic on mental health in the general population: a systematic review J Affect Disord 2020 277 55 64 10.1016/j.jad.2020.08.001 32799105 42. Burrai J Roma P Barchielli B Biondi S Cordellieri P Fraschetti A Pizzimenti A Mazza C Ferracuti S Giannini AM Psychological and emotional impact of patients living in psychiatric treatment communities during Covid-19 lockdown in Italy J Clin Med 2020 9 11 3787 10.3390/jcm9113787 33238610 43. Ravens-Sieberer U Kaman A Erhart M Devine J Schlack R Otto C Impact of the COVID-19 pandemic on quality of life and mental health in children and adolescents in Germany Eur Child Adolesc Psychiatry 2022 31 6 879 889 10.1007/s00787-021-01726-5 33492480 44. Richa Gupta M Alam A Agarwal P Modified support vector machine for detecting stress level using EEG signals Comput Intell Neurosci 2020 2020 1 14 10.1155/2020/8860841 45. Gupta R Alam MA Agarwal P Whale optimization algorithm fused with SVM to detect stress in EEG signals Intell Decis Technol 2021 15 1 87 97 10.3233/IDT-200047 46. Ahmed U Lin JCW Srivastava G Fuzzy contrast set based deep attention network for lexical analysis and mental health treatment Trans Asian Low-Resour Lang Inf Process 2022 21 5 1 16 10.1145/3506701 47. Rad D Rad G Maier R Demeter E Dicu A Popa M Mărineanu VD A fuzzy logic modelling approach on psychological data J Intell Fuzzy Syst 2022 43 2 1727 1737 10.3233/JIFS-219274 48. Mental and Behavioral Health Assessment Tools. Online. Available: https://www.icanotes.com/features/charting/assessment-tools/ 49. Almeida OP Almeida SA Short versions of the geriatric depression scale: a study of their validity for the diagnosis of a major depressive episode according to ICD-10 and DSM-IV Int J Geriat Psychiatry 1999 14 10 858 865 10.1002/(SICI)1099-1166(199910)14:10<858::AID-GPS35>3.0.CO;2-8 50. Swinson RP The GAD-7 scale was accurate for diagnosing generalised anxiety disorder Evid-Based Med 2006 11 6 184 184 10.1136/ebm.11.6.184 17213178 51. Kroenke K Spitzer RL Williams JBW Kroenke K Spitzer RL Williams JB The PHQ-9: validity of a brief depression severity measure J Gen Intern Med 2021 16 9 606 613 10.1046/j.1525-1497.2001.016009606.x 52. Almeida M Shrestha AD Stojanac D Miller LJ The impact of the COVID-19 pandemic on women’s mental health Arch Women's Ment Health 2020 10.1007/s00737-020-01092-2 53. Kaushik M Guleria N The impact of pandemic COVID-19 in workplace Eur J Bus Manage 2020 12 15 1 10 54. Hu N Pan S Sun J Wang Z Mao H Mental health treatment online during the COVID-19 outbreak Eur Arch Psychiatry Clin Neurosci 2020 270 6 783 784 10.1007/s00406-020-01129-8 32361812 55. Nanath K Balasubramanian S Shukla V Islam N Kaitheri S Developing a mental health index using a machine learning approach: assessing the impact of mobility and lockdown during the COVID-19 pandemic Technol Forecast Soc Chang 2022 178 121560 10.1016/j.techfore.2022.121560 56. Faisal RA Jobe MC Ahmed O Sharker T Mental health status, anxiety, and depression levels of Bangladeshi university students during the COVID-19 pandemic Int J Mental Health Addict 2022 20 3 1500 1515 10.1007/s11469-020-00458-y
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==== Front J Assist Reprod Genet J Assist Reprod Genet Journal of Assisted Reproduction and Genetics 1058-0468 1573-7330 Springer US New York 36508034 2677 10.1007/s10815-022-02677-9 Review MicroRNAs: key regulators of the trophoblast function in pregnancy disorders Liang Lingli 1 Chen Yanjun 1 Wu Chunyan 2 Cao Zitong 1 Xia Linzhen 1 Meng Jun 3 He Lu [email protected] 4 Yang Chunfen [email protected] 4 http://orcid.org/0000-0002-5753-0358 Wang Zuo [email protected] 1 1 grid.412017.1 0000 0001 0266 8918 Institute of Cardiovascular Disease, Key Laboratory for Arteriosclerology of Hunan Province, Hunan International Scientific and Technological Cooperation Base of Arteriosclerotic Disease, Hengyang Medical College, University of South China, Hengyang, 421001 China 2 grid.412017.1 0000 0001 0266 8918 Department of Cardiovascular, The Third Affiliated Hospital of University of South China, Hengyang, 421001 China 3 grid.461579.8 Department of Function, The First Affiliated Hospital of University of South China, Hengyang, 421001 China 4 grid.461579.8 Department of Gynecology, The First Affiliated Hospital of University of South China, Hengyang, 421001 China 12 12 2022 115 23 8 2022 30 11 2022 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. The placenta is essential for a successful pregnancy and healthy intrauterine development in mammals. During human pregnancy, the growth and development of the placenta are inseparable from the rapid proliferation, invasion, and migration of trophoblast cells. Previous reports have shown that the occurrence of many pregnancy disorders may be closely related to the dysfunction of trophoblasts. However, the function regulation of human trophoblast cells in the placenta is poorly understood. Therefore, studying the factors that regulate the function of trophoblast cells is necessary. MicroRNAs (miRNAs) are small, non-coding, single-stranded RNA molecules. Increasing evidence suggests that miRNAs play a crucial role in regulating trophoblast functions. This review outlines the role of miRNAs in regulating the function of trophoblast cells and several common signaling pathways related to miRNA regulation in pregnancy disorders. Keywords MicroRNAs Trophoblast cells Placenta Pregnancy disorders the Natural Science Foundation of ChinaNo. 81970389 Liang Lingli http://dx.doi.org/10.13039/501100004735 Natural Science Foundation of Hunan Province Grant No.2021JJ30626 2022JJ30533 Liang Lingli Scientific Research Project of Hunan Provincial Department of EducationGrant No.18B283 Liang Lingli http://dx.doi.org/10.13039/501100018540 Natural Science Foundation of Guangdong Province for Distinguished Young Scholars 2022JJ30038 Liang Lingli ==== Body pmcIntroduction The placenta is the first organ for human development and is of great importance for transporting nutrients and oxygen between the mother and fetus [1, 2]. It has been reported that trophoblast cells are the main cells in the placenta [3]. The term “trophoblast” was first used in 1889 to describe the cells that exchange materials between the mother and fetus [4]. So far, trophoblasts have been extensively studied in vivo and in vitro. During human pregnancy, first, human embryonic cells differentiate into two types of cells, namely, inner cell mass (ICM) and trophectoderm (TE). Then, they develop into the embryo and the key part of the placenta, respectively [5]. In the human placenta, TE differentiates into trophoblast stem cells (TSCs), which further differentiate into a type of highly proliferative cell population called cytotrophoblasts (CTBs) [6]. On the one hand, rapidly proliferating CTBs form syncytiotrophoblast (STB) through cell fusion to transport oxygen and nutrients from maternal blood [7, 8]. On the other hand, the rapidly proliferating CTBs break away from the STB layer, invade the maternal endometrium and myometrium, and differentiate into invasive extravillous trophoblast cells (EVTs) [9], which then reshape the artery and widen the diameter to ensure that the fetus has sufficient blood supply [10–13]. Trophoblast cells have a variety of biological functions, including invasion, proliferation, migration, differentiation, apoptosis, autophagy, pyroptosis, ferroptosis, cellular metabolism, and angiogenesis [14]. Trophoblast cell function maintenance plays a key role in human placenta development. Among them, the proliferation and differentiation of trophoblast cells continue throughout the development of the human placenta [15, 16], and the migration and invasion transfer trophoblast cells to maternal decidua and myometrium and widen the inner diameter of arteries to provide nutritional support for the embryo [17, 18]. In summary, maintaining normal trophoblast cell function is essential for healthy placental development and successful pregnancy. However, so far, the regulatory factors of trophoblast cell function are largely unclear, which limits their application in the treatment of placental abnormalities or pregnancy disorders [19–22]. The biological function of human placental trophoblasts is a complex process that involves multiple regulatory factors. It has been found that many factors can regulate the growth and development of the placenta by targeting trophoblast cells, such as immune cells [23], transcription factors [24, 25], extracellular matrix components [26], and epigenetic modifications [27]. Among them, epigenetics refers to the heritable changes in gene function that ultimately lead to phenotypic changes without changes in the DNA sequence of the gene [28], and it mainly includes histone modification, DNA methylation, and non-coding RNAs (ncRNAs) [29, 30]. Several lines of evidence suggest that ncRNAs, especially miRNAs, play an important role in regulating trophoblast function [31]. Pregnancy disorders The placenta not only plays a role during pregnancy but also has a profound impact on the future health of the fetus and mother [3]. Abnormal placenta development is closely related to many pregnancy disorders [32]. It has been reported that pregnancy disorders, such as hypertensive disorders of pregnancy (HDP), intrauterine growth restriction (IUGR), gestational diabetes mellitus (GDM), unexplained stillbirth, and miscarriage account for a large proportion of morbidity and mortality in mothers and newborns [33–35]. Among them, HDP is the leading cause of maternal and perinatal death [36, 37]. There are four main forms of HDP: chronic hypertension, gestational hypertension, pre-eclampsia-eclampsia, and chronic hypertension with superimposed pre-eclampsia [37]. Notably, pre-eclampsia (PE) is the most alarming pregnancy disorder [38]. PE is defined as new-onset hypertension with proteinuria and/or end-organ dysfunction after 20 weeks of gestation [39, 40]. Eclampsia is defined as a new-onset generalized tonic–clonic seizure in women with PE and is one of the serious complications of PE [41, 42]. The development of pregnancy disorders is known as a complex process, accompanied by dynamic changes in various cells and molecules in the placenta. During human placental development, the walls of the uterine spiral arteries undergo reactive changes called vascular remodeling. When the free CTBs come into contact with the extracellular matrix, they differentiate into interstitial extravillous trophoblast cells (iEVTs) [43]. When iEVTs invade the arterial lumen, they differentiate into endovascular extravillous trophoblast cells (enEVTs) [44, 45]. Next, enEVTs degrade the media and smooth muscle and replace the endothelium in the maternal arteries to form high-volume, low-resistance vessels to ensure adequate blood flow to the placenta as the fetus grows and progresses during pregnancy (Fig. 1) [28]. Nevertheless, the failure of vascular remodeling can lead to a series of pregnancy disorders, such as PE, GDM, and IUGR [46]. Hence, trophoblast function plays a crucial role in vascular remodeling and contributes to the occurrence and development of pregnancy disorders. Understanding the functional regulation of the trophoblast is of great importance for the prevention and treatment of pregnancy disorders.Fig. 1 Remodeling of normal and abnormal spiral arteries. Extravillous trophoblast cells widen the inner diameter of the artery through invasion and migration, completing the remodeling of the spiral artery. Dysregulation of extravillous trophoblast cell migration and invasion can lead to failure of spiral arterial remodeling and inadequate fetal nutrition. ICM, inner cell mass; CTBs, cytotrophoblasts; STB, syncytiotrophoblast; iEVTs, interstitial extravillous trophoblast cells; enEVTs, extravillous trophoblast cells; NK, natural killer cell; DSC, decidual stromal cells MiRNAs in placental development and pregnancy disorders MicroRNAs (miRNAs) are small, endogenous, ncRNA molecules with gene regulatory activities [47, 48], and they play a key role in the regulation of various pathophysiological processes in the human body [49]. During embryonic development, miRNAs regulate multiple stages: gamete development, embryonic development, and placentation [50]. Trophoblasts are the main source of multiple circulating miRNAs in the peripheral blood of pregnant women [51–54], such as miR-519a-3p, miR-187-5p, miR-204-5p, and miR-449a [23]. Trophoblasts express three miRNA clusters, namely, chromosome 19 miRNA clusters (C19MC), chromosome 14 miRNA clusters (C14MC), and miR-371-3 clusters [48, 53, 55]. Studies have shown that these miRNA clusters are related to the development of the placenta [56], the expression of miRNAs in C14MC gradually decreased during pregnancy, while the expression of C19MC and miR-371-3 cluster members increased significantly [52, 57]. The above evidence suggests that miRNAs may serve as serum markers associated with human pregnancy. In addition, accumulating studies suggest that the differential expression of various circulating miRNAs during pregnancy is closely related to the occurrence and development of pregnancy disorders, such as PE, GDM, IUGR, and recurrent pregnancy loss (RPL) [58–61]. Compared with normal pregnant women, the expression profile of circulating miRNA in PE patients has changed, among which the up-regulated miRNAs were miR-125b [62], miR-182-5p [63], miR-210 [64], and miR-125a-5p [65], down-regulated miRNAs are miR-218-5p [66], miR-320a [67], miR-525-5p [68], etc. Furthermore, to date, 32 different types of circulating miRNAs have been identified that are highly differentially expressed in GDM women compared to non-GDM women [69]. Taken together, miRNAs present in the maternal circulation have the potential to provide new diagnostic and therapeutic targets for pregnancy disorders. MiRNAs regulate the trophoblast cell function in pregnancy disorders Numerous studies have demonstrated that certain members of the miRNA cluster are involved in regulating the biological function of trophoblast, especially invasion [70–72], proliferation [73, 74], migration [75], differentiation [66], apoptosis [14, 72], autophagy [76], pyroptosis [77], ferroptosis [78], cellular metabolism [79, 80], and angiogenesis of trophoblast cell [81, 82]. MiRNAs regulate trophoblast invasion Placental trophoblasts invade the connective tissue of the mother’s uterus and remodel the uterine spiral arteries, resulting in an increase in the diameter of the spiral artery and ensuring that the placenta can obtain sufficient blood supply [83, 84]. Trophoblasts’ invasion ability abnormally leads to placenta implantation failure, causing a series of pregnancy disorders, such as IUGR, PE, stillbirth, and recurrent miscarriage [17]. It was found that there are several miRNAs in the regulation invasion of trophoblast cells in pregnancy disorders [85, 86], such as miR-218-5p [66], miR-125b [62, 87], miR-182-5p [63], and miR-210 [64], which promote or inhibit the invasion of trophoblast cells by acting on target genes. Transforming growth factor-beta2 (TGF-β2) is a multifunctional polypeptide growth factor that mainly transmits signals through the complex of type I and type II serine and/or threonine receptors and plays an important role in many cellular biological processes, such as cell invasion, proliferation, differentiation, and angiogenesis. In PE placentas, miR-218-5p promoted the invasion of trophoblasts by repressing TGF-β2 expression [66]. Unlike miR-218-5p, miR-125b and miR-182-5p in the trophoblast cells of the placenta of patients with PE are significantly up-regulated [62, 63]. The voltage-gated potassium channel Kv1.1 (KCNA1), as a selective potassium channel protein in the repolarization of the cell membrane, was closely associated with trophoblast invasion. Mechanistic studies have found that miR-125b can prevent the invasion of trophoblasts by targeting KCNA1 [87]. MiR-182-5p inhibited the invasion of placental trophoblasts by down-regulating the Rnd subclass of the Rho family of small guanosine triphosphate (GTP)–binding proteins (RND3) [63]. In PE, it is well established that miR-210 is a widely studied miRNA [88, 89], miR-210 suppresses trophoblast cell invasion by down-regulating multiple target genes expression, such as potassium channel modulatory factor 1 (KCMF1), thrombospondin type-1 domain-containing 7A (THSD7A), the central scaffold protein in the bacterial ISC iron-sulfur (Fe-S) cluster biosynthesis system (ISCU), Jigged 1, and extracellular signal-regulated kinase (ERK) pathway [90, 91]. MiRNAs regulate trophoblast proliferation Appropriate trophoblast proliferation is essential for normal fetal growth and pregnancy [92]. The proliferation of trophoblasts exists at every stage in the development of the human placenta. CTBs contribute to the rapid growth of the early placenta through high-speed proliferation [93]. The proliferating trophoblast cells merge with one another to form STB, which facilitates the delivery of nutrients and oxygen in the pregnant woman to the uterus. The rapidly proliferating CTBs differentiate to form EVTs, which then invade the uterine artery and reshape the spiral artery to ensure that the fetus has sufficient perfusion [93]. However, if trophoblast proliferation is insufficient, many pregnancy disorders, such as PE, IUGR, spontaneous abortion, and placenta accrete, will inevitably occur [94]. MiRNAs are involved in the bidirectional regulation of trophoblast proliferation [95]. In pregnancy disorders, significant differences exist in the expression profiles of four miRNAs, namely, miR-137, miR-125a-5p, miR-320a, and miR-525-5p. miR-137 was significantly up-regulated in GDM, while protein kinase AMP-activated catalytic subunitα1 (PRKAA1) was down-regulated. Next, miR-137 was found to inhibit trophoblast cell proliferation by targeting the PRKAA1/interleukin-6 (IL-6) axis [96]. In PE, the expression levels of miR-125a-5p up-regulated, whereas miR-320a and miR-525-5p down-regulated [65, 67, 68, 96, 97]. MiR-125a-5p and miR-320a inhibit the proliferation of trophoblasts by targeting vascular endothelial growth factor A (VEGFA) and interleukin-4 (IL-4), respectively [65, 67, 96]. Homeobox D10 (HOXD10) is an important regulator of gene transcription and plays a crucial role in cell proliferation, survival, and invasion. The placenta of PE patients showed low expression of MiR-525-5p and high expression of HOXD10, while inhibition of MiR-52-5p/overexpression of HOXD1 inhibited proliferation and invasion of trophoblasts [68]. MiRNAs regulate trophoblast migration Proper trophoblast migration is essential for a successful pregnancy [98, 99]. In the human placenta, CTBs migrate into the endometrium and myometrium and transform into EVTs to prepare for the invasion of spiral arteries by trophoblast cells [100]. However, insufficient trophoblast migration results in hypoperfusion of the placenta [101], which may lead to a series of pregnancy disorders [102–105]. MiRNAs are involved in the regulation of trophoblast migration positively or negatively [90, 106]. Tao found that placental miR-124-3p was significantly up-regulated in PE patients, and miR-124-3p inhibited the migration of trophoblast cells by targeting the placental growth factor (PLGF). PLGF is mainly synthesized by trophoblast cells and plays an important role in promoting placental development [77]. In PE patients, miR-182-5p and miR-125a-5p expression levels were up-regulated, and trophoblast migration was inhibited by targeting RND and VEGFA3, respectively [63, 65, 107–109]. In addition, compared with normal placentas, the expression of miR-18b was down-regulated in the placental tissue of PE patients, while the level of its target gene notch homolog protein 2 (Notch2) was increased. When trophoblast cells were transfected with mimics of miR-18b, the expression level of Notch2 decreased and the migration ability of trophoblast cells was enhanced [110]. MiRNAs regulate trophoblast differentiation The development of the early placenta is under hypoxic conditions, whereas late placental development is carried out under aerobic conditions [111]. During the entire process of placental development, the rapidly proliferating CTBs continue to differentiate into STBs and EVTs to prepare sufficient nutrients and oxygen for the growth and development of the placenta [101, 112, 113]. However, if differentiation is destroyed, serious pregnancy disorders occurred [114]. MiRNAs have been demonstrated to participate in the regulation of trophoblast cell differentiation [115–117]. The most common ones are the miR-17–92 cluster and the miR-106a-363 cluster. MiR-17–92 cluster encodes six miRNAs (miR-17, miR-18a, miR-19a, miR-20a, miR-19b-1, and miR-92a-1). The miR-106a-363 cluster also encodes six miRNAs (miR-106a, miR-18b, miR-20b, miR-19b-2, miR-92a-2, and miR-363) [118]. It was found that the miR-17–92 cluster and miR-106a-363 cluster were significantly up-regulated in CTBs while down-regulated in STBs. In PE, up-regulated miR-106a and miR-19b inhibit the differentiation of placental trophoblasts by inhibiting human CYP19A1 (hCYP19A1) and human GCM1 (hGCM1) expression, respectively [118]. hCYP19A1 is closely related to the synthesis of estrogen in pregnant women, which can promote placental angiogenesis and increase uteroplacental blood flow [119–121]. Elevated levels of miR-106a and miR-19b can cause insufficient STB cells in maternal blood and decreased angiogenesis of endometrium, leading to pregnancy disorders. MiRNAs regulate trophoblast apoptosis Apoptosis is a basic biological phenomenon and a basic measure to maintain the dynamic balance of the number of cells in the body. During the embryonic development stage, excess and mission-completed cells are removed through apoptosis, thereby ensuring the normal development of the embryo. Numerous studies have discovered that proper trophoblast apoptosis is beneficial to fetus growth and development. Insufficient and excessive apoptosis of trophoblast can lead to a series of pregnancy disorders [122, 123]. It was shown that intervention of trophoblast cell apoptosis may be a direction to prevent pregnancy disorders, especially regulating by miRNAs [124]. Pregnancy disorders can occur if trophoblast apoptosis is inhibited, such as PE, GDM, and IUGR. In the placenta of patients with GDM, miR-29b inhibited trophoblast cell apoptosis by targeting the hypoxia-inducible factor 3alpha gene (HIF3A) [77, 125]. HIF3A is a negative regulator of hypoxia-inducible gene expression, which regulates many adaptive responses to low oxygen tension (hypoxia) and has been shown to play a key role in cell metabolism and apoptosis. Moreover, excessive trophoblast apoptosis also brings a series of pregnancy disorders. In PE, one of the most up-regulated miRNAs is miR-30a-3p, which promotes trophoblast apoptosis through the targeted inhibition of insulin-like growth factor 1 (IGF-1) [72, 126]. Compared with normal pregnant women, miR-141 and miR-34a were significantly up-regulated in PE; miR-141 and miR-34a promoted trophoblast apoptosis by targeting C-X-C motif chemokine ligand 12 (CXCL12β) and anti-apoptosis member B-cell CLL/lymphoma 2 (BCL-2) gene expression, respectively [72, 123, 126]. MiRNAs regulate trophoblast autophagy, pyroptosis, and ferroptosis Autophagy, a type of programmed cell death, is a physiological mechanism for maintaining cellular homeostasis and nutrient cycling. Autophagy plays a crucial role in placenta formation and embryonic development [127]. Moderate trophoblast autophagy is important for maintaining a healthy pregnancy, and inappropriate trophoblast autophagy may interfere with cellular homeostasis and lead to placental abnormalities, which can lead to a range of pregnancy disorders [128]. It was found that in PE, LET-7I inhibits trophoblast autophagy by down-regulating the expression of autophagy-related 4B cysteine peptidase (Atg4B) [129]. Notably, the placenta is not only a conduit for material exchange between mother and baby, but it also provides a physical barrier to microbial invasion. Recently, accumulating studies suggest that intrauterine viral infection is the main cause of pregnancy disorders, such as PE, repeated miscarriages (RM), and IUGR. Studies have found that trophoblast autophagy may play a key role in intrauterine viral infection, and some miRNAs in the C19MC family are involved in the regulation of trophoblast autophagy. In the placenta of patients with intrauterine virus infection, miR517-3p, miR516b-5p, and miR512-3p promote trophoblast autophagy. However, the specific molecular mechanism remains to be further studied [130]. Therefore, excessive autophagy may be an important mechanism of pregnancy disorder induced by intrauterine virus infection. Pyroptosis is a new type of programmed cell death, which is characterized by dependence on caspases (mainly caspase-1, 4, 5, 11), accompanied by inflammatory factor release [131–133]. Excessive inflammation can lead to a variety of pregnancy disorders, such as PE, premature birth, or miscarriage in pregnant women [134]. Downregulated miR-520c-3p inhibits trophoblast pyroptosis by targeting the SET domain containing lysine methyltransferase 7 (SETD7) in placental tissue from PE patients [135]. Unlike miR-520c-3p, miR-124-3p was significantly up-regulated in PE patients, and miR-124-3p promotes trophoblast pyroptosis by inhibiting the expression of PLGF [77]. Ferroptosis is a novel iron-dependent programmed cell death [136]. Ferroptosis plays a crucial role in pregnancy disorders by causing damage to trophoblast cells [136–138]. Compared with normal placental tissue, the expression of miR-30b-5p was significantly up-regulated in the placenta of patients with PE, miR-30b-5p induces the expression of Ferroportin1 (an iron exporter) by down-regulating Cys2/glutamate antiporter (system Xc − , SLC7A11), thereby reducing glutathione (GSH) synthesis and increasing iron accumulation, thereby promoting trophoblast ferroptosis. Furthermore, the knockdown of miR-30b-5p slowed the onset of PE in a rat placenta of an eclampsia model [78]. Other functions regulated by miRNAs The oxygen concentration in the early stage of placental development is relatively low [139], and trophoblast cells mainly synthesize ATP through glycolysis and lactic acid fermentation to maintain the energy supply of tissues [140]. Pieces of evidence show that miRNAs regulate trophoblast metabolism through corresponding targets to adapt to changes in oxygen levels throughout pregnancy [140]. Compared with normal pregnant women, the expression of miR-143 in the placenta of GDM patients is down-regulated, and miR-143 improves mitochondrial function by up-regulating the expression of mitochondrial complexes 1, 2, and 3, which in turn increased trophoblast metabolism to adapt to changes in oxygen levels throughout pregnancy [141]. Mitochondrial dysfunction in the placenta of patients with pregnancy disorders has been reported to be closely associated with uncontrolled oxidative stress (OS). In the placenta of GDM patients, the up-regulated miR-130b-3p contributes to its OS by targeting the inhibition of peroxisome proliferator-activated receptor-gamma co-activator-1alpha (PGC-1α) expression [142]. MiR-199a-5p, which is overexpressed in the placenta of patients with IUGR, may play a role in placental OS and mitochondrial function damage, but the mechanism remains unclear [143]. Placental vascularization is critical for meeting the metabolic demands of a rapidly growing fetus [141]. Delayed or reduced placental vascular development can lead to a variety of pregnancy disorders, such as early embryo arrest (EEA), recurrent spontaneous abortion (RSA), and PE [16]. Early growth response factor 1 (EGR1) is a nuclear transcription factor related to cell proliferation, differentiation, and angiogenesis, which is involved in the regulation of multiple biological functions. In the placenta of EEA patients, up-regulated miR-518b inhibits placental angiogenesis by targeting EGR1 [144]. Compared with normal pregnant rats, overexpressed miR-126 in the placenta of RSA model rats inhibited placental angiogenesis by inhibiting the expression of VEGF. In addition, the down-regulation of miR-126 also resulted in endothelial dysfunction of placental vessels, which further supports the importance of miR-126 in placental vascular development [145–147]. In IUGR, it has been found that deletion of the miR-290 cluster in mice leads to disturbance of the labyrinthine vasculature, which in turn inhibits angiogenesis, but the exact mechanism still needs further investigation [74]; this also provides strong evidence that miRNAs are important regulators of placental vascular development. Of note, up to now, there is no evidence that miRNAs are involved in the regulation of trophoblast angiogenesis positively. Among the ways in which miRNAs regulate the function of trophoblast cells, there are several different ways: one miRNA regulates several biological functions, or one biological function is regulated by multiple miRNAs. For example, miR-124-3p regulates migration, invasion, and apoptosis of trophoblast cells [77]. MiR-182-5p regulates trophoblast migration and invasion [63]. The invasion of trophoblasts may be regulated by multiple miRNAs, such as miR-218-5p, miR-125b, and miR-182-5p [63, 66, 87]. The proliferation of trophoblast cells is regulated by miR-137, miR-320a, miR-125a-5p, and miR-525-5p [65, 67, 68, 96]. These pieces of evidence indicate that the regulation of miRNAs is a complex network in trophoblast cells (Table 1) and miRNAs may be used as specific non-invasive biomarkers and potential targets for the treatment of pregnancy disorders.Table 1 Functions and targets of microRNAs Function Pregnancy disorders MicroRNAs Targets Positive/negative regulation References Invasion PE miR-218-5p TGF-β2 +  [66] PE miR-125b KCNA1, GPC1 −  [62] PE miR-182-5p RND3 −  [63] PE miR-525-5p HOXD10 −  [68] PE miR-210 KCMF1, THSD7AISCU, Jigged1ERK pathway −  [90, 91] PE miR-378a-5p Nodal +  [154, 155] HDP miR-140-5p TGF-β/Smad +  [156] PE miR-195 ActRIIA/ActRIIB  −  [158] IUGR miR-210-3p FGF1  −  [162] RSA miR-410-5p ITGA6  −  [163] PE miR-519d-3p MMP-2  −  [176] PE miR-20b MMP-2  −  [177] PE miR-150-5p MMP-9  −  [178] PE miR-155 CCND1/eNOS  −  [185, 186] Proliferation GDM miR-137 PRKAA1/IL-6 – [96] PE miR-125a-5p VEGFA – [65] PE miR-320a IL-4 – [67] PE miR-525-5p HOXD10 +  [68] PE miR-378a-5p Nodal +  [154, 155] RSA miR-410-5p ITGA6 – [163] PE miR-144 PTEN +  [171] Migration PE PE PE PE PE HDP RSA PE PE miR-124-3p miR-182-5p miR-125a-5p miR-18b miR-378a-5p miR-140-5p miR-410-5p miR-519d-3p miR-20b PLGF RND3 VEGFA Notch2 Nodal TGF-β/Smad ITGA6 MMP-2 MMP-2 +  – – +  +  +  – – – [77] [63] [65] [110] [154, 155] [156] [163] [176] [177] Differentiation PE miR-106a hCYP19A1 – [118] PE miR-19b hGCM1 – [118] Apoptosis GDM miR-29b HIF3A – [77, 125] PE miR-30a-3p IGF-1 +  [72, 126] PE miR-141 CXCL12β +  [123] PE miR-34a BCL-2 +  [126] Autophagy PE LET-7I Atg4B – [129] Intrauterine viral infection miR517-3p Unknown +  [130] Intrauterine viral infection miR516b-5p Unknown +  [130] Intrauterine viral infection miR512-3p Unknown +  [130] Pyroptosis PE PE miR-520c-3p miR-124-3p SETD7 PLGF – +  [135] [77] Ferroptosis PE miR-30b-5p SLC7A11 +  [78] Cellular metabolism GDM miR-143 Mitochondrial complexes 1, 2,3 +  [141] GDM miR-130b-3p PGC-1α +  [142] IUGR miR-199a-5p Unknown +  [143] Angiogenesis EEA miR-518b EGR1 – [14] RSA miR-126 VEGF – [145–147] IUGR miR-290 Unknown – [74] TGF-β2 transforming growth factor beta-2, KCNA1 the voltage-gated potassium channel Kv1.1, GPC1 glypican-1, RND3 the Rnd subclass of the Rho family of small guanosine triphosphate (GTP)–binding proteins, KCMF1 potassium channel modulatory factor 1, THSD7A thrombospondin type-1 domain-containing 7A, ISCU the central scaffold protein in the bacterial ISC iron-sulfur (Fe-S) cluster biosynthesis system, ERK extracellular signal-regulated kinase, TGF-β transforming growth factor-β, ActRIIA activin type IIA receptor, ActRIIB activin type IIB receptor, FGF1 fibroblast growth factor 1, ITGA6 the adhesion molecule integrin alpha-6, MMP-2 matrix metalloproteinase-2, MMP-9 matrix metalloproteinase-9, eNOS endothelial nitric oxide synthase, PRKAA1 protein kinase AMP-activated catalytic subunit α1, IL-6 interleukin-6, VEGFA vascular endothelial growth factor A, IL-4 interleukin (IL)-4, HOXD10 homeobox D10, PTEN tensin homolog, PLGF placental growth factor, Notch2 notch homolog protein 2, hCYP19A1 human CYP19A1, hGCM1 human GCM1, HIF3A hypoxia-inducible factor 3alpha, IGF-1 insulin-like growth factor 1, CXCL12β C-X-C motif chemokine ligand 12, BCL-2 B-cell CLL/lymphoma 2, Atg4B autophagy-related 4B cysteine peptidase, SETD7 SET domain containing lysine methyltransferase 7, SLC7A11 Cys2/glutamate antiporter, PGC-1α peroxisome proliferator-activated receptor-gamma co-activator-1 alpha, EGR1 early growth response factor 1 Related pathways of miRNA regulation of trophoblast cell function The activity and function of trophoblasts involve a variety of molecular pathways. MiRNAs play a crucial role in regulating the function of trophoblast by inhibiting or promoting gene expression in related pathways. TGF-β TGF-β is a multifunctional cytokine involved in the regulation of various cellular biological functions, such as cell invasion, proliferation, migration, differentiation, apoptosis, and autophagy [148]. TGF-β belongs to the TGF superfamily, which contains more than 30 cytokines, such as Nodal, bone morphogenetic proteins (BMPs), activins/inhibins, growth and differentiation factors (GDFs), inhibins, and anti-Müllerian hormone (AMH) [149]. The TGF-β signaling pathway involves activation of the tetramers that make up type I and type II receptors, which in turn activate and phosphorylate intracellular effectors, namely, Sma- and Mad-related proteins (SMADs) [150, 151]. Numerous studies have demonstrated that the TGF-β pathway plays a key role in regulating the invasion and migration of trophoblast cells [152–154]. Multiple cytokines in the TGF-β family are targets of aberrant miRNA expression in pregnancy disorders [150]. Compared with normal pregnant women, the expression of miR-378a-5p was significantly decreased in PE patients; miR-378a-5p promotes trophoblast invasion, proliferation, and migration by targeting Nodal [154, 155]. Up-regulated miR-140-5p in patients with HDP promotes trophoblast invasion and migration by downregulating the activity of the TGF-β/Smad pathway [156]. Activin type IIA receptor (ActRIIA) and activin type IIB receptor (ActRIIB) are target genes that regulate certain key proteins in the TGF-β pathway [157]. It was found that down-regulated miR-195 in the placenta of patients with PE inhibited trophoblast invasion by inhibiting the expressions of ActRIIA and ActRIIB [158]. Taken together, miRNAs can regulate trophoblast function by targeting the TGF-β pathway. MAPK Signal molecules related to the mitogen-activated protein kinase (MAPK) pathway are a highly conserved family of protein kinases, which plays a crucial role in signal transmission between cells [150]. The MAPK pathway primarily includes three pathways, namely, classic MAPK, c-Jun amino-terminal kinase (JNK)/p38 MAPK (JNK/p38MAPK), and extracellular signal-regulated kinase 5 (ERK5). Among them, the JNK/p38MAPK pathway is mainly related to inflammation and cell apoptosis, while the ERK pathway is related to cell invasion, proliferation, migration, and differentiation. Studies have discovered that MAPK pathway plays an important role in regulating the biological function of trophoblasts [159], especially in trophoblast cell migration and invasion [160]. Recently, accumulating studies suggest that fibroblast growth factors (FGFs) have many physiological functions. Among them, the most important is activating MAPK to promote the invasion and proliferation of trophoblast cells [161]. In IUGR, fibroblast growth factor 1 (FGF1) is the direct target of miR-210-3p. MiR-210-3p suppresses the invasion of trophoblasts by inhibiting the expression of FGF1 [162]. The adhesion molecule integrin alpha-6 (ITGA6), as a member of the integrin family, can regulate the biological function of trophoblast through MAPK signal pathway. In the placenta of RSA patients, miR-410-5p down-regulated the proliferation, migration, and invasion of trophoblast by inhibiting the expression of ITGA6 [163]. PI3K/AKT Phosphatidylinositol-3-kinase (PI3K) is a dimer composed of regulatory subunit p85 and catalytic subunit p110. PI3K, which is activated by various extracellular factors, activates protein kinase B (AKT) through phosphorylation, thereby regulating cell biological functions [164]. Many pathophysiological activities are inseparable from the PI3K/AKT pathway. However, this pathway was terminated by tensin homolog (PTEN) [165]. As a phosphatase, PTEN can dephosphorylate Akt and prevent all downstream signaling events regulated by Akt and is a negative regulator of PI3K. Moreover, studies have shown that the different expression levels of PTEN may lead to corresponding changes in cell function, especially cell proliferation [166–169]. MiRNAs have been demonstrated to participate in the regulation of trophoblast cell functions by targeting PTEN [170]. For example, compared with the normal pregnancy group, the expression of miR-144 in the placenta of PE patients was down-regulated, while the expression of PTEN was up-regulated. MiR-144 promotes trophoblast proliferation by repressing PTEN [171]. Matrix metalloproteinases Matrix metalloproteinases (MMPS) are a large family, which require Ca2+, Zn2+, and other metal ions as cofactors. Among them, matrix metalloproteinase-2 (MMP-2) and matrix metalloproteinase-9 (MMP-9) play key roles in regulating the function of trophoblast cells [172–174], especially during gestational trophoblast cell invasion [175]. MMP-2 and MMP-9 can degrade elastin, collagen, and laminin, so that they can invade the extracellular matrix of uterine decidua, integrate into the wall of the muscular spiral artery, widen the arterial wall, and ensure that the fetus gets enough nutrition. In addition, it is interesting to note that MMP-2 and MMP-9 are direct targets of many miRNAs in pregnancy-related disorders, such as miR-519d-3p, miR-20b, and miR-150-5p [86, 176, 177]. In PE, up-regulated miR-519d-3p and miR-20b target the down-regulation of MMP-2 to inhibit trophoblast migration and invasion [176, 177]. Unlike miR-519d-3p and miR-20b, miR-150-5p, which is upregulated in PE patients, promotes trophoblast invasion by targeting MMP-9 expression [178]. Other pathways In addition to the pathways discussed above, many other pathways, such as Wnt [179, 180], Notch [181, 182], EphrinB2-EphB4 [183, 184], and endothelial nitric oxide synthase (eNOS), affect the biological function of trophoblast cells. In pregnancy disorders, especially PE and IUGR, multiple dysregulated circulating miRNAs impair the biological function of trophoblast cells by targeting different signaling molecules. Accumulating evidence suggests that in pregnancy disorders, miRNAs target multiple signaling molecules to regulate the biological functions of trophoblast cells (Fig. 2) [28]. For example, compared with normal pregnant patients, the expression of miR-210 and miR-155 was up-regulated in the placenta of PE patients. miR-210 suppresses trophoblast cell invasion by down-regulating multiple target genes expressions, such as KCMF1, THSD7A, ISCU, and Jigged 1 [90]. Up-regulated miR-155 inhibits trophoblast invasion by targeting Cyclin D1 (CCND1) and eNOS expression [185, 186].Fig. 2 TGF-β pathway, MAPK pathway, and PI3K/AKT pathway. MiRNAs regulate trophoblast biological functions through TGF-β pathway, MAPK pathway, and PI3K/AKT pathway. TGF-β, transforming growth factor β; BMP, bone morphogenetic protein; GDF, growth and differentiation factor; SMAD, Sma- and Mad-related protein; ActRIIA, activin type IIA receptor; ActRIIB, activin type IIB receptor; TGF-βRII, transforming growth factor-beta receptor II; BMPR2, bone morphogenetic protein receptor-2; MAPK, mitogen-activated protein kinase; ERK, extracellular signal-regulated kinase; JNK, c-Jun NH2-terminal kinase; MAP3K, MAPK kinase; MAP2K, MAPK kinase; MLK3, mixed-lineage kinase 3; ASK1, apoptosis signal-regulating kinase 1; MEKK1, MEK kinase 1; PI3K, phosphatidylinositol-3-kinase; AKT, protein kinase B; PTEN, tensin homolog Furthermore, it is interesting to note that certain proteins in various pathways may interact with one another by activating or inhibiting other pathways. For example, the main components of the IGF-1 signal can activate MAPK pathways and jointly regulate trophoblast cell biological function [187]. Wnt and TGF-β pathways can negatively regulate the expression of MMP-2/9 and down-regulate trophoblast cell invasion [188, 189]. Conclusions and perspectives This review summarized miRNAs that target corresponding mRNAs and regulate the biological function of trophoblasts in pregnancy disorders, including trophoblast cell invasion, proliferation, migration, differentiation, apoptosis, autophagy, pyroptosis, ferroptosis, cellular metabolism, and angiogenesis through different pathways. Proper function of the trophoblast is essential for embryonic development, while the abnormal function of the trophoblast may lead to pregnancy disorders [190, 191]. Of note, pyroptosis and ferroptosis are the most studied programmed cell death modes in recent years, but few studies have investigated the regulation of miRNAs in pregnancy disorders by regulating pyroptosis and ferroptosis of trophoblast cells. Therefore, plenty of work still needs to be done in determining the types of placental miRNAs and related pathways. At present, although hundreds of different miRNAs are known to be expressed in the placental trophoblast, the pathways by which most miRNAs regulate the biological functions of trophoblast cells remain unclear. Besides, the maternal ability to maintain pregnancy and nurture the fetus also depends on the strong endocrine function of the placenta, and trophoblast cells are the main endocrine cells in the placenta. However, to date, the regulation of miRNAs on the endocrine function of trophoblast cells has not been reported. In summary, these studies indicate that more data are necessary to investigate the mechanisms by which miRNAs regulate the biological and endocrine functions of trophoblast cells. NcRNAs are a class of non-protein-coding RNAs, which mainly include miRNAs, circulating long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). Among them, numerous studies have demonstrated that miRNAs regulate the function of trophoblast cells through different targets in pregnancy and thus participate in the occurrence and development of pregnancy disorders, while the application of lncRNAs and circRNAs in the regulation of trophoblast cell function is relatively rare [192]. In addition, miRNAs are specifically expressed according to various tissues, which can be directly collected from maternal blood samples and the content is relatively stable [56, 193]. The above pieces of evidence suggest that miRNAs can serve as ideal non-intrusive biomarkers in pregnancy disorders. Therefore, in-depth exploration of the precise roles of miRNAs in the regulation of trophoblast cells and active promotion of the development of circulating miRNAs as non-invasive biomarkers for pregnancy disorders will help prevent and treat pregnancy disorders in the future. It is interesting to note that the differential expression of lncRNA and circRNA is closely related to the occurrence and development of pregnancy disorders [190, 191, 194]. For example, so far, lncRNA H19 (H19) is one of the most thoroughly studied lncRNAs [195], and H19 is closely related to the occurrence and development of PE and IUGR [192, 196, 197]. Compared with normal pregnant women, patients with early RSA have 123 differentially expressed circRNAs, of which 78 are up-regulated and 45 are down-regulated, but the specific mechanism remains unclear [191]. Therefore, the differential expression of lncRNAs and circRNAs in pregnancy diseases may be a focus for future pregnancy disorders research. Recently, accumulating studies suggest that patients with coronavirus disease 2019 (COVID‐19) share many similarities with those with pregnancy disorders. COVID-19 patients are characterized by increased expression of proinflammatory cytokines, such as IL-2, IL6, IL-17, and tumor necrosis factor-alpha (TNFα) [198, 199]. During the development of pregnancy disorders, pro-inflammatory cytokines, such as IL-1β, IL-6, IL-17, and TNFα, are also significantly increased [200, 201]. Moreover, there is an increased incidence of preterm birth and low birth weight in COVID-19-positive pregnant women [202]. In humans, miRNAs can target inflammatory factors to regulate the function of trophoblast cells, and then participate in the occurrence and development of pregnancy disorders [67]. To date, no study has investigated whether miRNAs in COVID-19-positive pregnant women can regulate pregnancy disorders by targeting the expression of related inflammatory factors. Therefore, this research gap may be the focus of future research. Author contribution ZW conceptualized and designed the original idea. LL performed literature search and analysis and wrote the first draft. YC and CW provided valuable feedback and critically revised the work. LL generated the figures and tables and revised the draft. Supervision was provided by ZC, LX, JM, LH, CY, and ZW. All authors read and approved the final manuscript. Funding This study was supported by the Natural Science Foundation of China (No. 81970389) and the Natural Science Foundation of Hunan Province China (Nos. 2021JJ30626, 2022JJ30038, 2022JJ30533) and Scientific Research Project of Hunan Provincial Department of Education (Grant No.18B283). Declarations Conflict of interest The authors declare no competing interests. Lingli Liang, Yanjun Chen, and Chunyan Wu are co-first authors. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Gamage T The role of DNA methylation in human trophoblast differentiation Epigenetics 2018 13 12 1154 1173 10.1080/15592294.2018.1549462 30475094 2. Zaga-Clavellina V Central role of the placenta during viral infection: immuno-competences and miRNA defensive responses Biochim Biophys Acta Mol Basis Dis 2021 1867 10 166182 10.1016/j.bbadis.2021.166182 34058350 3. Turco MY and Moffett A Development of the human placenta. Dev. 2019;146(22). 10.1242/dev.163428. 4. Pijnenborg R Vercruysse L A.A.W. Hubrecht and the naming of the trophoblast Placenta 2013 34 4 314 319 10.1016/j.placenta.2013.01.002 23395301 5. Piliszek A Cell fate in animal and human blastocysts and the determination of viability Mol Hum Reprod 2016 22 10 681 690 10.1093/molehr/gaw002 26769259 6. James JL Can we fix it? Evaluating the potential of placental stem cells for the treatment of pregnancy disorders Placenta 2014 35 2 77 84 10.1016/j.placenta.2013.12.010 24406265 7. Burton GJ Fowden AL The placenta: a multifaceted, transient organ Philos Trans R Soc Lond B Biol Sci 2015 370 1663 20140066 10.1098/rstb.2014.0066 25602070 8. Gamage TK Chamley LW James JL Stem cell insights into human trophoblast lineage differentiation Hum Reprod Update 2016 23 1 77 103 10.1093/humupd/dmw026 27591247 9. Prakobphol A A role for the L-selectin adhesion system in mediating cytotrophoblast emigration from the placenta Dev Biol 2006 298 1 107 117 10.1016/j.ydbio.2006.06.020 16930583 10 Burton GJ Jauniaux E What is the placenta? Am J Obstet Gynecol 2015 213 4 Suppl S6.e1 S6-8 10.1016/j.ajog.2015.07.050 11. Cross JC Genetic insights into trophoblast differentiation and placental morphogenesis Semin Cell Dev Biol 2000 11 2 105 113 10.1006/scdb.2000.0156 10873707 12. Maltepe E Fisher SJ Placenta: the forgotten organ Annu Rev Cell Dev Biol 2015 31 523 552 10.1146/annurev-cellbio-100814-125620 26443191 13. Apps R Genome-wide expression profile of first trimester villous and extravillous human trophoblast cells Placenta 2011 32 1 33 43 10.1016/j.placenta.2010.10.010 21075446 14. Hayder H MicroRNAs: crucial regulators of placental development Reproduction 2018 155 6 R259 r271 10.1530/REP-17-0603 29615475 15. Red-Horse K Trophoblast differentiation during embryo implantation and formation of the maternal-fetal interface J Clin Invest 2004 114 6 744 754 10.1172/JCI200422991 15372095 16. Reynolds LP Redmer DA Angiogenesis in the placenta Biol Reprod 2001 64 4 1033 1040 10.1095/biolreprod64.4.1033 11259247 17 Huppertz B Traditional and new routes of trophoblast invasion and their implications for pregnancy diseases Int J Mol Sci 2019 21 1 289 10.3390/ijms21010289 31906245 18. Burton GJ Uterine glands provide histiotrophic nutrition for the human fetus during the first trimester of pregnancy J Clin Endocrinol Metab 2002 87 6 2954 2959 10.1210/jcem.87.6.8563 12050279 19. Mohaupt M Molecular aspects of preeclampsia Mol Aspects Med 2007 28 2 169 191 10.1016/j.mam.2007.02.005 17412411 20. Guttmacher AE Spong CY The human placenta project: it's time for real time Am J Obstet Gynecol 2015 213 4 Suppl S3 5 10.1016/j.ajog.2015.08.037 26428502 21. Nelson DM How the placenta affects your life, from womb to tomb Am J Obstet Gynecol 2015 213 4 Suppl S12 S13 10.1016/j.ajog.2015.08.015 26428490 22. Liu Y Single-cell RNA-seq reveals the diversity of trophoblast subtypes and patterns of differentiation in the human placenta Cell Res 2018 28 8 819 832 10.1038/s41422-018-0066-y 30042384 23. Li L miRNAs in decidual NK cells: regulators worthy of attention during pregnancy Reprod Biol Endocrinol 2021 19 1 150 10.1186/s12958-021-00812-2 34600537 24. Loregger T Pollheimer J Knöfler M Regulatory transcription factors controlling function and differentiation of human trophoblast—a review Placenta 2003 24 Suppl A S104 S110 10.1053/plac.2002.0929 25. Knöfler M Pollheimer J IFPA Award in Placentology lecture: molecular regulation of human trophoblast invasion Placenta 2012 33 Suppl(2) S55 62 10.1016/j.placenta.2011.09.019 22019198 26. Damsky CH Fitzgerald ML Fisher SJ Distribution patterns of extracellular matrix components and adhesion receptors are intricately modulated during first trimester cytotrophoblast differentiation along the invasive pathway, in vivo J Clin Invest 1992 89 1 210 222 10.1172/JCI115565 1370295 27. Seitz H A large imprinted microRNA gene cluster at the mouse Dlk1-Gtl2 domain Genome Res 2004 14 9 1741 1748 10.1101/gr.2743304 15310658 28. Kohan-Ghadr HR Potential role of epigenetic mechanisms in regulation of trophoblast differentiation, migration, and invasion in the human placenta Cell Adh Migr 2016 10 1–2 126 135 10.1080/19336918.2015.1098800 26745760 29. Halusková J Epigenetic studies in human diseases Folia Biol (Praha) 2010 56 3 83 96 20653993 30. Szyf M Epigenetics, DNA methylation, and chromatin modifying drugs Annu Rev Pharmacol Toxicol 2009 49 243 263 10.1146/annurev-pharmtox-061008-103102 18851683 31. Lytle JR Yario TA Steitz JA Target mRNAs are repressed as efficiently by microRNA-binding sites in the 5' UTR as in the 3' UTR Proc Natl Acad Sci U S A 2007 104 23 9667 9672 10.1073/pnas.0703820104 17535905 32. Smith GC First-trimester determination of complications of late pregnancy JAMA 2010 303 6 561 562 10.1001/jama.2010.102 20145237 33. Brosens I The "Great Obstetrical Syndromes" are associated with disorders of deep placentation Am J Obstet Gynecol 2011 204 3 193 201 10.1016/j.ajog.2010.08.009 21094932 34. Graham W Diversity and divergence: the dynamic burden of poor maternal health Lancet 2016 388 10056 2164 2175 10.1016/S0140-6736(16)31533-1 27642022 35. Chappell LC Pre-eclampsia Lancet 2021 398 10297 341 354 10.1016/S0140-6736(20)32335-7 34051884 36. Gestational Hypertension and Preeclampsia ACOG Practice Bulletin Summary, Number 222 Obstet Gynecol 2020 135 6 1492 1495 10.1097/AOG.0000000000003892 32443077 37. Wilkerson RG Ogunbodede AC Hypertensive disorders of pregnancy Emerg Med Clin North Am 2019 37 2 301 316 10.1016/j.emc.2019.01.008 30940374 38. Hypertension in pregnancy Report of the American College of Obstetricians and Gynecologists’ Task Force on Hypertension in Pregnancy Obstet Gynecol 2013 122 5 1122 1131 24150027 39. Uludag SZ Incidence and outcomes of eclampsia: a single-center 30-year study Hypertens Pregnancy 2019 38 2 119 123 10.1080/10641955.2019.1590719 30880504 40. Leeman L Dresang LT Fontaine P Hypertensive disorders of pregnancy Am Fam Physician 2016 93 2 121 127 26926408 41. Bergman L Investigating maternal brain alterations in preeclampsia: the need for a multidisciplinary effort Curr Hypertens Rep 2019 21 9 72 10.1007/s11906-019-0977-0 31375930 42. Magley M, Hinson MR, Haddad LM. Eclampsia (Nursing). 2022 Feb 16. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022. 43. Kemp B Invasive depth of extravillous trophoblast correlates with cellular phenotype: a comparison of intra- and extrauterine implantation sites Histochem Cell Biol 2002 117 5 401 414 10.1007/s00418-002-0396-0 12029487 44. Espinoza J Normal and abnormal transformation of the spiral arteries during pregnancy J Perinat Med 2006 34 6 447 458 10.1515/JPM.2006.089 17140293 45. Anin SA Vince G Quenby S Trophoblast invasion Hum Fertil (Camb) 2004 7 3 169 174 10.1080/14647270400006911 15590570 46. Lu S Effect of 20-hydroxyeicosatetraenoic acid on biological behavior of human villous trophoblasts and uterine vascular smooth muscle cells Mol Med Rep 2014 9 5 1889 1894 10.3892/mmr.2014.2017 24604088 47. Lai EC Micro RNAs are complementary to 3' UTR sequence motifs that mediate negative post-transcriptional regulation Nat Genet 2002 30 4 363 364 10.1038/ng865 11896390 48. Bartel DP MicroRNAs: genomics, biogenesis, mechanism, and function Cell 2004 116 2 281 297 10.1016/S0092-8674(04)00045-5 14744438 49. Qu K MicroRNAs: key regulators of endothelial progenitor cell functions Clin Chim Acta 2015 448 65 73 10.1016/j.cca.2015.06.017 26116893 50. Wilkins-Haug L Epigenetics and assisted reproduction Curr Opin Obstet Gynecol 2009 21 3 201 206 10.1097/GCO.0b013e32832d7b95 19458521 51. Donker RB The expression profile of C19MC microRNAs in primary human trophoblast cells and exosomes Mol Hum Reprod 2012 18 8 417 424 10.1093/molehr/gas013 22383544 52. Morales-Prieto DM MicroRNA expression profiles of trophoblastic cells Placenta 2012 33 9 725 734 10.1016/j.placenta.2012.05.009 22721760 53. Morales-Prieto DM Elsevier Trophoblast Research Award Lecture: origin, evolution and future of placenta miRNAs Placenta 2014 35 Suppl S39 45 10.1016/j.placenta.2013.11.017 24378039 54. Yang H Clinical application of exosomes and circulating microRNAs in the diagnosis of pregnancy complications and foetal abnormalities J Transl Med 2020 18 1 32 10.1186/s12967-020-02227-w 31969163 55. Slezak-Prochazka I MicroRNAs, macrocontrol: regulation of miRNA processing RNA 2010 16 6 1087 1095 10.1261/rna.1804410 20423980 56. Morales-Prieto DM Pregnancy-associated miRNA-clusters J Reprod Immunol 2013 97 1 51 61 10.1016/j.jri.2012.11.001 23432872 57. Gu Y Differential miRNA expression profiles between the first and third trimester human placentas Am J Physiol Endocrinol Metab 2013 304 8 E836 E843 10.1152/ajpendo.00660.2012 23443922 58. Aplin JD Tracking placental development in health and disease Nat Rev Endocrinol 2020 16 9 479 494 10.1038/s41574-020-0372-6 32601352 59. Hemmatzadeh M MicroRNAs: small molecules with a large impact on pre-eclampsia J Cell Physiol 2020 235 4 3235 3248 10.1002/jcp.29286 31595979 60. Addo KA Placental microRNAs: responders to environmental chemicals and mediators of pathophysiology of the human placenta Toxicol Rep 2020 7 1046 1056 10.1016/j.toxrep.2020.08.002 32913718 61. Chaiwangyen W PM10 alters trophoblast cell function and modulates miR-125b-5p expression Biomed Res Int 2022 2022 3697944 10.1155/2022/3697944 35036432 62. Yang W miR-125b enhances IL-8 production in early-onset severe preeclampsia by targeting sphingosine-1-phosphate lyase 1 PLoS ONE 2016 11 12 e0166940 10.1371/journal.pone.0166940 27935985 63. Fang YN Highly expressed miR-182-5p can promote preeclampsia progression by degrading RND3 and inhibiting HTR-8/SVneo cell invasion Eur Rev Med Pharmacol Sci 2018 22 20 6583 6590 30402829 64. Zhang Y Elevated levels of hypoxia-inducible microRNA-210 in pre-eclampsia: new insights into molecular mechanisms for the disease J Cell Mol Med 2012 16 2 249 259 10.1111/j.1582-4934.2011.01291.x 21388517 65. Andraweera PH Placental expression of VEGF family mRNA in adverse pregnancy outcomes Placenta 2012 33 6 467 472 10.1016/j.placenta.2012.02.013 22386962 66. Brkić J MicroRNA-218-5p promotes endovascular trophoblast differentiation and spiral artery remodeling Mol Ther 2018 26 9 2189 2205 10.1016/j.ymthe.2018.07.009 30061037 67. Xie N Jia Z Li L miR-320a upregulation contributes to the development of preeclampsia by inhibiting the growth and invasion of trophoblast cells by targeting interleukin 4 Mol Med Rep 2019 20 4 3256 3264 31432141 68. Zhang M Regulatory mechanism of miR-525-5p in over-invasion of trophoblast J Obstet Gynaecol Res 2021 47 2 679 688 10.1111/jog.14581 33258220 69. Zhu W Epigenetic alternations of microRNAs and DNA methylation contribute to gestational diabetes mellitus J Cell Mol Med 2020 24 23 13899 13912 10.1111/jcmm.15984 33085184 70. Xu P Variations of microRNAs in human placentas and plasma from preeclamptic pregnancy Hypertension 2014 63 6 1276 1284 10.1161/HYPERTENSIONAHA.113.02647 24664294 71. Luo R MicroRNA-210 contributes to preeclampsia by downregulating potassium channel modulatory factor 1 Hypertension 2014 64 4 839 845 10.1161/HYPERTENSIONAHA.114.03530 24980667 72. Niu ZR MicroRNA-30a-3p is overexpressed in the placentas of patients with preeclampsia and affects trophoblast invasion and apoptosis by its effects on IGF-1 Am J Obstet Gynecol 2018 218 2 249.e1 249.e12 10.1016/j.ajog.2017.11.568 73. Yan T MicroRNA-126 regulates EPCs function: implications for a role of miR-126 in preeclampsia J Cell Biochem 2013 114 9 2148 2159 10.1002/jcb.24563 23553946 74. Paikari A The eutheria-specific miR-290 cluster modulates placental growth and maternal-fetal transport Development 2017 144 20 3731 3743 28935707 75. Zhang M Primate-specific miR-515 family members inhibit key genes in human trophoblast differentiation and are upregulated in preeclampsia Proc Natl Acad Sci U S A 2016 113 45 E7069 e7076 10.1073/pnas.1607849113 27791094 76. Delorme-Axford E Human placental trophoblasts confer viral resistance to recipient cells Proc Natl Acad Sci U S A 2013 110 29 12048 12053 10.1073/pnas.1304718110 23818581 77. Tao J MiR-124-3p promotes trophoblast cell HTR-8/SVneo pyroptosis by targeting placental growth factor Placenta 2020 101 176 184 10.1016/j.placenta.2020.08.011 33010604 78. Zhang H miR-30-5p-mediated ferroptosis of trophoblasts is implicated in the pathogenesis of preeclampsia Redox Biol 2020 29 101402 10.1016/j.redox.2019.101402 31926626 79. Muralimanoharan S MIR-210 modulates mitochondrial respiration in placenta with preeclampsia Placenta 2012 33 10 816 823 10.1016/j.placenta.2012.07.002 22840297 80. Colleoni F Suppression of mitochondrial electron transport chain function in the hypoxic human placenta: a role for miRNA-210 and protein synthesis inhibition PLoS ONE 2013 8 1 e55194 10.1371/journal.pone.0055194 23383105 81. Zhu Y MicroRNA-16 inhibits feto-maternal angiogenesis and causes recurrent spontaneous abortion by targeting vascular endothelial growth factor Sci Rep 2016 6 35536 10.1038/srep35536 27748453 82. Ji L MiR-136 contributes to pre-eclampsia through its effects on apoptosis and angiogenesis of mesenchymal stem cells Placenta 2017 50 102 109 10.1016/j.placenta.2017.01.102 28161054 83. Abbas Y Investigation of human trophoblast invasion in vitro Hum Reprod Update 2020 26 4 501 513 10.1093/humupd/dmaa017 32441309 84. Moser G Human trophoblast invasion: new and unexpected routes and functions Histochem Cell Biol 2018 150 4 361 370 10.1007/s00418-018-1699-0 30046889 85. Doridot L Trophoblasts, invasion, and microRNA Front Genet 2013 4 248 10.3389/fgene.2013.00248 24312123 86. Yu Y MicroRNA-204 suppresses trophoblast-like cell invasion by targeting matrix metalloproteinase-9 Biochem Biophys Res Commun 2015 463 3 285 291 10.1016/j.bbrc.2015.05.052 26003727 87. Li Q Elevated microRNA-125b inhibits cytotrophoblast invasion and impairs endothelial cell function in preeclampsia Cell Death Discov 2020 6 35 10.1038/s41420-020-0269-0 32435510 88. Lv Y Roles of microRNAs in preeclampsia J Cell Physiol 2019 234 2 1052 1061 10.1002/jcp.27291 30256424 89. Kolkova Z Association of circulating miRNA expression with preeclampsia, its onset, and severity Diagnostics (Basel) 2021 11 3 476 10.3390/diagnostics11030476 33800458 90. Hu XQ Zhang L MicroRNAs in uteroplacental vascular dysfunction Cells 2019 8 11 1344 10.3390/cells8111344 31671866 91. Anton L miR-210 inhibits trophoblast invasion and is a serum biomarker for preeclampsia Am J Pathol 2013 183 5 1437 1445 10.1016/j.ajpath.2013.07.021 24035613 92. Sun M Cyclin G2 is involved in the proliferation of placental trophoblast cells and their interactions with endothelial cells Med Sci Monit 2020 26 e926414 10.12659/MSM.926414 32941407 93 Ali A The role of LIN28-let-7-ARID3B pathway in placental development Int J Mol Sci 2020 21 10 3637 10.3390/ijms21103637 32455665 94. Liu M miR-518b enhances human trophoblast cell proliferation through targeting Rap1b and activating Ras-MAPK signal Front Endocrinol (Lausanne) 2018 9 100 10.3389/fendo.2018.00100 29599749 95. Arthurs AL Lumbers ER Pringle KG MicroRNA mimics that target the placental renin-angiotensin system inhibit trophoblast proliferation Mol Hum Reprod 2019 25 4 218 227 10.1093/molehr/gaz010 30869150 96. Lu TM Lu W Zhao LJ MicroRNA-137 affects proliferation and migration of placenta trophoblast cells in preeclampsia by targeting ERRα Reprod Sci 2017 24 1 85 96 10.1177/1933719116650754 27270272 97. Li J A microRNA signature in gestational diabetes mellitus associated with risk of macrosomia Cell Physiol Biochem 2015 37 1 243 252 10.1159/000430349 26302821 98. Hammer A Immunological regulation of trophoblast invasion J Reprod Immunol 2011 90 1 21 28 10.1016/j.jri.2011.05.001 21641660 99. Soares MJ Adaptive mechanisms controlling uterine spiral artery remodeling during the establishment of pregnancy Int J Dev Biol 2014 58 2–4 247 259 10.1387/ijdb.140083ms 25023691 100. Silva JF Serakides R Intrauterine trophoblast migration: a comparative view of humans and rodents Cell Adh Migr 2016 10 1–2 88 110 10.1080/19336918.2015.1120397 26743330 101. Tan D CUL4A enhances human trophoblast migration and is associated with pre-eclampsia Int J Clin Exp Pathol 2017 10 10 10544 10551 31966394 102. Tantbirojn P Crum CP Parast MM Pathophysiology of placenta creta: the role of decidua and extravillous trophoblast Placenta 2008 29 7 639 645 10.1016/j.placenta.2008.04.008 18514815 103. Bolze PA Formalised consensus of the European Organisation for Treatment of Trophoblastic Diseases on management of gestational trophoblastic diseases Eur J Cancer 2015 51 13 1725 1731 10.1016/j.ejca.2015.05.026 26092638 104. Smith JM Are national policies and programs for prevention and management of postpartum hemorrhage and preeclampsia adequate? A key informant survey in 37 countries Glob Health Sci Pract 2014 2 3 275 284 10.9745/GHSP-D-14-00034 25276587 105. Kaufmann P Black S Huppertz B Endovascular trophoblast invasion: implications for the pathogenesis of intrauterine growth retardation and preeclampsia Biol Reprod 2003 69 1 1 7 10.1095/biolreprod.102.014977 12620937 106. Awamleh Z Gloor GB Han VKM Placental microRNAs in pregnancies with early onset intrauterine growth restriction and preeclampsia: potential impact on gene expression and pathophysiology BMC Med Genomics 2019 12 1 91 10.1186/s12920-019-0548-x 31248403 107. Nadiminty N Microarray analysis reveals potential target genes of NF-kappaB2/p52 in LNCaP prostate cancer cells Prostate 2010 70 3 276 287 10.1002/pros.21062 19827050 108. Paysan L Rnd3 in cancer: a review of the evidence for tumor promoter or suppressor Mol Cancer Res 2016 14 11 1033 1044 10.1158/1541-7786.MCR-16-0164 27555595 109. Bektic J Small G-protein RhoE is underexpressed in prostate cancer and induces cell cycle arrest and apoptosis Prostate 2005 64 4 332 340 10.1002/pros.20243 15754346 110. Yang Z Extracellular vesicle-derived microRNA-18b ameliorates preeclampsia by enhancing trophoblast proliferation and migration via Notch2/TIM3/mTORC1 axis J Cell Mol Med 2021 25 10 4583 4595 10.1111/jcmm.16234 33835684 111. Chang CW Wakeland AK Parast MM Trophoblast lineage specification, differentiation and their regulation by oxygen tension J Endocrinol 2018 236 1 R43 r56 10.1530/JOE-17-0402 29259074 112. James JL Carter AM Chamley LW Human placentation from nidation to 5 weeks of gestation. Part I: what do we know about formative placental development following implantation? Placenta 2012 33 5 327 334 10.1016/j.placenta.2012.01.020 22374510 113. Pijnenborg R Vercruysse L Hanssens M The uterine spiral arteries in human pregnancy: facts and controversies Placenta 2006 27 9–10 939 958 10.1016/j.placenta.2005.12.006 16490251 114. Reister F Macrophage-induced apoptosis limits endovascular trophoblast invasion in the uterine wall of preeclamptic women Lab Invest 2001 81 8 1143 1152 10.1038/labinvest.3780326 11502865 115. Hawkins SM Buchold GM Matzuk MM Minireview: The roles of small RNA pathways in reproductive medicine Mol Endocrinol 2011 25 8 1257 1279 10.1210/me.2011-0099 21546411 116. Renthal NE miR-200 family and targets, ZEB1 and ZEB2, modulate uterine quiescence and contractility during pregnancy and labor Proc Natl Acad Sci U S A 2010 107 48 20828 20833 10.1073/pnas.1008301107 21079000 117. Williams KC MicroRNA-200a serves a key role in the decline of progesterone receptor function leading to term and preterm labor Proc Natl Acad Sci U S A 2012 109 19 7529 7534 10.1073/pnas.1200650109 22529366 118. Kumar P The c-Myc-regulated microRNA-17~92 (miR-17~92) and miR-106a~363 clusters target hCYP19A1 and hGCM1 to inhibit human trophoblast differentiation Mol Cell Biol 2013 33 9 1782 1796 10.1128/MCB.01228-12 23438603 119. Rosenfeld CR Effect of estradiol-17beta on blood flow to reproductive and nonreproductive tissues in pregnant ewes Am J Obstet Gynecol 1976 124 6 618 629 10.1016/0002-9378(76)90064-8 1258914 120. Jobe SO Estradiol-17beta and its cytochrome P450- and catechol-O-methyltransferase-derived metabolites stimulate proliferation in uterine artery endothelial cells: role of estrogen receptor-alpha versus estrogen receptor-beta Hypertension 2010 55 4 1005 1011 10.1161/HYPERTENSIONAHA.109.146399 20212268 121. Kanasaki K Deficiency in catechol-O-methyltransferase and 2-methoxyoestradiol is associated with pre-eclampsia Nature 2008 453 7198 1117 1121 10.1038/nature06951 18469803 122. Crocker IP Differences in apoptotic susceptibility of cytotrophoblasts and syncytiotrophoblasts in normal pregnancy to those complicated with preeclampsia and intrauterine growth restriction Am J Pathol 2003 162 2 637 643 10.1016/S0002-9440(10)63857-6 12547721 123. Wu D Hypoxia-induced microRNA-141 regulates trophoblast apoptosis, invasion, and vascularization by blocking CXCL12β/CXCR2/4 signal transduction Biomed Pharmacother 2019 116 108836 10.1016/j.biopha.2019.108836 31004838 124. Liu C MicroRNA-138 targets SP1 to inhibit the proliferation, migration and invasion of hepatocellular carcinoma cells Oncol Lett 2018 15 1 1279 1286 29387246 125. Sun DG The miRNA-29b is downregulated in placenta during gestational diabetes mellitus and may alter placenta development by regulating trophoblast migration and invasion through a HIF3A-dependent mechanism Front Endocrinol (Lausanne) 2020 11 169 10.3389/fendo.2020.00169 32296392 126. Guo M Elevated microRNA-34a contributes to trophoblast cell apoptosis in preeclampsia by targeting BCL-2 J Hum Hypertens 2017 31 12 815 820 10.1038/jhh.2017.65 29022890 127. Kasture V Sahay A Joshi S Cell death mechanisms and their roles in pregnancy related disorders Adv Protein Chem Struct Biol 2021 126 195 225 10.1016/bs.apcsb.2021.01.006 34090615 128. Lokeswara AW Preeclampsia: from cellular wellness to inappropriate cell death, and the roles of nutrition Front Cell Dev Biol 2021 9 726513 10.3389/fcell.2021.726513 34805141 129. Xu Y Let-7i-Induced Atg4B suppression is essential for autophagy of placental trophoblast in preeclampsia J Cell Physiol 2017 232 9 2581 2589 10.1002/jcp.25661 27770612 130. Delorme-Axford E Autophagy as a mechanism of antiviral defense at the maternal-fetal interface Autophagy 2013 9 12 2173 2174 10.4161/auto.26558 24231730 131. Wang Y Chemotherapy drugs induce pyroptosis through caspase-3 cleavage of a gasdermin Nature 2017 547 7661 99 103 10.1038/nature22393 28459430 132. Orning P Pathogen blockade of TAK1 triggers caspase-8-dependent cleavage of gasdermin D and cell death Science 2018 362 6418 1064 1069 10.1126/science.aau2818 30361383 133. Muendlein HI cFLIP(L) protects macrophages from LPS-induced pyroptosis via inhibition of complex II formation Science 2020 367 6484 1379 1384 10.1126/science.aay3878 32193329 134. Park JY Tendril extract of Cucurbita moschata suppresses NLRP3 inflammasome activation in murine macrophages and human trophoblast cells Int J Med Sci 2020 17 8 1006 1014 10.7150/ijms.39003 32410829 135. Liu Z Melatonin regulates trophoblast pyroptosis, invasion and migration in preeclampsia by inhibiting HtrA1 transcription through the microRNA-520c-3p/SETD7 axis Am J Reprod Immunol 2022 87 4 e13523 10.1111/aji.13523 35137483 136. Li Y Ischemia-induced ACSL4 activation contributes to ferroptosis-mediated tissue injury in intestinal ischemia/reperfusion Cell Death Differ 2019 26 11 2284 2299 10.1038/s41418-019-0299-4 30737476 137. Beharier O PLA2G6 guards placental trophoblasts against ferroptotic injury Proc Natl Acad Sci U S A 2020 117 44 27319 27328 10.1073/pnas.2009201117 33087576 138. Meihe L The ferroptosis-NLRP1 inflammasome: the vicious cycle of an adverse pregnancy Front Cell Dev Biol 2021 9 707959 10.3389/fcell.2021.707959 34490257 139. Pringle KG Beyond oxygen: complex regulation and activity of hypoxia inducible factors in pregnancy Hum Reprod Update 2010 16 4 415 431 10.1093/humupd/dmp046 19926662 140. Kolahi KS Valent AM Thornburg KL Cytotrophoblast, not syncytiotrophoblast, dominates glycolysis and oxidative phosphorylation in human term placenta Sci Rep 2017 7 42941 10.1038/srep42941 28230167 141. Muralimanoharan S Maloyan A Myatt L Mitochondrial function and glucose metabolism in the placenta with gestational diabetes mellitus: role of miR-143 Clin Sci (Lond) 2016 130 11 931 941 10.1042/CS20160076 26993250 142. Jiang S Role of microRNA-130b in placental PGC-1α/TFAM mitochondrial biogenesis pathway Biochem Biophys Res Commun 2017 487 3 607 612 10.1016/j.bbrc.2017.04.099 28433632 143. Meng M Whole genome miRNA profiling revealed miR-199a as potential placental pathogenesis of selective fetal growth restriction in monochorionic twin pregnancies Placenta 2020 92 44 53 10.1016/j.placenta.2020.02.002 32063549 144. Yang W Increased miRNA-518b inhibits trophoblast migration and angiogenesis by targeting EGR1 in early embryonic arrest† Biol Reprod 2019 101 4 664 674 10.1093/biolre/ioz109 31291448 145. Herbert SP Stainier DY Molecular control of endothelial cell behaviour during blood vessel morphogenesis Nat Rev Mol Cell Biol 2011 12 9 551 564 10.1038/nrm3176 21860391 146. Nicolau Y SiRNA silencing of VEGF, IGFs, and their receptors in human retinal microvascular endothelial cells Am J Transl Res 2018 10 7 1990 2003 30093937 147. Li Y Vascular endothelial growth factor-A (VEGF-A) mediates activin A-induced human trophoblast endothelial-like tube formation Endocrinol 2015 156 11 4257 4268 10.1210/en.2015-1228 148. Peng C The TGF-beta superfamily and its roles in the human ovary and placenta J Obstet Gynaecol Can 2003 25 10 834 844 10.1016/S1701-2163(16)30674-0 14532952 149. Marhemati F Transforming growth factor beta 1 (TGFβ1) polymorphisms and unexplained infertility: a genetic association study Syst Biol Reprod Med 2020 66 4 267 280 10.1080/19396368.2020.1773575 32735465 150 Gusar V MiRNAs regulating oxidative stress: a correlation with Doppler sonography of uteroplacental complex and clinical state assessments of newborns in fetal growth restriction J Clin Med 2020 9 10 3227 10.3390/jcm9103227 33050114 151. Li Y Roles of TGF-β superfamily proteins in extravillous trophoblast invasion Trends Endocrinol Metab 2021 32 3 170 189 10.1016/j.tem.2020.12.005 33478870 152. Nadeem L Nodal signals through activin receptor-like kinase 7 to inhibit trophoblast migration and invasion: implication in the pathogenesis of preeclampsia Am J Pathol 2011 178 3 1177 1189 10.1016/j.ajpath.2010.11.066 21356369 153. Fu G MicroRNA-376c impairs transforming growth factor-β and nodal signaling to promote trophoblast cell proliferation and invasion Hypertension 2013 61 4 864 872 10.1161/HYPERTENSIONAHA.111.203489 23424236 154. Luo L MicroRNA-378a-5p promotes trophoblast cell survival, migration and invasion by targeting Nodal J Cell Sci 2012 125 Pt 13 3124 3132 22454525 155. Massagué J Chen YG Controlling TGF-beta signaling Genes Dev 2000 14 6 627 644 10.1101/gad.14.6.627 10733523 156. Li JY MiR-140-5p exerts a protective function in pregnancy-induced hypertension via mediating TGF-β/Smad signaling pathway Hypertens Pregnancy 2022 41 2 116 125 10.1080/10641955.2022.2056195 35354421 157. Bai Y Downregulated miR-195 detected in preeclamptic placenta affects trophoblast cell invasion via modulating ActRIIA expression PLoS ONE 2012 7 6 e38875 10.1371/journal.pone.0038875 22723898 158. Wu H MiR-195 participates in the placental disorder of preeclampsia via targeting activin receptor type-2B in trophoblastic cells J Hypertens 2016 34 7 1371 1379 10.1097/HJH.0000000000000948 27176145 159. Qiu Q Both mitogen-activated protein kinase and phosphatidylinositol 3-kinase signalling are required in epidermal growth factor-induced human trophoblast migration Mol Hum Reprod 2004 10 9 677 684 10.1093/molehr/gah088 15235105 160. Xia Y Gene expression network analysis identifies potential targets for prevention of preeclampsia Int J Gen Med 2022 15 1023 1032 10.2147/IJGM.S348175 35140505 161. Yang QE Giassetti MI Ealy AD Fibroblast growth factors activate mitogen-activated protein kinase pathways to promote migration in ovine trophoblast cells Reproduction 2011 141 5 707 714 10.1530/REP-10-0541 21310815 162. Li L miRNA-210-3p regulates trophoblast proliferation and invasiveness through fibroblast growth factor 1 in selective intrauterine growth restriction J Cell Mol Med 2019 23 6 4422 4433 10.1111/jcmm.14335 30993882 163. Wu S The miR-410-5p /ITGA6 axis participates in the pathogenesis of recurrent abortion by regulating the biological function of trophoblast J Reprod Immunol 2022 152 103647 10.1016/j.jri.2022.103647 35667342 164. Hemmings BA Restuccia DF PI3K-PKB/Akt pathway Cold Spring Harb Perspect Biol 2012 4 9 a011189 10.1101/cshperspect.a011189 22952397 165. Tamguney T Stokoe D New insights into PTEN J Cell Sci 2007 120 Pt 23 4071 4079 10.1242/jcs.015230 18032782 166. Gregorian C PTEN dosage is essential for neurofibroma development and malignant transformation Proc Natl Acad Sci U S A 2009 106 46 19479 19484 10.1073/pnas.0910398106 19846776 167. Song L MiR-21 modulates radiosensitivity of cervical cancer through inhibiting autophagy via the PTEN/Akt/HIF-1α feedback loop and the Akt-mTOR signaling pathway Tumour Biol 2016 37 9 12161 12168 10.1007/s13277-016-5073-3 27220494 168. Wang DD miR-222 induces adriamycin resistance in breast cancer through PTEN/Akt/p27(kip1) pathway Tumour Biol 2016 37 11 15315 15324 10.1007/s13277-016-5341-2 27699665 169. Zhu DY MiR-454 promotes the progression of human non-small cell lung cancer and directly targets PTEN Biomed Pharmacother 2016 81 79 85 10.1016/j.biopha.2016.03.029 27261580 170. Kent LN FOSL1 is integral to establishing the maternal-fetal interface Mol Cell Biol 2011 31 23 4801 4813 10.1128/MCB.05780-11 21947281 171. Xiao J miR-144 may regulate the proliferation, migration and invasion of trophoblastic cells through targeting PTEN in preeclampsia Biomed Pharmacother 2017 94 341 353 10.1016/j.biopha.2017.07.130 28772212 172. Isaka K Expression and activity of matrix metalloproteinase 2 and 9 in human trophoblasts Placenta 2003 24 1 53 64 10.1053/plac.2002.0867 12495660 173. Staun-Ram E Expression and importance of matrix metalloproteinase 2 and 9 (MMP-2 and -9) in human trophoblast invasion Reprod Biol Endocrinol 2004 2 59 10.1186/1477-7827-2-59 15294019 174. Zhu J Dysregulated expression of matrix metalloproteinases and their inhibitors may participate in the pathogenesis of pre-eclampsia and fetal growth restriction Early Hum Dev 2014 90 10 657 664 10.1016/j.earlhumdev.2014.08.007 25194834 175. Anacker J Human decidua and invasive trophoblasts are rich sources of nearly all human matrix metalloproteinases Mol Hum Reprod 2011 17 10 637 652 10.1093/molehr/gar033 21565864 176. Ding J MiR-519d-3p suppresses invasion and migration of trophoblast cells via targeting MMP-2 PLoS ONE 2015 10 3 e0120321 10.1371/journal.pone.0120321 25803859 177. Jin M MicroRNA-20b inhibits trophoblast cell migration and invasion by targeting MMP-2 Int J Clin Exp Pathol 2017 10 11 10901 10909 31966433 178. Zeng Y miR-150-5p mediates extravillous trophoblast cell migration and angiogenesis functions by regulating VEGF and MMP9 Placenta 2020 93 94 100 10.1016/j.placenta.2020.02.019 32250744 179. Pollheimer J Activation of the canonical wingless/T-cell factor signaling pathway promotes invasive differentiation of human trophoblast Am J Pathol 2006 168 4 1134 1147 10.2353/ajpath.2006.050686 16565489 180. Knöfler M Pollheimer J Human placental trophoblast invasion and differentiation: a particular focus on Wnt signaling Front Genet 2013 4 190 10.3389/fgene.2013.00190 24133501 181. Zhao WX Lin JH Notch signaling pathway and human placenta Int J Med Sci 2012 9 6 447 452 10.7150/ijms.4593 22859905 182. Haider S Notch1 controls development of the extravillous trophoblast lineage in the human placenta Proc Natl Acad Sci U S A 2016 113 48 E7710 e7719 10.1073/pnas.1612335113 27849611 183. Zeng X EphrinB2-EphB4-RASA1 signaling in human cerebrovascular development and disease Trends Mol Med 2019 25 4 265 286 10.1016/j.molmed.2019.01.009 30819650 184. Dong H Role of EFNB2/EPHB4 signaling in spiral artery development during pregnancy: an appraisal Mol Reprod Dev 2016 83 1 12 18 10.1002/mrd.22593 26501487 185. Dai Y MicroRNA-155 inhibits proliferation and migration of human extravillous trophoblast derived HTR-8/SVneo cells via down-regulating cyclin D1 Placenta 2012 33 10 824 829 10.1016/j.placenta.2012.07.012 22858023 186. Li X MicroRNA-155 inhibits migration of trophoblast cells and contributes to the pathogenesis of severe preeclampsia by regulating endothelial nitric oxide synthase Mol Med Rep 2014 10 1 550 554 10.3892/mmr.2014.2214 24806148 187. Siddle K Signalling by insulin and IGF receptors: supporting acts and new players J Mol Endocrinol 2011 47 1 R1 10 10.1530/JME-11-0022 21498522 188. Qiu Q EGF-induced trophoblast secretion of MMP-9 and TIMP-1 involves activation of both PI3K and MAPK signalling pathways Reproduction 2004 128 3 355 363 10.1530/rep.1.00234 15333786 189. Li Y Activin A increases human trophoblast invasion by inducing SNAIL-mediated MMP2 up-regulation through ALK4 J Clin Endocrinol Metab 2015 100 11 E1415 E1427 10.1210/jc.2015-2134 26305619 190. Dong L Circulating CUDR, LSINCT-5 and PTENP1 long noncoding RNAs in sera distinguish patients with gastric cancer from healthy controls Int J Cancer 2015 137 5 1128 1135 10.1002/ijc.29484 25694351 191. Yue Y Sufentanil alleviates pre-eclampsia via silencing microRNA-24-3p to target 11β-hydroxysteroid dehydrogenase type 2 Bioengineered 2022 13 5 11456 11470 10.1080/21655979.2022.2066753 35506414 192 Žarković M The role of non-coding RNAs in the human placenta Cells 2022 11 9 1588 10.3390/cells11091588 35563893 193. Tsochandaridis M Circulating microRNAs as clinical biomarkers in the predictions of pregnancy complications Biomed Res Int 2015 2015 294954 10.1155/2015/294954 25699269 194. Guglas K lncRNA in HNSCC: challenges and potential Contemp Oncol (Pozn) 2017 21 4 259 266 29416430 195. Yu L The H19 gene imprinting in normal pregnancy and pre-eclampsia Placenta 2009 30 5 443 447 10.1016/j.placenta.2009.02.011 19342096 196. Lu L Methylation pattern of H19 exon 1 is closely related to preeclampsia and trophoblast abnormalities Int J Mol Med 2014 34 3 765 771 10.3892/ijmm.2014.1816 24969494 197. Tsunoda Y Expression level of long noncoding RNA H19 of normotensive placentas in late pregnancy relates to the fetal growth restriction J Obstet Gynaecol Res 2020 46 7 1025 1034 10.1111/jog.14260 32323427 198. Mehta P COVID-19: consider cytokine storm syndromes and immunosuppression Lancet 2020 395 10229 1033 1034 10.1016/S0140-6736(20)30628-0 32192578 199. Abbas AM Ahmed OA Shaltout AS COVID-19 and maternal pre-eclampsia: a synopsis Scand J Immunol 2020 92 3 e12918 10.1111/sji.12918 32542883 200. Wang M The role of IL-37 and IL-38 in obstetrics abnormalities Front Med (Lausanne) 2021 8 737084 10.3389/fmed.2021.737084 34513891 201. Donath MY Shoelson SE Type 2 diabetes as an inflammatory disease Nat Rev Immunol 2011 11 2 98 107 10.1038/nri2925 21233852 202. Jing Y Potential influence of COVID-19/ACE2 on the female reproductive system Mol Hum Reprod 2020 26 6 367 373 10.1093/molehr/gaaa030 32365180
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==== Front Lancet Reg Health Eur Lancet Reg Health Eur The Lancet Regional Health - Europe 2666-7762 The Author(s). Published by Elsevier Ltd. S2666-7762(22)00252-6 10.1016/j.lanepe.2022.100556 100556 Articles Severity of Omicron (B.1.1.529) and Delta (B.1.617.2) SARS-CoV-2 infection among hospitalised adults: A prospective cohort study in Bristol, United Kingdom Hyams Catherine abg Challen Robert bcg Marlow Robin a Nguyen Jennifer d Begier Elizabeth d Southern Jo d King Jade e Morley Anna f Kinney Jane b Clout Madeleine b Oliver Jennifer b Gray Sharon d Ellsbury Gillian d Maskell Nick f Jodar Luis d Gessner Bradford d McLaughlin John d Danon Leon bc Finn Adam ab∗ The AvonCAP Research GroupMorley Anna Langdon Amelia Turner Anabella Mattocks Anya Osborne Bethany Grimes Charli Mitchell Claire Adegbite David Bridgeman Emma Scott Emma Perkins Fiona Bayley Francesca Ruffino Gabriella Valentine Gabriella Tilzey Grace Campling James Kellett Wright Johanna Brzezinska Julia Cloake Julie Milutinovic Katarina Helliker Kate Maughan Katie Fox Kazminder Minou Konstantina Ward Lana Fleming Leah Morrison Leigh Smart Lily Wright Louise Grimwood Lucy Bellavia Maddalena Clout Madeleine Vasquez Marianne Garcia Gonzalez Maria Jeenes-Flanagan Milo Chang Natalie Grace Niall Manning Nicola Griffiths Oliver Croxford Pip Sequenza Peter Lazarus Rajeka Walters Rhian Marlow Robin Heath Robyn Antico Rupert Nammuni Arachchge Sandi Suppiah Seevakumar Mona Taslima Riaz Tawassal Mackay Vicki Maseko Zandile Taylor Zoe Friedrich Zsolt Szasz-Benczur Zsuzsa a Population Health Sciences, University of Bristol, Bristol, UK b Bristol Vaccine Centre, Population Health Sciences, University of Bristol, Bristol, UK c Engineering Mathematics, University of Bristol, Bristol, UK d Vaccines Medical Development, Scientific and Clinical Affairs, Pfizer Inc, Collegeville, PA, USA e Vaccine and Testing Team, Clinical Research Facility, UHBW NHS Trust, Bristol, UK f Academic Respiratory Unit, University of Bristol, Southmead Hospital, Bristol, UK ∗ Corresponding author. Bristol Vaccine Centre, University of Bristol, Level 6, UHB Education and Research Centre, Upper Maudlin Street, Bristol BS2 8AE, UK. g These authors contributed equally, and should be considered co-first authors. 12 12 2022 2 2023 12 12 2022 25 100556100556 29 7 2022 8 11 2022 14 11 2022 © 2022 The Author(s) 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Background There is an urgent public health need to evaluate disease severity in adults hospitalised with Delta and Omicron SARS-CoV-2 variant infections. However, limited data exist assessing severity of disease in adults hospitalised with Omicron SARS-CoV-2 infections, and to what extent patient-factors, including vaccination, age, frailty and pre-existing disease, affect variant-dependent disease severity. Methods A prospective cohort study of adults (≥18 years of age) hospitalised with acute lower respiratory tract disease at acute care hospitals in Bristol, UK conducted over 10-months. Delta or Omicron SARS-CoV-2 infection was defined by positive SARS-CoV-2 PCR and variant identification or inferred by dominant circulating variant. We constructed adjusted regression analyses to assess disease severity using three different measures: FiO2 >28% (fraction inspired oxygen), World Health Organization (WHO) outcome score >5 (assessing need for ventilatory support), and hospital length of stay (LOS) >3 days following admission for Omicron or Delta infection. Findings Independent of other variables, including vaccination, Omicron variant infection in hospitalised adults was associated with lower severity than Delta. Risk reductions were 58%, 67%, and 16% for supplementary oxygen with >28% FiO2 [Relative Risk (RR) = 0.42 (95%CI: 0.34–0.52), P < 0.001], WHO outcome score >5 [RR = 0.33 (95%CI: 0.21–0.50), P < 0.001], and to have had a LOS > 3 days [RR = 0.84 (95%CI: 0.76–0.92), P < 0.001]. Younger age and vaccination with two or three doses were also independently associated with lower COVID-19 severity. Interpretation We provide reassuring evidence that Omicron infection results in less serious adverse outcomes than Delta in hospitalised patients. Despite lower severity relative to Delta, Omicron infection still resulted in substantial patient and public health burden and an increased admission rate of older patients with Omicron which counteracts some of the benefit arising from less severe disease. Funding AvonCAP is an investigator-led project funded under a collaborative agreement by Pfizer. Keywords COVID-19 SARS-CoV-2 Respiratory infection Vaccination ==== Body pmc Research in context Evidence before this study The burden of COVID-19 on hospital services is determined by the prevalence and severity of SARS-CoV-2 variants, and modified by individual factors such as age, frailty and vaccination status. Real world data suggest that vaccine effectiveness is lower and may wane faster over time against symptomatic disease with Omicron (B.1.1.529) than with Delta (B.1.617.2) SARS-CoV-2 variant. However, numbers of hospitalisations as a case proportion during the Omicron wave have been considerably lower than previous waves. Several reports have compared the risk of hospitalisation or severe disease based on SARS-CoV-2 variant, some suggesting that Omicron is probably less severe than Delta in vaccinated and unvaccinated individuals. Added value of this study This study provides robust data assessing the relative severity of Delta and Omicron SARS-CoV-2 variants in patients admitted to hospital, including the first analysis assessing risk for any positive pressure ventilatory support, as well as risk of supplementary oxygen requirement and extended hospital admission, that may guide resource planning in hospitals. We found evidence that infection with Omicron was associated with a milder clinical course following hospital admission than that caused by Delta and that vaccination was independently associated with lower in-hospital disease severity using these three separate severity measures. Specifically, compared to Delta, Omicron-related hospitalizations were 58%, 67%, and 16% less likely to require high flow oxygen >28% FiO2, positive pressure ventilatory support or more critical care, and to have a hospital stay lasting more than three days, respectively. This study reports the considerable morbidity resulting from Omicron infection, with 18% of Omicron admissions requiring oxygen supplementation FiO2 >28%, 6% requiring positive pressure ventilation, 62% needing hospitalization ≥four days, and 4% in-hospital mortality. In determining the reduced requirement of increased oxygen requirement and total positive pressure requirement, including non-invasive ventilation, this analysis should contribute to future hospital care and service planning assessments. Implications of all the available evidence The risk of severe outcomes following SARS-CoV-2 infection is substantially lower for Omicron than for Delta, with greater reductions for more severe disease outcomes. Significant variation in risk occurs with age and vaccination status, with older and unvaccinated individuals remaining at particular risk of adverse outcome. These results highlight the importance of maintaining high levels of vaccine coverage in patient groups at risk of severe disease. The impact of lower severity Omicron-related hospitalization must be balanced against increased transmissibility and overall higher numbers of infections with this variant and there remains a substantial patient and public health burden. The increased admission rate of older patients with Omicron counteracts some of the benefit arising from less severe disease. Despite the risk reduction in high level oxygen supplementation requirement and high dependency care with Omicron compared to earlier variants at the individual level, healthcare systems could still be overwhelmed. Introduction The emergence of SARS-CoV-2 has resulted in a global pandemic, with multiple variants detected since the wild-type virus emerged. The Delta variant (B.1.617.2) was first detected in India in March 2021, spread rapidly1 and resulted in a sharp rise in SARS-CoV-2 cases in the United Kingdom. 2 The Omicron (B.1.1.529) variant, first detected in South Africa in November 2021, rapidly replaced Delta as the main circulating variant globally and resulted in a fourth wave of SARS-CoV-2 infection in the UK. By 26th December 2021, 95% of UK SARS-CoV-2 cases were estimated to be caused by Omicron. 3 SARS-CoV-2 variants may differ in their capacity to infect and transmit, susceptibility either to vaccine- or infection-derived immunity and clinical phenotype including disease severity. Laboratory data suggest that vaccine-induced neutralizing antibody activity is lower against Delta4 , 5 and Omicron variants6 , 7 than against the Alpha variant and wild/prototype viral strains. Real world data subsequently confirmed vaccine effectiveness is lower against symptomatic disease with Omicron than with Delta and other prior variants,8 , 9 with protection that may also wane faster over time.10, 11, 12, 13 However, numbers of hospitalisations as a case proportion during the Omicron wave have been considerably lower than previous waves.2 , 14 Observational data suggest that vaccines remain effective against Omicron-related hospitalization.15 , 16 Several reports11 , 17, 18, 19 have compared the risk of hospitalization or severe disease based on SARS-CoV-2 variant, some suggesting that Omicron is probably less severe than Delta in vaccinated and unvaccinated individuals.11 , 17 , 18 However, a recent preliminary report found no difference in severity between Omicron and Delta.19 While some studies have stratified results by vaccination status11 , 17 , 18 and age,17 none have comprehensively evaluated the simultaneous impact of these and other important factors (e.g., chronic medical conditions, frailty) on more detailed measures of relative clinical severity in UK hospitalized patients. In this study, we assessed the relative impact of SARS-CoV-2 variant on three separate COVID-19-related severity measures in adults hospitalised with SARS-CoV-2 infection, after adjusting for important potential confounders, including age, frailty, and vaccination status. Methods Study design and study population We are conducting a prospective cohort study of adults hospitalised with acute respiratory illness to North Bristol and University Hospitals Bristol and Weston NHS Trusts and now report those presenting 1st June 2021–28th March 2022 inclusive. All adults aged ≥18 years admitted to these hospitals were screened for respiratory disease signs/symptoms.20 Of these, patients who tested positive for COVID-19 (detailed below) were included. Details of the UK COVID-19 Vaccination Programme are provided in Supplementary Data 1. Data collection Clinical data were collected from electronic and paper patient records and recorded on an electronic case report form using REDCap software.21 Variables collected included: gender; age in years; ethnicity; patient pre-existing diseases; vaccination status; age (categorical); markers of frailty (Charlson Comorbidity Index [CCI],22 QCovid2 hazard,23 Rockwood score24); immunosuppressive therapy; residence in a care home; index of multiple deprivation (IMD); symptom duration prior to admission; hospital site and study week number. We also collected data about treatment requirement, including: hospital length of stay (LOS); need for supplementary oxygen and level of oxygen provided; requirement for positive pressure ventilatory support. Data collection was undertaken by individuals not involved in data analysis and collection of data methods were identical for patients with Omicron and Delta variant infections. Vaccination records for each study participant were obtained by team members unaware of subjects' SARS-CoV-2 test results from linked hospital and GP records, including details of vaccination brand and administration date. The QCovid2 hazard score was calculated for each admission,23 estimating risk of hospitalisation or death due to COVID-19 infection. We also determined the CCI score,22 , 25 with higher scores indicating not only a greater mortality risk but also more severe comorbid conditions, and the Rockwood frailty score,24 a 9-point scale with score ≥5 indicating frailty. Case definitions and exclusions SARS-CoV-2 infection was defined as respiratory disease and a positive test result for SARS-CoV-2 on/during hospitalisation or within 7 days prior to hospital admission, using the established UK Health Security Agency (UKHSA) diagnostic assay deployed at the time. Infection with a particular SARS-CoV-2 variant was likewise determined using the standard UKHSA variant identification methods deployed at the time. Initially, Delta was identified by S-gene positive PCR (SGTP), which was replaced on 11th May 2021 by the P681R target following validation. Omicron was identified as S-gene negative (SGNP) and then by K417N mutation.26 Cases without variant identification results admitted between the 1st June 2021 and 7th November 2021 were inferred to be Delta, and those after 7th Feb 2022 were inferred to be Omicron. These two dates represent the first date of a proven Omicron admission and the last date of a proven Delta admission in the Bristol area, respectively. Patients developing symptoms >10 days prior to hospitalisation were excluded to avoid including individuals who may have falsely tested negative for SARS-CoV-2 upon admission because they presented to hospital late in their clinical course as were individuals who had been inpatients for >28 days prior to their first positive SARS-CoV-2 PCR test. Patients who were partially vaccinated, i.e. had received only one dose or a second dose <7 days before the time of symptom onset, and those who had previously recovered from COVID-19 and had not been vaccinated, were also excluded from the analysis, as their immunological status was uncertain and would prevent meaningful comparison between vaccinated and unvaccinated individuals. Individuals were defined as unvaccinated if they had never received any COVID-19 vaccine. Immunisation with only two vaccine doses was defined as receipt of two doses with ≥7 days elapsing between symptom onset and the second dose (and no third dose). Immunisation with three doses was defined as receipt of a third vaccine dose after receiving two doses, with ≥7 days elapsing between the third dose and symptom onset. Only patients being admitted with COVID-19 for the first time were included, as repeat admissions may be expected to follow different clinical courses. Outcome and covariates The primary comparison is between cases infected with SARS-CoV-2 Delta variant and SARS-CoV-2 Omicron variant in hospitalised adults. To investigate disease severity and consider the hypothesis that Omicron is associated with less severe outcomes in patients hospitalised with COVID-19, we considered three binary outcomes measured on the seventh day following admission: (1) maximum oxygen requirement FiO2 >28%, (2) a WHO outcome score greater than 5 (i.e. ventilation or intubation required or death) within the first seven days of hospitalisation (which also implies a maximum oxygen requirement FiO2 > 28%),27 and (3) length of stay longer than three days. The WHO outcome score, or clinical progression scale is based on the level of invasive ventilation required and, in admitted patients, scores range from 4 to 10 (4 = room air, 5 = oxygen supplementation required, 6 = non-invasive positive pressure ventilation [NIPPV] usage, and 7–9 needing endotracheal intubation). A score of 10 represents death. Outcome measures were chosen to reflect different operational concerns for hospitals, in particular the adequacy of oxygen supply, availability of high dependency care, and a measure of overall hospital bed utilisation. We measured the scores at day seven to include relevant data from the hospital admission and to prevent complications with right censoring. Thresholds for the outcomes used here were determined empirically following an initial investigation, and a sensitivity analysis conducted on the level of each threshold. Charlson Comorbidity Index and age were divided into categories. For CCI the scores were categorised into none (CCI of 0), mild (1–2), moderate (3–4) or severe (5 or more) and have an approximately even spilt across the data. For age, bands of 18–34 years (y), 35–49 y, 50–64 y, 65–74 y, 75–84 y and 85 y and over, were chosen as approximately even categories with more resolution in older age groups. Statistical analysis The demographics of patients with Delta and Omicron infection were described using mean ± standard deviation (SD) or median (interquartile range [IQR]) and compared using Fisher exact tests for categorical variables, two sided Kolmogorov–Smirnov tests for continuous variables and two-sided Wilcoxon-Mann-Whitney tests for score variables. Where categorical data were missing, this comparison was performed with both missing data removed and with missing data included as a separate category (Table 1 ). There were no missing data items for continuous variables. We examined trends in patients hospitalised over the study period, determining the proportion of hospitalisations with each variant, by vaccination status (unvaccinated, two or three dose of any COVID-19 vaccine) and age group.Table 1 Baseline characteristics of adults hospitalised with Delta and Omicron SARS-CoV-2 infection. Characteristic Group Delta Omicron P-value N Value N Value Age Median [IQR] 1114 57.7 [42.6–74.1] 679 70.6 [44.8–83.5] <0.001 Gender Male 628 56.4% [53.4–59.3] 349 51.4% [47.6–55.1] 0.045 (0.045) Female 486 43.6% [40.7–46.6] 330 48.6% [44.9–52.4] Ethnicity White British 669 60.1% [57.1–62.9] 463 68.2% [64.6–71.6] 0.025 (0.020) White other 72 6.5% [5.2–8.1] 28 4.1% [2.9–5.9] Mixed origin 11 1.0% [0.6–1.8] 5 0.7% [0.3–1.7] Black 39 3.5% [2.6–4.7] 19 2.8% [1.8–4.3] Asian 45 4.0% [3.0–5.4] 21 3.1% [2.0–4.7] Other ethnicity 21 1.9% [1.2–2.9] 7 1.0% [0.5–2.1] Unknown 257 23.1% [20.7–25.6] 135 19.9% [17.1–23.0] Missing 0 0.0% [0.0–0.3] 1 0.1% [0.0–0.8] QCovid2 HR Median [IQR] 1114 11.7 [1.23–108] 679 61.9 [1.41–232] <0.001 Rockwood score Median [IQR] 1114 4 [2–10] 676 6 [4–10] <0.001 CCI category None (0) 349 31.3% [28.7–34.1] 167 24.6% [21.5–28.0] <0.001 (<0.001) Mild (1–2) 253 22.7% [20.3–25.3] 98 14.4% [12.0–17.3] Moderate (3–4) 247 22.2% [19.8–24.7] 186 27.4% [24.2–30.9] Severe (5+) 265 23.8% [21.4–26.4] 228 33.6% [30.1–37.2] Vaccination Unvaccinated 551 49.5% [46.5–52.4] 164 24.2% [21.1–27.5] <0.001 (<0.001) 2 doses 507 45.5% [42.6–48.4] 106 15.6% [13.1–18.5] 3 doses 56 5.0% [3.9–6.5] 409 60.2% [56.5–63.8] On immunosuppression No 1033 92.7% [91.1–94.1] 631 92.9% [90.8–94.6] 0.567 (0.031) Yes 81 7.3% [5.9%–8.9%] 44 6.5% [4.9%–8.6%] Missing 0 0.0% [0.0%–0.3%] 4 0.6% [0.2%–1.5%] Confidence intervals shown are the 95% binomial confidence interval for each group, compared to other groups. P-values are shown for the comparison excluding missing values, and in parentheses for the comparison including missing values as a separate category. CCI – Charlson Comorbidity Index, HR – Hazard Ratio, IQR – interquartile range, SD – standard deviation. The complex interaction between the dynamics of UK variant distribution and the progressing age-stratified booster campaign rollout was hypothesised to influence both the risk profile of patients hospitalised and severity of outcome once hospitalised. The outcomes are relatively frequent in both groups which can make interpretation of odds ratios resulting from logistic regression complex.28 Thus, we used Poisson regression with a robust error variance28 to estimate the relative risk of each of the three outcomes. The primary comparison was the impact of the variant on hospital outcomes. Other covariates were identified that might also influence, with variable distribution by variant provided (Supplementary Table S3). Covariates were screened for systematic biases due to missing data, resulting in removal of IMD (Supplementary Tables S4 and S5). Remaining missing data were imputed using the fully conditional specification approach implemented using the ‘mice’ package in R.29 Multiple imputations were performed, with full analysis repeated for each imputation. The resulting coefficients for each imputation were combined using a mixture distribution, assuming normally distributed beta coefficients. For each factor and outcome, the univariate relative risk was estimated, followed by a multivariable model of a linear combination of genomic variant, vaccination, age and CCI.22 As a sensitivity analysis these were fully adjusted using the remaining covariates, gender, ethnicity, immunosuppressive therapy, residence in a care home, duration of symptoms prior to admission, hospital site, and study week number. Additional sensitivity analyses were conducted using different combinations of age and frailty markers, including CCI as a continuous variable, Rockwood score24 and QCovid2 hazard rate (which includes age).23 Further sensitivity analyses were conducted looking at different threshold values of each of the three binary outcomes. Statistical analyses were performed in R, version 4.0.2.30 Robust Poisson regression was performed using maximum likelihood estimation of a generalised linear model (positive outcome coded as 1, negative outcome as 0). We employed a logarithmic link function, and heteroscedasticity consistent covariance matrix estimators.28 , 31 Statistical significance was defined using a 2-sided significance level of α = 0.05. We also conducted sensitivity analysis on the statistical model using quasi-Poisson and log-binomial regression giving relative risks and logistic regression giving odds ratios. Ethics and permissions Approved by the Health Research Authority Research Ethics Committee (East of England, Essex), REC 20/EE/0157, including use of Section 251 of the 2006 NHS Act authorised by the Confidentiality Advisory Group. Role of the funding source This study was conducted as a collaboration between the University of Bristol and Pfizer. The University of Bristol is the study Sponsor. The funders of the study did not play any part in data collection; they collaborated in study design, data analysis and manuscript preparation. Results During the study period reported here, 3297 hospital-admissions with SARS-CoV-2 were identified, resulting in 1938 SARS-CoV-2 positive qualifying hospitalisations: 1190 (27 inferred) with Delta variant and 748 (119 inferred) with Omicron variant. Overall, 142 (76 Delta and 66 Omicron) cases were excluded from analysis due to being partially vaccinated, or with an infection acquired in hospital, or both (Fig. 1 ).Fig. 1 Flow diagram of adults hospitalised with SARS-CoV-2 infection. Inclusion and exclusion criteria in the cohort stratified by the primary comparison or SARS-CoV-2 variant. Any patient may be excluded for multiple reasons at each stage, hence the counts of reasons for exclusion may not add up to the number of patients excluded. FiO2, fraction of inspired oxygen; LOS, length of stay; VOC, variant of concern; WHO, World Health Organisation. Patients hospitalised with Omicron variant were statistically significantly older than those with Delta infection (median [IQR]: 70.6 y [44.8y–83.5y] versus 57.7 y [42.6 y–74.1 y] respectively, P < 0.001) and had a higher CCI (4 [1–5] versus 2 [0–4] respectively, P < 0.001). These individuals were also more likely to have received a third vaccination dose (60.2% (N = 679) versus 5.0% (N = 1114) respectively, P < 0.001) (Table 1). Additional analysis investigated the nature of the additional comorbidities (Supplementary Table S1) and vaccination (Supplementary Table S2), showing that patients admitted with Omicron infection were more likely to have pre-existing heart disease, hypertension, atrial fibrillation, dementia, mild chronic kidney disease (CKD), and peripheral vascular disease than patients admitted with Delta infection (all P < 0.001). The proportion of hospitalisations with the Omicron variant increased over time, with Omicron becoming the dominant variant in the last week of December 2021 (Fig. 2 A). As the vaccination campaign progressed over the study period, we saw an increasing proportion of hospitalised individuals who had received two vaccine doses or booster (Fig. 2B). Hospital admissions occurring early in the study tended to be younger: the admission age profile shifted towards older groups with time, with a change point in late December 2021, coincident with increasing Omicron cases (Fig. 2C). Overall, the patterns suggest that patients hospitalised between December and February were generally older and frailer, but more commonly vaccinated.Fig. 2 Hospitalisations with SARS-CoV-2 infection throughout the study. (A) Daily rates of hospitalisations with Delta and Omicron SARS-CoV-2 infection, (B) 14-day rolling proportions of hospitalisations by vaccination status (excluding people partially vaccinated on admission) and (C) 14-day rolling proportions of hospitalisations by age groups (in years) throughout the study. Vertical lines represent the earliest time an Omicron case was admitted and the latest time a Delta case was admitted. Before the earliest Omicron detection, cases are assumed to be Delta when sequencing results are not available, and after the last Delta detection, cases are assumed to be Omicron, when sequencing results are not available. However, patients hospitalised with Omicron infections experienced less severe outcomes compared to patients infected with Delta. Omicron hospitalisations required ventilation less frequently (Fig. 3 A), and when they did, a lower oxygen supplement was needed (Fig. 3B). The WHO outcome score was also lower within the first seven admission days (Fig. 3C). There was no discernible difference in these outcomes between Delta and Omicron in patients ≥85 years (Fig. 3D and E). Length of hospital stay was shorter for Omicron compared to Delta among patients <70 years of age but similar for ≥70 years (Fig. 3F).Fig. 3 The detailed breakdown of the three selected indicators of severity of hospital admission stratified by SARS-CoV-2 variant, and the comparison of three binary indicators of hospital burden and their relationship to SARS-CoV-2 variant and patient age, for patients admitted to hospital. The distribution of patients (A) requiring different peak levels of oxygen supplementation, (B) with different ventilation requirements as defined by the WHO outcome or clinical progression score, and (C) with different lengths of stay. The proportion of patients who (D) require high flow oxygen >28% FiO2, (E) have a WHO outcome score>5 (requiring NIPPV), and (F) have a hospital length of stay greater than three days, as assessed on the seventh day following admission. Error bars show 95% binomial confidence intervals for each outcome, compared to other outcomes. FiO2, Fraction of inspired oxygen; LOS, length of stay; NIPPV, non-invasive positive pressure ventilation. Direct associations such as unadjusted estimates account for neither the changes in patient frailty nor vaccination status observed over the study period (Fig. 3). Fig. 4 presents results of adjusted regression models that account for these time-varying factors observed over the study duration (methods in Supplementary Tables S3–S11, results in Supplementary Tables S12, S13). Relative to Delta, patients infected with Omicron were less likely to require oxygen supplementation of FiO2 >28% [Relative risk (RR) = 0.42 (95%CI: 0.34–0.52)], to have a WHO outcome score >5 (which implies that a patient required positive pressure ventilatory support or died in the hospital) [RR = 0.33 (95%CI: 0.21–0.50)], and to have a hospital stay lasting over three days [RR = 0.84 (95%CI: 0.76–0.92)]. In stratified analyses by vaccination status, infection with Omicron relative to Delta was associated with lower severity across all three measures in both vaccinated and unvaccinated patients.Fig. 4 Robust Poisson regression model relative risks for the three indicators of hospital burden. Relative risks describing the effect of different predictors on whether patients require oxygen supplementation with FiO2 >28% (first column), have a WHO outcome score greater than 5 (second column) or who remain in hospital for more than 3 days (third column) measured on the seventh day after admission. Numerical details of these regression models, including other explanatory variables that are not our primary interest, are given in Supplementary Table S15. A comparison of relative risks computed by different methods and odds ratios by logistic regression is shown in Supplementary Table S18. FiO2 – fraction inspired oxygen, LOS – length of stay, CCI – Charlson Comorbidity Index. Compared to unvaccinated patients, individuals vaccinated with two doses were less likely to require oxygen >28% FiO2 [RR = 0.78 (95%CI: 0.68–0.89)], positive pressure ventilatory support or increased critical care [RR = 0.56 (95%CI: 0.43–0.73)], and to have a hospital admission >3 days [RR = 0.90 (95%CI: 0.84–0.98)]. Results for vaccination with three doses were similar but had wider confidence intervals than for two doses. In analyses stratified by infecting variant, vaccination was associated with lower severity of disease using all three measures for both Omicron and Delta infections. In analyses assessing potential effect modification by adding an interaction term between variant and vaccination status to adjusted models, the interaction term was not significant for any severity outcome (Supplementary Table S14). In sensitivity analyses using threshold levels of increased severity to dichotomize outcomes, the relative lower severity of Omicron declined further when using higher thresholds for oxygen requirement [FiO2 >35%: RR = 0.27 (95%CI: 0.19–0.39); FiO2 >50%: RR = 0.23 (95%CI: 0.15–0.37); Supplementary Table S15]. Sensitivity analysis using a WHO outcome score threshold >6 (hence necessitating intubation) had insufficient statistical power (Supplementary Table S16). When longer thresholds for LOS were used, the lower relative severity of Omicron attenuated as the threshold increased [LOS >5 days: RR = 0.81 (95%CI: 0.71–0.92); LOS >7 days: RR = 0.85 (95%CI: 0.73–0.99); Supplementary Table S17], suggesting certain patient characteristics may be associated with shorter admissions. For vaccination, the protective effect of vaccines increased as the severity level threshold increased for each outcome measure. Associations were similar in sensitivity analyses that replaced age group and CCI with the QCovid2 score. Discussion We found evidence that in adults hospitalised with COVID-19, Omicron infection was associated with less severe illness than that caused by Delta and that vaccination was independently associated with lower in-hospital disease severity using three separate measures of severity. Compared to Delta, Omicron-related hospitalizations were 58%, 67%, and 16% less likely to require high flow oxygen >28% FiO2, positive pressure ventilatory support or more critical care, and to have a hospital stay lasting more than three days, respectively. These findings persisted even after controlling for multiple potential confounders including age, chronic medical conditions, frailty, and increasing vaccination coverage over time. Our findings are in keeping with previously published assessment of the relative severity of Omicron variant infection compared to other variants, which examined markers of severity such as hospitalization, ICU admission, mechanical ventilation, severe disease and death.11 , 17 , 18 , 32 , 33 Lauring et al. reported lower in-hospital severity for Omicron than for Delta among unvaccinated patients and that vaccinated patients experienced less severe disease regardless of infecting variant.11 Although studies have reported lower severity for Omicron relative to Delta, measured as the risk of hospitalization17 , 18 or death17 after taking into account vaccination status, the scientific evidence continues to evolve. However, in determining the reduced requirement of increased oxygen requirement and total positive pressure requirement, including non-invasive ventilation, this analysis should contribute to future hospital care and service planning assessments. The impact of lower severity Omicron-related hospitalization must be balanced with increased transmissibility and overall higher numbers of infections with this variant. Considerable morbidity resulted from Omicron infection, with 18% of Omicron admissions requiring oxygen supplementation FiO2 >28%, 6% requiring positive pressure ventilation, 62% needing hospitalization ≥four days, and 4% in-hospital mortality. Despite individual-level risk reduction of needing increasing oxygen supplementation or high dependency care with Omicron compared to earlier variants, healthcare systems could still be overwhelmed by the sheer case numbers and resulting high hospitalization burden, especially if the less severe variant is offset by increasingly frail and elderly patients requiring hospitalization. Omicron's increased transmissibility also increases the infection risk for clinical and other hospital staff, which can take a significant toll on staffing levels. The length of hospitalization in individuals who have already developed disease severe enough to merit hospital admission is affected by multiple factors which may confound the effect of any pathogen or strain, including patient frailty and need for continued care following discharge. Other events unrelated to the patient's primary pathology, such as secondary hospital-acquired infection, may also impact discharge. Therefore, discerning the effect of variant on hospital length of admission is difficult. In contrast, the reductions in oxygen requirements and lower WHO outcome scores we observe for Omicron infections are reassuring. This suggests that exhaustion of oxygen supplies or high dependency care beds are less likely in large waves of community Omicron infection than with Delta and other previous variants. Vaccination reduces these risks further and our results suggest it is an important modifier of the impact of these aspects on health services. Our study has several strengths. All patients were admitted to hospital with acute respiratory illness caused by SARS-CoV-2, so these results are unlikely to be subject to bias caused by admission for other causes (i.e., incidental COVID-19 disease). In the UK, all national programme vaccines are provided at no cost at the point of delivery; hence our cohort is not biased by issues surrounding the cost of vaccination that are seen in fee-based systems.34 While week of symptom onset was identified as a significant univariate predictor for adverse outcome, we observe it becomes non-significant on a multivariable analysis which includes time varying factors, such as vaccination, or variant status (Supplementary Tables S6, S8, S10). This reassures us that there are no other time varying factors for which we have not accounted. With a comparatively rich data set of prospectively collected information, we can determine timing of disease onset accurately and capture information on a range of factors more precisely, such as vaccination status and patient comorbidities, than could be done using a retrospective design. However, we are limited in this study to observation of patient outcomes in patients only after hospital admission. Thus, we cannot draw conclusions about the severity of Omicron infections occurring entirely in the community. We observed a change in the demographics of patients being admitted towards more elderly and frail populations, which could be explained if community Omicron disease were especially milder in young and healthy individuals. The effects we observed for Omicron and vaccination on clinical outcomes in hospitalised patients occurred over and above any community-level effects. In this study, lineage association was only done using lineage-specific PCRs, and it was not possible to attribute a particular case to an exact sub-lineage. During the period of this analysis the Omicron sub-lineages circulating in the UK were BA.1 and to a small extent BA.2. The Delta sub-lineages were principally undifferentiated B.1.617.2 and AY.4, as shown in Supplementary Figure S1. Estimates presented here are for the combined effect of the sub-lineages. We did not have sufficient data to determine the effectiveness of any individual vaccine against the outcomes studied and our results cannot be interpreted as a vaccine effectiveness estimate. Furthermore, we did not have sufficient statistical power to determine with confidence whether booster doses of COVID-19 vaccine offered additional protection against adverse outcomes. We are unable to control for pressures in the social care system following discharge, and large waves of community Omicron infection may put pressure on community elderly care facilities resulting in a backward pressure on hospital discharges. This could partially explain our observation that length of stay longer than three days is less associated with variant status and vaccination than other outcomes. Although dexamethasone was used as treatment in both Delta and Omicron waves, novel antivirals were introduced throughout the study and this may affect results. Whilst the population of the Bristol area is representative of the UK population, it is principally Caucasian, and our findings must be interpreted in this context. Routine testing for anti-nucleocapsid antibodies was not conducted, and we therefore do not have these data available for determining previous infection status of hospitalised individuals within the Bristol area nor how our findings were impacted by population-level changes in infection-derived or hybrid immunity over time. The study design does not involve any clustering of observations, but we cannot exclude spontaneous formation of clusters in the data set due to outbreaks in the catchment area, which we can only partly mitigate by including covariates of age, CCI and vaccination status. In this prospective study, patients hospitalised with Omicron infections had lower clinical severity than those with Delta infections, as assessed by maximal oxygen requirements, a validated WHO outcome score, and hospital length of stay. Omicron infection, however, still resulted in substantial patient and public health burden following admission. Older and frail patients remain particularly susceptible to severe SARS-CoV-2 infection, underscoring the importance of maintaining high levels of vaccine coverage in this population. Understanding differences in the risk of clinical disease caused by SARS-CoV-2 variants following infection and following hospitalisation, and the role of vaccination and other factors in modifying risk, is critical for planning of public health measures. Contributors CH, RC, RM, LD, JO, JN, JM, and AF generated the research questions and analysis plan. CH, AM, JK, MC, and The AvonCAP team were involved in data collection. CH, RC, RM, LD, and AF undertook data analysis. All authors (CH, RC, RM, JN, EB, JS, JK, AM, JK, MC, JO, GE, NM, LJ, SG, BG, JMM, LD, and AF) were involved in the final manuscript preparation and its revisions before publication. AF provided oversight of the research. Data sharing statement The data used in this study are sensitive and cannot be made publicly available without breaching patient confidentiality rules. All analysis code is available on GitHub: https://doi.org/10.5281/zenodo.7220569. Declaration of interests CH is Principal Investigator of the AvonCAP study which is an investigator-led University of Bristol study funded by Pfizer and has previously received support from the NIHR in an Academic Clinical Fellowship. JO is a Co-Investigator on the AvonCAP Study. AF is a member of the Joint Committee on Vaccination and Immunization (JCVI) and chair of the World Health Organization European Technical Advisory Group of Experts on Immunization (ETAGE) committee. In addition to receiving funding from Pfizer as Chief Investigator of this study, he leads another project investigating transmission of respiratory bacteria in families jointly funded by Pfizer and the Gates Foundation. LD, RC are members of SPI-M-O subgroups of SAGE and are also partly funded through AvonCAP. LD is a Co-Investigator of the AvonCAP study and has also received funding from Pfizer, UKRI and UKHSA for unrelated projects. EB, JS, JN, SG, GE, LJ, BG, and JMM are employees of Pfizer, Inc and may hold stock or stock options. The other authors have no relevant conflicts of interest to declare. Appendix A Supplementary data Supplementary Material Supplementary Data 1 Hyams STROBE checklist Acknowledgements The authors would like to thank the UK Health Security Agency (UKHSA) Vaccine Effectiveness Working group and the University of Bristol UNCOVER group for guidance in data analysis and study design. We thank colleagues at the University of Bristol for their support with this study, including Rachel Davies, Paul Savage, Emma Foose, Susan Christie, Mark Mummé, and Adam Taylor. We want to recognise the help from Kevin Sweetland and Aman Kaur-Singh in the AvonCAP study. We would also like to acknowledge the research teams at North Bristol and University Hospitals of Bristol and Weston NHS Trusts for making this study possible, including Helen Lewis-White, Rebecca Smith, Rajeka Lazarus, Mark Lyttle, Kelly Turner, Jane Blazeby, Diana Benton, and David Wynick. We acknowledge the invaluable contributions of Alison Horne, Mai Baquedano, Stewart Robinson, David Clint, and Henry Stuart. We would also like to acknowledge all participants of the many studies undertaken to find effective vaccines against SARS-CoV-2. Funding: This study is a University of Bristol sponsored study which is funded under an investigator-led collaborative agreement by Pfizer Inc. The study funder had no role in data collection, but collaborated in study design, data interpretation and analysis and writing this manuscript. The corresponding author had full access to all data in the study and had final responsibility for the decision to submit for publication. The AvonCAP Research Group: Anna Morley, Amelia Langdon, Anabella Turner, Anya Mattocks, Bethany Osborne, Charli Grimes, Claire Mitchell, David Adegbite, Emma Bridgeman, Emma Scott, Fiona Perkins, Francesca Bayley, Gabriella Ruffino, Gabriella Valentine, Grace Tilzey, James Campling, Johanna Kellett Wright, Julia Brzezinska, Julie Cloake, Katarina Milutinovic, Kate Helliker, Katie Maughan, Kazminder Fox, Konstantina Minou, Lana Ward, Leah Fleming, Leigh Morrison, Lily Smart, Louise Wright, Lucy Grimwood, Maddalena Bellavia, Madeleine Clout, Marianne Vasquez, Maria Garcia Gonzalez, Milo Jeenes-Flanagan, Natalie Chang, Niall Grace, Nicola Manning, Oliver Griffiths, Pip Croxford, Peter Sequenza, Rajeka Lazarus, Rhian Walters, Robin Marlow, Robyn Heath, Rupert Antico, Sandi Nammuni Arachchge, Seevakumar Suppiah, Taslima Mona, Tawassal Riaz, Vicki Mackay, Zandile Maseko, Zoe Taylor, Zsolt Friedrich, Zsuzsa Szasz-Benczur. Appendix A Supplementary data related to this article can be found at https://doi.org/10.1016/j.lanepe.2022.100556. ==== Refs References 1 Challen R. Dyson L. Overton C.E. Early epidemiological signatures of novel SARS-CoV-2 variants: establishment of B.1.617.2 in England medRxiv 2021 10.1101/2021.06.05.21258365 2 Government U Coronavirus (COVID-19) in the UK https://coronavirus.data.gov.uk/details/vaccinations?areaType=overview&areaName=United%20Kingdom 2022 3 UKHSA. SARS-CoV-2 variants of concern and variants under investigation in England, technical briefing 36. 2022. 4 Wang P. Nair M.S. Liu L. Antibody resistance of SARS-CoV-2 variants B. 1.351 and B. 1.1. 7 Nature 593 7857 2021 130 135 33684923 5 Liu Y. Liu J. Xia H. Neutralizing activity of BNT162b2-elicited serum N Engl J Med 384 15 2021 1466 1468 33684280 6 Nemet I. Kliker L. Lustig Y. Third BNT162b2 vaccination neutralization of SARS-CoV-2 omicron infection N Engl J Med 386 5 2021 492 494 34965337 7 Schmidt F. Muecksch F. Weisblum Y. Plasma neutralization of the SARS-CoV-2 omicron variant N Engl J Med 386 6 2021 599 601 35030645 8 Ferguson N. Ghani A. Hinsley W. Volz E. Report 50: hospitalisation risk for omicron cases in England 2022 Imperial College London 9 Sheikh A. Kerr S. Woolhouse M. McMenamin J. Robertson C. Severity of omicron variant of concern and vaccine effectiveness against symptomatic disease: national cohort with nested test negative design study in Scotland 2021 University of Edinburgh 10 UKHSA COVID-19 vaccine surveillance report: week 11 2022 UK Government 11 Lauring A.S. Tenforde M.W. Chappell J.D. Clinical severity of, and effectiveness of mRNA vaccines against, covid-19 from omicron, delta, and alpha SARS-CoV-2 variants in the United States: prospective observational study BMJ 376 2022 e069761 12 Ferdinands J. Rao S. Dixon B. Waning 2-dose and 3-dose effectiveness of mRNA vaccines against COVID-19–associated emergency department and urgent care encounters and hospitalizations among adults during periods of delta and omicron variant predominance — VISION network, 10 states, August 2021–January 2022 MMWR Morb Mortal Wkly Rep 71 2022 255 263 35176007 13 Thompson M. Natarajan K. Sa I. Effectiveness of a third dose of mRNA vaccines against COVID-19–associated emergency department and urgent care encounters and hospitalizations among adults during periods of delta and omicron variant predominance — VISION network, 10 states, August 2021–January 2022 MMWR Morb Mortal Wkly Rep 71 2022 139 145 35085224 14 Jassat W. Abdool Karim S.S. Mudara C. Clinical severity of COVID-19 in patients admitted to hospital during the omicron wave in South Africa: a retrospective observational study Lancet Global Health 10 7 2022 E961 E969 35597249 15 Kirsebom F.C.M. Andrews N. Stowe J. COVID-19 vaccine effectiveness against the omicron (BA.2) variant in England Lancet Infect Dis 22 7 2022 931 933 35623379 16 UKHSA UHSA COVID-19 vaccine surveillance report: week 19 https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1075115/COVID-19_vaccine_surveillance_report_12_May_2022_week_19.pdf 2022 17 Nyberg T. Ferguson N.M. Nash S.G. Comparative analysis of the risks of hospitalisation and death associated with SARS-CoV-2 omicron (B.1.1.529) and delta (B.1.617.2) variants in England: a cohort study Lancet 399 10332 2022 1303 1312 35305296 18 Bager P. Wohlfahrt J. Fonager J. Risk of hospitalisation associated with infection with SARS-CoV-2 lineage B.1.1.7 in Denmark: an observational cohort study Lancet Infect Dis 21 11 2021 1507 1517 34171231 19 Strasser Z. Hadavand A. Murphy S. Estiri H. SARS-CoV-2 omicron variant is as deadly as previous waves after adjusting for vaccinations, demographics, and comorbidities Research Square 2022 10.21203/rs.3.rs-1601788/v1 20 Hyams C. Marlow R. Maseko Z. Effectiveness of BNT162b2 and ChAdOx1 nCoV-19 COVID-19 vaccination at preventing hospitalisations in people aged at least 80 years: a test-negative, case-control study Lancet Infect Dis 21 11 2021 1539 1548 34174190 21 Harris P.A. Taylor R. Thielke R. Payne J. Gonzalez N. Conde J.G. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support J Biomed Inform 42 2 2009 377 381 18929686 22 Charlson M.E. Pompei P. Ales K.L. MacKenzie C.R. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation J Chronic Dis 40 5 1987 373 383 3558716 23 Hippisley-Cox J. Coupland C.A.C. Mehta N. Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study BMJ 374 2021 n2244 34535466 24 Rockwood K. Song X. MacKnight C. A global clinical measure of fitness and frailty in elderly people Can Med Assoc J 173 5 2005 489 495 16129869 25 Physicians RCo National Early Warning Score (NEWS) 2: standardising the assessment of acute-illness severity in the NHS. Updated report of a working party 2017 RCP London 26 UKHSA. SARS-CoV-2 variants of concern and variants under investigation in England, technical briefing 33, 2021. 27 Characterisation WHOWGotC, Management of C-i A minimal common outcome measure set for COVID-19 clinical research Lancet Infect Dis 20 8 2020 e192 e197 32539990 28 Zou G. A modified Poisson regression approach to prospective studies with binary data Am J Epidemiol 159 7 2004 702 706 15033648 29 van Buuren S. Groothuis-Oudshoorn K. mice: multivariate imputation by chained equations in R J Stat Software 45 3 2011 1 67 30 Team RC R: A language and environment for statistical computing 2014 Computing RFfS Vienna, Austria 31 Zeileis A. Köll S. Graham N. Various versatile variances: an object-oriented implementation of clustered covariances in R J Stat Software 95 1 2020 1 36 32 Lewnard J.A. Hong V.X. Patel M.M. Kahn R. Lipsitch M. Tartof S.Y. Clinical outcomes associated with SARS-CoV-2 Omicron (B.1.1.529) variant and BA.1/BA.1.1 or BA.2 subvariant infection in southern California Nat Med 28 9 2022 1933 1943 35675841 33 Van Goethem N. Chung P.Y. Meurisse M. Clinical severity of SARS-CoV-2 omicron variant compared with delta among hospitalized COVID-19 patients in Belgium during Autumn and Winter season 2021–2022 Viruses 14 6 2022 1297 35746768 34 Wheelock A. Miraldo M. Thomson A. Vincent C. Sevdalis N. Evaluating the importance of policy amenable factors in explaining influenza vaccination: a cross-sectional multinational study BMJ Open 7 7 2017 e014668
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==== Front Anaesth Crit Care Pain Med Anaesth Crit Care Pain Med Anaesthesia, Critical Care & Pain Medicine 2352-5568 Société française d'anesthésie et de réanimation (Sfar). Published by Elsevier Masson SAS. S2352-5568(22)00163-1 10.1016/j.accpm.2022.101182 101182 Editorial COVID-19 pneumonia: Therapeutic implications of its atypical features Gattarello Simone ab Camporota Luigi c Gattinoni Luciano b⁎ a Anesthesia and Intensive Care Medicine, IRCCS San Raffaele Scientific Institute, Milan, Italy b Department of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany c Guy’s and St Thomas’ NHS Foundation Trust, Department of Adult Critical Care, London, United Kingdom ⁎ Corresponding author at: Department of Anesthesiology, University Medical Center Göttingen, Robert Koch Strasse 40, 37075 Göttingen, Germany. 6 12 2022 2 2023 6 12 2022 42 1 101182101182 © 2022 Société française d'anesthésie et de réanimation (Sfar). Published by Elsevier Masson SAS. All rights reserved. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Keywords ARDS COVID-19 CARDS Mechanical ventilation Abbreviations C-ARDS, COVID-19 Acute Respiratory Distress Syndrome P-SILI, Patient Self-Induced Lung Injury ==== Body pmcIn a recent systematic review and meta-analysis, Reddy et al. [1] refuted the presence of “phenotypes” in patients with COVID-19 Acute Respiratory Distress Syndrome (C-ARDS), given that the distribution in their respiratory system compliance was near-Gaussian rather than bimodal. Consequently, they concluded that no change in conventional lung-protective ventilation strategies is warranted in C-ARDS, compared to standard ARDS. In the accompanying editorial, Schultz et al., supporting the same conclusion, warned: “we should always take a cautious approach when interpreting small case series, and we should change practice only on the basis of firm evidence” [2]. Historically, the advances in clinical medical research have been driven by two different approaches: (a) physiological, in which the research focus is to identify the physiological phenomenon underlying a specific clinical condition, usually tested on a restricted cohort of extensively studied individuals; and (b) epidemiological/statistical, in which the study hypothesis is tested in a large number of individuals, in order to confirm or reject a set of prespecified clinical outcomes on a probabilistic ground. The debate on typical or atypical ARDS for COVID-19 respiratory failure is an example that reflects these two different approaches. The relevance of this controversy, however, is not merely academic but carries important practical implications, which may affect patient outcomes. Ashbaugh et al., pertaining to the generation of the physiological approach, fully described the main features of ARDS based on a cohort of twelve individuals [3]. In that landmark paper, the authors referred to the following clinical features to define the presence of ARDS: refractory hypoxemia, (i.e., the inability to maintain 100 mmHg of arterial blood oxygenation even when breathing at 100% oxygen); reduced respiratory compliance, and bilateral and patchy lung infiltrates on chest X-ray. The great fortune of ARDS as an entity is deeply related to the birth of the intensive care units, a unique highly technological environment where these patients could be kept alive. Therefore, despite being a syndrome, ARDS became the “intensive care disease”. Indeed, regardless of its origin, the physiological and clinical features of patients with ARDS are similar and require a similar symptomatic approach: mechanical ventilation, whose ultimate goal is to “buy time” while the underlying disease is reversed. Because mechanical ventilation is a symptomatic therapy, the “best” mechanical ventilation treatment is the one that corrects life-threatening symptoms, such as severe hypoxemia, without contributing to further lung damage. Decades of basic, translational, and clinical research led to a simple conclusion: to decrease stress and strain. This can be achieved by applying a near-normal tidal volume of 6 mL.kg−1 [4] to prone-positioned patients with moderate-severe disease [5], thus allowing a more even distribution of stress and strain throughout the lung parenchyma [6]; and applying a moderate-high PEEP [7], according to the ‘open-lung’ concept [8]. These indications are the core of lung protective strategies, although the use of high PEEP is controversial, and proved harmful when set above 15 cmH2O [9]. In this context, in 2019 a new disease spread from China across the globe, leading to clinical conditions that, in several cases, fulfilled the ARDS criteria (hypoxemia and bilateral chest x-ray infiltrations) [10]. COVID-19 pneumonia is a specific disease with a well-defined etiology, and whose pathogenetic mechanisms are being progressively deciphered. During the first wave of the pandemic, the immediate reaction of the intensive care community was to apply a standard “lung protective strategy”, which includes low tidal volume and prone positioning. Due to the severity of hypoxemia, high PEEP was often used [11], as recommended by some authorities [12], and the COVID-19 Sepsis Surviving Campaign guidelines [13]. Unfortunately, because of the number of cases and the enormous strain on healthcare resources, little time for a careful understanding of COVID-19 pathophysiology and its possible implications for treatment was available. Indeed, the common clinical feature since the beginning of the pandemic – so common as to be also reported by the media – was the striking hypoxemia (with PaO2/FiO2 as low as <100 mmHg, as the refractory hypoxemia defined by Ashbaugh) in patients whose lungs were easy to ventilate, even at low airway pressures. Data from the lung CT scans performed in the early stages of COVID-19 disease showed high lung-gas volume and fraction of normally aerated tissue [14] despite the presence of severe hypoxemia. This is in sharp contrast with the typical ARDS, in which the hypoxemia is correlated with the size of the “baby lung”. The COVID-19 disease is characterized by ARDS with an “adult-size lung”, and its main characteristic is the uncoupling between lung mechanics/gas volume and gas exchange. The simultaneous presence of near-normal gas volumes (whose respiratory system compliance is a surrogate) and severe hypoxemia implies that the mechanisms underlying a decreased oxygenation in COVID-19 are different from the intrapulmonary right-to-left shunt, which is the primary cause of hypoxemia in typical ARDS. Briefly, there is growing evidence that the mechanisms of hypoxemia in COVID-19 are perfusion alterations with loss of hypoxic vasoconstriction, embolism, and, more relevant, the opening of intra-bronchial shunts, whose presence has been documented in pathological samples [15]. The lack of intrapulmonary shunt (i.e., atelectasis/consolidation) in early C-ARDS is incongruous with the use of high PEEP levels, whose effect will be detrimental to the hemodynamic and renal function. The studies summarized in the meta-analysis by Reddy et al. reported, however, respiratory mechanics values similar to the typical ARDS, implying that C-ARDS is also associated with low gas volumes and a “baby lung” [1]. So, how can we reconcile these observations with those reporting impressive dissociations between respiratory mechanics (near-normal compliance and low non-aerated lung tissue) and the degree of hypoxemia [16], [17]? Two possible reasons may account for this discrepancy. First, the respiratory system compliance usually reported in the literature is measured at “clinical PEEP”, which may lead to a substantial bias. Indeed, even a subject with healthy lungs (and expected normal compliance) would show low compliance if measured at high PEEP. Therefore, the condition in which respiratory system compliance is measured may lead to a severe underestimation of its actual value in the presence of near-normal lung gas volume. Second, the patients included in large trials are studied at different stages of COVID-19 disease. Over time, if the course of the disease is not modified by treatment, the evolution of the lung toward fibrosis is almost unavoidable, with associated decreased respiratory system compliance. In COVID-19 disease, the incidence of pneumothorax and pneumomediastinum are far more commonly reported than in typical ARDS, both in spontaneously breathing patients and in those undergoing mechanical ventilation [18]. It was previously reported that high-volume ventilation, even in spontaneously breathing subjects, leads to significant lung damage [19], and this process was recently defined as Patient Self-Induced Lung Injury (P-SILI) [20]. During COVID-19 disease, two concomitant processes may occur simultaneously: the natural progression of the disease and the presence of P-SILI dictated by an excessive respiratory drive and associated elevated stress and strain. It is astonishing the paucity of data relative to the esophageal (i.e., pleural) pressure measurements, albeit a high tidal esophageal pressure should indicate sedation and controlled mechanical ventilation in COVID-19 patients at this stage. Regardless of the discussion on whether COVID-19 disease is typical ARDS or not, the optimal treatment for COVID-19 disease is likely to be better identified when the following variables are assessed and measured: tidal volume, lung gas volume, and esophageal pressure (and the derived lung mechanics calculated). From this perspective, a small study enrolling a reduced number of individuals in which an extended set of measures is collected may provide more relevant information than large observational studies or a big randomized trial. Conflicts of interest None for issues related to this article. ==== Refs References 1 Reddy M.P. Subramaniam A. Chua C. Ling R.R. Anstey C. Ramanathan K. Respiratory system mechanics, gas exchange, and outcomes in mechanically ventilated patients with COVID-19-related acute respiratory distress syndrome: a systematic review and meta-analysis Lancet Respir Med 10 12 2022 1178 1188 10.1016/S2213-2600(22)00393-9 S2213-2600(22)00393-00399 36335956 2 Schultz M.J. van Meenen D.M. Bos L.D. COVID-19-related acute respiratory distress syndrome: lessons learned during the pandemic Lancet Respir Med 10 12 2022 1108 1110 10.1016/S2213-2600(22)00401-5 S2213-2600(22)00401-00405 36335954 3 Ashbaugh D.G. Bigelow D.B. Petty T.L. Levine B.E. Acute respiratory distress in adults Lancet 2 7511 1967 319 323 10.1016/s0140-6736(67)90168-7 4143721 4 Acute Respiratory Distress Syndrome Network Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome N Engl J Med 342 2000 1301 1308 10.1056/NEJM200005043421801 10793162 5 Guérin C. Reignier J. Richard J.C. Beuret P. Gacouin A. Boulain T. Prone positioning in severe acute respiratory distress syndrome N Engl J Med 368 2013 2159 2168 10.1056/NEJMoa1214103 23688302 6 Gattinoni L. Taccone P. Carlesso E. Marini J.J. Prone position in acute respiratory distress syndrome. Rationale, indications, and limits Am J Respir Crit Care Med 188 2013 1286 1293 10.1164/rccm.201308-1532CI 24134414 7 Briel M. Meade M. Mercat A. Brower R.G. Talmor D. Walter S.D. Higher vs lower positive end-expiratory pressure in patients with acute lung injury and acute respiratory distress syndrome: systematic review and meta-analysis JAMA 303 2010 865 873 10.1001/jama.2010.218 20197533 8 Lachmann B. Open up the lung and keep the lung open Intensive Care Med 18 1992 319 321 10.1007/BF01694358 1469157 9 Writing Group for the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial (ART) Investigators Effect of lung recruitment and titrated Positive End-Expiratory Pressure (PEEP) vs low PEEP on mortality in patients with acute respiratory distress syndrome: a randomized clinical trial JAMA 318 2017 1335 1345 10.1001/jama.2017.14171 28973363 10 ARDS Definition Task Force Acute respiratory distress syndrome: the Berlin definition JAMA 307 2012 2526 2533 10.1001/jama.2012.5669 22797452 11 Grasselli G. Zangrillo A. Zanella A. Antonelli M. Cabrini L. Castelli A. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy JAMA 323 16 2020 1574 1581 10.1001/jama.2020.5394 32250385 12 National Institutes of Health: COVID-19 Treatment Guidelines Panel. Coronavirus disease 2019 (COVID-19) treatment guidelines. https://www.covid19treatmentguidelines.nih.gov/. [Accessed 21 November 2022]. 13 Alhazzani W. Møller M.H. Arabi Y.M. Loeb M. Gong M.N. Fan E. Surviving sepsis campaign: guidelines on the management of critically ill adults with coronavirus disease 2019 (COVID-19) Intensive Care Med 46 5 2020 854 887 10.1007/s00134-020-06022-5 [Epub 28 March 2020] 32222812 14 Gattinoni L. Coppola S. Cressoni M. Busana M. Rossi S. Chiumello D. COVID-19 does not lead to a “typical” acute respiratory distress syndrome Am J Respir Crit Care Med 201 2020 1299 1300 10.1164/rccm.202003-0817LE 32228035 15 Galambos C. Bush D. Abman S.H. Intrapulmonary bronchopulmonary anastomoses in COVID-19 respiratory failure Eur Respir J 58 2021 10.1183/13993003.04397-2020 2004397 16 Chiumello D. Busana M. Coppola S. Romitti F. Formenti P. Bonifazi M. Physiological and quantitative CT-scan characterization of COVID-19 and typical ARDS: a matched cohort study Intensive Care Med 46 2020 2187 2196 10.1007/s00134-020-06281-2 33089348 17 Rello J. Storti E. Belliato M. Serrano R. Clinical phenotypes of SARS-CoV-2: implications for clinicians and researchers Eur Respir J 55 2020 10.1183/13993003.01028-2020 2001028 18 Paternoster G. Belmonte G. Scarano E. Rotondo P. Palumbo D. Belletti A. Macklin effect on baseline chest CT scan accurately predicts barotrauma in COVID-19 patients Respir Med 197 2022 10.1016/j.rmed.2022.106853 106853 19 Mascheroni D. Kolobow T. Fumagalli R. Moretti M.P. Chen V. Buckhold D. Acute respiratory failure following pharmacologically induced hyperventilation: an experimental animal study Intensive Care Med 15 1988 8 14 10.1007/BF00255628 3230208 20 Brochard L. Slutsky A. Pesenti A. Mechanical ventilation to minimize progression of lung injury in acute respiratory failure Am J Respir Crit Care Med 195 2017 438 442 10.1164/rccm.201605-1081CP 27626833
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==== Front Int Soc Work Int Soc Work ISW spisw International Social Work 0020-8728 1461-7234 SAGE Publications Sage UK: London, England 10.1177/00208728221137952 10.1177_00208728221137952 Article Community social work in Hong Kong during COVID-19: Intervention strategies to address social injustices Fung Kwok Kin Hong Kong Baptist University, Hong Kong https://orcid.org/0000-0002-1080-5203 Hung Suet Lin Hong Kong Baptist University, Hong Kong https://orcid.org/0000-0003-2930-035X Chan Yu Cheung Hong Kong Baptist University, Hong Kong Suet Lin Hung, Department of Social Work, Hong Kong Baptist University, AAB1024, Academic and Administration Building, Kowloon Tong, Kowloon, Hong Kong. Email: [email protected] 9 12 2022 9 12 2022 00208728221137952© The Author(s) 2022 2022 IASSW, ICSW, IFSW This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. In Hong Kong, professional social workers made their presence felt when they delivered a variety of services at the height of the pandemic. Social workers who were working in community development projects or who had adopted community work approaches have become the major service providers when the availability and accessibility of other types of social services have been seriously impeded. This article reports on a qualitative research study conducted to examine (1) how community social workers have planned and implemented services, (2) their use of information and communication technologies (ICTs), and (3) ideas for addressing injustices in disaster management work. Community development COVID-19 Hong Kong information technologies justice social work edited-statecorrected-proof typesetterts1 ==== Body pmcIntroduction The COVID-19 pandemic has become one of the largest and most severe global public health disasters in history, with people in every country having felt its economic, social and health impact. Disaster management response can be broken down into three main phases: emergency relief, recovery and reconstruction (Alexander, 1993). In all three of these phases, and all across the globe, social workers have been at the forefront of the disaster management of COVID-19. Hong Kong was one of the first cities in which COVID-19 emerged, with the virus beginning to spread in late January 2020, immediately after the Chinese New Year festivities. Although Hong Kong is a small city in terms of land area, its high population density and intensive cross-border activities with mainland China made it particularly vulnerable to the coronavirus. After the first two cases were confirmed on 23 January 2020, Hong Kong experienced five waves of the pandemic with the fifth wave only ending in early May 2022. The total number of recorded cases is 1,394,104 cases and 9346 deaths as of 12 August 2022 (https://chp-dashboard.geodata.gov.hk/covid-19/zh.html). As in many other places, the effects of the pandemic are not evenly distributed across different groups of the Hong Kong population. The degree of vulnerability, risk and suffering is disproportionately higher among disadvantaged groups in the city (Siu, 2021). The pandemic is thereby amplifying long-standing structural issues of poverty and inequality in such areas as employment, education and housing conditions experienced by different social groups differentiated by age, gender, ethnicity, migrant status and other factors (Pyles, 2007). In Hong Kong, professional social workers made their presence felt when they delivered a variety of services at the height of the pandemic. Social workers who were working in community development projects or who had adopted community work approaches became the major service providers in Hong Kong during the pandemic, with the availability and accessibility of other types of social services being seriously impeded. This article focuses on community social work in Hong Kong. It reports on a qualitative research study conducted to examine (1) how community social workers have planned and implemented services in accordance with the three stages of disaster management, (2) their use of information and communication technologies (ICTs), and (3) ideas for addressing injustices in post-disaster reconstruction work. The implications of the findings for social work practice are then discussed. The coronavirus pandemic in Hong Kong Hong Kong medical experts learned several public health lessons from the severe acute respiratory syndrome (SARS) outbreak in 2003, which infected 1755 people and caused 299 deaths in Hong Kong alone (Fung and Hung, 2004). Armed with this experience, the public and medical professionals have taken the COVID-19 outbreak seriously. On 7 February 2020, the Executive Council of the Hong Kong SAR government confirmed a state of public health emergency in Hong Kong and enacted a regulation to require all entrants from the mainland to undergo home quarantine (https://www.ceo.gov.hk). Throughout February and March, the city was characterised by widespread fear and a severe shortage of personal protective equipment (PPE). There were incidents of people queuing overnight to purchase surgical masks and being cheated when making online purchases of PPE, while supermarkets were selling out of toilet paper, sanitary materials, canned food, rice and noodles. During the peak of each of the four waves of the pandemic, the city implemented a phased closure of border control points, government offices, schools, bars and gyms. From mid-July to early September 2020 and from November 2020 to May 2021, respectively, the measures included a dine-in ban at restaurants, a two-person limit for gatherings and compulsory mask-wearing in all public areas. Although these measures have been considered essential and shown to be effective in curbing the spread of the virus, they have brought tremendous pressure to bear on many residents, especially among the disadvantaged and vulnerable sectors of the population (Siu, 2021). Hong Kong’s unemployment rate reached 6.1 percent in September 2020 and 7.2 percent in January 2021, which is at a 15-year and 17-year high in the city (http://www.news.gov.hk). Direct financial support was offered by the government in July 2020 in the form of the Cash Payout Scheme, under which each Hong Kong permanent resident received HKD$10,000. The biggest government move to address the problem of increasing unemployment is the HKD$80 billion Employment Support Scheme (ESS) (https://www.ess.gov.hk/en/), which has been used to provide time-limited financial support to employers for the retention of employees who would otherwise be made redundant. Nonetheless, the ESS has been criticised for tending to support employers rather than employees. With the money being paid directly to employers, there have also been reported cases of fraud and malpractice that have involved companies receiving the subsidies while firing staff, reducing salaries, revising terms of employment and demanding that employees take compulsory unpaid leave (Oxfam Hong Kong, 2020). Community social work The history of social work is marked by the parallel development of micro and macro intervention and its dual mission to enhance individual well-being and promote social justice. According to the International Federation of Social Workers (IFSW) and the International Association of Schools of Social Work (IASSW), community organising is a critical form of social work intervention. Social work and community development literature has emphasised the importance of the participation of ‘neighbourhood’ grassroots members for neighbourhood and policy changes (Checkoway, 1991; Lung-Amam and Dawkins, 2020). Community work, however, has become less of the core of social work services in many parts of the world where the states emphasise more rehabilitation and support at the individual level (Haynes, 1998; Jacobson, 2001). In Hong Kong, social work has a 70-year history. Community work has been one of the professional areas of practice of social work in the city since the late 1970s, when the colonial government began to fund Neighbourhood Level Community Development Projects (NLCDPs) which employed social workers to work in deprived areas, such as squatter areas, temporary housing areas and old public housing estates. Community development was expanded in the 1980s with the support of government funding (Fung and Hung, 2011). Community development services were then delivered primarily on a geographical basis through NLCDPs and Community Centres (CCs). NLCDPs focused on transient and marginalised communities, and CCs served community-based populations of about 8000 to 120,000 people (The Hong Kong Council of Social Service [HKCSS], 1997). In the mid-1990s, the Hong Kong government began to phase out geographically based community development projects and terminated the related funding. Community development further declined after the welfare subvention reforms of 2000. The new administrative practices introduced by the government, such as the Lump Sum Grant, Competitive Bidding System and Service Performance Monitoring System, limited the political roles of non-governmental organisations (NGOs) (Lee, 2012; Leung, 2002). Currently, there are 13 CCs and 17 NLCDPs in the city operated by NGOs (https://www.swd.gov.hk). Other non-government-funded projects target specific groups, such as low-income workers, single mothers, older adults or welfare recipients. Literature suggests the importance of community social workers’ roles in disaster intervention and management, particularly during the COVID-19 pandemic (Itzhaki-Braun, 2022; Santiago and Smith, 2020; Sim and He, 2022). Community social work interventions for disaster management include emergency relief work, such as identifying marginalised communities, assessing vulnerability and organising resources and community responses to reduce the threat of risk to the communities (Ersing, 2020). The community interventions also involve building the capacity of the communities and empowering collective action for community recovery and reconstruction (Dominelli, 2015). Social workers of various NGOs in Hong Kong have adopted community development approaches to respond to community needs during the COVID-19 pandemic (Lau et al., 2021; Santiago and Smith, 2020). However, studies examining how frontline community social workers work for/with the marginalised communities in this critical situation are few (Itzhaki-Braun, 2021). The low-income communities: Subdivided flats in old urban areas A continual decline in the supply of public rental housing, together with a drastic rise in the price of private homes since 2004, when the housing market recovered from the Asian financial crisis of 1997/1998, resulted in a continual increase of households residing in private rentals. As at end of June 2022, 242,600 households were on the waiting list for public rental housing, and the average waiting time for public rental housing units was 6.0 years (Hong Kong Housing Authority [HKHA], 2022). With the rising trend in private rental housing, there have been reports of a deterioration of housing conditions, particularly among housing units catering to low-income households. The emergence of subdivided units (SDUs) within the private rental market further testifies to the deterioration in the housing situations of private tenants (Leung and Yiu, 2019). According to the definition adopted by the Census and Statistics Department (CSD) of the HKSAR government, SDUs refer to flats ‘formed by splitting a unit of quarters into two or more “internally connected” and “externally accessible” units commonly for rental purposes’ (CSD, 2018: 2). Based upon the surveys carried out by the CSD and the Transport and Housing Bureau (THB) in 2016 and 2020, the median living space per person in SDUs ranged from 5.3 square metres (57.0 square feet; CSD, 2018) to 6.6 square metres (71.0 square feet; THB, 2021), compared with the allocation standard of minimum living space per person specified in public rental housing policy of 7.0 square metres (75.3 square feet; Hong Kong Legislative Council, 2020). Despite the inadequate size of these units, the rent-to-income ratio was 31.8 percent in 2016 and 32.0 percent in 2020, which is higher than the international standard of affordability for housing consumption of between 25 and 30 percent (Dewilde and De Decker, 2014). The number of households living in subdivided units rose from 85,500 (195,500 persons) in 2014 (CSD, 2015) to 91,800 (209,700 persons) in 2016 (CSD, 2018), and to 110,008 (22,6340 persons) in 2020 (THB, 2021). According to the CSD and THB survey findings, 43.4 percent of SDUs lacked independent cooking space or toilet (THB, 2021), and 48.3 percent of households were forced to move house at least once in the 3 years preceding the survey (CSD, 2016). The THB survey also identified the problems relating to SDUs and encountered by tenants, such as incomplete or no tenancy agreement, worsening states of repair and maintenance of the housing units, poor hygienic conditions and frequent changes of house on the request of landlords or due to rising rent levels (THB, 2021). In addition, studies found that low-income SDU households face higher risk of infection of COVID-19 because of their poor housing conditions and inability to afford enough PPE (Siu, 2021; Wang et al., 2022). Research methodologies To study systematically the intervention of community social workers in disaster management, this study adopted a qualitative research method with data collected from in-depth interviews. It examines how frontline community social workers worked for/with the marginalised communities in old urban areas, notably the SDU households, during the COVID pandemic. The study mainly investigates the experiences of the frontline community social workers to explore (1) how they have planned and implemented services, (2) their use of ICTs and (3) ideas for addressing injustices in post-disaster reconstruction work. A list of community development service units, located in old urban neighbourhoods and endorsing community development approaches during COVID-19, was developed by inviting self-reports from NGOs through a call for information and invitation extended by the research team based on their knowledge about the field. Purposive sampling was adopted to include those of different types and funding sources, and those serving different target groups and localities. Nineteen social workers working with 12 community development projects were interviewed, with each interview lasting 1–1.5 hours. The types of services included community centres (government-funded) and time-limited community development projects (non-government-funded) (see Table 1). The interviews were conducted from September to November 2020, in between the third and the fourth wave of the pandemic. They were audio-taped with the consent of all interviewees, with the tapes then transcribed. The data analysis followed the steps of previewing the data and developing a preliminary coding scheme composed of broad analytic categories, conceptualising the categories further and examining the interrelationships among them, and developing higher levels of abstraction as the analysis proceeded. The categories were coded into themes with the aid of the NVivo 12 software package. The findings were validated with peer audits among the authors and respondent validation by the interviewees. The study received approval from the ethics committee of the Hong Kong Baptist University. Table 1. Twelve community development projects studied by interviewing 19 social workers on their intervention during COVID-19. No. Service type Funding source Number of workers being interviewed 1 Time-limited project Non-government-funded 1 2 Time-limited project Non-government-funded 1 3 Time-limited project Non-government-funded 1 4 Community Centre Government-funded 1 5 Time-limited project Non-government-funded 1 6 Community Centre Government-funded 1 7 Community Centre Government-funded 1 8 Time-limited project Non-government-funded 1 9 Community Centre Government-funded 3 10 Time-limited project Non-government-funded 3 11 Community Centre Government-funded 2 12 Community Centre Government-funded 3 Findings Impacts of COVID-19 on low-income communities The respondents identified vulnerable groups in the communities, including those residing in SDUs, single mothers, migrants from mainland China, low-income manual labourers, those living on social welfare and older adults. Their basic rights to healthcare, education, social security and access to technology and communications have been constrained during the pandemic. A broad range of difficulties that the vulnerable populations have experienced were identified of a tangible, psychological and social nature and at the individual, family and community levels. Higher risk of infection and health problems Those residing in SDUs have been hit hardest by the pandemic. Their infection risk is increased by problems with physical building structures, such as limited air circulation due to lacking, small or broken windows, poor design or construction of water and toilet drains, drain blockages, insect or rat infestations and the sharing of ventilation fans and/or public areas between flats. The stockpiling and speculative purchases of facemasks and disinfection supplies, particularly in the early stages of the outbreak in Hong Kong, created a strong sense of hopelessness and despair among low-income families. The high price of facemasks and disinfecting products also imposed financial burden and psychological stress on them. The tiny living spaces provided by SDUs constrain the physical movements of family members, and the impact on children was amplified because they were compelled to stay at home and have classes online during the suspension of schools. Parents have reported an adverse impact on children’s physical health caused by a long-term lack of physical activities, restricted physical movement at home and prolonged use of digital devices when staying home all day. The children gained weight, their eyesight was weakening and they built up strong emotions under poor housing conditions during the pandemic. Unfavourable educational conditions for children The poor housing conditions of SDUs were disadvantageous to children attending online classes during the pandemic. They were easily disturbed by other family members within the tiny living spaces. Besides, the strong Internet connections and modern computing devices required for effective online learning are also lacking in many low-income households. Community social workers observed that few disadvantaged families have one digital device per family member. In the most extreme cases, an entire family shares one smartphone. In many families, children can only use mobile phones for online classes, and when there is more than one child in the family, coordinating the use of digital devices can create sibling conflicts. High-density residential communities, especially SDUs, often have inadequate infrastructure such as no or poor Wi-Fi access. Many low-income residents find SIM cards costly. Having students attend online classes has also generated problems relating to supervision of children’s use of digital devices. Proper participation in ICT services was also undermined by a lack of knowledge and technical support to deal with the variety of problems that can arise when using different types of digital devices and online platforms for different purposes and the unaffordability of maintenance services for technological equipment. In addition, students with special educational needs have shown deterioration in their learning and communication abilities and find it difficult to interact with peers after a prolonged lockdown when special training/classes were not held. Struggles of caregivers residing in SDUs The caregivers, primarily mothers, residing in SDUs suffered from intensive childcare during the pandemic. Many who were previously working part-time jobs have shifted to full-time childcare under lockdown due to the suspension of classes and diminishing job opportunities. The stress and anxiety in households are gendered, as mothers are expected to take on the additional roles of teachers, tutors and supervisors for their children’s education and to protect family members by providing PPE, all while carrying out even more intensive domestic work, such as cleaning and sterilising the home. Single mothers face additional difficulties when going out to buy food because this means leaving their children unattended at home. The intense stress caused by the health risks associated with the pandemic and the additional burdens placed on all family members has led to heightened marital, parent–child and sibling conflicts. Community social workers described the situation as ‘animals fighting in cages’, with no space for a time-out. Couples with husbands who are unemployed or underemployed were reporting more quarrels over family finances and the sharing of domestic responsibilities. Cases of domestic violence and divorce were also known to the social workers. Furthermore, the lockdowns put in place to manage the pandemic cut off the tangible support of family members who were crossing the border from the mainland to help with childcare so that mothers could work full-time or part-time. Aggravation of poverty The financial difficulties already faced by households in poverty are being aggravated by the pandemic. These households have great difficulties dealing with the loss of income because their expenses cannot be further reduced, as they have already been kept at a very low and basic level. SDU owners may even raise rents during such difficult periods because of the demand for low-priced private rentals. Many owners also charge more for electricity than the government rate when they divide the flats onto separate metres. The cost of electricity has also increased under lockdown with household members staying at home most of the time. In addition to residents of SDUs, labourers have been seriously affected by the pandemic, which has highlighted the long-term social injustices borne by low-income workers. During the peak of the pandemic, many employees were fired, forced to take unpaid leave or asked to resign. People working in the construction, hospitality and catering and retail industries were identified as the most affected. Cleaning workers are working even longer hours than usual but have not been provided with sufficient facemasks, particularly during the first and second waves. They were requested to provide their own PPE for work and lacked additional compensation for the health risks they were exposed to at work. Security guards, particularly those serving old urban buildings and hired by owners’ associations, are another vulnerable group. With service contracting to private companies having become the major model adopted by government and private organisations, most of the cleaning workers and security guards are also deprived of long service or severance payments when they are dismissed. Intervention strategies of community social work Community development services have been maintained to the greatest extent during COVID-19, with social workers actively planning and implementing interventions during the immediate relief and recovery stages (with the latter coming between waves when the number of cases drops and regulations are relaxed). According to the respondents, the shared philosophy of community development as a practice promotes human rights and empowers the community and has informed their practice. Immediate emergency relief interventions When government-run systems have failed to provide PPE to the needy, community social workers have acted to fill the gap. Top-down and bottom-up intervention strategies were used during the emergency relief stage. For the former, there was a revival of the traditional charitable approach, with community social workers delivering PPE, including surgical masks and sanitisers, and later distributing rice, canned foods and food coupons/packages, and then distributing SIM cards and lending mobile phones and tablets to those in need. Some projects (e.g. Project 4) attempted to set up platforms for the bulk purchase of necessary supplies. Community centres have made computers and printers available for children who must submit their school assignments in hard copy. Such immediate relief work was only made possible by social workers actively playing the role of broker by coordinating relief efforts and resources from different sources. The respondents reported that the PPE and tangible goods that they distributed were mainly donated by business enterprises, family foundations, small shops, passionate individuals and groups and civil organisations. With social workers operating from home, traumatic stress interventions are being performed by phone calls to residents. These calls, during which the social workers assess households’ needs, are in many cases the only connection these families have with the outside. Much administrative and liaison work has been conducted to help needy families to apply for various emergency funds and state social welfare. Beyond the distribution of tangible resources, immediate relief work has involved the improvement of the sanitation and safety of living environments. Some projects have mobilised the assistance of various professionals, including medical workers and architects, to repair drains and sterilise flats. Children’s right to play have been recognised by some projects. Simple game packs were designed and produced for pre-school and junior primary school students, with instructions and materials provided. These were distributed to mothers residing in SDUs to help them engage their children. Building community capacity for relief and recovery The uniqueness of community development services lies in their facilitation of residents’ participation in relief work and stress intervention and empowering individuals and groups by identifying strengths, developing capacity and building a sense of mastery. Bottom-up approaches were therefore also adopted by the respondents, who involved residents in the planning and implementing of community support services, mobilised residents to provide mutual support under the constraints of social distancing and invited residents to make various contributions to the community. Some examples of these initiatives are the mobilising of women with sewing skills to produce cloth facemasks for the community, having residents record videos to share life skills, such as cooking, producing hand sanitisers, demonstrating simple physical exercises and playing games with young children. These endeavours serve many purposes, including reducing isolation and fear, promoting mutual support, serving people deprived of PPE, recognising the values of traditional skills and empowering residents to serve as community resources. Many projects devised various strategies to organise income-generating activities for women, such as asking them to organise donated materials, provide occasional childcare services and distribute PPE. The pandemic has unexpectedly created an opportunity for unemployed men to gather to discuss the labour situation and refer jobs to each other. Some projects have organised home repair teams to provide emergency services when shops are closed. The work of involving residents in planning for and delivering PPE in the community extended to the ‘recovery stage’ between waves. With schools resuming, social distancing largely relaxed and social services largely operating as normal, community social workers have taken the opportunity to conduct home visits and organise face-to-face group and mass activities, such as mutual help groups and outdoor trips. Mothers’ and parent–child parallel groups were resumed. Community economic projects continued to produce goods as a form of informal economy. In old urban areas with SDUs, community campaigns were organised to mobilise residents to wash buildings and sterilise public areas. Collaborations within the community have been strengthened by social workers performing networking roles, such as arranging for secondary school students to tutor children through the Internet, and for mothers to produce small gifts for older adults. Training on the use of ICT was conducted to prepare for online activities when the pandemic returned. Advocacy efforts for emergency and unemployment support policies Community social workers shared the advocacy work that they practised during the recovery stage, such as organising concerned groups on unemployment. Three of the community projects were part of a coalition that conducted a community survey on unemployment support, with residents mobilised to describe their situations in a press conference (Projects 4, 6, 9). There was advocacy for relaxing application requirements for emergency funds and direct state unemployment support. Some residents who were concerned about a lack of PPE were interviewed by the mass media to air their grievances against the government. As mentioned by one interviewee (Project 9), COVID-19 is an opportunity to make community development services visible to the community and confirm their unique role in dealing with hazardous situations faced by individuals, families and the community. The use of ICT in social work intervention Social justice is particularly evidenced in relation to the use of ICT. This study found that inadequate access to digital devices and Internet services is prevalent in Hong Kong. Representatives of two of the projects insisted on not using online communication platforms even during the peak of the pandemic, preferring to keep their centres open to the public and deliver interventions face-to-face. The decision to operate in this fashion was based on the perceived limitations of using ICTs, which were in fact evident in the observations and work experiences of social workers involved in other projects. Most of the projects had long made use of telephone calls and messaging using mobile applications to arrange for meetings and activities. The use of online communications platforms, however, is new and challenging for social workers and service users. Under lockdown conditions, community social workers have to provide services online, including delivering classes, educational talks and other types of activities and running groups. Additional work must be done to prepare for service users’ online participation, such as making telephone calls or inviting them to come in person to learn and practise the use of the platforms, explaining the details of the activities beforehand and developing contingency plans for when the Internet fails. Cultural differences also present a problem, with migrants from mainland China and local people using different mobile applications to communicate and social workers needing to grasp all of those applications. The respondents described some benefits of using ICT to deliver their services. Information disseminated through social media platforms has a high transmission rate, extending the reach of services to those, such as the middle classes, who have not received them before. The reduced cost of participation in terms of time and travelling expenses has attracted those who could not join activities in the past, such as full-time caregivers and those with chronic illnesses. The use of ICT has also allowed easy access to social workers via communication applications and facilitated communication within groups through voice messages to show care and concern during the lockdown. There are, however, critical constraints to using ICT in service delivery, including the difficulties involved in facilitating interaction and in-depth sharing among members. The most critical constraints are a lack of digital devices, poor Internet connections in SDUs, inadequate digital literacy and a lack of support, all of which are issues associated with the digital divide. The respondents shared examples of conducting online mindfulness, physical exercise, artwork, yoga or tutorial classes. Delivering services via online platforms, however, can only benefit some but not all of those in need. Children and adults residing in SDUs also lack the physical space for many activities. Issues of social justice and intervention to be addressed in the post-pandemic reconstruction stage Although the pandemic had not disappeared at the time this analysis was conducted, community social workers had engaged in sufficient observation and reflection to formulate ideas about important agendas to be pursued in the post-disaster reconstruction stage. A need was expressed to review the responsibilities of the social work profession and the social service sector as a whole in dealing with disasters, of whatever nature and scope. The welfare of disadvantaged groups has been adversely affected by social workers working from home and by the closure of social services. There is a need to develop strategies that can effectively serve the community while balancing the need to protect social workers from health risks. When service suspension is considered too harmful for clients, social workers must be provided with PPE and allowed to revise the forms of service delivery. Some issues of injustice are specific to the pandemic, such as the closure or reduced office hours of government offices that deal with applications for social security, bankruptcy, public housing, divorce litigation and labour disputes. The delay in meeting urgent needs is traumatising for the needy. The respondents reported cases of families having all of their savings depleted and needing to make urgent applications for social welfare; labourers who were forced to resign or fired without compensation and were seeking to appeal through legal means; older people who could not visit hospitals to obtain medicines and people who needed urgent residential care. These cases go beyond what NGO community social workers can handle. The need to balance the welfare of public officers and disadvantaged groups is urgent and significant in view of the pandemic that will not be extinguished in the foreseeable future. Simplifying application procedures to shorten handling times, replacing home visits with other methods of assessment and maintaining efficiency when working from home are examples of measures proposed by the respondents. COVID-19 has also highlighted structural inequalities. Community social workers are sensitive to injustice experienced by low-income groups, which is rooted in the social structure. The pandemic has disputed the firm belief of many Chinese people that ‘as long as you have hands and legs, you won’t starve’ because disasters bring unexpected life situations that cannot be overcome merely by individual effort. Labour protection and unemployment security is now identified as a key issue by many social workers. The lack of private rental controls, abuse by owners of SDUs in charging for water and electricity and generally low levels of social welfare support are other key issues creating injustice. Relative to these long-standing structural issues, which are well known to social workers, digital inequality is new and has only become prominent amid the coronavirus pandemic. Addressing digital inequalities has become another priority for reconstruction work. Implications for social work practice in an era of social uncertainties Practising community social work The social work profession, including practitioners, professional social work organisations, social work academics and education institutes, has been highly responsive to the needs and issues driven by the development of the coronavirus pandemic over the course of 2020. Numerous publications have been produced in the past few months that discuss social work responses to COVID-19 in different parts of the world (e.g. Lavalette et al., 2020). The present analysis of community social work in Hong Kong exemplifies the unique and significant roles of social workers who adopt community work approaches in disaster management and the contribution of social work to societies with governments adopting neoliberal ideologies (Dominelli, 2021). The pandemic has demonstrated the significance of community social work and raised awareness among residents of the importance of social capital at the individual and community level (Ersing, 2020). Concern with the safety of neighbours is heightened when the population density is high and thus the risk of transmitting the virus is increased. The sense of community is strengthened by the presence of common concerns and languages among residents and more time for communication. Organising tangible and emotional support among residents is effective in connecting people in isolation. Community social work is definitely important in the emergency relief stage (Dominelli, 2015; Pyles, 2007). It is also significant in the reconstruction or rebuilding stage to achieve transformative changes and long-term social development that are essential to establishing the social, economic and political infrastructure to deal with ongoing uncertainties in society caused by natural or human-made disasters and, in particular, to address the needs of the disadvantaged (Dominelli, 2015; Ersing, 2020). Advocating for policy changes The global pandemic has revealed and worsened existing social inequalities. Disaster management by community social workers in Hong Kong has contributed to raising awareness of the root causes of vulnerability to disasters (Dominelli, 2015). It is evident from the Hong Kong experience that social work interventions during the three stages of disaster management should go beyond the micro level to innovate strategies to intervene in broader systems. It echoes the recommendations from the international social work community that there is a need for more social and community development, social policy practice and proclaiming the role of social workers as advocates and facilitators for a more socially just world (Amadasun, 2020; Truell, 2020). This study reveals that community social workers in Hong Kong are planning to advocate for changes in social policies even though the city is under a changing socio-political context (Wong et al., 2021). Community social workers, however, must work within the social, economic and political constraints of their societies, and cannot simply surpass structural hurdles. Hong Kong is a typical example of a market productivist welfare regime. The government is critical of social security and personal social services based on the work incentive implications of the former and the view that users of the latter are unproductive workers (Fung, 2017; Holliday, 2000), despite such policies helping to sustain social stability and legitimise the government (Gough et al., 2004). It is within this context that social workers in Hong Kong are targeting changes at the policy level. Given the hard evidence on how the low-income groups have suffered during the pandemic, social workers across the globe must place advocating for policy changes as a top priority as part of their recovery and reconstruction work (Dominelli, 2015). Addressing digital inequalities A digital divide has been identified in many societies (see DiMaggio et al., 2004; Van Dijk, 2020), and most people would agree that it has been exacerbated by COVID-19. The pandemic has not only made visible the previously hidden digital inequalities, but has also shown that technologies are a necessity rather than an option for social, economic, educational and leisure activities (Király et al., 2020). Studies have revealed that the digital divide has meant that some groups have had their life situations worsened more than others, and the COVID-19 pandemic has testified to this (e.g. Beaunoyer et al., 2020). Hong Kong, as a metropolis, has moved towards a knowledge-based economy with the rapid development in ICT over recent decades. Most Hong Kong residents have access to computers and the Internet. Nonetheless, this study has shown that a considerable number of disadvantaged and deprived people have been left behind and that low-income groups have had specific constraints on their digital access and usage during the pandemic, due to their financial resources, the types of devices they possess, the poor availability of broadband services in private rental flats and the lack of support available for using digital devices. There is a need for social workers to expand their concerns about inequalities to encompass e-exclusion and the digital divide. Finally, the implications for social work practices drawn from the experience of community social workers in Hong Kong are relevant to other places and other crisis events. Human society has already been radically changed by the global coronavirus pandemic. Other types of disasters, whether natural or human-made, are likely to create the same or even greater impact across national borders with people and systems so tightly linked. The social work profession must be ready not only to engage with immediate needs but also to address the emerging and future consequences of different crises through the massive mobilisation of people in communities to help each other, and through collaboration with different sectors to serve different needs and generate beneficial macro-level changes (Ersing, 2020). Limitations of the study Same as other activities, the data collection of this study was also constrained by COVID-19. The response from NGOs to our invitation to self-report was impeded by the overwhelming challenges facing frontline services and also the lower pace of work from home. The research team has tried its best to identify those projects that fit the sampling criteria. All interviews were conducted online and quantitative data about services were not available for reference under the special work situation. This study, nevertheless, documented the intervention strategies and the significant roles and contribution of community social work during and after disaster. Author biographies Kwok Kin Fung teaches on community work and social policy and has written extensively on areas including community development, social welfare policy, social capital and gender. Suet Lin Hung teaches in social work and has written extensively on areas including women and family, narrative practice, gender-based violence and community development. Yu Cheung Chan is studying a PhD with the Department of Social Work, Hong Kong Baptist University. The research topic is community capacity building. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Research Grants Council under the General Research Grant, Hong Kong [GRF16151116]. Funding: The authors received no financial support for the research, authorship and/or publication of this article. ORCID iDs: Suet Lin Hung https://orcid.org/0000-0002-1080-5203 Yu Cheung Chan https://orcid.org/0000-0003-2930-035X ==== Refs References Alexander D (1993) Natural Disasters. New York: Chapman & Hall. Amadasun S (2020) Social work and COVID-19 pandemic: An action call. International Social Work 63 (6 ): 753–756. Beaunoyer E Dupéré S Guitton MJ (2020) COVID-19 and digital inequalities: Reciprocal impacts and mitigation strategies. Computers in Human Behavior 111 : 106424.32398890 Census and Statistics Department (CSD) (2015) Thematic Household Survey Report No. 57: Housing conditions of sub-divided units in Hong Kong. Report, Census and Statistics Department, Hong Kong, China, July. Census and Statistics Department (CSD) (2016) Thematic Household Survey Report No. 60: Housing conditions of sub-divided units in Hong Kong. Report, Census and Statistics Department, Hong Kong, China, March. Census and Statistics Department (CSD) (2018) Thematic report: Persons living in subdivided units. Report, Census and Statistics Department, Hong Kong, China, January. Checkoway B (1991) Innovative participation in neighborhood service organisations. Community Development Journal 26 (1 ): 14–23. Dewilde C De Decker P (2014) Trends in housing inequalities in Europe: What has happened and why does it matter? HOWCOME Working Paper Series 4. Available at: https://biblio.ugent.be/publication/8529156 DiMaggio P Hargittai E Celeste C , et al . (2004) Digital inequality: From unequal access to differentiated use. In: Neckerman K (ed.) Social Inequality. New York: Russell Sage Foundation, pp. 355–400. Dominelli L (2015) The opportunities and challenges of social work interventions in disaster situations. International Social Work 58 (5 ): 659–672. Dominelli L (2021) A green social work perspective on social work during the time of COVID-19. International Journal of Social Welfare 30 (1 ): 7–16.33362429 Ersing RL (2020) Disaster response through community practice. In: Todd S Drolet J (eds) Community Practice and Social Development in Social Work. Singapore: Springer, pp. 1–20. Fung KK (2017) Neoliberalization and community development practices in Hong Kong. Community Development Journal 52 (1 ): 55–75. Fung KK Hung SL (2004) ‘Strength’ community: The role of community development services in SARS. The Hong Kong Journal of Social Work 38 (1–2 ): 109–121. Fung KK Hung SL (2011) Community work in Hong Kong: Changing agenda in the recent phase of economic globalisation. Community Development Journal 46 (4 ): 458–475. Gough I Wood G Barrientos A , et al . (2004) Insecurity and Welfare Regimes in Asia, Africa and Latin America: Social Policy in Development Contexts. Cambridge: Cambridge University Press. Haynes KS (1998) The one hundred-year debate: Social reform versus individual treatment. Social Work 43 (6 ): 501–509. Holliday I (2000) Productivist welfare capitalism: Social policy in East Asia. Political Studies 48 (4 ): 706–723. Hong Kong Housing Authority (HKHA) (2022) Publications and statistics, Hong Kong. Report, Hong Kong Housing Authority, Hong Kong, China. Hong Kong Legislative Council (2020) General housing policies on application for public housing, subsidised home ownership schemes and estate management. Report for Hong Kong Legislative Council and Housing Department. Report no. CB(1)913/19-20(01), 1 April. Hong Kong, China: Hong Kong Legislative Council. Itzhaki-Braun Y (2021) Community social workers’ perspectives on the challenges and opportunities presented by the COVID-19 pandemic. American Journal of Orthopsychiatry 91 (6 ): 714–723.34166058 Itzhaki-Braun Y (2022) Coping with COVID-19: Resilience factors amongst community social workers. The British Journal of Social Work 52 : 3443–3459. Jacobson WB (2001) Beyond therapy: Bringing social work back to human services reform. Social Work 46 (1 ): 51–61.11217494 Király O Potenza MN Stein DJ , et al . (2020) Preventing problematic Internet use during the COVID-19 pandemic: Consensus guidance. Comprehensive Psychiatry 100 : 152180.32422427 Lau SM Chan YC Fung KK , et al . (2021) Hong Kong under COVID-19: Roles of community development service. International Social Work 64 (2 ): 270–274. Lavalette M Ioakimidis V Ferguson I (2020) Social Work and the COVID-19 Pandemic: International Insights. Bristol: Policy Press. Lee EW (2012) The new public management reform of state-funded social service nonprofit organisations and the changing politics of welfare in Hong Kong. International Review of Administrative Sciences 78 (3 ): 537–553. Leung JCB (2002) The advent of managerialism in social welfare: The case of Hong Kong. The Hong Kong Journal of Social Work 36 (1 ): 61–81. Leung KM Yiu CY (2019) Rent determinants of sub-divided units in Hong Kong. Journal of Housing and the Built Environment 34 : 133–151. Lung-Amam WS Dawkins C (2020) The power of participatory story mapping: Advancing equitable development in disadvantaged neighbourhoods. Community Development Journal 55 (3 ): 473–495. Oxfam Hong Kong (2020) Hong Kong poverty report: COVID-19’s effects on unemployment and the poor. Report, Oxfam Hong Kong, Hong Kong, China, December. Pyles L (2007) Community organising for post-disaster social development: Locating social work. International Social Work 50 (3 ): 321–333. Santiago AM Smith RJ (2020) Community practice, social action, and the politics of pandemics. Journal of Community Practice 28 (2 ): 89–99. Sim T He M (2022) Social work competence in disaster management: An integrative review. European Journal of Social Work. Epub ahead of print 29 June. DOI: 10.1080/13691457.2022.2092455. Siu JYM (2021) Health inequality experienced by the socially disadvantaged populations during the outbreak of COVID-19 in Hong Kong: An interaction with social inequality. Health & Social Care in the Community 29 (5 ): 1522–1529.33125773 The Hong Kong Council of Social Service (HKCSS) (1997) NGO paper on community development services. Report, Hong Kong Council of Social Services, Hong Kong, China, July. Transport and Housing Bureau (THB) (2021) Report of the task force for the study on tenancy control of SDUs. Report, Secretariat for the Task Force for the Study on Tenancy Control of Subdivided Units, Transport and Housing Bureau, Hong Kong, China, March. Truell R (2020) News from our societies – IFSW: COVID-19: The struggle, success and expansion of social work – Reflections on the profession’s global response, 5 months on. International Social Work 63 (4 ): 545–548. Van Dijk J (2020) The Digital Divide. Cambridge: Polity Press. Wang Q Lung DC Chan P , et al . (2022) High attack rate in a Tong Lau house outbreak of COVID-19 with subdivided units in Hong Kong. Interface Focus 12 : 20210063.35261729 Wong FYM Liu CPB Chui CFR , et al . (2021) What really matters? An exploratory study on perceived effectiveness, actual practice and determinants of advocacy in social work. The Hong Kong Journal of Social Work 55 (1–2 ): 69–97.
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==== Front Eur J Political Theory Eur J Political Theory EPT spept European Journal of Political Theory 1474-8851 1741-2730 SAGE Publications Sage UK: London, England 10.1177/14748851221143450 10.1177_14748851221143450 Review Ambivalent thinking amid pandemic biopolitics https://orcid.org/0000-0002-5629-8147 Hall Chris 2537 University of the Ozarks , USA Chris Hall, Assistant Professor of English, University of the Ozarks, Clarksville, Arkansas, USA. Email: [email protected] 8 12 2022 8 12 2022 14748851221143450© The Author(s) 2022 2022 SAGE Publications This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. This review article surveys recent work in political theory that has brought together biopolitics and the COVID-19 pandemic. Centered on 2021 books by Giorgio Agamben and Benjamin Bratton, the essay outlines prominent visions of “negative” (Agamben) and “positive” (Bratton) biopolitical responses to the pandemic, engages public reactions to these approaches, and reassesses the position of biopolitical thinking in light of these. In doing so, the article recalls the foundations and original interventions of biopolitical theory, calling for a renewed engagement with the perspectives afforded by biopolitics that pushes past the negative/positive binary. Ultimately, the essay gathers together major developments in biopolitical thinking today, counters moves to discard the theoretical approach despite the limitations of recent examples, and repositions biopolitics as an ambivalent tool for political thought and practice going forward. Biopolitics COVID-19 political theory philosophy ambivalence critical theory pandemic Agamben Foucault edited-statecorrected-proof typesetterts19 ==== Body pmcSlavoj Žižek once wrote about the way in which, late in their careers, filmmakers like Ingmar Bergman and Federico Fellini began to produce films that were only approximations of the style known as, for instance, “Fellini films” (2006: 66). In such films spontaneity is lost, in favor of the reapplication of a simplified formula. One might have a similar sensation upon reading Giorgio Agamben's Where Are We Now? (2021), which collects brief essays and interviews on the COVID-19 pandemic that span from February 26 to November 23, 2020. The text, to be upfront about it, is a shallow grab-bag of Facebook-post-level conspiracy theorizations about COVID's fabricated dangers, and overreactions to resulting government overreach, dressed up in a facile approximation of Agamben's more rigorous political work. Benjamin Bratton, in The Revenge of the Real (2021b), is even more disdainful: “If you were to imagine Alex Jones not as a Texas good ol’ boy, but rather as a Heideggerian seminary student, you would have a sense of how Agamben approached the requests for public comment on the COVID-19 pandemic” (114). Yet despite—indeed because of—the general disposability of the critique presented in Where Are We Now? and its inability to answer the question posed in its title, the book points to the need for a reevaluation of how political theory—and biopolitical thought in particular, of which Agamben is a primary face—is relevant to our ongoing pandemic conditions. It tells you much of what you need to know about Where Are We Now? that Agamben invokes Nazism on the second page of the Foreword. This is not a new point of reference for him, and it is one he has developed to great effect in other works, but in the context of the pandemic it smacks of incaution. Agamben deploys the allusion, as he has in the past, to explain his notion of the “state of exception,” in which crisis conditions are capitalized upon for ever greater oppression by a state's rulers. The state of exception is the major framing concept for Agamben's short text, as he argues that western democracies have fostered panic and fear to curtail the freedoms of their citizenry and shore up the privileges of the political and bourgeois classes. It is a concept the philosopher developed, from Carl Schmitt, into incisive critiques of state power and crisis in past works, but here it becomes totally pervasive: “the state of exception which our governments have for quite some time accustomed us to has finally become the norm” (18). The state of exception is everywhere. Yet, as Marco D’Eramo has pointed out in response, “not all states of exception are the same” (2020: 25). When exception becomes the rule, it loses its diagnostic force. It would be difficult to support the argument that Agamben's work more broadly has not pushed political theory in productive directions. His concept of the bare life of homo sacer, or sacrificeable man, for instance, has become a touchstone for thinking about how populations are stripped of rights and individuals are forced to live in conditions of pure survival. But such potent concepts must be applied judiciously. Agamben is surely right to say that where we find Nazi death camps we find life reduced to its base form, to mere existence. Nazi politics were based in a state of exception, with laws and norms shifted under the aegis of crisis to render certain peoples exploitable and killable. Situated within its circumstances, this brings insightful scrutiny of how the Nazis viewed the elimination of a supposedly corrupting Jewish influence as means for cultivating the health of the Aryan race. Exception loses its rigor when it is used to name every conceivable governmental oppression, in a way that makes the concept banal. Legally defining a population as nonhuman, ejecting them from their homes and forcing them into camps, or enslaving and lynching them—clearly these are the work of an excepting state apparatus. What about mandating quarantine for COVID-19 contact? What about curfews? What about masking ordinances? What about required vaccinations? Agamben's answers (yes) here are clear, because the critical frame has overtaken the context. These questions are not beyond critique, but they seem to be beyond Agamben's critique. Bratton's Revenge of the Real is in many ways a response to Agamben's book, even containing a chapter entitled “Agamben, Having Been Lost,” of a piece with criticisms Bratton raised on the Verso blog in July 2021 (2021a). Bratton characterizes Agamben's approach as a “negative biopolitics,” where every legal measure enacted in the name of health and safety can be unmasked, as it were, as totalitarian, where every technological development presented as a life-saving innovation is secretly only another new method of control (2021a). Against Agamben's libertarian fantasies of governmental withdrawal and individual sovereignty, Bratton introduces a notion of “biopolitics in a positive and projective sense” (2021b: 5), which he variously describes, in daunting verbiage, as: “positive biopolitics at planetary scale” (30); the “epidemiological and biopolitical stack” (46); “post-pandemic positive biopolitics” (66); and “positive biogovernmentality” (120). For Bratton, putting lessons from the pandemic into practice involves crafting “the co-immunological commons” (65) and adopting global stratagems to circulate information, health, and equity. Bratton's language is often dense, though this attests primarily to the urgency with which he conveys his ideas and the register he is devising to do so. His general argument is clear: we possess the technological tools, global connectedness, and political agency for creating coordinated models of a mutually beneficial future. And, lest the style seems to promise a dry read, Bratton is often an entertaining and enthusiastic critic. Besides aggravated frontal attacks on Agamben, Revenge of the Real boasts among its short chapters engrossing analysis of 5G conspiracies, Karens, CHAZ, and the “impotent” politics of Instagrammed black squares and Kendall Jenner commercials (142). Along with these books, there have been a number of recent reflections on biopolitics in public venues such as The Point (Huneke, 2021) and American Affairs (Shullenberger, 2021). As a new branch of critical theory, biopolitics grew out of Michel Foucault's work of the 1970s, furthered especially by Agamben's writing from 1995 on. Biopolitical theory diagnoses the ways in which the management of various populations by the modern state becomes its key function, as it sorts life into different forms with different functions and uses, and in turn begins to think of itself as a living organism. As Agamben wrote in Stasis, biopolitics reveals that the modern state is predicated upon distinguishing “between population and people” (2015: 52) by producing populational hierarchies. This takes place through institutions and political strategies that situate individuals within identity groups (black, white, criminal, citizen, vaccinated, unvaccinated) and link these groups to programs of state intervention. The state then treats, disposes, contains, incarcerates, or ignores as it deems befits each group. In this way, politics becomes concerned at its core with life, and the political issues we are confronted with—everything from economics to infrastructure—are shown to have at their foundations concerns about, to paraphrase Foucault, who is made to live and who is left to die (2003: 247). As Foucault explains in a 1976 lecture, biopolitics involves measuring and directing the encouragement and curtailment of life by producing knowledge about how its citizens are born, live, and die. Foucault contends, like Agamben in Where Are We Now?, that such a regime involves “the right to make live” (241), but it cannot be assumed that this power is inevitably negative. Biopolitics would be a very limited critical perspective if it enabled us to account only for the repressive ways in which life acts as a political priority. Many recent critiques of biopolitical approaches to the pandemic have argued precisely that biopolitical analysis is doomed to be ineffective because it is indeed inherently negative. This criticism makes a great deal of sense when read against Where Are We Now?. Agamben situates biopolitics here under “biosecurity” (e.g. 9), and is concerned purely with its oppressive qualities (though he disputes the negativity of his position), with the ways citizens are “forced by law to be healthy” (56). But biopolitics as a field of thought cannot be attacked by attacking Agamben, because his version is not the only one. Numerous critics working in a biopolitical vein have themselves generated strong critiques of Agamben, including scholars of black feminism such as Alexander Weheliye (2014) and scholars of postcolonialism such as Scott Morgensen (2011). Bratton's criticisms are not exactly new ones. Revenge of the Real makes it clear that Agamben's negative tack is not essential to biopolitical thinking. A biopolitical perspective entails thinking how politics manages life; this management need not be a bad thing. Such thinking is valuable if, for instance, it allows us to see how and why states focus their knowledge-gathering mechanisms upon certain groups of people (say, unvaccinated college students), as well as if it allows us to, say, argue effectively for mask mandates as a form of mutual care in institutional settings. Such thinking is not valuable if it simply regurgitates familiar formulas, or if it leads us down the blind alley of omnipresent control, as Agamben does. Unlike Agamben, Bratton imagines a widely beneficial application of biopolitical thinking through a different application of its methodology. Even if we were to accept Agamben's position, it would be unclear what to do next. Revolt? Give up? Bratton is more practical, even if not always as explicit as might be hoped. His approach emphasizes gathering as much useful data as possible, comparing pandemic responses, and then crafting effective models that translate to different contexts and operate in coordination across borders. The approach is pragmatic: it measures problems and outcomes, evaluates, and offers solutions. Yet it is thoroughly biopolitical, for Bratton emphasizes that a renewed political ethics in our present crisis is possible only by making conscious “choices concerning what does and does not live” (2021b: 5). Our measuring and evaluating must be undertaken from the perspective of how to produce conditions of life for populations that have been rendered susceptible. Bratton uses this approach to offer definite solutions, and there is a texture to his analysis that is sorely needed in the noise of various pro/anti arguments. For instance, for those of us in the United States, living in the chaos of various bespoke tracing apps, we could instead model an approach from the top-down technique used in Taiwan: “a combination of high-tech and high-touch” where user location data is centrally housed and put to work to track contact and direct quarantines (2021b: 51). Similarly, wearing masks, “keeps you and others safe but also communicates solidarity with the immunological commons” (93). Not just personal health but social health and trust are at stake here, thought as forms of life of their own. As Bratton's title indicates, we must be realistic about the damage being done by the pandemic and the measures we possess to mitigate it. We cannot start by moralizing about freedom and surveillance, but must make the mechanisms for safety and care that we have work in the most ethical way possible. We might also then draw broader lessons from our masked lives, much like lessons learned about condoms from the HIV epidemic: “touchlessness can instill and realize actual care” (102). Such lessons are distinctly biopolitical, asking us to think as interconnected bodies from populations afforded different capacities and vulnerabilities. Bratton offers further responses to pressing pandemic issues. On social distancing: we should look to China, who never needed it, thanks to strict lockdowns. On vaccine distribution (COVID and otherwise): free global availability coordinated between countries based on need, which can only be mutually beneficial when thought at a scale of planetary inter-reliance. It benefits each of us, after all, if others who we will never meet do not become ill and provide new opportunities for disease to spread and mutate. Such arguments seem almost commonsensical, but their ethical and governmental framing lends them a theoretical durability built to withstand reactionary counterarguments based on racism, xenophobia, and self-interest How is it possible that Bratton and Agamben are applying the same theory with such different results? Going back to Foucault, it is precisely the point of biopolitics that state organization and maintenance of life is, in the abstract, ambivalent: we do not know how it works until we look at it. To qualify as biopolitical, a theory must only take up Foucault's tools and use them to gather information about how lives of different kinds are made to live or die. Such theorizing need not lead inexorably to arguments about either tyranny or utopia. As Foucault demonstrates in his lectures, biopolitical analysis gathers information about the state's management of life in a fashion analogous to how the biopolitical state itself gathers information on its citizenry. A state becomes biopolitical when it becomes concerned with things like birth rates and disabilities; a theory becomes biopolitical when it gathers information about this state effort. The shift in focus is methodological, not moral. Information on birth rates might be used to suppress procreation by indigenous populations through forced sterilization, or it might be used to channel funding to white daycare centers. Biopolitics makes visible new forms of welfare as well as new forms of violence. So there is no moral imperative in biopolitical theory. Use of its tools need not entail anti-statist or libertarian positions, nor must it start us down Bratton's path toward technocratic global governance. The work always remains to be done in discovering how states apply their biopolitical strategies: who are they helping or forcing to live, who are they killing or allowing to die, and why? Yet because biopolitical analysis involves these urgent questions of life and death and oppression and freedom, practical and moral conclusions developed out of this analysis are common, and rightly so. In practice, biopolitical thinking rarely remains purely methodological. For Bratton, lessons are being drawn as we continue the analysis; for Agamben, however, there are no new developments left: the moral has been found, and there is to be only ever more tone-deaf attempts to squeeze the evidence to fit it. Agamben does raise some valid concerns in Where Are We Now?, though it can be easy—and not always unwarranted—to dismiss them for being so closely adjacent to familiar conspiracy theories. Because of (to be charitable) the brevity of these essays, Agamben frequently repeats points with little sustained analysis, and so critiques that may be worth entertaining collapse into lists of grievances. Worthwhile criticisms of online schooling, disposal of the dead, and gutted national healthcare ultimately vacillate between tired attacks (e.g. on scientific consensus) and absurdities, as in one astonishing passage where Agamben argues that “The instructors who agree…to subject themselves to the new online dictatorship and to hold all their classes remotely are the exact equivalent of those university professors who, in 1931, pledged allegiance to the Fascist regime” (74). Criticisms worth considering in this text are blunted as they are leveraged into preposterous conclusions. Attacks Agamben makes upon western democracy are hampered by his insistence upon yet another exception, on loss of “freedoms” (what are these?), on crying oppression. Perhaps the life our pandemic measures preserve is indeed only bare life—surely a question worth asking—but have our potential responses to such an outcome really been reduced to nostalgia for the status quo? This truly is a negative critique, the vast conspiracy of a state of exception that only harms and never saves, only harming when it saves, despite obvious appearances to the contrary. So what does biopolitics has left to say to us today? Wherever a group is oppressed on biological grounds, biopolitics reminds us that this is undertaken in the service of some conception of the health of the body politic. It also reminds us that the “health” of a state does not necessarily equal the “universal good” of its people. Biopolitics prompts us, then, to ask anew who makes up the social body that is being cared for, whose health is being fostered, and whose is not. How, for instance, has black life in America been posited as less than human and relegated to spaces where it cannot dilute white life—prisons, low-income neighborhoods, and plantations? This is obviously oppressive, but not from the state's perspective. If Bratton's models are to be put to work, it will first be necessary to overcome the atomized vision of social life that Agamben appropriates from our commonplace rhetoric of personal choice and freedom. This has already been somewhat facilitated by our ever-present consciousness of the pandemic, which forces us to view the world epidemiologically (Bratton, 2021b: 33). Bratton's greatest foil is the pervasive neoliberal idea that society is a collection of autonomous individuals who must be allowed to make their own choices without government intervention or regard for others. We must instead “embrace a realist and materialist conception of the human body as a biochemical assemblage and collective human intelligence as the collaboration of such creatures working in concert” (Bratton, 2021b: 39). Flexible, top-down collaboration is needed, built upon the realistic awareness that our lives are not lived in isolation. Yet even as Bratton shows productive ways biopolitics can be mobilized to craft better post-pandemic futures, his response is not quite satisfactory either. Bratton's biopolitical ethics of epidemiological interconnectivity and his practical responses to the pandemic do inject biopolitical thinking with a usefulness and positivity shouted down by Agamben. But in Bratton's biogovernmentality and his stack of models and data that make global biopolitics possible, we lose much of the ambivalence that dwells in the methodological core of biopolitics. Ambivalence is what truly animates biopolitical thinking by refusing to lock in trajectories of either positivity or negativity. Given, too, that there are good models out there for organizing quarantines and distributing vaccines, how transposable and flexible is such modeling? There are times when Bratton slips into biopolitical utilitarianism, where we need only act on best principles and everyone's lives will improve. But how sure are we that these are the best principles? How can a utopia of models possibly be practicable in the impossibly heterogeneous lived situations across the globe? There is something distinctly unrealistic about this. To be fair, Bratton does not pretend that all answers are readily at hand. Some of his book's best moments come when he drifts more open-endedly, where he thinks “control” as both the naïve “oppression” that Agamben equates it with and as a way of giving necessary shape to the world. But the guiding teleology of “positive” biopolitics saps the potential for discovery and critique. Simply put, the positive/negative framing of biopolitics is too easy. Both are a dead end. Samuel Clowes Huneke has critiqued Foucauldian biopolitics by contending that “any theory of power that does not also account for how modern medicine has made life immeasurably better for most humans would seem to have lost the plot.” Yet this is precisely what biopolitics enables—not by checking off negatives and positives wherever life and health enter politics, but in an ambivalent reciprocity where some forms of life are harmed as others are cultivated. Callousness of experimentation, inequities in medical testing and availability, catastrophic healthcare costs—biopolitics enables renewed analysis of each of these, while also questioning the benefits accrued and for whom. True, we have many theories already that enable grappling with questions of animal testing, vaccine hoarding, and insurance classism. What distinguishes biopolitics is its capacity to think these together as strategic, legalized biological decisions arranging lives into categories of human/nonhuman, white/nonwhite, able/disabled, and wealthy/poor. Thinking in this manner lets us to see past racism, anthropocentrism, and xenophobia as errors in governance to be corrected (though in some aspects they can and should be), by viewing them as the very logic of the health of that governance. We can only overcome biopolitical oppression if we can see how such oppression appears as a good and then undermine the categories that make it possible. By way of closing, allow me to take up an issue not directly analyzed by Bratton—that of the unvaccinated by choice, the “anti-vaxxers.” Oppressed, perhaps, by such measures as travel restraints, they are also thereby protected. Concerned for their well-being before a mysterious drug, mistrusting corporate pharmaceuticals and believing that the choice concerns them alone, they abstain. Are these fears misplaced? Some of them, yes—we are certainly not subjecting ourselves to a secret microchipping enterprise in taking the vaccine. But in general, no. As Bratton emphasizes, however, these choices do not concern only myself and members of my group, but impact countless others. We have the means to make touch safe, let us use them. Thinking biopolitically, we become newly capable of arguing for a global vaccine mandate. Doing so means thinking our lives as interconnected, all of our populations as equally worth saving—not by thinking of us all as undifferentiated people, but as populations with particular legally enshrined affordances and deficits. The state truly does think of anti-vaxxers as disposable in not requiring their vaccination. By humoring them and leveraging them as political weapons, it kills them. We should think beyond the scapegoating of personal choice in this matter: it is the state that fails us. Is this a negative biopolitical position? Surely not, for it commands the state to act to preserve human lives thought in concert with the presence and touch of others. But this is not a positive biopolitics either: it recognizes the intense pain of overruling autonomy; it is quite likely that some will have negative reactions to the vaccine; this in no way places the medicine it gives beyond the veil of criticism. Yet it is the health of life itself that is at stake. We must grit our teeth and foster this. There is both benefit and harm here, and one does not simply outweigh the other. If biopolitical theory contains any inherent moral, it is that life must remain possible. We therefore should return to biopolitics as a site of critique that enables us to view life with ambivalence. Biopolitical thought has the enduring capacity to tell us who the state values and to ask the questions of who is being kept alive, what kinds of life are being preserved, at whose expense—who is benefiting, who is suffering, and for what? We must think biopolitically, ambivalently, about the global populations affected by accumulating vaccine stockpiles, about lives rendered disposable through anti-masking and anti-vaccination rhetorics of freedom, about science's retrenchment as supposed fount of objective truth. We can do any of this productively only by starting from the knowledge that such forces, and the politics they shape, preserve more than survival as they both save and oppress, and not along lines that are set or clearly discernable. The negative is possible, the positive is possible, but no state of affairs can be reduced to one or the other. Biopolitical thinking allows us to live in the tension, to continue the endless work of discovering mechanisms of oppression and of equity, without disappearing into conspiracy or utopia. The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding: The author received no financial support for the research, authorship, and/or publication of this article. ORCID iD: Chris Hall https://orcid.org/0000-0002-5629-8147 ==== Refs References Agamben G (2015) Stasis: Civil War as a Political Paradigm. Translated by Nicholas Heron. Stanford, CA: Stanford University Press. Agamben G (2021) Where Are We Now? The Epidemic as Politics. Translated by Valeria Dani. Lanham, MD: Rowman & Littlefield. Bratton B (2021a) Agamben WTF, or how philosophy failed the pandemic. In: Verso blog. Available at: https://www.versobooks.com/blogs/5125-agamben-wtf-or-how-philosophy-failed-the-pandemic (accessed 14 November 2022). Bratton B (2021b) The Revenge of the Real: Politics for a Post-pandemic World. New York: Verso. D’Eramo M (2020) The philosopher’s epidemic. New Left Review 122 : 23–28. Foucault M (2003) Foucault's translated by David Macey. In: Bertani M Fontana A (eds) “Society Must Be Defended”: Lectures at the Collège de France, 1975–1976. New York: Picador. Huneke SC (2021) “Do not ask me who I am”: Foucault and neoliberalism. In: The Point. Available at: https://thepointmag.com/politics/do-not-ask-me-who-i-am/ (accessed 14 November 2022). Morgensen SL (2011) The biopolitics of settler colonialism: Right here, right now. Settler Colonial Studies 1 (1 ): 52–76. Shullenberger G (2021) How we forgot Foucault. American Affairs 5 (2 ): 225–40. Weheliye AG (2014) Habeas Viscus: Racializing Assemblages, Biopolitics, and Black Feminist Theories of the Human. Durham, NC: Duke University Press. Žižek S (2006) The Parallax View. Cambridge, MA: The MIT Press.
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Eur J Political Theory. 2022 Dec 8;:14748851221143450
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Eur J Political Theory
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10.1177/14748851221143450
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==== Front J Vis Impair Blind J Vis Impair Blind JVB spjvb Journal of Visual Impairment & Blindness 0145-482X 1559-1476 SAGE Publications Sage CA: Los Angeles, CA 10.1177/0145482X221144438 10.1177_0145482X221144438 Comment Gathering Evidence on the Effect of the COVID-19 Pandemic on People Who Are Blind or Have Low Vision: Looking Back and Moving Forward, With Recommendations for Future Disasters Silverman Arielle 1 1 Public Policy and Research Department, American Foundation for the Blind, Arlington, VA, USA Arielle Silverman, PhD, Public Policy and Research Institute, American Foundation for the Blind, 1101 Wilson Blvd, 6th Floor, Arlington, VA 22209, USA. Email: [email protected] 7 12 2022 7 12 2022 0145482X221144438© American Foundation for the Blind 2022 2022 American Foundation for the Blind. All rights reserved. This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. edited-statecorrected-proof typesetterts19 ==== Body pmcUndoubtedly, most people can remember the events of March 2020 and recall a last trip outside of the home for a restaurant meal or the final day of working in an office or school setting before the lockdowns started. They may remember the feelings of uncertainty about the future and, of course, the shortages of toilet paper and cleaning supplies in stores. The COVID-19 pandemic impacted all individuals in many ways, but the effects were unique for people of all ages who are blind or have low vision. Over the past 2 years, researchers at the American Foundation for the Blind (AFB)'s Public Policy and Research Institute (PPRI), of which I am a member, have conducted several studies to examine the experiences of Americans who are blind or have low vision in a variety of areas during the pandemic. The first two surveys were conducted in the spring of 2020: Flatten Inaccessibility, which looked at the experiences of adults with visual impairments (Rosenblum et al., 2020a); and the first Access and Engagement survey, which focused on the educational experiences shared by parents and teachers of children with visual impairments (Rosenblum et al., 2020b). Later surveys were conducted to gather additional information at various points during the pandemic, including the Journey Forward survey, conducted in the summer of 2021 (Rhoads et al., 2022) and two additional follow-up surveys to the Access and Engagement survey (Rosenblum et al., 2021; Silverman et al., 2022b). Finally, AFB's Workplace Technology Study documented experiences with the transition to telework (Silverman et al., 2022a). Disproportionate Effect of the Pandemic on People With Visual Impairments Collectively, these studies reveal ways in which the pandemic disproportionately affected Americans who are blind or have low vision, particularly by exacerbating barriers posed by a lack of consistent access to transportation and digital information. For example: In April 2020, about 80% of respondents reported concerns that they would have trouble getting themselves or their loved ones to a COVID testing site or a healthcare provider if needed because they could not drive (Rosenblum et al., 2020a). In April 2020, as schools went virtual, three-fourths of the parents of school-age children who filled out the survey said they had concerns about their child's educational progress, and about half of the teachers surveyed said they could not reach at least one of their students (Rosenblum et al., 2020b). By November 2020, while many children were still attending online school at least part of the time, nearly 60% of teachers surveyed said their students could not access at least one digital tool, and 35% said their students could not access at least two digital tools (Rosenblum et al., 2021). In the summer of 2021, 45% of survey respondents said they had trouble getting food or supplies delivered during the pandemic. They cited challenges like inaccessible delivery applications (apps), a lack of available delivery time slots, or prohibitive costs (Rhoads et al., 2022). In the same 2021 survey, 70% of respondents tried to use telehealth services; of these, 57% had accessibility issues with the telehealth platform. When they tried to go in-person for healthcare services or COVID tests, some respondents said they were told to wait outside, sometimes in unsafe conditions, because they did not have a car in which they could wait (Rhoads et al., 2022). In the Workplace Technology Survey, although 41% of the respondents reported teleworking at least part-time before the pandemic started, 90% were teleworking by April 2020. Some of the respondents reported that they liked teleworking for a variety of reasons such as not needing to worry about transportation, having full control of their office setup, and having more control of how their blindness or low vision was disclosed in the workplace. However, many respondents also cited accessibility challenges with common videoconferencing platforms, and it was sometimes harder to remediate access issues without being physically present in an office (Silverman et al., 2022a). Like other disasters before it, the COVID-19 pandemic disproportionately affected people with disabilities. People who are blind or have low vision, including those with additional disabilities or medical challenges, and their families, faced especially difficult situations due to disrupted in-person supports, as well as often being at higher risk of complications from the illness. Although some issues (such as a lack of walkup COVID testing sites) were pandemic-created issues, many other problems manifested from systemic barriers that were present long before the pandemic began. Some of these barriers include the inconsistent accessibility and usability of digital tools and information; facilities and systems set up primarily for people who drive cars; and insufficient broadband coverage in some parts of the country, which caused some children to have difficulty accessing virtual instruction. Difference Between Accessibility and Usability As a totally blind woman, I was lucky in many ways during the pandemic. I had been a full-time teleworker before the pandemic, and I was self-employed, so I experienced little disruption to my workload or the technology I used. I also have a sighted husband who teleworked, went to the grocery store weekly, and drove me to my vaccination appointments, a privilege many of my peers who are blind or have low vision did not have. When I came home from a conference with a telltale sore throat in July 2022, my husband and I isolated from each other for 10 days. I did not want to have him expose himself to the virus by driving me to a testing site, nor did I want to use a rideshare service. My husband and I had rapid tests at home, and I knew some blind people who had tested themselves using a visual interpreting service (like Aira or Be My Eyes) to read their results. I did not trust myself to juggle several unfamiliar tiny tubes and droppers (labeled only in print) while holding them in front of my smartphone's camera, especially when I was sick, lethargic, and uncoordinated. I considered not testing at all, but as my symptoms worsened, I worried the lack of a positive test could delay my access to treatment. Eventually, my husband assisted me with a home test—on our balcony, with all the windows open. He wore a mask and I handed him the swab I had inserted in my nose, which he placed in the prepared test solution and later emailed me a photo with the caption, “Clearly positive test.” Fortunately, I recovered without treatment, and my husband never got sick at all. However, this experience is perhaps a clear example of the difference between accessibility and usability. Even when a tool, like an at-home COVID test, is technically accessible, it may not be fully usable during the ideal use case—when someone is ill and wishes to use it without any in-person assistance. As the end of 2022 approaches, the majority of individuals in the United States have largely returned to their pre-pandemic ways of life. Schools have reopened, many workers have returned to offices, and toilet paper supplies have been restored. However, the underlying systemic issues and inequities highlighted during the pandemic are still in need of remediation. Furthermore, the digital tools that became crucial during the pandemic will still play a continuing role in people's lives, including the lives of those who are blind or have low vision. Key Recommendations for Future Disasters Each of the PPRI research reports includes a series of recommendations for policymakers and other key decision makers to consider in order to mitigate the concerns highlighted by the research data. In considering recovery from the COVID-19 pandemic, as well as preparedness for potential future disasters, some key recommendations might include: Educational and workplace decision makers should “buy for inclusion,” by carefully considering the accessibility and usability of new digital tools before making procurement decisions. Digital information about disasters and emergencies, such as a global pandemic, should be made fully accessible to viewers who have low vision or are blind or deafblind, including charts, maps, and videos. Educational teams should provide intensive or compensatory services or both to students who have experienced learning losses during the pandemic. Healthcare facilities, as well as COVID-19 vaccination and testing sites, must be fully accessible to nondrivers. State and local transportation agencies should evaluate increasing on-demand transportation options for nondrivers. Public health agencies should incorporate the needs of people who are blind or have low vision into planning from the outset as they prepare for future disasters. Although the COVID-19 pandemic brought losses and struggles to many people, it has also brought some unexpected silver linings. Through the pandemic, individuals have learned to be more innovative and creative in using new tools, such as remote work tools, that have the potential to facilitate universal access to information and services. In the coming years, it will be important to ensure that new technologies and innovations fully include people with disabilities and that the lessons learned from this pandemic be incorporated in responses to future disasters. The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article. ==== Refs References Rhoads C. R. Bleach K. Chatfield S. Camarilla P. (2022). The journey forward: Impact of COVID-19 on blind, low vision, and deafblind U.S. Adults. American Foundation for the Blind. https://www.afb.org/research-and-initiatives/covid-19-research/journey-forward Rosenblum L. P. Chanes-Mora P. Fast D. Kaiser J. T. Wild T. Herzberg T. S. Rhoads C. R. Botsford K. D. DeGrant J. N. Hicks M. A. C. Cook L. K. Welch-Grenier S. (2021). Access and engagement II: An examination of how the COVID-19 pandemic continued to impact students with visual impairments, their families, and professionals nine months later. American Foundation for the Blind. https://static.afb.org/legacy/media/AFB_AccessEngagement_II_Accessible_F2.pdf Rosenblum L. P. Chanes-Mora P. McBride C. R. Flewellen J. Nagarajan N. Nave Stawaz R. Swenor B. (2020a). Flatten inaccessibility: Impact of COVID-19 on adults who are blind or have low vision in the United States. American Foundation for the Blind. https://afb.org/sites/default/files/2022-03/AFB_Flatten_Inaccessibility_Report_Revised-march-2022.pdf Rosenblum L. P. Herzberg T. S. Wild T. Botsford K. D. Fast D. Kaiser J. T. Cook L. K. Hicks M. A. C. DeGrant J. N. McBride C. R. (2020b). Access and engagement to education study: Examining the impact of Covid-19 on students birth-21 with visual impairments, their families, and professionals in the United States and Canada. American Foundation for the Blind. https://afb.org/sites/default/files/2022-03/AFB_Access_Engagement_Report_Revised-03-2022.pdf Silverman A. M. Munguia Rodriguez G. Rhoads C. R. Bleach K. (2022b). Access and engagement III: Reflecting on the impacts of the COVID-19 pandemic on the education of children who are blind or have low vision. American Foundation for the Blind. https://afb.org/sites/default/files/2022-06/AFB_AccessEngagement_III_Report_Accessible_FINAL.pdf Silverman A. M. Rosenblum L. P. Bolander E. C. Rhoads C. R. Bleach K. (2022a). Technology and accommodations: Employment experiences of U.S. adults who are blind, have low vision, or are deafblind. American Foundation for the Blind. https://www.afb.org/sites/default/files/2022-01/AFB_Workplace_Technology_Report_Accessible_FINAL.pdf
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J Vis Impair Blind. 2022 Dec 7;:0145482X221144438
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10.1177/0145482X221144438
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==== Front Nord J Nurs Res Nord J Nurs Res NJN spnjn Nordic Journal of Nursing Research 2057-1585 2057-1593 SAGE Publications Sage UK: London, England 10.1177/20571585221135428 10.1177_20571585221135428 Research Paper Patients experiences of their relationships with relatives and their collaboration with nurses during contact in non-COVID-19 hospital wards – A qualitative study https://orcid.org/0000-0002-7688-4362 Pedersen Birgith 123 Lerbæk Birgitte 24 https://orcid.org/0000-0002-4197-3066 Jørgensen Lone 125 Haslund-Thomsen Helle 56 Thorup Charlotte Brun 56 Albrechtsen Maja Thomsen 2 Jacobsen Sara 2 Nielsen Marie Germund 27 https://orcid.org/0000-0002-7695-3639 Kusk Kathrine Hoffmann 2 Laugesen Britt 28 Voldbjerg Siri Lygum 259 Grønkjær Mette 25 https://orcid.org/0000-0002-8411-1837 Bundgaard Karin 2510 1 Clinic for Surgery and Cancer Treatment, 53141 Aalborg University Hospital , Aalborg, Denmark 2 Clinical Nursing Research Unit, 53141 Aalborg University Hospital , Aalborg, Denmark 3 Clinical Cancer Research Centre, 53141 Aalborg University Hospital , Aalborg, Denmark 4 Clinic for Internal and Emergency Medicine, 53141 Aalborg University Hospital , Aalborg, Denmark 5 Department of Clinical Medicine, 1004 Aalborg University , Aalborg, Denmark 6 Clinic for Anesthesiology, Children, Circulation and Women, 53141 Aalborg University Hospital , Aalborg, Denmark 7 Department of Health Science and Technology, 1004 Aalborg University , Aalborg, Denmark 8 Center for Clinical Guidelines, Department of Clinical Medicine, 1004 Aalborg University , Aalborg, Denmark 9 Department of Nursing Education, University College North Denmark, Denmark 10 Clinic for Neuro-, Head and Orthopaedic Diseases, 53141 Aalborg University Hospital , Aalborg, Denmark Karin Bundgaard, Aalborg University Hospital, Søndre Skovvej 5, 3rd Floor, 9100 Aalborg, Denmark. Email: [email protected] 27 11 2022 27 11 2022 2057158522113542810 10 2022 © The Author(s) 2022 2022 Vårdförbundet This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. COVID-19 restrictions prevented relatives from visiting and accompanying patients to hospital and required that nurses wore personal protective equipment. These changes affected patients’ relationships with relatives and challenged their ability to connect with nurses. Individual, semi-structured interviews with 15 patients were carried out to explore patients’ experiences of their relationships with relatives and their collaboration with nurses during in- and outpatient contacts in non-COVID-19 hospital wards. The analysis of data was guided by phenomenological hermeneutic frame of reference and the study was reported according to the COREQ checklist. The findings illustrated that patients felt lonely and insecure when separated from relatives, caught between relatives and professionals during information exchange, and experienced the absence of relatives as both beneficial and burdening. Visitor restrictions provided patients with time to heal but prevented provision of informal care. Patients had to take responsibility for maintaining contact with relatives independent of their health condition. COVID-19 restrictions created distance with nurses, which potentially led to insufficient physical and psychosocial care. collaboration COVID-19 hermeneutic nurse–patient relationship patient perspective phenomenology relatives edited-statecorrected-proof typesetterts19 ==== Body pmcIntroduction With coronavirus disease (COVID-19), the context for, and the provision of, nursing care changed in the pandemic wards established to assess and treat patients with COVID-19. Likewise, the context changed for the remaining hospital wards that continued to provide care and treatment for other patients. In this paper, we refer to these wards as non-COVID-19 wards. The COVID-19 pandemic restricted relatives from visiting patients in and accompanying them to hospital unless they were relatives of critically ill patients.1 This affected the possibility and benefit of involving the relatives in the patients’ pathway for both patients and nurses.2–4 Research shows that collaboration with relatives during in- or outpatient hospital contact is essential for the patients5 as the relatives provide emotional support6,7 and advocate for the patient through supportive mediation.6,8 In addition, they help patients to understand information and make decisions9 as well as sometimes serve as an extended arm of the healthcare professionals (HCPs).2,5,7 Internationally, family is perceived as a unit of care that plays an important role in nursing and much suggests that this role becomes even more important during pandemics such as COVID-19.10–12 According to Griffin,13 the family-centered approach is understood as a way of planning, delivering, and evaluating healthcare based on a collaboration between HCPs and families of patients. Even though Griffin focuses on family in neonatal settings, the family-centered approach is highly relevant for adults as well as it involves the core concepts of dignity and reciprocal respect, information sharing, and family participation and collaboration.5,6,12 Additionally, involving patients and relatives in care is expected to improve patient safety, quality of care, coherence, and geographical equality in healthcare.14,15 Thus, high-quality nursing care relies on a triad consisting of patients, relatives, and HCPs, and involves a collaborative trialogue between these parties.9,16 The Fundamentals of Care (FoC) framework emphasizes how the delivery of high-quality nursing care rests on a nurse–patient relationship built upon mutual commitment.17,18 Furthermore, the FoC addresses how contextual factors within the healthcare system, as well as the skills, commitments, and abilities of the individual nurse, affect the ability to establish and maintain a relationship.19 To minimize transmission of the virus during the COVID-19 pandemic, wearing personal protective equipment (PPE) such as masks and shields and enforcing physical distancing were required. This physical barrier in the patient–nurse relationship may influence the patients’ and nurses’ ability to connect with one another, thus potentially affecting the quality of the nursing care provided. In addition, the relocation of experienced nurses to the pandemic wards may put an additional strain on the patients’ experience of receiving a timely, adequate, and high-quality standard of nursing care.20,21 Consequently, the opportunities for providing and receiving individual and family-centered nursing care may be limited. However, how patients’ have experienced their collaboration with nurses and what it means to be without physical interaction with their relatives while they are in contact with hospitals and in vulnerable situations is unknown. The aim of the present study was to explore patients’ experiences of relationships with relatives and collaboration with nurses during in- and outpatient contacts to non-COVID-19 hospital wards in a university hospital. Method The study was designed as a qualitative explorative study and guided by a phenomenological hermeneutic frame of reference, which is a mode of understanding in qualitative interviewing that aims to reveal patients’ perspective.22 The consolidated criteria for reporting qualitative research checklist were used as a guideline for facilitating and securing a complete reporting of the study.23 Setting Data were collected among patients in contact with non-COVID-19 in- and outpatient wards at a university hospital in Denmark during the first wave of the COVID-19 pandemic. During spring 2020, visitation opportunities were excessively restricted as no relatives were allowed to accompany patients unless they suffered from critical illness. Recruitment In total, 15 individuals were purposively recruited to participate in the study.24 The participants contacted the principal investigator by email after information about the study was displayed on the hospital's Facebook page. All participants had been in contact with the hospital due to acute or sub-acute health conditions (Table 1). Five of the participants were diagnosed with co-morbid physical illnesses. Four had more than one contact (admissions, examinations) with the hospital during the time of the pandemic-related restrictions. Table 1. Characteristics of the participants. Patient Age (years) Sex Contact reason Type of contact Relatives* 1 74 Female Respiratory distress Acute Spouse 2 65 Male Hyperglycemia, febrilia, pneumonia Acute Spouse 3 28 Male Diagnostic examinations Sub-acute Parents, spouse 4 50 Female Specific illness, low hemoglobin count, renal stress Acute Spouse, two children 5 28 Male Accident Acute Spouse, two children 6 30 Female Complication during pregnancy Acute Parents 7 36 Female Toxic shock syndrome, sepsis, erysipelas, pneumonia, influenza Acute Spouse 8 38 Female Diagnostic examination Sub-acute Mother 9 29 Female Complication during pregnancy Acute Spouse 10 38 Female Hypertension and tachycardia Acute Spouse 11 46 Female Surgery Sub-acute Spouse 12 42 Female Surgery Sub-acute No one specific 13  27 Female Observation after trauma – late pregnancy Acute Spouse 14  28 Female Complications during early pregnancy Acute Spouse 15  30 Female Complications during late pregnancy Acute Spouse * Relative mentioned by the participant as relevant in the situation. Data collection A semi-structured interview guide was used to explore the patients’ individual experiences providing detailed information based on the respondents’ own words.22 The interview guide contained a starting question and additional exploratory questions that facilitated the participants’ perspectives on their experiences of relationships with relatives and collaboration with nurses during in- and outpatient contacts in non-COVID-19 hospital wards. The 15 interviews were conducted by six researchers. The interviewers were five researchers with a PhD and one PhD student, who all had experience of interviewing. The duration of the interviews was 18–90 minutes (mean 35.41 minutes). Based on the patients’ preferences, two interviews were conducted on the telephone and 13 were conducted face-to-face. The latter took place in the patients’ homes or in a convenient office at the hospital. All the interviews were conducted during June and July 2020. All interviews were digitally recorded and transcribed verbatim. The patients are identified by numbers (patients 1–15) and in the citation's blocks, capitals are added to denote emphasis or intense distress. Data analysis According to Brinkman and Kvale,22 using a phenomenological hermeneutic approach aims to describe the manifest meaning of the transcribed text. Subsequently, through interpretation the latent meaning is extracted, which goes beyond what is said and thus reflects a deeper understanding. After an initial reading and re-reading of the interviews to get a sense of the whole, the analysis proceeded by means of content analytical steps where essential meaning units were identified, and then coded. In this process, the analysis moved from the manifest to the latent content. After coding, three of the interviewers combined and arranged data in themes and sub-themes25 (Table 2). To take the researchers preunderstanding into consideration, the interviewers questioned each other's interpretations until consensus was reached. All researchers discussed and approved the final analysis. Table 2. Extract of the analysis. Quotes from the text Condensed meaning units: manifest content Condensed meaning units: latent content Codes Themes It was LONELY [trembling in her voice] a loneliness I have never felt before, feeling UNSAFE, AFRAID. My husband could have held my hand and given me a feeling of physical safety (patient 4) The patient felt lonely and insecure and missed the support of her husband who helped her to feel safe When patients enter the hospital without their relatives it left them with feelings of being unwillingly separated from their relatives Loneliness and broken bonds Feeling lonely and insecure I got the answers and results and then I phoned my husband. Then, he asked me questions I was unable to answer … When the professionals came back, I asked them and subsequently I phoned my husband again to inform him. I felt I was in-between, which I didn't need in my condition (patient 14) Being without physical contact with the relatives meant that the patient had to ask and needed to be informed more than once and that she became caught between her husband and the HCPs The patients were expected to take responsibility for being a conduit of information and were caught between their relatives and the HCPs The role as mediator Remembering and comprehending information – caught between relatives and professionals I was simply feeling so sick, so it was actually a bit of a relief that no one came. And I had no surplus at all for anything else than myself (patient 13) (…) Anyway, I got my three meals, my medicine, I got my surgery and I am alive, but no one was sitting at my bedside and acknowledged my sorrow of losing an embryo and having been afraid of dying (patient 15) Lacking surplus energy, the patients expressed feeling relieved that the restrictions set the framework for visits. Furthermore, at the same time, they stated that they aware of their need for a close relative to be present The restrictions proved to have both advantages and disadvantages. The patients often lacked surplus energy to interact with relatives but at the same time found them indispensable for their informal care Benefits of restrictions Disadvantages of restrictions Absence of relatives –benefit or burden? HCP, healthcare professional. Ethical considerations The Regional Danish Data Protection Agency (ID 2020-072) was notified of the study and the regulations regarding research ethics and data management were followed.26,27 According to Danish legislation, no further ethical approval was needed. The participants received information about the study in written and oral form and provided informed, written consent when agreeing to participate. Findings The analysis resulted in three themes covering the patients experience of relationships and collaboration with relatives and nurses. The first theme described how loneliness and insecurity emerged when patients were separated from the relatives. The second theme revealed how patients felt caught between relatives and nurses when they were required to remember and comprehend information. The third theme showed how the absence of relatives during the patients’ hospital contact was experienced as both a benefit and a burden. Feeling lonely and insecure Irrespective of whether the patients attended the hospital for an acute illness, to give birth, or to undergo an examination, the relatives were asked not to come to the hospital to control the spread of the virus. The separation from one's relatives started as soon as the patients entered hospital grounds when relatives had to say their goodbyes outside, as if there was an invisible gate that signaled “No relatives are allowed in.” This restriction was enforced despite patients reporting extreme tiredness, pain, or being in labor.We drove to the hospital, and I was dropped off. My husband was not allowed to support me although I was barely able to crawl through the door (patient 13). Although the relatives could attend during active labor, they were excluded in the process up to the birth regardless of whether it lasted a few or many hours. This exclusion prevented a husband from supporting his wife during their child’s birth and kept the couple from sharing the full experience of becoming parents.Suddenly it became MY project, but it is not only MY child. It is OUR child. Although it is me who bears the child, he is as much a part of it as I am. He was excluded unwillingly because he wanted to take part in it all (patient 9). The requirement of entering the hospital without a relative left the patients seeking alternative solutions. They described how relatives stayed in their cars outside the hospital or drove around in the neighborhood waiting to be allowed to enter the hospital in case of an imminent birth or other critical conditions. In this way, the patients managed to keep their relatives nearby – though at a distance. Being separated from one's relative in a vulnerable situation caused feelings of loneliness, anxiety, and insecurity. This was expressed by a patient in his late 20s who was controlled for relapse of his cancer: “My dad has ALWAYS been involved in ALL scans since I was 15 years old. It is a ritual that provides safety” (patient 3). Another patient was on the verge of crying when she recalled her feelings at admission:It was LONELY [trembling in her voice], a loneliness I have never felt before, feeling UNSAFE, AFRAID. My husband could have held my hand and given me a feeling of physical safety (patient 4). Thus, the presence of relatives seemed crucial for safeguarding the patients because they knew them mentally, physically, and offered care and attention. The relatives also provided data of the patient's normal condition and habitual appearance. A woman suffering from severe high blood pressure after giving birth (undiagnosed pre-eclampsia) was nearly discharged. However, when her mother came to bring her home, she noticed that something was very wrong:My mom knows me in and out … she noticed that my body looked wrong, and she said it several times. She couldn't explain what it was, but she noticed I wasn't as I was supposed to be (patient 6). The mother's observation and persistence served as indispensable contributions to keeping the patient safe as she was subsequently transferred to the intensive care unit for treatment. In addition, the relatives could help patients with fundamental care needs. After having a surgery, the patient was informed of the importance of eating and drinking. However, she was only offered food and beverages at the three main meals.We can benefit from relatives because often you would like them to help, and they want to help. They notice it is a while since you had something to eat and drink (patient 15). Thus, the absence of the relatives potentially influenced the patients’ ability to be sufficiently nourished and hydrated during the day. Besides being unwillingly separated from one's relatives and the risk of feeling lonely and exposed to insufficient nursing care, the COVID-19 restrictions put an additional burden on the patients to understand and remember information. Remembering and comprehending information: Caught between relatives and nurses Patients were aware that vulnerable situations affected them mentally and emotionally. The absence of their relatives required them on their own to remember and comprehend information, ask the right questions, and keep an overview of the situation. This was difficult due to emotional constraints, and due to medication-induced sedation.I was very dazed because I got morphine and I was totally unable to remember anything. In this situation, it would have been great if my relatives were there when the professionals gave information (patient 5). This quote shows how an extra pair of ears could have helped patients remember and process information. In addition, the presence of relatives could lessen anxiety and worries as they possessed knowledge and understood the patients’ symptoms, sometimes better than the patients themselves. A patient diagnosed with lung and kidney cancer was treated for his lung cancer. He worried about his rapidly deteriorating condition.It would have meant a lot to me if I could have brought my wife and shared my worries with her because she knows more about my illness and the situation. I was afraid that my cancer exploded. I could have asked questions myself and angled for more information, but I belong to the generation who will not strain the nurses when they are busy (patient 2). The situation was overwhelming, and the patient was unable to comprehend all that happened. His wife, who worked in the healthcare sector, could have provided an indispensable support in this situation. Her absence contributed to an increased anxiety because the patient was unable to understand that his symptoms were side-effects from the treatment and not generated by his cancer. For this patient, it seemed essential that the nurses were able to read his needs and offered him help to evaluate and adapt the information that he did not demand for himself. However, irrespective of their condition, the patients were expected to take on the role as information mediators between relatives and nurses: “I was asked ‘have you brought your telephone to call your relative?” (patient 15). Although the patients felt exhausted and had a delimited ability to remember and process information, they displayed concerns about how to share the information properly. Consequently, some called their relatives repeatedly because they did not ask the questions the relatives needed answering.I got the answers and results and then I phoned my husband. Then, he asked me questions I was unable to answer … When the professionals came back, I asked them and subsequently I phoned my husband again to inform him (patient 14). Given the responsibility of sharing information and securing collaboration with the nurses and relatives, the informants acquired the role of a person that was “in between,” a dyad facing the relatives on one side and the nurses on the other. As one patient noted: “I felt I was in between, which I didn't need in my condition” (patient 14). The responsibility of being the mediator of information sharing triggered an additional burden on the patients and influenced the relationship with the relatives. Being in a serious condition and lacking surplus energy, a patient said: “I became short-tempered because I was feeling so sick. I just wanted to be on my own” (patient 13). In such situations there was a risk that patients had to cease telephone communication with the relatives to protect themselves. This diminished the relatives’ ability to be involved in the patients’ course of illness as well as the patients access to emotional support from their relatives. Absence of relatives: Benefit or burden? Although acknowledging the need for a present relative for support, it appeared evident that the COVID-19 restrictions also benefitted the patients when they felt seriously ill and without the surplus energy to relate to visitors.I was so sick and did not have the strength to think about anything else. The HCPs worked like horses, and they did everything for me. So, (no) I did not miss my husband (patient 1). When the patients were most affected by their disease, their need for professional assistance was at the forefront and their need for a close relative being present became secondary. In such acute situations, the patients’ focus was on getting cured or simply staying alive, and for this the support from the professionals was indispensable. In addition, the visitation restrictions on at the hospital resulted in a calm environment, where the patients found time and space to recover without being disturbed.I really think it depends on what you are there for. I was simply feeling so sick, so it was actually a bit of a relief that no one came. And I had no surplus at all for anything else than myself (patient 13). Another said, “It was a benefit because I didn't have to decide myself whether I wanted visitors or not” (patient 11). Thus, on the one hand, the patients had a lack of surplus energy and felt relieved that the restrictions set the framework for visits. On the other hand, the patients were aware of their need for a close relative to be present, as illustrated in the following quote: “It would have been nice to have had my husband present, but I did not need him to be (at that point of time)” (patient 9). Accordingly, it appeared to be the patients’ condition that was the main determinant of their need to have a relative present. However, the absence of relatives appeared to emphasize the patients’ need of person-centered care provided by the nurses and revealed a need that the nurses acted as a substitute for their missing relatives.I respect the nurses very much, but in the case where the relatives were excluded, I needed the nurses to understand my situation in another way. Sometimes they did, and sometimes they did not, and this was tough (patient 4). According to this quote, the patient experienced a lack of emotional support. This was underlined by another patient who sought a relationship with the nurses where personal issues could be discussed:I think the nurses had the best intentions. However, it seemed they lacked resources. They were running around like [they were] in a chicken yard trying to put out a fire … Anyway, I got my three meals, my medicine, I got my surgery, and I am alive, but no one was sitting at my bedside acknowledging my sorrow at losing an embryo and having been afraid of dying (patient 15). Busyness and lack of resources seemed to inhibit “good nursing care” when the nurses had to prioritize tasks. This involved the provision of a minimum of care that meant to keep the patients safe physically. In this respect, the patients’ emotional contact with the nurses was not maintained adequately. The perception of missing emotional support was further increased as the patients’ perceived a fundamental change in the nurses’ behavior regarding proximity. Physical distance was exercised in the encounters unless nurses were measuring blood pressure, giving medicine, helping with personal hygiene, breastfeeding, and so on, as this patient described: “They were not shaking hands or giving hugs although I could see they wanted to do so because I cried and was unhappy” (patient 6). Another said:I think the nurses kept a distance more than normally. They did not put a hand on a shoulder or contribute to close and warm contact … I felt they were restricting themselves (patient 10). Hence, the patients noticed how the nurses restricted themselves and limited physical contact in their endeavor to conform to the requirements of using PPE and distance. Although the patients acknowledged the nurses “were constrained due to the coronavirus” (patient 2), the patients clearly requested recognition of how the restricted physical contact affected their experience of comfort and care. Discussion The aim of the study was to explore patients’ experiences of their relationships with relatives and collaboration with nurses during in- and outpatient contact in non-COVID-19 hospital wards. Our study demonstrated that the COVID-19 restrictions induced separation from relatives made the patients feel lonely. Furthermore, it increased their vulnerability and anxiety, which ultimately left patients with feelings of being unsafe. This is in line with the study by Meide et al.,28 where busyness of HCPs and their focus on technical aspects of care negatively impacted on older patients’ participation and left them feeling lonely during hospitalization. However, our findings underlined that loneliness was not reserved for older patients, as younger patients equally experienced distress from being separated from their family. Comparable findings are revealed by Gonzales et al.,29 as visitors to patients in intensive care offered the patients moderate levels of reassurance, comfort, and calming. In our study, the patients experienced separation from their relatives as an unwilling exclusion. As dignity and respect are central concepts in family-centered care and core values in nursing ethics.11,12,30 This could be interpreted as they were deprived of their right to self-determination and the exercise of their personal values on how to involve their relatives. Our patients expected becoming parents to be a shared experience. However, the restrictions resulted in separation of the couple, which clearly affected the women giving birth as their partners were deprived of getting “the full experience.” This indicated an underlying distressing feeling of being forced to take responsibility for healthcare decisions for themselves and their unborn child. Corbet et al.31 showed health anxiety among pregnant women during the COVID-19 pandemic; they worried about their unborn child and themselves, which is congruent with our findings. In our study, health anxiety was seen in women in labor but also in patients experiencing acute illness. As described by Jarvis et al.,32 COVID-19 is a family-unfriendly virus. A family structure, such as the father being the only constant for his son during his cancer trajectory, was required to be put on hold. Our study pointed out that patients often became solely responsible for their own health and for finding ways to involve the relatives. In this case, the patient was denied the opportunity to involve the family as a resource, which is claimed to be important for family and person-centered care.10,33 Thus, the impact of COVID-19 on usual family structure and collaboration is considered extensive as the emotional ties, sense of belonging, and passion for being involved in one another's lives was severely affected. The exclusion of relatives required the patients to be information mediators between relatives and HCPs, which put an additional burden on them. An example was the mother in our study who persistently communicated her observation to the nurses, which subsequently influenced her daughter's safety and recovery. This is in line with Zani et al.34 and Conn et al.,3 where the representation of relatives at the hospital supported the patients’ safety and recovery as relatives contributed with observations and could warn HCPs of changes in the patients’ habitual condition. However, being left alone and positioned between relatives and HCPs caused a breakdown in the collaborative triad between the parties, which is essential for family-centered care.9 The ultimate consequence could be a fragmented nursing care, which compromises feelings of safety and prolongs recovery for the patients. Our study evidently displayed how patients, young or old, and regardless of their condition, became responsible for information sharing as they were asked to phone and update their relatives. This finding was also displayed in the study by Krewulak et al.,4 which underlined the difficulties patients experience when being expected to take responsibility for information sharing. Our study revealed the importance of finding alternative ways to bridge the distance between HCPs and the relatives to free the patients from an unnecessary burden. According to the FoC framework, the responsibility for establishing and maintaining a relationship relies on the nurses.17–19 Goldfarb et al.35 and Hart et al.12 suggested different ways of structuring and scheduling communication between the family and HCPs as well as facilitating phone or videoconferencing between patients and their families. This was shown to relieve patients of being solely responsible for the exchange of information. The patients’ experienced their most vital care needs being met, but to a lesser degree their psychosocial needs; for example, the patient who was encouraged to eat frequently, yet was only offered three meals a day. Consequently, having to ask for extra food, drinks, or help was perceived as uncaring and transgressive for the patient. The absence of relatives who could help with fundamental care needs such as nutrition, induced the patient's responsibility for self-care. However, our findings revealed conflicting feelings regarding excluding relatives since the patients openly stated how they were relieved as visitation restrictions gave space for rest and healing. This is in line with the study by Jørgensen et al.,2 where nurses described how visitation restrictions during COVID-19 contributed with less disturbances during the day. However, an increase in telephone contacts from relatives seemed to eat up most of the spare time. This could question the liberal and unrestricted visiting policies exercised in most hospitals throughout the day. A review on open visiting hours in an intensive care ward revealed that patients found it relaxing to have relatives nearby, but they also desired some limitations to the visits.36 This is in accordance with the study of Tanner,37 who showed that neither patients nor relatives preferred open visiting options. These findings diverge from a study that found unrestricted visiting hours preferable, although this flexibility should address the patients’ need for rest and privacy, for instance when receiving nursing care.38 In line with this, our findings indicated that patients needed nursing care that supported their psychosocial needs, respected their preferences, and contributed with time and space for recovery. In other words, a nursing care that supported a person-centered approach.17,18 Our findings showed that the absence of relatives increased the patients need for nurses to be a substitute for their relatives and to a higher degree provide physical and psychosocial help and support. However, the high level of busyness forced nurses to prioritize tasks. Moreover, the nurses’ behavior regarding proximity contributed to an (at times) inadequate provision of person-centered nursing care. These aspects could have been caused specifically by the COVID-19 pandemic. However, studies conducted before the pandemic confirm that higher workloads of nurses are associated with adverse patient outcomes,39,40 and high patient satisfaction is associated with higher patient-to-nurse ratios and negatively associated with inadequate nurse staffing.41 Thus, our study underlined how the COVID-19 pandemic from a patient perspective increased the nurses’ busyness and affected their prioritizing of tasks resulting in an (at times) inadequate person-centered care. Methodological considerations In this qualitative study, 15 interviewees contributed information power, as suggested by Malterud et al.42 Volunteering was a strength of this study because the patients’ participation was based on a desire to contribute with their perspective. However, seeking participants on the hospital website and Facebook may have appealed to a younger population as this group is often more comfortable using these technologies.43 This is reflected in our sample, with three participants aged over 50 years and with a mean age of 37.4 years (range, 27–74 years). Trustworthiness of this study was secured through a transparent and systematic data collection and analysis including the patients’ quotations to verify the findings. The researchers continuously discussed data until consensus was reached, which supported consistency and trustworthiness.25 Using investigator triangulation is considered a strength.44 All interviewers were experienced in interviewing which may counterbalance the fact that every researcher performed a limited number of interviews. Conclusion This study revealed how patients’ collaboration with the nurses and their ability to maintain a relation with relatives became extensively affected during the COVID-19 pandemic. The restrictions imposed an additional distancing from the nurses unless they were performing instrumental tasks, which resulted in an insufficient physical and psychosocial care. This clearly burdened the patients as it required them to be responsible for self-care in a situation characterized by acute illness, vulnerability, and insecurity. In addition, the unwilling exclusion of relatives could compromise the patients right to self-determination and affect their dignity. Visitor restrictions were experienced to be both positive and negative. They provided patients with time to heal but prevented them from receiving informal care that appeared essential because of the COVID-19 induced restrictions with distancing and an increased business of the nurses. Furthermore, the COVID-19 restrictions resulted in an increased demand for patients to mediate between relatives and HCPs and take responsibility for maintaining contact with relatives irrespective of their health condition. These demands further overloaded the patients in their situation of acute illness, vulnerability, and insecurity. The implications of this study during future pandemics highlights how a pandemic affects the nursing care of patients on non-pandemic wards. The preventive measures for further transmission of the virus severely challenge the physical and psychosocial wellbeing of the patients. To accommodate this, nurses and other HCPs must be ready to create new ways of ensuring collaboration between themselves and relatives to alleviate the patients’ burden of being responsible for their own care and information mediation. One way of involving all relevant parties could be through scheduled communication sessions (videoconferencing) between the family, nurses, and other HCPs. This has the potential of supporting family-centered care. In addition, the study points to the need to consider a controlled, yet still flexible and individualized, visiting policy to ensure the patients’ time to rest and heal. Acknowledgments We would like to thank the participants for their valuable contributions, learning from their perspective how it was experienced to be in contact with Aalborg University Hospital during the COVID-19 lockdown. The study was designed and conducted in collaboration with researchers affiliated to the Clinical Nursing Research Unit, Aalborg University Hospital, Denmark. BP, BL, LJ, CBT, HH, and KB conducted the interviews. BP, KB, and BL primarily analyzed the data and drafted the paper. All authors contributed to revising and approving the paper that presents the original results of the research. The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding: The authors received no financial support for the research, authorship, and/or publication of this article ORCID iDs: Birgith Pedersen https://orcid.org/0000-0002-7688-4362 Lone Jørgensen https://orcid.org/0000-0002-4197-3066 Kathrine Hoffmann Kusk https://orcid.org/0000-0002-7695-3639 Karin Bundgaard https://orcid.org/0000-0002-8411-1837 ==== Refs References 1 Nielsen DS Dieperink KB . Cultural perspectives and nurses reactions on the corona pandemic: a critical view from Denmark. J Transcult Nurs 2020; 31 : 333–336.32362211 2 Jørgensen L Pedersen B Lerbæk B , et al . Nursing care during COVID-19 at non-COVID-19 hospital units: a qualitative study. Nord J Nurs Res 2022; 42: 101–108.35729941 3 Conn LG Coburn NG Prospero LD , et al . Restricted family presence for hospitalized surgical patients during the COVID-19 pandemic: how hospital care providers and families navigated ethical tensions and experiences of institutional betrayal. SSM Qual Res Health 2022; 2 : 100147.35937964 4 Krewulak KD Jaworska N Spence KL , et al . Impact of restricted visitation policies during the first wave of the COVID-19 pandemic on communication between critically ill patients, families, and clinicians. Ann Am Thor Soc 2022; 19 : 1169–1176. 5 Hoffmann E Olsen PR . Like an ace up the sleeve: an interview study of nurses’ experiences of the contact with relatives in a somatic emergency ward. J Caring Sci 2018; 32 : 1207–1214. 6 Partanen E Lemetti T Haavisto E . Participation of relatives in the care of cancer patients in hospital—A scoping review. Eur J Cancer Care 2018; 27: e12821 . 7 Norlyk A Martinsen B . The extended arm of health professionals? Relatives’ experiences of patient’s recovery in a fast-track programme. J Adv Nurs 2013; 69 : 1737–1746.23072717 8 Dyrstad DN Laugaland KA Storm M . An observational study of older patients’ participation in hospital admission and discharge - exploring patient and next of kin perspectives. J Clin Nurs 2015; 24 : 1693–1706.25727777 9 Nors TB Sestoft B Dreyer P . Patients’ perspectives on relatives in the perioperative setting: a Danish study. Assoc PeriOper Reg Nurs J 2020; 111 : e1–e11. 10 Østergaard B Wagner L . The development of family nursing in Denmark: current status and future perspectives. J Fam Nurs 2014; 20 : 487–500.25398384 11 Canadian Foundation for Healthcare Improvement. Better together: Reintegration of family caregivers as essential partners in care in a time of COVID-19. 2020. Available at: https://www.cfhifcass.ca/docs/default-source/itr/tools-and-resources/bt-re-integration-of-family-caregivers-asessential-partners-covid-19-e.pdf?sfvrsn=5b3d8f3d_2. 12 Hart JL Turnbull AE Oppenheim IM , et al. Family-centered care during the COVID-19 era. J Pain Symptome Manag 2020; 60 : e93–e97. 13 Griffin T . Family-centered care in the NICU. J Perinat Neonat Nurs 2006; 20 : 98–102. 14 Park M Giap TT . Patient and family engagement as a potential approach for improving patient safety: a systematic review. J Adv Nurs 2020; 76 : 62–80.31588602 15 WHO (World Health Organization). Patient Engagement. Technical Series on Safer Primary Care. Geneva: World Health Organization, 2016. Available at: https://apps.who.int/iris/bitstream/handle/10665/252269/9789241511629-eng.pdf. 16 Cypress BS . Using the synergy model of patient care in understanding the lived emergency department experiences of patients, family members and their nurses during critical illness: a phenomenological study. Dimens Crit Care Nurs 2013; 32 : 310–321.24100433 17 Kitson AL . The fundamentals of care framework as a point-of-care nursing theory. Nurs Res 2018; 67 : 99–107.29489631 18 Feo R Kitson A Conroy T . How fundamental aspects of nursing care are defined in the literature: a scoping review. J Clin Nurs 2018; 27 : 2189–2229.29514402 19 Kitson A Conroy T Kuluski K , et al. Reclaiming and Redefining the Fundamentals of Care: Nursing’s Response to Meeting Patients’ Basic Human Needs. Adelaide, South Australia: School of Nursing, The University of Adelaide, 2013. 20 Gustafsson N Leino-Kilpi H Prga I , et al. Missed care from the patient’s perspective – a scoping review. Patient Prefer Adherence 2020; 14 : 383–400.32161449 21 Smith S Lapkin S Sim J , et al. Nursing care left undone, practice environment and perceived quality of care in small rural hospitals. J Nurs Manag 2020; 28 : 2166–2173.32034965 22 Brinkmann S Kvale S . InterViews: Learning the Craft of Qualitative Research Interviewing. 3rd ed. Los Angeles, CA: Sage, 2015. 23 Tong A Sainsbury P Craig J . Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care 2007; 19 : 349–357.17872937 24 Polit DF Beck CT . Nursing Research: Generating and Assessing Evidence for Nursing Practice (9th ed.). Philadelphia, PA: Wolters Kluwer Health. Lippincott Williams and Wilkins, 2012. 25 Graneheim UH Lundman B . Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness. Nurse Educ Today 2004; 24 : 105–112.14769454 26 WMA (World Medical Association). WMA declaration of Helsinki – Ethical principles for medical research involving human subjects. 2018 [updated 2018]. Available at: https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/. 27 Nordic Nurses. Ethical Guidelines for Nursing Research in the Nordic Countries. 4th ed. Oslo: Allservice AS, 2003. 28 Meide H Olthuis G Leget C . Feeling an outsider left in uncertainty – a phenomenological study on the experiences of older hospital patients. Scand J Caring Sci 2015; 29 : 528–536.25376968 29 Gonzalez CE Carroll DL Elliott JS , et al. Visiting preferences of patients in the intensive care unit and in a complex care medical unit. Am J Crit Care 2004; 13 : 194–198.15149052 30 International Council of Nurses. The ICN code of ethics for nurses. 2012. Available at: https://www.icn.ch/sites/default/files/inline-files/2012_ICN_Codeofethicsfornurses_%20eng.pdf. 31 Corbett GA Milne SJ Hehir MP , et al. Health anxiety and behavioural changes of pregnant women during the COVID-19 pandemic. Eur J Obstet Gynecol Reprod Biol 2020; 249 : 96–97.32317197 32 Jarvis MA Oyegbile YO Brysiewicz P . COVID-19, the family unfriendly virus: Is the family’s experience of the ED relevant within the confines of a pandemic? Int Emerg Nurs 2021; 54 . 100960. 33 Ekman I Swedberg K Taft C , et al . Person-centered care--ready for prime time. Eur J Cardiovasc Nurs 2011; 10 : 248–251.21764386 34 Zani AV Marcon SS Tonete VLP , et al. Communicative process in the emergency department between nursing staff and patients: social representations. Br J Nurs 2014; 13 : 11. 35 Goldfarb M Bibas L Burns K . Family engagement in the cardiovascular intensive care unit in the COVID-19 era. Can J Cardiol 2020; 36 : 1327 e1321–1327 e1322. 36 Whitton S Pittiglio LI . Critical care open visiting hours. Crit Care Nurs Q 2011; 34 : 361–366.21921719 37 Tanner J . Visiting time preferences of patients, visitors and staff. Nurs Times 2005; 101 : 38–42. 38 Carroll DL Gonzalez CE . Visiting preferences of cardiovascular patients. Prog Cardiovasc Nurs 2009; 24 : 149–154.20002339 39 Griffiths P Ball J Murrells T , et al. Registered nurse, healthcare support worker, medical staffing levels and mortality in English hospital trusts: a cross-sectional study. BMJ Open 2016; 6 : e008751. 40 Ball JE Bruyneel L Aiken LH , et al. Post-operative mortality, missed care and nurse staffing in nine countries: a cross-sectional study. Int J Nurs Stud 2018; 78 : 10–15.28844649 41 Aiken LH Sloane DM Ball J , et al. Patient satisfaction with hospital care and nurses in England: an observational study. BMJ Open 2018; 8 : e019189. 42 Malterud K Siersma VD Guassora AD . Sample size in qualitative interview studies: guided by information power. Qual Health Res 2016; 26 : 1753–1760.26613970 43 LaMonica HM Davenport TA Roberts AE , et al. Understanding technology preferences and requirements for health information technologies designed to improve and maintain the mental health and well-being of older adults: participatory design study. J Med Internet Res Aging 2021; 4 : e21461. 44 Carter N Bryant-Lukosius D DiCenso A , et al. The use of triangulation in qualitative research. Oncol Nurs Forum 2014; 41 : 545–547.25158659
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==== Front J Perioper Pract J Perioper Pract PPJ spppj Journal of Perioperative Practice 1750-4589 2515-7949 SAGE Publications Sage UK: London, England 36482722 10.1177/17504589221132404 10.1177_17504589221132404 Review Pharmacologic methods to minimise coughing during extubation in the era of COVID-19 Chabot Katherine 1 https://orcid.org/0000-0003-3859-5110 Yang Stephen Su 123 1 Department of Anaesthesia, McGill University, Montreal, QC, Canada 2 Division of Critical Care, McGill University, Montreal, QC, Canada 3 Lady Davis Institute of Research, Jewish General Hospital, Montreal, QC, Canada Stephen Su Yang, Lady Davis Institute of Research, Jewish General Hospital, Pavilion K-1400, 3755 chemin de la Cote Sainte Catherine Road, Montreal, QC H3T 1E2, Canada. Email: [email protected] 8 12 2022 8 12 2022 17504589221132404© The Author(s) 2022 2022 Association for Perioperative Practice This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. Background/aim: Given the current severe acute respiratory syndrome coronavirus 2 pandemic, coughing at the time of extubation is at risk of creating aerosolisation. This may place health care workers at risk of nosocomial infection during the perioperative period. This study aims to summarise the current pharmacologic methods to minimise cough at the time of extubation, and to determine whether some strategies could be more beneficial than others. Methods: This is a summary of systematic reviews. A comprehensive search through MEDLINE was performed. Thirty-three publications were screened for eligibility. Only the manuscripts discussing pharmacologic methods to minimise coughing on extubation were included in this review. Findings: Many pharmacological agents have been proposed to decrease the incidence of cough at the time of extubation. Of these, intravenous administration of dexmedetomidine (relative risk 0.4; 95% CI: 0.4–0.5) or remifentanil (RR 0.4; 95% CI: 0.4–0.5) seems to have the largest effect to reduce cough on extubation. Conclusion: The available data in the current literature is sparse. Yet, dexmedetomidine and remifentanil seem to be the most efficient agents to decrease the incidence of emergence coughing. Aerosol-generating procedures Airway management COVID-19 Tracheal intubation Anaesthesia edited-statecorrected-proof typesetterts1 ==== Body pmcIntroduction Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in December 2019 and has claimed over six million lives (John Hopkins University 2020, Yang et al 2020a). Its transmission occurs mostly through respiratory droplets (>5µm) and aerosol (<5µm particles) that can remain suspended in the air for prolonged periods (Meyerowitz et al 2021). Clinicians who perform airway procedures, such as tracheal intubation and extubation, are particularly at risk of contracting severe respiratory viral infections such as SARS-CoV-2, as these procedures are considered aerosol-generating procedures (odds ratio [OR] 6.6; 95% confidence interval [CI]: 2.3–18.9) (Jackson et al 2020, Tran et al 2012, Zayas et al 2012). More examples of aerosol-generating airway procedures include airway suctioning, tracheostomy and cardiopulmonary resuscitation (Schimmel & Berkowitz 2022). A recent publication suggests that 1 in 10 health care workers involved in airway management of suspected or confirmed COVID-19 patients subsequently reported infection (El-Boghdadly et al 2020). Coughing is commonly seen during extubation of a surgical patient; in fact, coughing occurs up to 15 times more common during extubation than during intubation and may contribute to additional aerosolisation (Asai et al 1998, Brown et al 2021). Therefore, minimising coughing during extubation is essential to mitigate the risk of nosocomial transmission (Wilson et al 2020). Clinicians have explored various innovative barrier methods to minimise the dispersion of aerosols during emergence from general anaesthesia. Some examples of these methods include the use of plastic sheets (Matava et al 2020) or a protection box (Yang et al 2020c). Although a barrier method may appear to be effective, they add an additional level of complexity to airway management and may delay the time of intubation (Begley et al 2020). Compared with barrier methods, a pharmacologic strategy offers the advantage of minimising disruption from a routine anaesthetic practice. We aim to summarise the current perioperative pharmacologic methods to minimise cough at the time of extubation, which is particularly beneficial given the current pandemic. We also aim to determine which strategy would be the most beneficial. Method For this summary of systematic reviews, we performed a comprehensive search through MEDLINE using the following search strategy: (intubation[tiab] OR extubation[tiab]) AND (cough*[tiab]) AND (systematic review[tiab]) from inception to 1 November 2021. A total of 33 publications resulted from this search strategy and were screened for eligibility. Publications were considered eligible for review if they were systematic reviews, including adult patients undergoing surgery under general anaesthesia with tracheal intubation. Only the manuscripts discussing pharmacologic methods to minimise coughing on extubation were included in this review. Exclusion criteria also include (1) study limited to the paediatric population, (2) study not performed in a perioperative setting, (3) no discussion of tracheal intubation and (4) coughing on intubation only. There were no language limits. Results Thirty-three articles were eligible based on the initial search. After title and abstract screening, five full-text articles were reviewed. One article was excluded because the outcome of interest was coughing on intubation only (Clivio et al 2019). Four systematic reviews were included for analysis (Figure 1). Many pharmacological interventions have been proposed to decrease the incidence of cough at the time of extubation. These include the use of lidocaine (either intravenous (IV), intracuff or topical), IV opioids and dexmedetomidine (Table 1). In a population of 1516 patients, the use of IV lidocaine demonstrated a decrease in the incidence of cough at extubation (relative risk (RR) 0.6; 95% CI: 0.5–0.9) (Yang et al 2020b). Similarly, the use of intracuff lidocaine (n = 963) (RR 0.6; 95% CI: 0.5–0.7) and tracheal tube lidocaine (n = 495) (RR 0.7; 95% CI: 0.6–0.8) also had similar effects to reduce cough (Tung et al 2020). In another systematic review of 868 patients, the use of intracuff lidocaine resulted in a significant decrease in the incidence of cough at the time of extubation (RR 0.5; 95% CI 0.3–0.7) (Peng et al 2020). In a large systematic review of 2146 patients, the use of lidocaine lubricants did not result in a statistical difference in the incidence of cough at the time of extubation (RR 0.9; 95% CI: 0.7–1.2) (Liao et al 2019). The use of dexmedetomidine (n = 857) (RR 0.4; 95% CI: 0.4–0.5), fentanyl (n = 126) (RR 0.5; 95% CI: 0.4–0.6) and remifentanil (n = 571) (RR 0.4; 95% CI: 0.4–0.5) all had large effect size to minimise coughing at extubation (Figure 2) (Tung et al 2020). There were no reported adverse events in any of the systematic reviews, although the use of dexmedetomidine was associated with bradycardia. An increase in time to extubation was seen in IV lidocaine (mean difference (MD) 1.9 min; 95% CI: 0.8–3.0 min), and intracuff lidocaine (MD 5.3 min; 95% CI: 1.9–8.8 min) (Tung et al 2020, Yang et al 2020b). The other strategies did not result in a statistically significant difference in time to extubation (Liao et al 2019, Tung et al 2020). Figure 1 Flow diagram of systematic review selection Figure 2 Pharmacologic interventions to reduce cough during extubation. Data are relative risks (RR) of coughing on extubation and 95% confidence intervals (CI), compared with placebo. Intracuff lidocaine = Tung et al. Intracuff lidocaine (2) = Peng et al Table 1 Summary of pharmacologic methods to minimise cough during extubation Authors (year) Surgical population Number of participants Intervention Doses Cough prevention RR (95% CI) Yang et al (2020b) GS, GYN, Neuro, Oph, Ortho, OTL, Uro. 1516 IV Lidocaine 1–2mg kg–1 0.6 (0.5–0.9) Tung et al (2020) a Any elective 963 Intracuff lidocaine Lidocaine 2% × 2–6mL Lidocaine 4% × 5mL 0.6 (0.5–0.7) Peng et al (2020) GYN, OTL, Dental, Opth, Spine, Plastic, Ortho, Uro 868 Intracuff lidocaine Lidocaine 1%–10% ± sodium bicarbonate 0.5 (0.3–0.7) Liao et al (2019) GS, GYN, Ortho, OTL 2146 Lidocaine lubricants Not reported 0.9 (0.7–1.2) Tung et al (2020) a Any elective 495 TT lidocaine 1–2mg kg −1 0.7 (0.6–0.8) Tung et al (2020) a Any elective 857 IV dexmedetomidine 0.25–1.2μg kg−1 0.4 (0.4–0.5) Tung et al (2020) a Any elective 126 IV fentanyl 1–2μg kg−1 0.5 (0.4–0.6) Tung et al (2020) a Any elective 571 IV remifentanil Bolus: 0.1–1.0μg kg−1 Inf: 0.001–0.3μg kg −1 min−1 0.4 (0.4–0.5) CI: confidence interval; GS: general surgery; GYN: gynaecology; Neuro: neurosurgery; OTL: otorhinolaryngology; Oph: ophthalmology; PS: plastic surgery; RR: relative risk versus placebo; TT: tracheal tube; Uro: urology. a Transformed data from absolute effects. Discussion The COVID-19 pandemic has raised awareness of the increased risk of viral transmission to health care workers when performing aerosol-generating procedures, especially tracheal extubation (Jackson et al 2020). This review aimed to summarise the current pharmacologic methods available to minimise cough at the time of extubation and to determine whether some strategies could be more beneficial than others. Based on the available data from various systematic reviews, dexmedetomidine and remifentanil seem to have the largest effect to reduce cough on extubation. Alternatively, the use of intracuff lidocaine is also an option to consider. The antitussive actions of opioids such as remifentanil are well known; opioids exert coughing suppression centrally by their effect on medullary cough centres. On the contrary, the mechanism(s) by which alpha-2 agonists, such as dexmedetomidine, exhibit cough suppressant effects remain unclear. One possible hypothesis may be related to the attenuation of C-fibre-mediated airway smooth muscle contraction (Mikami et al 2017). When we compare the RR of each medication (and their respective 95% CI), it seems like remifentanil and dexmedetomidine would be the optimal choice to decrease the incidence of coughing on extubation. However, the use of these medications would come with the caveat of adverse effects on respiratory drive, neuromuscular function and haemodynamics. Some concerns regarding prolongation of the extubation time when using medication to prevent coughing may also be raised. Although no statistical difference was seen in the systematic reviews included in this article, this may be due to an underpowered analysis. One could consider a combination of multiple strategies to prevent coughing on extubation would be even more effective and could minimise the side effects of each respective pharmacological agent. However, to the best of our knowledge, multimodal cough-prevention strategies have not yet been explored in randomised controlled trials. In addition, no retrospective study has been published to assess the strategies employed by health care workers who reported infection by SARS-CoV-2 after performing tracheal intubation or extubating of a patient with suspected or confirmed COVID-19. This summary of systematic reviews is limited by the sparse available data in the current literature. The generalisability of the effect size for each pharmacologic agent should be made with caution, as these systematic reviews may not include the same population of interest. Moreover, the systematic reviews performed by Liao et al 2019, Peng et al 2020 and Yang et al 2020b focused specifically on lidocaine lubricants and IV solutions, respectively, and did not examine the efficacy of alpha2-agonists and opioids on coughing prevention. On the contrary, Tung et al 2020 examined the efficacies of every pharmacologic agent included in this summary (lidocaine IV, intracuff, topical or tracheal application, dexmedetomidine, remifentanil and fentanyl). In other words, the only systematic review that assessed the effect of dexmedetomidine and remifentanil on cough prevention was that of Tung et al 2020. The authors concluded that all the medications studied (ie: lidocaine, dexmedetomidine, opioids) had the potential to decrease the incidence of coughing on extubation in comparison with either placebo or no medication. Yet, a post hoc ranking curve analysis (SUCRA) demonstrated that despite a lower number of participants to whom it was administered (857 participants versus 1458 having received lidocaine), dexmedetomidine had the highest likelihood of ranking first with regard to decreasing the incidence of emergence coughing, followed by remifentanil, which is consistent with our conclusion. Conclusion The results of this summary of systematic reviews are hypothesis-generating and emphasise the lack of available data at the present time. According to currently available systematic reviews, perioperative IV administration of dexmedetomidine and remifentanil, or intracuff injection of lidocaine, seem to have the largest effect on cough prevention at the time of tracheal extubation. Despite providing promising results, these pharmacologic agents should be further explored in a network meta-analysis to determine the granularity of the data. Furthermore, the relative efficacy for cough prevention and safety data for each medication should be determined with prospective randomised controlled trials. The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article. Funding: The author(s) received no financial support for the research, authorship and/or publication of this article. Provenance and Peer review: Unsolicited contribution; Peer reviewed; Accepted for publication 19 September 2022. ORCID iD: Stephen Su Yang https://orcid.org/0000-0003-3859-5110 ==== Refs References Asai T Koga K Vaughan RS 1998 Respiratory complications associated with tracheal intubation and extubation British Journal of Anaesthesia 80 767–775 9771306 Begley JL Lavery KE Nickson CP Brewster DJ 2020 The aerosol box for intubation in coronavirus disease 2019 patients: An in-situ simulation crossover study Anaesthesia 75 1014–1021 32397008 Brown J Gregson FKA Shrimpton A Cook TM Bzdek BR Reid JP Pickering AE 2021 A quantitative evaluation of aerosol generation during tracheal intubation and extubation Anaesthesia 76 174–181 Clivio S Putzu A Tramèr MR 2019 Intravenous lidocaine for the prevention of cough: Systematic review and meta-analysis of randomized controlled trials Anesthesia & Analgesia 129 1249–1255 30169416 El-Boghdadly K Wong DJN Owen R , et al 2020 Risks to healthcare workers following tracheal intubation of patients with COVID-19: A prospective international multicentre cohort study Anaesthesia 75 1437–1447 32516833 Jackson T Deibert D Wyatt G , et al 2020 Classification of aerosol-generating procedures: A rapid systematic review BMJ Open Respiratory Research 7 e000730 John Hopkins University 2020 Worldometer. COVID-19 Coronavirus Pandemic Available at https://www.worldometers.info/coronavirus Liao AH Yeoh SR Lin YC Lam F Chen T-L Chen C-Y 2019 Lidocaine lubricants for intubation-related complications: A systematic review and meta-analysis Can J Anaesth 66 1221–1239 31187403 Matava CT Yu J Denning S 2020 Clear plastic drapes may be effective at limiting aerosolization and droplet spray during extubation: Implications for COVID-19 Can J Anaesth 67 902–904 32246431 Meyerowitz EA Richterman A Gandhi RT Sax PE 2021 Transmission of SARS-CoV-2: A review of viral, host, and environmental factors Annals of Internal Medicine 174 69–79 Mikami M Zhang Y Kim B Worgall TS Groeben H Emala CW 2017 Dexmedetomidine’s inhibitory effects on acetylcholine release from cholinergic nerves in guinea pig trachea: A mechanism that accounts for its clinical benefit during airway irritation BMC Anesthesiology 17 52 Peng F Wang M Yang H Yang X Long M 2020 Efficacy of intracuff lidocaine in reducing coughing on tube: a systematic review and meta-analysis Journal of International Medical Research 48 (2 ) DOI: 10.1177/0300060520901872 Schimmel M Berkowitz DM 2022 Pulmonary procedures in the COVID-19 era Current Pulmonology Reports 11 39–47 35371910 Tran K Cimon K Severn M Pessoa-Silva CL Conly J 2012 Aerosol generating procedures and risk of transmission of acute respiratory infections to healthcare workers: A systematic review PLoS ONE 7 e35797 Tung A Fergusson NA Ng N Hu V Dormuth C Griesdale DEG 2020 Medications to reduce emergence coughing after general anaesthesia with tracheal intubation: A systematic review and network meta-analysis British Journal of Anaesthesia Epub ahead of print 22 February DOI 10.1016/j.bja.2019.12.041 Wilson NM Norton A Young FP Collins DW 2020 Airborne transmission of severe acute respiratory syndrome coronavirus-2 to healthcare workers: A narrative review Anaesthesia 75 1086–1095 32311771 Yang SS Lipes J Dial S , et al 2020a Outcomes and clinical practice in patients with COVID-19 admitted to the intensive care unit in Montréal, Canada: A descriptive analysis CMAJ Open 8 E788–E795 Yang SS Wang NN Postonogova T , et al 2020b Intravenous lidocaine to prevent postoperative airway complications in adults: A systematic review and meta-analysis British Journal of Anaesthesia 124 314–323 32000978 Yang SS Zhang M Chong JJR 2020c Comparison of three tracheal intubation methods for reducing droplet spread for use in COVID-19 patients British Journal of Anaesthesia 125 e190–e191 Zayas G Chiang MC Wong E MacDonald F Lange CF Senthilselvan A King M 2012 Cough aerosol in healthy participants: Fundamental knowledge to optimize droplet-spread infectious respiratory disease management BMC Pulmonary Medicine 12 11
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==== Front Workplace Health Saf Workplace Health Saf WHS spwhs Workplace Health & Safety 2165-0799 2165-0969 SAGE Publications Sage CA: Los Angeles, CA 36476243 10.1177/21650799221135583 10.1177_21650799221135583 Original Research Surface Contamination of Reusable Respirators and Face Shields During Care of Critically Ill COVID-19 Patients https://orcid.org/0000-0001-5908-3240 Shah Anand MD 1 Zhuang Eileen MD 1 German Jennifer PhD 2 Tai Sheldon PhD 2 Schanz Maria BA 2 Glendening Gabrielle 2 Mason Mackenzie 2 Kolesnik Olga MD 1 https://orcid.org/0000-0002-8350-9448 Hines Stella E. MD, MSPH 13 1 Division of Pulmonary and Critical Care Medicine, University of Maryland School of Medicine, Baltimore 2 University of Maryland, College Park 3 Division of Occupational and Environmental Medicine, University of Maryland School of Medicine, Baltimore Stella E. Hines, MD, MSPH, Division of Occupational and Environmental Medicine, University of Maryland School of Medicine, 11 South Paca Street, Suite 200, Baltimore, MD 21201, USA; email: [email protected]. 8 12 2022 8 12 2022 21650799221135583© 2022 The Author(s) 2022 American Association of Occupational Health Nurses This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. Background: With the emergence of SARS-CoV-2, healthcare workers (HCW) have relied on reusable personal protective equipment (PPE), including respirators and face shields (FSs). The effectiveness of decontamination procedures outside experimental settings is unclear. We examined the prevalence of surface contamination on reusable PPE used by HCWs at a hospital incorporating daily centralized decontamination and post-use wiping by sampling for common pathogens. Method: Samples were collected from HCWs’ CleanSpace Halo respirator face masks (FMs) and FSs at the start of shift, immediately after use, and after cleaning with disinfecting wipes. Samples were analyzed for pathogens using the Applied Biosystems™ TaqPath™ COVID-19 Combo Kit and ThermoFisher TaqMan Array Card. Patient charts were reviewed for clinical correlation. Findings: Of the 89 samples, 51 from FMs and 38 from FSs, none tested positive for SARS-CoV-2, despite 58 being obtained from PPE used in the care of patients with COVID-19, many with recent aerosol-generating procedures. Four samples tested positive (4.5%) for Staphylococcus aureus, two each from FMs and FSs. FMs that tested positive were not worn concurrently with FSs that tested positive. The FM and FS samples testing positive were worn in the care of patients without diagnosed S. aureus infection. No FMs tested positive following wipe-based disinfection, but both positive FS samples were found after disinfection wiping. Conclusion/Application to Practice: Contamination of reusable PPE appears uncommon, especially with SARS-CoV-2, when regular decontamination programs are in place. The rare presence of S. aureus highlights the importance of doffing procedures and hand hygiene by HCW to prevent surface contamination. SARS-CoV-2 personal protective equipment decontamination disinfection respiratory protective devices CleanSpace Technology Pty Ltd. CCT 3809-19 edited-statecorrected-proof typesetterts1 ==== Body pmcBackground Reusable respirator use increased during the COVID-19 pandemic due to shortages in disposable filtering facepiece respirators (FFRs; Hamby, 2020). Healthcare-based use of reusable respirators, such as elastomeric and powered air-purifying respirators (PAPRs), requires assurance that respirator surfaces do not harbor infectious agents or pose risk for fomite transmission to healthcare workers (HCWs) or patients. While COVID-19 infection arising from contact with infected surfaces is thought to be infrequent (Centers for Disease Prevention and Control [CDC], 2021), because contact transmission is possible, hospitals must ensure that reusable surfaces including respirators and face shield (FS) surfaces are adequately free of viral and other microbial contaminants. Prior studies have demonstrated that viruses such as influenza and SARS-CoV-2 can be detected and may retain infectivity for several days on surfaces of personal protective equipments (PPEs) including respirators (Kasloff et al., 2021; Marques & Domingo, 2021; Meyerowitz et al., 2021). Experimental studies show that influenza-contaminated reusable elastomeric respirator surfaces are completely disinfected following submersion in water with neutral detergent and chemical disinfectant solution (Lawrence et al., 2017). Hospitals have incorporated standardized, centralized, end-of-shift cleaning and disinfection of reusable respirators according to these protocols (Chalikonda et al., 2020; Hines et al., 2021; Koh et al., 2020). In between centralized disinfection, some hospitals instruct HCWs to clean their reusable respirators with disinfectant wipes (Hines et al., 2020). While chemical disinfectants show efficacy against a variety of pathogens, including SARS-CoV-2, it is unclear whether real-world use of chemical disinfectant wipes during a work shift adequately eliminates microbial pathogens from surfaces that could serve as fomites (U.S. Environmental Protection Agency [EPA], 2020). The CleanSpace ® HALO respirator is a reusable respirator that combines a tight-fitting clear, silicone face mask with a powered air mechanism, which was newly implemented for clinical use at several hospitals within a U.S. academic medical system in 2020. In a prior study, when CleanSpace HALO respirators were experimentally contaminated with influenza virus and simulated facial oil, cleaning of the face mask with detergent and disinfection with chemical disinfectant reliably eliminated the virus, but disinfection only with common hospital wipes did not (Hines et al., 2020). This experiment suggested that the practice of only requiring that a reusable respirator be wiped with a disinfectant wipe during healthcare use is inadequate with respect to the need for assurance of disinfection. In this study, we aimed to measure surface contamination on FSs and CleanSpace HALO respirator face masks (FMs) by SARS-CoV-2 and other pathogens during routine clinical use. We also evaluated differences in microbial surface contamination on FMs and FSs before and after wipe-based disinfection. We hypothesized that there would be low detectable levels of microbial contamination on the surfaces of FSs and FMs in routine clinical use and that real-world use of disinfectant wipes would significantly reduce levels of surface contamination. Method Setting The study was conducted in the intensive care unit (ICU) of a 272-bed community hospital that is part of a larger academic medical system in August 2021, during the delta variant surge of the COVID-19 pandemic. This 24-bed ICU housed patients with and without COVID-19 and included several airborne isolation rooms with negative-pressure ventilation. The hospital had not previously utilized CleanSpace HALO or reusable elastomeric respirators prior to the COVID-19 pandemic. With the launch of this new respirator, CleanSpace trainers provided live virtual education to small groups of designated respirator “super users.” Education included background about how the HALO respirator worked, its level of protection provided, and how to use, clean, and disinfect the respirator. Each super user practiced donning and doffing and adjusting the respirator for the best fit in front of a web camera, receiving feedback from the CleanSpace trainers. Then, super users fit-tested and trained HALO end users in these same tasks. End users received instructions on wiping the respirator after each doffing and instructions on where to drop off and collect FMs. At the conclusion of training, new users demonstrated respirator donning, doffing, and decontaminating according to a proficiency checklist. This hospital had instituted a program for HCWs to obtain HALO respirator FMs that had undergone centralized decontamination prior to the start of each shift. This decontamination was performed by dedicated staff and included cleaning the FMs by submersion in neutral detergent and water, followed by submersion in a chemical disinfectant and rinse, as per a procedure previously described by Bessesen et al. (2015). During the work shift, after exiting each patient room, HCWs disinfected their reusable PPE, including HALO FMs and power units and FSs, with EPA-registered hospital disinfecting wipes containing 55.5% isopropyl alcohol (IPA), 0.25% quaternary ammonium compound (QAC), and 0.25% benzyl ammonium chloride compounds. This product claimed germicidal activity after 2 min of contact time against 32 microbial pathogens, including SARS-CoV-2, Staphylococcus aureus and Methicillin-resistant S. aureus (MRSA) (EPA, 2020; “Super Sani-Cloth® Germicidal Disposable Wipe—PDI Healthcare,” n.d.). HCWs were expected to don their respirators and FSs and perform hand hygiene before entering patient rooms. They were also instructed to wear disposable procedure masks over the exhalation valve of the HALO FM as a form of source control from potential asymptomatic shedding of SARS-CoV-2 in exhaled breath (Chang et al., 2020). Upon exiting patient rooms, HCWs performed hand hygiene, removed their FSs and respirators, then donned gloves and disinfected their FSs and respirators (both FMs and power units) with wipes. FSs and HALO FMs remained with the HCW during the work shift. HALO power units were returned to charging stations in the nursing unit after use. Respirator HCWs used CleanSpace HALO, a PAPR with HEPA filtration. A silicone mask sits over the nose and mouth and is secured by a harness made of silicone and polycarbonate. A power unit composed of polycarbonate and containing an encased filter sits on the back of the neck. An adjustable neck support made of Acrylonitrile Butadiene Styrene plastic fits into the power unit. The entire respirator can be repeatedly decontaminated in accordance with manufacturer instructions and reused (CleanSpace Technology Pty Ltd., 2018). Sample Collection and Processing Samples were obtained from respirator FMs and FSs by swabbing surfaces using a standardized protocol with a BDTM Universal Viral Transport System and sterile swab applicator. This system is designed to transport specimens at room temperature. FMs were sampled by swabbing the exterior twice horizontally across the entire FM and twice vertically along the front of the FM. FSs were sampled by swabbing the exterior twice horizontally and twice vertically. Samples were collected at the start of shift (including from FMs that were just obtained from the decontamination station), immediately after use in patient rooms but before doffing, and after doffing and cleaning with disinfecting wipes. Patient charts were reviewed for the presence of documented infections, time from diagnosis of infection, use of airborne isolation precautions, and recent aerosol-generating procedures (AGP) within 6 hr. Samples were transported to the laboratory in insulated containers, processed within 24 hr, and stored at −80°C until analysis. Laboratory Analysis Processed samples were analyzed for bacterial and viral pathogens, including SARS-CoV-2, with quantitative reverse transcription polymerase chain reaction. Nucleic acids were first extracted with the MagMax Pathogen RNA/DNA Kit (Applied Biosystems) on KingFisher Duo Prime (ThermoFisher Scientific), following manufacturer protocols specific to sample type, the same day that PCR was to be run. Samples were assayed for SARS-CoV-2 using the Applied Biosystems™ TaqPath COVID-19 Combo Kit. Samples were also assayed using the TaqMan Array Card (TAC, ThermoFisher Scientific) and TaqMan Fast Virus One Step Master Mix (Applied Biosystems). The TAC is a low-density microfluidic card that can detect 21 individual respiratory pathogens including influenza A, influenza B, rhinovirus, adenovirus, Streptococcus pneumoniae, S. aureus, and Hemophilus influenzae. The level of detection (LoD) for the TaqPathTM is 250 copies per sample and TAC LoD ranges between 6,250 and 625,000 copies per sample depending on the target organism. Sample results were evaluated in relation to factors that potentially could contribute to the presence of surface contamination. The study was approved by the University of Maryland-Baltimore Institutional Review Board (IRB). The IRB granted a waiver of consent for the patient chart reviews and a waiver of written informed consent from the participating HCWs, who provided verbal consent after reviewing an approved information sheet. Results A total of 89 samples were obtained, 51 from FMs (57.3%) and 38 from FSs (42.7%). Nine samples were from PPE that had not yet been used that day for patient care, including 7 FMs (one of which had not undergone central decontamination) and 2 FSs. None of the 89 samples tested positive for SARS-CoV-2. Four (4.5%) samples tested positive, all of which were positive for S. aureus. Both positive FM samples came from the same FM—the first obtained at the start of shift prior to first use and the second after use but prior to cleaning with a disinfectant wipe. None of the samples that tested positive for S. aureus were used in the care of patients that had an S. aureus infection. Table 1 shows characteristics of various factors thought to potentially impact PPE surface contamination, including patient characteristics (infection with SARS-CoV-2 or other organism, intubation) and use in a negative-pressure patient room. Table 1. Characteristics of Samples Obtained From Personal Protective Equipment Samples HALO face masks Face shields Total samples 51 38 Positive for S. aureus 2/51 2/38 Positive for SARS CoV-2 0/51 0/38 Sample characteristics # positive/ total # samples From PPE obtained from centralized decontamination, prior to patient care use 1/6 N/a From PPE used in patient care, immediately after room exit 1/22 0/18 From PPE used in patient care, after wipe disinfection 0/22 2/18 From PPE used in care of SARS-CoV-2 positive patients 1/32 2/26 From PPE used in care of patients with non-SARS-CoV-2 infection 0/24 0/16 From PPE used in care of intubated patients 1/28 2/24 From PPE used in care of patients who underwent recent AGP (23 of these 27 samples from PPE worn in care of patients with SARS-CoV-2 infection) 1/15 1/12 From PPE used in care of patients who were in a negative pressure room 1/16 1/12 Note. PPE = personal protective equipment; AGP = aerosol generating procedure. Among samples collected from PPE used during care of patients infected with SARS-CoV-2, these patients had become symptomatic an average of 12.3 days prior and had positive PCR testing 9.1 days prior to sampling. Among the 44 samples obtained from FMs used in patient care prior to sampling, HCWs had worn either a disposable procedure mask or FS over their FM in 36 cases (81.8%) (not shown). Table 2 shows the potential impacts of the duration of PPE use and time since wipe disinfection on surface contamination detected by wipe samples. No consistent patterns were observed in either length of time of PPE use or in time since wipe disinfection associated with positive or negative samples. Table 2. Timing of PPE Use and Disinfection Among Positive and Negative Samples Samples Positive samples Negative samples HALO face masks 2/51 49/51  Mean time worn prior to sampling (minutes) 20.0 11.1  Mean time worn this shift (minutes) 20.0 36.8  Mean time since last wipe disinfection (minutes) N/aa 24.3b Face shields 2/38 36/38  Mean time worn prior to sampling (minutes) 10.5 13.0  Mean time worn this shift (minutes) 77.5 90.6  Mean time since last wipe disinfection (minutes) 3.0 32.6b a Both HALO FM samples that tested positive had not yet been disinfected with a wipe. b Not including samples that were obtained from PPE prior to first use of the day (and thus last disinfection time unknown). Discussion In this study, we found that surface contamination on FSs and CleanSpace HALO FMs was uncommon and when present was due to S. aureus, an organism commonly found on the skin (Taylor & Unakal, 2022) We measured microbial surface contamination by SARS-CoV-2 and other pathogens on in routine clinical use during the COVID-19 pandemic. We also assessed for differences in microbial presence pre- and post-disinfection with common hospital wipes. These results were found in a setting where HCWs decontaminated their respirators and FSs with disinfectant wipes following each patient room exit and submitted their FMs for central cleaning and disinfection at the end of each shift. Our results suggest that this strategy is associated with low risk for HCW contact with SARS-CoV-2 on CleanSpace HALO FM surfaces. We found S. aureus on two FM samples. Both positive samples came from the same FM, the first obtained immediately prior to and the other immediately following patient care but before disinfection wiping. It is unclear if contamination occurred from contact with the HCW’s skin, a surface where the FM may have rested before donning or contact with skin or a surface following centralized decontamination. The sample obtained immediately post-wipe from this same FM showed no contamination, as expected. Both FS samples testing positive for S. aureus, however, were obtained immediately following post-use disinfection wiping. Samples from both FSs that had been taken immediately post-use, but before disinfection, showed no contamination. The FMs from these HCW did not test positive for S. aureus. This suggests that the HCW wiping the FS contaminated the FS with their own skin, rested the FS on a contaminated surface during drying, or that the disinfection wipe did not completely remove surface contaminants. Studies of surface contamination by SARS-CoV-2 have shown variable patterns. Our finding of no surface contamination by SARS-CoV-2 is similar to findings from some authors. These studies have found low rates of contamination, ranging from 0% to 8% of specimens, where positive specimens were found on HCW gowns, stethoscopes, phones, a shoe, and an endotracheal intubation tube (Nakamura et al., 2020; Ong, Tan, Chia et al., 2020; Ong, Tan, Sutjipto et al., 2020; Peyrony et al., 2020). Other studies, however, have reported frequent SARS-CoV-2 surface contamination, ranging from 15% of HCW PPE to 78% of HCW cell phones and 57% of patient rooms with any positive surface samples (Chia et al., 2020; Jung et al., 2020; Pasquarella et al., 2020; Santarpia et al., 2020). Given the variability in the prevalence of surface contamination, multiple factors likely contribute, including the amount and duration of viral shedding from the patient, porosity and antimicrobial properties of surfaces, and the presence of engineering controls in the room. Our findings of limited S. aureus contamination are like studies showing bacterial surface contamination of items used repeatedly in healthcare. Many studies have cited high frequencies of HCW cell phone bacterial contamination, commonly by S. aureus (Kalra et al., 2021; Malhotra et al., 2020; Panigrahi et al., 2020). Furthermore, some data suggest that even disinfected stethoscopes maintain significant rates of bacterial contamination (Kalra et al., 2021). Thus, our findings are consistent with other studies showing that S. aureus surface contamination is not uncommon. Our study has several limitations. We did not assess viral viability with culture; however, our detection of no viral ribonucleic acid by PCR, a more sensitive indicator, suggests that this does not affect the interpretation of our results. Second, we sampled surfaces following short periods of use. While this differs from the extended use periods that occurred commonly at the beginning of the pandemic, short duration use likely reflects common patterns for healthcare respirator use (Kobayashi et al., 2020). Third, we did not measure air samples, which would have aided our understanding of risk of room contamination from SARS-CoV-2. The surface samples in this study were obtained from PPE worn in the care of patients who were several days into their illnesses, intubated, and mainly in airborne isolation rooms with negative pressure room ventilation. Studies have suggested that surface contamination from COVID-19 patients is more likely to occur early in the disease course, before day 7 (Chia et al., 2020; Santarpia et al., 2020). Thus, while our results may not reflect the highest risk periods for HCW exposure, it likely reflects the exposure scenarios during care of prolonged acute COVID-19 patient illness. In addition, while many HCWs wore procedure masks over the exhalation valve of the respirators, which likely limited FM surface contamination, the lack of SARS-CoV-2 on FSs, which also cover the FMs, suggests that this does not significantly alter the interpretation of our results. Although the testing positivity was low for both FMs and FSs, these findings highlight several areas for focus with healthcare reuse of PPE. First, HCWs must completely wipe the surfaces of their PPE. Second, doffing areas should be clean and free of microbial contaminants and support a standardized post-doffing practice. Third, disinfectants should have adequate properties against common hospital microbial pathogens. Although the wipes used in this setting were IPA and QAC-based disinfectants with claims against S. aureus, some literature suggests that hydrogen peroxide-based disinfection may be more effective against S. aureus, including MRSA, compared with routine cleaning methods in hospital settings (Dancer, 2014; French et al., 2004). Finally, given that FSs may be worn at times when respirators are not required, FSs may face more hand-to-surface and surface-to-surface contact. These devices require particular attention to decontamination. Our findings contribute to understanding of healthcare reusable PPE use in several ways. First, centralized respirator decontamination adds a layer of standardized cleaning and disinfection that likely significantly decreases the opportunities for sustained microbial contamination. Like other reusable equipment such as blood pressure cuffs, reuse of PPE should include attention to general housekeeping measures to limit contamination from commonly encountered microbes, especially those found on the skin. The use of appropriate disinfectant strategies against these microbes must be a routine component of policies and procedures addressing reusable PPE. In summary, we found no surface contamination with SARS-CoV-2 and infrequent contamination with S. aureus on reusable FSs and CleanSpace HALO respirator FMs disinfected after each patient room exit during the COVID-19 pandemic. Reuse of PPE allows hospitals to maintain sustainable resources for HCW safety. Routine, evidence-based disinfection strategies can provide assurance that HCWs have PPE that effectively provides protection and does not pose risks for fomite transmission of microbial contaminants. Implications for Occupational Health Practice HCWs have increasingly relied on reusable PPE since the onset of the COVID-19 pandemic. This equipment, while necessary to protect workers, could potentially act as a fomite for transmission of SARS-CoV-2 or other pathogens. The efficacy of decontamination and cleaning practices outside of experimental studies was not known. This study demonstrates that post-shift centralized decontamination and routine post-doffing use of disinfecting wipes are associated with a low risk of contamination of reusable PPE with SARS-CoV-2 and other respiratory pathogens. These results are reassuring for HCWs involved in the care of patients with common respiratory pathogens. Applying Research to Occupational Health Practice This study finds a low rate of contamination of reusable personal protective equipment (PPE) with common respiratory pathogens, including SARS-CoV-2, at a site using centralized daily PPE decontamination and post-doffing use of hospital disinfecting wipes to decontaminate respirator face masks and face shields. Hospital respiratory protection and infection prevention leaders should ensure appropriate processes are in place for the decontamination of PPE. Healthcare workers must be diligent in practicing hand hygiene and regularly disinfect PPE to minimize the risk of surface contamination. The authors would like to thank Jason Heavner, MD, Jordan Assadi, DO, Sandra Thomas, RRT, and Carol Ann Sperry, RN, MS for their assistance in completing the study. Authors’ Note: Data collection instruments may be obtained by contacting the authors. The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: A family member of SH works as an instructional trainer for CleanSpace Technology and was not involved in any of the current research endeavors. Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by a grant to the University of Maryland School of Medicine, contract CCT 3809-19 (Hines, PI) by CleanSpace Technology Pty Ltd. Human Subjects Review: The study was approved by the University of Maryland-Baltimore Institutional Review Board (IRB) (HP-00096953). The IRB granted a waiver of consent for the patient chart reviews and a waiver of written informed consent from the participating HCWs, who provided verbal consent after reviewing an approved information sheet. ORCID iDs: Anand Shah https://orcid.org/0000-0001-5908-3240 Stella E. Hines https://orcid.org/0000-0002-8350-9448 ==== Refs References Bessesen M. T. Adams J. C. Radonovich L. Anderson J. (2015). Disinfection of reusable elastomeric respirators by health care workers: A feasibility study and development of standard operating procedures. American Journal of Infection Control, 43 (6 ), 629–634. 10.1016/j.ajic.2015.02.009 25816692 Centers for Disease Prevention and Control. (2021). Science brief: SARS-CoV-2 and surface (fomite) transmission for indoor community environments. https://www.cdc.gov/coronavirus/2019-ncov/more/science-and-research/surface-transmission.html Chalikonda S. Waltenbaugh H. Angelilli S. Dumont T. Kvasager C. Sauber T. Nino S. Singh A. Diaz-Garcia R. (2020). Implementation of an elastomeric mask program as a strategy to eliminate disposable N95 mask use and resterilization: Results from a large academic medical center. Journal of the American College of Surgeons, 231 (3 ), 333–338. 10.1016/j.jamcollsurg.2020.05.022 32534935 Chang J. C. Johnson J. S. Olmsted R. N. (2020). Demystifying theoretical concerns involving respirators with exhalation valves during COVID-19 pandemic. American Journal of Infection Control, 48 (12 ), 1564–1565. 10.1016/j.ajic.2020.08.031 32860845 Chia P. Y. Coleman K. K. Tan Y. K. Ong S. W. X. Gum M. Lau S. K. Lim X. F. Lim A. S. Sutjipto S. Lee P. H. Son T. T. Young B. E. Milton D. K. Gray G. C. Schuster S. Barkham T. De P. P Vasoo S. Chan M. , . . . Singapore Novel Coronavirus Outbreak Research Team. (2020). Detection of air and surface contamination by SARS-CoV-2 in hospital rooms of infected patients. Nature Communications, 11 (1 ), Article 2800. 10.1038/s41467-020-16670-2 CleanSpace Technology Pty Ltd., C. T. P. (2018). USER INSTRUCTIONS CleanSpace HALO CS3000. Dancer S. J. (2014). Controlling hospital-acquired infection: Focus on the role of the environment and new technologies for decontamination. Clinical Microbiology Reviews, 27 (4 ), 665–690. 10.1128/CMR.00020-14 25278571 French G. L. Otter J. A. Shannon K. P. Adams N. M. Watling D. Parks M. J. (2004). Tackling contamination of the hospital environment by methicillin-resistant Staphylococcus aureus (MRSA): A comparison between conventional terminal cleaning and hydrogen peroxide vapour decontamination. Journal of Hospital Infection, 57 (1 ), 31–37. 10.1016/j.jhin.2004.03.006 15142713 Hamby C. (2020, May 27). They evoke Darth Vader, but these masks may save your doctor’s life. The New York Times. https://www.nytimes.com/2020/05/27/us/coronavirus-masks-elastomeric-respirators.html Hines S. Tai S. German J. Chen H. Madden M. Lulaj E. Tong C. Apte M. Herman S. Birrell A. Milton D. McDiarmid M. (2020). Halo respirator assessment of reprocessing and cleaning (ARC). Journal of the International Society for Respiratory Protection, 37 , 1–13. Hines S. Thurman P. Mcdiarmid M. (2021). Implementation guide to support use of elastomeric half mask respirators in healthcare. University of Maryland Baltimore. http://hdl.handle.net/10713/14748 Jung J. Kim J. Y. Bae S. Cha H. H. Kim E. O. Kim M. J. Kim S. H. (2020). Contamination of personal protective equipment by SARS-CoV-2 during routine care of patients with mild COVID-19. Journal of Infection, 81 (2 ), e165–e167. 10.1016/j.jinf.2020.06.021 Kalra S. Amin A. Albert N. Cadwell C. Edmonson C. Gaynes R. Hand M. Marinella M. Morely C. Sieck S. Vasudevan R. S. (2021). Stethoscope hygiene: A call to action. Recommendations to update the CDC guidelines. Infection Control & Hospital Epidemiology, 42 (6 ), 740–742. 10.1017/ice.2021.115 34009112 Kasloff S. B. Leung A. Strong J. E. Funk D. Cutts T. (2021). Stability of SARS-CoV-2 on critical personal protective equipment. Scientific Reports, 11 (1 ), Article 984. 10.1038/s41598-020-80098-3 Kobayashi L. M. Marins B. R. Costa P. Perazzo H. Castro R. (2020). Extended use or reuse of N95 respirators during COVID-19 pandemic: An overview of national regulatory authority recommendations. Infection Control & Hospital Epidemiology, 41 (11 ), 1364–1366. 10.1017/ice.2020.173 32319884 Koh F. H. Tan M. G. Chew M. H. (2020). The fight against COVID-19: Disinfection protocol and turning over of CleanSpace((R)) HALO in a Singapore Hospital. Updates in Surgery, 72 (2 ), 311–313. 10.1007/s13304-020-00809-3 32462609 Lawrence C. Harnish D. A. Sandoval-Powers M. Mills D. Bergman M. Heimbuch B. K. (2017). Assessment of half-mask elastomeric respirator and powered air-purifying respirator reprocessing for an influenza pandemic. American Journal of Infection Control, 45 (12 ), 1324–1330. 10.1016/j.ajic.2017.06.034 28844381 Malhotra S. Wlodarczyk J. Kuo C. Ngo C. Glucoft M. Sumulong I. Smit M. A. Bender J. M. (2020). Shining a light on the pathogenicity of health care providers’ mobile phones: Use of a novel ultraviolet-C wave disinfection device. American Journal of Infection Control, 48 (11 ), 1370–1374. 10.1016/j.ajic.2020.05.040 32512083 Marques M. Domingo J. L. (2021). Contamination of inert surfaces by SARS-CoV-2: Persistence, stability and infectivity. A review. Environmental Research, 193 , Article 110559. 10.1016/j.envres.2020.110559 Meyerowitz E. A. Richterman A. Gandhi R. T. Sax P. E. (2021). Transmission of SARS-CoV-2: A review of viral, host, and environmental factors. Annals of Internal Medicine, 174 (1 ), 69–79. 10.7326/M20-5008 32941052 Nakamura K. Morioka S. Kutsuna S. Iida S. Suzuki T. Kinoshita N. Suzuki T. Sugiki Y. Okuhama A. Kanda K. Wakimoto Y. Ujiie M. Yamamoto K. Ishikane M. Moriyama Y. Ota M. Nakamoto T. Ide S. Nomoto H. . . .Ohmagari N. (2020). Environmental surface and air contamination in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patient rooms by disease severity. Infection Prevention in Practice, 2 (4 ), Article 100098. 10.1016/j.infpip.2020.100098 Ong S. W. X. Tan Y. K. Chia P. Y. Lee T. H. Ng O. T. Wong M. S. Y. Marimuthu K. (2020). Air, surface environmental, and personal protective equipment contamination by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from a symptomatic patient. JAMA, 323 (16 ), 1610–1612. 10.1001/jama.2020.3227 32129805 Ong S. W. X. Tan Y. K. Sutjipto S. Chia P. Y. Young B. E. Gum M Lau S. K. Chan M. Vasoo S. Mendis S. Toh B. K. Leong J. Barkham T. Ang B. S. P. Tan B. H. Leo Y. S. Marimuthu K. Wong M. S. Y. Ng O. T. (2020). Absence of contamination of personal protective equipment (PPE) by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infection Control & Hospital Epidemiology, 41 (5 ), 614–616. 10.1017/ice.2020.91 32213231 Panigrahi S. K. Pathak V. K. Kumar M. M. Raj U. Priya P. K. (2020). Covid-19 and mobile phone hygiene in healthcare settings. BMJ Global Health, 5 (4 ), Article e002505. 10.1136/bmjgh-2020-002505 Pasquarella C. Colucci M. E. Bizzarro A. Veronesi L. Affanni P. Meschi T. Brianti E. Vitali P. Albertini R. (2020). Detection of SARS-CoV-2 on hospital surfaces. Acta Biomedica, 91 (9-S ), 76–78. 10.23750/abm.v91i9-S.10137 32701919 Peyrony O. Ellouze S. Fontaine J. P. Thegat-Le Cam M. Salmona M. Feghoul L. Mahjoub N. Mercier-Delarue S. Gabassi A. Delaugerre C. Le Goff J. , & Saint-Louis CORE Group. (2020). Surfaces and equipment contamination by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the emergency department at a university hospital. International Journal of Hygiene and Environmental Health, 230 , Article 113600. 10.1016/j.ijheh.2020.113600 Santarpia J. L. Rivera D. N. Herrera V. L. Morwitzer M. J. Creager H. M. Santarpia G. W. Crown K. K. Brett-Major D. M. Schnaubelt E. R. Broadhurst M. J. Lawler J. V. Reid S. P. Lowe J. J. (2020). Aerosol and surface contamination of SARS-CoV-2 observed in quarantine and isolation care. Scientific Reports, 10 (1 ), Article 12732. 10.1038/s41598-020-69286-3 Super Sani—Cloth® Germicidal Disposable Wipe—PDI Healthcare. (n.d.). https://pdihc.com/products/environment-of-care/super-sani-cloth-germicidal-disposable-wipe/ Taylor T. A. Unakal C. G. (2022). Staphylococcus aureus. StatPearls [Internet]. https://www.ncbi.nlm.nih.gov/books/NBK441868/ U.S. Environmental Protection Agency. (2020). List N tool: COVID-19 disinfectants. https://cfpub.epa.gov/wizards/disinfectants/
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==== Front Public Health Rep Public Health Rep PHR spphr Public Health Reports 0033-3549 1468-2877 SAGE Publications Sage CA: Los Angeles, CA 36482712 10.1177/00333549221138294 10.1177_00333549221138294 Research COVID-19 Outbreaks Linked to Workplaces, 23 US Jurisdictions, August–October 2021 https://orcid.org/0000-0002-3000-8818 Luckhaupt Sara E. MD 1 Horter Libby MPH 12 Groenewold Matthew R. PhD 1 de Perio Marie A. MD 1 https://orcid.org/0000-0003-1320-2739 Robbins Cheryl L. PhD 1 Sweeney Marie Haring PhD 1 https://orcid.org/0000-0001-6878-9704 Thomas Isabel MPH 13 https://orcid.org/0000-0002-9578-3751 Valencia Diana MS 1 Ingram Amanda MPH 4 Heinzerling Amy MD 5 Nguyen Alyssa BS 5 Townsend Emily B. MPH 6 Weber Rachel C. MPH 6 Reichbind Diana MPH 7 Dishman Hope MPH 8 Kerins Janna L. VMD 9 Lendacki Frances R. MPH 9 Austin Connie PhD 10 Dixon Liana MPH 11 Spillman Brooke MPH 11 Simonson Sean MPH 12 Tonzel Julius MPH 12 Krueger Anna MS 13 Duwell Monique MD 14 Bachaus Brian MS 14 Rust Britney MPH 15 Barrett Colleen MPH 16 Morrison Brooke MPH 17 https://orcid.org/0000-0002-5323-5079 Owers Bonner Katharine A. PhD 18 Karlsson Nicole D. ScD 18 https://orcid.org/0000-0002-8530-0066 Angelon-Gaetz Kim PhD 19 McClure Elizabeth S. PhD 19 Kline Kelly E. MPH 20 Dangar Dhara MPH 20 Reed Chasey EdD 21 Karpowicz Jacqueline MPH 21 Anderson Shoana M. MPH 22 Cantor Sophia MPH 23 Chaudhary Ifrah MPH 23 Ellis Esther M. PhD 24 Taylor Marissa L. MPH 25 Sedon Allison MPH 26 Kocharian Anna MS 27 Morris Collin BS 27 Samson Marsha E. PhD 28 Mangla Anil T. PhD 28 1 COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA 2 Goldbelt C6, LLC, Chesapeake, VA, USA 3 ORISE Fellowship, Oak Ridge Associated Universities, Oak Ridge, TN, USA 4 Alabama Department of Public Health, Montgomery, AL, USA 5 California Department of Public Health, Sacramento, CA, USA 6 Colorado Department of Public Health and Environment, Denver, CO, USA 7 Connecticut Department of Public Health, Hartford, CT, USA 8 Georgia Department of Public Health, Atlanta, GA, USA 9 Chicago Department of Public Health, Chicago, IL, USA 10 Illinois Department of Public Health, Springfield, IL, USA 11 Kentucky Department for Public Health, Frankfort, KY, USA 12 Louisiana Department of Health, Baton Rouge, LA, USA 13 Maine Center for Disease Control and Prevention, Augusta, ME, USA 14 Maryland Department of Health, Baltimore, MD, USA 15 Mississippi Department of Health, Jackson, MS, USA 16 Carson City Health and Human Services, Carson City, NV, USA 17 Churchill County Department of Health, Fallon, NV, USA 18 New Hampshire Division of Public Health Services, Department of Health and Human Services, Concord, NH, USA 19 North Carolina Department of Health and Human Services, Raleigh, NC, USA 20 Pennsylvania Department of Health, Harrisburg, PA, USA 21 Rhode Island Department of Health, Providence, RI, USA 22 Tennessee Department of Health, Nashville, TN, USA 23 Texas Department of State Health Services, Austin, TX, USA 24 US Virgin Islands Department of Health, Christiansted, VI, USA 25 CDC Foundation, US Virgin Islands, Christiansted, VI, USA 26 Virginia Department of Health, Richmond, VA, USA 27 Wisconsin Department of Health, Madison, WI, USA 28 District of Columbia Department of Health, Washington, DC, USA Sara E. Luckhaupt, MD, Centers for Disease Control and Prevention, COVID-19 Response Team, 1090 Tusculum Ave, MS R-12, Cincinnati, OH 45226, USA. Email: [email protected] 8 12 2022 8 12 2022 00333549221138294© 2022, Association of Schools and Programs of Public Health 2022 US Surgeon General’s Office This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. Objectives: Early in the COVID-19 pandemic, several outbreaks were linked with facilities employing essential workers, such as long-term care facilities and meat and poultry processing facilities. However, timely national data on which workplace settings were experiencing COVID-19 outbreaks were unavailable through routine surveillance systems. We estimated the number of US workplace outbreaks of COVID-19 and identified the types of workplace settings in which they occurred during August–October 2021. Methods: The Centers for Disease Control and Prevention collected data from health departments on workplace COVID-19 outbreaks from August through October 2021: the number of workplace outbreaks, by workplace setting, and the total number of cases among workers linked to these outbreaks. Health departments also reported the number of workplaces they assisted for outbreak response, COVID-19 testing, vaccine distribution, or consultation on mitigation strategies. Results: Twenty-three health departments reported a total of 12 660 workplace COVID-19 outbreaks. Among the 12 470 workplace types that were documented, 35.9% (n = 4474) of outbreaks occurred in health care settings, 33.4% (n = 4170) in educational settings, and 30.7% (n = 3826) in other work settings, including non–food manufacturing, correctional facilities, social services, retail trade, and food and beverage stores. Eleven health departments that reported 3859 workplace outbreaks provided information about workplace assistance: 3090 (80.1%) instances of assistance involved consultation on COVID-19 mitigation strategies, 1912 (49.5%) involved outbreak response, 436 (11.3%) involved COVID-19 testing, and 185 (4.8%) involved COVID-19 vaccine distribution. Conclusions: These findings underscore the continued impact of COVID-19 among workers, the potential for work-related transmission, and the need to apply layered prevention strategies recommended by public health officials. COVID-19 workplace disease outbreaks edited-statecorrected-proof typesetterts1 ==== Body pmcWorkplace transmission of SARS-CoV-2 has been recognized since the start of the COVID-19 pandemic, and several outbreaks have been linked with workplaces such as long-term care facilities,1 meat and poultry processing plants,2 and correctional facilities.3 Recommendations for operation of businesses and other facilities and stay-at-home measures to mitigate the spread of COVID-19 have evolved during the pandemic. COVID-19 vaccines became available in December 2020 in phases, with health care personnel and long-term care residents prioritized first4; availability and implementation of vaccines varied across the country. With the emergence of the Delta variant in summer 2021,5 workplaces continued to be important settings for mitigation efforts to reduce the risk of transmission. To help understand how much workplace transmission may have been occurring during August through October 2021 and in what settings, the Centers for Disease Control and Prevention (CDC) invited the health departments from all 50 states, 8 US territories and freely associated states, and the District of Columbia to report aggregate surveillance data for COVID-19 outbreaks occurring in public or private work settings from August 1 through October 31, 2021. Some states passed the request on to health departments representing individual cities or counties. Methods CDC requested information reported to the health department by workplace establishments on the number of workplace COVID-19 outbreaks, by workplace setting, and the total number of cases among workers linked to these outbreaks. We categorized workplaces according to categories based on the 2017 North American Industry Classification System.6 For this study, CDC asked health departments to apply the case definition of a workplace outbreak provided by the Council of State and Territorial Epidemiologists (CSTE), which is based on ≥2 COVID-19 cases among workers,7 to all workplaces. CSTE defines an outbreak in a nonresidential, non–health care workplace setting as the following: “Two or more laboratory-confirmed COVID-19 cases among workers at a facility with onset of illness within a 14-day period, who are epidemiologically linked, do not share a household, and are not listed as a close contact of each other outside of the workplace during standard case investigation or contact tracing.”7 CDC asked health departments to include only cases among workers associated with each outbreak. Health departments followed this guidance to the extent that they were able, given that many of them recorded workplace outbreaks based on different local passive reporting requirements (eg, California defined outbreaks in non–health care settings as ≥3 probable or confirmed cases8 rather than ≥2). CDC also asked health departments to report the total numbers of confirmed working-age cases9 (aged 18-64 years, including outbreak related and non–outbreak related) during the study period and the number of workplaces that they assisted for outbreak response, COVID-19 testing, vaccine distribution, or consultation on mitigation strategies. CDC reviewed this activity and conducted it consistent with applicable federal law and CDC policy (eg, 45 CFR part 46.102[I][2], 21 CFR part 56; 42 USC §241[d]; 5 USC §552a; 44 USC §3501 et seq). We estimated counts of workplace establishments and quarterly employment for the various workplace types by aggregating industry-specific second quarter 2021 Quarterly Census of Employment and Wages (QCEW) data for each jurisdiction covered by participating health departments into categories approximating those used by the health departments for reporting. The QCEW is a quarterly count of the number of business establishments, monthly employment, and quarterly wages for workers covered by state unemployment insurance laws and federal workers covered by the Unemployment Compensation for Federal Employees program compiled by the Bureau of Labor Statistics.10 Establishment counts are derived from administrative data from state and federal unemployment insurance programs. Employment and wage data are reported by employers. We calculated quarterly employment as the average monthly employment for the 3 months of the quarter. We conducted all analyses in SAS version 9.4 (SAS Institute Inc). Results Twenty-three health departments reported a total of 12 660 workplace COVID-19 outbreaks during August–October 2021 (Table 1, Figure 1). These outbreaks included at least 52 635 cases among workers, an average of 4.2 confirmed cases per outbreak. We found an average of 1.85 workplace outbreak–associated cases per 100 working-age cases in the participating jurisdictions. In 16 of 23 jurisdictions, the highest number of workplace outbreaks was reported in August. Table 1. Number of workplace COVID-19 outbreaks,a outbreak-associated cases, and total cases among working-age adults by jurisdiction, 23 US jurisdictions, August–October 2021b No. of workplace outbreaks August–October, no. Jurisdiction August September October August–October Outbreak-associated cases among workers Average cases per outbreak Total cases among working-age adultsc Workplace outbreak-associated cases per 100 working-age casesd Alabama 205 100 19 324 3820 11.8 154 977 2.5 Californiae 1703 827 677 3207 7812f,g,h 2.4 523 459 1.5 Coloradoi 118 118 54 290 1324 4.6 102 243 1.3 Connecticutj 75 49 42 166 563 3.4 27 194 2.1 District of Columbia 36 17 13 66 296 4.5 9006 3.3 Georgia 460 207 137 804 3117f,g 3.9 218 042 1.4 Illinois, excluding Chicago 180 76 41 297 1317 4.4 173 079 0.8 Chicagok 39 24 15 78 316 4.1 23 409 1.4 Kentuckyl 70 93 68 231 1848m 8.0 110 630 1.7 Louisianan 795 199 90 1084 5002 4.6 96 301 5.2 Maineo 41 79 26 146 894 6.1 14 340 6.2 Maryland 250 210 109 569 2748 4.8 58 934 4.7 Mississippi 167 67 21 255 1328 5.2 95 637 1.4 Nevadap 17 15 5 37 120 3.2 4986 2.4 New Hampshirei,o 35 47 23 105 468 4.5 10 458 4.5 North Carolina 367 248 79 694 4740 6.8 230 226 2.1 Pennsylvaniaq 119 89 117 325 1119f 3.4 162 352 0.7 Rhode Island 51 62 34 147 447 3.0 17 229 2.6 Tennessee 325 133 49 507 3103 6.1 169 841 1.8 Texas 60 24 2 86 358 4.2 387 545 0.1 US Virgin Islands 7 5 1 13 78 6.0 1751 4.5 Virginia 378 417 427 1222 5985g 4.9 143 394 4.2 Wisconsin 617 815 575 2007 5832g 2.9 108 699 5.4 Total 6115 3921 2624 12 660 52 635 4.2 2 843 732 1.9 a The Centers for Disease Control and Prevention invited the health departments from all 50 states, 8 US territories and freely associated states, and the District of Columbia to report aggregate surveillance data for COVID-19 outbreaks occurring in public or private work settings from August 1 through October 31, 2021. Some states passed the request on to health departments representing individual cities or counties. b Except where otherwise noted, “workplace outbreak” was defined for this study according to the Council of State and Territorial Epidemiologists’ surveillance definition for an outbreak in a nonresidential, non–health care workplace setting: “Two or more laboratory-confirmed COVID-19 cases among workers at a facility with onset of illness within a 14-day period, who are epidemiologically linked, do not share a household, and are not listed as a close contact of each other outside of the workplace during standard case investigation or contact tracing.”7 c Total cases among adults aged 18-64 years, including both outbreak-related and non–outbreak-related cases. d Workplace outbreak-associated cases per 100 working-age cases was calculated according to the following formula: number of outbreak-associated cases among workers (August–October 2021) divided by the total number of cases among working-age adults × 100. e California defines outbreaks in non–health care settings as ≥3 cases, rather than ≥2 cases. f Case counts include probable cases. g Case counts may include nonworker adults associated with the outbreaks. h Limited to people aged 18-64 years. Age only available for 67% of outbreak-associated cases reported by California; outbreak-associated cases without available age information were excluded from outbreak-associated case numbers. i Excluded outbreaks still active at the time of reporting. j Connecticut did not consistently track college/university or correctional facility outbreaks. k Chicago definition of school outbreak changed on October 4 (from 2 cases to 3). l Kentucky data exclude correctional facilities, hospitals, and skilled nursing facilities. m Kentucky definition of health care setting outbreaks and non–health care setting (except for education) outbreaks requires ≥5 cases. n Louisiana reporting in September was likely reduced because of Hurricane Ida. o Outbreak definition based on ≥3 confirmed cases (2 of which are staff). p Includes only Carson City, Churchill County, Douglas County, Lyon County, and Storey County. q Pennsylvania excluded Philadelphia County in all counts except for hospital outbreaks. Only daycares/preschools were included for educational settings. First response does not include any health care services (eg, emergency medical services). Figure 1. Workplace outbreaks reported to the Centers for Disease Control and Prevention by 23 US jurisdictions, August–October 2021. Data for Nevada were reported by these jurisdictions only: Churchill County, Carson City, Douglas County, Lyon County, and Storey County. Health departments documented workplace type for 12 470 (98.5%) outbreaks involving 49 938 (94.9%) workers; we grouped these workplace outbreaks into 3 broad settings: 4474 (35.9%) outbreaks involving 18 046 (36.1%) workers in health care settings, 4170 (33.4%) outbreaks involving 13 097 (26.2%) workers in educational settings, and 3826 (30.7%) outbreaks involving 18 795 (37.6%) workers in other work settings (Table 2). Of the >5 million workplace establishments in the 23 participating jurisdictions, 7.5% were categorized as health care, 2.6% as educational, and 89.9% as other non–health care settings; the corresponding proportions of all employed workers in these jurisdictions were 12.0%, 9.5%, and 78.5%. Most outbreaks in health care settings (81.7%; 3655 of 4474) occurred in nursing and residential care facilities, and most in educational settings (73.2%; 3051 of 4170) occurred in K-12 schools (kindergarten through 12th grade). Other settings included non–food manufacturing facilities (11.0%; 419 of 3826), correctional facilities (10.7%; n = 410), social services (6.7%; n = 258), retail trade (6.7%; n = 256), and food and beverage stores (5.9%; n = 226). Table 2. Workplace COVID-19 outbreaks,a by work setting category and specific work setting, 23 US jurisdictions, August–October 2021b No. (%) Work setting (approximate NAICS code)c No. of jurisdictions reporting Workplace outbreaks (n = 12 470)d Establishmentsef (n = 5 660 735) Outbreak-associated cases among workers (n = 49 938) Employed population (n = 71 758 633)e,f Any health care setting 23 4474 (35.9) 422 744 (7.5) 18 046 (36.1) 8 616 484 (12.0) Hospital (622) 17 404 (9.0) 7442 (1.8) 1625 (9.0) 2 741 842 (31.8) Nursing and residential health care facility (623) 20 3655 (81.7) 41 040 (9.7) 15 603 (86.5) 1 474 930 (17.1) Pharmacy (446110) 2 8 (0.2) 32 358 (7.7) 14 (0.1) 346 436 (4.0) Ambulatory health care (621) 14 175 (3.9) 341 904 (80.9) 795 (4.4) 4 053 276 (47.0) Health care setting–type not specified — 232 (5.2) — — — Any educational setting 23 4170 (33.4) 149 682 (2.6) 13 097 (26.2) 6 805 267 (9.5) Preschool or daycare (62441) 20 905 (21.7) 38 622 (25.8) 2264 (17.3) 412 461 (6.1) K-12 school (61111) 20 3051 (73.2) 43 562 (29.1) 9974 (76.2) 4 105 781 (60.3) Other schools and instructional settings (other 611) 13 168 (4.0) 67 498 (45.1) 2763 (21.1) 2 287 025 (33.6) Educational setting–type not specified — 46 (1.1) — — — Other setting 23 3826 (30.7) 5 088 309 (89.9) 18 795 (37.6) 56 336 882 (78.5) Correctional facility (92214) 19 410 (10.7) 2834 (0.1) 4420 (23.5) 248 867 (0.4) Non–food manufacturing facility (other 31-33) 16 419 (11.0) 169 403 (3.3) 2346 (12.5) 4 948 068 (8.8) Social service (624) 13 258 (6.7) 692 565 (13.6) 981 (5.2) 1 796 662 (3.2) Retail trade (44-45, excluding 446110 and 445) 10 256 (6.7) 417 278 (8.2) 1074 (5.7) 5 268 617 (9.4) Food and beverage store (445) 15 226 (5.9) 72 913 (1.4) 861 (4.6) 1 607 812 (2.9) Accommodation and food services (72) 7 192 (5.0) 380 006 (7.5) 592 (3.1) 6 244 896 (11.1) Other services (except public administration) (81 excluding 8122) 9 127 (3.3) 427 001 (8.4) 539 (2.9) 2 078 507 (3.7) Food manufacturing facility (311) 14 104 (2.7) 18 121 (0.4) 1098 (5.8) 729 479 (1.3) Construction (23) 7 140 (3.7) 413 839 (8.1) 349 (1.9) 3 897 096 (6.9) Professional, scientific, technical, management, administrative, and waste management services (54, 55, 56) 8 89 (2.3) 1 067 264 (21.0) 282 (1.5) 11 427 517 (20.3) Transportation and warehousing (48-49, excluding 485 and 491) 5 81 (2.1) 140 128 (2.8) 394 (2.1) 2 935 327 (5.2) Finance, insurance, real estate, rental, and leasing (52, 53) 7 83 (2.2) 495 138 (9.7) 211 (1.1) 4 120 430 (7.3) Arts, entertainment, and recreation (71) 7 73 (1.9) 88 658 (1.7) 245 (1.3) 1 109 333 (2.0) Public administration (except first responders and correctional facilities) (92, excluding 922) 13 112 (2.9) 54 365 (1.1) 669 (3.6) 2 905 067 (5.2) First response (92212, 92216, 92219) 11 58 (1.5) 6945 (0.1) 252 (1.3) 548 963 (1.0) Utilities (22) 7 58 (1.5) 14 080 (0.3) 198 (1.1) 275 998 (0.5) Agriculture, forestry, fishing, or hunting (11) 10 41 (1.1) 52 785 (1.0) 272 (1.4) 690 889 (1.2) Public transit (485) 9 41 (1.1) 10 364 (0.2) 203 (1.1) 217 677 (0.4) Wholesale trade (42) 4 32 (0.8) 313 101 (6.2) 148 (0.8) 2 978 484 (5.3) US Postal Service (491) 5 24 (0.6) 13 629 (0.3) 109 (0.6) 306 932 (0.5) Information (51) 4 17 (0.4) 112 813 (2.2) 37 (0.2) 1 554 359 (2.8) Death care (8122) 5 12 (0.3) 9167 (0.2) 57 (0.3) 69 235 (0.1) Mining, quarrying, and oil and gas extraction (21) 3 9 (0.2) 16 865 (0.3) 37 (0.2) 291 930 (0.5) Other or unknown 20 396 (10.4) 99 047 (2.0) 1870 (9.9) 84 738 (0.2) Abbreviations: —, does not apply; K-12, kindergarten through 12th grade; NAICS, North American Industry Classification System. a The Centers for Disease Control and Prevention invited the health departments from all 50 states, 8 US territories and freely associated states, and the District of Columbia to report aggregate surveillance data for COVID-19 outbreaks occurring in public or private work settings from August 1 through October 31, 2021. Some states passed the request on to health departments representing individual cities or counties. b Except where otherwise noted, “workplace outbreak” was defined for this study according to the Council of State and Territorial Epidemiologists’ surveillance definition for an outbreak in a nonresidential, non–health care workplace setting: “Two or more laboratory-confirmed COVID-19 cases among workers at a facility with onset of illness within a 14-day period, who are epidemiologically linked, do not share a household, and are not listed as a close contact of each other outside of the workplace during standard case investigation or contact tracing.”7 c Data source: US Census Bureau.6 d During August–October 2021, there were 12 660 workplace COVID-19 outbreaks reported overall; however, setting was unknown or undocumented for 190 workplace outbreaks. e Based on the second quarter 2021 Quarterly Census of Employment and Wages (QCEW). The QCEW is a quarterly count of the number of business establishments and monthly employment and quarterly wages for workers covered by state unemployment insurance laws and federal workers covered by the Unemployment Compensation for Federal Employees program compiled by the Bureau of Labor Statistics. Establishment counts are derived from administrative data from state and federal unemployment insurance programs. Employment and wage data are reported by employers. The QCEW covers >95% of all US jobs.9 f For major categories (ie, any health care setting, any educational setting, any other non–health care setting), column percentage denominators are based on the total number of establishments or employment across all work settings; for subcategories, column percentage denominators are based on the applicable major category. Among 11 health departments that reported 3859 workplace outbreaks during August–October 2021 and provided information about workplace assistance from health departments, 3090 (80.1%) instances of assistance involved consultation on COVID-19 mitigation strategies, 1912 (49.5%) involved outbreak response, 436 (11.3%) involved COVID-19 testing, and 185 (4.8%) involved COVID-19 vaccine distribution. Discussion Preventing and tracking COVID-19 workplace outbreaks is important because workers have little control over their work environment, workplace outbreaks can drive community transmission, and understanding the types of settings affected by COVID-19 can help inform interventions. A study of early COVID-19 cases in Colorado found that 47 of 99 (47%) cases with known infected contacts reported workplace exposure.11 Most workplace types reporting outbreaks in this study (ie, nursing and residential care facilities, K-12 schools, manufacturing facilities, correctional facilities) were previously identified as being at increased risk for COVID-19 spread. However, to our knowledge, our study is one of the first multistate reports to confirm that outbreaks continued to be common in non–health care, noneducational workplaces during a period dominated by the Delta variant, after COVID-19 vaccines and other mitigation measures became widely promoted by public health officials. Consultation on COVID-19 mitigation strategies was the most frequently requested assistance. We found a high ratio of reported outbreaks in health care and educational settings relative to the proportions of these settings among all workplaces. This high ratio may reflect a combination of a high risk of spread and increased testing and reporting in these settings compared with other workplaces. CDC published COVID-19 guidance for health care settings,12 educational settings,13 correctional and detention facilities,14 other industries, and general businesses.15 The Occupational Safety and Health Administration has also published guidance for workplaces.16 Both agencies emphasize that preventing workplace transmission of SARS-CoV-2 requires layering multiple mitigation strategies that include vaccination, improved building ventilation, the wearing of well-fitting face masks, physical distancing, handwashing, cleaning and disinfection, screening tests, isolation of cases, and quarantine of unvaccinated close contacts. Both CDC and Occupational Safety and Health Administration guidance recommend that employers report outbreaks to local health departments as required and support their contact tracing efforts; reporting is required by law in some jurisdictions. CSTE developed definitions of COVID-19 outbreaks in specific settings and provided guidance for documenting individual cases as outbreak associated. CSTE published separate outbreak definitions for nonresidential, non–health care workplace, educational, and health care settings.17 Many jurisdictions adapted the CSTE definitions to meet their local needs, as evidenced in the range in cases per outbreak and outbreak-associated cases per 100 cases reported by various jurisdictions. Health departments also developed various strategies for prioritizing workplace outbreak investigations.18 We applied the CSTE case definition of an outbreak in a nonresidential, non–health care workplace setting to all workplaces, including health care and educational settings. Using this definition, jurisdictions identified the highest number of workplace outbreaks during the study period in health care settings, followed by educational settings. Most other reported workplace settings were those in which workers interact with large numbers of the public (eg, retail trade, food and beverage stores) or work in close proximity to one another (eg, manufacturing facilities). Limitations Our study had several limitations. First, because data on workplace COVID-19 outbreaks are not consistently collected across health departments, our study was based on a passively collected convenience sample that depended on state-specific requirements. Second, reporting biases made comparisons among work settings challenging. Regular COVID-19 screening programs and public health emphasis in some work settings (eg, long-term care) meant that we compared settings that conducted active surveillance with those conducting passive surveillance. Third, difficulty in linking cases to workplaces, especially during widespread community transmission, may have resulted in under- or overcounting workplace COVID-19 outbreaks and associated cases. Fourth, use of the CSTE workplace outbreak case definition, which requires ≥2 cases among workers, could have resulted in an underestimation of outbreaks with an occupational component because of patient-, student-, or customer-to-worker transmission. Fifth, undercounts may also have resulted from a lack of reporting requirements, data lags, and other reporting challenges. Sixth, overcounts may have resulted from duplicate reporting caused by overlap among jurisdictions, ongoing cases from July outbreaks that were counted in August, transmission outside the workplace among workers, or data collection that does not distinguish between workers and nonworkers. However, CDC’s requirement that health departments report only the number of confirmed working-age cases (aged 18-64 years) minimized overcounts caused by counting nonworkers. Seventh, some limitations applied to the comparisons made between the distribution of workplace types and workers involved in the reported outbreaks and the underlying distribution of workplace types and workers in the participating jurisdictions based on QCEW data. Industry categories used in QCEW data differ slightly from industry categories used for outbreak reporting. We also note a slight mismatch between the geographic areas represented in the outbreak data and those available in the reference data. Eighth, data collection on workplace requests for assistance varied by jurisdiction: some jurisdictions included only workplace-initiated requests, and other jurisdictions included active outreach from health departments to workplaces. Follow-up data were not available to determine the extent to which the technical assistance and guidance were implemented and enforced. Ninth, data were also unavailable on the vaccination status of workers involved in outbreaks and on the prevalence of remote work in different work settings. Conclusion Our study illustrates that COVID-19 outbreaks linked to workplaces, as defined here, were commonly reported to health departments during August–October 2021, when the Delta variant was predominant in the United States. It also highlights the workplace demand for assistance that health departments experienced, particularly for consultations on COVID-19 mitigation strategies. These findings underscore the continued impact of COVID-19 among workers, the potential for work-related transmission, and the need to apply layered prevention strategies recommended by public health officials, especially as new variants of concern arise. Vaccination with the primary series and recommended boosters remain the leading public health prevention strategy to lessen economic impacts and to help end the COVID-19 pandemic by reducing transmission and risk of severe disease, hospitalization, and death. We acknowledge the following people for assistance in coordinating data collection and compilation: Namita Agravat, Caroline Bennett, Lauren Billick, Charles Braxton, Alicia Dunajcik, Laura Hill, Otto Ike, Geremy Lloyd, Veneranda Ngulefac, Francisco Palomeque, Neela Persad, Jessica Ricaldi, Laird Ruth, Rebecca Sabo, Fija Scipio, Denise Sheriff, and Christina Winfield, Centers for Disease Control and Prevention COVID-19 Response Team; Jade Angulo, Churchill County Department of Health; Katrina Hansen and Jonathan Stewart, New Hampshire Department of Public Health; Uche Ekwomadu, Salwa-Haque Mefruz, Will Still, and Christina Willut, District of Columbia Department of Health; Jaime Cassidy Comella, Monika Drogosz, Alison Green, Morgan Hargraves, Amanda Jain, Mukiio Hannah Kimanthi, Anna Makaretz, Theodore Marak, Dwayne Mitchell, Victoria Novotny, Shannon O’Rourke, and James C. Rajotte, Rhode Island Department of Health; and Elena Chan, Matt Frederick, Kathryn Gibb, Andrea Rodriguez, and Jessie Wong, California Department of Public Health. Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding: The authors received no financial support for the research, authorship, and/or publication of this article. ORCID iDs: Sara E. Luckhaupt, MD https://orcid.org/0000-0002-3000-8818 Cheryl L. Robbins, PhD https://orcid.org/0000-0003-1320-2739 Isabel Thomas, MPH https://orcid.org/0000-0001-6878-9704 Diana Valencia, MS https://orcid.org/0000-0002-9578-3751 Katharine A. Owers Bonner, PhD https://orcid.org/0000-0002-5323-5079 Kim Angelon-Gaetz, PhD https://orcid.org/0000-0002-8530-0066 ==== Refs References 1 McMichael TM Clark S Pogosjans S , et al . COVID-19 in a long-term care facility—King County, Washington, February 27–March 9, 2020. MMWR Morb Mortal Wkly Rep. 2020;69 (12 ):339-342. doi:10.15585/mmwr.mm6912e1 32214083 2 Waltenburg MA Rose CE Victoroff T , et al . Coronavirus disease among workers in food processing, food manufacturing, and agriculture workplaces. Emerg Infect Dis. 2021;27 (1 ):243-249. doi:10.3201/eid2701.203821 33075274 3 Lewis NM Salmanson AP Price A , et al . Community-associated outbreak of COVID-19 in a correctional facility—Utah, September 2020–January 2021. MMWR Morb Mortal Wkly Rep. 2021;70 (13 ):467-472. doi:10.15585/mmwr.mm7013a2 33793464 4 Dooling K McClung N Chamberland M , et al . The Advisory Committee on Immunization Practices’ interim recommendation for allocating initial supplies of COVID-19 vaccine—United States, 2020. MMWR Morb Mortal Wkly Rep. 2020;69 (49 ):1857-1859. doi:10.15585/mmwr.mm6949e1 33301429 5 Centers for Disease Control and Prevention. SARS-CoV-2 variant classifications and definitions. Updated April 26, 2022. Accessed September 15, 2022. https://www.cdc.gov/coronavirus/2019-ncov/variants/variant-classifications.html 6 US Census Bureau. North American Industry Classification System. Last revised September 15, 2022. Accessed September 15, 2022. https://www.census.gov/naics 7 Council of State and Territorial Epidemiologists. Proposed investigation criteria and outbreak definition for COVID-19 in non-residential, non-healthcare workplace settings. July 14, 2020. Accessed September 15, 2022. https://preparedness.cste.org/wp-content/uploads/2020/08/OH-Outbreak-Definition.pdf 8 California Department of Public Health. Non-healthcare congregate facilities COVID-19 outbreak definitions and reporting guidance for local health departments. May 18, 2020. Accessed September 15, 2022. https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/COVID-19/OutbreakDefinitionandReportingGuidance-10-13-2020.aspx 9 Centers for Disease Control and Prevention. National Notifiable Disease Surveillance System (NNDSS): coronavirus disease 2019 (COVID-19) 2021 case definition. Page last reviewed August 24, 2021. Accessed September 15, 2022. https://ndc.services.cdc.gov/case-definitions/coronavirus-disease-2019-2021 10 US Bureau of Labor Statistics. Quarterly census of employment and wages. Accessed September 15, 2022. https://www.bls.gov/cew 11 Marshall K Vahey GM McDonald E , et al . Exposures before issuance of stay-at-home orders among persons with laboratory-confirmed COVID-19—Colorado, March 2020. MMWR Morb Mortal Wkly Rep. 2020;69 (26 ):847-849. doi:10.15585/mmwr.mm6926e4 32614809 12 Centers for Disease Control and Prevention. Interim infection prevention and control recommendations for healthcare personnel during the coronavirus disease 2019 (COVID-19) pandemic. Updated February 2, 2022. Accessed September 15, 2022. https://www.cdc.gov/coronavirus/2019-ncov/hcp/infection-control-recommendations.html 13 Centers for Disease Control and Prevention. Operational guidance for K-12 schools and early care and education programs to support safe in-person learning. Updated August 11, 2022. Accessed September 15, 2022. https://www.cdc.gov/coronavirus/2019-ncov/community/schools-childcare/k-12-childcare-guidance.html 14 Centers for Disease Control and Prevention. Guidance on prevention and management of coronavirus disease 2019 (COVID-19) in correctional and detention facilities. Updated May 3, 2022. Accessed September 15, 2022. https://www.cdc.gov/coronavirus/2019-ncov/community/correction-detention/guidance-correctional-detention.html 15 Centers for Disease Control and Prevention. COVID-19 information for the workplace. Page last reviewed October 5, 2021. Accessed September 15, 2022. https://www.cdc.gov/niosh/emres/2019_ncov_default.html 16 Occupational Safety and Health Administration. Protecting workers: guidance on mitigating and preventing the spread of COVID-19 in the workplace. Updated June 10, 2021. Accessed September 15, 2022. https://www.osha.gov/coronavirus/safework 17 Council of State and Territorial Epidemiologists. COVID-19 outbreak investigations and reporting. Accessed September 15, 2022. https://preparedness.cste.org/?page_id=211 18 Bonwitt J Deya RW Currie DW , et al . COVID-19 surveillance and investigations in workplaces—Seattle and King County, Washington, June 15–November 15, 2020. MMWR Morb Mortal Wkly Rep. 2021;70 (25 ):916-921. doi:10.15585/mmwr.mm7025a3 34166336
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==== Front Sch Psychol Int Sch Psychol Int SPI spspi School Psychology International 0143-0343 1461-7374 SAGE Publications Sage UK: London, England 10.1177/01430343221138785 10.1177_01430343221138785 Special Issue: Resilience to COVID-19 Challenges Student resilience to COVID-19-related school disruptions: The value of historic school engagement https://orcid.org/0000-0002-3979-5782 Theron Linda University of Pretoria, South Africa Ungar Michael Resilience Research Centre, 3688 Dalhousie University , Canada Höltge Jan Resilience Research Centre, 3688 Dalhousie University , Canada Linda Theron, Department of Educational Psychology, University of Pretoria, Groenkloof Campus, Pretoria 0002, South Africa. Email: [email protected] Jan Höltge, Dalhousie University, School of Social Work, Resilience Research Centre, 6420 Coburg Rd, B3H 4R2, Halifax, NS, Canada. E-mail: [email protected] 9 12 2022 9 12 2022 01430343221138785© The Author(s) 2022 2022 SAGE Publications This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. Does historic school engagement buffer the threats of disrupted schooling – such as those associated with the widespread COVID-19-related school closures – to school engagement equally for female and male high school students? This article responds to that pressing question. To do so, it reports a study that was conducted in 2018 and 2020 with the same sample of South African students (n = 172; 66.30% female; average age in 2020: 18.13). A moderated moderation model of the 2018 and 2020 data showed that historic levels of school engagement buffered the negative effects of disrupted schooling on subsequent school engagement (R² = .43, β = −5.09, p < .05). This protective effect was significant for girl students at moderate and high levels of historic school engagement, but not at lower levels of historic school engagement. Disrupted schooling did not significantly affect school engagement for male students at any level of historic school engagement. In addition, student perceptions of teacher kindness were associated with higher school engagement and having experienced an adverse event at school with lower school engagement. The results point to the importance of facilitating school engagement and enabling school environments – also when schooling is disrupted. Disrupted schooling female students resilience school engagement South African adolescents Canadian Institutes of Health Research https://doi.org/10.13039/501100000024 IP2- 150708 Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung https://doi.org/10.13039/501100001711 P400PS_194538 edited-statecorrected-proof typesetterts19 ==== Body pmcIntroduction Across the globe, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2 or COVID-19) pandemic disrupted schooling during 2020 and 2021. Schools in at least 180 countries closed for varying periods of time (Azevedo, 2020; Lee, 2020). Although such school closures were well-intended (i.e., to limit the spread of COVID-19), they were associated with multiple costs to school students’ education, safety, and wellbeing (de Miranda et al., 2020; Van Lancker & Parolin, 2020). Even when empirical studies reported limited costs of school closures to students’ mental wellbeing in the short term (e.g., Luthar et al., 2020), these studies cautioned that the long-term costs were likely to be substantive. Of additional concern is that school closures could cause students to disengage from schooling and prompt poor long-term outcomes, including challenges to students’ future economic independence and mental wellbeing (Azevedo, 2020; Coker et al., 2020; World Bank, 2020). While these concerns apply to all students, students with experiences of marginalisation are likely more vulnerable to the costs of school closures (Dorn et al., 2020). Rather than focus on the costs of school closures to student wellbeing, this article investigates students’ capacity to remain school engaged in the face of COVID-19-related school closures. In specific, it investigates the capacity of a sample of South African high school students (n = 172), from a resource-constrained (i.e., marginalised) municipality, to remain school engaged following the closing of their schools in March 2020. It considers what could potentially buffer the negative effects of school closure on school engagement. The attention to buffering or protective factors –– i.e., those factors that facilitate positive outcomes despite exposure to significant stress –– fits with calls to advance child and youth resilience to COVID-19-related stressors (Dvorsky et al., 2020; Holmes et al., 2020), also in the school context (Luthar et al., 2020). Children in disadvantaged contexts – such as those living in resource-constrained, marginalised municipalities – are particularly reliant on education to beat the odds of their circumstances (World Bank, 2020), and so it is crucial to better understand and enable/sustain their school engagement in the face of school closures. School engagement School engagement, which is considered fundamental to progress at school and/or academic achievement, is defined as a student's involvement in, or commitment to, their schooling (Fredricks et al., 2004). Typically, behavioural, emotional, and cognitive commitment to schooling epitomises school engagement (Fredricks et al., 2005). Put differently, school engagement is demonstrated in a student's school-related behaviour (e.g., actively participating in learning and other school activities); school-related emotion (e.g., appreciating learning opportunities or liking their peers/teacher); and school-related cognitive processes (e.g., being attentive in class or associating new learning with prior learning) (Fredricks et al., 2004; Lam et al., 2014; Sinatra et al., 2015). As summarised next, multiple factors are associated with a student's capacity for school engagement. Whilst these resources all matter for sustained school engagement, which matter more is likely to vary for specific groups of students in specific contexts at specific points in time (Wang et al., 2020). Student factors A student's capacity for school engagement can relate to sociodemographic factors (e.g., race, age, gender; Wang & Eccles, 2012). In particular, female gender and non-membership of marginalised racial/ethnic groups are associated with higher levels of school engagement (Wang et al., 2011). While no definitive reason is given for girls being more school engaged, there is speculation that this relates to how girls are socialised (Roorda et al., 2011). However, vulnerable groups of girls (e.g., teenage mothers) might be more likely to disengage in the absence of supports to remain school engaged (Fredricks et al., 2004). Further, personal resources (e.g., grit, self-regulation skills, executive functioning skills, or social functioning) are implicated in a student's capacity to be behaviourally, emotionally, and cognitively invested in their schooling (Fredricks et al., 2004). Home environment factors Higher school engagement is positively associated with material resources in the home environment (e.g., education-enabling resources; space to study). It is also positively associated with supportive parenting (e.g., warm caregiving) and parental capacity to scaffold learning tasks at home (Sharkey et al., 2008; Wang & Eccles, 2012). Household routine and parental expectations that their children commit to their schooling are similarly enabling (Sharkey et al., 2008). School context factors Various school-related resources are associated with higher levels of school engagement (e.g., positive peers; positive classroom climate; Fredricks et al., 2004). When students feel safe and accepted at school, they tend to be more engaged in academic and extra-curricular activity (Bang et al., 2020). Teacher-student relationships can be especially pivotal to school engagement. Kind or caring teachers are positively associated with higher school engagement (Malindi & Machenjedze, 2012; Motti-Stefanidi & Masten, 2013; Quin, 2017; Roorda et al., 2011). Similarly, teacher competence (i.e., teachers who teach well) is associated with higher school engagement (Fredricks et al., 2004; Wang et al., 2020). A resource mix Typically, studies of school engagement point to a mix of resources that draws on strengths within students and their social ecologies (Fredricks et al., 2004). For example, a three-wave longitudinal study with 363 foster children (mean age: 11.30, SD = 3.22) in the Netherlands reported that better grades, no absenteeism, demographics (gender, younger age), and positive parenting predicted higher school engagement (Goemans et al., 2018). Similarly, a two-wave longitudinal study with 714 early adolescents in Korea reported that students who reported high levels of teacher and peer support also reported high levels of current and subsequent school engagement (Shin & Chang, 2022). The cost of school closures to the resources that inform school engagement Essentially, COVID-19-related school closures have the potential to disrupt access to the individual, home-, and school-related resources that matter for behavioural, emotional and cognitive engagement in schooling. For instance, COVID-related school closures were associated with significant threats to many students’ physical and mental health, more especially for students from disadvantaged households (Onyema et al., 2020; Rajmil et al., 2021). Reduced psychological wellbeing could jeopardise the personal resources (e.g., self-regulation; attentive involvement in learning; social functioning) implicated in higher levels of school engagement. Likewise, for students who depended on school feeding schemes, school closures probably resulted in hunger with negative knock-on effects for personal health and wellbeing resources (Clark et al., 2020). There were also concerns about student exposure to abuse/maltreatment and parental conflict during lockdown and students’ wellbeing, social functioning, and role functioning (e.g., at home/school) (Clark et al., 2020; Rajmil et al., 2021). Similarly, COVID-related school closures created substantive stress for many teachers and parents, thereby potentially straining teacher capacity for kindness and competence and parent capacity for warm, supportive caregiving (Fontanesi et al., 2020; Kim & Asbury, 2020; Panagouli et al., 2021). Even when students were supported to learn remotely while their schools were closed, remote access could not compensate for in-person interaction with supportive peers or stem the boredom and reduced social functioning that many youngsters reported (Onyema et al., 2020). Thus, in jeopardising student access to the individual, home-, and school-related resources that matter for commitment to schooling, school closure potentiates a direct threat to school engagement. Put differently, lockdown-related interruptions to schooling could lessen students’ behavioural, emotional, and cognitive commitment to schooling, especially for students from marginalised communities (Onyema et al., 2020). For example, a study with a large sample of school students (n = 943) and their parents and teachers in rural and disadvantaged parts of Indonesia reported school closure-related threats to school engagement (Indrawati et al., 2020). These included digital resource constraints that stymied student engagement with learning and prompted negative emotion (e.g., anxiety) toward schooling tasks. Students reported difficulty engaging in/completing academic tasks without the support of their teachers/peers. Additionally, economic constraints resulted in some students being engaged in domestic chores or child labour rather than remote learning and related declines in commitment to schooling. The costs of school closures appear to be higher for girls, possibly because girls are expected to contribute to the running of their households and/or take on care duties (Clark et al., 2020). For instance, girls exposed to the Ebola epidemic and other crises (e.g., economic crises in Ethiopia and Brazil) were more likely to report experiences of abuse and less likely to resume their schooling when schools reopened (World Bank, 2020). Similar trends have been reported during the COVID-19-related school closures (Coker et al., 2020; Molek & Bellizzi, 2022), with particular concern voiced for girls in sub-Saharan countries. For them, school closures typically meant heightened involvement in domestic chores and care duties and related disengagement with schooling (Oppong Asante et al., 2021). Further, compared with male students, higher rates of lockdown-related depression and anxiety were reported for female students in America (Luthar et al., 2020), and elsewhere (e.g., Iceland; Halldorsdottir et al., 2021; India, Malaysia, Korea, Thailand, Israel, Iran, and Russia; Loades et al., 2020). Again, these higher costs to girls might relate to how girls are socialized (e.g., to value relational resources; these resources were typically curtailed during lockdown). 2020 COVID-19-related school closures in South Africa Shortly after the World Health Organisation (WHO) declared COVID-19 a global pandemic in March 2020, South Africa announced a state of emergency that resulted in a stringent, national lockdown with five alert levels (level 5 being the most stringent). It was described as “one of the most rigid and extreme lockdowns announced anywhere in the world” (Habib, 2020). The lockdown prompted school closures. In addition, human movement was curtailed, public gatherings were banned, and all non-essential services disallowed. In short, this meant that from 18 March to 8 June (alert levels 3–5) young people could not go to school, roam their neighbourhood, socialise with their peers, or engage in sport or other extramural activity (Fouché et al., 2020). This was followed by a staggered return to school, with students in Grade 7 and 12 returning first. However, in response to a COVID-19 spike, schools were closed for a second time from 27 July to 24 August 2020. Although alert levels were adjusted downwards thereafter, public health requirements (e.g., maintenance of physical distance, face-masking) remained mandatory. Thus, even though schools were no longer officially closed, many schools could not accommodate all students simultaneously and so most South African students lost additional contact teaching days (Soudien et al., 2021). Overall, it was estimated that depending on their age and grade, South African students lost between 30 and 59 school days in the 2020 school year (Timm, 2021), or 22%-65% of regular/contact school time (Spaull & van der Berg, 2020; Soudien et al., 2021). Further, the reopening of schools did not eliminate high levels of insecurity about when next schools would close or diminish adolescents’ feelings of uncertainty about their present and future (Gittings et al., 2021). As in other parts of the world, the closure of South Africa's schools generated censure. There was pronounced concern for the nine million South African children who rely on school feeding schemes. The hunger that disrupted access to school feeding schemes would inevitably induce for this vast population of students, led to some labelling school closure “a form of abuse or neglect” (van Bruwaene et al., 2020). Further, given that only a minority of South African students have access to technology (Spaull & van der Berg, 2020), school closure was criticized for its disrespect of children's universal right to education and educational progress (Wolfson Vorster, 2020). The current study The current study's aim was to investigate the school engagement of a sample of South African high school students whose schooling was disrupted in the course of 2020, with particular interest in factors that could have protected continued school engagement regardless of how school closures disrupt access to the resources that enable school engagement. In so doing, the study responded to the multiple calls to better understand and advance youth resilience in the face of COVID-19-related challenges (Dvorsky et al., 2020; Holmes et al., 2020; Luthar et al., 2020). School engagement is frequently associated with the resilience of youth from disadvantaged contexts in South Africa (Van Breda & Theron, 2018). A better understanding of what might support continued school engagement despite the challenges of repeated school closures (Spaull & van der Berg, 2020), is crucial to sustaining that resilience. The literature on the negative impacts of school closure on the individual, home- and school-related resources that are fundamental to school engagement (e.g., Clark et al., 2020; Coker et al., 2020; de Miranda et al., 2020; Van Lancker & Parolin, 2020; World Bank, 2020) led us to expect that school engagement would be negatively impacted the longer the duration of disrupted schooling (i.e., number of days since schools were first closed). Simultaneously, this prompted our attention to the possible role of historic school engagement when access to the resources that typically sustain school engagement is jeopardized. However, our reading of the longitudinal studies of school engagement suggested that very little attention has been paid to the role of historic/prior levels of school engagement in predicting subsequent levels of school engagement. Exceptions included a study by Quin and colleagues with 719 Australian adolescents (average age: 16.96; SD = 0.38); they found that gender (i.e., female), higher prior (i.e., Grade 10) engagement levels, and better prior academic grades predicted higher school engagement in Grade 11. Similarly, prior levels of school engagement, gender, race, and advantaged versus disadvantaged family circumstances predicted student membership in higher behavioral and emotional school engagement trajectories in a study with 1,977 American adolescents (Li & Lerner, 2011). In short, being male, a student of color, and having a less advantaged family background predicted lower behavioral and emotional engagement. Further, Li and Lerner (2011) found that higher school engagement over time predicted better academic, behavioral, and emotional outcomes. Despite the paucity of studies documenting the role of historic school engagement on subsequent school engagement and achievement (Li & Lerner, 2011; Quin et al., 2018), their results let us expect that higher levels of historic school engagement might buffer the negative effects of exposure to disrupted schooling. On the contrary, lower levels of historic school engagement might be a risk factor for school engagement during school disruption. However, following broad understandings that gender is related to school engagement (i.e., girls are likely to report higher school engagement than boys; Li & Lerner, 2011; Wang & Eccles, 2012), the buffering effects of lower/higher levels of historic school engagement might be dependent on student gender. Overall, therefore, the main aim of the current study was to investigate if lower levels of historic school engagement increase, and higher levels of historic school engagement decrease, the expected negative effect of the duration of COVID-related school closures on present school engagement, and if these effects differ for female and male students. We hypothesized that (H1) compared with male students, female students would show a stronger negative effect of school disruption on present school engagement at lower levels of historic school engagement. We also expected that (H2) there would be no significant difference between female and male students in the effect of school disruption on present school engagement at higher levels of historic school engagement. Furthermore, we included multiple meaningful covariates in the analyses. Given the ‘resource mix’ that informs school engagement (e.g., Fredricks et al., 2004; Quin, 2017; Quin et al., 2018; Sharkey et al., 2008), we anticipated that resources at the level of individual students (i.e., mental health [fewer symptoms of depression]; intact social and role functioning), their households (harmonious functioning; family support; warm parenting), and school (teacher kindness; teacher competence; safe school environment) might matter for school engagement, even when access to schooling is disrupted. Method Procedure The sample was drawn from the Resilient Youth in Stressed Environments (RYSE) study. As detailed elsewhere (Ungar et al., 2021), RYSE investigated the multisystem resources that supported youth resilience over time in Canadian and South African communities stressed by economic and ecological challenges. Given the marginalization of African youth in the school engagement literature (Lam et al., 2014), the sample reported on in this paper is from RYSE South Africa (SA). RYSE SA was conducted in a semi-urban town and neighbouring township. Both are in a resource-constrained municipality in one of South Africa's poorer provinces (i.e., Mpumalanga). Most households in this municipality report limited resources. Of relevance to school closures, 80.5% of households in this municipality have a television but only 24.3% have a computer; 62.3% report no internet access (StatsSA, 2011). Similar statistics are reported for most South African households and that could account for the national education department's use of television broadcasts to facilitate remote learning (also in COVID-19 times) (Spaull & van der Berg, 2020). The principal RYSE investigators’ Institutional Review Boards provide ethical clearance. A Community Advisory Panel (CAP) that was made up of local adults and adolescents guided the study and facilitated participant recruitment (Ungar et al., 2021). Recruitment criteria were defined as: (a) residence/school attendance/employment in the town/township affiliated to RYSE; (b) 14- to 24-years-old; and (c) English literacy (English is the medium of instruction in most South African high schools and South Africa's official language of communication). Following prior resilience studies in South Africa (Van Rensburg et al., 2019) and the advice of the CAP, trained research assistants (RAs) administered the survey to small groups of participants. The RAs read an item aloud before participants self-completed it. This method was repeated in 2020, except that survey administration was one-on-one (as regulated by COVID-19 procedures). Each participant (and their parent/legal guardian if participants were younger than 18) consented in writing prior to survey completion and received a supermarket voucher for their time ($15 in 2018 and $30 in 2020). Measures The reliabilities of the scales can be found in Table 1. Table 1. Sample characteristics, reliabilities, and Spearman correlations. Variables M (SD) ω 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 SE 2018 120.88 (14.05) .92 – SE 2020 123.24 (13.63) .93 .44* – DSFSC 141.65 (42.35) – −.12 −.01 – Sex (female vs. male) Female: 66.30% – .08 .06 −.06 – Age 18.13 (1.73) – −.09 −.05 −.29* .18* – Depression (BDI-II) 15.35 (11.05) .91 −.15 −.26* −.20* −.16* .08 – Role functioning 5.55 (.87) .66# −.13 −.09 .17* .05 −.13 −.30* – Social functioning 4.99 (1.34) – −.00 .06 .10 .02 −.09 −.36* .30* – Adversity at home Yes: 30.30% – −.00 −.00 .11 −.18* −.02 −.06 −.02 −.16* – Limited functionality at home 1.88 (1.26) – −.05 −.12 −.02 −.12 .10 .22* −.16* −.27* .26* – Family support 9.23 (1.45) .74# .10 .22* −.08 .20* .14 −.36* .16* .23* −.12 −.23* – PC Warmth 11.51 (1.43) .91 .14 .16* −.20* .14 .00 −.26* .04 .14 −.09 −.21* .36* – Caregiver conflict Yes: 22.10% – .15* .12 −.15 .11 .02 −.29* .22* .16 −.17* −.21* .21* .15 – Teacher competence 1.09 (.28) – −.18* −.17* −.00 −.05 −.21* .18* −.06 −.10 −.02 .10 −.11 −.14 −.13 – Teacher kindness 1.11 (.33) – −.10 −.18* −.14 .00 −.03 .16* −.08 −.08 −.10 −.07 −.10 .04 .05 .10 – Adversity at school Yes: 23.80% – .06 −.13 −.02 .01 .06 −.01 .03 .19* −.37* −.16* .01 .04 .10 .02 −.01 – Limited functionality at school 1.82 (1.24) – −.10 −.16* .14 −.16* −.05 .26* −.17* −.12 .10 .48* −.24* −.14 −.23* .11 −.10 −.02 Note. N = 172. ω = Omega coefficient for reliability. SE = school engagement, DSFSC = Days since first school closure at participation, PC = Parental/Caregiver. *p < .05. #Spearman-Brown coefficient for reliability of two items. Student/individual factors Student/individual factors included demographic factors. Participants self-reported their sex (male/female) and age. Student/individual factors also included school engagement, mental health (depression symptoms), and social and role functioning. School engagement was assessed via the 32-item School Engagement Scale (SES; Lam et al., 2014). The original, cross-cultural study showed sufficient internal consistency of the overall scale (α = .78), sufficient concurrent validity (Lam et al., 2014), and that a second-order model fits the scale best with three subscales (i.e., affective, behavioral, cognitive) and one overarching school engagement factor. Sample items for each subscale include: ‘I am happy to be at this school’ (affective); ‘If I have trouble understanding a problem, I go over it again until I understand it’ (behavioral); and ‘When I study, I figure out how the information might be useful in the real world’ (behavioral). These items were summed into one overall SES score. Higher total scores indicated higher engagement. The scale uses a five-point Likert scale from 1 = “strongly disagree” to 5 = “strongly agree”, which results in a potential range of 32–160. Depressive symptomatology over the past two weeks (as an indicator for mental health) was assessed via the Beck Depression Inventory–II (BDI-II) (Beck et al., 1996). The scale assesses 21 depression-related symptoms (e.g., sleep problems, depressive mood, loss of interest) and a higher sum-score indicated higher levels of depression. Psychometric studies with high school students have shown adequate internal consistency (e.g., α = .92) and validity (Osman et al., 2008). A shortened version of the Short-Form Health Survey-20 (Ware et al., 1992) was used to assess social and role functioning. Both subscales have shown sufficient validity (McHorney et al., 1993) and role functioning sufficient reliability (α = .76; Carver et al., 1999). Social functioning was assessed with one item (“How much of the time, during the past month, has your health limited your social activities, like visiting with friends or close relatives?”; [1 = “Limited for more than 3 months”, 2 = “Limited for 3 months or less”, 3 = “Not limited at all”]) and role functioning with two items (“Does your health keep you from working at a job, doing work around the house, or going to school?”, “Have you been unable to do certain kinds or amounts of work, housework, or schoolwork because of your health?”; [1 = “All of the time“ to 5 = “None of the time”]). Home environment factors Home environment factors related to the relationship between students and their parents/caregivers, as well as the parental relationship. The Parental-Caregiver Warmth scale (which forms part of the Social and Health Assessment scale, Ruchkin et al., 2004) was used. It asks about the frequency of a participant experiencing that their parent/caregiver: “Is proud of me”, “Shows their love for me”, and “Makes me feel good when I am with them” (1 = “Never” to 4 = “Most of the time”). A higher sum-score indicated higher parental-caregiver warmth. This scale has shown sufficient internal consistency (α = 82; Barbot et al., 2012). Two items were used to indicate currently perceived family support: “My family stands by me during difficult times” and “I feel safe when I am with my family” (1 = “Not at all” to 5 = “A lot”). Both were taken from the Child and Youth Resilience Measure (Ungar & Liebenberg, 2011), an instrument that covers 28 different social-ecological resources which have been shown to be essential for child and youth resilience across countries. A higher sum-score indicated higher family support. Additionally, participants were asked if they lived in a home with fights (verbal or physical) or severe relationship problems between parents/parent-figures/caregivers (yes/no). They were also asked if the most upsetting or frightening event they experienced in the past year happened at home, school, in the neighborhood, or somewhere else (they could choose only one option). One dummy coded variable was included into the model for participants who had experienced this event at home (“Adversity at home”). In relation to this question, they had to indicate if this event caused problems for them at home (“Limited functionality at home”) (1 = “Not at all” to 5 = “A lot”). School context factors School context factors related to perceived teacher characteristics and the school environment. An item assessed participants’ subjective perception of their teacher kindness (“My teachers treat me well (e.g., are friendly)”), and another assessed teacher competence (“My teachers teach well”). Both items were used in the Pathways to Resilience Youth Measure (PRYM; Resilience Research Centre, 2010) that was adapted for use with South African students during the Pathways study (Van Rensburg et al., 2018). These items were rated on a three-point Likert scale (1 = “agree”, 2 = “unsure”, 3 = “disagree”). Higher scores indicate little teacher kindness and competence, respectively. Furthermore, one item investigated if participants had experienced their most upsetting or frightening event during the last year at school (“Adversity at school”). In relation to this question, they had to indicate if this event caused problems for them at school (“Limited functionality at school”) (1 = “Not at all” to 5 = “A lot”). Days since first school closure (DSFSC) This was calculated as time (in days) from first school closure because of COVID-19 lockdown measures (March 18th, 2020) to the date when the survey was conducted in 2020 (see Figure 1). Figure 1. Study timeline. Note. SC = school closure. Alert level in relation to COVID-19 regulations. Participants The 2018 sample consisted of N = 340 high school students. The analyses reported in this article include high school students who participated in 2018 and 2020, were still school attending in 2020, and completed the school engagement scales (i.e., n = 172; n = 114 female students; average 2020 age: 18.13 years [SD = 1.73]; 81.40% Black, 15.10% White, 3.50% Other). One student did not fill out the school engagement scale in 2018 and was therefore excluded. The mean score for total school engagement was 120.88 (SD = 14.06) and 123.24 (SD = 13.36) in 2018 and 2020 respectively. The period from the start of the first school closures (18 March 2020) to date of participation ranged from 77 to 215 days (see Figure 1). Please see Table 1 for further sample characteristics. In comparison to the 2020 sample, those who only participated in 2018 (n = 167, 49% drop-out) were majority female (59.9%). Their average age, 16.84 years (range 14–22 years), was significantly higher [t = 3.93, p < .01]). Like the 2020 sample, most self-identified as Black (82%). Compared to the 2020 sample, those who dropped out did not show any significant differences regarding school engagement: total (t = −.15, p > .05), affective (t = −.03, p > .05), behavioral (t = −.77, p > .05), and cognitive (t = −.53, p > .05) school engagement. However, they did show a significant difference regarding the grade they were in in 2018 (typically, a higher grade [r = .23, p < .01]). Analyses A random forest approach was used to impute missing values using missForest (for details see Stekhoven & Bühlmann, 2012) via R 4.0.4 in Rstudio 1.4.1103 (R Core Team, 2020). Overall, one person had one missing value in the BDI-II. Furthermore, the following assumptions of regression were tested (Hayes, 2018): homoscedasticity and linearity via plotting the relationship between standardized residuals and standardized predicted values, normal distribution of the errors via the Shapiro-Wilk test, and independence of the residuals via the Durbin-Watson test. The main model of interest was a moderated moderation model. A basic moderation analysis tests if the effect of a predictor on an outcome depends on the levels of a moderator, which is represented by a 2-way interaction between the predictor and moderator in the statistical model. A moderated moderation analysis tests if the influence of this first moderator itself depends on the levels of a second moderator, which is represented by a 3-way interaction. The respective effects of the predictor and moderators, as well as the 2-way interactions in the moderated moderation model must be interpreted as simple effects (and not main effects, for details see Hayes, 2018). The simple effect of a variable is its effect on the outcome when all other variables that are part of the interaction are zero. Hence, simple effects are only meaningful when the range of these variables includes zero. According to Hayes (2018), two models need to be estimated and formally tested to select the better fitting model to the data. First, a baseline model without any interaction term between the variables of interest (i.e., days since first school closure, school engagement in 2018, and the participants’ sex). The second model includes the interactions of interest (see Figure 2). In the case of this study, the moderated moderation model included three 2-way interactions between the variables of interest, as well as one 3-way interaction between all of them. All other variables that are presented in the Measures section were included as covariates. A simple effect in this moderated moderation model indicates, for example, the effect of sex on school engagement in 2020 when days since first school closure and school engagement in 2018 are zero. However, both variables, as well as sex, do not include zero and, therefore, their simple effects should not be interpreted (Hayes, 2018). Figure 2. Conceptual model. The PROCESS 3.5 add-on (Hayes, 2018) for IBM SPSS 26 (IBM Corp, 2020) was used to estimate the moderated moderation model and to test if the 3-way interaction term provided a significant increase in explained variance compared to a model without the term (i.e., test of highest order unconditional interaction). A Johnson-Neyman plot was used to identify regions of statistical significance in the case that the moderated moderation model fitted the data better than the baseline model and the 3-way interaction term was significant (Hayes, 2018; Johnson & Fay, 1950). This procedure shows if the effect of the predictor on the outcome is significant only at specific values of the moderator by taking the whole range of the moderator into account. This procedure was done using interactions 1.1.3 (Long, 2020). Results Model fit The preliminary analysis showed that the moderated moderation model (R² = .43, AIC = 1332, BIC = 1402) had a better fit to the data than the baseline model (R² = .22, AIC = 1375, BIC = 1425). The formal test showed a significant increase in R² (ΔR² = .21, F(6, 151) = 9.34, p < .01). The plotting of the relationship between the standardized residuals and standardized predicted values of the moderated moderation model was indicative of homoscedasticity and linearity (please see the Supplementary Material for the respective plot). Furthermore, a non-significant Shapiro-Wilk test indicated a normal distribution of the model's residuals (S-W statistic = .99, p > .05). A non-significant Durbin-Watson test indicated that the residuals were statistically independent (D-W statistic = 1.78, p > .05). Hence, all assumptions were met. Moderated moderation model The significant 3-way interaction (β = −5.09, p < .05, see Table 2) shows that the moderating effect of school engagement in 2018 on the effect of days since first school closure at participation on school engagement in 2020 was different for female and male pupils. The test of highest order unconditional interaction showed that this 3-way interaction significantly explained variance in school engagement in 2020 (F(1,151) = 4.08, p < .05, ΔR² = .05). As Figure 3 shows, the moderating effect of school engagement 2018 was only found for female pupils. Figure 3. Johnson-Neyman plots for girls (A) and boys (B). Note. SE 2018: school engagement in 2018, DSFSC: days since first school closure at participation, Effect of DSFSC on SE 2020: range of regression coefficients for the effect of DSFSC on school engagement in 2020. Dark grey areas indicate significant effects of DSFSC on SE 2020 in relation to the respective levels of SE 2018. The light grey area indicates non-significant effects of DSFSC on SE 2020 in relation to the respective levels of SE 2018. Table 2. Results for the moderated moderation model. b SE(b) β p 95% CI(b) DSFSC# −1.79 .56 −5.56 <.01 [−2.903, −.675] SE 2018# −1.78 .72 −1.90 .01 [−3.189, −.362] Sex (female vs. male)# −138.46 61.40 −4.82 .03 [−259.780, −17.147] Age .13 .55 .02 .82 [−1.223, .969] Depression −.14 .12 −.11 .25 [−.373, .096] Role functioning −1.71 1.09 −.11 .12 [−3.854, .439] Social functioning −.67 .75 −.07 .37 [−2.146, .801] Adversity at home −3.89 2.14 −.13 .07 [−8.109, .334] Limited functionality at home −.41 .85 −.04 .63 [−2.099, 1.270] Family support 1.025 .74 .11 .16 [−.425, 2.476] PC Warmth −.36 .82 −.04 .66 [−1.969, 1.259] Caregiver conflict .02 2.31 .00 .99 [−4.539, 4.574] Teacher competence −5.19 3.19 −.11 .11 [−11.501, 1.119] Teacher kindness −6.46 2.68 −.16 .02 [−11.760, −1.157] Adversity at school −6.47 2.19 −.20 <.01 [−10.796, −2.136] Limited functionality at school −1.28 .82 −.12 .12 [−2.899, .343] SE 2018 * DSFSC# .01 .00 5.55 <.01 [.005, .023] SE 2018 * Sex# 1.03 .50 4.72 .04 [.055, 2.011] DSFSC * Sex# .85 .38 5.55 .02 [.094, 1.612] SE 2018 * DSFSC * Sex −.01 .00 −5.09 .04 [−.012, −.001] Note. R² = .43. * indicate interaction terms. #simple effects. b: unstandardized effect, β: standardized effect, SE: standard error, CI: confidence interval, SE = school engagement, DSFSC: days since first school closure at participation. Figure 3A shows the regions of significance for female students. A negative effect of days since first school closure on school engagement in 2020 was estimated for a score of school engagement in 2018 between 74–115. Furthermore, a region of significance for a positive effect of days since first school closure on school engagement 2020 was also estimated for girls with a school engagement 2018 score between 135–147. Male pupils did not show any significant moderating effect of school engagement 2018. As can be seen in Figure 3B, no significant effect of days since first school closure on school engagement 2020 was found at any level of historic school engagement. Furthermore, two school-related covariates (i.e., teacher kindness and the most upsetting/frightening adversity experienced at school) showed significant effects on school engagement in 2020 (see Table 2). Discussion The current study investigated the school engagement of 172 South African high school students, from an economically marginalized municipality, who experienced COVID-19-related school disruptions in the course of 2020. The study's interest was in factors that could have protected (i.e., moderated) continued school engagement regardless of how school closures might disrupt access to the resources that enable school engagement. School engagement is frequently associated with the resilience of youth from disadvantaged contexts in South Africa (Van Breda & Theron, 2018). A better understanding of what might support continued school engagement, despite how repeated school closures are likely to disrupt the individual, home- and school-related resources that support school engagement (e.g., Clark et al., 2020; Coker et al., 2020; de Miranda et al., 2020; Spaull & van der Berg, 2020; Van Lancker & Parolin, 2020; World Bank, 2020), is crucial to sustaining/advancing youth resilience in the face of COVID-19-related challenges. Prior studies of the relationship between historic and subsequent levels of school engagement (i.e., Li & Lerner, 2011; Quin et al., 2018) led us to expect that historic school engagement might have a significant effect on the negative impact of school disruption on present school engagement. However, this effect might not be the same for female and male students (Wang & Eccles, 2012; Wang et al., 2011). Hence, it was the aim of this study to investigate if historic school engagement influences the expected negative effect of the duration of pandemic-related school closure on present school engagement, and if its influence is different for female and male students. We anticipated that lower levels of historic school engagement would be a risk factor in that it enhances the negative effect of school disruption on present school engagement (Li & Lerner, 2011; Quin et al., 2018), and that this interaction is stronger for female than male students (Wang & Eccles, 2012; Wang et al., 2011). In line with our first hypothesis, the analysis showed that prior levels of school engagement (i.e., as measured in 2018) mattered for school engagement in 2020 and only for female students. The longer the duration of COVID-19-related disruptions to schooling, the lower the 2020 levels of school engagement for female students who reported lower school engagement in 2018. Time since first school closure showed no effect on 2020 school engagement for female students who were moderately school engaged in 2018. However, no significant moderating effect of historical school engagement was found for male students. For male students, the time since the first school closure on present school engagement in 2020 had no significant effect at low as well as moderate levels of historic school engagement in 2018. Hence, this model confirmed that historic levels of school engagement operate differently for female and male students. Our second hypothesis expected that female and male students would show no significant differences in the effect of school disruption on present school engagement at higher levels of historic school engagement. When girls reported higher levels of 2018 school engagement, the time since the first school closure showed a significantly positive effect on 2020 school engagement. Hence, girls with higher levels of historic school engagement were able to increase their school engagement the longer the time since the first school disruption. For boys, however, no significant effect was found. Overall, while the effect of the time since the first school closure on present school engagement in 2020 is significantly impacted by the level of historic school engagement in female students, no such effects exist for male students. Also, the identified neutral and positive effects are at odds with historic reports of girls’ school engagement suffering more than that of boys when schooling is disrupted (e.g., during the Ebola pandemic; World Bank, 2020), and with concerns about girls being especially vulnerable to COVID-19 lockdown risks (e.g., increased rates of teenage pregnancy; Molek & Bellizzi, 2022). The potentially protective effect of historic school engagement on girls’ school engagement during times of prolonged school closure is an important contribution to the school engagement literature. Furthermore, two co-variates– both school-related – were significantly associated with school engagement in the context of COVID-19: teacher kindness and limited experience of adversity at school. This fits with the general school engagement literature that emphasizes the value of caring (i.e., kind) teachers and safe or affirming school environments to students’ school engagement (Bang et al., 2020; Fredricks et al., 2004; Quin, 2017). The resilience literature that focuses on South African and other students who are vulnerable (e.g., challenged by socioeconomic risks or social status) reports these same resources (Malindi & Machenjedze, 2012; Motti-Stefanidi & Masten, 2013; Van Breda & Theron, 2018), also during COVID-19 (Luthar et al., 2020). Implications for school psychologists Because the entire sample was drawn from a resource-constrained municipality that faced similar stressors (Ungar et al., 2021), it is difficult to theorize what might have contributed to the higher 2018 school engagement of some girls versus the lower school engagement of others. A follow-up study would be helpful to better understand what informed higher school engagement. Still, the important implication is that there is value in supporting students (particularly female ones) to be highly school engaged. While high levels of historic school engagement appear to strengthen school engagement in the context of disrupted schooling, even moderate levels of school engagement are likely to support girl students to remain school engaged when school closures/disruptions complicate their school journey. Although this finding might be too late for students impacted by COVID-19-related school closures, there is a high likelihood of future pandemics and other disasters (e.g., climate change related) and related school closures (World Bank, 2020). In short, there is merit in actively supporting girl students to be highly school engaged with a view to their reaping protective benefits for future disruptions to their schooling. Essentially, this would mean ensuring their access to the individual, household, and school-related resources that matter for school engagement (Fredricks et al., 2004; Quin, 2017; Quin et al., 2018; Sharkey et al., 2008). In this regard, school psychologists and other school-based practitioners are key advocates. As advocates, they will need to do more than support girl students to develop the necessary individual resources that matter for school engagement. Additionally, they will need to educate teachers and families that a ‘resource mix’ is pivotal to school engagement and heighten teachers’ and families’ appreciation for their personal potential to advance students’ engagement in schooling. For instance, teachers and families could benefit from knowing that time to be invested in their studies (i.e., fewer domestic chores/care duties), warm caregiving, and teacher kindness/competence can support girls to be school engaged. Boys’ school engagement should not be neglected by school psychologists, even if the non-significant effects found for boys imply that their school engagement was apparently less vulnerable to the negative effects of schooling disruptions at low levels of past school engagement. In stressed communities, like the RYSE SA one, school engagement is key to advancing boys’ wellbeing and prospects (Malindi & Machenjedze, 2012). Boys with historic levels of lower school engagement will require support to be school engaged; boys with historic levels of higher school engagement will require support to maintain/advance those levels in the face of school closure. Given that gendered socialization is probably implicated in girls being more school engaged (Roorda et al., 2011), supporting boys’ school engagement encourages changes to how boys are traditionally socialized. School psychologists can play a key psychoeducational role in this.  The finding that school-related factors – in particular, kind teachers and schools that protect students from adverse experiences at school – were salient to the school engagement of our sample of South African students during COVID-19, reinforces the importance of supporting teachers and schools to be resilience-enabling, also in times of national/global disaster (Luthar et al., 2020). Knowing that many school staff have experienced significant professional stress during COVID-19 (Kim & Asbury, 2020; Luthar et al., 2020; Spaull & van der Berg, 2020), underscores the need to enable/sustain the resilience of these adults (Theron, 2021), especially as shocks and stressors are likely to continue even when COVID-19 abates (World Bank, 2020). In the absence of teachers who are resilient enough to continue being supportive despite shocks and stressors, how much lower would students’ school engagement levels be? Likewise, what would the impact on school engagement be if school management staff are not resilient enough to facilitate a protective school environment in stressed times, particularly given the additional demands on school management in extraordinary circumstances like pandemics (Viner et al., 2020)? Essentially, championing the school engagement of students in COVID-19/extra-stressed times requires championing the resilience of their teachers and other school staff. School psychologists and other school-based practitioners have a special duty in this regard. Limitations and future studies It is possible that the school engagement levels of students who completed the RYSE survey when schools were open (i.e., parts of June/July; after schools reopened at the end of August), might have been confounded by the fact that they could attend school in-person. For instance, there are reports that the resumption of in-person schooling was embraced by students who were eager to return to school (Gittings et al., 2021). Likewise, there were parents and teachers who were critical of schools reopening and whose concerns might have influenced students’ engagement (Grootes, 2021). Even though we anticipated differences between female and male students, the analyses found significant moderating effects of historic school engagement for girls only. Since this variable did not differentiate between sub-groups of boys, future research needs to identify variables that are specific to boy students to facilitate adequate prevention programs. In addition, we acknowledge that future studies should explore intersections between school engagement and gender diversity. To do so, survey items should include terminology that cisgender and LGBT+ students can identify with (Pillay et al., 2022). The attrition of 49% of the sample from 2018 to 2020 is not uncommon in longitudinal South African studies (Cockcroft et al., 2019). Still, given the limited sample size, future research should investigate larger samples with an equal ratio of adolescent boys and girls. Also, it was impossible for the RYSE study to survey participants at an earlier time point (closer to the start of the school closure) due to COVID-19 regulations and related moratoriums on research with human participants. Hence, the survey assessments started about 2.5 months after the first school lockdown (18 March). It remains unclear, therefore, how the identified effects play out closer to the start of school closures. Future studies need to apply a design that makes it possible to administer surveys in resource-constrained communities in highly regulated pandemic circumstances. Additionally, future studies should make use of multi-item scales to more reliably investigate resources that were indicated by only one item in the RYSE survey (e.g., teacher competence/kindness, role functioning). Finally, a significant auto-correlation of school engagement over time might be responsible for the identified effects. However, our study found contrasting effects between girl and boy students and identified a non-significant region in the model for the female sample, too. This shows that past school engagement should have an effect on future school engagement in the context of the studied risk that goes beyond mere auto-correlation by being a resilience-supporting resource. Conclusion It is probable that school closures will form part of societies’ response to future pandemics and other disasters (World Bank, 2020). Accordingly, families and school communities need be ready to protect young people against the negative effects of school closure. The current study suggests that enabling young people's school engagement is an important first step to mitigating future effects of school closures, more particularly for girls. Supplemental Material sj-docx-1-spi-10.1177_01430343221138785 - Supplemental material for Student resilience to COVID-19-related school disruptions: The value of historic school engagement Click here for additional data file. Supplemental material, sj-docx-1-spi-10.1177_01430343221138785 for Student resilience to COVID-19-related school disruptions: The value of historic school engagement by Linda Theron, Michael Ungar and Jan Höltge in School Psychology International Acknowledgements The RYSE study is funded by the Canadian Institutes of Health Research (CIHR; grant: IP2- 150708). CIHR is gratefully acknowledged but not held responsible for the results reported in this paper. J.H. position was funded by the Swiss National Science Foundation (P400PS_194538). Author biographies Dr. Michael Ungar, PhD is a Family Therapist and Professor of Social Work at Dalhousie University (Halifax, Canada) where he holds the Canada Research Chair in Child, Family and Community Resilience. With over $12M in funded research, Dr. Ungar's clinical work and research spans more than a dozen low, middle, and high-income countries, with much of that work focused on the resilience of children, families, and adult populations experiencing mental health challenges, as well as stressed communities, especially those experiencing economic and social instability. Most recently, he acts as the Nominated Principal Investigator of the ground-breaking RYSE project (2018–2022). Professor Linda Theron, D. Ed. is an HPCSA-registered Educational Psychologist. She is also a full professor in the Department of Educational Psychology, University of Pretoria, South Africa. Her clinical and research interest is in child and adolescent resilience, with a special interest in how situational and cultural context shapes the resilience of African young people. She is the Co-Principal Investigator of the RYSE project (2018–2022). Dr. Jan Höltge, PhD is a postdoctoral research fellow in the Department of Psychology, University of Hawai'i at Mānoa, Honolulu, HI, USA, and at the Resilience Research Centre, Dalhousie University, Halifax, NS, Canada. His research interest are multisystemic resilience, collective resilience, multi-ethnical and Indigenous communities, and lifespan psychology. Author's note: Jan Höltge is also affiliated at Department of Psychology, University of Hawai'i at Mānoa, Honolulu, HI, USA. The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Canadian Institutes of Health Research, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, (grant number IP2- 150708, P400PS_194538). ORCID iD: Linda Theron https://orcid.org/0000-0002-3979-5782 Supplemental material: Supplemental material for this article is available online. ==== Refs References Azevedo J. P. (2020). How could COVID-19 hinder progress with Learning Poverty? Some initial simulations. World Bank Blogs. https://blogs.worldbank.org/education/how-could-covid-19-hinder-progress-learning-poverty-some-initial-simulations Bang H. Chang M. Lee C. (2020). Racial and linguistic status differences in the effect of interscholastic sport participation on school engagement and academic performance among high school students. Psychological Reports, 123 (2 ), 452–471. https://doi-org.uplib.idm.oclc.org/10.1177/0033294118813845.30451593 Barbot B. Haeffel G. J. Macomber D. Hart L. Chapman J. Grigorenko E. L. (2012). Development and validation of the Delinquency Reduction Outcome Profile (DROP) in a sample of incarcerated juveniles: A multiconstruct/multisituational scoring approach. Psychological Assessment, 24 (4 ), 901–912. https://pubmed.ncbi.nlm.nih.gov/22545698/. 10.1037/a0028193 22545698 Beck A. T. Steer R. A. Brown G. (1996). Manual for the Beck Depression Inventory-II. Psychological Corporation. Carver D. J. Chapman C. A. Thomas V. S. Stadnyk K. J. Rockwood K. E. N. N. E. T. H. (1999). Validity and reliability of the Medical Outcomes Study Short Form-20 questionnaire as a measure of quality of life in elderly people living at home. Age and Ageing, 28 (2 ), 169–174. 10.1093/ageing/28.2.169 10350414 Clark, H., Coll-Seck, A. M., Banerjee, A., Peterson, S., Dalglish, S. L., Ameratunga, S., Balabanova, D., Bhutta, Z. A., Borrazzo, J., Cleason, M., Doherty, T., El-Jardali, F., George, A. S., Gichaga, A., Gram, L., Hipgrave, D. B., Kwamie, A., Meng, Q., Mercer, R., & Costello, A. (2020). After COVID-19, a future for the world's children? The Lancet, 396(10247), 298-300. 10.1016/S0140-6736(20)31481-1 Cockcroft K. Goldschagg P. Seabi J. (2019). Longitudinal designs: The RANCH-SA study. In Laher S. Fynn A. Kramer S. (Eds.), Transforming research methods in the social sciences: Case studies from South Africa (pp. 36–51). Wits University Press. Coker M. Folayan M. O. Michelow I. C. Oladokun R. E. Torbunde N. Sam-Agudu N. A. (2020). Things must not fall apart: The ripple effects of the COVID-19 pandemic on children in sub-Saharan Africa. Pediatric Research, 89(5), 1078–1086. 10.1038/s41390-020-01174-y de Miranda D. M. da Silva Athanasio B. de Sena Oliveira A. C. Silva A. C. S. (2020). How is COVID-19 pandemic impacting mental health of children and adolescents? International Journal of Disaster Risk Reduction, 101845. 10.1016/j.ijdrr.2020.101845 32929399 Dorn E. Hancock B. Sarakatsannis J. Viruleg E . (2020). COVID-19 and student learning in the United States: The hurt could last a lifetime. https://www.childrensinstitute.net/sites/default/files/documents/COVID-19-and-student-learning-in-the-United-States_FINAL.pdf Dvorsky M. R. Breaux R. Becker S. P. (2020). Finding ordinary magic in extraordinary times: Child and adolescent resilience during the COVID-19 pandemic. European Child & Adolescent Psychiatry, 30(11), 1–3. 10.1007/s00787-020-01583-8 Fontanesi L. Marchetti D. Mazza C. Di Giandomenico S. Roma P. Verrocchio M. C. (2020). The effect of the COVID-19 lockdown on parents: A call to adopt urgent measures. Psychological Trauma: Theory, Research, Practice, and Policy, 12(S1). S79–S81. 10.1037/tra0000672 Fouché A. Fouché F. D. Theron L. C. (2020). Child protection and resilience in the face of COVID-19 in South Africa: A rapid review of C-19 legislation. Child Abuse & Neglect. 10.1016/j.chiabu.2020.104710 Fredricks J. A. Blumenfeld P. Friedel J. Paris A. (2005). School engagement. In Moore K. A. Lippmann L. H. (Eds.), What do children need to flourish? The search institute series on developmentally attentive community and society (Vol. 3 , pp. 305–321). Springer. 10.1007/0-387-23823-9_19 Fredricks J. A. Blumenfeld P. C. Paris A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74 (1 ), 59–109. 10.3102/00346543074001059 Gittings L. Toska E. Medley S. Cluver L. Logie C. H. Ralayo N. , … & Mbithi-Dikgole J. (2021). ‘Now my life is stuck!’: Experiences of adolescents and young people during COVID-19 lockdown in South Africa. Global Public Health, 1–17. 10.1080/17441692.2021.1899262 Goemans A. van Geel M. Wilderjans T. F. van Ginkel J. R. Vedder P. (2018). Predictors of school engagement in foster children: A longitudinal study. Children and Youth Services Review, 88 , 33–43. 10.1016/j.childyouth.2018.02.029 Grootes S. (2021). As painful as it gets: The great school reopening debate. Daily Maverick. https://www.dailymaverick.co.za/article/2021-01-17-as-painful-as-it-gets-the-great-school-reopening-debate/ Habib A. (2020). More eyes on COVID-19: Perspectives from Political Science: Insights from the political management of COVID-19. South African Journal of Science, 116 (7/8 ). https://sajs.co.za/article/view/8499. 10.17159/sajs.2020/8499 Halldorsdottir T. Thorisdottir I. E. Meyers C. C. Asgeirsdottir B. B. Kristjansson A. L. Valdimarsdottir H. B. , … Sigfusdottir I. D. (2021). Adolescent well–being amid the COVID–19 pandemic: Are girls struggling more than boys? JCPP Advances, 1 (2 ), e12027. https://acamh.onlinelibrary.wiley.com/doi/pdfdirect/10.1002/jcv2.12027. 10.1002/jcv2.12027 34514467 Hayes A. F. (2018). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press. Holmes E. A. O’Connor R. C. Perry V. H. Tracey I. Wessely S. Arseneault L. Ballard C. Christensen H. Silver R. C. Everall I. Ford T. John A. Kabir T. King K. Madan I. Michie S. Przybylski A. Shafran R. Sweeny A. , … Bullmore E. (2020). Multidisciplinary research priorities for the COVID-19 pandemic: A call for action for mental health science. The Lancet Psychiatry, 7 , 547–560. 10.1016/S2215-0366(20)30168-1 32304649 IBM Corp. (2020). IBM SPSS statistics: Version 26. IBM Corp. Indrawati M. Prihadi C. Siantoro A. (2020). The COVID-19 pandemic impact on children’s education in disadvantaged and rural area across Indonesia. International Journal of Education, 8 (4 ), 19–33. 10.5121/ije.2020.8403 Johnson P. O. Fay L. C. (1950). The Johnson-Neyman technique, its theory and application. Psychometrika, 15 (4 ), 349–367. https://link.springer.com/content/pdf/10.1007/BF02288864.pdf. 10.1007/BF02288864 14797902 Kim L. E. Asbury K. (2020). ‘Like a rug had been pulled from under you’: The impact of COVID–19 on teachers in England during the first six weeks of the UK lockdown. British Journal of Educational Psychology, 90 (4 ), 1062–1083. https://bpspsychub.onlinelibrary.wiley.com/doi/pdfdirect/10.1111/bjep.12381.32975830 Lam S.-F. Jimerson S. Wong B. P. H. Kikas E. Shin H. Veiga F. H. Hatzichristou C. Polychroni F. Cefai C. Negovan V. Stanculescu E. Yang H. Liu Y. Basnett J. Duck R. Farrell P. Nelson B. Zollneritsch J. (2014). Understanding and measuring student engagement in school: The results of an international study from 12 countries. School Psychology Quarterly, 29 (2 ), 213–232. 10.1037/spq0000057 24933218 Lee J. (2020). Mental health effects of school closures during COVID-19. The Lancet Child & Adolescent Health, 4 (6 ), 421. 10.1016/S2352-4642(20)30109-7 32302537 Li Y. Lerner R. M. (2011). Trajectories of school engagement during adolescence: Implications for grades, depression, delinquency, and substance use. Developmental Psychology, 47 (1 ), 233–247. 10.1037/a0021307 21244162 Loades M. E. Chatburn E. Higson-Sweeney N. Reynolds S. Shafran R. Brigden A. , …Crawley E. (2020). Rapid systematic review: The impact of social isolation and loneliness on the mental health of children and adolescents in the context of COVID-19. Journal of the American Academy of Child & Adolescent Psychiatry, 59 (11 ), 1218–1239. 10.1016/j.jaac.2020.05.009 32504808 Long J. A. (2020). Interactions: Comprehensive, user-friendly toolkit for probing interactions. R package version 1.1.3. https://CRAN.R-project.org/package=interactions Luthar S. S. Ebbert A. M. Kumar N. M. (2020). Risk and resilience during COVID-19: A new study in the Zigler paradigm of developmental science. Development and Psychopathology, 33(2), 565–580. 10.1017/S0954579420001388 Malindi M. J. Machenjedze N. (2012). The role of school engagement in strengthening resilience among male street children. South African Journal of Psychology, 42 (1 ), 71–81. https://hdl.handle.net/10520/EJC98676. 10.1177/008124631204200108 McHorney C. A. Ware J. E. Jr. Raczek A. E. (1993). The MOS 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Medical Care, 247–263. https:// www.jstor.org/stable/3765819#metadata_info_tab_contents. 10.1097/00005650-199303000-00006 8450681 Molek K. Bellizzi S. (2022). Teenage motherhood in Africa: The epidemic in the COVID–19 pandemic. International Journal of Gynecology & Obstetrics. https://obgyn.onlinelibrary.wiley.com/doi/10.1002/ijgo.14144. Motti-Stefanidi F. Masten A. S. (2013). School success and school engagement of immigrant children and adolescents: A risk and resilience developmental perspective. European Psychologist, 18 (2 ), 126–135. 10.1027/1016-9040/a000139 Onyema E. M. Eucheria N. C. Obafemi F. A. Sen S. Atonye F. G. Sharma A. Alsayed A. O. (2020). Impact of coronavirus pandemic on education. Journal of Education and Practice, 11 (13 ), 108–121. 10.7176/jep/11-13-12 Oppong Asante K. Quarshie E. N.-B. Andoh-Arthur J. (2021). COVID-19 school closure and adolescent mental health in sub-Saharan Africa. International Journal of Social Psychiatry, 67 (7 ), 958–960. https://doi-org.uplib.idm.oclc.org/10.1177/0020764020973684.33176525 Osman A. Barrios F. X. Gutierrez P. M. Williams J. E. Bailey J. (2008). Psychometric properties of the Beck Depression Inventory–II in nonclinical adolescent samples. Journal of Clinical Psychology, 64 (1 ), 83–102. 10.1002/jclp.20433 18161034 Panagouli E. Stavridou A. Savvidi C. Kourti A. Psaltopoulou T. Sergentanis T. N. Tsitsika A. (2021). School performance among children and adolescents during COVID-19 pandemic: A systematic review. Children, 8 (12 ), 1134. https://www.mdpi.com/2227-9067/8/12/1134. 10.3390/children8121134 34943330 Pillay S. R. Ntetmen J. M. Nel J. A. (2022). Queering global health: An urgent call for LGBT+ affirmative practices. The Lancet Global Health, 10 (4 ), e574–e578. 10.1016/S2214-109X(22)00001-8 35176236 Quin D. (2017). Longitudinal and contextual associations between teacher–student relationships and student engagement: A systematic review. Review of Educational Research, 87 (2 ), 345–387. 10.3102/0034654316669434 Quin D. Heerde J. A. Toumbourou J. W. (2018). Teacher support within an ecological model of adolescent development: Predictors of school engagement. Journal of School Psychology, 69 , 1–15. 10.1016/j.jsp.2018.04.003 30558745 Rajmil L. Hjern A. Boran P. Gunnlaugsson G. de Camargo O. K. Raman S. (2021). Impact of lockdown and school closure on children’s health and wellbeing during the first wave of COVID-19: A narrative review. BMJ Paediatrics Open, 5 (1 ). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8154298/. 10.1136/bmjpo-2021-001043 R Core Team (2020). A language and environment for statistical computing. R Foundation for Statistical Computing. Resilience Research Centre (2010). The pathways to resilience research manual. http://resilienceresearch.org/ Roorda D. L. Koomen H. M. Spilt J. L. Oort F. J. (2011). The influence of affective teacher–student relationships on students’ school engagement and achievement: A meta-analytic approach. Review of Educational Research, 81 (4 ), 493–529. 10.3102/0034654311421793 Ruchkin V. Schwab-Stone M. Vermeiren R. (2004). Social and Health Assessment (SAHA): Psychometric development summary. Yale University. Sharkey J. D. You S. Schnoebelen K. (2008). Relations among school assets, individual resilience, and student engagement for youth grouped by level of family functioning. Psychology in the Schools, 45 (5 ), 402–418. 10.1002/pits.20305 Shin H. Chang Y. (2022). Relational support from teachers and peers matters: Links with different profiles of relational support and academic engagement. Journal of School Psychology, 92 , 209–226. 10.1016/j.jsp.2022.03.006 35618371 Sinatra G. M. Heddy B. C. Lombardi D. (2015). The challenges of defining and measuring student engagement in science. Educational Psychologist, 50 , 1–13. 10.1080/00461520.2014.1002924 Soudien C. Reddy V. Harvey J. (2021). The impact of COVID-19 on a fragile education system: The case of South Africa. In Reimers F. M. (Ed.), Primary and secondary education during COVID-19: Disruptions to educational opportunity during a pandemic (pp. 303–326). Springer Nature. Spaull N. van der Berg S . (2020). Counting the cost: COVID-19 school closures in South Africa and its impact on children. South African Journal of Childhood Education, 10 (1 ), 1–13. 10.4102/sajce.v10i1.924 StatsSA (2011). Statistics by place: Govan Mbeki. Accessed on 20 April 2021 from http://www.statssa.gov.za/?page_id=4286&id=11518 Stekhoven D. J. Bühlmann P. (2012). MissForest – non-parametric missing value imputation for mixed-type data. Bioinformatics (Oxford, England) , 28 (1 ), 112–118. 10.1093/bioinformatics/btr597 22039212 Theron L. C. (2021). Learning about systemic resilience from studies of student resilience. In Ungar M. (Ed.), Multisystemic resilience: Change and adaptation in contexts of adversity (pp. 232–252). Oxford University Press. Timm W. J. (2021). Covid-19 triggering surge of absenteeism in SA schools. Daily Maverick. https://www.dailymaverick.co.za/article/2021-02-24-covid-19-triggering-surge-of-absenteeism-in-sa-schools/ Ungar M. Liebenberg L. (2011). Assessing resilience across cultures using mixed methods: Construction of the child and youth resilience measure. Journal of Mixed Methods Research, 5 (2 ), 126–149. 10.1177/1558689811400607 Ungar M. Theron L. Murphy K. Jefferies P. (2021). Researching multisystemic resilience: A sample methodology. Frontiers in Psychology, 11 , 3808. https://doi/10.3389/fpsyg.2020.607994. Van Breda A. D. Theron L. C. (2018). A critical review of South African child and youth resilience studies, 2009-2017. Child and Youth Services Review, 91 , 237–247. 10.1016/j.childyouth.2018.06.022 van Bruwaene L. Mustafa F. Cloete J. Goga A. Green R. J. (2020). What are we doing to the children of South Africa under the guise of COVID-19 lockdown? SAMJ: South African Medical Journal, 110 (7 ), 1–2. https://journals.co.za/doi/10.7196/SAMJ.2020.v110i7.14932 Van Lancker W. Parolin Z. (2020). COVID-19, school closures, and child poverty: A social crisis in the making. The Lancet Public Health, 5 (5 ), e243–e244. https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(20)30084-0/fulltext. 10.1016/S2468-2667(20)30084-0 32275858 Van Rensburg A. Theron L. C. Rothmann S. (2018). Adolescent perceptions of resilience-promoting resources: The South African pathways to resilience study. South African Journal of Psychology, 48 (1 ), 73–85. 10.1177/0081246317700757 Van Rensburg A. C. Theron L. C. Ungar M. (2019). Using the CYRM-28 with South African young people: A factor structure analysis. Research on Social Work Practice , 29 (1 ), 93–102. 10.1177/1049731517710326 Viner R. M. Russell S. J. Croker H. Packer J. Ward J. Stansfield C. , … & Booy R. (2020). School closure and management practices during coronavirus outbreaks including COVID-19: A rapid systematic review. The Lancet Child & Adolescent Health, 4 (5 ), 397–404. 10.1016/S2352-4642(20)30095-X 32272089 Wang M. T. Degol J. L. Amemiya J. Parr A. Guo J. (2020). Classroom climate and children’s academic and psychological wellbeing: A systematic review and meta-analysis. Developmental Review, 57 , 100912. 10.1016/j.dr.2020.100912 Wang M. T. Eccles J. S. (2012). Social support matters: Longitudinal effects of social support on three dimensions of school engagement from middle to high school. Child Development, 83 (3 ), 877–895. 10.1111/j.1467-8624.2012.01745.x 22506836 Wang M. T. Willett J. B. Eccles J. S. (2011). The assessment of school engagement: Examining dimensionality and measurement invariance by gender and race/ethnicity. Journal of School Psychology, 49 (4 ), 465–480. 10.1016/j.jsp.2011.04.001 21724001 Ware J. E. Sherbourne C. D. Davies A. R. (1992). Developing and testing the MOS 20-item short-form health survey: A general population application. In Stewart A. L. Ware J. E. (Eds.), Measuring functioning and well-being: The Medical Outcomes Study approach (pp. 277–290). Duke University Press. Wolfson Vorster R. (2020). The challenges of hunger and education for SA’S children. Daily Maverick. https://www.dailymaverick.co.za/opinionista/2020-05-05-part-one-the-challenges-of-hunger-and-education/#gsc.tab=0 World Bank (2020). The COVID-19 pandemic: Shocks to education and policy responses. https://www.skillsforemployment.org/edmsp1/groups/skills/documents/skpcontent/cdff/mjyw/∼edisp/edmsp1_260632.pdf
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==== Front Policy Polit Nurs Pract Policy Polit Nurs Pract PPN spppn Policy, Politics & Nursing Practice 1527-1544 1552-7468 SAGE Publications Sage CA: Los Angeles, CA 36482714 10.1177/15271544221141060 10.1177_15271544221141060 Article Individual and Work-Related Characteristics Associated with COVID-19 Vaccination Status among Ohio Nurses https://orcid.org/0000-0001-7510-7441 Jun Jin PhD, RN 1 Tubbs Cooley Heather PhD, RN, FAAN 1 https://orcid.org/0000-0001-5331-3340 O’Mathúna Dónal P. PhD 1 Kim Minjin PhD, RN 2 Pignatiello Grant PhD, RN 3 Fitzpatrick Joyce J. PhD, RN, FAAN, FNAP, FAANP(H) 3 https://orcid.org/0000-0002-4217-1559 Tucker Sharon PhD, APRN-CNS, NC-BC, FNAP, FAAN 4 1 College of Nursing, 2647 the Ohio State University , Columbus, OH, USA 2 College of Nursing, 2514 University of Cincinnati , Cincinnati, OH, USA 3 Frances Payne Bolton School of Nursing, 2546 Case Western Reserve University , Cleveland, OH, USA 4 Fuld EBP Institute, College of Nursing, 2647 the Ohio State University , Columbus, OH, USA Jin Jun, College of Nursing, the Ohio State University, 1585 Neil Ave, Columbus, OH 43210-1132, USA. Email: [email protected] 8 12 2022 8 12 2022 15271544221141060© The Author(s) 2022 2022 SAGE Publications This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. Uptake of the COVID-19 vaccine by nurses lags behind that of other health care professionals with minimal empirical evidence to understand this phenomenon. In this secondary analysis, we examined nurses’ individual and work-related characteristics and their association with COVID-19 vaccination status. Alumni of three Ohio nursing colleges and members of a professional organization were invited to complete questionnaires from June through August 2021. Logistic regression models were used to evaluate associations between nurse characteristics and vaccination status. Among 844 respondents, 754 (80.30%) had received at least one dose of the vaccine. Older age, having a bachelor's degree or higher, and working in critical care were associated with vaccination. Providing direct care for COVID-19 patients in the last 7 days and a higher perception of one's work being affected by COVID-19 were significantly associated with being vaccinated, whereas prior COVID-19 infection was inversely associated with vaccination status. Our findings suggest that COVID-19 vaccine uptake among nurses is influenced by a host of factors related to virus knowledge, beliefs, and risk perceptions. Awareness of these factors can aid the development of interventions to increase nurses’ acceptance of vaccines. COVID-19 vaccine nurses edited-statecorrected-proof typesetterts19 ==== Body pmcIntroduction Since the discovery of the first COVID-19 case in December 2019, the SARS-CoV-2 virus has infected more than 91 million people and caused over one million deaths in the United States (Ritchie et al., 2022). In December 2020, a nurse in New York City became the first non-research recipient of the COVID-19 vaccine in the U.S. while the world watched with hope and anticipation for the end of the pandemic (Inskeep & Mann, 2020). Vaccines enable societies and individuals to prosper and prolong life expectancy against infectious diseases that previously killed and disabled a large portion of the population (Piot et al., 2019). However, despite the societal and individual benefits from vaccines on human health in the last century, vaccine hesitancy persists and is considered a global public health threat (WHO, 2019). Healthcare professionals, particularly nurses, are an important target group for vaccination due to their proximity to patients and critical role in preventing healthcare-acquired infections (Poland & Tucker, 2012). Healthcare professionals generally have higher vaccine uptake than the public. Yet, nurses consistently have the lowest vaccination intent and lowest vaccination rates among healthcare professionals (Lee et al., 2021; Wang et al., 2021). For example, the influenza vaccination rate among nurses during the 2018–19 influenza season was 90.2% compared to physicians at 98% (CDC, 2020). In August 2021 (when our survey was conducted), around 75–88% of nurses in the United States had received COVID-19 vaccines or were planned to receive them compared to 96% of physicians (American Medical Association [AMA], 2021; American Nurses Association [ANA], 2021). This lower uptake is concerning, as nurses for 20 years straight have been rated as one of the most trusted professions in the United States (Gallup, 2020) and have a significant formal and informal influence on the healthcare decisions of patients, families, and the public at large (Larson et al., 2014; Wiley et al., 2013). A nurse's decision to decline the COVID-19 vaccine can potentially affect the public perception of vaccine safety and the safety of patients and communities that the workforce serves (Wendelboe et al., 2015). Research on COVID-19 vaccination among healthcare professionals provides an emerging view of factors influencing hesitancy, such as concerns about vaccine effectiveness, safety, side effects, and efficacy; misinformation and lack of knowledge; and distrust of the government (Khubchandani et al., 2022; Li et al., 2021). However, little is known about factors that specifically influence nurse COVID-19 vaccination, and this impedes the development of effective interventions to address vaccine hesitancy in a high-risk, high-influence occupational group. Therefore, the purpose of this study was to examine the demographic and professional characteristics of Ohio nurses and their relationship to COVID-19 vaccination. Study Data and Methods We conducted a secondary analysis of survey data collected from a larger study of nurses’ moral injury, resilience, and wellbeing during the COVID-19 pandemic (Fitzpatrick et al., 2022). Only the items relevant to the current study are included in this analysis. Setting and Sample Data were collected for ten weeks from June to August 2021 using an electronic self-administered survey distributed through QualtricsXM software. To be eligible for the study, nurses had to be engaged in clinical practice either full-time, part-time or per diem in any practice setting in the state of Ohio. Nurses were recruited via the nursing alumni listservs from three large universities located in Ohio and the advertisement on a professional organization document. No incentives were offered. Measures The survey included questions regarding individual demographics, work characteristics, COVID-19 vaccination status, and experiences with COVID-19. Demographic characteristics Demographics included both individual (age, gender, race) and professional (years of nursing experience, nursing degree, nursing role, employment status) characteristics. Items for work characteristics included the organizational types (e.g., hospital, long-term care facility, etc.) and nursing unit type (e.g., critical care unit, emergency rooms, ambulatory offices, etc.). The geographic locations of nurses’ primary practice were assessed as urban, suburban, or rural settings. The zip codes of the nurses’ primary clinical practice were also collected and then aggregated into five regions (Northeast, Northwest, Central, Southeast, and Southwest) in Ohio, following the map used by the state of Ohio Map (State of Ohio, 2022). All regions except Southeast included large metropolitan cities (Northwest–Cleveland, Northeast–Toledo, Central–Columbus, and Southwest–Cincinnati). COVID-19 experiences We included three COVID-19 related questions assessing the participants’ own experiences. The first question asked the participants to rate how much COVID-19 affected their clinical practice on a 10-point Likert scale ranging from “not at all” as 1 to “Extremely” as 10. The second question asked if participants had provided direct care to patients with COVID-19 in the last seven days, and the third question inquired if they had ever tested positive for the COVID-19 virus. These two latter question responses were recorded as either “No” or “Yes.” COVID-19 vaccination status The outcome of interest in this study was self-reported COVID-19 vaccination status, which was coded either as 0 “unvaccinated” if they had not received any dose of vaccine or 1 “vaccinated” if they reported having received at least one dose of any available COVID-19 vaccine. Statistical Analysis Frequencies and means were calculated to describe individual and work characteristics, COVID-19 experiences, and COVID-19 vaccination status. We performed a univariate analysis of each variable used to describe the sample, including its central tendency (mean and median) and distribution (range, variance, and standard deviation). Multivariate logistic regression models were used to examine associations between nurse characteristics and COVID-19 vaccination status. To determine factors associated with vaccination status, we present results as odds ratio (OR) with 95% confidence interval (CI) and set alpha at p < .05. Assessments of multicollinearity revealed that age and years of experience were highly correlated. Therefore, only age is included in the analysis. Other variables such as direct care to patients with COVID-19 in the last 7 days and the types of nursing units were also tested for multicollinearity using Spearman correlation and found to be independent of one another. Due to the racial homogeneity of the sample (majority white with few respondents from additional racial and ethnic backgrounds), we dichotomized race to white and non-white. Statistical analysis was performed using STATA 16.1 (StataCorp. 2019. Stata Statistical Software: Release 16. College Station, TX: StataCorp LLC.). Ethical Considerations Participation in the study was voluntary. Informed consent was obtained online when the invited nurse clicked on the “I agree” button to proceed with the survey. To preserve anonymity, the IP addresses of the computers used for the survey were not tracked, and the participants’ specific information on work settings, such as the name of their employers, were not collected. This study was reviewed and approved by the Institutional Review Board of Case Western Reserve University. Results There were 1,857 initial responses. After deleting cases with some missing responses, complete data from 844 respondents comprised the analytic sample. We were unable to calculate an overall response rate as the duplicate number of nurses who were on both listservs could not be obtained from the listserv owners. Additionally, the total number of nurses meeting the eligibility criteria was unavailable. Sample Characteristics Table 1 summarizes the individual and work characteristics of the participants, with some comparative data for all Ohio nurses. Most respondents self-identified as white (90.4%) and female (92.2%), with a median age of 44 years and a median of 12 years of nursing experience. Respondents most frequently reported holding a bachelor's degree in nursing (48.7%), followed by an associate degree or diploma (31.6%). Most respondents held a full-time permanent position (77.0%), while about 5% were in contract or travel positions. For the work characteristics, almost half of the nurses (48.9%) practiced in urban areas and most commonly worked in hospitals (62.2%). Nurses worked in various types of nursing units, including stepdown/med/surg units (22.5%), critical care (17.7%), emergency rooms/ambulatory offices (18.7%), or rehab/long-term care (15.3%). Approximately 81% of respondents (n = 680) had received at least one dose of the vaccine at the time of the survey. Table 1. Participant Characteristics (N = 844). Variables n (%) Ohio nurse demographics (%)a Sex  Male 59 (6.99) 9  Female 778 (92.18) 91  Others 7 (0.83) N/A Race  White 763 (90.40) 88.7  Black/African American 35 (4.15) 6.6  Asian 13 (1.54) 0.3  Hispanic/Latino(a) 10 (1.18) 1.3  Others 21 (2.49) 2.9 Age, mean years (SD) 45.5 (12.48) 49 Nursing experience, mean years (S.D.)* 15.86 (12.20) N/A Nursing degree  Associate/diploma 267 (31.64) 54  BSN 411 (48.70) 37  Masters/Doctorate 166 (19.67) 2 Roles  Staff nurses (including charge nurses) 567 (67.18)  Advanced practice nurses (NPs, CNSs) 51 (6.04)  Nurse administrators (NMs, Director) 89 (10.55)  Research/education 47 (5.57)  Others 90 (10.66) Job status  Full-time permanent 650 (77.01) 86  Part-time permanent 145 (17.18) 14  Contract/traveler 49 (5.81) N/A Practice location  Urban 404 (48.87)  Suburban 296 (35.07)  Rural 144 (17.06) Ohio region  Northwest (Toledo and surrounding areas) 117 (13.86)  Northeast (Cleveland and surrounding areas) 255 (30.21)  Southwest (Cincinnati and surrounding areas) 234 (27.73)  Southeast (No major cities) 56 (6.64)  Central (Columbus and surrounding areas) 182 (21.56) Types of facilities  Hospitals 525 (62.20)  LTC 109 (12.91)  Others (school, ambulatory care, etc) 210 (24.88) Unit types  Critical Care 149 (17.65)  In-patient units (med/surg, stepdown) 190 (22.51)  Emergency rooms/Ambulatory 158 (18.72)  Rehab/long-term care 129 (15.28)  Others 218 (25.83) Provided direct care to pts with COVID-19 in the last 7 days  Yes 172 (20.38)  No 672 (79.62) Tested positive for COVID-19  Yes 193 (22.87)  No 651 (77.13) Extent to which the COVID-19 pandemic affected practice Mean (SD) 7.88 (2.31) Note. *nursing experience was removed for the full model analysis due to the multicollinearity with age (r = .78). a Demographics of nurses in Ohio for comparison. Ohio Boards of Nursing. R.N. Workforce 2019. Retrieved from https://nursing.ohio.gov/wp-content/uploads/2020/02/RN-Workforce-2019-Final.pdf. COVID-19 Experiences Approximately one in four nurse respondents (22.9%) reported they had previously tested positive for COVID-19, and one in five nurses (20.4%) cared for patients with COVID-19 in the seven days prior to completing the survey. Nurses indicated that the COVID-19 pandemic greatly affected their clinical practices, with a mean score of 7.88 (SD 2.31) out of 10. Characteristics Associated with COVID-19 Vaccination status Several individual and work characteristics were significantly associated with vaccination status in the fully adjusted model (Table 2). For individual characteristics, each additional year of age was associated with a 4% increase in odds of being vaccinated (OR 1.04, 95% CI 1.02- 1.05). Further, compared to nurses with an associate degree or diploma, respondents with a bachelor's degree had twice the odds of being vaccinated (OR 2.14, 95% CI 1.39–3.28), and those with a master's or doctorate degree were 97% more likely to be vaccinated (OR 1.97, 95% CI 1.14–3.48) at the time of the survey. There were no significant differences in vaccination status according to respondent sex or race. Table 2. Characteristics Associated with Vaccine Uptake (N = 844). Variables Reference group Odds ratio 95% CI LL, UL Sex Male  Female .76 .35, 1.66  Other 1.05 .16, 6.96 Race White  Non-white .72 .40, 1.27 Age 1.04*** 1.02, 1.05 Nursing degree Associate/ diploma  BSN 2.14** 1.39, 3.28  Masters/doctorate 1.97* 1.14, 3.48 Position/role Non-staff  Staff 1.05 .69, 1.61 Practice location Urban  Suburban .73 .48, 1.12  Rural .87 .49, 1.54 Facilities Hospitals  Outpatient/homecare/specialty .81 .45, 1.43  Long-term care 1.25 .48, 3.27  Others .80 .41, 1.56 Unit types Stepdown/ med/surg  Critical care 2.32** 1.22, 4.42  Emergency room/ambulatory 1.67 .91, 3.10  Rehab/long-term care .97 .39, 2.42  Others 1.67 .96, 2.92 Work status Full-time permanent  Part-time permanent .73 .45, 1.22  Traveler/agency .56 .28, 1.18 Ohio region Northwest  Northeast 1.20 .65, 2.23  Southwest .84 .46, 1.52  Southeast .93 .40, 2.15  Central 1.31 .68, 2.53 Providing direct care to patients with COVID-19 in the last 7 days  Yes No 1.95* 1.12, 3.39 Tested positive to COVID  Yes No .58* .39, .89 How much COVID-19 affected practice 1.13** 1.05, 1.23 Note. adjusted R square = 0.11; *p < .05, **p < .01, ***p < .001. Participants working in critical care units had significantly greater odds of being vaccinated (OR 2.33, 95% CI 1.22–4.42) compared to those working in stepdown/med/surg units. Other work characteristics such as nursing role, job status, or geographic location were not associated with vaccination status. Nurses who reported providing direct care to COVID-19 patients in the last seven days were almost twice as likely to have received a COVID-19 vaccine (OR 1.95, 95% CI 1.12–3.39). Lastly, for each point increase in nurses’ perception that COVID-19 affected their clinical practice, the odds of nurses being vaccinated increased 13% (OR 1.13; 95% CI 1.05–1.23). Respondents who reported previously testing positive for COVID-19 were 40% less likely to be vaccinated at the time of the survey (OR 0.59, 95% CI 0.39–0.89). Discussion The COVID-19 vaccination rate among Ohio nurses in this study (80.56%) was similar to the U.S. national vaccination rates of nurses in other studies (Lee et al., 2021; Moniz et al., 2021). An American Nurses Association survey conducted in July 2021 revealed that 83% of nurses in Ohio had already received or planned to receive the COVID-19 vaccine. The data for our study were collected between June and August 2021, when almost all nurses (and healthcare workers) were eligible for the vaccine. However, organizational or government mandates were not in place until later, with the U.S. federal emergency mandate issued in November 2021 (CMS, 2021). Therefore, our findings highlight that most nurses chose to be vaccinated voluntarily. Nevertheless, we identified several demographic and work-related characteristics associated with COVID-19 vaccination status in this sample of Ohio nurses, including older age, higher levels of formal nursing education, working in a critical care setting, a recent experience providing direct patient care for COVID-19 patients, and a perception that the pandemic had significantly affected their clinical practice. We also found a significant negative association between prior reported COVID-19 infection and vaccination status. Our finding that age, education, and the type of nursing unit were associated with nurses’ vaccination status is consistent with results from other studies (Dubov et al., 2021; Fakonti et al., 2021; Paris et al., 2021; Wang et al., 2020). Of these characteristics, age was the only non-modifiable characteristic. In general, older adults are at a greater risk for negative consequences of the SARS-CoV-2 virus. Age has been consistently associated with one's vaccine uptake across the general public and healthcare professionals alike (Alshurman et al., 2021; Dubov et al., 2021; Fakonti et al., 2021). This trend may be due, in part, to public health messaging and policies prioritizing older individuals with earlier vaccine eligibility and outreach, thus increasing their awareness and self-perception of heightened risk compared to younger individuals. The other individual characteristics—education and type of nursing unit—are modifiable factors associated with nurses’ vaccination status. Education has been consistently associated with vaccination preference and status among the general public (Joshi et al., 2021), and nurses (Kwok et al., 2021; Li et al., 2021). In our study, those with bachelor's or more advanced degrees in nursing were more likely to be vaccinated compared to those with an associate degree or diploma. We could not locate another study that examined differences in vaccination rates among nurses by types of nursing degrees. However, evidence linking educational preparedness and patient care quality and safety is increasing (Liao et al., 2016), pointing to the educational gap between different entry degrees in nursing (Djukic et al., 2015). The variation in vaccination rates by education in nursing may be due to differences in the depth of the coursework offered at bachelor's or more advanced degree programs compared to associate degree or diploma programs. Nonetheless, the inadequate inclusion of immunization policies and infectious disease exposure in nursing education was identified as early as three decades ago (Goetz et al., 1992), highlighting the need to revisit today's nursing curriculum in associate degree and baccalaureate nursing programs to ensure adequate educational preparedness of nurses. It is also possible that education and unit type indirectly influence vaccination status; these characteristics may be proxy indicators for one's knowledge and perceptions of the virus and/or vaccines. Existing literature demonstrates that strong predictors for COVID-19 vaccine choice were the perception of disease severity, self-perceived risks, knowledge about the virus, and information about the vaccine (Biswas et al., 2021; Dini et al., 2018; Dubov et al., 2021). For example, in a survey of nursing students and COVID-19 vaccination status, those rated higher on their perceived knowledge of the virus and the vaccines were more likely to be vaccinated (Patelarou et al., 2021). In our study, nurses were more likely to be vaccinated when they had provided direct care to patients with COVID-19 in the previous 7 days and/or perceived COVID-19 as having a great influence on their practice. Critical care units are where seriously ill patients receive more intensive monitoring and advanced life support. Therefore, nurses working in critical care units witness more long-term negative consequences of COVID-19, including deaths. These first-hand experiences are most likely associated with their perceived risks, thus contributing to the higher vaccination rate. The findings of our study and the previous literature are aligned with the Health Belief Model, a theoretical model used to guide health promotion and disease prevention programs (Champion & Skinner, 2008). According to the Health Belief Model, one's desire to avoid illness and the belief that a certain specific health-related action will prevent illness are the two foundational components of one's health-related behaviors (Champion & Skinner, 2008). Thus, the ultimate course of action often depends on one's perceptions of the threats of illness and the benefits of and barriers to health behaviors, while socioeconomic and demographic factors modify these perceptions (Champion & Skinner, 2008). Interestingly, prior COVID-19 infection was inversely associated with vaccination status. This relationship could be a result of policies requiring a waiting period after infection before becoming eligible for the vaccine. Alternately, nurses with prior infection may hold a belief that natural immunity to the virus reduces or eliminates the need for a vaccine and/or that infection carries fewer individual risks than vaccination. Subjective perception of risk involves complex nuances of individual risk toleration, beliefs, experiences, and health behavior (Joshi et al., 2021; Rhudy et al., 2010). Therefore, the dichotomous grouping of “anti” or “pro” vaccine may not be adequate or accurate in capturing nurses’ perception and/or knowledge of the COVID-19 vaccine. In a recent study of healthcare professionals and their vaccination intention (Dubov et al., 2021), unvaccinated healthcare professionals were categorized into one of four groups: misinformed, undecided, uninformed, or unconcerned. Of these, all except the misinformed group indicated that they were open to changing their decision on vaccination if given relevant information and guidance (Dubov et al., 2021). Our findings hold important implications for organizations, education, research and public policy. Even before the COVID-19 pandemic, vaccine mandates for nurses were a challenging topic even as contagious viral respiratory infections like influenza impose significant healthcare and socioeconomic burdens worldwide (Dini et al., 2018; Josephson et al., 2021). The Advisory Committee on Immunization Practices has recommended influenza vaccinations for healthcare workers to protect patients and reduce staff illness and absenteeism since 1984 (CDC, 1997). Yet no consensus has been achieved, and instead, the discourse on this topic has increased. A meta-review of systematic reviews investigating interventions for improving vaccine uptake among healthcare workers found that implementing mandatory condition of service policies resulted in sustained vaccination rates up to 95%, with a small number of requests for medical and religious exemptions, terminations and voluntary resignations (Dini et al., 2018). However, the COVID-19 vaccine mandate for work is not simple and requires ongoing discussions centered on professional, ethical, and legal responsibilities to protect the public while respecting the individual nurse's rights and choice (Dumyati et al., 2021). Strategies for improving vaccine uptake constitute changes in behavior and social-professional norms, which require time and deliberate efforts underpinned by rigorous scientific evidence. Previous studies showed that perceived self-risk and desire for self-protection and protection of family and friends were the main determinants for vaccine uptake rather than absolute disease risk or protection for patients (Rhudy et al., 2010; Vasilevska et al., 2014). These discussions have been challenging as the COVID-19 vaccine became politicized in the United States. For example, areas with a higher percentage of Republican voters had lower vaccination rates and higher COVID-19 cases and deaths per 100,000 residents (Kates et al., 2021). Thus, overcoming political division and rebuilding trust in science and each other through safe and open dialogue with those unvaccinated without shaming must be incorporated in building combined strategies of mandatory vaccine policies, educational materials and training sessions, improved access to the vaccine, organized efforts to raise awareness, and/or the use of advocacy (Corace et al., 2016; Rashid et al., 2016). Our study also has several implications for research. Most health systems and professional organizations strongly encouraged vaccination even before federal or state mandates were in place. Nonetheless, many voiced increased concerns that the mandate would exacerbate the already severe nursing shortage due to nurses exiting their jobs and/or profession (Lopez et al., 2021). Since then, short-term employment trends have shown that some healthcare systems retained their nurses (Muoio, 2022) while others, such as skilled nursing facilities, experienced worsening of nursing staff shortage (Ochieng et al., 2022). The changes in nursing retention may not be related to the vaccine mandate, as our findings showed that the vast majority of nurses chose to be vaccinated without a mandate. However, continuing research is needed to the long-term effects of the vaccine mandate, if any, on the economic (e.g., nursing workforce recruitment and retention) and psychological (e.g., burnout) impacts. Limitations Our study has limitations. First, the cross-sectional nature of the data only provides a snapshot of respondents’ COVID-19 vaccination status at one point in time. The data were collected when a waiting period was required for those who tested positive for COVID-19. Thus, the interpretation of COVID-19 vaccination status warrants caution as the number of vaccinated personnel have increased since the collection of our data. Additionally, the cross-sectional nature of our study may not capture the changing dynamics of COVID-19 vaccine development and implementation. The data were collected from one state with slower COVID-19 vaccine uptake at around 55% compared to the national average of 61.1% (Ritchie et al., 2022), and we are unable to calculate a survey response rate due to listserv limitations. Thus, our findings may not be generalizable. Nurses affiliated with a state nursing organization and alumni of nursing schools in Ohio were invited, and their participation in the survey was voluntary, making it subject to selection bias. Those who were not active in state associations and/or their school alumni groups may have been omitted in the study. Lastly, we may have omitted other potentially impactful characteristics from our study, such as psychological attributes including confidence, complacency, and collective responsibility (Leung et al., 2022), knowledge of or attitudes towards the COVID-19 vaccine (Barry et al., 2021), or the degree of trust in government (Patelarou et al., 2021). We also did not collect data on socioeconomic background, which could confound a relationship between educational degree and vaccination status. Nonetheless, our findings indicate several characteristics that can identify sub-groups of nurses at risk for low vaccine uptake and potential areas of intervention to increase vaccination rates among nurses. Conclusion The lessons learned from vaccination during past epidemics and the current COVID-19 pandemic have taught us that vaccine uptake among nurses is a multi-factorial, complex phenomenon. The majority of nurses in our study had already received at least one dose of a COVID-19 vaccine before any COVID-19 vaccine mandate was introduced. Age, education, and the type of nursing unit were also found to be associated with nurses’ vaccination status, whereas prior COVID-19 infection was inversely associated with the vaccine status. Balancing nurses’ individual rights to bodily autonomy with professional responsibilities to protect patients is a dynamic process that requires ongoing dialog and the development of evidence-informed policies. Improving vaccine uptake requires time and deliberate efforts in behavior and social-professional norms changes. In particular, nursing education as a modifiable characteristic associated with nurses’ voluntary COVID-19 vaccination decision highlights an opportunity for further examination and potential intervention in entry-level nursing curricula to address vaccine hesitancy in the profession. Author Biographies Jin Jun is an assistant professor at the Ohio State University College of Nursing whose program of research focuses on the health and well-being of healthcare workforce. Heather Tubbs Cooley, PhD, RN, FAAN, is an associate professor at the Ohio State University College of Nursing. Her research focuses on understanding factors that both impede and enhance the quality and reliable delivery of core nursing care in neonatal and pediatric care settings. Dónal P. O'Mathúna, BSc (Pharm), MA, PhD is an associate professor at the Ohio State University College of Nursing. His research focuses on disasters, pandemics and humanitarian crises, in particular examining ethical issues in disaster research. Minjin Kim, PhD, RN is an assistant professor in the College of Nursing at the University of Cincinnati. She is a transcultural nurse implementation scientist devoted to addressing health disparities, health equity, and health justice using digital narrative/storytelling and artificial intelligence technology. Grant Pignatiello, PhD, RN is an instructor at Case Western Reserve University Frances Payne Bolton School of Nursing and a Clinical Research KL2 Scholar at the Clinical and Translational Science Collaborative. His research focuses on judgment & family decision-making process of the critically ill population in acute care settings. Joyce J. Fitzpatrick, PhD, MBA, RN, FAAN is Director at Marian K. Shaughnessy Nurse Leadership Academy, Elizabeth Brooks Ford professor of Nursing and Distinguished University Professor at Case Western Reserve University Frances Payne Bolton School of Nursing. She is a nurse educator and advocate for nursing, geriatrics, psychological care, and nursing theory. Sharon Tucker, PhD, APRN-CNS, NC-BC, FNAP, FAAN is Grayce Sills Endowed Professor in Psychiatric-Mental Health Nursing, Associate Dean for Health Promotion and Well-being, Director of the Center for Well-being and Prevention, and Director, Translational/Implementation Research Core, Helene Fuld Health Trust National Institute for EBP. Her research focuses on behavioral strategies to promote mental and physical health and wellness, prevent disease, and reduce stress and risks among working populations and their families. The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: GP is funded by the National Center for the Advancing Translational Sciences, grant number: KL2TR002547. ORCID iDs: Jin Jun https://orcid.org/0000-0001-7510-7441 Sharon Tucker https://orcid.org/0000-0002-4217-1559 Dónal P. O’Mathúna PhDhttps://orcid.org/0000-0001-5331-3340 ==== Refs References Alshurman B. A. Khan A. F. Mac C. Majeed M. Butt Z. A. (2021). What demographic, social, and contextual factors influence the intention to use COVID-19 vaccines: A scoping review. International Journal of Environmental Research and Public Health, 18 (17 ). 10.3390/ijerph18179342 American Medical Association (AMA) (2021). AMA survey shows over 96% of doctors fully vaccinated against COVID-19. https://www.ama-assn.org/press-center/press-releases/ama-survey-shows-over-96-doctors-fully-vaccinated-against-covid-19 American Nurses Association (ANA) (2021). COVID-19 Vaccine Facts Survey for Nurses. https://covidvaccinefacts4nurses.org/covid-19-survey Barry M. Temsah M. H. Alhuzaimi A. Alamro N. Al-Eyadhy A. Aljamaan F. Saddik B. Alhaboob A. Alsohime F. Alhasan K. Alrabiaah A. Alaraj A. Halwani R. Jamal A. Alsubaie S. Al-Shahrani F. S. Memish Z. A. Al-Tawfiq J. A. (2021). COVID-19 vaccine confidence and hesitancy among health care workers: A cross-sectional survey from a MERS-CoV experienced nation. PLOS ONE, 16 (11 ), e0244415. 10.1371/JOURNAL.PONE.0244415 34843462 Biswas N. Mustapha T. Khubchandani J. Price J. H. (2021). The nature and extent of COVID-19 vaccination hesitancy in healthcare workers. Journal of Community Health, 46 (6 ), 1244–1251. 10.1007/S10900-021-00984-3 33877534 Centers for Disease Control and Prevention (1997). Recommendations and Reports. https://www.cdc.gov/mmwr/preview/mmwrhtml/00050577.htm Centers for Disease Control and Prevention (2020). Influenza Vaccination Coverage Among Health Care Personnel—United States, 2019–20 Influenza Season. https://www.cdc.gov/flu/fluvaxview/hcp-coverage_1920estimates.htm Centers for Medicare & Medicaid Services. (2020). Current Emergencies. Retrieved from https://www.cms.gov/About-CMS/Agency-Information/Emergency/EPRO/Current-Emergencies/Current-Emergencies-page Champion V. Skinner C. (2008). The health belief model. In Glanz K. Rimer B. Viswanath K. (Eds.), Health behavior and health education (pp. 45–65). Jossey-Bass. Corace K. M. Srigley J. A. Hargadon D. P. Yu D. MacDonald T. K. Fabrigar L. R. Garber G. E. (2016). Using behavior change frameworks to improve healthcare worker influenza vaccination rates: A systematic review. Vaccine, 34 (28 ), 3235–3242. 10.1016/J.VACCINE.2016.04.071 27155491 Dini G. Toletone A. Sticchi L. Orsi A. Bragazzi N. L. Durando P. (2018). Influenza vaccination in healthcare workers: A comprehensive critical appraisal of the literature. Human Vaccines & Immunotherapeutics, 14 (3 ), 772. 10.1080/21645515.2017.1348442 28787234 Djukic M. Kovner C. T. C. T. Brewer C. S. C. S. Fatehi F. Jun J. (2015). Educational gaps and solutions for early-career nurse managers’ education and participation in quality improvement. Journal of Nursing Administration, 45 (4 ), 206–211. 10.1097/NNA.0000000000000186 25803802 Dubov A. Distelberg B. J. Abdul-Mutakabbir J. C. Beeson W. L. Loo L. K. Montgomery S. B. Oyoyo U. E. Patel P. Peteet B. Shoptaw S. Tavakoli S. Chrissian A. A. (2021). Predictors of COVID-19 vaccine acceptance and hesitancy among healthcare workers in Southern California: Not just “Anti” vs. “Pro” vaccine. Vaccines, 9 (12 ). 10.3390/VACCINES9121428 Dumyati G. Jump R. L. P. Gaur S. (2021). Mandating COVID-19 vaccine for nursing home staff: An ethical obligation. Journal of the American Medical Directors Association, 22 (10 ), 1967–1968. 10.1016/J.JAMDA.2021.08.017 34487686 Fakonti G. Kyprianidou M. Toumbis G. Giannakou K. (2021). Attitudes and acceptance of COVID-19 vaccination among nurses and midwives in Cyprus: A cross-sectional survey. Frontiers in Public Health, 9 , 481. 10.3389/FPUBH.2021.656138/BIBTEX Fitzpatrick J. J. Pignatiello G. Kim M. Jun J. O’Mathuna D. Duah H. Taibl J. Tucker S. (2022). Moral injury, nurse well being, and resilience among nurses practicing during the COVID-19 pandemic. The Journal of nursing administration, 52 (7-8), 392–398. 10.1097/NNA.0000000000001171 Gallup (2020). Honesty/Ethics in Profession. https://news.gallup.com/poll/1654/Honesty-Ethics-Professions.aspx Goetz A. Yu C. M. Muder R. R. (1992). Microbiology, infection control, immunizations, and infectious disease exposure: Education and practices in United States nursing schools. American Journal of Infection Control, 20 (3 ), 115–121. 10.1016/S0196-6553(05)80175-0 1386200 Inskeep S. Mann B. (2020). NYC Nurse Is Among The 1st To Get COVID-19 Vaccine In The U.S. National Public Radio. https://www.npr.org/2020/12/14/946253331/new-york-city-nurse-among-the-first-to-get-coronavirus-vaccine-in-the-u-s Josephson A. Kilic T. Michler J. D. (2021). Socioeconomic impacts of COVID-19 in low-income countries. Nature Human Behaviour, 5 (5 ), 557–565. 10.1038/s41562-021-01096-7 Joshi A. Kaur M. Kaur R. Grover A. Nash D. El-Mohandes A. (2021). Predictors of COVID-19 vaccine acceptance, intention, and hesitancy: A scoping review. Frontiers in Public Health, 9 , 1152. 10.3389/FPUBH.2021.698111/BIBTEX Kates J. Tolbert J. Orgera K. (2021). Kaiser Family Foundation Policy Report. The Red/Blue Divide in COVID-19 Vaccination Rates. https://www.kff.org/policy-watch/the-red-blue-divide-in-covid-19-vaccination-rates/ Khubchandani J. Bustos E. Chowdhury S. Biswas N. Keller T. (2022). COVID-19 vaccine refusal among nurses worldwide: Review of trends and predictors. Vaccines, 10 (2 ). 10.3390/VACCINES10020230 Kwok K. O. Li K. K. Wei W. I. Tang A. Wong S. Y. S. Lee S. S. (2021). Influenza vaccine uptake, COVID-19 vaccination intention and vaccine hesitancy among nurses: A survey. International Journal of Nursing Studies, 114 , 103854. 10.1016/j.ijnurstu.2020.103854 33326864 Larson H. J. Jarrett C. Eckersberger E. Smith D. M. D. Paterson P. (2014). Understanding vaccine hesitancy around vaccines and vaccination from a global perspective: A systematic review of published literature, 2007–2012. Vaccine, 32 (19 ), 2150–2159. 10.1016/j.vaccine.2014.01.081 24598724 Lee J. T. Althomsons S. P. Wu H. Budnitz D. S. Kalayil E. J. Lindley M. C. Pingali C. Bridges C. B. Geller A. I. Fiebelkorn A. P. Graitcer S. B. Singleton J. A. Patel S. A. (2021). Disparities in COVID-19 vaccination coverage among health care personnel working in long-term care facilities, by job category, national healthcare safety network—United States, March 2021. MMWR Recommendations and Reports, 70 (30 ), 1036–1039. 10.15585/mmwr.mm7030a2 Leung C. L. K. Li K. K. Wei V. W. I. Tang A. Wong S. Y. S. Lee S. S. Kwok K. O. (2022). Profiling vaccine believers and skeptics in nurses: A latent profile analysis. International Journal of Nursing Studies, 126 , 104142. 10.1016/J.IJNURSTU.2021.104142 34923316 Li M. Luo Y. Watson R. Zheng Y. Ren J. Tang J. Chen Y. (2021). Healthcare workers’ (HCWs) attitudes and related factors towards COVID-19 vaccination: A rapid systematic review. Postgraduate Medical Journal. 10.1136/POSTGRADMEDJ-2021-140195 Liao L. M. Sun X. Y. Yu H. Li J. W. (2016). The association of nurse educational preparation and patient outcomes: Systematic review and meta-analysis. Nurse Education Today, 42 , 9–16. 10.1016/J.NEDT.2016.03.029 27237346 Lopez V. Anderson J. West S. Cleary M. (2021). Does the COVID-19 pandemic further impact nursing shortages? 43 (3 ), 293–295. 10.1080/01612840.2021.1977875 Moniz M. H. Townsel C. Wagner A. L. Zikmund-Fisher B. J. Hawley S. Jiang C. Stout M. J. (2021). COVID-19 vaccine acceptance among healthcare workers in a United States Medical Center. MedRxiv, 2021.04.29.21256186. 10.1101/2021.04.29.21256186 Muoio D. (2022). How many employees have hospitals lost to vaccine mandates? Here are the numbers so far. https://www.fiercehealthcare.com/hospitals/how-many-employees-have-hospitals-lost-to-vaccine-mandates-numbers-so-far Ochieng N. Chidambaram P. Musumeci M. B. (2022). Kaiser Family Foundation Policy Report. Nursing Facility Staffing Shortages during the COVID-19 Pandemic. https://www.kff.org/coronavirus-covid-19/issue-brief/nursing-facility-staffing-shortages-during-the-covid-19-pandemic/ Paris C. Bénézit F. Geslin M. Polard E. Baldeyrou M. Turmel V. Tadié É Garlantezec R. Tattevin P. (2021). COVID-19 vaccine hesitancy among healthcare workers. Infectious Diseases Now, 51 (5 ), 484–487. 10.1016/J.IDNOW.2021.04.001 33964486 Patelarou A. Saliaj A. Galanis P. Pulomenaj V. Prifti V. Sopjani I. Mechili E. A. Laredo-Aguilera J. A. Kicaj E. Kalokairinou A. Cobo-Cuenca A. I. Celaj J. Carmona-Torres J. M. Bucaj J. Asimakopoulou E. Argyriadi A. Argyriadis A. Patelarou E. (2020). Predictors of nurses' intention to accept COVID-19 vaccination: A cross-sectional study in five European countries. Journal of clinical nursing, 31 (9-10 ), 1258–1266. 10.1111/jocn.15980 Piot P. Larson H. J. O’Brien K. L. N’kengasong J. Ng E. Sow S. Kampmann B. (2019). Immunization: Vital progress, unfinished agenda. Nature, 575 (7781 ), 119–129. 10.1038/s41586-019-1656-7 31695203 Poland G. A. Tucker S. (2012). The nursing profession and patient safety and healthcare provider influenza immunization: The puzzling stance of the American Nursing Association. Vaccine, 30 (10 ), 1753–1755. 10.1016/J.VACCINE.2012.01.077 22365104 Rashid H. Yin J. K. Ward K. King C. Seale H. Booy R. (2016). Assessing interventions to improve influenza vaccine uptake among health care workers. Health Affairs (Project Hope), 35 (2 ), 284–292. 10.1377/HLTHAFF.2015.1087 26858382 Rhudy L. M. Tucker S. J. Ofstead C. L. Poland G. A. (2010). Personal choice or evidence-based nursing intervention: Nurses’ decision-making about influenza vaccination. Worldviews on Evidence-Based Nursing, 7 (2 ), 111–120. 10.1111/J.1741-6787.2010.00190.X 20367806 Ritchie H. Mathieu E. Rodés-Guirao L. Apel C. Giattino C. Ortiz-Ospina E. Macdonald B. Beltekian D. Roser M. (2022). Coronavirus Pandemic (COVID-19). https://ourworldindata.org/coronavirus State of Ohio (2022). Ohio Regions. https://ohio.org/home/regions Vasilevska M. Ku J. Fisman D. N. (2014). Factors associated with healthcare worker acceptance of vaccination: A systematic review and meta-analysis. Infection Control & Hospital Epidemiology, 35 (6 ), 699–708. 10.1086/676427 24799647 Wang C. Wang Y. Han B. Zhao T. S. Liu B. Liu H. Chen L. Xie M. Zheng H. Zhang S. Zeng J. Huang N. H. Du J. Liu Y. Lu Q. B. Cui F. (2021). Willingness and SARS-CoV-2 vaccination coverage among healthcare workers in China: A nationwide study. Vaccines, 9 (9 ). 10.3390/VACCINES9090993/S1 Wang K. Wong E. L. Y. Ho K. F. Cheung A. W. L. Chan E. Y. Y. Yeoh E. K. Wong S. Y. S. (2020). Intention of nurses to accept coronavirus disease 2019 vaccination and change of intention to accept seasonal influenza vaccination during the coronavirus disease 2019 pandemic: A cross-sectional survey. Vaccine, 38 (45 ), 7049–7056. 10.1016/j.vaccine.2020.09.021 32980199 Wendelboe A. M. Grafe C. McCumber M. Anderson M. P. (2015). Inducing Herd immunity against seasonal influenza in long-term care facilities through employee vaccination coverage: A transmission dynamics model. Computational and Mathematical Methods in Medicine, 2015 . 10.1155/2015/178247 Wiley K. E. Massey P. D. Cooper S. C. Wood N. Quinn H. E. Leask J. (2013). Pregnant women’s intention to take up a post-partum pertussis vaccine, and their willingness to take up the vaccine while pregnant: A cross sectional survey. Vaccine, 31 (37 ), 3972–3978. 10.1016/J.VACCINE.2013.06.015 23777954 World Health Organization (2019). Ten threats to global health in 2019. https://www.who.int/news-room/spotlight/ten-threats-to-global-health-in-2019
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==== Front Crime Delinq Crime Delinq CAD spcad Crime and Delinquency 0011-1287 1552-387X SAGE Publications Sage CA: Los Angeles, CA 10.1177/00111287221130961 10.1177_00111287221130961 Original Research Article Violations of Emergent Norms Regarding COVID-19 Mitigation and Social Hygiene: An Application of Agnew’s General Theory of Crime Kabiri Saeed 1 https://orcid.org/0000-0002-1969-9419 Sharepour Mahmoud 1 Howell C. Jordan 2 Wellen Hadley 3 Smith Hayden P. 3 https://orcid.org/0000-0001-5227-1564 Cochran John K. 2 Shadmanfaat Seyyedeh Masoomeh (Shamila) 4 Andersen Tia Stevens 3 1 University of Mazandaran, Babolsar, Islamic Republic of Iran 2 University of South Florida, Tampa, FL, USA 3 University of South Carolina System, Columbia, SC, USA 4 University of Guilan, Rasht, Islamic Republic of Iran John K. Cochran, University of South Florida, 4202 E. Fowler Ave., SOC107, Tampa, FL 33620, USA. Email: [email protected] * Saeed Kabiri is now affiliated to Tehran University Jihad, Tehran, Islamic Republic of Iran. 8 12 2022 8 12 2022 00111287221130961© The Author(s) 2022 2022 SAGE Publications This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. This study examines self-reported violations of emergent norms and regulations regarding COVID-19 mitigation and social hygiene practices among a sample of high school students randomly selected from public schools in Rasht, Iran. The study seeks to explain these COVID-19 ordinance violations through the application of Agnew’s general integrated theory of crime. Findings demonstrate that life domains, motivations, and constraints have a direct effect on COVID-19 misbehavior. Moreover, life domains have an indirect effect on COVID-19 misbehavior through both constraints and motivations. Finally, the relationship between motivations and COVID-19 misbehavior is moderated by the peers domain, whereas the relationship between constraints and COVID-19 misbehavior is moderated by the family domain and school domain. COVID-19 social hygiene violations constraints motivations life domains edited-statecorrected-proof typesetterts1 ==== Body pmcIntroduction The emergence of COVID-19, also termed the novel coronavirus, led to massive social changes in daily activities related to culture, politics, economics, health behaviors, and criminal justice (Maimon & Howell, 2020). While most people infected with the virus experience mild to moderate respiratory illness and may recover without medical treatment, people who are older or who have pre-existing medical problems, such as cardiovascular disease, diabetes, chronic respiratory disease, or cancer face increased risk of morbidity and mortality. Globally, as of July 2022, there have been 562,672,324 confirmed cases of COVID-19, including 6,367,793 deaths (WHO, 2022). In Iran, according to the World Health Organization, about 7,289,542 people have been infected and about 141,532 people have died from COVID-19 (WHO, 2022). Since the initial outbreak, several countries and medical/pharmaceutical institutions have developed COVID-19 vaccines and treatments (Kim et al., 2021; Knoll & Wonodi, 2021; Le et al., 2020). By July 2022, 12,166,921,655 vaccines had been administered worldwide, with a total of 150,558,738 vaccine doses administered in Iran (WHO, 2022). Prior to and since the development of effective COVID-19 vaccines, a primary method of reducing the transmission of the disease has been to adhere to health protocols and physical distancing plans as mandated by governmental agencies (Barrios et al., 2021; Duczmal et al., 2020; Pedersen & Favero, 2020; Sen-Crowe et al., 2020). Iran is among the countries that implemented an urban quarantine plan, with the imposition of fines on citizens who violate COVID-1 ordinances (Alimohamadi et al., 2020; Thu et al., 2020). Breaking quarantine in Iran carries a fine of IRR 2,000,000 (USD 6.6). Research has shown that the successful implementation of urban quarantine schemes (i.e., health protocols and physical distancing), are limited by cultural, religious, social, and economic challenges (Aminnejad & Alikhani, 2020; Huynh, 2020; Lunn et al., 2020; Oosterhoff et al., 2020; Yezli & Khan, 2020). Triberti et al. (2021) found that many people simply do not follow social distancing guidelines. There is also evidence that individuals who violate public health measures, particularly the rejection of health protocols and failure to maintain social distance, continue to drive rates of COVID-19 within populations (Hardin et al., 2021). As such, the need to identify factors influencing the violation of the social laws related to the COVID-19 pandemic is both clear and crucial. Moreover, studies should employ a theoretical perspective to explain and predict these behaviors. One such theory, which may be particularly useful for explaining variation in COVID-19 ordinance violations, is Agnew’s (2005) integrated general theory of crime. The theory posits that several life domains influence the likelihood of criminal acts both directly and indirectly through motivations for crime and low constraints against crime. Although several studies have examined Agnew’s theory (see, e.g., Choi & Kruis, 2019; Cochran, 2017; Ngo & Paternoster, 2014; Zhang et al., 2012), empirical research remains limited. Despite the dearth of empirical research, the theory is purported as a general theory of offending and, as such, should be capable of explaining variation in offending across cultural contexts, including Iran, where the current study was conducted. Moreover, since COVID-19 ordinance violations stem from an array of interpersonal and societal pressures (Aminnejad & Alikhani, 2020; Huynh, 2020; Lunn et al., 2020; Oosterhoff et al., 2020; Yezli & Khan, 2020), Agnew’s general theory should provide nuanced understanding of decision making during a global pandemic. The current study contributes to the literature by examining the utility of Agnew’s general theory of crime for explaining youth violations of public health ordinances during the COVID-19 pandemic using an international sample. Specifically, we examine the direct, indirect, and moderating effects of these life domains on violations of COVID-19 public health ordinances among Iranian high school students. We are aware of no other studies in which the propositions of Agnew’s theory are tested against non-criminal rule-breaking behaviors using an international sample, despite the theory’s purported ability to explain all offending behaviors. As such, this study is an attempt to bridge the gap in this line of research. Theoretical Framework and Literature Review The current study is informed by Agnew’s (2005) integrated general theory of crime. Agnew (2005) sought to determine why criminals offend by synthesizing available theoretical constructs, including concepts from general strain theory1 (Agnew, 2001), into an integrated general theory of crime and deviant behavior. Agnew’s (2005) “variable approach” to theoretical integration (see Vold et al., 2010), rather than the more common forms of theoretical integration that have emerged in the literature (e.g., conceptual integration/absorption, end-to-end and/or top-down propositional integration (see Akers & Sellers, 2013; Liska et al., 1989), was initiated by his attempt to first identify key theoretical variables that are known and reliable correlates of criminal behavior from many different criminological theories. Agnew (2005) then set out to summarize and organize these known correlates into one of three causal constructs: constraints against crime, motivations for crime, and life domains that influence both deviant behavior and these constraints and motivations. The key theoretical proposition of the resultant integrated general theory was that criminal behavior is “most likely when the constraints against crime are low and the motivations for crime are high” (Agnew, 2005, p. 11). These constraints against and motivations for crime/deviance are themselves the products of a broad array of individual traits and social, environmental, and situational factors which, in turn, can be organized into one of five life domains: the self, the family, the peer group, school, and work. While Agnew argues constraints against crime and motivations for crime as the primary mechanisms through which the individual traits and environmental factors located within these life domains cause crime, these life domains can also have an independent, direct influence on crime (Cochran, 2017). Hence, crime is caused by the direct and indirect effects of the various individual traits and environmental variables that comprise the five key life domains and by the constraints against and motivations for them. These motivations and constraints mediate much of the total effects of the life domains. Moreover, the five life domains each condition or moderate the effect of constraints and/or motivations on criminal/deviant behavior. Constraints and Motivations For Agnew (2005), constraints are those factors that deter, inhibit, and/or dissuade individuals from engaging in criminal behavior. Agnew (2005) organized these constraints into one of three spheres: external controls, stakes in conformity, and internal controls. The theory asserts that people refrain for committing criminal acts because (1) they fear getting caught and punished (external control), (2) they fear the consequences and what they would risk losing if caught (stakes in conformity), and/or (3) they believe crime is wrong and produces guilt, shame, and embarrassment (internal control) (Ngo et al., 2011). External controls refer to social sanctions applied by others for violating the law or social norms. External controls may be directly or vicariously experienced and/or perceived/anticipated; they vary in both their likelihood (certainty) and intensity (severity) and they may be applied formally by the courts, police, school officials, employers, etc. or informally by family, neighbors, friends, classmates, colleagues, etc. (Cochran, 2017). Internal controls refer to those factors through which individuals restrain themselves and include (a) one’s moral values and attitudes toward the law and social norms, (b) the degree to which one has been effectively socialized toward conventional society, (c) personality traits that increase responsiveness to external constraints (i.e., self-control, risk aversion, delayed gratification, etc.), and (d) the extent to which individuals may sanction themselves for violating the law or social norms (Cochran, 2017). Finally, Agnew (2005) recognized a variety of “stakes in conformity” that individuals have established for themselves that they risk losing should they be caught for criminal acts. These stakes in conformity refer to the various investments, “side bets,” one makes in their current life and future through the establishment of conventional goals and strong social bonds with conventional others, activities, and social institutions (i.e., attachments, commitments, and involvements) that one risks harming or destroying through engagement in criminal behaviors (Cochran, 2017). While constraints may restrain one from criminal involvement, the term “motivations” refers to risks that tempt, lure, provoke, or pressure one toward crime. For Agnew (2005), such motivations include (a) stressors, strains, and negative emotions that pressure one toward crime, (b) coercive forces that may compel one to violate social rules, (c) social forces that may attract one to crime through neutralizations and alternative definitions of the situation that make crime more acceptable/appropriate, (d) social and non-social reinforcements that make crime more rewarding, and (e) encouragements for crime from significant others. These motivations are manifested through strain and the social learning process. Life Domains Agnew (2005) argues the constraints against, and the motivations for, crime are both influenced by, and are mediators of, a host of individual traits and environmental factors that he has organized around five variable clusters known as “life domains”: the self, the family, the peer group, school, and work. In the life domain of the self, Agnew (2005) recognizes two dominant sources of constraints and motivations: self-control and conventional socialization. High levels of self-control and the internalization of conventional beliefs, values, and norms are mechanisms of the self that serve to enhance constraints against, and to attenuate motivations for, criminal acts. Conversely, low self-control (i.e., impulsivity, risk- and sensation-seeking, irritability, etc.) reduces the effectiveness of constraints and amplifies motivations (Gottfredson & Hirschi, 1990). Similarly, poor/ineffective socialization into conventional values, beliefs, and social norms attenuate the effects of constraints and permit pro-criminal motivations to express themselves behaviorally. Borrowing from social bonding theory (Hirschi, 1969), Agnew’s family domain, at least for adolescents, is best conceptualized by the strength of one’s bond to their parents and other family members (parental attachment) and by the level of parental supervision experienced. Where parental attachment is strong and parental supervision is effective, the inhibiting effects of constraints are enhanced, and the criminal motivations are dampened (Gottfredson & Hirschi, 1990). Conversely, other factors within the family domain such as poor parenting, lack of parental support, family conflict, abuse/neglect, family substance abuse, and/or criminality may attenuate the effects of constraints against crime and may amplify the influence of criminal motivations. The peer group constitutes the third life domain in Agnew’s theory. Peer associates, through pressure, their own criminal involvements, conflicts, unstructured/unsupervised activities, etc. are a primary source of criminal motivations and weakened constraints. However, pro-social peers have the opposite effects. Strong attachments to school, teachers, and coaches, strong commitments to educational goals and aspirations, heavy investment and involvement in school-related activities, and effective monitoring and supervision by school officials are elements of the school domain that serve to activate and amplify constraints against crime and to mitigate the influence of pro-criminal motivations. Conversely, the absence, breaking, weakening etc. of any of these school bonds, such as poor treatment, poor teaching, bad grades, etc., stimulate criminal motivations while dampening the effects of constraints against criminal behavior. In a similar vein, strong attachments, commitments, and involvements to work, work goals and aspirations, employers, and co-workers, enhance constraints and reduce criminal motivations while weak or poor work attachments, commitments, and involvements have the opposite effect. Since the current study employs a sample of high school youth, we focus on the school, rather than work, domain. In short, Agnew’s general theory of crime posits that (a) constraints, motivations, and life domains have direct effects on offending, (b) both constraints and motivations partially mediate the effects of the life domains on offending, and (c) the life domains condition or moderate the effects of both constraints and motivations on offending. While a complete test of Agnew’s general theory is notoriously difficult (Vold et al., 2010), those who have partially tested the propositions of the theory have all found some support for the association between constraints, motivations, and variables within the life domains (e.g., employment, educational attainment, parental supervision, peer delinquency) and delinquency, offending, and recidivism (see Choi & Kruis, 2019; Cochran, 2017; Grubb & Posick, 2018; Kabiri et al., 2020; Muftić et al., 2014; Ngo & Paternoster, 2014; Ngo et al., 2011; Zhang et al., 2012). While previous studies highlight the direct effects of the various life domains on criminal offending, only a few tests examine the indirect effects of life domains (Cochran, 2017; Ngo et al., 2022; Zhang et al., 2012), with most studies utilizing a sample gathered in the USA (cf. Kabiri et al., 2020; Muftić et al., 2014). Ngo et al. (2022) conducted the most recent test of Agnew’s theory on the perpetration of intimate partner violence. The study, like most prior tests, provides support for the theory’s propositions: life domains have a direct and indirect effect on offending. Unfortunately, and also like most prior tests, the authors failed to examine the moderating role of the constructs. In fact, despite a few studies testing various interactions (i.e., Kabiri et al., 2020; Muftić et al., 2014), no known study has directly assessed whether life domains moderate the effects of low constraints and motivations on offending. Moreover, none of these studies have assessed the theory’s efficacy against data on violations of an emergent social norm such as behaviors violative of the social hygiene and social distancing norms and ordinances that have arisen recently under the exigency of the COVID-19 pandemic. The current study seeks to provide a more complete test of Agnew’s theory on COVID-19 misbehavior using a non-USA sample. Specifically, and expanding upon the literature reviewed above, we seek to test the following theoretically derived hypotheses: Hypothesis 1. Life domains will have a direct effect on COVID-19 ordinance violations. Hypothesis 2. Low constraints will increase engagement in COVID-19 ordinance violations. Hypothesis 3. Motivations will increase engagement in COVID-19 ordinance violations. Hypothesis 4. Low constraints will partially mediate the effect of life domains on COVID-19 ordinance violations. Hypothesis 5. Motivations will partially mediate the effect of life domains on COVID-19 ordinance violations. Hypothesis 6. Life domains will moderate the effect of low constraints on COVID-19 ordinance violations. Hypothesis 7. Life domains will moderate the effect of motivations on COVID-19 ordinance violations. Methodology The Iranian national headquarters responsible for addressing COVID-19 announced that “red cities” in the country, including Rasht, were to be quarantined for two weeks beginning on Saturday, December 22, 2020. A city is classified as red (high risk) when the average daily hospitalization rate is over 3 per 100,000 population in the previous two weeks. Although schools in Rasht are typically open between 7 a.m. and 1 p.m. from Saturday to Thursday, they converted to a hybrid model with some activities only available online during the quarantine. Moreover, schools strictly monitored for symptoms of the virus and symptomatic students were unable to attend the in-person activities. The present study was conducted during the quarantine in December, 2020. The main purpose of this study, which was approved by the university’s institutional review board, is to test the efficacy of Agnew’s general theory in explaining violations of these public health requirements during urban quarantine. To do so, we administered a self-reported survey to a sample of high school students in Rasht, Iran. The survey was completed using pen and paper. The questions were presented in Farsi then translated to English by the lead author. The sampling frame consisted of the 6,023 high school students in Rasht at the time of the survey. Members of the research team obtained a list from the Rasht Education Department of students enrolled in district high schools; this list served as the sampling frame for the present study. From this list, we utilized the Krejcie and Morgan (1970) sample-size estimation procedure2 and determined that 410 students should be randomly selected.3 The research team contacted the selected students and their parents to notify them of the nature of the study and obtain consent and parental permission to participate in this project. Questionnaires (in paper format) were then delivered to the students; completed questionnaires were subsequently picked-up for coding and data entry. As an incentive, participants received a health package that included hand sanitizer, a guide to health tips during quarantine, and a facemask. In total, of the 410 self-administered questionnaires distributed, 389 completed questionnaires were returned, yielding a 94.49% response rate. The 21 incomplete surveys were not considered in the final analysis. Although this response rate is high for the social sciences generally, prior research conducted in Iran, using pen and paper surveys, yield a similar response rate (e.g., Kabiri et al., 2022; Shadmanfaat et al., 2018, 2020). Descriptive statistics revealed that 27.8% of our respondents were in their first year of high school, 34.7% were in their second year of high school, and 37.5% were in their third year of high school. In terms of gender, 51.4% of the respondents were female and 48.6% were male. Dependent Variable The dependent variable is a summated scale of self-reported COVID-19 misbehaviors capturing norm violations. Since the study was conducted less than two weeks post quarantine implementation, we focused our analysis on norm violations within the prior week (i.e., 7 days) to ensure the quarantine was in effect. COVID-19 misbehavior is a four-item measure developed by Alessandri et al. (2020). Respondents were asked, “In the past 7 days, to what extent did you: (1) engage in social distancing; (2) keep the recommended distance from people and avoid crowded places; (3) limit your social interactions; and (4) follow the guidelines issued by the government.” Response options were given on a five-point scale from 1 (not at all) to 5 (a great deal). All items were reverse coded, then summated to create the final measure, COVID-19 misbehavior (α = .824), with higher scores indicating higher levels of COVID misbehavior. The dependent variable approximates a normal distribution (kurtosis = −.750) with a slight right skew (.193). Moreover, the average score across participants is 9.89 (SD = 3.69) with a median value of 10. Since the index ranged from 4 to 20, the mean value obtained is close to the mid-point of the interval (i.e., 10) suggesting an average level of compliance. The reliability of the scale described above was examined through calculations of Cronbach’s alpha coefficients (α) and composite reliability (CR). The Cronbach’s alpha and composite reliability coefficients were higher than the acceptable threshold of .70 as recommended by Nunally (1978). Reliability and validity measures are presented alongside the descriptive statistics in Table 1. Table 1. Descriptive Characteristic (N = 389). Variable name Mean Standard deviation Factor loadings CR α Minimum Maximum COVID-19 misbehavior 9.89 3.69 0.656–0.769 .825 .824 4 20 Motivations 13.53 4.13 0.521–0.603 .743 .745 6 30 Low constraints 16.90 4.87 0.408–0.736 .771 .778 6 27 Low peer domain 8.95 3.13 0.705–0.822 .859 .860 4 20 Low self-domain 34.73 10.32 0.490–0.769 .896 .901 15 75 Low family domain 13.95 3.78 0.623–0.778 .857 .859 6 34 Low school domain 17.58 5.01 0.632–0.833 .906 .907 8 40 Male 0.50 0.50 — — — 0 1 Education 2.10 0.80 — — — 1 3 Family at risk 0.32 0.47 — — — 0 1 Family death 0.23 0.42 — — — 0 1 Note: α = Cronbach’s alpha; CR = composite reliability. Constraints and Motivations Constraints: Constraints, as discussed in much depth above, are factors that deter, inhibit, and/or dissuade individuals from engaging in criminal behavior (Ngo et al., 2011). In the current study, two dimensions of constraints were measured using six items assessing internal control (shame) and informal control (embarrassment). Both shame and embarrassment were measured through their perceived certainty and severity, as developed by Cochran (2017). Responses were then summated to create the final measure, low constraints. Higher scores represent lower levels of constraint (α = .778). See Appendix A for a complete list of questions. Response options ranged from 6 to 27, with an average score of 16.90. Despite measuring two dimensions (shame and embarrassment), the measure proved to be unidimensional and approximated a normal distribution (Skewness = .320, Kurtosis = −.500). Motivations: While constraints may restrain one from criminal involvement, motivations are factors that tempt, lure, provoke, or pressure one toward crime. For the current study, two dimensions of motivation were measured using six items assessing strain-based motivations and social learning-based motivations. Responses were then summated to create the final measure, motivations. Higher scores represent higher motivations for crime (α = .745). See Appendix B for a complete list of questions. Response options ranged from 6 to 30, with an average score of 13.53. Despite measuring two dimensions (strain and social learning), the measure proved to be unidimensional and approximated a normal distribution (Skewness = .461, Kurtosis = .338). Life Domains In accordance with Agnew (2005), constraints and motivations are influenced by, and mediators of, individual traits and environmental factors organized around five “life domains”: the self, the family, the peer group, school, and work. Since we utilize a sample of high school students, we measure the first four of these life domains and exclude “work”. Below we discuss our conceptualization and operationalization of these life domains. Low family-domain Agnew’s social domain of the family is measured using a summated scale comprised of six items assessing attachment to parents, harsh parental discipline, and poor monitoring. Two of these six items address attachment to parents and were borrowed from Liu (2019): (1) “I have a close relationship with my parents,” and (2) “My parents understand me”. Items were rated on a five-point Likert scale (1 = strongly agree; 5 = strongly disagree). We also used two items from the Harsh Parental Discipline scale (Liu, 2019) to measure parental punitive style. We asked students, “When you misbehave, did your father or mother . . . (1) hit/beat up/slap you, and (2) taunt/scream at/ridicule you”. The response options ranged from 1 (never) to 5 (frequently). The final two items comprising the ineffective parenting scale assessed parents’ monitoring ability. These were captured by items used by Kabiri et al. (2020): (1) “How often do/does your parent or parents (guardians) know who you are with when you are away from home” and (2) “In the course of a day, how often do/does your parent or parents (guardians) know where you are.” Items were rated on a seven-point rating scale (1 = never; 7 = always). These two items were reverse coded. Responses to each of the items were summated to create the construct, low family domain (α = .859). Response options ranged from 6 to 34, with an average score of 13.95. Higher scores represent a lower family bond. The measure proved to be unidimensional and approximated a normal distribution (Skewness = .265, Kurtosis = −.284). Low school-domain To measure the impact of the school domain on misbehavior during the urban quarantine, we used eight items related to poor school support, ineffective disciplinary structure, school disorganization, and school attachment that were used in a previous study by Kabiri et al. (2020). The items included: (1) “Most teachers and other adults at this school care about all students;” (2) “Most teachers and other adults at this school treat student with respect;” (3) “Students at this school only get punished when they deserve it;” (4) “The school rules are fair;” (5) “There is much violence in my school;” (6) “There is a lot of stealing in my school;” (7) “I feel like a part of my school;” and (8) “I am happy to be at my school.” The responses ranged from 1 (completely agree) to 5 (completely disagree). Items 5 and 6 were reverse coded. Responses to each of the items were summated to create the construct, low school domain (α = .907). Response options ranged from 8 to 40, with an average score of 17.58. Higher scores represent a lower school bond. The measure proved to be unidimensional and approximated a normal distribution (Skewness = .492, Kurtosis = .187). Low peer domain Agnew’s peer domain was assessed from a four-item measure that captures deviant peer affiliation developed by Cutrín, Gómez-Fraguela, Maneiro, et al. (2017). We added one item related to COVID-19 misbehavior to the original scale. Respondents were asked: (1) “How many of your close friends get into trouble and problems;” (2) “How many of your close friends take drugs/drink alcohol or smoking cigarettes;” (3) “How many of your close friends carry out risky behavior;” and (4) “How many of your close friends violate the COVID-19 guidelines issued by the Government?” The response categories ranged from 1 (none of them) to 5 (all of them). Responses to each of the items were summated to create the construct, low peer domain (α = .860). Response options ranged from 4 to 20, with an average score of 8.95. Higher scores represent a decreased prosocial peer bond. The measure proved to be unidimensional and approximated a normal distribution (Skewness = .293, Kurtosis = −.500). Low self-domain Two scales were used to measure the impact of the self-domain: self-control and social concern. The ability to exercise self-control was assessed via the self-control scale created by Wikström et al. (2012). The social concern construct was a nine-item scale that assesses the four subcomponents of social concern: moral intuitions, empathy/sympathy, desire for close ties, and conformity to others. Moral intuitions were assessed using items adapted from the moral foundation questionnaire (Haidt & Graham, 2007), whereas the other components were assessed using measures adopted from Kabiri et al., (2020). See Appendix C for a complete list of questions used to create the summated scale, low self-domain (α = .901). Response options ranged from 15 to 75, with an average score of 34.73. Higher scores represent a lower self-domain (i.e., less self-control and social concern). The measure proved to be unidimensional and approximated a normal distribution (Skewness = −.015, Kurtosis = −.752). The reliability of each scale described above was examined through calculations of Cronbach’s alpha coefficients (α) and composite reliability (CR). All the Cronbach’s alpha and composite reliability coefficients were higher than the acceptable threshold of .70 as recommended by Nunally (1978). Reliability and validity measures are presented alongside the descriptive statistics in Table 1. Control Variables In this study, the effects of death experience from COVID-19 in the family (family death) is controlled with a single item: “Have you lost a family member due to coronavirus? Moreover, family members’ risky conditions (family at risk) are controlled with a single item: Do you have a family member with a pre-existing condition that puts her at particular risk during the corona outbreak?” Response options to both questions included 0 (no) and 1 (yes). Additionally, gender (male) was included as a control variable (0 = female; 1 = male). The final control variable included in the models is education, which was coded as an ordinal variable ranging from 1 (first year of high school) to 3 (third year of high school). Descriptive statistics for the control variables are presented in Table 1. Analytic Strategy Data analysis was performed in several phases. First, bivariate correlations between independent and dependent variables were examined. Next, structural equation modeling in AMOS software was performed to observe the direct effects of constraints, motivations, and life domains on COVID-19 misbehavior, in addition to the indirect effects of life domains on COVID-19 misbehavior through constraints and motivations. In the last step, we assess Agnew’s (2005) claim that constraints and motivations are moderated by the effect of life domains using OLS regression. Results Correlation analyses were used to examine the associations between Agnew’s key theoretical constructs and COVID-19 misbehavior. As reported in Table 2, each of the independent variables of interest (excluding the control variable, education) are correlated with COVID-19 misbehavior. These correlations are all positive, modest to moderate in strength, and statistically significant at the p < .01 level. Motivations and low constraints are positively associated with COVID-19 misbehavior (r = .49 and r = .45, respectively). Similarly, all the life domain scales (with higher scores representing lower domains) are positively associated with COVID-19 misbehavior (r = .31–.49). Finally, all the correlations among the key theoretical variables are also positive, statistically significant, and modest to moderate in strength (r = .16–.39). As such, these bivariate associations provide initial support for the application and efficacy of Agnew’s integrated general theory to an explanation of the violation of emergent social hygiene norms associated with the COVID-19 pandemic in Iran. In addition, the highest inter-item correlation is .49, suggesting multicollinearity is not an issue. Table 2. Correlation Matrix (N = 389). 1 2 3 4 5 6 7 8 9 10 1 COVID-19 misbehavior — 2 Low self-domain .46** — 3 Low family domain .44** .27** — 4 Low peers domain .31** .23** .19** — 5 Low school domain .49** .22** .16** .17** — 6 Motivations .49** .33** .39** .29** .33** — 7 Low constraints .45** .27** .27** .20** .24** .27** — 8 Male .26** .10* .09* .09* .15** .13** .17** — 9 Education −.04 −.04 −.02 .10* −.03 −.06 −.02 .02 — 10 Family at risk −.14** −.02 −.07 .03 −.03 −.01 −.05 −.04 −.10* — 11 Family death −.23** −.17** −.14** −.11* −.09* −.11* −.07 .03 −.07 −.01 Note: *p < .05. **p < .01. Table 3 presents the results of a structural equation model estimating: (1) the direct effects of life domains, motivations, and low constraints on COVID-19 misbehavior; (2) the direct effects of life domains on motivations and low constraints; and (3) the indirect effects of the life domains on COVID-19 misbehavior through motivations and low constraints. The overall structural model, depicted in Figure 1, proved to be a good fit to the data: df = 2.090, GFI = .979, IFI = 961, CFI = .958, RMSEA = .053. Table 3. Structural Equation Model Assessing Agnew’s General Theory on COVID-19 Misbehavior (N = 389). Independent variable Dependent variable Estimate Standard error p-Value R 2 Low self-domain COVID-19 misbehavior .21 .01 .001 Low family domain COVID-19 misbehavior .18 .04 .001 Low peers domain COVID-19 misbehavior .08 .04 .031 Low school domain COVID-19 misbehavior .29 .03 .001 Motivations COVID-19 misbehavior .17 .04 .001 Low constraints COVID-19 misbehavior .20 .03 .001 Male COVID-19 misbehavior .13 .25 .001 Education COVID-19 misbehavior −.02 .15 .485 Family at risk COVID-19 misbehavior −.11 .26 .002 Family death COVID-19 misbehavior −.11 .30 .001 R2 of model .53 Low self-domain Motivations .17 .02 .001 Low family domain Motivations .28 .05 .001 Low peers domain Motivations .15 .06 .001 Low school domain Motivations .21 .04 .001 Male Motivations .05 .35 .265 Education Motivations −.03 .22 .461 Family at risk Motivations .02 .38 .642 Family death Motivations −.01 .42 .938 R2 of model .28 Low self-domain Low constraints .16 .02 .002 Low family domain Low constraints .18 .06 .001 Low peers domain Low constraints .10 .08 .040 Low school domain Low constraints .15 .05 .002 Male Low constraints .11 .45 .022 Education Low constraints −.01 .28 .888 Family at risk Low constraints −.03 .48 .526 Family death Low constraints .01 .54 .893 R2 of model .15 Total Indirect Effects of Life Domains on COVID-19 Misbehavior Via Low Constraints and Motivations Low self-domain COVID-19 misbehavior .06 .01 .001 Low family domain COVID-19 misbehavior .08 .02 .001 Low peers domain COVID-19 misbehavior .05 .02 .001 Low school domain COVID-19 misbehavior .07 .01 .001 Note. Standardized coefficents are reported; Model fit indices: df = 2.090, GFI = .979, IFI = .961, CFI = .958, RMSEA = .053. * p < .05. **p < .01. Figure 1. Structural equation model assessing Agnew’s general theory on COVID-19 misbehavior. Note. Standardized coefficents are reported; Model fit indices: df = 2.090, GFI = .979, IFI = .961, CFI = .958, RMSEA = .053. *p < .05. **p < .01. Findings from this structural model demonstrate that all four life domains (low self-domain (β = .21, p < .01), low family domain (β = .18, p < .01), low peers domain (β = .08, p < .01), and low school domain (β = .29, p < .01) have a direct effect on COVID-19 misbehavior. Moreover, both motivations (β = .17, p < .01) and low constraints (β = .20, p < .01) have a direct effect on COVID-19 misbehavior. Taken together, these findings provide support for Agnew’s theory. Each of the control variables, except for education, were also significantly associated with the dependent variable of interest. In further support of Agnew’s theory, each of the life domains (low self-domain (β = .17, p < .01), low family domain (β = .28, p < .01), low peers domain (β = .15, p < .01), and low school domain (β = .21, p < .01)) have a direct effect of motivations. Similarly, each of the life domains (low self-domain (β = .16, p < .01), low family domain (β = .18, p < .01), low peers domain (β = .10, p < .05), and low school domain (β = .15, p < .01)) have a direct effect of low constraints. Thus, stated concisely, the social, environmental, and situational characteristics comprising the life domains all alter participants’ motivations for, and constraints against, offending. None of the control variables are associated with motivations and only male (β = .11, p < .05) is associated with low constraints, with males having lower levels of constraints than their female counterparts. Lastly, low self-domain (β = .06, p < .01), low family domain (β = .08, p < .01), low peers domain (β = .05, p < .01), and low school domain (β = .07, p < .01) all have an indirect effect on COVID-19 misbehavior through motivations and low constraints. Thus, the inter-individual characteristics comprising the life domains alter participants’ motivations and constraints, and through these constructs influence their decision to offend. As such, the life domains have a direct and indirect effect on COVID-19 misbehavior as proposed by Agnew. The structural model, with standardized effects presented, can be viewed in Figure 1. To further test Agnew’s general theory of crime, we assess whether, and to what extent, the relationship between motivations (Table 4) and low constraints (Table 5) and COVID-19 misbehavior is moderated by life domains. Table 4 presents the moderating role of the various life domains on the relationship between motivations and COVID-19 misbehavior. Specifically, interaction terms were included to test whether low self-domain (Model 1), low family domain (Model 2), low peers domain (Model 3), and low school domain (Model 4) moderate the effect of motivations on COVID-19 misbehavior. Results, as presented in Table 4, Model 2, indicate the relationship between motivations and COVID-19 misbehavior is only moderated by low peers domain (β = .09, p < .05), garnering partial support for Agnew’s theory. Indeed, and as depicted in Appendix D, Panel 1, and at the bottom of Table 4, the relationship between motivations and COVID-19 misbehavior is strongest for those who score high (+1 standard deviation) on the low peers domain. In other words, motivations to engage in COVID-19 misbehavior are more likely to result in ordinance violations when participants have increased association with delinquent peers. Contrary to the theoretical propositions set forth by Agnew, the interaction terms in Models 1, 2, and 4 are nonsignificant. Table 4. The Moderation Effect of Life Domains on the Relationship between Motivations and COVID-19 Misbehavior (N = 389). Model 1: Low self-domain Model 2: Low family domain Model 3: Low peers domain Model 4: Low school domain Independent variables Estimate Standard error p-Value Estimate Standard error p-Value Estimate Standard error p-Value Estimate Standard error p-Value Low self-domain .20 .01 .001 .20 .01 .001 .20 .01 .001 .20 .01 .001 Low family domain .18 .04 .001 .18 .04 .001 .16 .04 .001 .18 .04 .001 Low peers domain .08 .04 .028 .08 .04 .028 .08 .04 .029 .08 .04 .033 Low school domain .28 .03 .001 .28 .03 .001 .27 .03 .001 .28 .03 .001 Motivations .17 .04 .001 .17 .04 .001 .16 .04 .001 .17 .04 .001 Low constraints .19 .03 .001 .19 .03 .001 .18 .03 .001 .19 .03 .001 Male .12 .26 .001 .12 .26 .001 .13 .25 .001 .12 .26 .001 Education –.02 .16 .514 –.02 .16 .483 –.02 .16 .562 –.02 .16 .468 Family at risk –.10 .27 .003 –.11 .27 .002 –.11 .27 .002 –.11 .27 .002 Family death –.10 .31 .003 –.11 .31 .002 –.11 .31 .002 –.11 .31 .002 Low Self-domain × motivations −.05 .01 .149 — — — — — — — — — Low family domain × motivations — — — −.01 .01 .674 — — — — — — Low peers domain × motivations — — — — — — .09 .01 .017 — — — Low school domain × motivations — — — — — — — — — −.02 .01 .503 R2 of model .57 .57 .57 .57 R2 change .01 .01 .01 .01 F change 2.09 .09 5.73 .45 Sig. F change .149 .764 .017 .503 Low (−1 SD below the mean) — — — — — — .30 .05 .001 — — — Moderate (mean) — — — — — — .38 .04 .001 — — — High (+1 SD above the mean) — — — — — — .46 .05 .001 — — — Table 5. The Moderation Effect of Life Domains on the Relationship between Constraints and COVID-19 Misbehavior (N = 389). Model 1: Low self-domain Model 2: Low family domain Model 3: Low peers domain Model 4: School domain Independent variables Estimate Standard error p-Value Estimate Standard error p-Value Estimate Standard error p-Value Estimate Standard error p-Value Low self-domain .20 .01 .001 .19 .01 .001 .20 .01 .001 .20 .01 .001 Low family domain .18 .04 .001 .18 .04 .001 .17 .04 .001 .17 .04 .001 Low peers domain .08 .04 .035 .07 .04 .050 .08 .04 .039 .08 .04 .026 Low school domain .28 .03 .001 .27 .03 .001 .28 .03 .001 .24 .03 .001 Motivations .17 .04 .001 .16 .04 .001 .17 .04 .001 .16 .04 .001 Low constraints .19 .03 .001 .19 .03 .001 .19 .03 .001 .19 .03 .001 Male .12 .26 .001 .12 .26 .001 .12 .26 .001 .13 .26 .001 Education –.02 .16 .499 –.02 .16 .651 –.02 .16 .516 –.02 .16 .584 Family at risk –.11 .27 .002 –.10 .27 .003 –.11 .27 .002 –.11 .27 .002 Family death –.11 .31 .002 –.11 .31 .003 –.11 .31 .002 –.11 .31 .002 Low self-domain × low constraints .01 .01 .982 — — — — — — — — — Low family domain × low constraints — — — .08 .01 .018 — — — — — — Low peers domain × low constraints — — — — — — .01 .01 .833 — — — Low school domain × low constraints — — — — — — — — — .09 .01 .015 R2 of model .57 .57 .57 .57 R2 change .01 .01 .01 .01 F change .01 5.62 .04 5.94 Sig. F change .982 .018 .833 .015 Low (−1 SD below the mean) — — — .10 .05 .028 — — — .18 .04 .001 Moderate (mean) — — — .26 .03 .001 — — — .27 .03 .001 High (+1 SD above the mean) — — — .41 .04 .001 — — — .36 .04 .001 Table 5 presents the moderating role of the various life domains on the relationship between low constraints and COVID-19 misbehavior. Specifically, interaction terms were included to test whether low self-domain (Model 1), low family domain (Model 2), low peers domain (Model 3), and low school domain (Model 4) moderate the effect of low constraints on COVID-19 misbehavior. Table 5 indicates the effect of low constraints on COVID-19 misbehavior is moderated by low family domain (Model 2) (β = .08, p < .05) and low school domain (Model 4) (β = .09, p < .05), but not low self-domain (Model 1) or low peers domain (Model 3), garnering partial support for Agnew’s theory. Indeed, and as depicted in Appendix D, Panels 2 and 3, respectively, the relationship between low constraints and COVID-19 misbehavior is strongest for those who score high (+1 standard deviation) on low family domain and low school domain. In other words, low constraints against COVID-19 misbehavior are more likely to result in ordinance violations when participants have less attachment to their family and school. It should be noted that the inclusion of the interaction terms in both Tables 4 and 5 have a minimal effect on the amount of explained variance in COVID-19 misbehavior. Discussion The current study utilizes Agnew’s Integrated General Theory of Crime to examine deviant behavior during an urban quarantine period related to COVID-19. In accordance with the theory, and as discussed in great depth above, (a) constraints, motivations, and life domains have direct effects on offending, (b) both constraints and motivations partially mediate the effects of the life domains on offending, and (c) the life domains condition or moderate the effects of both constraints and motivations on offending. The current study focused on four domains—family, school, self, and peer—and hypothesized that Iranian high school students’ engagement in deviant behaviors, such as violations of health mandates and social distancing ordinances during the COVID-19 pandemic, would be influenced by the direct, indirect, and moderating effects of life domains and both constraints against and motivations for deviance. Indeed, the life domains, low constraints, and motivations constructs were observed to have significant direct effect on COVID-19 misbehavior. In other words, the social, environmental, and situational factors constituting the five life domains are predictive of COVID-19 ordinance violations. Moreover, the effects of the various life domains on COVID-19 misbehavior were mediated by constraints and/or motivations as predicted by the theory. That is, the structural equation model demonstrated that the impact of the different life domains on misbehaving during the lockdown were partially mediated by both deviant motivations for crime and low constraints against crime. As such, the inter-individual characteristics comprising the life domains alter participants’ constraints against crime and motivations for crime, and through these constructs have an indirect effect on COVID-19 misbehavior. This finding is consistent with those observed in previous tests of this mediation hypothesis (Choi & Kruis, 2019; Cochran, 2017; Kabiri et al., 2020; Muftić et al., 2014; Ngo et al., 2011; Zhang et al., 2012). The moderating nature of life domains was also examined in this study and the results showed that in addition to both direct and indirect effects, life domains played a significant role in the occurrence of deviant behaviors by moderating/conditioning the effects of these motivations and constraints. Specifically, the relationship between motivations and COVID-19 misbehavior is moderated by the peers domain, whereas the relationship between constraints and COVID-19 misbehavior is moderated by the family and school domains. In essence, this means participants with low constraints against crime are most likely to engage in ordinance violations when they are also associated with delinquent peers. Moreover, higher motivations for crime are most likely to result in ordinance violations for those lacking strong family and school bonds. The application of Agnew’s Integrated General Theory of Crime to explain high school students’ misbehavior during a global pandemic provides nuanced insight relevant for theoretical advancement and proactive policy development. Agnew (2005) argued that to reduce negative behaviors like COVID-19 deviancy, the impact of informal control forces, such as parents, school, and important others, should be increased. According to Agnew (2005), increasing the severity and certainty of punishment will only work for individuals that have a high level of self-control, are well equipped (or able) to resist environmental temptations, reside in an anti-crime environment, and have a history of less deviant behaviors. In such cases, increasing the severity and certainty of the punishment is most effective as it leads individuals to the conclusion that by engaging in COVID-19 misbehaving, the probability of formal and informal consequences will be high. According to Agnew (2005) the most effective response is to empower people and apply prevention programs in different areas of life: 1) reducing irritability, increasing levels of self-control, 2) improving positive and effective parenting patterns, 3) increasing the quality of marital relations, 4) improving the individual’s experiences in school and university, 5) reducing the affiliation with deviant peers, and 6) increasing suitable job opportunities for individuals. To reduce deviant behaviors during COVID-19, there is a need for comprehensive personal, family, and school empowerment programs (MacArthur et al., 2018). At the individual level, increasing levels of self-control and social concern through self-control training courses (Denson et al., 2011; Piquero et al., 2016), empathy/sympathy training (Şahin, 2012; Teding van Berkhout & Malouff, 2016; Wündrich et al., 2017), and moral training programs (Wikström & Treiber, 2017) can be effective in reducing deviant behaviors during the COVID-19 pandemic. This strategy may include support programs for families in need, such as parenting courses that improve communication skills with children and overall parenting methods (Cutrín, Gómez-Fraguela, & Sobral 2017b; DeGarmo & Forgatch, 2005; DeGarmo & Jones, 2019; Eddy et al., 2019). To lessen deviant peer affiliation, effective monitoring of children leisure activities (Elam et al., 2017; Mann et al., 2015), and using authoritative parenting styles (Li et al., 2015; Xiong et al., 2020) can reduce associations with deviant peers. Policy responses may also include developing student attachment to school by improving the quality of life in school (Ozgenel et al., 2018; Toraman & Aycicek, 2019), improving teachers’ relationships with students (Bao et al., 2015; Sanches et al., 2012), and employing experienced human resources in schools (Demanet & Van Houtte, 2012). While these findings are valuable, they are not without limitations. A reliance on self-reported data includes recognition of the threat of social desirability bias. Future efforts could include additional data techniques to better measure deviancy in response to COVID-19. Moreover, since our instruments were not pre-tested, future studies may expand upon our work and reformulate some of our theoretical constructs. In particular, we believe the operationalization of the measures “motivations” and “low constraints” could be improved upon. Additionally, the presence of cultural differences in diverse regions of Iran diminishes the generalizability of the findings obtained from high school students in Rasht (one of the northern cities of Iran). Additional studies would benefit from diverse geographical and cultural areas to promote generalizability and understand how socio-cultural factors influence behavioral patterns and COVID-19 mitigation efforts. Cross-cultural tests of Agnew’s theory would provide further nuance into the causal mechanisms of crime and deviance. Finally, the study suffers from potential omitted variable bias. Although Agnew (2005) sets forth a comprehensive theory, other variables not included in the analysis may explain variation in COVID-19 misbehavior. Conclusion In Iran, where the current study was conducted, about 6,293,695 people have been infected and about 132,333 people have died from COVID-19 (WHO, 2022). This represents a massive impact on the health, public safety, and social integration of the population. Evidence suggests that individuals who violate COVID-19 mitigation and prevention efforts continue to drive rates of COVID-19 within populations (Hardin et al., 2021). As such, the need to identify factors influencing the violation of the social laws related to the COVID-19 pandemic is both clear and crucial. The current study found compelling support for Agnew’s integrated general theory of crime and provides policy implications supported by the theory. Although much work is needed to understand decision making amid a global pandemic, the current study serves as a modest step forward. Author Biographies Saeed Kabiri is an affiliated researcher in the Institute of Humanities and Social Studies at Tehran University Jihad. He earned his master’s degree in Sociology at the University of Guillan (2012) and his PhD degree in Social Problems of Iran at the University of Mazandaran (2017). He has published several papers about the sociology and criminology of sports. His current research interests involve sport criminology. Kabiri’s recent research has been published in multiple peer-reviewed journals such as Deviant Behavior, Journal of Drug Issues, International Criminal Justice Review, the International Journal of Offender Therapy and Comparative Criminology, and International Journal of Cyber Criminology. Mahmoud Sharepour is Full Professor at the Department of Social Sciences, University of Mazandaran, Iran. His research interests include Sociology of Education, Urban Sociology, Social Capital, and Social Impact Assessment. He is the author of several books (in Persian) and articles dealing with these subjects. He has also translated several important sociological books to Farsi and is currently pursuing a study of second home and amenity migration in north of Iran. C. Jordan Howell is an Assistant Professor in the Department of Criminology at the University of South Florida. His research focuses on the human factor of cybercrime. He employs advanced computer science techniques to gather threat intelligence, which is then used to test social scientific theory, build profiles of active cyber-offenders, plot criminal trajectories, and disrupt the illicit ecosystem enabling cybercrime incidents. Hadley Wellen is a doctoral student in the Criminology and Criminal Justice department at the University of South Carolina. Her research interests include place-based criminology, quantitative methods, and mentoring and positive youth development. Hayden P. Smith is a Professor of Criminology and Criminal Justice at the University of South Carolina. His principal focus of study is the intersection of the criminal justice and public health systems. He is a national and international expert on self-injurious and suicidal behaviors occurring in incarcerated populations. Other areas of study include officer wellness and resiliency, the Prison Rape Elimination Act (PREA), reentry initiatives, and best practices in evaluating corrections-based programs. He has expertise in program evaluation and policy analysis and has worked with numerous correctional and health systems. His previous publications have appeared in Justice Quarterly, Crime & Delinquency, and Criminal Justice & Behavior. John K. Cochran is Professor and Chair in the Department of Criminology at the University of South Florida. He earned his degree in Sociology from the University of Florida in 1987. His areas of research interest are testing theories of crime and criminal behavior and examining issues associated with the death penalty. He has over 130 publications in peer-reviewed journals including Criminology, Journal of Research in Crime and Delinquency, Journal of Quantitative Criminology, Crime and Delinquency, Justice Quarterly, Journal of Criminal Justice, Criminal Justice and Behavior, and Deviant Behavior. Seyyedeh Masoomeh (Shamila) Shadmanfaat earned her master’s degree in Sociology at the University of Guillan (2016) and has published several papers about sociology and criminology of sport with a focus on gender differences. Her recent research has been published in multiple peer-reviewed journals such as Deviant Behavior, Journal of Drug Issues, International Criminal Justice Review, the International Journal of Offender Therapy and Comparative Criminology, and International Journal of Cyber Criminology. Tia Stevens Andersen is an Associate Professor in the Department of Criminology and Criminal Justice at the University of South Carolina. Her main areas of research include mentoring and other strength-based approaches to positive youth development, media constructions of girls’ violence, and gender and racial disparities in juvenile justice system processing. Appendix A: Items Compromising the Summated Scale, Low Constraints Item Response options Low shame Would you feel ashamed of yourself if you violate the COVID-19 guidelines issued by the Government? 1 (definitely would) to 4 (definitely would not) How big of a problem would feeling ashamed of yourself be for you if you violate the COVID-19 guidelines issued by the Government? 1 (a very big problem) to 5 (no problem at all) Low embarrassment Would most of the family members whose opinions you value lose respect for you if you violate the COVID-19 guidelines issued by the Government? 1 (definitely would) to 4 (definitely would not) Would most of your important others whose opinions you value lose respect for you if you violate the COVID-19 guidelines issued by the Government? 1 (definitely would) to 4 (definitely would not) How big of a problem would it be for you if your family members whose opinions matter to you lost respect for you because you violated the COVID-19 guidelines issued by the Government? 1 (a very big problem) to 5 (no problem at all) How big of a problem would it be for you if important others whose opinions matter to you lost respect for you because you violated the COVID-19 guidelines issued by the Government? 1 (a very big problem) to 5 (no problem at all) Appendix B: Items Compromising the Summated Scale, Motivations Item Response options Strain based I am strongly motivated to violate the Government-issued Covid-19 guidelines because I need to spend some time with my friends to relieve the stress of my daily life, and this is one of the reasons for violating health protocols.* 1 (completely agree) to 5 (completely disagree) I am strongly motivated to violate the Government-issued Covid-19 guidelines because when I am angry or frustrated from life events, spending time outside the home makes me feel good, and this is one of the reasons I violate health protocols.* 1 (completely agree) to 5 (completely disagree) I am strongly motivated to violate the Government-issued Covid-19 guidelines because to escape from daily strains, I sometimes engage in family gatherings without considering health protocols.* 1 (completely agree) to 5 (completely disagree) Social learning based I am strongly motivated to violate the Government-issued Covid-19 guidelines because it is consistent with my ethical standards and personal definitions. 1 (completely disagree) to 5 (completely agree) I am strongly motivated to violate the Government-issued Covid-19 guidelines because people around me do that in similar situations and I figured out it’s not wrong. 1 (completely disagree) to 5 (completely agree) I am strongly motivated to violate the Government-issued Covid-19 guidelines because people around me (whose opinions I value) do not regard the violation of the COVID-19 guidelines issued by the Government as a wrong behavior and this is one of my main reasons for COVID-19 misbehavior. 1 (completely disagree) to 5 (completely agree) * Items were reverse coded. Appendix C: Items Comprising the Summated Scale, Low Self Domain Self-control Item Response options I often act on the spur of the moment without stopping to think 1 (strongly disagree) to 5 (completely agree) I often try to avoid things that I know will be difficult 1 (strongly disagree) to 5 (completely agree) I lose my temper easily 1 (strongly disagree) to 5 (completely agree) When I am angry, other people better stay away from me 1 (strongly disagree) to 5 (completely agree) I often take a risk just for the fun of it 1 (strongly disagree) to 5 (completely agree) Sometimes I find it exciting to do things that are dangerous 1 (strongly disagree) to 5 (completely agree) Social concern  Moral intuitions When you decide whether something is right or wrong, to what extent are the following considerations relevant to your thinking: whether someone suffered emotionally 1 (extremely relevant) to 5 (not at all relevant)  Moral intuitions When you decide whether something is right or wrong, to what extent are the following considerations relevant to your thinking: whether someone cared for someone vulnerable 1 (extremely relevant) to 5 (not at all relevant)  Moral intuitions When you decide whether something is right or wrong, to what extent are the following considerations relevant to your thinking: whether some people were treated differently than other. 1 (extremely relevant) to 5 (not at all relevant)  Moral intuitions When you decide whether something is right or wrong, to what extent are the following considerations relevant to your thinking: whether someone acted unfairly. 1 (extremely relevant) to 5 (not at all relevant)  Empathy/sympathy I can easily understand how people are feeling even before they tell me. 1 (strongly agree) to 5 (strongly disagree)  Empathy/sympathy In general, the negative emotions of others (feelings like fear, anger, sadness, and embarrassment) greatly affect me. 1 (strongly agree) to 5 (strongly disagree)  Desire for close ties I desire to be accepted by those I communicate with or those whose opinion impress me (members of social and prestigious groups, adult authority figures, police officers, or neighbors.) 1 (strongly agree) to 5 (strongly disagree)  Conformity to others I rarely obey social norms, which are against my desires.* 1 (strongly agree) to 5 (strongly disagree)  Conformity to others Considering situations that I might find myself in with my close friends, I may break the rules that are accepted by most members of society, because of what my friends expect of me.* 1 (strongly agree) to 5 (strongly disagree) * Items were reverse coded. Appendix D: Interaction Plots Panel 1. The Moderation Effect of Low Peer Domain on the Relationship between Motivations and COVID-19 Misbehavior. Panel 2. The Moderation Effect of Low Family Domain on the Relationship between Low Constraints and COVID-19 Misbehavior. Panel 3. The Moderation Effect of Low School Domain on the Relationship between Low Constraints and COVID-19 Misbehavior. The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article. ORCID iDs: Mahmoud Sharepour https://orcid.org/0000-0002-1969-9419 John K. Cochran https://orcid.org/0000-0001-5227-1564 1. It should be noted that Agnew’s (2005) integrated general theory of crime (GTC) is distinct from his general strain theory (Agnew, 2001). 2. We also calculated the sample size needed to detect a medium effect size using the G*Power software with power (1-β err prob) set at 0.95 and α = 0.05, two-tailed. Results indicated a sample of 262 would be needed with 10 predictors (low family-domain, low school-domain, low self-domain, low peer-domain, low constraints, motivation, male, education, family member’s risky condition, and death experience from COVID-19 in family). 3. According to the Krejcie and Morgan (1970) sample size estimation, the acceptable sample is 360 students. To ensure the achievement of the appropriate sample size, 50 additional questionnaires were distributed (n = 410). ==== Refs References Agnew R. (2005). Why do criminals offend?: A general theory of and delinquency. Roxbury. Akers R. L. Sellers C. S. (2013). Criminological theories: Introduction, evaluation and application (6th ed.). Oxford University Press. Alessandri G. Filosa L. Tisak M. S. Crocetti E. Crea G. Avanzi L. (2020). Moral disengagement and generalized social trust as mediators and moderators of rule-respecting behaviors during the COVID-19 outbreak. Frontiers in Psychology, 11 , 2102. Alimohamadi Y. Holakouie-Naieni K. Sepandi M. Taghdir M. (2020). Effect of social distancing on COVID-19 incidence and mortality in Iran since February 20 to May 13, 2020: An interrupted time series analysis. Risk Management and Healthcare Policy, 13 , 1695–1700.33061703 Aminnejad R. Alikhani R. (2020). Physical distancing or social distancing: That is the question. Canadian Journal of Anesthesia/Journal canadien d'anesthésie, 67 (10 ), 1457–1458. Bao Z. Li D. Zhang W. Wang Y. (2015). School climate and delinquency among Chinese adolescents: Analyses of effortful control as a moderator and deviant peer affiliation as a mediator. Journal of Abnormal Child Psychology, 43 (1 ), 81–93.24962709 Barrios J. M. Benmelech E. Hochberg Y. V. Sapienza P. Zingales L. (2021). Civic capital and social distancing during the Covid-19 pandemic. Journal of Public Economics, 193 , 104310.33199928 Choi J. Kruis N. E. (2019). The effects of life domains on cyberbullying and bullying: Testing the generalizability of Agnew’s integrated general theory. Crime and Delinquency, 65 (6 ), 772–800. Cochran J. K. (2017). The effects of life domains, constraints, and motivations on academic dishonesty: A partial test and extension of Agnew’s general theory. International Journal of Offender Therapy Comparative Criminology, 61 (11 ), 1288–1308.26615039 Cutrín O. Gómez-Fraguela J. A. Maneiro L. Sobral J. (2017a). Effects of parenting practices through deviant peers on nonviolent and violent antisocial behaviors in middle-and late-adolescence. The European Journal of Psychology Applied to Legal Context, 9 (2 ), 75–82. Cutrín O. Gómez-Fraguela J. A. Sobral J. (2017b). Gender differences in youth substance use: The effects of parenting through a deviant peer group. Journal of Child and Adolescent Substance Abuse, 26 (6 ), 472–781. DeGarmo D. S. Forgatch M. S. (2005). Early development of delinquency within divorced families: Evaluating a randomized preventive intervention trial. Developmental Science, 8 (3 ), 229–239.15819755 DeGarmo D. S. Jones J. A. (2019). Fathering through change (FTC) intervention for single fathers: Preventing coercive parenting and child problem behaviors. Development and Psychopathology, 31 (5 ), 1801–1811.31489831 Demanet J. Van Houtte M. (2012). School belonging and school misconduct: The differing role of teacher and peer attachment. Journal of Youth and Adolescence, 41 (4 ), 499–514.21567214 Denson T. F. Capper M. M. Oaten M. Friese M. Schofield T. P. (2011). Self-control training decreases aggression in response to provocation in aggressive individuals. Journal of Research in Personality, 45 (2 ), 252–256. Duczmal L. H. Almeida A. C. L. Duczmal D. B. Alves C. R. L. Magalhães F. C. O. Lima M. S. D. Silva I. R. Takahashi R. H. C. (2020). Vertical social distancing policy is ineffective to contain the COVID-19 pandemic. Cadernos de Saúde Pública, 36 (5 ), e00084420. Eddy J. M. Kjellstrand J. M. Martinez C. R. Newton R. Herrera D. Wheeler A. Short J. W. Schumer J. E. Burraston B. O. Lorber M. F. (2019). Theory-based multimodal parenting intervention for incarcerated parents and their children. In Eddy J. M. Poehlmann-Tynan J. (eds.), Handbook on children with incarcerated parents (pp. 219–235). Springer. Elam K. K. Chassin L. Lemery-Chalfant K. Pandika D. Wang F. L. Bountress K. Dick D. Agrawal A. (2017). Affiliation with substance-using peers: Examining gene-environment correlations among parent monitoring, polygenic risk, and children’s impulsivity. Developmental Psychobiology, 59 (5 ), 561–573.28561888 Gottfredson M. Hirschi T. (1990). A general theory of crime. Stanford University Press. Grubb J. A. Posick C. (2018). Applying Agnew’s integrated theory of crime and delinquency to victimization risk: A contemporaneous and longitudinal examination. Criminal Justice Review, 43 (3 ), 289–308. Haidt J. Graham J. (2007). When morality opposes justice: Conservatives have moral intuitions that liberals may not recognize. Social Justice Research, 20 , 98–116. Hardin B. S. Smith C. V. Jordan L. N. (2021). Is the COVID-19 pandemic even darker for some? Examining dark personality and affective, cognitive, and behavioral responses to the COVID-19 pandemic. Personality and Individual Differences, 171 , 110504.33191963 Hirschi T. (1969). Causes of delinquency. Routledge. Huynh T. L. D. (2020). Does culture matter social distancing under the COVID-19 pandemic? Safety Science, 130 , 104872.32550745 Kabiri S. Shadmanfaat S. M. Choi J. Yun I. (2020). The impact of life domains on cyberbullying perpetration in Iran: A partial test of Agnew’s general theory of crime. Journal of Criminal Justice, 66 , 101633. Kabiri S. Shadmanfaat S. M. Howell C. J. Donner C. Cochran J. K. (2022). Performance-enhancing drug use among professional athletes: A longitudinal test of social learning theory. Crime & Delinquency, 68 (5 ), 867–891. Kim J. H. Marks F. Clemens J. D. (2021). Looking beyond COVID-19 vaccine phase 3 trials. Nature Medicine, 27 , 205–211. Knoll M. D. Wonodi C. (2021). Oxford–AstraZeneca COVID-19 vaccine efficacy. The Lancet, 397 (10269 ), 72–74. Krejcie R. V. Morgan D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30 (3 ), 607–610. Le T. T. Andreadakis Z. Kumar A. Román R. G. Tollefsen S. Saville M. Mayhew S. (2020). The COVID-19 vaccine development landscape. Nature Reviews Drug Discovery, 19 (5 ), 305–306. Li M. Chen J. Li X. Deater-Deckard K. (2015). Moderation of harsh parenting on genetic and environmental contributions to child and adolescent deviant peer affiliation: A longitudinal twin study. Journal of Youth and Adolescence, 44 (7 ), 1396–1412.25910772 Liska A.E. Krohn M. D. Messner S.F. (1989). Strategies and requisites for theoretical integration in the study of crime and deviance. In Messner S. F. Krohn M. D. Liska A. E. (eds.), Theoretical integration in the study of deviance and crime: Problems and prospects (pp. 1–20). State University of New York Press. Liu R. X. (2019). Harsh parental discipline and delinquency in mainland China: The conditional influences of gender and bonding to paternal grandparents. Sociological Focus, 52 (4 ), 274–291. Lunn P. D. Timmons S. Belton C. A. Barjaková M. Julienne H. Lavin C. (2020). Motivating social distancing during the Covid-19 pandemic: An online experiment. Social Science and Medicine, 265 , 113478.33162198 MacArthur G. Caldwell D. M. Redmore J. Watkins S. H. Kipping R. White J. Chittleborough C. Langford R. Er V. Lingam R. Pasch K. Gunnell D. Hickman M. Campbell R. (2018). Individual-, family-, and school-level interventions targeting multiple risk behaviors in young people. Cochrane Database of Systematic Reviews, 10 (10 ), CD009927. https://research-information.bris.ac.uk/ws/portalfiles/portal/185355798/Full_text_PDF_final_published_version_.pdf/ Maimon D. Howell C. J. (2020, May 26). The coronavirus pandemic moved life online – a surge in website defacing followed. The Conversation. Mann F. D. Kretsch N. Tackett J. L. Harden K. P. Tucker-Drob E. M. (2015). Person× environment interactions on adolescent delinquency: Sensation seeking, peer deviance and parental monitoring. Personality and Individual Differences, 76 , 129–134.25908885 Muftić L. R. Grubb J. A. Bouffard L. A. Maljević A. (2014). The impact of life domains on juvenile offending in Bosnia and Herzegovina: Direct, indirect, and moderating effects in Agnew’s integrated general theory. Journal of Research in Crime and Delinquency, 51 (6 ), 816–845. Ngo F. T. Fisher T. Ruiz R. A. (2022). Life domains, constraints, motivations, and intimate partner violence: Assessing the generality of Agnew’s general theory of crime and delinquency. Crime & Delinquency. Advance online publication. 10.1177/00111287221106951 Ngo F. T. Paternoster R. (2014). Contemporaneous and lagged effects of life domains and substance use: A test of Agnew’s general theory of crime and delinquency. Journal of Criminology, 2014 , 320486. Ngo F. T. Paternoster R. Cullen F. T. Mackenzie D. L. (2011). Life domains and crime: A test of Agnew’s general theory of crime and delinquency. Journal of Criminal Justice, 39 (4 ), 302–311. Nunally J. C. (1978). Psychometric theory. McGraw-Hill. Oosterhoff B. Palmer C. A. Wilson J. Shook N. (2020). Adolescents’ motivations to engage in social distancing during the COVID-19 pandemic: Associations with mental and social health. Journal of Adolescent Health, 67 (2 ), 179–185. Ozgenel M. Yilmaz F. Baydar F. (2018). School climate as a predictor of secondary school students’ school attachment. Eurasian Journal of Educational Research, 18 , 87–116. Pedersen M. J. Favero N. (2020). Social distancing during the COVID-19 pandemic: Who are the present and future noncompliers? Public Administration Review, 80 (5 ), 805–814.32836442 Piquero A. R. Jennings W. G. Farrington D. P. Diamond B. Gonzalez J. M. R. (2016). A meta-analysis update on the effectiveness of early self-control improvement programs to improve self-control and reduce delinquency. Journal of Experimental Criminology, 12 (2 ), 249–264. Şahin M. (2012). An investigation into the efficiency of empathy training program on preventing bullying in primary schools. Children and Youth Services Review, 34 (7 ), 1325–1330. Sanches C. Gouveia-Pereira M. Carugati F. (2012). Justice judgements, school failure, and adolescent deviant behavior. British Journal of Educational Psychology, 82(Pt 4), 606–621. Sen-Crowe B. McKenney M. Elkbuli A. (2020). Social distancing during the COVID-19 pandemic: Staying home save lives. The American Journal of Emergency Medicine, 38 (7 ), 1519–1520.32305155 Shadmanfaat S. M. Howell C. J. Muniz C. N. Cochran J. K. Kabiri S. Fontaine E. M. (2020). Cyberbullying perpetration: An empirical test of social learning theory in Iran. Deviant Behavior, 41 (3 ), 278–293. Shadmanfaat S. M. Howell C. J. Muniz C. N. Cochran J. K. Kabiri S. Richardson D. A. (2018). The predictive ability of self-control and differential association on sports fans’ decision to engage in cyberbullying perpetration against rivals. International Journal of Cyber Criminology, 12 (2 ), 362–375. Teding van Berkhout E. Malouff J. M . (2016). The efficacy of empathy training: A meta-analysis of randomized controlled trials. Journal of Counseling Psychology, 63 (1 ), 32–41.26191979 Thu T. P. B. Ngoc P. N. H. Hai N. M. (2020). Effect of the social distancing measures on the spread of COVID-19 in 10 highly infected countries. Science of The Total Environment, 742 , 140430.32623158 Toraman C. Aycicek B. (2019). An investigation of the relationships between attachment levels to school and the variables of the perception of school life quality and peer pressure among high school students. Journal of Education and Training Studies, 7 (1 ), 76–84. Triberti S. Durosini I. Pravettoni G. (2021). Social distancing is the right thing to do: Dark triad behavioral correlates in the COVID-19 quarantine. Personality and Individual Differences, 170 , 110453. Vold G. B. Bernard T. J. Snipes J. B. Gerould A. L. (2010) Theoretical criminology (6th ed.) Oxford University Press. WHO. (2022). World Health Organization coronavirus disease (COVID-19) situation dashboard. WHO. https://covid19.who.int/ Wikström P.-O. H. Oberwittler D. Treiber K. Hardie B. (2012). Breaking rules: The social and situational dynamics of young people’s urban crime. Oxford University Press. Wikström P.-O. H. Treiber K. (2017). Beyond risk factors: An analytical approach to crime prevention. In Teasdale B. Bradley M. S. (eds.), Preventing crime and violence (pp. 73–87). Springer. Wündrich M. Schwartz C. Feige B. Lemper D. Nissen C. Voderholzer U. (2017). Empathy training in medical students–a randomized controlled trial. Medical Teacher, 39 (10 ), 1096–1098.28749198 Xiong R. Li S. D. Xia Y. (2020). A longitudinal study of authoritative parenting, juvenile delinquency and crime victimization among Chinese adolescents. International Journal of Environmental Research and Public Health, 17 (4 ), 1405. Yezli S. Khan A. (2020). COVID-19 social distancing in the Kingdom of Saudi Arabia: Bold measures in the face of political, economic, social and religious challenges. Travel Medicine and Infectious Disease, 37 , 101692.32330561 Zhang Y. Day G. Cao L. (2012). A partial test of Agnew’s general theory of crime and delinquency. Crime and Delinquency, 58 (6 ), 856–878.
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==== Front Environ Plan B Urban Anal City Sci Environ Plan B Urban Anal City Sci spepb EPB Environment and Planning. B, Urban Analytics and City Science 2399-8083 2399-8091 SAGE Publications Sage UK: London, England 10.1177_23998083221142863 10.1177/23998083221142863 Special Issue: Urban Analytical Approaches to Combatting Covid-19 Deploying geospatial visualization dashboards to combat the socioeconomic impacts of COVID-19 https://orcid.org/0000-0002-7383-2751 Praharaj Sarbeswar PhD https://orcid.org/0000-0003-1374-9400 Solis Patricia PhD https://orcid.org/0000-0002-2881-0668 Wentz Elizabeth A PhD Knowledge Exchange for Resilience, School of Geographical Sciences and Urban Planning, 7864 Arizona State University , Tempe, AZ, USA Sarbeswar Praharaj, Knowledge Exchange for Resilience, School of Geographical Sciences and Urban Planning, Arizona State University, 976 S Forest Mall, Tempe, AZ 85287-1004, USA. Email: [email protected] 7 12 2022 7 12 2022 23998083221142863© The Author(s) 2022 2022 SAGE Publications This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. COVID-19 dashboards with geospatial data visualization have become ubiquitous. There is a growing sense of responsibility to report public health data pushing governments and community organizations to develop and share web-based dashboards. While a substantial body of literature exists on how these GIS technologies and urban analytics approaches support COVID-19 monitoring, their level of social embeddedness, quality and accessibility of user interface, and overall decision-making capabilities has not been rigorously assessed. In this paper, we survey 68 public web-based COVID-19 dashboards using a nominal group technique to find that most dashboards report a wealth of epidemiologic data at the state and county levels. However, these dashboards have limited emphasis on providing granular data (city and neighborhood level) broken down by population sub-groups. We found severe inadequacy in reporting social, behavioral, and economic indicators that shape the trajectory of the pandemic and vice versa. Our survey reveals that most COVID-19 dashboards ignore the provision of metadata, data download options, and narratives around visualizations explaining the data’s background, source, and purpose. Based on these lessons, we illustrate an empirical experiment of building a dashboard prototype—the COVID-19 Economic Resilience Dashboard in Arizona. Our dashboard project demonstrates a model that can inform decision-making (beyond plain information sharing) while being accessible by design. To achieve this, we provide localized data, drill-down options by geography and sub-population, visualization narratives, open access to the data source, and accessible features on the interface. We exhibited the value of linking pandemic-related information with socioeconomic data. Our findings suggest a pathway forward for researchers and governments to incorporate more action-oriented data and easy-to-use interfaces as they refine existing and develop new information systems and data analytics dashboards. COVID-19 dashboards public health GIS urban analytics Virginia G. Piper Charitable Trust https://doi.org/10.13039/100014024 edited-statecorrected-proof typesetterts10 ==== Body pmcIntroduction The rise in geospatial data availability in cities has encouraged authorities to invest in ways to explore, operationalize, and visually communicate vast amounts of information. There has been a growing trend of public-facing dashboards as instruments that policymakers use to integrate and visualize multi-agency data to monitor and respond to emergency events and organizational performance issues (Lee et al., 2015; Mattern, 2015). Dashboards are software tools enabling information visualization and data storytelling through maps, graphs, diagrams, indicators, and other interactive widgets, consolidated and arranged on a single screen or a webpage (Few, 2006; Rojas et al., 2020). Dashboards are dynamic visualizations because they are programmed to update as new data are released (Batty, 2015), helping the users track and compare over time and space to support real-time decision-making. The COVID-19 pandemic triggered a deluge of data dashboards that visualize cases of infection and fatalities over time and space. These dashboards emphasize the importance of spatial thinking and the effectiveness of geospatial technologies in understanding Covid-19 (Dangermond et al., 2020; Praharaj et al., 2022). However, all these dashboards are not created equal—in their layout, structure, visual flair, content, and navigability, nor do all communities access the data equally (Fareed et al., 2021; Lan et al., 2021). For all the COVID-19 data, graphs, and maps available to the decision-makers, the global response has been chaotic, inconsistent, and in places disastrous, implying that the mass visualization of inputs does not necessarily lead to better outputs (Budd et al., 2020). Stephen Few (2006) defines dashboards as a “visual display of the most important information needed to achieve one or more objectives.” Dashboard embodies the many ways of visualizing a variety of data that is representable, contextualizable, and intelligible to a non-expert target audience and can be used as a decision-support tool by governments, corporations, urban stakeholders, and communities (Batty, 2015; Kitchin, 2014; Mattern, 2015). A Scopus database search within article titles and abstracts reveals that 321 documents were published with the “COVID-19 dashboard” keyword as of 5th December 2021. The core focus of these projects has been on providing information to the public, enabling place comparisons, and monitoring public health scenarios. Ivanković et al. (2021), in an assessment of 158 COVID-19 dashboards, found that while these visualizations overwhelmingly reported public health indicators (e.g., cases, deaths, and hospitalizations), only a handful revealed the pandemic’s impact on the social and economic profile of communities. Lack of local and disaggregated data (by age, sex, socioeconomic status, and ethnic or racial groups) restricts dashboards’ utility for decision-making purposes and poses a risk of the public not being informed about these critical (and modifiable) differences. Furthermore, Pietz et al. (2020) state that less than 10% of dashboards explicitly stated the purpose and intended user, which raises questions about their efficacy. Previous research also shows the underuse of explanatory narratives in the widely used single-screen dashboards (Chiang, 2011) that are proven to clarify complex data for less-data-savvy users to use the information in their decision-making confidently. Overall, existing literature points to the need for dashboards to explore the connections between public health indicators and socioeconomic patterns to improve healthcare response mechanisms (Budd et al., 2020; Fareed et al., 2021; Lan et al., 2021; Pietz et al., 2020). Further research is necessary to examine the factors that make dashboards more fit for purpose and actionable in the context of COVID-19 and in general. The flurry of covid-19 dashboards is somewhat a technological response to resilience challenges at a time when we are experiencing that existing social and policy mechanisms are insufficient to deal with new kinds of global change. However, dashboards that communicate only epidemic indicators while being disconnected from social and economic contexts are less likely to influence change in how our communities consume data to prepare for and respond to emerging shocks (Crepaz and Arikan, 2021; Dangermond, 2020). While they might still be useful tools for policymakers, their potential for wider public dissemination to induce behavioral change and situational awareness among communities is limited. This study adopts a novel approach to emphasize the role of social learning (Coe et al., 2001), engaging with socioeconomic aspects of the pandemic to organize and inform communities. Our hypothesis is that disasters may provide windows of opportunity to transform traditional response mechanisms and build new narratives that the enhancement of community-based knowledge networks through tools such as data dashboards will provide pathways to a stronger and more effective model of community resilience (Sharifi et al., 2021; van der Voorn and de Jong, 2021). Our research particularly focuses on providing a socially embedded data and visualization interface for augmenting the technological capacity of communities to comprehend rapidly evolving issues and address them in a timely and efficient manner. This research advances the ongoing innovations in data analytics and urban science to shape community-focused decision-support systems (Kourtit and Nijkamp, 2018; Kitchin, 2014; Mattern, 2015; Pettit et al., 2017) to enable evidence-based and near-real-time decision-making. This work is grounded in the fact that building community resilience in response to emerging challenges requires a combination of timely data at the local scale (Haraguchi et al., 2022) and easy-to-use decision-support tools (Batty, 2015) that can inspire and organize local communities to initiate local action. Drawing on the lessons learned from the critical literature, we outline a community-driven approach to identify pressing resilience issues and deploy our dashboard tool on targeted areas for maximum community benefit. This approach addresses important gaps highlighted by Pettit et al. (2017) who suggested that dashboards often fail to engage with local issues as they provide high-level executive data and are often designed as a general instrument for conveying a range of discrete information without a clear delineation of expected users. Our research emphasizes a tool that focuses on a single aspect of economic resilience for tangible outcomes while outlining how digital data can be collected, processed, and disseminated through “public dashboards” during the event of a disaster to enable local communities to gain critical knowledge, decipher complex evolving issues, and prepare responses to the current and future crisis. This article explores 68 publicly available COVID-19 dashboards to identify whether the data presented over these dashboards were socially embedded and actionable to a diverse target audience. The goal was to examine which design elements make some dashboards easier to navigate, more inclusive, and more actionable than others. Based on the lessons from the case study analysis, we developed a dashboard prototype: Economic Resilience Dashboard that brings together multi-agency data to capture the links between the COVID-19 pandemic and the local economic and social dynamics in Arizona, US. The dashboard prototype demonstrates a model that can inform decision-making (beyond basic information sharing) while being accessible and actionable by design. As Mattern (2015) argues, data generated from complex systems cannot be understood without epistemological clarity, and as most of the data on COVID-19 dashboards is sanitized and treated, we investigate the broader knowledge and policy implications of these technological framing of public health crisis (Crepaz and Arikan, 2021). This study’s findings culminate into a set of guidelines and recommendations for dashboard designers to implement robust data visualization tools that are fit for use—meeting the specific information needs of targeted stakeholders. Critical assessment of the COVID-19 dashboards We assessed a sample of 68 publicly available web-based COVID-19 dashboards across the States in the US, Canada, and several other countries designed to help people better understand the evolving scenarios of COVID-19. The principal criteria for the selection of the dashboard were the authoritativeness of the projects, the diversity of actors involved in their development, and openly available tools accessible to a wide range of users. The first set of dashboards selected for this assessment is developed and maintained by the US States. These projects provide authoritative information for a broad range of stakeholders, supporting both policy actions and general awareness among communities. The samples also include renowned non-profit sector-generated dashboards (New York Times dashboard (NYTD), COVID Act Now (CAN), and The Atlantic’s COVID Tracking Project) and academic-sponsored projects like the Johns Hopkins Dashboard. These projects are also open and authoritative nonpartisan solutions attracting a diverse audience. Globally, the survey focused on the WHO Coronavirus (COVID-19) Dashboard, and several other state-sponsored projects in Canada and European countries. The list of dashboards assessed is presented in Supplementary Table S1. We find that 62 out of the 68 dashboards (91.18%) reported data at the county/district level, and all the assessed samples had state-level information. Just over 16% (11/68) of the dashboards showed city-level data, and none had numbers for the metropolitan statistical areas. Our analysis of COVID-19 dashboards further reveals that 9.24% (6/58) of the samples provided data going down to census tracts or postcode level, and none made pandemic statistics accessible for US public use microdata areas (PUMA). These trends highlight that dashboard makers primarily focus on providing macro-level aggregated data with minimal emphasis on granular data dissemination at the scale of local communities and neighborhoods. The findings are important as previous research (Fareed et al., 2021; Ivanković et al., 2021; Pietz et al., 2020) established that local data provision significantly improves public health decision-making abilities and dashboards’ actionability. Our analysis of the frequency of indicator themes reported by the dashboards presented in Table 1 highlights that COVID-19 dashboards overwhelmingly focused on reporting infection cases and deaths (68/68, 100%), testing rates and positivity (52/68, 76%), and hospitalization status (47/68, 69%). Indicators reported at moderate frequency are hospital bed, ICU, and ventilator capacities (42/68, 62%) and vaccinations (54/68, 79%). While the public health and epidemiological indicators were prominent on these COVID-19 dashboards, the emphasis on social, behavioral, and economic indicators was limited. Except for the state of California, no other dashboard provided data on the social impacts of the pandemic (e.g., measuring health equity, evictions, and food scarcity). A meager 4% (3/68) of dashboards (including the state of Ohio and Pennsylvania) presented data on changing economic and employment scenarios during the pandemic. Just over 10% (7/68) reported data on public adherence to restrictions, self-reporting, and the community’s behavioral response to various emergency orders, public restriction, and actions designed to safeguard people. Eight dashboards out of the 68 samples (California, Pennsylvania, and Michigan) disseminated some form of COVID-19 future projections or risk models). Ivanković et al. (2021), in an assessment of COVID-19 dashboards across 53 countries, found a strikingly similar trend of underreporting of social and economic indicators that limits the user’s ability to explore the links of socioeconomic outcomes inflicted by the pandemic.Table 1. Characteristics of the assessed COVID-19 dashboards (N = 68). Value (n) % Frequency of indicator themes reported  COVID-19 cases and deaths 68 100  Testing 52 76  Hospitalization status 47 69  Hospital bed, ICU, ventilator capacities 42 62  Vaccinations 54 79  Future projections/risk models 8 12  Mobility changes 6 9  Impacts on the economy and employment 3 4  Social impacts (evictions, food scarcity, etc.) 2 3  Public adherence to restrictions, self-reporting 7 10  Economic relief and packages 2 3 Data provision by population sub-groups  Age 54 79  Sex 44 65  Pediatric (children) 12 18  Pregnant 3 4  Ethnicity 47 69  Race 49 72  Income or socioeconomic status 0 0  Comorbidities 5 7  Others (schools, correctional facilities, etc.) 11 16 Table 1 summarizes the COVID-19 dashboard assessment of the provision of information by population sub-groups, indicating to what extent these tools offer disaggregation options. We found that the 68 dashboards offered eight types of breakdowns that allow users to investigate data by population sub-groups. Of these, the most common breakdowns included age (54/68, 79%), sex (44/68, 65%), ethnicity (47/68, 69%), and race (49/68, 72%). Although less frequently reported, other breakdowns included pediatric information (12/68, 18%) and schools and correctional facilities (11/68, 16%). Only 4% of dashboards (3/53) provide granular data on pregnant women and comorbidities with preexisting health conditions. None of the dashboards present data breakdowns by income or socioeconomic status. The analysis reveals that many COVID-19 dashboards, including those developed by Connecticut, Illinois, Iowa, Kansas, Alaska, and North Carolina, do not provide disaggregation options for viewing population sub-group level data. Kitchen (2014) argues that dashboard projects of this nature often translate into technological framing of a problem; rather, they should be designed as a humane solution that is cognizant of the context, people, and underlying unequal societies that these tools address. We assessed the design and functionality of the dashboards (n = 68) and analyzed the data (Supplementary Figure S1) to indicate the commonly used visualization techniques and the features that characterize an effective dashboard. The analysis shows that over one-third (28/68) of dashboards had a single-screen view, where all the data visualization is fitted on a set view with no option for up-and-down navigation or scrolling. The more favorable option was a multiple granular view dashboard interface which allows users to navigate across pages and scroll up and down over the webpage. The second option provides more space to align data visualization and integrate textual narratives alongside visuals. 54% of the dashboards (37/68) used narratives to describe the visualizations. The data download option—an essential dashboard element found missing in over half the dashboards (33/68). Similarly, 60% of the samples (41/68) did not provide metadata that describes critical information, such as the purpose of the data, time and date of creation, data quality, source, and the process used to create and explore the data. Most dashboards (48/68, 71%) included some user interaction element. For example, the New York Times dashboard provides dynamic click-to-filter options, where clicking on any chart or map creates a quick filter that applies to all dashboard data, delivering new insights instantly. Another interesting finding was that a high share of dashboards (36/68, 53%) did not use a color palette that meets accessibility standards. Less than half of these tools (31/68, 46%) used icons and menus that allow users to navigate data seamlessly. These are some of the fundamental elements of inclusive and accessible dashboards (Batty, 2015; Few, 2006). We also learned that 85% (58/68) of the samples presented visualizations in distinct sections to guide users through the data, an increasingly popular storytelling feature (Elias et al., 2013; Knaflic, 2015) in dashboard design practice. Methods and approach for the Economic Resilience Dashboard development Building on the lessons learned from the COVID-19 dashboard assessments in the previous section, we categorize the dashboard design observations and development challenges. We further identify approaches to address the issues and challenges scientifically and technically. The primary challenge with dashboard design we found is that higher-level aggregated data is less compelling and actionable. Broad data may provide interesting insights, but most agencies and groups interacting with such data lack the authority or responsibilities to act at that level. Our goal was hence to provide granular local data to assist local stakeholders in identifying key issues and solutions. As Pettit (2017) argues, integrating micro-level real-time data can assist executives and citizens in responding to disruptions in a timely and efficient manner. We collected economic data across spatial scales, the State, County, metro areas, and cities on several core indicators and sub-measures (Supplementary Table S2) that can quantify and visually capture the immediate economic loss and the policy-induced social processes during the pandemic. We also offer data segregation by population sub-groups (e.g., race, ethnicity, and education) that enlighten users about the unequal effects of the pandemic. Another design issue for at-a-glance dashboards is the lack of ability to explore time-series information (Praharaj and Wentz, 2022) and data segregation to drill into the history of data metrics (Kitchin, 2014). We address this limitation by providing time-series data at various frequencies for users to examine weekly, monthly, and annual trends. Our dashboard evaluation indicated the issue of limited background information and interpretation of data available over the single-screen dashboards, working as a barrier for many users. We tackle this fundamental design challenge by adopting a multiple-view scrolling webpage dashboard allowing more space to describe the contextual information behind the data and lay visualizations in clearly defined sections that improve users’ understanding and navigability. The previous section noted an acute lack of socially embedded data provided through the COVID-19 dashboards as they overwhelmingly focused on reporting public health data. This approach limits the authority’s ability to pinpoint disproportionately affected communities and establish connections between the pandemic and social vulnerability. Our dashboard emphasizes novel factors, including changes in earnings, delayed medical care, evictions and foreclosures, and food shortages that help communities visualize the interaction between economic changes and social stress. We designed a four-layer dashboard technical architecture (Figure 1) seamlessly connected to produce the dashboard's visual analytics interface. The first, database layers act as an edge-level device, providing secure data feeds. We connected with the servers of data providers through APIs to retrieve published historical time-series data in JSON data-interchange format. Specific processing and parsing were applied on machine-readable datasets in the controller logic to extract the relevant variables within the dataset and to render it into the real-time visualizations of the dashboard. In the integration layer, each file was stored locally, new data was refreshed as it became available, and we simultaneously used ArcGIS Pro and Tableau Business Intelligence (BI) software for layer joining and blending to match features and geographies to ensure the consistency of datasets from different sources. The third layer provided the platform for creating various maps, charts, widgets, and navigation menus assembled into the dashboard. We published the dashboards to a server to generate JavaScript codes for deploying the dashboard visualizations to a web page https://resilience.asu.edu/economic-resilience-dashboard. The user interface (fourth layer) provides the output view to navigate different metrics visualizations. We have optimized the dashboard for the visualization to adjust on both computer/laptop and mobile devices, and the interface allows users to enter full-screen view mode for each section for deeper dives into the data.Figure 1. Technical architecture and workflow for the Economic Resilience Dashboard development. Results Overview and analysis of the Economic Resilience Dashboard We present an overview of the different modules, sections, and infographics of the Economic Resilience Dashboard tool in Figure 2. The dashboard tool supports communities, planners, non-profit responding organizations, and policymakers to explore and query data to formulate questions and examine responses. They can evaluate issues like the monthly change in the unemployment rate in a County, or which sector experienced the most job loss in the last quarter. The graphical user interface adheres to the Model-View-Controller (MVC)—a three-part design pattern, dependent and connected, that allows the controller to receive handler inputs. It manages and sends a query to the model, which contains the data and the rules for carrying out a specific task. The interface provides users with a set view highlighting the most important trends, and detailed information can be visualized through drill-down buttons, navigation panels, map-based selection and filtering, and timeline sliders placed in strategic locations across the interface. The dashboard tool gives users the capability to perform historical data analysis in over 15 counties, seven metropolitan statistical areas, and 91 towns in Arizona. The dashboard is hierarchically organized into five different modules (see Supplementary Figures S2–S5 in Supplementary Materials) to enable a connected dashboard environment to be navigated across indicators from summary-to-detail exploration within a single system. The interface ultimately addresses the characteristics of exploratory dashboards (Kitchin, 2014).Figure 2. A screenshot of the Economic Resilience Dashboard. Source: https://resilience.asu.edu/economic-resilience-dashboard. The analysis presented in the dashboard links the economic trends with demographic information (e.g., race, ethnicity, and education) to examine equity issues around the COVID-19 impact on communities. The tool integrates weekly data from the Census household pulse survey, including households’ perceptions of loss in employment income, difficulty in paying household expenses, housing insecurity and the likelihood of eviction, food scarcity, and delayed medical care. Such data help users understand correlations and interdependencies between COVID-19 and social dynamics. The best practice design approach to information dashboard design (Few, 2006) is used to integrate a range of charts, maps, and big number KPIs to communicate and visualize the data. Line charts in our dashboard analyze indicators with historical time-series information. Donut charts visually capture proportional data such as the share of unemployment insurance claims by different racial/ethnic groups. The butterfly charts capture two-dimensional data (sector-wise total nonfarm employment and annual change in jobs generated by these sectors) and bar charts visualize categorical and continuous datasets (e.g., unemployment rate by cities). The dashboard also has KPI text indicators to highlight key facts and outliers, such as which county shows positive changes in unemployment in the last month or quarterly changes in wages across regions. The Economic Resilience Dashboard placed significant emphasis on map-based analysis to provide users with a spatial understanding of how the pandemic impacts different regions. We follow the approach of geospatial BI dashboards (Badard and Dubé, 2009; Presthus and Canales, 2015) to integrate spatial querying and filtering tools in our dashboard. The map area selection commands enable users to select different geographic units, dynamically changing the views over charts, graphs, and numbers. An introduction for the overall dashboard was provided first, followed by the background descriptions for each of the five sections to inform users about why we chose those indicator data, how they help us measure what we are trying to measure, and the sources of information. The dashboard provides links to the original data repositories to maintain transparency. The tool supports the download of maps, visualizations, and underlying datasets. Young and Kitchin (2020) found that an explanation of the history and epistemology of data and the provision of data and chart download play a crucial role in engaging users to create a participatory environment over dashboards. The first section of the dashboard presents the visualization output for the unemployment rate and labor force data (see Supplementary Figure S5). It provides a snapshot of how a combination of maps, various types of charts, and indicator KPIs were used to illustrate the changing state of the Arizonan economy while flagging key issues. Standard navigation tools, including a time slider and dropdown menus, were deployed to show historical unemployment data since 2018 visualized over varying geographic scales ranging from the State and Counties to the level of metropolitan areas and individual cities in Arizona. These tools allow users to select and visualize data for a defined timeframe and geography. KPIs were used strategically to highlight which regions were the worst hit and the ones that showed remarkable resilience to the COVID-19 economic shock. Tooltips were used throughout the visualizations allowing users to view background and contextual information, definitions, and description of the data when hovering over dashboard elements. The line chart reveals the striking impact of the pandemic on the unemployment rate in most places, including in the most populated Phoenix-Mesa-Scottsdale metropolitan area, where the unemployment rate shot up to 13.5% in April 2020 from 4% in February of the same year. The data allows researchers to investigate further questions, such as the linkage of these unemployment trends with government policies, including vaccination, lockdown and reopening, social distancing orders, and the COVID-19 Economic Impact (Stimulus) Payments. The second section shows data on weekly unemployment insurance claims highlighting which geographic regions, industry sectors, and socioeconomic groups received the most filings, and the changes observed every week (see Supplementary Figure S3). The maps and charts in this section and throughout the dashboard were built with color palettes that conform with accessibility standards (Healy, 2018) to engage with diverse users, including people with color blindness. Interactive features are embedded, which allow dynamic changes to multiple views and indicators when users select a county from the dropdown menu. The map highlights how the unemployment insurance claims in Maricopa County shot up from 1003 claims in February last week to over 48,000 in the first week of April 2020. The line chart establishes an apparent relationship between different waves of infections and related increases in claims by individuals due to job losses. A significant finding is that specific industries have emerged as most vulnerable to the COVID-19 effects. Workers from five industries—accommodations and food services, healthcare and social assistance, retail trade, administration, and manufacturing—received over 250,000 claims in Arizona during the initial COVID-19 outbreak (April to May 2020). Section 3 of the Economic Resilience Dashboard tool highlights nonfarm employment trends, monthly changes in employment by industry, and weekly average hours and wages/earnings of workers on the payroll (see Supplementary Figure S4). A significant drop in nonfarm employment was found during COVID-19, with a loss of 244,300 jobs between February and April 2020. The butterfly chart showing the employment change by sector points out that the leisure and hospitality sectors lost an overwhelming 138,000 jobs during that period, followed by 34,000 job losses in trade, transportation, and utilities, and 28,000 jobs in education and health services. While jobs were lost across sectors as an effect of COVID-19, the bar chart analysis suggests a trend of increasing wages/earnings during the pandemic. The dashboard also provides BAN (Big Ass Number) indicators to draw attention to the regions showing the most significant gains and losses in employment and earnings. A BAN is a big number meant to attract attention from end-users and is popularly used in business analytics dashboards (Badard and Dubé, 2009). The dashboard interface shows BANs as bold, big, and colored in a way that makes users notice them. The last two sections of the dashboard (see Supplementary Figure S5) explore the linkage and impact of the COVID-19 pandemic with the socioeconomic profile of communities. We visualize the weekly Census Household Pulse Survey data from the US Census Bureau (Schanzenbach and Pitts, 2020) to show the social and economic impacts of the COVID-19 pandemic on households. The dashboard visualization reveals severe issues; over half of the households surveyed in the Arizona and Phoenix metro area reported some form of loss in employment income by July 2021. Nearly 40% of the households faced a delay in accessing medical care in the State. Over a quarter of the households faced housing insecurity amidst the first wave of the pandemic. This analysis of the Census data also indicates how resilient our communities are and their ability to reconstruct and recover through the economic shocks, as our data suggest consistent improvements in the economic scenario since the relaxation of COVID-19 policies. The analytics on CARES Act fund allocations data, too, is a classic measure of the policy-induced dynamic ability of the economy to recuperate from disruptions through financial stimulus from the governments and donors. This dashboard section provides intuitive icons (Pettit et al., 2017) placed in strategic locations of the web interface for end-users to hover over the icons to view definitions and explanations of keywords (e.g., housing insecurity, food scarcity, and the likelihood of evictions). Usability assessment of the dashboard We performed a comprehensive evaluation experiment to understand how the dashboard meets the users’ needs and to determine future research and development priorities. We designed a set of usability metrics for assessing the dashboards based on established literature (Dowding and Merrill, 2018; Forsell and Johansson, 2010; Nielsen and Molich, 1990). User ratings on a five-point scale were obtained on these metrics through an online questionnaire survey (O’Brien and Cairns, 2015) with 30 survey participants. A detailed note on the participant backgrounds and recruitment process is outlined in Supplementary Material, Page 11. The first set of questions focused on assessing the suitability of indicators used in the dashboard and the overall clarity of understanding or ease of grasping the information presented in various sections of the tool. Lan et al. (2021) and Kitchin (2014) in their dashboard studies highlighted that user experience and engagement over visual dashboards are largely influenced by the nature of metrics provided and the clarity of information for a range of users. The second round of questions delved into the navigability and ease of data exploration (Letouzey, 2012) as well as the visual and aesthetic appeal of the various maps, charts, and widgets presented in the dashboard. Based on evidence from earlier studies by Pettit et al. (2017) and Fareed et al. (2021), we included questions to measure the users’ level of trust in the data sources used in the dashboard, the interactivity of different visualization elements, and whether the dashboard offers new knowledge and novel understandings to users. The last set of questions assessed the usefulness of the dashboard for decision-making for various user groups and based on the experience whether the users would recommend the tool within the wider community for extensive dissemination. We included these metrics based on previous studies (Batty, 2015; Kourtit and Nijkamp, 2018) that found dashboards that are actionable and useful for decision-making purposes are more likely to be used by the community. Figure 3 provides the results from the dashboard usability survey, where experts provided one to five ratings on a set of questions. A low rating of one—two suggests negative sentiment, whereas a higher four—five rating indicates a significantly positive opinion. A rating of three would mean a somewhat neutral response. We find that overall, 88% of respondents rated 4 to 5 indicating very high suitability of the indicators presented over the dashboard and that the metrics/themes adequately capture the critical components of the evolving economic scenario in Arizona during and post-pandemic. In response to Question 2 on the clarity of understanding, just over 70% rated 4–5, signaling that the dashboard provides information that is easy to understand, and digest. A sizeable 23% of respondents assigned a rating of three, taking a neither-agree nor-disagree positioning on this question. 74% believed the dashboard is easy to navigate and over 80% positively opined on the visual and aesthetic appeal of the data representation. 76% of the experts reposed a high level of trust in the data used for dashboard analytics as well as 92% suggested that the dashboard offers new knowledge to advance resilience thinking. Nearly 87% of survey respondents found that the dashboard is highly interactive and engaging, and an equal share would recommend the tool to their colleagues and community. A modest 63% believed that the dashboard is useful for decision-making. However, one-third of the respondents did not strongly agree with the question (providing a 3-point rating) indicating that further work and research are required to make the dashboard actionable. The usability ratings are further analyzed by the job roles and sectors represented by the respondents in Supplementary Figures S6 and S7 (pages 11–12 in Supplementary Material).Figure 3. Overall usability ratings (N = 30) on the Economic Resilience Dashboard. Discussion and findings This paper has examined and consolidated how public data can be collected and visualized through information dashboards and novel interaction techniques. We assessed the state of the art of public web-based COVID-19 dashboards in the US and worldwide to identify standard features, indicators, data granularity, and the design and functionality of these tools that make them engaging and actionable. We developed the prototype of the Economic Resilience Dashboard in Arizona, drawing on the lessons learned from the global dashboard review. The findings indicate that the COVID-19 dashboards ultimately share a common aim: to serve as both a communication tool and a decision-support system to respond to the COVID-19 pandemic. However, we find the approach to dashboard development varies from case to case in terms of their indicator selection, the geographical scale of data, granular data provision by population sub-groups, and the functional elements on the interface. We learned the common features that these visualization tools display and the elements that distinguish effective, more actionable, and inclusive dashboards from others. The study highlights that while there is no single approach to dashboard design, several aspects are critical for the successful application of such technologies, explained in the following paragraphs. Traditional information design textbooks define dashboards as a single-screen representation of various metrics (Few, 2006). While at-a-glance dashboards do offer users a span of control over a large amount of data, our analysis reveals that the COVID-19 dashboards are revolutionizing the design approach. We found that 57% of the dashboards were built using a multiple-view scrolling webpage format (e.g., New York Times and California State COVID-19 dashboards) against 43% of projects sticking to the traditional single-screen layout. At-a-glance dashboards show overall underuse of explanatory narratives (due to limited space on the interface), which are proven techniques for clarifying complex information for end-users, making them motivated and confident in using the data in their decision-making (Ivanković et al., 2021). A more extended viewing area on the multiple-view dashboards, such as the one provided in the Economic Resilience Dashboard, allows laying visualizations in distinct sections, building narratives around the maps, graphs, and charts to engage visitors, and attract them to spend longer on the site (Sarikaya et al., 2018). The custom-made multiple-view dashboard design approach is emerging much more robust than the standard single-screen layout in improving interpretation and storytelling, reducing cluttering of information and widgets, and leading to an overall improvement in delivery and communication. Existing literature established that data communicated over dashboards are not always neutral and value-free, independent of external influence, and always treated and engineered before sharing (Batty, 2015; Kitchin, 2014; Mattern, 2015). This study found that while COVID-19 dashboards reveal a broad set of epidemiological data (e.g., cases, deaths, hospitalizations, and vaccinations), they also in several cases hide critical data on population sub-groups, including ethnicity, income status, and comorbidities. There is also a severe gap in reporting social, behavioral, and economic impacts and interdependencies with the COVID-19 pandemic. Our findings are consistent with previous research (Lan et al., 2021) that noted without estimating and sharing data about meaningful population sub-groups, communities are at risk of not being educated about these issues. We find that the provision of segregated local data and data breakdown options over public dashboards offers novel opportunities for exploring interrelations between epidemiological trends and social determinants (e.g., economy and unemployment, behavioral responses to government policies, and equitable recovery). Inclusive design strategies determine the credibility and trustworthiness of dashboards. As Kitchin (2014) suggests, dashboards act as translators rather than mirrors, and it’s the designers who frame how data are visualized and thus what the user can see, what questions can be asked, and how the answers are displayed. We found that inclusive and convincing dashboards explicitly describe what data they choose, justify their selection, and provide a point of truth access to the data sources. Contextual information, metadata attached to visualizations, links to open data repositories, and options for downloading maps and charts over dashboards provide clarity and transparency while encouraging replicability and iterative improvements in outcomes. Our review suggests that more than half of the State dashboards in the US failed to recognize these elements, indicating the need for more transparency in public reporting of pandemic-related data. We demonstrate a range of inclusive design elements in the dashboard tool, including the use of an accessible color palette, info icons and signage, storytelling with clear sections, and data download menus, which improves community engagement, accessibility to a range of users, and serves to leverage the two-way communication potential of dashboards. Further research could explore the development of uniform standards to guide dashboard designers across States and Countries to produce inclusive and trustworthy data tools and bring uniformity to public health data reporting. The scientific novelty of this work advances the COVID-19 dashboard literature beyond technological or epidemiologic framing of data dissemination (Fareed et al., 2021; Shankar et al., 2021; Solis et al., 2021; Wang et al., 2022) to discourses around socially embedded participatory visualizations (Beheshti, 2020; Hippala, 2020; Lock et al., 2020). From identifying the qualities of actionable dashboards through expert opinion surveys to defining the data metrics and assessing the usability of the tool through the engagement of local leadership, this research explored the boundaries of user community-focused dashboards to meet pressing resilience challenges. The success of our dashboard project is reflected in the fact that leaders cutting across job roles and sectors agreed that the tool provides novel understandings of the evolving economic and social scenario during and post-COVID-19. Furthermore, the high usability ratings on indicators presented over the dashboard and positive experience with the interactivity of visualization elements reinforce the value of engaging local stakeholders in defining the scope of dashboard tools and grounding the metrics selection process within current debates that impacts the communities directly. As Dangermond et al. (2020) suggest the proliferation and growth of GIS technologies provide researchers and policymakers with several options to design dashboard visualization; however, how far they succeed in engaging the wider community and supporting critical social problems will determine their use and uptake in the future. Findings from this study offer new clues for the research and development community who are designing public-facing dashboards to explore further how different user groups perceive visualization tools differently and the ways these data tools can be standardized and co-designed to meet the expectations and needs of a wide range of audiences. Conclusion This article contributes to a rapidly growing research domain around dashboards and geospatial data visualization technologies used to monitor, inform, and respond to the ongoing public health crisis. Indicators, data, and software tools are increasingly playing a vital role in the shaping and proliferation of government policies, including resilience planning and disaster response. The ability of our organizations and cities to collect, process, and utilize data to enforce a logic of control enacted through digital technologies shows immense potential to transform how we address and respond to emerging challenges and shocks. While many dashboard project implementations are coming to fruition, there is still considerable research and development potential yet to be explored and exploited. Our global analysis of the 68 COVID-19 dashboards shows the varying contexts, levels of focus, data sources and indicators, and design elements—a testament to the advancements in health informatics and a growing sense of public responsibility to report health and community data. While this research acknowledges that there is no one-size-fits-all model for dashboard design, we encourage authorities to consider the essential features of inclusive and actionable dashboards identified in this study. This research highlights the existing gaps in COVID-19 dashboards in two dimensions. In terms of data provision, there is a lack of granular information at the local level, missing data by population sub-groups, and severe inadequacy in reporting social and economic indicators. From the perspective of user-interface design, we reveal the challenges of the single-screen dashboard layout adopted by many projects, limited focus on data download and metadata provision, and a general disregard for providing explanatory narratives to describe the background, source, and purpose of the data. Building on these gaps, we illustrate an empirical experiment of building a dashboard prototype—the COVID-19 Economic Resilience Dashboard. We demonstrated the fit-for-purpose dashboard model (Kitchin, 2014) that provides localized data, drill-down options, visualization narratives, open access to data, and accessible features on the interface to facilitate two-way information exchange. We emphasized and exhibited the value of linking pandemic-related information with socioeconomic data to illustrate how intervention policies affect the spread of COVID-19 and vice versa, a feature generally lacking in the existing COVID-19 dashboards (Fareed et al., 2021; Ivanković et al., 2021). The tools we have discussed and introduced here are synergetic to the broader agenda of “dashboard governance” (Few, 2006) where data sharing and visualization interface plays a vital role in everyday decision-making, acting as a potential channel of communication between decision-makers and community stakeholders. The application we provided can easily be replicated for other regions across the world as we consistently used standard technologies and open data. These findings together suggest a clear pathway forward for researchers and governments to incorporate more action-oriented data and easy-to-use interfaces as they refine existing and develop new information systems and data analytics dashboards. Such projects may generate an exciting collection of informed and engaged community development strategies on a systematic comparative basis. Supplemental Material Supplemental Material - Deploying geospatial visualization dashboards to combat the socioeconomic impacts of COVID-19 Click here for additional data file. Supplementary Material for Deploying geospatial visualization dashboards to combat the socioeconomic impacts of COVID-19 by Sarbeswar Praharaj, Patricia Solis, and Elizabeth A Wentz in Environment and Planning B: Urban Analytics and City Science. Sarbeswar Praharaj, PhD, is the Associate Director (Data and Visualization) and Assistant Research Professor at the Knowledge Exchange for Resilience, School of Geographical Sciences and Urban Planning at Arizona State University. He is a Senior Global Futures Scientist at the Julie Ann Wrigley Global Futures Laboratory. Dr Praharaj leads research on smart cities, critical urban studies, and data visualization and dashboards. He engages in research-led interactive teaching and learning pedagogies in urban planning and geographical science. Before joining ASU, he was a postdoctoral researcher and manager of the City Analytics Lab at the City Futures Research Center, UNSW Sydney, Australia. Patricia Solís, PhD, is Executive Director of the Knowledge Exchange for Resilience and Associate Research Professor at Arizona State University. She is Co-Founder and Director of YouthMappers, a consortium of student-led chapters on more than 208 university campuses in 48 countries who create and use open spatial data for humanitarian and development needs in collaboration with USAID. Prior to joining ASU, she was Co-Director of the Center for Geospatial Technology at Texas Tech University and a Research Associate Professor of Geography in the Department of Geosciences. She served as Deputy Director and Director of Research at the American Association of Geographers. Elizabeth Wentz, PhD, is the Vice Provost and Dean of the Graduate College and a Professor in the School of Geographical Sciences and Urban Planning at Arizona State University. She is the Director and PI of the Knowledge Exchange for Resilience, aiming to support knowledge sharing and discovery for community resilience in Maricopa County, Arizona. She is the former PI of ASU ADVANCE, to become a higher education leader in inclusion and diversity. Her research focuses on the design, implementation, and evaluation of geographic technologies with particular emphasis on how such technologies can be used to understand urban environments. ORCID iDs Sarbeswar Praharaj https://orcid.org/0000-0002-7383-2751 Patricia Solis https://orcid.org/0000-0003-1374-9400 Elizabeth A Wentz https://orcid.org/0000-0002-2881-0668 The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study is supported by Virginia G. Piper Charitable Trust. Supplemental Material: Supplemental material for this article is available online. ==== Refs References Badard T Dubé E (2009) Enabling geospatial business intelligence. Open Source Business Resource. Ottawa, Canada: Talent First Network. Available at: http://timreview.ca/article/289. Accessed on: 30 July 2022. Batty M (2015) A perspective on city dashboards. Regional Studies, Regional Science. 2 (1 ): 29–32. DOI: 10.1080/21681376.2014.987540 Beheshti A Tabebordbar A Benatallah B (2020) istory: Intelligent storytelling with social data. In:Companion Proceedings of the Web Conference 2020, Taipei, Taiwan, April 2020, pp. 253–256. Budd J Miller BS Manning EM , et al. (2020) Digital technologies in the public-health response to COVID-19. Nature Medicine 26 (8 ): 1183–1192. Chiang A (2011) What is a Dashboard? Defining Dashboards, Visual Analysis Tools and Other Data Presentation Media. Dashboard Insight. Coe A Paquet G Roy J (2001) E-Governance and Smart Communities: A Social Learning Challenge. Social science computer review 19 (1 ): 80–93. DOI: 10.1177/089443930101900107 Crepaz M Arikan G (2021) COVID-19 dashboards have a polarising effect on public trust. LSE COVID-19 Blog. London, UK: London School of Economics and Political Science. Dangermond J de Vito C Pesaresi C (2020) Using GIS in the Time of the COVID-19 Crisis, casting a glance at the future. A joint discussion. J-READING Journal of Reasearch and Didatics in Geography 1 : 195–205. Dowding D Merrill JA (2018) The development of heuristics for evaluation of dashboard visualizations. Applied Clinical Informatics 9 (3 ): 511–518.29998455 Elias M Aufaure M-A Bezerianos A (2013) Storytelling in visual analytics tools for business intelligence. In: IFIP Conference on Human-Computer Interaction, Cape Town, South Africa, 2–6 September 2013. Springer, pp. 280–297. Fareed N Swoboda CM Chen S , et al. (2021) US COVID-19 state government public dashboards: an expert review. Applied Clinical Informatics 12 (2 ): 208–221.33853140 Few S (2006) Information Dashboard Design: The Effective Visual Communication of Data. Sebastopol, CA: O’Reilly Media, Inc. Forsell C Johansson J (2010) An heuristic set for evaluation in information visualization. In: Proceedings of the International Conference on Advanced Visual Interfaces, Roma, Italy, 26–28 May 2010, pp. 199–206. Haraguchi M Nishino A Kodaka A Allaire M Lall U Kuei-Hsien L Onda K Tsubouchi K Kohtake N (2022) Human mobility data and analysis for urban resilience: A systematic review. Environment and Planning B: Urban Analytics and City Science 49 (5 ): 1507–1535. DOI: 10.1177/23998083221075634 Healy K (2018) Data Visualization: A Practical Introduction. Princeton, NJ: Princeton University Press. Hiippala T (2020) A multimodal perspective on data visualization. Data visualization in society. In: Engebretsen M Kennedy H (eds) Data Visualization in Society. Amsterdam, Netherlands: Amsterdam University Press. DOI: 10.5117/9789463722902_ch17 Ivanković D Barbazza E Bos V , et al. (2021) Features constituting actionable COVID-19 dashboards: descriptive assessment and expert appraisal of 158 public web-based COVID-19 dashboards. Journal of Medical Internet Research 23 (2 ): e25682.33577467 Kitchin R (2014) The real-time city? Big data and smart urbanism. GeoJournal 79 (1 ): 1–14. DOI: 10.1007/s10708-013-9516-8 Knaflic CN (2015) Storytelling with Data: A Data Visualization Guide for Business Professionals. New York, NY: John Wiley & Sons. Kourtit K Nijkamp P (2018) Big data dashboards as smart decision support tools for i-cities–An experiment on stockholm. Land Use Policy 71 : 24–35. Lan Y Desjardins MR Hohl A , et al. (2021) Geovisualization of COVID-19: state of the art and opportunities. Cartographica: The International Journal for Geographic Information and Geovisualization. 56 (1 ): 2–13. Lee D Ricardo J Felix A , et al. (2015) CityEye: Real-Time Visual Dashboard for Managing Urban Services and Citizen Feedback Loops. In: CUPUM 2015, Cambridge, MA, 7–10 July 2015. Letouzey JL (2012, June) The SQALE method for evaluating technical debt. In: 2012 Third International Workshop on Managing Technical Debt (MTD), Zurich, Switzerland, 5 June 2012. IEEE, pp. 31–36. Lock O Bednarz T Leao SZ , et al. (2020) A review and reframing of participatory urban dashboards. City, Culture and Society 20 : 100294. Mattern S (2015) Mission Control: A History of the Urban Dashboard. Cambridge, MA: Places. Nielsen J Molich R (1990) Heuristic evaluation of user interfaces. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 1–5 April 1990, pp. 249–256. O’Brien H Cairns P (2015) An empirical evaluation of the User Engagement Scale (UES) in online news environments. Information Processing & Management 51 (4 ): 413–427. Pettit C Lieske SN Jamal M (2017) Citydash: Visualising a Changing City using open data Lecture Notes in Geoinformation and Cartography. Berlin, Germany: Springer Berlin Heidelberg, 337–353. DOI: 10.1007/978-3-319-57819-4_19 Pietz J McCoy S Wilck JH (2020) Chasing John Snow: data analytics in the COVID-19 era. European Journal of Information Systems 29 (4 ): 388–404. Praharaj S Kaur H Wentz E (2022) The Spatial Association of Demographic and Population Health Characteristics with COVID‐19 Prevalence Across Districts in India. Geographical Analysis. DOI: 10.1111/gean.12336 Praharaj S Wentz E (2022) Building community resilience through geospatial information dashboards. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences 48 (4/W5 ): 151–157. DOI: 10.5194/isprs-archives-XLVIII-4-W5-2022-151-2022 Presthus W Canales CA (2015) Business Intelligence Dashboard Design. A Case Study Of A Large Logistics Company. Rojas E Bastidas V Cabrera C (2020) Cities-board: a framework to automate the development of smart cities dashboards. IEEE Internet of Things Journal 7 (10 ): 10128–10136. DOI: 10.1109/JIOT.2020.3002581 Sarikaya A Correll M Bartram L , et al. (2018) What do we talk about when we talk about dashboards? IEEE Transactions on Visualization and Computer Graphics 25 (1 ): 682–692. Schanzenbach D Pitts A (2020) How Much Has Food Insecurity Risen? Evidence from the Census Household Pulse Survey. Institute for Policy Research Rapid Research Report. Evanston, IL: Northwestern University. Shankar K Jeng W Thomer A , et al. (2021) Data curation as collective action during COVID 19. Journal of the Association for Information Science and Technology 72 (3 ): 280–284. Sharifi A Khavarian-Garmsir A Kummitha R (2021) Contributions of smart city solutions and technologies to resilience against the COVID-19 pandemic: A literature review. Sustainability 13 (14 ): 8018. DOI: 10.3390/su13148018 Solis P Dasarathy G Turaga P Drake A Vora K J Sajja A Raaman A Praharaj S Lattus R (2021) Understanding the Spatial Patchwork of Predictive Modeling of First Wave Pandemic Decisions by US Governors. Geographical Review 111 (4 ): 592–615. DOI: 10.1080/00167428.2021.1947139 van der Voorn T de Jong M (2021) Cope or Perish? Managing Tipping Points in Developing Coping Strategies for Emergency Response during the First Wave of the COVID-19 Outbreak in Europe. COVID 1 (1 ): 39–70. DOI: 10.3390/covid1010005 Wang C Li Z Clay Mathews M Praharaj S Karna B Solís P (2022) The spatial association of social vulnerability with COVID-19 prevalence in the contiguous United States. International Journal of Environmental Health Research 32 (5 ): 1147–1154. DOI: 10.1080/09603123.2020.1847258 33228411 Young GW Kitchin R (2020) Creating design guidelines for building city dashboards from a user’s perspectives. International Journal of Human-Computer Studies 140 : 102429. DOI: 10.1016/j.ijhcs.2020.102429
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==== Front Manag Commun Q Manag Commun Q spmcq MCQ Management Communication Quarterly 0893-3189 1552-6798 SAGE Publications Sage CA: Los Angeles, CA 10.1177_08933189221144997 10.1177/08933189221144997 Article How Family-Supportive Leadership Communication Enhances the Creativity of Work-From-Home Employees during the COVID-19 Pandemic https://orcid.org/0000-0002-2482-435X Lee Yeunjae 1 https://orcid.org/0000-0002-2973-9656 Kim Jarim 2 1 Department of Strategic Communication, 5452 University of Miami , Coral Gables, FL, USA 2 Department of Communication, 26721 Yonsei University , Seoul, Korea Yeunjae Lee, Department of Strategic Communication, University of Miami, 5100 Brunson Drive, Coral Gables, FL 33156, USA. Email: [email protected] 7 12 2022 7 12 2022 08933189221144997© The Author(s) 2022 2022 SAGE Publications This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. Adapting to the remote working environment has been one of the most visible challenges for many organizations during the COVID-19 pandemic. As employee creativity helps organizations’ survival and resilience during times of crisis, this study aims to examine the role of leadership communication, family-supportive leadership communication in particular, in fostering creativity among work-from-home employees. The current study specifically focuses on the mediating processes in this relationship and the moderating role of employees’ work-life segmentation preferences, using a survey of 449 employees who have worked from home during the COVID-19 outbreak. The results showed that employee-organization relationship (EOR) quality, positive affect, and work-life enrichment mediate the relationship between family-supportive leadership communication and employee creativity. The effects of family-supportive leadership communication on employees’ positive affect and work-life enrichment were more prominent for those who prefer to segment their work and lives. This paper concludes with a discussion of the theoretical and practical implications of these findings for leadership in organizational communication. COVID-19 creativity family-supportive leadership segmentation preference employee-organization relationship work-life enrichment positive affect Yonsei University Research Grant of 2022 2022-22-0180 edited-statecorrected-proof typesetterts10 ==== Body pmcAs a result of the unprecedented coronavirus (COVID-19) pandemic, which began in 2020, more employees have been working from home than ever before. A nationwide survey showed that approximately 66% of employees had to work from home in 2020 at least part of the week due to the pandemic (Herhold, 2020). Such working conditions have challenged organizations, yielding various problems such as employees’ digital fatigue, mental health issues caused by social isolation, and work-life conflict problems (Sen et al., 2021). In particular, due to the lack of physical compartmentalization between work and family space, COVID-19 has brought additional work-life boundary-blurring for these employees (Sahay & Wei, 2021), and family distractions presented by the new work-from-home reality have become one of the most pressing management issues (Gratton, 2020). To address these issues, creative and novel approaches and solutions that help organizations to adapt and manage the new working environment effectively are particularly required (Tang et al., 2020). Research has suggested that employees’ creative ideas are valuable for enhancing organizations’ abilities to both adapt resiliently to difficult situations and grow and compete by responding to opportunities—abilities that enable organizations to maintain their competitive advantages (Amabile, 1988; Oldham & Cummings, 1996). Creating conditions that foster employees’ creativity during challenging times thus has become a key challenge for organizational leaders. This study argues that leaders’ family-supportive communication plays an important role in facilitating creativity among work-from-home employees during the coronavirus crisis. Family-supportive leadership, referring to supervisory behaviors that enable employees to achieve a balance between their responsibilities at home and work (Thomas & Ganster, 1995), is a powerful form of interaction that fosters positive workplace outcomes such as enhanced job satisfaction, well-being, and work-life balance (Jang, 2009; Li & Bagger, 2011; McCarthy et al., 2013). It can thus be a viable and unique interpersonal resource that leaders can use to engender greater desire, particularly among work-from-home employees, to think creatively in crises by helping them manage work-life boundaries effectively. Although previous studies (e.g., Bagger & Li, 2014; Straub, 2012) have examined the implications of such leadership, they have mainly focused on its effects on employees’ attitudinal, behavioral, and health-related outcomes, and research investigating its impacts on creativity remains scarce. Thus, to enrich our understanding of the outcomes of family-supportive leadership communication, especially for working-from-home employees during the pandemic, we examine the link between family-supportive leadership and creativity. Grounded in the social exchange theory (SET), this study focuses specifically on the processes underlying this relationship including relationship building, positive affect, and work-life enrichment (WLE). Additionally, given that the pandemic has blurred the boundaries between work and family, this study tests how individuals’ work-home segmentation preferences (i.e., desire to segment or integrate work and family domains) moderate the effects of family-supportive leadership on employees’ perceived quality of relationship with their organizations, positive affect, and WLE. It has been shown that the negative effects of unexpected work-life conflicts on employee outcomes depend on individual differences (Derks et al., 2016), and thus, it is likely that work-from-home employees’ experiences and needs may vary according to their segmentation preferences. In sum, this study proposes an integrative model that investigates the effects of supervisors’ support for families on working-from-home employees’ creativity during the COVID-19 pandemic via three mechanisms (i.e., improving employee-organization relationship quality, fostering positive affect, and enriching work-life) and the moderating role of individuals’ segmentation preferences (Figure 1). This study provides much-needed theoretical insights on social exchange mechanisms regarding leaders’ communication roles in fostering creativity among work-from-home employees. The study also provides strategic guidelines that organizational leaders and communication practitioners can follow to manage employees’ work-life issues and enhance their creativity in remote work environments.Figure 1. Conceptual model. Literature Review Employee Creativity Defined as the generation of novel and useful ideas by employees, employee creativity is critical for employees’ performance as well as organizational effectiveness, success, and survival (Amabile, 1988). Although its relative importance may vary depending on the industry, the importance of creativity is not limited to particular occupations (Shalley et al., 2000). Prior studies have identified diverse factors at the individual and organizational levels that enhance employee creativity (Shalley & Gilson, 2004), and particularly highlighted the role of supportive behaviors by supervisors (Lee & Kim, 2021; Oldham & Cummings, 1996). Fostering creativity among employees is especially important in crises like the COVID-19 pandemic. To remain competitive in crisis situations, organizations must adjust to new environments (e.g., holding virtual conferencing or establishing a remote reporting system) that may require new norms for work. Employees’ creative ideas and solutions can help organizations to be resilient by simultaneously managing new work systems effectively and continuing to achieve their goals during turbulent times. Prior research has primarily focused on employees from certain industries that require high levels of creativity in their jobs or tasks (e.g., Ogbeibu et al., 2018). However, employees in almost every industry can supply creative ideas that improve the productivity and efficiency of their jobs (Shalley et al., 2000), and it is even more critical during a crisis where new approaches are valued for organizations to be resilient and adapt the new environment rapidly (Tang et al., 2020). An examination of the creativity of employees from a wide range of industries is thus vital, and effective communication intervention strategies can be critical to this process in times of crisis. Due to the high levels of uncertainty that accompany crises, employees may feel hesitant to share creative solutions or ideas as they have limited psychological resources to deal with the anxiety and strain associated with different outcome- and crisis-related risks (Folkman & Moskowitz, 2000). Given that managerial support can provide employees with significant psychological resources (Shin & Zhou, 2003), which help facilitate creative performance (Ford, 1996), leaders or managers must take proactive approaches during crises to promote employee creativity. Family-Supportive Leadership Communication We suggest leadership communication as a key intervention that helps employees to be creative during a coronavirus crisis. Believing that communication is a core constitutive element of leadership (Fairhurst & Connaughton, 2014), communication scholars have espoused the communication-centered view of leadership and defined leadership communication as the process through which organizational leaders connect with and influence stakeholders (Harrison & Mühlberg, 2014). Public relations researchers have also theorized leadership communication as it plays a critical role in organizations’ internal communication (Lee & Kim, 2021). Given the context of the current study, we argue that, among various leadership communication behaviors, family-supportive leadership is of particular value for employees working from home due to COVID-19 since the pandemic has presumably increased the work and family life demands they experience (Larson et al., 2020). Scholars have coined the term, supervisory family support, which refers to leadership behaviors that allow the employees to achieve a balance between their responsibilities at home and work (Thomas & Ganster, 1995). As one type of social support, family-supportive behaviors of supervisors are driven by their goodwill-based intentions to help employees balance work-family demands (Thompson et al., 1999), enabling them to adopt flexible work schedules that accommodate their family needs (Lapierre & Allen, 2006). Supervisors can serve as role models regarding the integration of work and family life by exhibiting family-supportive behaviors and assuaging employees’ concerns about possible negative career consequences (Thompson et al., 1999). Family-supportive supervisors frequently ask about employees’ family needs and express concerns and encouragement to subordinates who are strained by competition for resources from family and work (Bagger & Li, 2014). Drawing on previous studies, this study conceptualized family-supportive leadership communication as the level of support that employees believe they receive from their supervisors in terms of balancing their work-family demands. Such leadership communication that blurs the line between employees’ work and life domains has been discussed in organizational communication literature. Scholars have highlighted leaders’ creative responses to employees’ diverse work-life needs in every action to create progressive work-life culture (Tracy & Rivera, 2010). Studies have also examined leaders’ role in identifying and changing work practices that negatively affect employees’ personal lives and work outcomes through collaboration with employees (Golden, 2009; Hoeven et al., 2017). Family-supportive leadership communication is particularly important for employees during the COVID-19 pandemic, regardless of their diverse family situations. It was found that one of the biggest challenges people experience while working from home were distractions from family and other household members and balancing work with other family duties (Gratton, 2020). Their family distractions during the pandemic include not only care demands for the children and spouses but also dependent and elder care for both married and unmarried individuals (Crain & Stevens, 2018). Leaders’ behaviors of supporting and caring for these diverse family issues that become more salient while working-from-home due to the pandemic are thus critical aspects of leadership communication practices. It has been supported by empirical research that family support from supervisors reduces employees’ work-family conflicts (Hammer et al., 2009) and generates positive employee outcomes such as increased job satisfaction and low turnover intentions (Anderson et al., 2002; Li & Bagger, 2011). It also improves employees’ well-being and work-life balance (Jang, 2009; McCarthy et al., 2013). Limited research, however, examined whether and how family-supportive leadership communication increases employee creativity. In building a linkage between the two, the current study draws upon social exchange theory (SET: Blau, 1964). SET suggested that when employees receive socioemotional resources from their organizations, they build social exchange relationships, which are based on trust, interpersonal attachment, and long-term interactions (Shore et al., 2004). This social exchange relationship, in turn, triggers employees’ engagement in extra-role and pro-organizational behaviors as they feel obligated to return the benefits they receive. Previous studies have suggested that leaders’ actions are critical for developing social exchange relationships and determining their quality (e.g., Lee, 2021). In this study’s context, we propose that family-supportive leadership communication provides employees with socioemotional resources—the quality of employee-organization relationship, employees’ positive affect at work, and work-life enrichment—which have been associated with employee creativity (Ong & Jeyaraj, 2014; Spreitzer et al., 2005; Yu et al., 2018). These may serve as critical mediators that encourage employees to reciprocate positively by being creative in their work while working remotely during the pandemic. Therefore, the next section of this paper delineates three social exchange mechanisms that may translate family-supportive leadership into employee creativity. Then, the moderating role of individuals’ segmentation preference is discussed. The Mediating Role of Employee-Organization Relationship (EOR) First, this study expects that family-supportive leadership communication facilitates employee creativity by building high-quality relationships between organizations and their employees. Scholars across various disciplines including business, human resource management, and public relations have studied employee-organization relationships (EOR)—“an overarching term to describe the relationship between the employee and the organization” (Shore et al., 2004, p. 29). Among its many conceptualizations, one widely adopted definition of EOR describes it as a relational quality between organizations and their employees, characterized by “the degree to which an organization and its employees trust one another, agree on who has the rightful power to influence, experience satisfaction with each other, and commit oneself to the other” (Men & Stacks, 2014, p. 307), which includes the four major components: trust, control mutuality, commitment, and satisfaction (Hon & Grunig, 1999). Recognizing that, as representatives of organizations, leaders’ treatment of their subordinates influences how employees feel about their organizations, scholars have identified diverse types of leadership behaviors (e.g., authentic, empowering leadership) as critical antecedents of EOR (e.g., Lee et al., 2018; Men & Stacks, 2014). Employees often regard support from their supervisors as part of broader organizational efforts. Similarly, family-supportive leadership communication can elicit quality EORs because such behaviors demonstrate leaders’ supportiveness for and desire to enhance the work-life balance and well-being of their subordinates (Thompson et al., 1999). Due to its relationship-building function, family-supportive leadership thus enhances the quality of employee-organization relationships; when employees believe that their supervisors genuinely care about their well-being and allow them to meet their family needs without sacrificing their careers, employees will have positive perceptions of their organizations’ overall work environments and high-quality EORs may emerge (Bagger & Li, 2014). EOR facilitates organizational effectiveness by helping organizations effectively achieve their goals (Hon & Grunig, 1999). As high-quality EORs develop, employees may feel obligated to reciprocate the relationship-building efforts they receive from their organizations. According to SET, employees who trust their organizations are more willing to work hard, expend energy (Yu et al., 2018), and engage in positive behaviors that benefit their organizations (Lee, 2021). One important way for employees to fulfill the sense of obligation they feel toward their organizations is to exhibit their creativity at work (Pan et al., 2020). Creativity, the production of new ideas or solutions, is relevant to the type of bond that individuals have with the organizations they belong to (Amabile, 1988). Previous studies provide evidence that high-quality EORs can promote innovative behavior and creativity among employees (e.g., Yu et al., 2018). Employees exert effort to fulfill their organizational obligations and responsibilities by generating and implementing ideas when their organizations invest substantially in them (Cropanzano & Mitchell, 2005). Thus, because favorable EORs motivate employees to reciprocate and maintain balanced exchanges with their organizations, they may play key roles in fostering employees’ creative behaviors during crises. Based on this line of reasoning, we predicted that family-supportive leadership communication would operate through EOR in facilitating creativity: H1 The quality of EOR mediates the positive relationship between family-supportive leadership communication and employee creativity. The Mediating Role of Work-Life Enrichment (WLE) The fact that family-supportive leaders help employees achieve WLE may also help explain the effect of family-supportive leadership communication on creativity. Work and family life cannot be totally separated from each other. The resources earned from either area (i.e., work, life) can influence the quality of the other (Greenhaus & Powell, 2006). Defined as “the extent to which experiences in one role improve the quality of life in the other role” (Greenhaus & Powell, 2006, p. 72), WLE generally represents positive experiences’ transcendence between work and family life. According to Ten Brummelhuis and Bakker (2012), positive experiences formed in one dimension of life develop as personal resources, whether physical, intellectual, or psychological, and spill over the boundary between work and family life. Carlson et al. (2006) identified three dimensions of WLE: development (i.e., gains of instrumental resources such as knowledge, skills, capabilities, and perspectives in employees’ work domains), affect (i.e., gains of positive emotional states that benefits employees’ non-work lives), and capital (i.e., gains of psychosocial resources such as confidence, accomplishment, self-fulfillment, security, and self-esteem that help employees better fulfill their life roles). Previous research has shown that positive experiences at work influence self-efficacy (Chan et al., 2016), which further affects work-life balance and job and family satisfaction with heightened levels of work-to-family enrichment (Carlson et al., 2006). Working from home blurs the boundaries between family life and work and, as previously mentioned, supervisors’ family supportive behaviors can help employees better deal with family issues. The positive experiences employees obtain from supervisory family support in the work domain can accumulate as psychological resources in their lives and transfer back to their family life, enabling them to improve the quality of their family lives and achieve higher levels of WLE. Research has shown that the opportunity to discuss scheduling flexibility with their supervisor because of their non-work personal activities helps employees achieve higher levels of WLE (Carlson et al., 2006). Other scholars have also demonstrated that support from supervisors results in work-family enrichment because it helps employees feel satisfied with their job roles and improve their personal life experiences (Siu et al., 2015). When enhanced by supervisors’ family support, WLE can foster employees’ creativity at work. Consistent with the main assumption of SET, prior research has suggested that the psychological resources gained from family-supportive leaders should transfer to employees’ maintenance of quality family lives and that the resources gleaned from such family lives are also expected to spill over to the workplace by helping employees translate their ideas into creative performance (Ford, 1996; Tang et al., 2017). Sonnentag (2003) showed that family-to-work enrichment enables employees to deal with different work more actively, energetically, and with greater levels of motivation, which results in better performance at work (Greenhaus & Powell, 2006; Ten Brummelhuis & Bakker, 2012). As an important psychological resource that spills over from life, WLE can enhance employees’ energy levels and problem-solving abilities in their workplaces (Sonnentag et al., 2008), which in turn helps employees persist in their creative efforts (Atwater & Carmeli, 2009). Indeed, work-life harmony, a pleasant, harmonious arrangement of work and life roles, has been found to have a facilitative impact on employees’ creative performance at work (Ong & Jeyaraj, 2014). In sum, positive socioemotional resources—work and family life enrichment—employees obtain via family-supportive leadership communication motivate employees to reciprocate by being creative in their work. Based on this social exchange mechanism generated by family-supportive leaders, thus, we predicted that WLE would serve as a mediator that explains supervisory family support’s effect on employee creativity. H2 Work-life enrichment mediates the positive relationship between family-supportive leadership communication and employee creativity. The Mediating Role of Positive Affect Family-supportive leadership communication also influences employee creativity by contributing to employees’ positive affect (“a pleasant feeling state or good mood”; Estrada et al., 1994, p. 286). Leadership communication has been believed to affect employees’ positive emotions at work (Men & Yue, 2019). Family supportive leaders reduce employees’ concerns about their work that could potentially sap their energy (Edwards & Rothbard, 2000) and their concerns about making unfavorable impressions on their supervisors due to family-related obligations (Regan, 1994). Thus, family-supportive leadership communication may elicit positive affective reactions from employees. Supporting this viewpoint, Lapierre and Allen (2006) showed that family-supportive supervision helps protect employees’ affective well-being at work. Researchers have contended that positive affect stimulates creativity by influencing individuals’ cognitive activity (Clore et al., 1994). Positive emotions such as joy or love broaden individuals’ repertoires of cognitions and actions (Fredrickson & Branigan, 2005)—particularly, the scope of their attention by increasing the number of cognitive elements available for associations and the scope of their cognition by increasing the breadth of those elements that they can treat as relevant to a given problem. As a result, this mental activity leads to greater variation and prompts individuals to pursue novel, creative, and unscripted paths of thought and action. Miller (1997) provided a physiological explanation for the relationship between positive affect and creativity. Chemicals such as endorphins, epinephrine, and adrenalin released in the body when individuals are having fun increase their sense of well-being and energy, which elicits creative thinking accompanied by higher self-esteem. Positive affect also enhances social bonds and connectivity among employees, which makes them experience expansive emotional states that open possibilities for creativity, leading them to try new things (Spreitzer et al., 2005). More importantly, serving as a key job resource that helps employees to stay in a positive mood while working-from-home, family-supportive leaders fulfill the emotional and affective needs of employees in the workplace. As argued by SET, employees who receive emotional resources from family-supportive leaders are likely to commit themselves to organizations by being creative in their works. Based on this idea, we posed the following hypothesis: H3 Positive affect mediates the positive relationship between family-supportive leadership communication and employee creativity. In addition, positive emotions help individuals build high-quality relationships with others. In organizational settings, experiencing positive emotions broadens one’s awareness and thought-action repertoires by activating outward orientations, which in turn help build social resources such as relationships with coworkers or managers (Sekerka et al., 2012). Scholars have shown that employees’ affective experiences play crucial roles in developing and maintaining quality leader-member exchange relationships (Cropanzano et al., 2017). Similarly, positive affect may improve the quality of EORs, namely, employees’ feelings of trust, satisfaction, mutual control, and commitment toward their organizations. Men and Robinson (2018) empirically demonstrated that positive feelings at work such as joy, happiness, excitement, companionate love, affection, and warmth contribute to facilitating a favorable EOR. Therefore, we proposed the following hypothesis: H4 Positive affect mediates the positive relationship between family-supportive leadership communication and EOR. Positive affect also serves as a pathway between positive experiences in one life domain and experiences of enrichment in other life domains (Greenhaus & Powell, 2006). Researchers have noted that employees’ experiences of positive affect at work are not limited to the work domain but generalize into overall higher levels of positive affect across life domains (Heller et al., 2004). This general positive affect helps employees to feel energized and to engage in other life domains outside work such as home (Greenhaus & Powell, 2006). Positive emotions and affect experienced in one role (i.e., work) can be transferred to family (Wayne et al., 2006) as it enriches employees’ experiences in other roles (i.e., family) (Hanson et al., 2006). Therefore, we expected that high levels of positive affect at work would make employees function well in their family lives, leading us to propose the following hypothesis: H5 Positive affect mediates the positive relationship between family-supportive leadership communication and work-life enrichment. Segmentation Preference as a Moderator In a modern society where work-related demands can easily encroach upon the family domain, individual employees have different preferences for managing their work-home lives. While some employees prefer to integrate their work and family domains, others prefer to segment the two domains as much as possible (Kossek & Lambert, 2004). This boundary management preference to either integrate or separate work and private roles, which is a psychological state that is rather stable over time (Rothbard et al., 2005), has been considered an active coping strategy that individuals can use to balance their work and family lives (Edwards & Rothbard, 2000). It has been shown that permeability and flexibility determine one’s role integration-segmentation (Ashforth et al., 2000). In other words, employees who prefer to create and maintain permeable and integrated boundaries are more likely to experience spillover across the work and family domains, while those who prefer impermeable and segmented boundaries seek to prevent the two domains from influencing each other by keeping them separate. Individuals with high work-home segmentation preference levels (hereafter referred to as segmenters) tend to suffer less from the negative work-family spillover caused by job stress or mistreatment in work at home because they can effectively sever affective and behavioral connections across the domains (Liu et al., 2013) and suppress work-related feelings at home (Xin et al., 2018). Individuals with low work-home segmentation preference levels (hereinafter referred to as integrators) appreciate interactions across the domains (Derks et al., 2016). The current study proposes that the effects of family-supportive leadership communication on positive affect, EOR, and WLE described above will vary depending on individuals’ segmentation preferences. While facing unexpected and sudden changes in working environment, segmenters who began working from home due to the pandemic may likely experience more boundary violations between work and life than the integrators. Remote working causes work to intrude into family life and vice versa, and such boundary violations can especially lead to increased work-family conflicts and higher levels of stress and burnout particularly for employees who prefer to keep their work and family domains as separate as possible (Kreiner et al., 2009). Moreover, segmenters tend to perceive more failure to fulfill their roles in both domains when work-family conflicts occur unexpectedly (Zhang et al., 2019). Hence, we assume that family-supportive leadership communication may be particularly effective for segmenters during the COVID-19, compared to integrators, by helping them to simultaneously accommodate their increased responsibilities and demands in both the work and family domains. Leaders’ genuine care and concern for such employees’ family demands and needs can provide them with the flexibility and permeability to fulfill the demands they face in both domains. The fulfillment of such demands is associated with WLE, which facilitates the approaches they take to working from home. Moreover, family-supportive leadership communication can help segmenters perceive their EORs as high quality and promote higher levels of positive affect while working-from-home. Segmenters are generally expected to feel more burnout than integrators because they experience unexpected and sudden difficulties in managing both their work and home roles at home. Active communication supervisors accommodate, listen to, and show concerns for such employees’ family-related obligations may elicit more positive reactions by ameliorating their burnout states and helping them feel satisfied with their companies. This is because such communication helps reduce employees’ work-related concerns and fully participate in family-activities without feeling guilty and concerned about making unfavorable impressions by attending to family matters (Edwards & Rothbard, 2000; Regan, 1994). The positive consequences of family-supportive leadership communication may thus be particularly strengthened for those who prefer to segment life and work. Based on this line of reasoning, we proposed the following hypotheses regarding the moderating effects of individuals’ segmentation preferences: H6 Segmentation preference moderates the relationship between family-supportive leadership communication and EOR such that the relationship is stronger when the work-home segmentation preference level is high than when it is low. H7 Segmentation preference moderates the relationship between family-supportive leadership communication and positive affect such that the relationship is stronger when the work-home segmentation preference level is high than when it is low. H8 Segmentation preference moderates the relationship between family-supportive leadership communication and work-life enrichment such that the relationship is stronger when the work-home segmentation preference level is high than when it is low. Figure 1 shows the conceptual model. Methods Participants and Procedures An online survey with full-time employees across various industrial sectors1 and organizational sizes in the United States was conducted using Qualtrics panels. The data were collected for a week in June 2020, during which most states had implemented stay-at-home orders, beginning with California in mid-March (Mervosh et al., 2020), and there were about 1.9 million confirmed cases (Elflein, 2020). Given the purpose of the study, the sample included only those who started working from home due to COVID-19, meaning that workers who had been working from home (i.e., teleworkers) before the COVID-19 outbreak were screened before the survey. To achieve a representative sample of U.S. employees according to the most recent U.S. census data, Qualtrics used quota when recruiting the participants in terms of gender, age, and race/ethnicity. Of the 449 total participants (mean age = 35.82; SD = 10.14), 55.7% were male and the majority were White (65.9%). Most of the participants (94.4%) held bachelor’s degrees or higher. The income levels of the largest number of participants were between US$40,000 and US$59,999 (35.2%), followed by the US$60,000 to US$79,999 range (24.1%). A majority of the participants (64.6%) held management positions, followed by non-management positions (28.5%), and senior management positions (6.9%). The participants worked for organizations that varied in size from small- (4.2%), medium- (46.8%) to large-sized (27.2%) companies. About 39.4% of participants reported having worked for their current employers for 4–6 years, 29% for 1–3 years, and 15.1% for 6–8 years. The employers’ industries included information and telecommunications (21.8%), manufacturing (18.3%), finance and insurance (16.5%), construction (6.7%), professional, scientific, and technical services (5.8%), healthcare and social assistance (5.1%), and management of companies and enterprises (4.7%). Furthermore, 71.2% of participants responded that they had been working-from-home due to COVID-19 for more than 2 months. A total of 87% of them were currently married and 80.8% of them responded that they had at least one child in their household. Measures All the items used in the current study were adopted from previous literature adjusted to the current study’s context. Given the context of the current study, participants were asked to answer the questions for the items regarding their time working from home due to the COVID-19 outbreak, except for the measure of segmentation preference. Employee Creativity Five items adapted from Zhou and George (2001) were used to measure employee creativity. Items began with “While working-from-home, how often have you” and ended with each statement (e.g., suggested new and better ways of performing work tasks, came up with new and practical ideas to improve work performance, developed adequate plans and schedules for the implementation of new ideas, considered yourself as a good source of creative ideas, had a fresh approach to work-related problems). 7-point Likert scale was used, ranging from “1 = Never” to “7 = Always” (α = .80, M = 5.18, SD = 0.96). Family-Supportive Leadership Communication Family-supportive leadership communication was measured with six items adapted from previous studies (Clark, 2001; Thompson & Prottas, 2006). Participants were asked whether their direct supervisor/leader (1) listens when I talk about family issues, (2) understand my family needs, (3) acknowledges that I have obligations as a family member, (4) cares about the effects of work on family life, (5) supports my need to balance work and family issues, and (6) shows concerns for my family. They were measured with seven-point Likert scales ranging from “1 = strongly disagree” to “7 = strongly agree.” (α = .81, M = 5.38, SD = 0.93). EOR Measures for the quality of employee-organization relationship were adopted from Hon and Grunig (1999), comprised four second-level factors including trust (4 items; α = .76) (e.g., “My company treats employees like me fairly and justly”), control mutuality (3 items; α = .72) (e.g., “My company and an employee like me are attentive to what each other say”), commitment (3 items; α = .74) (e.g., “I feel that my company is trying to maintain a long-term commitment to employees like me”), and satisfaction (3 items; α = .71) (e.g., “I am happy with my company”). Seven-point Likert scale from “1 = strongly disagree” to “7 = strongly agree” was used (α = .92, M = 5.38, SD = 0.88). WLE Work-life enrichment measures were adopted from Carlson et al. (2006) and a total of 16 items was used with 7-point Likert scale from “1 = strongly disagree” to “7 = strongly agree” (α = .92, M = 5.31, SD = 0.83). It comprised three factors including development resources (6 items; α = .85) (e.g., “My involvement at work helps to develop my abilities and this helps me be a better family member”), affect resources (5 items; α = .81) (e.g., “My involvement at work helps to be in a good mood, and this helps me be a better family member”), and capital resources (5 items; α = .79) (e.g., “My involvement at work instills confidence in me, and this helps me be a better family member”). Positive Affect A total of 13 items was adopted from Van Katwyk et al. (2000) to measure positive affect. Items also began with “While working-from-home, how often have you felt” and ended with each emotion (e.g., satisfied, excited, energetic). This construct was also measured with 7-point Likert scales from “1 = Never” to “7 = Always” (α = .91, M = 5.23, SD = 0.96). Segmentation preference Individuals’ general segmentation preferences were measured with four items adopted from Kreiner (2006) with seven-point Likert scales ranging from “1 = strongly disagree” to “7 = strongly agree.” (α = .76, M = 5.32, SD = 0.95). Sample items include “In general, I prefer to keep work life at work.” Controls Based on the results of a series of ANOVA, t-tests, and regression analyses, participants’ gender, industry sectors, marital status, and the number of children were controlled. Analysis A two-step structural equation modeling (SEM) analysis, including a test of the measurement model using CFA followed by an assessment of the structural model, was performed using Mplus program. Hu and Bentlers’ (1999) joint-criteria, either CFI ≥.95 and SRMR ≤.10 or RMSEA ≤.06 and SRMR ≤.10, was used to assess the model fits. Results Testing the Measurement Model Table 1 presents the means, standard deviations, and zero-order Pearson correlations of all of the main variables. The CFA results showed that the measurement model fit the data well: χ2 (1462) = 3689.981, RMSEA = .058 [.056, .061], CFI = .954, TLI = .945, SRMR = .044. All factor loading values were significant and higher than the threshold value of 0.6 (p < .001). The composite reliabilities (CR) for all variables ranged from .83 to .93, demonstrating good internal consistency. In addition, as the values of the average of variance extracted (AVE) were greater than .5 and the square root values of AVE were greater than the construct correlations, convergent and discriminant validity of the measures were shown to be satisfactory. We thus proceeded with the structural model testing.Table 1. Descriptive Statistics and Correlations among Variables. M (SD) α 1 2 3 4 5 6 1. Employee creativity 5.18 (0.96) .80 — 2. Family supportive leadership communication 5.38 (0.93) .81 .51* — 3. Employee-organization relationship 5.38 (0.88) .92 .55* .68* — 4. Work-life enrichment 5.31 (0.83) .92 .56* .53* .59* — 5. Positive affect 5.23 (0.96) .91 .57* .48* .51* .64* — 6. Segmentation preference 5.32 (0.95) .76 .35* .48* .53* .46* .41* — *P < .01 Structural and Alternative Model Testing The hypothesized model fits the data well: χ2 (1307) = 3266.541, RMSEA = .058 [.055, .060], CFI = .954, TLI = .946, SRMR = .044. To assess the theoretical validity of the conceptual model, we compared the baseline model with other alternative models that include different flows of theoretical hierarchy among latent variables (Hair et al., 2006). Given that relationship and work-life enrichment lead to positive affect at work (Wepfer et al., 2018), the first alternative model included the direct effects from EOR and WLE on positive affect. It performed significantly worse than the proposed model (χ2 (1307) = 3435.939, RMSEA = .070 [.067, .074], CFI = .926, TLI = .920, SRMR = .089) (Δχ2 = 169.40, p < .001). Similarly, the second alternative model that reverse the sequence of the variables (the effect of creativity on family-supportive leadership communication via EOR, WLE, and positive affect) did not show a significantly better model fit than the baseline model (χ2 (1308) = 3627.357, RMSEA = .089 [.076, .091], CFI = .900, TLI = .891, SRMR = .112) (Δχ2 = 360.82, p < .001). In the third alternative model, we added a direct path from leadership communication to creativity that has been demonstrated in previous studies. The alternative model (χ2 (1306) = 3435.928, RMSEA = .065 [.054, .071], CFI = .933, TLI = .923, SRMR = .061) was not significantly better than the baseline model (Δχ2 = 169.39, p < .001). The distinctiveness and theoretical foundation of the hypothesized model was supported, and thus, was selected as the final model. We then interpreted the path coefficients (see Figure 2).Figure 2. Results of the hypothesized model. Hypotheses Testing In H1, we predicted that EOR would play a mediating role in the relationship between family-supportive leadership communication and employee creativity. Family-supportive leadership communication had a significant direct effect on EOR (.892, p < .001), and EOR significantly increased employee creativity (.147, p = .014). The results of a bias-corrected bootstrapping procedure (N = 5,000) with 95% confidence interval suggested that the indirect effect was also significant (.131, p = .014, 95% CI [.102, .276]). Thus, H1 was supported. H2 tested the mediation effect of WLE. Family-supportive leadership communication positively and significantly influenced WLE (.591, p < .001), and WLE significantly increased employee creativity (.323, p < .001), with a significant mediating effect (.191, p < .001, 95% CI [.092, .288]). Therefore, H2 was supported. H3 examined the indirect effect of family-supportive leadership communication on employee creativity through positive affect. The analysis showed positive and significant direct effects between family-supportive leadership communication and positive affect (.589, p < .001) and between positive affect and employee creativity (.483, p < .001). The indirect effect was also significant (.285, p < .001, 95% CI [.214, .364]). Thus, H3 was supported. Regarding H4-H5, positive affect did not have a significant direct effect on EOR (.047, p = .296), but it had a significant direct effect on WLE (.356, p < .001). In line with this, the path from family-supportive leadership communication to EOR via positive affect was insignificant (.028, p = .285, 95% CI [-.030, .136]), meaning H4 was not supported. Meanwhile, the analysis showed a significant indirect effect in the path from family-supportive leadership communication to WLE through positive affect (.210, p < .001, 95% CI [.135, .259]), supporting H5. H6–H8 concerned the moderating effects of employees’ segmentation preference. The results showed that the interaction term (work-home segmentation preference x family-supportive leadership communication) in the model was positively and significantly related to positive affect (.131, p = .002) and WLE (.108, p = .001), while it was not related to EOR (−.041, p = .186). Following Aiken et al.’s (1991) suggestion, the interaction pattern was further estimated by testing the nexuses between family-supportive leadership and positive affect and between family-supportive leadership and WLE at high and low (one SD above and below the mean respectively) segmentation preference levels. As Figure 3 shows, family-supportive leadership communication increased positive affect to a greater degree when segmentation preferences were high (simple slope = 0.519, p < .001) than when they were low (simple slope = 0.319, p < .001). Family-supportive leadership communication also increased WLE (see Figure 4) to a greater degree when segmentation preferences were high (simple slope = 0.588, p < .001) than when they were low (simple slope = 0.414, p < .001). Thus, H6 was rejected, while H7 and H8 were supported.Figure 3. Moderating effect of segmentation preference in the relationship between family-supportive leadership communication and positive affect. Figure 4. Moderating effect of segmentation preference in the relationship between family-supportive leadership communication and work-life enrichment. Discussion Grounded in SET, the current study examined the mechanisms through which family-supportive leadership communication influences the creativity of work-from-home employees in the context of the COVID-19 pandemic. The results of the analysis suggest that family-supportive leadership communication leads to better EOR quality, WLE, and positive affect, which in turn increases employees’ creativity. Family-supportive leadership communication and employees’ segmentation preferences had a positive joint effect on positive affect at work and WLE. These findings have significant theoretical and practical implications in organizational communication. This study is among the first to empirically investigate the link between family-supportive leadership communication and creativity. Numerous studies have highlighted the importance of various types of leadership in fostering employee creativity (e.g., Lee & Kim, 2021), but research examining family-supportive leadership behaviors remains scarce. In the context of COVID-19, the results of the current study demonstrate that leaders’ supportiveness for subordinates’ family issues is a crucial element in potentially improving employees’ creativity, which is a key asset for organizational resilience during a crisis. The fact that employee creativity improves organizations’ resilience and helps them effectively solve unexpected problems, address issues, and eventually build competitive advantage (Oldham & Cummings, 1996) demonstrates the importance of family-supportive leadership communication, especially for work-from-home employees during the pandemic who may face unexpected work-life conflicts and demands due in crises. This study’s examination of three mechanisms—the quality of EOR, employees’ positive affect, and WLE revealed the positive effect of family-supportive leadership communication on creativity. From a social exchange perspective, this study viewed family-supportive leadership communication as an essential socioemotional resource that can foster employees’ trusting and nurturing relationships with their organizations, balanced and enriching work and family life, as well as their positive emotions. This study identified positive emotion as a key proximate outcome of family-supportive leadership communication and delineates the subsequent social exchange mechanisms, in the form of EOR and WLE, which translated leadership communication into creativity during the COVID-19 crisis period. Family-supportive leadership communication fulfills the emotional, relational, and family needs in the workplace. To reciprocate these benefits they receive from the leaders, employees are motivated to pay back to their organization by exhibiting creativity in their work. This study thus enhances the theoretical proposition of SET to understand the motivations of creativity during the pandemic and contributes to the scholarly understanding of the dynamics of the leader support-creativity link by answering the question of how supervisors’ family support leads to creativity. The role of positive affect was notable in this study. The effect of family-supportive leadership communication on WLE was partially mediated by positive affect. In other words, family-supportive leadership communication evokes positive emotions in employees positive at work, which in turn spillover into their families. However, this positive affect does not necessarily relate to how much they trust, are satisfied with, or committed to their companies. This result may partially derive from the COVID-19 context of the study. The ways organizations or leaders effectively handle this crisis and the extent to which individuals are satisfied with their actions may exert a stronger influence on employees’ perceptions of their relationships with their companies. Our findings are particularly valuable given that this study only focused on “newly” remote employees whom the pandemic had partially forced to work from home. A rich body of literature has examined the importance of leadership communication and teleworkers’ productivity and engagement (e.g., Gibson et al., 2002). Teleworkers oftentimes volunteer to work at home to meet their own needs or because of their job characteristics (Golden et al., 2006). Admittedly, teleworkers who had been working at home before the pandemic could also likely be impacted by the stay-at-home work orders, causing work-home boundaries to be violated. Our study is among the first empirical attempts to test the effectiveness of leadership communication, focusing only on newly emerged remote workers in the midst of COVID-19 whose organizations asked them to work from home. These employees may have faced unexpected work- and family-related demands, which could have reduced their levels of productivity and their morale. With their experiences of the benefits and challenges of working-from-home, they may have altered their perceptions of the new norm of the workplace environment. This could be another issue that organizations should manage to meet their new expectations (e.g., hybrid work format) and improve the effectiveness and productivity of employees during and after the pandemic. By building a comprehensive model focusing on such employees, the current study explicates the implications of family-supportive leadership communication as an interpersonal and socio-emotional resource for these emerging types of workers and provides insights regarding ways to effectively manage work-from-home employees’ work-life issues during crises and boost their creativity in remote working environments. Finally, this study also showed that people’s boundary management preferences, which reflect how they regard their work and family roles, can also impact their positive affect and WLE in response to family-supportive leadership communication. Specifically, family-supportive leadership communication turned out to be more effective in enhancing positive affect and enriching work-life boundaries for segmenters who prefer to segment their work from their lives than for integrators. The analysis showed no significant difference between the two in terms of EOR. These findings suggest that segmenters are especially vulnerable to newly remote working environments caused by the pandemic because they are more likely to perceive the situation as a threat to their family-related roles and identities and to experience high levels of work-to-family guilt when work-to-family conflicts inevitably occur (Zhang et al., 2019). Likewise, their work identities and boundaries may have been impacted, which could threaten their family roles. By providing empirical evidence that supervisory support for such employees’ family concerns is even more critical for enriching their work-life boundaries and eliciting positive affect, the current study highlights the importance of individuals’ boundary preferences in managing work-from-home employees effectively. Moreover, it sheds light on organizational communication scholarship (e.g., Golden, 2009; Hoeven et al., 2017; Tracy & Rivera, 2010) by showing when and why domain-crossing leadership communication between work and home lives matter based on individuals’ predisposition. This study’s findings are valuable in practice as well. The blurred boundaries between work and family may cause employees to experience high demands in both domains while working from home. To mitigate increasing needs and potentially encourage employees to share creative ideas that may help organizations effectively overcome crises, organizational leaders and managers should exhibit their supportiveness, especially for the employees’ families. For example, leaders should respect and understand employees’ different family situations and needs through active interactions and discussion, using family-friendly language, and showing genuine care and concerns for family issues. Work-to-family conflicts may be inevitable during such times, and such efforts will help employees not only feel positive while working and trust their companies, but also perceive work demands as less of a threat to their family roles, which will enrich their family lives. These positive states toward both work and home will eventually enable them to exhibit creativity at work, which may prove critical for their organizations’ resilience in crises. This study’s analysis showed that family-supportive leadership communication is particularly effective for people with high segmentation preference levels in increasing positive affect and WLE, which in turn boosts creativity. Taking this into account, managerial training regarding the benefits of family support of employees may be a key intervention. Training should highlight the importance of identifying employees who prefer to segment their work and life and of frequently and proactively communicating and listening to the family-related concerns, needs, and interests of these employees when they are working from home. Limitations and Future Studies This study had several limitations that future research should seek to address. First, the demographics of the study participants varied; the study analyzed data of employees who were both married and unmarried and who had and did not have children. Although we controlled the variables in the model, individuals’ family demographic variables may significantly affect their work-life demands and the effectiveness of family-supportive leadership communication. Similarly, gender differences also exist. Given that women, especially women with children, are more likely to suffer emotionally than men during pandemics (Lyttelton et al., 2020), future studies could focus on specific groups of remote workers (e.g., working moms) to enrich our understanding of the dynamics of the work-from-home environment after the pandemic. Furthermore, our participants included workers in the U.S. from different organizations and industries, and most were White and highly educated. Thus, it was hard to identify the differences between types of workers (e.g., white-collar vs blue-collar workers) and the perspectives of minorities (e.g., people of color) may be underrepresented. Caution thus should be exercised in generalizing from our study samples. Finally, during the data collection period, participants’ levels of familiarity with remote working environments may have varied due to differing lengths of their working-from-home experiences. One possible issue is that family-supportive leadership communication may have been particularly important in the early stages of the pandemic when individuals’ unexpected family demands were high. Other research methods such as experimental or longitudinal designs could thus be employed in future studies to provide larger implications for the effectiveness of such leadership communication in the working-from-home environment going forward. Author Biographies Yeunjae Lee (PhD, Purdue University) is an assistant professor in the Department of Strategic Communication at University of Miami. Her main research interests include employee communication, internal issue/crisis management, and organizational diversity and justice. Jarim Kim (PhD, University of Maryland, 2014) is an associate professor in the department of communication at Yonsei University, Seoul, South Korea. Her research interests include public segmentation, activism, and crisis communication. ORCID iDs Yeunjae Lee https://orcid.org/0000-0002-2482-435X Jarim Kim https://orcid.org/0000-0002-2973-9656 Notes The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Yonsei University Research Grant of 2022 (2022-22-0180). 1 The current study did not particularly focus on the “creative” industries such as art, music, and architecture because employee creativity can exhibit in almost any occupation (Shalley et al., 2000) and creativity in their jobs and tasks is particularly important during the pandemic to help organizations to adapt to the new working environment (Tang et al., 2020). ==== Refs References Aiken L. S. West S. G. Reno R. R. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage. Amabile T. M. (1988). A model of creativity and innovation in organizations. Research in Organizational Behavior, 10 (1 ), 123–167. Anderson S. E. Coffey B. S. Byerly R. T. (2002). Formal organizational initiatives and informal workplace practices: Links to work-family conflict and job-related outcomes. Journal of Management, 28 (6 ), 787–810. 10.1177/014920630202800605 Ashforth B. E. Kreiner G. E. Fugate M. (2000). All in a day's work: Boundaries and micro role transitions. Academy of Management Review, 25 (3 ), 472–491. 10.5465/amr.2000.3363315 Atwater L. Carmeli A. (2009). Leader–member exchange, feelings of energy, and involvement in creative work. The Leadership Quarterly, 20 (3 ), 264–275. 10.1016/j.leaqua.2007.07.00 Bagger J. Li A. (2014). How does supervisory family support influence employees’ attitudes and behaviors? A social exchange perspective. Journal of Management, 40 (4 ), 1123–1150. 10.1177/0149206311413922 Blau P. (1964). Exchange and power in social life. New York, NY: Wiley. Carlson D. S. Kacmar K. M. Wayne J. H. Grzywacz J. G. (2006). Measuring the positive side of the work-family interface: Development and validation of a work–family enrichment scale. Journal of Vocational Behavior, 68 (1 ), 131–164. 10.1016/j.jvb.2005.02.002 Chan X. W. Kalliath T. Brough P. Siu O. L. O’Driscoll M. P. Timms C. (2016). Work-family enrichment and satisfaction: The mediating role of self-efficacy and work-life balance. The International Journal of Human Resource Management, 27 (15 ), 1755–1776. 10.1080/09585192.2015.1075574 Clark S. C. (2001). Work cultures and work/family balance. Journal of Vocational Behavior, 58 (3 ), 348–365. 10.1006/jvbe.2000.1759. Clore G. L. Schwarz N. Conway M. (1994). Affective causes and consequences of social information processing. In Wyer R. S. Srull T. K. (Eds), Handbook of social cognition: Basic processes; Applications (pp. 323–417). Mahwah, NJ: Lawrence Erlbaum Associates. Crain T. L. Stevens S. C. (2018). Family‐supportive supervisor behaviors: A review and recommendations for research and practice. Journal of Organizational Behavior, 39 (7 ), 869–888. 10.1002/job.2320 Cropanzano R. Dasborough M. T. Weiss H. M. (2017). Affective events and the development of leader-member exchange. Academy of Management Review, 42 (2 ), 233–258. 10.5465/amr.2014.0384 Cropanzano R. Mitchell M. S. (2005). Social exchange theory: An interdisciplinary review. Journal of Management, 31 (6 ), 874–900. 10.1177/0149206305279602 Derks D. Bakker A. B. Peters P. van Wingerden P. (2016). Work-related smartphone use, work–family conflict and family role performance: The role of segmentation preference. Human Relations, 69 (5 ), 1045–1068. 10.1177/0018726715601890 Edwards J. R. Rothbard N. P. (2000). Mechanisms linking work and family: Clarifying the relationship between work and family constructs. Academy of Management Review, 25 (1 ), 178–199. 10.5465/amr.2000.2791609 Elflein J. (2020). Number of cumulative cases of coronavirus (COVID-19) in the United States from January 22 to August 17, 2020. https://www.statista.com/statistics/1103185/cumulative-coronavirus-covid19-cases-number-us-by-day/ Estrada C. A. Isen A. M. Young M. J. (1994). Positive affect improves creative problem solving and influences reported source of practice satisfaction in physicians. Motivation and Emotion, 18 (4 ), 285–299. 10.1007/BF02856470 Fairhurst G. T. Connaughton S. L. (2014). Leadership: A communicative perspective. Leadership, 10 (1 ), 7–35. 10.1177/1742715013509396 Folkman S. Moskowitz J. T. (2000). Positive affect and the other side of coping. American Psychologist, 55 (6 ), 647–654. 10.1037/0003-066X.55.6.647 10892207 Ford C. M. (1996). A theory of individual creative action in multiple social domains. Academy of Management Review, 21 (4 ), 1112–1142. 10.5465/amr.1996.9704071865 Fredrickson B. L. Branigan C. (2005). Positive emotions broaden the scope of attention and thought-action repertoires. Cognition & Emotion, 19 (3 ), 313–332. 10.1080/02699930441000238 21852891 Gibson J. W. Blackwell C. W. Dominicis P. Demerath N. (2002). Telecommuting in the 21st century: Benefits, issues, and a leadership model which will work. Journal of Leadership Studies, 8 (4 ), 75–86. 10.1177/107179190200800407 Golden A. G. (2009). Employee families and organizations as mutually enacted environments: A sensemaking approach to work—life interrelationships. Management Communication Quarterly, 22 (3 ), 385–415. 10.1177/0893318908327160 Golden T. D. Veiga J. F. Simsek Z. (2006). Telecommuting's differential impact on work-family conflict: Is there no place like home? Journal of Applied Psychology, 91 (6 ), 1340. 10.1037/0021-9010.91.6.1340 17100488 Gratton L. (2020). How to help employees work from home with kids. MIT sloan management review. https://sloanreview.mit.edu/article/how-to-help-employees-work-from-home-with-kids/ Greenhaus J. H. Powell G. N. (2006). When work and family are allies: A theory of work-family enrichment. Academy of Management Review, 31 (1 ), 72–92. 10.5465/amr.2006.19379625 Hair J. F. Black W.C. Babin B. J. Anderson R.E. Tatham R. L. (Eds), (2006). Multivariate data analysis. Upper Saddle River: Pearson Prentice Hall. Hammer L. B. Kossek E. E. Yragui N. L. Bodner T. E. Hanson G. C. (2009). Development and validation of a multidimensional measure of family supportive supervisor behaviors (FSSB). Journal of Management, 35 (4 ), 837–856. 10.1177/0149206308328510 21660254 Hanson G. C. Hammer L. B. Colton C. L. (2006). Development and validation of a multidimensional scale of perceived work-family positive spillover. Journal of Occupational Health Psychology, 11 (3 ), 249. 10.1037/1076-8998.11.3.249 16834473 Harrison E. B. Mühlberg J. (2014). Leadership communication: How leaders communicate and how communicators lead in the today's global enterprise. Business Expert Press. Heller D. Watson D. Ilies R. (2004). The role of person versus situation in life satisfaction: A critical examination. Psychological Bulletin, 130 (4 ), 574. 10.1037/0033-2909.130.4.574 15250814 Herhold K. (2020). Working from home during the coronavirus pandemic: The state of remote work. Clutch. https://clutch.co/real-estate/resources/state-of-remote-work-during-coronavirus-pandemic Hoeven C. L. Miller V. D. Peper B. Dulk L. (2017). The work must go on”: The role of employee and managerial communication in the use of work-life policies. Management Communication Quarterly, 31 (2 ), 194–229. 10.1177/0893318916684980 29708121 Hon L. C. Grunig J. E. (1999). Guidelines for measuring relationships in public relations. Gainesville, FL: Institute for Public Relations, Commission on PR Measurement and Evaluation. Hu L. Bentler P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6 (1 ), 1–55. 10.1080/10705519909540118. Jang S. J. (2009). The relationships of flexible work schedules, workplace support, supervisory support, work-life balance, and the well-being of working parents. Journal of Social Service Research, 35 (2 ), 93–104. 10.1080/01488370802678561 Kossek E. E. Lambert S. J. (Eds), (2004). Work and life integration: Organizational, cultural, and individual perspectives. London: Psychology Press. Kreiner G. E. (2006). Consequences of work-home segmentation or integration: A person-environment fit perspective. Journal of Organizational Behavior: The International Journal of Industrial, Occupational and Organizational Psychology and Behavior, 27 (4 ), 485–507. 10.1002/job.386 Kreiner G. E. Hollensbe E. C. Sheep M. L. (2009). Balancing borders and bridges: Negotiating the work-home interface via boundary work tactics. Academy of Management Journal, 52 (4 ), 704–730. 10.5465/amj.2009.43669916 Lapierre L. M. Allen T. D. (2006). Work-supportive family, family-supportive supervision, use of organizational benefits, and problem-focused coping: Implications for work-family conflict and employee well-being. Journal of Occupational Health Psychology, 11 (2 ), 169–181. 10.1037/1076-8998.11.2.169 16649850 Larson B. Z. Vroman S. R. Makarius E. E. (2020). A guide to managing your (newly) remote workers. In Harvard business review. https://hbr.org/2020/03/a-guide-to-managing-your-newly-remote-workers Lee Y. (2021). Linking internal CSR with the positive communicative behaviors of employees: The role of social exchange relationships and employee engagement. Social Responsibility Journal, 18 (2 ), 348–367. 10.1108/SRJ-04-2020-0121. Lee Y. Kim J. (2021). Cultivating employee creativity through strategic internal communication: The role of leadership, symmetry, and feedback seeking behaviors. Public Relations Review, 47 (1 ), 101998. 10.1016/j.pubrev.2020.101998 Lee Y. Mazzei A. Kim J. N. (2018). Looking for motivational routes for employee-generated innovation: Employees’ scouting behavior. Journal of Business Research, 91 , 286–294. 10.1016/j.jbusres.2018.06.022 Li A. Bagger J. (2011). Walking in your shoes: Interactive effects of child care responsibility difference and gender similarity on supervisory family support and work-related outcomes. Group & Organization Management, 36 (6 ), 659–691. 10.1177/1059601111416234 Liu J. Kwan H. K. Lee C. Hui C. (2013). Work-to-family spillover effects of workplace ostracism: The role of work-home segmentation preferences. Human Resource Management, 52 (1 ), 75–93. 10.1002/hrm.21513 Lyttelton T. Zang E. Musick K. (2020). Gender differences in telecommuting and implications for inequality at home and work. 10.31235/osf.io/tdf8c McCarthy A. Cleveland J. N. Hunter S. Darcy C. Grady G. (2013). Employee work-life balance outcomes in Ireland: A multilevel investigation of supervisory support and perceived organizational support. The International Journal of Human Resource Management, 24 (6 ), 1257–1276. 10.1080/09585192.2012.709189 Men L. R. Robinson K. L. (2018). It’s about how employees feel! examining the impact of emotional culture on employee–organization relationships. Corporate Communications: An International Journal, 23 (4 ), 470–491. 10.1108/CCIJ-05-2018-0065 Men L. R. Stacks D. (2014). The effects of authentic leadership on strategic internal communication and employee-organization relationships. Journal of Public Relations Research, 26 (4 ), 301–324. 10.1080/1062726X.2014.908720 Men L. R. Yue C. A. (2019). Creating a positive emotional culture: Effect of internal communication and impact on employee supportive behaviors. Public Relations Review, 45 (3 ), 101764. 10.1016/j.pubrev.2019.03.001 Mervosh S. Lu D. Swales V. (2020). See which states and cities have told residents to stay at home. The New York times. https://www.nytimes.com/interactive/2020/us/coronavirus-stay-at-home-order.html Miller J. (1997). All work and no play may be harming your business. Management Development Review, 10 (6/7 ), 254–255. Ogbeibu S. Senadjki A. Gaskin J. (2018). The moderating effect of benevolence on the impact of organisational culture on employee creativity. Journal of Business Research, 90 , 334–346. 10.1016/j.jbusres.2018.05.032 Oldham G. R. Cummings A. (1996). Employee creativity: Personal and contextual factors at work. Academy of Management Journal, 39 (3 ), 607–634. 10.5465/256657 Ong H. L. C. Jeyaraj S. (2014). Work-life interventions: Differences between work-life balance and work-life harmony and its impact on creativity at work. Sage Open, 4 (3 ), 2158244014544289. 10.1177/2158244014544289 Pan W. Sun L. Y. Lam L. W. (2020). Employee–organization exchange and employee creativity: A motivational perspective. The International Journal of Human Resource Management, 31 (3 ), 385–407. 10.1080/09585192.2017.1331368 Regan M. (1994). Beware the work/family culture shock. Personnel Journal, 73 (1 ), 35–36. Rothbard N. P. Phillips K. W. Dumas T. L. (2005). Managing multiple roles: Work-family policies and individuals’ desires for segmentation. Organization Science, 16 (3 ), 243–258. 10.1287/orsc.1050.0124 Sahay S. Wei W. (2021). Work-family balance and managing spillover effects communicatively during COVID-19: Nurses’ perspectives (pp. 1–10). Health Communication. 10.1080/10410236.2021.1923155 Sekerka L. E. Vacharkulksemsuk T. Fredrickson B. L. (2012). Positive emotions: Broadening and building upward spirals of sustainable development. In The Oxford handbook of positive organizational scholarship (pp. 168–177). 10.1093/oxfordhb/9780199734610.013.0013 Sen P. Deb P. Kumar N. (2021). The challenges of work from home for organizational design. California Review Management. https://cmr.berkeley.edu/2021/07/the-challenges-of-work-from-home-for-organizational-design/ Shalley C. E. Gilson L. L. (2004). What leaders need to know: A review of social and contextual factors that can foster or hinder creativity. The Leadership Quarterly, 15 (1 ), 33–53. 10.1016/j.leaqua.2003.12.004 Shalley C. E. Gilson L. L. Blum T. C. (2000). Matching creativity requirements and the work environment: Effects on satisfaction and intentions to leave. Academy of Management Journal, 43 (2 ), 215–223. 10.5465/1556378 Shin S. J. Zhou J. (2003). Transformational leadership, conservation, and creativity: Evidence from Korea. Academy of Management Journal, 46 (6 ), 703–714. 10.5465/30040662 Shore L. M. Tetrick L. E. Taylor M. S. Coyle-Shapiro J. Liden R. C. McLean-Parks J. (2004). The employee-organization relationship: A timely concept in a period of transition. In Martocchio J. J. (Ed), Research in Personnel and Human Resources Management (pp. 291–370). Amsterdam: Elsevier. 10.1016/S0742-7301(04)23007-9 Siu O. L. Bakker A. B. Brough P. Lu C. Q. Wang H. Kalliath T. Timms C. (2015). A three-wave study of antecedents of work-family enrichment: The roles of social resources and affect. Stress and Health, 31 (4 ), 306–314. 10.1002/smi.2556 26468889 Sonnentag S. (2003). Recovery, work engagement, and proactive behavior: A new look at the interface between nonwork and work. Journal of Applied Psychology, 88 (3 ), 518–528. 10.1037/0021-9010.88.3.518 12814299 Sonnentag S. Binnewies C. Mojza E. J. (2008). Did you have a nice evening?” A day-level study on recovery experiences, sleep, and affect. Journal of Applied Psychology, 93 (3 ), 674. 10.1037/0021-9010.93.3.674 18457495 Spreitzer G. Sutcliffe K. Dutton J. Sonenshein S. Grant A. M. (2005). A socially embedded model of thriving at work. Organization Science, 16 (5 ), 537–549. 10.1287/orsc.1050.0153 Straub C. (2012). Antecedents and organizational consequences of family supportive supervisor behavior: A multilevel conceptual framework for research. Human Resource Management Review, 22 (1 ), 15–26. 10.1016/j.hrmr.2011.08.001 Tang C. Ma H. Naumann S. E. Xing Z. (2020). Perceived work uncertainty and creativity during the covid-19 pandemic: The roles of Zhongyong and creative self-efficacy. Frontiers in Psychology, 11 , 3008. 10.3389/fpsyg.2020.596232 Tang Y. Huang X. Wang Y. (2017). Good marriage at home, creativity at work: Family-work enrichment effect on workplace creativity. Journal of Organizational Behavior, 38 (5 ), 749–766. 10.1002/job.2175 Ten Brummelhuis L. L. Bakker A. B. (2012). A resource perspective on the work-home interface: The work-home resources model. American Psychologist, 67 (7 ), 545–556. 10.1037/a0027974 22506688 Thomas L. T. Ganster D. C. (1995). Impact of family-supportive work variables on work-family conflict and strain: A control perspective. Journal of Applied Psychology, 80 (1 ), 6–15. 10.1037/0021-9010.80.1.6 Thompson C. A. Beauvais L. L. Lyness K. S. (1999). When work-family benefits are not enough: The influence of work-family culture on benefit utilization, organizational attachment, and work-family conflict. Journal of Vocational Behavior, 54 (3 ), 392–415. 10.1006/jvbe.1998.1681 Thompson C. A. Prottas D. J. (2006). Relationships among organizational family support, job autonomy, perceived control, and employee well-being. Journal of Occupational Health Psychology, 11 (1 ), 100–118. 10.1037/1076-8998.10.4.100 16551178 Tracy S. J. Rivera K. D. (2010). Endorsing equity and applauding stay-at-home moms: How male voices on work-life reveal aversive sexism and flickers of transformation. Management Communication Quarterly, 24 (1 ), 3–43. 10.1177/0893318909352248 van Katwyk P. T. Fox S. Spector P. E. Kelloway E. K. (2000). Using the Job-Related Affective Well-Being Scale (JAWS) to investigate affective responses to work stressors. Journal of Occupational Health Psychology, 5 (2 ), 219–230. 10.1037/1076-8998.5.2.219 10784286 Wayne J. H. Randel A. E. Stevens J. (2006). The role of identity and work-family support in work-family enrichment and its work-related consequences. Journal of Vocational Behavior, 69 (3 ), 445–461. 10.1016/j.jvb.2006.07.002 Wepfer A. G. Allen T. D. Brauchli R. Jenny G. J. Bauer G. F. (2018). Work-life boundaries and well-being: Does work-to-life integration impair well-being through lack of recovery? Journal of Business and Psychology, 33 (6 ), 727–740. 10.1007/s10869-017-9520-y Xin J. Chen S. Kwan H. K. Chiu R. K. Yim F. H. K. (2018). Work-family spillover and crossover effects of sexual harassment: The moderating role of work-home segmentation preference. Journal of Business Ethics, 147 (3 ), 619–629. 10.1007/s10551-015-2966-9 Yu M. C. Mai Q. Tsai S. B. Dai Y. (2018). An empirical study on the organizational trust, employee-organization relationship and innovative behavior from the integrated perspective of social exchange and organizational sustainability. Sustainability, 10 (3 ), 864. 10.3390/su10030864 Zhang M. Zhao K. Korabik K. (2019). Does work-to-family guilt mediate the relationship between work-to-family conflict and job satisfaction? Testing the moderating roles of segmentation preference and family collectivism orientation. Journal of Vocational Behavior, 115 , 103321. 10.1016/j.jvb.2019.103321 Zhou J. George J. M. (2001). When job dissatisfaction leads to creativity: Encouraging the expression of voice. Academy of Management Journal, 44 (4 ), 682–696. 10.5465/3069410
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==== Front Perfusion Perfusion spprf PRF Perfusion 0267-6591 1477-111X SAGE Publications Sage UK: London, England 36476240 10.1177_02676591221144905 10.1177/02676591221144905 Original Manuscript Single-center experience of temporary-permanent pacemaker use in COVID-19 patients supported with veno-venous ECMO: A case series https://orcid.org/0000-0001-7580-9718 Frederiks Pascal 12 Bianchi Paolo 134 Hunnybun Daniel 5 Behar Jonathan 5 Garfield Ben 13 Ledot Stéphane 134 1 Department of Adult Intensive Care, 4964 Royal Brompton and Harefield NHS Foundation Trust , London, UK 2 Department of Cardiovascular Diseases, 74883 University Hospitals Leuven , Leuven, Belgium 3 Division of Anaesthetics, Pain Medicine, and Intensive Care, Department of Surgery and Cancer, 156726 Imperial College London , London, UK 4 Department of Anaesthesia, 4964 Royal Brompton and Harefield NHS Foundation Trust , London, UK 5 Department of Cardiology, 4964 Royal Brompton and Harefield NHS Foundation Trust , London, UK Pascal Frederiks, Department of Cardiovascular Diseases, University Hospitals Leuven, Herestraat 49, Leuven 3000, Belgium. Email: [email protected] 8 12 2022 8 12 2022 02676591221144905© The Author(s) 2022 2022 SAGE Publications This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. Introduction: In the first year of the COVID-19 pandemic, nine out of 129 patients (7%) developed life-threatening bradycardia episodes ultimately requiring a TPPM, whilst being supported with VV-ECMO for severe COVID-19 ARDS in our tertiary cardio-pulmonary failure center. Analysis: All subjects had asystole due to sinus node dysfunction and experienced at least one episode involving cardiopulmonary resuscitation. Most bradycardic events were seen in the context of vagal hypersensitivity. Mean time from general ICU admission to TPPM insertion was 20.6 ± 8.9 days. One patient developed a large chest wall hematoma weeks after TPPM implantation, no other TPPM-related issues were observed. No patient required a long-term pacing system. Six-months survival rate was high (89%). Conclusion: These findings suggested that transient life-threatening sinus node disease is not uncommon in ECMO-dependent COVID-19 ARDS patients. TPPM with an active fixation lead is sometimes needed to facilitate ongoing ICU care, however, long-term permanent pacing was not required. externalized temporary-permanent pacemakers COVID-19 veno-venous ECMO sinus node disease edited-statecorrected-proof typesetterts10 ==== Body pmcIntroduction Bradyarrhythmias have been reported in hospitalized patients with coronavirus disease 2019 (COVID-19). Niehues et al.1 described an incidence of 6% severe bradycardia during ICU stay in COVID-19 patients with moderate to severe acute respiratory distress syndrome (ARDS). Severe bradycardia requiring acute medical intervention are, however, less common.2–4 The initial approach of profound bradycardia in patients with COVID-19 ARDS should not differ from other patients.5 After ruling out reversible causes, medical management and secondly, temporary pacing should be considered. Early implantation of a permanent pacemaker system in patients with severe COVID-19, may be avoided, as the underlying mechanism is likely to be reversible and these patients face a higher risk of mortality from non-bradycardic causes.5,6 In our center, we use externalized temporary-permanent pacemakers (TPPM) in which an externally placed permanent pacemaker (i.e. transcutaneous setup, with pacemaker battery external) is connected to an active, screw-in fixation lead to support patients with life-threatening bradycardias during their protracked veno-venous extracorporeal membrane oxygenation (VV-ECMO) run. In this study, we aim to evaluate the feasibility and safety of TPPM during severe COVID-19 supported with respiratory ECMO. Assessment of the mechanism of bradycardia and the need for a permanent pacemaker system after COVID-19 ARDS recovery were also reviewed. Methods We conducted a retrospective analysis on all consecutive laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infected patients supported with respiratory ECMO in a tertiary cardio-respiratory failure center (Royal Brompton and Harefield Trust, UK), admitted between 20 March 2020 and 31 March 2021. Outcome data were analyzed until 6 months after hospitalization. To compare the frequency of TPPM use whilst on respiratory ECMO, an additional review of our VV-ECMO cohort of the 5 years before the COVID-19 pandemic was done, including the period from March 2015 until March 2020. This observational study was registered locally and was conducted as a service evaluation as defined by the UK NHS Health Research Authority (www.hra.nhs.uk), and therefore did not require review by the Research Ethics Committee. Due to the retrospective character of the study, the requirement for informed consent was waived. Entry criteria for respiratory ECMO candidacy were based on the National Health Services (NHS) of England and Scotland. These criteria were revised at the beginning of the COVID-19 pandemic.7 Our center is one of the five centers commissioned by NHS England to provide ECMO support to adults with respiratory failure. Patients with veno-arterial ECMO support were excluded from the analysis. Externalized TPPM use was considered in case of life-threatening bradycardia after excluding reversible causes and initial medical treatment attempt if tolerated. The decision for device insertion was made by the electrophysiology and critical care team. Data were collected from the electronic healthcare records. Data acquisition was started after the observation period. Patients who developed severe bradycardia requiring a pacing system whilst on VV-ECMO were further evaluated. In brief, this included patients’ demographics, clinical characteristics, pacemaker-related data and clinical outcomes including device performance, duration of TPPM therapy, device related complications, ICU and hospital survival, and 6-months survival after hospitalization. Pacing checks at implant and prior to removal were reviewed. Conventional pacing parameters were used at the discretion of the operator during implantation: pacing threshold <1.5 V at 0.4 ms, R-wave sensing amplitude >3 mV and pacing lead impedance of 200–2000 Ω. In the non-COVID-19 group, the use of TPPM during respiratory ECMO was analyzed with regards to frequency of TPPM use, pacing indication and TPPM-related complications during the ECMO run. Bradycardia was defined as a heart rate below 60 beats per minute. Descriptive variables are presented as a number (percentage), median and range, or mean with standard deviation, as appropriate. A Fisher’s exact test was used to compare the frequency of TPPM use during ECMO support before and throughout the first year of the COVID-19 pandemic. Data were defined as statistically significant at a p-value <0.05. Statistical analysis was conducted with IBM SPSS Statistics v24.0. Results Among 129 COVID-19 patients who were admitted with respiratory failure requiring VV-ECMO in the first year of the pandemic, nine patients (7%, median age 46 (33–60) years) developed life-threatening bradycardic episodes ultimately requiring TPPM (see Table 1). Profound sinus bradycardia, that is heart rate below 50 beats per minute, was noted in 22 patients (17%). Three patients were treated only medically with glycopyrronium boluses, while in nine patients backup with a TPPM was provided.Table 1. Clinical characterization of COVID-19 patients with TPPM. Case number 1 2 3 4 5 6 7 8 9 Demographics and clinical characteristics  Age (years) 43 33 60 53 41 37 49 48 46  Gender Male Male Male Female Male Female Female Female Male  BMI (kg/m2) 23.7 49.4 33.9 47.7 23.1 25 29.2 40.1 28.7  Heart failure No No No Yesa No No No No No  Ischemic heart disease No No No No No No No No No  History of arrhythmia No No No No No No No No No  Diabetes Yes No Yes Yes Yes No No No No  Hypertension Yes No Yes Yes No No No No No  Smoking No No No No No No No No No  Renal insufficiency No No No No No No No No No Physiologic Characteristics On ECMO Retrieval  PaO2 to FiO2 ratio (mmHg) 83.3 63.9 58.5 68.6 47.3 85.5 110.3 130.5 62.3  Days of IMV before ECMO 8 1 1 2 4 6 4 3 6  Murray lung injury score 3.25 2.25 3.5 3 3.5 3.75 3.5 3 3.3  Admission SOFA score 12 10 11 7 6 4 7 5 5  RESP score 4 7 4 5 4 4 5 4 4 Medical COVID-19 treatment  Steroids Yes No Yes Yes Yes Yes Yes No Yes  Tocilizumab No No No No Yes No No No No  Baricitinib No No No No No Yes No No No  Hydroxychloroquine No No No No No No No No No  Remdesivir Yes No No Yes No Yes Yes No No Laboratory tests at first bradycardic event (normal values)  Hemoglobin, g/dL (134–166) 88 80 75 94 94 83 75 109 89  CRP, mg/L (<3) 99 114 186 19 88 402 5 293 130  Ferritin, ng/mL (18–270) 525 930 510 247 736 217 354 1370 1337  D-dimer, ng/mL (208–318) 2758 3134 4400 605 5896 3109 845 13,140 3505  High-sensitivity TnI, ng/L (<11.6) 10.5 22.9 5.5 3.3 3.8 11.4 17.9 7.4 3.9 Electrocardiographic findings, At first bradycardic event  Sinus rhythm Yes Yes Yes Yes Yes Yes Yes Yes Yes  Ventricular rate, beats per minute 109 81 86 64 67 101 68 50 88  PR interval, msec 136 156 161 171 178 170 168 160 166  QRS width, msec 78 80 103 154 96 97 94 98 92  BBB present No No No LBBB No No No No No Abbreviations: n: number; SD: standard deviation; BMI: body mass index; VV-ECMO: extracorporeal membrane oxygenation; SOFA: Sequential Organ Failure Assessment; RESP: Respiratory ECMO survival prediction; WCC: White cell count; CRP: C-reactive protein; TnI: troponin I; LBBB: left bundle branch block. asuspicion of an unknown asymptomatic dilated cardiomyopathy in one patient. Significant anemia, electrolyte disturbances and thyroid dysfunction were excluded. Main comorbidities were obesity (mean BMI 33 ± 10 kg/m2), diabetes mellitus (44%) and arterial hypertension (33%). In retrospect one patient probably had preexisting chemotherapy induced cardiomyopathy. Most patients received systemic steroids as a treatment for severe COVID-19 pneumonitis (78%). All nine patients developed asystole due to sinus node dysfunction (see Table 2). In three subjects, bradycardic episodes were initially contributed to bradycardizing drugs. Stopping these drugs did, however, not resolve the issue of life-threatening bradycardic episodes. All required at least one period of cardiopulmonary resuscitation. Atrioventricular block was not observed in any patient. Sinus arrests were largely triggered (56%) by vagal manoeuvers like tracheal suctioning, coughing, head tilting or rolling of the patient, though a significant number of sinus arrests happened spontaneously as well. In patient #1, the ECMO return cannula was subsequently found to be impinging on the interatrial septum, but repositioning of the cannula did not prevent the recurrence of bradycardia.Table 2. Bradycardia-related characteristics and interventions. Case No Diagnosis Trigger Need for CPR AVN blocking agents Narcotic and sedative drugs Abnormal ECG and TTE findings Suspicion of acute coronary syndrome, (peri)myocarditis, or other TPPM implantation Initial pacing mode 1 Sinus arrest (SND, brady-tachy syndrome) After atrial tachycardia runs 1 time — Oxycodon, midazolam, propofol Return cannula migrated to interatrial septum, severe pulmonary hypertension, moderately impaired right ventricular function — Right ventricular lead, via right axillary vein VVI 50 2 Sinus arrest (SND) Vagal response 1 time Beta-blocker (stopped) Fentanyl, midazolam, propofol, ketamine, clonidine (stopped) Mildly impaired right ventricular function, unable to estimate pulmonary pressures — Right atrial lead, via left internal jugular vein AAI 50 3 Sinus arrest (SND) Vagal response and spontaneously 3 times — Oxycodon, propofol Mild right ventricle dilation, severe pulmonary hypertension — Right ventricular lead, via left internal jugular vein VVI 50 4 Sinus arrest (SND) Vagal response 2 times — Fentanyl, midazolam, propofol - Left bundle branch block Unknown preexisting chemotherapy induced cardiomyopathy (?) Right ventricular lead, via left internal jugular vein VVI 50 - Dilated left ventricle with severely reduced ejection fraction (LV EF 25%) - Moderately impaired right ventricle function 5 Sinus arrest (SND) Spontaneously 3 times Beta-blocker (stopped) Morphine, midazolam, propofol Mildly impaired right ventricular function, severe pulmonary hypertension — Right ventricular lead, via right internal jugular vein VVI 60 6 Sinus arrest (SND) Spontaneously 3 times — Fentanyl, midazolam, propofol Mildly impaired right ventricular function, severe pulmonary hypertension — Right ventricular lead, via right internal jugular vein VVI 60 7 Sinus arrest (SND) Vagal response 2 times — Fentanyl, midazolam, propofol Moderately impaired right ventricular function, indirect signs of severe pulmonary hypertension — Right ventricular lead, via right axillary vein VVI 60 8 Sinus arrest (SND) Vagal response 1 time — Fentanyl, propofol - Dynamic T wave changes in inferior and precordial leads Acute perimyocarditis, not confirmed with biopsy or cardiac MRI Right ventricular lead, via left axillary vein VVI 50 - Pericardial effusion, thickened pericardium- Moderate pulmonary hypertension 9 Sinus arrest (SND) Spontaneously 2 times — Fentanyl, midazolam, propofol, dexmedetomidine (stopped) Mildly impaired right ventricular function, mild pulmonary hypertension — Right ventricular lead, via left internal jugular vein VVI 40 Abbreviations: CPR: cardiopulmonary resuscitation; AVN: atrioventricular nodal; ECG: electrocardiogram; TTE: transthoracic echocardiography; TPPM: temporary permanent pacemaker; SND: sinus node dysfunction; MRI: magnetic resonance imaging. Eight out of nine patients received an externalized TPPM with a bipolar, active fixation lead (St Jude/Abbott Tendril™ STS 2088TC) placed in the right ventricle, one patient was treated with a atrial lead. Mean time from general intensive care unit (ICU) admission to TPPM insertion was 20.6 ± 8.9 days. The configuration of the TPPM was at the discretion of the cardiologist performing the procedure. The pacemaker lead insertion site varied from left or right internal jugular and left or right axillary vein, depending on the presence of a jugular ECMO cannula or other indwelling catheters. Ultrasound guidance was used for venous access approach, and subsequently fluoroscopy for positioning and fixation of the pacemaker lead. Systemic anticoagulation, such as unfractionated heparin or argatroban infusion, was held for the pacemaker lead insertion. The initial backup pacing rate was set between 40 and 60 beats per minute. This led to a median right ventricular pacing percentage of 1% (0.1%–35%), and <1% atrial pacing. Sensing amplitude, pacing threshold and pacing impedance remained all in acceptable range during follow-up (see Figure 1). After the acute phase, the rate was lowered to 30–40 beats per min to assess the need for a long-term pacing system.Figure 1. Device measurements. (a): TPPM amplitude, (b): TPPM threshold, (c): TPPM impedance. Dashed lines represent right atrial pacing system, solid lines are right ventricular pacing systems. Abbreviation: TPPM, temporary permanent pacemaker. One patient developed a left-sided large chest wall hematoma 3 weeks after TPPM insertion (via the left axillary vein) and whilst in multiple organ failure (see Figure 2). Coagulopathy correction, multiple blood transfusions and an attempted embolization in the catheterization lab were carried out. No other complications, such as lead dislocation, lead infection or secondary thrombosis (follow-up imaging in six out of nine patients available), were noted.Figure 2. CT imaging of a TPPM-related bleeding. (a): Sagittal CT imaging of a large left chest wall collection with heterogeneous attenuation, located between the pectoralis major and minor muscles (149 mm × 85 mm × 173 mm). The pacemaker wire traverses superiorly in the collection. (b): On the arterial phase study (axial plane), there is evidence of contrast blush at the deep margin of the collection, suggestive of active bleeding. A feeding vessel was not delineated. No patient required a long-term pacing system, with a follow-up period of 180 days after hospital discharge. All TPPM were removed before discharge from our ICU or afterwards in the referring hospital. Mean duration of TPPM backup therapy was 47.4 ± 34.1 days. Patients had a mean ECMO run of 50.8 ± 37.7 days and were 81.9 ± 44.8 (range 44–182) days in ICU. One patient died in multisystem organ failure secondary to COVID-19 whilst on ECMO. Long-term survival rate in this subgroup with TPPM was 89% at 6 months after hospital discharge, which is in line with our reported data for respiratory ECMO patients during the first period of the pandemic (84.9%).8 International data show a survival rate of around 60% for COVID-19 patients requiring ECMO support at the beginning of the pandemic, with a drop to about 50% after the first year.9 Our experience with TPPM during respiratory ECMO before the COVID-19 pandemic was limited. In a five-year period before the pandemic, 439 patients received respiratory ECMO support in our centre. In this group, two patients (0.5%) received an externalized TPPM, which is much less than during the pandemic (7% vs 0.5%, p < .001). It involved one VV-ECMO patient admitted for progressive interstitial lung disease with repeated vagally triggered asystolic arrests, and a second VV-ECMO patient with tachy-brady syndrome in the context of overwhelming influenza pneumonia with suspicion of acute myocarditis. Only the latter patient received a conventional permanent pacemaker after 23 days. Discussion In this COVID-19 study population, life-threatening bradycardia necessitating a temporary pacemaker system was not uncommon (7%) and was much more frequent than we experienced in the 5 years before the pandemic in patients with severe respiratory failure requiring VV-ECMO support. All subjects developed asystole due to sinus node dysfunction. Remarkably, this occurred after a protracted time of severe COVID-19 ARDS (time on ICU until TPPM was 20.6 ± 8.9 days) with no improvement after correcting possible reversible causes. The clinical trajectory of severe COVID-19 ARDS during the initial waves was often marked by a hyperinflammatory immune response. The pathogenesis of bradycardia, and more specifically sinus node dysfunction, during COVID-19 is poorly understood; yet it has been postulated to have a multifactorial mechanism including direct cardiac injury, ferroptosis of sinoatrial pacemaker cells, ongoing inflammatory cytokine release, and vagal overstimulation due to neuroinvasion.3,7,10,13 Furthermore, a frequent finding is right heart dysfunction and/or pulmonary hypertension in critically ill COVID-19 ARDS, likewise in all patients of this ECMO subgroup. Whether subendocardial ischemia in a pressure overloaded right ventricle might be a contributing factor to bradycardia is uncertain.11 Anyhow, we report no patient requiring a permanent pacing system after the acute phase, suggestive of a transient phenomenon. Specific guidance regarding treatment of severe bradycardia during veno-venous extracorporeal membrane oxygenation (VV-ECMO) is lacking. Reversible causes must be ruled out. Medical treatment should be considered but this can result in tachycardia leading to a lower ratio of ECMO blood flow to native cardiac output and subsequently might impair tissue oxygenation. Moreover, between episodes of severe bradycardia, most patients had a relatively high heart rate, and so infusion with chronotropic agents was not considered as a reliable treatment option. If pacing is required, there are many factors to consider in this critically ill population, for example bleeding risk, infection risk, limited vascular access, a prolonged intensive care stay and high mortality rates. As good evidence for temporary pacing systems in this context is lacking, the indications are mainly clinically driven (Table 3).12 Externalized TPPM with active fixation lead carries a much lower risk of loss of capture and under-sensing compared to conventional temporary pacing systems. In other cohorts, including ICU patients, the technique has been shown to be reasonably safe in providing reliable pacing for a longer period, whilst also ensuring that pacing leads are easily removable if no longer needed.13–15Table 3. Considerations for externalized TPPM in respiratory ECMO. • Repeated episodes of life-threathening bradycardia • Transient underlying pathophysiology • Unclear overall prognosis • Avoidance of (drug-induced) tachycardia (cfr ECMO-flow-to-cardiac-output ratio) • Access site • Pacing mode (including atrial and/or ventricular pacing wire) • Active fixation lead (less lead dislocation, allowing safer mobilization) • Ongoing infection risk • High bleeding risk • Secondary thrombosis In the decision-making for extended temporary cardiac pacing, there are two transvenous approaches to consider. Conventional passive fixation leads offer the advantage of bedside placement, but lead displacement and failure to capture occur more often than with an active (screw-in) fixation mechanism.13 Placement of a TPPM with active fixation leads requires fluoroscopy guidance and is usually done in theatre or the catheterization lab. The distal placement of this active fixation lead is done according to the conventional way with a corkscrew tip anchored in the endocardium. Transport of these ECMO patients out of ICU can be challenging, even more when done in full personal protective equipment. Implantation of a pacemaker lead should be executed with caution as patients supported with extracorporeal life support often develop a significant device-associated coagulopathy which can even be more pronounced during critical illness. Anticoagulation should be held temporarily for the insertion, but there is no specific data to support this precaution. Additional ultrasound guidance is not only useful for the punction during insertion, but can also exclude preexisting venous thrombosis as this is a frequent complication in COVID-19.16 Generally, temporary transvenous cardiac pacing systems are inserted on the contralateral side to where a permanent pacing system could be placed. However, in this patient cohort, venous access was not always straightforward due to the frequent presence of ECMO cannula and central venous catheters in the jugular and/or subclavian veins. We had one patient in our cohort with a significant chest wall hemorrhage late after pacemaker lead insertion via the left axillary vein. Whether axillary veins should be avoided in ECMO patients is not clear. With regard to the prescription of the temporary pacemaker and its configuration, our cohort demonstrated a preference to implant a single chamber right ventricular lead. One patient had a single atrial lead. For patients with an unclear forward clinical trajectory such as ICU patients with multiple organ dysfunction, the possibility of more sinister and high degree AV block is possible and for safety purposes, most physicians will elect to implant a right ventricular lead as backup. However, the actual pathology in this cohort was sinus node dysfunction resulting in prolonged pauses rather than clear AV block. In this context, it is of course reasonable to implant a single chamber atrial pacemaker however if any AV block ensues, the patient would not be protected. There is only limited data on the use of temporary dual-chamber pacing in patients with critical illness and known heart disease, and this approach was not considered in our patient group.13 There is no data in the literature regarding TPPM use during ECMO. Important arguments for the use of an externalized TPPM with a active lead fixation during VV-ECMO are repeated episodes of life-threatening bradycardia with suspected transient underlying pathophysiology, higher risk of displacement of other (passive) temporary transvenous wires during a prolonged intensive care stay, recurrent septic episodes, and an unclear prognosis. In accordance with our limited data, TPPM with an active fixation lead appears to be a reliable technique during ECMO in COVID-19 patients. This technique allows safe nursing, mobilization and physiotherapy whilst on ECMO for a longer period and these findings are in line with study results in other (non-ECMO) patient groups.13 Based on our clinical experience, we would be reluctant to use TPPM in cases with a clear reversible cause for bradycardia leading to quick resolution after correction, high risk vascular access and major coagulopathy, and in case of futility in the clinical trajectory. Some limitations should however be kept in mind when reading this paper. Firstly, although being a tertiary cardio-respiratory center with a high volume ECMO service, our case series remains relatively small and data were retrospectively collected from one center only. Patients who developed bradycardic episodes in which no TPPM was used, were not analysed. Furthermore, there are strict criteria for respiratory ECMO candidacy which enhances a patient selection bias. As this was an observational trial, no clear cut-off criteria were set to trigger the implantation of a TPPM. Also, insertion site and timing for removal were at the discretion of the electrophysiology and critical care team. Altogether, the analysis of this cohort allowed us to provide a good idea about TPPM use whilst on VV-ECMO. Findings related to the underlying mechanism of sinus node dysfunction and/or dysregulation of the autonomic nervous system remain speculative. Conclusion In patients supported with ECMO for COVID-19 ARDS, 7% had a requirement for a temporary pacemaker implant for transient life-threathening sinus node dysfunction. The use of TPPM with an active fixation lead during respiratory ECMO is feasible and facilitated imperative nursing and mobilization for ongoing ICU care. ORCID iD Pascal Frederiks https://orcid.org/0000-0001-7580-9718 Author contributions: PF: concept, data collection and analysis, drafting article; PB: concept, critical revision of article; DH: data collection; JB: data interpretation, critical revision of article; BG: critical revision of article; SL: concept, critical revision of article. The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: SL is scientific board member at Inspira Technologies (Ra’anana, Israel). Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article. ==== Refs References 1 Niehues P Wegner FK Wolfes J , et al. Incidence and predictors of cardiac arrhythmias in patients with COVID-19 induced ARDS. J Cardiol 2022; 80 : 298–302. DOI: 10.1016/j.jjcc.2022.04.010 35589465 2 Capoferri G Osthoff M Egli A , et al. Relative bradycardia in patients with COVID-19. Clin Microbiol Infect 2021; 27 (2 ): 295–296. DOI: 10.1016/j.cmi.2020.08.013 32822885 3 Cakulev I Sahadevan J Osman MN , et al. A case report of unusually long episodes of asystole in a severe COVID-19 patient treated with a leadless pacemaker. Eur Hear J Case Rep 2020; 4 (FI1 ): 1–6. DOI: 10.1093/ehjcr/ytaa238 4 Gatto MC Persi A Tung M , et al. Bradyarrhythmias in patients with SARS-CoV-2 infection: a narrative review and a clinical report. Pacing Clin Electrophysiol 2021; 44 (9 ): 1607–1615. DOI: 10.1111/pace.14308 34219243 5 European Society of Cardiology. ESC guidance for the diagnosis and management of CV disease during the COVID-19 pandemic. Eur Heart J 2020; 45 : 1–115, www.who.int/nmh/publications/ncd-profiles-2018/en/ 6 Armstrong RA Kane AD Kursumovic E , et al. Mortality in patients admitted to intensive care with COVID-19: an updated systematic review and meta-analysis of observational studies. Anaesthesia 2021; 76 (4 ): 537–548. DOI: 10.1111/anae.15425 33525063 7 Camporota L Meadows C Ledot S , et al. Consensus on the referral and admission of patients with severe respiratory failure to the NHS ECMO service. Lancet Respir Med 2021; 9 (2 ): e16–e17. DOI: 10.1016/S2213-2600(20)30581-6 33428874 8 Garfield B Bianchi P Arachchillage D , et al. Six month mortality in patients with COVID-19 and non-COVID-19 viral pneumonitis managed with veno-venous extracorporeal membrane oxygenation. ASAIO J 2021; 67 (9 ): 982–988. DOI: 10.1097/MAT.0000000000001527 34144551 9 Ling RR Ramanathan K Sim JJL , et al. Evolving outcomes of extracorporeal membrane oxygenation during the first 2 years of the COVID-19 pandemic: a systematic review and meta-analysis. Crit Care 2022; 26 (1 ): 147. DOI: 10.1186/s13054-022-04011-2 35606884 10 Han Y Zhu J Yang L , et al. SARS-CoV-2 infection induces ferroptosis of sinoatrial node pacemaker cells. Circ Res 2022; 130 (7 ): 963–977. DOI: 10.1161/CIRCRESAHA.121.320518 35255712 11 Bleakley C Singh S Garfield B , et al. Right ventricular dysfunction in critically ill COVID-19 ARDS. Int J Cardiol 2021; 327 : 251–258. DOI: 10.1016/j.ijcard.2020.11.043 33242508 12 Boriani G Fauchier L Aguinaga L , et al. European heart rhythm association (EHRA) consensus document on management of arrhythmias and cardiac electronic devices in the critically ill and post-surgery patient, endorsed by heart rhythm society (HRS), Asia pacific heart rhythm society (APHRS), card. Europace 2019; 21 (1 ): 7–8. DOI: 10.1093/europace/euy110 29905786 13 Suarez K Banchs J . A review of temporary permanent pacemakers and a comparison with conventional temporary pacemakers. J Innov Card Rhythm Manag 2019; 10 (5 ): 3652–3661. DOI: 10.19102/icrm.2019.100506 32477730 14 Dawood FZ Boerkircher A Rubery B , et al. Risk of early mortality after placement of a temporary-permanent pacemaker. J Electrocardiol 2016; 49 (4 ): 530–535. DOI: 10.1016/j.jelectrocard.2016.05.004 27222360 15 Pang B Everest E Mcgavigan AD . Utility of atrial temporary pacing as an acute treatment for bradyarrhythmias and tachyarrhythmias in the intensive care setting with preservation of atrioventricular synchrony. Intern Med J 2012; 42 (5 ): 581–585. DOI: 10.1111/j.1445-5994.2012.02767.x 22616964 16 Vandenbriele C Gorog DA . Screening for venous thromboembolism in patients with COVID-19. J Thromb Thrombolysis 2021; 52 : 985–991. DOI: 10.1007/s11239-021-02474-8 34019231
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==== Front J Telemed Telecare J Telemed Telecare JTT spjtt Journal of Telemedicine and Telecare 1357-633X 1758-1109 SAGE Publications Sage UK: London, England 36484151 10.1177/1357633X221136305 10.1177_1357633X221136305 RESEARCH/Original Article Telehealth in cancer care during the COVID-19 pandemic Burbury Kate 1 Brooks Peter 23 Gilham Leslie 4 Solo Ilana 5 Piper Amanda 6 Underhill Craig 78910 Campbell Philip 11 Blum Robert 12 Brown Stephen 13 Barnett Frances 14 Torres Javier 15 Wang Xiaofang 16 Poole William 17 Grobler Anneke 1618 Johnston Genevieve 9 Beer Cassandra 9 Cross Hannah 9 https://orcid.org/0000-0002-3055-2119 Wong Zee Wan 171920 1 The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Department of Haematology 3085 Peter MacCallum Cancer Centre , Melbourne Health, Victoria, Australia 2 Centre for Health Policy, University of Melbourne School of Population and Global Health, Parkville, Victoria, Australia 3 Northern Health, Epping, Victoria, Australia 4 104351 Breast Cancer Network Australia , Camberwell, Victoria, Australia 5 Loddon Mallee Integrated Cancer Service, Bendigo Health 6 Strategy and Support Division, 56367 Cancer Council Victoria , Melbourne, Victoria, Australia 7 240253 Border Medical Oncology , Research Unit, Albury, NSW, Australia 8 Latrobe University, Wodonga, Victoria, Australia 9 Victorian Comprehensive Cancer Centre Alliance, Parkville, Australia 10 UNSW School of Clinical Medicine, Rural Clinical Campus, Albury, NSW, Australia 11 3487 Barwon Health , Deakin University School of Medicine, Geelong, Victoria, Australia 12 1645 Bendigo Health Cancer Centre , Bendigo, Victoria, Australia 13 Ballarat Regional Integrated Cancer Centre, Ballarat, Victoria, Australia 14 Cancer Services, Northern Hospital, Epping, Victoria, Australia 15 72544 Goulburn Valley Health , Shepparton, West Hume Integrated Cancer Services, Melbourne University - Shepparton Clinical School, Victoria, Australia 16 34361 Murdoch Children's Research Institute , Parkville, Victoria, Australia 17 5644 Peninsula Health , Frankston, Victoria, Australia 18 Department of Paediatrics, University of Melbourne, Melbourne, Australia 19 Monash University, Peninsula Clinical School, Frankston, Victoria, Australia 20 Southern Melbourne Integrated Cancer Service, Melbourne, Victoria, Australia Zee Wan Wong, Peninsula Health, Monash University, Peninsula Clinical School, Frankston, Victoria, Australia. Email: [email protected] 9 12 2022 9 12 2022 1357633X22113630531 5 2022 14 10 2022 © The Author(s) 2022 2022 SAGE Publications This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. Introduction The Victorian COVID-19 Cancer Network (VCCN) Telehealth Expert Working Group aimed to evaluate the telehealth (TH) experience for cancer patients, carers and clinicians with the rapid uptake of TH in early 2020 during the COVID-19 pandemic. Methods We conducted a prospective multi-centre cross-sectional survey involving eight Victorian regional and metropolitan cancer services and three consumer advocacy groups. Patients or their carers and clinicians who had TH consultations between 1 July 2020 and 31 December 2020 were invited to participate in patient and clinician surveys, respectively. These surveys were opened from September to December 2020. Results The acceptability of TH via both video (82.9%) and phone (70.4%) were high though acceptability appeared to decrease in older phone TH users. Video was associated with higher satisfaction compared to phone (87.1% vs 79.7%) even though phone was more commonly used. Various themes from the qualitative surveys highlighted barriers and enablers to rapid TH implementation. Discussion The high TH acceptability supports this as a safe and effective strategy for continued care and should persist beyond the pandemic environment, where patient preferences are considered and clinically appropriate. Ongoing support to health services for infrastructure and resources, as well as expansion of reimbursement eligibility criteria for patients and health professionals, including allied health and nursing, are crucial for sustainability. Telehealth cancer care COVID-19 pandemic Department of Health, State Government of Victoria https://doi.org/10.13039/501100003747 edited-statecorrected-proof typesetterts19 ==== Body pmcIntroduction With pandemic-related strategies and social restrictions, healthcare providers have integrated digital tools and technology to maintain connectivity and create value-based innovations for healthcare delivery. Telehealth (TH) consultation by video or phone has enabled continued care delivery, such as outpatient and pre-therapy reviews, pre-habilitation programmes, patient education, acute and late-effects monitoring, anti-cancer therapy delivery (‘tele-chemotherapy’)1 and clinical trials (‘tele-trials’).2–4 It is important to recognise that TH is a facilitator of virtual care systems, not intended to replace in-person healthcare but an adjunct and a solution when face-to-face consultation is logistically challenging, not feasible or practical. With successful implementation of TH strategies, including digital health infrastructure, all Australians, independent of geographical, social and local infrastructure constraints, can access timely and quality cancer care.5 The COVID-19 pandemic has been a major catalyst for widespread deployment of TH to reduce travel across jurisdictions and minimise foot traffic through healthcare services.6–8 However, TH which has been utilised for more than 20 years to deliver care,9 offers additional benefits such as reduction of financial burden,10 social disruption and psychosocial distress; enhanced monitoring to mitigate treatment-related toxicities, initiate timely interventions and education; expansion of clinical care and research reach, improved efficiencies and flexibility for integrated care delivery.11, 12 Data supports the use of TH, with comparable outcomes to standard models of care. In some circumstances, TH may be superior, such as multi-disciplinary shared care with local providers, for interventions that require frequent supervision including exercise programmes, intensive cancer therapies or for routine care.13–15 The Victorian COVID-19 Cancer Network (VCCN)16 was formed in early 2020 as a joint initiative of the Victorian Comprehensive Cancer Centre (VCCC) Alliance and the Monash Partners Comprehensive Cancer Consortium (MPCCC) for advocacy on cancer issues in relation to the pandemic, provide peer forums for both clinicians and consumers for shared problem solving and support, advice and initiatives for optimal care including consumer perspectives. The VCCN Telehealth Expert Working Group was one of eighteen Expert Groups formed and aimed to evaluate the experience of TH implementation, understand ongoing barriers and enablers to its acceptability and usage from both consumer and clinician perspectives.16,17 It was envisaged that this can help inform health services and policy-makers for sustainable TH implementation as part of ongoing routine care beyond the pandemic. A cross-sectional, multi-centre survey to elucidate TH experiences in cancer care across Victoria was performed. Methods A web-based survey was developed by the VCCN-TH Survey Steering Committee comprising quantitative questions, 5-point Likert Scale questions and qualitative open-answer questions (see Appendix). The patient survey comprised 34-items and the clinician survey 28-items. Central ethics approval was granted by Peter MacCallum Cancer Centre (PMac) Ethics Committee (HREC/65637/PMCC) and site-specific approvals were obtained locally. Participants (patients and carers) who had a TH appointment between 1 July 2020 and 31 December 2020 extracted via patient information systems were invited to participate. Patients or their carers were sent a survey link via text, on mobile devices or email. All provided informed consent at the beginning of the survey. Others were verbally invited, informed and consented before completing the survey over the phone with a researcher. Clinicians were sent email links by lead clinicians within their health services. Consumers from Breast Cancer Network Australia, Cancer Council Victoria and Prostate Cancer Foundation Australia were also invited to participate through the respective organisations and completed the surveys online. De-identified survey responses were entered directly into a REDCap database. Categorical variables were represented as numbers and percentages. The 5-point Likert Scale included ‘strongly agree’, ‘agree’, ‘neutral’, ‘disagree’ and ‘strongly disagree’. Answers were stratified into two categories: ‘agree and strongly agree’ versus all other options. Data analysis was performed using Stata version 16.1 (StataCorp LLC). The Chi-square test was used for testing relationships between categorical variables. Respondents (consumers and clinicians) who have indicated that they have used both video and phone TH have their experience captured separately within the survey for each modality. Qualitative data analysis was reported as individual and multiple cases, with interpretation of patterns and themes in the data, and how these patterns/themes contributed to insights, in terms of understanding the utility of TH for clinical care delivery from both clinician and consumer perspectives. Locality, defined as metropolitan or regional according to the location of the health provider, included PMac, Peninsula Health and Northern Health as metropolitan while Ballarat Health, Barwon Health, Goulburn Valley Health, Bendigo Health, Albury Wodonga Regional Cancer Centre as regional. No providers were remote. Patients’ residential postcodes were classified using the Modified Monash Model categories to determine the level of remoteness with MM1 being a major city and MM7 very remote18. Results Of the 10,814 patients and 600 clinicians invited to participate, survey response rates were 23.7% (n = 2564) for patients and 33.8% (n = 203) for clinicians. Of these 2564 patients, 84 did not consent while 727 started the survey but did not complete. Of the 203 clinicians, 2 did not consent, 43 started the survey but did not complete. Ninety-nine of the 1753 respondents who completed the survey had not used TH and were excluded, hence 1654 responses were included in the analysis. Surveys were completed by patients (94.4%) with the remaining by carers or family. Complete data from 1654 (15.3%) patients and 158 (26.3%) clinicians were included in this analysis. Patient and carer experience Demographics Most respondents were females (61.1%), with a median age of 63 years (range 21–94), with at least high school education (97.3%) and nominated English as their first language (91.9%) (Table 1). Notably, 7.8% had hearing or 4.5% visual impairment, 2.0% both. More than three-quarters of TH consultations occurred with metropolitan centres, the majority at PMac. The commonest cancer diagnoses were breast, haematological and genitourinary. Most TH consultations were follow-up appointments (90%), 10% were for new diagnosis and fewer than 10% clinical trials. Table 1. Patient respondents who used TH and completed the survey (a) Baseline characteristics N (%) Gender Female 1010 (61.1%) Male 639 (38.6%) Non-binary 3 (0.2%) Prefer not to say 2 (0.1%) Diagnosis Blood cancers 236 (14.3%) Bowel (or lower gastrointestinal) 108 (6.5%) Breast 541 (32.7%) Cancer of unknown primary 3 (0.2%) Gynaecological 39 (2.4%) Head and neck 32 (1.9%) Lung 86 (5.2%) Melanoma or skin 84 (5.1%) Neuro-oncology (brain or spine) 20 (1.2%) Not receiving cancer care 95 (5.7%) Prostate or other genitourinary (testicular, kidney or bladder) 192 (11.6%) Sarcoma 45 (2.7%) Upper gastrointestinal 32 (1.9%) Others 141 (8.5%) Most recent cancer appointment Long term follow-up 912 (55.1%) Newly diagnosed 162 (9.8%) Non-cancer related 132 (8.0%) Ongoing acute cancer care 448 (27.1%) Stage of cancer Early 322 (19.5%) Advanced 322 (19.5%) Remission (past cancer) 519 (31.4%) Unsure 332 (20.1%) Do not have cancer 129 (7.8%) Prefer not to say 30 (1.8%) Type of appointment First consultation 164 (9.9%) Follow up 1490 (90.1%) Routine care 1503 (90.9%) Clinical trials 151 (9.1%) (b) Telehealth modality according to provider location Most recent TH Video only Phone only Both video and phone Total Patients, n (%) 433 (26.2%) 907 (54.8%) 314 (19.0%) 1654 Provider location Metropolitan, n (%) 370 (28.5%) 669 (51.6%) 258 (19.9%) 1297 Regional, n (%) 56 (20.0%) 179 (63.9%) 45 (16.1%) 280 Unknown, n (%) 7 (9.1%) 59 (76.6%) 11 (14.3%) 77 Provider location PMac, n (%) 337 (33.2%) 465 (45.8%) 213 (21.0%) 1015 Others, n (%) 96 (15.0%) 442 (69.2%) 101 (15.8%) 639 TH modality – video versus phone Most TH consultations occurred via phone (55%), 26% video and just under one-fifth both. Overall, phone TH was more commonly used in regional compared to metropolitan centres (63.9% vs 51.6%, p < 0.001). More than half of the respondents had two or more TH consultations (57.3%). Majority (92.4%) indicated no difficulty accessing, seeing or hearing during the TH consultations. Forty-eight (7.8%) reported difficulties with either video component, audio, TH platforms, internet issues, lack of link or instructions. Supportive services were offered in 22.1% whilst few (2.0%) utilised interpreter services. The use of video TH increased with higher education level (Figure 1). During the TH consultations, few (14.7%) received assistance from local care providers but most respondents (94.5%) felt supported. Figure 1. Percentage of patient survey respondents using video or phone telehealth according to education level The overall satisfaction and acceptability of TH were high, with a preference for video compared to phone (87.1% vs 79.7%, p < 0.001; 82.9% vs 70.4%, p < 0.001, respectively; Table 2). There was a trend for lower acceptability with increasing age in phone TH users (Table 3). Video TH users were more likely to report communication with their care providers to be as good as face-to-face, compared to phone TH users (58.6% vs 45.7%; p < 0.001). Concordantly participants who had experienced phone TH were more likely to prefer face-to-face consultations (55.3% vs 45.8%, p < 0.001). Video TH users were more likely to use and recommend TH (video 79.0% vs phone 63.4%, p < 0.001). Concerns with privacy and confidentiality with TH were similar regardless of modality or locality of providers. Table 2. Patient survey – video versus phone TH Video TH (V) (Includes 433 video only and 314 video plus phone) (n = 747) Phone TH (P) (Includes 907 phone only and 314 video plus phone) (n = 1221) p-value (Video vs. Phone) Patient survey Total Metro (M) Reg (R) Unknown Total Metro (M) Reg (R) Unknown Location of services 747 628 (84.1%) 101 (13.5%) 18 (2.4%) 1221 927 (75.9%) 224 (18.3%) 70 (5.7%) Satisfied with TH 651 (87.1%) 552/628 (87.9%) 85/101 (84.2%) M vs R p = 0.294 973 (79.7%) 759/927 (81.9%) 163/224 (72.8%) M vs R p = 0.002 p < 0.001 TH acceptability 619 (82.9%) 529/628 (84.2%) 76/101 (75.2%) M vs R p = 0.026 859 (70.4%) 673/927 (72.6%) 142/224 (63.4%) M vs R p = 0.007 p < 0.001 Adequacy of communication when compared to face to face 438 (58.6%) 389/628 (61.9%) 40/101 (39.6%) M vs R p < 0.001 558 (45.7%) 453/927 (48.9%) 84/224 (37.5%) M vs R p = 0.002 p < 0.001 Would use TH post pandemic 588 (78.7%) 508/628 (80.9%) 67/101 (66.3%) M vs R p = 0.001 857 (70.2%) 671/927 (72.4%) 142/224 (63.4%) M vs R p = 0.008 p < 0.001 Concerns with privacy and confidentiality 37 (5.0%) 29/628 (4.6%) 6/101 (5.9%) M vs R p = 0.564 84 (6.9%) 66/927 (7.1%) 13/224 (5.8%) M vs R p = 0.484 p = 0.084 Prefer face to face consultations 342 (45.8%) 275/628 (43.8%) 60/101 (59.4%) M vs R p = 0.003 675 (55.3%) 500/927 (53.9%) 130/224 (58.0%) M vs R p = 0.269 p < 0.001 Would use TH again 670 (89.7%) 569/628 (90.6%) 86/101 (85.1%) M vs R p = 0.092 952 (78.0%) 735/927 (79.3%) 167/224 (74.6%) M vs R p = 0.122 p < 0.001 Recommend TH to others 590 (79.0%) 510/628 (81.2%) 68/101 (67.3%) M vs R p = 0.001 774 (63.4%) 610/927 (65.8%) 122/224 (54.5%) M vs R p = 0.002 p < 0.001 TH saved time 643 (86.1%) 553/628 (88.1%) 75/101 (74.3%) M vs R p < 0.001 1006 (82.4%) 776/927 (83.7%) 178/224 (79.5%) M vs R p = 0.130 p = 0.031 Metro (M): Metropolitan; Reg (R): Regional; M vs R: Metropolitan versus Regional. Table 3. Video or phone TH acceptability by age group Video TH (n = 747) Phone TH (n = 1221) Agree/Strongly agree n (%) by age group <35 years 20/23 (87.0%) 27/28 (96.4%) 35–< 50 95/107 (88.8%) 85/123 (69.1%) 50–< 65 277/335 (82.7%) 362/508 (71.3%) 65–< 75 165/205 (80.5%) 295/424 (69.6%) > = 75 years 62/77 (80.5%) 90/138 (65.2%) Score test for trend of odds: Video TH p = 0.084; Phone TH p = 0.034. Majority (95%) agreed that TH saved time regardless of modality or locality (Figure 2). Two-thirds of respondents saved 2 hours or longer (66.9%) with one-third saving 4–8 hours (31.4%). According to the Modified Monash Model categories of remoteness (MM1 – 7),18 90% of TH users residing in MM6 saved 4 or more hours; 59% MM5, 66% MM4, 64% MM3, 38% MM2 and 18% for MM1, respectively. Figure 2. Time saved using telehealth. MM 1–7 = modified monash model; MM1 is major city and MM7 is most remote Patient qualitative data Of the 209 free-text responses, concerns raised included technical (23%) such as access to appropriate devices, internet connectivity, TH platforms, audio and visual quality and real-time technical support. Feelings of uncertainty whilst in the virtual waiting room (19%) was due to non-adherence to scheduled appointment times and lack of waiting room management or communication. Patient preferences on the choice of appointment for example video or phone TH or in-person were raised by 17%, citing concerns for the appropriateness of TH when used for first visits, with clinicians not previously known or when physical examination was required. About 15% advocated for preference of video over phone TH. Other concerns were suboptimal communication, administrative follow-up post TH and lack of access to care coordinators compared to in-person consultations, privacy concerns, lack of support persons and referral to allied health, gap payments charged and equity of TH access for vulnerable groups including the Culturally and Linguistically Diverse (CALD) and elderly populations. Clinician experience More than half of the clinicians (59.5%) have had prior experience with video TH pre-pandemic (Table 4). The usage of video TH increased dramatically (79.1%) during the pandemic (Figure 3). Half the clinicians estimated that a quarter or fewer of their consultations were via video. When more than half of their consultations were TH, clinicians were more likely to use phone than video (Figure 4). The video TH platforms used included Healthdirect or COVIU, Zoom, Microsoft Teams and Skype. Figure 3. Modality of telehealth used according to location of clinicians (a) pre and (b) during COVID. Figure 4. Clinic consultations via video or phone TH during COVID-19 pandemic Table 4. Clinician survey respondents N = 158 (%) Role Allied health 21 (13.3%) Haematologist 13 (8.2%) Medical oncologist 34 (21.5%) Others 32 (20.3%) Pharmacists 2 (1.3%) Radiation oncologist 20 (12.7%) Registrar in training 7 (4.4%) Specialist cancer nurses 14 (8.9%) Surgeon 15 (9.5%) Main site of practice Regional cancer services 21 (13.3) Metropolitan cancer services 137 (86.7) Type of TH used Pre-COVID Video only 28 (17.7%) Video and phone 66 (41.8%) Phone only 25 (15.8%) None 39 (24.7%) Use of Video Telehealth pre-COVID by clinicians n = 94 1–10 times 54/94 (57.4%) 11–20 times 9/94 (9.6%) More than 20 times 31/94 (33.0%) Type of TH used during COVID Video only 6 (3.8%) Video and phone 119 (75.3%) Phone only 27 (17.1%) None 6 (3.8%) Video TH platforms used (multiple choice) a Healthdirect / Coviu 115 Zoom 13 Microsoft Teams 6 Skype 2 Other platform (Facetime, WhatsApp, etc.) 14 Training before Video TH a None 94/125 (75.2%) Yes 31/125 (24.8%)  Types of training   - In-house 18   - Online 7   - Instructions from colleague 4   - Webinar 2 Difficulty with Video TH a Yes 35/125 (28.0%) Administrative / Operational Support Provided by institution for Video TH a Yes 115/125 (92.0%) a Video TH users (n = 125) included 6 who used video only and 119 who used both video and phone during COVID. Most clinicians (75.2%) did not attend training sessions but few experienced difficulties with TH platforms. Most training received was in-house. More than half the clinicians were willing to attend educational sessions to improve their experience (Table 5). The opportunity for a support person or carer was offered for most TH consultations. Phone TH users compared to video were concerned that TH was a barrier for the CALD community and those with hearing or visual impairment. TH was not perceived as a barrier for Aboriginal and or Torres Strait Islanders. Video TH users were more likely to involve other health professionals compared to phone (65.6% vs 43.2%, p < 0.001). Clinicians were able to pre-select patients suitable for TH ahead of their clinics. They agreed that TH allowed timely patient review according to clinical needs, created greater efficiencies and enabled greater continuity of care, including shared care. Clinicians reported greater satisfaction with video compared to phone (73.6% vs 58.9%, p = 0.011) and experienced more difficulty in establishing rapport with patients via phone versus video when compared to in-person attendance (75.3% vs 55.2%, p < 0.001). Most clinicians would use video or phone TH post pandemic where clinically appropriate. Table 5. Clinicians’ survey – video versus phone TH Video TH (Video only and video plus phone) n = 125 Phone TH (Phone only and video plus phone) n = 146 p-value Willing to attend education sessions 71 (56.8%) 79 (54.1%) 0.657 Opportunity for support person offered (Yes) 113 (90.4%) 122 (83.6%) 0.098 Concerns TH as a barrier for CALD (Yes) 58 (46.4%) 89 (61.0%) 0.016 Concerns TH as a barrier for ATSI (Yes) 21 (16.8%) 19 (13.0%) 0.381 Concerns for hearing or visual impairment (Yes) 88 (70.4%) 121 (82.9%) 0.015 Involvement of other health professionals during TH (Yes) 82 (65.6%) 63 (43.2%) <0.001 Select outpatients suitable for TH 95 (76.0%) 105 (71.9%) 0.446 TH allowed timely review of patients 109 (87.2%) 131 (89.7%) 0.515 TH created greater efficiencies 80 (64.0%) 104 (71.2%) 0.204 TH enabled greater continuity of care 90 (72.0%) 86 (58.9%) 0.024 Satisfied with TH 92 (73.6%) 86 (58.9%) 0.011 Felt their patients were satisfied with TH 93 (74.4%) 93 (63.7%) 0.058 Would use TH post pandemic 118 (94.4%) 126 (86.3%) 0.026 Difficult to establish rapport 69 (55.2%) 110 (75.3%) <0.001 CALD: Culturally and Linguistically Diverse; ATSI: Aboriginal and Torres Straits Islander Clinician qualitative data Majority (62%) reported access to technology and infrastructure either at the health service or patients’ homes as the main challenge. Some provided their own equipment, had limited real-time information technology (IT) support and concerns for their patients’ IT literacy. Other concerns included suboptimal communication (body language being less well appreciated, lack of engagement and clarity of visual and audio during TH consultation), infrequent use of interpreters, inability to perform physical examination, lack of administrative support and in-person care coordination, variable TH training, user acceptance of TH and consumers’ pre-occupation with other activities during TH appointments. The main enablers of adopting TH included adequate local IT, infrastructure and administrative support such as TH navigators, general perception that TH was necessary during the pandemic, prioritising patient preferences, education and training for clinician users, local health service leadership and TH user champions, staff engagement and ease of use of the existing platforms. Some felt that TH acceptability could be enhanced by enabling wider availability, regardless of the geographical location or restrictions of TH eligibility for government reimbursement, with a preference for video over phone TH. TH was valuable in the provision of palliative care, access to clinical trials and expert care for rare cancers including inter-state referrals to minimise travelling, rehabilitation programs and shared care with local clinicians within existing or new programs between regional general practitioners and specialists linking in with metropolitan-based specialists, in multi-disciplinary models of care. The administrative burden after TH appointments such as ensuring prescriptions and investigation requests reach the patient at home, need to be optimised and ideally within acceptable regulatory and governance electronic strategies. Discussion To the best of our knowledge, this is the largest TH survey across Australia for both cancer patients and clinicians conducted during the pandemic. While it is a cross-sectional survey early in the implementation of TH in Victoria, the survey results provided insights on the uptake and acceptability of both TH modalities. TH has a high level of utility, acceptability and satisfaction. In these early stages, phone was used more readily than video by providers largely due to pragmatic reasons and the rapidity in which care needed to be changed from in-person to TH due to safety concerns. Where access to technology and devices was available, video was the preferred platform by both consumers and clinicians due to enhanced communication and rapport with the patient, in addition to observing non-verbal cues. Voice, tone and body language are some key elements of personal communication.19 This was important especially where support persons were in attendance. Our survey results showed enhanced communication of video compared to phone TH which could be due to a superior interface when utilising an interpreter, ability to share digital images and reports with patients and utilisation of tools, such as whiteboard to enhance user experience. Though video platforms may provide better security through digital encryption and patient identification, we found that concerns for privacy and confidentiality were similar between video and phone modalities. The higher prevalence of phone TH usage highlighted its ease of use in terms of time efficiency and for those unable to use video TH or when the technology was not available or failed.17 Notably, our survey results from phone TH users were generally favourable albeit less across most domains compared to video TH. The strength of our survey lies in the representation from both regional and metropolitan centres, consumer advocacy groups and across multiple tumour streams. Overall patients and clinicians concurred that utilising TH was efficient and allowed continuity of high-quality healthcare during a time where social restrictions imposed logistic challenges. The advantages of TH regardless of modality in workflow, frequency of clinical review, cost savings and mitigation of social inconveniences such as travel, time off work, time away from family are consistent with previously reported literature. The additional amelioration in safety concerns and anxiety associated with in-person visits during lockdowns cannot be over-emphasised. Our survey indicates that both consumers and clinicians recommended ongoing context-appropriate use of TH in the post pandemic environment. Whist majority of the respondents were associated with one metropolitan health service, the higher proportion of video compared to phone TH at this health service may reflect enhanced digital infrastructure and Information Management Communication Technology support, as well as prior clinician experience using TH. This supports the ongoing investment in this space to enable the enhanced TH experience and utilisation. The low patient and clinician survey response rates, with predominance of metropolitan respondents and those with breast cancer diagnosis may have introduced biases. Regardless, we were able to draw useful conclusions from this survey and the qualitative data from both consumers and clinicians certainly added value for further review, refinement re-/co-design of TH, digital and virtual care strategies. Many concepts remain relevant for all healthcare providers across different specialties and consumers. While there may be limitations to TH – such as when used in the absence of pre-existing rapport with clinicians, when sharing emotionally difficult news or when physical examination is required, TH remains a highly useful adjunct to routine face-to-face consultations where appropriate20. With support and training on the use of video TH, the patient and clinician experience will improve over time. Apart from clinical indications, it is crucial to consider patient autonomy and joint-decision making with regards to the modality of clinical encounters. The COVID-19 pandemic has accelerated the uptake of TH significantly12,21,22 but it is only possible to keep up this momentum through ongoing funding, training and infrastructure support by policy-makers23,24,25. With the changes in government reimbursement for phone TH in Australia from 1 July 2022,26 it is probable that the use of phone TH which is the predominant modality in both general practice and specialist settings may be reduced significantly with a resultant increase in face-to-face consultations where a switch to video TH may not be feasible due to challenges previously identified.11,17 This could reduce the overall prevalence of TH usage especially in certain vulnerable subgroups11 such as the elderly and CALD populations. An appropriate hybrid model of cancer care with in-person and virtual care used where clinically applicable, taking into account patients’ preferences, has emerged during the pandemic.27 Moreover, TH has enabled access to expert and high-quality subspecialty care, particularly for regional and rural patients with increased ease, compared to conventional in-person attendance.20 This cannot be under-estimated in terms of equity of access to specialist cancer care including clinical trials beyond conventional geographical boundaries.3,4 While we do not yet have a standard analytical matrix to measure the quality of a face-to-face clinical consultation, it would be worthwhile to develop tools to assess the quality of TH. Acknowledgements We would like to acknowledge all the participants of the surveys, the lead clinicians and personnel from each participating site, the support from the Victorian Department of Health, the Victorian COVID-19 Cancer Network Taskforce and all members of the VCCN Telehealth Expert Working Group especially the VCCN-TH Survey Steering Committee (KB, LG, IS, CB, GJ, AG, HC, ZWW). Appendix (A) Telehealth survey questionnaire for patients 1. Please indicate who will be completing this survey a. Patient b. Carer or family member 2. Have you had a recent telehealth (Video / Phone) consultation with your cancer specialist in the last 3 months? a. Yes – Video only, go to Q4 b. Yes – Phone only, go to Q4 c. Yes – both video and phone, go to Q4 d. No, go to Q3 3. If you have not had a telehealth consultation, could you tell us the reason? a. My doctor's request b. Due to concerns with technology involving telehealth c. Due to need for translators d. Others, please specify For patients who have not had a successful telehealth consultations, go directly to Question 23 4. How many times have you had telehealth (video / phone) consultations in the last 3 months? a. First time b. 2–3 times c. > 3 times 5. Did you have difficulty accessing your telehealth (video or phone) consultation? a. Yes Please specify: b. No 6. Did you have any difficulty seeing and / or hearing during the telehealth (video / phone) consultation? a. Yes Please specify: b. No 7. I have some concerns with privacy and confidentiality during the telehealth (video / phone) consultation. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 8. I feel the communication about my cancer condition with my specialist during the telehealth (video / phone) consultation is as good as face to face consultation. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 9. Do you think a telehealth (video / phone) consultation is acceptable for cancer patients. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 10. When telehealth (video / phone) consultations are clinically appropriate, I would still prefer face to face consultations. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 11. Telehealth (video / phone) consultation saved time for me (and my family/carer). a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 12. How much time have you (or your family/carer) saved by attending a telehealth (video / phone) consultation compared to a face to face consultation? a. None b. < 2 hours c. 2–< 4 hours d. 4–< 6 hours (half a day) e. 6–8 hours (whole day) 13. Was your telehealth (video / phone) consultation for participation on a clinical trial? a. Yes b. No 14. Do you feel you were supported during your telehealth (video / phone) consultations? a. Yes b. No c. Prefer not to say 15. As part of your telehealth (video / phone) consultation were you offered a referral to supportive services, e.g. psychologist, oncology nurse, etc? a. Yes b. No c. Prefer not to say 16. Was your GP involved in any of your telehealth consultations? a. Yes b. No c. Prefer not to say 17. Did you utilise the service of an interpreter during any of the telehealth consultations? a. Yes b. No c. Prefer not to say 18. Overall, I am satisfied with the telehealth (video / phone) consultation. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 19. I would use telehealth (video / phone) consultation again. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 20. I would recommend telehealth (video / phone) consultation to other cancer patients. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 21. I would like to have the option of using telehealth (video / phone) even after the pandemic is over for my cancer care whenever it is considered appropriate by my cancer specialist. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 22. Do you have any suggestions for improving telehealth consultations for cancer patients? a. Yes Please specify b. No 23. Could you tell us a bit about yourself? a. Age i. < 35 ii. 35–< 50 iii. 50–< 65 iv. 65–< 75 v. ≥ 75 b. Gender i. Male ii. Female iii. Prefer not to say c. Is English your first language? i. Yes ii. No iii. Prefer not to say d. Highest educational level i. University / post-graduate ii. TAFE iii. High school / Secondary iv. Primary v. Prefer not to say e. Your home post code: _ _ _ _ f. Distance between your home and the health service where you had a telehealth consultation i. < 15 km ii. 15–< 30 km iii. 30–< 50 km iv. 50–< 100 km v. ≥ 100 km g. The type of cancer for which you are receiving care i. Breast ii. Lung iii. Bowel iv. Prostate v. Blood cancers vi. Others, please specify h. Stage of your cancer i. Early ii. Advanced iii. Unsure iv. Prefer not to say i. Type of clinic visit i. First visit ii. Review iii. Others, please specify j. Specialists involved in your recent telehealth consultation i. Medical oncologist ii. Haematologist iii. Radiation oncologist iv. Surgeon v. Nurse specialist vi. Others, please specify k. Would you be happy to be contacted for further interviews or discussions? i. Yes, please leave us your best contact details ii. No l. Any other comments Thank you very much for your time in participating in this survey. Your responses will be invaluable in addressing further improvement efforts in the use of telehealth consultations. (B) Telehealth survey questionnaire for clinicians 1. Can you tell us about your role? a. Medical oncologist b. Haematologist c. Surgeon d. Radiation oncologist e. Registrar in training f. Specialist cancer nurses g. Allied health h. Others, please specify 2. Have you had a recent telehealth (Video / Phone) consultation with your cancer patient? a. Yes – Video only b. Yes – Phone only c. Yes – both video and phone d. No 3. How many times have you conducted telehealth (video / phone) consultations? a. First time b. 1–10 times c. 11–20 times d. > 20 times 4. In the video consultations you have conducted, which platforms did you predominantly use? a. Healthdirect / Coviu b. Microsoft teams c. Zoom d. Skype e. Others, please specify f. Not applicable 5. Have you done telehealth consultation prior to the COVID-19 pandemic? a. Yes b. No 6. Did you have difficulty accessing your telehealth (video or phone) consultation? a. Yes Please specify: b. No 7. I have some difficulty seeing and / or hearing during the telehealth (video / phone) consultation with my cancer patients. a. Yes Please specify: b. No 8. Did you attend any training session prior to use of telehealth (video / phone)? a. Yes Please specify: b. No 9. Did you offer your patients the opportunity to have a support person or carer participate in the telehealth consultation? a. Yes b. No 10. Do you see telehealth as a barrier for patients from the Culturally and Linguistically Diverse (CALD) community? a. Yes Please specify b. No 11. Have you ever involved other health professionals in your telehealth consultation, e.g. general practitioner, allied health, oncology nurse? a. Yes Please specify b. No 12. Did your institution provide administrative and operational requirements for telehealth (scheduling and booking, instructions/assistance for use of technology) for the purposes of the clinical session? a. Yes Please specify: b. No Please specify: 13. As a cancer clinician, telehealth created greater efficiencies in terms of being able to see patients in a timely fashion and the frequency required, according to clinical needs a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 14. As a cancer clinician, telehealth created greater efficiencies in the running of my clinics. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 15. Telehealth will enable greater continuity of care for my cancer patients, such as shared care with local healthcare providers a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 16. My cancer patients are overall satisfied with using telehealth (video / phone) consultations. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 17. As a cancer clinician, I am generally satisfied with using telehealth (video / phone) consultations for my patients. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 18. I would use telehealth (video / phone) consultations for my cancer patients again. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 19. I am able to select patients who are suitable for telehealth (video / phone) consultations ahead of my clinics. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 20. It is more difficult to establish a rapport with cancer patients with telehealth (video / phone) consultations. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 21. If time permits, I would be keen to attend educational sessions to improve my ability to conduct telehealth (video / phone) consultations with my cancer patients, e.g. communication skills, how to conduct telehealth consultations. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 22. I would like to continue to use telehealth (video / phone) consultations post COVID-19 pandemic for cancer patients where clinically appropriate. a. Strongly agree b. Agree c. Neutral d. Disagree e. Strongly disagree 23. Could you tell us the postcode of your health service? _ _ _ _ 24. Could you tell us some of the challenges of adopting telehealth at your institution? 25. Could you tell me some of the enablers of adopting telehealth at your institution? 26. What aspect needs improvement to increase the value and acceptability of telehealth at your health service? 27. Would you be happy to be contacted for further interviews or discussions? a. Yes, please leave us your best contact details b. No 28. Any other comments: Thank you very much for your time in participating in this survey. Your responses will be invaluable in addressing further improvement efforts in the use of telehealth consultations. The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article. Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was partly funded by the Victorian Department of Health through the Victorian COVID-19 Cancer Network in 2020. ORCID iD: Zee Wan Wong https://orcid.org/0000-0002-3055-2119 ==== Refs References 1 Sabesan S Senko C Schmidt A , et al. Enhancing chemotherapy capabilities in rural hospitals: Implementation of a telechemotherapy model (QReCS) in North Queensland, Australia. J Oncol Pract 2018; 14 : e429–e437. 2018/07/12.29996068 2 Australasian Tele-Trial model : a national guide for implementation. Sydney: Clinical Oncology Society of Australia, 2016. (https://www.cosa.org.au/media/332325/cosa-teletrial-model-final-19sep16.pdf. opens in new tab) 3 Sabesan S Malica M Gebbie C , et al. Implementation of the Australasian Teletrial model: Translating idea into action using implementation science frameworks. J Telemed Telecare 2021 July 7: 1357633X211017805. doi:10.1177/1357633X211017805. Epub ahead of print. PMID: 34233548. 4 Collins IM Burbury K Underhill CR . Teletrials: Implementation of a new paradigm for clinical trials. Med J Aust 2020; 213 : 6. https://onlinelibrary.wiley.com/doi/10.5694/mja2.50741 32548879 5 Thomas J Barraket J Wilson C , et al. Measuring Australia’s Digital Divide: The Australian Digital Inclusion Index 2019. Melbourne: RMIT University and Swinburne University of Technology for Telstra, 2019. 6 Hollander JE Carr BG . Virtually perfect? Telemedicine for Covid-19. N Engl J Med. 2020; 382 : 1679–1681. Epub 2020 Mar 11. PMID: 32160451.32160451 7 Zomerdijk N Jongenelis M I Turner J , et al. Telehealth access among hematology patients during the COVID-19 pandemic in Australia: a cross-sectional survey. Leuk Lymphoma 2022; Jun;63(6):1488–1491. doi: 10.1080/10428194.2021.2023743. Epub ahead of print. PMID: 34989290. 8 Parsonson A O Grimison P Boyer M , et al. Patient satisfaction with telehealth consultations in medical oncology clinics: A cross-sectional study at a metropolitan centre during the COVID-19 pandemic. J Telemed Telecare 2021: 1357633X211045586. doi: 10.1177/1357633X211045586. Epub ahead of print. PMID: 34657513. 9 Tuckson RV Edmunds M Hodgkins ML . Telehealth. N Engl J Med. 2017; 377 : 1585–1592. PMID: 29045204.29045204 10 Snoswell CL Taylor ML Comans TA , et al. Determining if telehealth can reduce health system costs: Scoping review. J Med Internet Res 2020; 22 : e17298. PMID: 33074157; PMCID: PMC7605980.33074157 11 Murphy A Kirby A Lawlor A , et al. Mitigating the impact of the COVID-19 pandemic on adult cancer patients through telehealth adoption: A systematic review. Sensors (Basel) 2022; 22 : 3598. PMID: 35591287; PMCID: PMC9105995.35591287 12 Hall Dykgraaf S Desborough J de Toca L , et al. A decade’s worth of work in a matter of days": The journey to telehealth for the whole population in Australia. Int J Med Inform 2021; 151 : 104483. Epub 2021 May 7. PMID: 33984625; PMCID: PMC8103781.33984625 13 Jennifer Blackwood Kateri Rybicki . (2021) Outcomes of Telehealth-Delivered Physical Activity Programs in Adult Cancer Survivors: A Systematic Review. Rehabil Oncol. July 2021; 39(3) :128–136 (Published ahead of print) 14 Larson JL Rosen AB Wilson FA . The effect of TH interventions on quality of life of cancer survivors: A systematic review and meta-analysis. Health Informatics J 2020; 26 : 1060–1078.31566455 15 Cox A Lucas G Marcu A , et al. Cancer Survivors’ experience with telehealth: A systematic review and thematic synthesis. J Med Internet Res 2017; 19 : 11. PMID: 28069561; PMCID: PMC5259589. 16 https://www.viccompcancerctr.org/victorian-covid-19-cancer-network/ 17 Wong ZW Cross H . Telehealth in cancer care during the COVID-19 pandemic. Med J Aust 2020; 213 : 237. https://onlinelibrary.wiley.com/doi/full/10.5694/mja2.50740 18 https://www.health.gov.au/health-topics/health-workforce/health-workforce-classifications/modified-monash-model 19 Roter DL Frankel RM Hall JA , et al. The Expression of Emotion Through Non-verbal Behavior in Medical Visits. J Gen Intern Med. 2006 Jan;21 Suppl 1(Suppl 1):S28–34. 10.1111/j.1525-1497.2006.00306.x 20 Snoswell CL Chelberg G De Guzman KR , et al. The clinical effectiveness of telehealth: A systematic review of meta-analyses from 2010 to 2019. J Telemed Telecare 2021 Jun 29: 1357633X211022907. doi: 10.1177/1357633X211022907 21 Smith AC Thomas E Snoswell CL , et al. Telehealth for global emergencies: Implications for coronavirus disease 2019 (COVID-19). J Telemed Telecare 2020; 26 : 309–313. 2020/03/21.32196391 22 White J Byles J Walley T . The qualitative experience of telehealth access and clinical encounters in Australian healthcare during COVID-19: Implications for policy. Health Res Policy Syst 2022; 20 : 9. PMID: 35033107; PMCID: PMC8760598.35033107 23 Thomas EE Haydon HM Mehrotra A , et al. Building on the momentum: Sustaining telehealth beyond COVID-19. J Telemed Telecare 2022 May;28(4):301–308: 1357633X20960638. doi: 10.1177/1357633X20960638. Epub ahead of print. PMID: 32985380. 24 Mehrotra A Bhatia RS Snoswell CL . Paying for telemedicine after the pandemic. JAMA 2021; 325 : 431–432.33528545 25 Lopez AM Lam K Thota R . Barriers and facilitators to telemedicine: Can you hear me now? Am Soc Clin Oncol Educ Book 2021; 41 : 25–36. PMID: 34010056.34010056 26 http://www.mbsonline.gov.au/internet/mbsonline/publishing.nsf/Content/Factsheet-telehealth-1July22 27 Burbury K Wong Z Yip D , et al. Telehealth in cancer care: During and beyond the COVID-19 pandemic. Intern Med J 2021; 51 : 125–133. https://onlinelibrary.wiley.com/doi/10.1111/imj.15039 33572014
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==== Front J Emerg Med J Emerg Med The Journal of Emergency Medicine 0736-4679 0736-4679 Elsevier Inc. S0736-4679(22)00564-9 10.1016/j.jemermed.2022.09.034 Letters to the Editor Superior Vena Cava Syndrome and COVID-19 Vaccine Reaction Mungmunpuntipantip Rujittika *1 Wiwanitki Viroj † ⁎ Private academic consultant, Bangkok, Thailand † Dr. D.Y. Patil Medical College, Pune, India 1 Corresponding author. 12 12 2022 12 2022 12 12 2022 63 6 811811 10 8 2022 4 9 2022 © 2022 Elsevier Inc. All rights reserved. 2022 Elsevier Inc. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. ==== Body pmcTo the Editor: We would like to share ideas on the article by McNeilly and Wilkerson entitled “Not feeling swell: superior vena cava (SVC) syndrome falsely attributed to COVID-19 vaccine reaction” (1). According to McNeilly and Wilkerson, this instance emphasizes the value of conducting a comprehensive physical examination and keeping a wide-ranging differential diagnosis. The existence of Pemberton's sign in this case led to further investigation and suspicion of SVC syndrome (1). We are all concerned that the COVID-19 vaccine could be dangerous despite being beneficial. It is unable to pinpoint the precise source of the clinical issue in this case due to the dearth of prevaccination information on the health and immunological status of vaccine recipients. Information that is contradictory may cause people to revolt against immunizations and lose faith in them. A patient comorbidity may be the cause of the issue (2). Despite the patient's clear clinical state, there was a risk that there were still undiagnosed comorbid conditions. It is possible to classify coinfections that may develop in vaccine recipients after receiving the shot as a vaccine effect. To reach a judgement regarding the vaccine's effect on ocular problems, there must be sufficient data. To reach a judgement regarding the vaccine's effect on ocular problems, there must be sufficient data. A group of patients with known prevaccination immunological and health conditions who were afterward assessed to determine how the vaccine impacted clinical status would provide more conclusive evidence on this topic. In conclusion, McNeilly and Wilkerson stated that before diagnosing an unfavorable effect caused by vaccine, it is vital to rule out any other potential causes of medical problems. ==== Refs References 1 McNeilly BP Wilkerson RG. Not feeling swell: superior vena cava (SVC) syndrome falsely attributed to COVID-19 vaccine reaction J Emerg Med 63 2022 e31 e33 35945118 2 Kebayoon A Wiwanitkit V. Dengue after COVID-19 vaccination: possible and might be missed Clin Appl Thromb Hemost 27 2021 10760296211047229
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==== Front J Emerg Med J Emerg Med The Journal of Emergency Medicine 0736-4679 0736-4679 Elsevier S0736-4679(22)00727-2 10.1016/S0736-4679(22)00727-2 Article Issue Highlights 12 12 2022 12 2022 12 12 2022 63 6 iiiiii 2019 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. ==== Body pmc
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==== Front J Emerg Med J Emerg Med The Journal of Emergency Medicine 0736-4679 0736-4679 Elsevier S0736-4679(22)00728-4 10.1016/S0736-4679(22)00728-4 Article Contents 12 12 2022 12 2022 12 12 2022 63 6 ivv 2019 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. ==== Body pmc
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==== Front J Emerg Med J Emerg Med The Journal of Emergency Medicine 0736-4679 0736-4679 Elsevier S0736-4679(22)00703-X 10.1016/S0736-4679(22)00703-X Article (LEFT) Partial Contents; (RIGHT) Elsevier E-alert 1/2 pg vertical BW filler 12 12 2022 11 2022 12 12 2022 63 5 vivi 2019 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. ==== Body pmc
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==== Front J Emerg Med J Emerg Med The Journal of Emergency Medicine 0736-4679 0736-4679 Elsevier Inc. S0736-4679(22)00557-1 10.1016/j.jemermed.2022.04.037 Letters to the Editor Problems in Conducting and Reporting Logistic Regression Analysis Doğan Nurettin Özgür Department of Emergency Medicine, Faculty of Medicine, Kocaeli University, Kocaeli, Turkey 12 12 2022 11 2022 12 12 2022 63 5 709710 23 2 2022 23 4 2022 © 2022 Elsevier Inc. All rights reserved. 2022 Elsevier Inc. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. ==== Body pmcTo the Editor: I read the article by Thoppil et al. (1) entitled “SARS-CoV-2 positivity in ambulatory symptomatic patients is not associated with increased venous or arterial thrombotic events in the subsequent 30 days,” published in the June 2022 issue of the Journal (1). This article is a retrospective cohort study aiming to evaluate the relationship between SARS-CoV-2 test positivity and acute vascular thrombosis using the RECOVER registry. Although the study was based on a fairly large sample, the multivariable modeling used for venous and arterial thromboembolic disease does not meet the essential requirements of logistic regression analysis. In a study using multivariable logistic regression analysis, all possible variables that may affect the predictor variable should be included in the final analysis. In addition, the number of events per variable should be as large as possible for the validity of the model (2). In this study, only 7 variables were included in the model (presence of cancer, age, gender, hospital length of stay, intubation, intensive care unit stay, and SARS-CoV-2 positivity). It is not possible to claim that only these variables affect patient outcomes (the occurrence of arterial or venous thromboembolism). Both conditions occur with different pathophysiological processes, and the risk factors for each condition also differ. In a regression model, it should be stated whether the variables included in the multivariable model in logistic regression analysis were taken from previous studies or from univariate analysis results. In Thoppil et al. (1), it is not clear how these variables were included in the final analysis (1). In addition, the event rates in the groups are at the level of 0.3% to 0.4%, which can seriously affect the reliability of the model. One of the analyses that should be done in logistic regression analysis is multicollinearity. This analysis evaluates the effect of variables that correlate with each other in the multivariable model (2,3). In the absence of this analysis, the final result may appear statistically insignificant if there is a strong relationship between the 2 independent variables. In Thoppil et al. (1), the interaction of possibly correlated variables such as intubation and intensive care unit admission was not evaluated (1). Finally, in both models, goodness of fit should have been presented by a test such as receiver operating characteristic analysis or the Hosmer-Lemeshow test. Since these test results are not presented in the article, we have no chance to evaluate the goodness of fit. The problems mentioned here are not only the limitations of the article but are also the main problems that directly affect the study results. Basal characteristics of patients from a large registry cannot be evaluated accurately, possible confounding factors cannot be eliminated, and information about the severity of the predictor variable cannot be obtained. Statistical analysis was made in the article without fulfilling the basic requirements of logistic regression analysis. Instead, the results focused on odds ratios and p values. In addition, Tan et al. have reached opposite results in the meta-analysis they recently published (4). For this reason, I think that the conclusion put forward by Thoppil et al. (1) should be carefully evaluated (1). ==== Refs References 1 Thoppil JJ Courtney DM McDonald S SARS-CoV-2 positivity in ambulatory symptomatic patients is not associated with increased venous or arterial thrombotic events in the subsequent 30 days J Emerg Med 62 2022 716 724 35177286 2 Bagley SC White H Golomb BA. Logistic regression in the medical literature: standards for use and reporting, with particular attention to one medical domain J Clin Epidemiol 54 2001 979 985 11576808 3 Tanboğa IH Kurt M Işik T Assessment of multivariate logistic regression analysis in articles published in Turkish cardiology journals Turk Kardiyol Dern Ars 40 2012 129 134 22710601 4 Tan BK Mainbourg S Friggeri A Arterial and venous thromboembolism in COVID-19: a study-level meta-analysis Thorax 76 2021 970 979 33622981
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==== Front Comput Struct Biotechnol J Comput Struct Biotechnol J Computational and Structural Biotechnology Journal 2001-0370 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. S2001-0370(22)00563-3 10.1016/j.csbj.2022.12.007 Article SARS-CoV-2 virus classification based on stacked sparse autoencoder Coutinho Maria G.F. a Câmara Gabriel B.M. a Barbosa Raquel de M. b Fernandes Marcelo A.C. ac⁎ a Laboratory of Machine Learning and Intelligent Instrumentation, IMD/nPITI, Federal University of Rio Grande do Norte, Natal, Brazil b Department of Pharmacy and Pharmaceutical Technology, University of Granada, 18071 Granada, Spain c Department of Computer and Automation Engineering, Federal University of Rio Grande do Norte, Natal, Brazil ⁎ Corresponding author at: Department of Computer and Automation Engineering, Federal University of Rio Grande do Norte, Natal, Brazil. 9 12 2022 2023 9 12 2022 21 284298 21 6 2022 4 12 2022 5 12 2022 © 2022 The Author(s) 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Graphical abstract Since December 2019, the world has been intensely affected by the COVID-19 pandemic, caused by the SARS-CoV-2. In the case of a novel virus identification, the early elucidation of taxonomic classification and origin of the virus genomic sequence is essential for strategic planning, containment, and treatments. Deep learning techniques have been successfully used in many viral classification problems associated with viral infection diagnosis, metagenomics, phylogenetics, and analysis. Considering that motivation, the authors proposed an efficient viral genome classifier for the SARS-CoV-2 using the deep neural network based on the stacked sparse autoencoder (SSAE). For the best performance of the model, we explored the utilization of image representations of the complete genome sequences as the SSAE input to provide a classification of the SARS-CoV-2. For that, a dataset based on k-mers image representation was applied. We performed four experiments to provide different levels of taxonomic classification of the SARS-CoV-2. The SSAE technique provided great performance results in all experiments, achieving classification accuracy between 92% and 100% for the validation set and between 98.9% and 100% when the SARS-CoV-2 samples were applied for the test set. In this work, samples of the SARS-CoV-2 were not used during the training process, only during subsequent tests, in which the model was able to infer the correct classification of the samples in the vast majority of cases. This indicates that our model can be adapted to classify other emerging viruses. Finally, the results indicated the applicability of this deep learning technique in genome classification problems. Keywords COVID-19 Deep learning SARS-CoV-2 Sparse autoencoder Viral classification ==== Body pmc1 Introduction Since the emergence of the SARS-CoV-2 virus at the end of 2019, many works are been developed aiming to provide more comprehension about this novel virus. In March 2020, the World Health Organization (WHO) raised the level of contamination to the COVID-19 pandemic, due to its geographical spread across several countries. On July 9, 2021, the disease had registered more than 185 million confirmed cases, and more than 4 million confirmed deaths. In the case of a novel virus identification, the early elucidation of taxonomic classification and origin of the virus genomic sequence is essential for strategic planning, containment, and treatments of the disease [1], [2], [3]. One of the research field in the bioinformatics area is the analysis of genomic sequences. In the last years, many strategies based on alignment-free methods have been explored as an alternative for the alignment-based methods, considering the limitations of the second approach. Alignment-based programs assume that homologous sequences comprise a series of linearly arranged and more or less conserved sequence stretches, which is not always the case in the real world [4]. Among the alignment-free methodologies, there are some models based on deep learning (DL) techniques, that can provide significant performance in applications of genome analysis [5], [6], [7]. Deep neural networks (DNN) can improve prediction accuracy by discovering relevant features of high complexity [7]. Fig. 1 presents the genome analysis stages and how deep learning integrates this process. The genome analysis stages include the primary analysis, the secondary analysis, and the tertiary analysis. The primary and secondary analysis compose the genome sequencing. The primary analysis receives the biological sample and generates genomic data information, called “reads”, after the processing by the sequencer machine. Then, the secondary analysis processes the reads and produces the complete genome sequence. Lastly, the tertiary analysis provides the genome interpretation, which can be performed for many algorithms and techniques [8], [9], [10], as machine learning algorithms [11] and deep learning techniques [7]. The deep learning techniques have been successful used for the tertiary analysis in many viral classification problems associated with the diagnosis of viral infections, metagenomics, pharmacogenomics, and others [12], [13], [14], [15], [16].Fig. 1 Genome analysis stages with deep learning. Fig. 2 shows the steps of the tertiary analysis using DL, that are the mapping and processing stages. The mapping stage receives the DNA sequence information, that can be the reads, contigs, or the whole genome sequence, and maps this data into a feature space. Various mapping strategies have been present in the works from state of the art, such as one-hot encoding [17], [18], [19], [14], number representation [12], [13], digital signal processing [20], and other strategies, including multiple mapping strategies applied sequentially [21], [22]. The processing stage consists of the utilization of a DNN to perform classification, prediction, and other assumptions about the genome information.Fig. 2 Stages of viral genome analysis using deep learning. The mapping stage is crucial for the performance of the processing stage. The genome sequence length varies by the type of virus. Since the DNN only receive a fixed-size input, some researchers have not been using the whole or long sequence length. Nevertheless, longer sequences contain more information and thus are more convenient to make predictions [18]. The main contributions of this work are:• To provide an efficient viral genome classifier for the SARS-CoV-2 virus, based on the stacked sparse autoencoder (SSAE) technique. • To explore the utilization of a dataset based on k-mers image representation of the complete genome sequences as the SSAE input. • To provide different levels of taxonomic classification. • To deliver an approach that can be adapted to classify other emerging viruses. The present paper is organized as follows: This first section presents a general introduction, exposing the motivations and contributions of the work. Section 2 discusses some related works from state of the art. Section 3 presents the materials and methods used to perform the experiments. Section 4 will present the results of each experiment, a discussion of the results, and a comparison with a work from the state of the art. Finally, Section 5 will present the final considerations regarding the obtained results, the implications of the work and our plans for the future. 2 Related works Many works from the state of the art are using deep learning to solve biomedical problems [23], [24], [25], [26], [27]. Recently works in literature have been applying deep learning as tertiary analysis such as viral prediction, viral host prediction, and viral segments prediction [17], [12], [18], [20], [13], [28], [19], [29], [14], [30], [31], [32], [15], [16], [33], [34], [35], [36]. The work from [37] uses a deep learning approach combining a CNN with a Bi-directional LSTM (BLSTM) to classify the SARS-CoV-2 among Coronavirus and detect sequences with regulatory or transcription motifs. For the DNN input, they used the one-hot vectors to represent DNA sequences as 2D matrices. Table 1, Table 2 present some works from the state of the art that applied DNNs in order to analyse viral genome sequences. Table 1 details the focus of each work as the biology name, the group, the aim, indicates if the proposal was or was not applied for the COVID-19 and present the DNN used. The DNNs applied in those references are divide into 5 groups (CNN + FC, LSTM + FC, BLSTM + FC, BLSTM + CNN + FC, CNN + BLSTM + FC), as we show in the last column of Table 1. Table 2 shows the details about the input and the output of the DNN, besides the biology fields and the bioinformatics area.Table 1 State of the art references – Part 1. Biology name Group Aim Ref. COVID-19 DNN Genome prediction or sequence classification Genome classification (taxonomic classification) Viral classification Viral Subtyping [12] – CNN Primer design [13] Yes CNN Identified virus sequence [14] Yes LSTM CNN + FC Taxonomic classification [15] – BLSTM [16] – CNN Genome prediction Viral prediction Identified virus sequence [18] – CNN [17] – CNN Identified phage, chromossomes, plasmid [29] – CNN Host prediction Host classification Viral host classification Predicting viruses among several hosts [19] – BLSTM + CNN CNN Host prediction Viral host prediction [28] Yes CNN Genome segments prediction Genome segments classification Viral segments classification Prediction specific regions in the genome [20] – CNN + FC [30] – CNN + BLSTM [31] – CNN + BLSTM [32] – CNN + BLSTM Table 2 State of the art references – Part 2. Input Output Ref. Biology fields Bioinformatics The DNA or cDNA (RNA virus) of the virus. The whole or part of the genome is used. Number of the classes [12] Metagenomics Diagnosis of viral infections Pharmacogenomics Free alignments techniques [13] [14] [15] [16] Score [18] Metagenomics Phylogenetic analysis Binary output [17] Score [29] Number of the classes [19] Metagenomics Phylogenetic analysis Score [28] Metagenomics Number of the classes [20] Transcriptome Analysis [30] [31] Gene expression analysis [32] In the work presented in [12] was proposed a viral genome deep classifier (VGDC), the first viral genome subtyping based on deep learning techniques found in the literature. Their approach uses a Convolutional Neural Network (CNN) with 25 layers to classify several groups of viruses in subtypes. For the tests, were used five different datasets, each one containing genomes sequences of a specific type of virus. The whole virus genome sequence was used as the input to the network, where the corresponding ASCII code represented each nucleotide. The results indicated that the VGDC was able to achieve better results in comparison with previous works from the state of the art. In [13] was proposed an approach to assist the tests in the detection of SARS-CoV-2, based on the use of DL techniques. For this, a CNN architecture with 4 layers was used to extract characteristics of the virus genomes, as well as to classify SARS-CoV-2 among Coronavirus type viruses. As presented in [12], the CNN received as input the whole virus genome sequences. The nucleotides were mapped in numerical values (C  = 0.25, T  = 0.50, G  = 0.75, A  = 1.0). Missing entries received a value of 0.0. The experiments showed that the CNN was able to correctly identify the sequences even in cases where the noise was added to the genome, reaching accuracies between 0.9674 (with noise) and 0.9875 (without noise). Through the results, the authors also identified a sequence as exclusive for the SARS-CoV-2 virus. They proposed the use of this sequence as a primer for PCR tests. In [14], was proposed an approach to provide viral classification using the contigs (fragments of the genome sequence) and two different reverse-complement (RC) neural networks architectures: a RC-CNN and a RC-LSTM. These models were also applied to the SARS-CoV-2 virus. In works presented in [15], [16], a taxonomic classification for metagenomics applications is proposed. Both works used segments of genome (reads) with DL input (see Fig. 1), and the output is the number of the classes. In [15], it was proposed two DL models, one to classify species, and another to classify genus. In [16], a hierarchical taxonomic classification for viral metagenomic data via DL, called CHEER, was proposed. Similar to the work proposed in [15], the CHEER framework classifies the order, family, and genus. Proposals presented in [17], [18], [29] used the contigs with DL input for viral prediction, and classification. In [17], [18] a DL virus identification framework was proposed and both cases try to recognize if the input is a virus or not. In work from [17], called ViraMiner, was proposed and approach to detect the presence of viruses on raw metagenomic contigs from different human samples. They used a CNN architecture with two different convolutional branches (pattern and frequency branch) in order to extract relevant features. The outputs of these branches are concatenated and inserted into the fully connected (FC) layer. The ViraMiner output produces a single value that indicates the likelihood of the sequence belonging to the virus class. In the proposal presented in [18], called DeepVirFinder, the output is a score between 0 and 1 for a binary classification between virus and prokaryote. They fragmented the genomes into non-overlapping sequences of different sizes (150,300,500,1000, and 3000 bp). The sequences were mapped for the network input using the one-hot encoding method. Since they increase the length of the input, i.e. the sequence fragment, they achieve better performance results, which was measured by the area under the receiver operating characteristic curve (AUROC). The maximum AUROC achieved was 0.98 for the 3000 bp fragment. The work presented in [29] identifies metagenomic fragments as phages, chromosomes or plasmids using the CNN technique. The experiments were performed using artificial contigs and real metagenomic data. The network output, provided by a softmax layer, consists of 3 scores that indicate the probability that each fragment belongs to a specific class. In the works from [28], [19] are present DL architectures for host prediction and classification. [28] used a CNN to provide host and infectivity prediction of SARS-CoV-2 virus. In [19] was proposed an approach to predict viral host from three different virus species (influenza A virus, rabies lyssavirus and rotavirus A) from the whole or only fractions of a given viral genome. In the works from [20], [30], [31], [32] were proposed methodologies to predict or classify specific regions in the genome sequence. [20] presented a methodology for the classification of three different functional genome types: coding regions, long noncoding regions, and pseudogenes in genomic data. They used a digital signal processing (DSP) methods, called Genomic signal processing (GSP), that converts the nucleotide sequence into a graphical representation of the information contained in the sequence. A CNN with 19 layers was used to perform the classification results. The authors in [30] proposed a DL framework to identify similar patterns in DNA N6-methyladenine (6 mA) sites prediction. This framework, called Deep6mA, is composed of a CNN to extract high-level features in the sequence and a Bi-directional LSTM (BLSTM) to learn dependence structure along the sequence, besides a fully connected layer that determines whether the site is a 6 mA site. In [31] was provided a method based on CNN and BLSTM for exploring the RNA recognition patterns of the CCCTC-binding factor (CTCF) and identify candidate IncRNAs binding. The experiments conducted with two different datasets (human U2OS and mouse ESC) were able to predict CTCF-binding RNA sites from nucleotide sequences. Moreover, [32] propose a computational prediction approach for DNA–protein binding based on CNN and BLSTM. Considering the importance of providing viral classification and the advantages of the use of DL techniques in several applications, especially for many viral classification problems, as presented previously, the main objective of this work is to generate an efficient viral genome classifier for the SARS-CoV-2 virus using the DNN based on the stacked sparse autoencoder (SSAE) technique. The SSAE has been successfully applied in many biomedical works from the state of the art [38], [39], [40], [6]. Unlike most of the related works presented previously, this work intends to provide viral classification using the whole genome sequences, as presented in [12], [13]. However, in [12], [13] were used the length of the longest genome sequence of the dataset as the input of the DNN. So, it was necessary to add some padding for the missing entries. In this work, we will explore the utilization of k-mers image representation of the complete genome sequences as the DNN input, which will feasibly the use of genome sequences of any length and enable the use of smaller network inputs. The k-mers representation was used in many works that provide genome sequence classification, as presented in [41], which explores the spectral sequence representation based on k-mers occurrences. However, that work doesn’t explore the k-mers image representation. So, our work’s novelty consists in exploring the utilization of image representations of the complete genome sequences for the processing in the SSAE to provide an accurate viral classification of the SARS-CoV-2. We performed some experiments to provide various levels of taxonomic classification of the SARS-CoV-2 virus, similar to the proposed experiments in [11], using the SSAE technique with a dataset of k-mers images representations, available on [42]. 3 Materials and methods This section will explain the dataset used in this work, describe the equations and other details about the k-mers image representation applied, and explain how the data were partitioned for the experiments. Besides, the DNN Architecture will be presented, detailing the number of layers and neurons applied and the platform used to implement the technique. 3.1 Dataset For the experiments, we used a k-mers representation dataset of SARS-CoV-2 genome, available on [42]. This dataset is composed of 1,557 virus instances of SARS-CoV-2, as also, a data stream of 11,540 viruses from the Virus-Host DB dataset and the other three Riboviria viruses from NCBI (Betacoronavirus RaTG13, bat-SL-CoVZC45, and bat-SL-CoVZXC21). It also provides k-mers image representation of all data. The k-mers images were used to perform the experiments for this work. Assuming the dataset with D sequences (in this work D=1,557+11,540+3=13,100 sequemces), each d-th sequence, stored in dataset, is expressed by(1) sd=sd,1,…,sd,n,…,sd,Nd where Nd is the length of d-th sequence and sd,n is the n-th nucleotide of the d-th sequence. Each n-th sd,n can be characterized as a symbol belonging to an alphabet of 4 possible symbols expressed by set A,T,C,G for DNA or by set A,U,C,G for RNA, that is,(2) sd,n∈A,T,C,G∨A,U,C,G. In k-mers representation, each d-th nucleotide sequence, sd, is grouped in k-mers sub-sequences [43], [44] that can be expressed as(3) Hd=hd,1hd,2⋮hd,i⋮hd,Nd-khd,Nd-k+1=sd,1⋯sd,ksd,2⋯sd,k+1⋮⋱⋮sd,i⋯sd,i+k⋮⋱⋮sd,Nd-k⋯sd,Nd-1sd,Nd-k+1⋯sd,Nd where the matrix Hd stores the k-mers associated with each d-th sequence sd. The k-mers representations are based in each d-th matrix Hd and the matrix Γ, call here as symbol matrix. The symbol matrix is expressed as(4) Γ=γ1⋮γi⋮γM=γ1,1⋯γ1,k⋮⋱⋮γi,1⋯γi,k⋮⋱⋮γM,1⋯γM,k where each element γi,j∈A,T,C,G∨A,U,C,G. The symbol matrix, Γ, stores all M possibilities of the k-mers, where(5) M=4k. The k-mers count 1D representation can be expressed as(6) cd=cd,1,…,cd,i,…,cd,M where(7) cd,i=∑v=1Nd-k+1Bd,i,v and(8) Bd,i,v=0forγi≠hd,v(∃u=1,…,k:γi,u≠sd,v+u-1)1forγi=hd,v(∀u=1,…,k:γi,u=sd,v+u-1) So, the i-th cd,i indicates the number of occurrences of each d-th sub-sequence stored on the Γ matrix. Table 3 shows a example of the k-mers count 1D representation values (with k=2) for SARS-CoV-2 from China-Wuhan (ID: LR757995), USA-MA (ID: MT039888), Brazil (ID: MT126808), and Italy (ID: MT066156). The dataset provide in [42] has k-mers count 1D representation for k=2,…,6.4 .Table 3 Examples of k-mers count 1D representation values (with k=2) for SARS-CoV-2. k-mers (k=2) China-Wuhan USA-MA Brazil Italy (ID: LR757995) (ID: MT039888) (ID: MT126808) (ID: MT066156) AA 2862 2859 2853 2847 AC 2022 2022 2022 2022 AG 1741 1741 1742 1742 AT 2306 2309 2309 2308 CA 2085 2082 2084 2082 CC 886 888 888 888 CG 439 439 440 439 CT 2080 2081 2080 2082 GA 1612 1612 1612 1611 GC 1167 1167 1169 1168 GG 1092 1093 1092 1092 GT 1990 1990 1988 1989 TA 2373 2378 2377 2378 TC 1415 1412 1413 1413 TG 2589 2589 2587 2587 TT 3212 3217 3219 3216 Table 4 Examples of k-mers count 2D representation values (with k=2) for SARS-CoV-2. China-Wuhan (ID: LR757995) USA-MA (ID: MT039888) Λ17= 28622022174123062085886439208016121167109219902373141525893212 Λ32= 28592022174123092082888439208116121167109319902378141225893217 Brazil (ID: MT126808) Italy (ID: MT066156) Λ52= 28532022174223092084888440208016121169109219882377141325873219 Λ79= 28532022174223082084888439208216121169109219892377141325873216 The k-mers count 2D representation for each d-th sequence, sd, is described by(9) Λd=λd,1,1⋯λd,1,L⋮⋱⋮λd,i,1⋯λd,i,L⋮⋱⋮λd,L,1⋯λd,L,L=cd,1⋯cd,L⋮⋱⋮cd,(i-1)×L+1⋯cd,i×L⋮⋱⋮cd,M-L+1⋯cd,M where(10) L=M=2k. Finally, the k-mers image representation, for each d-th sequence, can be represented as(11) Φd=ϕd,1,1⋯ϕd,1,L⋮⋱⋮ϕd,i,1⋯ϕd,i,L⋮⋱⋮ϕd,L,1⋯ϕd,L,L where ϕd,i,j represents each pixel associated with d-th image Φd. Each pixel, ϕd,i,j, is be expressed as(12) ϕd,i,j=2b-1maxΛd×λd,i,j where max{·} is the maximum value in d-th matrix Λd,· is the greatest integer less than or equal, and b is number of bits associated with the image pixels. Fig. 3 show the k-mers image representation, matrix Φ, (with k=6 and b=8) for Geminiviridae (ID: HE616777), Alphacoronavirus (ID: JQ410000), and SARS-CoV-2 (Betacoronavirus) from China-Wuhan (ID: LR757995) and Brazil (ID: MT126808).Fig. 3 Examples of k-mers images representation with k=6. Based on Eq. 10, L=64 and each image, matrix Φ (see Eq. 11), is composed by 64×64 pixels with b=8 (see Eq. 12). In this work, we used k-mers image representation with k=6. That choice of k value was based on the fact that when k is a small value, the existing property vectors for the k-mer may not contain enough genome information [45], however, when large k values are used, many k-mers do not appear in the sequence, which generates sparse feature vectors and causes the overfitting problem [46]. Besides, in the work presented in [17], the 6-mers reached the best performance in comparisons with other values of k (3,4,5 and 7). The data of each experiment was partitioned using the holdout method, which splits the data into a training set and a validation set at random. We used the proportion of 80% for the training set and 20% for the validation set. Each class data was split respecting these percentages. The SARS-CoV-2 k-mers images were used only for the test set. 3.2 DNN architecture All experiments were performed using the SSAE technique. In these models each hidden layer is composed of an individually trained sparse autoencoder in an unsupervised way. A sparse autoencoder is an autoencoder whose training involves a sparse penalty, which functions as a regularizing term added to the loss function [47]. The autoencoder (AE) is a DL technique specialized in dimensionality reduction and feature extraction. The AE output can provide the reconstruction of the input information. These networks are composed of three layers: an input, a hidden and an output. The encoder is formed by the input and hidden layers, and the decoder is formed by the hidden and output layers [47]. For the output layer, we used a softmax layer, where the number of neurons consists of the number of classes of the experiment. Fig. 4 illustrates the DL SSAE with P inputs, K hidden layers, and a output layer. Each i-th hidden layer has Qi neurons and the output layer has U neurons. Functions φ(·) and f(·) are the action functions in each p-th neuron (in each i-th hidden layer) and each u-th neuron in output layer, respectively.Fig. 4 Deep learning stacked sparse autoencoder architecture (DL-SSAE). For all experiments, the network architecture used three hidden layers (K=3), containing 3000 neurons in the first hidden layer, Q1,1000 in the second hidden layer, Q2, and 500 in the third hidden layer Q3. For the softmax layer, the number of neurons corresponds to the number of classes of each experiment. So, the same model was used for all experiments, varying only the number of neurons of the output layer. For input of the SSAE, it was used k-mers images, with k=6, generating images, matrix Φ, with 64×64 pixels (based on Eq. 10, L=46=64). Each d-th image, Φd, associated with a d-th viral genome sequence is reshaped into a vector expressed by(13) yd=yd,10yd,20⋮yd,i-10yd,i0yd,i+10⋮yd,P-10yd,P0=ϕd,1,1⋮ϕd,L,1ϕd,1,2⋮ϕd,L,2⋮ϕd,1,L⋮ϕd,L,L with P=64×64=4096 values and applied to the SSAE. The number of neurons in output layer, U, is defined by the number of different viruses in a specific taxonomic level such as family, genus, realm and other. The output can be expressed by(14) o=o1⋮ou⋮oU where each u-th output, ou, represents a specific virus in a taxonomic level classification and is defined by(15) ou=1ifydistheu-thvirus0otherwise. Fig. 5 illustrates how the sequence information is passed through the DL-SSAE to perform the viral classification. The DL-SSAE input was normalized in the range of 0 to 1. First, the SSAE receives the training set as input to perform the training phase. Then, the validation set, which only contains samples that were not applied in the training phase, is used to identify the capacity of generalization of the DNN. After the network validation, the SSAE was applied for the test set, which only contains SARS-CoV-2 sequences. The SARS-CoV-2 k-mers images were not used for the training phase of the SSAE.Fig. 5 Viral classification process using k-mers images representation with the DL-SSAE. The SSAE was implemented in the Matlab platform (License 596681), adopting the deep learning toolbox. All network was trained with the Scaled Conjugate Gradient (SCG) algorithm. The loss function used for the training in each AE was the Mean Squared Error with L2 and Sparsity Regularizers, that can be expressed as(16) E=1I∑i=1I∑u=1U(ouiref-oui)2+λ×Ωweights+β×Ωsparsity, where I is the number of training examples, U is the number of classes, Ωweights is the L2 regularization term, λ is the coefficient for the L2 regularization term, Ωsparsity is the sparsity regularization term, and β is the coefficient for the sparsity regularization term. The loss function applied for the softmax layer was the Cross-Entropy. After the training in each layer, the results for the SSAE can be improved with the fine-tuning process, which perform the backpropagation on the whole network, as a multilayer network. In that process, we fine tune the network, which adjust the weights, by retraining the network with the training data in a supervised way [48]. In this work, we applied that retrained process to improve the classification results. The fine-tuning process also used the Cross-Entropy as the loss function, as in the softmax layer. 4 Results and discussion We performed four different experiments to provide different levels of taxonomic classification of the SARS-CoV-2 virus, similar to the experimental methodology present in [11]. The details about the data and the network architecture used in each experiment are shown in Table 5 . The data of each experiment was split into 80% for the training set and 20% for the validation set. The SSAE architecture was chosen by the observation of the MSE obtained with the reconstruction of the validation set in each AE. In order to validate the proposed idea of this work, the results are present by the confusion matrix for the validation and test sets. We also measured the performance of the viral classifier proposed with some popular classification metrics, as precision, recall, F1-score, and specificity. The precision value measure the percentages of all the examples predicted to belong to each class that are correctly classified, which corresponds to the positive predictive value. The recall, also called sensibility, corresponds to the percentages of all the examples belonging to each class that are correctly classified, which is the true positive rate. The F1-score can be interpreted as a weighted average of the precision and recall, and the specificity indicates the true negative rate. The column on the far right of each confusion matrix shows the percentages of precision per class, and the row at the bottom of each confusion matrix shows the percentages of recall per class. The cell in the bottom right of the plot of each confusion matrix shows the overall accuracy. Besides, for the validation set we also present the receiver operating characteristic (ROC) curve. The ROC curve measures the classification performance, that is the true positive rate and the false positive rate of each class, at various thresholds settings.Table 5 Experiments data. Experiments Classes Number of sequences SSAE architecture P-Q1-Q2-Q3-U Experiment 1 Adenoviridae 195 4096-3000-1000-500-14 Anelloviridae 114 Caudovirales 500 Circoviridae 243 Geminiviridae 500 Genomoviridae 115 Herpesvirales 136 Microviridae 102 Ortervirales 214 Papillomaviridae 354 Parvoviridae 168 Polyomaviridae 142 Riboviria 500 Tolecusatellitidae 150 Experiment 2 Picornaviridae 423 4096-3000-1000-500-8 Caliciviridae 392 Coronaviridae 206 Potyviridae 232 Flaviviridae 217 Rhabdoviridae 186 Betaflexiviridae 129 Reoviridae 111 Experiment 3 Alphacoronavirus 52 4096-3000-1000-500-4 Betacoronavirus 123 Deltacoronavirus 20 Gammacoronavirus 9 Experiment 4 Embecovirus 47 4096-3000-1000-500-4 Merbecovirus 17 Nobecovirus 9 Sarbecovirus 46 In Experiment 1, we intended to classify the viruses in 14 different classes, as presented in Table 5, which consists of 10 families (Adenoviridae, Anelloviridae, Circoviridae, Geminiviridae, Genomoviridae, Microviridae, Papillomaviridae, Parvoviridae, Polyomaviridae and Tolecusatellitidae), three orders (Caudovirales, Herpesvirales and Ortervirales) and Riboviria realm. The Riboviria class contains various families that belong to the realm Riboviria, including the Coronaviridae family. To ensure data balance, only the classes with at least 100 sequences from the original dataset were considered. For the classes with more than 500 sequences, only 500 sequences were selected at random, except for the Riboviria class, which was prioritized the Coronaviridade family sequences, to guarantee the correct classification of the test data (SARS-CoV-2 sequences), which is the focus of this work. In this particular case, were selected all Coronaviridade family sequences available in the dataset (206 samples), and the other 294 sequences were select from the rest of the Riboviria data at random. After this balancing, Experiment 1 comprised 3,433 samples of virus sequences. The SSAE architecture used in Experiment 1 was the 4096-3000-1000-500-14 architecture. The three AEs were trained for 400 epochs. The softmax layer was trained for 3000 epochs or until reach the minimum gradient (<1×10-6). Lastly, the fine-tuning was performed. For each experiment, the fine-tuning phase uses the same stopping condition as the softmax layer. The confusion matrix and the ROC curve from the validation set of Experiment 1 are present in Fig. 6, Fig. 7 , respectively. In Experiment 1, the classification accuracy from the validation set reached 92%. This result is promising, especially considering the challenges of the classification in high-level taxonomies because of the high diversity of the viruses sequences. It is essential to mention that the balancing process may have caused the classification more complicated because some crucial sequences may have been excluded from the dataset. However, this result can be improved in many ways that will be discussed following.Fig. 6 Confusion matrix of the validation set from the Experiment 1. Fig. 7 ROC curve of the validation set from the Experiment 1. Regarded to the classification performance per class, the precision value presented in the last column shows that the worse result was obtained from an order class (71.4% from the Herpesvirales). Among the five worst classification results, two are from order classes (71.4% and 83.3% from Herpesvirales and Ortervirales, respectively). Since these classes can contain viruses from many different realms and families, they can difficult the training process. The Riboviria realm, which is the focus of this work, reached a classification accuracy of 93%. Analyse the results per classes can give more understanding about the dataset used and the implications of this dataset for the results, which is important to make decisions for the next experiments. The confusion matrix from the test set of Experiment 1 is present in Fig. 8 . In the test phase of this experiment, all the 1557 sequences of SARS-CoV-2 was correctly classified as belonging to the Riboviria realm, so the classification accuracy reached 100%. For the test set, we only used samples of SARS-CoV-2. For that reason, the columns and rows corresponding to the classes that were not inferred in the test phase received the terminology NaN (Not a Number) in the confusion matrix plot.Fig. 8 Confusion matrix of the test set from the Experiment 1. NaN, which means Not a Number, appears in the columns and rows corresponding to the classes that were not inferred in the test phase. Experiment 2 performs the classification of Riboviria families. As in Experiment 1, only classes with at least 100 sequences were considered. This experiment includes 1896 sequences separated into eight families (Picornaviridae, Caliciviridae, Coronaviridae, Potyviridae, Flaviviridae, Rhabdoviridae, Betaflexiviridae and Reoviridae). We used the 4096-3000-1000-500-8 SSAE architecture. The three AEs were trained for 400 epochs each and the softmax layer was trained for 1000 epochs or until reaching the minimum gradient, as well as the fine-tuning phase. The confusion matrix and the ROC curve from the validation set of Experiment 2 are present in Fig. 9, Fig. 10 , respectively. The classification accuracy from Experiment 2 reached 96.3%. From the 379 sequences applied in this validation, only 11 were not correctly classified. Besides, the SSAE classified all sequences that belong to the Coronaviridade family correctly. The ROC curve from Experiment 2 also provides excellent results.Fig. 9 Confusion matrix of the validation set from the Experiment 2. Fig. 10 ROC curve of the validation set from the Experiment 2. The confusion matrix from the test set of Experiment 2 is present in Fig. 11 . The SSAE achieve 100% of classification accuracy, i.e., all SARS-CoV-2 sequences applied in this experiment were perfectly classified as Coronaviridae family sequences.Fig. 11 Confusion matrix of the test set from the Experiment 2. NaN, which means Not a Number, appears in the columns and rows corresponding to the classes that were not inferred in the test phase. In Experiment 3 we aim to provide the classification among the Coronaviridae genera. For this experiment, 204 sequences divided into four genera (Alphacoronavirus, Betacoronavirus, Deltacoronavirus and Gammacoronavirus) were used. The SSAE architecture used in this experiment was the 4096-3000-1000-500-4 architecture. The three AEs were trained for 400 epochs each, and the softmax layer was trained for 2000 epochs or until reaching the minimum gradient. Fig. 12, Fig. 13 show the resulting confusion matrix and ROC curve from the Experiment 3, respectively. This experiment achieved 95% of classification accuracy of the validation set. The classification performance of the model obtained for the Betacoronavirus genus was 95.8%. Also, the ROC curve plotted for all classes of Experiment 3 provides satisfactory results.Fig. 12 Confusion matrix of the validation set from the Experiment 3. Fig. 13 ROC curve of the validation set from the Experiment 3. Regarding the test set of Experiment 3, the confusion matrix is present in Fig. 14 . The test phase of Experiment 3 achieved 98.9% of classification accuracy. In the validation phase of Experiment 3, the Betacoronavirus genus did not reach the highest performance, which probably explains these result in the test phase.Fig. 14 Confusion matrix of the test set from the Experiment 3. NaN, which means Not a Number, appears in the columns and rows corresponding to the classes that were not inferred in the test phase. In Experiment 4, we provide the Betacoronaviridae subgenera classification. This test includes 119 genome sequences divided into four classes (Embecovirus, Marbecovirus, Nobecovirus and Sarbecovirus). The SSAE architecture was the same as the architecture used in Experiment 3 (4096-3000-1000-500-4), as well as the training parameters. The confusion matrix and the ROC curve from the validation set of Experiment 4 are present in Fig. 15, Fig. 16 , respectively. In this experiment, the SSAE achieved the highest classification accuracy (100%), which is reaffirmed for the ROC curve plot. 17 .Fig. 15 Confusion matrix of the validation set from the Experiment 4. Fig. 16 ROC curve of the validation set from the Experiment 4. Fig. 17 Confusion matrix of the test set from the Experiment 4. NaN, which means Not a Number, appears in the columns and rows corresponding to the classes that were not inferred in the test phase. Fig. 15 exposes the confusion matrix from the test set of Experiment 4. In this case, the SSAE achieved 99.9% of classification accuracy, that is equivalent to only one sequence wrong classified. Table 6 presents the results regarding some popular classification performance metrics obtained from the validation set. The first column of the table indicates the experiment proposed. The second column shows the overall accuracy for each experiment. The precision, recall, F1-score, and specificity are present in the others columns, which were obtained by the average of the values obtained for each class.Table 6 Classification performance metrics results obtained from the validation set. Experiment Accuracy Precision Recall F1 score Specificity 1 0.920 (92.0%) 0.924 (92.4%) 0.920 (92.0%) 0.931 (93.1%) 0.993 (99.3%) 2 0.963 (96.3%) 0.968 (96.8%) 0.971 (97.1%) 0.962 (96.2%) 0.997 (99.7%) 3 0.950 (95.0%) 0.979 (97.9%) 0.979 (97.9%) 0.955 (95.5%) 0.983 (98.3%) 4 1 (100%) 1 (100%) 1 (100%) 1 (100%) 1 (100%) All the metrics presented in Table 6 indicate that the viral classifier proposed performs great for all experiments. The highest performance was obtained for the Experiment 4. Besides, Experiments 2 and 3, reached values more than 0.95 for all the metrics evaluated. The classification performance slightly decreased in the Experiment 1, which is acceptable because of the high diversity of the viruses sequences applied. However, considering all the experiments, the specificity (true negative rate) reached values between 0.983 and 1. Table 7 presents the results regarding some popular classification performance metrics obtained from the test set. The first column of the table indicates the experiment proposed. The second column shows the overall accuracy for each experiment. And the last column shows the recall, or true positive rate, which were obtained only for the class that corresponds to the SARS-CoV-2 samples. The other metrics (precision, F1-score, and specificity) are not presented because in the tests we do not have false positives samples.Table 7 Classification performance metrics results obtained from the test set. Experiment Accuracy Recall 1 1 (100%) 1 (100%) 2 1 (100%) 1 (100%) 3 0.989 (98.9%) 0.989 (98.9%) 4 0.999 (99.9%) 0.999 (99.9%) When the SARS-CoV-2 samples were applied, all the experiments perform excellently. The accuracy reached values between 98.9% and 100%, as well as the recall (true positive rate). The results presented in Table 7 are very significant since the classification of the SARS-CoV-2 virus was the main objective of this study. We perform the error calculation of the classification analysis by the mean square error (MSE) between the target output and the SSAE output of each experiment. Table 8 shows the MSE obtained for the training, validation and test sets.Table 8 Mean Square Error obtained for the training, validation and test sets of each experiment. Experiment Training set Validation set Test set 1 5.8×10-13 1.1×10-2 3.4×10-103 2 4.1×10-13 9.4×10-3 2.9×10-24 3 5.8×10-13 2.2×10-2 5.3×10-2 4 1.6×10-12 1.1×10-12 3.8×10-4 Table 8 indicates that for all experiments, the MSE of the training set was very acceptable, as well as the MSE of the validation and test sets. As expected, for most experiments, the MSE of the training was lower than the MSE of the validation. In order to provide results about the temporal complexity of our experiments, Table 9 shows the training time of each experiment, describing the training time of each layer (AEs and softmax), the fine-tuning phase, and the total training time. The training in each autoencoder was performed with an NVIDIA GeForce GTX GPU (Intel Core i5-9300H host CPU), and for the softmax layer and the fine-tuning phase, a CPU (Intel Core i5-9300H 2.4 GHz) was used.Table 9 Final SSAE training time of each experiment. Experiment First Second Third Softmax Fine-tuning Total Training AE AE AE Layer Time 1 7h29m00s 19m12s 4m49s 44s 36m50s ≈8h30m 2 1h39m11s 11m56s 3m16s 10 s 5m24s ≈2h 3 32m24s 5m50s 2m22s 0s 27s ≈41m 4 19m15s 4m54s 1m16s 0s 11s ≈25m As shown in Table 9, most of the experiments finished the training in the softmax layer and the fine-tuning in seconds or a few minutes, That occurred because they reached the minimum gradient after some training epochs, indicating that the three AEs trained before extracted relevant information about the dataset used. In Table 10 , we compare the results obtained from each experiment and the results of another work from the state of the art, which performed taxonomy classification of the SARS-CoV-2 virus using different machine learning techniques.11 .Table 10 State of the art comparison associated with the classification accuracy of the validation set. Reference Algorithm Exp. 1 Exp. 2 Exp. 3 Exp. 4 This work SSAE 92% 96.3% 95% 100% [11] Linear Discriminant 91.7% 91.2% 98.1% 97.6% [11] Linear SVM 90.8% 89.2% 94.2% 98.4% [11] Quadratic SVM 95% 93.1% 95.2% 98.4% [11] Fine KNN 93.4% 90.3% 95.7% 97.6% [11] Subspace Discriminat 87.6% 89% 97.6% 98.4% [11] Subspace KNN 93.2% 90.4% 96.2% 97.2% [11] Average Accuracy 92% 90.5% 96.2% 97.6% Table 11 State of the art comparison associated with the mapping pipeline. Reference Mapping pipeline Number of inputs This work k-mers 4k [11] k-mers  + CGR  + FFT  + PCC D Table 10 shows that for experiments 1 and 3, the techniques used in [11] achieve lower, equivalent or superior accuracy than the SSAE technique applied in our work. However, considering experiments 2 and 4, the SSAE technique provides superior classification accuracy results than all the techniques applied in [11]. For experiment 1, the DL-SSAE had a slightly lower accuracy compared to Quadratic SVM (difference was 3%), Fine KNN (difference was 1.4%), and Subspace KNN (difference was 1.2%). For experiment 3, the DL-SSAE had a slightly lower accuracy compared to Linear Discriminant (difference was 3.1%), Quadratic SVM (difference was 0.2%), Fine KNN (difference was 0.7%), Subspace Discriminat (difference was 2.6%), Subspace KNN (difference was 1.2%), and Average Accuracy (difference was 1.2%). However, it is essential to understand that the proposal presented in [11] uses a high-complexity mapping pipeline. This pipeline is composed of the k-mers followed by chaos game representation (CGR), Fast Fourier transform (FFT) and Pearson correlation coefficient calculation (PPC) for each d-th sequence. In the final, each d-th sequence is converted into a D dimension vector, where D is the number of sequences in the dataset (see SubSection 3.1). In other words, the ML input size used in the proposal presented in [11] is a function of the number of sequences of the dataset. This characteristic can be prohibitive for several viral classification applications with a large dataset. In the work way, the work proposal in this manuscript, each d-th sequence is converted into a 4096 elements vector (or bi-dimensional matrix of 64×64) for k=6. In other words, the ML input is not dependent on the number of sequences in the dataset. In all experiments of this work, the SSAE technique provided great performance results, especially for the test set. However, some strategies can be applied in future experiments to improve classification accuracy results. One of them consists in the use of the k-fold cross-validation scheme. We also intend to study data balancing alternatives based on the analysis of the results presented here. Besides, we plan to extend this work by applying the SSAE technique to classify the SARS-CoV-2 variants. 5 Conclusions This work presented an efficient viral genome classifier for the SARS-CoV-2 virus using the DNN based on the stacked sparse autoencoder technique. Our model is able to classify genome sequences of the SARS-CoV-2 virus in various levels of taxonomy. We perform four experiments in order to classify realm, family, genus and subgenus. We explored the utilization of k-mers image representation of the whole genome sequence as the DNN input, which feasibility the use of genome sequences of any length and enable the use of smaller network inputs. We measured the effectiveness of the model by some popular classification performance metrics (accuracy, precision, recall, F1 score, and specificity), which are metrics used in many works in the literature, as presented in [12], [14], [15]. Besides, for each experiment, we plot the ROC curve for the validation set and the confusion matrix for the validation and test sets. All experiments provided great performance results, reaching accuracies between 92% and 100% for the validation set and between 98.9% and 100% for the test set, which contains only SARS-CoV-2 samples. These results indicated the applicability of using our model, based on the stacked sparse autoencoder technique, in genome classification problems. Our approach can be adapted to classify other emerging viruses. However, the model may require to be retrained to include new data and satisfy some conditions. It is essential to consider some implications of that training process since it is necessary to previously define the classes that will be used for training the SSAE. One of the requirements for the correct classification of a new virus by our model is that the training process includes samples that belong to the same class, which could be the family, genus or another taxonomic level of the new virus being classified. In the future, we plan to extend this work by performing experiments with another image representation of the genome sequences and applying the SSAE technique to classify the SARS-CoV-2 variants. Funding This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) - Finance Code 001. CRediT authorship contribution statement Maria G.F. Coutinho: Investigation, Methodology, Software, Validation, Visualization, Writing - original draft, Writing - review & editing. Gabriel B.M. Câmara: Investigation, Methodology, Software, Validation, Visualization, Writing - original draft, Writing - review & editing. Raquel M. de Barbosa: Data curation, Formal analysis, Investigation, Methodology, Supervision, Validation, Visualization, Writing - original draft, Writing - review & editing. Marcelo A.C. Fernandes: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing - original draft, Writing - review & editing. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments The authors wish to acknowledge the financial support of the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). ==== Refs References 1 Lam T.T.-Y. Shum M.H.-H. Zhu H.-C. Tong Y.-G. Ni X.-B. Liao Y.-S. Wei W. Cheung W.Y.-M. Li W.-J. Li L.-F. Identifying sars-cov-2 related coronaviruses in malayan pangolins Nature 2020 1 6 2 Andersen K.G. Rambaut A. Lipkin W.I. Holmes E.C. Garry R.F. The proximal origin of sars-cov-2 Nature Med 26 4 2020 450 452 32284615 3 R.L. Graham, R.S. Baric, Sars-cov-2: Combating coronavirus emergence, Immunity. 4 Zielezinski A. Vinga S. Almeida J. Karlowski W.M. Alignment-free sequence comparison: benefits, applications, and tools Genome Biol 18 1 2017 186 28974235 5 Zou J. Huss M. Abid A. Mohammadi P. Torkamani A. Telenti A. A primer on deep learning in genomics Nature Genet 51 1 2019 12 18 30478442 6 Tang B. Pan Z. Yin K. Khateeb A. Recent advances of deep learning in bioinformatics and computational biology Front Genet 10 2019 214 30972100 7 Eraslan G. Avsec Ž. Gagneur J. Theis F.J. Deep learning: new computational modelling techniques for genomics Nat Rev Genet 20 7 2019 389 403 30971806 8 Pareek C.S. Smoczynski R. Tretyn A. Sequencing technologies and genome sequencing J Appl Genet 52 4 2011 413 435 21698376 9 Pabinger S. Dander A. Fischer M. Snajder R. Sperk M. Efremova M. Krabichler B. Speicher M.R. Zschocke J. Trajanoski Z. A survey of tools for variant analysis of next-generation genome sequencing data Briefings Bioinform 15 2 2014 256 278 10 Posada-Cespedes S. Seifert D. Beerenwinkel N. Recent advances in inferring viral diversity from high-throughput sequencing data Virus Res 239 2017 17 32 27693290 11 Randhawa G.S. Soltysiak M.P. El Roz H. de Souza C.P. Hill K.A. Kari L. Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: Covid-19 case study Plos One 15 4 2020 e0232391 12 Fabijańska A. Grabowski S. Viral genome deep classifier IEEE Access 7 2019 81297 81307 13 A. Lopez-Rincon, A. Tonda, L. Mendoza-Maldonado, E. Claassen, J. Garssen, A.D. Kraneveld, Accurate identification of sars-cov-2 from viral genome sequences using deep learning, bioRxiv. 14 J.M. Bartoszewicz, A. Seidel, B.Y. Renard, Interpretable detection of novel human viruses from genome sequencing data, bioRxiv doi:10.1101/2020.01.29.925354. 15 Liang Q. Bible P.W. Liu Y. Zou B. Wei L. Deepmicrobes: taxonomic classification for metagenomics with deep learning NAR Genom Bioinform 2 1 2020 lqaa009 33575556 16 J. Shang, Y. Sun, Cheer: hierarchical taxonomic classification for viral metagenomic data via deep learning, Methods. 17 Tampuu A. Bzhalava Z. Dillner J. Vicente R. Viraminer: Deep learning on raw dna sequences for identifying viral genomes in human samples PloS One 14 9 2019 e0222271 18 Ren J. Song K. Deng C. Ahlgren N.A. Fuhrman J.A. Li Y. Xie X. Poplin R. Sun F. Identifying viruses from metagenomic data using deep learning Quant Biol 2020 1 14 19 F. Mock, A. Viehweger, E. Barth, M. Marz, Viral host prediction with deep learning, bioRxiv (2019) 575571. 20 Morales J.A. Saldaña R. Santana-Castolo M.H. Torres-Cerna C.E. Borrayo E. Mendizabal-Ruiz A.P. Vélez-Pérez H.A. Mendizabal-Ruiz G. Deep learning for the classification of genomic signals Math Probl Eng 2020 21 Nguyen N.G. Tran V.A. Ngo D.L. Phan D. Lumbanraja F.R. Faisal M.R. Abapihi B. Kubo M. Satou K. Dna sequence classification by convolutional neural network J Biomed Sci Eng 9 05 2016 280 22 Guo Y. Li W. Wang B. Liu H. Zhou D. Deepaclstm: deep asymmetric convolutional long short-term memory neural models for protein secondary structure prediction BMC Bioinform 20 1 2019 1 12 23 Heidari A. Jafari Navimipour N. Unal M. Toumaj S. Machine learning applications for covid-19 outbreak management Neural Comput Appl 2022 1 36 24 Heidari A. Toumaj S. Navimipour N.J. Unal M. A privacy-aware method for covid-19 detection in chest ct images using lightweight deep conventional neural network and blockchain Comput Biol Med 145 2022 105461 10.1016/j.compbiomed.2022.105461 https://www.sciencedirect.com/science/article/pii/S0010482522002530 25 Heidari A. Jafari Navimipour N. Unal M. Toumaj S. The covid-19 epidemic analysis and diagnosis using deep learning: A systematic literature review and future directions Comput Biol Med 141 2022 105141 10.1016/j.compbiomed.2021.105141 https://www.sciencedirect.com/science/article/pii/S0010482521009355 26 G.J.L., B. Abraham, S.M.S., M.S. Nair, A computer-aided diagnosis system for the classification of covid-19 and non-covid-19 pneumonia on chest x-ray images by integrating cnn with sparse autoencoder and feed forward neural network, Comput Biol Med 141 (2022) 105134. doi:https://doi.org/10.1016/j.compbiomed.2021.105134. https://www.sciencedirect.com/science/article/pii/S0010482521009288. 27 Carracedo-Reboredo P. Liñares-Blanco J. Rodríguez-Fernández N. Cedrón F. Novoa F.J. Carballal A. Maojo V. Pazos A. Fernandez-Lozano C. A review on machine learning approaches and trends in drug discovery, Computational and Structural Biotechnol J 19 2021 4538 4558 10.1016/j.csbj.2021.08.011 https://www.sciencedirect.com/science/article/pii/S2001037021003421 28 H. Zhu, Q. Guo, M. Li, C. Wang, Z. Fang, P. Wang, J. Tan, S. Wu, Y. Xiao, Host and infectivity prediction of wuhan 2019 novel coronavirus using deep learning algorithm, BioRxiv. 29 Fang Z. Tan J. Wu S. Li M. Xu C. Xie Z. Zhu H. Ppr-meta: a tool for identifying phages and plasmids from metagenomic fragments using deep learning GigaScience 8 6 2019 giz066 31220250 30 C. Pian, Z. Li, H. Jiang, L. Kong, Y. Chen, L. Zhang, Deep6ma: a deep learning framework for exploring similar patterns in dna n6-methyladenine sites across different species, bioRxiv. 31 Kuang S. Wang L. Identification and analysis of consensus rna motifs binding to the genome regulator ctcf NAR Genom Bioinform 2 2 2020 lqaa031 33575587 32 Zhang Y. Qiao S. Ji S. Li Y. Deepsite: bidirectional lstm and cnn models for predicting dna–protein binding Int J Mach Learn Cybern 2019 1 11 33 Remita M.A. Halioui A. Daigle B. Kiani G. Diallo A.B. A machine learning approach for viral genome classification BMC Bioinform 18 1 2017 208 34 Ren J. Song K. Deng C. Ahlgren N.A. Fuhrman J.A. Li Y. Xie X. Poplin R. Sun F. Identifying viruses from metagenomic data using deep learning Quant Biol 2020 1 14 35 L. Dey, S. Chakraborty, A. Mukhopadhyay, Machine learning techniques for sequence-based prediction of viral–host interactions between sars-cov-2 and human proteins, Biomed J. 36 Bzhalava Z. Tampuu A. Bała P. Vicente R. Dillner J. Machine learning for detection of viral sequences in human metagenomic datasets BMC Bioinform 19 1 2018 336 37 Whata A. Chimedza C. Deep learning for sars cov-2 genome sequences IEEE Access 9 2021 59597 59611 10.1109/ACCESS.2021.3073728 34812391 38 Xu J. Xiang L. Liu Q. Gilmore H. Wu J. Tang J. Madabhushi A. Stacked sparse autoencoder (ssae) for nuclei detection on breast cancer histopathology images IEEE Trans Med Imaging 35 1 2016 119 130 26208307 39 Pratiher S. Chattoraj S. Vishwakarma K. Application of stacked sparse autoencoder in automated detection of glaucoma in fundus images Unconventional Optical Imaging vol. 10677 2018 International Society for Optics and Photonics 106772X 40 Xiao Y. Wu J. Lin Z. Zhao X. A semi-supervised deep learning method based on stacked sparse auto-encoder for cancer prediction using rna-seq data Comput Methods Programs Biomed 166 2018 99 105 30415723 41 Rizzo R. Fiannaca A. La Rosa M. Urso A. A deep learning approach to dna sequence classification International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics 2015 Springer 129 140 42 R. de M. Barbosa, M.A. Fernandes, k-mers 1d and 2d representation dataset of sars-cov-2 nucleotide sequences, Mendeley Data v2. doi:https://doi.org/10.17632/f5y9cggnxy.2.https://data.mendeley.com/datasets/f5y9cggnxy/2. 43 Mapleson D. Garcia Accinelli G. Kettleborough G. Wright J. Clavijo B.J. KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies Bioinformatics 33 4 2016 574 576 10.1093/bioinformatics/btw663 44 Chor B. Horn D. Goldman N. Levy Y. Massingham T. Genomic dna k-mer spectra: models and modalities Genome Biology 10 10 2009 R108 19814784 45 Han G.-B. Cho D.-H. Genome classification improvements based on k-mer intervals in sequences Genomics 111 6 2019 1574 1582 10.1016/j.ygeno.2018.11.001 https://www.sciencedirect.com/science/article/pii/S0888754318304476 30439480 46 Ghandi M. Lee D. Mohammad-Noori M. Beer M.A. Enhanced regulatory sequence prediction using gapped k-mer features PLOS Comput Biol 10 7 2014 1 15 10.1371/journal.pcbi.1003711 47 Goodfellow I. Bengio Y. Courville A. Deep Learning 2016 MIT press 48 The MathWorks, Train Stacked Autoencoders for Image Classification,https://www.mathworks.com/help/deeplearning/ug/train-stacked-autoencoders-for-image-classification.html (Sep 2020).
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==== Front Dent Abstr Dent Abstr Dental Abstracts; a Selection of World Dental Literature 0011-8486 0011-8486 Published by Elsevier Inc S0011-8486(22)00436-8 10.1016/j.denabs.2022.09.007 The Big Picture Managing Oral Pain Through Tele(oral)medicine 12 12 2022 November-December 2022 12 12 2022 67 6 395396 © 2022 Published by Elsevier Inc. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. ==== Body pmcBackground In the first few months of the COVID-19 pandemic, many patients were unable to have the medical treatments and visits they needed, which delayed diagnosis and postponed treatment. In response, most medical institutions in the United States expanded the use of telehealth practices to provide an alternative way to provide patient services. Telehealth is the use of communication technologies and digital information to access health care services remotely. Although all health care professions have access to telehealth technologies, its use in oral medicine and other dental practices (teledentistry) has been sparse. The US military had used it since 1994, but limited the use to consultations, diagnosis, and treatment planning. Subsequent uses included remote dental screening, making diagnosis, providing consultations, and proposing provision treatment plans until an in-person visit can be made. The American Dental Association (ADA) includes synchronous and asynchronous patient care, remote patient monitoring, and mobile health. The synchronous modality uses a virtual video visit to permit a face-to-face encounter between patient and dentist. The asynchronous modality focuses on diagnosis and examination through data transfer of recorded health information, which includes videos, radiographs, and intraoral photographs. The University of California San Francisco implemented tele(oral)medicine practice for the diagnosis and management of some oral medicine conditions using synchronous and asynchronous modalities and continued its use beyond the lifting of the shelter-in-place restrictions. The role of tele(oral)medicine visits was tested based on its ability to manage pain recorded at the first telemedicine visit and comparing it to the pain recorded at the first follow-up visit. Methods A retrospective chart review of new patients seen via tele(oral)medicine between April 1, 2020 and December 22, 2020 was conducted. The video visits were done via Zoom and followed a standardized telehealth protocol. Patients were given detailed instructions on how to join the virtual visit and were asked to send any intraoral photos, biopsy results, or previous health records pertinent to their condition. Clinical data were entered into an electronic spreadsheet. In addition, Google Maps was used to calculate the distance from the patient’s home to the oral medicine clinic. Patients reported their pain level at each visit using a 0 to 10 scale, with 0 being no pain and 10 being the worst pain. Follow-up video visits also included pain scores and patients’ self-reported percentage of improvement since the previous visit. Presumptive diagnoses were made in the first visit. Results A total of 137 patients (median age 56 years) were seen. Fifty-seven percent were women, and among the 85 patients who chose to report their race/ethnicity, 82% reported they were white. In 67% of cases, the telehealth visit was covered by private medical insurance, in 23% by Medicare, in 3% by private dental insurance, and in 4% by Dentical. Sixty percent of the patients were referred by medical doctors, with 34% of the referrers being primary care physicians (Table 1 ). Twenty-six percent of the patients were self-referred. The median distance from the patients’ homes to the clinic was 65 miles, with a range from 0.9 to 100 miles.Table 1 Referring Doctors for 137 New Patients Seen Through a Tele(oral)medicine Visit from April 1 to December 22, 2020 Referring doctors N (%) Dentist 21 15 Medical doctors  Primary care physician 47 34  Otolaryngologist 17 12  Oral maxillofacial surgeon 5 4  Dermatologist 5 4  Pediatrician 3 2  Immunologist 2 1  Oncologist 2 1 Self-referred 35 26 (Courtesy of Alsafwani Z, Shiboski C, Villa A: The role of telemedicine for symptoms management in oral medicine: A retrospective observational study. BMC Oral Health 22:92, 2022.) Diagnostic Tests Thirty-seven percent of the patients needed an oral biopsy and were asked to schedule an in-person visit. Nine percent needed panoramic radiographs and 2% needed laboratory studies. Diagnosis and Pain Symptoms Forty percent of the presumptive diagnoses were reactive/inflammatory lesions and 23% were immune-mediated conditions (Table 2 ). Other diagnoses included orofacial pain disorders (13%), infections (12%), neoplasms (6%), metabolic and pre-neoplastic conditions (1%), and other (3%).Table 2 Diagnosis Category Among 137 New Patients at Their First Tele(oral)medicine Visit from April 1 to December 22, 2020 Diagnosis category N (%) Presumptive diagnosis n (%) Reactive 56 40 Fibroma, papilloma, pyogenic granu- loma: n = 37 (52%) Hypersensitivity reactions: n = 2 (3%) Other: n = 17 (30%) Autoimmune 31 23 Lichen planus: n = 14 (45%) Pemphigus/MMP: n = 3 (10%) RAS: n = 14 (45%) Orofacial Pain 18 13 Burning mouth syndrome: n = 16 (89%) TMJ: n = 1 (5.5%) Myofascial pain: n = 1 (5.5%) Infection 17 12 Oral candidiasis: n = 8 (47%) Bacterial infection: n = 1 (6%) Recurrent HSV infection: n = 2 (12%) Other: n = 6 (35%) Neoplasm 9 6 SCC: n = 3 (33%) Dysplasia: n = 6 (67%) Other 4 3 Pre-radiation Metabolic 1 1 IBD related oral ulcer Pre-neoplastic 1 1 Proliferative leukoplakia Abbreviations: SCC, Squamous cell carcinoma; IBD, inflammatory bowel disease; MMP, mucous membrane pemphigoid; RAS, recurrent aphthous stomatitis. (Courtesy of Alsafwani Z, Shiboski C, Villa A: The role of telemedicine for symptoms management in oral medicine: A retrospective observational study. BMC Oral Health 22:92, 2022.) The median pain reduction was 3 points from first video visit to first follow-up visit. The self-reported median improvement was 65%. Discussion Teledentistry provided both safe access to dental care and the delivery of needed diagnostic and management information. Advantages over in-person visits during the COVID-19 pandemic included the facilitation of public health mitigation strategies through the use of social distancing; reduced costs related to transportation; and reduced time loss for patients. Persons who were medically or social vulnerable or unable to access providers were able to receive oral health care remotely.Clinical Significance Tele(oral)medicine allows for patients to access dental care and avoid the problems associated with delaying care and having the situation progress. Patient satisfaction with video visits is high. Patients can have an initial screening for oral mucosal conditions, receive a diagnosis, and have a plan for treatment put in place. Those who live in remote regions where an oral health care specialist isn’t readily available can access the care they need. Continuing the use of tele(oral)medicine and expanding its reach have the potential to offer a well-received patient experience that can be applied in many situations besides pandemics. Alsafwani Z, Shiboski C, Villa A: The role of telemedicine for symptoms management in oral medicine: A retrospective observational study. BMC Oral Health 22:92, 2022 Reprints available from Z Alsafwani, Dept of Orofacial Sciences, School of Dentistry, Univ of California San Francisco, 513 Parnassus Ave, S-722, San Francisco, CA 94143, USA; e-mail: [email protected]
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Dent Abstr. 2022 Dec 12 November-December; 67(6):395-396
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==== Front Dent Abstr Dent Abstr Dental Abstracts; a Selection of World Dental Literature 0011-8486 0011-8486 Published by Elsevier Inc S0011-8486(22)00436-8 10.1016/j.denabs.2022.09.007 The Big Picture Managing Oral Pain Through Tele(oral)medicine 12 12 2022 November-December 2022 12 12 2022 67 6 395396 © 2022 Published by Elsevier Inc. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. ==== Body pmcBackground In the first few months of the COVID-19 pandemic, many patients were unable to have the medical treatments and visits they needed, which delayed diagnosis and postponed treatment. In response, most medical institutions in the United States expanded the use of telehealth practices to provide an alternative way to provide patient services. Telehealth is the use of communication technologies and digital information to access health care services remotely. Although all health care professions have access to telehealth technologies, its use in oral medicine and other dental practices (teledentistry) has been sparse. The US military had used it since 1994, but limited the use to consultations, diagnosis, and treatment planning. Subsequent uses included remote dental screening, making diagnosis, providing consultations, and proposing provision treatment plans until an in-person visit can be made. The American Dental Association (ADA) includes synchronous and asynchronous patient care, remote patient monitoring, and mobile health. The synchronous modality uses a virtual video visit to permit a face-to-face encounter between patient and dentist. The asynchronous modality focuses on diagnosis and examination through data transfer of recorded health information, which includes videos, radiographs, and intraoral photographs. The University of California San Francisco implemented tele(oral)medicine practice for the diagnosis and management of some oral medicine conditions using synchronous and asynchronous modalities and continued its use beyond the lifting of the shelter-in-place restrictions. The role of tele(oral)medicine visits was tested based on its ability to manage pain recorded at the first telemedicine visit and comparing it to the pain recorded at the first follow-up visit. Methods A retrospective chart review of new patients seen via tele(oral)medicine between April 1, 2020 and December 22, 2020 was conducted. The video visits were done via Zoom and followed a standardized telehealth protocol. Patients were given detailed instructions on how to join the virtual visit and were asked to send any intraoral photos, biopsy results, or previous health records pertinent to their condition. Clinical data were entered into an electronic spreadsheet. In addition, Google Maps was used to calculate the distance from the patient’s home to the oral medicine clinic. Patients reported their pain level at each visit using a 0 to 10 scale, with 0 being no pain and 10 being the worst pain. Follow-up video visits also included pain scores and patients’ self-reported percentage of improvement since the previous visit. Presumptive diagnoses were made in the first visit. Results A total of 137 patients (median age 56 years) were seen. Fifty-seven percent were women, and among the 85 patients who chose to report their race/ethnicity, 82% reported they were white. In 67% of cases, the telehealth visit was covered by private medical insurance, in 23% by Medicare, in 3% by private dental insurance, and in 4% by Dentical. Sixty percent of the patients were referred by medical doctors, with 34% of the referrers being primary care physicians (Table 1 ). Twenty-six percent of the patients were self-referred. The median distance from the patients’ homes to the clinic was 65 miles, with a range from 0.9 to 100 miles.Table 1 Referring Doctors for 137 New Patients Seen Through a Tele(oral)medicine Visit from April 1 to December 22, 2020 Referring doctors N (%) Dentist 21 15 Medical doctors  Primary care physician 47 34  Otolaryngologist 17 12  Oral maxillofacial surgeon 5 4  Dermatologist 5 4  Pediatrician 3 2  Immunologist 2 1  Oncologist 2 1 Self-referred 35 26 (Courtesy of Alsafwani Z, Shiboski C, Villa A: The role of telemedicine for symptoms management in oral medicine: A retrospective observational study. BMC Oral Health 22:92, 2022.) Diagnostic Tests Thirty-seven percent of the patients needed an oral biopsy and were asked to schedule an in-person visit. Nine percent needed panoramic radiographs and 2% needed laboratory studies. Diagnosis and Pain Symptoms Forty percent of the presumptive diagnoses were reactive/inflammatory lesions and 23% were immune-mediated conditions (Table 2 ). Other diagnoses included orofacial pain disorders (13%), infections (12%), neoplasms (6%), metabolic and pre-neoplastic conditions (1%), and other (3%).Table 2 Diagnosis Category Among 137 New Patients at Their First Tele(oral)medicine Visit from April 1 to December 22, 2020 Diagnosis category N (%) Presumptive diagnosis n (%) Reactive 56 40 Fibroma, papilloma, pyogenic granu- loma: n = 37 (52%) Hypersensitivity reactions: n = 2 (3%) Other: n = 17 (30%) Autoimmune 31 23 Lichen planus: n = 14 (45%) Pemphigus/MMP: n = 3 (10%) RAS: n = 14 (45%) Orofacial Pain 18 13 Burning mouth syndrome: n = 16 (89%) TMJ: n = 1 (5.5%) Myofascial pain: n = 1 (5.5%) Infection 17 12 Oral candidiasis: n = 8 (47%) Bacterial infection: n = 1 (6%) Recurrent HSV infection: n = 2 (12%) Other: n = 6 (35%) Neoplasm 9 6 SCC: n = 3 (33%) Dysplasia: n = 6 (67%) Other 4 3 Pre-radiation Metabolic 1 1 IBD related oral ulcer Pre-neoplastic 1 1 Proliferative leukoplakia Abbreviations: SCC, Squamous cell carcinoma; IBD, inflammatory bowel disease; MMP, mucous membrane pemphigoid; RAS, recurrent aphthous stomatitis. (Courtesy of Alsafwani Z, Shiboski C, Villa A: The role of telemedicine for symptoms management in oral medicine: A retrospective observational study. BMC Oral Health 22:92, 2022.) The median pain reduction was 3 points from first video visit to first follow-up visit. The self-reported median improvement was 65%. Discussion Teledentistry provided both safe access to dental care and the delivery of needed diagnostic and management information. Advantages over in-person visits during the COVID-19 pandemic included the facilitation of public health mitigation strategies through the use of social distancing; reduced costs related to transportation; and reduced time loss for patients. Persons who were medically or social vulnerable or unable to access providers were able to receive oral health care remotely.Clinical Significance Tele(oral)medicine allows for patients to access dental care and avoid the problems associated with delaying care and having the situation progress. Patient satisfaction with video visits is high. Patients can have an initial screening for oral mucosal conditions, receive a diagnosis, and have a plan for treatment put in place. Those who live in remote regions where an oral health care specialist isn’t readily available can access the care they need. Continuing the use of tele(oral)medicine and expanding its reach have the potential to offer a well-received patient experience that can be applied in many situations besides pandemics. Alsafwani Z, Shiboski C, Villa A: The role of telemedicine for symptoms management in oral medicine: A retrospective observational study. BMC Oral Health 22:92, 2022 Reprints available from Z Alsafwani, Dept of Orofacial Sciences, School of Dentistry, Univ of California San Francisco, 513 Parnassus Ave, S-722, San Francisco, CA 94143, USA; e-mail: [email protected]
0
PMC9742982
NO-CC CODE
2022-12-14 23:42:50
no
Dent Abstr. 2022 Dec 12 November-December; 67(6):424-426
latin-1
Dent Abstr
2,022
10.1016/j.denabs.2022.09.019
oa_other
==== Front Dent Abstr Dent Abstr Dental Abstracts; a Selection of World Dental Literature 0011-8486 0011-8486 Published by Elsevier Inc S0011-8486(22)00436-8 10.1016/j.denabs.2022.09.007 The Big Picture Managing Oral Pain Through Tele(oral)medicine 12 12 2022 November-December 2022 12 12 2022 67 6 395396 © 2022 Published by Elsevier Inc. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. ==== Body pmcBackground In the first few months of the COVID-19 pandemic, many patients were unable to have the medical treatments and visits they needed, which delayed diagnosis and postponed treatment. In response, most medical institutions in the United States expanded the use of telehealth practices to provide an alternative way to provide patient services. Telehealth is the use of communication technologies and digital information to access health care services remotely. Although all health care professions have access to telehealth technologies, its use in oral medicine and other dental practices (teledentistry) has been sparse. The US military had used it since 1994, but limited the use to consultations, diagnosis, and treatment planning. Subsequent uses included remote dental screening, making diagnosis, providing consultations, and proposing provision treatment plans until an in-person visit can be made. The American Dental Association (ADA) includes synchronous and asynchronous patient care, remote patient monitoring, and mobile health. The synchronous modality uses a virtual video visit to permit a face-to-face encounter between patient and dentist. The asynchronous modality focuses on diagnosis and examination through data transfer of recorded health information, which includes videos, radiographs, and intraoral photographs. The University of California San Francisco implemented tele(oral)medicine practice for the diagnosis and management of some oral medicine conditions using synchronous and asynchronous modalities and continued its use beyond the lifting of the shelter-in-place restrictions. The role of tele(oral)medicine visits was tested based on its ability to manage pain recorded at the first telemedicine visit and comparing it to the pain recorded at the first follow-up visit. Methods A retrospective chart review of new patients seen via tele(oral)medicine between April 1, 2020 and December 22, 2020 was conducted. The video visits were done via Zoom and followed a standardized telehealth protocol. Patients were given detailed instructions on how to join the virtual visit and were asked to send any intraoral photos, biopsy results, or previous health records pertinent to their condition. Clinical data were entered into an electronic spreadsheet. In addition, Google Maps was used to calculate the distance from the patient’s home to the oral medicine clinic. Patients reported their pain level at each visit using a 0 to 10 scale, with 0 being no pain and 10 being the worst pain. Follow-up video visits also included pain scores and patients’ self-reported percentage of improvement since the previous visit. Presumptive diagnoses were made in the first visit. Results A total of 137 patients (median age 56 years) were seen. Fifty-seven percent were women, and among the 85 patients who chose to report their race/ethnicity, 82% reported they were white. In 67% of cases, the telehealth visit was covered by private medical insurance, in 23% by Medicare, in 3% by private dental insurance, and in 4% by Dentical. Sixty percent of the patients were referred by medical doctors, with 34% of the referrers being primary care physicians (Table 1 ). Twenty-six percent of the patients were self-referred. The median distance from the patients’ homes to the clinic was 65 miles, with a range from 0.9 to 100 miles.Table 1 Referring Doctors for 137 New Patients Seen Through a Tele(oral)medicine Visit from April 1 to December 22, 2020 Referring doctors N (%) Dentist 21 15 Medical doctors  Primary care physician 47 34  Otolaryngologist 17 12  Oral maxillofacial surgeon 5 4  Dermatologist 5 4  Pediatrician 3 2  Immunologist 2 1  Oncologist 2 1 Self-referred 35 26 (Courtesy of Alsafwani Z, Shiboski C, Villa A: The role of telemedicine for symptoms management in oral medicine: A retrospective observational study. BMC Oral Health 22:92, 2022.) Diagnostic Tests Thirty-seven percent of the patients needed an oral biopsy and were asked to schedule an in-person visit. Nine percent needed panoramic radiographs and 2% needed laboratory studies. Diagnosis and Pain Symptoms Forty percent of the presumptive diagnoses were reactive/inflammatory lesions and 23% were immune-mediated conditions (Table 2 ). Other diagnoses included orofacial pain disorders (13%), infections (12%), neoplasms (6%), metabolic and pre-neoplastic conditions (1%), and other (3%).Table 2 Diagnosis Category Among 137 New Patients at Their First Tele(oral)medicine Visit from April 1 to December 22, 2020 Diagnosis category N (%) Presumptive diagnosis n (%) Reactive 56 40 Fibroma, papilloma, pyogenic granu- loma: n = 37 (52%) Hypersensitivity reactions: n = 2 (3%) Other: n = 17 (30%) Autoimmune 31 23 Lichen planus: n = 14 (45%) Pemphigus/MMP: n = 3 (10%) RAS: n = 14 (45%) Orofacial Pain 18 13 Burning mouth syndrome: n = 16 (89%) TMJ: n = 1 (5.5%) Myofascial pain: n = 1 (5.5%) Infection 17 12 Oral candidiasis: n = 8 (47%) Bacterial infection: n = 1 (6%) Recurrent HSV infection: n = 2 (12%) Other: n = 6 (35%) Neoplasm 9 6 SCC: n = 3 (33%) Dysplasia: n = 6 (67%) Other 4 3 Pre-radiation Metabolic 1 1 IBD related oral ulcer Pre-neoplastic 1 1 Proliferative leukoplakia Abbreviations: SCC, Squamous cell carcinoma; IBD, inflammatory bowel disease; MMP, mucous membrane pemphigoid; RAS, recurrent aphthous stomatitis. (Courtesy of Alsafwani Z, Shiboski C, Villa A: The role of telemedicine for symptoms management in oral medicine: A retrospective observational study. BMC Oral Health 22:92, 2022.) The median pain reduction was 3 points from first video visit to first follow-up visit. The self-reported median improvement was 65%. Discussion Teledentistry provided both safe access to dental care and the delivery of needed diagnostic and management information. Advantages over in-person visits during the COVID-19 pandemic included the facilitation of public health mitigation strategies through the use of social distancing; reduced costs related to transportation; and reduced time loss for patients. Persons who were medically or social vulnerable or unable to access providers were able to receive oral health care remotely.Clinical Significance Tele(oral)medicine allows for patients to access dental care and avoid the problems associated with delaying care and having the situation progress. Patient satisfaction with video visits is high. Patients can have an initial screening for oral mucosal conditions, receive a diagnosis, and have a plan for treatment put in place. Those who live in remote regions where an oral health care specialist isn’t readily available can access the care they need. Continuing the use of tele(oral)medicine and expanding its reach have the potential to offer a well-received patient experience that can be applied in many situations besides pandemics. Alsafwani Z, Shiboski C, Villa A: The role of telemedicine for symptoms management in oral medicine: A retrospective observational study. BMC Oral Health 22:92, 2022 Reprints available from Z Alsafwani, Dept of Orofacial Sciences, School of Dentistry, Univ of California San Francisco, 513 Parnassus Ave, S-722, San Francisco, CA 94143, USA; e-mail: [email protected]
0
PMC9742983
NO-CC CODE
2022-12-14 23:42:50
no
Dent Abstr. 2022 Dec 12 November-December; 67(6):403-404
latin-1
Dent Abstr
2,022
10.1016/j.denabs.2022.09.034
oa_other
==== Front Dent Abstr Dent Abstr Dental Abstracts; a Selection of World Dental Literature 0011-8486 0011-8486 Published by Elsevier Inc S0011-8486(22)00433-2 10.1016/j.denabs.2022.09.004 The Big Picture Recommendations from International Organizations 12 12 2022 November-December 2022 12 12 2022 67 6 385386 © 2022 Published by Elsevier Inc. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. ==== Body pmcBackground Worldwide, many dental practices were either closed or had to drastically reduce dental service provision during the initial days of the COVID-19 pandemic in 2020. Within a short time, governmental and professional bodies began publishing recommendations or guidelines for reopening or restructuring the delivery of dental services. Great uncertainty surrounds the risks associated with the use of aerosol-generating procedures (AGPs) in dentistry, and recommendations for procedural and environmental mitigation of the risks were prominent. The guidelines/recommendations overall and those specific to dental AGPs were highly variable. A review was undertaken to determine how dental APGs were defined in the international dental guidelines, what mitigations were suggested, and whether these mitigations were linked to COVID-19 epidemiology. Methods The databases of Google Scholar, MEDLINE and Embase Guidelines International Network, National Institute for Health and Care Excellence, New Zealand Guidelines Group, and Canadian Agency for Drugs and Technologies in Health were searched for relevant publications. Of the 75 guidance documents from 72 countries that were identified, 32 were from Europe, 9 from Africa, 3 from North America, 10 from South America, 6 from Central America, 9 from Asia, 4 from the Middle East, 1 from Australia, and 1 from New Zealand. Results AGP Definitions and Procedures Twenty-one documents defined AGPs and 39 provided a list of AGP procedures: high-speed handpieces, 3-in-1 syringes, powered (sonic or ultrasonic) scalers, slow-speed handpieces, and surgical handpieces. Eight provided references for the AGP definitions, and 5 provided references for AGPs. Ninety-eight percent of the documents advised that AGPs can be done in patients without COVID-19 but included caveats such as restricting these procedures where possible and only using them in emergency situations. Ninety-two percent of the documents indicated that patients with suspected or confirmed COVID-19 could be treated, although several indicated treatment should be limited to dental emergencies only and most advised that the care be provided in a specialized clinic or hospital rather than a general dental practice. Only 4 documents included references related to providing AGPs for COVID-negative patients and none provided references for patients with confirmed COVID-19. Personal Protective Equipment With respect to personal protective equipment (PPD), 94% of the documents advised the wearing of face masks and most also recommended using goggles or face shields. A third of the documents recommended surgical masks for use with patients without COVID-19, with 44 countries recommending FFP2/N95 masks and 19% advising the use of FFP3 masks. Just 19 documents provided guidance for the fit testing of FFP2/3 masks. For patients without COVID-19, 67% of the countries advised using surgical gowns and 51% recommended surgical caps or hats. Twenty-one percent of the countries suggested disposable aprons and 17% supported the use of shoe covers. Five countries advised double gloving. Fifty-four percent of the documents recommended that care providers wear the same level of face mask when treating patients with COVID-19 as when treating those without COVID-19. Just 12 documents advised that the specification be upgraded when a COVID-19 patient was being treated. The recommendation for face masks was evaluated in light of the COVID-19−related deaths per 1 million population and the country’s income level according to the World Bank status. Twenty-seven percent of countries with high death rates used surgical masks as a minimum, whereas 50% of countries with medium death rates and 41% of countries with low death rates had this recommendation. No significant difference in surgical masks as a minimum was associated with whether the country had high or medium/low income levels. Procedural Mitigation The use of mouthwash before procedures to reduce bioaerosols was recommended by 82% of the documents. Recommended agents included hydrogen peroxide, povidone iodine, either of these, or cetyl pyridinium mouthwash. Rubber dam use and high-speed suction were advised in 73% of documents for patients without COVID-19. Six countries provided evidence to support the use of rubber dams and high-volume suction. Environmental Mitigation Fifty-two percent of the documents mentioned aspects of general ventilation in the dental clinic for patients without COVID-19. In most cases this was in the context of ensuring that treatment rooms were well-ventilated and included recommendations for opening exterior windows and using air conditioning. Six documents advised the use of a negative pressure room or unidirectional airflow, and 9 countries recommended the use of high-efficiency particulate air filtration devices. Just 6 of the 33 documents that provided information on general ventilation supplied references to support their recommendation. Fallow Period Forty-eight percent of the documents recommended instituting a fallow period after AGPs are provided to a patient without COVID-19. The times ranged from 2 to 180 minutes, and only 2 documents provided references to support the recommendation. Five documents suggested the fallow period be longer for patients with COVID-19 than for those without COVID-19, but 21 recommended similar durations for the two patient groups. Half of the countries with a high death rate didn’t recommend a fallow time, along with 55% of countries with medium death rates and 51% of countries with low death rates. No significant difference in fallow time recommendations was found to be related to World Bank income levels. Supportive Evidence Documents showed little consistency in the supportive evidence that they provided or didn’t provide. Twelve of the articles provided a narrative literature review, letter, or overview of the topic area with no formal assessment of research evidence. Just 2 systematic reviews were cited, with one on preprocedural mouthwashes and the other on PPE to prevent highly infectious diseases related to exposure to contaminated body fluids in health care staff. Several clinical studies were cited that evaluated the effectiveness of rubber dams, the spread of bacterial aerosol contamination during dental treatment, and the bactericidal activity of povidone iodine. The rest of the references were in vitro or simulation studies with no direct applicability to COVID-19. Discussion Recommendations varied among the documents on topics such as the definition of AGDs, procedural and environmental mitigation strategies, and fallow times. Countries showed no significant differences in the levels of recommendations for face masks or the fallow time for patients without COVID-19 in relation to COVID-19−related mortality and income levels.Clinical Significance Future guidelines need to consider the complex interactions of compliance with restrictive measures and the delivery of appropriate dental care. Little high-quality direct evidence related to dentistry is currently available but the most helpful guidelines are explicit about recommendations and incorporate as much evidence as possible. Establishing international agreements on the definition and categorization of AGP procedures would improve research and reduce confusion. Fallow period duration should be studied to determine how much time is actually necessary. In addition, dental practices would be helped by the development of technologies that can eliminate fallow times without compromising clinical treatment. Outcome measures should include the potential benefits and harms as well as the impact on service delivery and capacity. AGP information relative to PPE requirements should also be a topic of research. Robertson C, Clarkson JE, Aceves-Martins M, et al: A review of aerosol generation mitigation in international dental guidance. Int Dent J 72:203-210, 2022 Reprints available from C Robertson, Health Services Research Unit, Univ of Aberdeen, AB25 2ZD, UK; e-mail: [email protected]
0
PMC9742984
NO-CC CODE
2022-12-14 23:42:49
no
Dent Abstr. 2022 Dec 12 November-December; 67(6):385-386
utf-8
Dent Abstr
2,022
10.1016/j.denabs.2022.09.004
oa_other
==== Front Dent Abstr Dent Abstr Dental Abstracts; a Selection of World Dental Literature 0011-8486 0011-8486 Published by Elsevier Inc S0011-8486(22)00465-4 10.1016/j.denabs.2022.09.036 Inquiry Opinions Regarding Aerosol Generating Procedure Guidance 12 12 2022 November-December 2022 12 12 2022 67 6 406407 © 2022 Published by Elsevier Inc. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. ==== Body pmcBackground Most dental offices shut down in the United Kingdom in March 2020 in response to the COVID-19 pandemic. The ramifications of the pandemic for managing aerosol generating procedures (AGPs) in dental settings were of considerable concern. Requirements for their performance included the institution of a fallow time after the AGP to allow aerosols to be dispersed, the definition of how many air changes per hour (ACH) would be required, the differences between natural and mechanical ventilation, and the impact mitigations that could be instituted. In August 2020, the Chief Dental Officer of Scotland set forth conditions so that dental practices could provide a limited range of AGPs to patients in need of urgent care. A rapid review of the evidence related to the mitigation of AGPs in dentistry and the risks associated with SARS-CoV-2 transmission was done by the Scottish Dental Clinical Effectiveness Programme (SDCEP), and a questionnaire was distributed to dental professionals to obtain their thoughts regarding the provision of AGPs, their beliefs, and their concerns. Methods The dental professionals who completed the questionnaire included dentists, therapists, hygienists, and hygienist-therapists. Their responses were evaluated quantitatively and qualitatively. The qualitative responses were analyzed using qualitative content analysis. Results The respondents were asked to expand on their responses to questions regarding the mitigation currently being used and their personal views regarding AGPs and the risk of SARS-CoV-2 transmission. Of 2847 questionnaire responses, 603 (21%) included a comment for at least 1 of the expanded questions, with 318 (11%) comments dealing with mitigation and 433 (15%) comments addressing personal views about these topics. The comments were categorized into 8 main themes: AGP mitigation, fallow time and cleaning, guidance regarding aerosol mitigation, risk of transmission of SARS-CoV-2, implications of the pandemic for patient care, financial implications, mental and physical impact on dental team members, and dental professionals’ opinions on the leadership during the pandemic. AGP Mitigation Respondents reported several different mitigation approaches and expressed uncertainty about the correct use and effectiveness of the mitigation procedures. Comments addressed environmental mitigating factors such as natural and mechanical ventilation, challenges such as non-opening windows and adverse weather conditions, and an inability to calculate ACH accurately, especially with natural ventilation conditions. Respondents also mentioned the financial costs associated with installing mechanical ventilation devices and their lack of trust in external suppliers. Guidance regarding ACH calculation was characterized as inadequate. The role of air scrubbers/cleaners was uncertain, with concern over the fact that these devices weren’t considered standard operating procedure. Among the mitigations covered were the effectiveness of a rubber dam and the time constraints and patient tolerance related to it. Comments tended to be critical of pre-procedural mouthwash use, especially for pediatric patients. The responses tended to positive regarding high-volume aspiration. Fallow Time and Cleaning A clear delineation of the end point of an AGP was lacking and concerns about this uncertainty were noted. Some respondents described booking appointment lengths with the ‘worst-case scenario’ in mind. The beginning of the fallow time also seemed poorly understood. Many respondents felt the added time required for preparation before appointments and cleaning afterward was problematic. The timing of cleaning with respect to the fallow time differed, with some waiting 45 minutes into the fallow time, others 10 minutes after the fallow time began, and still others at least 20 minutes after the start of the fallow time. Guidance for determining fallow time was lacking, with some indicating that regardless of the mitigation processes implemented, 1 hour was the local advice. It was suggested that this was put in place to discourage practices from investing in measures such as mitigation devices. Guidance Regarding Aerosol Mitigation An urgent call was made to clarify AGP mitigation and to make the guidance clear and nationally accepted. Several respondents questioned the sufficiency of the evidence base for the guidance. When too many sources of information and advice were given, senior staff and dental professionals struggled to select protocols and formulate risk assessments and standard operating procedures. Some respondents suggesting using social media, reviewing professional dental forms, attending webinars and online tutorials, and talking to other dentists to clarify the situation and determine what steps are needed in the absence of a single source for advice. Risk of Transmission of SARS-CoV-2 Respondents were frustrated by what appeared to be over-regulation of the profession and preventing dental professionals from exercising their clinical judgment. It was felt that the risk of transmission of COVID-19 in the dental setting was already minimal because of the screening done and the pre-existing cross-infection control measures in place. It was pointed out that previous infectious diseases hadn’t affected dental practices disproportionately to other health care providers even when extraordinary measures weren’t in place. These comparisons also included the hospitality industry and the mitigation steps taken in restaurants and bars. Implications of the Pandemic for Patient Care Respondents expressed anxiety that patients would come to harm because dentists couldn’t carry out the routine fillings or screenings for malignant diseases because of the reduced practice capacity. This was blamed on government by 1 respondent. Frustration was expressed that patients couldn’t access definitive care and didn’t understand all the restrictions such as fallow time. Financial Implications Implementing the fallow time and reducing patient throughput were viewed as a major stumbling block to financial turnover for the dental practice. As a result, some felt that the possibility that practices would close was very real. Different funding models between private practice and National Health Service (NHS) practitioners were suggested as the source of inequities. A few felt there was a divide between NHS and private dentistry with respect to the roles of the dental professionals, since NHS had furloughed many practitioners. Financial support for the entire profession was felt to be lacking. There was also a potential for redundancies as a result of the restrictions that were imposed along with the governmental financial support plans. Costs for making practices safe were an additional financial burden. Mental and Physical Impact on Dental Team Members The pandemic was taking a toll personally and professionally on dental professionals. Respondents raised concern over staff health and safety as well as the challenges associated with working in enhanced PPE. In addition, some PPE items were out of date and could be ineffective. The emotional well-being of dental staff members, including dentists, was also a concern. Hygienists and therapists said they were undervalued and had lost paid working hours and surgery space because of the fallow time requirements. Experienced dental nurses were also seen as discontented with their current remuneration compared to nursing colleagues in hospital situations. Dentists expressed job dissatisfaction. Opinions on Leadership During the Pandemic Some respondents were frustrated or dissatisfied with the leaders of the dental profession. They complained that they received mixed messages, felt there was a lack of direction, and had lost patience with the delays in providing proper guidance. These perceived shortcomings were also the potential source of rifts between dental professionals and could trickle down to patient care. Professional bodies and other organizations were accused of leaving dental professionals to undertake their own research or rely on colleagues’ help. Some respondents reserved their criticism in the light of the unprecedented circumstances. Areas that respondents felt could be handled better included communication and the provision of guidance and support at a local level. The role of the local health boards of dentistry with respect to procedures, risks related to fallow times, and required assessments was also unclear.Clinical Significance Uncertainty and concern about how dental care should be provided and the impact of restrictions on patients and practitioners were widely expressed in the responses of dental professionals to the questionnaire. Policymakers and leaders in dentistry and health care should consider the areas that have been mentioned. Formulating plans for future problems such as pandemics should address these concerns and bring greater clarity in guidelines and consideration of the human costs involved in similar widespread challenges. Cousins M, Patel K, Araujo M, et al: A qualitative analysis of dental professionals’ beliefs and concerns about providing aerosol generating procedures early in the COVID-19 pandemic. BDJ Open 8:2, 2022 Reprints available from J Knights; e-mail: [email protected]
0
PMC9742985
NO-CC CODE
2022-12-14 23:42:50
no
Dent Abstr. 2022 Dec 12 November-December; 67(6):406-407
utf-8
Dent Abstr
2,022
10.1016/j.denabs.2022.09.036
oa_other
==== Front Dent Abstr Dent Abstr Dental Abstracts; a Selection of World Dental Literature 0011-8486 0011-8486 Published by Elsevier Inc S0011-8486(22)00430-7 10.1016/j.denabs.2022.09.001 Commentary Enhancing the Impact of Research by Telling Stories 12 12 2022 November-December 2022 12 12 2022 67 6 372373 © 2022 Published by Elsevier Inc. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. ==== Body pmcBackground Misinformation abounds in relation to fluoridation and vaccines, including the most recent COVID-19 vaccination hesitancy problem. Usually public health organizations try to counter this misinformation with facts and data-centric messages, but widely held myths tend to be persistent and not dissipated by the truth. An approach involving storytelling can engage audiences and convey facts in a way that sticks with those who listen to the tale. The characteristics of good storytelling in oral health literacy efforts and recommendations for the best way to engage in storytelling were offered. Characteristics In storytelling, a narrative describing the experiences of people as they move through several events is used to communicate truths. Stories are easier for people to understand than lists of facts, and the information tends to stay with people longer than fact-centered approaches. Improved oral health literacy is crucial to managing oral health care challenges. The use of storytelling in an oral health study may appear to contradict the “plural of anecdote is not data” tenet, but data and stories don’t have to be in opposition. Incorporating stories into scientific writing increases the audience’s willingness to base decisions on evidence. Policymakers are often the audience that researchers try to inform. A barrier to reaching them may rest in the fact that most legislators, parliaments, and other policy-making bodies never conducted research or worked in academic settings. Policy decisions are often driven by values in addition to evidence, so storytelling can make information more relevant to the values of the policymaking audience. Techniques No template exists for storytelling, and the literature offers few insights into the process, the framework, or the tenets of using this method for reporting research. Several techniques appear to be more successful than others, however. These include identifying the story elements and using them to create a compelling story; incorporating conflict, underlying or background information, and facts the data alone may not tell; adding information on attitudes that influence health decisions; and allowing there to be no resolution of the problem. Engaging stories include conflict that is identified in the opening sentences of the tale. These conflicts may involve obstacles to optimal oral health, which might include policy barriers, gaps in clinical knowledge, or cultural factors. Background information can be given to build the audience’s interest by pointing out the matters underlying the situation. Sometimes the data fail to include information, but the storytelling approach can allow it to be told. For example, a journal article about Canadians’ visits to hospital emergency rooms (ERs) for nontraumatic dental conditions included not only the cost of the visits but the wasted dollars because most patients are discharged without the underlying oral disease being addressed, leading to future visits. Today’s pandemic adds another layer of drama because these visits are made while ERs are experiencing extreme stress related to COVID-19 cases. Storytelling can incorporate the traditional structure of introduction, methods, results, and discussion. However, in each section, brief stories can be part of the presentation and convey messages about challenges that had to be overcome and limitations that exist. Issues related to health equity can benefit from having information given by the community regarding attitudes, input on study design, and the incorporation of relevant concerns. Some may benefit from the use of focus groups or informant interviews that identify what factors affect health decisions. Stories generally have a resolution of the problem, but researchers shouldn’t pretend that they have all the answers or have completely solved the problem that the story presents. Even having a null result in research can provide insights and teach lessons. Researchers can identify the mysteries that remain to be addressed by others with respect to oral disease, risk factors, or other situations. This demonstrates that science works by accumulating a body of evidence through a process of incremental building. Application Storytelling can strengthen the scientific process and enhance the public’s trust in research findings. The COVID-19 vaccine hesitancy is an example. One factor in hesitancy is related to the fears that safety was compromised by moving too quickly with the development of the vaccines. Storytelling can point out the decades of research on earlier coronaviruses that allowed researchers to learn much about these entities, their vulnerabilities, and how to exploit their weaknesses. Pointing out that several COVID-19 vaccine programs were launched within days of the publication of the virus’ genome sequence on the internet in January 2020 helps the audience see that vaccine developers had a critical head start even as the pandemic began. So a foundation of knowledge was enhanced by new knowledge, which is the standard approach for a scientific process.Clinical Significance Oral health care researchers can gain additional guidance on storytelling by consulting with the schools of communication within their academic community. Often they have graduate courses on storytelling or they may be participating in a health-related storytelling initiative. Focusing on the numbers when telling stories keeps them anchored in an evidentiary process. Jacob M: Communicating a scientific story. J Dent Res 101:371-372, 2022 Reprints not available
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==== Front Anal Chem Anal Chem ac ancham Analytical Chemistry 0003-2700 1520-6882 American Chemical Society 36459151 10.1021/acs.analchem.2c03563 Article Rapid and Sensitive Genotyping of SARS-CoV-2 Key Mutation L452R with an RPA-PfAgo Method Zhao Chenjie †⊥ Yang Lihong †⊥ Zhang Xue † Tang Yixin † Wang Yue † Shao Xiaofu † https://orcid.org/0000-0002-0151-6493 Gao Song *† https://orcid.org/0000-0003-2464-6458 Liu Xin *‡ Wang Pei *§ † Jiangsu Key Laboratory of Marine Biological Resources and Environment, Co-Innovation Center of Jiangsu Marine Bio-industry Technology, Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, School of Pharmacy, Jiangsu Ocean University, Lianyungang 222005, China ‡ Key Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China § School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing 210023, China * Email: [email protected]. * Email: [email protected]. * Email: [email protected]. 02 12 2022 13 12 2022 94 49 1715117159 15 08 2022 21 11 2022 © 2022 American Chemical Society 2022 American Chemical Society This article is made available via the PMC Open Access Subset for unrestricted RESEARCH re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. In the two years of COVID-19 pandemic, the SARS-CoV-2 variants have caused waves of infections one after another, and the pandemic is not ending. The key mutations on the S protein enable the variants with enhanced viral infectivity, immune evasion, and/or antibody neutralization resistance, bringing difficulties to epidemic prevention and control. In support of precise epidemic control and precision medicine of the virus, a fast and simple genotyping method for the key mutations of SARS-CoV-2 variants needs to be developed. By utilizing the specific recognition and cleavage property of the nuclease Argonaute from Pyrococcus furiosus (PfAgo), we developed a recombinase polymerase amplification (RPA) and PfAgo combined method for a rapid and sensitive genotyping of SARS-CoV-2 key mutation L452R. With a delicate design of the strategy, careful screening of the RPA primers and PfAgo gDNA, and optimization of the reaction, the method achieves a high sensitivity of a single copy per reaction, which is validated with the pseudovirus. This is the highest sensitivity that can be achieved theoretically and the highest sensitivity as compared to the available SARS-CoV-2 genotyping assays. Using RPA, the procedure of the method is finished within 1.5 h and only needs a minimum laboratorial support, suggesting that the method can be easily applied locally or on-site. The RPA-PfAgo method established in this study provides a strong support to the precise epidemic control and precision medicine of SARS-CoV-2 variants and can be readily developed for the simultaneous genotyping of multiple SARS-CoV-2 mutations. Priority Academic Program Development of Jiangsu Higher Education Institutions 10.13039/501100012246 NA Lianyungang City NA LYG06521202133 Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening NA HY202004 Jiangsu Higher Education Institutions of China NA 20KJA416002 document-id-old-9ac2c03563 document-id-new-14ac2c03563 ccc-price This article is made available via the ACS COVID-19 subset for unrestricted RESEARCH re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. ==== Body pmcIntroduction The COVID-19 pandemic caused by coronavirus SARS-CoV-2 has resulted in more than 490 million confirmed cases and 6.19 million deaths worldwide, and the numbers are increasing [retrieved from https://2019ncov.chinacdc.cn/2019-nCoV/global.html]. After two years, the pandemic is still not ending. Instead, a series of variants emerged, including Alpha, Beta, Delta, and Omicron, causing waves of infections one after another.1,2 The key mutations on the S protein enable the SARS-CoV-2 variants with enhanced viral infectivity, immune evasion, and/or antibody neutralization resistance, causing difficulties in epidemic prevention and control.3−5 To give some examples, variants with the L452R mutation could escape the HLA-restricted cellular immunity,6 variants with the E484K/Q mutation showed enhanced resistance to neutralizing antibodies,7,8 and the P681R mutation could indirectly enhance the invasion process.9,10 To fight against the COVID-19 pandemic in a more efficient way, a system for precise epidemic control has to be established, and precision medicine for infections of variants with different mutations should also be considered. In support of precise epidemic control and precision medicine of the virus, a rapid genotyping method for the key mutations of SARS-CoV-2 variants needs to be developed. The next-generation sequencing (NGS) has been used as the major method to identify the mutations of SARS-CoV-2 and to determine the variants.11,12 However, this method depends on NGS platforms that are not widely equipped, and the result turn-around time is relatively long. Due to the fast-spreading capacity of the virus, NGS can hardly meet the rapid response requirement of a precise epidemic control system. It is essential to develop a new genotyping method for the key mutations of the virus that is faster and simpler than NGS. Genotyping of mutations is not a new theme in molecular detection. Other than sequencing-based technologies, TaqMan probe-based qPCR is a mature technology for this kind of application.13,14 The resolution is good in general, but to achieve single-nucleotide resolution, several hundred copies of the substrate are usually required. Ligation-based detection is another widely applied genotyping technology with higher sensitivity.15−17 Application of these technologies to SARS-CoV-2 had complications because of the RNA substrate. Special designs and combinations of multiple technologies were utilized, which made the procedures laborious.18,19 Introducing special nucleases to solve the mutation genotyping problem in SARS-CoV-2 has been effective, which makes the detection logic clear and simple: (1) the target fragment of the virus genome is amplified by a nucleic acid amplification technology and (2) the mutation within the fragment is recognized specifically by the nuclease, which is activated by the recognition itself, and makes the signal-producing cleavage. For example, the nuclease Cas12a in the CRISPR system has been applied to genotyping of SARS-CoV-2 mutations successfully. By combining with isothermal amplification technologies such as LAMP or RPA, Cas12a-based assays with rapid and simple procedures have been developed.20−22 The nuclease Argonaute from Pyrococcus furiosus (PfAgo) has been applied to molecular detections recently.23,24PfAgo cuts one strand of the target DNA at a specific site upon activation by a 5′-phosphorylated complementary ssDNA, the gDNA. Once activated, the PfAgo nuclease is specific. The cleavage site is between the 10th and 11th nucleotide of the target DNA strand counting from the 5′-end of the aligned gDNA. That is to say, the specific alignment of the gDNA and the target activates the PfAgo nuclease, which in turn makes a specific cleavage on the target at a definite site.25,26 For a genotyping task aiming for single-nucleotide resolution, this property of PfAgo, i.e., specific recognition at both activation and cleavage steps, surely has an advantage. Genotyping assays for SARS-CoV-2 mutations have been developed using PfAgo, with PCR or LAMP in the amplification step.27−29 The isothermal amplification technology recombinase polymerase amplification (RPA) has advantages over PCR and LAMP in terms of convenient reaction temperature (37–42 °C), potent amplification efficiency, and good tolerance to amplification inhibitors.30,31 In this study, we developed an RPA and PfAgo combined method for rapid and sensitive genotyping of SARS-CoV-2 key mutation L452R, which was identified in Delta and Omicron BA.5 variants.32 The method successfully reached single-nucleotide resolution with a high sensitivity of 100 copies per reaction. The genotyping procedure can be finished within 1.5 h, and using RPA, the method is more suitable for the on-site environment. It provides a strong support to the precise epidemic control and precision medicine of SARS-CoV-2 variants. Moreover, because of the specific cleavage of the signal-producing molecule by PfAgo, the method can be readily developed for the simultaneous genotyping of multiple SARS-CoV-2 mutations. Experimental Section Oligonucleotide Sequences A fragment of the S gene of the SARS-CoV-2 genome (wild-type GenBank accession no. NC_045512.2) containing the L452R mutation site was selected as the genotyping target. The fragment length was limited to the 60–100 nt range for three considerations: (1) the RPA amplification needed a minimum amplicon size (usually >60 bp) to be efficient; (2) the PfAgo-based detection had two rounds of cleavages and the gDNA for the second cleavage was the first-cleavage product from the RPA amplicon; and (3) the minimum gDNA length should be 16 nt, while lengths longer than 100 nt were not suggested based on our experience. A series of RPA primers (F1-F4, forward; R0-R3, reverse) were designed following the basic principle of RPA reaction as specified in the RT-RPA Nucleic Acid Amplification Reagent (Hangzhou ZC Bio-Sci & Tech Co. Ltd., Hangzhou, China) for the amplification of the fragment (Table 1). Ten gDNA sequences for PfAgo (gDNA1-gDNA10, 16 nt in length, 5′-phosphorylated) were designed placing the mutated base “G” responsible for the L452R mutation at different positions (Table 1). The two signal-producing ssDNA molecular beacon molecules (MB1 and MB2) were designed based on the screening results of the gDNAs (see Results and Discussion), with FAM fluorophore and BHQ1 quencher modifications at the two ends (Table 1). The MB had a 16 nt loop portion to potentially align to the gDNA for the second cleavage, and 6-nt complementary sequences at the two ends to form the stem. All of the oligonucleotides in this study were synthesized by General Biology Co. Ltd., Anhui, China. Table 1 Oligonucleotide Sequences reaction name sequence (5′-3′) qPCR/RT-qPCR S Gene-Forward ACAGCAAATGGGTCGGGATCCGCTCCAGGGCAAACTGGAA S Gene-Reverse GTGGTGGTGGTGGTGCTCGAGGCAACAGGGACTTCTGTGCAG RPA F1 ATCTTGATTCTAAGGTTGGTGGTAATTATA F2 CAATCTTGATTCTAAGGTTGGTGGTAA F3 CTAACAATCTTGATTCTAAGGTTGGTGG F4 GGAATTCTAACAATCTTGATTCTAAGGT R0 AGGTTTGAGATTAGACTTCC R1 AAGGTTTGAGATTAGACTTCCTAAACA R2 CTCTCAAAAGGTTTGAGATTAGACTTC R3 CTCTCTCAAAAGGTTTGAGATTAGA PfAgo gDNA1 CGGTATAGATTGTTTA gDNA2 CCGGTATAGATTGTTT gDNA3 ACCGGTATAGATTGTT gDNA4 TACCGGTATAGATTGT gDNA5 TTACCGGTATAGATTG gDNA6 AATTACCGGTATAGAT gDNA7 TAATTACCGGTATAGA gDNA8 TATAATTACCGGTATA gDNA9 TTATAATTACCGGTAT gDNA10 ATTATAATTACCGGTA MB1 FAM-cgcaccAATTACCGGTATAGATggtgcg-BHQ1 MB2 FAM-cgcaccTAATTATAATTACCGGggtgcg-BHQ1 Expression and Purification of PfAgo The DNA sequence coding for PfAgo as reported previously23 was synthesized into a pET28b(+) vector to construct the plasmid pET28b-6 × His-PfAgo for the recombinant expression of PfAgo (Table S1 and Figure S1A). PfAgo was overexpressed in the E. coli BL21(DE3)pLysS strain and purified with Ni-affinity chromatography on an AKTA Prime Plus system (GE Healthcare Life Sciences, Boston, MA) (Figure S1B). The purified PfAgo was concentrated and stored in 20 mM Tris–HCl, pH 8.0, 300 mM NaCl, 0.5 mM MnCl2, and 15% [v/v] glycerol in small aliquots under −80 °C. The concentration was determined by SDS-PAGE (Figure S1C). Preparation of RNA Standards The L452R mutation site (T to G) is located at position 22917 nt of the SARS-CoV-2 genome. For the in vitro transcription of the RNA standards, a 638-nt fragment containing the mutation site (GenBank accession no. NC_045512.2, 22793–23430 nt) was inserted into pET28b(+) vector between the T7 promotor and T7 terminator to construct the pET28b-S gene standard plasmid by DNA synthesis and molecular cloning. By site-directed mutagenesis, the pair of wild-type and mutation standard plasmids were constructed with T or G at the L452R mutation site (Figure S2A). The in vitro transcription of the RNA standards followed the instruction of T7 High Efficiency Transcription Kit (TransGen Biotech Co. Ltd., Beijing, China), using the standard plasmids as the templates. After the in vitro transcription, the RNA standards were purified by phenol–chloroform extraction, dissolved in DEPC water, and stored in small aliquots under −80 °C. The standard plasmids were quantified by a Qubit 4 fluorometer (ThermoFisher Scientific Inc, Wilmington, DE, USA), and the copy numbers were calculated based on their size (5971 bp). A qPCR standard curve was determined on the relationship of the copy number and the Ct value using the serially diluted standard plasmid (Figure S2B). This standard curve was used to determine the copy numbers of the RNA standards using RT-qPCR assays. The primers (S Gene-Forward and S Gene-Reverse) used for qPCR and RT-qPCR reactions in this section are listed in Table 1. The molecular biology reagents used in this section were obtained from Vazyme Biotech Co. Ltd., Nanjing, China, unless specified otherwise. PCR and Basic RPA PCR and basic RPA were used for the screening of the RPA primers. The 20 μL PCR mixture contained 10 μL of 2X Taq Master Mix (Vazyme Biotech Co. Ltd.), 1 μL of each forward and reverse primer (10 μM), and 1 μL of the plasmid standard as the template. The basic RPA procedure followed the instruction of RPA Nucleic Acid Amplification Reagent (Hangzhou ZC Bio-Sci & Tech Co. Ltd.). The 50 μL reaction mixture was prepared by adding 25 μL of A Buffer, 13.5 μL of deionized water, 2 μL of each forward and reverse primer (10 μM), 5 μL of the plasmid standard as the template, and 2.5 μL of B Buffer to the lyophilized enzyme pellet. The RPA reactions were conducted at 37 °C for 30 min. The amplification products were analyzed by native-PAGE (15%, 0.5X TBE). RT-RPA The reverse transcription (RT)-RPA reactions were carried out according to the instruction of RT-RPA Nucleic Acid Amplification Reagent (Hangzhou ZC Bio-Sci & Tech Co. Ltd.). The 50 μL reaction contained the lyophilized enzyme pellet, 40.5 μL of A Buffer, 2 μL of each forward and reverse primer (10 μM), 3 μL of the RNA template, and 2.5 μL of B Buffer. The RT-RPA reactions were conducted at 42 °C for 30 min. PfAgo Cleavage The 20 μL PfAgo reaction mixture contained 1.5 μM PfAgo and 2 μM gDNA in 20 mM HEPES, pH 7.5, 250 mM NaCl, and 0.5 mM MnCl2 (all concentrations final). Up to 5 μL of the column-purified amplification product was added and the reaction was incubated at 95 °C for 45 min. Up to 5 μL of the reaction mixture was analyzed by urea-PAGE (15%, 0.5X TBE). For fluorescence detection, 0.5 μM (final) of the signal-producing ssDNA molecular beacon was added to the 20 μL PfAgo reaction mixture in addition to the above-mentioned components, and the reaction was conducted on a Roche LightCycler 480 II qPCR machine (Basel, Switzerland) for 45 min at 95 °C with the FAM fluorescence signal recorded in 2 min intervals. SARS-CoV-2-MT-B.1.617 Pseudovirus The SARS-CoV-2-MT-B.1.617 pseudovirus (with the L452R mutation) was purchased from Fubio Biological Technology Co. Ltd., Shanghai, China. The viral RNA was extracted using TIANamp Virus RNA Kit (Tiangen Biotech Co Ltd., Beijing, China). Sample Simulation The throat swab samples were collected from the consent-informed healthy persons following the protocol specified in the COVID-19 Pneumonia Prevention and Control Plan (9th edition, China CDC). Two virus storage solutions (Jiangsu Kaiyuan Kangda Medical Instrument Co. Ltd., Yancheng, China; and Beyotime Biotechnology Co. Ltd., Shanghai, China) were used to make the throat swab samples in this study. The genomic DNA of two common respiratory tract pathogens, Pseudomonas aeruginosa (ATCC 9027) and Staphylococcus aureus (ATCC 25923), were preserved in the laboratory. The N gene fragments of MERS-CoV (GenBank accession no. NC_019843.3) and SARS-CoV (NC_004718.3) and the N and ORF1ab gene fragments of SARS-CoV-2 (NC_045512.2) were synthesized in the plasmids with the pET28b(+) background by General Biology Co. Ltd. The bacterial or plasmid DNA were spiked into the throat swab samples to make the simulated samples. DNA was extracted from the simulated samples for testing. Three additional SARS-CoV-2 pseudovirus containing wild-type S gene and mutations L452Q and L452M were provided by Fubio Biological Technology Co. Ltd. The pseudoviruses were spiked into the throat swab samples to make the simulated samples. RNA was extracted using TIANamp Virus RNA Kit for testing. Results and Discussion Principle of the RPA-PfAgo Method To fully utilize PfAgo’s specific recognition and cleavage property to achieve highly sensitive genotyping of the L452R mutation, a delicate procedure was designed (Scheme 1A). A fragment of the viral RNA of the size of 60–100 nt is exponentially amplified with RT-RPA. The amplified fragment (dsDNA, RPA amplicon) contains the T or G base corresponding to the L452R mutation, i.e., “T” in the wild-type (WT) L452 fragment and “G” in the mutant (MT) R452 fragment. To guide the specific recognition of PfAgo to the mutant “G”, the 16 nt, 5′-phosphorylated gDNA is designed to share the fragment sequence with the mutant “G” in the middle. With the guide of the gDNA, PfAgo can specifically cleave the strand of the amplified MT fragment that is complementary to the gDNA sequence (the first cleavage). This cleavage produces another ssDNA fragment with 5′-phosphorylation (g’), which serves as the gDNA to guide PfAgo to make the second cleavage. The substrate of the second cleavage is the signal-producing ssDNA molecular beacon molecule (MB). MB forms a hairpin structure in which the FAM fluorophore and BHQ1 quencher are in proximity. The 16 nt loop portion of MB is designed to be complementary to g’ and has the mutant “G” in the sequence. The specific cleavage of MB by PfAgo releases FAM from BHQ1, producing the fluorescence signal. For the amplified WT fragment, because there is no strand that is complementary to the gDNA, the first cleavage cannot happen, and there is no fluorescence signal. For a better illustration of the principle, exemplary sequences of the amplified fragments, the gDNA, the second cleavage gDNA g’, and the signal-producing molecule MB are presented in Scheme 1B. The exemplary sequences are determined in this study (see below). Please refer to the Experimental Section for detailed considerations of the sequences. With this design, the RPA-PfAgo method utilizes the specific recognition and cleavage property of PfAgo in both first and second cleavages. Because in both cleavages, specific recognition is taking place, this strategy has an additional layer of specificity assurance as compared to the CRISPR-based assays.33 This design should bring a good sensitivity to the mutant “G” of the SARS-CoV-2 L452R mutation with a single-nucleotide resolution. Scheme 1 Schematic of the RPA-PfAgo Method (A) The diagram of the method procedure. The T or G base corresponding to the L452R mutation and the bases complementary to them are indicated. MB: molecular beacon. g’: the newly generated gDNA for the second cleavage. F and Q: fluorophore and quencher. (B) Exemplary sequences in the PfAgo cleavage. The sequences are designed and determined in this study. The red arrows indicate the PfAgo cleavage positions. P: phosphorylation. Screening of RPA Primers for Efficient and Specific Amplification Amplification of the desired fragment of the viral genome is the fundamental step of the RPA-PfAgo method. Accurate and specific amplification of a fragment containing the mutation site with good efficiency is an essential requirement to achieve good sensitivity. To facilitate efficient cleavage of PfAgo in the subsequent step, the RPA primers were designed following two principles: (1) the RPA primers should be designed based on the rules of RPA reaction; (2) the RPA amplicons should be 60–100 bp in length so that the 5′-phosphorylated ssDNA fragment produced from the first cleavage (g’) would not be too long to serve as a gDNA for the second cleavage. The 12 combinations of the 4 forward and 4 reverse primers (Table 1) designed to meet these principles, namely, F1R1, F2R0, F2R1, F2R2, F2R3, F3R0, F3R1, F3R2, F3R3, F4R0, F4R1, and F4R2, were screened for better amplification efficiency by PCR (Figure 1A). The three combinations with better amplification efficiency, F3R1, F3R2, and F3R3, were further screened by basic RPA (Figure 1B). The combination F3R3 had a good RPA amplification, while the other two produced nonspecific amplification bands. Thus, F3 and R3 with good amplification efficiency and specificity were selected as the RPA primers for the RPA-PfAgo method. Figure 1 Screening of the RPA primers. (A) Preliminary primer screening by PCR. The amplification products of the 12 primer combinations were analyzed on a PAGE gel. (B) Primer screening by RPA. The amplification products of the 3 primer combinations with better performance in the PCR screening were analyzed on a PAGE gel. Sizes of selected marker bands are indicated. gDNA Screening for Specific Identification of Mutation L452R gDNA is the key factor in the PfAgo cleavage system in that it guides the specific recognition of a particular sequence (in the case of this study, a sequence containing the mutant “G”) in the target by PfAgo, which in turn activates the nuclease. To accurately genotype the L452R mutation, the gDNA should be able to distinguish the “G” or “T” single-nucleotide difference of the target sequence and guide an efficient PfAgo cleavage. Ten 5′-phosphorylated gDNAs were designed to identify the mutant sequence of the RPA amplicon (Table 1 and Figure 2A). To screen for the best gDNA, the 10 gDNAs were tested for the activation of PfAgo cleavage on the purified RPA amplicons of the wild-type (WT) and the L452R mutant (MT). In each cleavage reaction, 150 ng of the purified amplicon was used. The best gDNA should have an obvious cleavage on the L452R mutant fragment but no cleavage at all on the wild-type fragment. The results showed that gDNA1 and gDNA7 could guide complete cleavage on the mutant fragment. On the PAGE gel, the band corresponding to the 87 bp mutant fragment was digested to near complete in the case of gDNA1 or gDNA7 (Figure 2B). Meanwhile, gDNA1 and gDNA7 could keep the wild-type fragment intact (Figure 2C). Two signal-producing ssDNA molecular beacon molecules, MB1 and MB2, were designed based on the sequences of gDNA1 and gDNA7 and the corresponding cleavage products, respectively (Table 1), and were tested for fluorescence signals upon PfAgo cleavage. Using gDNA1, the reactions with the L452R mutant (MT) fragment produced a much higher fluorescence signal than using gDNA7, and the reactions with the wild-type (WT) fragment produced no signal (Figure 2D,E). A possible reason could be that the g’-fragment produced in the gDNA7-guided first cleavage had a low efficiency to guide the second cleavage. The results suggested that gDNA1 (with the corresponding MB1) was the best gDNA to be used for the specific identification of mutation L452R. Figure 2 gDNA screening. (A) Design of ten 5′-phosphorylated gDNAs (gDNA1–10). The relationship of the 10 gDNA sequences with the target sequences is shown. The G base corresponding to the L452R mutation and the related bases in the target sequences are colored in red. (B) and (C) gDNA screening with the mutant (B) and the wild-type (C) fragments as the cleavage targets. The cleavage reactions with different gDNAs were analyzed on urea-PAGE gels. (D) and (E) gDNA screening with the fluorescence molecular beacon. The fluorescence curves (D) and end-point fluorescence signals (E) of reactions with different gDNAs and different target fragments are shown. The error bars represent the standard errors of three parallel repeats. Optimization of the RPA-PfAgo Reaction To improve the overall performance of the RPA-PfAgo reaction, the concentrations of PfAgo and gDNA in the reaction mixture were optimized. Five different PfAgo concentrations from 0 to 2 μM were tested, and fluorescence signals were observed. The best PfAgo concentration was determined to be 1.5 μM final (Figure S3A). Similarly, five different gDNA concentrations from 0 to 8 μM were tested, and 2 μM final was determined to be the optimal gDNA concentration (Figure S3B). Sensitivity of the RPA-PfAgo Method To explore the sensitivity of the RPA-PfAgo method, 104, 102, 101, and 100 copies of the RNA standards of SARS-CoV-2 mutant (MT) and wild-type (WT) were tested. According to the fluorescence signals, with as low as 100 copies of the SARS-CoV-2 mutant (MT) RNA, the L452R mutation could be identified (Figure 3). The single-copy sensitivity is the highest sensitivity that can be achieved theoretically, and is also the highest sensitivity as compared to the available SARS-CoV-2 genotyping assays.34−36 According to the reports, the nucleic acid amplification and probe-based assays had sensitivities in the range of tens to hundreds of copies per reaction.37−39 The CRISPR-based assays had sensitivities of around 10 copies per reaction.21,40 By fully utilizing PfAgo’s specific recognition and cleavage property, the RPA-PfAgo method exhibited a solid advantage in terms of sensitivity with which a single copy could be sufficient for the mutation identification (Figure 3). The single-copy sensitivity is the highest sensitivity that can be achieved theoretically and is also the highest sensitivity as compared to the available SARS-CoV-2. Figure 3 Sensitivity of the RPA-PfAgo method. The RNA standards of SARS-CoV-2 mutant (MT) and wild-type (WT) were used in the reactions. The fluorescence curves (A) and the end-point fluorescence signals (B) of reactions with different template amounts are shown. The fluorescence curves represent a typical result of three independent experiments. The error bars represent the standard errors of three parallel repeats. The sensitivity was further confirmed with the SARS-CoV-2-MT-B.1.617 pseudovirus containing the L452R mutation. RNA of the pseudovirus was extracted and the gene copy number was determined by RT-qPCR. With 104, 102, 101, or 100 copies of the viral RNA, the L452R mutation could be identified successfully without exception, which confirmed the single-copy sensitivity of the method (Figure 4). In addition, the FAM signals could be clearly observed with a blue-light view (Figure 4C), which was a simpler way of result reading. Figure 4 Sensitivity confirmation with SARS-CoV-2 pseudovirus. The fluorescence curves (A), end-point fluorescence signals (B), and end-point visualized image under blue-light view (C) of reactions with different amounts of RNA extracted from the SARS-CoV-2 pseudovirus are shown. The error bars represent the standard errors of three parallel repeats. ****P < 0.001. Validation of the RPA-PfAgo Method with Simulated Samples Since clinical SARS-CoV-2 samples from infected patients are strictly controlled, this study has used simulated throat swab samples for the validation of the RPA-PfAgo method. First, the cross-reactivity with other targets was tested with simulated throat swab samples containing the genomic DNA of P. aeruginosa and S. aureus, the N gene fragments of MERS-CoV, SARS-CoV, and SARS-CoV-2, and the ORF1ab gene fragment of SARS-CoV-2. The standard plasmid containing the SARS-CoV-2 S gene fragment with the L452R mutation was used as the positive control. Only the positive control produced a fluorescence signal, suggesting that the method had no cross-reactivity with other targets (Figure 5A). Figure 5 Validation with simulated samples. (A) Cross-reactivity with other targets. The fluorescence curves of different targets extracted from simulated throat swab samples (solution: Jiangsu Kaiyuan Kangda Medical Instrument Co. Ltd.) were shown. The DNA were normalized to 20 ng/μL after extraction for testing. The curves represent a typical result of three independent experiments. (B) End-point fluorescence signals of simulated throat swab samples (solution: Jiangsu Kaiyuan Kangda Medical Instrument Co. Ltd.) with pseudovirus of different mutations at site 452. Two pseudovirus amounts were tested. The error bars represent the standard errors of three parallel repeats. (C) Fluorescence curves showing test results of simulated throat swab samples with two different solutions. Solution 1: Jiangsu Kaiyuan Kangda Medical Instrument Co. Ltd.; Solution 2: Beyotime Biotechnology Co. Ltd. The simulated samples were the R452 mutant or the L452 wild-type pseudovirus. The curves represent a typical result of three independent experiments. Second, the single-nucleotide resolution was validated with simulated throat swab samples of SARS-CoV-2 pseudovirus containing different mutations at site 452 of the S gene, namely, R452 (the target of this study), Q452 (BA.2.12.1), and M452 (BA.2.9.1 and BA.2.13). The wild-type L452 was also included. The results showed that only R452 had a distinct fluorescence signal, suggesting the method could accurately respond to the L452R mutation (Figure 5B). Finally, we tested the compatibility of this method with two different virus storage solutions that had been used for COVID-19 clinical sample collections in China. With both solutions, the identification of pseudovirus with the L452R mutation was clear (Figure 5C). We again confirmed the sensitivity to be the single copy for the simulated samples made with the two solutions. These validations suggest that the RPA-PfAgo method should be effective for real-life clinical samples. Advantages of the RPA-PfAgo Method The RPA-PfAgo method has achieved the single-copy sensitivity for genotyping the L452R mutation of SARS-CoV-2, which is advantageous over all of the other available SARS-CoV-2 genotyping assays as discussed above. An important feature of this method is its convenience. The amplification step uses RT-RPA that conducts isothermally at 42 °C; the temperature of the PfAgo cleavage is 95 °C. A precise thermal cycling equipment is not required. The method only needs minimum laboratorial support, such as some pipettors, a portable spin, a heat block, and a blue-light source. The whole procedure of the method can be finished within 1.5 h. Because the PfAgo enzyme is thermostable and the RPA reagent is lyophilized, the reagents used in this method do not require cold-chain transport and storage. The RPA-PfAgo method is a rapid and sensitive genotyping method for SARS-CoV-2 that can be easily applied locally or on-site. Another advantage of the RPA-PfAgo method is that it can be developed for the simultaneous genotyping of multiple SARS-CoV-2 mutations. Identification of multiple key mutations in an integrated assay should have great value for precise epidemic control. Because of the specific cleavage on the substrates by PfAgo, it is possible to assemble a one-pot assay with a panel of signal-producing molecules containing different sequences targeting different mutations. The signals can be distinguished using different fluorophores or other means. An assay with a “one-pot RPA amplification, one-pot PfAgo cleavage, and multiple signals” strategy can be developed on the basis of the RPA-PfAgo method established in this study. Conclusions This study established an RPA-PfAgo method for genotyping of SARS-CoV-2 key mutation L452R. The method utilizes PfAgo’s specific recognition and cleavage property and achieves a high sensitivity of a single copy per reaction, which is the highest sensitivity that can be achieved theoretically and the highest sensitivity as compared to the available SARS-CoV-2 genotyping assays.40−42 The procedure of the method is finished within 1.5 h and only needs minimum laboratorial support, suggesting that the method can be easily applied locally or on-site. It provides a strong support to the precise epidemic control and precision medicine of SARS-CoV-2 variants and can be readily developed for the simultaneous genotyping of multiple SARS-CoV-2 mutations. Supporting Information Available The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.analchem.2c03563.Sequence of the expression cassette of PfAgo in plasmid pET28b-6 × His-PfAgo; expression and purification of PfAgo; construction of the standard plasmids for SARS-CoV-2 wild-type and L452R mutation fragments; and optimization of the RPA-PfAgo reaction (PDF) Supplementary Material ac2c03563_si_001.pdf Author Contributions ⊥ C.Z. and L.Y. contributed equally to this work. The authors declare no competing financial interest. Acknowledgments This study was supported by grants from the China Postdoctoral Science Foundation (No. 2022M721665), the Key Natural Science Research Project of the Jiangsu Higher Education Institutions of China (No. 20KJA416002), the Jiangsu Funding Program for Excellent Postdoctoral Talent of China (No. 2022ZB358), the Research Program of “521 Project” of Lianyungang City of China (No. LYG06521202133), the Open-end Funds of Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening (No. HY202004), the “Blue Project” of Jiangsu Higher Education Institutions of China, and the Priority Academic Program Development of Jiangsu Higher Education Institutions of China. ==== Refs References Alkhatib M. ; Svicher V. ; Salpini R. ; Ambrosio F. A. ; Bellocchi M. C. ; Carioti L. ; Piermatteo L. ; Scutari R. ; Costa G. ; Artese A. ; Alcaro S. ; Shafer R. ; Ceccherini-Silberstein F. SARS-CoV-2 Variants and Their Relevant Mutational Profiles: Update Summer 2021. Microbiol. Spectrum 2021, 9 , e0109621 10.1128/Spectrum.01096-21. Kandeel M. ; Mohamed M. E. M. ; Abd El-Lateef H. M. ; Venugopala K. N. ; El-Beltagi H. S. Omicron Variant Genome Evolution and Phylogenetics. J. Med. Virol. 2022, 94 , 1627–1632. 10.1002/jmv.27515.34888894 Alaofi A. L. ; Shahid M. Mutations of SARS-CoV-2 RBD May Alter Its Molecular Structure to Improve Its Infection Efficiency. Biomolecules 2021, 11 , 1273 10.3390/biom11091273.34572486 Cosar B. ; Karagulleoglu Z. Y. ; Unal S. ; Ince A. T. ; Uncuoglu D. B. ; Tuncer G. ; Kilinc B. R. ; Ozkan Y. E. ; Ozkoc H. C. ; Demir I. N. ; Atak I. N. ; Mendi A. H. ; Bengi V. U. ; Seval G. C. ; Altuntas E. G. ; Kilic P. ; Demir-Dora D. Cytokine. SARS-CoV-2 Mutations and their Viral Variants. Cytokine Growth Factor Rev. 2022, 63 , 10–22. 10.1016/j.cytogfr.2021.06.001.34580015 Liu H. ; Wei P. ; Kappler J. W. ; Marrack P. ; Zhang G. SARS-CoV-2 Variants of Concern and Variants of Interest Receptor Binding Domain Mutations and Virus Infectivity. Front. Immunol. 2022, 13 , 825256 10.3389/fimmu.2022.825256.35154144 Motozono C. ; Toyoda M. ; Zahradnik J. ; Saito A. ; Nasser H. ; Tan T. S. ; Ngare I. ; Kimura I. ; Uriu K. ; Kosugi Y. ; Yue Y. ; Shimizu R. ; Ito J. ; Torii S. ; Yonekawa A. ; Shimono N. ; Nagasaki Y. ; Minami R. ; Toya T. ; Sekiya N. ; Fukuhara T. ; Matsuura T. ; Schreiber G. ; Consortium G. P. G2P-Japan. ; Ikeda T. ; Nakagawa S. ; Ueno T. ; Sato K. SARS-CoV-2 Spike L452R Variant Evades Cellular Immunity and Increases Infectivity. Cell Host Microbe 2021, 29 , 1124–1136.e11. 10.1016/j.chom.2021.06.006.34171266 Jangra S. ; Ye C. ; Rathnasinghe R. ; Stadlbauer D. ; Krammer F. ; Simon V. ; Martinez-Sobrido L. ; García-Sastre A. ; Schotsaert M. ; et al. SARS-CoV-2 Spike E484K Mutation Reduces Antibody Neutralisation. Lancet Microbe 2021, 2 , e283–e284. 10.1016/S2666-5247(21)00068-9.33846703 Zhang Y. ; Wei Y. ; Yang S. ; Li Y. ; Wang J. ; Nie Z. ; Bi Y. ; Liu W. ; Wang L. ; Yang L. Rapid and Accurate Identification of SARS-CoV-2 Variants Containing E484 Mutation. Innovation 2022, 3 , 100183 10.1016/j.xinn.2021.100183.34778856 Liu Y. ; Liu J. ; Johnson B. A. ; Xia H. ; Ku Z. ; Schindewolf C. ; Widen S. G. ; An Z. ; Weaver S. C. ; Menachery V. D. ; Xie X. ; Shi P. Delta Spike P681R Mutation Enhances SARS-CoV-2 Fitness over Alpha Variant. Cell Rep. 2022, 39 , 110829 10.1016/j.celrep.2022.110829.35550680 Saito A. ; Irie T. ; Suzuki R. ; Maemura T. ; Nasser H. ; Uriu K. ; Kosugi Y. ; Shirakawa K. ; Sadamasu K. ; Kimura I. ; Ito J. ; Wu J. ; Iwatsuki-Horimoto K. ; Ito M. ; Yamayoshi S. ; Loeber S. ; Tsuda M. ; Wang L. ; Ozono S. ; Butlertanaka E. ; Tanaka Y. ; Shimizu R. ; Shimizu K. ; Yoshimatsu K. ; Kawabata R. ; Sakaguchi T. ; Tokunaga K. ; Yoshida I. ; Asakura H. ; Nagashima M. ; Kazuma Y. ; Nomura R. ; Horisawa Y. ; Yoshimura K. ; Takaori-Kondo A. ; Imai M. ; Tanaka S. ; Nakagawa S. ; Ikeda T. ; Fukuhara T. ; Kawaoka Y. ; Sato K. ; et al. Enhanced Fusogenicity and Pathogenicity of SARS-CoV-2 Delta P681R Mutation. Nature 2022, 602 , 300–306. 10.1038/s41586-021-04266-9.34823256 Allen R. A. ; Williams C. L. ; Penrod Y. ; McCloskey C. ; Carpenter-Azevedo K. ; Huard R. C. ; King E. ; Terence Dunn S. A Pyrosequencing Protocol for Rapid Identification of SARS-CoV-2 Variants. J. Med. Virol. 2022, 94 , 3661–3668. 10.1002/jmv.27770.35416308 Singh L. ; San J. E. ; Tegally H. ; Brzoska P. M. ; Anyaneji U. J. ; Wilkinson E. ; Clark L. ; Giandhari J. ; Pillay S. ; Lessells R. J. ; Martin D. P. ; Furtado M. ; Kiran A. M. ; Oliveira Targeted Sanger Sequencing to Recover Key Mutations in SARS-CoV-2 Variant Genome Assemblies Produced by Next-Generation Sequencing. Microb. Genomes 2022, 8 , 1124–1136.e11. 10.1099/mgen.0.000774. Campsall P. A. ; Au N. H. ; Prendiville J. S. ; Speert D. P. ; Tan R. ; Thomas E. E. Detection and Genotyping of Varicella-Zoster Virus by TaqMan Allelic Discrimination Real-time PCR. J. Clin. Microbiol. 2004, 42 , 1409–1413. 10.1128/JCM.42.4.1409-1413.2004.15070981 Zhong L. ; Xie Y. Z. ; Cao T. T. ; Wang Z. ; Wang T. ; Li X. ; Shen R. C. ; Xu H. ; Bu G. ; Chen X. F. A Rapid and Cost-Effective Method for Genotyping Apolipoprotein E Gene Polymorphism. Mol. Neurodegener. 2016, 11 , 2 10.1186/s13024-016-0069-4.26754117 Gibriel A. A. ; Adel O. Advances in Ligase Chain Reaction and Ligation-Based Amplifications for Genotyping Assays: Detection and Applications. Res., Rev. Mutat. Res. 2017, 773 , 66–90. 10.1016/j.mrrev.2017.05.001. Park J. H. ; Jang H. ; Jung Y. K. ; Jung Y. L. ; Shin I. ; Cho D. Y. ; Park H. G. A Mass Spectrometry-Based Multiplex SNP Genotyping by Utilizing Allele-Specific Ligation and Strand Displacement Amplification. Biosens. Bioelectron. 2017, 91 , 122–127. 10.1016/j.bios.2016.10.065.28012317 Zhang W. ; Liu K. ; Zhang P. ; Cheng W. ; Zhang Y. ; Li L. ; Yu Z. ; Chen M. ; Chen L. ; Li L. ; Zhang X. All-In-One Approaches for Rapid and Highly Specific Quantifcation of Single Nucleotide Polymorphisms Based on Ligase Detection Reaction Using Molecular Beacons as Turn-On Probes. Talanta 2021, 224 , 121717 10.1016/j.talanta.2020.121717.33378999 Ding S. ; Chen R. ; Chen G. ; Li M. ; Wang J. ; Zou J. ; Du F. ; Dong J. ; Cui X. ; Huang X. ; Deng Y. ; Tang Z. One-Step Colorimetric Genotyping of Single Nucleotide Polymorphism Using Probe-Enhanced Loop-Mediated Isothermal Amplification (PE-LAMP). Theranostics 2019, 9 , 3723–3731. 10.7150/thno.33980.31281509 Liu Y. ; Lei T. ; Liu Z. ; Kuang Y. ; Lyu J. ; Wang Q. A Novel Technique to Detect EGFR Mutations in Lung Cancer. Int. J. Mol. Sci. 2016, 17 , 792 10.3390/ijms17050792.27223277 Lin H. ; Liang Y. ; Zou L. ; Li B. ; Zhao J. ; Wang H. ; Sun J. ; Deng X. ; Tang S. Combination of Isothermal Recombinase-Aided Amplification and CRISPR-Cas12a-Mediated Assay for Rapid Detection of Major Severe Acute Respiratory Syndrome Coronavirus 2 Variants of Concern. Front. Microbiol. 2022, 13 , 945133 10.3389/fmicb.2022.945133.35836420 Zhang T. ; Zhao W. ; Zhao W. ; Si Y. ; Chen N. ; Chen X. ; Zhang X. ; Fan L. ; Sui G. Universally Stable and Precise CRISPR-LAMP Detection Platform for Precise Multiple Respiratory Tract Virus Diagnosis Including Mutant SARS-CoV-2 Spike N501Y. Anal. Chem. 2021, 93 , 16184–16193. 10.1021/acs.analchem.1c04065.34818890 Zhang Y. ; Xi H. ; Juhas M. Biosensing Detection of the SARS-CoV-2 D614G Mutation. Trends Genet. 2021, 37 , 299–302. 10.1016/j.tig.2020.12.004.33402270 He R. ; Wang L. ; Wang F. ; Li W. ; Liu Y. ; Li A. ; Wang Y. ; Mao W. ; Zhai C. ; Ma L. Pyrococcus Furiosus Argonaute-Mediated Nucleic Acid Detection. Chem. Commun. 2019, 55 , 13219–13222. 10.1039/C9CC07339F. Liu Q. ; Guo X. ; Xun G. ; Li Z. ; Chong Y. ; Yang L. ; Wang H. ; Zhang F. ; Luo S. ; Cui L. ; Zhao P. ; Ye X. ; Xu H. ; Lu H. ; Li X. ; Deng Z. ; Li K. ; Feng Y. Argonaute Integrated Single-Tube PCR System Enables Supersensitive Detection of Rare Mutations. Nucleic Acids Res. 2021, 49 , e75 10.1093/nar/gkab274.33905513 Enghiad B. ; Zhao H. Programmable DNA-Guided Artificial Restriction Enzymes. ACS Synth. Biol. 2017, 6 , 752–757. 10.1021/acssynbio.6b00324.28165224 Swarts D. C. ; Hegge J. W. ; Hinojo I. ; Shiimori M. ; Ellis M. A. ; Dumrongkulraksa J. ; Terns R. M. ; Terns M. P. ; van der Oost J. Argonaute of the Archaeon Pyrococcus Furiosus is a DNA-Guided Nuclease that Targets Cognate DNA. Nucleic Acids Res. 2015, 43 , 5120–5129. 10.1093/nar/gkv415.25925567 He R. ; Wang L. ; Wang F. ; Yang J. ; Yu X. ; Wang Y. ; Liu Z. ; Li C. ; Ma L. Combination of Ultrashort PCR and Pyrococcus Furiosus Argonaute for DNA Detection. Analyst. 2021, 147 , 35–39. 10.1039/D1AN01521D.34881761 Wang F. ; Yang J. ; He R. ; Yu X. ; Chen S. ; Liu Y. ; Wang L. ; Li A. ; Liu L. ; Zhai C. ; Ma L. PfAgo-Based Detection of SARS-CoV-2. Biosens. Bioelectron. 2021, 177 , 112932 10.1016/j.bios.2020.112932.33429204 Ye X. ; Zhou H. ; Guo X. ; Liu D. ; Li Z. ; Sun J. ; Huang J. ; Liu T. ; Zhao P. ; Xu H. ; Li K. ; Zhao W. ; Liu Q. ; Xu S. ; Feng Y. ; et al. Argonaute-Integrated Isothermal Amplification for Rapid, Portable, Multiplex Detection of SARS-CoV-2 and Influenza Viruses. Biosens. Bioelectron. 2022, 207 , 114169 10.1016/j.bios.2022.114169.35334329 Lobato I. M. ; O’Sullivan C. K. Recombinase Polymerase Amplification: Basics, Applications and Recent Advances. TrAC, Trends Anal. Chem. 2018, 98 , 19–35. 10.1016/j.trac.2017.10.015. Piepenburg O. ; Williams C. H. ; Stemple D. L. ; Armes N. A. DNA Detection Using Recombination Proteins. PLoS Biol. 2006, 4 , e204 10.1371/journal.pbio.0040204.16756388 Tegally H. ; Moir M. ; Everatt J. ; Giovanetti M. ; Scheepers C. ; Wilkinson E. ; Subramoney K. ; Makatini Z. ; Moyo S. ; Amoako D. G. ; Baxter C. ; Althaus C. L. ; Anyaneji U. J. ; Kekana D. ; Viana R. ; Giandhari J. ; Lessells R. J. ; Maponga T. ; Maruapula D. ; Choga W. ; Matshaba M. ; Mbulawa M. B. ; Msomi N. ; Con-sortium N. ; Naidoo Y. ; Pillay S. ; Sanko T. J. ; San J. E. ; Scott L. ; Singh L. ; Magini N. A. ; Smith-Lawrence P. ; Stevens W. ; Dor G. ; Tshiabuila D. ; Wolter N. ; Preiser W. ; Treurnicht F. K. ; Venter M. ; Georginah C. ; McIntyre C. ; O’Toole A. ; Ruis C. ; Peacock ; T P. ; Roemer C. ; Pond S. L. K. ; Williamson C. ; Pybus O. G. ; Jinal N. ; Bhiman J. N. ; Glass A. ; Martin D. P. ; Jackson B. ; Rambaut A. ; Laguda-Akingba O. ; Gaseitsiwe S. ; Gottberg A. V. ; Oliveira T. D. ; et al. Emergence of SARS-CoV-2 Omicron Lineages BA.4 and BA.5 in South Africa. Nat. Med. 2022, 28 , 1785–1790. 10.1038/s41591-022-01911-2.35760080 Xun G. ; Lane S. T. ; Petrov V. A. ; Pepa B. E. ; Zhao H. A rapid, accurate, scalable, and portable testing system for COVID-19 diagnosis. Nat. Commun. 2021, 12 , 2905 10.1038/s41467-021-23185-x.34006857 Gomez-Martinez J. ; Henry S. ; Tuaillon E. ; Van de Perre P. ; Fournier-Wirth C. ; Foulongne V. ; Bres J. C. Novel Lateral Flow-Based Assay for Simple and Visual Detection of SARS-CoV-2 Mutations. Front. Cell. Infect. Microbiol. 2022, 12 , 902914 10.3389/fcimb.2022.902914.35909973 Huang X. ; Zhang F. ; Zhu K. ; Lin W. ; Ma W. dsmCRISPR: Dual synthetic mismatches CRISPR/Cas12a-based detection of SARS-CoV-2 D614G mutation. Virus Res. 2021, 304 , 198530 10.1016/j.virusres.2021.198530.34363850 Iijima T. ; Ando S. ; Kanamori D. ; Kuroda K. ; Nomura T. ; Tisi L. ; Kilgore P. E. ; Percy N. ; Kohase H. ; Hayakawa S. ; Seki M. ; Hoshino T. Detection of SARS-CoV-2 and the L452R Spike Mutation Using Reverse Transcription Loop-Mediated Isothermal Amplification Plus Bioluminescent Assay in Real-Time (RT-LAMP-BART). PLoS One 2022, 17 , e0265748 10.1371/journal.pone.0265748.35312732 Wang Y. ; Zhang Y. ; Chen J. ; Wang M. ; Zhang T. ; Luo W. ; Li Y. ; Wu Y. ; Zeng B. ; Zhang K. ; Deng R. ; Li W. Detection of SARS-CoV-2 and Its Mutated Variants via CRISPR-Cas13-Based Transcription Amplification. Anal. Chem. 2021, 93 , 3393–3402. 10.1021/acs.analchem.0c04303.33511840 Yang J. ; Hu X. ; Wang W. ; Yang Y. ; Zhang X. ; Fang W. ; Zhang L. ; Li S. ; Gu B. RT-LAMP Assay for Rapid Detection of the R203M Mutation in SARS-CoV-2 Delta Variant. Emerging Microbes Infect. 2022, 11 , 978–987. 10.1080/22221751.2022.2054368. Zhang T. ; Deng R. ; Wang Y. ; Wu C. ; Zhang K. ; Wang C. ; Gong N. ; Ledesma-Amaro R. ; Teng X. ; Yang C. ; Xue T. ; Zhang Y. ; Hu Y. ; He Q. ; Li W. ; Li J. A Paper-Based Assay for the Colorimetric Detection of SARS-CoV-2 Variants at Single-Nucleotide Resolution. Nat. Biomed. Eng. 2022, 6 , 957–967. 10.1038/s41551-022-00907-0.35835993 Meng Q. ; Wang X. ; Wang Y. ; Dang L. ; Liu X. ; Ma X. ; Chi T. ; Wang X. ; Zhao Q. ; Yang G. ; Liu M. ; Huang X. ; Ma P. Detection of the SARS-CoV-2 D614G Mutation Using Engineered Cas12a Guide RNA. Biotechnol. J. 2021, 16 , e2100040 10.1002/biot.202100040.33595922 Banada P. ; Green R. ; Banik S. ; Chopoorian A. ; Streck D. ; Jones R. ; Chakravorty S. ; Alland D. A Simple Reverse Transcriptase PCR Melting-Temperature Assay To Rapidly Screen for Widely Circulating SARS-CoV-2 Variants. J. Clin. Microbiol. 2021, 59 , e0084521 10.1128/JCM.00845-21.34288729 He C. ; Lin C. ; Mo G. ; Xi B. ; Li A. A. ; Huang D. ; Wan Y. ; Chen F. ; Liang Y. ; Zuo Q. ; Xu W. ; Feng D. ; Zhang G. ; Han L. ; Ke C. ; Du H. ; Huang L. Rapid and Accurate Detection of SARS-CoV-2 Mutations Using a Cas12a-Based Sensing Platform. Biosens. Bioelectron. 2022, 198 , 113857 10.1016/j.bios.2021.113857.34894625
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==== Front Diabetologie Die Diabetologie 2731-7447 2731-7455 Springer Medizin Heidelberg 981 10.1007/s11428-022-00981-7 Leitthema Schulungskonzepte mithilfe von Telemedizin in der pädiatrischen Diabetologie Training concepts with telemedicine in pediatric diabetologyBiester Sarah [email protected] Klusmeier Britta [email protected] Kinder- und Jugendkrankenhaus AUF DER BULT, Janusz-Korczak-Allee 12, 30173 Hannover, Deutschland 12 12 2022 16 11 11 2022 © The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Aufgrund der hohen Technologisierung der Behandlung des Diabetes mellitus Typ 1 konnte während der Coronapandemie die ambulante Versorgung mithilfe von Videosprechstunden sichergestellt werden. Die zunehmenden Erfahrungen der Familien, E‑Learning im Schul- oder Berufsalltag umzusetzen, und die geschaffenen Strukturen in Praxen und Kliniken, telemedizinische Kontakte durchzuführen, ließ die Entwicklung unterschiedlicher Schulungskonzepte in der pädiatrischen Diabetologie voranschreiten. Deren Einsatz ist vielfältig und individuell, und beinhaltet z. B. zusätzliche Betreuungspersonen an einer Präsenzschulung teilnehmen zu lassen, bei akuten Fragestellungen der Eltern durch die Datenanalyse gemeinsam eine zeitnahe Bearbeitung zu schaffen oder weite Fahrtstrecken für die Durchführung einer Beratung zu vermeiden. Wichtig bei der Durchführung sind eine strukturierte Vorbereitung mit allen notwendigen Hilfsmitteln, ein ruhiger Arbeitsplatz und das Einkalkulieren des möglichen Auftretens technischer Probleme auf beiden Seiten. Eine Back-up-Kontaktaufnahme mit dem Telefon ist hilfreich. Telemedizinische Schulungskonzepte in der Diabetesberatung bedeuten eine neue spannende Erfahrung und ergänzen die Betreuung der gesamten Familie mit einem Kind oder Jugendlichen mit Diabetes mellitus und sollten auch in Zukunft genutzt und ausgebaut werden. The high level of technologization in the treatment of type 1 diabetes mellitus made it possible to provide outpatient care during the coronavirus pandemic with the help of video consultations. The increasing experience of families’ e‑learning in school or professional life and the structures created in practices and clinics to provide telemedical consultations has allowed the continued development of different training concepts in pediatric diabetology. The use is diverse and individual, such as having additional caregivers participate in a face-to-face training sessions, to jointly perform timely processing in the case of acute questions from parents through data analysis, or to avoid long travel distances to attend a consultation. Important for implementation is a structured approach with all necessary tools, a quiet workplace, and the expectation of the possible occurrence of technical problems on both sides. Backup contact by telephone is helpful. Telemedicine training concepts in diabetes counselling is a new exciting experience and complements the care of the entire family with a child or adolescent with diabetes mellitus and should be used and expanded in the future. Schlüsselwörter Diabetes, Beratung Insulin, automatische Dosierung Videoschulung Ambulante Versorgung Typ-1-Diabetes Keywords Diabetes counseling Insulin, automated delivery Video education Ambulatory care Type 1 diabetes ==== Body pmcEinleitung Mit dem GKV-Versorgungsstrukturgesetz (GKV: gesetzliche Krankenversicherung) wurde festgelegt, dass auch Kontakte mit Patienten*innen telemedizinisch stattfinden können, wobei Telemedizin einen Kontakt zum Erkrankten durch Einsatz audiovisueller Kommunikationstechnologien trotz räumlicher Trennung bedeutet (bundesregierung.de). Während der coronabedingten Kontaktbeschränkungen stellte sich heraus, dass über diese Kontaktform verschiedene Themen der Diabetesberatung mit den Familien, Kindern und Jugendlichen besprochen werden können. In diesem Rahmen entstanden im Diabeteszentrum des Kinder- und Jugendkrankenhauses AUF DER BULT, in Orientierung an bestehenden Leitlinien und Schulungsprogrammen, unterschiedliche Schulungskonzepte mit Telemedizin. Schulungskonzepte in der pädiatrischen Diabetologie Diabetes mellitus Typ 1 bei Kindern und Jugendlichen bedeutet immer, die ganze Familie zu sehen und gemeinsam einen Weg aufzuzeigen, damit die Diagnose mit Zuversicht und Kraft verarbeitet werden kann. Behandlungsleitlinien sind Orientierungshilfen und können dem interdisziplinären Team Struktur geben und eine evidenzbasierte Behandlung der Kinder und Jugendlichen sicherstellen. Die Schulung der Familien, Kinder und Jugendlichen findet curricular mithilfe evaluierter Schulungsprogramme statt. Kinder im Alter von 6–12 Jahren erfahren die Inhalte und das Behandlungskonzept mit Hilfe des Diabetesbuch für Kinder und dessen Protagonisten Jan. Schritt für Schritt werden sie und ihre Familien im stationären Setting an die Therapie herangeführt. Das Behandlungs- und Schulungsprogramm für Jugendliche mit Diabetes mellitus besteht aus 4 Heften. Der Basisteil ermöglicht eine strukturierte Schulung bei Diagnosestellung, während die 3 Erweiterungen verschiedene Themen behandeln, die während der Entwicklung zwischen dem 12. und 18. Lebensjahr auftreten können und dann besprochen werden. Beide Schulungskonzepte beinhalten einen Lese- bzw. Vorleseanteil mit anschließenden Fragen am Ende. In der Beratung können anhand deren Beantwortung Inhalte nochmals wiederholt werden, und sie dienen als Überprüfung, ob das Besprochene und Gelesene verstanden wurden. Die initiale Schulung sollte weiterhin persönlich stattfinden Die initiale Schulung sollte sicherlich weiterhin persönlich stattfinden, um eine sofortige Verständigung für die Inhalten zu erhalten und den hohen praktischen Anteil, der zur Behandlung gehört, zu üben. Jedoch ist gerade die Therapie des Diabetes mellitus Typ 1 mittlerweile hoch technologisiert – durch automatische Insulinpumpensysteme, Glukosesensoren, digitale Pens und viele Apps, die Unterstützung bei der Ermittlung der Kohlenhydrate oder dem Errechnen der korrekten Insulinmenge bieten können. Die Technologien ermöglichen, dass die Therapie elektronisch sichtbar wird, was eine gute Voraussetzung ist, um telemedizinisch beraten und die Behandlung optimieren zu können. Veränderungen der Schulungsform im Lockdown Aufgrund der Coronapandemie musste innerhalb kürzester Zeit eine Lösung für die ambulante Behandlung chronisch Erkrankter gefunden werden. Persönliche Kontakte waren nicht möglich, aber die Entwicklung der Kinder und die damit verbundenen Anpassungen der Insulindosis fanden weiter statt. Mithilfe sicherer Arzt‑/Patientenportale konnte eine Videokonsultation stattfinden. Hierfür waren und sind verschiedene Vorbereitungen notwendig, auf die weiter unten eingegangen wird. Während der Zeit des Lockdowns konnten die telemedizinischen Konsultationen nach Erfüllen bestimmter Voraussetzungen abgerechnet werden. Zum jetzigen Zeitpunkt ist das jedoch nicht mehr ohne Beschränkungen möglich. Viele Familien und Jugendlichen wünschen jedoch weiterhin die Option einer Videosprechstunde, und auch die Einschränkungen der räumlichen Möglichkeiten mit ausreichend Abstand in den Praxis- oder Klinikräumlichkeiten führen dazu, dass die Telemedizin ein wichtiger Bestandteil in der Behandlung und Unterstützung von Familien mit einem Kind mit Diabetes mellitus Typ 1 ist. Zusätzlich ist es wichtig, die erlangte Kompetenz und die Ausarbeitung der Konzepte im Diabetesteam nicht zu verlieren, sondern zu stärken und zu verbessern. Neben den pandemiebedingten Einschränkungen der Versorgung im ambulanten Bereich gab es im stationären Setting Vorschriften über die Anzahl der Begleitpersonen bei einer Aufnahme. Damit nicht nur 1 Elternteil die Schulung erhalten konnte, wurde das andere Elternteil via Video dazugeschaltet. In derartigen Fällen dient die Telemedizin als ergänzendes Tool. Nachdem die Möglichkeit der Kontaktaufnahme per Video beim Diabetesteam und bei den Familien viel positive Resonanz fand und die Kontaktbeschränkungen bei Schulungen von Gruppen in Schulen, Kindergärten oder vulnerablen Gruppen (Großeltern) fortlaufend bestanden, kristallisierten sich weitere Ideen für telemedizinische Schulungskonzepte heraus. Verschiedene Möglichkeiten hierfür sind in der Infobox dargestellt. Infobox Telemedizinische Möglichkeiten in der pädiatrischen Diabetesberatung Ein Elternteil kann nicht anwesend sein und wird zur Schulung per Video dazugeschaltet. Glukosekurven werden ausgewertet und erörtert; eine Insulinanpassung kann besprochen werden. Individuelle Themen können behandelt werden, wie:Schulung der AID-Funktion (AID: automatische Insulindosierung), Klassenfahrt, Verhalten bei Alkoholkonsum, Wiederholung von Schulungsinhalten: Vermeidung einer diabetischen Ketoazidose, Verhalten bei Krankheit, Vorbereitung bei Sport. Insulinpumpen können vorgestellt werden. Informationen für Erzieher*innen, Lehrer*innen, Schul- oder Kindergartenassistenz, Großeltern können bereitgestellt und vermittelt werden. Notwendige Voraussetzungen für Telemedizin Um eine erfolgreiche telemedizinische Beratung bzw. Schulung durchzuführen, sind folgende Voraussetzungen notwendig: Familie und Patient*in Ein Computer mit Monitor oder ein Laptop müssen vorhanden sein. Das Smartphone ist meist nicht ausreichend, da das Display zu klein ist, um Präsentationen lesen oder Berichte zur Datenanalyse gut einsehen zu können. Eine stabile Internetverbindung wird benötigt. Familien und Patient*in müssen das Auslesen aller notwendigen Diabetesgeräte (Insulinpumpe, BZ-Messgerät [BZ: Blutzucker], Glukosesensoren) beherrschen. Der persönliche Account ist mit der Klinik/Praxis verbunden, sodass die Daten einsehbar sind. Die Umgebung zu Hause sollte möglichst ruhig sein, damit die Kommunikation nicht durch Geräusche beeinflusst wird. Die Telefonnummer der Diabetesberatung muss griffbereit sein, um bei Ton- oder Internetstörungen bzw. Unterbrechungen schnell Kontakt aufnehmen zu können. Diabetesberater*in Ein ruhiger Raum mit Tür stellt sicher, dass sensible Daten nicht von Anderen zu hören sind. Es wird ein sicheres Arzt‑/Patientenportal benötigt. Ein stabiles Internet ist Voraussetzung. Optimal sind 2 verstellbare Monitore mit Kamera. Die Sitzposition sollte vorher getestet werden, damit die zugeschaltete Person die Anwesenden auch sehen kann. An alle Teilnehmenden sollten elektronische Einladungen versendet werden. Es muss ausreichende Vor- und Nachbereitungszeit eingeplant werden. Notwendige Materialien sollten bereitgelegt werden, damit man nicht aufstehen muss und aus dem Sichtbereich verschwindet. Es sollten Präsentationen zum Thema aufgerufen werden (eigene Erstellung zu den Themen möglich, bei gerätespezifischen Schulungen den Hersteller um Unterstützung bitten). Schriftliches Schulungsmaterial sollte der eingeladenen Person vorher zugesandt werden. Die Telefonnummer der Patient*in sollte griffbereit sein. Vor der ersten Durchführung empfiehlt sich ein Testlauf mit Kolleg*innen, um die Ansicht, die Dauer, bis die Verbindung aufgebaut ist, und den Ton zu prüfen. Durchführung einer Hybridschulung Es kann verschiedene Gründe geben, warum ein Elternteil möglicherweise nicht mit an der Schulung vor Ort teilnehmen kann: Betreuung von Geschwisterkindern, Quarantäne, weite Distanz zur Klinik und keine Möglichkeit, täglich zu pendeln, Patchworkfamilien. Da die Schulungskapazität in der Diabetesberatung begrenzt ist und doppelte Schulungen kaum machbar sind, ist es hilfreich, weitere Personen, die das Kind oder den Jugendlichen begleiten, mit einzuladen (Abb. 1). Natürlich können praktische Aspekte nur vor Ort geübt werden, jedoch sind die gesprochenen Inhalte für beide Parteien identisch.Zu Beginn der Beratung sollte darauf hingewiesen werden, dass die Personen, die vor Ort sind, als Hauptansprechpartner*in gelten. Das ist wichtig, damit die Diabetesberatung nicht immer zwischen Bildschirm und anwesenden Personen hin und her schauen muss. Die Konzentration liegt bei den betroffenen Kindern und Jugendlichen und der anwesenden Betreuungsperson vor Ort. Verständnisfragen können sofort gestellt werden, sodass nicht ein Elternteil dem anderen die Inhalte übermitteln muss. Gerade in Situationen der Erstschulung bei Manifestation sind die Aufnahmekapazitäten der Eltern durch die schockierende Diagnose oft begrenzt. Schriftliches Schulungsmaterial kann vorab per E‑Mail zugesandt werden. Praktische Übungen (z. B. Vorbereitung und Injektion mit dem Pen) werden vor Ort geübt und mittels der Videokonsultation beobachtet. Beratung bei akuten Problemen Bei der Schulung zur Datenanalyse bei akuten Problemen, wie z. B. hyperglykämischen Phasen oder wiederholten hypoglykämischen Episoden, handelt es sich meistens um einen ungeplanten Kontakt. Der Betroffene oder dessen Eltern nehmen Kontakt per Telefon oder E‑Mail mit dem Krankenhaus bzw. der Praxis auf und erbitten Hilfe. Auch in solchen Fällen sind eine Vorbereitung und ein strukturiertes Vorgehen wichtig. Um eine konkrete Bearbeitung zu gewährleisten, sollten folgende Punkte vorab durch den Betroffenen/dessen Eltern mitgeteilt werden:Name und Geburtsdatum des Patienten, Informationen zur Diabetestherapie, ob ein Datenupload erfolgte und wenn ja, über welche Software, konkrete Fragestellung. Die Diabetesberatung kann dann eine Kontaktaufnahme vorschlagen, und eine Videokonsultation mit elektronischer Einladung kann erfolgen. Bei technischen Problemen mit den Systemen oder beim Hochladen der Daten wird konsequent auf die Hotline der zuständigen Firmen verwiesen. Der Diabetesberater*in evaluiert vor der Kontaktaufnahme die hochgeladenen Daten/das Problem. Zu Beginn derselben besprechen dann beide Parteien die zu analysierenden Daten, um konkret das Problem herauszustellen. Während des telemedizinischen Kontaktes sollte mit der Familie und ggf. dem Patient*in zusammen die Lösung erarbeitet werden, damit es ein Verständnis für die mögliche Änderung im Insulintherapieplan gibt und in Zukunft vielleicht selbstständige Anpassungen durchgeführt werden können. Das gemeinsame Besprechen der Berichte kann auch simple Änderungen, wie z. B. die Bolusabgabe vor dem Essen, verständlicher machen und so zu einer Verbesserung führen. Gerade in der Pädiatrie ist es notwendig, den Familien die Möglichkeit zur kurzfristigen Kontaktaufnahme zu geben, da bei Kindern immense Veränderungen im Insulinbedarf möglich sind, wenn Entwicklungssprünge stattfinden. Die reguläre Kontrolle der Entwicklung und die Überprüfung der Stoffwechseleinstellung mittels HbA1c (Glykohämoglobin) finden allerdings weiterhin zu den regelmäßigen Ambulanzbesuchen statt. Vorteile solcher akuter Schulungen sind eine schnelle Kontaktaufnahme und Bearbeitung der Fragestellung. Sie geben den Familien Sicherheit, gerade in der ersten Zeit zu Hause nach der Diagnose. Probleme werden zeitnah bearbeitet und nicht vergessen, wenn der Ambulanzkontakt möglicherweise erst in einigen Wochen stattfindet. Akute Stoffwechselveränderungen und mögliche Komplikationen werden erkannt und verhindert. Vorteile akuter Videoschulungen sind die schnelle Kontaktaufnahme und rasche Behandlung des Problems Als Nachteil kann sich ergeben, dass die Familien ständig eine Rückversicherung einfordern und „kurz eine E‑Mail schreiben“. Die Bearbeitung der dann entstehenden Menge der Anfragen ist sehr zeitaufwendig und stört den regulären Ablauf. Schulung der Systeme zur automatischen Insulindosierung (AID) Die zunehmende Technologisierung der Diabetestherapie bringt neue Themen mit sich:Was ist eine Software zum Auslesen der Geräte? Wie setzte ich den Upload der Insulinpumpe um? Was mache ich mit den Informationen? Es müssen erst einige Tage vergehen, damit AID-Systeme Daten zu Verfügung stellen, die eine Auswertung möglich machen. Weiterhin können einige dieser Systeme erst nach einer sog. Aufwärmphase die automatische Abgabe starten. Die Charakteristika der AID-Funktion können sehr gut in einem telemedizinischen Kontakt geschult werden (Abb. 2). Diesem muss eine technische Einweisung in das Insulinpumpensystem mit Glukosesensor vor Ort vorausgegangen sein. Je nach Voraussetzungen der Familie mit dem Kind findet diese mehrere Tage stationär, teilstationär oder ambulant statt. Beim telemedizinischen Termin werden zuerst die hochgeladenen Daten zusammen angesehen und besprochen. Anhand dieser Informationen können Veränderungen einzelner Parameter festgelegt und Fragen gestellt werden, wie die Familie und das Kind/der Jugendliche mit dem System im Alltag zurechtgekommen sind. Die Schulung zur AID-Funktion kann durch eine Präsentation unterstützt werden, die von den Herstellern zur Verfügung gestellt werden sollte. Solche Präsentationen geben einen strukturierten Ablauf vor, und alle Details der Funktionen werden besprochen. Wenn die AID-Funktion dann gestartet wird, kann die Pumpe zur Überprüfung in die Kamera halten werden. Nach Ende des Kontakts werden die Daten der Insulinpumpe erneut hochgeladen, und alle besprochenen Veränderungen können durch den Diabetesberater*in kontrolliert werden. Diese Art von Schulungsmodulen hat sich in letzter Zeit bewährt. Für die Familien entstehen keine Anfahrtszeiten in die Klinik. Das Üben des Uploads und das Analysieren der Daten mittels elektronischer Berichterstattung werden erlernt. Der Diabetesberater*in erklärt die einzelnen Inhalte der Software und welche sinnvoll sind, um die Therapie zu überprüfen. Die Erfahrung, auf diese Weise Kontakt mit dem Diabetesteam aufnehmen zu können, schafft für die Familien Sicherheit. Beratung zu individuellen Themen Eine weitere Möglichkeit, den telemedizinischen Kontakt zu nutzen, sind Schulungen zu individuellen Themen, wie z. B. Klassenfahrt, Zeitverschiebung bei Fernreisen, Aktivurlaub, Ketoazidose. Hierbei ist es sinnvoll, Merkblätter mit allen wichtigen Informationen zu dem jeweiligen Thema zu erstellen. Diese können als Tool individuell eingesetzt werden. Sie werden während der telemedizinischen Schulung gezeigt bzw. der Familie vorab per E‑Mail zugesandt. Das ist die Basis, um speziell auf die Bedürfnisse des Erkrankten eingehen und Fragen bearbeiten zu können. Werden Einstellungen in der Insulinpumpe verändert, können diese durch das Hochladen der Systemdaten in die jeweilige Datenbank kontrolliert werden. Vorstellung von Insulinpumpensystemen Durch die Weiterentwicklung der Technologien im Bereich Diabetes sind Modelle von Insulinpumpen und Glukosesensoren für Kinder/Jugendliche von unterschiedlichen Herstellern auf dem Markt verfügbar. Um die Kinder und Jugendlichen und deren Eltern bei der Entscheidung für ein System zu unterstützen, können diese an einer Schulung zu Insulinpumpen teilnehmen. Im ersten Teil derselben wird die allgemeine Handhabung der Insulinpumpe und des Glukosesensors erklärt. Dabei wird auf die Funktionsweise der Insulinpumpe, des AID-Systems, das Tragen des Katheters und den Nutzen im Alltag eingegangen. Im weiteren Verlauf der Schulung werden den Kindern und Jugendlichen und deren Eltern die Schritte der Beantragung und das Vorgehen zur Anlage des Insulinpumpensystems erklärt. Im letzten Teil wird auf die einzelnen Insulinpumpenmodelle eingegangen. Hierbei werden jedes Modell einzeln vorgestellt und die unterschiedlichen Funktionen erklärt. Für welches Modell sich das Kind bzw. der Jugendliche entscheidet, ist individuell. Bei der Schulung zur Insulinpumpenvorstellung kann man 2 Gruppen unterscheiden: Gruppen mit bestehender CSII-Therapie (CSII: kontinuierliche subkutane lnsulininfusion) und mit ICT (intensivierte konventionelle Insulintherapie) Behandelte. Es empfiehlt sich, diese beiden Gruppen getrennt zu schulen, da das Wissen über die CSII-Therapie sehr unterschiedlich ist. Die Schulung kann dabei einzeln oder in einer Gruppe stattfinden. Grundlegende Informationen zur Insulinpumpentherapie werden in einer Präsentation bereitgestellt Alle grundlegenden Informationen der Insulinpumpentherapie und die verschiedenen Pumpenmodelle werden in einer Präsentation bereitgestellt. Viele Bilder schaffen die Möglichkeit, dass sich die Familie und das Kind oder der Jugendliche die Systeme besser vorstellen können. Auch hier kann wieder auf Informationsmaterial der jeweiligen Hersteller zurückgegriffen werden. Zusätzlichen können Demonstrationspumpen in die Kamera gehalten bzw. eine Dokumentenkamera verwendet werden. Hierbei können Vergleichsobjekte, z. B. ein 2‑€-Stück, verwendet werden, um die Größen der Katheter zu veranschaulichen. Auch der Hinweis auf entsprechende Internetseiten und Apps der Hersteller ist hilfreich. Mit diesem Vorgehen können die Größe und das Aussehen eines Infusionssets besser vorgestellt werden. Dieses Schulungskonzept setzte sich jedoch nicht durch, sodass die Vorstellungen meistens wieder vor Ort durchgeführt werden. Als großen Nachteil gaben die Kinder und Jugendlichen mit ihren Familien an, dass das Anfassen der Modelle („Pumpe mal in die Hosentasche stecken“) und das Legen eines Katheters zur Entscheidungsfindung notwendig sind. Schulung von Betreuungspersonen Teilhabe ist gerade für Kinder und Jugendliche mit Typ-1-Diabetes besonders wichtig. Der Besuch eines Kindergartens, das Training im Sportverein sowie der Schulbesuch mit voller Konzentration auf die Inhalte des Unterrichts sollten hier im Vordergrund stehen. Damit die Kinder in der Therapie unterstützt werden bzw. diese im Notfall von den Erzieher*innen, Lehrer*innen, Trainer*innen und Schul- oder Kindergartenassistenz übernommen werden kann, sind eine Information und Schulung notwendig. Neben Schulungen vor Ort in den Einrichtungen oder mit Einzelpersonen in der Klinik erwies sich auch hier eine telemedizinische Möglichkeit als sehr hilfreich. Fast alle Berufsgruppen haben in der Phase des Lockdowns Besprechungen und Informationsveranstaltungen als Webinare kennengelernt und können sich so auch eine Fortbildung zum Thema Diabetes gut vorstellen. Außerdem ist es ein enormer zeitlicher Gewinn auf Seiten der Diabetesberatung, weil die z. T. weit entfernten Einrichtungen nicht persönlich besucht werden müssen. Zur Vorbereitung erstellt die Diabetesberatung eine Präsentation mit folgenden Inhalten.Diabetes mellitus Typ 1 und Unterschied zum Typ 2 Insulintherapie mit dem Pen oder einer Pumpe Glukosesensoren Ernährung Unter- und Überzuckerung Während der Schulzeit: handeln, unterstützen, begleiten Diese Präsentation dient als Struktur. Um eine lebhafte Beratung zu ermöglichen, sollten Fragen immer zugelassen sein. Besonders wichtig ist die Individualisierung der Präsentation. Im Vorfeld sollten die Therapie des Kindes und die Art des Glukosesensors betrachtet werden, um dann in der Schulung entsprechende Bilder und Bespiele zeigen zu können. Grundfolien zu den allgemeinen Themen sind immer gleich, aber die Bilder der Insulinpumpe, des Pens, des Sensors usw. können ausgetauscht werden. Wichtig ist auch, die Maßeinheit der Glukose (mg/dl oder mmol/l) vorab zu klären und auf die Folien zu übernehmen. Mittlerweile entstanden auf diese Weise viele Präsentationen mit allen Kombinationen, und jeder Kolleg*in hat Zugang dazu. Wenn alle Teilnehmer*innen anwesend sind, werden Regeln, wie z. B. Ton an oder aus, besprochen, um Störungen durch Umgebungsgeräusche zu minimieren. Fazit für die Praxis Telemedizin ist eine sehr gute ergänzende Möglichkeit, Familien mit Kindern und Jugendlichen mit Typ-1-Diabetes zu beraten. Bestimmte strukturelle Voraussetzungen sind notwendig, um Telemedizin durchführen zu können. Telemedizin ist ein ergänzendes Tool in der ambulanten und stationären Diabetesberatung. Schulungsmaterialien müssen in elektronischer Form vorhanden sein, erstellt oder von den Herstellern bereitgestellt werden. Die Möglichkeit, telemedizinische Beratungen zu erhalten, sollte allen Familien und deren Kinder und Jugendlichen zur Verfügung stehen. Einhaltung ethischer Richtlinien Interessenkonflikt S. Biester und B. Klusmeier geben an, dass kein Interessenkonflikt besteht. Für diesen Beitrag wurden von den Autorinnen keine Studien an Menschen oder Tieren durchgeführt. Für die aufgeführten Studien gelten die jeweils dort angegebenen ethischen Richtlinien. QR-Code scannen & Beitrag online lesen
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==== Front Sleep Vigil Sleep Vigil Sleep and Vigilance 2510-2265 Springer Nature Singapore Singapore 221 10.1007/s41782-022-00221-4 Correspondence Sleep is Vital for Brain and Heart: Post COVID-19 Assessment by World Health Organization and the American Heart Association http://orcid.org/0000-0002-2253-2644 Gulia Kamalesh K. [email protected] 1 http://orcid.org/0000-0002-8477-6679 Kumar Velayudhan Mohan [email protected] 2 1 grid.416257.3 0000 0001 0682 4092 Division of Sleep Research, Department of Applied Biology, Biomedical Technology Wing, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala 695012 India 2 Kerala Chapter, National Academy of Medical Sciences (India), New Delhi, India 12 12 2022 12 22 8 2022 17 10 2022 1 12 2022 © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. ==== Body pmcIn the absence of a clear line of treatment strategy, COVID-19 outbreak, during the initial months, had evoked humongous fear, anxiety and sufferings among people all over the world. Now, after more than two years, the attention is on post COVID-19 challenges for the mental health of all age groups across the globe. COVID-19 related mental health issues are not only due to the battered global economy, and loss of jobs in several organized and unorganized sectors, but also due to the loss of family members and friends, and living without social contacts for a long time. Anxiety about unknown threats to health in future, and exposure to virus by the children born during this period are worrying factors amongst the general population. Though mental health was given due importance by the World Health Organization (WHO) even before the pandemic [1], the post-pandemic emphasis given to it by this world organization is very timely [2]. Dr Tedros Adhanom Ghebreyesus, Director-General of the WHO, during the launch of World Mental Health Report—Transforming Health for All on 17 June 2022, quoted that there is no health without mental health [2]. This report has recognized that sleep loss is a potential risk factor for mental health issues. This report emphasizes on the transformation of our attitudes, actions and approaches to promote and protect mental health, to achieve the global objectives that are set out in the WHO Comprehensive mental health action plan 2013–2030 [3]. In this light, the management of sleep disturbances by locally available traditional practices and medicines is a viable and affordable option [4–7]. Even though the health of any individual is affected by disruption of sleep, women during pregnancy, shift workers, growing children and aging population are definitely more vulnerable [7–12]. It is very well documented now that chronic sleep loss lead to hypertension, metabolic disorders, obesity, insulin resistance, cardiovascular diseases, cognitive impairments, increased risk of cancer and finally overall deterioration in health and quality of life [13–15]. Sleep loss during pregnancy is shown to affect not only the health of the mother but also the development of the unborn child, which is a matter of serious concern. Anxiety and depression account for one third of the mental health disease burden. Thus, there is a dire need for sleep education for common people and healthcare providers. In the modern era, the competitive lifestyle is also posing a challenge to proper sleep. More recently, the American Heart Association has added sleep to cardiovascular health checklist [16]. The body can be maintained in a healthy state only if the vital organs like brain and heart get regular optimal sleep each day throughout life. COVID-19 pandemic has given rise to a growing realization about the importance of sleep for overall health in both developing and developed nations. It is necessary for developing countries with a huge population like India to focus on awareness programs on the importance of sleep. This can be considered as a preventive measure to deal with non-communicable diseases that definitely create a humongous burden on healthcare expenditure. Of course, a wide range of actions at the national level, including the alleviation of poverty and reduction of inequalities and discrimination, can also have positive benefits for mental health and sleep. Prevention of war and violent conflict, promoting access to employment, health care, housing, and education are also factors to be given due importance [17]. There is a global need to pay attention to sleep for a healthy body and mind. Data availability This statement is a suggestion based on this article, thus no data is required. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. WHO, Fundacao Calouste Gulbenkian Foundation. Social determinants of mental health. Geneva: World Health Organization; 2014. https://apps.who.int/iris/bitstream/handle/10665/112828/9789241506809_eng.pdf 2. World Mental Health Report: Transforming Mental Health for All. Geneva: World Health Organization; 2022. Licence: CC BY-NC-SA 3.0 IGO., ISBN 978–92–4–004933–8 (electronic version); ISBN 978–92–4–004934–5 (print version) https://www.who.int/news-room/events/detail/2022/06/17/default-calendar/launch-of-new-who-mental-health-report--transforming-mental-health-for-all 3. WHO, Comprehensive Mental Health Action plan 2013–2030. ISBN 978–92–4–003102–9 (electronic version); ISBN 978–92–4–003103–6 (print version), WHO 2021 4. Gulia KK Kumar VM Sleep Medicine in Ayurveda Sleep Med Rev 2016 25 131 10.1016/j.smrv.2015.02.006 26140863 5. Gulia KK, Radhakrishnan A, Kumar VM. Approach to Sleep Disorders in the Traditional School of Indian Medicine: Alternative Medicine II. In: Sleep Disorders Medicine: Basic Science, Technical Considerations and Clinical Aspects. (4th Edition) Chapter 57, 2017 ISBN 978–1–4939–6578–6, 1221–1232. 6. Gulia KK Sreedharan SE Yogic sleep and walking protocol induced improvement in sleep and wellbeing in postmenopausal subject: a longitudinal case study during COVID lockdown Sleep Vigilance 2021 10.1007/s41782-021-00180-2 7. Gulia KK Aswathy BS Kumar VM David G Leila K-G Developmental aspects of sleep Chapter 10 Pediatric Sleep Medicine 2021 Berlin Published by © Springer Nature 8. Radhakrishnan A Aswathy BS Kumar VM Gulia KK Sleep deprivation during late pregnancy produces hyperactivity and increased risk-taking behaviour in offspring Brain Res 2015 1596 88 98 10.1016/j.brainres.2014.11.021 25446439 9. Aswathy BS Kumar VM Gulia KK Immature sleep pattern in newborn rats when dams encountered sleep restriction during pregnancy Int J Dev Neurosci 2018 69 60 67 10.1016/j.ijdevneu.2018.06.007 29959981 10. Gulia KK Kumar VM Sleep disorders in the elderly: a growing challenge Psychogeriatrics 2018 18 155 165 10.1111/psyg.12319 29878472 11. Arango C Dragioti E Solmi M Cortese S Domschke K Murray RM Risk and protective factors for mental disorders beyond genetics: an evidence-based atlas World Psychiatry 2021 20 417 436 10.1002/wps.20894 34505386 12. Pires GN Benedetto L Cortese R Gozal D Gulia KK Kumar VM Tufik S Andersen ML Effects of sleep modulation during pregnancy in the mother and offspring–evidence from preclinical research J Sleep Res 2021 2 e13135 10.1111/jsr.13135 13. Durmer JS Dinges DF Neurocognitive consequences of sleep deprivation Semin Neurol 2005 25 1 117 129 10.1055/s-2005-867080 15798944 14. Knutson KL Spiegel K Penev P Van Cauter E The metabolic consequences of sleep deprivation Sleep Med Rev 2007 11 3 163 178 10.1016/j.smrv.2007.01.002 17442599 15. Noguti J Andersen ML Cirelli C Ribeiro DA Oxidative stress, cancer, and sleep deprivation: is there a logical link in this association? Sleep Breath 2013 17 3 905 910 10.1007/s11325-012-0797-9 23371889 16. AHA News; https://newsroom.heart.org/news/american-heart-association-adds-sleep-to-cardiovascular-health-checklist 17. Pandi-Perumal SR Kumar VM Pandian NG Scientists against war: a plea to world leaders for better governance Sleep Vigilance 2022 6 1 6 10.1007/s41782-022-00198-0 35317215
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2022-12-15 00:01:34
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Sleep Vigil. 2022 Dec 12;:1-2
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Sleep Vigil
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10.1007/s41782-022-00221-4
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==== Front J Child Fam Stud J Child Fam Stud Journal of Child and Family Studies 1062-1024 1573-2843 Springer US New York 2506 10.1007/s10826-022-02506-8 Original Paper “I have a Ph.D. in my daughter”: Mother and Child Experiences of Living with Childhood Chronic Illness Baker Kendall 1 http://orcid.org/0000-0002-2806-8790 Claridge Amy M. [email protected] 2 1 grid.443854.a Mary Bridge Children’s Hospital, MultiCare, 317 Martin Luther King Jr Way, Tacoma, WA 98405 USA 2 grid.253923.c 0000 0001 2195 7053 Child Development and Family Science, Department of Family and Consumer Sciences, College of Education and Professional Studies, Central Washington University, 400 E University Way, MS: 7565, Ellensburg, WA USA 12 12 2022 112 30 11 2022 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Children in the United States are increasingly living with chronic illnesses. Existing literature has focused on adolescent children’s experiences. The current study involved interviews with 10 families: children (ages 6–11) diagnosed with chronic illnesses and their mothers to better understand the experience of living with chronic illness. Using grounded theory, participants’ responses fell into several themes: impact on family dynamics, parental advocacy, initial difficulty followed by resilience, unique stressors, and areas of social support. Overall, both mothers and children reported unique challenges related to living with childhood chronic illness, especially in terms of family dynamics, sibling relationships, and the mother-child relationship. However, almost all families also emphasized their ability to be resilient. The results have implications for medical practitioners and teachers who work with school-age children with chronic illnesses. Mothers need to feel supported and understood by professionals. Families need support to cope with stressors and strengthen couple, sibling, and parent-child relationships. Highlights Children (ages 6–11) diagnosed with chronic illnesses and their mothers participated in semi-structured interviews. Both mothers and children reported unique challenges related to living with childhood chronic illness. Most families also emphasized their ability to be resilient in the face of childhood chronic illness. Children and mothers value support from medical professionals, family members, and friends to cope with childhood chronic illness. Keywords Child chronic illness Family dynamics Qualitative interview Parent-child relationship Resilience ==== Body pmcThe number of children in the United States (US) diagnosed with special health care needs (CSHCN) is on the rise (HRSA, 2022). According to the National Survey of Children’s Health, nearly 1 in 5 children in the US have a special health care need. CSHCN are those who have or are at increased risk for chronic physical, developmental, behavioral, or emotional conditions who also require health related services. Chronic illnesses, or medical conditions with debilitating symptoms lasting for three or more months, account for much of these health care needs. Chronic illnesses include illnesses such as asthma, type 1 diabetes, cystic fibrosis, celiac disease, and epilepsy, among others. Environmental influences such as malnutrition and rising poverty rates have increased the prevalence of certain illnesses (Judson, 2004), and SARS-CoV-2 infection may also increase risk of certain chronic illnesses, including diabetes (Barrett et al., 2022). Advances in medical technology have allowed for the management of many conditions at home rather than in hospital settings. These factors have increased the demands placed on families as they attempt to adjust to their children’s diagnoses. Experiences of Living with Child Chronic Illness Childhood is a period of rapid development, and chronic illnesses have the potential to impact all domains of development. Children who are born with a chronic illness or diagnosed shortly after birth may experience unique struggles as they do not know a life without an illness, and at the same time they may be better able to build a life around the illness (Venning et al., 2007). Children who are diagnosed during childhood may experience a range of physical and cognitive adjustments following a diagnosis including appearance changes, frequent school absenteeism, and long-term dietary changes (Gannoni & Shute, 2010). Children’s Perspectives Previous research into children’s perspectives following a diagnosis of a chronic illness is limited. The limited research that is available often focuses on the perspectives of older school-age children or adolescents (Alderfer et al., 2001; Gannoni & Shute, 2010; Sartain et al., 2000; Wollenhaupt et al., 2012). Existing literature mostly focuses on the educational experience of children with chronic illnesses (e.g., Sisk, 2016), and limited studies examine psychological or socioemotional outcomes (Emerson et al., 2016). Immediately following a diagnosis, children often experience negative psychological health outcomes and report feelings of loneliness and alienation (Sartain et al., 2000). However, they also seek to be active participants in the diagnosis process and can form opinions about their experiences. Existing literature has focused on the immediate adjustment of older school-age children and adolescents and their experiences with chronic illnesses. Younger children are also faced with understanding and incorporating a diagnosis of a chronic illness into their lives. This current study aims to understand the experiences of young school-age children as they navigate family, school, and personal changes that accompany a chronic illness diagnosis. Parents’ Perspectives Existing research specific to parents’ perspectives of chronic illness diagnoses highlights the ways in which child chronic illness impacts parenting and the family unit as well as important aspects of accepting, adjusting, and coping with chronic illness diagnosis. Parents must adjust to long-term stressors which accompany management of a childhood chronic illness (Pinquart, 2018), including financial demands (Foster et al., 2021; Gannoni & Shute, 2010; Romley et al., 2017), attending to children’s daily medical needs (Hafetz & Miller, 2010), and regularly managing unpredictable and uncertain situations (Nygård & Clancy, 2018). Parents report feeling a tremendous burden of ensuring their CSHCN are receiving the best possible care at home, school, and in healthcare settings. They also report feelings of guilt around the child’s diagnosis and wellbeing and worries about the child’s healthy siblings. In turn, parents report physical and mental health challenges resulting from caring for CSHCN. High stress levels in parents may, in turn, make it challenging to parent and contribute to child behavior problems (Hilliard et al., 2011). To cope with the stress and emotions associated with raising CSCHN, parents tend to rely on social support (Nygård & Clancy, 2018). However, family support networks are not always available, and when they are, parents express frustration that their family does not always understand the severity or chronicity of the diagnosis (Gannoni & Shute, 2010). Similarly, many parents report negative experiences with healthcare professionals (Nygård & Clancy, 2018). Existing literature highlights the short-term experiences, unique stressors, and support systems for parents of children with a chronic illness. However, parents’ long-term adjustments and impacts of child chronic illness on the parent-child relationship and family dynamics are still understudied. Impact on Families Consistent with the Social Ecological Model (Bronfenbrenner, 1977) and the Family Resilience Process model (Walsh, 2003), and across a myriad of family health research, it is clear that one family member’s health issues have the potential to impact the whole family’s emotional climate and health outcomes (e.g., Van Schoors et al., 2017; Woods et al., 2020). Following the diagnosis of a chronic illness, families are challenged to incorporate the diagnosis into their daily lives, redefine family roles, and attempt to cope with the demands placed on all family members (e.g., Gannoni & Shute, 2010; Knafl & Deatrick, 2002; Nabors et al., 2019). The changes in daily routine, additional stressors, and emotional adjustment that accompany a diagnosis of a chronic illness can immediately impact sibling, parent, and overall family functioning (Lummer-Aikey & Goldstein, 2021; Nabors et al., 2019; Rosenthal et al., 2021). Healthy siblings of CSHCN are at risk for poorer school engagement (Rosenthal et al., 2021), behavioral and mental health issues (Lummer-Aikey & Goldstein, 2021), and lower self-esteem (Havermans et al., 2015). When siblings receive inadequate information or feel isolated from their parents, they are at higher risk of negative outcomes (Lummer-Aikey & Goldstein, 2021). Siblings also express feeling treated inequitably by their parents, receiving less attention and parental time and taking on more responsibilities and independence. In turn, the sibling relationship may also be impaired (Batte et al., 2006). Birth order seems to contribute to siblings’ experiences such that older siblings tend to take on more caretaking responsibilities for their ill younger sibling, whereas, younger siblings are more likely to experience more restrictions in typical activities like playing with friends (Waite-Jones & Madill, 2008). Yet, many siblings are resilient and engage in positive coping behaviors despite the challenges (Lummer-Aikey & Goldstein, 2021). Key protective factors include social-emotional support from family members, peers, and teachers. Although a diagnosis of a chronic illness influences relationships among all family members, the parent-child relationship must especially adapt to the changing dynamics. Past research has focused on adolescents’ perspectives of the changing parent-child relationship following a diagnosis (Gannoni & Shute, 2010; Hafetz & Miller, 2010; Miller, 2009), and indicates shared decision-making contributes to more positive relationships (Miller, 2009). When parents fail to accept a child’s diagnosis they are at risk of more family conflict and less family cohesion and expressiveness (Popp et al., 2014). Although studies have focused on family functioning and relationships involving adolescents, it is unclear how these processes unfold among young children and their parents. Study Aims The current study aimed to better understand school-age children’s and their mothers’ perspectives of adjusting to life with a chronic illness. Previous literature has often neglected children’s perspectives, and when children are included, most studies rely on the experiences of older school-age children or adolescents (e.g., Miller, 2009). By including younger children’s perspectives in this study, it was possible to gain a more complete understanding of how diagnoses shape parent-child relationship dynamics. Further, because relationships are complex and require explanation beyond what a quantitative study can provide, we used a qualitative interview method to understand in-depth experiences of mothers and their children. Many studies about child chronic illness have focused on the immediate experiences following a diagnosis (e.g., Nabors et al., 2019). It is also important to consider how relationships evolve in a dynamic and transactional manner. As such, we examined experiences of mothers and their children at least six months out from diagnosis, to better understand the long-term changes in families of CSHCN. Method Author Positionality Two authors contributed to the current study. K. B. identifies as White and is unmarried, without children. She holds a master’s degree in Family and Child Life and is certified as a Child Life Specialist, working with children facing medical challenges in a hospital environment. A. C. identifies as White, is married, and has two young children who demonstrate typical development without special healthcare needs. She holds a doctoral degree in Marriage and Family Therapy and is a licensed clinician. Her primary role is as a teacher-scholar, although she provides parenting support to community members. Participants The study included 10 families, consisting of 10 mothers and 8 children, as 2 children opted out of the study. To be included, children must have been school-age (6–11 years old) and diagnosed with a chronic illness. Due to the prevalence of studies in the existing literature that have focused on asthma and cancer, children with those chronic illnesses were excluded from this study. Children with only behavioral (e.g., Autism Spectrum Disorder) or mental health disorders (e.g., depression) were also excluded, however, participants may have had existing comorbidities involving both a chronic illness and a behavioral diagnosis. Children must have also been at least six months post-diagnosis. The primary, residential caregiver to the child was interviewed, and in all 10 families, the caregiver was the child’s biological mother. Children in the 10 families all had different diagnoses (see Table 1). Children ranged in age from 6 to 11 years old (M = 8.50, SD = 1.84). Between 7 months to 10 years had passed since the child had been diagnosed (M = 4.45 years, SD = 3.70). The majority of families identified as White (n = 7, 70%). In only 2 (20%) families was the target child an only child. The majority of mothers were employed (n = 7, 70%). Most also had completed some higher education (n = 9, 90%). Additional demographic characteristics are presented in Table 1.Table 1 Participant demographic characteristics Pseudonym(s) Mother Child Chronic Illness Diagnosis Comorbidities Child’s Age Child’s Gradea Child’s Race/Ethnicity Time Since Diagnosis Number of Children in Household Parent Education Nina Kidney Disease Deny’s-Drash Syndrome 6 K White 5 years 3 Master’s degree Karen Jenna Type 1 Diabetes – 6 K White 1 year 3 Bachelor’s degree Susan James Growth Hormone Deficiency Tree Nut Allergy 7 1st African American, Korean, White 3.5 years 3 Associate degree Nicole Zach Lyme Disease – 8 2nd White 1 year 3 Some college Kelsey Eosinophilic Esophagitis Asthma, life threatening allergies 8 3rd Prefer not to say 8 years 1 Master’s degree Sara John Heterotaxy Syndrome Hypoplastic Left Heart Syndrome 9 2nd White 10 years 8 Some college and trade school Mary Ben Uveitis Autism Spectrum Disorder 9 3rd White 1.5 years 1 Bachelor’s degree Cathy Ryan Septo-Optic Dysplasia Autism Spectrum Disorder 10 4th White, Hispanic 10 years 3 High school diploma Linda Alexa ALPS Trisomy 21 11 6th Hispanic 4 years 5 Some college Carrie Jim Celiac Disease – 11 6th White 7 months 3 Associate degree Table is organized by target child’s age, from youngest to oldest. All presented diagnoses, comorbidities, race/ethnicity, and parent education are based on mothers’ reports and not a standardized set of response options. aK = Kindergarten Measures We conducted semi-structured interviews with the goal of promoting a conversational dynamic during interviews. Mothers and their children were asked demographic questions together, including the name of the diagnosis, time since diagnosis, age of child, grade in school, race/ethnicity, who lived in the residence, maternal education, and maternal employment status. Children were asked three broad, open-ended questions regarding their diagnosis, parent-child relationship, and family dynamics (e.g., “Tell me how you get along with your mother.”). Mothers were asked four broad questions regarding their child’s illness, their relationship with the child, family dynamics, and family resiliency (e.g., “How would you describe your relationship with your child?”). We asked follow-up questions to solicit more information, as appropriate. Procedures Following institutional review board approval (CWU #2020-062), we posted a recruitment flier on various social media pages, primarily Facebook. We mostly posted on support group pages for parents of children with chronic illnesses. Interested families contacted the researchers to schedule an interview. We conducted all interviews via Zoom between April – June 2020. At the time of the interview, we first completed an informed consent process with mothers, which involved an option for participating in member checking. Then we conducted an assent process with the target child. Interviews began with the demographic questions and then mothers and children were given the option of who wanted to complete the interview first. Mothers were encouraged to allow their children to participate in the interview independently without parental interference. Similarly, children were encouraged to exit the room during the parent portion of the interview. Interviews with children lasted approximately 15–30 min and mothers’ interviews ranged from 30 to 60 min. We audio recorded and transcribed verbatim all interviews. Data Analysis One researcher transcribed all interviews verbatim and another verified them for accuracy. Following transcription, we deleted the audio recordings to protect participants’ confidentiality. We analyzed the transcripts using a grounded theory approach, which allowed themes to emerge from the data as we attempted to review the interviews without prior assumptions (Strauss & Corbin, 1997). We first each read the transcripts multiple times to immerse ourselves in the data and gain a sense of the whole (Tesch, 1990). Then, we used an open, axial, and selective coding process (Strauss & Corbin, 1997). In open coding, we both openly coded the first two transcripts independently and then met to discuss our codes and a plan for the remaining coding process. We decided to divide the remaining transcripts and code them independently because we seemed to be coding similarly, and we had both read all of the transcripts. We used descriptive and in-vivo codes to capture each point discussed in the interviews. After open coding, we met to conduct axial coding where we reviewed all open codes and then developed categories among codes and identified patterns and relationships among and between transcripts. Finally, we grouped axial codes into overarching themes in a selective coding process. We present the results here in terms of overall themes which emerged from the data. We emailed a summary of the final themes to participants who opted into the member checking process (n = 8, 80%) to allow for validity checking of the data. Only one mother responded, indicating the themes accurately represented her experience. Results We identified five core themes through analysis of interviews: impact on family dynamics, parental advocacy, initial difficulty followed by resilience, unique stressors, and areas of social support. Each main theme also included subthemes. The themes and subthemes are discussed in detail below. “It’s affected pretty much every aspect of our life:” Impact on Family Dynamics Participants described a variety of impacts of the diagnosis of a chronic illness on family dynamics. Participants described resiliency and parentification of healthy siblings, varied parental couple dynamics, increased sacrifices made by mothers, and a highly involved but challenged mother-child relationship. Resiliency and parentification of healthy siblings In families with multiple children, almost all mothers discussed an increase in responsibility placed on healthy siblings. In some families, the older siblings took on parental roles. Linda talked about her oldest daughter taking care of her youngest son while she was at the hospital with the target child, “for the longest time he actually thought [she] was his mother because that’s who would take care of him all the time.” In other families, younger children assisted in therapies and daily care of the child with a chronic illness. For example, Sara said of her youngest daughter, “…during physical therapy, [she] would run off with the ball…[John] was slower and couldn’t quite do it but it really made him progress a lot. Because he had her.” Regardless of birth order, healthy siblings were given greater responsibility within the family. Mothers also described differences in parenting their CSHCN and their healthy children. Siblings often received less attention from parents and were held to higher expectations. Linda said of her youngest son, “he really has a hard time because this, uh, kind of, he’s kind of left out in the whole scenario.” However, participants felt siblings displayed greater resilience due to their experiences living with a chronically ill sibling. Sara remembered when her target child was not expected to live and how the experience shaped how her older sons handle hardships. She said, “it’s interesting to hear my oldest boys, when they go through something hard, they’re like ‘well, we have been through hard stuff before’… so it’s given them an added measure of confidence in facing hard things.” While most mothers indicated healthy siblings were given less attention, they also felt siblings were more resilient because they had a sibling with a chronic illness. Mothers’ and children’s perspectives on how the chronic illness influenced sibling relationships seemed to differ such that mothers reported a negative impact on healthy siblings whereas children tended to view their relationship with their siblings as unaffected by the diagnosis. Mothers often perceived the diagnosis as adding strain and challenge to sibling relationships. Sara said her oldest son, “gets super annoyed by [John] all the time and it doesn’t help that [John] is like developmentally a little young… he just finally, over the past year, has been fed up with that, and it’s, it’s tough.” However, most of the children reported their relationships with their siblings were not affected by the chronic illness. Many of the children reported not discussing their diagnosis with siblings and instead described developmentally-appropriate sibling relationships. For example, Jim said about his siblings, “I don’t really talk to them that much [about my diagnosis]. It doesn’t really affect them, it only affects me.” Overall, mothers reported more challenges in sibling relationships than children. Varied Parental Couple Dynamics Many mothers discussed how parental couple dynamics were influenced by the chronic illness diagnosis, but there was not one consistent way in which couple dynamics were described. Instead, couples’ dynamics tended to fall into one of three categories. The first dynamic involved both partners sharing in responsibilities and agreeing on treatment decisions. For example, Nina said, “my husband and I, um, try to share you know, care taking responsibilities… so there’s a lot of communication there.” The second dynamic was defined by conflict resulting from partners’ disagreement about medical treatment, parenting, or diagnosis. Carrie said, “it’s really hard when [my husband] does see the cost of something…and he just doesn’t, you know, he doesn’t get it…it’s obviously a medical issue but my husband doesn’t get that.” The final dynamic was one in which the child’s father was uninvolved in treatment and decision making. Kelsey mentioned, “it’s basically made it so my husband is not involved much, because he doesn’t um want to face the, he wants to treat her like a regular kid and ignore everything…he’s here but he’s not like involved.” The level of father involvement in decision making and degree to which parents agreed on medical care seemed to define the couple dynamic. Increased sacrifices made by mothers Mothers described having to make various sacrifices following the diagnosis of their child’s chronic illness. A few mothers mentioned the diagnosis completely changing their daily routines. For example, Kelsey said, “it’s affected pretty much every aspect of our life.” Some mothers were forced to make employment changes. Linda said, “I can’t go to work certain times when her immune system is down…it impacts my work a lot.” Other mothers felt the diagnosis left less time to spend with their partner. For example, Karen expressed that the diagnosis, “makes it virtually impossible to go on a date because there’s nobody that can truly take care of her.” Many mothers shared their struggle with lack of sleep due to monitoring and treatment throughout the night. Karen said, “lack of sleep is probably the hardest thing, I mean sleep deprivation is no joke. It is unbelievable…even if you got one night of rest it’s just not going to help you recover from the chronic sleep deprivation.” Mothers also mentioned the need for constant planning, which resulted in less spontaneity as a family. For instance, Susan said, “there’s traveling with needles, and the pens and the alcohol swabs. Um, and then where are you going to store it when you are traveling?” Similarly, Kelsey felt her daughter’s diagnosis had completely prevented any family outings or time for personal care, “she’s almost basically home bound…I feel like I can’t do things that I used to enjoy doing because I am stuck at home.” Multiple dimensions of mothers’ lives were impacted by the chronic illness diagnosis. Highly involved but challenged mother-child relationship Many mothers discussed the difficulty in parenting a child with a chronic illness. Difficulties centered on mothers needing to be highly involved with their child in order to manage the illness and struggling to set boundaries with the child. Some mothers reported the drawbacks of this parenting style, such as feeling guilty about the inability to set boundaries and wanting the child to be more independent. Linda said, “I think sometimes, um, I make her really dependent…. I’m her enabler I guess is what it is.” Kelsey also shared, “there’s just too many things, you know, that we need to do together which we shouldn’t. You know, she should be more independent at this point.” Others also discussed the benefits of being highly involved after fearing their child would die. For instance, Cathy said,I think, um, going through what we’ve been through with them, like as far as surgeries and hospitalizations and you know, emergency stuff, it just really makes me appreciate, probably more than normal, normal parents who have healthy kids. I don’t think they can understand the relationship I have with my kids. I really try to just appreciate every minute of every day. Mothers felt this had created a very close relationship with their children with chronic illnesses. Children also expressed feeling as if they had a close relationship with their mothers. John said, “[she’s] an actual human shield.” The feeling of a close and involved relationship was reciprocated in both mother and child interviews. During the interviews, many mothers illustrated the highly involved parenting dynamic they discussed as almost all mothers prompted children’s answers and repeated questions to the children. For example, when Zach responded with not knowing the hardest aspect of his illness, his mother Nicole prompted an answer for him, “maybe not eating what you like…and having to remember your pills.” Zach then agreed with his mother, “yeah, probably trying to remember…all my pills.” At the same time, mothers paid attention to what they disclosed in front of their children. Though most mother interviews began with both the child and mother present, many mothers moved to a separate room away from their child at some point during the interview to answer questions. For instance, when asked about how her relationship with the target child differed from her other children, Sara said, “I think I’m going to go into another room for this one.” Despite the high involvement of mothers in their children’s lives, they also demonstrated an ability to set boundaries and were conscious of what they discussed in front of their child during their own interviews. Disagreements between mothers and children often centered on the diagnosis, particularly management of treatments. Mothers expressed feeling guilty for forcing their child to comply with treatments in which the child was refusing. Sara reflected on having to force her child to comply with blood draws,To me it is very traumatic what he has to go through…just this last time we had to have a lab draw he was like, ‘no, no, it’s my body’…and I’m like, that would be abuse in any other situation when someone was saying. ‘it’s my body, stop.’…and yet here I am having to take him repeatedly into this situation. Children expressed feeling angry and upset when their mothers restricted access to food and activities due to their diagnosis. James said he disagrees with his mom about eating “candy” and he can “get a little mad” when he cannot have it because of his blood sugar levels. Ben mentioned, “mom wants me to have Fluorescein. And I don’t. Because Fluorescein is one of those shots I don’t like.” Mothers and children both felt this tension to force treatments and restrict activities was a difficult aspect of their relationship. Mothers often involved children in decision making surrounding chronic illness treatment, although the degree of involvement varied. Some mothers explained treatments to children and ensured they understood the purpose of treatment. For example, Cathy shared, “we are really open with [Ryan], um we tell him every time we have to go to the doctor if he’s going to get poked or if it’s going to hurt.” Linda also said, “we talk to her and we explain to her that this has to happen and um why it has to happen.” Other mothers similarly discussed treatment with their children, however, they acknowledged that their child had refused certain aspects of treatment. For instance, Susan said “we’ve just made [decisions] as parents… other than basically [James] did put his foot down that he wasn’t going to have shots in certain parts of his body so I will say he kind of made that decision.” Most mothers tried to give the child as many choices as possible during treatment when appropriate. Karen said, “we felt very strongly from the beginning that she needed to have choices… [Jenna] can decide whether to watch or not and she can decide whether we count or just go for it.” Similarly, Nina said, “when appropriate we do give [him] options, um, you know like ‘would you rather take your meds now or in ten minutes?’” While children had varying degrees of participation in decision making, most mothers explained treatments and provided choices when possible to children. “You’re a doctor, you have a Ph.D., but I have a Ph.D. in [my daughter]”: Parental Advocacy Mothers discussed the need to advocate for their child to multiple people in their lives. Many mothers focused on the need to repeatedly advocate with doctors for appropriate diagnoses and treatments. Linda described having to explain her child’s diagnosis various times to doctors and finally said, “you’re a doctor, you have a Ph.D, but I have a Ph.D in Alexa.” Karen also had to take her child to multiple doctors, saying “we knew that she was sick… I had taken her to the doctor three times before her diagnosis because I, I, my spidey sense knew something was going on.” Other mothers described how they had to educate teachers and nurses on daily care and emergency procedures. Nina said, “going into school was a new challenge. We had to make sure, you know, his teacher knew he needed to be drinking, we were in contact with the nurse.” Cathy mentioned she created a presentation to share with teachers. A few mothers also expressed the importance of extended family members having a clear understanding of the diagnosis and treatments. For instance, Carrie discussed the struggle of educating her extended family on appropriate food for her child, “it’s more training other people about it that’s been the hardest part with the family….it’s just training his grandparents.” Although areas of advocacy varied, most mothers mentioned an increased need to speak out and educate people who were involved with their child and the challenge this added to their experience of parenting a child with a chronic illness diagnosis. “I cried for like a good two months and had a pity party…now I’ve kind of put my big girl panties on”: Initial Difficulty Followed by Resilience Many mothers described the initial transition following their child’s diagnosis as extremely difficult and stressful. However, most families had created a new normal and felt their child’s diagnosis was now manageable. Initially, most mothers discussed feeling angry and discouraged. Karen said, “I cried for like a good two months and had a pity party.” Cathy said of her experience initially, “the first couple of years, they were pretty rough…we weren’t sure, it was kind of a day by day.” Most mothers discussed eventually accepting the diagnosis and incorporating it into their life. Karen continued about her experience, “now I’ve kind of put my big girl panties on and I’m back to just digging my heels in.” Sara felt, “I don’t feel like it’s a lot anymore. Especially compared to what it was before.” Nina said, “since then, he has been very stable and living a fairly normal life. As normal as can be for a trans, transplant patient.” For the minority of mothers who reported the diagnosis was unmanageable, they tended to express a sense of not accepting the diagnosis and a hopefulness that their child would get better. For instance, Kelsey said,I’m not really looking at her life as normal. I’m constantly trying to find a solution to make it more normal. So I, you know, there are therapies coming out…so she’ll feel better…it’s not happened so far but um, that’s why I kind of have a lot of hope, despite everything. While most mothers mentioned feeling like their child’s diagnosis was manageable now, they described a very difficult transition in the beginning. Children also described adjusting to their diagnosis. For example, Jim said of the beginning, “it was kind of annoying…but I kind of got over it and I realize that almost everything has a gluten free option.” James agreed that in the beginning, getting daily shots was difficult but now he can give them to himself. Ben also has adjusted to getting shots, “I have it every week, enough, that would be enough to get used to it.” Although Jenna reported she does not like her treatment, she acknowledged, “I don’t get sick anymore. I don’t like to get sick ‘cause I don’t get to go to school.” Ryan shared a similar reaction to his shots, saying the shots make him feel, “a little bit happy so that I don’t get sick.” Children initially struggled with daily treatments, however, seemed to have mostly accepted the necessity of treatments, and in turn, expressed a feeling of appreciation for feeling better following treatment. “It felt kind of powerless”: Unique Stressors Mothers described experiencing multiple unique stressors in relation to having a child with a chronic illness. These stressors centered on the unknown, possibility of child dying, increased responsibility to manage illness, and financial burdens. Children also discussed unique stressors related to managing a chronic illness. The unknown Many mothers discussed how one of the biggest stressors for their family was the unknown. This sense of not knowing was a factor in various aspects of their lives. The initial stress of not knowing how to help their child prior to diagnosis was mentioned by a few mothers. For example, Linda expressed “I think the hardest thing is um, seeing her struggle and not being able to really do anything about it.” Some mothers also described the difficulty of not knowing the right treatment for their child. Mary said, “it’s very abstract, knowing what is working, what wasn’t. It felt kind of powerless, you know, not being able to have like, a tangible idea of what we could do.” For a few mothers, there was the unknown of whether the diagnosis was genetic and would impact their other children. Susan shared her fears, “it might be hereditary or not. We do see some other trends in some of our other, um, boys, so we don’t know, yet know if it’s hereditary or not.” Karen shared similar fears for her daughters, “we’re also trying to keep an eye on her sisters to make sure we don’t miss any signs or symptoms if they do develop it as well.” Many mothers also experienced stress related to the possibility of flare ups occurring at any time. For example, Nina said, “he, um, will eventually need another kidney transplant. And so like every month when he has his labs…there’s that little bit of anxiety that’s like, ‘is, is this now, are we going to see a decline?’” Nicole similarly discussed her fears of flare ups, “once every, uh, 4-5 weeks he has a flare up…he’ll have temperatures of 105.8 for like 3–6 days and so we’re always trying to keep it down.” The unknowns of managing life with a child with a chronic illness contributed to the greatest stress for many of the mothers. Possibility of child dying Beyond the unknowns, the added stress from the possibility of their child dying was mentioned by many mothers. Some mothers said this thought was always in the back of their mind. For example, Sara discussed how “it’s always that pit of your stomach, like this could be it.” Other mothers acknowledged how grateful they were to have their child, recognizing the possibility of death. Linda shared her thoughts, “I just gotta be grateful and thankful for the years that I got her because I don’t know how much longer.” Other mothers were told at some point that their child would not survive and indicated they are constantly aware of the possibility. Sara said, “they told us that he was going to die and we just had like a miracle that he survived…we thought we were really going to lose him.” This experience of almost losing their child in the past or the possibility of their child dying in the future was a major stressor described by mothers. Increased responsibility to manage illness Multiple mothers described the pressure of the full responsibility to manage medications and treatments. For example, Mary felt “it’s harder, ‘cause I have a lot of responsibility to be the decision maker of treatment things, you know, kind of unilaterally.” Most mothers discussed the inability to leave their child because of the need for constant monitoring. Cathy said, “I can’t leave him with just anybody. He has to go to certain people who are aware of how serious his illness is…so um, we don’t leave him.” A few mothers mentioned the need to take medications to manage their own personal mental health. Nina shared, “I myself do take anti-anxiety meds” and Kelsey said, “I have become very anxious and um, developed insomnia.” The pressure and responsibility to manage treatments was discussed as an additional stressor for many mothers. Financial burdens A majority of mothers talked about the added financial strain on their family due to hospitalization, medications, and changed dietary needs. For children who required regular treatments, mothers emphasized the extreme financial burden of hospitalization. Linda described the stress of staying at the hospital with her child,It’s like having two households….I don’t get free nothing. You know, for everything that we, that I get there at the hospital, um, it has to come out of pocket…I’m having to be really conscious of you know, um, do I get food or do I leave it so the kids can get food at home? The price of medications also add stress for mothers. For example, Nicole said, “it’s like almost $1000 a month. Um, when you’re already living like month to month it’s hard to do… we have maxed out lots of credit cards trying to pay for it.” Some mothers reported having to completely change their family diet due to the diagnosis, which also added financial pressures. For example, Carrie has to use gluten free foods and said, “it is a lot more expensive in my life… the noodles are twice the cost.” The financial stress of raising a child with a chronic illness was discussed as a major stressor in many families. Children’s experiences of managing a chronic illness Children offered their own perspective of the unique stressors in their life related to their diagnosis. Some children expressed the stress of hospitalizations. John said the hardest part was “going to the hospital every once in a while.” Other children mentioned the stress of procedures. For example, Ryan said, “I sometimes need to get a big ol’ shot. Bigger than the shot I take every night.” A few children discussed the stress of side effects of some of the medications. Ben shared about one of the shots he is required to get, “it makes my pee yellow, which is kind of embarrassing.” Jenna expressed similar feelings that, “sometimes it’s embarrassing.” Children also mentioned the stress of the added responsibility to remember medications and to follow a treatment plan. Zach said, “probably trying to remember…all my pills” was the hardest aspect and Jim said “resisting food that have gluten in them” was really hard. Many of the stressors children mentioned seemed to focus on the difficulty of managing their chronic illness. “There’s a difference between a doctor that listens and a doctor that doesn’t”: Areas of Social Support Many mothers discussed the importance of having social support to cope with the stressors associated with having a child with a chronic illness. Mothers emphasized the importance of having a supportive and available doctor. For example, Mary said “honestly the one thing I need is a clinician who is going to be transparent with me.” Susan also reflected on her experience with doctors, “I’ve just now realized that there is a difference between a doctor that listens and a doctor that doesn’t.” A majority of mothers expressed feeling supported by extended family members. For instance, Cathy said “my mom literally lives next door…and she’s there, um for [Ryan] and us whenever we need her.” Nina also described the support from her mother and her in-laws, “if I need assistance with something, I can call any four of them and, and they’re around and available.” Mothers who did not feel supported from extended family members expressed the lack of support as a challenge. Kelsey said, “we don’t have a lot of extended family…and I have noticed that people I know with, who have extended family, um, around do better.” Some mothers mentioned they typically have support from extended family but due to the pandemic that was persisting during the study, they felt they lacked the ability to access this support. For instance, Karen said, “my mom is… super supportive…and of course with the quarantine, my mom hasn’t been out here.” Support from extended family and understanding doctors played a role in how a family managed their child’s chronic illness. Discussion The purpose of this study was to examine mothers’ and school-age children’s perceptions of the impact of childhood chronic illness on family dynamics. Qualitative interviews revealed multiple ways in which the child’s chronic illness impacted their family dynamics, including changes in sibling relationships, parental couple relationships, and mother-child relationships. Mothers expressed an increased need to advocate for their child and experienced a variety of unique stressors. Families described feeling overwhelmed initially with a chronic illness diagnosis, however, most reported adapting overtime and forming a “new normal.” Social support from extended family and doctors contributed to the ability to overcome stressors associated with a chronic illness diagnosis. Several findings were consistent with previous literature including parenting differences between healthy siblings and CSHCN (Lummer-Aikey & Goldstein, 2021). Mothers reported giving more attention to their chronically ill child than their other children and placing more responsibility on healthy children. In this study, children and mothers had differing perspectives about sibling relationships which is also consistent with prior research indicating parents’ reports of sibling dynamics tend to be significantly more negative than children’s reports (Sharpe & Rossiter, 2002). This may be due to parents being overprotective of their CSHCN and being sensitive to any negative experiences between siblings. Parents also may have socialized expectations for how a sibling relationship should function and therefore compare their own children’s relationships to a norm, whereas children do not have this comparison and see their sibling relationship as typical. Also consistent with previous literature (e.g., Nygård & Clancy, 2018; Rafferty & Sullivan, 2017), mothers reported needing to advocate for their chronically ill children across multiple contexts. As medical advances allow more children with chronic illnesses to return to school and daily life, parents are required to advocate for their child in multiple environments. Most mothers felt this need for advocacy was an additional stressor and reported how emotionally taxing it felt to constantly negotiate with doctors and to educate teachers and school staff. Since school-age children often are assigned a new teacher every year, it is important for schools to assist parents in ensuring teachers are prepared to support students with chronic illnesses. Mothers’ intense caretaking responsibilities seemed related to the unique stressors they reported. Existing research highlights high levels of parenting stress among parents of children with chronic illnesses (Pinquart, 2018). Consistent with previous literature, mothers reported facing financial concerns, increased management of medications, and being forced to make numerous sacrifices due to the intense care required for their children (Nygård & Clancy, 2018). In this study, some mothers reported that financial strains resulted in the need to make difficult decisions such as sacrificing eating while their child was in the hospital to ensure their family had enough money and maxing out credit cards to pay for medications. Hospital programs that assist and alleviate financial stress should be made available to families of CSHCN to reduce the financial burdens these families face. Consistent with previous literature, mothers also reported taking on additional responsibilities related to management of children’s daily medical needs. For example, mothers reported the difficulty of remembering all the necessary medications and ensuring medications were given at appropriate times throughout the day. As parents manage medication regimes at home, it is also helpful for healthcare teams to provide adequate and available information for parents regarding treatment plans (Mitchell & Sloper, 2002). Despite these stressors and sacrifices, both mothers and children discussed the ability to incorporate children’s diagnoses into daily routines and establish a new normal for their family. Mothers’ reports of their emotional experience following diagnosis tended to reflect the stages of grief (Kübler-Ross & Kessler, 2009). Initially, mothers expressed feelings of anger and denial as they grieved for the life they expected their child to live. However, most mothers discussed how they had created a new normal for their family over time, and at the time of the interview reported their child’s diagnosis was manageable. Mothers who felt they had created a new normal expressed acceptance of their child’s diagnosis, a stage of grief that allowed for the creation of a new reality. Moving toward this stage is important for families as acceptance and normalization of a diagnosis play a role in overall family functioning (Popp et al., 2014). For the few mothers who did not feel they had created a new normal, they expressed feelings of hopefulness that their child would eventually get better. This difference may be due to the time that had passed since diagnosis, as these families had experienced their child’s diagnosis most recently. As highlighted in existing literature, social support was important for families with CSHCN in terms of coping (Nygård & Clancy, 2018). The mothers who reported acceptance and normalization of their child’s illness tended to report a strong social network. Mothers reported relying on extended family and supportive doctors to cope with the stressors related to their children’s diagnosis. This finding is consistent with previous literature indicating availability of social support can help foster resiliency in families (Rehm & Bradley, 2005). For families who may not have available extended family, programs should be offered to connect them with other areas of support that can assist in creating and scaffolding resiliency. The findings related to family relationship dynamics expand the literature. Most mothers described feeling highly involved with their child but struggling to set boundaries for various reasons. Parental over-involvement in families of CSHCN has been documented in other studies among parents of adolescents (Hafetz & Miller, 2010; Pinquart, 2013). Our findings highlight the importance of balancing parental involvement and child independence in school-age children as well. Although intensive parental involvement may be useful in the initial time following a diagnosis, the continuation of intensive parenting over time may create dependency in children. Difficulty in boundary setting by mothers in this study is inconsistent with previous quantitative research that found parents of children with a chronic illness tend to demonstrate high demandingness (Pinquart, 2013). Mothers in this study tended to describe highly controlled parenting but a lack of demandingness in setting rules. These differences may be due to mothers’ hyperawareness of their parenting practices. Since mothers are so involved with their child, they have more opportunities to set boundaries and may be critical of their ability to do so. During interviews, many mothers demonstrated their ability to set boundaries by exiting the room to discuss certain topics apart from children. Hyperawareness and over-involvement may contribute to mothers’ perception of boundary difficulties. These findings add depth and complexity to the current understanding of parenting practices in families with CSHCN. Children and mothers both reported engaging in collaborative decision-making regarding treatment. Some mothers described a more passive decision-making process, explaining treatment and care to children and ensuring children understood the purpose of certain treatments, whereas others actively engaged children by providing choices and allowing for input (Knopf et al., 2008). Both processes are useful in improved general health in adolescents, and family cohesion, expressiveness, and support is associated with better child adjustment outcomes (Van Schoors et al., 2017). Although school-age children in this study expressed discontent when parents forced treatments, they also acknowledged and appreciated that treatments helped their body feel better. These findings highlight the ability of young school-age children to participate in the decision-making process and the importance of ensuring children understand the benefits of treatment to increase compliance. The study findings related to parental couple dynamics also add to existing literature. Mothers who did not feel their partner was involved or who did not agree with their partner on treatment decisions reported the most conflict. Existing literature highlights mutual involvement and supportive coparenting around illness-specific decisions tends to be related to more consistent compliance and treatment adherence in children with Type 1 Diabetes (Barzel & Reid, 2011). This study expands on those findings by emphasizing the importance of open communication and mutual involvement from both partners in treatment decision-making processes in families with CSHCN. Limitations Despite the contributions of this study, it was also limited in several ways. Participants self-selected into the study which likely biases the results. It is possible that families who were experiencing less stress may have been more interested or available to share their stories. Future studies should attempt to recruit using a probability sampling technique to avoid self-selection bias. Relatedly, although all parents were invited to participate in this study, we ended up only talking to mothers. The experiences and perspectives of mothers and fathers likely differ. We also did not include siblings, who likely have a unique perspective. Future researchers should attempt to incorporate additional family members to more fully understand family dynamics. All children in this study had different diagnoses and while this indicates the identified themes may be important across child diagnoses, it hinders in-depth understanding of experiences of specific diagnoses. Further research into experiences of specific diagnoses is needed. Additionally, because this study took place during the early stages of the COVID-19 pandemic, we completed all interviews virtually. This prevented us from conducting interviews with parents and children independently, which may have limited the openness of some participant responses. It is also possible families were under abnormally high stress, with less access to support networks at the time of the interview, perhaps influencing their responses. Additionally, each family structure was different and the time since diagnosis varied greatly. Parenting styles, acceptance of a diagnosis, and sibling relationships seemed to differ between families of children diagnosed at birth and those diagnosed later in life and should be further studied. Conclusion The findings of this study reveal the unique experiences of school-age children diagnosed with chronic illnesses and their mothers. Both mothers and children discussed unique hardships and difficulties associated with adjusting to life with a chronic illness, however, most all also emphasized their families’ resilience and ability to adapt to a new normal. School-age children demonstrated the ability and desire to actively participate in their treatment and should be given opportunities for independence when possible. Although mothers described difficulty in parenting children following the diagnosis, it is imperative to validate the strength of parents and children to adapt to a new reality. To further reinforce resiliency and reduce stress in families, support from extended family members and school staff should be promoted. Available and understanding primary physicians along with specialty practitioners who are willing to listen and build trust with families can also assist in navigating the complexities of life with a chronic illness. Support must be provided for all members of the family, including healthy siblings and couples, as childhood chronic illnesses influence the entire family system. Compliance with Ethical Standards Conflict of Interest The authors declare no competing interests. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Alderfer MA Wiebe DJ Hartmann DP Social behaviour and illness information interact to influence the peer acceptance of children with chronic illness British Journal of Health Psychology 2001 6 3 243 255 10.1348/135910701169188 14596725 Batte S Watson AR Amess K The effects of chronic renal failure on siblings Pediatric Nephrology 2006 21 2 246 250 10.1007/s00467-005-2064-9 16240159 Barrett CE Koyama AK Alvarez P Chow W Lundeen EA Perrine CG Pavkov ME Rolka DB Wiltz JL Bull-Otterson L Gray S Boehmer TK Gundlapalli AV Siegel DA Kompaniyets L Goodman AB Mahon BE Tauxe RV Remley K Saydah S Risk for newly diagnosed Diabetes > 30 days after SARS-CoV-2 infection among persons aged < 18 years—United States, March 1, 2020–June 28, 2021 Morbidity and Mortality Weekly Report 2022 71 2 59 65 10.15585/mmwr.mm7102e2 35025851 Barzel M Reid GJ Coparenting in relation to children’s psychosocial and diabetes-specific adjustment Journal of Pediatric Psychology 2011 36 5 618 629 10.1093/jpepsy/jsr022 21551123 Bronfenbrenner U Toward an experimental ecology of human development American Psychologist 1977 32 513 531 10.1037/0003-066X.32.7.513 Emerson ND Distelberg B Morrell HE Williams-Reade J Tapanes D Montgomery S Quality of life and school absenteeism in children with chronic illness The Journal of School Nursing 2016 32 4 258 266 10.1177/105984051615401 26572160 Foster, C. C., Chorniy, A., Kwon, S., Kan, K., Heard-Garris, N., & Davis, M. M. (2021). Children with special health care needs and forgone family employment. Pediatrics, 148(3). 10.1542/peds.2020-035378 Gannoni AF Shute RH Parental and child perspectives on adaptation to childhood chronic illness: A qualitative study Clinical Child Psychology and Psychiatry 2010 15 1 39 53 10.1177/1359104509338432 19914942 Hafetz J Miller VA Child and parent perceptions of monitoring in chronic illness management: A qualitative study Child: Care, Health and Development 2010 36 5 655 662 10.1111/j.1365-2214.2010.01102.x 20533917 Havermans T De Croock I Vercruysse T Van Diest I Belgian siblings of children with a chronic illness: Is their quality of life different from their peers? Journal of Child Health Care 2015 19 2 154 166 10.1177/13674935135503582 24154844 Hilliard ME Monaghan M Cogen FR Streisand R Parent stress and child behaviour among young children with type 1 diabetes Child: Care, Health and Development 2011 37 2 224 232 10.1111/j.1365-2214.2010.01162 21083686 Health Resources and Services Administration HRSA (2022). National Survey of Children’s Health data brief: Children and youth with special health care needs. Maternal and Child Health Bureau. Retrieved from https://mchb.hrsa.gov/sites/default/files/mchb/programs-impact/nhsc-data-brief-children-youth-special-health-care-needs.pdf Judson L Global childhood chronic illness Nursing Administration Quarterly 2004 28 1 60 66 10.1097/00006216-200401000-00013 14986511 Knafl KA Deatrick JA The challenge of normalization for families of children with chronic conditions Pediatric Nursing 2002 28 1 49 53 Knopf JM Hornung RW Slap GB DeVellis RF Britto MT Views of treatment decision making from adolescents with chronic illnesses and their parents: A pilot study Health Expectations 2008 11 4 343 354 10.1111/j.1369-7625.2008.00508.x 19076663 Kübler-Ross, E., & Kessler, D. (2009). The five stages of grief. In Library of Congress Catalog in Publication Data (Ed.), On Grief and Grieving (pp. 7–30). Lummer-Aikey S Goldstein S Sibling adjustment to childhood chronic illness: an integrative review Journal of Family Nursing 2021 27 2 136 153 10.1177/1074840720977177 33305651 Miller VA Parent–child collaborative decision making for the management of chronic illness: A qualitative analysis Families, Systems, & Health 2009 27 3 249 266 10.1037/a0017308 Mitchell W Sloper P Information that informs rather than alienates families with disabled children: Developing a model of good practice Health & Social Care in the Community 2002 10 2 74 81 10.1046/j.1365-2524.2002.00344.x 12121265 Nabors L Liddle M Graves ML Kamphaus A Elkins J A family affair: Supporting children with chronic illnesses Child: Care, Health and Development 2019 45 2 227 233 10.1111/cch.12635 30474877 Nygård C Clancy A Unsung heroes, flying blind—A metasynthesis of parents’ experiences of caring for children with special health‐care needs at home Journal of clinical nursing 2018 27 15–16 3179 3196 10.1111/jocn.14512 29754433 Pinquart M Parenting stress in caregivers of children with chronic physical condition—A meta‐analysis Stress and Health 2018 34 2 197 207 10.1002/smi.2780 28834111 Pinquart M Do the parent–child relationship and parenting behaviors differ between families with a child with and without chronic illness? A meta-analysis Journal of Pediatric Psychology 2013 38 7 708 721 10.1093/jpepsy/jsto20 23660152 Popp JM Robinson JL Britner PA Blank TO Parent adaptation and family functioning in relation to narratives of children with chronic illness Journal of Pediatric Nursing 2014 29 1 58 64 10.1016/j.pedn.2013.07.004 23973569 Rafferty KA Sullivan SL “You know the medicine, I know my kid”: How parents advocate for their children living with complex chronic conditions Health Communication 2017 32 9 1151 1160 10.1080/10410236.2016.1214221 27588934 Rehm RS Bradley JF The search for social safety and comfort in families raising children with complex chronic conditions Journal of Family Nursing 2005 11 1 59 78 10.1177/1074840704272956 16287818 Romley, J. A., Shah, A. K., Chung, P. J., Elliott, M. N., Vestal, K. D., & Schuster, M. A. (2017). Family-provided health care for children with special health care needs. Pediatrics, 139(1). 10.1542/peds.2016-1287. Rosenthal E Franklin Gillette S DuPaul GJ Pediatric siblings of children with special health care needs: well-being outcomes and the role of family resilience Children’s Health Care 2021 50 4 452 465 10.1080/02739615.2021.1933985 Sartain SA Clarke CL Heyman R Hearing the voices of children with chronic illness Journal of Advanced Nursing 2000 32 4 913 921 10.1046/j.1365-2648.2000.t01-1-01556.x 11095230 Sharpe D Rossiter L Siblings of children with a chronic illness: A meta-analysis Journal of Pediatric Psychology 2002 27 8 699 710 10.1093/jpepsy/27.8.699 12403860 Sisk, C. C. (2016). Children with special health care needs and disabilities: Perceptions of health care experiences [Doctoral dissertation, Tennessee Technological University]. Strauss A Corbin JM Grounded Theory in Practice 1997 Thousand Oaks, CA Sage Tesch R Qualitative research: Analysis types and software tools 1990 Bristol, PA Falmer Van Schoors M Caes L Knoble NB Goubert L Verhofstadt LL Alderfer MA Systematic review: Associations between family functioning and child adjustment after pediatric cancer diagnosis: A meta-analysis Journal of Pediatric Psychology 2017 42 1 6 18 10.1093/jpepsy/jsw070 28173163 Venning AJ Eliott J Whitford H Honnor J The impact of a child’s chronic illness on hopeful thinking in children and parents Journal of Social and Clinical Psychology 2007 26 6 708 727 10.1521/jscp.2007.26.6.708 Waite-Jones JM Madill A Amplified ambivalence: Having a sibling with juvenile idiopathic arthritis Psychology and Health 2008 23 4 477 492 10.1080/14768320701299906 25160580 Walsh F Family resilience: A framework for clinical practice Family Process 2003 42 1 18 10.1111/j.1545-5300.2003.00001.x 12698595 Wollenhaupt J Rodgers B Sawin KJ Family management of a chronic health condition: Perspectives of adolescents Journal of Family Nursing 2012 18 1 65 90 10.1177/1074840711427545 22184753 Woods SB Roberson PN Priest JB Family emotional climate and health: Testing conveyance of effects via psychobiological mediators Personal Relationships 2020 27 3 674 707 10.1111/pere.12337
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==== Front Telecommun Syst Telecommun Syst Telecommunication Systems 1018-4864 1572-9451 Springer US New York 971 10.1007/s11235-022-00971-6 Article Technoeconomic assessment of an FTTH network investment in the Greek telecommunications market Skoufis Aggelos [email protected] Aggelos Skoufis received the B.Sc. in Electronics from Piraeus University of Applied Sciences and M.Sc. in Telecommunication Networks and Telematic Services from Harokopio University. He is a doctoral candidate in technoeconomics of NGA networks in Harokopeion University. He has a strong working experience in fixed access networks, having worked for more than 10+ years in Greek ISPs as network engineer and now works as Test Engineer in Nokia R &D 5G FWA products. His current research interests include performance analysis of wireless and UAV-enabled communication systems. Chatzithanasis Georgios [email protected] Georgios Chatzithanasis is a Ph.D. candidate in the department of Informatics and Telematics of Harokopion University of Athens. He also holds a master’s degree in “Information Systems in Business Management” from the same University. The research subject of his doctoral dissertation is the techno-economic evaluation of technology. Research interest is now focused on bundling for technologies like Cloud Computing and developing an intelligent algorithm for brokering. http://orcid.org/0000-0003-2947-7470 Dede Georgia [email protected] Georgia Dede is Senior Information Security Consultant at Net -company-Intrasoft involved with Research (Horizon 2020) projects and Consulting Projects for EU Institutions. She is also adjunct lecturer and post-doctoral resea-rcher in the area of decision making and operational research in IoT applications and services at the Department of Informatics and Telematics of the Harokopio University. She has worked as a Network and Information Cybersecurity Officer at ENISA (European Union Agency for Cybersecurity). She has participated in EU and national projects. She has published papers in scientific journals, books and conferences, and is also a reviewer in scientific journals. Filiopoulou Evangelia [email protected] Evangelia Filiopoulou holds an Informatics and Telecommunications degree (University of Athens), an M.Sc. degree in Techno-Economical Systems Engineering (National Technical University of Athens) and a Ph.d. degree in the area of Cloud Computing Technoeconomics and Management (Harokopio University). She has been a highschool teacher of Computer Science for 17 years and for the last three years she has been working as a Research Associate in the department of Informatics and Telematics in Harokopio University. Her research interests include technoeconomics analysis, diffusion, pricing, adoption, implementation and resource management of the Internet of Things services and their effect in market trade. Kamalakis Thomas [email protected] Thomas Kamalakis (galaxy.hua.gr/~thkam) was born in Athens in 1975. He obtained his B.Sc. in Informatics and M.Sc. in Telecommunication with distinction, from the University of Athens in 1997 and 1999 respectively. In 2004 he completed his Ph.D. thesis in the design and modelling of Arrayed Waveguide Grating devices. He was a research associate for the Optical Communications Laboratory of the University of Athens from 2004 to 2007 and an assistant lecturer in Electronics for the University of Peloponnese at the same period. In 2008 he joined the Department of Informatics and Telematics at Harokopio University of Athens where he is currently a full professor. He has over 100 publications in peer reviewed journal and international conferences. His research interests include integrated optics, nanophotonics, optical detection and free space optics Michalakelis Christos [email protected] Christos Michalakelis is an Associate Professor at the Department of Informatics and Telematics, Harokopio University of Athens. His research interests and field of expertise focus on technoeconomics engineering, costing, pricing and brokering services in the area of ICT, mainly cloud computing and the Internet of Things (IoT). He has worked for many years with the Greek Ministry of Education, as an IT manager. He has participated into a number of projects regarding the design and implementation of database systems, as well as in several technoeconomic and socioeconomic activities for telecommunications, networks and services. He has published more than 100 papers to international journals and conferences. He is co-founder of “Study in Greece” (http://www.studyingreece.edu.gr ), the official portal and initiative of Greece (Hellas), for the promotion and support of studies and educational activities in Greece for international students, acting as a cultural an educational bridge between Greece and other countries. grid.15823.3d 0000 0004 0622 2843 Harokopio University of Athens, Department of Informatics and Telematics, Tavros, Greece 12 12 2022 117 31 10 2022 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Recent years have seen an increasing need for higher broadband connections, fueled by novel applications including fifth generation wireless networks (5G). The European Commission is working on achieving specific milestones regarding the development of next generation networks. Many EU countries have opted to adopt a gradual migration path towards the Fiber-to-the-Home (FTTH) technology in view of the high costs of implementation. The Fiber-to-the-Cabinet (FTTC) architecture, combined with very-high-bit-rate digital subscriber line 2 (VDSL2) and vectoring noise cancellation techniques may therefore provide a viable short-term basis solution. Techno-economic modeling and assessment is vital at the initial stages of the development of a telecommunication network investment project involving high capital expenditures for the infrastructure. The present work provides a techno-economic model in order to assess the prospects of such a network upgrade project from a financial perspective, following a three-way migration path. The three stages are: the implementation of the FTTC architecture with VDSL2 vectoring technology, the upgrade to FTTC with G.Fast and finally the migration to FTTH. The analysis is implemented over a suburb of the city of Athens, Greece. Different scenarios are evaluated, predicting profits even from the first years following the investment. The analysis includes the estimation of the degree of market penetration, analytical cost calculations for the implementation and operation of the network and the evaluation of crucial financial indicators, regarding the prospects of the investment in vectoring services. The study can serve as a complete road-map and can be applied in similar upgrade scenarios. The most important outcome of the analysis is that the profits resulted from each upgrade will finance the next step. Keywords Broadband Telecommunications VDSL2 Vectoring Technoeconomic analysis FTTC ==== Body pmcIntroduction According to the data published in 2019 by the European Commission [1], nearly 223 million EU households (99.9%) had access to at least one of next generation access (NGA) network technologies (excluding satellite) by the end of 2018. The estimated number of the EU households that enjoy benefits of the NGA networks count to a level of about 179.5 million. Between Q4 2020 and Q1 2021, the share of fiber-to-the-home (FTTH) connections in the total fixed broadband subscriptions went up by 0.8% and stood at 56.4%. Copper-based connections still dominate in Africa, while cable is the prevalent technology in the Americas and FTTH has the largest market share in Asia. At a European level, the penetration for FTTH is currently at 20% while the combined penetration of FTTH and fiber-to-the-building (FTTB) have reached 48.5%. Latest studies predict that in 2026, FTTH/FTTB penetration will reach 197 million for EU39 corresponding to (65.3%). It is therefore clear, that although the long-term tendency is to replace copper-related technologies, these will continue to be part of the access infrastructure for the next few years. Depending on regional policies and area characteristics, transitional fiber-to-the-cabinet (FTTC) architectures have therefore been adopted. In many countries, these decisions are dictated by policy-related deadlines for achieving deployment at higher broadband speeds and the high cost of fiber installation at the customer premises. Investing in gradual FTTC upgrades enable postponing FTTH installation until payback periods for existing infrastructure are reached. We therefore need to consider the evolution stages of the FTTC network to a purely FTTH network in greater detail to obtain realistic road-map. Vectored DSL constitutes a mature FTTC technology that can achieve a downstream bit-rate of 100 Mb/s at a distance of 500 m taking into advantage existing copper infrastructure [2]. With the use of VDSL2, 35b profile vectoring can be applied on a FTTB architecture (100m from the user’s premises) and the downstream bit-rate can exceed 200 Mb/s [3]. Although VDSL2 has advantages on the quality of the provided services, its performance can be limited due to Far-End Crosstalk (FEXT). FEXT derives from the large number of lines (few hundred) that can coexist in the same cable. Noise cancellation techniques can help reducing the FEXT and enable data rates that can reach the theoretical maximum of the line capacity [4]. In order to apply the vectoring technology, an anti-signal is generated to cancel the crosstalk [5]. It is important to point out that migration to vectoring involves all lines in the same cable to be controlled by a single service provider [6]. This is in contradiction to the current regulatory framework, which aims at promoting provider competition. Fixed access network sharing (FANS) [7] and single-operator vectoring (SOV) can be used to render VDSL compliant with such mandates. In Greece, the national regulatory authority, decided to adopt the SOV implementation model [8], in an attempt to avoid unfair competition between the incumbent provider (55% of market) and the three alternative providers. G.fast [9] is a relatively newer FTTC technology, that delivers user data rates up to 1 Gbps over copper twisted pairs, implemented with a Fiber-to-the distribution point architecture (FTTdp). FTTdp consists of distribution point units (DPUs) installed closer to the user premises (typically in mini cabinets or curb boxes) being connected via fiber to the central office. This enables bit rates of the order of 500 Mbps over a distance of 250 m. As an upgrade to VDSL, G.fast should co-exist with legacy DSL systems including vectored VDSL. In [10] it shown that deployment of spectral-compatible band plans is an effective means to improve vectored VDSL2 performance with small impact on G.fast. Moreover, the work of [11] investigates the performance of G.fast coexisting with VDSL2 suggesting a scenario where FTTC locations can be upgraded to also serve G.fast. Higher data rates are delivered to subscribers located close to the cabinet, while subscribers with longer lines or with legacy equipment are served with the legacy service. On September 2017, British Telecom (BT) announced a pilot deployment pilot of G.fast across the UK [12], where the service would be delivered over the existing access FTTC infrastructure. Similarities between UK and Greek access networks in terms of existing FTTC architecture and length of the copper cables (shorter than 300m in both cases, allowing G.fast upgrade), it can be concluded that G.fast is probably the best short term option for upgrading VDSL2 vectoring technology.Table 1 Access technology comparison Technology Speed Distance Channel Notes VDSL 17a 100 Mbps 500 m 17.6 MHz VDSL2 35b (FTTC implemented) 200 Mbps 100 m 35 MHz Noise cancellation techniques reduce FEXT G.fast (FTTC implemented) 500 Mbps 250 m 1st version 106 MHz and 2nd version 212 MHz Coexistence with legacy VDSL 1 Gbps 70 m FTTH 10 Gbps 20 Km 1310/1490 nm No Crosstalk On a longer term basis, access networks will converge to FTTH which involves installing optical fiber cables up to the subscriber’s premises. Passive optical networks (PON) is based on a point-to-multipoint architecture where a single optical fiber reaches a fiber optic splitter to provide connection to multiple customers. Two typical PON technologies are envisioned: Ethernet PON (EPON) and Gigabit PON (GPON). Both deliver Ethernet to the end-user but the main difference is that GPON is purposely built as a point-to-multipoint protocol whereas EPON relies on Ethernet to achieve this functionality [13]. PON-based FTTH can deliver large symmetric access rates to the end-user which can even reach 10Gbit/s within the 10G-PON standard [14]. With the last migration step, the provider will be able to offer high QoS and maximize the overall QoE by eliminating interference and cross-talk while increasing the efficiency of the service. In order to make the comparison easier, a summary of the key parameters of each technology is following (Table 1). VDSL 17a technology uses a signal bandwidth of up to 17Mhz with up to 4096 DTM carriers of 4.3 Khz each and a symbol rate of 4000 bps. This can provide speeds of over 100 Mbps (500m) and is related to line length and copper quality. VDSL2 35b uses a higher bandwidth of up to 35 Mhz with 8292 DMT carriers of 4.3 Khz each and a symbol rate of 4000 bps. This provides speeds of up to 200 Mbps downstream (100m). G.Fast is available with a bandwidth of up to 106Mhz (the specification allows for up to 212 Mhz) and provides speeds of up to 500 Mbps (250 m) with shorter rate adaptation times than VDSL2. Also, G.Fast uses a higher symbol rate (48 Kbps) than VDSL2 and provides lower latency. FTTH deployment support speeds up to 10 Gb/s with last-mile latency in GPON FTTH channels below 1.5 ms, even for links up to 20 km . Fiber carries much higher-frequency signals and is less susceptible to interference than cooper, so it is not vulnerable to crosstalk. In this work we carry out a techno-economic analysis of the FTTC migration path towards FTTH. Our case-study considers a scenario based on a suburb area of Athens. We outline a methodology which includes all the financial aspects of this migration. Regarding the proposed framework, its methodological contribution primarily lies on the usage of the technoeconomic approach in conjunction with the three phases migration method, described in the following Sections. Even if there are previous studies focused on the three phase method, our research introduces the technoeconomic aspect using technoeconomic models. Moreover, inspection of the results of this research reveals that the three phases migration method offers high speed services to the subscribers at low implementation cost and in a relatively short time. In this context, even providers with lack of funds can make the first upgrade to the network and the offered services. In addition, the most important result of the analysis is that the profits made from each upgrade will finance the next migration step. A comparison between the three phase scenario and the direct FTTH is also presented in terms of implementation and operation cost.The proposed framework may be used for further studies in the field of telecommunication investments, adjusted to the each specific case. The rest of the paper is organized as follows: in Sect. 2, we highlight the contribution of our work taking into account existing literature. In Sect. 3, we present the techno-economic framework that will be used in our analysis and show the main results. In Sect. 4, we discuss the effect of parameter changes using sensitivity analysis and Monte-Carlo simulations. Some concluding remarks are presented in Sect. 5. Related work Several works from existing literature discuss the economic prospects of hybrid optical/wireless networks for providing broadband services to the less populated areas. In [15] a cost effective optical/wireless architecture is proposed, offering broadband services to the rural areas with small density of inhabitants. In this context, a techno-economic analysis of the hybrid architecture was presented, focusing on network costs, divided into two categories. The first category referred to the implementation of the FTTH network costs, whereas the second referred to the implementation of long term evolution (LTE) and wireless local area network (WLAN) costs. In addition, a comparison between FTTC and hybrid alternatives was made, pointing out that fiber cable length essentially determines the cost-effectiveness of the FTTC. In [16], a methodology for analyzing the total cost of Ownership (TCO) of a number of backhaul options based on fiber, microwave and copper technologies, was presented. The proposed strategy was applied in a Greenfield scenario, comparing the estimated TCO values of four backhaul network architectures and in a Brownfield scenario, comparing the TCO values of six backhaul network migration options. Moreover, [17] suggested a techno-economic framework, examining not only the TCO but also the business viability of a heterogeneous network deployment. Two technology options for the transport network were considered based on either microwave or fiber systems, assuming both a homogeneous (i.e., purely macrocells) and a heterogeneous deployment. The results indicated a considerable increase in the backhaul TCO in heterogeneous deployments compared to the homogeneous scenario. In addition, the fiber backhaul proved the most cost-efficient and profitable technology for heterogeneous wireless deployments in areas with high density of users. According to the paper’s general conclusions, a low TCO level may not improve profitability, therefore it is recommended to choose a technology or a deployment option that requires a low upfront investment and generates income as early as possible. In [18], a generalized optimization framework aimed to cost-optimally plan 5G fixed wireless access and its optical x-haul network was proposed. The optimal deployment cost performance was examined, taking into consideration various network conditions and deployment scenarios. In [19], an economic analysis of different access network technologies and architectures was presented, where all the essential elements of a general economic framework were identified and specific issues related to the techno-economic evaluation of next generation access networks were examined. In [20] a flexible, generic model for techno-economic evaluation of an FTTH network was introduced, proposing a logical, modular model that allowed for calculating the different parts of the cost, such as infrastructure equipment. Different solutions considering equipment type and placement for a broad range of population densities were compared. The results of the analysis indicated the impact of trade-offs in equipment placement and distance to the central office. In [21] a techno-economic study of an FTTC/VDSL and purely FTTH deployments was performed. The financial issues and challenges associated with the incumbent’s decision to invest in dense urban and urban areas were examined, applying Discounted Cash Flow (DCF) analysis and Real Options Analysis (ROA). Calculation of the cost of the deployment of a PON FTTH network in terms of NPV, IRR and payback period was performed in [22]. The analysis considered several options for high data rate provisions depending on population density. Most of the above papers focus on hybrid optical/wireless networks, presenting alternative technologies that can be used as a last-mile solution, providing cost effective high-speed broadband access to areas where fixed broadband is limited. The current technoeconomic scenario and its evaluation is an extension of the work initially developed in [23], where a technoeconomic analysis was performed, focusing on VDSL2 vectoring technology with its subsequent G.Fast upgrade. The present work focuses on a similar scenario where traditional copper network infrastructure is already installed. Taking into consideration the need for extending beyond the payback period of the legacy network and the limited budget for an upfront investment, a migration path is investigated, based on three phases corresponding to the three access technologies discussed in Sect. 1. During the first phase, we opt for adopting a FTTC/vectoring VDSL2, to be upgraded later with G.fast technology. As soon as the investment becomes profitable the migration will enter its final phase, which is the provision of a purely FTTH network. The technoeconomic analysis performed in this work includes time dependent indicators, such as CAPEX, OPEX, revenue and the time period for which the evaluation is considered [24]. The current analysis adds to existing literature, since it evaluates the total investment in terms of income and revenue. The methodological contribution of the proposed model primarily lies on the usage of the technoeconomic approach in conjunction with the 3-phase migration method. Even if there are previous studies focused on the 3-phase method, our research introduces the technoeconomic aspect using technoeconomic models. The proposed framework may be used for further studies in the field of telecommunication investments, adjusted to the each specific case. In addition, we compare the CAPEX of the three-stage scenario with the CAPEX needed when FTTH is installed in a single stage, without considering intermediate vectoring and G.fast stages. The results indicate that a single-stage implementation could lead to large CAPEX which maybe difficult to cope with at a national or regional scale. In such circumstances the proposed three-stage approach could alleviate some of the economic burden for the provider. The reliability of the results is also verified by carrying out a sensitivity analysis. Different service bundles are offered to customers, whereas the prices are defined based on the pricing policy followed by the local providers of the market. In order to achieve more accurate results, extensive demand forecasting is applied based on price service and historical data from previous technology generations. Technoeconomic analysis The current technoeconomic analysis consists of the following steps [25]:Evaluation of the proposed scenarios, based on the network topology, the technologies, etc. Demand forecasting for the deployed services. Modelling costs, revenues and transforming them into annual cash flows and discounted cash flows, for a predefined time period. Investment analysis by calculating the fundamental financial indices, such as payback period, Net Present Value (NPV), Return on Investment (RoI) and Internal Rate of Return (IRR) for each scenario. Sensitivity analysis in order to identify the impact of input parameters over the project performance. The proposed techno-economic approach can be applied to various fields of the technology market, with small modifications customized to each specific case. Demand forecasting A major component to the evaluation of the project is the estimated demand for the offered services. Demand forecasting is usually achieved using diffusion models. The latter are mathematical functions of time, used to estimate the parameters of the diffusion process of a product or service life-cycle. They produce S-shaped curves corresponding to future demand at an aggregate level, rather than at an individual user level. The main advantage of the aggregate diffusion models is that they are able to provide accurate forecasts without relying on the underlying specific parameters that drive the process. Diffusion models have been successfully used to forecast telecommunications services [26]. The aggregated S-type diffusion models can be derived from the following differential Eq. (1):1 dY(t)dt=r×Y(t)×[S-Y(t)] Where Y(t) represents the total penetration at time t, S is the saturation level of the market for the technology under evaluation (the maximum expected adoption level) and r is the coefficient of diffusion, which describes the diffusion speed and correlates the diffusion rate with the actual and the maximum penetration. As observed in Eq. (1), the diffusion speed is proportional to both the population that has already adopted the service, denoted by Y(t), and the remaining market potential, represented by the quantity S-Y(t). Among the most popular models are the linear logistic [27] and the Gompertz models [28]. The former is described by the following equation:2 Y(t)=S1+e-a-bt while the latter by:3 Y(t)=Sexp-e-a-bt A more accurate approach is suggested in [29] showing that price affects the diffusion of mobiles and fixed telephony in six large regions. The use of the price-adjusted logistic model essentially modifies the market potential by introducing a multiplicative factor on reflecting the price. Subsequently, Eqs. (2 and 3) are transformed into:4 Y(t)=Se-αln(Pt/P0)1+e-a-bt 5 Y(t)=Sexp-e-a-bte-αln(Pt/P0) where Pt corresponds to the price at time t. The next step in the forecasting process is to determine the values of parameters that best describe the specific dataset. This is achieved by employing historical data describing the diffusion of the specific or similar technologies and use them as an input to a statistical software able to perform Nonlinear Least Squares (NLS) regression. The result of this process will provide the values of the parameters of the evaluated model and will consequently be used to provide the needed forecasts. Not all the aggregate models are able to accurately describe all historical datasets, since the latter are a result of the specific social and economic characteristics of the considered market. For this reason, forecasting should be better based on the application of more than one diffusion model, in order to provide a range, which diffusion is expected to lie within. Forecasts for the diffusion of the vectoring network can be based on the assumption that, since vectoring technology is the evolution of VDSL, demand can be based on historical data available from non-vectored VDSL which currently upgrades legacy ADSL service. Analysis of market penetration for the years 2005–2012 [30] for ADSL and 2012–2017 [31] for VDSL in Greece, leads to some insights regarding the expected adoption scheme: during the first year that both ADSL and VDSL were commercially introduced, only a small percentage of subscribers adopted the new service, the second year saw a significant growth, while the third year tripling the number of subscribers, followed by a steady annual increase observed in the year to come. We assume that the demand for vectoring will proceed in the same manner. Figure 1, shows the demand forecasting from 2020, when vectoring is introduced extended until 2040. According to the original data, the percentage of ADSL subscribers that adopted VDSL was 6.84% in 2012, 10.36% in 2013, 13.83% in 2014, 16.40% in 2015 and 17.76% in 2016. Assuming that the same penetration is expected for vectoring these values used as input in NLS to obtain the penetration from 2024 onward. By year 2020, the total number of subscribers available in the study area is 2.800 and an annual increase of 5% subscribers is calculated matching the broadband annual subscription growth [32]. Four years after the introduction of vectoring the second upgrade of NGA network takes place with the commercial launch of G.fast service. The time of G.fast introduction was taken to coincide with the break-even point of vectoring calculated in our subsequent analysis (see Sect. 3.3). For G.fast technology, the same inputs with VDSL2 vectoring are used shifted ahead in 2024, since we expect that the user tendency to adopt new technologies will not vary significantly over time. Figure 1, shows the gradual increase of VDSL2 vectoring subscribers for both models until the year 2024 where the logistic model is differentiated and a gradual decrease in demand begins. The transition of some vectoring users to the new technology enhances the presented downward trend. In contrast, the Gompertz model does not seem to be affected to such an extent by the introduction of G.fast and its declining period coincides with the commercial release of FTTH. From year 2024 onwards, when FTTH is introduced, the repeated downward trend is transmitted to G.fast users for the logistic model, while for the Gompertz model the subscribers number remain stable for the rest years of the analysis. In general, the figure illustrates the different results obtained by the two models which originates in the assumptions used for their construction. Application of more than one diffusion models, in the context of a technoeconomic analysis, is a common approach and results in a range of values within which the diffusion is expected to lie on.Fig. 1 Forecast for vectoring, G.fast and FTTH penetration Billing The vectoring broadband bundles provide faster internet access to the customers with downstream speeds up to 100 Mbps and 10 Mbps upstream data rates. These bundles are combined with various options for domestic and mobile calls [31], resulting into three different bundles for access technologies:Economy (E), which provides only unlimited broadband services. Unlimited (U), which combines unlimited broadband services and unlimited domestic calls to Greek landlines. Unlimited Plus (U+), which is similar to U, including 360 minutes calls to mobile phones. A major factor affecting the demand of a product is price. In order to achieve realistic results, the same pricing policy is applied, based on the data of Greek market and the offered bundles. In 2016, prices for the corresponding legacy VDSL economy (E), double play (U) and double play (U+) at 30 Mbps were at a level of 33.2€/month, 36.2€/month and 40.2€/month, respectively (service prices without the 24% of VAT). the price for VDSL at 50 Mbps was 40.2€/month and 44.2€/month for the U and U+ bundles, while no E option was offered for this access rate which represent the flagship of the operator. Furthermore, comparing the prices of VDSL2 bundles when firstly appeared, a correlation emerges in pricing policy. More specifically, the economic bundle of a service has a similar price with the U+ bundle of a slower speed service, while the price difference between U and U+ of the same speed service usually defined at 4–5€. Based on these figures, a pricing of 45€/month and 49€/month are assumed for the U and U+ 100 Mbps VDSL vectoring bundles in 2020, respectively. The pricing for vectoring starting from 2020 is estimated based on the similar billing policies of the legacy ADSL and VDSL packages during the time period from 2012 to 2017. The actual price variations in the service bundles depend on the specific strategy of each operator and can vary from year to year. In the present case, it is assumed that the price reduction follows a simple geometric distribution P(n)=P(1)(1-k)(n-1), where the index k is the average reduction rate for each year. The value of k for VDSL vectoring can be inferred from the price evolution of similar technologies, in our case legacy VDSL. Based on the available pricing data for the corresponding legacy VDSL bundles in Greece, it was derived that prices within 2012 and 2017 correspond to an average annual reduction k of 3.77% and 3.43% for U and U+, respectively. Applying the geometric formula, we can ascertain that the price reduction of U and U+ at the end of the 10 year period will be ≅32% and ≅30% and for a 20 year period the reduction is estimated to reach ≅54% and ≅50% respectively. Following the bundle policy of British Telecom, we introduce two different G.fast services with 400 Mbps/50Mbps and 200 Mbps/30 Mbps for downstream and upstream data rates respectively. When G.fast becomes available at 2024, the prices of the VDSL2 vectoring packages would be reduced by ≅5€. Furthermore, G.fast would replace VDSL2 U+ vectoring as the most expensive package. In order to maintain the price difference, G.fast pricing policy is estimated to follow the diminishing value of VDSL2 vectoring, incremented steadily by 6€ and 10€ for the 2 available G.fast packages respectively (G.fast 200 and G.fast 400). When FTTH is implemented in 2030 only one bundle would be available to customers with 800 Mbps downstream and 100 Mbps upstream. The price of the service will be steadily 6€more expensive than of the G.fast 400. That time G.fast 400 will be priced at 36.23€with the price of FTTH 42.24€. From the pricing strategies introduced above it is evident that the leading service from each technology has a similar pricing range of ≅42 €. As already mentioned, the Greek national authorities decided to adopt the SOV implementation model. In this model, each provider is responsible for implementing the FttC architecture in a specific demarcated area. The CAPEX and OPEX quantities for the network implementation and operation may vary depending on the chosen equipment and the suppliers but in general there are no major deviations as there have been set specifications for the chosen equipment by national network authority. The bundles and their price depend exclusively on each provider, under the condition that the price will remain the same regardless of whether users are in their region or not. By this way, competition is applied in national level. In order to demonstrate SOV in the techno-economic analysis, it is assumed that the incumbent provider would have the 55% of the total subscribers of the area while the remaining 45% will be owned to the other alternative providers and they would be served as wholesale subscribers. According to the Greek market, the wholesale prices vary, depending on the speed of the broadband service and are the same for all providers. Thus, for the existing available services the prices are 10.84€ for the 100 Mbps, 13.29€ for the 200 Mbps and 17.88€ for the 400 Mbps (the prices are without taxes 24%). These prices are for the first year and it is estimated to also follow the diminishing value of VDSL2 vectoring. With the price reduction, in 2030 wholesale G.fast 400 is expected to cost 14.19€and the wholesale price for FTTH to be 17.88€. The following example illustrates how SOV model works. If an alternative provider, X, offers vectoring 100 Mbps at the price of 45€and a subscriber of X is located in the area serviced by Z provider, then 10.84€will be paid to the area incumbent provider Z, for renting the line and the rest 34.16€will be the actual earning for X. Therefore, for provider X the 10.84€are considered as OPEX and, in contrast, for provider Z are considered as income. Implementation cost The investments required for the development of a NGA network based on the FTTC architecture are divided into CAPEX and OPEX. CAPEX refers to the funds used to acquire or upgrade physical assets, such as property, buildings and equipment, as well as the installation cost. OPEX are the expenses that a business incurs through its usual business operations, including rent, equipment, inventory costs, marketing, payroll, electrical consumption and maintenance of the infrastructure. The calculation of the cost is based on the actual region of Egaleo (a suburb of Athens, Greece), which was chosen for the needs of the present technoeconomic analysis. The complicated town planning and the local grove largely affect the optical fiber route (see Fig. 2). As a result, a detour needs to be made for the connection between the cabinets and the distribution center, which increases the final distance of the optical fiber network by several hundred meters. This is a useful case study, being one of the worst case scenarios, as it will raise the implementation cost and that’s why this specific region was preferred. The particular examined area is 188,000 m2 and there are 9 cabinets. In the map presented in Fig. 2, the exact location of the nine cabinets is marked along with the route of the optical fiber network from the distribution center to the cabinets and the overall covered area inside the blue lines. In 2030 the last update of the migration path will be implemented for the FTTH. Optical fiber network will be installed for all the street that are within the blue line margins. The total cost is estimated to be 6.900€.Fig. 2 Map of the Egaleo area Table 2 Cost calculation (CAPEX) CAPEX Equipment Units Cost / Unit (€) Total cost (€) VDSL G.Fast FTTH VDSL G.Fast FttH VDSL G.Fast FTTH Duct and fiber 2105(m) – 6.900 33 – 30 66,075 – 227,798 Cabinets 9 – – 1500 – – 13,500 – – DSLAM & control boards 9 9 – 6350 8900 – 57,150 80,100 – SFP 18 54 288 100 100 100 1800 5400 28,800 Fiber patch cord 18 54 – 5 5 – 90 270 – ODF 9 – 27 30 – 30 270 – 810 Filter reglet 135 90 – 25 25 – 3375 2250 – Batteries 36 – – 100 – – 3600 – – Cabin installation 9 9 9 7100 3000 4000 63,900 27,000 36,000 Power supply 9 – – 350 – – 3150 – – Technical design 9 – – 688 – – 6192 – – OLT 1 1 1 4000 9500 6000 4000 9500 6000 Switch 1 1 1 5200 5200 5200 5200 5200 5200 OCR 1 – 1 500 – 1460 500 – 1460 DC patchcord 18 54 576 5 5 5 90 270 2880 Air condition 1 – – 1150 – – 1150 – – DC installation 1 1 – 4100 3000 – 4,100 3000 4000 Subscriber router 300 450 – 25 40 – 7500 18,000 – Fiber spiltter 1:16 – – 360 – – 10 – – 3600 Cumulative cost 241,642 150,990 316,478 Table 3 Cost calculation (OPEX) Equipment Annual operation cost (€) VDSL G.Fast FTTH OPEX Cabinets 13,230 6930 – Distribution center 5145 2364 2364 Year Existing Copper cable (€) Duct and fiber (€) Cabinets (€) DSLAM equipment* (€) Distribution center**(€) Batteries, cooling system (€) Maintenance cost 2020 872.87 365.19 533.71 1085.75 485.73 – 2021 872.87 719.64 1053.59 2088.42 952.92 – 2022 872.87 709,29 1040.01 2011.30 935.74 4250 2023 872.87 699.30 1026.69 1939.74 919.77 – 2024 872.87 689.68 1013.64 2858.71 1385.45 4250 2025 872.87 680.41 1000.86 3648.97 1817.81 – 2026 872.87 671.49 988.37 3470.01 1773.66 4250 2027 872.87 662.93 976.16 3305.97 1733.21 – 2028 872.87 652.72 964.27 3155.76 1696.18 4250 2029 872.87 646.86 952.69 3018.29 1662.33 – 2030 872.87 639.35 941.46 2892.96 1631.43 4250 2031 872.87 1349.70 930.59 2778.69 2410.59 – 2032 872.87 1994.35 920.12 2674.86 3085.12 4250 2033 872.87 1926.50 910.08 2580.82 2969 – 2034 872.87 1863.52 900.50 2496.01 2869.17 4250 2035 872.87 1805.33 891.40 2419.90 2782.31 – 2036 872.87 1751.95 882.84 2352.01 2707.55 4250 2037 872.87 1703.47 874.84 2291.88 2643.68 – 2038 872.87 1660.08 867.43 2239.05 2589.70 4250 2039 872.87 1621.98 860.63 2193.06 2544.72 – 2040 872.87 1589.38 854.47 2153.427 2503.25 4250 DC distribution center, OCR optical consolitation rack, ODF optical distribution frame, OLT optical line termination, SFP small form-factor pluggable *Including DSLAM, control-service board,fiber patch cord, SFP, ODF, filtered reglets **Including OCR rack, OLT, OLT cards, switch, patch-cord CAPEX estimation Three-phase scenario CAPEX accounts for the cost for equipment purchase and the installation cost and are summarized in Table 2. The installation of the fiber optic network is estimated at 30€/meter. For the successful interconnection between the distribution center and the nine cabinets (the area is served by nine old copper cabinets, which will be replaced by an equivalent number of new optical cabinets) the total cost is 66,075€for a distance of about 2Km of optical fiber. In addition, the calculated cost for the purchase and the installation of the nine cabinets is 152,127€  including all the necessary equipment inside the cabinet, like DSLAM, batteries, optical distribution frame (ODF), copper line termination and cooling system. In the distribution center, the equipment cost is estimated at 15,940€, including the cost of telecom equipment, such as the optical consolidation rack, the optical line termination, switches and the cooling system. Finally, the operator will provide the subscribers with vectoring routers and this leads to an extra cost of 7,500€, in order to meet the estimated demand for the first 2 years. By the third year, depending on the demand, a new router batch purchase will be required. Taking into consideration the aforementioned analysis, the total cost for the deployment of the NGA network is 241,642€. When calculating costs, wherever technical work is required such as installing the fiber optic network and installing cabinets, prices also include the labor cost. Regarding the CAPEX of G.fast implementation there is an additional cost for purchasing and installing the new equipment. The advantage of the FTTC architecture is that the new equipment will be placed inside the cabinet and there is already available fiber optic network to support it. The implementation cost of active G.fast equipment (DSLAM, service boards, SFP) for the 9 cabinets, the distribution center and the G.fast routers is calculated at 150,990€including the labor cost when needed and is going to be installed during the 4th year of the VDSL2 vectoring operation. The last migration phase is going to be completed with the FTTH implementation by 2030. In FTTH architecture ducts and optical network installation have the highest cost. The main advantage of the gradual upgrade from FTTC to FTTH is that the infrastructure connecting the distribution center and the cabinet is already implemented.As a result, the cost of the optical network is split in two stages and in difficult economic periods the total cost of the investment becomes affordable. The CAPEX for the third phase (optical network from cabinet to subscriber) is estimated at 316,479€. The calculations are summarized in Tables 2 and 3 and Fig. 3. As far as the product lifetime is concerned, there is variation between the different network equipment. Table 4 shows the asset lifetimes of the network elements needed for the implementation of all 3 technologies [33]. Single-phase FTTH scenario In this section, the implementation cost for a single-phase FTTH network investment is also estimated for the same geographical area, as an attempt to better highlight the economic prospects of the three-phase scenario. As mentioned above, the main reason this paper considers the transition though a three-phase FTTH scenario is the high implementation cost of FTTH. In the context of the CAPEX calculation, the same data as in the three-phase scenario were used in order the results to be comparable. For this reason, FTTH network architecture was implemented with specifications to provide 600 Mbps bandwidth for each subscriber, in order to match the bandwidth offered in the last migration phase. We also consider the same number of buildings/subscribers as well as the same distances/routes for the optical fiber network. The Table 5 shows the cost of a single-phase FTTH implementation which is 584,465€ and is much higher compared to the cost of each phase of the tree-phase scenario. Considering that the area is relatively small, it is clear that at a national scale, the cost of investment for a provider can be prohibitive compared to the three phase scenario option which leads to a smoother migration towards FTTH. OPEX Three-phase scenario. For a FTTC network, the OPEX mostly depends on the electrical consumption and the maintenance of basic equipment and more specifically, DSLAMs, batteries and cooling system for the cabinets as well as optical line termination (OLT) equipment, switch and air conditioner for the distribution center. For a realistic estimation of the electrical consumption, the cooling system is considered to work at the maximum level during summer period, at 70% during spring, at its 50% for 3 months during autumn and at 20% during the winter. In a similar way, the DSLAM and other devices consumption is estimated, assuming they work for 6 h per day at maximum consumption, 10 h approximately at 50% and 30% for the rest of the day. As a result, the annual operational cost for the nine cabinets is expected to reach 13,230€and the OPEX for the central office 5,145€. An average cost of 0.16€for 1 kWh is assumed. On a daily basis, the cooling system of a single cabinet is expected to operate for 5 h during winter, 12 h during autumn, 17 h in the spring and 24 h at summer period. With an average power consumption of 0.800 kW the total daily consumption is 4 kWh, 9.6 kWh, 13.6 kWh and 19.2 kWh, respectively for the four different seasons while the daily cost is 0.64€, 1.53€, 2.17€and 3.07€. Summing up, for total cost for the winter period the cost is expected to be 58€, 138€in autumn, 195€in the spring and 276€in the summer. The annual cooling cost for a single cabinet is therefore calculated at 667€. In the same way, the annual energy consumption of the DSLAM and the power supply for the nine cabinets in addition to the OLT, switch and air conditioner for the distribution center are estimated. In the distribution center, there is also a monthly additional rental cost of 47€per rack and two of them are required for vectoring needs. When G.fast equipment is installed in all cabinets and the distribution center the OPEX are expected to be increased. The energy consumption of the new equipment will be added to the existing one. The energy consumption of G.fast equipment is calculated with the same methodology and as a result the annual cost is expected to reach 770€per cabinet. In the distribution center the annual energy consumption cost is calculated at 1,800€for the OLT and the switch while it will be used one more rack for the G.fast equipment with annual rental cost of 564€ as shown in Table 3. FTTH does not affect the OPEX of the cabinets because there is no active equipment installed. On the distribution center one more rack is needed for the FTTH equipment with additional cost of 564€/year. The annual energy consumption for the new equipment (aggregation and terminal switch) is calculated to be 1800€.Fig. 3 CAPEX individual costs for VDSL vectoring (V) and G.fast (G) and FTTH Fig. 4 OPEX Costs for VDSL vectoring (V), G.fast (G) and FTTH Over time, network equipment maintenance costs will typically decrease as shown in Table 3. In order to evaluate the annual equipment maintenance costs, we first estimate the decreasing equipment value, for each year after purchase [25]. Using these values, the annual maintenance cost of every equipment can be calculated [34], excluding the maintenance cost of the batteries and the cooling system. A precautionary maintenance cost is considered for the latter, after the third year and subsequently every 2 years, with a total cost of 4250€. The percentage of OPEX costs per equipment are presented in Fig. 4. Single-phase FTTH scenario In this section we calculate the OPEX for a direct upgrade to FTTH scenario. Contrary to the CAPEX, where the implementation cost of the FTTH network is much higher than the 3W scenario, here the data are inversely proportional. An FTTH network has lower operating costs since the optical network is passive and the equipment in the intermediate cabinets does not require power to operate. Maintenance costs remain the same for the rest equipment, as well as the operating cost regarding distribution center. Calculating all the operating costs with the same methodology as in the 3W scenario, it results that the total annual operating costs are 6945€. Investment analysis In Figs. 5a, b, a comparison between the CAPEX, OPEX and revenues is presented for the Gompertz and logistic models respectively. In this point, it should be mentioned that the number of subscribers who choose VDSL2 vectoring is equally divided between the 2 available bundles U and U+. By the same way, the subscriptions of G.fast are split for G.fast 200 and G.fast 400 services. By the end of 2023 (before the G.fast introduction), the number of VDSL2 vectoring subscribers is estimated to 479 subscriptions for logistic model and 483 for Gompertz model. Correspondingly, by the end of 2030 the total G.fast subscriptions is estimated at 640 for logistic and 764 for Gompertz model. After year 2030 with the availability of the FTTH service, for the logistic scenario the vectoring subscribers start to gradually decrease in contrast to the Gompertz in which they continue to increase. At the last year of the technoeconomic analysis, which runs until year 2040, FTTH subscribers stand at 791 for logistic and 982 for Gompertz. Both figures clearly illustrate that the venture can quickly outweigh its expenses, indicating a favorable investment opportunity.Table 4 Asset lifetimes by equipment type Equipment type Asset lifetimes (Years) Ducts and dark fiber 40 Street cabinet 20 Electronic equipment* 5 ODF 10 Batteries 2 Reglet 20 Rack and frames 10 Air condition 10 Subscriber router 10 Optical fiber interconnections 5 *Including DSLAM, control boards, service boards, SFP, OLT, Switch Based on these values, measurements of investment profitability, such as the NPV and the IRR can be calculated. By setting the annual discount rate to 5%, the calculated NPV for the first 20 years of operation is:613.438,46€, for the logistic model. 706.042,86€, for the Gompertz model. while the IRR for the same period is:28,91%, for the logistic model. 30,44%, for the Gompertz model. In both scenarios, the break-even point calculated in Fig. 7 is expected to occur in the first quarter of the fourth operational year. As expected, during the first 2 years the balance is negative due to the slow diffusion, while during the third year, where a larger increase of subscribers is expected, the investment will start showing signs of profitability. Following this, the investment is largely attributable during the fourth year and the profit level is half the initial invested capital. In the following years, the investment continues to generate revenues and, finally, during the last year of the analysis, the total recorded profit is expected to be 5.014.970,9€and 6.511.675,7€for both scenarios. Based on the fact that both NPV and IRR are positive for both scenarios, the investment is considered highly profitable. The presented indicators show that from the fourth year of operation the telecom provider will record constantly increasing profits. The analysis shows that the profits gained from the first two phases are critical, in order to support the funding of the third and final phase.Table 5 CAPEX for direct FTTH FTTH network Cost(€) Ducts and dark fiber 332,533 Street cabinet 83,592 Distribution center 48,340 CPEs 120,000 Total cost 584,465 Fig. 5 OPEX, CAPEX, revenues and earnings for a the Gompertz and b Logistic scenarios over the first 10 years of the investment Fig. 6 Break even point Sensitivity analysis In this section, the reliability of the results is discussed, by carrying out a sensitivity analysis. Since price is a very important parameter that affects the final outcome of the technoeconomic analysis the sensitivity analysis is performed over the price for the FTTH scenario. In order to further validate the reliability of the results, Monte Carlo simulations are performed by simultaneously changing the price over the years. The different values of price are perturbed from Pn to Pn (1+ΔPn), for then nth year, where the perturbations ΔPn are assumed zero mean, identically distributed, independent random variables uniformly distributed inside [-s s]. In an attempt to investigate the stability of the results we perturb the price ±10% and the results are presented in the figure below for the break even point of the FTTH scenario.Fig. 7 Break even point after price sensitivity analysis As shown in Fig. 6, even with perturbed values of price the computations are not significantly affected and interestingly enough the break even point is calculated almost at the same time as before. The sensitivity analysis presented in this section provides an indication of the reliability of the technoeconomic results against changes that may occur in price. Conclusions A technoeconomic evaluation of a three-way migration upgrade path was presented in this paper, starting from the vectoring VDSL2 technology and gradually leading to the FTTH. The proposed migration consists of a three stages implementation: initially the deployment of an FTTC architecture with VDSL2 vectoring technology, gradually upgraded with G.Fast technology and finally, migration to FTTH. The first 4 years of the analysis started with the use of VDSL2 vectoring technology, followed by the second migration step towards the G.Fast that has been proven to coexist successfully under the same infrastructure using noise canceling techniques. The last step is the expansion to FTTH in year 2030. The proposed framework, includes a detailed demand forecasting estimation for the three technologies in question. This, in turn, is used as an input for the calculation of CAPEX, OPEX, cash flows based on specific tariff policies and crucial financial indices that describe the investment, such as NPV, ROI, IRR and the payback period. Results show that investments in VDSL/G.fast vectoring networks as an intermediate migration step can be quite profitable at the initial stages, even if a pessimistic demand level and a less favorable area are assumed. The analysis shows that the profits deriving from the first two phases can cover the cost of FTTH (the third and final phase), which constitutes the main goal of the project. We also compared the CAPEX and OPEX of the three-stage scenario with that of single stage FTTH and showed that the latter corresponds to large CAPEX which could burden the provider at a national scale. In such circumstances therefore it is preferable to adopt a three-stage approach. Even if there are previous studies focused on the 3-phase method, our research introduces the technoeconomic aspect using technoeconomic models. The proposed framework may be used for further studies in the field of telecommunication investments, adjusted to the each specific case. Taking into consideration the effects of COVID-19 outbreak which, among others, foresees working from home and distance learning, it seems to be a suitable period for a provider to invest in optical networks as the demand for high broadband speeds constantly increases and it is note expected to decrease. In addition to the above, the present study incorporates the way particularities of the area can change the route of the fiber optical network, affecting the total cost and the return on investments. As far as VDSL2 vectoring with subsequent upgrade to G.fast is concerned, the time the service will be commercially available is imminent. With the vectoring solution, telecom providers bring new value to existing copper and manage to reach tomorrow’s speeds to today’s networks. However, with the high annual growth rate in demand for speed a FTTH architecture should be the final target, regardless which will be the chosen migration path. Currently, most service providers cannot afford the implementation cost of FTTH networks. To this extent, the most advantageous solution -in terms of low cost- investment and spectacular growth is the step-by-step upgrade combining different technologies and making a hybrid optical network. G.fast will be an option in cases where twisted-pair is available and fiber installation is not practical reducing each time the cost of implementation, while on the same time users will enjoy high quality services [35]. What remains to be seen in the years to come is whether the providers that have implemented FTTC networks will proceed to the implementation of FTTH, or they will try to use other alternatives to improve the network speed of the subscribers. This is another topic that requires further research, both from a technical and from an economic standpoint. Funding The authors have not disclosed any funding. Declarations Conflict of interest The authors have not disclosed any competing interests. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. European Commission. Mobile and Fixed Broadband Prices in Europe 2019. (2019). 2. Zidane R Huberman S Leung C Le-Ngoc Tho Vectored DSL: Benefits and challenges for service providers IEEE Communications Magazine 2013 51 2 152 157 10.1109/MCOM.2013.6461200 3. Norhan, N., Nuroddin, A. C. M., & Asrokin, A. (2017). VDSL2 capacity performance evaluation: Simulation versus measurement. In: Proceedings—2017 IEEE conference on systems, process and control, ICSPC 2017, 2018-January(December), pp. 140–145. 4. Guenach, M., Meas, J., Timmers, M., Lamparter, O., Bischoff, J. C., & Peeters, M. (2011). VectoringF in DSL systems: Practices and challenges. In: GLOBECOM—IEEE global telecommunications conference. 5. Plückebaum, T., Jay, S. & Neumann, K.-H. (2014). Benefits and regulatory challenges of VDSL Vectoring ( and VULA ). SSRN eLibrary. 6. Oksman V Schenk H Clausen A Cioffi J Mohseni M Ginis G Nuzman C Maes J Peeters M Fisher K Eriksson PE The ITU-T’s new G.vector standard proliferates 100 Mb/s DSL IEEE Communications Magazine 2010 48 10 140 148 10.1109/MCOM.2010.5594689 7. Cornaglia B Young G Marchetta Antonio Fixed access network sharing Optical Fiber Technology 2015 26 2 11 10.1016/j.yofte.2015.07.008 8. Hellenic Telecommunications and Post Commission (HTPC). Market analysis. https://www.eett.gr/opencms/opencms/EETT/Electronic_Communications/TelecomMarket/MarketData.html (2015). 9. Hincapie, D., Leibiger, M., & Oswald, E. (2018). Roll-out of giga-bit copper: Impact-analysis of deploying g. fast in FTTC access networks. In Broadband coverage in Germany; 12th ITG-symposium, VDE, pp. 1–6 10. Hincapie, D., & Maierbacher G. (2016). Impact-analysis for coexisting G.Fast and vectored VDSL2. In 2015 IEEE conference on standards for communications and networking, CSCN 2015, pp. 155–161. 11. Strobel, R., & Utschick, W. (2015). Coexistence of g.fast and VDSL in FTTDP and FTTC deployments. In 2015 23rd European signal processing conference (EUSIPCO), pp. 1103–1107. 12. British Telecom. GEA-NGA2 G.fast Pilot Service and Interface Description. https://www.btplc.com/sinet/sins/pdf/STIN520v2p0.pdf (2017). 13. Obite F Jaja ET Ijeomah G Jahun KI The evolution of ethernet passive optical network (EPON) and future trends Optik 2018 167 103 120 10.1016/j.ijleo.2018.03.119 14. D &O COMMITTEE of FTTH. (2018). FTTH Handbook. FTTH Council Europe, 5, 1–161. 15. Brešković, D. (2014). Techno-economic comparison of FTTC/VDSL and hybrid optical/wireless networks. In 2014 22nd international conference on software, telecommunications and computer networks (SoftCOM), pp. 349–355 16. Farias F Fiorani M Tombaz S Mahloo M Wosinska L Costa JCWA Monti P Cost- and energy-efficient backhaul options for heterogeneous mobile network deployments Photonic Network Communications 2016 32 3 422 437 10.1007/s11107-016-0676-6 17. Yaghoubi F Mahloo M Wosinska L Monti P De Farias FS Costa JCWA Chen J A techno-economic framework for 5G transport networks IEEE Wireless Communications 2018 25 5 56 63 10.1109/MWC.2018.1700233 18. Ranaweera C Monti P Skubic B Wong E Furdek M Wosinska L Machuca CM Nirmalathas A Lim C Optical transport network design for 5G fixed wireless access Journal of Lightwave Technology 2019 37 16 3893 3901 10.1109/JLT.2019.2921378 19. Kantor, M., Wajda, K., Lannoo, B., Casier, K., Verbrugge, S., Pickavet, M., Wosinska, L., Chen, J., & Mitcsenkov, A. (2010). General framework for techno-economic analysis of next generation access networks. In 2010 12th international conference on transparent optical networks, ICTON 2010. 20. Van der Wee, M., Casier, K., Bauters, K., Verbrugge, S., Colle, D., & Pickavet, M. (2012). A modular and hierarchically structured techno-economic model for FTTH deployments comparison of technology and equipment placement as function of population density and number of flexibility points. In 2012 16th international conference on optical network design and modelling (ONDM), IEEE, pp. 1–6. 21. Rokkas T Katsianis D Varoutas D Techno-economic evaluation of FTTC/VDSL and FTTH roll-out scenarios: Discounted cash flows and real option valuation Journal of Optical Communications and Networking 2010 2 9 760 772 10.1364/JOCN.2.000760 22. Rokkas, T. (2015) Techno-economic analysis of pon architectures for FTTH deployments: Comparison between gpon, xgpon and ng-pon2 for a greenfield operator. In 2015 Conference of telecommunication, media and internet techno-economics (CTTE), IEEE, pp. 1–8. IEEE. 23. Skoufis A Georgios C Georgia D Thomas K Christos M Technoeconomic analysis of a vdsl2/g.fast vectoring network: A case study from Greece NETNOMICS: Economic Research and Electronic Networking 2020 21 1 83 101 10.1007/s11066-020-09142-8 24. Zhao, R., Zhou, L., Machuca, C. M. (2010) Dynamic migration planning towards FTTH. In Proceedings of 2010 14th international telecommunications network strategy and planning symposium, networks 2010. 25. Paper, H., Stepstechno, R. Economic Evaluation, O F Network, and Deployment planning. White paper: Practical steps in Techno—economic evaluation of network, pp. 1–45. 26. Michalakelis C Varoutas D Sphicopoulos Thomas Diffusion models of mobile telephony in Greece Telecommunications Policy 2008 32 3 234 245 10.1016/j.telpol.2008.01.004 27. Michalakelis C Sphicopoulos T A population dependent diffusion model with a stochastic extension International Journal of Forecasting 2012 28 3 587 606 10.1016/j.ijforecast.2012.03.002 28. Gompertz B On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies Philosophical Transactions of the Royal Society of London 1825 115 513 583 10.1098/rstl.1825.0026 29. Meade N Islam Towhidul Forecasting in telecommunications and ICT-A review International Journal of Forecasting 2015 31 4 1105 1126 10.1016/j.ijforecast.2014.09.003 30. Hellenic Telecommunications and Post Commission (HTPC). (2015). HTPC’s Annual Reviews in Greek Electronic Communications and Postal Services Markets (2005–2015). http://www.eett.gr/opencms/opencms/EETT_EN/Journalists/MarketAnalysis/MarketReview/. 31. Hellenic Telecommunications Organization (OTE). (2016). OTE’s Annual reports (2012–2016). https://www.cosmote.gr/fixed/en/corporate/ir/publications/annual-reports. 32. Hellenic Telecommunications and Post Commission (HTPC). (2020). Market analysis. https://www.eett.gr/opencms/opencms/EETT/Electronic_Communications/TelecomMarket/MarketData.html. 33. Cartesian. Wholesale Local Access Market Review: NGA Cost Modelling, 2016. 34. Monath T Elnegaard NK Cadro P Katsianis D Varoutas D Economics of fixed broadband access network strategies IEEE Communications Magazine 2003 41 9 132 139 10.1109/MCOM.2003.1232248 35. Z Adamy. (2020) Changing the conversation: G.fast, the fiber extension. https://www.lightwaveonline.com/fttx/fttn-c/article/14184851/changing-the-conversation-gfast-the-fiber-extension.
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==== Front Int J Legal Med Int J Legal Med International Journal of Legal Medicine 0937-9827 1437-1596 Springer Berlin Heidelberg Berlin/Heidelberg 36507962 2926 10.1007/s00414-022-02926-7 Original Article Forensic age estimation in Barcelona: analysis of expert reports issued between 2011 and 2018 Taranilla Castro Ana Maria [email protected] 1 Pujol-Robinat Amadeo 12 Badía García Maria Angels 1 Milián Sebastià Sara 1 Martínez Alcázar Helena 1 Pomés Tallo Jaume 3 Oleaga Zufiría Laura 3 Xifró Collsamata Alexandre 12 1 Institut de Medicina Legal i Ciències Forenses de Catalunya, Barcelona, Spain 2 grid.5841.8 0000 0004 1937 0247 Facultat de Medicina i Ciències de La Salut, Universitat de Barcelona, Barcelona, Spain 3 grid.410458.c 0000 0000 9635 9413 Servei de Radiodiagnòstic, Hospital Clínic i Provincial de Barcelona, Barcelona, Spain 12 12 2022 18 20 10 2022 1 12 2022 © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Introduction In recent years, there has been a notable increase of migratory movements into Europe with the arrival of not (reliably) documented young individuals within EU-Member States. Accordingly, the need for forensic age assessments likewise increased in order to administratively differentiate along the legally relevant cut-off age of 18 completed years. The objective of our study was to analyse the expert reports of forensic age estimation issued in Barcelona between 2011 and 2018. Method In all cases, data on the medical history, physical examination, radiology of the left hand and orthopantomography were collected. In cases without third molars and a complete ossification of the hand, a CT scan of the clavicles was also performed. Results A total of 2754 expert reports were evaluated; 96.7% were males, the majority were of North African origin, mainly from Morocco (63.6%), and 19.6% were sub-Saharan Africans; 65.4% had a level of bone maturation corresponding to the last three standards of Greulich and Pyle. Most cases had mineralization of the third molar corresponding to the F, G or H stages of Demirjian. In 85.9%, there was a correspondence between bone and dental age. A total of 28.8% of the subjects were evaluated as being aged over 18 years; 86.2% of North Africans were considered to be younger than 18, and 82% of sub-Saharan Africans were considered to be over 18 years old. Conclusions In Barcelona, most of the subjects evaluated were male and North African, and 71.2% of the cases were considered to be minors. Keywords Forensic age estimation AGFAD recommendations Bone age Dental age Unaccompanied minors ==== Body pmcIntroduction Forensic age estimation is common within the field of forensic medicine, both in the living and in cadavers. The way in which this estimation is carried out is explained in the classic reference textbooks [1–3], but the procedure has greatly improved in recent years [4]. Since the early 1990s, the increase in migratory movements in Europe due to socio-economic problems, armed conflicts and other reasons, has led to a dramatic increase in requests for expert reports on forensic age estimation [5]. Allegedly doubtful minors must be evaluated because they lack documents proving their identity and thus their age, with an administrative objective. In most European countries, the relevant age limit for the compulsory protection of minors is 18 years [4, 6]. Due to its geographical location close to the African continent, Spain has experienced a particularly high influx of migrants in recent years. According to Eurostat data [7], from 2011 to 2018, Spain was among the top four countries in the European Community with the highest number of migrants welcomed (with 200 unaccompanied minors and 28,725 first-time applicants of subjects younger than 18 years), being second after Germany in the years 2016 to 2018, with a significant increase in cases in the years 2017 to 2019. According to a report of the State Attorney General’s Office for the year 2019, around 2000 files for age estimation were initiated per year in Spain from 2013 to 2015, 2971 in 2016, 5600 in 2017 and 12,152 in 2018 [8]. This implies a notable increase in the production of forensic age estimation reports in recent years in Spain, before the SARS-CoV-19 pandemic. Garamendi and López-Alcaraz recently published an article on the current situation in Spain regarding forensic age estimation reports, in which they described recent advances in the use of international protocols in many Spanish Institutes of Legal Medicine and Forensic Science [9]. Currently, the reference recommendations for forensic age estimation are those approved by the “Study Group on Forensic Age Diagnostics (AGFAD)” of the “German Society of Legal Medicine”, which was established in 2000 in Berlin and organizes an annual meeting of the group and a Proficiency Test that consists of correctly solving two practical expert cases [4, 10, 11]. The objective of these tests is to improve the quality of expert reports on forensic age assessment and to harmonize the approach in different countries [10–12]. In Spain, we follow the “Recommendations on methods of forensic age estimation in unaccompanied foreign minors. Consensus Document on Good Practices among the Institutes of Legal Medicine of Spain” (2010) [13], which are different to those of the AGFAD [4, 14]. From the legislative point of view, in Europe, article 25 of Directive 2013/32/EU specifies the path of commissioning medical age assessments by administrative authorities within asylum procedures and remarks that a medical assessment should only be performed in case of a doubtful minority allegation and not as a general evidence gathering in all minors [15]. Besides, in 2014, in Spain, the “Framework Protocol on certain actions in relation to Unaccompanied Foreign Minors” was published in the Official Gazette of the Spanish State, which regulates, among others, the performance of age estimation tests, following the previously mentioned Consensus Document [13, 16]. Here, we present the results of a review of the expert age estimation reports, issued in the city of Barcelona, from 2011 to 2018. Material and methods The forensic age estimation reports issued by the expert forensic doctors of the Institute of Legal Medicine and Forensic Sciences of Catalonia (IMLCFC) in the city of Barcelona, in the period between Jan 01, 2011 and Dec 31, 2018, were reviewed, most of them having been requested by the Juvenile Prosecutor’s Office in the province of Barcelona. In Spain, the Juvenile Prosecutor is also responsible for age assessments of unaccompanied minors who are not accused of any crime. They only requested us these reports when there was a doubt about the age of the subject. These reports were based on the standardized forensic age estimation protocol of the IMLCFC. We recorded sex, birth country, ethnic background, the reported age, nutritional information related to childhood, current or pre-existing diseases (especially those related to growth), medication and family diseases. The clinical examination included weight, height, constitutional type, calculated Body Mass Index, signs of sexual maturation (with specific consent) and dental examination to evaluate dental eruption, especially of the third molars. In all cases, an X-ray of the left hand and orthopantomography were performed. Before taking the radiographs, the subjects signed a written informed consent for these examinations, after being advised of the very improbable health risks. Those reports without a CT scan of the clavicles were signed by a specialized forensic physician. When a CT scan had to be evaluated, two experts signed the report. Cases of missing third molars in which a CT scan of the medial epiphysis of both clavicles had not been performed, incomplete reports and cases with severe dental pathology were discarded. Among a total of 2910 cases, 156 were excluded, leaving a final sample of 2754 cases. From these, we obtained data referring to the medical history, physical examination, results of the X-ray examination of the left hand according to the Greulich and Pyle standard (G-P) [17], the third molar mineralization according to the typology of Demirjian et al. [18] and in some cases the medial clavicular ossification on CT according to the Schmeling stages and Kellinghaus substages [19, 20]. All CT studies were performed on two Siemens Somatom Sensation 64 scanners and one Siemens Somatom go-Top 128 scanner. Subjects were placed in the supine position on the scanner table with their arms alongside their body. The FOV (field of view) used was 20 cm including both medial clavicular epiphyses. The thickness of the applied slice was 1 mm. A standard bone kernel was used for image reconstruction. Reconstructions of both medial clavicular epiphyses were performed in the axial, sagittal, and coronal planes, and the coronal epiphyses were reconstructed following the axis of the sternum. The images were reviewed in a bone window. For data processing, the Statistical Package for the Social Sciences (SPSS) 17.0 was applied. Descriptive statistics of all the variables were calculated, and an analysis of variance was performed to compare bone age (G-P) with dental maturation (Demirjian stage). Following the recommendations of the Spanish Consensus Document [13], we considered that a subject was at least 18 years old when the physical examination was compatible, the radiograph of the hand showed a standard of 18 or 19 years according to G-P and the orthopantomogram showed a third molar in Demirjian stage H, in the absence of developmental disorders. In doubtful cases or those without third molars with a complete ossification of the hand skeleton, a CT scan of the medial epiphysis of both clavicles was performed in axial and coronal projection. Accordingly, we do not totally follow AGFAD recommendations. The subject was considered older than 18 years when they had stage 3c, 4 or 5 of clavicular ossification according to the Schmeling stages and Kellinghaus substages [5, 19–21]. Results Of the 2754 cases studied, 2672 were requested by the Juvenile Prosecutor’s Office, 80 by an investigating court, one by a criminal court and one by a prison supervision court.Sociodemographic data: Figure 1 shows the number of cases per year and the considerable increase from 2016, with cases increasing to a maximum in 2018. In terms of sex, 96.7% were male. Over the years we studied, the percentage of women ranged from 1.2% (2011) to 5.8% (2014). Regarding the birth countries, it stands out that more than half came from Morocco (Table 1). By geographical area, 72% were from North Africa, 19.6% were sub-Saharan African, 6.5% Asian, 1.5% European and 0.4% “other” (8 from Chile, 1 from Cuba and 1 from Haiti). Figure 2 shows the distribution by geographical area over the years, highlighting that 2011 was the only year in which sub-Saharan Africans predominated (Fig. 2). Physical examinations: We did not identify any cases with developmental disorders. 62% of the subjects consented to evaluate the assessment of sexual maturity signs. Findings of radiology: The results of the radiographs of the left hand are detailed in Table 2, which highlights that 65.4% corresponded to the last three standards of G-P [17]. Review of these data for the two main geographical areas revealed that the 18- and 19-year-old standards predominated among sub-Saharans, whereas the 16- and 17-year-old standards predominated among the North Africans (Fig. 3). The Demirjian stage of the third molar is presented in Table 3; most of the cases were in stages F, G and H [18]. Considering only the two main geographical areas, we observed the predominance of stages G and H among sub-Saharans and stages D, E, F and G in North Africans (Fig. 4). Fifteen CT studies of the medial epiphysis of both clavicles were performed (Table 4), most of them due to the absence of third molars, except for two that were ordered directly by the judicial authority. Figure 5 shows the relationship between the result of the X-ray examination of the hand and the mineralization stage of the third molar in our series. A high correlation between bone and dental maturation (p < 0.001) was observed. Bone age (classified as ≥ 18 years if we had obtained a G-P standard in the hand radiograph of 18 or 19 years, or < 18 years if we had evaluated another standard) was related to dental age (classified as ≥ 18 years if we had recorded a Demirjian H stage in the third molar, or < 18 years if we had recorded an A-G stage). Concordance was found between the results of the two tests in 85.9% of cases. In cases of discrepancy, there was more often complete bone maturation and incomplete dental mineralization (Fig. 6). Conclusions of the expert reports: A total of 71.2% of the individuals were assessed as being under 18 years old (28.8% were older than 18 years). By geographical area, 86.2% of North Africans, 18% of sub-Saharans, 80.9% of Caucasians, 61.2% of Asians and 100% of others were considered younger than 18 years old. Fig. 1 Number of forensic age estimation reports issued each year Table 1 Distribution of cases by country of origin Country of origin Number Per cent Morocco 1753 63.65 Algeria 210 7.63 Ghana 147 5.34 Guinea Conakry 104 3.78 Pakistan 77 2.80 Gambia 67 2.43 Mali 44 1.60 Senegal 41 1.49 Afghanistan 30 1.09 Nigeria 30 1.09 Ivory Coast 27 0.98 Viet Nam 23 0.84 Cameroon 20 0.73 Other countries 181 6.57 Total 2754 100 Fig. 2 Distribution of cases by geographical area over the studied period Table 2 X-ray examination of left hand (G-P*) G-P (years) Number Per cent 10 1 0.04 11 5 0.18 11.5 1 0.04 12 2 0.07 12.5 12 0.44 13 37 1.34 13.5 28 1.02 14 193 7.01 15 228 8.28 15.5 86 3.12 16 352 12.78 16.5 8 0.29 17 685 24.87 18 450 16.34 19 666 24.18 Total 2754 100 *Greulich and Pyle Fig. 3 Bone maturation in the two predominant populations (G-P standards) Table 3 Third molar Demirjian stage Demirjian stage Number Per cent A 1 0.04 B 2 0.07 C 12 0.44 D 347 12.60 E 378 13.73 F 534 19.39 G 627 22.77 H 842 30.57 Absence of third molars 11 0.40 Total 2754 100 Fig. 4 Demirjian stages of the third molar in the two predominant populations Table 4 Findings of the cases in which clavicle CT was performed (n = 15) Country Geographical areas Hand x-ray (G-P) (years) Orthopantomogram (third molar’s Demirjian stage) Clavicle CT (Schmeling stage and Kellinghaus substage) Medicolegal assessment (> 18 years or < 18 years) Guinea Conakry Sub-Saharan 19 38H 5  > 18 years Afganisthan Asian 19 Third molars missing 3c  > 18 years Morocco North African 19 Third molars missing 3a  < 18 years Morocco North African 15.5 Third molars missing 1  < 18 years Morocco North African 19 38H 3c  > 18 years Algeria North African 19 Third molars missing 3c  > 18 years Algeria North African 19 Third molars missing 3c  > 18 years Morocco North African 18 Third molars missing 3c  > 18 years Morocco North African 19 Third molars missing 3c  > 18 years Morocco North African 19 Third molars missing 2a  < 18 years Algeria North African 19 Third molars missing 2b  < 18 years Guinea Conakry Sub-Saharan 19 Third molars missing 2b  < 18 years Morocco North African 19 38 missing. 48H 3c  > 18 years Albanian European 18 38 and 48 missing 2c  < 18 years Morocco North African 19 Third molars missing 3b  < 18 years G-P Greulich and Pyle Fig. 5 Correlation between bone maturation and third molar mineralization Fig. 6 Relationship between bone and dental age results (N = 2754) Discussion We reviewed 2754 forensic age estimation reports issued in Barcelona over 8 years (2011–2018). This is similar in number to the Hamburg series, which included 2578 cases in the period from 2009 to 2015 [12]. Most of the subjects were male (96.7%), and the percentage remained fairly stable throughout the period studied. Other series were also dominated by men: in Berlin (91%) [22] and Münster (91.8%) [23], and in Danish (93.1%) [24] and French series (97.7%) [25]. In our series, 91.6% came from the African continent. Of the total, Moroccans (63.6%) and sub-Saharans (19.6%) predominated; the majority were sub-Saharan (56.2% of a total of 249) only in 2011. In Spain, there has been a progressive increase in cases from 2016, with a maximum in 2018, reflecting the massive increase in immigration [26], a pattern analogous to that observed in our series. In the Finnish series [27], an increase in cases was observed in 2015 (149 cases) compared to previous years. In the Münster series [23], there was an increase in the number of reports in 2015, a subsequent decrease and a further increase in 2018, although the number of immigrants recorded this year was clearly lower than in 2016. These differences could be explained by the origin of the migratory flow. In Barcelona, 72% of the subjects came from North Africa, 19.6% were sub-Saharan, and 6.5% were Asian (includes individuals from Middle Eastern countries). Morocco was the prevailing country of origin in our study, which reflects its proximity to Spain as a country providing access to Europe. In contrast, in Finland, most came from Afghanistan, Iraq and Somalia [27]; in Berlin, from 1992 to 2000, the main countries of origin were Vietnam, Romania, Lebanon, Bangladesh and Turkey [22]; and in Münster, Asian subjects predominated between 2009 and 2016, whereas sub-Saharans predominated in 2017 and 2018 [23]. In contrast, in Montpellier, 80.4% of the cases evaluated were sub-Saharan [25]. Of the total number of cases included, 40.5% had a G-P standard of 18 or 19, unlike in the Danish series, in which almost all cases (91.4%) had a G-P standard of 18 or 19 [24]. In the majority of our series (85.9%) and in all the populations studied, there was a strong correlation between the results of bone age and dental age, as it was explained previously. When there was a discrepancy between the results, it was more frequent to find complete bone maturation and incomplete dental mineralization. The correlation between these two parameters was also evaluated in the Danish series, with a correlation in 94% of cases; in most of the cases where there was no correlation, dental age was greater than bone age, unlike in our series [24]. The difference between our protocol [13] and the AGFAD protocol [4, 5] is that in the AGFAD, a CT scan of the clavicles is performed in all cases in which the ossification of the hand is complete [28], as carried out by the working groups of Rudolf et al. [29], Hagen et al. [23] and Lossois et al. [25]. We performed 15 CT scans of the clavicles, and in all cases, the scan allowed us to estimate the forensic age beyond reasonable doubt [5]. Obviously, in our fourth CT case (Table 4), the CT was wrongly indicated because the X-ray hand was not completely ossified. It was a mistake by an inexpert forensic physician on duty at the beginning of the period using the CT in our institute. Identifying that error has allowed us to prevent it from happening again. The objective test that an individual has reached the age of 18, without doubt, is the presence of stage 3c, 4 or 5 ossification on the CT scan of the clavicles [5, 20, 21, 23, 30]. However, only 12 of 30 European countries use radiology of the clavicles in forensic age studies [23, 31]. In Spain, the Consensus Document [13] mentions the possibility of performing a CT scan of the clavicles as an option in doubtful cases, or in a population that has not been well studied, if the X-ray of the hand indicates a bone age ≥ 18 years; the importance of keeping in mind the radiation dose of the examinations, of medically assessing its indication and not repeating tests, is also emphasized. Following Schmeling, the radiation required to perform an X-ray of the hand is 0.0001 mSv, and for an orthopantomography, it is 0.026 mSv [4], which are considered almost completely harmless doses [32]. The irradiation required for a CT of the proximal end of the clavicles would be about 0.6–0.8 mSv [32], but this amount would be much lower than the annual natural radiation dose in Germany, with averages 2.1 mSv and in some regions up to 2.6 mSv per year [4, 33, 34]. That is, the radiation doses necessary to perform radiological tests for forensic age estimation are below the radiation exposures of daily life [33, 34]. Therefore, in cases where a clavicular CT scan is indicated, if it is performed by expert radiologists and in subjects around the age of 18 years or older, it can be performed with virtually no risk [32]. In 2003, Schmeling et al. reviewed 247 age assessments, performed in Berlin, which were based on history, physical examination, hand X-ray, orthopantomography and in some cases on clavicle X-ray. They obtained an error of ± 12 months in the 45 subjects whose ages were verified [22]. In other series, such as the Finnish and Danish series, the clavicle was not evaluated. In the Finnish work, forensic age assessment from 2005 to 2015 was based on hand radiography and orthopantomography [27], and in the 2012 Danish series, it was based on physical examination (without clinical dental assessment), hand radiography and dental radiographs (orthopantomography and third molar intraoral radiographs) [24]. As in our work, the 2017 Hamburg study limited CT scan of the clavicles to doubtful cases. However, it differed in that orthopantomography was performed first, and this test carries a lot of weight; if it was not conclusive, an X-ray of the hand was performed, which helped to calculate the minimum age if the subject was less than 18 years old. They only performed a CT scan of the clavicles when the third molars were missing or the two radiographic tests give quite different results [12]. Therefore, in these three publications, they do not follow the AGFAD recommendations. The combination of physical examination, hand radiography and orthopantomography was recommended in the Moroccan population by Garamendi et al. in 2005 [35] to avoid false positives of people over 18 years old (underage subjects considered as older, which would be an ethically unacceptable error), despite increasing the number of false negatives (older subjects evaluated as minors). Using the two tests, we ensured a very high probability that the subject was over 18 years old, as corroborated in the Hamburg study [12]. However, in the sub-Saharan population, we know that the minimum age of a subject with a lower third molar in stage H is 17.3 years [36], and therefore, in these cases, when the ossification of the hand is complete, a clavicular CT scan should be performed [4, 5]. In any case, we believe that the percentage of error in these cases is very low, since a recent meta-analysis of the mineralization of the third molar in 19,690 subjects of all ethnic groups confirmed that the percentage of false positives was very low, at 3.1% [37]. Likewise, in the recent work by Lossois et al., in which 80.4% of the subjects evaluated were sub-Saharan, 89% of the orthopantomographies performed found a Demirjian H stage in the third molars and, given that they followed the AGFAD recommendations for forensic age estimation (a clavicular CT scan was performed in all cases with complete ossification of the hand), they concluded that 95.85% of the cases studied were most likely at least 18 years old [25]. The difference between the high number of CT studies performed in Münster and Austria [23, 29], compared to the few or lack of CT studies performed in Hamburg, Denmark, Finland, Sweden and Barcelona [12, 24, 27, 38], can be attributed to the high radiation exposure and cost, and lack of therapeutic purposes. On the other hand, in Sweden [38], forensic age estimation is based on MRI of the knee and radiographic study of the third molar in the mandible, in which subjects who have completed maturation in one or the two tests are assessed as adults (Schmeling et al. stage 4 or 5 in the knee or Demirjian stage H in the lower third molar); however, the authors considered that around 33% of juvenile males were erroneously classified as adults. These results exemplify the importance of reducing the ethically unacceptable error highlighted by Garamendi et al. in 2005 [35], in the sense of minimizing to the maximum the number of minors misclassified as adults. In our sample, 28.8% of individuals were assessed as older than 18 years, whereas in the Münster series, Hagen et al. reported that 74.5% of the subjects had most probably reached the age of majority [23]. These results also differ from the Finnish study conducted in 2015, which concluded that 28% of their series were minors, although in 11% of cases, the results were inconclusive [27]. In the Danish series, 80% were assessed as being older than 18 years, bearing in mind that the authors accepted a risk of age overestimation, although it was low, by not using a clavicle scan [24]. In the Austrian series, 61% were considered older [29] and in the French series [25], 95.85% were considered older than 18 years. One of the limitations of our work is that it was a retrospective study, although it should be noted that the assessment and reporting protocol of the IMLCFC and the Spanish Consensus Document [13] was followed in all the cases we included. Probably the number of subjects classified as minors is too high because we try to avoid ethically unacceptable errors (minor subjects classified as adults), and that is the reason that some adults have probably been considered as minors [35]. Another limitation is the assessment method, which did not include a CT scan of the clavicles in subjects where skeletal development of the hand was completed, that is, we do not totally follow the AGFAD recommendations. In conclusion, in our large sample of forensic age estimation reports issued in Barcelona, the vast majority were male and of North African origin (especially from Morocco), and 71.2% of cases were estimated to be minors. The majority (86.2%) of North African subjects were minors whereas the majority of sub-Saharans (82%) were considered to be over 18 years old. We really suggest modifying our current protocol and adapting it to AGFAD recommendations [4, 5, 10] as well as applying the minimum age concept in all cases [4, 5, 14]. Acknowledgements We thank Mrs. Cèlia Rudilla and Mrs. María Luisa Caro from the library of the Institute of Legal Medicine and Forensic Sciences of Catalonia for their help in the bibliographic review. Declarations This retrospective study conducted with human participants was conducted in accordance with the 1964 Declaration of Helsinki and its latest amendments or comparable ethical standards. The study was approved by the “Research Ethics Committee of the Hospital Universitari de Bellvitge”, L’Hospitalet de Llobregat (Barcelona) (PR286/22). All the procedures carried out were part of the daily expert practice requested by the Prosecutor’s Office or judicial authorities. Conflict of interest The authors declare no conflict of interest. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Simonin C Medicina Legal Judicial 1962 Barcelona Editorial Jims 2. GisbertCalabuig JA Medicina Legal y Toxicología. Fundación García Muñoz 1977 Valencia Sección SABER 3. Simpson K Forensic Medicine 1979 8 London Edward Arnold 4. Schmeling A Dettmeyer R Rudolf E Vieth V Geserik G Forensic Age Estimation. Methods, Certainty, and the Law Dtsch Arztebl Int 2016 113 44 50 10.3238/arztebl.2016.0044 26883413 5. Schmeling A Forensic age assessment Rev Esp Med Leg 2019 45 4 163 169 6. Jayaraman J Roberts GJ Wong HM McDonald F King NM Ages of legal importance: implications in relation to birth registration and age assessment practices Med Sci Law 2016 56 77 82 10.1177/0025802415590172 26101440 7. Eurostat asylum statistics. https://ec.europa.eu/eurostat/web/migration-asylum/international-migration-citizenship. Accessed 10 Aug 2022 8. Memoria elevada al Gobierno de S.M. Fiscalía General del Estado (2019) [página en internet]. https://www.fiscal.es/memorias/memoria2020/FISCALIA_SITE/index.html. Accessed 10 Aug 2022 9. Garamendi González PM López-Alcaraz M Situación actual de la estimación forense de la edad en menores extranjeros no acompañados en España Rev Esp Med Legal 2019 45 133 135 10. Arbeitsgemeinschaft für Forensische Altersdiagnostik. (AGFAD). http://agfad.uni-muenster.de/agfad_start.html. Accessed 10 August 2022 11. Schmeling A Fuhrmann AW Lockemann U Geserick G Qualitätssicherung von Altersgutachten. 10. Ringversuch der Arbeitsgemeinschaft für Forensische Altersdiagnostik Rechtsmedizin 2013 23 22 28 10.1007/s00194-012-0859-0 12. Mansour H Fuhrmann A Paradowski I Jopp E Püschel K The role of forensic medicine and forensic dentistry in estimating the chronological age of living individuals in Hamburg, Germany Int J Legal Med 2017 131 593 601 10.1007/s00414-016-1517-y 28032243 13. Garamendi González PM Bañón González R PujolRobinat A Aguado Bustos FF LandaTabuyo MI Prieto Carrero JL Recomendaciones sobre métodos de estimación forense de la edad de los menores extranjeros no acompañados. Documento de Consenso de Buenas Prácticas entre los Institutos de Medicina Legal de España (2010) Rev Esp Med Legal 2011 37 1 22 29 14. Schmeling A Rudolf E Madea B Medical age assessment in living individuals Handbook of Forensic Medicine, 3 2022 Chichester Wiley 1027 1053 15. Directive 2013/32/EU of the European Parliament and of The Council, of 26 June 2013, on common procedures for granting and withdrawing international protection (recast). Official Journal of the European Union, 29 June 2013, L 180/60, 60–95 16. Ministerio de la Presidencia. Resolución de 13 de octubre de 2014, de la Subsecretaría, por la que se publica el Acuerdo para la aprobación del Protocolo Marco sobre determinadas actuaciones en relación con los Menores Extranjeros No Acompañados. BOE. Núm. 251. 16 de octubre de 2014. 83.894–83.919 17. Greulich WW Pyle SI Radiographic atlas of skeletal development of the hand and wrist 1959 2 California Stanford University Press 18. Demirjian A Goldstein H Tanner JM A new system of dental age assessment Hum Biol 1973 45 211 227 4714564 19. Schmeling A Schulz R Reisinger W Mühler M Wernecke K-D Geserick G Studies on the time frame for ossification of medial clavicular epiphyseal cartilage in conventional radiography Int J Legal Med 2004 118 1 5 8 10.1007/s00414-003-0404-5 14534796 20. Kellinghaus M Schulz R Vieth V Schmidt S Pfeiffer H Schmeling A Enhanced possibilities to make statements on the ossification status of the medial clavicular epiphysis using an amplified staging scheme in evaluating thin-slice CT scans Int J Legal Med 2010 124 321 325 10.1007/s00414-010-0448-2 20354711 21. Kellinghaus M Schulz R Vieth V Schmidt S Schmeling A Forensic age estimation in living subjects based on the ossification status of the medial clavicular epiphysis as revealed by thin-slice multidetector computed tomography Int J Legal Med 2010 124 149 154 10.1007/s00414-009-0398-8 20013127 22. Schmeling A Olze A Reisinger W König M Geserick G Statistical analysis and verification of forensic age estimation of living persons in the Institute of Legal Medicine of the Berlin University Hospital Charité Leg Med 2003 5 S367 S371 10.1016/S1344-6223(02)00134-7 23. Hagen M Schmidt S Schulz R Vieth V Ottow C Olze A Forensic age assessment of living adolescents and young adults at the Institute of Legal Medicine, Münster, from 2009 to 2018 Int J Legal Med 2020 134 745 751 10.1007/s00414-019-02239-2 31907616 24. Larsen ST Arge S Lynnerup N The Danish approach to forensic age estimation in the living: how, how many and what’s new? A review of cases performed in 2012 Ann Hum Biol 2015 42 342 347 10.3109/03014460.2015.1044469 26286458 25. Lossois M Cyteval C Baccino E Peyron PA Forensic age assessment of alleged unaccompained minors at the Medicolegal Institut of Montpellier: a 4-year retrospective study Int J Legal Med 2022 136 853 859 10.1007/s00414-022-02813-1 35278098 26. Niños migrantes no acompañados. Unicef. 2021. https://www.unicef.es/ninos-migrantes-no-acompanados. Accessed 11 August 2022 27. Metsäniitty M Varkkola O Waltimo-Sirén J Ranta H Forensic age assessment of asylum seekers in Finland Int J Legal Med 2017 131 243 250 10.1007/s00414-016-1498-x 27885431 28 Schmeling A Grundmann C Fuhrmann A Kaatsch HJ Knell B Ramsthaler F Criteria for age estimation in living individuals Int J Legal Med 2008 122 457 60 10.1007/s00414-008-0254-2 18548266 29. Rudolf E Kramer J Gebauer A Bednar A Recsey Z Zehetmayr J Standardized medical age assessment of refugees with questionable minority claim - a summary of 591 case studies Int J Legal Med 2015 129 595 602 10.1007/s00414-014-1122-x 25410091 30. Wittschieber D Schulz R Vieth V Küppers M Bajanowski T Ramsthaler F The value of sub-stages and thin slices for the assessment of the medial clavicular epiphysis: a prospective multi-center CT study Forensic Sci Med Pathol 2014 10 163 169 10.1007/s12024-013-9511-x 24277267 31. European Asylum Support Office (EASO) (2018) Practical guide on age assessment. Publications Office, 2nd edn. https://www.easo.europa.eu/sites/default/files/easo-practical-guide-on-ageassesment-v3-2018.pdf. Accessed 11 August 2022 32. Ramsthaler F Proschek P Betz W Verhoff MA How reliable are the risks estimates for X-ray examinations in forensic age estimations? A safety update Int J Leg Med 2009 123 199 204 10.1007/s00414-009-0322-2 33. Meier N Schmeling A Loose R Vieth V Altersdiagnostik und Strahlenexposition Rechtsmedizin 2015 25 30 33 10.1007/s00194-014-1005-y 34. Schumacher G, Schmeling A, Rudolf E (2018) JRC Science for Policy Report. Medical Age Assessment of Juvenile Migrants. An analysis of age marker-based assessment criteria. Publications Office of the European Union,Luxembourg.https://www.publications.jrc.ec.europa.eu/repository/bitstream/JRC1092. Accessed 15 August 2022 35. Garamendi PM Landa MI Ballesteros J Solano MA Reliability of the methods applied to assess age minority in living subjects around 18 years old: a survey on a Moroccan origin population For Sci Int 2005 154 3 12 36. Olze A Van Niekerk P Schulz R Ribbecke S Schmeling A The influence of impaction on the rate of third molar mineralisation in black Africans Int J Legal Med 2012 126 869 874 10.1007/s00414-012-0753-z 22885908 37. Haglund M Mörnstad H A systematic review and meta-analysis of the fully formed wisdom tooth as a radiological marker of adulthood Int J Leg Med 2019 133 231 239 10.1007/s00414-018-1842-4 38. Mostad P Tamsen F Error rates for unvalidated medical age assessment procedures Int J Legal Med 2019 133 613 623 10.1007/s00414-018-1916-3 30219926
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==== Front Int J Technol Des Educ Int J Technol Des Educ International Journal of Technology and Design Education 0957-7572 1573-1804 Springer Netherlands Dordrecht 9801 10.1007/s10798-022-09801-x Article Effects of association interventions on students’ creative thinking, aptitude, empathy, and design scheme in a STEAM course: considering remote and close association http://orcid.org/0000-0002-6936-1977 Zhan Zehui [email protected] 13 Yao Xiao 12 Li Tingting [email protected] 1 1 grid.263785.d 0000 0004 0368 7397 School of Information Technology in Education, South China Normal University, 510631 Guangzhou, P.R. of China 2 Shenzhen Fuyuan School, 510970 Shenzhen, P.R. of China 3 grid.419897.a 0000 0004 0369 313X Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, 510631 Guangzhou, P.R. of China 12 12 2022 123 2 12 2022 © The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. One of the primary goals of STEAM education is to equip students with the capability of creativity to solve problems. Creativity is believed to be closely related to the ability of making remote associations and combining unrelated concepts. This article explored the effects of three kinds of association interventions (i.e., remote association, close association, free association) on students’ creative thinking, creative aptitude, empathy, and design scheme. A total of 94 middle school students participated in the study and were assigned to three groups: the experiment group 1 (n = 30) used remote association and experiment group 2 (n = 32) used close association, the control group (n = 32) used free association (brainstorming) to complete the STEAM integration design projects respectively. Creative Thinking Test, Williams Creativity Aptitude Test (WCAT), Basic Empathy Scale (BES), design ideas, and interviews of students become source data for analysis. Results indicated that both remote and close association were effective strategies in promoting creativity in the STEAM course. However, students in the remote association group achieved a significantly higher degree of creative thinking. While students in the close association group significantly outperformed the remote association group on creativity aptitude and quality of design ideas. No significant difference was found among the three association conditions in students’ degree of empathy. The findings highlight the different effects of remote and close association for creativity cultivation in STEAM education. Keywords STEAM Education Creativity Remote Association Close Association Association intervention http://dx.doi.org/10.13039/501100012576 Major Projects of Guangdong Education Department for Foundation Research and Applied Research 2017WZDXM004 Zhan Zehui the Major Project of Social Science in South China Normal UniversityZDPY2208 Zhan Zehui ==== Body pmcIntroduction As one of the official 21st century skills, creative thinking is central to the arts, sciences, and daily life (Beaty, Benedek, Silvia & Schacter, 2016), and it has aroused tremendous attention in recent years (Lin et al., 2022). Taking the form of originality and usefulness (Mednick, 1962), creativity is the fountainhead of human civilizations, as all progress and innovation depend on our ability to change existing thinking patterns, break with the present, and build something new (Dietrich & Kanso, 2010; Zhan et al., 2022). Kaufman (2016) also claimed that people who value creativity may point to its role in most things that define our civilization. In the field of psychology, associative ability has an important impact on creativity (Mednick, 1962). Association intervention can be an effective method to foster creative idea generation (Acar, Runco & Park, 2020; Benedek et al., 2020; Green et al., 2015; Prabhakaran et al., 2014; Said-Metwaly et al., 2020). The association stimulus that is not closely related to the target object may be an effective enabler of successful creative idea generation as it contributes to promoting uncommon ideas by reducing the tendency to produce high-frequency ideas (Gupta et al., 2012). However, although great importance nowadays has been attached to fostering creative thinkers through STEAM education, there has been limited research on how to inspire and evaluate students’ creative thinking during the STEAM learning process. Studies generally emphasized that cross-disciplinary, or interdisciplinary/multidisciplinary education, is of great value in promoting the cultivation of students’ creativity ability (Bevan, 2017; Harris & De Bruin, 2018; Li & Zhan, 2022; Tan, 2014; Wilson et al., 2021), there is only little evidence based on empirical studies to confirm the practical effects (Conradty & Bogner, 2019; Perignat & Katz-Buonincontro, 2019; Shen et al., 2021; Timotheou & Ioannou, 2021; Wilson et al., 2021). In addition, it tends to focus on the hands-on works or tools application but lacks attention to students’ thinking process and creative idea generation (Blikstein, 2013; Conradty & Bogner, 2019). Without targeted creative thinking training and guidance, it is difficult for students to generate innovative ideas and put them into practice (Wu et al., 2022). The methods for inspiring and evaluating students’ creativity in STEAM courses are in urgent need of development. Empirical exploration is also needed to explore the effect of association intervention targeting at creative idea generation. Literature Review Creativity and association Creativity is frequently associated with originality, novelty, invention, appropriateness, imagination, etc. (Kaufman, 2016; Runco, 2014). According to existing research, there’s no universally agreed-upon definition for creativity. Representative researchers have studied the core concepts related to creativity, which focused mainly on two key determinants: originality and usefulness (Kaufman, 2016; Runco & Jaeger, 2012). In other words, the uniqueness and value orientation of creativity was emphasized respectively (Kaufman 2016; Simonton, 2012). For example, creative products must be both novel and appropriate (or useful), and not simply random responses (Prabhakaran, Green, & Gray, 2014). Except for originality and usefulness, ‘high quality’ was also suggested to be a third component of creativity(Sternberg et al., 2002). The essence of creative thinking was claimed to be closely related to association, which is a mental process that occurs when imagination is triggered by an indirectly-related target. Correspondingly, association intervention is a pedagogical approach adopting associations to exert influence on students’ mental association activity and imagination process in a planned way step by step towards the expected goal. According to the approach of launching associations, the association interventions can be classified into three categories (i.e., remote association, close association, and free association). Remote Association Intervention refers to the approach of using far-distance or irrelevant concepts as stimuli to trigger meaningful associations. Correspondingly, Close Association Intervention refers to the approach of using closely-related concepts as association stimuli, which can be an object that is obviously related to the target object or has similar or extended attributes for transfer. Both remote and close associations belong to compulsory associations that require students to think with a certain stimulus, and they are set up according to the semantic correlation distance between the associated source and target objects (Mednick, 1962). Whereas, free association allows students to think freely, and does not require compulsory stimuli. According to Mednick’s (1962) remote association theory, the creative thinking process was explained as the forming of associated elements into new combinations which either meet specified requirements or are in some way useful. The ability to use associations lies at the heart of creativity, and the structure and strength of participants’ associative hierarchies impact individual responses in making remote associations and fruitfully combining unrelated concepts (Benedek et al., 2020; Prabhakaran, Green, & Gray, 2014). Less creative individuals were regarded as having steep associative hierarchies in that the activation of one concept (e.g., milk) prompts the activation of mainly closely associated concepts (e.g., white, tea), while highly creative people have flat associative hierarchies also activate weakly associated concepts (e.g., exploit) (Abraham, Rutter, Bantin, & Hermann, 2018). Mednick (1962) also suggested the remote associates test (RAT) as a way of testing for individual differences in creativity, which laid the foundation for subsequent studies related to creativity. Some studies focused on the ability of people with different levels of creativity to recognize remote associations and close associations. Gruszka & Necka (2002) carried out an empirical study on examining the acceptance of remote and close association, in which participants were supposed to decide whether pair words presented to them were either close associations or remote associations. It appeared that participants were more inclined to accept close rather than remote associations, and they also needed more time to make their decisions in the remote rather than in the close condition. Furthermore, creative people acknowledged the connection between two words more frequently, particularly in the remote condition, when remote associations were preceded by neutral primes and, to some extent, when close associations were preceded by positive primes. Wu et al., (2016) studied the Mandarin speakers’ performance between remote and close association through the Chinese Remote Associates Test (CRAT). Results indicated the correct rate of close association was significantly higher than that of the remote association, and remote and close associations work differently as patterns in the brain network. Others studied the individual difference of associative ability while completing word-generation association tasks. In the verbal fluency tasks, participants’ responses were analyzed by means of latent semantic analysis (LSA) and scored for semantic distance as a measure of associative ability, and results provided support for the notion that both associative and executive processes underlie the production of novel ideas (Beaty et al., 2014). Some studies looked at the deliberate training of associations targeted at creative idea generation. Creativity is no longer being portrayed as a mysterious, elusive force (Runco, 2012). The generation of associations can occur either via spontaneous, free-associative or goal-directed, controlled mechanisms (Beaty et al., 2014; Benedek & Jauk, 2018; Sowden, Pringle, & Gabora, 2015). Usually, the spontaneous association occurs as an implicit, unconscious, bottom-up driven cognition during real everyday problem solving (Abraham et al., 2012). Free association reflects the basic spreading of activation in semantic networks, whereas controlled association generation reflects a goal-directed process of constrained recall considering specific search cues (Benedek et al., 2020). Supported by analogies between ideas generation and atoms combination, Martindale (2007) argued that the probability of having a creative idea was related in an inverted-U fashion to the degree that cognition was primordial in nature. Having a flat associative hierarchy, defocused attention or cognitive disinhibition allows access to more remotely associated concepts, thus it increases the likelihood of the generation of more unusual and original ideas (Abraham et al., 2018). Appropriate association intervention may affect the stimulation of creativity. In one study, participants were instructed to say a verb upon seeing a noun displayed on a computer screen and were cued to respond creatively to half of the nouns (Prabhakaran et al., 2014). Results (from latent semantic analysis, LSA) showed that semantic distance was higher in the cued than in the uncued condition, suggesting that untrained participants were able to modulate their word production effectively, and do so on demand. Evidence of this strategy can also be gleaned from the findings of another similar fMRI study (Green et al., 2015). In the verb-generation task, participants generated verbs that were more semantically distant from noun prompts when they were cued to think creatively. The large effect size elicited by this creativity cue extended previous evidence that creativity cues can enhance creative state. Benedek et al. (2020) designed three adjectives stimuli association tasks, requiring the generation of either (a) common associations (highly related concept to a given adjective, e.g., red: blood), (b) original associations (remotely related concept to a given adjective, e.g., red: ketchup stain), or (c) bi-associations ( two adjectives were presented and participants should find a concept that is semantically related to both cues and links them in an original way, e.g., red - round: clown nose). The concept generated needed to be a semantically related noun (either a single or multi-word term). Compared with the common association task, results showed that the original association task elicited more creative association responses. Their findings confirmed that the explicit instruction to “be creative” increases the creativity of responses. In one meta-analytic review, Acar, Runco & Park, 2020 reviewed 31 studies that compared the explicit instructions emphasizing creativity, originality, and quality to quantity. Results indicated that creativity and quality instructions increased performance on divergent thinking when added to quantity instructions, more than quantity instructions alone, while the originality instructions did not change divergent thinking performance. Therefore, explicit instructions may increase or decrease divergent thinking performance, depending on which alternative explicit instructions were used and how they were presented. Another instruction meta-analysis also revealed that explicit (vs. standard) instructions significantly enhanced creative performance (Said-Metwaly et al., 2020). This kind of “thinking cap” (i.e., to try and succeed at thinking more creatively) phenomenon is of broad importance for education and rich mental life (Green et al., 2015). It is also commonly experienced in some analogical reasoning activities, for example, creativity cues were used for open-ended analogical reasoning in a novel “Analogy Finding Task” and achieved positive effects (Weinberger et al., 2016). In the online test, participants were asked to seek valid analogical connections among the word-pairs matrix, assessed by the semantic distance and number of analogies identified. Findings showed that when explicitly instructed to think creatively or receiving proper creativity cues, participants could successfully elicit better creative state and perform more creative analogies. Together, these studies provided evidence that humans have an impressive potential to improve their creative state through deliberate effort. Among these studies, associations played a significant role in triggering transfer (Mednick, 1962), analogical reasoning (Green et al., 2012), divergent thinking (Nusbaum, Silvia & Beaty, 2014), dynamic conscious augmentation of creative state (Green et al., 2015), creative cognition (Beaty et al., 2014; Weinberger et al., 2016), and the production of novel ideas and solutions (Vendetti, Wu & Holyoak, 2014; Benedek et al., 2020). However, there is limited research further examining the effect of different types of association interventions, and that is one of the goals of this study. STEAM Education and Creativity There is a growing body of studies that suggested the many ways in which STEAM can motivate and support learners’ purposeful activity, and facilitate their development of creative thinking (e.g., Harris & De Bruin, 2018; Runco, 2014; Wilson et al., 2021). Although creative thinking (or creativity) was mentioned frequently in articles as an outcome of STEAM, there is a lack of describing or further expansion upon the ways in which creativity is developed, practiced, or fostered through STEAM education (Perignat & Katz-Buonincontro, 2019). In fact, some articles only provided experiential or conceptual descriptions of creativity in STEAM education (e.g., Harris & De Bruin, 2018), few articles have reported creativity as a measured outcome. For example, Wilson et al., (2021) conducted empirical comparison research in elementary and secondary schools, and found that students in the STEAM group reported a significant growth in their understanding of creative thinking, and also described more creative examples when solving problems. In the STEAM courses, Shen et al., (2021) examined the influence of teacher feedbacks on students’ creativity in 3D-printing performances, and found that brain-storming helped students to generate new ideas. According to the data collected from the Eugene Creativity Scale, the creativity score of the ‘teacher suggestions feedback group’ (teacher provided detailed instructions for students’ ideas) was significantly higher than the ‘teacher opinions feedback group’ (teacher only gave opinions feedback, such as your idea is good) and the ‘non-feedback group’ (no feedback was given to the students). Timotheou & Ioannou (2021) analyzed the video data and robot artifacts of primary school students, and their results showed that STEAM making activities can enact the development of collective creativity. A different result was also reported. Conradty & Bogner’s (2019) research showed that students’ creativity was not affected by a short-term STEAM intervention. In the four-hour science inquiry lesson, high school students participated in the workstation to explore the bird flight related scientific phenomena. Finally, results showed that the STEAM module produced long-term knowledge and built stable scores of intrinsic motivations, but not self-reported aspects of creativity. There was an overall lack of measured learning outcomes in the areas of improved creativity (Perignat & Katz-Buonincontro, 2019), let alone specific strategies that focus on the stimulation of creative idea generation. Educators often favor well-structured lessons, recipe-style-learning laboratory work, with a controlled time frame for learning activities, yet without giving creativity space to develop (Conradty & Bogner, 2019). STEAM activities rely on kits with step-by-step instructions to constrain the creative design of works and seek multiple ways of solving problems. Besides, STEAM provides learning environments rich in tools, materials, and technologies, but an emphasis on tools causes the risks of blindly indulging in the tools and obscure fully participatory and interest-driven learning (Bevan, 2017). Some also cautioned about the danger of sheer ability to design and turn out, using tools, a vast number of ‘products’ risks (e.g., 3-D printing) becoming an end unto itself (Blikstein, 2013). Few studies have shed light on the strategies related to the stimulation of creative ideas. Some works mentioned brainstorming in the context of creative idea generation (Zhan et al, 2022). Students were given a period of time for brainstorming and sharing ideas among group members to generate new ideas and design schemes (Khamhaengpol, Sriprom & Chuamchaitrakool, 2021; Conradty & Bogner, 2019; Shen et al., 2021). However, lacking in-depth guidance, students tend to generate ordinary ideas that lack creativity. Concrete and effective creativity training strategies are still missing. In summary, while creative idea generation stands in the core place of innovative design or production, practices of current STEAM education tend to focus more on “doing” than “thinking”, and more on “repeating” than “creating”. There is a need to focus on the participation of mindsets in STEAM education (Martin, 2015), and extend available training strategies for creativity inspiration. Drawing upon research on association and creativity from the field of psychology, association intervention might be a potential way to foster creativity in STEAM education. Remote association and close association intervention are the most typical interventions that are used to trigger students’ knowledge transfer and creativity, thus we tried to investigate their different impacts and find out possible regulations for enhancing higher-order learning. Research purpose and questions The present study aimed to investigate the effects of creative thinking, aptitude, empathy, and design scheme underlying different association interventions (i.e., remote association, close association, and free association) in a STEAM course. Two research questions drove this inquiry: RQ1 Will association intervention enhance students’ creative thinking, aptitude, empathy, and design scheme? RQ2 Will students who participate in remote association intervention develop more positive reactions to creative thinking, aptitude, empathy, and design scheme than those who participate in close association intervention? Method Participants The present study was conducted in a one-semester STEAM course of a public secondary school in Guangzhou, China. Altogether, ninety-four students aged from 13 to 16 years old participated in the study. They were randomly assigned to three conditions: remote association (class A), close association (class B), free association (class C). As Table 1 shows, class A had 30 students, class B had 32 students, Class C had 32 students. Class A and Class B consisted of the experimental groups, and Class C was the control group. Table 1 an overview of the research design Class Sample size Duration Project A (remote association group) 30 8 weeks Mask design challenge (4 weeks) 3D glasses design challenge (4 weeks) B (close association group) 32  C (free association group) 32 The Association intervention Students in all conditions participated in the STEAM course that included two design projects, one was to design a mask, another was to design a 3D glasses. Each design project followed four stages: Goal proposal, Creativity inspiration, Design challenge, Presentation and evaluation, as shown in Table 2. The curriculum was developed by the research team with backgrounds in STEAM education with guidance from information technology teachers from the middle school. In the stage of goal proposal, it focused on stimulating students’ interest in design and identifying the design task. By providing related stories, videos, and pictures, teachers guided students to identify the design theme, that is, to design creative masks and 3D glasses for these two projects respectively. Students needed to understand that the goal of associations was to generate creative ideas combined with the real problem situation. Next, students applied different association methods to promote the divergence and convergence of thinking and generate creative ideas. In the remote association condition, students were provided with an apple in the mask design project and a bulb in the 3D glasses design project as association stimuli. Both were not directly related to the design targets. In contrast, in the close association condition, students used Sichuan opera face and patch as association stimulus to help generate creative ideas. The stimuli are either similar to the target objects or have some identical or obvious attributes to the target design objects. At this stage, students analyzed the relevant characteristics of the associative stimulus as comprehensively as possible, and then compulsorily associated the target with these attributes to form novel and unique creative ideas. In the design stage, students were guided to analyze the real needs of users based on the many ideas initially formed, that is, using “empathy” to help form the final idea. In the last presentation and evaluation stage, each team displayed and reported their design plan, and summarized the problems and experiences encountered in the design process. This stage mainly aimed to facilitate the communication and learning between groups, and made the evaluation more fair and objective. Table 2 Comparison of intervention activities across conditions Intervention activity Remote association condition Close association condition Free association condition Purpose Goal proposal Goal definition of the design task, construction of the association context Goal definition of the design task, construction of the association context Goal definition of the design task, construction of the association context Stimulating learning interest Creativity inspiration Ideating by remote associative stimuli, such as apple and bulb Ideating by close associative stimuli, such as Sichuan opera face and patch Ideating by no associative stimulus-brainstorming Fostering divergent thinking and convergent thinking Design challenges Completing the design plan Completing the design plan Completing the design plan Cultivating empathy and creative thinking Presentation and evaluation Communicating and improving the design plan Communicating and improving the design plan Communicating and improving the design plan Encouraging inter-group learning Measure instruments Creative thinking, aptitude, and empathy were examined in this study. Measures included the Creative thinking test, Williams creativity aptitude test (WCAT), Basic Empathy Scale (BES), as presented in Table 3. All the measure instruments were translated into Chinese and double-checked by at least two domain experts and two English experts to ensure validity and reliability. Table 3 Instruments for data collection Construct Source Number of items Cronbach’s alpha Creative thinking test (CTT) Zheng & Xiao (1983) 5 0.93 Williams creativity aptitude test (WCAT) Williams (1993) 50 0.81 Basic Empathy Scale (BES) Jolliffe & Farrington (2006) 20 cognitive: 0.79 Affective: 0.85 Creative thinking test (CTT) items examined fluency, flexibility, and uniqueness. The test consists of 5 items, and the Cronbach’s alpha was 0.93 (Zheng & Xiao, 1983). The test content includes a language test and a graphics test. The “Consensual Assessment Technique” (Baer & McKool, 2009) was adopted to score the test: two authors from the research group scored separately, and then the average score was taken as the test score. If there was a big difference between the scores of the two people, one more researcher will be asked to score. Williams creativity aptitude test (WCAT) (Williams, 1993) consists of 50 items, including four aptitude elements: imagination, risk-taking, curiosity and challenge. The present study took the Chinese revised version (Lin & Wang, 1994), and the Cronbach’s alpha was 0.81. Basic Empathy Scale (BES) (Jolliffe & Farrington, 2006) is a 20-item scale (nine cognitive items and 11 affective items) that measures affective and cognitive empathy. Each item asked the participant to respond on a Likert scale from 1 representing “strongly disagree” to 5 representing “strongly agree”, depending on the degree to which the item described them. For the design scheme analysis, we developed the creative idea evaluation form to score students’ designs. According to Torrance (1966), creative thinking has four characteristics: fluency, uniqueness, flexibility, and precision. Besides, it is believed that people with high creativity can quickly and timely judge and grasp unique and novel concepts, which means that such people have high sensitivity. Therefore, this study took the five dimensions: fluency, flexibility, uniqueness, precision, and sensitivity, to evaluate the ideas generated by students under different association interventions. Finally, we invited one student from each group for an interview to collect students’ opinions on the association intervention strategies adopted in this study. Students are required to express their opinions about the learning experience, gains, and suggestions of this STEAM course. Research process Students participated in eight 1.5-hour class periods during the study (see Table 4). In week 1, students took the pretest. Later, students participated in two design tasks followed by instruction on either remote association, close association or free association: the mask design task during week 2 to 4, and the 3D glasses design task during week 5 to 7. On week 8, students completed the posttest. Overall, the study lasted for 2 months, spread across 8 weeks. Table 4 Schedule of the experiment Design task Week Content Mask designing 1st Pretest of Creative thinking, creative disposition and empathy 2nd Mask design: idea generation 3rd Mask design: design 4th Mask design: presentation and evaluation 3D glasses designing 5th 3D glasses design: idea generation 6th 3D glasses design: design 7th 3D glasses: presentation and evaluation 8th Posttest of Creative thinking, creative disposition, empathy, creative idea analysis and student interview Figure 1 demonstrates the research process of the study, and Fig. 2 presents the scenes of class activities when students were doing the design projects. All students and their parents were acknowledged that they were participating in an education research and their individual data would be collected only for research purposes. We ensured all procedures performed in this study were in accordance with the ethical standards of American Psychological Association. Fig. 1 Research process Fig. 2 Class activities of the design project Data Analysis All data in this study were analyzed using SPSS 26 to conduct descriptive statistics. The mean differences among three association conditions were tested by one-way analysis of variance (ANOVA), and the changes between the pre- and post-tests were tested by paired samples t-tests. Since there were multiple comparisons among three different groups for every dependent variable, one-way ANOVA Post Hoc analysis was adopted based on the Test of Homogeneity of Variances. Students’ design schemes were scored on five dimensions (i.e., fluency, flexibility, uniqueness, precision, and sensitivity) by adopting the consensus assessment technique. In order to validate and deepen the understanding of the statistical results, we randomly selected eight students for interviews, and obtained their feedback from three aspects (i.e., experience, gain, and suggestion), then summed up the main points related to the association interventions. Result Creative thinking For the creative thinking test, we calculated ANOVA on pre- and post-tests by condition. Results showed that a significant difference existed among the three conditions in both pretest (F = 4.888; p = .010) and posttest (F = 4.311; p = .016) (see Table 5). Then paired samples t-test was conducted to compare the change of each condition. Results show that both remote association (p = .000, d = 2.0048) and close association (p = .000, d = 1.0891) fostered students’ overall performance on the creative thinking test. For Fluency, no significant difference was found among the three groups either in the pretest (F = 1.468, p = .236) or the posttest (F = 0.680, p = .509). Compared with the pretest, students in the remote association condition (p = .000, d = 1.584) and close association condition (p = .000, d = 1.8817) both got significantly higher scores in the posttest. For Flexibility, the one-way ANOVA shows a significant difference among the three conditions in the posttest (F = 8.469, p = .000), while not in the pretest (F = 1.920, p = .152). In the posttest, according to the result of the Test of Homogeneity of Variances (Levene Statistic = 7.686, p = .001), we run a one-way ANOVA Post Hoc analysis (Tamhane’s T2). Results show that compared with the free association condition, the remote association (p = .001, d = 0.9129) and close association (p = .044, d = 0. 591) performed differently on fostering students’ flexibility of creative thinking. In addition, there was no significant difference between remote association and close association (p = .490). For Uniqueness, the one-way ANOVA shows that there is a significant difference among the three conditions in the pretest (F = 10.396, p = .000), while not in the posttest (F = 3.042, p = .053). According to the paired samples t-test, the remote association condition fostered students’ performance of Uniqueness significantly (p = .000, d = 1.0256). Students in the close association also performed significantly better in the posttest (p = .001, d = 0.1153). Table 5 Means and standard deviation of students’ creative thinking test CTT items Remote association(N = 30) Close association(N = 32) Free association(N = 32) Pre M (SD) Post M (SD) Pre M (SD) Post M (SD) Pre M (SD) Post M (SD) Fluency 18.43 (4.768) 24.87 (3.213) 19.50 (4.080) 25.69 (2.235) 17.88 (4.723) 23.94 (3.121) Flexibility 11.70 (4.252) 19.23 (3.711) 15.19 (4.518) 18.06 (2.929) 12.44 (5.913) 18.88 (5.142) Uniqueness 6.37 (2.906) 9.43 (3.059) 7.50 (3.370) 7.88 (3.220) 4.63 (2.612) 8.13 (3.998) Total 36.50 (9.790) 53.53 (6.962) 42.19 (10.256) 51.63 (6.714) 34.94 (12.062) 50.94 (10.439) Creativity aptitude Imagination, risk-taking, curiosity, and challenge were analyzed for Creativity aptitude. We calculated ANOVA on the total score of the Creativity aptitude survey. In the pretest, results showed no significant difference among the three conditions (F = 2.486, p = .089). In the posttest, a significant difference existed among the three conditions (F = 20.189, p = .000) (see Table 6). In the posttest, according to the result of the Test of Homogeneity of Variances (Levene Statistic = 0.116, p = .890), we ran a one-way ANOVA Post Hoc analysis (Least Significant Difference, LSD). Results showed that the significant difference only existed between remote association and free association (p = .037, d = 0.5227). In addition, there was a significant difference between remote association and close association (p = .000, d = 1.0719). That was, different association interventions affected students’ creativity aptitude, and the effect of the close association condition was more obvious than that of the remote association condition. For Imagination, the one-way ANOVA showed a significant difference among the three conditions in the posttest (F = 12.975, p = .000), while not in the pretest (F = 1.819, p = .168). In the posttest, according to the result of the Test of Homogeneity of Variances (Levene Statistic = 1.746, p = .180), we ran a one-way ANOVA Post Hoc analysis (Least Significant Difference, LSD). Results showed that there was a significant difference between remote association and free association condition (p = .000, d = 1.2374), while no difference between close association and free association condition (p = .136). In addition, there was also a significant difference between remote association and close association (p = .001, d = 0.8396). For Risk-taking, the one-way ANOVA showed a significant difference among the three conditions in the posttest (F = 7.566, p = .001), while not in the pretest (F = 1.128, p = .328). In the posttest, according to the result of the Test of Homogeneity of Variances (Levene Statistic = 0.549, p = .579), we ran a one-way ANOVA Post Hoc analysis (Least Significant Difference, LSD). Results showed that there was a significant difference between remote association and free association (p = .000, d = 0.9657) as well as close association and free association (p = .008, d = 0.6564). In addition, there was no significant difference between remote association and close association (p = .278). For Curiosity, the one-way ANOVA showed a significant difference among the three conditions in the posttest (F = 19.029, p = .000), while not in the pretest (F = 1.825, p = .167). In the posttest, according to the result of the Test of Homogeneity of Variances (Levene Statistic = 0.081, p = .922), we ran a one-way ANOVA Post Hoc analysis (Least Significant Difference, LSD). Results showed that there was a significant difference between remote association and free association condition (p = .000, d = 1.445), while no difference between close association and free association condition (p = .302). In addition, there was also a significant difference between remote association and close association (p = .000, d = 1.2293). For Challenge, the one-way ANOVA showed a significant difference among the three conditions in the pretest (F = 3.098, p = .050) and also in the posttest (F = 4.182, p = .018). Then paired samples t-test was conducted to compare the change of each condition. Results showed that the close association (p = .000, d = 0.7025) fostered students’ challenge reaction on the Creativity aptitude survey, but not in the remote association (p = .856). Table 6 Means and standard deviation of students’ creative aptitude test WCAT items Remote association(N = 30) Close association (N = 32) Free association (N = 32) Pre M (SD) Post M (SD) Pre M (SD) Post M (SD) Pre M (SD) Post M (SD) Imagination 28.67 (2.657) 29.03 (2.871) 29.31 (3.021) 31.25 (2.396) 31.44 (2.409) 29.19 (2.191) Risk-taking 24.40 (2.581) 26.20 (2.041) 25.25 (2.342) 26.81 (2.250) 25.00 (1.884) 28.31 (2.320) Curiosity 34.27 (3.600) 34.30 (2.215) 35.00 (2.664) 36.94 (2.078) 35.88 (3.626) 37.50 (2.214) Challenge 30.57 (2.096) 30.50 (1.925) 29.94 (2.699) 31.56 (1.831) 31.44 (2.409) 30.81 (1.908) Total 119.40 (8.669) 120.03 (6.003) 121.00 (8.096) 126.56 (6.180) 124.06 (8.428) 125.81 (6.255) Empathy For the empathy survey, we calculated ANOVA on pre- and post-tests by condition. Results showed that no significant difference existed among the three conditions either in pretest (F = 0.496; p = .611) or posttest (F = 2.352; p = .101) (see Table 7). Then paired samples t-test was conducted to compare the change of each condition. Results showed that both remote association (p = .000, d = 1.1882) and close association (p = .000, d = 1.6606) fostered students’ overall reaction on empathy. For cognitive empathy, the one-way ANOVA showed a significant difference among the three conditions in the posttest (F = 5.386, p = .006), while not in the pretest (F = 0.256, p = .775). In the posttest, according to the result of the Test of Homogeneity of Variances (Levene Statistic = 2.663, p = .075), we ran a one-way ANOVA Post Hoc analysis (Least Significant Difference, LSD). Results showed that there was a significant difference between remote association and free association condition (p = .002, d = 0.7375) as well as close association and free association condition (p = .031, d = 0.6197). In addition, there was no significant difference between remote association and close association (p = .300). For affective empathy, the one-way ANOVA showed no significant difference among the three conditions in the pretest (F = 0.427, p = .654), and not in the posttest (F = 1.255, p = .290) either. Then paired samples t-test was conducted to compare the change of each condition. Results showed that both remote association (p = .000, d = 0.7884) and close association (p = .000, d = 0.6692) fostered students’ affective empathy. Table 7 Means and standard deviation of students’ basic empathy test BES items Remote association (N = 30) Close association (N = 32) Free association (N = 32) Pre M (SD) Post M (SD) Pre M (SD) Post M (SD) Pre M (SD) Post M (SD) Cognitive empathy 31.20 (2.497) 33.93 (3.443) 31.00 (3.132) 34.69 (2.177) 31.50 (2.759) 34.25 (2.817) Affective empathy 31.63 (4.072) 35.10 (4.708) 30.81 (2.520) 33.19 (4.353) 31.06 (3.943) 32.69 (5.866) Total 62.83 (4.178) 69.03 (6.083) 61.81 (2.788) 67.88 (4.353) 62.56 (5.267) 66.94 (6.470) Design scheme Quantitative results of the Creative thinking test, Williams creativity aptitude test (WCAT) and Basic Empathy Scale (BES) showed that the association interventions had a certain effect in promoting the cultivation of students’ creative ability. To investigate the characteristics of students’ creative thinking, we analyzed the design scheme generated by students during the process of generating creative ideas through association. Some students’ design sketches under the three conditions were also shown in Figs. 3 and 4. Fig. 3 Examples of students’ Mask design sketches. (Note: Mask design: Inspired by the “Face-changing” technique in Sichuan Opera, students designed a reusable mask (with replaceable filters) that can show the changes in people’s emotions (left), and a school-specific multifunctional reusable mask (right).) Fig. 4 Example of students’ 3D glasses design sketches. (Note: 3D glasses design: Inspired by the patch, students designed auto-massaging 3D glasses (left), while inspired by the bulb, students designed 3D glasses that are with oval-shaped lenses, besides, the glasses are antivirus, automatic cooling, and shatter-resistant (right).) Students’ design ideas were scored on five dimensions: fluency, flexibility, uniqueness, precision, and sensitivity. As shown in Fig. 5, compared with the control group, both remote and close association interventions have promoted the generation of students’ creative ideas. Besides, students under the close intervention condition performed best and achieved highest scores among the three groups in all five dimensions. Fig. 5 Results for design scheme analysis Students interview Through interviews, we found that students had a positive attitude in constructing problem situations, analyzing the attributes of associations, compelling related associations, collaborative group discussions, hands-on operations, group presentation and evaluation. Students reported that the association intervention not only provided them with ideas for diverging associations in the process of idea generating, but also allowed them to converge the ideas generated. At the same time, the association interventions promoted their learning by mobilizing enthusiasm for active learning and stimulating their learning interest. In addition, through compulsory association, students not only learned to use association clues to generate ideas that were more suitable for user needs, but also cultivated their creative thinking and creativity. Students got practical experiences in creative problem-solving, empathy, and cooperation. Firstly, students reported that authentic problem situations could help inspire empathy. Everyone was faced with these problems that were closely related to life. For example, a student said: “Because we wear masks every day, such as going to school, taking the subway, we can understand the imagination of some special functions of masks during the COVID-19 pandemic” (Student 2). “When the cinema resumes business, audiences need to keep a safe distance when watching movies, and the 3D glasses used in public are not hygienic. These problems are real for each of us. So, when the teacher proposed the task of designing 3D glasses, everyone actively expressed their real experience and needs” (Student 4). Secondly, when students were cued to make relations between the association stimulus and targets, their creative thinking and creativity were fostered. They actively participated in the association activities and team discussions. There were obviously more ideas generated in the second design project (3D glasses) than in the first one (Mask), and the speed was also faster. One student said: “I have never thought the connections between these things, such as apple and mask, light bulb and 3D glasses. In this course, during the compulsory association process, our group members propose kinds of interesting and well-founded opinions.” (Student 8). Thirdly, students reported that through group collaboration, the members could listen to the opinions of others, and learned from each other. Through group discussion, they determined the theme of the design together. Students made joint effort and finally completed the design project. For example, student said: “When we discussed ‘apple’ in our group, from the external characteristics, some said that apples have red, green and yellow colors and associated the idea of discoloration; from the perspective of function, some put the point of view that as a kind of fruit, apples can provide energy for people etc. In this process, we are inspired from others, and our communication skills are also improved.” (Student 1). Student also said: “Our group combined the different design schemes suggested by each member, and through the discussion inside the group, we finally designed our own unique design, this feeling is very good” (Student 5). Finally, students gave positive feedback on the group reporting. Through the group presentation and evaluation, they could find problems of their design and solve them in time, which was conducive to promoting reflection. Besides, students could learn from other groups, and make progress together. “This kind of evaluation can help us learn the advantages of other groups” (Student 7). “We score ourselves, so that teacher evaluation is not the only determinant of performance. This can make the evaluation more objective” (Student 6). Students also put forward some suggestions. For example, some students suggested that in the process of compulsory association, teachers could provide them with more introductions related to the association stimulus to broaden their association range. Some students said that they encountered some difficulties in finding resources and hoped that more resources could be provided. Totally, the association interventions have a certain effect on students’ creative thinking, creativity, empathy, collaborative ability, and creative problem-solving ability. Although there are still some problems, it gained overall satisfactory feedbacks from students. Discussion In respect of the two research questions stated in Sect. 3, we may conclude that the association interventions have an impact on the cultivation of students’ creativity in the present STEAM course. Overall, the remote association and close association interventions could both promote students’ creative thinking, creativity aptitude, and empathy (RQ1). The remote association intervention worked better to help students to achieve a higher degree of creative thinking. While the close association intervention was more effective in improving students’ creativity aptitude and quality of design ideas (RQ2). In addition, for some aspects, the free association condition also has its advantages. Further discussion is elaborated as follows. Why did the association interventions foster students’ creativity? With respect to RQ1, as expected, students who participated in the STEAM course under the two association interventions gained positive performance of creativity by their progress from pre- to post-test. Students in the remote and close association conditions generated more ideas, and the speed was also faster, especially in the second design project (3D glasses), indicating that the association clues enhanced students’ creativity on the design-focused creative problem-solving tasks. This is consistent with the former studies (Wilson et al., 2021; Shen et al., 2021; Timotheou & Ioannou, 2021). The possible explanation is that association interventions construct compulsory association situations, in which students are cued to generate uncommon and useful ideas. The remote and close association interventions stimulated students to generate multiple creative ideas through providing association clues. On one hand, these clues clearly pointed out the association directions and also provided students with scaffolds for idea generating. When being explicitly asked to generate creative ideas, students are likely to generate more creative ideas (Acar, Runco & Park, 2020; Benedek et al., 2020; Green et al., 2015; Prabhakaran et al., 2014; Said-Metwaly et al., 2020; Weinberger et al., 2016). Besides, association stimulus may help break through psychological stereotypes, therefore, students could generate more uncommon and distantly related design ideas. On the other hand, association intervention relates to creativity because it enables persistence (i.e., sustained task-directed effort). Invoking the Dual Pathway to Creativity Model, De Dreu et al. (2012) hypothesized that working memory capacity (WMC) is related to creative performance because it enables persistent, focused, and systematic combining of elements and possibilities (persistence). It showed that the cognitive inhibition enabled the individual to maintain attention focused on the task and prevented undesirable mind wandering. Gupta et al. (2012) tested the hypothesis that highly creative individuals, as measured by the RAT, were able to access remote associations because they were not biased to consider only high-frequency words. In the experiment, for each RAT question, participants were presented with three cue words and asked to find the common associative link among them within the allotted time of 30-seconds. Result supported the claim that the tendency to consider high-frequency words impairs performance on the RAT. Individuals who performed poorly on the RAT should be biased to give high-frequency responses, while others who performed well in RAT were more inclined to use concepts that have low-frequency connections with cues as answers to questions. By clearly requiring students to break psychological stereotypes, the association stimulus used in the present study helped students to generate creative solutions that requiring avoidance of high-frequency candidate answers. Another possible explanation is that the compulsory association activities were relatively new to the participants, so involved in the experimental course helped stimulate students’ learning motivation, increase engagement, and stimulate creativity (Rutland and Barlex, 2008). Generally, when engaging in a design process to solve a defined problem, students brainstorm possible solutions, evaluate and prioritize alternative solutions, and then decide among existing alternatives (Aranda, Lie, & Guzey, 2020). Without direction and restraint, the ideas produced may not be able to meet the expectations. But the compulsory association helps extend associations from familiar fields to unfamiliar fields, even unexpected fields. In other words, it not only makes full use of existing designs, but also benefits from their mutual combination. Finally, empathy can also promote creativity. Empathy and the acquisition of empathy are considered essential components of adequate moral development (Jolliffe & Farrington, 2006), and empirical relations between many forms of prosocial behaviour and empathy have also been studied (e.g. Batson, Fultz, & Schoenrade, 1987). In line with this assertion, empathy helps raise feelings of human-centeredness and enhance thoughtfulness on design decisions. Therefore, while being asked to solve design problems that addressed the client’s demand, students showed consideration for others, thereby promoting the novelty and usefulness of creative thinking (Gong, 2018). Why did the remote association and close association show different effects on creativity cultivation? With respect to RQ2, results showed that the remote association intervention worked better than the close association intervention on improving students’ creative thinking and empathy. While in the creativity aptitude survey and the creative idea analysis, students in the close association condition outperformed the remote association condition. First, empirical studies have confirmed that remote association intervention may promote creativity better. For instance, Howard-Jones and colleagues (2005) conducted an experiment that requiring participants to produce creative (generate a story that was as creative as possible) and uncreative (generate a story that was as uncreative as possible) stories from related (e.g., magician, trick, rabbit) and unrelated (e.g., flea, sing, sword) word sets. In particular, the strategy that incorporating a set of words that were unrelated to each other was used to encourage semantic divergence. Results showed that the inclusion of unrelated words in the stories improved the rated creativity of the outcomes. It was also evident that the rated creativity of the outcomes of the stories was influenced by providing a ‘‘Be creative’’ or ‘‘Be uncreative’’ objective. In brief, piecing together a story from unrelated words predictably led to more creative responses than doing the same for related words, and it would appear that the rated creativity of stories was influenced more by objective in the unrelated conditions than in the related conditions. On the basis of the remote association theory, Gupta et al. (2012) also supported the claim that a tendency to consider high-frequency words impairs performance on the RAT. Individuals who performed poorly responded with high-frequency incorrect words. Therefore, remote association may be confirmed as a key enabler of successful creative idea generation as it contributes to promote the uncommon and long-distance semantic ideas, and reduce the tendency to produce high-frequency ideas. Second, the remote association condition did not outperform the close association condition in the creativity aptitude survey and the creative idea analysis as predicted. According to our study, different association interventions affected students’ creativity aptitude as well as the creative problem-solving ability, and judging from the total score, the effect of the close association condition was more obvious than that of the remote association condition. Specifically, for the creativity aptitude survey, students involved in the close association condition reported better response on the aspect of curiosity and imagination. Furthermore, for the challenge dimension, students in the close association condition performed significantly better in the posttest than the pretest, in contrast, students in the remote association showed a little declination. As for the risk-taking dimension, there was no significant difference between these two association intervention conditions. Possible explanations for the results may be that (a) the stimuli used in the close association intervention have a closer attribute relationship to the type of target object than those used in the remote association condition, thus it is easier to guide students to produce creative ideas within a certain range during the ideating process (Gruszka & Necka, 2002). The imagination was thus far more prompted. (b) the closer relationship between the object and the association stimulus may reduce fear of difficulty, then it is easy for students to have the feeling of ​​“the two are more easily related”, thus generating strong curiosity and challenge (Wu et al., 2016). (c) risk-taking may be susceptible to interference from the external environment. The provided association stimuli have shown the directions for the design project, so the risky nature has not changed much. For the creative scheme analysis, students under the close intervention condition performed better than the remote association condition in both two design projects. It may be inferred that considering the original creativity level of the participants, the close association intervention may be more effective at promoting the near-transfer than the remote association for far-transfer. Also, as Abraham et al. (2012) indicated, it is cognitively far more demanding to generate uncommon uses than common uses, even when explicitly told to generate uncommon uses, it is highly likely that the subjects will also think about common uses while doing so, and vice versa. It is undeniably more cognitively demanding to generate novel design ideas from unrelated association stimulus compared to related association stimulus. In STEAM education, similar result was also reported. Conradty & Bogner (2019) reported that the Short-term STEAM module produced long-term knowledge and built stable scores of intrinsic motivations, but not self-reported aspects of creativity. What are the differences among the three conditions for the measured variables? For the posttest, significant differences among the three conditions were reported both in the creativity thinking test and the creativity aptitude survey. While for the empathy survey, there existed no significant difference. Besides, the design idea analysis also provided evidence of the effectiveness of the association interventions, that is, students participated in the association intervention conditions reported better learning outcomes than those under the brainstorming condition. As predicted, the compulsory association conditions showed effectiveness on improving students’ creativity. But it is worth noting that free association also has its own advantages on creativity cultivation. Results show that for some dimensions, such as the risk-taking, curiosity and imagination of creativity aptitude, and also the cognitive empathy, free association condition can promote more positive outcomes. As for the reasons, one is that the design problems are complex and ill defined, and the creative problem-solving process is also extremely complicated. The creative thinking process may consist of four stages: preparation, incubation, illumination and verification) (Wallas, 1926), which suggests that the creativity does not happen overnight. Moreover, existing studies have discussed multiple elements possibly related to creative thinking, such as attention, working memory, executive function, intelligence, and emotion. (Bott et al., 2014; Moss, & Wilson, 2015; Lin, & Lien, 2013; Beaty et al., 2014; Benedek et al., 2014). In particular, another important reason for the results may be related to the conflicting views that the creative thinking is happened consciously or unconsciously (Beaty et al., 2014; Benedek & Jauk, 2018; Martindale, 2007; Segal, 2004; Smith, 1995; Sowden et al., 2015). From this perspective, it is understandable that the free association can promote part of the dimensions of creativity better. In conclusion, the findings illustrate that students could raise the level of creativity by deliberate training under different association strategies through the STEAM course. From one side of the coin, association intervention helps guide the development direction of individual creativity, but it does not determine its level. From another side, to some extent, the compulsory association may limit students’ thinking within a certain range. Students’ original level may affect the effect of creativity training: students who are originally at a low level of creativity may be more suitable for close association or brainstorming training, and students who are originally at a high level of creativity may be more suitable for remote association (Clapham, 1997; Fleith, Renzulli, & Westberg, 2002; Ge & Bai, 2007). More elements, such as time pressure, creative thinking stages, task types and so on, may also be taken into consideration for nurturing students’ creativity (Abraham et al., 2018; Conradty & Bogner, 2019; Wallas, 1926). Limitations and future studies The present study reported that STEAM course integrated with association interventions is beneficial for nurturing creativity. However, as creative thinking is among the most complex of human abilities (Abraham et al., 2012), to further elucidate the effects of association intervention on creativity, and the differences among association interventions through which link to creative performances, more empirical studies are needed. For example, it could be interesting to explore the effect of the combination of different association interventions, the effect of different stimuli amounts and types, and the effect of long-term vs. short-term interventions, etc. Funding This research was financially supported by the National Natural Science Foundation in China (62277018; 62237001), Ministry of Education in China Project of Humanities and Social Sciences (22YJC880106), the Major Project of Social Science in South China Normal University (ZDPY2208). Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Abraham A Pieritz K Thybusch K Rutter B Kröger S Schweckendiek J Hermann C Creativity and the brain: uncovering the neural signature of conceptual expansion Neuropsychologia 2012 50 8 1906 1917 10.1016/j.neuropsychologia.2012.04.015 22564480 Abraham A Rutter B Bantin T Hermann C Creative conceptual expansion: a combined fMRI replication and extension study to examine individual differences in creativity Neuropsychologia 2018 118 29 39 10.1016/j.neuropsychologia.2018.05.004 29733816 Acar S Runco MA Park H What should people be told when they take a divergent thinking test? A meta-analytic review of explicit instructions for divergent thinking Psychology of Aesthetics Creativity and the Arts 2020 14 1 39 10.1037/aca0000256 Aranda ML Lie R Guzey SS Productive thinking in middle school science students’ design conversations in a design-based engineering challenge International Journal of Technology and Design Education 2020 30 1 67 81 10.1007/s10798-019-09498-5 Baer, J., & McKool, S. S. (2009). Assessing creativity using the consensual assessment technique. Handbook of research on assessment technologies, methods, and applications in higher education (pp. 65–77). IGI Global. Batson CD Fultz J Schoenrade PA Eisenberg N Strayer J Adults’ emotional reactions to the distress of others Empathy and its development 1987 Cambridge Cambridge University Press 163 184 Beaty RE Benedek M Silvia PJ Schacter DL Creative cognition and brain network dynamics Trends in cognitive sciences 2016 20 2 87 95 10.1016/j.tics.2015.10.004 26553223 Beaty RE Silvia PJ Nusbaum EC Jauk E Benedek M The roles of associative and executive processes in creative cognition Memory & cognition 2014 42 7 1186 1197 10.3758/s13421-014-0428-8 24898118 Benedek, M., & Jauk, E. (2018). 22 Spontaneous and Controlled Processes. The Oxford handbook of spontaneous thought: Mind-wandering, creativity, and dreaming, 285. Benedek M Jurisch J Koschutnig K Fink A Beaty RE Elements of creative thought: investigating the cognitive and neural correlates of association and bi-association processes Neuroimage 2020 210 116586 10.1016/j.neuroimage.2020.116586 32001370 Bevan B The promise and the promises of making in science education Studies in Science Education 2017 53 1 75 103 10.1080/03057267.2016.1275380 Blikstein, P. (2013). Digital fabrication and ‘making’ in education: the democratization of invention. In J. Walter, Herrmann, & C. Buching (Eds.), € FabLabs: of machines, makers and inventors (pp. 203–222). Transcript Publishers. Bott N Quintin EM Saggar M Kienitz E Royalty A Hong DWC Reiss AL Creativity training enhances goal-directed attention and information processing Thinking Skills and Creativity 2014 13 120 128 10.1016/j.tsc.2014.03.005 Clapham MM Ideational skills training: a key element in creativity training programs Creativity research journal 1997 10 1 33 44 10.1207/s15326934crj1001_4 Conradty C Bogner FX From STEM to STEAM: cracking the code? How creativity & motivation interacts with inquiry-based learning Creativity Research Journal 2019 31 3 284 295 10.1080/10400419.2019.1641678 De Dreu CK Nijstad BA Baas M Wolsink I Roskes M Working memory benefits creative insight, musical improvisation, and original ideation through maintained task-focused attention Personality and Social Psychology Bulletin 2012 38 5 656 669 10.1177/0146167211435795 22301457 Dietrich A Kanso R A review of EEG, ERP, and neuroimaging studies of creativity and insight Psychological bulletin 2010 136 5 822 10.1037/a0019749 20804237 Fleith DDS Renzulli JS Westberg KL Effects of a creativity training program on divergent thinking abilities and self-concept in monolingual and bilingual classrooms Creativity research journal 2002 14 3–4 373 386 10.1207/S15326934CRJ1434_8 Ge C Bai X EFFECTS OF TRAINING METHODS ON CHILDREN WITH DIFFERENT CREATIVITY LEVELS Studies of Psychology and Behavior 2007 5 1 13 17 Gong, Z. (2018). The relationship between creativity and morality: individual and collective perspectives (Doctoral dissertation). Nanjing: Nanjing Normal University. Green AE Cohen MS Kim JU Gray JR An explicit cue improves creative analogical reasoning Intelligence 2012 40 6 598 603 10.1016/j.intell.2012.08.005 Green AE Cohen MS Raab HA Yedibalian CG Gray JR Frontopolar activity and connectivity support dynamic conscious augmentation of creative state Human brain mapping 2015 36 3 923 934 10.1002/hbm.22676 25394198 Gruszka A Necka E Priming and acceptance of close and remote associations by creative and less creative people Creativity Research Journal 2002 14 2 193 205 10.1207/S15326934CRJ1402_6 Gupta N Jang Y Mednick SC Huber DE The Road not taken: creative solutions require avoidance of high-frequency responses Psychological Science 2012 23 3 288 294 10.1177/0956797611429710 22344387 Harris A De Bruin LR Secondary school creativity, teacher practice and STEAM education: an international study Journal of Educational Change 2018 19 2 153 179 10.1007/s10833-017-9311-2 Howard-Jones PA Blakemore SJ Samuel EA Summers IR Claxton G Semantic divergence and creative story generation: an fMRI investigation Cognitive Brain Research 2005 25 1 240 250 10.1016/j.cogbrainres.2005.05.013 15993573 Jolliffe D Farrington DP Development and validation of the Basic Empathy Scale Journal of adolescence 2006 29 4 589 611 10.1016/j.adolescence.2005.08.010 16198409 Kaufman, J. C. (2016). Creativity 101. Springer publishing company. Khamhaengpol A Sriprom M Chuamchaitrakool P Development of STEAM activity on nanotechnology to determine basic science process skills and engineering design process for high school students Thinking Skills and Creativity 2021 39 100796 10.1016/j.tsc.2021.100796 Li T Zhan Z A systematic review on design thinking Integrated Learning in K-12 education Applied Sciences 2022 12 8077 10.3390/app12168077 Lin C Wang M The creativity assessment packet 1994 Taipei, Taiwan Psychological Publishing Lin WL Lien YW The different role of working memory in open-ended versus closed-ended creative problem solving: a dual-process theory account Creativity Research Journal 2013 25 1 85 96 10.1080/10400419.2013.752249 Lin, Z., Lin, Z., Zhan, Z., & Wang, X. (2022). Evaluating Student’s Creative Thinking in STEAM Education Model Construction and Validation. In 2022 3rd International Conference on Education Development and Studies, USA. 10.1145/3528137.3528143 Martin L The promise of the maker movement for education Journal of Pre-College Engineering Education Research (J-PEER) 2015 5 1 30 39 10.7771/2157-9288.1099 Martindale C Creativity, primordial cognition, and personality Personality and individual differences 2007 43 7 1777 1785 10.1016/j.paid.2007.05.014 Mednick S The associative basis of the creative process Psychological review 1962 69 3 220 232 10.1037/h0048850 14472013 Moss SA Wilson SG The positive emotions that facilitate the fulfillment of needs may not be positive emotions at all: the role of ambivalence Explore 2015 11 1 40 50 10.1016/j.explore.2014.10.006 25457443 Nusbaum EC Silvia PJ Beaty RE Ready, set, create: what instructing people to “be creative” reveals about the meaning and mechanisms of divergent thinking Psychology of Aesthetics Creativity and the Arts 2014 8 4 423 10.1037/a0036549 Perignat E Katz-Buonincontro J STEAM in practice and research: an integrative literature review Thinking skills and creativity 2019 31 31 43 10.1016/j.tsc.2018.10.002 Prabhakaran R Green AE Gray JR Thin slices of creativity: using single-word utterances to assess creative cognition Behavior research methods 2014 46 3 641 659 10.3758/s13428-013-0401-7 24163211 Runco, M. A. (2014). Creativity: theories and themes: Research, development, and practice. Elsevier. Runco MA Jaeger GJ The standard definition of creativity Creativity research journal 2012 24 1 92 96 10.1080/10400419.2012.650092 Rutland M Barlex D Perspectives on pupil creativity in design and technology in the lower secondary curriculum in England International Journal of Technology and Design Education 2008 18 2 139 165 10.1007/s10798-007-9024-6 Said-Metwaly S Fernández-Castilla B Kyndt E Van den Noortgate W Testing conditions and creative performance: Meta-analyses of the impact of time limits and instructions Psychology of Aesthetics Creativity and the Arts 2020 14 1 15 10.1037/aca0000244 Segal E Incubation in insight problem solving Creativity Research Journal 2004 16 1 141 148 10.1207/s15326934crj1601_13 Shen, S., Wang, S., Qi, Y., Wang, Y., & Yan, X. (2021). Teacher Suggestion Feedback Facilitates Creativity of Students in STEAM Education.Frontiers in Psychology,3653. Simonton DK Taking the US Patent Office criteria seriously: a quantitative three-criterion creativity definition and its implications Creativity research journal 2012 24 2–3 97 106 10.1080/10400419.2012.676974 Smith, S. M. (1995). Fixation, incubation, and insight in memory and creative thinking.The creative cognition approach,135–156. Sowden PT Pringle A Gabora L The shifting sands of creative thinking: connections to dual-process theory Thinking & Reasoning 2015 21 1 40 60 10.1080/13546783.2014.885464 Sternberg, R. J., Kaufman, J. C., & Pretz, J. E. (2002). The creativity conundrum: a propulsion model of kinds of creative contributions. Psychology Press. Tan AG Creativity in cross-disciplinary research E. Shiu (Ed.), Creativity research: an interdisciplinary and multidisciplinary research handbook 2014 London Routledge 68 85 Timotheou S Ioannou A Collective creativity in STEAM making activities The Journal of Educational Research 2021 114 2 130 138 10.1080/00220671.2021.1873721 Torrance EP The Torrance tests of creative thinking-norms-technical Manual Research Edition-Verbal tests, forms A and B-Figural tests, forms a and B 1966 Princeton, NJ Personnel Press Vendetti MS Wu A Holyoak KJ Far-out thinking: Generating solutions to distant analogies promotes relational thinking Psychological science 2014 25 4 928 933 10.1177/0956797613518079 24463552 Wallas, G. (1926). The art of thought. Weinberger, A. B., Iyer, H., & Green, A. E. (2016). Conscious augmentation of creative state enhances “real” creativity in open-ended analogical reasoning.PloS one, 11(3), e0150773. Williams FE Creativity Assessment Packet Examiner’s Manual 1993 Austin, TX PROED Wilson, H. E., Song, H., Johnson, J., Presley, L., & Olson, K. (2021). Effects of transdisciplinary STEAM lessons on student critical and creative thinking.The Journal of Educational Research,1–13. Wu, C., Zhong, S., & Chen, H. (2016). Discriminating the difference between remote and close association with relation to white-matter structural connectivity.PloS one, 11(10), e0165053. Wu, Q., Lu, J., Yu, M., Lin, Z., & Zhan, Z. (2022). Teaching Design Thinking in a C-STEAM Project: A Case Study of developing the Wooden Arch Bridges’ Intelligent Monitoring system. the 2022 13th International Conference on E-Education, E-Business, E-Management and E-Learning (IC4E). 10.1145/3514262.3514313 Zhan Z He W Yi X Ma S Effect of unplugged programming teaching aids on children’s computational thinking and classroom interaction: with respect to Piaget’s four stages theory Journal of Educational Computing Research 2022 10.1177/07356331211057143 Zheng RC Xiao B A study on the creativity of high school students Acta Psychologica Sinica 1983 04 445 452 Zhan Z Shen W Lin W Effect of product-based pedagogy on students’ project management skills, learning achievement, creativity, and innovative thinking in a high-school artificial intelligence course. Front. Psychol. 2022 13 849842 10.3389/fpsyg.2022.849842 36092027
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==== Front Arch Dermatol Res Arch Dermatol Res Archives of Dermatological Research 0340-3696 1432-069X Springer Berlin Heidelberg Berlin/Heidelberg 36508020 2507 10.1007/s00403-022-02507-z Original Paper Racial disparities in dermatology Narla Shanthi 1 Heath Candrice R. [email protected] 2 Alexis Andrew [email protected] 3 Silverberg Jonathan I. [email protected] 4 1 grid.449409.4 0000 0004 1794 3670 Department of Dermatology, St. Luke’s University Health Network, Easton, PA 18045 USA 2 grid.412374.7 0000 0004 0456 652X Department of Dermatology, Lewis Katz School of Medicine, Temple University Hospital, Philadelphia, PA 19140 USA 3 grid.5386.8 000000041936877X Department of Dermatology, Weill Cornell Medicine, New York, NY 10075 USA 4 grid.253615.6 0000 0004 1936 9510 Department of Dermatology, The George Washington University School of Medicine and Health Sciences, Suite 2B-430, 2150 Pennsylvania Avenue, Washington, DC 20037 USA 12 12 2022 19 19 6 2022 4 12 2022 5 12 2022 © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Significant racial/ethnic disparities in dermatologic care and their subsequent impact on dermatologic conditions were recently reported. Contributing factors include socioeconomic factors, gaps in educational exposure, and underrepresentation of minority groups in the dermatologic workforce. In 2021, the American Academy of Dermatology (AAD) announced its three-year plan to expand diversity, equity, and inclusion in dermatology. One way to reduce disparities in dermatology is for every dermatologist, regardless of race or ethnicity, to receive adequate education in diseases, treatments, health equity, and tailored approaches to delivering dermatologic care with cultural humility. In addition, a diverse dermatologic workforce—especially at the level of residency program educators and organizational leaders—will contribute to improved cross-cultural understanding, more inclusive research efforts, and improved treatment approaches for conditions that are more prevalent or nuanced in certain racial/ethnic populations. Finally, the dermatology and broader healthcare community needs to acknowledge and educate ourselves on the health impacts of racism. Keywords Race Disparities Dermatology Atopic dermatitis Psoriasis Mycosis fungoides Skin cancer Clinical trials Hidradenitis suppurativa Machine learning Structural racism ==== Body pmcIntroduction In dermatology, skin of color (SOC) identifies “individuals of particular racial and ethnic groups who share similar characteristics and disorders, as well reaction patterns to those disorders” including increased constitutive pigmentation, propensity toward reactive pigment alteration, and higher skin phototype [1]. While there is a wide range of skin phototypes across different racial subgroups and vice versa, individuals typically identified as SOC tend to fall into the US Census categories American Indian or Alaska Native, Asian, Black, and Native Hawaiian or other Pacific Islander [1]. This population is historically underrepresented in dermatologic education, research, and workforce; in addition, many of the dermatologic disorders that disproportionately affect SOC populations are hampered by limited treatment options [2–7]. By 2044, more than half of all Americans will belong to a self-identified racial/ethnic group that is characterized by having SOC [8]. However, 2020 was a year in which pervasive social injustice and racial inequalities in the US were brought to light, further magnified by the disproportionate impact of Coronavirus Disease 2019 (COVID-19) on minority communities of color. [9] The field of dermatology is no exception. In 2021, the American Academy of Dermatology (AAD) announced its three-year plan to expand diversity, equity, and inclusion in dermatology. The major category initiatives included promoting diversity and inclusion within the AAD, increasing the number of underrepresented minority dermatologists, ensuring that dermatologic education and research encompasses health disparities and SOC, and expanding the Academy’s Advocacy Priorities to prioritize addressing health inequities [10]. This review provides a summary of important gaps in dermatology related to workforce diversity, SOC education, racial/ethnic disparities in specific dermatologic disorders, underrepresentation of minoritized populations in clinical trials, and the role of structural racism on health outcomes among racial and ethnic minority groups. Ongoing and proposed strategies to reduce the aforementioned gaps are also discussed. Diversity in the dermatology workforce Underrepresented in medicine (URiM) physicians are more likely to care for underserved racial/ethnic minority populations [11, 12]. However, previous studies demonstrated that patient-dermatologist racial concordance was preferred but not required for a positive experience. Instead, satisfaction was related to the dermatologist’s knowledge about Black skin and hair and a culturally sensitive interaction style [13]. Moreover, increasing the number of dermatologists with SOC is not the sole answer. The answer to increasing diversity in dermatology, healthcare equity, and improving patient satisfaction with dermatologists rests on the shoulders of all dermatologists. While race-concordant visits may contribute to greater patient trust, a diverse dermatologic workforce—especially at the level of residency program educators and organizational leaders—will likely translate into improved cross-cultural understanding overall such that culturally competent patient care interactions can be expected independent of the racial/ethnic background of the dermatologist [14–16]. Despite the need, analysis of data from 1973 to 2015 by the Association of American Medical Colleges showed that even though there was an increase, the proportion of URiM full-time US medical school faculty remained < 10%. [17] Lower-ranked faculty had high proportions of URiM and females [17]. Analyzing data from 1970 to 2018 showed that the number of full-time US dermatology female faculty increased from 18 (10.8%) to 749 (51.2%), but URiM faculty only grew from 8 (4.8%) to 109 (7.4%) [18]. Across all US specialties, White individuals represented 79.7% of department chairs, while URiM faculty only represented 8.6% of department chairs, with Black faculty representing 3.6%, Native American 0.1%, and Hispanic 4.9% of department chairs in 2018 [18]. One approach to helping increase the number of URiM faculty to improve cross-cultural understanding and thereby ensure the delivery of culturally sensitive care is to ensure that applicants and matriculants at medical schools nationwide are representative of the general population. Data from the 2010 US Census Bureau and 2011 Association of American Medical Colleges demonstrated that the racial demographics of US medical school applicants and matriculants was significantly different from that of the general population, with underrepresentation of African American (AA)/Black and American Indian/Alaskan Indian individuals [19]. In 2015, out of 46 possible residencies listed in Electronic Residency Application Service (ERAS), dermatology ranked 35th for attracting a diverse applicant pool (i.e., the percentage of total minority applicants) [20]. Of 1,259 applicants to dermatology in 2020, nine (0.7%) were American Indian/Alaskan Native, 94 (7.5%) were African American/Black, 106 (8.4%) were Hispanic, Latino, or Spanish origin, and three were Hawaiian or Other Pacific Islander (0.2%) compared to 616 (48.9%) White applicants [21]. Alpha Omega Alpha (AOA) medical honor society status is an important criterion in dermatology residency applications with 251 applicants in the 2020 Dermatology ERAS cycle being members [21]. However, AOA membership for White students is nearly 6 times greater than for Black students, and nearly 2 times greater than for Asian students [22]. In four of six required clerkships, grading disparities were found to favor White students over either URiM or non-URiM minority students [23]. Whereas the size and magnitude of differences in clerkship director rating were small, URiM students received approximately half as many honor grades as non-URiM students [24]. Racial grading disparities in medical school clerkships is only one of several ways in which minority students are disadvantaged from entering into dermatology, thereby precluding diversification of the dermatology workforce. When asked about barriers to applying for dermatology residency, minority students reported lack of diversity, perceived negative perceptions of minority students by residencies, socioeconomic factors, and lack of mentors as major barriers [25]. Skin of color education in dermatology COVID-19 disproportionately affects non-White race/ethnicities. However, a systematic review (SR) showed that of 130 clinical photos of COVID-19-related skin lesions, 92% (120 of 130) of them showed Fitzpatrick skin types (FST) I-III, while only 6% of them (7 of 130) showed patients with type IV skin. There were no images representing FST V or VI skin [26]. As COVID-19 was spreading, the AAD and International League of Dermatological Societies established an international registry to catalog skin manifestation of COVID-19. Of the 682 patients in the registry, only 13 (1.9%) were Black/African American, and 34 (5.0%) were Hispanic/Latino [27]. These findings could represent either a lower likelihood of dermatologists taking photos of SOC and consenting them for use in the registry, or it could also be because the manifestations were seen but not diagnosed as frequently because of lack of training to recognize skin disease in those with SOC. Dermatological disease presents differently in different skin tones, and current dermatology training may not equip graduates to make diagnoses with ease. A previous study found that 47% of dermatologists felt that their training was inadequate to diagnose skin disease in SOC patients [28]. A survey of program directors (PDs) and chief residents (CRs) reported that only 25.4% of the CRs and 19.5% of the PDs reported having lectures on SOC from an acknowledged expert [29]. Only 14.3% of CRs and 14.6% of PDs recognized an expert at their institutions who conducted a SOC clinic. Finally, only 30.2% of CRs and 12.2% of PDs reported a specific rotation in which residents gained experience in treating SOC [29]. Analysis of educational opportunities on SOC at AAD annual meetings from 1996 to 2005 showed that the percentage of teaching events focused on SOC was only 2%. Only eight out of 370 events available each year were devoted to ethnic skin [30]. These events were forums and focus sessions; none were postgraduate courses, discussion groups, or poster discussion groups [30]. Analysis of 4,146 textbook images from a sample of four general preclinical anatomy textbooks (i.e., Atlas of Human Anatomy, Bates’ Guide to Physical Examination and History Taking, Clinically Oriented Anatomy, and Gray’s Anatomy for Students) (2013–2015 editions) assigned at top medical schools showed that only 4.5% of images represented darker skin tones [31]. In 2021, updated analysis of the same textbooks found that only 1 textbook had a greater than 1% increase in representation of dermatologic diseases in darker skin tones compared to the original analysis. Dermatologic diseases with a racial predisposition such as erythema dyschromicum perstans were not commonly represented. In contrast, infectious diseases such as syphilis remained well-represented in all skin types, suggesting a possible bias when darker skin types are chosen to represent particular disorders [32]. Inadequate exposure and training in SOC in dermatology residency may affect quality of care delivered to SOC patients through incorrect or delayed diagnoses. Medical students at Tulane University School of Medicine and the University of Oklahoma College of Medicine were shown clinical images of various dermatological conditions in all skin types and asked to identify them. The conditions with the greatest disparity in visual diagnosis based on Fitzpatrick skin phototypes IV-VI vs. I-III were squamous cell carcinoma, urticaria, and atopic dermatitis (AD). Nearly, 34% of students misdiagnosed squamous cell carcinoma in SOC as melanoma, which may be explained by the students’ reliance on dark pigment alone as the feature of melanoma [33]. Previous studies demonstrated that non-Hispanic Black people are often diagnosed with melanoma at later stages. Moreover, the 5-year survival rate is 66% for non-Hispanic Black patients, compared with 90% for non-Hispanic Whites [34]. Risk of surgical delay for melanoma (surgical excision performed > 6 weeks after diagnosis) was found to be increased in non-White patients [35]. Nonmelanoma skin cancer (NMSC) in Black individuals is uncommon with an incidence of 3.4 per 100,000. Nevertheless, Black patients present with later stage or more aggressive SCC [36]. Machine learning (ML), a form of artificial intelligence using computer algorithms, is being used to create programs capable of distinguishing between benign and malignant lesions [37]. A study that tested ML software in dermatology found that deep-learning convolutional neural networks detected potentially cancerous skin lesions better than most dermatologists included in the study (n = 58). [38] However, the images used in the study came from the International Skin Imaging Collaboration: Melanoma Project that heavily collects data from fair-skinned populations in the USA, Europe, and Australia. [39] Therefore, as it stands, ML may only benefit the detection of cancer in lighter skinned individuals. [39] Diversity of patient populations Financial incentives may be a factor in providing care to specific patient populations and may be a contributing factor in perpetuating healthcare inequalities. Among 183,054 Medical Expenditure Panel Survey (MEPS) respondents, Hispanic and Black patients were less likely to receive outpatient dermatological care than non-Hispanic White patients. Per capita expenditure of outpatient dermatologist visits for non-Hispanic White patients ($209.50) was approximately 3 times that of Hispanic ($73.09) and Black ($62.70) patients. The cost per visit was also greater for non-Hispanic White patients ($244.88) than for Hispanic ($191.14) and Black ($170.94) patients [40]. A cross-sectional study of 66,463 dermatology encounters across 30,036 patients showed that in the general dermatologic practice, the mean (standard deviation) work relative value units (wRVUs) per encounter was 1.40 (0.71). Compared to general dermatology visits with White patients, visits with Black patients generated 0.27 fewer wRVUs per encounter, visits with Asian patients generated 0.22 fewer wRVUs per encounter, and visits with patients of other races generated 0.19 fewer wRVUs per encounter. In the general dermatologic practice excluding Mohs surgeons, the observed differences in race were due to the destruction of premalignant lesions and biopsies in White patients. Consequently, it was suggested that compensation based on wRVUs may incentivize dermatologists to care for patients more likely to develop skin cancers and perpetuate disparities in dermatologic care [41]. Disparities in skin conditions Racial disparities exist in health-related quality of life within dermatologic diseases. One study enrolled 134 patients of which 28% (n = 35) were African American (AA); 67% (n = 84) were White; and 5% were classified as other. Median Dermatology Life Quality Index and Skindex-29 scores among AAs were significantly higher compared to Whites. Further, a larger proportion of AAs compared to Whites had stage 3 and 4 disease (more severe) by the Dermatology Index of Disease Severity [42]. Black patients with AD were less likely to receive desonide, tacrolimus, pimecrolimus, crisaborole, and dupilumab. The exception was hydrocortisone [43]. The National Ambulatory Medical Care Survey from 2005–2014 found that Black patients were less likely than White patients to visit a dermatologist for acne care [44]. Black patients with acne had significantly lower odds of receiving isotretinoin, adapalene, tazarotene, oral antibiotics, and spironolactone in comparison to White patients [43, 45]. The exceptions were tretinoin and benzoyl peroxide. Hispanic patients with acne had statistically lower odds of receiving tretinoin compared to non-Hispanics [43]. Even though African Americans had less psoriasis compared to Whites, they had more severe skin involvement with greater psychological impact and impaired quality of life (QOL) [46]. Previous studies also found that amongst Medicare recipients, Black patients had a significantly lower likelihood of receiving biologic medications [47]. A later study found that the disparity in the use of biologics amongst Black patients may be due to general unfamiliarity with biologic medications within this group of individuals, regardless of income or education level. In addition, they found that Black patients have increased fear of side effects and a stronger preference to avoid needles, which may contribute to racial disparities in psoriasis care [48]. Further education about use of biologics for psoriasis treatment is needed in Black patients. Mycosis fungoides (MF) also has a higher incidence and poorer prognosis in AA patients. In Black patients, MF often presents as polymorphic pigmentation and secondary lichenification that is frequently misdiagnosed as AD, tinea versicolor, and/or vitiligo [49]. Moreover, Black patients were three times as likely to have Stage 2 disease at diagnosis compared to Whites. In females, Black patients were younger at diagnosis and at death compared to Whites. In males, Blacks had 4 times the odds of late-stage disease and presented with 19% body surface area involvement on average compared to White patients. In another study examining 65 patients with stage III or IV disease, only seven of 20 AA patients (35%) compared with 30 of 45 (66%) White patients were treated with extracorporeal photopheresis (ECP). Further, ECP was discussed as an option for only 45% of AAs compared to 82% of Whites. When discussed as an option, AAs and Whites had identical rates of ECP use [50]. Earlier recognition of MF in SOC and closer follow-up of Black patients, especially females, may help mitigate disparities in outcomes [51]. AA race was identified as a predictor of poor overall survival in MF patients, even after controlling for disease characteristics, socioeconomic factors, and types of treatment, warranting further investigation into the underlying biology of MF and prescribed treatment modalities [52]. The true prevalence of hidradenitis suppurativa (HS) in the general US population may likely be higher due to limitations in diagnosis, underdiagnosis, misdiagnosis, and patient reluctance to seek treatment [53]. This may be especially true in SOC populations due to limited access to medical care, implicit biases, anatomical differences, genetics, and increased prevalence of lower socioeconomic status among these groups [54, 55]. HS is associated with increased odds of depression, antidepressant use, anxiety, anxiolytic use, and suicidality. [56]. This has serious implications for AAs and Latinos in comparison with Whites because they are already at risk for a wide range of psychosocial stressors [57]. A study that oversampled AAs and Hispanics/Latinos in relation to Whites found that major depression was most prevalent amongst Latinos (11%) followed by AAs (8%), and then Whites (8%). The differences in depression rates were thought to be due to functional limitations, lack of health insurance, and lifestyle factors such as smoking and exercise which varied among the racial groups [58]. Given these findings, AA and Latino patients with HS may be at higher risk for developing depression and more severe forms of depression in comparison with the overall HS population [59]. A recent study found AA patients accounted for almost half (47%) of US hospitalizations for HS. The study suggested a significant link between the geographic distribution of HS hospitalizations, racial distribution of AAs, and prevalence of adult obesity across the USA [60]. Further, a recent study demonstrated that urban zip codes with higher percentages of AAs tended to have  fewer dermatologists, while urban zip codes with lower percentages of AAs tended to have more dermatologists. In the areas with higher representation of AAs, dermatologists were responsible for more people per provider than recommended (> 25,000 people/dermatologist) [61]. Hence, limited access to care along with a higher number of comorbidities may contribute to more severe disease necessitating higher rates of hospitalization amongst African Americans [59]. Individuals with HS were significantly more likely to report being victimized by intimate partner violence (IPV) [62]. According to the 2010 National Intimate Partner and Sexual Violence Survey, non-Hispanic Black and Native American/Alaska Native women reported higher prevalence rates of lifetime IPV (43.7% and 46%, respectively) compared to non-Hispanic White women (34.6%). These disproportionate rates were also consistently documented in multiple US studies [63]. Screening for IPV should be incorporated into care of HS patients, especially those of SOC [59]. Further, β-lactams, such as cefazolin, are considered first-line therapy for Staphylococcus aureus and Streptococcus species causing skin and soft tissue infections (SSTIs). Alternative treatments, such as clindamycin, are considered inferior [64]. A large analysis (n = 1242) of adult inpatients from 91 US hospitals treated for SSTIs found that cefazolin was more commonly used in White inpatients than in Black inpatients [13% (n = 114) vs 5% (n = 11)]; clindamycin was more frequently used in Black inpatients than in White inpatients [12% (n = 27) vs 7% (n = 62)]. Adjusting for multiple factors (e.g., methicillin-resistant Staphylococcus aureus colonization, infection, and penicillin allergy), White inpatients were at an increased risk of cefazolin use [aOR, 2.82 (95% CI 1.41–5.63)] and decreased risk of clindamycin use [aOR, 0.54 (95% CI 0.30–0.96)] compared with Black inpatients [65]. Limitations of objective scoring systems One of the most commonly used classification systems in dermatology is the Fitzpatrick skin type [66]. It was developed in 1975 by Thomas B. Fitzpatrick to assess the propensity of the skin to burn during phototherapy. The original FST included skin types I through IV; skin types V and VI were later added to include individuals of Asian, Indian, and African origin with brown to black complexions [66]. From that, FST became used by providers as rather a surrogate to describe race and ethnicity instead of Fitzpatrick’s original intent of using it as a measure to label a person’s reaction to phototherapy. A study performed on 43 healthy Thai volunteers found that FST did not correspond well to the constitutive and facultative skin color. There was also no correlation between skin type and minimal erythema dose, and no relation between skin type and the slope of the dose–response curves for erythema and pigmentation [67]. Moreover, race and pigmentary phototypes do not provide an accurate predictor of sun sensitivity as defined by FST [68]. A survey of 140 dermatologists and dermatology trainees found that approximately one-third to one-half of academic dermatologists/dermatology trainees used FST to describe race/ethnicity and/or constitutive skin color. The misuse of FST may occur more frequently amongst physicians who do not identify as SOC [66]. Using FST as a proxy for race may still exist because there are no other widely accepted classification system for describing skin color in all skin types [66]. More culturally appropriate and clinically relevant methods for describing skin color need to be developed and used, and the original intent of FST should be emphasized and incorporated into dermatology education and training. Erythema in darker skin individuals may appear more violaceous and be completely missed by practitioners who are not trained to detect nuances in erythema presentation in SOC [69]. The use of common scoring systems that rely on skin erythema, including SCORAD, SASSAD, NESS, and EASI, were found to significantly underestimate the severity of AD in darker skin types [70–72]. Psoriasis in SOC patients may also present with less conspicuous erythema, even appearing violaceous or hyperchromic. It more often resolves with post-inflammatory hypo- or hyperpigmentation. In clinical research, severity of psoriasis is commonly assessed using the psoriasis area and severity index, which uses erythema as one of its indices. Similar to AD, erythema in psoriasis can be more challenging to detect in darker skinned individuals, as involved areas may have a dark brown or violaceous hue instead of the pink or red color typically observed in patients with lighter complexions. Further challenges can arise in those with heavily pigmented skin, where distinguishing psoriasis from lichen planus (especially the hypertrophic type), sarcoidosis, and cutaneous lupus can be more challenging and lead to unnecessary biopsies [73]. Patient diversity in clinical trials Inadequate representation of different races and ethnicities is a problem in national and international clinical trials. A SR of RCTs conducted between July 2010–July 2015 involving psoriasis, AD, acne, vitiligo, seborrheic dermatitis, alopecia areata, and lichen planus found that overall, only 52 of 626 international (11.3%) studies, and 58 of 97 studies (59.8%) conducted exclusively within the USA, reported on racial or ethnic demographics of study participants [74]. Psoriasis studies included the least diversity with 84.3% of total study participants recorded as White. Funding source and journal type did not demonstrate a statistically significant relationship with respect to diversity of study subjects [74]. In 2014, a review of US AD therapy studies was performed to assess for racial differences in treatment response. Only eighteen US studies were identified, of which nine were included. The sample size of patients ranged from 5 to 28. Only two studies reported data on treatment responses in different races or ethnicities. Moreover, a lack of diversity in clinical trials limits the generalizability of many results to racial and ethnic minorities [75, 76]. Reduced enrollment in clinical trials of SOC populations may be due to distance from clinical trial sites, lack of education regarding clinical trials, lack of awareness that clinical trials are available for the particular disorder, language barriers, and mistrust of researchers from historical experiences such as The United States Public Health Service Syphilis Study at Tuskegee [77]. A survey of 90 AA and White parents in an academic dermatology clinic found that AAs were 3 times as likely to feel that their child might be “treated like a guinea pig” if the child was a research subject. Nearly one-third more Whites than AAs were more inclined to enroll their healthy child in a research study if they had an established relationship with the healthcare provider informing them of the study. Nevertheless, there was no racial difference in the willingness to theoretically allow their child to participate in research studies [78]. Adalimumab is approved for HS treatment. However, clinical trials for adalimumab did not sufficiently examine treatment response in SOC patients [79–82]. One study was conducted solely in White and Romany individuals, [75] while another study consisted of 80–85% Whites [81]. No trials reported the percentage of patients that were Hispanic/Latino or stratified responses to adalimumab by race. [55] Other published systemic biologic agent trials for HS (e.g., etanercept, infliximab, anakinra, and ustekinumab) either did not report race or largely had a White population [83–86]. Structural racism in medicine A discussion about racial disparities in dermatology would not be complete without clearly acknowledging the role of structural racism on health outcomes amongst racial and ethnic minority groups. There is not necessarily one “official” definition of structural racism, but all definitions make clear that structural racism is not simply the product of individual prejudice and discrimination [87]. Structural racism include public policies, social forces, institutional practices, and macro-level systems that interact with each other to create an environment that continually perpetuates racial inequality. It brings to light forces within our society’s structure that allow racism to endure and adapt over time [88]. An example of structural racism that was identified in AD studies suggested possible gene-environment interactions may better explain the differences seen in the severity between racial and ethnic groups [89]. Factors that were previously discussed as contributing to AD severity (i.e., living in rented homes, being in lower income families, having caregivers with lower educational attainment, and living in highly segregated communities) were found to be more likely in AA children with AD [90]. Although redlining officially ended with the Fair Housing Act of 1968, its lasting effects are still seen today in US cities. Residential discrimination lead to a culture of broad social disinvestment, especially in neighborhood infrastructure (e.g., green space, housing stock, and roads), services (e.g., transport, schools, and garbage collection), and employment. [87] Moreover, neighborhoods that were not part of this redlining had lower levels of carcinogens and higher levels of canopy coverage which mitigates air pollutants and heat [91]. Systematic disinvestment in these neighborhoods makes it difficult to attract primary-care providers and specialists to predominantly Black neighborhoods and have lower-quality facilities with fewer clinicians than those in other neighborhoods [92]. This also highlights that the social construct of race should not be mistakenly viewed as being part of an intrinsic biologic difference [87]. Dismantling pervasive structural racism involves the whole of society. It requires moving beyond the individual to affecting change at the policy level and changing societal norms. The healthcare community can start by acknowledging and educating ourselves on the health impacts of racism. A previous study found that only 25 articles named institutionalized racism in the title or abstract among all articles published in the 50 highest-impact journals from 2002 to 2015 across six different categories representing the public health field in the USA [93] Institutionalized racism was a core concept in 16 of 25 articles [93]. Moreover, studies showed that despite the long history of racism and its effects on health, scientific research showing its impact on health is rarely published in major medical journals [92, 93]. Further, lack of diversity in clinical trials and the inclusion of SOC populations is leading to biased research that further bolsters structural racism. Efforts not only need to be made to ensure that the makeup of clinical trials is reflective of the general population and/or reflective of communities significantly burdened by the disorder being researched (e.g. HS), but also that more data that includes race and ethnicity should be encouraged and collected. Finally, something to be considered when measuring the success of an intervention could be how it narrows the inequitable gaps in health (e.g., between Black people and White people) instead of focusing solely on the overall population [87]. Conclusion There remains a significant amount of change that is needed across dermatology and a need for increased awareness of the current issues facing SOC populations. Dermatologists must be aware of existing racial/ethnic health disparities amongst SOC patients and how their treatment, satisfaction, QOL, and health outcomes are being impacted. We must continue to work toward increasing the diversity of the dermatology workforce, increasing diversity education of current dermatologists in practice, including a diverse range of skin tones in images used in dermatology training, and teaching trainees how diseases may present differently in different skin tones. Acknowledgements This manuscript was created based on lectures presented at the 2021 Revolutionizing Atopic Dermatitis (RAD) international, multidisciplinary conference on December 11-13, 2021. Author contributions S.N., C.H., A.A. and J.I.S. wrote and edited the main manuscript text. All authors reviewed the manuscript. Data availability Not applicable. Declarations Competing interests The authors declare no competing interests. Conflict of interests None. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Taylor SC, Kyei A. Defining Skin of Color. In: Kelly AP, Taylor SC, Lim HW, Serrano AMA, eds. Taylor and Kelly's Dermatology for Skin of Color, 2e. New York, NY: McGraw-Hill Education; 2016. 2. Yousuf Y Yu JC Improving representation of skin of color in a medical school preclerkship dermatology curriculum Med Sci Educator 2022 32 1 27 30 10.1007/s40670-021-01473-x 3. Wilson BN Sun M Ashbaugh AG Assessment of skin of color and diversity and inclusion content of dermatologic published literature: An analysis and call to action Int J Womens Dermatol 2021 7 4 391 397 10.1016/j.ijwd.2021.04.001 34621950 4. Buster KJ, Stevens EI, Elmets CA. Dermatologic health disparities. Dermatologic clinics. 2012;30(1):53–59, viii. 5. Lu JD Sverdlichenko I Siddiqi J Khosa F Barriers to diversity and academic promotion in dermatology: recommendations moving forward Dermatology 2021 237 4 489 492 10.1159/000514537 33823510 6. Akhiyat S Cardwell L Sokumbi O Why dermatology is the second least diverse specialty in medicine: How did we get here? Clin Dermatol 2020 38 3 310 315 10.1016/j.clindermatol.2020.02.005 32563342 7. Lawson CN Hollinger J Sethi S Updates in the understanding and treatments of skin & hair disorders in women of color Int J Womens Dermatol 2017 3 1 Suppl S21 s37 10.1016/j.ijwd.2017.02.006 28492036 8. Bureau UC. Projections of the size and composition of the U.S. population. In: Bureau UC, ed2015. 9. Tai DBG Shah A Doubeni CA Sia IG Wieland ML The disproportionate impact of COVID-19 on racial and ethnic minorities in the United States Clin Infect Dis 2020 72 4 703 706 10.1093/cid/ciaa815 10. Diversity In Dermatology: Diversity Committee Approved Plan 2021–2023 [press release]. 2021. 11. Marrast LM Zallman L Woolhandler S Bor DH McCormick D Minority physicians’ role in the care of underserved patients: diversifying the physician workforce may be key in addressing health disparities JAMA Intern Med 2014 174 2 289 291 10.1001/jamainternmed.2013.12756 24378807 12. Xierali IM Nivet MA The racial and ethnic composition and distribution of primary care physicians J Health Care Poor Underserved 2018 29 1 556 570 10.1353/hpu.2018.0036 29503317 13. Gorbatenko-Roth K Prose N Kundu RV Patterson S Assessment of black patients’ perception of their dermatology care JAMA Dermatol 2019 155 10 1129 1134 10.1001/jamadermatol.2019.2063 31433446 14. Grayson C Heath C An approach to examining tightly coiled hair among patients with hair loss in race-discordant patient-physician interactions JAMA Dermatol 2021 157 5 505 506 10.1001/jamadermatol.2021.0338 33787820 15. Jones NL Heath CR Hair at the intersection of dermatology and anthropology: a conversation on race and relationships Pediatr Dermatol 2021 38 S2 158 160 10.1111/pde.14721 34342039 16. Grayson C Heath CR Counseling about traction alopecia: a "compliment, discuss, and suggest" method Cutis 2021 108 1 20 22 10.12788/cutis.0297 17. Xierali IM, Fair, M.A., Nivet, M.A. Faculty Diversity in U.S. Medical Schools: Progress and Gaps Coexist. Analysis in brief. 2016;16(6). 18. Xierali IM Nivet MA Pandya AG US dermatology department faculty diversity trends by sex and underrepresented-in-medicine status, 1970 to 2018 JAMA Dermatol 2020 156 3 280 287 10.1001/jamadermatol.2019.4297 31913403 19. Smith MM Rose SH Schroeder DR Long TR Diversity of United States medical students by region compared to US census data Adv Med Educ Pract 2015 6 367 372 26028982 20. Van Voorhees AS Enos CW Diversity in dermatology residency programs J Investigative Dermatol Symp Proc 2017 18 2 S46 S49 10.1016/j.jisp.2017.07.001 21. AAMC. Residency applicants from U.S. M.D.-granting medical schools by specialty, race/ethnicity, 2020. 2020; https://www.aamc.org/media/39371/download. Accessed February 23, 2021. 22. Boatright D Ross D O'Connor P Moore E Nunez-Smith M Racial disparities in medical student membership in the alpha omega alpha honor society JAMA Intern Med 2017 177 5 659 665 10.1001/jamainternmed.2016.9623 28264091 23. Low D Pollack SW Liao ZC Racial/ethnic disparities in clinical grading in medical school Teach Learn Med 2019 31 5 487 496 10.1080/10401334.2019.1597724 31032666 24. Teherani A Hauer KE Fernandez A King TE Jr Lucey C How small differences in assessed clinical performance amplify to large differences in grades and awards: a cascade with serious consequences for students underrepresented in medicine Acad Med 2018 93 9 1286 1292 10.1097/ACM.0000000000002323 29923892 25. Soliman YS Rzepecki AK Guzman AK Understanding perceived barriers of minority medical students pursuing a career in dermatology JAMA Dermatol 2019 155 2 252 254 10.1001/jamadermatol.2018.4813 30624570 26. Lester JC Jia JL Zhang L Okoye GA Linos E Absence of images of skin of colour in publications of COVID-19 skin manifestations Br J Dermatol 2020 183 3 593 595 10.1111/bjd.19258 32471009 27. Freeman EE McMahon DE Lipoff JB The spectrum of COVID-19-associated dermatologic manifestations: an international registry of 716 patients from 31 countries J Am Acad Dermatol 2020 83 4 1118 1129 10.1016/j.jaad.2020.06.1016 32622888 28. Lester JC Taylor SC Chren MM Under-representation of skin of colour in dermatology images: not just an educational issue Br J Dermatol 2019 180 6 1521 1522 10.1111/bjd.17608 31157429 29. Nijhawan RI Jacob SE Woolery-Lloyd H Skin of color education in dermatology residency programs: Does residency training reflect the changing demographics of the United States? J Am Acad Dermatol 2008 59 4 615 618 10.1016/j.jaad.2008.06.024 18657339 30. Ebede T Papier A Disparities in dermatology educational resources J Am Acad Dermatol 2006 55 4 687 690 10.1016/j.jaad.2005.10.068 17010750 31. Louie P Wilkes R Representations of race and skin tone in medical textbook imagery Soc Sci Med 2018 202 38 42 10.1016/j.socscimed.2018.02.023 29501717 32. Adelekun A Onyekaba G Lipoff JB Skin color in dermatology textbooks: an updated evaluation and analysis J Am Acad Dermatol 2021 84 1 194 196 10.1016/j.jaad.2020.04.084 32335181 33. Fenton A Elliott E Shahbandi A Medical students' ability to diagnose common dermatologic conditions in skin of color J Am Acad Dermatol 2020 83 3 957 958 10.1016/j.jaad.2019.12.078 32017947 34. Culp MB Lunsford NB Melanoma Among Non-Hispanic Black Americans Prev Chronic Dis 2019 16 E79 10.5888/pcd16.180640 31228233 35. Adamson AS Zhou L Baggett CD Thomas NE Meyer A-M Association of delays in surgery for melanoma with insurance type JAMA Dermatol 2017 153 11 1106 1113 10.1001/jamadermatol.2017.3338 28979974 36. Buster KJ, Stevens EI, Elmets CA. Dermatologic health disparities. Dermatologic clinics. 2012;30(1):53-viii. 37. Esteva A Kuprel B Novoa RA Dermatologist-level classification of skin cancer with deep neural networks Nature 2017 542 7639 115 118 10.1038/nature21056 28117445 38. Haenssle HA Fink C Schneiderbauer R Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists Ann Oncol 2018 29 8 1836 1842 10.1093/annonc/mdy166 29846502 39. Adamson AS Smith A Machine learning and health care disparities in dermatology JAMA Dermatol 2018 154 11 1247 1248 10.1001/jamadermatol.2018.2348 30073260 40. Tripathi R Knusel KD Ezaldein HH Scott JF Bordeaux JS Association of demographic and socioeconomic characteristics with differences in use of outpatient dermatology services in the United States JAMA Dermatol 2018 154 11 1286 1291 10.1001/jamadermatol.2018.3114 30267073 41. Orenstein LAV, Nelson MM, Wolner Z, et al. Differences in Outpatient Dermatology Encounter Work Relative Value Units and Net Payments by Patient Race, Sex, and Age. JAMA Dermatology. 2021. 42. Are there racial disparities in health-related quality of life in patients with skin disease? Journal of the American Academy of Dermatology. 2008;58(2):AB76. 43. Bell MA Whang KA Thomas J Aguh C Kwatra SG Racial and ethnic disparities in access to emerging and frontline therapies in common dermatological conditions: a cross-sectional study J Natl Med Assoc 2020 112 6 650 653 32641259 44. Rogers AT Semenov YR Kwatra SG Okoye GA Racial disparities in the management of acne: evidence from the National Ambulatory Medical Care Survey, 2005–2014 J Dermatolog Treat 2018 29 3 287 289 10.1080/09546634.2017.1371836 28831837 45. Barbieri JS Shin DB Wang S Margolis DJ Takeshita J Association of race/ethnicity and sex with differences in health care use and treatment for acne JAMA Dermatol 2020 156 3 312 319 10.1001/jamadermatol.2019.4818 32022834 46. Kerr GS Qaiyumi S Richards J Psoriasis and psoriatic arthritis in African-American patients—the need to measure disease burden Clin Rheumatol 2015 34 10 1753 1759 10.1007/s10067-014-2763-3 25164561 47. Takeshita J Gelfand JM Li P Psoriasis in the US medicare population: prevalence, treatment, and factors associated with biologic use J Investig Dermatol 2015 135 12 2955 2963 10.1038/jid.2015.296 26214380 48. Takeshita J Eriksen WT Raziano VT Racial differences in perceptions of psoriasis therapies: implications for racial disparities in psoriasis treatment J Investig Dermatol 2019 139 8 1672 1679.e1671 10.1016/j.jid.2018.12.032 30738054 49. Okoye GA Newsome A McKay S Harvey VM Health disparities in mycosis fungoides Cogent Medicine 2016 3 1 1134041 10.1080/2331205X.2015.1134041 50. Agi C Kuhn D Chung J Zampella J Hinds G Racial differences in the use of extracorporeal photopheresis for mycosis fungoides J Dermatol Treat 2015 26 3 266 268 10.3109/09546634.2014.946381 51. Huang AH Kwatra SG Khanna R Semenov YR Okoye GA Sweren RJ Racial disparities in the clinical presentation and prognosis of patients with mycosis fungoides J Natl Med Assoc 2019 111 6 633 639 31623818 52. Su C Nguyen KA Bai HX Racial disparity in mycosis fungoides: an analysis of 4495 cases from the US National Cancer Database J Am Acad Dermatol 2017 77 3 497 502.e492 10.1016/j.jaad.2017.04.1137 28645647 53. Garg A Wertenteil S Baltz R Strunk A Finelt N Prevalence estimates for hidradenitis suppurativa among children and adolescents in the united states: a gender- and age-adjusted population analysis J Invest Dermatol 2018 138 10 2152 2156 10.1016/j.jid.2018.04.001 29660301 54. Lee DE Clark AK Shi VY Hidradenitis suppurativa: disease burden and etiology in skin of color Dermatology 2017 233 6 456 461 10.1159/000486741 29495009 55. Price KN, Hsiao JL, Shi VY. Race and Ethnicity Gaps in Global Hidradenitis Suppurativa Clinical Trials. Dermatology. 2019:1–6. 56. Patel KR, Lee HH, Rastogi S, et al. Association between hidradenitis suppurativa, depression, anxiety, and suicidality: A systematic review and meta-analysis. J Am Acad Dermatol. 2019. 57. Williams DR Priest N Anderson NB Understanding associations among race, socioeconomic status, and health: patterns and prospects Health Psychol 2016 35 4 407 411 10.1037/hea0000242 27018733 58. Dunlop DD Song J Lyons JS Manheim LM Chang RW Racial/ethnic differences in rates of depression among preretirement adults Am J Public Health 2003 93 11 1945 1952 10.2105/AJPH.93.11.1945 14600071 59. Narla SH, N., Hamazavi, I.H. Skin of Color. In: Shi VY, Hsaio, J.L., Lowes, M., Hamzavi, I.H. , ed. A Comprehensive Guide to Hidradenitis Suppurativa. First ed: Elsevier; 2022. 60. Anzaldi L, Perkins JA, Byrd AS, Kharrazi H, Okoye GA. Characterizing inpatient hospitalizations for hidradenitis suppurativa in the United States. J Am Acad Dermatol. 2019. 61. Vengalil N, Nakamura, M., Helfrich, Y. . Analyzing the Distribution of Dermatologists in the Urban Setting: Comparing Zip Codes with High and Low Representation of African Americans. American Academy of Dermatology; 2020. 62. Sisic M Tan J Lafreniere KD Hidradenitis suppurativa, intimate partner violence, and sexual assault J Cutan Med Surg 2017 21 5 383 387 10.1177/1203475417708167 28481644 63. Stockman JK Hayashi H Campbell JC Intimate partner violence and its health impact on ethnic minority women [corrected] J Womens Health (Larchmt) 2015 24 1 62 79 10.1089/jwh.2014.4879 25551432 64. Stevens DL Bisno AL Chambers HF Practice guidelines for the diagnosis and management of skin and soft tissue infections: 2014 update by the infectious diseases society of America Clinical Infect Dis 2014 59 2 e10 52 10.1093/cid/ciu296 24973422 65. Wurcel AG Essien UR Ortiz C Variation by race in antibiotics prescribed for hospitalized patients with skin and soft tissue infections JAMA Netw Open 2021 4 12 e2140798 e2140798 10.1001/jamanetworkopen.2021.40798 34940871 66. Ware OR Dawson JE Shinohara MM Taylor SC Racial limitations of fitzpatrick skin type Cutis 2020 105 2 77 80 32186531 67. Leenutaphong V Relationship between skin color and cutaneous response to ultraviolet radiation in Thai Photodermatol Photoimmunol Photomed 1996 11 5–6 198 203 68. He SY McCulloch CE Boscardin WJ Chren M-M Linos E Arron ST Self-reported pigmentary phenotypes and race are significant but incomplete predictors of Fitzpatrick skin phototype in an ethnically diverse population J Am Acad Dermatol 2014 71 4 731 737 10.1016/j.jaad.2014.05.023 24928709 69. Kaufman BP Guttman-Yassky E Alexis AF Atopic dermatitis in diverse racial and ethnic groups—variations in epidemiology, genetics, clinical presentation and treatment Exp Dermatol 2018 27 4 340 357 10.1111/exd.13514 29457272 70. Ben-Gashir MA Hay RJ Reliance on erythema scores may mask severe atopic dermatitis in black children compared with their white counterparts Br J Dermatol 2002 147 5 920 925 10.1046/j.1365-2133.2002.04965.x 12410701 71. Vachiramon V Tey HL Thompson AE Yosipovitch G Atopic dermatitis in African American children: addressing unmet needs of a common disease Pediatr Dermatol 2012 29 4 395 402 10.1111/j.1525-1470.2012.01740.x 22471955 72. Zhao CY Wijayanti A Doria MC The reliability and validity of outcome measures for atopic dermatitis in patients with pigmented skin: a grey area Int J Womens Dermatol 2015 1 3 150 154 10.1016/j.ijwd.2015.05.002 28491979 73. Alexis AF Blackcloud P Psoriasis in skin of color: epidemiology, genetics, clinical presentation, and treatment nuances J Clin Aesthet Dermatol 2014 7 11 16 24 74. Charrow A Xia FD Joyce C Mostaghimi A Diversity in dermatology clinical trials: a systematic review JAMA Dermatol 2017 153 2 193 198 10.1001/jamadermatol.2016.4129 28055072 75. Bhattacharya T Silverberg JI Efficacy of systemic treatments for atopic dermatitis in racial and ethnic minorities in the United States JAMA Dermatol 2014 150 11 1232 1234 10.1001/jamadermatol.2014.1674 25207604 76. Price KN Krase JM Loh TY Hsiao JL Shi VY Racial and ethnic disparities in global atopic dermatitis clinical trials Br J Dermatol 2020 183 2 378 380 10.1111/bjd.18938 32030728 77. Kailas A Dawkins M Taylor SC Suggestions for increasing diversity in clinical trials JAMA Dermatol 2017 153 7 727 10.1001/jamadermatol.2017.0850 78. Shaw MG Morrell DS Corbie-Smith GM Goldsmith LA Perceptions of pediatric clinical research among African American and Caucasian parents J Natl Med Assoc 2009 101 9 900 907 19806847 79. Arenbergerova M Gkalpakiotis S Arenberger P Effective long-term control of refractory hidradenitis suppurativa with adalimumab after failure of conventional therapy Int J Dermatol 2010 49 12 1445 1449 10.1111/j.1365-4632.2010.04638.x 21091684 80. Kimball AB Kerdel F Adams D Adalimumab for the treatment of moderate to severe Hidradenitis suppurativa: a parallel randomized trial Ann Intern Med 2012 157 12 846 855 10.7326/0003-4819-157-12-201212180-00004 23247938 81. Kimball AB Okun MM Williams DA Two phase 3 trials of adalimumab for Hidradenitis Suppurativa N Engl J Med 2016 375 5 422 434 10.1056/NEJMoa1504370 27518661 82. Miller I Lynggaard CD Lophaven S Zachariae C Dufour DN Jemec GB A double-blind placebo-controlled randomized trial of adalimumab in the treatment of hidradenitis suppurativa Br J Dermatol 2011 165 2 391 398 10.1111/j.1365-2133.2011.10339.x 21457202 83. Blok JL Li K Brodmerkel C Horvatovich P Jonkman MF Horvath B Ustekinumab in hidradenitis suppurativa: clinical results and a search for potential biomarkers in serum Br J Dermatol 2016 174 4 839 846 10.1111/bjd.14338 26641739 84. Pelekanou A Kanni T Savva A Long-term efficacy of etanercept in hidradenitis suppurativa: results from an open-label phase II prospective trial Exp Dermatol 2010 19 6 538 540 10.1111/j.1600-0625.2009.00967.x 19758320 85. Grant A Gonzalez T Montgomery MO Cardenas V Kerdel FA Infliximab therapy for patients with moderate to severe hidradenitis suppurativa: a randomized, double-blind, placebo-controlled crossover trial J Am Acad Dermatol 2010 62 2 205 217 10.1016/j.jaad.2009.06.050 20115947 86. Tzanetakou V Kanni T Giatrakou S Safety and efficacy of anakinra in severe hidradenitis suppurativa: a randomized clinical trial JAMA Dermatol 2016 152 1 52 59 10.1001/jamadermatol.2015.3903 26579854 87. Bailey ZD, Feldman JM, Bassett MT. How Structural Racism Works - Racist Policies as a Root Cause of U.S. Racial Health Inequities. The New England journal of medicine. 2021;384(8):768–773. 88. Gee GC Ford CL Structural racism and health inequities: old issues New Directions Du Bois Rev 2011 8 1 115 132 10.1017/S1742058X11000130 25632292 89. Berger M Sarnyai Z "More than skin deep": stress neurobiology and mental health consequences of racial discrimination Stress (Amsterdam, Netherlands) 2015 18 1 1 10 10.3109/10253890.2014.989204 25407297 90. Tackett KJ, Jenkins F, Morrell DS, McShane DB, Burkhart CN. Structural racism and its influence on the severity of atopic dermatitis in African American children. Pediatric dermatology. 2019. 91. Namin S Xu W Zhou Y Beyer K The legacy of the home owners’ loan corporation and the political ecology of urban trees and air pollution in the United States Soc Sci Med 2020 246 112758 10.1016/j.socscimed.2019.112758 31884239 92. Bailey ZD Krieger N Agénor M Graves J Linos N Bassett MT Structural racism and health inequities in the USA: evidence and interventions Lancet (London, England) 2017 389 10077 1453 1463 10.1016/S0140-6736(17)30569-X 28402827 93. Hardeman RR Murphy KA Karbeah J Kozhimannil KB Naming institutionalized racism in the public health literature: a systematic literature review Public Health Rep 2018 133 3 240 249 10.1177/0033354918760574 29614234
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==== Front Metab Brain Dis Metab Brain Dis Metabolic Brain Disease 0885-7490 1573-7365 Springer US New York 36507937 1134 10.1007/s11011-022-01134-x Review Article Remote monitoring of cognition in cirrhosis and encephalopathy: future opportunity and challenge http://orcid.org/0000-0002-0068-353X Buckholz Adam P. http://orcid.org/0000-0003-3981-7053 Rosenblatt Russell [email protected] grid.5386.8 000000041936877X NewYork-Presbyterian/Weill Cornell Medical College Division of Gastroenterology and Hepatology, New York, NY 10021 USA 12 12 2022 111 27 9 2022 24 11 2022 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Hepatic Encephalopathy (HE) is a critically important complication of chronic liver disease and portal hypertension, but especially in early covert stages remains underdiagnosed and a common cause of hospitalization and morbidity. Defined by often subtle neuropsychiatric changes, significant cognitive deficits have been extensively described. While traditional methods of assessment remain underutilized in practice and subject to significant confounding with other diseases, mobile technology has emerged as a potential future tool to provide simple and dynamic cognitive assessments. This review discusses the proliferation of cognitive assessment tools, describing possible applications in encephalopathy and the challenges such an implementation may face. There are significant potential advantages to assessing cognition in real time in order to aid early detection and intervention and provide a more realistic measurement of real-world function. Despite this, there are issues with reliability, privacy, applicability and more which must be addressed prior to wide proliferation and acceptance for clinical use. Regardless, the rapid uptake of mobile technology in healthcare is likely to have significant implications for the future management of encephalopathy and liver disease at large. Keywords Encephalopathy Portal hypertension Remote monitoring Mobile technology Cognition Liver disease ==== Body pmcIntroduction Hepatic encephalopathy (HE) is an important cause of hospitalization, need for transplant, and death in those with chronic liver disease and cirrhosis. Additionally, it has a profound deleterious effect on patient wellbeing. Multiple prior studies have demonstrated the negative quality of life changes in HE including increased fall risk, caregiver burden, reduced employability, and reduced performance at tasks requiring concentration such as driving (Amodio et al. 2016). As a progressive, relapsing and remitting consequence of hepatic dysfunction and portal hypertension, HE is characterized by neuropsychiatric alterations with variable characteristics (Weissenborn 2019). One of the major manifestations of HE is altered cognition, which will be the focus of this review. Given the challenges of cognitive assessment in encephalopathy as well as the multiple factors that impact disease progression in HE, it’s of considerable future interest to develop dynamic testing strategies. Herein we discuss the advances of remote monitoring of cognition in general and within HE specifically as well as potential applications in clinical practice and challenges therein. Cognition in hepatic encephalopathy Cognition in HE should be distinguished from consciousness, arousal, or psychiatric alterations. The classic West Haven criteria for grading of HE most readily assesses arousal and behavior in differentiating covert (stage 0 or 1) from overt (2–4) HE whereby a patient may progress to coma and death (Vilstrup et al. 2014). While there is significant interplay between arousal and cognition, the vast majority of HE in ambulatory medicine is covert encephalopathy (CHE), with no clear alterations in behavior or consciousness. Cognition, which encompasses intellectual functions including thought, attention and intelligence as well as judgment and decision making, is altered at all grades of encephalopathy, with significant implications for patients with liver disease (Revlin 2013). The cognitive manifestations of liver disease have been described since Hippocrates (Amodio 2015) and remain a bedrock of disease assessment (Montagnese et al. 2022). Attention, or vigilance, is a key component of cognition and has been repeatedly demonstrated to be diminished across the spectrum of HE (Weissenborn et al. 2001b) Both visual and auditory attention are diminished even in those with CHE, and functional studies of cerebral glucose metabolism demonstrate reduced utilization in those with encephalopathy (Lockwood et al. 2002). Attention deficits are captured by many of the currently utilized assessment tools in CHE, including the psychometric hepatic encephalopathy score (PHES), critical flicker frequency and Stroop (Felipo et al. 2012). Similarly, there is an ever-expanding body of research on the loss of fine motor skill and visuospatial abilities in progressive liver disease, as well as memory decline (Bahceci et al. 2005). While historically considered reversible, the cognitive changes from recurrent episodes of HE or persistent covert encephalopathy (CHE) may be permanent in some patients even after transplantation or other reversal of portal hypertension. More recently, the chronic edema and oxidative stress of portal hypertension have been recognized to cause astrocyte senescence in those with HE preferentially (Görg et al. 2018). Senescence, or biological aging, is seen commonly in neurodegenerative diseases and correlates strongly with cerebral oxidative stress (Nagelhus et al. 2013). Such senescence may reduce synaptic potential in the brain, permanently reducing cognitive ability. It is therefore of significant importance to identify cognitive changes early in order to prevent complications arising from altered cognition, such as vehicular accidents, and reverse the etiology. There has been great progress in the classification and management of overt HE. Despite this, we often fail to capture and intervene on subtle cognitive changes which, while not requiring hospitalization, may nonetheless cause detrimental effects in real time for far more patients than does overt disease. Adequate detection and early intervention are imperative to the future of liver disease care, and this review will focus on the potential for and challenges of remote cognitive assessment and monitoring in cirrhosis and encephalopathy. Limitations of current cognitive assessment tools in HE Given the importance of cognition for patient wellbeing, everyday functioning, and as a marker of progressive and potentially irreversible disease, there has been considerable focus on accurate measurement in cirrhosis. In fact, current HE guidelines suggest multimodal assessment of cognition via tests such as the Psychometric Hepatic Encephalopathy Score (PHES), Stroop, and critical flicker frequency. Despite the repeated validation of these tests, they are significantly underused in clinical practice. They are cumbersome, often unavailable outside of research settings, and, even when performed, are often misinterpreted. Additionally, these tests identify only altered cognition, without pointing to a precipitator and with significant risk of confounding (Amodio and Montagnese 2021). Another significant weakness to in-office assessment of cognition is that it’s widely accepted that cognition, and the ability to “think” more broadly, is dynamic. The PHES test must be performed under idealized conditions whereby patients are placed in a quiet room without distractions (Weissenborn et al. 2001a). This, however, is a poor simulation of the real world, and therefore fails to capture cognition in everyday life, where it is needed. Even under the same set of stressors, cognitive performance is not static throughout the day, as anyone who’s had to accomplish a difficult task late in the evening can attest. Moreover, intraindividual cognitive ability, or the so-called noise that affects our cognition, may actually be prognostic of eventual permanent decline (Christensen et al. 2005). While understudied at this time, it would be no surprise if there was prognostic importance to intraindividual cognitive changes over the course of hepatic encephalopathy. A small study found that not only did those with minimal HE demonstrate reduced mean cognition when evaluated with the inhibitory control test (ICT), but they had increased intraindividual variability, especially when performing more complex tasks (Bisiacchi et al. 2014). As with all pen and paper studies, however, this variability was assessed in a laboratory setting, rather than in clinical practice much less real life. Despite the many tools currently accepted to diagnose subtle cognitive changes in encephalopathy, they all suffer from lack of specificity and inter-test reliability. There is now ample literature describing the multitude of factors which can reduce cognition during any single assessment, including drugs (prescription and illicit), alcohol, concomitant neurological disease such as Alzheimer’s or Parkinson’s Disease, infection and electrolyte abnormalities. Likewise, mood disorders are common in cirrhosis and may cause similar findings to CHE without sharing a pathophysiologic basis or appropriate therapeutic direction. Whether these alterations are persistent or transient are poorly captured by a single test, and there may be significant discrepancy between test outcomes. Emergence of mobile and wearable technology Mobile technology has become ubiquitous in the developed world, with approximately 85% of Americans owning a phone with internet connectivity, often termed a “smartphone” (Pew Research Center 2021). These devices, and others like them, have an almost constant bidirectional flow of data related to the consumer. Unsurprisingly, there has been keen interest in the applicability of mobile technology to healthcare, which now represents a greater than $90 billion annual industry globally (Lee and Lee 2020). Two major components of this expanding field are the use of smartphone-based applications and the use of wearable technology. Broadly speaking, wearable health technology is any mobile device which collects and integrates real time biometric or spatial data relating to the wearer (Rutherford 2010). The wide variety of commercial and research technologies are beyond the scope of this review, but several have reached the level of FDA approval (Steil et al. 2006) or clearance (Dhruva et al. 2021) for the diagnosis of medical conditions. Likewise, given that nearly all age ranges in the developed world use smartphone applications on a daily basis (Parasuraman et al. 2017), many health researchers have sought to develop applications specifically for the prevention, detection and monitoring of disease. High frequency data collection in the setting of healthcare has the potential to produce a digital phenotype with dynamic information collected in a variety of settings and under true-to-life conditions (Torous et al. 2016). Such phenotypes are highly related to the fundamental goal of precision medicine, whereby diagnosis and management of medical conditions are derived from “n of 1” patient-centric data. Continuous monitoring leading to precision management strategies is highly attractive for its potential in cognition and cirrhosis (Fig. 1).Fig. 1 Hypothetical use of a mobile health platform for cognitive assessment in cirrhosis, leveraging technology to better diagnose and manage encephalopathy. Created with Biorender.com Applications of remote cognitive assessment in patients without cirrhosis There has been some research into the use of mobile technology as a real-world test of a patient’s status. Termed “ecological momentary assessment” (EMA), it relies on data collection as patients undergo their daily activities (ecological), in any given state (momentary). Such random assessments would provide not only a better understanding of average mental state, but also their variations in state (Sliwinski et al. 2018). Small studies have used EMA designs to evaluate ambulatory cognition as it relates to outcomes or disease states. In one, an ambulatory memory test with an aggregated cognitive score was more sensitive than laboratory testing for reduced hippocampal volume in pre-clinical Alzheimer’s (Allard et al. 2014). The Stroop test, which has also been used in an ambulatory setting in cirrhosis, was found to be potentially useful in recovering addicts, with elevated attention bias predicting relapse events (Marhe et al. 2013). By using Stroop, the researchers were able to infer the participants’ implicit cognitive state, increasing objectivity over subjective assessments of “focus” as relates to craving and likelihood of pending recidivism. Research into mobile applications to assess attention, an important domain of cognition, has also proliferated in recent years, especially in aging and after traumatic brain injury. The FDA has cleared the Immediate Post-Concussion Assessment and Cognitive Test Quick Test (ImPACT QT) for assessment of cognitive functioning after concussion (Wallace et al. 2020). Using visual prompts and including modules such as reverse number counting, the approximately 5-min test allows athletes to test cognitive performance against established baselines. An additional FDA cleared device, the SWAY System (SWAY Medical Inc., Tulsa, OK) was developed to leverage cognitive testing (reaction time, impulse control and inspection time) combined with balance and physical reaction times using the embedded tri-axial accelerometers within mobile devices (Burghart et al. 2019). Finally, mobile and wearable technology may be able to improve disease outcomes by fundamentally altering patient behavior. This has been termed “automated hovering”, and constitutes a significant new horizon for healthcare intervention (Asch et al. 2012) given that a significant majority of patient decisions are made without direct input from a clinician. For example, in one pilot randomized study, a wearable fitness tracker that provided real time biometric data and feedback increased activity and reduced sedentary time in a group at risk for cardiovascular disease (Roberts et al. 2019). Such interventions rely on the control theory, whereby a discrepancy between desired and observed performance leads to both conscious and unconscious behavioral alteration (Hermsen et al. 2016). While the long-term durability of such interventions remains to be determined, the concept is nonetheless appealing, especially given the limited relative time available for direct healthcare interaction with patients. Current and future uses of mobile technology in cirrhosis Biometric data is of critical importance in chronic liver disease and cirrhosis. Guidelines for the prevention of variceal bleeding recommend close titration of resting heart rate with blood pressure. Reduced mobility may represent progressive frailty, worsening ascites, or progression of encephalopathy. Likewise, fractured sleep may signal CHE or any of the mood disorders known to be intrinsic to liver disease. Because of the multitude of physiologic changes seen in cirrhosis, there are ample potential applications for mobile technology in liver disease (Fig. 2).Fig. 2 Potential applications of mobile and wearable technology to detect various complications of cirrhosis Given the approximately 50% readmission rate for patients with cirrhosis discharged from the hospital, and the outsized proportion of these for encephalopathy, it is clear that current outpatient monitoring strategies are inadequate (Bajaj et al. 2016). In one study, patients with HE had a more than fourfold increased risk of 30-day readmission relative to those without (Sood and Wong 2019), and encephalopathy is responsible for up to one third of readmissions in patient with cirrhosis (Gaspar et al. 2019). Reasons for readmission are beyond the scope of this review, but may include medication non-adherence, infection, or lack of close follow up. Despite the high risk of many preventable causes of rehospitalization, there are no widely accepted tools to monitor at risk patients and prevent emergent readmission. Overall, the literature regarding mobile health and remote monitoring in cirrhosis remains relatively sparse (Fig. 3).Fig. 3 Annual publications found in a pubmed.gov search for studies pertaining to "mobile health" and "remote monitoring" by disease state. While disease prevalence plays a role, cirrhosis continues to lag behind other diseases in proliferation of mobile technology Several attempts have already been made to assess cognition using mobile technology. Most notably, the Stroop test has been converted into mobile format in the EncephalApp, which has been broadly validated for the detection of CHE. More recently, a short form of EncephalApp, named QuickStroop, has shown promise for detection of CHE with only one minute of patient engagement – making it a more practical test to be used in clinical practice (Acharya et al. 2022). Many other traditional pen/paper based neuropsychological assessments have been converted into computerized versions outside of the scope of cirrhosis. For cognitive impairment related to possible early Alzheimer’s disease, one systematic review identified no less than 36 smartphone applications available for assessing attention, memory, executive function and/or visual special abilities (Charalambous et al. 2020). Some are simply conversions of previously published psychometric evaluations, such as the BrainTest, which is based on the Self-administered Gerocognitive Examination (SAGE) (Scharre et al. 2010). In many cases, the application publishers also include normative and validation data (Scharre et al. 2017). Verbal fluency is another cognitive domain known to be negatively affected by encephalopathy (Randolph et al. 2009). Recent studies have validated use of simple fluency tests such as the Animal Naming Test for diagnosis of CHE (Campagna et al. 2017). Such a test is simple, requires very little training to perform, and could be performed reasonably easily as a dynamic, mobile cognitive assessment (Moore et al. 2022). Further research has demonstrated slow speech in those with HE (Bloom et al. 2021), and while such technologies have yet to be assessed in cirrhosis, there are mobile applications being researched for real time assessment of fluency and speech rate (Aharonson et al. 2017). Several other mobile applications have been built to assess fluency and phonation for disease states such as Parkinson’s Disease (Byrom et al. 2018a). Wearable technology may also be a useful tool in dynamic assessment of cognitive state in HE. Electroencephalogram (EEG) alterations have been demonstrated to correlate to encephalopathy grades, but laboratory-based testing is too cumbersome for routine clinical use (Amodio et al. 2006). While it may never be feasible for long term ambulatory monitoring, so called “dry” lead EEG technology has been demonstrated to provide adequate approximation of real time neural activity (Hinrichs et al. 2020), potentially increasing its utility in encephalopathy. Dry lead EEG, which does not require specially applied, messy, and cumbersome gel for electrode placement, has rapidly increased interest in EEG technology for rapid cognitive assessment (Pei et al. 2018). For example, one study evaluating a dry lead EEG against established EEG technologies found comparable or even improved performance for cognitive assessment with visual evoked potentials (Hinrichs et al. 2020). Use of remote assessment for positive interventions in cirrhosis Another potential application of mobile cognitive tools in cirrhosis is to seek active cognitive improvement. Several commercially available applications have been extensively developed and marketed, including but not limited to Lumosity, Elevate Brain Training and NeuroNation. Interestingly, NeuroNation is now reimbursed by the national German health insurance (Byrom et al. 2018a). In another study, online cognitive training improved processing speed and cognitive flexibility in breast cancer survivors suffering from cognitive impairment after chemotherapy (Kesler et al. 2013). Such games have already been demonstrated to identify some of the same cognitive impairments as traditional tests for CHE (Tartaglione et al. 2014). While as yet no study has evaluated cognitive training in cirrhosis, future research could identify an important benefit. Remote monitoring also has the potential to further elucidate the relationship between intraindividual cognitive variability and outcomes in encephalopathy. There is a known continuous decline in performance in neurocognitive assessment as encephalopathy progresses from covert to overt. Declining activity levels and changes in biometrics such as body temperature and heart rate could be combined with dynamic assessment of cognition to signal an impending overt episode, potentially initiating therapy prior to disease progression. Given the known amount of noise in a single assessment, it’s important to better understand how variation from baseline and throughout the day may be correlating to a change in disease state. Such an assessment is possible only with mobile technology. Similarly, it can potentially improve our understanding of how other determinants of cognition relate to function in HE, allowing targeted interventions. For example, circadian rhythm disruption and sleepiness are known to impact concentration and working memory (Manly et al. 2002), and those with HE have repeatedly been demonstrated to have disruptions in sleep architecture and quality (Labenz et al. 2018). Sleep measurement is a ubiquitous feature of many commercially available wearable technologies, and several publications have suggested that such measurements reasonably approximate four stage sleep detection with gold standard polysomnography (Chinoy et al. 2021; Miller et al. 2021). Passively collected sleep data serves as just one example of how mobile technology could help researchers and clinicians better understand the course of encephalopathy. Sleep is also an example of how clinicians could impact outcomes in encephalopathy through wearable technology. If it becomes clear, for example, that consistent bed and wake times are preferrable for those with CHE, a clinician could “prescribe” a certain time, and then rely on control theory and passive feedback to encourage patient adherence. Challenges for implementation of remote monitoring of cognition In a multi-disciplinary perspective paper following a workshop organized by the NIH’s Big Data to Knowledge Centers of Excellence, the workshop participants outlined several tenets to implementing successful digital health programs, adapted in Table 1 below (Smuck et al. 2021). Full integration of such a program for cognition in cirrhosis is out of scope in this review, but several factors are worth considering for the challenges they may pose.Table 1 Challenges and recommendations for successful implementation of digital health programs. Adapted from Smuck et al 2021 and derived from a multidisciplinary NIH Big Data Workshop and subsequent position paper Clearly Defined Problem and Disease State Integrated System of Healthcare Delivery Technology support and service Personalized Experience Enhanced End User Experience Aligned Payment and Reimbursement Models Clinical Champions and Stakeholder Support In order to be successfully implemented, the mobile health technology must be capable of performing its prescribed task. In the case of HE, this means assessing whether remote cognitive assessment outperforms, or at least approximates, the current testing practices. Test performance itself can be judged by many metrics, but key among them is discriminatory ability for the diagnosis of interest. This is often weighted against an accepted gold standard, which may or may not be an appropriate metric. Validation of mobile technology for determining health indicators and outcomes is inevitable, with over 900 trials currently registered just within the United States at clinicaltrials.gov (Mitsi et al. 2022). Regulatory considerations are unlikely to be a significant barrier to accessing cognitive assessment tools, as most are likely to be classified as minimal potential for harm and clearable through an expedited 510(k) pathway in the United States or similar in the European Union and Canada (Byrom et al. 2018b). Generally speaking, the practical validity of a clinical tool should follow the “three V’s” of validation, including verification, analytical validity, and clinical validity (Goldsack et al. 2020). Verification evaluates the actual tool/sensor performance itself, insofar that it consistently generates an accurate reading of its intended biomarker. This could be acceleration, temperature, or attention and should be performed by the technology manufacturer, with published results available for clinicians and researchers. Analytical validation requires testing in human subjects to evaluate performance of the sensor for converting raw collected data into a meaningful metric (Witt et al. 2019). For example, validation may be performed to show that motion and accelerometry data can actually interpret gait velocity, or that temperature change, heart rate and motion can identify sleep duration. These should be tested against reference standards, for example polysomnography for sleep. Importantly, this analytical validation needs to be performed in each population of interest, and as companies are unlikely to expand their own validation studies beyond healthy volunteers, much of the burden will fall on clinicians and researchers. Finally, clinical validation applies an analytically valid tool to achieve a clinically meaningful endpoint. That endpoint could be whether ambulatory measurement of blood pressure impacts mortality, for example (Banegas et al. 2018). In the case of cognitive monitoring in HE, clinical validity may be whether an ambulatory assessment program reduces hospitalization for overt HE. As yet, there are no passive or active remote cognitive monitoring tools that have been clinically validated in cirrhosis. Additionally, it’s important that the technology be applied in a clearly defined patient population, a clearly defined disease state, and preferably clearly defined thresholds for action. One potential diagnosis sought by remote monitoring is the cognitive decline when patients transition from a covert or latent encephalopathy to an overt form requiring immediate medical attention, believed to be at an approximately 20% rate annually. In one pilot study, the Patient Buddy App was evaluated in a cirrhosis-specific context in an attempt to close some of this gap. The App was developed to improve provider and patient/caregiver communication across healthcare, and in this study its capabilities were enhanced by including simultaneous weekly use of EncephalApp and orientation questions, to be entered into the Buddy App. Likewise, the study team received alerts if patients were non-adherent to medications or failed to monitor sodium intake. In their short pilot study, the researchers identified 8 HE-related admissions (from 40 enrolled participants) which had been likely avoided by in app communication after assessments or alerts (Ganapathy et al. 2017). Overall, the app was well received but admission rates overall were similar to those previously published and overall usage and adherence was moderate at best. An illustrative example was recently published using mobile technology for ascites management (Bloom et al. 2020). In their study, they a weight increase of > 5 pounds over one week automatically triggered an email alert to providers, with high adherence on both the provider and patient side, and more than half of the alerts eliciting an intervention. A common challenge when considering mobile or wearable technology is its reliability, whether within the device itself or in comparison with another. It’s worth noting, however, that even presently accepted tools for measuring cognition are unreliable in some ways. Significant discordance between tests such as EncephalApp and PHES have been previously published (Duarte-Rojo et al. 2019). While it has not been significantly discussed in publication, it is unclear whether true technological reliability will be a limiting factor in implementing remote monitoring platforms. An effective cognitive monitoring tool in encephalopathy will retain patient engagement, which will likely prove challenging. In one study evaluating mobile device proficiency in cirrhosis, 84.6% owned mobile devices and 61.5% were interested in personalized mobile health management programs (Ismond et al. 2021). The researchers found similar technical proficiency among those with cirrhosis compared to the general population. Interestingly, a history of HE was not associated with worse technical proficiency, but formal cognitive assessment was not performed in that study. Regardless, given the known sociodemographic challenges facing those with liver disease, a cognitive monitoring tool has the potential to widen the already present gap in outcomes based on access to technology and health literacy (Reiners et al. 2019). Unfortunately, few studies have attempted to evaluate real world usage of cognitive monitoring in encephalopathy. In one prospective study, patients with cirrhosis were evaluated for usage of EncephalApp longitudinally, but only 32% actually completed a run of EncephalApp despite most expressing interest on enrollment (Louissant et al. 2020). There were multiple reasons cited for failure to complete, including technical difficulties, forgetting to use it, and recurrent admission. One recently presented study found that passively collected sleep data using commercially available wearable technology had higher (71.4%) participant adherence over a 6-month period (Buckholz et al. 2022), suggesting that perhaps passive data collection could improve some test performance. One solution posited by the Smuck et al. position paper was to incorporate “Apple genius bar” style technical support whereby trained staff members incorporate physician recommendations to assist patients in setting up and delivering appropriate data back to the physician. Passive data collection would require validation of indirect markers of cognition which has as yet not been performed. In a non-cirrhotic population, passively collected interactions with smart phones were strongly correlated with outcomes of neurocognitive testing (Dagum 2018). Overall, it seems likely that increased points of contact for patients with healthcare, even digital healthcare, are likely to improve outcomes. A study conducted by the Oshsner health system found that blood pressure data collected at home with a loop feedback approach to a treating physician helped 71% of patients reach target blood pressure, compared to 31% with usual care (Milani et al. 2017). One potential barrier, however, is uptake by gastroenterologists. In comparison with other specialties, the providers most responsible for the management of patients with chronic liver disease are among the least likely to use telemedicine and mobile health technology. In one study, only 7.9% of gastroenterologists used telemedicine, the lowest of any specialty, albeit the study was conducted prior to the COVID-19 pandemic, so usage is undoubtedly higher in the present day (Kane and Gillis 2018). Overall, the COVID-19 pandemic has increased comfort level among both patients and providers with remote health technology, and payer models are adjusting to the new health landscape. For example, the Centers for Medicare and Medicaid Services in 2018 incorporated Current Procedural Terminology (CPT) code 99,091, which allows billing for physiologic and patient-generated digital health information (Smuck et al. 2021). Mobile technology applied appropriately may also reduce caregiver and physician burden, which is a major concern in the management of encephalopathy. A study performed in the Kaiser Permanente health system noted that electronic management of diabetes medication improved glycemic control and reduced direct physician workload by 35% (Zhou et al. 2017). In order to achieve broad physician acceptance and patient benefit for a mobile health program, there must be efficient integration of the data into the electronic health record (EHR). It is likely unrealistic that healthcare providers will actively monitor all of the vast number of data points generated with mobile technology, and equally unrealistic that patients themselves can or would sift through to find meaningful metrics. By one estimate, over 400 wearables already have the ability to integrate into EHRs, but such a significant amount of data can overwhelm health system storage capacity (Kalid et al. 2017) and induce provider fatigue (Ramirez et al. 2018). Artificial technology may be a potential solution in the future, but such usage is in its infancy (Dinh-Le et al. 2019). This problem reiterates the need to have clearly defined thresholds for “alert” states and clearly outline mutual goals and recommendations with physicians and patients. A final challenge regards the privacy concerns with using often proprietary mobile technology for patient care. The relative lack of regulatory oversight means that mobile health data faces significant transmission and storage concerns across healthcare. In one study by the United Kingdom’s Health service, 66% of apps that were categorized as “trusted” for clinical use were transmitting data that was not properly encrypted, while 20% did not have any privacy policy at all (Huckvale et al. 2015). Moreover, the proliferation of entrepreneurially focused apps has the potential to create data silos (Mamlin and Tierney 2016), whereby there are so many different mobile applications that it’s unrealistic to expect clinicians to understand privacy and safety policies for each. Similarly, many mobile health companies do not publicize proprietary algorithms used to obtain or interpret health biometrics, deepening distrust between researchers, clinicians and mobile health companies (Depner et al. 2020). To adequately integrate a mobile cognitive assessment platform in cirrhosis, improved transparency and strict data management strategies will need to crucial. Conclusion Hepatic encephalopathy remains a devastating complication of chronic liver disease, responsible for considerable morbidity and healthcare expenditure. Because the vast majority of HE is covert, cognitive assessment is a critical component of disease identification and management. However, current assessment tools are cumbersome and underutilized in clinical practice, and capture only an isolated and idealized moment in a patient’s course. It’s well understood that cognition is dynamic and changes can occur due to myriad factors. From both a research and clinical care standpoint, the proliferation of mobile healthcare may offer new insight into cognition in HE. While many mobile cognitive tools have been developed, tested, and marketed, there has yet to be significant penetration within HE. While many questions remain as to how such tools can be validated and leveraged in cirrhosis, it’s important that researchers embrace the challenge in order to modernize and improve cognitive assessment. Certainly, all advances within mobile health and wearable technology should be met with appropriate levels of scrutiny and caution until they’re effectively validated. There is considerable research needed at all levels prior to true clinical implementation of such tools. Despite this, entrepreneurs, patients, healthcare providers, insurance companies and even government entities understand that mobile health will only continue to grow, and failing to capitalize on that growth within HE would represent a significant opportunity lost. Author’s contributions All authors contributed to the writing and editing of this review. The first draft was written primarily by Dr. Buckholz with conceptual and editing input from Dr. Rosenblatt. Data availability Not applicable Code availability Not applicable Declarations Ethics approval Not applicable Consent to participate Not applicable Consent for publication Not applicable Conflicting/Competing interests The authors have no relevant financial or non-financial interests to disclose. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Acharya C, Shaw J, Duong N et al (2022) QuickStroop, a shortened version of encephalapp, detects covert hepatic encephalopathy with similar accuracy within one minute. Clin Gastroenterol Hepatol. 10.1016/J.CGH.2021.12.047 Aharonson V Aharonson E Raichlin-Levi K A real-time phoneme counting algorithm and application for speech rate monitoring J Fluency Disord 2017 51 60 68 10.1016/J.JFLUDIS.2017.01.001 28159356 Allard M, Husky M, Catheline GL et al (2014) Mobile technologies in the early detection of cognitive decline. PLoS One 9. 10.1371/JOURNAL.PONE.0112197 Amodio P Hepatic encephalopathy: historical remarks J Clin Exp Hepatol 2015 5 S4 10.1016/J.JCEH.2014.12.005 26041956 Amodio P Montagnese S Lights and shadows in hepatic encephalopathy diagnosis J Clin Med 2021 10 1 10 10.3390/JCM10020341 Amodio P Pellegrini A Ubiali E The EEG assessment of low-grade hepatic encephalopathy: comparison of an artificial neural network-expert system (ANNES) based evaluation with visual EEG readings and EEG spectral analysis Clin Neurophysiol 2006 117 2243 2251 10.1016/J.CLINPH.2006.06.714 16931145 Amodio P, Montagnese S, Mullen K et al (2016) Where are we going? Translational research in hepatic encephalopathy. 10.1007/s11011-015-9728-3 Asch DA Muller RW Volpp KG Automated hovering in health care–watching over the 5000 hours N Engl J Med 2012 367 1 3 10.1056/NEJMP1203869 22716935 Bahceci F Yildirim B Karincaoglu M Memory impairment in patients with cirrhosis J Natl Med Assoc 2005 97 213 15712784 Bajaj JS Reddy KR Tandon P The three-month readmission rate remains unacceptably high in a large north american cohort of cirrhotic patients Hepatology 2016 64 200 10.1002/HEP.28414 26690389 Banegas JR Ruilope LM de la Sierra A Relationship between clinic and ambulatory blood-pressure measurements and mortality N Engl J Med 2018 378 1509 1520 10.1056/NEJMOA1712231/SUPPL_FILE/NEJMOA1712231_DISCLOSURES.PDF 29669232 Bisiacchi P Cona G Tarantino V Assessing inter- and intra-individual cognitive variability in patients at risk for cognitive impairment: the case of minimal hepatic encephalopathy Metab Brain Dis 2014 29 945 953 10.1007/S11011-014-9529-0 24682793 Bloom PP Robin J Xu M Hepatic encephalopathy is associated with slow speech on objective assessment Am J Gastroenterol 2021 116 1950 1953 10.14309/AJG.0000000000001351 34465696 Bloom P, Wang T, Marx M et al (2020) A smartphone app to manage cirrhotic ascites among outpatients: feasibility study. JMIR Med Inform 8(9):e17770. 10.2196/17770; https://medinform.jmir.org/2020/9/e177708:e17770. Accessed Sept 2022 Buckholz A Clarke LM Paik P Sa1454: longitudinal monitoring of sleep in covert hepatic encephalopathy reveals significant fracturing and loss of rem Gastroenterology 2022 162 S-1174 10.1016/S0016-5085(22)63499-1 Burghart M Craig J Radel J Huisinga J Reliability and validity of a motion-based reaction time assessment using a mobile device Appl Neuropsychol Adult 2019 26 558 10.1080/23279095.2018.1469491 30183372 Byrom B McCarthy M Schueler P Muehlhausen W Brain monitoring devices in neuroscience clinical research: the potential of remote monitoring using sensors, wearables, and mobile devices Clin Pharmacol Ther 2018 104 59 10.1002/CPT.1077 29574776 Byrom B Watson C Doll H Selection of and evidentiary considerations for wearable devices and their measurements for use in regulatory decision making: recommendations from the epro consortium Value in Health 2018 21 631 639 10.1016/j.jval.2017.09.012 29909867 Campagna F Montagnese S Ridola L The animal naming test: An easy tool for the assessment of hepatic encephalopathy Hepatology 2017 66 198 208 10.1002/HEP.29146/SUPPINFO 28271528 Charalambous AP, Pye A, Yeung WK et al (2020) Tools for app- and web-based self-testing of cognitive impairment: systematic search and evaluation. J Med Internet Res 22. 10.2196/14551 Chinoy ED, Cuellar JA, Huwa KE et al (2021) Performance of seven consumer sleep-tracking devices compared with polysomnography. Sleep 44. 10.1093/SLEEP/ZSAA291 Christensen H Dear KBG Anstey KJ Within-occasion intraindividual variability and preclinical diagnostic status: is intraindividual variability an indicator of mild cognitive impairment? Neuropsychology 2005 19 309 317 10.1037/0894-4105.19.3.309 15910117 Dagum P Digital biomarkers of cognitive function npj Digital Medicine 2018 1 1 10.1038/s41746-018-0018-4 31304287 Depner CM, Cheng PC, Devine JK et al (2020) Wearable technologies for developing sleep and circadian biomarkers: a summary of workshop discussions. Sleep 43. 10.1093/SLEEP/ZSZ254 Dhruva SS, Shah ND, Vemulapalli S et al (2021) Heart watch study: protocol for a pragmatic randomised controlled trial. BMJ Open 11. 10.1136/BMJOPEN-2021-054550 Dinh-Le C, Chuang R, Chokshi S, Mann D (2019) Wearable health technology and electronic health record integration: scoping review and future directions. JMIR Mhealth Uhealth 7. 10.2196/12861 Duarte-Rojo A Allampati S Thacker LR Diagnosis of covert hepatic encephalopathy: a multi-center study testing the utility of single versus combined testing Metab Brain Dis 2019 34 289 10.1007/S11011-018-0350-Z 30506333 Felipo V Ordoño JF Urios A Patients with minimal hepatic encephalopathy show impaired mismatch negativity correlating with reduced performance in attention tests Hepatology 2012 55 530 539 10.1002/HEP.24704 21953369 Ganapathy D Acharya C Lachar J The patient buddy app can potentially prevent hepatic encephalopathy-related readmissions Liver Int 2017 37 1843 1851 10.1111/LIV.13494 28618192 Gaspar R Rodrigues S Silva M Predictive models of mortality and hospital readmission of patients with decompensated liver cirrhosis Dig Liver Dis 2019 51 1423 1429 10.1016/J.DLD.2019.03.016 31113738 Goldsack JC Coravos A Bakker JP Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs) npj Digital Med 2020 3 1 10.1038/s41746-020-0260-4 Görg B Karababa A Häussinger D Hepatic encephalopathy and astrocyte senescence J Clin Exp Hepatol 2018 8 294 10.1016/J.JCEH.2018.05.003 30302047 Hermsen S Frost J Renes RJ Kerkhof P Using feedback through digital technology to disrupt and change habitual behavior: A critical review of current literature Comput Human Behav 2016 57 61 74 10.1016/J.CHB.2015.12.023 Hinrichs H Scholz M Baum AK Comparison between a wireless dry electrode EEG system with a conventional wired wet electrode EEG system for clinical applications Sci Rep 2020 10 1 10.1038/s41598-020-62154-0 31913322 Huckvale K Prieto JT Tilney M Unaddressed privacy risks in accredited health and wellness apps: a cross-sectional systematic assessment BMC Med 2015 13 EE 10.1186/S12916-015-0444-Y Ismond KP Eslamparast T Farhat K Assessing patient proficiency with internet-connected technology and their preferences for e-health in cirrhosis J Med Syst 2021 45 3 10.1007/S10916-021-01746-3 Kalid N, Zaidan AA, Zaidan BB et al (2017) Based real time remote health monitoring systems: a review on patients prioritization and related “big data” using body sensors information and communication technology. J Med Syst 42. 10.1007/S10916-017-0883-4 Kane CK Gillis K The use of telemedicine by physicians: still the exception rather than the rule Health Aff (millwood) 2018 37 1923 1930 10.1377/HLTHAFF.2018.05077 30633670 Kesler S Hadi Hosseini SM Heckler C Cognitive training for improving executive function in chemotherapy-treated breast cancer survivors Clin Breast Cancer 2013 13 299 10.1016/J.CLBC.2013.02.004 23647804 Labenz C Baron JS Toenges G Prospective evaluation of the impact of covert hepatic encephalopathy on quality of life and sleep in cirrhotic patients Aliment Pharmacol Ther 2018 10.1111/apt.14824 Lee SM Lee DH Healthcare wearable devices: an analysis of key factors for continuous use intention Serv Bus 2020 14 503 10.1007/S11628-020-00428-3 Lockwood AH Weissenborn K Bokemeyer M Correlations between cerebral glucose metabolism and neuropsychological test performance in nonalcoholic cirrhotics Metab Brain Dis 2002 17 29 40 10.1023/A:1014000313824 11893006 Louissant J, Lok A, Fortune BTE (2020) Acceptance and use of a smartphone application in cirrhosis. Liver International Mamlin BW Tierney WM The promise of information and communication technology in healthcare: extracting value from the chaos Am J Med Sci 2016 351 59 68 10.1016/J.AMJMS.2015.10.015 26802759 Manly T Lewis GH Robertson IH Coffee in the cornflakes: time-of-day as a modulator of executive response control Neuropsychologia 2002 40 1 6 10.1016/S0028-3932(01)00086-0 11595257 Marhe R Waters AJ van de Wetering BJM Franken IHA Implicit and explicit drug-related cognitions during detoxification treatment are associated with drug relapse: an ecological momentary assessment study J Consult Clin Psychol 2013 81 1 10.1037/A0030754 23231572 Milani Rv Lavie CJ Bober RM Improving hypertension control and patient engagement using digital tools Am J Med 2017 130 14 20 10.1016/j.amjmed.2016.07.029 27591179 Miller DJ Roach GD Lastella M A validation study of a commercial wearable device to automatically detect and estimate sleep Biosensors 2021 11 185 10.3390/BIOS11060185 34201016 Mitsi G Grinnell T Giordano S Implementing digital technologies in clinical trials: lessons learned Innov Clin Neurosci 2022 19 65 35958972 Montagnese S Romero Gómez M Larsen FS EASL clinical practice guidelines on the management of hepatic encephalopathy J Hepatol 2022 77 807 824 10.1016/J.JHEP.2022.06.001/ATTACHMENT/BA9A0C8B-4FCE-4720-B8E6-330A4A4138D5/MMC1.PDF 35724930 Moore RC, Ackerman RA, Russell MT et al (2022) Feasibility and validity of ecological momentary cognitive testing among older adults with mild cognitive impairment. Front Digit Health 4. 10.3389/FDGTH.2022.946685 Nagelhus EA Amiry-Moghaddam M Bergersen LH The glia doctrine: addressing the role of glial cells in healthy brain ageing Mech Ageing Dev 2013 134 449 459 10.1016/J.MAD.2013.10.001 24141107 Parasuraman S Sam AT Yee SWK Smartphone usage and increased risk of mobile phone addiction: A concurrent study Int J Pharm Investig 2017 7 125 10.4103/JPHI.JPHI_56_17 Pei G, Wu J, Chen D et al (2018) Effects of an integrated neurofeedback system with dry electrodes: EEG acquisition and cognition assessment. Sensors (Basel) 18. 10.3390/S18103396 Pew Research Center (2021) Mobile Fact Sheet. In: Pew Research Center. https://www.pewresearch.org/internet/fact-sheet/mobile/. Accessed 29 Aug 2022 Ramirez M Maranon R Fu J Primary care provider adherence to an alert for intensification of diabetes blood pressure medications before and after the addition of a “chart closure” hard stop J Am Med Inform Assoc 2018 25 1167 10.1093/JAMIA/OCY073 30060013 Randolph C Hilsabeck R Kato A Neuropsychological assessment of hepatic encephalopathy: ISHEN practice guidelines Liver Int 2009 29 629 635 10.1111/J.1478-3231.2009.02009.X 19302444 Reiners F, Sturm J, Bouw LJW, Wouters EJM (2019) Sociodemographic factors influencing the use of ehealth in people with chronic diseases. Int J Environ Res Public Health 16. 10.3390/IJERPH16040645 Revlin Russell (2013) Cognition : theory and practice. Worth Publishers, p 640 Roberts LM Jaeger BC Baptista LC Wearable technology to reduce sedentary behavior and CVD risk in older adults: a pilot randomized clinical trial Clin Interv Aging 2019 14 1817 1828 10.2147/CIA.S222655 31695350 Rutherford JJ Wearable technology IEEE Eng Med Biol Mag 2010 29 19 24 10.1109/MEMB.2010.936550 20659854 Scharre DW Chang SI Murden RA Self-Administered Gerocognitive Examination (SAGE): a brief cognitive assessment Instrument for mild cognitive impairment (MCI) and early dementia Alzheimer Dis Assoc Disord 2010 24 64 71 10.1097/WAD.0B013E3181B03277 20220323 Scharre DW, Chang SI, Nagaraja HN et al (2017) Digitally translated Self-Administered Gerocognitive Examination (eSAGE): relationship with its validated paper version, neuropsychological evaluations, and clinical assessments. Alzheimers Res Ther 9. 10.1186/S13195-017-0269-3 Sliwinski MJ Mogle JA Hyun J Reliability and validity of ambulatory cognitive assessments Assessment 2018 25 14 10.1177/1073191116643164 27084835 Smuck M Odonkor CA Wilt JK The emerging clinical role of wearables: factors for successful implementation in healthcare npj Digital Medicine 2021 4 1 10.1038/s41746-021-00418-3 33398041 Sood KT Wong RJ Hepatic encephalopathy is a strong predictor of early hospital readmission among cirrhosis patients J Clin Exp Hepatol 2019 9 484 10.1016/J.JCEH.2019.01.005 31571775 Steil GM Rebrin K Darwin C Feasibility of automating insulin delivery for the treatment of type 1 diabetes Diabetes 2006 55 3344 3350 10.2337/DB06-0419 17130478 Tartaglione Ev Derleth M Yu L Ioannou GN Can computerized brain training games be used to identify early cognitive impairment in cirrhosis? Am J Gastroenterol 2014 109 316 323 10.1038/AJG.2013.306 24594947 Torous J, Kiang Mv, Lorme J, Onnela JP (2016) New tools for new research in psychiatry: a scalable and customizable platform to empower data driven smartphone research. JMIR Ment Health 3. 10.2196/MENTAL.5165 Vilstrup H, Amodio P, Bajaj J et al (2014) Hepatic encephalopathy in chronic liver disease: 2014 practice guideline by the American association for the study of liver diseases and the European association for the study of the liver. Hepatology 60. 10.1002/hep.27210 Wallace J Schatz P Covassin T Iverson GL Brief iPad-based assessment of cognitive functioning with ImPACT® quick test: prevalence of low scores using multivariate base rates Arch Clin Neuropsychol 2020 35 1276 1282 10.1093/ARCLIN/ACAA078 33000122 Weissenborn K Hepatic encephalopathy: definition, clinical grading and diagnostic principles Drugs 2019 79 5 10.1007/S40265-018-1018-Z 30706420 Weissenborn K Heidenreich S Ennen J Attention deficits in minimal hepatic encephalopathy Metab Brain Dis 2001 16 13 19 10.1023/A:1011654210096 11726083 Weissenborn K Ennen JC Schomerus H Rückert N Hecker H Neuropsychological characterization of hepatic encephalopathy J Hepatol 2001 34 5 768 773 10.1016/s0168-8278(01)00026-5 11434627 Witt DR Kellogg RA Snyder MP Dunn J Windows into human health through wearables data analytics Curr Opin Biomed Eng 2019 9 28 46 10.1016/J.COBME.2019.01.001 31832566 Zhou YY, Kanter MH, Wang JJ, Garrido T (2017) Improved quality at kaiser permanente through e-mail between physicians and patients. 29:1370–1375. 10.1377/HLTHAFF.2010.0048
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==== Front Environ Sci Pollut Res Int Environ Sci Pollut Res Int Environmental Science and Pollution Research International 0944-1344 1614-7499 Springer Berlin Heidelberg Berlin/Heidelberg 36508100 24607 10.1007/s11356-022-24607-z Research Article Evaluating the symmetric and asymmetric effects of fossil fuel energy consumption and international capital flows on environmental sustainability: a case of South Asia http://orcid.org/0000-0003-4351-7176 Umair Muhammad [email protected] 1 http://orcid.org/0000-0003-2177-6804 Yousuf Muhammad Uzair [email protected] 2 1 grid.266518.e 0000 0001 0219 3705 Department of Economics, University of Karachi, Karachi, 75270 Pakistan 2 grid.440548.9 0000 0001 0745 4169 Department of Mechanical Engineering, NED University of Engineering and Technology, Karachi, 75270 Pakistan Responsible Editor: Roula Inglesi-Lotz 12 12 2022 117 20 7 2022 1 12 2022 © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. South Asia is primarily affected by environmental degradation. As a result, it is worthwhile to explore the impact of international capital flows on the ecological sustainability of the South Asian region. There are many studies in the literature on the CO2-remittances nexus, CO2-FDI nexus, and CO2-economic growth; however, no study has yet taken remittances and FDI into account in the symmetric and asymmetric model for the South Asian region. To address the research gap, this study investigates the effect of international capital flows, fossil fuel energy consumption, and economic growth on South Asian carbon emissions. This study examines the effect of fossil fuel energy consumption, remittances, foreign direct investment, and economic growth on the environmental sustainability of the South Asian region from 1975 to 2020. Autoregressive distributive lag (ARDL) and non-linear ARDL (NARDL) models are used to estimate the symmetrical and asymmetrical relationships among the variables. The findings of the ARDL models reveal that fossil fuel energy consumption and economic growth increase while remittances and FDI decrease carbon dioxide (CO2) in the long run. According to the NARDL empirical findings, positive remittances and negative FDI shock reduce CO2. Besides, the positive and negative fossil fuel energy consumption shock increases CO2. Moreover, the positive (negative) economic growth shock increases (decreases) CO2. The cumulative dynamic multipliers revealed the adjustment pattern to new long-run equilibria. The study recommends that policymakers regard remittances and FDI as policy instruments, particularly when developing long-term strategies and policies connected to environmental quality. Keywords Fossil fuel energy consumption Environmental sustainability Remittances Foreign direct investment ==== Body pmcIntroduction Environmental sustainability is a global concern, and the use of fossil fuels has adverse effects on the environment (Khan et al. 2021, 2022f; Weili et al. 2022). Fossil fuel energy consumption (FFEC) is primarily a non-renewable energy source. These fuels are the world’s principal energy source and were produced over millions of years from organic material. Despite a pervasive scientific consensus that present levels of fossil-fuel usage intimidate the environment with disastrous levels of global warming, the utilization of fossil fuels has continued and expanded (Painter 2019; Yousuf et al. 2022). The flue gases generated as a result of combustion are a significant source of excess carbon emissions, leading to rising carbon levels in the atmosphere (Marland et al. 1985). The COVID-19 recovery could be a tipping point for governments looking to reduce environmental degradation. The key findings of the Production Gap Report to stay on a 1.5 °C trajectory between 2020 and 2030 include reducing fossil fuel production by an annual 6% globally. Instead, countries are planning and predicting a 2% yearly growth, which would increase treble production by 2030 while staying under the 1.5 °C limit. As seen globally that the lockdown measures for the COVID-19 outbreak have resulted in short-term reductions in coal and gas production (Zhongming and Wei 2020). Specifically in South Asia, environmental pollution has become a major concern. South Asia, with 1.86 billion people, had around a quarter (24%) of the world’s population. The annual population growth of the region is 1.15% in 2020. From a global perspective, South Asia is a critical economic zone. The region has grown at an annual rate of 5.6% from 2000 to 2020. The yearly economic growth remained higher than 7% in different years over the last two decades; 2003–2007, 2010, and 2015–2016, while declined to a minimum of − 5.7% in 2020 due to COVID-19 (WDI 2022). Environmental degradation is indeed a problem among regional countries. With expected industrial activity and population increases, each South Asian country’s contribution to regional air pollution has grown over time (Adebanjo and Shakiru 2022; Hasnat et al. 2018). In India and Pakistan, environmental degradation is significantly caused by thermal power plants and traffic congestion. In Bangladesh, vehicular emissions and brick kilns are the biggest polluters. In Bhutan, the most significant source of air pollution is forest fires. In Nepal, the air quality is worsening due to harmful pollutants present in high concentrations. According to the Statistical review of World Energy 2021, coal is the dominant fuel in the region. Many factors, including urbanization, industrialization, and fossil fuels dependency, are responsible for increasing carbon emissions in the atmosphere (Khwaja et al. 2012). Many studies examined the link between energy consumption, carbon emissions, and other explanatory variables for different regions (Ahmad et al. 2021; Balsalobre-Lorente et al. 2022; Khan et al. 2020d; Rahman et al. 2019; Yang et al. 2020). However, the link between international financial flows and environmental degradation had not been examined in the South Asian region. Many workers migrate yearly from South Asian countries, making remittances (REM) an essential funding source for economic development. Remittances are funds sent home by citizens living in another country that account for a significant amount of the country’s output. Individual household incomes are considerably supplemented while local economies rely on remitted money. In 2018, the low- and middle-income countries received more than three quarters (US$ 529 billion) of global remittances (US$ 689 billion). Remittances to Tajikistan, Kyrgyz Republic, Nepal, Tonga, and Moldova were more than a quarter of the country’s aggregate output (Ratha et al. 2016). Remittances are an important source of income and a financial lifeline for many developing economies that affect their socioeconomic and demographic characteristics, i.e., the balance of payment, exchange rate, poverty, inequality, production, and consumption. They are affected by the home and host countries’ economic conditions (Khan et al. 2022e; Umair & Waheed 2017). The influx of remittances is doubled that of FDI. In 2020, South Asian remittances were US$ 147 billion, while the region’s FDI was US$ 69 billion (WDI 2022). The increase in remittances increases consumption and production, affecting environmental sustainability (Ahmad et al. 2022). FDI is also essential for the growth of emerging economies. It is a corporation’s investment in projects by controlling equity ownership of 10% or more other than the country of origin (Jamil et al. 2022; Khan et al. 2020c, 2022d; Lane & Milesi-Ferretti 2003). Trade liberalization and financial development attract FDI inflows in contributing to economic growth (Jamil 2022; Khan et al. 2020b, 2022a). FDI increases employment opportunities, boosts entrepreneurship and competitiveness, and intensifies productivity, technology, and innovation (Sabir et al. 2020). The increase in these financial flows affects environmental degradation (Khan et al. 2020d, 2022c; Rahman et al. 2019; Yang et al. 2020). South Asian remittances remained at an annual average of 3.7% and 4.2% of the aggregate output during 2001–2010 and 2011–2020, respectively, while FDI remained at a yearly average of 1.6% during 2001–2020. Remittances are increasing and have sustained a minimum value of 3% annually since 2001. With the global economic expansion, FDI peaked at 3.3% in 2008. The FFEC increased from an annual average of 36.8% of the total in 1975–1980 to 70.3% in 2011–2020. The increase in international capital flows and fossil fuel consumption supported the real per capita income increase from an annual average of 413.7 US$ during 1975–1980 to 1575.9 US$ during 2011–2020. The real per capita income peaked in 2020 (1743 US$). The solid fuel consumption emissions increased from an annual average of 199.2 megatons during 1975–1980 to 1432.4 megatons during 2011–2020. Most of the developing and emerging economies are facing difficulties related to environmental degradation because foreign finance is used to import fossil fuels to expand their economies causing environmental degradation. To lessen environmental deterioration, renewable energy must be used; yet, developing nations might not yet be at the point where they can obtain renewable energy. To safeguard environmental quality, it is crucial for developing nations to adopt policies that encourage the use of renewable energy instead of nonrenewable sources (Khan et al. 2021). South Asia is primarily affected by environmental degradation. As a result, it is worthwhile to investigate the impact of international capital flows on the ecological sustainability of the South Asian region. There are many studies in the literature on the CO2-remittances nexus, CO2-FDI nexus, CO2-economic growth, and others, but no study has yet taken remittances and FDI into account in the symmetric and asymmetric model for the South Asian region. This study aims to fill in the gaps in the literature by addressing different research questions. The four hypotheses in this context include (i) remittances significantly contribute to the environmental sustainability of South Asia (ii) FDI significantly improves the environmental quality of South Asia (iii) FFEC significantly contributes to South Asia’s environmental degradation, and (iv) The region’s economic growth is interrelated to environmental degradation. The findings reveal that the explanatory variables have a short- and long-run effect on South Asian carbon emissions. The ARDL model is better for a small data sample, non-stationary, and mixed-order integrated time series (Ndem et al. 2022). ARDL results show that an increase in REM and FDI decreases CO2 while increasing FFEC and GDP increases CO2. NARDL results for non-linear cointegration show that increasing the positive part of REM diminishes CO2. The rise in the positive and negative parts of FDI decreases CO2. The increase in the positive and negative parts of FFEC significantly adds to CO2. Finally, a rise in the positive part of GDP significantly increases CO2, while an increase in the negative part reduces CO2. The remainder of the study is structured as follows: The “Literature review” section critically evaluates the theoretical and empirical literature review. Materials and methods are discussed in the “Materials and methods” section followed by empirical findings in the “Results and discussions” section. Finally, the conclusions are drawn in the “Conclusion and policy implications” section. Literature review Remittances and environmental sustainability Remittances are significantly associated with environmental sustainability. Remittance growth has substantial socioeconomic and demographic effects on countries and regions. It supports an increased standard of living and improved financial systems (Meyer and Shera 2017). Therefore, remittances have a positive economic effect that contributes to human welfare. Furthermore, remittances are critical to support the balance of payment in low-income countries, generate employment opportunities, and expand global integration. Concurrently, increased production and consumption due to remittances increase carbon emissions (Rehman et al. 2019; Xu et al. 2021). Remittances contribute to the country’s economic development and industrialization via financial system improvement that has the potential to increase carbon emissions (Mohsin et al. 2022; Wang et al. 2021). In contrast, the increased remittances are liable to reduce carbon emissions via investment in education and affordability of eco-friendly resources at micro- and macro-levels (Zafar et al. 2022). Remittances are among the key factors in financial development since they boost the resources available for credit (Farhani and Ozturk 2015; Li and Tse 2015). Besides, Neog and Yadava (2020) examined an asymmetric relationship between CO2 emissions and remittances in India for the years 1980 to 2014. The study used time series data to develop a nonlinear ARDL model based on the theoretical links. The findings of the NARDL bound test imply the variables’ long-run cointegration. The results demonstrate that, in contrast to a negative shock, a positive shock in remittances increases CO2 emissions. Moreover, Brown et al. (2020) considered a modified version of the EKC, to find the relationship between CO2 emissions and remittances. The study employed ARDL bounds testing methods to Jamaican data (1976–2014) to clarify the causal connection between these factors. The findings show only statistically significant evidence of an asymmetric response of CO2 to changes in remittances in the short-run, but there is a long-run cointegrating link between remittances and CO2 on a per capita basis. The study suggested for creating initiatives that encourage investors and consumers to use remittances to make eco-friendly purchases. FDI and environmental sustainability Besides remittances, FDI is also linked to environmental sustainability. FDI increases capital inflows, supports the BOP constraints, promotes export, increases employment opportunities, increases competition among developing countries, and advances technology. However, marginal social costs remain higher if all marginal damages in the form of environmental degradation are added due to this FDI-led production- and consumption-polluting activities (Mohsin et al. 2022). FDI boosts domestic production. The investment rate also rises with access to new financial and technological resources. However, FDI, financial development, and energy consumption are interrelated to affect economic growth (Xu et al. 2018; Ziaei 2015). Earlier studies on FDI have mainly concentrated on production-based pollution, neglecting to consider consumption-based pollution (Liddle 2018). Trade is substantial for consumption-based emissions. However, they are not effective for territory-based emissions. Imports raise consumption-based emissions, while exports reduce them. The importance of fossil fuels in terms of energy is substantially more significant when it comes to emissions based on territory. A few studies showed that trade and globalization stimulate territory-based CO2 emissions (Abbasi et al. 2022a; Hasanov et al. 2018). Therefore, the consumption-related carbon emissions and FDI could be positively linked, confirming the pollutant haven hypothesis predicated on the assumption that FDI inflows negatively impact receiving economies (Gyamfi 2021). For the top five developing-nation emitters of GHG from fuel combustion between 1982 and 2016, Sarkodie and Strezov (2019) determined the impact of FDI, economic growth, and energy consumption on GHG emissions. The research demonstrated the validity of the pollution haven hypothesis and discovered a significant positive relationship between energy usage and GHG emissions. The SDGs will be accomplished by developing nations with FDI that includes the transfer of clean technologies and improvements in labor and environmental management standards. Besides, Jain (2017) examined the connections between environmental degradation, economic development, energy use, and FDI in six sub-Saharan African countries between 1980 and 2014. The results showed unidirectional causality running CO2 to FDI in the long-run. CO2 levels rose by 49% for every 1% increase in energy consumption. The study recommended using eco-technology to protect lives and preserve a green environment. In a panel of BRI nations from 1995 to 2016, Khan et al. (2020a) examined the effects of FDI and renewable energy on CO2 emissions by employing GMM and FMOLS. The BRI panel’s pollution haven hypothesis is refuted by empirical findings that renewable energy is effective in reducing CO2 emissions and the negative sign of FDI with CO2 emissions. Fossil fuels consumption and environmental sustainability For millennia, fossil fuel consumption is resulting in excessive pollution, traffic congestion, and increase environmental stress (Miller 2013). All countries and regions promote the need for a paradigm shift away from fossil fuels and toward renewable energy sources (Abbasi et al. 2022b; Asongu et al. 2020; Martins et al. 2019; Midilli & Dincer 2008). Earlier studies have determined the link between the use of fossil fuels and carbon emissions. Therefore, the adoption of more robust energy conservation programs is essential to reduce emissions and pollution (Al-Mulali and Sab 2012a, b; Alam et al. 2016; Apergis and Ozturk 2015; Behera and Dash 2017; Diao et al. 2009; Fodha and Zaghdoud 2010; Tao et al. 2008). In addition, fossil fuel resource extraction, delivery, and use are vulnerable to climate change, especially when combined with other global-scale changes. For example, changes in ambient temperature can have a direct impact on fossil energy demand. Since the year 2000, fossil fuel emissions have risen dramatically, partially due to the failure of most Kyoto Protocol signatories to reduce CO2 emissions and partly due to China (the world’s leading emitter) and India’s exceptionally rapid industrial expansion (Levin 2013). Moreover, Koengkan (2018) examined how the use of renewable energy affected CO2 emissions in five MERCOSUR countries. The short- and long-run results of the ARDL model showed that economic expansion and fossil fuel consumption raised CO2 emissions, whereas renewable energy use decreased them. Hanif (2017) examined how the use of fossil fuels, the use of electricity, and urbanization affected the environmental degradation that occurred in a panel of 20 developing Latin American and Caribbean economies by employing the system GMM from 1990 to 2015. The findings show that urbanization and fossil fuels both considerably contribute to environmental degradation. The results have also supported the EKC hypothesis. Lau et al. (2014) investigated the EKC for Malaysia between 1970 and 2008 on CO2 emissions, economic growth, FDI, and trade openness. The study, which considered FDI and trade, came to the inverted-U-shaped conclusion that there is an inverted U-shaped relationship between economic growth and CO2 emissions in both the short and long run for Malaysia. Hanif et al. (2019) studied the long- and short-run effects of economic expansion, FDI, and the use of fossil fuels on CO2 emissions in fifteen developing Asian countries. The ARDL model was used to analyze panel data for the years 1990 to 2013 in the empirical evidence. The findings demonstrated that efforts to promote economic growth contribute to the production of CO2 emissions and that the use of fossil fuels worsens the environment by increasing CO2 emissions. The results also provided proof that EKC exists in the panel. Finally, the research implied that limiting the use of fossil fuels and encouraging an environmentally sustainable economic growth approach will be beneficial for the overall wellbeing of the countries. Economic growth and environmental sustainability The issue of how to protect the environment has been a fundamental aspect for academia and policymakers for a couple of decades. There is a contentious discussion over the term “green growth” (Ekins 2002). A substantial amount of literature has previously determined the relationship between economic expansion and carbon emissions (Al-Mulali and Sab 2012a, b; Alam et al. 2016; Apergis and Ozturk 2015; Dashper 2020; Diao et al. 2009; Fodha and Zaghdoud 2010; Hanif 2018; Kirikkaleli 2020; Nasreen et al. 2017; Tao et al. 2008; Wang et al. 2016). Long-term policies should promote the use of renewable energy sources in different sectors. By employing FMOLS and the Granger causality test between 1973 and 2018, Salazar-Núñez et al. (2022) investigated the connections between energy consumption, economic growth, and CO2 emissions in Mexico. Economic growth had the largest impact on CO2 emissions, which gives empirical support for an EKC for Mexico. Renewable and nonrenewable energy and economic expansion contribute significantly to environmental degradation. The causality results also endorsed the relationship among the variables. In a panel of 22 of the top remittance-receiving countries, Zafar et al. (2022) investigated the link between remittances, export diversification, education, and CO2 emissions while adjusting for renewable energy and economic growth. The study used a variety of econometric techniques to show that export diversification, remittances, and renewable energy all contribute to slowing down environmental deterioration. In contrast, environmental deterioration is increased by economic expansion. Shan et al. (2021) gave detailed accounts of CO2 emissions for 294 Chinese cities. According to the findings, just 11% of cities showed high decoupling between 2005 and 2015, while 66% of cities showed weak decoupling and 23% showed no decoupling at all. The study also found that the improvement in production and carbon efficiency, which leads to a decrease in emission intensity, is the most significant socioeconomic element in explaining the economic-emission decoupling in cities. CO2 emissions and emissions-GDP decoupling in Chinese cities may have implications for other emerging nations when designing low-carbon growth strategies. A critical analysis of the literature shows that several studies researched the relationship between international capital flows, energy use, CO2 emissions, and other explanatory variables. For example, Deng et al. (2022), Rani et al. (2022), and Yang et al. (2020) studied the influence of remittances, energy use, and other macroeconomics variables on CO2 for a panel of countries while Ahmad et al. (2022) and Neog and Yadava (2020) conducted the same for a single country’s time series analysis. Rahman et al. (2019) and Zhang et al. (2022) examined the effect of FDI along with remittances, energy consumption, and other macroeconomics variables on environmental degradation for a panel of countries, while Jafri et al. (2022). Therefore, it is concluded that the past literature review mostly used ARDL and NARDL for a single country analysis. In contrast, other studies used NARDL-PMG, FMOLS, DOLS, and GMM for panel estimation. The earlier studies mostly remain limited to a country or two except Rani et al. (2022) which linked remittances, economic growth, and fossil fuel only for SAARC countries. None of the earlier studies have examined the symmetric and asymmetric impact of remittances along with FDI, FFEC, and per capita income (GDP) on environmental sustainability for the South Asian region. Along with remittances, South Asian countries experienced a fundamental shift in the 1990s that has been even more pronounced in subsequent years in the FDI environment (Sahoo 2006). South Asia is one of the world’s most populous regions. The population distribution of South Asia is rapidly transforming the way. A massive population implies that energy is used extensively for economic growth, resulting in increased CO2 emissions. As a result, the current study employs remittance and FDI as a tool for economic growth and reveals their involvement in boosting CO2 emissions for the region (Rahman et al. 2019). India and Pakistan are among the top remittance-receiving countries while India is among the top CO2 emitter economies, FDI destination, and energy consumers among these economies (WDI 2022). However, the empirical findings are still insufficient for advising effective policy to increase energy efficiency and environmental quality because of differences in periods, variables evaluated, countries or regions selection, and models used, particularly in the South Asian region. A summary of the literature is provided in Table 1.Table 1 Review of past literature S. No Authors Countries/region Data and methods Objectives/contributions Results/conclusions 1 Deng et al. (2022) BRICS 1991–2019 NARDL-PMG, FMOLS, DOLS Studied the effect of REM on renewable energy usage (REC) and ecological sustainability (CO2) LR: FDI↑ CO2↑, LR: REM + ↑ REC↑, REM-↑ REC↑, LR: REM-↑ CO2↑ 2 Zhang et al. (2022) Top 10 remittance-receiving countries 1990–2018 CUP-FM, CUP-BC EKC hypothesis: evaluated the influence of REM and FDI on the ecological footprint (EFP) with economic growth and renewable (REC) and non-renewable energy (NRENV) REM↑ EFP↑, FDI↑ EFP↑, NRENV↑ EFP↑, REC↑ EFP↓. The turning point calculated using long-run regression was $1369 3 Jafri et al. (2022) China 1981–2019 ARDL, NARDL The study examined the asymmetric effect of FDI and REM on CO2 LR and SR: REM + ↑ CO2↓, REM-↑ CO2↓, FDI + ↑ CO2↑, FDI-↑ CO2↑, ΔFDI +  > ΔFDI- 4 Mohsin et al. (2022) European and Central Asian countries 1971–2016 ARDL Determined the relationship between sustainable environment (CO2), EC, REM, GDP, and FDI LR: GDP↑ CO2↓, SR: GDP↑ CO2↑, GDP → CO2, CO2 → EC, CO2 → FDI 5 Khan et al. (2020d) BRICS 1986–2016 CCEMG and FM-LS Researched the possible link between REM, FDI, GDP, energy use (EC), and CO2 REM↑CO2↑, FDI↑CO2↑. The study is supporting the pollution haven hypothesis. The energy consumption promotes the energy-led emanation phenomenon. REM ↔ CO2 6 Rani et al. (2022) SAARC 1990–2020 FMOLS, DOLS, FE-OLS Studied the causal linkage between energy consumption (EC), financial development (FD), and CO2 emissions using remittances (REM) as a GDP instrument REM↑CO2↑, FD↑CO2↑, EC↑CO2↑, GDP↑CO2↑ 7 Itoo & Ali (2022) India 1980–2018 ARDL, FMOLS, DOLS, CCR Examined the impact of NREC, remittances and GDP on CO2 REM↑ CO2↑. The study is not supporting EKC hypothesis 8 Islam (2022) Top eight remittance-receiving countries 1980–2018 GLS, PMG, D-H panel causality The study investigated the environmental effect of remittances LR: REM + ↑ CO2↓, REM-↑ CO2↓, most of the variables have a bidirectional causality 9 Zafar et al. (2022) Top 22 remittance-receiving countries 1986–2017 CUP-FM, CUP-BC, GQR The study estimated the dynamic linkage between remittances, renewable energy consumption, economic growth, and CO2 REM↑ CO2↓ 10 Mahalik et al. (2021) India 1978–2014 ARDL The relative impact of remittances and overall aid and energy aid on CO2 is examined REM↑CO2↓, FDI↑CO2↓ 11 Ahmad et al. (2022) Pakistan 1980–2018 ARDL, NARDL The study investigated whether REM has a symmetric or asymmetric impact on CO2 emissions LR and SR: REM + ↑ CO2↑, REM-↑ CO2↑, ΔREM +  > ΔREM- 12 Neog & Yadava (2020) India 1980–2014 ARDL, NARDL The study determines the asymmetric relationship between CO2, REM, and FD LR: REM + ↑ CO2↑, REM-↑ CO2↓ 13 Yang et al. (2020) 97 countries 1990–2016 GMM The study analyzed the influence of REM, EC, FD, urbanization, trade (T), globalization (KOF index), and GDP on CO2 REM↑ CO2↑, EC↑ CO2↑, KOF↑ CO2↓. The study is suggesting strict market regulations and monitoring for environmentally friendly production technologies and renewable energy sources 14 Rehman et al. (2019) Top six Asian remittance-receiving countries 1982–2014 ARDL Investigated the relationship among REM, FDI, EC, and CO2 LR and SR: EC↑ CO2↑, LR: REM↑ CO2↑ (Sri Lanka, Pakistan, Philippines, Bangladesh), LR: FDI↑ CO2↑ (China, India, and Sri Lanka). The relationship between international capital flows and CO2 differs across countries 15 Ahmad et al. (2019) China 1980–2014 ARDL, NARDL The study determined the environmental effect of remittances LR: REM + ↑ CO2↑, REM-↑ CO2↓ 16 Sharma et al. (2019) Nepal 1971–2013 ARDL The study investigated the impact of remittances and economic growth on CO2 REM↑CO2↓, GDP↑CO2↑ Materials and methods Data source The study examined the link between fuel energy consumption and international capital flows with carbon emissions in South Asia from 1975 to 2020. The natural logarithm of the variables is used to analyze the proportional link between the variables. The summary of the dataset is shown in Table 2. The World Development Indicator, WDI (2022), collects data for all the variables in question.Table 2 Summary of dataset Variable Explanation Source CO2 CO2 emissions from solid fuel consumption (kilotons) WDI (2022) REM Personal remittances received (% of GDP) FDI Foreign direct investment, net inflows (% of GDP) FFEC Fossil fuel energy consumption (% of total) GDP GDP per capita (constant 2015 US$) Model The changes in REM, FDI, FFEC, and GDP are among the most critical factors in CO2 emission. The functional form and model are constructed as follows:1 CO2=f(REM,FDI,FFEC,GDP) 2 CO2t=α0+α1REMt+α2FDIt+α3FFECt+α4GDPt+εt where α0 is the intercept, α1 to α4 are the slopes, and εt is the error term. For time series analysis, there are irregular ups and downs in the movement of variables over time, and the relationship between variables could be interrelated directly. There are random walks and drifts in the time trend of related variables. Graphical representations of related variables would also be analyzed to test trends and drift in variables. The initial stages will determine descriptive statistics and correlation between associated variables. The time series should be separated from random effects and required to be stationary. With a null hypothesis of unit root, ADF (Dickey and Fuller 1979), and PP (Phillips and Perron 1988) testsare used for the order of integration. Stationarity test by unit root testing is required for meaningful estimation and interpretation of the relationship for policy implication. ADF unit root test is used to find the maximum number of integrations. Besides, the PP test is robust against heteroscedasticity, allows for weaker assumptions on the distribution of errors, and controls for higher-order serial correlation (Khanal et al. 2022). The ADF test is more appropriate for finite data, while the PP test provided a non-parametric correction to t test statistics employed by Mohsin et al. (2022). As a result, the study used both the ADF and PP tests to check stationarity. The least-squares method for the individual intercept is used in the ADF and PP tests in Eqs. (3) and (4) as.3 ADF:Δyt=α0+αyt-1+∑i=1pβjΔyt-i+εt 4 PP:Δyt=(p-1)yt-1+εt where Δ is the first difference operator, α0 is the intercept, p is the lag order of the autoregressive process, and εt is the error term. Long-run relationships between series are relatively more important for policymakers than short run as these variables are used to change the policies with caution. Moreover, outcomes of changes in one variable significantly cause a short- or long-run difference in related variables as all macroeconomic variables, to some extent, are interrelated with each other. There are several econometric approaches with their applications to obtain long-run relations. Engle and Granger (1987) was widely used for the long-run relationship among variables in the past. This study used the ARDL technique by Pesaran et al. (2001) to analyze the long-run relationship between the variables. ARDL is preferred over others as the order of integration is not a significant subject matter, while old techniques required testing of the order of integration in the initial steps. Another significance of the model is that it can be used effectively for relatively small samples, for instance, whether the variables may have different lags. The ARDL model representation is devised in Eq. (5) as:5 ΔCO2t=α0+∑i=1mδiΔCO2t-i+∑i=0mγiΔREMt-i+∑i=0mβiΔFDIt-i+∑i=0mωiΔFFECt-i+∑i=0mφiΔGDPt-i+λ1CO2t-1+λ2REMt-1+λ3FDIt-1+λ4FFECt-1+λ5GDPt-1+εt The study used Pesaran et al. (2001) technique to formulate long-run functional relationships between related variables. F test is employed in this methodology with a joint significance test. The cointegration is assessed based on the bounds F test. F test would be indecisive in the range of upper and lower bound limits. Equation (6) represents the error correction term (ECT) as:6 ΔCO2=α0+∑i=1mδiΔCO2t-i+∑i=0mγiΔREMt-i+∑i=0mβiΔFDIt-i+∑i=0mωiΔFFECt-i+∑i=0mφiΔGDPt-i+λECTt-1+εt ECT shows the speed of adjustment (λ) to the steady-state. A simple and linear model has two limitations: it cannot be used to test for asymmetric uncertainty effects, and the data may include other nonlinearities. NARDL is the extension of simple ARDL. Shin et al. (2014) developed the NARDL for short- and long-run nonlinearities generated through positive and negative partial sum decompositions of the explanatory variables. As a result, using more robust statistical methodologies, this study attempts to fill a gap in the existing literature. Compared to ARDL, the NARDL approach has different advantages. The NARDL approach distinguished between short- and long-run asymmetries, testing dependent variable responses to positive and negative changes in each explanatory factor, and is adaptive to cointegration dynamics between variables (Ahmad et al. 2022). None of the earlier studies have yet examined asymmetries to decompose the shocks of explanatory variables into partial positive and negative sums for the South Asian region. The policymakers are concerned more about asymmetries that typical symmetrical approaches do not capture. The explanatory variables are divided into positive and negative changes by a partial sum approach:7 REMt+=∑n=1tΔREMt+=∑n=1tmax(ΔREMt,0) 8 REMt-=∑n=1tΔREMt-=∑n=1tmin(ΔREMt,0) 9 FDIt+=∑n=1tΔFDIt+=∑n=1tmax(ΔFDIt,0) 10 FDIt-=∑n=1tΔFDIt-=∑n=1tmin(ΔFDIt,0) 11 FFECt+=∑n=1tΔFFECt+=∑n=1tmax(ΔFFECt,0) 12 FFECt-=∑n=1tΔFFECt-=∑n=1tmin(ΔFFECt,0) 13 GDPt+=∑n=1tΔGDPt+=∑n=1tmax(ΔGDPt,0) 14 GDPt-=∑n=1tΔGDPt-=∑n=1tmin(ΔGDPt,0) Substituting Eqs. (7)–(14), the modified model in Eq. (15) will be as follows:15 ΔCO2t=γ0+∑k=1pδkΔCO2t-k+∑k=0pθkΔREMt-k++∑k=0pϕkΔREMt-k-+∑k=0pϑkΔFDIt-k++∑k=0pβkΔFDIt-k-+∑k=0pρkΔECt-k++∑k=0pτkΔECt-k-+∑k=0pωkΔGDPt-k++∑k=0pϖkΔGDPt-k-+φ1CO2t-1+φ2REMt-1++φ3REMt-1-+φ3FDIt-1++φ4FDIt-1-+φ5ECt-1++φ6ECt-1-+φ7GDPt-1++φ8GDPt-1-+εt Results and discussions The mean value of the logarithmic variables, CO2, REM, FDI, FFEC, and GDP, are 13.14, 0.86, − 1.21, 3.99, and 6.54, respectively (Table 3). All variables have a positive mean value except the FDI. The higher standard deviation implies that the FDI is widely distributed among the member countries. The min–max values for FDI also indicate the same. The data is nearly symmetrical for CO2 and GDP. REM has the highest (leptokurtic) while GDP and CO2 have the lowest (platykurtic) kurtosis values among the variables. Following the descriptive statistics, a correlation matrix indicates the degree of relationship between the variables. There is a strong positive correlation among the variables.Table 3 Descriptive statistics and correlation matrix Statistics CO2 REM FDI FFEC GDP Mean 13.14 0.86  − 1.21 3.99 6.54 Median 13.19 0.86  − 0.66 4.06 6.49 Maximum 14.24 1.55 1.21 4.27 7.28 Minimum 12.11  − 0.85  − 5.42 3.58 5.99 Std. Dev 0.62 0.50 1.60 0.22 0.39 Skewness  − 0.01  − 0.98  − 0.56  − 0.58 0.32 Kurtosis 1.93 4.90 2.62 2.07 1.91 Correlation matrix   CO2 1.00   REM 0.82* 1.00   FDI 0.93* 0.85* 1.00   FFEC 0.98* 0.79* 0.94* 1.00   GDP 0.99* 0.83* 0.90* 0.94* 1.00 Authors’ calculation. *Significance level at 1% Table 4 shows the results of the ADF and PP unit root tests. The study used the maximum available lag length with automatic selection criteria (using EViews 10). Some variables are stationary at the level, but all are stationary at the first difference. Only REM is stationary at the level and the first difference, with both trend and trend and intercept in ADF and PP. The variables in this study have a mixed nature of stationarity properties, stationary at both the level, and the first difference.Table 4 Unit root test Variables ADF PP I (0) I (1) I (0) I (1) CO2 0.09  − 7.59* 0.12  − 7.49* REM  − 4.43*  − 6.47*  − 3.8  − 6.69* FDI  − 0.29  − 6.45* 0.3  − 6.86* FFEC  − 2.63***  − 2.67***  − 2.43  − 5.07* GDP 1.29  − 4.42* 1.29  − 4.45* Authors’ calculation. *, **, and ***Significance level at 1%, 5%, and 10%, respectively The short-run and long-run ARDL and NARDL estimates are reported in Table 5. The study used the maximum available lag length with automatic selection criteria (dependent variable maximum lags = 2 and regressors maximum lags = 2). According to ARDL’s empirical findings, the short-run analysis shows that there is a positive effect of REM and FFEC on CO2; that is, a 1% rise in REM and FFEC contributes to CO2 by 0.08% and 1.81% at the 1% significance level, respectively. Furthermore, the result indicates that FDI is negatively related to CO2 in the short run; a 1% rise in FDI contributes by 0.03% to CO2. The long-run association of the ARDL model shows that FFEC and GDP are positive while REM and FDI are negatively related to CO2 significantly. According to the findings, a 1% increase in FFEC and GDP contributes 0.98% and 1.40% to CO2, respectively. On the other hand, the long-run analysis shows that a 1% increase in REM and FDI decreases CO2 by − 0.18% and − 0.04%, respectively. The findings imply that South Asia's international capital flows are reducing CO2 while energy consumption and economic growth adversely affect the environment. NARDL estimates are also summarized in Table 5. The short-run analysis shows that REM + and FFEC + positively impact CO2. The results reveal that a 1% increase in the REM + and FFEC + increases CO2 by 0.10% and 1.28%. A 1% rise in GDP- increases CO2 by 6.52%, while a 1% increase in the FDI- causes a decrease in CO2 by 0.02%. The long-run analysis shows that REM + is significant and negatively related to CO2, while the negative part is negative but insignificant. A 1% rise in REM + decreases CO2 by 0.31%. A 1% increment in FDI + insignificantly decreases CO2 by 0.06%, while a 1% gain in FDI- significantly decreases CO2 by 0.11%. A 1% increase in FFEC + and FFEC- significantly increases CO2 by 1.08% and 106.44%, respectively. Finally, a 1% rise in GDP + significantly increases CO2 by 1.84%, while a 1% increase in GDP- significantly increases CO2 by 22.18%. The results are consistent with Rani et al. (2022), Zafar et al. (2022), Wang et al. (2021), Yang et al. (2020), and Rahman et al. (2019).Table 5 Short- and long-run estimates of ARDL (1, 2, 2, 1, 0) and NARDL (1, 2, 0, 0, 2, 1, 2, 0, 1) Variable ARDL NARDL Coeff SE t Stat Prob Coeff SE t Stat Prob Short-run   D (CO2)  − 0.61* 0.11  − 5.35 0.00  − 0.47* 0.12  − 3.81 0.00   D (REM)  − 0.11 0.04  − 3.04 0.01   D (REM (− 1)) 0.09* 0.03 3.29 0.00   D (REM +) 0.10* 0.03 3.38 0.00   D (REM + (-1)) 0.12* 0.03 3.44 0.00   D (FDI)  − 0.03* 0.01  − 2.95 0.01   D (FDI (− 1)) 0.02** 0.01 2.58 0.02   D (FDI-)  − 0.02*** 0.01  − 1.81 0.08   D (FDI-(− 1)) 0.05* 0.01 4.20 0.00   D (FFEC) 1.81* 0.17 10.90 0.00   D (FFEC +) 1.28* 0.19 6.85 0.00   D (FFEC-) 30.99* 2.80 11.08 0.00   D (FFEC-(− 1))  − 38.47* 6.27  − 6.13 0.00   D (GDP-) 6.52** 2.70 2.42 0.02 R squared 0.75 0.84   Durbin-Watson stat 1.91 2.00   Akaike info criterion  − 4.98  − 5.22   Schwarz criterion  − 4.71  − 4.83 Long-run   REM  − 0.18* 0.05  − 3.32 0.00   REM +   − 0.31** 0.12  − 2.59 0.02   REM- 0.10 0.20 0.51 0.61   FDI  − 0.04*** 0.02  − 1.87 0.07   FDI +   − 0.06 0.06  − 1.06 0.30   FDI-  − 0.11** 0.05  − 2.11 0.05   FFEC 0.98* 0.19 5.20 0.00   FFEC +  1.08*** 0.58 1.87 0.08   FFEC- 106.44** 42.54 2.50 0.02   GDP 1.40* 0.10 13.70 0.00   GDP +  1.84* 0.37 5.03 0.00   GDP-  − 22.18** 10.77  − 2.06 0.05   C 0.19 0.62 0.30 0.76 13.47* 0.78 17.19 0.00 Bound test   F test 15.05* 8.58*   ECT  − 0.61* 0.06  − 10.45 0.00  − 0.47* 0.04  − 11.07 0.00 Diagnostic tests   LM 0.11 0.34   BPG Hetero.   test 0.28 0.63 RESET 2.10 0.51 Authors’ estimation. *, **, and ***Significance level at 1%, 5%, and 10%, respectively The bound test of ARDL and the NARDL confirms the long-run relationship among the variables. ECT has a negative and statistically significant value for the ARDL (− 0.61) and the NARDL (− 0.47), ensuring the pace with which the system adjusts to the long-run equilibrium path. The ECT results are consistent with many studies that have also estimated a relatively high speed of adjustment to equilibrium such as Khalid et al. (2021) estimated a value of − 0.51 for Bangladesh, − 0.57 for India, − 0.96 for Nepal, − 0.69 for Pakistan, − 0.94 for Sri Lanka, − Ali et al. (2019) estimated − 0.76 for Pakistan, − Shahbaz et al. (2015) estimated more than − 0.7 for many African countries, Waqih et al. (2019) estimated − 0.52 for SAARC region, Attiaoui et al. (2017) estimated − 0.44 for African countries, and Jafri et al. (2022) estimated − 0.64 (ARDL), and − 0.74 (NARDL) for China. The study uses multiple statistical tests on the dataset to confirm the validity of the findings, including the tests for serial correlation, heteroskedasticity, and normality. All diagnostic test statistics show no evidence of model misspecification. Figure 1 shows the results of the CUSUM and CUSUMSQ for ARDL (Fig. 1a and b) and NARDL (Fig. 1c and d) models to look at the parameter constancy, as suggested by Brown et al. (1975) and Pesaran and Pesaran (1999). The findings indicate that the statistics graph for CUSUM and CUSUMSQ stays within the critical range at the 5% threshold, indicating that the coefficients of the energy equation are stable (Fig. 1a and d) otherwise crossing the range at the 5% threshold (Fig. 1b and c). The study employed the recursive coefficients test for stability assessment (Rahman and Alam 2022; Taghvaee et al. 2022). All the plotted figures have expressed the better stability of this model (Fig. 1e and f).Fig. 1 CUSUM, CUSUMSQ, and recursive coefficients test for ARDL and NARDL The dynamic multiplier graphs are drawn in Fig. 2. The cumulative dynamic multipliers revealed the adjustment pattern to new long-run equilibria. For example, the adjustment to positive and negative shocks at a specific prediction horizon is represented by the positive (continuous black) and negative (dashed black) curves. The broken red asymmetry plot shows the difference in the responses of multipliers with 95% confidence intervals. The plots further reveal that negative shocks in decomposed variables (excluding FFEC) affect the long run more than positive shocks. In contrast, positive shocks in FFEC affect the long run more than negative shocks.Fig. 2 Dynamic multiplier graphs Conclusion and policy implications There are many studies in the literature on the CO2-remittances nexus, CO2-FDI nexus, CO2-economic growth, and others, but no study has yet taken remittances and FDI into account in the model for the South Asian region. This research examines if international capital flows, fossil fuel energy consumption, and economic growth have symmetric and asymmetric impacts on South Asian carbon emissions. The study employed a time series data set from 1975 to 2020 for the South Asian region ignored by the existing literature. The main contribution is that it uses a new asymmetric ARDL technique to examine whether international capital flows have positive or negative shocks. The study used ADF and PP for the unit root test. The ARDL and NARDL results confirm a linear and non-linear connection between the CO2, REM, FDI, FFEC, and GDP in the short and long run. According to the empirical evidence, the positive effect of FFEC outweighs the negative impact of FFEC, while the opposite is true for the other variables. Carbon emissions have been a major cause of extreme environmental pollution, with negative repercussions for human life regardless of whether a country’s economy is developed or underdeveloped. Therefore, cutting such emissions in developing nations is critical to maintaining economic growth. South Asia mainly relies on fossil fuels to meet its energy needs, whose imports are primarily financed by international capital flows. Despite increased energy output, the demand is much more than the supply. As a result, countries rely on fossil fuel imports to meet their energy needs. Initiatives to enhance energy security include diversifying the energy mix, raising the proportion of renewable energy sources, fostering regional cooperation to maximize the hydropower potential of the region, and putting energy-saving measures in place to minimize transmission and distribution losses. The region’s large economies contributing more to environmental degradation should serve as a platform for national and regional bodies to collaborate on similar concerns about transboundary pollution (Han and BiBi 2022; Khan et al. 2022b). It is essential that all sectors, especially the industrial sector of South Asian countries, should be sensitized to ensure that emission levels comply with worldwide health and environmental standards. These regulations should be enforced with legal consequences to ensure and limit the type and amount of environmental degradation. The International Energy Agency (IEA) emphasizes a historic surge in renewable and energy investment to avoid severe climate change impacts. The clean energy investment must have tripled to four trillion dollars to achieve net zero emissions by 2050. This will create millions of new employment opportunities and boost global economic development. Financially constrained countries can efficiently use remittances and FDI for these investments. However, sustainable energy investments frequently face an uphill battle due to controlled prices or taxes that favor fossil fuels in almost all South Asian countries (IEA 2021). In addition, the region needs to improve its green infrastructure through international capital flows. The present levels of fossil fuel energy use are ineffective for environmental protection. To achieve long-term environmental and economic goals, governments must adopt transformation initiatives toward green energy and less polluting economic growth sectors. This study is limited to the South Asian region. However, this can be expanded to other regions for a comparative study, particularly by using more recent data and other sources of foreign financial flows such as foreign aid and others. Acknowledgements Authors would like to thank the World Bank for publicizing the raw data and reports. Author contribution M. Umair: conceptualization, data curation, formal analysis, investigation, software, writing, and reviewing. M.U.Yousuf: conceptualization, data curation, formal analysis, investigation, validation, writing, and reviewing. Data availability These data were obtained from the World Development Indicators, DataBank organized by the World Bank. Declarations Ethical approval Not applicable. Consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Abbasi KR Hussain K Haddad AM Salman A Ozturk I The role of financial development and technological innovation towards sustainable development in Pakistan: fresh insights from consumption and territory-based emissions Technol Forecast Soc Chang 2022 176 121444 10.1016/j.techfore.2021.121444 Abbasi KR Shahbaz M Zhang J Irfan M Alvarado R Analyze the environmental sustainability factors of China: the role of fossil fuel energy and renewable energy Renew Energy 2022 187 390 402 10.1016/j.renene.2022.01.066 Adebanjo SA, Shakiru TH (2022) Dynamic relationship between air pollution and economic growth in Jordan: an empirical analysis. J Environ Sci Econ 1:30–43. 10.56556/jescae.v1i2.17 Ahmad M Ul Haq Z Khan Z Khattak SI Ur Rahman Z Khan S Does the inflow of remittances cause environmental degradation? Empirical evidence from China Econ Res-Ekonomska Istraživanja 2019 32 2099 2121 10.1080/1331677X.2019.1642783 Ahmad M Khan Z Rahman ZU Khattak SI Khan ZU Can innovation shocks determine CO2 emissions (CO2e) in the OECD economies? A new perspective Econ Innov New Technol 2021 30 89 109 10.1080/10438599.2019.1684643 Ahmad W Ozturk I Majeed MT How do remittances affect environmental sustainability in Pakistan? Evid NARDL Approach Energy 2022 243 122726 10.1016/j.energy.2021.122726 Al-Mulali U Sab CNBC The impact of energy consumption and CO2 emission on the economic growth and financial development in the Sub Saharan African countries Energy 2012 39 180 186 10.1016/j.energy.2012.01.032 Al-Mulali U Sab CNBC The impact of energy consumption and CO2 emission on the economic and financial development in 19 selected countries Renew Sustain Energy Rev 2012 16 4365 4369 10.1016/j.rser.2012.05.017 Alam MM Murad MW Noman AHM Ozturk I Relationships among carbon emissions, economic growth, energy consumption and population growth: testing environmental Kuznets curve hypothesis for Brazil, China, India and Indonesia Ecol Ind 2016 70 466 479 10.1016/j.ecolind.2016.06.043 Ali R Bakhsh K Yasin MA Impact of urbanization on CO2 emissions in emerging economy: evidence from Pakistan Sustain Cities Soc 2019 48 101553 10.1016/j.scs.2019.101553 Apergis N, Ozturk I (2015) Testing environmental Kuznets curve hypothesis in Asian countries. Ecol Indic 52:16–22. 10.1016/j.ecolind.2014.11.026 Asongu SA Agboola MO Alola AA Bekun FV The criticality of growth, urbanization, electricity and fossil fuel consumption to environment sustainability in Africa Sci Total Environ 2020 712 136376 10.1016/j.scitotenv.2019.136376 31927442 Attiaoui I Toumi H Ammouri B Gargouri I Causality links among renewable energy consumption, CO2 emissions, and economic growth in Africa: evidence from a panel ARDL-PMG approach Environ Sci Pollut Res 2017 24 13036 13048 10.1007/s11356-017-8850-7 Balsalobre-Lorente D Ibáñez-Luzón L Usman M Shahbaz M The environmental Kuznets curve, based on the economic complexity, and the pollution haven hypothesis in PIIGS countries Renew Energy 2022 185 1441 1455 10.1016/j.renene.2021.10.059 Behera SR Dash DP The effect of urbanization, energy consumption, and foreign direct investment on the carbon dioxide emission in the SSEA (South and Southeast Asian) region Renew Sustain Energy Rev 2017 70 96 106 10.1016/j.rser.2016.11.201 Brown L McFarlane A Campbell K Das A Remittances and CO2 emissions in Jamaica: an asymmetric modified environmental Kuznets curve J Econ Asymmetries 2020 22 e00166 10.1016/j.jeca.2020.e00166 Brown RL Durbin J Evans JM Techniques for testing the constancy of regression relationships over time J R Stat Soc Ser B Methodol 1975 37 149 163 10.1111/j.2517-6161.1975.tb01532.x Dashper K Mentoring for gender equality: supporting female leaders in the hospitality industry Int J Hosp Manag 2020 88 102397 10.1016/j.ijhm.2019.102397 Deng Z Liu J Sohail S Green economy design in BRICS: dynamic relationship between financial inflow, renewable energy consumption, and environmental quality Environ Sci Pollut Res 2022 29 22505 22514 10.1007/s11356-021-17376-8 Diao XD Zeng SX Tam CM Tam VW EKC analysis for studying economic growth and environmental quality: a case study in China J Clean Prod 2009 17 541 548 10.1016/j.jclepro.2008.09.007 Dickey DA Fuller WA Distribution of the estimators for autoregressive time series with a unit root J Am Stat Assoc 1979 74 427 431 10.1080/01621459.1979.10482531 Ekins P (2002) Economic growth and environmental sustainability: the prospects for green growth. Routledge, London. 10.4324/9780203011751 Engle RF, Granger CW (1987) Co-integration and error correction: representation, estimation, and testing. Econometrica: Journal of the Econometric Society 251–276. 10.2307/1913236 Farhani S Ozturk I Causal relationship between CO2 emissions, real GDP, energy consumption, financial development, trade openness, and urbanization in Tunisia Environ Sci Pollut Res 2015 22 15663 15676 10.1007/s11356-015-4767-1 Fodha M Zaghdoud O Economic growth and pollutant emissions in Tunisia: an empirical analysis of the environmental Kuznets curve Energy Policy 2010 38 1150 1156 10.1016/j.enpol.2009.11.002 Gyamfi BA (2021) Consumption-based carbon emission and foreign direct investment in oil-producing Sub-Sahara African countries: the role of natural resources and urbanization. Environ Sci Pollut Res 1-13. 10.1007/s11356-021-16509-3 Han L, BiBi R (2022) The role of technological innovations and renewable energy consumption in reducing environmental degradation: evidence from the belt and road initiative countries. Environ SciPollut Res 1-15. 10.1007/s11356-022-21006-2 Hanif I Economics-energy-environment nexus in Latin America and the Caribbean Energy 2017 141 170 178 10.1016/j.energy.2017.09.054 Hanif I Impact of fossil fuels energy consumption, energy policies, and urban sprawl on carbon emissions in East Asia and the Pacific: A panel investigation Energ Strat Rev 2018 21 16 24 10.1016/j.esr.2018.04.006 Hanif I Raza SMF Gago-de-Santos P Abbas Q Fossil fuels, foreign direct investment, and economic growth have triggered CO2 emissions in emerging Asian economies: some empirical evidence Energy 2019 171 493 501 10.1016/j.energy.2019.01.011 Hasanov FJ Liddle B Mikayilov JI The impact of international trade on CO2 emissions in oil exporting countries: territory vs consumption emissions accounting Energy Econ 2018 74 343 350 10.1016/j.eneco.2018.06.004 Hasnat GT, Kabir MA, Hossain MAJHoemm (2018) Major environmental issues and problems of South Asia, particularly Bangladesh. In: Hussain C (ed) Handbook of Environmental Materials Management. Springer, Cham. 10.1007/978-3-319-58538-3_7-1 IEA (2021) Net zero by 2050, IEA, Paris. https://www.iea.org/reports/net-zero-by-2050. Accessed 2 Jul 2022 Islam M Do personal remittances cause environmental pollution? Evidence from the top eight remittance-receiving countries Environ Sci Pollut Res 2022 29 35768 35779 10.1007/s11356-021-18175-x Itoo HH, Ali N (2022) Analyzing the causal nexus between CO2 emissions and its determinants in India: evidences from ARDL and EKC approach. Manag Environ Qual. 10.1108/MEQ-01-2022-0014 Jafri MAH Abbas S Abbas SMY Ullah S Caring for the environment: measuring the dynamic impact of remittances and FDI on CO2 emissions in China Environ Sci Pollut Res 2022 29 9164 9172 10.1007/s11356-021-16180-8 Jain H (2017) Trade liberalization process and India’s growth experiences, trade liberalisation, economic growth and environmental externalities. Palgrave Macmillan, Singapore. 10.1007/978-981-10-2887-8_4 Jamil MN (2022) Critical analysis of energy consumption and its impact on countries economic growth: an empirical analysis base on countries income level. J Environ Sci Econ 1:1–14. 10.56556/jescae.v1i2.11 Jamil MN, Rasheed A, Mukhtar Z (2022) Corporate social responsibility impacts sustainable organizational growth (firm performance): an empirical analysis of Pakistan stock exchange-listed firms. J Environ Sci Econ 1:25–29. 10.56556/jescae.v1i2.16 Khalid K Usman M Mehdi MA The determinants of environmental quality in the SAARC region: a spatial heterogeneous panel data approach Environ Sci Pollut Res 2021 28 6422 6436 10.1007/s11356-020-10896-9 Khan A Hussain J Bano S Chenggang Y The repercussions of foreign direct investment, renewable energy and health expenditure on environmental decay? An econometric analysis of B&RI countries J Environ Planning Manage 2020 63 1965 1986 10.1080/09640568.2019.1692796 Khan H Khan I Binh TT The heterogeneity of renewable energy consumption, carbon emission and financial development in the globe: a panel quantile regression approach Energy Rep 2020 6 859 867 10.1016/j.egyr.2020.04.002 Khan H, Khan I, Kim Oanh LT, Lin Z (2020c) The dynamic interrelationship of environmental factors and foreign direct investment: dynamic panel data analysis and new evidence from the globe. Math ProblEng 2020c. 10.1155/2020/2812489 Khan H Weili L Khan I Institutional quality, financial development and the influence of environmental factors on carbon emissions: evidence from a global perspective Environ Sci Pollut Res 2022 29 13356 13368 10.1007/s11356-021-16626-z Khan H, Weili L, Khan I (2022b) The role of financial development and institutional quality in environmental sustainability: panel data evidence from the BRI countries. Environ SciPollut Res 1-12. 10.1007/s11356-022-21697-7 Khan H, Weili L, Khan I (2022c) Examining the effect of information and communication technology, innovations, and renewable energy consumption on CO2 emission: evidence from BRICS countries. Environ SciPollut Res 1-17. 10.1007/s11356-022-19283-y Khan H Weili L Khan I The role of institutional quality in FDI inflows and carbon emission reduction: evidence from the global developing and belt road initiative countries Environ Sci Pollut Res 2022 29 30594 30621 10.1007/s11356-021-17958-6 Khan H Weili L Khan I Han L The effect of income inequality and energy consumption on environmental degradation: the role of institutions and financial development in 180 countries of the world Environ Sci Pollut Res 2022 29 20632 20649 10.1007/s11356-021-17278-9 Khan I, Han L, Khan H, Kim Oanh LT (2021) Analyzing renewable and nonrenewable energy sources for environmental quality: dynamic investigation in developing countries. Mathe Probl Eng 2021. 10.1155/2021/3399049 Khan I Han L Khan H Renewable energy consumption and local environmental effects for economic growth and carbon emission: evidence from global income countries Environ Sci Pollut Res 2022 29 13071 13088 10.1007/s11356-021-16651-y Khan ZU Ahmad M Khan A On the remittances-environment led hypothesis: empirical evidence from BRICS economies Environ Sci Pollut Res 2020 27 16460 16471 10.1007/s11356-020-07999-8 Khanal A Rahman MM Khanam R Velayutham EJESR Does tourism contribute towards zero-carbon in Australia? Evid ARDL Modell Approach 2022 43 100907 10.1016/j.esr.2022.100907 Khwaja MA, Umer F, Shaheen N, Sherazi A, Shaheen FH (2012) Air pollution reduction and control in South Asia, Working Paper Series 121, Sustainable Development Policy Institute (SDPI) Islamabad. https://sdpi.org/sdpiweb/publications/files/Air%20Pollution%20Reduction%20and%20Control%20in%20South%20Asia%20(W-121).pdf. Accessed 10 Jun 2022 Kirikkaleli D New insights into an old issue: exploring the nexus between economic growth and CO2 emissions in China Environ Sci Pollut Res 2020 27 40777 40786 10.1007/s11356-020-10090-x Koengkan M The decline of environmental degradation by renewable energy consumption in the MERCOSUR countries: an approach with ARDL modeling Environ Syst Decis 2018 38 415 425 10.1007/s10669-018-9671-z Lane PR Milesi-Ferretti GM International financial integration IMF Staff Pap 2003 50 82 113 10.2307/4149916 Lau L-S Choong C-K Eng Y-K Investigation of the environmental Kuznets curve for carbon emissions in Malaysia: do foreign direct investment and trade matter? Energy Policy 2014 68 490 497 10.1016/j.enpol.2014.01.002 Levin SA (2013) Encyclopedia of biodiversity academic press, Amsterdam Li WC Tse H Health risk and significance of mercury in the environment Environ Sci Pollut Res 2015 22 192 201 10.1007/s11356-014-3544-x Liddle B Consumption-based accounting and the trade-carbon emissions nexus Energy Econ 2018 69 71 78 10.1016/j.eneco.2017.11.004 Mahalik MK Villanthenkodath MA Mallick H Gupta M Assessing the effectiveness of total foreign aid and foreign energy aid inflows on environmental quality in India Energy Policy 2021 149 112015 10.1016/j.enpol.2020.112015 Marland G Rotty R Treat N CO2 from fossil fuel burning: global distribution of emissions Tellus B 1985 37 243 258 10.1111/j.1600-0889.1985.tb00073.x Martins F Felgueiras C Smitkova M Caetano N Analysis of fossil fuel energy consumption and environmental impacts in European countries Energies 2019 12 964 10.3390/en12060964 Meyer D Shera A The impact of remittances on economic growth: an econometric model Economia 2017 18 147 155 10.1016/j.econ.2016.06.001 Midilli A Dincer I Hydrogen as a renewable and sustainable solution in reducing global fossil fuel consumption Int J Hydrogen Energy 2008 33 4209 4222 10.1016/j.ijhydene.2008.05.024 Miller C (2013) Energy resources and policy: vulnerability of energy resources and resource availability–fossil fuels (oil, coal, natural gas, oil shale). Climate Vulnerability.10.1016/B978-0-12-384703-4.00304-X Mohsin M Naseem S Sarfraz M Azam T Assessing the effects of fuel energy consumption, foreign direct investment and GDP on CO2 emission: new data science evidence from Europe & Central Asia Fuel 2022 314 123098 10.1016/j.fuel.2021.123098 Nasreen S Anwar S Ozturk I Financial stability, energy consumption and environmental quality: evidence from South Asian economies Renew Sustain Energy Rev 2017 67 1105 1122 10.1016/j.rser.2016.09.021 Ndem BE, James HT, Agala FB (2022) Autoregressive distributed lag approach (ARDL) to corruption and economic growth nexus in Nigeria. J Environ Sci Econ 1:8–14. 10.56556/jescae.v1i3.181 Neog Y Yadava AK Nexus among CO2 emissions, remittances, and financial development: a NARDL approach for India Environ Sci Pollut Res 2020 27 44470 44481 10.1007/s11356-020-10198-0 Painter DS (2019) Burning up: a global history of fossil fuel consumption. MIT Press One Rogers Street, Cambridge, MA 02142–1209, USA journals-info … Pesaran B, Pesaran H (1999) Microfit 4.1 interactive econometric analysis. Oxford University Press, Oxford Pesaran MH Shin Y Smith RJ Bounds testing approaches to the analysis of level relationships J Appl Econ 2001 16 289 326 10.1002/jae.616 Phillips PC Perron P Testing for a unit root in time series regression Biometrika 1988 75 335 346 10.1093/biomet/75.2.335 Rahman MM, Alam K (2022) Impact of industrialization and non-renewable energy on environmental pollution in Australia: do renewable energy and financial development play a mitigating role? Renew Energy. 10.1016/j.renene.2022.06.012 Rahman Zu, Cai H, Ahmad M (2019) A new look at the remittances-FDI-energy-environment nexus in the case of selected Asian nations. Singap Econ Rev 1-19. 10.1142/S0217590819500176 Rani T, Wang F, Rauf F, Ali H (2022) Linking personal remittance and fossil fuels energy consumption to environmental degradation: evidence from all SAARC countries. Environ Dev Sustain 1-22. 10.1007/s10668-022-02407-2 Ratha D, Eigen-Zucchi C, Plaza S (2016) Migration and remittances factbook 2016, 3rd edtion. Washington, DC: World Bank. https://openknowledge.worldbank.org/bitstream/handle/10986/23743/9781464803192.pdf. Accessed 6 Mar 2022 Rehman A Rauf A Ahmad M Chandio AA Deyuan Z The effect of carbon dioxide emission and the consumption of electrical energy, fossil fuel energy, and renewable energy, on economic performance: evidence from Pakistan Environ Sci Pollut Res 2019 26 21760 21773 10.1007/s11356-019-05550-y Sabir S Qayyum U Majeed T FDI and environmental degradation: the role of political institutions in South Asian countries Environ Sci Pollut Res 2020 27 32544 32553 10.1007/s11356-020-09464-y Sahoo P (2006) Foreign direct investment in South Asia: Policy, trends, impact and determinants. Asian Development Bank. http://hdl.handle.net/11540/3644. Accessed 6 Mar 2022 Salazar-Núñez HF Venegas-Martínez F Lozano-Díez JA Assessing the interdependence among renewable and non-renewable energies, economic growth, and CO2 emissions in Mexico Environ Dev Sustain 2022 24 12850 12866 10.1007/s10668-021-01968-y Sarkodie SA Strezov V Effect of foreign direct investments, economic development and energy consumption on greenhouse gas emissions in developing countries Sci Total Environ 2019 646 862 871 10.1016/j.scitotenv.2018.07.365 30064112 Shahbaz M Solarin SA Sbia R Bibi S Does energy intensity contribute to CO2 emissions? A trivariate analysis in selected African countries Ecol Ind 2015 50 215 224 10.1016/j.ecolind.2014.11.007 Shan Y Fang S Cai B Zhou Y Li D Feng K Hubacek K Chinese cities exhibit varying degrees of decoupling of economic growth and CO2 emissions between 2005 and 2015 One Earth 2021 4 124 134 10.1016/j.oneear.2020.12.004 Sharma K, Bhattarai B, Ahmed S (2019) Aid, growth, remittances and carbon emissions in Nepal. Energy J 40. 10.5547/01956574.40.1.ksha Shin Y, Yu B, Greenwood-Nimmo M (2014) Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In: Sickles R, Horrace W (eds) Festschrift in Honor of Peter Schmidt. Springer, New York, NY. 10.1007/978-1-4899-8008-3_9 Taghvaee VM, Arani AA, Soretz S, Agheli L (2022) Diesel demand elasticities and sustainable development pillars of economy, environment and social (health): comparing two strategies of subsidy removal and energy efficiency. Environ Dev Sustain 1-31. 10.1007/s10668-021-02092-7 Tao S Zheng T Lianjun T An empirical test of the environmental Kuznets curve in China: a panel cointegration approach China Econ Rev 2008 19 381 392 10.1016/j.chieco.2007.10.001 Umair M Waheed A What drives remittances from Saudi Arabia to Pakistan? Home versus host country's economic conditions Int Migr 2017 55 141 153 10.1111/imig.12344 Wang S Li Q Fang C Zhou C The relationship between economic growth, energy consumption, and CO2 emissions: empirical evidence from China Sci Total Environ 2016 542 360 371 10.1016/j.scitotenv.2015.10.027 26520261 Wang Z Zaman S Rasool SF Impact of remittances on carbon emission: fresh evidence from a panel of five remittance-receiving countries Environ Sci Pollut Res 2021 28 52418 52430 10.1007/s11356-021-14412-5 Waqih MAU Bhutto NA Ghumro NH Kumar S Salam MA Rising environmental degradation and impact of foreign direct investment: an empirical evidence from SAARC region J Environ Manage 2019 243 472 480 10.1016/j.jenvman.2019.05.001 31125893 WDI (2022) DataBank, World Development Indicators, The World Bank. https://databank.worldbank.org/source/world-development-indicators. Accessed 1 Jan 2022 Weili L Khan H Han L The impact of information and communication technology, financial development, and energy consumption on carbon dioxide emission: evidence from the Belt and Road countries Environ Sci Pollut Res 2022 29 27703 27718 10.1007/s11356-021-18448-5 Xu X Abbas HSM Sun C Gillani S Ullah A Raza MAA Impact of globalization and governance determinants on economic growth: an empirical analysis of Asian economies Growth Chang 2021 52 1137 1154 10.1111/grow.12475 Xu Z Baloch MA Meng F Zhang J Mahmood Z Nexus between financial development and CO2 emissions in Saudi Arabia: analyzing the role of globalization Environ Sci Pollut Res 2018 25 28378 28390 10.1007/s11356-018-2876-3 Yang B Jahanger A Khan MA Does the inflow of remittances and energy consumption increase CO2 emissions in the era of globalization? A global perspective Air Qual Atmos Health 2020 13 1313 1328 10.1007/s11869-020-00885-9 Yousuf MU, Abbasi MA, Kashif M, Umair M (2022) Energy, exergy, economic, environmental, energoeconomic, exergoeconomic, and enviroeconomic (7E) analyses of wind farms: a case study of Pakistan. Environ Sci Pollut Res 1-24. 10.1007/s11356-022-20576-5 Zafar MW Saleem MM Destek MA Caglar AE The dynamic linkage between remittances, export diversification, education, renewable energy consumption, economic growth, and CO2 emissions in top remittance-receiving countries Sustain Dev 2022 30 165 175 10.1002/sd.2236 Zhang L Yang B Jahanger A The role of remittance inflow and renewable and non-renewable energy consumption in the environment: accounting ecological footprint indicator for top remittance-receiving countries Environ Sci Pollut Res 2022 29 15915 15930 10.1007/s11356-021-16545-z Zhongming Z, Wei L (2020) World’s governments must wind down fossil fuel production by 6% per year to limit catastrophic warming. Global S&T Development Trend Analysis Platform of Resources and Environment. http://119.78.100.173/C666/handle/2XK7JSWQ/306243. Accessed 8 Mar 2022 Ziaei SM Effects of financial development indicators on energy consumption and CO2 emission of European, East Asian and Oceania countries Renew Sustain Energy Rev 2015 42 752 759 10.1016/j.rser.2014.10.085
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==== Front Drugs Drugs Drugs 0012-6667 1179-1950 Springer International Publishing Cham 36508116 1803 10.1007/s40265-022-01803-2 Current Opinion Should We Interfere with the Interleukin-6 Receptor During COVID-19: What Do We Know So Far? http://orcid.org/0000-0003-0932-6739 Plocque Alexia 1 http://orcid.org/0000-0001-8612-8731 Mitri Christie 2 Lefèvre Charlène 1 http://orcid.org/0000-0003-1997-2400 Tabary Olivier 2 http://orcid.org/0000-0001-9165-4701 Touqui Lhousseine 345 http://orcid.org/0000-0002-7323-0742 Philippart Francois [email protected] 16 1 grid.414363.7 0000 0001 0274 7763 Medical and Surgical Intensive Care Unit, Groupe Hospitalier Paris Saint Joseph, Paris, France 2 grid.418241.a 0000 0000 9373 1902 Centre de Recherche Saint-Antoine, CRSA, Sorbonne Université, Inserm, 75012 Paris, France 3 grid.7429.8 0000000121866389 INSERM U938 Unit, St. Antoine Research Centre, Sorbona University, Paris, France 4 grid.428999.7 0000 0001 2353 6535 Mucoviscidosis and Pulmonary Disease Units, Institute Pasteur, Paris, France 5 grid.428999.7 0000 0001 2353 6535 Cystic fibrosis and Bronchial diseases team-INSERM U938, Institut Pasteur, Paris, France 6 grid.460789.4 0000 0004 4910 6535 Endotoxins, Structures and Host Response, Department of Microbiology, Institute for Integrative Biology of the Cell, UMR 9891 CNRS-CEA-Paris Saclay University, 98190 Gif-sur-Yvette, France 12 12 2022 136 27 10 2022 © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Severe manifestations of COVID-19 consist of acute respiratory distress syndrome due to an initially local reaction leading to a systemic inflammatory response that results in hypoxia. Many therapeutic approaches have been attempted to reduce the clinical consequences of an excessive immune response to viral infection. To date, systemic corticosteroid therapy is still the most effective intervention. More recently, new hope has emerged with the use of interleukin (IL)-6 receptor inhibitors (tocilizumab and sarilumab). However, the great heterogeneity of the methodology and results of published studies obfuscate the true value of this treatment, leading to a confusing synthesis in recent meta-analyses, and the persistence of doubts in terms of patient groups and the appropriate time to treat. Moreover, their effects on the anti-infectious or pro-healing response are still poorly studied. This review aims to clarify the potential role of IL-6 receptor inhibitors in the treatment of severe forms of COVID-19. ==== Body pmcKey Points The dysregulation of inflammatory response associated with COVID-19 requiring hospitalization has been suggested to be a potential target of monoclonal antibodies. Tocilizumab and sarilumab are monoclonal humanized antibodies directed against the IL-6 receptor. During severe COVID-19, tocilizumab appears to have demonstrated efficacy by reducing mortality. However, there does not appear to be a class effect as sarilumab failed to demonstrate any similar benefit, although there is a broad discrepancy between studies that is still not explained. No study has focused on the safety of tocilizumab in acute, infection-associated inflammatory response. Introduction Over the past 2 years, several variants of the SARS coronavirus (SARS-CoV2) have been involved in a COVID-19 (Coronavirus Disease 2019) pandemic. COVID-19 is of particular concern due to its high inter-individual transmission [1] and, in certain cases, its association with a significant risk of acute respiratory distress syndrome (ARDS) and ultimately patient death [2–12]. SARS-CoV2 infection can affect many organs but is primarily an infection of the airways, invading the entire respiratory tree [13], from bronchia to alveolar lung parenchyma [14–19]. Transmission of the virus is still a subject of debate. For further information, we recommend that the readers refer to [20–23]. Among the considerable number of inflammatory mediators produced or secreted in the inflammatory response, interleukin-6 (IL-6) has been shown to play a significant role [24], which is likely due to its high levels of expression rather than to the singularity of its action, as all mediators produced are somewhat redundant in their actions [25]. Nonetheless, pro-inflammatory mediators, in particular IL-6, are extensively produced by lung epithelial cells during COVID-19 and notably infect type 2 pneumocytes [26]. Such tropism of SARS-CoV2 for type 2 pneumocytes is considered to be a predominant factor in the intense local production of proinflammatory mediators and may significantly contribute to the subsequent alveolar consequences. The therapeutic management of COVID-19 initially focused on supporting organ failure, essentially oxygen supply in hypoxemic respiratory diseases. The initial lack of specific treatment during this severe viral infection rapidly led to numerous therapeutic attempts to control the virus. Concomitantly, attempts to control the systemic inflammatory response were also undertaken. Among all the tested treatments, corticosteroids were the first to show a potential improvement in survival in more severe situations [27–29]. At the same time, despite their lack of survival benefit in sepsis, the limited information available in ARDS, and the debatable use of single cytokine inhibition during extensive inflammation [30], strategies targeting various cytokine pathways started to be explored in COVID-19 patients. Among them, the most promising results have been achieved with inhibition of the interleukin-6 receptor (IL-6R). Method of Literature Review For this narrative review, we addressed the question of the place of IL-6 receptor inhibitors in COVID-19. Studies were identified by a double search in PubMed/MEDLINE (National Library of Medicine) databases until April 2022 by two independents authors (AP & FP). Randomized studies and meta-analyses were systematically included. The final selection of papers was made by the authors, as a function of their relevance to the addressed question. Additional articles, cited in those already selected, were included if they were considered of major importance in the field. The Interleukin-6 (IL-6) Pathway and the Inhibition of IL-6 Receptors Interleukin-6 is a 26 kD cytokine of 184 amino acids. Initially described as a B-cell stimulator, IL-6 is a pleiotropic cytokine that stimulates immune cell differentiation and proliferation, favors expression of IL-17-producing CD4+ T helper lymphocytes (Th17), and inhibits of the generation of regulatory T cells (Treg). Aside from having a major quantitative role in chronic and acute inflammation, IL-6 is involved in endothelial activation, favoring vascular leakage, and takes part in the regulation of metabolism and tissue regeneration [31]. Mainly expressed by monocytes and macrophages in response to microbe (and damage)-associated molecular patterns, IL-6 can also be produced by B and T cells during viral infection [32]. Moreover, its expression is upregulated by a positive feedback favored by degradation and reduced expression of Regnase. Such amplification may contribute to the high levels of IL-6 measured in septic patients. Three main interactions of IL-6 with the IL-6R have been described. IL-6 can directly interact with the membrane-bound IL-6R of the receptor allowing interaction with a second ubiquitously expressed transmembrane protein: pg130 (classic signaling). Signal transduction can also be obtained by the binding of IL-6 to the soluble IL-6R (trans-signaling). Finally, gp130 activation has been described, in T cells interacting with specialized dendritic cells (DC). In this situation, DC membrane-bound IL-6R associated with IL-6 activates the gp130 pathway allowing the priming of TH17 cells [32, 33]. Transduction of the IL-6 signal is then primarily mediated by the gp130-JAK-STAT3 (signal transducer and activator of transcription 3) and gp130-JAK-SHP-2 (SH2-domain containing protein tyrosine phosphatase-2) pathways. Several inhibitors of the IL-6 pathway have been developed to reduce the consequences of chronic IL-6 stimulation [33], including antibodies directed against the IL-6R, which have a central clinical role in the treatment of chronic inflammation diseases [31, 33]. Among them are tocilizumab, a humanized IgG1, and sarilumab, a human IgG1 antibody, directed against the IL-6R [31]. They bind directly at the IL-6 binding epitope (tryptophan-serine-X-tryptophan-serine domain), allowing inhibition of the three types of signal transduction [32, 33]. Initially developed to treat patients with systemic chronic inflammatory diseases, such as rheumatoid arthritis, juvenile idiopathic arthritis, Castleman disease, and Takayasu arteritis, anti-IL-6R antibodies have been more recently suggested for the treatment of cytokine release syndrome associated with the use of chimeric antigen receptor T (CAR-T) cells [33–37]. During COVID-19, the intensity of the inflammatory response has been shown to correlate with the severity of acute respiratory distress. As a major quantitative mediator expressed in response to cells of innate immunity, IL-6 is strongly associated with hypoxemia [38, 39]. Inhibition of the IL-6R and IL-6 pathway could mitigate the initial inflammatory response, reduce capillary permeability, and thus limit respiratory failure. Moreover, by targeting a specific proinflammatory mediator, these biologic agents may allow the control of inflammation with a less severe immunosuppression than with usual immunosuppressive treatments [33]. Another element that may also take part in the observed effect of IL-6R blockade by specific antibodies: the redundancy of IL-6 family which may blunt the potential efficiency of IL-6 inhibition by favoring the role of immunomodulatory cytokines from the IL-6 superfamily that transduce their signal through gp130. IL-27 may contribute to reduce Th17 differentiation and promote Tregs production [40, 41]. However these elements need to be confirmed in COVID-19 as IL-27 has also been shown to be involved in the promotion of proinflammatory responses and the Th1 differentiation of T cells [41]. To date, the hypothetical rationale of IL-6R blockade in the specific situation of severe SARS-CoV2 infection is still poorly supported by experimental data. Clinical results are also conflicting. Many uncertainties remain concerning the importance of the intensity of IL-6 production, the correlation with clinical severity, and the timing of the administration of anti-IL-6R inhibitors or local pulmonary bioavailability of these monoclonal antibodies. Finally, the beneficial effect of tocilizumab appears to depend on its concomitant use with corticosteroids [42, 43], as higher doses of dexamethasone are associated with clinical improvement [44, 45] and the doses of corticosteroids used are much lower than those used in bolus therapy for certain immunological diseases [35–37, 46]. Given the cost, the uncertainty of pharmacodynamics during COVID-19 (no pharmacodynamics class effect), and the potential threat of modification of the immune response modification by inhibiting inflammation, the appropriateness of IL-6 pathway inhibitors needs to be closely analyzed. Role of IL-6 Receptor Inhibitors: Uncertainty due to Circulating IL-6 Concentration Clinical studies have broadly confirmed the presence of circulating IL-6 in the blood of moderate and severe COVID-19 patients (see Tables 1 and 2). However, during COVID-19, the initial insult takes place in the lung parenchyma rather than in the blood [13–19, 47]. Therefore, the immunologic response develops mainly in the lungs, especially the alveoli, with cytokine concentrations observed in the circulation being only an approximative marker of the intensity of the proinflammatory response [24]. Numerous studies in patients with disease of varying severity have found consistent values of serum IL-6 levels from 5.0 to approximately 240 pg/mL (see Tables 1 and 2), partially depending on the degree of severity [11, 25, 39, 42, 43, 47–58]. In mild and moderate COVID-19, requiring hospitalization but not intensive care or resuscitation, circulating IL-6 concentrations are particularly low, around 5 pg/mL [42, 59]. In severe COVID-19, requiring mechanical ventilation, IL-6 serum concentrations may reach 125 pg/mL [47, 57, 59–61]. Such IL-6 serum concentration are similar to those measured during influenza, especially H3N2 (30 pg/mL) [62], H1N1 (approximately 150 pg/mL in mechanically ventilated patients) [63], H5N1 [64], and H7N9 (30–200 pg/mL) [62, 64–67], exceptionally reaching 500 pg/mL in the most severe case [66]. In all these situations, serum IL-6 values are much lower than those observed during classical ARDS/sepsis, in which concentrations may reach more than 2500 pg/mL, and cytokine release syndrome (CRS) associated with CAR-T cell activation, with 10-fold higher serum IL-6 concentrations measured [16, 25, 30, 34, 68–77]. Such observations raise questions about the importance of the systemic proinflammatory response during severe COVID-19 [69, 72, 74, 78–80]. These data also raise questions about whether tocilizumab is useful in the early phase of mild to moderate disease. Remarkably, studies demonstrating a potential benefit of tocilizumab in severe COVID-19 (with a PaO2/FiO2 around 150) found higher initial circulating IL-6 concentrations (144.1–238.3 pg/mL) [56], confirming the potential link between the systemic component of the response and the potential benefit of the treatment. In conclusion, the systemic magnitude of inflammatory mediator expression thus appears to play a considerable role in the assessment of severity and consequently in the therapeutic management of severe COVID-19 [16, 17].Table 1 Serum IL-6 levels during COVID-19 in cohort and retrospective studies Serum concentration of interleukin-6 (ng/ml) Ref. Prognostic Severity Sex Whole population Survival Death Asymptomatic Mild Moderate Severe Critical M F [130] – – 6.44 (2.34–13.94) 15.3 (7.70–22.64) 10.79 (6.93–16.35) 16.09 (8.08–26.47) 21.84 (19.88–32.69) 18.16 (9.16–31.83) 12.67 (6.93–17.09) - [49] 13.3 (3.9–41.1) 25.2 (9.5–54.5) [11] 6.05 (5.12–6.99) 10.07 (7.36–14.80) – – – – Without ARDS: 6.29 (5.36–7.83) with ARDS: 7.39 (5.63–10.89) – – 6.98 (5.46–9.02) [50] – – – – – – – – – 7.9 (6.1–10.6) [47] – – – – – 15.3 (6.2–29.5) 41.5 (24.8–114.2) – – 26.6 (7.5–43.4) [51] – – – – about 5 About 12 about. 15 – – – [59] from 6.41 (2.17) to 159.2 (268.95) from 10.96 (5.25) to 2291.46 (568.27) - - - from 5.0 (3.64) to 51.7 (65.6)) from 7.4 (3.64) to 103.9 (43.6) – – – [39] - - - - 10.4(3.8–31.0) 5.8 (3.1–16.9) 64.0 (25.6–111.9) – – – [60] - - - - About 100 – – – [116] - - Non severe: 15·67 +/– 6, 34 Severe: 19.0 +/– 7.74 - - - ARDS acute respiratory distress syndrome Table 2 Serum IL-6 levels during COVID-19 in clinical trials considering tocilizumab and sarilumab Article Serum concentration of interleukin-6 (ng/ml) First author or study group year Réf. Placebo / standard of care Active Tocilizumab Veiga VC 2021 [96] 208 (586) 192 (313) RECOVERY 2021 [127] - - Stone JH 2020 [43] 25.4 (14.6–40.3) 23.6 (14.0–49.9) Salvarani C 2020 [42] 34.3 (19.0–59.3) 50.4 (28.3–93.2) Lescure FX 2021 [52] 13.0 (3.6–23.5) Two groups : 11.6 (5.1–23.5) 12.7 (5.5–26.5) Soin AS 2021 [53] 85.2 (232.2) 115.5 (245.6) Guaraldi G 2020 [56] 144.1 (41.1–385.8) SC : 90.2 (86.6–401.0) IV : 238.3 -140.2–731.9) Vazquez Guillamet MC 2021 [57] 48 (26–512.5) 66.8 (55–739.7) Sarilumab SARICORa 2021 [120] 8 (38-80) S200 mg: 59 (43-88) S400 mg: 70 (43-127) SARTRE 2021 [58] 13.25 [3.85–43.35] 19.20 [6.00–46.00] Sivapalasingam S 2022 [61] “severe patients” (median; min- max) 61.5 (9.10–571.26) “critical patients” 85.6 (9.1-2324.8) “severe patients” S200: 53.3 (9.1–1713.2) S400: 58.2 (9.10–2771.4) “critical patients” S200: 116.1 (6.82–6531.58) S400: 125.9 (9.1–21545.3) aPatients selected to have IL-6 ≥ 40 ng/ml or elevated S200 Sarilumab: 200 mg, S400: Sarilumab: 400 mg, IV intravenous administration, SC subcutaneous administration Role of IL-6 Receptor Inhibitors: Uncertainty of Clinical Severity and IL-6 Concentration It is well known that the wide variability in the individual inflammatory response during COVID-19 is responsible for a significant part of the differences in the responses to therapeutic interventions involving specific cytokine inhibitors [16, 81]. Although an early large study [82] found a correlation between the circulating IL-6 levels and mortality, the substantial variability in values, sometimes involving low levels, cast doubt on these conclusions. Initially, blood concentrations of major cytokines such as IL-6 were considered not to correlate with the severity of clinical damage in COVID-19 [24, 25, 83–85] and to be weakly associated with viral proliferation [39, 86]. A better, but still partial correlation (intensive care unit [ICU] vs non-ICU patients) was observed early in IL-6 expression in blood leukocytes (monocytes and CD4+ lymphocytes) [87]. More recent data have tended to demonstrate a better correlation [88] but a potential publication bias was highlighted in a recent meta-analysis [89]. More than a single measure, the evolution of cytokine expression over time appears to be a potential prognostic predictor [90]. The lack of a strong association between the blood concentration of IL-6 and severity may be partly due to the absence of a correlation noted between the local, alveolar, and systemic inflammatory response, in particular, for IL-6 [91]. The lack of a strong association between IL-6 production and clinical outcomes may be partly due to possible immune dysregulation. A major study conducted by Giamarellos-Bourboulis et al. [92] underlined the correlation between intermediate severity, the presence of immune dysregulation, notably defined by HLA-DR expression, and patients with macrophage activation syndrome (highlighted by increased serum ferritin concentration) during COVID-19. These elements, however, show no clear clinical correlation with respiratory severity or the need for mechanical assistance. This observation raises the importance of the inflammatory response kinetics, the clinical consequences of initial proinflammatory mediator release being observed during the compensatory anti-inflammatory response syndrome. On the other hand, the evolution of IL-6 levels during the disease, independently from the use of IL-6 pathway inhibitors, may be of greater prognostic value for survival [57]. A similar variation has been described for ARDS of other origins, leading to the distinction of two groups: hyperinflammatory and hypoinflammatory ARDS patterns [70, 79]. This observation can also be viewed from another perspective in which the increased IL-6 concentration may be, at least in part, due to a compensatory response, in which IL-6 seeks to supplant the failure of other inflammatory pathways [93]. Finally, it would be wrong to assume that the inhibition of IL-6 would be linearly associated with improved survival because the inflammatory reaction does not depend on a single inflammatory mediator [19]. Finally, another important aspect in this field is related to the contrasting functions of IL-6. IL-6 promotes the reduction of type I/III interferon production. Similarly, serum IL-6 concentration correlates with lymphocyte exhaustion (marked by PD-1 or Tim3 expression) [94] and inversely correlates with NK cell count [18]. Role of IL-6 Receptor Inhibitors: Uncertainty of Administration Timing Shock (due to endothelial hyperpermeability, resulting in reduced intravascular volume) is essential to the decision to introduce tocilizumab during the CRS [80, 95]. Information on hemodynamic failure is lacking in the vast majority of COVID-19 cases, including its critical forms [27, 42, 43, 52–54, 96–100]. During COVID-19, patients who develop a disproportionate inflammatory response, marked by high blood levels of proinflammatory cytokines, may benefit from a reduction in the intensity of the immune response [15, 71]. Therefore, tocilizumab may have a true therapeutic effect in this context, but the targeted patients, especially in terms of severity, remain very poorly defined [16, 24], and broad use is unquestionably expensive and irrelevant [101]. Role of IL-6 Receptor Inhibitors: Uncertainty About the Lung Bioavailability of Tocilizumab The easier accessibility of blood samples has led to the identification of proinflammatory mediators in this compartment [24, 42, 43, 47, 51–54, 59, 71, 77, 79, 83, 84], supporting the perception of an initial systemic response [102, 103]. The bioavailability and duration of efficacy of tocilizumab in the vascular compartment (12 days–3 weeks) [103, 104] appear to be satisfactory in the context of systemic cytokine release. However, as mentioned above, the clinical evolution during COVID-19 is centered on a local and regional bronchopulmonary inflammatory response [14–19, 24, 103, 105–107]. The clinical evolution of COVID-19 is underlined by a major alteration of hematosis during the acute phase, followed by destruction and sustained pathological remodeling of the pulmonary parenchyma. A reduction of parenchymal inflammation appears to be the most crucial parameter to consider for the prevention of severe forms and even reduction of the mortality linked to viral infection. The lack of information on the bioavailability of tocilizumab in the alveolar fluid and the higher pulmonary concentration of IL-8 when patients are treated with tocilizumab rather than with corticosteroids [106] raises doubts about the value of the local use of tocilizumab in the pulmonary parenchyma. Nonetheless, tocilizumab may have a local vascular rather than an alveolar effect. Salvati et al. have demonstrated an improvement in gas exchange, a decrease in alveolo-arterial gradient and a reduction in the radiographic score for patients who received tocilizumab [108]. No definite explanation is currently available, but the improvement in endothelial dysfunction, including permeability and the activation of coagulation, mentioned by the authors [108], may represent a relevant avenue for future investigations [109]. Relevance of the Early Administration of Tocilizumab During COVID-19 Initial Publications on the Administration of Tocilizumab During COVID-19 As early as 2020, the first cohort studies highlighting the potential benefit of tocilizumab included ICU patients [110, 111]. Similarly, there appeared to be a benefit in situations of major systemic inflammatory response, characterized in particular by the severity of pulmonary involvement and the presence of other organ failures, notably the kidney or bone marrow [24, 43, 111]. In a multicenter retrospective Italian cohort of 544 patients, mortality appeared to be reduced by tocilizumab administration, but the difference only occurred for patients with a PaO2/FiO2 ratio < 150 [56]. However, the benefit appeared to be mitigated if tocilizumab was administered too late during mechanical ventilation: this drug was able to reduce 28-day mortality by 4-fold (8% vs 36%; p = 0.001; HR 0.54, 95% CI 0.29–1.00) when administered during the first 48 hours of mechanical ventilation [110]. Similar results were observed in a multicenter study (23 centers, 118 patients) treated within the first 24 hours of invasive ventilation [112]. Conversely, administration beyond this period was associated with increased mortality (OR: 3.513 [1.15–11.97]; p = 0.003) [112]. Comparative Clinical Trials Non-Randomized Comparative Studies Many articles have been published about the potential value of tocilizumab during COVID-19. However, most of these studies were only retrospective non-randomized comparisons [56, 99, 110–117]. In these publications, survival was not systematically improved [57, 110–114, 118], particularly that of ventilated patients [112, 118]. Other studies even reported an increase in mortality [112, 119]. At the time the patients in these retrospective studies were treated, the importance of corticosteroids was just beginning to be recognized [145], and the same is true for clinical improvement and reduction in hospital stay or risk of intensive care admission [143]. There have been rapid changes in the organization of the research plan, allowing the implementation of randomized studies that have provided new information (Table 3). However, the persistence of high heterogeneity in study design has made interpretation difficult.Table 3 Randomized studies of tocilizumab and sarilumab in COVID-19 Study Oxygen therapy Intervention Benefit Criteria Ref Number of days from onset of symptoms Number of patients Oxygen HFNO NIV IMV Anti-IL-6R Corticosteroids Yes/No Mortality IMV requirement Improvement of WHO-CPS score Other [121] – 68 vs 80 100% – – – Sarilumab 7% (usual care) 15% (sarilumab) No On day 14: - mechanical ventialtion or death: 31% (sarilumab) and 22% (usual care) - Mortality (day 14): 9% vs 11% - Mortality (day 28): 12% vs 18% - Mortality (day 90) : 15% vs 21% On day 4 : worsening of the score for 26% in both groups * On day 14 : worsening requiring HFNO or mechanical ventilation or death : 37% (sarilumab) and 34%(usual care) [54] 12.1 +/–6.6 11.4+/–6.9 294 vs 144 26.5% vs 30.6% 32.0% vs 27.1% 15.3% vs 10.4% Tocilizumab 19.4% vs 28.5% No At D28 : 19.7% vs 19.4% 27.9% vs 36.7% - *Median value for clinical status on 7-category ordinal scale : 1.0 (1.0 to 1.0) vs 2.0 (1.0 to 4.0) - *Incidence of ICU admission : 21.3% vs 35.9% [120] 9 (7-11) 9 (7-12) 9 (8-11) 39 vs 37 vs 39 100% – – – Sarilumab Dexamethasone: 54% vs 46% vs 56% Methylprednisolone: 34% vs 43% vs 36% No D28 : 8% vs 11% vs 0% D28: 10% vs 16% vs 8% D28: 88% vs 84% vs 94% Discharge from hospital: 84% vs 84% vs 92% [58] 10.0 (8.0, 12.0) vs 9.0 (8.0, 11.0) 99 vs 102 100% (NB: high oxygen requirement, including face mask, were excluded) – – – Sarilumab Methylprednisolone : 100% (standard of care in both group) for at least 3 days No D15: 1.96% vs 0.0% D28: 1.96% vs 2.02% - - *HFNO or NIV or CPAP: - D15: 39.22% vs 42.42% - D28: 39.22% vs 42.42% *ICU admission: - D15: 9.8% vs 7.07% - D28: 9.8% vs 7.07% *Median time to hospital discharge: 7 [6–8] [125] 8.8 +/– 4.8 vs 8.9 +/– 4.7 T+R: 430 P+R: 210 T+R: 6.7% P+R: 6.2% T+R: 78.1% P+R: 83.3% T+R: 9.1% P+R: 4.3% (ECMO : 6.0 % and 6.2%) Tocilizumab T+R: 83.2% P+R: 86.4% No D28: 19.5% vs 18.1% D60: 22.6% vs 25.7% D28: Mechanical ventilation or death. P+R: 29.0% T+R: 28.6% Clinical status at day 14 assessed on the 7-category scale: NS Time to hospital discharge or “ready for discharge”: 14 [12–15] vs 14 [11–16] [98] - T: 353 S; 48 C: 402 T: 1 S: 0 C: 2 T: 101 S: 17 C:110 T: 147 S: 23 C:169 T: 104 S: 8 C:121 Tocilizumab or Sarilumab T: 50 S: 0 C: 52 Yes - Hospital: T: 28% S: 22% C: 36% Pooled anti-IL-6R: 27% Survival OR: 1.64 (1.14 – 2.35) - - Organ support-free days (median [IQR]): T: 10 [−1 to 16] S: 11 [0 to 16] C: 0 [−1 to 15] [43] T: 9.0 [6.0–13.0] P: 10.0 [7.0–13.0] T: 161 P: 82 T: 133 P: 61 T: 5 P: 5 T: 0 P: 1 Tocilizumab – No T: 5.6% P: 3.6% T: 6.8% P: 9.7% T: 91.3% P: 87.8% - [97] T: 8.0 [0.0 – 31.0] P: 8.0 [0.0 – 36.0] T: 249 P: 128 T: 161 P: 81 T: 64 P: 36 None Tocilizumab T: 55.4% P: 67.2% Yes T: 10.4% P: 8.6% mechanical ventilation or death: T: 12.0% P: 19.3% (p = 0.04) D28: T: 88% P: 84% - [42] T: 7.0 [4.0 -11.0] C: 8.0 [6.0 -11.0] T: 60 C: 66 T: 100% C: 100% T: 0% C: 0% T: 0% C: 0% Tocilizumab T: 1.7% C: 6.0% No D30: T: 3.3% C: 1.6% - - Admission to the ICU: T: 10.0% C: 7.9% [127] T: 9 [7–13] C: 10 [7–14] T: 2022 C: 2094 T: 46% C: 45% T: 41% C: 41% T: 13% C: 14% Tocilizumab Systemic corticosteroids: T: 82% C: 82% Dexamethasone: T: 2% C: 2% Yes D28: T: 31% C: 35% (p= 0.0028) T: 35% C: 42% - - [53] - T: 91 P: 88 T: 81 C: 80 T: 28 C: 20 T: 5 C: 4 Tocilizumab T: 91% C: 91% No D28: T: 12% C: 17% - - -Ventilator-free days T: 24.3+/– 9.2 C: 23.2 +/– 10.6 - ICU admission: T: 78% C: 73% [96] T: 10.0 +/–3.1 C: 9.5 +/– 3.0 T: 65 C: 64 T: 39 C: 28 T: 15 C: 26 T: 11 C: 10 Tocilizumab T: 45 C: 47 No - D28: T: 21% C: 9% - Hospital: T: 21% C: 9% T: 7 C: 11 - Ventilator-free days: T: 19.4 +/–12.0 C: 20.5 +/–10.8 [100] T: 10 [7 . 13] C: 10 [8–13] T: 63 C: 67 T: 0% C: 0% T: 0% C: 0% T: 0% C: 0% T: 100% C: 100% Tocilizumab Corticosteroids: - Prior randomization: T: 16% C: 18% - After randomization: T: 30% C: 55% Dexamethasone: - Prior randomization: T: 6% C: 7% - After randomization: T: 14% C: 28% No D28: T: 11% C: 12% Median score at D14: T: 2 [2–5] C: 4 [2–7] - [61] “median duration of illness” in “critical stratum” : 9.0 days Phase 2: P: 90 vs S200: 187 Vs S400: 180 Phase 3 (cohort 1) : P : 294 vs S200: 489 vs S400: 582; Phase 3 (cohort 2) : P : 6 vs S800 : 2 P: 95 S200: 190 S400: 188 “critical patients” (oxygen by nonrebreather mask or HFNO, NIV or IMV): Critical receiving MV: P: 80 S200: 164 S400: 179 Critical not receiving MV: P: 134 S200: 171 S400: 244 Sarilumab “severe patients”: P: 27.4% S200: 27.9% S400: 26.6% “critical patients” Critical receiving MV: P: 27.5% S200: 22.6% S400: 27.9% Critical not receiving MV: P: 35.1% S200: 33.3% S400: 35.7% No In patients receiving MV at baseline: D29 mortality: P: 41.9% S400: 36.4% D60: P: 51.6% S400: 39.4% Risk difference: -5.5% [-20.2, 8.7] Critical patient not receiving MV: D29 mortality: P: 15.7% S400: 26.4% D60: P: 25.0% S400: 29.9% Risk difference: +10.7% [.9, 19.3] - On day 22: Severe patients: P: 92.0% S200: 92.0% S400: 68.6% Critical patients: P:34.1% S200: 47.9% S400: 60.2% MSOD/IC: P: 47.6% S200: 39.5% S400: 43.9% [122] Tocilizumab part: T: 11 (9–15) C: 11 (9–14) Sarilumab part: S: 11 (9–15) C: 11 (8–21) Tocilizumab part: T: 51 C: 46 Sarilumab part: S: 50 C: 41 WHO-CPS at least 5 Tocilizumab And Sarilumab - Tocilizumab part: Corticosteroids: Dexamethasone: - Sarilumab part: Corticosteroids: Dexamethasone: 0% No Risk of death up to D90: -Tocilizumab part: C: 30% vs T: 24%; HR 0.67 [0.30 to 1.49] -Sarilumab: C: 39% vs S: 29% ; HR 0.74 ([0.35 to 1.58] D14 IMV or NIV or ONHD weaning: Tocilizumab part: T: 47% C: 42% Sarilumab part: S: 38% C: 33% ---- D28 VFD: Tocilizumab part: T: 9.8 (9.5) C: 7.2 (9.4) Sarilumab part: S: 7.5 (9.5) C: 4.6 (7.6) Decrease WHO-CPS at D4: Tocilizumab part: T:28.6% C: 30.2% Sarilumab part: S: 29.2% C: 21.2% No need NIV or IMV at D14: Tocilizumab part: C: 42% vs T: 47% Sarilumab part: C: 338% vs S: 33% [126] DX: 9 [7−11] DX+T: 9 [7−11] DX: 226 DX+T: 224 100% 0% Tocilizumab 100% No - D14: DX: 5% DX+T: 5% - D28: DX: 8% DX+T:7% - D60: DX: 10% DX+T: 8% - D90: DX: 11% DX+T: 8% D14 IMV or death: DX: 14% DX+T: 12% Independency from oxygen at: - D14: DX :62% DX+T: 71% - D28: DX: 72% DX+T: 82% Bayesian analysis: DX+T has a 72.8% chance of being superior to DX alone C control group / Standard care group / usual care group, CPAP continuous positive airway pressure, DX Dexamethasone, DX+T Dexamethasone and Tocilizumab, HFNO High flow oxygen, IL-6R Interleukin-6 receptor, IMV invasive mechanical ventilation, MSOD/IC multi-system organ dysfunction/immunocompromised, MV Mechanical ventilation, NIV Noninvasive ventilation, NS non-significant, P Placebo, P+R Placebo and Remdesivir, S Sarilumab group, S200 Sarilumab (200 mg) group, S400 Sarilumab (400 mg) group, S800 Sarilumab (800 mg) group, T Tocilizumab group, T+R: Tocilizumab and Remdesivir, VFD: Ventilator-free days, Positive results are indicated in bold WHO score: 1, Discharged (or “ready for discharge”). 2, Non-ICU hospital ward (or “ready for hospital ward”) not requiring supplemental oxygen. 3, Non-ICU hospital ward (or “ready for hospital ward”) requiring supplemental oxygen. 4, ICU or non-ICU hospital ward, requiring noninvasive ventilation or high-flow oxygen. 5, ICU, requiring intubation and mechanical ventilation. 6, ICU, requiring extracorporeal membrane oxygenation or mechanical ventilation and additional organ support. 7, Death Randomized Studies: Raw Results Two IL-6 receptor inhibitors were randomized: tocilizumab and sarilumab. All studies were performed used the intravenous rather than subcutaneous form of these inhibitors. Blinded studies with sarilumab (200 or 400 mg once) found no improvement in survival with this treatment [52, 58, 61, 120]. An open-label randomized trial, including 115 patients mostly requiring oxygen supply, using two different doses of sarilumab (200 or 400 mg once), also found no significant survival benefit or modification in the initial clinical course [120]. Another prospective, randomized, multicentric study involving 201 patients did not show a significant benefit in sarilumab administration during an ‘unfavorable’ respiratory course, or against the risk of ICU admission or associated death [58]. Similarly a recent phase II/III randomized trial that included ‘critical patients’ (defined by low flow oxygen requirement by mask, or high flow nasal oxygen, or mechanical ventilation) did not find any improvement in survival, regardless of the dose of sarilumab (200 mg, 400 mg or 800 mg) [61]. These results are in contrast with those of the REMAP-CAP, which tested sarilumab or tocilizumab and showed a potential benefit [98]. More recently, two French open-label randomized Bayesian studies from the CORIMMUNO-19 research group did not show any survival benefit for moderate [121] or severe patients [122]. Other studies (ClinicalTrials.gov identifiers: NCT044327388, NTC044315298) are still underway and will most likely show a more specific potential benefit in the therapeutic arsenal. In mild forms of the disease, tocilizumab does not improve weaning from oxygen therapy (either at day 14 [43, 100] or at day 28 [43]) in the overall population of hypoxemic patients. The absence of significant renal, hemodynamic, or respiratory failure (often assessed by the PaO2/FiO2 ratio or the need for mechanical ventilation) appears to be associated with the absence of a benefit [42, 43, 99]. However, a post-hoc analysis of the study by Soin et al. suggests the possibility of a survival benefit at day 28 for initially severe patients [53]. Numerous studies have highlighted the probable lack of benefit of tocilizumab in mild forms of COVID-19 [42, 43, 53, 54, 97, 122–124] and its potential value for patients with more severe forms [97]. In more severe disease, the administration of tocilizumab may reduce the risk of mechanical ventilation or transfer to the ICU (both on day 14 [43, 100] and day 28 [43]). However, these results were not confirmed by other studies that included similar patients and assessed the deterioration of their health at the same time points [42, 43, 53, 96, 97, 100, 122, 125]. The absence of a beneficial effect was even observed up to day 60 [97, 125] and day 90 [126] in other studies. The duration of mechanical ventilation could also be reduced, but the low proportion of ventilated patients in the studies makes it difficult to draw any definitive conclusion, mainly because the duration of ventilation has not been reported anywhere else [126]. A recent large, double-blind, placebo-controlled, multicenter study comparing the combination of remdesivir (a selective inhibitor of viral RNA-dependent RNA polymerase) with or without tocilizumab found no difference in mortality, length of hospital stay, or avoidance of invasive mechanical ventilation [125]. Adding remdesivir raises the question of the potential benefit of tocilizumab for patients treated with remdesivir, but tends to demonstrate the absence of the supposed additive or synergistic effect as observed with corticosteroids [125]. The authors also emphasized the imbalance between the groups despite randomization in terms of the requirement for mechanical ventilation or corticosteroid administration at the date of inclusion [125]. However, these parameters probably do not explain the absence of the expected effect. Two studies (RECOVERY and REMAP-CAP) have reported a reduction in mortality when patients were treated with IL-6 inhibitors. RECOVERY Study In the RECOVERY study [127], mortality at day 28 was 31% (621 patients) in the treated group and 35% (729 patients) in the group without specific treatment (RR: 0.85 [0.76–0.94]; p = 0.0028). The risk of developing renal failure requiring dialysis also appears to have been reduced [127]. However, there are many limitations to consider. The difference in all-cause mortality disappeared when focusing on COVID-19-related deaths and only seemed to exist in association with deaths from unknown causes. Another critical element is observed: the survival benefit appeared to only be present for patients receiving concomitant corticosteroid therapy (mortality: 29% vs 35%; RR: 0.79 [0.70–0.89]) [155]. This is particularly important given that 17% of patients did not receive study treatment in the intervention group [127]. The observed difference for the secondary need for invasive mechanical ventilation (265/1754 [15%] vs 343/1800 [19%]; RR: 0.79 [0.69–0.92]; p = 0.0019), the observed difference disappeared when focusing on the population not receiving any ventilation at the time of randomization [127]. This suggests a greater benefit for initially more severe patients, in particular those on non-invasive ventilation or high-flow nasal oxygen therapy. Conversely, no improvement in the duration of mechanical ventilation was observed when tocilizumab was administered to patients already intubated at the time of randomization [127]. Too-high severity of the disease eliminated any benefit, confirming what was previously observed by Rosas et al. [54]. These elements better define a population of interest for the administration of tocilizumab: patients with severe (non-invasive ventilation or high-flow nasal oxygen therapy) but not critical (invasive ventilation). Interestingly, in their subgroup analysis, the RECOVERY team did not find any benefit of tocilizumab in women, with the full benefit being present in men (an effect also observed for hospital discharge). Such information is of paramount interest given the well-known difference in inflammatory response according to sex [128–131]. Estrogens are known to be capable of modulating inflammatory response without compromising the anti-infectious properties of leukocytes. During COVID-19, androgens are responsible for an increased expression of transmembrane serine protease 2 (TMPRSS2), and may favor the infection of cells, especially those in the lung [132]. On the other hand, protective interferon-α expression is favored by estrogens and could ease the control of viral infection [128, 132]. Moreover, a decrease in estradiol has been observed in association with IL-6 production [133]. This may partly explain the clinical discrepancy observed in RECOVERY according to sex. REMAP-CAP Study The primary outcome in the REMAP-CAP study was the number of days without the need for respiratory or hemodynamic support for patients initially admitted to the ICU [98]. In-hospital survival was also improved with tocilizumab or sarilumab (72% and 78%, respectively, versus 64%), as was 90-day survival [98]. The frequency of hemodynamic failure (up to 20% need for vasopressor support) and the lack of information related to renal function are two parameters that weaken the importance of the obtained results [98]. Hemodynamic failure during COVID-19 is relatively modest and often delayed whereas renal damage in the most severe forms frequently requires dialysis. In this context, the differences in survival highlight the importance of initial treatment of the actual pathology and confirmation of COVID-19. Of note, the reduction of hemodynamic and respiratory failure by inhibition of IL-6 receptor antagonists appears to occur to a greater extent for patients with the highest levels of C-reactive protein (CRP) [98]. As CRP is produced in response to IL-6 stimulation (linear correlation), the observed benefit of tocilizumab in this study was the greatest in the population with the most intense inflammatory response [98]. However this correlation remains uncertain as many critical patients have relatively low CRP levels, similar to those with severe disease [134]. Conversely, the presence of invasive mechanical ventilation at the time of treatment is not associated with a benefit in the duration of ventilation but could improve patient survival [98]. The post-hoc nature of these various analyses reduces their impact, but their consistency with the other observations is no less attractive. Finally, the Bayesian model used also raises other questions, in particular about the neutrality of the initial hypothesis, as there is no firmly established data in this specific therapeutic area. Increased Mortality: The TOCIBRAS Study In contrast to the other studies, one study was stopped early (129 of the 150 patients initially planned were included) because of excess mortality (17% vs 3% at day 15 and 21% vs 9% at day 28) in the group of patients receiving the study treatment, even though they were less severe at the time of randomization (more oxygen therapy in the tocilizumab group: 60% vs 44% and less noninvasive ventilation or HFNO (high flow nasal oxygen): 23% vs 41%) [96]. Of note, the results of a post-hoc analysis adjusted for baseline levels of respiratory support were consistent with those of the main analysis and did not show a significant effect on the primary outcome. No clear explanation is currently available to explain the observed higher mortality. Considering on the one hand the clinical effect of tocilizumab on CRP and on the other hand the attribution of deaths to acute respiratory failure or multiple organ dysfunction secondary to COVID-19, reported by the authors [96], it is possible that the anti-inflammatory effect was associated with an impairment in the control of viral infection. This may have been exacerbated by the use of high amount of corticosteroids (approximately half of the patients received at least 0.5 mg/kg/d of prednisone equivalent). Randomized Studies: Potential Limitations The first issue concerning the randomized studies is the broad heterogeneity in patient severity, ranging from room-air breathing to ARDS requiring invasive mechanical ventilation and often neuromuscular blocking drugs [42, 43, 52–54, 61, 85, 96–98, 100, 122, 126, 127]. Similarly, the inclusion [42, 52, 54, 61, 96–98, 122, 127] or not [43, 100, 126] of patients on high-flow nasal oxygen therapy (sometimes at very low flow rates [98]) contributes to confusion in interpreting the results. The lack of blinding in many studies [42, 53, 96, 98, 100, 122, 126] is also problematic because knowledge of the treatment and the undisputed favorable bias associated with its use may have considerably modified subsequent therapeutic interventions, including the decision to transfer to the ICU or the type of intensification chosen. The frequency of administration of confounding treatments (antivirals, other cytokine inhibitors, anti-inflammatory drugs, etc.) [42, 43, 52–54, 96–100, 122, 126, 127], which were often distributed heterogeneously during the initial period of the pandemic, has led to more complex analysis even though certain post-hoc analyses do not find any effect of these combined treatments [52]. Positive results obtained with corticosteroids led to their routine administration from June 2020 [27–29]. Their role in tocilizumab [54, 96–98, 100] and sarilumab [52, 98, 121] studies is an additional confounding factor. The potential relationship between the absence of corticosteroids and the poor efficacy of sarilumab has been widely suggested [121]. However, a study investigating the potential benefit of sarilumab and including corticosteroids (methylprednisolone) in the ‘standard of care’ found no difference between the groups regardless of the intensity of the inflammatory response [58]. Regrettably, the study was designed before the efficacy of dexamethasone was demonstrated, allowing neither the possible confirmation of the potentialization of bitherapy nor the effect of methylprednisolone in COVID-19 [58]. Another study has been recently published that included severe patients randomized and stratified on corticosteroid use at the time of inclusion [61]. Although no clinical benefit of sarilumab could be demonstrated, a post-hoc analysis tended to demonstrate a potential benefit of the association for the most severe patients (requiring invasive mechanical ventilation) (HR: 0.49; 95% CI 0.25–0.94) [61]. Unfortunately, the class of corticosteroids was not specified. The use of corticosteroids other than dexamethasone further complicates interpretation of the data [97, 98, 127]. The difference in the frequency of corticosteroid use between groups can be considerable [100]. Analysis of these subgroups sometimes showed lower mortality independent of tocilizumab administration [54]. In the most extensive studies, subgroup analysis of the combination with corticosteroids found a disappearance of the initial effect in the absence of the association with corticosteroids, undermining the main conclusions of the studies [127]. The lack of efficacy of tocilizumab in studies that did not include steroid administration tends to confirm the importance of anti-inflammatory treatment in the potential benefit of IL-6 pathway inhibitors [42, 43, 122, 126]. The inability of tocilizumab to control severe inflammatory responses has already been suggested as an explanation for the current conflicting results in randomized studies [85]. Based on all these data, the addition of tocilizumab may enhance the systemic anti-inflammatory effect of steroid therapy, specifically on the IL-6 pathway [100]. However, a recent study from the CORIMMUNO group did not find any reduction in the requirement for mechanical ventilation or mortality with the association of tocilizumab and dexamethasone among patients with moderate to severe disease [126]. An analysis of the influence of tocilizumab on the inflammatory response is also absent from many studies. Inhibition of the IL-6 pathway may be associated with an increase in circulating concentrations of interferon-α, a lack of reduction in IL-2 and TNF levels, and a reduction in IL-10 expression, both of which suggest a more pronounced proinflammatory response in treated patients than in the group of patients who did not receive the anti-inflammatory drug, even though the greater decrease in CRP confirms the effect of tocilizumab [96]. Variations in efficacy as a function of patient severity highlights the importance of the timing of tocilizumab therapy [135]. Intervention that is received too early may promote the failure of viral control [19, 24, 136, 137]. Conversely, treatment that is received too late is clearly associated with a lack of efficacy. This time frame has been generally unclear in clinical studies [53, 54, 96–100], which took into account the length of hospitalization and not the extent of disease progression. Although the importance of the time between symptom onset and treatment is still uncertain, changes in cytokine expression could explain the variation in efficacy of tocilizumab efficacy. In the RECOVERY study, the mean time was 9 days from the onset of symptoms to the start of hospitalization (2 days) [127], reinforcing the results of the non-randomized study of Gupta et al. in which a benefit was observed when the period between symptom onset and ICU admission was < 3 days [99]. In the REMAP-CAP study, the median length of stay from admission to inclusion in the study was 1.2–1.4 days [98]. Subgroup analysis showed that the effect of the treatment disappeared if the patient was hospitalized beyond 7 days after the onset of clinical symptoms [127]. The hypothesis of an early benefit of tocilizumab in severe disease is indirectly reinforced in the multicenter study of Rosas et al. (COVACTA), in which inclusions were made around the 12th day of symptoms, finding no benefit of tocilizumab [54]. Given all available data, the potential benefit of tocilizumab for severely ill patients would be before day 10, probably as soon as they require high flow oxygen or noninvasive ventilation. Despite the widely used seven-category ordinal scale of clinical status, patient classification in studies remains heterogeneous and contributes to the observed confusion. For example, in different studies, ‘severe’ included those with pulse oxygen saturation (SpO2) >90% in room air [53, 96, 100] or respiratory rates >30 cycles per minute [53, 96, 100], even though they are managed outside of the ICU and require neither mechanical ventilation nor high flow nasal oxygen [43, 96, 97, 100]. In other studies, ward and ICU patients were indiscriminately included [52, 53, 96, 97, 127], limiting the ability to distinguish the appropriate population of therapeutic interest. Similarly, the use of composite outcome criteria is associated with inextricable results [43, 97, 98, 100]. For example, in the study of Salama et al. involving 389 patients admitted to the ward or intensive care unit (14.5% vs 17.2%), the administration of tocilizumab appeared to improve the endpoint of 28-day survival and reduce the need for invasive ventilation or extra-corporeal membrane oxygenation (ECMO), but did not change 28-day mortality, when assessed separately, or mortality at day 60 (11.6% vs 11.8%) [97]. More disturbing is the higher occurrence of death without mechanical ventilation in the placebo group, with no explanation for the absence of therapeutic intensification [97]. Finally, the fact that there was no difference in length of stay or the rate of decrease in clinical severity (assessed by the WHO 7-point scale) argues against the actual effectiveness of the treatment [97]. Finally, the absence of a ‘class effect’ highlighted by the failure of sarilumab studies to demonstrate a beneficial effect is a significant issue. Sarilumab is an undoubtedly effective IL-6 receptor inhibitor with a 20-fold higher affinity for the IL-6 receptor alpha chain than tocilizumab, and is broadly used [58, 138]. The difference in IL-6R occupancy between sarilumab and tocilizumab [138] may contribute to the observed discrepancy in the clinical results. However, the higher affinity and the prolonged efficiency of sarilumab can be expected to be associated with a better clinical efficiency. There are many other possible explanations for the failure to demonstrate a clinical effect in this particular pattern of acute viral infection. However, such limitations should be the same for tocilizumab. One hypothesis is that there is a possible specific inhibitor effect of tocilizumab that involves the interaction of other cytokine receptors, such as IL-27. Recent Meta-Analysis on IL-6 Receptor Inhibition During COVID-19 The recent original RCT studies have been meta-analyzed, alone or in association with previous cohort studies, providing heterogeneous results (cf. Table 4). Currently, sarilumab does not appear to be a relevant therapeutic option during COVID-19 [139, 140], even if a class effect was used in one meta-analysis [141].Table 4 Meta analyses of trials of tocilizumab and sarilumab in COVID-19 Study Benefit Ref. Number of studies included Total number of patients Number of patients in Anti-IL6R group Survival benefit Progression to ICU admission Progression to invasive mechanical ventilation Place of corticosteroids Serious adverse events [153] 23 6279 1897 Morality: - All types of severity:–0.062 (- 0.118,–0.005) - Severe patients:–0.119 (- 0.177,–0.06) - All types of severity: 0.003 (-0.135, 0.141) - Severe patients:0.096 (- 0.009, 0.200) - All types of severity:–0.041 (- 0.145, 0.063) - Severe patients:–0.108 (- 0.193,–0.024) Not evaluated Not evaluated [139] 27 10 930 6449 Day 28: OR: 0.86, 95%CI: 0.79-0.95; P = 0.003 Absolute mortality risk: 22% for IL-6 antagonists and 25% for usual care/placebo - Tocilizumab: 0.83, 95%CI: 0.74-0.92; P < .001) - Sarilumab: 1.08 (95%CI: 0.86-1.36; P = .52) Not evaluated Not evaluated Progression to IMV, ECMO or death (whole population): - without CS: 0.96, 95% CI: 0.79-1.17 - with CS: 0.71, 95% CI: 0.63-0.80 Progression to IMV, ECMO or death (Tocilizumab): - without CS: 0.95, 95% CI: 0.76-1.20 - with CS: 0.69, 95% CI: 0.61-0. 78 Progression to IMV, ECMO or death (Sarilumab): - without CS: 0.98, 95% CI: 0.67-1.44 - with CS: 1.08, 95% CI: 0.67-1.75 28-days mortality: - without CS: 1.09, 95% CI: 0.91-1.30 - with CS: 0.78, 95% CI: 0.69-0.88 Not evaluated [142] 10 6493 3358 - Mortality: 24.4% vs. 29.0%; OR 0.87, 95% CI: 0.74–1.01; p = 0.07; I2 = 10%. - Mortality in patients requiring ICU admission at enrollment: 34.7% vs. 39.6%; OR 0.84, 95% CI: 0.65–1.10; p = 0.20; I2 = 24% - Mortality in trials with low risk of bias: 12.3% vs. 10.7%; OR 1.09, 95% CI: 0.75–1.57; p = 0.65; I2 = 0%. - Sensitivity analysis using a fixed effect model: OR 0.85, 95% CI: 0.76–0.96; p = 0.006; I2 = 10%; TSA adjusted CI: 0.70–1.04. 34.9% vs. 41.5%; OR 0.73, 95% CI: 0.38–1.39; p = 0.34; I2 = 60% - Progression to severe disease: 28.9% vs. 36.6% ; OR 0.72, 95% CI: 0.59–0.89; p = 0.002; I2 = 26% 8.7% vs. 10.5%; OR 0.70, 95% CI: 0.54–0.89; p = 0.004; I2 = 0% Not evaluated Not evaluated [150]† 36 RCT: 8, Cohorts: 28 6311 3267 - short term mortality: RR: 0.91, 95%CI: 0.72, 1.07, I2 = 25%). “Poor outcome”: RR: 0.82 (95% CI: 0.76, 0.90, I2 = 3%) RR: 0.84, 95% CI: 0.76, 0.93, I2 = 0% Composite factor (mortality or mechanical ventilation): - Receiving CS: 1.02, 95%CI: 0.79, 1.31 - Not receiving CS: 0.98, 95%CI: 0.89, 1.07 - SAE: 0.85, 95% CI: 0.63, 1.16 - Risk of infection: RR: 0.67, 95% CI: 0.45, 0.99 [154] 9 6489 3358 - Fixed-effect model: OR: 0.87; 95% CI: 0.75, 0.94; I2: 24% - Random-effect model: OR: 0.87; 95% CI: 0.71–1.07 - Mortality for moderate disease: * Global: OR: 1.30; 95% CI: 0.64–2.64; I2: 0% *Fixed-effect model: OR: 0.84; 95% CI: 0.75–0.94; I2: 53% *Random-effect model: OR: 0.89; 95% CI: 0.71–1.18 Not evaluated Not evaluated Not evaluated Not evaluated [155] 8 6481 3264 - Global population: RR: 0.89, 95% CI: 0.82-0.96 - after exclusion of RECOVERY: RR: 0.89, 95% CI: 0.75-1.06 - ICU patients: RR: 0.94, 95%CI 0.74-1.19 (I2=60%) - Early mortality (14-15 days): RR: 2.18, 95% CI: 1.01-4.69, I2=31%). RR: 0.68, 95% CI 0.50-0.92, I2=6% RR: 0.79, 95% CI: 0.68-0.91, I2=0% Not evaluated - AE: RR: 0.97, 95% CI: 0.88-1.07, I2=28% - SAE: RR: 0.87, 95% CI: 0.72-1.06, I2=0% - Superinfection: RR: 0.64, 95% CI: 0.64-0.97, I2=44% - Severe superinfection: RR: 0.57, 95% CI: 0.35-0.93, I2=42% - Neutropenia: RR: 8.70, 95% CI: 2.34-32.39 [156] 52 (9 RCT, 43 observational) 27004 among which RCT patients: 6604 8048 among which RCT patients: 3358 - Considering RCT: RR: 0.89, 95% CI: 0.82–0.96, 95%, PI: 0.80–0.97; I2 = 0.3% - Considering observational studies: RR: 0.69, 95% CI: 0.58–0.83, 95%, PI: 0.28 to 1.73 ; I2 = 84.0% - Considering RCT: RR: 0.81, 95% CI: 0.71 to 0.93, 95%, PI: 0.60 to 1.09; I2=0.0% - Considering observational studies: RR: 0.81, 95%, CI: 0.57 to 1.14, 95%, PI: 0.28 to 2.29 ; I2 = 70.2% Composite endpoint of ICU admission or IMV: - Considering RCT: RR: 0.80, 95% CI: 0.70 to 0.92, 95%, PI: 0.67 to 0.97; I2=0.0% - Considering observational studies: RR: 1.08, 95% CI: 0.85 to 1.38, 95% PI: 0.67 to 1.73; I2 = 18.4% - Considering RCT: RR: 0.99, 95% CI: 0.79, 1.24; I2 = 64.6% - Considering observational studies: RR: 0.67, 95% CI: 0.54, 0.81; I2 = 59.9% Not evaluated [140] 10 (Sarilumab and Tocilizumab) 20 (Tocilizumab) 11 (Sarilumab) 6 (Klazakisumab) 2 (Olokizumab) 1 (Siltuximab) 1(Levilimab) 6428 - Tocilizumab: - D28: RR: 0.89, 95% CI: 0.82 to 0.97; I2 = 0.0% - D≥60: RR: 0.86, 95% CI: 0.53 to 1.40; I2 = 0.0% Sarilumab: - D28: RR: 0.77, 95% CI: 0.43 to 1.36 - D≥60: RR: 1.00, 95% CI: 0.50 to 2.0 Progression Score of level of 7 or above: RR: 0.99, 95% CI: 0.56 to 1.74; I2 = 64.4% Tocilizumab and clinical improvement : RR: 1.06, 95% CI: 1.00 to 1.13; I2 = 40.9% - Not evaluated Tocilizumab: - AE: RR: 1.23, 95% CI: 0.87 to 1.72; I2 = 86.4% - SAE: RR: 0.89, 95% CI: 0.75 to 1.06; I2 = 0.0% Sarilumab: - AE: RR: 1.05, 95% CI: 0.88 to 1.25 - SAE: RR: 1.17, 95% CI: 0.77 to 1.77 [114] 45 comparatives studies and 28 single-arm studies 13189 and 1770 3992 and “not appropriate" Risk of mortality: RR: 0.76, 95%CI: 0.65 to 0.89, P < 0.01 Clinical improvement (comparative studies): RR: 1.19 (95% CI: 1.00 to 1.42; P = 0.05, I2 = 81.2%) ICU admission (comparative studies): RR: 0.98 (95% CI: 0.36 to 2.66; P = 0.99; I2 = 89.4%) RR:0.48, 95% CI: 0.24 to 0.97, p = 0.04 Not evaluated Secondary infections (comparative studies): RR: 1.24 (95% CI: 0.98 to 1.56; P = 0.07; I2 = 66.5%) [163] 13 2120 674 OR: 0.42, 95% CI: 0.26 to 0.69, P = 0.0005, I2 = 55% Not evaluated OR = 0.95, 95% CI: 0.53 to 1.72, P= 0.88, I2 = 61% Not evaluated Not evaluated [143] 38: 3 double-blinded RCT, 4 open-label RCT, 23 prospective cohorts, 5 case-control studies 13 412 4090 Whole population: OR: 0.54, 95 % CI: 0.42– 0.71, p < 0.00001, I2 = 79 % Subgroup analysis excluding observational studies: OR: 0.90, 95 % CI: 0.64–1.26, p = 0.54, I2 = 0 % Alteration of severity: OR: 1.05, 95 % CI: 0.92–1.20, p = 0.47, I2 = 84 % Not evaluated - SAE: OR: 0.91, 95 % CI: 0.71–1.15, p = 0.42, I2 = 46 % [144] 6 2057 1177 HR: 0.83; 95% CI 0.66–1.05 Not evaluated Composite endpoint of requirement of mechanical ventilation and all-cause mortality: OR: 0.62; 95% CI: 0.42-0.91 Not evaluated Not evaluated [146] 71 (including 6 RCT): - Tocilizumab: 58 - Anakinra: 6 - Tocilizumab and Anakinra: 1 - Sarilumab and Tocilizumab: 1 - Sarilumab: 4 - Siltuximab: 1 22058 7328 (therapy under review) 6563 (Tocilizumab) Tocilizumab: - Global: RR: 0.83, 95% CI: 0.72 to 0.96, I2=0.0% -Prospective studies: HR: 0.70, 95% CI: 0.44 to 1.10, I2=0% -Retrospective studies: HR: 0.52, 95% CI: 0.41 to 0.66, I2=76.6% -RCT alone: RR: 0.85, 95% CI: 0.71 to 1.01 I2=0.0%) Sarilumab: aOR: 2.01, 95% CI: 1.18 to 4.71 Outcomes on the Ordinal scale: * Tocilizumab: - Prospective studies: GenOR: 1.09, 95% CI: 0.99 to 1.19, I2=84.3% - Retrospective studies: GenOR: 1.34, 95% CI: 1.10 to 1.64, I2=98%. * Sarilumab: GenOR: 1.07, 95% CI: 0.90 to 1.27 Not evaluated “similar” [145] 6 1038 - RR: 1.03; 95% CI: 0.72 to 1.46; p = 0.89, I2 = 0.0% - Random-effect: RR: 0.71; 95% CI: 0.37 to 1.38; p = 0.32, I2 = 36% - Random-effect: RR: 0.70; 95% CI: 0.51 to 0.96; p = 0.02, I2 =0% Not evaluated SAE: - Random-effect: RR: 0.63; 95% CI: 0.35 to 1.14; p = 0.12, I2 = 57.9% - Fixed-effect: RR: 0.68; 95% CI: 0.57 to 0.81; p = 0.00, I2 = 77.4% [152] 9 6778 3647 - Meta analysis: * Studies mortality rate: 0.19; 95% CI: 0.18 – 0.2, I2: 98.8% Not evaluated Not evaluated Not evaluated Not evaluated [157] 26: 23 retrospectives, 1 prospective, 2 randomized controlled 8272 2112 RR: 1.65, 95% CI: 1.37 – 2.00, I2: 70% Not evaluated Not evaluated Not evaluated Not evaluated [147] 8 6314 3267 D28: OR, 0.92; 95% CI, 0.66–1.28; I2 = 62% D28: OR: 0.51; 95% CI: 0.28–0.92; I2 = 30% Incidence of mechanical ventilation à D28: OR: 0.75; 95% CI: 0.62–0.90; I2 = 11% Steroids at admission: OR: 0.89; 95% CI: 0.56–1.43; I2 = 81% - AE: OR: 1.03; 95% CI: 0.71–1.49; I2 = 43% - SAE: OR: 0.86; 95% CI: 0.67–1.12; I2 = 0% - Infection: OR: 0.87; 95% CI: 0.63–1.20; I2 = 0 [148] 29 11 487 2651 RR: 0.74; 95% CI: 0.59–0.93; P = 0.008; I2 = 80% RR: 1.40, 95% CI : 0.64–3.06 ; P = 0.4; I2 = 88% RR: 0.83 95% CI: 0.57–1.22; P = 0.34; I2 = 65% Secondary infection: RR: 1.30, 95% CI: 0.97–1.74; P = 0.08; I2 = 65% [158] 25 10 201 4056 OR: 0.70, 95% CI: 0.54–0.90, P = 0.007; I2: 74% Not evaluated OR: 0.59, 95% CI: 0.37–0.93, P = 0.02; I2: 56% Not evaluated Not evaluated [151] 9 6490 3358 RR: 0.89, 95% CI: 0.80–0.98, p = 0.02; I2: 6% Not evaluated RR: 0.80, 95% CI: 0.71–0.89, p < 0.0001; I2: 0% RR: 0.87, 95% CI 0.80–0.95, p = 0.0009; I2: 0% Not evaluated [141] 18 - Tocilizumab: 16 - Sarilumab: 1 - Siltuximab: 1 RCT: 1, Cohort: 14, case control : 3 3303 - Tocilizumab or Sarilumab: RR: 0.61, 95% CI: 0.49–0.76; I2: 58% Not evaluated RR: 0.68, 95% CI: 0.32–1.45; I2: 75% Not evaluated Not evaluated [159] 17‡ 14 054 Not evaluated “Treatment failure”: RR: 0.62, 95% CI: 0.42 – 0.91; I2: 60% Mortality in SOC vs Tocilizumab and corticosteroid therapy: RR: 0.62, 95% CI: 0.42 – 0.91; I2: 60% RR: 1.11, 95% CI: 0.81 – 1.53, I2 was 0%, ( p = 0.84) [164] 39 15 531 3657 OR 0.74, 95% CI: 0.55–1.01, p = 0.057, I2: 79.5% Studies with adjusted, estimated, Tocilizumab: HR: 0.50, 95% CI: 0.38–0.64, p < 0.001 OR: 3.79, 95% CI: 0.38–37.34, p = 0.254 Studies with adjusted, estimated, Tocilizumab: OR: 0.16, 95% CI: 0.06–0.43, p < 0.001 OR: 2.21 95% CI: 0.53–9.23, p = 0.277, I2: 86.57% OR: 0.49, 95% CI: 0.36–0.65, p < 0.05 OR: 2.36, 95% CI: 1.01–5.54, p = 0.050, I2: 87.96% [165] 64: controlled observational studies: 54, RCT: 10 20 616 7668 - Broad mortality: OR: 0.73, 95% CI: 0.56–0.93, I2 = 82%, (p < 0.001) - Patients receiving CS: OR: 0.67, 95% CI: 0.54–0.84 - In wards: OR: 1.25, 95% CI: 0.74–2.18, I2: 82.9% - In ICU: OR: 0.66, 95% CI: 0.59–0.76, I2: 0.00% - Tocilizumab before D10: OR: 0.71, 95% CI: 0.35–1.42 - Tocilizumab after D10: OR: 0.83, 95% CI: 0.48–1.45 Not evaluated Not evaluated Not evaluated Secondary infection: OR: 1.04, 95% CI: 0.72–1.52, I2: 87.8% [149] 6 5426 2849 RR: 0.90, 95% CI: 0.76 to 1.07, I2=0% Not evaluated Not evaluated separately Not evaluated SAE : RR: 0.82, 95% CI: 0.62 to 1.10, I2=0 [160]# All experimental treatments: 222 Tocilizumab: 12 All experimental treatments: 102 950 Tocilizumab: 13606 - - Fixed-effect model: OR: 0.85, 95% CrI: 0.77–0.95 - Random-effect model: OR of 0.91, 95% CrI: 0.74 -1.16 Not evaluated OR: 0.75, 95% CrI: 0.65–0.86 Not evaluated Not evaluated [161]* 15 (including 7 unpublished) 5339 1661 - Oxygen only: median OR: 0.70 (95% CrI, 0.50-0.91). PPBA: 98.9%. PPMCA: 95.5% - NIV: median OR: 0.81 (95%CrI, 0.63-1.03). PPBA: 95.5% PPMCA: 82.2% - IMV: median OR: 0.89 (95%CrI, 0.61-1.22) PPBA: 75.4% PPMCA: 52.9% Not evaluated Not evaluated All included patients have received corticosteroids Not evaluated [162] 9 6490 3358 OR: 0.87; 95% CI: 0.73-1.04; I2: 15% Non severe disease: OR: 0.1.3; 95% CI: 0.77-2.20; I2: 0% Severe disease: OR: 0.84; 95% CI: 0.63-1.12; I2: 57% OR: 0.66; 95% CI : 0.40-1.08; I2: 29% OR : 0.74; 95% CI: 0.64-0.86; I2: 0% Initial use of steroids in more than 50% of participants: OR: 0.87; 95% CI: 0.66-1.13; I2: 46% Initial use of steroids in more than 50% of participants: OR: 1.07 ; 95% CI : 0.0.70-1.64; I2: 0% - One AE: OR: 1.38; 95% CI: 0.87-2.19; I2: 70% - Serious AE: OR: 0.90; 95% CI: 0.70-1.14; I2: 0% - Infection: OR: 0.89; 95% CI: 0.65-1.23; I2: 0% - Serious infection: OR: 0.57; 95% CI: 0.36-0.89 ; I2: 21% AE Adverse event, CS corticosteroids, ECMO extra-corporeal membrane oxygenation, IL-6R Receptor of interleukin-6, IMV invasive mechanical ventilation, NIV Noninvasive ventilation, NS not significant, PI prediction interval, PPBA Posterior probability of benefit association, PPMCA Posterior probability of meaningful clinical association, RCT Randomized and controlled trial, AE adverse events, SAE Severe adverse events, SOC standard of care †Presented results include only the analysis of RCT. ‡ Corticosteroids: Methylprednisolone # Bayesian meta-analysis * Bayesian reanalysis of previous meta-analysis (33) Positive results are indicated in bold The ability of tocilizumab to reduce short-term mortality during COVID-19 remains unclear in a recent meta-analysis [114, 139–162]. A positive effect on raw mortality values can be observed in many works [114, 139, 140, 143, 146, 148, 151–153, 155–158, 160, 163–165], sometimes only in statistical analysis using a fixed-effect model [142, 154, 160], with a loss of significance in a random-effect model [154, 160], and this improvement in survival does not appear to be confirmed beyond day 60 [140]. In other meta-analyses, no difference in whole population mortality [142, 144, 145, 147, 149, 150, 162, 164] was observed, notably in studies including only RCTs [143, 146, 162, 163], or in sensitivity analyses including only trials with a low risk of bias [114, 140, 142–150, 163], although this point is uncertain [151, 156]. A detailed analysis shows that the potential benefit appears to be possibly stronger for more severe patients. Classified as ‘severe’ or ‘critical’, these patients generally corresponded to those requiring high flow oxygen, noninvasive ventilation or invasive ventilation, or to class 6–9 of the WHO classification [154]. However, severe cases include classes 4 and 5 of the WHO classification without distinction. Improvement in patients already invasively ventilated or requiring ECMO is still debatable. Similarly, despite initial hope [98], no survival benefit was observed in patients requiring ICU admission at study inclusion [142, 155], and a benefit for patients already requiring mechanical ventilation is yet to be demonstrated [161, 162]. Delayed administration of tocilizumab is associated with the loss of previous significance despite a large number of available included patients [165]. A reduction in mortality may depend on the concomitant administration of corticosteroids [139, 151, 164]. Similarly, progression to ICU [139], invasive mechanical ventilation [139], or ECMO [139] may be reduced by the combination of tocilizumab and corticosteroids rather than by inhibition of the IL-6 receptor alone. Unfortunately, specific analysis of this combination has not been systematically carried out [114, 140–144, 146, 148, 149, 152, 153, 155, 156, 158, 163, 165]. On the other hand, steroid administration at inclusion does not appear to modify the mortality rate in treated patients relative to the standard of care [147]. Another question to be raised is whether progression to ICU admission can be reduced. Tocilizumab may be effective [142, 147, 148, 155, 156] but has not been so in every meta-analysis [114, 145, 148, 153, 164], and clinical improvement is often absent [114, 140, 143, 146]. More restrictively, tocilizumab may reduce progression to invasive mechanical ventilation [114, 142, 145, 147, 150, 151, 153, 155, 156, 158, 160, 162] but the true effect on this parameter is still unclear [141, 148, 163, 164]. Numerous risks of bias have been highlighted as a major limitation to the interpretation of meta-analyses. They include methodological issues [141, 143, 146, 148, 151, 152, 159, 160, 164, 165], such as open-label design [142, 144, 151, 154, 155, 162], the existence of a second randomization (RECOVERY) [155], using the study drug depending on its local availability [155], modification of outcomes during patient recruitment [155], early termination of studies for futility or safety [155], and heterogeneity in patient recruitment, with a large difference in the incidence of mechanical ventilation [155] and patient severity [149, 160, 162], especially in terms of inflammatory severity [162]. Also lacking is a clear definition of patient severity, the indication for ICU admission, and the need for invasive mechanical ventilation [140, 142, 149, 158, 160, 165]. Considerable variation in the standard of care and the administration of supposed anti-COVID-19 treatments has been extensively documented [140, 143, 146, 151, 155, 156, 159, 162, 164, 165].The potential effect of industry sponsorship has also been reported [142]. Last but not least, the lack of structured reporting of superinfections may constitute an issue in safety analysis [155]. Concerning the meta-analyses themselves, the inclusion of studies before peer review [140, 142, 160, 161, 164], asymmetry of funnel plots for publication or selective reporting [114, 141, 142, 151, 156, 160, 163], and the weight of a small number of trials in the overall analysis [142, 151, 155, 156] were the most noted limitations. Should We Try to Specifically Inhibit the IL-6 Pathway During COVID-19? Should Tocilizumab Be Used? The considerable heterogeneity of the population included in these studies and meta-analysis makes it difficult to determine the groups of interest [54, 81, 96, 166] and the relevant intervention period [19, 110, 112]. However, the first 2 days following ICU admission or the early period after the introduction of invasive ventilation appear to be the most agreed upon [19, 99, 110, 112]. Conversely, the administration of treatment too early could be useless [1–11] or even deleterious because of the important role of IL-6 in anti-infective control [19, 24, 136, 137]. Despite the limitations discussed above, Stone et al. propose the inclusion of an IL-6 cut-off value in the decision to introduce an IL-6 pathway inhibitor [43]. Furthermore, consistency between the IL-6 level and the amount of tocilizumab administered was partially reinforced in the study by Soin et al., in which high IL-6 levels were probably poorly controlled by too low a dose of tocilizumab [53]. These last elements may explain the importance of the association with corticosteroids. However, the central role that corticosteroids appear to play, recently emphasized by Matthay and Luetkemeyer [101], brings up the relevance of a single cytokine inhibition rather than enhanced inhibition of broad-spectrum proinflammatory mediators by higher doses of steroids. This point is reinforced by the recent results of studies using a high dose of dexamethasone [44, 45]. The current main hypothesis is the association of tocilizumab and dexamethasone to attenuate inflammation. However, preclinical models are urgently needed to decipher these clinical observations. Finally, a more recent question is the relevance of inhibiting the IL-6 pathway in vaccinated patients. IL-6 (B cell-stimulating factor) plays a central role in B-cell stimulation [32, 93, 137, 167]. Interfering with antibody production in mild to moderate infection may contribute to worsening of the disease rather than preventing deterioration. This aspect is yet to be elucidated. Tocilizumab for Whom? The global magnitude of COVID-19 highlights the urgent need for a better definition of patients eligible for tocilizumab. On the one hand, it is important to not overlook people with a potential survival benefit, but on the other hand, the current waste of product and money is unacceptable [101]. The currently available data strongly discourage early and widespread use of immunotherapies, including IL-6 pathway inhibitors, in low severity COVID-19 [24, 42, 43, 52–54, 56, 58, 81, 97, 127, 168]. At the other end of the severity spectrum, the extent of inflammation and/or duration of disease evolution in the most severe patients requiring invasive mechanical ventilation or ECMO is associated with low efficacy of IL-6 pathway inhibition [85, 101, 110]. Although the heterogeneity of the existing data and the broad spectrum of severity groups [43, 53, 96, 97, 122, 127] makes it difficult to draw conclusions, the available information tends to demonstrate the futility of tocilizumab for mechanically ventilated patients [100]. At the other end of the severity spectrum, no benefit was observed for patients receiving moderate-flow oxygen (stage 5 of the WHO classification) [126]. Conversely, among patients requiring high oxygen flows, tocilizumab may contribute to prevent invasive mechanical ventilation [97]. Similarly, the RECOVERY study suggests that the benefit of the treatment is centered on patients requiring noninvasive ventilation [127]. However, an early study that focused on patients under high-flow oxygen or non-invasive ventilation failed to demonstrate a benefit of tocilizumab in the absence of an association with corticosteroids [42]. Given the pharmacodynamics of tocilizumab, the IL-6 serum concentration may help to define the target population for IL-6R blockade. However, IL-6 measurements are lacking for many randomized studies and the heterogeneity of patients does not make it possible to determine the clinical severity and biological elevation of IL-6. Despite an interesting correlation observed between the potential benefit and CRP levels in the REMAP-CAP study [98], no benefit of tocilizumab was observed for patients with approximately 25 pg/mL [43] or 100 pg/mL IL-6 [53]. Similar observations were noted for higher concentrations of IL-6 (around 200 pg/mL) [54, 96]. In the RECOVERY study, the median time of administration was 9 days from the onset of symptoms [127]. Interestingly, a Spanish observational monocentric study found better 90-day survival (95.0% vs 83.4%) for patients who received tocilizumab later (9 [7–10] vs 6 [5–7] days after symptom onset) [169]. These data suggest a potential benefit of tocilizumab for patients of intermediate severity requiring oxygen therapy but not mechanical ventilation approximately 9 days after the onset of COVID-19 symptoms. As fibrinogen levels appear to be able to predict the pejorative evolution of COVID-19 [170], they could be used (cut-off to be defined) to better define the population of potential interest for tocilizumab treatment. A better definition of severity, probably using biological criteria, such as a cut-off level for inflammatory mediators (CRP, IL-6), would be highly useful in defining the ideal target patients. Safety of Tocilizumab The major adverse events observed during tocilizumab and sarilumab use in COVID-19 clinical trials are summarized in Table 5.Table 5 Major adverse events associated with tocilizumab during clinical trials Article Adverse events First author or study group Ref. Placebo Tocilizumab REMAP-CAP [98] Four bleeding events Seven thromboses One secondary bacterial infection Five bleeding events two cardiac events One deterioration in vision Rosas IO [54] Patients with at least 1 AE: 116 (81.1%) Infections: 58 (40.6%) Serious: 37 (25.9%) Opportunistic: 1 (0.7%) Patients with at least 1 AE: 228 (77.3%) Infections: 113 (38.3%) Serious: 62 (21.0%) Opportunistic: 1 (0.3%) Veiga VC [96] Any: 21 (34%) Secondary infection: 14.7 (8.2%) Thrombotic events: 4 (6%) Neutropenia: 0(0%) Severe raised in ALT, AST, or bilirubin level: 3(5%) Any: 29 (43%) Secondary infection: 11.3 (8.0%) Thrombotic events: 3 (5%) Neutropenia: 1 (1%) Severe raised in ALT, AST, or bilirubin level: 7(10%) RECOVERY [127] - One pulmonary abscess One external otitis One Staphylococcus aureus bacteremia Stone JH [43] Infection of grade 3 or 4: 14 (17.1%) DVT: 3(3.7%) PE: 2 (2.4%) Stroke: 0 Neutropenia (≥ grade 3): 1 (1.2%) Infection of grade 3 or 4: 13 (8.1%) DVT: 2 (1.2%) PE: 2 (1.2%) Stroke: 2 (1.2%) Neutropenia (≥ grade 3): 22 (13.7%) Gupta S [99] Secondary infection: 1085 (31.1%) Thrombotic complications: 342 (9.8%) AST or ALT level elevation (> 250U/L): 452 (12.9%) Secondary infection: 140 (32.3%) Thrombotic complications: 46 (10.6%) AST or ALT level elevation (> 250U/L): 72 (16.6%) Salvarani C [42] Any: 7 (11.1%) Infection: 4 (6.3%) Laboratory abnormalities: 2 (3.2%) Vascular disorders: 0 Any: 14 (23.3%) Infection: 1 (1.7%) Laboratory abnormalities: 8 (13.3%) Vascular disorders: 1 (1.7%) Hermine O [100] At least one: 36 (54%) No. of events: 86 Patients with at least 1 SAE: 29 (43%) Hepatic cytolysis: 4 Neutropenia: 0 ARDS (death): 19 (9%) Bacterial sepsis: 11 Fungal sepsis: 2 PE (death): 3 At least one: 28 (44%) No. of events: 66 Patients with at least 1 SAE: 20 (32%) Hepatic cytolysis: 4 Neutropenia: 4 ARDS (death): 9 (7%) Bacterial sepsis: 2 Fungal sepsis: 0 PE (death): 0 Lescure FX [52] Total: 55 (65%) Leading to death: 9 (11%) Sarilumab (200 mg): - Total: 103 (65%) - Leading to death: 17 (11%) Sarilumab (400 mg): - Total: 121 (70%) - Leading to death: 18 (10%) Soin AS [53] Total: 22 (25%) Serious: 15 (17%) ARDS: 7 Total: 33 (36%) Serious: 18 (20%) ARDS: 7 Guaraldi G [56] Secondary infection*: 14 (4%) Neutropenia: 0 Secondary infection*: 24 (13%) Neutropenia: 1 (<1%) SARTRE [58] Overall: 15.7% Infection and infestation: 2.9% Increased Alanine aminotransferase: 2.9% Increased aminotransferase: 2.0% Nervous system disorders: 1.0% Gastrointestinal disorders: 0.0% Blood and lymphatic system disorders: 0.0% Overall: 18.2% Infection and infestation: 1.0% Increased Alanine aminotransferase: 7.1% Increased aminotransferase: 5.1% Nervous system disorders: 0.0% Gastrointestinal disorders: 1.0% Blood and lymphatic system disorders: 2.0% REMDACTA [125] P+R: - Overall: 530 - Of “special interest”: 149 . Infection: 33.3% . Serious infection: 24.9% . Opportunistic: 2.3% . Bleeding: 10.3% . Serious bleeding: 3.3% . Stroke: 3.8% . Hepatic events: 1.4% .Gastrointestinal perforation: 0.5% T+R: - Overall: 1094 - Of “special interest”: 268 . Infection: 30.5% . Serious infection: 20.0% . Opportunistic: 0.7% . Bleeding: 12.8% . Serious bleeding: 2.6% . Stroke: 2.3% . Hepatic events: 1.4% .Gastrointestinal perforation: 0.2% CORIMUNO-SARI-1 [121] At least one AE :33 (43%) Multiple AE: 11 (14%) Serious AE: 28 (37%) ---ARDS:11 ---Bacteria sepsis:7 ---Hepatic cytolysis: 3 ---Neutropenia: 0 ---Death: 16 (21%) At least one AE: 37 (54%) Multiple AE: 17 (25%) Serious AE: 27 (40%) ---ARDS: 7 ---Bacteria sepsis: 12 ---Hepatic cytolysis: 6 ---Neutropenia: 5 Death:10 (15%) SARICOR [120] AE: 39 Cytolysis: 1 Nosocomial infection: 3 Bacteremia: 1 Tachyarrhythmia: 2 ---S200: AE: 37 Cytolysis: 0 Nosocomial infection: 5 Bacteremia: 1 Tachyarrhythmia: 0 ---S400: AE: 39 Cytolysis: 1 Nosocomial infection: 2 Bacteremia: 1 Tachyarrhythmia: 1 EMPACTA [97] Total AE: 187 At least 1 AE: 67 (52.8%) Serious AE: 25 (19.7%) Death: 15 (11.8%) Infection: 16 (12.6%) Serious infection: 9 (7.1%) Total AE: 250 At least 1 AE: 127 (50.8%) Serious AE: 38 (15.2%) Death: 29 (11.6%) Infection: 25 (10.0%) Serious infection: 13 (5.2%) Sivapalasingam S [61] - Severe patients > TEAE: 7 (28.0%) > SAE: 1 (4.0%) > TEAE LD: 0 - Critical patients > TEAE: 28 (63.6) > SAE: 26 (59.1%) > TEAE LD: 14 (31.8%) - MSOD/IC patients > TEAE: 16 (76.2%) > SAE: 12 (57.1%) > TEAE LD: 9 (42.9%) MSOD/IC patients - Severe patients * S200: > TEAE: 19 (38.0%) > SAE: 5 (10.0%) > TEAE LD: 2 (4.0%) *S400: > TEAE: 25 (49.0%) > SAE: 16 (31.4%) > TEAE LD: 8 (15.7%) - Critical patients * S200: > TEAE: 69 (73.4%) > SAE: 56 (59.6%) > TEAE LD: 37 (39.4%) *S400: > TEAE: 56 (63.6%) > SAE: 41 (46.6%) > TEAE LD: 22 (25.0%) - MSOD/IC patients * S200: > TEAE: 35 (81.4%) > SAE: 29 (67.4%) > TEAE LD: 20 (46.5%) *S400: > TEAE: 33 (80.5%) > SAE: 27 (65.9%) > TEAE LD: 15 (36.6%) CORIMUNO-19 bis [122] Tocilizumab AE: 30 (70%) SAE: 27 (63%) ARDS: 15 Bacterial and fungal sepsis: 13 Hepatic cytotoxicity: 5 Neutropenia: 0 Sarilumab AE: 22 (68%) SAE: 19 (57.6%) ARDS: 9 Bacterial and fungal sepsis: 4 Hepatic cytotoxicity: 5 Neutropenia: 2 Tocilizumab AE: 33 (67%) SAE: 31 (63%) ARDS: 13 Bacterial and fungal sepsis: 27 Hepatic cytotoxicity: 12 Neutropenia:1 Sarilumab AE: 32 (68%) SAE: 31 (64.6%) ARDS: 15 Bacterial and fungal sepsis: 19 Hepatic cytotoxicity: 3 Neutropenia: 0 AE Adverse event, ARDS acute respiratory distress syndrome, DVT Deep venous thrombosis, MSOD/IC multi-system organ dysfunction/Immunocompromised, PE Pulmonary embolism, SAE severe adverse event, TEAE treatment-emergent adverse event, TEAE LD treatment-emergent adverse event leading to death P+R: Placebo and Remdesivir T+R: Tocilizumab and Remdesivir *(p < 0.0001) During the chronic use of IL-6 pathway inhibitors, it is well established that the incidence of serious infection events is approximately 5.5 per 100 patient-years [32, 167, 171, 172]. The potential risks associated with tocilizumab during management of COVID-19 is still unclear. It should be noted that patients with suspected active infection were generally excluded from the studies. Numerous studies have investigated the risk of infection, with sometimes conflicting results [114]. Randomized studies show a minor short-term risk [42, 54, 96–100, 120, 127]. The majority of recent meta-analyses that have specifically examined superinfection did not find any increase in risk [114, 146–148, 153, 165]. However, this still a subject of debate [150, 155], particularly due to the issue of adverse events collected in currently available RCTs. Several studies have emphasized the increasing risk of bacteremia [57, 173], pneumonia [57, 119], and any secondary infections [56, 110, 119] following tocilizumab administration. Other studies did not demonstrate any therapeutic or iatrogenic effect of tocilizumab [42]. The most recent meta-analysis provided heterogeneous results, highlighting an increase in the risk of secondary infection [150, 153, 155] or no significant difference in superinfection [114, 146–148, 162, 165], usually not correlated with improved survival. However, in the various RCTs, the risk of infection associated with tocilizumab was only observed when a clinical benefit of the anti-IL-6R was observed. IL-6 pathway inhibition may even be associated with a decrease in infectious risk [43, 99, 113, 118, 162], possibly because of the reduced risk of subsequent immune reprogramming [174, 175]. Regardless of the modification of infectious risk, the benefit obtained allows a reduction in mortality, independently of the occurrence of secondary infections. Conversely, in mild and moderate COVID-19, the risk associated with potential infection appears greater than the expected benefit. As well described, immune exhaustion is associated with severe COVID-19 [92, 176–178]. Excess IL-6 levels are associated with impaired NK-cell function [179] by the downregulation of activating receptors (NKp30 and NKG2D) [180] and reduction of granzyme B and perforin expression [179, 180]. IL-6 also promotes the reduction of type I/III IFN production and is inversely correlated with NK cell count [18] and lymphocytes depletion (marked by PD-1 or Tim3 expression) [94]. A recent Greek study including COVID-19 patients with macrophage activation-like syndrome and/or complex immune dysregulation demonstrated improved mHLA-DR expression on circulating CD14+/CD45+ cells (p = 0.001) in ICU patients treated with tocilizumab [60]. As a decrease in HLA-DR expression is generally considered to be a marker of immunocompromise, we may expect a potential benefit of inhibiting the IL-6 pathway in the excessive inflammatory state associated with severe COVID-19. However, these observations were not associated with an improvement in proinflammatory cytokine production in vitro by peripheral blood mononuclear cells (PBMCs) in response to endotoxin or heat-killed Candida albicans [60]. In summary, tocilizumab may curb immunity exhaustion by limiting the quantity of excess IL-6 and the duration of IL-6 stimulation [181]. Aside from the potential impairment of immunity associated with IL-6 inhibitors, the recommended association with corticosteroids may cause undue concern about an increased risk of nosocomial infections. However, current data on short-term (<10 days) steroid treatment in sepsis [182] or during COVID-19 [27, 28, 183] suggest that it is not a factor that favors secondary infections. Conclusion IL-6 receptor inhibitors may have a benefit in the management of severe COVID-19 and are now included in guidelines [184]. The timing of administration and intensity of inflammation are the best actors to guide IL-6 pathway blockade. The population most likely to benefit from treatment appears to be high-flow oxygen-dependent patients and, in general, those just admitted to the ICU or shortly thereafter [101]. Conversely, in mild and intermediate COVID-19, requiring only ward-based oxygen therapy, tocilizumab seems unnecessary, and the associated risk has not yet been evaluated. At the other end of the severity spectrum, patients requiring invasive ventilation or even extra-corporeal membrane oxygenation are unlikely to benefit from tocilizumab, the intensity of inflammation rendering the efficacy of interruption of a single pathway unlikely. A second issue is the place of corticosteroids. The relevance of combining the two treatments or increasing the dose of corticosteroids must be studied. Finally, the risks inherent in using a humanized antibody that disrupts the anti-infectious and scarring response are still very poorly understood, both in the acute phase and later, and need to be carefully studied. As the guidelines point out, “Further research is needed to identify the optimal patient population for treatment with IL-6 receptor antagonist” [185] to delineate the optimal population who would benefit from IL-6 receptor inhibition in this context [85]. Thus, prospective studies appear to be more appropriate than an iterative meta-analysis of currently existing work. The authors warmly thank Nora Touqui for her precious and meticulous proofreading and English improvement of the present article. Author contributions Conceptualization, FP. Methodology, FP and AP. Validation, FP and AC. Original draft preparation, AP, CM and FP. Writing review and editing: OT, LT and FP. Declarations Conflicts of interest AP, CM, CL, OT, LT, and FP have no conflicts of interest to declare. Funding No external funding source was used in the preparation of this manuscript. Ethics approval Not applicable. Informed consent Not applicable. Data availability Not applicable. ==== Refs References 1. Ai J, Zhang H, Zhang Y, Lin K, Zhang Y, Wu J, et al. Omicron variant showed lower neutralizing sensitivity than other SARS-CoV-2 variants to immune sera elicited by vaccines after boost. Emerg Microbes Infect. 2021;1:1-24. 2. Bradley BT Bryan A Emerging respiratory infections: The infectious disease pathology of SARS, MERS, pandemic influenza, and Legionella Semin Diagn Pathol 2019 36 152 159 10.1053/j.semdp.2019.04.006 31054790 3. Yin Y Wunderink RG MERS, SARS and other coronaviruses as causes of pneumonia Respirol Carlton Vic. 2018 23 130 137 10.1111/resp.13196 4. Vijayanand P Wilkins E Woodhead M Severe acute respiratory syndrome (SARS): a review Clin Med Lond Engl. 2004 4 152 160 10.7861/clinmedicine.4-2-152 5. Fehr AR Channappanavar R Perlman S Middle east respiratory syndrome: emergence of a pathogenic human coronavirus Annu Rev Med 2017 68 387 399 10.1146/annurev-med-051215-031152 27576010 6. Gralinski LE Baric RS Molecular pathology of emerging coronavirus infections J Pathol 2015 235 185 195 10.1002/path.4454 25270030 7. Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. JAMA. 2020;(13):1239-1242 8. Cummings MJ Baldwin MR Abrams D Jacobson SD Meyer BJ Balough EM Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study Lancet Lond Engl. 2020 395 1763 1770 10.1016/S0140-6736(20)31189-2 9. Guan W-J, Ni Z-Y, Hu Y, Liang W-H, Ou C-Q, He J-X, et al. clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020. 10. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy. JAMA. 2020;(16):1574-1581 11. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med [Internet]. 2020 [cited 2020 Mar 24]. Accessed Nov 2021.  https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2763184. 12. Sinha P Calfee CS Cherian S Brealey D Cutler S King C Prevalence of phenotypes of acute respiratory distress syndrome in critically ill patients with COVID-19: a prospective observational study Lancet Respir Med. Elsevier 2020 8 1209 1218 10.1016/S2213-2600(20)30366-0 13. Bhaskar S Sinha A Banach M Mittoo S Weissert R Kass JS Cytokine storm in COVID-19-immunopathological mechanisms, clinical considerations, and therapeutic approaches: the REPROGRAM consortium position paper Front Immunol 2020 11 1648 10.3389/fimmu.2020.01648 32754159 14. von der Thüsen J, van der Eerden M. Histopathology and genetic susceptibility in COVID‐19 pneumonia. Eur J Clin Invest [Internet]. 2020 [cited 2021 Jan 3]. Accessed Nov 2021. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267318/. 15. de la Rica R Borges M Gonzalez-Freire M COVID-19: in the eye of the cytokine storm Front Immunol 2020 11 558898 10.3389/fimmu.2020.558898 33072097 16. Schultze JL Aschenbrenner AC COVID-19 and the human innate immune system Cell 2021 184 1671 1692 10.1016/j.cell.2021.02.029 33743212 17. Lucas C Wong P Klein J Castro TBR Silva J Sundaram M Longitudinal analyses reveal immunological misfiring in severe COVID-19 Nature 2020 584 463 469 10.1038/s41586-020-2588-y 32717743 18. Vabret N Britton GJ Gruber C Hegde S Kim J Kuksin M Immunology of COVID-19: current state of the science Immunity 2020 52 910 941 10.1016/j.immuni.2020.05.002 32505227 19. Ascierto PA, Fu B, Wei H. IL-6 modulation for COVID-19: the right patients at the right time? J Immunother Cancer. 2021;9. 20. Handiso TB Jifar MS Nuriye HS Coronavirus’s (SARS-CoV-2) airborne transmission SAGE Open Med. 2022 10 20503121221094184 10.1177/20503121221094185 21. Wilson AM Sleeth DK Schaefer C Jones RM Transmission of respiratory viral diseases to health care workers: COVID-19 as an example Annu Rev Public Health 2022 43 311 330 10.1146/annurev-publhealth-052120-110009 34995130 22. Menon NG Mohapatra S The COVID-19 pandemic: Virus transmission and risk assessment Curr Opin Environ Sci Health. 2022 28 100373 10.1016/j.coesh.2022.100373 35669052 23. Mourmouris P Tzelves L Roidi C Fotsali A COVID-19 transmission: a rapid systematic review of current knowledge Osong Public Health Res Perspect. 2021 12 54 63 10.24171/j.phrp.2021.12.2.02 33979995 24. Jones SA, Hunter CA. Is IL-6 a key cytokine target for therapy in COVID-19? Nat Rev Immunol. 2021;6:1-3 25. Stolarski AE Kim J Zhang Q Remick DG Cytokine Drizzle-The Rationale for Abandoning “Cytokine Storm” Shock Augusta Ga. 2021 56 667 672 10.1097/SHK.0000000000001769 34652339 26. Schifanella L, Anderson JL, Galli M, Corbellino M, Lai A, Wieking G, et al. Massive viral replication and cytopathic effects in early COVID-19 pneumonia. 2020 [cited 2022 Jan 11]. https://arxiv.org/abs/2005.00004v1. 27. Horby P Lim WS Emberson JR Mafham M Bell JL RECOVERY Collaborative Group Dexamethasone in hospitalized patients with Covid-19 N Engl J Med 2021 384 693 704 10.1056/NEJMoa2021436 32678530 28. Tomazini BM Maia IS Cavalcanti AB Berwanger O Rosa RG Veiga VC Effect of dexamethasone on days alive and ventilator-free in patients with moderate or severe acute respiratory distress syndrome and COVID-19: the CoDEX randomized clinical trial JAMA 2020 324 1307 1316 10.1001/jama.2020.17021 32876695 29. Sterne JAC Murthy S Diaz JV Slutsky AS Villar J WHO Rapid Evidence Appraisal for COVID-19 Therapies (REACT) Working Group Association between administration of systemic corticosteroids and mortality among critically ill patients with COVID-19: a meta-analysis JAMA 2020 324 1330 1341 10.1001/jama.2020.17023 32876694 30. Fajgenbaum DC June CH Cytokine storm N Engl J Med 2020 383 2255 2273 10.1056/NEJMra2026131 33264547 31. Tanaka T Narazaki M Kishimoto T Therapeutic targeting of the interleukin-6 receptor Annu Rev Pharmacol Toxicol 2012 52 199 219 10.1146/annurev-pharmtox-010611-134715 21910626 32. Garbers C Heink S Korn T Rose-John S Interleukin-6: designing specific therapeutics for a complex cytokine Nat Rev Drug Discov 2018 17 395 412 10.1038/nrd.2018.45 29725131 33. Kang S Tanaka T Narazaki M Kishimoto T Targeting interleukin-6 signaling in clinic Immunity 2019 50 1007 1023 10.1016/j.immuni.2019.03.026 30995492 34. Frigault MJ Maus MV State of the art in CAR T cell therapy for CD19+ B cell malignancies J Clin Invest 2020 130 1586 1594 10.1172/JCI129208 32235098 35. Turtle CJ Hanafi L-A Berger C Gooley TA Cherian S Hudecek M CD19 CAR-T cells of defined CD4+:CD8+ composition in adult B cell ALL patients J Clin Invest 2016 126 2123 2138 10.1172/JCI85309 27111235 36. Maude SL Frey N Shaw PA Aplenc R Barrett DM Bunin NJ Chimeric antigen receptor T cells for sustained remissions in leukemia N Engl J Med 2014 371 1507 1517 10.1056/NEJMoa1407222 25317870 37. Lee DW Kochenderfer JN Stetler-Stevenson M Cui YK Delbrook C Feldman SA T cells expressing CD19 chimeric antigen receptors for acute lymphoblastic leukaemia in children and young adults: a phase 1 dose-escalation trial Lancet Lond Engl. 2015 385 517 528 10.1016/S0140-6736(14)61403-3 38. Sabaka P Koščálová A Straka I Hodosy J Lipták R Kmotorková B Role of interleukin 6 as a predictive factor for a severe course of Covid-19: retrospective data analysis of patients from a long-term care facility during Covid-19 outbreak BMC Infect Dis 2021 21 308 10.1186/s12879-021-05945-8 33781216 39. Chen X Zhao B Qu Y Chen Y Xiong J Feng Y Detectable serum severe acute respiratory syndrome coronavirus 2 viral load (RNAemia) is closely correlated with drastically elevated interleukin 6 level in critically ill patients with coronavirus disease 2019 Clin Infect Dis Off Publ Infect Dis Soc Am. 2020 71 1937 1942 10.1093/cid/ciaa449 40. Kang S Narazaki M Metwally H Kishimoto T Historical overview of the interleukin-6 family cytokine J Exp Med 2020 217 e20190347 10.1084/jem.20190347 32267936 41. Liu H Rohowsky-Kochan C Interleukin-27-mediated suppression of human Th17 cells is associated with activation of STAT1 and suppressor of cytokine signaling protein 1 J Interferon Cytokine Res 2011 31 459 469 10.1089/jir.2010.0115 21235411 42. Salvarani C Dolci G Massari M Merlo DF Cavuto S Savoldi L Effect of tocilizumab vs standard care on clinical worsening in patients hospitalized with COVID-19 pneumonia: a randomized clinical trial JAMA Intern Med 2021 181 24 31 10.1001/jamainternmed.2020.6615 33080005 43. Stone JH Frigault MJ Serling-Boyd NJ Fernandes AD Harvey L Foulkes AS Efficacy of tocilizumab in patients hospitalized with Covid-19 N Engl J Med 2020 383 2333 2344 10.1056/NEJMoa2028836 33085857 44. Taboada M, Rodríguez N, Varela PM, Rodríguez MT, Abelleira R, González A, et al. Effect of high versus low dose of dexamethasone on clinical worsening in patients hospitalised with moderate or severe COVID-19 Pneumonia: an open-label, randomised clinical trial. Eur Respir J. 2021;2:2102518. 45. Granholm A Munch MW Myatra SN Vijayaraghavan BKT Cronhjort M Wahlin RR Dexamethasone 12 mg versus 6 mg for patients with COVID-19 and severe hypoxaemia: a pre-planned, secondary Bayesian analysis of the COVID STEROID 2 trial Intensive Care Med 2022 48 45 55 10.1007/s00134-021-06573-1 34757439 46. Maude S Barrett DM Current status of chimeric antigen receptor therapy for haematological malignancies Br J Haematol 2016 172 11 22 10.1111/bjh.13792 26560054 47. Chen G, Wu D, Guo W, Cao Y, Huang D, Wang H, et al. Clinical and immunologic features in severe and moderate Coronavirus Disease 2019. J Clin Invest [Internet]. American Society for Clinical Investigation; 2020 [cited 2020 Mar 29]. Accessed Nov 2021 https://www.jci.org/articles/view/137244. 48. Zhou F Yu T Du R Fan G Liu Y Liu Z Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study Lancet Lond Engl. 2020 395 1054 1062 10.1016/S0140-6736(20)30566-3 49. Qin C Zhou L Hu Z Zhang S Yang S Tao Y Dysregulation of immune response in patients with coronavirus 2019 (COVID-19) in Wuhan, China Clin Infect Dis Off Publ Infect Dis Soc Am. 2020 71 762 768 10.1093/cid/ciaa248 50. Chen N Zhou M Dong X Qu J Gong F Han Y Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study The Lancet 2020 395 507 513 10.1016/S0140-6736(20)30211-7 51. Tjan LH Furukawa K Nagano T Kiriu T Nishimura M Arii J Early differences in cytokine production by severity of coronavirus disease 2019 J Infect Dis 2021 223 1145 1149 10.1093/infdis/jiab005 33411935 52. Lescure F-X, Honda H, Fowler RA, Lazar JS, Shi G, Wung P, et al. Sarilumab in patients admitted to hospital with severe or critical COVID-19: a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Respir Med. 2021;(5):522-532. 53. Soin AS, Kumar K, Choudhary NS, Sharma P, Mehta Y, Kataria S, et al. Tocilizumab plus standard care versus standard care in patients in India with moderate to severe COVID-19-associated cytokine release syndrome (COVINTOC): an open-label, multicentre, randomised, controlled, phase 3 trial. Lancet Respir Med. 2021;(5):511-521. 54. Rosas IO Bräu N Waters M Go RC Hunter BD Bhagani S Tocilizumab in hospitalized patients with severe Covid-19 pneumonia N Engl J Med 2021 384 1503 1516 10.1056/NEJMoa2028700 33631066 55. Huang C Wang Y Li X Ren L Zhao J Hu Y Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China Lancet Lond Engl. 2020 395 497 506 10.1016/S0140-6736(20)30183-5 56. Guaraldi G Meschiari M Cozzi-Lepri A Milic J Tonelli R Menozzi M Tocilizumab in patients with severe COVID-19: a retrospective cohort study Lancet Rheumatol. 2020 2 e474 e484 10.1016/S2665-9913(20)30173-9 32835257 57. Vazquez Guillamet MC Kulkarni HS Montes K Samant M Shaikh PA Betthauser K Interleukin-6 trajectory and secondary infections in mechanically ventilated patients with coronavirus disease 2019 acute respiratory distress syndrome treated with interleukin-6 receptor blocker Crit Care Explor. 2021 3 e0343 10.1097/CCE.0000000000000343 33554125 58. Sancho-López A Caballero-Bermejo AF Ruiz-Antorán B Múñez Rubio E García Gasalla M Buades J Efficacy and safety of sarilumab in patients with COVID19 pneumonia: a randomized, phase iii clinical trial (SARTRE Study) Infect Dis Ther 2021 10 2735 2748 10.1007/s40121-021-00543-2 34658006 59. Udomsinprasert W Jittikoon J Sangroongruangsri S Chaikledkaew U Circulating levels of interleukin-6 and interleukin-10, but not tumor necrosis factor-alpha, as potential biomarkers of severity and mortality for COVID-19: systematic review with meta-analysis J Clin Immunol 2021 41 11 22 10.1007/s10875-020-00899-z 33128665 60. Karakike E, Dalekos GN, Koutsodimitropoulos I, Saridaki M, Pourzitaki C, Papathanakos G, et al. ESCAPE: an open-label trial of personalized immunotherapy in critically lll COVID-19 patients. J Innate Immun. 2021;3:1-11. 61. Sivapalasingam S, Lederer DJ, Bhore R, Hajizadeh N, Criner G, Hosain R, et al. Efficacy and safety of sarilumab in hospitalized patients with COVID-19: a randomized clinical trial. Clin Infect Dis Off Publ Infect Dis Soc Am. 2022; vol. 3, p. ciac 153. 62. Chi Y Zhu Y Wen T Cui L Ge Y Jiao Y Cytokine and chemokine levels in patients infected with the novel avian influenza A (H7N9) virus in China J Infect Dis 2013 208 1962 1967 10.1093/infdis/jit440 23990573 63. Almansa R Anton A Ramirez P Martin-Loeches I Banner D Pumarola T Direct association between pharyngeal viral secretion and host cytokine response in severe pandemic influenza BMC Infect Dis 2011 11 232 10.1186/1471-2334-11-232 21880131 64. Zhou J Wang D Gao R Zhao B Song J Qi X Biological features of novel avian influenza A (H7N9) virus Nature 2013 499 500 503 10.1038/nature12379 23823727 65. Shen Z Chen Z Li X Xu L Guan W Cao Y Host immunological response and factors associated with clinical outcome in patients with the novel influenza A H7N9 infection Clin Microbiol Infect Off Publ Eur Soc Clin Microbiol Infect Dis. 2014 20 O493 500 66. Wang Z Zhang A Wan Y Liu X Qiu C Xi X Early hypercytokinemia is associated with interferon-induced transmembrane protein-3 dysfunction and predictive of fatal H7N9 infection Proc Natl Acad Sci U S A 2014 111 769 774 10.1073/pnas.1321748111 24367104 67. Wu W Shi Y Gao H Liang W Sheng J Li L Immune derangement occurs in patients with H7N9 avian influenza Crit Care 2014 18 R43 10.1186/cc13788 25030090 68. Vardhana SA, Wolchok JD. The many faces of the anti-COVID immune response. J Exp Med [Internet]. 2020 [cited 2020 Dec 14];217. Accessed Aug 2021. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7191310/. 69. Leisman DE Ronner L Pinotti R Taylor MD Sinha P Calfee CS Cytokine elevation in severe and critical COVID-19: a rapid systematic review, meta-analysis, and comparison with other inflammatory syndromes Lancet Respir Med. Elsevier 2020 8 1233 1244 10.1016/S2213-2600(20)30404-5 70. Sinha P Matthay MA Calfee CS Is a “Cytokine Storm” relevant to COVID-19? JAMA Intern Med 2020 180 1152 1154 10.1001/jamainternmed.2020.3313 32602883 71. Chen LYC, Hoiland RL, Stukas S, Wellington CL, Sekhon MS. Confronting the controversy: interleukin-6 and the COVID-19 cytokine storm syndrome. Eur Respir J [Internet]. 2020 [cited 2020 Dec 14];56. Accessed Aug 2021 .https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7474149/. 72. Remy KE Brakenridge SC Francois B Daix T Deutschman CS Monneret G Immunotherapies for COVID-19: lessons learned from sepsis Lancet Respir Med 2020 8 946 949 10.1016/S2213-2600(20)30217-4 32444269 73. Leisman DE Deutschman CS Legrand M Facing COVID-19 in the ICU: vascular dysfunction, thrombosis, and dysregulated inflammation Intensive Care Med 2020 46 1105 1108 10.1007/s00134-020-06059-6 32347323 74. Kox M, Waalders NJB, Kooistra EJ, Gerretsen J, Pickkers P. Cytokine levels in critically ill patients with COVID-19 and other conditions. JAMA. 2020;(15):1565-1567 75. Monneret G Benlyamani I Gossez M Bermejo-Martin JF Martín-Fernandez M Sesques P COVID-19: What type of cytokine storm are we dealing with? J Med Virol 2021 93 197 198 10.1002/jmv.26317 32681651 76. Frigault MJ Nikiforow S Mansour MK Hu Z-H Horowitz MM Riches ML Tocilizumab not associated with increased infection risk after CAR T-cell therapy: implications for COVID-19? Blood 2020 136 137 139 10.1182/blood.2020006216 32457999 77. Blot M Bour J-B Quenot JP Bourredjem A Nguyen M Guy J The dysregulated innate immune response in severe COVID-19 pneumonia that could drive poorer outcome J Transl Med 2020 18 457 10.1186/s12967-020-02646-9 33272291 78. McElvaney OJ McEvoy NL McElvaney OF Carroll TP Murphy MP Dunlea DM Characterization of the inflammatory response to severe COVID-19 illness Am J Respir Crit Care Med 2020 202 812 821 10.1164/rccm.202005-1583OC 32584597 79. Hedrick TL Murray BP Hagan RS Mock JR COVID-19: clean up on IL-6 Am J Respir Cell Mol Biol 2020 63 541 543 10.1165/rcmb.2020-0277LE 32750259 80. Neelapu SS Tummala S Kebriaei P Wierda W Gutierrez C Locke FL Chimeric antigen receptor T-cell therapy—assessment and management of toxicities Nat Rev Clin Oncol 2018 15 47 62 10.1038/nrclinonc.2017.148 28925994 81. Huang E Jordan SC Tocilizumab for Covid-19—the Ongoing Search for Effective Therapies N Engl J Med [Internet] 2020 10.1056/NEJMe2032071 82. Del Valle DM Kim-Schulze S Huang H-H Beckmann ND Nirenberg S Wang B An inflammatory cytokine signature predicts COVID-19 severity and survival Nat Med 2020 26 1636 1643 10.1038/s41591-020-1051-9 32839624 83. Zheng H-Y, Zhang M, Yang C-X, Zhang N, Wang X-C, Yang X-P, et al. Elevated exhaustion levels and reduced functional diversity of T cells in peripheral blood may predict severe progression in COVID-19 patients. Cell Mol Immunol. 2020;5;1-3. 84. Pablos JL Galindo M Carmona L Lledó A Retuerto M Blanco R Clinical outcomes of hospitalised patients with COVID-19 and chronic inflammatory and autoimmune rheumatic diseases: a multicentric matched cohort study Ann Rheum Dis 2020 79 1544 1549 10.1136/annrheumdis-2020-218296 32796045 85. Angriman F Ferreyro BL Burry L Fan E Ferguson ND Husain S Interleukin-6 receptor blockade in patients with COVID-19: placing clinical trials into context Lancet Respir Med 2021 9 655 664 10.1016/S2213-2600(21)00139-9 33930329 86. Blot M Jacquier M Aho Glele L-S Beltramo G Nguyen M Bonniaud P CXCL10 could drive longer duration of mechanical ventilation during COVID-19 ARDS Crit Care Lond Engl. 2020 24 632 10.1186/s13054-020-03328-0 87. Zhou Y Fu B Zheng X Wang D Zhao C Qi Y Pathogenic T-cells and inflammatory monocytes incite inflammatory storms in severe COVID-19 patients Natl Sci Rev 2020 7 998 1002 10.1093/nsr/nwaa041 34676125 88. Maeda T Obata R Rizk DOD Kuno T The association of interleukin-6 value, interleukin inhibitors, and outcomes of patients with COVID-19 in New York City J Med Virol 2021 93 463 471 10.1002/jmv.26365 32720702 89. Mudatsir M Fajar JK Wulandari L Soegiarto G Ilmawan M Purnamasari Y Predictors of COVID-19 severity: a systematic review and meta-analysis F1000Research. 2020 9 1107 10.12688/f1000research.26186.1 33163160 90. Li J Rong L Cui R Feng J Jin Y Chen X Dynamic changes in serum IL-6, IL-8, and IL-10 predict the outcome of ICU patients with severe COVID-19 Ann Palliat Med. 2021 10 3706 3714 10.21037/apm-20-2134 33615814 91. Reynolds D Vazquez Guillamet C Day A Borcherding N Vazquez Guillamet R Choreño-Parra JA Comprehensive immunologic evaluation of bronchoalveolar lavage samples from human patients with moderate and severe seasonal influenza and severe COVID-19 J Immunol Baltim Md 1950 2021 207 1229 1238 92. Giamarellos-Bourboulis EJ Netea MG Rovina N Akinosoglou K Antoniadou A Antonakos N Complex immune dysregulation in COVID-19 patients with severe respiratory failure Cell Host Microbe 2020 27 992 1000.e3 10.1016/j.chom.2020.04.009 32320677 93. McElvaney OJ Curley GF Rose-John S McElvaney NG Interleukin-6: obstacles to targeting a complex cytokine in critical illness Lancet Respir Med 2021 9 643 654 10.1016/S2213-2600(21)00103-X 33872590 94. Lingeswaran M Goyal T Ghosh R Suri S Mitra P Misra S Inflammation, Immunity and Immunogenetics in COVID-19: a narrative review Indian J Clin Biochem IJCB. 2020 35 260 273 10.1007/s12291-020-00897-3 32641873 95. Brudno JN Kochenderfer JN Recent advances in CAR T-cell toxicity: Mechanisms, manifestations and management Blood Rev 2019 34 45 55 10.1016/j.blre.2018.11.002 30528964 96. Veiga VC Prats JAGG Farias DLC Rosa RG Dourado LK Zampieri FG Effect of tocilizumab on clinical outcomes at 15 days in patients with severe or critical coronavirus disease 2019: randomised controlled trial BMJ 2021 372 n84 10.1136/bmj.n84 33472855 97. Salama C Han J Yau L Reiss WG Kramer B Neidhart JD Tocilizumab in patients hospitalized with Covid-19 pneumonia N Engl J Med 2021 384 20 30 10.1056/NEJMoa2030340 33332779 98. Gordon AC Mouncey PR Al-Beidh F Rowan KM Nichol AD REMAP-CAP Investigators Interleukin-6 receptor antagonists in critically ill patients with Covid-19 N Engl J Med 2021 384 1491 1502 10.1056/NEJMoa2100433 33631065 99. Gupta S Wang W Hayek SS Chan L Mathews KS Melamed ML Association between early treatment with tocilizumab and mortality among critically ill patients with COVID-19 JAMA Intern Med 2021 181 41 51 10.1001/jamainternmed.2020.6252 33080002 100. Hermine O Mariette X Tharaux P-L Resche-Rigon M Porcher R Ravaud P Effect of tocilizumab vs usual care in adults hospitalized with COVID-19 and moderate or severe pneumonia: a randomized clinical trial JAMA Intern Med 2021 181 32 40 10.1001/jamainternmed.2020.6820 33080017 101. Matthay MA Luetkemeyer AF IL-6 receptor antagonist therapy for patients hospitalized for COVID-19: who, when, and how? JAMA 2021 326 483 485 10.1001/jama.2021.11121 34228779 102. Georgiev T Angelov AK Complexities of diagnosis and management of COVID-19 in autoimmune diseases: potential benefits and detriments of immunosuppression World J Clin Cases. 2020 8 3669 3678 10.12998/wjcc.v8.i17.3669 32953843 103. Singh TU Parida S Lingaraju MC Kesavan M Kumar D Singh RK Drug repurposing approach to fight COVID-19 Pharmacol Rep PR. 2020 72 1479 1508 10.1007/s43440-020-00155-6 32889701 104. Damiani I Corsini A Bellosta S Potential statin drug interactions in elderly patients: a review Expert Opin Drug Metab Toxicol 2020 16 1133 1145 10.1080/17425255.2020.1822324 32909838 105. Gustine JN Jones D Immunopathology of hyperinflammation in COVID-19 Am J Pathol 2021 191 4 17 10.1016/j.ajpath.2020.08.009 32919977 106. Pandolfi L Fossali T Frangipane V Bozzini S Morosini M D’Amato M Broncho-alveolar inflammation in COVID-19 patients: a correlation with clinical outcome BMC Pulm Med 2020 20 301 10.1186/s12890-020-01343-z 33198751 107. McGonagle D Ramanan AV Bridgewood C Immune cartography of macrophage activation syndrome in the COVID-19 era Nat Rev Rheumatol 2021 17 145 157 10.1038/s41584-020-00571-1 33547426 108. Salvati L Occhipinti M Gori L Ciani L Mazzoni A Maggi L Pulmonary vascular improvement in severe COVID-19 patients treated with tocilizumab Immunol Lett 2020 228 122 128 10.1016/j.imlet.2020.10.009 33161002 109. Manti S Parisi GF Papale M Mulè E Aloisio D Rotolo N Looking beyond pulmonary disease in COVID-19: a lesson from patients with cystic fibrosis Med Hypotheses 2021 147 110481 10.1016/j.mehy.2020.110481 33421691 110. Somers EC, Eschenauer GA, Troost JP, Golob JL, Gandhi TN, Wang L, et al. Tocilizumab for treatment of mechanically ventilated patients with COVID-19. Clin Infect Dis Off Publ Infect Dis Soc Am. 2020;(2):e445-e454 111. Rossotti R Travi G Ughi N Corradin M Baiguera C Fumagalli R Safety and efficacy of anti-il6-receptor tocilizumab use in severe and critical patients affected by coronavirus disease 2019: A comparative analysis J Infect 2020 81 e11 e17 10.1016/j.jinf.2020.07.008 112. Petrak RM Van Hise NW Skorodin NC Fliegelman RM Chundi V Didwania V Early tocilizumab dosing is associated with improved survival in critically ill patients infected with severe acute respiratory syndrome coronavirus-2 Crit Care Explor. 2021 3 e0395 10.1097/CCE.0000000000000395 33817660 113. Roumier M Paule R Vallée A Rohmer J Ballester M Brun A-L Tocilizumab for severe worsening COVID-19 pneumonia: a propensity score analysis J Clin Immunol 2021 41 303 314 10.1007/s10875-020-00911-6 33188624 114. Rezaei S, Fatemi B, Karimi Majd Z, Minaei H, Peikanpour M, Anjidani N, et al. Efficacy and safety of tocilizumab in severe and critical COVID-19: a systematic review and meta-analysis. Expert Rev Clin Immunol. 2021;5:1-13 115. Biran N Ip A Ahn J Go RC Wang S Mathura S Tocilizumab among patients with COVID-19 in the intensive care unit: a multicentre observational study Lancet Rheumatol. 2020 2 e603 e612 10.1016/S2665-9913(20)30277-0 32838323 116. Price CC Altice FL Shyr Y Koff A Pischel L Goshua G Tocilizumab treatment for cytokine release syndrome in hospitalized patients with coronavirus disease 2019: survival and clinical outcomes Chest 2020 158 1397 1408 10.1016/j.chest.2020.06.006 32553536 117. Rossi ND, Scarpazza C, Filippini C, Cordioli C, Rasia S, Mancinelli CR, et al. Early use of low dose tocilizumab in patients with COVID-19: a retrospective cohort study with a complete follow-up. EClinicalMedicine [Internet]. Elsevier; 2020 [cited 2021 Aug 3];25. Accessed Aug 2021. https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(20)30203-0/abstract. 118. Rojas-Marte G Khalid M Mukhtar O Hashmi AT Waheed MA Ehrlich S Outcomes in patients with severe COVID-19 disease treated with tocilizumab: a case-controlled study QJM Mon J Assoc Physicians. 2020 113 546 550 10.1093/qjmed/hcaa206 119. Kimmig LM Wu D Gold M Pettit NN Pitrak D Mueller J IL-6 inhibition in critically ill COVID-19 patients is associated with increased secondary infections Front Med 2020 7 583897 10.3389/fmed.2020.583897 120. Merchante N, Cárcel S, Garrido-Gracia JC, Trigo-Rodríguez M, Esteban Moreno MÁ, León-López R, et al. Early use of sarilumab in patients hospitalised with COVID-19 pneumonia and features of systemic inflammation. Antimicrob Agents Chemother. 2021; vol. 2, p. AAC0210721. 121. Mariette X Hermine O Tharaux P-L Resche-Rigon M Porcher R Ravaud P Sarilumab in adults hospitalised with moderate-to-severe COVID-19 pneumonia (CORIMUNO-SARI-1): An open-label randomised controlled trial Lancet Rheumatol 2022 4 e24 32 10.1016/S2665-9913(21)00315-5 34812424 122. Hermine O, Mariette X, Porcher R, Resche-Rigon M, Tharaux P-L, Ravaud P, et al. Effect of interleukin-6 receptor antagonists in critically ill adult patients with COVID-19 pneumonia: two randomised controlled trials of the CORIMUNO-19 collaborative group. Eur Respir J. 2022; vol. 2: p. 2102523. 123. WHO Working Group on the Clinical Characterisation and Management of COVID-19 infection A minimal common outcome measure set for COVID-19 clinical research Lancet Infect Dis 2020 20 e192 e197 10.1016/S1473-3099(20)30483-7 32539990 124. Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial. The Lancet [Internet]. [cited 2021 May 23]. Accessed Aug 2021. https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(21)00676-0/fulltext. 125. Rosas IO Diaz G Gottlieb RL Lobo SM Robinson P Hunter BD Tocilizumab and remdesivir in hospitalized patients with severe COVID-19 pneumonia: a randomized clinical trial Intensive Care Med 2021 47 1258 1270 10.1007/s00134-021-06507-x 34609549 126. Hermine O Mariette X Porcher R Djossou F Nguyen Y Arlet J-B Tocilizumab plus dexamethasone versus dexamethasone in patients with moderate-to-severe COVID-19 pneumonia: a randomised clinical trial from the CORIMUNO-19 study group EClinicalMedicine. 2022 46 101362 10.1016/j.eclinm.2022.101362 35350097 127. Abani O Abbas A Abbas F Abbas M Abbasi S Abbass H Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial The Lancet 2021 397 1637 1645 10.1016/S0140-6736(21)00676-0 128. Scully EP Haverfield J Ursin RL Tannenbaum C Klein SL Considering how biological sex impacts immune responses and COVID-19 outcomes Nat Rev Immunol 2020 20 442 447 10.1038/s41577-020-0348-8 32528136 129. Bunders MJ Altfeld M Implications of sex differences in immunity for SARS-CoV-2 pathogenesis and design of therapeutic interventions Immunity 2020 53 487 495 10.1016/j.immuni.2020.08.003 32853545 130. Chi Y Ge Y Wu B Zhang W Wu T Wen T Serum cytokine and chemokine profile in relation to the severity of coronavirus disease 2019 in China J Infect Dis 2020 222 746 754 10.1093/infdis/jiaa363 32563194 131. Li Y Jerkic M Slutsky AS Zhang H Molecular mechanisms of sex bias differences in COVID-19 mortality Crit Care 2020 24 405 10.1186/s13054-020-03118-8 32646459 132. Kovats S Estrogen receptors regulate innate immune cells and signaling pathways Cell Immunol 2015 294 63 69 10.1016/j.cellimm.2015.01.018 25682174 133. Dhindsa S Zhang N McPhaul MJ Wu Z Ghoshal AK Erlich EC Association of circulating sex hormones with inflammation and disease severity in patients with COVID-19 JAMA Netw Open 2021 4 e2111398 10.1001/jamanetworkopen.2021.11398 34032853 134. Bouadma L Mekontso-Dessap A Burdet C Merdji H Poissy J Dupuis C High-dose dexamethasone and oxygen support strategies in intensive care unit patients with severe COVID-19 acute hypoxemic respiratory failure: the COVIDICUS randomized clinical trial JAMA Intern Med [Internet] 2022 10.1001/jamainternmed.2022.2168 135. Bersanelli M Controversies about COVID-19 and anticancer treatment with immune checkpoint inhibitors. Immunotherapy Future Med 2020 12 269 273 136. Lauder SN Jones E Smart K Bloom A Williams AS Hindley JP Interleukin-6 limits influenza-induced inflammation and protects against fatal lung pathology Eur J Immunol 2013 43 2613 2625 10.1002/eji.201243018 23857287 137. Hunter CA Jones SA IL-6 as a keystone cytokine in health and disease Nat Immunol 2015 16 448 457 10.1038/ni.3153 25898198 138. Xu C Rafique A Potocky T Paccaly A Nolain P Lu Q Differential binding of sarilumab and tocilizumab to IL-6Rα and effects of receptor occupancy on clinical parameters J Clin Pharmacol 2021 61 714 724 10.1002/jcph.1795 33314148 139. Cl V, Pj G, D F, Jpt H, F S, J S, et al. Association between administration of IL-6 antagonists and mortality among patients hospitalized for COVID-19: a meta-analysis. JAMA [Internet]. JAMA; 2021 [cited 2022 Jan 18];326. Accessed April 2021 .https://pubmed.ncbi.nlm.nih.gov/34228774/. 140. Ghosn L Chaimani A Evrenoglou T Davidson M Graña C Schmucker C Interleukin-6 blocking agents for treating COVID-19: a living systematic review Cochrane Database Syst Rev 2021 3 CD013881 33734435 141. Pinzon RT Wijaya VO Buana RB Interleukin-6 (IL-6) inhibitors as therapeutic agents for coronavirus disease 2019 (COVID-19): a systematic review and meta-analysis J Infect Public Health 2021 14 1001 1009 10.1016/j.jiph.2021.06.004 34153723 142. Snow TAC Saleem N Ambler G Nastouli E Singer M Arulkumaran N Tocilizumab in COVID-19: a meta-analysis, trial sequential analysis, and meta-regression of randomized-controlled trials Intensive Care Med 2021 47 641 652 10.1007/s00134-021-06416-z 34019122 143. Hariyanto TI Hardyson W Kurniawan A Efficacy and safety of tocilizumab for coronavirus disease 2019 (Covid-19) patients: a systematic review and meta-analysis Drug Res 2021 71 265 274 10.1055/a-1336-2371 144. Kow CS Hasan SS The effect of tocilizumab on mortality in hospitalized patients with COVID-19: a meta-analysis of randomized controlled trials Eur J Clin Pharmacol 2021 77 1089 1094 10.1007/s00228-021-03087-z 33532896 145. Juul S Nielsen EE Feinberg J Siddiqui F Jørgensen CK Barot E Interventions for treatment of COVID-19: second edition of a living systematic review with meta-analyses and trial sequential analyses (The LIVING Project) PLoS ONE 2021 16 e0248132 10.1371/journal.pone.0248132 33705495 146. Khan FA Stewart I Fabbri L Moss S Robinson K Smyth AR Systematic review and meta-analysis of anakinra, sarilumab, siltuximab and tocilizumab for COVID-19 Thorax 2021 76 907 919 10.1136/thoraxjnl-2020-215266 33579777 147. Lin W-T Hung S-H Lai C-C Wang C-Y Chen C-H The effect of tocilizumab on COVID-19 patient mortality: a systematic review and meta-analysis of randomized controlled trials Int Immunopharmacol 2021 96 107602 10.1016/j.intimp.2021.107602 33812260 148. Chen C-X Hu F Wei J Yuan L-T Wen T-M Gale RP Systematic review and meta-analysis of tocilizumab in persons with coronavirus disease-2019 (COVID-19) Leukemia 2021 35 1661 1670 10.1038/s41375-021-01264-8 34002026 149. Gupta S Padappayil RP Bansal A Daouk S Brown B Tocilizumab in patients hospitalized with COVID-19 pneumonia: systematic review and meta-analysis of randomized controlled trials J Investig Med Off Publ Am Fed Clin Res. 2022 70 55 60 150. Tleyjeh IM Kashour Z Riaz M Hassett L Veiga VC Kashour T Efficacy and safety of tocilizumab in COVID-19 patients: a living systematic review and meta-analysis, first update Clin Microbiol Infect Off Publ Eur Soc Clin Microbiol Infect Dis. 2021 27 1076 1082 151. Selvaraj V Khan MS Bavishi C Dapaah-Afriyie K Finn A Lal A Tocilizumab in Hospitalized Patients with COVID-19: A Meta Analysis of Randomized Controlled Trials Lung 2021 199 239 248 10.1007/s00408-021-00451-9 34050796 152. Tharmarajah E Buazon A Patel V Hannah JR Adas M Allen VB IL-6 inhibition in the treatment of COVID-19: A meta-analysis and meta-regression J Infect 2021 82 178 185 10.1016/j.jinf.2021.03.008 33745918 153. Aziz M Haghbin H Abu Sitta E Nawras Y Fatima R Sharma S Efficacy of tocilizumab in COVID-19: a systematic review and meta-analysis J Med Virol 2021 93 1620 1630 10.1002/jmv.26509 32918755 154. Maraolo AE Crispo A Piezzo M Di Gennaro P Vitale MG Mallardo D The Use of tocilizumab in patients with COVID-19: a systematic review, meta-analysis and trial sequential analysis of randomized controlled studies J Clin Med 2021 10 4935 10.3390/jcm10214935 34768455 155. Avni T Leibovici L Cohen I Atamna A Guz D Paul M Tocilizumab in the treatment of COVID-19-a meta-analysis QJM Mon J Assoc Physicians. 2021 114 577 586 10.1093/qjmed/hcab142 156. Kyriakopoulos C Ntritsos G Gogali A Milionis H Evangelou E Kostikas K Tocilizumab administration for the treatment of hospitalized patients with COVID-19: a systematic review and meta-analysis Respirol Carlton Vic. 2021 26 1027 1040 10.1111/resp.14152 157. Nugroho CW Suryantoro SD Yuliasih Y Rosyid AN Asmarawati TP Andrianto L Optimal use of tocilizumab for severe and critical COVID-19: a systematic review and meta-analysis F1000Research. 2021 10 73 10.12688/f1000research.45046.1 33763201 158. Wei Q Lin H Wei R-G Chen N He F Zou D-H Tocilizumab treatment for COVID-19 patients: a systematic review and meta-analysis Infect Dis Poverty 2021 10 71 10.1186/s40249-021-00857-w 34001244 159. Alkofide H Almohaizeie A Almuhaini S Alotaibi B Alkharfy KM Tocilizumab and systemic corticosteroids in the management of patients with COVID-19: a systematic review and meta-analysis Int J Infect Dis IJID Off Publ Int Soc Infect Dis. 2021 110 320 329 160. Zhang C Jin H Wen YF Yin G Efficacy of COVID-19 treatments: a bayesian network meta-analysis of randomized controlled trials Front Public Health 2021 9 729559 10.3389/fpubh.2021.729559 34650951 161. Albuquerque AM Tramujas L Sewanan LR Williams DR Brophy JM Mortality rates among hospitalized patients with COVID-19 infection treated with tocilizumab and corticosteroids: a Bayesian Reanalysis of a Previous Meta-analysis JAMA Netw Open 2022 5 e220548 10.1001/jamanetworkopen.2022.0548 35226077 162. Mutua V Henry BM von Csefalvay C Cheruiyot I Vikse J Lippi G Tocilizumab in addition to standard of care in the management of COVID-19: a meta-analysis of RCTs Acta Bio-Medica Atenei Parm. 2022 93 e2022014 163. Sarfraz A Sarfraz Z Sarfraz M Aftab H Pervaiz Z Tocilizumab and COVID-19: a meta-analysis of 2120 patients with severe disease and implications for clinical trial methodologies Turk J Med Sci. 2021 51 890 897 10.3906/sag-2010-131 33244947 164. Mahroum N Watad A Bridgewood C Mansour M Nasr A Hussein A Systematic review and meta-analysis of tocilizumab therapy versus standard of care in over 15,000 COVID-19 pneumonia patients during the first eight months of the pandemic Int J Environ Res Public Health 2021 18 9149 10.3390/ijerph18179149 34501738 165. Rubio-Rivas M Forero CG Mora-Luján JM Montero A Formiga F Homs NA Beneficial and harmful outcomes of tocilizumab in severe COVID-19: a systematic review and meta-analysis Pharmacotherapy 2021 41 884 906 10.1002/phar.2627 34558742 166. Murthy S, Lee TC. IL-6 blockade for COVID-19: a global scientific call to arms. Lancet Respir Med. 2021 May;9(5):438-440. 167. Rose-John S Winthrop K Calabrese L The role of IL-6 in host defence against infections: immunobiology and clinical implications Nat Rev Rheumatol 2017 13 399 409 10.1038/nrrheum.2017.83 28615731 168. Strohbehn GW Heiss BL Rouhani SJ Trujillo JA Yu J Kacew AJ COVIDOSE: a phase II clinical trial of low-dose tocilizumab in the treatment of noncritical COVID-19 pneumonia Clin Pharmacol Ther 2021 109 688 696 10.1002/cpt.2117 33210302 169. Diaz RM, García MAA, Muñoz FJT, Perez LES, Gonzalez MM, Bermejo JAM, et al. Does timing matter on tocilizumab administration? Clinical, analytical and radiological outcomes in COVID-19. Eur J Hosp Pharm [Internet]. British Medical Journal Publishing Group; 2021 [cited 2021 Aug 3]. Accessed April 2021. https://ejhp.bmj.com/content/early/2021/04/18/ejhpharm-2020-002669. 170. Rostami M Khoshnegah Z Mansouritorghabeh H Hemostatic system (Fibrinogen Level, D-Dimer, and FDP) in severe and non-severe patients with COVID-19: a systematic review and meta-analysis Clin Appl Thromb Off J Int Acad Clin Appl Thromb. 2021 27 10760296211010972 171. Schiff MH Kremer JM Jahreis A Vernon E Isaacs JD van Vollenhoven RF Integrated safety in tocilizumab clinical trials Arthritis Res Ther 2011 13 R141 10.1186/ar3455 21884601 172. Strand V Ahadieh S French J Geier J Krishnaswami S Menon S Systematic review and meta-analysis of serious infections with tofacitinib and biologic disease-modifying antirheumatic drug treatment in rheumatoid arthritis clinical trials Arthritis Res Ther 2015 17 362 10.1186/s13075-015-0880-2 26669566 173. Buetti N Ruckly S de Montmollin E Reignier J Terzi N Cohen Y COVID-19 increased the risk of ICU-acquired bloodstream infections: a case-cohort study from the multicentric OUTCOMEREA network Intensive Care Med 2021 47 180 187 10.1007/s00134-021-06346-w 33506379 174. Angus DC van der Poll T Severe sepsis and septic shock N Engl J Med 2013 369 840 851 10.1056/NEJMra1208623 23984731 175. Hotchkiss RS Monneret G Payen D Sepsis-induced immunosuppression: from cellular dysfunctions to immunotherapy Nat Rev Immunol 2013 13 862 874 10.1038/nri3552 24232462 176. Schulte-Schrepping J Reusch N Paclik D Baßler K Schlickeiser S Zhang B Severe COVID-19 is marked by a dysregulated myeloid cell compartment Cell 2020 182 1419 1440.e23 10.1016/j.cell.2020.08.001 32810438 177. Wilk AJ Rustagi A Zhao NQ Roque J Martínez-Colón GJ McKechnie JL A single-cell atlas of the peripheral immune response in patients with severe COVID-19 Nat Med 2020 26 1070 1076 10.1038/s41591-020-0944-y 32514174 178. Modabber Z Shahbazi M Akbari R Bagherzadeh M Firouzjahi A Mohammadnia-Afrouzi M TIM-3 as a potential exhaustion marker in CD4+ T cells of COVID-19 patients Immun Inflamm Dis. 2021 9 1707 1715 10.1002/iid3.526 34499819 179. Cifaldi L Prencipe G Caiello I Bracaglia C Locatelli F De Benedetti F Inhibition of natural killer cell cytotoxicity by interleukin-6: implications for the pathogenesis of macrophage activation syndrome Arthritis Rheumatol Hoboken NJ 2015 67 3037 3046 10.1002/art.39295 180. Wu J Gao F-X Wang C Qin M Han F Xu T IL-6 and IL-8 secreted by tumour cells impair the function of NK cells via the STAT3 pathway in oesophageal squamous cell carcinoma J Exp Clin Cancer Res CR. 2019 38 321 10.1186/s13046-019-1310-0 31324197 181. Diao B Wang C Tan Y Chen X Liu Y Ning L Reduction and functional exhaustion of T Cells in patients with coronavirus disease 2019 (COVID-19) Front Immunol 2020 11 827 10.3389/fimmu.2020.00827 32425950 182. Annane D Bellissant E Bollaert PE Briegel J Keh D Kupfer Y Corticosteroids for treating sepsis in children and adults Cochrane Database Syst Rev [Internet] 2019 10.1002/14651858.CD002243.pub4/full/fr 183. Chaudhuri D Sasaki K Karkar A Sharif S Lewis K Mammen MJ Corticosteroids in COVID-19 and non-COVID-19 ARDS: a systematic review and meta-analysis Intensive Care Med 2021 47 521 537 10.1007/s00134-021-06394-2 33876268 184. Interleukin-6 Inhibitors [Internet]. COVID-19 Treat. Guidel. [cited 2021 Aug 13]. Accessed Aug 2021. https://www.covid19treatmentguidelines.nih.gov/therapies/immunomodulators/interleukin-6-inhibitors/. 185. Chalmers JD, Crichton ML, Goeminne PC, Cao B, Humbert M, Shteinberg M, et al. Management of hospitalised adults with coronavirus disease-19 (COVID-19): a European Respiratory Society living guideline. Eur Respir J [Internet]. European Respiratory Society; 2021 [cited 2021 May 23]. Accessed Aug 2021. https://erj.ersjournals.com/content/early/2021/03/07/13993003.00048-2021.
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==== Front J Risk Uncertain J Risk Uncertain Journal of Risk and Uncertainty 0895-5646 1573-0476 Springer US New York 9396 10.1007/s11166-022-09396-7 Article Seen and not seen: How people judge ambiguous behavior during the COVID-19 pandemic http://orcid.org/0000-0002-4341-9659 Molnar Andras [email protected] 1 Moore Alex [email protected] 1 Fowler Carman [email protected] 2 Wu George [email protected] 1 1 grid.170205.1 0000 0004 1936 7822 Booth School of Business, University of Chicago, Chicago, USA 2 grid.26009.3d 0000 0004 1936 7961 Fuqua School of Business, Duke University, Durham, USA 12 12 2022 119 27 9 2022 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. How do we judge others’ behavior when they are both seen and not seen—when we observe their behavior but not the underlying traits or history that moderate the perceived riskiness of their behavior? We investigate this question in the context of the COVID-19 pandemic: How people make sense of, and judge, vaccination-contingent behaviors—behaviors, such as going to the gym or a bar, which are considered to be more or less risky and appropriate, depending on the target’s vaccination status. While decision theoretic models suggest that these judgments should depend on the probability that the target is vaccinated (e.g., the positivity of judgments should increase linearly with the probability of vaccination), in a large-scale pre-registered experiment (N = 936) we find that both riskiness and appropriateness judgments deviate substantially from such normative benchmarks. Specifically, when participants judge a stranger’s behavior, without being asked to think about the stranger’s vaccination status, they tend to judge these behaviors similarly positively to behaviors of others who are known to be fully vaccinated. By contrast, when participants are explicitly prompted to think about the vaccination status of others, they do so, leading them to view others more disparagingly, at times even more negatively than what a normative benchmark would imply. More broadly, these results suggest new directions for research on how people respond to risk and ambiguity. We demonstrate that even subtle cues can fundamentally alter what information is “top of mind,” that is, what information is included or excluded when making judgments. Supplementary Information The online version contains supplementary material available at 10.1007/s11166-022-09396-7. Keywords COVID-19 Pandemic Ambiguity Uncertainty Vaccination status Attributions JEL classification: D81 D91 I12 I18 ==== Body pmcIntroduction On May 13, 2021, the United States Center for Disease Control and Prevention (CDC) changed its guidelines such that: “fully vaccinated people no longer need to wear a mask or physically distance in any setting.”1 The new guidelines surprised and confused many observers. The guidance was not only a radical departure from previous recommendations, but the absence of vaccination passports and other methods of verifying vaccination status in the United States made behavior a matter of trust. Lisa Maragakis, a John Hopkins epidemiologist, summed this up: “The guidance shifts all the burden onto individuals to be ‘on their honor’ and choose the appropriate actions when deciding whether to wear a mask. There is no way to know who is vaccinated and who is not in most scenarios.”2 The COVID-19 pandemic has undoubtedly transformed life. In much of 2020 and 2021, everyday social activities—as mundane as drinking at a bar to giving a friend a hug—were deemed inappropriate, putting others at unnecessary risk. But as vaccination against COVID-19 has become widespread, these judgments have become contingent on vaccination status. While it was once generally viewed as inappropriate for anyone to go to the bar, for many, it is now inappropriate only for the unvaccinated to do so. Vaccination status, though, is largely private. In most circumstances, people are “seen and not seen,” that is, even though we can clearly observe their behaviors, we cannot tell whether they are vaccinated or not. Given this ambiguity about vaccination status, how do we make sense of, and judge, behaviors that are appropriate when vaccinated but inappropriate otherwise? And how do we think about the risks that these behaviors pose to the people around them? As the world transitions out of the COVID-19 pandemic, the ways people judge others’ behaviors in these ambiguous situations has implications for how individuals engage with each other and whether these interactions are contentious or civil. In turn, perceptions of risk caused by these behaviors will also affect whether people enter or refrain from public spaces in which the vaccination status of others is not known or ambiguous. In this paper, we examine behaviors, such as going to the gym or a bar, which are judged more appropriate if the target of the judgment is vaccinated, as opposed to unvaccinated. For the remainder of this article, when we refer to judgment, we mean judgments of the appropriateness (or riskiness) of a behavior. Normatively, the favorability of these judgments should increase with the likelihood that the target is vaccinated. For example, when 70% of the population in an area is vaccinated, people ought to judge strangers (whose vaccination status is unknown to observers) drinking at the bar as behaving more appropriately than in an area where only 15% are vaccinated. We document a pattern of evaluation that departs, at times dramatically, from this normative benchmark. Let b be a behavior, and V and V¯, indicate that a person is vaccinated or unvaccinated, respectively.3 We denote J(b) to be the judgment of behavior b, where higher values indicate a more favorable evaluation. A behavior is a vaccination-contingent behavior if J(b|V)>J(b|V¯), i.e., a vaccinated person engaging in behavior b is judged more favorably than someone who is unvaccinated. Furthermore, let p=Pr(V|b) denote an observer’s belief about the conditional probability of a target being vaccinated given that they are engaging in behavior b. Note that Pr(V|b) may be the same, higher, or lower than the prior or unconditional probability of someone being vaccinated in a target population, Pr(V). Importantly, although observers’ subjective probability estimates may or may not be accurate, our comparison of judgments to the normative benchmark merely requires that judgments be consistent with the observers’ own (subjective) probability estimates. In a complex and dynamically changing social situation, such as the current global pandemic, one could argue that a variety of judgments are normative. In this article, we use the probability-weighted average of the judgment of vaccinated and unvaccinated individuals as this normative benchmark of judging a behavior b under uncertainty. We do not imply that all people ought to make these judgments in this fashion, but this approach provides a straightforward way to compare observed judgments to a standard. At the same time, it is reasonable to assume that many normative rules for judgment, particularly consequentialist ones, ought to include the probability of vaccination in some way, and this probability-weighted averaging is the simplest possible rule that reflects this. We define the probability-weighted normative standard in the following way:1 p×J(b|V)+(1-p)×J(b|V¯). As p gets close to 1 (an observer believes it is almost certain that a target is vaccinated), Eq. (1) approaches J(b|V), the judgment of someone known to be vaccinated. Similarly, as p nears 0, the target person should be viewed the same as an unvaccinated individual, J(b|V¯). To understand how participants think about appropriateness and risk in uncertain situations, we compare judgments of the appropriateness and the riskiness of behaviors to the normative benchmark defined in Eq. (1). To do this, we compare participants’ judgments when they have full knowledge of vaccination status (either vaccinated in the “vaccinated” condition or unvaccinated in the “unvaccinated” condition) with cases where vaccination status is ambiguous. Specifically, we compare judgments made under full knowledge with those made when nothing about a target’s vaccination status is indicated (“no information” condition), as well as judgments of targets whose vaccination status we explicitly describe as “unknown” (“unknown status” condition) and targets who are equally likely to be vaccinated or unvaccinated (“50-50” condition). We document judgments under uncertainty that differ substantially from the normative benchmark that relies on a linear probability weighting model. Although the “no information” and “unknown status” conditions are identical with respect to the information conveyed, evaluations of the target vary dramatically, with evaluations in the “no information” being significantly more positive (i.e., generally appropriate and posing relatively little risk to others) than evaluations in the “unknown status.” Apparently, the normatively relevant consideration of a person’s vaccination status does not reliably come to mind unless prompted, leading to, in most cases, overly generous judgments of targets engaging in vaccination-contingent behaviors. Judgments are more critical when participants are reminded to think about vaccination status in the “unknown status” condition. These judgments sometimes cohere with the normative benchmark, but when the judgments depart from it, evaluations tend to be disparaging and closer to the evaluations of unvaccinated targets (i.e., generally inappropriate and posing relatively high risk). Our paper proceeds as follows. In Sect. 2, we present the materials and methods, while Sect. 3 describes the results. In Sect. 4, we discuss how our findings build on previous empirical findings about dealing with uncertainty and ambiguity and the prevalence of non-consequentialist reasoning. Finally, in Sect. 5, we conclude by discussing some of the implications of our results. Method Participants We recruited 936 participants on Prolific (https://prolific.co). The eligibility criteria for the study were that participants must be at least 18 years old and residing in the United States. Participants could complete the experiment only once. Among recruited participants, 16 (1.7%) quit the study before finishing it. Of the 920 participants who completed the study, we excluded 148 participants (16.1%) from the data analyses: 13 (1.4%) who failed the attention check and 135 (14.7%) who indicated that they had not received a COVID-19 vaccine and were not intending to get vaccinated (“vaccine hesitants”). We excluded this latter group of individuals because a pilot survey indicated that many of these people had incorrect beliefs about the efficacy and riskiness of vaccination (i.e., believing that being vaccinated against COVID-19 does not change, or even increases, the risk posed to others), and also made disparaging judgments about the appropriateness of the behaviors of those who had been fully vaccinated. The main results we report later may not generalize to the entire population due to the exclusion of these participants who were not planning on getting vaccinated, since our analyses do not capture the judgments of this group.4 These exclusion criteria, as well as the intended sample size and the data collection stopping rule were pre-registered at AsPredicted.org.5 The final sample contained 772 responses (52.3% female; Mage=32.8 years). Participants received a fixed compensation of $2 in exchange for completing an online survey that took between 5–10 minutes (M=8.1 min). Procedure Participants were directed to a Qualtrics survey, which had three main parts. In the first part of the survey, participants were asked to imagine situations in which they saw another person in their community engaging in various behaviors. For example, participants read the following: “Imagine that you just saw a person in your community going to an indoor bar.” Then, depending on the experimental condition (see Sect. 2.3), participants were asked to judge how appropriate (“Appropriateness” conditions) or how risky these behaviors were (“Risk” conditions). In total, participants read 16 scenarios, each describing a different behavior: eight behaviors which we hypothesized were affected by COVID-19 (e.g., going to a bar, hugging friends; see Table 1 top panel) and eight which we surmised were not affected by COVID-19 but were risky or violated a social norm (e.g., speeding, littering; see Table 1 bottom panel). Participants were presented with one behavior at a time and had to rate the appropriateness or riskiness of that behavior before proceeding to the next behavior. The order of the 16 behaviors was randomized. In addition, we included an attention check question during the presentation of these behaviors, to which participants had to provide a specific response. As pre-registered, we excluded all participants who failed to comply with the instructions of this attention check. In the second part of the survey, participants were given the same set of eight COVID-19 behaviors (Table 1 top panel) and were asked to estimate the percent chance (0% to 100%) that a person engaging in each of these behaviors has been fully vaccinated against COVID-19.6 In the third and final part, participants answered a set of COVID-19-related questions:“How worried are you about COVID-19 in general?” “How worried are you personally about contracting COVID-19?” “Do you have any pre-existing conditions that put you at a higher risk of COVID-19?” “Do you currently live with anyone who has a pre-existing condition that puts them at a higher risk of COVID-19?” “What is your COVID-19 vaccination status?” “During the COVID-19 pandemic, are you working from home?” “How comfortable are you getting one of the currently available COVID-19 vaccines?” “How knowledgeable would you say you are about the COVID-19 virus?” “Have you, or any family members, been diagnosed with COVID-19?” In addition to the above questions, participants provided an estimate of the proportion of the eligible population that have been fully vaccinated at the time of the survey (May 17–20, 2021): 1) in their state; and 2) within their ZIP code. Finally, participants provided their demographic information: age, gender, ethnicity, ZIP code, household size, number of children in household, highest level of education, political affiliation, and employment status.Table 1 Behaviors used in the judgment study Behaviors affected by COVID-19   1. Going to an indoor bar   2. Sitting at a coffee shop with other people, indoors   3. Eating at a restaurant with other people, indoors   4. Hugging when greeting a friend   5. Going to the gym   6. Greeting a friend with a fist bump   7. Having a picnic with friends, outdoors   8. Having a conversation with a friend on a park bench without a mask Behaviors NOT affected by COVID-19   1. Driving 15 miles per hour over the speed limit   2. Riding a bicycle without wearing a helmet   3. Driving a car without wearing a seat belt   4. Being so intoxicated that they had a hard time standing up   5. Smoking a cigarette in a non-smoking area   6. Not returning a shopping cart at a grocery store   7. Dropping an empty soda can on the street   8. Cutting in line at the supermarket checkout Top panel shows the list of eight behaviors affected by COVID-19. Bottom panel shows the list of eight behaviors hypothesized NOT to be affected by COVID-19. Participants rated the appropriateness (or riskiness) of all 16 behaviors, one at a time, in a randomized order Experimental manipulation and dependent measures The second and third parts (where participants were asked about conditional probabilities of vaccination and general questions related to COVID-19) were identical for all participants. However, we manipulated how the items were presented in the first part (where participants indicated their judgments of others’ behaviors). The study had a 2 (judgment type) × 5 (information type) between-subjects design, i.e., each participant was randomly assigned to one of 10 conditions. The first factor, judgment type, represents the type of judgments participants made when evaluating the set of 16 behaviors. In the “Appropriateness” conditions, participants were presented with the following question after each behavior: “How appropriate or inappropriate is this person’s behavior?” to which participants provided their responses on a 7-point Likert scale, ranging from “Extremely Inappropriate” to “Extremely Appropriate.” In the “Risk” conditions, participants were asked “How much or how little risk does this pose to others?” after each behavior, to which they provided their responses on a 7-point Likert scale, ranging from “No Risk” to “Very high Risk.” The second factor that we manipulated between subjects was the type of information provided about the vaccination status of the target person who engaged in the behaviors described in the scenarios. The five types of information were: “No information” conditions: There was no reference to the target person’s vaccination status. Participants in these conditions simply read about the target’s behavior and had to rate the appropriateness/riskiness of these behaviors. “Unknown status” conditions: Participants were told that the target’s vaccination status is unknown. “50-50” conditions: Participants were told that the target person is 50% likely to be vaccinated and 50% likely to be unvaccinated. “Vaccinated” conditions: Participants were told that the target person is fully vaccinated against COVID-19. “Unvaccinated” conditions: Participants were told that target person is not vaccinated against COVID-19. We refer to the first three conditions as the “uncertainty” conditions, because participants in these conditions do not know the vaccination status of the target. These conditions contrast with the final two conditions where participants are given the vaccination status of the person. Results Non-COVID behaviors We included the non-COVID behaviors as controls to ensure that our conditions only affected the judgments of COVID-related behaviors and not other risky and/or socially undesirable behaviors. We re-coded the Likert scale ratings of appropriateness and riskiness to range from -3 to +3, with 0 being a neutral value that divided appropriate and inappropriate behaviors and low and high risk behaviors. The means for all eight items, as well as the average of the eight items, and all 10 conditions are shown in the Appendix (Figs. A.1 and A.2). Across all information conditions, all eight of the non-COVID behaviors were judged as inappropriate, or below the midpoint of the 7-point Likert scale, while three of the behaviors were viewed as rather risky to others (speeding, being drunk, and smoking). Note that we treated these measures as continuous variables in the primary analyses reported in the subsequent sections. However, our primary results are robust to alternative analyses: We obtain almost identical results when we treat these measures as ordinal, using either ordered logit regression or logit regressions in which we dichotomize these measures using different cutoff points (i.e., +1, 0, or -1). We report the results of these robustness checks in the Appendix (see Figs. A.3–A.8 and Table B.4). We examine whether appropriateness and risk judgments among the control conditions vary by information about the target’s vaccination status. For simplicity, we consider the average of the eight behaviors. The five conditions yield 10 possible pairwise comparisons each for appropriateness and risk, i.e., 20 possible pairwise comparisons in total. We expected that judgments of these behaviors would not vary between conditions. Out of the 20 pairwise comparisons, none were significant at the conventional p<.05 level. We report the detailed test statistics for these comparisons in Table B.1 in the Appendix. COVID-19 behaviors We next turn to the eight COVID behaviors (see Figs. 1 and 2). We start by examining the “vaccinated” and “unvaccinated” conditions to test whether judgments of these behaviors are contingent on vaccination status. We let Ja(b) and Jr(b) denote the appropriateness and riskiness judgments of behavior b. For all of the COVID behaviors, Ja(b|V)>Ja(b|V¯) and Jr(b|V)>Jr(b|V¯), all ts >8.11, all ps <.001, confirming that the judgments of these behaviors are indeed vaccination-contingent (see green vs. red bars in Figs. 1 and 2). For all behaviors except for “greeting a friend with a fist bump,” behaviors for unvaccinated targets are seen as high risk (Jr(b|V¯)<0) and inappropriate (Ja(b|V¯)<0), whereas the same behavior for vaccinated individuals is viewed as low risk (Jr(b|V)>0) and appropriate (Ja(b|V)>0).Fig. 1 Mean appropriateness ratings for the eight COVID behaviors as well as the average of the eight behaviors across the five experimental conditions. Error bars indicate ± 1 standard error. We report the dichotomized versions of these measures (using cutoff points of +1, 0, and -1) in Figs. A.3–A.5 in the Appendix Fig. 2 Mean risk ratings for the eight COVID behaviors as well as the average of the eight behaviors across the five experimental conditions. Error bars indicate ± 1 standard error. We report the dichotomized versions of these measures (using cutoff points of +1, 0, and -1) in Figs. A.6–A.8 in the Appendix We also note the size of the difference in how people judge vaccinated and unvaccinated targets, Jr(b|V)-Jr(b|V¯) and Ja(b|V)-Ja(b|V¯). Across these eight items, the mean differences range from 1.58 to 2.87 for risk and 1.85 to 3.00 for appropriateness, where a positive difference means that people judge the behavior while vaccinated as more appropriate or less risky. As a comparison, the difference between judgments of an unvaccinated person going to a bar and an unvaccinated person greeting with a fist bump, the behaviors judged to be most and least inappropriate for an unvaccinated individual, is 1.69. We find that, on average, appropriateness and risk judgments are significantly more positive in the “no information” condition (grey bars in Figs. 1 and 2) than the “50-50” (orange bars) or “unknown status” conditions (black bars), all p<.001. We report the detailed test statistics for these comparisons in Table B.2 in the Appendix. Furthermore, for all behaviors with the exception of “having a conversation with a friend on a park bench without a mask,”7 appropriateness and risk judgments in the “no information” condition are significantly more positive than both the “unknown status” and “50-50” conditions, all p<.001 (see Table B.3 in the Appendix). Finally, as before, our results are almost identical when appropriateness and risk judgments are treated as ordinal variables. We report the results of these robustness checks in Table B.4 in the Appendix. Taken together, these results show that both appropriateness and risk judgments in the “no information” condition are overly generous, when participants are not prompted to think about vaccination status. We test whether these judgments significantly deviate from a normative benchmark in Sect. 3.4. Probability estimates In order to investigate whether judgments deviated from a normative benchmark (see Sect. 3.4), we asked participants to estimate the likelihood that someone engaging in each of the eight COVID-contingent behaviors was fully vaccinated. In addition, participants estimated the percentage of individuals in their state and ZIP code who were fully vaccinated. Figure 3 depicts these estimates. The mean estimates throughout were slightly higher than 38.3%, the actual proportion of Americans vaccinated as of May 20, 2021.8 Estimates of state-level vaccination rates were correlated with actual vaccination rates (r=.158,p<.001). Estimates for behaviors were also slightly higher than but close to the equal chance indicated in the “50-50” condition (Ms from 48.54 to 59.6). Also note that the mean estimates for the likelihood that a person engaging in a behavior is vaccinated, Pr(V|b), is higher than the mean estimates of the likelihood that eligible individuals in their ZIP code or state are vaccinated. It is noteworthy that probability estimates are positively related to judgments of appropriateness in the “unknown status” condition (t=4.16) but not in the “no information” condition (t=1.06).9 This relationship is consistent with the notion that individuals are sometimes sensitive to normatively relevant factors, in this case, the probability that a person is vaccinated, but these factors may not automatically come to mind.10Fig. 3 Mean estimates of the probability (percent chance) that a target person is fully vaccinated, when the target engages in each of the eight COVID-19-related behaviors. The figure also depicts the average estimate for the eight behaviors, as well as the estimate for the proportion of eligible individuals in their state and ZIP code. The dashed horizontal lines indicate the percentage of all (black) and eligible (red) Americans who were fully vaccinated as of May 20, 2021. Error bars indicate ± 1 standard error Deviations from the normative benchmark To test whether the judgments are different from the normative benchmark in Eq. (1), we construct an index for each behavior, each judgment type, and the uncertainty conditions. Let bi refer to behavior i, where i=1,...,9, and the first eight behaviors correspond to the COVID behaviors in Table 1 and i=9 is the average of the eight behaviors. Let Jt(bi|C) be the judgment of behavior i for the two judgment types t∈{a,r}, and the five information conditions, C∈{V,V¯,NI,UK,50-50}, where NI, UK, and 50-50 indicate the “no information,” “unknown status,” and “50-50” conditions, respectively. We denote the three uncertainty conditions as UC∈{NI,UK,50-50}. We construct an index:2 It(bi,UC)=Jt(bi|UC)-Jt(bi|V¯)Jt(bi|V)-Jt(bi|V¯). The index captures how close judgments for the uncertainty conditions are to the extreme judgments, vaccinated (It(bi,V)=1) and unvaccinated (It(bi,V¯)=0). Normatively, the statistic should be the same as Pr(bi|UC), which we take to be .5 for the “50-50” condition and the probability estimates described in Sect. 3.3 for the other conditions. Thus, we test the null hypothesis that the following statistic is 0:3 St(bi,UC)=It(bi,UC)-Pr(bi|UC)=Jt(bi|UC)-Jt(bi|V¯)Jt(bi|V)-Jt(bi|V¯)-Pr(bi|UC). To implement this test, we bootstrap St(bi,UC) for all behaviors (i=1,...,8) and the average of behaviors (i=9), appropriateness and riskiness measures (t∈{a,r}), and for the three uncertainty conditions (UC∈{NI,UK,50-50}). The bootstrapping procedure samples the three judgments in Eq. (2) as well as probability estimates for the “no information” and the “unknown status” conditions. For the “50-50” condition, .5 is used for the probability estimate. Positive values of this bootstrapped statistic St(bi,UC) correspond to overly generous judgments (i.e., more appropriate and less risky than what the normative benchmark would imply), whereas negative values of St(bi,UC) indicate overly disparaging judgments (i.e., less appropriate and more risky). Figures 4 and 5 depict point estimates and 95% bootstrapped confidence intervals based on 1, 000 samples for the appropriateness measure (Fig. 4) and the riskiness measure (Fig. 5). The statistical tests show that appropriateness and risk judgments for the “no information” condition are overly generous for all behaviors with the exception of conversation, while risk judgments for the “unknown status” and “50-50” conditions are for the large part disparaging. Finally, these effects are robust to demographic factors (e.g., gender, age, political affiliation), that is, participants judged others’ behavior significantly more generously in the “no information” condition than what a normative benchmark would imply, regardless of their demographic characteristics. We report the detailed results of these robustness check analyses in Appendix C.Fig. 4 Point estimates and 95% bootstrapped confidence intervals for the statistic in Eq. (3) for all eight COVID-19 behaviors and the average of behaviors with t=a (appropriateness measure) and for the “50-50,” “unknown status,” and the “no information” conditions. Positive values indicate overly generous judgments (more appropriate), whereas negative values indicate overly disparaging judgments (less appropriate), relative to the normative benchmark. CIs are based on n=1,000 samples Fig. 5 Point estimates and 95% bootstrapped confidence intervals for the statistic in Eq. (3) for all eight COVID-19 behaviors and the average of behaviors with t=r (riskiness measure) and for the “50-50,” “unknown status,” and the “no information” conditions. Positive values indicate overly generous judgments (less risky), whereas negative values indicate overly disparaging judgments (more risky), relative to the normative benchmark. CIs are based on n=1,000 samples Psychological explanations Weighted-average models are commonly employed in both economic and psychological models (e.g., Savage, 1954; von Neumann & Morgenstern, 1953; Coombs et al., 1970; Anderson, 1981). Our findings show significant departures from the normatively compelling model in which judgments under uncertainty are a probability-weighted average of judgments of vaccinated and unvaccinated targets (Eq. (1)). A long history of research in judgment and decision making has documented discrepancies between normative models, many of which are weighted-average models, and actual judgments and decisions (Edwards, 1954; Keren & Wu, 2015). We unpack the probability-weighted model and suggest that it relies on four distinct psychological assumptions: (Representation) Judges identify factors that are relevant for the judgment at hand. Here, it is assumed that judges recognize the relevance of vaccination status; (Probabilistic Sophistication) Judges make assessments of the probability of the critical factor and that these assessments satisfy the laws of probability theory. Here, it is assumed that judges assess Pr(V|b) and that Pr(V¯|b) and Pr(V|b)+Pr(V¯|b)=1; (Consequentialism) Judges make judgments or evaluations conditional on the relevant states of nature. Here, it is assumed that judges makes judgements about the appropriateness or riskiness of behavior, conditional on vaccination and non-vaccination, J(b|V) and J(b|V¯); (Integration) Judges combine (2) and (3) according to Eq. (1). Previous psychological findings call into question each of these steps. Judges identify the relevant factors Kahneman (2011) suggested that our mental model of a situation is often limited by how that situation is presented or what is top of mind (see also Slovic’s (1972) concreteness principle). As a result, factors that are relevant for making a decision may not factor into the process unless they are easily accessible. Kahneman’s notion that “What you see is all there is” was explored by Enke (2020). Enke found that participants’ inferences ignored how the data were generated. Participants made judgments that were close to the Bayesian benchmark when they were prompted to think about selection biases, but apparently selection effects in generating data did not come readily to mind. The differences in judgments between the informationally identical “unknown status” and “no information” conditions is consistent with this notion of a “lazy” mental model. They are also consistent with a broader set of findings that document how people fail to rely on important factors when making judgments. For example, people engage in non-probabilistic thinking in situations that call for considerations of likelihood (Rottenstreich & Kivetz, 2006), purchase less when taxes are made salient (Chetty et al., 2009), and are inattentive to missing, but relevant, information (Johnson & Levin, 1985; Sanbonmatsu et al., 1992; Gurney & Loewenstein, 2020). Judges make assessments that satisfy the laws of probability theory A large literature in cognitive psychology has documented biases in probabilistic reasoning (e.g., Kahneman et al., 1982). Individuals tend to use heuristics when engaged in probabilistic thinking, and these heuristics can lead to systematic biases such as attention to recent, salient, and vivid information (Tversky & Kahneman, 1973). Because we compare appropriateness and riskiness judgments under uncertainty to probability estimates, our investigation does not hinge on the accuracy of estimates of vaccination. It does rely, however, on probability estimates satisfying the basic laws of probability, in this case, additivity of probabilities: Pr(V|b)+Pr(V¯|b)=1. This condition, termed binary complementarity, has substantial empirical support (Tversky & Koehler, 1994). Judges make conditional judgments Although decision theoretic notions require that individuals think through all the relevant consequences, the literature has documented violations of consequentialist reasoning. Tversky and Shafir (1992) offered an early demonstration of violations of consequentialist reasoning when they documented a dramatic violation of Savage’s (1954) sure thing principle. In one study, participants were told that they had just taken an important exam. Some participants were informed that they had passed. Others were told that they had failed. The remaining participants were told that they would find out tomorrow whether they had passed or failed. All participants were given a hypothetical opportunity to purchase an attractively-priced vacation, with an option to wait and delay their decision at a cost. The majority of participants who had either passed or failed the exam chose to book the vacation immediately while the majority of participants who were unsure of whether they had passed or failed chose to wait until they found out about the exam. This pattern was inconsistent with consequential thinking because the outcome of the exam did not impact the decision to book the vacation (see also Esponda & Vespa, 2019). A related finding is Gneezy et al. (2006)'s uncertainty effect. They showed a substantial violation of monotonicity. Participants priced a lottery in which they would receive either a $50 or $100 gift certificate less than the $50 gift certificate, even though the normative model requires that their valuation be between the valuation of the more and less attractive gift certificates. Non-consequentialist reasoning has also been documented in moral psychology. For example, a large body of research has documented this type of reasoning in the “trolley problem” (Foot, 1978). Participants in these experiments often report that they would not kill one individual to save many, particularly when they must participate directly in the killing (Cushman et al., 2006). Other research has focused on protected values (Baron & Spranca, 1997) and taboo trade offs (Fiske & Tetlock, 1997) whereby some values are resistant to trade offs in ways that seem to contradict consequentialist reasoning (c.f. Bartels, 2008). Judges weight probabilities linearly The last assumption is that judges integrate conditional judgments by weighting these judgments by the probabilities. A large literature has documented a tendency to weight probabilities nonlinearly in decisions under risk, when probabilities are known (Kahneman & Tversky, 1979; Tversky & Kahneman, 1992), as well decisions under uncertainty or ambiguity, when probabilities are not available or are subjective (Trautman & van De Kuilen, 2015). In many cases, nonlinear weighting of probabilities biases valuations toward the worst outcome (e.g., Ellsberg, 1961), a pattern consistent with the risk judgments for the “50-50” and “unknown status” conditions. Discussion How do we make sense of people’s behavior when they are seen and not seen—when we observe their behavior but not their vaccination status? Decision theoretic models suggest that these judgments should depend on the probability that the target is vaccinated, but apparently vaccination status may not come naturally to mind—a striking finding given how ubiquitous discussions, debates, and recommendations of vaccination against COVID-19 have become. Participants in our study, unless prompted to think about vaccination status, view going to a bar as equally appropriate for a person who is fully vaccinated and one whose vaccination status is unknown. Importantly, when participants are prompted to think about vaccination status, they do so, leading them to view others more disparagingly, at times even more negatively than what a normative benchmark would imply. This pattern holds for participants who have been vaccinated, as well as those who plan to; liberal, as well as conservative, respondents; and for those who are relatively unconcerned about the risks of COVID-19 as well as those who are very concerned. While vaccination status is not always top of mind, cues in the environment may bring attention to the pandemic, and thereby, highlight the importance of vaccination status when judging others’ behaviors. The one COVID-19 behavior that differs from the rest is “having a conversation with a friend on a park bench without a mask.” This wording — “without a mask” specifically — naturally highlights the counterfactual that the target could have been wearing a mask. It is important to note that the real world analog of this situation may or may not prompt cognitions related to COVID-19. Seeing two people talking on a bench without a mask seems ordinary, unless you remember that this kind of behavior has been comparatively rare over the past year. Similarly, how we judge a stranger working out at a gym depends on whether environmental cues bring up thoughts about COVID-19. For instance, whether the woman on the elliptical trainer next to the target is wearing a mask could have a large effect on how you view the appropriateness of the target going to a gym. The masked gym patron may bring cognitions related to COVID-19 to mind, leading to more disparaging judgments of the target. Although the scope of our empirical investigation is limited to perceptions of riskiness and appropriateness of behaviors within the context of the COVID-19 pandemic, our work also addresses a broader theoretical question: what information do people retrieve, and rely on, when making decisions under risk and ambiguity, depending on contextual cues? Past research has typically focused on how people use and integrate the information they have to make judgments in ambiguous situations, and relatively little attention has been paid to what information feeds into these processes (e.g., Camerer & Weber, 1992; Trautman & van De Kuilen, 2015). One underlying, often implicit, assumption in this past work is that people incorporate all decision-relevant information that they have. An implication of this is that contextual cues that do not provide novel information should not affect decisions and judgments, since decision-makers possess the same information, regardless of the presence or absence of these cues. By contrast, as we demonstrated in this paper, contextual cues may highlight or obscure information that decision-makers already possess, thus even uninformative cues may have the ability to alter judgments and decisions in meaningful ways, through changing what information comes to the decision-maker’s mind. Risky behaviors, inside and outside of the pandemic, are both seen and not seen; we see others’ behaviors but not the underlying traits that moderate their riskiness. Some things are not seen because they are unavailable—we lack perfect information about the people around us. Other things are not seen despite “being seen”—we have the information we need to make a good decision but fail to use that information when making judgment. However, what is not seen may be as important as what is. As in the case of vaccination-contingent judgments, many of the risks people face on a regular basis are contingent on unobservable “states”—that can drastically alter the level of risk involved in these situations—and subtle contextual cues might highlight or obscure these contingencies. For example, the risk of food poisoning at restaurants is highly contingent on an establishment’s hygiene rating, but poor ratings are often hidden from plain sight or deliberately withheld from consumers. Thus, when a hygiene rating is missing, consumers should be more cautious when ordering meals, as the missing information might indicate a potentially higher risk of food poisoning. However, as Gurney and Loewenstein (2020) demonstrated, patrons fail to adjust their judgments of risk when hygiene ratings are missing, unless this fact is explicitly highlighted (e.g., by adding the following note: “Sanitary inspection grade: Not reported by owner”). Similarly, when investors discover a promising new company with a stellar performance, they might not readily think about the contingency that a company’s reports are fraudulent—which should drastically affect their risk assessments—even when they know that a small percentage of reports are fraudulent, without being explicitly prompted to consider this possibility. Conclusion When people judge others’ behaviors on riskiness and appropriateness, depending on others’ COVID-19 vaccination status, they sometimes violate the normative principle that judgments should depend on the probability that others are vaccinated. In our study, participants made reasonable judgments when cues guided them to include COVID considerations in their representation of the situation. When such cues were not present, however, people defaulted to a representation which apparently did not incorporate important pandemic-relevant factors, such as vaccination status of others. These results suggest that the representations that form prior to making judgments may play a crucial role in shaping judgments and decisions in the face of ambiguity. Different representations of a situation may include (or exclude) different information and alternative structures which fundamentally alter judgments. Our research suggests that current models of decisions under under ambiguity may be incomplete because they fail to account for such differences in representation. Future research should therefore address the interplay between representations and resulting choices. Supplementary Information Below is the link to the electronic supplementary material.Supplementary file1 (PDF 8.60 MB) Declarations Competing interest None. 1 https://www.cdc.gov/coronavirus/2019-ncov/vaccines/fully-vaccinated-guidance.html 2 https://www.washingtonpost.com/health/2021/05/14/cdc-mask-update-decision-confusion 3 For simplicity, throughout the paper, we will view vaccination as binary: either fully vaccinated or not. 4 However, we speculate that the general principles we document in the present study (Sect. 4) would still generalize to this group (e.g., lazy mental processing in a situation where risk is conditioned on an unobserved trait). 5 https://aspredicted.org/pk5s4.pdf 6 We defined “fully vaccinated” as a person who received their final dose of a COVID-19 vaccine two or more weeks ago. We displayed this definition to participants at the beginning of the second part of the survey. 7 We address why this behavior might be judged differently from the other seven behaviors in the Discussion. 8 https://www.mayoclinic.org/coronavirus-covid-19/vaccine-tracker Numbers refer to the percentage of all Americans. At the time of the survey, adults and children 12 and older were eligible. Approximately 48 out of 328 million Americans are under the age of 12 (https://www.statista.com/statistics/457786/number-of-children-in-the-us-by-age/), making the actual percent of eligible Americans vaccinated 44.9%. 9 t-statistics are from regressions in which all eight COVID behaviors are pooled. Regressions include dummy variable controls for each behavior. Standard errors are clustered at the level of individual participants. 10 Interestingly, there is no relationship between probability estimates and risk judgments for either the “no information” condition (t=0.07) or the “unknown status” condition (t=0.06). Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Anderson NH Foundations of Information Integration Theory 1981 New York Academic Press Baron J Spranca M Protected Values Organizational Behavior and Human Decision Processes 1997 70 1 1 16 10.1006/obhd.1997.2690 Bartels D Principled Moral Sentiment and the Flexibility of Moral Judgment and Decision Making Cognition 2008 108 2 381 417 10.1016/j.cognition.2008.03.001 18486121 Camerer C Weber M Recent Developments in Modeling Preferences: Uncertainty and Ambiguity Journal of Risk and Uncertainty 1992 5 4 325 370 10.1007/BF00122575 Chetty R Looney A Kroft K Salience and taxation: Theory and evidence American Economic Review 2009 99 4 1145 77 10.1257/aer.99.4.1145 Coombs, C. H., Dawes, R. M., & Tversky, A. (1970). Mathematical Psychology: An Elementary Introduction. Prentice-Hall. Cushman F Young L Hauser M The role of conscious reasoning and intuition in moral judgment: Testing three principles of harm Psychological Science 2006 17 12 1082 1089 10.1111/j.1467-9280.2006.01834.x 17201791 Edwards W The theory of decision making Psychological Bulletin 1954 51 4 380 417 10.1037/h0053870 13177802 Ellsberg, D. (1961). Risk, ambiguity, and the Savage axioms. Quarterly Journal of Economics, 643–669. Enke B What you see is all there is Quarterly Journal of Economics 2020 135 3 1363 1398 10.1093/qje/qjaa012 Esponda, I., & Vespa, E. (2019). Contingent thinking and the sure-thing principle: Revisiting classic anomalies in the laboratory. Working paper. Fiske AP Tetlock P Taboo Trade-offs: Reactions to Transactions That Transgress the Spheres of Justice Political Psychology 1997 18 2 255 297 10.1111/0162-895X.00058 Foot P The problem of abortion and the doctrine of double effect The Oxford Review 1978 5 5 15 Gneezy U List JA Wu G The uncertainty effect: When a risky prospect is valued less than its worst possible outcome Quarterly Journal of Economics 2006 121 4 1283 1309 10.1093/qje/121.4.1283 Gurney, N., & Loewenstein, G. (2020). Filling in the blanks: What restaurant patrons assume about missing sanitation inspection grades. Journal of Public Policy & Marketing, 39(3), 266–283. Johnson RD Levin IP More than meets the eye: The effect of missing information on purchase evaluations Journal of Consumer Research 1985 12 2 169 177 10.1086/208505 Kahneman D Thinking, Fast and Slow 2011 New York Macmillan Kahneman, D., Slovic, P., & Tversky, A. (Eds.). (1982). Judgment under uncertainty: Heuristics and biases. Cambridge University Press. Kahneman D Tversky A Prospect Theory: An Analysis of Decision under Risk Econometrica 1979 47 2 263 291 10.2307/1914185 Keren, G., & Wu, G. (2015). A bird’s-eye view of the history of judgment and decision making. In G. Keren & G. Wu (Eds.), The Wiley Blackwell Handbook of Judgment and Decision Making (pp. 1–39). New York: Wiley-Blackwell. von Neumann J Morgenstern O Theory of Games and Economic Behavior 1953 3 Princeton, NJ Princeton University Press Rottenstreich Y Kivetz R On decision making without likelihood judgment Organizational Behavior and Human Decision Processes 2006 101 1 74 88 10.1016/j.obhdp.2006.06.004 Sanbonmatsu DM Kardes FR Herr PM The role of prior knowledge and missing information in multiattribute evaluation Organizational Behavior and Human Decision Processes 1992 51 1 76 91 10.1016/0749-5978(92)90005-R Savage LJ The Foundations of Statistics 1954 New York Wiley Slovic P From Shakespeare to Simon: Speculations-And Some Evidence-About Man’s Ability to Process Information Oregon Research Institute Bulletin 1972 12 2 1 28 Trautmann ST Van De Kuilen G Keren G Wu G Ambiguity attitudes The Wiley Blackwell Handbook of Judgment and Decision Making 2015 New York Wiley-Blackwell 89 116 Tversky A Kahneman D Availability: A heuristic for judging frequency and probability Cognitive Psychology 1973 5 2 207 232 10.1016/0010-0285(73)90033-9 Tversky A Kahneman D Advances in prospect theory: Cumulative representation of uncertainty Journal of Risk and Uncertainty 1992 5 4 297 323 10.1007/BF00122574 Tversky A Koehler DJ Support theory: A nonextensional representation of subjective probability Psychological Review 1994 101 4 547 10.1037/0033-295X.101.4.547 Tversky A Shafir E Choice under conflict: The dynamics of deferred decision Psychological Science 1992 3 6 358 361 10.1111/j.1467-9280.1992.tb00047.x
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Special Topics 1951-6355 1951-6401 Springer Berlin Heidelberg Berlin/Heidelberg 727 10.1140/epjs/s11734-022-00727-y Review Paper based microfluidic devices: a review of fabrication techniques and applications Anushka http://orcid.org/0000-0003-3371-7879 Bandopadhyay Aditya [email protected] Das Prasanta Kumar [email protected] grid.429017.9 0000 0001 0153 2859 Department of Mechanical Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302 India 12 12 2022 135 23 8 2022 9 11 2022 © The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. A wide range of applications are possible with paper-based analytical devices, which are low priced, easy to fabricate and operate, and require no specialized equipment. Paper-based microfluidics offers the design of miniaturized POC devices to be applied in the health, environment, food, and energy sector employing the ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment free and Deliverable to end users) principle of WHO. Therefore, this field is growing very rapidly and ample research is being done. This review focuses on fabrication and detection techniques reported to date. Additionally, this review emphasises on the application of this technology in the area of medical diagnosis, energy generation, environmental monitoring, and food quality control. This review also presents the theoretical analysis of fluid flow in porous media for the efficient handling and control of fluids. The limitations of PAD have also been discussed with an emphasis to concern on the transformation of such devices from laboratory to the consumer. ==== Body pmcIntroduction In microfluidics, fluids and particles are controlled and manipulated by precise equipment on scales of tens to hundreds of micrometers. Microfluidics leverages fluids in microchannels to exploit their most obvious characteristics small size and laminar flow. Microfluidics is also used for medical and chemical applications, such as lab-on-a-chips (LOC) and micro total analysis systems (μTAS). This technology features superior advantages over conventional macro-scale platforms (e.g. centrifuges, flow cytometers, etc.) because it can precisely control and manipulate biological particles and the surrounding microenvironment. Although microfluidics has been developing rapidly, the progression of POC microfluidic systems still faces various barriers like sample processing, chip to real-world connection, sensing, and miniaturization or abolition of additional fluid control elements. The difficulty and high expenses of advancement of microfluidic products, make it difficult to reach end customers. Therefore, Martinez et al. [1] merged the concept of microfluidics with paper, as paper meets the optimal base material parameters for the transfer of these devices from the lab to consumers. These paper-based analytical devices (PADs) offer a seperate site for liquid transportation via capillary forces without the use of additional pumps. Paper-based microfluidics is a rapidly growing field that has attracted significant attention due to its advantages over traditional microfluidics, such as low manufacturing costs, accessibility, ease of operation, scalability, fast response, POC diagnostics, and little solution usage. Therefore, this technology meets the guidelines of WHO for an ideal POC diagnostic system. Under WHO guidelines, the diagnostic test/device must meet the ASSURED requirements (as shown in Fig. 1) which include being (i) affordable, (ii) sensitive, (iii) specific, (iv) user-friendly, (v) rapid and robust, (vi) equipment-free, and (vii) deliverable to end-users for the selection of diagnostics [2, 3].Fig. 1 An illustration of the WHO’s ASSURED criteria for diagnostics As a result, the field of testing is constantly developing and discovering new tools for identifying both infectious and non-infectious disorders. Incorporating microfluidics and biosensing principles can meet the criteria listed by the WHO here for choosing testing tools [3, 4]. In addition to satisfying the ASSURED criteria, microfluidic chip biosensors provide many additional advantages, such as portability, the need for fewer samples, the possibility of installation in rural parts, reduced energy consumption, less errors, numerous biomarker identification, etc. Creating channels is all that is necessary to execute multiplexed analysis by a succession of hydrophilic-hydrophobic microstructures on paper substrates to create PADs. Photolithography, wax printing, screen printing, inkjet printing, and plasma oxidation are some of the common methods to create channels in the device. To improve the sensitivity and working of the device, certain modifications like the incorporation of the electrode were required. Colorimetric, chemiluminescence, and electrochemical techniques are employed for the goal of detection, and they entail the measurement of color intensity created on the PAD. Figure 2 shows a typical configuration for a paper-based microfluidic analytical device in which patterns were created on a simple Whatman filter paper to create the hydrophobic-hydrophilic contrast and then reagents and samples have been loaded to analyze the developed color in the reaction zone. There are many detection techniques have been explored including colorimetric analysis, fluorescent analysis, electrochemical analysis, etc. Colorimetric detection is a good method for μPADs, which has the benefits of visual monitoring, quick sensing, practicality for rural applications, ease of use, and greater stability. In spite of improvements, there are still a few problems with paper-based microfluidic technology. The issues to take into account relate to the devices’ stability and shelf life, particularly those that involve biological tests for analysis. The field of ‘PADs’ has experienced tremendous growth, but there are still many obstacles to overcome and possibilities to seize. The development of tools that are simpler to use must also continue. The complexity of assays for current technologies can be limited because of their intrinsic simplicity, or they can do complicated activities but are difficult to operate. This review explains the design and fabrication methods with various adjustments to generate practical assay with efficient handling and regulation of fluids, since μPADs primary issue is the paucity of flow control, this slows down the process from the lab to the public hands and creates marketing challenges. Then it will transition to how these technologies carry out detection. The quantitative understanding of capillary flow was also revealed with various theoretical analysis of fluid flow in porous media. The Review will conclude with applications of PAD technology across medical diagnosis, environmental monitoring, energy generation, and food safety monitoring before concluding with a consideration of future directions of paper-based devices.Fig. 2 PAD a filter paper, b patterned hydrophobic channels, c loading reagents, d loading sample, and e result Fabrication Like any other microfluidic system, fabrication is very important also for paper based device. The remarkable characteristics of paper have been the key to the development of PADs. There is no need to use external energy devices with paper-based microfluidics since it relies on capillary action to transfer liquids. Two basic steps are involved in creating μPADs: Paper patterning and device customization to serve the purposes for which they are intended. Patterning Patterning is the first step in the fabrication of any PAD and is required to achieve hydrophilic-hydrophobic contrast in a porous paper. The two main patterning techniques for creating microfluidic channels on paper substrates are mechanical cutting and hydrophobic material treatment. Direct and indirect methods can be used to further categorize the second technique into two categories. In the direct technique, the hydrophobic material is applied directly to the paper, although for the indirect methods, the hydrophobic material is applied selectively at different stages using a mask, as indicated in Fig. 3. Wax printing, inkjet printing, flexographic printing, and laser cutting are examples of direct techniques while indirect method involves Plasma etching, photolithography, laser treatment, etc. The strategies of patterning principles can be separated based on the binding states of the hydrophobic agent: (1) physically sealing the pores of the paper, (2) physically depositing a hydrophobizing substance on the cellulose fiber surfaces, and (3) chemically altering the surfaces of the fibers.Fig. 3 Classification of patterning methods to form microfluidic channels. Patterning is classified based on the technique of transferring hydrophobic material on paper. If the hydrophobic material is applied directly to the hydrophilic paper substrate, it is called the direct method while if the hydrophobic material is applied selectively at different stages, it is the indirect method Photolithography Photolithography was used to create the first paper-based microfluidic devices, and it continues to be preferable due to its accuracy and high resolution [5]. The photolithography begins by covering the complete paper with a negative photoresist as shown in Fig. 4. Moreover, the photoresist is crosslinked in the appropriate pattern by using a photomask. Finally, the substrate is developed in solvent to eliminate the remaining photoresist that hasn’t been exposed [6, 7]. Martinez et al. [1] demonstrated the photolithography technique and used SU-8 2010 photoresist to create patterns on chromatography paper, then soaked and deposited the photoresist onto the paper. Now, the paper was baked for a few minutes to take off the cyclopentanone in the SU-8 formula. After that, a photo mask that had been precisely aligned with the aid of a mask aligner was used to expose the paper to UV light for couple of seconds. Although SU-8 is pricey and the procedure is complicated, the manufactured PADs have good resolution. Furthermore, Whitesides and colleagues used a SC photoresist [8] and an epoxy negative photoresist [9] for the SU-8 2010 photoresist.Fig. 4 Diagram showing the photolithography process. a Chromatography paper, b soaking the paper in a photoresist, c after prebaking aligning under a mask, d exposure to UV light, and e cleaning the developed pattern Wax patterning Wax is a hydrophobic substance that can be used on the hydrophobic surface using different ways. There are many benefits of using wax printing for the patterning of devices, including ease of fabrication, non-toxicity, disposability, and lower production costs. In 2009, Lu et al. [10] created a new wax impregnation process known as wax printing. Molten wax, as opposed to ink or toner, is imprinted on the surface of the paper by solid ink printers used for wax printing [11, 12]. Heat is applied to a piece of paper with a wax design printed on one side in order to flow the wax and permit it to reach the paper’s thickness [13, 14]. This creates a hydrophobic barrier that is entirely impermeable and has a hydrophilic zone enclosed inside it that is shaped like a wax printing pattern. To prevent the reverse side of paper from becoming wet and to stop the permeation-related leakage of reagents and samples to the other side, a clear tape [15, 16] or laminated film is lastly applied to one side of the paper. While the wax is heated, it spreads both laterally and vertically, therefore this must be taken into consideration when drawing the designs. Channels of various sizes can be produced by printing wax in a variety of thicknesses or quantities. Wax dipping Compared to photolithography, it is a more expedient and economical printing method. It only requires wax dipping, and the channel was created in under a minute using subsequent soaking and standard heating techniques [13]. Hydrophobic barriers were created using melted wax, and hydrophilic channels were shielded using an iron mould as in Fig. 5. The magnetic field of a magnet was used to apply the iron mould to the paper. The paper absorbs the molten wax whenever the specimen is submerged in it, but some sections of the iron mould are shielded from the wax’s absorption. The size of the iron mould that is used determines the precise width of the manufactured microfluidic channel.Fig. 5 Diagram showing the wax dipping process. a Filter Paper, b a magnet was mounted to the rear of a glass slide to generate an assembly of paper between a glass plate and a mould, c assembly was submerged in a wax chamber, d peeling off the glass plate and detaching the iron mould at room temperature resulted in the creation of the hydrophobic and hydrophilic regions of the μPADs Inkjet printing In this method, a solvent is used in place of ink to pattern paper using a commercial inkjet printer. One application of this method involves first totally hydrophobizing paper by soaking it in a polystyrene solution. The paper is then treated with toluene inkjet printed in a specific pattern to remove some of the polystyrenes [17, 18]. The printers used for inkjet printing are relatively inexpensive and easily available and the reagents used for inkjet printing can directly print onto the device, helping in making an entire device in just one step. Abe et al. [18] used an inkjet-printed device for the sensing of glucose, proteins, and pH and proposed a method for creating mesoporous colloidal nanoparticle ink using an inkjet printer on both rigid and flexible substrates [19]. This technique permits sophisticated vapor responses for multiple-color PC patterns, and variations in color intensity have been seen with the unaided eye. Maejima et al. [20] created PADs using a similar inkjet printing technique. However, they substituted AKD in this instance with a hydrophobic UV curable acrylate composition made of non-volatile and non-flammable substances as shown in 6. After the unique ink had been printed on the paper, hydrophobic barriers were created by curing the material under UV light for 60 s [21]. The drawback of this method is that inkjet printing frequently necessitates the production of many printed layers and can result in print resolution issues. Since a large number of solvents used to emulsify detecting compounds are flammable, which might clog printers or result in errors in the quantity of reagents that are printed.Fig. 6 Schematic diagram illustrating inkjet printing. a Top view of filter paper, b printing of ink pattern, c UV curing on the top side, d bottom view of filter paper, e printing of ink, f UV curing on the bottom side Laser treatment The CO2 laser is the most often utilized laser source for creating paper-based devices. Without support material to shield the material at the back, this can go into anything in a single pass. In order to create microfluidic devices, double-sided adhesive, PMMA, and paper are frequently sliced using a CO2 laser while maintaining the specific value of operational parameters like the strength of the laser and the reading rate to prevent paper cutting. Mani et al. [22] reported a microchip to diagnose tuberculosis (TB) in the human body, which was framed using a laser cutting procedure. This TB ELISA is a fast, low-cost, and magnetically operated platform. The test duration could be halved to about 15 min while maintaining detection efficiencies on par with those of traditional, classical ELISA. Renault et al. [23] considerably enhanced the rate of flow of liquid on the porous chip and decreased nonspecific adsorption by cutting a channel with a laser to create an intermediate hollowed-out sandwich chip sensor (hollow channel). Chitnis et al. [24] proposed a laser-treated microfluidic device with the use of a substrate made of parchment paper. With the use of computer-controlled CO2 optical trimming and engraving machinery, the texture of the parchment paper was altered. The parchment sheet was treated after being spread open and placed on a pedestal. The intended pattern was created on the parchment paper using rapid scanning of the laser beam throughout the face. However, its usage is constrained by the need for expensive equipment and cautious processing. Plotting In the earlier days, 2D plotter was used for the fabrication of PADs. It is a charting tool that can print or plot two-dimensional items on a plane. By altering the type of plotter head being used, one can switch between plotting and printing [25]. Fabrication of PADs often involves the employment of a spray nozzle that emits an ink stream. A 2D plotter sprays hydrophobic ink onto the paper that is within the plotter. Computing systems have the ability to predetermine or regulate the spray pattern. Depending on the density of the ink and its ability to penetrates into the paper at different temperatures, heating the paper after plotting may or may not be necessary. Bruzewicz et al. [26] modified the x-y plotter to print the solution of polydimethylsiloxane (PDMS) in hexane over the filter paper. The hydrophobic polymer entered the paper’s depths and blocked aqueous solutions from entering the filter paper. This process produces inexpensive, paper-based, physically flexible gadgets. An easier approach to creating paper devices was the use of wax pens [10]. Wax was used to trace the necessary patterns across both faces of a piece of filter paper, which was then baked for a brief length of time. Because of the high temperature, the wax may melt and permeate the paper in the precise pattern of channels needed to create a hydrophobic wall. Laser plotting is another plotting technique to create microchannels by using a laser plotter [27]. In essence, the thermal deterioration action that engraves the surface of the chosen material is the basis for the microstructures produced by this technique. Ink plotting is also a commonly used plotting method in which hydrophobic barriers are created on paper using an X–Y plotter and hydrophobic inks are put into pens [26, 28]. The hydrophobic ink is absorbed in the sheet of paper due to the proper selection of ink viscosity and plotter head pressure. Although this method is cheap, the resolution of the pattern is only moderate. The method takes a long time, thus it’s better suited for creating small quantities of devices. Flexographic printing It is a direct and quick manufacturing technique for mass production in a roll-to-roll method as shown in Fig. 7 [9, 29]. On various substrates, commercial flexographic printers can manufacture the devices at very high speeds. An anilox roll is charged with ink, which is then delivered to a paper that is fastened to the impression roll. As an ink, polystyrene solution in an organic solvent is employed at various concentrations. The amount of ink transferred from the anilox roll to the printing plate, which has a design known as the relief pattern, is determined by the numerous cells that surround it. The doctor’s blade removes any extra ink that may still be present in the anilox roll. To distribute the ink to the paper, the anilox roll is turned four times, along with the plate roll and impression roll. Getting enough ink to saturate the paper substrate, the optimization of the printing speed and pressure between rolls is necessary. The pipet is configured to automatically add ink to the ink tank after printing the first layer. After finishing a few ink layers, the anilox roll needs to be washed; otherwise, the print quality begins to deteriorate. The hydrophobic characteristics of the printed layers are influenced by the number of layers that are printed. Flexographic printing is used to print channels through the use of polystyrene ink that had been dissolved in volatile organic solvents. By adjusting the solvent’s viscosity, vapor pressure, and polystyrene content, channels on the device can be printed partially or entirely through the paper. Flexographic printing also uses commercial ink PDMS. For PDMS to cut through paper, multiple replicate print layers are needed.Fig. 7 Schematic diagram illustrating a flexographic printing method b structures created on porous substrate using flexographic printing Ink stamping Due to the simplicity of the stamping method, it has been extensively used by researchers to create PADs using various stamps and inks [30]. The portable stamp used in the stamping method is the only tool utilized to form a pattern on the filter paper, thus it should be simple to make and apply. A PDMS stamp is used to define a fluidic structure by bringing indelible ink into contact with filter paper. Without using any external force, the PDMS stamp was repeatedly dipped into the stone pad that had been wet with permanent ink. This allowed the stamp to make brief contact with the filter paper. Although ink stamping was straightforward and less expensive, the PDMS stamp was made in a very sophisticated manner. The filter paper was dipped into the liquid paraffin, let to cool, and then placed on the surface of the original paper. The hydrophobic barriers were created by transferring the wax from the p-paper to the n-paper using a warmed metal stamp. Since they are quick and inexpensive prototyping methods based on producing ink channels on substrate with a PDMS mark and permanent inks, the double side printing technique developed by Akyazi et al. [31] and the ink stamping method suggested by Curto et al. [32] have recently emerged as alternatives to conventional wax printing. They might be viewed as low-cost fabrication techniques, but their fundamental flaw is that because they involve manual labor, there is little consistency from one device to the next. De et al. [30] developed a new method for stamping that uses paraffin over a substrate made of chemically altered paper with the help of lightweight, portable stainless-steel stamp for quick prototyping of paper-based devices. Screen printing In this procedure, photolithography is used to pattern the desired design on a screen. The model is constructed first, and then solid wax is applied to the filter paper by rubbing it through a screen model. The wax was heated after printing so that melted wax could seep into the substrate and create hydrophobic barriers using a heated plate. Sameenoi et al. [33] applied polystyrene rather than wax onto the paper in a screen printing model. This method is appropriate for modest amounts of PAD manufacturing because screen printing is frequently utilized in the production of pieces of printing materials. This method has the benefit of being compatible with a greater variety of inks. The key drawback is that it is not suited for quick device prototyping because of the high number of screens needed. Plasma treatment Plasma treatment was utilized to construct μPAD by initially making a hydrophobic surface, and then hydrophobic material was then precisely removed by presenting the substrate to plasma over a physical barrier with the necessary pattern. The shield stay helps in the selective itching of the porous substrate and makes the paper sheet a combination of hydrophobic and hydrophilic regions. Alkyl ketene dimer(AKD) and octadecyltrichlorosilane (OTS)are two chemicals that are frequently used to make paper hydrophobic. Both a plasma cleaner [34, 35] and a portable corona generator [36] have been proposed for plasma treatment. Li et al. [34] patterned the paper by dipping it in an AKD–heptane solution and then putting it in a fume hood evaporate the heptane. The AKD was then treated on filter paper by heating it in an oven, making the material hydrophobic. A vacuum plasma reactor was used to process the modified paper while it was positioned between two metal masks with the necessary patterns. Following the plasma treatment, the exposed portions turned hydrophilic. As a typical industrial material, AKD is affordable and easily accessible. However, each pattern is unique to metal masks. The metal masks should be costly and difficult as a result. Fluorocarbon plasma polymerization for the creation of PADs was proven [37]. Two masks i.e., a positive mask and a negative mask were tightly positioned on either side of the filter paper. Afterward, the plasma system made the hydrophobic barrier on sandwiched by puncturing the fluorocarbon. Obeso and colleagues have reported using plasma and poly (hydroxybutyrate) for the production of PADs. The plasma procedure resembles the plasma therapy that was previously mentioned. But in this instance, the paper is dried at ambient temperature after being submerged in various solutions in succession. This method involves producing the paper beforehand, which takes time but results in a straightforward plasma procedure. Chemical vapor-phase deposition Kwong and Gupta [38] first introduced the chemical vapor-phase deposition-based patterning technology for functional polymers, and afterward, the methodology was expanded for pure polymers. A magnet and a metal mask were positioned on either side of the filter paper. The monomer was placed in a sublimation chamber that had been emptied in order to undergo pyrolysis and create radical monomers. These were applied to the exposed area of the paper, where they were subsequently polymerized to form hydrophobic barriers. Then, a similar method for creating PADs that involved vapor-phase layering of pure polymers was published [39]. In the latter procedure, a magnet and a metal mask were placed on top of the filter paper. A suitable quantity of monomers was added to an evacuated sublimation chamber, where they were allowed to evaporate before being pyrolyzed into radical monomers. They were then applied to the exposed surface of the paper and polymerized to form hydrophobic barriers. This technique was also employed to create PADs. The only distinction between the two techniques is the polymer that Chen et al. [40] utilized, a fluoropolymer covering of poly (1 H, 2 H, 2 H-per-fluorodecyl acrylate). Hand-held corona treatment Jiang et al. [41] proposed the fabrication of μPAD using corona discharge and created PADs using a portable corona treater. First, octadecyltrichlorosilane (OTS) was used to make a filter paper hydrophobic as shown in 8. After that, a plastic mask was used to expose the hydrophobic paper to the corona. The portion that was exposed changed from being hydrophobic to being hydrophilic as a result.Fig. 8 Schematic illustration of designing of μPADs: a paper, b octadecyltrichlorosilane (OTS) coated paper, c soft pad and PMMA mask were separated by OTS-coated paper and subjected to corona discharge after assembly, d patterned μPAD Fast lithographic activation of sheets (FLASH) FLASH is based on photolithography in which UV light and a hotplate are the essential tools required for it [8]. In contrast to photolithography, FLASH does not require a clean space. If UV lamp and hotplate are not accessible, FLASH method can still be successfully used in the sunshine. This technique makes it simple to design in paper small hydrophilic channels as small as 200 m. Photomasks are created as previously described. The photoresist is poured onto the paper and distributed evenly during the FLASH process as shown in Fig. 9. In order to evaporate the propylene glycol monomethyl ether acetate (PGMEA) included in the photoresist. During the cooling process, the paper is brought to ambient conditions. A transparency film is applied to one side of the paper, and black construction paper is applied to the other, in order to reduce the reflection of UV radiation. The border of the construction paper should have adhered to transparent film with the three parts. On the transparent film, black patterns were imprinted to distinguish between hydrophilic and hydrophobic regions. Now, a brief UV exposure is given to the FLASH material. The transparency film and construction paper are then taken off. The paper is cleaned with isopropyl alcohol and acetone after soaking in acetone for one minute.Fig. 9 Schematic diagram for FLASH method to fabricate microfluidic device a after applying the photoresist to a paper, sandwich a black paper between an adhesive transparent material, b utilising an inkjet printer to print designs onto substrate, c the paper being exposed to UV light, d peel out the transparent film and black paper from the impregnated paper PDMS screen printing On chromatography paper, hydrophobic barriers are made using the polymer PDMS, which has a very flexible character. This approach involves moving substrates in different directions under the control of a printing table. The chromatography paper is covered with a nylon mesh screen stencil that has been designed according to specifications. After that, PDMS is applied to the surface and rubbed into the chromatography paper to create a pattern over the paper. The patterned paper is dried for 30 min at 120 ∘C before being chilled to room temperature, as depicted in Fig. 10. The comparison of different patterning techniques highlighting their principles, benefits, and drawbacks are mentioned in Table 1.Fig. 10 Schematic depiction of PDMS-screen-printing method. a Chromatography paper b placing the screen on the paper; c, d applying PDMS to the screen; e curing the PDMS-Screenprinted paper in an oven Table 1 Different fabrication techniques and their underlying principles, along with benefits and drawbacks Method Patterning Agent Patterning principle Benefits Drawbacks Photolithography Photoresist Physical blockage of paper pores Good resolution, convenient, narrow width channels Expensive agent and equipment, extra cleaning required Wax Patterning Wax Physical blockage of paper pores Mass production, simple and quick High printer cost, poor resolution Wax dipping Wax Physical blockage of paper pores Mass production, simple and quick Heating required Inkjet printing AKD Chemical surface modification Agent is cheap, mass production Sophisticated steps, requirement of advanced printer Laser treatment Depend on paper types Physical blockage of paper pores Good resolution Require extra steps Plotting PDMS Physical blockage of paper pores Cheap agent, easy fabrication, flexible can’t use for mass production FlexographicPrinting Polystyrene Physical blockage of paper pores Mass production, no heat treatment Polystyrene solution must be printed twice, and various printing plates are needed Plasma Treatment AKD Chemical surface modification Inexpensive agent, very flexible, no heat treatment required Customized masks are required, slow production rate Screen Printing Wax Physical blockage of paper pores Easy process Low resolution Chemical Vapor-Phase Deposition Chemical monomer Chemical surface modification High resolution Expensive FLASH Photoresist Physical blockage of paper pores Quick Expensive, multiple steps PDMS screen printing PDMS Physical blockage of paper pores Enhanced flexibility Low resolution Incorporating operational functionality Although paper is a unique substrate for containing liquids in specific areas and controlling fluid flow without the use of external power, the above characteristics of porous substrates only provide a limited amount of control over fluid transport, particularly over flow rate and direction. These limitations render inappropriate handling of complex chemical matrices and ill-timed performance of multi-step tasks. The early PADs had limited influence in the analytical community because they were incapable of performing complicated tasks. To integrate enhanced capability for handling liquids and enabling safe operation, various functionalities were incorporated into the device. Flow rate control (programming and timing) One of the earliest examples of fluid flow control was made by Martinez et al. [42] in 2010, who created a multi-dimensional μPAD with ‘on’ buttons that could be used only once to change the flow path. When pressed, fluidic channels were connected between layers of porous material and tape that were strategically spaced apart. Until it was pressed, this computerized valve could fully stop the flow. While single-use valves have their drawbacks, this work showed how programmable PADs might be useful for testing or manually regulating the sequence of reactions. Other researchers [43–45] published additional techniques for managing fluidic transport by changing the shape of the channel. When a channel junction changes from narrow to wide, the flow rate decreases. Another way of flow control was introduced by Toley et al. [46] by redirecting the flow through an adjustable cellulosic shunt that was put in the direction of flow and in direct contact with the paper. By wicking fluid via a bridge made of soluble sugars, Houghtaling et al. [47] used a similar idea to digital ‘on/off’ switches, successfully shutting off the flow. Afterward, a water-soluble pullulan film was created by Jahanshahi et al. [48] that performed a comparable function. Multi-step processing Automating multi-step procedures is the first step in the trend toward making PAD tests more functional. By adding numerous steady portions of paper for each step of the reagent addition process, Fu et al. [49] and Lutz et al. [50] examined the successive transportation of various chemicals to a detecting zone. To build an automated sandwich ELISA experiment, Apilux et al. [51] defined numerous flow routes of variable lengths with various chemicals in each path. Li et al. [52] use of magnetically timed ‘open/closed’ single-use valves allowed them to show device control for multi-step tests. The facial tissue that made up each valve was essentially a porous substance attached with a cantilever. At the beginning of time, either the valve was lowered onto the stream, allowing fluid to flow through it, or it was lifted just above stream, preventing flow. The cantilever was activated by a resistor when the stream from the inlet approached the resistor. The intended delay for on-chip processes determined the length of the timing channel. Furthermore, Fridley et al. [53] showed that depending on the manner in which reagents are put in devices, compounds dried in the paper are amenable for multi-step processing. In their method, a single detection zone made by a PAD cut from nitrocellulose was downstream of channels that carried dry chemicals and each was a different size from the monitoring zone. All three reagents in the porous substance attached at the same time and were closest to the detection zone overall arrived and reached the detection zone first. In an effort to cut the price and size of the LFAs development process, Anderson et al. [54] offered a revolutionary platform centered on the adaptability and capacity of an autonomous fluid handling system. The technology was first successfully used to create an LFA for malaria, but it was quickly expanded to allow for the development of LFAs for SARS-CoV-2 and Mycobacterium tuberculosis as well. This automatic system increased both the number and quality of LFA assay development efforts by cutting down on hands-on time, increasing experiment size, and facilitating enhanced repeatability. Another automatic flow shutdown system was created using pullulan, a quickly dissolving polymer [48]. The paper channel is partially replaced by a deflectable capillary channel produced by a dissoluble film, enabling automatic flow control. In order to accommodate time-sensitive or multi-step reactions and tests, the user can manage fluid movement using this time-dependent flow shutdown technology. Switches and valves Device construction must enable effective control over fluid motion and multi-step protocols. A switch was achieved in PAD by manually bifurcating the channel in order to allow or prevent the capillary flow [34]. The valves operate on the idea that exerting pressure on two vertical fluidic channels changes their gap, allowing fluids to wick along the connected channels. However, functioning without controller or actuator, valves are challenging to integrate into paper-based devices. Switches and valves were built on the same platform and were utilized for more specific applications. The idea behind paper-based microfluidic valves is comparable to that of electronic field programmable gate arrays. Likewise, Martinez et al. [42] built a valve mechanism in 3-D μPADs by exerting pressure to close the space between two fluidic channels that were vertically aligned. Fluids can wick along the joined channels by sealing the gap. Then, Glavan et al. [55] and Liu et al. [56] implemented the folding valve concept into an open-channel device and a laminated device, respectively. When channels in folding valves are folded and unfolded, the direction of fluid flow changes; folding the channel past a 90-degree angle stops the flow. In the literature, self-actuated type valves were also mentioned for sample in/ out tests. Newsham et al. [57] examined and modeled multiple configurations of thermally actuated valves to incorporate the valve into an LFIA with exact control over various flow parameters. To specifically characterize the microfluidic properties of PAD, fluorescent nanoparticles were measured using micro-particle image velocimetry. This method identified divergent bulk flow parameters that might explain extra variability in LFIA signal generation. Li et al. [58] demonstrated a self-powered rotating paper-based microfluidic chip with an integrated movable valve to detect thrombin. The sandwich was created by joining the DNA sequence (DNA1) and a DNA sequence ((GOx)-DNA2 modified by the glucose oxidase enzyme in order to get the supercapacitor signal. The (GOx)-DNA2 may then be released and employed to catalyse the oxidation of glucose as thrombin binds with its specific aptamer through strong binding affinity. The required voltage may be generated to refill the paper supercapacitor as a result of the (GOx)-triggered reaction, and a multimeter can monitor its signal. Electrode incorporation The challenge associated with paper-based devices is obtaining low limit of detection with reasonable efficiency due to a dependency on color identification of the human. Electrochemical detection ability of paper devices bridges the gap between conventional paper-based devices and advanced automatic devices. Devices based on electrochemical detection provide great sensitivity and selectivity while also being a good match for low-cost detection. Making a paper-based device compatible with commercial readers like glucometers was a goal of the development process. The most significant factors affecting the performance of an electrochemical device are the electrode’s shape, material composition, and fabrication techniques. Furthermore, various electrode materials are discussed below. Carbon electrodes Due to ease of manufacturing, ease of chemical alteration, and large possible opening in liquids, carbon is a desirable electrode material. For these reasons, carbon was the first material to be used as a functioning electrode in ePADs [59]. Since then, other instances of carbon electrodes and related fabrication techniques have been demonstrated. The dual-based lab-on-paper device created by Apilux et al. [60] demonstrated a quick and easy way to quantify Au(III) using colorimetry as indicated in Fig. 11.Fig. 11 Depiction of the basic design containing three electrodes (working electrode (WE), counter electrode (CE), and silver/ silver chloride ink as the reference electrode (RE)) screened on patterned paper 1. Screen-printing It is widely used method for fabricating carbon electrodes [61–64]. Polymerizing photoreactive polymer-coated screens around masks is commonly accomplished through photolithography. Another technique involves printing through a silk screen-adhered solid film with a craft- or laser-cut pattern. For the electrocatalytic detection of thiols, Dossi et al. printed an electrode that was combined with cobalt phthalocyanine [65]. Graphene or nanoparticles have also been used in other examples to increase the performance of screen-printed carbon electrodes (SPCE) [66]. 2. Stencil-printing Screen printing and stencil printing are relatively similar processes [67]. This technique uses transparency film or sticky tape to make masks instead of the usual screen materials. Using craft or laser cutters, stencils are easily made. In order to maintain pattern fidelity while stencil printing as compared to screen printing, more dense ink is required so the electrode material is dispensed via an open hole as opposed to a mesh. Viscous ink improves electrode conductivity but reduces the endurance of the electrodes and the adhesion of the paper [68, 69]. The improvement of ink viscosity and composition can help either screen printing or stencil printing. 3. Pencil drawing For inexpensive aqueous and nonaqueous media detection, graphite pencil leads are also used to make electrodes on paper. Santhiago et al. reported using the graphite pencil concept to create electrodes for a paper-based device [70]. For precise detection, lead and graphite were first polished before being put in touch with the paper device. In early works, H-type pencils were used to create the electrodes in order to get a satisfactory electrochemical reaction. However, more recent studies have discovered that soft lead, which has a greater graphite-to-binder ratio, is the ideal material for creating conductive electrodes on paper. Dossi et al. [71] established the concept of pencil lead production after recognizing the significance of binders composition in electrodes. Different binder compositions and additives, such as decamethylferrocene or CoPC, were used during the pencil lead’s fabrication to enhance performance and serve as a mediator during electrochemical detection, respectively. 4.Painting carbon electrodes Painting carbon ink on electrodes directly, without using masks, is one direct way of electrode production. On apply a handmade CNT ink to the substrate and then slice it into strips, all you need is a paintbrush. To create a potentiometric sensor electrode for the measurement of potassium, ammonium, and pH, an ion-selective membrane is applied to the strips. Utilizing precut sheets of paper to outline the painting area results in more repeatable electrode geometries [72]. The mixture of carbon black and readily available carbon inks made up the ink. Metallic electrodes Based on either electrode modification procedures or innate electron transport processes, metallic electrodes provide a wide range of choices for electrochemical detection. The most widely utilized techniques for creating metallic electrodes are thin-layer deposition by sputtering and evaporation. 1. Thin films It is an indirect technique for making electrodes in which metal is placed on paper after a mask has been used. By depositing metals onto the paper using sputtering, evaporation, or spraying, the paper gains conductive characteristics. Sputtering was used to deposit gold on polyester to form a metallic electrode. This electrode was used to quantify the discharge and separation of an ascorbic acid and uric acid mixture specimen on paper at clinically significant concentrations using amperometry. Then, using a metal mask and a gold-sputtered technique, 200 nm thin film electrodes were made in order to identify paracetamol and 4-aminophenol from a particular test [73]. Sputter coating is used to create platinum electrodes, which are subsequently adhered to solid substrates and put in close proximity to the paper. The flow injection detection of glucose in urine was carried out using sputtered electrodes. In urine samples, hydrogen peroxide was discovered amperometrically as a result of the reaction between glucose and glucose oxidase. 2. Wires Compared to electrodes made of carbon ink, microwires are always thought to be a superior electrode choice. Microwire electrodes have a lower resistance than conventional electrodes, which improves the electrochemical response during detection. Additionally, they are simple to clean and/or adjust before incorporating into equipment like gold. Microwires were cleaned with piranha solution to enhance the electrochemical reactivity [74]. Employing thiol-based chemistry, which connected an inner monolayer with a negative terminal, the electrodes were subsequently altered to only react to positive analytes. 3. Microelectrodes Santhiago et al. [68] created the first microelectrode for a paper-based device to carry out an operation identical to stencil printing, but instead of printing directly onto the paper, they used a laser to carve very small holes into a translucent sheet, which they then filled with carbon paste as seen in the picture. For electrochemical detection, elliptical microelectrodes were created using laser ablation. On the back of the transparency, several backfilled holes with a single electrical connection were constructed in order to carry out microelectrode array detection. With more microelectrodes in an array, the limiting current value for sigmoidal voltammetric curves rises. 4. Nanoparticle modification A technique to alter the printed electrodes on the paper involves the deposition of nanoparticles. Nanoparticles can change a material’s conductivity, modifying chemical functionality and expanding the surface area of electrodes. On SPCEs that are available for purchase, Pt nanoparticles were electrodeposited [75]. Pt boosted the measured current response at the electrode surface by catalyzing the oxidation of hydrogen peroxide. On the surface of the working electrode, gold clusters were also formed using electrodeposition. With the aid of gold-thiol chemistry, the gold enhanced the electrode’s surface area and made it possible to attach capture aptamers. Au nanoparticles were placed on cellulose fibres treated with graphene to boost the accuracy and durability of the framework for DNA detection [76]. Additionally, Au nanoparticles were deposited on the fiber’s surface, forming an interconnected layer that served as the basis for a special working electrode [77]. High conductivity and electrodes with a large surface area are produced using these manufacturing techniques. Connections In order to generate power, μPADs can use paper-based batteries; nevertheless, according to WHO guidelines, a flawless diagnostic device would operate without the use of additional batteries [78, 79]. These fluidic batteries are constructed so that the power supply is near the test, making it simpler to connect them. The fluidic battery cannot operate until the sample is placed inside the device. As a result, the sample can be utilized to power any required assay-related components in addition to conducting an assay. Due to integrated galvanic cells, fluidic batteries may provide the appropriate voltage or current. These cells can also be changed to incorporate the smallest amount of electrolytes and electrodes required for a specific procedure [80]. Detectors and readout The production of an effective paper-based device requires patterning, but patterning by itself cannot produce a suitable device unless a decent detector is built into the device. The analyte should be able to be quantified by a paper-based instrument. A single analyte was first detected by a device; however, as paper-based microfluidic devices advanced, the idea of numerous monitoring areas to capture many analytes within a single device was introduced. After printing hydrophobic patterns onto the hydrophilic paper, sensing zones can be created by spotting chemicals in the monitoring areas. The main objective of creating accurate and user-friendly devices is to eliminate the need for external instrumentation. When a ‘yes/no’ response could determine therapy, quantitative or semi-quantitative detections or readouts are preferred for on-site diagnostics devices. The most popular method for non-instrumented analysis is the employment of an externally or internally placed visual color intensity comparator. The technology is now compatible with smartphones and detectors like CCD, CMOS, flatbed scanners, etc. that are reasonably affordable and simple to use with only light to moderate training. Due to a number of factors, mobile camera technology has evolved significantly in recent years. As a result, new opportunities for using PAD technology to investigate detection in various situations have arisen. The techniques for quantitative feedback described in this study include equipment-free methods, digital cameras, and mobile phone cameras. Smartphones and digital cameras Smartphones have created a wide range of new options for analysis in contexts with limited resources, whether by on-site analysis or distant data transmission to a single location. Information can be captured remotely and kept for subsequent transportation to a central location because to the device’s enormous data storage capacity, eliminating the requirement to carry samples. In addition to having a digital camera and a light source, modern smartphones are also capable of doing tasks that would often be performed by costly spectrophotometers, fluorometers, or silicon photodetectors. Smartphones have been used to identify drugs, biomarkers, explosives, dangerous metals, and bacterial and phage infections. Smartphones operate more quickly than flatbed scanners, however, because ambient light conditions change, image intensities are inconsistent. A smartphone intensity-correction app was created to address this issue, or detection could also be made by physically blocking ambient light while taking images. Handheld devices In the past, POC applications, which can cost over 10, 000, required bulky, benchtop instruments. Although these paper devices are effective for POC applications, they do not meet the ASSURED criteria (device must be Affordable, Sensitive, Specific, User-friendly, Rapid and robust, Equipment-free, and Deliverable) of the WHO for the medical or environmental community as mentioned in the preceding section due to their pricey integrated pieces. Therefore, the detector cost-structure system must be substantially lower. For simultaneous amperometric detection of glucose, lactate, and uric acid, a low-cost eight-channel potentiostat was developed [81]. The design of the gadget for multiple electrochemical detections at once included eight unique bespoke electrochemical wells. In a handheld potentiostat more recently, 48 channels were added [82]. A portable potentiostat that can mix samples on board, execute a variety of electrochemical assays, and wirelessly send analytical data over speech through a cellphone audio connection is made for environments with limited resources. It was intended for this data transfer to make older consumer phones compatible with their system. It has also been stated that other commercially available handheld instruments may measure water contamination electrochemically or explosively using fluorometry. Detection techniques Microfluidic devices based on paper have been proposed with several different detection techniques. These detection methods have applications in environmental testing, food pathogen detection, medical diagnostics, power generation, etc. Colorimetric detection It is currently one of the frequently utilized methods for detection in PADs because of the benefits of a visible interpretation, quick detection efficiency, practicality for rural field applications, simple operation, and good stability. In colorimetric detection, the analyte solution is passively transported by capillary action to the test zone of the apparatus, where it reacts with properly positioned reagents to generate a perceptible color change. Basically, the digital/CMOS cameras, scanners, or cell phones used in PAD colorimetric detection systems are used to capture the detection zone images, which are then sent to a computer or a mobile device for processing. For colorimetry-based analysis, LFAs are the most popular PADs. Because LFAs are simple to use, biodegradable, quick, and lab-free, they are beneficial for POCT and allow for the quick sensing of biomolecules like proteins in complicated samples without prior pretreatment. The majority of commercial LFAs that rely on optical sensings, such as HIV testing, pregnancy tests, and other bios studies, have been developed using aptamer- or protein-labeled gold nanoparticle (AuNP) conjugate probes. A PAD for the identification of acetylcholinesterase activity and inhibitor screening was created by Liu and Gomez [83] based on colorimetric sensing. The fabrication of the PAD used a direct wax printing procedure in which wax was applied to the paper to form the hydrophobic barrier. Cardoso et al. [84] proposed a variety of colorimetric PADs for the measurement of numerous analytes, like whiskey, BSA, tear glucose, urea, ketone bodies, nitrite, glucose, bilirubin, etc [85, 86]. To detect Hg+2 ions, Meelapsom et al. [87] created an Ag nanoparticle-processed multi-layered PAD employing thick paper and an ink-jet printing technique. The Hg+2 ions used in the detecting procedure oxidized the Ag nanoparticles, causing them to break up into smaller particles, reducing Hg+2 to Hg, and the detection zone’s color is changed from deep yellow to vibrant yellow. It was demonstrated that the gadget could detect particles as small as 1×10-3 ppm. A PAD was created by Yamada et al. [88] to deliver the findings of chemical analysis in the manner of ”text” by combining the utilization of a conventional colorimetric indicator with an inert colorant. Protein in urine has been utilized as a proof-of-concept model analytical target. Human urine was used in user tests, and the results showed that the created device’s accuracy was on a level with a conventional dipstick. For the colorimetric detection of Hg+2, Cd+2, Zn+2, Ni+2+, and Fe+3 ions in drinking water or effluent using chromogenic chemicals, Mujawar et al. [89] proposed a PAD for recycling waste to create low-cost analytical devices. The Fe+3 ions were determined using an extremely reactive 2-hydroxy-1-naphthaldehyde (HyNA) reagent in an optical assay plate with conical wells. An excellent limit of detection and limit of quantification of total Fe+3 ions were achieved. The proposed approach proved successful in detecting and precisely determining Fe+3 ions in tap and marine water samples. Chowdury et al. [90] proposed a μPAD added with a nanosensor made of gold and functionalized with α-lipoic acid and thioguanine for detection of arsenic in hand tubewells water. By raising the pH of the PADs to 12.1, a technique was created to prevent the influence of the alkaline metals (Ca, Mg, K, and Na) prevalent in Bangladesh groundwater. This test, which evaluates if the concentration of arsenic in the water is beyond or under the WHO recommended limit of 10 g/L, was the inaugural paper-based test to be approved using water samples from Bangladesh. Liu et al. [91] demonstrated an effective framework consisting of a paper-based/PMMA chip with a colorimetric sensor to measure SO2 concentrations. The sample in the suggested apparatus was kept on a small piece of paper that had been treated with an acid–base marker before being placed inside a PMMA microchip. It was shown that the SO2 percentage results taken for 15 industrial food samples using the suggested methodology deviated from the values obtained using a recognized macroscale approach by a maximum of 4.29 percent [92]. Mahmoudi et al. [93] designed a colorimetric PAD for rapid and hands-free telomerase activity sensing by utilizing color shift in accordance with enzyme activity. The telomerase was extended along with a biotinylated probe and an oligonucleotide that was complementary to the telomeres. The hydroxylamine hydrochloride approach for enlarging the AuNPs allows for a signal enhancement that results in color that is apparent to the naked eye once the assembly has been joined. With a measurement range of 6 to 25,000 cells, visual telomerase activity identification was achieved down to 6 cells when the analytical performance of the enzyme extracted from breast cancer cells was assessed. The hue of the porous sheet evolved from light-red to light-red-blue to black-red with increasing telomerase content. Fu et al. [94] suggested a colorimetric assay for telomerase activity detection on functionalized cellulose paper using methylene blue (MB) as a colorimetric probe and was focused on telomeric elongation and collecting amplification. The telomerase substrate was placed onto sterile cellulose paper (TS). Telomerase will lengthen this primer, resulting in a long single DNA that will further catch more probes and raise the assay’s responsiveness. When MB-labeled oligonucleotides hybridize with sDNA, the color will change. Signal strength is correlated with sDNA content and hence with telomerase activity. Oligonucleotides are unable to hybridize with sDNA when telomerase is not present in the samples. Telomerase will stretch this primer to generate a single DNA (sDNA), which will further attract more probes and improve the sensitivity of the assay. The color will change when MB-labeled oligonucleotides hybridize with sDNA. The quantity of sDNA and thus the activity of telomerase is associated with signal strength. In samples lacking telomerase, oligonucleotides are not able to hybridise with sDNA. Electrochemical detection Dungchai et al. [59] merged the concept of electrochemical detection with μPADs. The channels in chromatography paper were created using photolithography and carbon electrodes were printed using screen-printing techniques. By sensing uric acid, lactate, and glucose in biological samples, Dungchai and coworkers further demonstrated the device’s biosensory capacity. The three different electrodes in this trial are changed with lactate oxidase, glucose oxidase, and urease, respectively, by adding enzyme solution into the corresponding test region. Diabetes is a very common disease and the glucose levels of the patient must be continuously monitored in an easy way. In order to measure glucose levels, Fernando et al. [95] created an electrochemical microfluidic paper-based analysis device (PAD) that utilises sweat and saliva as a sample. The creation of a three-electrode system uses pseudo-reference stainless steel and a working electrode that has been anodized using sodium potassium tartrate tetrahydrate. With a limit of detection of 0.058 mmol dm-3 and a working range of 1 to 10 mmol dm-3, cyclic voltammetric-based assessment of glucose using PAD achieved a linear response. Fonseca et al. [96] gave the basic concept of making disposable ePADs by employing screen printing and inexpensive materials. All the devices were built utilizing liner paper as a base and carbon ink that was made with wood glue and graphite powder. The ePAD was assessed as a biosensor and electrochemical sensor. Moreover, Tomei et al. [97] fabricated a strip to identify the level of glutathione in blood. A filter paper was used as a substrate where WE and CE were screen-printed, hydrophobic channels were wax printed and then the solution was confined in an area to prevent diffusion of electric contacts. The loaded cystamine on WE and the glutathione, which was liberated by blood lysis, engage in a thiol-disulfide exchange reaction, which is the basis for the detection. Due to the electrocatalytic abilities of Prussian Blue included in the WE, this reaction results in cysteamine, a molecule readily oxidizable. Ruecha et al. [98] proposed a label-free disposable PAD to detect human interferon-gamma (IFN-γ) by making three electrodes on the Whatman filter paper grade No. In order to screen print the working electrode (WE) and the reference (RE) and counter electrodes, the wax-patterned device was divided into two tabs (CE) so that they can fold over one another. The working electrode was made with graphene ink and polyaniline to immobilize human IFN-γ monoclonal antibodies covalently. Wang et al. [99] developed an origami-style device to detect breast cancer MCF-7 cell line. Three spatially isolated sections of wax and a screen-printed WE of carbon were printed on paper grade 2. The hydrophilic zone in the reference region also has a carbon CE and an Ag/AgCl RE. The produced Au@3D-rGO was then coated with the MCF-7 cell-specific aptamer H1. To make it straightforward to combine the full screen-printed, three-electrode electrochemical cell, the different patterned pieces of the paper component were wrapped in a two-step folded pattern once the solution had been added. Likewise, Moazeni et al. [100] detected the biomarker of tumor i.e., α-fetoprotein in human serum by embedding finger-type silver-carbon electrode pairs on paper substrate. The devices were created using a top layer of a substrate treated with aldehydes and a lower flexible sheet of plastic. Diphenylalanine nanostructures were positioned on the paper to integrate different groups and help with the covalent immobilisation of antibodies to the target compound. To detect CEA in samples of human serum, another paper employed the multilayer structure. On a section of the device with structure, a molecularly imprinted polymer (MIP), which was electro-synthesized in the presence of the target analyte, was electro-synthesized and used as the particular receptor for these target analytes. In a different but identical portion of the device, a non-imprinted polymer was created in the same way as the MIP [101]. Also, for the rapid and easy identification of infectious diseases, brought on by pathogenic microorganisms by aiding affinity-based biosensors and amplification of the genetics were used in many papers. Like, He at al. [102] created an origami style PAD to identify the salmonella pathogen Salmonella typhimurium by combining wax and screen printing. By flipping the various origami pieces, the device was used to execute cell lysis, DNA extraction, and LAMP. When compared to PCR results, the device could identify the pathogens in whole blood with a sensitivity of 82 percent and a specificity of 91 percent. Finding antibiotic resistance is an intriguing strategy for managing infectious diseases. Santhiago et al. [103] described the electrochemical characterization of a 3-D PAD for p-nitrophenol analysis. The filtration-integrated PAD was made using regular printing paper that had been wax-printed with a design to allow quick evaluate p-nitrophenol information with a quick response code. The instruments were used to measure the presence of p-nitrophenol in water samples, with a recovery rate varying from 91.8 to 108.2 percent. Nowadays, cardiovascular disease (CVD) is the major cause of death worldwide. As a result, for the diagnosis and monitoring of illnesses, a sophisticated and reasonably priced POC-detecting device is required. Bookaew et al. [104] made an ePAD to simultaneously measure three key CVDs biomarkers, including C-reactive protein (CRP), troponin I (cTnI), and procalcitonin, using a label-free immunoassay. The sample inlet, all detection zones, and their connecting channels were defined by wax on the paper. They used square wave voltammetry to measure the concentrations of the CVDs biomarkers (SWV). When the cardiac marker was present, there was a noticeable reduction difference in the response curve in a concentration-dependent manner, even though there was no discernible difference in the response curve when it was absent. Yakoh et al. [105] designed two models for fluid delivery in a μPAD that can successively store and transport reagents to the required zone without an external source. This 3D capillary-driven device was made of origami folded paper and a portable pad for electrochemical detection of biological organisms to illustrate the breadth of this technique. The single buffer injection was developed for ascorbic acid sensing utilizing a flow-through arrangement. They extended the usefulness of the device to integrate experiments by adopting a stopped-flow mode. Fluorescent detection It is centered on the estimation of the amount of light that a material emits after having first absorbed electromagnetic radiation. It typically encounters problems in PADs because a commonly available paper with chemicals that also self-fluoresce and generate a lot of background noise. However, numerous fluorescence sensors incorporated with any textile material have been created and have poor sensitivity. Wang et al. [106] illustrated a cloth/paper hybrid μPAD for identification of mercury(Hg+2) and lead (Pb+2) ions in water. After adhering quantum dots to the cotton cloth, ion-imprinted polymers were employed to alter the fluorescence-detecting cloth-based component (IIP). The limits of detection for the fluorescence signals were achieved using fluorescence quenching action. Zhu et al. [107] tested Alkaline phosphatase and butyrylcholinesterase simultaneously by 3D origami μPAD in which sample-in-result-out platform fitted. These two indicators were also used in a rationally designed cascade catalytic reaction for sensing ALP and BChE. Using appropriate metal molds and one-step mapping with a black oil-based pigment, a 3D origami PAD with 4 levels and two parallel channels was created. Using a smartphone camera and red-green-blue software, fluorescent images on the detecting region can be obtained after simply folding the paper and then again unfolding nearby surfaces to begin the reactivity of charged chemicals. Under ideal circumstances, the suggested platform was used to sense ALP and BChE in human serum samples do not necessitate any preparatory procedures. Shi et al. [108] proposed a simple method for creating carbon nanodots that are nitrogen-doped in yellow fluorescence (y-CDs). The 4-amino salicylic acid was used as the precursor compound in a one-step hydrothermal process without further surface passivation or modification to create the sensor strip of paper comprising y-CDs. These y-CDs have been used for intracellular Al+3 imaging and paper-based Al+3 sensing in living cells without interference from autofluorescence because of these outstanding features. In order to detect Hg+2 ions, Zong et al. [109] created the reversible red fluorescent probe the (NDI-5), which was primarily composed of the receptor bis[2-(3,5-dimethylpyrazol-1 yl)ethyl]amine and the strong electron-withdrawing unit naphthalene diimide. The probe NDI-5 showed a rapid and selective ‘turn-on’ fluorescence response to Hg+2 ions because the coordination of Hg+2 ions can push the potential twisted intermolecular charge transfer (TICT) in the entire molecule. For the semi-quantitative testing of Cu+2 ions, Liu et al. [110] showed how to make dual-colored CD ratiometric fluorescent test paper. The visual assessment of Cu+2 ions using the ratiometric fluorescent test paper has been effectively created in multiple key areas. (1) The remaining p-PDA effectively binds Cu+2 ions on the surface of r-CDs. (2) The Cu+2 ion functions as a link, allowing the small b-CDs to be transferred onto the surface of larger r-CDs by its double coordinating connections with the surface ligands of both r-CDs and b-CDs. (3) The b-CDs undergo a particular spectral energy transfer to the r-CD-Cu+2 complex. Chemiluminescence detection Another sensitive and effective detection method for PADs is chemiluminescence sensing. The method shines in terms of its ease of use, fast response, and interoperability with micro technologies, enabling numerous applications, even for those who are not trained [111]. However, the sensing must be done in the dark, which makes it more difficult to make the device. Portable chemiluminescence readers are also required for this procedure. The chemiluminescence (CL) technique and μPADs were integrated for the first time by Yu et al. [112] to create a unique CL PAD biosensor. The oxidase enzyme reactions and the chemiluminescence reaction between a rhodanine derivative and produced H2 O2 in an acid medium are the foundations of this lab-on-paper biosensor. This CL PAD biosensor was skillful in quantitatively determining uric acid with accurate and satisfying results. Then, the same researcher [113] created a PCAD to sense both glucose and uric acid in fake urine simultaneously. They discovered that by varying the ranges that the samples traveled, it was feasible to simultaneously measure uric acid and glucose. Al et al. [114] invented a portable PAD for on-site screening of dangerous mercury ions (Hg+2) in cosmetics with a limit of detection of 0.04 g ml. It is founded on the fundamental ability of quantum dots of carbon (CQDs) to function as an excellent emitter for the bis(2,4,6-trichlorophenyl)oxalate (TCPO)-hydrogen peroxide (H2O2) CL reaction. Zangheri et al. [115] created a biosensor that uses a CL-lateral flow immunoassay (LFIA) technique to detect salivary cortisol quantitatively using a smartphone app. The biosensor works by using a peroxidase-cortisol conjugate in a direct competitive immunoassay and detecting the result by incorporating the chemiluminescent substrates enhancer/H2O2/luminol. It provides quantitative analysis between 0.3 and 60 ng/ml for the therapeutically appropriate range of salivary cortisol detection. Electrochemiluminescence Electrochemical processes are the basis for electrochemiluminescence sensing methods, which produce luminescence. When electrochemically produced intermediates go through exergonic processes, they enter an electrically excited state. As they unwind and become more tranquil, the molecules in this condition produce light, enabling monitoring systems without a photo-detector being necessary. The ability of electrochemiluminescence sense to be enforced to both luminescence and electrochemical sensing techniques is its most notable characteristic. In comparison to chemiluminescence, electrochemiluminescence also has some benefits, including a decreased background, the ability to manage reagent synthesis, and greater selectivity through potential control [116]. Delaney et al. [117] firstly merged paper microfluidics with electrochemiluminescent (ECL) detection by paring inkjet-printed paper with screen-printed electrodes, that may be read without a conventional photodetector. For the first time, Wu et al. [118] created a paper-based electrochemiluminescence (ECL) origami device (PECLOD) and combined the rolling circle amplification (RCA) method with oligonucleotide functionalized carbon dots (CDs) to create a cascade signal amplification method for the sensing of IgG antigen. The RCA product’s tandem-repeat cycles could serve as an excellent model for the regular construction of CDs, which would then display many CD tags for ECL readout per protein recognition event. The recently suggested wax-printed 2D μPADs based on immediately screen-printed electrodes on paper was the first to incorporate electrochemiluminescence (ECL) immunoassay [119]. Four tumor markers were identified using a standard tris -(bipyridine)- ruthenium - tri -n- propylamine ECL system in actual clinical serum samples. Eight working electrodes were consecutively inserted into the circuit with the help of a simple mounted and a section switch included into the analyzer to start the ECL response in the scanning band between 0.5 to 1.1 V at ambient conditions. Yan et al. [120] included electrochemiluminescence immunoassay capabilities into wax-patterned PADs that were based on screen-printed electrodes. At room temperature, the ECL reaction was started with the help of a homemade device holder. This paper-based ECL 3D immunodevice was utilized to perform a standard tris(bipyridine)ruthenium-tri-n-propylamine ECL system for the diagnosis of carcinoembryonic antigens in actual clinical serum samples. Theoretical Analysis The fluid moves in the porous substrate can be categorized into two processes, the wet-out process, and the fully wetted flow (as shown in Fig. 12). The wet-out process: the fluid is moving forward the dry porous media. It is modeled using the Lucas-Washburn equation. In the fully wetted flow, the fluid moves along the wetted porous media and is described by Darcy’s law.Fig. 12 Representation of physical mechanisms governing the behaviour of liquids in porous materials Lucas-Washburn equation Lucas and Washburn proposed this model to explain the behavior of liquid wicking in porous materials. The porous microstructure of paper can be compared to a collection of cylindrical tubes where capillary action drives the liquid flow [121]. It is a process of momentum balancing between the hydrostatic pressure, capillary force, and viscous force. According to L–W equation: Inertia force = surface tension + gravity force + viscous force1 ρπr2δδt(h(t)δh(t)δt)=2πrσcosϕ-πr2ρgh(t)-8πηh(t)δh(t)δt where σ is surface tension, r is the radius of the meniscus, ρ is the density of the liquid, ϕ is the equilibrium contact angle and h are distance the liquid front has traveled. The Lucas-Washburn model considers a few key assumptions, including that (i) evaporation does not take place (ii) gravity and inertia forces are neglected, (iii) the fibrous porous material is homogenous, (iv) boundaries have no impact on capillary flow, and (v) wicking liquid is laminar, incompressible, and low viscous. In consideration of these assumptions, Eq. (1) will become,2 2πrσcosϕ=8πηh(t)δh(t)δth=4σcosϕζηϵrt1/2 Where t is the liquid absorption period and h is the length of the paper’s wetted area after time. Since σ,ϕ,η, and r are all constants and the wicking length (h) is proportional to the square root of time the fluid-front velocity drops over time due to the flow resistance provided by porous media’s surface [49]. The aforementioned assumptions place restrictions on Eq. (2). As a result, many changed models are created to provide better explanations. L- W model considering gravity force In some circumstances, it can be challenging to utilize the standard L-W equation to determine the performance of device as different diagnostic tools and experimental paper strips operated vertically. The force of gravity commences existing as a result of fluid flowing vertically. The gravitational force eventually becomes a significant role in the liquid immigration process as the liquid rises, which causes a substantial difference between the theoretical and experimental liquid front. A general correlation between the liquid front and time is created to address this issue [122, 123]. From Eq. (1) we obtain2πrσcosϕ=πr2ρgh(t)+8πηh(t)δh(t)δt The equation can be further written in the scaling form:σrh∼ρg+ηhr2 Therefore, the driving capillary pressure gradient is balanced by both the force of gravity and viscous friction. After integrating the above equationh=2σrtη-ρgr2tη Substituting the radius rl of the leading meniscus (deduced from the condition (δhδr)=0 at r=rl) in the previous equationrl∼ηr8ρ2g2t1/3 we obtain the value of h(t) at r=rl3 h(t)∼σ2tηρg1/3 The connection demonstrates that the h has a linear relationship with t1/3 as shown in Eq. (3). The modified model considering evaporation When the temperatures are high and the relative humidity is low, the assumption that there is no evaporation occurs may cause an overestimation of liquid flow over an extended period in an open environment. By ignoring the gravitational influence, one can examine evaporation, which is consistent with observations on the wetting process [48, 124]. Empirical correlation from the ASHRAE handbook to calculate the rate of water evaporation at each relative humidity,mev=(ps-pp)×(0.089+0.0782hfg)ma where, ps,pp,hfg, and ma are the saturation pressure, partial pressure of water vapor, latent heat of vaporization, and air flow rate respectively. The partial pressure of water vapour in the air and the water saturation pressure at a fixed pressure and temperature are used to define the relative humidity. The relative humidity(π)=ppps Therefore, we obtain4 mev′=(1-π)×ps×(0.089+0.0782×hfg)ma The integral formula can be used to determine the total evaporation mass at every instant in the evaporation model:5 mev=2∫0tmev′wh~dt where, h~ is the expected wicking height of the liquid. The expected wicking liquid mass me at any instance is the difference between the theoretical value mo and the evaporation mass mev,me=mo-mev=ρwδ4σϵcosϕζηrt1/2-2∫0tmev′wh~dt Wicking mass of liquid me can be attained by the wicking liquid density and its volume,me=ρwδϵh~ Therefore, the wicking liquid height can be given by6 h~=mevρwδϵ=4σcosϕζηϵrt1/2-2mev′ρδϵ∫0th~dt By taking a time derivative, the Eq. (6) is recast as:7 dh~dt=Rt-1/2-Sh~ Boundary condition: h~=0, at t=0R=2mev′ρδϵS=σcosϕζηϵr The solution to Eq. (7) is therefore8 h~=2Se-Rt∫0teRt2dt The liquid-wicking process exhibits a dynamic character due to evaporation. Equation (8) represents the wicking distance with due accounting of evaporation from the surface. This adjustment may be needed depending on the particular experiment. Darcy’s Law It was first used in 1856 to describe the fluid flow through a fully saturated porous substrate by Henry Darcy [125]. This model was created using the momentum equation to address the issue of liquid flow in pre-wet porous media under steady-state conditions. By examining how water moves through sand, the viscous pressure loss is written as:9 ∇P=-ηζv where v is the average velocity vector, ζ is the substrate permeability, η fluid viscosity, and ∇P is the pressure drop per unit length also known as Laplace pressure. Using the paper substrate, calculate the fluid’s imbibition rate (v^), the above equation is further expanded to yield:v^=ζi∇Pηh(t) where ζi=ζϵ is the interstitial permeability and the porosity ϵ=1-γρh,γ is the weight, ρ and h are the density and thickness of the paper respectively. Darcy’s law finds out the flow rate Q under a pressure differential ∇P, by using the Navier–Stokes equation:10 Q=-ζγhηL∇P⇒∇P=-ηLζγhQ In this expression, ∇P=P(0)-P(h), where P(0) is the pressure at x=0, and P(l) is the average capillary pressure. A hydrodynamic load term with a general flow resistance Rhyd is also included in the flow domain for the model system under considerationQ=-∇PRhyd The above equation is analogous to Ohm’s law of an electrical circuit, I=∇VR, where I is the electric current, R is the electrical resistance and ∇V is the potential drop. In hydrodynamic systems the volumetric flow rate, Q is the volume per unit of time, while in electric system current is the charge per unit of time. Also, ∇P is analogous to potential drop. Since capillary force is the primary factor influencing analyte transport in PADs, low spontaneous imbibition rates may reduce the detection sensitivity. For building sensitive and precise PADs, a quantitative understanding of internal spontaneous capillary flow progression is necessary. Wang et al. [126] examined the capillary flow in a porous substrate both experimentally and numerically. The authors computationally analyzed the experimental data in order to enhance the prediction of spontaneous imbibition. The quasi-static pore-network modeling of a real filter paper used to establish the equilibrium two-phase flow material parameters reveals that neither the single-phase Darcy model nor the Richards equation adequately anticipates spontaneous imbibition. A new numerical simulation using the finite element method called PORE-FLOW was presented to describe these imbibitional flows in wicks with complex forms [127]. Additionally, two-dimensional (2D) wicking in modified cylindrical wicks with two different cross-sectional areas is predicted using the simulation. Later, the wicking behavior of a few further types of changed wicks with noticeable changes in their cross-sectional areas was statistically examined. It was found that the history of the liquid ingested was related to the height of the liquid front as a function of time. The Richards equation, which accounts for the dynamic capillarity effect, shows the capacity to predict when wetting saturation will begin. Liu et al. [128] used three-width strips of filter paper to measure the liquid mass and height through experimental and numerical investigation. To calculate wicking height and mass, a modified model that takes the evaporation impact into account was developed. It was found that after initially declining sharply, the wicking speed stabilized at a lower level and remained steady. With a wider strip, more wicking mass could be achieved, but reagent loss increases in proportion. Ouyang et al. [129] advanced the use of the numerical simulation method to examine PAD fuel cells. To show how the paper-based microfluidic fuel cell functions as a whole, both transient and steady-state modes were used. Moreover, the effects of several structural characteristics on cell performance, such as electrode spacing, the distance between the electrode and the inlet, channel thickness, and electrode length, were also explored. Results demonstrated that decreasing cell output power to varying degrees, as major structural factors are increased. Modha et al. [130] described the behavior of paper-grooved channels and evaluated how well they function as ‘delay’ mechanisms for a multi-fluid paper-based sensor. Moreover, the author also performed In-silico simulations that can accurately anticipate imbibition in both natural paper and grooved channels. Elizalde et al. [131] hypothetically investigated capillary imbibition in substrates that mimic paper in order to more clearly visualize fluid transport in the context of the macroscopic shape of the flow domain. A model that predicts the cross-sectional profile required for a specific fluid velocity or mass transfer rate has been created for uniform materials with arbitrary cross-sectional shapes. The capillary flow in a closed system is described by two theoretical models that are provided [132]. Both the first and second models account for liquid imbibition into the paper matrix and flow through non-absorbing surfaces (flow in the gap). Significant conformity between the experimental results and the model solutions was found. The provided volume to the flow on the non-absorbing surface was shown to have an impact that improved the forecasts. The influence was found to be minimal at low flow rates but strong at high flow rates. This work demonstrates that the flow dynamics are influenced when a casing is added to a device, despite the fact that several experiments on flow in PADs were carried out on open systems. Employing various width sheets of filter paper, Patari et al. [124] conducted experimental and computational research on the wicking height and mass. Given that there is a linear relationship between wicking height and mass, it is convenient to evaluate the effective porosity. The proposed model with evaporation was required in order to explain the foundations of flowing fluid in testing paper and to provide relevant and useful benchmarks for the creation of PAD. Rosenfeld et al. [133] described an analytical and experimental investigation of a brand-new PAD for sample focusing by isotachophoresis. The author demonstrated that peak enhancement by significant sample focusing (on the order of 1000-fold) may be accomplished in a matter of minutes, despite the fact that dispersion was far more significant in paper than in glass. A handy figure of merit was provided by our analytical approach for assessing the effectiveness of ITP focusing. They demonstrated that, despite the stated improvements, the device’s efficiency was only about 10 percent, meaning the amount of sample accumulated was well below the theoretical upper limit. In microgravity, the phenomenon of absorption in a porous substrate underneath the presence of capillary forces was studied [134]. The impact of non-stationary and convective factors on the imbibition process is examined in the analysis of the momentum conservation equation. The outcomes of numerical modeling of the recurrent imbibition process under the influence of capillary forces in microgravity in an irregularly shaped porous material are reported. The mathematical model of the imbibition phenomenon was presented by More et al. [135] to compare the saturation level for different time and distance levels that have been discussed between homogeneous and heterogeneous porous medium for various types of sands. Numerous natural and industrial processes can be benefited from spontaneous imbibition. Using the phase-field method, numerical simulations of counter-current absorption in porous media with various pore structures were carried out [136]. According to the simulation results, heterogeneous porous medium produced more oil than homogeneous porous media did. According to evidence, counter-current imbibition was significantly influenced by the differential between capillary driving pressure and capillary back pressure, which were both directly related to the pore structure and pore size distribution of porous media. Wang et al. [137] used numerical simulation to examine the paper-based microfluidic fuel cells in both transient and steady-state modes. Additionally, the effects of several structural characteristics on cell performance, such as electrode spacing, the distance between the electrode and the inlet, channel thickness, and electrode length, were also explored. The findings accelerated the development of microfluidic fuel cells by serving as both a theoretical foundation and a point of reference for the next optimization efforts. Applications Medical diagnosis Point-of-care (POC) diagnosis is crucial for both the diagnosis and treatment of diseases. The objective of POC is to offer a solution when a sample is delivered to the equipment to make an informed decision. The main goal of paper-based microfluidics is to give developing nations a platform for low-cost illness diagnostics and environmental monitoring. It emerged as less priced, simple to use, and portable analytical test equipment. The development of medical science is aided by cutting-edge research in the field of PAD that provide quick, effective POC diagnostics. Due to the appealing features of PADs (low cost, no external pumping system needed, multiplexed assays, etc.) and their clinical applications, their range has expanded to POCs in resource-poor environments, home medical care, and severe disease biomedical diagnosis. However, the technology is semi-ready, and it still needs further development to achieve proper quantitative analysis. Here are some of the most important applications of PAD in the medical field: Plasma separation Since most medical diagnoses require a blood test as a prerequisite or necessary step, blood is the most important clinical analyte. The accurate interpretation of blood can deliver extensive information about a candidate’s physiological state, enabling effective pathological diagnosis. The examination of blood, which is a complicated mixture of red blood cells, white blood cells, plasma, and other necessary components, is challenging. Because it transports all the vitamins, proteins, and minerals throughout the body, it controls all hemostatic and physiological parameters and could be used as a diagnostic analyte. First, the serum must be isolated from whole blood to be clinically diagnosed. For diagnosing either erythrocyte-related information or a routine concern of the other blood constituents excluding the erythrocytes, the separation of plasma from that of the whole blood is always the first step. Due to the presence of erythrocytes during the diagnosis, it is frequently difficult to detect a complex analyte like blood utilizing colorimetric, fluorescence, and chemiluminescence methods. These red blood cells may agglutinate and interfere with biochemical processes, as well as convert chemical signals to optical signals when used with color-based or optical-based sensing technologies. Erythrocytes influence the rheological dynamics of the blood in electrochemical detection situations. Therefore, separating the plasma from the erythrocytes is a step that must be taken while diagnosing blood. The use of RBC-specific adherent membranes, which permit plasma to pass through the paper, is the most used method for separating RBCs [138]. To separate RBCs from whole blood, electrochemical techniques [139] and agglutination reagent [140] have attracted interest as they could directly operate the whole blood sample as shown in Fig. 13. A cheap paper-based platform was created by Kar et al. [141] to extract blood plasma from a whole blood sample. They created a paper gadget based on the elegant separation method and the straightforward origami method, where the complete device is built by folding a single sheet of flat paper. This technique can be used to quickly identify sick states in blood samples without the use of experienced workers or specialized lab settings. Another device for separating plasma from whole blood and determining glucose concentration was described [142]. This device does not require a membrane to separate the plasma from the whole blood sample and will be helpful in creating POC testing equipment that can identify analytes in small sample quantities. A BPS PAD was created by Burgos et al. [143] to identify and measure the S100B biomarker in peripheral whole blood. The VF2 collecting pad, which conducts vertical and lateral plasma separation was added with the complete blood sample. As a result of the cells creating and becoming trapped in the VF2 matrix due to hypertonic circumstances, the addition of NaCl to the VF2 pad causes RBCs to aggregate and increased plasma wicking.Fig. 13 Schematic diagram of the RBC agglutination to increase the effectiveness of filtration to separate blood plasma from entire blood. a Due to their deformability, RBCs can pass freely via filters. b RBCs cannot pass through filtration with pores smaller than 2.5 mm, while the flow of segregated plasma is severely hampered by small pores. c Large multicellular aggregates made of agglutinated RBCs might be removed utilising filters with large-diameter pores, allowing for faster flow rates of segregated plasma through the filters Blood typing The classification of blood due to the presence of antibodies and hereditary antigenic compounds on the surface of red blood cells is known as blood typing. For several medical operations, including blood transfusion and transplantation, it is important to know your blood type [144]. The situations of hemolytic transfusion reactions and other deadly outcomes can be avoided with the accurate identification of blood groups. The earliest techniques for blood typing relied on laboratory-based equipment, which does not adhere to WHO’s ASSURED recommendations. Gel columns [145], thin-layer chromatography (TLC)-immunostaining [146], are the traditional blood-typing methods. In order to determine the blood type using agglutinated and nonagglutinated red blood cells. Khan et al. [147] proposed an inexpensive, appealing paper-based alternative. A piece of paper that had been treated with an antibody was the subject of an investigation by Jarujamrus et al. [148] The network of paper fibers becomes tangled with a mass of agglutinated cells that are produced when antibodies are desorbed from cellulose fibers. The assay performance influencing variables have been investigated, including antibody stability, papermaking additives, and paper structure. Larpant et al. [149] simultaneously suggested a simple and low-cost PAD for phenotyping RBC antigens. Using this Rh typing method, five Rh antigens on RBCs can be recognised and observed under a microscope in less than 12 min. The suggested Rh phenotyping is dependent on the hemagglutination in the sample zones following immobilisation of the antibodies directed at each Rh antigen. Detection of hormones in non-invasive body fluids Non-invasive fluids are defined as substances that exist out of the human body. These include human breast milk, saliva, perspiration, and urine. These fluids have also been used for monitoring blood sugar, diagnosing celiac disease, evaluating alteration in body fluids, measuring pH and sodium levels in saliva and sweat, determining body fluid dynamics, and more ( [150–152], etc.). A DNA aptamer-based sensor was developed [153] to identify dopamine in urine. Duplex aptamer dissociation served as the method’s foundation, in which dopamine in the urine caused the sensor to alter conformation and become released from the capture probe. Schonhorn et al. [154] created a sandwich immunoassay for the pregnancy biomarker (human chorionic gonadotropin) hCG detection in urine. The experiment involved a three-dimensional patterned piece of paper with unaltered and hydrophobic wax-printed sections. The detection limit for this colorimetric approach was 6.7 mIU/ml, and the detection range was 0–250 mIU/ml. Within 10 min, the test’s findings were ready. A unique molecularly imprinted polymer (MIP) grafted PAD for the sensing of 17-E2, which are essential for female menstrual and estrous cycles, was created by Xiao et al. [155] by using 12 mL of acetonitrile as the solvent, and using the molar ratios of 12:12:1 for the crosslinker, functional monomer, and template molecule. The detection limit for 17-estradiol in samples of human milk and urine using this method was determined to be 0.25 g/l. Detection of hormones in invasive body fluids These bodily fluids are the liquids that remain in the body. These consist of pleural fluids, blood plasma, blood serum, cerebrospinal fluid, and ascitic fluid [156]. Other applications of invasive body fluids include glucose monitoring [157], proteome analysis [158], the creation of wearable electrochemically active biosensors [159], the detection of antibodies [160], postmortem toxicology profiles, the diagnosis of Alzheimer’s disease using specific peptides [161], and the identification of biomarkers for various diseases. A device was created by Rattanarat et al. [162] to detect dopamine in serum samples using electrochemical paper that had been treated with sodium dodecyl sulfate. With a dynamic detection range of 1–100 uM and a detection limit of 0.37 M, this three-layer device was a simple, affordable technique. Shao et al. [163] created a low-cost kit for quick PCT detection because procalcitonin (PCT) is frequently utilized as a detector for bacterial infection. This approach was created for quick on-site detection with quick results by combining a double antibody sandwich immunofluorescent test with the traditional LFA. The WHO designated the onset of a novel coronavirus disease to be a public health emergency of global concern in January 2020. A general strategy to stop the spread of the COVID-19 outbreak is to isolate the infected individuals using efficient diagnostic techniques; the commonly used diagnosis technique currently in use is RT-PCR. Paper-based devices, as opposed to RT-PCR, are analytical tools that may perform rapid and accurate biomolecular detection without the need for laboratory-grade equipment or trained personnel. A low-cost and easily available serological technique to detect SARS-CoV-2 humanized antibodies was developed [164]. In this study, a common serological assay technique, ELISA, was combined with paper-based devices and the synthesized SARS-CoV-2 nucleocapsid antigen was deposited on the PAD. The recombinant antigen on the device might bind to the target antibodies in the human serum and create an immunological complex. It only took 30 min to complete the colorimetric reaction using the tetramethylbenzidine substrate and horseradish peroxidase (TMB/HRP), which is substantially faster than a typical ELISA experiment (usually 1 to 2 h). Yang et al. [165] suggested a possible RNA-based POC diagnostic tool for COVID-19 detection that integrates a paper-based POC diagnostic tool and LAMP assay technology. Nasal swabs can be used by home quarantine patients to collect their infected specimens. The colorimetric outcome of the LAMP reaction can then be seen on paper with the addition of certain reagents. The user could submit the output to cloud storage through the Internet by using a mobile phone camera to record the colorimetric shift. Using the Francisella novicida Cas9 enzyme [166], created a CRISPR-based diagnostic paper test strip for the detection of the N501Y mutation. This assay has the potential to be tailored to additional interesting mutations in addition to being able to identify SARS-CoV-2 infection with this mutation. Yakoh et al. [105] presented a paper-based electrochemical biosensor, outlining a label-free technique for S protein antigen detection. An origami platform was created using chromatography paper as the substrate, and carbon-based electrodes were printed on it. SARS-CoV-2 IgM was then immobilized at the working electrode that had been modified with graphene oxide for antigen binding. Additionally, paper microfluidics and ELISA tests were coupled to allow for the detection and quantification of multiplex antibodies from an individual health serum sample. Gong et al. [167] carried this out utilizing a porous material and wax fabrication method for printing. It executes all the necessary ELISA test phases as well as the instrument-free sampling and monitoring of serum samples. A paper-based biosensor with gold-hybridized zinc oxide nanowires (ZnO NWs) was presented [168], in which the working electrode was a critical component (WE). In less than 30 min, our biosensor could distinguish between IgG antibody concentrations against the SARS-CoV-2 spike glycoprotein S1 unit utilizing impedimetric signal variations. For the quick and accurate sensing of SARS-CoV-2 spike antigen, Liu et al. [169] created a novel lateral flow strip-integrated nanozyme and enzymatic chemiluminescence immunoassay-based chemiluminescence testing. The paper test is based on a potent Co-Fe@hemin-peroxidase nanozyme that catalyses chemiluminescence equivalent to native peroxidase HRP and boosts immune reaction signal. Detection of other biomarkers Monitoring of protein- and DNA-based indicator is one of the most rapidly expanding areas of research for POC detection. For the unique detection of active pharmacological components in antituberculosis (TB) medications, color bars were used [170]. Similar to this, Koesdjojo et al. [171] proposed a method for anti-malarial medication. To increase the enzymatic filtration of the HIV DNA tenfold in a short period of time, a PAD for the detection of HIV DNA was developed. Monitoring of protein- and DNA-based biomarkers is one of the most rapidly expanding areas of research for POC detection. The enzymatic preservation, element blending, and repressor polymerase amplification of HIV DNA processes are all combined on the paper by PAD. The Zika virus (ZIKV) was tested on a platform created [172] using RT-LAMP, and the entire procedure was carried out on a microfluidic chip made of wax-printed paper. The paper fibers in the device could pretreat large size molecules when a volume of blood serum or urine was introduced. Furthermore, proteins and other cell pieces were left behind due to the significant negative polarity of the cellulose fibers in paper, while the viral RNA with negative charges migrated to the end of the channel. On a straightforward hot plate, the target nucleic acids were amplified, and the results of the amplification can be determined by gauging the intensity of the pH indicator dye that was added. The most frequent infection that causes gastroenteritis in children, rotavirus A, has also been detected using LAMP-based paper devices [173]. It simply took 30 min to finish the thermal RNA amplification and nucleic acid extraction on a plain paper disc. Rotavirus A positive amplification result is instantly visible to the unaided eye as rose-red on the paper. Environmental monitoring Environmental deterioration has recently become the top worry for environmentalists. Ample resources, such as power and water, are needed for both home and industrial activities due to the continuously growing population and progress of the human race. The side products and leftovers of industrialization are released into the ambiance at the same time in the form of hazardous gases and effluents. Therefore, it is urgently necessary to control and regulate the toxins, particularly in the ambiance fluid. Nie et a. [67] presented the first instance of a paper-based sensor designed for the sensing of heavy metal in 2010. To move the sample through the device, they used screen-printed electrodes made from paper, on which microchannels were created using patterning methods. Mensah et al. [174] developed solid-contact ion-selective electrodes (SC-ISEs) based on a porous site to quantify Cd+2, Ag+, and K+. To accomplish the specificity for the ions, PAD was equipped with a membrane that contains ionic sites, and traditional ionophores for Cd+2, Ag+, and K+. Yu et al. [175] created a device based on the lamination approach to detect lead. A spatula was used to apply conductive electrodes to the paper after it had been cut out using a CO2 laser to seep the ink into the paper. The electrode layer of PAD was then positioned between two more paper layers that had been sandwiched together and layered with the biodegradable polyester polycaprolactone (PCL). The resulting laminated electrodes were then permanently put together to provide a durable and practical device. Wang et al. [176] created a paper-based multianalyte detection system in 2018 using nitrocellulose paper (0.45 m pore size). The three-electrode cell used in the paper-based electrodes was created using the magnetron sputtering technique, which spat a thin layer of gold onto the paper. PAD’s capabilities were initially tested for the purpose of detecting Cu+2, which was then used to refine the voltammetric parameters. Studying the interference from Pb+2, Cd+2, Zn+2, Bi+3, Cl, Na+, and K+ revealed that the Cu+2 signal decreased by up to 10 percent, reaching a value of 15 percent in the presence of Pb+2, while still demonstrating the device’s good performance. A separate methodology was proposed by Shimizu et al. [177] for quantification of phosphate over paper. The Murphy and Riley approach was used by the authors, and they took advantage of the P-Mo complex’s creation in a solution before introducing the analyte and the reagents to the paper electrode. It has been demonstrated that using this method enables simultaneous increases in the active regions and unhindered redox processes. For the monitoring of paraoxon-ethyl in soil and fertilized soil samples, Cioffi et al. [178] created an electrochemical biosensor based on office paper. The sample required 100 L of aqueous solution (2 percent ethanol) for the treatment, accompanied by a vortex and filtration with an MF-Millipore Membrane Filter. The bio detector was able to detect quantities of 10 and 25 ng/mL in soil with recovery values of 84 percent and 97 percent, respectively, based on a signal-to-noise ratio of 3 in standard solutions. A unique paper-based immunoassay was created for the accurate measurement of ethinyl estradiol (EE2) in water samples [179]. The silica nanoparticles were utilized to enhance the coating of biomolecule immobilization, enabling an improvement in their assimilation into the device and resulting in signal amplification. In order to capture and preconcentrate EE2, river water specimen were integrated to the amended layer of hydrophilic microzones as shown in Fig. 14. Paper microzones were then placed over the decreased graphene sheet on a carbon electrode that had been screen-printed. To desorbate the bound EE2, sulfuric acid solution was placed to the paper microzones. The recovered EE2 was electrochemically detected using square-wave voltammetry, and the oxidation current that resulted was comparable to the EE2 level in the sample.Fig. 14 Schematic diagram of the electrochemical paper-based immunocapture assay to determine the quantity of ethinylestradiol (EE2) in samples. a Paper microzones, b paper altered with anti-EE2 specific antibodies and silica nanoparticles (SNs) and then the addition of river water sample, c collect paper microzones to collect with the layer of reduced graphene on electrode d On the edge of reduced graphene, paper microzones were applied, e bound EE2 was dissolved by applying a weak acid solution to the paper, f electrochemical detection by square-wave voltammetry (SWV) A paper-based instrument was created to detect the presence of diclofenac (DCF) in samples of spiked tap water [180]. A circular design was initially wax printed on paper before being heated to 100∘C for one minute of curing. The reference and counter electrodes of the commercial connector were gold-plated pins spanning a piece of black plastic. The wires served as electrodes and a handy connection for the industrial interaction that was attached to the power supply unit. A clip was made by fusing the reference and counter electrodes together. By creating an 8 electrochemical cell framework for multiple observations, the idea’s adaptability was shown. Energy devices Paper is a desirable material for energy storage devices due to its availability, minimal cost, readily disposed of, and environmentally acceptable due to the nonhazardous waste they produce. The most often used paper-based energy components include capacitors, cells, transistors, power stations, detectors, RFID tags, solar panel arrays, digital displays, and medical surveillance systems. Guo et al. [181] proposed a paper-based self-charging power unit that combines a paper-based triboelectric nanogenerator and a supercapacitor, to simultaneously harvest and store energy from body movement. However, these devices need to scale up for the generation of power in large quantities. Below are some of the most recent developments in creating energy devices based on the idea of paper-based microfluidics: Batteries POC devices must meet the ASSURED criteria of the WHO and be self-powered, integrated with power-generating units, and should be used without the use of any additional equipment. Thom et al. [78] demonstrated the first microfluidic device that could produce its own electricity when a sample was added. The device possesses fluidic channels with fluidic batteries built right in. These batteries were fabricated by stacking the various layers of the paper, with the electrodes, electrolyte, and salt bridge loaded into the appropriate paper sheet in a dry state. Lee [79] created paper-based batteries by using copper as the current collector, magnesium foil for the anode, and filter paper coated with copper chloride for the cathode. A maximum voltage and power of 1.56 V and 15.6 mW were delivered by the battery when a sample of urine, salvia, or tap water was added. Paper-based batteries are appropriate for single-use ones since these batteries are activated upon the application of reagent, and the power output of batteries tends to decrease as reagent decays over time. Based on the idea of origami, Liu et al. [182] developed a self-powered ePAD that can detect glucose. The device integrates with a primary battery and can directly activate analyte solutions. A simple origami bacteria battery that can fold and unfold to accommodate various power requirements was proposed [183]. The device is filled with water or wastewater that has a very little amount of bacteria dissolved into it. As the liquid moves through the fluidic channels, it eventually reaches the batteries and produces electricity. Al-air battery is one of the great options among many various metal-air batteries available in the market. Shen et al. [184] integrated the idea of paper-based microfluidics with aluminum-air batteries in 2019 to eliminate the need for costly air electrodes or external pump devices. They sandwiched a piece of graphite foil coated with a catalyst between an anode made of aluminum foil and a cathode made of graphite foil. As shown in Fig. 15, an absorbent pad was also employed with a paper channel to ensure a uniform flow of electrolytes.Fig. 15 Schematic representation of an aluminum foil anode, a catalyst-coated graphite foil cathode, and a thin sheet of fibrous capillary paper are sandwiched in a paper-based Al-air battery Al-air battery on paper microfluidic channel demonstrates much-increased capacity when compared to traditional Al-air battery. A paper-based Al-air battery with a maximum power density of 21 mW/cm2 was also reported by Wang et al. [185]. One flexible zinc-air battery containing a brand-new hollow channel construction was described by Yang et al [186]. To lower the internal resistance of ZABs, one hollow channel structure was successfully constructed and incorporated. The maximum power density of the hollow channel-based ZAB was 138 mW/cm2, 283% greater than that of traditional P-ZABs. When the device was bent from 0∘ to 180∘, it was capable of controlling a calculator. Wang et al. [80] created a 5-cell battery with an efficiency of up to 97% after discovering that Al corrosion could be stopped in an alkaline environment using paper-based delivery. This battery pack was successfully scaled up and used to illustrate how to charge portable electronics. Fuel cells It is a device that generates electricity through a chemical process. In contrast to batteries, cells do not deplete or require a recharge. The identification and application of sustainable and environmentally friendly energy supplies are required due to the rapid increase in energy consumption. Applications for wind energy, photovoltaics, and other renewable energy sources are constrained by their low efficiency. As a more efficient means of converting a fuel’s chemical energy into electric power, fuel cells have emerged as a superior alternative for generating energy. These microfluidic fuel cells include chemical sensors in addition to being employed with communication and transportation systems. Zebda et al. [187] proposed an enzyme-based micro fuel cell in which electrodes were positioned along the catholyte and anolyte streams of the fuel and oxidant streams in the Y-direction. While glucose oxidase worked at the anode to oxidize glucose, laccase worked at the cathode to reduce O2. Noh and Shim [188] reported another enzymatic fuel cell by immobilizing enzyme (glucose oxidases) molecules to the electrode surface in order to further lower the cost and extend the life of the fuel cell up to 16 days. The power density and open circuit voltage produced by the conversion of glucose into gluconic acid and hydrogen peroxide are 0.78 mW cm2 and 0.48 V, respectively. Using graphite electrodes attached to conductive wires through silver adhesive paste on a Y-shaped filter paper strip, Arun et al. [189] created a capillarity-mediated fuel cell. Inlet channels were soaked in a solution of sulfuric acid (oxidant) and formic acid (fuel). Formic acid produced 32 mW cm2 of electricity for more than 15 h by utilizing 1 mL of fuel. On the anode, formic acid broke down into CO2 and electrons, which were then transmitted to the cathode by the external circuit. Based on the idea of reversed electrodialysis, Chang et al. created a multi-layered paper device for energy harvesting. This approach uses asymmetric ion transport through ion-selective membranes to extract energy from two solutions with varying salt contents. A voltage differential across the membrane is caused by the concentration difference, which generates electricity. Wax was used to define the flow, and the paper was coated with Ag/AgCl ink to create the electrodes. When a potassium chloride concentration gradient (0.1 mM/100 mM) was applied across the membrane of the device, which uses an ion-selective membrane placed between two layers of wax-printed paper, the device produced a power density of 275 nW cm2. In order to control the capillary flow on paper, Wang et al. [137] proposed coupling the microfluidic channel outputs with a photothermal module for water evaporation. As a proof of concept, prototype paper-based microfluidic fuel cells coupled to a photothermal module are created. Their peak power density can rise when exposed to simulated sunlight. The recent research opens a new avenue for controlling the functionality of PAD, a problem that has long existed in this field. It not only provides a realistic way to improve the efficiency of solar-powered paper-based microfluidic fuel cells. Food quality One of the essentials of life is food, and the nutritional content of the food is quite important for ensuring a healthy lifestyle. As a result, access to high-quality, safe foods is a must for human existence. Both physical and mental health can be maintained with food. Food safety has become one of the most critical challenges in the world due to the introduction of numerous chemical dangers to improve the flavor or aesthetic look of food, satisfy high market demand, and reduce costs. The issue of poor food quality is more serious in developing nations, especially in rural regions. Therefore, diagnosis technology must be affordable, portable, and small. The amounts of nitrite, a preservative used to give the meat a fresh appearance and extend shelf life were determined [190]. A wax stamping technique was used to create a paper-based microplate. The Griess reagents, which generate a pink color when reacting with nitrite ions in food, were then put in each microzone as colorimetric markers. The amount of nitrite present in the meat directly correlated with the intensity of the resulting pink color. By analyzing the coffee-ring effect of the produced colors on the well plates, Trofimchuk et al. [191] improved the limit of detection for a similar device. As low as 1.1 mg/kg was determined to be the detection limit of this test for nitrite in pork, demonstrating the potential uses of regularly checking the nitrite level in meat samples. For the colorimetric detection of amylose content in rice, Hu et al. [192] created PADs. Their suggested technique of detection was based on the interaction between amylose and iodine, which might result in an amylose-iodine complex with an obvious blue color. They demonstrated that this method may be used to evaluate rice products with an accuracy of 6.3% and amylose levels ranging from 1.5 to 26.4%. Nogueira et al. [193] used a redox titration technique to colorimetrically identify the alcohol concentration of whiskey samples on PADs. In this reaction, the amount of oxalic acid consumed during the back-titration was used to indirectly quantify the amount of ethanol in whiskey while taking the stoichiometric ratio into account. They have demonstrated that their suggested detection approach, which has a detection limit of 2.1% at the point of need, is affordable and only needs a tiny amount of reagent to precisely assess the concentration of ethanol in an alcoholic beverage. For the simultaneous spot test analysis of boric acid, maltodextrin, and hydrogen peroxide, Patari, and Mahapatra [194] designed a paper test card. Using a laser printer to print toner ink, hydrophobic channels with a 14 mm diameter were created on Whatman Grade 4 filter sheets. A camera was used to take pictures of the reaction zone to assess the color variation of the area. The reaction zone will turn orange, bluish chocolate, and brown depending on the presence of boric acid, maltodextrin, and H2O2. A μPAD the concurrent calorimetric measurement of urea, H2O2, and pH was published by Guinati et al. [195]. To ensure that the paper was completely cut without any surface damage, the EVA-coated polyester Gazela laminator model was used to laminate the paper at 140∘C. Then a layout of the ‘PAD’ was created to be cut out using a craft cutter printer, which can produce gadgets quickly, cheaply, and with a minimum amount of technical equipment. The software version was used to analyze the digital photographs after they had all been digitized at a resolution of 600 dpi. Despite the numerous benefits provided by paper-based devices, there is still much room for technology development. Colorimetric detection methods are commonly used in PADs, which makes getting quantitative results difficult. Furthermore, when it comes to PAD-based energy generation, the technology is semi-ready and needs to be scaled up. List of PADs successfully demonstrated for diverse applications The devices are small, light, portable, and cost little to manufacture, use, and dispose of. Low reagent and analyte consumption is a unique benefit of microfluidics. A wide range of practical applications has been found for them in a variety of research fields: chemistry, biochemistry, genomics, forensics, toxicology, immunology, environmental studies, and biomedicine. Microfluidics have been used successfully in the past in the clinical analysis of blood, the detection and identification of infections, proteins, and environmental toxins, genetic research, and in the pharmaceutical sector. The analytical and diagnostic capabilities of these simple devices may revolutionize medicine and pharmaceuticals. Therefore, providing a list of PADs (specifically for clinical and home applications) which has been successfully demonstrated at least at the laboratory level.Table 2 List of ‘μPADs’ Field-up application Short description Medical diagnosis Antibody screening tool that shows whether a patient has a contagious disease infection and an immune reaction to it [196] Medical diagnosis Devices used to identify uropathogenic E. coli rely on the ability to detect nitrite, which is produced when E. coli reduces nitrate. [197] Food quality control Pesticide detection sensor made of paper for crop samples [198] Food quality control 3D PAD for identifying the milk allergen casein [199] Food quality control Colorimetric PAD to detect Salmonella [200] Medical diagnosis A pop-up, DNA-based, label-free ePAD for HBV (a biomarker of liver disorders) detection [201] Medical diagnosis A vertical flow-based paper sandwich-type immunosensor for sensing of influenza H1N1 viruses [202] Food quality control Instrument to measure aluminium in water without pre-treatment or pre-concentration of the sample [203] Medical diagnosis PAD for detection of malaria [204] Medical diagnosis Device for medical diagnosis and sweat analysis that simultaneously measures glucose, lactate, pH, chloride, and volume [205] Medical diagnosis Platform for electrochemical immunosensing for pmol/L Ebola virus detection [206] Medical diagnosis Human chorionic gonadotropin (a pregnancy indicator) detection via a PAD [207] Medical diagnosis PAD to immobilize different antibodies or anti-immunoglobulin E onto screen-printed carbon electrodes [208] Medical diagnosis PAD for COVID-19 diagnosis [209–211] Medical diagnosis Biosensor for POC sensing of dengue virus [212] Food quality control PAD to track total ammonia in fish pond water [213] Medical Diagnosis Electrochemical and self-powered paper-based device for glucose sensing [214, 215] Medical diagnosis PAD for eliminating the necessity for a micropipette in quantitative analysis [216] Medical diagnosis PAD to extract blood plasma from a whole blood sample [138] Medical diagnosis A disposable ePAD for quantification of albumin in a urine sample [217] Food quality control 3D PAD to simultaneously detect multiple chemical adulterants in milk [195, 218] Medical diagnosis An intelligent paper-based UV monitor that can detect the solar UV intensity in real time for human health and safety [219] Food quality control For estimation of the peroxide value in vegetable oils using colorimetric PAD [220] Medical diagnosis Using exhaled air, an ePAD wearable sensor can detect hydrogen peroxide in real time [221] Food quality control Escherichia coli and Staphylococcus aureus, the two main pathogenic bacteria that cause milk poisoning, can be found using a colorimetric PAD [222] Medical diagnosis PAD for blood typing. [129, 147, 185] Medical diagnosis Detection of 17-E2, which is crucial for female menstrual and estrous cycles [155] Medical diagnosis Peptide-based Alzheimer’s diagnostic device [161] Energy generation A power unit that incorporates a paper-based supercapacitor and a triboelectric nanogenerator (TENG) to concurrently harvest and store energy from the movement [181] Food quality control Device to detect the presence of diclofenac (DCF) in samples of spiked tap water [179] Energy generation Paper-based batteries with maximum voltage and power of 1.56 V and 15.6 mW [78] Food quality control Device to detect the amount of nitrite, a preservative used in meat [190, 191] Food quality control Device based on redox titration technique to calorimetrically identify the alcohol concentration of whiskey samples [193] Limitations The outstanding qualities of paper-based microfluidic devices made them suitable for an endless number of applications. However, due to the characteristics of paper, fabrication processes, analytes chosen, and sensing techniques used in the devices, μPADs do have some limitations. In addition, major drawbacks of paper-based devices include sample retention in fluidic channels and significant sample evaporation during operation, both of which reduce device efficiency. The amount of sample needed increases because only about half of the entire introduced sample volume reaches the detecting zone. The effectiveness of some pattering techniques is greatly influenced by the environment in which the device will be used, and the effectiveness of some hydrophobic chemicals is insufficient to create robust hydrophobic barriers that can tolerate samples with different properties. When a liquid with low surface tension comes into contact with wax channels, the liquid starts to penetrate even in hydrophobic parts, whereas the hydrophobic channels or AKD only function properly for particular liquids with surface tension higher than a critical value. This phenomenon occurs as wax creates hydrophobicity by obstructing the pores of paper and lowering the surface energy of paper to effectively direct liquids. Without highly skilled and experienced people, comparison-based detection methods cannot produce accurate results. Various detection techniques are unable to pick up contamination in samples with low contamination levels. These are the present drawbacks of paper-based microfluidic technology that must be overcome. Conclusion Paper is meeting the optimum foundation material requirement for bringing this technology from the lab to the market due to the development of new fabrication protocols for PADs. Litmus paper is among the first papers to be used in chemical analysis. Despite being widely used, litmus paper was a revolutionary invention at the time because it made possible accurate pH measurements. Analytical devices began to be developed slowly with one of the most notable developments being the LFA, which was first industrialized as an over-the-counter pregnancy test in 1975 [223]. In 2007, Whitesides’ group published a paper that ignited the field [1]. The paper-based devices meet WHO specifications for diagnostic devices used in developing countries. According to WHO, the device should be ASSURED, that is, affordable, sensitive, specific, user-friendly, rapid and robust, equipment-free, and deliverable. Paper enables fluid flow without pumps, purication, electrode stabilization, and other applications. Paper devices can be equipment-free if consider integrated devices or colorimetric detection, with the exception of capillary forces that render external pumping obsolete. The devices are portable because the paper is thin, and it is also widely available worldwide. Consider that fully integrated, reusable, sensing platforms will soon be available as paper-based electronics advance. This review discusses the fabrication methods and detection modes in detail. We also discussed recent advances in μPAD for POC diagnostics, food quality control, power generation, and environmental control with theoretical analysis of fluid flow in paper. With minor changes to the device design and fabrication methods, PADs can be effectively implemented for the analysis of basic and extensive systems. There are several issues that remain despite advancements in paper-based microfluidic technology. Fabrication of μPADs requires the printing of hydrophilic paper by using methods like photolithography, screen printing, etc to control the flow of liquid in the appropriate manner. Although these patterning methods can efficiently define the flow in a porous substrate, various other fabrication techniques are also required for the successful mass production of these devices. Therefore, large-scale printing methods should be investigated to fabricate μPADs with multilayer complex structures that can be made at low cost, high resolution, and with easy process steps. It will be difficult to achieve the big goals discussed above. The field must continue to develop in the future, focusing on both basic and applied research areas while also considering the elements needed for industrialization. Materials science has a chance to contribute more to fundamental research by improving techniques for controlling the reactivity of devices using materials building and surface alteration. Although several papers manufactured from different natural or synthetic fibres have been created, PADs are still widely applied in biosensor applications. Fiber-based materials have mechanical stability, a hydrophobic interface, porosity, and the capacity to change the texture through interaction with biorecognition molecules. Some examples of these materials include Teflon, glass fibres, graphene and graphene oxide, polypropylene, poly(lactic acid), and carbon nanotubes. The ongoing exploration of hybrid devices that combine various materials and flow patterns and a detailed understanding of circulation in these systems will enable the creation of new systems from first principles instead of using a considerably slower empirical approach. It is critical from a translational perspective to keep broadening the PAD usage field with an emphasis on applications where PADs actually bring value that is unique from other technologies. By approaching it from this angle, you’ll be able to enter the marketplace more quickly and potentially effect real change. ==== Refs References 1. Martinez AW Phillips ST Butte MJ Whitesides GM Patterned paper as a platform for inexpensive, low-volume, portable bioassays Angew. Chem. 2007 119 8 1340 1342 10.1002/ange.200603817 2. A.W. Martinez, S.T. Phillips, G.M. Whitesides, E. Carrilho, Diagnostics for the developing world: microfluidic paper-based analytical devices (2010) 3. Tay A Pavesi A Yazdi SR Lim CT Warkiani ME Advances in microfluidics in combating infectious diseases Biotechnol. Adv. 2016 34 4 404 421 10.1016/j.biotechadv.2016.02.002 26854743 4. D. Mark, S. Haeberle, G. Roth, F.v. Stetten, R. Zengerle, Microfluidic lab-on-a-chip platforms: requirements, characteristics and applications. Microfluid. Based Microsyst. pp. 305–376 (2010) 5. B. Bhushan, in Springer handbook of nanotechnology (Springer, 2017), pp. 1–19 6. D. Lin, B. Li, J. Qi, X. Ji, S. Yang, W. Wang, L. Chen, Low cost fabrication of microfluidic paper-based analytical devices with water-based polyurethane acrylate and their application for bacterial detection. Sens. Actuators B: Chem. 303, 127,213 (2020) 7. Martinez AW Phillips ST Whitesides GM Three-dimensional microfluidic devices fabricated in layered paper and tape Proc. Natl. Acad. Sci. 2008 105 50 19606 19611 10.1073/pnas.0810903105 19064929 8. Martinez AW Phillips ST Wiley BJ Gupta M Whitesides GM Flash: a rapid method for prototyping paper-based microfluidic devices Lab Chip 2008 8 12 2146 2150 10.1039/b811135a 19023478 9. Carrilho E Phillips ST Vella SJ Martinez AW Whitesides GM Paper microzone plates Anal. Chem. 2009 81 15 5990 5998 10.1021/ac900847g 19572563 10. Lu Y Shi W Jiang L Qin J Lin B Rapid prototyping of paper-based microfluidics with wax for low-cost, portable bioassay Electrophoresis 2009 30 9 1497 1500 10.1002/elps.200800563 19340829 11. He Y Wu Y Fu JZ Wu WB Fabrication of paper-based microfluidic analysis devices: A review RSC Adv. 2015 5 95 78109 78127 10.1039/C5RA09188H 12. Yang Y Noviana E Nguyen MP Geiss BJ Dandy DS Henry CS based microfluidic devices: emerging themes and applications Anal. Chem. 2017 89 1 71 91 10.1021/acs.analchem.6b04581 27936612 13. Songjaroen T Dungchai W Chailapakul O Laiwattanapaisal W Novel, simple and low-cost alternative method for fabrication of paper-based microfluidics by wax dipping Talanta 2011 85 5 2587 2593 10.1016/j.talanta.2011.08.024 21962687 14. Carrilho E Martinez AW Whitesides GM Understanding wax printing: a simple micropatterning process for paper-based microfluidics Anal. Chem. 2009 81 16 7091 7095 10.1021/ac901071p 20337388 15. Mani V Kadimisetty K Malla S Joshi AA Rusling JF based electrochemiluminescent screening for genotoxic activity in the environment Environ. Sci. Technol. 2013 47 4 1937 1944 10.1021/es304426j 23331021 16. Kaewarsa P Laiwattanapaisal W Palasuwan A Palasuwan D A new paper-based analytical device for detection of glucose-6-phosphate dehydrogenase deficiency Talanta 2017 164 534 539 10.1016/j.talanta.2016.12.026 28107969 17. Yamada K Henares TG Suzuki K Citterio D Paper-based inkjet-printed microfluidic analytical devices Angew. Chem. Int. Ed. 2015 54 18 5294 5310 10.1002/anie.201411508 18. Abe K Suzuki K Citterio D Inkjet-printed microfluidic multianalyte chemical sensing paper Anal. Chem. 2008 80 18 6928 6934 10.1021/ac800604v 18698798 19. Bai L Xie Z Wang W Yuan C Zhao Y Mu Z Zhong Q Gu Z Bio-inspired vapor-responsive colloidal photonic crystal patterns by inkjet printing ACS Nano 2014 8 11 11094 11100 10.1021/nn504659p 25300045 20. Maejima K Tomikawa S Suzuki K Citterio D Inkjet printing: an integrated and green chemical approach to microfluidic paper-based analytical devices RSC Adv. 2013 3 24 9258 9263 10.1039/c3ra40828k 21. Maattanen A Ihalainen P Pulkkinen P Wang S Tenhu H Peltonen J Inkjet-printed gold electrodes on paper: characterization and functionalization ACS Appl. Mater. Interfaces. 2012 4 2 955 964 10.1021/am201609w 22233965 22. Mani V Paleja B Larbi K Kumar P Tay JA Siew JY Inci F Wang S Chee C Wang YT Microchip-based ultrafast serodiagnostic assay for tuberculosis Sci. Rep. 2016 6 1 1 11 10.1038/srep35845 28442746 23. Renault C Li X Fosdick SE Crooks RM Hollow-channel paper analytical devices Anal. Chem. 2013 85 16 7976 7979 10.1021/ac401786h 23931456 24. Chitnis G Ding Z Chang CL Savran CA Ziaie B Laser-treated hydrophobic paper: an inexpensive microfluidic platform Lab Chip 2011 11 6 1161 1165 10.1039/c0lc00512f 21264372 25. Das S Bhatia R based microfluidic devices: fabrication, detection, and significant applications in various fields Rev. Anal. Chem. 2022 41 1 112 136 10.1515/revac-2022-0037 26. Bruzewicz DA Reches M Whitesides GM Low-cost printing of poly (dimethylsiloxane) barriers to define microchannels in paper Anal. Chem. 2008 80 9 3387 3392 10.1021/ac702605a 18333627 27. Faustino V Catarino SO Lima R Minas G Biomedical microfluidic devices by using low-cost fabrication techniques: a review J. Biomech. 2016 49 11 2280 2292 10.1016/j.jbiomech.2015.11.031 26671220 28. Amin R Ghaderinezhad F Bridge C Temirel M Jones S Toloueinia P Tasoglu S Pushing the limits of spatial assay resolution for paper-based microfluidics using low-cost and high-throughput pen plotter approach Micromachines 2020 11 6 611 10.3390/mi11060611 32599882 29. Olkkonen J Lehtinen K Erho T Flexographically printed fluidic structures in paper Anal. Chem. 2010 82 24 10246 10250 10.1021/ac1027066 21090744 30. P. de Tarso Garcia, T.M.G. Cardoso, C.D. Garcia, E. Carrilho, W.K.T. Coltro, A handheld stamping process to fabricate microfluidic paper-based analytical devices with chemically modified surface for clinical assays. Rsc Adv. 4(71), 37,637–37,644 (2014) 31. Akyazi T Saez J Elizalde J Benito-Lopez F Fluidic flow delay by ionogel passive pumps in microfluidic paper-based analytical devices Sens. Actuators, B Chem. 2016 233 402 408 10.1016/j.snb.2016.04.116 32. Curto VF Lopez-Ruiz N Capitan-Vallvey LF Palma AJ Benito-Lopez F Diamond D Fast prototyping of paper-based microfluidic devices by contact stamping using indelible ink RSC Adv. 2013 3 41 18811 18816 10.1039/c3ra43825b 33. Sameenoi Y Nongkai PN Nouanthavong S Henry CS Nacapricha D One-step polymer screen-printing for microfluidic paper-based analytical device (μpad) fabrication Analyst 2014 139 24 6580 6588 10.1039/C4AN01624F 25360590 34. Li X Tian J Nguyen T Shen W based microfluidic devices by plasma treatment Anal. Chem. 2008 80 23 9131 9134 10.1021/ac801729t 19551982 35. Chunfang Y Siyang Y Yan J Qiaohong H Hengwu C Fabrication of paper-based microfluidic devices by plasma treatment and its application in glucose determination Acta Chim. Sinica 2014 72 10 1099 1104 10.6023/A14060496 36. Jiang Y Hao Z He Q Chen H A simple method for fabrication of microfluidic paper-based analytical devices and on-device fluid control with a portable corona generator RSC Adv. 2016 6 4 2888 2894 10.1039/C5RA23470K 37. Kao PK Hsu CC One-step rapid fabrication of paper-based microfluidic devices using fluorocarbon plasma polymerization Microfluid. Nanofluid. 2014 16 5 811 818 10.1007/s10404-014-1347-5 38. Kwong P Gupta M Vapor phase deposition of functional polymers onto paper-based microfluidic devices for advanced unit operations Anal. Chem. 2012 84 22 10129 10135 10.1021/ac302861v 23113699 39. Demirel G Babur E Vapor-phase deposition of polymers as a simple and versatile technique to generate paper-based microfluidic platforms for bioassay applications Analyst 2014 139 10 2326 2331 10.1039/C4AN00022F 24699534 40. Chen B Kwong P Gupta M Patterned fluoropolymer barriers for containment of organic solvents within paper-based microfluidic devices ACS applied materials & interfaces 2013 5 23 12701 12707 10.1021/am404049x 24283374 41. Jiang Y Study on fabrication of microfluidic paper-based analytical devices and manipulation of microfluidic flow in paper-based channels using a hand-held corona treater 2014 HangZhou, China ZheJiang University 42. Martinez AW Phillips ST Nie Z Cheng CM Carrilho E Wiley BJ Whitesides GM Programmable diagnostic devices made from paper and tape Lab Chip 2010 10 19 2499 2504 10.1039/c0lc00021c 20672179 43. Kauffman P Fu E Lutz B Yager P Visualization and measurement of flow in two-dimensional paper networks Lab Chip 2010 10 19 2614 2617 10.1039/c004766j 20676410 44. Fu E Lutz B Kauffman P Yager P Controlled reagent transport in disposable 2d paper networks Lab Chip 2010 10 7 918 920 10.1039/b919614e 20300678 45. Tian J Kannangara D Li X Shen W Capillary driven low-cost v-groove microfluidic device with high sample transport efficiency Lab Chip 2010 10 17 2258 2264 10.1039/c003728a 20589291 46. Toley BJ McKenzie B Liang T Buser JR Yager P Fu E Tunable-delay shunts for paper microfluidic devices Anal. Chem. 2013 85 23 11545 11552 10.1021/ac4030939 24245747 47. Houghtaling J Liang T Thiessen G Fu E Dissolvable bridges for manipulating fluid volumes in paper networks Anal. Chem. 2013 85 23 11201 11204 10.1021/ac4022677 24228812 48. Jahanshahi-Anbuhi S Henry A Leung V Sicard C Pennings K Pelton R Brennan JD Filipe CD based microfluidics with an erodible polymeric bridge giving controlled release and timed flow shutoff Lab Chip 2014 14 1 229 236 10.1039/C3LC50762A 24195917 49. Fu E Ramsey SA Kauffman P Lutz B Yager P Transport in two-dimensional paper networks Microfluid. Nanofluid. 2011 10 1 29 35 10.1007/s10404-010-0643-y 22140373 50. Lutz BR Trinh P Ball C Fu E Yager P Two-dimensional paper networks: programmable fluidic disconnects for multi-step processes in shaped paper Lab Chip 2011 11 24 4274 4278 10.1039/c1lc20758j 22037591 51. Apilux A Ukita Y Chikae M Chailapakul O Takamura Y Development of automated paper-based devices for sequential multistep sandwich enzyme-linked immunosorbent assays using inkjet printing Lab Chip 2013 13 1 126 135 10.1039/C2LC40690J 23165591 52. Li X Zwanenburg P Liu X Magnetic timing valves for fluid control in paper-based microfluidics Lab Chip 2013 13 13 2609 2614 10.1039/c3lc00006k 23584207 53. Fridley GE Le H Yager P Highly sensitive immunoassay based on controlled rehydration of patterned reagents in a 2-dimensional paper network Anal. Chem. 2014 86 13 6447 6453 10.1021/ac500872j 24882058 54. Anderson CE Huynh T Gasperino DJ Alonzo LF Cantera JL Harston SP Hsieh HV Marzan R McGuire SK Williford JR Automated liquid handling robot for rapid lateral flow assay development Anal. Bioanal. Chem. 2022 414 8 2607 2618 10.1007/s00216-022-03897-9 35091761 55. Glavan AC Martinez RV Maxwell EJ Subramaniam AB Nunes RM Soh S Whitesides GM Rapid fabrication of pressure-driven open-channel microfluidic devices in omniphobic rf paper Lab Chip 2013 13 15 2922 2930 10.1039/c3lc50371b 23719764 56. Liu W Cassano CL Xu X Fan ZH Laminated paper-based analytical devices (lpad) with origami-enabled chemiluminescence immunoassay for cotinine detection in mouse serum Anal. Chem. 2013 85 21 10270 10276 10.1021/ac402055n 24117197 57. E.I. Newsham, E.A. Phillips, H. Ma, M.M. Chang, S.T. Wereley, J.C. Linnes, Characterization of wax valving and μpiv analysis of microscale flow in paper-fluidic devices for improved modeling and design. Lab on a Chip (2022) 58. Q. Li, Y. Xu, J. Qi, X. Zheng, S. Liu, D. Lin, L. Zhang, P. Liu, B. Li, L. Chen, A self-powered rotating paper-based analytical device for sensing of thrombin. Sensors and Actuators B: Chemical 351, 130,917 (2022) 59. Dungchai W Chailapakul O Henry CS Electrochemical detection for paper-based microfluidics Anal. Chem. 2009 81 14 5821 5826 10.1021/ac9007573 19485415 60. Apilux A Dungchai W Siangproh W Praphairaksit N Henry CS Chailapakul O Lab-on-paper with dual electrochemical/colorimetric detection for simultaneous determination of gold and iron Anal. Chem. 2010 82 5 1727 1732 10.1021/ac9022555 20121066 61. Jagadeesan KK Kumar S Sumana G Application of conducting paper for selective detection of troponin Electrochem. Commun. 2012 20 71 74 10.1016/j.elecom.2012.03.041 62. Wu Y Xue P Kang Y Hui KM based microfluidic electrochemical immunodevice integrated with nanobioprobes onto graphene film for ultrasensitive multiplexed detection of cancer biomarkers Anal. Chem. 2013 85 18 8661 8668 10.1021/ac401445a 23937646 63. Sekar NC Shaegh SAM Ng SH Ge L Tan SN A paper-based amperometric glucose biosensor developed with prussian blue-modified screen-printed electrodes Sens. Actuators, B Chem. 2014 204 414 420 10.1016/j.snb.2014.07.103 64. Renault C Anderson MJ Crooks RM Electrochemistry in hollow-channel paper analytical devices J. Am. Chem. Soc. 2014 136 12 4616 4623 10.1021/ja4118544 24635569 65. Dossi N Toniolo R Pizzariello A Carrilho E Piccin E Battiston S Bontempelli G An electrochemical gas sensor based on paper supported room temperature ionic liquids Lab Chip 2012 12 1 153 158 10.1039/C1LC20663J 22076475 66. Cunningham JC Brenes NJ Crooks RM Paper electrochemical device for detection of dna and thrombin by target-induced conformational switching Anal. Chem. 2014 86 12 6166 6170 10.1021/ac501438y 24871788 67. Nie Z Nijhuis CA Gong J Chen X Kumachev A Martinez AW Narovlyansky M Whitesides GM Electrochemical sensing in paper-based microfluidic devices Lab Chip 2010 10 4 477 483 10.1039/B917150A 20126688 68. Santhiago M Wydallis JB Kubota LT Henry CS Construction and electrochemical characterization of microelectrodes for improved sensitivity in paper-based analytical devices Anal. Chem. 2013 85 10 5233 5239 10.1021/ac400728y 23581428 69. Godino N Gorkin R Bourke K Ducree J Fabricating electrodes for amperometric detection in hybrid paper/polymer lab-on-a-chip devices Lab Chip 2012 12 18 3281 3284 10.1039/c2lc40223h 22842728 70. Santhiago M Kubota LT A new approach for paper-based analytical devices with electrochemical detection based on graphite pencil electrodes Sens. Actuators, B Chem. 2013 177 224 230 10.1016/j.snb.2012.11.002 71. Dossi N Toniolo R Impellizzieri F Bontempelli G Doped pencil leads for drawing modified electrodes on paper-based electrochemical devices J. Electroanal. Chem. 2014 722 90 94 10.1016/j.jelechem.2014.03.038 72. Ciniciato GP Lau C Cochrane A Sibbett SS Gonzalez ER Atanassov P Development of paper based electrodes: From air-breathing to paintable enzymatic cathodes Electrochim. Acta 2012 82 208 213 10.1016/j.electacta.2012.06.094 73. Shiroma LY Santhiago M Gobbi AL Kubota LT Separation and electrochemical detection of paracetamol and 4-aminophenol in a paper-based microfluidic device Anal. Chim. Acta 2012 725 44 50 10.1016/j.aca.2012.03.011 22502610 74. Fosdick SE Anderson MJ Renault C DeGregory PR Loussaert JA Crooks RM Wire, mesh, and fiber electrodes for paper-based electroanalytical devices Anal. Chem. 2014 86 7 3659 3666 10.1021/ac5004294 24625315 75. Yang J Nam YG Lee SK Kim CS Koo YM Chang WJ Gunasekaran S fluidic electrochemical biosensing platform with enzyme paper and enzymeless electrodes Sens. Actuators, B Chem. 2014 203 44 53 10.1016/j.snb.2014.06.077 76. Lu J Ge S Ge L Yan M Yu J Electrochemical dna sensor based on three-dimensional folding paper device for specific and sensitive point-of-care testing Electrochim. Acta 2012 80 334 341 10.1016/j.electacta.2012.07.024 77. Ge S Ge L Yan M Song X Yu J Huang J A disposable paper-based electrochemical sensor with an addressable electrode array for cancer screening Chem. Commun. 2012 48 75 9397 9399 10.1039/c2cc34887j 78. Thom NK Yeung K Pillion MB Phillips ST “fluidic batteries” as low-cost sources of power in paper-based microfluidic devices Lab Chip 2012 12 10 1768 1770 10.1039/c2lc40126f 22450846 79. Lee KB Urine-activated paper batteries for biosystems J. Micromech. Microeng. 2005 15 9 S210 10.1088/0960-1317/15/9/S06 80. Y. Wang, W. Pan, H.Y. Kwok, H. Zhang, X. Lu, D.Y. Leung, Liquid-free al-air batteries with paper-based gel electrolyte: a green energy technology for portable electronics. Journal of Power Sources 437, 226,896 (2019) 81. C. Zhao, M.M. Thuo, X. Liu, A microfluidic paper-based electrochemical biosensor array for multiplexed detection of metabolic biomarkers. Science and technology of advanced materials 14(5), 054,402 (2013) 82. Ramfos I Vassiliadis N Blionas S Efstathiou K Fragoso A O’Sullivan CK Birbas A A compact hybrid-multiplexed potentiostat for real-time electrochemical biosensing applications Biosens. Bioelectron. 2013 47 482 489 10.1016/j.bios.2013.03.068 23624017 83. Liu C Gomez FA A microfluidic paper-based device to assess acetylcholinesterase activity Electrophoresis 2017 38 7 1002 1006 10.1002/elps.201600206 28008633 84. Cardoso TM Channon RB Adkins JA Talhavini M Coltro WK Henry CS A paper-based colorimetric spot test for the identification of adulterated whiskeys Chem. Commun. 2017 53 56 7957 7960 10.1039/C7CC02271A 85. Gabriel EFM Garcia PT Lopes FM Coltro WKT Based colorimetric biosensor for tear glucose measurements Micromachines 2017 8 4 104 10.3390/mi8040104 86. Cardoso TM de Souza FR Garcia PT Rabelo D Henry CS Coltro WK Versatile fabrication of paper-based microfluidic devices with high chemical resistance using scholar glue and magnetic masks Anal. Chim. Acta 2017 974 63 68 10.1016/j.aca.2017.03.043 28535882 87. Meelapsom R Jarujamrus P Amatatongchai M Chairam S Kulsing C Shen W Chromatic analysis by monitoring unmodified silver nanoparticles reduction on double layer microfluidic paper-based analytical devices for selective and sensitive determination of mercury (ii) Talanta 2016 155 193 201 10.1016/j.talanta.2016.04.037 27216673 88. Yamada K Suzuki K Citterio D Text-displaying colorimetric paper-based analytical device Acs Sensors 2017 2 8 1247 1254 10.1021/acssensors.7b00464 28809488 89. Mujawar LH Dhavamani J El-Shahawi MS A versatile optical assay plate fabricated from e-waste and its application towards rapid determination of fe 3+ ions in water New J. Chem. 2017 41 18 9731 9740 10.1039/C7NJ01627A 90. Chowdury MA Walji N Mahmud MA MacDonald BD based microfluidic device with a gold nanosensor to detect arsenic contamination of groundwater in bangladesh Micromachines 2017 8 3 71 10.3390/mi8030071 91. Liu CC Wang YN Fu LM Yang DY Rapid integrated microfluidic paper-based system for sulfur dioxide detection Chem. Eng. J. 2017 316 790 796 10.1016/j.cej.2017.02.023 92. Carneiro MC Rodrigues LR Moreira FT Sales MGF Colorimetric paper-based sensors against cancer biomarkers Sensors 2022 22 9 3221 10.3390/s22093221 35590912 93. T. Mahmoudi, A.P. Tazehkand, M. Pourhassan-Moghaddam, M. Alizadeh-Ghodsi, L. Ding, B. Baradaran, S.R. Bazaz, D. Jin, M.E. Warkiani, Pcr-free paper-based nanobiosensing platform for visual detection of telomerase activity via gold enhancement. Microchemical Journal 154, 104,594 (2020) 94. Fu AC Hu Y Zhao ZH Su R Song Y Zhu D Functionalized paper microzone plate for colorimetry and up-conversion fluorescence dual-mode detection of telomerase based on elongation and capturing amplification Sens. Actuators, B Chem. 2018 259 642 649 10.1016/j.snb.2017.12.124 95. W. Fernando, H. Jayarathna, M. Kaumal, Low-cost microfluidic electrochemical paper-based device to detect glucose. Journal of Science of the University of Kelaniya Sri Lanka 15(1) (2022) 96. Fonseca WT Castro KR de Oliveira TR Faria RC Disposable and flexible electrochemical paper-based analytical devices using low-cost conductive ink Electroanalysis 2021 33 6 1520 1527 10.1002/elan.202060564 97. Tomei MR Cinti S Interino N Manovella V Moscone D Arduini F based electroanalytical strip for user-friendly blood glutathione detection Sens. Actuators, B Chem. 2019 294 291 297 10.1016/j.snb.2019.02.082 98. Ruecha N Shin K Chailapakul O Rodthongkum N Label-free paper-based electrochemical impedance immunosensor for human interferon gamma detection Sens. Actuators, B Chem. 2019 279 298 304 10.1016/j.snb.2018.10.024 99. Wang H Zhou C Sun X Jian Y Kong Q Cui K Ge S Yu J Polyhedral-aupd nanoparticles-based dual-mode cytosensor with turn on enable signal for highly sensitive cell evalution on lab-on-paper device Biosens. Bioelectron. 2018 117 651 658 10.1016/j.bios.2018.07.004 30005386 100. Moazeni M Karimzadeh F Kermanpur A Peptide modified paper based impedimetric immunoassay with nanocomposite electrodes as a point-of-care testing of alpha-fetoprotein in human serum Biosens. Bioelectron. 2018 117 748 757 10.1016/j.bios.2018.07.016 30029196 101. J. Qi, B. Li, N. Zhou, X. Wang, D. Deng, L. Luo, L. Chen, The strategy of antibody-free biomarker analysis by in-situ synthesized molecularly imprinted polymers on movable valve paper-based device. Biosensors and Bioelectronics 142, 111,533 (2019) 102. He T Li J Liu L Ge S Yan M Liu H Yu J Origami-based “book” shaped three-dimensional electrochemical paper microdevice for sample-to-answer detection of pathogens RSC Adv. 2020 10 43 25808 25816 10.1039/D0RA03833D 35518615 103. Santhiago M Henry CS Kubota LT Low cost, simple three dimensional electrochemical paper-based analytical device for determination of p-nitrophenol Electrochim. Acta 2014 130 771 777 10.1016/j.electacta.2014.03.109 104. S. Boonkaew, I. Jang, E. Noviana, W. Siangproh, O. Chailapakul, C.S. Henry, Electrochemical paper-based analytical device for multiplexed, point-of-care detection of cardiovascular disease biomarkers. Sensors and Actuators B: Chemical 330, 129,336 (2021) 105. Yakoh A Chaiyo S Siangproh W Chailapakul O 3d capillary-driven paper-based sequential microfluidic device for electrochemical sensing applications ACS sensors 2019 4 5 1211 1221 10.1021/acssensors.8b01574 30969113 106. L. Wang, B. Li, J. Wang, J. Qi, J. Li, J. Ma, L. Chen, A rotary multi-positioned cloth/paper hybrid microfluidic device for simultaneous fluorescence sensing of mercury and lead ions by using ion imprinted technologies. Journal of Hazardous Materials 428, 128,165 (2022) 107. Y. Zhu, X. Tong, Q. Wei, G. Cai, Y. Cao, C. Tong, S. Shi, F. Wang, 3d origami paper-based ratiometric fluorescent microfluidic device for visual point-of-care detection of alkaline phosphatase and butyrylcholinesterase. Biosensors and Bioelectronics 196, 113,691 (2022) 108. Shi L Li L Li X Zhang G Zhang Y Dong C Shuang S Excitation-independent yellow-fluorescent nitrogen-doped carbon nanodots for biological imaging and paper-based sensing Sens. Actuators, B Chem. 2017 251 234 241 10.1016/j.snb.2017.05.065 109. Zong L Xie Y Li Q Li Z A new red fluorescent probe for hg2+ based on naphthalene diimide and its application in living cells, reversibility on strip papers Sens. Actuators, B Chem. 2017 238 735 743 10.1016/j.snb.2016.07.052 110. Liu C Ning D Zhang C Liu Z Zhang R Zhao J Zhao T Liu B Zhang Z Dual-colored carbon dot ratiometric fluorescent test paper based on a specific spectral energy transfer for semiquantitative assay of copper ions ACS Applied Materials & Interfaces 2017 9 22 18897 18903 10.1021/acsami.7b05827 28516780 111. Nuchtavorn N Macka M A novel highly flexible, simple, rapid and low-cost fabrication tool for paper-based microfluidic devices (μpads) using technical drawing pens and in-house formulated aqueous inks Anal. Chim. Acta 2016 919 70 77 10.1016/j.aca.2016.03.018 27086101 112. Yu J Ge L Huang J Wang S Ge S Microfluidic paper-based chemiluminescence biosensor for simultaneous determination of glucose and uric acid Lab Chip 2011 11 7 1286 1291 10.1039/c0lc00524j 21243159 113. Yu J Wang S Ge L Ge S A novel chemiluminescence paper microfluidic biosensor based on enzymatic reaction for uric acid determination Biosens. Bioelectron. 2011 26 7 3284 3289 10.1016/j.bios.2010.12.044 21257303 114. I. Al Yahyai, H.A. Al-Lawati, J. Hassanzadeh, Carbon dots-modified paper-based chemiluminescence device for rapid determination of mercury (ii) in cosmetics. Luminescence (2022) 115. Zangheri M Cevenini L Anfossi L Baggiani C Simoni P Di Nardo F Roda A A simple and compact smartphone accessory for quantitative chemiluminescence-based lateral flow immunoassay for salivary cortisol detection Biosens. Bioelectron. 2015 64 63 68 10.1016/j.bios.2014.08.048 25194797 116. Yetisen AK Akram MS Lowe CR based microfluidic point-of-care diagnostic devices Lab Chip 2013 13 12 2210 2251 10.1039/c3lc50169h 23652632 117. Delaney JL Hogan CF Tian J Shen W Electrogenerated chemiluminescence detection in paper-based microfluidic sensors Anal. Chem. 2011 83 4 1300 1306 10.1021/ac102392t 21247195 118. Wu L Ma C Zheng X Liu H Yu J based electrochemiluminescence origami device for protein detection using assembled cascade dna-carbon dots nanotags based on rolling circle amplification Biosens. Bioelectron. 2015 68 413 420 10.1016/j.bios.2015.01.034 25618373 119. Ge L Yan J Song X Yan M Ge S Yu J Three-dimensional paper-based electrochemiluminescence immunodevice for multiplexed measurement of biomarkers and point-of-care testing Biomaterials 2012 33 4 1024 1031 10.1016/j.biomaterials.2011.10.065 22074665 120. Yan J Ge L Song X Yan M Ge S Yu J Paper-based electrochemiluminescent 3d immunodevice for lab-on-paper, specific, and sensitive point-of-care testing Chemistry-A European Journal 2012 18 16 4938 4945 10.1002/chem.201102855 22392821 121. Cai J Jin T Kou J Zou S Xiao J Meng Q Lucas-washburn equation-based modeling of capillary-driven flow in porous systems Langmuir 2021 37 5 1623 1636 10.1021/acs.langmuir.0c03134 33512167 122. Ponomarenko A Quéré D Clanet C A universal law for capillary rise in corners J. Fluid Mech. 2011 666 146 154 10.1017/S0022112010005276 123. Fries N Dreyer M An analytic solution of capillary rise restrained by gravity J. Colloid Interface Sci. 2008 320 1 259 263 10.1016/j.jcis.2008.01.009 18255086 124. Patari S Mahapatra PS Liquid wicking in a paper strip: An experimental and numerical study ACS Omega 2020 5 36 22931 22939 10.1021/acsomega.0c02407 32954142 125. S. Bhattacharya, S. Kumar, A.K. Agarwal, Paper microfluidics (Springer, 2019) 126. Wang Y Ye D Zhu X Yang Y Qin C Chen R Liao Q Spontaneous imbibition in paper-based microfluidic devices: Experiments and numerical simulations Langmuir 2022 38 8 2677 2685 10.1021/acs.langmuir.1c03403 35168321 127. Masoodi R Tan H Pillai KM Darcy’s law-based numerical simulation for modeling 3d liquid absorption into porous wicks AIChE J. 2011 57 5 1132 1143 10.1002/aic.12343 128. Liu Z Hu J Zhao Y Qu Z Xu F Experimental and numerical studies on liquid wicking into filter papers for paper-based diagnostics Appl. Therm. Eng. 2015 88 280 287 10.1016/j.applthermaleng.2014.09.057 129. T. Ouyang, J. Lu, P. Xu, X. Hu, J. Chen, Mechanism study and evaluation of high efficiency paper-based microfluidic fuel cell coupled with capillary force. Journal of Power Sources 520, 230,807 (2022) 130. S. Modha, Control and modeling of imbibition in paper-based microfluidic devices. Ph.D. thesis, University of California, Riverside (2022) 131. Elizalde E Urteaga R Berli CL Rational design of capillary-driven flows for paper-based microfluidics Lab Chip 2015 15 10 2173 2180 10.1039/C4LC01487A 25813247 132. J. Songok, M. Toivakka, Modelling of capillary-driven flow for closed paper-based microfluidic channels. Journal of Micromechanics and Microengineering 27(6), 065,001 (2017) 133. Rosenfeld T Bercovici M 1000-fold sample focusing on paper-based microfluidic devices Lab Chip 2014 14 23 4465 4474 10.1039/C4LC00734D 25256832 134. Dushin V Smirnov N Nikitin V Skryleva E Weisman YG Multiple capillary-driven imbibition of a porous medium under microgravity conditions: Experimental investigation and mathematical modeling Acta Astronaut. 2022 193 572 578 10.1016/j.actaastro.2021.06.054 135. P.A. More, P.V. Tandel, Study of parametric effect on saturation rate in imbibition phenomenon for various porous materials. Journal of Ocean Engineering and Science (2022) 136. Q. Meng, L. Zhao, P. Li, F. Yang, J. Cai, Experiments and phase-field simulation of counter-current imbibition in porous media with different pore structure. Journal of Hydrology 608, 127,670 (2022) 137. W. Wang, L.L. Shen, H. Yu, W. Xu, J. Wang, C. Yong, G.R. Zhang, D. Mei, Solar-boosted paper-based microfluidic fuel cells for miniaturized power sources. Advanced Materials Technologies p. 2200154 (2022) 138. Songjaroen T Dungchai W Chailapakul O Henry CS Laiwattanapaisal W Blood separation on microfluidic paper-based analytical devices Lab Chip 2012 12 18 3392 3398 10.1039/c2lc21299d 22782449 139. Noiphung J Songjaroen T Dungchai W Henry CS Chailapakul O Laiwattanapaisal W Electrochemical detection of glucose from whole blood using paper-based microfluidic devices Anal. Chim. Acta 2013 788 39 45 10.1016/j.aca.2013.06.021 23845479 140. Yang X Forouzan O Brown TP Shevkoplyas SS Integrated separation of blood plasma from whole blood for microfluidic paper-based analytical devices Lab Chip 2012 12 2 274 280 10.1039/C1LC20803A 22094609 141. Kar S Maiti TK Chakraborty S Capillarity-driven blood plasma separation on paper-based devices Analyst 2015 140 19 6473 6476 10.1039/C5AN00849B 26270006 142. Kim D Kim S Kim S An innovative blood plasma separation method for a paper-based analytical device using chitosan functionalization Analyst 2020 145 16 5491 5499 10.1039/D0AN00500B 32597456 143. Burgos-Flórez F Rodríguez A Cervera E De Ávila M Sanjuán M Villalba PJ Microfluidic paper-based blood plasma separation device as a potential tool for timely detection of protein biomarkers Micromachines 2022 13 5 706 10.3390/mi13050706 35630172 144. G. Daniels, I. Bromilow, Essential guide to blood groups (John Wiley & Sons, 2011) 145. Proverbio D Spada E Baggiani L Perego R Assessment of a gel column technique for feline blood typing Vet. Res. Commun. 2009 33 1 201 203 10.1007/s11259-009-9275-7 19578954 146. Ota M Fukushima H Yonemura I Hasekura H Detection of ab0 blood group-active glycolipids extracted from red cell membrane and heat hematoma using tlc-immunostaining Z. Rechtsmed. 1988 100 2 215 221 3051781 147. Khan MS Thouas G Shen W Whyte G Garnier G Paper diagnostic for instantaneous blood typing Anal. Chem. 2010 82 10 4158 4164 10.1021/ac100341n 20415489 148. Jarujamrus P Tian J Li X Siripinyanond A Shiowatana J Shen W Mechanisms of red blood cells agglutination in antibody-treated paper Analyst 2012 137 9 2205 2210 10.1039/c2an15798e 22433943 149. N. Larpant, W. Niamsi, J. Noiphung, W. Chanakiat, T. Sakuldamrongpanich, V. Kittichai, T. Tongloy, S. Chuwongin, S. Boonsang, W. Laiwattanapaisal, Simultaneous phenotyping of five rh red blood cell antigens on a paper-based analytical device combined with deep learning for rapid and accurate interpretation. Analytica Chimica Acta 1207, 339,807 (2022) 150. Pasinszki T Krebsz M Biosensors for non-invasive detection of celiac disease biomarkers in body fluids Biosensors 2018 8 2 55 10.3390/bios8020055 29914179 151. Kouw PM de Vries PM Donker AJ Non-invasive measurement of body fluid dynamics Int. Yearb. Nephrol. 1992 1993 333 351 152. Olthof C De Vries P Kouw P Oe P Schneider H De Lange J Donker A Non-invasive conductivity method for detection of dynamic body fluid changes: in vitro and in vivo validation Nephrol. Dial. Transplant. 1993 8 1 41 46 10.1093/oxfordjournals.ndt.a092270 8381934 153. S. Dalirirad, A.J. Steckl, Lateral flow assay using aptamer-based sensing for on-site detection of dopamine in urine. Analytical biochemistry 596, 113,637 (2020) 154. Schonhorn JE Fernandes SC Rajaratnam A Deraney RN Rolland JP Mace CR A device architecture for three-dimensional, patterned paper immunoassays Lab Chip 2014 14 24 4653 4658 10.1039/C4LC00876F 25300302 155. Xiao L Zhang Z Wu C Han L Zhang H Molecularly imprinted polymer grafted paper-based method for the detection of 17β-estradiol Food Chem. 2017 221 82 86 10.1016/j.foodchem.2016.10.062 27979279 156. Bauça JM Martínez-Morillo E Diamandis EP Peptidomics of urine and other biofluids for cancer diagnostics Clin. Chem. 2014 60 8 1052 1061 10.1373/clinchem.2013.211714 24212086 157. Beaucamp A Culebras M Collins MN Sustainable mesoporous carbon nanostructures derived from lignin for early detection of glucose Green Chem. 2021 23 15 5696 5705 10.1039/D1GC02062E 158. Hu S Loo JA Wong DT Human body fluid proteome analysis Proteomics 2006 6 23 6326 6353 10.1002/pmic.200600284 17083142 159. Pérez D Orozco J Wearable electrochemical biosensors to measure biomarkers with complex blood-to-sweat partition such as proteins and hormones Microchim. Acta 2022 189 3 1 28 10.1007/s00604-022-05228-2 160. J.M. Bhagu, Probing the in-situ conformation of monoclonal antibodies at hydrophobic interfaces using nmr spectroscopy. Ph.D. thesis, Florida Agricultural and Mechanical University (2021) 161. Veerabhadrappa B Delaby C Hirtz C Vialaret J Alcolea D Lleó A Fortea J Santosh MS Choubey S Lehmann S Detection of amyloid beta peptides in body fluids for the diagnosis of alzheimer’s disease: Where do we stand? Crit. Rev. Clin. Lab. Sci. 2020 57 2 99 113 10.1080/10408363.2019.1678011 31661652 162. Rattanarat P Dungchai W Siangproh W Chailapakul O Henry CS Sodium dodecyl sulfate-modified electrochemical paper-based analytical device for determination of dopamine levels in biological samples Anal. Chim. Acta 2012 744 1 7 10.1016/j.aca.2012.07.003 22935367 163. Shao XY Wang CR Xie CM Wang XG Liang RL Xu WW Rapid and sensitive lateral flow immunoassay method for procalcitonin (pct) based on time-resolved immunochromatography Sensors 2017 17 3 480 10.3390/s17030480 28264502 164. Kasetsirikul S Umer M Soda N Sreejith KR Shiddiky MJ Nguyen NT Detection of the sars-cov-2 humanized antibody with paper-based elisa Analyst 2020 145 23 7680 7686 10.1039/D0AN01609H 32975254 165. T. Yang, Y.C. Wang, C.F. Shen, C.M. Cheng. Point-of-care rna-based diagnostic device for covid-19 (2020) 166. M. Kumar, S. Gulati, A.H. Ansari, R. Phutela, S. Acharya, M. Azhar, J. Murthy, P. Kathpalia, A. Kanakan, R. Maurya, et al., Fncas9-based crispr diagnostic for rapid and accurate detection of major sars-cov-2 variants on a paper strip. Elife 10, e67,130 (2021) 167. F. Gong, H.x. Wei, J. Qi, H. Ma, L. Liu, J. Weng, X. Zheng, Q. Li, D. Zhao, H. Fang, et al., Pulling-force spinning top for serum separation combined with paper-based microfluidic devices in covid-19 elisa diagnosis. ACS sensors 6(7), 2709–2719 (2021) 168. Y. Ming, S. Hao, F. Wang, Y.R. Lewis-Israeli, B.D. Volmert, Z. Xu, A. Goestenkors, A. Aguirre, C. Zhou, Longitudinal morphological and functional characterization of human heart organoids using optical coherence tomography. Biosensors and Bioelectronics 207, 114,136 (2022) 169. D. Liu, C. Ju, C. Han, R. Shi, X. Chen, D. Duan, J. Yan, X. Yan, Nanozyme chemiluminescence paper test for rapid and sensitive detection of sars-cov-2 antigen. Biosensors and Bioelectronics 173, 112,817 (2021) 170. Weaver AA Reiser H Barstis T Benvenuti M Ghosh D Hunckler M Joy B Koenig L Raddell K Lieberman M Paper analytical devices for fast field screening of beta lactam antibiotics and antituberculosis pharmaceuticals Anal. Chem. 2013 85 13 6453 6460 10.1021/ac400989p 23725012 171. Koesdjojo MT Wu Y Boonloed A Dunfield EM Remcho VT Low-cost, high-speed identification of counterfeit antimalarial drugs on paper Talanta 2014 130 122 127 10.1016/j.talanta.2014.05.050 25159388 172. Kaarj K Akarapipad P Yoon JY Simpler, faster, and sensitive zika virus assay using smartphone detection of loop-mediated isothermal amplification on paper microfluidic chips Sci. Rep. 2018 8 1 1 11 10.1038/s41598-018-30797-9 29311619 173. Ye X Xu J Lu L Li X Fang X Kong J Equipment-free nucleic acid extraction and amplification on a simple paper disc for point-of-care diagnosis of rotavirus a Anal. Chim. Acta 2018 1018 78 85 10.1016/j.aca.2018.02.068 29605138 174. Mensah ST Gonzalez Y Calvo-Marzal P Chumbimuni-Torres KY Nanomolar detection limits of cd2+, ag+, and k+ using paper-strip ion-selective electrodes Anal. Chem. 2014 86 15 7269 7273 10.1021/ac501470p 25023061 175. Yu P Heist CA Remcho VT A novel laminated polycaprolactone/paper/silver electrode for lead (ii) detection Anal. Methods 2017 9 11 1702 1706 10.1039/C6AY03414D 176. Wang X Sun J Tong J Guan X Bian C Xia S based sensor chip for heavy metal ion detection by swsv Micromachines 2018 9 4 150 10.3390/mi9040150 30424084 177. Shimizu FM Pasqualeti AM Nicoliche CY Gobbi AL Santhiago M Lima RS Alcohol-triggered capillarity through porous pyrolyzed paper-based electrodes enables ultrasensitive electrochemical detection of phosphate ACS sensors 2021 6 8 3125 3132 10.1021/acssensors.1c01302 34399053 178. Cioffi A Mancini M Gioia V Cinti S Office paper-based electrochemical strips for organophosphorus pesticide monitoring in agricultural soil Environmental Science & Technology 2021 55 13 8859 8865 10.1021/acs.est.1c01931 34165948 179. Scala-Benuzzi ML Raba J Soler-Illia GJ Schneider RJ Messina GA Novel electrochemical paper-based immunocapture assay for the quantitative determination of ethinylestradiol in water samples Anal. Chem. 2018 90 6 4104 4111 10.1021/acs.analchem.8b00028 29473416 180. E. Costa-Rama, H. Nouws, C. Delerue-Matos, M.d.C. Blanco-López, M.T. Fernández-Abedul, Preconcentration and sensitive determination of the anti-inflammatory drug diclofenac on a paper-based electroanalytical platform. Analytica Chimica Acta 1074, 89–97 (2019) 181. Guo H Yeh MH Zi Y Wen Z Chen J Liu G Hu C Wang ZL Ultralight cut-paper-based self-charging power unit for self-powered portable electronic and medical systems ACS Nano 2017 11 5 4475 4482 10.1021/acsnano.7b00866 28401759 182. Y. Liu, K. Cui, Q. Kong, L. Zhang, S. Ge, J. Yu, A self-powered origami paper analytical device with a pop-up structure for dual-mode electrochemical sensing of atp assisted by glucose oxidase-triggered reaction. Biosensors and Bioelectronics 148, 111,839 (2020) 183. Lee H Choi S An origami paper-based bacteria-powered battery Nano Energy 2015 15 549 557 10.1016/j.nanoen.2015.05.019 184. Shen LL Zhang GR Biesalski M Etzold BJ based microfluidic aluminum-air batteries: toward next-generation miniaturized power supply Lab Chip 2019 19 20 3438 3447 10.1039/C9LC00574A 31556903 185. Y. Wang, H.Y. Kwok, W. Pan, H. Zhang, X. Lu, D.Y. Leung, Parametric study and optimization of a low-cost paper-based al-air battery with corrosion inhibition ability. Applied energy 251, 113,342 (2019) 186. Y. Yang, H. Zhang, X. Zhu, D. Ye, R. Chen, Q. Liao, A hollow structure for flow and bendable paper-based zinc-air battery. International Journal of Energy Research (2022) 187. Zebda A Renaud L Cretin M Pichot F Innocent C Ferrigno R Tingry S A microfluidic glucose biofuel cell to generate micropower from enzymes at ambient temperature Electrochem. Commun. 2009 11 3 592 595 10.1016/j.elecom.2008.12.036 188. Noh HB Shim YB Catalytic activity of polymerized self-assembled artificial enzyme nanoparticles: applications to microfluidic channel-glucose biofuel cells and sensors Journal of Materials Chemistry A 2016 4 7 2720 2728 10.1039/C5TA08823B 189. Arun RK Halder S Chanda N Chakraborty S A paper based self-pumping and self-breathing fuel cell using pencil stroked graphite electrodes Lab Chip 2014 14 10 1661 1664 10.1039/C4LC00029C 24671425 190. Cardoso TM Garcia PT Coltro WK Colorimetric determination of nitrite in clinical, food and environmental samples using microfluidic devices stamped in paper platforms Anal. Methods 2015 7 17 7311 7317 10.1039/C5AY00466G 191. E. Trofimchuk, Y. Hu, A. Nilghaz, M.Z. Hua, S. Sun, X. Lu, Development of paper-based microfluidic device for the determination of nitrite in meat. Food chemistry 316, 126,396 (2020) 192. Hu X Lu L Fang C Duan B Zhu Z Determination of apparent amylose content in rice by using paper-based microfluidic chips J. Agric. Food Chem. 2015 63 44 9863 9868 10.1021/acs.jafc.5b04530 26495809 193. Nogueira SA Lemes AD Chagas AC Vieira ML Talhavini M Morais PA Coltro WK Redox titration on foldable paper-based analytical devices for the visual determination of alcohol content in whiskey samples Talanta 2019 194 363 369 10.1016/j.talanta.2018.10.036 30609544 194. S. Patari, P.S. Mahapatra, in 2021 IEEE Sensors (IEEE, 2021), pp. 1–4 195. Guinati BG Sousa LR Oliveira KA Coltro WK Simultaneous analysis of multiple adulterants in milk using microfluidic paper-based analytical devices Anal. Methods 2021 13 44 5383 5390 10.1039/D1AY01339D 34734929 196. Dong M Wu J Ma Z Peretz-Soroka H Zhang M Komenda P Tangri N Liu Y Rigatto C Lin F Rapid and low-cost crp measurement by integrating a paper-based microfluidic immunoassay with smartphone (crp-chip) Sensors 2017 17 4 684 10.3390/s17040684 28346363 197. Bhakta SA Borba R Taba M Jr Garcia CD Carrilho E Determination of nitrite in saliva using microfluidic paper-based analytical devices Anal. Chim. Acta 2014 809 117 122 10.1016/j.aca.2013.11.044 24418141 198. Menger R Bontha M Beveridge J Borch T Henry C Fluorescent dye paper-based method for assessment of pesticide coverage on leaves and trees: a citrus grove case study J. Agric. Food Chem. 2020 68 47 14009 14014 10.1021/acs.jafc.0c01835 33170700 199. Jiang D Ge P Wang L Jiang H Yang M Yuan L Ge Q Fang W Ju X A novel electrochemical mast cell-based paper biosensor for the rapid detection of milk allergen casein Biosens. Bioelectron. 2019 130 299 306 10.1016/j.bios.2019.01.050 30776617 200. Srisa-Art M Boehle KE Geiss BJ Henry CS Highly sensitive detection of salmonella typhimurium using a colorimetric paper-based analytical device coupled with immunomagnetic separation Anal. Chem. 2018 90 1 1035 1043 10.1021/acs.analchem.7b04628 29211962 201. C. Srisomwat, P. Teengam, N. Chuaypen, P. Tangkijvanich, T. Vilaivan, O. Chailapakul, Pop-up paper electrochemical device for label-free hepatitis b virus dna detection. Sensors and Actuators B: Chemical 316, 128,077 (2020) 202. Jilani TN Jamil RT Siddiqui AH H1n1 influenza (swine flu) 2020 Treasure Island (FL) StatPearls 203. Nguyen MP Kelly SP Wydallis JB Henry CS Read-by-eye quantification of aluminum (iii) in distance-based microfluidic paper-based analytical devices Anal. Chim. Acta 2020 1100 156 162 10.1016/j.aca.2019.11.052 31987136 204. Reboud J Xu G Garrett A Adriko M Yang Z Tukahebwa EM Rowell C Cooper JM based microfluidics for dna diagnostics of malaria in low resource underserved rural communities Proc. Natl. Acad. Sci. 2019 116 11 4834 4842 10.1073/pnas.1812296116 30782834 205. S. Ardalan, M. Hosseinifard, M. Vosough, H. Golmohammadi, Towards smart personalized perspiration analysis: An iot-integrated cellulose-based microfluidic wearable patch for smartphone fluorimetric multi-sensing of sweat biomarkers. Biosensors and Bioelectronics 168, 112,450 (2020) 206. Kaushik A Tiwari S Jayant RD Marty A Nair M Towards detection and diagnosis of ebola virus disease at point-of-care Biosens. Bioelectron. 2016 75 254 272 10.1016/j.bios.2015.08.040 26319169 207. Cao L Fang C Zeng R Zhao X Jiang Y Chen Z based microfluidic devices for electrochemical immunofiltration analysis of human chorionic gonadotropin Biosens. Bioelectron. 2017 92 87 94 10.1016/j.bios.2017.02.002 28189070 208. Honikel MM Lin CE Cardinell BA LaBelle JT Penman AD Direct measurement of a biomarker’s native optimal frequency with physical adsorption based immobilization ACS sensors 2018 3 4 823 831 10.1021/acssensors.8b00064 29533605 209. D. Thompson, Y. Lei, Mini review: Recent progress in rt-lamp enabled covid-19 detection. Sensors and Actuators Reports 2(1), 100,017 (2020) 210. J.P. Broughton, X. Deng, G. Yu, C.L. Fasching, J. Singh, J. Streithorst, A. Granados, A. Sotomayor-Gonzalez, K. Zorn, A. Gopez, et al., Rapid detection of 2019 novel coronavirus sars-cov-2 using a crispr-based detectr lateral flow assay. MedRxiv (2020) 211. Q. Hui, Y. Pan, Z. Yang, based devices for rapid diagnostics and testing sewage for early warning of covid-19 outbreak. Case Studies in Chemical and Environmental Engineering 2, 100,064 (2020) 212. R. Suvanasuthi, S. Chimnaronk, C. Promptmas, 3d printed hydrophobic barriers in a paper-based biosensor for point-of-care detection of dengue virus serotypes. Talanta 237, 122,962 (2022) 213. P. Mufidah Sari, A. Daud, H. Sulistyarti, A. Sabarudin, D. Nacapricha, An application study of membraneless-gas separation microfluidic paper-based analytical device for monitoring total ammonia in fish pond water using natural reagent. Analytical Sciences 38(5), 759–767 (2022) 214. Amor-Gutiérrez O Costa-Rama E Fernández-Abedul MT Fully integrated sampler and dilutor in an electrochemical paper-based device for glucose sensing Microchim. Acta 2021 188 9 1 8 10.1007/s00604-021-04946-3 215. A. Pal, H.E. Cuellar, R. Kuang, H.F. Caurin, D. Goswami, R.V. Martinez, Self-powered, paper-based electrochemical devices for sensitive point-of-care testing. Advanced materials technologies 2(10), 1700,130 (2017) 216. Komatsu T Gabatino RR Hofileña H Maeki M Ishida A Tani H Tokeshi M Using a paper-based analytical device designed for remote learning environments to achieve simple quantitative colorimetry without micropipettes J. Chem. Educ. 2021 98 9 3050 3054 10.1021/acs.jchemed.1c00100 217. P. Yomthiangthae, O. Chailapakul, W. Siangproh, Rapid urinary albumin detection using a simple redox cycling process coupled with a paper-based device. Journal of Electroanalytical Chemistry 911, 116,230 (2022) 218. Patari S Datta P Mahapatra PS 3d paper-based milk adulteration detection device Sci. Rep. 2022 12 1 1 14 10.1038/s41598-022-17851-3 34992227 219. Zhao J Zhang Y Liu F Yan M Wang X Wang W Sunlight-responsive titania-hydrated tungsten oxide heteronanoparticles/paper-based color-switching film for solar ultraviolet radiation monitors ACS Applied Nano Materials 2022 5 3 4009 4017 10.1021/acsanm.2c00003 220. E. Ghohestani, J. Tashkhourian, B. Hemmateenejad, Colorimetric determination of peroxide value in vegetable oils using a paper based analytical device. Food Chemistry p. 134345 (2022) 221. Maier D Laubender E Basavanna A Schumann S Guder F Urban GA Dincer C Toward continuous monitoring of breath biochemistry: a paper-based wearable sensor for real-time hydrogen peroxide measurement in simulated breath ACS sensors 2019 4 11 2945 2951 10.1021/acssensors.9b01403 31610653 222. M. Asif, F.R. Awan, Q.M. Khan, B. Ngamsom, N. Pamme, based analytical devices for colorimetric detection of s. aureus and e. coli and their antibiotic resistant strains in milk. Analyst 145(22), 7320–7329 (2020) 223. B. O’Farrell, in Lateral flow immunoassay (Springer, 2009), pp. 1–33
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==== Front Blood Blood Blood 0006-4971 1528-0020 by The American Society of Hematology S0006-4971(22)08350-1 10.1182/blood.2022015917 Regular Article The Histone Methyltransferase MLL1/KMT2A in Monocytes Drives Coronavirus-Associated Coagulopathy and Inflammation Sharma Sriganesh B. 1 Melvin William J. 1 Audu Christopher O. 12 Bame Monica 3 Rhoads Nicole 4 Wu Weisheng 5 Kanthi Yogendra 6 Knight Jason S. 7 Adili Reheman 4 Holinstat Michael 24 Wakefield Thomas W. 12 Henke Peter K. 12 Moore Bethany B. 3 Gallagher Katherine A. 123 Obi Andrea T. 12∗ 1 Department of General Surgery, University of Michigan, Ann Arbor, Michigan 2 Section of Vascular Surgery, Department of Surgery, Ann Arbor, Michigan 3 Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan 4 Department of Pharmacology, University of Michigan, Ann Arbor, Michigan 5 Bioinformatics core, Biomedical research core facilities, University of Michigan, Ann Arbor, Michigan 6 Laboratory of Vascular Thrombosis & Inflammation, National Heart, Lung, and Blood Institute, Bethesda, Maryland 7 Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan ∗ Corresponding author: Dr. Andrea T. Obi, MD 11 12 2022 11 12 2022 14 2 2022 15 11 2022 15 11 2022 © 2022 by The American Society of Hematology. 2022 The American Society of Hematology Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Coronavirus-associated coagulopathy (CAC) is a morbid and lethal sequela of SARS-CoV-2 infection. CAC results from a perturbed balance between coagulation and fibrinolysis and occurs in conjunction with exaggerated activation of monocytes/macrophages (MO/Mφs) and the mechanisms that collectively govern this phenotype seen in CAC remain unclear. In this study, using experimental models that employ the murine betacoronavirus MHVA59, a well-established model of SARS-CoV-2 infection, we identify that the histone methyltransferase Mixed Lineage Leukemia 1 (MLL1/KMT2A) is an important regulator of MO/Mφ expression of procoagulant and profibrinolytic factors such as tissue factor (F3; TF), urokinase (PLAU), and urokinase receptor (PLAUR) (herein “coagulopathy-related factors”) in non-infected and infected cells. We show that MLL1 concurrently promotes the expression of the proinflammatory cytokines while suppressing the expression of interferon α (IFNα), a well-known inducer of TF and PLAUR. Using in vitro models, we identify MLL1-dependent NFκB/RelA-mediated transcription of these coagulation-related factors and identify a context dependent MLL1-independent role for RelA in the expression of these factors in vivo. As functional correlates for these findings, we demonstrate that the inflammatory, procoagulant and profibrinolytic phenotypes seen in vivo after coronavirus infection were MLL1-dependent despite blunted Ifna induction in MO/Mφs. Finally, in an analysis of SARS-CoV-2 positive human samples, we identify differential upregulation of MLL1 and coagulopathy-related factor expression and activity in CD14+ MO/Mφs relative to non-infected and healthy controls. We also observed elevated plasma urokinase and TF activity in COVID-positive samples. Collectively, these findings highlight an important role for MO/Mφ MLL1 in promoting coronavirus-associated coagulopathy and inflammation. ==== Body pmc ==== Refs Supplementary Material Supplemental Methods, Tables and Figures
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Blood. 2022 Dec 11; doi: 10.1182/blood.2022015917
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==== Front Matter Matter Matter 2590-2393 2590-2385 Elsevier Inc. S2590-2385(22)00658-0 10.1016/j.matt.2022.11.027 Article Supramolecular filaments for concurrent ACE2 docking and enzymatic activity silencing enable coronavirus capture and infection prevention Anderson Caleb F. 12 Wang Qiong 3 Stern David 12 Leonard Elissa K. 4 Sun Boran 12 Fergie Kyle J. 12 Choi Chang-yong 3 Spangler Jamie B. 1457 Villano Jason 8 Pekosz Andrew 78 Brayton Cory F. 8 Jia Hongpeng 3∗ Cui Honggang 12569∗∗ 1 Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA 2 Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD 21218, USA 3 Division of Pediatric Surgery, Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA 4 Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA 5 Department of Oncology and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA 6 Center for Nanomedicine, The Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA 7 Department of Molecular Microbiology and Immunology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA 8 Molecular and Comparative Pathobiology, The Johns Hopkins School of Medicine, Baltimore, MD 21205, USA ∗ Corresponding author ∗∗ Corresponding author 9 Lead contact 12 12 2022 12 12 2022 10 8 2022 11 10 2022 16 11 2022 © 2022 Elsevier Inc. 2022 Elsevier Inc. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Coronaviruses have historically precipitated global pandemics of severe acute respiratory syndrome (SARS) into devastating public health crises. Despite the virus’s rapid rate of mutation, all SARS coronavirus 2 (SARS-CoV-2) variants are known to gain entry into host cells primarily through complexation with angiotensin-converting enzyme 2 (ACE2). Although ACE2 has potential as a druggable decoy to block viral entry, its clinical use is complicated by its essential biological role as a carboxypeptidase and hindered by its structural and chemical instability. Here we designed supramolecular filaments, called fACE2, that can silence ACE2’s enzymatic activity and immobilize ACE2 to their surface through enzyme-substrate complexation. This docking strategy enables ACE2 to be effectively delivered in inhalable aerosols and improves its structural stability and functional preservation. fACE2 exhibits enhanced and prolonged inhibition of viral entry compared with ACE2 alone while mitigating lung injury in vivo. Graphical abstract Progress and potential The structural and functional instability of therapeutic proteins represents a big challenge for their effective delivery and eventual use in the clinic. This work evidences enhanced deposition and retention of therapeutic proteins in the lungs through their complexation with high-affinity supramolecular filaments. Our results suggest that supramolecular filaments not only allow facile incorporation of peptide-based substrates on their surfaces for binding and delivering therapeutic proteins through enzyme-substrate interactions but also provide a means of preserving the proteins’ structure and function as the filament and cargo endure harsh interfacial forces during aerosol formation. This eventually led to prolonged inhibition of coronavirus infection in vitro and in vivo. The materials showcased here possess high translational potential to curb coronavirus infections and establish a new platform for inhalable delivery of protein therapeutic agents for other human diseases. Peptide-based supramolecular filaments were designed to specifically bind and immobilize decoy ACE2 on their surface through enzyme-substrate interactions, which facilitated delivery of the protein in respirable aerosols. This docking strategy afforded structural and functional preservation of ACE2, leading to prolonged inhibition of SARS coronavirus infection in vivo. These protein-docking supramolecular filaments represent a new platform to deliver therapeutic proteins in inhalable aerosols for treatment of infectious and other human diseases. Keywords peptide amphiphiles supramolecular filaments ACE2 coronavirus biomaterials drug delivery protein therapeutics Published: December 12, 2022 ==== Body pmcIntroduction Numerous infectious diseases are contracted primarily via deposition of bacteria and/or viruses into the respiratory tract, including tuberculosis, influenza, and, recently, coronavirus disease 2019 (COVID-19). The global COVID-19 pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; also known as 2019-nCoV), has progressed into a grievous public health crisis with over 460 million confirmed cases of the disease and 6 million deaths worldwide as of March 15, 2022.1 , 2 Therefore, it continues to be of paramount importance to rapidly develop effective vaccine or therapeutic strategies to address the ongoing COVID-19 pandemic and potential future epidemics.3 Although the US Food and Drug Administration (FDA) has granted full approval and emergency use authorization for some vaccine formulations and disease treatments,4 , 5 the virus continues to spread rapidly and subsequently mutate, leading to emergence of variants of concern (VOCs) of SARS-CoV-2; exactly how these prophylactic and therapeutic agents will handle these and future mutations alongside new viruses is subject of an evolving investigation.6 , 7 , 8 , 9 Although SARS-CoVs may mutate, these viruses predominantly function by their S protein binding to the cognate receptor angiotensin-converting enzyme 2 (ACE2), which is the first step for viral entry, replication, and transmission; therefore, ACE2 is a logical druggable target for combating current and future CoVs.10 , 11 , 12 , 13 ACE2 exists in membrane-bound and soluble forms, where both share the same enzymatic and viral binding functionalities, but only membrane-bound ACE2 is believed to facilitate viral entry and consequent infectivity.14 , 15 Therefore, soluble ACE2 can serve as a decoy receptor by binding to the S protein on the virus surface and block the mechanism of viral entry into host cells, making soluble ACE2 an attractive candidate for preventing CoV infection.16 , 17 , 18 Clinical translation of soluble ACE2 remains challenging in the context of SARS-related CoV infections because the enzyme is unstable and can quickly degrade, especially in an inflammatory setting.19 An additional hurdle exists in delivery of therapeutic ACE2 to its target site (in the case of COVID-19, the airway and the lungs), where efficacy suffers from its short half-life and lack of active transport mechanisms from the circulation into the epithelial lining fluid of the lungs when delivered by intravenous injection.20 , 21 , 22 Recent advances in nanomaterials have yielded carriers of decoy ACE2 that help address these challenges; for instance, development of cell membrane-derived nanoparticles that curb SARS-CoV-2 infectivity in lung tissue.23 , 24 , 25 However, given the essential roles of ACE2, as a carboxypeptidase, in regulating cardiovascular function, hypertension, and innate immune systems, it remains unclear whether delivery of enzymatically active ACE2 would lead to unknown mid- to long-term complications to the host.20 In this context, we harness the multivalent nature of ACE2, where the enzyme’s proteolytic activity and viral receptor properties are independent and non-interfering (sites highlighted in the ACE2 structure in Figure 1A),20 to silence ACE2’s enzymatic function and display the decoy receptors on the surface of peptide-based supramolecular filamentous nanostructures via enzyme-substrate complexation. We designed peptide amphiphiles (PAs), a class of molecular building units capable of spontaneously associating in aqueous solution to form one-dimensional supramolecular biomaterials,26 , 27 , 28 , 29 to present a peptide ligand/inhibitor capable of binding to the active proteolytic site of ACE2 on the filament surface. Peptide-based supramolecular materials have been designed to facilitate various supramolecular interactions to immobilize proteins on structure surfaces to enhance protein stability and delivery30 , 31 , 32 , 33 , 34 and could be highly advantageous as carriers for decoy ACE2. In addition to being deliverable in aerosols,35 , 36 the charged surface and high aspect ratio likely aid deposition and retention atop the mucus layer coating the lung epithelium while mitigating cellular internalization, extending the availability of ACE2 at its target site while also mitigating potential hazardous contact of captured virus with host cells.37 , 38 , 39 , 40 , 41 , 42 In this work, we developed ACE2-docking supramolecular filaments that effectively bind ACE2 through enzyme-substrate complexation to inhibit its enzymatic activity and demonstrate the decoy function of ACE2 to effectively capture SARS-CoVs and attenuate viral infectivity in vivo.Figure 1 Design of ACE2-docking and silencing supramolecular filaments and their assembly in aqueous solution (A) Cartoon representation of soluble ACE2 alongside its protein structure, with the SARS-CoV-2 S protein RBD-binding site on ACE2 highlighted in yellow (PDB: 6M17) and the cleft of the carboxypeptidase active site of ACE2 highlighted in cyan (PDB: 1R42). The protein structure was generated using ChimeraX software. (B) Chemical structure of the investigated ACE2-binding Ligand (top) and Filler (bottom) PA molecules; both contain the same aliphatic region (black) and the same intermolecular hydrogen bond-contributing sequence (blue). The Filler PA contains negatively charged glutamic acid residues (cyan) to pair with the positively charged lysine residues (red) of the Ligand PA. The flexible, hydrophilic spacer (green) of the Ligand PA distances the ACE2-binding peptide DX600 (pink, with amino acid sequence GDYSHCSPLRYYPWWKCTYPDPEGGG) from the surface of assembled supramolecular structures. (C) The two PAs can be dissolved together in aqueous solution to spontaneously associate and co-assemble into supramolecular filaments that display the ACE2-binding ligand on their surfaces. Subsequently, soluble ACE2 can be added to filament solutions to allow binding via inhibition of the ACE2 proteolytic active site to yield decoy ACE2-docking filaments, called fACE2. (D) fACE2 can be delivered to nasal passageways and lung tissue, where it can bind to and capture SARS-CoVs to block viral entry into host cells. (E) Representative low-magnification transmission electron microscopy (TEM) images of ACE2-docking supramolecular filaments (20:1 molar ratio of Filler to Ligand) after dissolving at 1 mM in PBS at pH 7.4 and aging for 24 h, revealing ribbon-like filaments several microns in length. Scale bar represents 200 nm. (F) High-magnification TEM image of the boxed area in (E). Filament diameter is represented as mean ± SD (n = 35). Scale bar represents 50 nm. (G–J) Representative cryo-TEM micrographs of ACE2-docking supramolecular filaments formed from co-assembly of varying molar ratios of Filler to Ligand (fixed 50 μM Ligand concentration: G, 1:0; H, 10:1; I, 20:1; and J, 50:1) after dissolving in PBS at pH 7.4 and aging for 24 h, confirming a ribbon-like morphology with slight twisting. Scale bar represents 100 nm (G) or 200 nm (H–J). Results and discussion Design and assembly of ACE2-docking supramolecular filaments When designing our supramolecular filaments, we aimed to leverage the carboxypeptidase activity of ACE2 to allow enzyme docking and presentation of the SARS-CoV-2 S protein receptor-binding domain (RBD) binding site of ACE2 at the filament surface. These two sites on ACE2 are distinct and non-interfering (the ACE2 structure with these sites highlighted is shown in Figure 1A).11 , 13 , 43 With this rationale, we selected a known potent peptide inhibitor of ACE2 enzymatic activity to incorporate into the design of an ACE2-binding PA, called Ligand (the molecular design is highlighted in Figures 1B and S1), and paired this PA with another self-assembling constituent of the filaments, a filler PA, called Filler (the molecular design is shown in Figures 1B and S2), which serves to modulate the distribution density of the Ligand to optimize ACE2 docking and regulate surface charge.44 On the C terminus of the Ligand, we present the non-cleavable peptidic ACE2 inhibitor DX600 (Ki = 2.8 nM, KD = 10.1 nM), through which ACE2 can reversibly bind at its active site,45 allowing effective immobilization and release of soluble ACE2 from filament surfaces. The DX600 peptide ligand is extended away from the filament surface with a short, flexible, hydrophilic oligoethylene glycol (OEG4) chain and a double glycine segment (GG) as a spacer for better accessibility and to mitigate undesired interactions between ACE2 and the charged filament surface. The Ligand and Filler were molecularly crafted to have matching but oppositely charged intermolecular interaction-regulating peptide segments (VVVGKK and VVVGEE, respectively) to facilitate formation of a hydrogen bonding network within the filaments (VVV) and to enhance supramolecular cohesion through electrostatic complexation (KK/EE), promoting co-assembly of the two components into filamentous structures.27 , 46 Both PAs contain a dodecyl chain (C12 alkyl group) at their respective N termini to enable hydrophobic collapse for self-assembly in aqueous environments. Both molecules were synthesized following standard solid-phase peptide synthesis techniques and subsequently purified and characterized with reverse-phase high-performance liquid chromatography (RP-HPLC) and MALDI-TOF mass spectroscopy, respectively (Figures S1 and S2). Together, Ligand and Filler monomers can be mixed at varying ratios in aqueous solutions to spontaneously associate and form supramolecular filaments, and, subsequently, soluble ACE2 can be added to solutions of these filaments to bind to the presented ligand at the surface, yielding ACE2-docking filaments bearing decoy ACE2, called fACE2 (Figure 1C). Solutions of fACE2 can be delivered to nasal passageways and lung tissue, where the presented decoy ACE2 can bind to SARS-CoV spike proteins and block viral entry into host cells, curbing viral infectivity (Figure 1D). After successful synthesis and purification, the self-assembly behavior of each molecule was studied. After aging for 24 h in water, the Ligand PA alone was observed, using transmission electron microscopy (TEM), to form spherical and other irregularly shaped aggregates, and this shape was corroborated by similar size measurements with dynamic light scattering (DLS) and disordered random-coil circular dichroism (CD) spectra (Figure S3), which is likely due to a combination of a relatively large hydrophilic segment with steric hinderance from neighboring DX600 ligands that hinders the formation of ordered hydrogen bonds between monomers that typically yield one-dimensional structures.27 Using TEM, the Filler PA was observed to form ribbon-like filaments over several microns in length (Figure S4); thus, the Filler likely not only serves a purpose as a diluting agent to regulate ligand density but is also key for providing dimensionality to the co-assembly of the supramolecular structure components. When mixed together in PBS at pH 7.4, the Ligand and Filler PAs co-assemble into ribbon-like filaments over several microns in length, with diameters measuring around ∼11.3 nm under TEM (Figures 1E, 1F, and S4), which is corroborated by the observed increasing β-sheet character of the hydrogen bonding within the filaments as Ligand content is increased (Figure S5). The ratio of Filler to Ligand PAs in the co-assembled structures is expected to be a key parameter in maximizing ACE2 binding because it determines DX600 density on the filament surface44 and affects the supramolecular stability of the structures, which is critical for maintaining structural integrity during aerosol formation for inhalable delivery.36 Because the assembled state represents a dynamic equilibrium between the filaments and monomers, the thermodynamic stability of each PA and their mixture was evaluated by assessing the critical micelle concentration (CMC) for each system via Nile Red assay, revealing CMC values of around 2.9, 1.3, and 0.63 μM for the Filler and Ligand and a 1:1 molar ratio mixture, respectively (Figure S6). By preparing filaments well above the CMC of the Ligand, we can ensure that the majority of the Ligand monomers are incorporated in the supramolecular structure and increase the likelihood of ACE2 docking to the filament surface. The reduction in CMC for the mixed system corroborates the enhanced stability conferred by the additional electrostatic interactions incorporated through opposite charges in our molecular designs and provides additional evidence of co-assembly of the two PAs into supramolecular structures. We varied the molar ratios of Filler to Ligand (10:1, 20:1, and 50:1, with set 50 μM Ligand to be higher than CMC) and observed the resulting supramolecular structures under cryogenic TEM (cryo-TEM) and conventional TEM (Figures 1G–1J and S4). Our cryo-TEM imaging confirms the ribbon-like morphology, with evidence of slight, intermittent twisting for all tested ratios in PBS, suggesting incorporation of the Ligand into filamentous structures with minimal effect on morphology. Our analysis of structure, hydrogen bonding characteristics, and CMC supports supramolecular copolymerization of Filler and Ligand PAs into filaments. Docking decoy ACE2 to supramolecular filament surfaces With confirmation of successful incorporation of Ligand PA into supramolecular filaments, we next aimed to assess whether ACE2 can successfully bind to the Ligand PA and dock to filament surfaces. We assessed the specificity of the binding interaction between Ligand and ACE2. We designed a scrambled analog to Ligand, sLigand, in which the order of the amino acids of DX600 are shuffled, to serve as a negative control. Like the ACE2-specific Ligand, sLigand also forms spherical aggregates in water and PBS (Figure S7). Binding of Ligand and sLigand to immobilized ACE2 was analyzed via biolayer interferometry (BLI). We observed a distinct binding response between ACE2 and Ligand compared with sLigand, which demonstrates specificity of the Ligand and ACE2 binding interaction (Figure 2A). For high concentrations above the CMC value, we observe a higher background signal, indicative of nonspecific interactions occurring between the spherical aggregates and ACE2 (Figures 2B and 2C). Because of these solubility limitations of Ligand and sLigand, a binding saturation point was not reached, and an accurate binding affinity constant could not be determined (for the free DX600 peptide, the binding affinity has been reported as KD = 10.1 nM, where our Ligand likely performs at or below this level).45 Although we do observe a relatively fast off-rate of ACE2 from Ligand, this rate is likely unimportant in the context of inhibiting viral entry because bound and unbound ACE2 can capture SARS CoVs. Nevertheless, these results support the hypothesis that a specific interaction between Ligand and ACE2 does occur.Figure 2 Docking ACE2 to supramolecular filament surfaces via enzyme-substrate complexation Shown is BLI-based analysis of the interaction kinetics of Ligand and sLigand with immobilized ACE2 by 3-fold dilution (33.3–0.137 μM). (A) Equilibrium response signal of Ligand and sLigand evaluated a moment before the dissociation step (299 s). Response signals are normalized to their respective maximum values. (B and C) BLI kinetics traces of (B) Ligand and (C) sLigand association with immobilized ACE2, with the dissociation step occurring at 300 s. (D) Kinetics measurement of evolved fluorescence of the activity probe by ACE2 cleavage in the presence of various ACE2-docking filament components (ACE2, free rhACE2; 20:1 Fil, 20:1 molar ratio of Filler to Ligand). Data are presented as mean ± SD (n = 3). (E) Initial velocity calculated from kinetics measurements of ACE2 activity in the presence of ACE2-docking filament components. Data are presented as mean ± SD (∗p < 0.05; ∗∗p < 0.01; ns, p > 0.05; ∗∗∗∗p < 0.0001 for ACE2, Filler, and sLigand versus every other group; one-way ANOVA with Tukey’s post hoc test, n = 3). (F) Zeta potential measurements of Ligand and sLigand before and after incubation with ACE2. Data are presented as mean ± SD (∗∗∗p < 0.001; ns, p > 0.05 otherwise; one-way ANOVA with Tukey’s post hoc test, n = 3). (G) Effect of Filler:Ligand molar ratio on docking efficiency, holding Ligand (50 μM) and ACE2 (50 nM) concentrations fixed while varying Filler concentration, highlighting optimization of spacing between Ligand PAs within filaments. Data are presented as mean ± SD (∗∗p < 0.01; ns p > 0.05; ∗∗∗∗p < 0.0001 otherwise; one-way ANOVA with Tukey’s post hoc test, n = 3). (H) Effect of Ligand:ACE2 molar ratio on docking efficiency, holding Ligand concentration (50 μM) and Filler:Ligand molar ratio (20:1) fixed while varying Ligand:enzyme ratio by adjusting ACE2 concentration. Data represent mean ± SD (∗p < 0.05; ns, p > 0.05; ∗∗∗∗p < 0.0001 otherwise; one-way ANOVA with Tukey’s post hoc test, n = 3). (I) Effect of Ligand concentration on docking efficiency, holding Filler concentration (1 mM) and Ligand:ACE2 molar ratio (1,000:1) fixed while varying Ligand concentration, reflecting optimization of minimal Ligand concentration to ensure that ACE2 binding occurs with filaments. Data are presented as mean ± SD (ns, p > 0.05; ∗∗∗∗p < 0.0001 otherwise; one-way ANOVA with Tukey’s post hoc test, n = 3). Shown is Optimization of co-assembly and loading parameters to maximize ACE2 docking to supramolecular filaments, determined by the extent of enzymatic inhibition relative to free ACE2 control (G–I). We next aimed to verify that the observed binding interaction was occurring at the proteolytic active site of ACE2 and at the surface of the supramolecular structures. Using a fluorogenic peptide substrate for ACE2 (7-methoxycoumarin-4-yl)acetyl-YVADAPK(2,4-dinitrophenyl)-OH (Mca-YVADAPK(Dnp)-OH) where active ACE2 will cleave the quencher moiety from the peptide and yield a detectable fluorescence signal, we assessed the effect of various components of the ACE2-docking filaments on ACE2 activity (evolved fluorescence for different conditions is shown in Figure 2D). Assuming Michaelis-Menten enzyme kinetics, we also approximated the initial velocity of the reaction (50 nM ACE2) for each condition based on the observed signal (Figure 2E).45 We observed a slight effect on ACE2 activity in the presence of Filler PA alone, where the small reduction in velocity may likely be attributed to nonspecific interactions between ACE2 and the filaments and also to diffusion limitations presented by a dense filament network (1 mM Filler); however, this activity is much higher compared with the Ligand alone (50 μM), highlighting that DX600 peptide design is key for the ACE2 interaction/inhibition. Compared with the sLigand (50 μM), the Ligand drastically reduces ACE2 initial velocity, confirming that the ACE2-Ligand interaction is occurring at the ACE2 proteolytic site. Although slightly higher, there is no appreciable difference in the initial velocity of ACE2 cleavage in the presence of the Ligand in comparison with the free DX600 peptide alone. For the co-assembled system (20:1 molar ratio of Filler to Ligand), we observed a higher initial velocity compared with the Ligand alone despite equal Ligand concentrations. This could likely be due to a more confined orientation of the DX600 peptide presented on the filament surface, limiting accessibility to ACE2 to some extent, in combination with slower diffusion of ACE2 through the filament network. This reduction relative to the initial velocity of free ACE2 shows around 93% inhibition of added ACE2, suggesting binding to presented inhibitor ligands on the docking filaments. Next, we aimed to validate that the binding interaction with ACE2 occurs at the surface of the supramolecular structures and not predominately and/or exclusively with monomers in solution. We first conducted zeta potential measurements of ACE2 alone (pI ≈ 5.36) and in the presence of Ligand and sLigand spherical aggregates at physiological pH (7.4) in PBS (Figure 2F) because, if the two entities are not interacting, then we expect the measured zeta potential to be equivalent to the intensity-averaged zeta potential of the mixture. We measured a large drop in zeta potential for the Ligand micelles mixed with ACE2 and relatively no change with the sLigand system, suggesting ACE2 complexation at the particle surface and emphasizing the key role of Ligand binding in facilitating this interaction as opposed to other nonspecific interactions. The lower zeta potential is expected with ACE2 binding because the exposed spike RBD-binding site on ACE2 has a negative electrostatic potential.47 The same phenomenon is also observed with the co-assembled supramolecular system, where the zeta potential decreases after ACE2 binding, suggesting ACE2 docking at the filament surface (Figure S8). Optimizing ACE2 presentation on the supramolecular filament surface To maximize the docking efficiency of added ACE2 and optimize presentation of ACE2 on the surface of the ACE2-docking supramolecular filaments, we investigated the effects of different co-assembly variables in facilitating ACE2 docking, such as molar ratios of the two filament components and relative ACE2 content. First we examined the influence of the Filler:Ligand molar ratio on ACE2 docking efficiency, which we represent as the extent of observed inhibition of ACE2 enzymatic activity for each tested group (initial velocity using a fluorogenic peptide substrate assay) in comparison with free ACE2 activity under the same conditions. For fixed concentrations of Ligand and ACE2 (50 μM and 50 nM, respectively), we observe that, with increasing Filler content relative to Ligand, we achieve greater ACE2 docking (Figures 2G and S9). This is likely reflective of enlarged spacing between neighboring ligands, which facilitates effective ACE2 binding by mitigating steric hinderance that may result from crowding of ligands and/or ACE2 (∼85 kDa). With at least a 20:1 molar ratio of Filler:Ligand, we achieve around 96% of the added ACE2 bound at the filament surface, and higher ratios from this point achieve minimal increases in ACE2 incorporation. We therefore selected the 20:1 ratio as the optimal spacing because this also minimizes Filler demand, which, in turn, decreases the total number of filaments and likelihood of physical crosslinks that can increase solution viscosity and potentially impede ACE2 diffusion, which could have negative effects on the occurrence of binding events between ACE2 and Ligand at filament surfaces.32 , 48 Considering the binding equilibrium that exists between our Ligand, ACE2, and the Ligand-ACE2 complex, we next investigated the effects of the molar Ligand:enzyme ratio, a key parameter in enhancing docking efficiency. Holding the Filler:Ligand ratio (20:1) and Ligand concentration (50 μM) constant, we varied the Ligand:enzyme ratio by adjusting the added ACE2 concentration (10–250 nM) and determined its effect on ACE2 activity inhibition. As expected, we find that, with increasing the Ligand:enzyme ratio, the docking efficiency increases (greater observed enzymatic inhibition) as binding equilibrium is shifted toward formation of the Ligand-ACE2 complex (Figures 2H and S10). With a 1,000:1 molar ratio of Ligand:ACE2 at our optimal ligand spacing, we successfully dock around 95% of the added ACE2 to the filament surface, where further increases show negligible changes in docking efficiency. At higher ACE2 concentrations, docking may be limited by the accessibility of ligands at the filament surface or other steric effects. We selected the 1,000:1 molar ratio of Ligand:ACE2 as optimal for future preparations of fACE2 because this ratio ensures that almost all added ACE2 will bind to the filament surface. After examining the role of Filler concentration and the ratio of Ligand to ACE2, we next studied the effect of Ligand concentration on maximizing docking efficiency. Although holding the Filler concentration constant (1 mM) and varying added ACE2 to maintain a 1,000:1 molar ratio of Ligand:ACE2, we adjusted the Ligand content in the filaments (5–50 μM) and determined its effect on ACE2 activity (Figures 2I and S11). We observe that increasing the ligand concentration yields greater docking of ACE2, as expected. We also see a drastic drop in ACE2 docking with the lower concentrations of Ligand tested (10 μM), suggesting the existence of a critical point in Ligand concentration where, despite being at the optimal ratio relative to ACE2, the density of Ligand is too low, and the equilibrium is likely not shifted in favor of formation of the Ligand-ACE2 complex. At these lower concentrations of Ligand, the probability of ACE2 binding to a presented Ligand molecule is too low (whereas, for the study detailed in Figure 2G, the Ligand concentration held at a constant reflects an equal probability of a binding event between conditions). These results validate that, without presentation of the enzymatic inhibitory ligand at their surface, there is negligible interaction of ACE2 with the filaments. Last, we determined the minimal incubation time sufficient to achieve the maximum docking efficiency of added ACE2. At the previously determined optimal conditions for ACE2 docking (20:1 Filler:Ligand and 1,000:1 Ligand:ACE2), we pre-incubated filaments with ACE2 (25 nM) for a range of times (0–120 min) before assessing ACE2 activity (Figure S12). We observed an almost instantaneous capture of ACE2 to the filament surface (0 min incubation, ∼83% inhibition), which is likely due to the strong binding affinity of the DX600 ligand for ACE2. Within 15 min, we achieve the maximum docking efficiency of around 95%, with longer incubation times showing negligible increases in ACE2 inhibition. This is promising with respect to translation of the system to a clinical setting because ACE2 will dock to filament surfaces within a few minutes, yielding fACE2 ready for administration. Delivery of fACE2 in respirable aerosols Having validated successful docking of ACE2 to the supramolecular filament surface, we next evaluated the ability of the filaments to carry ACE2 in respirable aerosols as a means of delivering ACE2 directly to lung tissues via jet nebulization. Because of the noncovalent nature of filament assembly and binding of ACE2, we expect structural integrity and activity to be affected by air-liquid interface (ALI) enrichment and shear stress during aerosol droplet formation.36 , 49 , 50 This is of particular importance with respect to the decoy function of ACE2 because potential ACE2 unfolding and aggregation from aerosolization may negatively influence the ability of the viral S protein to effectively bind to decoy ACE2. We therefore investigated the stability of docked ACE2, reflected by its proteolytic activity (because unfolded and/or aggregated ACE2 will likely exhibit inhibited activity), by collecting and analyzing the emitted mist from a jet nebulizer, after which ACE2 was unbound and separated from filament surfaces by dialysis. Although reduced compared with pre-nebulization, we find that ACE2 delivered on filaments exhibits much higher enzymatic activity (around 67% relative initial velocity relative to the ACE2 control) compared with free ACE2 (around 14% relative to the control) after jet nebulization (Figures 3A and 3B). These results suggest that our docking strategy not only facilitates delivery of decoy ACE2 in respirable aerosols but also provides protection against protein denaturization by harsh aerosolization forces, ensuring greater fractions of delivered ACE2 in the correct conformation. We speculate that two factors contribute to the structural preservation of ACE2 in this system (shown in Figure 3C). First, the strong binding affinity of ACE2 to the Ligand molecule likely aids in mitigating adsorption of ACE2 to the highly hydrophobic ALI, which can result in protein unfolding and aggregation, by shifting the equilibrium toward the docked state and reducing ACE2 content in the bulk solution. Second, the PA monomers of the supramolecular filaments exchange frequently between their assembled state and the ALI, where the hydrophobic influence of the ALI shifts the assembly-disassembly equilibrium from the supramolecular structure to the monomeric form.36 , 51 Subsequent enrichment of the ALI by PA monomers likely impedes ACE2 adsorption and potential unfolding and/or aggregation, preserving its structure and activity. Therefore, using supramolecular filaments as inhalable carriers appears to be highly advantageous for protein delivery within respirable aerosols, particularly because of the surface activity of PAs. Based on this proposed mechanism, improvements to ACE2 activity and structure preservation could be afforded by increasing the strength of the binding interaction between ACE2 and the filament surface (such as using a tighter binder to the proteolytic active site in the Ligand design) and/or optimizing the extent of interface enrichment of the PAs to aerosol droplet surfaces (by modulating their CMCs).Figure 3 Delivery of fACE2 in respirable aerosols via jet nebulization (A) Kinetics measurement of evolved fluorescence intensity of the proteolytic activity probe by ACE2 after nebulization and after separation of ACE2 from filaments via dialysis, highlighting the increased ACE2 activity afforded by fACE2 compared with free ACE2. Data represent mean ± SD (n = 3). (B) Estimated initial velocities of ACE2 proteolytic activity, determined from kinetics measurements (relative to free ACE2 control), emphasizing the preservation effect afforded by the docking strategy. Data are presented as mean ± SD (∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001 for ACE2 versus NEB ACE2, one-way ANOVA with Tukey’s post hoc test, n = 3). (C) Schematic of the hypothesized mechanism of ACE2 structural preservation afforded by fACE2, where binding affinity interactions of ACE2 at the filament surface and enrichment of the air-liquid interface (ALI) by filament PA monomers mitigate the interaction strength of ALI on ACE2 together prevent protein unfolding and aggregation, preserving ACE2 activity. (D) Representative TEM images of fACE2 at 1 mM in PBS at pH 7.4 before (left) and after (right) jet nebulization, showing retention of filament shape but reduction in length. Diameter measurements are represented as mean ± SD (n = 35). Scale bar represents 200 nm. (E) Population size distribution of observed filament contour lengths after jet nebulization of fACE2 (20 bins, 50 nm each) from TEM images, where average contour length (μ) is given as mean ± SD alongside median (M) length (n = 398 analyzed filaments). To further elucidate the behavior of fACE2 during aerosol delivery, we next assessed its structural stability during jet nebulization. This is of concern because filaments measure over several microns in length and form from noncovalent interactions, and the resulting size distribution after nebulization will be critical for achieving ideal distribution and retention of fACE2 in lung tissue.39 , 52 As observed with TEM, fACE2 maintains its ribbon-like morphology after addition of ACE2 (50 nM), and after jet nebulization, fACE2 maintains its filamentous shape with an observed reduction in contour length, which is expected because of ALI enrichment and shear during aerosol droplet formation (Figure 3D).36 , 53 The influence of these factors is corroborated by CD measurements, where the observed reduction in signal intensity is reflective of weakened hydrogen bonding because of dissociation into smaller structures and/or PA monomers (Figure S13). The average contour length of fACE2 after nebulization measured around 343 ± 196 nm, although nebulization does induce polydispersity with respect to filament length (Figure 3E). However, this distribution of size could be advantageous with respect to diffusion through the mucus layer atop airway epithelia because some fACE2 may penetrate the mucus and some remains on top of or closer to the mucus layer surface.39 Integration of fACE2 throughout the mucus layer may potentially increase the likelihood of successful virus capture before viral entry into host cells. The degree of filament fragmentation is consistent regardless of formulation concentration (0.2–1 mM filament concentration range), where the average contour length is around 330 nm, with similar distributions for each tested concentration (Figure S14). Jet nebulizer emission of fACE2 is linear over the course of a nebulization event, with release of around 6.3%/min (by mass) of the loaded dose (Figure S15). These data suggest that fACE2 exhibits steady release from a jet nebulizer with consistent size distribution, which is imperative for achieving more uniform distributions in lung tissue for inhalation-based delivery. Inhibition of pseudotyped CoV entry in vitro by fACE2 Having shown that ACE2-docking filaments bind ACE2 to their surface and carry ACE2 in respirable aerosols, we next evaluated the ability of fACE2 to capture SARS-CoV-1 and -2 spike protein pseudotyped feline immunodeficiency virus (FIV) and prevent viral entry in vitro. First we assessed the cytotoxicity of ACE2-docking filaments against relevant human cell lines (NL20, bronchial epithelial cells; A549, alveolar basal epithelial adenocarcinoma cells; and 293/ACE2/TMPRSS2, stable-producing human ACE2 and co-receptor, TMPRSS2,12 HEK293 cells, used in following antiviral studies). For all tested concentrations of filaments (0.1–100 μM), cells maintained high viability after treatment (>90%), which is promising for use of this system as a safe delivery vehicle of soluble ACE2 (Figure S16). The negligible cytotoxicity likely does not interfere with evaluation of antiviral efficacy in the following in vitro assessments. To evaluate the antiviral effect of fACE2, pseudotyped viruses (PsVs) were generated for SARS-CoV-2 and SARS-CoV (with vesicular stomatitis virus G protein [VSV-G] as a negative control) to yield virus particles decorated with their respective spike protein and containing an expression cassette for luciferase to assess viral entry into 293/ACE2/TMPRSS2 cells. We first assessed the decoy effect of fACE2 and relevant controls (free recombinant human [rhACE2] and empty ACE2-docking filaments [20:1 molar ratio Filler:Ligand filaments without ACE2 docked to their surface, Fil]) by pre-incubating varying doses with each PsV and subsequently challenging 293/ACE2/TMPRSS2 cells with the mixture (Figure 4A). We found that SARS-CoV-2 and SARS-CoV PsV infection is strongly inhibited by fACE2 and ACE2 in a dose-dependent manner, suggesting that ACE2 displayed on the surface of fACE2 hijacks S protein-mediated viral infection and that docking of ACE2 does not impede viral capture (Figures 4B and 4C). This trend is not observed for the VSV-G PsV, as expected, and the empty filaments alone show little to no viral capture for all PsVs tested, emphasizing the key role of ACE2 in inhibiting S protein-mediated viral entry. An increase in inhibition is observed at higher concentrations of filaments (∼18% at the highest dose against SARS-CoV-2 PsV), which may be due to nonspecific interactions between virus particles and filaments; this may explain the higher PsV infection inhibition observed for fACE2 (∼88%) compared with free ACE2 (∼66%). Against SARS-CoV-2 and SARS-CoV, fACE2 exhibited potent inhibitory activity, which shows promise in providing broad-spectrum antiviral efficacy for current and future SARS-CoVs.Figure 4 fACE2 inhibits PsV infection and docking of ACE2 extends its decoy function (A) Schematic of the study design for assessing the decoy effect of fACE2. (B–D) Shown is inhibitory activity of fACE2 and controls (rhACE2 and empty filaments [20:1 molar ratio Filler:Ligand filaments without ACE2 docked to their surface]; Fil) against PsV. SARS-CoV-2 (B), SARS-CoV (C), and VSV (D) viral entry. Data are presented as mean ± SD (for the highest tested dose: ns, p > 0.05; ∗∗∗p < 0.001; ∗∗∗∗p < 0.0001 for fACE2 and ACE2 versus Fil for SARS-CoV-2 and SARS-CoV PsV; one-way ANOVA with Tukey’s post-hoc test, n = 3 independent experiments). (E) Schematic of the study design for assessing the preventative effect of fACE2 against SARS-CoV-2 PsV challenge. (F) Inhibitory activity of fACE2 and controls after set incubation times against SARS-CoV-2 PsV viral entry evaluated at 0.5 nM ACE2 or the equivalent dose. Data are presented as mean ± SD (ns, p > 0.05; ∗p < 0.05; ∗∗p < 0.01; ∗∗∗p < 0.001, with fACE2 versus ACE2 represented above the fACE2 line and ACE2 versus Fil above the ACE2 line; ∗∗∗∗p < 0.0001 for fACE2 and ACE2 versus Fil otherwise; one-way ANOVA with Tukey’s post hoc test, n = 3 independent experiments). (G) Inhibitory activity of fACE2 and Fil after set incubation times (continuing from F) against SARS-CoV-2 PsV viral entry. Data are presented as mean ± SD (for each time point: ns, p > 0.05; ∗p < 0.05; ∗∗∗p < 0.001, unpaired two-tailed t test with Welch’s correction, n = 3 independent experiments). Because ACE2 degrades quickly, extending its availability as a decoy is highly desirable for blocking SARS CoV infections.19 Therefore, we next aimed to assess the preventative effect of fACE2 and whether our docking strategy serves to extend the decoy function. To achieve this, we pre-treated 293/ACE2/TMPRSS2 cells with fACE2 and relevant controls (0.5 nM ACE2 dose) and allowed them to incubate for a set time before challenge with SARS-CoV-2 PsV (Figure 4E). We observed that, for all tested incubation times, fACE2 exhibited a greater inhibitory effect compared with free ACE2; the extent of inhibition by free ACE2 began to steadily decrease around 2 h and became almost identical to empty filaments by 6 h (Figure 4F). In stark contrast, fACE2 inhibitory potential declined at a much slower rate, maintaining around ∼60% inhibition of PsV infection at 6 h. The preventative effect was assessed for longer incubation times for fACE2 and empty filaments (excluding ACE2 because the inhibitory effect became equivalent to that of the empty filament control). After 12 h, fACE2 preventative efficacy begins to wane and becomes indistinguishable from that of empty filaments around 36–48 h (Figure 4G). These results highlight a key advantage of fACE2 in preventing viral entry, where it exhibits more potent and sustained inhibitory efficacy compared with free ACE2, likely because of docking to the filament surface. Binding of ACE2 to the filament likely impedes premature degradation and/or cellular uptake of ACE2, enhancing and prolonging its antiviral efficacy. Attenuation of SARS-CoV-2 viral loads in vivo by inhalation of fACE2 After demonstrating the enhanced and extended antiviral efficacy afforded by our docking strategy against pseudotyped FIV, we next assessed the efficiency of fACE2 delivery into the lungs and its ability to subsequently capture SARS-CoV-2 in vivo. For delivery to mice, we used an intranasal mucosal atomizer to subject fACE2 to shear forces necessary to generate respirable aerosols before administration, which also yielded filaments of reduced contour length (Figure S17). By loading ACE2-docking filaments with a near-infrared fluorescent dye (Cyanine 5.5) to allow in vivo visualization, we evaluated the distribution and retention of the ACE2-docking filaments administered via intranasal inhalation and intratracheal instillation into K18-hACE2 transgenic mice. 3 h after administration, the fluorescence signal is still detectable in nasal passageways of treated mice, evidencing the presence of filaments. After 24 h, excised lungs show a strong fluorescence signal throughout the distal lungs, suggesting migration and long-term retention of filaments, which may likely be afforded by their filamentous shape (Figure S18).54 , 55 Histology of lung tissue sections taken at the 24-h time point indicates no obvious signs of structural damage, apoptosis, inflammation, or neutrophil infiltration induced by treatment with ACE2-docking filaments compared with the PBS control (Figure S19). These results suggest that ACE2-docking filaments exhibit long-term retention within lung tissues after inhalation and are safe, biocompatible delivery vehicles for ACE2. Having achieved successful inhalation delivery of ACE2-docking filaments in vivo, we next assessed the clinical potential of fACE2 as a preventative therapeutic agent against CoV infection. As shown in Figure 5A, we administered atomized fACE2 (20 nM dose of ACE2), rhACE2 (20 nM), or empty filaments (equivalent to the 20 nM ACE2 dose) to K18-hACE2 mice via intranasal inhalation 1 h before inoculating mice with prototype SARS-CoV-2 virus (USA-WA1/2020, 105 plaque-forming units [PFUs]/mouse). 2 days after inoculation, the mice were euthanized, and their lung tissue was harvested. As evidenced by increased cycle threshold (Ct) values for N protein gene expression and reduced N protein detection in lung tissue, treatment with fACE2 greatly reduces viral load in SARS-CoV-2-infected lungs compared with empty filaments and rhACE2 alone (Figures 5B and 5H), although the body weight loss in each group was similar (Figure 5C). The similar negligible effect on viral load by empty filaments and free rhACE2 suggests that the observed enhanced efficacy of fACE2 can likely be attributed to structural and functional preservation of ACE2 by our docking strategy as opposed to nonspecific interactions between filaments and virus particles. In parallel with the reduced viral load, mice that received treatment with fACE2 also exhibited decreased expression of the pro-inflammatory cytokine interleukin-6 (IL-6; Figure 5D), a hallmark of the hyperinflammatory response and cytokine storm in human and animal models of SARS-CoV-2 infection.56 , 57 , 58 Enhanced expression of the antiviral cytokine interferon gamma (IFN-γ; Figure 5E) was observed, suggesting restored antiviral immune responses and balanced inflammatory responses, which are typically lacking in patients with progressing COVID-19 and animal models and are indicative of severe COVID-19.59 , 60 , 61 , 62 fACE2-treated mice displayed alleviated lung inflammation and related pathology, as evidenced by mitigated inflammatory cell infiltration into lung tissue (neutrophils and monocytes; Figures 5F, 5G, and S20).63 These results highlight the prophylactic and therapeutic potential afforded by our docking strategy of decoy ACE2 to filament surfaces to improve antiviral efficacy, clearly illustrating the preventative potential of fACE2 in clinical practice. Although preventative efficacy is directly investigated here, these results also highlight the potential of fACE2 as a treatment tool for those already infected with SARS-CoV-2 by reducing the viral load in the airways and distal lungs through trapping newly replicated and released viral particles at the sites of infection.Figure 5 fACE2 attenuates viral load and lung injury after SARS-CoV-2 inoculation in vivo (A) Experimental timeline to assess the effectiveness of fACE2 and controls delivered via inhalation in mitigating the viral infectivity of subsequent SARS-CoV-2 inoculation (USA-WA1/2020, 1.5 × 105 TCID50 dose) in K18-hACE2 transgenic mice. (B) Ct values of SARS-CoV-2 in harvested lungs of K18-hACE2 mice after treatment with atomized fACE2 (20 nM ACE2 dose in PBS) and controls (Ctrls, PBS; Fil, atomized equivalent empty filament dose in PBS (20:1 molar ratio Filler:Ligand filaments without ACE2 docked to their surface); rhACE2, recombinant human ACE2, 20 nM dose in PBS). Data are presented as mean ± SD (∗p < 0.05; ns, p > 0.05 otherwise; one-way ANOVA with Tukey’s post hoc test, n = 8 mice per group). (C) Change in mouse body weight as a percentage of initial weight 2 days after treatment and SARS-CoV-2 inoculation. Data are presented as mean ± SD (ns, p > 0.05, one-way ANOVA with Tukey’s post-hoc test, n = 8). (D) Pro-inflammatory cytokine interleukin-6 (IL-6) mRNA expression from harvested mouse lungs by qRT-PCR after treatment and SARS-CoV-2 inoculation (the “naive” group represents expression levels in healthy, untreated, and unchallenged mice). Data are presented as mean ± SD (∗∗p < 0.01; ns, p > 0.05 otherwise; one-way ANOVA with Tukey’s post hoc test, n = 8). (E) Antiviral cytokine interferon gamma (IFN-γ) mRNA expression from harvested mouse lungs by qRT-PCR after treatment and SARS-CoV-2 inoculation (the “naive” group represents expression levels in healthy, untreated, and unchallenged mice). Data are presented as mean ± SD (∗p < 0.05; ns, p > 0.05 otherwise; one-way ANOVA with Tukey’s post hoc test, n = 8). (F) Hematoxylin and eosin (H&E) staining of harvested mouse lung tissue sections after treatment and SARS-CoV-2 inoculation. Scale bars represent 50 μm. (G) Summary of pathology scoring of analyzed mouse lung tissue sections as described in the Supplemental experimental procedures. Data are presented as mean ± SD (∗p < 0.05; ∗∗p < 0.01; ns, p > 0.05 otherwise; one-way ANOVA with Tukey’s post hoc test, n = 8). (H) IF staining of harvested mouse lung tissue sections after treatment and SARS-CoV-2 inoculation, showing SARS-CoV-2 N protein (anti-SCV2 N protein antibody, green) and nucleus (DAPI, blue) signals. Scale bars represent 50 μm. Conclusions In this work, we demonstrate the development of peptide-based supramolecular filaments for delivery of ACE2 in inhalable aerosols to capture SARS-CoVs and prevent infection for a prolonged period of time. Through incorporation of a peptide that inhibits the carboxypeptidase activity of ACE2 into our design, we are able to dock ACE2 to the surface of supramolecular filaments through enzyme-substrate complexation while leaving the spike protein RBD-binding site exposed. This docking strategy enables us to silence ACE2’s enzymatic activity, while stabilizing ACE2 for nebulization and inhalable delivery and increasing its retention in lung tissue when inhaled as a respirable aerosol. We demonstrate that fACE2 can act as a decoy for viral binding, as evidenced by enhanced and prolonged reduction of SARS-CoV-2 viral load in vitro and in vivo, and this reduction in viral load is able to prevent lung damage. Future work will investigate the therapeutic potential of fACE2 for treating COVID-19. This study establishes that our novel fACE2 system has high translational potential to prevent current and future CoV infections, affording a new platform for inhalable delivery of protein therapeutic agents to treat other human diseases. Experimental procedures Resource availability Lead contact Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, H.C. ([email protected]). Materials availability The materials generated in this study are available from the lead contact upon request. This study did not generate new unique reagents. Materials and reagents All fluorenylmethyloxycarbonyl (Fmoc)-protected amino acids and resins were purchased from Advanced Automated Peptide Protein Technologies (Louisville, KY). The OEG4 spacer (Fmoc-N-amido-PEG4-acid) was purchased from BroadPharm (San Diego, CA). rhACE2 protein (carrier free) was purchased from R&D Systems, Bio-Techne (Minneapolis, MN). Biotinylated human recombinant (His tag) ACE2 protein was purchased from Sino Biological (Wayne, PA). Free DX600 peptide used as a control was purchased from Cayman Chemical (Ann Arbor, MI). The near-infrared fluorescent dye Cyanine 5.5 carboxylic acid was purchased from Lumiprobe (Hunt Valley, MD). All other reagents and solvents were sourced from VWR, Avantor (Radnor, PA) or Sigma-Aldrich, Millipore Sigma (St. Louis, MO) without any further purification unless otherwise indicated. Molecular self-assembly and co-assembly of PAs to form supramolecular structures For self-assembly of PAs, lyophilized powders of PA were dissolved in 200 μL of hexafluoro-2-propanol (HFIP) to disrupt any preassembled structures. Samples were vortexed and sonicated for 5 min to aid dissolution and mixing. For co-assembled systems, appropriate volumes of Ligand solutions were added to solutions of Filler to achieve the specific molar ratios used in this study (Filler:Ligand ranging from 1:1–200:1 molar ratio), and tubes of the mixtures were vortexed and sonicated for 5 min to aid dissolution and mixing of the 2 components. Next, HFIP was evaporated and dried under a vacuum overnight to remove all traces of HFIP. After drying, Milli-Q water or PBS was added to yield the appropriate final concentrations (1 mM for Filler alone and 1 mM Filler for all co-assembly systems; 200 μM Ligand and sLigand alone and varied concentrations of Ligand relative to Filler for all co-assembly systems) of PAs and then vortexed to aid dissolution. The pH of the solutions was then adjusted with addition of 0.1 M HCl(aq) and 0.1 M NaOH(aq) to yield a final pH of 7.4. The solutions were then heated at 80°C in a water bath for 1 h to aid dissolution and facilitate the annealing process and then cooled at room temperature overnight. For docking of ACE2 to filament surfaces, solutions of ACE2 in PBS were mixed with filament solutions at an equal volume and allowed to incubate at room temperature for a set time until use, yielding fACE2. For encapsulation of the near-infrared dye Cy5.5 (Cyanine 5.5 carboxylic acid, Lumiprobe, Hunt Valley, MD) into hydrophobic filament cores, the same procedure was followed as described above; Cy5.5 was dissolved with filament components in HFIP at 2:1 molar excess relative to the Filler. After removal of HFIP, dissolution in PBS, annealing, and aging overnight, unencapsulated Cy5.5 (precipitated) was removed by centrifugation (13,400 rpm, 3 min), and filament-containing supernatant was removed for analysis and in vivo lung distribution studies. TEM and cryo-TEM Solutions of PAs were added (10-μL drop) onto a carbon film copper grid (400-square mesh, Electron Microscopy Sciences, Hatfield, PA) and allowed to sit for 1 min. Then the excess solution was wicked away with filter paper to leave a thin film of the sample on top of the grid. To achieve negative staining, a 7-μL droplet of uranyl acetate solution (2 wt % in Milli-Q water) was added on top of the grid and blotted away after 30 s. Grids were left to dry for at least 3 h before imaging on an FEI Tecnai 12 Twin transmission electron microscope (100-kV acceleration voltage). All images were recorded using an SIS Megaview III wide-angle charge-coupled device (CCD) camera. Filament diameters and contour lengths were measured using ImageJ software (NIH, Bethesda, MD); a minimum of 35 individual structures were analyzed for diameter length measurements, and a minimum of 350 separate filamentous structures were analyzed for contour length measurements. For cryo-TEM, lacey carbon-coated copper grids (Electron Microscopy Sciences, Hatfield, PA) were treated with plasma air for 30 s before sample preparation to render the lacey carbon film hydrophilic. Sample addition to the grids was achieved with a Vitrobot with a controlled humidity chamber (FEI, Hillsboro, OR) maintained at 95% humidity. Droplets of sample solutions (in PBS at pH 7.4, 6 μL) were added to suspended grids in the Vitrobot and allowed to sit for 1 min before the grid was blotted with filter paper using Vitrobot preset parameters and then immediately plunged into a liquid ethane reservoir precooled by liquid nitrogen to produce a thick vitreous ice film on the surface of the grid. The grids were then transferred to a cryo-holder and cryo-transfer stage that were also cooled by liquid nitrogen. All imaging was performed on an FEI Tecnai 12 Twin transmission electron microscope, operating at a 100-kV acceleration voltage. The cryo-holder temperature was maintained below −170°C with liquid nitrogen to prevent sublimination of vitreous water during imaging. All images were acquired with a 16-bit 2K × 2K FEI Eagle bottom-mount camera. ACE2 activity assays The fluorogenic peptide substrate Mca-YVADAPK(Dnp)-OH (R&D Systems, Bio-Techne, Minneapolis, MN), was diluted from stock (4 mM) to a final concentration of 1 mM in dimethyl sulfoxide (DMSO). All monitored reactions with ACE2 were conducted in black, 96-well, flat-bottom, tissue culture-treated microplates (Falcon, Corning, NY) in 100 μL of PBS (pH 7.4) at room temperature with substrate (1–5 μL, 10–50 μM final concentration, DMSO concentration maintained at ≤5% [v/v]) added immediately before measurement. An equal volume of ACE2 was added to solutions of the supramolecular structure and incubated for 1 h for all experiments unless stated otherwise. ACE2 activity was monitored continuously (every 5 min for 2 h total) by measuring fluorescence intensity (λex = 320 nm, λem = 405 nm) upon substrate hydrolysis using a SpectraMax M3 microplate reader (Molecular Devices, San Jose, CA). The initial velocity for each reaction was determined from the rate of fluorescence evolved over the 5- to 20-min time course (the slope from linear regression analysis of this region). The extent of enzymatic inhibition (used as a reflection of the docking efficiency of ACE2 to the filament surface) was determined as the measured initial velocity of a tested condition relative to free ACE2 at the same ACE2 and substrate concentration. Aerosolization of ACE2-docking filaments and fACE2 For studies involving jet nebulization of ACE2-docking filaments and fACE2, solutions of these (3 mL) were added to a disposable jet nebulizer (Neb Kit 500, Drive Medical, Port Washington, NY) and connected to a nebulizer compressor (Rite-Neb 4, ProBasics, Marlboro, NJ) for constant air flow supply (∼6–10 L/min). The emitted mist was collected by fitting the outlet of the nebulizer with a 50-mL conical tube, where liquid aerosol droplets condense on the walls of the tube. Then the conical tubes were centrifuged at 4,000 rpm for 3 min, and the collected solution was removed for analysis. For quantification of ACE2 activity after nebulization, emitted mist solutions of fACE2 were dialyzed against PBS for 48 h using a Spectra/Por Float-A-Lyzer G2 dialysis device (MWCO, 20 kDa; Spectrum Labs, Rancho Dominquez, CA) to facilitate ACE2 separation from filaments before analysis. For the release rate of ACE2-docking filaments from the nebulizer, the device was weighed before and after addition of filament solutions (3 mL). For the course of a 10-min nebulization event, solution in the reservoir (50 μL) was collected at 2-min intervals, and the nebulizer with the remaining solution was weighed, and mass was recorded. Using analytical HPLC, the collected reservoir samples were assessed to determine the concentration of filaments left over at each time point. Using gravimetric data and the analyzed concentrations, release profiles were determined for the filaments via mass balance analysis. For in vivo studies involving inhalation delivery of ACE2-docking filaments to mice, filament solutions were loaded into a BD Luer-Lok 1-mL syringe equipped with a, MAD Nasal intranasal mucosal atomization device (Teleflex Medical, Morrisville, NC) to emit liquid droplets by pushing solution through the syringe. Collected solutions were used for administration to mice (inhalation or intratracheal instillation). Inhibition of pseudotyped virus (PsV) infection in vitro SARS-CoV and SARS-CoV-2 S protein cDNA (a gift from Dr. Marc Johnson, University of Missouri School of Medicine) was used to pseudotype FIV expressing luciferase using methods described previously.64 A VSV-G protein pseudotyped FIV expressing luciferase was used as a positive control for viral transduction. For the dose-response decoy effect studies (Figures 4A–4D), prior to infection, 2 μL of PsV (PsV titers: SARS-CoV-2, 1.7 × 1014 virus particles [VP]/mL; SARS-CoV, 1.7 × 1014 VP/mL; VSV, 4.0 × 1014 VP/mL) was added to 100 μL of Opti-MEM medium (Gibco, Invitrogen) supplemented with 2% (v/v) fetal bovine serum (FBS); 10 μL of fACE2, free ACE2, or empty ACE2-docking filaments (in 1× PBS at pH 7.4) was then added to achieve the desired final concentration of ACE2 (or the equivalent dose for empty filaments). The mixture was incubated at 37°C for 45 min. Then 100 μL of the mixture was transferred to the target cells (293/ACE2/TMPRSS2, >90% confluency) in 24-well flat-bottom, tissue culture-treated plates (Falcon). Cells were incubated for an additional hour, and then the culture medium was changed to fresh medium. After an additional 48-h incubation, the Luciferase Assay System Kit (Promega) was used to analyze luciferase activity following the manufacturer’s protocol. Experiments were performed with 6 technical repeats for each condition with a total of 3 biological repeats. For assessment of the preventative effect of fACE2 (Figures 4E–4G), 293/ACE2/TMPRSS2 cells (>90% confluency) in a 24-well flat-bottom, tissue culture-treated plates were treated with 100 μL of Opti-MEM medium supplemented with 2% (v/v) FBS containing fACE2, ACE2, or empty ACE2-docking filaments (at 0.5 nM ACE2 dose or its equivalent in 1× PBS at pH 7.4). The treated cells were incubated at 37°C for set time points (ranging from 0 min to 8 h for all 3 groups and an additional 12–48 h for fACE2 and empty filament groups) before being challenged by addition of SARS-CoV-2 PsV (2 μL; titer, 1.7 × 1014 VP/mL). With the added PsV, cells were incubated for an additional hour, and then the culture medium was replaced with fresh medium. After an additional 48 h of incubation, luciferase activity was assessed with the Luciferase Assay System Kit (Promega) following the manufacturer’s protocols. Experiments were performed with 6 technical repeats for each condition with a total of 3 biological repeats. Animal studies K18-hACE2 mice (male and female, 8–16 weeks old; The Jackson Laboratory Lab) were utilized for all animal experiments, which were approved by the Johns Hopkins University Animal Care and Use Committee. The animals were housed individually with access to food, water, and cage enrichment. After 1 week of acclimatization in the animal biosafety level 3 (ABSL-3) facility, the animals were anesthetized with ketamine and xylazine for intranasal inhalation of 20 μL of PBS, filament, rhACE2 (20 nM), or fACE2 (20 nM). Details regarding the methodology for preparing fACE2 and empty filaments before administration to mice are detailed in the above section “Aerosolization of ACE2-docking filaments and fACE2.” 1 h after reagent administration, mice were inoculated with 1.5 × 105 50% tissue culture infectious dose (TCID50) of SARS-CoV-2 (USA-WA1/2020), delivered in 30 μL of DMEM. Mice were monitored daily for signs of sepsis or casualties. All mice were sacrificed 2 days after SARS-CoV-2 infection, and lung tissue was collected for analysis. Histopathology and immunofluorescence Formalin-fixed and paraffin-embedded tissue sections were stained with hematoxylin and eosin (H&E) or anti-SARS-CoV-2 N protein antibody (Novus Biologicals, NB100-56576; at a dilution of 1:200). Morphometric analyses were performed on affected lung tissues using ImageJ software (NIH, USA). At a minimum, three fields of view were obtained from each animal (n = 8 animals, 4 male and 4 female). Heat-induced epitope retrieval was conducted by heating slides to 95°C for 20 min in sodium citrate-based ER1 buffer (Leica Biosystems, Richmond, IL) before immunostaining. Immunostaining was performed using the Bond RX automated system (Leica Biosystems, Richmond, IL). Positive immunostaining was visualized using immunofluorescence (IF). Lung pathology score was calculated according to Zheng et al.63 in brief as follows: Neutrophil infiltration was evaluated by severity-based ordinal scoring: 0, within normal limits; 1, scattered PMNs sequestered in septa; 2, 1 plus solitary PMNs extravasated in airspaces; 3, plus small aggregates in vessel and airspaces. Mononuclear infiltrates were evaluated by distribution-based ordinal scoring of 200× lung fields on a Nikon Eclipse 55i light microscope: 0, none; 1, uncommon detection in less than 5% of 200× lung fields; 2, detectable in up to 33% of 200× lung fields; 3, detectable in up to 33%–66% of 200× lung fields; 4, detectable in more than 66% of 200× lung fields. Edema, hyaline membranes, necrotic cell debris, necrosis, and hemorrhage were not identified and not scored. Specimens were also assessed for inflammatory change, epithelial change, vascular change, edema, and hemorrhage. qRT-PCR Total mouse lung RNA was isolated using TRIzol reagent (Life Technologies) following the manufacturer’s protocols. RNA was reverse transcribed using the iScript cDNA Synthesis Kit (Bio-Rad). SARS-CoV-2 N gene expression was determined by quantitative TaqMan PCR (Integrated DNA Technologies) following the protocols set by the manufacturer. The Ct values were normalized by the Ct value of a housekeeping gene, GAPDH (Bio-Rad). All other genes expression was determined by SyBr Green qRT-PCR as described in our previous publication.65 Supplemental information Document S1. Figures S1–S21 and Supplemental experimental procedures Document S2. Article plus supplemental information Data and code availability The data used to support the findings of this study are available from the lead contact upon request. This paper does not report original code. Acknowledgments The work reported here is supported by the 10.13039/100000002 National Institutes of Health (1R2AI14932101, 3R21AI149321-01S1, and 1R01AI148446-01A1) and a 10.13039/100001621 Fisher Center Discovery Program grant. E.K.L. is supported by NIH training grant K12 GM123914 01A1. We thank Maggie Lowman, Morgan Craney, and Amanda J. Wong for technical support; Dr. David Hackam for consultation with respect to experimental design; the Integrated Imaging Center (IIC) at The Johns Hopkins University for use of the TEM facility; and the Johns Hopkins University Department of Chemistry Mass Spectroscopy facility for use of the MALDI-TOF instrument. Aspects of the schematics depicted in Figure 4 were created with BioRender.com. Author contributions H.J. and H.C. conceived the idea of delivering soluble ACE2 with supramolecular polymers. H.J. and H.C. guided experiments and provided insight into final interpretation of the results. C.F.A. conceived design of ACE2-docking supramolecular filaments; synthesized materials; designed and performed material characterization, docking optimization, and in vitro cell studies; and interpreted the results. Q.W. executed in vivo studies. D.S. aided design and execution of docking optimization experiments and interpretation of the results. B.S. and K.J.F. aided in execution of in vitro cell studies. E.K.J. aided in design of and executed binding affinity experiments and interpretation of the results. J.B.S. aided in design and interpretation of binding affinity results. C.-Y.C. aided execution of in vivo experiments. J.V. provided oversight of in vivo ASBL3 experiments. C.F.B. processed and analyzed pathology samples. A.P. provided viral stocks and oversight of in vitro and in vivo experiments. C.F.A. analyzed all data, and H.J. analyzed in vivo data. C.F.A., H.J., and H.C. co-wrote the manuscript. All authors discussed results and contributed to the manuscript write-up. Declaration of interests The authors declare no competing interests. Supplemental information can be found online at https://doi.org/10.1016/j.matt.2022.11.027. ==== Refs References 1 Wang C. Horby P.W. Hayden F.G. Gao G.F. A novel coronavirus outbreak of global health concern Lancet 395 2020 470 473 10.1016/S0140-6736(20)30185-9 31986257 2 Zhou P. Yang X.-L. Wang X.-G. Hu B. Zhang L. Zhang W. Si H.-R. Zhu Y. Li B. Huang C.-L. A pneumonia outbreak associated with a new coronavirus of probable bat origin Nature 579 2020 270 273 10.1038/s41586-020-2012-7 32015507 3 Tay M.Z. Poh C.M. Rénia L. MacAry P.A. Ng L.F.P. The trinity of COVID-19: immunity, inflammation and intervention Nat. Rev. Immunol. 20 2020 363 374 10.1038/s41577-020-0311-8 32346093 4 Wang Y. Zhang D. Du G. Du R. Zhao J. Jin Y. Fu S. Gao L. Cheng Z. Lu Q. Remdesivir in adults with severe COVID-19: a randomised, double-blind, placebo-controlled, multicentre trial Lancet 395 2020 1569 1578 10.1016/S0140-6736(20)31022-9 32423584 5 Williamson B.N. Feldmann F. Schwarz B. Meade-White K. Porter D.P. Schulz J. van Doremalen N. Leighton I. Yinda C.K. Pérez-Pérez L. Clinical benefit of remdesivir in rhesus macaques infected with SARS-CoV-2 Nature 585 2020 273 276 10.1038/s41586-020-2423-5 32516797 6 Hacisuleyman E. Hale C. Saito Y. Blachere N.E. Bergh M. Conlon E.G. Schaefer-Babajew D.J. DaSilva J. Muecksch F. Gaebler C. Vaccine breakthrough infections with SARS-CoV-2 variants N. Engl. J. Med. 384 2021 2212 2218 10.1056/NEJMoa2105000 33882219 7 To K.K.-W. Hung I.F.-N. Ip J.D. Chu A.W.-H. Chan W.-M. Tam A.R. Fong C.H.-Y. Yuan S. Tsoi H.-W. Ng A.C.-K. Coronavirus disease 2019 (COVID-19) Re-infection by a phylogenetically distinct severe acute respiratory syndrome coronavirus 2 strain confirmed by whole genome sequencing Clin. Infect. Dis. 73 2020 e2946 e2951 10.1093/cid/ciaa1275 8 Li Q. Wu J. Nie J. Zhang L. Hao H. Liu S. Zhao C. Zhang Q. Liu H. Nie L. The impact of mutations in SARS-CoV-2 spike on viral infectivity and antigenicity Cell 182 2020 1284 1294.e9 10.1016/j.cell.2020.07.012 32730807 9 Zhang L. Jackson C.B. Mou H. Ojha A. Peng H. Quinlan B.D. Rangarajan E.S. Pan A. Vanderheiden A. Suthar M.S. SARS-CoV-2 spike-protein D614G mutation increases virion spike density and infectivity Nat. Commun. 11 2020 6013 10.1038/s41467-020-19808-4 33243994 10 Kuba K. Imai Y. Rao S. Gao H. Guo F. Guan B. Huan Y. Yang P. Zhang Y. Deng W. A crucial role of angiotensin converting enzyme 2 (ACE2) in SARS coronavirus–induced lung injury Nat. Med. 11 2005 875 879 10.1038/nm1267 16007097 11 Lan J. Ge J. Yu J. Shan S. Zhou H. Fan S. Zhang Q. Shi X. Wang Q. Zhang L. Wang X. Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor Nature 581 2020 215 220 10.1038/s41586-020-2180-5 32225176 12 Hoffmann M. Kleine-Weber H. Schroeder S. Kruger N. Herrler T. Erichsen S. Schiergens T.S. Herrler G. Wu N.H. Nitsche A. SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor Cell 181 2020 271 280.e8 10.1016/j.cell.2020.02.052 32142651 13 Yan R. Zhang Y. Li Y. Xia L. Guo Y. Zhou Q. Structural basis for the recognition of SARS-CoV-2 by full-length human ACE2 Science 367 2020 1444 10.1126/science.abb2762 32132184 14 Zoufaly A. Poglitsch M. Aberle J.H. Hoepler W. Seitz T. Traugott M. Grieb A. Pawelka E. Laferl H. Wenisch C. Human recombinant soluble ACE2 in severe COVID-19 Lancet Respir. Med. 8 2020 1154 1158 10.1016/S2213-2600(20)30418-5 33131609 15 Yeung M.L. Teng J.L.L. Jia L. Zhang C. Huang C. Cai J.-P. Zhou R. Chan K.-H. Zhao H. Zhu L. Soluble ACE2-mediated cell entry of SARS-CoV-2 via interaction with proteins related to the renin-angiotensin system Cell 184 2021 2212 2228.e12 10.1016/j.cell.2021.02.053 33713620 16 Chan K.K. Dorosky D. Sharma P. Abbasi S.A. Dye J.M. Kranz D.M. Herbert A.S. Procko E. Engineering human ACE2 to optimize binding to the spike protein of SARS coronavirus 2 Science 369 2020 1261 10.1126/science.abc0870 32753553 17 Glasgow A. Glasgow J. Limonta D. Solomon P. Lui I. Zhang Y. Nix M.A. Rettko N.J. Zha S. Yamin R. Engineered ACE2 receptor traps potently neutralize SARS-CoV-2 Proc. Natl. Acad. Sci. USA 117 2020 28046 10.1073/pnas.2016093117 33093202 18 Monteil V. Kwon H. Prado P. Hagelkrüys A. Wimmer R.A. Stahl M. Leopoldi A. Garreta E. Hurtado del Pozo C. Prosper F. Inhibition of SARS-CoV-2 infections in engineered human tissues using clinical-grade soluble human ACE2 Cell 181 2020 905 913.e7 10.1016/j.cell.2020.04.004 32333836 19 Jia H. Pulmonary angiotensin-converting enzyme 2 (ACE2) and inflammatory lung disease Shock 46 2016 239 248 27082314 20 Jia H. Neptune E. Cui H. Targeting ACE2 for COVID-19 therapy: opportunities and challenges Am. J. Respir. Cell Mol. Biol. 64 2020 416 425 10.1165/rcmb.2020-0322PS 21 Liu P. Wysocki J. Souma T. Ye M. Ramirez V. Zhou B. Wilsbacher L.D. Quaggin S.E. Batlle D. Jin J. Novel ACE2-Fc chimeric fusion provides long-lasting hypertension control and organ protection in mouse models of systemic renin angiotensin system activation Kidney Int. 94 2018 114 125 10.1016/j.kint.2018.01.029 29691064 22 Haschke M. Schuster M. Poglitsch M. Loibner H. Salzberg M. Bruggisser M. Penninger J. Krahenbuhl S. Pharmacokinetics and pharmacodynamics of recombinant human angiotensin-converting enzyme 2 in healthy human subjects Clin. Pharmacokinet. 52 2013 783 792 10.1007/s40262-013-0072-7 23681967 23 Zhang Q. Honko A. Zhou J. Gong H. Downs S.N. Vasquez J.H. Fang R.H. Gao W. Griffiths A. Zhang L. Cellular nanosponges inhibit SARS-CoV-2 infectivity Nano Lett. 20 2020 5570 5574 10.1021/acs.nanolett.0c02278 32551679 24 Rao L. Xia S. Xu W. Tian R. Yu G. Gu C. Pan P. Meng Q.F. Cai X. Qu D. Decoy nanoparticles protect against COVID-19 by concurrently adsorbing viruses and inflammatory cytokines Proc. Natl. Acad. Sci. USA 117 2020 27141 27147 10.1073/pnas.2014352117 33024017 25 Li Z. Wang Z. Dinh P.-U.C. Zhu D. Popowski K.D. Lutz H. Hu S. Lewis M.G. Cook A. Andersen H. Cell-mimicking nanodecoys neutralize SARS-CoV-2 and mitigate lung injury in a non-human primate model of COVID-19 Nat. Nanotechnol. 16 2021 942 951 10.1038/s41565-021-00923-2 34140674 26 Yu Y.-C. Berndt P. Tirrell M. Fields G.B. Self-assembling amphiphiles for construction of protein molecular architecture J. Am. Chem. Soc. 118 1996 12515 12520 10.1021/ja9627656 27 Hartgerink J.D. Beniash E. Stupp S.I. Self-assembly and mineralization of peptide-amphiphile nanofibers Science 294 2001 1684 10.1126/science.1063187 11721046 28 Hartgerink J.D. Beniash E. Stupp S.I. Peptide-amphiphile nanofibers: a versatile scaffold for the preparation of self-assembling materials Proc. Natl. Acad. Sci. USA 99 2002 5133 10.1073/pnas.072699999 11929981 29 Zhang P. Cheetham A.G. Lin Y.-a. Cui H. Self-assembled tat nanofibers as effective drug carrier and transporter ACS Nano 7 2013 5965 5977 10.1021/nn401667z 23758167 30 Hudalla G.A. Sun T. Gasiorowski J.Z. Han H. Tian Y.F. Chong A.S. Collier J.H. Gradated assembly of multiple proteins into supramolecular nanomaterials Nat. Mater. 13 2014 829 836 10.1038/nmat3998 24930032 31 Lee S.S. Hsu E.L. Mendoza M. Ghodasra J. Nickoli M.S. Ashtekar A. Polavarapu M. Babu J. Riaz R.M. Nicolas J.D. Gel scaffolds of BMP-2-binding peptide amphiphile nanofibers for spinal arthrodesis Adv. Healthc. Mater. 4 2015 131 141 10.1002/adhm.201400129 24753455 32 Miller S.E. Yamada Y. Patel N. Suárez E. Andrews C. Tau S. Luke B.T. Cachau R.E. Schneider J.P. Electrostatically driven guanidinium interaction domains that control hydrogel-mediated protein delivery in vivo ACS Cent. Sci. 5 2019 1750 1759 10.1021/acscentsci.9b00501 31807676 33 Li Y. Lock L.L. Wang Y. Ou S.-H. Stern D. Schön A. Freire E. Xu X. Ghose S. Li Z.J. Cui H. Bioinspired supramolecular engineering of self-assembling immunofibers for high affinity binding of immunoglobulin G Biomaterials 178 2018 448 457 10.1016/j.biomaterials.2018.04.032 29706234 34 Krishnamurthy S. Wohlford-Lenane C. Kandimalla S. Sartre G. Meyerholz D.K. Théberge V. Hallée S. Duperré A.-M. Del’Guidice T. Lepetit-Stoffaes J.-P. Engineered amphiphilic peptides enable delivery of proteins and CRISPR-associated nucleases to airway epithelia Nat. Commun. 10 2019 4906 10.1038/s41467-019-12922-y 31659165 35 Si Y. Tian Q. Zhao F. Kelly S.H. Shores L.S. Camacho D.F. Sperling A.I. Andrade M.S. Collier J.H. Chong A.S. Adjuvant-free nanofiber vaccine induces in situ lung dendritic cell activation and TH17 responses Sci. Adv. 6 2020 eaba0995 10.1126/sciadv.aba0995 32821819 36 Anderson C.F. Chakroun R.W. Su H. Mitrut R.E. Cui H. Interface-enrichment-induced instability and drug-loading-enhanced stability in inhalable delivery of supramolecular filaments ACS Nano 13 2019 12957 12968 10.1021/acsnano.9b05556 31651153 37 Geng Y. Dalhaimer P. Cai S. Tsai R. Tewari M. Minko T. Discher D.E. Shape effects of filaments versus spherical particles in flow and drug delivery Nat. Nanotechnol. 2 2007 249 255 10.1038/nnano.2007.70 18654271 38 Edwards D.A. Hanes J. Caponetti G. Hrkach J. Ben-Jebria A. Eskew M.L. Mintzes J. Deaver D. Lotan N. Langer R. Large porous particles for pulmonary drug delivery Science 276 1997 1868 10.1126/science.276.5320.1868 9188534 39 Lai S.K. Hanlon D.E. Harrold S. Man S.T. Wang Y.-Y. Cone R. Hanes J. Rapid transport of large polymeric nanoparticles in fresh undiluted human mucus Proc. Natl. Acad. Sci. USA 104 2007 1482 10.1073/pnas.0608611104 17244708 40 Lock L.L. Reyes C.D. Zhang P. Cui H. Tuning cellular uptake of molecular probes by rational design of their assembly into supramolecular nanoprobes J. Am. Chem. Soc. 138 2016 3533 3540 10.1021/jacs.6b00073 26890853 41 Chung E.J. Mlinar L.B. Sugimoto M.J. Nord K. Roman B.B. Tirrell M. In vivo biodistribution and clearance of peptide amphiphile micelles Nanomed. Nanotechnol. Biol. Med. 11 2015 479 487 10.1016/j.nano.2014.08.006 42 Champion J.A. Mitragotri S. Role of target geometry in phagocytosis Proc. Natl. Acad. Sci. USA 103 2006 4930 4934 10.1073/pnas.0600997103 16549762 43 Towler P. Staker B. Prasad S.G. Menon S. Tang J. Parsons T. Ryan D. Fisher M. Williams D. Dales N.A. ACE2 X-ray structures reveal a large hinge-bending motion important for inhibitor binding and catalysis J. Biol. Chem. 279 2004 17996 18007 10.1074/jbc.M311191200 14754895 44 Li Y. Lock L.L. Mills J. Ou B.S. Morrow M. Stern D. Wang H. Anderson C.F. Xu X. Ghose S. Selective capture and recovery of monoclonal antibodies by self-assembling supramolecular polymers of high affinity for protein binding Nano Lett. 20 2020 6957 6965 10.1021/acs.nanolett.0c01297 32852220 45 Huang L. Sexton D.J. Skogerson K. Devlin M. Smith R. Sanyal I. Parry T. Kent R. Enright J. Wu Q.L. Novel peptide inhibitors of angiotensin-converting enzyme 2 J. Biol. Chem. 278 2003 15532 15540 10.1074/jbc.M212934200 12606557 46 Behanna H.A. Donners J.J.J.M. Gordon A.C. Stupp S.I. Coassembly of amphiphiles with opposite peptide polarities into nanofibers J. Am. Chem. Soc. 127 2005 1193 1200 10.1021/ja044863u 15669858 47 Amin M. Sorour M.K. Kasry A. Comparing the binding interactions in the receptor binding domains of SARS-CoV-2 and SARS-CoV J. Phys. Chem. Lett. 11 2020 4897 4900 10.1021/acs.jpclett.0c01064 32478523 48 Zhang S. Greenfield M.A. Mata A. Palmer L.C. Bitton R. Mantei J.R. Aparicio C. de la Cruz M.O. Stupp S.I. A self-assembly pathway to aligned monodomain gels Nat. Mater. 9 2010 594 601 10.1038/nmat2778 20543836 49 Adjei A. Gupta P. Pulmonary delivery of therapeutic peptides and proteins J. Contr. Release 29 1994 361 373 10.1016/0168-3659(94)90081-7 50 Hertel S.P. Winter G. Friess W. Protein stability in pulmonary drug delivery via nebulization Adv. Drug Deliv. Rev. 93 2015 79 94 10.1016/j.addr.2014.10.003 25312674 51 Berndt P. Fields G.B. Tirrell M. Synthetic lipidation of peptides and amino acids: monolayer structure and properties J. Am. Chem. Soc. 117 1995 9515 9522 52 Choi H.S. Ashitate Y. Lee J.H. Kim S.H. Matsui A. Insin N. Bawendi M.G. Semmler-Behnke M. Frangioni J.V. Tsuda A. Rapid translocation of nanoparticles from the lung airspaces to the body Nat. Biotechnol. 28 2010 1300 1303 10.1038/nbt.1696 21057497 53 Anderson C.F. Chakroun R.W. Grimmett M.E. Domalewski C.J. Wang F. Cui H. Collagen-binding peptide-enabled supramolecular hydrogel design for improved organ adhesion and sprayable therapeutic delivery Nano Lett. 22 2022 4182 4191 10.1021/acs.nanolett.2c00967 35522052 54 Liu Q. Guan J. Qin L. Zhang X. Mao S. Physicochemical properties affecting the fate of nanoparticles in pulmonary drug delivery Drug Discov. Today 25 2020 150 159 10.1016/j.drudis.2019.09.023 31600580 55 Geiser M. Kreyling W.G. Deposition and biokinetics of inhaled nanoparticles Part. Fibre Toxicol. 7 2010 2 10.1186/1743-8977-7-2 20205860 56 Pedersen S.F. Ho Y.-C. SARS-CoV-2: a storm is raging J. Clin. Investig. 130 2020 2202 2205 10.1172/JCI137647 32217834 57 Antinori S. Bonazzetti C. Gubertini G. Capetti A. Pagani C. Morena V. Rimoldi S. Galimberti L. Sarzi-Puttini P. Ridolfo A.L. Tocilizumab for cytokine storm syndrome in COVID-19 pneumonia: an increased risk for candidemia? Autoimmun. Rev. 19 2020 102564 10.1016/j.autrev.2020.102564 32376396 58 Zhang X. Tan Y. Ling Y. Lu G. Liu F. Yi Z. Jia X. Wu M. Shi B. Xu S. Viral and host factors related to the clinical outcome of COVID-19 Nature 583 2020 437 440 10.1038/s41586-020-2355-0 32434211 59 Lagunas-Rangel F.A. Chávez-Valencia V. High IL-6/IFN-γ ratio could be associated with severe disease in COVID-19 patients J. Med. Virol. 92 2020 1789 1790 10.1002/jmv.25900 32297995 60 Abers M.S. Delmonte O.M. Ricotta E.E. Fintzi J. Fink D.L. de Jesus A.A.A. Zarember K.A. Alehashemi S. Oikonomou V. Desai J.V. An immune-based biomarker signature is associated with mortality in COVID-19 patients JCI Insight 6 2021 e144455 10.1172/jci.insight.144455 33232303 61 Ghazavi A. Ganji A. Keshavarzian N. Rabiemajd S. Mosayebi G. Cytokine profile and disease severity in patients with COVID-19 Cytokine 137 2021 155323 10.1016/j.cyto.2020.155323 33045526 62 Kim M.-H. Salloum S. Wang J.Y. Wong L.P. Regan J. Lefteri K. Manickas-Hill Z. Gao C. Li J.Z. Sadreyev R.I. Type I, II, and III interferon signatures correspond to coronavirus disease 2019 severity J. Infect. Dis. 224 2021 777 782 10.1093/infdis/jiab288 34467988 63 Zheng J. Wong L.-Y.R. Li K. Verma A.K. Ortiz M.E. Wohlford-Lenane C. Leidinger M.R. Knudson C.M. Meyerholz D.K. McCray P.B. Perlman S. COVID-19 treatments and pathogenesis including anosmia in K18-hACE2 mice Nature 589 2021 603 607 10.1038/s41586-020-2943-z 33166988 64 Johnson M.C. Lyddon T.D. Suarez R. Salcedo B. LePique M. Graham M. Ricana C. Robinson C. Ritter D.G. Simon V. Optimized pseudotyping conditions for the SARS-COV-2 spike glycoprotein J. Virol. 94 2020 10.1128/JVI.01062-20 e01062-e01020 65 Sodhi C.P. Nguyen J. Yamaguchi Y. Werts A.D. Lu P. Ladd M.R. Fulton W.B. Kovler M.L. Wang S. Prindle T. A dynamic variation of pulmonary ACE2 is required to modulate neutrophilic inflammation in response to Pseudomonas aeruginosa lung infection in mice J. Immunol. 203 2019 3000 10.4049/jimmunol.1900579 31645418
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==== Front Anal Chem Anal Chem ac ancham Analytical Chemistry 0003-2700 1520-6882 American Chemical Society 36475600 10.1021/acs.analchem.2c03846 Article Long-Range SERS Detection of the SARS-CoV-2 Antigen on a Well-Ordered Gold Hexagonal Nanoplate Film https://orcid.org/0000-0003-2366-5390 Wu Ping *† https://orcid.org/0000-0002-3899-0105 Luo Xiaojun †‡ Xu Yihong † Zhu Jingtian † Jia Wenyu † Fang Ningning † https://orcid.org/0000-0002-3578-2415 Cai Chenxin *† https://orcid.org/0000-0002-8201-1285 Zhu Jun-Jie *§∥ † Jiangsu Key Laboratory of New Power Batteries, Jiangsu Collaborative Innovation Center of Biomedical Functional Materials, College of Chemistry and Materials Science, Nanjing Normal University, Nanjing210023, P. R. China ‡ School of Science, Xihua University, Chengdu610039, P. R. China § State Key Laboratory of Analytical for Life Science, School of Chemistry & Chemical Engineering, Nanjing University, Nanjing210023, P. R. China ∥ Shenzhen Research Institute of Nanjing University, Shenzhen518000, China * Email: [email protected]. * Email: [email protected]. * Email: [email protected]. 07 12 2022 acs.analchem.2c0384601 09 2022 01 11 2022 © 2022 American Chemical Society 2022 American Chemical Society This article is made available via the PMC Open Access Subset for unrestricted RESEARCH re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. The development of an effective method for identifying severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) via direct viral protein detection is significant but challenging in combatting the COVID-19 epidemic. As a promising approach for direct detection, viral protein detection using surface-enhanced Raman scattering (SERS) is limited by the larger viral protein size compared to the effective electromagnetic field (E-field) range because only the analyte remaining within the E-field can achieve high detection sensitivity. In this study, we designed and fabricated a novel long-range SERS (LR-SERS) substrate with an Au nanoplate film/MgF2/Au mirror/glass configuration to boost the LR-SERS resulting from the extended E-field. On applying the LR-SERS to detect the SARS-CoV-2 spike protein (S protein), reagent-free detection achieved a low detection limit of 9.8 × 10–11 g mL–1 and clear discrimination from the SARS-CoV S protein. The developed technique also allows testing of the S protein in saliva with 98% sensitivity and 100% specificity. National Natural Science Foundation of China 10.13039/501100001809 21834004 Guangdong Basic and Applied Basic Research Foundation NA 2020B1515120026 Priority Academic Program Development of Jiangsu Higher Education Institutions 10.13039/501100012246 NA document-id-old-9ac2c03846 document-id-new-14ac2c03846 ccc-price This article is made available via the ACS COVID-19 subset for unrestricted RESEARCH re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. ==== Body pmcIntroduction The establishment of highly efficient, accurate, and cost-effective detection methods for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the causative agent of COVID-19, is crucial for combatting the current pandemic. At present, the most common method of COVID-19 diagnosis is detection of the viral RNA using quantitative reverse transcription-polymerase chain reaction; however, this technique is costly and time- and labor-consuming.1 Detection of antibodies through serological testing can be performed quickly; however, this technique does not function well in early screening and thus limits the prevention of disease spread during an outbreak because of the delay in antibody generation in SARS-CoV-2-infected individuals.2,3 Instead, testing for viral antigens is an appropriate alternative, which has already been available in the diagnosis of respiratory viruses such as influenza, respiratory syncytial viruses, and SARS-CoV-1 and has even been urgently launched for SARS-CoV-2.4,5 Antigen detection is more rapid, simpler, and less expensive than RNA detection but is often limited by its moderate detection sensitivity.6 For example, the detection sensitivity of a rapid test (COVID-19 Ag Respi-Strip) from Coris BioConcept is ∼60% and reaches only ∼80% in Sofia SARS antigen fluorescent immunoassay (FIA).7,8 The relatively low sensitivity of these antigen tests compared to the RNA test is partly attributed to the limited quality of biomaterials employed for their development. Therefore, the development of reagent-free approaches for virus antigen detection can eliminate the negative effects of the quality of the reagents involved in the detection, reduce the cost, and simplify the operational process. Label-free surface-enhanced Raman scattering (SERS) detection is a good candidate for a reagent-free detection approach because of its capability to provide fingerprint information with ultrahigh sensitivity down to the single-molecule level.9,10 However, SERS is often considered a near-field phenomenon.11,12 Indeed, only the analytes that are present at or very close to the SERS-enhanced substrate surface (within 5 nm13) can respond sensitively because the enhanced E-field dominantly contributing to SERS enhancement decays rapidly with increasing distance from the substrate surface. This characteristic limits the label-free SERS detection of viral antigens because of their large size and steric hindrance. For example, the protruding outer spike (S) protein (one of the four structural proteins of SARS-CoV-2) is becoming a major detection target in SARS-CoV-2 assays because of its antigenicity. Nevertheless, owing to the larger size of the S protein (∼7 nm in width and 22 nm in length14) than the effective E-field range provided by conventional SERS-active substrates (∼5 nm13), the region buried in the interior of the S protein or domains without direct contact with the SERS-active substrates cannot respond sensitively to SERS sensing. Therefore, the S protein SERS spectra hardly contain incomplete molecular information of the whole protein and may even show different profiles resulting from the various orientations of the S protein onto the SERS substrate. This fact has prompted researchers to look for a SERS-active substrate with an extensively enhanced E-field that can be used for boosting Raman signals at longer distances beyond the substrate surface to cover the full region of the S protein. An effective way to produce the E-field associated with the long-range SERS (LR-SERS) effect is to excite long-range surface plasmon polaritons (LRSPPs). LRSPPs are electromagnetic wave modes propagating along a thin metal film sandwiched between two dielectrics with similar refractive indices, which display 1 order of magnitude slower attenuation of the E-field than do conventional surface plasmons (SPs).15,16 Accordingly, LRSPPs can support increased intensity and a deeper penetration depth of the E-field compared to those typically afforded by conventional SPs. However, since the obversion of LRSPPs in the 1980s,17 much less attention has been devoted toward LRSPP-based SERS sensing. Only recently have a few LRSPP applications been reported as promising strategies to increase the probing distance of SERS: Xu et al. constructed prism-type Kretschmann configurations to achieve LR-SERS measurement.18 Yu et al. excited LRSPPs using Au nanohole arrays (NHAs) as grating couplers instead of prism couplers.13,19 Moreover, in our previous work, we used a 20 nm-thick film containing triangle-shaped NHAs to excite LRSPPs in a symmetric dielectric environment.20 However, despite the achievements in LR-SERS performance, the fabrication methods of NHAs relying on top-down approaches, including lithography, the pattering technique, and thermal evaporation, are limited in precise control of the nanostructured geometries, especially for sharp edges, vertices, nanogaps <5 nm, and atomic-scale surface roughness,21,22 making rational manipulation of the E-field coupling challenging. With these facts in mind, we used a self-assembly approach to fabricate a large-area grating-like two-dimensional (2D) plasmonic film. The state-of-the-art of nanofabrication allows accurate control over the shape, size, surface, and nanogaps of the nanoparticle (NP),23 which results in better plasmonic tunability than that afforded by top-down approaches. In this study, a thin Au film composed of well-ordered hexagonal Au nanoplates (Au NPLs) was self-assembled and bound by symmetric dielectrics. Both finite-difference time-domain (FDTD) simulations and SERS measurements demonstrated the LR-SERS effect achieved on this Au film. Subsequently, a highly sensitive and rapid reagent-free SERS detection method for S protein was developed using the as-synthesized Au NPL film as a sensing platform, which can distinguish S protein-infected saliva from healthy human saliva combined with principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). This work not only explores a self-assembled approach to develop a novel SERS substrate with extended probing distance but also presents a promising reagent-free approach to detect S protein with high sensitivity and accuracy. Experimental Section Preparation of the Hexagonal Au NPLs First, triangular plates were prepared by a three-step seed-mediated growth method. Briefly, gold NP seeds with an average diameter of 5 nm were obtained by mixing vigorously with deionized (DI) water (36 mL), trisodium citrate (10 mM, 1 mL), HAuCl4·3H2O (10 mM, 1 mL), and freshly prepared NaBH4 (0.1 M, 1 mL) for 2 min with subsequent aging for 2–6 h. Three growth solutions were prepared for the seed-mediated growth step: growth solutions 1 and 2, which were identical, comprised hexadecyltrimethylammonium bromide (CTAB, 0.05 M, 9 mL), HAuCl4 (0.01 M, 0.25 mL), NaOH (0.1 M, 0.05 mL), KI (0.01 M, 0.05 mL), and ascorbic acid (0.1 M, 0.05 mL). On the other hand, growth solution 3 contained CTAB (0.05 M, 90 mL), HAuCl4 (0.01 M, 2.5 mL), NaOH (0.1 M, 0.5 mL), KI (0.01 M, 0.5 mL), and ascorbic acid (0.1 M, 0.5 mL). The formation of the triangular plates was initiated by adding 1 mL of seed solution to growth solution 1 with mild shaking. The mixed solution was then added to growth solution 2. After gentle shaking for 5 s, the mixture was added to growth solution 3 and then left undisturbed at 30 °C for 24 h, allowing the triangular plates to precipitate at the bottom of the reaction vessel. The supernatant was removed and the purified triangular plates were redispersed in DI water overnight to allow corner rounding of the sharp corners of the triangular plates. Finally, 0.5 mL of circular Au plate solution (extinction value pre-adjusted to 3.0 at the major plasmon peak) was added into the overgrowth solution (25 μL of 0.01 M HAuCl4 with 0.25 mL of 0.1 M CTAB, 12.5 μL of 0.1 M ascorbic acid, and DI water) at 30 °C for 10 h to obtain hexagonal Au NPLs. Fabrication of the SERS Substrates The as-fabricated 6 mL hexagonal Au NPL colloid was added to a glass container with subsequent addition of 2 mL of hexane to form a water/hexane interface. Next, 1.6 mL of ethanol was added dropwise at 0.1 mL/min. Pervious works demonstrate that gold nanocrystals spontaneously form a monolayer at the water/oil interface if the surface charge of the nanocrystals is gradually reduced. The addition of ethanol (1–2 mL) can decrease the surface charge of Au NPLs.24 To obtain better formation of a monolayer of Au NPLs, the addition of ethanol was optimized because the stacking and aggregation of Au NPLs could occur when ethanol was added excessively and rapidly. Herein, the optimal injection of ethanol was tested to be 1.6 mL at the rate of 0.1 mL/min. Upon the evaporation of hexane, a large-area film of close-packed Au NPLs appeared floating on the water surface. For the preparation of the SERS-active substrate, the Au NPL film was transferred onto two different solid supporting substrates, namely, a glass substrate and MgF2/Au mirror/glass multilayer (detailed preparation process in the following). Taking the glass substrate as an example, the glass was cleaned by ultra-sonication in soapy DI water, DI water, acetone, and isopropyl alcohol for 20 min each at 40 °C. The clean glass was then carefully slid beneath the Au NPL film, which was then slowly lifted from the water. The Au NPL film was thus transferred onto the glass to form an Au NPL film/glass substrate. Similarly, the Au NPL film was transferred to the MgF2/Au mirror/glass multilayer using the same method, but with MgF2/Au mirror/glass instead of glass. Preparation of the MgF2/Au Mirror/Glass Multilayer The glass substrate (∼1 cm2) was cleaned by soapy DI water, DI water, acetone, and isopropanol each for 20 min at 40 °C by means of ultrasonic cleaning and then put into a UV–O3 cleaner for 20 min. A drop of 50 μL of adhesion promoter 3-mercaptopropyltrimethoxysilane was dropped onto the cleaned glass substrate in a vacuum desiccator for 2 h. Next, a 100 nm Au mirror was thermally evaporated onto the pre-treated glass substrate. Finally, a 200 nm MgF2 layer was thermally evaporated onto the Au mirror to form a MgF2/Au mirror/glass multilayer as the supporting substrate. The thicknesses of the Au mirror and MgF2 layer were controlled by fixing at a deposition rate of 0.02 nm/s under a background pressure of 2 × 10–6 mbar. SERS Measurements SERS measurements were carried out using a Labram HR 800 microspectrometer (Jobin Yvon, France). A 785 nm laser excitation coupled with a 63× water objective (NA = 1) was used. The SERS spectra were collected with a spectral resolution of 3 cm–1 and grating of 600 grooves/mm in the range of 400–1800 cm–1. For SERS spectra of methylene blue (MB)-labeled DNA, an integration time of 3 s and accumulation of 3 were used. For SERS spectra of the S protein, an integration time of 10 s and accumulation of 10 were used. All of the SERS spectra were acquired in aqueous environment. A low-power laser (0.5 mW) was applied to prevent the evaporation of the solution under irradiation. All spectra were baseline corrected and smoothed (Savitzky–Golay smoothing, standard values: degree 2) using LabSpec 5 software. For the mapping modality, a spacing of 2 μm and an integration time of 3 s was used. Each map was composed of 676 spectra over an area of 50 × 50 μm2. SERS results were compared with the results obtained from enzyme linked immunosorbent assay (ELISA) assay, which was performed under guidance in SARS-CoV-2 (2019-nCoV) Spike ELISA kit (Sino Biological, Inc., China). Results and Discussion Fabrication of LR-SERS Substrate The preparation of the LR-SERS substrate started with the synthesis of Au NPL colloids using a seed-mediated growth method.25,26 Au NPLs were selected as building blocks because of their ease of self-assembly into hexagonal two-dimensional assemblies and high SERS activity. Au NPLs with an average lateral size of 155 ± 5 nm and a thickness of ∼20 nm were obtained in a high yield of ∼90% (Figure S1), and well-defined lattice fringes with 0.235 nm spacing were observed parallel to one of the Au NPL sides (Figure S2A). A hexagonal symmetry of the diffraction spots indexed to {422}, {220}, and forbidden 1/3{422} reflections were observed in the corresponding selected area electron diffraction pattern (Figure S2B). Moreover, the ratio of the diffraction intensities for the {111} and {200} Au NPL planes was calculated from the X-ray diffraction pattern analysis (Figure S2C) as ∼17. These results show that the as-prepared Au NPL is a single crystal with a preferential (111) orientation. The as-synthesized Au NPLs can be assembled into a smooth Au film in which Au NPLs stand vertically and are closely packed via a bottom-up approach. Such a film displays a thickness of ∼20 nm that meets the demand of excitation LRSPPs because the LRSPPs launch and propagate along a thin metal film with a thickness of <100 nm.17,27 Then, a continuous Au film composed of ordered Au NPLs was self-assembled, and subsequently transferred onto a solid substrate. Typically, hexane was added into the as-prepared Au NPLs colloid solution. As a result, an immiscible water/hexane interface was formed after standing for a few minutes (Figure 1A,A′). Then, a 1.6 mL of ethanol was dropped, leading to an entrapment of Au NPLs at the water/hexane interface (Figure 1B). At this time, the red brown colloid solution gradually turned colorless. The Au NPLs were spontaneously assembled and compressed into close-packed monolayer film during the evaporation of hexane via the interfacial tension at the hexane–water interface.28 The addition amount and rate of ethanol are important for the formation of Au NPLs monolayer (please refer to Experimental Section).The floating mirror-like metallic sheen resulted from optical coupling of Au NPLs appeared (Figure 1B′).29,30 Finally, this film was carefully transferred onto the prepared supporting substrates (glass or MgF2/Au mirror/glass multilayers) by placing the supporting substrate under the floating film at a very small angel and gently lifting up (Figure 1C). Upon the Langmuir–Blodgett transferring technique, the surface of the supporting substrate was visibly intact and uniform with metallic-color across the entire substrate (Figure 1C′). Figure 1 Schematic illustration of fabricating and transferring Au NPL film (A–C) and corresponding optical images (A′–C′): (A,A′) dropwise addition of ethanol into the Au NPLs suspension. (B,B′) Self-assembly of Au NPLs at the water/hexane interface during hexane evaporating. (C,C′) Transferring Au NPL monolayer film onto solid supporting substrate. (D,E) Scanning electron microscopy (SEM) images of the Au NPL film supported on silicon. The red dashed line indicates the real space rhombic lattice vectors superimposed on Au NPLs superlattice. ax and ay are the primitive lattice vectors with magnitudes of 161 and 279 nm, respectively. (F) UV–vis spectrum of colloid Au NPLs (a) the Au NPL film supported on glass (b). (G) Charge distributions (left) and corresponding E-field distribution profiles (right) for a single Au NPL at the wavelength of 620 nm (top) and 800 nm (bottom), respectively. The scale bar represents (Emax/E0)2 on a log scale. (H) Diffraction patterns obtained from fast Fourier transform of selected area in SEM image from figure (D). Figure 1D shows a uniform film with a well-ordered and close-packed Au NPL monolayer. Subsequent UV–vis absorption analysis revealed broader red-shifted absorption peaks compared to those of the colloidal Au NPLs (Figure 1F). For the colloid Au NPLs, the FDTD-simulated peaks at 620 and 800 nm arise from the in-plane quadrupolar and dipolar plasmon resonance modes of the Au NPL, respectively. A strong local E-field was confined at the vertices and side edges of the Au NPL (Figure 1G). These regions bring high refractive index sensitivities for the Au NPLs, making it feasible to tailor the plasmonic characteristics of the Au NPL film when the dielectric environment is changed. Upon self-assembly, the in-plane quadrupolar band red-shifted from 620 to 750 nm, and the dipolar band red-shifted from 800 to 915 nm. These results indicated the successful self-assembly of the Au NPLs into close-packed assemblies. The Au NPLs were hexagonally close-packed (Figure 1E), enabling the assembled Au NPLs to act as plasmonic crystals. This is evident in Figure 1H, which shows the diffraction patterns for the reciprocal space superlattice through the fast Fourier transform analysis, indicating the formation of a hexagonal close-packed 2D NP lattice.31 Therefore, the mismatched momentum between the SP polaritons (SPPs) and free-space light can be bridged by Bragg vectors provided by the rhombic lattice in the hexagonal lattice (Figure S3), resulting in the excitation of the SPPs onto the Au NPL film. More interestingly, the excited SPPs can be further endowed with a long-range feature in a symmetrical dielectric environment, thus extending the E-field. Demonstration of LR-SERS Performance To demonstrate the excitation of LRSPPs on Au NPL film, we explored FDTD simulations. Initially, we simulated the reflected property of Au NPL film (modeled as Au NPLs array in simulation) and compared with that of uniform Au film. As depicted in Figure 2A(a,b), the reflectance spectrum of Au NPLs array on a glass substrate (namely C-SERS substrate) is evident to have the similar profile with that of uniform 20 nm-thick Au film on glass, which gives the Au NPLs assemblies behavior of continuous film.32,33 A reflection peak at ∼500 nm ascribed to an interband transition of gold exhibits. This peak is accounted for the golden color of continuous and bulk gold,31 indicative of the film-like characteristic of the Au NPLs assemblies. It is worth noting that Au NPLs array has extra three resonance modes more than the continuous Au film. The dips in the reflectance spectrum are correspond to the peaks of the extinction spectrum in curve b of Figure 1F. A pronounced dip resonance at 320 nm (noted as mode I) has a very narrow full width at half-maximum (FWHM, 1–2 nm). In general, lattice plasmonic resonance (LPR) generated by coupling between the localized SP resonance (LSPR) of individual NPs and diffracted wave propagated along the array is featured with a narrow FWHM.34 Moreover, using Bragg’s law (i.e., λ = 2a sin θ, where θ = 90° for backscattering collection),35 wavelength of LPR was predicted to be 322 nm when the primitive lattice vectors ax is 161 nm, consistent with the simulated result (320 nm) closely. Hence, mode I was identified as LPR. According to their propagation features in Figures S4 and S5, the dips at 766 (mode II)/920 nm (mode III) show obvious plasmonic gap modes, which were generated via near-field coupling of adjacent Au NPLs. These gap modes at Au NPL film resemble standing waves where the EM field is localized at the interstitial holes in our tightly packed nanocrystal assembly. Figure 2 (A) Reflectance spectra of the Au film on glass (a), C-SERS (b), and LR-SERS (c) substrates. (B) Schematic of the structure of the LR-SERS substrate. (C) The z component of the E-field distribution (Ez) of the LR-SERS substrate at wavelengths of (a) 320, (b) 756, (c) 910, and (d) 695 nm, respectively; the color bar represents (Ez/E0). The arrow represents decay depth of each mode. (D) Dependence of the normalized E-field intensity on penetration depth (Lp) into water. The red and green curves represent the intensity at (a) 320, (b) 756, (c) 910, and (d) 695 nm for the LR-SERS and C-SERS substrates, respectively. The color backgrounds (purple) in D are used to highlight Lp where the Ez amplitude decreases to 1/e of its initial value. We next modeled an LR-SERS substrate with an Au NPL array/MgF2/Au mirror/glass configuration (Figure 2B). Because long-range SP resonance (LRSPR) are only formed by coupling of the SPs propagated along the opposite interfaces of the thin metal film bound by two dielectrics with matched refractive indices,36 we inserted a MgF2 layer, with a refractive index (n = 1.3818−20) comparable to that of water (n = 1.33), under the Au NPL array, leading to the formation of insulator–metal–insulator (IMI) structure. To enhance the coupling efficiency, we further embedded a flat 100 nm-thick Au mirror between the MgF2 layer and glass to construct a metal–insulator–metal (MIM) configuration comprising a Fabry–Pérot cavity between the MgF2 layer and Au mirror.37 We observed that a new resonance mode at 695 nm (mode IV) appeared in the spectrum. However, the position of the modes I, II, and III nearly is unchanged compared to those of the C-SERS substrate (Figure 2A). These invariant changes are inherent in the structure of the Au NPL array. After carefully investigating their Ez-field in Figure 2C(d), we speculated mode IV arose from the hybridization of Fabry–Pérot cavity mode resulted from MIM structure with SPR mode resulted from IMI structure. To confirm the Fabry–Pérot cavity mode, we modeled an Au NPL array/MgF2/glass multilayer by removing the Au mirror. As depicted in Figure S6, we did not observe this resonant mode when the nanocavity disappeared. Thus, mode IV was identified to be responsible to the cavity mode arising from SPP hybridization occurring on either side of the MgF2 layer. To confirm LRSPR mode, we changed the refractive index of the insulator and formed an asymmetrical dielectric environment. We found there was a wavelength shift and intensity change in mode IV and there was no shift in other gap modes (Figure S7A). This comparison indicated the sensitivity of mode IV to the dielectric medium. The effect of the MgF2 layer thickness was also investigated. As depicted in Figure S8, the position of the lattice and gap modes (mode I, II, and III) are nearly unchanged when varying the thickness of MgF2 in the range of 0–400 nm. In contrast, the resonance positions of mode IV are MgF2-thickness dependent. Its (Emax/E0)2 at the Au–water interfaces of the top Au NPL array reach a maximum of 1060 when MgF2-thickness is 200 nm. Thus, we optimized the thickness of MgF2 to be 200 nm. In conclusion, this hybridization mode is highly sensitive to the thickness and refractive index of the insulator materials, which is consistent with the previous reported characteristics of Fabry–Pérot cavity mode and LRSPR mode.38,39 Finally, to test LRSPP excitation, we described the z components of the E-field distributions for all the mentioned modes of the LR- and C-SERS substrates (Figures 2C and S5). Both substrates exhibited propagating SPPs along the opposite sides of the Au NPL array and well-confined localized SPs (LSPs) within the interstitial spaces. Among these two types of SPs, the E-field of the E-field SPPs was much weaker but more extended in the z-direction than that of the LSPs. We observed a distinct feature in mode IV of the LR-SERS substrate, whereby its propagating wavelength (distance measured from a point on one wave to the equivalent part of the next wave) is two-fold larger than those for the other three. Interestingly, for mode IV, the decay of the E-field intensity in the z-direction above the Au NPL array is slower than those of the other three modes. Figure 2D shows that the distances from the maximum E-field intensity (Emax/E0)2 of each mode at which the amplitude decreases by a factor of 1/e (Lp) for modes I, II, and III are ∼19, 35, and 19 nm, respectively. These values are identical for both the LR- and C-SERS substrates because these modes are related to the intrinsic structure of the Au NPL array. For mode IV, the Lp is ∼70 nm, which is 3.7-, 2.0-, and 3.7-fold deeper than those of modes I, II, and III, respectively. These results clearly reveal that mode IV in the LR-SERS substrate affords the most extended E-field and slowest E-field intensity decay. We also evaluated the Lp for mode IV in other MIM configurations (Figure S7B) where the MgF2 layer was substituted by other dielectrics with refractive indices of 1.2 or 1.46, which reduced its value to 38 and 41, respectively. The Lp in the asymmetrical dielectrics was also less than that observed with MgF2. These results indicate that LRSPPs are associated with an extended E-field launched at the LR-SERS substrate. We also simulated the effect of different thicknesses of Au NPLs film on the LR-SERS performance via FDTD simulation. In Figure S9, as the film thickness increased to 10, 20, 50, and 100 nm, enhancement factor (EF) at 0 nm above the film decreased to 2.51 × 1010, 1.26 × 109, 1.26 × 108, to 9.55 × 106, showing SERS enhancement of Au NPLs is highly sensitive to their thickness. At distance of 10 nm above the film, EF decreased to 1.26 × 106, 1.59 × 105, 2.51 × 103, to 13.5 as the thickness of Au NPLs increased from 10 to 100 nm. For the 100 nm-thickness film, EF was decreased substantially to 13.5, which dropped 4 and 5 orders of magnitude relative to that obtained with 10 and 20 nm films, respectively, indicating the vanishing of the LR-SERS effect. These comparisons also imply the achievement of LR-SERS effect on thin Au NPLs film because that LRSPR can only excite at the metal film thinner than 100 nm.17,27 Following the FDTD simulations, we proceeded to conduct proof-of-concept studies to verify the LR-SERS effect of the LR-SERS substrate using dye-labeled rigid variable-length double-stranded DNAs (dsDNAs) as rulers (Figure 3A). DsDNA is known to be rigid up to 50 nm (∼150 bps) persistence length and we used 6-mercapto-1-hexanol blocking to ensure the dsDNA remained straight.40 Moreover, to avoid the bending of dsDNA, the adsorption amount of dsDNA was controlled to be monolayer via incubating the LR-SERS substrate in ssDNA solution in excess (please refer to Supporting Information). This is because that the more the DNA molecule bonds to the surface, the lesser is the probability of bending.41 Thus, the separation distance between the dye (MB was used) and the substrate can be ranged from 4.4 to 25.2 nm (Table S1). The details, including the assembly of the dsDNA on the SERS substrate and evaluation of the separation distance between the labeled MB dye and the top surface of the substrate, are provided in the Supporting Information. Figure 3 (A) Illustration of the SERS rulers. (B) SERS spectra of 1 nM MB-labeled dsDNA with varied chain lengths collected on the LR-SERS substrate. (C) Comparison of the decay of the calculated log (EF) as a function of the separation distance between MB and the surface of the SERS substrate; the error bars show the standard deviation determined from five independent assays. (D,E) Respective SERS mappings of 1 nM MB-dsDNA (5 bps) based on the intensities of the peak at 1620 cm–1 from 676 spectra of LR-SERS and C-SERS substrates (50 × 50 μm2, laser spot 2 μm2, and step size 2 μm). Figure 3B shows how the SERS intensities of the MB dye vary with increasing separation distance. All the measurements were recorded in a water environment to ensure symmetric and moderate dielectric environment and avoid modification of the optical properties of the self-assembled Au NPL array in extreme pH or ionic value. Although the SERS intensities gradually decreased when MB moved farther away from the LR-SERS substrate surface, the SERS signal remained distinct for the MB-labeled at the terminal of 70 mer-dsDNA (separation distance of 25.2 nm). This performance far exceeds that provided by traditional SERS substrates (∼5 nm). To ensure that the SERS signal originates from the MB dye rather than the DNA, we also recorded the SERS spectrum of 1 nM free MB dye on the LR-SERS substrate. As shown in 0 nm in Figure 3B, free MB displays the same SERS profile as that of the MB-modified dsDNA because the signal of the MB dye far outweighs that of the DNA. Therefore, the characteristic Raman peaks shown in Figure 3B were assigned to MB, including peaks at 450, 770, 1175, 1375, and 1620 cm–1 for C–N–C skeletal deformation, C–H in-plane bending, C–H out-of-plane bending, C–N symmetric stretching, and C–C ring stretching, respectively.42,43 The strongest intensity, at 1620 cm–1, was selected to scale the EF dependence of the LR-SERS substrate on the separation distance. Figure 3C shows that the EF values are distance-dependent: 2.5 × 109, 7.9 × 107, 2.0 × 107, 5.0 × 106, 2.0 × 106, 1.0 × 106, 6.3 × 105, 5.0 × 105, and 2.0 × 105 at distances of 0, 4.4, 6.0, 9.2, 12.5, 15.6, 18.8, 22.0, and 25.2 nm above the LR-SERS substrate, respectively. For better comparison, we also recorded the SERS response on the C-SERS substrate (Figure S10) and plotted the EF values as functions of the separation distances (Figure 3C). We observed that the EF of the C-SERS substrate at 0 nm was 10.0-fold smaller than that of the LR-SERS substrate. This weaker SERS enhancement of the C-SERS substrate was attributed to the weaker E-fields of conventional SPPs relative to those of LRSPPs together with the absence of cavity coupling for the C-SERS substrate. Conversely, the EF of the C-SERS substrate decreased much more rapidly than that of the LR-SERS substrate with increasing separation distance. For example, C-SERS substrate EF values of 3.2 × 106 and 5.0 × 105 were observed at respective distances of 4.4 and 6.0 nm above the substrate, which are, respectively, 25- and 40-fold lower than those of the LR-SERS substrate at the same distances. Notably, at a distance of 9.2 nm from the C-SERS substrate surface, the SERS signal diminished, which contrasts sharply with the EF of 5.0 × 106 at the same distance for the LR-SERS substrate. We evaluated the EF decay using the slope of the logarithm of EF versus the separation distance. The descending slope is 0.29 nm–1 for the LR-SERS substrate and 0.91 nm–1 for C-SERS, clearly showing a slower EF attenuation on the former substrate. These comparisons are strongly indicative of the LR-SERS effect achieved on the LR-SERS substrate. To confirm the above results, we examined the signal reproducibility of both the LR-SERS and C-SERS substrates. We selected 5 bp dsDNA as the model and carried out SERS mapping measurements to demonstrate the homogeneity and reproducibility of the SERS signal on the LR-SERS and C-SERS substrates (Figure 3D,E). The color distribution suggests uniformity of the SERS signal on both substrates. The relative standard deviations (RSDs) for the 1620 cm–1 Raman band over 676 repeated measurements of the LR-SERS and C-SERS substrates were 4.7 and 4.9%, respectively. These results indicate a high signal reproducibility of the fabricated SERS substrate, attributed to the well-ordered structure of the Au NPL assemblies, together with the stable adsorption and configuration of the dsDNA probes. To further verify the reproducibility of the fabricated SERS substrates, we also collected the SERS spectra of the 5 bp dsDNA on five independent LR-SERS substrates (Figure S11). Repeated SERS signals with an RSD of 4.1% were achieved, indicating good batch-to-batch reproducibility of the fabricated SERS substrates. These results indicate that the evaluation of the LR-SERS performance is reliable. Detection of S Protein Motivated by its LR-SERS performance, we next explored LR-SERS as a sensing platform to detect the SARS-CoV-2 S protein. Figure 4A shows the averaged SERS spectra of the S protein at concentrations ranging from 1 × 10–10 to 1 × 10–5 g mL–1. Numerous bands were clearly recognized to obtain structure information of the S protein, even at a low concentration, including amide III C–N stretching and N–H deformation in the 1220–1305 cm–1 region; amide II C–N stretching and N–H deformation at 1495–1567 cm–1; amide I C=O stretching, N–H deformation, and C–N stretching at 1612–1662 cm–1; and the N–Cα–C band at 928 cm–1.44,45 According to these typical amide bands, it can be inferred that the secondary structure of the S protein is mainly an α-helix and a coiled-coil, consistent with previously reported data.46 In addition, some typical Raman bands attributed to amino acid side-chains are also well distinguished, including tryptophan bands at 745, 883, and 1371 cm–1; a tyrosine band at 825 cm–1; phenylalanine bands at 1003 and 1040 cm–1; a peptide bond C–N stretching vibration band at 1130 cm–1; and a C–H deformation band at 1443 cm–1.43,47,48 However, the SERS signal was very weak when detecting the S protein using the C-SERS substrate even at a high concentration. We compared the Raman spectrum of the S protein collected on LR- and C-SERS substrates. For example, as shown in Figure S12, the signal intensity of 1 × 10–5 g mL–1 S protein recorded on the C-SERS substrate (curve b) is even slightly lower than that from 1 ×10–9 g mL–1 S protein on the LR-SERS substrate (curve a). Moreover, the presented Raman profile on the C-SERS substrate is partially different from that obtained on the LR-SERS substrate since only the portion of the protein that is closer to the C-SERS substrate could contribute to the spectrum due to the near-field effect. Furthermore, well-defined Raman peaks were hardly to be observed at the C-SERS substrate when the concentration of S protein decreased to 1 × 10–6 g mL–1. However, distinct Raman peaks of the S protein are still present when detecting 1 × 10–10 g mL–1 S protein on the LR-SERS substrate (Figure 4A). These comparisons clearly show the higher performance in SERS detection of the LR-SERS compared to the C-SERS substrate. Figure 4 (A) Averaged SERS spectra of the SARS-CoV-2 S protein at different concentrations ranging from 1 × 10–10 to 1 × 10–5 g mL–1 collected on the LR-SERS substrate (curves a–f). (B) Dependence of the SERS intensity at 1220 cm–1 on the S protein concentrations on a logarithmic scale; the error bar was obtained from five independent experiments. (C) PCA score plots of the SARS-CoV-2 S protein (yellow) and SARS-CoV S protein (blue). A total of 60 spectra were analyzed in the spectral range 600–1800 cm–1 and each point represents an individual Raman spectrum. (D,E) Loading plots of PC1 and PC2 showing discrimination of the SARS-CoV-2 S protein from the SARS-CoV S protein; a total of 60 spectra were analyzed. (F) Difference spectrum of the SARS-CoV-2 S and SARS-CoV S proteins. The concentration of the S protein is 1 × 10–10 g mL–1. We collected SERS spectra of the S protein at 25 different sites on the LR-SERS substrate, whereby an RSD of 9.4% was achieved at 1220 cm–1 (Figure S13), indicating the high detection reproducibility when using the LR-SERS substrate. This is likely because the LR-SERS substrate provides an extended E-field so that the S protein is completely within the effective E-field. Therefore, the different orientations of the S protein on the LR-SERS substrate only cause a minor difference in its SERS profile. Using the linearity relationship established between the SERS intensity at 1220 cm–1 and the logarithm of the target S protein concentration [Y = 5866.6 + 568.9X with a high correlation coefficient (R2) of 0.986 (Figure 4B)], the limit of detection (LOD) of the S protein was calculated to be 2.8 × 10–11 g mL–1 when the signal-to-noise ratio (S/D) was 3 (linear range from 1 × 10–10 to 1 × 10–5 g mL–1). Notably, the exhibited detection sensitivity using a label-free strategy on our LR-SERS substrate is superior to that obtained by the commonly used PCR-based technique, in which a linear range of 1.25 × 10–6 to 4.7 × 10–3 g mL–1 and an LOD of 1.9 × 10–8 g mL–1 was achieved.49,50 We challenged the detection specificity of the CoV-2 S protein since the S protein of SARS-CoV-2 shares 75.9% sequence identity with that of SARS-CoV.47 The averaged SERS spectrum of the SARS-CoV S protein is shown in Figure S14. Owing to the high homology of the two virus proteins, a similar SERS profile was unsurprisingly presented, and, thus, we combined the PCA method to examine the detection specificity. Figure 4C shows the PCA score plot of the SERS spectra of the SARS-CoV/SARS-CoV-2 S protein, in which well-defined clusters appear; PC1 and PC2 contribute 70.2 and 14.7% of the total variance, respectively. As revealed in Figures 4D,E, the PC1 loading presented positive peaks at 1003, 1220, 1295, and 1360 cm–1 related to the amino acid side chain (highlighted in blue), while the PC2 loading presented negative bands at 1245, 1272, and 1371 cm–1 related to amides II and III (highlighted in yellow). Such a difference can also be visualized in the difference spectrum (Figure 4F), which arises from the different amino acid sequences and conformation between the two S proteins. All these results indicate that the developed label-free method has the capability to discriminate between the SARS-CoV-2 S and SARS-CoV S proteins despite their high homology. Determination of S Protein in Saliva Finally, to assess the practical application of the LR-SERS substrate for S protein detection, we carried out the test in saliva to approach the real clinical environment. The typical SERS spectrum of the negative sample [i.e., filtered saliva suspended in viral transport medium (VTM)] on the LR-SERS substrate is shown in Figure 5A(a), which displays prominent vibrational modes at ∼740, 850, 1005, 1105, 1156, 1245, 1366, 1457, 1545, and 1697 cm–1, assigned to the proteins, amino acids, lipids, and DNA and/or RNA. The detailed assignment of these Raman peaks is listed in Table S2.51,52 The SERS spectra of the positive sample (i.e., VTM containing saliva spiked with 1 × 10–10 g mL–1 of SARS-CoV-2 S protein) were next recorded. As shown in Figure 5A(b), the Raman bands appear stronger than those of the negative sample. The saliva and VTM contributions to the positive sample were well observed, and, thus, we subtracted the spectra of the negative sample and used the Raman difference spectra to highlight the changes caused by the S protein, as shown in Figure 5A(c). The characteristic peaks of the S protein were clearly distinguished and well matched those of the native S protein, indicating that the difference between the positive and negative samples is induced by the S protein. As expected, the LR-SERS biosensing platform is feasible for the direct detection of S proteins in saliva, even at its lower limit of linear range (1 × 10–10 g mL–1) for the developed detection approach. To evaluate the analytical performance of the developed method in the saliva sample, SERS measurements were carried out using saliva samples spiked with increasing concentrations of the SARS-CoV-2 S protein (1 × 10–10 to 1 × 10–8 g mL–1). As shown in Figure S15, the calibration plot displays good linearity with R2 of 0.973. The LOD was achieved to be 3.9 × 10–11 g mL–1 at S/D of 3, suggesting that it will be suitable as a diagnostic tool for the detection of COVID-19 infection. Figure 5 (A) SERS spectra of the negative (VTM containing saliva, curve a) and positive (VTM containing saliva spiked with SARS-CoV-2 S protein, curve b) samples and their difference spectrum (c). (B) PCA score plots of the positive (blue) and negative (red) samples. A total of 60 spectra were analyzed and each point represents an individual Raman spectrum. (C) PC1 and PC2 loading plots. (D) Receiver operating characteristic curves for separating the positive from the negative samples. (E) PLS-DA prediction plot showing good discrimination between the positive and negative samples. The concentration of the S protein is 1 × 10–10 g mL–1. We further utilized PCA to discriminate between the SARS-CoV-2 S-protein-spiked saliva from the healthy samples, wherein the corresponding PC1 and PC2 plots revealed clear segregation between the infected and control groups (Figure 5B). The first two PC components accounted for 70.0% (PC1, 62.7%; PC2, 7.3%) of the total Raman variations (Figure 5C), demonstrating that the infected group can be easily distinguished from the control group using the PCA method. Finally, we tested the discrimination capability using PLS-DA, wherein the discrimination model was built on the SERS spectra of 30 positive and 30 negative samples. The receiver operating characteristic (ROC) curve for the differentiation between the positive and negative samples is shown in Figure 5D. The integrated area under the ROC curve of the PLS-DA model was 0.99, proving the efficiency of using Raman data along with PLS-DA for distinguishing the SARS-CoV-2 S protein in saliva. In Figure 5E, the PLS-DA results clearly display two zones dominated by “positive” and “negative” Raman spectra, indicating that the positive and negative samples can be differentiated based on their Raman spectra. The PLS-DA technique yields 98% sensitivity, 100% specificity, and collectively a diagnostic accuracy of 99% based on a threshold of 0.4 (Figure 5E). The detection sensitivity is thus improved compared to the 60% sensitivity of the “COVID-19 Ag Respi-Strip” from CORIS BioConcept and 80% sensitivity of FIA.7,8 These results demonstrate that implementation of label-free Raman sensing together with PLS-DA provides robust differentiation between SARS-CoV-2 S protein positive and negative samples. To validate the accuracy of our proposed method, we used a SARS-CoV-2-specific-ELISA in parallel to test the level of the spiked SARS-CoV-2 S protein. The SERS results corresponding to the same sample are in agreement with the values from ELISA (Figure S16), implying that our label-free method possesses high accuracy. Nonetheless, this method has not been applied in detection of real samples, that is, S protein extracted from SARS-CoV-2. Proteins or RNAs other than the S protein presented in purification may interfere with the SERS signal of the S protein. Conclusions In summary, we have developed a novel LR-SERS substrate with an Au NPL film/MgF2/Au mirror/glass configuration. In contrast to previously reported fabrication methods for LR-SERS substrates, a bottom-up strategy for preparing a continuous Au film from Au NPL building blocks combined with a robust Langmuir–Blodgett assembly technique was applied in the construction of LR-SERS substrates. The fabricated LR-SERS substrates exhibited strong SERS enhancement, signal repeatability, and good batch-to-batch reproducibility. More importantly, the FDTD simulation results demonstrated that this LR-SERS substrate was endowed with an extended E-field resulting from LRSPPs. SERS measurements verified that a reliable EF of 2.0 × 105 was retained at distances of 25.2 nm beyond the LR-SERS substrate. The decay of EF observed for the LR-SERS substrate was 3.1-fold slower than that of the C-SERS substrate. Consequently, reproducible and well-defined S protein SERS spectra were obtained using an LR-SERS substrate as the sensing platform, which provided more information on the secondary structure of the S protein and greatly improved the detection sensitivity compared to those achieved on the C-SERS substrate. This novel LR-SERS substrate can be used for reagent-free detection of the S protein in saliva and to distinguish S protein-infected saliva from healthy human saliva. Therefore, an interesting LR-SERS substrate with an extended probing distance together with its efficient and robust fabrication methods is reported herein, which shows great potential for application as a good sensing platform for rapid viral proteins in clinical diagnosis. Supporting Information Available The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.analchem.2c03846.Details of FDTD simulation; calculation of the separation distance and SERS enhancement factor; PCA and PLS-DA analysis; sequences of the used oligonucleotides and assignments of typical Raman bands of the antigen; TEM image of the synthesized Au NPLs, histogram of the Au NPLs’ lateral size distributions, and AFM image and height profile; HRTEM images and lattice fringes in the selected area of a single Au NPL, corresponding SAED pattern of a single Au NPL, and XRD spectrum of Au NPLs; orientation direction of incident light with respect to the rhombic lattice and Bragg excitation of the lowest order SPP modes; FDTD-simulated E-field distribution at the x–y plane of the top NPL film of the C-SERS substrate at different wavelengths; z component of the E-field distribution of the C-SERS substrate at different wavelengths; FDTD-simulated reflectance spectrum and z component of the E-field distribution of a multilayer substrate at different wavelengths; FDTD simulation of reflection spectra and maximum electric field intensity versus wavelength at the Au/water interfaces of the top Au NPL array; comparison of the decay of the simulated log (EF) of the LR-SERS substrate with different thicknesses of the Au NPL film at different distances above the film; SERS spectra of MB dye-labeled dsDNA on the C-SERS substrate; SERS spectra of 5 bp MB-labeled dsDNA collected at five different spots on five independent LR-SERS substrates; SERS spectra of SARS-CoV-2 S protein of different concentrations on LR-SERS and C-SERS substrates; averaged SERS spectrum of SARS-CoV-2 S protein on the LR-SERS substrate; SERS spectra of spiked S protein of different concentrations in saliva and dependence of the SERS intensity on S protein concentrations; and comparison of the relative level of SARS-CoV-2 S protein detected by the developed SERS sensor and ELISA measurement PDF Supplementary Material ac2c03846_si_001.pdf Author Contributions P.W., C.C., and J.-J.Z. designed the research; X.L., Y.X., N.F., and J.Z. performed the research; J.W. performed the computational calculations. All authors contributed to the data analysis. P.W. wrote the manuscript, which was revised and reviewed by all authors. C.C., and J.-J.Z. supervised the project. The authors declare no competing financial interest. Acknowledgments This work was supported by the NSFC (21834004), Priority Academic Program Development of Jiangsu Higher Education Institutions, and Guangdong Basic and Applied Basic Research Foundation (2020B1515120026). ==== Refs References Smyrlaki I. ; Ekman M. ; Lentini A. ; Rufino de Sousa N. ; Papanicolaou N. ; Vondracek M. ; Aarum J. ; Safari H. ; Muradrasoli S. ; Rothfuchs A. G. ; Albert J. ; Högberg B. ; Reinius B. Massive and Rapid COVID-19 Testing is Feasible by Extraction-Free SARS-CoV-2 RT-PCR. Nat. Commun. 2020, 11 , 4812 10.1038/s41467-020-18611-5.32968075 Cazares L. H. ; Chaerkady R. ; Samuel Weng S. H. S. ; Boo C. C. ; Cimbro R. ; Hsu H.-E. ; Rajan S. ; Dall’Acqua W. ; Clarke L. ; Ren K. ; McTamney P. ; Kallewaard-LeLay N. ; Ghaedi M. ; Ikeda Y. ; Hess S. Development of a Parallel Reaction Monitoring Mass Spectrometry Assay for the Detection of SARS-CoV-2 Spike Glycoprotein and Nucleoprotein. Anal. Chem. 2020, 92 , 13813–13821. 10.1021/acs.analchem.0c02288.32966064 Zhao J. ; Yuan Q. ; Wang H. ; Liu W. ; Liao X. ; Su Y. ; Wang X. ; Yuan J. ; Li T. ; Li J. ; Qian S. ; Hong C. ; Wang F. ; Liu Y. ; Wang Z. ; He Q. ; Li Z. ; He B. ; Zhang T. ; Fu Y. ; Ge S. ; Liu L. ; Zhang J. ; Xia N. ; Zhang Z. Antibody Responses to SARS-CoV-2 in Patients with Novel Coronavirus Disease 2019. Clin. Infect. Dis. 2020, 71 , 2027–2034. 10.1093/cid/ciaa344.32221519 Zhang N. ; Wang L. ; Deng X. ; Liang R. ; Su M. ; He C. ; Hu L. ; Su Y. ; Ren J. ; Yu F. ; Du L. ; Jiang S. Recent Advances in the Detection of Respiratory Virus Infection in Humans. J. Med. Virol. 2020, 92 , 408–417. 10.1002/jmv.25674.31944312 Carter L. J. ; Garner L. V. ; Smoot W. ; Li Y. ; Zhou Q. ; Saveson J. ; Sasso J. M. ; Gregg A. C. ; Soares D. J. ; Beskid R. ; et al. Assay Techniques and Test Development for COVID-19 Diagnosis. ACS Cent. Sci. 2020, 6 , 591–605. 10.1021/acscentsci.0c00501.32382657 Babiker A. ; Myers C. W. ; Hill C. E. ; Guarner J. SARS-CoV-2 Testing. Am. J. Clin. Pathol. 2020, 153 , 706–708. 10.1093/ajcp/aqaa052.32227199 Quidel. Sofia SARS Antigen Fluorescent Immunoassay (FIA). https://www.quidel.com/immunoassays/rapid-sars-tests/sofia-sarsantigenfia (accessed Nov 01, 2022). Lambert-Niclot S. ; Cuffel A. ; Le Pape S. ; Vauloup-Fellous C. ; Morand-Joubert L. ; Roque-Afonso A.-M. ; Le Goff J. ; Delaugerre C. Evaluation of a Rapid Diagnostic Assay for Detection of SARS-CoV-2 Antigen in Nasopharyngeal Swabs. J. Clin. Microbiol. 2020, 58 , 009777-20 10.1128/JCM.00977-20. Dadosh T. ; Sperling J. ; Bryant G. W. ; Breslow R. ; Shegai T. ; Dyshel M. ; Haran G. ; Bar-Joseph I. Plasmonic Control of the Shape of the Raman Spectrum of a Single Molecule in a Silver Nanoparticle Dimer. ACS Nano 2009, 3 , 1988–1994. 10.1021/nn900422w.19534506 Tapio K. ; Mostafa A. ; Kanehira Y. ; Suma A. ; Dutta A. ; Bald I. A Versatile DNA Origami-Based Plasmonic Nanoantenna for Label-Free Single-Molecule Surface-Enhanced Raman Spectroscopy. ACS Nano 2021, 15 , 7065–7077. 10.1021/acsnano.1c00188.33872513 Li J.-F. ; Zhang Y.-J. ; Ding S.-Y. ; Panneerselvam R. ; Tian Z.-Q. Core-Shell Nanoparticle-Enhanced Raman Spectroscopy. Chem. Rev. 2017, 117 , 5002–5069. 10.1021/acs.chemrev.6b00596.28271881 Dreaden E. C. ; Alkilany A. M. ; Huang X. ; Murphy C. J. ; El-Sayed M. A. The Golden Age: Gold Nanoparticles for Biomedicine. Chem. Soc. Rev. 2012, 41 , 2740–2779. 10.1039/c1cs15237h.22109657 Galvan D. D. ; Špačková B. ; Slabý J. ; Sun F. ; Ho Y.-H. ; Homola J. ; Yu Q. Surface-Enhanced Raman Scattering on Gold Nanohole Arrays in Symmetrical Dielectric Environments Exhibiting Electric Field Extension. J. Phys. Chem. C 2016, 120 , 25519–25529. 10.1021/acs.jpcc.6b08294. Petrov D. Photopolarimetrical Properties of Coronavirus Model Particles: Spike Proteins Number Influence. J. Quant. Spectrosc. Radiat. Transfer 2020, 248 , 107005 10.1016/j.jqsrt.2020.107005. Berini P. Long-Range Surface Plasmon Polaritons. Adv. Opt. Photonics 2009, 1 , 484–588. 10.1364/aop.1.000484. Yang C.-T. ; Méjard R. ; Griesser H. J. ; Bagnaninchi P. O. ; Thierry B. Cellular Micromotion Monitored by Long-Range Surface Plasmon Resonance with Optical Fluctuation Analysis. Anal. Chem. 2015, 87 , 1456–1461. 10.1021/ac5031978.25495915 Sarid D. Long-Range Surface-Plasma Waves on Very Thin Metal-Films. Phys. Rev. Lett. 1981, 47 , 1927–1930. 10.1103/physrevlett.47.1927. Liu Y. ; Xu S. ; Xuyang X. ; Zhao B. ; Xu W. Long-Range Surface Plasmon Field-Enhanced Raman Scattering Spectroscopy Based on Evanescent Field Excitation. J. Phys. Chem. Lett. 2011, 2 , 2218–2222. 10.1021/jz200963x. Hou C. ; Galvan D. D. ; Meng G. ; Yu Q. Long-Range Surface Plasmon Resonance and Surface-Enhanced Raman Scattering on X-Shaped Gold Plasmonic Nanohole Arrays. Phys. Chem. Chem. Phys. 2017, 19 , 24126–24134. 10.1039/c7cp04564f.28837198 Luo X. ; Zhu J. ; Jia W. ; Fang N. ; Wu P. ; Cai C. ; Zhu J.-J. Boosting Long-Range Surface-Enhanced Raman Scattering on Plasmonic Nanohole Arrays for Ultrasensitive Detection of MiRNA. ACS Appl. Mater. Interfaces 2021, 13 , 18301–18313. 10.1021/acsami.1c01834.33821612 Si S. ; Liang W. ; Sun Y. ; Huang J. ; Ma W. ; Liang Q. ; Bao Q. ; Jiang L. Facile Fabrication of High-Density Sub-1-nm Gaps from Au Nanoparticle Monolayers as Reproducible SERS Substrates. Adv. Funct. Mater. 2016, 26 , 8137–8145. 10.1002/adfm.201602337. Qin D. ; Xia Y. ; Whitesides G. M. Soft Lithography for Microand Nanoscale Patterning. Nat. Protoc. 2010, 5 , 491–502. 10.1038/nprot.2009.234.20203666 Biswas A. ; Bayer I. S. ; Biris A. S. ; Wang T. ; Dervishi E. ; Faupel F. Advances in Top-down and Bottom-up Surface Nanofabrication: Techniques, Applications & Future Prospects. Adv. Colloid Interface Sci. 2012, 170 , 2–27. 10.1016/j.cis.2011.11.001.22154364 Reincke F. ; Hickey S. G. ; Kegel W. K. ; Vanmaekelbergh D. Spontaneous Assembly of a Monolayer of Charged Gold Nanocrystals at the Water/Oil Interface. Angew. Chem., Int. Ed. 2004, 43 , 458–462. 10.1002/anie.200352339. Hong S. ; Shuford K. L. ; Park S. Shape Transformation of Gold Nanoplates and their Surface Plasmon Characterization: Triangular to Hexagonal Nanoplates. Chem. Mater. 2011, 23 , 2011–2013. 10.1021/cm103273c. Qin F. ; Zhao T. ; Jiang R. ; Jiang N. ; Ruan Q. ; Wang J. ; Sun L.-D. ; Yan C.-H. ; Lin H.-Q. Thickness Control Produces Gold Nanoplates with Their Plasmon in the Visible and Near-Infrared Regions. Adv. Opt. Mater. 2016, 4 , 76–85. 10.1002/adom.201500496. Sarid D. ; Deck R. T. ; Craig A. E. ; Hickernell R. K. ; Jameson R. S. ; Fasano J. J. Optical Field Enhancement by Long-Range Surface-Plasma Waves. Appl. Opt. 1982, 21 , 3993–3995. 10.1364/ao.21.003993.20400996 Li Y.-J. ; Huang W.-J. ; Sun S.-G. A Universal Approach for the Self-Assembly of Hydrophilic Nanoparticles into Ordered Monolayer Films at a Toluene/Water Interface. Angew. Chem., Int. Ed. 2006, 45 , 2537–2539. 10.1002/anie.200504595. Park Y.-K. ; Yoo S.-H. ; Park S. Assembly of Highly Ordered Nanoparticle Monolayers at a Water/Hexane Interface. Langmuir 2007, 23 , 10505–10510. 10.1021/la701445a.17854209 Park Y.-K. ; Park S. Directing Close-Packing of Midnanosized Gold Nanoparticles at a Water/Hexane Interface. Chem. Mater. 2008, 20 , 2388–2393. 10.1021/cm703498y. Chen C.-F. ; Tzeng S.-D. ; Chen H.-Y. ; Lin K.-J. ; Gwo S. Tunable Plasmonic Response from Alkanethiolate-Stabilized Gold Nanoparticle Superlattices: Evidence of Near-Field Coupling. J. Am. Chem. Soc. 2008, 130 , 824–826. 10.1021/ja0773610.18163631 Murray W. A. ; Astilean S. ; Barnes W. L. Transition from Localized Surface Plasmon Resonance to Extended Surface Plasmon-Polariton as Metallic Nanoparticles Merge to Form a Periodic Hole Array. Phys. Rev. B: Condens. Matter Mater. Phys. 2004, 69 , 165407 10.1103/physrevb.69.165407. Etchegoin P. G. ; Le Ru E. C. ; Meyer M. An Analytic Model for the Optical Properties of Gold. J. Chem. Phys. 2006, 125 , 164705 10.1063/1.2360270.17092118 Kravets V. G. ; Kabashin A. V. ; Barnes W. L. ; Grigorenko A. N. Plasmonic Surface Lattice Resonances: A Review of Properties and Applications. Chem. Rev. 2018, 118 , 5912–5951. 10.1021/acs.chemrev.8b00243.29863344 Tao A. ; Sinsermsuksakul P. ; Yang P. Tunable Plasmonic Lattices of Silver Nanocrystals. Nat. Nanotechnol. 2007, 2 , 435–440. 10.1038/nnano.2007.189.18654329 Fong N. R. ; Menotti M. ; Lisicka-Skrzek E. ; Northfield H. ; Olivieri A. ; Tait N. ; Liscidini M. ; Berini P. Bloch Long-Range Surface Plasmon Polaritons on Metal Stripe Waveguides on a Multilayer Substrate. ACS Photonics 2017, 4 , 593–599. 10.1021/acsphotonics.6b00930. Lin L. ; Zheng Y. Optimizing Plasmonic Nanoantennas via Coordinated Multiple Coupling. Sci. Rep. 2015, 5 , 14788 10.1038/srep14788.26423015 Yang K. ; Yao X. ; Liu B. ; Ren B. Metallic Plasmonic Array Structures: Principles, Fabrications, Properties, and Applications. Adv. Mater. 2021, 33 , 2007988 10.1002/adma.202007988. Tao A. R. ; Ceperley D. P. ; Sinsermsuksakul P. ; Neureuther A. R. ; Yang P. Self-Organized Silver Nanoparticles for Three-Dimensional Plasmonic Crystals. Nano Lett. 2008, 8 , 4033–4038. 10.1021/nl802877h.18928325 Keighley S. D. ; Li P. ; Estrela P. ; Migliorato P. Optimization of DNA Immobilization on Gold Electrodes for Label-free Detection by Electrochemical Impedance Spectroscopy. Biosens. Bioelectron. 2008, 23 , 1291–1297. 10.1016/j.bios.2007.11.012.18178423 Dulkeith E. ; Ringler M. ; Klar T. A. ; Feldmann J. ; Muñoz Javier J. A. ; Parak W. J. Gold Nanoparticles Quench Fluorescence by Phase Induced Radiative Rate Suppression. Nano Lett. 2005, 5 , 585–589. 10.1021/nl0480969.15826091 Gehan H. ; Fillaud L. ; Chehimi M. M. ; Aubard J. ; Hohenau A. ; Felidj N. ; Mangeney C. Thermo-induced Electromagnetic Coupling in Gold/Polymer Hybrid Plasmonic Structures Probed by Surface Enhanced-Raman Scattering. ACS Nano 2010, 4 , 6491–6500. 10.1021/nn101451q.21028846 Marchi S. D. ; Vázquez-Iglesias L. ; Bodelón G. ; Pérez-Juste I. ; Fernández L. A. ; Pérez-Juste J. ; Pastoriza-Santos I. Programmable Modular Assembly of Functional Proteins on RamanEncoded Zeolitic Imidazolate Framework-8 (ZIF-8) Nanoparticles as SERS Tags. Chem. Mater. 2020, 32 , 5739–5749. 10.1021/acs.chemmater.0c01518. Stanborough T. ; Given F. M. ; Koch B. ; Sheen C. R. ; Stowers-Hull A. B. ; Waterland M. R. ; Crittenden D. L. Optical Detection of CoV-SARS-2 Viral Proteins to Sub-Picomolar Concentrations. ACS Omega 2021, 6 , 6404–6413. 10.1021/acsomega.1c00008.33718731 Daoudi K. ; Ramachandran K. ; Alawadhi H. ; Boukherroub R. ; Dogheche E. ; Khakani M. A. E. ; Gaidi M. Ultra-Sensitive and Fast Optical Detection of the Spike Potein of the SARS-CoV-2 Using AgNPs/SiNWs Nanohybrid Based Sensors. Surf. Interfaces 2021, 27 , 101454 10.1016/j.surfin.2021.101454.34957346 Bangaru S. ; Ozorowski G. ; Turner H. L. ; Antanasijevic A. ; Huang D. ; Wang X. ; Torres J. L. ; Diedrich J. K. ; Tian J.-H. ; Portnoff A. D. ; Patel N. ; Massare M. J. ; Yates J. R. III ; Nemazee D. ; Paulson J. C. ; Glenn G. ; Smith G. ; Ward A. B. Structural Analysis of Full-Length SARS-CoV-2 Spike Protein from an Advanced Vaccine Candidate. Science 2020, 370 , 1089–1094. 10.1126/science.abe1502.33082295 Kahraman M. ; Sur I. ; Çulha M. Label-Free Detection of Proteins from Self-Assembled Protein-Silver Nanoparticle Structures using Surface-Enhanced Raman Scattering. Anal. Chem. 2010, 82 , 7596–7602. 10.1021/ac101720s.20795644 Rygula A. ; Majzner K. ; Marzec K. M. ; Kaczor A. ; Pilarczyk M. ; Baranska M. Raman Spectroscopy of Proteins: A Review. J. Raman Spectrosc. 2013, 44 , 1061–1076. 10.1002/jrs.4335. Sunwoo H. H. ; Palaniyappan A. ; Ganguly A. ; Bhatnagar P. K. ; Das D. ; El-Kadi A. O. S. ; Suresh M. S. Quantitative and Sensitive Detection of the SARS-CoV Spike Protein Using Bispecific Monoclonal Antibody-Based Enzyme-Linked Immunoassay. J. Virol. Methods 2013, 187 , 72–78. 10.1016/j.jviromet.2012.09.006.22995576 Ahmed S. F. ; Quadeer A. A. ; McKay M. R. Preliminary Identification of Potential Vaccine Targets for the COVID-19 Coronavirus (SARS-CoV-2) Based on SARS-CoV Immunological Studies. Viruses 2020, 12 , 254 10.3390/v12030254.32106567 Qian K. ; Wang Y. ; Hua L. ; Chen A. ; Zhang Y. New Method of Lung Cancer Detection by Saliva Test Using Surface-Enhanced Raman Spectroscopy. Thorac. Cancer 2018, 9 , 1556–1561. 10.1111/1759-7714.12837.30168669 Yuen C. ; Zheng W. ; Huang Z. Improving Surface-Enhanced Raman Scattering Effect Using Gold-Coated Hierarchical Polystyrene Bead Substrates Modified with Postgrowth Microwave Treatment. J. Biomed. Opt. 2008, 13 , 064040 10.1117/1.3050447.19123686
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==== Front Anal Chem Anal Chem ac ancham Analytical Chemistry 0003-2700 1520-6882 American Chemical Society 36480911 10.1021/acs.analchem.2c03442 Article Ultrasensitive Isothermal Detection of SARS-CoV-2 Based on Self-Priming Hairpin-Utilized Amplification of the G-Rich Sequence Li Yan † Kim Hansol † Ju Yong † Park Yeonkyung † https://orcid.org/0000-0002-5387-6458 Kang Taejoon ‡§ Yong Dongeun ∥ https://orcid.org/0000-0001-9978-3890 Park Hyun Gyu *† † Department of Chemical and Biomolecular Engineering (BK21 Four), Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon34141, Republic of Korea ‡ Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Yuseong-gu, Daejeon34141, Republic of Korea § School of Pharmacy, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do16419, Republic of Korea ∥ Department of Laboratory Medicine and Research Institute of Bacterial Resistance, Yonsei University College of Medicine, Seoul03722, Republic of Korea * Email: [email protected]. 08 12 2022 acs.analchem.2c0344208 08 2022 28 11 2022 © 2022 American Chemical Society 2022 American Chemical Society This article is made available via the PMC Open Access Subset for unrestricted RESEARCH re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. The outbreak of the novel coronavirus disease 2019 (COVID-19) pandemic induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of fatalities all over the world. Unquestionably, the effective and timely testing for infected individuals is the most imperative for the prevention of the ongoing pandemic. Herein, a new method was established for detecting SARS-CoV-2 based on the self-priming hairpin-utilized isothermal amplification of the G-rich sequence (SHIAG). In this strategy, the target RNA binding to the hairpin probe (HP) was uniquely devised to lead to the self-priming-mediated extension followed by the continuously repeated nicking and extension reactions, consequently generating abundant G-rich sequences from the intended reaction capable of producing fluorescence signals upon specifically interacting with thioflavin T (ThT). Based on the unique isothermal design concept, we successfully identified SARS-CoV-2 genomic RNA (gRNA) as low as 0.19 fM with excellent selectivity by applying only a single HP and further verified its practical diagnostic capability by reliably testing a total of 100 clinical specimens for COVID-19 with 100% clinical sensitivity and specificity. This study would provide notable insights into the design and evolution of new isothermal strategies for the sensitive and facile detection of SARS-CoV-2 under resource constraints. Korean National Police Agency 10.13039/501100003600 PA-K000001-2019-101 National Research Foundation of Korea NA NRF-2021R1A2B5B03001739 KRIBB Research Initiative Program NA NA KRIBB Research Initiative Program NA 1711134081 document-id-old-9ac2c03442 document-id-new-14ac2c03442 ccc-price This article is made available via the ACS COVID-19 subset for unrestricted RESEARCH re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. ==== Body pmcSince its appearance in late December 2019, coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has quickly transmitted worldwide. The World Health Organization (WHO) declared it as a global pandemic on 11 March 2020.1 As of 30 May 2022, COVID-19 has infected and killed more than 520 and 6.2 million people worldwide, respectively,2 posing unprecedented challenges to the global health and economy. In comparison with severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), or other epidemic human coronaviruses (HCoVs), SARS-CoV-2 virus exhibits increased human-to-human transmission and individuals carrying SARS-CoV-2 virus show no symptoms in many clinical cases, accelerating the viral transmission and significantly increasing its pandemic potential.3−6 Furthermore, the SARS-CoV-2 virus has consistently mutated over time, resulting in the continual emergence of new SARS-CoV-2 variants showing higher transmissibility than the original virus,7,8 which would make the prevention of the outbreak more challenging.9 Most representatively, the Omicron variant spreads more easily than earlier variants including the Delta variant, and anyone with Omicron infection can spread the virus to others whether or not they have symptoms.10−12 Despite playing a predominant role in protecting individuals against severe forms of COVID-19, the coronavirus vaccines are not completely effective in preventing infection13−15 and the Omicron variant is known to infect vaccinated people.16−18 Therefore, timely testing COVID-19 cases through rapid and accurate methods and keeping infected patients under surveillance to curb further transmission are still of the most importance to control and manage the ongoing pandemic.19,20 The gold standard method for diagnosing COVID-19 is quantitative reverse transcription polymerase chain reaction (qRT-PCR) where the viral RNA is first converted to the complementary DNA (cDNA) succeeded by a qPCR process with the cDNA.21−23 Despite its high clinical sensitivity and specificity, the qRT-PCR requires temperature cycling, takes a relatively lengthy testing period (3–4 h), and needs to be conducted in a centralized laboratory by an experienced operator, restricting its widespread applicability for point-of-care testing (POCT) purpose under resource constraints.24−26 Isothermal strategies to amplify nucleic acids could simplify and speed up the testing process, providing a compelling alternative to the conventional method based on thermocycling machine.27−29 Since the early 1990s, dozens of isothermal amplification methods have been reported, such as Nucleic Acid Sequence Based Amplification (NASBA),30,31 Strand Displacement Amplification (SDA),32,33 Loop-mediated Isothermal Amplification (LAMP),34,35 Rolling Circle Amplification (RCA),36,37 target-induced Chain Amplification Reaction (CAR),38 Nicking and Extension Chain Reaction System-based Amplification (NESBA),39 and so on.40−42 By taking advantage of the simplicity of apparatus and reaction procedure, most of the isothermal techniques showed great potential for POCT applications,43 but several drawbacks including the requirement for multiple primers/probes,44−46 relatively high reaction temperature,47 and insufficient amplification efficiency48−51 remain to be solved. Based on this context, we herein developed a new technique to identify SARS-CoV-2 based on the self-priming hairpin-utilized isothermal amplification of the G-rich sequence (SHIAG). The self-priming hairpin probe (HP) was verified to enable the detection of synthetic DNA and RNA under the isothermal condition without any exogenous primers.42 By making the most of the self-priming HP and the combined extension and nicking reactions to generate abundant G-rich sequences capable of producing fluorescence signals through specific interaction with thioflavin T (ThT), we successfully identified target SARS-CoV-2 genomic RNA (gRNA) as low as sub-femtomolar level with excellent selectivity in a one-pot reaction while applying only a single HP without any exogenous primers or prior labelings. Experimental Section Materials All DNA oligonucleotides utilized in the current work were HPLC-purified and purchased from Bioneer (Daejeon, Korea). The target RNA oligonucleotide was RNase-free HPLC purified and purchased from Integrated DNA Technologies, Inc. (Coralville, IA, USA). All oligonucleotides are presented in Table S1. The gRNAs of SARS-CoV-2, HCoV-NL63, and MERS-CoV were supplied by the National Culture Collection for Pathogens (NCCP, Cheongju, Korea). The gRNAs of SARS-CoV and HCoV-HKU-1 were purchased from Intergrated DNA Technologies Inc. (Coralville, IA, USA) while the gRNAs of HCoV-OC43 and HCoV-229E were purchased from the Korea Bank for Pathogenic Viruses (KBPV, Seoul, Korea). Bst 2.0 WarmStart DNA polymerase (Bst, M0538S), Nt.BstNBI (R0607S), NEBuffer 3.1 (B7203S), ThermoPol reaction buffer (B9004S), and deoxynucleotide (dNTP) solution mix (N0447S) were purchased from New England Biolabs Inc. (Beverly, MA, USA). Diethyl pyrocarbonate (DEPC)-treated water (95284) and ThT (T3516) were purchased from Sigma-Aldrich (St. Louis, MO, USA). All other chemicals were of analytical grade and used as received without further purification. SHIAG Reaction for SARS-CoV-2 Detection Prior to use, 1 μM HP in 1× HP buffer (1 mM MgSO4, 5 mM (NH4)2SO4, 5 mM KCl, 7.5 mM MgCl2, 47.5 mM Tris–HCl, 75 mM NaCl, 0.05% Triton X-100, 75 μg/mL BSA) was heated at 95 °C for 5 min and then cooled to 25 °C (0.1 °C/s) to ensure proper intramolecular folding and form a hairpin structure. The 20 μL SHIAG reaction solution was prepared to contain 0.5 μL of pretreated HP solution (1 μM), 1 μL of 10× ThermoPol reaction buffer (20 mM MgSO4, 100 mM (NH4)2SO4, 100 mM KCl, 200 mM Tris–HCl, 1% Triton X-100, pH 8.8), 1.5 μL of 10× NEBuffer 3.1 (100 mM MgCl2, 500 mM Tris–HCl, 1 M NaCl, 1 mg/mL BSA, pH 7.9), 0.5 μL of dNTP (10 mM), 0.2 μL of Bst (8 U/μL), 0.16 μL of Nt.BstNBI nicking endonuclease (10 U/μL), 2 μL of ThT (250 μM), and 2 μL of target analyte, which was incubated at 37 °C for 60 min. From the reaction products, the fluorescence emission spectra in a range of 480–650 nm or the fluorescence emission intensities at 496 nm were monitored at an excitation wavelength of 440 nm by using a Tecan Infinite M200 Pro microplate reader (Männedorf, Switzerland) and 384-well Greiner Bio-One microplates (Ref. 781077, Courtaboeuf, France). To optimize reaction conditions, the fluorescence signal from ThT was recorded at an interval of 60 s at 37 °C by using a CFX Connect Real-Time System (Bio-Rad, CA, USA). Polyacrylamide Gel Electrophoresis (PAGE) Analysis For the PAGE assay, 10 μL of the reaction solution was resolved on 15% polyacrylamide gel at 120 V for 90 min using 1X TBE as the running buffer. After ethidium bromide (EtBr) staining, the gel was scanned using the ChemiDoc Imaging System (Bio-Rad, CA, USA). Clinical Sample Testing with the SHIAG Reaction Real clinical nasopharyngeal swab and sputum specimens (n = 100) were provided by Gyeongsang National University College of Medicine and Severance Hospital. The specimens were collected from individuals with suspected COVID-19 infection and stored in universal transport media at −70 °C. The protocols for these studies were reviewed and approved by the Institutional Review Board (IRB) of Gyeongsang National University College of Medicine (IRB approval number: 2020-10-002; Jinju, Korea) and Severance Hospital (IRB approval number: 4-2020-0465; Seoul, Korea). The gRNAs of the clinical specimens were extracted by using the AdvanSure Nucleic Acid R kit (LG chem, Seoul, Korea) and subjected to the SHIAG reaction according to the procedure as described above. Clinical Specimen Analysis with qRT-PCR For the clinical specimens provided by Gyeongsang National University College of Medicine, the qRT-PCR was carried out following the manufacturer’s protocol of the Luna Universal One-Step RT-qPCR Kit (New England Biolabs Inc., Beverly, MA, USA). Reverse transcription (RT) was first conducted for 10 min at 55 °C, and the PCR was carried out for 1 min at 95 °C for initial denaturation, succeeded by 45 cycles of 10 s at 95 °C and 30 s at 60 °C. For the clinical samples acquired from Severance Hospital, the qRT-PCR was carried out following the manufacturer’s protocol of the Allplex 2019-nCoV assay kit (Seegene Inc., Seoul, Korea). RT was first conducted for 20 min at 50 °C, and the PCR was carried out for 15 min at 95 °C for initial denaturation, succeeded by 45 cycles of 15 s at 94 °C and 30 s at 58 °C. Fluorescence signals of all specimens were monitored each cycle by using a CFX96 Real-Time System (Bio-Rad, CA, USA). The diagnostic call of each specimen was provided based on Ct values calculated by built-in system software. Results and Discussion Working Principle of the SHIAG Reaction for Detecting SARS-CoV-2 The working principle of the SHIAG reaction for detecting SARS-CoV-2 is depicted in Scheme 1. The core element actuating the SHIAG reaction is the uniquely designed HP containing four functional domains: target binding region in stem and loop (black domain), self-priming region along the 3′ end (red and purple domain), and nicking endonuclease recognition site (orange domain) and G-rich sequence template at the 5′ overhang (blue domain). Scheme 1 Schematic Illustration of the SHIAG Reaction for Detecting SARS-CoV-2 In the absence of target RNA, HP maintains its stable hairpin structure in the solution as the self-primer region is caged within the hairpin stem region, and no following enzymatic reactions proceed. In the presence of target RNA, however, the target binding region of HP hybridizes with target RNA, which would disrupt its hairpin structure and rearrange its 3′-end to be self-primed. The self-primed 3′ end is then extended by DNA polymerase to produce a dsDNA intermediate product (IP). During the extension, target RNA is concomitantly displaced and recycled to open another HP. Owing to the presence of a nicking endonuclease recognition site within IP, continuously repeated nicking and extension reactions would be promoted through the combined activity of nicking endonuclease and DNA polymerase, consequently generating abundant G-rich sequences. The G-rich sequences finally produce the significantly enhanced fluorescence signals by forming G-quadruplex structures and specifically interacting with ThT, which can be used to identify target RNAs. Feasibility of the SHIAG Reaction for Detecting SARS-CoV-2 The detection feasibility of the SHIAG reaction was verified by recording the fluorescence emission spectra obtaining from the reactions under diverse combinations of reaction elements (Figure 1a). First, when the sample contained neither target RNA and nicking endonuclease, the HP just kept its initial structure and no following enzymatic reactions proceeded as evidenced by a very negligible fluorescence signal (curve 1). Even when target RNA was additionally applied, the fluorescence signal remained negligible in the absence of nicking endonuclease (curve 2) because free G-rich sequences cannot be produced from the IP without the action of nicking endonuclease. Most importantly, significant fluorescence enhancement was detected when all reaction elements including HP, nicking endonuclease, and DNA polymerase were applied to the positive sample containing target RNA (curve 4), which was quite coincident with the case where the synthetic G-rich sequences were externally introduced to ThT (curve 5). Notably, a marginal nonspecific fluorescence signal was detected from the negative sample without target RNA but containing all the reaction elements, indicating that the HP might be slightly rearranged to actuate the reaction even without the interaction of target RNA, which could be a limitation of the proposed strategy. Nevertheless, the specific signal obtained from target RNA was far greater and more than enough to be clearly discriminated from the nonspecific signal. The results indicate that target RNA is exclusively responsible to initiate the reaction, and nicking endonuclease and also DNA polymerase are imperative to promote the whole reaction to produce G-rich sequences, which would lead to significantly enhanced fluorescence signals through specific interaction with ThT. Figure 1 Feasibility of the SHIAG reaction for detecting SARS-CoV-2 RNA. (a) Fluorescence emission spectra of ThT under various combinations of reaction elements. (1) HP + Bst + ThT, (2) HP + target RNA + Bst + ThT, (3) HP + Bst + Nt.BstNBI + ThT, (4) HP + target RNA + Bst + Nt.BstNBI + ThT, (5) G-rich sequence + ThT. The final concentrations of target RNA, HP, Bst, Nt.BstNBI, and ThT are 1 nM, 25 nM, 0.08 U/μL, 0.08 U/μL, and 25 μM, respectively. (b) PAGE image of the SHIAG reaction products. L: ultra-low range ladder, (1) target RNA, (2) HP, (3) G-rich sequence, (4) HP + target RNA, (5) HP + target RNA + Bst, (6) HP + Bst, (7) HP + target RNA + Bst + Nt.BstNBI, (8) HP + Bst + Nt.BstNBI. The final concentrations of target RNA, HP, Bst, and Nt.BstNBI are 200 nM, 500 nM, 0.16 U/μL, and 0.16 U/μL, respectively. In this study, synthetic 40-mer RNA (Table S1) was used as target RNA. We additionally carried out the PAGE assay for the reaction elements and products generated from the SHIAG reaction (Figure 1b) to further support the results from the fluorescence emission spectra. First, the intense band corresponding to the IP was correctly observed when the samples contained the three elements required for the production of IP, such as HP, target RNA, and DNA polymerase (lane 5 and lane 7). On the other hand, the initially applied HP was just kept unextended and no band for the IP was observed when either DNA polymerase (lane 4) or target RNA (lane 6 and lane 8) was omitted. Most importantly, an intense band corresponding to the free G-rich sequence, the final product of the SHIAG reaction was clearly observed only from the solution comprising all the reaction elements including HP, nicking endonuclease, DNA polymerase, and target RNA (lane 7). Collectively, these results verify that the SHIAG reaction is efficiently actuated by target RNAs and works effectively as envisioned by the mechanism in Scheme 1. Sensitivity of the SHIAG Reaction for SARS-CoV-2 Detection To maximize the performance of the SHIAG reaction, we optimized the reaction conditions by monitoring the fluorescence enhancement generated from the SHIAG reactions as (F – F0)/F0, where the fluorescence intensities at 496 nm of the reaction solutions without and with target RNA are indicated as F0 and F, respectively. As shown in Figures S1–S7, 37 °C, 25 nM HP, 0.5× ThermoPol reaction buffer, 0.75× NEBuffer 3.1, 0.08 U/μL of Bst, and 0.08 U/μL of Nt.BstNBI, 60 min were optimal, which were employed throughout further assays. To evaluate the sensitivity of the SHIAG reaction, the reaction was conducted by employing target gRNA at various concentrations (0–10 pM) and the resulting fluorescence signals were analyzed. As presented in Figure 2a, the fluorescence intensity enhanced as concentration of SARS-CoV-2 gRNA increased, and an excellent linear relationship (F496 = 377.63 log(Ctarget(fM)) + 2173.9, R2 = 0.99) was detected in the range of 1 fM to 10 pM when fluorescence intensity at 496 nm (F496) was plotted as a function of logarithmic SARS-CoV-2 gRNA concentration (Figure 2b), revealing that the proposed method is fully capable for the quantitative identification of SARS-CoV-2 gRNA. The limit of detection (LOD) was determined to be 0.19 fM (114 copies/μL) based on the equation: LOD = 3σ/S, where the standard deviation of the blank and the slope of the calibration line are indicated as σ and S, respectively. The LOD is comparable to those from previous SARS-CoV-2 detection methods (Table 1). As shown in Table 1, the SHIAG reaction is capable of SARS-CoV-2 detection without involving any exogenous primers, multiple probes, prior labelings, and thermal cycling, remarkably simplifying the detection procedure and presenting prominent advantages over previous methods. Figure 2 Sensitivity of the SHIAG reaction for detecting SARS-CoV-2 gRNA. (a) Fluorescence emission spectra and (b) fluorescence intensity at 496 nm (F496) obtained from the SHIAG reactions with SARS-CoV-2 gRNA at various concentrations (0–10 pM). Inset in panel (b): linear relationship between F496 and logarithmic SARS-CoV-2 gRNA concentration (1 fM-10 pM). Error bars were calculated from triplicate experiments. Table 1 Comparison of SHIAG Method with Previous SARS-CoV-2 Detection Methods methods limit of detection (copies/μL) limitations reference qRT-PCR 1.25 requirement for reverse-transcription step and thermal cycler (52) RT-LAMP 100 requirement for multiple primers (53,54) RT-LAMP 100/158 requirement for multiple primers (55) RT-LAMP 50 requirement for multiple primers (56) RT-LAMP 0.2–2 requirement for multiple primers (57) paper COV-ID 380 requirement for multiple primers and long preparation time (58) RT-LAMP-Cas12 10 requirement for multiple primers and CRISPR-Cas12a system (59) all-in-one dual CRISPR-Cas12a 5 requirement for multiple primers and CRISPR-Cas12a system (60) RT-LAMP-Cas13 25 requirement for multiple primers and CRISPR-Cas13a system (61) EXPAR 72.6 false-positive signal (62) CHA 2.5 × 107 low sensitivity (63) NISDA 10 labeling with fluorophore and quencher (64) SHIAG 114 marginal nonspecific signal This work Specificity of the SHIAG Reaction for SARS-CoV-2 Detection The detection specificity of the SHIAG reaction for SARS-CoV-2 detection was next analyzed through comparing the fluorescence enhancement obtained from target SARS-CoV-2 gRNA with those from other types of HCoV gRNAs including SARS-CoV gRNA, HCoV-HKU-1 gRNA, HCoV-OC43 gRNA, HCoV-NL63 gRNA, HCoV-229E gRNA, and MERS-CoV gRNA. As shown in Figure 3, significantly enhanced fluorescence was examined only from target SARS-CoV-2 gRNA, while only negligible fluorescence enhancement was observed from all non-target gRNAs. The results verify that the specific binding between the HP and target RNA needs to be essentially proceeded to properly promote the SHIAG reaction, ensuring the excellent specificity of the SHIAG reaction only toward the target RNA. Figure 3 Specificity of the SHIAG reaction for detecting SARS-CoV-2 gRNA. Fluorescence enhancement ((F – F0)/F0, where the fluorescence intensities at 496 nm without and with gRNAs are indicated as F0 and F, respectively) obtained from the SHIAG reactions with SARS-CoV-2 gRNA or other non-target gRNAs including SARS-CoV gRNA, HCoV-HKU-1 gRNA, HCoV-OC43 gRNA, HCoV-NL63 gRNA, HCoV-229E gRNA, and MERS-CoV gRNA. The concentration of each type of gRNA is 1 pM. Error bars were calculated from triplicate experiments. Clinical Applicability of the SHIAG Reaction The clinical applicability of the SHIAG reaction was lastly demonstrated by monitoring the fluorescence signals resulting from the reactions with gRNAs extracted from real clinical nasopharyngeal swab and sputum specimens (n = 100). As shown in Figure 4a, 68 specimens among total 100 specimens produced significant fluorescence increases from the SHIAG reactions and were called positive based on the general threshold guideline of background + 5SD, where the background and SD represent the average fluorescence enhancement of the blank and the standard deviation of the blank, respectively.65 The remaining 32 specimens produced only very negligible fluorescence increases and were called negative. All the fluorescence increase (F – F0)/F0 values for 100 clinical specimens were displayed in the corresponding heat map to more vividly visualize the results by color (Figure 4b), which further manifests the clear discrimination of positive specimens against negative specimens. We also conducted the testing for the same 100 clinical specimens but using the current gold standard qRT-PCR method. As the results presented in Table 2 and Table S2, the qRT-PCR identified the same 68 specimens as positive and the same 32 specimens as negative, which fully agreed with the SHIAG method. By using the diagnostic call from qRT-PCR as reference, the SHIAG reaction successfully confirmed all the 100 clinical specimens with 100% clinical sensitivity and specificity, verifying that the proposed strategy could reliably test COVID-19 specimens in practical clinical applications and could replace the current qRT-PCR. Figure 4 Clinical specimen analysis with the SHIAG reaction. (a) Fluorescence enhancement ((F – F0)/F0, where the fluorescence intensities at 496 nm without and with gRNAs extracted from clinical specimens are indicated as F0 and F, respectively) obtained from the SHIAG reactions with 100 nasopharyngeal swab and sputum specimens. The threshold is calculated as background + 5SD, where the background represents the average fluorescence enhancement of the blank and SD represents the standard deviation of the blank, which was used to call specimens positive (1–68) or negative (69–100). Error bars were calculated from triplicate experiments. (b) Heat map of (F – F0)/F0 values from testing on 100 clinical specimens using the SHIAG reaction. Table 2 Clinical Specimen Analysis for 68 Positive and 32 Negative Cases with qRT-PCR and the SHIAG Method diagnostic parameter   qRT-RCR SHIAG positive true 68 68   false     negative true 32 32   false             sensitivity (%)   100 100 (95% CI%)a   (94.72–100) (94.72–100)         specificity (%)   100 100 (95% CI%)a   (89.11–100) (89.11–100) a Confidence interval (MedCalc software, version 20.027). Conclusions The development of testing methods to accurately and rapidly identify infected individuals at scale is an urgent goal to efficiently contain the current COVID-19 pandemic. We herein proposed a new isothermal amplification strategy termed the SHIAG reaction and successfully identified SARS-CoV-2 gRNA as low as 0.19 fM (114 copies/μL) with excellent selectivity. The clinical capability of the SHIAG reaction was further verified by reliably testing 100 clinical specimens with 100% clinical sensitivity and specificity, confirming its robust clinical applicability. The SHIAG reaction described in this work yields several distinct advantages for nucleic acid detection. First, due to the unique design of the HP possessing the elemental fractions to enable from the initial self-priming to the final signaling, the final fluorescent signals could be produced instantly upon its binding to target RNA without involving any exogenous primers but only a single HP is enough to actuate the whole isothermal process. Second, the SHIAG reaction continuously displaces and recycles the bound target RNA, consequently achieving ultrasensitive detection for target RNA even under the isothermal condition. Third, the final G-rich sequences produced through continuously repeated nicking and extension reactions produce the signal just by interacting with ThT, eliminating the need for any prior labelings. This technique could be generally applied to identify other pathogens by simply redesigning the flexible HP sequence according to the target and thereby has a great potential to be a new robust isothermal tool enabling facile molecular testing of new emerging pathogens. Supporting Information Available The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.analchem.2c03442.Sequence information (Table S1); qRT-PCR results of clinical samples (Table S2); optimization of the SARS-CoV-2 detection method (Figures S1–S7) (PDF) Supplementary Material ac2c03442_si_001.pdf Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. The authors declare no competing financial interest. Acknowledgments This research was supported by the Mid-career Researcher Support Program of the National Research Foundation (NRF) funded by MSIT of Korea (NRF-2021R1A2B5B03001739) and KRIBB Research Initiative Program (1711134081). This research was also supported by the Korean National Police Agency (Project Name: Development of visualization technology for biological evidence in crime scenes based on nano-biotechnology/Project Number: PA-K000001-2019-101). ==== Refs References WHO-Statement. WHO Timeline - COVID-19. 2020. https://www.who.int/news-room/detail/27-04-2020-who-timeline---covid-19 (accessed 2020 April). WHO. WHO Coronavirus (COVID-19) Dashboard. 2022. https://covid19.who.int/ (accessed 2022 April). Petersen E. ; Koopmans M. ; Go U. ; Hamer D. H. ; Petrosillo N. ; Castelli F. ; Storgaard M. ; Al Khalili S. ; Simonsen L. Comparing SARS-CoV-2 with SARS-CoV and influenza pandemics. Lancet Infect. Dis. 2020, 20 , e238–e244. 10.1016/S1473-3099(20)30484-9.32628905 Abdelrahman Z. ; Li M. ; Wang X. Comparative review of SARS-CoV-2, SARS-CoV, MERS-CoV, and Influenza A respiratory viruses. Front. Immunol. 2020, 11 , 552909 10.3389/fimmu.2020.552909.33013925 Shang J. ; Wan Y. ; Luo C. ; Ye G. ; Geng Q. ; Auerbach A. ; Li F. Cell entry mechanisms of SARS-CoV-2. Proc. Natl. Acad. Sci. U. S. A. 2020, 117 , 11727–11734. 10.1073/pnas.2003138117.32376634 Mao K. ; Zhang H. ; Yang Z. Can a paper-based device trace COVID-19 sources with wastewater-based epidemiology?. Environ. Sci. Technol. 2020, 54 , 3733–3735. 10.1021/acs.est.0c01174.32202421 Campbell F. ; Archer B. ; Laurenson-Schafer H. ; Jinnai Y. ; Konings F. ; Batra N. ; Pavlin B. ; Vandemaele K. ; Van Kerkhove M. D. ; Jombart T. ; et al. Increased transmissibility and global spread of SARS-CoV-2 variants of concern as at June 2021. Eurosurveillance 2021, 26 , 2100509.34142653 Lyngse F. P. ; Molbak K. ; Skov R. L. ; Christiansen L. E. ; Mortensen L. H. ; Albertsen M. ; Moller C. H. ; Krause T. G. ; Rasmussen M. ; Michaelsen T. Y. ; et al. Increased transmissibility of SARS-CoV-2 lineage B.1.1.7 by age and viral load. Nat. Commun. 2021, 12 , 7251 10.1038/s41467-021-27202-x.34903718 WHO-Departmental News. Tracking SARS-CoV-2 variants. 2022. https://www.who.int/en/activities/tracking-SARS-CoV-2-variants/ (accessed 2022 April). Callaway E. ; Ledford H. How bad is Omicron? What scientists know so far. Nature 2021, 600 , 197–199. 10.1038/d41586-021-03614-z.34857948 Kupferschmidt K. ; Vogel G. COVID-19 How bad is Omicron? Some clues are emerging. Science 2021, 374 , 1304–1305. 10.1126/science.acx9782.34882443 CDC. Omicron variant: what you need to know. 2022. https://www.cdc.gov/coronavirus/2019-ncov/variants/omicron-variant.html (accessed 2022 March). Edwards K. M. ; Orenstein W. A. COVID-19: Vaccines to prevent SARS-CoV-2 infection. 2022. https://www.uptodate.com/contents/covid-19-vaccines-to-prevent-sars-cov-2-infection (accessed 2022 April). Maragakis L. ; Kelen G. D. Breakthrough infections: Coronavirus after vaccination. 2021. https://www.hopkinsmedicine.org/health/conditions-and-diseases/coronavirus/breakthrough-infections-coronavirus-after-vaccination (accessed 2021 November). WHO-Science Conversation. Can I get infected after vaccination? 2021. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/media-resources/science-in-5/episode-49-can-i-get-infected-after-vaccination (accessed 2021 August). Garcia-Beltran W. F. ; St Denis K. J. ; Hoelzemer A. ; Lam E. C. ; Nitido A. D. ; Sheehan M. L. ; Berrios C. ; Ofoman O. ; Chang C. C. ; Hauser B. M. ; et al. mRNA-based COVID-19 vaccine boosters induce neutralizing immunity against SARS-CoV-2 Omicron variant. Cell 2022, 185 , 457–466. 10.1016/j.cell.2021.12.033.34995482 Kuhlmann C. ; Mayer C. K. ; Claassen M. ; Maponga T. ; Burgers W. A. ; Keeton R. ; Riou C. ; Sutherland A. D. ; Suliman T. ; Shaw M. L. ; et al. Breakthrough infections with SARS-CoV-2 omicron despite mRNA vaccine booster dose. Lancet 2022, 399 , 625–626. 10.1016/S0140-6736(22)00090-3.35063123 Zhou R. ; To K. K. ; Peng Q. ; Chan J. M. ; Huang H. ; Yang D. ; Lam B. H. ; Chuang V. W. ; Cai J. P. ; Liu N. ; Au K. K. ; Tsang O. T. ; Yuen K. Y. ; Chen Z. Vaccine-breakthrough infection by the SARS-CoV-2 omicron variant elicits broadly cross-reactive immune responses. Clin. Transl. Med. 2022, 12 , e720 10.1002/ctm2.720.35083867 Hellewell J. ; Abbott S. ; Gimma A. ; Bosse N. I. ; Jarvis C. I. ; Russell T. W. ; Munday J. D. ; Kucharski A. J. ; Edmunds W. J. ; et al. Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. Lancet Glob. Health 2020, 8 , e488–e496. 10.1016/S2214-109X(20)30074-7.32119825 Taleghani N. ; Taghipour F. Diagnosis of COVID-19 for controlling the pandemic: A review of the state-of-the-art. Biosens. Bioelectron. 2021, 174 , 112830 10.1016/j.bios.2020.112830.33339696 Binnicker M. J. Emergence of a novel coronavirus disease (COVID-19) and the importance of diagnostic testing: Why partnership between clinical laboratories, public health agencies, and industry is essential to control the outbreak. Clin. Chem. 2020, 66 , 664–666. 10.1093/clinchem/hvaa071.32077933 Corman V. M. ; Landt O. ; Kaiser M. ; Molenkamp R. ; Meijer A. ; Chu D. K. ; Bleicker T. ; Brunink S. ; Schneider J. ; Schmidt M. L. ; et al. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Eurosurveillance 2020, 25 , 2000045.31992387 Freeman W. M. ; Walker S. J. ; Vrana K. E. Quantitative RT-PCR: pitfalls and potential. BioTechniques 1999, 26 , 112–125. 124-125 10.2144/99261rv01.9894600 Tang Y. W. ; Schmitz J. E. ; Persing D. H. ; Stratton C. W. Laboratory diagnosis of COVID-19: Current issues and challenges. J. Clin. Microbiol. 2020, 58 , e00512–e00520.32245835 Carter L. J. ; Garner L. V. ; Smoot J. W. ; Li Y. ; Zhou Q. ; Saveson C. J. ; Sasso J. M. ; Gregg A. C. ; Soares D. J. ; Beskid T. R. ; et al. Assay techniques and test development for COVID-19 diagnosis. ACS Cent. Sci. 2020, 6 , 591–605. 10.1021/acscentsci.0c00501.32382657 Lee H. N. ; Lee J. ; Kang Y. K. ; Lee J. H. ; Yang S. ; Chung H. J. A lateral flow assay for nucleic acid detection based on rolling circle amplification using capture ligand-modified oligonucleotides. BioChip J. 2022, 1–10. Obande G. A. ; Banga Singh K. K. Current and future perspectives on isothermal nucleic acid amplification technologies for diagnosing infections. Infect. Drug Resist. 2020, Volume 13 , 455–483. 10.2147/IDR.S217571. Zhu X. ; Wang X. ; Han L. ; Chen T. ; Wang L. ; Li H. ; Li S. ; He L. ; Fu X. ; Chen S. ; et al. Multiplex reverse transcription loop-mediated isothermal amplification combined with nanoparticle-based lateral flow biosensor for the diagnosis of COVID-19. Biosens. Bioelectron. 2020, 166 , 112437 10.1016/j.bios.2020.112437.32692666 Subsoontorn P. ; Lohitnavy M. ; Kongkaew C. The diagnostic accuracy of isothermal nucleic acid point-of-care tests for human coronaviruses: A systematic review and meta-analysis. Sci. Rep. 2020, 10 , 22349 10.1038/s41598-020-79237-7.33339871 Guatelli J. C. ; Whitfield K. M. ; Kwoh D. Y. ; Barringer K. J. ; Richman D. D. ; Gingeras T. R. Isothermal, in vitro amplification of nucleic acids by a multienzyme reaction modeled after retroviral replication. Proc. Natl. Acad. Sci. U. S. A. 1990, 87 , 1874–1878. 10.1073/pnas.87.5.1874.2308948 Compton J. Nucleic acid sequence-based amplification. Nature 1991, 350 , 91–92. 10.1038/350091a0.1706072 Walker G. T. ; Little M. C. ; Nadeau J. G. ; Shank D. D. Isothermal in vitro amplification of DNA by a restriction enzyme/DNA polymerase system. Proc. Natl. Acad. Sci. U. S. A. 1992, 89 , 392–396. 10.1073/pnas.89.1.392.1309614 Walker G. T. ; Fraiser M. S. ; Schram J. L. ; Little M. C. ; Nadeau J. G. ; Malinowski D. P. Strand displacement amplification--an isothermal, in vitro DNA amplification technique. Nucleic Acids Res. 1992, 20 , 1691–1696. 10.1093/nar/20.7.1691.1579461 Notomi T. ; Okayama H. ; Masubuchi H. ; Yonekawa T. ; Watanabe K. ; Amino N. ; Hase T. Loop-mediated isothermal amplification of DNA. Nucleic Acids Res. 2000, 28 , E63 10.1093/nar/28.12.e63.10871386 Hong T. C. ; Mai Q. L. ; Cuong D. V. ; Parida M. ; Minekawa H. ; Notomi T. ; Hasebe F. ; Morita K. Development and evaluation of a novel loop-mediated isothermal amplification method for rapid detection of severe acute respiratory syndrome coronavirus. J. Clin. Microbiol. 2004, 42 , 1956–1961.15131154 Fire A. ; Xu S. Q. Rolling replication of short DNA circles. Proc. Natl. Acad. Sci. U. S. A. 1995, 92 , 4641–4645. 10.1073/pnas.92.10.4641.7753856 Harcourt E. M. ; Kool E. T. Amplified microRNA detection by templated chemistry. Nucleic Acids Res. 2012, 40 , e65 10.1093/nar/gkr1313.22278881 Kim H. Y. ; Song J. ; Park H. G. Ultrasensitive isothermal method to detect microRNA based on target-induced chain amplification reaction. Biosens. Bioelectron. 2021, 178 , 113048 10.1016/j.bios.2021.113048.33550160 Ju Y. ; Kim J. ; Park Y. ; Lee C. Y. ; Kim K. ; Hong K. H. ; Lee H. ; Yong D. ; Park H. G. Rapid and accurate clinical testing for COVID-19 by nicking and extension chain reaction system-based amplification (NESBA). Biosens. Bioelectron. 2022, 196 , 113689 10.1016/j.bios.2021.113689.34688112 Song J. ; Kim H. Y. ; Kim S. ; Jung Y. ; Park H. G. Self-priming phosphorothioated hairpin-mediated isothermal amplification. Biosens. Bioelectron. 2021, 178 , 113051 10.1016/j.bios.2021.113051.33548651 Ju Y. ; Kim H. Y. ; Ahn J. K. ; Park H. G. Ultrasensitive version of nucleic acid sequence-based amplification (NASBA) utilizing a nicking and extension chain reaction system. Nanoscale 2021, 13 , 10785–10791. 10.1039/D1NR00564B.34076022 Song J. Y. ; Jung Y. ; Lee S. ; Park H. G. Self-priming hairpin-utilized isothermal amplification enabling ultrasensitive nucleic acid detection. Anal. Chem. 2020, 92 , 10350–10356. 10.1021/acs.analchem.0c00511.32551503 Ganguli A. ; Ornob A. ; Yu H. ; Damhorst G. L. ; Chen W. ; Sun F. ; Bhuiya A. ; Cunningham B. T. ; Bashir R. Hands-free smartphone-based diagnostics for simultaneous detection of Zika, Chikungunya, and Dengue at point-of-care. Biomed. Microdevices 2017, 19 , 73 10.1007/s10544-017-0209-9.28831630 Dhama K. ; Karthik K. ; Chakraborty S. ; Tiwari R. ; Kapoor S. ; Kumar A. ; Thomas P. Loop-mediated isothermal amplification of DNA (LAMP): a new diagnostic tool lights the world of diagnosis of animal and human pathogens: a review. Pak. J. Biol. Sci. 2014, 17 , 151–166. 10.3923/pjbs.2014.151.166.24783797 Dirks R. M. ; Pierce N. A. Triggered amplification by hybridization chain reaction. Proc. Natl. Acad. Sci. U. S. A. 2004, 101 , 15275–15278. 10.1073/pnas.0407024101.15492210 Yin P. ; Choi H. M. ; Calvert C. R. ; Pierce N. A. Programming biomolecular self-assembly pathways. Nature 2008, 451 , 318–322. 10.1038/nature06451.18202654 Mori Y. ; Notomi T. Loop-mediated isothermal amplification (LAMP): a rapid, accurate, and cost-effective diagnostic method for infectious diseases. J. Infect. Chemother. 2009, 15 , 62–69. 10.1007/s10156-009-0669-9.19396514 Watts M. R. ; James G. ; Sultana Y. ; Ginn A. N. ; Outhred A. C. ; Kong F. ; Verweij J. J. ; Iredell J. R. ; Chen S. C. ; Lee R. A loop-mediated isothermal amplification (LAMP) assay for Strongyloides stercoralis in stool that uses a visual detection method with SYTO-82 fluorescent dye. Am. J. Trop. Med. Hyg. 2014, 90 , 306–311. 10.4269/ajtmh.13-0583.24323513 Deiman B. ; van Aarle P. ; Sillekens P. Characteristics and applications of nucleic acid sequence-based amplification (NASBA). Mol. Biotechnol. 2002, 20 , 163–180. 10.1385/MB:20:2:163.11876473 Loens K. ; Ursi D. ; Ieven M. ; van Aarle P. ; Sillekens P. ; Oudshoorn P. ; Goossens H. Detection of Mycoplasma pneumoniae in spiked clinical samples by nucleic acid sequence-based amplification. J. Clin. Microbiol. 2002, 40 , 1339–1345. 10.1128/JCM.40.4.1339-1345.2002.11923354 Jang M. ; Kim S. Inhibition of non-specific amplification in loop-mediated isothermal amplification via tetramethylammonium chloride. BioChip J. 2022, 16 , 326–333. 10.1007/s13206-022-00070-3.35909465 Farfour E. ; Lesprit P. ; Visseaux B. ; Pascreau T. ; Jolly E. ; Houhou N. ; Mazaux L. ; Asso-Bonnet M. ; Vasse M. ; The Allplex 2019-nCoV (Seegene) assay: which performances are for SARS-CoV-2 infection diagnosis?. Eur. J. Clin. Microbiol. Infect. Dis. 2020, 39 , 1997–2000. 10.1007/s10096-020-03930-8.32462501 Baek Y. H. ; Um J. ; Antigua K. J. C. ; Park J. H. ; Kim Y. ; Oh S. ; Kim Y. I. ; Choi W. S. ; Kim S. G. ; Jeong J. H. ; Chin B. S. ; Nicolas H. D. G. ; Ahn J. Y. ; Shin K. S. ; Choi Y. K. ; Park J. S. ; Song M. S. Development of a reverse transcription-loop-mediated isothermal amplification as a rapid early-detection method for novel SARS-CoV-2. Emerg. Microbes. Infect. 2020, 9 , 998–1007. 10.1080/22221751.2020.1756698.32306853 Mautner L. ; Baillie C. K. ; Herold H. M. ; Volkwein W. ; Guertler P. ; Eberle U. ; Ackermann N. ; Sing A. ; Pavlovic M. ; Goerlich O. ; et al. Rapid point-of-care detection of SARS-CoV-2 using reverse transcription loop-mediated isothermal amplification (RT-LAMP). Virol. J. 2020, 17 , 160 10.1186/s12985-020-01435-6.33087160 Odiwuor N. ; Xiong J. ; Ogolla F. ; Hong W. ; Li X. H. ; Khan F. M. ; Wang N. U. ; Yu J. P. ; Wei H. P. A point-of-care SARS-CoV-2 test based on reverse transcription loop-mediated isothermal amplification without RNA extraction with diagnostic performance same as RT-PCR. Anal. Chim. Acta 2022, 1200 , 339590 10.1016/j.aca.2022.339590.35256137 Rabe B. A. ; Cepko C. SARS-CoV-2 detection using isothermal amplification and a rapid, inexpensive protocol for sample inactivation and purification. Proc. Natl. Acad. Sci. U. S. A. 2020, 117 , 24450–24458. 10.1073/pnas.2011221117.32900935 Song J. ; El-Tholoth M. ; Li Y. ; Graham-Wooten J. ; Liang Y. ; Li J. ; Li W. ; Weiss S. R. ; Collman R. G. ; Bau H. H. Single- and two-stage, closed-tube, point-of-care, molecular detection of SARS-CoV-2. Anal. Chem. 2021, 93 , 13063–13071. 10.1021/acs.analchem.1c03016.34541844 Warneford-Thomson R. ; Shah P. P. ; Lundgren P. ; Lerner J. ; Morgan J. ; Davila A. ; Abella B. S. ; Zaret K. ; Schug J. ; Jain R. ; et al. A LAMP sequencing approach for high-throughput co-detection of SARS-CoV-2 and influenza virus in human saliva. Elife 2022, 11 , e69949 10.7554/eLife.69949.35532013 Broughton J. P. ; Deng X. D. ; Yu G. X. ; Fasching C. L. ; Servellita V. ; Singh J. ; Miao X. ; Streithorst J. A. ; Granados A. ; Sotomayor-Gonzalez A. ; et al. CRISPR-Cas12-based detection of SARS-CoV-2. Nat. Biotechnol. 2020, 38 , 870–874. 10.1038/s41587-020-0513-4.32300245 Ding X. ; Yin K. ; Li Z. Y. ; Lalla R. V. ; Ballesteros E. ; Sfeir M. M. ; Liu C. C. Ultrasensitive and visual detection of SARS-CoV-2 using all-in-one dual CRISPR-Cas12a assay. Nat. Commun. 2020, 11 , 4711 10.1038/s41467-020-18575-6.32948757 Agrawal S. ; Fanton A. ; Chandrasekaran S. S. ; Charrez B. ; Escajeda A. M. ; Son S. ; McIntosh R. ; Bhuiya A. ; de Leon Derby M. D. ; Switz N. A. ; et al. Rapid, point-of-care molecular diagnostics with Cas13. medRxiv 2021. Carter J. G. ; Iturbe L. O. ; Duprey J. L. H. A. ; Carter I. R. ; Southern C. D. ; Rana M. ; Whalley C. M. ; Bosworth A. ; Beggs A. D. ; Hicks M. R. ; et al. Ultrarapid detection of SARS-CoV-2 RNA using a reverse transcription-free exponential amplification reaction, RTF-EXPAR. Proc. Natl. Acad. Sci. U. S. A. 2021, 118 , e2100347118 10.1073/pnas.2100347118.34400545 Do J. Y. ; Jeong J. Y. ; Hong C. A. Catalytic hairpin DNA assembly-based chemiluminescent assay for the detection of short SARS-CoV-2 target cDNA. Talanta 2021, 233 , 122505 10.1016/j.talanta.2021.122505.34215120 Mohammadniaei M. ; Zhang M. ; Ashley J. ; Christensen U. B. ; Friis-Hansen L. J. ; Gregersen R. ; Lisby J. G. ; Benfield T. L. ; Nielsen F. E. ; Henning Rasmussen J. ; et al. A non-enzymatic, isothermal strand displacement and amplification assay for rapid detection of SARS-CoV-2 RNA. Nat. Commun. 2021, 12 , 5089 10.1038/s41467-021-25387-9.34429424 Fotis C. ; Meimetis N. ; Tsolakos N. ; Politou M. ; Akinosoglou K. ; Pliaka V. ; Minia A. ; Terpos E. ; Trougakos I. P. ; Mentis A. ; et al. Accurate SARS-CoV-2 seroprevalence surveys require robust multi-antigen assays. Sci. Rep. 2021, 11 , 6614 10.1038/s41598-021-86035-2.33758278
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==== Front J Psychosom Res J Psychosom Res Journal of Psychosomatic Research 0022-3999 1879-1360 Published by Elsevier Inc. S0022-3999(22)00402-0 10.1016/j.jpsychores.2022.111117 111117 Letter to the Editor Social communication pathways to COVID-19 vaccine side-effect correspondence Sookaromdee Pathum a⁎ Wiwanitkit Viroj b a Private Academic Consultant, Bangkok, Thailand b Dr DY Patil Vidhyapeeth, Pune, India ⁎ Corresponding author. 12 12 2022 12 12 2022 11111721 11 2022 9 12 2022 10 12 2022 © 2022 Published by Elsevier Inc. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. ==== Body pmc
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==== Front Can J Cardiol Can J Cardiol The Canadian Journal of Cardiology 0828-282X 1916-7075 Canadian Cardiovascular Society. Published by Elsevier Inc. S0828-282X(22)01092-3 10.1016/j.cjca.2022.12.003 Clinical Research One-Year Risk of myocarditis after COVID-19 infection: a systematic review and meta-analysis Zuin Marco MD FESC FACC FANMCO 12# Rigatelli Gianluca MD PhD FACC FSCAI 3 Bilato Claudio MD PhD 1 Porcari Aldostefano MD, FISC 45 Merlo Marco MD 45 Roncon Loris MD 6 Sinagra Gianfranco MD FESC 45 1 Department of Cardiology, West Vicenza Hospital, Arzignano, Vicenza, Italy 2 Department of Translational Medicine, University of Ferrara, Ferrara, Italy 3 Department of Cardiology, Ospedali Riuniti Padova Sud, Padova, Italy 4 Center for Diagnosis and Treatment of Cardiomyopathies, Cardiovascular Department, Azienda Sanitaria Universitaria Giuliano-Isontina (ASUGI), University of Trieste, Trieste 5 European Reference Network for Rare, Low Prevalence and Complex Diseases of the Heart-ERNGUARD-Heart 6 Department of Cardiology, Santa Maria della Misericordia Hospital, Rovigo, Italy # Corresponding author: Dr Marco Zuin, MD FESC FACC FANMCO, Department of Translational Medicine, University of Ferrara, Via Aldo Moro 8, 44124 Ferrara, Italy. 12 12 2022 12 12 2022 24 10 2022 22 11 2022 7 12 2022 © 2022 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved. 2022 Canadian Cardiovascular Society Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Background Acute myocarditis has been described as a relatively rare cardiovascular complication of COVID-19 infection. However, data regarding the risk of myocarditis during the post-acute phase of COVID-19 are scant. We assess the risk of incident myocarditis in COVID-19 survivors within one year from the index infection by a systematic review and meta-analysis of the available data. Methods Data were obtained searching MEDLINE and Scopus for all studies published at any time up to September 1, 2022, and reporting the long-term risk of incident myocarditis in COVID-19 survivors. Myocarditis risk data were pooled using the Mantel–Haenszel random effects models with Hazard ratio (HR) as the effect measure with 95% confidence interval (CI). Heterogeneity among studies was assessed using Higgins and Thomson I2 statistic. Results Overall, 20.875.843 patients (mean age 56.1 years, 59.1% males) were included in this analysis. Of them, 1.245.167 survived to COVID-19 infection. Over a mean follow-up of 9.5 months, myocarditis occurred to 0.21 [95% CI: 0.13- 0.42) out of 1000 patients survived to COVID-19 infection compared to 0.09 [95% CI: 0.07-0.12] out of 1000 control subjects. Pooled analysis revealed that recovered COVID-19 patients presented an increased risk of incident myocarditis (HR: 5.16, 95% CI: 3.87-6.89, p<0.0001, I2=7.9%) within one year from the index infection. The sensitivity analysis confirmed yielded results. Conclusion Our findings suggest that myocarditis represents a relatively rare but important post-acute COVID-19 sequelae. Graphical abstract Key words COVID-19 Long COVID Myocarditis follow-up ==== Body pmcIntroduction Acute myocarditis (AM) has been described as a relatively rare complication of COVID-19 infection [1]. Viral infections are a common cause of acute myocarditis, due to a combination of direct cellular injury and T-cell cytotoxicity pointed at the myocardium, which can be amplified by the cytokine storm syndrome, as described in SARS-CoV-2 infection [2, 3, 4]. Recent analyses have mainly focused on the potential pathophysiological mechanisms and occurrence of AM either as a complication of the infection during the acute phase of disease or after the administration of COVID-19 vaccines [5, 6, 7, 8]. Conversely, few studies have investigated the risk of myocarditis following the index SARS-CoV-2 infection and the estimation of potential post-acute COVID-19 myocarditis represents a major knowledge-gap to be addressed. Therefore, the aim of the present manuscript is to assess the risk of incident myocarditis in COVID-19 survivors within one year from the index infection by a systematic review and meta-analysis of the available data. Material and Methods Study design This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline (Supplemental Table S1) [9]. Data were obtained searching MEDLINE and Scopus for all studies published at any time up to September 1, 2022 and reporting the long-term risk of incident myocarditis in COVID-19 survivors diagnosed between 4 months (minimum follow-up length of revised investigations) and a maximum of 12 months post discharge (maximum follow-up length of revised studies) after index infection. In the revised manuscripts, this group of patients were compared to contemporary cohorts, defined as subjects who did not experience the SARS-CoV-2 infection and developed an AM in the same follow-up period. The reviewed investigations identified the occurrence of AM by screening the medical records of enrolled patients using the International Classification of Diseases 10th Revision (ICD-10) codes I40 and I51.4. Data extraction and quality assessment The selection of studies to be included in our analysis was independently conducted by two authors (M.Z., C.B.) in a blinded fashion. Any discrepancies in study selection were resolved by consulting a third author (G.R.). The following MeSH terms were used for the search: “Myocarditis” AND “COVID-19 sequelae” OR “myocarditis” AND “COVID-19”. Moreover, we searched the bibliographies of the target studies for additional references. Specifically, inclusion criteria were: (i) studies enrolling subjects with previous confirmed COVID-19 infection (ii) providing the hazard ratio (HR) and relative 95% confidence interval (CI) for the risk of incident myocarditis in the long-term period after the index infection compared to contemporary control cohorts. Conversely, case reports, review articles, abstracts, editorials/letters, and case series with less than 10 participants were excluded. Data extraction was independently conducted by two authors (M.Z., G.R). For all investigations reviewed we extracted, when provided, the number of patients enrolled, the mean age, male gender, prevalence of cardiovascular comorbidities such as arterial hypertension (HT), diabetes mellitus (DM), chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), obesity, pre-existing HF, cerebrovascular disease and length of follow-up. The quality of included studies was graded using the Newcastle-Ottawa quality assessment scale (NOS) [10]. Data synthesis and analysis Continues variables were expressed as mean while categorical variables were presented as numbers and relative percentages. Myocarditis risk data were pooled using the Mantel–Haenszel random effects models with Hazard ratio (HR) as the effect measure with 95% confidence interval (CI). Heterogeneity among studies was assessed using Higgins and Thomson I2 statistic. Specifically, the I2 values correspond to the following levels of heterogeneity: low (<25%), moderate (25%-75%) and high (>75%). The presence of potential publication bias was verified by visual inspection of the funnel plot. Due to the low number of the included studies (<10), small-study bias was not examined as our analysis was underpowered to detect such bias. However, a predefined sensitivity analysis (leave-one-out analysis) was performed removing 1 study at the time, to evaluate the stability of our results regarding the risk of myocarditis. All meta-analyses were conducted using Comprehensive Meta-Analysis software, version 3 (Biostat, USA). Results Search results and included studies A total of 5.235 articles were obtained using our search strategy. After excluding duplicates and preliminary screening, 372 full-text articles were assessed for eligibility. Among them, 368 studies were excluded for not meeting the inclusion criteria, leaving 4 investigations fulfilling the inclusion criteria (Figure 1 ) [11, 12, 13, 14].Figure 1 Flow diagram of selected studies for the meta-analysis according to the Preferred reporting items for systematic reviews and meta-analyses (PRISMA). Characteristics of the population and quality assessment Overall, 20.875.843 patients (mean age 56.1 years, 59.1% males) were included in this analysis [4, 5, 6, 7]. Among them 1,245,167 had confirmed COVID-19 infection. The general characteristics of the studies included are presented in Table 1 . Although the demographic characteristics and concomitant comorbidities were not systematically recorded in all investigations, the cohorts mainly consisted of middle-aged patients. The mean length of follow-up was 9.5 months. Over the follow-up period, myocarditis occurred to 0.21 [95% CI: 0.13- 0.42] out of 1000 patients survived to COVID-19 infection. Conversely, AM occurred in 0.09 [95% CI: 0.07-0.12] out of 1000 control subjects. Quality assessment showed that all studies were of moderate-high quality according to the NOS scale (Table 1) [9].Table 1 General characteristics of the population reviewed. HT: Arterial Hypertension; DM: Diabetes Mellitus; COPD: chronic obstructive pulmonary disease; CKD: Chronic Kidney disease; HF: Heart failure; FW: Follow-up; NOS: Newcastle-Ottawa quality assessment scale; NR: Not reported. *Defined as Chronic Pulmonary disease; **Only DM type 2 Sample size Age (years) Males HT DM COPD CKD Obesity HF Cancer Cerebrovascular disease FW-length (months) NOS Cohen et al. [10] 2.895.943 75.7 1.227.545 (42.0%) 2.081.772 (72.0%) 938.043 (32.7%) 578.650 (20%)* 528.314 (14.0%) 478.902 (17.0%) 334654 (12%) 418.700 (14.4%) 364.782 (13.0%) 4 8 Wang et al. [11] 2.940.988 43.8 1.241.483 (42.2%) 440.998 (14.9%) 188.488 (6.4%)** 51592 (1.7%) 59177 (2.0%) 286338 (9.7%)** NR NR NR 12 7 Xie et al. [12] 5.791.407 62.5 5.228.431 (90.2%) 1.525.944 (26.3%) 1.321.907 (22.8%) 633.000 (10.9%) 970.057 (16.7%) 2.462.44 (42.5%) NR 357.192 (6.1%) NR 12 8 Daugherty et al. [13] 9.247.505 42.4 4.640.393 (50.2%) NR 521.699 (5.6%) NR NR NR NR NR NR 6 6 One-year risk of incident myocarditis During the follow-up period, recovered COVID-19 patients presented an increased risk of incident myocarditis (HR: 5.16, 95% CI: 3.87-6.89, p<0.0001, I2=7.9%) compared to subjects who did not experience COVID-19 infection but developed an AM over the same period (Figure 2 ). The funnel plot disclosed the presence of potential publication bias (Supplemental Figure S1). The sensitivity analysis confirmed yielded results reporting an HR ranging between 4.97 (95% CI: 3.81-6.47, p<0.0001, I2:0%) and 5.67 (95% CI: 4.06-7.88, p<0.0001, I2:16.7%), indicating that the obtained results were not driven by any single study.Figure 2 Forest plots investigating the long-term risk of incident myocarditis after COVID-19 Infection Discussion Our findings, based on a large population of more than 20 million people, demonstrated that myocarditis occurred in about 0.2 out of 1000 patients survived to COVID-19 infection. Moreover, after COVID-19 recovery, subjects had a significantly higher risk of myocarditis within one year from the index infection. To the best of our knowledge, the present analysis represents the first attempt to comprehensively assess the risk of incident myocarditis in the post-acute phase of COVID-19 subjects. Currently, long COVID represents a world-wide epidemic, caused by long-lasting multi-organ involvement, including cardiovascular system, that endures for weeks or months after the index SARS-CoV-2 infection has already subsided [15]. Our results demonstrate that the incidence rate of myocarditis among survivors of COVID-19 is 2-fold higher than that observed in unvaccinated subjects with COVID-related myocarditis in a recent study by Barda et al (21 vs 11 cases per 100.000 individuals) [16]. Of note, in that analysis, two contemporary series of subjects (vaccinated and unvaccinated) were followed up for 42 days after the administration of the first dose of mRNA vaccine against SARS-CoV-2 infection. AM has been also recognized as a rare complication of COVID-19 mRNA vaccinations, especially in young adult and adolescent males, with an estimated incidence of about 12.6 cases per million doses of second-dose mRNA vaccine [17]. mRNA vaccines contain nucleoside-modified mRNA, encoding the viral spike glycoprotein of SARS-CoV-2. However, selected RNA molecules can be immunogenic and stimulate the innate immune system, destroying the mRNA before it reaches target cells, preventing the spike protein and neutralizing antibody production, promoting the activation of an aberrant innate and acquired immune response and which may lead to the activation of proinflammatory cascades and immunologic pathways triggering AM [18, 19].However, the benefit-risk assessment for COVID-19 vaccination shows a favorable balance for all age and sex groups; therefore, COVID-19 vaccination is currently recommended for everyone ≥12 years of age [17]. Findings from the present study point towards a mild increase in the incidence of myocarditis in the first year compared to that observed in the first 1-2 months following the index SARS-CoV-2 infection. Moreover, the risk of AM resulted higher compared to other subjects who did not experience the infection in the same period. Available studies did not systematically report data regarding the risk of incident myocarditis according to age, gender, pre-existence of any cardiovascular conditions, and hospitalization for COVID-19 infection; therefore, dedicated sub analyses on this were not feasible. However, a higher risk of incident myocarditis after COVID-19 recovery has been reported in younger patients, aged < 44 years [5, 6], as well as in subjects with previous cardiovascular disease prior to the SARS-CoV-2 exposure [7, 8]. Moreover, available data regarding the risk of AM during the follow-up period are controversial as Daugherty et al. [14] observed a higher risk among subjects who were not hospitalized for the COVID-19 infection, while Xie et al [13] reported an increased risk in patients managed in the intensive care unit at the time of the index infection. No significant gender differences were observed regarding AM. The different recovery setting, and therefore the illness severity may have influenced such results. Indeed, subjects with a mild/moderate COVID-19 infection, gene3rally treated at home, should have received a lower dosage or neither immunomodulatory treatment, as corticosteroids, while those admitted into intensive care unit, due to a more severe disease, may have received higher dose of immunomodulatory drugs. Therefore, the different systemic corticosteroid regimens, or more in general the administration of immunomodulatory drugs, related to the severity of the infection, may have influenced the patient’s immunosuppression and as consequence the cytocidal effect of the virus on cardiac muscle, which has a critical role in the genesis of myocarditis [18, 19]. Several pathophysiological mechanisms have been suggested to explain the cardiac involvement including a direct damage to the myocardium by the virus, a micro-thrombotic damage to vessels or endothelium and a persistent systemic inflammation [20]. Intriguingly, our results demonstrates that the incidence and risk of myocarditis after hospital discharge is much lower compared to the in-hospital incidence and relative risk observed during the acute phase of COVID-19 infection [21]. Unfortunately, to date, specific markers, able to identify and guide managing physicians in the treatment of long COVID, and its cardiovascular sequelae have not yet been identified. Dedicated studies are urgently required in the future to identify the profiles of subjects at higher risk of post-acute COVID sequelae and strategies to minimize their cardiovascular risk. To this regard, future investigation assessing the risk of post-COVID-19 sequelae, will have to evaluate whether current criteria for vaccination against COVID-19 should be revised or enriched especially in subjects with previous cardiovascular disease or just having some cardiovascular risk factors [22] Limitations Our study has several limitations related to the observational nature of the studies reviewed and their own limitations with all inherited bias. Potential underestimation could derive from detection bias considering that most of the articles reviewed identified the occurrence of an incident myocarditis from larger medical records dataset using the relative ICD-10 codes; therefore, the investigators did not perform a clinical follow-up; thus, we cannot exclude that miscoding may have biased our results. Moreover, we cannot exclude potential overestimation of our results due to the presence of competing risks. Nevertheless, the sample size analyzed, the sensitivity analysis and the very low heterogeneity level observed confirmed the robustness of our results. Unfortunately, the revised studies did not systematically report data regarding potential risk factors for AM as well as no data related to the characteristics of observed events. Moreover, sampling bias by the competing risk of death could be another potential source of biases. Furthermore, available data from included study did not allow us to provide information on the diagnostic criteria adopted (non-invasive or invasive) and the type of AM, the type and number of vaccinations against SARS-CoV-2 as well as the proportion of patients having a COVID-related myocarditis during the index infection. Finally, the reviewed data may have underestimated the real impact of myocarditis after COVID-19 recovery especially during the early phase of the pandemic, for the presence of undiagnosed cases and for patients lost during the follow-up period. Unfortunately, no data were provided regarding the demographical and clinical characteristics of subjects experiencing an acute myocarditis after the COVID-19 infection, limiting potential sub-analyses. Conclusions Myocarditis represents a relatively rare post-acute COVID-19 sequelae within one year after the index infection. Physicians must be aware of this potential sequalae allowing its prompt recognition and treatment. Supplementary Material Acknowledgements None Funding Sources: None Disclosures: None of the authors have conflicts of interest to declare Conflicts of interest: None of the authors have conflicts of interest to declare ==== Refs References 1 Ammirati E. Lupi L. Palazzini M. Hendren N.S. Grodin J.L. Cannistraci C.V. Schmidt M. Hekimian G. Peretto G. Bochaton T. Hayek A. Piriou N. Leonardi S. Guida S. Turco A. Sala S. Uribarri A. Van de Heyning C.M. Mapelli M. Campodonico J. Pedrotti P. Barrionuevo Sánchez M.I. Ariza Sole A. Marini M. Matassini M.V. Vourc'h M. Cannatà A. Bromage D.I. Briguglia D. Salamanca J. Diez-Villanueva P. Lehtonen J. Huang F. Russel S. Soriano F. Turrini F. Cipriani M. Bramerio M. Di Pasquale M. Grosu A. Senni M. Farina D. Agostoni P. Rizzo S. De Gaspari M. Marzo F. Duran J.M. Adler E.D. Giannattasio C. Basso C. McDonagh T. Kerneis M. Combes A. Camici P.G. de Lemos J.A. Metra M. Prevalence, Characteristics, and Outcomes of COVID-19-Associated Acute Myocarditis Circulation 145 2022 1123 1139 35404682 2 Yajima T. Knowlton K.U. Viral myocarditis Circulation 119 2009 2615 2624 19451363 3 Hu B. Huang S. Yin L. The cytokine storm and COVID-19 J Med Virol 93 2021 250 256 32592501 4 McKinney J. Connelly K.A. Dorian P. Fournier A. Goodman J.M. Grubic N. Isserow S. Moulson N. Philippon F. Pipe A. Poirier P. Taylor T. Thornton J. Wilkinson M. Johri A.M. COVID-19-Myocarditis and Return to Play: Reflections and Recommendations From a Canadian Working Group Can J Cardiol 37 2021 1165 1174 33248208 5 Haussner W. DeRosa A.P. Haussner D. Tran J. Torres-Lavoro J. Kamler J. Shah K. COVID-19 associated myocarditis: A systematic review Am J Emerg Med 51 2022 150 155 34739868 6 Castiello T. Georgiopoulos G. Finocchiaro G. Claudia M. Gianatti A. Delialis D. Aimo A. Prasad S. COVID-19 and myocarditis: a systematic review and overview of current challenges Heart Fail Rev 27 2022 251 261 33761041 7 Bozkurt B. Kamat I. Hotez P.J. Myocarditis With COVID-19 mRNA Vaccines Circulation 144 2021 471 484 34281357 8 Simone A. Herald J. Chen A. Gulati N. Shen A.Y. Lewin B. Lee M.S. Acute Myocarditis Following COVID-19 mRNA Vaccination in Adults Aged 18 Years or Older JAMA Intern Med 181 2021 1668 1670 34605853 9 Moher D. Liberati A. Tetzlaff J. Altman D.G. PRISMA Group Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement PLoS Med 6 2009 e1000097 10 Wells GA, Shea B, O’Connell D, Peterson J, Welch V, Losos M, Tugwell P. The Newcastle-Ottawa Scale (NOS) for assessing the quality if nonrandomized studies in meta-analyses, 2012. http://wwwohrica/programs/clinical_epidemiology/oxfordasp, Accessed September 29, 2022 11 Cohen K. Ren S. Heath K. Dasmariñas M.C. Jubilo K.G. Guo Y. Lipsitch M. Daugherty S.E. Risk of persistent and new clinical sequelae among adults aged 65 years and older during the post-acute phase of SARS-CoV-2 infection: retrospective cohort study BMJ 376 2022 e068414 12 Wang W. Wang C.Y. Wang S.I. Wei J.C. Long-term cardiovascular outcomes in COVID-19 survivors among non-vaccinated population: A retrospective cohort study from the TriNetX US collaborative networks EClinicalMedicine 53 2022 101619 13 Xie Y. Xu E. Bowe B. Al-Aly Z. Long-term cardiovascular outcomes of COVID-19 Nat Med 28 2022 583 590 35132265 14 Daugherty S.E. Guo Y. Heath K. Dasmariñas M.C. Jubilo K.G. Samranvedhya J. Lipsitch M. Cohen K. Risk of clinical sequelae after the acute phase of SARS-CoV-2 infection: retrospective cohort study BMJ 373 2021 n1098 34011492 15 Gyöngyösi M. Alcaide P. Asselbergs F.W. Brundel B.J.J.M. Camici G.G. da Costa Martins P. Ferdinandy P. Fontana M. Girao H. Gnecchi M. Gollmann-Tepeköylü C. Kleinbongard P. Krieg T. Madonna R. Paillard M. Pantazis A. Perrino C. Pesce M. Schiattarella G.G. Sluijter J.P.G. Steffens S. Tschöpe C. Van Linthout S. Davidson S.M. Long COVID and the cardiovascular system - elucidating causes and cellular mechanisms in order to develop targeted diagnostic and therapeutic strategies: A joint Scientific Statement of the ESC Working Groups on Cellular Biology of the Heart and Myocardial & Pericardial Diseases Cardiovasc Res 2022 10.1093/cvr/cvac115 Epub ahead of print 16 Barda N. Dagan N. Ben-Shlomo Y. Kepten E. Waxman J. Ohana R. Hernán M.A. Lipsitch M. Kohane I. Netzer D. Reis B.Y. Balicer R.D. Safety of the BNT162b2 mRNA Covid-19 Vaccine in a Nationwide Setting N Engl J Med 385 2021 1078 1090 34432976 17 Bozkurt B. Kamat I. Hotez P.J. Myocarditis With COVID-19 mRNA Vaccines Circulation 144 2021 471 484 34281357 18 Karikó K. Buckstein M. Ni H. Weissman D. Suppression of RNA recognition by Toll-like receptors: the impact of nucleoside modification and the evolutionary origin of RNA Immunity 23 2005 165 175 16111635 19 Caso F. Costa L. Ruscitti P. Navarini L. Del Puente A. Giacomelli R. Scarpa R. Could Sars-coronavirus-2 trigger autoimmune and/or autoinflammatory mechanisms in genetically predisposed subjects? Autoimmun Rev 19 2020 102524 20 Siripanthong B. Asatryan B. Hanff T.C. Chatha S.R. Khanji M.Y. Ricci F. Muser D. Ferrari V.A. Nazarian S. Santangeli P. Deo R. Cooper L.T. Jr. Mohiddin S.A. Chahal C.A.A. The Pathogenesis and Long-Term Consequences of COVID-19 Cardiac Injury JACC Basic Transl Sci 7 2022 294 308 35165665 21 Priyadarshni S. Westra J. Kuo Y.F. Baillargeon J.G. Khalife W. Raji M. COVID-19 Infection and Incidence of Myocarditis: A Multi-Site Population-Based Propensity Score-Matched Analysis Cureus 14 2022 e21879 22 Oster M.E. Shay D.K. Su J.R. Gee J. Creech C.B. Broder K.R. Edwards K. Soslow J.H. Dendy J.M. Schlaudecker E. Lang S.M. Barnett E.D. Ruberg F.L. Smith M.J. Campbell M.J. Lopes R.D. Sperling L.S. Baumblatt J.A. Thompson D.L. Marquez P.L. Strid P. Woo J. Pugsley R. Reagan-Steiner S. DeStefano F. Shimabukuro T.T. Myocarditis Cases Reported After mRNA-Based COVID-19 Vaccination in the US From December 2020 to August 2021 JAMA 327 2022 331 340 35076665
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Can J Cardiol. 2022 Dec 12; doi: 10.1016/j.cjca.2022.12.003
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==== Front New Microbes New Infect New Microbes New Infect New Microbes and New Infections 2052-2975 The Author(s). Published by Elsevier Ltd. S2052-2975(22)00116-0 10.1016/j.nmni.2022.101064 101064 Systematic Review The efficacy of mouthwashes in reducing SARS-CoV-2 viral loads in human saliva: A systematic review Ziaeefar Pardis a1 Bostanghadiri Narjes b1 Yousefzadeh Parsa a Gabbay Julian c Shahidi Bonjar Amir Hashem d Ghazizadeh Ahsaie Mitra e Centis Rosella f Sabeti Mohammad c∗∗∗ Sotgiu Giovanni g Migliori Giovanni Battista f∗∗ Nasiri Mohammad Javad a∗ a Department of Microbiology, School of Medicine, Shahid Beheshti University of Medical Science, Tehran, Iran b Department of Microbiology, School of Medicine, Iran University of Medical Science, Tehran, Iran c School of Dentistry, University of California, San Francisco, USA d Clinician Scientist of Dental Materials and Restorative Dentistry, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran e Department of Oral and Maxillofacial Radiology, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran f Servizio di Epidemiologia Clinica delle Malattie Respiratorie, Istituti Clinici Scientifici Maugeri IRCCS, Tradate, Italy g Clinical Epidemiology and Medical Statistics Unit, Department of Medicine, Surgery and Pharmacy, University of Sassari, Italy ∗ Corresponding author. ∗∗ Corresponding author. ∗∗∗ Corresponding author. 1 equally first authors. 12 12 2022 November-December 2022 12 12 2022 49 101064101064 1 11 2022 5 12 2022 6 12 2022 © 2022 The Author(s) 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. This systematic review aimed to evaluate existing randomized controlled trials (RCT) and cohort studies on the efficacy of mouthwashes in reducing SARS-CoV-2 viral loads in human saliva. Searches with pertinent search terms were conducted in PubMed, MEDLINE, Scopus, and Web of Science databases for relevant records published up to Oct 15, 2022. Google Scholar and ProQuest were searched for grey literature. Manual searches were conducted as well for any pertinent articles. The protocol was prospectively registered at PROSPERO (CRD42022324894). Eligible studies were critically appraised for risk of bias and quality of evidence to assess the efficacy of mouthwash in reducing the SARS-CoV-2 viral load in human saliva. Eleven studies were included. The effect on viral load using various types of mouthwash was observed, including chlorhexidine (CHX), povidone-iodine (PI), cetylpyridinium chloride (CPC), hydrogen peroxide (HP), ß-cyclodextrin-citrox mouthwash (CDCM), and Hypochlorous acid (HCIO). Eight articles discussed CHX use. Five were found to be significant and three did not show any significant decrease in viral loads. Eight studies reviewed the use of PI, with five articles identifying a significant decrease in viral load, and three not showing a significant decrease in viral load. HP was reviewed in four studies, two studies identified significant viral load reductions, and two did not. CPC was reviewed in four studies, two of which identified significant viral load reductions, and two did not. CDCM was reviewed in one article which found a significant decrease in viral load reduction. Also, HCIO which was evaluated in one study indicated no significant difference in CT value. The current systematic review indicates that based on these eleven studies, mouthwashes are effective at reducing the SARS-CoV-2 viral load in human saliva. However, further studies should be performed on larger populations with different mouthwashes. The overall quality of evidence was high. Keywords COVID-19 CT value Mouth rinse Mouthwashes Salivary viral load SARS-CoV-2 ==== Body pmc1 Introduction Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first discovered in December 2019 in Wuhan (China) followed by a rapid worldwide spread in a short duration of time. Multiple public health strategies such as mandated mask-wearing, medications, and vaccinations have been recommended to control the epidemiology of the pandemic. Medications and vaccinations are designed to target the cell structure of the coronavirus, which helps reduce virulence [1]. Cell entry mechanisms of SARS-CoV-2 are based on the binding of the virus spike protein and the human angiotensin-converting enzyme 2 (ACE2) receptor [2]. High expression of ACE2 receptors in oral and nasopharynx epithelium makes the oral cavity a vulnerable anatomical target [3]. Using mouthwashes that are low-cost and feasible for all individuals to reduce the risk of COVID-19 infection as a prevention strategy is noteworthy [4]. In addition, dental professionals and their patients could be at risk of transmission and infection following the aerosol produced by dental instruments [5]. Mouthwashes might reduce the individual risk. Several studies evaluated the role played by mouthwashes in the reduction of the risk of SARS-CoV-2 infection; however, conflicting data on their efficacy were published. The present study aims to systematically review the efficacy of mouthwashes in reducing SARS-CoV-2 viral loads in human saliva. 2 Methods The Preferred Reporting Items for Systematic Reviews were adopted to describe the methodology and results [6] (PROSPERO 2022 CRD42022324894) of the present systematic review. Population: Patients infected by SARS-CoV-2. Interventions: Different mouthwashes, including chlorhexidine (CHX), povidone-iodine (PI), cetylpyridinium chloride (CPC), hydrogen peroxide (HP), ß-cyclodextrin-citrox mouthwash (CDCM), and Hypochlorous acid (HCIO). Comparisons: Distilled water and placebo. Outcomes: Saliva viral loads. Study designs: Randomized controlled clinical trials (RCTs) and observational cohort studies. 2.1 Search strategy PubMed/MEDLINE, Scopus, Web of Science, Google Scholar, and ProQuest databases were searched for studies reporting on the efficacy of mouthwashes against SARS-CoV-2, published up to Oct 15, 2022. The following search terms were used: (COVID-19) OR (Coronavirus Disease 2019) OR (SARS-CoV-2) AND (mouthwashes) OR (mouth rinse) OR (mouth bath) OR (mouth wash) OR (chlorhexidine) OR (hydrogen peroxide) OR (hydroperoxide) OR (saline solution) OR (oral rinse) OR (povidone-iodine) OR (chloride) OR (cetylpyridinium) OR (oral hygiene). Only studies written in English were selected. All records were imported into the bibliographic software EndNote X7 (Thomson Reuters, Toronto, ON, Canada). 2.2 Study selection The records found through database searching were merged, and duplicates were removed. Two reviewers (P.Z. and P.Y.) independently screened records by title/abstract and full text to exclude those unrelated to the study topic. Studies meeting the following criteria were included: (1) inclusion of patients diagnosed with SARS-CoV-2 infection; (2) inclusion of patients exposed to mouthwashes; and (3) description of the outcome of saliva viral load. Calibration between reviewers was performed by a joint evaluation of the first 15 consecutive articles. Disagreements were resolved by consulting a third reviewer (M.J.N.). Reasons for exclusion at the full-text stage were recorded. Conference abstracts, editorials, reviews, study protocols, in-vitro studies, and molecular or experimental studies on animal models were excluded. 2.3 Data extraction The following data were extracted and placed into an excel spreadsheet (Microsoft, Redmond, WA): First author's name; year of publication; study duration; type of study; the country where the study was conducted; the number of patients with SARS-CoV-2 infection; patient age; treatment protocols; demographics (i.e., age, sex, nationality); and treatment outcome. 2.4 Risk of bias assessment Two reviewers (P.Z. and P.Y.) independently used two tools to assess study quality: The Newcastle-Ottawa Scale (NOS) for observational studies, and 2) the Cochrane risk of bias tool for experimental studies [7,8]. The Cochrane risk of bias tool evaluated the studies across seven different domains: random sequence generalization, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other bias. A study was determined to be “low risk” if all categories were rendered as low risk. If one domain was categorized as possessing an unclear risk of bias, the paper was classified as having “some risk of bias.” If the study had three or more domains that had an unclear risk or had one category considered high risk, the study was classified as “high risk.” The NOS scale was used to evaluate the risk of bias in observational studies across three domains: (1) selection of participants, (2) comparability, and (3) outcomes. A study can be awarded a maximum of one point for each numbered item within the selection of participants and outcome categories. A maximum of two-point can be given for comparability. Scores of 0–3, 4–6, and 7–9 were assigned for the low, moderate, and high-quality studies, respectively. Disagreements were resolved by consultation with a third reviewer (M.J.N.). 3 Results 3.1 Search results A total of 2,915 records were found. After removing duplicates, 1,675 titles and abstracts were screened (Fig. 1 ). Of these, 51 articles were selected for a full-text review and 11 met the inclusion criteria: Two observational and nine experimental studies [[9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19]].Fig. 1 Flow chart of study selection for inclusion in the systematic review. Fig. 1 3.2 Study Characteristics 3.2.1 Population The eleven studies included a total of 1020 patients ranging from 18 to 90 years old (Table 1 ). All participants were COVID-19 patients whose diagnosis was confirmed via the detection of SARS-CoV-2 by reverse transcriptase-polymerase chain reaction (RT-PCR). Exclusion criteria consisted of patients with allergies to any of the mouthwashes, nasogastric or endotracheal tubes, thyroid disease, renal failure, developmental/cognitive disability, severe acute or chronic medical or psychiatric condition, pregnancy, current radioactive iodine treatment, or antiseptic mouthwash consumption 48 hours before the start of the study.Table 1 Characteristics of included studies. Table 1First author Year Location Type of study Participants age range Total number of participants Intervention Control solution Duration of intervention Intervention (no.) Control (no.) Definition of outcome Outcomes Huang [13] 2020 USA Observational 23-89 294 0.12%CHX Oral rinse NR 4 days 66 55 Salivary viral load based on CT-value using RT-PCR Significant difference 0.12%CHX Oral rinse posterior oropharyngeal spray 93 80 Seneviratne [14] 2020 Singapore Observational NR 16 0.5%PI Distilled water 1 day 4 2 Salivary viral load based on CT-value using RT-PCR Significant difference 6 h post-rinsing 0.12%CHX 6 No significant difference 0.075%CPC 4 Significant difference 5 min and 6 h post-rinsing Elzein [15] 2020 Lebanon Experimental 17-85 61 0.2%CHX Distilled water 1 day 25 9 Salivary viral load based on CT-value using RT-PCR Significant difference 5 min post-rinsing 1%PI 27 Significant difference 5 min post-rinsing de Paula Eduardo [10] 2020 Brazil Experimental ≥18 43 0.075%CPC+0.28%Zinc lactate Distilled water 1 day 7 9 Salivary viral load based on CT-value using RT-PCR Significant difference immediately after rinsing 1.5%HP 7 Significant difference immediately after rinsing, 30 min and 60 min post-rinsing 0.12%CHX 8 Significant difference 30 min and 60 min after rinsing 1.5%HP+0.12%CHX 12 Significant difference immediately after rinsing Ferrer [11] 2020 Spain Experimental >18 58 2%PI Distilled water 1 day 9 12 Salivary viral load based on CT-value using RT-PCR No significant difference 1%HP 14 No significant difference 0.07%CPC 11 No significant difference 0.12%CHX 12 No significant difference Chaudhary [12] NR(2021) USA Experimental 24-82 40 Normal saline NR 1 day NR NR Salivary viral load based on CT-value using RT-PCR Significant difference between baseline viral load and viral load at 15 min and 45 min post-rinsing 1%HP 0.12%CHX 0.5%PI Arefin [16] 2020 Bangladesh Experimental ≥18 189 0.4, 0.5, 0.6% PI (NI) 0.5, 0.6% PI (NS) Distilled water 1 day 162 27 Salivary viral load based on CT-value using RT-PCR Significant difference Carrouel [9] 2020 France Experimental 18-85 154 CDCM Placebo 7 days 88 88 Salivary viral load based on CT-value using RT-PCR Significant difference 4 h post-rinsing No significant difference at day 7 Natto [17] 2022 Saudi Arabia Experimental ≥18 60 CHX (mouth rinse) Saline 1 day 45 15 Salivary viral load based on CT-value using RT-PCR No significant difference between all groups at two times Significant reduction in viral load of all four groups Significant reduction of both salivary load and CT value in PI CHX (lozenges) PI Sánchez Barrueco [18] 2022 Spain Experimental 25-90 44 2% PI Distilled water 1 day 9 Salivary viral load No significant difference 1% HP 6 0.07% CPC 10 0.12% CHX 9 Sevinç Gül [19] 2022 Turkey Experimental 20-83 61 0.02% HCIO 0.9% Saline 1 day 20 20 Salivary viral load based on CT-value using RT-PCR No significant difference 0.5 % PI 21 CHX; Chlorhexidine, PI; Povidone Iodine, HP; Hydrogen peroxide, CPC; Cetylpyridinium Chloride, ß-cyclodextrin citrox mouthwash, HCIO; Hypochlorous acid, NI; Nasal irrigation, NS; Nasal spray, NR; not reported. 3.2.2 Intervention The following mouthwashes were prescribed: CHX in eight studies with the dosage of 0.12, and 0.2% [[10], [11], [12], [13], [14], [15],17,18], PI with the dosage of 0.4, 0.5, 0.6, 1, and 2% in eight studies [11,12,[14], [15], [16], [17], [18], [19]], the dose of 0.07 % of CPC in four studies [10,11,14,18], HP with the dosage of 1, and 1.5 % in four studies [[10], [11], [12],18], CDCM in one study [9], and 0.02% HCIO in one study [19]. Mouth rinses in the intervention groups were compared with distilled water as the control groups for nine of the studies [[10], [11], [12],[14], [15], [16], [17], [18], [19]]. In the study of Carrouel et al., the control group used a placebo as mouthwash [9]. That is to say, the same mouthwash that the test group but without the active molecules (citrox and b-cyclodextrin). In the study of Huang et al., the control group didn't use mouthwash [13]. 3.2.3 Outcome assessment The outcome was measured through RT-PCR: % reduction in viral load was the target. Studies evaluated salivary viral load clearance with CT value changes [9,10,12,14,15,[17], [18], [19]] and/or RT-PCR [14], quantitative RT-PCR [[9], [10], [11], [12],18], qualitative RT-PCR [16], and real-time RT-PCR [13,15,17,19]. 3.3 Risk of bias The mean (standard deviation [SD]) NOS score was 8.0 (0.6), which is suggestive of high methodological quality and a low risk of bias (Table 2 ). Four studies had a low risk of bias in all seven domains [9,11,12,15] (Table 3 and Fig. 2 ). One study has a high risk of bias in cases of allocation concealment, blinding of participants, and blinding of the outcome; and a low risk of bias in all other domains [16]. De Paula Eduardo et al. had a high risk of bias in the blinding of outcome assessments, and a low risk of bias in all other categories [10].Table 2 Quality assessment of the observational studies included in the meta-analysis (The NOS tool). Table 2Author Selection Comparability Outcome Representativeness of exposed cohort Selection of non-exposed cohort Ascertainment of exposure Demonstration that outcome of interest was not present at start of study Adjust for the most important risk factors Adjust for other risk factors Assessment of outcome Follow-up length Loss to follow-up Rate Total quality score Huang et al. [13] 1 1 1 1 1 0 1 1 1 8 Seneviratne et al. [14] 1 1 1 1 1 0 1 1 1 8 Table 3 Quality assessment of the experimental studies included in the meta-analysis (the Cochrane tool). Table 3Author Random sequence generation Allocation concealment Blinding of participants andpersonnel Blinding of outcome assessment Incomplete outcome data Selective reporting Other bias Elzein et al. [15] Low risk Low risk Low risk Low risk Low risk Low risk Low risk de Paula Eduardo et al. [10] Low risk Low risk Low risk High risk Low risk Low risk Low risk Arefin et al. [16] Low risk High risk High risk High risk Low risk Low risk Low risk Carrouel et al. [9] Low risk Low risk Low risk Low risk Low risk Low risk Low risk Ferrer et al. [11] Low risk Low risk Low risk Low risk Low risk Low risk Low risk Chaudhary et al. [12] Low risk Low risk Low risk Low risk Low risk Low risk Low risk Natto et al. [17] Low risk Low risk Low risk Low risk Low risk Low risk Low risk Sánchez Barrueco wt al [18]. Low risk Low risk Low risk Low risk Low risk Low risk Low risk Sevinç Gül et al. [19] Low risk Low risk Low risk Low risk Low risk Low risk Low risk Fig. 2 Review of the author's assessment of the risk of bias domains for each experimental study, displayed as percentages across included studies. Fig. 2 3.3.1 Chlorhexidine Eight studies evaluated the efficacy of CHX [[10], [11], [12], [13], [14], [15],17,18]. Four examined 0.12% CHX mouth rinses and measured viral load reduction at 5 and 60 minutes. The studies found a significant decrease in viral load at both times [10,12,13,15]. Three studies observed viral load four days after continuous daily use of CHX and also found significant viral load reduction [10,13,15]. Rinsing with HP mouthwash followed by CHX mouthwash reduced viral load immediately after consumption [10]. Significant viral load clearance was seen following four days of usage of CHX oral rinse with a posterior oropharyngeal spray (86%) via swabbing the oropharynx to test the presence of SARS-CoV-2 by rRT-PCR. The combination of CHX oral rinse with a posterior oropharyngeal spray in addition to the second study group, the aforementioned combination was used in 15 healthcare workers as a preventive strategy in addition to hand sanitizing, mask-wearing, and social distancing. None of the healthcare workers developed COVID-19 infection during the study time, whilst nearly 50% of all healthcare workers in their respective hospitals developed infection [13]. Also, in the study conducted by Natto et al., both CHX mouthrinse and lozenges were administrated and significantly reduced the viral load [17]. However, three studies indicated no significant difference using the CHX mouth rinses [11,14,18]. (Table 1). 3.3.2 Povidone-iodine Eight studies surveyed the efficacy of PI on the SARS-CoV-2 viral load [11,12,[14], [15], [16], [17], [18], [19]]. Five studies confirmed its efficacy as follows [12,[14], [15], [16], [17]]; 5 minutes post-rinsing of 1% PI, 15 and 45 minutes, and 6 hours after 0.5% PI. Similarly, different concentrations of PI in forms of nasal irrigation (NI) and nasal spray (NS) indicated showed viral load clearance; however, a significant viral load reduction of 0.5% PI NI compared to 0.5% PI NS was found. The most incident adverse event was nasal irritation [16]. Three studies found that 0.5% [19] and 2% PI [11,18] consumption did not have any significant efficacy in viral load reduction. 3.3.3 Hydrogen peroxide Four studies evaluated the effectiveness of HP [[10], [11], [12],18]. 1.5% HP significantly reduced SARS-CoV-2 viral load immediately, after 30 and 60 minutes [10]. HP at a concentration of 1%, evaluated with 15 and 45-minute post-rinsing measurements, significantly reduced the SARS-CoV-2 load [12]. Two studies using 1% HP as a mouth rinse indicated no significant efficacy on viral load clearance [11,18]. 3.3.4 Cetylpyridinium chloride A total of four studies evaluated CPC efficacy [10,11,14,18]: two reported the effectiveness shortly after administration and showed a reduction in SARS-CoV-2 viral load (2, 4). Two studies showed no significant differences in terms of viral load reduction [11,18]. 3.3.5 ß-cyclodextrin-citrox mouthwash One study evaluated CDCM effectiveness: a significant reduction in viral load was described four hours after rinsing [9]. 3.3.6 Hypochlorous acid One study evaluated the efficacy of HCIO which was previously approved as an effective disinfectant against COVID-19 with a dosage of 0.01%, whilst this study indicated that 0.02% HICO mouthwash had no significant efficacy regarding viral load reduction [19]. 4 Discussion The present systematic review investigated the efficacy of oral rinses against SARS-CoV-2. The eleven studies included a total of 1020 patients who were reviewed [[9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19]]. Since the emergence of SARS-CoV-2, global public health efforts have focused on preventative strategies such as vaccinations, social distancing, lockdowns, mask-wearing, and increased hand sanitizer use [14]. Some mouthwashes can inhibit the replication of SARS-CoV-2 by stopping its attachment to ACE2-positive epithelial cells [20] or can oxidize the structure of the virus [21,22]. CHX is a mouth rinse routinely used in dental offices for periodontal disease and to decrease infection rates in the oral cavity [23]. Administration of 0.12% CHX as both mouthwash and nasopharyngeal spray was found to have a high clearance of the SARS-CoV-2 viral load [13]. Elzian et al. found that using CHX rinse in patients for 30 seconds markedly reduced viral load [15]. Huang et al. highlight that CHX mouth rinse for 2-3 weeks can significantly prevent the spread to other individuals [13]. A study conducted by Fernanda et al. observed the use of CHX after rinsing with HP: Viral loads did not significantly reduce but by switching the order of mouthwash consumption an improvement can be recorded [10]. Bernstein et al. performed a study on the effectiveness of 0.12% CHX against herpes, influenza, and parainfluenza virus, and found a viral load reduction [24]. A systematic review by Fernandez et al. also found CHX to be an effective antiviral agent against HSV-1 and Influenza A viruses [25]. PI is an antiseptic mostly prescribed as a pre-and post-surgical disinfectant [26] against non-enveloped and enveloped viruses [22,27,28]. The studies included in this systematic review found significant viral load reductions when rinsing the oral cavity with a concentration of 0.5% and 1% PI [12,[14], [15], [16]]. However, when using 2% PI, no significant viral load reduction was seen [11]. Conflicting results were described by other studies: Lamas et al. found a noteworthy viral load reduction in SARS-CoV-2 [29], whereas Guenezan et al. reported PI to be ineffective in reducing nasopharyngeal viral load. PI usage also resulted in unwanted side effects such as nasal tingling and transient elevated TSH [30]. HP is an oxidizing agent with antiviral and antibacterial properties [31]. It works by disrupting the viral envelope and degrading the viral RNA [32]. A systematic review by Hossainian et al. sought to determine the effectiveness of hydrogen peroxide mouthwash on plaque and the gingiva. They found that short-term use had no significant impact on plaque reduction, but long-term use was correlated with benefits for the reduction of gingival inflammation (36). The studies included in our systematic review had varying results: two showed a significant decrease in the viral load [10,12], and one no decrease [11]. The antiviral effect of CPC is similar to PI. Both mechanisms destroy the lipid membrane of SARS-CoV-2, which could lead to a sustained impact on the salivary viral load reduction [14]. In the present systematic review, three studies on CPC were selected [10,11,14]. Two found a significant decrease in the viral load (2, 4), and one did not [11]. A randomized clinical trial by Mukherjee et al. evaluated the efficacy of CPC mouthwashes against coronavirus, influenza, and rhinoviruses: it did reduce the severity and duration of upper respiratory tract infections [33]. Only one study assessed the efficacy of CDCM in mild symptomatic and asymptomatic infected individuals four hours post-rinse [9]. Clinical application: administration of aforementioned mouthwashes can minimize the saliva SARS-CoV-2 viral load which can lead to a reduction of risk of spread of CPVID-19 which is a cost-effective strategy in reducing viral load both in dental settings and in the public. This systematic review presents some limitations. There was a discrepancy in the populations of the studies included. Likewise, due to the limited raw data, we were not able to perform a meta-analysis of the included studies. The concentrations of the mouthwashes were not homogeneous in studies, and limited information about patients' oral conditions was reported. Our results must be interpreted with caution until further investigations are carried out. In conclusion, this systematic review found that mouth rinses could effectively reduce the viral load of SARS-CoV-2. Also, this study indicated the efficacy of oral rinses in reducing the risk of transmitting the virus from SARS-CoV-2 positive patients, however, the results of some studies were contradictory, and due to the emergence of new SARS-CoV-2 variants and vaccinations, new scientific data are needed, as well as a shared methodology. Also, further studies should be conducted for a longer time as well as evaluating the preventive efficacy of oral rinses on negative SARS-Cov-2 individuals who do not develop the disease. Author's contribution All authors have read and approved the manuscript. CRediT authorship contribution statement Pardis Ziaeefar: Conceptualization, Investigation, Validation, Writing – original draft. Narjes Bostanghadiri: Data curation, Investigation, Validation, Writing – original draft. Parsa Yousefzadeh: Investigation. Julian Gabbay: Methodology, Writing – review & editing. Amir Hashem Shahidi Bonjar: Investigation. Mitra Ghazizadeh Ahsaie: Investigation. Rosella Centis: Methodology, Writing – review & editing. Mohammad Sabeti: Methodology, Supervision, Writing – review & editing. Giovanni Sotgiu: Methodology, Writing – review & editing. Giovanni Battista Migliori: Methodology, Writing – review & editing. Mohammad Javad Nasiri: Conceptualization, Investigation, Data curation, Methodology, Supervision, Validation, Writing – review & editing. Declaration of competing interest The authors have no conflict of interests or any outside funding. Acknowledgment This study was supported by the Research Department of the School of Medicine, Shahid Beheshti University of MedicalSciences, Tehran, Iran (Grant number: 32811). ==== Refs References 1 Chen Y. Liu Q. Guo D. Emerging coronaviruses: genome structure, replication, and pathogenesis J Med Virol 92 4 2020 418 423 31967327 2 Chen Y. Structure analysis of the receptor binding of 2019-nCoV Biochem Biophys Res Commun 525 1 2020 135 140 32081428 3 Castro-Ruiz C. Vergara-Buenaventura A. Povidone–iodine solution: a potential antiseptic to minimize the risk of COVID-19? A narrative review J Int Soc Preventive Commun Dentistry 10 6 2020 681 4 Mateos-Moreno M. Oral antiseptics against coronavirus: in-vitro and clinical evidence J Hospital Infection 113 2021 30 43 5 Peng X. Transmission routes of 2019-nCoV and controls in dental practice Int J Oral Sci 12 1 2020 1 6 31900382 6 Moher D. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement Ann Internal Med 151 4 2009 264 269 19622511 7 WellsGA S. O’connellD P. WelchV L. The newcastle-ottawa scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses 2012 Ottawa Hospital Research Institute Web Site 8 Higgins J.P. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials Bmj 2011 343 9 Carrouel F. Use of an antiviral mouthwash as a barrier measure in the SARS-CoV-2 transmission in adults with asymptomatic to mild COVID-19: a multicentre, randomized, double-blind controlled trial Clin Microbiol Infection 27 10 2021 1494 1501 10 de Paula Eduardo F. Salivary SARS-CoV-2 load reduction with mouthwash use: a randomized pilot clinical trial Heliyon 7 6 2021 e07346 11 Ferrer M.D. Clinical evaluation of antiseptic mouth rinses to reduce salivary load of SARS-CoV-2 Scientific Reports 11 1 2021 1 9 33414495 12 Chaudhary P. Estimating salivary carriage of severe acute respiratory syndrome coronavirus 2 in nonsymptomatic people and efficacy of mouthrinse in reducing viral load: a randomized controlled trial J Am Dental Assoc 152 11 2021 903 908 13 Huang Y.H. Huang J.T. Use of chlorhexidine to eradicate oropharyngeal SARS-CoV-2 in COVID-19 patients J Med Virol 93 7 2021 4370 4373 33755218 14 Seneviratne C.J. Efficacy of commercial mouth-rinses on SARS-CoV-2 viral load in saliva: randomized control trial in Singapore Infection 49 2 2021 305 311 33315181 15 Elzein R. In vivo evaluation of the virucidal efficacy of chlorhexidine and povidone-iodine mouthwashes against salivary SARS-CoV-2. A randomized-controlled clinical trial J. Evid Based Dental Practice 21 3 2021 101584 16 Arefin M.K. Virucidal effect of povidone iodine on COVID-19 in the nasopharynx: an open-label randomized clinical trial Indian J Otolaryngol Head Neck Surg 2021 1 5 17 Natto Z.S. The short-term effect of different chlorhexidine forms versus povidone iodine mouth rinse in minimizing the oral SARS-CoV-2 viral load: an open label randomized controlled clinical trial study Medicine 101 30 2022 18 Sánchez Barrueco Á. Effect of oral antiseptics in reducing SARS-CoV-2 infectivity: evidence from a randomized double-blind clinical trial Emerging Microbes Infections 11 1 2022 1833 1842 35796097 19 Sevinç Gül S.N. Effect of oral antiseptics on the viral load of SARS-CoV-2: a randomized controlled trial (Online) 2022 Dent. Med. Probl. 20 Liu L. Epithelial cells lining salivary gland ducts are early target cells of severe acute respiratory syndrome coronavirus infection in the upper respiratory tracts of rhesus macaques J Virol 85 8 2011 4025 4030 21289121 21 Eggers M. Infectious disease management and control with povidone iodine Infectious Dis Therapy 8 4 2019 581 593 22 Kawana R. Inactivation of human viruses by povidone-iodine in comparison with other antiseptics Dermatol. 195 Suppl. 2 1997 29 35 23 Jones C.G. Chlorhexidine: is it still the gold standard? Periodontol 15 1997 55 62 2000 24 Bernstein D. In vitro virucidal effectiveness of a 0.12%-chlorhexidine gluconate mouthrinse J. Dental Res. 69 3 1990 874 876 25 Fernandez M.d.S. Virucidal efficacy of chlorhexidine: a systematic review Odontol 2021 1 17 26 Formulary W.W.M. Stuart M.C. Kouimtzi M. Hill S.R. World health organization 2009 Geneva, Switzerland 27 Wutzler P. Virucidal activity and cytotoxicity of the liposomal formulation of povidone-iodine Antiviral Res 54 2 2002 89 97 12062394 28 Kariwa H. Fujii N. Takashima I. Inactivation of SARS coronavirus by means of povidone-iodine, physical conditions and chemical reagents Dermatology 212 Suppl. 1 2006 119 123 16490989 29 Lamas L.M. Is povidone-iodine mouthwash effective against SARS-CoV-2? First in vivo tests Oral Dis 2020 30 Guenezan J. Povidone iodine mouthwash, gargle, and nasal spray to reduce nasopharyngeal viral load in patients with COVID-19: a randomized clinical trial JAMA Otolaryngol Head Neck Surg. 147 4 2021 400 401 33538761 31 Block S.S. Disinfection, sterilization, and preservation 2001 Lippincott Williams & Wilkins 32 Linley E. Use of hydrogen peroxide as a biocide: new consideration of its mechanisms of biocidal action J Antimicrobial Chemotherapy 67 7 2012 1589 1596 33 Mukherjee P.K. Randomized, double-blind, placebo-controlled clinical trial to assess the safety and effectiveness of a novel dual-action oral topical formulation against upper respiratory infections BMC Infect Dis 17 1 2017 1 8 28049444
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==== Front J Infect Public Health J Infect Public Health Journal of Infection and Public Health 1876-0341 1876-035X The Authors. Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. S1876-0341(22)00347-1 10.1016/j.jiph.2022.12.009 Original Article Lactate dehydrogenase and PaO2/FiO2 ratio at admission helps to predict CT score in patients with COVID-19: An observational study Russo Antonio a Pisaturo Mariantonietta a De Luca Ilaria a Schettino Ferdinando r Maggi Paolo b Numis Fabio Giuliano c Gentile Ivan d Sangiovanni Vincenzo e Rossomando Anna Maria f Gentile Valeria g Calabria Giosuele h Rescigno Caroliona i Megna Angelo Salomone j Masullo Alfonso k Manzillo Elio l Russo Grazia m Parrella Roberto n Dell’Aquila Giuseppina o Gambardella Michele p Ponticiello Antonio q Reginelli Alfonso r Coppola Nicola a⁎ on behalf of CoviCam group a Infectious Diseases, Department of Mental Health and Public Medicine, University of Campania "L. Vanvitelli", Napoli, Italy b Infectious Diseases Unit, A.O. S Anna e S Sebastiano Caserta, Italy c Emergency unit, PO Santa Maria delle Grazie, Pozzuoli, Italy d Infectious disease unit; University Federico II, Naples, Italy e Third Infectious Diseases Unit, AORN dei Colli, P.O. Cotugno, Naples, Italy f IV Infectious Disease Unit, AORN dei Coli, PO Cotugno, Naples, Italy g Hepatic Infectious Disease Unit, AORN dei Colli, PO Cotugno, Naples, Italy h IX Infectious Disease Unit, AORN dei Coli, PO Cotugno, Naples, Italy i First Infectious Disease Unit, AORN dei Coli, PO Cotugno, Naples, Italy j Infectious Diseease Unit, A.O. San Pio, PO Rummo, Benevento, Italy k Infectious disease unit, A.O. San Giovanni di Dio e Ruggi D’Aragona Salerno, Italy l VIII Infectious Disease Unit, AORN dei Coli, PO Cotugno, Naples, Italy m Infectious Disease Unit, Ospedale Maria S.S. Addolorata di Eboli, ASL Salerno, Italy n Respiratory Infectious Diseases Unit, AORN dei Colli, PO Cotugno, Naples, Italy o Infectious Diseases Unit, AO Avellino, Italy p Infectious Diseease Unit, PO S. Luca, Vallo della Lucania, ASL Salerno, Italy q Pneumology Unit, AORN Caserta, Italy r Radiology Unit, Departement of Precision Medicine, University of Campania "L. Vanvitelli", Napoli, Italy ⁎ Correspondence to: Department of Mental Health and Public Medicine, Section of Infectious Diseases, University of Campania Luigi Vanvitelli, Via L. Armanni 5, 80131 Naples, Italy. 12 12 2022 1 2023 12 12 2022 16 1 136142 29 7 2022 4 12 2022 7 12 2022 © 2022 The Authors. Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Introduction Since the beginning of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pandemic an important tool for patients with Coronavirus Disease 2019 (COVID-19) has been the computed tomography (CT) scan, but not always available in some settings The aim was to find a cut-off that can predict worsening in patients with COVID-19 assessed with a computed tomography (CT) scan and to find laboratory, clinical or demographic parameters that may correlate with a higher CT score. Methods We performed a multi-center, observational, retrospective study involving seventeen COVID-19 Units in southern Italy, including all 321 adult patients hospitalized with a diagnosis of COVID-19 who underwent at admission a CT evaluated using Pan score. Results Considering the clinical outcome and Pan score, the best cut-off point to discriminate a severe outcome was 12.5. High lactate dehydrogenase (LDH) serum value and low PaO2/FiO2 ratio (P/F) resulted independently associated with a high CT score. The Area Under Curve (AUC) analysis showed that the best cut-off point for LDH was 367.5 U/L and for P/F 164.5. Moreover, the patients with LDH> 367.5 U/L and P/F < 164.5 showed more frequently a severe CT score than those with LDH< 367.5 U/L and P/F> 164.5, 83.4%, vs 20%, respectively. Conclusions A direct correlation was observed between CT score value and outcome of COVID-19, such as CT score and high LDH levels and low P/F ratio at admission. Clinical or laboratory tools that predict the outcome at admission to hospital are useful to avoiding the overload of hospital facilities. Keywords CT score Pan score COVID-19 SARS-CoV-2 infection Severity of disease ==== Body pmcIntroduction Since December 2019 a new coronavirus, the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), the causative agent of Coronavirus Disease 2019 (COVID-19), associated with substantial morbidity and mortality [1]. COVID-19 is the clinical manifestation of SARS-CoV-2 infection with a large severity spectrum ranging from asymptomatic to severe manifestation [2], [3]. Considering the impact on the healthcare system [4], the need to identify prognostic factors of severe disease is and has been a priority of the scientific community [5], [6], [7], [8], [9]. Studies showed that the most important clinical factors at admission that can predict severity of COVID-19 were diabetes, hypertension, chronic kidney disease, active oncological disease and dementia [5], [6], [7], [8], and the most common laboratory parameters that can predict COVID-19 prognosis were the alteration of white blood cell counts, elevated neutrophil-to-lymphocyte ratios and platelet-to-lymphocyte, elevated high sensitivity cardiac troponin I, C-reactive proteins, ferritin, lymphocytopenia, elevation of aminotransferases and elevation of lactate dehydrogenase [9], [10], [11], [12], [13]. Since the beginning of the pandemic an important tool for the evaluation of the patient suffering from COVID-19 has been the computed tomography (CT) scan [14], but not always available in some settings. both for economic reasons and for the intensity of traffic on hospital facilities during the waves. The CT feature included ground glass opacity (GGO), consolidation, septal thickening and crazy paving [14]. The predictive power of the CT scan on the outcome was clear [15], [16], [17], [18], [19], [20], [21]. However, to our knowledge, few studies have been carried out on the identification of biochemical factors that predict a worse CT score at admission for COVID-19 [18], [19], [20], [21]. Considering the data available, the aim of the present study was to find a cut-off that can predict a disease worsening in patients evaluated by the semi-quantitative visual CT severity Pan score[22]. In addition, we wanted to find laboratory, clinical or demographic parameters that can correlate with a higher CT score to reserve CT scan for high-risk patients or those suspected of having complications or worsening of the respiratory status. Materials and methods Study design and setting We performed a multicenter, observational, retrospective study involving seventeen COVID-19 Units in eight cities in the Campania region in southern Italy: Naples, Caserta, Salerno, Benevento, Avellino, Pozzuoli, Eboli and Vallo della Lucania. All adult (≥18 years old) patients, hospitalized with a diagnosis of SARS-CoV-2 infection confirmed by a positive reverse transcriptase-polymerase chain reaction (RT-PCR) on a naso-oropharyngeal swab, from February 28th 2020 to November 1st 2021 at one of the centers participating in the study, were enrolled in the CoviCamp cohort. Exclusion criteria included minority age (<18 years old), and lack of clinical data and/or of informed consent. No study protocol or guidelines regarding the criteria of hospitalization were shared among the centers involved in the study and the patients were hospitalized following the decision of physicians of each center. From the CoviCamp cohort, we included all patients for whom a determination at admission of CT score using the Pan et al. score [22] was available. The CT scans were independently evaluated by two radiologists (Al.Re and F.S.) who achieved a common score. The CT scans were evaluated with a semi-quantitative scoring system used to estimate the pulmonary volume involvement. Each of the five lung lobes was visually scored on a scale of 0–5, with 0 indicating no involvement; 1, less than 5% involvement; 2, 5–25% involvement; 3, 26–49% involvement; 4, 50–75% involvement; and 5, more than 75% involvement [18]. The total CT score was the sum of the individual lobar scores and ranged from 0 (no involvement) to 25 (maximum involvement) [18]. The study was approved by the Ethics Committee of the University of Campania L. Vanvitelli, Naples (n°10877/2020). All procedures performed in this study were in accordance with the ethics standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethics standards. Informed consent was obtained from all participants included in the study. This study was reported following the STROBE recommendations for an observational study (Supplementary Table 1). Data collection All demographic and clinical data and therapy details of patients with SARS-CoV2 infection enrolled in the cohort were collected in an electronic database. From this database we extrapolated the data for the present study. Definitions The microbiological diagnosis of SARS-CoV-2 infection was defined as a positive RT-PCR test on a naso-oropharyngeal swab. All the sites included used the same RT-PCR kit, Bosphore V3 (Anatolia Genework, Turkey). We divided the patients enrolled according to the clinical outcome of COVID-19 during hospitalization in two groups, the first including patients with mild or moderate, the second including severe outcome or death during hospitalization. Precisely, the patients with a mild infection did not need oxygen (O2) therapy and/or had a MEWS score below 3 points during hospitalization. The patients with a moderate infection were hospitalized and required non-invasive O2 therapy (excluding high flow nasal cannula) and/or had a MEWS score equal to or above 3 points (≥3) during hospitalization. The patients with a severe infection needed management in an intensive care unit (ICU) and/or high flow nasal cannula or invasive/non-invasive mechanical ventilation during hospitalization. The patients were followed until SARS-CoV-2-RNA negativity at naso-oropharyngeal swab and/or discharged from hospital or died. Statistical analysis For the descriptive analysis, categorical variables were presented as absolute numbers and their relative frequencies. Continuous variables were summarized as mean and standard deviation if normally distributed or as median and interquartile range (Q1-Q3) if not normally distributed. We performed a comparison of patients with mild and moderate disease, severe disease or who died using chi square for categorical variables or Student’s t-test for continuous variables or Mann-Whitney tests for non-parametric independent ordinal variables. Multivariate analysis was performed using binomial logistic regression; this analysis was performed only for parameters resulting statistically significant at univariate analysis. A p-value below 0.05 was considered statistically significant. The receiver operating characteristic (ROC) curve was used to determine the optimum cut-off point for possible effective variables on the patients’ outcome. Analyses were performed by STATA (StataCorp. 2019) [23]. Results A total of 2054 adult patients were admitted with a documented diagnosis of COVID-19 to one of the nineteen centers from February 20, 2020 to November 1, 2021 and participated in the CoviCamp cohort. Considering the inclusion criteria, 321 patients were included, while 1278 were excluded for missing CT data and 455 for different CT severity scores ( Fig. 1).Fig. 1 Flow-chart of patients included in the study. Fig. 1 Considering the 321 patients included, 67.9% were males, with a mean age of 65 years (SD 14.25) and a median of Charlson Comorbidity Index of 3 (1−4), and a median of 6 days (2−9) from first symptoms of COVID-19 to admission to hospital ( Table 1). Only 6 (1.87%) patients had been vaccination against SARS-CoV-2 with full schedule (two doses). The most frequent comorbidities were hypertension (52.2%), cardio-vascular disease (32%) and diabetes (24.4%) (Table 1). As regards the COVID-19-related symptoms, 57.5% of the patients had recent history of fever, while 73.8% had dyspnea and 33.4% cough (Table 1). The patients with a mild or moderate outcome were 57.3% while patients with a severe disease or who died during hospitalization were 42.7%.Table 1 Demographic and clinical parameters of patients included in the study. Table 1 Number of patients with data available Males, n° (%) 321 218(67.9) Age, years, mean (SD) 321 65(14.25) Days from symptoms to admission, median (Q1-Q3) 213 6(2–9) Charlson comorbidity index, mean (SD) 317 3(1–4) n° (%) with hypertension 316 165(52.2) n° (%) with cardio-vascular disease 316 101(32) n° (%) with diabetes 316 77(24.4) n° (%) with chronic kidney disease 317 24(7.6) n° (%) with chronic obstructive pulmonary disease 316 26(8.2) n° (%) with chronic hepatopathy 316 13(4.0) n° (%) with malignancy 315 22(6.9) n° (%) with dementia 316 12(3.7) n° (%) with fever during recent history 320 184(57.5) n° (%) with dyspnea during recent history 320 236(73.8) n° (%) with astheny during recent history 320 97(30.3) n° (%) with cough during recent history 320 107(33.4) n° (%) with ageusia/dysgeusia during recent history 319 4(1.3) n° (%) with anosmia/hyposmia during recent history 319 5(1.6) n° (%°) with diarrhoea during recent history 319 9(2.8) n° (%) with skin lesions during recent history 318 0(0) Days from admission to discharge*, mean (SD) 318 12(7–17) Patients with mild or moderate outcome, n° (%) 321 184(57.3) Patients with severe outcome or who died during hospitalization, n° (%) 321 137(42.7) n° (%) patients who died during hospitalization 321 48(15) CT score, mean (SD) 321 13.05(4.79) * or who died during hospitalization The CT score mean was 13.5 (SD 4.79) (Table 1 ). Dividing the patients in two groups, with a mild or moderate outcome or a severe outcome or who died during hospitalization, the difference in the CT severity score was statistically significant (mean 11.23 (SD: 4) vs mean 15.49(SD: 4.7), p < 0.008) ( Fig. 2 A). We calculated the AUC for the CT severity score and the result was 0.749 (95%CI: 0.695–0.803, p < 0.0001) (Supplementary Figure 1a) with the best cut-off point of 12.5 (sensitivity: 71.5%, specificity: 66.3%).Fig. 2 : A:Box plot of CT score value at admission in patients who did not need ICU care and patients who needed it. B: Stacked column graph considering CT score and LDH/PF value at admission (data in percentage). Fig. 2 For the second aim (to find laboratory, clinical or demographic parameters correlated with a higher CT score), we divided the patients in two groups the first included the 161 patients with less than 13 of CT severity score (Group 1), the second included the 160 patients with more than or equal to 13 of CT severity score (Group 2). Considering the two groups, no difference was found in the demographic or clinical history at admission, excluding the presence of dyspnea (65.6% vs 81.9%, p < 0.001) ( Table 2). Considering laboratory parameters at admission we found a statistical significance between Group 1 and Group 2 evaluating the count of white blood cells [median 7300 cells/uL (6000−10,400) vs 8100 (6200−11,640) (p = 0.041)], ALT serum concentration [median 27 U/L (22−43) vs 38.5 U/L (23.5–59.5) (p = 0.002)], AST serum concentration [median 29.5 U/L (21−44) vs 41.5 U/L (29−59) (p < 0.001)], LDH serum concentration [median 293 U/L (235−563) vs 412 U/L (330−563)(p < 0.001)] and PaO2/FiO2 ratio (P/F) [median 213 (146−294) vs 133 (98–186.5) (p < 0.001)] (Table 2). In order to identify the factors independently associated with a higher CT score, we performed a multivariate binomial logistic regression including AST, dyspnea, P/F, LDH, and white cell count (Table 2); since AST and ALT proved correlated (p = 0.635), we excluded ALT serum value from this analysis. The only factors associated with a higher CT score were LDH (OR 1.005; 95% CI: 1.003–1.008) and low P/F ratio (OR 0.993; 95%CI: 0.989–0.997) (Table 2).Table 2 Laboratory parameters of patients included in the study. Table 2 Number of patients with data available Median (Q1-Q3) white blood cells (WBC) at admission (cells/uL) 269 7900(6100–10700) Mean (SD) International Normalized Ratio (INR) at admission 230 1.10(0.29) Median (Q1-Q3) Blood creatinine at admission (mg/dl) 266 0.9(0.75–1.17) Median (Q1-Q3) creatine phosphokinase (CPK) at admission (U/L) 148 100.5(54–189.5) Median (Q1-Q3) lactate dehydrogenase (LDH) at admission (U/I) 243 347(267–461) Median (Q1-Q3) PaO2/FiO2 Ratio (P/F) at admission 273 164(115–251) Median (Q1-Q3) ALT at admission (U/L) 242 32(22–52) Median (Q1-Q3) AST at admission (U/L) 262 36.5(25–50) Median (Q1-Q3) Bilirubin at admission(mg/dl) 204 0.64(0.495–0.975) Median (Q1-Q3) procalcitonin at admission (ng/ml) 162 0.09(0.05–0.24) Considering the data above, we calculated the AUC for LDH considering the severe outcome group or patients who died as the status variable and the result was 0.748 (95%CI: 0.686–0.810, p < 0.0001) (Supplementary Figure 1b), with the best cut-off point of 367.5 U/L (sensitivity: 66.7%, specificity: 72.5%), showing a direct correlation between the severity of disease and increase in LDH; instead, the AUC for P/F considering the mild or moderate group as the status variable was 0.733 (95%CI: 0.675–0.792, p < 0.0001) (Supplementary Figure 1c), with the best cut-off point of 164.5 (sensitivity: 67.9%, specificity: 68.4%), showing a better CT score in patients with a higher P/F. Moreover, considering the cut-offs of these two parameters, the 66 patients with both LDH> 367.5 U/L and P/F < 164.5 more frequently showed a severe CT-score than those with both LDH< 367.5 U/L and P/F> 164.5, and those with only one severe parameter (P/F<164.5 or LDH >367.5 U/L): 83.4%, 20%, 40% and 48%, respectively (p < 0.0001) (Fig. 2B). Considering the data above we calculated a positive (PPV) and a negative predictive value (NPV). In patients who presented LDH< 367.5 and P/F > 164.5 the PPV was 80% and NPV was 37.7% to predict a CT score < 12.5; in patients who presented LDH> 367.5 U/L and P/F> 164.5 the PPV was 71.4% and the NPV was 73.3% to predict a CT score > 12.5; in patients who had P/F< 164.5 and LDH< 367.5 U/L the PPV was 67% and NPV was 72.3% to predict a CT score > 12.5; in patients who had LDH> 364.5 U/L and P/F< 164.5 the PPV was 83.3% and the NPV was 69.1% to predict a CT score > 12.5. Discussion Given the important impact that the COVID-19 pandemic has determined all over the globe [1], despite the scientific advances made in the last 2 years with the introduction of vaccines, monoclonal antibodies and antivirals for prevention, it still appears a healthcare emergency linked to the spread of infection. Clinical or laboratory tools that predict the outcome at admission to hospital are useful to reduce the need for hospitalization and avoid overloading hospital facilities. The utility of the CT scan to stage COVID-19 pneumonia is well known but, considering the overload and the availability of machinery, it is not always possible to perform, especially in some geographical areas. In the present observational retrospective study performed in 19 COVID-19 units in southern Italy enrolling 321 patients, we confirmed a correlation between the CT score according to Pan and disease progression, as found in previously published studies [15], [16], highlighting that the best cut-off to predict a worse outcome (severe or death) was 12.5. The data available in the literature on this point are few identifying the best cut-off to predict ICU admission with Pan CT scores [15], [16], ranging from 11 [16] to 12.5 [15]. In particular, Aziz-Ahari et al. [15] including 148 patients with a high mortality rate (37%) found the best CT score cut-off for discriminating severe patients was 12.5 with 68.3% sensitivity and 72.7% specificity. Shayganfar et al., including 176 patients with a 21.5% mortality rate found a CT score cut-off point of about 11. Moreover, we found a direct correlation between the CT score value and LDH levels and an indirect correlation between the CT score value and P/F at admission. In particular, we demonstrated that an LDH value higher than 367.5 U/L and a P/F ratio less than 164.5 at admission were associated with a severe CT score (>12.5). In addition, our data showed than when LDH was less than 367.5 U/L and P/F was more than 164.5, the PPV to predict a CT score less than 12.5 was 80%; instead, if LDH was > 367.5 U/L and P/F < 164.5 the PPV to predict a CT score > 12.5 was 83.3%. Some studies showed that LDH usually increase in COVID-19 patients and it’s increase could predict severity [24], [25]. LDH is a cytoplasmatic enzymes highly expressed in the lung, liver, hearth, kidney and skeletal muscle, generally release in blood after cell death: thus, the lung damage, frequently founded in COVID-19 postmortem pathology [26], could increase LDH blood levels [27]. The P/F, a parameters widely used to define the severity of Acute Respiratory Distress Syndrome [28], has already been shown to be able to predict outcome in patients with COVID-19 [29], [30]; moreover, one study highlighted its inverse correlation with extension of the pulmonary inflammatory process on CT [31]. In the literature, to our knowledge, few studies evaluated the clinical and laboratory parameters that can predict a worse CT score at admission [18], [19], [20], [21]. The study by Francone et al., including 130 symptomatic COVID-19 patients showed that the Pan CT score was significantly correlated with C-reaction protein (CRP) (p < 0.0001) and D-dimer (p < 0.0001) levels [18]. The paper by Yadzi et al. [19] is the largest study, to our knowledge, including 478 participants, that evaluated the impact of different laboratory, clinical and demographic parameters to predict a CT score, with a score 0–25 based, similar to the Pan score. They found that anosmia, respiratory rate, CRP (with a cut-off of 90), WBC (with a cut-off of 10.000) and SpO2 (with a cut-off point of 93) was associated with a higher chest CT score. In the study by Man et al. [20], they found that the neutrophil-to-lymphocyte ratio and platelets-to-lymphocyte rate correlated positive with CT scan severity [20]. However, the inhomogeneity observed in these studies was certainly due to the demographic, clinical and laboratory differences in the patients included, the period of inclusion, the different mortality, response to the therapy applied and routine examinations performed during admission. Our study shows some limits: first, the retrospective nature of the study; second, we evaluated only hospitalized patients and hospital mortality; third, some data are missing considering the studies published; fourth, nevertheless the impact of vaccination and viral variants on the clinical presentation and clinical outcome of COVID-19 [32], [33] the data of viral variants were not available and the number of patients enrolled in the present study with full vaccination was very low. Table 3.Table 3 Demographic, clinical and laboratory data at admission according to the CT score. Table 3 Patients with CT score less than 12.5 n° 161 (50.1%) Patients with CT score more than 12.5 n° 160 (49.9%) p value Multivariate analysis Binomial Logistic Regression OR (95% CI) P value Males, n° (%) 108 (67.1%) 110 (68.8%) 0.749a – – Age, years, mean (SD) 64.73 (14.08) 66.83 (14.383) 0.188b – – Days from symptoms to admission, median (Q1-Q3) 5(2–10) 6(2–9) 0.56c – – Charlson comorbidity index, median (Q1-Q3) 2.5(1–4) 3(1–4) 0.32c – – n° (%) with hypertension 76 (47.2%) 89 (55.6%) 0.114a – – n° (%) with cardio-vascular disease 50 (31.1%) 51 (31.9%) 0.843a – – n° (%) with diabetes 36 (22.4%) 41 (25.6%) 0.472a – – n° (%) with chronic kidney disease 10 (6.2%) 14 (8.8%) 0.369a – – n° (%) with chronic obstructive pulmonary disease 15 (9.3%) 11 (6.9%) 0.432a – – n° (%) with liver cirrhosis 6 (3.7%) 7 (4.4%) 0.759a – – n° (%) with malignancy 12 (7.5%) 10 (6.3%) 0.692a – – n° (%) with dementia 9 (5.6%) 3 (1.9%) 0.81a – – n ° (%) with fever during recent history 98(61.3) 86(53.8) 0.213a – – n° (%) with dyspnea during recent history 105(65.6) 131(81.9) 0.001a 0.755 (0.353–1.615) 0.468 n° (%) with astheny during recent history 54(33.8) 43(26.9) 0.224a – – n° (%) with cough during recent history 52(32.5) 55(34.4) 0.813a – – n° (%) with ageusia/dysgeusia during recent history 3(1.9) 1(0.6) 0.371a – – n° (%) with anosmia/hyposmia during recent history 4(2.5) 1(0.6) 0.214a – – n° (%) with diarrhea during recent history 5(3.1) 4(2.5) 0.750a – – n° (%) with skin lesion during recent history 0(0) 0(0) ND – – Median (Q1-Q3) white blood cells (WBC) 7300(6000–10400) 8100(6200–11640) 0.041b 1.000 (1.000–1.000) 0.859 Mean (SD) International Normalized Ratio (INR) 1.12 (0.352) 1.09 (0.201) 0.463b – – Median (Q1-Q3) Blood creatinine 0.9(0.77–1.13) 0.915(0.725–1.22) 0.299b – – Median (Q1-Q3) creatine phosphokinase (CPK) 91(53–163) 105(68–268) 0.125b – – Median (Q1-Q3) lactate dehydrogenase (LDH) 293(235–360) 412(330–563) 0.001b 1.005(1.003–1.008) 0.0001 Median (Q1-Q3) PaO2/FiO2 Ratio (P/F) 213(146–294) 133(98–186.5) 0.001b 0.993(0.989–0.997) 0.001 Mean(SD) ALT 27(22–43) 38.5(23.5–59.5) 0.002b – -d Median (Q1-Q3) AST 29.5(21–44) 41.5(29–59) 0.001b 1.003(0.986–1.019) 0.752 Median (Q1-Q3) Bilirubin 0.6(0.47–0.91) 0.7(0.5–1) 0.069b – – Median (Q1-Q3) Procalcitonin 0.08(0.04–0.18) 0.11(0.07–0.36) 0.083b – – a, Chi-square test; b, Student-T test; c, Wilcoxon rank-sum (Mann-Whitney) test.; d: Not included in multivariate due to the high correlation with AST (0.635) The strengths of our study were the multicenter nature of the design and the size of the population; moreover, this study highlights that two simple biochemical markers generally carried out at admission to hospital can predict the CT score value, thus allowing to discriminate, in a moment of greater affluence to the healthcare facilities, any priorities on the execution of CT. In conclusion, our study suggests that the best CT score to predict a severe outcome or death during hospitalization in patients with COVID-19 was 12.5 (sensitivity: 71.5%, specificity: 66.3%) and that LDH and P/F values at admission correlated with the CT score. Moreover, the data suggest that the patients with a low LDH and high P/F ratio at admission have a low probability of having a severe CT score and, thus, they may undergo CT scan with less urgency, while those with both high LDH and low P/F ratio more frequently have a severe CT score and, thus, should undergo CT scan immediately. However, studies on larger cohorts of patients with the analysis of all the biochemical parameters are needed to confirm these data. Institutional review board statement The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of the University of Campania L. Vanvitelli, Naples (n°10877/2020, May 11, 2020). Funding “POR Campania FESR 2014–2020-Avviso per l’acquisizione di manifestazioni di interesse per la realizzazione di servizi di ricerca e sviluppo per la lotta contro il Covid-19 (DGR n. 140 del 17 marzo 2020), Project: ”IDENTIFICAZIONE DEI FATTORI DEMOGRAFICI, CLINICI, VIROLOGICI, GENETICI, IMMUNOLOGICI E SIEROLOGICI ASSOCIATI AD OUTCOME SFAVOREVOLE NEI SOGGETTI CON COVID-19”, Regione Campania, Italy, and POR FESR Campania 2014 – 2020- Avviso per l’acquisizione di manifestazioni di interesse da parte degli Organismi di Ricerca per la realizzazione di servizi di ricerca, sviluppo e innovazione per la lotta contro il Covid-19 (DGR n. 504 del 10.11.2021)-Regione Campania, Italy; Project: Impatto delle nuove varianti, l’uso di terapie antivirali precoci e stato vaccinale sulla presentazione clinica del COVID-19: studio restrospettivo/prospettico multicentrico. CRediT authorship contribution statement NC, AR, MP and AlRe were involved in study concept and design, drafting of the manuscript,: AlRe, FS, PM, IG, FGN, VS, VE, RP, RoPa, GC, EM, AM, ASM, GDA, GR, MG, AP, CR and IDL, were involved in critical revision of the manuscript for important intellectual content; FS, PM, IG, FGN, VS, VE, RP, RoPa, AlRe, GC, EM, AM, ASM, GDA, GR, MG, AP, CR and IDL were involved in acquisition of data, analysis and interpretation of data and in critical revision of the manuscript; CoviCamp (Campania COVID-19 group) was involved in the enrolment of the patients. All authors contributing to data analysis, drafting or revising the article have agreed on the journal to which the article will be submitted, gave final approval of the version to be published, and agreed to be accountable for all aspects of the work. Conflicts of Interest The authors declare no conflict of interest. Appendix A Supplementary material Supplementary material . Supplementary material . Acknowledgments Campania COVID-19 network: Nicola Coppola, Caterina Monari, Caterina Sagnelli, Paolo Maggi, Vincenzo Sangiovanni, Fabio Giuliano Numis, Ivan Gentile, Alfonso Masullo, Carolina Rescigno, Giosuele Calabria, Angelo Salomone Megna, Michele Gambardella, Elio Manzillo, Grazia Russo, Vincenzo Esposito, Giuseppina Dell’Aquila, Roberto Parrella, Rodolfo Punzi, Antonio Ponticiello, Mariantonietta Pisaturo, Enrico Allegorico, Raffaella Pisapia, Giovanni Porta, Margherita Macera, Federica Calò, Annamaria Rossomando, Mariana Di Lorenzo, Ferdinando Calabria, Nicola Schiano Moriello, Antonio Russo, Giorgio Bosso, Claudia Serra, Ferdinando Dello Vicario, Valentina Minerva, Giulia De Angelis, Stefania De Pascalis, Giovanni Di Caprio, Addolorata Masiello, Domenica Di Costanzo, Mariano Mazza, Vincenzo Bianco, Valeria Gentile, Antonio Riccardo Buonomo, Biagio Pinchera, Riccardo Scotto. Appendix A Supplementary data associated with this article can be found in the online version at doi:10.1016/j.jiph.2022.12.009. ==== Refs References 1 WHO Coronavirus (COVID-19) Dashboard | WHO Coronavirus (COVID-19) Dashboard With Vaccination Data, https://covid19.who.int/, [Accessed: 2022-05–26]. 2 Sagnelli C. Celia B. Monari C. Cirillo S. De Angelis G. Bianco A. Coppola N. Management of SARS-CoV-2 pneumonia J Med Virol 93 3 2021 1276 1287 10.1002/jmv.26470 Epub 2020 Oct 10. PMID: 32856728; PMCID: PMC7461283 32856728 3 Macera M. De Angelis G. Sagnelli C. Coppola N. Vanvitelli Covid-Group. Clinical presentation of COVID-19: case series and review of the literature Int J Environ Res Public Health 17 14 2020 5062 10.3390/ijerph17145062 PMID: 32674450; PMCID: PMC7399865. 32674450 4 Sheinson D.M. Wong W.B. Solon C.E. Cheng M.M. Shah A. Elsea D. Meng Y. Estimated impact of public and private sector COVID-19 diagnostics and treatments on US healthcare resource utilization Adv Ther 38 2 2021 1212 1226 10.1007/s12325-020-01597-3 Epub 2020 Dec 26. PMID: 33367984; PMCID: PMC7765700 33367984 5 Pisaturo M. Calò F. Russo A. Camaioni C. Giaccone A. Pinchera B. Gentile I. Simeone F. Iodice A. Maggi P. Coppola N. Dementia as risk factor for severe coronavirus disease 2019: a case-control study Front Aging Neurosci 13 2021 698184 10.3389/fnagi.2021.698184 PMID: 34267649; PMCID: PMC8276052. 6 Monari C. Sagnelli C. Maggi P. Sangiovanni V. Numis F.G. Gentile I. Masullo A. Rescigno C. Calabria G. Megna A.S. Gambardella M. Manzillo E. Russo G. Esposito V. Camaioni C. Messina V. Pisaturo M. Allegorico E. Pinchera B. Pisapia R. Catalano M. Salzillo A. Porta G. Signoriello G. Coppola N. More severe COVID-19 in patients with active cancer: results of a multicenter cohort study Front Oncol 11 2021 662746 10.3389/fonc.2021.662746 PMID: 34026639; PMCID: PMC8139554 7 Sardu C. D'Onofrio N. Balestrieri M.L. Barbieri M. Rizzo M.R. Messina V. Maggi P. Coppola N. Paolisso G. Marfella R. Outcomes in patients with hyperglycemia affected by COVID-19: can we do more on glycemic control? Diabetes Care 43 7 2020 1408 1415 10.2337/dc20-0723 Epub 2020 May 19. PMID: 32430456; PMCID: PMC7305003 32430456 8 Gallo Marin B., Aghagoli G., Lavine K., Yang L., Siff E.J., Chiang S.S., Salazar-Mather T.P., Dumenco L., Savaria M.C., Aung S.N., Flanigan T., Michelow I.C. Predictors of COVID-19 severity: A literature review. Rev Med Virol. 2021 Jan;31(1):1–10. doi: 10.1002/rmv.2146. Epub 2020 Jul 30. PMID: 32845042; PMCID: PMC7855377. 9 Russo A. Pisaturo M. Palladino R. Maggi P. Numis F.G. Gentile I. Sangiovanni V. Esposito V. Punzi R. Calabria G. Rescigno C. Salomone Megna A. Masullo A. Manzillo E. Russo G. Parrella R. Dell’Aquila G. Gambardella M. Ponticiello A. Coppola N. on behalf of CoviCam Group Prognostic value of transaminases and bilirubin levels at admission to hospital on disease progression and mortality in patients with COVID-19—an observational retrospective study Pathogens 11 6 2022 652 https://doi.org/10.3390/pathogens11060652 35745506 10 Saini R.K. Saini N. Ram S. Soni S.L. Suri V. Malhotra P. Kaur J. Verma I. Sharma S. Zohmangaihi D. COVID-19 associated variations in liver function parameters: a retrospective study Post Med J 98 1156 2022 91 97 10.1136/postgradmedj-2020-138930 Epub 2020 Nov 12 11 Tripon S. Bilbault P. Fabacher T. Lefebvre N. Lescuyer S. Andres E. Schmitt E. Garnier-Kepka S. Borgne P.L. Muller J. Merdji H. Chaffraix F. Mutter D. Baumert T.F. Meziani F. Doffoel M. Abnormal liver tests and non-alcoholic fatty liver disease predict disease progression and outcome of patients with Covid-19 Clin Res Hepatol Gastroenterol 2022 101894 10.1016/j.clinre.2022.101894 Epub ahead of print. PMID: 35227956 12 Chu X. Zhang G.F. Zheng Y.K. Zhong Y.G. Wen L. Zeng P. Fu C.Y. Tong X.L. Long Y.F. Li J. Liu Y.L. Chang Z.G. Xi H. Clinical features and risk factors of severely and critically ill patients with COVID-19 World J Clin Cases 10 3 2022 840 855 10.12998/wjcc.v10.i3.840 PMID: 35127900; PMCID: PMC8790448. 35127900 13 Chen C.H. Lin S.W. Shen C.F. Hsieh K.S. Cheng C.M. Biomarkers during COVID-19: Mechanisms of Change and Implications for Patient Outcomes Diagn (Basel) 12 2 2022 509 10.3390/diagnostics12020509 PMID: 35204599; PMCID: PMC8870804. 14 Shen Z.Y. Yan X.C. You X.D. Zhang X.W. CT imaging research progress in COVID-19 Curr Med Imaging 18 3 2022 267 274 10.2174/1573405617666210816091217 PMID: 34465280; PMCID: PMC8972255. 34465280 15 Aziz-Ahari A. Keyhanian M. Mamishi S. Mahmoudi S. Bastani E.E. Asadi F. Khaleghi M. Chest C.T. severity score: assessment of COVID‑19 severity and short-term prognosis in hospitalized Iranian patients Wien Med Wochenschr 172 3–4 2022 77 83 10.1007/s10354-022-00914-5 Epub 2022 Feb 8. PMID: 35133531; PMCID: PMC8824536 35133531 16 Shayganfar A. Sami R. Sadeghi S. Dehghan M. Khademi N. Rikhtehgaran R. Basiratnia R. Ferdosi F. Hajiahmadi S. Risk factors associated with intensive care unit (ICU) admission and in-hospital death among adults hospitalized with COVID-19: a two-center retrospective observational study in tertiary care hospitals Emerg Radiol 28 4 2021 691 697 10.1007/s10140-021-01903-8 33534017 17 Laino M.E. Ammirabile A. Lofino L. Lundon D.J. Chiti A. Francone M. Savevski V. Prognostic findings for ICU admission in patients with COVID-19 pneumonia: baseline and follow-up chest CT and the added value of artificial intelligence Emerg Radiol 29 2 2022 243 262 10.1007/s10140-021-02008-y Epub 2022 Jan 20. PMID: 35048222; PMCID: PMC8769787 35048222 18 Francone M. Iafrate F. Masci G.M. Coco S. Cilia F. Manganaro L. Panebianco V. Andreoli C. Colaiacomo M.C. Zingaropoli M.A. Ciardi M.R. Mastroianni C.M. Pugliese F. Alessandri F. Turriziani O. Ricci P. Catalano C. Chest CT score in COVID-19 patients: correlation with disease severity and short-term prognosis Eur Radiol 30 12 2020 6808 6817 10.1007/s00330-020-07033-y Epub 2020 Jul 4. PMID: 32623505; PMCID: PMC7334627 32623505 19 Yazdi N.A. Ghadery A.H. SeyedAlinaghi S. Jafari F. Jafari S. Hasannezad M. Koochak H.E. Salehi M. Manshadi S.A.D. Meidani M. Hajiabdolbaghi M. Ahmadinejad Z. Khalili H. Mehrabi Nejad M.M. Abbasian L. Predictors of the chest CT score in COVID-19 patients: a cross-sectional study Virol J 18 1 2021 225 10.1186/s12985-021-01699-6 Erratum in: Virol J. 2021 Dec 6;18(1):241. PMID: 34794467; PMCID: PMC8600490 34794467 20 Man M.A. Rajnoveanu R.M. Motoc N.S. Bondor C.I. Chis A.F. Lesan A. Puiu R. Lucaciu S.R. Dantes E. Gergely-Domokos B. Fira-Mladinescu O. Neutrophil-to-lymphocyte ratio, platelets-to-lymphocyte ratio, and eosinophils correlation with high-resolution computer tomography severity score in COVID-19 patients PLoS One 16 6 2021 e0252599 10.1371/journal.pone.0252599 PMID: 34181675; PMCID: PMC8238190 21 Canovi S. Besutti G. Bonelli E. Iotti V. Ottone M. Albertazzi L. Zerbini A. Pattacini P. Giorgi Rossi P. Colla R. Fasano T. Reggio Emilia COVID-19 Working Group;. The association between clinical laboratory data and chest CT findings explains disease severity in a large Italian cohort of COVID-19 patients BMC Infect Dis 21 1 2021 157 10.1186/s12879-021-05855-9 PMID: 33557778; PMCID: PMC7868898. 33557778 22 Pan F. Ye T. Sun P. Gui S. Liang B. Li L. Zheng D. Wang J. Hesketh R.L. Yang L. Zheng C. Time course of lung changes at chest CT during recovery from coronavirus disease 2019 (COVID-19) Radiology 295 3 2020 715 721 10.1148/radiol.2020200370 Epub 2020 Feb 13. PMID: 32053470; PMCID: PMC7233367 32053470 23 StataCorp. 2019. Stata Statistical Software: Release 16. College Station, TX: StataCorp LLC. 24 Fialek B. Pruc M. Smereka J. Jas R. Rahnama-Hezavah M. Denegri A. Szarpak A. Jaguszewski M.J. Peacock F.W. Szarpak L. Diagnostic value of lactate dehydrogenase in COVID-19: a systematic review and meta-analysis Cardiol J 2022 10.5603/CJ.a2022.0056 Epub ahead of print. PMID: 35762075 25 Wu M.Y. Yao L. Wang Y. Zhu X.Y. Wang X.F. Tang P.J. Chen C. Clinical evaluation of potential usefulness of serum lactate dehydrogenase (LDH) in 2019 novel coronavirus (COVID-19) pneumonia Respir Res 21 1 2020 171 10.1186/s12931-020-01427-8 PMID: 32631317; PMCID: PMC7336103. 32631317 26 Hammoud H. Bendari A. Bendari T. Bougmiza I. Histopathological findings in COVID-19 cases: a systematic review Cureus 14 6 2022 e25573 10.7759/cureus.25573 PMID: 35784976; PMCID: PMC9249248 27 Drent M. Cobben N.A. Henderson R.F. Wouters E.F. van Dieijen-Visser M. Usefulness of lactate dehydrogenase and its isoenzymes as indicators of lung damage or inflammation Eur Respir J 9 8 1996 1736 1742 10.1183/09031936.96.09081736 8866602 28 ARDS Definition Task Force, Ranieri VM, Rubenfeld GD, Thompson BT, Ferguson ND, Caldwell E, Fan E, Camporota L, Slutsky AS. Acute respiratory distress syndrome: the Berlin Definition. JAMA. 2012 Jun 20;307(23):2526–33. doi: 10.1001/jama.2012.5669. PMID: 22797452. 29 Vedovati M.C. Barbieri G. Urbini C. D'Agostini E. Vanni S. Papalini C. Pucci G. Cimini L.A. Valentino A. Ghiadoni L. Becattini C. Clinical prediction models in hospitalized patients with COVID-19: A multicenter cohort study Respir Med 202 2022 106954 10.1016/j.rmed.2022.106954 Epub ahead of print. PMID: 36057141; PMCID: PMC9392655 30 Sartini S. Massobrio L. Cutuli O. Campodonico P. Bernini C. Sartini M. Cristina M.L. Castellani L. Ceschi L. Spadaro M. Gratarola A. Barbera P. Role of SatO2, PaO2/FiO2 Ratio and PaO2 to Predict Adverse Outcome in COVID-19: A Retrospective, Cohort Study Int J Environ Res Public Health 18 21 2021 11534 10.3390/ijerph182111534 PMID: 34770046; PMCID: PMC8582831. 34770046 31 Turcato G. Panebianco L. Zaboli A. Scheurer C. Ausserhofer D. Wieser A. Pfeifer N. Correlation between arterial blood gas and CT volumetry in patients with SARS-CoV-2 in the emergency department Int J Infect Dis 97 2020 233 235 10.1016/j.ijid.2020.06.033 Epub 2020 Jun 15. PMID: 32553834; PMCID: PMC7295461 32553834 32 Baradaran H.R. Dehghanbanadaki H. Moradpour F. Eshrati B. Moradi G. Azami M. Haji Ghadery A. Mehrabi Nejad M.M. Moradi Y. The effect of COVID-19 mRNA vaccines against postvaccination laboratory-confirmed SARS-CoV-2 infection, symptomatic COVID-19 infection, hospitalization, and mortality rate: a systematic review and meta-analysis Expert Rev Vaccin 2022 1 10 10.1080/14760584.2022.2102001 Epub ahead of print. PMID: 35830883 33 Mendiola-Pastrana I.R. López-Ortiz E. Río de la Loza-Zamora J.G. González J. Gómez-García A. López-Ortiz G. SARS-CoV-2 variants and clinical outcomes: a systematic review Life (Basel) 12 2 2022 170 10.3390/life12020170 PMID: 35207458; PMCID: PMC8879159. 35207458
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==== Front Colloids Surf B Biointerfaces Colloids Surf B Biointerfaces Colloids and Surfaces. B, Biointerfaces 0927-7765 1873-4367 Elsevier B.V. S0927-7765(22)00774-3 10.1016/j.colsurfb.2022.113090 113090 Article Role of cholesterol-recognition motifs in the infectivity of SARS-CoV-2 variants Baier Carlos Javier a1 Barrantes Francisco J. b2 a Instituto de Ciencias Biológicas y Biomédicas del Sur (INBIOSUR), Universidad Nacional del Sur (UNS), Consejo de Investigaciones Científicas y Técnicas (CONICET), Departamento de Biología, Bioquímica y Farmacia, San Juan 670, B8000ICN, Bahía Blanca b Laboratory of Molecular Neurobiology, BIOMED UCA-CONICET, 1600 Av. A. Moreau de Justo, C1107AAZ Buenos Aires, Argentina 1 ORCID: 0000-0001-6572-0664 2 ORCID: 0000-0002-4745-681X 12 12 2022 12 12 2022 1130906 11 2022 2 12 2022 10 12 2022 © 2022 Elsevier B.V. All rights reserved. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. The presence of linear amino acid motifs with the capacity to recognize the neutral lipid cholesterol, known as Cholesterol Recognition/interaction Amino acid Consensus sequence (CRAC), and its inverse or mirror image, CARC, has recently been reported in the primary sequence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike S homotrimeric glycoprotein. These motifs also occur in the two other pathogenic coronaviruses, SARS-CoV, and Middle-East respiratory syndrome CoV (MERS-CoV), most conspicuously in the transmembrane domain, the fusion peptide, the amino-terminal domain, and the receptor binding domain of SARS-CoV-2 S protein. Here we analyze the presence of cholesterol-recognition motifs in these key regions of the spike glycoprotein in the pathogenic CoVs. We disclose the inherent pathophysiological implications of the cholesterol motifs in the virus-host cell interactions and variant infectivity. Graphical abstract Keywords Cholesterol cholesterol recognition motifs viral infectivity cell-surface phenomena cholesterol-protein interactions fusion proteins ==== Body pmc1 Introduction The appearance of ligand recognition in living organisms has occurred in various instances as a result of coevolution between interacting partners. In the case of pathogens like viruses, the interactions between their infective machinery and eukaryotic cell-surface receptors may not follow this coevolutionary mechanism [1]. This is because the virion receptors, transmembrane proteases in the case of coronaviruses (CoVs), fulfill preexisting physiological roles in the eukaryotic cells which the viruses exploit to serve their own pathophysiological cycle. Soon after the irruption of the COVID-19 pandemic, structural work using cryo-electron microscopy (cryo-EM), and to a lesser extent X-ray diffraction and nuclear magnetic resonance (NMR) spectroscopy, produced spectacular advances in our knowledge of the causative agent, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). These unprecedentedly vertiginous developments produced, in the course of a few months, atomistic depictions of the virus and its canonical cell-surface receptor, the metalloprotease angiotensin converting enzyme 2 (ACE2), and abundant hypotheses on the mechanistic interactions between the two (reviewed in [1]). A possible reason why ACE2 has an evolutionarily advantage in SARS-CoV-2 as a target molecule is the ubiquitous cell-surface distribution of the enzyme in many host tissues, particularly mucosal epithelia [1], [2]. The spike (S) glycoprotein of SARS-CoV-2 and other pathogenic CoVs is the one that interacts with ACE2. Binding to and fusion with the host-cell membrane appear to be sensitive to the lipid environment in which these two coupled processes occur [3]. Cholesterol plays important roles in orchestrating the biophysical properties of both proteins and lipids in the plasma membrane [4]. The observed cholesterol dependence of some viruses leads us to consider how they take advantage of cholesterol properties, in so doing optimizing viral infection or other steps of their life cycle. Several viral cholesterol-binding proteins relevant to virus entry processes have been described [5]. The amount of cholesterol in the virus envelope also apears to play a role: in members of the alphavirus genus (Chikungungya, Sindibis, Venezuelan equine encephalitis and Ross River virus), the cholesterol/phospholipid molar ratio is higher than in the host plasma membranes [6]. The higher cholesterol level in the viral particle is important in the organization of the viral envelope [7]. Cholesterol depletion in the influenza A virus envelope produces nicks and holes in the viral envelope, reducing virus infectivity [8]. Moreover, virions of influenza A virus and respiratory syncytial virus released from the cholesterol-depleted cells were less stable than those released from untreated cells [9]. The transmembrane gp41 subunit, an HIV-1 envelope protein, interacts directly with cholesterol in the viral membrane [10], [11]. Recent structural work is beginning to unravel the functional relationship between the S protein and cholesterol, present in both the host-cell membrane and the viral envelope bilayer [12]. ACE2 of Vero E6 and Caco-2 cells is recovered in the detergent-resistant phase in biochemical assays, an experimental finding that is conventionally, albeit not universally, taken as evidence that a protein resides in liquid-ordered (Lo) lipid domains, also termed “lipid rafts”. There is also substantial evidence in favor of the notion that SARS-CoV-2 entry requires the participation of cholesterol [13], [14]. In this regard, Tang et al. [15] proposed that rather than simply organizing ACE2 and SARS-CoV-2 proteins into cholesterol-rich Lo lipid domains, cholesterol might be directly involved in membrane fusion dynamics, guaranteeing the formation of the fusion intermediate. Meher et al. [16] and Pattnaik et al. [17] demonstrated that membrane cholesterol is vital for the fusogenic activity of SARS-CoVs viruses. Nardacci et al. [18] reported that the accumulation of lipids in SARS-CoV-2 infected cells, both in vitro and in the lungs of patients, could be involved in SARS-CoV-2 pathogenesis. Furthermore, membrane cholesterol depletion of ACE2-expressing HEK293T cells with methyl-β-cyclodextrin reduced SARS-CoV-2 infection, suggesting that cholesterol-rich lipid domains, as well as endosomal acidification, are essential requirements for SARS-CoV-2 infection [13]. Sanders et al. [14] showed that pre-treatment of SARS-CoV-2 with methyl-β-cyclodextrin blocked virus infection, further reinforcing the notion that cholesterol content in the viral particle is critical for infectivity. Here we analyze the presence of cholesterol-recognition motifs in key regions of the spike glycoprotein in the pathogenic CoVs and disclose their possible pathophysiological implications in the virus-host cell interactions. 2 Material and Methods Search for the presence and localization of the consensus sequence for the "CRAC" motif, [L/V]–[X](1–5)–[Y]–[X](1–5)–[R/K], or the "CARC" motif, [R/K]–[X](1–5)–[ YFW]–[X](1–5)–[L/V], was carried out on the SARS-CoV-1 (Accession: AAU04646), SARS-CoV-2 (Accession: YP_009724390), MERS-CoV (Accession: K9N5Q8), and Omicron BA.1 (Accession: 7WP9_A) spike protein sequences, available at the National Center for Biotechnology Information (NCBI). To this end, we employed the Fuzzpro application of the Jemboss software (European Molecular Biology Open Software Suite, EMBOSS) as in our original description of the onsensus motifs [19]. Molecular representations were performed with Visual Molecular Dynamics (VMD) software, and the PDB files available in the protein data bank (PDB files 6XR8 and 7WP9, for SARS-CoV-2 and Omicron BA.1 spike proteins, respectively). 3 Results and Discussion 3.1 Consensus cholesterol-recognition sequences in the pathogenic CoVs Cell-surface receptors for neurotransmitters have been instrumental in the discovery of linear amino acid sequences with the capacity to recognize cholesterol. Studies of the benzodiazepine receptor led to the identification of the sequence (L/V)-X−5-(Y)-X−5-(K/R), known as Cholesterol Recognition/interaction Amino acid Consensus sequence (CRAC) [20] ( Fig. 1  A). Work on the nicotinic acetylcholine receptor (nAChR) identified the inverse or mirror image of CRAC, which we coined “CARC”: (K/R)-X1−5-(Y/F/W)-X1−5-(L/V) [19] (Fig. 1  A). In subsequent work, we found that these two cholesterol consensus motifs are present in a great variety of membrane proteins [21], including the superfamily of ligand-gated ion-channel (LGIC) proteins [21], other channels like the transient receptor potential (TRP) channel [22], and in the large superfamily of membrane-bound GPCR proteins [21]. CRAC/CARC sequences share a central aromatic residue, like tyrosine for CRAC, and tyrosine, phenylalanine, or tryptophan for CARC, flanked on both sides by one to five amino acid residues ending in a basic (arginine or lysine) and an apolar terminus (valine or leucine) (Fig. 1  A). Both CARC and CRAC are vectorial motifs, with CARC preferentially, albeit not exclusively, located in the exofacial membrane leaflet, whereas CRAC most often occurs in the cytoplasmic-facing leaflet of the plasma membrane [21].Fig. 1 Cholesterol-recognition motifs in the TM region of spike S glycoprotein from SARS-CoV-2, SARS-CoV, and MERS-CoV. A) Sequences of the cholesterol-recognition motifs. B) Schematic diagram of SARS-CoV-2 primary structure. SS, signal sequence; NTD, N-terminal domain; RBD, receptor binding domain; FP, fusion peptide; HR1, heptad repeat 1; CH, central helix; CD, connector domain; HR2, heptad repeat 2; TM, transmembrane domain; CT, cytoplasmic tail. C) Cholesterol-recognition motifs along the linear sequences of the TMs. The TM region exhibits back-to-back mirror images of highly conserved CRAC (green) and CARC (red) motifs at the N-term juxtamembrane aromatic region. Fig. 1 The three pathogenic CoVs, namely the severe acute respiratory syndrome (SARS-CoV), the virus that gave rise to the epidemic at the brink of the 21st century, followed by the Middle-East respiratory syndrome CoV (MERS-CoV), and the contemporary SARS-CoV-2 associated with the pandemic, possess cholesterol-recognition motifs (Fig. 1  A) in various regions of the virion, and most prominently in the spike S glycoprotein. Several cholesterol-recognition motifs occur in the transmembrane (TM) domain (Fig. 1), in the fusion peptide (FP, Fig. 2), in the amino-terminal domain (NTD, Fig. 3), and the receptor binding domain (RBD, Fig. 4) of SARS-CoV-2 S protein. Fig. 1B depicts the SARS-CoV-2 spike (S) glycoprotein sequence, where the different functionally relevant regions of the virus can be identified, starting from the signal sequence (SS) in the S1 subunit, which also harbors the NTD and the important RBD. The key role of the S1 subunit is to prevent the praecox fusion of the S2 subunit to the target plasma membrane in the host cell and to bind to the mammalian cell-surface receptor, the metalloprotease angiotensin-converting enzyme-2 (ACE2). This step involves the proteolytic cleavage that activates the S protein by the host cell plasma membrane-resident transmembrane protease TMPRSS2 [23], a requisite for the corformational change of the S2 subunit [24] from a structurally disordered state into a wedge-shaped conformer [25] apt to undergo the fusion of the viral and plasma membranes via its FP.Fig. 2 Cholesterol-recognition motifs in the fusion peptide of the spike S glycoprotein from the SARS-CoV-2, SARS-CoV, and MERS-CoV, the three highly pathogenic members of the heptad human CoVs. A) FP segment (red ribbon) in the viral envelope of the SARS-CoV-2 S glycoprotein B) Close-up view of the FP in the SARS-CoV-2 S protein. C) Cholesterol-recognition motifs along the linear sequences of the FPs. Fig. 2 Fig. 3 Cholesterol-recognition motifs in the N-terminal domain (NTD) region of the spike S glycoprotein from SARS-CoV-2. Sequences of the cholesterol-recognition motifs, A) CRAC and b) CARC, localized in the NTD region of SARS-CoV-2 spike protein. C) CARC and CARC motifs are colored in the NTD segment. The yellow and orange segments represent the CARC129-141 and CRAC141-150 motifs, respectively. D) Close-up view of the segments shown in C). Fig. 3 Fig. 4 Top view of SARS-CoV-2, and Omicron BA.1 spike protein. CRAC and CARC motifs are colored green and red, respectively. The approximate position of the sequences SARS-CoV-2 444-461, and Omicron BA.1 441-458 are highlighted by a dotted light-blue circle. Letters highlighted in yellow correspond to plasma membrane-interacting residues proposed by Overduin et al. [43]. Fig. 4 3.2 CARC/CRAC cholesterol recognition motifs in the S protein transmembrane (TM) domain The TM domain of the S protein anchors the glyoprotein in the virus envelope (Fig. 1B-C). It consists of three portions: a juxtamembrane aromatic region, a central hydrophobic region, and a cysteine-rich region [26]. As shown in Fig. 1  C, the membrane-embedded regions of the S protein of the three pathogenic human CoVs share essentially the same cholesterol-recognition motifs, with a high degree of amino acid homology, especially in the two SARS virus. The CARC motif is deeper in the aromatic amino acid-rich part of the TM, with a CRAC laying immediately adjacent to it, partly embedded in the juxtamembrane portion, in a tail-to-tail disposition. We originally described this CARC-CRAC “back-to-back (or tail-to-tail)” mirror-image configuration in members of the GPCR superfamily [21]. The sequence homology observed in the TMs shown in Fig. 1  C (and fusion peptide, see below), attests to the possible functional relevance of the cholesterol-recognition motifs in CoVs [26]. The interaction between cholesterol and SARS-CoV-2 TM regions could be impaired after pre-treatment of SARS-CoV-2 with the cholesterol-depleting compound methyl-β-cyclodextrin. This cholesterol-sequestering organic compound induces a conformational change in the viral particle that could be responsible, at least in part, for the reduced virus infectivity reported by Sanders et al. [14]. Wei and coworkers recently reported the occurrence of six such tail-to-tail cholesterol mirror motifs in the SARS-CoV-2 S protein and experimentally demonstrated, using a microscale thermophoresis assay, that the S protein binds cholesterol with a half-maximum inhibitory concentration IC50 of ~195 nM, but does not bind the cholesterol analogs campesterol or epicholesterol [27]. Contrary to expectations, the TM segment (residues 1203-1218) used in the article of Wei et al. [27] did not show interactions with cholesterol. A preliminary study using atomistic molecular dynamics simulations found that cholesterol preferred the C-terminal half of the TM segment instead of binding to the CRAC/CARC motifs in the TM region [28]. Concerning SARS-CoV 2 S protein TM segment-cholesterol interactions, the differences between live cells experiments and in silico analyses or synthetic TM-segments-cholesterol interactions may be due to the role played by the rest of the S protein in live cells, acting as a final translator that defines virus infectivity. 3.3 Cholesterol recognition motifs in the fusion peptide (FP) of the S glycoprotein For enveloped viruses, the release of their genome into the host cell requires the fusion of their membrane bilayer to either the plasma membrane or the endocytic vesicle membranes of the target cell. The FP is a short segment (~28 amino acid residues long) of the S2 domain that constitutes the functional fusogenic element in SARS-CoV-2 needed for direct fusion to the host lipid membrane [15] (Fig. 2A). Dacon et al. [29] have recently highlighted the potential of the FP as a target epitope to design next-generation CoV vaccines. Cholesterol affects the extent of SARS-CoV-2 binding and fusion to cellular membranes [16], [17], [30], [31]. In Fig. 2A-B, the SARS-CoV-2 S protein FP is highlighted in red in the pre-fusion conformation of the S glycoprotein. The fusion peptide is precluded from fusing to the target cell, well hidden in the S protein core. The cholesterol-recognition motifs CARC and its mirror image CRAC of the three pathogenic viruses are shown in Fig. 2C. Interestingly, the S glycoprotein FP region contains a conserved CARC motif in the FP N-term (Fig. 2C), and an almost identical CARC motif (KQYG[D/E]CL) in SARS-CoV and SARS-CoV-2 in their C-term region. Conversely, CARC/CRAC motifs are absent in the FP C-term of another pathogenic CoV, MERS-CoV (Fig. 2C). Madu et al. [32] reported that the SARS-CoV S2 fusion peptide 798 SFIEDLLFNKVTLADAGFMKQY 819 GCGKKKK (linker), which includes ~90% of the N-term, and ~40% of the C-term CARC motifs, respectively, promoted a greater extent of lipid mixing in POPC-POPS-cholesterol (1:3:1) liposomes. Mahajan et al. [31], demonstrated that a 64-residue long fusion peptide (LFP) [31], [33], 758 RNTREVFAQVKQMYKTPTLKYFGGFNFSQILPSPLKPTKRSFIEDLLFNKVTLADAGFMKQYGE 821, which includes 7 CARC-motifs and a CRAC motif, exhibits a dose-dependent lipid mixing activity in DMPC liposomes, highlighting its fusogenic potential. An NMR spectroscopy study has recently shown that the FP transforms from an intrinsically disordered structure in solution into a wedge-shaped structure in lipid bicelles, with the hydrophobic, narrow end inserted in the lipid moiety [34]. The FP region that interacts more strongly with bicelles contains the CARC regions shown in Fig. 2C. Santamarina et al. [35] reported that an FP fragment containing the first CARC motif (Fig. 2C) penetrates into the hydrophobic acyl region of the host cell plasma membrane, increasing the dynamics of the fatty acid acyl tails and weakening the membrane structural integrity, possibly a requisite towards viral penetration. Importantly, the increase in membrane flexibility is more pronounced in the more rigid, Lo plasma membrane regions rich in cholesterol [35]. Shen et al. [36] have recently compared the binding modes of SARS-CoV and SARS-CoV-2 FPs using in silico molecular dynamics. They showed that SARS-CoV-2 FP binds to a synthetic POPC/POPE/cholesterol bilayer membrane more effectively than the SARS-CoV FP [36]. Although the amino acid sequences of both FPs are quite similar (Fig. 2C), the corresponding cryo-electron microscopy structures show that the helix length of SARS-CoV FP is longer than that of the SARS-CoV-2 FP [36]. The higher hydrophobicity of the SARS-CoV-2 FP may also contribute to disrupting the target cell membrane [37]. All in all, these structural differences could be responsible for the differential affinities between SARS-CoV and SARS-CoV-2 FPs [36]. The amino acids F817, I818, and L821 present in the short α-helix of the SARS-CoV-2 FP exhibited a stronger interaction with the cell membrane than those of the long α-helix from SARS-CoV [36]. The three hydrophobic amino acid residues involved are part of the N-term CARC motif present in the SARS-CoV-2 FP (Fig. 2C) and are an indispensable requirement for cholesterol binding in the CARC motif [19], [38]. In addition, SARS-CoV FP has two favorable membrane-binding modes, which overlap with the presence of CARC motifs in the N-term and C-term portions of the PF [36] (Fig. 2C). The presence of CARC motifs in the SARS-CoV and SARS-CoV-2 FP could be indicative of an absolute requirement for cholesterol-protein interactions during the early stages of the fusion of the viral particle with the host-cell plasma membrane. The occurrence of a cholesterol-recognition motif in a key region like the FP suggests a relevant biosensor role, guiding the S glycoprotein to cholesterol-rich domains in the host plasma membrane, and improving the efficiency of the virus infectivity. 3.4 Cholesterol recognition motifs in the NTD of the S glycoprotein Scavenger receptor class B type 1 (SR-B1) is a multifunctional membrane-bound protein mainly expressed in liver and one of the heavy-density lipoprotein (HDL) receptors [3]. Wei and coworkers [27] demonstrated that expression of SR-B1 confers susceptibility to SARS-CoV-2 infection, facilitating the attachment and entry of the virus. Since SR-B1 only enhanced viral uptake in the presence of ACE2, the authors interpreted these last results as an indication that SR-B1 is an entry cofactor of SARS-CoV-2 (reviewed in [3]). Inhibitors of SR-B1 or silencing of its expression abrogates SARS-CoV-2 infection, and the presence of HDL significantly increases viral infection. Blocking the cholesterol/HDL binding site of SARS-CoV-2 with mAb 1D2 strongly reduced HDL-enhanced SARS-CoV-2 infection [27]. The mAb 1D2 overlaps antigenic sites with mAb 48 A, a neutralizing human antibody that recognizes the NTD of the S protein [39] (Fig. 1  A). Utilizing cryo-electron microscopy, Chi et al. [39] determined that mAb 4A8 mainly binds to the NTD through three complementarity-determining regions (CDRs). The amino acids Lys147, Lys150, and Tyr145, located in a CRAC motif of NTD-SARS-2-S (Fig. 3A), were identified as important antigenic sites for recognition by mAb 4A8 antibody [27], [39]. Through an in vitro binding assay, Wei et al. [27] found that three cholesterol-binding peptides encompassing the CRAC/CARC region are present in the NTD of SARS-CoV-2: amino acid residues 24-32, 129-150, and 267-277, respectively [27] (Fig. 3A-B). Interestingly, the peptide region that displays the highest interaction with cholesterol is the segment 129-150 [27]. This segment presents two cholesterol recognition motifs along its sequence, i.e., a CARC motif 129KVCEFQFCNDPFL141, and a CRAC motif 141LGVYYHKNNK150 (Fig. 3 C-D; CARC129-141 in yellow, CRAC141-150 in orange). According to Wei et al. [27], SARS-CoV-2 first binds cholesterol and high-density lipoprotein (HDL) (or one of its components). This complex is then recognized by SR-B1 as an entry cofactor, helping to increase the complex concentration in host-cell membrane regions where ACE2 is expressed and facilitating successful encounters with the receptor [3], [27]. It is intriguing how a simple lipid molecule like cholesterol can constitute a molecular target and subsequently bind to a protein motif located outside the plasma membrane. There is, however, a precedent of this molecular interaction: in the Smoothened (SMO) protein, a G protein-coupled receptor, cholesterol binds to the extracellular cysteine-rich domain, located outside the extracellular leaflet of the plasma membrane [40]. Fantini et al. [41], [42] described a ganglioside-binding domain in the NTD, which could enable the binding of SARS-CoV-2 to the plasma membrane-lipid Lo domains. Each spike protein can simultaneously bind three ganglioside molecules. This multivalent binding process could modify the membrane curvature, facilitate lipid coalescence and ACE2 receptor recruitment, thus increasing the chances of finding functional ACE2 receptor molecules in the host membrane [41]. Several mutations in the spike protein contribute to the increased transmissibility of some SARS-CoV-2 variants. The most accepted explanation is that mutations conferring higher affinity of the spike protein for the ACE2 receptor result in more transmissible virus variants. This does not necessarily account for the success of the Omicron variant, suggesting that spike ectodomains directly interact with host plasma membrane bilayers [43]. Overduin et al. [43] recently undertook a detailed in silico study of the membrane-binding surfaces of the spike protein variants, showing that membrane binding propensities increase through different versions, over time, impacting the S protein’s affinity for cell membranes. Spike protein trimers are shown to shift from initial perpendicular stances to increasingly tilted positions that draw viral particles alongside host cell membranes before engaging ACE2 receptors. This culminates in the assembly of the fusion apparatus, enhancing membrane interactions of the more infective variants [43]. The flexibility of the S glycoprotein has been documented experimentally by cryo-electron microscopy [44] and by coarse-grained molecular dynamics studies showing that the protein can lay almost parallel to the membrane surface [45]. In an end-on view of the spike protein ectodomain, as seen from the host cell (Fig. 4), the area of CRAC and CARC exposed motifs in the NTD and RBD increase from the wild-type Wuhan SARS-CoV-2 to the highly infective Omicron BA.1 variant. The RBD segment 445-461 from SARS-CoV-2[27], which contains in its sequence the CRAC442-454 /CARC441-452 motifs exposed in the spike protein surface, has been experimentally shown to interact with cholesterol [27] (Fig. 4). Even though the segments shown in Fig. 4 are conserved in both SARS-CoV-2 444-461 and Omicron BA.1 441-458 virus variants, differences in the protein conformation may result in a better CRAC/CARC surface exposure in the Omicron variant. Higher exposure of CRAC/CARC motifs on the virus S protein binding surface could contribute to the enhanced ability of the spike protein to interact with the host plasma membrane, and consequently, augment virus infectivity. 4 Conclusions From the data presented here, we propose two functional attributes of the cholesterol-recognition motifs in the S glycoprotein of the SARS-CoV-2: 1) the presence of CARC and CRAC motifs in the surface of the S trimer (NTD and RBD) that docks onto the host membrane surface is indicative of actual S protein-cholesterol interactions occurring at the earliest stage of virus infection, that is, during the landing of the virion on the host cell surface; 2) the presence of cholesterol-recognition motifs in the FP segment strongly suggests their involvement in the subsequent fusion step. Thus, the presence of the cholesterol consensus regions provides the structural basis for the sequential i) reduction of dimensionality of the virion binding step, i.e., from the random walk in the 3D space to the 2D of the membrane surface, ii) the accelerated diffusion of the S trimer in the target plasma membrane to iii) dock in cholesterol-rich domains containing the ACE2 receptor. The combination of these cholesterol-dependent steps appears to bear direct relevance to the higher infectivity of the Omicron SARS-CoV-2 variant. Funding Project PIP 222021-2023 GI to FJB. CRediT authorship contribution statement CJB and FJB contributed equally in data curation; FJB conceptualization and writing the initial draft; both authors wrote/edited subsequent multiple versions of the manuscript. CJB conducted analysis of the data and produced all illustations. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author contributions Conceptualization: FJB, CJB; Methodology: FJB, CJB; Investigation: FJB, CJB; Visualization: CJB; Writing: original draft: FJB; review & editing: FJB, CJB. Competing interests Authors declare that they have no competing interests. Data availability Data will be made available on request. ==== Refs References 1 Barrantes F.J. The Contribution of Biophysics and Structural Biology to Current Advances in COVID-19 Annu Rev Biophys 50 2021 493 523 33957057 2 Barrantes F.J. The unfolding palette of COVID-19 multisystemic syndrome and its neurological manifestations Brain Behav Immun Health 14 2021 100251 3 Barrantes F.J. The constellation of cholesterol-dependent processes associated with SARS-CoV-2 infection Prog Lipid Res 87 2022 101166 4 Maxfield F.R. van Meer G. Cholesterol, the central lipid of mammalian cells Curr Opin Cell Biol 22 2010 422 429 20627678 5 Schroeder C. Cholesterol-binding viral proteins in virus entry and morphogenesis Subcell Biochem 51 2010 77 108 20213541 6 Sousa I.P. Jr. Carvalho C.A.M. Gomes A.M.O. Current Understanding of the Role of Cholesterol in the Life Cycle of Alphaviruses Viruses 13 2020 7 Sousa I.P. Jr. Carvalho C.A. Ferreira D.F. Weissmuller G. Rocha G.M. Silva J.L. Gomes A.M. Envelope lipid-packing as a critical factor for the biological activity and stability of alphavirus particles isolated from mammalian and mosquito cells, The Journal of biological chemistry 286 2011 1730 1736 21075845 8 Barman S. Nayak D.P. Lipid raft disruption by cholesterol depletion enhances influenza A virus budding from MDCK cells Journal of virology 81 2007 12169 12178 17855515 9 Bajimaya S. Frankl T. Hayashi T. Takimoto T. Cholesterol is required for stability and infectivity of influenza A and respiratory syncytial viruses Virology 510 2017 234 241 28750327 10 Nieto-Garai J.A. Arboleya A. Otaegi S. Chojnacki J. Casas J. Fabrias G. Contreras F.X. Krausslich H.G. Lorizate M. Cholesterol in the Viral Membrane is a Molecular Switch Governing HIV-1 Env Clustering Adv Sci (Weinh) 8 2021 2003468 11 Epand R.F. Thomas A. Brasseur R. Vishwanathan S.A. Hunter E. Epand R.M. Juxtamembrane protein segments that contribute to recruitment of cholesterol into domains Biochemistry 45 2006 6105 6114 16681383 12 Glende J. Schwegmann-Wessels C. Al-Falah M. Pfefferle S. Qu X. Deng H. Drosten C. Naim H.Y. Herrler G. Importance of cholesterol-rich membrane microdomains in the interaction of the S protein of SARS-coronavirus with the cellular receptor angiotensin-converting enzyme 2 Virology 381 2008 215 221 18814896 13 Li X. Zhu W. Fan M. Zhang J. Peng Y. Huang F. Wang N. He L. Zhang L. Holmdahl R. Meng L. Lu S. Dependence of SARS-CoV-2 infection on cholesterol-rich lipid raft and endosomal acidification Comput Struct Biotechnol J 19 2021 1933 1943 33850607 14 Sanders D.W. Jumper C.C. Ackerman P.J. Bracha D. Donlic A. Kim H. Kenney D. Castello-Serrano I. Suzuki S. Tamura T. Tavares A.H. Saeed M. Holehouse A.S. Ploss A. Levental I. Douam F. Padera R.F. Levy B.D. Brangwynne C.P. SARS-CoV-2 requires cholesterol for viral entry and pathological syncytia formation Elife 10 2021 e65962 15 Tang T. Bidon M. Jaimes J.A. Whittaker G.R. Daniel S. Coronavirus membrane fusion mechanism offers a potential target for antiviral development Antiviral Res 178 2020 104792 16 Meher G. Bhattacharjya S. Chakraborty H. Membrane Cholesterol Modulates Oligomeric Status and Peptide-Membrane Interaction of Severe Acute Respiratory Syndrome Coronavirus Fusion Peptide J Phys Chem B 123 2019 10654 10662 31743644 17 Pattnaik G.P. Bhattacharjya S. Chakraborty H. Enhanced Cholesterol-Dependent Hemifusion by Internal Fusion Peptide 1 of SARS Coronavirus-2 Compared to Its N-Terminal Counterpart Biochemistry 60 2021 559 562 33569952 18 Nardacci R. Colavita F. Castilletti C. Lapa D. Matusali G. Meschi S. Del Nonno F. Colombo D. Capobianchi M.R. Zumla A. Ippolito G. Piacentini M. Falasca L. Evidences for lipid involvement in SARS-CoV-2 cytopathogenesis Cell Death Dis 12 2021 263 33712574 19 Baier C.J. Fantini J. Barrantes F.J. Disclosure of cholesterol recognition motifs in transmembrane domains of the human nicotinic acetylcholine receptor Scientific reports 1 2011 69 22355588 20 Li H. Papadopoulos V. Peripheral-type benzodiazepine receptor function in cholesterol transport. Identification of a putative cholesterol recognition/interaction amino acid sequence and consensus pattern Endocrinology 139 1998 4991 4997 9832438 21 Fantini J. Epand R.M. Barrantes F.J. Cholesterol-Recognition Motifs in Membrane Proteins Adv Exp Med Biol 1135 2019 3 25 31098808 22 Lee A.G. Interfacial Binding Sites for Cholesterol on TRP Ion Channels Biophysical Journal 117 2019 2020 2033 31672270 23 Hoffmann M. Kleine-Weber H. Schroeder S. Krüger N. Herrler T. Erichsen S. Schiergens T.S. Herrler G. Wu N.H. Nitsche A. Müller M.A. Drosten C. Pöhlmann S. SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor Cell 181 2020 271-280.e278 24 Cai Y. Zhang J. Xiao T. Peng H. Sterling S.M. Walsh R.M. Rawson S. Rits-Volloch S. Chen B. Distinct conformational states of SARS-CoV-2 spike protein Science (New York, N.Y.) 369 2020 1586 1592 32694201 25 Koppisetti R.K. Fulcher Y.G. Van S.R. Doren, Fusion Peptide of SARS-CoV-2 Spike Rearranges into a Wedge Inserted in Bilayered Micelles Journal of the American Chemical Society 2021 26 X. Xia, Domains and Functions of Spike Protein in SARS-Cov-2 in the Context of Vaccine Design, 13 (2021) 109. 27 Wei C. Wan L. Yan Q. Wang X. Zhang J. Yang X. Zhang Y. Fan C. Li D. Deng Y. Sun J. Gong J. Yang X. Wang Y. Wang X. Li J. Yang H. Li H. Zhang Z. Wang R. Du P. Zong Y. Yin F. Zhang W. Wang N. Peng Y. Lin H. Feng J. Qin C. Chen W. Gao Q. Zhang R. Cao Y. Zhong H. HDL-scavenger receptor B type 1 facilitates SARS-CoV-2 entry Nature metabolism 2 2020 1391 1400 28 S. Lall, P. Balaram, S. Gosavi, M.K. Mathew, Dynamics and self-assembly of the SARS-CoV-2 spike transmembrane domain, (2021) 2021.2006.2007.447334. 29 Dacon C. Tucker C. Peng L. Lee C.D. Lin T.H. Yuan M. Cong Y. Wang L. Purser L. Williams J.K. Pyo C.W. Kosik I. Hu Z. Zhao M. Mohan D. Cooper A.J.R. Peterson M. Skinner J. Dixit S. Kollins E. Huzella L. Perry D. Byrum R. Lembirik S. Drawbaugh D. Eaton B. Zhang Y. Yang E.S. Chen M. Leung K. Weinberg R.S. Pegu A. Geraghty D.E. Davidson E. Douagi I. Moir S. Yewdell J.W. Schmaljohn C. Crompton P.D. Holbrook M.R. Nemazee D. Mascola J.R. Wilson I.A. Tan J. Broadly neutralizing antibodies target the coronavirus fusion peptide Science 2022 eabq3773 35857439 30 Correa Y. Waldie S. Thepaut M. Micciula S. Moulin M. Fieschi F. Pichler H. Trevor Forsyth V. Haertlein M. Cardenas M. SARS-CoV-2 spike protein removes lipids from model membranes and interferes with the capacity of high density lipoprotein to exchange lipids J Colloid Interface Sci 602 2021 732 739 34157514 31 Mahajan M. Chatterjee D. Bhuvaneswari K. Pillay S. Bhattacharjya S. NMR structure and localization of a large fragment of the SARS-CoV fusion protein: Implications in viral cell fusion Biochim Biophys Acta Biomembr 1860 2018 407 415 28988778 32 Madu I.G. Roth S.L. Belouzard S. Whittaker G.R. Characterization of a highly conserved domain within the severe acute respiratory syndrome coronavirus spike protein S2 domain with characteristics of a viral fusion peptide Journal of virology 83 2009 7411 7421 19439480 33 Mahajan M. Bhattacharjya S. NMR structures and localization of the potential fusion peptides and the pre-transmembrane region of SARS-CoV: Implications in membrane fusion Biochim Biophys Acta 1848 2015 721 730 25475644 34 Koppisetti R.K. Fulcher Y.G. Van S.R. Doren, Fusion Peptide of SARS-CoV-2 Spike Rearranges into a Wedge Inserted in Bilayered Micelles J Am Chem Soc 143 2021 13205 13211 34375093 35 Santamaria A. Batchu K.C. Matsarskaia O. Prevost S.F. Russo D. Natali F. Seydel T. Hoffmann I. Laux V. Haertlein M. Darwish T.A. Russell R.A. Corucci G. Fragneto G. Maestro A. Zaccai N.R. Strikingly Different Roles of SARS-CoV-2 Fusion Peptides Uncovered by Neutron Scattering J Am Chem Soc 144 2022 2968 2979 35157798 36 Shen H. Wu Z. Chen L. Different Binding Modes of SARS-CoV-1 and SARS-CoV-2 Fusion Peptides to Cell Membranes: The Influence of Peptide Helix Length J Phys Chem B 2022 37 Lai A.L. Freed J.H. SARS-CoV-2 Fusion Peptide has a Greater Membrane Perturbating Effect than SARS-CoV with Highly Specific Dependence on Ca2+ Journal of Molecular Biology 433 2021 166946 38 Di Scala C. Baier C.J. Evans L.S. Williamson P.T.F. Fantini J. Barrantes F.J. Relevance of CARC and CRAC Cholesterol-Recognition Motifs in the Nicotinic Acetylcholine Receptor and Other Membrane-Bound Receptors Current topics in membranes 80 2017 3 23 28863821 39 Chi X. Yan R. Zhang J. Zhang G. Zhang Y. Hao M. Zhang Z. Fan P. Dong Y. Yang Y. Chen Z. Guo Y. Zhang J. Li Y. Song X. Chen Y. Xia L. Fu L. Hou L. Xu J. Yu C. Li J. Zhou Q. Chen W. A neutralizing human antibody binds to the N-terminal domain of the Spike protein of SARS-CoV-2 Science 369 2020 650 655 32571838 40 Kinnebrew M. Woolley R.E. Ansell T.B. Byrne E.F.X. Frigui S. Luchetti G. Sircar R. Nachtergaele S. Mydock-McGrane L. Krishnan K. Newstead S. Sansom M.S.P. Covey D.F. Siebold C. Rohatgi R. Patched 1 regulates Smoothened by controlling sterol binding to its extracellular cysteine-rich domain Sci Adv 8 2022 eabm5563 35658032 41 Fantini J. Chahinian H. Yahi N. Leveraging coronavirus binding to gangliosides for innovative vaccine and therapeutic strategies against COVID-19 Biochemical and biophysical research communications 538 2021 132 136 33097184 42 Fantini J. Chahinian H. Yahi N. Synergistic antiviral effect of hydroxychloroquine and azithromycin in combination against SARS-CoV-2: What molecular dynamics studies of virus-host interactions reveal Int J Antimicrob Agents 56 2020 106020 43 Overduin M. Kervin T.A. Tran A. Progressive membrane-binding mechanism of SARS-CoV-2 variant spike proteins iScience 25 2022 104722 44 B. Turoňová, M. Sikora, C. Schürmann, W.J.H. Hagen, S. Welsch, F.E.C. Blanc, S. von Bülow, M. Gecht, K. Bagola, C. Hörner, G. van Zandbergen, J. Landry, N.T.D. de Azevedo, S. Mosalaganti, A. Schwarz, R. Covino, M.D. Mühlebach, G. Hummer, J. Krijnse Locker, M. Beck, In situ structural analysis of SARS-CoV-2 spike reveals flexibility mediated by three hinges, (2020) eabd5223. 45 Wang B. Zhong C. Tieleman D.P. Supramolecular Organization of SARS-CoV and SARS-CoV-2 Virions Revealed by Coarse-Grained Models of Intact Virus Envelopes Journal of Chemical Information and Modeling 62 2022 176 186 34911299
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==== Front J Infect Public Health J Infect Public Health Journal of Infection and Public Health 1876-0341 1876-035X Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. S1876-0341(22)00349-5 10.1016/j.jiph.2022.12.008 Original Article Do selected lifestyle parameters affect the severity and symptoms of COVID-19 among elderly patients? The retrospective evaluation of individuals from the STOP-COVID registry of the PoLoCOV study Kapusta Joanna a1⁎ Chudzik Michał bc1⁎⁎ Kałuzińska-Kołat Żaneta cd Kołat Damian cd Burzyńska Monika e Jankowski Piotr b Babicki Mateusz f a Department of Internal Medicine and Cardiac Rehabilitation, Medical University of Lodz, 70–445 Lodz, Poland b Department of Internal Medicine and Geriatric Cardiology, Medical Centre for Postgraduate Education, 01–813 Warsaw, Poland c Boruta Medical Center, 95–100 Zgierz, Poland d Department of Experimental Surgery, Medical University of Lodz, 90–136 Lodz, Poland e Department of Epidemiology and Biostatistics, Social and Preventive Medicine of the Medical University of Lodz, 90–752 Lodz, Poland f Department of Family Medicine, Wroclaw Medical University, 51–141 Wroclaw, Poland ⁎ Corresponding author. ⁎⁎ Corresponding author at: Department of Internal Medicine and Geriatric Cardiology, Medical Centre for Postgraduate Education, 01–813 Warsaw, Poland. 1 These authors contributed equally to this work and share first authorship. 12 12 2022 1 2023 12 12 2022 16 1 143153 1 10 2022 30 11 2022 8 12 2022 © 2022 Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Background Older individuals tend to include less physical activity in their routine and are more prone to chronic diseases and severe medical complications, making them the most burdened group that is losing years of life due to pandemic-related premature mortality. This research aimed to assess the lifestyle factors that affect the COVID-19 course among patients ≥ 65 years old. Methods The study included 568 convalescents (64.1% women and 35.9% men) with persistent clinical symptoms after isolation. The mean age was 70.41 ± 4.64 years (minimum: 65 years; maximum: 89 years). The patients completed the questionnaire during their in-person visit to the medical center. The survey included questions regarding their health status when suffering from COVID-19, basic sociodemographic data, and medical history concerning chronic conditions and lifestyle. Results Physical inactivity (p < 0.001) and feeling nervous (p = 0.026) increased the risk of having a severe disease course. Coronary artery disease raised both the risk of a severe disease course (p = 0.002) and the number of present symptoms up to 4 weeks (p = 0.039). Sleep disturbances increased the number of symptoms during infection (p = 0.001). The occurrence of any symptoms was also associated with the female sex (p = 0.004). The severity of the course was associated with longer persistent symptoms (p < 0.001) and a greater number of symptoms (p = 0.004); those with a more severe course were also at a greater risk of persistent symptoms for up to 4 weeks (p = 0.006). Senior citizens in the third pandemic wave suffered with more severe disease (p = 0.004), while illness during the fourth (p = 0.001) and fifth (p < 0.001) waves was associated with a lower risk of persistent symptoms for up to 4 weeks. The disease duration was significantly shorter among vaccinated patients (p = 0.042). Conclusions Elderly COVID-19 patients should re-think their lifestyle habits to consider a physical activity level that is adjusted to their abilities, in order to decrease the risk of a severe disease course and to further limit both the number and duration of symptoms. The research was carried out in accordance with the Declaration of Helsinki, and approval from the Bioethics Committee of Lodz Regional Medical Chamber to conduct the study was obtained (approval number 0115/2021). The PoLoCOV-Study ClinicalTrials.gov identifier is NCT05018052. Keywords COVID-19 SARS-CoV-2 Lifestyle Elderly Old age Physical activity ==== Body pmc1 Introduction In 2019, in the city of Wuhan in the Chinese province of Hubei, the first cases of a new, highly infectious variant of the coronavirus—SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), causing the disease called COVID-19 (ang. Coronavirus Disease 2019), were reported [1]. This disease may be asymptomatic, cause mild cold-like symptoms, and also lead to severe pneumonia with acute respiratory distress syndrome [2]. On March 11, 2020, cases of the disease had already been reported in approximately 114 countries, including Europe [3]. In 2021, SARS-CoV-2 infection was confirmed in nearly 400 million people worldwide, of which approximately 6 million died. Infection with the pathogen in Poland was detected in approximately 5 million people, and the death rate was 2.2% [4]. On January 30, 2020, the World Health Organization (WHO) declared the coronavirus (COVID-19) epidemic as a global health threat [5]. Due to the steadily increasing number of confirmed cases of COVID-19 and to avoid overloading the healthcare system, it was necessary to reduce person-to-person contact by prohibiting movement and closing many recreational facilities. This has resulted in a shift to a more sedentary lifestyle, significantly worsening the health of citizens, especially the elderly, as they are less active than younger people and more prone to chronic disease [6]. Many risk factors for severe COVID-19 have been defined [7], one of the most important being the age of patients [8] (patients 65 years or older are particularly at risk of severe disease [9], [10]). In addition to age, other risk factors for the severe course of COVID-19 infection are comorbidities such as hypertension, chronic obstructive pulmonary disease, and diabetes [11], [12], [13], [14]. It was observed that the persistence of the pandemic, the emergence of new virus mutations and the vaccination program (introduced in Poland at the end of 2020) led to significant changes in the clinical picture of the disease [15]. It has been found that the body's ability to respond to a viral infection is extremely important, which depends on various factors, including variants of the virus, implemented vaccinations, general health of the patient, individual predispositions or behavior related to lifestyle. Recognized beneficial factors for a healthy lifestyle include eating a healthy diet [16], maintaining a healthy body weight, avoiding stress [17], getting enough sleep [18], and exercising regularly [19]. The positive effect of a healthy lifestyle is related to the improvement of the processes of the immune system, as well as slowing down the processes related to the aging of the body. Regular exercise increases the number and activity of macrophages, thus reducing the risk of community-acquired infectious diseases and related mortality [20]. In the body, the activity of lymphocytes that destroy cells replicating viruses increases, and the pool of granulocytes in blood and tissues increases. The release of muscle-derived anti-inflammatory cytokines is also observed, coupled with the inhibition of pro-inflammatory cytokines [21]. In addition, the so-called immune memory, in the event of another attack of the same antigen, enables a faster and more effective reaction of the body [21]. A healthy lifestyle is aimed at ensuring optimal health and minimizing the risk of developing diseases known as social, i.e., cardiovascular diseases (hypertension, atherosclerosis, and ischemic heart disease), type 2 diabetes, bronchial asthma or obesity. In addition, it can significantly increase the body's resistance in people of all ages, contributing to a milder course of viral infection, including SARS-CoV-2 [22]. The benefits of a healthy lifestyle are visible not only in limiting the development of diseases and improving the physical fitness of patients, but also in the mental sphere —improving the mood (reducing anxiety and depression) and general well-being of patients (reducing mental stress and improving sleep quality). This is very important due to the negative impact of social distancing caused by the COVID-19 pandemic on the mental and physical health of people around the world [6]. Accordingly, this study aimed to assess whether (and which) factors of a healthy lifestyle influence the course of COVID-19 in the elderly. This study used data from the STOP-COVID registry, which was developed to assess the course of COVID-19 infection and its early and late cardiovascular complications in hospitalized and non-hospitalized patients. In addition, the registry focuses on the assessment of the incidence of COVID-19 debts taking into account complications and predictive factors. 2 Materials and methods 2.1 Patients and eligibility criteria This retrospective study investigated the COVID-19 symptoms that were present during the isolation period and up to 4 weeks after the disease course among ≥ 65 years old patients. The mean age was 70.41 ± 4.64 years (min.: 65; max.: 89). All participants were natives of Poland. The medical assessment was based on a questionnaire that was prepared for the needs of the STOP-COVID registry of the PoLoCOV-Study (ClinicalTrials.gov identifier: NCT05018052). This research was carried out in accordance with the Declaration of Helsinki, and approval from the Bioethics Committee of Lodz Regional Medical Chamber to conduct the study was obtained (approval number 0115/2021). All subjects from individual groups were informed about the purpose of the study and gave their written consent to participate. The decisive criteria for including patients in the study were:a) SARS-CoV-2 infection (asymptomatic; mild, moderate, and severe course; and hospitalization) confirmed by a Real-Time PCR or antigen test (in accordance with guidelines of the Ministry of Health of Poland in a specific timeframe); b) Age in the range of 65–89 years; c) Consent of the respondent to participate in the study. The exclusion criteria were:a) No consent to participate in the study; b) Age< 65 years. The patients completed the questionnaire during their in-person visit to the medical center. The survey included questions regarding their health status when suffering from COVID-19; basic sociodemographic data, such as age, gender, body mass and height (used to calculate body mass index—BMI); and medical history concerning chronic conditions. Additionally, the collected information included the course of COVID-19, including the date of onset of symptoms, and the duration or quantity of symptoms. The isolation period of patients was taken into account, enabling to assign them to a specific wave of the pandemic, in accordance with the infection pattern in Poland (collectively based on [15], [23], [24]):1. First (I) wave—from March 1, 2020 to August 30, 2020 (due to the small number of patients in the first wave, they were not included in the current analysis); 2. Second (II) wave—from September 1, 2020 to January 30, 2021; 3. Third (III) wave—from February 1, 2021 to August 30, 2021; 4. Fourth (IV) wave—from September 1, 2021 to December 31, 2021; 5. Fifth (V) wave—from January 1, 2022 to the end of the observation period (May 2022). The distribution of five COVID-19 waves in the Polish population is shown in Fig. 1.Fig. 1 The prevalence of five waves of COVID-19 in Polish population [25]. Fig. 1 The next part of the survey comprised single- and multiple-choice questions regarding the most common clinical symptoms of COVID-19, such as fever, subfebrile states, chills, cough, shortness of breath, rhinitis, smell/taste/hearing disorders, headaches, vomits, diarrhea, myalgia, arthralgia, and chest pain. Patients reported symptoms that were present during isolation due to SARS-CoV-2 infection or up to 4 weeks after COVID-19. The duration of the symptoms was determined from the first day when it occurred till the last day of symptoms. The sum of the symptoms was defined as the total number of symptoms that occurred during the course of the disease. Vaccination status was also taken into account in this study. During the program, the collection of data on vaccination status was started, which was introduced in Poland in December 2021. Those who completed the pre-isolation treatment regimen (i.e., two doses of the Pfizer / Moderna / AstraZeneca vaccine or one dose of Johnson & Johnson) were considered to have completed a full vaccination course. The patient also completed the section of the survey regarding lifestyle risk factors: smoking, stress, sleep disorders and lack of regular physical activity. These parameters were defined as follows:a) Smoking—a smoker was considered someone who, in the past 12 months, has used any tobacco products; b) Stress/feeling nervous—subjective assessment of being anxious, on edge, unable to stop or control worrying for more than half a day within the 4 weeks prior to COVID-19 infection; c) Sleep disorders—sleep disorder was diagnosed when the patient subjectively assessed at least one of the following three parameters persisting for at least half of the 4 weeks prior to COVID-19 infection: difficulties in falling asleep or staying asleep, or somnolence during the next day; d) Lack of regular physical activity—less than 150 min of any physical activity per week adjusted to abilities in the last 3 months before COVID-19 (in accordance with European Society of Cardiology guidelines [26]). Patients subjectively assessed the severity of COVID-19 symptoms during the course of the disease (on a 0–3 scale where: 0—asymptomatic; 1—mild; 2—moderate; 3—severe) and were then categorized as asymptomatic/mildly symptomatic patients or those having moderate/severe symptoms. Asymptomatic patients were those with no symptoms, despite having positive a Real-Time PCR test; their subjective evaluation on a 0–3 scale was “0”. The mild group included those who stayed at home during infection, who subjectively evaluated disease severity as a light course ("1" on a 0–3 scale) and whose duration of symptoms was up to 7 days. Patients were classified as having a moderate course of disease if their subjective evaluation was “2” or “3” on a 0–3 scale or if they had fever> 38 °C or dyspnea or symptoms of any severity lasting 7–14 days. A severe course of disease included those who were hospitalized with a diagnosis of one of the following: pneumonia, respiratory failure, intensive care unit, assisted breathing or thromboembolic complications during hospitalization. Alternatively, it also comprised a home course with symptoms lasting> 14 days, subjective evaluation by the patient as severe ("3" on a scale of 0–3), with temperature> 38 °C, dyspnea or saturation below 94 lasting more than 3 days. 2.2 Statistical analysis Statistical analysis was performed using the PQStat software v1.8.4 and PAST v4.09. The analyzed variables were quantitative, variable and dichotomous. Quantitative variables were characterized by providing basic descriptive statistics, such as mean values, medians, first and third quartiles, and standard deviation (SD). The normality of the distribution was verified using the Shapiro–Wilk test. Due to the fact that the normality criterion was not met, the non-parametric Mann–Whitney U test was used for the comparison of the two variables. In the case of dichotomous variables, the relationship between them was verified with the Chi2 independence test. If the Cochran assumption was not met in the Chi2 test, the Yates correction was used. To determine the effect of factors on the severity of COVID-19, a complex logistic regression model was built (both full and reduced with the backward stepwise method), where the dependent variable was the assessment of disease severity, and the independent variables were sociodemographic variables, i.e., chronic diseases, vaccination status, period of illness (pandemic wave), smoking, stress, sleep disorders and lack of physical activity. Linear regression analysis (both full model and reduced model with backward stepwise method) was used to assess the impact of the above variables on the duration of the disease and the number of symptoms. In the case of continuous variables, the relationships between them were determined using the Spearman correlation. Risk factors for the occurrence of symptoms up to 4 weeks after the onset of COVID-19 were assessed through logistic regression analysis using the backward stepwise method, where the dependent variable was the presence of at least one symptom and the independent variables were chronic conditions, sociodemographic variables, vaccination status, pandemic wave and lifestyle. The effect of the above variables on the number of symptoms present up to 4 weeks was assessed through linear regression analysis using the backward stepwise method. In each case, the results with p < 0.05 were considered statistically significant. 3 Results The study included 568 senior citizens; the mean age was 70.41 ± 4.64 years (minimum: 65; maximum: 89); however, no impact of age on the severity of COVID-19 was noted (p = 0.431). The vast majority were women (64.1%). Furthermore, 502 patients (88.4%) had at least one chronic disease, the most common of which was arterial hypertension (66.7%) and diabetes (22.5%). Of all subjects, 145 senior citizens had a verified vaccination status, of which 100 (68.9%) were fully vaccinated. The largest group was the one with senior citizens from the third wave of the pandemic in Poland (37.4%). The median duration of the disease for the entire study group was 10 days (min.: 7; max.: 14) and the number of symptoms was 7 (min.: 5; max.: 10). In the assessment of the respondents’ lifestyle, as many as 68.1% were not physically active in the last 3 months before the disease, and 36.4% suffered from sleep disorders. Most of the patients were non-smokers (93.1%). There was no effect of vaccinations on the severity of COVID-19 (p = 0.223) and the number of symptoms (p = 0.972), while the median duration of the disease was significantly lower (p = 0.042). Furthermore, a much more severe course of COVID-19 was observed (72.1% vs. 44.2%) among patients who were not considered to be physically active (p < 0.001). Moreover, patients who were exposed to increased stress within the 4 weeks prior to infection had a greater number of clinical symptoms (p < 0.001) and a longer duration of the disease (p = 0.010). Table 1 summarized the study group and its lifestyle.Table 1 Characteristics of the study group: lifestyle, taking into account the severity of COVID-19, its duration and the number of present clinical symptoms. Table 1Variable COVID-19 severity The sum of the symptoms during COVID-19 The duration of the symptoms (days) during COVID-19 The entire group (N = 568) Asymptomatic and mild (N = 209) Moderate and severe (N = 359) p Median [Q1; Q3] p Median [Q1; Q3] p Age Mean± SD 70.41 ± 4.64 70.46 ± 4.79 70.38 ± 4.57 0.431 – – – – Median [Q1; Q3] 69 [67; 73] 69 [67; 73] 69 [67; 73] – – – – BMI Mean± SD 28.77 ± 5.22 29.10 ± 5.74 28.58 ± 5.23 0.775 – – – – Median [Q1; Q3] 28.1 [25.6; 31.3] 28.4 [25.8; 31.6] 28.6 [25.5; 31.2] – – – – Sex Female 364 (64.1%) 127 (34.9%) 237 (65.1%) 0.243 8 [5; 10] 0.001 10 [7; 14] 0.928 Male 204 (35.9%) 82 (40.2% 122 (59.8%) 7 [4; 9] 10 [6; 14] Diabetes Mellitus Yes 128 (22.5%) 41 (32.0%) 87 (68.0%) 0.204 8 [5.5; 10] 0.171 10 [7; 14] 0.315 No 440 (77.5%) 168 (38.2%) 272 (61.8%) 7 [5; 10] 10 [7; 14] Coronary Artery Disease Yes 101 (17.8%) 2322.8%) 78 (77.2%) 0.001 7 [5; 10] 0.016 10 [7; 14] 0.131 No 467 (82.2%) 186 (39.8%) 281 (60.2%) 7 [5; 10] 10 [7; 14] Heart Failure Yes 23 (4.1%) 6 (26.1%) 17 (73.9%) 0.281 8 [5; 12] 0.234 10 [7; 14]] 0.857 No 544 (95.9%) 202 (37.1%) 342 (62.9%) 7 [5; 10] 10 [8; 14] Hypertension Yes 379 (66.7%) 137 (36.2%) 242 (63.8%) 0.650 8 [5; 10] 0.015 10 [7; 14] 0.735 No 189 (33.3%) 72 (38.1%) 117 (61.9%) 7 [4; 9] 10 [7; 14] COPD Yes 36 (6.3%) 11 (30.6%) 25 (69.4%) 0.532 10.5 [7; 12] 0.001 14 [8; 14] 0.150 No 532 (93.7%) 198 (37.2%) 334 (62.8%) 7 [5; 10] 10 [7; 14] Asthma Yes 67 (11.8%) 20 (29.9%) 47 (70.1%) 0.209 8 [6; 11] 0.003 9 [7; 14] 0.883 No 501 (88.2%) 189 (37.7%) 312 (62.3%) 7 [5; 10] 10 [7; 14] Comorbidities Yes 502 (88.4%) 181 (36.1%) 321 (63.9%) 0.382 8 [5; 10] 0.012 10 [7; 14] 0.651 No 66 (11.6%) 28 (42.4%) 38 (57.6%) 6 [4; 9] 10 [6; 14] Any sleep disorders Yes 207 (36.4%) 79 (38.2%) 128 (61.8%) 0.673 8 [6; 11] < 0.001 10 [7; 14] 0.208 No 361 (67.3%) 130 (36.0%) 231 (64.0%) 7 [4; 10] 10 [6; 14] Smoking Yes 39 (6.9%) 21 (53.9%) 18 (46.2%) 0.034 6 [4; 10] 0.449 7 [5; 10] 0.013 No 529 (93.1%) 188 (35.5%) 341 (64.5%) 8 [5; 10] 10 [7; 14] Stress in the last 4 weeks before COVID-19 Yes 83 (14.6%) 23 (27.7%) 60 (72.3%) 0.082 9 [5; 11] 0.001 10 [7; 14] 0.010 No 485 (85.4%) 186 (38.4%) 299 (61.7%) 7 [5; 10] 10 [7; 14] Regular activity 3 months before COVID-19 Yes 181 (31.9%) 101 (55.8%) 80 (44.2%) < 0.001 7 [4; 9] 0.128 8 [6; 14] 0.022 No 387 (68.1%) 108 (27.9%) 279 (72.1%) 8 [5; 10] 10 [7; 14] COVID-19 Vaccination (n = 145) Yes 100 (68.9%) 44 (44.0%) 56 (56.0%) 0.223 8 [5; 10] 0.972 8 [7; 14] 0.042 No 45 (31.1%) 15 (33.3%) 30 (66.7%) 8 [6; 0] 10 [7; 14] Pandemic Wave II 187 (32.9%) 80 (42.8%) 107 (57.2%) 0.017 7 [4; 10] 0.497 10 [7; 14] 0.005 III 212 (37.4%) 61 (28.8%) 151 (71.2%) 7 [5; 10] 10 [8; 14] IV 104 (18.3%) 40 (38.5%) 64 (61.5%) 8 [6; 9] 10 [7; 14] V 65 (11.4%) 28 (43.1%) 37 (56.9%) 7 [5; 9] 7 [5; 10] COVID-19 Severity Asymptomatic/ mild – – – – 6 [3; 8] < 0.001 7 [4; 10] < 0.001 Moderate / severe – – – – 8 [6; 10] 12 [9; 14] SD – Standard deviation; Q1; Q3 – first and third quartile; COPD – chronic obstructive pulmonary disease; BMI – Body Mass Index. Statistically significant values are in bold with the significance level set at p < 0.05. 3.1 Risk factors of the severe COVID-19 course, the disease duration and the quantity of present clinical symptoms Among the potential risk factors in both the full and the reduced models with a backward stepwise method, it was shown that a lack of physical activity increased the risk of severe COVID-19 in senior citizens by more than 3.4 times and the severity of stress by 1.85-fold. In addition, a history of coronary artery disease also increased the risk of severe COVID-19 in patients ≥ 65 years old by 2.3-fold. The detailed results of the full and the reduced models are shown in Table 2.Table 2 Full and reduced backward stepwise logistic regression analysis model assessing the impact of risk factors on the severity of COVID-19. Table 2Variable OR -95% CI + 95% CI p Full logistic regression analysis model Age 0.991 0.952 1.033 0.699 Any sleep disorders 0.896 0.595 1.348 0.599 Smoking 0.485 0.233 1.011 0.054 Stress in the last 4 weeks before COVID-19 1.851 1.055 3.248 0.032 No regular activity 3 months before COVID-19 3.571 2.410 5.291 < 0.001 Female 1.103 0.747 1.629 0.619 BMI 0.966 0.931 1.022 0.070 Diabetes Mellitus 1.223 0.759 1.987 0.403 Coronary Artery Disease 2.151 1.247 3.710 0.005 Heart Failure 0.771 0.278 2.130 0.615 Hypertension 0.920 0.576 1.471 0.728 COPD 1.128 0.489 2.598 0.777 Asthma 1.403 0.754 2.612 0.284 COVID-19 Vaccination 0.636 0.305 1.327 0.228 III pandemic wave 1.920 1.223 3.014 0.004 IV pandemic wave 1.395 0.851 2.377 0.221 V pandemic wave 1.084 0.569 2.065 0.805 Reduced backward stepwise logistic regression analysis model No regular activity 3 months before COVID 3.441 2.349 5.041 < 0.001 Coronary Artery Disease 2.283 1.348 3.867 0.002 Stress in the last 4 weeks before COVID-19 1.858 1.075 3.212 0.026 III pandemic wave 1.849 1.193 3.865 0.002 OR – Odds ratio; 95% CI – 95% Confidence interval; COPD – chronic obstructive pulmonary disease; BMI – Body Mass Index. Statistically significant values are in bold with the significance level set at p < 0.05. 3.2 Factors affecting the duration and number of symptoms during COVID-19 In the constructed linear regression models with applied backward stepwise analysis, it was demonstrated that both the severe course of COVID-19 (value 2.712; p = 0.004) and COPD (chronic obstructive pulmonary disease) (value 3.722; p = 0.004) increased the number of clinical symptoms. In addition, sleep disturbances were also associated with a greater number of symptoms during SARS-CoV-2 infection (value 1.532; p = 0.001). For disease duration, the severity of COVID-19 was associated with longer-lasting symptoms (value 6.368; p < 0.001). The Spearman correlation analysis showed no relationship between BMI and age in relation to the number of symptoms (rBMI = 0.015; p = 0.807; rage = 0.031; p = 0.582) and disease duration (rBMI = −0.102; p = 0.100; rage = 0.043; p = 0.492). A detailed comparison of the full and reduced models is presented in Table 3.Table 3 Full and reduced backward stepwise linear regression analysis model assessing the effect of COVID-19 severity, sociodemographic variables, vaccination status, pandemic wave, chronic conditions and lifestyle on disease duration and the number of clinical symptoms. Table 3Variable The sum of the symptoms during COVID-19 The duration of the symptoms (days) during COVID-19 Value SD t p Value SD t p Full linear regression analysis model COVID-19 Severity 2.647 0.508 5.209 < 0.001 6.429 1.105 5.815 < 0.001 Age -0.093 0.057 -1.612 0.109 0.042 0.124 0.342 0.732 Any sleep disorders 1.134 0.489 2.319 0.022 2.310 1.065 2.169 0.032 Smoking -0.756 0.986 -0.767 0.444 -1.413 2.147 -0.658 0.511 Stress in the last 4 weeks before COVID-19 0.152 0.640 0.238 0.812 1.133 1.137 0.998 0.321 No regular activity 3 months before COVID 0.807 0.522 1.546 0.124 -1.823 1.163 -1.567 0.112 Sex, female 0.807 0.514 1.569 0.119 -1.701 1.120 -1.519 0.131 BMI 0.075 0.052 1.501 0.135 -0.004 0.124 -0.0.044 0.965 Diabetes Mellitus 1.009 0.652 1.547 0.124 0.098 1.419 0.069 0.944 Coronary Artery Disease 0.204 0.6851 0.297 0.766 0.234 1.491 0.157 0.875 Heart Failure -1.742 2.057 -0.847 0.398 -4.707 4.478 -1.051 0.295 Hypertension -0.254 0.557 -0.456 0.649 -1.098 1.213 -0.904 0.367 COPD 4.363 1.379 3.161 0.001 3.382 3.003 1.125 0.262 Asthma 0.431 0.697 0.617 0.537 -0.043 1.518 -0.029 0.997 COVID-19 vaccination 0.058 0.534 0.109 0.912 -1.823 1.162 -1.567 0.112 Pandemic wave -0.505 0.444 -1.136 0.257 -2.537 0.968 -2.620 0.009 Reduced backward stepwise linear regression analysis model COVID-19 Severity 2.712 0.474 2.919 0.004 6.368 1.005 6.334 < 0.001 Pandemic wave – – – – -2.366 0.914 -2.586 0.011 Any sleep disorders 1.532 0.467 3.318 0.001 – – – – COPD 3.722 1.275 2.919 0.004 – – – – SD – Standard deviation; BMI – Body Mass Index; COPD – chronic obstructive pulmonary disease. Statistically significant values are in bold with the significance level set at p < 0.05. 3.3 Symptoms up to 4 weeks after COVID-19 In assessing the presence of at least one symptom up to 4 weeks after COVID-19 onset, 513 patients (90.3%) were included, of which 308 (60.0%) reported such symptoms. The median of symptoms up to 4 weeks among the analyzed patients is 7 (min.: 5; max.: 10). The logistic regression analysis showed that the severity of the disease (value 1.733; p = 0.002), sleep disturbance (value 1.638; p = 0.004), COPD (value 4.571; p = 0.017) and coronary artery disease (value 1.836; p = 0.039) had an effect on the number of symptoms present up to 4 weeks after COVID-19. In contrast, the occurrence of any symptoms in the group of patients of ≥ 65 years old was associated with the severity of the disease (Odds Ratio (OR) = 1.816; p = 0.006) and the female sex (OR 1.747; p = 0.004). Patients infected in the fourth and fifth waves of the pandemic showed a much lower risk of persistent symptoms for up to 4 weeks than senior citizens at the beginning of the pandemic. Pre-disease lifestyle has not been shown to significantly affect the risk of symptom persistence. The comparison of the exact results of the linear and logistic regression model with regard to the number and occurrence of symptoms is presented in Table 4.Table 4 Influence of sociodemographic variables, lifestyle, vaccination status, pandemic wave and chronic diseases on the persistence of symptoms up to 4 weeks after the onset of COVID-19 and the number of symptoms. Table 4Variable At least one symptom 4 weeks after COVID-19# The number of symptoms 4 weeks after COVID-19* OR -95% CI + 95% CI p Value SD t p Full model COVID-19 severity 1.993 1.323 3.003 < 0.001 1.490 0.641 2.236 0.022 Age 0.967 0.929 1.001 0.643 -0.129 0.065 -1.999 0.049 Any sleep disorders 1.072 0.702 1.636 0.746 0.745 0.641 1.116 0.249 Smoking 1.809 0.803 4.075 0.153 -0.363 1.032 -0.352 0.726 Stress in the last 4 weeks before COVID-19 0.879 0.504 1.533 0.651 0.334 0.752 0.444 0.658 No regular activity 3 months before COVID 0.953 0.624 1.454 0.823 0.707 0.631 1.121 0.265 Sex, female 1.762 1.178 2.634 0.005 0.979 0.611 1.601 0.114 BMI 0.991 0.955 1.028 0.643 0.076 0.058 1.205 0.232 Diabetes Mellitus 0.974 0.601 1.573 0.914 0.897 0.827 1.085 0.282 Coronary Artery Disease 1.748 1.022 2.988 0.041 2.038 0.958 2.213 0.037 Heart Failure 0.922 0.299 2.848 0.889 -0.087 2.756 -0.032 0.974 Hypertension 0.897 0.585 1.368 0.614 0.194 0.708 0.273 0.785 COPD 0.856 0.390 1.882 0.700 5.443 2.043 2.665 0.009 Asthma 1.001 0.540 1.856 0.995 0.132 00.843 0.156 0.876 COVID-19 vaccination 1.398 0.636 3.071 0.403 0.001 0.609 0.003 0.998 III pandemic wave 1.048 0.662 0.715 0.841 – – – – IV pandemic wave 0.416 0.242 0.715 0.001 – – – – V pandemic wave 0.248 0.120 0.510 < 0.001 – – – – Reduced backward stepwise model COVID-19 severity 1.816 1.118 2.783 0.006 1.733 0.563 3.075 0.002 Sex, female 1.747 1.189 2.567 0.004 – – – – IV pandemic wave 0.421 0.249 0.711 0.001 – – – – V pandemic wave 0.265 0.133 0.527 < 0.001 – – – – Coronary Artery Disease – – – – 1.836 0.880 2.087 0.039 COPD – – – – 4.571 1.884 2.425 0.017 Any sleep disorders – – – – 1.638 0.562 2.912 0.004 # – Linear regression analysis; * – Logistic regression analysis; OR – Odds ratio; COPD – chronic obstructive pulmonary disease; BMI – Body Mass Index. Statistically significant values are in bold with the significance level set at p < 0.05. 4 Discussion The COVID-19 pandemic caused lifestyle changes on a global scale [27]. It is forecasted that living in such an unhealthy environment will increase the presence of unhealthy populations, which leads to unhealthy offspring [28]. Elderly people tend to be less active compared to younger people and are more prone to chronic diseases [29]; they are now the most burdened individuals that are losing years of life due to pandemic-related premature mortality [30]. Using patients’ data from the STOP-COVID registry of the PoLoCOV-Study, the current research focused on the assessment of the lifestyle factors that can affect the course of COVID-19 in patients of ≥ 65 years old. This group is of particular importance since older adults are the most susceptible to severe medical complications and death due to COVID-19 [31]. In brief, results present that disease severity, physical inactivity, stress, coronary artery disease, COPD, sleeping disturbance, female sex, pandemic wave and vaccination status were of significance in terms of the COVID-19 course. The pre-infection lifestyle analysis showed that both physical inactivity and feeling nervous significantly contributed to the occurrence of severe disease, increasing the risk by 3.5 and 1.85 times, respectively. There are many reports on physical inactivity in the literature; among others, Yuan et al. observed pre-existent physical inactivity to be associated with an increased risk of severe COVID-19 [32]. Similarly, another source indicates that a physically active lifestyle might decrease the rate of acute respiratory infection incidence and the severity of COVID-19 symptoms [33]. Hamer et al. characterized the risk profile of patients that were hospitalized during study follow-up; the lack of physical activity was one of the variables that contribute to the risk profile [34]. The mitigation of infection progress could be achieved by both home- and outdoor-based exercise, regardless of age and chronic conditions [35]. Sallis et al. recommended promoting physical activity by public health agencies and incorporating it into routine medical care, since constantly inactive COVID-19 patients had a greater risk of hospitalization and admission to the intensive care unit or even death, compared to patients who were consistently meeting physical activity guidelines. The same applies to the comparison of constantly inactive patients to individuals who were somewhat physically active, in favor of the latter group [36]. It has been summarized that various mechanisms involving redox-sensitive transcription factors, cytokines, and molecules associated with cellular stress or fatty acid oxidation are responsible for the beneficial effects of exercise [37]. Similarly, inflammatory markers were reported to correlate with symptoms related to cognitive deficits [38]. In the Schou et al. study, disease severity and duration of symptoms were identified as risk factors of psychiatric sequelae, while neuroimmune alterations were supported by the fact that: (1) Angiotensin-converting enzyme 2 (ACE2) is expressed on neurons and glial cells; (2) SARS-CoV-2 can be detected in the brain; and (3) astrocytes and microglia cells are activated during COVID-19 [38]. Recently, a longitudinal prospective observational cohort study by Ayling et al. revealed that more psychological distress during the early pandemic phase was significantly associated with further reports of SARS-CoV-2 infection, as well as with more severe disease and a greater number of symptoms [39]. Sjöberg et al. concluded that for future pandemics or waves of COVID-19, the appropriate strategies are required to counteract physical inactivity, especially among older individuals [40]. Regarding COVID-related stress, Hadjistavropoulos and Asmundson conceptualized several ways in which the pandemic may uniquely impact stress levels among the elderly [41]. In the review of Grolli et al., the cause–effect scheme was proposed, in which the stress triggers the hypothalamus–pituitary–adrenal axis and the inflammatory processes that are related to immunosenescence in advanced age. This scenario can culminate in a higher degree of chronic inflammation, predisposing the elderly to psychiatric sequelae, e.g., anxiety or major depressive disorder [42]. Of the chronic conditions, a history of coronary artery disease not only 2.2-fold increased the risk of a severe disease course but also increased the number of symptoms up to 4 weeks after COVID-19. Other studies have demonstrated an increased risk of complications and mortality in people with COVID-19 and pre-existing cardiovascular disease (CVD), as well as in people with one or more comorbidities, such as hypertension, diabetes, hypercholesterolemia or obesity [43], [44], [45]. A meta-analysis performed on the Chinese population has shown an increased mortality in people with cardiovascular diseases infected with COVID-19; the mortality rate was approximately 11% [46]. Similar conclusions were drawn from the review by Xintao Li et al. [47]. Several mechanisms of action have been proposed; first, patients with cardiac burden are more prone to the deterioration of hemodynamic status after infection with the SARS-CoV-2 virus [48]. ACE-2 plays a key role in the development of cardiovascular complications [49], and the virus enters the host cells through this receptor, causing damage to the lung tissue. It also binds to vascular endothelial cells of other organs, such as the kidneys and the heart [50]. Severe pneumonia puts a significant strain on the ventricles, which may aggravate pre-existing left ventricular dysfunction and even cause cardiogenic shock [51]. Another mechanism may be an infection-induced inflammatory reaction that may transform chronic coronary artery disease into acute coronary syndrome [52], [53]. It has been observed that the occurrence of cardiovascular events in people with COVID-19 is associated with vascular inflammation and remodeling resulting from endothelial dysfunction [50]. Systemic inflammation along with local inflammatory infiltration can lead to the hypercoagulability and rupture of atherosclerotic plaque [54]. In addition, prioritizing COVID-19 treatment while neglecting other comorbidities may predispose patients with cardiovascular disease to adverse clinical outcomes. Recently, Karadavut and Altintop’s study on elderly individuals demonstrated that long-term cardiovascular complications were more frequent in patients with severe COVID-19 [55]. Similarly, Napoli et al. highlighted that cardiometabolic comorbidities and aging are associated with a higher frequency and severity of disease in the elderly [56]. Furthermore, the current study found that COPD increases the number of clinical symptoms during SARS-CoV-2 infection, as well as up to 4 weeks after COVID-19. Gerayeli et al. performed a systematic review and meta-analysis, which indicated that the diagnosis of COPD is related to poorer clinical outcomes in COVID-19 patients; COPD patients were considered a high-risk group that should be targeted for preventative measures and vaccination [57]. COPD was also found to be a risk factor in the study of Higham et al. [58], and another study reported an increased risk of over 5-fold for severe COVID-19 due to COPD [59]. The mechanisms that could explain COPD-related poorer COVID-19 outcomes include ACE2 upregulation in the airways and lungs of individuals with COPD, which facilitates progression [60], [61] or impaired innate immune response among COPD patients [62]. The latter may be due to altered interferon responses that have been associated with an increased risk of severe COVID-19 [63]. The presence of other risk factors that are common in people with COPD (e.g., older age, CVD, hypertension, and diabetes) might also be associated with more severe COVID-19 [64]. In COPD patients with SARS-CoV-2 infection, respiratory failure-related symptoms increased, and the clinical condition worsened, affecting the complications and mortality [65]. Moreover, we found sleep disturbances to be associated with a greater number of symptoms during viral infection. This complements the findings of Kim et al., where a lack of sleep at night and severe sleep problems were proposed as COVID-19 risk factors, based on data from six countries [66]. Another report indicates that in a group of patients exhibiting poor sleep quality, the duration of hospitalization and the depression rate were higher [67]. Pataka et al. observed that compared with dyspnea or depression, insomnia symptoms were more frequently reported in acute COVID-19 patients [68]. Recently, Bhat and Chokroverty underlined that poor sleep is indeed associated with a greater susceptibility to COVID-19 infection and a worse disease course, but the exact cause-and-effect relationship remains undefined [69]. In another study, a group of patients was divided into good and poor sleepers, which allowed the identification of the lower absolute lymphocyte count and increased neutrophil-to-lymphocyte ratio in the latter subgroup [70]. Another scientific group mentions that prolonged exposure to proinflammatory mediators and innate immune molecules may modulate neuroinflammation and causes clinical symptoms of insomnia, arousal, and diminished sleep efficiency [71]. It is worth mentioning that the relation between sleep disturbances and symptom quantity can be a double-edged sword, as COVID-19 patients report sleep problems due to illness-related symptoms that make rest difficult. Pataka et al. mentioned that elderly patients and those with comorbid chronic diseases were more likely to report sleep problems [68]. The occurrence of any symptoms was also associated with the female sex. A study by Pelà et al. indicated that females were more symptomatic than males not only in the acute phase but also at follow-up. Gender was also found to be a significant predictor of persistent symptoms, such as dyspnea, fatigue, chest pain, and palpitations among females [72]. In contrast, other researchers concluded that the female sex is not a risk factor associated with COVID-19 symptoms but is associated with long-term COVID symptoms [73]. In the authors’ opinion, a systematic review will be of relevance in the case of literature contradictions; one of such data collections was prepared by Sylvester et al. [74]. They found that COVID-19 sequelae related to psychiatric, ear/nose/throat (ENT), musculoskeletal, and respiratory complications were more frequent among females, whereas renal sequelae were prevalent among males. Moreover, the likelihood of having long-COVID was also greater among females, with ENT, gastrointestinal, psychiatric, neurological, and dermatological disorders being more prevalent among females, while those related to endocrine and renal complications were more frequent among males. It appears that any complications except for endocrine or renal complications are related to the female sex, which verifies our observations. It has been proposed that such differences between females and males could be due to immune system function [75], [76] or hormone regulation [77]. Although there are reports that are in line with our findings (e.g., Jacobs noticed that not only older participants aged 65–75 years, but also women, experienced more persistent symptoms for up to 35 days after the acute phase [78]), Doerre and Doblhammer present an interesting discussion with regard to gender-specific diagnoses taking into account many additional aspects [79]. Nevertheless, it is imperative to not disregard all significant symptoms among women and profoundly evaluate the findings on a larger scale. The severity of the course was significantly associated with longer persistent symptoms and a greater number of symptoms; in addition, those with a more severe course were at greater risk of persistent symptoms for up to 4 weeks after the acute phase of the disease. The meta-analysis of He et al. revealed that fever, cough, dyspnea, expectoration, hemoptysis, abdominal pain, diarrhea, anorexia, and fatigue occurred more frequently in patients with severe COVID-19 than in mild cases, while chest pain, pharyngalgia, nausea, vomiting, headache and myalgia did not show such tendency [80]. It appears that symptoms differentiate the groups. Furthermore, Tenforde et al. found that a prolonged symptom duration and disability are more common in hospitalized COVID-19 patients [81], while the study of Lane et al. demonstrated that the only factors associated with a prolonged duration of symptoms are the presence of lower respiratory symptoms or neurologic symptoms at disease onset [82]. Our findings verify the former study and are of particular importance for the elderly as they tend to be susceptible to a more severe course of COVID‐19 [83]. Senior citizens with illness during wave III of the pandemic were most likely to undergo severe disease, while illness during wave IV and wave V were associated with a lower risk of persistent symptoms up to 4 weeks after isolation. It is challenging to find appropriate data for comparison with our findings since much research related to COVID-19 do not distinguish pandemic waves (which was the advantage of our previous research [15]), and many studies outside Poland assume different period for each pandemic wave. However, in Jassat et al. study the waves’ timeframe was similar to our research, i.e., from 0 to 3 months of difference [84]. Compared with each preceding wave, fewer patients were admitted to the hospital during the fourth wave, with less clinically severe illness and a lower case-fatality ratio. Another report by Matsunaga et al., despite having greater disparities regarding timeframe, indicated that each wave had different characteristics. Namely, the first wave was characterized by a more severe disease and the worst case-fatality rate, the second wave included young patients and mild disease, while the third wave had older patients with comorbidities. Clinically significant differences concerned age, the severity of illness at admission, and hypertension [85]. Definitely, our observations are in line with the connection of older patients with a third wave, as well as alleviating the clinical manifestation from the fourth wave onwards. In addition, there was no effect of vaccination on the severity of disease course or persistence of symptoms up to 4 weeks after COVID-19. Interestingly, the duration of disease was significantly shorter, similar to research by Thompson et al., where partially or fully vaccinated patients spent 2.3 fewer days sick in bed compared to unvaccinated participants [86]. Likewise, Ronchini et al. recently concluded that the probability of infection after vaccination is not only lower compared to natural infection, but is also associated with a shorter duration of infection (than that of first infection and reinfection) and is inversely correlated with circulating immunoglobulins G [87]. Lytras et al. evaluated vaccine effectiveness against severe COVID-19 and found that efficacy gently declined after two doses, but a third restored the protection [88]. In the case of our research, the observation of vaccines shortening disease duration should now be only considered as a hint, as the vaccination status was verified only in a quarter of all patients included in this study. The slightly modest percentage is due to the inclusion of second-wave elderly patients that were not able to be vaccinated as no programme was available in that period for this group in Poland. Nevertheless, it seems reasonable to direct the profound investigation to a larger group of patients in the future. The findings of this study are subject to at least three other limitations. First, there is a lack of data regarding the use of pharmacotherapy in the course of the disease. While specific guidelines for treating COVID-19 were provided during the pandemic, physicians often executed their own regimens, including antibiotic therapy, antiviral medications, and amantadine or ivermectin. However, based on worldwide reports [89], [90], [91], [92], these medications do not affect the disease course or severity; however, it cannot be ruled out that their heterogeneous usage did not influence the disease course for the individual patient. Another drawback is the retrospective nature of data collection, which entails a risk of memory error, influencing the reliability of estimated symptoms frequency. In addition, recording data on all ailments in a given period may result in underestimating or overestimating the frequency of individual symptoms. Moreover, the group of patients analyzed in our study are those who self‐referred to the health centre due to persistent symptoms after recovery from COVID‐19. Obviously, these are not all individuals who are COVID-19 survivors, and thus, the findings should not be extrapolated to the entire population. In conclusion, elderly COVID-19 patients should re-think their lifestyle habits to consider a physical activity that is adjusted to their abilities, in order to decrease the risk of severe disease course and to further limit both the number and duration of symptoms. This will facilitate repose and further reduce stress, improving well-being. Exercise is especially an ally for risk groups having comorbidities (e.g., coronary artery disease or COPD) to combat the severity of disease and/or number of clinical symptoms, the latter especially among females. The vaccines require further investigation but are promising with regard to decreases in disease duration among Polish elderly patients. From the fourth wave onwards, it is encouraging to observe a reduction in the risk of symptoms up to 4 weeks after isolation. Conflicts of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Acknowledgments NA. Funding The authors received no financial support for the research, authorship, and/or publication of this article. Author contributions JK – interpretation of obtained results, preparation of the text of the study, review and editing. MC – development of assumptions and research methods, collecting source materials and carrying out research, preparation of the text of the study; ŻKK – preparation of the text of the study, data collection, review and editing; DK – preparation of the text of the study, data collection, review and editing; MBu – statistical analysis of research results, interpretation of the obtained results; PJ – interpretation of obtained results, review and editing; MBa – statistical analysis of research results, interpretation of the obtained results, preparation of the text of the study, review and editing. ==== Refs References 1 Holshue M.L. DeBolt C. Lindquist S. Lofy K.H. Wiesman J. Bruce H. First Case of 2019 Novel Coronavirus in the United States N Engl J Med 382 10 2020 929 936 10.1056/NEJMoa2001191 32004427 2 Gibson P.G. Qin L. Puah S.H. COVID-19 acute respiratory distress syndrome (ARDS): clinical features and differences from typical pre-COVID-19 ARDS e1 Med J Aust 213 2 2020 54 56 10.5694/mja2.50674 32572965 3 World Health Organization. WHO Director-General's opening remarks at the media briefing on COVID-19, https://www.who.int/emergencies/diseases/novel-coronavi-rus-2019/events-as-theyhappen; 2020 [accessed 18 February 2022]. 4 Our World in Data. Daily new confirmed COVID-19 deaths per million people, https://ourworldindata.org/explorers/coronavirus-data-explorer; 2020 [accessed 20 February 2022]. 5 Bentlage E. Ammar A. How D. Ahmed M. Trabelsi K. Chtourou H. Practical Recommendations for Maintaining Active Lifestyle during the COVID-19 Pandemic: A Systematic Literature Review Int J Environ Res Public Health 17 17 2020 10.3390/ijerph17176265 6 Roschel H. Artioli G.G. Gualano B. Risk of Increased Physical Inactivity During COVID-19 Outbreak in Older People: A Call for Actions J Am Geriatr Soc 68 6 2020 1126 1128 10.1111/jgs.16550 32392620 7 Schetelig J. Baldauf H. Wendler S. Heidenreich F. Real R. Kolditz M. Risk Factors for a Severe Course of COVID-19 in Persons Aged 18 to 61 Dtsch Arztebl Int 118 16 2021 288 289 10.3238/arztebl.m2021.0200 34180791 8 Wolff D. Nee S. Hickey N.S. Marschollek M. Risk factors for Covid-19 severity and fatality: a structured literature review Infection 49 1 2021 15 28 10.1007/s15010-020-01509-1 32860214 9 Jin J.M. Bai P. He W. Wu F. Liu X.F. Han D.M. Gender Differences in Patients With COVID-19: Focus on Severity and Mortality Front Public Health 8 2020 152 10.3389/fpubh.2020.00152 32411652 10 Petrilli C.M. Jones S.A. Yang J. Rajagopalan H. O'Donnell L. Chernyak Y. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study BMJ 369 2020 m1966 10.1136/bmj.m1966 32444366 11 Simonnet A. Chetboun M. Poissy J. Raverdy V. Noulette J. Duhamel A. High Prevalence of Obesity in Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Requiring Invasive Mechanical Ventilation 28 2020 Obesity (Silver Spring), 1195 1199 10.1002/oby.22831 12 Wang D. Hu B. Hu C. Zhu F. Liu X. Zhang J. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China JAMA 323 11 2020 1061 1069 10.1001/jama.2020.1585 32031570 13 Zhang J.J. Dong X. Cao Y.Y. Yuan Y.D. Yang Y.B. Yan Y.Q. Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan China Allergy 75 7 2020 1730 1741 10.1111/all.14238 32077115 14 Zhang Y. Cui Y. Shen M. Zhang J. Liu B. Dai M. Association of diabetes mellitus with disease severity and prognosis in COVID-19: A retrospective cohort study Diabetes Res Clin Pr 165 2020 108227 10.1016/j.diabres.2020.108227 15 Chudzik M. Babicki M. Kapusta J. Kolat D. Kaluzinska Z. Mastalerz-Migas A. Do the Successive Waves of SARS-CoV-2, Vaccination Status and Place of Infection Influence the Clinical Picture and COVID-19 Severity among Patients with Persistent Clinical Symptoms? The Retrospective Study of Patients from the STOP-COVID Registry of the PoLoCOV-Study J Pers Med 12 5 2022 10.3390/jpm12050706 16 Holly J.M.P. Biernacka K. Maskell N. Perks C.M. Obesity, Diabetes and COVID-19: An Infectious Disease Spreading From the East Collides With the Consequences of an Unhealthy Western Lifestyle Front Endocrinol (Lausanne) 11 2020 582870 10.3389/fendo.2020.582870 17 Abdulhasan M. Ruden X. Rappolee B. Dutta S. Gurdziel K. Ruden D.M. Stress Decreases Host Viral Resistance and Increases Covid Susceptibility in Embryonic Stem Cells Stem Cell Rev Rep 17 6 2021 2164 2177 10.1007/s12015-021-10188-w 34155611 18 Radhakrishnan A. Govindaraj R. Sasidharan A. Ravindra P.N. Yadav R. Kutty B.M. People with dyssomnia showed increased vulnerability to CoVID-19 pandemic: a questionnaire-based study exploring the patterns and predictors of sleep quality using the latent class analysis technique in Indian population Sleep Med 79 2021 29 39 10.1016/j.sleep.2020.12.041 33485259 19 Scartoni F.R. Sant'Ana L.O. Murillo-Rodriguez E. Yamamoto T. Imperatori C. Budde H. Physical Exercise and Immune System in the Elderly: Implications and Importance in COVID-19 Pandemic Period Front Psychol 11 2020 593903 10.3389/fpsyg.2020.593903 20 Chastin S.F.M. Abaraogu U. Bourgois J.G. Dall P.M. Darnborough J. Duncan E. Effects of Regular Physical Activity on the Immune System, Vaccination and Risk of Community-Acquired Infectious Disease in the General Population: Systematic Review and Meta-Analysis Sports Med 51 8 2021 1673 1686 10.1007/s40279-021-01466-1 33877614 21 Jimeno-Almazan A. Pallares J.G. Buendia-Romero A. Martinez-Cava A. Franco-Lopez F. Sanchez-Alcaraz Martinez B.J. Post-COVID-19 Syndrome and the Potential Benefits of Exercise Int J Environ Res Public Health 18 10 2021 10.3390/ijerph18105329 22 de Frel D.L. Atsma D.E. Pijl H. Seidell J.C. Leenen P.J.M. Dik W.A. The Impact of Obesity and Lifestyle on the Immune System and Susceptibility to Infections Such as COVID-19 Front Nutr 7 2020 597600 10.3389/fnut.2020.597600 23 Singh S. Kishore D. Singh R.K. Pathak C. Ranjan K. Higher BCG-induced trained immunity prevalence predicts protection from COVID-19: Implications for ongoing BCG trials Clin Transl Disco 2 2 2022 e60 10.1002/ctd2.60 24 Gujski M. Mularczyk-Tomczewska P. Raciborski F. Samel-Kowalik P. Samolinski L. Olczak-Kowalczyk D. Screening for SARS-CoV-2 Infection in Students at the Medical University of Warsaw, Poland Between November 15 and December 10, 2021 Using a Single Lateral Flow Test, the Panbio COVID-19 Ag Rapid Test Med Sci Monit 28 2022 e936962 10.12659/MSM.936962 25 Worldometer. Worldometer's COVID-19 Data, https://www.worldometers.info/coronavirus/country/poland; 2020 [accessed 27 September 2022]. 26 Visseren F.L.J. Mach F. Smulders Y.M. Carballo D. Koskinas K.C. Back M. ESC Guidelines on cardiovascular disease prevention in clinical practice 34 Eur Heart J 2021 42 2021 3227 3337 10.1093/eurheartj/ehab484 27 Li X. Li J. Qing P. Hu W. COVID-19 and the Change in Lifestyle: Bodyweight, Time Allocation, and Food Choices Int J Environ Res Public Health 18 19 2021 10.3390/ijerph181910552 28 Di Ciaula A. Krawczyk M. Filipiak K.J. Geier A. Bonfrate L. Portincasa P. Noncommunicable diseases, climate change and iniquities: What COVID-19 has taught us about syndemic Eur J Clin Invest 51 12 2021 e13682 10.1111/eci.13682 29 Langhammer B. Bergland A. Rydwik E. The Importance of Physical Activity Exercise among Older People Biomed Res Int 2018 2018 7856823 10.1155/2018/7856823 30 Ugarte M.P. Achilleos S. Quattrocchi A. Gabel J. Kolokotroni O. Constantinou C. Premature mortality attributable to COVID-19: potential years of life lost in 17 countries around the world, January-August 2020 BMC Public Health 22 1 2022 54 10.1186/s12889-021-12377-1 35000578 31 Abdelbasset W.K. Stay Home: Role of Physical Exercise Training in Elderly Individuals' Ability to Face the COVID-19 Infection J Immunol Res 2020 2020 8375096 10.1155/2020/8375096 32 Yuan Q. Huang H.Y. Chen X.L. Chen R.H. Zhang Y. Pan X.B. Does pre-existent physical inactivity have a role in the severity of COVID-19 17534666211025221 Ther Adv Respir Dis 15 2021 10.1177/17534666211025221 33 Bielik V. Grendar M. Kolisek M. A Possible Preventive Role of Physically Active Lifestyle during the SARS-CoV-2 Pandemic; Might Regular Cold-Water Swimming and Exercise Reduce the Symptom Severity of COVID-19? Int J Environ Res Public Health 18 13 2021 10.3390/ijerph18137158 34 Hamer M. Kivimaki M. Gale C.R. Batty G.D. Lifestyle risk factors, inflammatory mechanisms, and COVID-19 hospitalization: A community-based cohort study of 387,109 adults in UK Brain Behav Immun 87 2020 184 187 10.1016/j.bbi.2020.05.059 32454138 35 Filgueira T.O. Castoldi A. Santos L.E.R. de Amorim G.J. de Sousa Fernandes M.S. Anastacio W. The Relevance of a Physical Active Lifestyle and Physical Fitness on Immune Defense: Mitigating Disease Burden, With Focus on COVID-19 Consequences Front Immunol 12 2021 587146 10.3389/fimmu.2021.587146 36 Sallis R. Young D.R. Tartof S.Y. Sallis J.F. Sall J. Li Q. Physical inactivity is associated with a higher risk for severe COVID-19 outcomes: a study in 48 440 adult patients Br J Sports Med 55 19 2021 1099 1105 10.1136/bjsports-2021-104080 33849909 37 Farshbafnadi M. Kamali Zonouzi S. Sabahi M. Dolatshahi M. Aarabi M.H. Aging & COVID-19 susceptibility, disease severity, and clinical outcomes: The role of entangled risk factors Exp Gerontol 154 2021 111507 10.1016/j.exger.2021.111507 38 Schou T.M. Joca S. Wegener G. Bay-Richter C. Psychiatric and neuropsychiatric sequelae of COVID-19 - A systematic review Brain Behav Immun 97 2021 328 348 10.1016/j.bbi.2021.07.018 34339806 39 Ayling K. Jia R. Coupland C. Chalder T. Massey A. Broadbent E. Psychological Predictors of Self-reported COVID-19 Outcomes: Results From a Prospective Cohort Study Ann Behav Med 56 5 2022 484 497 10.1093/abm/kaab106 34979556 40 Sjoberg L. Triolo F. Saadeh M. Dekhtyar S. Calderon-Larranaga A. Welmer A.K. Factors associated with physical activity reduction in Swedish older adults during the first COVID-19 outbreak: a longitudinal population-based study Eur Rev Aging Phys Act 19 1 2022 9 10.1186/s11556-022-00287-z 35365065 41 Hadjistavropoulos T. Asmundson G.J.G. COVID stress in older adults: Considerations during the Omicron wave and beyond J Anxiety Disord 86 2022 102535 10.1016/j.janxdis.2022.102535 42 Grolli R.E. Mingoti M.E.D. Bertollo A.G. Luzardo A.R. Quevedo J. Reus G.Z. Impact of COVID-19 in the Mental Health in Elderly: Psychological and Biological Updates Mol Neurobiol 58 5 2021 1905 1916 10.1007/s12035-020-02249-x 33404981 43 Cenko E. Badimon L. Bugiardini R. Claeys M.J. De Luca G. de Wit C. Cardiovascular disease and COVID-19: a consensus paper from the ESC Working Group on Coronary Pathophysiology & Microcirculation, ESC Working Group on Thrombosis and the Association for Acute CardioVascular Care (ACVC), in collaboration with the European Heart Rhythm Association (EHRA) Cardiovasc Res 117 14 2021 2705 2729 10.1093/cvr/cvab298 34528075 44 Madjid M. Safavi-Naeini P. Solomon S.D. Vardeny O. Potential Effects of Coronaviruses on the Cardiovascular System: A Review JAMA Cardiol 5 7 2020 831 840 10.1001/jamacardio.2020.1286 32219363 45 Clerkin K.J. Fried J.A. Raikhelkar J. Sayer G. Griffin J.M. Masoumi A. COVID-19 and Cardiovascular Disease Circulation 141 20 2020 1648 1655 10.1161/CIRCULATIONAHA.120.046941 32200663 46 The Novel Coronavirus Pneumonia Emergency Response Epidemiology T. The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19) - China, 2020. China CDC Wkly. 2020;2(8):113–22. 47 Li X. Guan B. Su T. Liu W. Chen M. Bin Waleed K. Impact of cardiovascular disease and cardiac injury on in-hospital mortality in patients with COVID-19: a systematic review and meta-analysis Heart 106 15 2020 1142 1147 10.1136/heartjnl-2020-317062 32461330 48 Yang C. Jin Z. An Acute Respiratory Infection Runs Into the Most Common Noncommunicable Epidemic-COVID-19 and Cardiovascular Diseases JAMA Cardiol 5 7 2020 743 744 10.1001/jamacardio.2020.0934 32211809 49 Ziegler C.G.K. Allon S.J. Nyquist S.K. Mbano I.M. Miao V.N. Tzouanas C.N. SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues e19 Cell 181 5 2020 1016 1035 10.1016/j.cell.2020.04.035 32413319 50 Liu H. Wang Z. Sun H. Teng T. Li Y. Zhou X. Thrombosis and Coagulopathy in COVID-19: Current Understanding and Implications for Antithrombotic Treatment in Patients Treated With Percutaneous Coronary Intervention Front Cardiovasc Med 7 2020 599334 10.3389/fcvm.2020.599334 51 Driggin E. Madhavan M.V. Bikdeli B. Chuich T. Laracy J. Biondi-Zoccai G. Cardiovascular Considerations for Patients, Health Care Workers, and Health Systems During the COVID-19 Pandemic J Am Coll Cardiol 75 18 2020 2352 2371 10.1016/j.jacc.2020.03.031 32201335 52 Corrales-Medina V.F. Madjid M. Musher D.M. Role of acute infection in triggering acute coronary syndromes Lancet Infect Dis 10 2 2010 83 92 10.1016/S1473-3099(09)70331-7 20113977 53 Zeng J. Huang J. Pan L. How to balance acute myocardial infarction and COVID-19: the protocols from Sichuan Provincial People's Hospital Intensive Care Med 46 6 2020 1111 1113 10.1007/s00134-020-05993-9 32162032 54 Zhou F. Yu T. Du R. Fan G. Liu Y. Liu Z. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study Lancet 395 10229 2020 1054 1062 10.1016/S0140-6736(20)30566-3 32171076 55 Karadavut S. Altintop I. Long-term cardiovascular adverse events in very elderly COVID-19 patients Arch Gerontol Geriatr 100 2022 104628 10.1016/j.archger.2022.104628 56 Napoli C. Tritto I. Benincasa G. Mansueto G. Ambrosio G. Cardiovascular involvement during COVID-19 and clinical implications in elderly patients. A review Ann Med Surg (Lond) 57 2020 236 243 10.1016/j.amsu.2020.07.054 32802325 57 Gerayeli F.V. Milne S. Cheung C. Li X. Yang C.W.T. Tam A. COPD and the risk of poor outcomes in COVID-19: A systematic review and meta-analysis EClinicalMedicine 33 2021 100789 10.1016/j.eclinm.2021.100789 58 Higham A. Mathioudakis A. Vestbo J. Singh D. COVID-19 and COPD: a narrative review of the basic science and clinical outcomes Eur Respir Rev 29 158 2020 10.1183/16000617.0199-2020 59 Lippi G. Henry B.M. Chronic obstructive pulmonary disease is associated with severe coronavirus disease 2019 (COVID-19) Respir Med 167 2020 105941 10.1016/j.rmed.2020.105941 60 Leung J.M. Yang C.X. Tam A. Shaipanich T. Hackett T.L. Singhera G.K. ACE-2 expression in the small airway epithelia of smokers and COPD patients: implications for COVID-19 Eur Respir J 55 5 2020 10.1183/13993003.00688-2020 61 Milne S. Yang C.X. Timens W. Bosse Y. Sin D.D. SARS-CoV-2 receptor ACE2 gene expression and RAAS inhibitors Lancet Respir Med 8 6 2020 e50 e51 10.1016/S2213-2600(20)30224-1 32411576 62 Mallia P. Message S.D. Gielen V. Contoli M. Gray K. Kebadze T. Experimental rhinovirus infection as a human model of chronic obstructive pulmonary disease exacerbation Am J Respir Crit Care Med 183 6 2011 734 742 10.1164/rccm.201006-0833OC 20889904 63 Lee J.S. Park S. Jeong H.W. Ahn J.Y. Choi S.J. Lee H. Immunophenotyping of COVID-19 and influenza highlights the role of type I interferons in development of severe COVID-19 Sci Immunol 5 49 2020 10.1126/sciimmunol.abd1554 64 Zaki N. Alashwal H. Ibrahim S. Association of hypertension, diabetes, stroke, cancer, kidney disease, and high-cholesterol with COVID-19 disease severity and fatality: A systematic review Diabetes Metab Syndr 14 5 2020 1133 1142 10.1016/j.dsx.2020.07.005 32663789 65 Betancourt-PeñA J. RodríGuez-Castro J. Carlos Avila-Valencia J. Benavides V. Clinical Condition and Symptoms of Patients with Copd with Sars-Cov-2 Infection Chest 160 4 2021 10.1016/j.chest.2021.07.1626 66 Kim H. Hegde S. LaFiura C. Raghavan M. Luong E. Cheng S. COVID-19 illness in relation to sleep and burnout BMJ Nutr Prev Health 4 1 2021 132 139 10.1136/bmjnph-2021-000228 67 Akinci T. Melek Basar H. Relationship between sleep quality and the psychological status of patients hospitalised with COVID-19 Sleep Med 80 2021 167 170 10.1016/j.sleep.2021.01.034 33601228 68 Pataka A. Kotoulas S. Sakka E. Katsaounou P. Pappa S. Sleep Dysfunction in COVID-19 Patients: Prevalence, Risk Factors, Mechanisms, and Management J Pers Med 11 11 2021 10.3390/jpm11111203 69 Bhat S. Chokroverty S. Sleep disorders and COVID-19 Sleep Med 91 2022 253 261 10.1016/j.sleep.2021.07.021 34391672 70 Zhang J. Xu D. Xie B. Zhang Y. Huang H. Liu H. Poor-sleep is associated with slow recovery from lymphopenia and an increased need for ICU care in hospitalized patients with COVID-19: A retrospective cohort study Brain Behav Immun 88 2020 50 58 10.1016/j.bbi.2020.05.075 32512133 71 Ibarra-Coronado E.G. Pantaleon-Martinez A.M. Velazquez-Moctezuma J. Prospero-Garcia O. Mendez-Diaz M. Perez-Tapia M. The Bidirectional Relationship between Sleep and Immunity against Infections J Immunol Res 2015 2015 678164 10.1155/2015/678164 72 Pela G. Goldoni M. Solinas E. Cavalli C. Tagliaferri S. Ranzieri S. Sex-Related Differences in Long-COVID-19 Syndrome J Women’s Health (Larchmt) 31 5 2022 620 630 10.1089/jwh.2021.0411 35333613 73 Fernandez-de-Las-Penas C. Martin-Guerrero J.D. Pellicer-Valero O.J. Navarro-Pardo E. Gomez-Mayordomo V. Cuadrado M.L. Female Sex Is a Risk Factor Associated with Long-Term Post-COVID Related-Symptoms but Not with COVID-19 Symptoms: The LONG-COVID-EXP-CM Multicenter Study J Clin Med 11 2 2022 10.3390/jcm11020413 74 Sylvester S.V. Rusu R. Chan B. Bellows M. O'Keefe C. Nicholson S. Sex differences in sequelae from COVID-19 infection and in long COVID syndrome: a review Curr Med Res Opin 38 8 2022 1391 1399 10.1080/03007995.2022.2081454 35726132 75 Klein S.L. Flanagan K.L. Sex differences in immune responses Nat Rev Immunol 16 10 2016 626 638 10.1038/nri.2016.90 27546235 76 Sharma G. Volgman A.S. Michos E.D. Sex Differences in Mortality From COVID-19 Pandemic: Are Men Vulnerable and Women Protected? JACC Case Rep 2 9 2020 1407 1410 10.1016/j.jaccas.2020.04.027 32373791 77 Stewart S. Newson L. Briggs T.A. Grammatopoulos D. Young L. Gill P. Long COVID risk - a signal to address sex hormones and women's health Lancet Reg Health Eur 11 2021 100242 10.1016/j.lanepe.2021.100242 78 Jacobs L.G. Gourna Paleoudis E. Lesky-Di Bari D. Nyirenda T. Friedman T. Gupta A. Persistence of symptoms and quality of life at 35 days after hospitalization for COVID-19 infection PLoS One 15 12 2020 e0243882 10.1371/journal.pone.0243882 79 Doerre A. Doblhammer G. The influence of gender on COVID-19 infections and mortality in Germany: Insights from age- and gender-specific modeling of contact rates, infections, and deaths in the early phase of the pandemic PLoS One 17 5 2022 e0268119 10.1371/journal.pone.0268119 80 He X. Cheng X. Feng X. Wan H. Chen S. Xiong M. Clinical Symptom Differences Between Mild and Severe COVID-19 Patients in China: A Meta-Analysis Front Public Health 8 2020 561264 10.3389/fpubh.2020.561264 81 Tenforde M.W. Kim S.S. Lindsell C.J. Billig Rose E. Shapiro N.I. Files D.C. Symptom Duration and Risk Factors for Delayed Return to Usual Health Among Outpatients with COVID-19 in a Multistate Health Care Systems Network - United States, March-June 2020 MMWR Morb Mortal Wkly Rep 69 30 2020 993 998 10.15585/mmwr.mm6930e1 32730238 82 Lane A. Hunter K. Lee E.L. Hyman D. Bross P. Alabd A. Clinical characteristics and symptom duration among outpatients with COVID-19 Am J Infect Control 50 4 2022 383 389 10.1016/j.ajic.2021.10.039 34780804 83 Dadras O. SeyedAlinaghi S. Karimi A. Shamsabadi A. Qaderi K. Ramezani M. COVID-19 mortality and its predictors in the elderly: A systematic review Health Sci Rep 5 3 2022 e657 10.1002/hsr2.657 84 Jassat W. Abdool Karim S.S. Mudara C. Welch R. Ozougwu L. Groome M.J. Clinical severity of COVIbD-19 in patients admitted to hospital during the omicron wave in South Africa: a retrospective observational study Lancet Glob Health 10 7 2022 e961 e969 10.1016/S2214-109X(22)00114-0 35597249 85 Matsunaga N. Hayakawa K. Asai Y. Tsuzuki S. Terada M. Suzuki S. Clinical characteristics of the first three waves of hospitalised patients with COVID-19 in Japan prior to the widespread use of vaccination: a nationwide observational study Lancet Reg Health West Pac 22 2022 100421 10.1016/j.lanwpc.2022.100421 86 Thompson M.G. Burgess J.L. Naleway A.L. Tyner H. Yoon S.K. Meece J. Prevention and Attenuation of Covid-19 with the BNT162b2 and mRNA-1273 Vaccines N Engl J Med 385 4 2021 320 329 10.1056/NEJMoa2107058 34192428 87 Ronchini C. Gandini S. Pasqualato S. Mazzarella L. Facciotti F. Mapelli M. Lower probability and shorter duration of infections after COVID-19 vaccine correlate with anti-SARS-CoV-2 circulating IgGs PLoS One 17 1 2022 e0263014 10.1371/journal.pone.0263014 88 Baum U., Poukka E., Leino T., Kilpi T., Nohynek H., Palmu A.A. High vaccine effectiveness against severe Covid-19 in the elderly in Finland before and after the emergence of Omicron (preprint). 2022. https://doi.org/10.1101/2022.03.11.22272140. 89 Popp M. Stegemann M. Riemer M. Metzendorf M.I. Romero C.S. Mikolajewska A. Antibiotics for the treatment of COVID-19 Cochrane Database Syst Rev 10 2021 CD015025 10.1002/14651858.CD015025 90 Vegivinti C.T.R. Evanson K.W. Lyons H. Akosman I. Barrett A. Hardy N. Efficacy of antiviral therapies for COVID-19: a systematic review of randomized controlled trials BMC Infect Dis 22 1 2022 107 10.1186/s12879-022-07068-0 35100985 91 Cortes-Borra A. Aranda-Abreu G.E. Amantadine in the prevention of clinical symptoms caused by SARS-CoV-2 Pharm Rep 73 3 2021 962 965 10.1007/s43440-021-00231-5 92 Popp M. Stegemann M. Metzendorf M.I. Gould S. Kranke P. Meybohm P. Ivermectin for preventing and treating COVID-19 Cochrane Database Syst Rev 7 2021 CD015017 10.1002/14651858.CD015017.pub2
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==== Front J Policy Model J Policy Model Journal of Policy Modeling 0161-8938 1873-8060 The Society for Policy Modeling. Published by Elsevier Inc. S0161-8938(22)00119-3 10.1016/j.jpolmod.2022.12.001 Article Containment Measures during the COVID Pandemic: The role of non-Pharmaceutical Health Policies☆ Funke Michael ab Ho Tai-kuang c⁎ Tsang Andrew d a Hamburg University, Department of Economics, Germany b Tallinn University of Technology, Department of Economics and Finance, Estonia c National Taiwan University, Department of Economics, Taiwan d ASEAN+3 Macroeconomic Research Office – AMRO, Singapore ⁎ Corresponding author. 12 12 2022 12 12 2022 12 6 2022 27 9 2022 9 10 2022 © 2022 The Society for Policy Modeling. Published by Elsevier Inc. All rights reserved. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Many countries have imposed a set of non-pharmaceutical health policy interventions in an effort to slow the spread of the COVID-19 pandemic. The objective of this paper is to examine the effects of the interventions, drawing on evidence from the OECD countries. A special feature here is the mechanism that underlies the impact of the containment policies. To this end, a causal mediation analysis decomposing the total effect into a direct and an indirect effect is conducted. The key finding is a dual cause-effect channel. On the one hand, there is a direct effect of the non-pharmaceutical interventions on the various health variables. Beyond this, a quantitatively dominant indirect impact of non-pharmaceutical interventions operating via voluntary changes in social distancing is shown. Keywords COVID-19 pandemic non-pharmaceutical interventions mediation analysis causal effects ==== Body pmc1 Introduction To contain and mitigate the novel coronavirus (SARS-CoV-2), most countries have implemented a wide range of non-pharmaceutical health policy interventions. These interventions vary between countries and over time but include social distancing restrictions, bans of large gatherings, business closures, national border closures, partial or complete kindergarten and school closures, measures to isolate symptomatic individuals and their contacts, rules for wearing a mask, enhanced surveillance, comprehensive testing and advising the population to self-isolate voluntarily and preferably meet only the same people in ‘social bubbles.’1 Beyond these containment measures, governments have taken a multitude of fiscal and social safety net responses limiting the human and economic impact of the COVID-19 pandemic.2 Understanding whether these interventions have had the desired effect of controlling the pandemic, and which interventions are successful in maintaining control, is critical given their large economic and social costs. Countries vary in their capacity to surveil and enforce laws and regulations. Government interventions, entailing rigorous implementation of mobility restrictions throughout China, appeared to be effective in stemming the outbreak in Wuhan (Kraemer et al., 2020, Prem et al., 2020). In countries where a similar level of enforcement may not be feasible, people must comply voluntarily with mobility restrictions for them to be effective (Reluga, 2010). People may then choose not to comply because they perceive the risk of the pandemic or the benefits of mobility restrictions for themselves to be low. Of particular relevance in this context is the compliance with social distancing measures, in particular (not) meeting friends and acquaintances.3 On the other hand, agents respond to the health hazards and voluntarily change their behavior to less risky activities. One can also put it this way: de jure interventions are only part of the story; de facto compliance and voluntary social distancing matter as well. In the case of recurrent outbreaks, this distinction is particularly relevant, as this leads people to be less respectful of rules and less careful about their behavior. The overall impact of the various measures to “flatten the curve” thus depends on two transmission channels. The first impact channel consists of the mobility changes evoked by the imposition of mitigation policies - the rigor element of governmental stringency measures - and voluntary social distancing - the fear element.4 Stated differently, this channel is mediated by changes in mobility. All the other treatment effects belong to the second non-mobility-mediated impact channel. The causal importance of these two containment channels will be quantified below. This unpacking exercise is called causal mediation analysis.5 The exclusive focus of impact assessments on whether and how much a policy measure works has been repeatedly criticized (Deaton, 2010). Instead, there should be a stronger focus on the question of why a policy intervention works. Statistical framework for the analysis of such causal mechanisms will not only enhance the understanding of causal mechanisms behind non-pharmaceutical policy interventions, but may also enable policymakers to prescribe better policy designs.6 The remainder of the paper is organized as follows. We start by presenting the data and some stylized facts in Section 2. In Section 3, we present the econometric causal mediation methodology and the estimation results. With this retrospective cross-country analysis, we provide estimates regarding the effectiveness of different mandatory non-pharmaceutical interventions versus voluntary social distancing during the first three pandemic waves. To close, we conclude and present some policy implications in Section 4. 2 Data and Variables In this section, we describe the data that we use in our empirical analysis and the variables that we construct to study the effects of non-pharmaceutical interventions. For our analysis, we assemble a panel dataset comprising 36 OECD countries (all the OECD countries except Iceland, for which mobility data are not available) and five variables: (i) COVID-19 infections; (ii) COVID-19-related fatalities; (iii) the COVID-19 effective reproduction rates; (iv) government non-pharmaceutical interventions; and (v) country-level mobility data. The health data are reported with a daily frequency. To investigate their potential impact, weekly data are considered.7 Our sample period covers February 26, 2020 to July 27, 2021. Overall, 2280 data points are available, implying a sufficiently high number of degrees of freedom. We use the number of COVID-19 cases and fatalities as a proxy for the severity of the pandemic in each country. We gather daily data on confirmed new cases and new fatalities from Roser et al. (2020). As an alternative indicator for the time course of the pandemic we also look at the real time reproduction rate, Rt, as constructed by Arroyo-Marioli et al. (2021).8 The time-varying reproduction rate Rt mirrors the infection dynamics due to the decline in susceptible individuals (intrinsic factors) and the implementation of control measures (extrinsic factors). If Rt<1, it suggests that the pandemic is in decline and may be regarded as being under control at time t (vice versa if Rt>1). Not surprisingly, all COVID-19 waves started with a value of Rtabove 1 and ended with a value below 1. The time-varying growth rate is estimated using the Kalman filter from data on the number of infected individuals, and their specification can be assessed by standard statistical test procedures. The advantage of the time series approach is that it can adapt very quickly to the most recent information and hence produce timely real-time estimates. This flexibility enables the effects of changes in policy, virus mutations and human behavior to be tracked.9 Since the fraction of detected COVID-19 cases changes rapidly over short windows of time, statistical filtering techniques are employed by Arroyo-Marioli et al. (2021) to obtain a smoothed version of Rt. In order to evaluate the impact of government policies and thus the treatment effect on the above variables, we employ data from the Oxford COVID-19 Government Response Tracker (OxCGRT) for containment measures.10 The OxCGRT collects and quantifies information on government policy responses across fourteen dimensions, namely: (i) school closures; (ii) workplace closures; (iii) public event cancellations; (iv) gathering restrictions; (v) public transportation closures; (vi) stay-at-home orders; (vii) restrictions on internal movement; (viii) international travel bans; (ix) facial coverings; (x) testing policy; (xi) contact tracing; (xii) public information campaigns; (xiii) cash unemployment payments; and (xiv) freezing of households’ financial obligations. The stringency indices in the database are rank scaled, depending on whether the measure is a recommendation or a requirement and whether it is targeted or nationwide. To exploit the information from the various sub-indices optimally, we calculate the first principal component instead of simple averages, allowing some measures to be less weighted than others.11 Increasing values of the index imply stricter regulations. To review behavioral responses to the containment policies, de facto mobility measures are needed. A straightforward and useful set of high-frequency social distancing indicators is based on the location history of mobile devices, which was exceptionally made available by Google due to the COVID-19 pandemic. It provides a daily pulse of economic activity, proxied by the extent to which people frequent recreational spots and their workplaces. In addition to their timeliness, an advantage of the mobility indices is their standardized format and availability for a large group of economies, allowing cross-country comparisons. The availability of de-identified and aggregated Google mobility data divided into different categories opens up the possibility to quantify the effectiveness of the compliance with the measures decreed. The mobility data of people with smartphones and with “location history” turned on in their phones’ settings are available for six location categories (grocery and pharmacies, parks, residential, retail and recreation, transit stations and workplaces). Google has constructed these data by comparing visits to and lengths of stays in certain places compared with a baseline using information from Google Maps.12 This study works with the first principal component of the various categories.13 In the following section, we will present the instrument variables mediation estimation results. The mediator that we consider is the first principal component of the actual Google mobility measures. The goal is to find causal treatment effect; and the IV mediation analysis is an important econometric tool to achieve this objective. In particular, the mediation analysis unpacks the black box of causality and allows researchers to assess the relative importance of direct and indirect effects. 3 Estimation Methodology and Estimation Results This section describes the empirical methodology used to examine the causal effect of mandatory and voluntary social distancing on COVID-19 infections and fatalities. To investigate this subject, we employ a causal mediation instrumental variable setup. To identify the fraction of the total health impact Yit in country i in period t that is explained by the behavioral response Mit, we conduct a mediation analysis that decomposes the total effect of the mandatory interventions Titon Yit into (i) the mediated indirect effect of Tit on Yit that operates via mandatory and voluntary social distancing Mit and (ii) the intervention effects that do not work via Mit. The outcome variable Yitis allowed to be any type of random variable (continuous, binary or categorical). Among others, examples are health system measures like mandates for wearing masks, mass testing and contact tracing. In Figure 1, we illustrate the formal mediation framework for decomposing an overall effect into interventional direct and indirect impacts.Fig. 1 Direct and Indirect Treatment Effects in the Mediation Analysis. Note: Solid arrows between nodes represent causal effects. The diagram is a customized panel data version reprinted from Dippel et al. (2020). Fig. 1 The key quantity of interest is the calculation of how much of the treatment variable Tit is transmitted via the focal mediation variable Mit. In other words, causal mediation analysis decomposes the total effect into its indirect and direct components. The indirect component represents a posited explanation for why the treatment works, while the direct component represents all other possible explanations. The interest focuses on what proportion of the total effect is indirect. An obvious problem is that in most real-world applications the treatment Tit is systematically nonrandom and therefore needs to be instrumented by a variable Zit which is a reasonable strong predictor of Tit. Given a scalar instrument variable with these properties, Figure 1 shows that Mit mediates the effect of the treatment Titon Yit, as indicated by the Tit=fT(Zit,εT,it)→Mit=fM(Tit,εM,it)→Yit=fY(Tit,Mit,εY,it) path. This is the indirect effect of the treatment Tit on Yit. Another arrow indicates that there is also a direct impact of the treatment Tit=fTZit,εT,it→Yit=fYTit,Mit,εY,it that does not work via Mit. For identification, we require the validity of Zit⊥εT,it,εM,it,εY,it, where ⊥denotes statistical independence (VanderWeele, 2015). Establishing causality in the pandemic is difficult because countries’ decision to implement containment measures crucially depends on the evolution of the virus. In other words, the non-pharmaceutical interventions (treatments) Tit are an endogenous policy variable. This implies that addressing causality requires us to control effectively for this endogenous response, which would otherwise lead to biased estimates of the treatment effect. To identify the causal effect, we instrument the interventions of each OECD country i=1,⋯,36 with the weighted average of the interventions of all other OECD countries j=1,⋯,36,j≠i. In other words, the instrument represents the non-own interventions. The results below explore the validity of the instrument.14 Formally, given the anticipated endogeneity of the treatment variable, the standard instrumental variables estimation approach for Tit and Mit at the country–week level is(1) Tit=βTZ×Zit+μi+εT,it (2) Mit=βMT×Tˆit+μi+εM,it, whereTˆit is the estimated value of Tit in the first-stage regression (1), Zit is a reasonably strong scalar instrument (predictor) for the endogenous COVID-19 treatment variable Tit, μi are country fixed effects, εT,it and εM,it are the unobserved error terms in the first- and second-stage regressions and the indices i and t refer to the country and the week. The country fixed effects allow for idiosyncratic but persistent differences across countries. Dippel et al. (2020) showed that the total effect, the indirect causal mediation effect and the direct treatment effect can be estimated as follows:(3) Mit=βMZ×Zit+βMT×Tit+μi+εM,it, (4) Yit=βYM×Mˆit−k+βYT×Tit−k+μi+εY,it, whereMˆit is the estimated value of Mit in the first-stage regression (3) and k is the number of lags. Dippel et al. (2020) have shown that the total treatment effect (non-pharmaceutical interventions enacted against the COVID-19 virus) is then given as the sum of the indirect causal mediation effect βMT×βYM and the direct treatment effectβYT.15 The overall total impact βMT×βYM+βYT is expected to be negative. In order to decompose the total policy impact into a direct and an indirect effect, the chosen instrument must satisfy two conditions. The first condition is that the instrument is informative and thus the problem of weak instruments does not exist. The reason is that weak instruments can produce biased IV estimators and hypothesis tests with large size distortions. To test for informative instruments, we report in Table 1 the Kleibergen and Paap (2006) statistic, which is a robust version of the Cragg and Donald (1993) test for weak instruments. The finding is that we can reject the weak instrument hypothesis and thus the chosen instrument is relevant. The second identification assumption underlying the causal mediation analysis is that the instrument is weakly exogenous. One possible objection to the instrument inspired by Autor et al. (2013) is that neighboring OECD countries might have a similar cultural background (individualism, libertarian) or like-minded governments which could violate the exclusion restriction. The countries may even have coordinated interventions internationally. This possible objection requires to discuss the instrument validity with care. To verify the logic of the instrument we present a heat map of the stringency of country-specific containment measures over time in Figure 2. The heat map uses a dark-to-light color spectrum to highlight country differences in the timeline of containment measure stringency. What does the visual storytelling reveal? During the sample period, governments have enforced different on-pharmaceutical interventions, under rapidly changing, unprecedented circumstances. The OECD government responses included the laissez-faire strategy, which implies doing little to nothing, the herd immunity strategy, which implies a few measures only or measures relying on voluntary compliance, and more aggressive approaches based on the implementation of a wide range of stringent measures, sometimes even limiting civil rights and liberty. The heat map illustrates that the containment policies of the OECD countries differed substantially in the stringency, timing and sequencing of non-pharmaceutical interventions. This cross-country dissimilarity and variation thus supports the choice of the chosen instrument.16 Table 1 IV Mediation Estimation Results for the Number of New Infections, the Number of New Pandemic-Related Fatalities, and the Reproduction Rate. Table 1Outcome Variable Weekly New Infections Weekly New Pandemic-Related Fatalities Average Weekly Reproduction Rate Total Impact -0.31***(0.02) -0.28***(0.02) -0.26***(0.02) Direct Non-pharmaceutical Policy Impact -0.08**(0.04) -0.08**(0.03) -0.08**(0.03) Indirect Mediation Mobility Impact -0.23***(0.04) -0.20***(0.04) -0.18***(0.04) Causal Mediation Effect in % 74.02 72.55 70.39 F-Stat One (T on Z) 270.98 147.28 172.56 F-Stat Two (M on Z|T) 40.47 44.12 45.57 Kleibergen and Paap (2006) F-statistic for excluded instruments in the first stage one regression (T on Z) and the first stage two regression (M on Z|T) are denoted as F-Stat One (T on Z) and F-Stat Two (M on Z|T), respectively. Fig. 2 Heat Map of the Non-pharmaceutical Interventions in the OECD Countries. Note: The chart shows the weekly-average strength of the OxCGRT non-pharmaceutical stringency index for 36 OECD countries which is based on a hierarchical coding scheme. Source: OxCGRT. Fig. 2 Table 1 presents our baseline estimation results for the 36 OECD countries. The estimates decompose the total impact into direct and indirect effects. The mandatory non-pharmaceutical interventions have a causal effect on the health variables, but part of this effect occurs through voluntary social distancing. This causal indirect effect occurs because the mandatory measures influence voluntary social distancing, which in turn influences the future course of the pandemic. The indirect and direct effects together form the total effect. The key quantity of interest is the calculation of how much of the treatment variable is transmitted by the mediating variable. The sample period is February 26, 2020 to July 27, 2021. The three dependent variables are the log-difference of the new confirmed COVID-19 cases per million population, the log-difference of the new confirmed COVID-19 fatalities per million population, and the weekly reproduction rate Rt.17 All the specifications include country fixed effects to control for omitted factors. Prior to the actual estimation, the appropriate lag structure in (4) needs to be determined. In the estimates for the infection rate and the reproduction rate, the policy and mobility variables Tit and Mit are lagged by one week, respectively.18 In the estimates for fatalities, the lag is two weeks. The estimation results for the various health policy metrics in the first three columns of Table 1 show a consistent pattern. Several findings are worth noting. First, according to the Kleibergen and Paap (2006) test statistics, the null hypotheses that the instrument is weak is comfortably rejected. Second, all coefficients generally have the expected sign. Third, the direct intervention effects are significant and thus contribute to the containment of the pandemic. Fourth, the indirect mediation variable “de facto mobility” has paramount importance for the evolution of the pandemic across countries and over time. In the case of new COVID-19 infections, the causal explanatory proportion is 74 %. In the case of new pandemic-related fatalities and the reproduction rate, it is 73 % and 70 %, respectively. Finally, the flip side of the coin is that the direct public health policies, like mandating mask wearing, test-and-trace policies, restricting visits to care/elderly/retirement homes and specific testing in such homes, have a subordinate impact as can be seen from the smaller coefficients.19 Overall, our estimates for the three health policy metrics enable us to reach an important conclusion. For the purpose of modeling the impacts of non-pharmaceutical intervention on the health policy metrics, the de facto mobility index is the pivotal causal mediation variable as it captures the ultimate impacts of both the rigor element of government policies and the behavioral changes that they trigger. In other words, the mobility indices can be interpreted as the all-encompassing societal response to the imposed lockdown measures rather than that of the government alone. This conclusion is supported by Chen et al. (2020). It is also consistent with Maloney and Taskin (2020), showing that mandatory social distancing policies matter less than voluntary demobilization in reducing mobility and enabling social distancing. Similarly, the great significance of induced cautious behavior was shown by Goolsbee and Syverson (2021). They found that visits to businesses declined by up to 60 % because of the pandemic but that legal restrictions explained only 7 percentage points of this drop. Finally, the results in Golstein et al. (2021) also match this finding. Their results indicate that a fading effect of non-pharmaceutical interventions can be attributed to an increasing non-compliance with mobility restrictions. In other words, lockdown fatigues diminish the effectiveness of de jure containment policies. 4 Conclusion and Policy Implications In program evaluations, analysts tend to focus solely on the study of health policy impact. Policymakers may, however, demand deeper explanations for why interventions matter. Causal mediation analyses are able to shed light on such causal mechanisms. Our analysis contributes to the body of work that is trying to understand the effectiveness of different measures to control the spread of COVID-19. Coupling the data of confirmed COVID-19 cases, fatalities and the COVID-19 reproduction rate with non-pharmaceutical interventions and Google mobility data, we employ a causal mediation instrumental-variable approach, using as instrument for each country a jackknife (leave-one-out) mean of the other countries’ interventions. Thus, we decompose the total effect into direct and indirect impacts. The methodology reveals the mechanism through which non-pharmaceutical health policy interventions affect the future course of the pandemic. Ideally, such studies could inform public health policy in the onset of the COVID-19 pandemic. The underlying idea is that health policy stringency and actual mobility are distinct concepts. The effectiveness of additional policy measures depends on their adherence. Conversely, relaxing restrictions does not guarantee an increase of economic activity if the general public remains concerned about the virus and therefore exercises voluntary social distancing. Therefore, the mobility index reflects both government policies and preferences of the general public, and it can thus be thought of as the society’s policy choice rather than that of the government alone. Two main findings are prominent. First, the estimation results indicate that the de facto mitigation effort reflected in the mobility data plays the key role in safeguarding people’s health and lives. Given that governments can only influence mobility behavior to a certain extent, this is corroborative of recent work modeling an endogenous agent response to health risks. The underlying proposition of this work is that significant voluntary social distancing will be practiced regardless of the presence of non-pharmaceutical interventions.20 Second, the estimation results highlight effective and convincing communication as a critical component of the management of the COVID-19 pandemic. Furthermore, to achieve compliance, governmental legitimacy is needed.21 The relevance of the results is obvious. COVID-19 could reappear in further waves, especially when highly contagious mutations occur. Returning to pre-pandemic routines may be impossible until mass vaccinations have taken place. In addition, future virus mutations must not call into question possible vaccination achievements. Until then, the above conclusions apply. To flatten the curve and contain the repeated infection waves, a reduction in de facto mobility is imperative and the key to success. Uncited reference (Goldstein et al. (2021)) Appendix : List of OECD Countries Included in the Regressions See Appendix section here.TableCountry ISO Code Country ISO Code Country ISO Code Australia AUS Greece GRC New Zealand NZL Austria AUT Hungary HUN Norway NOR Belgium BEL Ireland IRL Poland POL Canada CAN Israel ISR Portugal PRT Chile CHL Italy ITA Slovakia SVK Colombia COL Japan JPN Slovenia SVN Czech Republic CZE South Korea KOR Spain ESP Denmark DNK Latvia LVA Sweden SWE Estonia EST Lithuania LTU Switzerland CHE Finland FIN Luxembourg LUX Turkey TUR France FRA Mexico MEX United Kingdom GBR Germany DEU Netherlands NLD USA USA Note: Iceland is excluded owing to missing data. Acknowledgement We would like to thank the editor and the anonymous referees for helpful comments and suggestions on an earlier draft of the paper. All remaining errors are our own. ☆ 7 Dreve Lansrode, Rhode St. Genese, Belgium 1640 [email protected] www.JournalofPolicyModeling 1 Since the onset of the pandemic, multiple modeling approaches have been used to analyze disease dynamics and shed light on the impact of physical distancing and other public health measures (Alfano et al., 2022, Anderson et al., 2020, Bonfiglio et al., 2022, Kumar et al., 2021). For a review of this literature analyzing the effect of containment measures, see the IMF (2020, pp. 65–84). 2 For an overview of the country-specific fiscal responses, see https://www.imf.org/en/Topics/imf-and-covid19/Policy-Responses-to-COVID-19. 3 The compliance with governmental strictness measures has been attributed to factors such as personal attitudes, risk-taking behavior, political orientation, social norms, trust in the government, trust in media sources and belief in science (Allcott et al., 2020, Bargain and Aminjonov, 2020, Malmandier and Nadler, 2011, Simonov et al., 2020, Webster et al., 2020). 4 See Van Bavel et al. (2020) for several of these behavioral interventions. Their overview of knowledge in social and behavioral science explored the potential avenues and channels through which these disciplines can support the management of the pandemic crisis. 5 Mediation analysis moves beyond calculation of average treatment impacts and instead seeks to quantify the impact of a treatment that operates through a particular causal mechanism. In other words, the mediator can be interpreted as an intermediate outcome. Nontechnical surveys to causal mediation analysis are provided by Imai et al. (2011) and Celli (2021). 6 The review article of Ludwig et al. (2011, p. 20) has highlighted how understanding mechanisms in policy analyses plays a “crucial and underappreciated role”. 7 A drawback of daily data is that the reported infection numbers exhibit irregular fluctuations due to reporting delays and varying test incidence due to local holidays and weekends. In other words, weekly data overcome time delays from alternative reporting bodies. Another reason for using weekly data is that, in many countries, a time lag exists between the federal government’s lockdown decision and its effective implementation at the regional level. 8 The daily Rt data are available for download at http://www.globalrt.live/. We have converted the Rt data into a weekly series, so that the frequency matches that of the other data. 9 The simple and transparent methodology is data driven and so are different from the structural models used by epidemiologists which rely on assumptions about transmission and behavior (see, e.g. Avery et al., 2020). 10 See https://www.bsg.ox.ac.uk/research/research-projects/coronavirus-government-response-tracker. 11 Another justification for the aggregate intervention variable is the multicollinearity problem as many containment measures have often been introduced simultaneously or very close together. 12 According to Google’s mobility report, the baseline day represents a normal value for that day of the week, so the baseline day is the median value from the five-week period January 3 to February 6, 2020. A growing literature has provided evidence of the usefulness of now-casting mobility data to assess the impact of the COVID-19 pandemic containment policies (see, e.g., Buckee et al., 2020 and Chen et al., 2020). 13 A drawback is that that the mobility data only measure intra-national mobility. In other words, cross-border mobility is not recorded. For the cross-border mobility effects, data on international passenger volumes and flight routes have been used in the literature; see, for example, Keita (2020) and Wu et al. (2020). 14 The instrument choice parallels the procedure followed by Autor et al. (2013) who instrument trade exposure from China with the trade exposure that a set of other countries face. The identifying assumption is that this set of countries is unlikely to be subject to the same (correlated) demand shocks such that the instrument identifies increasing trade exposure due to exogenous productivity increase in China and not changes in domestic demand conditions. 15 In contrast, the alternative causal mediation estimator of Frölich and Huber (2017) requires separate instruments for the treatment and the mediation variable. 16 Sebhatu et al. (2020) have analyzed the speed of adoption of the different COVID-19 policies across OECD countries. The diffusion analysis shows two characteristics. On the one hand, significant country-specific heterogeneity exists. Certain policy measures have not been adopted at all by individual countries. Furthermore, countries differed in the speed of implementation. The econometric analysis reveals that economic, demographic, political, and public health-related characteristics help explaining these cross-country differences. On the other hand, government policies are also driven by the policies initiated in neighboring countries - all else being equal. These two properties indicate that the chosen instrument is correlated with the endogenous variable, while satisfying the exclusion restriction. 17 The testing of the appropriate functional form of the dependent variable is performed using the Box–Cox statistic. The test decisively favors the logarithmic form. 18 Askitas et al. (2021) found that the COVID-19 infections started to drop with a time lag of about 1 week after the containment policies were introduced. The 2-week lag for fatalities confirms the well-known fact that particularly severe disease progressions become apparent after 10–14 days. 19 To be effective, test-and-trace policies require testing on a truly mass scale and the ability to carry out testing swiftly, which many OECD countries have struggled to implement (OECD, 2020). 20 Several models integrating social distancing decision making into canonical epidemiology models have been developed. Examples include the work by Eichenbaum et al., 2020a, Eichenbaum et al., 2020b, Eichenbaum et al., 2020c and Krueger et al. (2020). These modeling frameworks underline the role of voluntary social distancing, which is important for delaying and flattening the COVID-19 infection curve, and thus help to design policies that improve the trade-off between economic and health outcomes during the pandemic. 21 Christensen and Lægreid (2020) defined government legitimacy as the belief that the government does what is desirable, appropriate and fair. They hypothesized that Norway’s success in handling the pandemic and the compliance with stay-at-home orders were mostly due to its government’s legitimacy. ==== Refs References Alfano V. Ercolano S. Pinto M. “Fighting the COVID Pandemic: National Policy Choices in Non-Pharmaceutical Interventions” Journal of Policy Modeling 44 2022 22 40 35034999 Allcott H. Boxell L. Conway J. Gentzkow M. Thaler M. Yang D. “Polarization and public health: Partisan differences in social distancing during the coronavirus pandemic” Journal of Public Economics 2020 Anderson R.M. Heesterbeek H. Klinkenberg D. Hollingsworth T.D. “How will country-based mitigation measures influence the course of the COVID-19 epidemic?” The Lancet Vol. 395 2020 931 934 Arroyo-Marioli F. Bullano F. Kucinskas S. Rondón-Moreno C. “Tracking of COVID-19: A new real-time estimation using the Kalman filter” PLoS ONE 16 2021 e0244474 Askitas N. Tatsiramos K. Verheyden B. “Estimating Worldwide Effects of Non-pharmaceutical Interventions on COVID-19 Incidence and Population Mobility Patterns Using a Multiple-Event Study Science Report Vol. 11 2021 Article # 1972 Autor D.H. Dorn D. Hanson G.H. “The China syndrome: Local labor market effects of import competition in the United States” American Economic Review Vol. 103 2013 2121 2168 Avery C. Bossert W. Clark A. Ellison G. Fisher Ellison S. “An Economist's Guide to Epidemiology Models of Infectious Disease Journal of Economic Perspectives 34 2020 79 104 Bargain O. Aminjonov U. Trust and Compliance to Public Health Policies in Times of COVID-19 Journal of Public Economics 192 2020 104316 Bavel J.J.V. Baicker K. Boggio P.S. “Using social and behavioural science to support COVID-19 pandemic response” Nature Human Behaviour Vol. 4 2020 460 471 Bonfiglio A. Coderoni S. Esposti R. “Policy Responses to COVID-19 Pandemic Waves: Cross-Region and Cross-Sector Economic Impact” Journal of Policy Modeling 44 2022 252 279 35400770 Buckee C.O. Balsari S. Chan J. Crosas M. Dominici F. Gasser Urs Yonatan H.G. Grenfell B. Halloran M.E. Kraemer M.U.G. Lipsitch M. Metcalf C.J.E. Meyers L.A. Perkins T.A. Santillana M. Scarpino S.V. Viboud C. Wesolowski A. Schroeder A. Aggregated mobility data could help fight COVID-19 Science Vol. 368 2020 145 146 Celli V. “Causal Mediation Analysis in Economics: Objectives, Assumptions, Models” Journal of Economic Surveys 35 2021 1 21 Chen S. Igan D. Pierri N. Presbitero A.F. Tracking the Economic Impact of COVID-19 and Mitigation Policies in Europe and the United States 2020 IMF Working Paper WP/20/125 Washington, DC Christensen T. Lægreid P. “Balancing governance capacity and legitimacy: How the Norwegian Government handled the COVID-19 crisis as a high performer” Public Administration Review Vol. 80 2020 774 779 Cragg J.G. Donald S.G. “Testing identifiability and specification in instrumental variables models” Econometric Theory Vol. 9 1993 222 240 Deaton A. “Understanding the mechanisms of economic development” Journal of Economic Perspectives 24 2010 3 16 Dippel C. Ferrara A. Heblich S. “Causal mediation analysis in instrumental-variables regressions” The Stata Journal Vol. 20 2020 613 626 Eichenbaum M. Rebelo S. Trabandt M. The Macroeconomics of Epidemics 2020 NBER Working Paper No. 26882 Cambridge, MA. Eichenbaum M. Rebelo S. Trabandt M. The Macroeconomics of Testing and Quarantining 2020 NBER Working Paper No. 27104 Cambridge, MA Eichenbaum M. Rebelo S. Trabandt M. Epidemics in the Neoclassical and New Keynesian Models 2020 NBER Working Paper No. 27430 Cambridge, MA Frölich M. Huber M. “Direct and indirect treatment effects – Causal chains and mediation analysis with instrumental variables” Journal of the Royal Statistical Society, Series B Vol. 79 2017 1645 1666 Goldstein P. Yeyati E.L. Sartorio L. “Lockdown fatigue: The diminishing effects of quarantines on the spread of COVID-19” Covid Economics 67 2021 1 23 Goolsbee A. Syverson C. “Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020” Journal of Public Economics Vol. 193 2021 104311 Imai K. Keele L. Tingley D. Yamamoto T. “Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies” American Political Science Review 105 2011 765 789 IMF (2020), World Economic Outlook: A Long and Difficult Ascent, October 2020, Washington, DC. Keita S. Air Passenger Mobility, Travel Restrictions, and the Transmission of the COVID-19 Pandemic between Countries, Covid Economics No. 9 2020 CEPR London 77 96 Kleibergen F. Paap R. “Generalized reduced rank tests using the singular value decomposition” Journal of Econometrics Vol. 133 2006 97 126 Kraemer M.U.G. Yang C. Gutierrez B. Wu C. Klein B. Pigott D.M. Open COVID-19 Data Working Group du Plessis L. Faria N.R. Li R. Hanage W.P. Brownstein J.S. Layan M. Vespignani A. Tian H. Dye C. Pybus Ol.G. Scarpino S.V. The effect of human mobility and control measures on the COVID-19 epidemic in China Science Vol. 368 2020 493 497 Krueger D. Uhlig H. Xie T. Macroeconomic Dynamics and Reallocation in an Epidemic 2020 NBER Working Paper No. 27047 Cambridge, MA Kumar A. Priya B. Srivastava S.K. “Response to the COVID-19: Understanding Implications of Government Lockdown Policies” Journal of Policy Modeling 43 2021 76 94 33132465 Ludwig J. Kling J.R. Mullainathan S. “Mechanism experiments and policy evaluations” Journal of Economic Perspectives 25 2011 17 38 Malmandier U. Nadler S. “Depression babies: Do macroeconomic experiences affect risk-taking?” Quarterly Journal of Economics Vol. 126 2011 373 416 Maloney W.F. Taskin T. “Social distancing and economic activity during COVID-19: A global view” COVID Economics Vol. 13 2020 156 176 OECD (2020), Testing for COVID-19: A Way to Lift Confinement Restrictions, Paris. Prem K. Liu Y. Russell T.W. Kucharski A.J. Eggo R.M. Davies N. “The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: A modelling study” Lancet Public Health Vol. 5 2020 e261 e270 Reluga T.C. “Game theory of social distancing in response to an epidemic” PLOS Computational Biology Vol. 6 2010 e1000793 Roser M. Ritchie H. Ortiz-Ospina E. Hasell J. Coronavirus Pandemic (COVID-19) 2020 [online]. Available from 〈https://ourworldindata.org/coronavirus〉 Sebhatu A. Wennberg K. Arora-Jonsson S. Lindberg S.I. “Explaining the Homogeneous Diffusion of COVID-19 Nonpharmaceutical Interventions Across Heterogeneous Countries2 PNAS 117 2020 21201 21208 32788356 Simonov A. Sacher S.K. Dubé J.-P. Biswas S. The Persuasive Effect of Fox News: Non-compliance with Social Distancing during the COVID-19 Pandemic 2020 NBER Working Paper No. 27237 Cambridge, MA VanderWeele T.J. Explanation in Causal Inference: Methods for Mediation and Interaction 2015 Oxford (Oxford University Press) Webster R.K. Brooks S.K. Smith L.E. “How to improve adherence with quarantine: Rapid review of the evidence” Public Health Vol. 182 2020 163 169 Wu J.T. Leung K. Leung G.M. “Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: A modelling study” The Lancet Vol. 395 2020 689 697
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==== Front ACS Sens ACS Sens se ascefj ACS Sensors 2379-3694 American Chemical Society 36482673 10.1021/acssensors.2c01340 Article Amplification Free Detection of SARS-CoV-2 Using Multi-Valent Binding https://orcid.org/0000-0002-4549-7239 Roychoudhury Appan † Allen Rosalind J. ‡ Curk Tine § https://orcid.org/0000-0002-1893-1773 Farrell James ∥⊥ McAllister Gina # Templeton Kate # https://orcid.org/0000-0001-6121-2021 Bachmann Till T. *† † Infection Medicine, Edinburgh Medical School: Biomedical Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, EH16 4SB, United Kingdom ‡ School of Physics and Astronomy, University of Edinburgh, Edinburgh, EH9 3FD, United Kingdom § Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois60208, United States ∥ Institute of Physics, Chinese Academy of Sciences, Beijing, 100190, China ⊥ School of Physical Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China # Department of Laboratory Medicine, Royal Infirmary of Edinburgh, Edinburgh, EH16 4SA, United Kingdom * E-mail: [email protected]. 09 12 2022 acssensors.2c0134024 06 2022 24 11 2022 © 2022 The Authors. Published by American Chemical Society 2022 The Authors This article is made available via the PMC Open Access Subset for unrestricted RESEARCH re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. We present the development of electrochemical impedance spectroscopy (EIS)-based biosensors for sensitive detection of SARS-CoV-2 RNA using multi-valent binding. By increasing the number of probe–target binding events per target molecule, multi-valent binding is a viable strategy for improving the biosensor performance. As EIS can provide sensitive and label-free measurements of nucleic acid targets during probe–target hybridization, we used multi-valent binding to build EIS biosensors for targeting SARS-CoV-2 RNA. For developing the biosensor, we explored two different approaches including probe combinations that individually bind in a single-valent fashion and the probes that bind in a multi-valent manner on their own. While we found excellent biosensor performance using probe combinations, we also discovered unexpected signal suppression. We explained the signal suppression theoretically using inter- and intra-probe hybridizations which confirmed our experimental findings. With our best probe combination, we achieved a LOD of 182 copies/μL (303 aM) of SARS-CoV-2 RNA and used these for successful evaluation of patient samples for COVID-19 diagnostics. We were also able to show the concept of multi-valent binding with shorter probes in the second approach. Here, a 13-nt-long probe has shown the best performance during SARS-CoV-2 RNA binding. Therefore, multi-valent binding approaches using EIS have high utility for direct detection of nucleic acid targets and for point-of-care diagnostics. SARS-CoV-2 electrochemical biosensor point-of-care diagnostics multi-valent binding electrochemical impedance spectroscopy. H2020 European Research Council 10.13039/100010663 682237 University Of Edinburgh 10.13039/501100000848 IS3-R2.47 19/20 document-id-old-9se2c01340 document-id-new-14se2c01340 ccc-price ==== Body pmcIn 2020, the devastating pandemic of Coronavirus disease 2019 (COVID-19) emerged as a result of rapid human-to-human transmission of the severe acute respiratory syndrome 2 virus (SARS-CoV-2). The success of the response to the pandemic was critically dependent on diagnostics and created a huge global demand for suitable COVID-19 tests to help with rapid detection and isolation of positive cases. Presently, most countries rely on serological and viral nucleic acid tests for COVID-19 diagnostics.1−3 Several nucleic acid based methods such as real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR),4−6 clustered regularly interspaced short palindromic repeats (CRISPR),7,8 and isothermal amplification9,10 have been reported for SARS-CoV-2 detection. Among them, RT-qPCR is used globally as a gold standard for detecting viral RNA. Nonetheless, RT-qPCR has some shortcomings, including the requirement for costly instruments, reagents, and trained personnel, transportation of samples to reference laboratories, and a longer sample-to-result time.11,12 Therefore, rapid, accurate, and easy-to-implement methods for SARS-CoV-2 RNA detection are still an unmet need. Previous studies addressed direct detection of SARS-CoV-2 but require assay procedures which limit their suitability for point-of-care testing.13−15 Point-of-care test compatible biosensors, especially those using electrochemical transducers, provide a good alternative to PCR analysis owing to their on-site detection capabilities, low cost, easy operation, and scalability for mass production.16,17 Due to their simplicity and ease of miniaturization, electrochemical biosensors are especially advantageous in clinical diagnostics and point-of-care testing (POCT).18 In particular, electrochemical impedance spectroscopy (EIS) has previously been used to build fast and sensitive tests for nucleic acid assays.19−21 EIS methods allow for single-step and label-free measurements of the targets during nucleic acid hybridization events utilizing simple hand-held instrumentations and readout.22,23 This could help with the development of a rapid and easy screening technology for COVID-19. EIS biosensors for nucleic acid testing generally use sequence-specific single-strand nucleic acid probes which are immobilized on the electrode surfaces. Conventionally, these probes are designed to be complementary to only one region of the target molecule. While the individual probe binds strongly, the overall target capture is dependent on only one binding event.12 In contrast, multi-valent binding, in which several regions of the target nucleic acid hybridize simultaneously to the probe (or probes), provides an alternative approach with potential advantages. By increasing the number of probe–target binding sites, multi-valent binding could enhance the sensitivity of the biosensor. Our recent computational modeling study suggested that the design of short oligonucleotide probes for multi-valent binding to a nucleic acid target could lead to high sensitivity and selectivity, especially for long targets and in the case where probe design took account of both target and nontarget sequences.24 In the present study, we developed EIS biosensors for multi-valent targeting SARS-CoV-2 RNA. We compared two approaches to build the biosensor: (1) combinations of probes that each bind in a single-valent manner and (2) probes that bind multi-valently on their own. This study suggests that multi-valent binding is a highly promising approach for direct detection of nucleic acids in the development of molecular diagnostics at point-of-care. Experimental Section Reagents, Probes, and Targets Tris(2-carboxyethyl)phosphine hydrochloride (TCEP), sulfuric acid (H2SO4), dimethyl sulfoxide (DMSO), dimethylformamide (DMF), sodium chloride (NaCl), monosodium phosphate (NaH2PO4), disodium phosphate (Na2HPO4), potassium ferricyanide {K3Fe(CN)6}, and potassium ferrocyanide {K4Fe(CN)6} were purchased from Sigma-Aldrich (Gillingham, UK). 6-Mercapto-1-hexanol (MCH) and 1,6-hexanedithiol (HDT) were procured from ProChimia Surfaces (Gdynia, Poland). All of the other reagents were of analytical grade and used without any further purification. All aqueous solutions were made with deionized water (resistivity >18 MΩ cm) from a Millipore Milli-Q water purification system (Bedford, MA, USA). Peptide nucleic acid (PNA) single-stranded probes were ordered via Cambridge Research Biochemicals (Cleveland, UK) and obtained from Panagene (Daejeon, South Korea). Probes (>95% HPLC purified) were synthesized with an 11-mercapto-1-undecanol linker on the N-end of the PNA (equivalent to 5′-end of DNA) for specific attachment onto the gold surfaces via self-assembly. Stock solutions of PNA probe were made with 50% (v/v) dimethylformamide (DMF) aqueous solution and used further for sensing layer formation. Exact size-matched DNA (T-RdRp1, T-RdRp2, T-RdRp3, T-N1, T-MV1, T-MV2, and T-MV3) and MV3 RNA targets were the reverse complementary sequences of their respective probes. DNA and RNA target sequences were bought from Metabion (Martinsried, Germany) and used after preparing stock solutions by dissolving lyophilized targets into nuclease-free deionized (DI) water. The stock solutions of PNA probe and DNA target were both kept at −20 °C when not in use. Details of the sequence and structure of PNA probes and DNA or RNA targets are given in Table S1. Buffer for diluting SARS-CoV-2 RNA after bench-extraction was purchased from Takara Bio Europe (Saint-Germain-en-Laye, France) and preserved at −20 °C during storage. Remel MicroTest M4RT viral transport media (VTM) was purchased from Thermo Fisher Scientific (Waltham, MA, USA). Probe Design Single-valent probe sequences were designed after selecting three target regions from the RNA-dependent RNA polymerase (RdRp) gene4 and one target region of the nucleocapsid protein (N) gene6 of the SARS-CoV-2 genome. The P-RdRp1, P-RdRp2, and P-RdRp3 sequences are specific for the target regions at 15431–15452 bp, 15505–15530 bp, and 15470–15494 bp, respectively, whereas the P-N1 sequence is specific for the 28287–28306 bp region of the SARS-CoV-2 genome (see Scheme S1). For the multi-valent probe design, please see the Supplementary Experimental Section in Supporting Information. PNA probes were modified with a spacer comprising three ethylene glycol units (abbreviated as AEEEA) and a terminal thiol group at the N-end. Details on theoretical calculation for intra- and inter-probe interactions, statistics for data analysis, and the preparation of SARS-CoV-2 RNA from cell culture or patient samples can be found in Supplementary Experimental Section. Electrode Preparation Screen-printed gold electrodes (DRP-C223BT, DropSens) were functionalized with PNA probes as per the protocol used in our earlier study.25 In brief, following electrochemical cleaning using 100 mM sulfuric acid solution and cyclic voltammetry technique (0 to 1.6 V potential range, 100 mV/s scan rate, 10 cycles), the PNA probe molecules were immobilized onto the gold working electrodes by exposing the cleaned electrodes with a mixed solution containing specific concentrations of the probe (thiol-modified PNA probe + 100 μM MCH + 200 μM HDT + 5 mM TCEP in 50% DMSO solution) for 16 h followed by blocking with 1 mM MCH solution for 2 h. Finally, the probe-functionalized electrodes were serially rinsed with 50% (v/v) DMSO aqueous solution and DI water and then used for subsequent impedance measurements (see Figure 1). Figure 1 Electrode preparation, characterization, and SARS-CoV-2 detection: (A) process showing electrode preparation for SARS-CoV-2 RNA hybridization, flow cell for electrochemical measurements, and electrical circuit for electrochemical impedance spectroscopy (EIS) Nyquist plot fitting, (B) cyclic voltammetry, (C) EIS Nyqusit plot characterizations at each surface modification of electrode, and (D) dose dependent detection of SARS-CoV-2 RNA (9.09 × 101 – 9.09 × 105 copies/μL) after electrical circuit fitting of Nyquist plots and interpretation on charge transfer resistance (Rct). Rs, W, and CPE represent solution resistance, Warburg element, and constant phase element, respectively. Electrochemical Impedance Spectroscopy (EIS) Measurements All electrochemical measurements including EIS were conducted using an Autolab PGSTAT128N potentiostat/galvanostat system (Metrohm Autolab, Utrecht, Netherlands). EIS measurements were recorded in the frequency range 0.3 Hz to 100 kHz with a signal amplitude of 10 mV rms at the measured open circuit potential. Nyquist plots for each measurement were used to fit the data in an equivalent Randles’ circuit and to calculate the charge transfer resistance (Rct) values using the NOVA 2.1 software. The Randles’ equivalent circuit was designed with a constant phase element (as nonideal capacitance) in place of the double layer capacitance (Cdl) and the corresponding changes in the Rct values were considered in the Faradaic EIS measurements. EIS measurements were performed pre and post hybridization with a 35 min sample incubation using probe-functionalized electrodes, and the increase in Rct values (ΔRct) from pre (baseline measurement) to post (sample measurement) hybridization was considered during the plotting of impedance data. All EIS studies were performed in 10 mM sodium phosphate buffer, pH 7 with 20 mM sodium chloride and 0.2 mM potassium ferri/ferrocyanide redox mediator (EIS measurement buffer), while the cyclic voltammetric characterization of electrodes was performed with 10 times concentrated EIS measurement buffer (see Figure 1). Results Design of Single-Valent Probes As a member of the coronavirus family, SARS-CoV-2 possesses single-stranded positive-sense RNA (+ssRNA) which is ∼3 kb in length.26 As shown in Scheme S1, the SARS-CoV-2 genome comprises the 5′ untranslated region (UTR), replicase complex (ORF1ab), spike surface glycoprotein gene (S gene), small envelope gene (E gene), matrix gene (M gene), nucleocapsid gene (N gene), 3′ UTR, and several nonstructural open reading frames. We designed four probes (P-N1, P-RdRp1, P-RdRp2, and P-RdRp3) to bind in a single-valent manner, i.e., for one binding site in the SARS-CoV-2 genome each. We verified the binding of SARS-CoV-2 target with the respective probes by calculating probe–genome interaction free energy using NuPack (Figure 2). Each probe showed a strong binding signal at the respective complementary target region. Figure 2 Theoretical free energy (ΔG) of SARS-CoV-2 target (nc045512) for binding with (A) P-N1, (B) P-RdRp1, (C) P-RdRp2, and (D) P-RdRp3 probes. The arrows indicate the respective binding regions. Predicted free energy of binding ΔG, of the SARS-CoV-2 genome to selected probes, resolved by position along the genome. To make these plots, the SARS-CoV-2 was split into 100 nt sections. For each section of the genome, the free energy of binding to the probe ΔG was calculated using NuPack,27 with parameters for RNA–RNA interactions at 1 M salt (to screen out electrostatic interactions) and 20 °C,28 and without considering intra-genome binding to model PNA–DNA interactions, as described in the Supplementary Experimental Section. Performance of Single-Valent Probes with Size-Matched DNA Target The performance of each single-valent probe was investigated at the same probe concentration (9 μM) using EIS. The relative strength of the measured EIS signals (ΔRct) was, in order of intensity: P-N1 > P-RdRp1 > P-RdRp2 > P-RdRp3 (Figure S6). Probe P-RdRp2 had a low EIS response, presumably due to the formation of several secondary structures. No further work was conducted subsequently with the P-RdRp3 probe because of its poor response (p = 0.96 w.r.t blank measurements). We found 7 and 4 self-annealing sites for P-RdRp2 and P-RdRp3, respectively, while both the probes showed one hairpin loop formation structure. For our planned multi-valent binding of SARS-CoV-2 RNA, we first considered the optimal single-valent probe concentrations (Figure S1). Next, we combined two or three of the single-valent probes together, to achieve multi-valent binding of the target. Please see Supplementary Results Section for the details on effect of probe concentration, probe combination, signal suppression, hybridization temperature, and our theoretical calculation to explain response suppression during the probe combinations. SARS-CoV-2 RNA Detection with Single-Valent Probes To test the utility of our probe combinations for direct detection of SARS-CoV-2 RNA, we investigated the performance of the single-valent probes with a long, native RNA target from cell culture, consisting of the SARS-CoV-2 RNA genome. To this end, we performed EIS measurements for the P-N1 + P-RdRp1 combination at equimolar concentration (3 μM each), and for the individual P-N1 (3 μM) and P-RdRp1 (3 μM) with SARS-CoV-2 RNA (9.09 × 105 copies/μL) at 50 °C (Figure 3). As negative controls, we recorded the signals after incubation with reagents used in the sample preparation of the SARS-CoV-2 RNA and the EIS buffer. We found a strong, significant enhancement in the EIS signal for the P-N1 + P-RdRp1 combination and the P-N1 alone (p < 0.0001 in both cases) upon addition of the SARS-CoV-2 RNA target. The P-RdRp1 showed a less significant signal increase (p = 0.12) upon target addition. Importantly, we did not observe any significant signal increase for the negative controls. Figure 3 Direct detection of SARS-CoV-2 RNA with single-valent probes: EIS signals (ΔRct) of electrodes functionalized with P-N1 and P-RdRp1 either alone or in combination at 3 μM each after 35 min incubation at 50 °C with buffer, viral transport media (VTM) control, negative diluent control, or SARS-CoV-2 RNA (9.09 × 105 copies/μL). Data represent the mean ± SD; n = 3. Dose Dependence of SARS-CoV-2 RNA Detection and COVID-19 Patient Sample Analysis To investigate whether our biosensor could detect SARS-CoV-2 RNA at clinically relevant concentrations, we studied its response to a dilution series of RNA derived from the same SARS-CoV-2 sample and the P-N1 + P-RdRp1 combination (3 μM each) at 50 °C (see Figure S7 for the overlay of Nyquist and Bode plots). The dose response curve (Figure 1D or S8) for the EIS studies with SARS-Cov-2 RNA concentrations showed an EIS signal (ΔRct) that correlated strongly with the target concentration. We obtained a Limit of Detection (LOD) of 182 copies/μL (equivalent to 303 aM) and Limit of Quantitation (LOQ) of 4550 copies/μL (equivalent to 7.58 fM) based on the blank measurements29 (mean value 4.45 kΩ, standard deviation ±1.52 kΩ, and n = 3). For further investigation with real patient samples, SARS-CoV-2 RNA from COVID-19 positive samples were analyzed, and the results (Figure 4) demonstrate a significant increase (p < 0.0001), as compared to background (buffer control), and a decent correlation (Pearson r = 0.36) with the gold standard qPCR method. Figure 4 COVID-19 patient sample analysis: (A) EIS signals (ΔRct) of electrodes functionalized with the combination of P-N1 and P-RdRp1 (3 μM each) after 35 min incubation at 50 °C with either COVID-19 positive samples (1:2.5 dilution with measurement buffer and deionized water) or measurement buffer control. Data represent the mean ± SD; n = 10. (B) Pearson correlation showing the relationship between the sensor signal (ΔRct) and gold standard qPCR method (Ct value). Design of Multi-Valent Probes We designed three shorter probes (8, 10, and 13 nt in length) to bind multi-valently to the SARS-CoV-2 RNA, i.e., to have multiple binding sites on the target RNA (Figure 5). The probe design approach also ensured that our multi-valent probes would bind specifically to SARS-CoV-2 rather to other coronavirus genomes (see Supplementary Experimental Section). By using short probes we hoped to avoid within-probe secondary structure formation. By designing the probes to bind multi-valently, we hoped to achieve the advantages of multi-valent binding, without encountering the problems with probe–probe interaction that we observed during the co-immobilization of single-valent probes. Figure 5 Binding free energy (ΔG) of SARS-CoV-2 target (nc045512) for binding with (A) P-MV1, (B) P-MV2, and (C) P-MV3 probes, predicted using NuPack (see Supplementary Experimental Section). The arrows indicate the binding regions. SARS-CoV-2 RNA Detection with Multi-Valent Probes We analyzed solutions of SARS-CoV-2 RNA at two different concentrations (9.09 × 105 copies/μL and 4.74 × 105 copies/μL) at room temperature (21 °C) with the P-MV1, P-MV2, and P-MV3 probes at 6 μM probe concentration. We also studied the SARS-CoV-2 solution with 9.09 × 105 copies/μL concentration at 50 °C. All three multi-valent probes (P-MV1, P-MV2, and P-MV3) showed higher signals for the SARS-CoV-2 sample with 9.09 × 105 copies/μL concentration as compared to the negative controls both at room temperature and 50 °C (Figure 6). The P-MV2 and P-MV3 probes displayed a further increase in the EIS signals (ΔRct) at 50 °C as compared to room temperature. Figure 6 Direct detection of SARS-CoV-2 RNA with multi-valent probes: EIS signals (ΔRct) of electrodes functionalized with 6 μM solutions of P-MV1, P-MV2, and P-MV3, after 35 min sample incubation with buffer, viral transport media (VTM), negative diluent control, or SARS-CoV-2 RNA samples of 4.74 × 105 copies/μL at 21 °C, and 9.09 × 105 copies/μL at 21 and 50 °C. Multi-Valent Binding Analysis with P-MV3 Probe To check the multi-valent binding of the target, we took our best performing multi-valent probe P-MV3 and did dose dependence studies for the size-matched RNA oligo (single biding site) and the full-length SARS-CoV-2 RNA (multiple binding sites). We observed a lower equilibrium binding constant (KD = 19.64 fM) for the SARS-CoV-2 target (multiple binding sites in target) as compared to the size matched RNA oligo target with only one binding site (KD = 94.01 nM) (Figure S10). We anticipate that the lower KD value resulted from the multi-valent binding of the target with P-MV3. Comparison of Single-Valent Probe Combination with Multi-Valent Probes for SARS-CoV-2 RNA Detection To compare the two ways of achieving multivalency, combinations of single-valent probes and the use of individual multi-valent probes, we studied the EIS responses (ΔRct) of the P-N1 + P-RdRp1 combination (3 μM each) and the P-MV1, P-MV2, and P-MV3 multi-valent probes (6 μM). We used a single SARS-CoV-2 RNA sample (9.09 × 105 copies/μL) to ensure the same conditions for all probes and incubated at 50 °C for 35 min. Both the P-N1 + P-RdRp1 probe combination and the P-MV3 multi-valent probe produced strong signals, although the signal from the other multi-valent probes was less strong (Figure 7). We used a microRNA-specific control probe (P-miR122), which showed a lower response than the P-N1 + P-RdRp1 probe combination and the P-MV3 probe (Figure S9). Therefore, further investigation of the sensitivity and selectivity properties of both the dual combination of single-valent probes and of the multi-valent P-MV3 would be useful (e.g., at different probe concentrations and different concentrations of the target). However, the measurements performed in this study suggest that the combination of the two single-valent probes P-N1 + P-RdRp1 has higher sensitivity than the designed multi-valent probes, despite the presence of signal suppression due to probe–probe interactions. Figure 7 Comparison of direct detection of SARS-CoV-2 RNA by a single-valent probe combination with multi-valent probes: EIS signals (ΔRct) of electrodes functionalized with either the combination of P-N1 and P-RdRp1 (3 μM each) or P-MV1, P-MV2, or P-MV3 (6 μM each) after 35 min sample incubation at 50 °C with buffer, viral transport media (VTM), negative diluent control, or SARS-CoV-2 RNA sample (9.09 × 105 copies/μL). Data represent the mean ± SD; n = 3. Discussion As the COVID-19 pandemic has shown, it is highly desirable to detect SARS-CoV-2 RNA at point-of-care. Here, we aimed to develop electrochemical biosensors for COVID-19 POCT by functionalizing commercially available screen-printed electrodes with SARS-CoV-2 RNA specific PNA probes following two strategies: (i) combinations of probes with a single target binding region each and (ii) individual probes with multiple target binding regions each.24 Our most important finding was that a combination of single-valent probes can perform well for direct detection of the SARS-CoV-2 RNA target, with a clinically relevant detection limit. We achieved a detection limit of 182 copies/μL (303 aM) for SARS-CoV-2 RNA. This is well within the relevant clinical range of SARS-CoV-2 RNA as the viral load is often between 101 and 105 copies/μL in throat swaps and sputum samples on days 1 to 8 after onset of the disease.11,30,31 As a comparison, typical detection limits for SARS-CoV-2 RNA RT-qPCR assays are in the range of 0.45–7.8 copies/μL.4,5,32 For POCT detection of SARS-CoV-2 DNA/RNA, a wide range of different methods have been proposed.12,33−36 Among studies that report detection limits for the whole SARS-CoV-2 RNA genome, some have obtained more sensitive detection, but at the cost of greater methodological complexity. For example, Zhao et al. obtained a LOD of 0.2 copies/μL for SARS-CoV-2 RNA from the clinical specimens using calixarene functionalized graphene oxide combined with a sandwich-type assay and differential pulse voltammetry (DPV),12 while Kong et al. obtained a LOD of 0.03 copies/μL for SARS-CoV-2 nucleic acid (cDNA and in vitro transcribed RNA) detection using a Y-shaped DNA dual probe-functionalized graphene-field effect transistor to simultaneously target the ORF1ab and N genes.35 This strong performance of our biosensor occurred despite the fact that we found combinations of single-valent probes to be prone to signal suppression. Our study suggests that both secondary structure formation within probes and probe–probe hybridization can significantly suppress target binding. This conclusion emerges from the fact that we could account quantitatively for our response suppression data using a theoretical analysis based on the thermodynamics of intra- and inter-probe binding, that assumed only unhybridized probe monomers could contribute to target binding. These observations complement those of a previous study by Gao et al., who showed that the presence of secondary structures in probes, as well as in targets, can adversely affect DNA–DNA hybridization kinetics both in solution and on surfaces.37 Indeed, since target-probe binding is far more thermodynamically favorable than inter- or intra-probe binding, our observation points to the relevance of kinetic effects in probe–target binding. For multi-valent probes, we did not expect the same signal suppression issue, since here one does not need to use probe mixtures, and the multi-valent probes were also shorter, reducing intra-probe self-hybridization potential. Our previous computational study has shown that multi-valent probes can lead to higher sensitivity and specificity for detection of long DNA targets.24 Multiple binding sites produce strong overall binding (even if individual binding sites are weak), leading to high sensitivity. In this study, we indeed obtained good sensitivity for the multi-valent P-MV3, although the dual combination of single-valent probes showed somewhat higher sensitivity. Perhaps the length of the SARS-CoV-2 RNA (∼3 kb) was too short to fully realize the benefits of multi-valent probe design. Our work shows a simple, low-cost, and easy-to-implement EIS-based method for detection of SARS-CoV-2 RNA at point-of-care that can give a LOD within the clinical range. To our knowledge, our study is the first to use EIS for direct detection of SARS-CoV-2 RNA. Most other reported EIS-based techniques for SARS-CoV-2 detection have targeted the spike protein or have been immunoassay-based,19,38−40 although EIS-based detection of the whole SARS-CoV-2 particle has been reported.41 The measurements performed in this study suggest that multi-valent binding, combined with EIS, can be a promising approach for direct detection of SARS-CoV-2 RNA. Further investigation of the properties of the multi-valent probes would be useful (e.g., at different probe concentrations and different concentrations of the target). As demonstrated by various theoretical and experimental studies,24,42−44 multi-valent probes can have superselective targeting properties, which should aid in achieving better specificity in detecting SARS-CoV-2 RNA from samples containing other similar viruses. Therefore, specificity studies of the designed multi-valent probes for the SARS-CoV-2 target, and a comparison of specificity performance with the single-valent probe combination, would be intriguing and relevant in future research. In particular, we plan to investigate the specificity of the designed probes in the presence of other common cold corona viruses, such as HCoV-OC43, HCoV-HKU1, HCoV-229E, and HCoV-NL63. Conclusions We have demonstrated direct, amplification free detection of SARS-CoV-2 RNA with clinically relevant sensitivity using an EIS biosensor and a multi-valent binding approach. Two approaches, single-valent probe combination and multi-valent probes, were found feasible. We further found that multiple probe combinations can lead to unexpected signal suppression and provided a theoretical model to explain these. In summary, multi-valent target binding is highly promising for direct detection of SARS-CoV-2 RNA and likely offers significant opportunities for molecular diagnostics of other diseases at point-of-care. Supporting Information Available The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acssensors.2c01340.Supplementary experimental section, supplementary results section, nomenclature and sequence of probes and targets, SARS-CoV-2 structure and genome organization with target regions, single-valent probe-to-probe comparison, dose dependence studies of SARS-CoV-2 RNA using the combination of P-N1 and P-RdRp1, overlay of Nyquist and Bode plots, comparison of specific probes with negative control probe, dose dependent target detection for analyzing multivalency of P-MV3 (PDF) Supplementary Material se2c01340_si_001.pdf The authors declare no competing financial interest. Acknowledgments The authors acknowledge financial support from the University of Edinburgh-Institutional Strategic Support Fund (ISSF3) award (ref. no. IS3-R2.47 19/20). The authors thank Chris Brackley, Jure Dobnikar, and Daan Frenkel for valuable discussions on the theoretical analysis. RJA was funded by the European Research Council under Consolidator Grant 682237 EVOSTRUC. ==== Refs References Weissleder R. ; Lee H. ; Ko J. ; Pittet M. J. COVID-19 diagnostics in context. Sci. Transl. Med. 2020, 12 (546 ), eabc1931 10.1126/scitranslmed.abc1931.32493791 Yuan X. ; Yang C. ; He Q. ; Chen J. ; Yu D. ; Li J. ; Zhai S. ; Qin Z. ; Du K. ; Chu Z. ; Qin P. Current and perspective diagnostic techniques for COVID-19. ACS Infect. Dis 2020, 6 (8 ), 1998–2016. 10.1021/acsinfecdis.0c00365.32677821 Pokhrel P. ; Hu C. ; Mao H. Detecting the coronavirus (COVID-19). ACS Sens 2020, 5 (8 ), 2283–2296. 10.1021/acssensors.0c01153.32627534 Corman V. M. ; Landt O. ; Kaiser M. ; Molenkamp R. ; Meijer A. ; Chu D. K. ; Bleicker T. ; Brünink S. ; Schneider J. ; Schmidt M. L. ; Mulders D. G. ; Haagmans B. L. ; van der Veer B. ; van den Brink S. ; Wijsman L. ; Goderski G. ; Romette J.-L. ; Ellis J. ; Zambon M. ; Peiris M. ; Goossens H. ; Reusken C. ; Koopmans M. P. ; Drosten C. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Eurosurveillance 2020, 25 (3 ), 2000045 10.2807/1560-7917.ES.2020.25.3.2000045.31992387 Chu D. K. W. ; Pan Y. ; Cheng S. M. S. ; Hui K. P. Y. ; Krishnan P. ; Liu Y. ; Ng D. Y. M. ; Wan C. K. C. ; Yang P. ; Wang Q. ; Peiris M. ; Poon L. L. M. Molecular diagnosis of a novel coronavirus (2019-nCoV) causing an outbreak of pneumonia. Clin. Chem. 2020, 66 (4 ), 549–555. 10.1093/clinchem/hvaa029.32031583 Real-time RT-PCR panel for detection 2019-Novel Coronavirus; Centers for Disease Control and Prevention: Atlanta, GA, 2020. Guo L. ; Sun X. ; Wang X. ; Liang C. ; Jiang H. ; Gao Q. ; Dai M. ; Qu B. ; Fang S. ; Mao Y. ; Chen Y. ; Feng G. ; Gu Q. ; Wang R. R. ; Zhou Q. ; Li W. SARS-CoV-2 detection with CRISPR diagnostics. Cell Discov 2020, 6 (1 ), 34 10.1038/s41421-020-0174-y.32435508 Hou T. ; Zeng W. ; Yang M. ; Chen W. ; Ren L. ; Ai J. ; Wu J. ; Liao Y. ; Gou X. ; Li Y. ; Wang X. ; Su H. ; Gu B. ; Wang J. ; Xu T. Development and evaluation of a rapid CRISPR-based diagnostic for COVID-19. PLOS Pathog 2020, 16 (8 ), e1008705 10.1371/journal.ppat.1008705.32853291 Lamb L. E. ; Bartolone S. N. ; Ward E. ; Chancellor M. B. Rapid detection of novel coronavirus/Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) by reverse transcription-loop-mediated isothermal amplification. PLoS One 2020, 15 (6 ), e0234682 10.1371/journal.pone.0234682.32530929 Yu L. ; Wu S. ; Hao X. ; Dong X. ; Mao L. ; Pelechano V. ; Chen W.-H. ; Yin X. Rapid detection of COVID-19 Coronavirus using a reverse transcriptional loop-mediated isothermal amplification (RT-LAMP) diagnostic platform. Clin. Chem. 2020, 66 (7 ), 975–977. 10.1093/clinchem/hvaa102.32315390 Pan Y. ; Zhang D. ; Yang P. ; Poon L. L. M. ; Wang Q. Viral load of SARS-CoV-2 in clinical samples. Lancet Infect. Dis 2020, 20 (4 ), 411–412. 10.1016/S1473-3099(20)30113-4.32105638 Zhao H. ; Liu F. ; Xie W. ; Zhou T.-C. ; OuYang J. ; Jin L. ; Li H. ; Zhao C.-Y. ; Zhang L. ; Wei J. ; Zhang Y.-P. ; Li C.-P. Ultrasensitive supersandwich-type electrochemical sensor for SARS-CoV-2 from the infected COVID-19 patients using a smartphone. Sens. Actuators B Chem. 2021, 327 , 128899 10.1016/j.snb.2020.128899.32952300 Alekseenko A. ; Barrett D. ; Pareja-Sanchez Y. ; Howard R. J. ; Strandback E. ; Ampah-Korsah H. ; Rovšnik U. ; Zuniga-Veliz S. ; Klenov A. ; Malloo J. ; Ye S. ; Liu X. ; Reinius B. ; Elsässer S. J. ; Nyman T. ; Sandh G. ; Yin X. ; Pelechano V. Direct detection of SARS-CoV-2 using non-commercial RT-LAMP reagents on heat-inactivated samples. Sci. Rep 2021, 11 (1 ), 1820 10.1038/s41598-020-80352-8.33469065 Dighe K. ; Moitra P. ; Alafeef M. ; Gunaseelan N. ; Pan D. A rapid RNA extraction-free lateral flow assay for molecular point-of-care detection of SARS-CoV-2 augmented by chemical probes. Biosens. Bioelectron 2022, 200 , 113900 10.1016/j.bios.2021.113900.34959185 Garcia-Venzor A. ; Rueda-Zarazua B. ; Marquez-Garcia E. ; Maldonado V. ; Moncada-Morales A. ; Olivera H. ; Lopez I. ; Zuñiga J. ; Melendez-Zajgla J. SARS-CoV-2 direct detection without RNA isolation with loop-mediated isothermal amplification (LAMP) and CRISPR-Cas12. Front. Med. 2021, 8 , 627679 10.3389/fmed.2021.627679. Ronkainen N. J. ; Halsall H. B. ; Heineman W. R. Electrochemical biosensors. Chem. Soc. Rev. 2010, 39 (5 ), 1747–1763. 10.1039/b714449k.20419217 Turner A. P. F. Biosensors: sense and sensibility. Chem. Soc. Rev. 2013, 42 (8 ), 3184–3196. 10.1039/c3cs35528d.23420144 Roychoudhury A. ; Basu S. ; Jha S. K. Dopamine biosensor based on surface functionalized nanostructured nickel oxide platform. Biosens. Bioelectron 2016, 84 , 72–81. 10.1016/j.bios.2015.11.061.26626970 Zhang Z. ; Pandey R. ; Li J. ; Gu J. ; White D. ; Stacey H. D. ; Ang J. C. ; Steinberg C.-J. ; Capretta A. ; Filipe C. D. M. ; Mossman K. ; Balion C. ; Miller M. S. ; Salena B. J. ; Yamamura D. ; Soleymani L. ; Brennan J. D. ; Li Y. High-affinity dimeric aptamers enable the rapid electrochemical detection of wild-type and B.1.1.7 SARS-CoV-2 in unprocessed saliva. Angew. Chem. Int. Ed 2021, 60 (45 ), 24266–24274. 10.1002/anie.202110819. Corrigan D. K. ; Schulze H. ; Henihan G. ; Ciani I. ; Giraud G. ; Terry J. G. ; Walton A. J. ; Pethig R. ; Ghazal P. ; Crain J. ; Campbell C. J. ; Mount A. R. ; Bachmann T. T. Impedimetric detection of single-stranded PCR products derived from methicillin resistant Staphylococcus aureus (MRSA) isolates. Biosens. Bioelectron 2012, 34 (1 ), 178–184. 10.1016/j.bios.2012.01.040.22365363 Chiriacò M. S. ; Primiceri E. ; Monteduro A. G. ; Bove A. ; Leporatti S. ; Capello M. ; Ferri-Borgogno S. ; Rinaldi R. ; Novelli F. ; Maruccio G. Towards pancreatic cancer diagnosis using EIS biochips. Lab Chip 2013, 13 (4 ), 730–734. 10.1039/c2lc41127j.23287869 Yang L. ; Chen T. A handheld electrochemical sensing platform for point-of-care diagnostic applications; 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS); 19–21 Oct. 2017; pp 1–4.30406220 Lu Z. ; Wang H. ; Naqvi S. R. ; Fu H. ; Zhao Y. ; Song H. ; Christen J. B. Point of care electrochemical impedance spectroscopy device; 2015 28th IEEE International System-on-Chip Conference (SOCC); 8–11 Sept. 2015; pp 240–244. Curk T. ; Brackley C. A. ; Farrell J. D. ; Xing Z. ; Joshi D. ; Direito S. ; Bren U. ; Angioletti-Uberti S. ; Dobnikar J. ; Eiser E. ; Frenkel D. ; Allen R. J. Computational design of probes to detect bacterial genomes by multivalent binding. Proc. Natl. Acad. Sci. U.S.A 2020, 117 (16 ), 8719–8726. 10.1073/pnas.1918274117.32241887 Roychoudhury A. ; Dear J. W. ; Bachmann T. T. Proximity sensitive detection of microRNAs using electrochemical impedance spectroscopy biosensors. Biosens. Bioelectron 2022, 212 , 114404 10.1016/j.bios.2022.114404.35635974 Ding X. ; Yin K. ; Li Z. ; Lalla R. V. ; Ballesteros E. ; Sfeir M. M. ; Liu C. Ultrasensitive and visual detection of SARS-CoV-2 using all-in-one dual CRISPR-Cas12a assay. Nat. Commun. 2020, 11 (1 ), 4711 10.1038/s41467-020-18575-6.32948757 Zadeh J. N. ; Steenberg C. D. ; Bois J. S. ; Wolfe B. R. ; Pierce M. B. ; Khan A. R. ; Dirks R. M. ; Pierce N. A. NUPACK: Analysis and design of nucleic acid systems. J. Comput. Chem. 2011, 32 (1 ), 170–173. 10.1002/jcc.21596.20645303 Egholm M. ; Buchardt O. ; Christensen L. ; Behrens C. ; Freier S. M. ; Driver D. A. ; Berg R. H. ; Kim S. K. ; Norden B. ; Nielsen P. E. PNA hybridizes to complementary oligonucleotides obeying the Watson–Crick hydrogen-bonding rules. Nature 1993, 365 (6446 ), 566–568. 10.1038/365566a0.7692304 McNaught A. D. ; Wilkinson A. Compendium of chemical terminology; Blackwell Science Oxford, 1997; Vol. 1669 . Pan X. ; Chen D. ; Xia Y. ; Wu X. ; Li T. ; Ou X. ; Zhou L. ; Liu J. Asymptomatic cases in a family cluster with SARS-CoV-2 infection. Lancet Infect. Dis 2020, 20 (4 ), 410–411. 10.1016/S1473-3099(20)30114-6.32087116 Kim J. Y. ; Ko J.-H. ; Kim Y. ; Kim Y.-J. ; Kim J.-M. ; Chung Y.-S. ; Kim H. M. ; Han M.-G. ; Kim S. Y. ; Chin B. S. Viral load kinetics of SARS-CoV-2 infection in first two patients in Korea. J. Korean Med. Sci. 2020, 35 (7 ), 1 10.3346/jkms.2020.35.e86. Wang X. ; Yao H. ; Xu X. ; Zhang P. ; Zhang M. ; Shao J. ; Xiao Y. ; Wang H. Limits of detection of 6 Approved RT–PCR kits for the novel SARS-Coronavirus-2 (SARS-CoV-2). Clin. Chem. 2020, 66 (7 ), 977–979. 10.1093/clinchem/hvaa099.32282874 Hwang C. ; Park N. ; Kim E. S. ; Kim M. ; Kim S. D. ; Park S. ; Kim N. Y. ; Kim J. H. Ultra-fast and recyclable DNA biosensor for point-of-care detection of SARS-CoV-2 (COVID-19). Biosens. Bioelectron 2021, 185 , 113177 10.1016/j.bios.2021.113177.33915435 Kumar M. S. ; Nandeshwar R. ; Lad S. B. ; Megha K. ; Mangat M. ; Butterworth A. ; Knapp C. W. ; Knapp M. ; Hoskisson P. A. ; Corrigan D. K. ; Ward A. C. ; Kondabagil K. ; Tallur S. Electrochemical sensing of SARS-CoV-2 amplicons with PCB electrodes. Sens. Actuators B Chem. 2021, 343 , 130169 10.1016/j.snb.2021.130169. Kong D. ; Wang X. ; Gu C. ; Guo M. ; Wang Y. ; Ai Z. ; Zhang S. ; Chen Y. ; Liu W. ; Wu Y. ; Dai C. ; Guo Q. ; Qu D. ; Zhu Z. ; Xie Y. ; Liu Y. ; Wei D. Direct SARS-CoV-2 nucleic acid detection by Y-shaped DNA dual-probe transistor assay. J. Am. Chem. Soc. 2021, 143 (41 ), 17004–17014. 10.1021/jacs.1c06325.34623792 Qiu G. ; Gai Z. ; Tao Y. ; Schmitt J. ; Kullak-Ublick G. A. ; Wang J. Dual-functional plasmonic photothermal biosensors for highly accurate severe acute respiratory syndrome Coronavirus 2 detection. ACS Nano 2020, 14 (5 ), 5268–5277. 10.1021/acsnano.0c02439.32281785 Gao Y. ; Wolf L. K. ; Georgiadis R. M. Secondary structure effects on DNA hybridization kinetics: a solution versus surface comparison. Nucleic Acids Res. 2006, 34 (11 ), 3370–3377. 10.1093/nar/gkl422.16822858 Li X. ; Qin Z. ; Fu H. ; Li T. ; Peng R. ; Li Z. ; Rini J. M. ; Liu X. Enhancing the performance of paper-based electrochemical impedance spectroscopy nanobiosensors: An experimental approach. Biosens. Bioelectron 2021, 177 , 112672 10.1016/j.bios.2020.112672.33461849 Rashed M. Z. ; Kopechek J. A. ; Priddy M. C. ; Hamorsky K. T. ; Palmer K. E. ; Mittal N. ; Valdez J. ; Flynn J. ; Williams S. J. Rapid detection of SARS-CoV-2 antibodies using electrochemical impedance-based detector. Biosens. Bioelectron 2021, 171 , 112709 10.1016/j.bios.2020.112709.33075724 Soares J. C. ; Soares A. C. ; Angelim M. K. S. C. ; Proença-Modena J. L. ; Moraes-Vieira P. M. ; Mattoso L. H. C. ; Oliveira Jr O. N. Diagnostics of SARS-CoV-2 infection using electrical impedance spectroscopy with an immunosensor to detect the spike protein. Talanta 2022, 239 , 123076 10.1016/j.talanta.2021.123076.34876273 Hussein H. A. ; Kandeil A. ; Gomaa M. ; Mohamed El Nashar R. ; El-Sherbiny I. M. ; Hassan R. Y. A. SARS-CoV-2-impedimetric biosensor: virus-imprinted chips for early and rapid diagnosis. ACS Sens 2021, 6 (11 ), 4098–4107. 10.1021/acssensors.1c01614.34757734 Dubacheva G. V. ; Curk T. ; Auzély-Velty R. ; Frenkel D. ; Richter R. P. Designing multivalent probes for tunable superselective targeting. Proc. Natl. Acad. Sci. U.S.A 2015, 112 (18 ), 5579–5584. 10.1073/pnas.1500622112.25901321 Dubacheva G. V. ; Curk T. ; Mognetti B. M. ; Auzély-Velty R. ; Frenkel D. ; Richter R. P. Superselective targeting using multivalent polymers. J. Am. Chem. Soc. 2014, 136 (5 ), 1722–1725. 10.1021/ja411138s.24400591 Tito N. B. ; Frenkel D. Optimizing the selectivity of surface-adsorbing multivalent polymers. Macromolecules 2014, 47 (21 ), 7496–7509. 10.1021/ma5014918.25400296
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==== Front Int J Biol Macromol Int J Biol Macromol International Journal of Biological Macromolecules 0141-8130 1879-0003 Elsevier B.V. S0141-8130(22)02959-2 10.1016/j.ijbiomac.2022.12.057 Article Ginkgolic acids inhibit SARS-CoV-2 and its variants by blocking the spike protein/ACE2 interplay Xiang Yusen a1 Zhai Guanglei b1 Li Yaozong cd Wang Mengge a Chen Xixiang ae Wang Ruyu a Xie Hang f Zhang Weidong ag Ge Guangbo a Zhang Qian h Xu Yechun i Caflisch Amedeo c Xu Jianrong ej⁎ Chen Hongzhuan a⁎ Chen Lili a⁎ a Shanghai Frontiers Science Center of TCM Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China b Shanghai HighsLab Therapeutics. Inc., Shanghai 201203, China c Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland d Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden e Academy of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Shanghai 201203, China f School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China g Shanghai Institute of Infectious Diseases and Biosafety, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China h Department of Medicinal Chemistry, School of Pharmacy, Fudan University, Shanghai 201203, China i CAS Key Laboratory of Receptor Research, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China j Shanghai Universities Collaborative Innovation Center for Translational Medicine, Shanghai Jiao Tong University School of Medicine, 280 South Chongqing Road, Shanghai 200025, China ⁎ Corresponding authors. 1 These authors have contributed equally to this work. 12 12 2022 31 1 2023 12 12 2022 226 780792 27 9 2022 3 12 2022 6 12 2022 © 2022 Elsevier B.V. All rights reserved. 2022 Elsevier B.V. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Targeting the interaction between the spike protein receptor binding domain (S-RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and angiotensin-converting enzyme 2 (ACE2) is a potential therapeutic strategy for treating coronavirus disease 2019 (COVID-19). However, we still lack small-molecule drug candidates for this target due to the missing knowledge in the hot spots for the protein-protein interaction. Here, we used NanoBiT technology to identify three Ginkgolic acids from an in-house traditional Chinese medicine (TCM) library, and they interfere with the S-RBD/ACE2 interplay. Our pseudovirus assay showed that one of the compounds, Ginkgolic acid C17:1 (GA171), significantly inhibits the entry of original SARS-CoV-2 and its variants into the ACE2-overexpressed HEK293T cells. We investigated and proposed the binding sites of GA171 on S-RBD by combining molecular docking and molecular dynamics simulations. Site-directed mutagenesis and surface plasmon resonance revealed that GA171 specifically binds to the pocket near R403 and Y505, critical residues of S-RBD for S-RBD interacting with ACE2. Thus, we provide structural insights into developing new small-molecule inhibitors and vaccines against the proposed S-RBD binding site. Graphical abstract Unlabelled Image Keywords SARS-CoV-2 S-RBD Ginkgolic acid ==== Body pmc1 Introduction The coronavirus disease 2019 (COVID-19) is caused by a novel coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is spreading rapidly around the world. To date, >600 million confirmed cases of COVID-19, including >6 million deaths, have been reported to the World Health Organization (WHO) (https://covid19.who.int/table). Most patients present with multiorgan symptoms such as shortness of breath, palpitations, joint pain, and headache. In some discharged patients, the dysfunctions and complications may persist for at least six months [1]. Therefore, there is an urgent need to develop new drugs for specific and effective treatment beyond preventive vaccination. SARS-CoV-2, an enveloped single-stranded RNA β-coronavirus, mediates receptor binding and membrane fusion through its surface spike (S) protein [2]. Coronavirus S protein has a transmembrane structure and forms a trimer in its functional state. Proteases can cleave the protein's ectodomain into S1 and S2 subunits [2]. The receptor binding domain (RBD) in S1 subunit can bind to the host cell receptor and cause the conformational change of the S2 subunit, thereby mediating the fusion of the viral and cellular membrane [3]. Many studies have shown that SARS-CoV-2 enters host cells by targeting angiotensin-converting enzyme 2 (ACE2), a type I membrane protein widely expressed in humans, with a higher affinity than that for SARS-CoV binding to ACE2 [4], [5], [6], [7]. Therefore, the search for antiviral candidates that target S-RBD/ACE2 interactions has become an obvious priority. Traditional Chinese medicine (TCM) has shown great potential in preventing and treating COVID-19 as more and more active antiviral TCM ingredients are emerging [8], [9], [10], [11]. Lyu et al. summarized and discussed the clinical effects and potential mechanisms of TCM at different disease stages for the treatment of COVID-19, emphasizing the scientific value of TCM in combating COVID-19 [12]. Ginkgolic acid, the main component of Ginkgo biloba, has a variety of biological activities, such as antitumor [13], anti-inflammatory [14], antibacterial [15], and broad-spectrum antiviral effects [16], [17], [18]. A recent study found that Ginkgolic acid C15:1 (GA151) inhibited several enzymes that play crucial roles in viral polyprotein processing, e.g., 3-chymotrypsin-like protease (3CLpro) and papain-like protease (PLpro) [19]. The inhibition affects the SARS-CoV-2 infection and replication [19]. In addition, the inhibitory effect of GA151 on HIV protease protects human peripheral blood mononuclear cells from HIV infection [20]. Moreover, GA151 exhibited a broad-spectrum inhibitory effect on the viral fusion process of several enveloped viruses, such as Herpes Simplex Virus 1 (HSV-1), Human Cytomegalovirus (HCMV), and Zika Virus (ZIKV) [21]. Furthermore, GA151 can inhibit both the production of human coronavirus and the synthesis of viral N protein, which is conserved among the α, β, and γ genera of coronaviruses [18]. Therefore, further study on the antiviral mechanism of Ginkgolic acid is of great significance in exploring effective compounds against SARS-CoV-2. Computational methods play essential roles in understanding the pathogenesis of COVID-19 and discovering drug candidates against it. For example, molecular dynamics (MD) and free energy simulations were implemented to explore critical residues for the identification between SARS-CoV-2 S-RBD and the host ACE2 [22], [23]. Combined with X-ray crystallography, researchers used molecular simulations to understand how variants escape the host immune system, i.e., the omicron variant [24], [25]. Furthermore, during the COVID-19 pandemic, several research groups used in silico methods to propose small-molecules to treat the disease against multiple drug targets, i.e., the nonstructural proteins [26], [27], [28], 3CLpro [29], [30], [31], [32], and RNA-dependent RNA polymerase (RdRp) [33], [34]. Using small-molecules to target S-RBD is promising among potential therapeutic targets as it could block the ACE2/S-RBD interaction. S-RBD is unique for the coronavirus; thus, targeting it could reduce the possibility of suffering side effects. Recent studies have made efforts in this direction [35], [36]. Here, we screened our in-house TCM library by NanoBiT technique and discovered three Ginkgolic acid compounds that show the activity of blocking SARS-CoV-2 S-RBD/ACE2 interaction. Our experiments showed that one of the compounds Ginkgolic acid C17:1 (GA171) exhibited potent inhibitory activity against SARS-CoV-2-S pseudovirus with low cytotoxicity. We confirmed the binding sites of the compound by combining molecular simulations and multiple biological and biophysical experiments. One binding site locates in a particular place of S-RBD that blocks its interaction with ACE2. This study shows an example for the first time that a drug-like small-molecule can bind S-RBD and potentially block the viral invasion to the human cell via the binding to the protein ACE2. 2 Materials and methods 2.1 Cell culture and cell viability assays HEK293 and HEK293T cell lines were obtained from ATCC (Manassas, VA, USA). Normal human bronchial epithelial BEAS-2B cells were purchased from EK-Bioscience (Shanghai, China). African green monkey kidney epithelial Vero-E6 cells and HEK293F cells were obtained from the Cell Bank of the Type Culture Collection of the Chinese Academy of Sciences (Shanghai, China). Mouse aorta smooth muscle cells (MASMCs) were a kind gift from Professor Jiange Zhang from Shanghai University of Traditional Chinese Medicine, China. All adherent cells were routinely maintained in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10 % fetal bovine serum (FBS), 100 U/mL penicillin, and 100 μg/mL streptomycin in a humidified atmosphere containing 5 % CO2 at 37 °C. HEK293F cells were grown in OPM-293 CD05 medium (OPM Biosciences, Shanghai, China), cultured at 37 °C with 8 % CO2 and 125 rpm in an orbital shaking incubator. For cell toxicity assays, the cytotoxicity of the test compound to BEAS-2B, Vero-E6, and MASMCs was determined by Cell Counting Kit-8 (CCK-8, Meilunbio, Dalian, China). In brief, 50 μL cell suspensions were added to each well of 96-well plates. After 12 h of incubation, cells were pretreated with 10 μL 10× compounds at 37 °C for 1 h, and 40 μL medium was added to each well. After 24 h of incubation, the culture medium was refreshed, and the cells were incubated for another 24 h. Then the medium was replaced with CCK-8 solution according to the manufacturer's instructions. The OD value was measured at a wavelength of 450 nm (BioTek, Winooski, USA). 2.2 Pseudovirus production The recombinant plasmid expressing SARS-CoV-2 spike protein (pcDNA3.1-SARS-CoV-2-S) and plasmids including pAX2, pHB-Rluc, pcDNA3.1-ACE2 were obtained from Precedo (Anhui, China). The codon-optimized expression plasmid encoding full-length spike protein of Omicron SARS-CoV-2 was purchased from GenScript (Nanjing, China) and the plasmids expressing spike protein of Delta (Cat. No. #172320), and Gamma (Cat. No. #170450) of SARS-CoV-2 were from Addgene (Watertown, MA, USA). The SARS-CoV-2 pseudovirus was generated as previously described [37]. Briefly, HEK293T cells were co-transfected with three plasmids using the LipoFiter 3.0 transfection reagent (Hanbio, Shanghai, China) according to the manufacturer's instructions. After 6 h, the culture medium was replaced with fresh DMEM. After 48 h, the supernatant containing pseudovirus was collected by centrifuge (3000 g, 10 min) and filtered with 0.45 μm membrane (Jet Bio-Filtration, Guangzhou, China). Use the pseudovirus immediately or store at −80 °C in 1 mL aliquots until use. 2.3 Pseudovirus neutralization assays HEK293T cells were seeded in 96-well plates after transient transfection with pcDNA3.1-ACE2 plasmid by the LipoFilter 3.0 transfection reagent. For the neutralization assay, hACE2/HEK293T cells were pre-incubated with the test compounds at 37 °C for 1 h, then SARS-CoV-2 pseudovirus and Polybrene (6 μg/mL) (Absin, Shanghai, China) were added to each well and incubated for 24 h. Then, the culture medium was refreshed, and 30 μL Renilla luciferase Reagent (Promega, Madison, WI, USA) was added into each well after 48 h postinfection. The contents were mixed on an orbital shaker for 2 min to induce cell lysis, and the relative luciferase activity was detected using a Multilabel Reader (SpectraMax Paradigm, Molecular Devices, CA, USA). The Relative Luminescence (%) was calculated according to the procedures recommended by the manufacturer. The half-maximal inhibitory concentration (IC50) values were calculated by non-linear regression analysis using GraphPad Prism 8.0 (San Diego, CA, USA). 2.4 NanoBiT assay NanoBiT assays were performed as previously described [37]. Briefly, HEK293 cells were co-transfected using FuGENE HD transfection reagent (Promega, Madison, WI, USA) with SARS-CoV-2 S-RBD-LgBiT and SmBiT-ACE2 plasmids according to the manufacturer's instructions. Cells were incubated for 6 h at 37 °C with a transfection medium. Cells were then reseeded into a 96-well white plate with fresh medium for 16 h. Subsequently, the corresponding concentrations of compounds were incubated with the cells at 37 °C for 3 h. Finally, Nano-Glo Live Cell Assay reagent (Promega, Madison, WI, USA) was added to the cells, and luminescence was determined using the Envision plate reader (Perkin Elmer, Waltham, MA, USA). To exclude the interference of the compounds to the NanoBiT system per se, the cytotoxicity of the compounds was measured by CellTiter-Glo (CTG) Luminescent Cell Viability Assay (Promega, Madison, WI, USA), and the inhibitory effects of the compounds on NanoLuc (HEK293/NanoLuc stable cells) were also determined. The activities of the compounds were evaluated by NanoBiT inh% (SARS-CoV-2 S-RBD/ACE2 interaction), NanoLuc inh% (NanoLuc luciferase), and Cytotox inh% (cell proliferation). 2.5 Protein expression and purification The DNA fragment encoding S-RBD (residues 319–541) was subcloned into the mammalian expression vector pTT5 with a C-terminal 6 × His tag. The high-quality plasmids were transfected into HEK293F cells by PEI (Polysciences, Warrington, PA, USA). After five days of culture, the cell culture supernatant was harvested and purified by Ni-NTA. Purified proteins were analyzed by SDS-PAGE to ensure purity and appropriate molecular weights. 2.6 Binding site prediction of GA171 to S-RBD The SARS-CoV-2 S-RBD was selected as the binding target. The crystal structure 6M0J was chosen for the model building [38]. Before predicting how GA171 binds to the protein, all crystal water molecules were removed, and glycosylated residue Asn343 was turned to its unmodified form. To determine the appropriate states of the S-RBD residues, we analyzed the interaction between S-RBD and ACE2 by Maestro [39]. The states of S-RBD's interfacial residues that interact with ACE2 were determined by considering the protein-protein interactions. After checking the hydrogen binding networks of the complex structure, titratable residues were turned to their correct states, which was assisted by the pKa prediction from PROPKA3 [40]. The orientation of polar residues was also determined by the interaction analysis and flipping along their original planes, for example, histidine, asparagine, and glutamine. Finally, chain E of 6M0J, i.e., the S1 sub-domain of S-RBD ranging from T333 to G526, was extracted from the complex crystal structure of viral protein's S-RBD bound to ACE2. The chemical structure of GA171 was drawn by MarvinSketch [41], and its most populated protonation state in the aqueous solution was determined according to its predicted micro pKa values by the “Cxcalc” module of ChemAxon [41]. The 3D model of the ligand was generated by the “Molconvert” module of ChemAxon [41]. The hydroxyl and carboxyl groups on the benzene ring were protonated and deprotonated, respectively. The initial poses were sampled by the docking software Smina [42], a fork of Autodock Vina with improved flexibility [43]. The docking site was defined by a 100 × 100 × 100Å cubic grid box and centered on the S-RBD coordinates (x-axis: −32.38; y-axis: 25.84; y-axis: 21.45). This relatively large size of the grid box ensures embodying the entire structure during the docking simulations. The parameter “exhaustiveness” was set to 200 to enhance the configurational sampling of binding poses. The rest of the parameters were left as the default. Finally, all 200 docking poses were output for further analysis. The 200 docking poses mainly emerged on five different sites of the protein surface. For each potential binding site suggested by the docking simulations, we only considered the first two best-ranked poses for further MD simulations. In total, ten protein-ligand complex systems were constructed. Each of the S-RBD-GA171 modeled complex structures was solvated in an 88 Å rhombic dodecahedron TIP3P water box [44], which ensured a 12 Å buffer distance between protein atoms and water box boundary. 0.15 M of sodium chloride was added to the water box to neutralize the protein-ligand system and mimic the physiological condition. The CHARMM36m force field was used to describe the S-RBD protein, and GA171was parametrized by the CGenFF force field [45], [46]. Each complex system was initially minimized to 10,000 steps by mixing the conjugate gradient and adopted basis Newton Raphson algorithms under a series of restraints and constraints to remove its unreasonable contacts and geometry. The minimized structure was heated to 300 K and equilibrated in an NVT condition (constant volume and temperature). Finally, the structure was further equilibrated in an NPT condition (constant pressure and temperature). The heating-up and equilibration phases lasted for one ns using the CHARMM program (version 42b1) [47]. Production MD simulations were continued in NPT conditions. The pressure was controlled at 1 atm by the Nosé–Hoover Langevin piston method [48], [49]. The temperature was maintained at 300 K using the Nosé–Hoover thermostat [50]. The masses of temperature and pressure pistons were kept at 20 % and 2 % of the system mass, respectively. The integration time step was set to 2 fs by fixing all bonds connecting hydrogen atoms by the SHAKE algorithm [51]. Van der Waals energies were calculated using a switching function with a switching distance from 10 to 12 Å. Electrostatic interactions were evaluated using the particle mesh Ewald summation (PME) method with a 1 Å of grid spacing [52]. Each system was simulated for 5 ns, and three independent runs with the same initial coordinates and random velocities were carried out. Thus, a cumulative sampling of 15 ns trajectories (1500 snapshots saved every 10 ps) was collected from each system. Time-evolved root-mean-square deviation (RMSD) values and average structure were calculated based on the 1500 snapshots of each system. 2.7 Alanine scanning validation For single-point mutations on S-RBD, including R346A, R403A, T430A, Y505A, and Y505H, the corresponding residues were substituted by Ala or His. All mutant plasmids were constructed using the Mut Express II Fast Mutagenesis Kit V2 (Vazyme, Guangzhou, China) according to the manufacturer's instructions. After all mutant plasmids were sent to Sangon Biotech (Shanghai, China) for nucleic acid sequencing, the proteins were generated using HEK293F expression system and purified as described above. 2.8 Circular dichroism The circular dichroism (CD) spectra were used to explore the secondary structure of SARS-CoV-2 S-RBD and its mutants on BRIGHT TIME Chirasca (Applied Photophysics, Britain) spectropolarimeter. Proteins in phosphate-buffered saline (PBS) were recorded at 25 °C in a quartz cell of 0.5 mm path length. The concentration of proteins was 0.5 mg/mL, and the spectrum was recorded at wavelengths between 200 and 260 nm. The spectra represent an average of three corrected scans. The analysis of secondary structure content was performed using CDNN software (version 2.1). 2.9 Surface plasmon resonance assay Biacore T200 instruments (Cytiva) were used to evaluate the binding affinity of the compounds to human ACE2 (10108-H05H, Sino Biological, Beijing, China), SARS-CoV-2 S-RBD and the S-RBD mutants via surface plasmon resonance (SPR), as previously described [37]. Briefly, all the proteins were immobilized on the different channels of the CM5 chip by using an amine-coupling approach at a flow rate of 10 μL/min in 10 mM sodium acetate buffer (pH 4.0), respectively. The sensor surface was activated with a 7 min injection of the mixture of 50 mM N-hydroxysuccinimide (NHS) and 200 mM 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC). Then 10 μg/mL of human ACE2 and 50 μg/mL of S-RBD or mutants were injected for 420 s, and the surface was blocked with 1 M ethanolamine, pH 8.5. Series concentrations of the compounds were injected into the flow system and analyzed for 90 s, and the dissociation was 120 s. As for the binding affinity of S-RBD mutants to human ACE2, the association time was set to 120 s, while the dissociation time was set to 300 s. All binding analysis was performed in PBS with 0.05 % (v/v) Tween-20 and 1 % DMSO, pH 7.4, at 25 °C. Prior to analysis, double reference subtractions and solvent corrections were made to eliminate bulk refractive index changes, injection noise, and data drift. The binding affinity was determined by fitting a Langmuir 1:1 binding model within the Biacore Evaluation software (Cytiva). 2.10 Statistical analysis Data are presented as mean ± standard deviation (SD). Statistical differences were analyzed and determined based on P-values (* p < 0.05, ** p < 0.01, and *** p < 0.001). 3 Results 3.1 Ginkgolic acids exhibit inhibitory activity against SARS-CoV-2-S pseudovirus To screen effective inhibitors that block SARS-CoV-2 S-RBD/ACE2 interaction, we used the NanoBiT-based high-throughput system to screen 115 compounds at the concentration of 50 μM and Niclosamide (Nic) was used as a positive compound (Fig. S1) [53], [54]. After the selection, six candidate compounds were identified, which showed an inhibitory effect on S-RBD/ACE2 interaction (Fig. 1A). Among the six compounds, Ginkgolic acid C13:0 (GA) exhibited a strong blocking activity (Inhibition rate = 62 %). We therefore considered another three derivatives of GA, including Ginkgolic acid C15:0 (GA150), GA151, and GA171, for the following pseudovirus neutralization assay. We performed the assay to evaluate the ability of the nine compounds to block SARS-CoV-2-S pseudovirus infection in hACE2/HEK293T cells. The results showed that seven compounds including GA, GA151, GA150, GA171, Isoxanthohumol (IXN), Neobavaisoflavone (NBIF), and Licochalcone A (LicA), exhibited anti-pseudovirus activities at a 100 μM concentration. By contrast, Pectolinarigenin (PEC) and Hispidulin (HPD) had no significant antiviral activities at either 10 or 100 μM (Fig. 1B). We then investigated the cytotoxicities of these seven compounds to hACE2/HEK293T cells to exclude false positive results through CTG assay. The results showed that four compounds had strong cytotoxic effects on hACE2/HEK293T cells except for GA150, GA151, and GA171 (Fig. 1C). We further assessed the inhibitory activities of the three compounds against SARS-CoV-2-S pseudovirus and their cytotoxicities to hACE2/HEK293T cells. As shown in Fig. 1D-F, GA150, GA151, and GA171 exhibited a dose-dependent inhibition of SARS-CoV-2-S pseudovirus, resulting in IC50 values of 15.03, 31.13 and 79.43 μM, respectively. The half-maximal cytotoxic concentration (CC50) value of GA151 was over 200 μM, demonstrating its low cytotoxicity to hACE2/HEK293T cells. The CC50 values of GA171 and GA150 were 130.80 and over 66.67 μM, respectively. Notably, the selectivity index (SI, defines as [CC50]/[IC50]) of GA171 (SI = 8.70) is much higher than that of GA150 (SI > 2.14) and GA151 (SI > 2.52), suggesting that GA171 has more potential than GA150 and GA151.Fig. 1 Screening of the compounds and evaluation of anti-SARS-CoV-2-S pseudovirus activities and cytotoxicities. (A) Six compounds were screened as potent SARS-CoV-2 S-RBD/ACE2 interaction inhibitors. (B-C) Antiviral activities and cytotoxicities of Ginkgolic acid C13:0 (GA), Ginkgolic acid C15:1 (GA151), Ginkgolic acid C15:0 (GA150), Ginkgolic acid C17:1 (GA171), Isoxanthohumol (IXN), Pectolinarigenin (PEC), Hispidulin (HPD), Neobavaisoflavone (NBIF), Licochalcone A (LicA), and the positive compound Niclosamide (Nic) in preliminary screening. IC50 and CC50 values of (D) GA150, (E) GA151, and (F) GA171 were determined. Fig. 1 3.2 Ginkgolic acids interfere with the S-RBD/ACE2 interaction Based on the results from the pseudovirus assay, we further determined IC50 values of the three compounds with serially-diluted concentrations for SARS-CoV-2 S-RBD/ACE2 interaction (NanoBiT inh%), NanoLuc luciferase (NanoLuc inh%) and CC50 values for the cytotoxicity (Cytotox inh%) on HEK293 cells (Fig. 2A-C). GA171 exhibited the most potency for inhibiting S-RBD/ACE2 interaction (NanoBiT IC50 = 28.17 μM) despite sharing similar cytotoxicity with the other two inhibitors (Fig. 2C). Thus, GA171 deserves further investigation due to its distinguished properties on inhibitory effect on S-RBD/ACE2 interaction, the anti-SARS-CoV-2-S pseudovirus activity, and the maximum SI value.Fig. 2 NanoBiT-based validation of SARS-CoV-2 S-RBD/ACE2 interaction inhibitors. Effect of (A) GA150, (B) GA151, and (C) GA171 on NanoBiT-based SARS-CoV-2 S-RBD/ACE2 interaction. NanoBiT inh%: the inhibition rates against SARS-CoV-2 S-RBD/ACE2 interaction; NanoLuc inh%: the inhibition rates against NanoLuc luciferase; Cytotox inh%: the inhibition rates against the transfected HEK293 cells proliferation. (D) The chemical structure of GA150, GA151, and GA171. n = 3. Fig. 2 3.3 Determining the interactions between Ginkgolic acids and SARS-CoV-2 S-RBD or ACE2 by SPR assay To understand how the compounds block the S-RBD/ACE2 interaction, we utilized SPR assay to detect whether they could directly bind to S-RBD or ACE2. As shown in Fig. 3 , GA150, GA151, and GA171 can bind to SARS-CoV-2 S-RBD and ACE2. Although the compounds’ binding affinities are in the millimolar range, the well-shaped binding curves confirmed their association and dissociation processes. In addition, the compounds exhibited faster kinetics and higher affinities when binding to SARS-CoV-2 S-RBD than human ACE2.Fig. 3 Compounds bound to SARS-CoV-2 S-RBD or ACE2. Interactions of SARS-CoV-2 S-RBD or ACE2 with the compounds measured by SPR. The SARS-CoV-2 S-RBD or ACE2 was coated on the CM5 sensor chip, and serial dilutions of the compounds (1562.5, 3125, 6250, 12,500, 25,000, 50,000, and 100,000 nM) were used as analytes. Changes in plasmon resonance are shown as response units. Binding curves (colored lines) were obtained by passing different concentrations of GA150 (A), GA151 (C), and GA171 (E) over immobilized ACE2. Binding curves (colored lines) were obtained by passing different concentrations of GA150 (B), GA151 (D), and GA171 (F) over immobilized S-RBD. Fig. 3 3.4 Mapping binding sites of GA171 to S-RBD To detect the binding sites of Ginkgolic acids, we preferentially selected S-RBD and the compound GA171 as the target and ligand, respectively. We chose S-RBD as the drug target due to the following two factors. First, its druggability has been validated by widely used vaccines and antibodies. Second, S-RBD is a part of the virus protein; thus, targeting it will reduce the possibility of suffering unexpected side effects as targeting human proteins like ACE2. As S-RBD has multiple potential binding cavities on its protein surface, we decided to conduct an unbiased search for the candidate binding sites of GA171; namely, no prior knowledge was used to locate any plausible binding pockets. This so-called “blind” molecular docking simulation provided five potential binding sites of the compound (Fig. 4A and B) [55]. To validate the stability of these docking poses, we conducted multiple short MD simulations (see the method section for details). We evaluated the stability of these docking poses during MD simulations by checking their RMSD values to the corresponding docked poses (Fig. S2). Smaller average RMSD values and their deviation indicate more stable binding poses. The analysis showed that the ligand poses in sites 1, 3, and 5 (Fig. 4C, D, and E) are relatively stable, indicating their pronounced potential as the actual binding pockets (Fig. S2A). The MD-based RMSD analysis can efficiently filter out false positives than docking scores [56]. Indeed, the vina docking score cannot distinguish which binding sites GA171 prefers on both wild-type and mutant S-RBD (Fig. S3).Fig. 4 Potential binding pockets and poses of GA171 to S-RBD. (A-B) Binding poses predicted by molecular docking. For each binding pocket, the best and second best poses ranked by the vina scoring function are colored in light gray and green, respectively. Every pocket is indicated by an arrow with representative residues. The binding pockets and poses were predicted through the “blind” docking mode via Autodock Vina. (C-E) Optimized binding poses by MD simulations after docking. The ligand is shown in a gray ball-and-stick. Three binding sites suggested by MD simulations are shown here, i.e., sites 1, 3, and 5. The structural figures were prepared by PyMOL [57]. Fig. 4 In Fig. S2, we described the rules for proposing residues for further mutagenesis validation. We analyzed the MD-optimized binding modes and identified potential critical residues for the ligand-protein interactions, such as R346, T430, R403, and Y505. We constructed single-point alanine mutations for the four residues to confirm the critical residues for the GA171/S-RBD binding. The four mutant proteins were expressed and purified, and their secondary structures were checked by the Far-UV CD spectra (Fig. 5A and B). The spectra were used to ensure that the binding change of GA171 to mutants is not caused by the proteins' improper folding. Comparative analysis of the spectra between S-RBD's wild-type (WT) and mutants provided similar secondary structure contents. The result indicates that single-point alanine mutations at selected residues do not affect the secondary structures of S-RBD (Fig. 5B and C). We used SPR to measure the binding affinities of the four mutants to GA171. As a result, R403A and Y505A showed approximately 25- and 7-fold reduced binding affinity with GA171, respectively, compared to S-RBD WT (Fig. 5D). T430A underwent an about 6-fold weakened binding. By contrast, R346A did not experience a detectable change. These results indicate that sites 1 and 5 are likely the binding pockets of GA171, but site 3 is not (Fig. 4C-E).Fig. 5 Binding changes of GA171 to S-RBD mutants. (A) SDS-PAGE of S-RBD WT and mutants (protein purity >95 %). (B) CD spectra of 0.5 mg/mL S-RBD WT and mutants. (C) Secondary structure analysis determined by Far-UV CD spectroscopy. (D) Comparison of the KD values of GA171 among SARS-CoV-2 S-RBD WT and mutants. ⁎P < 0.05, ⁎⁎P < 0.01, ⁎⁎⁎P < 0.001 compared to KD value of GA171 binding to the SARS-CoV-2 S-RBD group. Fig. 5 Our model shows that, for site 1, GA171's carboxyl group interacts with R403 by a salt bridge; meanwhile, it also forms a hydrogen bond with Y453 (Fig. 4C). Moreover, Y505 interacts with the salicylic acid aromatic ring by an edge-to-face π-π interaction. In short, the salicylic acid ring is the compound's warhead for the specific recognition by site 1. By contrast, the aliphatic tail of the compound was highly dynamic during the MD simulation and did not show specific interactions with site 1. In site 5 (Fig. 4E), GA171's salicylic acid warhead is recognized explicitly by T430 and S514 via two hydrogen bonds and the aliphatic tail coils in the surface pocket. Because the R403A mutant shows the most significant reduction for the ligand binding, site 1 is probably the primary binding site, and site 5 might be a side pocket. 3.5 GA171 blocks S-RBD/ACE2 interaction by interrupting their interface The structural analysis shows that some residues of S-RBD may play an essential role in specifically recognizing ACE2, e.g., Y505, Y449, and T500, because they directly contribute to the interaction between the two proteins [38]. For example, S-RBD's Y505 forms two hydrogen bonds with ACE2's E37 and R393 (Fig. 6A). Meanwhile, it also interacts with the hydrophobic part of ACE2's K353. Interestingly, this site is also predicted to be the GA171's binding site on S-RBD (site 1 in Fig. 4). After superposing the predicted binding pose of the ligand to the heterodimer interface, we find that GA171 interrupts the S-RBD/ACE2 interaction (Fig. 6A). The salicylic acid ring specifically recognizes the S-RBD interfacial site by polar interactions. At the same time, the dynamic aliphatic tail disables the accessibility of ACE2 to S-RBD. This binding mode rationalizes why Ginkgolic acid compounds interfere with the interaction between S-RBD and ACE2 (Fig. 2). Interestingly, the model also suggests the possibility that GA171 blocks the binding of the Omicron S-RBD to ACE2 (Fig. 6B).Fig. 6 GA171 interrupts the S-RBD/ACE2 interface. (A-B) Interfacial interactions of ACE2 with S-RBD WT (A) and Y505H mutant (B). The MD-optimized binding pose of GA171 against S-RBD WT (shown in white gray ball-and-stick) is superposed onto the two heterodimer interfaces. The heterodimers of the S-RBD WT and Y505H mutant (Omicron variant S-RBD) are made by crystal structures 6M0J and 7WPB, respectively. For consistency, the sequence numberings of S-RBD of WT and Omicron are kept the same in the figs. (C-F) SPR binding curves (colored lines) were obtained by passing different concentrations of SARS-CoV-2 S-RBD WT and mutants over immobilized ACE2. Fig. 6 The interaction analysis encouraged us to measure the binding affinities of the multiple single-point mutants studied in the last section to ACE2, i.e., R346, T430, R403, and Y505 (Fig. 6C-F, Fig. S4). As a result, the Y505A mutation abolished S-RBD's binding affinity with ACE2, and other alanine mutants weakened the protein's binding strength by ranging about one to three folds. A similar result was also observed in a recent report [58]. The current SARS-CoV-2 variant Omicron has accumulated extensive mutations on S-RBD, evading most existing neutralizing antibodies [59]. Therefore, we mutated Y505 to histidine to mimic the Omicron's S-RBD and determined Y505H's binding affinity with ACE2 by SPR. Consistent with previous studies [60], [61], the mutated S-RBD shows an approximately two-fold reduction in binding to ACE2 compared to S-RBD WT (Fig. 6F). Our data confirmed the key residues, including R403 and Y505, for the binding of S-RBD to ACE2 and GA171. More importantly, our results pinpoint the hot spots for the small-molecule targeting by blocking the interplay between S-RBD and ACE2, thus proposing a new strategy to treat COVID-19. 3.6 GA171 inhibits the entry of pseudo-typed SARS-CoV-2 variants into cells We constructed multiple variant pseudoviruses using the same lentiviral system as SARS-CoV-2-S to determine the capacity of GA171 on antiviral effects against the variants of concern (VOCs), including SARS-CoV-2 Delta, Gamma, and Omicron. We then evaluated the in vitro antiviral efficacy of GA171 against these variants (Fig. 7A). The results indicated that GA171 exhibited similar antiviral activity against these pseudo-typed SARS-CoV-2 strains entering hACE2/HEK293T cells (IC50 = 28.25–32.54 μM), including the currently circulating Omicron strains (Fig. 7B and C). Importantly, our data showed that GA171 did not produce significant cytotoxicity to hACE2/HEK293T cells or several typical cell types, including BEAS-2B, Vero-E6, and MASMCs at effective antiviral concentrations (Fig. S5). As described above, GA171 has shown potent antiviral activity against SARS-CoV-2 variants and exhibited no safety concerns in normal cells in vitro, emphasizing its potential as a therapeutic agent for the treatment of COVID-19.Fig. 7 Antiviral activity of GA171 against pseudo-typed Delta, Omicron, and Gamma SARS-CoV-2. (A) Comparison of residue changes of S protein in Gamma (orange), Delta (green), and Omicron (blue) variants. (B) GA171 blocked infections of hACE2/HEK293T cells by different pseudo-typed coronaviruses. (C) The IC50 values of GA171 in inhibiting pseudo-typed coronaviruses. Fig. 7 4 Discussion Ginkgolic acid is a mixture of several 2-hydroxy-6-alkylbenzoic acids, which can be designated as GA, GA150, GA151, and GA171 according to the number of carbon atoms contained in the alkyl chain and the position of the unsaturated bond. Ginkgolic acid is the alkylphenol component of Ginkgo biloba extract, which has the potential therapeutic effect, including anti-tumor, anti-inflammatory, and antiviral activities [17]. Previous studies indicated that GA151 has broad-spectrum inhibitory effects on several enveloped viruses by inhibiting viral fusion and protein synthesis [21]. The study by Xiong et al. showed that GA, GA150, GA151, and GA171 have inhibitory effects on SARS-CoV-2 3CLpro. At the same time, GA171 and GA150 strongly inhibited SARS-CoV-2 3CLpro in a mixed-inhibition manner, implying that they are mixed-type inhibitors against SARS-CoV-2 3CLpro [62]. In addition, GA151 and GA150 were reported to be dual inhibitors against SARS-CoV-2 3CLpro and PLpro, showing the ability to inhibit the replication of SARS-CoV-2 in vitro [19]. More importantly, GA151 acts as an irreversible inhibitor of PLpro and 3CLpro, indicating that it is a covalent inhibitor [19]. Moreover, Ginkgolic acid exhibited antiviral activity against acyclovir-resistant herpes simplex virus type 1 through virucidal activity and fusion inhibition and significantly reduced the mortality of infected BABL/cJ mice [17]. Notably, Ginkgolic acid disrupts the early stage of the Alphavirus replication cycle and inhibits the expression of viral proteins structural E1 and non-structural nsP1, showing antiviral activity against the arboviruses [16]. In addition, it has been suggested that Ginkgolic acids effectively inhibit the release of inflammatory mediators and pro-inflammatory cytokines in ox-LDL-induced HUVECs, HMEC-1, and hPBMCs cells by blocking the activation of the NF-κB pathway [14], [63]. Because Ginkgolic acids could inhibit SARS-CoV-2 by targeting multiple enzymes and proteins, we tried the same “blind” docking procedure on other four proteins, i.e., SARS-CoV-2 RdRp, 3CLpro, PLpro, and human ACE2. However, the best docking scores of GA171 with proteins ranged from −5.0 to −6.4, and thus cannot tell which proteins the compound prefers to bind to and which is the actual binding site for a specific protein (Fig. S6). Therefore, we conducted biological experiments to evaluate the effects of GA171 on the above four proteins. As shown in Fig. S7, GA171 exhibited dose-dependent inhibition of SARS-CoV 3CLpro and PLpro with IC50 values of 3.80 and 17.85 μM, respectively. This suggests that GA171 exerts antiviral effects by dual targeting S-RBD/ACE2 interaction and key enzymes of viral replication. Importantly, GA171 has no effect on the catalytic activity of human ACE2, indicating the specificity and safety of GA171 for blocking S-RBD/ACE2 interaction. However, during optimizing GA171 against S-RBD, protein binding and cell inhibition of its derivatives should be further monitored for other potential targets. That would indicate whether multiple targeting helps the efficacy. We reported for the first time that GA171 has antiviral activity against pseudo-typed SARS-CoV-2 and variants with different mutations in S protein by interfering with SARS-CoV-2 S-RBD and ACE2 interaction, implying that GA171 is a good starting point for developing small-molecule drugs against COVID-19. In addition, the potential binding sites of GA171 to S-RBD were identified by combining molecular simulations and binding experiments. GA171 lost a 25-fold binding affinity with the R403A mutated S-RBD, confirming the hot spot for the GA171 and S-RBD recognition (Fig. 5D). R403 is also crucial for S-RBD to recognize the host ACE2 by a salt bridge with ACE2's E37. The salt-bridge interaction was essential to stabilize the ACE2/S-RBD protein-protein interface, which was suggested by computational alanine scanning and structural analysis [64]. Meanwhile, our SPR experiment results showed that single-mutation Y505A abolished the binding of ACE2 (Fig. 6E), which is consistent with the results of Xu et al., who highlighted the role of residue Y505 as a decisive factor in the specific recognition of S-RBD by ACE2 [58]. Structure-based interaction energy evaluation will help us understand the interaction between S-RBD and ACE2, providing insights into the design of neutralizing antibodies or structure-based vaccine design [64]. Watanabe et al. analyzed the interactions between 12 antibodies/peptides and SARS-CoV-2 S-RBD by the fragment molecular orbital method [65]. They found that the residue Y505 on the S-RBD can interact with the residues on the antibody BD-629 Fab through XH/π interactions, providing helpful information for the design of effective neutralizing antibodies [65]. Interestingly, both sites R403 and Y505 are located in binding site 1 proposed by our simulations (Fig. 4C). Residue Y505 on S-RBD is located at the binding interface of ACE2/S-RBD and participates in forming protein-protein hydrogen bonds [64]. More importantly, Y505 and R403 directly interact with GA171, thus providing the atomic mechanism of how GA171 blocks the ACE2/S-RBD interaction. Recently, several groups also used in silico methods to locate multiple potential small-molecule inhibitors on the S-RBD surface that directly interacts with ACE2 [35], [36], [66]. Further optimization on GA171 may use all these chemical features to generate more potent inhibitors and improve their efficacy against SARS-CoV-2. On this basis, pseudo-typed Delta, Omicron, and Gamma SARS-CoV-2 were constructed to evaluate the antiviral activity of GA171 against SARS-CoV-2 VOCs. The results showed that GA171 treatment entirely abolished the infectivity of Delta, Omicron, and Gamma pseudoviruses with similar IC50 values at 28.25, 32.54, and 29.25 μM, respectively. However, the toxicity of Ginkgolic acid limits the clinical use of Ginkgo biloba [67]. Liu et al. found that Ginkgolic acid is cytotoxic to HepG2 cells and primary rat hepatocytes, and cytochrome P450-mediated reactions enable GA151 metabolism to produce more cytotoxic compounds [68]. Furthermore, Berg et al. investigated the cytotoxicity and mutagenicity of GA, GA151, and GA171 [69]. The results showed that none of the three compounds had the mutagenic issue in vitro but caused cytotoxicity in V79 cells, with GA171 having the lowest toxicity (IC50 = 94 μM) [69]. Nonetheless, our results showed that GA171 did not exhibit apparent cytotoxicity in the normal cells, such as BEAS-2B (CC50 > 100 μM) and MASMCs (CC50 > 100 μM), which are representative of human and mouse lower airway cells (Fig. S5). In addition, Vero-E6 (CC50 > 200 μM) cells were also used to assess the cytotoxicity of GA171 as it is a standard cell line used in live SARS-CoV-2 infection experiments (Fig. S5). Our results highlighted again the importance of blocking the S-RBD/ACE2 interaction, and would facilitate future research on the treatment of COVID-19. 5 Conclusions GA171 is a good starting point for further development to inhibit SARS-CoV-2 and its variants, including Delta, Gamma, and Omicron. We have revealed the antiviral mechanism of GA171 and developed atomic models for continuous optimization. Our results provide a new platform to develop new protein-protein inhibitors by targeting the pocket near R403 and Y505 of S-RBD. Further optimization of GA171 could improve its potency and enhance its antiviral activity, leading to more effective chemical entities against many epidemic variants. CRediT authorship contribution statement Lili Chen, Hongzhuan Chen, Jianrong Xu conceived and designed the experiments. Yusen Xiang, Guanglei Zhai, Mengge Wang, Xixiang Chen, Ruyu Wang, and Hang Xie carried out the experiments and data analysis. Yaozong Li and Amedeo Caflisch designed and carried out all the molecular simulations. Yusen Xiang, Guanglei Zhai, and Yaozong Li wrote the manuscript. Lili Chen, Jianrong Xu, Qian Zhang, Hongzhuan Chen, Guangbo Ge, Weidong Zhang, Yechun Xu and Amedeo Caflisch critically revised the manuscript. Declaration of competing interest The authors declare no competing interests. Appendix A Supplementary data Supplementary material Image 1 Data availability Data will be made available on request. Acknowledgments This work was supported by 10.13039/501100001809 National Natural Science Foundation of China (82141203), Shanghai Municipal Science and Technology Major Project (ZD2021CY001, China), Shanghai Municipal Health Commission (ZY(2021-2023)-0103, China), the International Postdoc Grant funded by the 10.13039/501100004359 Swedish Research Council (Grant VR 2019-00608 to Y.L., Sweden), and an Excellence grant of the 10.13039/501100001711 Swiss National Science Foundation (310030B_189363 to A.C., Switzerland). We thank the Swedish National Infrastructure for Computing (SNIC) at the High-Performance Computing Center North (HPC2N) for providing the computational resources. We thank Dr. Huaqiang Xu for providing the SARS-CoV-2 RdRp protein. Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.ijbiomac.2022.12.057. ==== Refs References 1 The L. Facing up to long COVID Lancet 396 10266 2020 1861 33308453 2 Fehr A.R. Perlman S. Coronaviruses: an overview of their replication and pathogenesis Maier H.J. Bickerton E. Britton P. Coronaviruses: Methods and Protocols 2015 Springer New York New York, NY 1 23 3 Xiang Y. Wang M. Chen H. Chen L. Potential therapeutic approaches for the early entry of SARS-CoV-2 by interrupting the interaction between the spike protein on SARS-CoV-2 and angiotensin-converting enzyme 2 (ACE2) Biochem. Pharmacol. 192 2021 114724 4 Yan R. Zhang Y. Li Y. Xia L. Guo Y. Zhou Q. Structural basis for the recognition of SARS-CoV-2 by full-length human ACE2 Science 367 6485 2020 1444 1448 32132184 5 Wrapp D. Wang N. Corbett Kizzmekia S. Goldsmith Jory A. Hsieh C.-L. Abiona O. Graham Barney S. McLellan Jason S. Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation Science 367 6483 2020 1260 1263 32075877 6 Zhou P. Yang X.-L. Wang X.-G. Hu B. Zhang L. Zhang W. Si H.-R. Zhu Y. Li B. Huang C.-L. Chen H.-D. Chen J. Luo Y. Guo H. Jiang R.-D. Liu M.-Q. Chen Y. Shen X.-R. Wang X. Zheng X.-S. Zhao K. Chen Q.-J. Deng F. Liu L.-L. Yan B. Zhan F.-X. Wang Y.-Y. Xiao G.-F. Shi Z.-L. A pneumonia outbreak associated with a new coronavirus of probable bat origin Nature 579 7798 2020 270 273 32015507 7 Walls A.C. Park Y.J. Tortorici M.A. Wall A. McGuire A.T. Veesler D. Structure, function, and antigenicity of the SARS-CoV-2 spike glycoprotein Cell 181 2 2020 281 292.e6 32155444 8 Yu S. Chen Y. Xiang Y. Lin H. Wang M. Ye W. Zhang P. Chen H. Lin G. Zhu Y. Chen L. Zhang J. Pseudoephedrine and its derivatives antagonize wild and mutated severe acute respiratory syndrome-CoV-2 viruses through blocking virus invasion and antiinflammatory effect Phytother. Res. 35 10 2021 5847 5860 34472141 9 Yang C. Pan X. Xu X. Cheng C. Huang Y. Li L. Jiang S. Xu W. Xiao G. Liu S. Salvianolic acid C potently inhibits SARS-CoV-2 infection by blocking the formation of six-helix bundle core of spike protein Signal Transduct.Target.Ther. 5 1 2020 220 33024075 10 Wang W. Li S.-S. Xu X.-F. Yang C. Niu X.-G. Yin S.-X. Pan X.-Y. Xu W. Hu G.-D. Wang C. Liu S.-W. Danshensu alleviates pseudo-typed SARS-CoV-2 induced mouse acute lung inflammation Acta Pharmacol. Sin. 43 4 2022 771 780 34267343 11 Yu S. Zhu Y. Xu J. Yao G. Zhang P. Wang M. Zhao Y. Lin G. Chen H. Chen L. Zhang J. Glycyrrhizic acid exerts inhibitory activity against the spike protein of SARS-CoV-2 Phytomedicine 85 2021 153364 12 Lyu M. Fan G. Xiao G. Wang T. Xu D. Gao J. Ge S. Li Q. Ma Y. Zhang H. Wang J. Cui Y. Zhang J. Zhu Y. Zhang B. Traditional Chinese medicine in COVID-19 Acta Pharm. Sin. B 11 11 2021 3337 3363 34567957 13 Liang J.-R. Yang H. Ginkgolic acid (GA) suppresses gastric cancer growth by inducing apoptosis and suppressing STAT3/JAK2 signaling regulated by ROS Biomed. Pharmacother. 125 2020 109585 14 Li J. Li A. Li M. Liu Y. Zhao W. Gao D. Ginkgolic acid exerts an anti-inflammatory effect in human umbilical vein endothelial cells induced by ox-LDL Pharmazie 73 7 2018 408 412 30001776 15 Lee J.-H. Kim Y.-G. Ryu S.Y. Cho M.H. Lee J. Ginkgolic acids and Ginkgo biloba extract inhibit Escherichia coli O157:H7 and Staphylococcus aureus biofilm formation Int. J. Food Microbiol. 174 2014 47 55 24457153 16 Campos D. Navarro S. Llamas-González Y.Y. Sugasti M. González-Santamaría J. Broad antiviral activity of ginkgolic acid against Chikungunya, Mayaro, Una, and Zika viruses Viruses 12 4 2020 449 32326564 17 Bhutta M.S. Shechter O. Gallo E.S. Martin S.D. Jones E. Doncel G.F. Borenstein R. Ginkgolic acid inhibits herpes simplex virus type 1 skin infection and prevents zosteriform spread in mice Viruses 13 1 2021 86 33435520 18 Bhutta M.S. Sausen D.G. Gallo E.S. Dahari H. Doncel G.F. Borenstein R. Ginkgolic acid inhibits coronavirus strain 229E infection of human epithelial lung cells Pharmaceuticals 14 10 2021 980 34681204 19 Chen Z. Cui Q. Cooper L. Zhang P. Lee H. Chen Z. Wang Y. Liu X. Rong L. Du R. Ginkgolic acid and anacardic acid are specific covalent inhibitors of SARS-CoV-2 cysteine proteases Cell Biosci. 11 1 2021 45 33640032 20 Lü J.-M. Yan S. Jamaluddin S. Weakley S.M. Liang Z. Siwak E.B. Yao Q. Chen C. Ginkgolic acid inhibits HIV protease activity and HIV infection in vitro Med. Sci. Monit. 18 8 2012 BR293 BR298 22847190 21 Borenstein R. Hanson B.A. Markosyan R.M. Gallo E.S. Narasipura S.D. Bhutta M. Shechter O. Lurain N.S. Cohen F.S. Al-Harthi L. Nicholson D.A. Ginkgolic acid inhibits fusion of enveloped viruses Sci. Rep. 10 1 2020 4746 32179788 22 Wang Y. Liu M. Gao J. Enhanced receptor binding of SARS-CoV-2 through networks of hydrogen-bonding and hydrophobic interactions Proc. Natl. Acad. Sci. 117 25 2020 13967 13974 32503918 23 Lan J. He X. Ren Y. Wang Z. Zhou H. Fan S. Zhu C. Liu D. Shao B. Liu T.-Y. Wang Q. Zhang L. Ge J. Wang T. Wang X. Structural insights into the SARS-CoV-2 omicron RBD-ACE2 interaction Cell Res. 32 6 2022 593 595 35418218 24 Jawad B. Adhikari P. Podgornik R. Ching W.-Y. Binding interactions between receptor-binding domain of spike protein and human angiotensin converting enzyme-2 in omicron variant J.Phys.Chem.Lett. 13 17 2022 3915 3921 35481766 25 Wu L. Zhou L. Mo M. Liu T. Wu C. Gong C. Lu K. Gong L. Zhu W. Xu Z. SARS-CoV-2 omicron RBD shows weaker binding affinity than the currently dominant Delta variant to human ACE2 Signal Transduct.Target.Ther. 7 1 2022 8 34987150 26 Singh R. Bhardwaj V.K. Sharma J. Purohit R. Kumar S. In-silico evaluation of bioactive compounds from tea as potential SARS-CoV-2 nonstructural protein 16 inhibitors J. Tradit. Complement. Med. 12 1 2022 35 43 34099976 27 Sharma J. Kumar Bhardwaj V. Singh R. Rajendran V. Purohit R. Kumar S. An in-silico evaluation of different bioactive molecules of tea for their inhibition potency against non structural protein-15 of SARS-CoV-2 Food Chem. 346 2021 128933 28 Singh R. Bhardwaj V.K. Das P. Purohit R. A computational approach for rational discovery of inhibitors for non-structural protein 1 of SARS-CoV-2 Comput. Biol. Med. 135 2021 104555 29 Bhardwaj V.K. Singh R. Sharma J. Rajendran V. Purohit R. Kumar S. Identification of bioactive molecules from tea plant as SARS-CoV-2 main protease inhibitors J. Biomol. Struct. Dyn. 39 10 2021 3449 3458 32397940 30 Bhardwaj V.K. Singh R. Das P. Purohit R. Evaluation of acridinedione analogs as potential SARS-CoV-2 main protease inhibitors and their comparison with repurposed anti-viral drugs Comput. Biol. Med. 128 2021 104117 31 Singh R. Bhardwaj V.K. Das P. Bhattacherjee D. Zyryanov G.V. Purohit R. Benchmarking the ability of novel compounds to inhibit SARS-CoV-2 main protease using steered molecular dynamics simulations Comput. Biol. Med. 146 2022 105572 32 Chauhan M. Bhardwaj V.K. Kumar A. Kumar V. Kumar P. Enayathullah M.G. Thomas J. George J. Kumar B.K. Purohit R. Kumar A. Kumar S. Theaflavin 3-gallate inhibits the main protease (Mpro) of SARS-CoV-2 and reduces its count in vitro Sci. Rep. 12 1 2022 13146 35908093 33 Singh R. Bhardwaj V.K. Purohit R. Potential of turmeric-derived compounds against RNA-dependent RNA polymerase of SARS-CoV-2: an in-silico approach Comput. Biol. Med. 139 2021 104965 34 Bhardwaj V.K. Singh R. Sharma J. Rajendran V. Purohit R. Kumar S. Bioactive molecules of tea as potential inhibitors for RNA-dependent RNA polymerase of SARS-CoV-2 Front.Med. 8 2021 684020 35 Singh R. Bhardwaj V.K. Sharma J. Kumar D. Purohit R. Identification of potential plant bioactive as SARS-CoV-2 spike protein and human ACE2 fusion inhibitors Comput. Biol. Med. 136 2021 104631 36 Guimond S.E. Mycroft-West C.J. Gandhi N.S. Tree J.A. Le T.T. Spalluto C.M. Humbert M.V. Buttigieg K.R. Coombes N. Elmore M.J. Wand M. Nyström K. Said J. Setoh Y.X. Amarilla A.A. Modhiran N. Sng J.D.J. Chhabra M. Young P.R. Rawle D.J. Lima M.A. Yates E.A. Karlsson R. Miller R.L. Chen Y.-H. Bagdonaite I. Yang Z. Stewart J. Nguyen D. Laidlaw S. Hammond E. Dredge K. Wilkinson T.M.A. Watterson D. Khromykh A.A. Suhrbier A. Carroll M.W. Trybala E. Bergström T. Ferro V. Skidmore M.A. Turnbull J.E. Synthetic heparan sulfate mimetic pixatimod (PG545) potently inhibits SARS-CoV-2 by disrupting the spike–ACE2 interaction ACS Cent.Sci. 8 5 2022 527 545 35647275 37 Xiong J. Xiang Y. Huang Z. Liu X. Wang M. Ge G. Chen H. Xu J. Zheng M. Chen L. Structure-based virtual screening and identification of potential inhibitors of SARS-CoV-2 S-RBD and ACE2 interaction Front. Chem. 9 2021 740702 38 Lan J. Ge J. Yu J. Shan S. Zhou H. Fan S. Zhang Q. Shi X. Wang Q. Zhang L. Wang X. Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor Nature 581 7807 2020 215 220 32225176 39 Maestro 2020 Schrödinger, LLC New York, NY 40 Olsson M.H.M. Søndergaard C.R. Rostkowski M. Jensen J.H. PROPKA3: consistent treatment of internal and surface residues in empirical pKa predictions J. Chem. Theory Comput. 7 2 2011 525 537 26596171 41 ChemAxon MarvinSketch 21.20.0 http://www.chemaxon.com 2013 42 Koes D.R. Baumgartner M.P. Camacho C.J. Lessons learned in empirical scoring with smina from the CSAR 2011 benchmarking exercise J. Chem. Inf. Model. 53 8 2013 1893 1904 23379370 43 Trott O. Olson A.J. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading J. Comput. Chem. 31 2 2010 455 461 19499576 44 Jorgensen W.L. Chandrasekhar J. Madura J.D. Impey R.W. Klein M.L. Comparison of simple potential functions for simulating liquid water J. Chem. Phys. 79 2 1983 926 935 45 Vanommeslaeghe K. Hatcher E. Acharya C. Kundu S. Zhong S. Shim J. Darian E. Guvench O. Lopes P. Vorobyov I. MacKerell A.D. CHARMM general force field: a force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields J. Comput. Chem. 31 4 2010 671 690 19575467 46 Huang J. MacKerell A.D. Jr. CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data J. Comput. Chem. 34 25 2013 2135 2145 23832629 47 Brooks B.R. Brooks C.L. Mackerell A.D. Nilsson L. Petrella R.J. Roux B. Won Y. Archontis G. Bartels C. Boresch S. Caflisch A. Caves L. Cui Q. Dinner A.R. Feig M. Fischer S. Gao J. Hodoscek M. Im W. Kuczera K. Lazaridis T. Ma J. Ovchinnikov V. Paci E. Pastor R.W. Post C.B. Pu J.Z. Schaefer M. Tidor B. Venable R.M. Woodcock H.L. Wu X. Yang W. York D.M. Karplus M. CHARMM: the biomolecular simulation program J. Comput. Chem. 30 10 2009 1545 1614 19444816 48 Martyna G.J. Tobias D.J. Klein M.L. Constant-pressure molecular-dynamics algorithms J. Chem. Phys. 101 5 1994 4177 4189 49 Feller S.E. Zhang Y.H. Pastor R.W. Brooks B.R. Constant-pressure molecular-dynamics simulation - the Langevin Piston method J. Chem. Phys. 103 11 1995 4613 4621 50 Hoover W.G. Canonical dynamics: equilibrium phase-space distributions Phys. Rev. A 31 3 1985 1695 1697 51 Ryckaert J.-P. Ciccotti G. Berendsen H.J.C. Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes J. Comput. Phys. 23 3 1977 327 341 52 Essmann U. Perera L. Berkowitz M.L. Darden T. Lee H. Pedersen L.G. A smooth particle Mesh ewald method J. Chem. Phys. 103 19 1995 8577 8593 53 Jeon S. Ko M. Lee J. Choi I. Byun Soo Y. Park S. Shum D. Kim S. Identification of antiviral drug candidates against SARS-CoV-2 from FDA-approved drugs Antimicrob. Agents Chemother. 64 7 2020 e00819 e00820 32366720 54 Braga L. Ali H. Secco I. Chiavacci E. Neves G. Goldhill D. Penn R. Jimenez-Guardeño J.M. Ortega-Prieto A.M. Bussani R. Cannatà A. Rizzari G. Collesi C. Schneider E. Arosio D. Shah A.M. Barclay W.S. Malim M.H. Burrone J. Giacca M. Drugs that inhibit TMEM16 proteins block SARS-CoV-2 spike-induced syncytia Nature 594 7861 2021 88 93 33827113 55 Hetényi C. van der Spoel D. Blind docking of drug-sized compounds to proteins with up to a thousand residues FEBS Lett. 580 5 2006 1447 1450 16460734 56 Guterres H. Im W. Improving protein-ligand docking results with high-throughput molecular dynamics simulations J. Chem. Inf. Model. 60 4 2020 2189 2198 32227880 57 The PyMOL Molecular Graphics System Version 2.2 2018 Schrödinger, LLC New York, NY 58 Xu C. Wang Y. Liu C. Zhang C. Han W. Hong X. Wang Y. Hong Q. Wang S. Zhao Q. Wang Y. Yang Y. Chen K. Zheng W. Kong L. Wang F. Zuo Q. Huang Z. Cong Y. Conformational dynamics of SARS-CoV-2 trimeric spike glycoprotein in complex with receptor ACE2 revealed by cryo-EM Sci. Adv. 7 1 2021 eabe5575 59 Cao Y. Wang J. Jian F. Xiao T. Song W. Yisimayi A. Huang W. Li Q. Wang P. An R. Wang J. Wang Y. Niu X. Yang S. Liang H. Sun H. Li T. Yu Y. Cui Q. Liu S. Yang X. Du S. Zhang Z. Hao X. Shao F. Jin R. Wang X. Xiao J. Wang Y. Xie X.S. Omicron escapes the majority of existing SARS-CoV-2 neutralizing antibodies Nature 602 7898 2022 657 663 35016194 60 Starr T.N. Greaney A.J. Hilton S.K. Ellis D. Crawford K.H.D. Dingens A.S. Navarro M.J. Bowen J.E. Tortorici M.A. Walls A.C. King N.P. Veesler D. Bloom J.D. Deep mutational scanning of SARS-CoV-2 receptor binding domain reveals constraints on folding and ACE2 binding Cell 182 5 2020 1295 1310.e20 32841599 61 Zhang S. Qiao S. Yu J. Zeng J. Shan S. Tian L. Lan J. Zhang L. Wang X. Bat and pangolin coronavirus spike glycoprotein structures provide insights into SARS-CoV-2 evolution Nat. Commun. 12 1 2021 1607 33707453 62 Xiong Y. Zhu G.-H. Wang H.-N. Hu Q. Chen L.-L. Guan X.-Q. Li H.-L. Chen H.-Z. Tang H. Ge G.-B. Discovery of naturally occurring inhibitors against SARS-CoV-2 3CLpro from Ginkgo biloba leaves via large-scale screening Fitoterapia 152 2021 104909 63 Zhang J. Yan J. Protective effect of ginkgolic acid in attenuating LDL induced inflammation human peripheral blood mononuclear cells via altering the NF-κB signaling pathway Front. Pharmacol. 10 2019 01241 64 Laurini E. Marson D. Aulic S. Fermeglia M. Pricl S. Computational alanine scanning and structural analysis of the SARS-CoV-2 spike protein/angiotensin-converting enzyme 2 complex ACS Nano 14 9 2020 11821 11830 32833435 65 Watanabe K. Watanabe C. Honma T. Tian Y.-S. Kawashima Y. Kawashita N. Takagi T. Fukuzawa K. Intermolecular interaction analyses on SARS-CoV-2 spike protein receptor binding domain and human angiotensin-converting enzyme 2 receptor-blocking antibody/peptide using fragment molecular orbital calculation J.Phys.Chem.Lett. 12 16 2021 4059 4066 33881894 66 Eskandari V. Repurposing the natural compounds as potential therapeutic agents for COVID-19 based on the molecular docking study of the main protease and the receptor-binding domain of spike protein J. Mol. Model. 28 6 2022 153 35578055 67 Hu Y. Hua Q. Sun G. Shi K. Zhang H. Zhao K. Jia S. Dai Y. Wu Q. The catalytic activity for ginkgolic acid biodegradation, homology modeling and molecular dynamic simulation of salicylic acid decarboxylase Comput. Biol. Chem. 75 2018 82 90 29751208 68 Liu Z.H. Zeng S. Cytotoxicity of ginkgolic acid in HepG2 cells and primary rat hepatocytes Toxicol. Lett. 187 3 2009 131 136 19429255 69 Berg K. Braun C. Krug I. Schrenk D. Evaluation of the cytotoxic and mutagenic potential of three ginkgolic acids Toxicology 327 2015 47 52 25448085
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Int J Biol Macromol. 2023 Jan 31; 226:780-792
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==== Front Chem Eng J Chem Eng J Chemical Engineering Journal 1385-8947 1385-8947 Elsevier B.V. S1385-8947(22)06410-5 10.1016/j.cej.2022.140930 140930 Article Fluoroalkane modified cationic polymers for personalized mRNA cancer vaccines Li Junyan ab Wu Yuanyuan ab Xiang Jian d Wang Hairong c Zhuang Qi ab Wei Ting e Cao Zhiqin ab Gu Qingyang d⁎ Liu Zhuang ab⁎ Peng Rui ab⁎ a Institute of Functional Nano & Soft Materials (FUNSOM), Soochow University, 199 Ren’ai Rd, Suzhou, Jiangsu, 215123, China b Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, 199 Ren’ai Rd, Suzhou, Jiangsu, 215123, China c Children's Hospital of Soochow University, Suzhou, Jiangsu, 215006, China d WuXi AppTec (Suzhou) Co., Ltd., 1336 Wuzhong Avenue, Wuzhong District, Suzhou 215104, China e InnoBM Pharmaceuticals Co. Ltd., Suzhou, Jiangsu, 215123, China ⁎ Corresponding authors. 12 12 2022 12 12 2022 1409301 9 2022 12 11 2022 10 12 2022 © 2022 Elsevier B.V. All rights reserved. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Graphical abstract Messenger RNA (mRNA) vaccines, while demonstrating great successes in the fight against COVID-19, have been extensively studied in other areas such as personalized cancer immunotherapy based on tumor neoantigens. In addition to the design of mRNA sequences and modifications, the delivery carriers are also critical in the development of mRNA vaccines. In this work, we synthesized fluoroalkane-grafted polyethylenimine (F-PEI) for mRNA delivery. Such F-PEI could promote intracellular delivery of mRNA and activate the Toll-like receptor 4 (TLR4)-mediated signaling pathway. The nanovaccine formed by self-assembly of F-PEI and the tumor antigen-encoding mRNA, without additional adjuvants, could induce the maturation of dendritic cells (DCs) and trigger efficient antigen presentation, thereby eliciting anti-tumor immune responses. Using the mRNA encoding the model antigen ovalbumin (mRNAOVA), our F-PEI-based mRNAOVA cancer vaccine could delay the growth of established B16-OVA melanoma. When combined with immune checkpoint blockade therapy, the F-PEI-based MC38 neoantigen mRNA cancer vaccine was able to suppress established MC38 colon cancer and prevent tumor reoccurrence. Our work presents a new tool for mRNA delivery, promising not only for personalized cancer vaccines but also for other mRNA-based immunotherapies. Keywords fluoropolymer mRNA delivery antigen presentation personalized mRNA cancer vaccine cancer immunotherapy ==== Body pmc1 Introduction Cancer vaccines, which trigger tumor-specific cell-mediated immunity to recognize and kill cancer cells, are one of the most interesting approaches in cancer immunotherapy[1], [2], [3]. mRNA-based vaccines are a promising vaccine platform for several reasons[4], [5]. Firstly, mRNA is delivered into the cytosol for rapid production of large quantity of endogenous protein or peptide antigens, which are processed by the proteasome and presented to the cell surface by the major histocompatibility complex class I (MHC I) to activate CD8+ T cells that are thought to play a key role in the antitumor immunity[6], [7], [8], whereas exogenous peptide/protein antigens are mainly been processed in the lysosome and presented via MHC II, inducing humoral immunity [9]. Therefore, compared with peptide/protein vaccines, mRNA vaccines may induce stronger cellular immune responses for antitumor immunity. Secondly, compared with protein antigens, mRNA antigens have stronger immunogenicity and possess intrinsic adjuvant properties, which could further enhance immune responses [10]. Thirdly, compared with DNA vaccines, mRNA vaccines only need to be internalized into the cytoplasm for translation, without raising the risk of gene integration or other safety issues[11]. However, due to the abundance of RNases and the difficulty of mRNA molecules in entering cells, biocompatible delivery carriers that can improve the mRNA stability and transport mRNA into antigen-presenting cells (APCs) are essential in the development of mRNA vaccines[12], [13], [14]. Currently, lipid nanoparticles (LNPs) have demonstrated great successes as the delivery system in the fabrication of mRNA vaccines[15], [16], [17]. However, LNPs usually are composed by a variety of different lipid components with rather complicated compositions. Moreover, state-of-art microfluidic devices are usually required in the fabrication processes to produce LNP-based mRNA vaccines[18]. Developing new mRNA delivery carriers with simple composition and easy preparation process would still be of great interests for mRNA-based biotechnology. An effective mRNA delivery carrier should be able to pack and protect the mRNA from enzymatic degradation, to transport the mRNA either directly into the cytosol or via escaping from the lysosome, and finally to release the mRNA cargo to the cellular translation machinery. Therefore, both the affinity of the carrier towards the mRNA cargo and the interaction(s) of the carrier with the target cell would contribute to its delivery efficiency. Fluorine-containing amphiphiles have been reported to show promising gene and protein delivery effects [19], [20], [21], [22]. Fluorinated compounds with both hydrophobic and lipophobic features show a high tendency of phase separation in both polar and non-polar environments[23], [24], enabling their penetration across the lipid bilayer of cell membranes as well as endosomal/lysosomal membranes[25], [26]. In our previous work, we reported that a fluoroalkane modified polyethylenimine (PEI) with a molecular weight of 25 kDa (F-PEI25 kDa), while serving as an agonist for the Toll-like receptor 4 (TLR4)-mediated signaling pathway, could self-assemble with protein or peptide antigens to form nanovaccines without the need of additional adjuvants[27]. However, regular PEI with high molecular weight possesses certain cytotoxicity, thus limiting its potential in bio-applications[28], [29]. Here, a low molecular weight (1.8 kDa) PEI with low cytotoxicity was chosen for further optimization in this study. Two fluoroalkane-grafted PEI polymers (F-PEI1.8 kDa) were synthesized for efficient mRNA delivery and TLR4 activation. By simply mixing F-PEI with the mRNA encoding tumor antigens (Ag), without additional adjuvants, we obtained F-PEI/mRNAAg nanovaccines which could promote high level of dendritic cells (DCs) activation and MHC I antigen processing and presentation by APCs, subsequently inducing antigen-specific CD8+ T cell immune responses to effectively inhibit the growth of established B16-OVA melanoma tumors. We further demonstrated that using the mRNA encoding neoantigens of MC38 tumors, F-PEI-based personalized nanovaccine, in combination with the immune checkpoint inhibitors, could eradicate established tumors (Fig. 1 ). This work presents a new type of mRNA delivery vector that may be of great interests to the development of mRNA-based personalized cancer vaccines as well as other mRNA-based immunotherapies.Fig. 1 Design of the F-PEI/mRNA nanovaccine platform for cancer treatment. (a) Schematic illustration showing the preparation of F-PEI/mRNA nanovaccine. F-PEI was synthesized by grafting fluorine ligands on PEI (MW 1.8 kDa), and then mixed with the mRNA encoding antigen (Ag) to form F-PEI-based mRNA nanovaccine (F-PEI/mRNAAg). (b) After administration, F-PEI/mRNAAg nanovaccine is taken up by dendritic cells (DCs), to promote antigen presentation and maturation of DCs. Then activated DCs would migrate to the draining lymph nodes, triggering robust antigen-specific CD8+ T cell responses. Activated CD8+ T cells would then recognize and kill target cancer cells and exert powerful antitumor efficacy. Combining with immune checkpoint inhibitors would further enhance the efficacy of F-PEI-based mRNA nanovaccine to eliminate established tumors. Ag, antigen. i.d., intradermal. 2 Experimental 2.1 Materials Branched polyethylenimine (MW 1.8 kDa) was purchased from Sigma-Aldrich (St. Louis, MO). 3-(perfluorohex-1-yl)-1,2-propenoxide was purchased from J&K Scientific (Shanghai, China). Firefly-luciferase and OVA expression mRNAs were obtained from Trilink. MC38 neoantigen expression mRNA was commissioned to construct by Stemirna (Shanghai, China). The firefly-luciferase mRNA labeled with the fluorophore Cy5 was obtained from APExBIO. Lipofectamine MessengerMAX was purchased from Invitrogen. 2.2 Animals and cells Female C57BL/6 mice (6-8 weeks) were purchased from Nanjing Pengsheng Biological Technology Co., Ltd. Female OT-I transgenic mice (6-8 weeks) were a kind gift from Prof. Xuefeng Wang, Soochow University. All animal experiments were performed according to the guidelines for the protection of animal life and protocols approved by Laboratory Animal Ethics Committee in Soochow University. B16-OVA cells (a gift from Prof. Yuhui Huang, Soochow University), RAW264.7 cells (obtained from American Type Culture Collection) were cultured in Dulbecco’s modifed Eagle medium (DMEM) with 10% fetal bovine serum (FBS) and 1% penicillin sulfate and streptomycin (PS) at 37 °C in 5% CO2. DC2.4 cells (a gift from Prof. Chao Wang, Soochow University), MC38 cells (obtained from American Type Culture Collection) were cultured in Roswell Park Memorial Institute (RPMI) 1640 medium 10% FBS and 1% PS at 37 °C in 5% CO2. HEK-Dual mTLR4 (NF/IL8) cells (obtained from InvivoGen) were cultured in DMEM with 10% FBS and 1% PS supplemented with 100 μg mL–1 Hygromycin B Gold (InvivoGen) and 50 μg mL–1 Zeocin (InvivoGen) at 37 °C in 5% CO2. 2.3 Synthesis of F-PEI Epoxides of fluoroalkanes were added dropwisely into PEI1.8k in methanol at different molar ratios (75:1 or 100:1). The mixture was stirred at room temperature for 48 hours, then the products were purified by intensive dialysis against methanol and double distilled water (molecular weight cut off 1000 Da). The products were collected and lyophilized under vacuum to obtain F-PEI. 2.4 In vitro cytotoxicity assessment DC2.4 cells or RAW264.7 macrophages were seeded into 96-well plates at 5×104 cells per well and incubated with different concentrations of F-PEI or PEI for 24 h, and relative cell viability was measured by standard MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide) assay. 2.5 Nucleic acid condensation ability assay Agarose Gel Electrophoresis (AGE) was used to verify the ability of F-PEI to condense mRNA. F-PEI/mRNA complexes at various w/w ratios (from 0.25 to 2) were prepared, added with 2× RNA loading dye (Solarbio), heat-treated at 65°C for 8 min, loaded onto a 1% agarose denaturing gel containing GelRed dye (Beyotime), and then electrophoresed at 125 V for 30 min. The electrophoretic band was imaged by using Amersham Imager 600 UV System. 2.6 Characterization of F-PEI/mRNA The synthesized F-PEI was mixed with mRNA in deionized water at a mass ratio of 1:1 for 15 min. The size and zeta potential of the formed F-PEI/mRNA NPs were measured using a Zetasizer Nano ZS (Malvern Instruments). The morphology of the NPs was observed with a FEI TF20 transmission electron microscope. 2.7 in vivo mRNA expression assay The F-PEI/mRNALuc (10 μg mRNALuc per mouse) was intradermally injected at the tail base of each C57BL/6 mouse, followed by intraperitoneal injection of 0.2 mL of d-luciferin (1.5 μg mL-1) after 6 h and 24 h. After 15 min of reaction, the mice were subjected to bioluminescence assays using IVIS Kinetic Imaging System (Perkin Elmer). 2.8 BMDC activation and antigen presentation For in vitro DC maturation experiments, BMDCs were plated at 106 cells per well in a 24-well plate and incubated with mRNAOVA, F-PEI/mRNAOVA or Lipofectamine MessengerMAX/mRNAOVA (mRNAOVA = 3 μg mL-1, the w/w ratio of material and mRNAOVA was 1:1). After 24 h incubation, BMDCs were harvested and washed with FACS buffer (1% FBS in PBS), and incubated with anti-CD16/32 at 4 °C, then stained with anti-CD11c-FITC, anti-CD80-APC and anti-CD86-PE for DC maturation analysis, or anti-CD11c-APC and anti-SIINFEKL/H-2Kb-PE for antigen presentation analysis. 2.9 In vitro mRNA cellular uptake To assess the cellular uptake of mRNA by BMDCs, 106 BMDCs were plated in 24-well plate and incubated with Cy5-labelled mRNALuc (Cy5-mRNALuc), F13-PEI1.8k-1/Cy5-mRNALuc, F13-PEI1.8k-2/Cy5-mRNALuc for 6 h (Cy5-mRNALuc = 1 μg mL-1, The w/w ratio of material and mRNALuc was 1:1). BMDCs were harvested and added with trypan blue to quench the extracellular fluorescence. After washing for three times, BMDCs were incubated with anti-CD16/32 for 15 min at 4 °C before being stained with anti-CD11c-FITC, and then analyzed using flow cytometer (BD Accurit C6 Plus). 2.10 In vitro CD8+ T-cell priming assay BMDCs were incubated with F-PEI/mRNAOVA NPs. Then the treated BMDCs were washed by PBS containing 0.1% BSA. CD8+ T lymphocytes were negatively selected from the spleen of OT-I mice by magnetic separation (MACS system, Miltenyi Biotec) according to the manufacturer's instructions and stained with the CellTrace CFSE Cell Proliferation Kit (Invitrogen) according to the experimental protocol. The treated BMDCs (105 mL–1) were then mixed with CFSE-stained splenic CD8+ T cells at a ratio of 1:10, and incubated in round-bottom 96-well plates (Beyotime) for 72 h. Cells were washed by FACS buffer, before being incubated with anti-CD16/32 at 4 °C then stained with anti-CD3-PerCP for flow cytometer measurement. 2.11 Detection of Cytokine The supernatant after incubation in CD8+ T-cell priming assay was collected, and the secretion level of IFN-γ in the cell supernatant was detected by enzyme-linked immunosorbent assay (ELISA). The experimental steps were performed according to the instructions of the ELISA kit (Invitrogen). 2.12 Lymph node analysis C57BL/6 mice were immunized with PBS, mRNAOVA or F-PEI/mRNAOVA by intradermal injection on Day 0. The injected dose of mRNAOVA per mouse was 10 μg. On Day 3 after mouse immunization, we assessed DC maturation and antigen presentation in mouse inguinal lymph nodes (LNs). LNs from immunized mice were treated by mechanical disruption, then filtered through 200-mesh nylon mesh to obtain single-cell suspensions, which were incubated with anti-CD16/32 for 15 min at 4°C before being stained with anti-CD11c-FITC, anti-CD86-PE and anti-CD80-APC for DC maturation analysis, or anti-CD11c-APC and anti-SIINFEKL/H-2Kb-PE for antigen presentation analysis. 2.13 Tetramer analysis and peptide re-stimulation of splenocytes C57BL/6 mice were intradermally immunized with PBS, mRNAOVA or F-PEI/mRNAOVA on Day 0 and 7. On Day 14, the spleens of the immunized mice were minced and filtered with a 300 mesh cell strainer to obtain splenocytes, and then RBCs (Red blood cells) were lysed with RBC lysis buffer (Beyotime). Splenocytes were stained with PE-labelled SIINFEKL-MHC I tetramer, anti-CD8-APC and anti-CD3-FITC, then analyzed the percentage of OVA-specific CD8+ T cells using the tetramer staining assay following the standard protocol. For enzyme linked immunospot assay (ELISPOT) analysis of IFN-γ spot-forming cells (BD Biosciences), 5×105 splenocytes were plated in each well and incubated with 10 μg mL–1 OVA257–264 peptide (SIINFEKL), Reps1 peptide (AQLANDVVL), Dpagt1 peptide (SIIVFNLL) or Adpgk peptide (ASMTNMELM). The plates were kept at 37 °C in 5% CO2 for 24 h. Following the experimental protocol, an automated ELISPOT Plate Reader (AID iSpot) was used to determine the amount of IFN-γ spot-forming cells and the data were presented as spot-forming cells per half million cells. To demonstrate the cellular responses, 106 immunized mice splenocytes were incubated with 10 μg mL-1 OVA257-264 peptide (SIINFEKL) in the medium containing brefeldin A inhibitor and monensin inhibitor for 6 h. Cells were incubated with anti-CD16/32 antibody at 4°C for 15 min, and then stained with anti-CD3e-FITC and anti-CD8a-APC at 4°C for 30 min. Then the cells were stained anti-IFN-γ-PE according to the intracellular staining protocol before the flow cytometry measurement. 2.14 Hematoxylin and eosin (H&E) staining C57BL/6 mice were intradermally treated two times with F13-PEI1.8k-1/mRNAOVA or F13-PEI1.8k-2/mRNAOVA at 1 week intervals. Mice were euthanized and collected major organs on Day 1, 7 and 21 after two vaccination. The major organs were fixed in 4% paraformaldehyde solution, and then sectioned for H&E staining. 2.15 Treatment of the B16-OVA tumor model C57BL/6 mice were subcutaneously inoculated with 5×105 B16-OVA cells on Day 0. Mice were intradermally treated with PBS, mRNAOVA or F-PEI/mRNAOVA on Day 4 and 11. The injected dose of mRNAOVA per mouse was 10 μg. The tumor growth were regularly measured and recorded: tumor volume = length × width × width/2. Mice were euthanized when the tumor volume reached 1500 mm3. 2.16 Neoantigen mRNA vaccine combined with immune checkpoint inhibitor for tumor therapy C57BL/6 mice were subcutaneously injected with 106 MC38 colon cancer cells on Day 0. Tumor-bearing mice were randomly divided into 4 groups and treated with different treatments: (1) PBS, (2) anti-PD-1, (3) F13-PEI1.8k-1/mRNAMC38, (4) F13-PEI1.8k-1/mRNAMC38 + anti-PD-1. Mice were intradermally immunized with F13-PEI1.8k-1/mRNAMC38 on Days 8 and 15. The injected dose of mRNAMC38 per mouse was 10 μg. On Day 9 and 16, mice were intravenously injected with anti-PD-1 (20 μg per mouse). On Day 12 and 19, mice were intravenously injected with anti-PD-1 (10 μg per mouse). Mice were euthanized when the tumor volume reached 1000 mm3. For tumor rechallenge experiment, tumor-eliminated mice treated with neoantigen mRNA nanovaccine combined with immune checkpoint inhibitors were subcutaneously injected with 5×105 MC38 cells on Day 60. The tumor growth was monitored and recorded to evaluate the immune memory effect. 2.17 CD8+ T cell depletion Each C57BL/6 mouse was subcutaneously injected with 106 MC38 cells on Day 0. The tumor-bearing mice were randomly divided into 4 groups and treated with different methods: (1) mouse-IgG (as Control, Southern Biotech), (2) anti-mouse-CD8a (BioXcell), (3) F13-PEI1.8k-1/mRNAMC38 + anti-PD-1 + anti-mouse-CD8a, (4) F13-PEI1.8k-1/mRNAMC38 + anti-PD-1 + mouse-IgG. On Day 7, 10 and 13, mice were intravenously injected with anti-mouse-CD8a or mouse-IgG antibody (20 μg per mouse). On Day 8, mice were intradermally immunized with F13-PEI1.8k-1/mRNAMC38. On Day 9, mice were intravenously injected with anti-PD-1 (20 μg per mouse). On Day 12, mice were intravenously injected with anti-PD-1 (10 μg per mouse). The peripheral blood of mice was collected on Day 10, and the depletion of CD8+ T cells was detected by flow cytometry. 3 Results and Discussion 3.1 Characterization and the mRNA delivery efficiency of fluoropolymers Branched PEI (MW 1.8 kDa) was grafted with fluoroalkanes (3-(perfluoro-n-hexyl)-1,2-propenoxide, F13) via amine-epoxide reaction[22]. The F13 ligand was mixed with PEI at 2 different feed ratios: 75:1, 100:1, and the obtained materials were named as F13-PEI1.8k-1 and F13-PEI1.8k-2 with the fluorine contents of 35.98% and 40.36%, respectively. Firstly, we verified the ability of F-PEI to condense nucleic acids by agarose gel electrophoresis. The two F-PEIs were simply mixed with mRNA at increasing w/w ratios. Both F13-PEI1.8k-1 and F13-PEI1.8k-2 could successfully encapsulate mRNA at a very low ratio to prevent its leakage by forming particles (Fig. 2 a), demonstrated by the disappearance of the free mRNA band. The cytotoxicity of F-PEIs was also explored. Cell viability was analyzed after incubating RAW264.7 macrophages and DC2.4 cells with the two F-PEIs or bare PEI1.8k. Both F-PEIs showed comparable low cytotoxicity with bare PEI1.8k (Supplementary Fig. S1), demonstrating that the fluorine modification did not affect the biocompatibility. Considering no obvious toxicity could be observed at 10 μg mL-1 (Supplementary Fig. S1), the w/w ratio of F13-PEI1.8k-1/mRNA and F13-PEI1.8k-2/mRNA was set at 1:1 accordingly giving a working concentration of 3-10 μg mL-1. At this ratio, the particle sizes were both about 280 nm in hydrodynamic diameter (Fig. 2b) with spherical shape under TEM (Fig 2c), and their zeta potentials were approximately -6.5 mV and -12.3 mV, respectively (Fig. 2d).Fig. 2 Characterization and mRNA delivery efficiency of F-PEI. (a) Agarose gel electrophoresis of F-PEI/mRNA at different w/w ratios. (b) Dynamic light scattering analysis of F-PEI/mRNA. (c) Transmission electron microscopy imaging shown F13-PEI1.8k-1/mRNA and F13-PEI1.8k-2/mRNA. Scale bar = 200 nm. (d) Zeta potentials of the F13-PEI1.8k-1, F13-PEI1.8k-2, mRNA, F13-PEI1.8k-1/mRNA and F13-PEI1.8k-2/mRNA. (e&f) Representative flow cytometry plots (e) and the mean fluorescence intensity (MFI) of Cy5 (f) in BMDCs incubated with F-PEI/Cy5-mRNALuc for 6 h. (g&h) F-PEI/mRNALuc (10 μg mRNALuc per mouse) was intradermally injected at the tail base of mice to evaluate the in vivo mRNA delivery efficiency, and the bioluminescence images (g) and statistical data (h) were recorded at 6 h and 24 h post injection. d,f, The data show mean ± standard deviation (n = 3). h, The data show mean ± standard error of mean (n =3 mice per group). f,h, Statistical significance between the indicated groups was determined using two-sided unpaired t-tests. **P < 0.01, ***P < 0.001. We next investigated the mRNA cellular delivery efficiency of F-PEIs in vitro. mRNA encoding firefly luciferase (mRNALuc) was labeled with Cyanine 5 (Cy5) fluorescent dye (Cy5-mRNALuc) for intracellular tracking. Compared with free Cy5-mRNALuc, both F13-PEI1.8k-1/Cy5-mRNALuc and F13-PEI1.8k-2/Cy5-mRNALuc promoted mRNA uptake by mouse bone marrow-derived dendritic cells (BMDCs) (Fig. 2e & 2f), indicating that F13-PEI1.8k-1 and F13-PEI1.8k-2 could significantly improve the mRNA entry efficiency, and the mRNA delivery efficiency of F13-PEI1.8k-1 was significantly higher than that of F13-PEI1.8k-2. The mRNA delivery efficacy of F-PEI was also explored in vivo. F-PEI/mRNALuc was intradermally injected at the tail base of mice, and the bioluminescence intensities at the injection site were evaluated after intraperitoneal injection of d-luciferin. The expression of luciferase was recorded at 6 h and 24 h post injection. Based on the bioluminescence intensities, it was found that F13-PEI1.8k-1 showed better in vivo mRNA delivery efficiency than F13-PEI1.8k-2 (Fig. 2g & 2h), consistent with their abilities of mRNA packing and cellular delivery. 3.2 DC activation and OVA-specific T cell immune responses The maturation of DCs was essential for antigen presentation and subsequent initiation of T cell immune responses (Fig. 3 a). BMDCs were pulsed with mRNAOVA, F13-PEI1.8k-1/mRNAOVA, F13-PEI1.8k-2/mRNAOVA or Lipofectamine MessengerMAX/mRNAOVA, the latter of which was a commercial mRNA transfection reagent. It was found that F13-PEI1.8k-1/mRNAOVA and F13-PEI1.8k-2/mRNAOVA treated BMDCs showed a high up-regulation in co-stimulatory molecules (CD80 and CD86) compared to the control group and the mRNAOVA group, indicating significantly stimulated maturation of BMDCs (Fig. 3b).Fig. 3 Potent DC activation and antigen-specific T cell responses mediated by F-PEI/mRNA. (a) Schematic illustrating the mRNA encoding the specific antigen, the process of DC activation, antigen presentation and subsequent T cell proliferation. UTR, untranslated region. (b&c) Flow-cytometry analysis of CD80+CD86+ (b) and SIINFEKL-H-2Kb (c) in BMDCs treated with mRNAOVA, F-PEI/mRNAOVA, or Lipofectamine MessengerMAX/mRNAOVA. The mRNAOVA concentration was fixed at 3 μg mL-1. (d) HEK-Dual Null (NF/IL8) cells (as control) and HEK-Dual mTLR4 (NF/IL-8) cells were stimulated with 10 μg mL–1 F13-PEI1.8k-1 or F13-PEI1.8k-2, respectively. Lipopolysaccharide (LPS, 2 μg mL–1) was used as the positive control. After 12 h of incubation, activation of the TLR4 signaling pathway was determined by measuring the reporter Lucia luciferase activity. RLU, Relative light unit of treated groups. RLU0, RLU of the blank group. (e&f) Representative flow cytometry plots (e) and statistical data (f) showing proliferation of OT-I CD8+ T cells after co-cultured with BMDCs pre-treated with mRNAOVA or F-PEI/mRNAOVA. (g) Enzyme-linked immunosorbent assay (ELISA) measurement of IFN-γ in cell supernatants from the stimulated OT-I CD8+ T cells in (f). The data show mean ± s.d. from 3 independent experiments (n = 3). b,c,d,f,g, Statistical significance between the indicated groups was determined using two-sided unpaired t-tests. *P < 0.05, **P < 0.01. We then examined the antigen presentation efficiency via the MHC I pathway in BMDCs treated with F-PEI/mRNAOVA NPs. Compared with the mRNAOVA group, F13-PEI1.8k-1/mRNAOVA, F13-PEI1.8k-2/mRNAOVA and Lipofectamine MessengerMAX/mRNAOVA all could enhance the MHC I-associated SIINFEKL peptide presentation (Fig. 3c). More importantly, the F13-PEI1.8k-1/mRNAOVA could induce a higher level of MHC I antigen presentation, and its efficiency was significantly higher than that of the Lipofectamine MessengerMAX/mRNAOVA (Fig. 3c). A recent study demonstrated that F-PEI with PEI molecular weight of 25 kDa could activate the TLR4 signaling pathway to stimulate DC activation[27]. TLR4 is an important member of the TLR protein family for pathogen recognition[30]. It has been reported that, by binding to its ligand, TLR4 promotes innate immune activation, and the activation of the TLR4 signaling pathway can enhance antigen-specific adaptive immune response, linking innate and adaptive immune responses [31]. Therefore, we next wanted to verify whether F-PEI with PEI molecular weight of 1.8 kDa could also possess the ability to activate the TLR4-mediated signaling pathway. As shown in Fig. 3d, the activation of TLR4 signaling pathway by F13-PEI1.8k-1 and F13-PEI1.8k-2 was confirmed using murine TLR4 (NF-κB-SEAP/KI-[IL-8]Lucia) dual-reporter HEK293 cells with stably transfected mouse TLR4 (mTLR4) MD-2/CD14 genes. Our results also showed that F13-PEI1.8k-1 could trigger TLR4 activation to a level significantly higher than F13-PEI1.8k-2 (Fig. 3d), suggested that F13-PEI1.8k-1, as an mRNA delivery vehicle, could be the better one for both cellular uptake enhancement and immune stimulation. The OT-I CD8+ T cell contain transgenic T cell receptor designed to study the response of CD8+ T cells to specific OVA antigen. Using in vitro OT-I CD8+ T cell priming assay, BMDCs pre-treated with F13-PEI1.8k-1/mRNAOVA or F13-PEI1.8k-2/mRNAOVA could induce significant proliferation of OT-I CD8+ T cells, while the BMDCs pre-treated with F13-PEI1.8k-1/mRNAOVA induced higher levels of OT-I CD8+ T cell proliferation compared with those pre-treated with F13-PEI1.8k-2/mRNAOVA (Fig. 3e & 3f). Furthermore, for those CD8+ T cells activated by BMDCs pre-treated with F-PEI/mRNAOVA, a significant increase in the secretion of interferon-γ (IFN-γ) was also observed (Fig. 3g). Again, the above data indicated that F13-PEI1.8k-1/mRNAOVA NPs exhibited a better ability to activate BMDCs and trigger subsequent OVA-specific T cell responses. 3.3 In vivo stimulation of robust immune responses Next, the immunization efficacy of the F-PEI/mRNAOVA vaccine was evaluated in vivo. C57BL/6 mice were intradermally injected with different formulations, the activation and antigen presentation of DCs in the inguinal lymph nodes of the mice were detected on Day 3 (Fig. 4 a). Compared with the control group, in the lymph nodes of mice immunized with F13-PEI1.8k-1/mRNAOVA, the proportion of DCs with up-regulated expression of the co-stimulatory molecules CD80/CD86 was significantly increased, and the MHC I antigen presentation of the model antigen OVA was also significantly increased (Fig. 4b & 4c).Fig. 4 In vivo immune stimulation by the F-PEI/mRNAOVA nanovaccine. (a) Timeline of the experimental design to evaluate the in vivo immune responses triggered by the indicated formulations (mRNAOVA or F-PEI/mRNAOVA, 10 μg mRNAOVA per mouse). (b&c) Proportions of CD80+CD86+ DCs (b) and SIINFEKL-H2Kb+ (MHC I bound SIINFEKL+) DCs (c) among DCs in LNs on Day 3 post one immunization. (d&e) Representative flow dot plots (d) and statistical data (e) of SIINFEKL-specific CD8+ T cells in the spleen on Day 14 post two immunization by flow-cytometry analysis of MHC I/SIINFEKL tetramer+CD8+ T cells. (f&g) ELISPOT analysis of IFN-γ spot-forming cells (f) and statistical data (g) among splenocytes after ex vivo restimulation on Day 14 post two immunization. (h) The percentages of IFN-γ expression T cells in CD8+ T cells from restimulated splenocytes on Day 14 post two immunization. b,c,e,g,h, The data show mean ± s.d. (b,c, n = 4-5 mice per group; e,g,h, n = 6 mice per group). Statistical significance between the indicated groups was determined using two-sided unpaired t-tests. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. LNs, lymph nodes. i.d., intradermal. After C57BL/6 mice were immunized twice with indicated formulations at 1 week intervals, the frequency of OVA-specific CD8+ T cells in the splenocytes was analyzed on Day 14 (Fig. 4a). Notably, compared with the mRNAOVA group and the F13-PEI1.8k-2/mRNAOVA group, the frequency of SIINFEKL-MHC-I tetramer+CD8+ T cells in the F13-PEI1.8k-1/mRNAOVA group increased by 6.7-fold and 3.2-fold, respectively (Fig. 4d & 4e), suggesting that F13-PEI1.8k-1/mRNAOVA vaccination could trigger the most robust OVA-specific immune responses. Splenocytes from the twice-immunized mice were then restimulated with OVA antigen peptide (SIINFEKL), and OVA-specific T cell responses were examined. Compared with the mRNAOVA group and the F13-PEI1.8k-2/mRNAOVA group, the F13-PEI1.8k-1/mRNAOVA group triggered the strongest IFN-γ responses, as evidenced by the highest level of IFN-γ producing cells from the enzyme-linked immuno spot assay (ELISPOT) (Fig. 4f & 4g) and the flow cytometry analysis (Fig. 4h). The results again indicated that the F13-PEI1.8k-1/mRNAOVA vaccine triggered a strong OVA-specific T cell immune response in vivo. Based on the strong antigen-specific immune responses induced by F-PEI/mRNA, we further assessed its antitumor efficacy. C57BL/6 mice were subcutaneously inoculated with B16-OVA cells to establish the tumor-bearing mouse model. The mice were then treated two times with either phosphate buffered saline (PBS), mRNAOVA, F13-PEI1.8k-1/mRNAOVA or F13-PEI1.8k-2/mRNAOVA at 1 week interval after 4 days (Fig. 5 a). It could be observed that the F13-PEI1.8k-1/mRNAOVA cancer vaccine showed a strong tumor suppressive effect and effectively prolonged the survival time of mice (Fig. 5b & 5c), suggesting that the F13-PEI1.8k-1/mRNAAg had the potential to be a therapeutic mRNA cancer vaccine.Fig. 5 F-PEI/mRNAOVA nanovaccine inhibits tumor growth and prolongs survival in tumor-bearing mice. (a) A scheme of tumor challenge experiment design (n = 6). (b) Tumor growth curves for B16-OVA on mice after the various treatments. The data show mean ± s.e.m. (c) Survival curves of mice bearing B16-OVA tumor in different treatment groups. (d) Timeline of the vaccination and H&E staining experiment of mice major organs. (e) H&E staining of major organs collected from vaccinated mice on Day 8. Major organs from untreated healthy mice of the same age were collected on Day 28 as control. Scale bar = 200 μm. s.c., subcutaneous; i.d., intradermal. Hematoxylin and eosin (H&E) staining of major organs of the F13-PEI1.8k-1/mRNAOVA or F13-PEI1.8k-2/mRNAOVA vaccinated mice showed no obvious sign of any acute organ damage or inflammatory lesions in mice on Day 8, Day 14, and Day 28 (Fig. 5d, 5e and Supplementary Fig. S2), suggesting the good biosafety of our treatment in mice. 3.4 F-PEI-based neoantigen mRNA vaccination combined with immune checkpoint blockade for personalized cancer therapy Tumor neoantigens are non-self antigens produced by somatic cell mutations[32]. They only exist in cancer cells, not in normal cells[33]. Tumor neoantigens are highly immunogenic and can drive effective anti-tumor immune responses[34], [35], and thus are showing strong prospects in the design of cancer vaccines[36], [37], [38]. In order to prove the applicability of our cancer vaccine platform, we constructed F-PEI-based neoantigen vaccines to treat MC38 colon cancer model. It has been reported that the MC38 tumor cell line-specific mutant peptides Reps1, Dpagt1 and Adpgk could be used as neo-epitopes for T cells[39], and these mutant peptides could trigger specific CD8+ T cell responses [40], [41]. The encoding sequences of Reps1, Dpagt1 and Adpgk peptides were included in the open reading frame (ORF) of the mRNA to construct the MC38 neoantigen mRNA (mRNAMC38) (Fig. 6 a).Fig. 6 F-PEI-based neoantigen mRNA vaccine for personalized immunotherapy. (a) Design of the MC38 tumor neoantigen mRNA vaccine. (b) C57BL/6 mice were immunized with the indicated formulations (PBS, mRNAMC38, and F13-PEI1.8k-1/mRNAMC38, 10 μg mRNAMC38 per mouse). (c) Statistical data of IFN-γ producing cells among splenocytes after ex vivo restimulation with peptide antigens on Day 14 post immunization (6 mice for each group, data shown as mean ± s.d.). (d) The timeline of F13-PEI1.8k-1/mRNAMC38 nanovaccine treatment combined with anti-PD-1 therapy. (e&f) Tumor growth curves (e) and survival curves (f) of mice in different treatment groups (data shown as mean ± s.e.m.) (g) Survival curves of the 4 cured mice (from 6f, the F13-PEI1.8k-1/mRNAMC38 vaccine + anti-PD-1 combination treatment group) rechallenged with MC38 cells on Day 60. Untreated: healthy mice of the same age challenged with MC38 cells. (h) The timeline of CD8+ T cell depletion experiment. (i) Flow cytometry analysis of CD8+ T cells in the mouse blood on the third day after treatment with anti-CD8a or an isotype mouse monoclonal antibody (IgG). (j) Tumor growth curves of the tumor-bearing mice pre-treated with either anti-CD8a or IgG followed by the combined F13-PEI1.8k-1/mRNAMC38 + anti-PD-1 therapy (data shown as mean ± s.d.). e,f,j, 7-8 mice for each group. Statistical significance between the indicated groups was determined using two-sided unpaired t-tests. ***P < 0.001, ****P < 0.0001. s.c., subcutaneous; i.d., intradermal ; i.v., intravenous. Next, we selected F13-PEI1.8k-1, which performed better in the previous experiments, as the neoantigen mRNA delivery vehicle. We simply mixed mRNAMC38 with F13-PEI1.8k-1 to synthesize the F13-PEI1.8k-1/mRNAMC38 nanovaccine with an average size of ∼ 250 nm and a zeta potential of -6.8 mV (Supplementary Fig. S3). Compared with the control group and the mRNAMC38 group, the splenocytes from mice immunized with F13-PEI1.8k-1/mRNAMC38 showed significantly increased IFN-γ producing cells after restimulation with Reps1, Dpagt1 and Adpgk peptides, respectively, indicating that F13-PEI1.8k-1/mRNAMC38 could induce potent antigen specific CD8+ T cell responses for each displayed antigen (Fig 6b & 6c). The F13-PEI1.8k-1/mRNAMC38 cancer vaccine was then combined with the immune checkpoint inhibitor anti-PD-1 to evaluate its antitumor effect (Fig. 6d). It could be seen that the tumor growth in F13-PEI1.8k-1/mRNAMC38 immunized mice was significantly delayed compared with the mice in the control group and the anti-PD-1 group. Moreover, the combined treatment with anti-PD-1 could further improve the antitumor therapeutic effect of F13-PEI1.8k-1/mRNAMC38 vaccine (Fig. 6e). In fact, F13-PEI1.8k-1/mRNAMC38 combined with anti-PD-1 treatment significantly prolonged the survival time of mice (Fig 6f), and 50% of mice showed complete tumor regression. Notably, when mice that survived from the combinational treatment were rechallenged with MC38 cells on Day 60, compared to healthy mice challenged with MC38 cells (the untreated group), 100% of the cured mice survived (Fig. 6g), indicating effective immunological memory effect triggered by the F13-PEI1.8k-1/mRNAMC38 combined with anti-PD-1 treatment against tumor recurrence. In order to verify the importance of CD8+ T cells in the combination therapy, anti-CD8a was used to perform the CD8+ T cell depletion experiment (Fig. 6h). The depletion of CD8+ T cells in the peripheral blood of mice was analyzed by flow cytometry on the third day after intravenous injection of anti-CD8a or mouse IgG (as control). The results showed complete depletion of CD8+ T cells from the peripheral blood of mice treated with anti-CD8a, while CD8+ T cells in the mice treated with mouse IgG remain unaffected (Fig. 6i). As expected, after CD8+ T cell depletion, the inhibitory effect of the combination therapy on tumor growth was dramatically impaired (Fig. 6j), suggesting that CD8+ T cells played a key role in the tumor suppression by the combination therapy. 4 Conclusions In this work, we synthesized fluoroalkane modified cationic polymers for mRNA vaccine delivery and immune stimulation. We established a fluorinated polymer-based mRNA nanovaccine platform, by simple blending of F-PEI with mRNA encoding antigen(s). Our fluorinated polymer-based mRNA vaccine could effectively promote the uptake of mRNA by DCs, activate the TLR4 signaling pathway, trigger the DC activation and antigen presentation by DCs, therefore induce T cell priming, stimulate the tumor antigen-specific cellular immunity, and significantly delay the tumor growth after therapeutic vaccination. We further combined the fluorinated polymer-based MC38 neoantigen mRNA vaccine with the immune checkpoint inhibitor, and eradicated tumors in 50% of the MC38 tumor-bearing mice and successfully prevented tumor reoccurrence. In conclusion, we have developed a novel cancer vaccine platform suitable for the delivery of mRNA vaccines, and demonstrated synergistic therapeutic effects of such personalized neoantigen vaccines in combination with immune checkpoint inhibitors. In the future, the mRNA delivery polymer developed in this work might be extended to applications in other mRNA-based therapeutics where high level of mRNA delivery is desired, or both robust cellular and humoral immune responses are crucial, e.g., in the fight against viral infections, besides neutralizing antibody induction, strong cellular immune responses are required to eliminate the infected cells. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data availability No data was used for the research described in the article. Acknowledgements This work is dedicated to the memory of Dr. Jun Xu, who passed away in a tragic accident. Jun took part in the original design, the functionalization & optimization of the F-PEI polymers, and several efficacy evaluation assays. This work was partially supported by the National Key Research and Development (R&D) Program of China (2022YFB3804604 and 2021YFF0701800), the National Natural Science Foundation of China (32071382, 52032008, and 21927803), the Natural Science Foundation of Jiangsu Higher Education Institutions of China (19KJA310008), Suzhou Science and Technology Development Project-Science and Technology Innovation in Medicine and Health Care (SKY2021033), the Collaborative Innovation Center of Suzhou Nano Science and Technology (Nano-CIC), the 111 Project, the National Center of Technology Innovation for Biopharmaceuticals (NCTIB), and the Suzhou Key Laboratory of Nanotechnology and Biomedicine. ==== Refs References 1 Vermaelen K. Vaccine Strategies to Improve Anti-cancer Cellular Immune Responses Front Immunol 10 2019 00008 2 Kim C.G. Sang Y.B. Lee J.H. Chon H.J. Combining Cancer Vaccines with Immunotherapy: Establishing a New Immunological Approach International journal of molecular sciences 22 2021 8035 34360800 3 Zhang Q.L. Hong S. Dong X. Zheng D.W. Liang J.L. Bai X.F. Wang X.N. Han Z.Y. Zhang X.Z. Bioinspired nano-vaccine construction by antigen pre-degradation for boosting cancer personalized immunotherapy Biomaterials 287 2022 121628 4 Deng Z. Tian Y. Song J. An G. Yang P. mRNA Vaccines: The Dawn of a New Era of Cancer Immunotherapy Front Immunol 13 2022 887125 5 Shi J. Huang M.W. Lu Z.D. Du X.J. Shen S. Xu C.F. Wang J. Delivery of mRNA for regulating functions of immune cells Journal Of Controlled Release 345 2022 494 511 35337940 6 Moser M. Leo O. Key concepts in immunology Vaccine 28 2010 C2 C13 20713253 7 Appay V. Douek D.C. Price D.A. CD8(+) T cell efficacy in vaccination and disease Nat Med 14 2008 623 628 18535580 8 Ji X. Guo D. Ma J. Yin M. Yu Y. Liu C. Zhou Y. Sun J. Li Q. Chen N. Fan C. Song H. Epigenetic Remodeling Hydrogel Patches for Multidrug-Resistant Triple-Negative Breast Cancer Advanced materials 33 18 2021 2100949 9 Eggenhuizen P.J. Ng B.H. Ooi J.D. Antigen-driven CD4(+) T-cell anergy: a pathway to peripheral T regulatory cells Immunology and cell biology 99 2021 252 254 33277740 10 Linares-Fernandez S. Lacroix C. Exposito J.Y. Verrier B. Tailoring mRNA Vaccine to Balance Innate/Adaptive Immune Response Trends in molecular medicine 26 2020 311 323 31699497 11 Pardi N. Hogan M.J. Porter F.W. Weissman D. mRNA vaccines - a new era in vaccinology Nat Rev Drug Discov 17 2018 261 279 29326426 12 Shuai Q. Zhu F.T. Zhao M.D. Yan Y.F. mRNA delivery via non-viral carriers for biomedical applications Int J Pharmaceut 607 2021 121020 13 Pardi N. Hogan M.J. Weissman D. Recent advances in mRNA vaccine technology Current opinion in immunology 65 2020 14 20 32244193 14 Yin Y. Li X. Ma H. Zhang J. Yu D. Zhao R. Yu S. Nie G. Wang H. In Situ Transforming RNA Nanovaccines from Polyethylenimine Functionalized Graphene Oxide Hydrogel for Durable Cancer Immunotherapy Nano Lett 21 2021 2224 2231 33594887 15 Polack F.P. Thomas S.J. Kitchin N. Absalon J. Gurtman A. Lockhart S. Perez J.L. Marc G.P. Moreira E.D. Zerbini C. Bailey R. Swanson K.A. Roychoudhury S. Koury K. Li P. Kalina W.V. Cooper D. Frenck R.W. Hammitt L.L. Tureci O. Nell H. Schaefer A. Unal S. Tresnan D.B. Mather S. Dormitzer P.R. Sahin U. Jansen K.U. Gruber W.C. Grp C.C.T. Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine New Engl J Med 383 2020 2603 2615 33301246 16 Baden L.R. El Sahly H.M. Essink B. Kotloff K. Frey S. Novak R. Diemert D. Spector S.A. Rouphael N. Creech C.B. McGettigan J. Khetan S. Segall N. Solis J. Brosz A. Fierro C. Schwartz H. Neuzil K. Corey L. Gilbert P. Janes H. Follmann D. Marovich M. Mascola J. Polakowski L. Ledgerwood J. Graham B.S. Bennett H. Pajon R. Knightly C. Leav B. Deng W.P. Zhou H.H. Han S. Ivarsson M. Miller J. Zaks T. Grp C.S. Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine New Engl J Med 384 2021 403 416 33378609 17 X.C. Hou, T. Zaks, R. Langer, Y.Z. Dong, Lipid nanoparticles for mRNA delivery, Nat Rev Mater, 7 (2022) 65-65. 18 Evers M.J.W. Kulkarni J.A. van der Meel R. Cullis P.R. Vader P. Schiffelers R.M. State-of-the-Art Design and Rapid-Mixing Production Techniques of Lipid Nanoparticles for Nucleic Acid Delivery Small Methods 2 9 2018 19 Xiong S.-D. Li L. Jiang J. Tong L.-P. Wu S. Xu Z.-S. Chu P.K. Cationic fluorine-containing amphiphilic graft copolymers as DNA carriers Biomaterials 31 9 2010 2673 2685 20034666 20 Wang M.M. Cheng Y.Y. Structure-activity relationships of fluorinated dendrimers in DNA and siRNA delivery Acta Biomater 46 2016 204 210 27662807 21 Zhang J.H. Wang W.J. Zhang J. Xiao Y.P. Liu Y.H. Yu X.Q. ROS-responsive fluorinated polycations as non-viral gene vectors Eur J Med Chem 182 2019 111666 22 Zhang Z.J. Shen W.W. Ling J. Yan Y. Hu J.J. Cheng Y.Y. The fluorination effect of fluoroamphiphiles in cytosolic protein delivery Nat Commun 9 2018 1377 29636457 23 Horvath I.T. Rabai J. Facile Catalyst Separation without Water - Fluorous Biphase Hydroformylation Of Olefins Science 266 1994 72 75 17814001 24 Cametti M. Crousse B. Metrangolo P. Milani R. Resnati G. The fluorous effect in biomolecular applications Chem Soc Rev 41 2012 31 42 21691620 25 Kasuya M.C.Z. Nakano S. Katayama R. Hatanaka K. Evaluation of the hydrophobicity of perfluoroalkyl chains in amphiphilic compounds that are incorporated into cell membrane J Fluorine Chem 132 2011 202 206 26 Wang M.M. Liu H.M. Li L. Cheng Y.Y. A fluorinated dendrimer achieves excellent gene transfection efficacy at extremely low nitrogen to phosphorus ratios Nat Commun 5 2014 3053 24407172 27 Xu J. Lv J. Zhuang Q. Yang Z.J. Cao Z.Q. Xu L.G. Pei P. Wang C.Y. Wu H.F. Dong Z.L. Chao Y. Wang C. Yang K. Peng R. Cheng Y.Y. Liu Z. A general strategy towards personalized nanovaccines based on fluoropolymers for post-surgical cancer immunotherapy Nat Nanotechnol 15 2020 1043 1052 33139933 28 Hall A. Lachelt U. Bartek J. Wagner E. Moghimi S.M. Polyplex Evolution: Understanding Biology, Optimizing Performance Mol Ther 25 2017 1476 1490 28274797 29 Pandey A.P. Sawant K.K. Polyethylenimine: A versatile, multifunctional non-viral vector for nucleic acid delivery, Materials science & engineering C, Materials for biological applications 68 2016 904 918 27524093 30 Steinhagen F. Kinjo T. Bode C. Klinman D.M. TLR-based immune adjuvants Vaccine 29 2011 3341 3355 20713100 31 Shetab Boushehri M.A. Lamprecht A. TLR4-Based Immunotherapeutics in Cancer: A Review of the Achievements and Shortcomings Molecular pharmaceutics 15 2018 4777 4800 30226786 32 Xu P. Luo H. Kong Y. Lai W.-F. Cui L. Zhu X. Cancer neoantigen: Boosting immunotherapy Biomedicine & Pharmacotherapy 131 2020 110640 32836075 33 Sahin U. Tureci O. Personalized vaccines for cancer immunotherapy Science 359 2018 1355 1360 29567706 34 Perumal D. Imai N. Lagana A. Finnigan J. Melnekoff D. Leshchenko V.V. Solovyov A. Madduri D. Chari A. Cho H.J. Dudley J.T. Brody J.D. Jagannath S. Greenbaum B. Gnjatic S. Bhardwaj N. Parekh S. Mutation-derived Neoantigen-specific T-cell Responses in Multiple Myeloma Clin Cancer Res 26 2020 450 464 31857430 35 Yarchoan M. Johnson B.A. Lutz E.R. Laheru D.A. Jaffee E.M. Targeting neoantigens to augment antitumour immunity (vol 17, pg 209, 2017) Nat Rev Cancer 17 2017 569 28835723 36 Blass E. Ott P.A. Advances in the development of personalized neoantigen-based therapeutic cancer vaccines Nat Rev Clin Oncol 18 2021 215 229 33473220 37 Ott P.A. Hu Z.T. Keskin D.B. Shukla S.A. Sun J. Bozym D.J. Zhang W.D. Luoma A. Giobbie-Hurder A. Peter L. Chen C. Olive O. Carter T.A. Li S.Q. Lieb D.J. Eisenhaure T. Gjini E. Stevens J. Lane W.J. Javeri I. Nellaiappan K. Salazar A.M. Daley H. Seaman M. Buchbinder E.I. Yoon C.H. Harden M. Lennon N. Gabriel S. Rodig S.J. Barouch D.H. Aster J.C. Getz G. Wucherpfennig K. Neuberg D. Ritz J. Lander E.S. Fritsch E.F. Hacohen N. Wu C.J. An immunogenic personal neoantigen vaccine for patients with melanoma Nature 547 2017 217 221 28678778 38 Cafri G. Gartner J.J. Zaks T. Hopson K. Levin N. Paria B.C. Parkhurst M.R. Yossef R. Lowery F.J. Jafferji M.S. Prickett T.D. Goff S.L. McGowan C.T. Seitter S. Shindorf M.L. Parikh A. Chatani P.D. Robbins P.F. Rosenberg S.A. mRNA vaccine-induced neoantigen-specific T cell immunity in patients with gastrointestinal cancer J Clin Invest 130 2020 5976 5988 33016924 39 Yadav M. Jhunjhunwala S. Phung Q.T. Lupardus P. Tanguay J. Bumbaca S. Franci C. Cheung T.K. Fritsche J. Weinschenk T. Modrusan Z. Mellman I. Lill J.R. Delamarre L. Predicting immunogenic tumour mutations by combining mass spectrometry and exome sequencing Nature 515 2014 572 576 25428506 40 Kuai R. Ochyl L.J. Bahjat K.S. Schwendeman A. Moon J.J. Designer vaccine nanodiscs for personalized cancer immunotherapy Nat Mater 16 2017 489 496 28024156 41 Wang W.J. Liu Z.D. Zhou X.X. Guo Z.Q. Zhang J. Zhu P. Yao S. Zhu M.Z. Ferritin nanoparticle-based SpyTag/SpyCatcher-enabled click vaccine for tumor immunotherapy Nanomed-Nanotechnol 16 2019 69 78
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Chem Eng J. 2022 Dec 12;:140930
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==== Front Mol Ther Mol Ther Molecular Therapy 1525-0016 1525-0024 The American Society of Gene and Cell Therapy. S1525-0016(22)00706-7 10.1016/j.ymthe.2022.12.002 Original Article Treatment with Quercetin inhibits SARS-CoV-2 N protein-induced acute kidney injury by blocking Smad3-dependent G1 cell cycle arrest Wu Wenjing 1234 Wang Wenbiao 1 Liang Liying 2 Chen Junzhe 25 Wei Biao 2 Huang Xiao-Ru 12 Wang Xiaoqin 34∗∗∗ Yu Xueqing 1∗∗ Lan Hui-Yao 12∗ 1 Guangdong-Hong Kong Joint Laboratory for Immunological and Genetic Kidney Disease, Departments of Nephrology and Pathology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Science, Guangzhou, China 2 Departments of Medicine & Therapeutics, Li Ka Shing Institute of Health Sciences, Lui Che Woo Institute of Innovative Medicine, and The Chinese University of Hong Kong (CUHK) - Guangdong Academy of Medical Sciences / Guangdong Provincial People’s Hospital (GAMS/GPPH) Joint Research Laboratory on Immunological and Genetic Kidney Diseases, The Chinese University of Hong Kong, Hong Kong, China 3 Hubei University of Chinese Medicine, Wuhan, China 4 Department of Nephrology, Hubei Provincial Hospital of Traditional Chinese Medicine, Hubei Province Academy of Traditional Chinese Medicine, Wuhan, China 5 Department of Nephrology, The Third Affiliated hospital, Southern Medical University, Guangzhou, China ∗ Corresponding author Professor Hui-Yao Lan, Departments of Medicine & Therapeutics, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China. ; ∗∗ Corresponding author Professor Xueqing Yu, Guangdong Academy of Medical Science, Guangdong Provincial People’s Hospital, Guangzhou, China, ∗∗∗ Corresponding author Professor Xiaoqin Wang, Department of Nephrology, Hubei Provincial Hospital of Traditional Chinese Medicine, Hubei Province Academy of Traditional Chinese Medicine, Wuhan, China, 12 12 2022 12 12 2022 10 10 2022 8 12 2022 © 2022 The American Society of Gene and Cell Therapy. 2022 The American Society of Gene and Cell Therapy Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Increasing evidence shows that SARS-CoV-2 can infect kidneys and cause acute kidney injury (AKI) in critically ill COVID-19 patients. However, mechanisms through which COVID-19 induces AKI are largely unknown and treatment remains no-effective. Here, we report that kidney-specifically overexpressing SARS-CoV-2 N gene can cause AKI including tubular necrosis and elevated levels of serum creatinine and BUN in 8-week-old diabetic db/db mice, which become worse in those with older age (16 weeks) and underlying diabetic kidney disease (DKD).Treatment with quercetin, a purified product from the traditional Chinese medicine (TCM) that shows effective treatment of COVID-19 patients, can significantly inhibit SARS-CoV-2 N protein-induced AKI in diabetic mice with or without underlying DKD. Mechanistically, quercetin can block the binding of SARS-CoV-2 N protein to Smad3, thereby inhibiting Smad3 signaling and Smad3-mediated cell death via the p16-dependent G1 cell cycle arrest mechanism in vivo and vitro. In conclusion, SARS-CoV-2 N protein is pathogenic and can cause severe AKI in diabetic mice, particularly in those with older age and pre-existing DKD, via the Smad3-dependent G1 cell cycle arrest mechanism. Importantly, we identify that quercetin may be an effective TCM compound capable of inhibiting COVID-19 AKI by blocking SARS-CoV-2 N-Smad3-mediated cell death pathway. Graphical abstract Wu and colleagues found that kidney-specifically overexpressing SARS-CoV-2 N protein can induce AKI in diabetic mice via a Smad3-depenent G1 cell cycle arrest mechanism. Treatment with quercetin can effectively inhibit the binding of SARS-CoV-2 N protein to Smad3, thereby inhibiting the Smad3-mediated cell death and AKI under diabetic conditions. Keywords SARS-CoV-2 N protein AKI Quercetin Smad3 p16 G1 cell cycle arrest ==== Body pmc
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Mol Ther. 2022 Dec 12; doi: 10.1016/j.ymthe.2022.12.002
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Mol Ther
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10.1016/j.ymthe.2022.12.002
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==== Front Appl Nurs Res Appl Nurs Res Applied Nursing Research 0897-1897 1532-8201 Elsevier Inc. S0897-1897(22)00107-0 10.1016/j.apnr.2022.151665 151665 Article Exercise, diet, and sleep habits of nurses working full-time during the COVID-19 pandemic: An observational study☆ Rangel T.L. PhD, MSN, RN, CNL a⁎ Saul T. PhD, RN, PMGT a Bindler R. PharmD ab Roney J.K. DNP, RN, NPD-BC, CCRN-K a Penders R.A. PhD, RNC-OB, C-ONQS a Faulkner R. MS, RD a Miller L. PhD c Sperry M. DNP, MSN, RN a James L. PhD b Wilson M.L. PhD, MPH, RN b a Providence Health System, United States of America b Washington State University, United States of America c Lincoln Memorial University, United States of America ⁎ Corresponding author at: Providence Sacred Heart Medical Center, 101 W 8th Ave, Spokane, WA 99204, United States of America. 12 12 2022 2 2023 12 12 2022 69 151665151665 17 8 2022 14 10 2022 6 12 2022 © 2022 Elsevier Inc. All rights reserved. 2022 Elsevier Inc. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Background Healthy diet, exercise, and sleep practices may mitigate stress and prevent illness. However, lifestyle behaviors of acute care nurses working during stressful COVID-19 surges are unclear. Purpose To quantify sleep, diet, and exercise practices of 12-hour acute care nurses working day or night shift during COVID-19-related surges. Methods Nurses across 10 hospitals in the United States wore wrist actigraphs and pedometers to quantify sleep and steps and completed electronic diaries documenting diet over 7-days. Findings Participant average sleep quantity did not meet national recommendations; night shift nurses (n = 23) slept significantly less before on-duty days when compared to day shift nurses (n = 34). Proportionally more night shift nurses did not meet daily step recommendations. Diet quality was low on average among participants. Discussion Nurses, especially those on night shift, may require resources to support healthy sleep hygiene, physical activity practices, and diet quality to mitigate stressful work environments. Keywords Diet Sleep Exercise Nurses Shift-workers COVID-19 ==== Body pmc1 Introduction Nurses represent a critical and essential component of the health care team. Support of both short and long-term health of nurses is imperative to ensure an adequate workforce is available to provide vital healthcare services to community members across the spectrum of wellbeing and illness. Studies have demonstrated an inherent connection between self-care activities of physical activity (PA), diet quality, sleep hygiene, and physical/mental health in the nursing workforce (Berent et al., 2021; Jiang et al., 2021; Mazurek Melnyk et al., 2022). For example, high-quality sleep, healthy eating habits, and regular physical activity are associated with a reduced risk of psychological conditions such as stress and burnout (Fitzpatrick & Valentine, 2021) and lower risk for all-cause mortality (Saeidifard et al., 2019; Sotos-Prieto et al., 2017; Yin et al., 2017). Despite advanced health knowledge and the professional expectation to provide healthy diet, physical activity, and sleep education to patients, nurses do not always follow national recommendations for health-promoting behaviors (Priano et al., 2018), increasing risk for negative physical and emotional conditions. According to Orem's theory of self-care (Denyes et al., 2001), individual patterns of engaging in self-care activities such as adequate sleep, diet and exercise, are influenced by personal attributes (i.e. age, gender), environmental situations such as occupational stress, self-efficacy, and ability to act on self-care needs. The COVID-19 pandemic has caused lasting emotional strain on nurses working in hospitals and, according to Orem's theory of self-care, nursing ability to engage in self-care activities may have suffered as a result. Reasons creating increased stress on nurses included fear of at-work COVID-19 exposure, personal illness with the virus, and infecting family members and friends (Cui et al., 2020; Kellogg et al., 2021). Inadequate personal protective equipment supply was also reported as an emotional stressor (Kellogg et al., 2021), along with critical short staffing situations that continue today (Galanis et al., 2021). Witnessing unprecedented, sudden clinical deterioration and death (Cui et al., 2020) in the context of extreme visitor limitations leaving patients isolated and dying alone (Kellogg et al., 2021) also created emotional turmoil. Finally, public misperceptions of the lived experience of working during the COVID-19 pandemic as a direct patient care nurse (Cui et al., 2020) is cited as a reason that the acute care nursing workforce has reported a disproportionate amount of stress since the COVID-19 pandemic (Al Maqbali et al., 2021; Sriharan et al., 2021). Individuals experiencing high levels of stress and fatigue may report worsened sleep quantity and quality (Al Maqbali et al., 2021; Cui et al., 2020; Neculicioiu et al., 2022), diet quality (Khubchandani et al., 2020), and physical activity (Is et al., 2021), threatening overall wellbeing. There is an urgent call to action to mitigate nursing fatigue to support nursing and patient safety and wellbeing (Caruso et al., 2019). Measuring changes to sleep, diet, and physical activity during times of high stress such as the COVID-19 pandemic is warranted as a first step to inform targeted wellness strategies. Wearable fitness trackers and smartphones allow for objective, valid, and reliable collection of lifestyle behaviors data including sleep duration, quality, and efficiency (Fuller et al., 2020), diet quality and composition (Zhang et al., 2021), and number of steps walked per day (Guillodo et al., 2020; Jin et al., 2022). Mobile applications empower individuals to self-report sleep, diet, and physical activity habits daily into electronic repositories (Jin et al., 2022). Despite the relative abundance of wearable devices and smartphone applications for documenting self-care activities, few studies reported using technology to remotely measure the self-care activities of registered nurses during COVID-19 (Vigoureux et al., 2022). The purpose of this observational research was to use Orem's theory of self-care as a lens to describe sleep, diet, and physical activity habits of registered nurses working 12-h shifts in hospitals following the onset of the COVID-19 pandemic using wearable devices and validated smartphone applications. Secondary aims included 1) determine if differences in socio-demographics, lifestyle behaviors or stress were noted between nurses working night versus day shifts, and 2) test for correlations between lifestyle behaviors and stress. 2 Methods 2.1 Study design and settings Nurses were recruited remotely to participate in this observational, week-long study between November 2020 and September 2021 from ten hospitals in three states: Washington, California, and Texas. Registered nurses provided sleep, diet, and physical activity data using smartphone applications and wearable tracking devices for one week, and completed surveys capturing demographics, stress, and sleep metrics. 2.2 Participants RNs working full-time (totaling six shifts and 72 h every 14 days), 12-hour day or night shifts (not alternating) in the hospital who were not pregnant, breastfeeding, or reporting a chronic illness and owned a smartphone were eligible to participate. 2.3 Procedures Registered Nurse study sponsors at 10 urban hospitals within a large health system posted approved recruitment flyers containing a brief study description and a quick response (QR) code that led to an electronic screening form. Recruitment across sites was phased. Three hospitals in Washington began recruitment first followed by five hospitals in California and finally the two hospitals in Texas advertised the study. Flyers were removed from all sites by the end of September 2021 once enough participants consented. Eligible, self-screened RNs were emailed a link to an electronic consent form. After e-consenting, participants were assigned a study identification (ID) number and were emailed a document detailing how to track their personal health habits per study protocol. Additional instructions on protocol adherence were provided via an interactive, online module, and each participant received a phone call from researchers to describe the protocol, clarify questions, and coordinate mailing of study supplies. Supplies needed for this study included actigraphs, pedometers, and measuring tape, including a prepaid return shipping package for those RNs who did not already have monitoring devices. Participants completed four tasks during the study protocol. The first task was entering demographics, sleep quality measures, self-reported physical activity, stress measures, and items measuring COVID-19's impact on lifestyle behaviors into REDCap. The second task involved wearing a wrist actigraph daily for 10 days (three control nights, then seven days coinciding with three on-duty and four off-duty time periods). The third task required participants to record three completed post-shift ASA24 diet recalls. The final task was to input seven consecutive days of sleep timing (onset and wake), meal timing, shift condition (on-duty versus off-duty) and total steps walked into log sheets within REDCap (Fig. 1 ).Fig. 1 Study tasks and timing for participants. Fig. 1 2.4 Measurements Study variables of interest included: 1. demographics, including the perceived impact of COVID-19 on self-care activities, 2. sleep, 3. diet quality, 4. physical activity, and 5. perceived stress. 2.4.1 Socio-demographic characteristics Baseline and daily data logs were entered into Research Electronic Data Capture (REDCap) by the participant (Harris et al., 2009). Demographics (age range, gender, education, shift worked, waist circumference, height and weight) were collected during the baseline survey. Body Mass Index (BMI) was calculated using participant reported height and weight. The impact of COVID-19 on self-care activities was assessed through author-created items asking whether diet quality, sleep quantity, sleep quality, and physical activity (respectively) worsened, stayed the same, or improved since the onset of COVID-19. 2.4.2 Sleep Objective sleep data were collected via a wrist actigraph (either a researcher-supplied ReadiBand or participant-owned wearable device compatible with the ReadiOne system which measured sleep quality, sleep quantity, and sleep efficiency). Data were downloaded from the wrist actigraph into the ReadiOne smartphone application (Fatigue Sciences). The sleep data provided by the Fatigue Science Corporation have been shown to be valid (Russell et al., 2000) and reliable (Driller et al., 2016). Subjective sleep data included the Revised Morningness-Eveningness Questionnaire (rMEQ) which is a 5-item valid and reliable survey that measures one's preference to rise early in the morning, later in the day, or to report no affinity for when to wake up (Chelminski et al., 2000). In our study, this measure had a Cronbach's alpha of 0.73, demonstrating strong reliability. 2.4.3 Diet Dietary intake was measured using the valid and reliable Automated Self-Administered Recall System (ASA24) 24-hour diet recall daily during on-duty time periods (Thompson et al., 2015). Detailed dietary intake was calculated in this platform which researchers used to quantify a diet quality scored called the Healthy Eating Index (HEI) (Reedy et al., 2018). 2.4.4 Physical activity Physical activity was self-reported during the baseline survey using the International Physical Activity Questionnaire (IPAQ). Participants monitored their steps daily during the study period using a researcher-supplied pedometer or participant-owned wrist pedometer by entering total daily steps into a REDCap survey, a valid and reliable method for collecting step data (Prince et al., 2008). 2.4.5 Stress Stress was measured using the valid and reliable Perceived Stress Scale (PSS-4) during the baseline survey (Abdulameer et al., 2019). In our study, this scale demonstrated a strong Cronbach's alpha of 0.78. 2.5 Data analysis Data were collected between November 2020 and September 2021 and were reviewed to ensure participant completion of each study task. Due to data being collected from multiple sources, all data exports were concatenated using participant ID as the key identifier. The concatenation process started with the export of data files from all sources (REDCap, ReadiOne, and ASA24) after completion of the data collection portion of the study. Once the uniformity of participant ID was completed, exports were uploaded into a local project server in the database management tool PostgreSQL via pgAdmin. Exports of the cleaned, complete dataset were then used for the analysis process. Analyses were conducted within SPSS Statistics by IBM Corp version 27 (2020). Categorical variables were described with counts and percentages while numeric variables were described with means and standard deviations. Chi-square tests were completed to assess any significant differences in completing the study for categorical variables; effect size (phi) was also calculated and reported. Independent t-tests were conducted for continuous data with Cohen's d for effect size reporting among normally distributed continuous variables. All tests were conducted as two-tailed to remain conservative, with a p-value of 0.05 or less regarded as a significant finding. To quantify the number of days the goals were reached, endpoints for sleep (minutes asleep), diet (HEI score), and physical activity (step count and IPAQ score) were categorized into “met goal” or “did not meet goal.” The goal for daily sleep was set at a lower limit of 450 min (7.5 h) due to the National Sleep Foundation's (2020) current recommendation. The HEI goal was set at a score of over 80 per recommendations, while scores between 51 and 79 indicated “needs improvement,” and anything 50 or lower was considered a “very poor” diet (Reedy et al., 2018). The researchers dichotomized reaching the daily step goal as a step value of >7000 steps versus less than this goal (Paluch et al., 2021). Furthermore, nurses were categorized as meeting national physical activity guidelines if reporting 150 min of moderate intensity, 75 min of vigorous intensity, or 150 min of combined intensities on the IPAQ (U.S. Department of Health and Human Services, 2018). Finally, the proportion of nurses who reported that self-care behaviors had worsened since COVID-19 were categorized as having a negative lifestyle change due to the pandemic. Last, correlations were run between continuous, numeric variables via the Pearson's Correlation Coefficient (PCC). Significant correlations with sleep (minutes asleep or rMEQ score), diet (HEI score), or physical activity (step count) were reported with the PCC, also known as “r”, and a p-value. 2.6 Ethical review The study received institutional review board (IRB) approval from the Principal Investigator's healthcare institutional system. All participants provided electronic informed consent prior to initiating the protocol and received a gift card ($50) upon completion. 3 Results 3.1 Participant socio-demographic characteristics A total of 57 nurses participated (Table 1 ). Most of the nurses were female (82.5 %), had a bachelor's degree (77.2 %), had been working their current shift over four years (M = 4.16; SD = 5.22), and reported a stress score of 5.98 on the 16-point scale (SD = 2.79). Most responders indicated that the COVID-19 pandemic did not have an impact on the amount or quality of sleep they were getting each day (70.2 % and 71.9 % reporting no differences, respectively), with no difference in responses between day shift and night shift nurses. Nearly half of responding nurses (47.4 %) reported they were exercising less when compared to pre-pandemic times with no between-shift differences in answers. Finally, many participating nurses (42.1 %) reported their diet had worsened since the start of the COVID-19 pandemic compared to staying the same or improving. Significantly more night shift nurses reported having their diet negatively impacted than those working the day shift (X 2 = 5.88; p = 0.05).Table 1 Study participant characteristics. Table 1 All nurses (N = 57) Day shift nurses (n = 34) Night shift nurses (n = 23) n % n % n % Age Range  21 to 30 years  31 to 40 years  41 to 50 years  51 to 60 years 18 25 8 6 31.6 43.9 14 10.5 7 17 5 5 20.6 50 14.7 14.7 11 8 3 1 47.8 34.8 13 4.3 Gender  Female  Male 47 10 82.5 17.5 24 6 70.6 29.4 19 4 82.6 17.4 Highest RN Degree  Associates  Bachelors  Masters 9 44 4 15.8 77.2 7 7 24 3 20.6 70.6 8.8 2 20 1 8.7 87 4.3 Met PA Guidelines  Yes  No  Missing 32 21 4 60.4 39.6 7 20 13 1 60.6 39.4 2.9 12 8 3 60 40 13 M ± SD M ± SD M ± SD Months Working Current Shift 49.91 ± 62.67 40.21 ± 39.25 64.26 ± 85.59 Body Mass Index in kg/m2 26.22 ± 5.83 25.4 ± 5.08 27.43 ± 6.72 Waist Circumference in inches 33.75 ± 6.13 33.61 ± 6.31 33.95 ± 6.02 Perceived Stress Scale Score 5.98 ± 2.79 5.91 ± 2.73 6.09 ± 2.94 Reduced Morningness-Eveningness Questionnaire Score 14.75 ± 4.24 15.74 ± 3.93⁎ 13.3 ± 4.34⁎ Recorded Minutes of Daily Sleep† 410.75 ± 125.04 409.24 ± 106.98 412.54 ± 144.1 Recorded Daily Step Count‡ 8429.01 ± 5240.47 8732.09 ± 5178.46 8016.4 ± 5324.68 Healthy Eating Index Score during Workdays§ 58.54 ± 10.91 59.51 ± 11.26 56.73 ± 10.34 ⁎ p < 0.05; Abbreviations: Mean plus or minus Standard Deviation (M ± SD); p-value (p). † Forty-one participants provided sleep data over an average of 5.88 days (SD: 1.81). ‡ Fifty-four participants provided step data over an average of 6.83 days (SD: 0.47). § Forty-six participants provided diet data over an average of 2.41 on-duty days (SD: 0.83). 3.2 Sleep findings On the baseline survey, participant self-reported daily sleep quantity averaged 417 min (7.0 h; SD = 74.4) with day shift (m = 409.2 min; 6.8 h; SD = 72.6) and night shift (m = 429 min; 7.15 h; SD = 77.4) estimations being similar. According to sleep actigraphy data (see Table 1) mean daily sleep totaled 410.75 min (6.8 h; SD = 125.04) across the sample while no difference was found between day shift (m = 409.24 min; SD = 106.98) and night shift (m = 412.54; SD = 144.1) nurses. On the rMEQ sleep measurement, day shift nurses (n = 34) scored significantly higher (m = 15.74) than night shift (n = 23; m = 13.3) nurses (p = 0.032), indicating a preference to rise earlier in the day. Day shift nurses attained similar amounts of sleep during both on-duty and off-duty time periods, while night shift nurses did not (see Table 2 ). Individuals working the day shift averaged 406.33 min (6.8 h) of sleep daily (SD = 96.2) during on-duty time periods and 411.43 min (6.9 h) of sleep (SD = 115.08) during off-duty time periods (p = 0.796). Nurses working the night shift averaged only 366.44 min (6.1 h) of sleep (SD = 151.29) during on-duty time periods while sleeping significantly more (448.93 min; 7.5 h; SD = 128.11) during off-duty time periods (p = 0.004). The proportion of day shift nurses who reached recommended sleep quantity between on-duty and off-duty time periods did not differ; however, night shift nurses were significantly less likely to meet the goal during on-duty time periods compared to off-duty time periods (X 2 = 14.27; p < 0.001). During off-duty time periods, significantly more RNs working nights reached the sleep goal compared to those working days (X 2 = 7.39; p = 0.007) (see Table 3 ).Table 2 Differences in sleep quantity between on and off-duty days for day and night shift nurses. Table 2 On-duty days (M ± SD) Off-duty days (M ± SD) On-duty – off-duty between group differences Mean difference p-Value Cohen's d Average daily minutes of sleep  Day shift nurses (n = 23) 406.33 ± 96.2 411.43 ± 115.08 5.11 0.796 0.048  Night shift nurses (n = 18) 366.44 ± 151.29 448.93 ± 128.11 82.49 0.004⁎ 0.594 Abbreviations: Mean plus or minus Standard Deviation (M ± SD). ⁎ p < 0.05. Table 3 Nightly sleep quantity goals met for day and night shift nurses over study. Table 3 Day shift nurses (n = 23) Night shift nurses (n = 18) Day shift – night shift between group differences n % n % X2 p-Value Phi Met daily sleep goal (7.5 h)  All study days  Yes 35 28.9 39 38.2 2.16 0.141 0.098  No 86 71.1 63 61.8  On-duty day observations  Yes 14 26.9 8 17.8 1.15 0.283 0.109  No 38 73.1 37 82.2  Off-duty day observations  Yes 21 30.4 31 54.4 7.39 0.007⁎ 0.242  No 48 69.6 26 45.6 On-duty – off-duty between group differences  X2 0.18 14.27  p-Value 0.673 <0.001⁎  Phi 0.038 0.374 Abbreviations: Percent (%); Chi-square (X2). ⁎ p < 0.05. 3.3 Diet findings Nurses had an average Healthy Eating Index score of 58.54 (SD = 10.91) during on-duty time periods (see Table 1) with no significant differences between day shift and night shift nurses. During the study period, a score of >80 (the cut-off for an optimal diet) was only recorded twice (1.75 %) while a score lower than 50 was recorded 33 times (28.9 %). Nearly one-quarter (23.9 %) of participating nurses averaged a Healthy Eating Index score below 50. 3.4 Physical activity (step) findings Nurses in the sample averaged 8429.01 steps per day (SD = 5240.47) with no difference between day shift (m = 8732.09; SD = 5178.46) and night shift (m = 8016.4; SD = 5324) (see Table 1). All participants averaged 10,587.84 steps daily (SD = 5441.52) during on-duty time periods and 6756.88 steps (SD = 4419.82) during off-duty time periods (p < 0.001). Both groups of nurses averaged significantly more steps during on-duty than off-duty time periods (see Table 4 ). Day shift nurses averaged greater step counts during both on-duty and off-duty time periods compared to night shift nurses, although not statistically significant (see Table 4). A similar relationship was noted when using a cut-off of 7000-steps daily, with a greater percentage of day shift nurses reaching the step goal across all study time periods (see Table 5 ). A significantly smaller proportion of night shift nurses met the step goal during on-duty time periods when compared to day shift nurses. Using the IPAQ, 39.4 % of day shift nurses (n = 13) and 40 % of night shift nurses (n = 8) reported engaging in insufficient minutes of physical activity in the prior 7 days according to national recommendations (p > 0.05).Table 4 Differences in average daily step count between on and off-duty days for day and night shift nurses. Table 4 On-duty days (M ± SD) Off-duty days (M ± SD) On-duty – off-duty between group differences Mean difference p-Value Cohen's d Average daily step count  Day shift nurses (n = 33) 11,296.53 ± 4816.65 6828.79 ± 4597.16 4467.74 <0.001⁎ 0.952  Night shift nurses (n = 21) 9701.37 ± 6091.14 6655.74 ± 4180.13 3045.64 <0.001⁎ 0.594 Abbreviations: Mean plus or minus Standard Deviation (M ± SD). ⁎ p < 0.05. Table 5 Step quantity goals met for day and night shift nurses over study. Table 5 Day shift nurses Night shift nurses Day shift – night shift between group differences n % n % X2 p-value Phi Reached daily step quantity goal  All overserved study days  Yes 134 60.1 87 52.1 2.49 0.115 0.078  No 89 39.9 80 47.9  On-duty observations  Yes 83 87.4 54 72 6.33 0.012⁎ 0.193  No 12 12.6 21 28  Off-duty observations  Yes 51 39.8 33 36.3 0.29 0.591 0.036  No 77 60.2 58 63.7 On-duty – off-duty between group differences  X2 51.4 21.1  p-Value <0.001⁎ <0.001⁎  Phi 0.48 0.356 Abbreviations: Percent (%); Chi-square (X2). ⁎ p < 0.05. 3.5 Correlations between sleep, diet, physical activity, and stress Few significant correlations were observed. Participants self-reported sleep was inversely related to the length of time they have been in the current shift (r = −0.306; p = 0.039) indicating individuals reported less sleep the longer they have been working their shift. Step counts were found to be inversely correlated with PSS-4 score (r = −0.363; p = 0.013) showing nurses taking more steps had lower PSS-4 scores (indicating less perceived stress) and vice-versa. Finally, Healthy Eating Index scores were directly related with rMEQ scores (r = 0.384; p = 0.008) meaning those with higher Healthy Eating Index scores also had higher rMEQ scores, indicating a preference to rise earlier in the day (Danielsson et al., 2019). 4 Discussion In all, 57 acute care nurses across 10 hospitals participated in this technology-based study conducted after the onset of the COVID-19 pandemic. On average, nurses did not sleep per general recommendations for at least 7.5 h per 24 h (National Sleep Foundation, 2020), on-duty diet quality did not reach high-quality scores (Reedy et al., 2018), and nurses did not meet physical activity standards for number of steps taken (Paluch et al., 2021) during off-duty time periods. Few significant differences emerged between night and day shift nurses; notably, night shift nurses were more likely to report a worsened diet quality since the onset of the COVID-19 pandemic, prefer to rise later in the day, and sleep less time during on-duty time periods compared to day shift counterparts. Viewed through the lens of Orem's theory of self-care, it appears that during times of heightened occupational stress, self-care activities among full-time nurses may suffer. Sleep findings from our study indicate significant differences in the sleep attained between day and night shift nurses. This was especially evident when considering the difference between sleep attained by nurses during on-duty versus off-duty periods. Day shift nurses received roughly equivalent sleep regardless of duty, whereas night shift nurses received almost an hour and a half more sleep per 24-hour period when off-duty, suggesting compensating for sleep debt accumulated during the work week. This finding is supported by previous research, including from our own work funded by the Agency for Health Research and Quality (AHRQ) where we found significant differences between sleep attained by day and night shift nurses (James et al., 2020). We found a steady decline in the sleep attained by night shift nurses over the work week (three consecutive 12-hour shifts), leading to accumulation of sleep debt that is partially recovered through longer periods of sleep during days off. The reduction in sleep associated with night shift work is driven by circadian factors which make it difficult for people to sleep during the day to attain sufficient sleep, hence the need to “catch up” (Boivin & Boudreau, 2014). This pattern has repeated itself in prior studies by our team that also indicate night shift nurses revert to nighttime sleep patterns on their off-duty time periods and report worse sleep quality on average than their day shift counterparts (Riedy et al., 2017). Analysis of the Healthy Eating Index (HEI) scores indicated that nurses had a poor diet quality during on-duty time periods. A multitude of individual and social factors can influence eating patterns, particularly among night shift workers (Gupta et al., 2019). It is possible that nurses were under more stress during their workday due to the COVID-19 pandemic, leading to a preference for foods of lower dietary quality that may help temporarily boost mood (van Galen et al., 2021). Essential care workers such as nurses also experienced restricted access to healthy foods amid the COVID-19 pandemic compared to prior availability (Clay & Rogus, 2021). Occupational factors such as availability of on-the-job food choices or break timing may also influence diet quality. In the recruitment sites for this study, on-site cafeterias were closed, leaving foods sold in vending machines, traditionally low in nutritional value, as the only option for food to purchase in the workplace during the duration of the study. Participants were also frequently the recipients of community outpouring and were provided meals both high and low in nutritional value by various vendors while working which could have influenced diet quality. Aside from COVID-19, night shift nurses traditionally have restricted access to the cafeteria due to limited hours open during the night which could impact diet quality during on-duty time periods. Previous work by our team found that nurses report inconsistencies in access to break time (Landis et al., 2021) and lack of resources such as a quiet place to rest (Wilson et al., 2018) which may contribute to poorer eating habits while at work. Sleep disruptions may affect hunger cues which could drive unhealthy eating choices, particularly for night shift nurses. Feelings of hunger as well as plasma ghrelin and leptin levels [the hormones that regulate hunger and appetite] have been shown to be altered when sleep duration is restricted (McHill et al., 2022; Spiegel et al., 2004) which could also explain mechanisms behind our nurses' dietary choices. Our findings displayed a trend toward night shift nurses reporting poorer diet quality while on-duty than day shift nurses, but this finding was not significant. Yet, night shift nurses in our study were more likely to report a worsened diet quality since the onset of the COVID-19 pandemic, indicating these nurses may need more support to follow a healthy diet under times of increased stress. Furthermore, our work suggested higher HEI scores were correlated with a higher rMEQ score, indicating a preference to rise earlier in the day (Danielsson et al., 2019) and aligning with prior studies suggesting that nurses working day shift hours may follow a healthier diet (Yoshizaki et al., 2018). Future research should continue to investigate the connection between diet quality on off-duty versus on-duty time periods and how workplace attributes, sleep patterns, and individual variables contribute to or detract from healthy eating behaviors employed by nurses. On average, nurses in this study met the commonly recommended step goal of 7000 steps daily over the course of a 7-day period (Paluch et al., 2021) although significantly fewer night shift nurses attained this metric compared to day shift nurses. Yet, most nurses were not meeting this step goal during their off-duty time periods. Inadequate physical activity measured by step count may have clinical consequences including increased risk for cardiovascular disease and all-cause mortality which may be mitigated by increased physical activity, even among those walking 7000 steps daily (Sheng et al., 2021). Furthermore, a large proportion of nurses reported their physical activity decreased since the onset of the COVID-19 pandemic. This may have contributed to the relatively low reported physical activity and steps taken during off-duty time periods and aligns with evidence demonstrating fewer steps were taken following lockdown measures aimed at reducing the spread of COVID-19 (Sun et al., 2020). Additionally, a higher number of steps walked significantly correlated with a lower perceived stress score in our study. Given that the overall stress score was higher than norms estimated by prior research (Vallejo et al., 2018), and literature supporting emotional and occupational health benefits of increased physical activity among nurses (Stanulewicz et al., 2019), our study suggests that nurses may reduce stress through increased PA. Further research to enhance nursing engagement in physical activity, even when off-duty and particularly during times of increased occupational stress, are warranted. Our study may have suffered selection bias, given that studies involving applications and devices to document diet (Zhang et al., 2021) or steps (Chaudhry et al., 2020) usually attract participants who are interested in healthy lifestyles. Yet, given our sample size and diverse recruitment strategy, we mitigated this risk and are confident in representativeness of our findings. It is possible that diet may have been incorrectly documented in the ASA24 platform, potentially skewing findings, yet studies support validity of mobile applications to collect diet data (Zhang et al., 2021), and our team opted to use a valid and reliable diet instrument, increasing our confidence in findings. Our pilot study was not adequately powered to detect differences for variables with small effect sizes (<0.1); most effect sizes were moderate or larger, suggesting an adequate sample size to support validity of results. Night shift nurses were unable to accurately submit step data as most wearable pedometers time steps from midnight to midnight, and on-duty time periods likely only reflected steps taken during the first half of the worked shift. However, between-group differences for day and night shift nurses in terms of steps walked when on versus off-duty varied in the same direction, suggesting the variation may not have been clinically significant and increasing confidence in physical activity results. Nurses were not asked about specialty area of practice which could have influenced stress levels as certain specialties were more impacted by COVID-19 than others, yet a strength of study design was standardizing shift length and number of hours worked during the study period among participants. Stress was only measured at baseline and while it encompassed perceived stress in the prior month, more transient changes in stress could not be ascertained. Finally, despite the protocol requiring nurses to work three, 12-h shifts during the seven days of observation, one nurse reported working only two shifts due to illness while others (n = 7) picked up an extra shift due to high incentives to work overtime during short staffing conditions. While a small percentage of the total sample, such variability in work hours should be considered for future health research in this population, especially in the context of a global pandemic. 5 Conclusions While nurses are responsible to provide high-quality care for their patients, environmental conditions such as workforce shortages, increased patient workloads and augmented personal stress can lead to poor self-care strategies and worsened physical and emotional outcomes. According to Orem's self-care theory, when external demands overpower the ability to engage in self-care practices, a self-care deficit is the result. Our findings urge organizations to put resources in place to support nursing self-care practices during on-duty time periods, particularly for those working night shift. Innovative strategies may include providing space for napping when nurses (particularly during night shift) are on break to promote healthy sleep, ensuring access to healthy eating options in the workplace, and providing safe indoor spaces for physical activity such as walking while nurses are working. Promoting healthy self-care practices of nurses, especially during times of heightened occupational stress, can support overall nursing wellbeing and may contribute to improved occupational outcomes such as less missed days of work, less worker's compensation claims, and lower levels of turnover (Salvagioni et al., 2017). The implications for improved patient care and occupational savings can be far-reaching when a healthier nursing workforce is in place. Funding This study received funding from the Selinger Shone Foundation and the Providence Inland Northwest Washington Foundation. The sponsors had no role in the conduct of the study. Declaration of competing interest The authors declared no potential conflicts of interest with respect to the conduct of research, authorship, or publication of this article. Acknowledgments Our study team would like to thank Washington State University collaborators and researchers for donating several wearable devices to make this work feasible. We would also like to acknowledge all Providence and Washington State University students and research assistants who made data entry, cleaning, and analysis possible. We finally acknowledge the Selinger Shone Foundation (2493-3930) and Providence Inland Northwest Washington Foundation (P20-11-23) for generously funding our work. ☆ This study was reviewed by the Providence St. Joseph Health Institutional Review Board and received expedited approval on September 8, 2020 (STUDY2020000434). ==== Refs References Abdulameer S.A. Al-Jewari W.M. Sahib M.N. Psychological health status and salivary IgA among pharmacy students in Iraq: Validation of PSS-4 and WHO-5 wellbeing (Arabic version) Pharmacy Education 19 2019 10 18 Al Maqbali M. Al Sinani M. Al-Lenjawi B. Prevalence of stress, depression, anxiety and sleep disturbance among nurses during the COVID-19 pandemic: A systematic review and meta-analysis Journal of Psychosomatic Research 141 2021 110343 10.1016/j.jpsychores.2020.110343 Boivin D.B. Boudreau P. Impacts of shift work on sleep and circadian rhythms Pathologie Biologie 62 5 2014 292 301 10.1016/j.patbio.2014.08.001 25246026 Caruso C.C. Baldwin C.M. Berger A. Chasens E.R. Edmonson J.C. Gobel B.H. Tucker S. … Policy brief: Nurse fatigue, sleep, and health, and ensuring patient and public safety Nursing Outlook 67 5 2019 615 619 10.1016/j.outlook.2019.08.004 31582105 Chaudhry U.R. Wahlich C. Fortescue R. Cook D.G. Knightly R. Harris T. The effects of step-count monitoring interventions on physical activity: Systematic review and meta-analysis of community-based randomised controlled trials in adults International Journal of Behavioral Nutrition and Physical Activity 17 1 2020 129 10.1186/s12966-020-01020-8 33036635 Chelminski I. Petros T.V. Plaud J.J. Ferraro F.R. Psychometric properties of the reduced Horne and Ostberg questionnaire Personality and Individual Differences 29 3 2000 469 478 10.1016/S0191-8869(99)00208-1 Clay L.A. Rogus S. Impact of employment, essential work, and risk factors on food access during the COVID-19 pandemic in New York state International Journal of Environmental Research and Public Health 18 4 2021 1451 10.3390/ijerph18041451 33557142 Cui S. Zhang L. Yan H. Shi Q. Jiang Y. Wang Q. Chu J. Experiences and psychological adjustments of nurses who voluntarily supported COVID-19 patients in Hubei Province, China Psychology Research and Behavior Management 13 2020 1135 1145 10.2147/prbm.s283876 33312005 Danielsson K. Sakarya A. Jansson-Fröjmark M. The reduced morningness-eveningness questionnaire: Psychometric properties and related factors in a young Swedish population Chronobiology International 36 4 2019 530 540 10.1080/07420528.2018.1564322 30614272 Denyes M.J. Orem D.E. Bekel G. Self-care: A foundational science Nursing Science Quarterly 14 1 2001 48 54 11873354 Berent D. Skoneczny M. Macander M. Wojnar M. The association among health behaviors, shift work and chronic morbidity: A cross-sectional study on nurses working in full-time positions Journal of Public Health Research 2021 10.4081/jphr.2021.2099 Driller M. McQuillan J. O’Donnell S. Inter-device reliability of an automatic-scoring actigraph for measuring sleep in healthy adults Sleep Science 9 3 2016 198 201 10.1016/j.slsci.2016.08.003 28123660 Fitzpatrick T.A. Valentine N.M. Dealing with COVID-19 post-traumatic stress: Strategies for preserving the nursing workforce and supporting all vital frontline personnel Nursing Economics 39 5 2021 225 250 http://www.nursingeconomics.net/necfiles/2021/SO21/225.pdf http://www.nursingeconomics.net/necfiles/2021/SO21/225.pdf Fuller D. Colwell E. Low J. Orychock K. Tobin M. Simango B. Buote R. Van Heerden D. Luan H. Cullen K. Slade L. Taylor N.A. Reliability and validity of commercially available wearable devices for measuring steps, energy expenditure, and heart rate: Systematic review Journal of Medical Internet Research mHealth and uHealth 8 9 2020 e18694 10.2196/18694 Galanis P. Vraka I. Fragkou D. Bilali A. Kaitelidou D. Nurses' burnout and associated risk factors during the COVID-19 pandemic: A systematic review and meta-analysis Journal of Advanced Nursing 77 8 2021 3286 3302 10.1111/jan.14839 (John Wiley & Sons, Inc.) 33764561 Guillodo E. Lemey C. Simonnet M. Walter M. Baca-García E. Masetti V. Moga S. Larsen M. Ropars J. Berrouiguet S. Clinical applications of mobile health wearable–based sleep monitoring: Systematic review Journal of Medical Internet Research mHealth and uHealth 8 4 2020 e10733 10.2196/10733 Gupta C.C. Coates A.M. Dorrian J. Banks S. The factors influencing the eating behaviour of shiftworkers: What, when, where, and why Industrial Health 57 4 2019 419 453 10.2486/indhealth.2018-0147 30404995 Harris P.A. Taylor R. Thielke R. Payne J. Gonzalez N. Conde J.G. Research electronic data capture (REDCap) – A metadata-driven methodology and workflow process for providing translational research informatics support Journal of Biomedical Informatics 42 2 2009 377 381 10.1016/j.jbi.2008.08.010 18929686 Jiang H. Huang N. Jiang X. Jianghong Y. Zhou Y. Hengping P. Factors related to job burnout among older nurses in Guizhou province,China PeerJ 1–16 2021 10.7717/peerj.12333 IBM Corp IBM SPSS statistics for Windows, version 27.0 Released 2020 IBM Corp Armonk, NY Is E.E. Sahillioglu A. Demirel S. Kuran B. Ozdemir H.M. Effect of COVID-19 pandemic on physical activity habits, musculoskeletal pain, and mood of healthcare workers Medical Bulletin of Sisli Etfal Hospital 55 4 2021 462 468 10.14744/SEMB.2021.87523 35317382 James L. James S. Wilson M. Brown N. Dotson E. Edwards C. Butterfield P. Sleep health and predicted cognitive effectiveness of nurses working 12-hour shifts: An observational study International Journal of Nursing Studies 2020 103667 10.1016/j.ijnurstu.2020.103667 Jin D. Halvari H. Maehle N. Olafsen A.H. Self-tracking behaviour in physical activity: A systematic review of drivers and outcomes of fitness tracking Behaviour & Information Technology 41 2 2022 242 261 10.1080/0144929X.2020.1801840 Kellogg M.B. Schierberl Scherr A.E. Ayotte B.J. “All of this was awful:” Exploring the experience of nurses caring for patients with COVID-19 in the United States Nursing Forum 56 4 2021 869 877 10.1111/nuf.12633 34292603 Khubchandani J. Kandiah J. Saiki D. The COVID-19 pandemic, stress, and eating practices in the United States European Journal of Investigation in Health, Psychology and Education 10 4 2020 950 956 10.3390/ejihpe10040067 34542428 Landis T.T. Wilson M. Bigand T. Cason M. Registered nurses' experiences taking breaks on night shift: A qualitative analysis Workplace Health and Safety 69 6 2021 252 256 10.1177/2165079920983018 33514298 Mazurek Melnyk B. Pavan Hsieh A. Tan A. Teall A.M. Weberg D. Jun J. Gawlik K. Hoying J. Associations among nurses' mental/physical health, lifestyle behaviors, shift length, and workplace wellness support during COVID-19: Important implications for health care systems Nursing Administration Quarterly 46 1 2022 5 18 10.1097/NAQ.0000000000000499 34551423 McHill A.W. Hull J.T. Klerman E.B. Chronic circadian disruption and sleep restriction influence subjective hunger, appetite, and food preference Nutrients 14 9 2022 1800 10.3390/nu14091800 35565768 National Sleep Foundation How much sleep do you really need? Retrieved from https://www.thensf.org/how-many-hours-of-sleep-do-you-really-need/ 2020 Neculicioiu V.S. Colosi I.A. Costache C. Sevastre-Berghian A. Clichici S. Time to sleep? A review of the impact of the COVID-19 pandemic on sleep and mental health International Journal of Environmental Research and Public Health 19 6 2022 10.3390/ijerph19063497 Paluch A.E. Gabriel K.P. Fulton J.E. Lewis C.E. Schreiner P.J. Sternfeld B. Sidney S. Siddique J. Whitaker K.M. Carnethon M.R. Steps per day and all-cause mortality in middle-aged adults in the coronary artery risk development in young adults study JAMA Network Open 4 9 2021 10.1001/jamanetworkopen.2021.24516 e2124516-e2124516 Priano S.M. Hong O. Chen J.L. Lifestyles and health-related outcomes of U. S. hospital nurses: A systematic review Nursing Outlook 66 1 2018 66 76 10.1016/j.outlook.2017.08.013 29037501 Prince S.A. Adamo K.B. Hamel M.E. Hardt J. Gorber S.C. Tremblay M. A comparison of direct versus self-report measures for assessing physical activity in adults: A systematic review International Journal of Behavioral Nutrition and Physical Activity 5 1 2008 1 24 18182102 Reedy Lerman Krebs-Smith Subar Kahle Tooze Evaluation of the healthy eating index-2015 Journal of the Academy of Nutrition and Dietetics 118 9 2018 1622 1633 10.1016/j.jand.2018.05.019 30146073 Riedy S.M. English A. Albritton S. Burton J. Himmel M. Morgan P. Kadel K. Van Dongen H. Wilson M. 0169 sleep patterns during duty periods and during off-days between duty cycles in hospital employees working 12-hour night shifts Sleep 40 suppl_1 2017 10.1093/sleepj/zsx050.168 A63-A63 Russell C. Caldwell J.A. Arand D. Myers L. Wubbels P. Downs H. Validation of the fatigue science readiband actigraph and associated sleep/wake classification algorithms 2000 Arch LLC Saeidifard F. Medina-Inojosa J.R. West C.P. Olson T.P. Somers V.K. Bonikowske A.R. Prokop L.J. Vinciguerra M. Lopez-Jimenez F. The association of resistance training with mortality: A systematic review and meta-analysis European Journal of Preventive Cardiology 26 15 2019 1647 1665 10.1177/2047487319850718 31104484 Salvagioni D.A.J. Melanda F.N. Mesas A.E. González A.D. Gabani F.L. Andrade S.M.D. Physical, psychological and occupational consequences of job burnout: A systematic review of prospective studies PloS one 12 10 2017 e0185781 10.1371/journal.pone.0185781 Sheng M. Yang J. Bao M. Chen T. Cai R. Zhang N. Chen H. Liu M. Wu X. Zhang B. Liu Y. Chao J. The relationships between step count and all-cause mortality and cardiovascular events: A dose-response meta-analysis Journal of Sport and Health Science 10 6 2021 620 628 10.1016/j.jshs.2021.09.004 34547483 Sotos-Prieto M. Bhupathiraju S.N. Mattei J. Fung T.T. Li Y. Pan A. Willett W.C. Rimm E.B. Hu F.B. Association of changes in diet quality with total and cause-specific mortality New England Journal of Medicine 377 2 2017 143 153 10.1056/NEJMoa1613502 28700845 Spiegel K. Tasali E. Penev P. Van Cauter E. Brief communication: Sleep curtailment in healthy young men is associated with decreased leptin levels, elevated ghrelin levels, and increased hunger and appetite Annals of Internal Medicine 141 11 2004 846 850 10.7326/0003-4819-141-11-200412070-00008 15583226 Sriharan A. Ratnapalan S. Tricco A.C. Lupea D. Women in healthcare experiencing occupational stress and burnout during COVID-19: A rapid review British Medical Journal Open 11 4 2021 e048861 10.1136/bmjopen-2021-048861 Stanulewicz N. Knox E. Narayanasamy M. Shivji N. Khunti K. Blake H. Effectiveness of lifestyle health promotion interventions for nurses: A systematic review International Journal of Environmental Research and Public Health 17 01 2019 17 10.3390/ijerph17010017 31861367 Sun S. Folarin A.A. Ranjan Y. Rashid Z. Conde P. Stewart C. Cummins N. Matcham F. Dalla Costa G. Simblett S. Leocani L. Lamers F. Sørensen P. Buron M. Zabalza A. Guerrero Pérez A. Penninx B. Siddi S. Haro J. Dobson R. … Using smartphones and wearable devices to monitor behavioral changes during COVID-19 Journal of Medical Internet Research 22 9 2020 e19992 10.2196/19992 Thompson F.E. Dixit-Joshi S. Potischman N. Dodd K.W. Kirkpatrick S.I. Kushi L.H. Subar A.F. … Comparison of interviewer-administered and automated self-administered 24-hour dietary recalls in 3 diverse integrated health systems American Journal of Epidemiology 181 12 2015 970 978 10.1093/aje/kwu467 25964261 U.S. Department of Health and Human Services Physical activity guidelines for Americans 2nd ed. 2018 U.S Department of Health and Human Services Vallejo M.A. Vallejo-Slocker L. Fernández-Abascal E.G. Mañanes G. Determining factors for stress perception assessed with the Perceived Stress Scale (PSS-4) in Spanish and other European samples Frontiers in Psychology 9 37 2018 10.3389/fpsyg.2018.00037 van Galen K.A. Ter Horst K.W. Serlie M.J. Serotonin, food intake, and obesity Obesity Reviews 22 7 2021 e13210 10.1123/jpah.2013-0098 Vigoureux T.F. Mu C.X. Mason T.M. Gonzalez B.D. Lee S. Adapting research to a global pandemic: A fully remote actigraphy and ecological momentary assessment study Nursing Research 71 2 2022 119 127 10.1097/NNR.0000000000000561 35212497 Wilson M. Reidy S. Himmel M. English A. Burton J. Albritton S. Johnson K. Morgan P. Van Dongen H.P.A. Sleep quality, sleepiness and the influence of workplace breaks: A cross-sectional survey of health-care workers in two US hospitals Chronobiology International 35 6 2018 849 852 10.1080/07420528.2018.1466791 Epub ahead of print March 8, 2018 29737881 Yin J. Jin X. Shan Z. Li S. Huang H. Li P. Peng X. Peng Z. Yu K. Bao W. Yang W. Chen X. Liu L. Relationship of sleep duration with all-cause mortality and cardiovascular events: A systematic review and dose-response meta-analysis of prospective cohort studies Journal of the American Heart Association 6 9 2017 e005947 10.1161/JAHA.117.005947 Yoshizaki T. Komatsu T. Tada Y. Hida A. Kawano Y. Togo F. Association of habitual dietary intake with morningness-eveningness and rotating shift work in Japanese female nurses Chronobiology International 35 3 2018 392 404 10.1080/07420528.2017.1410169 29300497 Zhang L. Misir A. Boshuizen H. Ocké M. A systematic review and meta-analysis of validation studies performed on dietary record apps Advances in Nutrition 12 6 2021 2321 2332 10.1093/advances/nmab058 34019624
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==== Front J Chromatogr B Analyt Technol Biomed Life Sci J Chromatogr B Analyt Technol Biomed Life Sci Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences 1570-0232 1873-376X Published by Elsevier B.V. S1570-0232(22)00452-4 10.1016/j.jchromb.2022.123547 123547 Article HPLC-DAD Quantification of Favipiravir in Whole Blood after Extraction from Volumetric Absorptive Microsampling Devices Azzahra Rahmadhani Cahaya a Harahap Yahdiana ab⁎ Aisyah Rahmania Tesia b a Faculty of Pharmacy, Universitas Indonesia, Depok, Indonesia b Faculty of Military Pharmacy, Republic of Indonesia Defense University, Bogor, Indonesia ⁎ Corresponding author. 12 12 2022 12 12 2022 12354713 6 2022 18 11 2022 21 11 2022 © 2022 Published by Elsevier B.V. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Favipiravir is a prodrug of T-1105 made by modifying the pyrazine group as a COVID-19 therapy. During the pandemic, a safe and comfortable biosampling technique is needed for the subject or patient. Volumetric Absorptive Microsampling (VAMS) is a biosampling technique with a small blood volume and minimum hematocrit effect. The aims of this study were to develop and validate an analytical method for quantifying favipiravir extracted from VAMS using High Performance Liquid Chromatography – Photodiode Array with remdesivir as an internal standard. Analysis of favipiravir was performed using a C18 column (Waters, Sunfire™ 5µm; 250 × 4.6 mm), with injection volume of 50 µL, flow rate of 0.8 mL/min, column temperature 30 ℃, and wavelength 300 nm. The separation was conducted under gradient elution with mobile phase consists of acetonitrile-0.2% formic acid-20 mM sodium dihydrogen phosphate pH 3.5 and run time 12 minutes. Sample preparation was carried out using a protein precipitation method with 500 µL of methanol as precipitating agent. Samples were mixed on vortex for 30 seconds, sonicated for 15 minutes, and centrifuged at 10,000 rpm for 10 minutes. Lower Limit of Quantification (LLOQ) obtained was 0.5 µg/mL and the calibration curve ranged from 0.5 to 160 µg/mL. Sensitivity, linearity, selectivity, carry-over, accuracy, precision, recovery, and stability were validated by the guideline from Food and Drug Administration 2018. The method developed has successfully met the full validation requirements by FDA 2018 with the LLOQ obtained was 0.5 µg /mL. Keywords Favipiravir Volumetric Absorptive Microsampling biosampling technique Liquid Chromatography ==== Body pmc1 Introduction Favipiravir is one of the repurposed drugs given to COVID-19 patients in some countries during the pandemic. Favipiravir is a prodrug of T-1105 made by modifying the pyrazine group and works as a substrate for the enzyme RNA dependent RNA polymerase (RdRp), an enzyme that plays a role in the synthesis of viral mRNA in host cells. Favipiravir will be metabolized into a guanine nucleotide analog which will be recognized as a nucleotide base by RdRp so that it will stop the genome replication process that occurs [1]. The in vitro study conducted stated that the EC50 value or the effective concentration to inhibit 50% of SARS-CoV2 in VeroE6 model cells was 61.88 M or equivalent to 9721.35 ng/mL. The target concentration for achieving pharmacological effects in favipiravir therapy is 40-80 μg/mL. The difference between the target concentration range used and the results of in vitro studies may be due to the form of the prodrug favipiravir that must be activated first through ribosylation and phosphorylation in host cells, so that differences in metabolic processes in cultured cells may affect these differences in results [2]. Side effects that can occur are gastrointestinal problems such as diarrhea, nausea, vomiting, and increased blood uric acid and transaminase enzymes such as aspartate aminotransferase (SGOT), alanine transaminase (SGPT), and a decrease in the number of neutrophils [3]. Based on in vitro studies on HEK293 cultured cells, favipiravir can inhibit hERG channels, namely potassium channels in the heart at a concentration of 1000 M or equivalent to 157.1 g/mL [4].Fig 1. Fig 2. Figure 1 Favipiravir chemical structure Figure 2 3D plot of wavelength for favipiravir analysis using remdesivir as internal standards Analysis of drug and/or their metabolites levels can be carried out using the biological samples, including plasma or serum, whole blood, saliva, and breathe [5]. In blood sample collection, the microsampling technique provides greater advantages compared to conventional blood sampling because it is less invasive and easier to send samples from one place to another without having to freeze the samples. One of the recently developed microsampling methods is by using Volumetric Absorptive Microsampling (VAMS). VAMS is a microsampling technique from whole blood by using an absorbent that can absorb volume precisely [6]. VAMS can overcome the problems of the dried blood spot (DBS) technique that has been used since 1963, namely the effect of hematocrit and blood homogeneity [7]. In addition, the use of VAMS could facilitate the sampling process during the pandemic because the use of the finger prick technique so that it is more efficient and can be taken by the patient itself without the need for experts [8]. Several studies have developed favipiravir quantification methods on biological samples using various instruments such as Ultra High-Performance Liquid Chromatography Tandem Mass Spectrophotometry (HPLC-SM/SM) and High-Performance Liquid Chromatography-UV detector (HPLC-UV) [9], [10], [11]. This study aimed to develop and validate an analytical method of favipiravir in VAMS samples using High-Performance Liquid Chromatography-Diode Array Detector (HPLC-DAD) with remdesivir as the internal standard (IS). Hence, it is hoped that this method can be useful for the quantification of favipiravir levels in the blood which can increase the comfort level of the subject. 2 Materials and Methods 2.1 Material Favipiravir was purchased from TRC (USA), Remdesivir as internal standard was purchased from Cayman Chemical (USA), formic acid, acetonitrile, ethanol, methanol, and sodium dihydrogen phosphate were obtained from Merck (Germany), Volumetric Absorptive Microsampling were purchased from Neoteryx (USA), whole blood was obtained from Indonesian Red Cross (Jakarta, Indonesia), and aquabidestilata was purchased from Ikapharmindo (Indonesia). 2.2 Chromatographic Condition for Analysis The analysis was carried out with a High Performances Liquid Chromatography-Diode Array Detector consists of pumps, autosampler, C18 column (Waters, Sunfire™, 5 µ; 250 × 4.6 mm), photodiode array detector (Waters 2996). Separation of favipiravir was conducting using gradient elution conditions with mobile phase consisting of acetonitrile-0.2% formic acid-20 mM sodium dihydrogen phosphate pH 3.5 (Table 1 ). Analysis was performed with a 12 minutes run time, injection volume of 50 µL, column temperature 30 ℃, and wavelength 300 nm.Table 1 Gradient elution profile Time (min) Flow rate (mL/min) Composition of ACN-0.2% FA-20 mM NaH2PO4 pH 3.5 0-6 0.8 20:40:40 6-10 0.8 80:5:15 10-12 0.8 20:40:40 2.3 ACN: Acetonitrile; FA: Formic acidSample Preparation Whole blood containing favipiravir was absorbed with a 45° angle between blood and VAMS. After the tip turning into completely red, the VAMS device was held for 2 more seconds and dried for 2 hours at room temperature. The dried tip was separated from VAMS devices, moved into a microtube, and prepared by protein precipitation method, then 30 µL of IS remdesivir 20 µg/mL and 500 µL of methanol was added to the microtube. Microtube were vortexed for 30 seconds, sonicated for 15 minutes, and centrifuged for 10 minutes at 10.000 rpm. The supernatant was evaporated under N2 gas flow. Dried aliquots were reconstituted with 150 µL mobile phase, vortexed for 30 seconds, sonicated for 10 minutes, and centrifuged for 5 minutes at 10.000 rpm. Afterwards 50 µL of supernatant was injected onto the HPLC-DAD. 2.4 Preparation of Stock Solution and Spiked Blood Standards Stock Solutions of favipiravir or remdesivir were prepared by diluting them in ethanol to obtain favipiravir concentration of 3200 µg/mL and remdesivir concentration of 1000 µg/mL, respectively. Mixture of 20 µg/mL favipiravir and 20 µg/mL remdesivir was made by diluting 3200 µg/mL favipiravir and 1000 µg/mL remdesivir stock solution with ethanol-0.1% formic acid (1:1). Spiked Blood Standards made from 10 µg/mL to 3200 µg/mL working solutions of favipiravir by diluting 25 µL working solutions and internal standards remdesivir with whole blood up to 500 µL. 2.5 Optimization of Favipiravir Analytical Condition Fifty microliters mix solutions of 20 µg/mL favipiravir and 20 µg/mL remdesivir as internal standard was injected into the HPLC-DAD system. 3D Chromatogram (210 nm-400 nm) generated by the system was analyzed to choose the optimum wavelength of the favipiravir and remdesivir mixture. The optimum mobile phase was chosen between a combination of acetonitrile, 20 mM sodium dihydrogen phosphate, and 0.2% formic acid. Optimization of elution profile was conducted using isocratic and gradient elution. Buffer pH was optimized in 3.5, 4, and without adjustment of pH. The mobile phase flow rate was optimized in 0.8, 1.0, and 1.2 mL/min. Lastly, column temperature was optimized at 30, 40, and 45 °C. The optimum analytical condition was then evaluated by a system suitability test. 2.6 System Suitability Test Condition of analysis obtained from optimization must be examined to ensure that the analytical condition and instrument performance are suitable for analysis. Fifty microliters mix solutions of 20 µg/mL favipiravir and 20 µg/mL remdesivir as internal standard was injected into the HPLC-DAD system in six different runs. Coefficients of variation (%CV) for retention time and peak area ratio (PAR) should be <2.0%. Other parameters, namely, resolution, theoretical plates, HETP value, and tailing factor were observed. 2.7 Optimization of VAMS Sample Preparation The sample preparation of VAMS was optimized based on the extraction procedure. Optimization of VAMS drying time was carried out by drying VAMS devices for 1,2, and 3 hours after absorption of spiked blood. Protein precipitation was chosen as method extraction due to the simplicity and time saving properties of the procedure. The extraction solution was selected between ethanol, methanol, acetonitrile, and methanol-acetonitrile (1:1). Vortex time was compared in 15, 30, and 60 seconds. Sonication time was compared in 5, 10, and 15 minutes. Centrifugation time was compared at 10,000 rpm at 5, 10, and 15 minutes. The optimized method obtained from optimization of analytical condition and sample preparation was then validated based on requirements from Food and Drug Administration 2018. 2.8 Method Validation Validation of the analytical method was conducted refers to the requirement of full validation from Food and Drug Administration 2018. Parameters of full validation assessed were sensitivity, linearity, selectivity, carry-over, accuracy, precision, recovery, and stability [12]. 3 Result and Discussion 3.1 Optimization of Favipiravir Analytical Condition The optimum wavelength obtained for analyzing the mixture of favipiravir and remdesivir was 300 nm due to minimum noise observed. Mobile phase combination consists of acetonitrile - 20 mM sodium dihydrogen phosphate pH 3.5 - 0.2% formic acid was found to have the highest peak area and theoretical plates. Analysis was conducted under gradient elution to provide a good chromatogram within 12 minutes. A higher flow rate not only causes a decrease in retention time, but also an increase in column backpressure which made the flow rate of 1.2 mL/minutes produced the highest column backpressure [13]. Therefore, the flow rate of 0.8 mL/minutes was chosen as the optimum flow rate as the analysis produced lower column backpressure and was conducted within 12 minutes. Lastly, a column temperature of 30 °C was chosen because it provided a better theoretical plate as the retention time was slightly decreased. 3.2 System Suitability Test Analytical condition obtained from optimization was evaluated by system suitability test. Analysis of 6 injections showed that %CV of mix solution retention time and peak area was ≤2.0%. The retention time of favipiravir and remdesivir was 6.2 and 10.9 minutes, respectively. All theoretical plates obtained were >2000, resolution >1.5, and tailing factor close to 1. Chromatogram of the mixed solution containing favipiravir and remdesivir solution was shown in Fig.3 .Figure 3 Chromatograms from system suitability test 3.3 Optimization of Favipiravir Sample Preparation Optimizations of sample preparation were carried out by comparing peak area ratio response of different parameters. Optimizations of sample preparation were started with optimization of VAMS drying time. The optimum drying time for VAMS samples containing favipiravir was 2 hours at room temperature. Extraction of favipiravir was carried out with protein precipitation method and 500 µL of methanol was observed to extract more favipiravir compared to another extracting solution, data is shown in Table 2 . The optimum vortex mixing, sonication, and centrifugation time that could extract more favipiravir from VAMS were 30 seconds, 15 minutes, and 10 minutes, respectively.Table 2 Comparation of extraction solution for precipitation protein Extraction Solution for Precipitation Protein PAR Ethanol 2.786 Methanol 3.468 Acetonitrile 2.602 Methanol-Acetonitrile (50:50) 3.193 3.4 Method Validation 3.4.1 Sensitivity Analysis using five replicates of VAMS containing 500 ng/mL favipiravir showed that %diff obtained was –0.66 to 3.13% and %CV obtained was 1.65%. Lower Limit of Quantification (LLOQ) obtained for favipiravir was 500 ng/mL and has met the FDA requirements. Chromatograms of LLOQ showed in Figure 4 .Figure 4 Chromatogram of favipiravir at LLOQ concentration (0.5 µg/mL) 3.4.2 Linearity Calibration samples were prepared using VAMS devices at 7 concentration levels (0.5, 5, 20, 40, 80, 100, and 160 µg/mL), zero, and blank according to the sample preparation procedure explained above. Calibration curves obtained were linear with correlation coefficients of >0.998 (Table 3 ).Table 3 Results of calibration curve in three consecutive days Replicate Slope Intercept R 1 0.00020 0.00304 0.99834 2 0.00019 0.00437 0.99860 3 0.00019 0.00543 0.99825 3.4.3 Selectivity Analysis from 6 diverse sources of matrices showed that there are no interferences detected in the retention time of favipiravir. Furthermore, %interference found in retention time of remdesivir was <5% and showed that analysis method had fulfill the requirements of bioanalytical method validation from FDA (2018). However, interference from other drugs or favipiravir metabolites were not tested. 3.4.4 Carry-over Carry-over test was carried out by injecting the blank samples after the upper limit of quantification (ULOQ), the results on the blank samples should not exceed 20% of LLOQ. Based on the results of this study, no carry-over was found in the blank samples after the injection of ULOQ concentration. 3.4.5 Accuracy, Precision, and Recovery Accuracy and Precision test was conducted by analyzing 5 replicates in 4 different concentration levels, namely, LLOQ (0.5 µg/mL), QCL (1.5 µg/mL), QCM (64 µg/mL), and QCH (120 µg/mL) at three consecutive days. Chromatograms of favipiravir at QCL, QCM, and QCH concentration are shown in Figure 5 , Figure 6 , and Figure 7 , respectively. Accuracy and Precision within and between run are shown in Table 4 .Figure 5 Chromatogram of favipiravir at QCL concentration (1.5 µg/mL) Figure 6 Chromatogram of favipiravir at QCM concentration (64 µg/mL) Figure 7 Chromatogram of favipiravir at QCH concentration (120 µg/mL) Table 4 Results of accuracy and precision within-run and between-run Actual conc. (μg/mL) Within-run Between-run Measured concentration (Average ± SD; μg/mL CV (%) %diff Measured concentration (Average ± SD; μg/mL CV (%) %diff 0.5 0.51±0.046 9.20 -8.34 to 10.97% 0.49±0.047 9.62 -12.57 to 13.70% 1.5 1.35±0.090 6.66 -13.75 to 0.80% 1.41±0.109 7.74 -14.94 to 4.95% 64 56.44±2.562 4.54 -13.60 to -4.70% 59.75±4.591 7.68 -14.31 to 12.12% 120 115.67±4.849 4.19 -9.06 to 0.53 % 113.87±3.757 3.30 -9.06 to 0.53% The recovery test was carried out using 3 levels of concentration, namely, QCL, QCM, and QCH. The efficiency of extraction was assessed by comparing pre- and post-extraction samples. Pre-extraction samples were made by spiking a certain concentration of favipiravir standard solution in whole blood and prepared on VAMS according to the procedure above. Post-extraction samples were made by extracting the blank samples first, then spiking the supernatant with favipiravir standard solution in the same concentration. The results of the recovery test are shown in Table 5 .Table 5 Recovery of Favipiravir in VAMS Actual concentration (μg/mL) Replicate Recovery (Average±SD; %) CV (%) 1.5 3 70.53±0.91 1.29 64 3 69.39±0.51 0.73 120 3 73.30±0.97 1.33 The study conducted using 3 replicates of sample. The study conducted using 3 replicates of sample.From the data above, it is shown that the extraction recovery of this study was in range of 69.39% to 73.30% which is lower than previous study that conducted using plasma sample and extracted by liquid-liquid extraction method [14]. However, it is shown that the method can still delivered the accurate and precise results with short time extraction using simple protein precipitation method. 3.4.6 Stability Stability evaluation performed includes stock solution stability, short term stability in VAMS, long term stability in VAMS, autosampler stability, and heat stability. Stock solution favipiravir was stable for 6 hours at room temperature and 30 days at refrigerator temperature (2-8 °C). Stock solution remdesivir was found stable for 24 hours at room temperature and 7 days at refrigerator temperature (2-8 °C). The short-term stability test was performed by storing VAMS at room temperature for 0, 6, and 24 hours. The results showed that favipiravir in VAMS was not stable for 6 hours at room temperature because %diff and %CV obtained were >15.0%. (Table 6 ). Therefore, further stability evaluation of favipiravir in VAMS at room temperature for less than 6 hours can be conducted to determine the stability of favipiravir in VAMS. The long-term stability test was performed at –20 °C freezer for 0, 7, and 28 days (about 4 weeks). The results showed that favipiravir in VAMS was stable enough at –20 °C freezer for 28 days (Table 7 ). Autosampler stability was assessed by storing extracted samples in the autosampler for 24 hours. The results showed that favipiravir was stable at autosampler for 24 hours (Table 8 ). Lastly, a heat stability test was performed to observe the stability of favipiravir at the temperature used to inactivate infectious samples (56 °C for 30 minutes). Favipiravir is one of the drugs given to COVID-19 patients and analyzing favipiravir in patient’s blood should be done with the inactivation process. The results showed that heated samples were stable for 14 days at –20 °C freezer (Table 9 ).Table 6 Short-term stability of Favipiravir in VAMS at room temperature Hours QCL (1.5 μg/mL) QCH (120 μg/mL) Measured concentration (Average ± SD; μg/mL CV (%) %diff Measured concentration (Average ± SD; μg/mL CV (%) %diff 0 1.61±0.032 2.01 5.03 to 8.95% 114.75±2.075 1.81 -5.91 to -2.51% 6 0.73±0.121 16.56 -60.14 to -44.49% 114.37±2.552 2.23 -6.11 to -2.25% 24 0.67±0.021 3.24 -56.62 to -53.88% 94.95±16.789 17.87 -29.97 to -5.55% Table 7 Long-term stability of Favipiravir in VAMS at -20 °C freezer Days QCL (1.5 μg/mL) QCH (120 μg/mL) Measured concentration (Average ± SD; μg/mL CV (%) %diff Measured concentration (Average ± SD; μg/mL CV (%) %diff 0 1.61±0.032 2.01 5.03 to 8.95% 114.75±2.075 1.81 -5.91 to -2.51% 7 1.35±0.084 6.31 -14.14 to -3.68% 122.29±11.502 9.41 -9.16 to 7.54% 28 1.46±0.124 8.52 -9.38 to 6.40% 117.92±5.380 4.56 -4.35 to 3.44% Table 8 Autosampler stability of Favipiravir for 24 hours Hours QCL (1.5 μg/mL) QCH (120 μg/mL) Measured concentration (Average ± SD; μg/mL CV (%) %diff Measured concentration (Average ± SD; μg/mL CV (%) %diff 0 1.61±0.032 2.01 5.03 to 8.95% 114.75±2.075 1.81 -5.91 to -2.51% 24 1.51±0.191 12.72 -6.33 to -2.93% 122.93±12.401 10.09 -4.47 to 14.33% Table 9 Heat stability of Favipiravir at 56 C° for 30 minutes Conditions QCL (1.5 μg/mL) QCH (120 μg/mL) Measured concentration (Average ± SD; μg/mL CV (%) %diff Measured concentration (Average ± SD; μg/mL CV (%) %diff Not heated 1.43±0.097 6.83 -11.10 to 1.92% 115.66±1.107 0.96 -4.63 to -2.82% 56℃/30 min 1.47±0.131 8.91 -9.95 to -1.91% 106.46±3.030 2.85 -14.2 to -9.74% 56℃/30 min + 7 days 1.38±0.086 6.23 -13.59 to -2.16% 116.17±3.026 2.61 -5.37 to -0.43% 56℃/30 + 14 days 1.38±0.035 2.56 -10.01 to -5.32% 116.49±0.564 0.48 -3.44 to -2.53% The study conducted using 3 replicates of sample. The study conducted using 3 replicates of sample. The study conducted using 3 replicates of sample. 4 Conclusion The method developed for favipiravir quantification has met the full validation requirements by Food and Drug Administration 2018. LLOQ obtained was 500 ng/mL and linear calibration curves obtained with range of 0.5 to 160 µg/mL. The method developed can be applied to quantify levels of favipiravir in human’s blood with more comfortable and less invasive biosampling techniques. Declarations Author contribution statement All authors listed have significantly contributed to the development and the writing of this article Funding statement This work was supported by Universitas Indonesia Data availability statement Data included in article/supplementary material/referenced in article. Additional information No additional information is available for this paper. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data availability Data will be made available on request. ==== Refs References 1 Zhu W. Chen C. Gorshkov K. Xu M. Lo D. Zheng W. RNA-Dependent RNA Polymerase as a Target for COVID-19 Drug Discovery SLAS DISCOVERY: Advancing the Science of Drug Discovery. 25 10 2020 1141 1151 2 Du Y, Chen X. Response to “Dose Rationale for Favipiravir Use in Patients Infected With SARS‐CoV‐2”. Clinical Pharmacology & Therapeutics. 2020;108(2):190-190. 3 Joshi S. Parkar J. Ansari A. Vora A. Talwar D. Tiwaskar M. Patil S. Barkate H. Role of favipiravir in the treatment of COVID-19 International Journal of Infectious Diseases. 102 2021 501 508 33130203 4 Pharmaceuticals and Medical Devices Agency. Report on the deliberation results Avigan Tablet 200 mg. [Internet]. 2014 [cited 2021 Jul 29]. Available from: https://www. Pharmaceuticals and Medical Devices Agency.go.jp/files/000210319.pdf 5 Junaid T. Wu X. Thanukrishnan H. Venkataramanan R. Therapeutic Drug Monitoring 2019 Practice and Research Clinical Pharmacy Education 425 436 6 Kok M. Fillet M. Volumetric absorptive microsampling: Current advances and applications Journal of Pharmaceutical and Biomedical Analysis. 147 2018 288 296 28803682 7 Qu Y. Brady K. Apilado R. O’Malley T. Reddy S. Chitkara P. Ibarra C. Alexander R. Dervieux T. Capillary blood collected on volumetric absorptive microsampling (VAMS) device for monitoring hydroxychloroquine in rheumatoid arthritis patients Journal of Pharmaceutical and Biomedical Analysis. 140 2017 334 341 28391006 8 Harahap Y. Diptasaadya R. Purwanto D. Volumetric Absorptive Microsampling as a Sampling Alternative in Clinical Trials and Therapeutic Drug Monitoring During the COVID-19 Pandemic: A Review Drug Design, Development and Therapy. 14 2020 5757 5771 33414636 9 Moriiwa Y. Morikawa G.o. Okazawa K. Yanagida A. Optimization of Analytical Procedure for In-hospital Rapid Quantification of Serum Level of Favipiravir in the Pharmacological Treatment of COVID-19 Analytical Sciences. 37 9 2021 1301 1304 33612558 10 Sağlam O. Demiray G. Güney B. Doğan-Kurtoğlu E. Ulusoy M. Saraner N. Sevici G. Nacak M. Erenmemişoğlu A. Tüzer V. Single Dose, Two-way Crossover Bioequivalence Study of Favipiravir Tablet in Healthy Male Subjects Journal of Pharmacy and Drug Development. 2020 11 Morsy M.I. Nouman E.G. Abdallah Y.M. Zainelabdeen M.A. Darwish M.M. Hassan A.Y. Gouda A.S. Rezk M.R. Abdel-Megied A.M. Marzouk H.M. A novel LC-MS/MS method for determination of the potential antiviral candidate favipiravir for the emergency treatment of SARS-CoV-2 virus in human plasma: Application to a bioequivalence study in Egyptian human volunteers Journal of Pharmaceutical and Biomedical Analysis. 199 2021 114057 33831737 12 U.S. Food and Drug Administration. 2021 [cited 2021 Aug 16]. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/bioanalytical-method-validation-guidance-industry 13 Cabo-Calvet E. Ortiz-Bolsico C. Baeza-Baeza J. García-Alvarez-Coque M. Description of the Retention and Peak Profile for Chromolith Columns in Isocratic and Gradient Elution Using Mobile Phase Composition and Flow Rate as Factors Chromatography. 1 4 2014 194 210 14 Hailat, Mohammad et al. “Development And Validation Of A Method For Quantification Of Favipiravir As COVID-19 Management In Spiked Human Plasma”. Molecules, vol 26, no. 13, 2021, p. 3789. MDPI AG, https://doi.org/10.3390/molecules26133789.
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==== Front Int J Educ Res Open Int J Educ Res Open International Journal of Educational Research Open 2666-3740 The Authors. Published by Elsevier Ltd. S2666-3740(22)00095-4 10.1016/j.ijedro.2022.100219 100219 Article The effects of Covid-19 pandemic on the education system in Nigeria: The role of competency-based education Okagbue Ekene Francis ab⁎ Ezeachikulo Ujunwa Perpetua bc Nchekwubemchukwu Ilokanulo Samuel ab Chidiebere Ilodibe Emeka ab Kosiso Obisoanya bd Ouattaraa Cheick Amadou Tidiane ab Nwigwe Esther Onyinye ab a Faculty of Education, Southwest University, Chongqing, China b Organization of African Academic Doctors (OAAD), P.O. Box 14833-00100, Langata, Nairobi, Kenya c Faculty of Education, Southwest University, Chongqing, China. Department of Sociology, School of Public Administration, Hohai University, Nanjing, China d College of International Study, Southwest University, Chongqing, China ⁎ Corresponding author. 12 12 2022 2023 12 12 2022 4 100219100219 18 8 2022 3 12 2022 4 12 2022 © 2022 The Authors 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Covid-19 revealed the strengths and weaknesses in the global education atmosphere in both developed and developing countries. To that effect, this current study explored the impacts of the covid-19 pandemic on Nigeria's education system and in the process provided a distinctive solution to the challenges facing the sustainability of education in the country. However, the closure of schools for over six months at the onset of the covid -19 pandemic, and the inability of schools to engage learners in educational activities while at home also revealed the poor state of the education system in the country, which led to the discovery of the unavailability of distance online education, web-based learning system and ICT infrastructure in the Nigerian education environment. Covid-19 incidence impacted the stability of the academic calendar, caused teachers attrition, increased the rate of students dropout, and lack of interest in digital education. These outcomes resulted in the exploration of students' and teachers’ perceptions, attitudes, literacy, competency, and willingness to engage in distance online education. A cross-sectional approach was applied through an online survey to obtain data from n = 82 learners across the three levels of institutions. And SPSS was used to analyze the demography data, while SMART PLS was used for structural equation modeling (SEM). The study outcome satisfied the objectives of the study that the lack of student-teacher digital competencies influences their perception and acceptability of web-based learning approach and use of smart learning and teaching devices. Keywords Effects of Covid-19 Online distance education Competency-based education ICT Nigeria ==== Body pmc1 Introduction Since the emergence of COVID-19 to date, Nigeria's education system has suffered unprecedented setbacks, and continuously experiencing the impact of Covid-19 after the long shutdown period of the schools as a result of the ravaging nature of the pandemic (Crawford et al., 2020). For almost three years, there is staggering growth in education development as other variants of the virus mutated such as the Delta variant, Omicron variant, etc. This has increased the fear and tension for the school leadership on the possibility of a second lockdown of the academic institutions (Samuel, 2020). The conditions of the first lockdown of schools that lasted for over six months have quadrupled the retrogressive situations of Nigeria's education, such as the high rate of teachers’ attrition (Alhat, 2020), school dropout percentage has risen dramatically as students do not fancy going to schools as to avoid the unknown outcome of the virus and its mutational potency in affecting their lives (Lee, Malcein, & Kim, 2021). The reports that the pandemic would still exist beyond its anticipated period attributed to the attritional and dropout rate in Nigerian schools, coupled with not being totally immune from getting infected after being vaccinated (UNESCO-IESALC, 2020). Hence, the fear of the unknown caused by the widespread of the virus and the mortality tendencies led to teachers' attritions and students' withdrawals from school (Hu et al., 2021). As of now, school administrators are finding it difficult to get the teachers and students back to school to continue teaching and learning as a result of long-term school closure (Samuel, 2020). These issues occurred due to the lack of implementing alternative means to engage students in educational activities during the lockdown period (Jowsey, Foster, Cooper-ioelu, & Jacobs, 2020). In addition, financial condition is perceived as a factor causing the hesitancy of students and teachers returning to school (Amir et al., 2020). The majority of the parents feel that the tuition paid before the lockdown was not adequately implemented in ensuring continuous learning activity at home, therefore need the assistance of their kids in making enough monies for their schooling (Crawford et al., 2020). Evidently, the lack of implementing blended teaching and learning system before the emergence of the Covid-19 pandemic has creates a huge divide and irregularities in the Nigerian education systems (Adefuye, Adeola, & Busari, 2021). One crucial function of a blended or virtual learning system is its transformability tendency in increasing the competency base learning of the students and the teachers. Numerous studies underscored that distance education played a significant role in sustaining educational programmes during the covid-19 outbreak in some nations (Songsom, Nilsook, Wannapiroon, Fung, & Wong, 2019). Distance education or online education has become a sophisticated validated teaching and learning tool in this 21st century to support pedagogical activities having the potency to build competent teachers and students (Khan & Abid, 2021). Countries with advanced distance education like the USA, Estonia, Canada, China, Germany, France, etc are testimonies to Khan and Abid's (2021) assertion on distance education is a tool to inculcate competencies and innovative mindset both the teachers and students teaching and learning abilities. Another benefit of distance education is the tendency to enhance smart learning culture thereby exposing teachers and students to the understanding and use of intelligent learning devices efficacy (Lee et al., 2021). Also, the engagement of students in the blended learning atmosphere improves students' confidence and creates inner trust in believing in the learning behavior (King, Pegrum, & Forsey, 2018). Consequently, Chaichumpa et al. (2021) state that learning institutions with the incorporation of web-based tutoring and learning smart technologies help in elevating the positive learning behaviors of the students and improving their digital ability. Furthermore, distance online education enhances adequate personalized learning and strengthens users' confidence and competency. Similarly, teaching remote or online classes requires teachers to possess a considerable amount of digital skills with apt understanding to be able to influence learners with positive competency (Lee, 2020). For example, one of the salient skills teachers ought to have in digital education is the ability to issue personalized feedback through smart devices, prepare teaching content to meet learners learning capability, increase flexibility in learning for students and ability to use different smart devices, and learning APPS that elevate their cognitive ability and brain power (Farber, 2013). In furtherance, this current study aims to give an in-depth overview of the struggles the education sector has witnessed especially the Nigerian schools during the covid-19 period, however, from the extensive explorations of literature on this discourse, the authors discovered strands of studies focused majorly on medical aspects of coronavirus on individual's health, such as the (i) influence of Covid-19 on mental health (Krohn et al., 2021), (ii) individual's breathing (Liu et al., 2021), (iii) psychological impacts on the medical practitioners and students (Martínez, Lázaro, Gómez, & Fernández, 2020). Meanwhile, amongst all the studies done on Covid-19 related phenomena, fewer studies have explored the impacts of covid-19 on the Nigerian education sector focusing on the need for distance education and web-based learning as the new trend (Oyebode, 2020). Students from different Nigerian academic institutions revealed the reasons they couldn't engage in academic activities at home are due to lack of online learning apps for a synchronous mode of learning, poverty, lack of internet connectivity, lack of digital literacy, lack of ICT teaching and learning devices such as computer desktops, projectors, screens, to engage students for immersive learning at homes. In addition, many students lamented that not engaging in learning for over six months of lockdown affected their psychological, emotional, and mental breakdown, including the development of acute depression syndrome (Adefuye et al., 2021). In defense of the failure of school administrations in finding alternative learning means for the students, Oyebode (2020) opined that schools have no wherewithal to fund distance education and remote learning systems, and there reduce the competencies in education. Interestingly, the study sets to examine the students' and teachers' competency, perception, internet/computer literacy or skill, attitude, and willingness to execute their classroom activities and learn remotely. the core focus of the paper is to understudy teacher-student competency, willingness, attitude, literacy or skill, and perception of distance education, web-based learning, remote learning, etc as it is predicted to be the new normal for education sustainability in post-covid-19 education (Dhawan, 2020). Sanches (2020) reinforces that the adoption of distance education can protect education from the brink of collapse in future pandemics or any unforeseeable social crises (Sanches, 2020). In line with this purpose, the research questions that drive this study centered on; RQ1: How feasible can distance online education be in Nigerian Schools for competency-based education? RQ2: To what extent can teachers and students accept distance online education as an alternative means of learning and teaching for competency development? In order to elevate competency-based education in the country's education through distance education, the article thereby suggests the need for professional training programs for educators and teachers with no ICT competency and computer knowledge for effective teaching. At the same time inform the education policymakers, stakeholders, and school leaders see the need of institutionalizing distance online education to protect learners' future. 2 Summary of literature review Digital distance education is inevitably quintessential in this 21st century, thus making teaching and learning more seamless. However, it makes education convenient and efficient for teachers and learners to teach and learn (Boca, 2021). Digital distance schooling transcends conventional and traditional modes of education into an electronic system of schooling (Alhat, 2020). Numerous researchers revealed the submissions of students from different levels of education on online distance education stating its acceptability, flexibility, and influencing power to search for more information (Naidu, 2014). Many students confirmed that learning online improves their attention rate to assimilate what has been taught and heightened their intentional learning behavior more than face-to-face classes. An effective virtual classroom is achieved through adaptative learning possibilities with virtual learning technologies (Boca, 2021). Evans and Moore (2012) opined that exposing students to ICT devices for their personalized learning provides an avenue for deep learning and in-depth learning behaviour for self-development. Evidently, Covid-19 hastened the quest for internet-inclined schooling to be fostered in academic institutions across the globe (Alhat, 2020). The Covid-19 incident created universal awareness of education digitization globally. Additionally, the incidence of the pandemic awakened the consciousness of the African education system especially Nigeria in charting a new part for the unprecedented education evolution with technology (Singh & Thurman, 2019). This created a new pathway for educational reformulation and a total overhaul in knowledge delivery tactics (Parmigiani, Benigno, Giusto, Silvaggio, & Sperandio, 2021). Distance digital schooling illuminated plentiful benefits, as iterated above that the remote pedagogical approach encompasses synchronous and asynchronous characteristics that improve the learning behavior of the students and web-based education (Haghshenas, 2019). Student-teacher usability of ICT devices and educational applications (APPS) triggers some sort of responsibility to learn and revise the recorded classes with the playback function (for students), and teachers volitiously attempt significant ways to stimulate instructional activities in the virtual learning environment (Amir et al., 2020). The ability of distance online education learning devices to provide timely assessment and feedback encourages spontaneous readjustment in the student's academic performance and attitude (Cavalcanti et al., 2021). Also, the artificial intelligence and machine learning features in some teaching applications give high precisional grading scale feedback. Proper inclusive education has been realized from online instructional pedagogy (Tedre et al., 2021). Teachers' and students' skills are said to attain greater heights from their engagements in digital educational activities (Parmigiani et al., 2021). Arguably, teaching APPS such as Tencent/Voov, DingTalk, Skype, etc is pivotal in content delivery in electronic education. An appropriate pedagogical teaching and learning APPS makes distance and electronic education enjoyable and convenient (Sayibu et al., 2021). The chatbox in the digital learning applications helps in smooth communication during online classes, this also motivated learners to ask questions without being intimidated. In relation to the covid-19 period, it is evidenced that distance online education was claimed to be a factor in the student-teacher insignificant mortality rate from being affected by the virus, thus bringing life security and reducing the human transferability potency of the virus (Parmigiani et al., 2021). The first research question raises concern about the feasibility of distance online education in Nigerian schools for competency-based learning. Given the level of the digital divide, this questions the attainability of this purpose with the intense digital disparity across the country. For instance, the digital divide in the Nigerian education domain is extremely pronounced, invariably affecting the achievement of progressive distance online education integration in the educational atmosphere (Ajadi et al., 2008; Alkaria & Alhassan, 2017; Kpae, 2020). Hence, creating a lack of self-confidence and lack of trust in teachers and students (Jou, Tennyson, Wang, & Huang, 2016). The posing threat to the feasibility is the non-existential of the ICT framework in the schools, this is the result of the non-participation of the education stakeholders and administrative leadership in investing substantively in the education sector. The appropriated financial resources for the education sector are insignificant to achieving this aim due to the insufficiency of the allocated funds (Oboh Stephen & Oboh Omonyemen, 2020). The second challenges are the unawareness of the distance of education, poverty, and negative perception by the teachers, parents, and students on the use of digital devices for personalized and autonomous learning both in and outside the school vicinity (Reinhart et al., 2021). This necessitated the lack of digital competency, literacy, and skills for a great percentage of students and teachers. However, the political and economic factors are the causatives of the poor digital education application across the education system (eLearning Africa, 2020). Furthermore, factors such as unsteady power supply, unavailability of unlimited internet connectivity, shortage of ICT framework in an education environment, and high prevalence of poverty constitute the influencing factors to the unavailability of distance education infrastructure (De Giusti, 2020). The negligence of electronic learning implementation deprives about 25 million learners of education for almost six months (Agbele & Oyelade, 2020). For absolute incorporation of distance and virtual learning, teachers' professional training is deemed critical and crucial for instructional efficiency and effectiveness. The rigorousness and technicalities of ICT and smart technological education devices ought to be taught to teachers and students for a complete understanding of the operationalities of the devices (Scull et al., 2020). The TPD (teachers' professional development and training) equips teachers adequately on how to deliver content, and stimulate learning, thereby training students on the usability and applicability of smart education devices for their autonomous learning (Amir et al., 2020). Instructors ' and teachers ' digital literacy is essential to achieve maximum efficiency of blended learning with the internet and cloud-based devices. Also, regular professional training programs for improvement are pivotal. Boling et al.'s (2012) study applied the cognitive apprentice model to expound on the educational benefits of computer-mediated learning for learners' effective learning. They further stated that the attainment of cognitive ability in a web-based environment lies in the teachers' teaching strategy to engage the learners. That achievement lies in the four tested CAM parameters, interactions, sociology, sequencing, content, and method. Additionally, Affouneh, Salha, and Khalaf (2020) postulated eight frameworks and dimensions of electronic education learning; "(1) institutional, (2) pedagogical, (3) technological, (4) interface design, (5) evaluation, (6) management, (7) resource support, and (8) ethics"(Affouneh, Salha, & Khlaif, 2020). Nigerian education system yearns for a total overhaul and institutional restructuring including curriculum adjustment to accommodate the characteristics of online distance education. According to Boiling et al. (2012) postulation on the financial cost of online education delineated that remote education is relatively cheaper than the face-to-face approach (Boling, Hough, Krinsky, Saleem, & Stevens, 2012). The second research question tries to assess the readiness of the students and teachers to accept remote learning and distance online education. Numerous scholarships revealed that perception, and willingness to try new things bring acceptability, and a positive attitude to explore learning devices (Filho, Price, Wall, Shiel, & Azeiteiro, 2021). As distance online education or web-based learning system is a new concept in the Nigerian education environment, adequate sensitization is needed to enlighten the public on its benefits of it. To achieve that joint efforts by the school leaders and ministries of education would be effective in creating awareness to minimize the negative perceptions of web-based education. Nilsen, Almås, and Gram (2020) suggested the practicability of teaching and learning with smart devices and ICT should be adopted at the early stage of education for competency and raising of technocrats. In order to promote education sustainability, an adequate propagation of the essence of digital and distance education ought to be widely communicated to the schools' leaders, parents, students, and the general society for a complete understanding (Albrahim, 2020; Stewart & Lowenthal, 2021; UNESCO, 2020). Regardless of the strengths of DOE (distance online education), some scholars (Distler, 2015; Ma et al., 2022; Rizun & Strzelecki, 2020) hold contrasting views on its tendency to influence progressive learning, some scholars argued that the removal of conventional teaching styles might reduce the learning and teaching interest of the students, thereby causing learners' poor performance and teachers quitting their jobs (Chen et al., 2020). The conventional teaching method of the face-to-face approach cannot automatically be displaced due to the nature of some courses like STEM programmes with laboratory and experimental components (Bacon & Peacock, 2021). The systematic approach that is designed to balance e-learning is the blended learning forum, this learning methodology entails face-to-face and web-based teaching and learning systems (Series, 2021). This satisfies the argument of (Bacon & Peacock, 2021) on the traditional way of teaching will not be annihilated in place of digital distance education. According to (Batdı, Doğan, & Talan, 2021) the combination of these two concepts of learning (i) physical learning mode and (ii) technology enhance learning strategically creates an intense competency level in teachers and students. The cointegration of these two modes of instruction and schooling sustains the looming pandemic that is still on the rise to avoid the reoccurrence of school closure during the initial lockdown. Conclusively, digital education, virtual learning, distributed learning, mobile learning, etc, have restored the hopes of education as a means to mitigate the unforeseeable incidence that might affect the bearing of education (Adefuye et al., 2021). 3 Methods and materials 3.1 Study design The cross-sectional survey was structured to cover the three levels of education, primary, secondary and higher education. The questionnaire covered the main focus questions in conjunction with the reports on the effects of coronavirus on the Nigerian education system. The electronic questionnaire was shared to capture the perception of pupils and students in the above-mentioned education levels to get their responses on the acceptability of distance online education. Also, the distributed electronic questionnaire was created with a single link that validated the study with a pilot study, from which 82 responses were gotten were quantitatively analyzed. Thus, the hypotheses of the study were tested alongside the validated variables as structurally expressed in Table 1 . Further exploration and robust analysis, research parameters such as correlation, significance testing, and good model fitness were inductively reported.Table 1 Explanation of the variables and hypotheses predictors. Table 1Variables Descriptions Authors Competency Possession of Pedagogical competencies and knowledge of remote learning skills with an understanding of synchronous and asynchronous dimensions of a digital classroom. (Addleman et al., 2014; Alkaria & Alhassan, 2017; Stickler, Hampel, & Emke, 2020) Perception It is perceived feelings and beliefs of the assessment of an individual's technical know-how of web-based instruction and operation of ICT gadgets to accepting or rejecting remote learning. (Awotokun, 2016; Bayram, 2013; Wang, 2014) Attitude Intentions and behaviour of accepting or rejecting virtual learning, and the knowledge of how to use digital devices. (Addleman et al., 2014; Milovanović et al., 2020; Stickler et al., 2020; Wu, Hu, & Wang, 2019) Literacy/skills This entails the acquisition of computer literacy and skills in the operations of smart devices including learning software. (Awotokun, 2016; Samuel, 2020; Wu et al., 2019) Willingness The total acceptance to opt for mobile learning as a means of schooling, simultaneously possessing a significant competency level to try a new phenomenon. (Almaiah, Al-Khasawneh, & Althunibat, 2020; Cicha et al., 2021; Larreamendy-Joerns & Leinhardt, 2006) Table 2 Study hypotheses and dimensions, Fig. 1. Table 2Hypotheses Dimensions H1 Competency is positively associated with the attitude of teachers and learners to digital distance learning. H2 Attitude has a positive effect on willingness to accept distance learning. H3 Competency is positively associated with perception. H4 Perception has a positive influence on digital literacy and ICT skills. H5 Perception has a positive effect on willingness. H6 Competency has a positive on literacy and skill. H7 Attitude influences literacy and skills H8 Computer literacy and skill are positively associated with the willingness to accept online distance education. 3.2 Data collection approach As stated earlier that data collection was targeted at three categories of education (primary, secondary, and higher education). However, it is important to state that no data was gathered from the primary school level. This was so due to the inability of learners at this level of education to comprehend the contents of the questionnaire, and the lack of digital devices to answer the questions. As a result, the study explored the responses obtained from secondary school and higher education. Although the questionnaire was an electronic version, the age of the participant was also considered in responding to the questionnaire. Given the outcome from the primary school level, the authors targeted secondary school students from the age of 18 upwards and higher education students that can understand the questions and provide reasonable answers to questions, and also must have smart devices to provide their responses electronically. Notably, the questionnaire link was shared with the teachers in these three levels of education using the requirements set by the authors to select eligible respondents for the study. Nonetheless, the data collected measured the competency, perception, attitude, literacy/skill, and willingness of the students to switch to web-based learning. Finally, the total respondents of (n = 82) were statistically logical to represent the study population. 3.3 Study model (1) Ywi=α+β1compt1+β2percept2+β3atti3+β4lit4+ε The mathematical linear model equation explores the linearity of the estimated variables of the study. Wi = the independent variable, willingness, compt = competence, percept = perception, atti = attitude, lit = literacy, ε = error term 3.4 Procedure and measures Distributed digital survey link shared has comprehensive six structured constructs with 34 items. The study established its independent or outcome variable to be willingness; this implies the willingness of the learners and teachers' acceptability determines the degree of effort the education policymakers and stakeholders to implement structures for digital learning (Crawford et al., 2020; Lee, 2020; Parmigiani et al., 2021; Wear & Levenson, 2004). The participants were questioned on "their willingness to accept online distance learning." The questions were streamlined to assess students' willingness and attitude in considering online distance education for their personal academic growth (Cicha, Rizun, Rutecka, & Strzelecki, 2021). Dependent variables: The dependent variables that lead to willingness are competency, perception, attitude, and literacy/skill (mediator). The description of the variables is detailed in Table 1. The itemized constructs explore the measurement of these variables. 3.5 Data analysis 3.5.1 Descriptive analysis The descriptive analysis illustrates the demography variables of the study such as gender, age, education, school category, and schools as shown in Table 3 . However, Smartpls for structural equation modeling was used to explore the interconnectedness among variables (predictors and predicting variables). The adopted robust experimental parameters, Cronbach alpha, composite reliability, factor loading, and extraction of the variance average are fully illustrated in Table 4 using Smartpls software (SEM) to estimate the correlational strengths of the variables. The tested validity and reliability of the study items were examined with composite reliability parameters with the loading figure higher than 0.7 symmetrically align with the designed data construct (van der Linden, Klein Entink, & Fox, 2010). The descriptive analysis was executed with SPSS software.Table 3 Demographic descriptive results. Table 3V1 V2 Frequency Percent% Mean StdDeviation Variance N (Sample) Skewness Kurtosis Gender Female 47 57.3 1.43 .498 .248 82 .301 -1.958 Male 35 42.7 Age 12-18 0 0 2.63 .824 .679 82 .778 -1.078 18-27 48 58.5 27-30 16 19.5 30< 18 22.0 Education Primary 0 0 3.00 .157 .025 82 .000 40.500 school Secondary 1 1.2 school Higher Edu. 80 97.6 Dropout 1 1.2 School Type Private 6 7.3 2.04 .429 .184 82 .219 2.661 School Public 67 81.7 School None 9 11.0 School Category Polytechnic, College of Education University 11, 3, 68 13.4, 3.7, 82.9 2.70 .697 .486 82 -1.966 2.067 Table 4 Factor analysis, factor loading, reliability, and validity. Table 4Constructs Loading of Variables Average Variance Extracted Composite Reliability Competency 0.788 0.890 0.773 0.787 0.743 Perception 0.785 0.834 0.811 0.856 0.729 Attitude 0.688 0.794 0.741 0.782 Literacy/Skill 0.803 0.807 0.639 0.683 0.881 Willingness 0.777 0.776 0.882 0.5570 0.847 df 3.00 sig .000 Overall, Cronbach Alpha Test 0.852 Note: Higher Edu in Table 3 means higher education, and dropouts are students who were in school before the emergence of coronavirus, then decided not to go back to school. 3.5.2 Result The percentage of female to male participants in the study is 57.3% and 42.7%, represented in Table 3. The ages with distance education knowledge are between 18-27 years to 30 years and above. The 18-27 age range outweighs the rest of the population with 58.5%, 27-30 years 19.5%, 30 years and above has 22.0%, and the least of them all, 12-18 years recorded zero percent (note that there was zero response from the primary school pupils due to their lack of understanding of the topic, and not being exposed to any form of digital education). The demographic descriptive Table 3 highlighted the salient analyses of the constructs such as the standard deviation, variance, skewness, kurtosis, mean score, etc. The study also revealed that 97.6% of the respondents are aware of online distance education and had once indulged in one form of distance online education (either in self-developmental tutorials and classes electronically), which most are students from tertiary education. The responses led to questioning the school's alternative measures in maintaining continuous learning activity during the lockdown period during the heat of covid-19. However, 63.4% confirmed there was no means of continuous learning initiated by the school, and this shows that many education leaders lack digital education competency. Schleicher (2020) stated that insufficient financial resources remain the numerating factor of schools not incorporating ICT structure to enhance distance online education. Furthermore, 75.6% of respondents narrated that their school was shut down for over six months during covid-19 and it affected their learning behavior after school was reopened. The factor analysis of the conceptualized constructs (Competency, Perception, Attitude, Literacy/Skill, and Willingness). The loadings of the items of each construct were tested and above 0.6 standardized thresholds. The Cronbach alpha for validity and reliability is 0.852, Table 4. However, Cronbach's alpha output indicates the collinearity and satisfactory dimension of the variables as stipulated by Publications, Reserved, Pdf, and Datasets (2019). The tested Cronbach reliabilities are greater than the 0.6 approved acceptability level. Statistically, the CFA approach was employed in the assessment of variable loading. Precision moderations and augmentations of the low loading of items were carried out to improve model measurement. One of the benefits of the structure model with smart pls is the deletion of the inconsequential items for the improvement of the model. Note, items below 0.6 levels were accommodated in the process of structural equation modeling (Mohamad, Mohammad, Azman, & Ali, 2016) as shown in Table 4. The competency construct has the highest factor loading of 0.890, and 0.639 for literacy/skill is the least. Convergent validity testing with the experimentation of average variance extract (AVE) and the measurement of a correlation matrix. The average variance extract (AVE) value < 0.5 falls within the approval mark of convergent validity (Sayibu et al., 2021). The output of the average variance extract shows the justification of latent model measurement for the constructs, thus validating the correlation between high values and discrepancies. This shows that the square root value of AVE is greater than the constructs correlations outcomes. The detailed analysis of convergent validity is shown in Table 4. 3.5.3 Structural model results analysis In the measurement of the model fitness index, the cutoff fit models have a high susceptibility to the quality of the measurement (Mcneish et al., 2017). The parsimonious fit, absolute fit, and incremental fit are categorized as fit model characteristics. The study considers reporting some of the salient models fit, with the estimated significance level, noting that the cutoff points vary in different contexts and studies (Mcneish et al., 2017). For testing the model fitness and its dimensions, TLI (Tucker-Lewis Index), RMSEA (Root Mean Square of Error Approximation), CHSQ/DF (ChiSquare/ Degree of Freedom), and Chi-Square Discrepancy, CFI (Comparative Fit Index) were all recorded (Awang, Wan Afthanorhan, & Asri, 2015). Table 6 displays a good fitness measurement of TLI, RMSEA, and CFI (Ene, 2020). The comparative fit index (CFI) of 0.915 shows a perfect fitness model and reliability. And it becomes proof that the experimented variables satisfy the standards of the model fits and quality of the measurements. The root means square of error approximation (RMSEA) acceptable benchmark is 0.06 to evaluate multiple fit parametric tests of latent variables. This demonstrates that competency, perception, attitude, literacy/skill, and willingness are highly justified as better constructs. 4 Hypotheses analysis and discussion The standardized testing model with constant latent variables was tested with path regression coefficients as illustrated in Table 6. Table 7, elaborated the outcomes of the study established hypotheses and their significance and non-significance dimensions. Hypothesis 1 (H1) (β = 0.230, t = 3.241, p < 0.003), the result shows a significant relationship between competency and attitude, which implies that competency can trigger an attitude to accept distance online education. This result outcome corroborates what numerous existing studies affirmed that teachers' and learners' ICT competency encourage them to adopt digital learning and teaching approach without self-doubt in their ability to learn and teach effectively (Crawford et al., 2020). Hypothesis 2 (H2) (β = 0.314, t = 4.043, p < 0.000), indicated that attitude is significantly related to the willingness of remote learning acceptability. This implies that learning attitude determines the online distance education mindset. Learners' background in ICT is vital for their willingness to opt for a digital learning approach (Boca, 2021). Family financial status can determine the learners’ knowledge of ICT and online education willingness, given that some students are from a poor background and have not heard about computer or owned any digital device (Okagbue, Wang, & Ezeachikulo, 2022). This also extends to the attitude of school administrators and the level of digital competence they have can determine their conscious efforts in integrating web-based learning in the learning environment. The third hypothesis (H3) (β = 0.163, t = 1.325, p < 0.124), there is no significant relationship between competency and perception. Although statistically, the result shows a parallel relationship between competency and perception, Dhawan (2020) holds a contrary view that digital competency and efficacy influence teachers' and learners' perceptions of online distance education. In justification of his statement, possession of firsthand knowledge of the benefits of digital learning increases the chance of learning online(Almaiah et al., 2020). Also, hypothesis 4, perception and literacy/skill, H4 (β = 0.042, t = 0.678, p < 0.426), perception and willingness, H5 (β = 0.281, t = 3.535, p < 0.001), competency and literacy, H6 (β = 0.135, t = 1.486, p < 0.133), attitude and literacy H7 ((β = 0.221, t = 2.864, p < 0.004), literacy and willingness, H8 (β = 0.026, t = 0.652, p < 0.311). The H4 shows no positive association between perception and literacy and skill. To justify this outcome Almaiah et al. (2020) opined that negative perception toward electronic education can be caused by a lack of ICT basic skills, and also supported their claims that digital illiteracy and technical know-how become contributory factors to the preference for electronic education or non- electronic learning approach. In order to lay more emphasis on the H4 outcome, Alkaria and Alhasan (2017) affirmed that a negative perception of web-based class platforms diminishes the motivation to accept online education. Hypothesis 5 explored the association between willingness and perception, and the study showed that there is a significant relationship between these two variables, H5 (β = 0.281, t = 3.535, p < 0.001), the relationship of these two variables confirms the assertions, those positive and negative perceptions towards distance education influence the attitude of students and teachers in their decisions to adopt technology in their learning and teaching activities (Lee, 2020). Hypothesis 6, for competency and literacy, (β = 0.135, t = 1.486, p < 0.133), there is a non-statistical significant relationship with the variables, this simply means there is no positive relationship between competency and literacy. Although the study indicated no relationship between competency and literacy, some scholars narrated that digital competency and literacy influence students' decisions in trusting distance and online education. This outcome answers the question of the feasibility of distance online education in Nigerian schools, supporting the responses given by the respondents that school leaders and managers have no digital competency and literacy to provide a learning platform during the lockdown period. Hypothesis 7 result revealed the statistical significance of attitude having a positive association with the literacy H7 (β = 0.221, t = 2.864, p < 0.004), Milovanović et al. (2020) agreed that students and individuals with enthusiastic learning attitudes tend to invest more time in seeking more skills in pursuance to academic excellence, also equip themselves by engaging in some digital self-learning programmes. The final hypothesis, (H8) on the association between literacy and willingness having the output (β = 0.026, t = 0.652, p < 0.311). This result shows no significant association between digital literacy/skill and willingness for online education. The indicator that illustrates P < 0.311 which implies the parallel and non-statistical linearity of these two variables. On this result, the study by Jou et al. (2016) evinced that digital literacy and skills can affect the intention of learners to indulge in digital classes, they further narrated that having ICT skills and knowledge boost learners' motivation and satisfaction. Juniu (2019) supported the statement of Jou et al. (2016) against the H8 result, narrating that technological literacy by the teachers aids in stimulating learning activities outcome and trigger learners' interest to see distance online education as a viable schooling option. In support of the H8 validated statement, Vanderlinde, Aesaert, and Van Braak (2014) espoused that learners can still have the willingness to accept distance online education without possessing digital skills and literacy. Many students with no digital knowledge can develop an interest in distance online education depending on the teachers' competency and engaging style (Vanderlinde, Aesaert, & Van Braak, 2014), which can foster students' decision and mindset to perfect their skills in ICT (Baek & Touati, 2017). From the survey, participants were asked whether they "prefer online distance education to in-class learning," shockingly, 63.4% answered 'NO,' 28% said 'YES, and '8.5% ticked 'MAYBE'; this result justifies the H5 result with a p-value of 0.001 on perception with a positive association to willingness. On the other hand, the H7 result proves the responses from participants which 32.9% of them affirmatively stated that their lack of computer literacy influences their judgment and perception of not subscribing to online distance education. These responses validate that Nigerian schools lack proper computer learning courses and information and communication technology in the school environment. Zhang and Kenny (2010) delineated that the digital ecosystem in schools breeds a positive perception that will convince learners to acquire digital education. More so, practical digital education courses should be added to the schools’ learning curriculum to create willingness for the students. To adequately sustain distance education, teachers’ professional training on the use of ICT devices and teaching APPS is highly needed to elevate and instill digital skills and mindset in the learner (Hatzigianni, Gregoriadis, & Fleer, 2016). Especially, training teachers to master the synchronous and asynchronous dynamics of electronic education for efficient learning (Alhih et al., 2017). In responding to the research questions on the feasibility and sustaining possibility of online distance education in Nigerian education and, the readiness and acceptance of ODE by the teachers and students (online distance education), determined by the attitude and efforts of the school leaders, managers, policymakers and education stakeholders in providing the needed resources to develop online and distance education in schools in the schools (Hatzigianni et al., 2016; Vanderlinde et al., 2014). It is also important to note that the correlations of the experimented variables showed moderate and robust relationships, as displayed in Table 5 .Table 5 Fornell-Larcker discriminant validity results. Table 5Variables 1 2 3 4 5 Mean Competency 0.834 3.54 (1.22) Perception 0.660⁎⁎ 0.808 3.89 (1.05) Attitude 0.620⁎⁎ 0.550⁎⁎ 0.745 1.90 (2.02) Literacy/Skill 0.520⁎⁎ 0.600⁎⁎ 0.500⁎⁎ 0.720 4.00 (1.60) Willingness 0.518⁎⁎ 0.629⁎⁎ 0.475⁎⁎ 0.510⁎⁎ 0.712 4.11 (1.10) ⁎⁎ P < 0.005, SD = standard deviation Table 6 Model fit index. Table 6Good fitness Values CFI .915>0.95 TLI .920>0.95 RMSEA .063<0.08 IFI .930>0.90 Chi-Square/df 2.400<3.0 GFI .937>0.90 AGFI .864>0.95 Chi-square/degree of freedom(Chsq/df), *P<.01, **P<.001, and **P<.005, Root mean Square of error of approximation=RMSEA, Normed Fit Index= IFI. Table 7 Regression path coefficients (β)weights and hypotheses. Table 7hypotheses tested Items β SE t-value p-value Condition H1 Comptency Attitude 0.230 0.061 3.241 0.003 Accepted H2 Attitude Willingness 0.314 0.054 4.043 0.000 Accepted H3 Competency Perception 0.163 0.050 1.325 0.124 Not H4 Perception Literacy 0.042 0.084 0.678 0.426 Not H5 Perception Willingness 0.281 0.059 3.535 0.001 Accepted H6 Competency Literacy/Skill 0.135 0.073 1.486 0.133 Not H7 Attitude Literacy 0.221 0.067 2.864 0.004 Accepted H8 Literacy Willingness 0.026 0.082 0.652 0.311 Not 4.1 Structural equation model The Fig. 2 below is the path diagram of the SEM and the connections of the latent variables. However, the predicting endogenous variables are Competency, Attitude, Perception, and Literacy/Skill. And the scales of observed indicators measure the structured latent variables. In turn, each of these latent variables is measured by sets of indicators or observed variables. Thus, the latent variables establishment aims to illustrate its relationship with the hypotheses as predicted. As willingness is the exogenous variable, the four endogenous variables are presumed to exert their effects in the study. More so, the study indicators are presented as reflective indicators with latent variables (Wahbeh, Yount, Vieten, Radin, & Delorme, 2021).Fig. 1 Conceptual framework. Fig 1 Fig. 2 Latent variables. Fig 2 5 Conclusion Our study highlighted the importance of institutionalizing distance online education or a web-based learning system in the Nigerian education system as the new normal in post-covid-19 education. The study also pinpointed that the engagement of students in electronic education increases their competency and confidence to acquire digital knowledge and skills and master how to apply them in their learning activities (Scull et al., 2020). On the teachers' side, teaching with smart devices fosters creativity and immense digital literacy to instruct learners effectively and enhance competency-based learning (Batdı, Doğan, & Talan, 2021). The suggestions this article raised to the education policymakers, school administrators, and stakeholders were from the complaints of the students during the shutdown of the schools for over six months at the emergence of coronavirus, due to schools leadership provided no continuous learning platforms for them while at home. For that reason, this current research aimed to explore and understand learners' competency, perception, attitude, literacy/skill, and willingness on distance online education, and their intention to accept electronic learning as a viable learning approach. Furthermore, given the incidences of Covid-19 and its impacts on education globally, numerous efforts have been made to blend web-based learning with distance education to mitigate the threats of the pandemic on learners' life (Zhang, & Kenny, 2010) and health, and thereby encourage schools to adopt and adapt to digital, and distance learning approach, as a new normal of schooling, along the line normalizing the culture of remote learning and distance education. Concerning the research questions of the study, the H7 validates the concern of the questions with 0.001 significant statistical relationships between perception and willingness, this proves that teacher's and student's feelings, and views towards digital learning approach and distance education determine influence learners' behaviour and the decision to accepting them as means of learning (Cabero-Almenara & Meza-Cano, 2019). Finally, this research aims to suggest to the ministry of education and appropriate stakeholders to consider making digital distance education inducted as an acceptable schooling approach to encourage students and teachers to become tech-savvy, simultaneously enhancing their cognitive and efficacy abilities (Milovanović et al., 2020). Most importantly, creating a digital environment and culture in the education environment that sustains educational growth against future pandemics or threats that will affect education in the country (Lee et al., 2021). 6 The limitation and future direction The study shows good model fitness, and hypotheses were cross-sectionally tested. However, the study explored the ICT-related variables to evaluate why many Nigerian students prefer face-to-face learning to online distance education, at the same time brings new insights to properly understand the plight of the students and their perceptions of learning with ICT devices and provide accurate approaches to solve the issue of digital and distance education in school. Additionally, the study tested small-scale participants but suggested that future studies on this discourse should consider larger participants for holistic views. Statistically, out of the eight hypotheses proposed for the study, four were not significant, and four were confirmed significant. We, therefore, suggested that further studies should consider exploring those not significant variables in a wider context for further justifications. More so, as this article summarized the few experiences Nigeria students and Nigerian education systems witnessed during the school lockdown, the authors advised that future studies should apply a qualitative research approach with an in-depth interview to get extensive information from the students, teachers, and school leaders on their experiences during the lockdown, and the challenges Nigerian's education system are still encountering the after the covid-19 school lockdown was lifted. The information gathered from future studies can equally consult our findings in this study to adequately advise the administrative leaders and education policymakers on the dire need to integrate distance online education and virtual learning approach in the country's education system for its sustainability. Funding This study received no funding. CRediT authorship contribution statement Ekene Francis Okagbue: Project administration, Writing – review & editing, Visualization, Conceptualization, Methodology, Formal analysis, Data curation, Writing – original draft. Ujunwa Perpetua Ezeachikulo: Project administration, Writing – review & editing, Visualization, Conceptualization, Methodology, Formal analysis, Data curation, Writing – original draft. Ilokanulo Samuel Nchekwubemchukwu: Visualization, Writing – review & editing. Ilodibe Emeka Chidiebere: Visualization, Writing – review & editing. Obisoanya Kosiso: Visualization, Writing – review & editing. Cheick Amadou Tidiane Ouattaraa: Visualization, Writing – review & editing. Esther Onyinye Nwigwe: Visualization, Writing – review & editing. Declaration of Competing Interest The authors declare no conflict of interest in this current study. ==== Refs References Adefuye A.O. Adeola H.A. Busari J. The covid-19 pandemic: The benefits and challenges it presents for medical education in Africa Pan African Medical Journal 40 September 2021 10.11604/pamj.2021.40.42.28489 Addleman R.A. Nava R.C. Cevallos T. Brazo C.J. Dixon K. Preparing teacher candidates to serve students from diverse backgrounds: Triggering transformative learning through short-term cultural immersion International Journal of Intercultural Relations 43 PB 2014 189 200 10.1016/j.ijintrel.2014.08.005 Affouneh S. Salha S. Khlaif Z.N. Designing quality E-learning environments for emergency remote teaching in coronavirus crisis Interdisciplinary Journal of Virtual Learning in Medical Sciences 11 2 2020 1 3 Agbele A.T. Oyelade E.A. Impact of COVID-19 on the Nigerian educational system: Strengths and challenges of online/virtual education Asian Journal of Education and Social Studies 13 1 2020 26 35 10.9734/ajess/2020/v13i130322 Ajadi T.O. Salawu I.O. Adeoye F.A. E-learning and distance education in Nigeria Turkish Online Journal of Educational Technology 7 4 2008 61 70 Albrahim F.A. Online teaching skills and competencies TOJET: The Turkish Online Journal of Educational Technology 19 1 2020 9 20 Alhat S. Virtual classroom: A future of education post-COVID-19 Shanlax International Journal of Education 8 4 2020 101 104 10.34293/education.v8i4.3238 Alhih M. Ossiannilsson E. Berigel M. Levels of interaction provided by online distance education models Eurasia Journal of Mathematics, Science and Technology Education 13 6 2017 2733 2748 10.12973/eurasia.2017.01250a Alkaria A. Alhassan R. The effect of in-service training of computer science teachers on scratch programming language skills using an electronic learning platform on programming skills and the attitudes towards teaching programming Journal of Education and Training Studies 5 11 2017 1 10.11114/jets.v5i11.2608 Almaiah M.A. Al-Khasawneh A. Althunibat A. Exploring the critical challenges and factors influencing the E-learning system usage during the COVID-19 pandemic Education and Information Technologies 25 6 2020 5261 5280 10.1007/s10639-020-10219-y 32837229 Amir, L. R., Tanti, I., Maharani, D. A., Wimardhani, Y. S., Julia, V., & Sulijaya, B. (2020). Student perspective of classroom and distance learning during the COVID-19 pandemic in the undergraduate dental study program Universitas Indonesia. 1–8. Awotokun A.O. Information and Communications Technology (ICT) in Nigeria educational assessment system - Emerging challenges Universal Journal of Educational Research 4 6 2016 1351 1356 10.13189/ujer.2016.040612 Bacon, K. L., & Peacock, J. (2021). Sudden challenges in teaching ecology and aligned disciplines during a global pandemic : Reflections on the rapid move online and perspectives on moving forward. (October 2020), 3551–3558. https://doi.org/10.1002/ece3.7090. Baek Y. Touati A. Exploring how individual traits influence enjoyment in a mobile learning game Computers in Human Behavior 69 2017 347 357 10.1016/j.chb.2016.12.053 Batdı V. Doğan Y. Talan T. Effectiveness of online learning : multi-complementary approach research with responses from the COVID-19 pandemic period Interactive Learning Environments 0 0 2021 1 34 10.1080/10494820.2021.1954035 Bayram L. Enhancing an online distance education course with video Procedia - Social and Behavioral Sciences 83 2013 463 467 10.1016/j.sbspro.2013.06.091 Boca G.D. Factors influencing students’ behavior and attitude towards online education during covid-19 Sustainability (Switzerland) 13 2021 13 10.3390/su13137469 Boling E.C. Hough M. Krinsky H. Saleem H. Stevens M. Cutting the distance in distance education: Perspectives on what promotes positive, online learning experiences Internet and Higher Education 15 2 2012 118 126 10.1016/j.iheduc.2011.11.006 Cabero-Almenara J. Meza-Cano J.M. Online undergraduate students’ perceptions of the impact of Web 2.0 on higher education /Percepciones de estudiantes de licenciatura en línea sobre el impacto de la Web 2.0 en educación superior Cultura y Educacion 31 3 2019 481 508 10.1080/11356405.2019.1630953 Cavalcanti A.P. Barbosa A. Carvalho R. Freitas F. Tsai Y.S. Gašević D. Mello R.F. Automatic feedback in online learning environments: A systematic literature review Computers and Education: Artificial Intelligence 2 2021 10.1016/j.caeai.2021.100027 Chaichumpa S. Wicha S. Temdee P. Personalized learning in a virtual learning environment using modification of objective distance Wireless Personal Communications 2021 10.1007/s11277-021-08126-7 (0123456789) Chen T. Peng L. Jing B. Wu C. Yang J. Cong G. The impact of the COVID-19 pandemic on user experience with online education platforms in China Sustainability (Switzerland) 12 18 2020 10.3390/SU12187329 Cicha K. Rizun M. Rutecka P. Strzelecki A. Covid-19 and higher education: First-year students’ expectations toward distance learning Sustainability (Switzerland) 13 4 2021 1 20 10.3390/su13041889 Crawford J. Henderson K.B. Rudolph J. Malkawi B. Glowatz M. Burton R. Lam S. COVID-19 : 20 countries ’ higher education intra-period digital pedagogy responses Journal of Applied Learning & Teaching 3 1 2020 1 20 De Giusti A. Policy brief: Education during COVID-19 and beyond 2020 Revista Iberoamericana de Tecnología En Educación y Educación En Tecnología e12 10.24215/18509959.26.e12 Dhawan S. Online learning: A panacea in the time of COVID-19 crisis Journal of Educational Technology Systems 49 1 2020 5 22 10.1177/0047239520934018 Distler J.W. Online nurse practitioner education Nurse Practitioner 40 11 2015 44 49 10.1097/01.NPR.0000472249.05833.49 26474204 Ene, M. C. (2020). Scholar commons investigating accuracy of model fit indices in multilevel confirmatory factor analysis. eLearning Africa The effect of Covid-19 on education in Africa and its implications for the use of technology 2020 EdTech 10.5281/zenodo.4018774 Evans, M. J., & Moore, J. S. (2012). Peer tutoring with the aid of the internet. https://doi.org/10.1111/j.1467-8535.2011.01280.x. Farber R.S. Distance education and teaching online: My journey from mystery to mastery Occupational Therapy in Health Care 27 3 2013 272 279 10.3109/07380577.2013.809180 23855613 Filho W.L. Price E. Wall T. Shiel C. Azeiteiro U.M. COVID-19 : The impact of a global crisis on sustainable development teaching Environment, Development, and Sustainability 2021 10.1007/s10668-020-01107-z (0123456789) Hatzigianni M. Gregoriadis A. Fleer M. Computer use at schools and associations with social-emotional outcomes A holistic approach. Findings from the longitudinal study of Australian children Computers and Education 95 2016 134 150 10.1016/j.compedu.2016.01.003 Haghshenas, M. (2019). A model for utilizing social software in learning management system of E-learning. 1(4), 25–38. Hu B. Sohail M. Noman M. Irshad M. Awais M. Tang X. Song C. ScienceDirect a pilot study of global global ICT ICT strategy application applications in sustainable continuing education Procedia Computer Science 183 2021 849 855 Jou M. Tennyson R.D. Wang J. Huang S.Y. A study on the usability of E-books and APP in engineering courses: A case study on mechanical drawing Computers and Education 92–93 2016 181 193 10.1016/j.compedu.2015.10.004 Jowsey T. Foster G. Cooper-ioelu P. Jacobs S. Nurse Education in Practice Blended learning via distance in pre-registration nursing education : A scoping review Nurse Education in Practice 44 October 2018 2020 102775 10.1016/j.nepr.2020.102775 Khan Z.H. Abid M.I. Distance learning in engineering education: Challenges and opportunities during COVID-19 pandemic crisis in Pakistan International Journal of Electrical Engineering Education 2021 1 20 10.1177/0020720920988493 King M. Pegrum M. Forsey M. MOOCs and OER in the Global South: Problems and potential International Review of Research in Open and Distance Learning 19 5 2018 2 20 10.19173/irrodl.v19i5.3742 Kpae G. Impact of Covid-19 on society, economics and education of Nigeria International Journal of English Literature and Social Sciences 5 5 2020 1773 1778 10.22161/ijels.55.66 Krohn K.M. Sundberg M.A. Quadri N.S. Stauffer W.M. Dhawan A. Pogemiller H. Hendel-Paterson B. Perspective piece global health education during the COVID-19 pandemic: Challenges, adaptations, and lessons learned American Journal of Tropical Medicine and Hygiene 105 6 2021 1463 1467 10.4269/ajtmh.21-0773 34634769 Larreamendy-Joerns J. Leinhardt G. Going the distance with online education Review of Educational Research 76 4 2006 567 605 10.3102/00346543076004567 Lee K. Who opens online distance education, to whom, and for what? Distance Education 41 2 2020 186 200 10.1080/01587919.2020.1757404 Lee Y.C. Malcein L.A. Kim S.C. Information and communications technology (ICT) usage during COVID-19: Motivating factors and implications International Journal of Environmental Research and Public Health 18 7 2021 10.3390/ijerph18073571 Liu P. Xu M. Cao L. Su L. Lu L. Dong N. Xu J. Impact of COVID-19 pandemic on the prevalence of respiratory viruses in children with lower respiratory tract infections in China Virology Journal 18 1 2021 1 7 10.1186/s12985-021-01627-8 33397387 Ma G. Black K. Blenkinsopp J. Charlton H. Hookham C. Pok W.F. Alkarabsheh O.H.M. Higher education under threat: China, Malaysia, and the UK respond to the COVID-19 pandemic Compare 52 5 2022 841 857 10.1080/03057925.2021.1879479 Martínez J. Lázaro C. Gómez J. Fernández M. Psychological impact of COVID-19 emergency on health professionals: Burnout incidence at the most critical period in Spain Journal of Clinical Medicine December 2019 2020 1 18 Retrieved from https://www.mdpi.com/2077-0383/9/9/3029/html 33374498 Mcneish, D., An, J., Hancock, G. R., Mcneish, D., An, J., & Hancock, G. R. (2017). The thorny relation between measurement quality and fit index cutoffs in latent variable models The thorny relation between measurement quality and fit index cutoffs in latent variable models. 3891(March). https://doi.org/10.1080/00223891.2017.1281286. Milovanović A. Kostić M. Zorić A. Dordević A. Pešić M. Bugarski J. Josifovski A. Transferring COVID-19 challenges into learning potentials: Online workshops in architectural education Sustainability (Switzerland) 12 17 2020 1 21 10.3390/su12177024 Mohamad M. Mohammad M. Azman N. Ali M. The impact of life satisfaction on substance abuse : Delinquency as a mediator International Journal of Adolescence and Youth 3843 March 2017 2016 1 11 10.1080/02673843.2016.1267021 Naidu S. In search of “what works” in online and distance education Distance Education 35 1 2014 1 3 10.1080/01587919.2014.902887 Nilsen A.G. Almås A.G. Gram H. Producing Digital Learning Resources (DLR) for teacher training Designs for Learning 12 1 2020 71 80 10.16993/dfl.153 Oboh Stephen O. Oboh Omonyemen J. Covid-19 and its effect on secondary school students learning in Benin City, Covid-19 and its effect on secondary school students learning in Benin City, Edo State, Nigeria International Journal of Advanced Education and Research International 5 3 2020 111 117 10.25215/0802.071 Okagbue E.F. Wang M. Ezeachikulo U.P. Does school bullying show a lack of effective multicultural education in the school curriculum? International Journal of Educational Research Open 3 March 2022 100178 10.1016/j.ijedro.2022.100178 Oyebode, J. (2020). Engineering education during pandemic: reflection, rethink and future projection for educational transformation. Parmigiani D. Benigno V. Giusto M. Silvaggio C. Sperandio S. E-inclusion: Online special education in Italy during the Covid-19 pandemic Technology, Pedagogy and Education 30 1 2021 111 124 10.1080/1475939X.2020.1856714 Publications, S., Reserved, A. R., Pdf, T., & Datasets, M. (2019). Learn about structural equation modeling in SmartPLS with data from the customer behavior in electronic commerce study in Ecuador (2017) Learn about structural equation modeling in SmartPLS with data from the customer behavior in electronic commerce Stu. (2017). Reinhart A. Malzkorn B. Döing C. Beyer I. Jünger J. Bosse H.M. Undergraduate medical education amid COVID-19: A qualitative analysis of enablers and barriers to acquiring competencies in distant learning using focus groups Medical Education Online 26 1 2021 10.1080/10872981.2021.1940765 Rizun, M., & Strzelecki, A. (2020). Students ’ acceptance of the COVID-19 impact on shifting higher education to distance learning in Poland. 1–19. Sanches, M. (2020). Research education, distance learning, and the COVID-19 era. Samuel A.I. Coronavirus (COVID-19) and Nigerian education system: Impacts, management, responses, and way forward Education Journal 3 4 2020 101 102 10.31058/j.edu.2020.34009 Sayibu, M., Jianxun, C., Yinka, T., Olayemi, R., Koroma, J., Simeon, T., & Shahani, R. (2021). Social sciences & humanities open nexus between students ’ attitude towards self-learning, tencent APP usability, mobile learning, and innovative performance. 4. Schleicher A. The impact of COVID-19 on education: Insights from education at a glance 2020 OECD Journal: Economic Studies 2020 1 31 Retrieved from https://www.oecd.org/education/the-impact-of-covid-19-on-education-insights-education-at-aglance-2020.pdf Scull J. Phillips M. Sharma U. Garnier K. Scull J. Phillips M. Sharma U. Innovations in teacher education at the time of COVID-19 : an Australian perspective Innovations in teacher education at the time of COVID-19 : An Australian perspective Journal of Education for Teaching 00 00 2020 1 10 10.1080/02607476.2020.1802701 Series, C. (2021). Mathematics learning through e-learning during the pandemic covid-19 in grade 9 of a junior high school in Bandung Mathematics learning through e-learning during the pandemic covid-19 in grade 9 of a junior high school in Bandung. https://doi.org/10.1088/17426596/1806/1/012084. Singh V. Thurman A. How many ways can we define online learning? A systematic literature review of definitions of online learning (1988-2018) American Journal of Distance Education 33 4 2019 289 306 10.1080/08923647.2019.1663082 Songsom N. Nilsook P. Wannapiroon P. Fung C.C. Wong K.W. The system architecture of a student relationship management system using the Internet of Things to collect the digital footprint of higher education institutions International Journal of Emerging Technologies in Learning 14 23 2019 125 140 10.3991/ijet.v14i23.11066 Stewart W.H. Lowenthal P.R. Distance education under duress: A case study of exchange students’ experience with online learning during the COVID-19 pandemic in the Republic of Korea Journal of Research on Technology in Education 0 0 2021 1 14 10.1080/15391523.2021.1891996 Stickler U. Hampel R. Emke M. A developmental framework for online language teaching skills Australian Journal of Applied Linguistics 3 1 2020 133 151 10.29140/ajal.v3n1.271 Retrieved from Tedre M. Toivonen T. Kahila J. Vartiainen H. Valtonen T. Jormanainen I. Pears A. Teaching machine learning in K-12 Classroom: Pedagogical and technological trajectories for artificial intelligence education IEEE Access 9 2021 110558 110572 10.1109/ACCESS.2021.3097962 UNESCO-IESALC COVID-19 and higher education: Today and tomorrow 2020 UNESCO International Institute for Higher Education in Latin America and the Caribbean (IESALC) 1 46 Retrieved from https://bit.ly/34TOSvu Van der Linden W.J. Klein Entink R.H. Fox J.P. IRT parameter estimation with response times as collateral information Applied Psychological Measurement 34 5 2010 327 347 10.1177/0146621609349800 Vanderlinde R. Aesaert K. Van Braak J. Institutionalised ICT use in primary education: A multilevel analysis Computers and Education 72 2014 1 10 10.1016/j.compedu.2013.10.007 Wahbeh, H., Yount, G., Vieten, C., Radin, D., & Delorme, A. (2021). Measuring extraordinary experiences and beliefs : A validation and reliability study [version 3 ; peer review : 3 approved]. Wang Y.D. Building student trust in online learning environments Distance Education 35 3 2014 345 359 10.1080/01587919.2015.955267 Wear J.O. Levenson A. Distance education Clinical Engineering Handbook 35 3 2004 309 311 10.1016/B978-012226570-9/50079-X Wu B. Hu Y. Wang M. Scaffolding design thinking in online STEM preservice teacher training British Journal of Educational Technology 50 5 2019 2271 2287 10.1111/bjet.12873 Zhang Z. Kenny R.F. Learning in an online distance education course: Experiences of three international students International Review of Research in Open and Distance Learning 11 1 2010 17 36 10.19173/irrodl.v11i1.775
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==== Front J Med Chem J Med Chem jm jmcmar Journal of Medicinal Chemistry 0022-2623 1520-4804 American Chemical Society 36475694 10.1021/acs.jmedchem.2c01716 Article Discovery and Crystallographic Studies of Nonpeptidic Piperazine Derivatives as Covalent SARS-CoV-2 Main Protease Inhibitors Gao Shenghua †‡○ Song Letian †○ Claff Tobias § Woodson Molly ∥⊥ Sylvester Katharina § https://orcid.org/0000-0002-7698-5657 Jing Lanlan † https://orcid.org/0000-0002-1736-8085 Weiße Renato H. # Cheng Yusen † https://orcid.org/0000-0002-2001-0500 Sträter Norbert # Schäkel Laura § https://orcid.org/0000-0002-9376-7897 Gütschow Michael § Ye Bing † Yang Mianling † Zhang Tao ∇ https://orcid.org/0000-0001-9232-953X Kang Dongwei † Toth Karoly ∥⊥ https://orcid.org/0000-0002-8711-4240 Tavis John ∥⊥ Tollefson Ann E. *∥⊥ https://orcid.org/0000-0002-0013-6624 Müller Christa E. *§ https://orcid.org/0000-0002-9675-6026 Zhan Peng *† https://orcid.org/0000-0002-7302-2214 Liu Xinyong *† † Department of Medicinal Chemistry, Key Laboratory of Chemical Biology, Ministry of Education, School of Pharmaceutical Sciences, Shandong University, Ji’nan250012, China ‡ Shenzhen Research Institute of Shandong University, A301 Virtual University Park in South District, Shenzhen518057, Guangdong, China § PharmaCenter Bonn & Pharmaceutical Institute, Department of Pharmaceutical & Medicinal Chemistry, University of Bonn, An der Immenburg 4, Bonn53113, Germany ∥ Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, Missouri63104, United States ⊥ Saint Louis University Institute for Drug and Biotherapeutic Innovation, St. Louis, Missouri63104, United States # Institute of Bioanalytical Chemistry, Center for Biotechnology and Biomedicine, Leipzig University, Deutscher Platz 5, Leipzig04103, Germany ∇ Shandong Qidu Pharmaceutical Research Institute, Yinfeng Biological City, Chunlan Road 1177, High Tech District, Ji’nan250101, China * Email: [email protected]. * Email: [email protected]; Tel: +49-(0)228-73-2301. * Email: [email protected]; Tel: 086-531-88382005. * Email: [email protected]; Tel: 086-531-88380270. 07 12 2022 acs.jmedchem.2c0171624 10 2022 © 2022 American Chemical Society 2022 American Chemical Society This article is made available via the PMC Open Access Subset for unrestricted RESEARCH re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. The spread of SARS-CoV-2 keeps threatening human life and health, and small-molecule antivirals are in demand. The main protease (Mpro) is an effective and highly conserved target for anti-SARS-CoV-2 drug design. Herein, we report the discovery of potent covalent non-peptide-derived Mpro inhibitors. A series of covalent compounds with a piperazine scaffold containing different warheads were designed and synthesized. Among them, GD-9 was identified as the most potent compound with a significant enzymatic inhibition of Mpro (IC50 = 0.18 μM) and good antiviral potency against SARS-CoV-2 (EC50 = 2.64 μM), similar to that of remdesivir (EC50 = 2.27 μM). Additionally, GD-9 presented favorable target selectivity for SARS-CoV-2 Mpro versus human cysteine proteases. The X-ray co-crystal structure confirmed our original design concept showing that GD-9 covalently binds to the active site of Mpro. Our nonpeptidic covalent inhibitors provide a basis for the future development of more efficient COVID-19 therapeutics. Volkswagen Foundation 10.13039/501100001663 NA Foreign Cultural and Educational Experts Project NA GXL20200015001 Natural Science Foundation of Shandong Province 10.13039/501100007129 ZR2021ZD17 Natural Science Foundation of Guangdong Province 10.13039/501100003453 ZR2020JQ31 Natural Science Foundation of Guangdong Province 10.13039/501100003453 2021A1515110740 China Postdoctoral Science Foundation 10.13039/501100002858 2021M702003 document-id-old-9jm2c01716 document-id-new-14jm2c01716 ccc-price This paper was published ASAP on December 7, 2022, with entries missing from Table 1. The corrected version was reposted on December 8, 2022. This article is made available via the ACS COVID-19 subset for unrestricted RESEARCH re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. ==== Body pmc1 Introduction The coronavirus disease 2019 (COVID-19) pandemic continues to cause a worldwide health emergency. The pathogen of COVID-19, severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), encodes a positive-sense, single-stranded RNA genome of 30 kilobases.1 Apart from asymptomatic cases, clinical characteristics of COVID-19 vary from upper respiratory tract symptoms to pneumonia, fatigue, diarrhea, and life-threatening cardiovascular complications or multiorgan failure.2−4 The large number of infected patients and the high mutagenesis rate of SARS-CoV-2 have caused a series of emerging new variants with increased transmissibility and resistance to current vaccines and antibody therapies.5−8 As of mid-November of 2022, SARS-CoV-2 has caused 635 million confirmed infections and 6.6 million deaths, according to the World Health Organisation (WHO).9 Direct-acting antiviral agents are needed to mitigate the consequences of the ongoing COVID-19 pandemic. Mpro acts as a key enzyme in coronavirus multiplication by processing the viral polyprotein into functional proteins.10 The catalytic dyad comprised Cys145/His41 and several binding pockets (S1, S1’, S2, S4) form the Mpro ligand-binding site.11 The fundamental role of Mpro in the SARS-CoV-2 life cycle and the absence of homologous proteins in the human body make it an ideal target for antiviral drug development.12 Current Mpro inhibitors include covalent inhibitors and noncovalent inhibitors. Covalent inhibitors utilize Cys145 as an anchoring site for their electrophilic warheads, while closely interacting with key residues in the active site. Specifically, peptide-based covalent inhibitors of Mpro bearing an aldehyde function are currently the most studied and developed structural class.13,14 Among them, nirmatrelvir (PF-07321332; in Paxlovid) is the first and only protease inhibitor currently approved for COVID-19 therapy;14 further inhibitors have entered clinical trials (Figure 1).15 These compounds share some favorable properties, such as high Mpro inhibition and clinical efficacy. Nevertheless, their peptide scaffold and reactive aldehyde group are vulnerable to cellular metabolism, thus leading to low oral bioavailability.16 As a matter of fact, both GC-37617 and PF-00835231,18 further members of this class of compounds that are in clinical trials, require intravenous administration (PF-00835231 in the form of phosphate prodrug PF-07304814).17,18 In Paxlovid, nirmatrelvir is dosed orally in combination with the CYP3A inhibitor ritonavir to avoid extensive metabolism. However, the addition of ritonavir raises the risks of drug interactions and side effects. Off-target inhibition toward host proteases is also a concern for most peptide-like covalent inhibitors.19 Considering the disadvantages of the current covalent Mpro inhibitors, drug candidates with improved properties are urgently needed. Figure 1 Structures and activities of peptidic covalent Mpro inhibitors in clinical trials. IC50 refers to the enzyme inhibitory potency; EC50 refers to antiviral activity in vitro; CC50 refers to cytotoxicity in vitro; and CC50 values of the four compounds are higher than 100 μM. Recently, the development of nonpeptidic covalent Mpro inhibitors has been advanced by library screening and rational design. Some of these compounds showed remarkable potency and/or broad chemical space for further modification and optimization (Figure 2).20−24 Based on experience in protein kinase inhibitor development, one viable strategy is to fuse various cysteine-targeting warheads with the main scaffold of reported noncovalent inhibitors.25 Guided by this strategy and starting from the lead compound ML188, Jun9-62-2R22 and Y18023 were designed and synthesized by replacing the S1’-binding group with different covalent warheads (see Figure 2). They are endowed with significantly increased activities and no detectable effects on host proteases. Moreover, Y180 had 92.9% oral bioavailability and showed outstanding in vivo antiviral activity in mice.23 However, as most of these compounds have advanced to clinical trials, additional noncovalent Mpro inhibitors with new scaffolds need to be developed. Figure 2 Structures and activities of nonpeptidic covalent Mpro inhibitors. Covalent warheads are shown in red. In the quest for novel piperazine-based noncovalent Mpro inhibitors, GA-17S was discovered through rational drug design (Figure 3A). To increase permeability and in vivo antiviral activity, GC-14 with a replaced S1-binding group was designed, as recently reported.26 Figure 3 Development of piperazine-based Mpro inhibitors. (A) Structures and activities of GA-17S and GC-14, reported in our previous work.26 (B) Distance between the piperazine-N4 and the Cys145 thiol group (PDB ID: 8ACD), and general formula of the new GD series of compounds presented in this study. Co-crystal structures showed that the 4-nitrogen of the piperazine ring localizes at the junction of the S1 and the S1’ subsites, with a close distance (4.2 Å) from the thiol group of Cys145 (Figure 3B), potentially reachable by covalent warheads. Some piperazine-containing covalent fragments27 were previously reported as very weak inhibitors of Mpro. To design covalent Mpro inhibitors with improved potency and selectivity, we herein replaced the S1 nicotinoyl group of GA-17S to attach covalent warheads extending to Cys145 in the S1 cavity. The target compounds in this study represent combinations of the main scaffold and the S2/S4 groups of GC-14 with previously verified28−31 or expected covalent warheads. A total of 30 analogues with different covalent warheads of varied length and reactivity were synthesized. Their SARS-CoV-2 Mpro inhibitory potency, in vitro antiviral activity, and cytotoxicity in Vero E6 cells were assayed leading to the discovery of the most promising compound, GD-9. Mass spectrometry, time- and concentration-dependent enzymatic inhibition assays, and crystallography proved a covalent binding mode of the representative compound GD-9. This work reveals a novel class of nonpeptidic covalent SARS-CoV-2 Mpro inhibitors, which are valuable lead structures for further development of clinical candidates for COVID-19 therapy. 2 Results and Discussion 2.1 Chemistry The synthetic protocol for the newly designed derivatives is depicted in Scheme 1. Briefly, the intermediate 3 was attained by Chan–Lam coupling reaction from commercially available 1-(tert-butyl)-3-methyl-(S)-piperazine-1,3-dicarboxylate (2) and 3,4-dichlorophenylboronic acid (1) in the presence of cupric acetate and oxygen. After hydrolysis of intermediate 3 by lithium hydroxide, intermediate 5 was synthesized through the amide condensation reaction of intermediate 4 and thiophen-2-ylmethylamine. Finally, the tert-butyloxycarbonyl (Boc) protecting group was removed to give the key intermediate 6, which was then treated with carboxylic acids or sulfonylation reagents to produce a total of 30 final products. All target compounds (shown in Table 1) were confirmed by spectral data (HRMS, 1H NMR, and 13C NMR shown in the Supporting Information). Scheme 1 Synthetic Route to the Intermediates and Target Compounds of the GD Series Reagents and conditions: (i) Cu(OAc)2, O2, pyridine, dichloromethane (DCM), r.t.; (ii) LiOH, MeOH, tetrahydrofuran (THF), water, r.t.; (iii) 1-(bis(dimethylamino)methylene)-1H-[1,2,3]triazolo[4,5-b]pyridine-1-ium 3-oxide hexafluorophosphate (HATU), N,N-diisopropylethylamine (DIPEA), DCM, r.t.; (iv) CF3CO2H, DCM, r.t.; (v) carboxylic acids, HATU, DIPEA, DCM, r.t. or sulfonylation reagents, DIPEA, DCM, r.t. Table 1 Chemical Structures and Enzyme Inhibitory Activities of GD Series Compounds a IC50 values were obtained based on measurements over 30 min. Data are presented as geometric mean values of at least three independent experiments. b N.D., not determined. 2.2 Biological Activity and Structure–Activity Relationship (SAR) Study Main protease inhibition activities were measured for all target compounds in this study using a well-established fluorescence resonance energy transfer (FRET) assay.26 At a preliminary screening concentration of 10 μM, several compounds displayed significantly improved enzyme inhibition compared to the lead compound MCULE-5948770040.31 For compounds showing an inhibition >80%, we determined their IC50 values, based on the substrate turnover during 30 min, consistent with previous studies.20 As shown in Table 1, compounds GD-9 (IC50 = 0.18 ± 0.01 μM) and GD-13 (IC50 = 0.31 ± 0.02 μM) were identified as the two most promising inhibitors. GD-9 and GD-13 displayed 28- and 16-fold improvement, respectively, over MCULE-5948770040 (IC50 = 5.1 μM), and they were more potent than GC-14 (IC50 = 0.40 μM). Notably, GD-9 displayed potency in the same range as the approved drug nirmatrelvir (IC50 = 0.092 μM). These data provided the first evidence to prove our design concept. Preliminary SAR analysis revealed that the monosubstituted haloacetamides GD-9 and GD-13 showed the most potent inhibition of all compounds, while di- and tri-substituted haloacetamides (GD-10 ∼ 11 and GD-12 ∼ 14) were inactive. Enzyme inhibitory activities were basically lost with hydroxyacetyl or cyanoacetyl groups, exemplified by compounds GD-15 (9% inhibition at 10 μM) and GD-16 (34% inhibition at 10 μM). When the covalent warheads were altered to vinylsulfonamide (in GD-1 and GD-2), to sulfamoyl fluoride (GD-3 and GD-4), or to α-ketoamide functions (GD-5 ∼ 8), only GD-4 showed potent inhibition (IC50 = 1.55 ± 0.17 μM), which demonstrated that other warheads could not effectively bind to the active site and react with the catalytic Cys145 residue. It is worth noting that only the propioloyl group resulted in moderate activity (GD-24, IC50 = 2.77 ± 0.13 μM) when α,β-unsaturated olefin and alkyne groups (GD-20 ∼ 24) were connected to the N4-position of the piperazine ring. It seems that the covalent bond is especially difficult to generate when a methyl group is linked to the terminal alkyne, causing a substantial decrease in the inhibition rate (GD-23, 10% inhibition rate at 10 μM). Further, the introduction of several widely applied novel covalent warheads (GD-25–GD-30), which have been shown to covalently bind with cysteine, did not lead to inhibitors with increased potency. Of note, some warheads that had been highly active when they were attached to Ugi reaction-generated scaffolds,20,21 turned out to be ineffective when fused to the piperazine ring of the present core structure. Two plausible explanations are conceivable: (i) co-crystal structures show that the N4-substitution on the piperazine ring projects toward the protein surface near the oxyanion loop, and thus may give rise to steric collision and thereby block covalent warheads from reaching Cys145; (ii) covalent inhibitors reported here lack groups occupying the S1 cavity and interacting with the critical residue His163, which leads to weaker noncovalent interactions and reduces overall affinity.26,32 2.3 Anti-SARS-CoV-2 Activity The antiviral activity against SARS-CoV-2 of four selected compounds showing strong enzyme inhibition, and of two marketed drugs (remdesivir and nirmatrelvir) were assessed in Vero E6 cell cultures using a published, highly reproducible plaque assay.26 In addition, the new compounds were evaluated for their cytotoxicity. The biological results, expressed as EC50 (antiviral activity) and CC50 (cytotoxicity), are collected in Table 2. Three of the new compounds possessed good potency against SARS-CoV-2, comparable to remdesivir. GD-9 (EC50 = 2.64 ± 0.62 μM) and GD-24 (EC50 = 1.37 ± 0.43 μM) were identified as the two most promising inhibitors. However, compared to nirmatrelvir (EC50 = 0.38 μM), they were somewhat weaker. It is noteworthy that GD-9 and GD-24 possessed enhanced antiviral activity (at least 100-fold improvement) over the lead compound MCULE-5948770040. In contrast, GD-4 showed weak antiviral activity, probably due to the instability of its fluorosulfonyl group in the cellular system.33GD-9, GD-13, and GD-24 displayed some cytotoxicity (CC50 = 6.51–12.51 μM), as shown in Table 2. As is well known, strong electrophiles are prone to cause cell damage by reacting with glutathione, DNA, or nucleophilic protein sites. To explore the compounds’ selectivity, we determined the inhibitory activity of compound GD-9 on other human cysteine proteases (see Section 2.5). Table 2 Antiviral Activity and Cytotoxicity of GD-4, GD-9, GD-13, and GD-24 against SARS-CoV-2 in Vero E6 Cells a Antiviral effect; nirmatrelvir and remdesivir were used as positive controls (n = 3 biological replicates). b Error bars represent SD values of three independent experiments. c Cytotoxicity values were measured in Vero E6 cells with the MTS-based method.26 2.4 Validation of Covalent Inhibition Mechanism To explore the mechanism of action of our newly identified most promising inhibitor GD-9, enzyme kinetics and native mass spectrometry analyses were conducted. The former experiments were performed with a fluorogenic tetrapeptide substrate containing a C-terminal 7-amino-4-methylcoumarin (AMC) portion.21 As depicted in Figure 4A,B, GD-9 displayed a time-dependent inhibition typical for a covalent, irreversible inhibitor. For the determination of the first-order rate constant of inactivation, kobs, the progress curves were monitored for 60 min in the presence of five different inhibitor concentrations and analyzed by nonlinear regression. To obtain the second-order rate constants of inactivation, kinac/Ki, the kobs values were replotted against the inhibitor concentrations using the equation kinac/Ki = (1 + [S]/Km) × kobs/[I]. Compound GD-9 presented strong, irreversible inhibitory potency against SARS-CoV-2 Mpro with a kinac/Ki value of 21 500 ± 2200 M–1s–1. Figure 4 Inhibition mechanism of SARS-CoV-2 Mpro by GD-9. (A) Representative progress curves of enzyme-catalyzed hydrolysis of the substrate Boc-Abu-Tle-Leu-Gln-AMC in the absence (red) or presence of increasing concentrations of GD-9 (from top to bottom: 50, 100, 150, 200, and 250 nM). (B) Plot of first-order rate constants kobs versus inhibitor concentrations and linear regression resulting in a kinac/Ki value of 21 500 ± 2200 M–1s–1 (n = 3). Moreover, matrix-assisted laser desorption ionization/time-of-flight (MALDI-TOF) mass spectrometry was used to verify whether GD-9 is a covalent inhibitor. After preincubation of Mpro and GD-9, the obtained molecular weight of the enzyme-inhibitor adduct demonstrated a mass shift of 410 Da, consistent with the predicted result. This confirmed a covalent adduct of GD-9 with Mpro in a 1:1 stoichiometry (Figure 5), which is consistent with previously reported data on the covalent inhibitor Jun9-62-2R possessing a dichloroacetamide warhead.19 Overall, the enzyme kinetics and MALDI-TOF/TOF MS studies demonstrated that GD-9 is an irreversible covalent inhibitor of SARS-CoV-2 Mpro. Figure 5 MALDI/TOF mass spectra of SARS-CoV-2 Mpro with GD-9. (A) Mass spectrum of Mpro with a molecular weight of 33 804 Da. (B) Mass spectrum of Mpro after incubating with GD-9 for 30 min. 2.5 Target Selectivity Most of the existing peptide-like covalent Mpro inhibitors display poor target selectivity since the reactive warheads are prone to covalent off-target interactions, which may result in many side effects upon clinical application. In the first two years of the epidemic, an urgent demand for clinical drugs made a certain degree of side effects tolerable. However, in current and future drug design and development, extra attention has to be paid to the target selectivity of covalent Mpro inhibitors. Thus, the target specificity of our designed representative covalent Mpro inhibitor was further assessed. GD-9 was selected to evaluate the potential inhibition of human cathepsins B, F, K, and L, and caspase 3. As expected, GD-9 did not inhibit these human cysteine proteases at concentrations up to 30 μM, which is a relatively high concentration (Table 3), indicating that GD-9 displays target selectivity for the coronavirus protease and may thus possess a favorable safety profile. Table 3 Inhibitory Potency of GD-9 against Human Cysteine Proteases protease IC50 (μM) GD-9 cathepsin B >30 cathepsin F >30 cathepsin K >30 cathepsin L >30 caspase 3 >30 2.6 Crystallographic Studies To gain insights into the binding mode of the most potent Mpro inhibitor of the present series, GD-9, and to investigate drug–enzyme interactions, we co-crystallized GD-9 with SARS-CoV-2 Mpro and determined the complex structure by X-ray crystallography (Figure 6A,B). GD-9 formed a covalent bond between the methylene carbon of the N4-acyl group and the sulfur atom of Cys145. This covalent linkage was generated through the nucleophilic attack of the active-site thiolate at the electrophilic chloroacetamide warhead and accounted for irreversible inhibition of Mpro (Figure 6C). Additional, noncovalent interactions included hydrogen bonds between the N4-acetyl oxygen and the backbone nitrogens of Asn142 and Cys145, in addition to an interaction of the 2-carboxamido oxygen and the backbone of Glu166. The NH function of the 2-carboxamido group was bridged with the flexible side chain of Gln189 via a single water molecule. The thiophen-2-ylmethyl substituent did not form intramolecular π–π stacking interactions as observed for structurally similar reversible Mpro inhibitors26 but was largely surface-exposed and formed hydrophobic contacts to Gln189 and the backbone of Glu166. The dichlorophenyl group was located in a hydrophobic pocket formed by His41, Met49, Tyr54, Met165, Asp187, and Gln189 with stabilization by π–π stacking interactions to His41 (Figure 6B). Moreover, its p-chloro substituent came into a favorable distance (3.3 Å) for a potential halogen bonding interaction with the backbone of Asp187 (Figure 6B). The distance corresponded to the sums of their van der Waals radii (3.27 Å), whereas the C–Cl···O angle of 150 was 30° off from the linear orientation, ideal for a strong directional polarization.34 Figure 6 Co-crystal structure of GD-9 with SARS-CoV-2 Mpro (PDB ID: 8B56). (A) Mpro binding pocket interactions of the dominant conformation of GD-9 (orange, occupancy 0.7), covalently bound to Cys145. (B) Binding pocket view of GD-9 rotated by approximately 180° and with Cys145 highlighted as the irreversible anchor. The 2Fo – Fc electron density of GD-9 is shown in yellow mesh and was contoured at 1.0 σ (carve distance 1.6); see Figure S1 for the density of Cys145. Water molecules are shown as red spheres, and hydrogen-bond interactions are depicted as black dashed lines. π–π interactions are shown as blue dashed lines. (C) Reaction of GD-9 with Cys145. Slight ambiguities in the electron density map suggested a second alternate position of GD-9, distinguished from the first structure in the orientation of the Cys145 side chain and the covalent bond to Mpro, but without differences regarding critical interactions (Figure S1). In the alignment comparison between GD-9 and GC-14, a significant conformational change of the central piperazine ring was observed (Figure 7A,B). The piperazine ring was refined in a twisted boat form in GD-9, in contrast to the typical chair conformation observed in the GC-14 co-crystal structure. Remarkably, the thiophen-2-ylmethyl group in GD-9 was shifted by 3.8 Å away from the position taken by GC-14 (Figure 7B). These differences in the binding patterns of the two inhibitors were largely due to the covalent linkage of GD-9, which enforced a reorientation of the amide group at the piperazine ring. As a result, the piperazine ring adopted an energetically less favorable twisted boat conformation to allow the dichlorophenyl ring to stay approximately at the same site as in the GC-14 binding mode and to form the π-stacking interactions with His-41. In the complex structure with GC-14, the other face of the dichlorophenyl group formed an additional π-stacking with the thiophene ring of the inhibitor. Due to the large rotation and shift of the thiophene ring in the binding mode of GD-9, this stacking interaction was not observed for the covalently bound inhibitor. Instead, the thiophene ring of GD-9 formed hydrophobic interactions with the Gln189 side chain, located between the thiophene and the dichlorophenyl moieties. In the co-crystal structure with GC-14, Gln189 had a different conformation and also the Cα-position of this residue was shifted by 1.5 Å compared to the GD-9 complex structure. Figure 7 Comparison of binding poses of compound GD-9 (purple, PDB: 8B56) and its analogue, GC-14 (orange, PDB: 8ACL). Mpro is represented by the white semitransparent surface. (A) View from the opening of the Mpro active center. (B) 90° rotated view highlighting the flipped piperazine ring in GD-9, and the shift of the thiophene ring. Distances are given in Å unit. Despite the high potency of GD-9, these findings suggest further modifications. For example, introducing new central scaffolds to relieve the strain in the piperazine ring, may further improve the compound’s potency. To address their toxicity, overall modifications are needed to avoid too strong and harmful electrophilic groups while maintaining high activity. Introducing noncanonical warheads may also increase the interactions in the S1/S1’ pocket, and potentially reduce cellular toxicity. Furthermore, given the limited space left for placement of an additional warhead due to the proximity between the catalytic cysteine and noncovalent inhibitors, a covalent fragment-based approach was conducted in our lab to seek highly potent and selective covalent inhibitors of SARS-CoV-2 Mpro. 3 Conclusions Direct-acting antiviral agents are urgently needed to combat the COVID-19 epidemic. Combination of various cysteine-targeting warheads with privileged scaffolds reported as noncovalent inhibitors is a feasible and efficient strategy to develop novel potent Mpro inhibitors. Taking previous findings into account with the goal to design covalent Mpro inhibitors with improved potency and selectivity, the S1 nicotinoyl group of GC-14 was replaced to attach covalent warheads extending to Cys145 in the S1 pocket of the enzyme. Altogether, 30 covalent inhibitors with a piperazine scaffold containing different warheads were synthesized and evaluated leading to potent Mpro inhibitors that possess strong antiviral activity. This novel series of nonpeptidic covalent SARS-CoV-2 Mpro inhibitors serve as a valuable basis for the further development of potential clinical candidates for COVID-19 therapy. 4 Experimental Section 4.1 Chemistry 4.1.1 Synthetic Procedures and Analytical Data The solvents and reagents were purchased from commercial suppliers and used as received. All reactions were routinely monitored by thin-layer chromatography (TLC) on silica gel GF254. Column chromatography was performed on columns packed with silica gel (200–300 mesh) purchased from Qingdao Haiyang Chemical Company. All melting points (mp) were determined on a micro melting point apparatus (RY-1G, Tianjin TianGuang Optical Instruments). 1H NMR and 13C NMR spectra were obtained on a Bruker AV-600 MHz spectrometer (Bruker BioSpin, Fällanden, Switzerland) in DMSO-d6. Chemical shifts were expressed in δ units (ppm), using trimethylsilane (TMS) as an internal standard, and J values were reported in Hertz (Hz). The high-resolution mass spectra (HRMS) of representative compounds were performed on an LTQ Orbitrap XL (Thermo Fisher). The purity of representative final compounds was evaluated on a Shimadzu HPLC system. HPLC conditions were as follows: Agilent ZORBAX, SB-C18 column (250 mm × 4.6 mm × 5 μm); isocratic elution method: mobile phase A: methanol (80%); mobile phase B: water (20%); flow rate 1.0 mL/min; wavelength: 254 nm, temperature, 30 °C. All tested compounds possessed purities of >95%. 4.1.2 General Synthetic Procedure for the Intermediates of the GC Series 4.1.2.1 1-(tert-Butyl)-3-methyl (S)-4-(3,4-Dichlorophenyl)piperazine-1,3-dicarboxylate (3) A 250 mL round-bottom flask was charged with 3,4-dichlorophenylboronic acid (compound 1) (7.8 g, 41.1 mmol) and 1-(tert-butyl) 3-methyl (S)-piperazine-1,3-dicarboxylate (compound 2) (5.0 g, 20.5 mmol), which were dissolved with 80 mL of DCM under stirring. Anhydrous copper(II) acetate (3.75 g, 20.7 mmol) and pyridine (3.24 g, 41.0 mmol) were then added to the mixture simultaneously. The mixture was stirred under an oxygen atmosphere and room temperature for 12 h, then washed with water (4 mL × 60 mL) in a separating funnel to remove the copper salt and pyridine. The resulting organic phase was separated, dried over anhydrous MgSO4, then the organic solvent was removed under reduced pressure. The resulting dark-green oil was purified through silica gel column chromatography (EtOAc/hexane = 1:20) to give compound 3 (4.05 g, 10.4 mmol, 51%) as a colorless thick oil. ESI-MS: m/z 389.2 [M + H]+. C17H22Cl2N2O4 (388.1). 4.1.2.2 (S)-4-(tert-Butoxycarbonyl)-1-(3,4-dichlorophenyl)piperazine-2-carboxylic acid (4) LiOH (1 M aqueous solution, 41.2 mL, 41.2 mmol) was added dropwise in an ice bath to a stirred solution of compound 3 (4.0 g, 10.3 mmol) in THF/MeOH (60 mL, v/v = 1:1). Then, the mixture was allowed to react at room temperature for 7 h. When the reaction finished, organic solvents in the mixture were removed under reduced pressure. The resulting aqueous solution was again cooled in an ice bath. 1 M HCl was added dropwise accompanied with stirring. The water phase along with precipitates was extracted with EtOAc (4 mL × 30 mL). The organic phase was collected and dried over anhydrous Na2SO4, and concentrated under reduced pressure to give compound 4 (3.59 g, 9.60 mmol, 93%) as a colorless foam. ESI-MS m/z [M + H]+ calcd for C16H20Cl2N2O4, 374.1; found 375.1. 4.1.2.3 tert-Butyl (S)-4-(3,4-Dichlorophenyl)-3-((thiophen-2-ylmethyl)carbamoyl) piperazine-1-carboxylate (5) HATU (5.59 g, 14.4 mmol) was added to a suspension of compound 4 (3.59 g, 9.60 mmol) and DCM (80 mL) in a 0 °C ice bath and stirred for 30 min. Then, DIPEA (3.71 g, 28.8 mmol, 3.0 equiv) and thiophen-2-ylmethanamine (1.30 g, 11.5 mmol, 1.2 equiv) were added to the system successively. The reaction was stirred for 9 h at room temperature. Upon completion, the reaction mixture was washed with 0.5 M HCl, water, and saturated NaCl solution successively, dried over anhydrous Na2SO4, and evaporated under reduced pressure. The residue was purified by flash column chromatography (MeOH/DCM = 1:60) on silica gel to yield 5 (4.03 g, 8.60 mmol, 89%) as a light-yellow solid. ESI-MS m/z [M + H]+ calcd for C21H25Cl2N3O3S, 469.1; found 470.1. 4.1.2.4 (S)-1-(3,4-Dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide trifluoroacetate (6) Compound 5 (4.0 g, 8.53 mmol) was dissolved in DCM (40 mL) in an ice bath with stirring. A mixture of trifluoroacetic acid (6.8 g, 59.7 mmol) and DCM (25 mL) was added through a dropping funnel dropwise in a 0 °C ice bath. Upon finishing, the organic solution was evaporated under reduced pressure to remove DCM and trifluoroacetic acid. The remaining oil was redissolved in 50 mL of DCM, and 40 mL of saturated Na2CO3 aqueous solution was added. After vigorous stirring, the organic phase was separated, washed with saturated NaCl solution, and dried over anhydrous Na2SO4, then concentrated under reduced pressure. Compound 6 was thus acquired (3.38 g, 7.00 mmol, 82%) as a light-brown solid. 1H NMR (400 MHz, DMSO-d6) δ 9.09 (s, 1H), 8.49 (s, 1H), 7.58–7.37 (m, 2H), 7.22–7.13 (m, 1H), 7.08–6.87 (m, 3H), 4.71–4.53 (m, 2H), 4.48 (dd, J = 25.7, 5.8 Hz, 1H), 3.69 (dd, J = 53.0, 13.3 Hz, 2H), 3.53 (d, J = 11.9 Hz, 1H), 3.26 (d, J = 13.1 Hz, 2H), 3.10 (d, J = 20.9 Hz, 1H). ESI-MS m/z [M + H]+ calcd for C16H17Cl2N3OS, 369.0; found, 370.1. 4.1.3 General Procedure for GD-1 and GD-2 DIPEA (0.128 g, 1.0 mmol, 4.0 equiv) and compound 6 (0.12 g, 0.25 mmol, 1.0 equiv) were added successively into 6 mL of DCM under stirring. The mixture was cooled in an ice bath, then various sulfonyl chlorides (0.30 mmol, 1.2 equiv) were added into the system. The reaction was carried out at room temperature for another 2 h. Then, sulfonyl chlorides were quenched by saturated NaHCO3. Organic phase was separated, washed with saturated NaCl solution, dried over anhydrous Na2SO4, and concentrated under reduced pressure. The resulting crude products were separated by flash column chromatography on silica gel (MeOH/DCM = 1:80) to give final products. 4.1.3.1 (S,E)-1-(3,4-Dichlorophenyl)-4-(styrylsulfonyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-1) White solid. Yield: 70%, mp: 182–184 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.67 (t, J = 5.9 Hz, 1H), 7.73 (dd, J = 7.5, 2.2 Hz, 2H), 7.46–7.41 (m, 4H), 7.38–7.33 (m, 2H), 7.24 (d, J = 15.4 Hz, 1H), 7.01 (d, J = 2.9 Hz, 1H), 6.94–6.89 (m, 2H), 6.82 (dd, J = 9.0, 3.0 Hz, 1H), 4.49 (t, J = 3.8 Hz, 1H), 4.42 (d, J = 5.9 Hz, 2H), 3.94 (d, J = 10.8 Hz, 1H), 3.68 (dt, J = 14.0, 4.2 Hz, 1H), 3.57–3.49 (m, 2H), 3.20 (dd, J = 12.3, 4.5 Hz, 1H), 2.98 (td, J = 11.7, 10.9, 3.6 Hz, 1H). 13C NMR (150 MHz, DMSO-d6) δ 169.62, 149.86, 143.30, 142.74, 133.12, 132.00, 131.32, 130.88, 129.39, 129.22, 127.06, 125.51, 125.30, 122.81, 120.18, 116.40, 115.25, 57.71, 47.07, 44.94, 44.33, 37.91. ESI-MS: m/z 536.0 [M + H]+. C24H23Cl2N3O3S2 (535.06). 4.1.3.2 (S)-1-(3,4-Dichlorophenyl)-N-(thiophen-2-ylmethyl)-4-(vinylsulfonyl)piperazine-2-carboxamide (GD-2) White solid. Yield: 90%, mp: 158–160 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.67 (t, J = 6.0 Hz, 1H), 7.40–7.37 (m, 1H), 7.03 (d, J = 3.0 Hz, 1H), 6.93 (d, J = 3.5 Hz, 2H), 6.83 (dd, J = 9.0, 3.0 Hz, 1H), 6.74 (dd, J = 16.5, 10.0 Hz, 1H), 6.20–6.08 (m, 2H), 4.49 (dd, J = 4.4, 2.8 Hz, 1H), 4.44 (d, J = 5.9 Hz, 2H), 3.90 (dt, J = 12.2, 2.2 Hz, 1H), 3.67 (dt, J = 12.4, 3.7 Hz, 1H), 3.51 (ddd, J = 12.4, 10.4, 3.7 Hz, 1H), 3.48–3.42 (m, 1H), 3.10 (dd, J = 12.3, 4.3 Hz, 1H), 2.89 (ddd, J = 11.4, 9.9, 3.6 Hz, 1H). 13C NMR (150 MHz, DMSO-d6) δ 169.53, 149.86, 142.70, 133.14, 132.02, 130.90, 129.91, 127.07, 125.61, 125.34, 120.20, 116.41, 115.27, 57.64, 46.95, 44.78, 44.30, 37.92. ESI-MS: m/z 460.2 [M + H]+. C24H21Cl2N3O3S (459.02). 4.1.3.3 Procedure for (S)-4-(3,4-Dichlorophenyl)-3-((thiophen-2-ylmethyl)carbamoyl) Piperazine-1-sulfonyl fluoride (GD-3) Compound 6 (0.12 g, 0.25 mmol, 1.0 equiv) was dissolved in 8 mL of acetonitrile in an ice bath with stirring. 1-(Fluorosulfonyl)-2,3-dimethyl-1H-imidazol-3-ium trifluoromethanesulfonate (0.082 g, 0.25 mmol, 1.0 equiv) was dissolved in 5 mL of acetonitrile, then added to the reaction dropwise. The mixture was stirred at room temperature for 2 h, then acetonitrile was removed under reduced pressure. The remaining solid was resuspended in a mixture of 2 mL of hexane and 2 mL of DCM and stirred for 30 min. The purified product was filtered out of the mixture as a white solid. Yield: 90%, mp: 153–156 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.79 (t, J = 5.9 Hz, 1H), 7.48–7.35 (m, 2H), 7.07 (d, J = 3.0 Hz, 1H), 7.00–6.90 (m, 2H), 6.86 (dd, J = 9.0, 3.0 Hz, 1H), 4.72–4.58 (m, 1H), 4.46 (d, J = 5.9 Hz, 2H), 4.26–4.11 (m, 1H), 3.76 (td, J = 13.2, 3.9 Hz, 2H), 3.56 (td, J = 15.4, 13.9, 4.6 Hz, 2H), 3.47–3.32 (m, 2H). 13C NMR (150 MHz, DMSO-d6) δ 168.98, 149.47, 142.63, 132.08, 130.97, 127.06, 125.64, 125.41, 120.47, 116.49, 115.28, 57.31, 47.62, 46.08, 43.44, 37.98. HRMS (ESI) m/z [M + H]+ calcd for C16H16Cl2FN3O3S2, 450.9994; found, 452.0069. HPLC purity: 98.00%. 4.1.4 General Procedure for GD-4–GD-30 A dried 25 mL flask was charged with 9 mL of DCM and a stir bar. Various carboxylic acids (0.31 mmol, 1.1 equiv) and HATU (0.42 mmol, 1.5 equiv) were added, then the mixture was stirred for 30 min at 0 °C. DIPEA (0.84 mmol, 3 equiv) and intermediate 6 (0.28 mmol, 1.0 equiv) were added to the system. The mixture was warmed to room temperature and stirred for 5 h. When the reaction was finished monitoring by TLC, the organic solution was washed by 1 M HCl, saturated NaHCO3 solution, and saturated NaCl solution successively. The organic layer was dried over anhydrous Na2SO4 and concentrated under reduced pressure. Residue oil was purified by flash column chromatography (MeOH/DCM = 1:80) on silica gel to afford the final products. 4.1.4.1 (S)-2-(4-(3,4-Dichlorophenyl)-3-((thiophen-2-ylmethyl)carbamoyl)piperazin-1-yl)-1,1-difluoro-2-oxoethane-1-sulfonyl fluoride (GD-4) White solid. Yield: 46%, mp: 130–132 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.93 (t, J = 5.9 Hz, 1H), 8.84 (d, J = 4.4 Hz, 1H), 8.77–8.66 (m, 1H), 7.64 (dt, J = 8.1, 3.9 Hz, 1H), 7.44 (d, J = 9.0 Hz, 1H), 7.39–7.29 (m, 1H), 7.02 (dd, J = 14.0, 3.0 Hz, 1H), 6.98–6.87 (m, 2H), 6.82 (ddd, J = 17.1, 9.0, 3.0 Hz, 1H), 4.59–4.48 (m, 2H), 4.48–4.42 (m, 1H), 4.26–4.13 (m, 1H), 3.86 (tt, J = 9.9, 5.3 Hz, 1H), 3.72 (dt, J = 35.9, 7.5 Hz, 2H), 3.57–3.45 (m, 1H). 13C NMR (150 MHz, DMSO-d6) δ 169.70, 152.88, 140.58, 134.79, 132.09, 130.98, 130.17, 127.07, 125.69, 125.45, 121.64, 115.73, 114.67, 58.58, 44.88, 38.07, 29.54, 27.40. HRMS (ESI) m/z [M + H]+ calcd for C18H16Cl2F3N3O4S2, 528.9911; found, 532.0725. HPLC purity: 99.13%. 4.1.4.2 (S)-1-(3,4-Dichlorophenyl)-4-(2-oxopropanoyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-5) Yellow solid. Yield: 74%, mp: 145–147 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.76 (t, J = 6.0 Hz, 1H), 7.44–7.32 (m, 2H), 7.01 (dd, J = 41.8, 3.0 Hz, 1H), 6.95–6.87 (m, 2H), 6.81 (ddd, J = 32.4, 9.1, 3.0 Hz, 1H), 4.50–4.32 (m, 3H), 4.04–3.97 (m, 1H), 3.71 (ddt, J = 25.0, 12.9, 4.4 Hz, 1H), 3.63 (dd, J = 13.8, 4.2 Hz, 1H), 3.61–3.52 (m, 1H), 3.45–3.37 (m, 1H), 3.17 (ddd, J = 13.4, 9.7, 3.9 Hz, 1H), 2.31 (d, J = 33.3 Hz, 3H). 13C NMR (150 MHz, DMSO-d6) δ 199.19, 170.10, 165.96, 149.48, 143.74, 132.09, 130.94, 127.06, 125.74, 125.44, 119.95, 116.03, 114.87, 58.57, 45.64, 44.22, 43.14, 37.97, 27.69. HRMS (ESI) m/z [M + H]+ calcd for C19H19Cl2N3O3S, 439.0524; found, 440.0590. HPLC purity: 97.10%. 4.1.4.3 (S)-1-(3,4-Dichlorophenyl)-4-(2-oxo-2-phenylacetyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-6) Light-yellow oil. Yield: 60%. 1H NMR (600 MHz, DMSO-d6) δ 8.74 (dt, J = 137.8, 6.1 Hz, 1H), 7.95–7.91 (m, 1H), 7.86–7.83 (m, 1H), 7.76 (q, J = 7.5, 6.8 Hz, 1H), 7.64–7.56 (m, 2H), 7.40 (d, J = 10.0 Hz, 1H), 7.37–7.33 (m, 1H), 6.99 (dd, J = 26.4, 3.0 Hz, 1H), 6.96–6.91 (m, 1H), 6.91–6.80 (m, 1H), 6.79 (dd, J = 8.5, 3.6 Hz, 1H), 4.73–4.55 (m, 1H), 4.49 (d, J = 5.8 Hz, 1H), 4.36–4.29 (m, 1H), 4.19 (dt, J = 13.1, 4.8 Hz, 1H), 3.90–3.83 (m, 1H), 3.82–3.71 (m, 1H), 3.69–3.62 (m, 1H), 3.55–3.48 (m, 2H), 3.47–3.36 (m, 1H). 13C NMR (150 MHz, DMSO-d6) δ 191.31, 169.81, 165.53, 150.43, 143.26, 135.69, 135.49, 132.09, 130.96, 130.09, 129.92, 129.52, 127.10, 127.04, 125.69, 125.39, 120.22, 116.54, 114.95, 58.16, 46.37, 43.97, 43.07, 37.88. HRMS (ESI) m/z [M + H]+ calcd for C24H21Cl2N3O3S, 501.0681; found, 502.0755. HPLC purity: 94.61%. 4.1.4.4 (S)-1-(3,4-Dichlorophenyl)-4-(2-oxo-2-(thiophen-2-yl)acetyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-7) Light-yellow solid. Yield: 60%, mp: 108–110 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.76 (dt, J = 118.1, 5.9 Hz, 1H), 8.28–8.19 (m, 1H), 7.81 (dd, J = 113.8, 3.9 Hz, 1H), 7.40 (d, J = 9.0 Hz, 1H), 7.37–7.29 (m, 2H), 6.99 (dd, J = 32.3, 3.0 Hz, 1H), 6.94–6.75 (m, 3H), 4.68–4.53 (m, 1H), 4.51–4.41 (m, 1H), 4.34–4.29 (m, 1H), 4.01–3.87 (m, 1H), 3.83–3.68 (m, 1H), 3.67–3.58 (m, 1H), 3.55–3.45 (m, 2H), 3.40–3.33 (m, 1H). 13C NMR (150 MHz, DMSO-d6) δ 183.37, 170.60, 164.65, 149.69, 142.36, 139.99, 138.72, 137.96, 132.62, 130.96, 129.91, 127.11, 127.06, 125.71, 125.48, 125.40, 120.25, 116.05, 114.92, 58.17, 46.54, 43.98, 42.63, 37.62. ESI-MS: m/z 508.0 [M + H]+. C22H19Cl2N3O3S2 (507.02). 4.1.4.5 (S)-1-(3,4-Dichlorophenyl)-4-(2-(furan-2-yl)-2-oxoacetyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-8) Light-yellow solid. Yield: 61%, mp: 102–104 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.76 (dt, J = 108.3, 5.9 Hz, 1H), 8.18 (dd, J = 14.8, 1.7 Hz, 1H), 7.53 (d, J = 3.6 Hz, 1H), 7.40 (dd, J = 9.1, 1.4 Hz, 1H), 7.36 (td, J = 4.1, 3.5, 1.6 Hz, 1H), 6.99 (dd, J = 27.0, 3.0 Hz, 1H), 6.93–6.77 (m, 4H), 4.64–4.52 (m, 1H), 4.45 (qd, J = 15.4, 5.9 Hz, 1H), 4.40–4.31 (m, 1H), 4.08–3.92 (m, 1H), 3.74 (ddd, J = 30.8, 13.4, 4.7 Hz, 1H), 3.62 (dt, J = 12.5, 4.4 Hz, 1H), 3.54–3.43 (m, 2H), 3.35 (ddd, J = 13.2, 9.1, 4.1 Hz, 1H). 13C NMR (150 MHz, DMSO-d6) δ 178.61, 169.84, 163.82, 151.08, 149.89, 149.68, 142.47, 132.06, 129.41, 127.06, 125.70, 125.40, 123.90, 120.26, 116.06, 114.94, 113.74, 58.24, 45.59, 44.91, 42.67, 37.83. ESI-MS: m/z 492.1 [M + H]+. C22H19Cl2N3O4S (491.05). 4.1.4.6 (S)-4-(2-Chloroacetyl)-1-(3,4-dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-9) White solid. Yield: 83%, mp: 138–140 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.77 (d, J = 4.7 Hz, 1H), 7.47–7.31 (m, 2H), 6.98 (dd, J = 46.1, 3.0 Hz, 1H), 6.93–6.88 (m, 2H), 6.78 (ddd, J = 38.3, 9.1, 3.0 Hz, 1H), 4.49–4.35 (m, 4H), 4.30 (t, J = 11.1 Hz, 1H), 4.18–4.08 (m, 1H), 3.89 (ddt, J = 95.6, 11.5, 5.8 Hz, 1H), 3.68–3.56 (m, 2H), 3.42 (dd, J = 13.8, 4.9 Hz, 1H), 3.25–3.12 (m, 1H). 13C NMR (150 MHz, DMSO-d6) δ 170.16, 165.10, 150.90, 142.63, 132.03, 130.89, 127.06, 125.80, 125.47, 120.73, 117.09, 114.64, 58.75, 46.03, 44.14, 43.35, 42.06, 38.35. HRMS (ESI) m/z [M + H]+ calcd for C18H18Cl3N3O2S, 445.0185; found, 446.0262. HPLC purity: 98.84%. 4.1.4.7 (S)-4-(2,2-Dichloroacetyl)-1-(3,4-dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-10) White solid. Yield: 80%, mp: 186–188 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.77 (dt, J = 24.6, 6.0 Hz, 1H), 7.39 (dd, J = 9.0, 2.2 Hz, 1H), 7.35 (ddd, J = 6.5, 5.0, 1.3 Hz, 1H), 7.13 (d, J = 80.5 Hz, 1H), 6.98 (dd, J = 20.2, 3.0 Hz, 1H), 6.91 (dt, J = 5.2, 3.0 Hz, 1H), 6.89 (s, 1H), 6.78 (ddd, J = 18.4, 9.0, 3.0 Hz, 1H), 4.51–4.44 (m, 1H), 4.42–4.37 (m, 2H), 4.38–4.22 (m, 1H), 3.97–3.87 (m, 1H), 3.66–3.57 (m, 2H), 3.48 (dd, J = 13.7, 4.8 Hz, 1H), 3.42–3.33 (m, 1H). 13C NMR (150 MHz, DMSO-d6) δ 170.81, 161.70, 150.64, 143.21, 132.03, 130.90, 127.97, 125.71, 125.53, 121.15, 115.46, 113.87, 66.52, 58.21, 45.97, 44.06, 42.74, 37.35. ESI-MS: m/z 480.0 [M + H]+. C18H17Cl4N3O2S (478.98). 4.1.4.8 (S)-4-(2-Chloro-2,2-difluoroacetyl)-1-(3,4-dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-11) White solid. Yield: 70%, mp: 118–120 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.86 (dt, J = 44.9, 5.9 Hz, 1H), 7.42 (d, J = 2.1 Hz, 2H), 7.01–6.86 (m, 3H), 6.77 (ddd, J = 29.5, 9.1, 3.0 Hz, 1H), 4.56–4.41 (m, 2H), 4.38–4.34 (m, 1H), 3.99–3.93 (m, 1H), 3.69–3.54 (m, 3H), 3.54–3.35 (m, 1H). 13C NMR (150 MHz, DMSO-d6) δ 169.72, 159.72, 153.29, 149.33, 142.56, 132.83, 130.97, 127.48, 125.83, 125.52, 124.54, 115.65, 114.54, 58.40, 51.83, 44.77, 43.49, 37.83. ESI-MS: m/z 480.2 [M - H]−. C18H16Cl3F2N3O2S (481.00). 4.1.4.9 (2S)-4-(2-Bromo-2-chloroacetyl)-1-(3,4-dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-12) White solid. Yield: 82%, mp: 162–164 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.77 (dq, J = 29.6, 6.1 Hz, 1H), 7.39 (d, J = 7.3 Hz, 1H), 7.38–7.32 (m, 1H), 7.19–7.00 (m, 1H), 6.99–6.93 (m, 1H), 6.93–6.86 (m, 2H), 6.83–6.73 (m, 1H), 4.52–4.45 (m, 1H), 4.45–4.34 (m, 2H), 4.29–4.20 (m, 1H), 3.98–3.92 (m, 1H), 3.72–3.59 (m, 2H), 3.56–3.37 (m, 3H). 13C NMR (150 MHz, DMSO-d6) δ 170.24, 163.04, 152.64, 150.20, 144.81, 133.75, 130.89, 127.06, 125.47, 119.81, 115.81, 113.90, 58.58, 52.38, 46.26, 44.48, 43.27, 37.38. ESI-MS: m/z 523.9 [M + H]+. C18H17BrCl3N3O2S (522.93). 4.1.4.10 (S)-4-(2-Bromoacetyl)-1-(3,4-dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-13) White solid. Yield: 78%, mp: 152–154 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.90–8.74 (m, 1H), 7.45–7.27 (m, 2H), 7.02 (dd, J = 43.1, 2.8 Hz, 1H), 6.96–6.89 (m, 2H), 6.88–6.71 (m, 1H), 4.63–4.21 (m, 4H), 4.19–3.77 (m, 3H), 3.73–3.48 (m, 2H), 3.48–3.36 (m, 1H), 3.34–3.07 (m, 1H). 13C NMR (150 MHz, DMSO-d6) δ 172.96, 170.30, 150.19, 143.30, 132.01, 130.88, 127.05, 125.70, 125.41, 119.65, 115.63, 114.54, 60.33, 58.66, 55.37, 54.29, 43.86, 37.88. HRMS (ESI) m/z [M + H]+ calcd for C18H18BrCl2N3O2S 488.9680; found, 489.9753. HPLC purity: 99.20%. 4.1.4.11 (S)-4-(2,2-Dibromoacetyl)-1-(3,4-dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-14) White solid. Yield: 81%, mp: 158–160 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.76 (dt, J = 33.7, 6.0 Hz, 1H), 7.39 (d, J = 9.0 Hz, 1H), 7.37–7.31 (m, 1H), 7.09–6.97 (m, 1H), 6.95 (d, J = 2.9 Hz, 1H), 6.94–6.85 (m, 2H), 6.77 (ddd, J = 20.0, 9.1, 3.0 Hz, 1H), 4.51–4.39 (m, 3H), 4.38–4.34 (m, 1H), 3.98–3.86 (m, 1H), 3.66–3.55 (m, 2H), 3.50–3.42 (m, 1H). 13C NMR (150 MHz, DMSO-d6) δ 170.73, 164.92, 150.19, 142.74, 132.02, 130.88, 127.71, 125.69, 125.52, 125.28, 119.75, 115.41, 113.51, 58.42, 55.72, 44.12, 38.35, 37.94. ESI-MS: m/z 568.1 [M + H]+. C18H17Br2Cl2N3O2S (566.88). 4.1.4.12 (S)-4-(2-Cyanoacetyl)-1-(3,4-dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-15) White solid. Yield: 69%, mp: 188–190 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.78 (dt, J = 24.4, 6.0 Hz, 1H), 7.39 (dd, J = 9.0, 5.3 Hz, 1H), 7.37–7.34 (m, 1H), 7.05–6.91 (m, 2H), 6.90 (d, J = 3.3 Hz, 1H), 6.78 (ddd, J = 50.4, 9.1, 3.0 Hz, 1H), 4.47 (t, J = 3.4 Hz, 1H), 4.42 (dd, J = 9.6, 5.6 Hz, 2H), 4.12–4.03 (m, 1H), 4.02–3.89 (m, 2H), 3.69 (d, J = 18.9 Hz, 1H), 3.58 (ddd, J = 18.2, 12.8, 3.8 Hz, 2H), 3.50–3.40 (m, 1H), 3.38–3.32 (m, 1H). 13C NMR (150 MHz, DMSO-d6) δ 169.31, 161.99, 149.53, 142.61, 132.63, 130.89, 127.08, 125.81, 125.57, 125.31, 119.80, 115.90, 114.74, 58.72, 46.08, 44.34, 41.60, 37.97, 24.92. ESI-MS: m/z 437.1 [M + H]+. C19H18Cl2N4O2S (436.05). 4.1.4.13 (S)-1-(3,4-Dichlorophenyl)-4-(2-hydroxyacetyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-16) White solid. Yield: 91%, mp: 185–188 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.76 (q, J = 6.2, 5.3 Hz, 1H), 7.37 (dd, J = 16.8, 7.0 Hz, 2H), 7.02–6.83 (m, 3H), 6.81–6.72 (m, 1H), 4.57 (q, J = 5.0, 4.1 Hz, 1H), 4.50–4.34 (m, 3H), 4.09 (dt, J = 14.8, 7.6 Hz, 1H), 4.05–3.95 (m, 2H), 3.64–3.52 (m, 3H), 3.45–3.41 (m, 1H), 3.16–3.12 (m, 1H). 1H NMR (600 MHz, DMSO-d6) δ 8.76 (q, J = 6.2, 5.3 Hz, 1H), 7.37 (dd, J = 16.8, 7.0 Hz, 2H), 7.02–6.83 (m, 3H), 6.81–6.72 (m, 1H), 4.57 (q, J = 5.0, 4.1 Hz, 1H), 4.50–4.34 (m, 3H), 4.09 (dt, J = 14.8, 7.6 Hz, 1H), 4.05–3.95 (m, 2H), 3.64–3.52 (m, 3H), 3.45–3.41 (m, 1H), 3.16–3.12 (m, 1H). HRMS (ESI) m/z [M + H]+ calcd for C18H19Cl2N3O3S, 427.0524; found, 428.0588. HPLC purity: 96.91%. 4.1.4.14 (S)-1-(3,4-Dichlorophenyl)-4-(thiazole-2-carbonyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-17) White solid. Yield: 79%, mp: 118–120 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.81 (dt, J = 50.5, 5.8 Hz, 1H), 8.07–7.95 (m, 2H), 7.40 (d, J = 9.1 Hz, 1H), 7.29 (dd, J = 13.5, 5.0 Hz, 1H), 6.96 (d, J = 3.0 Hz, 1H), 6.82 (ddd, J = 57.3, 8.9, 3.2 Hz, 3H), 4.78 (d, J = 117.1 Hz, 1H), 4.44 (d, J = 14.9 Hz, 1H), 4.37 (d, J = 25.5 Hz, 1H), 4.26 (qd, J = 15.3, 5.7 Hz, 1H), 4.21–4.09 (m, 1H), 4.08–3.98 (m, 1H), 3.73–3.44 (m, 3H). 13C NMR (150 MHz, DMSO-d6) δ 170.59, 164.69, 160.40, 151.80, 143.90, 142.54, 132.05, 131.37, 126.98, 125.85, 125.43, 125.33, 119.67, 116.22, 114.21, 59.42, 47.29, 43.88, 43.10, 37.76. ESI-MS: m/z 481.0 [M + H]+. C20H18Cl2N4O2S2 (480.02). 4.1.4.15 (S)-4-(Benzo[d]thiazole-2-carbonyl)-1-(3,4-dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-18) White solid. Yield: 60%, mp: 112–114 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.84 (dt, J = 62.1, 5.8 Hz, 1H), 8.22 (d, J = 9.3 Hz, 1H), 8.14 (dd, J = 20.0, 8.4 Hz, 1H), 7.67–7.56 (m, 2H), 7.41 (d, J = 9.0 Hz, 1H), 7.17 (dd, J = 74.3, 6.4 Hz, 1H), 6.98 (dd, J = 7.7, 2.9 Hz, 1H), 6.92–6.81 (m, 1H), 6.79 (dd, J = 9.1, 2.7 Hz, 1H), 6.76–6.65 (m, 1H), 4.78 (ddd, J = 81.1, 12.0, 3.1 Hz, 1H), 4.55–4.44 (m, 1H), 4.44–4.36 (m, 1H), 4.24 (qd, J = 15.4, 5.8 Hz, 2H), 4.10 (dd, J = 14.0, 4.4 Hz, 1H), 3.76–3.43 (m, 3H). 13C NMR (150 MHz, DMSO-d6) δ 170.48, 164.84, 159.90, 152.99, 149.71, 141.21, 136.45, 133.07, 130.95, 127.45, 127.41, 126.86, 125.33, 125.10, 124.80, 122.27, 119.77, 115.39, 114.31, 58.56, 46.91, 45.65, 43.25, 37.71. HRMS (ESI) m/z [M + H]+ calcd for C24H20Cl2N4O2S2, 530.0405; found, 531.0475. HPLC purity: 98.43%. 4.1.4.16 (S)-(3-(4-(3,4-Dichlorophenyl)-3-((thiophen-2-ylmethyl)carbamoyl)piperazine-1-carbonyl)-5-nitrophenyl)boronic acid (GD-19) White solid. Yield: 72%, mp: 108–110 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.76 (d, J = 76.0 Hz, 1H), 8.68–8.43 (m, 2H), 8.32–7.97 (m, 2H), 7.47–7.16 (m, 2H), 7.03–6.62 (m, 4H), 4.49 (d, J = 33.4 Hz, 2H), 4.18 (d, J = 74.0 Hz, 2H), 3.85 (s, 1H), 3.68–3.49 (m, 3H), 3.10 (s, 1H). 13C NMR (150 MHz, DMSO-d6) δ 173.33, 166.98, 152.90, 149.07, 147.50, 141.55, 136.27, 131.70, 130.87, 129.13, 127.39, 126.93, 125.54, 125.21, 121.72, 119.36, 115.58, 113.61, 62.83, 53.97, 42.29, 40.62, 37.90, 18.49. ESI-MS: m/z 563.1 [M + H]+. C23H21BCl2N4O6S (562.07). 4.1.4.17 (S,E)-1-(3,4-Dichlorophenyl)-N-(thiophen-2-ylmethyl)-4-(4,4,4-trifluorobut-2-enoyl)piperazine-2-carboxamide (GD-20) White solid. Yield: 69%, mp: 106–108 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.78 (dt, J = 25.5, 6.0 Hz, 1H), 7.40 (d, J = 9.0 Hz, 1H), 7.33 (ddd, J = 11.6, 5.0, 1.3 Hz, 1H), 7.29–7.19 (m, 1H), 6.98 (dd, J = 45.8, 2.9 Hz, 1H), 6.92–6.86 (m, 2H), 6.83–6.75 (m, 1H), 6.75–6.67 (m, 1H), 4.49–4.28 (m, 4H), 4.12–3.93 (m, 1H), 3.62 (dddd, J = 25.5, 18.1, 9.8, 5.0 Hz, 2H), 3.50–3.41 (m, 1H), 3.23 (ddd, J = 13.3, 9.2, 3.8 Hz, 1H). 13C NMR (150 MHz, DMSO-d6) δ 170.01, 162.42, 149.71, 142.57, 132.03, 130.90, 130.41, 127.01, 125.65, 125.37, 124.37, 122.58, 119.78, 115.74, 114.62, 58.74, 46.42, 43.29, 41.79, 37.88. ESI-MS: m/z 492.1 [M + H]+, C20H18Cl2F3N3O2S (491.04). 4.1.4.18 (S)-4-Acryloyl-1-(3,4-dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-21) White solid. Yield: 61%, mp: 96–100 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.76 (d, J = 35.2 Hz, 1H), 7.49–7.29 (m, 2H), 7.05–6.85 (m, 3H), 6.76 (dd, J = 33.2, 9.1 Hz, 1H), 6.70–6.59 (m, 1H), 6.09 (dd, J = 37.9, 16.7 Hz, 1H), 5.67 (dd, J = 39.4, 10.5 Hz, 1H), 4.39 (s, 2H), 4.37–4.29 (m, 1H), 4.11–3.90 (m, 1H), 3.72–3.64 (m, 1H), 3.59 (s, 2H), 3.45 (d, J = 18.5 Hz, 1H), 3.23 (d, J = 10.5 Hz, 1H). 13C NMR (150 MHz, DMSO-d6) δ 170.36, 165.79, 149.89, 142.77, 132.01, 130.88, 128.37, 127.68, 127.04, 125.69, 125.06, 120.38, 115.91, 114.40, 59.34, 46.53, 43.44, 41.23, 37.41. ESI-MS: m/z 424.0 [M + H]+, C19H19Cl2N3O2S (423.06). 4.1.4.19 (S)-1-(3,4-Dichlorophenyl)-4-(2-fluoroacryloyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-22) White solid. Yield: 78%, mp: 100–102 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.79 (t, J = 6.0 Hz, 1H), 7.40 (d, J = 9.0 Hz, 1H), 7.36 (dd, J = 5.0, 1.3 Hz, 1H), 6.95 (d, J = 3.0 Hz, 1H), 6.92 (dd, J = 5.0, 3.4 Hz, 1H), 6.90–6.86 (m, 1H), 6.76 (dd, J = 9.0, 3.0 Hz, 1H), 5.28 (d, J = 17.7 Hz, 1H), 5.16 (dd, J = 49.7, 4.0 Hz, 1H), 4.45 (dd, J = 15.4, 6.1 Hz, 1H), 4.41–4.19 (m, 3H), 3.87 (d, J = 81.0 Hz, 2H), 3.67–3.43 (m, 3H). 13C NMR (150 MHz, DMSO-d6) δ 170.37, 161.17, 160.97, 149.64, 142.63, 132.05, 130.92, 127.04, 125.62, 125.36, 119.80, 115.45, 114.36, 99.83, 58.73, 52.99, 50.16, 43.62, 37.89. ESI-MS: m/z 442.2 [M + H]+, C19H18Cl2FN3O2S (441.05). 4.1.4.20 (S)-4-(But-2-ynoyl)-1-(3,4-dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-23) White solid. Yield: 69%, mp: 120–122 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.76 (dt, J = 32.5, 6.0 Hz, 1H), 7.43–7.33 (m, 2H), 6.96 (dd, J = 4.5, 2.9 Hz, 1H), 6.94–6.86 (m, 2H), 6.78 (dt, J = 9.1, 3.6 Hz, 1H), 4.54–4.35 (m, 4H), 4.08–3.95 (m, 1H), 3.63–3.53 (m, 2H), 3.51 (ddd, J = 12.5, 8.8, 4.2 Hz, 1H), 3.22 (ddd, J = 13.1, 8.8, 4.3 Hz, 1H), 2.01 (d, J = 27.6 Hz, 3H). 13C NMR (150 MHz, DMSO-d6) δ 170.26, 152.88, 149.83, 142.66, 132.04, 130.91, 127.06, 125.61, 119.83, 115.60, 114.52, 89.47, 73.24, 58.55, 47.32, 45.25, 44.10, 43.11, 40.89, 37.89. ESI-MS: m/z 436.0 [M + H]+, C20H19Cl2N3O2S (435.06). 4.1.4.21 (S)-1-(3,4-Dichlorophenyl)-4-propioloyl-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-24) White solid. Yield: 63%, mp: 120–124 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.78 (dt, J = 26.9, 5.9 Hz, 1H), 7.40 (dd, J = 9.0, 2.4 Hz, 1H), 7.36 (td, J = 4.9, 1.3 Hz, 1H), 6.97 (dd, J = 7.7, 2.9 Hz, 1H), 6.95–6.85 (m, 2H), 6.78 (ddd, J = 9.0, 5.7, 3.0 Hz, 1H), 4.54–4.48 (m, 1H), 4.45 (ddd, J = 10.8, 9.5, 5.3 Hz, 1H), 4.42–4.33 (m, 2H), 4.02 (ddt, J = 61.3, 13.6, 5.0 Hz, 1H), 3.65–3.54 (m, 2H), 3.56–3.45 (m, 1H), 3.26 (ddd, J = 13.1, 8.7, 4.2 Hz, 1H), 2.81 (d, J = 94.5 Hz, 1H). 13C NMR (150 MHz, DMSO-d6) δ 170.22, 162.63, 151.98, 149.69, 142.59, 132.05, 130.93, 127.06, 125.64, 119.90, 115.63, 114.54, 83.00, 82.33, 75.88, 58.60, 57.66, 47.25, 37.91. HRMS (ESI) m/z [M + H]+ calcd for C19H17Cl2N3O2S 421.0419; found, 422.0492. HPLC purity: 97.63%. 4.1.4.22 (S)-1-(3,4-Dichlorophenyl)-4-(2-fluoro-5-nitrobenzoyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-25) Light-yellow solid. Yield: 79%, mp: 168–170 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.72 (dt, J = 122.9, 6.0 Hz, 1H), 8.40 (dt, J = 9.1, 3.6 Hz, 1H), 8.26–8.13 (m, 1H), 7.64 (dt, J = 8.8, 4.4 Hz, 1H), 7.41–7.38 (m, 1H), 7.35 (ddd, J = 8.7, 4.7, 1.6 Hz, 1H), 6.99 (t, J = 3.2 Hz, 1H), 6.93–6.87 (m, 1H), 6.87–6.71 (m, 2H), 4.55–4.39 (m, 2H), 4.28–4.18 (m, 2H), 3.78–3.67 (m, 2H), 3.63–3.51 (m, 2H), 3.38 (dq, J = 8.9, 5.2, 4.5 Hz, 1H). 13C NMR (150 MHz, DMSO-d6) δ 170.45, 170.06, 162.67, 149.66, 144.53, 142.43, 132.05, 130.91, 127.81, 127.05, 125.56, 125.38, 125.30, 119.93, 118.32, 118.16, 115.74, 114.65, 58.44, 47.29, 43.08, 41.68, 37.75. HRMS (ESI) m/z [M + H]+ calcd for C23H19Cl2FN4O4S 536.0488; found, 537.0561. HPLC purity: 97.52%. 4.1.4.23 (S)-1-(3,4-Dichlorophenyl)-4-(2-fluoro-5-(methylsulfonyl)benzoyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-26) White solid. Yield: 69%, mp: 152–154 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.65 (t, J = 6.1 Hz, 1H), 8.10 (ddd, J = 7.8, 4.7, 2.4 Hz, 1H), 7.94–7.87 (m, 1H), 7.64 (t, J = 8.9 Hz, 1H), 7.41–7.32 (m, 3H), 6.91 (dd, J = 5.2, 3.4 Hz, 1H), 6.78 (td, J = 9.5, 3.0 Hz, 2H), 4.57–4.39 (m, 3H), 4.27–4.16 (m, 3H), 3.76–3.67 (m, 3H), 3.54 (ddd, J = 28.7, 14.1, 6.7 Hz, 3H). 13C NMR (150 MHz, DMSO-d6) δ 170.04, 165.12, 163.29, 149.64, 142.61, 138.30, 132.04, 131.68, 130.91, 127.05, 125.58, 125.39, 119.86, 117.98, 115.83, 115.65, 114.73, 114.57, 58.78, 44.02, 43.03, 41.66, 38.72, 37.89. ESI-MS: m/z 570.0 [M + H]+, C24H22Cl2FN3O4S2 (569.04). 4.1.4.24 (S)-4-(4-Chloro-3-nitrobenzoyl)-1-(3,4-dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-27) Light-yellow solid. Yield: 88%, mp: 140–142 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.74 (d, J = 106.5 Hz, 1H), 8.07–7.97 (m, 1H), 7.86 (d, J = 8.0 Hz, 1H), 7.62 (dd, J = 8.3, 2.0 Hz, 1H), 7.43–7.31 (m, 2H), 6.99 (d, J = 3.0 Hz, 1H), 6.91 (dd, J = 5.2, 3.2 Hz, 1H), 6.85 (s, 1H), 6.79 (dd, J = 9.1, 3.0 Hz, 1H), 4.56–4.34 (m, 2H), 4.33–4.14 (m, 2H), 3.92–3.65 (m, 2H), 3.61–3.45 (m, 2H), 3.44–3.33 (m, 1H). 13C NMR (150 MHz, DMSO-d6) δ 166.77, 149.73, 147.93, 142.50, 136.26, 132.75, 132.48, 132.05, 130.93, 127.04, 126.66, 125.69, 125.42, 124.66, 119.89, 115.68, 114.60, 58.43, 47.90, 43.08, 41.81, 37.83. ESI-MS: m/z 553.1 [M + H]+, C23H19Cl3N4O4S (552.02). 4.1.4.25 (S)-4-(5-Cyano-2-fluorobenzoyl)-1-(3,4-dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-28) Off-white solid. Yield: 81%, mp: 146–148 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.88–8.56 (m, 1H), 8.05 (ddd, J = 8.8, 4.8, 2.2 Hz, 1H), 7.79 (s, 1H), 7.59 (t, J = 8.8 Hz, 1H), 7.48–7.29 (m, 2H), 6.98 (dd, J = 6.6, 2.9 Hz, 1H), 6.96–6.83 (m, 2H), 6.78 (td, J = 9.1, 8.4, 2.9 Hz, 1H), 4.70–4.41 (m, 2H), 4.33–4.10 (m, 2H), 3.84–3.62 (m, 2H), 3.61–3.45 (m, 2H), 3.38 (ddd, J = 12.4, 8.5, 3.8 Hz, 1H). 13C NMR (150 MHz, DMSO-d6) δ 170.39, 170.03, 162.84, 149.65, 142.55, 136.68, 133.63, 132.04, 130.91, 127.08, 125.66, 125.46, 119.87, 118.51, 118.37, 118.00, 115.64, 114.56, 108.66, 58.67, 45.51, 43.06, 41.64, 37.88. ESI-MS: m/z 517.1 [M + H]+, C24H19Cl2FN4O2S (516.06). 4.1.4.26 (S)-1-(3,4-Dichlorophenyl)-4-(5-nitrofuran-2-carbonyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-29) Yellow solid. Yield: 77%, mp: 144–148 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.82 (d, J = 58.1 Hz, 1H), 7.76 (d, J = 3.9 Hz, 1H), 7.41 (d, J = 9.0 Hz, 1H), 7.29 (dd, J = 20.4, 4.5 Hz, 2H), 6.99 (s, 1H), 6.90–6.75 (m, 3H), 4.53 (d, J = 13.7 Hz, 1H), 4.46–4.28 (m, 3H), 4.12 (s, 1H), 3.87 (d, J = 70.8 Hz, 1H), 3.65 (s, 3H). 13C NMR (150 MHz, DMSO-d6) δ 170.32, 157.40, 151.71, 149.57, 147.89, 142.62, 132.05, 130.93, 127.01, 125.56, 125.28, 119.77, 117.60, 115.45, 114.34, 113.36, 58.63, 55.36, 47.01, 43.18, 42.33, 37.87. ESI-MS: m/z 509.0 [M + H]+, C21H18Cl2N4O5S (508.04). 4.1.4.27 (2S)-4-(3-Chloro-2-hydroxypropanoyl)-1-(3,4-dichlorophenyl)-N-(thiophen-2-ylmethyl)piperazine-2-carboxamide (GD-30) Light-yellow solid. Yield: 57%, mp: 102–104 °C. 1H NMR (600 MHz, DMSO-d6) δ 8.89–8.67 (m, 1H), 7.51–7.27 (m, 2H), 7.03–6.83 (m, 3H), 6.81–6.73 (m, 1H), 5.91–5.56 (m, 1H), 4.53–4.28 (m, 5H), 4.02–3.81 (m, 2H), 3.71 (ddd, J = 28.7, 12.3, 4.5 Hz, 2H), 3.65–3.50 (m, 3H), 3.48–3.40 (m, 1H). 13C NMR (150 MHz, DMSO-d6) δ 170.44, 165.10, 149.68, 142.71, 132.02, 130.88, 127.06, 125.61, 125.38, 119.65, 115.53, 114.43, 68.81, 59.32, 46.70, 45.58, 43.07, 38.72, 37.97. ESI-MS: m/z 428.2 [M + H]+, C18H19Cl2N3O3S (427.05). Supporting Information Available The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jmedchem.2c01716.Molecular formula strings (CSV) Additional figures and tables as described in the manuscript, procedures for in vitro activity experiment, co-crystallization and data, and spectral data of the target compounds (PDF) Supplementary Material jm2c01716_si_001.csv jm2c01716_si_002.pdf Accession Codes SARS-CoV-2 Mpro complexes: GD-9, PDB entry: 8B56. Author Contributions ○ S.G. and L.S. contributed equally to this work. The authors declare no competing financial interest. Acknowledgments The authors gratefully acknowledge financial support from Major Basic Research Project of Shandong Provincial Natural Science Foundation (no. ZR2021ZD17), Guangdong Basic and Applied Basic Research Foundation (no. 2021A1515110740), China Postdoctoral Science Foundation (no. 2021M702003), Science Foundation for Outstanding Young Scholars of Shandong Province (no. ZR2020JQ31), Foreign Cultural and Educational Experts Project (no. GXL20200015001). C.E.M., M.G., and N.S. were supported by the Volkswagen Foundation. The authors acknowledge DESY (Hamburg, Germany), a member of the Helmholtz Association HGF, and the EMBL for the provision of experimental facilities at synchrotron beamlines P13 and P14 and the MX Laboratory at the Helmholtz Zentrum Berlin (BESSY II) for beam time. The authors thank Selina Storm and Isabel Bento for assistance in using the EMBL beamlines. Abbreviations 3CLpro 3C-like protease AMC 7-amino-4-methylcoumarin COVID-19 coronavirus disease 2019 DCM dichloromethane DIPEA N,N-diisopropylethylamine MALDI-TOF matrix-assisted laser desorption ionization/time-of-flight THF tetrahydrofuran FRET fluorescence resonance energy transfer HATU 1-(bis(dimethylamino)methylene)-1H-[1,2,3]triazolo[4,5-b]pyridine-1-ium 3-oxide hexafluorophosphate HPLC high-performance liquid chromatography Mpro main protease SAR structure–activity relationship SARS-CoV-2 severe acute respiratory syndrome coronavirus 2 TLC thin-layer chromatography TMS tetramethylsilane ==== Refs References Lu R. ; Zhao X. ; Li J. ; Niu P. ; Yang B. ; Wu H. ; Wang W. ; Song H. ; Huang B. ; Zhu N. ; Bi Y. ; Ma X. ; Zhan F. ; Wang L. ; Hu T. ; Zhou H. ; Hu Z. ; Zhou W. ; Zhao L. ; Chen J. ; Meng Y. ; Wang J. ; Lin Y. ; Yuan J. ; Xie Z. ; Ma J. ; Liu W. J. ; Wang D. ; Xu W. ; Holmes E. C. ; Gao G. F. ; Wu G. ; Chen W. ; Shi W. ; Tan W. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet 2020, 395 , 565–574. 10.1016/S0140-6736(20)30251-8.32007145 Fung T. S. ; Liu D. X. Similarities and dissimilarities of COVID-19 and other coronavirus diseases. Annu. Rev. Microbiol. 2021, 75 , 19–47. 10.1146/annurev-micro-110520-023212.33492978 Hu B. ; Guo H. ; Zhou P. ; Shi Z. L. Characteristics of SARS-CoV-2 and COVID-19. Nat. Rev. Microbiol. 2021, 19 , 141–154. 10.1038/s41579-020-00459-7.33024307 Xu L. ; Tu Y. ; Li J. ; Zhang W. ; Wang Z. ; Zhuang C. ; Xue L. Structure-based optimizations of a necroptosis inhibitor (SZM594) as novel protective agents of acute lung injury. Chin. Chem. Lett. 2022, 33 , 2545–2549. 10.1016/j.cclet.2021.09.059. Fiolet T. ; Kherabi Y. ; MacDonald C. J. ; Ghosn J. ; Peiffer-Smadja N. Comparing COVID-19 vaccines for their characteristics, efficacy and effectiveness against SARS-CoV-2 and variants of concern: a narrative review. Clin. Microbiol. Infect. 2022, 28 , 202–221. 10.1016/j.cmi.2021.10.005.34715347 Harvey W. T. ; Carabelli A. M. ; Jackson B. ; Gupta R. K. ; Thomson E. C. ; Harrison E. M. ; Ludden C. ; Reeve R. ; Rambaut A. ; Peacock S. J. ; Robertson D. L. ; SARS-CoV-2 variants, spike mutations and immune escape. Nat. Rev. Microbiol. 2021, 19 , 409–424. 10.1038/s41579-021-00573-0.34075212 Rana R. ; Kant R. ; Huirem R. S. ; Bohra D. ; Ganguly N. K. Omicron variant: current insights and future directions. Microbiol. Res. 2022, 265 , 127204 10.1016/j.micres.2022.127204.36152612 Chen H. ; Ma X. ; Zhang X. ; Hu G. ; Deng Y. ; Li S. ; Chen Z. ; He N. ; Wu Y. ; Jiang Z. Novel aerosol detection platform for SARS-CoV-2: Based on specific magnetic nanoparticles adsorption sampling and digital droplet PCR detection. Chin. Chem. Lett. 2023, 34 , 107701 10.1016/j.cclet.2022.07.044.35911611 WHO Coronavirus (COVID-19) Dashboard. https://covid19.who.int/ (accessed November 2022). Lee J. ; Kenward C. ; Worrall L. J. ; Vuckovic M. ; Gentile F. ; Ton A. T. ; Ng M. ; Cherkasov A. ; Strynadka N. C. J. ; Paetzel M. X-ray crystallographic characterization of the SARS-CoV-2 main protease polyprotein cleavage sites essential for viral processing and maturation. Nat. Commun. 2022, 13 , 5196 10.1038/s41467-022-32854-4.36057636 Zhao Y. ; Zhu Y. ; Liu X. ; Jin Z. ; Duan Y. ; Zhang Q. ; Wu C. ; Feng L. ; Du X. ; Zhao J. ; Shao M. ; Zhang B. ; Yang X. ; Wu L. ; Ji X. ; Guddat L. W. ; Yang K. ; Rao Z. ; Yang H. Structural basis for replicase polyprotein cleavage and substrate specificity of main protease from SARS-CoV-2. Proc. Natl. Acad. Sci. U.S.A. 2022, 119 , e2117142119 10.1073/pnas.2117142119.35380892 Jin Z. ; Du X. ; Xu Y. ; Deng Y. ; Liu M. ; Zhao Y. ; Zhang B. ; Li X. ; Zhang L. ; Peng C. ; Duan Y. ; Yu J. ; Wang L. ; Yang K. ; Liu F. ; Jiang R. ; Yang X. ; You T. ; Liu X. ; Yang X. ; Bai F. ; Liu H. ; Liu X. ; Guddat L. W. ; Xu W. ; Xiao G. ; Qin C. ; Shi Z. ; Jiang H. ; Rao Z. ; Yang H. Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors. Nature 2020, 582 , 289–293. 10.1038/s41586-020-2223-y.32272481 Citarella A. ; Scala A. ; Piperno A. ; Micale N. SARS-CoV-2 Mpro: A Potential target for peptidomimetics and small-molecule inhibitors. Biomolecules 2021, 11 , 607 10.3390/biom11040607.33921886 Owen D. R. ; Allerton C. M. N. ; Anderson A. S. ; Aschenbrenner L. ; Avery M. ; Berritt S. ; Boras B. ; Cardin R. D. ; Carlo A. ; Coffman K. J. ; Dantonio A. ; Di L. ; Eng H. ; Ferre R. ; Gajiwala K. S. ; Gibson S. A. ; Greasley S. E. ; Hurst B. L. ; Kadar E. P. ; Kalgutkar A. S. ; Lee J. C. ; Lee J. ; Liu W. ; Mason S. W. ; Noell S. ; Novak J. J. ; Obach R. S. ; Ogilvie K. ; Patel N. C. ; Pettersson M. ; Rai D. K. ; Reese M. R. ; Sammons M. F. ; Sathish J. G. ; Singh R. S. P. ; Steppan C. M. ; Stewart A. E. ; Tuttle J. B. ; Updyke L. ; Verhoest P. R. ; Wei L. ; Yang Q. ; Zhu Y. An oral SARS-CoV-2 Mpro inhibitor clinical candidate for the treatment of COVID-19. Science 2021, 374 , 1586–1593. 10.1126/science.abl4784.34726479 Dai W. ; Zhang B. ; Jiang X. M. ; Su H. ; Li J. ; Zhao Y. ; Xie X. ; Jin Z. ; Peng J. ; Liu F. ; Li C. ; Li Y. ; Bai F. ; Wang H. ; Cheng X. ; Cen X. ; Hu S. ; Yang X. ; Wang J. ; Liu X. ; Xiao G. ; Jiang H. ; Rao Z. ; Zhang L. K. ; Xu Y. ; Yang H. ; Liu H. Structure-based design of antiviral drug candidates targeting the SARS-CoV-2 main protease. Science 2020, 368 , 1331–1335. 10.1126/science.abb4489.32321856 Qiao J. ; Li Y. S. ; Zeng R. ; Liu F. L. ; Luo R. H. ; Huang C. ; Wang Y. F. ; Zhang J. ; Quan B. ; Shen C. ; Mao X. ; Liu X. ; Sun W. ; Yang W. ; Ni X. ; Wang K. ; Xu L. ; Duan Z. L. ; Zou Q. C. ; Zhang H. L. ; Qu W. ; Long Y. H. ; Li M. H. ; Yang R. C. ; Liu X. ; You J. ; Zhou Y. ; Yao R. ; Li W. P. ; Liu J. M. ; Chen P. ; Liu Y. ; Lin G. F. ; Yang X. ; Zou J. ; Li L. ; Hu Y. ; Lu G. W. ; Li W. M. ; Wei Y. Q. ; Zheng Y. T. ; Lei J. ; Yang S. SARS-CoV-2 Mpro inhibitors with antiviral activity in a transgenic mouse model. Science 2021, 371 , 1374–1378. 10.1126/science.abf1611.33602867 Cáceres C. J. ; Cardenas-Garcia S. ; Carnaccini S. ; Seibert B. ; Rajao D. S. ; Wang J. ; Perez D. R. Efficacy of GC-376 against SARS-CoV-2 virus infection in the K18 hACE2 transgenic mouse model. Sci. Rep. 2021, 11 , 9609 10.1038/s41598-021-89013-w.33953295 Boras B. ; Jones R. M. ; Anson B. J. ; Arenson D. ; Aschenbrenner L. ; Bakowski M. A. ; Beutler N. ; Binder J. ; Chen E. ; Eng H. ; Hammond H. ; Hammond J. ; Haupt R. E. ; Hoffman R. ; Kadar E. P. ; Kania R. ; Kimoto E. ; Kirkpatrick M. G. ; Lanyon L. ; Lendy E. K. ; Lillis J. R. ; Logue J. ; Luthra S. A. ; Ma C. ; Mason S. W. ; McGrath M. E. ; Noell S. ; Obach R. S. ; O’Brien M. N. ; O’Connor R. ; Ogilvie K. ; Owen D. ; Pettersson M. ; Reese M. R. ; Rogers T. F. ; Rosales R. ; Rossulek M. I. ; Sathish J. G. ; Shirai N. ; Steppan C. ; Ticehurst M. ; Updyke L. W. ; Weston S. ; Zhu Y. ; White K. M. ; García-Sastre A. ; Wang J. ; Chatterjee A. K. ; Mesecar A. D. ; Frieman M. B. ; Anderson A. S. ; Allerton C. Preclinical characterization of an intravenous coronavirus 3CL protease inhibitor for the potential treatment of COVID19. Nat. Commun. 2021, 12 , 6055 10.1038/s41467-021-26239-2.34663813 Ma X. R. ; Alugubelli Y. R. ; Ma Y. ; Vatansever E. C. ; Scott D. A. ; Qiao Y. ; Yu G. ; Xu S. ; Liu W. R. MPI8 is potent against SARS-CoV-2 by inhibiting dually and selectively the SARS-CoV-2 main protease and the host cathepsin L. ChemMedChem 2022, 17 , e202100456 10.1002/cmdc.202100456.34242492 Pillaiyar T. ; Flury P. ; Krüger N. ; Su H. ; Schäkel L. ; Barbosa Da Silva E. ; Eppler O. ; Kronenberger T. ; Nie T. ; Luedtke S. ; Rocha C. ; Sylvester K. ; Petry M. R. I. ; McKerrow J. H. ; Poso A. ; Pöhlmann S. ; Gütschow M. ; O’Donoghue A. J. ; Xu Y. ; Müller C. E. ; Laufer S. A. Small-molecule thioesters as SARS-CoV-2 main protease inhibitors: enzyme inhibition, structure-activity relationships, antiviral activity, and X-ray structure determination. J. Med. Chem. 2022, 65 , 9376–9395. 10.1021/acs.jmedchem.2c00636.35709506 Breidenbach J. ; Lemke C. ; Pillaiyar T. ; Schäkel L. ; Al ; Hamwi G. ; Diett M. ; Gedschold R. ; Geiger N. ; Lopez V. ; Mirza S. ; Namasivayam V. ; Schiedel A. C. ; Sylvester K. ; Thimm D. ; Vielmuth C. ; Phuong Vu L. ; Zyulina M. ; Bodem J. ; Gütschow M. ; Müller C. E. Targeting the main protease of SARS-CoV-2: from the establishment of high throughput screening to the design of tailored inhibitors. Angew. Chem., Int. Ed. 2021, 60 , 10423–10429. 10.1002/anie.202016961. Ma C. ; Xia Z. ; Sacco M. D. ; Hu Y. ; Townsend J. A. ; Meng X. ; Choza J. ; Tan H. ; Jang J. ; Gongora M. V. ; Zhang X. ; Zhang F. ; Xiang Y. ; Marty M. T. ; Chen Y. ; Wang J. Discovery of di- and trihaloacetamides as covalent SARS-CoV-2 main protease inhibitors with high target specificity. J. Am. Chem. Soc. 2021, 143 , 20697–20709. 10.1021/jacs.1c08060.34860011 Quan B. X. ; Shuai H. ; Xia A. J. ; Hou Y. ; Zeng R. ; Liu X. L. ; Lin G. F. ; Qiao J. X. ; Li W. P. ; Wang F. L. ; Wang K. ; Zhou R. J. ; Yuen T. T. ; Chen M. X. ; Yoon C. ; Wu M. ; Zhang S. Y. ; Huang C. ; Wang Y. F. ; Yang W. ; Tian C. ; LI W. M. ; Wei Y. Q. ; Yuen K. Y. ; Chan J. F. ; Lei J. ; Chu H. ; Yang S. An orally available Mpro inhibitor is effective against wild-type SARS-CoV-2 and variants including Omicron. Nat. Microbiol. 2022, 7 , 716–725. 10.1038/s41564-022-01119-7.35477751 Ghosh A. K. ; Raghavaiah J. ; Shahabi D. ; Yadav M. ; Anson B. J. ; Lendy E. K. ; Hattori S. I. ; Higashi-Kuwata N. ; Mitsuya H. ; Mesecar A. D. Indole chloropyridinyl ester-derived SARS-CoV-2 3CLpro inhibitors: enzyme inhibition, antiviral efficacy, structure-activity relationship, and X-ray structural studies. J. Med. Chem. 2021, 64 , 14702–14714. 10.1021/acs.jmedchem.1c01214.34528437 Lu X. ; Smaill J. B. ; Patterson A. V. ; Ding K. Discovery of cysteine-targeting covalent protein kinase inhibitors. J. Med. Chem. 2022, 65 , 58–83. 10.1021/acs.jmedchem.1c01719.34962782 Gao S. ; Sylvester K. ; Song L. ; Claff T. ; Jing L. ; Woodson M. ; Weiße R. H. ; Cheng Y. ; Schäkel L. ; Petry M. ; Gütschow M. ; Schiedel A. C. ; Sträter N. ; Kang D. ; Xu S. ; Toth K. ; Tavis J. ; Tollefson A. E. ; Müller C. E. ; Liu X. ; Zhan P. Discovery and crystallographic studies of trisubstituted piperazine derivatives as non-covalent SARS-CoV-2 main protease inhibitors with high target specificity and low toxicity. J. Med. Chem. 2022, 65 , 13343–13364. 10.1021/acs.jmedchem.2c01146.36107752 Douangamath A. ; Fearon D. ; Gehrtz P. ; Krojer T. ; Lukacik P. ; Owen C. D. ; Resnick E. ; Strain-Damerell C. ; Aimon A. ; Ábrányi-Balogh P. ; Brandão-Neto J. ; Carbery A. ; Davison G. ; Dias A. ; Downes T. D. ; Dunnett L. ; Fairhead M. ; Firth J. D. ; Jones S. P. ; Keeley A. ; Keserü G. M. ; Klein H. F. ; Martin M. P. ; Noble M. E. M. ; O’Brien P. ; Powell A. ; Reddi R. N. ; Skyner R. ; Snee M. ; Waring M. J. ; Wild C. ; London N. ; von Delft F. ; Walsh M. A. Crystallographic and electrophilic fragment screening of the SARS-CoV-2 main protease. Nat. Commun. 2020, 11 , 5047 10.1038/s41467-020-18709-w.33028810 Povedano J. M. ; Rallabandi R. ; Bai X. ; Ye X. ; Liou J. ; Chen H. ; Kim J. ; Xie Y. ; Posner B. ; Rice L. ; De Brabander J. K. ; McFadden D. G. A multipronged approach establishes covalent modification of β-tubulin as the mode of action of benzamide anti-cancer toxins. J. Med. Chem. 2020, 63 , 14054–14066. 10.1021/acs.jmedchem.0c01482.33180487 Owens T. D. ; Brameld K. A. ; Verner E. J. ; Ton T. ; Li X. ; Zhu J. ; Masjedizadeh M. R. ; Bradshaw J. M. ; Hill R. J. ; Tam D. ; Bisconte A. ; Kim E. O. ; Francesco M. ; Xing Y. ; Shu J. ; Karr D. ; LaStant J. ; Finkle D. ; Loewenstein N. ; Haberstock-Debic H. ; Taylor M. J. ; Nunn P. ; Langrish C. L. ; Goldstein D. M. Discovery of reversible covalent bruton’s tyrosine kinase inhibitors PRN473 and PRN1008 (rilzabrutinib). J. Med. Chem. 2022, 65 , 5300–5316. 10.1021/acs.jmedchem.1c01170.35302767 Haag S. M. ; Gulen M. F. ; Reymond L. ; Gibelin A. ; Abrami L. ; Decout A. ; Heymann M. ; van der Goot F. G. ; Turcatti G. ; Behrendt R. ; Ablasser A. Targeting STING with covalent small-molecule inhibitors. Nature 2018, 559 , 269–273. 10.1038/s41586-018-0287-8.29973723 Clyde A. ; Galanie S. ; Kneller D. W. ; Ma H. ; Babuji Y. ; Blaiszik B. ; Brace A. ; Brettin T. ; Chard K. ; Chard R. ; Coates L. ; Foster I. ; Hauner D. ; Kertesz V. ; Kumar N. ; Lee H. ; Li Z. ; Merzky A. ; Schmidt J. G. ; Tan L. ; Titov M. ; Trifan A. ; Turilli M. ; Van ; Dam H. ; Chennubhotla S. C. ; Jha S. ; Kovalevsky A. ; Ramanathan A. ; Head M. S. ; Stevens R. High-throughput virtual screening and validation of a SARS-CoV-2 main protease noncovalent inhibitor. J. Chem. Inf. Model. 2022, 62 , 116–128. 10.1021/acs.jcim.1c00851.34793155 Chen K. X. ; Lesburg C. A. ; Vibulbhan B. ; Yang W. ; Chan T. Y. ; Venkatraman S. ; Velazquez F. ; Zeng Q. ; Bennett F. ; Anilkumar G. N. ; Duca J. ; Jiang Y. ; Pinto P. ; Wang L. ; Huang Y. ; Selyutin O. ; Gavalas S. ; Pu H. ; Agrawal S. ; Feld B. ; Huang H. C. ; Li C. ; Cheng K. C. ; Shih N. Y. ; Kozlowski J. A. ; Rosenblum S. B. ; Njoroge F. G. A novel class of highly potent irreversible hepatitis C virus NS5B polymerase inhibitors. J. Med. Chem. 2012, 55 , 2089–2101. 10.1021/jm201322r.22247956 Mukherjee H. ; Debreczeni J. ; Breed J. ; Tentarelli S. ; Aquila B. ; Dowling J. E. ; Whitty A. ; Grimster N. P. A study of the reactivity of S(VI)-F containing warheads with nucleophilic amino-acid side chains under physiological conditions. Org. Biomol. Chem. 2017, 15 , 9685–9695. 10.1039/C7OB02028G.29119993 Auffinger P. ; Hays F. A. ; Westhof E. ; Ho P. S. Halogen bonds in biological molecules. Proc. Natl. Acad. Sci. U.S.A. 2004, 101 , 16789–16794. 10.1073/pnas.0407607101.15557000
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==== Front Research in Transportation Business & Management 2210-5395 2210-5395 Elsevier Ltd. S2210-5395(22)00086-4 10.1016/j.rtbm.2022.100865 100865 Article Experts' opinions about lasting innovative technologies in City Logistics Zenezini Giovanni Mangano Giulio ⁎ De Marco Alberto Department of Management and Production Engineering, Politecnico di Torino, corso Duca degli Abruzzi 24, 10129 Torino (TO), Italy ⁎ Corresponding author. 29 7 2022 12 2022 29 7 2022 45 100865100865 14 1 2022 13 7 2022 15 7 2022 © 2022 Elsevier Ltd. All rights reserved. 2022 Elsevier Ltd Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. The COVID-19 pandemic has highlighted the relevance of goods delivery in urban areas. However, this activity often generates negative environmental impact and several technologies have been proposed in recent years to reduce it, thus forming a complex innovation landscape characterized by different levels of maturity and effects on the City Logistics (CL) system. This complexity causes a deep uncertainty over the future of CL. This paper aims to tackle this uncertainty by forecasting the future of a set of CL technologies. A Delphi survey has been submitted to experts of this field to achieve a stable consensus over 33 projections related to 7 CL technologies for the year 2030. Results show that real-time data collection will help the coordination process between stakeholders, engendering an increased awareness over the value of using logistics data as well as its potential drawbacks. Moreover, experts share a positive attitude towards the expansion of Parcel Lockers, which should be monitored by public authorities to avoid a negative impact on land use. Finally, technologies such as drones and crowd-logistics have drawn the lowest level of consensus due to their lower level of maturity, which arouse the necessity to further explore several issues such as legal and technical barriers. Keywords Technology forecast City Logistics Delphi survey Statistical analysis ==== Body pmc1 Introduction The dramatic increase of last mile logistics, as a result of the booming trends of ecommerce, is causing several problems in urban areas such as traffic congestion, noise and air pollution. The ecommerce business has been significantly strengthened with the COVID-19 pandemic (Guthrie, Fosso-Wamba, & Arnaud, 2021) and several studies state that consumers are going to maintain their new digital purchasing behaviors even once the pandemic ends (Kim, 2020; Sheth, 2020). In this context, recent innovative technologies are being developed and applied in City Logistics (CL) that will likely bring significant changes in the next future. Currently, several recent technologies are reported in the literature. In particular, Taniguchi, Thompson, and Qureshi (2020) identify Intelligent Transportation Systems (ITS), Autonomous Vehicles, Parcel Lockers, Crowd Shipping Platforms, and Electric Vehicles, as promising technologies to foster future CL systems especially if combined with Internet of Things (IoT) and Big Data. These technologies can be considered as pillars for CL implementations in the coming years (de Gauna, Villalonga, & Sánchez, 2020; Dolati Neghabadi, Espinouse, & Lionet, 2021). Big Data Analytics (BDA) are also foreshadowing benefits in terms of real-time prediction, adaptation, quality of life and greater ease of movement (Kandt & Batty, 2021). However, the implementation of these technologies is quite difficult, their returns on investment are uncertain, and several barriers must be overcome. In fact, CL projects must often deal with critical operations and financial feasibility (Katsela & Pålsson, 2020). As a result, many initiatives have reported promising outcomes in their initial implementation phases, but have not been able to survive in the long run due to their low profitability (Gammelgaard, 2015). Thus, there is a literature gap about the evaluation of the expectations on innovative technologies on CL that might be a support for driving future investments by private operators and for a more accurate design of policies by public authorities. This evaluation might be uncertain, and the point of view of expert professionals should be taken into account. Forecasting based on experts' opinions has the major advantage of rooting the forecasts in a detailed understanding of the causes underlying the future trends of a system (McKinnon & Piecyk, 2013). The Delphi method represents a structured approach to elicit experts' opinions on a range of subjects, particularly future developments and trends. Its objective is to structure complex group opinions (Rauch, 1979) and to develop consensus on future developments (Turoff & Linstone, 2002). Hence, with the aim of bridging this research gap, the objective of this paper is to investigate the future scenarios related to a set of CL technologies that are identified through a careful analysis of relevant literature. The future scenarios are traced by eliciting experts' consensus via a Delphi approach. In particular, the opinions and the perceptions of a panel of last-mile logistics experts are gathered to assess the impact of the above-mentioned innovative technologies and to identify the levers able to support their diffusion together with the barriers than can negatively affect their adoption. The paper is structured as follows. First, an overview of the current literature focusing on contributions that deal with technology forecasting methods as well as Delphi applications in logistics and supply chain is presented. After that, the methodological steps of the research are listed, namely the panel selection, the development of projections, survey submission and data analysis and testing. The results are then analyzed. In particular, it can be noticed that Intelligent Transportation Systems are expected to enhance the sharing of information among logistics operators and with the customers. Another important finding is the need of stronger involvement of policy makers for more standard regulations about the use of innovative technologies such as drones. Finally, discussions and conclusions are proposed. 2 Literature review This section of the paper is twofold. In the first part an overview of the existing literature on the possible methodological approaches for technology forecasting is provided. The other part is focused on describing applications of the Delphi method in the fields of logistics and supply chain management. 2.1 Previous research on technology forecasting Several approaches are adopted in the literature to anticipate and predict future impacts and applications of technology such as simulation, prediction, Artificial Intelligence, trend explorations and machine learning algorithms, analytical models and surveys. Simulation methodologies provide a suitable approach to provide insights into the future outcomes of last-mile initiatives. For instance, Teo, Taniguchi, and Qureshi (2012) and van Duin et al. (2012) propose an agent-based model combined with a vehicle routing approach to evaluate CL measures such as road pricing. System Dynamics has been adopted to assess the impact of public regulations and incentives aimed at reducing CO2 emissions (Egilmez & Tatari, 2012; Stepp et al., 2009), as well as to explore the potential for diffusion of last-mile innovations such as electric vehicles (Cagliano et al., 2017; Gorbea, Lindemann, & de Weck, 2011; Shepherd, Bonsall, & Harrison, 2012) and Information and Communication Technologies (ICT) platforms for enhancing stakeholders' interaction (Mangano et al., 2019). Prediction might be obtained through the exponential smoothing (Moghram & Rahman, 1989). As a consolidated methodology for anticipating the level of success of a product or service in terms of demand prediction. Temporal causality modeling exploits previous data to determine future time series (Nafil et al., 2020). More recently, artificial intelligence can be used for predictions. This approach might be adopted together with more established methodologies such as Multi Criteria Decision Methods, in order to assign more precise weights to every criteria at issue (Savun-Hekimoğlu et al., 2021). (Li et al., 2019) combine the expert opinion with trend analysis approach for forecasting the trend of a technology. In this context, trend extrapolation as a numerical method that combines different approaches is able to overcome the limitations associated to the adoption of a single techniques and in turn to enrich the results of the analysis (Yuskevich et al., 2021). Data Envelop Analysis might also be suitable for carrying out estimations on the technology rate of change (Anderson et al., 2002). Finally, more recently machine learnings algorithms are exploited for evaluating and improving logistics processes (Baghdadi et al., 2018). However, in order to adopt quantitative methodologies to extrapolate future states of a system from present behaviors scholars assume that past trends will continue indefinitely. Case studies might be used for carrying out an ex-ante assessment and consequently for providing scientific based issue to be used in future debate (Prosperi, Lombardi, & Spada, 2019). They prove their suitability in testing the effectiveness of a selected measure of policy in CL systems (Bozzo, Conca, & Marangon, 2014). Analytical models are typically developed for anticipate configurations of complex logistics systems, by considering different perspectives of the business such as the management of the inventory or the level of revenues and costs (Gu, Liu, & Qing, 2017; Wang & Mersereau, 2017). Also, surveys can be taken into account as an excellent way to collect personal opinion on a certain product, service, policy, or behavior (Yabe et al., 2021). 2.2 Pertinent Delphi applications to logistics and supply chain research Logistics and supply chain contexts represent an interesting field of application for the Delphi method. Scholars have been using Delphi surveys to project future trends in supply chain management (Melnyk et al., 2009), supply chain risks (Markmann, Darkow, & Von Der Gracht, 2013), logistics service industry (Von Der Gracht & Darkow, 2010), and greenhouse emissions in the transport and logistics sectors (McKinnon & Piecyk, 2013). Literature has also found fertile ground in exploring the potential of the Delphi method for technology foresight and developing future implementation scenarios, namely for autonomous trucks (Fritschy & Spinler, 2019) and Big Data Analytics in Supply Chain (Roßmann et al., 2018). To the best of our knowledge, the proposed study is the first Delphi survey applied to last-mile logistics technologies. Most of these studies apply a two-round Delphi survey built from initial formulations developed from multiple sources, usually pertinent literature, brainstorming and desk research, which were then pre-tested with a pre-panel of senior researchers or managers. The pre-test has the objective of testing for content and face validity of the survey items, which are usually closed-ended questions to ensure such validity (Hsu & Sandford, 2007). Scholars using the Delphi method in logistics, transportation and Supply Chain sectors have always been careful not to generate fatigue in the experts by proposing the right number of items for the experts' evaluation, generally spanning between 16 and 41. In all papers except one, survey items take the form of projections for a future timeframe, usually set at 15–20 years from the year of submission. The exception is represented by the paper of McKinnon and Piecyk (2013) where experts are asked to predict the changes in a set of key transport variables. Purposive sampling is used to select the most suitable and knowledgeable experts on the topic at issue, whereby expertise is further approximated with the years of experience or self-assessed by the experts. The number of experts participating in the survey ranges from 15 to 275, with different groups involved (e.g. academics, consultants, public authorities and other private firms) to ensure a variety of opinions. Therefore, the present literature review shows that the Delphi method supports the research objective by providing a structured approach to identify the future technological trends of the CL. 3 Methodology A Delphi approach is used in this study because it stimulates a panel of experts to formulate a collective understanding through balanced communication that minimizes difficulties related to social status or personality traits in interacting groups (Rowe, Wright, & Bolger, 1991). The Delphi method has proven to be efficient for gathering insights on a topic when only a limited amount of data is available or when future projections are explored (Markmann et al., 2013). In these contexts, reliable and stable results can be achieved through the subsequent rounds of a Delphi survey (Landeta, 2006; von der Gracht, 2012). Researchers have found that Delphi studies consistently outperform normal surveys, as experts provide a more accurate forecast than traditional survey groups (Rowe & Wright, 2001). Hence, the research has been conducted through the following steps. First, a literature research about the identified technologies and their impacts and applications on last-mile logistics is conducted on scholarly databases, desk research and participation to international workshops. Second, a group of experts is selected to take part to the Delphi survey. Third, two rounds of the questionnaire are carried out. At the end of the first one preliminary results are shared in order to give evidence about the consensus and the discord for the projections at issues. Then, the results are analyzed both qualitatively and quantitatively via the Kruskal-Wallis test. 3.1 Development of technology projections Projections represent brief future statements with the intent to provoke a reflective assessment from experts. The year of reference for the projections is set to be 2030, which is consistent with the typical 10–15 years forecasting horizon of similar studies (Culot et al., 2020). The development of the projections is the result of a literature exploration conducted on SCOPUS, which is recognized as the most complete bibliometric database of scientific peer-reviewed literature (Vila et al., 2020). In last-mile logistics contexts, many innovative applications of recent technologies can be found, such as sharing the capacity of vehicles, distribution centers and information systems. For example, the pool of potential drivers that represents the “crowd” can benefit from flexible earnings opportunities (Carbone, Rouquet, & Roussat, 2015) while customers can benefit from faster and cheaper deliveries (Arslan et al., 2019). Furthermore, drones are gaining popularity in last mile services after a successful adoption in construction, monitoring and surveillance (Macrina, Pugliese, Guerriero, & La Porte, 2020) especially when several major on line retailer such as Amazon and Google have claimed to introduce drones for carrying out their parcel operations activities (Yoo, Yu, & Jung, 2018). Intelligent Transportation Systems (ITS) are innovative solutions aimed at supporting a proper management of transports and more in general of traffic with positive effects on air and noise pollution. They have been deployed during the past decade with a wide spectrum of devices such as smart infrastructure, vehicle connectivity and real-time information (Zhang et al., 2018). In last-mile logistics they allow to save time, cost, and improve the operations effectiveness (Martins, Anholon, & Quelhas, 2019). In addition, municipalities are trying to reduce the amount of traffic congestion by promoting the adoption of zero-emission vehicles such as cargo bikes and electric vehicles for last mile delivery (Cattaruzza et al., 2015). In particular cargo bikes are proving to be suitable for low weight parcels, and might achieve short delivery times. At the same time, they are able to ensure significant congestion reduction with no emissions (Nürnberg, 2019). Similarly, freight vehicles powered with electric engines represent and interesting solution in decarbonizing CL operations especially if electricity is generated from renewable energies. In fact, since electric engine do not emit any gas emission, the electric vehicles are considered as a crucial lever for improved air quality in the cities (Soret, Guevara, & Baldasano, 2014). Low impact vehicles are often used together with parcel lockers, typically located in high frequency areas (such as train or bus stations) (Enthoven et al., 2020). Parcel lockers store parcels to be picked up by final customers who have to identify themselves via integrated terminals (Schwerdfeger & Boysen, 2020). They provide a convenient solution especially for people often not at home during the typical delivery times (Iwan, Kijewska, & Lemke, 2016). CL systems can also be enhanced by using Internet of Things (IoT) solutions (Wang et al., 2020) that are likely to bring opportunities in the field of the intelligent logistics, by improving the efficiency, reducing the costs and increasing the competitiveness (Fu, 2018). Indeed, IoT applications have received a lot of attention in the field of traffic and transportation (Tahaei et al., 2020), since they are able to facilitate the exchange of goods and services by connecting each object to a data network and assigning a digital identity (Golpîra, Khan, & Safaeipour, 2021). The related final aim is to create a worldwide network to connect people, things, data and processes (Malik, Dutta, & Granjal, 2019). A first list of 65 projections is developed from the literature. Then, 24 projections were excluded after a brainstorming session among the researchers participating in this study in order to avoid redundancies. The list of 41 projections has been submitted to a panel of 6 senior experts, who ensured that items were both compelling, non-trivial, clearly expressed and understandable. Moreover, the test with the panel of experts aimed at achieving the reliability of the survey by ensuring that the wording of the questions would not influence the answers (Gordon, 1992) by avoiding ambiguity and conditional statements (Rowe & Wright, 2011). Reliability ensures that “true consensus” is reached, rather than a consensus based on the absence of real debate. The revised version of the projections was again submitted to the pre-panel to check that all changes requested were included in the final list. The final list includes 33 projections phrased according to consolidated practices regarding the length and number of elements in each sentence. The projections can be classified according to the seven technologies being investigated and four categories of analysis (Table 1 ). These categories are traced back on how technology is traditionally assessed in literature. In particular:i. Barriers to the implementation of technology can be referred to lack of knowledge, more focus on operations processes lack of understanding the strategic importance, and the scarcity of human resources (Yu & Schweisfurth, 2020); ii. External factors that may enable the uptake intended as long-term process that is hard to manage given the multidimensional aspects (e.g. economic, user-friendliness) of a technology (Haque, 2022); iii. Benefits of using the technology to last-mile stakeholders that often have different goals in dealing with CL (Amaya et al., 2021); iv. Impacts on last-mile stakeholders that are the drivers towards the selection and implementation of the appropriate solution in every specific case (Nathanail et al., 2021). Table 1 Final list of projections. Table 1Technology ID Projection Category Big Data Analytics (BDA) 1.1 BDA have enabled de-centralization of decision-making processes in supply networks and have supported the growth of micro-retailing, such as “nanostores”. Benefits of using the technology 1.2 The application of BDA has increased order frequency for B2B customers. Impacts on stakeholders 1.3 The market share of same day delivery services is higher due to more precise demand forecasting supported by BDA. Impacts on stakeholders 1.4 At an operational level, Big Data is used for supporting interaction between final customers and Logistics Service Providers (LSP) – e.g. Real time coordination with drivers-. Benefits of using the technology Crowd Logistics 2.1 Acceptability by customer (trust, safety, and security) is one of the main barriers blocking the adoption of crowd logistics solutions. Barriers to the implementation 2.2 For e-commerce home-deliveries, traditional delivery vans are still preferred to crowd-logistics due to their more efficient use of the vehicle (i.e. delivery vans have higher load factors). Impacts on stakeholders 2.3 Crowd logistics is better suited in nonstandard non-scheduled deliveries (groceries, flowers, etc.) and in less dense (i.e. rural) environments. Benefits of using the technology 2.4 Crowd logistic services are economically viable only in high demand areas. Enabling factors 2.5 Crowd logistics does not provide environmental benefits if associated with private cars. Impacts on stakeholders 2.6 Crowd-logistics services negatively impacts the level of salaries for last-mile professional drivers. Impacts on stakeholders 2.7 Crowd-logistics ensures the same level of service even though the carriers are, usually, not trained professionals. Benefits of using the technology Drones 3.1 Urban drone deliveries are economically viable only if paired with centralized urban fullfilment and/or consolidation centres. Enabling factors 3.2 To support the adoption of drone-based delivery, how important it has been to overcome the following issues: [Lack of dedicated regulation frameworks.] Barriers to the implementation 3.3 To support the adoption of drone-based delivery, how important it has been to overcome the following issues: [Social acceptance -e.g. privacy, surveillance concerns-] Barriers to the implementation 3.4 To support the adoption of drone-based delivery, how important it has been to overcome the following issues: [Technological issues -e.g.range, capacity, resistance to extreme weather, landing capabilities, safety, advanced navigation and coordination algorithms-] Barriers to the implementation 3.5 Drone-based deliveries are enabled by being integrated with delivery vans (both autonomous and manned) for the first leg of the journey (Outward journey). Enabling factors 3.6 Drone-based delivery are better suited in limited scenarios such as rural deliveries, medical deliveries or emergency relief. Benefits of using the technology 3.7 The adoption of drone-based delivery reduces the size of last-mile vehicle fleets and in turn the number of required drivers. Benefits of using the technology Intelligent Transportation Systems (ITS) 4.1 The number of freight delivery bays have increased, and their locations and size are optimized. In addition, delivery bay monitoring and booking systems have been deployed and enforced (i.e. ensuring that illegal behaviors are fined). Impacts on stakeholders 4.2 Public authorities are focusing their efforts on enforcing access restrictions such as Low Emission Zones and congestion charges through ITS systems (e.g. automated plate reading and electronic payments). Impacts on stakeholders 4.3 ITS implementations aim at gathering reliable, precise, deep and broad data on last-mile systems -e.g. number of vehicles, volumes transported, load factors, traffic flows etc.-. Benefits of using the technology Low Emission Vehicles 5.1 Adoption of EVs is still related to the implementation of public policies such as: access restrictions and economic incentives. Enabling factors 5.2 Only LSPs with high consumer density are able to use cargo bikes efficiently. Enabling factors Parcel Lockers 6.1 Parcel Lockers diffusion has reached a plateau due to the investment costs needed to reach all customers. Barriers to the implementation 6.2 Local administrations allow parcel lockers to be installed on public space only if they are accessible via public transportation. Enabling factors 6.3 Only LSPs with high consumer density are able to use parcel lockers efficiently. Enabling factors 6.4 Shared parcel lockers are supported by LSPs. Impacts on stakeholders 6.5 Parcel Locker systems have been associated with automobile dependent travel behavior. Impacts on stakeholders 6.6 Parcel Lockers are more likely to be installed in urban rather than suburban areas. Impacts on stakeholders 6.7 Parcel Lockers are more likely to be installed in high density (i.e. urban) rather than low density (i.e. rural) areas. Impacts on stakeholders Internet of Things (IoT) and connected devices 7.1 The main barrier to the increase of communication and coordination mechanisms between carriers and customers is the customers' inertia to technology adoption. Barriers to the implementation 7.2 Acceptability by customers (trust, safety, and security) is one of the main barriers blocking the adoption of IOT-based logistics services (e.g. smart locks, digital keys for in-car delivery etc.) Barriers to the implementation 7.3 Real-time data from multiple sources (e.g. traffic, road disruptions) are more available and thus enable a more widespread usage of dynamic vehicle routing algorithms Enabling factors Regarding the relations between technologies and category of analysis, a clarification is due. In fact, technologies are not necessarily associated with projections spanning over all four categories, due to the different maturity levels achieved by such technologies and the consensus reached in the literature. For instance, ITS implementations are entangled with local enforcement and thus they are more associated with bearing impacts on last-mile stakeholders. Parcel Lockers instead have proved the value that they can bring about operational, economic, and environmental benefits, and thus the projections focus on other aspects linked with their future implementation scenarios. As for BDA, the projections are more focused on impacts and benefits to last-mile stakeholders rather than barriers and enabling factors because the adoption of BDA occurs at the supply chain level, and it is therefore outside the scope of this study. Crowd-logistics and Drones instead are less consolidated technologies, and thus more attention has been posed towards the barriers to the implementations, as well as the enabling factors. 3.2 Panel selection Experts have been selected through a rigorous selection procedure to account for the diversity between groups of stakeholders. A pool of 226 experts has been asked to take part to this study. These experts have been recognized as last-mile logistics experts due to their enrollment in the Urban Mobility group of ALICE, Alliance for Logistics Innovation through Collaboration in Europe, which aggregates experts of last-mile logistics and coordinates European level initiatives in this field. Moreover, representatives from last-mile companies were found through last-mile logistics special interest groups on LinkedIn. A final number of 27 experts has taken part in the study, equally distributed across different categories of experience and work positions (Fig. 1 ). Therefore, a response rate of 12.4% has been reached, which is deemed acceptable (Monzon, Julio, & Garcia-Martinez, 2020). The respondents have been classified according to several demographic aspects (de Oliveira et al., 2021), such as the number of years of experience as a proxy of the level of expertise (Arditi, Mangano, & De Marco, 2015), and the role profile (De Marco, Mangano, & De Magistris, 2021). Respondents have been grouped as Academics to consider the theoretical perspective, Consultants, or Managers so as to include both internal and external business points of view. Finally, the type of affiliation has been considered to identify similarities or differences between research centers and universities, companies, and other entities such as public agencies.Fig. 1 Distribution of panel across different demographic classes. Fig. 1 3.3 Survey submission The survey is composed is twofold. In the first part experts have been asked to position themselves in the stakeholder category and provide some demographic information, such as professional affiliation, job position and years of experience. In the second part, respondents have been asked to rate the future probability of occurrence for each item, on a 5-point Likert Scale where 1 = Very Improbable, 2 = Improbable, 3 = Possible, 4 = Probable, and 5 = Very Probable. Qualitative statements were also given by the experts to justify their answers. The projections are presented as closed-ended statements in order to achieve content and face validity of the Delphi survey (Hsu & Sandford, 2007). Moreover, the questionnaire was structured into clusters of topics to make it easy to follow. The first round of the survey has been disseminated via e-mail and through specialized online groups on LinkedIn between 08/10/2020 and 13/10/2020. Prior to the second round, we provide descriptive statistics for each item and a general overview of the reasons for such evaluation. Then, the second round has been submitted on 05/11/2020. During the second round, experts could change their quantitative evaluation as many times as they want, providing a reason for this change. 3.4 Data analysis and testing In order to measure consensus, two parameters are used, namely the Interquartile Range (IQR) and the Reliability within group (rwg). IQR calculates the dispersion from the median response, while rwg is a measure of inter-rater agreement. Both parameters are frequently used for analyzing data non-normally distributed, as it is typical of the Delphi survey (Gossler et al., 2019; Jiang, Kleer, & Piller, 2017; Von Briel, 2018). A projection reaches true consensus if IQR is ≤ 1 (Gossler et al., 2019) and Rwg exceeds 0,3 (LeBreton & Senter, 2008). Both parameters need to fall within the required thresholds in order to meet true consensus. The obtained data are also analyzed via the Kruskal-Wallis test, with the goal of finding out whether the samples at issue belong to the same population (Guo, Zhong, & Zhang, 2013). This non-parametric test is able to run when data do not follow a normal distribution and it works also in the case of small sample groups (even smaller than 25) (Kitchen, 2009). Its null hypothesis is the stochastic homogeneity, with stochastic heterogeneity being the alternative one (Vargha & Delaney, 1998). In practical terms, when the null hypothesis has to be rejected, in favor of the alternative one, a significant difference among the medians of the sub-groups exists (Ruxton & Beauchamp, 2008). The level of significance of the test is associated with the p-value. If the test shows p-value lower than the significance level (usually 5%), the null hypothesis can be rejected meaning that there is at least one difference among the groups under study. This means that at least one group has a different perception about the probability of occurrence for a specific projection. In the Delphi methodology the final goal is to obtain a general consensus about the proposed projections. Thus, the Kruskal-Wallis test highlights those items with diverging opinions. For this reason, the tests have been run for both rounds in order to understand if a broader consensus can be observed in the second round. This test has been also carried out by splitting the respondents in two groups. The first one includes the quick respondents. On the contrary, the second group has the late respondents who also received a reminder. Reminder represents a time consuming and expensive strategy aimed at converting reluctant and hesitant participants to late respondents. These approaches assume that late respondents resemble non-respondents more than initial respondents do. Thus, on the one hand increasing response rate by converting hesitant respondents to actual participants can reduce the magnitude of response bias since the pool of respondents becomes more representative of the total sample (Studer et al., 2013). On the other hand, the quality and reliability of the answer might increase since the willingness to take part to the investigation for a hesitant respondent could be lower and in turn the attention given to the questionnaire, with resulting bias (Af Wåhlberg & Poom, 2015). In order to highlight this potential effect, a Kruskal-Wallis test has been carried out between the groups of early and late respondents. The performed tests do not highlight significant differences for most of the projections. Only Projection 2.5 “Crowd logistics does not provide environmental benefits if associated with private cars” shows a median score equal to 5 for late respondents and equal to 4 for the early ones. However, since this difference is not heavily relevant it does not impact on the general consensus of the projection at issue. Also, Projection 6.1 “Parcel Locker diffusion has reached a plateau due to the investment costs needed to reach all customers.” outcomes are different for the two groups of respondents. Similarly, the difference of the median scores is large enough to influence the consensus on the projection. 4 Results In this section the main results obtained by the application of the Delphi approach are described. With the aim of achieving a more shared consensus on the projections at issue the participants involved in the research have received the questions twice. First, the consensus among all experts is evaluated with the Interquartile Range (IQR) and the Reliability within group (rwg). Second, the difference between experts' groups with regards to their assessment is explored via the Kruscal-Wallis test. 4.1 Consensus among experts The first result of the survey is the high level of consensus reached among respondents. Only 8 projections did not reach a consensus after the second round, as shown in Fig. 2 that lists the median and IQR values for all projections, in descending order of consensus (i.e., ascending order of IQR).Fig. 2 Results from the second round of the Delphi survey. All projections are listed here together with their median and IQR. Fig. 2 This is a significant improvement from the results of the first round, where scholars' evaluations did not agree on two thirds of all projections (22 out of 33) (Fig. 3 ).Fig. 3 Results from the first round of the Delphi survey. All projections are listed here together with their median and IQR. Fig. 3 All projections except one have improved both criteria for consensus building (i.e., IQR and rwg). In particular, IQR for projections 4.3, 5.1 and 7.1 has improved by 1.5 points while still maintaining the same median value. Overall, the median value has shifted from round 1 to round 2 in only 4 projections out of 14, and only by one scale point. The highest consensus has been reached by projections 4.3 and 7.1: experts agree that ITS will be used to gather reliable and detailed data on last-mile logistics and that improving the communication between providers and customers will not be hampered by customers' inertia in adopting new technologies. Projections 6.3 has also achieved strong consensus among the experts, who stated that parcel lockers will be attractive to different LSPs regardless of their customers' density. Experts therefore agree that parcel lockers will be more widespread due to their adoption by more LSPs. With regard to projection 6.4, experts agree that it is not yet possible to determine whether LSPs will adopt a shared parcel lockers configuration (Faugère & Montreuil, 2020). In terms of drones' adoption, technological barriers are still found to be very relevant even in future scenarios (projection 3.4). The highest median evaluations have been given to projections 3.2 and 4.2, which reflect the need for involving public authorities in last-mile logistics. As a matter of fact, experts strongly argue that the most relevant barrier for drones' adoption is the lack of regulation frameworks (projection 3.2) and that public authorities will focus on enforcing restrictions through ITS implementations. All projections pertaining to BDA, IoT, ITS and low impact vehicles have reached a consensus. Three projections out of four regarding BDA have received a median evaluation of 4 out of 5, showing that BDA is expected to increase both order frequency for B2B and the share of same day delivery by exploiting a more precise demand forecasting. Another potential application of BDA to last-mile logistics is also represented by a better and improved interaction with the final customer (e.g. by coordinating real-time with the driver. Regarding IoT, projection 7.2 shows that experts are neutral with regards to the barrier of customers' acceptability to IoT technologies such as smart locks due to trust and safety issues. A further application of ITS, besides the above mentioned use to gather data and high impact on local enforcement, lies in the optimization and real-time monitoring and booking systems of loading/unloading areas. Concerning low impact vehicles, experts argue that cargo bikes will be beneficial to a multitude of LSPs and that public incentives will still lead the way for the adoption of another green technology, namely Electric Vehicles. As mentioned above, the Delphi method shows its value even when disagreement among experts is found. With this regard, two technologies have provoked the highest share of projections without consensus, namely crowd-logistics and drones (3 projections out of 7 each). Therefore, it can be argued that it is too early to determine the financial feasibility of drone deliveries (projection 3.1), the best operational configuration in combination with traditional delivery vans (projection 3.5) and thus its impact on the number of traditional vehicles (projection 3.7). Similar results are obtained by the crowd-logistics, where experts do not agree on the acceptability by customers (projection 2.1), the scope of application (projection 2.3) and thus the substitution effect with regards to traditional vans (projection 2.2). Finally, the opinion of the experts is divided about the suitability of adopting parcel lockers in high-density and urban areas rather in suburban or rural areas. 4.2 Difference between experts' groups Table 2 demonstrates that there are few significant differences among the stakeholders' groups, according to the outcomes of the Kruskal-Wallis statistical test. This test has been carried out for all projections after the final round of the survey where consensus (or lack thereof) has been reached.Table 2 Items with significant differences among sub-groups. Table 2Projection Final Round Years of Experience Kruskal Wallis 0–4 years 5–9 years 10–14 years >15 years P-value adj for ties Median Score Median Score Median Score Median Score 1.1 1 3.5 3.0 3.0 3.5 0.025 3.2 1 5.0 5.0 5.0 4.0 0.007 3.4 2 4.5 4.0 4.0 3.0 0.041 JobPosition Academic Consultant Manager Median Score Median Score Median Score 1.1 1 3.00 4.00 3.00 0.049 2.4 2 2.0 3.5 3.0 0.044 Affiliation Others Private Company University/Research Centre Median Score Median Score Median Score 1.1 1 3.5 4.0 3.0 0.022 6.1 1 3.0 2.0 2.0 0.030 In fact, only 5 out of the 33 projections have a dissimilar perspective across the identified subgroups of the sample. In particular projection 1.1 “BDA have enabled de-centralization of decision-making processes in supply networks and have supported the growth of micro-retailing, such as “nanostores” is considered to be more realistic for the youngest and oldest professionals. On the contrary, respondents with an average length of professional experience have expressed just a medium preference, meaning that from their perspective Big Data will not necessarily facilitate the decentralization of decision making processes in the supply chain. This projection shows a discrepancy in the evaluation also by observing the Job Position, whereby the Consultant group provides a higher evaluation compared to academics and managers. Projection 2.4 related to the feasibility of crowd logistics services in high density areas show different perceptions. The academic subsample considers this scenario less plausible thus meaning that crowd-logistics services might be useful also in other business environments. On the contrary, managers and consultants state that this technology is expected to be exploited more effectively in the specific geographical context of an urban area. According to more experienced respondents, Item 3.2 “To support the adoption of drone-based delivery, how important it has been to overcome the following issues: [Lack of dedicated regulation frameworks.]”, is not as crucial as it is considered for the other ones, meaning that the level of awareness related to the policy framework associated with the use of drones is more significant for younger experts. Moreover, for Item 3.4 “To support the adoption of drone-based delivery, how important it has been to overcome the following issues: Technological issues -e.g., range, capacity, resistance to extreme weather, landing capabilities, safety, advanced navigation and coordination algorithms” the alignment of opinion according to the years of experience is not achieved. Older professionals consider less important the technological burdens that impact on the adoption of drones. Finally, Universities and Private Companies provide a low rate to Item 6.1 “Parcel Locker diffusion has reached a plateau due to the investment costs needed to reach all customers”. Thus, cost is not considered as a crucial factor for Parcel Locker diffusion for these stakeholders. 5 Discussion of results The two projections that reached the highest level of consensus, namely the future use of ITS data and the technology adoption inertia by consumers (i.e., projections 4.3 and 7.1), are likely linked together to the extent that private companies and city administrations alike will collect a large amount of logistics data via ITS systems. Such large amount of data will probably be used to overcome the technology resistance by customers, as to achieve direct communications and better coordination with customers. For example, real-time freight data sharing and route optimization software would help operators to provide quicker logistics services and to align with the customers' whereabouts and preferred time windows. Similarly, projection 1.4 confirms that operators will use BDA for a more effective interaction with last-mile actors (e.g.: drivers, LSPs). However, with projection 7.2 experts are not so confident that all customers will understand the value and accept the usage of IoT and BDA. Moreover, not all BDA-based applications will provide benefits to last-mile logistics processes. In fact, BDA will likely support local businesses' ordering policies by enabling short lead times, high frequency and low volume orders. Therefore, BDA will make B2B deliveries rather similar to B2C deliveries in terms of their impact to last-mile logistics (Melkonyan et al., 2020; Morganti, Dablanc, & Fortin, 2014). This statement is strongly supported by consultants who are supposed to be deeply involved on BDA projects (Hughes & Ball, 2020). As for the future of parcel lockers utilization, as stated in the results, experts foresee that this technology will likely be adopted by LSPs regardless of their customers' density, but are still uncertain over the most likely installation choice (i.e., under a single-provider or a shared configuration) and whether parcel lockers will be more adopted in either urban or suburban environments. This will open doors for studies that would highlight the potential for widespread adoption in far remote areas. The diffusion that could result from this process could generate negative impacts on public land use, unless regulated through restrictions imposed by public administrations and assets sharing policies. Likewise, the role of public authorities is reinforced in projections 3.2, 4.2 and 5.1 that view public authorities as both regulators and major players of the technology adoption process. These findings underline the more proactive role public authorities have been playing in the last-mile logistics sector in recent years. The missing consensus about the future of drones reflects the infancy of this technology, due to still unsolved issues, like security (e.g. thefts and damages) (Kunze, 2016), limited flight range, carrying capacity, and potential congestion around their depots (Moshref-Javadi & Winkenbach, 2021). Younger experts pay more attention to these issues than more experienced ones, and thus it is expected that solving these hurdles will be a priority for the future. In fact, the adoption of drones for delivery aims is expected to increase as a feasible way to deal with the continuous growth of e-commerce and the higher demand for speed of delivery services. Same dissent is found among the crowd-logistics projections, which generate a mixed technology landscape for the future of such innovative solution. In fact, experts agree that crowd logistics will provide a lower level of service than traditional delivery. This will have a more negative impact on customers' acceptance than trust, safety and security issues connected to this innovative delivery service. Therefore, e-commerce B2C delivery via traditional vehicles will still be more efficient than crowd-logistics. Such projection does not achieve the consensus, even though 75% of respondents rate this projection higher than the neutral value (i.e.: 3 over 5). Nevertheless, scholars and professionals disagree as to the profitability of crowd-logistics in high-demand environments (i.e.: projection 2.4). This might depend on their different perspective. On the one hand, academics tend to argue that lower levels of road infrastructure development in rural areas are leading to a larger use of crowd-logistics for the distribution of packages outside of the city centers (Lewis, 2020). On the other hand, managers and consultants highlight that the current ongoing urbanization, the rapid growth in e-commerce deliveries, and increasing urban traffic congestion, make crowd logistics beneficial in urban environments with high level of population density (Raj & Sah, 2019). In general, though this innovation could be profitable for operators in a wide range of contexts, it will not completely replace traditional delivery approaches. Nevertheless, a successful diffusion of crowd logistics might increase the pressure on drivers' salaries. Furthermore, most asset sharing applications might be enhanced though the integration between public entities owing traffic and infrastructure data and private companies that deal with data related to urban freight transport (Cleophas et al., 2019). Private companies in charge of providing logistics services by applying Crowd Logistics or Crowd Shipping are increasingly outsourcing the logistics processes and sub-processes to individuals (Melkonyan et al., 2020). These applications offer potential advantages for different stakeholders (Ermagun & Stathopoulos, 2020). 6 Conclusions This research has explored the future scenarios for some of the most relevant innovations in CL, from an experts' perspective. To this end, this study has adopted a two-round online Delphi survey to rigorously extrapolate patterns originated from the experts' assessment of 33 projections focusing on seven technologies and four categories of analysis. Results shows that consensus among the experts has been reached through the two-round survey. This consensus is widespread across the projections (i.e., experts have agreed on 76% of the projections) and yet it does not rule out a healthy level of disagreement between experts both at the individual and group level, thus safeguarding everyone's opinion. Moreover, in the second round of the survey experts have mostly shifted their opinion towards the median evaluation achieved in the first round rather than changing their evaluation altogether, showing that the Delphi has supported the achievement of a “real” consensus rather than an artificial one. In the next subsections the main implications, limitations and future research directions are highlighted. 6.1 Implications From a theoretical perspective this work enlarges the body of knowledge about the adoption patterns of innovative technologies in last mile operations. Thus, it might stimulate research about the most relevant technologies that are likely to have an impact on CL processes. In addition, the present study exploits the Delphi methodology that has proven to be effective and to provide robust results in different fields of applications (Von Briel, 2018; Von Der Gracht & Darkow, 2010). Finally, this research tests the outcomes of the Delphi approach by using the Kruskal-Wallis test as a way for highlighting potential misalignments among the subgroups of the sample. From a practical point of view, the innovative technologies evaluated in this study might enable a deeper understanding of their potential future application to CL. Thus, this research might support companies to properly plan future technical choices and better address related investments. This aspect is particularly crucial, considering the high uncertainty associated with the innovative markets and the relevant level of financial engagement required for implementing new technologies (Kurata, 2019). Similarly, public authorities might be facilitated by this work in designing suitable urban policies and in turn to intervene in new contexts that are still not involved by the innovative trends in last mile. 6.2 Limitations This study aims to identify and analyze technology patterns related to the field of CL, by adopting a structured approach intended to frame the views from a selected group of experts in a quantitative way. However, it has to be pointed out that the scope of this study might hinder the generalizability of such results. In fact, experts are drawn from a list of professionals and scholars working for European institutions, due to the relative ease of connection with the authors. Moreover, a set of technologies that appears to be more relevant nowadays for CL have been chosen. Such sub-set of technologies is deemed to be exhaustive of current implementations but does not intend to represent all technologies available for CL applications, especially in the near future. 6.3 Future research directions Drawing from the scope limitations, future research could be directed towards applying the Delphi methodology to CL technologies after the time frame considered in this study. This future path could for instance validate the experts' opinion and enlarge the scope of technologies evaluated. This study highlights some open questions regarding few technologies. It can be stated for instance that real-time data collection by private and public stakeholders alike will help the coordination process between stakeholders and final customers. However, an increased awareness over the value of logistics data as well as their potential drawbacks from the customers' perspective, such as an increased order frequency by B2B customers, is needed. Regarding the drones, the future looks promising as multiple logistics companies are planning to implement such innovation and younger experts from the sample seem keener on reducing the barriers to such implementation. This stream is very promising due to the increasing number of e-commerce retailers and express couriers developing their own drones fleet and starting their pilot implementations (Roland Berger, 2020). However, future research streams should aim at solving its major issues, such as safety of the package and flight range. Parcel Lockers will expand significantly, and their success should be monitored by public authorities, who could foster and incentivize the shared configuration to decrease their impacts on land use. Finally, crowd-logistics will remain a lesser mean for last-mile delivery but may become beneficial deliveries that are outside the scope of traditional e-commerce, thus potentially increasing the pressure on the drivers' salaries. To this end, scholars are called to engage into studies that will guide LSPs towards a successful implementation of crowd-logistics without reducing their workers' salaries. This is particularly relevant considering the recent Covid-19 pandemic, which has exposed the importance of last-mile logistics for the whole population, making drivers essential workers of urban areas. Data availability Data will be made available on request. ==== Refs References Af Wåhlberg A. Poom L. An empirical test of nonresponse bias in internet surveys Basic and Applied Social Psychology 37 6 2015 336 347 Amaya J. Urban freight logistics: What do citizens perceive? Transportation Research Part E: Logistics and Transportation Review 152 2021 102390 Anderson T. Further examination of Moore’s law with data envelopment analysis Technological Forecasting and Social Change 69 5 2002 465 477 Arditi D. Mangano G. De Marco A. Assessing the smartness of buildings Facilities 33 9/10 2015 553 572 Arslan A.M. Crowdsourced delivery—A dynamic pickup and delivery problem with ad hoc drivers Transportation Science 53 1 2019 222 235 Baghdadi A. A machine learning approach to detect changes in gait parameters following a fatiguing occupational task Ergonomics 61 8 2018 1116 1129 29452575 Bozzo R. Conca A. Marangon F. Decision support system for city logistics: Literature review, and guidelines for an ex-ante model Transportation Research Procedia 3 2014 518 527 10.1016/j.trpro.2014.10.033 Cagliano A.C. Analyzing the diffusion of eco-friendly vans for urban freight distribution International Journal of Logistics Management 28 4 2017 10.1108/IJLM-05-2016-0123 Carbone V. Rouquet A. Roussat C. Carried away by the crowd: What types of logistics characterise collaborative consumption 1st International Workshop on Sharing Econom, Utrecht, Netherlands 2015 Cattaruzza D. Vehicle routing problems for city logistics EURO Journal on Transportation and Logistics 2015 1 29 10.1007/s13676-014-0074-0 Cleophas C. Collaborative urban transportation: Recent advances in theory and practice European Journal of Operational Research 273 3 2019 801 816 Culot G. The future of manufacturing: A Delphi-based scenario analysis on industry 4.0 Technological Forecasting and Social Change 157 2020 120092 32351256 De Marco A. Mangano G. De Magistris P. Evaluation of project management practices in the automotive original equipment manufacturers Procedia Computer Science 181 2021 310 324 Dolati Neghabadi P. Espinouse M.-L. Lionet E. Impact of operational constraints in city logistics pooling efficiency International Journal of Logistics Research and Applications 2021 1 25 van Duin J.H.R. Towards an agent-based modelling approach for the evaluation of dynamic usage of urban distribution centres Procedia - Social and Behavioral Sciences 39 2012 333 348 10.1016/j.sbspro.2012.03.112 Egilmez G. Tatari O. A dynamic modeling approach to highway sustainability: Strategies to reduce overall impact Transportation Research Part A: Policy and Practice 46 7 2012 1086 1096 Enthoven D.L. The two-echelon vehicle routing problem with covering options: City logistics with cargo bikes and parcel lockers Computers & Operations Research 118 2020 104919 Ermagun A. Stathopoulos A. Crowd-shipping delivery performance from bidding to delivering Research in Transportation Business & Management 2020 100614 Faugère L. Montreuil B. Smart locker bank design optimization for urban omnichannel logistics: Assessing monolithic vs. modular configurations Computers & Industrial Engineering 139 2020 105544 Fritschy C. Spinler S. The impact of autonomous trucks on business models in the automotive and logistics industry–a Delphi-based scenario study Technological Forecasting and Social Change 148 2019 119736 10.1016/j.techfore.2019.119736 Fu H. Factors influencing user usage intention on intelligent logistics information platform Journal of Intelligent Fuzzy Systems 35 3 2018 2711 2720 Gammelgaard B. The emergence of city logistics: The case of Copenhagen’s Citylogistik-kbh International Journal of Physical Distribution and Logistics Management 45 4 2015 333 351 10.1108/IJPDLM-12-2014-0291 de Gauna D.E.R. Villalonga C. Sánchez L.E. Multi-agent systems in the field of urbane-mobility: A systematic review IEEE Latin America Transactions 18 12 2020 2186 2195 Golpîra H. Khan S.A.R. Safaeipour S. A review of logistics internet-of-things: Current trends and scope for future research Journal of Industrial Information Integration 22 100194 2021 Gorbea C.E. Lindemann U. de Weck O.L. System dynamics modeling of new vehicle architecture adoption 2011 Gordon T.J. The methods of futures research The Annals of the American Academy of Political and Social Science 522 1 1992 25 35 Gossler T. Applying the Delphi method to determine best practices for outsourcing logistics in disaster relief Journal of Humanitarian Logistics and Supply Chain Management 9 3 2019 438 474 von der Gracht H. Consensus measurement in Delphi studies: Review and implications for future quality assurance Technological Forecasting and Social Change 79 8 2012 1525 1536 Gu H. Liu Z. Qing Q. Optimal electric vehicle production strategy under subsidy and battery recycling Energy Policy 109 2017 579 589 Guo S. Zhong S. Zhang A. Privacy-preserving kruskal–Wallis test Computer Methods and Programs in Biomedicine 112 1 2013 135 145 23871682 Guthrie C. Fosso-Wamba S. Arnaud J.B. Online consumer resilience during a pandemic: An exploratory study of e-commerce behavior before, during and after a COVID-19 lockdown Journal of Retailing and Consumer Services 61 2021 102570 Haque N. Planning for clean technology diffusion: Identifying innovation system functions in country technology action plans Energy Research & Social Science 90 2022 102595 Hsu C.-C. Sandford B.A. Minimizing non-response in the Delphi process: How to respond to non-response Practical Assessment, Research and Evaluation 12 17 2007 1 5 Hughes J. Ball K. Sowing the seeds of value? Persuasive practices and the embedding of big data analytics Technological Forecasting and Social Change 161 2020 120300 Iwan S. Kijewska K. Lemke J. Analysis of parcel lockers Efficiency as the last mile delivery solution - The results of the research in Poland 2016 644 655 10.1016/j.trpro.2016.02.018 Jiang R. Kleer R. Piller F.T. Predicting the future of additive manufacturing: A Delphi study on economic and societal implications of 3D printing for 2030 Technological Forecasting and Social Change 117 2017 84 97 Kandt J. Batty M. Smart cities, big data and urban policy: Towards urban analytics for the long run Cities 109 2021 102992 Katsela K. Pålsson H. Viable business models for city logistics: Exploring the cost structure and the economy of scale in a Swedish initiative Research in Transportation Economics 2020 100857 Kim R.Y. The impact of COVID-19 on consumers: Preparing for digital sales IEEE Engineering Management Review 48 3 2020 212 218 Kitchen C.M. Nonparametric vs parametric tests of location in biomedical research American Journal of Ophthalmology 147 4 2009 571 572 19327444 Kunze O. Replicators, ground drones and crowd logistics a vision of urban logistics in the year 2030 Transportation Research Procedia 19 2016 286 299 Kurata H. Is the information of customer types and preferences to personal selling worth the investment in innovative technology? A modeling approach Journal of Retailing and Consumer Services 49 2019 371 379 Landeta J. Current validity of the Delphi method in social sciences Technological Forecasting and Social Change 73 5 2006 467 482 LeBreton J.M. Senter J.L. Answers to 20 questions about interrater reliability and interrater agreement Organizational Research Methods 11 4 2008 815 852 Lewis N. A tech company engineered drones to deliver vital COVID-19 medical supplies to rural Ghana and Rwanda in minutes URL https://www.businessinsider.com/zipline-drone-coronavirus-supplies-africa-rwanda-ghana-2020-5 2020 [Preprint] Li X. Identifying and monitoring the development trends of emerging technologies using patent analysis and twitter data mining: The case of perovskite solar cell technology Technological Forecasting and Social Change 146 2019 687 705 Macrina G. Pugliese L.D.P. Guerriero F. La Porte G. Drone-aided routing: A literature review. ransportation Research Part C: Emerging Technologies 120 102762 2020 Malik M. Dutta M. Granjal J. A survey of key bootstrapping protocols based on public key cryptography in the internet of things IEEE Access 7 2019 27443 27464 Mangano G. The dynamics of diffusion of an electronic platform supporting City logistics services Operations Management Research 12 3–4 2019 10.1007/s12063-019-00147-7 Markmann C. Darkow I.-L. Von Der Gracht H. A Delphi-based risk analysis—Identifying and assessing future challenges for supply chain security in a multi-stakeholder environment Technological Forecasting and Social Change 80 9 2013 1815 1833 Martins V.W.B. Anholon R. Quelhas O.L.G. Sustainable transportation methods Encyclopedia of sustainability in higher education 2019 1847 1853 McKinnon A.C. Piecyk M.I. Application of the Delphi method to the forecasting of long-term trends in road freight, logistics and related CO2 emissions International Journal of Transport Economics: Rivista Internazionale di Economia dei Trasporti XL 2 2013 241 266 Melkonyan A. Sustainability assessment of last-mile logistics and distribution strategies: The case of local food networks International Journal of Production Economics 228 2020 107746 Melnyk S.A. Mapping the future of supply chain management: A Delphi study International Journal of Production Research 47 16 2009 4629 4653 Moghram I. Rahman S. Analysis and evaluation of five short-term load forecasting techniques IEEE Transactions on Power Systems 4 4 1989 1484 1491 Monzon A. Julio R. Garcia-Martinez A. Hybrid methodology for improving response rates and data quality in mobility surveys Travel Behaviour and Society 20 2020 155 164 Morganti E. Dablanc L. Fortin F. Final deliveries for online shopping: The deployment of pickup point networks in urban and suburban areas Research in Transportation Business and Management 11 2014 23 31 10.1016/j.rtbm.2014.03.002 Moshref-Javadi M. Winkenbach M. Applications and research avenues for drone-based models in logistics: A classification and review Expert Systems with Applications 2021 114854 Nafil A. Comparative study of forecasting methods for energy demand in Morocco Energy Reports 6 2020 523 536 Nathanail E. A sustainability cross-case assessment of city logistics solutions Case Studies on Transport Policy 9 1 2021 219 240 Nürnberg M. Analysis of using cargo bikes in urban logistics on the example of Stargard Transportation Research Procedia 39 2019 360 369 de Oliveira L.K. Evaluating problems and measures for a sustainable urban freight transport in Brazilian historical cities Sustainable Cities and Society 69 2021 102806 Prosperi M. Lombardi M. Spada A. Ex ante assessment of social acceptance of small-scale agro-energy system: A case study in southern Italy Energy Policy 124 2019 346 354 Raj A. Sah B. Analyzing critical success factors for implementation of drones in the logistics sector using grey-DEMATEL based approach Computers & Industrial Engineering 138 2019 106118 Rauch W. The decision delphi Technological Forecasting and Social Change 15 3 1979 159 169 Roland Berger Cargo drones: The future of parcel delivery 2020 Roland Berger Available at https://www.rolandberger.com/en/Insights/Publications/Cargo-drones-The-future-of-parcel-delivery.html Roßmann B. The future and social impact of big data analytics in supply chain management: Results from a Delphi study Technological Forecasting and Social Change 130 2018 135 149 Rowe G. Wright G. Armstrong J.S. Expert opinions in forecasting: The role of the Delphi technique BT - principles of forecasting: A handbook for researchers and practitioners 2001 Springer US Boston, MA 125 144 10.1007/978-0-306-47630-3_7 Rowe G. Wright G. The Delphi technique: Past, present, and future prospects—Introduction to the special issue Technological Forecasting and Social Change 78 9 2011 1487 1490 Rowe G. Wright G. Bolger F. Delphi: A reevaluation of research and theory Technological Forecasting and Social Change 39 3 1991 235 251 Ruxton G. Beauchamp G. Some suggestions about appropriate use of the Kruskal–Wallis test Animal Behaviour 76 3 2008 1083 1087 Savun-Hekimoğlu B. Evaluation of water supply alternatives for Istanbul using forecasting and multi-criteria decision making methods Journal of Cleaner Production 287 2021 125080 Schwerdfeger S. Boysen N. Optimizing the changing locations of mobile parcel lockers in last-mile distribution European Journal of Operational Research 285 3 2020 1077 1094 Shepherd S. Bonsall P. Harrison G. Factors affecting future demand for electric vehicles: A model based study Transport Policy 20 2012 62 74 Sheth J. Impact of Covid-19 on consumer behavior: Will the old habits return or die? Journal of Business Research 117 2020 280 283 32536735 Soret A. Guevara M. Baldasano J. The potential impacts of electric vehicles on air quality in the urban areas of Barcelona and Madrid (Spain) Atmospheric Environment 99 2014 51 63 Stepp M.D. Greenhouse gas mitigation policies and the transportation sector: The role of feedback effects on policy effectiveness Energy Policy 37 7 2009 2774 2787 Studer J. Examining non-response bias in substance use research—Are late respondents proxies for non-respondents? Drug and Alcohol Dependence 132 1–2 2013 316 323 23535061 Tahaei H. The rise of traffic classification in IoT networks: A survey Journal of Network and Computer Applications 154 2020 102538 Taniguchi E. Thompson R.G. Qureshi A.G. Modelling city logistics using recent innovative technologies Transportation Research Procedia 46 2020 3 12 Teo J.S.E. Taniguchi E. Qureshi A.G. Evaluating city logistics measure in E-commerce with multiagent systems Procedia - Social and Behavioral Sciences 39 2012 349 359 10.1016/j.sbspro.2012.03.113 Turoff M. Linstone H.A. The Delphi method-techniques and applications 2002 Vargha A. Delaney H.D. The Kruskal-Wallis test and stochastic homogeneity Journal of Educational and Behavioral Statistics 23 2 1998 170 192 Vila N.A. Scopus analysis of the academic research performed by public universities in Galicia and north of Portugal Information Resources Management Journal (IRMJ) 33 1 2020 16 38 Von Briel F. The future of omnichannel retail: A four-stage Delphi study Technological Forecasting and Social Change 132 2018 217 229 Von Der Gracht H.A. Darkow I.-L. Scenarios for the logistics services industry: A Delphi-based analysis for 2025 International Journal of Production Economics 127 1 2010 46 59 32288260 Wang J. An intelligent logistics service system for enhancing dispatching operations in an IoT environment Transportation Research Part E: Logistics and Transportation Review 135 2020 101886 Wang Z. Mersereau A.J. Bayesian inventory management with potential change-points in demand Production and Operations Management 26 2 2017 341 359 Yabe N. Relationship between internet use and out-of-home activities during the first wave of the COVID-19 outbreak in Japan Transportation Research Interdisciplinary Perspectives 10 2021 100343 34514369 Yoo W. Yu E. Jung J. Drone delivery: Factors affecting the public’s attitude and intention to adopt Telematics and Informatics 35 6 2018 1687 1700 Yu F. Schweisfurth T. Industry 4.0 technology implementation in SMEs–A survey in the Danish-German border region International Journal of Innovation Studies 4 3 2020 76 84 Yuskevich I. Model-based approaches for technology planning and roadmapping: Technology forecasting and game-theoretic modeling Technological Forecasting and Social Change 168 2021 120761 Zhang S. Fine-grained vehicle emission management using intelligent transportation system data Environmental Pollution 241 2018 1027 1037 30029310
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==== Front Can J Public Health Can J Public Health Canadian Journal of Public Health = Revue Canadienne de Santé Publique 0008-4263 1920-7476 Springer International Publishing Cham 36508152 721 10.17269/s41997-022-00721-w Special Issue on Sociocultural and Behavioural Factors Affecting Communities' Responses to Public Health Measures: Implications for the Covid-19 Pandemic and Beyond Foreword Avant-proposDubé Eve [email protected] 12 MacDonald Noni E. 34 1 grid.434819.3 0000 0000 8929 2775 Institut national de santé publique du Québec, Québec, Québec Canada 2 grid.23856.3a 0000 0004 1936 8390 Centre de recherche du CHU de Québec - Université Laval, Québec, Québec Canada 3 grid.55602.34 0000 0004 1936 8200 Department of Pediatrics, Dalhousie University, Halifax, Nova Scotia Canada 4 grid.414870.e 0000 0001 0351 6983 IWK Health Centre, Halifax, Nova Scotia Canada 12 12 2022 13 © The Author(s) under exclusive license to The Canadian Public Health Association 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. ==== Body pmcWe are pleased to introduce you to this special issue of the Canadian Journal of Public Health (CJPH) that draws from findings from a large, multi-site, multi-study qualitative research project conducted in four Canadian provinces (British Columbia, Ontario, Quebec, and Nova Scotia), thanks to funding from the Canadian Institutes of Health Research. As of October 1, 2022, the COVID-19 pandemic has caused more than 4 million cases and 45,455 deaths in Canada (Government of Canada, 2022), in addition to significant social and economic consequences. As in many countries, the pandemic also strongly challenged the public health workforce, stretching it to its limits over two years of working to manage and mitigate COVID-19 impacts, including the deployment of Canada’s largest mass vaccination campaign. The articles in this special issue explore the impacts of the COVID-19 pandemic and of the public health measures put in place to curb the spread of the virus on diverse segments of the Canadian population (youth, people of Asian descent, low-income individuals, among others). In the context of information overload—the COVID-19 infodemic—and increased polarization (World Health Organization, 2022), the articles also unravel the challenges of communication in the context of a health emergency such as COVID-19. As a result of systemic racism and health inequalities in Canada, infectious diseases have disproportionately affected migrant and ethnic minority populations as well as First Nations, Inuit, and Métis peoples (Chang et al., 2018). Due to disproportionate representation in precarious occupations not subject to COVID-19 lockdowns, lack of access early on to personal protective equipment, and poor working/living conditions, these populations were also subject to differential exposure to COVID-19 (National Advisory Committee on Immunization, 2020). These groups also had lower rates of vaccine uptake early on due to systemic barriers in access to health and vaccination services and vaccine demand and acceptance issues. Public acceptance of effective, scientifically rigorous, and ethically sound recommendations to reduce transmission, including vaccine acceptance, is predicated on trust in government, public health authorities, and pharmaceutical companies; however, establishing public trust in such messages is not straightforward. The mission of the CJPH is to advance public health practice in Canada and contribute to the improvement of population health. We believe that this special issue hones in on these objectives. The articles assembled describe how different segments of the Canadian population differentially responded to public health recommendations, providing insights into how public health authorities can communicate more effectively to build trust and resilience in the system and ensure better adherence to recommended measures by the majority without being either patronizing or stigmatizing. A good understanding of different community dynamics, sociocultural factors, and local knowledge (i.e., individual/community understanding of disease, priorities, and fears, including public health messaging) that may impact the understanding and acceptance of public health recommendations by communities is critical for success. These studies highlight the varied issues and problem foci and emphasize how best to use communication to respond and guide efforts to address misinformation, fear, and stigma related to the COVID-19 pandemic and for future health crises in diverse communities in Canada. The articles in this special issue provide an in-depth exploration of five different sociocultural contexts and communities. These findings will be useful for public health practitioners now and in the future for how best to communicate recommendations, in a transparent and non-stigmatizing manner, to better encourage adherence. Tailoring communication of public health recommendations and consideration of the sociocultural factors that may lead to inequalities can ultimately contribute to improving the health of the Canadian population beyond the COVID-19 pandemic. The observations and findings should also resonate beyond our country as Canada is not alone in having public health diversity and inequity issues. Eve Dubé, Guest Editor Noni E. MacDonald, Guest Editor Avant-propos Nous sommes heureuses de vous présenter ce numéro spécial de la Revue canadienne de santé publique (RCSP) qui s’inspire des résultats d’un vaste projet de recherche qualitative multi-sites et multi-études mené dans quatre provinces canadiennes (Colombie-Britannique, Ontario, Québec et Nouvelle-Écosse), grâce au financement des Instituts de recherche en santé du Canada. En date du 1er octobre 2022, plus de 4 millions de cas et 45 455 décès sont attribuables à la pandémie de la COVID-19 au Canada (Government of Canada, 2022), en plus d’importantes conséquences sociales et économiques. Comme dans de nombreux pays, la pandémie a également mis à rude épreuve le personnel de santé publique, l’amenant à ses limites au cours des deux années de travail consacrées à la gestion et à l’atténuation des impacts de la COVID-19, y compris le déploiement de la plus grande campagne de vaccination de masse au Canada. Les articles réunis dans ce numéro spécial explorent les impacts de la pandémie de la COVID-19 et des mesures de santé publique mises en place pour enrayer la propagation du virus sur divers groupes de la population canadienne (incluant les jeunes adultes, les personnes d’origine asiatique, les personnes à faible revenu). Dans un contexte de surabondance d’information—ou infodémie—et de polarisation accrue (World Health Organization, 2022), les articles dévoilent également les défis de communication dans le contexte d’une urgence sanitaire telle que la COVID-19. En raison du racisme systémique et des inégalités en matière de santé au Canada, les maladies infectieuses ont touché de manière inégale les populations migrantes et les minorités ethniques, ainsi que les Premières Nations, les Inuits et les Métis (Chang et al., 2018). En raison d’une représentation disproportionnée dans des métiers précaires et non soumis aux mesures de confinement, du manque d’accès à l’équipement de protection individuelle au début de la pandémie et aux mauvaises conditions de travail et de vie, ces populations étaient également soumises à une exposition plus importante à la COVID-19 (National Advisory Committee on Immunization, 2020). Pourtant, ces groupes présentaient des taux de vaccination contre la COVID-19 plus faibles en raison d’obstacles systémiques dans l’accès aux services de santé et de vaccination et d’un manque de confiance et d’acceptabilité de la vaccination. L’acceptabilité par le public de recommandations efficaces, scientifiquement rigoureuses et éthiquement fondées pour réduire la transmission, y compris la vaccination, repose sur la confiance envers le gouvernement, les autorités de santé publique et les sociétés pharmaceutiques; or, il n’est pas aisé d’établir la confiance du public dans de tels messages. La mission de la RCSP est de faire progresser la pratique de la santé publique au Canada et de contribuer à l’amélioration de la santé de la population. Nous pensons que ce numéro spécial répond à ces objectifs. Les articles rassemblés décrivent comment différents groupes de la population canadienne ont réagi de façon différente aux recommandations de santé publique. Ils donnent un aperçu de la façon dont les autorités de santé publique peuvent communiquer plus efficacement pour renforcer la confiance et la résilience du système et assurer une meilleure adhésion aux mesures recommandées par la majorité, sans être ni condescendants ni stigmatisants. Pour y parvenir, il est essentiel de bien comprendre les différentes dynamiques communautaires, les facteurs socioculturels et les savoirs locaux (c’est-à-dire la compréhension de la maladie des individus et des groupes, les priorités de santé et les craintes, y compris les messages de santé publique) qui peuvent avoir un impact sur la compréhension et l’acceptabilité des recommandations de santé publique par les communautés. Ces études mettent en évidence les diverses questions et sources de problèmes et discutent de la meilleure façon d’utiliser la communication pour répondre et guider les efforts visant à lutter contre la désinformation, la peur et la stigmatisation liées à la pandémie de COVID-19 ainsi qu’aux futures crises sanitaires dans différentes communautés au Canada. Les articles de ce numéro spécial offrent une exploration approfondie de cinq contextes socioculturels et communautés différents. Ces résultats seront utiles aux professionnels de santé publique, aujourd’hui et demain, dans la communication des recommandations, de manière transparente et non stigmatisante, afin d’encourager l’adhésion de la population. La prise en compte de facteurs socioculturels susceptibles d’entraîner des inégalités dans la communication des recommandations de santé publique peut certainement contribuer à améliorer la santé de la population canadienne au-delà de la pandémie de la COVID-19. Les observations et les résultats devraient également trouver résonnance au-delà du Canada, puisqu’il n’est pas le seul pays à rencontrer des problèmes de diversité et d’inégalité en matière de santé publique. Eve Dubé, rédactrice invitée Noni E. MacDonald, rédactrice invitée Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References/Références Chang AY Riumallo-Herl C Perales NA Clark S Clark A Constenla D Garske T Jackson ML Jean K Jit M Jones EO Li X Suraratdecha C Bullock O Johnson H Brenzel L Verguet S The equity impact vaccines may have on averting deaths and medical impoverishment in developing countries Health Affairs 2018 37 2 316 324 10.1377/hlthaff.2017.0861 29401021 Government of Canada. (2022). COVID-19 epidemiology update. Retrieved October 11, 2022 from https://health-infobase.canada.ca/covid-19/ National Advisory Committee on Immunization. (2020). Preliminary guidance on key populations for early COVID-19 immunization. Retrieved October 11, 2022 from https://www.canada.ca/en/public-health/services/immunization/national-advisory-committee-on-immunization-naci/guidance-key-populations-early-covid-19-immunization.html World Health Organization. (2022). Infodemic. Retrieved October 11, 2022 from https://www.who.int/health-topics/infodemic/the-covid-19-infodemic#tab=tab_1
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==== Front J Bioeth Inq J Bioeth Inq Journal of Bioethical Inquiry 1176-7529 1872-4353 Springer Nature Singapore Singapore 36508143 10218 10.1007/s11673-022-10218-3 Letter to the Editor Maintaining Basic Social Ethics: Economic Man or Social Man? Chen Bingyuan [email protected] 1 http://orcid.org/0000-0003-1633-1480 Fang Laitan [email protected] 2 Liu Ronghui [email protected] 3 1 Library of Northeastern University at Qinhuangdao, Qinhuangdao, 066004 China 2 grid.449559.0 0000 0004 0545 6445 Nueva Ecija University of Science and Technology Graduate School Gen, Tinio Street, 3100 Cabanatuan City, Philippines 3 grid.410726.6 0000 0004 1797 8419 School of Economic and Management, University of Chinese Academy of Sciences, Beijing, 100080 China 12 12 2022 12 6 4 2022 12 6 2022 © Journal of Bioethical Inquiry Pty Ltd. 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Keywords Economic man Social man Compatibility Bioethics ==== Body pmcDear Editor, With economic and social development, the improvement of people’s living standards, the fast-paced life created by urbanization, the huge pressures of balancing work and life, and excessive and disorderly marketization, the result has been mercenary pursuits to acquire benefits and avoid disadvantages, with the mentality of “every man for himself,” regardless of others. The consequence has been reflected in neighbours who do not know each other and do not communicate on weekdays, rampant economic materialism, social avoidance, commercial fraud, a lack of ethics, and moral decay that constantly erodes the bottom line of basic principles of social bioethics. Recent examples in China include crises with an unwillingness to help the elderly when they fall because of the rampant exploitation of good Samaritans. However, establishing a market economic order under good order and the rule of law is the basic goal of Hayek’s great society. The primacy of the rule of law, constitutionalism, and freedom are the core concepts of his economic, political, and social thoughts (Ebenstein 2014). Therefore, to some extent, whether we are focused on economic development or social development, there is no direct conflict with basic social ethics, and the development of a market economy will not become an obstacle to the practice of abiding by social ethics. As an example, we have seen the emergence of a tiny supermarket, initiated by a gift of soft drink, during the pandemic in Shanghai, in which a community member shared a box of cola for free and inadvertently initiated a sociological experiment.1 In this way, China’s old saying that “distant relatives are not as good as close neighbors, since neighbours watch and help each other” and other similar traditional ethical and moral principles invite neighbors to unite, to help the weak, and to create community warmth and harmony. In April 2022, the pandemic situation in Shanghai was at its most serious point, and daily essentials were the scarcest. On the evening of April 11, Mr. Sun, a resident of a community in Pudong District, Shanghai, took the initiative to put a box of twelve bottles of cola in the lobby of the building, after disinfection, to share with his neighbours free of charge. The notion of cola as a means of exchange became popular. Free cola sharing evolved into an ongoing game to express warm-heartedness and love. Gradually, bartering resulted in a shop with shelves, fresh food, dry goods, daily necessities, drinks, and so on. It has formed a tiny supermarket, with everything for people in need, with the understanding they provide their own items free of charge in compensation. Others continue to disinfect, sterilize, and clean up for free. Everyone leads orderly lives, and there is no case of COVID-19 in this building. Bartering is the most primitive trading method, existing before the emergence of money, but in this situation it is not necessarily commercial exchange, but more about sharing truth, passing love, thanking others, taking the initiative to self-consciously express kindness and neighborly affection, and communicating spiritually. For example, a resident exchanges milk for cola, reminding everyone to pay attention to nutritional balance. During the pandemic, cola became a hard currency at the top of the food chain that could be exchanged for everything. In this situation, it is an exchange of love, which is priceless. In this era of so-called “moral decay,” during a serious pandemic, the basic compatibility of economic and social principles are demonstrated. There are debates in modern society debates between those who stress the importance of the economy and those who stress the importance of society, and the development of the market economy continues to challenge the basic social ethical and moral bottom line. This trend could have made people increasingly pessimistic and uncertain, but this time, a real situation and sincere sociological experiment during the pandemic in Shanghai has rekindled our confidence, not only in the development of the market economy but also in maintaining basic social ethics and morality. As long as we respect each human life and promote everyone’s interests and freedom, these practices will rekindle confidence. Individual autonomy is the most prominent principle in bioethics and underpins most ethical and legal deliberations (Ashby 2020). It is also the basis for the sustainable development of the market economy (Ebenstein 2014). Economics and ethics are not at odds. This is more conspicuous and important than ever. Despite all kinds of difficulties and problems, the ability to maintain basic social ethics is still alive and well in community practice, although sometimes it is dormant or blocked for a while. The opportunity to awaken social ethics at any time has always existed. This is the awakening and return of human nature, the rise and reshaping of morality, the renunciation of a narrow utilitarianism, and the affirmation of the dignity of human nature and the power of affective sensibility. Social ethics and morality are not antagonistic with economic development. Social ethics and morality are the basis and premise of the emergence of the economic man and the social man and the foundation and guarantee of the sustainable development of the market economy. They can complement each other! Declarations Conflicts of Interest The authors declare no personal or financial conflicts of interest of relevance to this topic. 1 https://m.toutiao.com/is/FqW2BJc/. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Ashby MA No man (or woman) is an island? Journal of Bioethical Inquiry 2020 17 3 315 317 10.1007/s11673-020-10062-3 33044716 Ebenstein A Friedrich Hayek: A biography 2014 Louisiana, Saint Martinville St. Martin’s Press
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==== Front Diabetologie Die Diabetologie 2731-7447 2731-7455 Springer Medizin Heidelberg 983 10.1007/s11428-022-00983-5 Journal Club Auswirkungen einer verringerten Routineversorgung bei Menschen mit Diabetes auf die nicht-Coronavirus-19(COVID-19)-assoziierte Sterblichkeit Associations between reductions in routine care delivery in people with diabetes and non-COVID-19-related mortalityHenn Amrei [email protected] grid.411339.d 0000 0000 8517 9062 Klinik und Poliklinik für Endokrinologie, Nephrologie, Rheumatologie, Universitätsklinikum Leipzig, Liebigstr. 20, 04103 Leipzig, Deutschland 12 12 2022 12 21 11 2022 © The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. ==== Body pmcOriginalpublikation Valabhji J, Barron E, Gorton T et al (2022) Associations between reductions in routine care delivery and non-COVID-19-related mortality in people with diabetes in England during the COVID-19 pandemic: a population-based parallel cohort study. Lancet Diabet Endocrinol. 10.1016/S2213-8587(22)00131-0 Hintergrund. Während der Pandemie mit Coronavirus 2019 (COVID-19-Pandemie) wurden die Sterblichkeitsraten in der Bevölkerung durch Regierungen und nationale Institute streng überwacht. Im Oktober 2021 warnte das „United Kingdom Government Office for Health Improvement and Disparities“ vor einem Anstieg nicht-COVID-19-assoziierter Todesfälle im Vergleich zu vor der Pandemie. Weiterführende Untersuchungen ergaben einen überproportionalen Anstieg nicht-COVID-19-assoziierter Todesfälle bei Patienten mit Diabetes mellitus. Gleichzeitig erfolgte eine Verringerung der Routineversorgung von Patienten mit Diabetes im Rahmen der Pandemie [1]. Bereits in früheren Arbeiten wurde der Zusammenhang zwischen der Routineversorgung von Menschen mit Diabetes und der Sterblichkeit aufgezeigt [2]. Ziel dieser Arbeit war es nun, den Zusammenhang zwischen den akuten Veränderungen in der Routineversorgung vor und nach Beginn der COVID-19-Pandemie und der nicht-COVID-19-assoziierten Sterblichkeit zu evaluieren. Methoden. Hier vorliegend ist eine bevölkerungsbasierte parallele Kohortenstudie. Um die Sterblichkeiten während und vor der Pandemie vergleichen zu können, wurden mittels des „National Diabetes Audit“ Patienten in die Indexkohorte eingeschlossen, die während der Coronapandemie 2019–2020 und 2020–2021 an jährlichen Kontrollen bezüglich des Diabetes mellitus teilgenommen hatten. Die Vergleichskohorte bestand aus Diabetespatienten mit Kontrolluntersuchungen vor Beginn der Pandemie in den Zeitspannen 2017–2018 und 2018–2019. Das National Institute for Health and Care Excellence (NICE) empfiehlt für Diabetespatienten jährlich 8 Untersuchungen. Die Patienten der Index- sowie der Vergleichskohorte wurden in 4 Gruppen je nach Inanspruchnahme der jährlichen Kontrollen in den unterschiedlichen Zeitspannen eingeteilt. Zusätzlich wurden als mögliche Einflussfaktoren der Diabetestyp (Typ 1, Typ 2 und andere), das Alter (5 verschiedene Alterskategorien), das Geschlecht (weiblich, männlich oder unbekannt), die ethnische Herkunft und auch sozioökonomische Faktoren erhoben. Verglichen wurden anschließend die nicht-COVID-19-assoziierten Todesfälle der Diabetespatienten innerhalb einer spezifischen 15-wöchigen Zeitspanne im Jahr 2021 (Indexkohorte) mit den Gesamttodesfällen in der äquivalenten 15-wöchigen Zeitspanne im Jahr 2019 (Vergleichskohorte). In einem 2. Schritt wurde mit einbezogen, ob die Teilnahme an den 8 vorgesehenen jährlichen Untersuchungen Einfluss auf die nicht-COVID-19-assoziierten Todesfälle hatte, unter Berücksichtigung der zusätzlich gewählten Einflussfaktoren Diabetestyp, Alter, Geschlecht, ethnische Herkunft und sozioökonomische Faktoren. Schlussendlich wurden die Todesursachen in beiden Kohorten untersucht. Ergebnisse. Insgesamt 3.218.570 Patienten mit Diabetes mellitus wurden in die Indexkohorte der Zeitspannen 2019–2020 und 2020–2021 eingeschlossen, während in die Vergleichskohorte der Zeitspannen 2017–2018 und 2018–2019 insgesamt 2.973.645 Diabetespatienten eingeschlossen werden konnten. Die Charakteristiken der 2 parallelen Kohorten waren weitestgehend gleich. In der Indexkohorte zeigte sich im Pandemiejahr 2021 im vorgegebenen 15-wöchigen Zeitintervall eine Sterblichkeitsrate von 936/100.000, während diese in der Vergleichskohorte 2019 nur bei 912/100.000 lag. In beiden Kohorten zeigten sich die höchsten Sterberaten bei den Patienten, die in keinem der beiden Jahre alle 8 Vorsorgeuntersuchungen durchführen ließen, eine mittlere Sterberate bei Patienten, die in nur 1 Jahr nicht alle Vorsorgeuntersuchungen wahrnahmen, und die geringste Sterberate bei Diabetespatienten, die alle Kontrolluntersuchungen erhielten. Während der Anteil der Diabetespatienten, die alle 8 Untersuchungen erhielten, in der Vergleichskohorte vor Beginn der Pandemie weitestgehend gleichbleibend war, zeigte sich in der Indexkohorte zu Beginn und während der COVID-19-Pandemie der Anteil derer, die alle 8 Kontrollen durchführen ließen, im Jahr 2020–2021 um 44,8 % geringer als im Jahr 2019–2020. Bei der genaueren Untersuchung der Todesursachen zeigten sich höhere Todesfälle bei Diabetespatienten im Jahr 2021 im Vergleich zu 2019 unspezifisch über alle Todesursachen hinweg (z. B. kardiovaskuläre Erkrankungen, Krebsleiden oder pulmonale Erkrankungen). Kommentar Die vorliegende Studie zeigte in einem definierten Zeitraum von 15 Wochen eine Zunahme nicht-COVID-19-assoziierter Todesfälle von Diabetespatienten im Jahr 2021 im Vergleich zu einer Kontrollkohorte vor Beginn der Pandemie 2019. Gleichzeitig war diese höhere nicht-COVID-19-assoziierte Sterblichkeit 2021 mit einer Verminderung des Anteils der Patienten vergesellschaftet, die die empfohlenen 8 Vorsorgeuntersuchungen wahrnahmen. Andere signifikante Unterschiede zwischen den beiden Kohorten konnten nicht identifiziert werden. Interessant an dieser Studie ist, dass sie den indirekten Effekt der COVID-19-Pandemie auf Patienten mit Diabetes mellitus aufzeigt. Sie zeigt zudem kurzfristige Effekte einer abrupten Verringerung der Vorsorgeuntersuchungen an. Sie kann dabei nicht differenzieren, ob die Verminderung der Vorsorgeuntersuchungen aufgrund fehlender Termine zustande kam oder ob die Patienten aus diversen Gründen, wie der Angst vor Infektionen, den Kontrollen selbstständig fernblieben. Langfristige Auswirkungen der verminderten Kontrollen auf z. B. diabetesassoziierte Komplikationen können aufgrund dieser Auswertung ebenfalls nicht beleuchtet werden. Dies wäre in der Zukunft sicher eine interessante Fragestellung, um die langfristigen Effekte der COVID-19-Pandemie auf die Gesundheit von Diabetespatienten zu erfassen. Fazit für die Praxis Patienten mit Diabetes mellitus trugen während der Coronapandemie ein doppeltes Risiko, da sie einerseits ein erhöhtes Risiko schwerer Verläufe haben und zum anderen durch das Verschieben elektiver Untersuchungen einem zusätzlichen Risiko ausgesetzt waren. Eine regelmäßige Durchführung der Vorsorgeuntersuchungen ist für Diabetespatienten unabdingbar. Interessenkonflikt A. Henn gibt an, dass kein Interessenkonflikt besteht. QR-Code scannen & Beitrag online lesen ==== Refs Literatur 1. Carr MJ Wright AK Leelarathna L Impact of COVID-19 restrictions on diabetes health checks and prescribing for people with type 2 diabetes: a UK-wide cohort study involving 618 161 people in primary care BMJ Qual Saf 2021 10.1136/bmjqs-2021-013613 2. Holman N Knighton P O’Keefe J Completion of annual diabetes care processes and mortality: a cohort study using the National Diabetes Audit for England and Wales Diabetes Obes Metab 2021 23 2728 2740 10.1111/dom.14528 34405512
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==== Front J Bioeth Inq J Bioeth Inq Journal of Bioethical Inquiry 1176-7529 1872-4353 Springer Nature Singapore Singapore 36508142 10221 10.1007/s11673-022-10221-8 Letter to the Editor The Impossible Triangle Model of Pandemic Prevention and Control Chen Bingyuan [email protected] 1 Fang Laitan [email protected] 2 Liu Ronghui [email protected] 3 1 Library of Northeastern University at Qinhuangdao, Qinhuangdao, 066004 China 2 grid.449559.0 0000 0004 0545 6445 Nueva Ecija University of Science and Technology Graduate School, Gen. Tinio Street., 3100 Cabanatuan City, Philippines 3 grid.410726.6 0000 0004 1797 8419 School of Economic and Management, University of Chinese Academy of Sciences, Beijing, 100080 China 12 12 2022 12 12 6 2022 © Journal of Bioethical Inquiry Pty Ltd. 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. ==== Body pmc Dear Editor Every major pandemic has forcefully changed the direction of human history. It is the preference of nations and people to balance bioethics with the needs of the economy, society, politics, and so on, but without a way to simultaneously obtain these objectives in all areas, the balance of bioethics with other social demands needs to be weighed and balanced based on the most human basic ethics and morality. In more direct terms, it is difficult to balance the three sides of an impossible triangle: health protection, social consensus, and economic development. These choices have been decisive factors in human history. For example, in 541 AD, a plague swept through Rome, and when it reached the beautiful and prosperous city of Constantinople, the city suddenly fell into hell on earth. From then on, the Roman Empire was economically depressed, and its influence on European civilization also declined. In the 1420s, the Black Death swept through Europe, killing tens of millions and reducing the continent’s population by a third. In the view of many historians, the plague gave birth to modern Western civilization (McNeill 1998; Tian 2020). COVID-19 is the most serious pandemic in the past century. In the face of this big test of history and under international and domestic pressure, what decisions would governments all over the world make when facing the impossible triangle? Facing COVID-19, countries all over the world have undertaken various prevention and control measures in accordance with their specific conditions, including economic, social, cultural, religious, institutional, and national considerations. Because risks can come at any time, we need to maintain these measures for a long time (Ashby 2022). The Chinese government and people have based their response on principles that include the notion of a community with a shared future for humankind, the paramountcy of the people, the paramountcy of life, the need for fair and just decision-making, and the responsibilities of a major country. They have led by example with prudent decision-making and a firm belief in the success of their strategies, uniting all forces that could be united, coordinating international and domestic platforms, and making use of the global industrial supply chains. China launched a people’s war for COVID-19 pandemic prevention and control, which brought together the wisdom and strength of all humankind, and won a series of major battles, and achieved to a certain extent the “three victories” of health protection, social consensus, and economic development based on bioethics. China's approach to balancing the impossible triangle model may only be a special case and does not necessarily apply to other countries. There is no single best, suitable solution. We cannot universally politicize and ideologize anti-pandemic measures; they conform to the conditions and basic social ethics of particular nations. China does not comment on the pandemic prevention policies of other countries but only shares its own experience and provides timely help and guidance to countries in need. China’s anti-pandemic strategy is applicable to diseases with strong infectivity and lethality, especially in countries with a large population and insufficient medical resources. Adherence to the concepts of people first and life first aim to better balance the relationship between pandemic prevention and control and economic and social development. With this strategy, the pandemic can be contained quickly, saving lives and restoring economic production and daily life. Of course, a strong capacity for organizational mobilization and implementation are also needed. As the virus continues to mutate, becoming more and more infectious and less lethal, this balance strategy will become more and more difficult to implement, and there will be an increasing number of factors to be considered, such as balancing the choice between public health measures that decrease the threat to life and the risk of the people's economic income continuing to decrease and the risk of increasing unemployment. The medical and bioethical dilemma caused by increasing infection rates after the liberalization of public safety measures needs more time and practice to resolve. COVID-19, albeit mutated, remains with us, changing our lives, forcing us to face the impossible triangle. The cost is inevitable, and the outcome is different. Different pandemic prevention and control measures in different countries do not need to be evaluated ideologically. What is more important is to respect the choices made by countries according to their actual situation and characteristics. Different prevention and control measures have different application scenarios and preconditions; there is still a long way to go, and the merits and demerits are best assessed by future historians. Declarations Conflicts of Interest The authors declare no personal or financial conflicts of interest of relevance to this topic. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Ashby MA Liminality: The not-so-new normal? Journal of bioethical inquiry 2022 19 1 1 5 10.1007/s11673-022-10180-0 35384620 McNeill WH Plagues and Peoples 1998 New York Anchor Books Tian X A plague that changed the course of history China Journal of Literature and History 2020 3 108 109
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==== Front Pediatr Surg Int Pediatr Surg Int Pediatric Surgery International 0179-0358 1437-9813 Springer Berlin Heidelberg Berlin/Heidelberg 36507955 5319 10.1007/s00383-022-05319-4 Review Article The Global Initiative for Children’s Surgery: conception, gestation, and delivery Greenberg Sarah L. M. [email protected] 1210 Cockrell Hannah C. 12 Hyman Gabriella 34 Goodman Laura 5 Kaseje Neema 67 Oldham Keith T. 89 1 grid.240741.4 0000 0000 9026 4165 Division of Pediatric General and Thoracic Surgery, Seattle Children’s Hospital, 4800 Sand Point Way NE, Seattle, WA 98105 USA 2 grid.34477.33 0000000122986657 Department of Surgery, University of Washington, 1959 NE Pacific Street, Seattle, WA 98195 USA 3 grid.11951.3d 0000 0004 1937 1135 Department of Surgery, University of the Witwatersrand, 1 Jan Smuts Avenue, Braamfontein, Johannesburg, 2000 South Africa 4 grid.414240.7 0000 0004 0367 6954 Department of Surgery, Chris Hani Baragwanath Hospital, 26 Chris Hani Road, Johannesburg, 1864 South Africa 5 Department of Pediatric General and Thoracic Surgery, Children’s Health Orange County, 505 S. Main Street, Suite 225, Orange, CA 92868 USA 6 Surgical Systems Research Group, P.O. Box 4074, Kisumu, Kenya 7 grid.3575.4 0000000121633745 World Health Organization Emergency and Essential Surgical Care Program, 20 Avenue Appia, 1211 Geneva, Switzerland 8 Department of Pediatric Surgery, Children’s Wisconsin, 999 N. 92nd Street, Suite 320, Milwaukee, WI 53226 USA 9 grid.30760.32 0000 0001 2111 8460 Department of Surgery, The Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226 USA 10 grid.240741.4 0000 0000 9026 4165 Division of Pediatric General and Thoracic Surgery, Seattle Children’s Hospital, 4800 Sand Point Way NE, Seattle, WA 98122 USA 12 12 2022 2023 39 1 4823 11 2022 © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. More than two thirds of the global population lack access to safe, affordable surgical and anesthesia care. This inequity disproportionately affects children in low- and middle-income countries (LMIC). In 2016, a group of pediatric surgical care providers founded the Global Initiative for Children’s Surgery (GICS). Their goal was to assemble a multidisciplinary team of specialists and advocates to improve surgical care for children, with a particular emphasis on those in low-resource settings. This review details the history of GICS, the process of its inception, the values guiding its work, its past achievements, and its current initiatives. The experience of GICS may serve as an effective model for global collaboration on other areas of public and global health. Keywords Global surgery Pediatric surgery Public health Social justice Health equity issue-copyright-statement© Springer-Verlag GmbH Germany, part of Springer Nature 2023 ==== Body pmcThe Global Initiative for Children’s Surgery organization (GICS) was founded in 2016 to improve the surgical care of children around the world with a particular emphasis on children in low-resource settings. A review of the reasons for the formation of GICS, the process of its inception, the values driving its work, and its current endeavors and areas of focus are detailed below. The experience of GICS may provide an effective model of global collaboration for other neglected but critical areas of public and global health. Background: defining the need and historic context Surgical conditions comprise a large and rising proportion of the global burden of disease [1–3]. Despite this, most people around the world cannot access surgical care [2, 4]. Children are disproportionately affected, as they constitute up to half the population in the least developed regions of the world [5]. Lack of access to surgical care threatens the health and welfare of individuals and their families, as well as the economic development and security of the communities and countries in which they live [2, 6]. Access to surgery is challenging for many underserved populations, not only in low- and middle-income countries (LMICs), but also in high-income countries (HICs) [4, 7]. Access can be further compromised for populations in crisis, such as those experiencing war and other conflicts. Access can also be impeded for people facing displacement, such as refugees, or those encountering natural or man-made disasters. To frame the current picture in numeric terms, surgical conditions represent over 30% of the global disease burden [1]. Five billion people—over two thirds of the world’s population—lack access to safe, affordable surgical and anesthesia care when needed [4]. This inequity falls most heavily on the poor; 94% of the population in low- and lower-middle-income countries lack adequate access to surgical care [2]. Only three percent of children in low-income countries and eight percent of children in lower-middle-income countries have access to surgery, compared to 85% of children in high-income countries [7]. This means that many common and otherwise easily treatable conditions, such as appendicitis or long bone fractures, could result in death or a lifelong disability. In addition to the physical, psychological, and social impacts of inadequate access to surgery for patients with surgical disease and the families and communities who help care for them, the financial impact of reaching care can be immense. Financial catastrophe is experienced by one quarter of people who successfully access surgical care [2]. This does not include the financial impact to the many people who are unable to reach care. Aside from the health equity and social justice arguments as to why these numbers are unacceptable, there are also powerful economic drivers for prioritizing access to surgery. The opportunity cost to low- and middle-income countries is estimated to be $12.3 trillion by 2030 without accelerated investment in surgical scale-up [6]. These problems and their devastating effects have been known for a long time. In 1980, Dr. Halfdan Mahler, then Director General of the World Health Organization (WHO), stated that “the vast majority of the world’s population has no access whatsoever to skilled surgical care and little is being done to find a solution… I beg of you to give serious consideration to this most serious manifestation of social inequity in health care” [8]. Healthcare supporters, providers, and advocates of global surgery1 have worked tirelessly to change the state of surgical care delivery around the world. However, these calls for largescale improvement had historically been ignored, prompting global surgery to be dubbed the “neglected stepchild of global health” [9]. Around 2015, however, global surgery finally began to gain traction within the global health, development, and academic communities. The 3rd edition of Disease Control Priorities,2 published by the World Bank in 2015, included an entire volume on essential surgery for the first time [10]. Also in 2015, The Lancet prioritized surgery with the publication of the report from The Lancet Commission on Global Surgery, which showed that investing in surgical care is affordable, saves lives and promotes economic growth [2]. At the start of the first meeting of the Commission, then World Bank president Jim King called surgery an “indivisible, indispensable part of health care” [11]. Momentum continued to build as the World Bank started including surgical measures in the World Development Index and the global health and development community transitioned from the Millennium Development Goals to a set of Sustainable Development Goals, many of which are not attainable without access to surgery [12, 13]. Finally, the WHO formally recognized the essential role of surgery and trauma care as a part of Universal Health Coverage, starting with passage of resolution 68.15 at the 68th World Health Assembly [14]. With this growing support for access to surgical care for the global community, 2015 was called the “year of global surgery.” Development of the Global Initiative for Children’s Surgery: priorities, methods, and successes Despite these advances in the global prioritization of surgery, details specific to specialty care, including the surgical care of children, were not widely included in the burgeoning global surgery discussions. Recognizing that the surgical needs of children differ from those of adults, and that meeting those needs can require different human and material resources, a group of pediatric surgeons, anesthetists, and nurses from around the world came together to found the Global Initiative for Children’s Surgery in 2016 [15]. The goal in creating GICS was to assemble a multidisciplinary team of specialists and advocates from countries of all income levels that would work to improve surgical care for children around the world, with a particular emphasis on children in low-resource settings. Through this inclusive approach, and utilizing a series of international meetings, the organization, GICS, developed and articulated a vision in which every child has access to safe, quality, timely, affordable surgical, anesthesia, and nursing care. This vision was coupled with a mission to define and promote optimal resources for children’s surgery in low-resource regions of the world. GICS instituted a model where needs, priorities, and solutions were identified and driven by stakeholders in LMICs and supported by advocates in countries of all income levels. The key strategies and approaches used by GICS to progress towards its goals, as well as several of its more significant accomplishments, are highlighted in the paragraphs to follow. The first official meeting of GICS was held at the Royal College of Surgeons in London, United Kingdom in May of 2016. The goal of this meeting was to bring together surgeons from LMICs to evaluate the current state of surgical care for children in low-resource settings and to identify local and global priorities for care improvements. Prior to the meeting, a survey was sent to all invitees to initiate dialog regarding challenges and solutions to delivering surgical care to children. Fifty-two providers from 21 different countries, over half of which were LMICs, attended this inaugural 2-day event. During the gathering, themes from the survey were discussed, and working groups convened around the topics of infrastructure, service delivery, training, and research. It was determined that additional needs assessments were essential, that defining optimal resources and best practices for children’s surgical care were needed, and that the next meeting should center around connecting LMIC providers with professional associations and non-governmental organizations to begin to match global resources with identified needs. To continue this work after the first meeting, a transnational group of trainees came together to form the Core Operations and Logistics (COL) team. Driven by the enthusiasm, optimism, and passion of these trainees, the COL team would prove to be one of the most dynamic and influential aspects of GICS. The COL team assists with nearly every aspect of GICS, helping to support the administration, coordinate meetings, enhance training, and research programs, drive advocacy and policy initiatives, and provide a social media presence. Building on the work of the inaugural GICS gathering, a second meeting was held in Washington DC, United States in October of 2016, with a report-out immediately following at the gathering of the World Federation of Associations of Pediatric Surgeons (WOFAPS). The primary goal of this meeting was to develop an implementation plan for realizing GICS’ vision that every child has access to safe, quality, timely, affordable surgical, anesthesia, and nursing care. This second meeting was attended by 94 participants from 38 different countries. Representatives included individual healthcare providers, delegates of non-governmental and governmental organizations, academicians, policy makers, and hospital administrators. Specialty- and country-specific presentations were given to delineate barriers to surgical care delivery for children. Strategies to address these barriers were discussed amongst the multidisciplinary group of participants. Work commenced on developing an Optimal Resources for Children’s Surgery (OReCS) document to define human and material resources necessary to deliver optimal pediatric surgical care in LMICs and to create action plans for how to improve children’s surgery across all levels of the health system. This document built on the work of the American College of Surgeons’ Children’s Surgery Verification Quality Improvement Program but was modeled for more resource-variable environments. Between the second and third meetings, GICS became a non-profit organization with 501(c)(3) status in the United States, allowing it to build further collaborations and accept charitable donations. In addition, a formal Board of Directors, comprised of approximately 20 members from both LMICs and HICs, was created to help guide GICS. The third official meeting of GICS was held in Vellore, India in January of 2018. Goals of this meeting were implementation-based and included refining and finalizing the OReCS document; defining bellwether procedures for children; incorporating children’s surgery into National Surgical, Obstetric and Anesthesia Plans (NSOAPs)3; and building partnerships and collaborations with organizations. One hundred and ten participants from 33 countries attended the meeting, including delegates from a vast array of organizations such as the WHO; Médecins Sans Frontières; World Federation of Societies of Anesthesiologists; College of Surgeons of East, Central and Southern Africa (COSECSA); LifeBox; Smile Train; InterSurgeon; and Kids Operating Room (KidsOR). Following the meeting in Vellore, the OReCS document4 was completed, and an executive summary was published in the World Journal of Surgery [16]. The OReCS document, developed by GICS’ multidisciplinary collaboration of stakeholders from around the world, describes the resources necessary to care for children with surgical diseases in low-resource settings and provides strategies to incorporate the surgical care of children within national health plans. The document is comprised of two main parts. The first part consists of resource guidelines for different levels of care and types of facilities within a health system. The second delineates the supplies, equipment, and infrastructure necessary to deliver surgical care to children in low-resource environments. The fourth, and most recent in-person meeting of GICS was held in Johannesburg, South Africa in January of 2020. This was GICS’ largest meeting to date, convening 225 attendees from 44 different countries. The goal of this meeting was to delve further into implementation plans, with specific focus on strategies to best apply OReCS work. Additional discussions took place regarding the inclusion of children’s surgery within NSOAPs and incorporation of the surgical care of children within broader pediatric and global health initiatives. Further dialog centered around promoting the idea that the health and well-being of individuals, communities, populations, and economies cannot be realized without universal access to surgery, and without special consideration for the surgical needs of children beyond those of adults. As these four meetings progressed, working groups were created across numerous clinical specialties to further examine each area of focus. These working groups include anesthesia, cardiac surgery, congenital anomalies, critical care, dental and oral surgery, family support, adult general surgery, pediatric general surgery, neurosurgery, nursing, oncology, ophthalmology, orthopedic surgery, otolaryngology, plastic surgery, radiology, trauma surgery, and urology. Over time, additional committees were created in the realms of administration and finances; financing, advocacy, and policy; infrastructure, standards, and verification; partnerships and memorandum of understandings (MOUs); publications; research webinar; research, data, and quality improvement; training, human resources, and education; and website, networking, and communications. These working groups and committees provide periodic updates on their endeavors to the larger GICS community during the international gatherings, as well as via quarterly online membership meetings and newsletters. The working groups then use feedback generated from these events to guide their work and collaborations. To prioritize involvement of participants from LMICs, GICS worked with numerous donors and sponsors to provide scholarships for flights and housing for delegates from low-resource settings to attend these four in-person meetings. Professional organizations, non-governmental organizations and academic institutions served as the primary donors [17]. For the later meetings, participants had the option of submitting research posters to highlight investigative projects in surgical care delivery around the world. As not all knowledge is captured by research endeavors, all meetings had a series of presentations from participants to highlight successes and difficulties in care provision. Meeting content and focus was driven by participants and GICS members. Ideas were shared broadly to amplify discussion and magnify impact. Collaboration across countries, sectors and areas of expertise were promoted to foster ideas and promote sweeping change. As 2020 progressed and SARS-CoV-2 impacted the global community, GICS expanded its focus to combat this new threat. It rapidly developed a compendium of resources to support the global surgical community in fighting this disease.5 It held webinars on challenges and mitigation strategies and supported research aimed at improving surgical care delivery during the pandemic. Due to the dangers of travel and social gatherings, GICS held a 2-day webinar in February of 2022 in lieu of an in-person meeting. The hope is that GICS will be able to gather safely in person again in 2024 in the Philippines for its fifth official meeting. GICS today Today, despite the pandemic, GICS is flourishing. It is one of the largest multidisciplinary groups of advocates for the surgical care of children in low-resource settings in the world. It holds monthly board meetings and quarterly membership discussions. Its expansive number of working groups and committees have developed robust partnerships in the realms of clinical care delivery, research, training and education, and advocacy and policy work. Its COL group of trainees continues to function as an indispensable action arm and influential force for the organization. Although the full extent of the work of GICS and its members is beyond the scope of this review, several partnerships and areas of focus are discussed below to highlight its efforts. Multiple GICS members have been integral in working within existing policy structures to incorporate the surgical care of children within NSOAPs for their countries. For example, Dr. Lubna Samad, Senior Consultant and Pediatric Surgeon with Indus Hospital and Health Network in Pakistan, has been instrumental in working with Pakistan to become Asia’s first country to develop a national surgical plan. Dr. Samad and her team started with garnering ministerial support, performing situational and baseline assessments, and generating stakeholder engagement. Eventually, they were able to develop the National Vision for Surgical Care to align with the National Health Vision for Pakistan and develop a Universal Health Coverage Benefit Package pilot that specifically incorporates surgical care for children.6 Similarly, Professor Emmanuel Ameh, Commissioner for The Lancet Commission on Global Surgery, Professor and Consultant Pediatric Surgeon for the National Hospital, Abuja, Nigeria, and current GICS Chair, played a fundamental role in working with his country to develop a surgical plan that includes children. Through a series of strategic conversations and deliberations, using a method of inclusion and diversity, Nigeria developed a National Surgical, Obstetrics, Anaesthesia and Nursing Plan (NSOANP).7 This plan includes components for the surgical care of children, who comprise 62% of the total population in the country. In addition to policy, GICS is also very engaged in research efforts. GICS has developed a formal partnership with Pediatric Surgery International, generating a platform for publishing both policy documents and research articles within the global children’s surgical community. Pediatric Surgery International is part of the Health InterNetwork Access to Research Initiative (HINARI) program.8 HINARI is a collaboration that was established between the WHO and numerous publishers that allows countries with limited resources to gain free or low-cost access to a large collection of health literature. It includes over 8,500 journals and 7,000 electronic books. Through its various partnerships, GICS has published numerous papers on improving global surgical care for children.9 It has supported its members in research efforts by organizing research methodology workshops, providing study design assistance, creating research support and mentorship networks, and holding research webinars. GICS has partnered with Miss Naomi Wright in her leadership role of the Global PaedSurg Research Collaboration.10 She is a longstanding member of the COL team, Pediatric Surgery Registrar, and Wellcome Trust Clinical PhD Fellow at King's Centre for Global Health and Health Partnerships, King's College London. The Global PaedSurg Research Collaboration is the world’s largest prospective cohort study of gastrointestinal congenital anomalies. It aims to address the paucity of research on congenital anomalies in LMICs, identify factors affecting outcomes for children with congenital anomalies, and enhance research capacity amongst collaborators. The group recently published a landmark, multicenter, international prospective cohort study of children with gastrointestinal congenital anomalies, highlighting stark differences in mortality for children in low-income, middle-income, and high-income countries [18]. This work underscores the need for improved access to high quality neonatal surgical care in LMICs and will serve as a foundation for future efforts. GICS and its members are also very active in the realms of capacity building, training, and education. One example of this is through the work of its members with KidsOR, the world’s leading provider of access to safe surgery for children in LMICs. This pioneering organization installs operating theaters for children in low-resource settings and provides specialized training and education to strengthen local surgical capacity and health care systems. One such example of an educational endeavor is the Pan-African Paediatric Surgery E-Learning Program (PAPSEP). PAPSEP is Africa’s first comprehensive pediatric surgery e-learning educational repository. It aims to bolster knowledge of trainees in pediatric surgery in Africa using content created by African surgeons. It is a collaboration between KidsOR, the Institute of Global Surgery at the Royal College of Surgeons in Ireland (RCSI), COSECSA, and the West African College of Surgeons (WACS). The platform was launched in May of 2021 as part of the World Health Assembly. Additional recent educational efforts of GICS include dissemination of pertinent onco-surgical webinars through the oncology working group, creation of an online GICS grand rounds which launched in June of 2022 and collaboration with the WHO in updating the Surgical Care at the District Hospital Manual to include the surgical care of children. One final example of the work of GICS is the mentorship and subsequent capacity building it provides via the COL group. Trainee engagement with GICS’ diverse offerings and extensive network of peers and mentors provides unparalleled career development in the avenues of clinical care delivery, education, research, and advocacy. The global shortage of pediatric surgical care providers is large and disproportionately affects LMICs, where the median pediatric surgical workforce density is approximate 1% of that in HICs [19]. While interest in pursuing careers in pediatric surgical care exists, trainees—particularly in low-resource settings—often lack the mentorship, networks, opportunities, and financial support necessary to realize these career goals. By engaging and partnering with trainees in all aspects of its work, GICS has created a pipeline to help support development of well-rounded pediatric surgical care providers who are equipped to fulfill the roles of academician, clinician, and advocate. Through its model of sustainable advocacy and capacity building for pediatric surgical care, GICS provides trainees a platform for ongoing leadership development and collaboration. GICS, through the dedication and focus of its members, will continue to work until every child has access to safe, quality, timely and affordable surgical, anesthetic, and nursing care. It will do this through its general principles of transparency, inclusion, equity and the inherent worth of all people. Through scoping partnerships and collective action, it will continue to promote the basic human right to health for all children and families through facilitating universal access to surgical care. Author contributions All authors contributed to the study conception and design. Material preparation and data acquisition were performed by Dr. SG. The first draft of the manuscript was written by Dr. SG. Dr. HC, Dr. GH, Dr. LG, Dr. NK, and Dr. KO provided critical revisions of the manuscript. All authors read and approved the final manuscript. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Data availability statement All data used for this review are available in the public domain. Declarations Conflict of interest The authors have no financial conflict of interest to disclose. Sarah Greenberg and Laura Goodman are on the Board of Directors for GICS, and Keith Oldham is part of the Advisory Group for GICS. All authors have interacted with GICS via working groups and meetings. Keith Oldham was previously on the Editorial Board for Pediatric Surgery International. 1 Global surgery is a “field that aims to improve health and health equity for all who are affected by surgical conditions or have a need for surgical care, with a particular focus on underserved populations in countries of all income levels, as well as populations in crisis, such as those experiencing conflict, displacement and disaster” [20]. 2 Disease Control Priorities provides a periodic review of the most up-to-date evidence on cost-effective interventions to address the burden of disease in low-resource settings. 3 NSOAPs are pathways to incorporate surgery, obstetrics, and anesthesia within national health strategies. The term NSOAP was originally developed by The Lancet Commission on Global Surgery in its 2015 report entitled Global Surgery 2030: evidence and solutions for achieving health, welfare, and economic development. Methods for NSOAP formation were further delineated in The NSOAP Manual, which was created by UNITAR (United Nations Institute for Training and Research), Harvard’s PGSSC (Program in Global Surgery and Social Change) and the Global Surgery Foundation: https://www.globalsurgeryfoundation.org/nsoap-manual-program. 4 The Optimal Resources for Children’s Surgery (OReCS) document can be found on and downloaded from the GICS website at https://www.globalchildrenssurgery.org/optimal-resources/. 5 The COVID-19 resource page compiled by GICS can be found at https://www.globalchildrenssurgery.org/gics-network/covid-19-resources/. 6 Addition information about Pakistan’s National Vision for Surgical Care and its use of access to surgery as a modality to realize Universal Health Coverage can be found at https://www.globalsurgeryfoundation.org/pakistan-nsoap. 7 Nigeria’s National Surgical, Obstetric, Anaesthesia and Nursing Plan for 2019–2023 can be found at https://www.pgssc.org/_files/ugd/d9a674_1f7aa8161c954e2dbf23751213bc6f52.pdf. 8 Additional information regarding HINARI, including country eligibility, can be found at http://www.emro.who.int/information-resources/hinari/hinari.html. 9 A list of GICS publications can be found at https://www.globalchildrenssurgery.org/publications/. 10 Additional information about the Global PaedSurg Research Collaborative can be found at http://globalpaedsurg.com. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Shrime MG Bickler SW Alkire BC Mock C Global burden of surgical disease: an estimation from the provider perspective Lancet Global Heal 2015 3 S8 S9 10.1016/s2214-109x(14)70384-5 2. Meara JG Leather AJM Hagander L Global surgery 2030: evidence and solutions for achieving health, welfare, and economic development Lancet 2015 386 569 624 10.1016/s0140-6736(15)60160-x 25924834 3. Kassebaum NJ Arora M Barber RM Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015 Lancet 2016 388 1603 1658 10.1016/s0140-6736(16)31460-x 27733283 4. Alkire BC Raykar NP Shrime MG Global access to surgical care: a modelling study Lancet Global Heal 2015 3 e316 e323 10.1016/s2214-109x(15)70115-4 5. Greenberg SLM Ng-Kamstra JS Ameh EA An investment in knowledge: research in global pediatric surgery for the 21st century Semin Pediatr Surg 2016 25 51 60 10.1053/j.sempedsurg.2015.09.009 26831138 6. Verguet S Alkire BC Bickler SW Timing and cost of scaling up surgical services in low-income and middle-income countries from 2012 to 2030: a modelling study Lancet Global Heal 2015 3 S28 S37 10.1016/s2214-109x(15)70086-0 7. Mullapudi B Grabski D Ameh E Estimates of number of children and adolescents without access to surgical care B World Health Organ 2019 97 254 258 10.2471/blt.18.216028 8. Mahler (1980) Address by Dr. H. Mahler Director-general of the world health organization to the XXII biennial world congress of the international college of surgeons 9. Farmer PE Kim JY Surgery and global health: a view from beyond the OR World J Surg 2008 32 533 536 10.1007/s00268-008-9525-9 18311574 10. Disease Control Priorities, 3rd edition (DCP3). https://dcp-3.org/. Accessed 10 June 2022 11. Kim (2015) Jim Kim’s keynote address at the North American launch of the lancet commission on global surgery. The Lancet Commission on Global Surgery, YouTube. https://www.youtube.com/watch?v=bxhdFM7FL9s. Accessed 10 June 2022 12. Ng-Kamstra J Raykar N Meara JG Shrime MG Measuring surgical systems: a new paradigm for health systems strengthening 2016 New York World Bank Blogs 13. United Nations Sustainable Development Goals. https://sdgs.un.org. Accessed 11 June 2022 14. WHO (2015) Resolution WHA68.15. Strengthening emergency and essential surgical care and anaesthesia as a component of universal health coverage. https://apps.who.int/medicinedocs/documents/s21904en/s21904en.pdf. Accessed 1 Dec 2019 15. Farmer DL Audacious goals—2.0: the Global Initiative for Children’s Surgery J Pediatr Surg 2018 53 2 11 10.1016/j.jpedsurg.2017.10.007 16. Global Initiative for Children’s Surgery Global Initiative for Children’s Surgery: a model of global collaboration to advance the surgical care of children World J Surg 2019 43 1416 1425 10.1007/s00268-018-04887-8 30623232 17. Goodman LF Linden A Jensen G Funding flows for the Global Initiative for Children’s Surgery (GICS): lessons learned Ann Glob Health 2017 83 84 85 10.1016/j.aogh.2017.03.186 18. Wright NJ Leather AJM Ade-Ajayi N Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study Lancet Lond Engl 2021 398 325 339 10.1016/s0140-6736(21)00767-4 19. Bouchard ME Tian Y Justiniano J A critical threshold for global pediatric surgical workforce density Pediatr Surg Int 2021 37 1303 1309 10.1007/s00383-021-04939-6 34106329 20. Dare AJG, Gillies Caris E et al (2014) Global surgery: defining an emerging global health field. Lancet 2014:2245–2247
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==== Front Clin Exp Med Clin Exp Med Clinical and Experimental Medicine 1591-8890 1591-9528 Springer International Publishing Cham 36508048 964 10.1007/s10238-022-00964-4 Research Use of remdesivir for COVID-19 in patients with hematologic cancer https://orcid.org/0000-0002-8627-404X Martin-Onraët Alexandra [email protected] Barrientos-Flores Corazón [email protected] https://orcid.org/0000-0001-8564-8735 Vilar-Compte Diana [email protected] https://orcid.org/0000-0002-0212-9436 Pérez-Jimenez Carolina [email protected] https://orcid.org/0000-0002-8873-8573 Alatorre-Fernandez Pamela [email protected] grid.419167.c 0000 0004 1777 1207 Infectious Diseases Department, Instituto Nacional de Cancerología, Avenida San Fernando 22, Col Sección 16 Belisario Dominguez, 14080 Tlalpan CDMX, Mexico 12 12 2022 18 1 11 2022 23 11 2022 © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Purposes Patients with hematologic malignancies (HM) are among the individuals with highest risk of COVID-19 complications. We report the impact of remdesivir in patients with hematologic malignancies (HM) during Omicron in Mexico City. Methods All patients with HM and COVID-19 during December 2021–March 2022 were included. Socio-demographic and clinical data were collected. The primary outcome was COVID-19 progression. Variables associated with progression were analyzed. Results 115 patients were included. Median age was 50 years (IQR 35–63); 36% (N = 41) had at least one comorbidity. Fifty-two percent had non-Hodgkin lymphoma. Fifty patients (44%) had at least two doses of SARS-CoV-2 vaccine. COVID-19 was classified as mild (52.6%), moderate (9.7%), and severe/critical (28%). Twenty-eight patients (24%) received remdesivir. Nine patients received remdesivir at the ambulatory clinic (33%), the rest during hospital admission. Overall, 22(19%) patients progressed to severe/critical COVID-19; nine died due to COVID-19(8%). Hospital admission for non-COVID-19 causes was associated with higher odds of progression. Remdesivir did not reduce the risk of progression in hospitalized patients; none of the patients who received remdesivir in the ambulatory clinic progressed to severe COVID-19 or died. Conclusions Patients with HM and COVID-19 continue to present with high risk of complications. More prospective studies are needed to define the impact of antivirals in this high-risk group, including the best duration of treatment. Also, better vaccine coverage and access to treatment are mandatory. Supplementary Information The online version contains supplementary material available at 10.1007/s10238-022-00964-4. Keywords Remdesivir COVID-19 Hematologic malignancies Omicron ==== Body pmcIntroduction Since the rollout of the vaccines, hospitalizations and mortality associated with the COVID-19 Pandemic have decreased overall. The Omicron variant of SARS-CoV-2 appeared in November 2021 in South Africa, and soon after, spread globally replacing the Delta strain. The Omicron variant has been characterized by a higher transmissibility, but lower virulence than other strains, with a lower rate of hospitalization and mortality in the general population and vaccinated individuals, compared to Delta variant [1–3]. Mexico’s fourth wave was characterized by a rapid increase in cases in the last week of December 2021 [4] up to March 2022. The National Genomic surveillance reported the presence of Omicron (B.1.1.529, BA.1, BA.1.1, BA.2) in late December 2021, with an escalating predominance to > 90% of sequences in Mexico City by early January 2022 [5]. Despite a high proportion of vaccinated individuals, immunosuppression and advanced age are high-risk conditions for worse outcomes [6–8]. Patients with COVID-19 and cancer have a higher risk of adverse outcomes, with increased mortality compared to the general population [8]. They have a poor humoral response to vaccines compared to non-immunosuppressed individuals and frequent breakthrough infections, which is particularly the case of patients with hematologic malignancies (HM) [9–11]. Moreover, in Mexico, many different vaccines have been approved besides mRNA vaccines and AZ1222, including other viral vector vaccines (Sputnik-V and Cansino) and inactivated vaccines (Sinovac) [12], all with different efficacy rates. The clinical outcomes of the infection with the Omicron variant in immunosuppressed patients have been poorly reported [7, 13–16], and much more focused on the protection conferred by the mRNA vaccines [17–19]. Access to antivirals for SARS-CoV-2 has been scarce in Mexico, even for patients with cancer. In January 2022, with the surge of the fourth wave caused by Omicron, remdesivir was made available for a subset of patients at our Institution. We report the clinical characteristics and outcomes of a cohort of patients with HM during the Omicron wave and the impact of remdesivir use in these high-risk patients. Methods Setting Instituto Nacional de Cancerología (Incan) is a 133-bed tertiary care hospital located in Mexico City, that serves uninsured patients with cancer coming mostly from the central region of the country. During the Pandemic, INCan worked as a hybrid hospital and kept receiving patients for treatment and follow up of their cancer. However, an area of the hospital was reconverted for COVID-19 care, with a consultation for respiratory triage and COVID testing, and a ward for hospitalization and critical care of severe COVID-19 patients. During 2020 and 2021, there was no access to antivirals or monoclonal antibodies, and SARS-COV2 infected patients were only treated for severe disease to mitigate the inflammatory response. At the end of January 2022, remdesivir was available in the hospital for patients with active cancer and less than 7 days of symptoms. Procedures An algorithm was created to prioritize the highest risk patients for severe COVID-19, which included patients with active HM among others [20] (see Fig. 1, supplementary material). An ambulatory clinic was established to administer a three-day regimen of remdesivir for patients with mild COVID-19 and no criteria for hospitalization. If patients were hospitalized with mild COVID-19, due to other conditions (such as febrile neutropenia), or with severe COVID, they received remdesivir in the hospital. According to the protocol of our hospital, and based on the evidence reported [21], mild to moderate cases with no oxygen requirement received only three days of remdesivir. Patients with oxygen requirements received 5 days of treatment [22, 23]. Severity of COVID-19 was defined according to World Health Organization and National Institutes of health as mild (tested positive for SARS-CoV-2 with or without COVID-19 symptoms and absence of dyspnea or abnormal chest imaging), moderate (evidence of pneumonia on clinical assessment or chest imaging with saturation > 94%), severe (evidence of pneumonia on clinical assessment or chest imaging with saturation > 90%) and critical (acute respiratory distress syndrome, mechanical ventilation or shock) [21, 24]. Study participants For study purposes, we included all patients with an HM diagnosed with COVID-19 from December 1st, 2021, to March 31st, 2022. The diagnosis was based on a positive SARS-CoV-2 PCR or rapid antigen test in symptomatic patients with fever or respiratory symptoms. Asymptomatic positive patients to PCR screening prior to chemotherapy were also included. Information was collected from the electronic files, including socio-demographic data, days of symptoms, type of neoplasm, COVID-19 severity, vaccine status, treatment received, progression of COVID-19 and death. For remdesivir use, we describe the number of days of remdesivir administered, the setting (ambulatory vs. hospitalized) and time from initiation of symptoms. We defined COVID-19 progression as the change of patient's clinical status from mild/moderate to any category with oxygen requirements [21]. Statistical analysis We described data as simple proportions and median interquartile range (IQR) for qualitative and quantitative variables, respectively. The outcomes of interest were progression to a more severe clinical presentation, and death. We performed a univariate analysis of variables associated with progression and death and compared the risk of progression in patients who received remdesivir for 3 or 5 days. We used the Chi-square or Fisher exact test for qualitative variables, and Mann–Whitney test for quantitative variables, as appropriate. For analysis purpose, we excluded asymptomatic patients (detected through pre-chemotherapy screening) and critical patients (which were already progressed) from the univariate and multivariate analysis of outcomes. To compare progression proportions with or without the use of remdesivir, we excluded patients who received it after seven days of symptoms. To account for confounders, we performed a multivariate analysis using all variables with a p value < 0.2 in the univariate analysis, for both outcomes of progression and death. Results We included 115 patients. The characteristics of the cohort are presented in Table 1. Women represented 35% (N = 40) of the sample. Median age was 50 years (IQR 35–63); 35.7% (N = 41) had at least one comorbidity, mainly obesity, diabetes, and high blood pressure. Eleven patients (10%) were living with HIV, and the median CD4 count closest to COVID-19 was 294 cells/mm3. Nine patients (82%) were on antiretroviral (ARV) therapy with undetectable viral load. Two patients had recently been diagnosed with HIV and not on ARV. The main oncological diagnosis was non-Hodgkin lymphoma (N = 60, 52.2%), followed by acute lymphoblastic leukemia (N = 16, 14%), acute myeloid leukemia 12 (10.4%) and Hodgkin Lymphoma (N = 12, 10.4%). Ten patients had received a bone marrow transplant (8.7%). Almost 50% (N = 54) had received chemotherapy within the last month, and 30.4% (N = 35) had received rituximab (RTX) within the last six months. Only 16.5% (N = 19) were not on active treatment.Table 1 Clinical characteristics of the 115 participants, N = 115(%) Women 40 (34.8) Median age in years (IQR) 50 (35–63) At least one comorbidity 41 (35.7) Comorbidities Obesity 15 (13) Diabetes 18 (15.7) High blood pressure 13 (11.3) Chronic renal failure 4 (3.5) Previous cardiovascular events 3 (2.6) Patients living with HIV 11 (9.7) Type of hematologic malignancy: Acute myeloid leukemia 12 (10.4) Acute lymphoblastic leukemia 16 (14) Non-Hodgkin Lymphoma 60 (52.2) Hodgkin Lymphoma 12 (10.4) Myeloma/plasmacytoma 9 (7.8) Myelodysplastic syndrome 2 (1.7) Chronic lymphocytic leukemia 4 (3.5) Active neoplasia 96 (83.5) SARS COV2 vaccination status (n = 114) Not vaccinated 26 (22.8) One dose 15 (13.2) Two doses 50 (43.8) Three doses 23 (20.2) Bone marrow transplant 10 (8.7) Chemotherapy < 30 days 54 (47) Rituximab in the last six months 35 (30.4) Median of days since rituximab, (IQR) 46 (15–134) Regarding SARS-CoV-2 vaccination, 88 patients (77.2%) had been vaccinated with at least one dose; 44% (N = 50) had 2 doses and 20% (N = 23) had three doses. Of 83 patients who reported the type of vaccine, 32 (38.6%) received AZ1222, 22 (26.5%) BNT162b2 and 17 (20.5%) Sputnik-V. Twelve patients (14.5%) received other vaccines such as Cansino or Sinovac. The median days from the onset of symptoms to COVID-19 diagnosis was 3 (IQR 2–6) days. COVID-19 was classified as mild in 52.6% of cases, moderate in 9.7%, and severe or critical in 28%. Eleven patients (9.7%) were asymptomatic at the time of diagnosis. These patients were diagnosed due to screening prior to chemotherapy. In total, 53 (46%) patients required hospitalization at some point of the disease; 30 of them were related to COVID-19. The other 23 patients were hospitalized due to other causes, such as febrile neutropenia (N = 15) or activity of the HM. Of the 53 patients who required hospitalization, 44 were hospitalized at COVID-19 diagnosis, and the rest (9 patients) were hospitalized days later, due to COVID-19 progression (Table 2).Table 2 COVID-19 characteristics Median days from the onset of symptoms (n = 103) 3 (2–6) Initial COVID-19 classification (n = 114) Asymptomatic 11 (9.7) Mild 60 (52.6) Moderate 11 (9.7) Severe/critical 32 (28) Cause of hospital admission (n = 115) COVID-19 30 (26.1) Non-COVID-19 causesa 23 (20) Not admitted 62 (53.9) Treatment of COVID-19 Remdesivir 28 (24.4) Inhaled steroids 22 (19.1) Convalescent plasma 6 (5.2) Systemic steroids 35 (30.4) Baricitinib 6 (5.2) Progression to severe COVID19 22 (19.1) Invasive mechanical ventilation 7 (6.1) Death 11 (9.7) COVID-19-related death 9 (7.8) a15 patients hospitalized for febrile neutropenia Laboratory values at COVID-19 diagnosis were available for 43 patients. The median neutrophil count was 1.5 × 109/L, and the median lymphocyte count was 0.7 × 109/L. Patients who were hospitalized had significantly lower median neutrophil count (0.6 vs 2.450 × 109/L, p = 0.006) and median lymphocyte counts (0.3 vs 0.95 × 109/L, p < 0.001) at COVID-19 diagnosis, and differed in their hematological diagnosis (acute leukemias and non-Hodgkin lymphomas accounted for 84.5% of hospitalized patients vs. 77% of non-hospitalized patients, p = 0.009). Also, there were more patients with recently diagnosed, untreated hematological malignancies or with progression of their malignancy in the hospitalized group. There were no differences in the median neutrophil-to-lymphocyte ratio by hospital admission, COVID-19 progression, or death. Nine patients (7.8%) were diagnosed with COVID-19 more than 10 days after being admitted to the hospital (from 10 to 31 days after admission) which corresponds to 7.8% of the cohort. These were patients who had been admitted for workup of their hematologic diagnosis or febrile neutropenia; they were considered as nosocomial COVID-19. Regarding treatment, 28 patients (24.4%) received remdesivir. Information on the timing of remdesivir is missing from one patient. For the 27 individuals left, remdesivir was administered during the first seven days of symptoms in 24 patients (88.9%). Twelve patients (44.4%) were treated in the first three days of symptoms. Two patients were treated in days 8 and 9. One patient who had prolonged COVID-19 received remdesivir during a flare, at day 47. Two patients were asymptomatic, 14 had mild COVID-19, 6 were moderate, and 6 were severe. None of the critical patients received remdesivir. Nineteen patients received three days of remdesivir; seven patients received five days of treatment. One patient received only two days of treatment (3.7%); remdesivir was stopped by the attending physician after receiving the Cycle threshold results for his initial PCR which were > 34. Nine patients with mild COVID-19 received remdesivir at the ambulatory clinic (33.3%). The rest were treated while being hospitalized. Of the 53 patients who were hospitalized, the median of hospital stay was 8 days (IQR 5-19) for patients who received remdesivir vs. 15 days (IQR 6-31) for those who did not receive the antiviral (p = 0.3). Among patients who were hospitalized for non-COVID reasons, median days of hospitalization were 11.5 (IQR 7-19) for those who received remdesivir, compared to 26 days (IQR 9-33) for those who did not (p = 0.2). Twenty-two (19.1%) patients progressed to severe/critical COVID-19. None of the patients who received remdesivir in the ambulatory clinic progressed to severe COVID-19 or died. Overall, eleven patients died (9.7%), two due to acute leukemia, and nine died of COVID-19 (7.8%). The mortality rate in hospitalized patients was 16.9% (Table 2). In the univariate analysis, patients who progressed were older than those who did not progress (56 years-old vs. 48 years, p = 0.018). Other variables associated with progression were active neoplasia, prior use of rituximab, being hospitalized at the diagnosis of COVID-19, and the initial severity of COVID-19 infection. Being vaccinated with one, two or three doses was not associated with less progression (Table 3). None of the patients in remission progressed (p = 0.016). Neutrophil count or lymphocyte count at COVID-19 diagnosis was not associated with the outcomes. Interestingly, patients who were hospitalized for non-COVID causes progressed more than patients not hospitalized (p = 0.025).Table 3 Variables associated with COVID-19 progression* Progressed N = 21 (%) Did not progress N = 79 (%) P value Median age in years (IQR) 56 (52–64) 48 (31–60) 0.018 Men 13 (20.6) 50 (79.4) 0.907 Women 8 (21.6) 29 (78.4) At least one comorbidity 9 (25.7) 26 (74.3) 0.397 No comorbidities 12 (18.5) 53 (81.5) Two or more vaccine doses 12 (19.7) 49 (80.3) 0.868 Less than two vaccine doses 8 (21) 30 (79) Chemotherapy < 30 days 14 (29.2) 34 (70.8) 0.054 Chemotherapy > 30 days 7 (13.5) 45 (86.5) Time from rituximab to onset of symptoms, in days (IQR) 25 (6.5–64) 58 (20–160) 0.077 Neoplasia in remission 0 (0) 18 (100) 0.016 Active neoplasia 21 (25.6) 61 (74.4) Clinical stage at diagnosis Mild 5 (8.3) 55 (91.7)  < 0.001 Moderate 6 (54.6) 5 (45.4) Severe 10 (34.5) 19 (65.5) Rituximab 16 (32) 34 (68) 0.007 No rituximab 5 (10) 45 (90) Hospital admission at COVID-19 12 (35.3) 22 (74.7) 0.012 Diagnosis ambulatory at COVID-19 diagnosis 9 (13.6) 57 (86.4) Hospital admission for Non-COVID causes Yes 7 (41.2) 10 (58.8) 0.025 No 14 (16.9) 69 (83.1) Remdesivir 8 (30.8) 18 (69.2) 0.155 No remdesivir 13 (17.6) 61 (82.4) *Asymptomatic and critical cases are excluded Regarding remdesivir recipients, patients who received three days of remdesivir progressed less than patients who received 5 days (16% vs 57%, p = 0.057). Sixteen percent of the patients who received remdesivir on the first seven days of symptoms progressed, compared to 100% of patients who received it after seven days (p = 0.012). None of the patients who received ambulatory remdesivir progressed, compared to 32% of those who received it during hospitalization (p = 0.036) (Table 4).Table 4 Variables associated with progression in remdesivir recipients, n = 27 Progressed (%) Did not progress p Number of remdesivir doses, n = 26 3 3 (15.8) 16 (84.2) 0.057a 5 4 (57.1) 3 (42.9) Time from onset of symptoms to remdesivir administration 0–7 days 4 (16.7) 20 (83.3) 0.012a  > 7 days 3 (100) 0 (0) Ambulatory remdesivir Yes 0 9 (100) 0.036a No 7 (31.9) 11 (61.1) aFisher exact test In the multivariate analysis, after adjusting for confounders, there was no association between the use of remdesivir and progression. However, there was still an association of progression with hospital admission for non-COVID-19 causes (Table 5).Table 5 Multivariate analysis for variables associated with progressiona, n = 100 Progressed Did not progress P value aOR (95% CI) p value Age in years, median (IQR) 56 (52–64) 48 (31–60) 0.018 1.04 (0.99–1.08) 0.065 Chemotherapy < 30 days 14 (29.2) 34 (70.8) 0.054 1.93 (0.62–5.97) 0.255 Rituximab use 16 (32) 34 (68) 0.007 2.65 (0.70–10.02) 0.151 Remdesivir use 8 (30.8) 18 (69.2) 0.155 0.83 (0.24–2.89) 0.767 Hospital admission for non-COVID causes 7 (41.2) 10 (58.8) 0.025 4.77 (1.09–20.87) 0.038 aAsymptomatic and critical patients were excluded When we analyzed death as an outcome, only age and hospitalization were associated with higher odds of dying in the univariate analysis, but this was not found in the multivariate analysis. Discussion We describe a cohort of individuals with HM and COVID-19 during the BA.1 and BA.2 Omicron wave of COVID-19 in Mexico. Most patients were diagnosed early, with a median onset of symptoms of three days, and more than half initially classified as mild (56%). Despite that Omicron has been reported to be milder, almost 20% of this cohort of cancer patients progressed to more severe forms of disease and 8% died due to COVID-19. The mortality rate among hospitalized patients was 16%. So far, few reports have been published on the outcomes of Omicron in immunosuppressed patients. Publications have described cohorts of cancer with COVID-19 prior to Omicron. An Israeli study reported a mortality rate of 20% in hematologic patients, before the Delta wave [25]. At INCan, we reported a cohort of non-vaccinated patients with Cancer and COVID-19, with a mortality rate of 18% [26]. Regarding Omicron, Taenaka et al. reported an outbreak of 9 patients with HM in February 2022, with a mortality rate of 22% [13]. The OnCOVID European Study, a multisite European Registry of patients with cancer and COVID-19, compared the outcomes of Omicron to the “alpha-delta” variant phase and the pre-vaccination phase [14]. The case fatality rate at 28 days was 13% during Omicron, lower than the pre-vaccination phase (29%) and the alpha-delta phase (23.9%). However, after adjusting for vaccination, the mortality rate in unvaccinated patients during the Omicron phase was as high as the mortality reported during the pre-vaccination phase. The authors report an impact of vaccination in both alpha/delta and Omicron. However, most patients had solid tumors and there was only a small proportion of HM (only 63 patients during Omicron). Salmanton-García et al. recently reported the outcomes of 593 HM patients infected with Omicron from a multicenter Registry including mainly European Countries (EPICOVIDEHA) [15]. Their progression and mortality rates were like our findings (17% and 16% respectively). Older age, active malignancy and pre-existing pulmonary disease were associated with progression or death, as in our cohort. A higher lymphocyte count and the use of monoclonal antibodies were associated with a lower risk for mortality. They also reported a protective effect of 3 doses of the vaccine against progression to critical illness in hospitalized patients. Regarding vaccination, other reports have demonstrated protection of the vaccine in patients with HM. Piñana et al. reported the incidence of breakthrough infections in patients vaccinated with 2 doses of mainly mRNA vaccines from a prospective multicenter Spanish Registry of hematologic patients registered before Omicron [10]. They analyzed SARS-Cov2 antibodies titers and found lower levels in patients with breakthrough infections compared to patients without COVID-19. They also found more symptomatic disease, pneumonia, and hospitalization in individuals with titers less than 250 BAU/mL. In our cohort, 44% of patients were vaccinated with 2 doses, but we did not find an association of full vaccination status with better outcomes. This could be related to the fact that a higher proportion of our patients were vaccinated with non-mRNA vaccines, which have lower efficacy rates (only 26% received an mRNA vaccine). Also, a third of our patients were receiving rituximab, an anti-CD20 monoclonal antibody that has been associated with B cell depletion and poor vaccine response [27]. This B cell depletion can last up to 6 to 9 months after the end of the therapy, and many reports including hematologic and rheumatologic patients have shown reduced humoral response and less immunogenicity with the vaccines [28, 29]. Most of the studies report the efficacy using mRNA vaccines and the information with other vaccines is scarce. Rituximab has been reported to reduce antibody titers of inactivated vaccines (coronavac) as well [30]. Regarding SARS-CoV-2-targeted treatment options, few treatments have been approved for COVID-19. Recently, new antivirals have shown to reduce progression of COVID-19 [22, 31, 32]. Remdesivir administered for three days in the first 7 days of symptom onset in ambulatory patients showed an 87% reduction of the risk of hospitalization or death in patients with at least one risk factor for progression compared to placebo [22]. All patients from these trials were non-vaccinated individuals. Also, the proportion of immunosuppressed patients in these trials was low (less than 5% in all trials). In our series, all patients had cancer and different degrees of immunosuppression; half of them were vaccinated with at least 2 doses of COVID-19 vaccines. Most patients who received remdesivir did so as a 3-day regimen for mild COVID-19, and early, following the Pinetree trial results [22]. Despite having a mild COVID-19, only 9 patients were treated on ambulatory basis, because they had other criteria for hospital admission at COVID-19 diagnosis. None of the 9 patients treated with ambulatory remdesivir progressed or died, which suggests a favorable impact of early treatment. A recent article published by Rajme and colleagues found a 84% reduction of hospitalization or death in patients with high-risk factors treated with early ambulatory remdesivir, from a tertiary care center in Mexico City [16]. Almost all patients were immunosuppressed, but only 12% had a hematologic disorder. In their study, authors only included patients who received ambulatory remdesivir. They did not include patients with mild COVID-19 who required hospital admission due to other causes. We included in our study mild COVID-19 cases admitted to the hospital, and we found that being hospitalized at diagnosis, or for non-COVID reasons, was associated with progression of COVID-19. In these patients there was no association of remdesivir use with better outcomes after adjusting for other variables. With these findings, it is difficult to say that remdesivir in mild COVID-19 had a positive impact on progression in hospitalized patients with non-COVID admission criteria. One explanation for the lack of impact of remdesivir on progression in our cohort could be the duration of treatment in patients with prolonged shedding and poor capacity of neutralization [11, 19, 33, 34]. It is possible that immunosuppressed patients with mild COVID-19 could benefit from longer treatment with remdesivir, and further studies are needed to evaluate the best duration of treatment. Small reports have shown potential benefits of prolonged courses of remdesivir in these patients and an improved response with combination treatments of remdesivir and convalescent plasma [35, 36]. Our study has some limitations. It is a retrospective study from one center, and few patients had access to remdesivir (only 24% of our sample). A bigger sample of patients exposed to the antiviral will probably yield more valuable information. We did not measure viral load or Cycle thresholds routinely in our patients, to evaluate the viral dynamics with the use of remdesivir. This could help to understand the action of this antiviral in highly immunosuppressed patients such as the ones in this series and define the best duration of treatment in these patients. On the other hand, Incan is the most important oncologic referral center of the country and there is almost no literature published in middle income countries. In summary, we report a sample of hematologic patients with considerable morbi-mortality during the Omicron wave, early in 2022 in Mexico City. Only a quarter had access to an antiviral. Patients who received ambulatory remdesivir for three days did not progress to more severe COVID-19. However, in patients who were admitted to the hospital at COVID-19 diagnosis, remdesivir use was not associated with improved outcomes. These patients were more immunosuppressed than ambulatory patients, which is associated with poor outcomes. More prospective studies with larger samples are needed, and prolonged treatments should be considered in prospective trials. Finally, only two thirds of the cohort had a complete vaccination scheme, and there was no significant impact of the vaccine status in the outcomes. Although efficacy rates are lower, it is imperative to improve vaccine coverage in this group of patients. Also, better access to antivirals in these high-risk patients is mandatory. Supplementary Information Below is the link to the electronic supplementary material.Supplementary file1 (JPG 619 KB) Acknowledgements To all the patients and staff who have had to work hard during COVID-19 times. Author’s contributions AMO, DVC and CBF designed the study. CBF collected the data. AMO, CBF, DVC, CPJ and PAF analyzed and interpreted the data and integrated the manuscript. All authors read and approved the final manuscript. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Data availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Declarations Conflict of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Consent to participate Due to the retrospective and observational nature of the study, the INCan’s “Comité de Ética en Investigación” waived the written informed consent. Ethics approval The study was performed in line with the principles of the Declaration of Helsinki and approved by the Institutional Review Committee “Comité de Ética en Investigación” of the INCan, #INCAN/CI0234/2022. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Nyberg T Ferguson NM Nash SG Webster HH Flaxman S Andrews N Comparative analysis of the risks of hospitalisation and death associated with SARS-CoV-2 omicron (B.1.1.529) and delta (B.1.617.2) variants in England: a cohort study Lancet Lond Engl 2022 399 10332 1303 1312 10.1016/S0140-6736(22)00462-7 2. Shuai H Chan JFW Hu B Chai Y Yuen TTT Yin F Attenuated replication and pathogenicity of SARS-CoV-2 B11529 Omicron Nature 2022 603 7902 693 699 10.1038/s41586-022-04442-5 35062016 3. Zhao H Lu L Peng Z Chen LL Meng X Zhang C SARS-CoV-2 Omicron variant shows less efficient replication and fusion activity when compared with delta variant in TMPRSS2-expressed cells Emerg Microbes Infect 2022 11 1 277 283 10.1080/22221751.2021.2023329 34951565 4. John Hopkins University. Coronavirus resource center [Internet]. [cited 2022 Aug 31]. Available from: https://coronavirus.jhu.edu/region/mexico 5. CoViGen-Mex. Programa de Vigilancia Genómica del SARS-CoV-2 realizado por el CoViGen-Mex [Internet]. 2022. Available from: http://mexcov2.ibt.unam.mx:8080/COVID-TRACKER/open/reports/26%20de%20Enero%20del%202022.pdf 6. Kuderer NM Choueiri TK Shah DP Shyr Y Rubinstein SM Rivera DR Clinical impact of COVID-19 on patients with cancer (CCC19): a cohort study The Lancet 2020 395 10241 1907 1918 10.1016/S0140-6736(20)31187-9 7. Lee M Quinn R Pradhan K Fedorov K Levitz D Fromowitz A Impact of COVID-19 on case fatality rate of patients with cancer during the Omicron wave Cancer Cell 2022 40 4 343 345 10.1016/j.ccell.2022.02.012 35219358 8. Han S Zhuang Q Chiang J Tan SH Chua GWY Xie C Impact of cancer diagnoses on the outcomes of patients with COVID-19: a systematic review and meta-analysis BMJ Open 2022 12 2 e044661 10.1136/bmjopen-2020-044661 9. Schmidt AL Labaki C Hsu CY Bakouny Z Balanchivadze N Berg SA COVID-19 vaccination and breakthrough infections in patients with cancer Ann Oncol Off J Eur Soc Med Oncol 2022 33 3 340 346 10.1016/j.annonc.2021.12.006 10. Piñana JL López-Corral L Martino R Vazquez L Pérez A Martin-Martin G SARS-CoV-2 vaccine response and rate of breakthrough infection in patients with hematological disorders J Hematol OncolJ Hematol Oncol 2022 15 1 54 10.1186/s13045-022-01275-7 35526045 11. Zeng C Evans JP Reisinger S Woyach J Liscynesky C Boghdadly ZE Impaired neutralizing antibody response to COVID-19 mRNA vaccines in cancer patients MedRxiv Prepr Serv Health Sci. 2021 11 1 16 12. Secretaria de Salud. Información de la Vacuna [Internet]. [cited 2022 Aug 31]. Available from: https://vacunacovid.gob.mx/wordpress/informacion-de-la-vacuna/ 13. Taenaka R Obara T Kohno K Aoki K Ogawa R Infections with the SARS-CoV-2 Omicron variant show a similar outcome as infections with the previous variants in patients with hematologic malignancies Ann Hematol 2022 101 8 1877 1878 10.1007/s00277-022-04833-8 35391563 14. Pinato DJ Aguilar-Company J Ferrante D Hanbury G Bower M Salazar R Outcomes of the SARS-CoV-2 omicron (B.1.1.529) variant outbreak among vaccinated and unvaccinated patients with cancer in Europe: results from the retrospective, multicentre on Covid registry study Lancet Oncol 2022 23 7 865 875 10.1016/S1470-2045(22)00273-X 35660139 15. Blennow O Salmanton-García J Nowak P Itri F Van Doesum J López-García A Outcome of infection with omicron SARS-CoV-2 variant in patients with hematological malignancies: an EPICOVIDEHA survey report Am J Hematol 2022 97 8 E312 E317 10.1002/ajh.26626 35702878 16. Rajme-López S Martinez-Guerra BA Zalapa-Soto J Román-Montes CM Tamez-Torres KM González-Lara MF Early outpatient treatment with remdesivir in patients at high risk for severe COVID-19: a prospective cohort study Open Forum Infect Dis 2022 9 10 ofac502 10.1093/ofid/ofac502 36285176 17. Mair MJ Mitterer M Gattinger P Berger JM Trutschnig W Bathke AC Enhanced SARS-CoV-2 breakthrough infections in patients with hematologic and solid cancers due to Omicron Cancer Cell 2022 40 5 444 446 10.1016/j.ccell.2022.04.003 35429443 18. Zeng C Evans JP Chakravarthy K Qu P Reisinger S Song NJ COVID-19 mRNA booster vaccines elicit strong protection against SARS-CoV-2 Omicron variant in patients with cancer Cancer Cell 2022 40 2 117 119 10.1016/j.ccell.2021.12.014 34986328 19. Fendler A Shepherd STC Au L Wu M Harvey R Schmitt AM Omicron neutralising antibodies after third COVID-19 vaccine dose in patients with cancer Lancet Lond Engl 2022 399 10328 905 907 10.1016/S0140-6736(22)00147-7 20. National institutes of health. The COVID-19 treatment guidelines panel’s interim statement on patient prioritization for outpatient anti-SARS-CoV-2 therapies or preventive strategies when there are logistical or supply constraints [Internet]. [cited 2022 Aug 31]. Available from: https://www.covid19treatmentguidelines.nih.gov/ 21. National institutes of health. Coronavirus disease 2019 (COVID-19) treatment guidelines [Internet]. [cited 2022 Aug 31]. Available from: https://www.covid19treatmentguidelines.nih.gov/ 22. Gottlieb RL Vaca CE Paredes R Mera J Webb BJ Perez G Early remdesivir to prevent progression to severe COVID-19 in outpatients N Engl J Med 2022 386 4 305 315 10.1056/NEJMoa2116846 34937145 23. Goldman JD Lye DCB Hui DS Marks KM Bruno R Montejano R Remdesivir for 5 or 10 days in patients with severe COVID-19 N Engl J Med 2020 383 19 1827 1837 10.1056/NEJMoa2015301 32459919 24. World Health Organization. COVID-19 clinical management: living guidance. 2021 [cited 2022 Aug 31]. Available from: https://www.who.int/publications/i/item/WHO-2019-nCoV-clinical-2021-2. Accessed 25 Jan 2021. 25. Levy I Lavi A Zimran E Grisariu S Aumann S Itchaki G COVID-19 among patients with hematological malignancies: a national Israeli retrospective analysis with special emphasis on treatment and outcome Leuk Lymphoma 2021 62 14 3384 3393 10.1080/10428194.2021.1966782 34405767 26. De-la-Rosa-Martinez D Aranda-Audelo M Martin-Onraet A Islas-Muñoz B Perez-Jimenez C Alatorre-Fernandez P Clinical characteristics and outcomes in a cohort of oncologic patients with COVID-19 during the first year of the pandemic in Mexico Cancer Med 2022 11 8 1827 1836 10.1002/cam4.4582 35166033 27. Furlan A Forner G Cipriani L Vian E Rigoli R Gherlinzoni F COVID-19 in B cell-depleted patients after rituximab: a diagnostic and therapeutic challenge Front Immunol 2021 12 763412 10.3389/fimmu.2021.763412 34804051 28. Bacova B Kohutova Z Zubata I Gaherova L Kucera P Heizer T Cellular and humoral immune response to SARS-CoV-2 mRNA vaccines in patients treated with either Ibrutinib or Rituximab Clin Exp Med 2022 10.1007/s10238-022-00809-0 29. Furer V Eviatar T Zisman D Peleg H Paran D Levartovsky D Immunogenicity and safety of the BNT162b2 mRNA COVID-19 vaccine in adult patients with autoimmune inflammatory rheumatic diseases and in the general population: a multicentre study Ann Rheum Dis 2021 80 10 1330 1338 10.1136/annrheumdis-2021-220647 34127481 30. Seyahi E Bakhdiyarli G Oztas M Kuskucu MA Tok Y Sut N Antibody response to inactivated COVID-19 vaccine (CoronaVac) in immune-mediated diseases: a controlled study among hospital workers and elderly Rheumatol Int 2021 41 8 1429 1440 10.1007/s00296-021-04910-7 34109466 31. Jayk Bernal A, Gomes da Silva MM, Musungaie DB, Kovalchuk E, Gonzalez A, Delos Reyes V, et al. Molnupiravir for oral treatment of COVID-19 in nonhospitalized patients. N Engl J Med 2022;386(6):509–20 10.1056/NEJMoa2116044. 32. Hammond J Leister-Tebbe H Gardner A Abreu P Bao W Wisemandle W Oral nirmatrelvir for high-risk, nonhospitalized adults with COVID-19 N Engl J Med 2022 386 15 1397 1408 10.1056/NEJMoa2118542 35172054 33. Altamirano-Molina M Pacheco-Modesto I Amado-Tineo J Prolonged viral shedding of SARS-CoV-2 in patients with acute leukemia Hematol Transfus Cell Ther 2022 44 2 299 300 10.1016/j.htct.2021.11.017 35071991 34. Goubet AG Dubuisson A Geraud A Danlos FX Terrisse S Silva CAC Prolonged SARS-CoV-2 RNA virus shedding and lymphopenia are hallmarks of COVID-19 in cancer patients with poor prognosis Cell Death Differ 2021 28 12 3297 3315 10.1038/s41418-021-00817-9 34230615 35. Weinbergerová B Demel I Víšek B Válka J Čerňan M Jindra P Successful early use of anti-SARS-CoV-2 monoclonal neutralizing antibodies in SARS-CoV-2 infected hematological patients—a Czech multicenter experience Hematol Oncol 2022 40 2 280 286 10.1002/hon.2974 35120267 36. Furlan A Forner G Cipriani L Vian E Rigoli R Gherlinzoni F Dramatic response to convalescent hyperimmune plasma in association with an extended course of remdesivir in 4 B cell-depleted non-hodgkin lymphoma patients with SARS-Cov-2 pneumonia after rituximab therapy Clin Lymphoma Myeloma Leuk 2021 21 9 e731 e735 10.1016/j.clml.2021.05.013 34217677
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==== Front Med Klin Intensivmed Notfmed Med Klin Intensivmed Notfmed Medizinische Klinik, Intensivmedizin Und Notfallmedizin 2193-6218 2193-6226 Springer Medizin Heidelberg 36507960 973 10.1007/s00063-022-00973-x CME Interhospitaler Intensivtransport Interhospital critical care transportFeth Maximilian 1 Zeiner Carsten 2 Danziger Guy 2 Eimer Christine 3 Mang Sebastian 2 Kühn Stefan 1 Villalobos Nick 4 Muellenbach Ralf M. 5 Hörsch Sabrina I. 6 http://orcid.org/0000-0003-3620-0912 Lepper Philipp M. [email protected] 2 1 grid.415600.6 0000 0004 0592 9783 Klinik für Anästhesiologie, Intensivmedizin, Notfallmedizin und Schmerztherapie, Bundeswehrkrankenhaus Ulm, Ulm, Deutschland 2 grid.411937.9 Klinik für Innere Medizin V – Pneumologie, Allergologie und Intensivmedizin, Universitätsklinikum des Saarlandes, Kirrberger Str. 100, 66421 Homburg/Saar, Deutschland 3 grid.412468.d 0000 0004 0646 2097 Klinik für Anästhesiologie und Operative Intensivmedizin, Campus Kiel, Universitätsklinikum Schleswig-Holstein, Kiel, Deutschland 4 grid.416653.3 0000 0004 0450 5663 Dept. of Pneumology, Critical Care and Sleep Medicine, Brooke Army Medical Center, San Antonio, TX USA 5 grid.419824.2 0000 0004 0625 3279 Klinik für Anästhesiologie, Notfallmedizin, Schmerz- und Intensivmedizin, Klinikum Kassel, Kassel, Deutschland 6 grid.411937.9 Zentrale Notaufnahme und Klinik für Anästhesiologie, Schmerz- und Intensivmedizin, Universitätskliniken des Saarlandes, Homburg, Deutschland Wissenschaftliche Leitung Uwe Janssens, Eschweiler Michael Joannidis, Innsbruck Konstantin Mayer, Karlsruhe Guido Michels, Eschweiler 12 12 2022 111 12 7 2022 14 9 2022 20 9 2022 © The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Kritisch kranke Patienten, die spezialisierte diagnostische oder therapeutische Verfahren benötigen, jedoch in einem Krankenhaus ohne diesbezügliche Ausstattung versorgt werden, müssen unter Fortführung intensivmedizinischer Maßnahmen zu geeigneten Zentren transportiert werden. Solche Transporte sind herausfordernde Einsätze mit hohem Ressourcenbedarf und logistischem Aufwand, die durch ein spezialisiertes Team bewältigt werden müssen. Hierzu ist neben einem effizienten Crew Resource Management eine gute Planung des Einsatzes notwendig. Bei adäquater Vorbereitung sind solche Einsätze für den Patienten sicher und komplikationsarm durchführbar. Neben Routineintensivtransporten gibt es Sondereinsätze (z. B. isolationspflichtiger Patienten oder Patienten mit extrakorporaler Organunterstützung), die eine Anpassung des Teams oder des vorgehaltenen Materials erfordern. Dieser Beitrag beschreibt die Grundlagen des interhospitalen Intensivtransportes, seine Phasen und Sonderfälle. Critically ill patients in need of specialized diagnostic or therapeutic procedures, but are being cared for in a hospital without such equipment, have to be transferred to appropriate centers without discontinuation of current critical care (interhospital critical care transfer). These transfers are resource intensive, challenging, and require high logistical effort, which must be managed by a specialized and highly trained team, predeployment planning and efficient crew–resource management strategies. If planned adequately, interhospital critical care transfers can be performed safely without frequent adverse events. Beside routine interhospital critical care transfers, there are special missions (e.g., for patients in quarantine or supported by extracorporeal organ support) that might require adaption of the team composition or standard equipment. This article describes interhospital critical care transport missions including their different phases and special circumstances. Schlüsselwörter Intensivmedizin Rettungsdienst Patiententransport Rettungswagen Crew Ressource Management Keywords Critical care Emergency medical services Transportation of patients Ambulances Crew ressource management ==== Body pmcLernziele Nach Lektüre dieses Artikels …kennen Sie verschiedene Arten des Intensivtransports sowie deren Charakteristika; identifizieren Sie Herausforderungen bei Intensivtransporten; kennen Sie die verschiedenen Durchführungsphasen des Intensivtransports; verwenden Sie Algorithmen zur strukturierten Patientenübergabe. Hintergrund Die Versorgungsstruktur deutscher Kliniken hat sich in den letzten Jahrzehnten im Zuge der Spezialisierung und Zentrumsbildung deutlich gewandelt. Dies hat Auswirkungen auf die Versorgung kritisch kranker Patienten. Während die meisten Krankenhäuser eine Intensivstation zur Versorgung dieser Patienten vorhalten, sind spezielle Diagnostik- und Therapieverfahren nur in gewissen Zentren verfügbar. Folglich müssen bestimmte Patienten ohne Unterbrechung der erforderlichen intensivmedizinischen Therapie zeitgerecht zwischen Krankenhäusern transportiert werden können. Die Anzahl solcher Intensivtransporte in Deutschland nimmt seit Jahren kontinuierlich zu. Dieser Artikel stellt verschiedene Phasen eines Intensivtransports dar und nimmt Stellung zu Spezialtransporten. Fallbeispiel An einem Samstag wird der diensthabende Intensivmediziner eines Maximalversorgers von einer peripheren Klinik kontaktiert. Ein 50-jähriger vorgesunder, allerdings adipöser Mann wird dort bereits seit 5 Tagen aufgrund eines „acute respiratory distress syndrome“ (ARDS) unklarer Genese intensivmedizinisch behandelt. Trotz maximaler Invasivität der Beatmung sowie Eskalation der antiinfektiven Therapie (AIT) verschlechtert sich der Gasaustausch kontinuierlich, mittlerweile befindet sich der Patient im Mehrorganversagen (Lunge, Kreislauf, Niere). In Zusammenschau aller Faktoren wird die Entscheidung getroffen, den Patienten ggfs. nach Initiierung einer extrakorporalen Membranoxygenierung (ECMO) zur weiteren Therapie in das Klinikum der Maximalversorgung zu übernehmen und den Transport somit als ECMO-Team durchzuführen. Als Mitglied des ECMO-Teams telefonieren Sie mit dem diensthabenden Kollegen der peripheren Klinik und erhalten neben o. g. Anamnese folgende Eckdaten: Patient intubiert/beatmet (inspiratorische Sauerstofffraktion [FiO2] 1,0; positiver endexspiratorischer Druck [PEEP] 12 mbar; Oxygenierungsindex [OI] 70 mm Hg), Richmond Agitation Sedation Scale [RASS] +2 trotz medikamentöser 4‑fach-Kombination sowie vasopressorenpflichtige Kreislaufinstabilität (Noradrenalin 0,7 µg/kg/min). Hiernach machen Sie sich auf den Weg in das etwa 40 km entfernte Krankenhaus. Bei Ankunft dort scheinen sich die Informationen zunächst zu bestätigen. Im Rahmen der ersten eigenen körperlichen Untersuchung vor Übernahme fällt ihnen ein deutlich abgeschwächtes Atemgeräusch auf der rechten Seite auf, sodass sich eine Thoraxsonographie anschließt, die wiederum einen großen, punktionsbedürftigen Pleuraerguss zur Darstellung bringt. Im Teamkonsens beschließen Sie diesen zunächst zu entlasten, da aufgrund des ausgedehnten Befunds mit einer deutlichen Verbesserung der Beatmungssituation zu rechnen und somit eine ECMO-Anlage zu vermeiden ist. Da der diensthabende Kollege der Quellklinik ungeübt in einer solchen Punktion ist, übernehmen Sie diesen invasiven Eingriff. Nach problem- und komplikationsloser Punktion können 2000 ml milchig-trüber Pleuraerguss entlastet werden und nach kurzem Recruitment verbessert sich die pulmonale Situation deutlich. Im Rahmen der Ursachenforschung aspirieren Sie alle Schenkel des einliegenden zentralen Venenkatheters (ZVK) und bemerken, dass diese nicht mehr aspirierbar sind. Eine Point-of-care-Analyse des Pleurapunktats zeigt hohe Glukosewerte, sodass sich der Verdacht einer pleuralen Fehllage des ZVK und eines konsekutiven iatrogenen Pleuraergusses (Propofol, parenterale Ernährung, Vasopressoren) ergibt bzw. erhärtet. Letztlich legen Sie daher kontralateral einen neuen ZVK. Hiernach ist der Patient problemlos zu sedieren und die Vasopressorenlast kann halbiert werden. Aufgrund der medizinischen Maßnahmen lassen Sie noch vor Beginn des Transports eine Röntgenuntersuchung des Thorax durchführen, die eine korrekte Platzierung der neuen Katheters bestätigt und Komplikationen ausschließt. Nach insgesamt 3 h vor Ort treten Sie nun gemeinsam mit dem Patienten den Heimweg an, Transport sowie die Umlagerungen verlaufen ohne nennenswerte Komplikationen. Grundlagen des Intensivtransports Grundsätzlich werden Primäreinsätze (Einsätze zur Erstversorgung von Notfällen) von Sekundäreinsätzen als Einsatz zum Transport von Patienten unter kompetenter Betreuung und Erhalt sowie Überwachung von Vitalfunktionen zwischen Gesundheitseinrichtungen unterschieden [1]. Transporte kritisch kranker Patienten unter Fortführung der intensivmedizinischen Maßnahmen (Intensivtransport) sind daher als SekundärtransportSekundärtransport zu werten. Aufgrund der Ressourcenintensivität werden Intensivtransporte als eigenes Element des Rettungsdiensts geführt und mit speziellen Fahrzeugen, sog. Intensivtransportwagen (ITW), oder luftgebunden mit Intensivtransporthubschraubern (ITH) durchgeführt ([2, 3]; Abb. 1). Intensivtransporte können je nach Zustand des Patienten und Transportindikation in verschiedene Dringlichkeitsstufen (elektive/dringliche/Notfallverlegung) eingeteilt werden (Infobox 1). Aufgrund des hohen Aufkommens an planbaren Intensivtransportanfragen können ITW teilweise stark ausgelastet und gelegentlich ein notfallmäßiger Intensivtransport durch einen Rettungswagen (RTW) des Regelrettungsdiensts notwendig sein. Bei der Nutzung eines RTW werden begleitende Ärzte meist durch die Quellklinik abgestellt. In seltenen Fällen kann der Transport auch durch einen regulären Notarzt (Notarzteinsatzfahrzeug [NEF]/Rettungshubschrauber [RTH]) übernommen werden. Dies sollte jedoch weitgehend vermieden werden, um die notfallmedizinische Versorgung des entsprechenden Rettungsdienstbereichs nicht negativ zu beeinflussen. Um die Hochwertressource ITW/ITH logistisch sinnvoll, effizient und entsprechend der Dringlichkeit einsetzen zu können, werden Intensivtransporte meist zentral koordiniert [4]. Infobox 1 Indikationen zum Intensivtransport (Auswahl) Transport eines Patienten von einem Krankenhaus niedrigerer Versorgungsstufe zu einer spezialisierten Diagnostik/Therapie Rückverlegungen solcher Patienten nach erfolgter Diagnostik/Therapie Transporte in Rehabilitationseinrichtungen (z. B. Weaningkliniken, Neurofrührehabilitation). Transporte kritisch kranker Patienten aus dem Ausland in die Heimat (z. B. System zur medizinische Evakuierung [MedEvac] der Bundeswehr) Besatzung und Ausbildung Der deutsche Rettungsdienst ist mittels Landesrettungsdienstgesetzen föderal geregelt. Während diese Gesetze für die Notfallrettung klare Vorgaben beinhalten, ist die Regelung von Intensivtransporten bundeslandabhängig stark unterschiedlich [5]. Daraus entsteht eine heterogene Ausgangslage hinsichtlich der Personalqualifikation im Intensivtransport. Um diesem Problem zu begegnen, hat die Deutsche Interdisziplinäre Vereinigung für Intensiv- und Notfallmedizin (DIVI) Empfehlungen zum ärztlichen und nichtärztlichen Besetzungsstandard im Rahmen des Intensivtransports erarbeitet, die zwar fachgesellschaftlich akzeptiert, aber rechtlich nicht bindend sind. (Tab. 1). Darüber hinaus empfiehlt die DIVI die Absolvierung des 20-stündigen DIVI-Curriculums „Intensivtransportkurs“ für jegliches Personal im Intensivtransport. Qualifikation Notarzt 3 Jahre klinische Weiterbildung in einem Fachgebiet mit intensivmedizinischen Versorgungsaufgaben 6 Monate Tätigkeit auf einer Intensivstation Qualifikation als Notarzt gemäß Landesrecht Mindestens 1 Jahr Erfahrung im Notarztdienst 20-stündiger Kurs Intensivtransport gemäß dem DIVI-Curriculum „Intensivtransportkurs“ Notfallsanitäter Berufsbezeichnung Notfallsanitäter Mindestens 2 Jahre Tätigkeit im Rettungsdienst Mindestens 14-tätige Hospitation auf einer ICU 20-stündiger Kurs Intensivtransport gemäß dem DIVI-Curriculum „Intensivtransportkurs“ Gesundheits- und Krankenpfleger Berufsbezeichnung Gesundheits- und Krankenpfleger Mindestens 2 Jahre Tätigkeit auf einer ICU (min. 6 Betten) Mindestens 14-tätige Hospitation auf einem ITW 20-stündiger Kurs Intensivtransport gemäß dem DIVI-Curriculum „Intensivtransportkurs“ ICU Intensivstation, ITW Intensivtransportwagen Leider kommt es im Rahmen von Notfallverlegungen immer wieder vor, dass ärztliches Personal zur Transportbegleitung abgestellt wird, das die DIVI-Empfehlungen nicht erfüllt. Der Mangel an Ausbildung und Erfahrung kann hierbei zu einer Patientengefährdung führen und möglicherweise als sog. Übernahmeverschulden bei Eintreten von Patientenschäden juristische Folgen für den Arzt sowie den ITW-Betreiber nach sich ziehen. Daher sei an dieser Stelle sowohl an die ITW-Träger appelliert, nur adäquat ausgebildetes Personal einzusetzen, als auch an die durchführenden Kollegen, nur Transporte anzunehmen, zu denen sie sich selbst, z. B. gemäß der DIVI-Empfehlungen, befähigt sehen. Die Geräteausstattung eines ITW ist in der Regel unterschiedlich zu der eines RTW oder einer Klinik. Folglich ist eine Einweisung des ITW-Personals in die jeweiligen Geräte gemäß Medizinproduktegesetz (MPG) eine Grundvoraussetzung zur Teilnahme am ITW-Dienst. Dies gewährleistet in Kombination mit regelmäßigem Training eine rechtskonforme und patientensichere Anwendung der Geräte. Neben einer qualitativ hochwertigen Ausbildung ist eine gute Teamführung für den Erfolg solcher Transporte notwendig. Dazu gehören unter anderem eine klare Rollenverteilung, Team-Time-Outs und eine konsequente „closed loop communication“ [7]. Merke Eine hochwertige Ausbildung sowie Crew-Resource-Management-Maßnahmen tragen zu einem sicheren Transport bei. Durchführung des Intensivtransports Planung und Vorbereitung Nach Alarmierung des ITW erfolgt die Kontaktaufnahme mit der Quellklinik, um bereits im Vorfeld durch einen medizinischen Informationsaustausch einen Eindruck vom Patienten zu gewinnen und transportrelevante Besonderheiten zu erfragen (Infobox 2). Zusätzlich sollten hierbei Empfehlungen des ITW-/ITH-Notarztes (z. B. Sicherung des Atemwegs) zur Herstellung der Transportfähigkeit kommuniziert werden, um spätere Zeitverluste zu minimieren. Infobox 2 Inhalte eines Arzt-Arzt-Gesprächs zur Transportvorbereitung (Auswahl) Diagnose, Intensivverlauf und Verlegungsgrund Vorerkrankungen und Dauermedikation Aktueller Zustand des Patienten Aktuelle Therapie (inklusive Beatmungsmodalitäten) und Medikation (Dosierung, Applikationsform) Relevante radiologische, laborchemische und mikrobiologische Befunde Ansprechpartner in der Zielklinik inklusive Erreichbarkeit Weitere Besonderheiten (z. B. Sprachbarriere). Grundlegend ist es, im Rahmen dieser Transportanmeldung die Eignung des Transportmittels für den jeweiligen Patienten zu prüfen. Dies kann im Besonderen bei Patienten mit einer ausgeprägten Adipositas problematisch sein. Hier ist festzustellen, ob das Rettungsmittel über entsprechende Transportsysteme verfügt, die für das Patientengewicht zugelassen sind. Für den Fall, dass das beabsichtigte Transportmittel aufgrund des Patientengewichts nicht eingesetzt werden kann, werden bisweilen Schwerlast-ITW vorgehalten. Sollte ein luftgebundener Transport eines stark adipösen Patienten geplant sein, muss neben dem geringen Platzangebot in den meisten Luftrettungsmitteln auch das maximal zulässige Abfluggewicht des Luftrettungsmittels bedacht werden (gegebenenfalls empfiehlt sich vorab ein klärendes Gespräch mit dem Piloten). Vorgespräche im Rahmen eines Intensivtransportes sollten grundsätzlich als Arzt-Arzt-Gespräch und zur Vermeidung von Informationsverlusten idealerweise auf Grundlage einer Checkliste durchgeführt werden [8]. Auf Basis dieser Übergabe erfolgt ein Briefing des gesamten ITW-/ITH-Teams inklusive Rollen- und Aufgabenzuweisung. Anschließend sollte eine Kontaktaufnahme mit der Zielklinik erfolgen, um deren Aufnahmebereitschaft sicherzustellen. Während der Vorbereitung des Intensivtransports müssen logistische Aspekte, wie die Vorhaltung entsprechender Geräte inkl. Stromversorgung und Rückfallebene, notwendiger Medikamente und medizinischer Gase, unter Berücksichtigung der zu erwartenden Transportzeit bedacht werden. Die meisten ITW/ITH verfügen dabei über einen Transportrespirator, der zur differenzierten Beatmung beispielsweise von Patienten im schweren Lungenversagen in der Lage ist. Hier hat sich der Einsatz von Transportrespiratoren mit Turbinenbetrieb aufgrund der Unabhängigkeit von Druckluftsystemen als sinnvoll erwiesen. Wird ein Intensivtransport mit einem RTW durchgeführt, muss vor Transportbeginn geprüft werden, ob ein Austausch des Respirators notwendig und weitere für den Intensivtransport erforderliche Materialausstattung (z. B. Anzahl der Spritzenpumpen, Möglichkeit invasiver Blutdruckmessung) verfügbar ist [9]. Aufgrund der meist begrenzten Stromversorgung während des Transports kann der Austausch elektronischer Geräte (z. B. Wasserschloss statt elektronischer Thoraxdrainagesysteme) in Betracht gezogen werden. Falls zusätzliche Medizingeräte mitgenommen werden, muss auf eine vorschriftsmäßige Sicherung der Ladung geachtet werden. Eine Möglichkeit zur Absaugung sollte verfügbar sein. Von Seiten der Quellklinik sollte zur Transportvorbereitung auf eine Reduktion kontinuierlich verabreichter Medikamente (Spritzenpumpenanzahl) auf ein notwendiges Minimum und die patientennahe Markierung notwendiger Infusions- bzw. Messleitungen (z. B. am ZVK) und im Verlauf geachtet werden. Dies minimiert Dislokationsmöglichkeiten bei der Umlagerung und erleichtert die Verabreichung von Medikamenten während des Transports. Patientenübernahme Die Patientenübernahme findet in der Regel bettseitig auf der Intensivstation des abgebenden Krankenhauses statt. Sie beginnt mit einer strukturierten PatientenübergabePatientenübergabe durch das zuständige ärztliche und Pflegepersonal. Zur Vereinheitlichung der Übergabestruktur und Reduktion von Informationsverlusten sollten hierbei gängige Übergabeschemata (Tab. 2) Anwendung finden. Anschließend können möglicherweise aufgetretene Unklarheiten geklärt werden, bevor das übernehmende Team wesentliche Inhalte der Übergabe zusammenfasst. Außerhalb von Notfallsituationen (z. B. beobachteter Herz-Kreislauf-Stillstand) sollten während des Übergabegesprächs keine Maßnahmen am Patienten durchgeführt werden.ISOBAR-Schema AT-MIST-Schema „Identifikation“ Name, Geschlecht, Alter „Age“ Patientenalter, -name „Situation“ Leitsymptom, aktueller Patientenzustand „Time“ ICU-Aufnahme und -Dauer „Observations“ Intensivverlauf, funktionsdiagnostisch, radiologisch, laborchemisch und mikrobiologisch relevante Befunde „Mechanism“ Aufnahmegrund und -mechanismus (notfallmäßige vs. geplante Aufnahme nach Operation/Intervention) „Background“ Vorerkrankungen, Medikation „Injury“ Leitsymptom „Assessment“ Vitalwerte, aktuelle Therapie „Symptoms/signs“ Aktuelle Symptome inklusive Schmerz, Vitalparameter „Recommendation“ Ergänzungen, Empfehlungen, Ansprechpartner Zielklinik „Treatment“ Aktuelle Therapie ICU Intensivstation Weiterhin sollte die Übergabe den Inhalt eventueller Vorsorgedokumente (z. B. Patientenverfügung) sowie eine mögliche Betreuungssituation erfassen. Auch wenn schwerwiegende Komplikationen während eines Intensivtransports selten sind, kann die Übergabe solcher Informationen bei Bedarf eine schnelle Entscheidung im Sinne des Patientenwillens unterstützen. Darüber hinaus sollte vor Transportbeginn bei betreuten Patienten das Transporteinverständnis des juristischen Vertreters überprüft werden. Im Anschluss an die Übergabe verschafft sich der begleitende Notarzt im Rahmen einer orientierenden Untersuchung einen Überblick über den aktuellen Zustand des Patienten. Diese Untersuchung sollte mindestens folgende Punkte umfassen:Kreislauf (Herzfrequenz, Blutdruck, Katecholamintherapie, aktueller EKG-Befund) Atmung (Spontanatmung ohne Unterstützung/nichtinvasive/invasive Beatmung inklusive Beatmungsparametern), aktuelle Blutgasanalyse und Atemwegszugang (Art, Größe, Fixierung, Lage) Vigilanz, Neurologie, Schmerz (Glasgow Coma Scale [GCS], RASS-Score, Pupillenkontrolle, periphere Durchblutung, Motorik und Sensibilität [pDMS]) Gefäßzugänge, Drainagenlage, Verbände/Schienen. Der Patient sollte vor Transportbeginn bestmöglich stabilisiert sein, um einen sicheren Transport zu ermöglichen. Ergibt sich aus der Untersuchung die Notwendigkeit zur Anpassung der aktuellen Therapie (z. B. der Beatmung), sollte dies idealerweise vor Transportbeginn inklusive Erfolgskontrolle (z. B. BGA) durchgeführt werden. Besteht die Möglichkeit, dass während des Transports die Gabe von Blutprodukten nötig werden könnte, sollte vor Verlassen der Quellklinik durch den ITW/ITH-Notarzt ein Bedside-Test durchgeführt werden. Merke Vor Transportbeginn ist der Patient bestmöglich zu stabilisieren, um Komplikationen während des Transports vorzubeugen. Im Anschluss an diese Untersuchung erfolgt eine schrittweise Umstellung der laufenden intensivmedizinischen Maßnahmen von den Geräten der Intensivstation auf die Transportgeräte. Nach Meinung der Autoren hat sich hierbei folgende Reihenfolge bewährt: Monitoring → Spritzenpumpen → Beatmungsgerät. Sollte keine invasive Blutdruckmessung etabliert sein, ist das Intervall der nichtinvasiven Blutdruckmessung (NIBP) an den Patientenzustand anzupassen (z. B. 1–5 min). Bei Übernahme der laufenden Medikation mittels Spritzenpumpe ist obligat auf das Mischungsverhältnis der jeweiligen Medikamente zu achten. Bisweilen gibt es zwischen Kliniken und Rettungsdiensten Unterschiede in den Verdünnungsverhältnissen kontinuierlich verabreichter Medikamente. Um fehlerhafte Applikationen zu vermeiden, kann eine Umstellung auf die dem Team bekannten Medikamentenmischungen sinnvoll sein. Während mancher Transporte kann eine Antibiotikagabe notwendig werden. Antibiotika werden im Intensivtransport standardmäßig meist nicht vorgehalten. Häufig kann jedoch eine Absprache mit der Quellklinik getroffen und von dort das entsprechende Medikament mitgeführt werden. Beim Wechsel auf den Transportrespirator ist darauf zu achten, bei einer Beatmung mit hohem PEEP einen PEEP-Verlust und damit mögliche Lungenschäden sowie akute Oxygenierungsprobleme zu vermeiden (z. B. durch Klemmen des Tubus). Das Ausmaß der Therapieänderungen sollte sich auf ein notwendiges Minimum beschränken. Dennoch können beispielsweise Anpassungen der Medikamente zur Analgesie und Stressreduktion während des Transports (z. B. vertiefte Sedierung eines beatmeten Patienten) erforderlich sein. Nach Umstellung des Monitorings und der Therapiemaßnahmen auf die mobilen Geräte des ITW/ITH folgt die Umlagerung des Patienten auf die Transporttrage. Umlagerungen stellen aufgrund der Gefahr von Dislokation und Diskonnektion von Zugängen kritische Situationen dar. Dem muss dadurch Sorge getragen werden, dass zu diesem Zeitpunkt auf eine ausreichende Personalstärke, größtmögliche Sorgfalt und klare Anweisungen geachtet wird. Nach Umlagerung sollten umgehend die Zugänge auf Funktion sowie die freie Lage aller Leitungen und Kabel geprüft werden. Letztlich sollte vor Verlassen der Quellklinik die Vollständigkeit der Patientendokumentation (Arztbriefe, aktuelle laborchemische und mikrobiologische Befunde, Bildgebung, Versicherungskarte, Kontaktmöglichkeiten zu Angehörigen, Vorsorge‑/Betreuungsdokumente) sichergestellt werden. Eine Sichtung der Vorsorge‑/Betreuungsdokumente sollte erfolgen, um insbesondere bei kritischen Situationen während des Transports adäquat und gemäß etwaiger Verfügungen handeln zu können. Darüber hinaus sollte sich in der Praxis rückversichert werden, ob das Einverständnis der juristischen Stellvertretung (Betreuung/vorsorgebevollmächtige Person) für den Transport vorliegt. Merke Die Umlagerung eines Intensivpatienten stellt eine kritische Situation dar, die sorgfältig und mit ausreichendem Personal durchgeführt werden muss. Transportphase Nach Übernahme des Patienten wird dieser unter Fortführung des Monitorings und sämtlicher erforderlicher Intensivmaßnahmen in den ITW/ITH verbracht. Die notwendige Intensivtherapie (z. B. Analgosedierung, Katecholamintherapie) muss während des gesamten Transports fortgeführt werden. Zusätzlich sollten auch Maßnahmen zum Wärmeerhalt (z. B. Aufheizen der Fahrgastzelle, Wärmedecken) in Betracht gezogen werden. Grundsätzlich stellt der Transport eines Intensivpatienten außerhalb einer Intensivstation ein Risiko dar. Es können patientenbezogene von ausrüstungsbezogenen (z. B. Gerätefehlfunktion) und transportbezogenen Komplikationen (erhöhter Verbrauch medizinischer Gase/Medikamente bei verkehrsbedingter Transportverlängerung) unterschieden werden. Patientenbezogene Komplikationen während des Transports können dabei in gravierende (z. B. Herz-Kreislauf-Stillstand) und moderate Komplikationen (z. B. Notwendigkeit der Beatmungsanpassung bei mäßigem Abfall der peripheren Sauerstoffsättigung) unterteilt werden. Bezüglich dieser patientenbezogenen Komplikationen hat sich gezeigt, dass gravierende Zwischenfälle während des Transports im Vergleich zu moderaten Komplikationen selten und Intensivtransporte mit entsprechender Vorbereitung in der Regel sicher durchführbar sind [11, 12]. Nichtsdestotrotz muss sich das Team allzeit über mögliche Komplikationen im Klaren sein, um eine adäquate Therapie zügig zu initiieren. Bei Unsicherheiten z. B. im Rahmen von persistierenden Komplikationen nach Evaluation des Patienten und bestmöglicher Therapie sollte ggf. Kontakt mit der Quell- oder Zielklinik aufgenommen werden. Diese Reach-back-Funktion kann in komplexen Fällen eine wertvolle Hilfe sein, die im NEF-Dienst häufig nicht verfügbar ist. Merke Obwohl schwerwiegende Zwischenfälle während Intensivtransporten selten sind, muss kontinuierlich mit dem Auftreten von Komplikationen gerechnet werden. Standardmäßig befindet sich der Patient während des Transports in einer 30°-Oberkörperhochlagerung. Allerdings können patientenimmanente Faktoren (z. B. hämodynamische Situation) eine Modifikation notwendig machen. Lagerungshilfsmittel wie Schienen sind eher selten von Nöten. Während der gesamten Transportphase müssen Vitalparameter und die laufende Therapie kontinuierlich dokumentiert werden. Dies umfasst mindestens:Vitalparameter (Herzfrequenz [HF], Blutdruck [RR], periphere Sauerstoffsättigung [SpO2], GCS); Beatmungsparameter (Atemfrequenz [AF], Tidalvolumen [VT], Beatmungsdrücke, Verhältnis der Inspirations- zur Expirationszeit [I-E-Verhältnis], endtidaler Kohlendioxidpartialdruck [etCO2]); Flüssigkeits- und Medikamentenapplikation (Dosierungen, Laufraten); spezifische Dokumentation (z. B. intraaortale Ballonpumpe [IABP], ECMO). Meist wird zur Dokumentation eines Intensivtransports ein für den Intensivtransport angepasstes Protokoll (z. B. DIVI-Intensivtransportprotokoll) genutzt, das auch die Dokumentation bestimmter, intensivtransportspezifischer Merkmale (Arzt-Arzt-Gespräch) ermöglicht. Ziel der Dokumentation ist neben einer juristischen Absicherung vor allem eine Darstellung des medizinischen Verlaufs während des Transports. Patientenübergabe Die Übergabe des Patienten in der Zielklinik erfolgt analog zur Patientenübernahme und sollte im Patientenzimmer unter Anwesenheit des zuständigen ärztlichen und pflegerischen Personals stattfinden. Auch hier ist auf eine strukturierte Übergabe sowie eine schrittweise Umstellung von Transport- auf Klinikgeräte und eine sorgfältige Umlagerung des Patienten zu achten. Spezialtransporte Patienten mit extrakorporalen Organersatzverfahren Extrakorporale Organunterstützungen (z. B. ECMO) sind Bestandteile der modernen Intensivtherapie, die jedoch meist nur an ausgewählten Kliniken verfügbar sind. Patienten solcher Kliniken können entweder vor Beginn der spezialisierten Therapie oder nach Etablierung des Verfahrens in der Quellklinik durch ein mobiles Spezialteam zur aufnehmenden Klinik transportiert werden ([13]; Abb. 2). Diese Verfahren sind komplex und bedürfen Erfahrung mit dem entsprechenden Krankheitsbild, der Technik im Allgemeinen sowie dem jeweiligen Gerät im Speziellen. Entsprechend kann für Personal, das nicht regelmäßig mit diesen Verfahren arbeitet, keine Routine vorausgesetzt werden. Da dies auf einen Großteil der ITW-Notärzte und des Rettungsfachpersonals zutrifft, sollte ein solcher Transport durch einen mit diesem Verfahren vertrauten Spezialisten begleitet werden. Eine gesetzliche Regelung für die personelle Besetzung eines solchen Spezialtransportes besteht derzeit nicht. Es muss jedoch bedacht werden, dass ein Notarzt, der ein solches Verfahren ohne eingehende Kenntnisse übernimmt, im Schadensfall unter Umständen im Sinne eines Übernahmeverschuldens haftbar gemacht werden könnte. Ein grundsätzliches Problem bei dem Transport von Patienten mit solchen Verfahren war die Fixierung der Geräte. Inzwischen sind hierfür jedoch kommerzielle Halterungen verfügbar, die einen sicheren Transport ermöglichen. Fahrzeuge, die mit diesen Halterungen ausgestattet sind, sollten bei solchen Transporten bevorzugt werden. Wie Einsätze zum Intensivtransport von Patienten mit Organersatzverfahren sind auch Transporte neonatologischer Patienten komplex und ressourcenintensiv (z. B. Notwendigkeit eines Transportinkubators). Diese Einsätze erfordern neben Detailwissen mit diesem speziellen Patientengut auch Erfahrung im Umgang mit dem Transportinkubator. Daher sollten sie auch durch entsprechendes Fachpersonal begleitet werden. Transport isolationspflichtiger Patienten Infektionen und Isolationsmaßnahmen gehören zum Alltag jeder Intensivstation. Der Transport von Intensivpatienten mit erhöhtem Infektionsrisiko ist folglich ein häufiges Einsatzbild (z. B. während der Pandemie durch die Coronaviruserkrankung 2019 [COVID-19]) und muss neben der Sicherheit des Patienten (z. B. bei patientenimmanenter Präexposition für Infektionen) auch die des begleitenden Personals sicherstellen. Gemäß der S1-Leitlinie „Hygienemaßnahmen beim Patiententransport“ können Patienten in einem solchen Transportszenario in folgende Kategorien eingeteilt werden [14]:A: kein Anhalt für eine Infektionserkrankung; B: diagnostizierte Infektion, die jedoch bei für den Transport üblichen Kontakten nicht übertragen wird (z. B. Tuberkulose exklusive offene Lungentuberkulose); C1: begründeter Verdacht auf oder gesicherte kontagiöse Infektionserkrankung (z. B. offene Lungentuberkulose) oder bekannte Infektion/Kolonisation durch einen multiresistenten Erreger (z. B. methicillinresistenter Staphylococcus aureus [MRSA]); C2: mindestens begründeter Verdacht einer Infektion mit einem besonders gefährlichen Erreger (z. B. Ebola, „severe acute respiratory syndrome coronavirus type 2“ [SARS-CoV-2]) D: Patienten, die in besonderem Maße infektionsgefährdet sind (z. B. manifeste AIDS-Erkrankung). Maßnahmen, die über die Standardhygiene hinausgehen, können in der Folge logistischer Natur sein (z. B. Trennung der Fahrerkabine von der Transportkabine) oder bei Exposition/Infektion von Personal oder Patient Therapiemaßnahmen bzw. Postexpositionsprophylaxen umfassen. Für den Transport dieser Patienten müssen der jeweilige Erreger und die notwendigen Hygienemaßnahmen bereits bei der Anmeldung des Intensivtransports angegeben werden. Gängige Bestandteile persönlicher Schutzausrüstung (PSA, z. B. Schutzbrillen, FFP2-/-3-Masken, Schutzkittel) werden in der Regel durch den ITW-Betreiber vorgehalten. Besondere PSA, wie etwa Schutzanzüge mit Eigenluftsystem, müssen meist erst beschafft werden und verlängern somit die Vorbereitungsphase. Während detaillierte Übergabegespräche in diesem Fall auch außerhalb des Patientenzimmers möglich sind, müssen die Übernahmeuntersuchung und Beurteilung der Transportfähigkeit des Patienten trotzdem am Patientenbett unter entsprechender PSA erfolgen. Obwohl solche Transporte durch die PSA eine deutlich höhere Belastung für das Transportteam darstellen, sind sie unter Beachtung entsprechender Schutzmaßnahmen sicher durchführbar (Abb. 3; [15]). Luftgebundener Intensivtransport Der luftgebundene Transport von Intensivpatienten ist mit einem ITH oder Flächenflugzeug möglich (Abb. 4). Bedacht werden muss, dass der luftgebundene Patiententransport deutlich abhängiger von externen Faktoren (Dunkelheit, Wetter) als der ITW-Transport ist. Aktuell ist nur eine geringe Anzahl an RTH/ITH nachtflugtauglich ausgestattet. Bei schlechtem Wetter oder Dunkelheit kann es folglich zum Ausfall eines geplanten Intensivtransports kommen und neue Planungen können notwendig werden. Bei der Beurteilung der Transportfähigkeit muss bei Lufttransporten vor allem die zu erwartende Druckänderung von gasgefüllten Räumen (z. B. Innenohr, Pneumothorax) in Abhängigkeit von der Flughöhe bedacht werden. Hierbei gilt: Je höher die Flughöhe, desto niedriger ist der Umgebungsdruck, was zu einer Ausdehnung gasgefüllter Kompartimente führt. Auch Luftfahrzeuge mit Druckkabine (wie z. B. Ambulanzflugzeuge) erreichen an Bord Druckwerte, die in der Regel dem Luftdruck in 2000–2500 m Höhe entsprechen. Dies kann z. B. im Rahmen eines Pneumothorax zu einer Spannungskomponente mit akuter vitaler Bedrohung führen, weshalb ein vorhandener Pneumothorax vor Transportbeginn immer mit einer Drainage versorgt werden sollte. Zusätzlich ist aufgrund der Lärmbelastung während des Flugs darauf zu achten, dem Patienten unabhängig von der Vigilanz einen adäquaten Gehörschutz zur Verfügung zu stellen. Merke Bei luftgebundenen Intensivtransporten muss die Ausdehnung luftgefüllter Kompartimente in Abhängigkeit von der Flughöhe im Rahmen der Transportfähigkeit mitbedacht werden und ggf. frühzeitig eine Drainageanlage erfolgen. Ebenso sollten aufgrund der beengten Platzverhältnisse innerhalb des Luftrettungsmittels invasive Maßnahmen, die eventuell während des Flugs notwendig werden können, bereits vor Flugbeginn abgeschlossen sein. Werden im Rahmen eines luftgebundenen Transports Ländergrenzen überschritten, müssen vor Beginn des Transports die verschiedenen Einreisevoraussetzungen sowie die Anmeldung des Transports bei entsprechenden Behörden sichergestellt werden. Fazit für die Praxis Der Transport kritisch kranker Patienten zwischen Krankenhäusern ist logistisch sowie bisweilen auch medizinisch herausfordernd und erfordert eine sorgfältige Planung sowie eine gute Teamperformance. Auch wenn gravierende Komplikationen während des Transports selten sind, sollte der Patient vor Transportbeginn bestmöglich stabilisiert sein, um einen sicheren Transport zu ermöglichen. Während der Planungsphase des Transports ist insbesondere auf ein Arzt-Arzt-Gespräch zwischen dem Notarzt des Intensivtransportwagens/-hubschraubers und den zuständigen Ärzten in Quell- und Zielklinik zu achten, um etwaige Transportbesonderheiten frühzeitig zu identifizieren und die Aufnahmebereitschaft der Zielklinik sicherzustellen. Wie auch die Übergabe am Patientenbett sollten diese Gespräche anhand eines Algorithmus oder einer Checkliste erfolgen, um Informationsverluste zu vermeiden. CME-Fragebogen Während Ihres Diensts als Besatzung eines Intensivtransportwagens werden Sie zur Verlegung eines Patienten mit abdomineller Sepsis und refraktärem Kreislaufversagen alarmiert. Der Transport zur weiteren operativen Versorgung und Intensivtherapie soll aus einem Krankenhaus der Grund- und Regelversorgung in ein Universitätsklinikum durchgeführt werden. Um welche Transportart handelt es sich hierbei? Primärtransport Infektionstransport Tertiärtransport Sekundärtransport Luftgebundener Transport Im Rahmen eines Intensivtransports mittels Intensivtransporthubschrauber übernehmen Sie einen Patienten mit nichtdrainiertem Mantelpneumothorax nach Polytrauma im Rahmen eines Motorradunfalls und erschwertem Weaning zum Transport in eine Weaningklinik. Was ist vor Transportbeginn zu beachten? Computertomographie zur Beurteilung der Größe des Pneumothorax Entlastung des Pneumothorax mittels Nadelpunktion Drainage des Pneumothorax, Transport mit abgeklemmter Drainage Entlastung des Pneumothorax mittels Thoraxdrainage, Transport mit offener Drainage Chirurgische Exploration der Thoraxhöhle vor Transportbeginn Der Transport von intensivmedizinischen Patienten ist mit gefährlichen Risiken verbunden. Eine hochwertige Ausbildung entsprechend den Empfehlungen der Deutschen Interdisziplinären Vereinigung für Intensiv- und Notfallmedizin (DIVI) trägt maßgeblich zur Transportsicherheit bei. Welche Anforderungen gemäß DIVI werden an das Personal des Intensivtransportwagens (ITW) gestellt? ITW-Ärzte sollten mindestens über 3 Jahre Berufserfahrung in einem Fachgebiet mit intensivmedizinischen Versorgungsaufgaben verfügen. Gesundheits- und Krankenpfleger sollten mindestens eine zusätzliche Ausbildung als Rettungssanitäter haben. ITW-Ärzte sollten den 80-stündigen Kurs „Intensivtransport“ der DIVI besucht haben. Notfallsanitäter sollten mindestens 4 Jahre Berufserfahrung im Rettungsdienst haben. Notfallsanitäter sollten mindestens 14 Wochen auf einer Intensivstation hospitiert haben. Die sorgfältige Vorbereitung eines Intensivtransports verbessert Abläufe und reduziert sowohl logistische als auch medizinische Probleme während des Transports. Welcher Aspekt sollte im Rahmen der Planung eines Intensivtransportes bedacht werden? Nach Disposition des Transports ist eine Kontaktaufnahme mit der Quellklinik durch das Intensivtransportwagen(ITW)-Team nicht erforderlich. Das Arzt-Arzt Gespräch sollte anhand einer Checkliste geführt werden, um den Informationsverlust zu minimieren. Die Abfrage von Patientenbesonderheiten wie etwa dem Körpergewicht bietet im Rahmen des Arzt-Arzt Gesprächs keinen Vorteil für die Transportplanung. Mithilfe des Arzt-Arzt-Gespräches wählt der ITW-Arzt eine passende Zielklinik für den Patienten aus. In dem Arzt-Arzt-Gespräch dürfen keine Empfehlungen zur Herstellung der Transportfähigkeit ausgesprochen werden. Welche Maßnahme trägt nicht zur Verbesserung des Patientenkomforts im Rahmen eines Intensivtransports bei? Patientenadaptierte Anpassung der Sedierung bei beatmeten Patienten Muskelrelaxierung bei nichtinvasiver Beatmung Hypothermieprophylaxe Stressreduzierende Maßnahmen wie z. B. adäquate Analgesie Einlage eines Gehörschutzes beim Lufttransport Welche Untersuchung sollte im Rahmen der Übernahme eines Patienten zum Intensivtransport nach erfolgtem Übergabegespräch durchgeführt werden? Elektrokardiogramm (EKG) inklusive der inferioren Ableitungen Magnetresonanztomographie (MRT) des Thorax Evaluation der Beatmungssituation Sonographische Beurteilung des Ductus hepatocholedochus (DHC) Elektroenzephalographie (EEG) Gemäß der S1-Leitlinie „Hygienemaßnahmen beim Patiententransport“ können Intensivtransporte in unterschiedliche Kategorien eingeteilt werden, die unter anderem auch Hinweise auf eine mögliche Gefährdung des Personals eines Intensivtransportwagens geben. Von welcher Kategorie geht die geringste Gefahr für das Transportteam aus? Kategorie A Kategorie B Kategorie B1 Kategorie C1 Kategorie C2 Im Rahmen der Übernahme eines Patienten zum Intensivtransport findet im Arztzimmer einer Intensivstation im Beisein des Transportteams sowie des betreuenden Pflegepersonals und des Stationsarztes das Übergabegespräch an das Transportteam statt. Dieses wird anhand einer Checkliste durchgeführt und bearbeitet systematisch alle wesentlichen Informationen zum Patienten und dessen Krankheitsverlauf. Während des Übergabegesprächs finden keine weiteren Tätigkeiten statt. Im Anschluss fasst der Notarzt des Intensivtransportwagens die wichtigsten Punkte der Übergabe zusammen. Welcher Aspekt dieser exemplarischen Übergabephase kann verbessert werden? Örtlichkeit der Übergabe Anwesenheit des involvierten Personals Struktur des Übergabegesprächs Aufmerksamkeit der Gesprächsteilnehmer Zusammenfassung der Übergabe durch das Transportteam Das ISOBAR-Schema kann zur Vermeidung von Informationsverlusten im Rahmen einer Patientenübergabe angewendet werden. Für welche Informationen stehen die Akronymbestandteile im ISOBAR-Schema? „Intensive care“ steht für aktuelle Intensivbehandlung. „Situation“ steht für Leitsymptom, aktueller Patientenzustand. „Observations“ steht für Vorerkrankungen, Dauermedikation. „Background“ steht für Intensivverlauf, relevante diagnostische Befunde. „Assessment“ steht für Ansprechpartner Zielklinik, Empfehlungen. Die Umlagerung eines Intensivpatienten stellt einen kritischen Moment im Rahmen eines Intensivtransports dar. Wie gehen Sie bei der Umlagerung eines Intensivpatienten vor? Zur Vermeidung von Kommunikationsproblemen sollte eine Umlagerung durch maximal 2 Personen durchgeführt werden. Im Rahmen der Umlagerung sollte der Patient kurzzeitig von der maschinellen Beatmung oder einer supplementären Sauerstoffgabe getrennt werden. Nach erfolgter Umlagerung sollten Gefäßzugänge und Drainagen auf Funktion und eine freie Lage überprüft werden. Auf ein apparatives Monitoring während der Umlagerung sollte verzichtet werden. Die Umlagerung eines Patienten vom Klinikbett auf die Transporttrage muss durch klinikinternes Personal durchgeführt werden. Einhaltung ethischer Richtlinien Interessenkonflikt Gemäß den Richtlinien des Springer Medizin Verlags werden Autoren und wissenschaftliche Leitung im Rahmen der Manuskripterstellung und Manuskriptfreigabe aufgefordert, eine vollständige Erklärung zu ihren finanziellen und nichtfinanziellen Interessen abzugeben. Autoren M. Feth: A. Finanzielle Interessen: M. Feth gibt an, dass kein finanzieller Interessenkonflikt besteht. – B. Nichtfinanzielle Interessen: Weiterbildungsassistent, Klinik für Anästhesiologie, Intensivmedizin, Notfallmedizin und Schmerztherapie, Bundeswehrkrankenhaus Ulm (Klinischer Direktor: OTA Prof. Dr. M. Kulla); aktuell Research Fellow, United States Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, Texas, USA | Mitgliedschaften: Deutsche Interdisziplinäre Vereinigung für Intensiv-und Notfallmedizin (DIVI), Berufsverband deutscher Anästhesisten (BDA), Arbeitsgemeinschaft südwestdeutscher Notärzte (agswn), Extracorporeal Life Support Organisation (ELSO). C. Zeiner: A. Finanzielle Interessen: C. Zeiner gibt an, dass kein finanzieller Interessenkonflikt besteht. – B. Nichtfinanzielle Interessen: Oberarzt Universitätsklinikum des Saarlandes, Klinik für Innere Medizin V, Homburg/Saar | Mitgliedschaften: DIVI, DGIM, DGP, DGIIN. G. Danziger: A. Finanzielle Interessen: G. Danziger gibt an, dass kein finanzieller Interessenkonflikt besteht. – B. Nichtfinanzielle Interessen: Oberarzt, Intensivmedizin, Klinik für Innere Medizin V, Uniklinik des Saarlandes, Homburg; Facharzt für Anästhesie | Mitgliedschaft: BDA. C. Eimer: A. Finanzielle Interessen: C. Eimer gibt an, dass kein finanzieller Interessenkonflikt besteht. – B. Nichtfinanzielle Interessen: berufliche Tätigkeit: Klinik für Anästhesiologie und Operative Intensivmedizin am Universitätsklinikum Schleswig-Holstein, Campus Kiel seit 2015; Fachärztin für Anästhesiologie, Zusatzbezeichnungen Notfallmedizin und Intensivmedizin, leitende Notärztin | Mitgliedschaften: DGAI; Arbeitsgemeinschaft Norddeutscher Notärzte e. V., Mitglied des Vorstands als Kassenprüferin. S. Mang: A. Finanzielle Interessen: S. Mang gibt an, dass kein finanzieller Interessenkonflikt besteht. – B. Nichtfinanzielle Interessen: angestellter Assistenzarzt für Innere Medizin und Pneumologie, Universitätsklinikum des Saarlandes. S. Kühn: A. Finanzielle Interessen: S. Kühn gibt an, dass kein finanzieller Interessenkonflikt besteht. – B. Nichtfinanzielle Interessen: angestellter Anästhesist, Zeitsoldat, Bundeswehrkrankenhaus Ulm, Klinik für Anästhesiologie, Notfallmedizin, Intensivmedizin und Schmerztherapie (Klinischer Direktor: OTA Prof. Dr. M. Kulla) | Mitgliedschaft: DGAI. N. Villalobos: A. Finanzielle Interessen: N. Villalobos gibt an, dass kein finanzieller Interessenkonflikt besteht. – B. Nichtfinanzielle Interessen: Medical Director, Intensive Care Unit, Brooke Army Medical Center, San Antonio, USA. R.M. Muellenbach: A. Finanzielle Interessen: R.M. Muellenbach gibt an, dass kein finanzieller Interessenkonflikt besteht. – B. Nichtfinanzielle Interessen: Chefarzt, operative Intensivmedizin, Klinik für Anästhesiologie, Intensivmedizin, Notfallmedizin und Schmerztherapie, Klinikum Kassel | Gesundheit Nordhessen Holding AG, Kassel | Mitgliedschaften: DGAI, DIVI und BDA. S.I. Hörsch: A. Finanzielle Interessen: S.I. Hörsch gibt an, dass kein finanzieller Interessenkonflikt besteht. – B. Nichtfinanzielle Interessen: Oberärztin der Klinik für Anästhesiologie, Intensivmedizin und Schmerztherapie (Klinikdirektor: Prof. Dr. med. Th. Volk), Universitätsklinikum des Saarlandes, Homburg/Saar | Mitgliedschaften: Bund Deutscher Anästhesisten (BDA), Deutsche Gesellschaft für Anästhesie und Intensivmedizin (DGAI). P.M. Lepper: A. Finanzielle Interessen: P.M. Lepper gibt an, dass kein finanzieller Interessenkonflikt besteht. – B. Nichtfinanzielle Interessen: leitender Oberarzt der Klinik für Innere Medizin V, Universitätsklinikum des Saarlandes | Mitgliedschaften: DGP, DGIIN. Wissenschaftliche Leitung Die vollständige Erklärung zum Interessenkonflikt der wissenschaftlichen Leitung finden Sie am Kurs der zertifizierten Fortbildung auf www.springermedizin.de/cme. Der Verlag erklärt, dass für die Publikation dieser CME-Fortbildung keine Sponsorengelder an den Verlag fließen. Für diesen Beitrag wurden von den Autor/-innen keine Studien an Menschen oder Tieren durchgeführt. Für die aufgeführten Studien gelten die jeweils dort angegebenen ethischen Richtlinien. Zur verbesserten Lesbarkeit wird in diesem Beitrag das generische Maskulinum verwendet. Grundsätzlich werden jedoch alle im Intensivtransport tätigen Personen angesprochen. QR-Code scannen & Beitrag online lesen ==== Refs Literatur 1. Normung DIf (2008) DIN 13050. Rettungswesen – Begriffe 2. Schlechtriemen TKHA Das Intensivtransportsystem – ein neues Konzept fuer den bodengebundenen Intensivtransport Notfall Rettungsmed 2000 3 7 420 424 10.1007/s100490070016 3. Wenninger RHE Neue organisatorische Versorgungskonzepte: Der Intensivtransporthubschrauber Notarzt 2000 16 04 130 132 10.1055/s-2000-3808 4. Roessler M Reinhardt K Luhmann U Interhospital transport of intensive care patients in Lower Saxony : statewide need-based and effective management Anaesthesist 2011 60 8 759 771 10.1007/s00101-011-1925-9 21842251 5. Reifferscheid F Grasner JT Hocker J Organisation and scheduling of interhospital intensive care patient transport Anasthesiol Intensivmed Notfallmed Schmerzther 2013 48 5 352 356 23757018 6. Notfallmedizin DIVfI‑u (2021) Empfehlungen zur personellen Qualifikation im ausserklinischen Intensivtransport 7. Baker DP Day R Salas E Teamwork as an essential component of high-reliability organizations Health Serv Res 2006 41 4 Pt 2 1576 1598 10.1111/j.1475-6773.2006.00566.x 16898980 8. Hales BM Pronovost PJ The checklist—a tool for error management and performance improvement J Crit Care 2006 21 3 231 235 10.1016/j.jcrc.2006.06.002 16990087 9. Boussen S Gainnier M Michelet P Evaluation of ventilators used during transport of critically ill patients: a bench study Respir Care 2013 58 11 1911 1922 10.4187/respcare.02144 23592785 10. Beament T Ewens B Wilcox S Reid G A collaborative approach to the implementation of a structured clinical handover tool (iSoBAR), within a hospital setting in metropolitan Western Australian: A mixed methods study Nurse Educ Pract 2018 33 107 113 10.1016/j.nepr.2018.08.019 30273803 11. Seymour CW Kahn JM Schwab CW Fuchs BD Adverse events during rotary-wing transport of mechanically ventilated patients: a retrospective cohort study Crit Care 2008 12 3 R71 10.1186/cc6909 18498659 12. Strauch U Bergmans DC Winkens B Roekaerts PM Short-term outcomes and mortality after interhospital intensive care transportation: an observational prospective cohort study of 368 consecutive transports with a mobile intensive care unit BMJ Open 2015 5 4 e006801 10.1136/bmjopen-2014-006801 13. Javidfar J Brodie D Takayama H Safe transport of critically ill adult patients on extracorporeal membrane oxygenation support to a regional extracorporeal membrane oxygenation center ASAIO J 2011 57 5 421 425 10.1097/MAT.0b013e3182238b55 21869618 14. AWMF-Leitlinie (2019) Hygienemaßnahmen beim Patiententransport. https://register.awmf.org/assets/guidelines/029-029l_S1_Hygienemaßnahmen-beim-Patiententransport_2019-07.pdf. Accessed 8 Feb 2022 15. Javidfar J Labib A Ragazzo G Mobile extracorporeal membrane oxygenation for Covid-19 does not pose extra risk to transport team ASAIO J 2022 68 2 163 167 10.1097/MAT.0000000000001602 34802012
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==== Front Int J Cogn Ther Int J Cogn Ther International Journal of Cognitive Therapy 1937-1209 1937-1217 Springer International Publishing Cham 155 10.1007/s41811-022-00155-9 Article Development of the COVID-19-Specific Obsessive Compulsive Symptoms Scale with Various Validity and Reliability Proofs Şengül Avşar Asiye 1 http://orcid.org/0000-0001-9427-9425 Avşar Volkan [email protected] 2 1 grid.412216.2 0000 0004 0386 4162 Department of Measurement and Evaluation in Education, Recep Tayyip Erdoğan University, Rize, Turkey 2 grid.412216.2 0000 0004 0386 4162 Department of Psychological Counselling and Guidance, Recep Tayyip Erdoğan University, Rize, Turkey 12 12 2022 123 29 11 2022 © Springer Nature Switzerland AG 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. The COVID-19 epidemic, which spread rapidly around the world, has had a significant negative impact on mental health. Obsessive–compulsive disorder (OCD) issues are among the main mental health effects of COVID-19. The purpose of this study is to develop a brief measurement tool that reliably and validly measures obsessive–compulsive (OC) symptoms in people with COVID-19. A total of 483 people took part in the research online. Individuals with aberrant item scores were excluded, and a series of validity and reliability analyses were performed to determine the psychometric properties of the COVID-19-specific obsessive compulsive symptoms scale (C19-OCS). C19-OCS was found to be a valid and reliable measure for assessing OC symptoms in relation to COVID-19. Mental health professionals could use C19-OCS to develop evidence-based intervention strategies and programs. Keywords COVID-19 Obsessive–compulsive symptoms Scale development Validity Reliability ==== Body pmcThe global outbreak of novel coronavirus disease (COVID-19) has had a devastating effect in various areas from health to economy, from education to social life. One of the main destructive effects of COVID-19 has been on physical and mental health. In Turkey, more than 16 million people were diagnosed with COVID-19 while more than 100,000 people died of it (WHO, 2022a). Because COVID-19 is transmitted through respiratory secretions, contact with contaminated surfaces or close contact of people with each other (WHO, 2022b) can cause it to rapidly spread. Since the onset of COVID-19, individuals have taken many measures to prevent or slow down its transmission, such as frequent washing of hands or using disinfectants, using masks, paying attention to social distance, isolation, and quarantine of infected individuals, monitoring and testing of potential contacts (Adhikari et al., 2020). However, the high rates of transmission and death of COVID-19, the significant damage to health by the infection, the uncertainties about the course of the disease, its negative consequences on daily life, and the measures taken to prevent its transmission have fueled the development of pandemic-specific fear and anxiety among people (Khan et al., 2022; Pacitti et al., 2022; Theberath et al., 2022; Wang et al., 2021). Fear is an adaptive emotion that usually arises in the event of a concrete and real threat or danger that develops suddenly in the time and environment in which the person is in, informing the person that they are in danger, and enabling them to act quickly to protect themselves and survive (Tompkins, 2013). During the COVID-19 pandemic, fear may have a functional role in encouraging people to engage in less risky behavior and take preventative measures such as masks, social distancing, and hand hygiene (Harper et al., 2021; Idrees et al., 2022). However, when fear is excessive or disproportionate, it becomes harmful to the person and becomes a key component in the development or exacerbation of mental health problems (Garcia, 2017). In other words, while fear of COVID-19 can help people stay safe, when fear leads to excessive worry and distress, it can harm one’s mental health (Alimoradi et al., 2022; Belen, 2022; Fitzpatrick et al., 2020; Simsir et al., 2022). Obsessive–compulsive disorder (OCD) is one of the key mental health problems most affected by fear of COVID-19 (Guzick et al., 2021; Linde et al., 2022). According to the American Psychiatric Association, OCD is characterized by obsessions and compulsions. While obsessions are characterized by unwanted, recurrent, and persistent intrusive thoughts, images, or urges, complications are characterized by repetitive behaviors or mental acts aimed at reducing one’s anxiety provoked by obsessions (APA, 2013). Extreme and excessive fear of COVID-19 may help drive the onset or increase of obsessive–compulsive symptoms by causing irrational and unclear thoughts (Khan et al., 2022; Matsunaga et al., 2020; Pacitti et al., 2022). Moreover, fear of COVID-19 may exacerbate contamination/cleaning and obsessions/checking symptoms (Mataix-Cols et al., 2005). These are likely to be affected because COVID-19 is a virus-transmitted disease and numerous health messages have called for frequent hand washing, paying attention to hygiene, using disinfectants, paying attention to social distancing, or minimizing contact with others to reduce the risk of transmission (Grant et al., 2022). In addition, contamination, cleaning, and the thought and fear of contracting a disease are major concerns for people with OCD (Silva et al., 2021). Thus, due to fear of contamination, people with OCD may spend hours worrying about the possibility of coming into contact with a contagious disease, avoiding potential contaminants (e.g., not touching certain surfaces or reducing social contacts), and/or various compulsive washing behaviors (e.g., washing or disinfecting their hands) (Demaria et al., 2022; Fontenelle & Miguel, 2020). Studies analyzing the effect of COVID-19 on OCD have obtained different results. While some studies have shown that people with OCD cope well with COVID-19 in the early stages of the pandemic that there is no significant exacerbation or even reduction in Obsessive-Compulsive (OC) symptoms (Moreira-de-Oliveira et al., 2022; Schwartz-Lifshitz et al., 2021; Sharma et al., 2021), others found exacerbated level of symptoms during the pandemic (especially in contamination and washing symptoms) (Fontenelle et al., 2021; Grant et al., 2022; Guzick et al., 2021; Jelinek et al., 2021a), development of new symptoms related to COVID-19 (Nissen et al., 2020), or the onset of OC symptoms in people who did not have OCD prior to the pandemic (Alateeq et al., 2021; Fontenelle et al., 2021; Pan et al., 2021). Assessing such COVID-19-related symptoms is complicated by several factors. First, according to Fischer et al. (2021), the first months of the lockdown during the pandemic may have caused a temporary decrease in some symptoms, as it led people with OCD to avoid potential contamination situations. This may have been reinforced by the alignment of the existing OCD rituals with recommended social practices, such as quarantining, avoiding contact with other people and objects, frequent handwashing, and using disinfectants (Pan et al., 2021). Moreover, this alignment of OC symptoms and social practices likely helps to minimize feelings of stigma, self-blame, and shame due to rituals that might otherwise induce these feelings (Aardema, 2020). Finally, even believing that they will be protected from COVID-19 thanks to their current obsessions and compulsions may have contributed to the decrease of the severity of some individuals’ symptoms. A second factor that may limit the assessment and interpretation of past results is the evaluation of OC symptoms with measurement tools that were developed before COVID-19; as such, they do not include specific items related to COVID-19 and this likely to have impacted the results. Despite these constraints, it is important to identify OC symptoms linked with COVID-19. If the adverse psychological effects of COVID-19 in inducing or intensifying OC symptoms are not identified and responded to quickly, there is a risk of long-term negative consequences for mental health. Moreover, dealing with these psychological effects will become more difficult and expensive as time goes on (Zhou et al., 2020). Furthermore, understanding people’s psychological reactions to COVID-19 contamination will be critical in preventing and controlling the pandemic’s spread (Taylor, 2019). Several measures have been developed of fear, worry, anxiety, stress, perception of threat, phobia, and obsessions that develop as a result of COVID-19. These measures include the Fear of Coronavirus-19 Scale (Ahorsu et al., 2022), the COVID-19 Phobia Scale (Arpaci et al., 2020), the Coronavirus Anxiety Scale (Lee, 2020a), the Questionnaire on Perception of Threat from COVID-19 (Pérez-Fuentes et al., 2020), the COVID-19 Impact Battery (Schmidt et al., 2022), Obsession with COVID-19 Scale (OCS) (Lee, 2020b), and the COVID Stress Scales (CSS) (Taylor et al., 2020). Among these measures, the OCS and CSS assess obsessions related to COVID-19. The OCS is a unidimensional measurement tool for obsessive thinking about COVID-19. The CSS has a five-dimensional structure and was designed to measure COVID-19 stress and anxiety symptoms. Two of these dimensions assess OC symptoms (“COVID danger and contamination fears,” “compulsive checking”). It is said that COVID-19 causes fear of contamination and obsessive thoughts, and cleaning standards advocated by organizations such as the WHO, such as washing, become compulsive rituals (Jelinek et al., 2021b; Silverman et al., 2022; Tanir et al., 2020). A problem with the OCS and CSS measures is that they are limited in not assessing compulsive cleaning and washing. Another problem with most studies examining the effect of COVID-19 on OC symptoms is that they use clinical interviews or previously developed measurement tools that contain no COVID-19-related items (e.g., Grant et al., 2022; Pacitti et al., 2022; Sharma et al., 2021). Based on these considerations, it is critical that a measure be developed that includes items related to COVID-19 and evaluates OC symptoms in the dimensions of contamination/cleaning and obsessions. The goal of this study was to create a brief measurement tool that assesses the effect of COVID-19 on these key OC symptoms in a valid and reliable manner. Method Participants This study, performed at the beginning of the COVID-19 pandemic (July 2020), was approved by the Recep Tayyip Erdoğan University Social and Humanities Ethics Committee (Approval No: 2020/104). A total of 438 volunteers participated in this online study. At the beginning of the study, all participants were informed about the purpose of the study, that their answers were handled anonymously, and that the collected answers would only be used for research purposes. A total of 438 people who gave informed consent and volunteered were included in the study. Participants filled out the measurement tools used in the research via Google Forms. This research was conducted with participant data excluding individuals with aberrant item scores. In the literature, it has been stated that individuals with aberrant item scores have negative effects on validity results (Şengül Avşar, 2021). Individuals with aberrant item scores may respond the items in the measurement tools carelessly, and respond randomly or with an incomplete motivation without reading the items (Meijer, 1996; Sijtsma & Molenaar, 2002). Removing individuals with aberrant item scores before the analysis increases the accuracy of the analysis results in terms of validity (de Vroege et al., 2018; Liu et al., 2019). In order to determine individuals with aberrant item scores, person-fit statistics (PFS) is utilized (Emons, 2008). In this study, the average normed number of Guttman errors (GNP), which is one of the non-parametric PFS, which is easier to apply and more advantageous in many respects than parametric methods, was taken into account in determining individuals who have aberrant item scores. A total of 51 people who have aberrant item scores according to GNP were identified. These individuals were excluded from the data set, and validity and reliability studies were carried out on data from 387 participants. Information on the demographic characteristics of the participants in the study is given in Table 1.Table 1 Demographic characteristics of the study sample Characteristics N % Gender   Female 268 69.3   Male 119 30.7 Age   18–30 226 58.4   31–45 134 34.6   46–65 27 7.0 Educational level   Graduated from primary school 2 0.5   Graduated from high school 17 4.4   Graduated from university 135 34.9   University student 173 44.7   Graduated from advance research programs 60 15.5 Psychological support   Yes 69 17.8   No 318 82.2 Psychological diagnosis   Yes 20 5.2   No 367 94.8 Status of leaving home   I am definitely not leaving home   In mandatory situations, I go out of the house for a short time   I am not limiting myself about going out of the house   I go out because I work 41 307 26 13 10.6 79.3 6.7 3.4 Total 387 100.0 When Table 1 is examined, it is seen that the number of female participants in the study is greater (69.3%), and the participants are mostly university students (44.7%). While 17.8% of the participants stated that they received psychological support, 5.2% stated that they had a psychological diagnosis. Psychological diagnoses of the participants are respectively social anxiety (0.3%), attention deficit hyperactivity disorder (0.8%), depression (1.0%), panic attack (1.3%), and anxiety (1.6%). Most of the participants (79.3%) stated that they went out for a short time in mandatory situations during the COVID-19. Measures In this study, which aims to develop C19-OCS, various measurement tools were used. A demographic information form was developed by the researchers to determine the demographic characteristics of the participants. The criterion-related validity of C19-OCS was evaluated using Beck Anxiety Inventory (BAI) and Dimensional Obsessive–Compulsive Scale (DOCS). General information about these measurement tools and the psychometric properties of this research obtained from the study group are given below, respectively. Demographic information form In this form, the participants are asked about their gender, age, educational level, whether they have received psychological support, whether they have a psychological diagnosis, and their status of leaving home during the COVID-19 pandemic. COVID-19-specific obsessive compulsive symptoms scale Various steps have been followed in the development of the C19-OCS. First of all, a detailed literature review has been made. The scales developed specifically for the COVID-19 process were examined in detail, and later on, the item writing process started. For C19-OCS, 49 items were written. In the evaluation of the items written, the method suggested by Lawshe (1975) was followed. The items written were evaluated by a team of experts consisting of a psychiatry professor, two associate professors specialized in psychological counseling and guidance, and two psychometrists. Each item was evaluated by the expert team in three categories (unnecessary, useful but not sufficient, necessary). Then, content validity ratio and content validity index were calculated. Considering both the results of the Lawshe (1975) method and the warnings of experts that some items have similar content or explanation, it was decided to leave 17 items in the scale. The remaining items were applied to six female and four male university students with an average age of 19.40, and as a result of the application, it was determined that all the item expressions were clear and understandable. Based on their experiences in the last month, the participants indicate how much they agree with each item using one of the 5 ratings (1 strongly disagree to 5 strongly agree). All the items in C19-OCS are included in the Appendix. Beck Anxiety Inventory The validity and reliability studies for the Turkish version of BAI developed by Beck et al. (1988) were carried out by Ulusoy et al. (1998). In the study, it was stated that BAI has a construct with two factors: “Subjective Anxiety (SA)” and “Somatic Symptoms (SS).” In addition to this, Cronbach alpha of BAI was calculated as 0.93. In this study, confirmatory factor analysis (CFA) was applied for the validity of the structure of BAI, which is determined according to Turkish culture. The goodness-of-fit values obtained for the two-factor structure are as follows: χ2(188) = 1105.00, p = 0.00; χ2/188 = 5.87; CFI = 0.93; GFI = 0.79; NFI = 0.92; RFI = 0.91; RMSEA = 0.11; SRMR = 0.07 (bold values indicate that the model is acceptable). According to the values obtained, it can be said that BAI gives valid results in the sample of the research. In addition, Cronbach alpha reliability of the scores obtained from BAI was calculated as 0.91 for the SA factor, 0.81 for the SS factor, and 0.93 for the whole BAI. So, it can be said that BAI offers valid and reliable results in the sample of the research. Dimensional Obsessive–Compulsive Scale The validity and reliability studies for the Turkish version of DOCS developed by Abramowitz et al. (2010) were carried out by Şafak et al. (2018). In the study, it was determined that DOCS consists of four subscales, which are “Contamination,” “Responsibility,” “Unacceptable thoughts,” and “Symmetry,” and Cronbach alpha reliability of the scores obtained from each subscale are respectively 0.87, 0.93, 0.93, and 0.92 for the whole scale. The contamination (DOCS-C) subscale was used in this study. Within the scope of the research, CFA was performed for the scores obtained from the DOCS-C. The goodness-of-fit values achieved for the DOCS-C subscale are as follows: χ2(5) = 44.54, p = 0.00; χ2/5 = 8.91; CFI = 0.92; GFI = 0.96; NFI = 0.91; RFI = 0.82; RMSEA = 0.14; SRMR = 0.06 (bold values indicate that the model is acceptable). In addition to this, Cronbach alpha reliability of the scores obtained from the DOCS-C subscale was calculated as 0.70. According to these values, it can be said that the DOCS-C subscale gives reliable and valid results in the sample of the research. Procedure A series of various validity and reliability analysis have been implemented to determine the psychometric properties of C19-OCS. In validity studies, Mokken Scale Analysis (MSA), exploratory factor analysis (EFA)-parallel analysis (PA), convergent and discriminant validity, criterion-related validity (CRV), and upper/lower group differences were investigated for construct validity. Scaling is performed according to various test theories in determining the psychometric properties of measurement tools. One of the non-parametric Item Response Theory (NIRT) models, the Mokken Model, allows items and persons to be ordered in measuring instruments with small sample sizes or a small number of items (Meijer & Baneke, 2004). The purpose of the Mokken Model is to order the individuals along their latent traits by using their scores (Stochl et al., 2012). According to the Mokken Model, automated item selection procedure (AISP) is taken into account in the selection of the item. AISP creates unidimensional Mokken Scales (MS) by separating items that do not scale according to Mokken Model (van der Ark et al., 2020). In MSA, scalability coefficient H is taken into account. In the evaluation of H coefficients, also known as item discrimination index, for 0.30 ≤ H < 0.40 weak, for 0.40 ≤ H < 0.50 medium, and for H ≥ 0.50, high criteria are used (Meijer & Baneke, 2004; Sijtsma & Molenaar, 2002; Sijtsma & van der Ark, 2017). In this study, scaling was carried out according to Mokken Homogeneity Model (MHM), which can be considered as an explanatory model (Sodano et al., 2014), and initial analysis of the data was performed with AISP. Since the sample of this research was not large, MHM that is concordant with small samples was used. In data sets scaled according to MHM, respondents can be ordered reliably and validly based on their total scores (Sijtsma & Molenaar, 2002). The reliability of the scores obtained from C19-OCS was investigated with Cronbach alpha (α), Guttman lambda 2 (λ), latent class reliability coefficient (LCRC), composite reliability (CR), McDonald’s omega (ω), and test–retest reliability. R Studio 4.0.2, LISREL 8.71, and JAMOVI 1.1.9 programs were used in the analysis of the data in this study. “PerFit Package” (for determining aberrant item scores), “Mokken Package” (for Mokken analysis), and “Psych Package” (for PA) were used. While CFA for factor structures of BAI and DOCS-C measurement tools was investigated with LISREL 8.71 program, JAMOVI 1.1.9 program was used for EFA, CRV, and McDonald’s omega (ω). Statistical analyses for construct validity in this study are MSA, EFA, PA, CRV, and upper/lower group differences. Statistical analysis for the reliability of the scores obtained from the scale is the determination of internal consistency reliability coefficients (Cronbach alpha (α), Guttman lambda 2 (λ), latent class reliability coefficient (LCRC), composite reliability (CR), McDonald’s omega (ω)), and the correlations between the scores obtained as a result of the test re-test. Results Initial validity analysis of C19-OCS As a first step, it was determined whether C19-OCS was scaled according to MHM. For this, the H coefficients of the items and the standard error values calculated for these coefficients were obtained. The results obtained are given in Table 2.Table 2 H coefficients and standard error (SE) of H for C19-OCS items Items H SE Items H SE Item 1 0.429 0.034 Item 10 0.420 0.035 Item 2 0.490 0.029 Item 11 0.472 0.027 Item 3* 0.208 0.039 Item 12 0.467 0.028 Item 4 0.503 0.031 Item 13 0.538 0.026 Item 5 0.357 0.033 Item 14 0.553 0.024 Item 6 0.470 0.029 Item 15 0.512 0.026 Item 7 0.482 0.029 Item 16 0.542 0.027 Item 8 0.455 0.031 Item 17 0.536 0.029 Item 9 0.459 0.028 Scale 0.461 0.022 *H < 0.30 When the evaluation criteria of H are taken into account, it is seen that the scalability coefficient of item 3 (I am tired of watching the news about COVID-19) is below 0.30: that is to say, it is not scaled to MHM. As it was not scaled to MHM, this item was removed from the scale and MHM analyses were repeated. The results obtained are given in Table 3.Table 3 H coefficients and standard error (SE) of H for C19-OCS items-excluded item 3 Items H SE Items H SE Item 1 0.450 0.034 Item 10 0.447 0.035 Item 2 0.505 0.029 Item 11 0.498 0.028 Item 4 0.515 0.031 Item 12 0.484 0.028 Item 5 0.375 0.033 Item 13 0.557 0.027 Item 6 0.481 0.030 Item 14 0.574 0.024 Item 7 0.503 0.030 Item 15 0.537 0.027 Item 8 0.474 0.031 Item 16 0.553 0.028 Item 9 0.478 0.028 Item 17 0.553 0.029 Scale 0.497 0.022 When Table 3 is examined, it is seen that the scalability coefficients of the items increase after item 3 was removed. Based on the H evaluation criteria, generally, items have medium and strong fit levels to MHM. The H value for the whole scale was calculated as 0.497 (0.022). Accordingly, C19-OCS has a medium level of fit to MHM. As seen in Table 3, all items were scaled according to MHM. Additionally, the results of monotonicity assumptions are included in Table 4.Table 4 Monotonicity assumptions of C19-OCS Active comparisons Violations Significant violations Crit Item 1 24 0 0 0 Item 2 21 0 0 0 Item 4 7 0 0 0 Item 5 24 0 0 0 Item 6 15 0 0 0 Item 7 19 0 0 0 Item 8 18 0 0 0 Item 9 21 0 0 0 Item 10 20 0 0 0 Item 11 18 0 0 0 Item 12 19 0 0 0 Item 13 9 0 0 0 Item 14 16 0 0 0 Item 15 16 0 0 0 Item 16 12 0 0 0 Item 17 19 0 0 0 Table 4 contains the crit value, which is an important criterion in MHM. When interpreting the crit value, crit < 40, suitable; 40 ≤ crit < 80, suspicious; and crit > 80, seriously incompatible criteria are taken into account (Crișan et al., 2019). When Table 4 is examined, it is seen that there is no item that violates monotonicity assumption. It is stated that MHM can be used as an exploratory model in scale development processes (Sijtsma et al., 2008). It can be said that MHM is useful in determining the items that give valid measurement results. In that regard, all items except for item 3 were decided to be included in the scale. The number of unidimensional MS in C19-OCS was determined using AISP. The threshold for the cutoff (lower bound) values are used in determining unidimensional MS. It is stated that these values should be interpreted with an increase by 0.05 (Stochl et al., 2012). In this research, as in similar studies (Chou et al., 2017; Vaughan & Grace, 2018), the cutoff values were created in different values starting from the default value of 0.30 and increasing by 0.05 (0.30–0.65). The unidimensional MS obtained are shown in Table 5.Table 5 Determination of unidimensional MS for the C19-OCS Lower bounds Items 0.30 0.35 0.40 0.45 0.50 0.55 0.60 0.65 Item 1 1 1 1 1 2 2 2 0 Item 2 1 1 1 1 1 1 0 0 Item 4 1 1 1 1 1 1 1 2 Item 5 1 1 0 0 0 0 0 0 Item 6 1 1 1 1 1 0 0 2 Item 7 1 1 1 1 1 1 3 0 Item 8 1 1 1 1 2 2 0 0 Item 9 1 1 1 1 2 2 2 0 Item 10 1 1 1 1 0 0 0 0 Item 11 1 1 1 1 1 3 0 0 Item 12 1 1 1 1 1 3 0 0 Item 13 1 1 1 1 1 1 1 1 Item 14 1 1 1 1 1 1 1 1 Item 15 1 1 1 1 1 1 3 0 Item 16 1 1 1 1 1 1 1 1 Item 17 1 1 1 1 1 1 1 1 Number of ıtems for scale 1 16 16 15 15 11 8 5 4 Number of ıtems for scale 2 0 0 0 0 3 3 2 2 Number of ıtems for scale 3 - - - - - 2 2 - When Table 5 is examined, it is seen that the cutoff has one MS for 0.30, 0.35, 0.40, and 0.45 lower bounds, two MS for 0.50 and 0.65 lower bounds, and three MS for 0.55 and 0.60 lower bounds. There are different number of items in the MS. It is stated that MS should not have a small number of items, i.e., that it should consist of at least four items (Chou et al., 2017; Stochl et al., 2012). Based on this, it is seen from Table 5 that the cutoff values can be selected as 0.35 or 0.45. Generally, all or 15 of the 16 items create a single MS. If the cutoff value is taken as 0.40 or 0.45, it is recommended that item 5 (I am afraid of having infected someone with COVID-19 unknowingly) is removed from the scale. Based on the relevant item’s content and its high H value, it was decided by the researchers that it is kept it in the scale. In summary, the number of MS obtained according to AISP gave information about the number of dimensions of the scale. Based on this information, it was predicted that a scale with a dominant factor was obtained from the results of the MSA. Validity studies For C19-OCS validity studies, EFA-PA, convergent and discriminant validity, CRV, and upper/lower differences were investigated, and the findings obtained are given below, respectively. First of all, descriptive statistics related to the items of C19-OCS are given in Table 6.Table 6 Descriptive statistics of items Minimum Maximum Mean Std. deviation Skewness Kurtosis Item 1 1 5 3.67 1.01  − 0.84 0.22 Item 2 1 5 2.40 1.11 0.63  − 0.51 Item 4 1 5 1.64 0.78 1.49 2.87 Item 5 1 5 2.95 1.29 0.01  − 1.25 Item 6 1 5 2.10 1.05 0.85  − 0.04 Item 7 1 5 2.26 1.08 0.73  − 0.33 Item 8 1 5 3.90 1.04  − 1.01 0.42 Item 9 1 5 3.00 1.18 0.10  − 1.02 Item 10 1 5 2.27 0.96 0.78 0.05 Item 11 1 5 3.00 1.16  − 0.06  − 1.16 Item 12 1 5 2.67 1.14 0.26  − 1.09 Item 13 1 5 1.97 0.95 1.16 1.10 Item 14 1 5 2.48 1.18 0.42  − 0.99 Item 15 1 5 3.16 1.18  − 0.26  − 1.08 Item 16 1 5 1.78 0.88 1.32 1.78 Item 17 1 5 2.03 0.97 0.96 0.41 When Table 6 is examined, it is seen that item scores mean vary between 1.64 and 3.90, standard deviation between 0.78 and 1.29, skewness value between − 1.01 and 1.49, and kurtosis value between − 1.25 and 2.87. Considering that the skewness and kurtosis values are between − 3.0 and 3.0, it can be stated that the distribution of item scores does not deviate from the normal distribution (Kline, 2011). Also, West et al. (1995) stated that when the absolute value of the skewness coefficient is greater than 2 and the absolute value of the kurtosis coefficient is greater than 7, the normal distribution is not achieved. Findings of EFA We conducted EFA with principal axis factoring (PAF) method and PA for construct validity. The sample size for EFA should be sufficient. While determining the sample size for the data collected on a voluntary basis, the widely accepted ratio of 1:10 in the literature, in other words, the need to reach people at least 10 times the number of items, was taken into account (Hair et al., 2019). Data from 387 participants who responded to 16 items were used in this study. According to literature, the number of participants is sufficient for EFA. In addition, Kaiser measure of sampling adequacy for EFA was 0.942, and Bartlett test of sphericity was significant, χ2(120) = 3011.465, p < 0.01. These values show that the sample size is statistically sufficient as well. Table 7 shows communalities, item-total correlations, and the factor loadings obtained from the direct oblimin rotation method.Table 7 PAF results of C19-OCS Factors Items Communalities 1 2 r Obsessive thoughts (1) Item 17 0.668 0.887  − 0.120 0.745* Item 16 0.606 0.842  − 0.109 0.719* Item 13 0.577 0.753 0.010 0.738* Item 4 0.478 0.741  − 0.084 0.652* Item 14 0.637 0.724 0.110 0.792* Item 6 0.440 0.619 0.067 0.673* Item 7 0.459 0.581 0.139 0.699* Item 10 0.367 0.568 0.057 0.619* Item 2 0.458 0.503 0.236 0.705* Item 12 0.411 0.479 0.220 0.676* Contamination fears and cleaning (2) Item 8 0.636  − 0.141 0.878 0.613* Item 1 0.436 0.044 0.631 0.597* Item 15 0.522 0.345 0.453 0.732* Item 9 0.452 0.296 0.446 0.683* Item 5 0.292 0.144 0.438 0.561* Item 11 0.449 0.334 0.408 0.690* *p < 0.01, r, item-total correlations According to the PAF method, the communalities of all items except item 5 (0.29) were higher than the threshold of 0.30. Since the factor loading of item 5 is higher than 0.40, it was decided to keep it in the scale. It is seen that item-total correlations ranged between 0.561 and 0.792. Also, the total variance explained by the first factor is 43.78%, the total variance explained by the second factor is 5.52%, and the total variance explained is 49.30%. Scree plot graphics obtained as a result of PAF and PA are given in Fig. 1.Fig. 1 Scree plots of C19-OCS When Fig. 1 is examined, it is seen that the data obtained from C19-OCS has a dominant factor. Considering the clustering of the items, it was determined that the items in the first dimension are related to obsessive thoughts, and the items in the second dimension are related to contamination fears and washing compulsion. Findings of convergent and discriminant validity Average variance extracted (AVE) values are calculated for convergent validity. The factor loadings required to calculate the AVE values were obtained from CFA. Since this research was studied with a single sample, the CFA results of C19-OCS were taken into account only in the calculation of AVE values. In other words, the goodness-of-fit values obtained from the CFA were not directly presented as proof of construct validity for C19-OCS. The most important reason for this is that searching EFA and CFA in the same data set will give biased results in favor of CFA. AVE values of C19-OCS were calculated as 0.53 for the first factor, and as 0.63 for the second factor. These values are higher than the cutoff point of 0.50 for convergent validity, and this finding shows that convergent validity is provided (Hair et al., 2019). For discriminant validity, the calculated AVE values and the correlation between the dimensions of C19-OCS were considered. The fact that the square roots of the AVE values calculated for the dimensions (0.73 and 0.79, respectively) are higher than the correlation values between the dimensions (0.71) can be presented as evidence of discriminative validity (Fornell & Larcker, 1981). Findings of CRV Table 8 shows the Pearson’s Product-Moment correlations between C19-OCS, BAI, and DOCS-C scale scores of the participants. It is determined that CF19-OCS has a significant, moderate, and positive trending relationship between BAI and DOCS-C. Significant correlation coefficients can be presented as evidence for the CRV of C19-OCS.Table 8 Correlations between C19-OCS, BAI, and DOCS-C 1 2 3 4 5 6 7 C19-OCS-obsessive thoughts (1) 1 C19-OCS-contamination fears and cleaning (2) 0.71** (0.67, 0.76) 1 C19-OCS-total (3) 0.95** (0.94, 0.96) 0.89** (0.87, 0.91) 1 BAI-SA (4) 0.54** (0.45, 0.62) 0.45** (0.37, 0.52) 0.54** (0.46, 0.61) 1 BAI-SS (5) 0.41** (0.32, 0.50) 0.37** (0.29, 0.44) 0.42** (0.34, 0.50) 0.78** (0.73, 0.82) 1 BAI-total (6) 0.52** (0.44, 0.60) 0.44** (0.37, 0.51) 0.53** (0.45, 0.59) 0.98** (0.97, 0.98) 0.90** (0.87, 0.92) 1 DOCS-C (7) 0.47** (0.39, 0.53) 0.49** (0.42, 0.56) 0.51** (0.44, 0.58) 0.36** (0.27, 0.44) 0.31** (0.23, 0.39) 0.36** (0.29, 0.44) 1 **p < 0.01, Bootstrap 95% confidence intervals reported in brackets Findings of lower–upper group differences As an additional proof of construct validity, upper and lower group differences were tested. In the data set, the first 27% group with the highest score from C19-OCS and the last 27% group with the lowest scores were determined. Whether there was a significant difference between the scores that these groups got from C19-OCS was determined by independent sample t-test. The results obtained are given in Table 9.Table 9 Independent sample t-tests of C19-OCS scores for lower–upper groups Groups N Mean Sd Q25 Q50 Q75 t pa Effect size C19-OCS/obsessive thoughts Lower 104 13.53 2.49 12.00 13.00 15.00  − 31.01 0.00** 4.45 Upper 104 31.69 5.20 28.00 31.00 36.00 C19-OCS/contamination fears and cleaning Lower 104 14.01 3.31 11.00 14.00 17.00  − 26.91 0.00** 3.87 Upper 104 25.17 2.38 24.00 25.00 27.00 C19-OCS/total Lower 104 27.54 4.37 24.00 29.00 31.00  − 37.23 0.00** 5.34 Upper 104 56.86 6.41 51.50 56.00 61.00 ap value for the independent samples t-test **p < 0.01 When Table 9 is examined, the scores of the participants in the upper group in the obsessive thoughts with contamination fears and washing compulsion dimensions of the C19-OCS scale and the whole scale are statistically significantly higher than the scores of the participants in the lower group. When the Cohen’s D effect size is taken into account, it is seen that the difference between upper and lower groups is in large effect size. Reliability studies The results obtained from various reliability analyses made for the reliability of the scores obtained from C19-OCS are given in Table 10.Table 10 Reliability findings of C19-OCS Cronbach α Guttman 2 λ LCRC CR ω r C19-OCS/obsessive thoughts 0.90 0.91 0.91* 0.92 0.90 0.76** C19-OCS/contamination fears and cleaning 0.82 0.82 0.81* 0.91 0.82 0.74** C19-OCS 0.92 0.92 0.92 0.95 0.92 0.78** *The coefficient was calculated separately for dimensions generated after EFA; r, test–retest reliability **p < 0.01 When the values given in Table 10 are examined, it is seen that the scores obtained for C19-OCS give reliable results. Reliability values obtained from different reliability coefficients are very close to each other. The lowest reliability estimation in Table 10 was obtained from the test–retest reliability estimation method. For test–retest reliability, C19-OCS was reapplied to 50 participants 2 weeks later. The correlation coefficients between pre-test and post-test scores of these participants were calculated. Although these values are lower compared to other reliability estimation methods, they are generally acceptable (> 0.70). According to the results obtained, C19-OCS is a measurement tool that provides valid and reliable results. While the lowest scores that can be obtained from this measurement tool are 10 for the obsessive thoughts dimension, six for the contamination fears and washing compulsion dimension, 16 for the whole scale, the highest scores that can be obtained from this measuring tool are 50 for the obsessive thoughts dimension, 30 for the contamination fears and washing compulsion dimension, and 80 for the whole scale. It can be said that as the scores obtained from the scale increase, the levels of obsessive thoughts with contamination fears and washing compulsion for COVID-19 increase in individuals. Discussion Due to the prevalence and persistence of the epidemic, peoples’ anxieties and fears of contamination are exacerbated because they are repeatedly exposed to anxiety provoking information about COVID-19. If the adverse psychological effects caused by COVID-19 are not identified and responded to quickly, there is a risk of long-term negative consequences for mental health. The C19-OCS was developed in the present study to measure obsessive thoughts associated with contamination fears and washing compulsions observed in people in relation to COVID-19. A series of psychometric analyses were performed to determine whether the scores obtained from the C19-OCS provide valid and reliable results. Individuals with aberrant item scores within the scope of NIRT were identified and excluded from the study. As a result of the investigation, a two-dimensional C19-OCS with a dominant factor was discovered. There are scales developed in the literature to determine the effects of COVID-19 on OC symptoms (Lee, 2020b; Taylor et al., 2020). The C19-OCS differs from other existing scales in the literature in that it measures both obsessive thoughts associated with contamination fears and washing compulsion associated with COVID-19, using a single scale and brief items in a valid and reliable manner. This feature of C19-OCS allows us to investigate the multidimensional effect of COVID-19 (Khosravani, et al., 2021) on OC symptoms in general. At the same time, the fact that the C19-OCS items are specifically related to COVID-19 will provide a more accurate representation of the severity of OC symptoms that began or worsened as a result of the pandemic. It is important to determine individuals’ psychological characteristics using measurement tools that provide valid and reliable results (Ransing et al., 2020). The investigation of the psychological effects of COVID-19, whose physiological effects on humans are well studied, is facilitated by the development of new COVID-19 measurement tools (Gasparro et al., 2020; Harper et al., 2021; Lee et al., 2021; Parlapani et al., 2020). During COVID-19, OC symptoms can to some extent serve a protective function as well as become a psychological problem (Meșterelu et al., 2021). When COVID-19-related OC symptoms worsen and have negative consequences, they become a permanent problem if not treated (Abba-Aji et al., 2020; Knowles & Olatunji, 2021). C19-OCS can be used to determine the severity of OC symptoms associated with COVID-19 in order to make preventive interventions or prevent symptom deterioration. There are some limitations of the study. First, the study group of the research is composed of mostly university students, although they are in a wide age range. In that respect, it is recommended that the factor structure of the scale in large groups is investigated, and the scale is monitored. Second, the data of the study was obtained from the non-clinical group. It is recommended that clinical groups are contacted. Third is the C19-OCS self-report measurement tool. When responding to self-report measurement tools, several factors such as social desirability can be influential. In this study, individuals with aberrant item scores were identified and excluded from the analysis. Future studies can include measures of social desirability responding. Despite these limitations, the study’s findings show that C19-OCS produces reliable and valid results when measuring obsessive thoughts associated with contamination fears and washing compulsions associated with COVID-19. C19-OCS can assist mental health professionals in identifying COVID-19-related OC symptoms. Furthermore, the C19-OCS can be used to develop evidence-based intervention strategies and programs. We also anticipate that C19-OCS may be useful in the future to evaluate OC symptoms associated with COVID-19-like outbreaks (e.g., mode of transmission, rate of spread). Evidence for the construct validity of the C19-OCS should be obtained after the items have been updated to reflect the new outbreak. Appendix Table 11Table 11 Items of C19-OCS This measurement tool includes items related to the anxieties experienced after the COVID-19 pandemic. Please read each item carefully and answer how much you agree with the statement in the relevant item based on your experiences in the last month. Strongly disagree Disagree Undecided Agree Strongly agree Item 1 I am afraid of catching COVID-19 myself 1 2 3 4 5 Item 2 The thought of getting COVID-19 prevents me from doing my work 1 2 3 4 5 Item 4 I lose sleep thinking that I will catch COVID-19 1 2 3 4 5 Item 5 I am afraid of having infected someone with COVID-19 unknowingly 1 2 3 4 5 Item 6 I am experiencing physical symptoms (e.g., heart palpitations, difficulty breathing, sweating) when I think I will get COVID-19 1 2 3 4 5 Item 7 I avoid places where people are not even present thinking I may get COVID-19 1 2 3 4 5 Item 8 I am terrified that someone I know will get COVID-19 1 2 3 4 5 Item 9 I am afraid that I will not be able to cope with it if I get COVID-19 1 2 3 4 5 Item 10 I constantly research about COVID-19 1 2 3 4 5 Item 11 I wash my hands excessively for fear of catching COVID-19 1 2 3 4 5 Item 12 I feel overwhelmed from using chemical products such as cologne, bleach, disinfectant frequently to avoid catching COVID-19 1 2 3 4 5 Item 13 I do not feel at ease no matter how much I clean 1 2 3 4 5 Item 14 I am tired of the negative thoughts about COVID-19 that come to my mind inadvertently during the day 1 2 3 4 5 Item 15 I am afraid that I will get COVID-19 when I go out even if I avoid any contact 1 2 3 4 5 Item 16 I spend most of my time thinking whether I caught COVID-19 during the day 1 2 3 4 5 Item 17 I often find it difficult to keep negative thoughts about COVID-19 away from my mind 1 2 3 4 5 Data Availability The datasets analyzed during the current study are available from the corresponding author on reasonable request. Declarations Ethics Approval Ethics approval to conduct the study was received from the Recep Tayyip Erdoğan University Social and Humanities Ethics Committee (Reference Number: 2020/104). Conflict of Interest The authors declare no competing interests. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Aardema, F. (2020). COVID-19, obsessive-compulsive disorder and invisible life forms that threaten the self. Journal of Obsessive-Compulsive and Related Disorders, 26, Article 100558. 10.1016/j.jocrd.2020.100558 Abba-Aji, A., Li, D. I., Hrabok, M., Shalaby, R., Gusnowski, A., Vuong, W., Surood, S., Nkire, N., Li, X. M., Greenshaw, A. J., & Agyapong, V. I. O. (2020). COVID-19 pandemic and mental health: Prevalence and correlates of new-onset obsessive-compulsive symptoms in a Canadian province. International Journal of Environmental Research and Public Health, 17(19), 1–11, Article 6986. 10.3390/ijerph17196986 Abramowitz JS Deacon BJ Olatunji BO Wheaton MG Berman NC Losardo D Timpano KR McGrath PB Riemann BC Adams T Bjorgvinsson T Storch EA Hale LR Assessment of obsessive-compulsive symptom dimensions: Development and evaluation of the Dimensional Obsessive-Compulsive Scale Psychological Assessment 2010 22 1 180 198 10.1037/a0018260 20230164 Adhikari, S. P., Meng, S., Wu, Y. J., Mao, Y. P., Ye, R. X., Wang, Q. Z., Sun, C., Sylvia, S., Rozelle, S., Raat, H., & Zhou, H. (2020). Epidemiology, causes, clinical manifestation and diagnosis, prevention and control of coronavirus disease (COVID-19) during the early outbreak period: A scoping review. Infectious Diseases of Poverty, 9(1). 10.1186/s40249-020-00646-x Ahorsu DK Lin CY Imani V Saffari M Griffiths MD Pakpour AH The fear of COVID-19 scale: Development and initial International Journal of Mental Health and Addiction 2022 20 3 1537 1545 10.1007/s11469-020-00270-8 32226353 Alateeq, D. A., Almughera, H. N., Almughera, T. N., Alfedeah, R. F., Nasser, T. S., & Alaraj, K. A. (2021). The impact of the coronavirus (COVID-19) pandemic on the development of obsessive-compulsive symptoms in Saudi Arabia. Saudi Medical Journal, 42(7), 750–760. 10.15537/smj.2021.42.7.20210181 Alimoradi, Z., Ohayon, M. M., Griffiths, M. D., Lin, C. Y., & Pakpour, A. H. (2022). Fear of COVID-19 and its association with mental health-related factors: Systematic review and meta-analysis. Bjpsych Open, 8(2), 1–26, Article e73. 10.1192/bjo.2022.26 American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5) (5th ed.). American Psychiatric Publishing. 10.1176/appi.books.9780890425596 Arpaci, I., Karatas, K., & Baloglu, M. (2020). The development and initial tests for the psychometric properties of the COVID-19 Phobia Scale (C19P-S). Personality and Individual Differences, 164, Article 110108. 10.1016/j.paid.2020.110108 Beck AT Brown G Epstein N Steer RA An inventory for measuring clinical anxiety: Psychometric properties Journal of Consulting and Clinical Psychology 1988 56 6 893 897 10.1037/0022-006x.56.6.893 3204199 Belen H Fear of COVID-19 and mental health: The role of mindfulness in during times of crisis International Journal of Mental Health and Addiction 2022 20 1 607 618 10.1007/s11469-020-00470-2 33935608 Chou YH Lee CP Liu CY Hung CI Construct validity of the depression and somatic symptoms scale: Evaluation by Mokken scale analysis Neuropsychiatric Disease and Treatment 2017 13 205 211 10.2147/Ndt.S118825 28182138 Crișan, D. R., Tendeiro, J., & Meijer, R. (2019). The crit value as an effect size measure for violations of model assumptions in Mokken scale analysis for binary data. 10.31234/osf.io/8ydmr de Vroege, L., Emons, W. H. M., Sijtsma, K., & van der Feltz-Cornelis, C. M. (2018). Alexithymia has no clinically relevant association with outcome of multimodal treatment tailored to needs of patients suffering from somatic symptom and related disorders. A clinical prospective study. Frontiers in Psychiatry, 9, Article 292. 10.3389/fpsyt.2018.00292 Demaria, F., Pontillo, M., Di Vincenzo, C., Di Luzio, M., & Vicari, S. (2022). Hand washing: When ritual behavior protects! Obsessive-compulsive symptoms in young people during the COVID-19 pandemic: A narrative review. Journal of Clinical Medicine, 11, Article 3191. 10.3390/jcm11113191 Emons WHM Nonparametric person-fit analysis of polytomous item scores Applied Psychological Measurement 2008 32 3 224 247 10.1177/0146621607302479 Fischer C Gyekye-Mensah H Pampaloni I Chandler A Govender A Sibanda-Mbanga J A preliminary study into the effects of the COVID-19 pandemic on Yale-Brown Obsessive Compulsive Scale (Y-BOCS) scores of patients with obsessive compulsive disorder Bjpsych Open 2021 7 Suppl 1 S249 S250 10.1192/bjo.2021.668 Fitzpatrick KM Harris C Drawve G Fear of COVID-19 and the mental health consequences in America Psychological Trauma: Theory Research Practice and Policy 2020 12 S1 17 21 10.1037/tra0000924 Fontenelle LF Miguel EC The impact of coronavirus (COVID-19) in the diagnosis and treatment of obsessive-compulsive disorder Depression and Anxiety 2020 37 6 510 511 10.1002/da.23037 32383802 Fontenelle LF Albertella L Brierley ME Thompson EM Destree L Chamberlain SR Yucel M Correlates of obsessive-compulsive and related disorders symptom severity during the COVID-19 pandemic Journal of Psychiatric Research 2021 143 471 480 10.1016/j.jpsychires.2021.03.046 33958180 Fornell C Larcker DF Evaluating structural equation models with unobservable variables and measurement error Journal of Marketing Research 1981 18 1 39 50 10.2307/3151312 Garcia R Neurobiology of fear and specific phobias Learning & Memory 2017 24 9 462 471 10.1101/lm.044115.116 28814472 Gasparro, R., Scandurra, C., Maldonato, N. M., Dolce, P., Bochicchio, V., Valletta, A., Sammartino, G., Sammartino, P., Mariniello, M., di Lauro, A. E., & Marenzi, G. (2020). Perceived job insecurity and depressive symptoms among Italian dentists: The moderating role of fear of COVID-19. International Journal of Environmental Research and Public Health, 17(15), Article 5338. 10.3390/ijerph17155338 Grant JE Drummond L Nicholson TR Fagan H Baldwin DS Fineberg NA Chamberlain SR Obsessive-compulsive symptoms and the Covid-19 pandemic: A rapid scoping review Neuroscience and Biobehavioral Reviews 2022 132 1086 1098 10.1016/j.neubiorev.2021.10.039 34740755 Guzick, A. G., Candelari, A., Wiese, A. D., Schneider, S. C., Goodman, W. K., & Storch, E. A. (2021). Obsessive–compulsive disorder during the COVID‑19 pandemic: A systematic review. Current Psychiatry Reports, 23(11), Article 71. 10.1007/s11920-021-01284-2 Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Annabel Ainscow. Harper CA Satchell LP Fido D Latzman RD Functional fear predicts public health compliance in the COVID-19 pandemic International Journal of Mental Health and Addiction 2021 19 5 1875 1888 10.1007/s11469-020-00281-5 32346359 Idrees, M., Asif, M., & Ghazal, S. (2022). Effect of risk perceptions, fear and myths about Covid-19 infection susceptibility on protective behaviors in Pakistan. Asean Journal of Psychiatry, 23(2), 1–8. 10.54615/2231-7805.47324 Jelinek, L., Moritz, S., Miegel, F., & Voderholzer, U. (2021a). Obsessive-compulsive disorder during COVID-19: Turning a problem into an opportunity? Journal of Anxiety Disorders, 77. 10.1016/j.janxdis.2020.102329 Jelinek, L., Goritz, A. S., Miegel, F., Moritz, S., & Kriston, L. (2021b). Predictors of trajectories of obsessive-compulsive symptoms during the COVID-19 pandemic in the general population in Germany. Translational Psychiatry, 11, Article 323. 10.1038/s41398-021-01419-2 Khan YS Jouda M Albobali Y Abouelseoud MO Souid A AlMeraisi MJ Alabdulla M COVID-19 pandemic fears and obsessive-compulsive symptoms in adolescents with pre-existing mental disorders: An exploratory cross-sectional study Clinical Child Psychology and Psychiatry 2022 27 1 89 103 10.1177/13591045211017606 34049450 Khosravani, V., Aardema, F., Ardestani, S. M. S., & Bastan, F. S. (2021). The impact of the coronavirus pandemic on specific symptom dimensions and severity in OCD: A comparison before and during COVID-19 in the context of stress responses. Journal of Obsessive-Compulsive and Related Disorders, 29(19), Article 100626. 10.1016/j.jocrd.2021.100626 Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). Guilford Publications. Knowles, K. A., & Olatunji, B. O. (2021). Anxiety and safety behavior usage during the COVID-19 pandemic: The prospective role of contamination fear. Journal of Anxiety Disorders, 77(1), Article 102323. 10.1016/j.janxdis.2020.102323 Lawshe CH A quantitative approach to content validity Personnel Psychology 1975 28 4 563 575 10.1111/j.1744-6570.1975.tb01393.x Lee SA Coronavirus anxiety scale: A brief mental health screener for COVID-19 related anxiety Death Studies 2020 44 7 393 401 10.1080/07481187.2020.1748481 32299304 Lee SA How much “Thinking” about COVID-19 is clinically dysfunctional? Brain Behavior and Immunity 2020 87 97 98 10.1016/j.bbi.2020.04.067 32353520 Lee SRA Jobe MC Mathis AA Mental health characteristics associated with dysfunctional coronavirus anxiety Psychological Medicine 2021 51 8 1403 1404 10.1017/S003329172000121x 32297852 Linde, E. S., Varga, T. V., & Clotworthy, A. (2022). Obsessive-compulsive disorder during the COVID-19 pandemic—A systematic review. Frontiers in Psychiatry, 13, Article 806872. 10.3389/fpsyt.2022.806872 Liu, T., Sun, Y. C., Li, Z., & Xin, T. (2019). The impact of aberrant response on reliability and validity. Measurement: Interdisciplinary Research and Perspectives, 17(3), 133–142. 10.1080/15366367.2019.1584848 Mataix-Cols, D., do Rosario-Campos, M. C., & Leckman, J. F. (2005). A multidimensional model of obsessive-compulsive disorder. American Journal of Psychiatry, 162(2), 228-238.10.1176/appi.ajp.162.2.228 Matsunaga H Mukai K Yamanishi K Acute impact of COVID-19 pandemic on phenomenological features in fully or partially remitted patients with obsessive–compulsive disorder Psychiatry and Clinical Neurosciences 2020 74 10 565 566 10.1111/pcn.13119 32697002 Meijer RR Person-fit research: An introduction Applied Measurement in Education 1996 9 1 3 8 10.1207/s15324818ame0901_2 Meijer RR Baneke JJ Analyzing psychopathology items: A case for nonparametric item response theory modeling Psychological Methods 2004 9 3 354 368 10.1037/1082-989x.9.3.354 15355153 Meșterelu, I., Rîmbu, R., Blaga, P., & Stefan, S. (2021). Obsessive-compulsive symptoms and reactions to the COVID-19 pandemic. Psychiatry Research, 302, Article 114021. 10.1016/j.psychres.2021.114021 Moreira-de-Oliveira ME de Menezes GB Loureiro CD Laurito LD Albertella L Fontenelle LF The impact of COVID-19 on patients with OCD: A one-year follow-up study Journal of Psychiatric Research 2022 147 307 312 10.1016/j.jpsychires.2022.01.065 35123340 Nissen, J. B., Hojgaard, D. R. M. A., & Thomsen, P. H. (2020). The immediate effect of COVID-19 pandemic on children and adolescents with obsessive compulsive disorder. Bmc Psychiatry, 20, Article 511. 10.1186/s12888-020-02905-5 Pacitti F Socci V D’Aurizio G Jannini TB Rossi A Siracusano A Rossi R Di Lorenzo G Obsessive-compulsive symptoms among the general population during the first COVID-19 epidemic wave in Italy Journal of Psychiatric Research 2022 153 18 24 10.1016/j.jpsychires.2022.06.043 35792342 Pan KY Kok AAL Eikelenboom M Horsfall M Jorg F Luteijn RA Rhebergen D van Oppen P Giltay EJ Penninx BWJH The mental health impact of the COVID-19 pandemic on people with and without depressive, anxiety, or obsessive-compulsive disorders: A longitudinal study of three Dutch case-control cohorts Lancet Psychiatry 2021 8 2 121 129 10.1016/S2215-0366(20)30491-0 33306975 Parlapani, E., Holeva, V., Voitsidis, P., Blekas, A., Gliatas, I., Porfyri, G. N., Golemis, A., Papadopoulou, K., Dimitriadou, A., Chatzigeorgiou, A. F., Bairachtari, V., Patsiala, S., Skoupra, M., Papigkioti, K., Kafetzopoulou, C., & Diakogiannis, I. (2020). Psychological and behavioral responses to the COVID-19 pandemic in Greece. Frontiers in Psychiatry, 11, Article 821. 10.3389/fpsyt.2020.00821 Pérez-Fuentes, M. D., Jurado, M. D. M., Ruiz, N. F. O., Martos Martínez, Á. M., Simón Márquez, M. D. M., Herrera-Peco, I., & Gázquez Linares, J. J. (2020). Questionnaire on perception of threat from COVID-19. Journal of Clinical Medicine, 9(4), Article 1196. 10.3390/jcm9041196 Ransing R Ramalho R Orsolini L Adiukwu F Gonzalez-Diaz JM Larnaout A da Costa MP Grandinetti P Bytyci DG Shalbafan M Patil I Nofal M Pereira-Sanchez V Kilic O Can COVID-19 related mental health issues be measured? Brain Behavior and Immunity 2020 88 32 34 10.1016/j.bbi.2020.05.049 32470593 Şafak Y Say Öcal D Özdel K Kuru E Örsel S Obsesif kompülsif bozuklukta boyutsal yaklaşım: Boyutsal Obsesif Kompülsif Bozukluk Ölçeği Türkçe’nin psikometrik özellikleri [Dimensional approach to obsessive-compulsive disorder: Dimensional Obsessive-Compulsive Scale with Turkish psychometric properties] Türk Psikiyatri Dergisi [turkish Journal of Psychiatry] 2018 29 2 122 130 30215841 Schmidt NB Allan NP Koscinski B Mathes BM Eackles K Accorso C Saulnier KG Allan DM Potter K Garey L Suhr J Austin M Zvolensky MJ COVID-19 impact battery: Development and validation Journal of Psychopathology and Behavioral Assessment 2022 44 2 326 343 10.1007/s10862-021-09919-7 34518734 Schwartz-Lifshitz, M., Basel, D., Lang, C., Hertz-Palmor, N., Dekel, I., Zohar, J., & Gothelf, D. (2021). Obsessive compulsive symptoms severity among children and adolescents during COVID-19 first wave in Israel. Journal of Obsessive-Compulsive and Related Disorders, 28,. 10.1016/j.jocrd.2020.100610 Şengül Avşar A Aberrant individuals’ effects on fit indices both of confirmatory factor analysis and polytomous IRT models Current Psychology 2021 10.1007/s12144-021-01563-4 Sharma LP Balachander S Thamby A Bhattacharya M Kishore C Shanbhag V Sekharan JT Narayanaswamy JC Arumugham SS Reddy JYC Impact of the COVID-19 pandemic on the short-term course of obsessive-compulsive disorder Journal of Nervous and Mental Disease 2021 209 4 256 264 10.1097/Nmd.0000000000001318 33625069 Sijtsma K van der Ark LA A tutorial on how to do a Mokken scale analysis on your test and questionnaire data British Journal of Mathematical and Statistical Psychology 2017 70 1 137 158 10.1111/bmsp.12078 27958642 Sijtsma K Emons WHM Bouwmeester S Nyklicek I Roorda LD Nonparametric IRT analysis of Quality-of-Life Scales and its application to the World Health Organization Quality-of-Life Scale (WHOQOL-Bref) Quality of Life Research 2008 17 2 275 290 10.1007/s11136-007-9281-6 18246447 Sijtsma, K., & Molenaar, I. W. (2002). Introduction to nonparametric item response theory. Sage Publications. Silva RM Shavitt RG Costa DL Obsessive-compulsive disorder during the COVID19 pandemic Brazillian Journal of Psychiatry 2021 43 1 108 117 10.1590/1516-4446-2020-1189 Silverman ME Nag S Kalishman A Cox PH Mitroff SR Increases in symptoms associated with obsessive-compulsive disorder among university students during the COVID-19 pandemic Journal of American College Health 2022 10.1080/07448481.2022.2080507 Simsir Z Koc H Seki T Griffiths MD The relationship between fear of COVID-19 and mental health problems: A meta-analysis Death Studies 2022 46 3 515 523 10.1080/07481187.2021.1889097 33641626 Sodano SM Tracey TJG Hafkenscheid A A brief Dutch language Impact Message Inventory-Circumplex (IMI-C Short) using nonparametric item response theory Psychotherapy Research 2014 24 5 616 628 10.1080/10503307.2013.847984 24188739 Stochl, J., Jones, P. B., & Croudace, T. J. (2012). Mokken scale analysis of mental health and well-being questionnaire item responses: A non-parametric IRT method in empirical research for applied health researchers. BMC Medical Research Methodology, 12, Article 74. 10.1186/1471-2288-12-74 Tanir, Y., Karayagmurlu, A., Kaya, I., Kaynar, T. B., Turkmen, G., Dambasan, B. N., Meral, Y., & Coskun, M. (2020). Exacerbation of obsessive compulsive disorder symptoms in children and adolescents during COVID-19 pandemic. Psychiatry Research, 293, Article 113363. 10.1016/j.psychres.2020.113363 Taylor, S., Landry, C. A., Paluszek, M. M., Fergus, T. A., McKay, D., & Asmundson, G. J. G. (2020). Development and initial validation of the COVID Stress Scales. Journal of Anxiety Disorders, 72, Article 102232. 10.1016/j.janxdis.2020.102232 Taylor, S. (2019). The psychology of pandemics: Preparing for the next global outbreak of infectious disease. Cambridge Scholars. Theberath, M., Bauer, D., Chen, W. Z., Salinas, M., Mohabbat, A. B., Yang, J., Chon, T. Y., Bauer, B. A., & Wahner-Roedler, D. L. (2022). Effects of COVID-19 pandemic on mental health of children and adolescents: A systematic review of survey studies. Sage Open Medicine, 10,. 10.1177/20503121221086712 Tompkins, M. A. (2013). Anxiety and avoidance: A universal treatment for anxiety, panic, and fear. New Harbinger Publications, Inc. Ulusoy M Sahin NH Erkmen H Turkish version of the Beck Anxiety Inventory: Psychometric properties Journal of Cognitive Psychotherapy: An International Quarterly 1998 12 2 163 172 van der Ark, L. A., Letty Koopman, L., H., S. J., & D., v. d. B. (2020). Conducts Mokken Scale Analysis [PDF file]. Retrieved May 15, 2020, from https://cran.r-project.org/web/packages/mokken/mokken.pdf Vaughan, B., & Grace, S. (2018). A Mokken scale analysis of the peer physical examination questionnaire. Chiropractic & Manual Therapies, 26, Article 6. 10.1186/s12998-018-0176-0 Wang YH Shi L Que JY Lu QD Liu L Lu ZA Xu YY Liu JJ Sun YK Meng SQ Yuan K Ran MS Lu L Bao YP Shi J The impact of quarantine on mental health status among general population in China during the COVID-19 pandemic Molecular Psychiatry 2021 26 9 4813 4822 10.1038/s41380-021-01019-y 33483692 West SG Finch JF Curran PJ Hoyle RH Structural equation models with nonnormal variables: Problems and remedies Structural equation modeling: Concepts, issues, and applications 1995 Sage Publications Inc 56 75 World Health Organization. (2022a). WHO coronavirus (COVID-19) dashboard. Retrieved November 28, from https://covid19.who.int/ World Health Organization. (2022b). Coronavirus disease (COVID-19): How is it transmitted? Retrieved July 2022, from https://www.who.int/news-room/questions-and-answers/item/coronavirus-disease-covid-19-how-is-it-transmitted Zhou, P., Yang, X. L., Wang, X. G., Hu, B., Zhang, L., Zhang, W., Si, H. R., Zhu, Y., Li, B., Huang, C. L., Chen, H. D., Chen, J., Luo, Y., Guo, H., Jiang, R. D., Liu, M. Q., Chen, Y., Shen, X. R., Wang, X., … & Shi, Z. L. (2020). A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature, 579, 270–273. 10.1038/s41586-020-2012-7
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==== Front Can J Public Health Can J Public Health Canadian Journal of Public Health = Revue Canadienne de Santé Publique 0008-4263 1920-7476 Springer International Publishing Cham 36508153 717 10.17269/s41997-022-00717-6 Population Health Intervention Research The Victoria Assistive Devices and Coach (VADAC) study http://orcid.org/0000-0002-5982-8879 McGowan Patrick [email protected] 1 https://orcid.org/0000-0001-8923-4337 Hofer Scott 2 1 grid.143640.4 0000 0004 1936 9465 Institute on Aging & Lifelong Health, University of Victoria, Suite 210, 4907 Chisholm Street, Delta, BC V4K 2K6 Canada 2 grid.143640.4 0000 0004 1936 9465 Institute on Aging & Lifelong Health, University of Victoria, R Hut, PO Box 1700 STN CSC, Victoria, BC V8W 2Y2 Canada 12 12 2022 114 20 10 2021 25 10 2022 © The Author(s) under exclusive license to The Canadian Public Health Association 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Intervention A 90-day intervention employed peer coaching, with and without home-based electronic devices connected to an app, to assess effectiveness in enhancing self-reported health outcomes of older adults. Research question Does peer coaching aid older adults to better manage their chronic health conditions, and is the coaching further enhanced by home-based electronic devices? Methods The study employed a pre-post intervention randomized controlled trial design with three groups: control (no coach, no devices), coach only, and coach + devices. Participants were 163 adults living in British Columbia, Canada, aged 65 to 98 years, with one or more chronic health conditions and access to a computer and Wi-Fi. Responses on five questionnaires assessed health outcomes pre- and post-intervention: Self-Efficacy Scale, PHQ-9, Medical Care, Patient Activation Measure and the RAND 36-Item Health Survey 1.0 Questionnaire. Results Compared with the control group (no coach, no devices), participants with a coach reported decreased depression, higher activation levels and energy levels, and better handling of role limitations due to physical health, social functioning, and communication with their physician. Participants with coaches and devices showed similar improvements on these measures with further decreases in depression severity as well as improved self-efficacy, better handling of role limitations due to emotional problems, higher level of emotional well-being and general health ratings, and lower pain. Conclusion Peer coaches alone and in combination with assistive devices demonstrated several positive outcomes for older persons with chronic conditions that lasted at least 90 days. The program can enhance effectiveness of care provided by general practitioners. Résumé Intervention Une intervention de 90 jours a employé l’encadrement des pairs, avec et sans appareils électroniques à la maison connectés à une application, pour évaluer l’efficacité de l’amélioration des résultats cliniques autodéclarés d’adultes d’âge mûr. Question de recherche L’encadrement des pairs aide-t-il les adultes d’âge mûr à mieux prendre en charge leurs affections chroniques, et cet encadrement est-il renforcé par l’utilisation d’appareils électroniques à la maison? Méthode L’étude a employé un plan d’essai comparatif randomisé avant et après l’intervention avec trois groupes : un groupe témoin (sans pair aidant, sans appareils), un groupe avec pair aidant seulement et un groupe avec pair aidant et appareils. Les participants étaient 163 adultes de 65 à 98 ans vivant en Colombie-Britannique, au Canada, présentant une ou plusieurs affections chroniques et ayant accès à un ordinateur et au Wi-Fi. Les résultats cliniques avant et après l’intervention ont été analysés d’après les réponses à cinq questionnaires : échelle d’auto-efficacité, Patient Health Questionnaire (PHQ-9), questionnaire Medical Care, Patient Activation Measure et Questionnaire Rand de 36 questions sur l’état de santé (version 1.0). Résultats Comparativement au groupe témoin (sans pair aidant, sans appareils), les participants encadrés par un pair aidant ont déclaré une dépression réduite, des niveaux d’activation et d’énergie plus élevés et une meilleure gestion de leurs limites fonctionnelles dues à leur santé physique, à leur fonctionnement social et à leurs communications avec leurs médecins. Les participants ayant un pair aidant et des appareils ont présenté des améliorations semblables de ces indicateurs, avec des réductions plus poussées de la sévérité de la dépression, ainsi qu’une auto-efficacité améliorée, une meilleure gestion de leurs limites fonctionnelles dues aux troubles affectifs, de plus hauts niveaux de bien-être émotionnel et de santé générale, et moins de douleur. Conclusion Les pairs aidants à eux seuls et en combinaison avec des accessoires fonctionnels sont à l’origine de plusieurs résultats positifs pour les personnes d’âge mûr atteintes d’affections chroniques ayant duré au moins 90 jours. Le programme peut améliorer l’efficacité des soins offerts par les omnipraticiens. Keywords Elderly Chronic disease Coaching Assistive devices Randomized controlled trial Patient-reported outcome measures Mots-clés Personne âgée maladie chronique encadrement appareils fonctionnels essai contrôlé randomisé indicateurs de résultats déclarés par les patients http://dx.doi.org/10.13039/501100000024 Canadian Institutes of Health Research 143564 Hofer Scott ==== Body pmcIntroduction Chronic pain, restricted mobility, and depressive feelings and emotions all take a toll on patients’ quality of life and health outcomes as well as the broader health care system in terms of possibly reducing hospitalization rates and associated costs. Increased ability to manage these problems, therefore, clearly has many broad benefits for individuals and society. During the past decade, research studies have consistently found that individual management and outcomes of chronic disease are enhanced through the use of peer and professionally-led self-management education (Cheng et al., 2017; Chrvala et al., 2016; Brady et al., 2013). Using another model, telephone peer coaching, clinicians, and peers have also demonstrated effectiveness in bringing about improved outcomes (Gagliardino et al., 2013; McGowan et al., 2019; Thom et al., 2013; Walker et al., 2011; Wolever et al., 2010). Peer coaching has been shown to be effective with several health conditions. A review (Elstad et al., 2010) of 47 papers from eight countries that looked at pre/post-natal care, diabetes, asthma, cardiovascular disease, HIV, smoking cessation, mental health, and drug use reported that 83% of the studies reported significant between-group or pre-post changes showing benefits of peer support, across different age demographics. Recently, with the advent of smart technology, the use of home-based electronic devices is becoming popular; however, digital medicine is a young field, and little of the research focuses on older adults with chronic illnesses (Denton & Spencer, 2010). The present study was conducted as part of a larger initiative of expanding digital medicine and bridging peer coaching programs with the electronic assistance aimed to assess the impacts of peer coaching, with and without the additional use of electronic devices, on a number of outcome measures in older adults experiencing chronic health conditions. A randomized controlled trial design was used to evaluate whether integrated electronic home monitoring improved health outcomes and self-management over and above only using the Self-Management Telephone Health Coach Program. This program is a free, individualized telephone program comprised of weekly 30-min calls between a participant and a trained peer self-management coach. Coaches telephone their assigned participants once a week for 12 consecutive weeks and inquire how they are managing their chronic conditions, medications, and other general life challenges. When participants identify a problem, coaches assist them in following problem-solving steps to select an action to take to resolve it. Coaches then encourage and assist participants to develop an “action plan” to complete the activity during the following week. A summary of the Self-Management BC Health Coach Program can be found at http://www.selfmanagementbc.ca/healthcoachprogram. Ethical approval to conduct the research was acquired from the Joint Island Health and University Research Ethics Board. Methods Participants The target population of the research was older adults with one or more chronic conditions, living in their own homes and having access to the internet and Wi-Fi. Government Health data was used to estimate that 125,805 older persons lived in this geographic area. Several methods were used to recruit participants from this target population, including newspaper ads, posters, and flyers; radio and internet; in-person and virtual presentations to older person groups and health professionals; and collaborations with community organizations that provided coordination and assistance to older people. Persons who met the inclusion criteria (e.g., hearing, comprehension, etc.) completed a Study Consent Form and a questionnaire which served as the baseline assessment for data analyses. When the consent form and questionnaire were returned, persons were randomized to one of three study groups. One hundred ninety-three participants were recruited to the study and assigned to one of three groups, a control group and two treatment groups (coach only and coach + devices), using a blocked randomization technique (Efird, 2011). This randomization method maximizes the similarity of the three groups with regard to known and unknown factors while keeping the group sizes equal at baseline. Furthermore, in longitudinal studies, randomly assigning participants across the different treatment groups as they enter the study is also desirable as this controls for external factors such as seasons/weather and historical factors (e.g., changes in government policies) that may potentially and inadvertently impact the key outcome measures. In our case, this was particularly fortuitous because the COVID-19 pandemic hit about halfway through recruitment into our study. Furthermore, we chose larger blocks of participants (blocks of 15) and pseudo-randomized the orders of assignment to always assign participants to the two treatment groups that use trained peer coaches first, to maximize the coaches’ availability and maintain their interest in the study. Persons randomized to the control group received a participant book entitled Living a Healthy Life with Chronic Conditions (Lorig et al., 2020) or Living a Healthy Life with Chronic Pain (LeFort et al., 2015) and were placed on a 3-month waitlist to receive a coach. Members of this group completed the questionnaire again 3 months later and received a $25 honorarium each time they completed the questionnaire. Participants randomized to the coach-only group also received a participant book and were paired with a coach. Participants and coaches were matched based on background collected for eligibility. In this group, coaches telephoned participants and conversed for approximately 30 min weekly for a period of 3 months. Participants in this group also completed the questionnaire again 3 months after baseline, and received a $25 honorarium. Participants randomized to the coach + devices group received the participant book and were matched with a coach, similar to the process used in the coach-only group. Each person also received three assistive devices, namely (a) a steel wrist-worn watch which collects physical activity and sleep data; (b) Body+ Scale, a scale which tracks weight, heart rate, body composition (such as bone density), and environmental data (such as weather and air quality); and (c) Nokia Sleep, a sleep-tracking pad that is installed underneath the participant’s mattress that tracks sleep cycles (deep, light, REM), sleep onset and duration, and sonority quality and provides an overall sleep quality score. Data collected by the devices is sent via Bluetooth Low Energy to a Health Mate app downloaded onto a smartphone or tablet computer. Before the COVID interruption (prior to March 2020), the devices were installed by the devices coordinator who visited participants in their homes. After August 2020, when the study resumed following a 5-month recruitment stoppage due to the COVID-19 pandemic, devices were installed in participants’ homes through telephone and online communication between the devices coordinator and participant. Participants in this coach + devices group also completed the questionnaire again 3 months after their baseline assessment, and received a $25 honorarium. Health coaches Coach recruitment included advertising in newsletters, websites and community newspapers, posters, and brochures. Interested candidates were registered into a 2-day coach-training workshop. Each trainee received a copy of the Self-Management Health Coach Program Coach Manual (Self-Management BC, 2020). In the training, coaching role, expectation, commitment, and core functions were explained and trainees practiced key self-management strategies, namely problem solving and action planning. Basic and complex scenarios were used to generate resolution of difficult situations. The training concluded with a review of self-compassion; effective communication techniques; a review of information in participants’ books; key community resources; potential coaching challenges; personal safety; a Coach Code of Conduct; and Key Points for Self-Management Health Coaching. Twelve in-person workshops were delivered prior to March 2020 which trained 82 coaches. Because of COVID, participant recruitment discontinued for approximately 5 months mainly because the devices coordinator was unable to enter participants’ homes. Following the re-start in August, three additional sessions which trained 14 new coaches were delivered through virtual 2-day webinars. In total, 96 persons completed the coach training. Coach-participant pairing After completing the training, coaches and participants were paired on the basis of gender, age, and interests. The first regularly scheduled coach-participant phone call was scheduled by the coach coordinator. Weekly phone calls lasted a minimum of 30 min. During the 3-month intervention, either the coach coordinator or project lead called coaches three times to provide support, problem solve, and ensure program fidelity. These calls addressed difficulties coaches had getting their participants to describe problems managing their condition(s) and their medications, in their home and family environment, and in making weekly action plans describing the steps they would take to solve the problem. Coaches received an honorarium of $72 at the end of the 3 months of the study. Outcome measures These measures were chosen because they have been used in our prior studies, have been validated, and assess the specific outcomes of interest. Our prior experience with these measures also indicates that participants are comfortable with the length of the battery, and as noted above, participants were compensated each time they complete the battery. Self-efficacy scale (Lorig et al., 1996) This is a 6-item scale, with responses ranging from 1 (not at all confident) to 10 (totally confident). Responses are added to produce a total score for each participant. Scores can range from 6 to 60, with higher scores indicating higher self-efficacy. Depression Severity Measure (PHQ-9) (Kroenke et al., 2001) A 9-item scale, asking respondents to rate how often they experience a number of negative feelings in the past 2 weeks (e.g., little interest or pleasure in doing things; feeling down, depressed, or hopeless; trouble falling/staying asleep; etc.). Responses range from not at all (0) to nearly every day (3). Responses are added, and total score can range from 0 to 27, with higher scores indicating more frequent negative feelings. One additional overall item is also asked at the end, where the respondent is asked to indicate, on a 4-point response scale, how difficult the negative feelings make it for them to work, take care of things at home, or get along with other people, ranging from not difficult at all (0) to extremely difficult (4). Medical care (Lorig et al., 1996) Three items ask about communicating with their doctor. These ask about preparing a list of questions; asking about things the respondent wants to know about or does not understand about their treatment; and discussing any personal problems related to their illness. Responses range from never (0) to always (5). The three responses are summed to give an overall score, ranging from 0 to 15. Three questions ask about health care services utilization in the past 6 months (Thom et al., 2013): the number of visits with a physician; number of visits to an emergency room; and number of nights spent in hospital. These are treated as individual outcome measures. Health literacy (Chew et al., 2008) Three follow-up questions ask about communication and visits: how often does someone help you read hospital materials; how often do you have problems learning about your medical condition; and how confident are you in filling out forms by yourself. Responses range from always (1) to never (5). These are treated as separate outcome measures. Patient Activation Measure (PAM) (Hibbard et al., 2004) This 13-item questionnaire asks about self-reported role in caring for their own health. Items ask about their responsibility for managing their condition and their ability to maintain lifestyle changes. Items ask about (1) their confidence in taking care of their health (e.g., actively minimizing symptoms, telling their provider about concerns), following medical treatment at home, and (2) their knowledge and understanding of their condition (e.g., the nature and causes of the condition, medication(s), medical treatment options). Responses range from strongly disagree (1) to strongly agree (4) with no neutral/middle points, but a “not applicable” (N/A) response option is also available. All items are phrased positively. Each person’s responses are added to obtain a total, excluding items with N/A responses, and the sum is divided by the number of items answered (excluding N/A items) and multiplied by 13. These raw PAM scores are then converted to a PAM activation scale score, ranging from 0 to 100, with higher scores indicating higher activation level, as suggested by Moljord et al. (2015). The RAND 36-Item Health Survey 1.0 Questionnaire (SF-36) (RAND Corporation, 1992a) The 36 items are recoded and summarized into eight scale scores, each ranging from 0 to 100. The subscales assess self-reports regarding physical functioning, role limitations due to physical health, role limitations due to emotional problems, energy/fatigue, emotional well-being, social functioning, pain, and general health. Scale scores represent the average scores of items that the respondent answered (i.e., excluding items not responded to). The individual items were recoded and subscales were scored according to the instructions (RAND Corporation, 1992b). Higher scores indicate more favourable health states. Analyses Four sets of analyses were conducted. First, to ensure that the randomization worked and the three groups were equivalent at baseline, a one-way analysis of variance (ANOVA) was conducted on all demographic variables and baseline outcome measures. Second, to assess whether the device installation may have had an impact on the outcome measures, participants in the coach + devices group were split into groups based on when they enrolled in the study, either prior to the COVID shutdown (prior to March 2020) or after (August to December 2020). A set of 2 × 2 mixed-factorial ANOVAs was conducted on all outcome measures, with each pre/post outcome measure as the repeated-measures factor and the two subgroups of this group as the between-subjects factor. Although not planned for, the overall potential impact of the COVID shutdown on the outcome measures was also examined in the whole baseline sample. The third set of analyses looked at the pre- versus post-treatment scores on each outcome measure across the three groups. A 2 × 3 mixed-factorial ANOVA was conducted to test for a statistically significant interaction effect with larger pre- to post-test changes expected in the coach-only and coach + devices groups. Because the outcome measures intend to assess different aspects of the participants’ experience, and to retain statistical power to detect group differences and reduce type II error, the ANOVA F test for each outcome measure was conducted at the 0.05 level of statistical significance. Significant interactions were followed up with post hoc t tests to compare the two treatment groups with the control group and to each other, using Bonferroni correction for type I error for two-sided familywise error at .05. The final set of analyses examined the potential influences of four covariates on the outcome measures. Sex was included as a factor in a 3-way ANOVA, with study group and sex as between-subjects factors. Age (in years), number of health conditions, and years of education were included in repeated-measures general linear models as continuous predictors (analyses of covariance). All analyses were conducted using SPSS version 22. Results Randomization: group differences at baseline Table 1 shows the demographic characteristics of the whole sample and each of the three study groups. No statistically significant differences were seen among the three groups, except a slightly higher proportion of men in the coach-only group and correspondingly smaller proportion of men in the coach + devices group. Table 1 Demographic description of study participants at baseline (excluding dropouts) All participants at baseline (N = 163) Control group (N = 55) Coach only (N = 56) Coach + devices(N = 52) Test statistic for group differencesa p value Sex: N (%) men 41 (25.2%) 14 (25.5%) 19 (33.9%) 8 (15.49%) χ2(2) = 4.929 0.085 Ageb: M (SD) 76.0 (6.5) 77.4 (7.5) 75.3 (5.0) 75.2 (6.6) F(2, 160) = 2.133 0.122 Education: M (SD) years 15.5 (3.0) 15.5 (3.0) 15.6 (2.7) 15.5 (3.4) F(2, 160) = 0.029 0.971 Education level: N (%)  Less than high school (6–11 years) 8 (4.9%) 2 (3.6%) 1 (1.8%) 5 (9.6%) χ2(6) = 6.592 0.360  High school graduate (12 years) 26 (16.0%) 9 (16.4%) 11 (19.6%) 6 (11.5%)  College/university (13–16 years) 85 (52.1%) 32 (58.2%) 26 (46.4%) 27 (51.9%)  Graduate school (17–22 years) 44 (27.0%) 12 (21.8%) 18 (32.1%) 14 (26.9%) Language: N (%) English 150 (92.0%) 51 (92.7%) 53 (94.6%) 46 (88.5%) χ2(2) = 1.460 0.482 Living situation: N (%) live alone 77 (47.2%) 23 (41.8%) 25 (44.6%) 29 (55.8%) χ2(2) = 2.318 0.314 Total number of chronic conditions: M (SD) 3.55 (2.89) 3.13 (1.82) 3.82 (2.52) 3.69 (2.89) F(2, 160) = 1.262 0.286 aF value from one-way analysis of variance for testing M (SD) equal across three study groups; χ2 test of independence for N (%) equal across three study groups bAge was computed as the difference between 2020 and the year of birth Tables 2 and 3 show a description of the three groups, at baseline, on all the outcome measures. Both tables also give the scale reliability, using Cronbach’s alpha, as applicable. Table 2 provides information on all outcome measures except the SF-36 Health Survey, which is shown in Table 3. There were no differences in the frequencies of the various chronic conditions among the three groups. The most frequently reported chronic conditions were arthritis (50.3% of all participants) and cardiovascular disease (45.6%). About one in five reported chronic pain (21.8%) and/or a neurological disorder (22.8%). Some (14.5%) reported respiratory disease, and about 11% reported cancer. Table 2 Baseline means (M) and standard deviations (SD) on outcome measures (excluding dropouts) Outcome measure at baseline # of items Possible rangea Cronbach’s αb Whole sample (N = 163) Control group (N = 55) Coach only (N = 56) Coach + devices (N = 52) F valuec p valuec Self-efficacy scale score 6 6 to 60* .91 39.84 (11.39) 41.05 (10.27) 40.27 (11.09) 38.12 (12.76) < 1.0 0.390 Depression severity 9 0* to 27 .85 7.30 (5.38) 6.35 (4.94) 7.46 (4.96) 8.14 (6.15) 1.494 0.228 If problems with feelings, how difficult? 1 1 to 4 – 1.87 (0.77) 1.76 (0.72) 1.91 (0.77) 1.92 (0.81) < 1.0 0.484 Communication with doctor 3 0 to 15* .77 9.01 (3.79) 8.85 (4.09) 9.18 (3.64) 8.98 (3.69) < 1.0 0.902 Number of visits to doctor in past 3 months 1 0* to 90 – 2.65 (2.89) 2.76 (2.61) 2.38 (2.39) 2.85 (3.61) < 1.0 0.665 Number of visits to ER in past 3 months 1 0* to 90 – 0.25 (0.57) 0.18 (0.48) 0.20 (0.40) 0.38 (0.77) 2.117 0.124 Number of nights spent in hospital in past 3 months 1 0* to 90 – 0.48 (1.80) 0.25 (1.38) 0.64 (2.09) 0.56 (1.87) < 1.0 0.496 Help reading hospital material 1 1 to 5* – 4.62 (0.94) 4.60 (1.01) 4.57 (0.97) 4.69 (0.83) < 1.0 0.787 Problems learning about treatment 1 1 to 5* – 4.54 (0.81) 4.51 (0.90) 4.61 (0.82) 4.50 (0.70) < 1.0 0.747 Confidence in filling out forms 1 1* to 5 – 1.53 (1.11) 1.51 (1.15) 1.45 (0.99) 1.63 (1.21) < 1.0 0.695 Patient Activation Measure 13 0 to 100* .88d 59.8 (14.2) 60.3 (14.0) 59.0 (15.1) 60.1 (13.6) < 1.0 0.870 aAsterisks in this column indicate the best/most favourable score on the scale bBased on all participants (N = 193, including dropouts) and baseline scores cF and p values are from one-way analyses of variance with (2, 160) degrees of freedom for testing the null hypothesis that the means of the three study groups are equal dBased on N = 164, and raw responses to 13 individual items with responses ranging from 1 to 4 Table 3 Baseline means (M) and standard deviations (SD) on subscales of the 36-item short form (SF-36) of the Health Survey (excluding dropouts) Health survey subscale scores at baselinea Whole sample Control (N = 55) Coach only (N = 56) Coach + devices (N = 52) Group differences? # of items Cronbach’s αb M (SD) M (SD) M (SD) M (SD) F valuec p valuec Physical functioning 10 .907 52.8 (26.4) 52.0 (25.3) 53.7 (29.3) 52.60 (24.6) < 1.0 0.948 Role limitations due to physical health 4 .792 25.8 (33.5) 28.6 (31.3) 22.8 (34.8) 26.0 (34.6) < 1.0 0.655 Role limitations due to emotional problems 3 .796 60.5 (40.4) 68.5 (39.2) 58.9 (41.2) 53.8 (40.2) 1.837 0.163 Energy/fatigue 4 .833 42.4 (23.7) 46.7 (22.6) 38.0 (23.8) 42.4 (24.4) 1.885 0.155 Emotional well-being 5 .769 72.0 (15.7) 72.7 (16.2) 72.4 (16.1) 70.9 (14.9) < 1.0 0.817 Social functioning 2 .817 63.0 (26.5) 70.5 (22.6) 59.4 (28.2) 58.9 (27.3) 3.415 0.035 Pain 2 .881 50.8 (25.6) 50.4 (24.5) 50.3 (25.8) 51.7 (26.9) < 1.0 0.951 General health 5 .776 50.4 (21.7) 51.9 (20.1) 49.6 (23.5) 49.6 (21.7) < 1.0 0.820 aThe possible range of scores on all subscales is 0 to 100, with higher scores indicating more favourable outcomes bBased on all participants (N = 193) and baseline scores cF and p values are from one-way analyses of variance with (2, 160) degrees of freedom for testing the null hypothesis that the means of the three study groups are equal Dropouts Thirty participants (15.5%) dropped out of the study. Proportionally, the dropout rate was not impacted by the COVID interruption (χ2(1, N = 193) = 0.182, p = 0.670), with 20 of the 135 (14.8%) who enrolled pre-COVID dropping out and 10 of the 58 (17.2%) who enrolled post-COVID shutdown dropping out. The dropouts did not differ from those who remained in the study in terms of sex (χ2(1, N = 193) = 2.035, p = 0.154); age (t(191) = 1.126, p = 0.262); years of education (t(189) = 0.462, p = 0.645); and whether they lived alone or with someone (χ2(1, N = 193) = 0.003, p = 0.954). They did differ on language, with a higher proportion (7, 35.0%) of non-English participants compared with (23, 13.3%) English speakers (χ2(1, N = 193) = 6.434, p = 0.011), and the total number of chronic conditions (t(191) = 2.429, p = 0.016), with participants who dropped out reporting fewer (M = 2.43, SD = 1.30) compared with those who stayed in the study (M = 3.55, SD = 2.44). Participants who dropped out did not differ on any of the outcome measures (all p > 0.123), except the SF36-Social subscale (t(190) = 3.597, p < 0.001), and marginally on the three items about health literacy (0.017 < p < 0.063). There was a difference in the dropout rate across the three study groups (χ2(2, N = 193) = 6.763, p = 0.034), with a higher proportion of participants in the coach + devices (16) compared with 4 in the control group and 10 in the coach-only group. Reasons for dropping out included dissatisfaction being randomized to the control group (N = 1); discomfort receiving weekly telephone calls from their coach (N = 5 in coach only, N = 2 in coach + devices); falling ill (N = 4 in coach only; N = 4 in coach + devices); unable to use devices (N = 1) or found them too difficult (N = 7); moving out of the area (N = 1); coach became ill (N = 1 in coach only, N = 1 in coach + devices); and the post-questionnaire was not returned for unknown reasons (N = 3 in control). Impact of device installation and the COVID-19 shutdown Table 4 shows the results comparing study participants at baseline grouped into pre-COVID shutdown (N = 134) and post-COVID shutdown (N = 58) enrolled between August and December 2020. The COVID shutdown did result in slight differences on six of the 19 baseline outcome measures, at the 0.05 level of significance (bolded p values). Two measures of health services utilization in the past 3 months decreased and four of the eight health survey subscales showed higher baseline ratings by the post-COVID enrollees. Table 4 Baseline outcome measure (M, SD) comparisons of participants recruited pre- versus post-COVID shutdown (including dropouts) Outcome measure (at baseline) Recruited pre-COVID (N = 134) Recruited post-COVID (N = 58) t valuea p valuea Self-efficacy scale score 38.34 (11.34) 41.60 (10.42) − 1.878 0.062 Depression severity 7.94 (5.60) 6.57 (5.17) 1.573 0.117 If had problems, how difficult? (single item) 1.92 (0.79) 1.74 (0.70) 1.507 0.134 Communication with doctor (3-item scale score) 8.76 (3.69) 9.57 (3.92) − 1.353 0.178 Number of visits to doctor in past 3 months 3.10 (2.82) 1.60 (2.89) 3.338 0.001 Number of visits to ER in past 3 months 0.30 (0.65) 0.14 (0.40) 2.174 0.031 Number of nights spent in hospital in past 3 months 0.55 (1.86) 0.41 (1.66) 0.475 0.635 Help reading hospital material (single item) 4.55 (1.04) 4.52 (1.06) 0.189 0.851 Problems learning about treatment (single item) 4.49 (0.85) 4.45 (0.88) − 0.300 0.765 Confidence in filling out forms (single item) 1.64 (1.17) 1.48 (1.11) 0.894 0.372 Patient Activation Measure (PAM Activation scale score) 59.21 (13.83) 59.54 (15.22) − 0.147 0.884 SF-36: Physical functioning 48.89 (26.62) 60.93 (24.16) − 2.961 0.003 SF-36: Role limitations due to physical health 22.41 (32.79) 33.62 (35.22) − 2.1304 0.034 SF-36: Role limitations due to emotional problems 58.52 (41.42) 62.07 (39.71) − 0.553 0.581 SF-36: Energy/fatigue 40.15 (23.25) 46.03 (24.23) − 1.592 0.113 SF-36: Emotional well-being 71.30 (16.17) 72.46 (14.74) − 0.345 0.730 SF-36: Social functioning 57.46 (26.86) 66.16 (26.59) − 2.067 0.040 SF-36: Pain 48.50 (25.52) 55.43 (25.37) − 1.733 0.085 SF-36: General health 48.59 (21.92) 55.26 (19.94) − 1.989 0.048 at and p values are from independent-samples t tests with 190 degrees of freedom; p value is two tailed Table 5 shows the average pre-test/post-test mean differences for the coach + devices group, divided into pre- and post-COVID shutdown, to assess any potential impacts of the difference in device installation. None of the mean differences in the outcome measures reached statistical significance, suggesting that the method of device installation does not impact participants’ changes in the outcome measures; however, the statistical power for this unanticipated 2 × 2 repeated-measures ANOVA was relatively low. Table 5 Pre- to post-intervention mean differences on outcome measures for participants in the coach + devices group based on COVID-19 recruitment into the study (pre- versus post-COVID shutdown) Outcome measure (at baseline) Recruited pre-COVID (N = 34) Recruited post-COVID (N = 18) F valuea p valuea Self-efficacy scale score 8.56*** (10.55) 3.00 (10.46) 3.286 0.076 Depression severity − 2.50** (4.46) − 1.75 (4.89) < 1.0 0.593 If had problems, how difficult? (single item) − 0.21 (0.64) − .018 (0.64) < 1.0 0.878 Communication with doctor (3-item scale score) 0.85* (2.27) 0.71 (3.55) < 1.0 0.858 Number of visits to doctor in past 3 months − 0.85 (3.00) − 0.11 (3.92) < 1.0 0.450 Number of visits to ER in past 3 months − 0.24 (1.13) 0.06 (0.42) 1.105 0.298 Number of nights spent in hospital in past 3 months 0.71 (4.36) − 0.50 (1.89) 1.245 0.270 Help reading hospital material (single item) − 0.06 (0.60) − 0.50 (1.04) 3.770 0.058 Problems learning about treatment (single item) − 0.03 (0.67) 0.28 (0.67) 2.459 0.123 Confidence in filling out forms (single item) 0.03 (0.76) − 0.28 (1.07) 1.439 0.236 Patient Activation Measure (PAM activation scale score) 2.83 (10.45) 8.03* (14.25) 2.260 0.139 SF-36: Physical functioning 2.21 (10.09) 4.03 (11.22) < 1.0 0.554 SF-36: Role limitations due to physical health 13.24* (37.56) 2.78 (18.96) 1.222 0.274 SF-36: Role limitations due to emotional problems 13.73 (45.78) 19.61* (35.47) < 1.0 0.645 SF-36: Energy/fatigue 9.56* (21.58) 8.61* (13.78) < 1.0 0.867 SF-36: Emotional well-being 1.88 (12.58) 7.94* (11.91) 2.832 0.054 SF-36: Social functioning 13.24** (27.34) 11.81** (15.74) < 1.0 0.839 SF-36: Pain 5.66 (17.13) 6.94 (15.59) < 1.0 0.792 SF-36: General health 3.82 (13.77) 5.28 (11.04) < 1.0 0.701 *p < 0.05; **p < 0.01; ***p < 0.001 two tailed, for paired-samples t tests of the null hypothesis that the mean difference (post- minus pre-intervention) is statistically different from zero (excluding dropouts) aF and p values are for the (1, 50) degrees of freedom interaction effect of pre-/post-intervention and 2 subgroups in 2 × 2 repeated-measures ANOVAs Impact of coaches, with and without devices, on outcome measures Table 6 shows the mean differences for the three groups for each of the 19 outcome measures. Group mean differences statistically different from 0 are shown in bold, and also shown graphically in Figs. 1, 2, and 3. For the statistically significant interactions, post hoc tests of pairwise comparisons of the mean differences obtained by the three study groups, using Bonferroni type I error correction, revealed several group differences. Table 6 Post- minus pre-intervention mean differences on each outcome measure for participants across the three study groups Outcome measure Control (N = 55) Coach only (N = 56) Coach + devices (N = 51) F valuea p valuea Self-efficacy scale score − 0.09 2.34 6.63*** 6.205 0.003 Depression severity 0.38 − 1.21* − 2.26*** 5.667 0.004 If had problems, how difficult? (single item) − 0.04 − 0.18 − 0.20* < 1.0 0.408 Communication with doctor (3-item scale score) 0.37 0.77* 0.80* < 1.0 0.686 Number of visits to doctor in past 3 months − 0.64 − 0.48 − 0.60 < 1.0 0.948 Number of visits to ER in past 3 months 0.24 − 0.11 − 0.14 3.677 0.027 Number of nights spent in hospital in past 3 months 0.15 − 0.34 0.29 < 1.0 0.418 Help read hospital material (single item) 0.00 − 0.18 − 0.21 < 1.0 0.441 Problems learning about treatment (single item) 0.07 − 0.18 0.08 1.503 0.226 Confidence in filling out forms (single item) 0.24 0.09 − 0.08 < 1.0 0.394 Patient Activation Measure (PAM activation scale score) 1.71 4.40** 4.63** 1.034 0.358 SF-36: Physical functioning 2.33 0.45 2.84 < 1.0 0.637 SF-36: Role limitations due to physical health 7.27 16.52** 9.62* 1.044 0.354 SF-36: Role limitations due to emotional problems − 7.88 5.36 15.69* 4.417 0.014 SF-36: Energy/fatigue 0.12 7.95** 9.23*** 3.164 0.045 SF-36: Emotional well-being − 1.60 0.64 3.98* 2.759 0.066 SF-36: Social functioning − 4.77 7.37* 12.74*** 7.129 0.001 SF-36: Pain 0.77 1.79 6.11** 1.03.7 0.357 SF-36: General health 2.00 3.48 4.33* < 1.0 0.697 aF and p values are for the interaction effect of 2 × 3 repeated-measures ANOVAs, with pre-/post-intervention and three study groups. Degrees of freedom for F values are (2, 160). Data exclude dropouts *p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001 two-tailed, for paired-samples t tests of the null hypothesis that the mean difference (post- minus pre-intervention) is statistically different from zero (within each group) Fig. 1 Changes in participants’ ratings on self-efficacy, depression severity, communication with physician, and patient activation measure (PAM) across the three study groups (error bars are 95% confidence intervals of the mean post- minus pre-intervention differences) Fig. 2 Changes in participants’ ratings on SF-36 subscales across the three study groups (error bars are 95% confidence intervals of the mean post- minus pre-intervention differences) Fig. 3 Changes in participants’ service utilization and self-ratings of health literacy across the three study groups (error bars are 95% confidence intervals of the mean post- minus pre-intervention differences) As shown in Fig. 1, the coach + devices group increased their self-efficacy relative to both the control (p = 0.002) and coach-only groups (p = 0.080), and the latter two did not differ from each other (p = 0.604). The depression severity scores of the coach + devices group became less negative relative to those of the control group (p = 0.003) but did not differ from those of the coach-only group (p = 0.547) which did not statistically differ from those of the control group (p = 0.120). For the PAM activation scores, the interaction was not statistically significant due to the large variability in the scores, but participants in the two coach groups did increase their PAM scores by almost the same amount. There was quite a lot of variability in the scores on the eight subscales of the SF-36 (see Fig. 2), but several group differences were statistically or marginally statistically (p < 0.10) significant. Specifically, for ratings of role limitations due to emotional problems, whereas the ratings of the control group decreased over time, ratings of both coach-only and coach + devices groups increased, with the coach + devices group differing from control (p = 0.011) but not from the coach-only group (p = 0.584), and the coach-only group average, while in the positive direction, not differing from the control group (p = 0.272). For the energy/fatigue subscale, while the coach-only group did not differ from the control group (p = 0.136) and the two coach groups did not differ from each other (p = 1.000), the coach + devices group did differ from the control group (p = 0.067), but marginally significant differences were also seen for emotional well-being, where only the coach + devices group differed from control (p = 0.062). Finally, with regard to social functioning, the coach-only group increased their ratings relative to the control group (p = 0.031) as did the coach + devices group (p = 0.001), but the two coach groups did not differ from each other (p = 0.779). Group differences in ratings on the SF-36 subscales for physical functioning, role limitations due to physical health, pain, and general health did not reach statistical significance. No statistically significant differences were found for communication with physician; the average number of visits to the ER; and the three items about health literacy. Influence of sex, age, education, and number of chronic conditions Table 7 shows that the influences of sex, age, years of education, and the number of chronic conditions did not impact the outcomes. There were only two statistically significant effects at the 0.05 level. There was a potential effect of gender on the number of visits to a physician, with men in the coach + devices group decreasing the number of visits to the doctor (M = 5.13 visits on average prior to the study and M = 2.38 visits at the conclusion of the study; all other sex-study groups had a mean difference less than 0.72 visits). This is likely due to one participant (a man in the coach + devices study who reported 20 visits, the remaining participants reported 13 or fewer visits). The second covariate was age and it seemed to influence social functioning; there was no correlation of age with social functioning at baseline (b = − .069, p = 0.831), but there did appear to be a positive weak relationship of social functioning with age at the conclusion of the study (b = .635, p = 0.063), such that older participants across all three groups were more likely to be engaged socially at the end of the study (could also be a type I error). Table 7 Effects of sex, age, education, and health conditions on the mean differences on each outcome measure across the three study groups (p values) Outcome measure Sexa Ageb Educationb Number of health conditionsb Self-efficacy scale score .267 .893 .983 .987 Depression severity .411 .481 .566 .569 If had problems, how difficult? (single item) .828 .227 .821 .249 Communication with doctor (3-item scale score) .968 .837 .686 .163 Number of visits to doctor in past 3 months .040 .184 .401 .293 Number of visits to ER in past 3 months .527 .463 .224 .271 Number of nights spent in hospital in past 3 months .792 .539 .163 .070 Help read hospital material (single item) .903 .458 .803 .557 Problems learning about treatment (single item) .283 .602 .625 .200 Confidence in filling out forms (single item) .768 .292 .063 .513 Patient Activation Measure (PAM activation scale score) .543 .134 .540 .766 SF-36: Physical functioning .366 .466 .728 .912 SF-36: Role limitations due to physical health .941 .141 .875 .416 SF-36: Role limitations due to emotional problems .663 .494 .104 .443 SF-36: Energy/fatigue .799 .982 .577 .747 SF-36: Emotional well-being .561 .804 .082 .459 SF-36: Social functioning .795 .020 .716 .657 SF-36: Pain .473 .425 .458 .874 SF-36: General health .344 .944 .061 .796 ap values for 2 (pre-/post-study score) × 3 (study groups) × 2 (male/female) interaction effect bp values for 2 (pre/post-study score) × covariate interaction term in ANCOVA with (1, 159) degrees of freedom Discussion The study’s participant randomization process was effective in that there were no statistically significant differences in demographic characteristics among the groups and there was only one difference in the social functioning subscale score of the Rand 36-item Health Survey Questionnaire at baseline. Furthermore, within the control group, participants’ scores on the outcome measures did not change statistically significantly during the intervention time interval on any of the outcome measures, indicating that any observed changes in outcomes for the two intervention groups are unlikely due to confounding variables due to time. Despite our best efforts in conducting this randomized control pre-post-test study, its limitations include differential dropout rates across the three intervention groups and the sudden appearance of the COVID-19 pandemic midway through. Thirty persons withdrew from the study with an equal proportion withdrawing before and during COVID. Subjects who withdrew differed from those who stayed with respect to their language being non-English, having fewer chronic health conditions, and scoring lower on the SF-36 Social subscale, and marginally lower on health literacy, ability to read hospital materials, having problems learning about their medical condition and in their confidence filling out forms (likely due to the language issue). A majority of dropouts were from the coach + devices group, with almost half of these reporting they found the devices difficult to use. This differential dropout rate for the group with the devices was a study limitation that future research can take into account, and perhaps explore individual difference factors, such as familiarity and comfort with new devices, which likely play a role in using the devices for enhancing health outcomes effectively. The impact of the COVID shutdown was seen on six of the outcome measures. Participants who enrolled after the shutdown reported fewer doctor visits and fewer trips to the emergency department in the prior 3 months, not surprising as this was mandated by the health officials at the start of the pandemic. This group also had higher baseline scores on four of the eight Health Survey subscales, namely physical functioning; role limitation due to physical health; social functioning; and general health. It is interesting that older adults who felt stronger physically, but did not differ in terms of the more emotional subscales (role limitation due to emotional problems, emotional well-being, energy/fatigue, and pain), were more likely to be recruited during the pandemic. Exploring this observation, however, is beyond the scope of this study. Finally, and luckily, the method of device installation (i.e., in person by study personnel vs. by telephone instructions) that was required by the COVID shutdown did not impact the outcome scores and changes in the outcome measures for participants in the coach + devices group. In terms of the main hypotheses of the study, several results stand out. Compared with the control group, participants who worked with a coach (only) reported decreased depression, higher activation levels, better handling of role limitations due to physical health, higher energy levels, better social functioning, and better communication with their physician. Participants who had devices along with a coach showed similar improvements on all of these measures, with even larger decreases in depression severity. In addition, participants with devices also improved in terms of their self-efficacy, better handling of role limitations due to emotional problems, higher level of emotional well-being, lower pain, and higher general health ratings. None of the covariates tested—sex, age, education level, and number of chronic conditions—contributed to the differences in outcome measures, which is consistent with the findings of another study on the effectiveness of peer coaches (McGowan et al., 2019). Overall, participants who worked with a coach for the 3-month intervention, with or without devices, experienced improvements in several outcomes, providing evidence that the 3-month intervention works. It remains unclear, however, how the use of the three assistive devices impacted the outcome measures; that remains beyond the scope of this work. The same coaching intervention was used for both study groups, but participants in the group which also had devices had improvements on more outcome measures than the group without devices. Studies that have examined the causal link between peer coaching and outcomes have found that coaches provide practical assistance to achieve and sustain complex behaviours (Brownson & Heisler, 2009); help people access and navigate clinical care and community resources (Rees & Williams, 2009); and help people address complex multi-morbidities, serving as a bridge between primary and behavioural health (Colella & King, 2004; Dunn et al., 2003; Fisher et al., 2009). A possible explanation in this study may be that using the devices assisted persons to monitor and achieve their weekly goals, and achievement of weekly goals leads to the development of even higher levels of self-efficacy. An additional analysis will be conducted by the study Co-PI to investigate the relationship of the data collected by the three devices to outcome measure results. Conclusion By employing a RCT design, the current study has advanced the understanding of the effectiveness of peer health coaches assisting older persons with chronic health conditions and that including assistive devices may provide additional benefits. Future research involving assistive devices and peer health coaches would benefit by having a devices-only group and a qualitative component to bring understanding to the relative and potentially different experiences of using assistive devices and/or being involved with a peer health coach. Contributions to knowledge What does this study add to existing knowledge? The study provides strong evidence, from a pre-post intervention randomized control trial design, that 90 days of weekly peer-to-peer coaching improves several self-rated health outcomes for older adults with chronic health conditions. The additional use of home-based electronic devices connected to an app showed further benefits. These results held for all participants and were not impacted by the COVID-19 interruption, nor were there differential effects based on age, sex, and education level, at least in the participant group in this relatively highly educated, predominantly female and English-speaking Canadian sample. What are the key implications for public health interventions, practice, or policy? The key implications for public health practice and policy are several-fold. First and foremost, the relatively inexpensive, easy to implement and run peer-delivered telephone Self-Management Health Coach Program (Self-Management BC, 2020) has been shown, in several studies now, to be very effective in helping people with chronic health conditions manage their health outcomes, even without any devices. The shortage of general practitioners in the province could be eased by incorporating peer coaches, with or without the devices, to help patients, likely of all ages, manage their chronic health issues. Acknowledgements This research was made possible through a generous grant from the Canadian Institutes of Health Research. The following research staff had an integral role in the success of the study: Frances Hensen, RN, BScN, MAL/Ed - Project Lead; Suzanne Harmandian, RSA Dip Bus Studies - Coach Coordinator; Harjot Grewal, BSc - Devices Coordinator; and Helena Kadlec, PhD - Statistical Consultant. Author contributions The first author was responsible for developing the health coach intervention, randomizing participants to the study groups, analyzing the data, and writing the manuscript. As well, the first author hired and supervised the research staff to recruit participants, obtain consent forms and questionnaires, and recruit, train, and support coaches during the intervention period. The second author was responsible for developing the original research grant application to the funding body, making grant modifications, procuring the assistive devices used in the study, serving as the main contact with the Joint Island Health and University of Victoria Research Ethics Board, and supervising the project devices coordinator. Both authors read and approved the final manuscript. Funding This research was funded through a Canadian Institutes of Health Research Operating Grant FRN: 143564. Availability of data and material Available upon request from corresponding author Code availability Data were analyzed with SPSS version 22. Declarations Ethics approval Ethical approval was granted by the Joint Island Health and University of Victoria Research Ethics Board. Consent to participate Participants signed the Joint Island Health and University of Victoria Research Ethics Consent Form. Consent for publication None to declare Conflict of interest The authors declare no competing interests. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Brady TJ Murphy L O'Colmain BJ Beauchesne D Daniels B Greenberg M A meta-analysis of health status, health behaviors, and health care utilization outcomes of the Chronic Disease Self-Management Program Preventing Chronic Disease 2013 10 120112 10.5888/pcd10.120112 23327828 Brownson CA Heisler M The role of peer support in diabetes care and self-management Patient 2009 2 1 5 17 10.2165/01312067-200902010-00002 22273055 Cheng L Sit JW Choi KC Chair SY Li X He XL Effectiveness of interactive self-management interventions in individuals with poorly controlled type 2 diabetes: A meta-analysis of randomized controlled trials Worldviews on Evidence-Based Nursing 2017 14 1 65 73 10.1111/wvn.12191 27984672 Chew LD Griffin JM Partin MR Noorbaloochi S Grill JP Snyder A Validation of screening questions for limited health literacy in a large VA outpatient population Journal of General Internal Medicine 2008 23 5 561 566 10.1007/s11606-008-0520-5 18335281 Chrvala CA Sherr D Lipman RD Diabetes self-management education for adults with type 2 diabetes mellitus: A systematic review of the effect on glycemic control Patient Education and Counseling 2016 99 6 926 943 10.1016/j.pec.2015.11.003 26658704 Colella TJ King KM Peer support. An under-recognized resource in cardiac recovery European Journal of Cardiovascular Nursing 2004 3 3 211 217 10.1016/j.ejcnurse.2004.04.001 15350230 Denton FT Spencer BG Chronic health conditions: Changing prevalence in an aging population and some implications for the delivery of health care services Canadian Journal on Aging 2010 29 1 11 21 10.1017/s0714980809990390 20202262 Dunn J Steginga SK Rosoman N Millichap D A review of peer support in the context of cancer Journal of Psychosocial Oncology 2003 21 2 55 67 10.1300/J077v21n02_04 Efird J Blocked randomization with randomly selected block sizes International Journal of Environmental Research and Public Health 2011 8 1 15 20 10.3390/ijerph8010015 21318011 Elstad EA Boothroyd RI Henes AL Maslow GR Nelson K Fisher EB Global systematic review of peer support for complex health behavior International Journal of Behavioral Medicine 2010 17 SUPPL 1 86 86 Fisher EB Strunk RC Highstein GR Kelley-Sykes R Tarr KL Trinkaus K A randomized controlled evaluation of the effect of community health workers on hospitalization for asthma: the asthma coach Archives of Pediatrics & Adolescent Medicine 2009 163 3 225 232 10.1001/archpediatrics.2008.577 19255389 Gagliardino JJ Arrechea V Assad D Gagliardino GG González L Lucero S Type 2 diabetes patients educated by other patients perform at least as well as patients trained by professionals Diabetes/Metabolism Research and Reviews 2013 29 2 152 160 10.1002/dmrr.2368 23166062 Hibbard JH Stockard J Mahoney ER Tusler M Development of the Patient Activation Measure (PAM): conceptualizing and measuring activation in patients and consumers Health Services Research 2004 39 4 Pt 1 1005 1026 10.1111/j.1475-6773.2004.00269.x 15230939 Kroenke K Spitzer RL Williams JB The PHQ-9: validity of a brief depression severity measure Journal of General Internal Medicine 2001 16 9 606 613 10.1046/j.1525-1497.2001.016009606.x 11556941 LeFort SM Webster L Lorig K Holman H Sobel D Laurent D Living a healthy life with chronic pain 2015 Bull Publishing Company Lorig, K., Stewart, A., Ritter, P., González, V., Laurent, D., & Lynch, J. (1996). Outcome measures for health education and other health care interventions: SAGE Publications. Lorig, K., Laurent, D., González, V., Sobel, D., Minor, M., & Gecht-Silver, M. (2020). Living a healthy life with chronic conditions (5th Edition ed.): Bull Publishing Company. McGowan P Lynch S Hensen F The role and effectiveness of telephone peer coaching for adult patients with type 2 diabetes Canadian Journal of Diabetes 2019 43 6 399 405 10.1016/j.jcjd.2019.03.006 31080092 Moljord Psychometric properties of the Patient Activation Measure-13 among out-patients waiting for mental health treatment: A validation study in Norway Patient Education and Counseling 2015 98 11 1410 1418 10.1016/j.pec.2015.06.009 26146239 RAND Corporation (1992a). 36-Item Short Form Survey (SF-36). https://www.rand.org/health-care/surveys_tools/mos/36-item-short-form.html. Accessed 11 July 2021. RAND Corporation (1992b). 36-Item Short Form Survey (SF-36) scoring instructions. https://www.rand.org/health-care/surveys_tools/mos/36-item-short-form/scoring.html. Accessed 11 July 2021. Rees, S., & Williams, A. (2009). Promoting and supporting self-management for adults living in the community with physical chronic illness: A systematic review of the effectiveness and meaningfulness of the patient-practitioner encounter. JBI Library of Systematic Reviews, 7(13), 492-582. 10.11124/01938924-200907130-00001. Self-Management BC (2020). Health coach training manual. Thom DH Ghorob A Hessler D De Vore D Chen E Bodenheimer TA Impact of peer health coaching on glycemic control in low-income patients with diabetes: a randomized controlled trial Annals of Family Medicine 2013 11 2 137 144 10.1370/afm.1443 23508600 Walker EA Shmukler C Ullman R Blanco E Scollan-Koliopoulus M Cohen HW Results of a successful telephonic intervention to improve diabetes control in urban adults: A randomized trial Diabetes Care 2011 34 1 2 7 10.2337/dc10-1005 21193619 Wolever RQ Dreusicke M Fikkan J Hawkins TV Yeung S Wakefield J Integrative health coaching for patients with type 2 diabetes: A randomized clinical trial The Diabetes Educator 2010 36 4 629 639 10.1177/0145721710371523 20534872
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Can J Public Health. 2022 Dec 12;:1-14
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==== Front Nat Rev Genet Nat Rev Genet Nature Reviews. Genetics 1471-0056 1471-0064 Nature Publishing Group UK London 565 10.1038/s41576-022-00565-7 Research Highlight CHIPping away at the genetic aetiology of clonal haematopoiesis Minton Kirsty [email protected] Nature Reviews Genetics, http://www.nature.com/nrg/ 12 12 2022 11 © Springer Nature Limited 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. A study in Nature reports the identification of new germline variants associated with particular subtypes of clonal haematopoiesis of indeterminate potential (CHIP) and their links to different health outcomes. Subject terms Clinical genetics Genetic association study Rare variants ==== Body pmcReporting in Nature, Kessler et al. describe the use of exome sequencing to identify individuals with clonal haematopoiesis of indeterminate potential (CHIP), coupled with genetic association studies to discover new germline variants associated with particular CHIP subtypes and their links to particular health outcomes. Clonal haematopoiesis — the age-related expansion of particular blood cell lineages — results from somatic mutations that confer a selective advantage to haematopoietic stem cells. In the absence of a haematological malignancy, this is referred to as CHIP. CHIP has previously been associated with increased risk of cardiovascular disease (CVD), infection and all-cause mortality, in addition to haematological malignancies. Thus, it is important to understand how germline variation might predispose to CHIP as a basis for understanding the biological mechanisms of CHIP and determining potential therapeutic targets.Orchidpoet/E+/Getty Focusing on 23 well-defined, CHIP-associated genes, the authors used exome-sequencing data from 454,803 individuals from the UK Biobank (UKB) and 173,585 individuals from the Geisinger MyCode Community Health Initiative (GHS) to identify 27,331 and 12,877 individuals, respectively, with CHIP mutation carrier status (having single or multiple CHIP gene-specific somatic mutations). Genetic association analyses were then performed to identify germline loci associated with CHIP carrier status. In total, 57 common variants in 24 loci (21 of which were previously unknown) were identified as having significant association with CHIP. In addition, the authors identified a rare frameshift variant of CHEK2 that was significantly associated with CHIP. The cancer-associated genes ATM and CHEK2, as well as the telomere maintenance gene CTC1, were also associated with an increased risk of CHIP via rare variant gene burden testing. Next, the authors separately analysed individuals with somatic mutations in one of eight of the most commonly mutated CHIP genes (but no other CHIP gene mutations) and identified genomic loci associated with particular CHIP subtypes, including some that were not significant in the overall CHIP association study. CHIP with somatic mutation of DNMT3A (DNMT3A CHIP) had the largest number of significantly associated genomic loci, most of which had variants that increased CHIP risk. Exceptions to this were PARP1 and LY75 variants, which decreased CHIP risk. Some genomic loci were associated with several CHIP subtypes, sometimes in an opposing manner; for example, TCL1A variants increased the risk of DNMT3A CHIP but decreased the risk of TET2 CHIP or ASXL1 CHIP. Together, the results show that different genomic loci can have shared, unique or opposing effects on CHIP subtypes. Cross-sectional analysis of 5,041 health traits from the UKB showed, as previously reported, that CHIP carrier status is associated with cardiovascular, haematological, neoplastic, infectious, renal and/or smoking-related phenotypes. ASXL1 CHIP was associated with the largest number of health traits. DNMT3A CHIP and TET2 CHIP had opposing associations with haematopoietic phenotypes such as white blood cell count. Unexpectedly, body mass index and fat percentage were associated with CHIP carrier status — negatively with DNMT3A CHIP but positively with TET2 CHIP and ASXL1 CHIP. PPM1D CHIP was associated with an increased risk of severe COVID-19. These results were complemented by longitudinal analysis of subsequent disease phenotypes in individuals with CHIP carrier status at the time of biobank enrolment and by Mendelian randomization. TET2 CHIP carriers in the UKB had a significantly increased subsequent risk of CVD, although the risk estimate was lower than in a previous analysis of a smaller number of individuals and the risk of CVD was not replicated in the GHS cohort or by Mendelian randomization. Furthermore, an earlier finding of a cardio-protective effect of IL6R mutation in CHIP carriers was not replicated in the UKB or GHS cohorts. Looking at cancer phenotypes, and excluding individuals with a previous cancer diagnosis, CHIP carriers had a significantly increased risk of developing blood cancer, particularly myeloproliferative neoplasms. CHIP carriers also had an increased risk of developing lung cancer, prostate cancer and non-melanoma skin cancer in the UKB, but only the lung cancer risk was replicated in the GHS cohort. The lung cancer risk was driven, in particular, by DNMT3A CHIP and ASXL1 CHIP carriers and was independent of smoking status in both the UKB and GHS cohorts. Finally, all-cause mortality was significantly increased across DNMT3A, TET2 and ASXL1 CHIP subtypes. “different genomic loci can have shared, unique or opposing effects on CHIP subtypes” In summary, the large size of this study and the use of exome sequencing have enabled the identification of new genomic variants associated with CHIP and show the importance of considering CHIP subtypes separately. Although the study did not look at mechanisms directly, the loci identified offer some clues for further investigation. For example, PARP1 variants that reduce PARP1 expression (which has a role in DNA repair) decrease the risk of DNMT3A CHIP; thus, PARP1-inhibitory drugs that have already been developed might limit the expansion of DNMT3A CHIP clones. ==== Refs References Original article Kessler MD Common and rare variant associations with clonal haematopoiesis phenotypes Nature 2022 10.1038/s41586-022-05448-9 Related article Silver AJ Bick AG Savona MR Germline risk of clonal haematopoiesis Nat. Rev. Genet. 2021 22 603 617 10.1038/s41576-021-00356-6 33986496
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Nat Rev Genet. 2022 Dec 12;:1
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==== Front Z Arbeitswiss Z Arbeitswiss Zeitschrift Fur Arbeitswissenschaft 0340-2444 2366-4681 Springer Berlin Heidelberg Berlin/Heidelberg 347 10.1007/s41449-022-00347-1 Editorial Digital human modelling – Quo vadis, Homo Sapiens Digitalis? Fritzsche L. [email protected] 1 Bengler K. 2 Spitzhirn M. 1 imk Industrial Intelligence GmbH, 09128 Chemnitz, Germany 2 grid.6936.a 0000000123222966 Technical University of Munich, School of Engineering and Design, Chair of Ergonomics, Boltzmannstraße 15, 85747 Garching, Germany 12 12 2022 13 21 11 2022 © The Author(s), under exclusive licence to Der/die Autor(en), exklusiv lizenziert an Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. ==== Body pmcThis issue of ZfA is dedicated to the topic of digital human modelling with focus on the wide variety of applications in the field of prospective ergonomics of products and production. The topics of this issue are highly related to the contents of GfA’s Fall Conference 2022 organized by imk Industrial Intelligence GmbH and Federal Institute for Occupational Safety and Health (BAuA) in Leipzig. “The evolution of digital human models” was the title of a remarkable dinner speech by Prof. Heiner Bubb, one of the pioneers in the field of Digital Human Modeling (DHM). His speech illustrated that, in Germany, this development of ergonomics research and DHM dates back into the mid-1970s. According to Bubb, the idea was inspired by the first physical human representations like the “Kieler Puppe”, a two-dimensional paper-model of the human body shape with moveable extremities based on anthropometric measurements that was created by Hans Wilhelm Jürgens. This template was mainly used for the ergonomic design of busses and passenger cars in the range of a 5th percentile female and 95th percentile male model, motivated by industry needs to find “one-size-fits-all” solutions. In the beginning of the 1980s the development of computer models began, facilitated by an exchange of ideas with American researchers, pioneers like Don B. Chaffin. Today, almost 50 years later, DHMs are state-of-the-art technologies in the ergonomic design process of many products, as well as production planning and digital factory planning. Over time, many software tools have been developed and introduced to the market. Sofia Scataglini and Gunther Paul (2019) provide an excellent and very comprehensive overview in their book “DHM and Posturography”. However, the increasing need for digitization in almost all fields of applied science, like ergonomics, has led to many new developments and advancements of established models during the last several years. This was facilitated by exponentially increasing computer power and changed work requirements during COVID-19 pandemic, for industrial practitioners as well as for researchers and lecturers at universities. Accordingly, the 2022 Fall Conference of the German Ergonomics Society (GfA) in Leipzig asked “Quo vadis, Homo Sapiens Digitalis?” (inspired by the title of an excellent textbook by Angelika C. Bullinger-Hoffmann and Jens Mühlstedt (2016)). The conference was compiled to provide an overview about current and future developments in the field of DHM, showing presentations and exhibitions of various DHMs and related technologies, such as Virtual Reality and Motion Capturing solutions. One very important aspect of the conference was to include the perspective of the human being who is working in the digitalized world (with tools like DHMs) and the implications for work safety and well-being. Hence, the keynote address of Isabel Rothe, president of the German Federal Institute for Occupational Safety and Health (BAuA) was dedicated to the question if digitalization in general should be considered rather as a chance or a risk for work safety and ergonomics. In the presented data, there are some indications that mobile (i.e., digital) office work can have both: beneficial effects like increased flexibility and better work-life balance as well as negative effects like social isolation and reduced physical activity. Moreover, many emerging digital instruments, such as sensorized protective clothing and wearable assistive devices, have the potential to greatly improve work safety and the inclusion of people with restricted physical or mental abilities. Additionally, the introduction of artificial intelligence may make such devices, other work equipment, and software tools like DHMs smarter and more adjustable to individual needs. However, the increasing digitalization of work will require appropriate regulations on the legislative level as well as balanced agreements between employer and employees to avoid negative outcomes and facilitate positive effects. This was also underlined in a later presentation by Lars Adolph, who clearly showed current limitations and challenges of intelligent systems with regard to work safety: humans usually expect a certain system behavior that may have been learned and trained over years. If tools and equipment suddenly adapt and slightly change their behavior every day, it may become hard to control by end-users and the responsible safety experts. Hence, European and National regulations are currently developed, dedicated to the use of AI-systems in the working world. Another focal point of the conference was the application of DHMs in various domains: Klaus Bengler showed advancements of the RAMSIS model for designing autonomous driving passenger cars; Nele Russwinkel presented cognitive models for understanding pilot and system behavior in large airplanes; Peter Kuhlang demonstrated the idea of “MTM-Motion” as a standard interface to process and assess human motion data generated with various digital tools (Virtual Reality, 3D Simulation, Motion Capturing); Angelika Bullinger-Hoffman gave an overview about projects in the framework of her research cluster “Hybrid Societies” at Technical University of Chemnitz; Simon Auer and Mark Tröster presented the application of the biomechanical DHM “AnyBody Modeling System” for assessing the design and efficiency of exoskeletons; and Sascha Ullmann illustrated the use of “ema Work Designer” in production planning for creating suitable work stations for people with physical restrictions. In addition, a special session was dedicated to EU-project SOPHIA with several partners presenting their latest developments in the design of human-robot-interaction applications for industry use (www.project-sophia.eu). This issue of ZfA and the related GfA conference shows the potential of current DHMs as powerful tools in research and application, ranging from the evaluation of exoskeletons to the combined simulation of work environment factors; it shows that cooperation in the field of ergonomics across specialized areas and disciplines is needed to siginifcantly advance DHM simulation technologies. Starting point of this issue is an opening message from the IEA Technical Committee Digital Human Modeling and Simulation, which gives an overview of important developments in the field of DHMs in recent years. The article “Lean Ergonomics” raises the question “Are relevant synergies of DHMs and digital twins defining a new emerging subdiscipline?” and addresses, that a combination of lean management methods, digital twin and digital ergonomics could generate additional economic and ergonomic potentials. The fact that the consideration of the work environment is also essential for a human-centered design of workplaces and processes is the topic of the article “Simulation of work environment factors for human-oriented and efficient workplaces”. Using different simulation tools of digital ergonomics, it is shown how ergonomic design of the work environment can be holistically evaluated and designed by using the example of physical stress, lighting, acoustics and thermal environment. Auxiliary tools, such as exoskeletons and robots, can support people and reduce work-related stress. The question arises: What is the added value of such tools? “Biomechanical assessment of the design and efficiency of occupational exoskeletons with the AnyBody Modeling System” highlights the possibilities of musculoskeletal models for assessing the design and efficiency of occupational exoskeletons. Several practical use cases are described along with distinct descriptions of common implications for musculoskeletal and exoskeleton modeling. “Human-centered design of robotic systems and exoskeletons using digital human models within the research project SOPHIA” describes how DHMs can facilitate planning and simulating work processes and shows to which extent the goal of creating personalized human models to optimize the ergonomics of employees that work with robotic systems or exoskeletons has already been achieved. “Considering individual abilities and age-related changes in digital production planning-human-centered design of industrial work tasks with ema software” describes an inclusion approach by considering age factors and performance restrictions in DHMs and planning tools using the example of ema Work Designer. The developed methods and workflows for ability-appropriate workplace design are shown by use cases from industry. New trends in the automotive industry such as automated driving also requires new concepts in DHMs. “Ergonomic Simulation in automated vehicles using RAMSIS” shows how the RAMSIS model is applied to evaluate vehicle designs for automated driving concepts by simulate the occupant behavior capabilities. Another important aspect for future work planning could be the ability of planners to remotely cooperate when they assess and design future digitally enhanced workplaces. Hybrid Work Systems offers a concept for a digital platform to ergonomics experts and workplace designers where they can collaboratively develop economically and ergonomically suitable workplaces. Such an approach requires an extension and combination of existing digital methods, like the combination of human simulation and motion capture for time and ergonomic evaluation. In conclusion, this issue of ZfA shows various possibilities of digital product and process design as well as the digitalization of human characteristics. Even if the discipline of DHM is almost 50 years old now, many exciting and important developments await us in the upcoming years. ==== Refs References Bullinger-Hoffmann AC Mühlstedt J Homo Sapiens Digitalis – Virtuelle Ergonomie und digitale Menschmodelle 2016 Wiesbaden, Heidelberg Springer Vieweg Scataglini S Paul G DHM and posturography 2019 London Academic Press
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==== Front J. Ind. Bus. Econ. Journal of Industrial and Business Economics 0391-2078 1972-4977 Springer International Publishing Cham 246 10.1007/s40812-022-00246-w Article How processing trade assists local industrial upgrading: input–output analysis of export processing zones in China http://orcid.org/0000-0001-8016-2496 Wu Weixiao [email protected] 1 Hong Chang 2 1 Department of Economics, Finance and International Business, Grenon School of Business, Assumption University, Worcester, MA 01609 USA 2 grid.431409.b 0000 0001 1939 444X United States International Trade Commission, Washington, DC 20436 USA 12 12 2022 129 14 4 2022 18 11 2022 5 12 2022 © The Author(s) under exclusive licence to Associazione Amici di Economia e Politica Industriale 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Processing trade and related policies have been at the center of some major disputes concerning global segmentation. China has built numerous Export Processing Zones (EPZs) with the backing of local governments to facilitate greater integration into the global supply chain and boost local industrial upgrading. We create a series of backward and forward linkage indices and examine the spillover effect of the increase in EPZ processing trade on local economic activities and industry upgrades using Chinese firm-level industrial trade data and input–output table. Evidence reveals that EPZs have enhanced nearby enterprises' performance and productivity in the policy zone's upstream and horizontal industries. But the downstream industries show no signs of improvement. We also find that foreign-owned and young enterprises profit more from proximity to an EPZ. Additionally, the spillover benefits of EPZs are greater when the zone is moderate in size, supports high-tech industries, or encourages heavy import-and-assembly processing trade. The study sheds light on the processing trade's industrial linkage effects. The findings will provide an invaluable resource for developing policies aimed at both deeper integration into the global value chain and fostering local industrial upgrading. Keywords Global segmentation Input/output table Industrial linkage Processing trade Industrial upgrading Spillover effect JEL Classification F13 F14 D22 ==== Body pmcIntroduction Since Levitt (1993) first introduced the notion of market globalization, the growth of large multinational firms has generated a trend of global segmentation of supply chains. Along with the globalization trend, the processing trade has had a period of prosperity, attracting significant FDI to emerging economies (Parente & Prescott, 1994). Since China joined the WTO, the Chinese government has proposed to deepen its integration with the world economy through the construction of special trade zones according to its Tenth Five-Year Plan. Leveraging global trend of resource reallocation, China sought to first fiercely grow processing trade, then progressively promote its own brand production and optimize the domestic economic structure. In this context, export processing zones (EPZs) have sprung up in emerging nations, especially China, to promote processing trade and increase global industrial chain integration (Temu, 2019).1 However, since the sino-US trade war and the outbreak of the COVID-19 pandemic, recent literature has pointed out a trend of anti-globalization (Shrestha et al., 2020) and bringing manufacturing back to local roots.2 EPZs, one of the fastest expanding export promotion policies, are currently at the center of numerous debates over whether China should continue its export-driven strategy or switch to a domestic demand-driven economy. A deeper knowledge of how EPZs help local economies and assist in the industrial upgrading could provide scholarly and empirical reasons for development zone policies, thereby informing policymakers.Fig. 1 Types of processing trade The reasons for special economic zone policy have acquired empirical support since Ladd (1994). Place-based policies, such as EPZs, can attract FDI, relocate local resources, encourage industry agglomeration, and stimulate the reorganization of production clustering in the nearby enclaves. Such clustering may result in knowledge and technological spillovers, increased availability of specialist labor, and a rising pool of specialized input providers (Zheng et al., 2017). However, the influence of FDI and multinational firms on surrounding enclaves is still debated. Researchers have advanced a variety of arguments regarding the overall usefulness of such policies designed to attract foreign capital. Girma and Gong (2008), and Girma et al. (2008) both argue that the FDI inflows cannot have beneficial spillover effects on nearby enclaves, and state that such effects are particularly limited for state-owned enterprises (SOEs). By contrast, Wang and Zhao (2008) demonstrate the beneficial effects of vertical linkage in the supply chain and argue that these advantages will be more efficient for foreign ownership. Zheng et al. (2017) and Huang et al. (2017) both examined the spatial decay of spillovers from Special Economic Zones (SEZs) when surrounding firms are tightly linked to zone industries. Evidence showed that the closer the linking (both forward and backward linkage) between a policy zone and the local industries, the larger the spillover on local economies. However, EPZs differ significantly from typical SEZs in that EPZs focus solely on accelerating processing trade which, by nature, is more isolated from the outside economies.3 Hence, we believe that the work on the externalities of FDI and multinational firms that focuses on how SEZs promote local economies does not account for the full spectrum of processing trade activities and their spillovers on nearby enclaves. According to Wu et al. (2020), positive agglomeration externalities assist local firms outside EPZs, but the effect diminishes with distance. However, they only assessed the total EPZ spillovers without elaborating on how such spillovers occur along the supply chain as a result of industry aggregation near the policy zone. In this study, we believe that EZP spillovers occur primarily through industry agglomeration and technology spillovers. Therefore, how the industries inside EPZs link with outside industries matters. This study is based on three hypotheses. To begin, EPZs have the potential to generate spillovers of knowledge and technology across horizontal industries. One explanation for this is that the increased availability of specialized labor and input suppliers promotes synergy between low- and high-skill workers inside and near the zone (Blomström & Kokko, 1998; Cheung & Ping, 2004; Glass & Saggi, 2002). Second, we hypothesize that greater upstream (backward) linkage between the policy zone and external industries increases the likelihood that the policy would have spillover effects on local economies. It promotes a vertical industry agglomeration, which means more affordable suppliers for processing companies within the policy zone (Cheung & Ping, 2004; Jabbour & Mucchielli, 2007; Pack & Saggi, 2001). The final hypothesis is that, because the Chinese Custom prohibits direct downstream (forward) linkage, which means that no final goods from processing trade may be resold domestically,4 EPZ policy can still indirectly promote local downstream industries by enticing an upgrade of the entire supply chain, as described in hypotheses one and two. Notably, the policy implications of establishing an EPZ vary depending on the validity of the alternative hypotheses. If the study shows that the EPZ policy benefits primarily upstream industries, then the policy zone's benefit is limited, as it merely produces transitory demand for raw materials from the processing zones. However, if spillovers on forward linking industries can be observed, EPZ policy is more likely to fundamentally expedite technology upgrades throughout the entire supply chain, and thus permanently benefit the local economy. In our study of EPZ spillovers on local economies, we base the research on that of Wu et al. (2020) and combine the approaches of Zheng et al. (2017) and Ciani and Imbruno (2017) to examine the EPZ spillover effects on the neighboring upstream and downstream industries. We focus on EPZs in China, where processing trade accounts for more than half of its world trade. Apart from the standard spillover impact measured by distance from the zone, we utilize input–output tables to examine the extent to which the presence of upstream or downstream multinationals within the EPZ increases the local firms' TFP, export, and output. Hence, we construct a novel dataset that merges a geocoded map with the Annual Surveys of Industrial Firms (ASIFs), Custom Trade data, EPZ policy data, and the 2002 Input/Output table using 6-digit zip code and HS industry code. This dataset provides detailed information on both the physical proximity of firms relative to an EPZ as well as their industry linkage along the supply chain. We discover that local upstream industry firms benefit the most from the EPZ policy, while horizontal linkage industries benefit only slightly. However, the downstream linkage does not play a significant role—local downstream firms did not benefit from the zone policy, and some evidence even showed detrimental effects on these firms. At the same time, we explicitly compare these linking effects at the firm and EPZ levels, taking into account a variety of heterogeneous factors. We discover that the scale of the firm's output, the industry in which it operates, the weight of import-and-assembly trade within the policy zone, and the age and ownership of local firms all matter significantly. The rest of the paper is organized as follows. Section 2 provides context for China's EPZ policy. Section 3 discusses how to generate horizontal, backward, and forward linkage indices using the Input/Output table. We present the data in Sect. 4, showing diverse trends in production and trade between upstream and downstream local industries. The empirical methodology and results are then reported in Sect. 5. The estimated spillovers effects with heterogeneous controls are reported in Sect. 6. We then provide concluding remarks in the final section. Processing trade in the EPZs According to the administrative rules of the Chinese Customs,5 all processing trade zones (EPZs) must be built inside a SEZ upon approval of Customs.6 Since an EPZ allows for the import of raw materials duty free and gives firms access to the country's inexpensive labor force, it is particularly attractive to export-oriented multinationals that specialize in processing trade (Feenstra et al., 2013).7 With the surge of EPZs since 2000, firms engaged in intense processing trade have clustered within the policy zones.8 EPZs are designed to be a single-purpose policy zone devoted to processing trade: only processing trade and related business are permitted within the zone; all final products must be exported under supervision, with no retail, ordinary trade, or transit trade allowed. Due to their simplicity, EPZs make an ideal experiment for studying the influence of processing trade on local economies. Processing trade can be divided into two categories: pure-assembly processing trade (where the processing firm receives foreign inputs for free) and import-and-assembly processing trade (where the processing firm sources and pays for imported inputs) (Fig. 1), with each category accounting for approximately half of business in EPZs. Since EPZs are built within SEZs, one concern about our study is that the effects of EPZs may be entangled with those of SEZs. In order to address the challenge of studying the impact of EPZ policies on local value chains while controlling for the Marshallian externalities generated by the clustering of firms in SEZs, we consider the following two arguments. Firstly, all EPZs were built about a decade after the establishment of SEZs, so we have reason to believe that after years of implementation and development, the policy of SEZs has remained somewhat consistent and stable. Then, the advent of EPZs brings new shocks to the market, which are unsynchronized with the existing SEZ policy. Second, we use post-EPZ year dummies to study the impact of EPZ implementation compared with pre-EPZ baseline effects in the same region. Evidence shows that in the years following the establishment of the EPZ, local industries have seen significant improvements in their production and export levels. The difference around EPZ events should be attributed to the EPZ policy, since it is extremely unlikely that other policies will always occur simultaneously with EPZs across different cities and in different years. In order to be more cautious, we also apply the event study method to separate the impacts of EPZs from SEZs and to test the robustness of our findings (Clarke & Tapia-Schythe, 2021). There is a wide recognition that agglomeration economies contribute to economic development (Marshall, 2009). Through the establishment of EPZ special zones, upstream and downstream firms cluster can be formed within nearby regions, thus enhancing the overall local economy (Amiti & Javorcik, 2008). According to the aforementioned hypothesis, the spillover impact of EPZ processing trade might occur in three stages (Fig. 2). In stage one, the EPZ attracts foreign direct investments and starts limited interaction with local firms in two ways: first, outsourcing part of the assembly procedures to local firms; second, allowing for a small number of imported raw materials being resold domestically with authorization. However, spillovers are limited at this stage due to Customs' rigorous control over outsourcing and reselling. As a result, we believe that the majority of domestic firms will benefit only marginally from the policy zone and will experience no fundamental improvement in technology or productivity during this stage. However, at this early stage, industrial agglomeration starts to form as firms opt to locate in regions where intermediate goods are readily available and their products can easily be supplied to others (Amiti & Javorcik, 2008).Fig. 2 Escalation of EPZ spillovers along the supply chain As the EPZ develops and related industries cluster around it, the spillovers from the EPZ enter stage two, which has the most significant and direct impact on local economies. According to traditional industrial agglomeration theories, industrial clusters can generate positive externalities by encouraging pooling of labor markets, easy access to specialized goods and services, and knowledge spillovers (Marshall, 2009). More recently, Görg and Strobl (2002) and Markusen and Venables (1999) have further emphasized the agglomeration effects through linkages. Their study examines the impact of multinationals on local firms through both upstream and downstream links. Hence, at the stage two, as EPZ processing firms directly purchasing intermediate input from domestic upstream providers, the presence of EPZ can benefit upstream sectors by promoting globalization and technology. Then, At the final stage of EPZ spillovers, local economies undergo a shift from processing trade to ordinary trade. With the benefits of EPZ technology spillover on local upstream and horizontal industries, more industries closely linked to the zone cluster are co-locating in the neighborhood, and local infrastructures are significantly developed. According to research, the existence of more downstream or upstream establishments makes it more appealing to local companies by providing them an easier way to connect with suppliers and buyers. As a result, median and small firms tend to follow larger firms to re-locate nearby and further strengthen the agglomeration effect (Belderbos & Carree, 2002). With the development of a mature domestic supply chain, local firms gradually acquire the ability to produce comparable final goods independently, and they eventually achieve the objective of substituting pure domestic manufacturing for foreign processing trade and form a matured supply chain. Hence, if this final stage is arrived, we expect all linked firms can benefit in some way from the policy zone. Industrial Linkage Index In the literature, linkage can be broken down into horizontal linkage and vertical linkage, the latter of which further includes backward (upstream) linkage and forward (downstream) linkage (Fig. 3). Input–output tables are used to operationalize upstream and downstream links, interacting with industry weight matrices, including the industry’s weight based on firm numbers (Debaere et al., 2010), industrial output share (Ciani & Imbruno, 2017), and the weight of total employment (Zheng et al., 2017). We employ Ciani and Imbruno (2017)'s approach of using the industry output9 share as the weight in generating the linkage index in this work.Fig. 3 Forward, backward, and horizontal linkages The horizontal linkage index of any two-digit industry i can be calculated as:1 Hspilli=Ai where Ai is the agglomeration factor of industry i, defined as the share of total industrial production of industry i inside the EPZ policy region. Hspilli measures how industry i horizontally links to the policy zone. Then, the forward linkage index (Fspill) and backward linkage index (Bspill) can be built by interaction the input and output factors from the I/O table with the agglomeration factor for each industry:2 Bspilli=∑m=1NHi,mAm 3 Fspilli=∑m=1NHm,iAm where i represents industries outside the zones and m denotes industries locate within the EPZ. Hi,m is the output factor of sector i from the I/O table, indicating the percentage of sector i’s output that is supplied to all EPZ sectors (m). The backward linkage index, Bspilli, is the weighted average of these output factors of industry i, using the agglomeration factor for each EPZ-sector m as a weight. This indicates an EPZ's reliance on the output of local suppliers. Similarly, the input factor of sector i, Hm,i, represents the proportion of sector i’s input that originates from all EPZ sectors (m). The forward linkage index, Fspilli, is defined as the weighted average of these input factors. It quantifies an EPZ’s ability to supply input to local buyers (Table 1).Table 1 Variable definition Variables Definitions Average Linkage Index Horizontal linkage Hspilli=Ai, the agglomeration factor of industry i inside EPZ 0.069 Backward linkage Bspilli=∑m=1NHi,mAm, the weighted average of the industry i’s output factors with all sectors within the zone. Bspill measures the reliance of an EPZ on local suppliers’ output 0.040 Forward linkage Fspilli=∑n=1NHn,iAn, the weighted average of the industry i’s input factors with all sectors within the zone. Fspill measures the ability of an EPZ to supply input to local buyers 0.031 EPZ factors Tech  = 1, for EPZ policy that supports high-tech industries  = 0, for EPZ policy that supports labor-intensive industries 68.59% EPZ’s output EPZ’s total real output 8247 million CNY (about $996 million) import-and-assembly% The rate of import-and-assembly processing export in an EPZ’s total export 42% Firm factors Foreign owned  = 1, for foreign owned firms  = 0, for domestic firms Young  = 1, for firms established after 1998 (late stage of economic reform)  = 0, for firms established before 1998 YEARct A set of year dummies representing the number of years post the EPZ establishment Distance  = the distance (km) between local firm and EPZ 37 km All linkage indices have a value between 0 and 1. The greater the index value, the stronger the linkage to local industries. Only the industries that exist inside the policy zone have a positive Hspill, however all industries have a backward and forward linkage to the zone. A correlation matrix of the industrial linkage indices at the firm level is provided in Appendix 1. It indicates that a firm's forward and backward links to the zone are mildly correlated. We anticipate a greater spillover in those policy zones that are more closely tied to neighboring enclaves along the supply chain, consistent with Amiti and Javorcik (2008) and Zheng et. al (2017)'s findings. Data and trend analysis Data The study of how EPZ processing trade benefits local economies takes into account a variety of factors, including the utilization of domestic intermediate inputs in processing trade, technology spillovers throughout the supply chain, and industrial agglomeration around the policy zone. In this study, the output, productivity, wage, and export of local upstream, horizontal, and downstream firms are used as major indicators of how EPZs affect local economic activity. We rely on a variety of sources for our data, including the Annual Industrial Survey, specific information on EPZs, the Customs trade data, input/output table, and zip code maps. Firm production and export data come from the Annual Survey of Industrial Firms (ASIFs)10 and the China Customs Data (2000–2006). Key variables that are used in this study include ownership, employment, gross output, wages, industry affiliation, zip code, export, and trade type. Production and export values are converted into real terms using annual price indexes. Each firm can be geocoded to a zip code based on its address. We follow the Olley and Pakes’s (1996) method to calculate the total factor productivity (TFP) to measure the local firms’ performance under the impact of a nearby EPZ policy. We use Ciani and Imbruno (2017)’s approach to build the industry linkage index for each 2-digit industry in the I/O table. The horizontal linkage index, which measures industrial clustering within the EPZ, is calculated using the within-EPZ industry production weight. Then, the backward linkage and forward linkage indices can be built using the 2002 China I/O table and agglomeration factor of industries within the EPZ. Because I/O statistics take a long time to calculate, and data are updated slowly (Ma, et al., 2019), our work has to apply the 2002 I/O table to construct the key linkage indices for the full research period. As a result, this study did not take into account the changes in input–output relations in China, particularly in the context of China's recent accelerating economic growth. By comparing 2002 I/O to 2007 I/O, we found that half of the sectors, i.e., raw materials, energy, and imported inputs, had a significant increase in supplying inputs to the other sectors, seeing an average growth of 40%. In the meantime, other sectors like agriculture have seen a large decrease as the inputs of other sectors which dropped by more than 22% on average. Since the only input–output survey available during our study period was in 2002, our estimations are not able to reflect the changes in the IO relations between 2002 and 2007. Thus, we might over-estimate the weight of sectors whose input/output contributions deteriorated while under-estimate the sectors whose production grew rapidly during this period. We use the official list of 57 EPZs from the National Development and Reform commission (NDRC).11 This list contains each EPZ’s ID, name, built year, city, zip code, land area, and the target industries supported by the zone policy. Combining EPZ data with the annual industrial survey and China Customs Data, we aggregate the total output, export, and employment at the firm- and industry-level both inside and outside the zone. We also calculate all firms’ relative geographical proximity to the EPZ within the same city. Since there are 7 cities (out of 42) with multiple EPZs, we follow Chen, Poncet, and Xiong’s method (2017) and limit our analysis to the first EPZ built in each city. This ensures that our estimates accurately reflect the causal effect of the cities' first EPZs and do not errantly include effects of multiple EPZs.12 After removing observations with missing output values or zip code information, we were left with an unbalanced panel of 208,010 firms across a 7-year period. Summary statistics for different linkage groups outside EPZs Table 2 summarizes statistics for firms located outside EPZs with varying degrees of linkage to the policy zone. The first three columns summarize changes in output, export, productivity, and annual wage for all firms outside the policy zone. For illustration purposes,13 we then generate four subsamples: the top 5% of forward-linked local industries (downstream local consumers) with the EPZ region, the top 5% of backward-linked local industries (upstream local providers) with the zone, the EPZ's horizontal local industries, and the least linked industries (such industries neither exist inside the zone nor are vertically closely related to the EPZ). We align firms' annual performance using the EPZ's building year. Both the "before" and "after" periods cover a period up to six years prior to and after the establishment of an EPZ. The percent change for each sub-group is reported in the last column of each section.Table 2 Descriptive statistics for changes in firms outside the EPZ ($1000) All firms Top 5% EPZ's forward linked local industries Top 5% EPZ's backward linked local industries Horizontal industries Least linked industries (1) Before (2) After (3) % (4) Before (5) After (6) % (7) Before (8) After (9) % (10) Before (11) After (12) % (13) Before (14) After (15) % Output 5824 12,740 119 6420 13,196 106 5858 13,432 129 5898 12,168 106 5845 11,990 105 TFP 3.32 3.82 15 3.35 3.85 15 3.34 3.87 16 3.30 3.82 16 3.36 3.83 14 Wage 2.55 3.14 23 2.54 3.20 26 2.51 3.19 27 2.51 3.14 25 2.60 3.16 22 Export 2903 6005 107 3695 9185 149 2849 8575 201 3209 6542 104 2472 4084 65 Comparing the outside firms’ average performances across different linkage groups, we observe that, prior to implementation of the EPZ policy (Table 2 columns 4, 7, 10, and 13), the most linked downstream industries have the highest output, productivity, wage, and export levels, while the least linked industries have the lowest trade and production performances. However, after the establishment of an EPZ policy, the least linked group still perform the worst among all industries, but the upstream linked industries now become the “winner” during the post-EPZ period. These industries saw their export tripled and total output more than doubled (column 9). Several findings are apparent from Table 2. First, the upstream industries that closely connected with EPZ industries tend to benefit the most from a nearby EPZ. The industries with horizontal and forward linkage also see significant increases, although smaller, in output and export. The performances of the least linked industries show the lowest growth after the EPZ policy. Such facts suggest that EPZs do generate business opportunities for the local industries, especially for upstream industries. Second, there is no evidence showing any significant growth in TFP across the linkage groups in productivity (only increases by 15% on average) and wage (all increase by approximately 25%) both before and after the EPZ establishment. This fact casts doubt on our hypothesis that EPZ policies can stimulate local technology upgrades via supply chain spillovers. This will be tested in the next section. Figure 4 plots the performance trends for backward, forward, horizontal linked, and the least linked firms. The founding year of the first EPZ in each city is marked as the event year (t = 0) and the standardized city-level annual output, export, wage, and the TFP growth are aligned based on this event year.14 Panels 1 and 3 show how EPZs generate spillovers to the peripheral economy: firms outside the EPZs maintained a stable trend in output and export prior to EPZ, but have experienced a pronounced jump during the post-EPZ period. However, panels 2 and 4 do not show any significant difference in TFP growth and wage between the pre- and post-EPZ period. We also found that backward linked industries have shown a higher TFP growth, followed by the forward and horizontal linked industries. The least linked industries experienced the slowest growth in TFP, exports, and wages, and thus benefit the least from the policy zone.Fig. 4 Annual trend of output, TFP, export, and wage (outside EPZ) To determine whether the effects vary by firm’s geographical proximity to the zone, we plot firm performance relative to its average distance from the EPZ. Figure 5 shows that average firm production, export, and TFP growth increase as firms locate closer to an EPZ. Firms that fall into the 10-km radius have an advantage over other firms, and this advantage is even greater for vertical linkage firms. Conversely, the least linked firms demonstrate no significant trend associated with distance to the policy zone.Fig. 5 Spatial distribution of neighboring firms with different linkages Within-EPZ economic factors Table 3 summarizes the production and export within the EPZ. Panel 1 presents the firm-level statistics; panel 2 summarizes the industry linkages of local industries to EPZs; and panel 3 reveals the aggregated output and export at the EPZ level.Table 3 Descriptive statistics for changes in the EPZ PANEL 1: Firms' average performances ($1000) Firm average Processing (93%) Ordinary (7%) Pure Imp. and Assy All Output 20,278 25,675 21,208 26,921 TFP 3.66 3.78 3.75 4.13 Wage 2.79 2.81 2.59 3.27 Export 12,100 14,500 11,800 4777 Import 8615 8320 8540 3821 Number 19,236 43,880 61,834 4444 PANEL 2: Industry linkage with EPZ Weight using: Horizontal Linkage Index Forward linkage Backward linkage Mean Min Max Mean Min Max Mean Min Max Employment 0.073 0 0.536 0.031 0.0004 0.339 0.038 0.0003 0.339 Sales 0.070 0 0.789 0.031 0.0002 0.379 0.040 0.0007 0.382 Production 0.069 0 0.716 0.031 0.0002 0.374 0.040 0.0004 0.376 Firm number 0.071 0 0.395 0.031 0.0008 0.227 0.039 0.0014 0.226 PANEL 3: EPZ's performances EPZ total High-tech preference All EPZs Support Not support Output (million $) 1,030 939 996 Firm number 50 70 57 Distance to city center (km) 42 17 33 Export (million $) 798 248 592  1. Ordinary 102 93 99  2. Processing 697 155 494   2.1 Pure 123 31 89   2.2 Import and assemble 574 123 405 Import (million $) 560 132 400  1. Ordinary 159 42 115  2. Processing 401 90 284   2.1 Pure 59 22 45   2.2 Import and assemble 342 68 239 Import and assemble export% 59% 37% 51% In panel 1, 93% of the firms inside the policy zone engage in processing trade, which is consistent with the primary objective of an EPZ policy, which is to promote processing trade. This table also demonstrates that import-and-assembly processing trade has a larger volume, a greater number of firms, and a higher rate of productivity than pure processing trade. Because import-and-assembly trade enables greater production autonomy, multinational firms engaged in this trade type are more likely to interact with local firms. Therefore, we hypothesize that EPZs with a higher percentage of import-and-assembly trade tend to benefit local economies more. In panel 2, we follow the current literature to construct the three linkage dimensions for each industry based on employment, sales, production, and number of firms.15 The summary statistics indicate that the results are similar regardless of which weight is used to calculate the linkage indices. Hence, we use production as the weight of industry clustering when building the linkage indices. The table shows that the average horizontal linkage is the highest in EPZs and then follows the backward linkage index. The forward linkage index is the smallest among others. This indicates that EPZ policy zones are better "fit" into their vicinity in terms of same-industry synergies and upstream-industry collaboration, while loosely connecting with downstream industries outside the zone. The EPZ’s total production and export volumes are shown in the last column of Table 3 panel 3, which indicates that, on average, EPZ locates 33 km from the CBD, serves 57 multinational firms, and concentrates on processing trade. The import-and-assembly processing trade contributes half of the trade volumes within the zone.16 As mentioned before, the direct interaction between the EPZ and local firms is realized through importing domestic intermediate inputs from local upstream providers by the import-and-assembly processing firms within the zone. Hence, the weight of import-and-assembly trade in an EPZ can partially reflect its spillovers on nearby enclaves, especially the upstream local industries. Next, columns 1 and 2 consider the heterogeneous trade patterns between EPZs based on different targeted industries within the zone. Data indicates that high-tech intensive EPZs (column 1) have higher export volume and engage in more import-and-assembly trade than non-high-tech EPZs (column 2). EPZ spillover estimation and results Baseline spillover effect of EPZs We begin with an analysis of Backward spillovers of EPZs on the suppliers outside the zone. We first run a baseline model to examine the performance of upstream-industry firms (local industries that supply inputs to the EPZs) outside the zone during the post-EPZ period. We focus on the following "benchmark" specification which is in line with the existing literature (Ciani & Imbruno, 2017):4.1 Yfict=β0+β1·distancef+β2·Bspillit·distancef+Linkageit+δic+δit+δct+εfict Yfict indicates the performance of firm f in industry i located outside the EPZ in city c in year t. We consider four performance variables: annual real output, annual real export, productivity growth, and annual real wage. β1 is an estimation of the spatial decay rate of EPZ spillovers.17 We then interact the backward linkage index (Bspilli) with distance to study the decay rate of spillovers with different levels of backward linkage with local industries. Linkageit is a vector that includes all related linkage indices. Here, we only consider Bspilli in this baseline model. Last, we add city-industry fixed effects δic to control for unobserved time-invariant factors that may correlate with the establishment of an EPZ. δit and δct are fixed effects that capture time-varying effects at the city and industry level.18 The error term εfict indicates unobservable factors and is clustered at the city level. Our main interest here is in the coefficient β2, which is the estimator of an EPZ’s spillover on the local suppliers. We expect this coefficient to be negative, suggesting that a local supplier can benefit from being vertically close to the policy zone. We also estimate the EPZ policy’s spillover on horizontal linked local industries:4.2 Yfict=β0+β1·distancef+β2·Hspillit·distancef+Linkageit+δic+δit+δct+εfict where the horizontal linkage index (Hspilli) interacts with distance to give an estimation of the policy’s spillover on local horizontal industries. Note that the Linkageit now only includes Hspilli. We still expect a negative β2, in line with the findings of Wu et al. (2020). That is, incumbent firms located adjacent to an EPZ should benefit from being in the same industry as the EPZ. We then examine how the degree to which this park "fits" into the local incumbent industries will affect the spatial decay rate of its spillovers. In the literature, it is believed that the spillover effect decays less drastically with distance if adjacent firms are closely related to each other. Following the specification adopted in Ciani and Imbruno (2017) and Zheng et al. (2017), we use horizontal, backward, and forward linkage indices to describe the industry linkage between outside industries and an EPZ policy zone:5 Yfict=β0+β1·distancef+β2·Hspillit·distancef+β3·Bspillit·distancef+β4·Fspillit·distancef+Linkageit+δic+δit+δct+εfict where the Linkageit consists of both horizontal and vertical linkage indices. β2, β3, and β4 are the EPZ spillovers on neighboring firms with horizontal, backward, and forward linkages, respectively. We hypothesize β2 and β3 to be negative, which would validate our hypotheses that the horizontal and upstream local industries benefit the most from EPZ’s technology spillovers. Moreover, if β4 is also negative, then downstream industries can also benefit from nearby policy zones. Baseline regression results are reported in Table 4.19 The general results (row 1) indicate a significant EPZ spillover on nearby firms: local firms show higher output, export, TFP growth rate, and wage as they get closer to the policy zone. Specifically, columns 1–4 present our estimates of EPZ spillovers on local upstream industries that are close suppliers of firms within the zone. Columns 5–8 show our estimates of EPZ spillovers on horizontal local industries, which are the same industries supported by local government and dominate the policy zone. According to the negative estimators, local firms that are more backward or horizontally related to the zone can benefit more from policy spillover if they are located closer to the zone.20 However, neither the production nor the wage shows any significant impact, and the firm’s export and productivity growth are affected by the policy spillovers at only 5–10% significance level.21Table 4 EPZ Spillovers with different industry linkages Baseline-backward linkage Baseline-horizontal linkage Baseline-all linkage (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Production Export dln TFP Wage Production Export dln TFP Wage Production Export dln TFP Wage General spillover Distance to EPZ − 0.002** − 0.004* − 0.001*** − 0.002*** − 0.002** − 0.004: − 0.001*** − 0.002*** − 0.001* − 0.002 − 0.001*** − 0.002*** (0.001) (0.003) 0.000 0.000 (0.001) (0.003) 0.000 0.000 (0.001) (0.004) 0.000 0.000 Industry linkage spillover Horizontal − 0.001 − 0.019** − 0.002* − 0.001 0.005 − 0.049** − 0.005* − 0.011***  × Distance (0.002) (0.008) (0.001) (0.001) (0.003) (0.024) (0.003) (0.002) Backward − 0.009 − 0.060** − 0.012* − 0.003 − 0.034** − 0.063 − 0.029*** − 0.000  × Distance (0.006) (0.028) (0.006) (0.002) (0.015) (0.118) (0.011) (0.011) Forward 0.015 0.158 0.021 0.032***  × Distance (0.015) (0.138) (0.013) (0.010) Industry × year Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Year × city Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes City × industry Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations 675,195 762,085 545,291 504,339 675,195 762,085 545,291 504,339 675,195 762,085 545,291 504,339 Data from Annual Industrial Survey, Customs Trade Data, I/O Table (2002), and EPZ Index (2007). Dependent variable is firm-level annual real output (ln output), export (ln export), productivity growth (d ln TFP), and annual wage (ln wage). Columns 1–4 are the results for Eq. 4.1. Columns 5–8 represent results for Eq. 4.2. Columns 9–12 represent results for Eq. 5. Robust standard errors are clustered at the city level and shown in parentheses *Significant at the 10% level **Significant at the 5% level ***Significant at the 1% level Columns 9–12 report the results of Eq. 5 that incorporate not only the horizontal EPZ linkage but also the upstream and downstream linkage to the local economy. First, results show that local horizontal industry firms see an improvement in their export, TFP, and wage by locating near the policy zone. In comparison, local upstream firms can benefit even more by supplying intermediate inputs to EPZ processing firms. However, our study finds that downstream firms cannot significantly benefit from EPZ policy. The positive and less significant estimators indicate that downstream local firms may perform worse when located closer to the policy zone, opposite to our initial hypothesis. There are two reasons that might explain this conflict. First, according to the Customs regulation, all final goods produced during processing trade must be exported to foreign buyers, which limits the development potential of downstream firms as they cannot get access to higher-quality intermediate outputs produced inside the zone. Second, it might take much longer for downstream firms to benefit from the upgrade of the local industrial supply chain stimulated by the EPZ policy. Since our data only covers at most 6 years post EPZ establishment, the benefits received by downstream firms may not be fully captured. Therefore, the impact of EPZ spillovers on local downstream industries may require further study. Annual spillover effects A potential issue with spillovers is that their effects may vary over time. Understandably, it may take time for spillovers to occur (Irwin & Klenow, 1994). Following the estimation framework in Moser and Voena (2012), we allow for an annual spillover effect βt instead of an average effect:6 Yfict=β0+β1·distancef+β2,t·YEARct·Hspilli,t·distancef+β3,t·YEARct·Bspillit·distancef+β4,t·YEARct·Fspillit·distancef+Linkageit+δic+δit+δct+εfict where YEARct is a set of year dummies representing the number of years post the EPZ establishment (Table 1). β2,t, β3,t, and β4,t all now measure the spillovers affected by horizontal, upstream, and downstream linkages, respectively, for each year after the establishment of an EPZ. Notice here, the year dummy is different from the year fixed effect. Year dummies represent the number of years following the founding of each EPZ. Consequently, for different EPZs, one year post EPZ (YEAR = 1) may result in different calendar years. Thus, including both post-EPZ year dummies and year fixed effects will not lead to collinearity problem. Figures 6 presents the 90% confidence interval of an EPZ’s annual spillover effects based on Eq. 6. All the periods with significant spillover effects are highlighted on the graph. Consistent with previous findings (e.g., Capron & Cincera, 1998; Chang & Xu, 2008; Wang, 2013; Wu et al., 2020), results indicate that it takes several years for the full effects of an EPZ to materialize. We also find that such a delay varies with different linkage level in various performance variables. After the building of an EPZ, the spillover effect on a firm’s economic performance generally became stronger and more significant with time. The upstream firms outside the EPZ receive the most significant spillovers: the export and TFP growth jump significantly when the firm is located closer to the policy zone. However, such impact is slower and relatively insignificant for total output. Interestingly, these spillovers on export and productivity of upstream firms lasted for 5 years then disappeared thereafter. In the meantime, the spillovers on the output of upstream firms start to take effect at the 5th year. One possible explanation is that expanding business takes time—local firms need to gradually adjust their production plans or build new factories to accommodate for the increasing needs of EPZ processing firms. For local firms in the horizontal industries, we see no significant improvement in output or productivity. Some growth is found in export only after the 4th year after the establishment of an EPZ. This effect might be explained by the delay in technology spillover, which is consistent with the finding of Wu et al. (2020) that the EPZ spillovers generally take 3–4 years to become effective. Finally, almost no spillovers are observed on downstream industries outside the zone. A possible explanation for this is that since downstream firms cannot directly benefit from the business opportunities brought by the EPZ policy, these firms can only receive very limited spillovers through technology upgrades along the local supply chain. This also suggests that six years is not enough for local supply chain to implement a full range of technology upgrades to benefit all firms along the chain, including both horizontal and vertical industries. We also find that the establishment of an EPZ negatively affected the total welfare of local workers: 3 years after the EPZ policy was implemented, the annual wage of local workers in both upstream and downstream industries significantly decreased.Fig. 6 Annual spillover effects with different industry linkages. Figure shows a 90% confidence interval of the annual spillover effects Heterogeneity in EPZ spillovers We now test for EPZ spillover heterogeneity in two dimensions. The first dimension is based on the characteristics of the EPZ policy, including (1) zone size, (2) whether the policy supports high-tech industries, and (3) the weight of import-and-assembly processing trade within the zone. Our first hypothesis is that an EPZ in moderate size will implement larger spillovers as indicated in the summary statistics. As we explained in the previous section, multinational firms in larger EPZs may have higher quality standard of their inputs, hence prefer importing raw materials from foreign providers instead of using domestic inputs. Then, we hypothesize that EPZs that attract more firms in high-tech industries (e.g., electronics, aircraft, drugs, and vehicles) tend to generate larger spillovers (Capron & Cincera, 1998; Wu et al., 2020). Last, as previously mentioned, if the EPZ spillovers mainly take effect through direct business between multinational processing firms within the zone and their upstream local providers, we expect that EPZs with higher percentage of import-and-assembly trade are more likely to benefit local economies through technology spillover. Next, we account for the second heterogeneity dimension, the firm-specific characteristics, including (1) the ownership of the firm (foreign vs. domestic), and (2) age of the firm. We hypothesize that foreign owned firms and young firms are more likely to benefit from EPZ spillovers. To account for these heterogeneous spillover effects, we interact these factors with industrial linkage indices:7 Yfict=β0+β1·distancef+β2·EPZfactorct·Hspilli,t·distancef+β3·EPZfactorct·Bspillit·distancef+β4·EPZfactorct·Fspillit·distancef+δic+δit+δct+εfict 8 Yfict=β0+β1·distancef+β2·Firmfactorct·Hspilli,t·distancef+β3·Firmfactorct·Bspillit·distancef+β4·Firmfactorct·Fspillit·distancef+δic+δit+δct+εfict where EPZfactorct controls for three different policy characteristics, including the EPZ’s total real output, high-tech dummy variable (equal to 1 if an EPZ targets technologically intensive industries and 0 otherwise),22 and the ratio of import-and-assembly processing export in an EPZ’s total export. Firmfactorct, on the other hand, controls for foreign-owned firms and young firms.23 The estimators β2, β3, and β4 measure how the EPZ spillovers vary with each of these characteristics. Table 5 reports the estimation results for Eq. 6. For all different EPZ-specific factors, the spillovers on local output and wage are insignificant. In comparison, as an export-targeted policy, an EPZ exerts a significant positive impact on local export volume. Consistent with our previous estimations, the data in the second column, row 2 indicates a larger positive spillover associated with closer distance to the policy zone for all local firms (base group). Then, the heterogeneity estimation results show that EPZ spillovers are negatively related to its size (row 2 and row 5 have opposite signs): the larger the EPZ, the smaller spillover it generates on local economies. The reason for this, which was discussed in the summary statistics section, is that because large EPZs are more developed, multinational firms inside these zones are more likely to import foreign inputs of higher quality instead of using domestic intermediate inputs. The results in columns 6 and 7 show that EPZs supporting high-tech industries typically generate larger spillovers on the export and productivity growth of upstream firms (row 5). Interestingly, evidence indicates a negative impact on downstream firms from the policy zone (row 3): those firms show a higher export volume if they are located farther away from the policy region, and an EPZ supporting high-tech industries can accelerate such opposite impact (row 6). Last, we also find that EPZs that focus more on import-and-assembly trade generate higher spillovers on local upstream industries’ export and TFP (columns 10 and 11, row 6).Table 5 EPZ spillovers with heterogeneous EPZ-specific factors EPZ factors EPZ output EPZ tech-focus EPZ import and assembly% (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Dependent Var Output Export TFP% Wage Output Export TFP% Wage Output Export TFP% Wage Industry linkage spillover Horizontal − 0.024 0.108 0.016 − 0.025*** 0.005 − 0.014 0.002 − 0.003 0.005 − 0.016 0.008** − 0.003  × Distance (0.025) (0.094) (0.015) (0.008) (0.007) (0.031) (0.002) (0.002) (0.006) (0.020) (0.004) (0.002) Backward 0.107 − 1.716*** 0.009 0.065 − 0.030: − 0.490** − 0.006 − 0.006 − 0.024 − 0.174** 0.001 − 0.009  × Distance (0.087) (0.544) (0.051) (0.042) (0.018) (0.181) (0.009) (0.010) (0.020) (0.080) (0.011) (0.009) Forward 0.020 1.164** − 0.048 0.022 0.011 0.547*** − 0.006 0.012: 0.014 0.271*** − 0.027* 0.017**  × Distance (0.127) (0.570) (0.044) (0.029) (0.026) (0.135) (0.007) (0.008) (0.028) (0.096) (0.014) (0.007) Heterogeneous spillover Horizontal 0.002 − 0.009 − 0.001 0.002** − 0.002 − 0.014 0.000 − 0.002 − 0.006 0.060 − 0.016* 0.002  × EPZfactor × Distance (0.002) (0.007) (0.001) (0.001) (0.009) (0.039) (0.004) (0.003) (0.016) (0.044) (0.008) (0.005) Backward − 0.009 0.131*** − 0.002 − 0.004 − 0.024 − 0.470*** − 0.055*** 0.007 0.004 − 0.618*** − 0.042** 0.012  × EPZfactor × Distance (0.006) (0.037) (0.003) (0.003) (0.031) (0.167) (0.011) (0.022) (0.042) (0.209) (0.018) (0.022) Forward 0.000 − 0.091** 0.004 − 0.001 0.030 0.355* 0.054*** 0.000 0.000 0.199 0.084** − 0.017  × EPZfactor × Distance (0.009) (0.041) (0.003) (0.002) (0.033) (0.203) (0.019) (0.013) (0.070) (0.135) (0.032) (0.018) Industry × year Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Year × city Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes City × industry Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations 671,382 671,382 462,307 462,307 675,195 762,085 545,291 545,291 313,767 400,657 370,207 370,207 Data from Annual Industrial Survey, Customs Trade Data, I/O Table (2002), and EPZ Index (2007). Dependent variable is firm-level annual real output (ln output), export (ln export), productivity growth (d ln TFP), and wage. The first four columns discuss the heterogeneous EPZ spillovers with different zone total output volume. Columns 5–8 indicate estimations of spillovers of the EPZs that focus on high-tech industries. The last four columns discuss how EPZ spillovers associate with the weight of import-and-assembly trade within the policy zone. Robust standard errors clustered at the city level in parentheses *Significant at the 10% level **Significant at the 5% level ***Significant at the 1% level The results of how EPZ spillovers vary with different firm-specific factors (Eq. 7) are reported in Table 6. First, panel 1 columns 1–4 indicate that foreign ownership resulted in larger improvement in both export, output, and productivity growth from the spillovers of a nearby policy zone. Then, columns 5–8 present the spillover heterogeneity in firm age. The results indicate that younger upstream firms enjoy larger improvement in their export and production by locating near the policy zone (row 5). However, in regards to TFP growth rate, no significant difference is observed between young firms and established firms.Table 6 EPZ spillovers with heterogeneous firm-specific factors Firm factors Foreign-owned firm Young firm (1) (2) (3) (4) (1) (2) (3) (4) Dependent Var Output Export TFP% Wage Output Export TFP% Wage Base group spillover Horizontal 0.015*** 0.118*** 0.003 0.001 − 0.006 − 0.001 − 0.005* − 0.003*  × Distance (0.004) (0.031) (0.002) (0.002) (0.004) (0.016) (0.003) (0.002) Backward − 0.072*** − 0.489*** − 0.029*** − 0.017* − 0.054** − 0.03 − 0.034*** − 0.006  × Distance (0.019) (0.118) (0.011) (0.010) (0.021) (0.074) (0.009) (0.010) Forward 0.011 − 0.052 0.012 0.008 0.070*** − 0.022 0.041*** 0.014*  × Distance (0.017) (0.088) (0.011) (0.008) (0.023) (0.065) (0.014) (0.007) Heterogeneous spillover Horizontal 0.130*** 1.428*** 0.002 0.038** 0.004 0.060*** − 0.002 − 0.001  × Firmfactor × Distance (0.031) (0.252) (0.008) (0.015) (0.004) (0.018) (0.001) (0.002) Backward − 0.039*** − 0.349*** − 0.009*** − 0.016*** − 0.030 − 0.316*** 0.008 0.009**  × Firmfactor × Distance (0.010) (0.094) (0.003) (0.005) (0.020) (0.074) (0.006) (0.004) Forward 0.057** 0.323 0.025* 0.041** − 0.010 − 0.037 − 0.005 − 0.007  × Firmfactor × Distance (0.027) (0.285) (0.013) (0.018) (0.012) (0.060) (0.007) (0.006) Industry × year Yes Yes Yes Yes Yes Yes Yes Yes Year × city Yes Yes Yes Yes Yes Yes Yes Yes City × industry Yes Yes Yes Yes Yes Yes Yes Yes Observations 675,195 762,085 545,291 504,339 662,990 746,403 531,869 491,627 Data from Annual Industrial Survey, Customs Trade Data, I/O Table (2002), and EPZ Index (2007). Dependent variable is firm-level annual real output (ln output), export (ln export), productivity growth (d ln TFP), and wage. The table shows heterogeneous spillovers on foreign owned firms and firms in their young age. Robust standard errors clustered at the city level in parentheses *Significant at the 10% level **Significant at the 5% level ***Significant at the 1% level Robustness check Event study: disentangle the effects of EPZ from SEZ As aforementioned, one concern of this work is to separate the spillover effect of EPZ from the Marshallian externality generated by the clustering of firms in the surrounding SEZ area. To address this issue, current literature on EPZ spillover effect has adopted a Difference-in-difference method (Wu et al., 2020), in which, the authors treat the prior-EPZ market condition as a benchmark and discover a jump in the production and export of local firms immediately following the EPZ event. Since most EPZs are built in different years, in different SEZs, in different cities, it is not possible to have other policies that happen synchronously with EPZs to explain this post-prior EPZ gap in local economy. Following this idea, we adopt the Event Study (Clarke & Tapia-Schythe, 2021) as an alternative to the Difference-in-difference model, to study the effects of EPZ on the local value chain. We define the base year as the year EPZ was built (t = 0) and seek to determine the impacts of the EPZ event on local firms’ production. We assume that the SEZ and local policies will not have changed significantly near the time of EPZ establishment. Then, we regress the firm’s production, export, TFP, and wage on the three main linkage indices and control for year, industry, and city fixed effects. It is shown in Fig. 7 that, after considering the industrial linkage with EPZ, local firms have experienced an increase in production for three years following its construction. Exports are affected more profoundly and for a longer period of time. Moreover, in the aftermath of the EPZ policy, local firms' TFP has only increased slightly, while the wage level has not changed as obvious from the graph. Results presented here are in agreement with those presented in the annual spillover effects section.Fig. 7 Event study of the effects of EPZ industrial linkages on local firms Other specifications of fixed effects The purpose of this section is to test the robustness of our empirical model by experimenting with different specifications of fixed effects. To begin with, we run regressions by excluding all the fixed effects associated with the city, industry, and year. We then control for only the city and industry effects and exclude the year effect. Lastly, we include industry-specific factors, such as industry output, in our model as a complement to the industry fixed-effect variable, which we believe allows us to better account for the differences between industries. There are still significant spillover effects on local businesses in close proximity to EPZ zones, regardless of the specification of the control variables. Our findings are well supported by these test results. Due to the complexity of presenting all these results, the regression tables are available upon request. Conclusion We study the spillover effects of EPZs in China under an industrial linkage framework at the firm-level. Using data on Chinese EPZs, the Annual Industrial Survey, custom trade data, and input–output tables, we construct horizontal, backward, and forward linkage indices to examine the spillover effects associated with the surge in processing trade within EPZs on the nearby business activities and local industrial upgrades. We find that EPZs improve the performance of nearby firms in the policy zone's upstream and horizontal industries. We notice, however, minimal improvement in an EPZ's downstream industries. Our findings indicate that China has been only partially successful in achieving its goal of using their valuable processing trade expertise to drive domestic industrial upgrades. EPZ policy can truly benefit the production and productivity of firms in its upstream and horizontal industries. However, since evidence indicates that downstream industries were left out of the EPZ boom, China's goal of achieving a full supply chain upgrade has yet to be realized, at least not within the 6 years after the built of EPZs. Even worse, we observe some potential detrimental EPZ spillovers on the downstream firms, which may be caused by local preferential policies toward industries with closer connection with processing trade. Hence, the Chinese government's goal of leveraging processing trade to boost domestic production still remains a long-term and challenging task. We also examine the potential heterogeneous effects of EPZ- and firm-related factors and find that foreign-owned firms and young firms experience a greater benefit by locating closer to an EPZ. Moreover, the spillover effects of EPZs are larger when the EPZ is of moderate size, supports high-tech industries, and conducts more import-and-assembly processing trade. Overall, both domestic suppliers and foreign firms benefited from the establishment of an EPZ. This study sheds light on how to optimize EPZ spillovers on the local supply chain and assist policy makers in developing more effective policies, such as those that support high-tech industries, in favor of emerging firms, and attract processing firms of a median size. Additionally, by integrating characteristics such as distance and the types of industries supported by EPZs, our findings can also aid entrepreneurs in firm location and business industry decision-making. While our findings are encouraging, a note of caution is also warranted. We have concluded that there has been not very significant improvement in the local downstream industries following the implementation of the EPZ policy, at least not after 6 years. Consequently, if generating spillovers into the local industrial chain upgrade is part of the reason for attracting processing companies and foreign direct investments, it may not be easy to achieve, but rather a long-term endeavor. Appendix 1: Correlation of linkage indices Bspill (backward) Fspill (forward) Hspill (horizontal) Bspill (backward) 1 Fspill (forward) 0.558 1 Hspill (horizontal) 0.5302 0.684 1 Author contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by WW and CH. The first draft of the manuscript was written by WW, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Funding The authors did not receive support from any organization for the submitted work. The authors have no relevant financial or non-financial interests to disclose. Data availability The data that support the findings of this study are available from the corresponding author, WW, upon reasonable request. 1 EPZ, as one of the main policies in China to stimulate export, experienced a leap in numbers from 2000–2005: the local Chinese governments established 57 EPZs across 42 cities in 22 provinces (see Appendix Figure A1, Wu et al., 2020) in this period. 2 Since the tax reform in 2018, the US government has appealed to bring factories back to America and supported “Made in USA” products. China also slowed down its expansion to international markets. In June 2020, Li Keqiang, the Prime Minister, urged the country to “accelerate the establishment of a ‘dual circulation’ development pattern in which the domestic economic cycle plays a leading role” and “supported the domestic sale of export products.” (Report on the Work of the Government, May 22, 2020). 3 Processing trade is a type of export mode including the import of intermediate materials, the process and assembly of the raw materials, and the export of final goods to foreign markets. All processing firms inside the EPZs are strictly restricted by Chinese custom that their final goods must be exported to foreign markets. Such regulation largely restricts the ability of EPZs in benefiting the outside local economies through business and technology spillovers. 4 All the final goods of processing firms must be exported to foreign markets, which restricts the possibility of these processing firms being the suppliers of outside industries. 5 [1988] No.88, Administrative Rules of the Customs of the Peoples Republic of China Concerning the Bonded Factory of Processing Trade. 6 SEZs include the Economic Development Zone, High Tech Zone, Export Processing Zone, etc. In China, although not every processing trade happens inside an EPZ, most of processing firms join the EPZ to take advantage of accommodative policies and more convenience Custom custody. 7 EPZs can be distinguished from other special zones by their relatively small size and intense processing trade business. By regulation, all EPZs must be no more than 3 square km in size, without exception. Comparatively, most of the special economic zones in China are more than 10 square km. Moreover, 93% of the export happened inside the zones are processing trade. 8 Prior to EPZ policy, the processing trade in the targeted region contributed less than 20% of the total export in that city. However, after the establishment of the EPZ policy zone, the regional processing trade has accelerated and now contributes more than 40% of the city’s export. During 2000–2006, 93% of the business done within the zones were processing trade. 9 Compared to the other two variables, firm production has the least missing observations. Other weights are also used as robustness checks. Results are similar to our study and tables are available upon request. 10 The Annual Survey of Industrial Firms is conducted by the National Bureau of Statistics of China (NBSC). This survey provides information on financial statements and nonfinancial variables for all manufacturing firms, state owned or otherwise, with sales 5 million RMB (about US$600,000) and above (called the “above-scale” firms). 11 The official list is available from the NDRC website: http://www.ndrc.gov.cn/zcfb/zcfbgg/200704/t20070406_126961.html 12 Data show that only 7 cities (out of 42 in total) have multiple EPZs. We use a subsample of 35 single-EPZ cities to test the validity of this approximation. These results are available upon request. 13 Please note that the following regressions are still based on the full dataset. 14 Simply taking the average of output across EPZ cities could lead to bias toward large cities with high output (export). Hence, we define the founding year of EPZ as our base year and divide the output of all other years by the base year value to standardize the economic performance of each city. TFP growth is calculated as the log difference of TFP in two sequential years. 15 Linkage index is a value between 0 to 1. Here, 0 represents two industries with no linkage and no business between them. A value of 1 means that the two industries are 100% related—the outputs of one industry are all supplied to another industry. These two extreme cases do not exist. From the summary table, we see that the average upstream and downstream of an industry are at most 30–40%. 16 The last row in the summary table indicates that, on average, 51% of total trade volumes are import-and-assembly trade, while the rest are pure-processing and ordinary trade. 17 In the literature, spillover is estimated using distance from the policy zone (Zheng et al., 2017). Its geographical spillover is typically interpreted as a negative relation between a measure of local firms' production and the relative distance from the policy zone. Our main variables are the three linkage indices. Our objective is to examine how the effect of these industrial links decays with distance by interfacing the indices with the distance. 18 A challenge when examining any causal relationship on agglomeration and spillover is to effectively control for other hypotheses of clusters like comparative advantage or government incentives. To address this issue, we include specifications with region-time-specific effects, time-industry-specific effects, and region-industry-specific effects. 19 It is important to note that the number of observations in the empirical table varies depending on which dependent variable is used. This is due to the data availability problem, i.e., there are more missing data in wage data. We also conduct a test by limiting the number of observations for all models in order to facilitate a better comparison across the results using different dependent variables. This results in the reduction of our data to a total of 504,339 observations. These regression results are in agreement with those reported in this paper. Upon request, results tables with a fixed observation are available. 20 Quantitatively, a one standard deviation increase in exposure to horizontal linkage with local firms explains 0.26% of the variation in the growth in export and 0.03% of the TFP growth over the period. Similarly, a one standard deviation increase in Bspill explains 0.28% and 0.06% of the export and TFP growth in this period, respectively. 21 These results comply with the result of Wu et al. (2020). Our results are less significant because we studied all industries inside the zone while Wu et al. (2020) focuses only on the three main industries supported by EPZ policy. 22 Since the China Industry Classification system (GB) does not define high-tech industries, we adopt the definition of high-tech industries from the U.S. Bureau of Labor Statistics, according to the share of jobs in each industry held by STEM workers (See Appendix Table A2, Wu et al., 2020). We define an EPZ as “high-tech supportive” if two or more pillar industries (out of three) are high-tech. 23 Following Zheng et al., 2017, we group all plants into 2 age categories based on their establishment year: before 1998 (earlier stage of the economic reform) and after 1998 (later stage of the reform). The young firm dummy equals 1 if a firm is established after 1998. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Amiti M Javorcik BS Trade costs and location of foreign firms in China Journal of Development Economics 2008 85 1–2 129 149 10.1016/j.jdeveco.2006.06.001 Bajgar M Javorcik B Climbing the rungs of the quality ladder: FDI and domestic exporters in Romania The Economic Journal 2020 130 628 937 955 10.1093/ej/ueaa003 Belderbos R Carree M The location of Japanese investments in China: Agglomeration effects, keiretsu, and firm heterogeneity Journal of the Japanese and International Economies 2002 16 2 194 211 10.1006/jjie.2001.0491 Blomström M Kokko A Multinational corporations and spillovers Journal of Economic Surveys 1998 12 3 247 277 10.1111/1467-6419.00056 Capron H Cincera M Exploring the spillover impact on productivity of world-wide manufacturing firms The Economics and Econometrics of Innovation 1998 49 50 565 587 Chang SJ Xu D Spillovers and competition among foreign and local firms in China Strategic Management Journal 2008 29 5 495 518 10.1002/smj.674 Chen Z Poncet S Xiong R Inter-industry relatedness and industrial-policy efficiency: Evidence from China’s export processing zones Journal of Comparative Economics 2017 45 4 809 826 10.1016/j.jce.2016.01.003 Cheung KY Ping L Spillover effects of FDI on innovation in China: Evidence from the provincial data China Economic Review 2004 15 1 25 44 10.1016/S1043-951X(03)00027-0 Ciani A Imbruno M Microeconomic mechanisms behind export spillovers from FDI: Evidence from Bulgaria Review of World Economics 2017 153 4 703 734 10.1007/s10290-017-0290-4 Clarke D Tapia-Schythe K Implementing the panel event study The Stata Journal 2021 21 4 853 884 10.1177/1536867X211063144 Debaere P Lee J Paik M Agglomeration, backward and forward linkages: Evidence from South Korean investment in China Canadian Journal of Economics/revue Canadienne D'économique 2010 43 2 520 546 10.1111/j.1540-5982.2010.01582.x Feenstra R Hong C Ma H Spencer B Contractual versus non-contractual trade: The role of institutions in China Journal of Economic Behavior and Organization 2013 94 281 294 10.1016/j.jebo.2013.08.009 Ge W Special economic zones and the economic transition in China 1999 World Scientific Girma S Gong Y FDI, linkages and the efficiency of state-owned enterprises in China The Journal of Development Studies 2008 44 5 728 749 10.1080/00220380802009233 Girma S Gong Y Görg H Foreign direct investment, access to finance, and innovation activity in Chinese enterprises The World Bank Economic Review 2008 22 2 367 382 10.1093/wber/lhn009 Glaeser, E. L., & Gottlieb, J. D. (2008). The economics of place-making policies (No. w14373). National Bureau of Economic Research. Glass AJ Saggi K Multinational firms and technology transfer Scandinavian Journal of Economics 2002 104 4 495 513 10.1111/1467-9442.00298 Görg H Strobl E Multinational companies and indigenous development: An empirical analysis European Economic Review 2002 46 7 1305 1322 10.1016/S0014-2921(01)00146-5 Huang Z He C Zhu S Do China’s economic development zones improve land use efficiency? The effects of selection, factor accumulation and agglomeration Landscape and Urban Planning 2017 162 145 156 10.1016/j.landurbplan.2017.02.008 Irwin DA Klenow PJ Learning-by-doing spillovers in the semiconductor industry Journal of Political Economy 1994 102 6 1200 1227 10.1086/261968 Jabbour L Mucchielli JL Technology transfer through vertical linkages: The case of the Spanish manufacturing industry Journal of Applied Economics 2007 10 1 115 136 10.1080/15140326.2007.12040484 Ladd H Spatially targeted economic development strategies: do they work? Cityscape: A Journal of Policy Development and Research 1994 1 193 218 Levitt, T. (1993). The globalization of markets. Readings in International Business: a Decision Approach, 249. Ma X Huang C Fu Y Gao J Qin B Study on evolution of China’s construction industry based on input-output analysis and complex network Tehnički Vjesnik 2019 26 1 208 216 Manova K Yu Z How firms export: Processing vs. ordinary trade with financial frictions Journal of International Economics 2016 100 120 137 10.1016/j.jinteco.2016.02.005 Markusen JR Venables AJ Foreign direct investment as a catalyst for industrial development European Economic Review 1999 43 2 335 356 10.1016/S0014-2921(98)00048-8 Marshall A Principles of economics: Unabridged 2009 8 Cosimo Inc Moser P Voena A Compulsory licensing: Evidence from the trading with the enemy act American Economic Review 2012 102 1 396 427 10.1257/aer.102.1.396 Neumark D Kolko J Do enterprise zones create jobs? Evidence from California’s enterprise zone program Journal of Urban Economics 2010 68 1 1 19 10.1016/j.jue.2010.01.002 Neumark D Simpson H Place-based policies Handbook of regional and urban economics 2015 Elsevier 1197 1287 Pack H Saggi K Vertical technology transfer via international outsourcing Journal of Development Economics 2001 65 2 389 415 10.1016/S0304-3878(01)00142-0 Pak CD Park JD The special economic zones of China and their impact on its economic development 1997 Greenwood Publishing Group Parente SL Prescott EC Barriers to technology adoption and development Journal of Political Economy 1994 102 2 298 321 10.1086/261933 Shrestha N Shad MY Ulvi O Khan MH Karamehic-Muratovic A Nguyen USD The impact of COVID-19 on globalization One Health 2020 11 100180 10.1016/j.onehlt.2020.100180 33072836 Temu, I. (2019). Export processing zone policy in Papua New Guinea. Wang, C., & Zhao, Z. (2008). Horizontal and vertical spillover effects of foreign direct investment in Chinese manufacturing. Journal of Chinese economic and foreign trade studies. Wang J The economic impact of special economic zones: Evidence from Chinese municipalities Journal of Development Economics 2013 101 133 147 10.1016/j.jdeveco.2012.10.009 Wei YD Zone fever, project fever: Development policy, economic transition, and urban expansion in China Geographical Review 2015 105 2 156 177 10.1111/j.1931-0846.2014.12063.x Wu W Hong C Muhammad A The Spillover effect of export processing zones China Economic Review 2020 63 101478 10.1016/j.chieco.2020.101478 Zhang J Interjurisdictional competition for FDI: The case of China's “development zone fever” Regional Science and Urban Economics 2011 41 2 145 159 10.1016/j.regsciurbeco.2010.12.002 Zheng S Sun W Wu J Kahn ME The birth of edge cities in China: Measuring the effects of industrial parks policy Journal of Urban Economics 2017 100 80 103 10.1016/j.jue.2017.05.002
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==== Front Adv Health Sci Educ Theory Pract Adv Health Sci Educ Theory Pract Advances in Health Sciences Education 1382-4996 1573-1677 Springer Netherlands Dordrecht 36508137 10192 10.1007/s10459-022-10192-w Article “Every day that I stay at home, it's another day blaming myself for not being at #Frontline”–Understanding medical students' sacrifices during COVID-19 Pandemic http://orcid.org/0000-0003-0731-9308 Lima Ribeiro Diego [email protected] 12 http://orcid.org/0000-0002-2688-1905 Pompei Sacardo Daniele 2 https://orcid.org/0000-0003-1668-2002 Jaarsma Debbie 3 https://orcid.org/0000-0001-7008-4092 de Carvalho-Filho Marco Antonio 4 1 grid.4494.d 0000 0000 9558 4598 University Medical Center Groningen, University of Groningen, Groningen, The Netherlands 2 grid.411087.b 0000 0001 0723 2494 Department Public Health, Medical Sciences College, University of Campinas, Campinas, Brazil 3 grid.5477.1 0000000120346234 Dean at the Faculty of the Veterinary Medicine, Utrecht University, Utrecht, Netherlands 4 grid.4494.d 0000 0000 9558 4598 LEARN (Lifelong Learning, Education & Assessment Research Network), University Medical Center Groningen, Groningen, The Netherlands 12 12 2022 121 5 5 2022 24 11 2022 © The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. COVID-19 struck the world and stretched the healthcare system and professionals. Medical students engaged in the pandemic effort, making personal and professional sacrifices. However, the impact of these sacrifices on students` professional development is still unknown. We applied constructivist grounded theory to individual audio diaries (total time = 5h38 min) and interviews (total time = 11h57min) performed with 18 last-year medical students during the first wave of COVID-19 pandemic in Brazil. The perspective of making sacrifices caused initial emotional distress in medical students, followed by a negotiation process revolving around three themes: predisposition to sacrifice, sense of competence, and sense of belonging. This negotiation process led to three response patterns: Pattern A: “No sense of duty”–the sacrifice was perceived as meaningless, and students showed intense anger and a desire to flee; Pattern B: “Sense of duty with hesitation to act”–the sacrifice was acknowledged as legitime, but students felt unprepared to contribute, leading to feelings of frustration and shame; and, Pattern C: “Sense of duty with readiness to act”–the engagement with the sacrifice was perceived as an opportunity to grow as a doctor, leading to fulfillment and proudness. Students ready to engage with the COVID-19 effort experienced identity consonance, reinforcing their professional identities. Students who felt incompetent or found the sacrifice meaningless experienced identity dissonance, which led to emotional suffering and the consideration of abandoning the course. Monitoring students' emotional reactions when facing professional challenges creates opportunities to problematize the role of sacrifice in the medical profession and scaffold professional identity development. Supplementary Information The online version contains supplementary material available at 10.1007/s10459-022-10192-w. Keywords Identity formation Professional development Undergraduate medical education Qualitative research ==== Body pmcIntroduction Since 2019, COVID-19 successive cases waves burden the healthcare system and its devoted professionals (Guan et al., 2020; Wang et al., 2021). Although facing the COVID-19 pandemic in the frontline may bring professional fulfillment to healthcare workers (Johnson & Butcher, 2021; Royal Collage Of Physicians, 2020; Simons & Vaughan, 2020), it can also trigger higher levels of distress (Kisely et al., 2020; Lai et al., 2020; Pollock et al., 2020) and increase the risk of getting infected and sometimes becoming critically ill (Shanafelt et al., 2020). Medical students also joined the COVID-19 effort, taking up diverse roles with different levels of exposure and risk, often making personal and professional sacrifices. However, we still do not understand how medical students deal with and make sense of the sacrifice related to engaging in the COVID-19 pandemic effort. The existing literature on students’ involvement in the pandemic is still mainly quantitative, survey-based, and the medical education field could benefit from more nuanced, qualitative understanding. For instance, realizing how students deal with and make sense of the sacrifices related to the pandemic may provide medical educators with insights to improve educational strategies to support students` professional development and guide educators in similar situations in the future. The COVID-19 pandemic challenged healthcare professionals worldwide to stand up and engage in unprecedented sacrifice (Aschwanden, 2021; Wang et al., 2021). Risking becoming sick, working extra hours, dealing with the scarcity of resources, and self-isolating from loved ones are examples of sacrifices embraced with courage, responsibility and commitment (Rosenbaum, 2020). The pandemic also unsettled undergraduate medical education, raising new challenges for both educators and students (Balanchivadze & Donthireddy, 2020; Eva, 2020; Lapolla & Mingoli, 2020; McCullough et al., 2020). Initially, students were, in general, removed from clinical activities because of their potential for being infected or spreading the contamination (Long et al., 2020; Rasmussen et al., 2020; Soled et al., 2020). However, in different countries, medical students' role in the pandemic gradually changed, and they became part of the pandemic task force (Klasen et al., 2020; Rose, 2020; Tempski et al., 2021). This call to help with the pandemic effort imposed sacrifices to medical students similar to those imposed on healthcare professionals. Sacrifice in medical education The Cambridge dictionary defines sacrifice as "an act of giving up something valued for the sake of something or someone else regarded as more important or worthy" (Cambridge Dictionary, 2021). Sacrifice has a multidimensional nature and has been the subject of study in several academic areas, each contributing with a different perspective to its understanding (Florczak, 2004; Lambek, 2014). Theologians recognize the crucial role of sacrifice in many religions, such as Judaism, Christianism, Muslimism, and Hinduism, as a way to connect with God or the sacred (Florczak, 2004). Sociologists and anthropologists explore how many societal groups use sacrifice as a rite of passage or an asset to feed the interconnectedness of members and sustain membership (Mayblin & Course, 2014). Most psychological theories understand making personal sacrifices as a process of moving away from the comfort zone towards achieving personal development and maturity (Lambek, 2014). However, medical educators still debate the role of sacrifice in the realm of medical practice and have different views on the role of sacrifice in students' professional development (McCullough et al., 2020; Nistelrooy, 2014; Rose, 2020; Tempski et al., 2021). Historically, practicing medicine involves assuming the burden of exposing oneself to the risk of getting sick and an implicit acceptance of personal sacrifice (Florczak, 2004; Lambek, 2014; Nistelrooy, 2014). Many medical educators and practitioners consider the disposition to sacrifice as a cornerstone of the medical profession (Cruess et al., 2016; Nistelrooy, 2014; Ritchie, 1988). They believe that sacrifice in the format of altruism is a virtue present already in the Hippocratic oath, and medical educators should embrace and even encourage professional sacrifice during medical training (Wicks et al., 2011). Those authors argue that when a physician is caring for a patient, there is always a degree of self-sacrifice in order to prioritize patients` needs and interests over her/his own (Nistelrooy, 2014). Following this line of thought, the moral duty to help needs to prevail over doctors' personal interests (Post et al., 1995) to achieve patient-centered care. Many medical educators, however, claim that this call to sacrifice may inadvertently become an idealization of sacrifice, which may alienate doctors from their own motivations and beliefs, bringing negative consequences for doctors' physical and mental health (Johnson & Butcher, 2021; Jones, 2002). These educators believe that when sacrifice is idealized, students and doctors alike risk ending up feeling insufficient and, consequently, frustrated, invaded by feelings of low self-esteem, burnout, and compassion fatigue (Bishop & Rees, 2007). For instance, this culture of sacrifice may drive doctors to embrace excessive workload and accept sub-optimal work conditions (Bishop & Rees, 2007; Johnson & Butcher, 2021; Rosenbaum, 2020). According to this view, doctors need to prioritize their own well-being to be able to take care of others (Bishop & Rees, 2007; Cox, 2020; Rosenbaum, 2020; Sarkar & Cassel, 2021). Aim By combining the two arguments, it is reasonable to assume that sacrifice in medicine can both drive to connection with patients and the profession (Florczak, 2004; Nistelrooy, 2014), and also trigger emotional suffering and detachment (Nakatsu, 2021). We believe that the COVID-19 pandemic offers an opportunity to explore how medical students deal with and reflect on the idea of sacrificing themselves for the benefit of patients and society. Understanding students` processes of making sense of the sacrifice related to engaging in the COVID-19 pandemic effort may both shed light on the role of sacrifice in the medical training and also offer insights on how pedagogical approaches could scaffold students` personal and professional development when dealing with situations related to perceived self-sacrifice. Methods Study design This is a qualitative study performed under a constructivist paradigm, which means that we acknowledge reality as a plural and subjective construct born within a certain context. We used constructivist grounded theory methodology to guide the collection and analysis of a data set comprised of last-year medical students' audio diaries and individual interviews (Kennedy & Lingard, 2006; Monrouxe, 2009; Tai & Ajjawi, 2016; Watling & Lingard, 2012). Consistent with this methodology, we collected the audio diaries, scheduled the interviews, and analyzed the data iteratively so that data analysis informed data collection and vice-versa (Watling & Lingard, 2012; Watling et al., 2017). This study received ethical approval from the research ethics committee of the State University of Campinas (CAAE:36,882,620.3.0000.5404). Study context and participants We carried out this study with last-year medical students from one school in Brazil. In the Brazilian context, undergraduate medical training lasts six years. The last two years are clinical, and medical students have daily responsibilities in the direct care of patients. It is worth noticing that recently graduated physicians in Brazil are allowed to work autonomously in primary and emergency care, both areas directly involved in the frontline of the COVID-19 effort. We collected the data in a public university connected to a Brazilian public hospital that provides tertiary care for a population of six million inhabitants (Hospital de Clínicas da Unicamp, 2022). This hospital operates in an overcrowded and low-resource context. During the pandemic, it became a reference center for COVID-19 care, which increased demand and reduced the availability of already low resources. Over the study, it recorded 36.614 COVID-19 cases with 593 confirmed deaths (Hospital de Clínicas da Unicamp, 2021). During this study, medical students' engagement with the pandemic effort had different phases. Initially, Brazilian medical schools discontinued onsite practical activities, which were replaced by lectures and small group sessions in an online environment. During this initial period, students could: (a) volunteer to work with telemedicine initiatives related to COVID-19, (b) engage in practical activities with COVID-19 patients in temporary field hospitals created to deal with the overflow of patients, or (c) participate solely in the online activities. As the pandemic grew, some medical schools, including the one where this study was conducted, resumed curricular clinical activities and senior students had to participate in the mandatory practical activities at the university hospital and primary care facilities, where the exposure to COVID-19 patients was inevitable (Legislativa, 2021; Tempski et al., 2021). We did not observe an impact of the nature of the activities (volunteer x mandatory) on students’ internal negotiation process. Recruitment DLR, the first author, who worked in the frontline supervising medical students, contacted class representatives directly and explained the research plan and objectives. The class representatives shared the information about the project with the students. The ones interested in participating contacted DLR by phone or email. The research team purposefully included students of different ages, genders, and socioeconomic backgrounds. The selected students received the instruction as follows: “We invite you to record audio diaries about the experiences you are living during the pandemic. We are particularly interested in the daily incidents involving choices about whether or not to participate in practical clinical activities related to COVID-19. We would like you to share your thoughts, doubts, and feelings and how they affect your professional development. During this period, I will schedule an interview with you to talk about your experiences.” Students were free to send as many audio diaries as they found relevant and were interviewed during the data collection period (March-December 2020) by DLR. The interviews and audio diaries were collected throughout the first pandemic wave (Ministério da Saúde, 2021; Secretaria Municipal de Saúde, 2020), as shown in Fig. 1.Fig. 1 Audio diaries and interviews of medical students during the first wave of the COVID-19 pandemic in Campinas. Campinas State University, Campinas, Brazil, 2020 As the research group realized that students had different perspectives, emotional reactions, and attitudes about their participation in the pandemic effort, DLR purposefully recruited new participants to cover different behaviors and emotional reactions. The fact that DLR had daily contact with students during the clinical work helped in this matter. Data collection and analysis Eighteen medical students participated in the study, resulting in 89 audios (average of 4.94 audios per student) with a total time of 5h38min and 18 interviews with a total time of 11h57min (average of 40min23sec per student). The students recorded the audios and sent them to DLR through a storage cloud or smartphone messages (by their choice). DLR transcribed and anonymized the audio files before sending them to MACF and DS. The interviews happened through videoconference and were recorded and transcribed verbatim without identifying data. The audio diaries were intended to capture students' immediate reactions when confronted with the idea of participating in the COVID-19 effort. These diaries were collected throughout the first pandemic wave and included the period when students had to migrate from voluntary work to mandatory clinical activities. At the time of the interviews, the research team had already collected and analyzed some of the audio-diaries transcripts. The concept of “sacrifice” appeared spontaneously and remarkably. Thus, in the interviews, DLR (a) examined how the pandemic fluid context (as governmental institutions and the university were making constant decisions to adapt to the ever-changing pandemic reality) was affecting students` personal and professional lives, (b) invited them to deepen their reflections (already started in the audio-diaries) on the sacrifice they were making individually and as a group, searching for the “why,” “what,” and “how”; and (c) explored the experiences narrated in the audio diaries, inviting students to make sense of these experiences. The interviews were also spread along the first pandemic wave to capture different moments and contexts and allow researchers to explore the nuances of this complex social process. DLR was responsible for collecting the data. DLR, MACF, and DS analyzed the data iteratively and constantly compared new data and interpretations with previous assumptions and understandings, an approach consistent with the grounded theory methodology (Kennedy & Lingard, 2006; Tai & Ajjawi, 2016; Watling & Lingard, 2012). First, DLR, DS, and MACF read the initial audio diaries transcripts in detail, interpreting and identifying the first codes related to understanding how students were dealing with the COVID-19 pandemic. They met weekly to compare the codes in a process that allowed the addition, subtraction, or transformation of the codes. The first audio diaries' analysis allowed the research team to reflect and elaborate on the topics to address in the first interview. However, during the interview, DLR was thorough in keeping the conversation open, adopting an active listening attitude, constantly elaborating the following question from the perspective of the last answer. Next, the same three authors read the first transcribed interview individually and coded it line by line. In a group discussion, the authors compared their interpretations to reach a consensus on the initial codes. Then, these researchers returned to the audio diaries to elaborate further on their coding process and contrast assumptions and understandings. After the first interview, data analysis and collection went on in cycles that followed the structure: transcribing and coding the new audio diaries, elaborating on the interview protocol, coding the interview transcript, re-checking the audio diaries, and refining the coding. After each cycle, the researchers engaged in meaning-making and insightful discussions to elaborate on the elements, context, mechanisms, and relationships in place when students were dealing with the idea of sacrifice related to the COVID-19 pandemic. The codes and selected quotations were translated to English and shared with DJ so she could engage in the discussion. DJ, who comes from a different cultural background, helped the authors to make strange what was already taken for granted, enriching data analysis. DLR used a logbook to register discussions and insights and keep track of the process. The research group meetings were recorded to allow further reflection on the ideas, interpretations, codes, and diagrams, aiming to create meaning at a conceptual level. Along this process, the research team aligned the codes into themes, which were elaborated further at a theoretical level, generating the diagram shown in Fig. 2. Following information power theory in qualitative research, the researchers decided to stop data collection after the first pandemic wave when the data generated through the analysis and theoretical interpretation of audio-diaries and interviews conveyed sufficient information to construct new knowledge to answer our research questions (Malterud, 2012; Malterud et al., 2016; Morse, 2015; Varpio et al., 2017), i.e., we stopped data collection when we could comprehend the complexity of the student's emotional reactions, internal negotiation processes, and response patterns concerning the sacrifices made during the pandemic first wave.Fig. 2 Medical students' responses when facing sacrifices in COVID-19 pandemic. Campinas State University, Campinas, Brazil, 2020 Research group and reflexivity The debate about sacrifice may inspire passions and pre-conceived ideas about what is “right” and what is “wrong” or, even, what should be expected from a doctor or medical student. For instance, frontline health care professionals may take the willingness to sacrifice for granted and negatively judge students who hesitate in engaging in the pandemic effort. With this in mind, we understood that we needed a diverse group capable of bringing different perspectives to this discussion. DLR is a general clinical practitioner who worked in the emergency room in the frontline at the same institution where data was collected. He brought an insider view tempered by his own sacrifices during the pandemic and his expectations as a clinical supervisor. DS is a psychologist and bioethics professor in the same institution with a particular interest in identity and moral development. She offered a non-clinical perspective and helped modulate the debate by pointing out the blind spots of the physicians. DJ is an experienced medical education researcher and has a different cultural background. She helped the group fine-tune data analysis to identify the most relevant contributions to the field and expand group insights on the general idea of sacrifice—a phenomenon deeply influenced by culture. Finally, MACF is also an emergency physician who has worked for fifteen years in the emergency department of the same institution as a clinical teacher but who went through a career change during the last five years, when he gave up clinical activities to become a medical educator and qualitative researcher full time, with a particular interest in medical students´ transition to practice. He did not engage in the pandemic effort as a clinician, which allowed him to combine the clinical and educational perspectives. It is worth mentioning that the data was collected in Portuguese (the native language of DLR, DS, and MACF). Pieces of the data, the codes, and the themes, were translated to English to allow DJ to engage in the data analysis. DLR, DS, and MACF, who are also fluent in English, guaranteed that the translations were faithful to the meanings conveyed, especially when metaphors, slang, or idiomatic expressions were used (Helmich et al., 2017a, 2017b). Results The participants' ages ranged between 20 and 27 years old, and fourteen were women. Among the eighteen participants, four reported having financial difficulties, and at least six reported having no financial restrictions. We did not notice any connection between these different backgrounds and participants’ narratives. The frequent use of sarcasm, metaphors, and swearwords suggested that recording the audio diaries (quotations ending with the letter A) offered students an opportunity for catharsis and outbursts. The interviews (quotations ending with the letter I) provided complementary information by inviting students to deepen their reflections, which generated insights about their meaning-making processes. In the following paragraphs, we will share our understanding of the mechanisms by which medical students make sense of the sacrifices related to the Covid-19. First, we describe the medical students' initial emotional reactions to the prospect of making sacrifices during the pandemic. Second, we elaborate on students' internal negotiation process that revolved around three themes (Predisposition to Sacrifice, Sense of Competence, and Sense of Belonging). Finally, we reflect on how this negotiation evolved to three different response patterns (A—"No sense of duty,", B—"Sense of duty with hesitation to act" and C -"Sense of duty with readiness to act"). These patterns involved attitudinal, emotional, and behavioral aspects, as show in Fig. 2. Initial emotional reactions Fear, sadness and anxiety were the first emotional reactions evoked by the perspective of making personal and professional sacrifices during the pandemic. The risk of getting severely ill or bringing the disease to their loved ones evoked fear. The perception of a global scenario of suffering brought sadness. The uncertainty about the fast spread of an unknown disease without any specific treatment, the initial lack of training to deal with this disease and the possibility of delaying graduation triggered high levels of anxiety. Moreover, this anxiety was particularly burdensome for students with a previous anxious personality.ADA1I “I've always been an anxious person. In this quarantine, it is something that I have seen as a pattern for all my 6th-year friends. Everyone who already had some anxiety went crazy at some point. This thing… like, you do not know how your last year of graduation will be; you do not know when you will graduate. It is not only the graduation. But also, the fear: Do I have asymptomatic COVID? Will my mom get COVID and die? And sadness too, because all this suffering is terrible. I feel sorry for the (medical) residents who got sick…” After this initial reaction, students started an internal negotiation process to figure out whether they should or should not engage in making personal and professional sacrifices to embrace the effort to fight COVID-19. As the same student said:ADA1A6 “I know that many people are terrified with the possibility of getting coronavirus, of getting sick, of dying… Anyway, I felt as if having to make a choice between my family, my boyfriend and doing something that I feel is my duty, you know?” In the next paragraphs, we elaborate on how this negotiation unfolded around three main intertwined themes (Fig. 2). Themes Predisposition to sacrifice Some students recognize sacrifice as a core element of the medical identity. These students started reflecting on the role of sacrifice in medicine even before entering medical school and often came from families who embraced making sacrifices to help others as a paramount moral or religious value. In fact, this willingness to sacrifice was nurtured by students` social interactions inside and outside the medical realm. These students considered making sacrifices a source of meaning, fulfillment, and even joy.ADA5I “...oh, I think I have always learned that I need to get involved with what is going on. That I need to be useful. That I need to be proactive and help people. My father always gets involved with social matters, and my mother is a teacher. So, I was raised like that. There is also the religion I chose and I practice. My faith, the things I believe, all that influences my decision about what I should be doing in a moment of crisis. I want to be useful.” This readiness to accept sacrifices helped students face complex and challenging situations related to the decision of engaging with patient care during the pandemic, such as isolating themselves from their families, abdicating from caring for sick relatives, or not going to funerals of loved ones. Choosing to embrace their professional duties while not being able to care for their families in these challenging times was particularly painful to those students.ADA4A4 “... but also, I get really scared about getting sick and infecting people in my family, right? So, as I'm taking shifts in the emergency department and helping in the field hospital, I had to leave home because my father is old and my mother takes care of her mother, who has Alzheimer [...] I'm already two or three weeks away from home ... But this situation is very difficult.” Some students did not recognize sacrifice as a core element of the medical profession. This group felt betrayed and treated unfairly when asked to engage with patient care during the pandemic as if they had received an "unexpected request". This group also pointed out a gap between society's expectations about how doctors should embrace sacrifice and the inadequate working conditions they face in the healthcare system, such as the high workload and lack of resources and structure. Besides, these students believe that the idealization of sacrifice is an instrument to sustain a paternalist and oppressive culture in which doctors, particularly the newcomers, have to accept the status quo without complaining. The perspective of being obligated to make (perceived) meaningless sacrifices generated anger and was so painful that some students considered giving up medical school. These students do not accept the idea that doctors are saviors or selfless heroes.ADA8A2 “I have been reflecting a lot about the profession I chose, and more and more, I am sure that this is not my place. Being a doctor, for me, is not a vocation. It is not awesome. A doctor is a worker, a factory worker, like any other. There is nothing noble that you should be so grateful for. There are earnings, sometimes much more than one should have. There are no special places for doctors in heaven. I kept thinking that these noble and deified thoughts (about being a doctor) end up making doctors risk their lives. This devotion in moments of crisis does not fool me. For me, it is only food for the doctor's Ego fantasy.” A third group of students manifested an ambiguous attitude towards sacrificing during the pandemic. These students felt an urge to help and perceived the value of sacrificing themselves. Still, they could not transform this inclination into a concrete action because they were afraid of getting sick and not being prepared as doctors. Students in this group perceived their hesitation as a lack of resolution, which generated frustration and sadness, together with feelings of low self-esteem. Those hurtful emotional reactions were still latent during the interviews, and some students cried spontaneously or stopped talking abruptly.ADA1A9 “I talked a lot about it with my friend, about what were the reasons I would not volunteer. Staying in the hospital twice a week with a few patients (with covid-19) and feeling the fear of bringing home the disease. And I'm not in my best mental health at this moment. I'm very anxious... and so far, I'm still not comfortable with my decision about not volunteering. I thought going wouldn't do me any good, but I'm feeling guilty about not going...” Sense of competence Some students felt competent to engage in patient care and were excited about the possibility of helping. They believed there is always something that one can do to help, regardless of one's skills level. Indeed, they mentioned they could establish a good doctor-patient relationship, gather relevant clinical information, conduct an efficient physical examination, develop a coherent diagnostic workout, and build up a structured therapeutic plan—all relevant competencies for taking care of COVID patients. They tried to seize the opportunity the pandemic offered to deepen their learning. They engaged in the care of as many patients as possible, optimizing the learning opportunities born from the contact with patients, residents, and supervisors. They also tried to participate as much as they could in clinical procedures. Feeling competent to engage in patient care brought those students professional fulfillment and a sense of purpose, making them proud of themselves.ADA16I “I knew I had little time and that I had to absorb as much as I could in those days (of dealing with COVID patients). I was at the resident's feet: "What are you seeing? What do you think of the residency? This case … Show me the EKG! How is it? What should we do? What is the dose of this medication?" The whole time I was imagining it as if I was taking the lead [...] I wanted to stay longer. The fact that we have less time makes us waste no time: any patient who arrives, you go there, see, talk, so that you can really learn there. And you learn a lot there.” Students who judged themselves incompetent to engage in clinical care felt insecurity, fear, and low self-esteem. The lack of practical experience to perform complex procedures such as orotracheal intubation or central line placement froze those students. It prevented them from feeling confident to provide medical care during the pandemic. Worth noticing is that they mentioned that supervisors did not expect students to perform such complex procedures. These students did not see the pandemic context as conducive to learning and felt angry when called to join clinical care.ADA6I “A big concern I have this year, I think it should be for every medical student, is technical skills. I keep thinking that I'm very incompetent technically. I still need to learn a lot, and I feel very insecure about going into professional life. And especially at the beginning of the quarantine, I felt very anguish with that... I thought "I didn't pass through the anesthesiology (rotation) yet, so I've never performed an orotracheal intubation in my life" Sense of belonging Feeling part of the medical community motivated students to engage in the pandemic effort while feeling an outsider demotivated them. This sense of belonging to the medical community happened in three different but complementary spheres. First, for some participants, being a medical student during the pandemic created a sense of connection with all the students facing the same challenges and making the same sacrifices around the country and the globe. Next, some students also felt connected with the residents mobilized ‘to fight’ the pandemic, often migrating from their regular placements to COVID-19 observation units, helping in clinical activities different from their field of expertise. Finally, a group of students felt proud of belonging to the community of healthcare professionals in this unprecedented time. Feeling part of these groups nurtured students with courage. Also, these students felt that being part of the medical community and not volunteering to help would not be fair to their colleagues, especially in circumstances where health professionals were risking their own lives to protect others.ADA13I “The residents are very overloaded, and they don't have a choice. So, as I had the option to help, I said "I'll help!". So, they (the residents and healthcare professionals) are working because they don't have a choice, but I have the option, I will work, I'll help, I think any help in this situation helps a lot.” On the other hand, some students felt isolated, abandoned, and did not identify with any of those spheres (medical students, residents, or health care professionals). Those students felt excluded or neglected most of the time, often referring to the medical community as "them"—a distant group they did not belong to. Besides, when they felt excluded from the decision-making process about their training activities during the pandemic, it reinforced their outsider stance.ADA2A2 “You hear everywhere: "Ah, doctors are heroes! They are the front lines! What a wonderful profession!" And several friends are saying that they feel they have a duty to do something as a medical student, saying that they must do something... Then there's a report that medical students are doing volunteer work, saying: "Look, that's awesome!" And everyone says, "Wow, that's perfect!" And in my chest, I don't feel any of that, you know?” Synergy among the predisposition to sacrifice, sense of competence, and sense of belonging The themes mentioned above range in a spectrum of intensity and are interconnected reinforcing or hampering each other. Students who mentioned a predisposition to sacrifice were the same who felt competent to help and saw themselves as members of the medical community. Students who did not embrace the idea of sacrificing also felt incompetent and outsiders. In-between, there was a group of students with an ambiguous attitude. After the negotiation around these themes, students came to a one-off decision-point related to their 'duty' as a doctor, showing three distinct response patterns (Fig. 2). Students response patterns Pattern A—no sense of duty (Angriness, Abandonment, Desire to flee) Students with pattern A could not find meaning in helping with the pandemic effort and even considered it wrong. For these students, their lack of clinical abilities would jeopardize patient care, and their presence in the front line would only increase the circulation of the virus. Moreover, they felt harassed by the health and educational system. They considered the idealization of professional sacrifice an instrument of intimidation to obligate doctors to work in conditions they consider psychologically or physically unacceptable. Those students expressed constant anger throughout the pandemic that varied only in intensity. They demonstrated sarcastic attitudes towards peers, doctors, other health professionals, and health care institutions. This lack of identification with the medical profession made them feel very uncomfortable in the doctor's role. They steadily manifested a desire to flee, even by abandoning medical school and training.ADA6A/I "I thought, "I'm just a student. I shouldn't go to the front line". I don't know how to do an orotracheal intubation, I do not know how to prescribe medicines[...] I would have to be on the front line totally unprepared! [...] I came to a conclusion with myself that, at that moment, I was not needed […]And when the practical activities became obligatory again, it was such a suffering for me. And it made me angry too because it started to cross my mind: "They (the clinical teachers) are definitely forcing us to come back." And then, there's a mix of feelings like anxiety and anger that it's been tough to deal with in the last two weeks." Pattern B—sense of duty with hesitation to act (Frustration, Guilt, Shame) Students with pattern B acknowledged the importance of helping and engaging in the pandemic effort but suffered to transform this disposition into concrete action. Although they volunteered for remote/online activities, they did not feel ready to participate in onsite clinical encounters during the pandemic. These students perceived this lack of readiness as a failure, which led to frustration, guilt, and feelings of shame. The shame was often so intense that some students avoided making eye contact during the interviews when sharing their initial decisions of not participating in the clinical activities.ADA2A2 "I keep thinking of doing this volunteer work… We learn a lot there, with the experience and everything else… To do what I believe is expected of us as medical students, as almost graduated doctors... But I can't identify what I really want to do and every day I stay at home, it's a day blaming myself for not being there in the hashtag frontline […]for being useless while Brazil needs me" Empowerment—During our study, some students who started the pandemic with this pattern changed their attitude and progressively felt empowered to embrace the clinical activities due to their growing sense of competence and belonging. Gradually, as they were exposed to the clinical care of COVID-19 patients, they realized that their skills were sufficient. In addition, getting closer to the health professionals strengthened their bonds, increasing their sense of belonging. They also understood how to minimize the risk of getting sick by adopting the necessary protective measures. In the end, these students made sense of the sacrifice, and the hesitation, insecurity, and frustration turned into proudness and fulfillment.ADA11I "So, I created this confidence that I didn't have before of being able to deal with situations like this. And then, this gave me security for taking the risk of being inside the hospital. After we had all that demonstration of how to use the individual protection equipment, I said, "well, of all the people who can volunteer and who will bring benefits to this place, I can be one of them." Then I decided that I already had the self-confidence to be able to do the work, I already had the means, and I felt like it, so I said, "it's possible." Pattern C—sense of duty with readiness to act (Proudness, Self-confidence, Fulfillment) Students with pattern C could transform the initial fearful and sad reaction into a disposition to act and help. Their acceptance of sacrifice as a vital element of the medical identity, associated with a strong bond with their peers and an internal disposition to make themselves useful, culminated in a readiness to help and engage in the COVID-19 effort. Whenever these students could play the doctors´ role, they felt excited, proud of themselves, and professionally fulfilled.ADA1I “All right, there is not really a right and wrong, but there is my right and wrong. Like, what kind of doctor do I want to be? I want to be a doctor who will be there when the population needs it. I want to be a doctor in the public health system, I want to work for people, I want to do... I want my work to help in some way, you know?” Discussion Our results shed light on how students dealt with and made sense (or not) of engaging in the effort to control the COVID-19 pandemic. First, we recognize that the perspective of making sacrifices during the pandemic led medical students to three different response patterns: no sense of duty, sense of duty with hesitation to act, and sense of duty with readiness to act. Second, we understood that making sense of such a sacrifice is an intensely emotional process that can either culminate in personal and professional fulfillment or feeling abandoned, angry and/or ashamed. Third, we realized that these responses could intensify or attenuate students' connection with the healthcare community. Finally, it become clear that such a sacrifice can be so stressful that some students feel the desire to flee and experience intense emotional suffering to the point of needing psychological support. The impact of medical students' sacrifices on their professional identity formation We believe that the sacrifices related to COVID-19 challenged students` professional identity. Our findings are aligned with Goldie's Identity Theory (Goldie, 2012; House, 1977). Goldie highlights the roles of social structure, an individual's personality, and the interaction between them in professional identity formation (Côté & Levine, 2014). According to Goldie, integrating new professional identities into personal identities is a more straightforward process for people whose personal identities align with their new professional role (Goldie, 2012). However, individuals who encounter an incongruity between their personal values and the belief system of the chosen profession experience identity dissonance (Joseph et al., 2017; Monrouxe, 2010; Wald, 2015). Identity dissonance can lead a medical student to intense emotional distress, including uncertainties about their own values, ambitions, and abilities (Dornan et al., 2015; Holden et al., 2015). In addition, students with identity dissonance can develop dysfunctional coping mechanisms, such as cynicism and emotional detachment–in an extreme, they may drop out of the course (Costello, 2005; Dornan et al., 2015). In our study, when students’ values and beliefs drove them towards what the medical community understood as their professional duty, students experienced identity consonance (Goldie, 2012; House, 1977). In this case, engaging in the pandemic effort was rewarding and offered an opportunity for medical students to bond with the profession (Côté & Levine, 2014), peers, and patients, strengthening their professional identity (Goldie, 2013; Joseph et al., 2017; Monrouxe, 2010). Being capable of helping meant being ready to become a doctor, empowered to be “part of the group”. This empowerment was also observed by Badger et al. (Badger et al., 2022), who registered that volunteering positively impacted medical students’ well-being and professional identity formation. According to Badger, the “sense of belonging and pride in achievement are drivers of engagement in authentic workplace-based practices and therefore learning”. Compton et al. (Compton et al., 2020) also pointed out that feeling part of the team influenced medical students' preferences to participate in clinical activities during the pandemic: “This is consistent with students' desire to be held to the high ethical standards of medical professionals and to be part of the medical team.” However, students who experienced identity dissonance struggled to make sense of professional sacrifices and felt forced to adopt behaviors and attitudes perceived as meaningless or even harmful. These students felt powerless outsiders and experienced intense emotional suffering. Extrapolating our data to other sacrifices related to the medical practice, we suggest that identifying whether sacrifices trigger identity consonance or dissonance is crucial to understanding what kind of support medical students will need. Coming back to the debate about the role of sacrifice we addressed in the introduction, we believe that both the idealization of sacrifice and its avoidance may restrain open and clear discussions about this theme. Open, safe, and democratic discussions about the role of sacrifice in medicine are fundamental to support students during their developmental process of approaching, giving meaning, and dealing with situations where they have to give up something of value to connect with patients, the profession and themselves. According to Costello, 'integrating new professional identities into personal identities is an easy process for people whose personal identities are consonant with their new professional role, but traumatic for those whose personal identities are dissonant with it' (Costello, 2005). Practical implications Students' emotional responses are a thermometer that indicates whether they are experiencing identity consonance or dissonance If educators manage to create a safe space for students to share their emotional responses, they will be able to identify students with different needs (Dornan et al., 2015). These sensitive conversations should be facilitated by a mentor who is not a medical professional because it can be very challenging for doctors to set their own expectations aside when addressing issues related to elements close to the core of their professional identities (Vries‐Erich et al., 2016), such as the role of sacrifice in the medical profession. Students feeling proud and ready to sacrifice need to become aware of the dangers of compassion fatigue and need to learn about setting limits that respect their well-being (Bishop & Rees, 2007). Students feeling frustrated and ashamed, which often reflects a conflict between “what they want to do” and “what they feel ready to do,” need support to come up with a plan to build up competence and self-confidence to engage in activities initially perceived as unachievable. Finally, students feeling angry, who cannot make sense of the challenges they have ahead, need time and space to engage in a more profound reflection about the profession, themselves, and their next steps (Dunn et al., 2008). These students would probably benefit from open conversations about medicine's different professional trajectories—trajectories with varying types of sacrifice and lifestyles. These conversations may enlighten their professional course, bringing comfort and hope. However, depending on the level of their suffering, these students may also need professional psychological support to deal with the career choices they have to face, even to reflect on the possibility of finding joy in a different profession (Dunn et al., 2008). The trajectory to become a doctor is a collective enterprise but an individual journey In the last years, educators in general and medical educators in particular have discussed the importance of individualizing learning trajectories to optimize students’ development (Cruess et al., 2015). We believe that this individualization is also necessary for professional identity development (Joseph et al., 2017). Although medical students have similar educational and professional experiences along the medical course, their professional identities develop at a different pace and probably follow different pathways. The three patterns we identified are living proof of this heterogeneity. Interestingly, students initially hesitating to engage with the pandemic effort were able to adopt a more proactive behaviour when they had the opportunity to feel empowered by increasing their competence level. This transition towards agency suggests that these patterns are dynamic and may be influenced by contextual forces, such as educational interventions targeting the specific professional skills needed to deal with the sacrifices at hand. Medical educators and clinical teachers should realize that students will make sense of the sacrifices according to their personal values and professional identity developmental stage. Discussing the meaning-making process around sacrifices may offer an opportunity to discuss professional identity development and personal fulfillment. As Picton recently suggested, students believe that there is a “cross-generational” and “underlying culture of self-sacrifice within medicine that could influence their work-life balance” (Picton, 2021). We hope this manuscript will contribute to the conversation about the role of sacrifice in medicine, going beyond the controversy about the “idealizating” or “demonizing” sacrifice, towards embracing the inherent complexity surrounding this topic. Sacrifices in low-resource settings We carried out this study in a middle-income country where physicians often work in understaffed teams, and frequently deal with the lack of structure, such as insufficient ICU beds, mechanical ventilators, and specific high-cost medications. Health care professionals, including doctors, in this context, are exposed to increased risks of contamination by infectious diseases such as tuberculosis (Ibañez, 2015). The lack of personnel often oblige doctors to work extra hours, which culminates in higher levels of stress, burnout, and emotional detachment (Kruk et al., 2018). Although the sacrifice imposed by the pandemic is exceptional (Dreifus, 2020), because of the magnitude (worldwide healthcare system impact), the intensity (brisk and significant increase in mortality rates), and the time-frame (long-lasting pandemic), it shares similarities with sacrifices physicians encounter in low-income and middle-income countries (Ibañez, 2015; Kruk et al., 2018). Medical students who are in-training in low-resource settings face these sacrifices routinely, which may lead to moral distress and influence their professional identity formation (Helmich et al., 2017a, 2017b; Silveira et al., 2019). Limitations Although our study has strengths, we suggest some caveats. First, in the context of our study, students were mandated at some point to engage with the caring of COVID patients. If students had more autonomy and freedom to decide whether and how to face the sacrifice related to the pandemic's efforts, perhaps the findings would be different. For example, if students had more autonomy or ownership over the process of engaging with the pandemic effort, they could come up with individualized and tailored approaches, which would possibly evoke different emotional reactions and response patterns. Second, our study comprises the first pandemic wave period only, so we could not investigate how and if these response patterns changed (or not) over the following pandemic waves. Third, we could not explore how and if these response patterns relate to sacrifices experienced in regular clinical experiences. Forth, DLR, the first author, worked on the pandemic frontline and supervised students, so his judgments and reflections on sacrifice may have influenced the data analysis and collection. However, as MACF and DS, who have different backgrounds and work contexts, analyzed the data independently, they helped DLR minimize that influence. Also, DJ has a diverse experience and comes from another culture, allowing the authors to "make strange" what was already accepted as natural or part of the culture. Fifth, we translated the coded audios and interviews from Portuguese to English to allow researchers with different cultural backgrounds to engage in data interpretation, broadening our perspectives. However, nuances and meanings can be lost during the translation, preventing a full comprehension of participants' perspectives. We minimized this impact by having frequent "reading-together" sections with the non-Portuguese speakers of our research group (Helmich et al., 2017a, 2017b). Sixth, the study was carried out in a single center (from one country), which makes the study's external validity difficult to ascertain. Seventh, there are inherent methodology limitations—the students who participated in the study could be more interested in sharing their experiences, and their responses may differ from the general student population. Also, we did not make before and after quantitative measurements since, as a qualitative study, it focused on exploring how medical students deal with and reflect on the idea of making sacrifices during the pandemic. Nonetheless, qualitative studies provide a singular opportunity to understand medical students' behavioral responses and therefore provide complementary knowledge to quantitative studies. Finally, we did not know our students' previous emotional and developmental status to understand whether the identity dissonance and consonance observed were solely related to the pandemic or processes already in course. Conclusion Students reacted differently to the sacrifice imposed by the COVID-19 pandemic. The three response patterns we described (no sense of duty, sense of duty with hesitation to act, and sense of duty with readiness to act) were accompanied by intense emotional reactions. Students who undergo a lack of alignment between personal beliefs and professional expectations experience identity dissonance and develop an “identity crisis.” Students who see the sacrifice as an opportunity to grow, serve society, and connect with their peers and future profession experience identity consonance and reassure their professional identity development. We wonder if exploring further these moments of “identity crisis or reassurance” could offer opportunities to shed light on the process of professional identity development while offering insights to devise supportive pedagogical interventions. We foresee that reflecting on these moments of crisis or reassurance may help students to develop ownership over their personal and professional development, and amplify their understanding about the profession they chose, and the career options they have. Fundamentally, elaborating on the process of handling professional sacrifices may guide students in matching their values, expectations, and beliefs with professional and societal needs. Supplementary Information Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 688 kb) Acknowledgements The authors thank the students who were brave enough to share their experiences. The authors also thank Bruno de Jorge for helping in designing figure 2. Author contributions MACF, DLR, and DS were responsible for the conception and design of the work. The first author (DLR) collected the data. MACF, DLR, DS, and DJ were responsible for data analysis and interpretation. All authors were involved in writing the manuscript and approved its final version. Funding None to declare. Declarations Conflicts of interest None to declare. Ethical approval The authors received ethical approval for the study from the Research Ethics Committee of the State University of Campinas (CAAE:36882620.3.0000.5404). Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Aschwanden C How covid is changing the study of human behavior Nature 2021 593 331 333 10.1038/d41586-021-01317-z 34007072 Badger K Morrice R Buckeldee O Cotton N Hunukumbure D Mitchell O Mustafa A Oluwole E Pahuja J Davies D Morrell MJ Smith S Leedham-Green K More than just a medical student: a mixed methods exploration of a structured volunteering programme for undergraduate medical students BMC Medical Education 2022 22 1 1 12 10.1186/s12909-021-03037-4 34980091 Balanchivadze N Donthireddy V Hematology/oncology fellowship emergency restructuring in response to the COVID-19 pandemic—henry ford hospital Michigan JCO Oncology Practice 2020 16 9 e943 e947 10.1200/op.20.00261 32407178 Bishop JP Rees CE Hero or has-been: is there a future for altruism in medical education? Advances in Health Sciences Education 2007 12 391 399 10.1007/s10459-007-9064-4 17530433 Cambridge University Press (2021) Cambridge Dictionary Retrieved 12 Dec, 2021, from https://dictionary.cambridge.org/pt/dicionario/ingles/sacrifice. Compton S Sarraf-Yazdi S Rustandy F Krishna LKR Medical students preference for returning to the clinical setting during the COVID-19 Medical Education 2020 54 10 943 950 10.1111/medu.14268 32519383 Costello CY Professional identity crisis: race, class, gender, and success at professional schools 2005 Vanderbilt University Press Côté JE Levine CG Identity, formation, agency, and culture: a social psychological synthesis 2014 Psychology Press Cox CL Healthcare heroes: problems with media focus on heroism from healthcare workers during the COVID-19 pandemic Journal of Medical Ethics 2020 46 510 513 10.1136/medethics-2020-106398 32546658 Cruess RL Cruess SR Boudreau JD Snell L Steinert Y A schematic representation of the professional identity formation and socialization of medical students and residents: a guide for medical educators Academic Medicine 2015 90 6 718 725 10.1097/ACM.0000000000000700 25785682 Cruess RL Cruess SR Steinert Y Amending miller’s pyramid to include professional identity formation Academic Medicine 2016 91 2 180 185 10.1097/ACM.0000000000000913 26332429 Dornan T Pearson E Carson P Helmich E Bundy C Emotions and identity in the figured world of becoming a doctor Medical Education 2015 49 174 185 10.1111/medu.12587 25626748 Dreifus, B. (2020). I ’ m a health care worker. you need to know how close we are to breaking. The New York Times. Dunn LB Iglewicz A Moutier C A conceptual model of medical student well being: promoting resilience and preventing Burnout Academic Psychiatry 2008 32 44 53 10.1176/appi.ap.32.1.44 18270280 Eva KW Strange days Medical Education 2020 54 6 492 493 10.1111/medu.14164 32221976 Florczak KL An exploration of the concept of sacrifice Nursing Science Quarterly 2004 17 3 195 200 10.1177/0894318404266423 15200718 Goldie, J. (2013). Identity formation in medical students: an elaboration of a previous conceptualisation and review of the literature. MedEDWorld, 1–23. Goldie J The formation of professional identity in medical students: considerations for educators Medical Teacher 2012 10.3109/0142159X.2012.687476 Guan W Ni Z Hu Y Liang W Ou C He J Liu L Shan H Lei C Hui DSC Du B Li L Zeng G Yuen K-Y Chen R Tang C Wang T Chen P Xiang J Zhong N Clinical characteristics of coronavirus disease 2019 in China New England Journal of Medicine 2020 382 18 1708 1720 10.1056/nejmoa2002032 32109013 Helmich E Cristancho S Diachun L Lingard L How would you call this in English?: Being reflective about translations in international, cross-cultural qualitative research Perspectives on Medical Education 2017 6 2 127 132 10.1007/s40037-017-0329-1 28220459 Helmich E Yeh HM Kalet A Al-Eraky M Becoming a doctor in different cultures: toward a cross-cultural approach to supporting professional identity formation in medicine Academic Medicine 2017 92 1 58 62 10.1097/ACM.0000000000001432 27782917 Holden MD Buck E Luk J Ambriz F Boisaubin EV Clark MA Mihalic AP Sadler JZ Sapire KJ Spike JP Vince A Dalrymple JL Professional identity formation: creating a longitudinal framework through TIME (Transformation in Medical Education) Academic Medicine 2015 90 6 761 767 10.1097/ACM.0000000000000719 25853688 Hospital de Clínicas da Unicamp. (2021). Institucional. Retrieved 05 Out, 2022, from https://www.unicamp.br/unicamp/coronavirus. Hospital de Clínicas da Unicamp. (2022). Institucional. Retrieved 05 Out, 2022, from https://hc.unicamp.br/institucional/. House JS The three faces of social psychology Sociometry 1977 40 2 161 177 10.2307/3033519 Ibañez, N. (2015). Política nacional de atenção às urgências no Brasil: periodização e marcos legais. In Conass. https://www.conass.org.br/biblioteca/caderno-conass-documenta-n-28/ Johnson SB Butcher F Doctors during the COVID-19 pandemic: what are their duties and what is owed to them? Journal of Medical Ethics 2021 47 12 15 10.1136/medethics-2020-106266 33060186 Jones R Declining altrism in medicine BMJ 2002 324 624 625 10.1136/bmj.324.7338.624 11895808 Joseph K Bader K Wilson S Walker M Stephens M Varpio L Unmasking identity dissonance: exploring medical students’ professional identity formation through mask making Perspectives on Medical Education 2017 6 2 99 107 10.1007/s40037-017-0339-z 28247208 Kennedy TJT Lingard LA Making sense of grounded theory in medical education Medical Education 2006 40 2 101 108 10.1111/j.1365-2929.2005.02378.x 16451236 Kisely S Warren N McMahon L Dalais C Henry I Siskind D Occurrence, prevention, and management of the psychological effects of emerging virus outbreaks on healthcare workers: rapid review and meta-analysis BMJ 2020 369 m1642 10.1136/bmj.m1642 32371466 Klasen JM Meienberg A Nickel C Bingisser R SWAB team instead of SWAT team: medical students as a frontline force during the COVID-19 pandemic Medical Education 2020 54 9 860 10.1111/medu.14224 32403176 Kruk ME Gage AD Arsenault C Jordan K Leslie HH Roder-DeWan S Adeyi O Barker P Daelmans B Doubova SV English M Elorrio EG Guanais F Gureje O Hirschhorn LR Jiang L Kelley E Lemango ET Liljestrand J Pate M High-quality health systems in the sustainable development goals era: time for a revolution The Lancet Global Health 2018 6 11 e1196 e1252 10.1016/S2214-109X(18)30386-3 30196093 Lai J Ma S Wang Y Cai Z Hu J Wei N Wu J Du H Chen T Li R Tan H Kang L Yao L Huang M Wang H Wang G Liu Z Hu S Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019 JAMA 2020 3 3 1 12 Lambek M Afterthoughts on sacrifice Ethnos 2014 79 3 430 437 10.1080/00141844.2012.747552 Lapolla P Mingoli A COVID-19 changes medical education in Italy: will other countries follow? Postgraduate Medical Journal 2020 96 1137 375 376 10.1136/postgradmedj-2020-137876 32404497 Legislativa, A. (2021). A Ficha informativa DECRETO N 65.140, DE 19 DE AGOSTO DE 2020 (pp. 13–16). Retrieved 12 Dec, 2021, from https://www.al.sp.gov.br/repositorio/legislacao/decreto/2020/decreto-65140-19.08.2020.html. Long, N., Wolpaw, D. R., Boothe, D., Caldwell, C., Dillon, P., Gottshall, L., Koetter, P., Pooshpas, P., Wolpaw, T., & Gonzalo, J. D. (2020). Contributions of health professionss students to health system needs during the COVID-19 pandemic: potential strategies and process for u.s medical schools. Academic Medicine. Malterud K Systematic text condensation: a strategy for qualitative analysis Scandinavian Journal of Public Health 2012 40 8 795 805 10.1177/1403494812465030 23221918 Malterud K Siersma VD Guassora AD Sample size in qualitative interview studies: guided by information power Qualitative Health Research 2016 26 13 1753 1760 10.1177/1049732315617444 26613970 Mayblin M Course M The other side of sacrifice: introduction Ethnos 2014 79 3 307 319 10.1080/00141844.2013.841720 McCullough LB Coverdale J Chervenak FA Teaching professional formation in response to the COVID-19 pandemic Academic Medicine. 2020 95 1488 1491 10.1097/ACM.0000000000003434 33006868 Ministério da Saúde. (2021). Boletim_Epidemiológico_Brasil. Retrieved 12 Dec, 2021, from https://covid.saude.gov.br/. Monrouxe LV Solicited audio diaries in longitudinal narrative research: a view from inside Qualitative Research 2009 9 1 81 103 10.1177/1468794108098032 Monrouxe LV Identity, identification and medical education: why should we care? Medical Education 2010 44 1 40 49 10.1111/j.1365-2923.2009.03440.x 20078755 Morse JM Data were saturated Qualitative Health Research 2015 25 5 587 588 10.1177/1049732315576699 25829508 Nakatsu L The COVID clerkship Academic Medicine 2021 96 8 1136 10.1097/acm.0000000000004172 34010862 Royal Collage Of Physicians. (2020). Ethical dimensions of COVID-19 for frontline staff. Rcp Setting Higher Standards, April, 1–8. Picton A Work-life balance in medical students: self-care in a culture of self-sacrifice BMC Medical Education 2021 21 1 1 12 10.1186/s12909-020-02434-5 33388043 Pollock A Campbell P Cheyne J Cowie J Davis B McCallum J McGill K Elders A Hagen S McClurg D Torrens C Maxwell M Interventions to support the resilience and mental health of frontline health and social care professionals during and aſter a disease outbreak, epidemic or pandemic: a mixed methods systematic review (Review) Cochrane Database of Systematic Reviews 2020 11 1 162 10.1002/14651858.CD013779 Post SG Botkin JR Headrick LA Medical students in a time of HIV: education and the duty to treat Medical Education 1995 29 2 128 132 10.1111/j.1365-2923.1995.tb02815.x 7623699 Rasmussen S Sperling P Poulsen M Emmersen J Andersen S Medical students for health-care staff shortages during the COVID-19 pandemic The Lancet 2020 395 e79 e80 10.1016/S0140-6736(20)30923-5 Ritchie K professionalism, altruism, and overwork The Journal of Medicine and Philosophy 1988 13 447 455 10.1093/jmp/13.4.447 3246582 Rose S Medical student education in the time of COVID-19 JAMA 2020 323 21 2131 2132 10.1001/jama.2020.5227 32232420 Rosenbaum L Once upon a time… the hero sheltered in place New England Journal of Medicine 2020 383 2 e5 10.1056/nejmp2015556 32374957 Sarkar U Cassel C Humanism before heroism in medicine JAMA 2021 10.1001/jama.2021.9569 Secretaria Municipal de Saúde. (2020). Boletim_epidemiológico_COVID-19_campinas. Retrieved 05 April, 2022, from https://covid-19.campinas.sp.gov.br/boletim-epidemiologico. Shanafelt T Ripp J Trockel M Understanding and addressing sources of anxiety among health care professionals during the COVID-19 pandemic JAMA 2020 323 21 2133 2134 10.1001/jama.2020.5893 32259193 Silveira GL Campos LKS Schweller M Turato ER Helmich E de Carvalho-Filho MA Speed up! the influences of the hidden curriculum on the professional identity development of medical students Health Professions Education 2019 5 3 198 209 10.1016/j.hpe.2018.07.003 Simons J Vaughan J Sacrifice and risk in the time of COVID-19 Future Healthcare Journal 2020 7 2 158 160 10.7861/fhj.2020-0035 32550647 Soled D Goel S Barry D Erfani P Joseph N Kochis M Uppal N Velasquez D Vora K Scott KW Medical student mobilization during a crisis: lessons from a COVID-19 medical student response team Academic Medicine 2020 95 9 1384 1387 10.1097/ACM.0000000000003401 32282373 Tai J Ajjawi R Undertaking and reporting qualitative research Clinical Teacher 2016 13 3 175 182 10.1111/tct.12552 27146221 Tempski P Arantes-Costa FM Kobayasi R Siqueira MAM Torsani MB Amaro BQRC Nascimento MEFM Siqueira SL Santos IS Martins MA Medical students’ perceptions and motivations during the COVID-19 pandemic PLoS ONE 2021 16 3 1 15 10.1371/journal.pone.0248627 van Nistelrooy I Self-sacrifice and self-affirmation within care-giving Medicine, Health Care and Philosophy 2014 17 4 519 528 10.1007/s11019-013-9523-z 25273334 Varpio L Ajjawi R Monrouxe LV O’Brien BC Rees CE Shedding the cobra effect: Problematising thematic emergence, triangulation, saturation and member checking Medical Education 2017 51 1 40 50 10.1111/medu.13124 27981658 Vries-Erich DJM Dornan T Boerboom TB Jaarsma ADC Helmich E Dealing with emotions: medical undergraduates’ preferences in sharing their experiences Medical Education 2016 50 8 817 828 10.1111/medu.13004 27402042 Wald HS Professional identity (Trans)formation in medical education: reflection, relationship, resilience Academic Medicine 2015 90 6 701 706 10.1097/ACM.0000000000000731 25881651 Wang C Wang Z Wang G Lau JY-N Zhang K Li W COVID-19 in early 2021_ current status and looking forward Signal Transduction and Targeted Therapy 2021 6 1 14 33384407 Watling C Lingard L Grounded theory in medical education research: amee guide 70 Medical Teacher 2012 34 10 850 861 10.3109/0142159X.2012.704439 22913519 Watling C Wright S Cristancho S Varpio L Necessary groundwork : planning a strong grounded theory study Journal of Graduate Medical Education 2017 9 1 129 130 10.4300/JGME-D-16-00693.1 28261409 Wicks L Noor S Rajaratnam V Altruism and medicine BMJ 2011 343 d4537 10.1136/bmj.d4537
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==== Front Stud East Eur Thought Studies in East European Thought 0925-9392 1573-0948 Springer Netherlands Dordrecht 9528 10.1007/s11212-022-09528-4 Article Ota Weinberger’s conception of democracy: reconstructing an unexplored political theory http://orcid.org/0000-0002-1263-935X Sekerák Marián [email protected] Department of Security and Law, AMBIS College, Lindnerova 575/1, 180 00 Prague 8 – Libeň, Czech Republic 12 12 2022 117 15 11 2022 © The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Ota Weinberger was a Czech-Austrian jurist, whose core academic work on issues of democracy was mostly published in the 1990s. In his writings, he focused primarily on legal philosophy from a positivist perspective. However, there are also significant overlaps with the field of political theory as Weinberger examined the conditions for the functioning of contemporary democracies. In this paper, some of the main features of his conception of the so-called “structured democracy” are clarified. The conception opposed several other democratic theories, especially the elitist (Schumpeterian), the majoritarian, but also the discursive one, as represented by Jürgen Habermas, with whom Weinberger fundamentally disagreed. The paper focuses on several key elements of his theory, such as the leading ideas, the role of institutions, open society, and his critique of marketing methods in politics. Keywords Ota Weinberger Jürgen Habermas Deliberative democracy Institutions Positivism AMBIS Vysoká školaInternal Grant Agency ==== Body pmcIntroduction Ota Weinberger was one of the most illustrious successors of the so-called Brno (Normative) School of Jurisprudence/Legal Theory (Procházka 1964; Vojáček 2008; Kindl 2014; Večeřa 2015; Bröstl 2016; Maršálek 2017). He himself emphasized that this school of thought is “fundamentally open and wants to serve free scientific dynamics” as opposed to the Vienna School, represented by the Hans Kelsen Institute, which “has a strong tendency to advocate for Kelsen’s teachings” (Weinberger 2003b, p. 9). He labeled his theory “institutionalist legal positivism,” or briefly “neoinstitutionalism” (Weinberger 1999c, 1999d, 2000b), which should not be confused with the neo-institutionalist approach in political science (see Peters 1999). Weinberger, the Czech émigré and a “representative of logical optimism” (Večeřa 2019, p. 36), was a renowned legal philosopher, logician, and jurist, whose studies significantly overlapped with political theory. He analyzed the issue of both political and legal argumentation (Weinberger 1992, 1994a, 1995c) as well as the role of norms and rules in society (Weinberger 1988, 1995b). From a legal-philosophical perspective, he also analyzed the issue of justice, believing that it is possible both “to argue rationally about problems of justice” and “to show that something is unjust” (MacCormick and Weinberger 1986, pp. 207 and 208; see also Weinberger 1993b). He developed his scholarship under the intellectual influence of logical (L. Wittgenstein) and legal (H. Kelsen) positivism. His reflections on law were based on ideas about the nature of law and its function in society, namely the belief that law is primarily a sociological phenomenon, one reflected in various social institutions that bring it to life. He sought to provide a comprehensive view of the consequences of law in human society, because it was only this view that he assumed to be beneficial for understanding the nature of the effect of legal regulation on human behavior (cf. Gerloch and Tryzna 2009, p. 62). His view of the functioning of law in society seems to be crucial. On the one hand, it cannot be reduced to a mere social reality devoid of the normative effect of law, i.e., a completely pragmatic approach to law. On the other hand, the social dimension of law cannot be ignored, and one cannot focus exclusively on its normative side, i.e., strict legal formalism. It should be noted that Weinberger’s positivist legal thought has already received considerable academic attention, not only within Czech jurisprudence (Fischer 2009; Smolak 2009; Večeřa 2009, 2020; Trávníček 2020), but also abroad (Herget 1996, chap. 7). However, his work on political theory remains neglected. Weinberger published his books, chapters in edited volumes, and articles in several languages (especially Czech, German, and English), thus his opus is partly available to international audience. Let us mention the English translation of one of his German-written books, which is interdisciplinary in nature and includes law, philosophy, sociology, and political science (see Weinberger 1991). Here, among other things, Weinberger “unfolds his vision on democracy and justice, a vision that is mainly aimed at drawing the formal critical frameworks of a pluralistic politics” (van Roermund 1992, p. 577). It seems, however, to have not been given due attention abroad, especially when it comes to Weinberger’s political theory. Therefore, this paper’s aim is to present and thoroughly analyze his perception of democracy in which he responded primarily to Habermas’s discursive approach, and in which his legal positivist thinking can be traced (see esp. Weinberger 1994c). In what follows, the key elements of Weinberger’s model of democracy will be comprehensively described. Since the jurist is not very well known outside of Central Europe, it will be useful to present his short biography in the first part. Subsequently, the paper’s methodological background will be briefly sketched. The third part offers a critical reconstruction of his quasi-original model of “structured democracy,” while highlighting what is (or could be) valuable and inspiring from the current perspective. In the following part, attention will be paid to several types of criticism that Weinberger formulated with regard to not only the then-existing models of democracy, but also political practice, especially that of media manipulation. Special emphasis will be put on his critical view of Habermas and his discursive approach to democracy “based not on voting, mechanisms of fair aggregation, or rhetorical persuasion, but on the quality of debate in the public sphere” (Verovšek 2022, p. 409). The last section will elucidate the role of institutions, as his political theory is inseparable from the (neo)institutionalist approach of his legal philosophy. A short biography Ota Weinberger (1919–2009) was born in Brno, in the newly independent Czechoslovak Republic. He grew up in an assimilated Jewish family and was raised to believe in tolerance and democracy. As he himself stated, “no ethnic or religious prejudices were instilled in him” during his upbringing (Weinberger 2000b, p. 276). After graduating from secondary school (1937), he studied law and philosophy at the local university. In 1946, he started practicing law. In the years 1953–1956, i.e., under the communist totalitarian regime, he was forced to work as a locksmith for political reasons. In the years 1956–1968, he taught logic at Charles University in Prague, where he defended his dissertation in 1961. Three years later, he habilitated as a docent (associate professor) in logic. Weinberger criticized Stalinist party dictatorship and advocated for liberal and democratic reforms. After the Warsaw Pact’s invasion of Czechoslovakia in August 1968, he participated in the World Congress of Philosophers in Vienna. Due to his recent activities in the Club of Committed Non-Party Members (see Kusin 1972), he decided not to return to Czechoslovakia and took up a visiting lecturer’s position in Vienna (1968–1969; cf. Koller 2009, p. 1). From 1969, he obtained the same position at the University of Graz, where he was awarded full professorship in legal philosophy in 1972. He became emeritus in 1989 but taught until 1991. He was awarded the Humboldt Prize, several regional awards, and honorary doctorates at the Paris Lodron University Salzburg (1993) and at Masaryk University (2004). Methodological background As mentioned earlier, Weinberger’s legal and political theory was firmly rooted in institutionalism and legal positivism, which was largely reflected in the application of logical methods in his study of legal norms. However, there are two reasons why this approach is barely helpful in analyzing his conception of democracy. First, it would mean to reproduce and replicate his own methodological procedures. Second, a different methodological framework is required to reveal his either hidden or overt motivations, as well as to attempt a critical reconstruction of his concept of democracy. Such a framework should not only better reflect current practices in social sciences, but also put a particular concept into a broader perspective and compare it with other models, against which it has been or still is challenging. It could be believed that both critical social theory and comparative political theory offer the desired framework. Both provide a useful toolkit for a critical analysis of Weinberger’s patchy conception of democracy. When it comes to critical social theory, its role “is to unmask […] tacit presumptions, showing how they have a determining impact on the most abstract modes of theorizing and, perhaps most importantly, how, in failing adequately to scrutinize its socio-historical elements, philosophy risks becoming ideology” (McNay 2008, p. 86). This approach presupposes using standard methodological tools, such as conceptual analysis, content analysis, and interpretation of texts. In this text, the last of these tools will primarily be used. This will be appropriately complemented with comparative political theory, which has been designed to examine the justification of (universal) epistemic claims of particular theories and explore their critical-transformative possibilities, while claiming that they “cannot be formed on the basis of partial or arbitrarily exclusive perspectives” (March 2009, p. 562; see also Freeden and Vincent 2013; Kapust and Kinsella 2017, pp. 1–18). The “structured democracy” As mentioned above, Weinberger’s model of democracy, which he called “structured democracy,” is based on his (neo)institutional legal theory and can be reconstructed from a variety of fragments scattered throughout his writings. Probably the most coherent and accessible source is his book published in Czech in 1993 under the title Philosophy, Law, Morality: Problems of Practical Philosophy and in two Slovak editions (1995 and 2010) entitled Institutionalism: A New Theory of Procedure, Law and Democracy. Of the two titles, the latter seems to better describe legal and political theory. It is necessary to clarify first how Weinberger perceived democracy, and then what characteristics and qualities he ascribed to it. He assumed that “[d]emocracy is not just a formal system of organization and formation of the social will,” (Weinberger 1996c, p. 522), but also based on an open system of substantive principles, such as tolerance, freedom of thought and religion, plurality of agents of political opinion and the existence of platforms for a free exchange of views. Human rights and civil liberties, which today are considered to be immanent components of a democratic worldview, should not be seen as a priori givens, but as components of a democratic worldview that are evolving and are subject to discussions. (ibid.) In these words, one can observe not only the echo of political liberal theories of the second half of the twentieth century, especially the one represented by John Rawls (for a comprehensive overview of various liberalistic approaches, see Nussbaum 2011), but also a rather progressive approach to the definition of human rights, to which Weinberger attributes a dynamic character. These “substantive principles” are the basis and main starting point (or rather normative assumption) of his theory of democracy. He pointed out elsewhere that these “principles of democracy can be understood as a kind of leading idea of democratic institutions” (Weinberger 2010, p. 293; italics added). These are not, however, strict rules of conduct, but goals and regulatory ideas that are developed through concrete analyses. They are authoritative for evaluating organizations and for assessing the functioning of institutions. Adequate consideration of material principles is only guaranteed if democracy is understood as consultation, discussion and criticism, rather than just as a fight for majority. (ibid.) Notably, the discussion element is a part of Weinberger’s democratic theory, but not of the kind presented by Habermas, with whom he fundamentally disagreed, as will be shown later. Such a discussion can be understood as free democratic critique of public life, which Weinberger assumed to be a key tool to prevent the erosion of democratic principles. Other such tools included the establishment of democratic customs and beliefs, as well as the democratic system’s self-control mechanisms (cf. Weinberger 2010, pp. 254–255). Regarding democratic principles as leading ideas of democratic institutions (his conceptualization of them will be illuminated in the last part of this paper), it would be a mistake to assume that Weinberger preferred a static value concept similar to, let us say, religious dogmatism. On the contrary, it is a dynamic approach to societal values that a pluralist democratic state should reflect: “The ideals of democracy represent an open category of values and requirements that are subject to change in the historical process and in the context of technological, economic and spiritual development” (Ibid., p. 291). These “leading ideas of democracy” consist of “postulates like protection of minorities, tolerance, opportunity for free social discourses, chances for the free realization of a specific way of life, ideas of solidarity and the protection of the weak, etc. […] are always under discussion and imply a certain restriction for popular will-formation” (Weinberger 1999b, pp. 351–352). Although Weinberger did not use the term, he came quite close to a liberal democratic conception of democracy. The mentioned “open category of values” and the possibility of contesting or supplementing existing catalogues of human rights and/or lifestyles are meaningful and applicable for contemporary political theory, especially when confronting the so-called conservative backlash in politics (Alter and Zürn 2020). Although it might seem from the aforementioned remarks that Weinberger defined democracy more or less negatively (as a reaction to several approaches, in particular the procedural, the discursive and the Marxist one—howsoever he understood them), a positive element can be found, namely the appeal both to a certain “normative core” or “leading ideas” and to Popper’s concept of open society, which Weinberger appreciated. He considered the idea of an open society to be “a very important partial characteristic of a democratic society,” which “concerns primarily ideological and cultural liberty in a democratic state, but which also makes a significant impact on other aspects of democratic life. […] An open society stands or falls on conducting the battle of opinion as rationally as possible, not through coercion or mere propaganda” (Weinberger 1994b, p. 445). Such a society “is directed toward critical scrutiny realized by democratic elites” (Weinberger 1994c, p. 248). In the context of his critical remarks on contemporary democratic theories and political practice, it is barely surprising which terms Weinberger chooses to defend this concept. According to him, “the democratic idea of an open society trusts in the power of free discourse and in the fight against chauvinism and fundamentalism. But these systems of nationalist or religious fanaticism are not willing to participate in rational discourse; they seek to isolate their group and build upon their emotions and irrational faith” (Weinberger 1996d, p. 76). This appears to be a surprisingly far-sighted anticipation of the problems Western democracies have begun to face in recent years. Above all, it relates to the influence and power of social networks to create and strengthen “echo chambers” (Barberá 2020; Rhodes 2021). Here, citizens come together not only on the basis of shared nationalistic or religious ideas (as Weinberger warned), but rather thematically (COVID-19, vaccination, the Russian invasion of Ukraine, etc.) to form a kind of counterculture challenging the current democratic civil discourse. In addition, the emotions and irrational faith that he also warned against have been reflected in the spread of misinformation and fake news, which ultimately undermine the very foundations of democratic open society. It should be noted here that Weinberger’s political and legal theory is strictly secular and does not rely on any metaphysical conception. In any case, he finds it crucial for a democratic state to create adequate conditions for the existence of an open society. These conditions are explicitly listed by him: “plurality of political opinion makers, an open debate not only between political forces, but also between different layers of intelligentsia and between different interest groups” (Ibid., p. 77). It is quite obvious, then, that pluralism in a democratic society is something Weinberger believes is yet to be achieved. He looks for viable institutional ways to get to that point, which contrasts with Rawls’ view of (reasonable) pluralism as something given, as “a permanent feature of modern societies with ‘free institutions’ ” (Hedrick 2010, p. 21; see also Talisse 2003). To reach such a pluralism, as Weinberger points out, it is crucial to ensure sufficient information in the democratic decision-making process: “Modern democracy is possible only on the basis of a cultivated and informed people, and it is characterized by the existence and the leading role of political parties” (Weinberger 1996b, p. 253). He was well aware that “democratic political activity means activity within political parties” (Weinberger 2000b, p. 274). Parties play an important role in Weinberger’s democratic model, which corresponds to the considerable importance attached to political elites, as will be explained later. Based on the current widespread perspective, this enthusiastic approach to political parties can be assessed rather critically, especially in view of the long-discussed crisis of both representative democracy (Tormey 2014; Landemore 2020, chap. 2; Hagevi et al. 2022) and (traditional) political parties, as accompanied by the emergence of new types of parties (Ignazi 1996; Bader 2014; Deschouwer 2017). According to Weinberger, the role of parties is, among other things, to engage in a “multi-layered” democratic discourse with interest groups, individual politicians, bureaucracy, the media, the sciences, various “clubs,” and “institutions of popular education” (Weinberger 2010, pp. 293–294). Obviously, Weinberger did not write anything about an intra-party deliberative democracy, which has become a prolific research topic in recent years (Invernizzi-Accetti and Wolkenstein 2017; Gherghina and Jacquet 2022). Instead, he offered the idea of broad society-wide deliberation, yet without any clearer description of its structure. Various societal actors were supposed to engage not only in democratic discourse, but also in democratic control built as “a network system in which science and the mass media and, at least potentially, every individual can participate in addition to political factors and organizations” (Weinberger 2010, p. 300). However, Weinberger did not provide a precise distinction between democratic discourse and this bottom-up “network-style democratic control.” Nor did he offer a more detailed and nuanced specification of agents and their specific tasks. For this reason, his “structured democracy” remains largely a sketch of several freely emerging procedures and rules, obviously set within a liberal, democratic-like framework. Weinberger’s multiple types of critique Based on current predominat perspective, Weinberger cannot be viewed either as a discursive or a radical democrat. Rather, he developed his own “theory of structured democracy” in opposition to the abovementioned Habermas’s theory. He also opposed (1) Schumpeter’s procedural democracy, (2) Downs’s economic theory of democracy, (3) Marxist economism with all its implications for democracy, as well as what he called (4) “a romantic perception of democracy.” In doing so, he differs from Habermas, whom he criticized and who, for the purposes of his own theory, distinguishes just three democratic models: liberal, republican, and his preferred procedural one, which he calls deliberative (cf. Habermas 1998, chap. 9). Based on today’s perspective, the romantic type of democracy could be characterized as a populist effort to proliferate direct democracy, according to which “the people are always right” (Weinberger 2010, p. 278). This perception, as Weinberger (2010, p. 279) pointed out, “opens the door to manipulation” of the crowd. According to him, “it is not necessary for the [self-]ruling people to be directly involved in decisions at every stage of decision making” (Ibid., p. 287). Obviously, he was somewhat critical of the various, more or less dominant and prevailing theories of democracy. He wrote literally about his “dissatisfaction,” because he believed they “are marked by romantic ideas […], on the one hand, and they absolutize partial aspects […], on the other hand” (Weinberger 2000b, p. 283). Critique of the majoritarian approach Furthermore, Weinberger also rejected a mere majoritarian approach to democracy, which does not take reasonable pluralism in society and a “normative core” (Weinberger 2010, p. 289) of democracy into account. He emphasized that the [a]ctual majority or qualified consensus is useful for practical democratic decisions. But I wonder whether it can really serve as a definite answer to the problem under consideration. It is no tool for deciding between objective truth and falsehood, or to found moral or legal rules objectively, once and for all. In my opinion, democratic consensus is relevant only as a continuous process of endeavour to improve our knowledge and our moral and political opinion. (Weinberger 1996a, p. 177) Apparently, Weinberger did not oppose consensual democratic decision-making entirely, but refused to universalize it and elevate it to a method that could elicit the “truth,” or a true result. This reservation stemmed from his (mis)understanding of the discursive theory of democracy. He strictly distinguished “majority opinion” or “universally accepted opinion” from “objective truth or objective validity” (Weinberger 1994c, p. 244). It might seem that by rejecting the procedural approach, as emphasized above, Weinberger must have rejected elitism as well. However, his attitude to the role of political elites in a democratic society is not unequivocally negative. Elitism, like an imaginary other side of the same coin and a kind of counterpart to majority decision-making, is acceptable under certain conditions: “Elites are the creators and bearers of leading ideas, not the passive mouthpieces of the masses” (Weinberger 2010, p. 288). Thus, while he did not reject political elites and recognized their importance, he warned that the elites “often make decisions based on ‘feeling’ or in order to satisfy some pressure groups” (Ibid., p. 301). He argued that political elites must not imitate the opinion of the majority. On the contrary, they are supposed to become the bearers of the “leading ideas” that will shape the democratic political system. Critique of “media propaganda” It is widely assumed that current liberal democracies are faced with various challenges, especially when it comes to populism, the technocratic approach to governance, as well as the role of the media, manipulation, and the growing role of political marketing and professionalized election campaigns. Weinberger paid attention to all these facts, especially in his writings from the 1990s, in which he concluded that [m]any political scientists believe that democracy is always at risk, so that there is a need for a constant struggle for the ideals of democracy. I share this view. I believe that what primarily matters in today’s situation is to fight for an open society and against misleading marketing-type advertising in politics. The widespread feelings of political frustration that we can see in today’s society have their roots, among other things, in feelings of opposition to the rampant political advertising that feeds half-truths to voters. (Weinberger 1994b, p. 449) In his political theory, Weinberger called for a democratic discourse that could be resistant (or at least sufficiently robust) to marketing methods in politics, although he preferred the word “propaganda.” As is evident from the quotations below, he used these terms complementarily or interchangeably. Discourses in society are essential for democratic systems, but they themselves do not guarantee the optimal result. Emotional propaganda leads to people’s indoctrination and interferes with the normal way of democratic discourse. A significant number of citizens respond to trivial and emotionally impressive narratives. This substantially limits the rational nature of discourse and establishes political domination. Thus, he feared that “democratic processes can be destroyed by propaganda, ideological indoctrination or manipulation” (Weinberger 2010, p. 253). This concern of his has turned out to be justified, since contemporary liberal democracies are facing fundamental problems related to the phenomenon of fake news and mass manipulation (Farkas and Schou 2020; Giusti and Piras 2021). This goes far beyond political marketing, as was imaginable in Weinberger’s time, and includes the technical and ethical dimensions. Weinberger used quite sharp words to point out the rapid development of political marketing and its perceived specific position, apparently based on his observations of developments in Western Europe at the time: In the practice of political propaganda in democratic states, there is a strong tendency today to apply similar methods as in commercial advertising. The marketing methods of purely emotional propaganda penetrate into political life, where factual argumentation […] recedes into the background. […] If we start from the idea that the democratic formation of the will of society comes from the people, marketing indoctrination will appear to us as a danger to the functioning of democratic processes. The people becomes an object of manipulation. (Weinberger 1996d, p. 76) Weinberger seemed to have a sort of physical sensation of the then-growing industry of political marketing and spin doctoring, which he deemed as one of the greatest threats to democracy. He assumed that marketing methods raised serious doubts that it is the people who really decide on political matters in contemporary democratic systems (cf. Weinberger 2000b, p. 282). From a psychological point of view, it is known that any marketing methods (not just political ones) act primarily on the human subconscious and shape people’s emotions, often for a specific purpose. As Weinberger was also aware of this, he strongly warned against media manipulation, which could also have political consequences. According to him, “[t]he mass media has become a major dominant factor and marketing methods, i.e. emotional advertising, have found their way into politics. The alienation between citizens and politics has further advanced, posing an unpredictable danger to modern democracy” (Weinberger 1999a, p. 427). Although Weinberger certainly cannot be considered a proponent of critical theory (nor do his writings refer to such a source of inspiration), it seems that some aspects of his thinking on the democratic politics of Western capitalist societies were not far from the critical remarks introduced by representatives of the Frankfurt School a few decades earlier (see Petryszak 1977). This is not the only similarity with this school that can be traced in Weinberger’s writings. Also worth mentioning is his critique of the growing influence of capital (economic power) on the political structures of democratic countries, a fact he considered to be significant to his “concept of democracy based on leading ideas” (Weinberger 2000b, p. 283). Critique of Habermas’s discursive approach A quick glance at Weinberger’s writings on issues of political theory suggests that he paid close attention to Habermas’s discursive (or, as Weinberger sometimes wrote, argumentative) theory of democracy. He can be considered one of the biggest and first polemicists with Habermas and his democratic theory (together with another famous native of Brno, Ernst Tugendhat; see Tugendhat 1985). He stands somewhere far ahead in the imaginary long sequence of political theorists that have analyzed Habermas’s deliberative democracy to date (e.g., Avio 2000; White and Farr 2012; Ingram 2014; De Angelis 2021; Kędziora 2021). As Weinberger was a bit repetitive in many of his texts, several points will suffice to summarize his criticism. First and foremost, it should be noted that Weinberger considered discursive practices (together with the idea of an open society) “inseparable elements of democracy” (Weinberger 2000b, p. 283). However, as he further argued, “even free discourses do not guarantee that optimal decisions will be made (as assumed by Habermas’s philosophy of discourse)” (ibid.). As is well known, Habermas’s philosophical method—briefly put—“is a Kantian-style transcendental deduction of the presupposed communicative ideals of uncoerced dialogue in which the equal participants are committed to truth, sincerity, and normative rightness” (Campbell 1998, p. 88; see also Finlayson 2019, pp. 90–95). Unsurprisingly, then, such a method was found unsatisfactory by Weinberger. He suggested that it is “in some way a result of a Marxist tendency to glorify collective endeavour in opposition to individual activity” (Weinberger 1996a, p. 172). Weinberger also disagreed that “discourses as such are a measure and […] a sufficient legitimation and justification of any result of social discursive processes” (Weinberger 1994c, p. 247). However, he did not offer any concept of justification or legitimation, especially when it comes to their relationship to democracy, its institutions, and the political decisions that are taken at various levels. Moreover, when analyzing the relationship to deliberative (or discursive) democracy, he overlooked at least two things. First, as Gutmann (2006, p. 181) pointed out, one of the advantages of this democratic model is that it recognizes the provisional nature of justification in politics. Since Weinberger’s thought was rooted in positivism, he assumed that justification was static and unambiguous throughout a political process. Second, in general justification, as Forst (2001, p. 365) remarked, “one may even accept a decision as justifiable without thinking that the best decision has been reached—provided that moral reasons have not been overlooked or trumped by other considerations and that procedures have been fair.” But Weinberger assumed that the deliberative process must always produce a true and valid (and therefore the best possible) outcome. Weinberger claimed that the correctness of a thesis does not depend on whether it could be the result of a discourse, but only on whether or not good reasons can be adduced in its favor. He further assumed that a mere consensus can hardly be a criterion of truth since such a consensus might quickly prevail in situations of mass psychosis (cf. Weinberger 1983, pp. 188–189 and 192). In light of this, at least one critical point can be mentioned here, that is, as rightly pointed out by Alexy (2021, chap. 17), the situation of mass psychosis is the exact opposite of rational discourse. Discursive theory presupposes discourse actors’ (1) adherence to the rules of rational argumentation and (2) ability to distinguish between good and bad reasons. For Weinberger, a discursive process could have some “detrimental methodological implications” (Weinberger 1996a, p. 173). Even the very basic criteria of ideal discourses were viewed by him as “an unrealistic ideal” (Weinberger 1999b, p. 339) that can hardly “provide for an optimal treatment of the problems under consideration” (ibid.). Above all, he focused on the conditions of eliminating power and other hierarchies within the deliberative group, which is presupposed by deliberative democracy. Such a “powerless situation,” he wrote, is an “absolute illusion—so that even approximation to this ideal is not realizable” (Weinberger 1996a, p. 175; see also Weinberger 1992, p. 259). Thus, although he did not question the need, or even the necessity, of discourse in democracy, by challenging the very assumptions of Habermas’s theory he ultimately questioned the whole model, its plausibility in political theory, and probably even its relevance to political practice. Some inaccurate interpretations of Habermas’s theory can also be found scattered in various parts of Weinberger’s critique, such as the necessity to defend one’s own claims within the deliberative process. Here, he used an interesting, albeit unsuitable, example: “Another Habermas’s view is also incorrect, namely that anyone who has articulated a claim also assumes the obligation to defend it in a discourse. There are claims that cannot be proved intersubjectively (e.g. ‘I love you’). […] If I was really allowed to articulate only such claims that I am able to reliably prove in a discourse, I would become a very reticent person” (Weinberger 1994b, p. 444). This appears to be a misreading of Habermas, as one cannot attribute to him the argument that any subjective claim of any participant in the deliberative process must be defended in this way. Surely, there are claims that have to do with the subject of deliberation and are of utmost relevance. Those are expected to have been rationally defended by the interlocutor’s arguments. And in a standard deliberative democracy, “participants in the deliberative process are required not only to offer arguments, but to offer arguments persuasive to all” (Festenstein 2004, p. 295). However, there is a difference between rational argumentation and reason-giving in the context of deliberation, on the one hand, and proving as a form of positivist logic, on the other hand, which is the approach Weinberger preferred (see Kosinka 2019, for Weinberger’s position in the debate on the relationship between iuspositivism and iusnaturalism). The example of subjective emotion appears to be inappropriate. Undoubtedly, emotions and passions, such as love, play an important role in deliberation (see Hall 2007; Neblo 2020), but they are not the very subject of deliberation. The “reticence” that Weinberger fears is therefore not a threat in the discursive process. And when it does occur, it is not for reasons he attributes to Habermas’s democratic model. Weinberger’s positivist, essentially Popperian approach, is mirrored in his critique of the process of reaching consensus through deliberation, which does not search for truth in its “traditional concept” (Weinberger 1992, p. 261). Indeed, a deliberative body will not get the truth or the “rightness” (Ibid., p. 265) by reaching an agreement within a democratic discourse, but exclusively by verifying or falsifying hypotheses. However, Habermas’s understanding of these categories, as is well known, is a bit different. Whilst rightness for Habermas “means rational acceptability supported by good reasons” (Habermas 1996, p. 226), “the unconditionality of truth is expressed only in the idealizing presuppositions of our argumentative practice of justification, and hence at the level of language use” (Ibid., p. 35). It is hardly surprising that such an approach presupposed the idea of practical reason as “a tool for transforming thoughts relative to action” (Weinberger 1992, p. 266). For Weinberger, discursive theory failed to provide any acceptable conception of such practical reason (cf. Weinberger 1992, p. 264). It can be remarked, however, that the critique of what a theory of interest is or is not able to achieve always depends on the specific reference criteria against which it is measured. This is even more the case in Weinberger’s approach. Therefore, Weinberger’s nonacceptance of deliberative theory’s ability to satisfy the framework of practical reason, as defined by himself, is ineffective, as Habermas explicitly announced at the beginning of his fundamental work that his (discursive) theory of communicative action replaces practical reason with a communicative one (cf. Habermas 1996, p. 3). In spite of these misunderstandings of Habermas, Weinberger could (if he were alive) certainly find some common points of view with (later) Habermas. Let us recall Weinberger’s critique of fundamentalism and fanaticism producing isolated groups built upon shared emotions and irrational faith. It has already been mentioned that these tendencies are accelerated in online “echo chambers” of like-minded groups of people connected via social networks. And it was Habermas who warned against the harmful effects of these phenomena when pointing out that “the rise of millions of fragmented chat rooms across the world tend […] to lead to the fragmentation of large but politically focused mass audiences into a huge number of isolated issue publics” (Habermas 2006, p. 423, note no. 3). In any case, neither of the two thinkers was able to imagine the kind of impact this civic fragmentation and isolation could have on the very democratic foundations of society when “those seeking to manipulate the online public sphere can capitalise on declining levels of trust in institutions and experts” (Morgan 2018, p. 39). Institutions and their role in society Weinberger’s political theory cannot be properly understood without basic knowledge of his legal philosophy, especially his concept of institutions (see Weinberger 2000a). For him, institutions form a broader framework of human action. All forms of action and human interaction depend on them. However, they cannot be defined behaviorally, as they are “based on a nucleus of practical information” (Weinberger 1993a, p. 172) and manifest themselves in an observable way in reality. The human being is the originator of these institutions, but her/his behavior is also determined by them. They are characterized by a “leading idea” and by both stability and dynamics in the course of historical development. If the institution runs counter to its leading idea, it may be regarded as dysfunctional. A basic characteristic of Weinberger’s “structured democracy” is leading idea, which he perceives as a system of notions characterizing the tasks and purposes of the institution (cf. Weinberger 2010, p. 290). Weinberger’s institutionalism examines institutions primarily in terms of theory of action. It emphasizes that institutions create not only legal relationships, legal obligations, claims, and possibilities of action, but also other psychological and social consequences in a field of interest. Institutions open up spaces for action, raise expectations of the behavior of others, and have consequences outside relations between members of a society (cf. Weinberger 1995a, p. 101). The validity of each legal system is determined by the fact that the relevant system of legal norms actually determines the social organization and functioning of institutions. Thus, to recognize law means to understand the meaning of legal norms and their institutionalized functions. According to Weinberger, institutions are made up of three parts. Firstly, the core of practical information that determines how “we should behave within an institution and how we should evaluate behaviour from the perspective of the institution” (Weinberger 2003a, p. 406). Such an ideal core is composed of norms, purposes, values, and preferences (cf. Weinberger 1997, p. 197). Institutions are not just some standardized and regular types of human behavior; they always have “a certain normative core, which should be understood as practical information” (Weinberger 2010, p. 289). Secondly, institutions rely on the substrate of their personnel, i.e., qualities and capacities of the people (individuals and collectives) involved in the life of institutions as their “bearers, actors and bodies” (Weinberger 1997, p. 198). Thirdly, they also rely on a substantive substrate, namely “objects and products which are created and used for their institutionally determined functions” (ibid.). Regarding classification of institutions, Weinberger distinguishes between normative and real institutions. Normative institutions, which are generally referred to as legal institutions, are an established system of practical information and its connection with social processes and institutional realities. These are, for example, property, marriage or manifold contracts; they are the building blocks of the whole legal system. As for real institutions, practical information forms the very centre of them. At the same time, Weinberger emphasized that when institutions are referred to as a generic term, there is no need to present any exhaustive or rigorous categorization of institutions (cf. Weinberger 1995a, pp. 35–37; see also Kováčová and Surmajová 2009). Conclusion When it comes to his political theory, Ota Weinberger cannot be viewed as a deliberative or even radical democrat. His concept of democracy goes well beyond these approaches, which can be found in the history of democratic thought after the 1980s. However, certain elements thereof overlap with some major approaches. For example, the critique of “media manipulation” and marketing methods in politics is shared with critical theory, or the emphasis on respect for human rights (including minority protection) and civil liberties (including fair elections) is shared with political liberalism. In any case, Weinberger did not provide a coherent model for later strategic and systematic development by himself or by any successor. And although it remains relatively isolated—as a by-product of his legal philosophy—it contains several notable components, which could inspire contemporary political theory. First, Weinberger emphasized not only the irreplaceable role of political parties in representative democracy, but also the importance of political elites, which in his conception should somehow determine political direction, but should not be subjected (in today’s vocabulary) to populist deception. Second, in a democratic society, institutions are based not only on norms, but also on human action. The discursive involvement of various social actors (including political parties or the media) could therefore become an impetus and a challenge for today’s democracies (although it is legitimate to debate the scope, nature, and role of these actors in the discursive process). Third, an open society ensuring pluralism of opinion and well-informed citizenry is a crucial precondition for any kind of democratic government. This has become even more acute in recent years; intolerance and public polarization based on disinformation and fake news have been spreading even in the democracies of the global West. Fourth and last, human rights evolve over time; they are subject to discussions, historical processes, as well as the spiritual, economic, and technical development of society. Their catalogue can therefore be supplemented or expanded in view of changing circumstances. These are conclusions that seem to be inspiring, despite some shortcomings in Weinberger’s democratic conception, his misunderstanding of Habermas’s theory, and the largely fragmentary nature of his “structured democracy.” Acknowledgements I would like to thank an anonymous reviewer for his/her valuable comments and suggestions that significantly improved an earlier version of this study. Funding This paper was supported by the Internal Grant Agency of AMBIS College. Declarations Competing Interests The author has no conflicts of interest to declare that are relevant to the content of this article. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Alexy Robert Law’s ideal dimension 2021 Oxford Oxford University Press Alter Karen J. Zürn Michael Conceptualising backlash politics: Introduction to a special issue on backlash politics in comparison British Journal of Politics & International Relations 2020 22 4 563 584 10.1177/1369148120947958 Avio Kenneth L. Scarcity, discourses of implementation, and habermasian law and democracy Ratio Juris 2000 13 2 148 161 10.1111/1467-9337.00147 Bader Veit Crisis of political parties and representative democracies: Rethinking parties in associational, experimentalist governance Critical Review of International Social and Political Philosophy 2014 17 3 350 376 10.1080/13698230.2014.886380 Barberá Pablo Persily Nathaniel Tucker Joshua A. Social media, echo chambers, and political polarization Social media and democracy: The state of the field and prospects from reform 2020 Cambridge Cambridge University Press 34 55 Bröstl Alexander Pattaro Enrico Roversi Corrado 20th-century legal philosophy in Czechoslovakia, the Czech Republic, and the Slovak Republic A treatise of legal philosophy and general jurisprudence 2016 Dordrecht Springer 613 634 Campbell Tom Legal positivism and deliberative democracy Current Legal Problems 1998 51 1 65 92 10.1093/clp/51.1.65 De Angelis Gabriele Habermas, democracy and the public sphere: Theory and practice European Journal of Social Theory 2021 24 4 437 447 10.1177/13684310211038753 Deschouwer Kris Harfst Philipp Kubbe Ina Poguntke Thomas New parties and the crisis of representation: Between indicator and solution Parties, governments and elites 2017 Wiesbaden Springer 73 85 Farkas Johan Schou Jannick Post-truth, fake news and democracy: Mapping the politics of falsehood 2020 New York Routledge Festenstein Matthew Deliberative democracy and two models of pragmatism European Journal of Social Theory 2004 7 3 291 306 10.1177/1368431004044194 Finlayson James Gordon The Habermas-Rawls Debate 2019 New York Columbia University Press Fischer Michael Ota Weinberger: Jedno Déjà vu Časopis pro právní vědu a praxi 2009 17 1 4 9 Forst Rainer The rule of reasons: Three models of deliberative democracy Ratio Juris 2001 14 4 345 378 10.1111/1467-9337.00186 Freeden Michael Vincent Andrew Freeden Michael Vincent Andrew Introduction: The study of comparative political thought Comparative political thought: theorizing practices 2013 London Routledge 1 23 Gerloch Aleš Tryzna Jan Zamyšlení nad přínosem profesora Oty Weinbergera k objasnění prostředků a cílů právní argumentace Časopis pro právní vědu a praxi 2009 17 1 53 70 Gherghina Sergiu Jacquet Vincent Why political parties use deliberation: A framework for analysis Acta Politica 2022 10.1057/s41269-022-00232-z Giusti Serena Piras Elisa Democracy and fake news: Information manipulation and post-truth politics 2021 New York Routledge Gutmann Amy Koggel Christine M. Democracy, philosophy, and justification Moral issues in global perspectives 2006 2 Toronto Broadview Press 178 183 Habermas Jürgen Between facts and norms. Contributions to a discourse theory of law and democracy 1996 Cambridge, Mass The MIT Press Habermas Jürgen The inclusion of the other: Studies in political theory 1998 Cambridge The MIT Press Habermas Jürgen Political communication in media society: Does democracy still enjoy an epistemic dimension? The impact of normative theory on empirical research Communication Theory 2006 16 4 411 426 10.1111/j.1468-2885.2006.00280.x Hagevi Magnus Blombäck Sofie Demker Marie Hinnfors Jonas Loxbo Karl Hagevi Magnus Blombäck Sofie Demker Marie Hinnfors Jonas Loxbo Karl A crisis for representative democracy? An introduction Party realignment in Western Europe: Electoral drivers and global constraints 2022 Cheltenham Edward Elgar Publishing 1 28 Hall Cheryl Recognizing the passion in deliberation: toward a more democratic theory of deliberative democracy Hypatia 2007 22 4 81 95 10.1111/j.1527-2001.2007.tb01321.x Hedrick Todd Rawls and Habermas: Reason, pluralism, and the claims of political philosophy 2010 Stanford Stanford University Press Herget James E. Contemporary German legal philosophy 1996 Philadelphia University of Pennsylvania Press Ignazi Piero The crisis of parties and the rise of new political parties Party Politics 1996 2 4 549 566 10.1177/1354068896002004007 Ingram David Reconciling positivism and realism: Kelsen and Habermas on democracy and human rights Philosophy and Social Criticism 2014 40 3 237 267 10.1177/019145371352016 Invernizzi-Accetti Carlo Wolkenstein Fabio The crisis of party democracy, cognitive mobilization, and the case for making parties more deliberative American Political Science Review 2017 111 1 97 109 10.1017/S0003055416000526 Kapust Daniel J. Kinsella Helen M. Kapust Daniel J. Kinsella Helen M. Introduction: Theory’s landscapes Comparative political theory in time and place: Theory’s landscapes 2017 New York Palgrave Macmillan 1 24 Kędziora Krzysztof Habermas on Rawls and the normative foundations of democracy European Journal of Social Theory 2021 24 4 545 561 10.1177/1368431020985416 Kindl Vladimír Kdo vlastně patřil k Brněnské škole normativní teorie? Malé zamyšlení nad bibliografií Brněnské školy ryzí nauky právní a jejím využitím k právněhistorickému studiu Právněhistorické studie 2014 44 2 108 115 Koller Peter Ota Weinberger: Stručný životopis Časopis pro právní vědu a praxi 2009 17 1 1 4 Kosinka Jan Petr Pozitivismus vs. iusnaturalismus: Opravdu jen přeceňovaný pseudoproblém, nebo spíše úhelný kámen řešení otázky legitimity práva? Právník 2019 158 5 489 502 Kováčová Denisa Surmajová Žaneta Sehnálek David Valdhans Jiří Dávid Radovan Kyncl Libor Normativistický inštitucionalizmus Ota Weinbegera Dny práva 2009 2009 Brno Masarykova univerzita 716 727 Kusin Vladimir V. Political grouping in the Czechoslovak reform movement 1972 London Macmillan Landemore Hélène Open democracy: Reinventing popular rule for the twenty-first century 2020 Princeton Princeton University Press MacCormick Neil Weinberger Ota An institutional theory of law: New approaches to legal positivism 1986 Dordrecht Springer March Andrew F. What is comparative political theory? The Review of Politics 2009 71 4 531 565 10.1017/S0034670509990672 Maršálek Pavel Gábriš Tomáš Horák Ondřej Tauchen Jaromír Brněnská normativní právní teorie Školy, osobnosti, polemiky: Pocta Ladislavu Vojáčkovi k 65. narozeninám 2017 Brno The European Society for History of Law 330 337 McNay Lois Leopold David Stears Marc Recognition as a fact and norm: The method of critique Political theory: Methods and approaches 2008 Oxford/New York Oxford University Press 85 105 Morgan Susan Fake news, disinformation, manipulation and online tactics to undermine democracy Journal of Cyber Policy 2018 3 1 39 43 10.1080/23738871.2018.1462395 Neblo Michael A. Impassioned democracy: The roles of emotion in deliberative theory American Political Science Review 2020 114 3 923 927 10.1017/S0003055420000210 Nussbaum Martha C. Perfectionist liberalism and political liberalism Philosophy & Public Affairs 2011 39 1 3 45 10.1111/j.1088-4963.2011.01200.x Peters Guy B. Institutional theory in political science: The new institutionalism 1999 London Pinter Petryszak Nicholas The frankfurt school’s theory of manipulation Journal of Communication 1977 27 3 32 40 10.1111/j.1460-2466.1977.tb02121.x Procházka Adolf Rechcigl Miloslav The Brno School of Jurisprudence The Czechoslovak contribution to world culture 1964 Berlin/Boston De Gruyter Mouton 405 413 Rhodes Samuel C. Filter bubbles, echo chambers, and fake news: How social media conditions individuals to be less critical of political misinformation Political Communication 2021 10.1080/10584609.2021.1910887 Smolak Marek Byl Ota Weinberger měkkým pozitivistou? Časopis pro právní vědu a praxi 2009 17 1 24 28 Talisse Robert B. Rawls on pluralism and stability Critical Review 2003 15 1–2 173 194 10.1080/08913810308443578 Tormey Simon The contemporary crisis of representative democracy Democratic Theory 2014 1 2 104 112 10.3167/dt.2014.010211 Trávníček Zdeněk Weinbergerovo pojetí významu normativní věty Právník 2020 159 7 540 549 Tugendhat Ernst Seebass Gottfried Tuomela Raimo Habermas on communicative action Social action 1985 Dordrecht Springer 179 186 van Roermund Bert Law, institution and legal politics. Fundamental problems of legal theory and social philosophy (law and philosophy library 14) by O. Weinberger (book review) Tijdschrift voor Filosofie 1992 54 3 577 Večeřa Miloš Právo jako institucionální skutečnost (K Weinbergerovu konceptu právní vědy) Časopis pro právní vědu a praxi 2009 17 1 9 18 Večeřa Miloš Schelle Karel Tauchen Jaromír Brněnská normativní právní škola Encyklopedie českých právních dějin, I. svazek A–Č 2015 Pilsen Aleš Čeněk 360 366 Večeřa Miloš Bárány Eduard Sociologický a ekonomický koncept práva Zmeny v chápaní práva: Pluralita systémov, prameňov, perspektív 2019 Bratislava Ústav štátu a práva SAV 30 44 Večeřa Miloš Večeřa Miloš Valdhans Jiří Weinbergerův koncept právního normativismu Dny práva 2019: Část VII – 100 let Brněnské školy normativní teorie 2020 Brno Masarykova univerzita 104 124 Verovšek Peter J. The reluctant postmodernism of Jürgen Habermas: Reevaluating Habermas’s debates with Foucault and Derrida The Review of Politics 2022 84 3 397 421 10.1017/S0034670522000316 Vojáček Ladislav Neckář Jan Radvan Michal Sehnálek David Valdhans Jiří Brněnská novokantovská právní škola Dny práva 2008 Brno Masarykova univerzita 542 546 Weinberger Ota Krawietz Werner Alexy Robert Logische Analyse als Basis der juristischen Argumentation Metatheorie juristischer Argumentation 1983 Berlin Dunker & Humblot 159 232 Weinberger Ota The role of rules Ratio Juris 1988 1 3 224 240 10.1111/j.1467-9337.1988.tb00016.x Weinberger Ota Law, institution and legal politics: Fundamental problems of legal theory and social philosophy 1991 Dordrecht/Boston/London Kluwer Academic Weinberger Ota Conflicting views on practical reason. Against pseudo-arguments in practical philosophy Ratio Juris 1992 5 3 252 268 10.1111/j.1467-9337.1992.tb00128.x Weinberger Ota Institutional theory of action and its significance for jurisprudence Ratio Juris 1993 6 2 171 180 10.1111/j.1467-9337.1993.tb00145.x Weinberger Ota Hungr Pavel Spravedlnost jako základní idea demokracie Právní filosofie (Vybrané problémy pro IX. semestr) 1993 Brno Masarykova univerzita 57 80 Weinberger Ota Argumentace v právu a v politice Právník 1994 83 7 577 589 Weinberger Ota Demokracie mezi propagandou a otevřenou společností Právny obzor 1994 77 5 441 449 Weinberger Ota Habermas on democracy and justice. Limits of a sound conception Ratio Juris 1994 7 2 239 253 10.1111/j.1467-9337.1994.tb00178.x Weinberger Ota Inštitucionalizmus: Nová teória konania, práva a demokracie 1995 Bratislava Archa Weinberger Ota Norma a instituce (úvod do teorie práva) 1995 Brno Masarykova univerzita Weinberger Ota Zur Theorie der politichse Argumentation: Gleichzeitig ein Beitrag zu einem aktuellen Problem der Demokratie Rechtstheorie 1995 27 163 182 Weinberger Ota Basic puzzles of discourse philosophy Ratio Juris 1996 9 2 172 181 10.1111/j.1467-9337.1996.tb00235.x Weinberger Ota Information and human liberty Ratio Juris 1996 9 3 248 257 10.1111/j.1467-9337.1996.tb00243.x Weinberger Ota Teorie spravedlnosti, demokracie a právní politika Právník 1996 84 7 514 523 Weinberger Ota Tolerance, společenská informace, diskurzní demokracie Acta Universitatis Carolinae: Iuridica 1996 1–2 71 77 Weinberger Ota Alternativní teorie jednání: Zároveň kritický rozbor praktické filozofie Georga Henrika von Wrighta 1997 Prague Filosofia Weinberger Ota Föderalismus und das Haus Europa Rechtstheorie 1999 30 417 430 Weinberger Ota Legal validity, acceptance of law, legitimacy: some critical comments and constructive proposals Ratio Juris 1999 12 4 336 353 10.1111/1467-9337.00129 Weinberger Ota Wintgens Luc J. Neo-institutionalism: my views on the philosophy of law The law in philosophical perspectives. Law and philosophy library 1999 Dordrecht Springer 253 272 Weinberger Ota Od brněnské školy k neo-institucionalismu Časopis pro právní vědu a praxi 1999 7 4 307 316 Weinberger Ota Nový institucionalismus jako základ právní a politické teorie Právník 2000 1 139 1 22 Weinberger Ota Za hlasem intelektuálního svědomí Časopis pro právní vědu a praxi 2000 8 3 273 284 Weinberger Ota Kosek Jan Od brněnské školy k neoinstitucionalismu Brněnská škola právní teorie (Normativní teorie) 2003 Prague Karolinum 389 408 Weinberger Ota Machalová Tatiana Vývoj a perspektivy brněnské školy ryzí nauky právní Místo normativní teorie v soudobém právním myšlení: K odkazu Františka Weyra a Hanse Kelsena 2003 Brno Masarykova univerzita 9 21 Weinberger Ota Inštitucionalizmus: Nová teóra konania, práva a demokracie 2010 Bratislava Kalligram White Stephen K. Farr Evan Robert “No-saying” in Habermas Political Theory 2012 40 1 32 57 10.1177/009059171142685
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==== Front Risk Manag Risk Management 1460-3799 1743-4637 Palgrave Macmillan UK London 107 10.1057/s41283-022-00107-9 Original Article Exploring the indirect links between enterprise risk management and the financial performance of SMEs http://orcid.org/0000-0003-1401-9784 Syrová Lenka [email protected] http://orcid.org/0000-0001-5699-9544 Špička Jindřich [email protected] grid.266283.b 0000 0001 1956 7785 Department of Strategy, Faculty of Business Administration, Prague University of Economics and Business, Prague, Czech Republic 12 12 2022 2023 25 1 110 9 2022 © The Author(s), under exclusive licence to Springer Nature Limited 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. This paper responds to the lack of empirical evidence on how enterprise risk management (ERM) and the financial performance of small and medium-sized enterprises (SMEs) are related. Structural equation modeling is used to explore new mediators in the relationship between ERM and SME financial performance. The results show that organizational culture (mission dimension) and strategic risk management performance are full and positive mediators between ERM and financial performance. These research results highlight the fact that the implementation of ERM in an enterprise does not by itself generate the expected effects without the existence of a mature organizational culture and the monitoring of strategic risk management performance. These findings are particularly relevant for SMEs with “pretend ERM” that lacks the strategic and operational components. ERM also helps to transform the negative effect of foreign capital in SME equity on financial performance into a positive effect. Keywords Enterprise risk management SMEs Structural equation modeling Organizational culture Strategic risk management performance JEL Classification G32 M14 M20 http://dx.doi.org/10.13039/501100001823 Ministerstvo Školství, Mládeže a Tělovýchovy IGA VŠE F3/16/2021 Syrová Lenka issue-copyright-statement© Springer Nature Limited 2023 ==== Body pmcIntroduction Increasing levels of uncertainty call for proactive risk management in all organizations. The parallel crises triggered by the COVID-19 pandemic (Chakraborty and Maity 2020) and the military conflict in Ukraine have impacted most industries and businesses, unlike the Great Recession of the late 2000s, which primarily affected the financial sector (Gertler and Gilchrist 2018). Systematic risk has long been underestimated in advanced economies (Pagach and Wieczorek-Kosmala 2020). In such a situation, an intuitive assessment of risk outcomes, as often performed by smaller enterprises, is not enough (Grondys et al. 2021). Companies face new challenges and find it harder to maintain their profitability and competitiveness. Therefore, holistic enterprise risk management (ERM) is becoming increasingly important in small and medium-sized enterprises (SMEs). Nonfinancial SMEs are mostly unregulated. Thus, there is little pressure to implement a comprehensive risk management system. Nevertheless, in recent years, SMEs have started implementing formal risk management processes to increase their competitiveness (Wirahadi and Pasaribu 2022). ERM improves the quality of the information about enterprise risk profiles. The adoption of ERM reduces systematic risk. The purpose of ERM is to reduce the probability of losses and, therefore, reduce the need to borrow external resources, which positively impacts the expected cost of capital (Berry-Stölzle and Xu 2018). The implementation of a risk management system entails many internal changes. International risk management standard ISO 31000 provides principles, frameworks, and procedures for risk management regardless of the size and orientation of the organization (Aven 2017). The Committee of Sponsoring Organizations of the Treadway Commission (COSO) provides an alternative ERM framework. Such strategic changes are financially and organizationally challenging and sometimes take several years to implement. The difficulty of implementing a holistic risk management system such as ERM may not be as great for large and capital-intensive companies. Nevertheless, the organizational integration of ERM can take a long time given the complexity of the organizational structure of large companies. On the other hand, SMEs usually do not have as high of a capital capacity for implementing ERM, but organizational integration may be faster due to the greater flexibility of SME decision-making (Adomako et al. 2021). SMEs are a vulnerable group of companies because they may lack the resources necessary to overcome a crisis (Rathore and Khanna 2020). At the same time, the high volatility of the economic environment exacerbates the uncertainty and unpredictability of economic factors, increasing the risk associated with doing business (Gengatharan et al. 2020). In addition, the size of the business influences the amount of risk taken, which is generally lower for larger companies (Jenny 2020). Moreover, SMEs are a vital part of the European economy. The average value contributed by SMEs to the economy in the European Union is approximately 56% (Statista 2021). Most research on ERM has been conducted empirically in large financial and publicly traded companies in emerging markets (Florio and Leoni 2017). SMEs are largely unregulated, and there is no intense pressure to implement a holistic risk management system. However, SMEs are now in a more difficult situation. ERM is a way for SMEs to proactively manage their business risks while improving their business performance, as confirmed among large enterprises (Syrová and Špička 2022b). The research gap lies in the unanswered question of whether the implementation of ERM improves the financial performance of SMEs. This article responds to the ongoing crisis and changes in the business environment. The authors emphasize the growing need to study the impact of the ERM approach among SMEs. ERM can significantly contribute to the maintenance of company competitiveness and crisis survival. This research results in the development of a new model that extends the theoretical understanding of ERM in SMEs. The study reveals significant mediators that positively influence the relationship between ERM and firm financial performance. The findings provide a critical understanding of the role of ERM in SMEs and the realization that the ERM approach is not self-sustaining. Simply implementing an ERM approach does not directly impact SME performance. This research focuses on the implementation of ERM in Czech SMEs. The Czech Republic is a Central European country, and most Czech SMEs were established in the early 1990s after forty years under the centrally planned socialist economy. The Czech Republic is an open and export-oriented economy in which services and industry play a dominant role. It has been operating in the European Union’s single market since 2004. The contribution of SMEs to GDP is approximately 40%, below the EU average, and SME exports account for more than half of all Czech exports (Bures 2017). The management of SMEs in the Czech Republic was affected by the loss of business continuity. An integral part of the transformation into a postsocialist economy was the incorporation of risk into management decisions in the 1990s. Research from neighboring Slovakia shows that risk management was conducted in a relatively intuitive manner, without data support or the appropriate methods, know-how, and trained staff to make management decisions (Klučka and Grünbichler 2020). The study by Virglerova (2019) points out the lack of financial risk management experts. This paper explores the relationship between ERM and subjective financial performance among nonfinancial SMEs in the Czech Republic. To achieve this goal, the study quantifies the mediating effects of organizational culture and strategic risk management performance and recapitulates the previously revealed mediators of this relationship. The main contribution of the paper lies in the development of a new model for studying the impact of ERM on the subjective financial performance of SMEs. The results show that organizational culture (mission dimension) is a catalyst for ERM effects, while at the same time, the implementation of an ERM performance monitoring system improves the subjective financial performance of the enterprise. The originality of the paper is in showing that ERM is not self-sustaining. ERM does not spill over to all levels of management nor have desirable effects on the strategic financial objectives of the SME without a strong organizational culture and a good performance monitoring system. Theoretical foundation The goal of risk management is to minimize key risks, and an appropriate level of risk management that enhances value for owners and other stakeholders must be chosen (Meulbroek 2002). The ERM approach focuses on all potential future risks (both pure and speculative) (Schiller and Prpich 2014). Enterprises can focus on risk management opportunities by incorporating the dual nature of speculative risks (Lundqvist 2015). The ERM approach should, among other things, explicitly identify the threats to firm value and the opportunities to increase it (Gatzert and Martin 2015). The findings of a systematic literature review (Syrová and Špička 2022b) show that the relationship between ERM and company performance is not direct but is mediated by strategic agility (Ai Ping et al. 2017), competitive advantage (Yang et al. 2018), strategic planning (Sax and Andersen 2019), and information systems quality (Kurdi et al. 2019). Previous research has mainly been conducted in listed companies and large international firms (Callahan and Soileau 2017; Farrell and Gallagher 2019; Kommunuri et al. 2016; Laisasikorn and Rompho 2014; Malik et al. 2020; Quon et al. 2012). Only a few studies have focused on SMEs. The results of the recent research studies show mostly positive relationship between ERM and SME performance (Hanggraeni et al. 2019; Jenya and Sandada 2017; Rehman and Anwar 2019; Yang et al. 2018). However, the results of some studies on SMEs identified the relationship between ERM and performance as insignificant (Glowka et al. 2020; Hiebl et al. 2019). Other studies quantified the relationship ambiguously depending on the analysis of the individual components of ERM (Heong and Teng 2018; Yakob 2019). The authors of the studies conducted in SMEs mainly used subjective assessment of firm performance and multiple regression analysis. The purpose of ERM is to integrate risks into the enterprise’s organizational design and decision-making process (Ogutu et al. 2018). Given that ERM is a critical initiative that helps increase organizational resiliency in times of uncertainty, it is reasonable to assume that the internal culture of the firm is a significant factor in ERM adoption. Indeed, ERM adopters encounter issues related to organizational culture, but the mediating effect of organizational culture on the relationship between ERM and organizational financial performance has not yet been empirically evaluated and demonstrated. Organizational culture Organizational culture is the set of the underlying values, beliefs, and assumptions within an organization, the patterns of behavior that result from those perspectives, and the symbols that express the connections among the assumptions, values, and behaviors of organizational members (Denison 1990). Several empirical studies have demonstrated the positive impact of organizational culture on organizational performance (Han 2012; Tadevosyanová 2015; Bhuiyan et al. 2020). However, the effect of organizational culture on the effectiveness of ERM implementation has not yet been demonstrated. Organizational culture enables more effortless penetration of ERM into all functional areas of the organization and faster adaptation under the conditions of risk and uncertainty (Thomya and Saenchaiyathon 2015). There are different types of organizational culture: market culture, clan culture, adhocratic culture, and hierarchical culture (Cameron and Quinn 2011). Research has shown that only clan cultures positively affect project performance and internal and external organizational performance. In contrast, hierarchical cultures, market cultures, and adhocratic cultures do not affect organizational performance (Yazici 2011). However, the same research (Yazici 2011) also showed that managerial experience enhances the positive influence of clan culture (on project performance), adhocratic culture (on project performance and internal and external firm performance), and market culture (on external firm performance). On the other hand, a hierarchical culture does not impact performance because it creates a hostile work environment by bureaucratizing the organizational structure. A hierarchical culture is characterized by a formalized and structured work environment emphasizing procedures and regulations whose unifying element is formal rules. Managers are expected to be good coordinators and organizers who can keep the organization running smoothly, consistently, and efficiently (Cameron and Quinn 2011). Denison’s Organizational Culture Questionnaire is one of the most popular methods for operationalizing organizational culture (Denison 1990). A study by Denison and Mishra (Denison and Mishra 1995) found that all four dimensions of organizational culture—mission, consistency, commitment, and adaptability—were related to various performance criteria. Commitment and adaptability are indicators of flexibility, openness, and responsiveness and are strong drivers of organizational growth. Consistency and mission indicate organizational direction, integration, and vision and are good predictors of profitability. All four characteristics of organizational culture are essential predictors of quality, employee satisfaction, and overall performance. According to Denison, the strongest predictor of performance is the organization’s mission, i.e., whether the organization has an articulated mission and whether its employees share that mission. Denison’s scales for consistency (e.g., Do you have coordinated systems that allow you to build consensus based on your core values?) and mission (e.g., Do you know where you are going? Do you have clear goals and a strategy to achieve them?”) might be good indicators of organizational culture in the context of the relationship between ERM and financial performance. H1 Organizational culture (mission dimension) mediates the relationship between ERM and the subjective financial performance of SMEs. H2 Organizational culture (consistency dimension) mediates the relationship between ERM and the subjective financial performance of SMEs. Through organizational culture, ERM is disseminated and cultivated throughout the organization. The overarching dimensions of organizational culture, namely, consistency and mission, could provide an appropriate implementation framework for ERM because organizational culture is a system of shared assumptions, attitudes, beliefs, habits, and values that form the basis for typical behavior patterns (Gordon 1991). Strategic risk management performance Research in strategic risk management has highlighted the importance of creating a risk management culture at all levels of the organization (Moeller 2007). A risk management culture is defined as the shared values and beliefs of an organization’s employees (decision-makers) regarding risk-taking (Bui et al. 2018). Through their risk management culture, organizations are able to quickly identify and hedge key risks and respond to and mitigate unforeseen risks while identifying and capitalizing on new opportunities early on using an ERM approach to improve risk performance (Sax and Andersen 2019). A risk management culture is critical to an organization’s strategic decision-making and requires the active involvement of the board and senior management. Top management shapes risk culture through leadership, transparent communication, and risk management using appropriate processes and resources (Osman and Lew 2020). While the impact of ERM and strategic reactivity has been tested in terms of firm performance and value, little is known about the impact of ERM on strategic risk performance (Sax and Torp 2015). Strategic risk management can be integrated into effective, well-known processes to bridge the gap between the risk and strategic management literatures. Risk management is not just the concern of the central risk management department. To create an effective risk management system, the enterprise must build a dynamic risk management team that quickly identifies and addresses new threats and opportunities. Thus, the risk management becomes strategic as it encompasses the culture and leadership styles and is reinforced by strategic responsiveness. Incorporating evaluations of strategic risk management performance as an integral part of governance could make ERM more effective in terms of the financial goals it seeks to achieve. Moreover, the 2017 update to the COSO framework emphasizes the importance of integrating ERM with business strategy and performance (COSO 2017). H3 Strategic risk management performance mediates the relationship between ERM and the subjective financial performance of SMEs. Materials and methods The level of ERM in a company can generally be determined through a questionnaire survey or a content analysis of company documents. Early empirical studies assessed the level of ERM with a binary approach, used primarily in content analysis (Silva et al. 2019). Content analysis can be used as a method to determine the presence of ERM by determining whether ERM is used (1 = the company uses ERM, or relevant keywords are listed in company documents) or not (0 = the company does not use ERM, or relevant keywords are not listed in company documents). However, a binary score alone cannot determine the extent of ERM implementation. For this reason, some authors have adopted an ordinal measure (Husainia et al. 2019; Darmastuti et al. 2020), with individual ERM metrics (obtained either from a content analysis or a questionnaire survey) summed together. The resulting summation yields the value of a simplified maturity index (Florio and Leoni 2017). Moreover, the disclosure of risk management information in SME reporting is voluntary. For this reason, the authors of this study choose the quantitative questionnaire survey method. Through the questionnaire survey, it is possible to obtain primary data and more accurate information on the level of ERM implementation in a given company when secondary data in company reports are not available, as with SMEs. The authors chose quantitative research because the vast majority of previous studies on the relationship between ERM and corporate financial performance have been based on quantitative research. Quantitative research is more objective than qualitative research, and the results are based on larger samples that are representative and generalizable to the population (in this case to SMEs in the Czech Republic). Quantitative research can provide accurate, reliable and consistent data that can be processed using validated statistical methods. The sample covers nonfinancial SMEs in the Czech Republic. The targeted sample consists of 300 SMEs that are members of the Association of Small and Medium-sized Enterprises in the Czech Republic. The sample size provides sufficient statistical power for the tests. Quota sampling ensures the representativeness of the sample and the generalizability of the results although it is not based on random selection but on a predefined panel of firms willing to respond. Data were collected from September to November 2021 through the external research company Ipsos which closely cooperates with Association of Small and Medium-sized Enterprises in the Czech Republic. Respondents were owners, CEOs, senior managers, sales managers, and finance/commercial managers. These roles should have a sufficient level of responsibility to ensure the accuracy of the responses. Unlike large and multinational companies, SMEs do not typically employ a chief risk officer or risk manager, as risk management is the responsibility of the top management or the business owners. Response variability was calculated and unusual values were identified to clean the original sample of 300 SMEs, and a final sample of 296 respondents was obtained. The self‐reporting is frequently applied for measuring the individual opinions and statements in the quantitative research. Unlike objective measures, which are not affected by personal bias and are represented by facts, the subjective self-reporting is associated with possible biases negatively affecting validity and reliability. Using self-reported information for decision-making results in endogenous selection bias which creates spurious associations between the measure being reported and factors that influence reporting (Scott and Balthrop 2021). However, self-reporting through the batteries of questions is the standard form of information-gathering mechanism for Structural Equation Modelling which effectively tests the relationship between latent variables (Hatcher 2013). Independent variable (ERM) The study uses an ordinally scaled ERM index incorporating the number of ERM characteristics. There are 14 characteristics, each taking on a binary value (1 if the company reports the presence of the characteristic, 0 if not). The ERM characteristics were adopted from Miloš Sprčić et al. (2017), who were inspired, for example, by COSO (2004), Lundqvist (2014), and Meulbroek (2002). The ERM construct (Appendix 1) assumes that SMEs may not have formalized policies or internal regulations regarding risk management. The methodology used to assess the level of ERM has already been validated in empirical research in Central Europe, which has used the same terminology in its construction of the questions (Miloš Sprčić et al. 2017; Marc et al. 2018; Mardessi and Ben Arab 2018). Dependent variable (subjective financial performance) Subjective financial performance (Appendix 1) is measured using the validated construct developed by Uhlaner et al. (2014) and is based on three indicators: the financial performance of the company compared to its competitors (5-point scale from 1 = much worse to 5 = much better), profitability in the last fiscal year (7-point scale from 1 = extreme losses to 7 = extremely profitable in the last fiscal year), and current liquidity (4-point scale from 1 = very low liquidity to 4 = substantial liquidity). This subjective assessment of financial performance is not tied to companies’ financial statements, which are generally published only by medium-large and large companies (Kamboj and Rahman 2015; Abbasi and Weigand 2017; Kumar et al. 2018). In contrast, a subjective assessment of financial performance is appropriate for questionnaire surveys among SMEs. Mediators Organizational culture is the hypothetical mediator of the relationship between ERM and the subjective financial performance of SMEs (Appendix 1). The construct of organizational culture is taken from Denison (1990). Only two dimensions (corporate mission and corporate consistency) are expected to relate to company performance and stability based on previous research (Tadevosyanová 2015). Answers to individual statements are given on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). Strategic risk management performance (SRMP) is another hypothetical mediator of the relationship between ERM and the subjective financial performance of SMEs (Appendix 3). The scales for strategic risk management performance were adopted from Sax and Torp (2015), where respondents were asked to make three comparisons with their competitors, considering the past three years, using a 7-point scale (from 1 = significantly worse to 7 = significantly better). Specifically, the comparisons are ‘Ability to hedge against key known risks and uncertainties’, ‘Ability to respond to and mitigate unforeseen risks’, and ‘Ability to seize new opportunities’. Control variables The ERM control variables are firm size as measured by the number of employees (Beasley et al. 2015; Gordon et al. 2009), firm age (Yang et al. 2018), and the proportion of foreign capital in the firm (Syrová and Špička 2022a). Previous studies have shown that foreign direct investment has a positive effect on the ability to use advanced forms of technology, to employ managers with greater international experience and who are more skilled in using modern management techniques, to apply good corporate governance practices and to access credit in international financial markets (Abor 2010). SMEs may have limited opportunities for foreign investment compared to large firms. Another reason could be the historical context of post-communist countries, where fear of foreign investment or investors may still exist. Structural equation modeling The method used to explore the relationship between ERM and the subjective financial performance of SMEs is structural equation modeling (SEM). This method has also been applied by other authors who have studied the effects of ERM, e.g., (Ai Ping and Muthuveloo 2015; Wisutteewong and Rompho 2015). SEM is a method of multivariate analysis used to test and estimate complex causal relationships among variables, even when those relationships are hypothetical or not directly observable (Williams et al. 2009). The authors selected SEM because ERM, subjective financial performance, and the proposed mediators cannot be measured directly with a simple question. The main advantage of SEM is the more efficient evaluation of measurement and structural path models, mainly when the structural model contains multiple dependent variables and latent constructs based on proxy variables with multiple items (Astrachan et al. 2014). Compared to other statistical methods such as regression, SEM allows researchers to simultaneously assess the relationships between constructs with multiple items (latent variables) and reduces the overall error associated with the model. Another advantage over regression is the ability to conduct a path analysis for all structural relationships at once, which leads to more accurate results (Astrachan et al. 2014). There are two basic types of SEM—covariance-based SEM (CB-SEM) and partial least squares SEM (PLS-SEM). CB-SEM is used mainly to confirm theories. To this end, it determines how well a proposed theoretical model can estimate the covariance matrix for a sample of data. In contrast, PLS-SEM is used mainly for theory development in exploratory research, as it explains the variance of the dependent variable when the model is examined (Hair et al. 2017). Although PLS-SEM is a regression method, it is nonparametric. That is, it makes no assumptions regarding the distribution of the data. PLS-SEM does not assume that the data are normally distributed; moreover, it is appropriate to use PLS-SEM when the data are categorical or ordinal or contain a single item (Hair et al. 2017). PLS-SEM does not assume that the proxies created are identical to the constructs (latent variables) that they replace. They are explicitly recognized as proxies (Hair et al. 2017). In this exploratory study, PLS-SEM and the bootstrapping method (5,000 iterations, path weighting scheme) are used to test the significance of the relationships in the model. Results The structure of the sample is matched to that of the national economy to ensure the representativeness of the sample in terms of company size and sector (Table 1).Table 1 Structure of the sample by number of employees (size) and sector Absolute frequency Relative frequency (%) 4–49 employees 159 53.7 50–99 employees 77 26.0 100–249 employees 60 20.3 Primary 13 4.4 Secondary 88 29.7 Tertiary 173 58.4 Quaternary 22 7.4 Note: The primary sector provides raw materials and unprocessed food; it includes agriculture, forestry, fishing, hunting and mining (NACE Sections A and B). The secondary sector processes raw materials from the primary sector into goods; it includes industry, construction, handicrafts, and other nonindustrial manufacturing (NACE Sections C, D, E, F). The tertiary sector provides services, trade, and transportation; it includes transportation, marketing, attention, access, and experience (NACE Sections H, I, J, K, L, O, Q, R, S, T). The quaternary sector includes research and development, consulting, and education (NACE Sections M, P) Source Own calculations The authors use a formative measurement approach for the PLS-SEM analysis (see Appendix 2). The PLS-SEM contains the following:Latent variables: ERM level (ERM), subjective financial performance of the company (FP), organizational culture–mission dimension (ORGM), organizational culture–consistency dimension (ORGC), and strategic risk management performance (SRMP). Manifest variables: proportion of foreign capital in the company (FC), firm size (FS), and firm age (FA). Table 2 contains basic description of the latent and manifest variables. Descriptive statistics of the latent variables were calculated from the mean scores of the partial manifest variables for each enterprise because of the relatively high reliability of the constructs.Table 2 Descriptive statistics of the latent and numeric manifest variables Statistics Number of valid observations Mean Standard Deviation Minimum Maximum ERM 296 0.39 0.31 0 1 FP 296 3.47 0.71 1.33 5.33 ORGM 296 3.61 0.48 1 4.73 ORGC 296 3.48 0.45 1.47 4.8 SRMP 296 4.21 0.98 1.33 7 FC (%) 272 17.3 28.97 0 100 FA (years) 286 18.33 11.36 1 70 Source Own calculations The PLS-SEM analysis follows the steps recommended by Hair et al. (2017). The final model is iteratively explored (Fig. 1).Fig. 1 Iterative exploration of the final model through PLS-SEM. Source Authors’ own elaboration The proposed model with proxy variables shows a high discriminant validity (HTMT) value for the relationship between ORGC and ORGM (0.977). In addition, ORGC proved to be a nonsignificant mediator at a 5% significance level. Moreover, the internal variance inflation factor (VIF) between ORGC and ORGM is high (3.544). Therefore, organizational culture–consistency dimension (ORGC) was excluded from further modeling. The next step resulted in the identification of ORGM as a full mediator in the relationship between ERM level and strategic risk management performance (Zhao et al. 2010). Figure 2 presents the final model.Fig. 2 Final PLS-SEM model. Source Own calculations The final model satisfies the assumptions of a robust model (discriminant validity according to HTMT, collinearity, reliability). Appendix 3 presents the details. The model results (Table 3) show that foreign capital share and firm size have a direct and positive effect on ERM level, while firm age has an inversely proportional effect on ERM level. Organizational culture–mission dimension is a significant mediator between ERM and subjective financial performance. The strategic risk management performance tracking system also plays an important role in the relationship between ERM and subjective financial performance. The standardized root mean square residual (SRMR) and the RMS theta indicate a well-fitting model (Table 4). The final model also includes the results for the indirect effects, which are discussed in the next section (Table 5).Table 3 Estimated parameters for the final model Statistics Original Sample (O) Sample Mean (M) Standard →Deviation (STDEV) T Statistics (|O/STDEV|) P→ Values FA—> ERM − 0.168 − 0.173 0.048 3.499 0.001 ERM—> ORGM 0.183 0.188 0.090 2.040 0.042 SRMP—> FP 0.371 0.367 0.050 7.415 0.000 FC—> ERM 0.345 0.345 0.068 5.053 0.000 FC—> ORGM − 0.179 − 0.174 0.091 1.974 0.049 ORGM—> SRMP 0.356 0.369 0.044 8.068 0.000 ORGM—> FP 0.210 0.220 0.058 3.610 0.000 FS—> ERM 0.178 0.183 0.059 3.029 0.003 Source Own calculations Table 4 Model fit measures Model Fit Measure Saturated Model Estimated Model Standardized Root Mean Square Residual (SRMR) 0.08 0.08 d_ULS 4.699 4.797 d_G 0.763 0.769 Chi-Squared 1231.83 1239.822 Normed Fit Index (NFI) 0.728 0.726 RMS Theta X 0.092 Notes: An SRMR value less than 0.10 or 0.08 (in a more conservative version; see Hu and Bentler (1999) is considered a good fit. RMS_Theta values below 0.12 indicate a well-fitting model (Henseler et al. 2014). Source Own calculations Table 5 Indirect effects in the final model Specific Indirect Effects Specific Indirect Effects FA→ ERM →ORGM →FP − 0.006 FA→ ERM →ORGM→ SRMP − 0.011 FC→ ERM→ ORGM →SRMP 0.022 FA→ ERM →ORGM − 0.031 ERM→ ORGM→ SRMP 0.065 FS→ ERM→ ORGM→ SRMP→ FP 0.004 ERM →ORGM →FP 0.038 FC→ ORGM→ SRMP − 0.064 ERM→ ORGM→ SRMP→ FP 0.024 FC→ ORGM→ FP − 0.038 FC→ ERM→ ORGM 0.063 FC→ ERM→ ORGM→ SRMP→ FP 0.008 FS→ ERM→ ORGM→ SRMP 0.012 ORGM→ SRMP→ FP 0.132 FC→ ERM→ ORGM→ FP 0.013 FC→ ORGM→ SRMP→ FP − 0.024 FS→ERM→ ORGM→ FP 0.007 FS→ ERM→ ORGM 0.032 FA→ ERM→ ORGM→ SRMP→ FP − 0.004 Source Own calculations Discussion This study identifies new significant variables that mediate the effect of ERM on the subjective financial performance of SMEs. The model includes the latent variables of ERM level (Miloš Sprčić et al. 2017), strategic risk management performance (Sax and Torp 2015), organizational culture→mission dimension (Denison 1990), and subjective financial performance (Uhlaner et al. 2014)→and the determinants of ERM identified in previous studies: the proportion of foreign capital in the company, firm size, and firm age. The results show that firm size directly affects the level of ERM in a given firm (0.178), which supports the findings of previous studies (Nasir 2018; Jurdi and AlGhnaimat 2021). As company size increases, there is a need to manage the company using formal procedures and internal guidelines. The need to manage the business increases, as does the need to manage risk formally. Small enterprises may lack the resources and reliable mechanisms needed to support their risk management activities (Brustbauer 2014). In addition, for small enterprises that are do not face regulatory pressure, full ERM implementation may not be necessary because the benefits of ERM do not outweigh the associated costs. SMEs do not necessarily benefit from adopting formal ERM methods (Hiebl et al. 2019). Because a firm’s processes become more formalized as it grows, SMEs have a greater need for more efficient ERM techniques and, therefore, may be able to implement ERM because of a greater availability of resources. In addition, previous research has shown that companies that have implemented ERM perform better (Gordon et al. 2009; Grace et al. 2015), have higher value (Farrell and Gallagher 2015), and have a lower cost of capital (Berry-Stölzle and Xu 2018). Large companies’ business activities and transaction types are more diverse and complex than those of smaller companies (Witek-Crabb 2014). In addition, larger companies can devote more resources and capacity to more diversified alternative investments (Golshan and Rasid 2012). Thus, growing companies that have not implemented ERM may be missing opportunities to improve their business performance and value. From a management perspective, it would be valuable to understand why some mid-sized companies have not implemented ERM or are hesitant about implementing ERM. A reluctance to adopt ERM and the corresponding lack of benefits relate to firm age. The study results show that the age of the company has an inverse influence on the level of ERM (− 0.168). Younger companies are not encumbered by history, are more flexible, and are led by managers with better theoretical knowledge of modern management methods. The historical context of the Czech Republic is characterized by the disappearance of many SMEs due to the political regime and centrally planned economy. After the political regime changed in 1990, SMEs started to form again, but with a loss of continuity in their management styles (Tarko 2020). The older a company is, the less likely it is to use advanced ERM techniques. Older companies that have operated for a longer time tend to institutionalize existing processes and adopt bureaucratic behavior, leading to barriers to strategic change (Hannan and Freeman 1984), which can also negatively affect financial performance. Thus, firm age could harm ERM implementation, a finding that contrasts with the results of a study examining the relationship between firm age and innovation in the work environment, which shows that firm age has a positive effect (Dukeov et al. 2018). An explanation for the relationship between firm age and the level of ERM implementation can also be found in Greiner’s theoretical model of firm growth (Greiner 1989). Older companies may suffer from a bureaucratic crisis in which the company spends more and more time only on internal matters, leaving no time to implement new management practices, including ERM. Our research has also explored the positive impact of foreign capital in SME equity on ERM levels (0.345), which is one of the important contributions of this paper. The global business environment and internationalization are great challenges for companies that want to expand their business activities, but they also pose a risk if those companies’ business plans fail. Competition and constant changes in material costs, tax and insurance burdens, and growth in energy processes are the sources of many problems that can lead to a loss of market share and to financial losses (Hudáková and Masár 2018). However, most SMEs do not have to own a foreign subsidiary directly in order to participate in other international activities (Gubik and Bartha 2014), such as direct investments or other foreign equity investments. A study that examined the presence of foreign direct investment in SMEs found a positive relationship with SME development (Lu and Beamish 2006). Many SMEs resist foreign investment and foreign capital. The arguments of the owners, which invoke national tradition, are not always beneficial for the company from a long-term strategic point of view and often express a hidden fear for their own career and the fear of losing control over their company. This is confirmed by the research findings of this paper: the share of foreign capital positively impacts the level of ERM (0.345). The inflow of foreign capital means a strengthening of capital and more control, which can be exploited precisely through ERM. Foreign investors can result in faster adoption of international standards such as ISO. However, the adoption rate does not depend on the amount of foreign investment but on the investor (Prakash and Potoski 2007). The Czech Republic receives investments mainly from Western European countries, where the ERM approach may be more widespread. Another argument supporting the positive impact of foreign capital on the level of ERM is the ability to adequately manage the increased risks associated with receiving foreign capital. A study conducted with a sample of African financial institutions supports the authors’ research findings. The results show that the presence of foreign capital significantly affects ERM implementation (Matovu 2017). Implementing ERM alone does not result in improved business performance or other benefits. The implementation of formal ERM practices and processes must be supported by general agreements among employees and management. Organizational culture is a catalyst for the ERM approach. Our study also examines the ability of strategic risk management to connect all levels of management. The PLS-SEM results support H1: Organizational culture (mission dimension) mediates the relationship between ERM and the subjective financial performance of SMEs. However, the proportion of foreign equity has an adverse effect on the organizational culture – mission dimension (− 0.179). This negative effect could be caused by different understandings of the mission from the investors’ point of view. With the fragmentation of investors, there may be fewer common goals in a given company. This negative impact may even affect firm performance (Foreign capital→ Organizational culture–mission→ Financial performance: indirect effect = − 0.038; Table 5). However, when a firm uses the ERM approach, the overall indirect effect of the proportion of foreign equity on the subjective financial performance of the firm is positive in the presence of the mediating variable ERM (Foreign capital→ ERM level→ Organizational culture–mission→ Financial performance: indirect effect = 0.013; Table 5). Thus, the level of ERM as a mediating variable can transform the negative effect of foreign equity on financial performance into a positive effect through the organizational culture (mission dimension). This result demonstrates the central role of ERM in organizations, which is consistent with previous studies (e.g., Baxter et al. 2013; Hoyt and Liebenberg 2011; Laisasikorn and Rompho 2014). The results clearly show the inevitable and crucial role of ERM when companies decide to expand abroad or allow foreign investors. The ERM approach mitigates the negative impact of foreign capital on the consistency of organizational culture (mission dimension) and supports the financial performance of the company at the same time. According to previous studies, organizational culture itself positively affects firm performance (Han 2012; Tadevosyanová 2015; Bhuiyan et al. 2020). However, previous studies have not established a link between organizational culture, ERM and the business performance of SMEs. The PLS-SEM results do not support H2; the variable organizational culture (consistency dimension) was removed from the model due to the high value of discriminant validity with organizational culture (mission dimension) and the concurrent insignificance of the relationship at the 5% significance level. The results of the PLS-SEM analysis do not support Hypothesis H3: strategic risk management performance mediates the relationship between ERM and the subjective financial performance of SMEs. The ERM approach should be present at all management levels within the organization and should also positively influence the performance of strategic risk management. The relationship is indirect and is mediated through organizational culture (mission dimension). The mission dimension of organizational culture is strategic and positively supports the strategic risk management performance (0.356). However, the ERM approach should include strategic, operational, and control perspectives (Dvorski Lacković et al. 2022); moreover, COSO (2017) also includes the components of “strategy and objective-setting” and “performance”. The results may have been obtained because a relatively large proportion of companies (approximately 30%) use a version of ERM called “pretend ERM”, where the SMEs have formally implemented an ERM approach, but the risk management system lacks the strategic and operational components of an ERM system and focuses only on the reporting aspect (Dvorski Lacković et al. 2022; Syrová and Špička 2022a). Conclusion and implications Regarding the theoretical implications, this study reveals new mediators between ERM and the subjective financial performance of SMEs. The PLS-SEM method is suitable for analyzing complex relationships and testing causal relationships. Exploring indirect pathways can reveal consequential effects and help managers and owners understand various relationships. Complicated ERM indices (e.g., Gordon et al. 2009) are not suitable for the nonfinancial sector because the input variables for calculating such indices are difficult or impossible to obtain. The model works with the direct and indirect effects of ERM implementation. The indirect effects show the crucial role of organizational culture (mission dimension) and evaluations of strategic risk management performance in the relationship between ERM and the subjective financial performance of SMEs. From the management perspective, it is essential to establish functional and integrated processes for ERM implementation. ERM must be integrated with the organizational culture and the performance monitoring systems in the SME. Managers and owners should emphasize the functional implementation of ERM, not just a pretend ERM (Syrová and Špička 2022a) that lacks all the elements of an ERM approach. The ERM system must not be a “facade without the substance” that does not contribute to better planning and decision-making processes (Dvorski Lacković et al. 2022). This research provides new information about the role of foreign capital in nonfinancial SMEs—it is a determinant that has a positive impact on ERM implementation. The share of foreign capital results in an inflow of new management practices and process innovations and the transfer of international management techniques. At the same time, the contribution of foreign capital leads to a greater need for corporate control and integrated management of the risks associated with foreign investors or other foreign activities. Managers and owners need to monitor the impact of foreign capital on the company’s internal organization and organizational culture and subsequent changes. The share of foreign capital in equity can harm a company’s internal environment, which is consistent with the results of our research. When deciding to use foreign capital for business development, it is important to control for the associated external risks (investment, credit, interest rate, and market risks) and for internal consistency and risks arising from the inclusion of other types of capital. The effect of foreign capital puts managers and owners in a difficult position. It is essential to focus on the internal consistency of the company, proper communication within the company, and the maintenance of consistency in the direction and vision of the company. It is recommended that ERM be implemented in nonfinancial SMEs because the level of ERM can transform the negative effect of foreign equity on financial performance into a positive effect through organizational culture (mission dimension). Thus, the study reveals that ERM plays a positive mediating role for SMEs. The research findings provide new information on the level and impact of ERM in the Visegrad Four country. The findings on the use of foreign capital, facilitating the implementation of ERM even at the expense of deterioration of organizational culture—the mission dimension, is new information for owners/managers in SMEs. It is foreign capital that is one of the problem areas in post-communist countries. There is an area for further research outside of Central Europe to compare the role of foreign capital in SMEs. Further opportunities for research were identified by the authors in the area of Organizational Culture and its other dimensions, which were not examined in the study. The mediating variables were selected based on the literature review, but there are still a number of variables that need to be analyzed in more detail in the SME environment. Investigating the differences between family and non-family businesses in SME ERM could also provide interesting results, with the possibility of building on the findings by Glowka et al. (2020). Another opportunity is to conduct qualitative research to identify the reasons that reflect the relatively high percentage of low levels of ERM implementation in SMEs. Quantitative research has shown that ERM has a positive impact on the subjective financial performance of the company. The authors see the biggest challenge in finding out why SMEs have a relatively low adoption of ERM approaches. One limitation of this study could be the study sample, which focuses only on the Czech Republic. However, this study could be interesting for other Central European countries that have experienced similar historical events in the second half of the twentieth century. Another limitation of this research could be the subjective evaluation of the variables. However, to minimize the effects of this limitation, the authors conducted pilot tests and used validated constructs. Objective assessments of the variables within SMEs may not be feasible given the low level of disclosure related to ERM among SMEs. Appendix 1: Description of the manifest variables ERM ERM_1: Is there a chief risk officer in your company, responsible for risk management? 1 – Yes ERM_2: Is there a special department in your company dedicated to risk management? 0 – No ERM_3: Does your company have a written statement of the firm’s risk appetite? ERM_4: Are there official risk management policies and procedures in your company? ERM_5: Do you apply the COSO integrated framework for ERM in your company? ERM_6: Do you apply the ISO 31000 risk management standard in your company? ERM_7: Is risk managed with an integrated analysis and management of all identified corporate risks (e.g., financial, strategic, operational, compliance, and reporting risks)? ERM_8: Do you determine correlations and portfolio risk effects of combined risks? ERM_9: Do you determine quantitative impacts risks may have on key performance indicators? ERM_10: Do you organize workshops in your company where managers discuss exposures to different types of risks and risk management? ERM_11: Does your company create a risk map indicating position of risks the company is exposed to, considering probability of occurrence and significance of identified risk to the business activity? ERM_12: Do you have a risk response plan for all significant events? ERM_13: Do you submit a formal report on risk and risk management to the management board at least annually? ERM_14: Do you monitor key risk indicators aimed at emerging risks (not past performance)? Authors: (Miloš Sprčić et al., 2017).ORGC ORGC_1: Our approach to doing business is very consistent and predictable 1 – Stronly disagree ORGC_2: There is good alignment of goals across levels of this organization 2—Disagree ORGC_3: People from different organizational units still share a common perspective 3—Neutral ORGC_4: It is easy to coordinate projects across functional units in this organization 4—Agree ORGC_5: Working with someone from another part of this organization is like working with someone from a different company 5 – Strongly Agree ORGC_6: When disagreements occur, we work hard to achieve “win–win” solutions ORGC_7: This organization has a strong culture ORGC_8: There is clear agreement about the right way and the wrong way to do things in this organization ORGC_9: It is easy for us to reach consensus, even on difficult issues ORGC_10: We often have trouble reaching agreement on key issues ORGC_11: There is a clear and consistent set of values in this company that governs the way we do business ORGC_12: This company has a characteristic management style and a distinct set of management practices ORGC_13: The managers in this company “practice what they preach.” ORGC_14: This organization has an ethical code that guides our behavior and tells us right from wrong ORGC_15: Ignoring the core values of this organization will get you in trouble ORGM ORGM_1: This organization has a clear mission that gives meaning and direction to our work 1 – Stronly disagree ORGM_2: This organization has a long-term purpose and direction 2—Disagree ORGM_3: The strategic direction of this organization is unclear to me 3—Neutral ORGM_4: This organization has a clear strategy for the future 4—Agree ORGM_5: Our organization’s strategy is leading other firms to change the ways that they compete 5 – Strongly Agree ORGM_6: There is widespread agreement about the goals of this organization ORGM_7: The leaders of this organization set goals that are ambitious, but realistic ORGM_8: The leadership of this organization has “gone on record” about the objectives we are trying to meet ORGM_9: We continuously track our progress against our stated goals ORGM_10: The people in this organization understand what needs to be done for us to succeed in the long run ORGM_11: We have a shared vision of what this organization will be like in the future ORGM_12: The leaders in this organization have a long-term orientation ORGM_13: Short-term thinking often compromises long-term vision ORGM_14: Our vision creates excitement and motivation for our employees ORGM_15: We are able to meet short-term demand without compromising our long-term vision Retrieved from (Denison, 1990).SRMP SRMP_1: Ability to hedge important known risks and uncertainties 1 – Significantly worse SRMP_2: Ability to react to and reduce unforeseen risks 2 – Worse SRMP_3: Ability to exploit new opportunities 3 – Slightly worse 4 – Approximately the same 5 – Slightly better 6 – Better 7 – Significantly better Retrieved from (Sax and Torp, 2015).FP FP_1: Firm´s financial performance compared to competitors 1 – Much worse 2 – Worse 3 – Approximately the same 4 – Better 5 – Much better FP_2: Profitability in the last fiscal year 1 – Extremely unprofitable 2 – Unprofitable 3 – Slightly unprofitable 4 – Approximately the same 5 – Slightly profitable 6 – Profitable 7 – Extremely profitable FP_3: Current liquidity 1 – Very little liquidity 2 – Little liquidity 3 – Medium liquidity 4 – Significant liquidity Retrieved from (Uhlaner et al. 2014). Appendix 2: Initial model including all manifest variables Appendix 3: Discriminant validity, reliability and inner VIF of the final model Discriminant validity (HTMT ratio) FA ERM SRMP FP FC ORGM FS FA ERM 0.19 SRMP 0.086 0.096 FP 0.087 0.159 0.548 FC 0.059 0.438 0.07 0.087 ORGM 0.135 0.265 0.399 0.427 0.169 FS 0.038 0.329 0.061 0.077 0.432 0.135 Source own calculation Reliability Cronbach's Alpha rho_A Composite Reliability Average Variance Extracted (AVE) FA 1.000 1.000 1.000 1.000 ERM 0.898 0.906 0.913 0.431 SRMP 0.845 0.849 0.906 0.763 FP 0.646 0.723 0.799 0.579 FC 1.000 1.000 1.000 1.000 ORGM 0.869 0.900 0.893 0.381 FS 1.000 1.000 1.000 1.000 Source own calculation Inner VIF FA ERM SRMP FP FC ORGM FS FA 1.008 ERM 1.229 SRMP 1.145 FP FC 1.238 1.229 ORGM 1 1.145 FS 1.236 Source own calculation Author contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by JŠ and LS. The first draft of the manuscript was written by JŠ and LS and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Funding This study was funded by Prague University of Economics and Business, Faculty of Business Administration, grant number IGA VŠE F3/16/2021 “The relationship between the level of ERM and the economic performance of companies”. Data availability Data were collected by the private company Ipsos (https://www.ipsos.com/cs-cz) and is not publicly available. Declarations Conflict of interest The authors have no relevant financial or non-financial interests to disclose. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Abbasi T Weigand H The Impact of Digital Financial Services on Firm’s Performance: A Literature Review Papers 2017 1705 10294 1 15 Abor J Foreign direct investment and firm productivity: Evidence from firm-level data Global Business and Economics Review 2010 12 4 267 285 10.1504/GBER.2010.036055 Adomako S Frimpong K Amankwah-Amoah J Donbesuur F Opoku RA Strategic Decision Speed and International Performance: The Roles of Competitive Intensity, Resource Flexibility, and Structural Organicity Management International Review 2021 61 1 27 55 10.1007/s11575-021-00439-w Ai Ping T Muthuveloo R The impact of enterprise risk management on firm performance: Evidence from Malaysia Asian Social Science 2015 11 22 149 159 10.5539/ass.v11n22p149 Ai Ping T Yeang Lee K Muthuveloo R The Impact of Enterprise Risk Management, Strategic Agility, and Quality of Internal Audit Function on Firm Performance International Review of Management and Marketing 2017 7 1 222 229 Astrachan CB Patel VK Wanzenried G A comparative study of CB-SEM and PLS-SEM for theory development in family firm research Journal of Family Business Strategy 2014 5 1 116 128 10.1016/j.jfbs.2013.12.002 Aven T The flaws of the ISO 31000 conceptualisation of risk Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 2017 231 5 467 468 10.1177/1748006X17690672 Baxter R Bedard JC Hoitash R Yezegel A Enterprise Risk Management Program Quality: Determinants, Value Relevance, and the Financial Crisis Contemporary Accounting Research 2013 30 4 1264 1295 10.1111/j.1911-3846.2012.01194.x Beasley M Branson B Pagach D An analysis of the maturity and strategic impact of investments in ERM Journal of Accounting and Public Policy 2015 34 3 219 243 10.1016/j.jaccpubpol.2015.01.001 Berry-Stölzle TR Xu J Enterprise Risk Management and the Cost of Capital Journal of Risk and Insurance 2018 85 1 159 201 10.1111/jori.12152 Bhuiyan F Baird K Munir R The association between organisational culture, CSR practices and organisational performance in an emerging economy Meditari Accountancy Research 2020 28 6 977 1011 10.1108/MEDAR-09-2019-0574 Brustbauer J Enterprise risk management in SMEs: Towards a structural model International Small Business Journal: Researching Entrepreneurship 2014 34 1 70 85 10.1177/0266242614542853 Bui DG Fang Y Lin C-Y The influence of risk culture on firm returns in times of crisis International Review of Economics & Finance 2018 57 291 306 10.1016/j.iref.2018.01.015 Bures, M. 2017. What share of GDP do small and medium-sized enterprises account for? Are they really that important? Finance.cz. Callahan C Soileau J Does Enterprise risk management enhance operating performance? Advances in Accounting 2017 37 June 122 139 10.1016/j.adiac.2017.01.001 Cameron, K. S., and R. E. Quinn. 2011. Diagnosing and Changing Organizational Culture: Based on the Competing Values FrameworkWiley. Chakraborty I Maity P COVID-19 outbreak: Migration, effects on society, global environment and prevention Science of the Total Environment 2020 728 138882 10.1016/j.scitotenv.2020.138882 32335410 COSO-ERM. 2017. Enterprise Risk Management Integrating with Strategy and Performance. Committee of Sponsoring Organizations of the Treadway Commission. COSO. 2019. Welcome to COSO. Committe Spons. Organ. Treadw. Comm. Darmastuti D Sugiarti R Maulana A ERM sophistication, asymmetric information and audit quality International Journal of Innovation, Creativity and Change 2020 10 11 368 391 Denison D Corporate Culture and Organizational Effectiveness 1990 John Wiley & Sons Denison DR Mishra AK Toward a Theory of Organizational Culture and Effectiveness Organization Science 1995 6 2 204 223 10.1287/orsc.6.2.204 Dukeov, I., J. P. Bergman, P. Heilmann, V. Platonov, and V. Jaschenko. 2018. How do a firm’s age and size affect its organizational innovation? Journal of Innovation Management, 6(3):98–133, 10.24840/2183-0606_006-003_0005. Dvorski Lacković I Kurnoga N Miloš Sprčić D Three-factor model of Enterprise Risk Management implementation: Exploratory study of non-financial companies Risk Management 2022 24 101 122 10.1057/S41283-021-00086-3 Farrell M Gallagher R The Valuation Implications of Enterprise Risk Management Maturity Journal of Risk and Insurance 2015 82 3 625 657 10.1111/jori.12035 Farrell M Gallagher R Moderating influences on the ERM maturity-performance relationship Research in International Business and Finance 2019 47 January 616 628 10.1016/j.ribaf.2018.10.005 Florio C Leoni G Enterprise risk management and firm performance: The Italian case British Accounting Review 2017 49 1 56 74 10.1016/j.bar.2016.08.003 Gatzert N Martin M Determinants and value of enterprise risk management: Empirical evidence from the literature Risk Management and Insurance Review 2015 18 1 29 53 10.1111/rmir.12028 Gengatharan R Al Harthi ES Ekhlass Said SS Effect of Firm Size on Risk and Return: Evidences from Sultanate of Oman European Journal of Business and Management 2020 10.7176/ejbm/12-9-08 Gertler M Gilchrist S What Happened: Financial Factors in the Great Recession Journal of Economic Perspectives 2018 32 3 3 30 10.1257/JEP.32.3.3 Glowka G Kallmünzer A Zehrer A Enterprise risk management in small and medium family enterprises: The role of family involvement and CEO tenure International Entrepreneurship and Management Journal 2020 10.1007/s11365-020-00682-x Golshan NM Rasid SZA Determinants of enterprise risk management adoption: An empirical analysis of Malaysian public listed firms World Academy of Science, Engineering and Technology 2012 62 453 460 Gordon GG Industry Determinants of Organizational Culture Academy of Management Review 1991 16 2 396 415 10.5465/amr.1991.4278959 Gordon LA Loeb MP Tseng CY Enterprise risk management and firm performance: A contingency perspective Journal of Accounting and Public Policy 2009 28 4 301 327 10.1016/j.jaccpubpol.2009.06.006 Grace MF Leverty JT Phillips RD Shimpi P The value of investing in enterprise risk management Journal of Risk and Insurance 2015 82 2 289 316 10.1111/jori.12022 Greiner, L. E. 1989. Evolution and Revolution as Organizations Grow; Pp. 373–387. In Readings in Strategic Management. Macmillan Education UK, London 10.1007/978-1-349-20317-8_25. Grondys K Ślusarczyk O Hussain HI Androniceanu A Risk Assessment of the SME Sector Operations during the COVID-19 Pandemic International Journal of Environmental Research and Public Health 2021 18 8 4183 10.3390/ijerph18084183 33920916 Gubik, A. S., and Z. Bartha. 2014. SME Internalisation Index (SMINI) Based on the Sample of the Visegrad Countries. International Entrepreneurship and Corporate Growth in Visegrad Countries, (July):23–40. Hair, J. F., T. M. Hult, C. M. Ringle, and M. Sarstedt. 2017. Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publishing. Han H The Relationship among Corporate Culture, Strategic Orientation, and Financial Performance Cornell Hospitality Quarterly 2012 53 3 207 219 10.1177/1938965512443505 Hanggraeni D Ślusarczyk B Sulung LAK Subroto A The Impact of Internal, External and Enterprise Risk Management on the Performance of Micro Small and Medium Enterprises Sustainability 2019 11 7 2172 10.3390/su11072172 Hannan MT Freeman J Structural Inertia and Organizational Change American Sociological Review 1984 49 2 149 10.2307/2095567 Hatcher, L. 2013. Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results. Lightning Source Inc. Henseler J Dijkstra TK Sarstedt M Ringle CM Diamantopoulos A Straub DW Ketchen DJ Hair JF Hult GTM Calantone RJ Common Beliefs and Reality About PLS Organizational Research Methods 2014 17 2 182 209 10.1177/1094428114526928 Heong YKA Teng YS COSO Enterprise Risk Management: Small-Medium Enterprise Evidence Asia-Pacific Management Accounting Journal 2018 13 2 83 111 Hiebl MRW Duller C Neubauer H Enterprise risk management in family firms: Evidence from Austria and Germany Journal of Risk Finance 2019 20 1 39 58 10.1108/JRF-01-2018-0003 Hoyt RE Liebenberg AP The Value of Enterprise Risk Management Journal of Risk and Insurance 2011 78 4 795 822 10.1111/j.1539-6975.2011.01413.x Hu L Bentler PM Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives Structural Equation Modeling: A Multidisciplinary Journal 1999 6 1 1 55 10.1080/10705519909540118 Hudáková, M., and M. Masár. 2018. The Assessment of Key Business Risks for SMEs in Slovakia and Their Comparison with other EU Countries. Entrepreneurial Business and Economics Review, 6(4):145–160, 10.15678/EBER.2018.060408. Husainia S Saputra J Albra W A study of supply chain manangement of board composition, enterprise risk management, and performance of non and Islamic companies in Indonesia International Journal of Supply Chain Management 2019 8 5 349 357 Jenny F Economic Resilience, Globalization and Market Governance: Facing the COVID-19 Test SSRN Electronic Journal 2020 10.2139/ssrn.3563076 Jenya, B., and M. Sandada. 2017. Enhancing Success of SMES Through Risk Enterprise Management: Evidence From A Developing Country. Pakistan Journal of Applied Economics, 27(2). Jurdi DJ AlGhnaimat SM The Effects of ERM Adoption on European Insurance Firms Performance and Risks Journal of Risk and Financial Management 2021 14 11 554 10.3390/jrfm14110554 Kamboj S Rahman Z Marketing capabilities and firm performance: Literature review and future research agenda International Journal of Productivity and Performance Management 2015 64 8 1041 1067 10.1108/IJPPM-08-2014-0117 Klučka, J., and R. Grünbichler. 2020. Enterprise Risk Management – Approaches Determining Its Application and Relation to Business Performance. Quality Innovation Prosperity, 24(2):51, 10.12776/qip.v24i2.1467. Kommunuri J Narayan A Wheaton M Jandug L Gonuguntla S Firm performance and value effects of enterprise risk management New Zealand Journal of Applied Business Research 2016 14 2 17 28 Kumar P Maiti J Gunasekaran A Impact of quality management systems on firm performance International Journal of Quality & Reliability Management 2018 35 5 1034 1059 10.1108/IJQRM-02-2017-0030 Kurdi, I. A., A. F. Naji, and A. N. Naseef. 2019. Enterprise risk management and performance of financial institutions in Iraq: The mediating effect of information technology quality. Journal of Information Technology Management, 11(4):80–91, 10.22059/JITM.2019.74764. Laisasikorn K Rompho N A study of the relationship between a successful enterprise risk management system, a performance measurement system and the financial performance of Thai listed companies The Journal of Applied Business and Economics 2014 16 2 81 Lu JW Beamish PW SME internationalization and performance: Growth vs. profitability Journal of International Entrepreneurship 2006 4 1 27 48 10.1007/s10843-006-8000-7 Lundqvist SA An Exploratory Study of Enterprise Risk Management Journal of Accounting, Auditing & Finance 2014 29 3 393 429 10.1177/0148558X14535780 Lundqvist SA Why firms implement risk governance - Stepping beyond traditional risk management to enterprise risk management Journal of Accounting and Public Policy 2015 34 5 441 466 10.1016/j.jaccpubpol.2015.05.002 Malik MF Zaman M Buckby S Enterprise risk management and firm performance: Role of the risk committee Journal of Contemporary Accounting and Economics 2020 16 1 100178 10.1016/j.jcae.2019.100178 Marc, M., D. Miloš Sprčić, and M. Mešin Žagar. 2018. Is enterprise risk management a value added activity? E+M Ekonomie a Management, 21(1):68–84, 10.15240/tul/001/2018-1-005. Mardessi SM Ben Arab SD Determinants of ERM implementation: The case of Tunisian companies Journal of Financial Reporting and Accounting 2018 16 3 443 463 10.1108/JFRA-05-2017-0044 Matovu, S. 2017. The influence of the external environment on the design of Management Accounting Systems and Enterprise Risk Management. Master Thesis. Meulbroek LK A Senior Manager’s Guide To Integrated Risk Management Journal of Applied Corporate Finance 2002 14 4 56 70 10.1111/j.1745-6622.2002.tb00449.x Miloš Sprčić D Kožul A Pecina E Managers’ Support – A Key Driver behind Enterprise Risk Management Maturity Zagreb International Review of Economics and Business 2017 20 s1 25 39 10.1515/zireb-2017-0003 Moeller, R. R. 2007. COSO enterprise risk management : understanding the new integrated ERM framework. 367. Wiley. Nasir N Effect of Enterprise Risk Management on Firm Value: Empirical Evidence from Non-Financial Firms in Pakistan International Journal of Financial Management 2018 8 4 15 28 Ogutu J Bennett M Olawoyin R Closing the Gap: Between Traditional and Enterprise Risk Management Systems Professional Safety 2018 63 04 42 47 Osman A Lew CC Developing a framework of institutional risk culture for strategic decision-making Journal of Risk Research 2020 24 9 1072 1085 10.1080/13669877.2020.1801806 Pagach D Wieczorek-Kosmala M The Challenges and Opportunities for ERM Post-COVID-19: Agendas for Future Research Journal of Risk and Financial Management 2020 13 12 323 10.3390/jrfm13120323 Prakash A Potoski M Investing Up: FDI and the Cross-Country Diffusion of ISO 14001 Management Systems International Studies Quarterly 2007 51 3 723 744 10.1111/j.1468-2478.2007.00471.x Quon TK Zéghal D Maingot M Enterprise risk management and business performance during the financial and economic crises Problems and Perspectives in Management 2012 10 3 95 103 Rathore U Khanna S From Slowdown to Lockdown: Effects of the COVID-19 Crisis on Small Firms in India SSRN Electronic Journal 2020 10.2139/ssrn.3615339 Rehman AU Anwar M Mediating role of enterprise risk management practices between business strategy and SME performance Small Enterprise Research 2019 26 2 207 227 10.1080/13215906.2019.1624385 Sax J Torp S Speak up! enhancing risk performance with enterprise risk management, leadership style and employee voice Management Decision 2015 53 7 1452 1468 10.1108/MD-10-2014-0625 Sax J Andersen TJ Making Risk Management Strategic: Integrating Enterprise Risk Management with Strategic Planning European Management Review 2019 16 3 719 740 10.1111/emre.12185 Scott A Balthrop A The consequences of self-reporting biases: Evidence from the crash preventability program Journal of Operations Management 2021 67 5 588 609 10.1002/joom.1149 Schiller F Prpich G Learning to organise risk management in organisations: What future for enterprise risk management? Journal of Risk Research 2014 17 8 999 1017 10.1080/13669877.2013.841725 Silva JR da Silva AF Chan BL Enterprise Risk Management and Firm Value: Evidence from Brazil Emerging Markets Finance and Trade 2019 55 3 687 703 10.1080/1540496X.2018.1460723 Statista. 2021. Europe: number of SMEs. Statista. Syrová L Špička J The Impact of Foreign Capital on the Level of ERM Implementation in Czech SMEs Journal of Risk and Financial Management 2022 15 2 83 10.3390/JRFM15020083 Syrová L Špička J Which factors moderate and mediate the relationship between enterprise risk management and firm performance A meta-analysis and conceptual study European J. of International Management 2022 1 1 1 10.1504/ejim.2022.10044223 Tadevosyanová LŠ Organizational Culture in the Czech Republic and its impact on value creation Ekonomika a Management 2015 2015 3 1 16 Tarko V Understanding post-communist transitions: The relevance of Austrian economics Review of Austrian Economics 2020 33 1–2 163 186 10.1007/s11138-019-00452-1 Thomya W Saenchaiyathon K The effects of organizational culture and enterprise risk management on organizational performance: A conceptual framework International Business Management 2015 9 2 158 163 10.3923/ibm.2015.158.163 Uhlaner, L., L. M. Uhlaner, R. H. Floren, and J. R. Geerlings. Forthcoming. Owner commitment and relational governance in the privately-held firm: An empirical study. 10.1007/s11187-006-9009-y. Virglerova Z Differences in the Concept of Risk Management in V4 Countries International Journal of Entrepreneurial Knowledge 2019 6 2 100 109 10.2478/ijek-2018-0017 Williams LJ Vandenberg RJ Edwards JR Structural Equation Modeling in Management Research: A Guide for Improved Analysis The Academy of Management Annals 2009 3 1 543 604 10.1080/19416520903065683 Wirahadi, A., and M. Pasaribu. 2022. Business Model Innovation: The Role of Enterprise Risk Management and Strategic Agility. 283–289, 10.2991/AEBMR.K.220304.037. Witek-Crabb A Business Growth Versus Organizational Development Reflected in Strategic Management of Polish Small, Medium and Large Enterprises Procedia - Social and Behavioral Sciences 2014 150 66 76 10.1016/J.SBSPRO.2014.09.008 Yakob, S., H.-S. B.A.M, R. Yakob, and N. Raziff. 2019. The Effect of Enterprise Risk Management Practice on SME Performance. The South East Asian Journal of Management, 13(2):151–169, 10.21002/seam.v13i2.11785. Yang S Ishtiaq M Anwar M Enterprise Risk Management Practices and Firm Performance, the Mediating Role of Competitive Advantage and the Moderating Role of Financial Literacy Journal of Risk and Financial Management 2018 11 3 35 10.3390/jrfm11030035 Yazici HJ Significance of organizational culture in perceived project and business performance EMJ - Engineering Management Journal 2011 23 2 20 29 10.1080/10429247.2011.11431892 Zhao X Lynch JG Chen Q Reconsidering Baron and Kenny: Myths and truths about mediation analysis Journal of Consumer Research 2010 37 2 197 206 10.1086/651257
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==== Front J Econ Finan Journal of Economics and Finance 1055-0925 1938-9744 Springer US New York 9609 10.1007/s12197-022-09609-4 Article Volatility and dependence in energy markets Liu Jinan 1 http://orcid.org/0000-0002-4169-7524 Serletis Apostolos [email protected] 2 1 grid.266815.e 0000 0001 0775 5412 Department of Economics, University of Nebraska at Omaha, Omaha, Nebraska USA 2 grid.22072.35 0000 0004 1936 7697 Department of Economics, University of Calgary, Calgary, Alberta T2N 1N4 Canada 12 12 2022 123 7 11 2022 © Academy of Economics and Finance 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. We use a semiparametric GARCH-in-Mean copula model to examine the price evolution and volatility dynamics of crude oil, natural gas, and hydrocarbon gas liquids markets using data from January 2002 to December 2021. We find that uncertainty has a positive and statistically significant effect on the returns of crude oil and natural gas, but has a negative and statistically significant effect on ethane returns. We also find that the Frank copula is the best copula to describe the (bivariate) dependence structures between the crude oil, natural gas, and hydrocarbon gas liquids markets, except for the relationship between ethane and butane where the Clayton copula is the most fitted copula. It suggests that weak lower and upper tail dependence exists between the energy returns, and there is statistically significant lower tail dependence between ethane and butane. In other words, extremely low crude oil prices are associated with low prices of natural gas and hydrocarbon gas liquids, and vice versa. When ethane returns go down, there is excess comovement in the returns of butane. Moreover, the tail dependence is strongest between crude oil and natural gas. Keywords Copula GARCH-in-Mean model Crude oil price Natural gas price Hydrocarbon gas liquids prices JEL Classification C58; F37; G17 ==== Body pmcIntroduction Energy prices have been variable in the past decades. The monthly crude oil price decreased 51% in February 2020, and increased 28% in April 2020. The wide price fluctuations in crude oil have contributed to the increased natural gas and hydrocarbon gas liquids prices and production. In December 2021, the natural gas production in the United States had reached the highest daily growth on record, with 118.8 billion cubic feet per day. Moreover, the United States has become the largest global source of hydrocarbon gas liquids supply and a major hydrocarbon gas liquids exporter. Current elevated levels of domestic oil and gas development have pushed hydrocarbon gas liquids production and price to an all-time high as of 2022. Hydrocarbon gas liquids have not attracted enough attention in academic research. Hydrocarbon gas liquids, which include ethane, propane, butane, isobutane, and natural gasoline, produced in conjunction with natural gas, or as a by-product of crude oil refining, are used as inputs for petrochemical plants, burned for space heat and cooking, and blended into vehicle fuel. In 2020, hydrocarbon gas liquids accounted for about 18% of total petroleum consumption in the United States, and 90% of the total hydrocarbon gas liquids production in the United States is from natural gas processing. Crude oil, natural gas, and hydrocarbon gas liquids markets can be disrupted by extreme geopolitical events that create uncertainty about future supply or demand, which can lead to higher volatility in prices and excess comovements of prices at extreme values. In this paper, we examine the volatility and dependence across hydrocarbon gas liquids, crude oil, and natural gas. In particular, we examine the following questions: what are the price evolution and volatility dynamics in the crude oil, natural gas, and hydrocarbon gas liquids markets? Does the volatility or uncertainty affect the mean of the energy returns? What is the bivariate dependence structure across the crude oil, natural gas, and hydrocarbon gas liquids markets? Is there any extreme value dependence in these markets? Is the dependence symmetric or asymmetric? By answering these questions, we hope to get a better understanding of the comovements of the crude oil, natural gas, and hydrocarbon gas liquids markets and the risks associated with the dependence structure between these markets. Extensive volatility and correlation analyses have been performed in the traditional energy markets. For example, Ewing et al. (2002), Efimova and Serletis (2014), and Serletis and Xu (2016) use multivariate GARCH models to estimate the volatility and time-varying dependence structure in energy markets, including the crude oil, natural gas, coal, and electricity markets. However, the multivariate GARCH model is often based on severe restrictions to guarantee a well-defined covariance matrix. First, it is assumed that the stochastic term follows an elliptical (Gaussian or Student’s t-) distribution with linear dependence. However, energy data are usually non-elliptically distributed. In this regard, Jahan and Serletis (2019) show that crude oil, natural gas, and hydrocarbon gas liquids returns are skewed, leptokurtic, and fat-tailed. Using an elliptical model to estimate non-elliptical data and inference the potential nonlinear dependence based on linear correlations can be very misleading. Moreover, the actual relationship between crude oil, natural gas, and hydrocarbon gas liquids markets is possibly nonlinear and asymmetric, but the multivariate GARCH models can only measure the linear correlations among variables. The linear correlation coefficient does not carry any information on how the markets are related differently in tranquil periods and in volatile periods, and it fails to model the structure of dependence and the tail dependence. For example, crude oil returns appear to be more related to natural gas returns when the energy markets are highly volatile compared to normal times. In this paper, we use copula-based GARCH-in-Mean models to address the drawbacks of standard multivariate GARCH analysis. According to Sklar’s (1973) theorem, any joint distribution function can be decomposed into its marginal distributions and a copula that describes the dependence between the variables. A copula function can be used to connect the univariate distributions of each energy return to restore the joint distribution of energy returns. First, in contrast to restrictions of multivariate GARCH models on the marginal distributions, copulas do not impose any restrictions on the marginal distributions and even allow marginals to be from different distribution families. Second, compared to linear correlation, copulas are a more informative measure of dependence between two (or more) variables, as they can capture the nonlinear dependence of the marginals. Copulas contain information about the joint behavior of the random variables in the tails of the distribution, which allows us to examine the changes in the dependence structure when extreme values and rare events occur. Third, similar to Chen and Fan (2006), we can use GARCH-in-Mean models and copulas to construct flexible multivariate distributions, exhibiting rich patterns of tail behavior, ranging from tail independence to tail dependence, and different types of asymmetry. Thus, the copula-based GARCH-in-Mean model allows for better flexibility in modeling joint distributions than standrad multivariate GARCH models. Copulas have been widely used in the finance literature and have been gradually introduced into the empirical analysis of energy markets. Patton (2006), Rodriguez (2007), and Ning (2010) have used copulas to analyze the dependence structure between financial markets and the foreign exchange market. Wu et al. (2012) and Aloui et al. (2013) use a copula-GARCH approach to study the conditional dependence structure between crude oil prices and U.S. dollar exchange rates. Reboredo (2011) uses copulas to examine the dependence structure between benchmark crude oil prices. Tong et al. (2013) investigate the tail dependence and the asymmetry in the propagation of crises (bubbles) between the crude oil market and the refined petroleum markets based on copula models and find evidence of both positive lower and upper tail dependencies between these markets. In this paper, we investigate the volatility and bivariate dependence between the returns of crude oil, natural gas, and hydrocarbon gas liquids by combining copula functions with GARCH-in-Mean models. We use a GARCH-in-Mean model to study the volatility and price evolution of crude oil, natural gas, and hydrocarbon gas liquids. To estimate the bivariate dependence structure between crude oil, natural gas, and hydrocarbon gas liquids returns, we apply various copulas on the GARCH-in-Mean filtered returns of crude oil, natural gas, and hydrocarbon gas liquids, and select the one with the best goodness of fit based on the Akaike Information Criterion (AIC). We find that volatility has a statistically significant positive effect on crude oil and natural gas returns, but has a statistically significant negative effect on the returns of ethane. We find that the Frank copula is superior to the asymmetric copulas in terms of the description of the bivariate dependence structure between crude oil, natural gas, and hydrocarbon gas liquids returns, suggesting that there is both upper tail and lower tail dependence structure in the energy markets. Clayton copula is the best to capture the dependence structure between ethane and butane. The tail dependence provides a measure of the probability of simultaneous extreme losses. The lower tail dependence and the likelihood of extreme joint losses suggest a higher than normal value-at-risk. The dependence parameter is the highest between crude oil and natural gas. Our contribution to the literature is three-fold. First, we fill the gap in examining the volatility and price evolution of hydrocarbon gas liquids returns. Using the GARCH-in-Mean model, we find that volatility has a statistically significant negative effect on the returns of ethane, but does not have any statistically significant effects on the returns of butane and propane. Second, we use the copula-based models to analyze the bivariate dependence structure of crude oil, natural gas, and hydrocarbon gas liquids returns. The copula-based models can be used to capture the potential asymmetric and tail dependence between crude oil, natural gas, and hydrocarbon gas liquids returns. We test for both the degree and type of their dependence at extreme levels conditionally on the possibility of extreme events such as market crashes. The tail dependence enables us to examine how crude oil, natural gas, and natural gas liquids returns are related to each other during bearish and bullish markets. Third, the combination of GARCH-in-Mean models and copula functions is of particular interest because they capture a richer volatility and dependence structure than the standard multivariate GARCH framework. A copula is able to describe the dependence structure of marginals from different families of distributions. The volatility and price evolution of crude oil, natural gas, and hydrocarbon gas liquids are very different yet might have common extreme variations. The copula-GARCH model enables us to capture some of the essential empirical features of the data, such as the nonlinear dependence, skewness, and fat tails, while allowing each marginal distribution to vary considerably. The rest of the paper is organized as follows. Section 2 presents the data. Section 3 presents the empirical results of univariate volatility analysis of crude oil, natural gas, ethane, propane, and butane returns. Section 4 presents the copula approach to the investigation of (bivariate) nonlinear dependence structures as well as tail dependence between the energy returns. The last section concludes. The data We retrieve the monthly price data of crude oil, natural gas, ethane, propane, and isobutane from Bloomberg and the United States Energy Information Administration. Prices are monthly averages of close-of-day spot prices. The crude oil price is the Brent crude oil price; the natural gas price is the Henry Hub natural gas price; the ethane, propane, and isobutane prices are at Mt. Belvieu non-LST (Lone Star Terminal). Our sample period is from January 2002 to December 2021 with 240 observations. We compute the return series by taking logarithmic first differences of the monthly prices, that is, rt = 100 × (logPt − logPt− 1). The log prices and return series are plotted in Figures 1, 2, 3, 4 and 5, with shaded areas indicating NBER recessions. Figure 6 compares the historical evolution of the log prices of crude oil, natural gas, ethane, propane, and butane over the sample period. Fig. 1 Log crude oil price and its growth rate Fig. 2 Log natural gas price and its growth rate Fig. 3 Log ethane price and its growth rate Fig. 4 Log propane price and its growth rate Fig. 5 Log butane price and its growth rate Fig. 6 Log energy prices As shown in Figure 6, until 2009, United States spot prices for natural gas and hydrocarbon gas liquids tracked the price of crude oil closely. According to the United States Energy Information Administration, in 2021, one-third of the United States energy consumption was from natural gas supply, and the United States is the world’s largest producer of natural gas. Due to the surging demand in China and the rest of Asia, the global demand for liquefied natural gas has hit record highs each year since 2015. Much of that global appetite has been met by the steadily rising exports of liquefied natural gas from the United States, which have reached new records every year since 2016 and are poised to continue in 2022. Hydrocarbon gas liquids prices in the United States followed the crude oil prices closely and were bound by international market dynamics until the 2007-2009 financial crisis. This historical relationship, was based on the general assumption that most fuels are interchangeable, and the United States was a net importer of hydrocarbon gas liquids. Since the 2007-2009 financial crisis, the hydrocarbon gas liquids prices began to move away from crude oil prices. Such a divergence reflected the growth production of hydrocarbon gas liquids in the United States and the switch position of the United States from a net importer to a net exporter. By 2013 and 2014, the continuing increase in the production of propane further depressed the price of propane in the United States. The main consumption of propane in the United States is as a fuel, usually in areas where access to natural gas is limited. Isobutane prices began to fall closer to propane since 2013. The price of ethane delinked from the price of crude oil starting in 2012, and began to follow the price of natural gas closely. Such change is due to the production process of ethane and the lack of alternative markets for ethane, which left natural gas processors with the only option of leaving the ethane as a component of pipeline natural gas and therefore setting ethane prices at the natural gas heating value. The price of ethane started to move away from the link to natural gas prices since late 2017 due to the expansion of ethane export capacity, which allows United States ethane products to reach more distant markets. The ethane consumption in the United States has increased over the past several years due to the lowered cost and increased supply. Ethane is mainly used to produce plastics. Clearly, there are trend comovements among the energy prices during the recessions and booms. During the 2007-2009 financial crisis and the 2020 Covid-19 recession, all the energy prices were crushed. The high volatility in world oil prices and energy prices in the past decade demonstrates the uncertainty in the global markets. Descriptive statistics and distributional characteristics of the log price and return series are reported in Table 1. For the price series, the standard deviation of the ethane price is the highest, followed by crude oil, butane, natural gas, and propane. For the return series, the standard deviation of ethane returns is the highest, followed by natural gas, butane, propane, and crude oil. All the return series are negatively skewed at a statistically significant level, except for ethane. The negative skewness indicates that return series are skewed to the left. With respect to the excess kurtosis statistics, the values of all energy returns are positive, with the most pronounced being the ones for natural gas and crude oil, implying that the distribution of returns has larger, thicker tails than the normal distribution. It indicates that the probability of extreme realizations could be higher than that of a normal distribution. The (Jarque and Bera 1980) test rejects the null hypothesis of normality for all the energy return series. Table 1 Summary statistics Mean Standard deviation Skewness Kurtosis Normality A. Log prices Crude oil 2.364 0.446 − 0.403(0.011) − 0.506(0.115) 9.057(0.011) Natural gas 2.538 0.423 − 0.457(0.004) − 0.178(0.579) 8.674(0.013) Ethane 1.719 0.538 0.232(0.145) − 0.930(0.004) 10.800(0.005) Propane 2.169 0.418 − 0.282(0.076) − 0.765(0.017) 9.028(0.011) Butane 2.350 0.427 − 0.280(0.257) − 0.812(0.011) 7.902(0.019) B. Returns Crude oil 0.006 0.098 − 1.251(0.000) 4.142(0.000) 233.148(0.000) Natural gas 0.006 0.116 − 0.937(0.000) 7.200(0.001) 551.220(0.000) Ethane 0.002 0.130 − 0.197(0.215) 1.267(0.000) 17.529(0.000) Propane 0.005 0.109 − 0.678(0.000) 1.185(0.000) 32.282(0.000) Butane 0.005 0.113 − 0.519(0.001) 2.482(0.000) 72.063(0.000) Monthly data: 2002:01-2021:12 (T = 240). Numbers in parentheses are p-values We also conduct a set of unit root and stationary tests for each of the logarithmic energy prices. Panel A of Table 2 shows that the null hypothesis of the presence of a unit root for all the (log) energy price series cannot be rejected by the Augmented Dickey Fuller (ADF) test (see Dickey and Fuller 1981) nor the Phillips-Perron (PP) test (see Phillips and Perron 1988), suggesting nonstationarity in the price series. The optimal lag length in the ADF test is selected based on the Bayesian information criterion (BIC) with a maximum lag length of 4. Moreover, given that unit root tests have low power against trend stationary alternatives, we also use the KPSS test (see Kwiatkowski et al. 1992) to test the null hypothesis of stationarity around a trend. As shown in panel A of Table 2, the null hypothesis of trend stationarity is rejected at the 1 percent statistical significance level. We thus conclude that none of the log energy price series is stationary. Table 2 Unit root and stationary tests Series ADF PP KPSS Decision A. Log prices Crude oil − 2.968 − 2.675 0.755 I(1) Natural gas − 3.283 − 3.108 0.476 I(1) Ethane − 3.337 − 3.211 0.476 I(1) Propane − 3.336 − 3.069 0.521 I(1) Butane − 3.042 − 2.895 0.675 I(1) B. Returns Crude oil − 10.996 − 10.781 0.054 I(0) Natural gas − 12.223 − 12.162 0.053 I(0) Ethane − 13.204 − 13.218 0.085 I(0) Propane − 11.358 − 11.198 0.119 I(0) Butane − 12.591 − 12.532 0.073 I(0) Monthly data: 2002:01-2022:12 (T = 240). The 1% and 5% critical values are − 4.000 and − 3.430 for the ADF test and the PP test, and 0.216 and 0.146 for the KPSS test We repeat the unit root and stationary tests on the first differences of the logarithms of the energy price series. As shown in panel B of Table 2, the ADF and PP tests reject the null hypotheses of a unit root for all the return series. Moreover, the KPSS test cannot reject the null hypothesis of stationarity for all the return series, suggesting that all the energy return series are stationary. Therefore, the energy price series are integrated of order one, I(1), and the energy return series are integrated of order zero, I(0). Univariate volatility analysis We adopt the GARCH-in-Mean model, developed by Engle (1982) and Bollerslev (1987), to examine the evolution path and volatility of the crude oil, natural gas, ethane, propane, and butane return series. The GARCH-in-Mean model provides a natural and convenient way to model the dynamic trade-off between expected return and risk by including the conditional standard deviation term into the conditional mean equation. The (univariate) GARCH-in-Mean model is commonly used in financial time series analysis, and it allows volatility to directly affect the conditional mean. It is given by 1 yt=ϕ0+∑i=1pϕiyt−i+∑j=1q𝜃j𝜖t−j+ψht+𝜖t 2 ht=ω+α1𝜖t−12+β1ht−1 3 𝜖t=htvtvt∼N(0,1) where yt is the return of the crude oil, natural gas, ethane, propane, and butane prices, respectively. 𝜖t is the shock, and ht is the conditional variance of returns at time t. The standardized innovations, vt, is distributed with E(vt) = 0 and E(vt2)=1. Equation 1 gives the relationship between the expected return and the risks. Equation 2 provides the dynamics of the conditional variance assuming a GARCH(1,1) process. We examine univariate ARMA(1,1)-GARCH(1,1)-in-Mean models for each of the energy return series. As can be seen in panel A of Table 3, the GARCH-in-Mean term is positive and statistically significant in the case of crude oil (0.280 with a p-value 0.000) and natural gas (0.196 with a p-value 0.000), suggesting that the conditional volatility has a positive and statistically significant effect on crude oil and natural gas returns. However, the GARCH-in-Mean term is negative and statistically significant in the case of ethane (− 1.500 with p-value 0.000). The GARCH-in-Mean term is not statistically significant for propane or butane returns. Table 3 Univariate GARCH-in-Mean models Coefficient Crude oil Natural gas Ethane Propane Butane A. Conditional mean equation constant − 0.010 (0.044) 0.000 (0.000) 0.192 (0.000) 0.011 (0.138) − 0.016 (0.000) yt− 1 0.290 (0.000) − 0.063 (0.000) 0.031 (0.663) 0.057 (0.462) 0.025 (0.940) 𝜖t− 1 − 0.042 (0.594) 0.180 (0.000) 0.074 (0.301) 0.234 (0.002) 0.138 (0.679) ht 0.280 (0.000) 0.196 (0.000) − 1.500 (0.000) − 0.003 (0.965) 0.278 (0.630) B. Conditional variance equation constant 0.004 (0.000) 0.000 (0.000) 0.007 (0.000) 0.004 (0.000) 0.008 (0.041) 𝜖t−12 0.573 (0.000) 0.959 (0.000) 0.129 (0.000) 0.303 (0.000) 0.368 (0.124) ht− 1 0.010 (0.870) − 0.019 (0.000) 0.474 (0.000) 0.372 (0.000) 0.023 (0.958) C. Standardized residual diagnostics 𝜖^ mean − 0.107 − 0.150 − 0.000 − 0.045 − 0.055 𝜖^ standard error 0.996 1.006 1.002 1.002 1.001 Jarque − Bera (0.000) (0.000) (0.000) (0.000) (0.000) Q(8) (0.269) (0.022) (0.775) (0.072) (0.781) Q2(10) (0.706) (0.840) (0.419) (0.712) (0.803) AIC − 2.103 − 2.008 − 1.245 − 1.679 − 1.616 Monthly data: 2002:01-2021:12 (T = 240). Numbers in parentheses are p-values Panel B of Table 3 shows the parameter estimates in equation (2). The parameter α1 in front of the ARCH terms in the variance specification is statistically significant for all return series except for Butane (0.573 with a p-value 0.000 for crude oil, 0.959 with a p-value 0.000 for natural gas, 0.129 with a p-value 0.000 for ethane, 0.303 with a p-value 0.000 for propane). The parameter β1 in front of the GARCH term ht− 1 is statistically significant in the case of natural gas (− 0.019 with a p-value of 0.000), ethane (0.474 with a p-value of 0.000), and propane (0.372 with a p-value of 0.000), reflecting the persistence of volatility in natural gas, ethane, and propane returns. Panel C of Table 3 reports diagnostic test statistics based on the standardized residuals, 𝜖t^=𝜖t/ht. The Ljung-Box Q test cannot reject the null hypothesis that the residuals are independently distributed (with p-values of 0.269, 0.022, 0.775, 0.072, and 0.781 for crude oil, natural gas, ethane, propane, and butane, respectively). Also, the McLeod-Li Q2 test cannot reject the null hypothesis that the squared residuals are independently distributed (with p-values of 0.706, 0.840, 0.419, 0.712, and 0.803 for crude oil, natural gas, ethane, propane, and butane, respectively). Both diagnostic tests suggest that the standardized residuals are serially uncorrelated and are approximately i.i.d. However, the Jarque-Bera test rejects the null hypothesis that the residuals are normally distributed. Overall, the diagnostic tests show that the GARCH-in-Mean model can capture the nonlinearity in the conditional variance and is correctly specified for each of the five return series. Correlation and dependence analysis Copulas are a powerful tool for modelling nonlinear dependence between random variables, and in particular dependence at extremely values and in the tails of the distributions. Two measures of tail dependence related to copulas, known as the upper and the lower tail dependence coefficients, are particularly helpful for measuring the tendency of random variables to move together—Trivedi and Zimmer (2007). Upper tail dependence, λU, and lower tail dependence, λL, are defined as λU=lima→1Pr[𝜖2t>F2−1(a)|𝜖1t>F1−1(a)]λL=lima→0Pr[𝜖2t≤F2−1(a)|𝜖1t≤F1−1(a)]. where F− 1(q) = inf{x ∈ R : F(x) ≥ a}, that is, the inverse of the cumulative probability distribution function for a. Tail dependence measures the probability that one event is extreme conditional on another extreme event. When λL = λU, there is symmetric tail dependence. We can interpret λUc1>λUc2 as copula c1 is more concordant than copula c2. According to Sklar’s Theorem (1973), for continuous multivariate distributions, the modeling of the univariate marginals and the dependence structure can be separated, and the multivariate structure can be represented by a copula. Copulas can be used to express a multivariate distribution in terms of its marginal distributions—see Joe (2014, p. 7). In this paper, we consider a number of copulas which are widely used in the literature. They are the Gaussian copula, the Clayton (1978) copula, the Gumbel (1960) copula, and the Frank (1979) copula. The Gaussian copula The copula of 𝜖 t = (𝜖1t,𝜖2t) is assumed to be the normal copula with unknown correlation matrix Σ. Let Ψ denote the univariate standard normal distribution and ΨΣ,2 the bivariate normal distribution with correlation matrix Σ. Then the bivariate normal copula with correlation matrix Σ is Cu;Σ=ΨΣ,2(Ψ−1(u1),Ψ−1(u2)). More explicitly, C(u1,u2;α)=∫−∞Ψ−1(u1)∫−∞Ψ−1(u2)12π1−α2exp−𝜖1t2−2α𝜖1t𝜖2t+𝜖2t22(1−α2)d𝜖1td𝜖2t where u = (u1,u2), and u1 = Ψ(𝜖1t) and u2 = Ψ(𝜖2t) are the cumulative distribution functions of 𝜖1t and 𝜖2t, respectively. The copula dependence parameter, α ∈ (− 1,1), is the collection of all the unknown correlation coefficients in Σ. If α≠ 0, then the normal copula generates joint symmetric dependence, but no tail dependence. The Clayton copula For 0<α<∞, the Clayton copula (1978) can capture the lower tail dependence. The Clayton copula takes the form: C(u1,u2,α)=(u1−α+u2−α−1)−1/α. The density of the Clayton copula is c(u1,u2;α)=(1+α)(u1−α+u2−α−1)−1α−2(u1u2)α+1. The lower tail dependence can be calculated as λL = 2− 1/α. The Gumbel copula For 1≤α<∞, the Gumbel (1960) copula takes the form: C(u1,u2;α)=exp−[(−lnu1)α+(−lnu2)α]1/α. The density of the Gumbel copula is c(u1,u2;α)=C(u1,u2;α)(lnu1lnu2)α−1{[(−lnu1)α+(−lnu2)α]1/α+α−1}u1u2[(−lnu1)α+(−lnu2)α]2−1/α. The Gumbel copula can capture positive upper tail dependence, but it cannot capture neither negative dependence nor lower tail dependence. The upper tail dependence can be calculated as λU = 2 − 21/α. The Frank copula Frank copula captures the symmetric dependence. For −∞<α<∞, the CDF of the Frank (1979) copula takes the form: C(u1,u2;α)=−α−1ln1−e−α−(1−e−αu1)(1−e−αu2)1−e−α. The density is c(u1,u2;α)=α(1−e−α)e−α(u1+u2)[1−e−α−(1−e−αu1)(1−e−αu2)]2 where the dependence parameter α captures the symmetric dependence. Copula estimation In this paper, we estimate the copula model using the two-stage semiparametric procedure similar to that described in Chen and Fan (2006). In particular, having estimated, for each energy returns series, the univariate GARCH-in-Mean model using quasi-maximum likelihood estimation, we estimate Fj, j = 1,2, using the empirical cumulative distribution functions of the residuals, 𝜖jt(𝜃 )t=1n 4 Fj(x)=1n∑t=1n1𝜖jt𝜃≤x,j=1,2 where n is the number of observations. As pointed out in Chen and Fan (2006), since the estimation of the marginals is nonparametric, our copula estimation is robust and free of specification errors. Note that the dependence captured by a copula is invariant with respect to increasing and continuous transformations of the marginal distributions. The bivariate copula dependence parameter α is estimated by α^=argmax1n∑t=1nlncF1(𝜖1t),F2(𝜖2t);α and α^ is obtained by solving the score equations, ∂Lc/∂α = 0. The equation is nonlinear in general, and standard quasi-Newton iterative algorithms are employed. One advantage of the two-step estimation approach compared to the fully parametric approach is that the dependence statistics of the two-step estimated parameters are not affected by the models of the conditional mean and variance. In sum, our semiparametric GARCH-in-Mean copula model specifies the conditional mean and conditional variance parametrically, but specifies the distribution of the marginal (standardized) innovations semiparametrically. A parametric copula is evaluated at the nonparametric univariate marginals. The copula function captures the concurrent dependence between the components of the multivariate innovation. Thus, a semiparametric GARCH-in-Mean copula model is very flexible in capturing a wide range of nonlinear, asymmetric dependence structures and the marginal behavior of multivariate time series. Dependence analysis using Copulas Conditional on the marginal specifications, we estimate copula dependence structures for each pair of energy returns. We estimate the empirical distribution of the marginals based on Eq. 4. Table 4 summarizes the results of the linear and rank correlation coefficients for energy returns. As Poon et al. (2004) notes, the conventional dependence measure, which is the linear correlation calculated as the average of deviations from the mean, assumes a linear relationship of the variables which follow a joint Gaussian distribution. The risk from joint extreme events could be underestimated. Moreover, it cannot distinguish between positive and negative returns, neither the large nor small values. Table 4 Bivariate dependence between crude oil, natural gas, ethane and natural gas liquids Overall Non-recession Recession Correlation Kendall’s τ Spearman’s ρ Correlation Kendall’s τ Spearman’s ρ Correlation Kendall’s τ Spearman’s ρ Crude oil-Natural gas 0.826 0.664 0.827 0.769 0.642 0.809 0.976 0.829 0.921 Crude oil-Ethane 0.509 0.347 0.497 0.435 0.321 0.465 0.735 0.543 0.694 Crude oil-Propane 0.669 0.459 0.632 0.629 0.435 0.604 0.822 0.676 0.810 Crude oil-Butane 0.669 0.459 0.632 0.629 0.435 0.604 0.822 0.676 0.810 Natural gas-Ethane 0.521 0.397 0.550 0.457 0.376 0.523 0.711 0.581 0.718 Natural gas-Butane 0.657 0.464 0.632 0.593 0.430 0.594 0.805 0.771 0.923 Natural gas-Propane 0.643 0.509 0.677 0.600 0.484 0.650 0.805 0.714 0.853 Ethane-Propane 0.681 0.493 0.663 0.643 0.477 0.642 0.837 0.619 0.813 Ethane-Butane 0.574 0.401 0.559 0.527 0.369 0.519 0.733 0.619 0.783 Propane-Butane 0.762 0.556 0.731 0.728 0.532 0.709 0.899 0.733 0.882 Monthly data: 2002:01-2021:12 (T = 240) Alternatively, both Kendall’s τ and Spearman’s ρ statistics, which use the ranking of the data instead of the actual values of the data, can describe the nonlinear tail dependence structure. Specifically, Kendall’s τ is as follows: ρτ(X,Y)=Pr[(X1−X2)(Y1−Y2)>0]−Pr[(X1−X2)(Y1−Y2)<0]. Spearman’s ρ is as follows: ρS(X,Y)=ρ(F1(X),F2(Y)) where X and Y are two random variables and F1 and F2 are the corresponding distribution functions. The positive Kendall’s τ and Spearman’s ρ statistics in Table 4 indicate a positive relationship for all pairs of energy returns during the whole sample period as well as during the recessions. Moreover, the rank correlations are stronger during the recessions, indicating stronger comovements during economic contractions. The positive and high rank correlation values indicate that energy prices move together in the same direction during economic downturns. The highest Kendall’s τ value and Spearman’s ρ values are for the crude oil-natural gas pair, indicating that the probability of concordance in crude oil and natural gas price movements is significantly higher than the probability of discordance. The two measures of dependence are consistent with each other. To explore the dependence structure in energy returns and the choice of the appropriate copula to use, we scatter plot all the pairs of 𝜖it and 𝜖jt (i≠j) in Figures 7, 8, 9, 10, 11, 12, 13, 14, 15 and 16. In general, the dots are mainly clustered in the center for all pairs. Moreover, it seems the dependence structures at the tails are symmetric. In other words, we do not observe the clustering of the dots in one tail obviously more sizeable than the clustering of the dots in the other tail in the scatter plots of all pairs. Fig. 7 Scatter plot of crude oil and natural gas Fig. 8 Scatter plot of crude oil and ethane Fig. 9 Scatter plot of crude oil and propane Fig. 10 Scatter plot of crude oil and butane Fig. 11 Scatter plot of natural gas and ethane Fig. 12 Scatter plot of natural gas and propane Fig. 13 Scatter plot of natural gas and butane Fig. 14 Scatter plot of ethane and propane Fig. 15 Scatter plot of ethane and butane Fig. 16 Scatter plot of propane and butane We consider the four copula functions discussed in Section 4 — the Gaussian, Clayton, Gumbel, and Frank copulas. The estimates of the copula parameters are presented in Table 5. The copula parameters for all the pairs are highly statistically significant. They suggest that there is considerable bivariate dependence between the crude oil, natural gas, and hydrocarbon gas liquids markets over the sample period. The AIC values of the copula models are summarized in Table 6. The AIC clearly selects the Frank copula for all cases except for the pair of ethane and butane. Notice that the Frank copula is able to capture the symmetric lower and upper tail dependence. The Frank copula suggests that all of the energy return pairs we study exhibit weakly positive and symmetric upper tail and lower tail dependence. The contagion effect intensity is different across the energy markets, with the highest between crude oil and natural gas markets. In the hydrocarbon gas liquids market, the dependence parameter between butane and propane is the highest among all the pairs, suggesting that extreme outcomes in the propane market are easier to extend to the butane market, and vice versa. Table 5 Dependence parameter estimates of different copula models α^ Pair Gaussian Gumbel Clayton Frank Crude oil-Natural gas 0.814 (0.000) 1.778 (0.000) 2.400 (0.000) 8.611(0.000) Crude oil-Ethane 0.486 (0.000) 1.203 (0.000) 0.731 (0.000) 3.245 (0.000) Crude oil-Propane 0.610 (0.000) 1.320 (0.000) 1.072 (0.000) 4.607 (0.000) Crude oil-Butane 0.598 (0.000) 1.325 (0.000) 1.075 (0.000) 4.457 (0.000) Natural gas-Ethane 0.519 (0.000) 1.225 (0.000) 0.792 (0.000) 3.686 (0.000) Natural gas-Propane 0.654 (0.000) 1.362 (0.000) 1.201 (0.000) 5.318 (0.000) Natural gas-Butane 0.608 (0.000) 1.344 (0.000) 1.115 (0.000) 4.572 (0.000) Ethane-Propane 0.635 (0.000) 1.399 (0.000) 1.287 (0.000) 5.045 (0.000) Ethane-Butane 0.575 (0.000) 1.296 (0.000) 0.976(0.000) 3.865 (0.000) Propane-Butane 0.716 (0.000) 1.502 (0.000) 1.586 (0.000) 6.148(0.000) Monthly data: 2002:01-2021:12 (T = 240). Numbers in parentheses are p-values. Numbers in bold font are corresponding to the lowest AIC values Table 6 AIC values of different copula functions AIC Pair Gaussian Gumbel Clayton Frank Crude oil-Natural gas 4.537 2.101 − 1.011 −1.048 Crude oil-Ethane 5.348 2.784 − 0.210 −0.242 Crude oil-Propane 5.159 2.588 − 0.388 −0.439 Crude oil-Butane 5.188 2.583 − 0.391 −0.422 Natural gas-Ethane 5.305 2.762 − 0.233 −0.302 Natural gas-Propane 5.068 2.546 − 0.440 −0.549 Natural gas-Butane 5.167 2.563 − 0.407 −0.433 Ethane-Propane 5.093 2.477 − 0.492 −0.502 Ethane-Butane 5.217 2.627 −0.334 − 0.326 Propane-Butane 4.896 2.372 − 0.626 −0.680 Monthly data: 2002:01-2021:12 (T = 240). Numbers in bold font are the minimums in each row The statistically significant Frank copula parameter estimate indicates that in times of rare events, such as market crushes and large changes in energy market returns, as one energy return tends to reach its lower/upper limit, there is a high chance that the other energy return will be close to its lower/upper limit too. The existence of left (right) tail dependence implies a much higher downside (upside) risk in crude oil market investments than in the case of no-tail dependence. The high likelihood of extreme joint extreme values in the hydrocarbon gas liquids markets implies a higher value-at-risk than that of a joint normal distribution; as discussed in Poon et al. (2004), tail dependence measures the systematic risk in times of extreme market events. We also explore the possible asymmetric tail dependence between returns of crude oil, natural gas, and hydrocarbon gas liquids using Clayton copula and Gumbel copula. Clayton copula can capture the lower tail dependence, and Gumbel copula can capture the upper tail dependence. Table 6 shows that Frank copula has the lowest AIC values for all pairs except for ethane and butane. There is a theoretical literature on comovements of the energy markets. In general, the contagious movements can be explained by fear spillover, as in the financial markets, or by real links including production and trading. It has been argued, for example, that correlations between financial markets increase during market downturns as a consequence of investors facing greater uncertainty about the state of the economy. Asymmetric responses of agents to energy prices are also a possible cause of asymmetric dependence. Details on theoretical discussions of the comovements in the energy markets are beyond the scope of this paper. Conclusion and policy implications Frequent extreme events, such as financial crises, natural disasters, and global pandemics, suggest that the volatility and tail dependence in the crude oil, natural gas, and hydrocarbon gas liquids markets could remain an important feature in the energy markets landscape. This paper investigates the volatility and dependence structure in the crude oil, natural gas, and hydrocarbon gas liquids markets using copula GARCH-in-Mean models and monthly data over the period from January 2002 to December 2021. We first investigate the volatility of each energy return using ARMA GARCH-in-Mean models. The ARMA GARCH-in-Mean models show that volatility has a statistically significant positive effect on the returns of crude oil and natural gas, but a statistically significant negative effect on the returns of ethane. There is no statistically significant effect on the returns of propane and butane. The rank correlations show that the dependence among these markets increases during economic contractions indicating the potential contagious movements in the energy markets. The lack of theoretical evidence on the dependence structure in the energy markets, and the observation of asymmetric comovements in these markets, motivate us to use a flexible dependence structure specification. Four copula models are used to examine the dependence of the marginals and the goodness of fit of different copulas is compared based on the AIC. By implementing the copula approach, we are able to capture the nonlinear, asymmetric tail dependence across the energy markets while allowing different univariate distributions for each energy market return. We find that the dependence intensity is different across the crude oil, natural gas, and hydrocarbon gas liquids markets. The Frank copula is the best copula to describe the bivariate dependence in all pairs of crude oil, natural gas, and hydrocarbon gas liquids returns, except for the pair of ethane and butane. It suggests that there is symmetric positive tail dependence for all of the considered pairs. The contagion effect is strongest between crude oil and natural gas. Within the hydrocarbon gas liquids markets, the dependence is strongest between propane and butane. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Aloui R Ben A Safouane M Nguyen DK Conditional dependence structure between oil prices and exchange rates: A copula-GARCH approach J Int Money Financ 2013 32 C 719 738 10.1016/j.jimonfin.2012.06.006 Bollerslev T A conditionally heteroskedastic time series model for speculative prices and rates of return Rev Econ Stat 1987 69 3 542 547 10.2307/1925546 Chen X Fan Y Estimation and model selection of semiparametric copula-based multivariate dynamic models under copula misspecification J Econ 2006 135 125 154 10.1016/j.jeconom.2005.07.027 Clayton DG A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence Biometrika 1978 65 141 151 10.1093/biomet/65.1.141 Dickey D Fuller W Likelihood ratio statistics for autoregressive time series with a unit root Econometrica 1981 49 4 1057 72 10.2307/1912517 Efimova O Serletis A Energy markets volatility modelling using GARCH Energy Econ 2014 43 264 273 10.1016/j.eneco.2014.02.018 Engle R Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation Econometrica 1982 50 4 987 1007 10.2307/1912773 Ewing BT Malikb F Ozfidanc O Volatility transmission in the oil and natural gas markets Energy Econ 2002 24 525 538 10.1016/S0140-9883(02)00060-9 Frank MJ On the simultaneous associativity of F(x,y) and x + y − F(x,y) Aequationes Math 1979 19 194 226 10.1007/BF02189866 Gumbel EJ Distributions des valeurs extremes en plusieurs dimensions Publications de lâ, Institute de Statistque de lâ Universite de Paris 1960 9 171 173 Jahan S Serletis A Business cycles and hydrocarbon gas liquids prices J Econ Asymmetries 2019 19 C 1 1 Jarque CM Bera AK Efficient tests for normality, homoscedasticity, and serial independence of regression residuals Econ Lett 1980 6 255 259 10.1016/0165-1765(80)90024-5 Joe H. (2014) Dependence modeling with copulas. Chapman and Hall Kwiatkowski D Phillips PCB Schmidt P Shin Y Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? J Econ 1992 54 159 178 10.1016/0304-4076(92)90104-Y Ning C Dependence structure between the equity market and the foreign exchange market: a copula approach J Int Money Financ 2010 29 5 743 759 10.1016/j.jimonfin.2009.12.002 Patton AJ Modelling asymmetric exchange rate dependence Int Econ Rev 2006 47 527 556 10.1111/j.1468-2354.2006.00387.x Phillips PCB Perron P Testing for a Unit Root in Time Series Regression Biometrika 1988 75 2 335 346 10.1093/biomet/75.2.335 Poon S Rockinger M Tawn J Extreme value dependence in financial markets: diagnostics, models, and financial implications Rev Financ Stud 2004 17 2 581 610 10.1093/rfs/hhg058 Reboredo J How do crude oil prices co-move?: a copula approach Energy Econ 2011 33 5 948 95 10.1016/j.eneco.2011.04.006 Rodriguez JC (2007) Measuring financial contagion: a copula approach. J Empir Finance, 14(3) Serletis A Xu L Volatility and a century of energy markets dynamics Energy Econ 2016 55 C 1 9 10.1016/j.eneco.2016.01.007 Sklar A Random variables, joint distributions, and copulas Kybernetica 1973 9 449 460 Tong BI Wu C Zhou C Modeling the co-movements between crude oil and refined petroleum markets Energy Econo 2013 40 C 882 897 10.1016/j.eneco.2013.10.008 Trivedi P Zimmer D Copula modeling: an introduction for practitioners Found Trends Econom 2007 1 1 1 111 10.1561/0800000005 Wu C Chung H Chang Y The economic value of co-movement between oil price and exchange rate using copula-based GARCH models Energy Econ 2012 34 1 270 282 10.1016/j.eneco.2011.07.007
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==== Front J Hepatol J Hepatol Journal of Hepatology 0168-8278 1600-0641 European Association for the Study of the Liver. Published by Elsevier B.V. S0168-8278(22)03319-0 10.1016/j.jhep.2022.11.024 Letter to the Editor More efforts to explore the association between cirrhosis and COVID-19 mortality, and the association between NAFLD and severe COVID-19 Li Zheng MD, PhD 12† Hu Yue MSN 3† Li Qiang PhD 12∗ 1 Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, China 2 Lanzhou Heavy Ion Hospital, Lanzhou, China 3 Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China ∗ Corresponding author. Institute of Modern Physics, Chinese Academy of Sciences, 509 Nanchang Road, Lanzhou 730000, China. . † Contributed equally as co-first authors. 9 12 2022 9 12 2022 7 11 2022 23 11 2022 © 2022 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved. 2022 European Association for the Study of the Liver Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Keywords Coronavirus disease 2019 Liver cirrhosis Non-alcoholic fatty liver disease Meta-analysis Letter ==== Body pmcTo the Editor: Financial support None. Conflict of interest The authors declare no conflicts of interest. Authors' contributions Conception and design, data acquisition, analysis, and interpretation: Zheng Li, Yue Hu, and Qiang Li. Zheng Li and Yue Hu wrote the initial draft. Qiang Li revised the manuscript. All authors reviewed and approved the final manuscript. Data availability statement The data that support the findings of this study are all included in this article and the supplementary material. With great interest, we contrastively read the two meta-analyses by Wang et al. 1 , 2 published in the Journal of Hepatology in September 2022 and October 2022, respectively. The authors conducted two congeneric meta-analyses to investigate the association between cirrhosis and COVID-19 mortality,1 and the association between NAFLD and severe COVID-19,2 respectively. One meta-analysis is consistent with the findings of the study by Marjot et al.,1 , 3 while the other meta-analysis is contrary to the findings of the study by Marjot et al..2 , 4 Therefore, the methodology quality of the meta-analysis should be further discussion. The work by Wang et al. 1 , 2 is significant to settle the controversies in the novel subjects noted in the EASL position paper by Marjot et al. 5 because of the advantages of meta-analysis.6 , 7 However, some methodological flaws in the two meta-analyses1 , 2 should be noted, especially for the meta-analysis contrary to the results of the study by Marjot et al..2 , 4 The comparative analysis of the two meta-analyses1 , 2 indicated that the inherent deficiencies deviating from methodological norms6 , 7 would result in the same potential biases, until these issues could be taken seriously. Addressing these deficiencies is necessary to avoid the general queries by the readers and promote wide citations of the article. First, although the authors stated that their meta-analyses were performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines in the second paragraph, there is no statement regarding protocol and registration (item 5 of PRISMA) throughout both of the two articles.1 , 2 , 7 The protocol registration is a necessary reporting item for meta-analysis according to the PRISMA statement because the prospective registration could promote transparency and minimize the potential of bias.6 , 7 Second, the subject heading (e.g. Medical Subject Headings (MeSH)) is a necessary approach to improve both sensitivity and precision of the search results (Table 1 ).6 A model of search strategy including the MeSH approach in PubMed is exhibited in Table 1. However, the authors used free-text only in their search strategy displayed in the second paragraph of each meta-analysis.1 , 2 In fact, some eligible and crucial studies were missed for the meta-analysis (such as the study by Bajaj et al. published in Gut),8 , 9 which has already resulted in a significant bias (Supplementary material).6 , 7 , 10 Furthermore, although the authors reported the test of publication bias in the fourth paragraph,1 , 2 the results for detecting publication bias are inaccurate and invalid because of the incomplete data by missing eligible included studies.6 , 8 , 9 Table 1 A model of search strategy including the MeSH approach in PubMed. Step The detailed search terms, approach and logical calculus Category #1 (a) The search for the first meta-analysis (https://doi.org/10.1016/j.jhep.2022.09.015:) "Liver Cirrhosis"[Mesh] MeSH search (b) The search for the second meta-analysis (https://doi.org/10.1016/j.jhep.2022.10.009:) "Non-alcoholic Fatty Liver Disease"[Mesh] #2 (a) The search for the first meta-analysis (https://doi.org/10.1016/j.jhep.2022.09.015:) cirrhosis[All Fields] OR “liver fibrosis”[All Fields] OR “Hepatic fibrosis”[All Fields] Free-text search (b) The search for the second meta-analysis (https://doi.org/10.1016/j.jhep.2022.10.009:) “non-alcoholic fatty liver disease”[All Fields] OR NAFLD[All Fields] OR “metabolic associated fatty liver disease”[All Fields] OR MAFLD[All Fields] OR “Nonalcoholic Steatohepatitis”[All Fields] OR “Nonalcoholic Steatohepatitides”[All Fields] #3 #1 OR #2 Logical OR #4 "COVID-19"[Mesh] OR "SARS-CoV-2"[Mesh] MeSH search #5 “severe acute respiratory syndrome coronavirus 2”[Title/Abstract] OR SARS-CoV-2[Title/Abstract] OR “coronavirus disease 2019”[Title/Abstract] OR COVID-19[Title/Abstract] OR “2019 novel coronavirus”[Title/Abstract] OR 2019-nCoV[Title/Abstract] Free-text search #6 #4 OR #5 Logical OR #7 (a) The search for the first meta-analysis (https://doi.org/10.1016/j.jhep.2022.09.015:) "Mortality"[Mesh] OR "Survival Analysis"[Mesh] OR "Survival Rate"[Mesh] MeSH search #8 (a) The search for the first meta-analysis (https://doi.org/10.1016/j.jhep.2022.09.015:) mortality[All Fields] OR death[All Fields] OR dead[All Fields] OR survival[All Fields] Free-text search #9 #7 OR #8 Logical OR #10 #3 AND #6 AND #9 (a, Cirrhosis); #3 AND #6 (b, NAFLD) Logical AND MeSH, medical subject headings; NAFLD, non-alcoholic fatty liver disease; MAFLD, metabolic associated fatty liver disease. Third, the seventeenth item (study selection) and the eighteenth item (study characteristics) of the PRISMA statement require the meta-analysis to present a detailed flow diagram of the studies selection, characteristics (such as sample size, PICOS, follow-up period) and citations of each included study.7 However, all of these necessary items could not be found in each meta-analysis.1 , 2 , 7 The authors should present these items in the supplementary material. At least, the included studies for meta-analysis should be listed in the form of references in the supplementary material because it is difficult for the readers to identify the included studies just by the author names in Figure 1 in the two articles.1 , 2 Fourth, the risk of bias in individual studies (the items 12 and 19 of the PRISMA statement) is necessary for the meta-analysis reporting.7 However, there is no corresponding analysis in each meta-analysis.1 , 2 , 7 The authors should present detailed assessment data for within-study biases in the supplementary material. And a sensitivity analysis should be conducted based on the identified studies at lower risk of bias to test the robustness and reliability of the meta-analysis findings.6 , 7 Fifth, the authors stated that “We included 29 articles including data on 6,872,587 individuals with COVID-19.”, and “22,056 cases” in the fourth paragraph.1 , 2 Actually, the real number of eligibility for the final meta-analysis is more valuable than the rough sampled population.6 , 10 Therefore, the authors should specify whether the huge number “6,872,587” and “22,056” (especially for “6,872,587”) are the total sample sizes for the actual meta-analyses, and list the individual sample size (involved in the meta-analysis) of each included study.6 , 10 Sixth, the authors should specify which effect measure was chosen for data synthesized calculation in one meta-analysis1 (https://doi.org/10.1016/j.jhep.2022.09.015) according to the item 13 (summary measures) of the PRISMA statement, just like their reporting of odds ratio (OR) in the other meta-analysis.1 , 2 , 7 We congratulate Wang et al. for their breakthrough in the association between cirrhosis and COVID-19 mortality,1 and the association between NAFLD and severe COVID-19.2 Meanwhile, it is necessary to address the aforementioned deficiencies to provide more convincing evidence. As a key remediation, we have listed all the references for the included studies in our Supplementary material. Appendix A Supplementary data The following is/are the supplementary data to this article: Acknowledgements The authors would like to thank Jinyi Lang (Sichuan Cancer Hospital & Institute, School of Medicine, University of Electronic Science and Technology of China), Xiaohu Wang, Qiuning Zhang, Hongtao Luo and Ruifeng Liu (Institute of Modern Physics, Chinese Academy of Sciences, and Lanzhou Heavy Ion Hospital) for their valuable help in data collection and analysis. Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.jhep.2022.11.024. ==== Refs References Author names in bold designate shared co-first authorship 1 Wang Y. Hu M.K. Yang H.Y. Cirrhosis is an independent predictor for COVID-19 mortality: A meta-analysis of confounding cofactors-controlled data J Hepatol 2022 10.1016/j.jhep.2022.09.015 2 Wang Y. Wang Y.D. Duan G.C. Yang H.Y. NAFLD was independently associated with severe COVID-19 among younger patients rather than older patients: A meta-analysis J Hepatol 2022 10.1016/j.jhep.2022.10.009 3 Marjot T. Moon A.M. Cook J.A. Abd-Elsalam S. Aloman C. Armstrong M.J. Outcomes following SARS-CoV-2 infection in patients with chronic liver disease: An international registry study J Hepatol 74 3 2021 567 577 33035628 4 Marjot T. Buescher G. Sebode M. Barnes E. ASth Barritt Armstrong M.J. SARS-CoV-2 infection in patients with autoimmune hepatitis J Hepatol 74 6 2021 1335 1343 33508378 5 Marjot T. Eberhardt C.S. Boettler T. Belli L.S. Berenguer M. Buti M. Impact of COVID-19 on the liver and on the care of patients with chronic liver disease, hepatobiliary cancer, and liver transplantation: An updated EASL position paper J Hepatol 77 4 2022 1161 1197 35868584 6 Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.3 (updated February 2022). Cochrane, 2022. Available from www.training.cochrane.org/handbook. 7 Moher D. Liberati A. Tetzlaff J. Altman D.G. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement Bmj 339 2009 b2535 19622551 8 Bajaj J.S. Garcia-Tsao G. Biggins S.W. Kamath P.S. Wong F. McGeorge S. Comparison of mortality risk in patients with cirrhosis and COVID-19 compared with patients with cirrhosis alone and COVID-19 alone: multicentre matched cohort Gut 70 3 2021 531 536 32660964 9 Chen V.L. Hawa F. Berinstein J.A. Reddy C.A. Kassab I. Platt K.D. Hepatic Steatosis Is Associated with Increased Disease Severity and Liver Injury in Coronavirus Disease-19 Dig Dis Sci 66 9 2021 3192 3198 32980956 10 Guyatt G.H. Oxman A.D. Kunz R. Brozek J. Alonso-Coello P. Rind D. GRADE guidelines 6. Rating the quality of evidence--imprecision J Clin Epidemiol 64 12 2011 1283 1293 21839614
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==== Front Adv Radiat Oncol Adv Radiat Oncol Advances in Radiation Oncology 2452-1094 The Author(s). Published by Elsevier Inc. on behalf of American Society for Radiation Oncology. S2452-1094(22)00031-8 10.1016/j.adro.2022.100924 100924 Scientific Article Experience of Telemedicine Visits in Radiation Oncology During the COVID-19 Pandemic: A US National Survey and Lessons Learned for Incorporating Telemedicine Post-COVID-19 Ma Ting Martin MD, PhD a Parikh Neil R. MD, MBA b Philipson Rebecca G. MD c van Dams Ritchell MD d Chang Eric M. MD e Hegde John V. MD a Kishan Amar U. MD a Kaprealian Tania B. MD, MBA a Steinberg Michael L. MD a Raldow Ann C. MD, MPH a⁎ a Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, California b San Antonio Cancer Center, San Antonio, Texas c Department of Radiation Oncology, Torrance Memorial Medical Center, Torrance, California d Department of Radiation Oncology, Dana Farber Cancer Institute/Brigham and Women's Hospital, Boston, Massachusetts e Department of Radiation Oncology, Oregon Health and Science University, Portland, Oregon ⁎ orresponding author: Ann C. Raldow, MD, MPH 12 12 2022 12 12 2022 1009247 10 2021 6 1 2022 © 2022 The Author(s) 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Purpose We sought to survey the attitudes and perceptions of US radiation oncologists toward the adoption of telemedicine during the COVID-19 pandemic and offer suggestions for its integration in the postpandemic era. Methods and Materials A 25-question, anonymous online survey was distributed nationwide to radiation oncologists. Results One hundred and twenty-one respondents completed the survey, with 92% from academia. Overall, 79% worked at institutions that had implemented a work-from-home policy, with which 74% were satisfied. Despite nearly all visit types being conducted in-person before COVID-19, 25%, 41%, and 5% of the respondents used telemedicine for more than half of their new consultations, follow-up, and on-treatment visits, respectively, during the COVID-19 pandemic. Most (83%) reported being comfortable integrating telemedicine. Although telemedicine was appreciated as being more convenient for patients (97%) and reducing transmission of infectious agents (83%), the most commonly perceived disadvantages were difficulty in performing physical examinations (90%), patients’ inability to use technology adequately (74%), and technical malfunctions (72%). Compared with in-person visits, telemedicine was felt to be inferior in establishing a personal connection during consultation (90%) and assessing for toxicity while on-treatment (88%) and during follow-up (70%). For follow-up visits, genitourinary and thoracic were perceived as most appropriate for telemedicine while gynecologic and head and neck were considered the least appropriate. Overall, 70% were in favor of more telemedicine, even after pandemic is over. Conclusions Telemedicine will likely remain part of the radiation oncology workflow in most clinics after the pandemic. It should be used in conjunction with in-person visits, and may be best used for conducting follow-up visits in certain disease sites such as genitourinary and thoracic malignancies. ==== Body pmcIntroduction Long before the emergence of the COVID-19 pandemic, the effectiveness of telemedicine in oncology has been established, specifically in the setting of chemotherapy supervision, symptom management, palliative care, and more.1 Its advantages, such as convenience, reduced travel time and costs, reduced appointment wait times, enhanced access to care, and overall ease of use were recognized.2 , 3 In the field of radiation oncology, pilot studies of telemedicine prepandemic have been well received.4, 5, 6 However, until the COVID-19 pandemic, its use was limited primarily to patients in rural and underserved areas, largely due to lack of technological infrastructure and reimbursement.1 , 7 The COVID-19 pandemic, however, catalyzed immediate new interest in and demand for telemedicine. On March 30, 2020, 2 months after the index case in the United States, the US Centers for Medicare & Medicaid Services released an interim final rule loosening prior restrictions on the delivery of telemedicine, specifically lifting geographic restrictions, broadening eligibility, relaxing supervision requirements and importantly, preserving reimbursement.8 States and private payers soon followed suit, leading to a rapid temporary deregulation of telehealth services. In a survey conducted by the American Society for Radiation Oncology on May 20, 2020, most radiation oncology practices (89%) had begun to offer telemedicine options for patients, most commonly for routine follow-up and consultation visits.9 This magnitude of change was not unique to the United States, a rapid adoption of telemedicine was also seen globally.10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 In a survey sent by European Society Radiation Oncology in May 2020 with complete responses from 139 European radiation oncology centers, telemedicine was used in 78% of the departments.16 In an international survey of oncologists, telemedicine was implemented by 80% of respondents.21 Today, almost 2 years after the first known case in the United States, the COVID-19 pandemic appears to be far from being over, and telemedicine continues to play an important role in radiation oncology care today. To date, there are a paucity of studies gauging the perceptions and experiences of US radiation oncology providers in conducting telemedicine in different clinical visit types and disease sites.22 The purpose of this study was to survey the attitudes and perceptions of US radiation oncologists toward the adoption of telemedicine during the COVID-19 pandemic and offer suggestions for its integration in the postpandemic era. Methods and Materials An anonymous, web-based survey (sample in Appendix E1) was developed to assess US radiation oncologists’ experience, perception and attitude toward adoption of telemedicine in new patient consultations, on-treatment visits (OTVs) and follow-up visits. The survey was distributed via Qualtrics platform (Seattle, WA) as an open link. The link was distributed to all radiation oncology residency program directors and department chairs in the United States, as well as to additional private practice physicians. The e-mail recipients were encouraged to share the links with resident physician trainees at their institution as well as with other radiation oncologist colleagues. Participation was voluntary, and responses remained anonymized and confidential. As an incentive, at the end of the survey, respondents who completed the survey could opt to input their e-mail addresses to receive a $10 gift card. The study was approved by the institutional review board (IRB#20-001389). The survey contained 25 questions, with 24 multiple-choice questions (with write-in fields for certain questions if the respondents chose the “other” option) and one free text question at the end to solicit additional feedback. Questions pertaining to radiation oncologist perception of telemedicine appropriateness, comfort level and satisfaction, questions comparing in-person versus telemedicine and gauging the appropriateness of telemedicine follow-up in various scenarios were answered on a 5-point Likert scale to the statement at hand. The median time to complete the survey was 7.3 minutes. Only respondents who completed the survey in its entirety between October 12, 2020 and January 8, 2021 were included in the analysis. Descriptive statistics were used to analyze survey responses. In subgroup analysis, Fisher's exact test was used to determine whether there was a statistically significant difference between responses in different subgroups. Results Respondent demographics A total of 121 respondents completed the survey and were included in the analyses. Overall, 43% of the respondents were resident physicians; 16%, 7%, 16%, and 8% had been practicing as attending physicians for 0 to 5, 6 to 10, 11 to 20, and ≥21 years, respectively. Females accounted for 39%, and males accounted for 61% of the total responses. The majority (92%) practiced in the academic setting, 5% in the community practice setting, and 3% in other. Similarly, the majority (94%) practiced in urban areas and 6% were in rural areas. Practice areas in order of descending frequency were Northeast (40%), Southwest (22%), Midcontinent (17%), Southeast (12%), Rocky Mountain (6%), and Northwest-Pacific Islands (3%). Compared with the national average, 40% reported significantly higher COVID-19 prevalence in the area of practice, 48% reported approximately equal prevalence, and 12% reported significantly lower prevalence. The respondents had a balanced representation of disease sites treated, including gastrointestinal (63%), breast (62%), genitourinary (62%), central nervous system (60%), thoracic (57%), gynecologic (54%), head and neck (49%), sarcoma (46%), lymphoma (42%), and melanoma (36%). Work-from-home policy Overall, 79% reported that their institution had implemented a work-from-home policy; 80% and 77% of attending and resident physicians reported an affirmative answer, respectively (Fig. 1 A). Among these, 15% reported personally working 0 d/wk from home, 35% reported 1 d/wk, 31% reported 2 d/wk, 12% reported 3 d/wk, and 2% reported 4 d/wk, with the remaining 5% reported a variable schedule. The breakdown between attending and resident physicians is shown in Fig 1B. Most respondents were somewhat or extremely satisfied with the work-from-home flexibility (86%) and decreased commute to and from work (83%). Regarding the effect on workflow, 46% respondents were somewhat or extremely satisfied, and 18% were somewhat or extremely dissatisfied. The response to interaction with patients was more mixed, with 40% somewhat or extremely satisfied and 31% reporting somewhat or extremely dissatisfied. Nevertheless, overall, 74% were somewhat or extremely satisfied with the work-from-home policy with only 11% somewhat or extremely dissatisfied (Fig 1C).Fig. 1 Work-from-home policy and physician's satisfaction with working from home. (A) Respondents were asked the question “has your institution implemented a work-from-home policy?” (B) Respondents were asked the question “if you have implemented a work-from-home policy, how many days per week are you working from home?” (C) Respondents were asked the question, “if you have implemented a work-from-home policy, how satisfied are you with this modified workflow on each of the following dimensions?” A diverging stacked bar graph was plotted with a dashed line going through the middle of the “neither satisfied nor dissatisfied” answer. Fig 1 Adoption of telemedicine Before COVID-19, virtually all clinic visits were conducted in-person: 93%, 97%, and 86% of the respondents reported that 100% of the new consultations, OTV and follow-up visits, respectively, were in-person. Even for respondents who had incorporated telemedicine in follow-up visits, most (85%) only used it for 25% or less of the time (Fig 2 A-C). After the start of the pandemic, however, only 10% and 2% of respondents reported conducting new consultations and follow-up visits face-to-face only, respectively. Notably, 30% conducted more than three-quarters of their follow-up visits by telemedicine. For OTVs, however, in-person visits remain the predominant modality, with 68% of respondents reporting conducting 100% of visits in-person.Fig. 2 Utilization of telemedicine before and after the start of the COVID-19 pandemic for different visit types and physician's comfort in conducting telemedicine visits. (A) New consultation, (B) on-treatment visits, and (C) follow-up visits. Telemedicine visits included video and telephone only visits. (A-C) Respondents were asked the question, “on average, before and after COVID-19, what percent of your encounters occurred through telephone, telemedicine (video), or in-person?” Blue bars denote before COVID-19 and orange bars denote after COVID. (D) Respondents were asked the question, “what is your comfort level in conducting telemedicine video visits?” Fig 2 Most respondents (62%) were extremely comfortable with conducting telemedicine, 21% somewhat comfortable and only 11% somewhat or extremely uncomfortable. No difference in level of comfort was found between resident physicians and attending physicians (P = .707). Most respondents found the need to supplement telemedicine visits with in-person visits to be uncommon: 55%, 76%, and 84% reported that they required in-person visits after new patient consults, OTVs, or follow-up visits by telemedicine, respectively, less than one-quarter of the time (Fig 3 A). Similarly, 70%, 93%, and 82% reported that they required additional testing after new patient consults, OTVs, or follow-up visits by telemedicine, respectively, less than one-quarter of the time (Fig 3B).Fig. 3 Self-sufficiency of telemedicine visits in requiring additional in-person visits (A) or tests (B). Participants were asked the question, “what percent of the time was your telemedicine visit not enough (ie, needing to be supplemented by an in-person visit or an additional test)?” Fig 3 Advantages and disadvantages of telemedicine The top 2 cited advantages of telemedicine, compared with the traditional in-person approach, were increased convenience to patients (97%) and reduced transmission of infectious agents (83%). These were followed by increased convenience to physicians (47%), improved efficiency (40%), lower cost to the health system (36%) and positive effect on patient satisfaction (30%) (Fig. 4 A). The most commonly reported disadvantages of telemedicine included not being able to perform in-person physical examinations (90%), patient's inability to use technology adequately (74%), and technical malfunctions (72%).Fig. 4 Perceived advantages and disadvantages of telemedicine versus in-person visits. (A) Respondents were asked the question, “which of the following do you consider to be considerable advantages to Telemedicine (check all that apply)?” (B) Respondents were asked the question, “which of the following do you consider to be considerable disadvantages to Telemedicine (check all that apply)?” (C) Respondents were asked the question, “how do telemedicine video visits compare to in-person visits on the following dimensions?” A diverging stacked bar graph was plotted with a dashed line going through the middle of the “approximately equal” answer. Fig 4 These were followed by uncertainty regarding reimbursement levels over the long term (36%), negative effect on patient satisfaction (33%), less familiar (covering) physicians forced to assess patients in acute settings (20%), cost of setting up telemedicine infrastructure (7%), and privacy risk of conducting visit through an Internet connection (7%; Fig 4B). When comparing telemedicine and in-person visits in performing certain critical tasks, such as answering questions regarding radiation therapy, half (51%) of the respondents expressed that they are approximately equal, and 43% believed that in-person visits are slightly or much better. In terms of obtaining adequate history and physical exam and collecting relevant information during consultation, and assessing for toxicity or recurrence during follow-up, 57% and 70% of the respondents believed that in-person visits were slightly or much better, respectively. The 2 tasks where telemedicine faired most poorly were establishing personal connection with patient and family during consultation (90% believed in-person visit to be slightly/much better) and assessing for toxicity while on-treatment (88% believed in-person visit to be slightly/much better; Fig 4C). Appropriateness of telemedicine in various infection scenarios and disease sites We next surveyed the participants regarding the appropriateness of telemedicine in scenarios with varying COVID-19 infection risks (Fig 5 A). An overwhelming majority of the respondents believed that telemedicine was somewhat or extremely appropriate in scenarios where the physician was confirmed to be COVID-19 positive (91%), where the physician had mild symptoms but was not tested (88%) and where the patient was confirmed COVID-19 positive (86%). Dissent widened when asked about patients with mild symptoms but not tested, patients asymptomatic but living with at-risk person, physician asymptomatic but living with at-risk person or patient asymptomatic but recently in high-risk zones within the past 14 days. Nevertheless, for all the aforementioned scenarios, >50% of the respondents found it somewhat or extremely appropriate to use telemedicine.Fig. 5 Appropriateness of telemedicine for different levels of corona virus disease 2019 infection risk (A) and for follow-up visits in various disease sites (B). (A) Respondents were asked the question, “for each of the following types of cancer patients treated definitively with radiation, how often do you anticipate a telemedicine follow-up being appropriate (assume if labs/imaging were ordered as part of routine visit, they did not reveal any definitive evidence of recurrence)?” (B) Respondents were asked the question, “for each of the following types of cancer patients treated definitively with radiation, how often do you anticipate a telemedicine follow-up being appropriate (assume if labs/imaging were ordered as part of routine visit, they did not reveal any definitive evidence of recurrence)?” Diverging stacked bar graph were presented dashed lines going through the middle of “neither appropriate nor inappropriate” and “about half the tie appropriate” answers. Abbreviations: CNS = central nervous system. Fig 5 We then assessed the appropriateness of telemedicine follow-ups in various disease sites (Fig 5B). Disease sites with descending votes of most of the time appropriate or always appropriate for telemedicine follow-ups were genitourinary (69%), thoracic (53%), gastrointestinal (47%), breast (47%), lymphoma (46%), sarcoma (46%), central nervous system (44%), and melanoma (40%). Respondents who treated genitourinary cancers as part of their practice were not statistically significantly more likely to choose “most of the time appropriate” or “always appropriate” than the rest of the respondents when assessing the appropriateness of a genitourinary follow-up visit using telemedicine (74% vs 61%, P = .204). Similarly, respondents who treated thoracic malignancies were not statistically significantly more likely to favor thoracic telemedicine follow-up visits than those who did not (61% vs 42%, P = .08). Three sites thought to be least appropriate for telemedicine follow-ups were pediatric (20%), gynecologic (19%), and head and neck (10%). Telemedicine in the postpandemic era When asked about the overall impression of telemedicine, 70% were in favor of more telemedicine, even after the COVID-19 pandemic; 22% were in favor of telemedicine during COVID-19, but would like to see things return to prepandemic patterns afterward; and the remaining 7% were against the use of telemedicine unless absolutely necessary (eg, patient or physician is COVID-19 positive, or absolutely unable to make it in person; Fig 6 ). Resident physicians were significantly less likely than junior attending physicians (in practice for 0-10 years) to be against the use of telemedicine unless absolutely necessary (1/52 vs 5/28, P = .0183). There was no significant difference between junior and senior attending physicians (in practice for >10 years; 5/28 vs 3/41, P = .2551) or between resident physicians and attending physicians overall (1/52 vs 8/69, P = .0762). In addition, there was not a statistically significant difference in the proportion of respondents who were in favor of more telemedicine after the pandemic, when stratified by practice setting (academic vs private practice, 69% vs 100%, P = .32), practice area (urban vs rural, 71% vs 57%, P = .42) or geographic location (P = .11).Fig. 6 Physician's overall impression of telemedicine. Respondents were asked the question, “what is your overall impression of telemedicine in radiation oncology workflow?” Fig 6 In response to the optional free-text question at the end of the survey for additional comments, some respondents believed that physical examination was the only limiting factor for telemedicine going forward, and others were less amenable to the idea of continuing telemedicine as part of clinical practice post-COVID-19. One respondent suggested dedicated telemedicine clinics: “the best way to make it work is to have dedicated telemedicine clinics - it's impossible to do good virtual visits in the midst of a busy clinic of in-person visits. But with the need for a good examination in my practice (breast cancer) and patient's inability to use the technology, routine telemedicine visits are not reasonable after the pandemic.” Another respondent advocated a hybrid model of telemedicine and in-person visits postpandemic: “the idea of post-COVID having maybe a day or 2 that you could do virtual or work from home is quite enticing, and in our field seems feasible. But I do think there is a lot of value of being in-person for both workplace benefits (creating a culture) and for patient benefit (better attention and interaction).” Discussion In the prepandemic era, telemedicine was primarily used for patients in rural and underserved areas, largely due to lack of technological infrastructure and reimbursement.1 , 7 Nevertheless, these initial experiences were encouraging. Hamilton et al reported their experience of providing telemedicine services to the regional and rural population at the Townsville Cancer Center in northern Queensland in Australia. Patient satisfaction was high, with 55% preferring telemedicine for future consultations, 35% preferring a mixture of telemedicine and in-person consultations and only 1 patient (0.9%) indicating a preference for in-person only.4 Thomas Jefferson University reported their pilot trial using telemedicine for the first postradiation visit during 2016 to 2018 and similarly found very high level of patient and provider satisfaction.5 Canada's Ontario Telemedicine Network is one of the largest telemedicine service providers, and saw an average annual utilization growth of 51% between 2008 and 2013.20 , 23 By 2016 to 2018, 20% of Ontario's medical and radiation oncologists had used telemedicine, although these visits were mostly ad hoc.20 After the pandemic, radiation oncology practices adapted quickly by employing telemedicine to facilitate treatment continuity together with other measures to continue to provide optimal care to oncology patients despite lack of prior experience.9 , 24 , 25 However, given that these drastic changes were made in the wake of a major public health emergency, the long-term effect of the pandemic on radiation oncology practice remains uncertain. The existing telehealth waivers will expire once the COVID-19 public health emergency is declared over. Coverage for telemedicine visits and limitations on out-of-state practice and licensing vary by state and payer, and the degree that telemedicine is incorporated into clinical practice will be heavily influenced by the regulatory environment moving forward. Nevertheless, barring a drastic reduction in reimbursement and policies restricting its use at a state or federal level, it is safe to infer that telemedicine will likely continue to be an integral part of care delivery, albeit to a lesser extent. This is supported by the strong motivation and high demand from providers and patients alike in multiple surveys to retain telemedicine as a delivery modality,22 , 25, 26, 27 with some even reporting preference of telemedicine over face-to-face visits for future encounters.4 , 26 In the present study, a drastic increase in the portion of new consultations and follow-up visits conducted through telemedicine was seen and the majority (82%) felt comfortable conducting telemedicine. Most respondents appreciated telemedicine for its increased convenience to patient and physicians and reduced transmission of infectious agents. Our study also revealed high provider satisfaction, with 70% in favor of more telemedicine, even after the pandemic. This is in agreement with other available studies showing high satisfaction from both physicians as well as patients with telemedicine visits,22 , 25, 26, 27, 28, 29, 30 with some showing no significant difference in the satisfaction scores of patients between office and telemedicine consultations.27 In a study conducted by the Memorial Sloan Kettering Cancer Center (MSKCC),27 more patients (45%) preferred telemedicine than those preferring office visits (34%), a testimony to the high effectiveness of telemedicine visits. At the same time, a pattern of drawbacks of telemedicine compared with traditional in-person visits started to emerge. The top 3 from our study were an inability to perform physical examinations adequately, difficulty in assessing for toxicity, and recurrence during follow-up, challenges in establishing personal connection with patient or family during consultation, and issues related to a patient's lack of digital health literacy and technical malfunctions. It is imperative that we address and mitigate these concerns. There appears to be a divide in physicians’ experience regarding the ability to connect with patients through telemedicine. In a survey to U attending radiation oncologists,22 48% of respondents strongly agreed or agreed with the statement that a telemedicine consultation felt impersonal, 16% were neutral while a considerable proportion (36%) disagreed or strongly disagreed. In contrast, studies from the perspective of patients are generally more favorable.27 , 31 One potential explanation for the more favorable responses from patients is the change in location. With telemedicine, patients are in their own comfortable environments, often at home, and with family, friends and caregivers, rather than in an unfamiliar outpatient clinic. Nevertheless, for us as clinicians, we should be cognizant of the limitation of telemedicine in conveying subtle signs of empathy and compassion and adjust our communication styles accordingly. A helpful guide is written by Banerjee et al from MSKCC32 regarding strategies to effectively respond to patients’ medical needs and concerns, alleviate distress, and provide support via videoconferencing. Admittedly, certain physical examination maneuvers are difficult to perform, if not downright impossible, through telemedicine visit. However, whether a lack of examination by radiation oncologists negatively effects the design of the radiation plan, monitoring of side effects and continued surveillance after radiation therapy still needs to be further studied and understood. There indeed appears to be a divide in the perception of the physicians.22 In a survey of radiation oncologists from a large academic center,25 only 14% of the respondents expressed that physical examination by a radiation oncologist is preferred, 14% expressed that examination by other providers can be used, 37% expressed that visually inspecting patients through video suffices, 12% reported that examination can be deferred until day of treatment, and the remaining 23% deemed physical examination not necessary (mostly reliant on imaging). In the new consultation setting, in certain disease sites, such as thoracic and upper gastrointestinal, imaging and endoscopic findings may be of greater importance than the physical examination in formulating an appropriate radiation plan. In one large academic center,33 the radiation oncology department has stopped all endoscopic procedures for head and neck cancer and used multiple forms of cross-sectional imaging such as positron emission tomography/computed tomography and magnetic resonance imaging for radiation planning. In the follow-up setting, physical examinations are recommended for many cancer sites, although evidence is generally limited.34, 35, 36, 37 However, in a few disease sites, follow-up physical examinations play a more critical role, such as laryngoscopy for head and neck cancers, lymph node palpation for lymphomas and pelvic examinations for gynecologic cancers.25 For these scenarios, telemedicine may be less appropriate. Notably, during the COVID-19 pandemic, multiple physical examinations tailored specifically for telemedicine visits have been developed, including neurologic examination of the spine, musculoskeletal examination and dermatologic examination.38, 39, 40, 41 Additionally, substitution with examinations from other disciplines, cross-sectioning imaging, or even omission if clinically appropriate can be considered for many disease sites. Another potential barrier to telemedicine is the heterogeneity of digital health literacy and potentially technical challenges. More than 30% of US households are headed by a person aged 65 or older lacking a desktop or laptop computer and more than half lack smartphones.42 Uninsured patients, patients with Medicaid, and patients with lower median household incomes have also been shown to have lower rates of completing a virtual care visit.43 Therefore not all may benefit equally due to “digital divide,”44 in part due to poor digital health literacy and in part due to lack of infrastructure such as access to high-speed Internet. Improving digital health literacy is an important component in expanding the world of telemedicine care delivery. It is crucial that we approach these new processes with a health equity lens with efforts to screen for patients with access difficulties so as to minimize health disparities.45 The effectiveness and appropriateness of telemedicine visits varies considerably with visit types. We believe that in general, telemedicine visits are most appropriate for follow-up visits, followed by new consultations and least appropriate for OTVs; this agrees with the telemedicine utilization pattern reported by our respondents (Fig 2A-C). In a survey to staff physicians at Mayo Clinic Florida,26 overall, 68% were open to using telemedicine routinely in the future for consultations, and 88% were open for follow-ups. For routine follow-up and surveillance visits, the need for emotional support or rapport building is generally not as great, and in many disease sites, laboratory and imaging surveillance are sufficient, reducing the need for an in-person examination. For new patient consultations, our field uniquely requires in-office patient presence for radiation simulation, thus allowing a virtual consultation as an introduction and the presimulation office visit as a built-in opportunity to modify the treatment plan, answer questions, and further review the care plan.25 For OTVs, on the other hand, telemedicine generally lends itself poorly after the pandemic for multiple reasons: (1) the need for close examination to manage acute side effects. In our study, 88% of the respondents agreed that telemedicine is inferior to in-person visits in that regard. (2) The need to continue relationship-building when patients feel most vulnerable, and (3) technical difficulties easily bypassed by visiting the patient and there is not much to be gained in terms of commute time for patients; the patients are already visiting the treatment facility for radiation therapy. Our tiered recommendation regarding visit types is also in agreement with patients’ satisfaction level in the literature, as 100%, 94%, and 73% patients were satisfied with virtual follow-ups, consultations and OTVs, respectively, according to one study.28 Additionally, our international colleagues have offered insights into the adoption of telemedicine into routine clinical care in a postpandemic world. The group from Princess Margaret Hospital described a system of distributed leadership and decision-making, and the use of a Service Design process to map the ambulatory encounter onto a digital workflow, which the authors believed were crucial for a large-scale virtual transition.20 Abdel-Wahab et al from Austria also discussed best areas of telemedicine integration as well as the International Atomic Energy Agency's initiatives in broadening the application of telemedicine in radiation therapy delivery and education.18 The present study has several limitations. First, we were unable to calculate the response rate of the survey. The survey link was distributed to all radiation oncology residency program directors and department chairs in the United States, as well as additional private practice physicians. The email recipients were encouraged to share the links with resident physician trainees at their institution as well as other radiation oncologist colleagues. Therefore, the denominator of the response is unknown. Second, the majority of the respondents were from urban academic centers, so this study may not reflect the practice pattern and experience of community radiation oncologists. The community radiation oncologists that we emailed the survey link to were personal contacts of senior authors (MLS and ACR) and were likely biased toward practices in urban areas. Forty-three percent of the respondents were resident physicians at various stage of training and the survey results may be different from an all-attending physician cohort. Third, we did not track the affiliations of the respondents and it is possible that certain large institutions might have represented the majority of respondents from a given geographic area. Fourth, due to length limitations, our survey focused on radiation therapy with curative intent. However, telemedicine can be especially valuable for selected patients being considered for palliative radiation therapy (eg, patients with known central nervous system metastasis) who may have poorer performance status, are already seeing many physicians, and for whom physical examinations have minimal benefit. Fifth, similar to all survey-based studies, participation bias may be a confounding factor as physicians particularly satisfied or dissatisfied with telemedicine may have been more likely to respond to the survey. Lastly, the relatively small sample size of certain subgroups may preclude accurate detection of significant differences due to a lack of statistical power, although this is not a primary objective of the study. Conclusions The COVID-19 pandemic has caused a seismic shift in the workflow of radiation oncology, with rapid adoption of telemedicine as a hallmark of change. The studies by us and others have consistently demonstrated an overall high level of satisfaction with telemedicine among physicians and patients,22 , 25, 26, 27 as well as the overwhelming demand to continue telemedicine as part of care delivery after the pandemic.22 , 25, 26, 27, 28, 29, 30 However, heterogeneity in the appropriateness and effectiveness of telemedicine across disease sites and visit types exists. We believe telemedicine is best used for routine follow-up visits, followed by new patient consultations, although OTVs are more poorly suited in most situations. Disease sites such as thoracic and genitourinary, where physical examinations play a less crucial role, are best suited for telemedicine, and sites such as head and neck and gynecologic malignancies may benefit from a higher-than-average level of face-to-face encounters. We should remain cognizant of the heterogeneity of patients’ digital health literacy and access to technology and communication barriers (eg, laryngectomy, cognitive impairment, hearing loss, neurologic conditions, and limited English proficiency) when triaging patients for telemedicine visits. It is crucial that we continue to keep our patients at the center as we make changes to the radiation oncology workflow. Appendix Supplementary materials Image, application 1 Acknowledgement The authors would like to thank the STOP Cancer Grant for funding support. Sources of support: This study was supported by the STOP Cancer Grant. Disclosures: Dr Raldow reports consulting work for Intelligent Automation Inc and Viewray Inc, honoraria from Varian Medical Systems, Clarity PSO/RO-ILS RO-HAC, research grants from Viewray Inc, and rectal cancer panel member of the Veteran's Health Administration Radiation Oncology Quality Surveillance Program Services. Dr Kishan reports funding support from grant P50CA09213 from the Prostate Cancer National Institutes of Health Specialized Programs of Research Excellence, as well as grant RSD1836 from the Radiologic Society of North America, the STOP Cancer organization, the Jonsson Comprehensive Cancer Center, and the Prostate Cancer Foundation. Detailed data tables available upon request. T.M.M. and N.R.P. contributed equally to this work. Supplementary material associated with this article can be found in the online version at doi:10.1016/j.adro.2022.100924. ==== Refs References 1 Sirintrapun SJ Lopez AM. Telemedicine in cancer care Am Soc Clin Oncol Educ Book 38 2018 540 545 30231354 2 Kitamura C Zurawel-Balaura L Wong RK. How effective is video consultation in clinical oncology? A systematic review Curr Oncol 17 2010 17 27 3 Larson JL Rosen AB Wilson FA. The effect of telehealth interventions on quality of life of cancer patients: A systematic review and meta-analysis Telemed J E Health 24 2018 397 405 29112484 4 Hamilton E Van Veldhuizen E Brown A Brennan S Sabesan S. Telehealth in radiation oncology at the Townsville Cancer Centre: Service evaluation and patient satisfaction Clin Transl Radiat Oncol 15 2019 20 25 30582017 5 Miller RC Simone BA Lombardo JF A pilot trial using telemedicine in radiation oncology: The future of health care is virtual Telemed Rep 2 2021 171 178 34250522 6 Lewis GD Hatch SS Wiederhold LR Swanson TA. Long-term institutional experience with telemedicine services for radiation oncology: A potential model for long-term utilization Adv Radiat Oncol 5 2020 780 782 32391444 7 Scott Kruse C Karem P Shifflett K Vegi L Ravi K Brooks M Evaluating barriers to adopting telemedicine worldwide: A systematic review J Telemed Telecare 24 2018 4 12 29320966 8 Royce TJ Sanoff HK Rewari A. Telemedicine for cancer care in the time of COVID-19 JAMA Oncol 6 2020 1698 1699 32672821 9 American Society for Radiation Oncology. COVID-19's Impact on Radiation Oncology: Initial Results of a Nationwide Physician Survey. ASTRO. Available at:https://www.astro.org/ASTRO/media/ASTRO/News%20and%20Publications/PDFs/ASTROCOVID19Survey1-ExecSummary.pdf. Accessed June 1, 2021. 10 Al-Shamsi HO Alhazzani W Alhuraiji A A practical approach to the management of cancer patients during the novel coronavirus disease 2019 (COVID-19) pandemic: An International Collaborative Group Oncologist 25 2020 e936 e945 32243668 11 De Felice F D'Angelo E Ingargiola R A snapshot on radiotherapy for head and neck cancer patients during the COVID-19 pandemic: A survey of the Italian Association of Radiotherapy and Clinical Oncology (AIRO) Head and Neck Working Group Radiol Med 126 2021 343 347 33025304 12 Di Franco R Borzillo V D'Ippolito E COVID-19 and radiotherapy: Potential new strategies for patients management with hypofractionation and telemedicine Eur Rev Med Pharmacol Sci 24 2020 12480 12489 33336767 13 Fernández C Ruiz V Couñago F. COVID-19 and information and communication technology in radiation oncology: A new paradigm World J Clin Oncol 11 2020 968 975 33437658 14 Appel S Lawrence YR Symon Z Kaidar-Person O. COVID-RO study: The radiation oncology practice at times of COVID-19 outbreak - international survey Rep Pract Oncol Radiother 26 2021 20 28 33948298 15 Boon IS Lim JS Au Yong TPT Boon CS Digital healthcare and shifting equipoise in radiation oncology: The butterfly effect of the COVID-19 pandemic J Med Imaging Radiat Sci 52 2021 11 13 33097437 16 Slotman BJ Lievens Y Poortmans P Effect of COVID-19 pandemic on practice in European radiation oncology centers Radiother Oncol 150 2020 40 42 32544604 17 Helissey C Cessot A Boudin L Evaluation of medical practices in oncology in the context of the COVID-19 pandemic in France: Physicians' point of view: the PRATICOVID study Cancer Med 9 2020 8875 8883 33022134 18 Abdel-Wahab M Rosenblatt E Prajogi B Zubizarretta E Mikhail M. Opportunities in telemedicine, lessons learned after COVID-19 and the way into the future Int J Radiat Oncol Biol Phys 108 2020 438 443 32890528 19 Deantonio L Bosetti D Cima S #Stayathome: Smart working for radiation oncologists during the corona pandemic Strahlenther Onkol 196 2020 1094 1095 32945893 20 Rodin D Lovas M Berlin A. The reality of virtual care: Implications for cancer care beyond the pandemic Healthc (Amst) 8 2020 100480 21 Ürün Y Hussain SA Bakouny Z Survey of the impact of COVID-19 on oncologists' decision making in cancer JCO Glob Oncol 6 2020 1248 1257 32755479 22 Chhabra AM Chowdhary M Choi JI Hasan S Press RH Simone CB, 2nd. A national survey of radiation oncology experiences completing tele-consultations during the coronavirus disease (COVID-19) pandemic Adv Radiat Oncol 6 2021 100611 23 Whitten P Holtz B. Provider utilization of telemedicine: The elephant in the room Telemed J E Health 14 2008 995 997 19035815 24 Wakefield DV Sanders T Wilson E Initial impact and operational responses to the COVID-19 Pandemic by American Radiation Oncology Practices Int J Radiat Oncol Biol Phys 108 2020 356 361 32890512 25 Zhang H Cha EE Lynch K Radiation oncologist perceptions of telemedicine from consultation to treatment planning: A mixed-methods study Int J Radiat Oncol Biol Phys 108 2020 421 429 32890525 26 Malouff TD TerKonda SP Knight D Physician satisfaction with telemedicine during the COVID-19 pandemic: The Mayo Clinic Florida experience Mayo Clin Proc Innov Qual Outcomes 5 2021 771 782 34226884 27 Shaverdian N Gillespie EF Cha E Impact of telemedicine on patient satisfaction and perceptions of care quality in radiation oncology J Natl Compr Canc Netw 2021 1 7 28 Gutkin PM Prionas ND Minneci MO Telemedicine in radiation oncology: Is it here to stay? Impacts on patient care and resident education Int J Radiat Oncol Biol Phys 108 2020 416 420 32890524 29 Di Lalla V Patrick H Siriani-Ayoub N Kildea J Hijal T Alfieri J. Satisfaction among cancer patients undergoing radiotherapy during the COVID-19 pandemic: An institutional experience Curr Oncol 28 2021 1507 1517 33920247 30 The COVID-19 Healthcare Coalition Telehealth Impact Study Work Group. Telehealth Impact: Physician Survey Analysis. Available at:https://c19hcc.org/telehealth/physician-survey-analysis/. Accessed June 1, 2021. 31 Coelho JJ Arnold A Nayler J Tischkowitz M MacKay J. An assessment of the efficacy of cancer genetic counselling using real-time videoconferencing technology (telemedicine) compared to face-to-face consultations Eur J Cancer 41 2005 2257 2261 16176873 32 Banerjee SC Staley JM Howell F Communicating effectively via tele-oncology (Comskil TeleOnc): A guide for best practices for communication skills in virtual cancer care J Cancer Educ 2021 1 6 33 Kang JJ Wong RJ Sherman EJ Be safe, be smart, be kind"-A multidisciplinary approach increasing the use of radiation and embracing telemedicine for head and neck cancer Cancer 126 2020 4092 4104 32639615 34 Jeffery M Hickey BE Hider PN See AM. Follow-up strategies for patients treated for non-metastatic colorectal cancer Cochrane Database Syst Rev 11 2016 Cd002200 35 Montgomery DA Krupa K Cooke TG. Follow-up in breast cancer: Does routine clinical examination improve outcome? A systematic review of the literature Br J Cancer 97 2007 1632 1641 18000508 36 Cunniffe NG Robson J Mazhar D Williams MV. Clinical examination does not assist in the detection of systemic relapse of testicular germ cell tumour Clin Oncol (R Coll Radiol) 24 2012 39 42 21723715 37 Johnstone PA McFarland JT Riffenburgh RH Amling CL. Efficacy of digital rectal examination after radiotherapy for prostate cancer J Urol 166 2001 1684 1687 11586202 38 Goyal DKC Divi SN Schroeder GD Development of a telemedicine neurological examination for spine surgery: A pilot trial Clin Spine Surg 33 2020 355 369 32969872 39 Piche J Butt BB Ahmady A Patel R Aleem I. Physical examination of the spine using telemedicine: A systematic review Global Spine J 11 2021 1142 1147 32959711 40 Laskowski ER Johnson SE Shelerud RA The telemedicine musculoskeletal examination Mayo Clin Proc 95 2020 1715 1731 32753146 41 Mounessa JS Chapman S Braunberger T A systematic review of satisfaction with teledermatology J Telemed Telecare 24 2018 263 270 28350281 42 United States Census Bureau. Computer and Internet Use in the United States: 2015. US Census Bureau. Available at:https://www.census.gov/content/dam/Census/library/publications/2017/acs/acs-37.pdf. Accessed June 1, 2021. 43 Tam S Wu VF Williams AM Disparities in the uptake of telemedicine during the COVID-19 surge in a multidisciplinary head and neck cancer population by patient demographic characteristics and socioeconomic status JAMA Otolaryngol Head Neck Surg 147 2021 209 211 33151289 44 Levy H Janke AT Langa KM. Health literacy and the digital divide among older Americans J Gen Intern Med 30 2015 284 289 25387437 45 Franco I Perni S Wiley S Drapek L. Equity in radiation oncology post-COVID: Bridging the telemedicine gap Int J Radiat Oncol Biol Phys 108 2020 479 482 32890538
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==== Front Prospects (Paris) Prospects (Paris) Prospects 0033-1538 1573-9090 Springer Netherlands Dordrecht 9628 10.1007/s11125-022-09628-3 Editorial Reaching SDG 4: Our shared responsibility and renewed commitment to action Ydo Yao [email protected] UNESCO International Bureau of Education, P.O. Box 199, 1211 Geneva 20, Switzerland 12 12 2022 17 25 11 2022 © The Author(s) under exclusive licence to UNESCO International Bureau of Education 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. ==== Body pmcIn 2015, all United Nations Member States committed to achieving 17 Sustainable Development Goals (SDGs) by 2030. SDG 4 seeks to ensure access to equitable and quality education through all stages of life, as well as to increase the number of young people and adults who have the relevant skills for employment, decent jobs, and entrepreneurship: “Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all” (UN, 2015). SDG 4 emphasizes that inclusion and equity lay the foundations for quality education. It also stresses the need to address all forms of exclusion, marginalization, disparities, and inequalities in access, participation, and learning processes and outcomes. However, progress toward meeting the SDG 4 education targets (including universal literacy and numeracy) by 2030 is slipping further out of reach. Based on the latest data and estimates, a sobering picture emerges: the 2030 Agenda for Sustainable Development is in grave jeopardy due to multiple cascading and intersecting crises, including Covid-19, climate change, and conflict (UN, 2022a). These challenges have deepened a massive crisis in education, with severe disruptions in education systems worldwide. The magnitude of the crisis was highlighted in a joint World Bank, UNESCO, & UNICEF report (2021): Learning losses are substantial, with the most marginalized children and youth often disproportionately affected. Entrenched inequities in education have only worsened during the pandemic. Prolonged school closures have heightened the risk that children will not return to school. As the UN Secretary-General António Guterres said, to recover from the Covid-19 pandemic and deliver global sustainability, we need an urgent rescue effort for the SDGs (UN, 2022a). In this context, reaching SDG 4 has become an even greater global priority. It has thrown new light on the immediate need to develop education systems that are designed to include all of our children and young people. Moreover, it has highlighted the urgent need to completely “transform” education systems and reimagine them for the world of today and tomorrow (UN, 2022b). This special issue of Prospects brings together leading scholars to discuss ways in which we can urgently and decisively advance the SDG 4 and deliver on our commitments to support the world’s most vulnerable people, communities, and nations. Monica Mincu argues that if education change is to be systemic and transformative, it cannot occur uniquely at the individual teachers’ level. School organization is fundamental to circulating and consolidating new innovative actions, cognitive schemes, and behaviors in coherent collective practices, and school leaders should play a key role in quality and equitable schooling. Mincu formulates several assumptions that clarify the importance of leadership in any organized change. The way teachers act and represent their reality is strongly influenced by the architecture of their organization, while their ability to act with agency is directly linked to the existence of flat or prominent hierarchies, both potentially problematic for deep and systemic change. Sugata Mitra states that education that does not include an understanding of the Internet and how to live with it is deficient. He describes how the Internet can be learned in schools, what the curriculum for such learning should be at various stages of schooling, what pedagogical methods should be used to achieve learning objectives, and what methods should be used to assess learning outcomes. He bases his proposal on decades of experiments and observations carried out by himself and others. Ali Ibrahim asks what hurts or helps teacher collaboration. Despite the positive impact of collaborative school cultures on teachers’ professional growth and student achievement, it is difficult to create such a culture. His article explores the types of school cultures in one school district in the United Arab Emirates (UAE) to identify factors that could foster or inhibit true teacher collaboration. Results show that the most common types of school cultures were contrived collegiality and comfortable collaboration, and that true collaboration was the least common. There is also evidence that when teachers’ work is governed by mandated learning outcomes, students’ assessment requirements, and external accountability demands, teachers lack the time, autonomy, or willingness to create a truly collaborative work culture. His article concludes that teacher autonomy and internal accountability are key elements for creating truly collaborative cultures in UAE schools. Oscar Espinoza, Luis Eduardo González, and Noel McGinn look at whether teachers in the national system of Second Opportunity Centers of Chile have characteristics similar to those of effective teachers in similar schools in other countries. A nationally representative sample of teachers in 40 centers completed a self-administered questionnaire describing their background, training, teaching, and assessment strategies. Answers were compared with reports of effective schools for dropouts in other countries. Second Opportunity teachers in Chile appear to have characteristics and use practices much like those reported for teachers in effective schools elsewhere. More definitive statements await direct observation of teaching practices and information about students. The success of alternative schooling for dropouts varies directly with its differentiation to match the student population it serves. To improve effectiveness, future research must generate close-up, fine-grained data describing individual characteristics, teaching practices, and specific student reactions and outcomes. Michael H. Romanowski and Xiangyun Du argue that transferring educational reform models for the systematic improvement of education is nowhere else more evident than in the Gulf Cooperation Council states, which have implemented primarily Western decentralized reform models to overhaul their educational systems. Their article reports nonempirical research, written as a conceptual analysis that examines the current situation of the educational reform in Qatar. The theory of education transferring serves as a conceptual framework to scrutinize Qatar’s recent educational change to Project-Based Learning. This illustrates the shift from the initial decentralized reform to its current centralized state. Contextual factors that influence decentralization are discussed. Carina Omoeva and Rachel Hatch investigate the relationship of early marriage to school participation and whether other factors, including individual or family characteristics and childbirth, moderate the relationship. They use national household survey data for Eastern Africa, pooled at the regional level, to show that marriage and schooling appear largely incompatible across the Eastern Africa region at present. The results of the main analysis indicate that married girls are roughly 31 percentage points less likely to be attending school than their unmarried peers. The effect of marriage on school participation trumps other observed factors, including childbirth. Based on an extended analysis using the timing of marriage and two consecutive years of education data in Malawi and Kenya, their article concludes that marriage is a predictor of subsequent school exit. Simon McGrath argues that skills systems often remain marginalized within educational debates and plans, with vocational learning often dismissed as low quality and low status. The UNESCO International Commission on the Futures of Education imagines a positive future in which skills development can be harnessed for the benefits of people and planet, in line with the loftiest vision of the Sustainable Development Goals. Reflecting on the work done for the commission on future skills, McGrath considers the nature of the challenges of the present in building better skills futures for Africa. He argues that we must be clear-sighted regarding the failings of past theory and practice if, together, we are to construct better futures for learning, working, and living. Only then can we develop institutions, programs, and curricula that can meet the challenges and realize the opportunities of the future. Margo O’Sullivan argues that teacher absenteeism is a key reason behind the fact that significant investments in supporting teachers to improve learning have not enabled improved learning outcomes. She highlights poor teacher motivation as an explanation for teacher absenteeism, with poor remuneration emerging as teachers’ main reason for not attending school and/or class. O’Sullivan explores the use of financial incentives, which have been sidelined within the education aid architecture, to improve teacher motivation, address teacher absenteeism, and improve learning. Her article distills the successes and lessons learned from the research literature to devise a framework to guide financial-incentive-focused strategies. The framework is currently informing a research-based intervention in schools in Uganda, using cost-effective mobile-phone-based and teacher-motivation-focused strategies and tools to improve learning. Miriam Ham looks at the ongoing reform of the Nepali education system, which is guided by the commitment of Nepal’s Ministry of Education, Science, and Technology to improve educational outcomes by aligning with international educational policy. The reform goals require Nepali teachers to change their classroom practices to become child-friendly, flexible, and responsive to students’ needs. Evaluation reports describe Nepali teachers’ response as limited but do not explain the reasons why, do not contain the voices of Nepali teachers, and do not indicate whether Nepali teachers’ beliefs align with the reform goals. Ham reports the findings of a mixed-methods research project conducted with Nepali teachers. Her article shows the close alignment between Nepali teachers’ beliefs and the reform goals and then examines the factors that Nepali teachers report have limited their response to change. These factors center around endemic issues of instability and inequity within the Nepali context. Her article also outlines teachers’ recommendations for stability and equitable strategies. Christina-Aimilia Vogiatzi, Garyfalia Charitaki, Elias Kourkoutas, and Chris Forlin argue that while the literature contains cases of validation of the Teacher Efficacy for Inclusive Practices (TEIP) scale in many countries, it finds none in Greece. Consequently, there is a clear need to ensure that teacher self-efficacy in Greece is explored with a reliable and valid measure. Their article provides a detailed review and evaluation of the psychometric properties of the TEIP and its use in supporting teachers to promote and adapt inclusive practices in Greek classrooms. They also evaluate the scale’s use in identifying teachers’ perceived efficacy at implementing inclusive practices. Their research finds that the Greek TEIP demonstrates sufficient evidence of validity and reliability for assessing teachers’ attitudes toward their efficacy for implementing inclusive practices. Results indicate poor perceived efficacy to implement inclusive practices, in terms of using inclusive instruction, collaborating effectively, and managing behavioral problems. Michael H. Romanowski argues that South Africa shows a deficit in social capital in under-resourced and underperforming schools, which limits students’ educational opportunities and achievement. Partners for Possibility (PfP) responds to the lack of social capital in South African schools by partnering school principals and business leaders to develop support structures such as collaboration, networking, and professional learning communities. Findings from a site visit, conversational interviews, and examining participants’ portfolios indicate that PfP provides opportunities for developing three types of social capital: structural, cognitive, and relational. These produce options that would otherwise be unavailable to these students. The discussion raises issues about social capital as a resource for development and offers suggestions for further research. Hanaa Ouda Khadri argues that there is an urgent need to identify new roles for STEM education that will prepare students for this post-normal world and the sustainability mindset it requires. STEM education supports sustainable development by building the capacities of future generations. The integration of Future Studies (FS) into STEM education practices is therefore critical to support efforts at sustainability and to ensure that students are competent 21st-century problem-solvers. Building STEM students’ competencies in this area depends on their teachers having the appropriate knowledge and skills to integrate FS within their subjects. Based on a sample of 52 Egyptian university academics, the article reveals the basic knowledge and skills that should be included in a Future-Proof STEM teachers’ capacity-building program. Matthew A. Witenstein and Joanna Abdallah argue that affiliated colleges in India, with their positioning in the bureaucratic landscape, historically have had a limited role in curriculum and exam policies and development, yet they are embedded in local communities where they can often find meaningful knowledge to best support them. Moreover, affiliated college members, purported street-level bureaucrats who work at the intersections of policy and discretion, have a notably limited role. This policy study explores high-impact and emerging high-impact practices of affiliated college faculty members in India with regard to curriculum and exam policies. To guide the analysis, it proposes a new framework, the Four Tenets of Street-Level Bureaucracy Framework for Education Policy Discernment, based on Michael Lipsky’s street-level bureaucracy framework. Four high-impact practices and two emerging high-impact practices offer meaningful insight for policy adaptation consideration to Indian higher education policymakers, faculty members at universities and colleges, and higher education institutions. The four high-impact practices are flexibility, change, and adaptation; successful coping and adapting; connecting theory and industry/practice; and belief in one's training and capacity leading to de facto policymaking at the micro level. The two emerging practices are establishing feedback channels from the bottom up and re-envisioning broader faculty involvement in bureaucratic structures. Miku Ogawa examines the emerging unfair inequality in Kenyan secondary schools through comparative case studies of three secondary schools in western Kenya. Qualitative data were collected through fieldwork over a four-year period, with participant observation and semi- or non-structured interviews, to understand how interactions among schools, households, and communities impact the improvement of educational quality. Ogawa demonstrates that educational inequality stems from economic background and academic performance. While establishing new schools allowed students to choose better schools in their vicinity, increasing school competition resulted in a school hierarchy, restricting uniform access due to factors of affordability and academic achievement. This suggests that unplanned establishment of new schools constrains vulnerable students from continuing their education. Expanding educational opportunities and improving quality are important facets of education; however, it is necessary to pay attention to the beneficiaries of this process, as economic inequality may translate into educational inequality. Anwynne Kern notes that in South Africa, the process toward inclusion commenced in October 1996 and was realized in 2001 with the Education White Paper 6. However, the implementation of inclusion in South Africa has been marred by challenges. These challenges have largely been examined through an ecosystemic theoretical lens offering insight into the contextual challenges facing inclusion, but have not adequately explored the role that the person involved in the implementation and their specific dispositions play in the enactment of inclusion. This article argues that, to better understand the challenges individuals face with implementing inclusion, a broader lens integrating bioecological theory and the capability approach is needed. This integration highlights the need to look at a complexity of issues to understand what is valued, as competing values, and the choices between them, will influence the implementation of inclusion. Gordana Nikolić, Marija Cvijetić, Vesna Minić, and Borka Vukajlović examine teachers’ opinions on the quality of textbooks and didactic materials used in teaching students with developmental disabilities and learning difficulties (hereinafter referred to as special educational needs). The results of their empirical research show that teachers in special schools rely relatively little (29.1%) on general textbooks intended for use in regular schools and instead often prepare their own materials for teaching students with special educational needs (69.6%). A significantly higher percentage of special educators, compared to regular teachers, personally prepare materials for students. These results have verified the need for adapted textbooks and have further found that special educators significantly prefer the paper form of adapted textbooks, while regular teachers give preference to electronic textbooks. Alexander N. Kosarikov and Natalia G. Davydova analyze the experience gained during the development and implementation of a high-school extracurricular program in Russia that combined project-based learning with a national contest of research projects which students completed as one of their electives. By employing the principles of social-emotional learning, the combination of the extracurricular program and the contest played a key role in the development of the creative and divergent capabilities of high-school students. Mona M. Al-Kuwari, Xiangyun Du, and Muammer Koç present an in-depth analysis of the Qatar education system (K–12 level), focusing on the current assessment approaches and remaining challenges that hinder the development and implementation of proper performance-assessment methods aligned with SDGs. Based on a proposed theoretical framework influenced by the constructive alignment theory, they examine the current performance assessment practices in Qatar and recommend potential improvement avenues with respect to SDGs and education goals (EGs). Using this framework as an analytical tool, their results reveal a lack of alignment between the assessment practices, educational goals, and the SDGs. This work shows that tailored, contextually proper, and progressive assessment strategies need to be developed to accurately evaluate and guide the 21st-century skills of the students toward the achievement of SDGs. Their article further presents and discusses locally relevant and consistent recommendations for performance assessment methodologies that must be redesigned to be compatible with, align with, and support the SDGs and EGs. Rhonda Di Biase, Stefano Malatesta, and Marcella Schmidt di Friedberg explore the critical role of education in promoting sustainable development in the Maldives context. Their article presents the outcomes of a small-scale project, Playing with Solar, implemented in a small island school in collaboration with the island community. Because of the environmental and educational principles embedded in this project, it is presented as one that prioritizes sustainable development, actively engages with the community, and aligns with the key competencies underpinning the Maldives National Curriculum Framework. The Playing with Solar project is an example of transformative pedagogy aligned with sustainable development. By promoting problem-based learning, the project shows how key competencies and pedagogical principles can be operationalized in line with National Curriculum Framework syllabi that promote interdisciplinary learning, in contrast to textbook-based, transmission models of teaching. Karen Parish presents findings from a study that investigated how the global logic of human rights, as incorporated by the International Baccalaureate schools into their policies and practices, is experienced and adhered to by students who are following the International Baccalaureate Diploma Programme (IBDP) in different contexts. In her study, the cases for comparison were a private school in Norway and a state-funded school in Poland. Although selected for their differences, they offered functional equivalence in the standardized diploma program. The article used a multiple-methods approach, including both quantitative and qualitative data. Findings reveal significant differences between students’ levels of adherence to human rights logic. Reasons for this difference point both to logic hybridity within the school organization and a diverse school learning community. In the Profiles of Educators section, Piotr Toczyski, Joachim Broecher, and Janet Painter use historical and autobiographical approaches combined with interviews to analyze the case of the Europa-Kontakt in pre-1989 Poland and West Germany within the framework of Europeanization. The international education encounters exemplify the tendencies to Europeanize, which emerged in both countries despite the Iron Curtain. The painful relationship between Poland and Germany is contrasted with the personal trust and cooperation between Polish and German exchange pioneers since the 1970s. Their pioneering work focused on multinational inclusion, participation, intercultural learning, gifted education, creativity, and building leadership skills. It merged German adaptation of the United States’ HighScope model with philosophy of encounters typical of scouting tradition, Janusz Korczak’s pedagogy, and Carl Rogers’s humanistic psychology, preparing ground for the 1989–2004 European Union enlargement process. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References UN [United Nations] (2015). SDG 4. https://sdgs.un.org/goals/goal4 UN (2022a). The Sustainable Development Goals Report 2022. https://unstats.un.org/sdgs/report/2022/The-Sustainable-Development-Goals-Report-2022.pdf UN (2022b). Transforming Education Summit. https://www.un.org/en/transforming-education-summit World Bank, UNESCO, & UNICEF (2021). The state of the global education crisis: A path to recovery. https://www.worldbank.org/en/topic/education/publication/the-state-of-the-global-education-crisis-a-path-to-recovery
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==== Front Präv Gesundheitsf Pra¨vention Und Gesundheitsfo¨rderung 1861-6755 1861-6763 Springer Berlin Heidelberg Berlin/Heidelberg 1002 10.1007/s11553-022-01002-7 Originalarbeit Studentische Gesundheitsförderung aus Sicht der Studierenden in Österreich Student health promotion from the perspective of university students in Austriahttp://orcid.org/0000-0003-0284-527X Nöhammer Elisabeth [email protected] [email protected] grid.41719.3a 0000 0000 9734 7019 Department of Public Health, Health Services Research & Health Technology Assessment, UMIT TIROL – Private Universität für Gesundheitswissenschaften und Gesundheitstechnologie, Eduard-Wallnöfer-Zentrum 1, 6060 Hall in Tirol, Österreich 12 12 2022 16 23 7 2022 13 11 2022 © The Author(s), under exclusive licence to Der/die Autor(en), exklusiv lizenziert an Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature 2022, Springer Nature oder sein Lizenzgeber (z.B. eine Gesellschaft oder ein*e andere*r Vertragspartner*in) hält die ausschließlichen Nutzungsrechte an diesem Artikel kraft eines Verlagsvertrags mit dem/den Autor*in(nen) oder anderen Rechteinhaber*in(nen); die Selbstarchivierung der akzeptierten Manuskriptversion dieses Artikels durch Autor*in(nen) unterliegt ausschließlich den Bedingungen dieses Verlagsvertrags und dem geltenden Recht. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Hintergrund und Ziel Im Setting Universität ist studentische Gesundheitsförderung (SGF) noch nicht sehr verbreitet, wird aber als hoch relevant angesehen. Um von der Zielgruppe genutzt zu werden, sollte die SGF deren Erwartungen und Bedürfnissen entsprechen. Eine bundesweite Online-Befragung dazu wurde im Juni 2022 abgeschlossen. Material und Methoden Über 40 quantitative Items und diverse offene Fragen bildeten die Einstellung zu Nutzung und Auswirkung von Nutzungskriterien, Wünschen und Bedürfnissen bzgl. SGF ab. Die Items waren 5‑stufig skaliert nach Likert und auf Deutsch und Englisch verfügbar. Ergebnisse Insgesamt finden 90,6 % die Idee von SGF gut, ein entsprechendes Angebot finden jedoch nur 49,8 % an ihrer Hochschule vor. 56,7 % wünschen sich in Zukunft mehr SGF-Angebote, v. a. zu psychischer Gesundheit (Werte + 70 % bis + 60 % Zustimmung). Gleiches gilt für Ernährung und bestimmte Ernährungsempfehlungen, Sport und Bewegung, Ergonomie sowie Ausgleich zum Sitzen. Mehr Suchtprävention wird von 26,9 % gewünscht. Zirka 60 % wünschen sich im Rahmen der SGF mehr thematische Vernetzungsmöglichkeiten, knapp unter 50 % bzgl. Lerngruppen und fachliche Diskussionsrunden. Viele weitere Empfehlungen zu Verhältnisprävention und Angebotskonkretisierungen wurden angemerkt. Schlussfolgerung Die SGF wird als sehr positiv und ausbaufähig angesehen, v. a. bzgl. Psyche, Ernährung und Bewegung. Eine Möglichkeit ist ein studienphasenorientierter Zugang, der zu Beginn auf Information und Kompetenzentwicklung setzt und diese später ergänzt. Background and aim Student health promotion (SHP) is not yet widely applied but is considered highly relevant. To be of interest for the target group, SHP should meet their expectations and wishes. For this purpose, a nation-wide online survey was completed in June 2022. Materials and methods More than 40 quantitative items and several open questions surveyed attitudes towards, use and impact of, determinants of participation, wishes, and needs regarding SHP. The items were assessed using a Likert scale (5 categories) and were available in German and English. Results Overall, 90.6% like the idea of SHP, but only 49.8% found an offer at their university. Furthermore, 56.7% wish for more offers, mainly regarding mental health (+ 70% and + 60% agreement). The same is true for nutrition and specific nutrition suggestions, exercise, ergonomics, and compensation exercise for prolonged sitting. Furthermore, 26.9% want more offers for prevention of substance abuse. About 60% wish for more offers regarding various networking opportunities. Many suggestions regarding setting design and specific offers were provided in the open comments. Conclusion SHP is seen very positively and should be increased, mainly regarding mental health, nutrition, and exercise. A possibility might be to focus on information and competence development at the start of their studies and then complement it with further specifics later. Schlüsselwörter Universität Fachhochschule Pädagogische Hochschule Bedürfnisse Einstellungen Keywords University University of Applied Sciences University College of Teacher Education Needs Attitudes http://dx.doi.org/10.13039/501100009968 Tiroler Wissenschaftsförderung UNI-0404-2156 Nöhammer Elisabeth ==== Body pmcInsgesamt studierten 2020/2021 in Österreich 387.775 Personen [24]. Zwar gelten Studierende meist als eher jung und gesund, ihre Gesundheit ist jedoch oft schlechter als die von Vergleichsgruppen [7] und teilweise stärker herausgefordert [26]. Die Notwendigkeit von Gesundheitsförderung für Studierende wurde während der Pandemie deutlich [20], ist in Österreich aber noch nicht sehr verbreitet. Um gute Angebote zu ermöglichen, sollten diese den Erwartungen und Bedürfnissen der Zielgruppe entsprechen. Hintergrund Nur wenige Hochschulen in Österreich engagieren sich im Bereich der studentischen Gesundheitsförderung. An der medizinischen Universität Graz bestehen beispielsweise gute Erfahrungen mit Wahlfächern zum Thema Gesundheitsförderung [25]. An der Fachhochschule Kärnten [13, 14, 18] wird ebenfalls ein Fokus auf Studierendengesundheit gelegt. Gründe für die wenig ausgeprägte Verbreitung sind die meist geringen externen Fördermöglichkeiten sowie das Bestehen spezialisierter, aber isoliert agierender Einrichtungen für Bewegung, psychologische Beratung und Ernährung von Universitätsangehörigen. Die österreichweit sieben Universitätssportinstitute (USI; [4]) und die an sechs Standorten verfügbare psychologische Studierendenberatung [3] sind dafür gut etabliert. Vielfach wird auch in der Gastronomie auf Nachhaltigkeit geachtet, beispielsweise den Mensen [6]. Eine kombinierte Betrachtung bzw. ein übergreifendes Management von Gesundheitsförderung für Studierende liegt jedoch nicht vor. Dies wäre ratsam, da Gesundheitsförderung einen verschränkten Ansatz aus salutogener Gestaltung der Lebenswelt (hier: Setting Universität) sowie der Stärkung bzw. Verbesserung des persönlichen Gesundheitsverhaltens zusammensetzt [27]. Die Relevanz von studentischer Gesundheitsförderung (SGF) wurde v. a. in der Pandemie deutlich [20]. Einige österreichische Hochschulen setzten während der Pandemie Befragungen zur Belastung durch Online-Lehre um [20]. Hier wurden die Notwendigkeit psychischer Gesundheitsförderung sowie die Bedeutung von Schulungen der digitalen Kompetenz evident. War vor der SARS-CoV-2-Pandemie („severe acute respiratory syndrome coronavirus 2“) der Bedarf an SGF unklar, ist er nun als erhöht zu erwarten, da wichtige Lebensaspekte in der Pandemie stark beeinträchtigt wurden [8, 11]. Dies kann zu einer Gesundheitsgefährdung führen, wogegen die SGF ressourcenstärkend wirken kann. Das Angebot von SGF könnte auch zu einer höheren Attraktivität der anbietenden Hochschulen führen, was im Kontext der Studienplatzfinanzierung [1] für die Institutionen möglicherweise von Interesse ist. Um von der Zielgruppe genutzt zu werden, sollte die SGF jedoch deren Erwartungen und Bedürfnissen entsprechen. Die vorliegende Arbeit geht daher der Frage nach den Einstellungen, Wünsche und Nutzungskriterien bzgl. SGF seitens der Studierenden nach. Methode Literaturbasiert wurde ein Fragebogen erstellt und über die Plattform LimeSurvey (Survey Services & Consulting, Hamburg, Deutschland) online verfügbar gemacht. Die Nutzung war auf Deutsch und Englisch möglich. Um einen möglichst umfassenden Überblick hinsichtlich der Einstellungen und Wünsche der Studierenden zur SGF zu erhalten, wurden alle österreichischen Hochschulen zur Teilnahme an der Erhebung eingeladen. Sie wurden zunächst über die Erhebung informiert und bei einer Teilnahmeentscheidung gebeten, den Link zum Online-Fragebogen an die Studierenden weiterzuleiten. Dies erfolgte entweder über zuständige Verwaltungsstellen, die Hochschülerschaft oder das Rektorat bzw. zuständige Vizerektorat. Sowohl für die Hochschulen als auch die Studierenden war die Teilnahme völlig freiwillig. Die Studierenden nahmen anonym teil und konnten die Beantwortung der Fragen erst nach Bestätigung eines „informed consent“ beginnen. Die im Juni 2022 abgeschlossene Querschnitterhebung umfasste neben Fragen zur studentischen Gesundheitsförderung auch Themen wie den „impact“ der Pandemie und wurde seitens der freiwilligen, institutionellen Ethikkommission, dem Research Committee for Scientifc Ethical Questions (RCSEQ) der Privatuniversität UMIT TIROL sowie der fh gesundheit, unter der GZ 2987/21 bearbeitet. In der RCSEQ-Stellungnahme vom 05.10.2021 zu GZ 2987/21 wurde bestätigt, dass „an diesem Forschungsvorhaben keine besonders schutzwürdigen Personen beteiligt sind bzw. keine besonderen Kategorien personenbezogener Daten verarbeitet werden“. Knapp über 40 quantitative Items und mehrere offene Fragen erhoben die Einstellung zu und Nutzung von SGF, Nutzungskriterien, Wünschen und Bedürfnissen sowie Auswirkungen von SGF. Die Items waren von „trifft zu“ bis „trifft nicht zu“ 5‑stufig nach Likert bzw. ordinalskaliert, inklusive der Möglichkeit einer neutralen Kategorie („weder/noch“). Wo erforderlich, gab es die zusätzliche Kategorie „nicht verfügbar“. Beispielitems:Ich weiß über die Angebote der studentischen Gesundheitsförderung an meiner Hochschule Bescheid. Ich finde die Idee von Gesundheitsförderung für Studierende gut. Ich möchte in meiner Freizeit keine gesundheitsfördernden Angebote der Hochschule nutzen. Ich wünsche mir für die Zukunft mehr Angebote zur studentischen Gesundheitsförderung. Offene Fragen („Sonstiges: bitte nennen“) gaben den Teilnehmenden die Möglichkeit, eigene weitere Anregungen zu Unterstützungsangeboten im Rahmen der SGF im Allgemeinen, bezogen aus Bewegung und Sport sowie hinsichtlich sozialer Aktivitäten zu beschreiben. Ergebnisse Die Auswertung der Daten erfolgte deskriptiv unter Verwendung der Software SPSS® Version 27. Insgesamt liegen 4600 Zugriffe mit Dateneintragung vor. Für die Fragenblöcke zu SGF kann auf ein n von 3687 bis ca. 3660 für allgemeine Themen zurückgegriffen werden, bei konkreten Maßnahmenwünschen auf je ca. 3240–3230 Antworten. Zu letzteren wurden nur Personen befragt, die sich in Zukunft mehr SGF-Angebote wünschen bzw. dazu nicht eindeutig konträr eingestellt sind (Splittingfrage). Weiblich sind 72,9 % der Befragten, 26,3 % männlich und 0,7 % divers. Der Großteil (81,2 %) ist unter 30 Jahren, die meisten (44,8 %) zwischen 21 und 25 Jahren alt. Die meisten (64,2 %) studieren im Bachelorstudium. Damit zusammenhängend geben 19 % an im ersten, 30,5 % im zweiten oder dritten Semester zu studieren. Im Folgenden werden die Ergebnisse zu Einstellung und Angebot, Nutzung(sbedingungen) sowie Wünschen dargelegt. Die jeweils angegebenen kumulierten Prozentwerte betreffen die kombinierten Kategorien von „trifft zu“ und „trifft eher zu“ mit der jeweils entsprechenden Anzahl an Personen, welche eine dieser beiden Antwortoptionen wählten. Einstellung und Angebot Insgesamt finden 90,6 % (n = 3340) die Idee von SGF gut, ein entsprechendes Angebot finden jedoch nur 49,8 % (n = 1827) an ihrer Hochschule vor. Entsprechend gering ist der Anteil derer, die über das Angebot der Hochschule Bescheid wissen (26,9 %; n = 991) bzw. wissen, wo sie darüber Informationen finden (30,9 %; n = 1137). 24,9 % (n = 916) empfinden das Angebot ihrer Hochschule interessant, nur 10 % (n = 367) nutzten es bisher, bei 3,6 % (n = 134) ist dies derzeit der Fall. Nutzung und Nutzungsbedingungen Das Sportangebot der eigenen oder einer anderen Hochschule wird wenig genutzt (7,1 % [n = 260] bzw. 7,6 % [n = 278]), die psychologische Studierendenberatung wird von 5 % (n = 184) in Anspruch genommen. 3,7 % (n = 134) fühlen sich durch SGF im alltäglichen Leben, 4,6 % im Hochschulleben (n = 168), 3 % (n = 110) im beruflichen Leben unterstützt. Es fühlen sich 61,4 % (n = 2258) zeitlich zu eingespannt, um SGF zu nutzen und insgesamt 32,6 % (n = 1196) möchten kein SGF-Angebot in der Freizeit in Anspruch nehmen und 72,4 % (n = 2657) decken ihre gesundheitlichen Bedürfnisse außerhalb der Hochschule ab. Generell kein Interesse an SGF äußern 19,3 % (n = 710), 45,5 % (n = 1668) nehmen bei für sie interessanten Angeboten teil. Studienkolleg:innen zu treffen motiviert 38,5 % (n = 1413) zur Teilnahme, 13,8 % möchten keine Kommiliton:innen bei SGF antreffen (n = 507). Die einfache Integration in den Alltag ist für 67 % (n = 2454) wichtig, ein kostenloses Angebot für 48,2 % (n = 1765). Insgesamt 20,9 % (n = 765) möchten SGF online, 35,4 % (n = 1295) nur in Präsenz, 76,7 % (n = 2807) sprechen sich für eine Kombination aus. Wünsche In Zukunft mehr Angebote der SGF wünschen sich 56,7 % (n = 2076). Wie oben erwähnt, wurden Personen, die bei dieser Frage „trifft nicht zu“ (n = 388) angegeben hatten, zur Spezifizierung von Wünschen nicht mehr befragt. Die Angaben im Folgenden beziehen sich daher nur auf die (n = 3272), welche „trifft zu“, „trifft eher zu“, „weder/noch“ oder „trifft eher nicht zu“ angegeben hatten, um eine maximale Abdeckung der nicht absolut konträr eingestellten Personen zu erreichen. Gewünscht werden v. a. Angebote zu seelischem Wohlbefinden (77,6 %; n = 2522), Entspannungstrainings (74,2 %; n = 2409), Mentoring/Coaching (66,5 %; n = 2158), Zeit- (63,5 %; n = 2060) und Stressmanagement (77,6 %; n = 2120). Sport und Bewegung sollte mehr Unterstützung erfahren (67 %; n = 2171), ebenso die Themen Ergonomie (Lern‑/Arbeitsplätze einrichten; 61,4 %; n = 1981) sowie Ausgleich zum Sitzen (76,2 %; n = 2461). Mehr Suchtprävention wird von 26,9 % (n = 872) gewünscht. Ernährung als allgemeines Thema aufzugreifen wird von 64,4 % (n = 2079) stärker angeregt, Unterstützung hinsichtlich schneller und gesunder Ernährung im Studienalltag von 76,8 % (n = 2485), von 67,1 % (n = 2167) zu Brain- und Powerfood. Die Ausweitung sozialer Angebote wird ebenfalls angeraten. 62,2 % (n = 2007) wünschen sich im Rahmen der SGF mehr Unterstützung zu Vernetzungsmöglichkeiten von Interessensgruppen, 59,2 % bzgl. Fachgruppen (n = 1909), 47,4 % (n = 1531) für Lerngruppen. 48,1 % (n = 1554) würden vermehrte fachliche Diskussionsrunden wie Ringvorlesungen o. ä. begrüßen, 35,1 % (n = 1132) das Angebot für ehrenamtliches Engagement für die Hochschule. Viele weitere Anmerkungen, Empfehlungen und Konkretisierungen der Angebote (z. B. bestimmte Sportarten oder Ernährungsangebote) werden in offenen Kommentaren gegeben. Ein Überblick darüber wird im Folgenden gegeben. Die Studierenden wünschen sich im Rahmen des Studiums Sensibilisierung für ihre Gesundheit und Gesundheitsthemen im späteren Berufsalltag, um Problemen vorzubeugen. Zu Beginn des Studiums wird mehr praktische Information zum Ablauf eines Studiums erhofft: zur Selbstorganisation, Lernstrategien, zu Anlaufstellen für die auftretenden Fragestellungen – insbesondere auch bei psychischen Problemen. Auch der Suizidprävention sollte Platz geschaffen werden. Die Themen Leistungsdruck (v. a. bei paralleler Berufstätigkeit und/oder Familienverantwortung) und Belastungen durch die Pandemie werden häufig genannt. Dies ist für die Studierenden ein gesamtgesellschaftliches, aber auch hochschulinhärentes Problem, das aus ihrer Sicht dringend diskutiert werden sollte. Als Entlastung wird u. a. vorgeschlagen, dass der Besuch von nur jährlich stattfinden Lehrveranstaltungen nicht Voraussetzung für den Besuch nicht darauf aufbauender Inhalte gelten sollte, der tatsächliche Aufwand eines Studiums und einzelner Lehrveranstaltungen transparenter analysiert und kommuniziert und Anwesenheitspflichten gelockert werden sollten. Eine teilnehmende Person hierzu:„Das [strenge Anwesenheitspflichten, Anm.] erzeugt Stress und führt dazu, dass man auch krank an Lehrveranstaltungen teilnimmt/teilnehmen muss. Man sollte auch mal krank sein dürfen und von den Lehrpersonen/Professoren verstanden werden. Eine Schulung der Professoren würde hier eventuell helfen, bessere Lösungen für Fehlzeiten zu finden.“ Eine Stelle für akute Beratungsnotwendigkeit pro Hochschule sowie Gesundheits-Buddies als Personen, die in gesundheitlichen Fragen und ggf. sogar bei Arztbesuchen begleiten, werden ebenso vorgeschlagen wie Austauschmöglichkeiten in Gruppen:„…für manche kann es beruhigend sein, andere mit ähnlichen Problemen zu sehen, Thema ‚Ich bin nicht allein‘. Andere können das hinderlich finden, weil sie zuerst Ihre Scham über das Thema überwinden müssten.“ Gegenseitige Unterstützung sowie Konfliktmanagement (zwischen Studierenden sowie zwischen Studierenden und Lehrenden) werden als Inhalte von SGF gewünscht, inklusive Anregung für ehrenamtliches Engagement auch ECTS erwerben zu können. Auf die Notwendigkeit von Angeboten zu Kontaktknüpfungen unter anderem über fachliche und studienphasenbezogene Vernetzungsangebote wird insbesondere wegen der Einschränkungen durch die Pandemie deutlich hingewiesen. Betont wird, dass die zeitliche Gestaltung und lokale Erreichbarkeit von SGF generell gegeben und an besonders belastete Gruppen angepasst sein sollte. Nicht zu übersehen ist hier, dass internationale Studierende Angebote auf Englisch benötigen: „I would really appreciate if these opportunities are available in English“. Auch die Bewerbung von SGF wird angesprochen: Diese sollte v. a. auch über digitale Medien erfolgen und in Inhalt und Kommunikation auf Gesundheitsförderung und nicht Selbstoptimierung ausgerichtet sein:„Auch die Formulierungen der Angebote finde ich sehr wichtig. Mich spricht ein Vortrag nach dem Schema ‚5 radikale Tips [sic] um dein (…) zu optimieren!‘ einfach nicht an. Ich möchte mich nicht als Maschine betrachten, dessen [sic] Fehler und Makel es zu optimieren gilt.“ Im Zusammenhang zu Nicht-Diskriminierung wird betont, dass SGF-Angebote entsprechend gestaltet sein müssten, beispielsweise sollten „Sport- und Ernährungsangebote (…) sizeinklusive sein. (…) Führt sonst zu Diskriminierung Übergewichtiger, psychischer Belastung, Förderung von Essstörungen und einem nicht teilnehmen an Gesundheitsangeboten“. Als organisierende Stelle wird eine Person gewünscht, welche die Bedürfnisse der Studierenden versteht. Außerdem angeregt werden genügend Termine und dass nicht zwingend das Erfordernis von Mindestteilnehmerzahlen besteht. Zusätzlich wird betont, dass gute Durchführende der Maßnahmen benötigt werden:„Die vorhandenen Angebote sind teilweise einfach zu schlecht, um für mich interessant zu sein.“ Hinsichtlich Verhältnisprävention wird angemerkt, dass Mensen nicht überall verfügbar und (bestimmte) gesunde Ernährungsweisen auch dort nicht immer möglich sind. Mikrowellenzugänge und Informationen zu gesunder Ernährung werden gewünscht. Auf die Wichtigkeit der ansprechenden und ergonomischen räumlichen Gestaltung der Hochschule wird hingewiesen und dass beispielsweise Aufenthaltsräume verfügbar sein sollten. Eine teilnehmende Person schrieb dazu:„When the space meets student needs (ie. appropriate atmosphere, lighting … access to safe and clean facilities … available learning tools necessary for the studies), then students are provided with the tools to thrive in their learning environment. If these things go neglected, then how should the students be expected to excel in their studies?“ Diskussion Gesundheitsförderung zielt auf die Stärkung von Gesundheitsressourcen ab [2]. Dies erfolgt insbesondere in Lebenswelten und hinsichtlich des individuellen Verhaltens, das von den Möglichkeiten im Setting stark beeinflusst wird [3]. Aus diesem Grund wird empfohlen, die dort für Gesundheit relevanten Lebensbedingungen und Lebensweisen zu bewahren, zu stärken sowie zu erweitern [1]. Dies bedingt einen dualen Ansatz an den Verhältnissen wie Strukturen und Möglichkeiten im Setting sowie am persönlichen Gesundheitsverhalten. Die Bedeutung von ersterem wird von den Studierenden in den offenen Kommentaren deutlich betont. Die SGF wird von den Befragten als sehr positiv und auszubauend angesehen. Auch die Literatur legt letzteres generell und insbesondere postpandemisch nahe [5, 9, 10]. Es ist von pandemiebedingten Verzerrungen bzgl. der Nutzung(smöglichkeit) von SGF im Erhebungszeitraum auszugehen, was auch die geringen Prozentwerte der Nutzung von bestehenden Angeboten und das geringe Unterstützungsempfinden erklären könnte. Der Vergleich mit einer Erhebung nach der Pandemie scheint erforderlich, um hier konkretere Aussagen treffen zu können. Der Pandemiekontext muss als Limitierung der Studie genannt werden. Neben einem möglichen Bias durch selbstberichtete Angaben ist denkbar, dass insbesondere gesundheitsaffine Personen an der Erhebung teilgenommen haben. Andererseits wären diese auch ein großer Teil der ersten Nutzenden von SGF und damit mögliche Multiplikator:innen sowohl während als auch nach Abschluss des Studiums [4]. Viele Studierende decken derzeit ihren Bedarf an Gesundheitsförderung außerhalb der Hochschule. Dies liegt vermutlich an einer Kombination von zeitlichem Druck, aber auch eingeschränkter Verfügbarkeit von SGF in Österreich i. Allg. und während der Pandemie. Das Interesse ist höher als das Nutzungsausmaß, hier sind zukünftig detailliertere Befragungen zu Nutzungsbarrieren nötig [10]. Erste Ansatzpunkte liefert die vorliegende Erhebung. Basierend auf den Daten ist derzeit davon auszugehen, dass aktuelle Angebote in einer Kombination aus Online- und Präsenzmodus weitergeführt werden sollten, aber eine Ergänzung nötig ist. Dazu sind insbesondere nötige Umgestaltungen des Settings zu nennen, die bewegungsförderlich sind und die langen Phasen des Sitzens unterbrechen [16, 21]. Die Studierenden wünschen sich auch Informationen zu Ergonomie, um ihre Lern- und Arbeitsplätze gut gestalten zu können. Adaptierungen der universitären Raumgestaltung und Möblierung könnten angedacht werden [16]. Auffällig ist der Wunsch nach Unterstützung hinsichtlich Stress- und Zeitmanagement bzw. Entspannungstrainings. In Kombination mit dem SGF-Nutzungshemmnis Zeit und den offenen Nennungen deutet dies stark auf eine hohe Arbeitsbelastung der Studierenden hin. Diese ergibt sich in vielen Fällen aus mehreren Lebensbereichen (Studium, Arbeit, Familie; [13, 17]). Nicht nur für diese Gruppen wäre Ressourcenschaffung und -bewusstmachung ratsam [9], wobei die offenen Kommentare zeigen, dass die Reflexionsqualität ausgeprägt ist. Ressourcenorientierte Arbeit [9, 19] wäre auch in den gewünschten Coachings vorstellbar, könnte aber auch Thema im Kontext der fachlichen Vernetzung sein. Ein komplexer, aber phasenweise optimierter Zugang zu Gesundheitsförderung ist denkbar. Studierende sollten bereits früh Zugang zu SGF-Angeboten erhalten [12]. Zu Beginn des Studiums könnte ein Fokus auf gesundheitsrelevanten Informationen und entsprechendem Kompetenzaufbau hinsichtlich des Verhaltens liegen, der später hinsichtlich (Berufs)gruppen spezifiziert wird. Hintergrund hierfür sind entsprechend unterschiedliche Anforderungsausprägungen [2, 9, 12, 13, 17, 22]. Dabei sollte nicht nur eine kontinuierliche Begleitung durch eine gesunde Gestaltung des Settings (unter anderem Mensa, Bewegungsförderung) selbstverständlich sein, auch eine gute Mischung aus Online- und Präsenzangeboten wäre für viele Gruppen hilfreich. Erweiterte private Verantwortung wie Kinder oder Pflege Angehöriger sowie ein berufsbegleitendes Studium führen zu zeitlichen Engpässen, die z. T. über die Integration in das Studium bzw. Online-Angebote gelöst werden könnten. Außerdem können letztere kostengünstig große Populationen erreichen und sehr niederschwellig gestaltet werden [15]. Zusätzlich dazu könnten Kooperationen zwischen Hochschulen die Kosten senken, was angesichts der aktuellen Kostensteigerungen und Inflation sehr relevant sein kann. Allerdings wird von den Studierenden sehr betont, dass der Bedarf an Präsenzangeboten nach und wegen der Pandemie höher ist. In Anlehnung an innerbetriebliche Kommunikation [23] ist jedoch davon auszugehen, dass allgemeine Gesundheitsinformationen sowie generelle Tipps zu großen Anteilen über elektronische Medien und dezentral in Kooperationen zur Verfügung gestellt werden können. Eine Konkretisierung kann in persönlicheren, individuelleren Settings erfolgen. Fazit für die Praxis Viele Studierende decken ihren Bedarf an Gesundheitsförderung außerhalb der Hochschule, empfinden die studentische Gesundheitsförderung (SGF) aber als guten Ansatz. Als nötig sehen sie Veränderungen im Setting, beispielsweise eine bessere zeitliche Gestaltung von Prüfungsphasen und die bessere Ermöglichung von berufsbegleitendem Studieren. Die Notwendigkeit von Unterstützung kann in einem ersten Schritt beispielsweise in der Studieneingangsphase über Informationsweitergabe zu Zeitmanagement, einer SGF-Angebotsübersicht und Workshops zu gesunder Küche entsprochen werden. Generell sollten Lehrraum- und Unterrichtsgestaltung überdacht (Bewegungsförderung, weniger Sitzen) und fachliche Vernetzungsmöglichkeiten an der Hochschule stärker forciert werden. Ein kombiniertes Angebot aus Präsenz- und Online-Möglichkeiten hilft, die SGF in den Alltag zu integrieren und die Kosten-Nutzen-Effekte für alle Beteiligten zu optimieren. Einhaltung ethischer Richtlinien Interessenkonflikt E. Nöhammer gibt an, dass kein Interessenkonflikt besteht. Die Studie wurde von der Tiroler Wissenschaftsförderung (TWF), Grant Nr.: UNI-0404-2156, gefördert. Das Studiendesign wurde vom zuständigen Kollegialorgan geprüft. Es wurde festgehalten (Stellungnahme des RCSEQ – Research Committee for Scientific Ethical Questions [UMIT TIROL/fh gesundheit] Nr. 2987), dass an diesem Forschungsvorhaben keine besonders schutzwürdigen Personen beteiligt sind bzw. keine besonderen Kategorien personenbezogener Daten verarbeitet werden. ==== Refs Literatur 1. Verordnung des Bundesministers für Bildung, Wissenschaft und Forschung über die Umsetzung der kapazitätsorientierten, studierendenbezogenen Universitätsfinanzierung (Universitätsfinanzierungsverordnung – UniFinV); StF: BGBl. II Nr. 202/2018idF. BGBl. II Nr. 397/2021, (2021). https://www.ris.bka.gv.at/GeltendeFassung.wxe?Abfrage=Bundesnormen&Gesetzesnummer=20010276. Zugegriffen: 10.11.2022 2. Apolinário-Hagen J Groenewold S Salewski C Kemper J Krings L Die Gesundheit Fernstudierender stärken. Das GFS-Projekt an der FernUniversität in Hagen: Vom Gesundheitssurvey zur Implementierung von gesundheitsfördernden eHealth-Programmen und mHealth-Apps Präv Gesundheitsf 2018 13 151 158 10.1007/s11553-017-0620-3 3. Bundesministerium für Bildung WuFFMfE, Science and Research Psychologische Hilfe und Unterstützung für Studierende zur aktuellen Krisensituation. https://www.studentenberatung.at/. Zugegriffen: 18.07.2022 4. Bundesministerium für Bildung WuFFMfE, Science and Research Universitätssport. https://www.bmbwf.gv.at/Themen/HS-Uni/Studium/UniSport.html. Zugegriffen: 18.07.2022 5. Fialho P Spatafora F Kühne L Busse H Helmer S Zeeb H Perceptions of study conditions and depressive symptoms during the COVID-19 pandemic among university students in Germany: results of the international COVID-19 student well-being study Public Health Front 2021 10.3389/fpubh.2021.674665 6. Getzinger G Danzer J Lindenthal T Rieg L Thaler J Klimaneutrale Universitäten – eine Initiative der Allianz Nachhaltige Universitäten in Österreich Ecol Perspect Sci Soc 2022 31 2 126 128 7. Grützmacher J, Gusy B, Lesener T, Sudheimer S, Willige J (2018) Gesundheit Studierender in Deutschland 2017. Ein Kooperationsprojekt zwischen dem Deutschen Zentrum für Hochschul- und Wissenschaftsforschung, der Freien Universität Berlin und der Techniker Krankenkasse. https://www.tk.de/resource/blob/2050660/8bd39eab37ee133a2ec47e55e544abe7/gesundheit-studierender-in-deutschland-2017-studienband-data.pdf. Zugegriffen: 11.11.2022 8. Holzer J Lüftenegger M Korlat S Pelikan E Salmela-Aro K Spiel C Higher education in times of COVID-19: University students’ basic need satisfaction, self-regulated learning, and well-being Aera Open 2021 7 23328584211003164 10.1177/23328584211003164 34192126 9. Kirsch A-S Laemmert P Tittlbach S Gesundheitliche Anforderungen und Ressourcen von Studierenden: Eine Studie mit Studierenden der Sportökonomie Präv Gesundheitsf 2017 12 181 188 10.1007/s11553-017-0584-3 10. Klemmt M Heinrichs L Kretzschmann C Reusch A Neuderth S Gesundheitsfördernde Angebote für Studierende in Stadt und Landkreis Würzburg – Bestands- und Bedarfsanalyse Präv Gesundheitsf 2020 15 167 173 10.1007/s11553-019-00745-0 11. Kohls E Baldofski S Moeller R Klemm S-L Rummel-Kluge C Mental health, social and emotional well-being, and perceived burdens of university students during COVID-19 pandemic lockdown in Germany Front Psychiatry 2021 12 441 10.3389/fpsyt.2021.643957 12. Koinzer C Hirsch K Richter EP Berth H Psychische Gesundheit von Studierenden Präv Gesundheitsf 2022 17 178 184 10.1007/s11553-021-00846-9 13. Limarutti A Flaschberger S Mir E Wo steht mir der Kopf? – Herausforderungen von berufsbegleitend Studierenden während der COVID-19-Pandemie HeilberufeScience 2021 12 39 47 10.1007/s16024-021-00351-1 33898155 14. Limarutti A Mir E Ressourcen in Krisenzeiten. Selbst- und Sozialkompetenzen bei berufsbegleitend Studierenden ProCare 2020 25 4 12 13 10.1007/s00735-020-1188-2 15. Lutz-Kopp C Luka-Krausgrill U Honsbrok B Meinhardt-Injac B Gropalis M Development, implementation and first evaluation of an online portal to promote the mental health of university students (me@ JGU) Int J Environ Res Public Health 2021 18 3 1179 10.3390/ijerph18031179 33525749 16. Mann D Helten J Hoffmann SW von Sommoggy J Rüter J Loss J Bewegungsfördernde Bibliotheksarbeitsplätze an Hochschulen Präv Gesundheitsf 2020 10.1007/s11553-020-00806-9 17. Mindermann N Schattschneider R Busch S Studieren mit Pflegeverantwortung? Präv Gesundheitsf 2021 16 225 233 10.1007/s11553-020-00813-w 18. Mir E Maier M Gritsch A Jenull B Die Universität – ein kohärentes Setting? Messung des studentischen Kohärenzgefühls Präv Gesundheitsf 2009 4 66 70 10.1007/s11553-008-0149-6 19. Niewöhner T Hoerdler L Roxel A Meindl M Teuber Z Zielorientierung, Burnout und Engagement im Hochschulkontext: Integration von Zielorientierung in das Study Demands-Resources-Modell Präv Gesundheitsf 2021 17 1 6 10.1007/s11553-021-00840-1 20. Nöhammer E (2022) The lockeddown: Austria. Report on analysis of surveys. Project Website. https://www.healthbit.com/wp-content/uploads/2022/03/report_lockeddown_fin.pdf. Zugegriffen: 11.11.2022 21. Paulus M Kunkel J Schmidt S Bachert P Wäsche H Neumann R Standing breaks in lectures improve university students’ self-perceived physical, mental and cognitive condition Int J Environ Res Public Health 2021 18 4204 10.3390/ijerph18084204 33921094 22. Römer DP Appel J Drews F Rauin U Burnout-Risiko von Lehramts- und Jurastudierenden der Anfangssemester Praev Gesundheitsf 2012 7 203 208 10.1007/s11553-012-0345-2 23. Schick S Interne Unternehmenskommunikation. Strategie entwickeln, Strukturen schaffen, Prozesse steuern 2002 Stuttgart Schäffer-Poeschel 24. Statistics Austria Students in Austria from 2018/19 to 2020/21 2021. http://www.statistik.at/web_en/statistics/PeopleSociety/education/universities/students_studies/029840.html. Zugegriffen: 9. Sept. 2021 25. Vajda C Matzer F Den Umgang mit psychosozialen Krisen im Medizinstudium und späteren Beruf erlernen Präv Gesundheitsf 2017 12 4 280 284 10.1007/s11553-017-0619-9 26. Weber R Ehrenthal JC Pförtner T-K Albus C Stosch C Die schönste Zeit des Lebens? Psychische Belastungen von Studierenden am Beispiel einer deutschen Hochschule Z Klin Psychol Psychother 2020 10.1026/1616-3443/a000573 27. WHO (1986) Ottawa Charter for Health Promotion. First International Conference on Health Promotion, Ottawa, Canada: WHO Divison of Health Promotion, Education and Communication. https://www.euro.who.int/__data/assets/pdf_file/0004/129532/Ottawa_Charter.pdf. Zugegriffen: 11.11.2022
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==== Front J Gen Intern Med J Gen Intern Med Journal of General Internal Medicine 0884-8734 1525-1497 Springer International Publishing Cham 7978 10.1007/s11606-022-07978-4 Concise Research Report Anxiety and Depression Risk Among Healthcare Workers During the COVID-19 Pandemic: Findings from the US Census Household Pulse Survey http://orcid.org/0000-0003-2852-7106 Nguyen Oliver T. MSHI [email protected] 1 Merlo Lisa J. PhD, MPE 2 Meese Katherine A. PhD, MPH 3 Turner Kea PhD, MPH, MA 145 Alishahi Tabriz Amir MD, PhD, MPH 145 1 grid.468198.a 0000 0000 9891 5233 Department of Health Outcomes and Behavior, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL USA 2 grid.15276.37 0000 0004 1936 8091 Department of Psychiatry, University of Florida, Gainesville, FL USA 3 grid.265892.2 0000000106344187 Department of Health Services Administration, University of Alabama at Birmingham, Birmingham, AL USA 4 grid.170693.a 0000 0001 2353 285X Department of Oncologic Science, University of South Florida, Tampa, FL USA 5 grid.468198.a 0000 0000 9891 5233 Department of Gastrointestinal Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL USA 12 12 2022 14 1 9 2022 2 12 2022 © The Author(s), under exclusive licence to Society of General Internal Medicine 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. ==== Body pmcBACKGROUND The COVID-19 pandemic is a persistent stressor for healthcare workers (HCWs) globally. Systematic reviews demonstrate that many HCWs reported heightened levels of anxiety and depressive symptoms during the initial stages of the pandemic.1,2 However, most studies used data from non-US health systems and may reflect systemic differences in COVID-19 response compared to the US health system (e.g., lockdown measures). Quantifying and identifying correlates of pandemic-related mental health burden among US HCWs can inform policy and intervention design as part of the national response to COVID-19-related distress among HCWs. This study assessed the prevalence and determinants of anxiety and depression risk among US HCWs during the COVID-19 pandemic. METHODS We used July 2021–May 2022 U.S. Census Bureau Household Pulse survey data, which included anxiety and depression screenings, demographic factors (sex, race, ethnicity, age, disability, COVID-19 vaccination status), and social determinants of health (living alone, marital status, having children, financial hardship, US region).3 We restricted the sample to HCW respondents (unweighted n=39,566). Healthcare workers were defined as those who worked in hospital, nursing, and residential healthcare facility, pharmacy, and ambulatory healthcare center settings. Anxiety symptoms were measured by the Generalized Anxiety Disorder-2 (GAD-2) instrument. Depressive symptoms were measured by the Patient Health Questionnaire-2 (PHQ-2) instrument. A GAD-2 score of 3 or greater was used to indicate being at risk for anxiety. A PHQ-2 score of 3 or greater was used to indicate being at risk for depression. We conducted multivariable logistic regression models to identify factors associated with being at risk for anxiety and depression when controlling for other factors. To develop nationally representative estimates, we used jackknife replication weights. We interpreted p<0.05 as significant. All analyses were conducted using Stata 17.0 (StataCorp). RESULTS Using the weighted sample (n=9,566,489 HCWs), we estimated that 66.8% were at risk for anxiety and 54.2% were at risk for depression (Table 1). After controlling for other factors, HCWs had greater odds of anxiety risk when reporting having a little (OR=2.53, 95% CI: 2.27–2.81), somewhat (OR=3.60, 95% CI: 3.06–4.23), or very challenging time (OR=7.36, 95% CI: 5.68–9.54) paying their bills compared to those who reported no difficulties. Similarly, HCWs had greater odds of depression risk when reporting having a little (OR=2.67, 95% CI: 2.41–2.97), somewhat (OR=3.87, 95% CI: 3.30–4.54), or very challenging time (OR=7.81, 95% CI: 5.91–10.32) paying their bills compared to those who reported no difficulties. Female HCWs had greater odds of being at risk for anxiety (OR=1.68, 95% CI: 1.50–1.88) and depression (OR=1.60, 95% CI: 1.43–1.79) than male HCWs. HCWs that had at least one disability had greater odds of being at risk for anxiety (OR=2.86, 95% CI: 2.60–3.14) and depression (OR=3.10, 95% CI: 2.83–3.40). We also observed differences in the risk of anxiety or depression by race, age, marital status, and COVID-19 vaccination status (Table 2). Table 1 Sample characteristics (Weighted N = 9,566,489)a–b Characteristic Unweighted n (%) Weighted n (%) At risk for anxiety  No 13,901 (35.1) 3,179,751 (33.2)  Yes 25,665 (64.9) 6,386,738 (66.8) At risk for depression  No 12,512 (31.6) 4,379,908 (45.8)  Yes 27,054 (68.4) 5,186,581 (54.2) Sex  Male 9193 (23.2) 2,652,633 (27.7)  Female 30,373 (76.8) 6,913,856 (72.3) Race  White, alone 32,688 (82.6) 7,229,371 (75.6)  Black, alone 3049 (7.7) 1,189,379 (12.4)  Asian, alone 2235 (5.7) 673,655 (7.0)  Any other race alone, or race in combination 1594 (4.0) 474,084 (5.0) Ethnicity  Not of Hispanic, Latino, or Spanish origin 36,866 (93.2) 8,497,681 (88.8)  Of Hispanic, Latino, or Spanish origin 2700 (6.8) 1,068,808 (11.1) Age (in years)  18–34 4268 (10.8) 1,734,047 (18.1)  35–50 15,579 (39.4) 3,351,496 (35.0)  51–64 11,723 (29.6) 2,392,556 (25.0)  65–74 4011 (10.1) 751,697 (7.9)  75 or older 3985 (10.1) 1,336,693 (14.0) Marital status  Not married 15,881 (40.1) 3,935,941 (41.1)  Married 23,685 (59.9) 5,630,548 (58.9) Lives alone  No 33,498 (84.7) 8,873,773 (92.8)  Yes 6068 (15.3) 692,716 (7.2) Having children in household  None 23,916 (60.5) 5,606,590 (58.6)  Only children under 5 year old 2657 (6.7) 786,325 (8.2)  Only children aged between 5 and 11 years old 3128 (7.9) 764,517 (8.0)  Only children aged between 12 and 17 years old 4847 (12.3) 1,183,875 (12.4)  Children across multiple age groups 5018 (12.7) 1,225,182 (12.8) Disability status  No disability 18,811 (47.5) 4,387,089 (45.9)  Has at least one disability 20,755 (52.5) 5,179,400 (54.1) COVID-19 vaccination status  Yes 37,230 (94.1) 8,804,288 (92.0)  No 2336 (5.9) 762,201 (8.0) Financial hardship  Not at all 22,731 (57.5) 4,718,942 (49.3)  A little bit 9248 (23.4) 2,495,654 (26.1)  Somewhat challenging 4966 (12.6) 1,458,901 (15.3)  Very challenging 2621 (6.6) 892,992 (9.3) US region  Northeast 6801 (17.2) 1,835,746 (19.2)  South 11,587 (29.3) 3,408,240 (35.6)  Midwest 9517 (24.1) 2,319,678 (24.2)  West 11,661 (29.5) 2,002,825 (20.9) Week  Jul 21–Aug 2, 2021 3218 (8.1) 778,755 (8.1)  Aug 4–Aug 16, 2021 3570 (9.0) 859,126 (9.0)  Aug 18–Aug 30, 2021 3623 (9.2) 786,996 (8.2)  Sep 1–Sep 13, 2021 3336 (8.4) 819,848 (8.6)  Sep 15–Sep 27, 2021 3043 (7.7) 821,026 (8.6)  Sep 29–Oct 11, 2021 3002 (7.6) 892,291 (9.3)  Dec 1–Dec 13, 2021 2952 (7.5) 811,426 (8.5)  Dec 29, 2021–Jan 10, 2022 3570 (9.0) 775,115 (8.1)  Jan 26–Feb 7, 2022 3632 (9.2) 792,742 (8.3)  Mar 2–Mar 14, 2022 3869 (9.8) 764,416 (8.0)  Mar 30–Apr 11, 2022 2932 (7.4) 737,518 (7.7)  Apr 27–May 9, 2022 2819 (7.1) 727,229 (7.6) Table 2 Adjusted odds ratios for being at-risk for anxiety and depression among US healthcare professionals (Weighted n = 9,566,489)a–b Characteristic At risk for anxiety OR (95% CI) p-value At risk for depression OR (95% CI) p-value Sex  Male Ref --- Ref ---  Female 1.68 (1.50–1.88) <0.001 1.60 (1.43–1.79) <0.001 Race  White, alone Ref --- Ref ---  Black, alone 0.53 (0.45–0.64) <0.001 0.58 (0.48–0.70) <0.001  Asian, alone 0.68 (0.58–0.79) <0.001 0.73 (0.63–0.85) <0.001  Any other race alone, or race in combination 1.15 (0.93–1.43) 0.199 1.23 (0.97–1.55) 0.086 Ethnicity  Not of Hispanic, Latino, or Spanish origin Ref --- Ref ---  Of Hispanic, Latino, or Spanish origin 0.87 (0.72–1.06) 0.160 0.86 (0.71–1.05) 0.143 Age (in years)  18–34 Ref --- Ref ---  35–50 0.67 (0.59–0.76) <0.001 0.66 (0.59–0.75) <0.001  51–64 0.37 (0.32–0.44) <0.001 0.36 (0.31–0.42) <0.001  65–74 0.23 (0.19–0.27) <0.001 0.23 (0.19–0.27) <0.001  75 or older 0.73 (0.60–0.89) 0.002 0.69 (0.57–0.84) <0.001 Marital status  Not married Ref --- Ref ---  Married 0.85 (0.77–0.94) 0.003 0.81 (0.72–0.91) <0.001 Lives alone  No Ref --- Ref ---  Yes 0.90 (0.79–1.03) 0.133 0.94 (0.79–1.10) 0.421 Having children in household  None Ref --- Ref ---  Only children under 5 year old 1.01 (0.82–1.25) 0.937 0.93 (0.75–1.17) 0.550  Only children aged between 5 and 11 years old 1.16 (0.95–1.41) 0.143 1.12 (0.92–1.36) 0.260  Only children aged between 12 and 17 years old 0.92 (0.79–1.08) 0.303 0.86 (0.73–1.01) 0.063  Children across multiple age groups 1.03 (0.89–1.19) 0.732 0.98 (0.84–1.14) 0.768 Disability status  No disability Ref --- Ref ---  Has at least one disability 2.86 (2.60–3.14) <0.001 3.10 (2.83–3.40) <0.001 COVID-19 vaccination status  Yes Ref --- Ref ---  No 0.46 (0.38–0.55) <0.001 0.45 (0.37–0.54) <0.001 Financial hardship  Not at all Ref --- Ref ---  A little bit 2.53 (2.27–2.81) <0.001 2.67 (2.41–2.97) <0.001  Somewhat challenging 3.60 (3.06–4.23) <0.001 3.87 (3.30–4.54) <0.001  Very challenging 7.36 (5.68–9.54) <0.001 7.81 (5.91–10.32) <0.001 US region  Northeast Ref --- Ref ---  South 0.91 (0.79–1.04) 0.175 0.88 (0.75–1.02) 0.091  Midwest 0.89 (0.77–1.02) 0.085 0.84 (0.72–0.97) 0.021  West 0.99 (0.84–1.16) 0.882 0.98 (0.82–1.17) 0.821 Week  Jul 21–Aug 2, 2021 Ref --- Ref ---  Aug 4–Aug 16, 2021 1.07 (0.90–1.27) 0.459 1.05 (0.87–1.27) 0.587  Aug 18–Aug 30, 2021 1.17 (0.94–1.46) 0.164 1.17 (0.96–1.44) 0.121  Sep 1–Sep 13, 2021 1.21 (1.01–1.44) 0.037 1.20 (1.00–1.44) 0.053  Sep 15–Sep 27, 2021 1.21 (0.95–1.55) 0.127 1.20 (0.95–1.52) 0.128  Sep 29–Oct 11, 2021 0.89 (0.73–1.10) 0.270 0.93 (0.73–1.19) 0.580  Dec 1–Dec 13, 2021 1.06 (0.84–1.33) 0.624 1.03 (0.82–1.29) 0.801  Dec 29, 2021–Jan 10, 2022 1.34 (1.12–1.60) 0.002 1.42 (1.18–1.71) <0.001  Jan 26–Feb 7, 2022 1.01 (0.84–1.21) 0.957 0.99 (0.81–1.20) 0.882  Mar 2–Mar 14, 2022 1.03 (0.84–1.25) 0.805 1.09 (0.89–1.33) 0.421  Mar 30–Apr 11, 2022 0.85 (0.71–1.03) 0.103 0.92 (0.75–1.12) 0.397  Apr 27–May 9, 2022 0.89 (0.74–1.09) 0.259 0.92 (0.75–1.14) 0.459 DISCUSSION Our findings suggest that, during COVID-19, over half of US HCWs were at risk for anxiety or depression based on brief screeners, which exceeded estimates from non-US samples.1,2 These differences in prevalence rates may stem from variability in national responses to COVID-19 (e.g., speed of implementing social distancing requirements, acceptability of masking, and vaccine requirements) and overall sociopolitcal environment. Consistent with findings in the general population,4 factors associated with being at risk for anxiety or depression among HCWs included having financial hardship, younger age, and female sex. Additional efforts are needed to implement and evaluate interventions to improve mental health among US HCWs.5 Our findings suggest that interventions to reduce financial hardship and better support younger and female HCWs and those with disabilities may be needed. Study limitations included self-report bias and limited information on HCW-specific variables (e.g., professional role, clinical setting, patient load)6 and COVID-19 rates and variants. Notwithstanding, this study offers nationally representative estimates of mental health burden among US HCWs during COVID-19 and identifies potential factors to inform future intervention design. Acknowledgements We would like to thank the peer reviewers and their comments that strengthened this manuscript. Author Contribution Conceptualization: Oliver T. Nguyen, Lisa J. Merlo, Katherine A. Meese, Amir Alishahi Tabriz, Kea Turner Methodology: Oliver T. Nguyen, Lisa J. Merlo, Katherine A. Meese, Amir Alishahi Tabriz, Kea Turner Formal analysis and investigation: Oliver T. Nguyen Writing—original draft preparation: Oliver T. Nguyen Writing—review and editing: Lisa J. Merlo, Katherine A. Meese, Amir Alishahi Tabriz, Kea Turner Declarations Conflict of Interest The authors declare that they do not have a conflict of interest. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Vizheh M, Qorbani M, Arzaghi SM, Muhidin S, Javanmard Z, Esmaeili M. The mental health of healthcare workers in the COVID-19 pandemic: A systematic review. J Diabetes Metab Disord. 2020;19(2):1967-1978. 2. Chutiyami M, Cheong AMY, Salihu D, et al. COVID-19 pandemic and overall mental health of healthcare professionals globally: a meta-review of systematic reviews. Front Psychiatry. 2021;12:804525. 3. U.S. Census Bureau. Measuring household experiences during the coronavirus pandemic. https://www.census.gov/data/experimental-data-products/household-pulse-survey.html. Accessed 16 Aug 2022. 4. Wang J, Wu X, Lai W, et al. Prevalence of depression and depressive symptoms among outpatients: a systematic review and meta-analysis. BMJ Open. 2017;7(8):e017173. 5. Zaçe D, Hoxhaj I, Orfino A, Viteritti AM, Janiri L, Di Pietro ML. Interventions to address mental health issues in healthcare workers during infectious disease outbreaks: A systematic review. J Psychiatr Res. 2021;136:319-333. 6. Meese KA, Alejandra Colon-Lopez MA, Dill R, Naik GA, Cendoma MSHA MBA P, Rogers DA. Perceptions of inequitable compensation reductions among healthcare workers during Covid-19. J Health Care Finance. 2021;0(0). http://healthfinancejournal.com/~junland/index.php/johcf/article/view/269. Accessed 17 Aug 2022.
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==== Front J Neurol J Neurol Journal of Neurology 0340-5354 1432-1459 Springer Berlin Heidelberg Berlin/Heidelberg 11513 10.1007/s00415-022-11513-0 Original Communication The insula modulates the effects of aerobic training on cardiovascular function and ambulation in multiple sclerosis Albergoni Matteo 1 Storelli Loredana 1 Preziosa Paolo 125 Rocca Maria A. 125 http://orcid.org/0000-0002-5485-0479 Filippi Massimo [email protected] 12345 1 grid.18887.3e 0000000417581884 Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132 Milan, Italy 2 grid.18887.3e 0000000417581884 Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy 3 grid.18887.3e 0000000417581884 Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy 4 grid.18887.3e 0000000417581884 Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy 5 grid.15496.3f 0000 0001 0439 0892 Vita-Salute San Raffaele University, Milan, Italy 12 12 2022 110 14 9 2022 30 11 2022 1 12 2022 © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Background Impairment of cardiovascular control is common in multiple sclerosis (MS), possibly due to damage of strategic brain regions such as the insula. Aerobic training (AT) targets cardiopulmonary system and may represent a neuroprotective strategy. Purpose To investigate whether insular damage (T2-hyperintense lesions and volume) is associated with cardiovascular fitness (CF) and influences AT effects in MS. Methods Sixty-one MS patients were randomized to an AT intervention group (MS-AT) and a motor training control group (MS-C). At baseline and after training (24 sessions over 2–3 months), peak of oxygen consumption (VO2max), heart rate reserve (HRR), 6-min walk test (6MWT) and whole brain and insula MRI data were collected. Two healthy control (HC) groups were enrolled for CF and MRI data analysis. Results At baseline, MS patients vs HC showed impaired VO2max, HRR and 6MWT (p < 0.001) and widespread gray matter atrophy, including bilateral insula. In MS patients, left insula T2-lesion volume correlated with HRR (r = 0.27, p = 0.042). After training, MS-AT, especially those without insular T2-hyperintense lesions, showed 6MWT improvement (p < 0.05) and a stable insular volume, whereas MS-C showed left insular volume loss (p < 0.001). Conclusions By increasing 6MWT performance, our results suggest that AT may improve walking capacity and submaximal measure of CF in MS patients. Such beneficial effect may be modulated by insula integrity. Keywords Multiple sclerosis Exercise Insula Magnetic resonance imaging Aerobic training http://dx.doi.org/10.13039/501100003196 Ministero della Salute GR-2019-12369599 Preziosa Paolo ==== Body pmcIntroduction Multiple sclerosis (MS) is one of the most common causes of neurological disability in young adults and its incidence and socioeconomic impact are increasing worldwide [1]. Typical clinical manifestations include locomotor, sensory, visual and cognitive impairment; however many other symptoms and signs can occur [2]. Dysfunction of the autonomic system with impairment of cardiovascular function regulation, including attenuated increases in hearth rate (HR) and systolic blood pressure during exercise, has been described in up to 60% of MS patients [3]. Among the brain regions potentially implicated in modulating autonomic system function, the insula represents a key area involved in the regulation of cardiac functions, most likely through its direct projections to the lateral hypothalamic area, the parabrachial nucleus, and the nucleus of the solitary tract [4]. The insula is anatomically and functionally divided into a larger anterior and a smaller posterior lobule by the central sulcus [5]. However, the role of insular sub-regions involved in this autonomic control shows large variations across studies [5–8]. Moreover, some evidence suggests a certain degree of insular lateralization in cardiac representation [7, 8]. Cardiac acceleration has been correlated with the right insula function, while cardiac deceleration with the left one [6]. Aerobic training (AT) directly targets cardiovascular and pulmonary systems [9]. In healthy controls (HC), AT promotes improvements in cardiopulmonary functions, including lowering HR at rest and increasing maximal oxygen consumption (VO2max) [9]. In MS patients, AT may ameliorate aerobic capacity, fatigue, quality of life and emotional aspects [10]. Some studies have suggested that AT may exert neuroprotective effects in aging [11] and several neurological diseases [12], including MS [13], possibly due to the creation of a better environment for CNS-resident cells [14]. In MS, focal demyelinating lesions and irreversible tissue loss frequently affect the insula and are clinically relevant [15, 16]. A higher T2-hyperintense WM lesion volume (LV) in the left insula was associated with a shift of sympathetic–parasympathetic cardiac modulation toward sympathetic predominance, with increased sympathetic blood pressure modulation [15] and prolongation of QT interval duration [16]. Since the insula modulates the function of the autonomic system, it is tempting to speculate that the accumulation of structural damage in this region in these patients may have a detrimental impact on the regulation of cardiovascular functions and on the beneficial effects promoted by AT. By evaluating a quite large cohort of MS patients who were randomized to perform AT or a motor training not influencing the cardiopulmonary system, we explored whether focal WM lesions and volume of the insula were associated with cardiovascular functions and whether insula involvement modulated improvements on cardiovascular fitness (CF) and walking performances promoted by AT. Materials and methods Subjects In this secondary analysis of an interventional ongoing study, 61 MS patients (20 relapsing–remitting and 41 progressive) enrolled between 2017 and 2021 were retrospectively analyzed. To be included they had to be between 18 and 65 years old, right-handed, without additional neurologic, psychiatric, orthopedic or rheumatologic diseases and not engaged in structured physical activity for more than 3 times a week. MS patients had to have an Expanded Disability Status Scale (EDSS) < 7.0, be relapse- and steroid free for at least 3 months and on a stable treatment for at least 1 month. Data from two groups of HC without any neurologic diseases or systemic disorders potentially affecting the CNS recruited at our Unit for ongoing studies were also evaluated. The first group (“HC-clinic”) (n = 20) was selected to analyze baseline cardiopulmonary data, whereas the second one (“HC-MRI”) (n = 60) was selected for MRI analysis. Two different HC groups were selected since subjects included in the HC-clinic group did not perform the MRI acquisition, while subjects of the HC-MRI group did not have data on CF. Clinical evaluation At the beginning and immediately after the training period (see below for details), MS patients underwent clinical evaluation with rating of Expanded Disability Status Scale (EDSS) score, disease duration, clinical phenotype, body mass index (BMI), and cardiopulmonary exercise testing to assess peak of VO2max, maximal peak of HR (HRmax), heart rate reserve (HRR), 6-min walk test (6MWT) and timed 25-foot walk (T25FW). Relapses and adverse events were recorded during the whole training period. At baseline, HC-clinic group underwent the same cardiopulmonary evaluation of patients. Intervention MS patients were randomly allocated to two groups: intervention group (MS-AT, n = 31) and control group (MS-C, n = 30). Both groups performed 24 training sessions of 30–40 min for 2–3 times a week with constant monitoring of HR over a period of 2–3 months. MS-AT performed moderate AT with HR between 55 and 75% of HRmax, while MS-C performed a non-specific motor training in which subjects performed lower limb stretching, passive–active mobilization and balance exercises without a direct involvement of cardiopulmonary system established as no increase of HR during physical effort. MRI acquisition Using a 3.0 Tesla Philips Ingenia CX scanner (Philips Medical Systems) and standardized procedures for subjects positioning and repositioning, the following brain MRI sequences were acquired at baseline and immediately after the training for all MS subjects and at baseline for HC-MRI group: (a) sagittal 3D fluid attenuation inversion recovery (FLAIR), FOV = 256 × 256 mm, pixel size = 1 × 1 mm, 192 slices, 1 mm thick, matrix = 256 × 256, TR = 4800 ms, TE = 270 ms, inversion time (TI) = 1650 ms, echo train length (ETL) = 167, acquisition time (TA) = 6.15 min; (b) sagittal 3D T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE), FOV = 256 × 256, pixel size = 1 × 1 mm, 204 slices, 1 mm thick, matrix = 256 × 256, TR = 7 ms, TE = 3.2 ms, TI = 1000 ms, flip angle = 8°, TA = 8.53 min. MRI analysis Focal T2-hyperintense WM lesions were identified by a fully automated approach using co-registered 3D FLAIR and 3D T1-weighted images as inputs [17]. T2-hyperintense WM LVs were obtained for each patient from their lesion masks, after a careful visual check of the results provided by the automatic segmentation from expert physicians. At baseline, normalized brain volume (NBV), normalized GM volume (NGMV) and normalized WM volume (NWMV) were measured on 3D T1-weighted images, after lesion-filling, using the FSL-SIENAx software. Three masks of bilateral, right and left insula were created merging the six bilateral sub-regions defined by the Human Brainnetome Atlas (http://atlas.brainnetome.org) [18]. T2-hyperintense WM LVs and volumes of right and left insula were extracted by non-linearly registering the insular masks on both FLAIR and 3D T1-weighted images of each subject, respectively. At follow-up, new T2-hyperintense WM lesions were identified by estimating the difference of lesion mask between follow-up and baseline (after co-registration between the two time-points). Longitudinal percentage brain volume change (PBVC) was also obtained from 3D T1-weighted images using SIENA toolbox (FSL version 5.0.9). Voxel-based morphometry (VBM) was applied on T1-weighted images to obtain a voxel-based distribution of regional GM atrophy. VBM was performed using SPM12 (Matlab version 2017) and the Diffeomorphic Anatomic Registration using Exponentiated Lie algebra (DARTEL) toolbox [19]. First, T1-weighted images were segmented into GM, WM and cerebrospinal fluid. An initial template was obtained by aligning GM and WM images for all subjects, then refined by non-linear registration including the DARTEL toolbox. Finally, images were spatially normalized to the MNI space, modulated and smoothed with an 8-mm FWHM Gaussian kernel. Tensor-based morphometry (TBM), as implemented in SPM12, was used to map longitudinal regional volume changes within and between patient groups [20]. The method produces a mid-point average template image after group-wise alignment of each subject’s scans [21]. The rate of volume change was quantified from images of the Jacobian determinants as the ratio between volume differences and the volume in the mid-point average template, which was used as reference: negative values indicate tissue volume loss, positive values volume increase. Statistical analysis Baseline demographic, clinical and MRI measures and their within-group and between-group longitudinal changes were compared using the χ2 Pearson test for categorical variables and Mann–Whitney or t test for continuous variables. In MS patients, correlations between baseline clinical and MRI measures were assessed using Spearman’s partial correlations (age- and sex adjusted). T2-hyperintense WM LVs were log-transformed before statistical analysis. Longitudinal changes of global variables were expressed as baseline normalized percentages. Longitudinal differences of clinical variables between MS-AT and MS-C groups were assessed by a 2 × 2 (group by time) repeated-measures analysis of variance. To explore the impact of insular lesions on baseline CF, MS patients were dichotomized according to the presence (MS with insular lesions [MS-WL]) or absence (MS without insular lesions [MS-WOL]) of T2-hyperintense lesions. To understand the role of insular damage on AT effects, differences of cardiopulmonary variables over time between MS patients with and without baseline insular lesions of the two study groups were assessed by a 2 × 2 (group by time) repeated-measures analysis of variance. Such an analysis was limited to those cardiopulmonary variables that changed after AT or that showed a correlation at baseline with insular damage. All previous analyses were performed using SPSS software (version 25.0) with p-value < 0.05. Using a general linear model and the theory of Gaussian fields [22], voxel-wise between-group comparisons of baseline GM volume as well as within-group and between-group longitudinal changes of GM volumes were performed using SPM12 and an analysis of covariance (ANCOVA), including age, sex, and the intracranial volume as covariates. To limit the analysis to the GM, masks obtained from the GM DARTEL templates, transformed to standard space, smoothed and thresholded at 0.25, were used. Using SPM12, Spearman’s partial correlations (age- and sex adjusted) were performed between baseline clinical and MRI measures as well as between clinical and MRI longitudinal changes. VBM and TBM results were assessed at a threshold of p < 0.05, family-wise-error (FWE) corrected for multiple comparisons and at a threshold of p < 0.001 uncorrected (cluster extension kE ≥ 10). Results Baseline demographic, clinical and MRI findings MS patients and HC clinic did not differ for age (p = 0.08) and sex (p = 0.53), whereas MS patients had impaired VO2max, HRR, 6MWT and T25FW (p < 0.001 for all comparisons) (Table 1).Table 1 Baseline demographic, clinical and MRI variables among MS and HC groups and between MS subgroups MS (n = 61) HC-clinic (n = 20) HC-MRI (n = 60) p* p° MS-AT (n = 31) MS-C (n = 30) p MS-WL (n = 27) MS-WOL (n = 34) p Age Mean (SD) [years] 49.72 (7.57) 45.67 (11.61) 48.57 (8.97) 0.081 0.448 49.06 (7.78) 50.40 (7.42) 0.901 51.78 (5.97) 48.09 (8.36) 0.058 Sex: male/female 23/38 6/14 20/40 0.532 0.615 11/20 12/18 0.716 11/23 12/15 0.427 BMI Median (IQR) [Kg/m2] 22.9 (19.4;15.5) 22.2 (20.5;24.8) – 0.954 – 22.7 (19.5;25.9) 20.1 (19.36;25.9) 0.241 22.89 (20.2;24.9) 22.74 (19.3;27.1) 0.959 EDSS Median (IQR) 4.5 (3.0;6.5) – – – – 4.3 (3.0;6.5) 4.0 (3.0;6.5) 0.611 5.5 (4.0;6.5) 4.0 (2.5;6.0) 0.044 Disease duration Median (IQR) [years] 18.0 (10.9;25.8) – – – – 15.9 (10.9;25.6) 19.0 (11.0;25.8) 0.682 23.0 (13.5;27.0) 15.8 (9.5;21.0) 0.053 Phenotype: RR/P 20/41 – – – – 8/23 12/18 0.238 21/6 20/14 0.171 Disease-modifying treatments: no/first line/second line [n] 7/21/33 – – – – 4/8/19 3/13/14 0.354 1/8/18 6/13/15 0.117 VO2max* Median (IQR) [mL/Kg/min] 15.4 (11.9;18.5) 28.3 (25.6;31.0) –  < 0.001 – 15.7 (11.8;18.7) 16.1 (11.8;18.6) 0.831 13.1 (11.6;17.9) 16.45 (11.9;18.9) 0.066 HRR* Median (IQR) [bpm] 51 (32;63) 14 (9;23) –  < 0.001 – 53 (34;64) 46 (34;63) 0.171 54 (34;65) 47 (32;63) 0.257 6MWT* Median (IQR) [meters] 324 (185;420) 602 (564;659) –  < 0.001 – 314 (175;420) 367 (180;420) 0.163 225 (165;414) 351 (188;420) 0.050 T25FW* Median (IQR) [sec] 6.67 (5.32;10.2) 4.30 (3.85;4.57) –  < 0.001 – 7.44 (5.31;10.45) 6.16 (5.31;10.34) 0.262 7.45 (5.48;10.77) 6.15 (5.25;9.92) 0.080 T2-hypeintense WM LV* Mean (SD) [mL] 6.30 (2.82;12.1) – 0.02 (0.00;0.05) –  < 0.001 5.69 (2.76;12.07) 6.45 (2.79;12.12) 0.885 11.81 (6.70;20.80) 2.91 (1.20;6.40)  < 0.001 NBV* Mean (SD) 1474 (60) – 1550 (42) –  < 0.001 1481 (1433;1518) 1467 (1431;1517) 0.369 1448 (47) 1494 (62) 0.002 NGMV* Mean (SD) [mL] 821 (46) – 859 (35) –  < 0.001 826 (801;850) 816 (800;848) 0.404 800 (47) 837 (38) 0.002 NWMV* Mean (SD) [mL] 653 (34) – 691 (28) –  < 0.001 655 (631;674) 651 (631;673) 0.643 648 (31) 657 (36) 0.283 Left Insula T2-hyperintense LV* Median (IQR) [mL] 0.00 (0.00;1.00) – 0.00 (0.00;0.01) –  < 0.001 0.00 (0.00;1.50) 0.00 (0.00;1.25) 0.499 2.00 (0.00;18.50) 0.00 (0.00;0.00)  < 0.001 Right Insula T2-hyperintense LV* Median (IQR) [mL] 0.00 (0.00;3.00) – 0.00 (0.00;0.01) –  < 0.001 0.00 (0.00;2.00) 0.00 (0.00;3.25) 0.089 5.00 (0.00;11.50) 0.00 (0.00;0.00)  < 0.001 Left Insula volume* Mean (SD) [mL] 6.07 (0.96) – 7.06 (0.75) –  < 0.001 6.64 (5.53;6.74) 6.45 (5.50;6.69) 0.604 5.70 (0.90) 6.37 (0.96) 0.007 Right Insula volume* Mean (SD) [mL] 5.54 (0.87) – 6.38 (0.70) –  < 0.001 6.07 (4.87;6.16) 5.81 (4.87;6.05) 0.387 5.22 (0.83) 5.79 (0.82) 0.009 Statistically significant comparisons are shown in bold BMI body mass index, bpm beats per minute, EDSS Expanded Disability Status Scale, HC-clinic healthy control group for baseline cardiopulmonary and clinical comparison, HC-MRI healthy control group for baseline magnetic resonance imaging comparison, HRR heart rate reserve, IQR interquartile range, Kg kilograms, min minutes, LV lesion volume, mL milliliters, MRI magnetic resonance imaging, MS multiple sclerosis, MS-A MS group that performed aerobic training, MS-C MS group that performed motor control training without direct involvement of cardiopulmonary system, MS-WL MS patients with baseline insula lesions, MS-WOL MS patients without baseline insula lesions, NBV normalized brain volume, NGMV normalized gray matter volume, NWMV normalized white matter volume, P progressive, p p-value, RR relapsing–remitting, SD standard deviation, T25FW timed 25-foot walk test, VO2max maximal oxygen consumption, 6MWT six-minute walk test Compared to HC-MRI, MS patients were comparable for age (p = 0.45) and sex (p = 0.62), whereas they showed significant higher brain and insular T2-hyperintense WM LV as well as lower NBV, NGMV, NWMV and bilateral insular volume (p < 0.001 for all comparisons) (Table 1). At baseline, demographic, clinical, cardiopulmonary and MRI measures did not differ between MS-AT and MS-C. In addition, the type of disease-modifying treatments was equally distributed between the two groups of patients (p ≥ 0.163) (Table 1). Compared to MS-WOL, MS-WL showed higher EDSS score (p = 0.044), lower NBV (p = 0.002), lower NGMV (p = 0.002), and lower bilateral insular volumes (p ≤ 0.009). They also showed a trend for older age (p = 0.058), longer disease duration (p = 0.053), lower VO2max (p = 0.066), shorter 6MWT distance (p = 0.050) and longer T25FW (p = 0.080) (Table 1). Baseline VBM findings Compared to HC, MS patients had a widespread pattern of GM atrophy, including sensorimotor, cerebellar, occipital areas, bilateral insula and deep GM nuclei (p < 0.05, FWE) (Fig. 1). No significant differences were found between MS-AT and MS-C or between MS-WL and MS-WOL.Fig. 1 Baseline voxel-based morphometry results. SPM analysis showing significant differences in GM volume (lower volume encoded in blue/light blue color-coded, p < 0.05 family-wise corrected, cluster extent = 10) superimposed on the custom GM template. (a) Clusters showing widespread pattern of lower GM volume in MS patients compared to HC-MRI. (b) The insula masks used for local VBM analysis (left mask in red and right mask in blue), (c) clusters showing lower GM volume within bilateral insula areas in MS compared to HC-MRI. GM gray matter, HC-MRI healthy control group for baseline magnetic resonance imaging comparison, MS multiple sclerosis, SPM statistical parametric mapping Correlations between baseline clinical and MRI findings In MS patients, a higher left insular T2-hyperintense WM LV correlated with a higher HRR (r = 0.27, p = 0.042). A trend towards a correlation between higher right insular T2-hyperintense WM LVs and higher HRR (r = 0.23, p = 0.083) was also found. No other significant correlations among clinical variables and MRI measures were found (Table 2).Table 2 Baseline correlations between MRI measures and clinical cardiopulmonary variables in MS patients VO2max HRR HRrest MWT6 T25FW T2-hyperintense WM LV r-value 0.057 − 0.010 − 0.162 − 0.0204 0.094 p-value 0.668 0.941 0.220 0.125 0.506 NGMV r-value 0.245 0.052 0.170 0.259 − 0.164 p-value 0.077 0.714 0.199 0.061 0.240 Left Insula T2-hyperintense LV r-value − 0.219 0.268 − 0.079 − 0.028 0.038 p-value 0.098 0.042 0.551 0.837 0.791 Right Insula T2-hyperintense LV r-value 0.074 0.230 − 0.123 0.081 0.112 p-value 0.579 0.083 0.354 0.547 0.430 Left Insula volume r-value − 0.480 0.239 0.047 − 0.40 0.148 p-value 0.719 0.071 0.723 0.768 0.294 Right Insula volume r-value − 0.069 0.207 0.054 − 0.046 0.148 p-value 0.606 0.119 0.687 0.743 0.294 Statistically significant comparisons are shown in bold bpm beats per minute, HRrest heart rate at rest, HRR heart rate reserve, IQR interquartile range, Kg kilograms, min minutes, mL milliliters, MS-A Multiple sclerosis (MS) patients that performed aerobic training, MS-C MS group that performed motor control training without direct involvement of cardiopulmonary system, MS-WL-A MS patients with baseline insula lesions that performed aerobic training, MS-WOL-A MS patients without baseline insula lesions that performed aerobic training, MS-WL-C MS patients with baseline insula lesions that performed motor control training, MS-WOL-C MS patients without baseline insula lesions that performed motor control training, WM white matter, NGMV normalized gray matter volume, T25FW timed 25-foot walk test, VO2max maximal oxygen consumption, 6MWT six-minute walk test The GM volume of clusters in fronto-temporo-parietal cortices and the cerebellum, but not in the insula, was significantly correlated with cardiopulmonary variables (r values ranging from 0.434 to 0.504) (Table 3).Table 3 Baseline correlations between voxel-based morphometry results and clinical data (p < 0.001 uncorrected, cluster extension kE ≥ 10) Variable Side Area BA MNI (x y z) kE T-value R-value VO2max L Cerebellum (Crus2) NA − 34 − 80 − 34 724 3.98 0.504 L Middle frontal gyrus 46 − 39 56 14 26 3.83 0.489 R Postcentral gyrus 43 57 − 14 36 74 3.73 0.480 R Fusiform gyrus 37 33 − 57 − 9 22 3.64 0.471 R Superior temporal pole 48 60 4 3 33 3.59 0.465 R Middle temporal gyrus 21 57 − 46 − 3 17 3.54 0.461 L Rolandic operculum° 48 − 57 12 4 21 3.5 0.457 Vermis (7) 18 − 3 − 75 − 18 16 3.38 0.444 HRR L Middle frontal gyrus 46 − 32 20 38 43 3.31 0.437 R Hippocampus 20 34 − 12 − 22 16 3.21 0.425 6MWT R Postcentral gyrus 43 60 − 10 33 310 4.08 0.503 R Rolandic operculum 48 62 8 4 81 3.97 0.492 L Inferior parietal lobule 2 − 51 − 28 48 56 3.52 0.449 L Postcentral gyrus 2 − 44 − 33 50 3.38 0.434 L Rolandic operculum 48 − 57 9 4 22 3.48 0.444 R Superior parietal lobule 7 26 − 63 54 48 3.46 0.442 T25FW R Inferior frontal gyrus (Orb) 11 27 30 − 24 35 3.93 − 0.496 R Inferior parietal lobule 40 32 − 46 54 43 3.49 − 0.451 BA Brodmann area, kE cluster extension, L left, MNI Montreal Neurological Institute, R right, T25FW timed 25-foot walk test, VO2max maximal oxygen consumption, 6MWT six-minute walk test Longitudinal clinical and MRI findings All MS patients completed the training period. No relapses or adverse events were recorded during the training period. Table 4 summarizes longitudinal clinical changes in MS subgroups.Table 4 Longitudinal clinical and cardiopulmonary results in MS subgroups, focus on lesion-based groups in those variables where longitudinal changes or baseline correlations were statistically significant Group (n) Timepoint p-value Baseline Follow-up Delta % Group Time Interaction VO2max Median (IQR) [mL/Kg/min] MS-AT (31) 15.7 (11.8;18.7) 14.6 (11.3;19.0) 5.5 (− 17.5;15.7) 0.91 0.39 0.64 MS-C (30) 16.1 (11.8;18.6) 15.3 (12.0;15.3) 4.7 (− 12.9;13.3) HRR Median (IQR) [bpm] MS-AT (31) 53 (34;64) 52 (38;67) − 2.8 (− 21.4;24.8) 0.93 0.29 0.44 MS-C (30) 46 (34;63) 49 (37;61) 11.7 (− 9.9;37.8) 6MWT Median (IQR) [meters] MS-AT (31) 314 (175;420) 317 (134;424) 5.7 (− 3.3;13.7) 0.01 0.89 0.05 MS-C (30) 367 (180;420) 328 (215;443) 1.4 (− 13.0;6.1) T25FW Median (IQR) [seconds] MS-AT (31) 7.44 (5.31;10.45) 6.62 (5.50;11.36) − 2.0 (− 9.6;8.8) 0.40 0.67 0.09 MS-C (30) 6.16 (5.31;10.34) 6.81 (5.15;9.71) 0.4 (− 6.3;10.2) 6MWT Median (IQR) [meters] MS-WL-AT (13) 252 (162;417) 210 (85;340) 3.1 (− 3.4;13.5) 0.04 0.36 0.05 MS-WOL-AT (18) 347 (188;420) 385 (191;471) 6.4 (3.2;14.9) 6MWT Median (IQR) [meters] MS-WL-C (14) 377 (197;414) 340 (193;363) − 5.7 (− 14.6;1.8) 0.15 0.15 0.06 MS-WOL-C (16) 351 (185;420) 370 (267;460) 4.6 (− 5.8;6.1) HRR Median (IQR) [bpm] MS-WL-A (13) 64 (37;65) 60 (41;73) −  6.3 (− 10.1;23.0) 0.67 0.64 0.49 MS-WOL-A (18) 46 (34;64) 49 (36;56) 1.1 (− 21.8;24.8) HRR Median (IQR) [bpm] MS-WL-C (14) 39 (26;57) 41 (38;56) 2.9 (− 8.9;41.9) 0.47 0.84 0.42 MS-WOL-C (16) 46 (32;63) 51 (31;64) − 0.8 (− 8.5;20.4) Statistically significant comparisons are shown in bold. Delta% = [(follow-up) – (baseline)/(baseline)] × 100 bpm beats per minute, HRR heart rate reserve, IQR interquartile range, Kg kilograms, min minutes, mL milliliters, MS-AT Multiple sclerosis (MS) patients that performed aerobic training, MS-C MS group that performed motor control training without direct involvement of cardiopulmonary system, MS-WL-AT MS patients with baseline insula lesions that performed aerobic training, MS-WOL-AT MS patients without baseline insula lesions that performed aerobic training, MS-WL-C MS patients with baseline insula lesions that performed motor control training, MS-WOL-C MS patients without baseline insula lesions that performed motor control training, T25FW timed 25-foot walk test, VO2max maximal oxygen consumption, 6MWT six-minute walk test At follow-up, all clinical and cardiovascular measures showed a substantial improvement in MS-AT, even though only the 6MWT distance increase was statistically significant (median 6MWT delta =  + 5.7%, in MS-AT), confirmed by group (p < 0.01) and time-group interaction significance level (p < 0.05). Within MS-AT, only 6MWT distance showed a significant improvement for MS-WOL (median 6MWT delta =  + 6.4%) compared to MS-WL (median 6MWT delta =  + 3.1%) patients (p < 0.05) (Table 4). At follow-up, no new T2-hyperintense WM lesions were found in MS patients and PBVC was − 0.19% ± 0.76%. PBVC did not differ between MS-AT (− 0.91% ± 0.82%) and MS-C (− 0.31% ± 0.47%) nor between MS-WL-AT and MS-WL-C (p ≥ 0.133). Within MS-WOL, MS-AT showed a lower brain atrophy (mean PBVC = 0.08% ± 1.01%) compared to MS-C patients (− 0.46% ± 0.54%), although not significant (p = 0.067). Insular volume change did not differ within and between MS-AT and MS-C groups (p ≥ 0.231). TBM findings At follow-up, MS-AT showed increased GM volume in the right middle frontal gyrus and decreased GM volume in cerebellar, temporal and occipital areas. MS-C showed increased GM volume in few clusters within cerebellar and frontal areas and decreased GM volume in several clusters of occipital–temporal, cerebellar and frontal areas as well as bilateral insula (p < 0.01, uncorrected). Compared to MS-C, MS-AT showed significant GM volume increase in frontotemporal regions and GM volume decrease in parieto-occipital areas (Fig. 2).Fig. 2 Longitudinal tensor-based morphometry results. SPM analysis showing significant GM volume changes (increased volumes are encoded in red–yellow, while decreased volumes are encoded in blue–light blue, p < 0.001 uncorrected, cluster extent = 10). (a) Clusters showing GM volume increase within MS-AT group after training. (b) Clusters showing GM volume increase within MS-C group after training. (c) Clusters showing GM atrophy within MS-AT group after training. (d) Clusters showing GM atrophy within MS-C group after training. (e) Clusters showing greater GM volume increase in MS-AT compared to MS-C. (f) Clusters showing greater GM atrophy in MS-AT compared to MS-C. GM gray matter, MS multiple sclerosis, MS-AT MS group that performed aerobic training, MS-C MS group that performed motor control training without direct involvement of cardiopulmonary system, SPM statistical parametric mapping. The arrow in (d) points out the atrophy process experienced by MS-C within left insula area Correlations between longitudinal clinical and MRI findings In MS-AT, greater improvement in 6MWT distance was correlated with more limited left anterior insula volume loss (r = 0.651, p < 0.001 uncorrected). No other correlations were found. Discussion By evaluating cardiopulmonary and MRI data from a cohort of MS patients who underwent rehabilitation, we investigated the role of insular damage in modulating CF and training responses in this condition. At baseline, compared to HC, MS patients showed significantly lower VO2max and 6MWT, higher HRR, especially in the presence of insular lesions, as well as widespread GM atrophy, including the bilateral insula. After training, MS-AT patients showed greater improvement in 6MWT compared to MS-C, especially in MS patients without insular lesions, and a significant association between a longer 6MWT distance and a more limited left anterior insula volume loss. Our study showed that, compared to HC, MS patients had significantly lower VO2max and 6MWT, higher HRR and a widespread pattern of GM atrophy, suggesting that the disease is associated with worse aerobic fitness and walking capacity [23] together with irreversible neurodegeneration [24]. Consistently with previous literature [15, 16], our study shows a crucial role of insular damage on CF, despite the fact that no correlation has been found with HR at rest, but only with HRR, a measure of heart function during maximal physical effort. In MS patients, higher T2-hyperintense WM LV in the left insula, but not global T2-hyperintense WM LV or volumetric data, was significantly associated with higher HRR, indicating worst cardiopulmonary performance. Moreover, although not reaching the statistical significance, MS patients with insular lesions tended to have lower insular volumes, lower VO2max and shorter 6MWT distance, suggesting that insular damage may negatively influence maximal and submaximal indicators of aerobic fitness. Our results should be interpreted cautiously, since MS patients with lesions had more severe disability and structural brain damage that may also contribute to worse CF. However, they may explain, at least partially, the attenuated cardiovascular system response to exercise that is typically seen in MS patients compared to HC [3]. Disappointingly, insular volume was not associated with CF. The inclusion of MS patients with heterogeneous disease course and severity and the small sample size may contribute to explain this negative finding. However, it is tempting to speculate that insular focal WM lesions may be more relevant than atrophy in influencing CF. A disconnection of the insula from other brain regions involved in cardiac autonomic control may be one of the underlying phenomena. This process has been described in other neurological conditions, such as Parkinson disease [25], and it has been shown to contribute to cognitive impairment in MS [26]. Our analysis of the effects of AT confirmed that this rehabilitation strategy may significantly ameliorate aerobic and walking capacity in MS patients [27]. Indeed, MS-AT patients showed a significant improvement in 6MWT compared to MS-C and a trend toward improvement in all the other variables. It is noteworthy that the insula showed a key role in modulating the effects of AT. In particular, MS patients without insular lesions experienced a greater improvement in cardiopulmonary and walking capacity (i.e., 6MWT) after AT compared to those having insular lesions. It is also interesting that in patients who did not perform AT the presence of insular lesions led to a faster process of cardiopulmonary deconditioning over a period of three months (6MWT: − 5.7% vs + 4.6%, HRR: + 2.9% vs − 0.8%). Accordingly, the presence of insular lesions seems to impair the physiological improvement of cardiovascular fitness promoted by AT and may worsen CF in those MS patients not performing aerobic activity. Consistently with previous studies [28], following rehabilitation both groups of MS patients showed dynamic volume modifications of GM areas involved in sensorimotor control, visual processing, and cognitive functions. Several physiological processes, such as synaptic sprouting and plasticity, angiogenesis, as well as changes at axonal, myelin, and non-neuronal cell levels, may concur to explain these volumetric changes following rehabilitative trainings [29]. In line with previous studies [23, 27], these longitudinal MRI results endorse the possible neuroprotective role of AT with a reduced atrophy progression rate in MS patients who performed this type of training. Noteworthy, longitudinal volumetric analysis further supported the relevant interplay between insular structural integrity, CF modulation and response to AT. MS patients who performed AT did not experience insular atrophy and their greater improvement in 6MWT distance was correlated with a more limited progression of insular volume loss. Conversely, MS patients who performed motor training not involving the cardiopulmonary system showed a significant progression of left insular atrophy. The prevailing role of the left compared to the right insula is in line with previous literature [30, 31] showing a stronger link between left rather than right insular lesions after a stroke and cardiovascular dysfunction in human and experimental models, supporting a lateralization of functions in the insula [6]. Moreover, the dominant hemisphere might be more vulnerable to the accumulation of damage for increased excitability and consequent overuse [32]. Our study is not without limitations. We evaluated a relatively small number of MS patients with some heterogeneities in the training protocol, thus possibly limiting our statistical power. However, given the nature of the study, the concomitant COVID-19 pandemic and the time commitment required, it was difficult to enroll a desirable larger number of subjects. For these reasons, our exploratory results should be confirmed on a larger sample. The lack of clinical and MRI longitudinal comparisons from matched HC did not allow to explore the potential effect of different training on HC’s CF and brain structure. Finally, although cortical lesions have been consistently reported in the insular cortex, a specific MRI sequence for their assessment was not available for our patients. In conclusion, this study provides evidence that AT is an effective tool to improve cardiovascular function and walking capacity and to exert neuroprotective effects in MS patients. The insula, especially the left one, can modulate CF and AT responses in MS patients, thus its integrity should be taken into account to optimize the efficacy of AT treatments. Determining insula integrity using MRI can be informative of the possible results the patient can expect from moderate AT. However, further studies are needed to determine the best tailored treatment for patients also taking into account the insula status. Acknowledgements None. Funding This study has been supported by grant from Italian Ministry of Health (GR-2019–12369599). Data availability The dataset used and analyzed during the current study is available from the corresponding author on reasonable request. Declarations Conflicts of interest M. Albergoni has nothing to disclose. L. Storelli declared the receipt of grants and contracts from FISM—Fondazione Italiana Sclerosi Multipla—within a fellowship program (cod. 2019/BR/009). P. Preziosa received speaker honoraria from Roche, Biogen, Novartis, Merck Serono, Bristol Myers Squibb and Genzyme. He has received research support from Italian Ministry of Health and Fondazione Italiana Sclerosi Multipla. M.A. Rocca received consulting fees from Biogen, Bristol Myers Squibb, Eli Lilly, Janssen, Roche; and speaker honoraria from Bayer, Biogen, Bristol Myers Squibb, Bromatech, Celgene, Genzyme, Merck Healthcare Germany, Merck Serono SpA, Novartis, Roche, and Teva. She receives research support from the MS Society of Canada and Fondazione Italiana Sclerosi Multipla. She is Associate Editor for Multiple Sclerosis and Related Disorders. M. Filippi is Editor in-Chief of the Journal of Neurology, Associate Editor of Human Brain Mapping, Associate Editor of Radiology, and Associate Editor of Neurological Sciences; received compensation for consulting services from Alexion, Almirall, Biogen, Merck, Novartis, Roche, Sanofi; speaking activities from Bayer, Biogen, Celgene, Chiesi Italia SpA, Eli Lilly, Genzyme, Janssen, Merck-Serono, Neopharmed Gentili, Novartis, Novo Nordisk, Roche, Sanofi, Takeda, and TEVA; participation in Advisory Boards for Alexion, Biogen, Bristol-Myers Squibb, Merck, Novartis, Roche, Sanofi, Sanofi-Aventis, Sanofi-Genzyme, Takeda; scientific direction of educational events for Biogen, Merck, Roche, Celgene, Bristol-Myers Squibb, Lilly, Novartis, Sanofi-Genzyme; he receives research support from Biogen Idec, Merck-Serono, Novartis, Roche, Italian Ministry of Health, Fondazione Italiana Sclerosi Multipla, and ARiSLA (Fondazione Italiana di Ricerca per la SLA). Ethics approval Approval was received from the institutional ethical standards committee on human experimentation of IRCCS Ospedale San Raffaele for any experiments using human subjects (Protocol number 59/INT/2015). Written informed consent was obtained from all subjects prior to study participation according to the Declaration of Helsinki. ==== Refs References 1. Filippi M Bar-Or A Piehl F Preziosa P Solari A Vukusic S Multiple sclerosis Nat Rev Dis Primers 2018 4 1 43 10.1038/s41572-018-0041-4 30410033 2. Compston A Coles A Multiple sclerosis Lancet 2008 372 9648 1502 1517 10.1016/S0140-6736(08)61620-7 18970977 3. Huang M Jay O Davis SL Autonomic dysfunction in multiple sclerosis: implications for exercise Auton Neurosci 2015 188 82 85 10.1016/j.autneu.2014.10.017 25458432 4. Gogolla N The insular cortex Curr Biol 2017 27 12 R580 R586 10.1016/j.cub.2017.05.010 28633023 5. Oppenheimer S Cechetto D Terjung R The insular cortex and the regulation of cardiac function Comprehensive physiology 2016 Hoboken John Wiley & Sons, Inc. 1081 1133 6. Chouchou F Mauguière F Vallayer O Catenoix H Isnard J Montavont A How the insula speaks to the heart: cardiac responses to insular stimulation in humans Hum Brain Mapp 2019 40 9 2611 2622 10.1002/hbm.24548 30815964 7. Kaada BR Somato-motor, autonomic and electrocorticographic responses to electrical stimulation of rhinencephalic and other structures in primates, cat, and dog; a study of responses from the limbic, subcallosal, orbito-insular, piriform and temporal cortex, hippocampus-fornix and amygdala Acta Physiol Scand Suppl 1951 24 83 1 262 8. Oppenheimer SM Gelb A Girvin JP Hachinski VC Cardiovascular effects of human insular cortex stimulation Neurology 1992 42 9 1727 1732 10.1212/WNL.42.9.1727 1513461 9. Nystoriak MA Bhatnagar A Cardiovascular effects and benefits of exercise Front Cardiovasc Med 2018 5 135 10.3389/fcvm.2018.00135 30324108 10. Halabchi F Alizadeh Z Sahraian MA Abolhasani M Exercise prescription for patients with multiple sclerosis; potential benefits and practical recommendations BMC Neurol 2017 17 1 185 10.1186/s12883-017-0960-9 28915856 11. Chen FT Hopman RJ Huang CJ Chu CH Hillman CH Hung TM The effect of exercise training on brain structure and function in older adults: a systematic review based on evidence from randomized control trials J Clin Med 2020 9 4 10.3390/jcm9040914 12. Mackay CP Kuys SS Brauer SG The effect of aerobic exercise on brain-derived neurotrophic factor in people with neurological disorders: a systematic review and meta-analysis Neural Plast. 2017 2017 4716197 10.1155/2017/4716197 29057125 13. Negaresh R Motl RW Zimmer P Mokhtarzade M Baker JS Effects of exercise training on multiple sclerosis biomarkers of central nervous system and disease status: a systematic review of intervention studies Eur J Neurol 2019 26 5 711 721 10.1111/ene.13929 30734989 14. Consorti A, Di Marco I, Sansevero G. Physical exercise modulates brain physiology through a network of long- and short-range cellular interactions. (1662–5099 (Print)). 15. Winder K Linker RA Seifert F Wang R Lee D-H Engelhorn T Cerebral lesion correlates of sympathetic cardiovascular activation in multiple sclerosis Hum Brain Mapp 2019 40 17 5083 5093 10.1002/hbm.24759 31403742 16. Turri G, Calabrese M, Pancheri E, Monaco S, Gajofatto A, Marafioti V. QTc interval in patients with multiple sclerosis: an inference from the insula of Reil? (1468–1331 (Electronic)). 17. Valverde S Cabezas M Roura E Gonzalez-Villa S Pareto D Vilanova JC Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach Neuroimage 2017 155 159 168 10.1016/j.neuroimage.2017.04.034 28435096 18. Fan L Li H Zhuo J Zhang Y Wang J Chen L The human brainnetome atlas: a new brain atlas based on connectional architecture Cereb Cortex 2016 26 8 3508 3526 10.1093/cercor/bhw157 27230218 19. Ashburner J Friston KJ Voxel-based morphometry–the methods Neuroimage 2000 11 6 Pt 1 805 821 10.1006/nimg.2000.0582 10860804 20. Leow AD Klunder AD Jack CR Jr Toga AW Dale AM Bernstein MA Longitudinal stability of MRI for mapping brain change using tensor-based morphometry Neuroimage 2006 31 2 627 640 10.1016/j.neuroimage.2005.12.013 16480900 21. Ashburner J Ridgway GR Symmetric diffeomorphic modeling of longitudinal structural MRI Front Neurosci 2012 6 197 23386806 22. Friston KJ Holmes AP Poline JB Grasby PJ Williams SC Frackowiak RS Analysis of fMRI time-series revisited Neuroimage 1995 2 1 45 53 10.1006/nimg.1995.1007 9343589 23. Dalgas U Exercise therapy in multiple sclerosis and its effects on function and the brain Neurodegen Dis Manag 2017 7 6s 35 40 10.2217/nmt-2017-0040 24. Andravizou A Dardiotis E Artemiadis A Sokratous M Siokas V Tsouris Z Brain atrophy in multiple sclerosis: mechanisms, clinical relevance and treatment options Auto Immun Highlights 2019 10 1 7 10.1186/s13317-019-0117-5 32257063 25. Fathy YY Hepp DH de Jong FJ Geurts JJG Foncke EMJ Berendse HW Anterior insular network disconnection and cognitive impairment in Parkinson's disease Neuroimage Clin. 2020 28 102364 10.1016/j.nicl.2020.102364 32781423 26. Rocca MA Amato MP De Stefano N Enzinger C Geurts JJ Penner IK Clinical and imaging assessment of cognitive dysfunction in multiple sclerosis Lancet Neurol 2015 14 3 302 317 10.1016/S1474-4422(14)70250-9 25662900 27. Rampello A Franceschini M Piepoli M Antenucci R Lenti G Olivieri D Effect of aerobic training on walking capacity and maximal exercise tolerance in patients with multiple sclerosis: a randomized crossover controlled study Phys Ther 2007 87 5 545 555 10.2522/ptj.20060085 17405806 28. Rocca MA Meani A Fumagalli S Pagani E Gatti R Martinelli-Boneschi F Functional and structural plasticity following action observation training in multiple sclerosis Mult Scler 2019 25 11 1472 1487 10.1177/1352458518792771 30084706 29. Zatorre RJ Fields RD Johansen-Berg H Plasticity in gray and white: neuroimaging changes in brain structure during learning Nat Neurosci 2012 15 4 528 536 10.1038/nn.3045 22426254 30. Min J Farooq MU Greenberg E Aloka F Bhatt A Kassab M Cardiac dysfunction after left permanent cerebral focal ischemia: the brain and heart connection Stroke 2009 40 7 2560 2563 10.1161/STROKEAHA.108.536086 19443809 31. Oppenheimer SM Kedem G Martin WM Left-insular cortex lesions perturb cardiac autonomic tone in humans Clin Auton Res 1996 6 3 131 140 10.1007/BF02281899 8832121 32. Preziosa P Pagani E Mesaros S Riccitelli GC Dackovic J Drulovic J Progression of regional atrophy in the left hemisphere contributes to clinical and cognitive deterioration in multiple sclerosis: a 5-year study Hum Brain Mapp 2017 38 11 5648 5665 10.1002/hbm.23755 28792103
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==== Front J Behav Educ J Behav Educ Journal of Behavioral Education 1053-0819 1573-3513 Springer US New York 9503 10.1007/s10864-022-09503-3 Original Paper A Rapid Assessment of Sensitivity to Reward Delays and Classwide Token Economy Savings for School-Aged Children https://orcid.org/0000-0003-0520-1680 Kim Ji Young [email protected] 12 https://orcid.org/0000-0002-0593-2929 Fienup Daniel M. 2 https://orcid.org/0000-0002-5854-3425 Reed Derek D. 3 https://orcid.org/0000-0001-5995-2610 Jahromi Laudan B. 2 1 grid.29857.31 0000 0001 2097 4281 Psychology Department, Pennsylvania State University—Harrisburg, 777 W Harrisburg Pike, Middletown, PA 17057 USA 2 grid.21729.3f 0000000419368729 Teachers College, Columbia University, New York, USA 3 grid.266515.3 0000 0001 2106 0692 University of Kansas, Lawrence, USA 12 12 2022 124 16 11 2022 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Delay discounting tasks measure the relation between reinforcer delay and efficacy. The present study established the association between delay discounting and classroom behavior and introduced a brief measure quantifying sensitivity to reward delays for school-aged children. Study 1 reanalyzed data collected by Reed and Martens (J Appl Behav Anal 44(1):1–18, https://doi.org/10.1901/jaba.2011.44-1, 2011) and found that 1-month delay choices predicted student classroom behavior. Study 2 examined the utility of the 1-month delay indifference point in predicting saving and spending behavior of second-grade students using token economies with two different token production schedules. Collectively, results showed (a) the 1-month delay indifference point predicted classroom behavior, (b) children who discounted less and had greater self-regulation, accrued and saved more tokens, and (c) a variable token production schedule better correlated with discounting than a fixed schedule. Implications are discussed regarding utility of a rapid discounting assessment for applied use. Keywords Delay discounting Classroom Sensitivity to reward delays Token economy ==== Body pmcIntroduction Delay discounting is a concept within behavioral economics that examines preferences between smaller/sooner and larger/later reinforcers (abbreviated as SSR and LLR, respectively). Accordingly, this concept presents applied implications for constructs such as “delay of gratification” (Mischel, 1983) or tolerance for delayed reinforcers. While behavioral economics researchers study the effects of reinforcer constraints on operant responses (Hursh & Roma, 2016)—typically measured in operant demand—behavioral economists have translated microeconomic concepts to study delay discounting. Delay discounting, defined as the systematic devaluation of reinforcement as a function of increasing temporal delays, quantifies a person’s operant sensitivity to delayed reinforcers. Studying delay discounting involves a variety of procedures, ranging from hypothetical choice arrangements to experiential tasks (see review in Reed et al., 2020); central to all discounting tasks is the measurement of responding toward either SSRs or LLRs. Despite the apparent translational utility of delay discounting in bridging applied behavior analytic concepts and broader constructs outside behaviorism, this topic remains relatively under-researched within applied behavior analysis. Quantifying sensitivity to delayed reinforcement renders it especially conducive to understanding everyday behavior related to constructs such as impulsivity (for a critique of this term, though, see Strickland & Johnson, 2020), which are thought to be associated with myopic reinforcer preferences. Indeed, delay discounting is associated with many maladaptive outcomes of social importance [e.g., myriad health problems (Daugherty & Brase, 2010), psychiatric conditions (Amlung et al., 2019), cigarette smoking (Mitchell, 1999), drug and alcohol abuse (Richards et al., 1999), overeating (Weller et al., 2008), and gambling (Reynolds, 2006)] and findings have shown that these choice patterns are consistent across contexts (Odum, 2011a, 2011b). Shallow discounting is also associated with “delay of gratification,” or what some behavior scientists call “self-control,” which is the behavior of selecting the more advantageous LLR over a less advantageous SSR (Dixon & Tibbetts, 2009). Behavior analysts have thereby proposed that delay discounting may be a promising approach to understanding socially important behavior from an operant perspective, while using concepts and procedures more readily accepted and understood by mainstream psychology (see Critchfield & Kollins, 2001). Outside of applied behavior analysis, the majority of research on delay discounting has been conducted in laboratory settings with adult populations completing hypothetical delay discounting tasks. Nevertheless, studies have shown that younger populations discount delayed rewards (Reed & Martens, 2011) and that discounting relates to real-world outcomes that are of interests to educators and clinicians. Researchers have shown that adolescents discount more compared to adults (Steinberg et al., 2009) and that greater delay discounting correlated with lower IQ (Dougherty et al., 2014) and lower educational attainment (Jaroni et al., 2004). A review of delay discounting studies with participants with a mean age of 12.99 years old or younger showed: (a) the majority of studies used hypothetical choices about money, (b) less than half of the assessments included visual aids for comprehension of choice options, and (c) only one study was conducted in a classroom setting (Staubitz et al., 2018). In an applied behavior analytic example, Reed and Martens (2011) investigated delay discounting in a classroom setting and compared reinforcement delivered immediately after class or in 24 h when the students could exchange for backup reinforcers. The researchers found that for students with higher discounting rates, the delayed rewards were less effective in improving on-task behavior compared to immediate rewards. Given that younger populations discount delayed rewards, additional studies on delay discounting in an applied setting with younger populations are needed to translate the laboratory measures of delay discounting to a more naturalistic setting. The findings can help educators find the optimal use of rewards and schedules of reinforcement to promote delay of gratification in younger populations especially those at higher risk for poor long-term outcomes. Further, delay discounting has clear implications for saving and spending behavior. People set a financial goal but often divert from their initial plan and spend money on smaller, immediately available goods or services at the expense of saving money for a more advantageous, delayed reward. One way to measure children’s saving and spending behavior is by using a classwide token economy system which mimics a real-world economy where consumers (i.e., students) and producers (i.e., teachers) interact to allocate limited resources (i.e., backup reinforcers). Students’ saving and spending behavior can be captured in this process, and researchers can thus use the data to relate it to delay discounting measure. A classwide token economy captures younger students’ spending and saving behavior because these behaviors start to evolve at a young age as children develop the ability to grasp the concept of “temptation” and the consequences of spending sooner on future opportunities (Sonuga-Barke & Webley, 1993). Children between ages of 6 and 12 years start to understand the value of saving and the association between saving and better future opportunity (Te’eni-Harari, 2016). At around 12 years of age, youth formulate and engage in more complex saving and spending strategies (Sherraden et al., 2011). Studies also found that saving behavior in adolescence was associated with adult saving (Ashby et al., 2011) and in general, older children save more money compared to younger children (Mischel & Mischel, 1983). A recent study showed that delay discounting is related to risky financial and household savings behavior for smokers (Snider et al., 2019); however, more studies are needed to understand the relation between delay discounting and saving and spending behavior of younger populations. Understanding children’s saving and spending behavior and relating it to delay discounting can broaden the scope of delay discounting and provide insight into its utility with children, which would inform researchers on the development of interventions aimed to improve long-term delay of gratification and financial decision making. Despite the applicability of delay discounting measures across populations and behavioral problems, and implications for saving and spending behavior, the complex nature of deriving meaningful numbers impedes its widespread use among educators and clinicians (Critchfield & Reed, 2009). Typically, researchers would find several indifference points, which are points at which the value switches from the LLR to the SSR (i.e., the points at which the subjective values of LLR and SSR are equal; Reed et al., 2013), through delay discounting tasks with binary intertemporal choices and use them to find discounting parameters (e.g., k values; see Odum, 2011a, 2011b) through nonlinear modeling (see Gilroy et al., 2017) and area under the discounting curve (AUC; e.g., Myerson et al., 2001) to quantify sensitivity to reward delays. Finding the parameters and AUC involves mathematical equations and a certain level of knowledge in statistics and software (Motulsky & Christopoulis, 2006). Thus, a brief and rapid delay discounting assessment is warranted. The higher-order pattern of choice behavior observed in delay discounting occurs consistently across contexts for adults (Odum, 2011a, 2011b). Since this choice pattern is relatively stable across contexts, a brief assessment of sensitivity to reward delay could be a predictor for socially significant behavior across various contexts. The development of a brief assessment could be especially useful for children as it would measure delayed reward sensitivity across different contexts relevant to this population such as classroom behavior. In response, the current study investigated a Brief Intertemporal Choice Task for applied settings that can be used to assess the degree of delayed reward sensitivity of younger populations. The overall goal was to evaluate the association between delayed reward sensitivity and classroom behavior in children and suggest the potential applied use of the findings. The original study plan included investigating the relation between student saving and spending behavior using a classwide token economy system and delay discounting measures with several indifference points. However, when schools closed as a response to the COVID-19 pandemic during the course of the study, the researchers were only able to complete the delay discounting task at 1-month delay and serendipitously found that the indifference point at 1-month delay may be enough to predict token economy saving and spending behavior for a younger population. Unexpected lines of research and findings like such refer to “discovery research” (Roane et al., 2003) and the serendipitous findings can be meaningful and noteworthy for the scientific community. Therefore, the primary goal of this study was to bridge the gap between basic and applied research on delay discounting by (a) reanalyzing the discounting task data from Reed and Martens (2011; Study 1 of this report), and (b) introducing a rapid assessment called the Brief Intertemporal Choice Task (BRIC Task) to assess the degree of sensitivity to reward delays in a younger population and measure how performance on this task predicts student saving and spending behavior (Study 2 of this report). A secondary goal was to determine individual differences in saving and spending patterns across the different token production schedules for school-aged children and to examine whether individual differences in children’s delay discounting were related to another measure of self-regulation behavior. Study 1 The purpose of Study 1 was to reanalyze discounting task data from Reed and Martens (2011) to evaluate (a) test–retest reliability of indifference points associated with the 1 month delay value used in their assessment for all 46 participants in the classwide intervention (the published study only included discounting data for the 26 students whose data met inclusionary criteria for systematic discounting and were analyzed with nonlinear curve-fitting), (b) correlations between the 1 month delay indifference point and AUC of the overall discounting function, (c) analysis of ED50 of the k values from the 26 participants in the original study, and (d) correlations (for all 46 participants) between the 1 month delay indifference point and their primary dependent variable from the classwide token system: the difference in mean on-task behavior between immediate and delayed token exchanges. Method Discounting Data As described in Reed and Martens (2011), the original study assessed delay discounting and on-task behavior for 46 sixth graders who averaged 12.10 (SD = 0.30) years of age and attended a rural public elementary school. All participants (a) did not have a formal disability classification, (b) were proficient in English, and (c) read independently based on teacher evaluations. The discounting procedure consisted of a rapid titration of binary choices between SSRs and LLRs (monetary; the magnitude of the undiscounted LLR was $100) across delays ranging from 1 day to 4 years. The researchers administered the discounting procedure to each participant twice, with each procedure separated by 1 week. Delay discounting analyses in the original study were limited to the 26 participants meeting the following inclusionary criteria: “if the mean of the indifference points from the three shortest delay conditions exceeded the mean of the indifference points from the three longest delay conditions, with no more than … two instances of increasing indifference points across successive delays” (p. 8). The researchers fitted both the hyperbolic (Mazur, 1987) and hyperboloid discounting (Myerson & Green, 1995) models to render rates of discounting (i.e., k values) to these 26 participants’ discounting by fitting the mean of each participant’s indifference points of the two assessments to the hyperbolic and hyperboloid models. However, all 46 participants returned indifference points for all delays; thus, AUC (see original study) was available for all 46 participants, as well. On-Task Behavior Direct Observation Data The Reed and Martens study (2011) included direct observation of on-task behavior for all 46 participants under both immediate (following the 20-min observation) and delayed (24-h after observation) token exchange delays during a classwide intervention (see original study for specific details). The authors calculated the difference in off-task behavior between the two exchange delay phases of the intervention as a primary dependent variable. Results and Discussion Table 1 displays a summary of the findings of the reanalysis. Reanalysis of the 46 participants’ discounting data from the original Reed and Martens study (2011; i.e., data not reported in their original study) suggested the indifference points and AUC values did not pass the D’Agostino and Pearson normality test, indicating the need for nonparametric statistics. Further reanalysis yielded a median 1-month indifference point of $30.00 (IQR = 7.00 to 70.00) at Time 1, and a median of $50.00 (IQR = 6.25 to 80.00) at Time 2. The median AUC was 0.13 (IQR = 0.04 to 0.24) at Time 1, and a median of 0.12 (IQR = 0.02 to 0.29) at Time 2. The test–retest reliability of the 1-month indifference point was significantly strong, rs = 0.80, p < 0.001, N = 46 (a coefficient between 0.75 and 1.00 indicates “excellent” reliability and clinical significance; Cicchetti, 1994). Note that the reported rs for the 26 participants meeting criteria for systematic discounting in the original study was 0.81; thus, the data from all 46 participants are as reliable as those for the 26 participants subsample in the original study. Similarly, the test–retest reliability of AUC was significant and strong, rs = 0.83, p < 0.001, N = 46. Finally, correlations between the 1-month indifference point and AUC were significant and relatively strong at both Time 1 (rs = 0.45, p < 0.001, N = 46) and Time 2 (rs = 0.58, p < 0.001, N = 46). In sum, it appears the 1-month indifference point is reliable across 1 week, and is a sufficient proxy to an overall AUC.Table 1 Summary of reanalysis of Reed and Martens (2011) Measure Time 1 Time 2 Median 1-month indifference point $30 (IQR = 7.00 to 70.00) $50.00 (IQR = 6.25 to 80.00) Median AUC 0.13 (IQR = 0.04 to 0.24) 0.12 (IQR = 0.02 to 0.29) Correlations between the 1-month indifference point and AUC rs = .45*** rs = .58*** Correlations between the 1-month indifference point and the difference scores between immediate and delayed classroom contingencies rs =  − 0.33* Test–retest reliability of the 1-month indifference point rs = 0.80*** ED50 34.27 days (SD = 40.14) AUC area under the curve, ED effective delay *p < .05; *** p < .001 Reed and Martens (2011) provided k values for the 26 participants meeting inclusion criteria for fitting discounting curves. At the time of their publication, they failed to explore a secondary analysis of discounting rate: ED50. Yoon and Higgins (2008) proposed that the inverse of k renders the “effective delay” (ED) associated with 50% discounting—this ED50 variable is convenient as it provides a simple delay-scaled metric associated with discounting. That is, ED50 permits a precise quantification of the delay (in time-based units like days/weeks) associated with a 50% reduction in the subjective value of delayed reinforcer, which provides an easily communicable metric of delayed reward sensitivity to non-behaviorists. Across the 26 participants’ data from Table 1 of Reed and Martens, ED50 was calculated for the 20 participants with nonzero k values; ED50 was normally distributed (according to the D’Agostino & Pearson test) and ranged from 0.54 to 100 days, with the mean ED50 equal to 34.27 days (SD = 40.14)—approximately equal to 1 month. That ED50 approximated 1 month lends further evidence that the 1-month delay is particularly useful in understanding school-aged students’ discounting and sensitivity to reward delays. To evaluate the potential of a one-time indifference point at the 1-month delay serving as a proxy to sensitivity to reward delay in practice, researchers examined the correlation between the Time 1 indifference points and the difference scores between immediate and delayed classroom contingencies. The correlation was significant and moderate, rs = -0.33, p = 0.026, N = 46, suggesting that higher indifference points (i.e., higher valuation of a reward at 1-month delay) were associated with smaller sensitivity to classroom token delay contingencies. Simply put, participants who featured less differences in on-task behavior between immediate and delayed token exchange schedules also featured higher indifference points. Collectively, these data suggest the relationship between sensitivity to hypothetical 1-month monetary reward delays and classroom behavior in children. In sum, the findings of this reanalysis suggest the 1-month delay from Reed and Martens’ discounting task (2011) appear to be reliable and predictive of classroom behavior. These findings lend promise to the potential use of a single delay discounting task as a rapid assessment of reinforcement delay sensitivity in school-aged children. Study 2 The reanalysis of Reed and Martens (2011) showed that the indifference point at 1-month period significantly related to classroom behavior and adequately proxied participants’ sensitivity to reward delay. The primary purpose of Study 2 was to extend the findings of Study 1 by (a) examining how the 1-month delay from the discounting task predicts school-aged children’s spending and saving behavior in a classwide token economy, and (b) establishing a rapid assessment of reinforcement delay sensitivity in school-aged children, also called the Brief Intertemporal Choice Task (BRIC Task). The secondary purpose was to study individual differences for responding to two different token production schedules. Finally, because laboratory measures of delay of gratification have been linked to children’s self-regulation, or the capacity to resist a prepotent response (e.g., Jahromi et al., 2019), the researchers also investigated whether delay discounting was related to individual differences in teachers’ ratings of children’s self-regulation on a measure often used in mainstream psychology, the Behavior Rating Inventory of Executive Functioning 2 (BRIEF2; Gioia et al., 2015). Method Participants Seventeen second graders (7 female and 10 male students) participated. The participants’ ages ranged from 7.08 to 7.92 (M = 7.54) years old. Four participants had Individualized Education Programs (IEP) with classifications of specific learning disability, autism spectrum disorder, language impairment, and other health impairment with the diagnosis of attention-deficit/hyperactivity disorder (ADHD). One participant qualified for a 504 plan. Of the 17 participants, seven received free/reduced lunch (i.e., an index of a participant’s family’s socio-economic status), and six participants qualified as English-Language Learners (ELL). Fifteen participants had experience with a classwide token economy system the prior school year. Two participants were new to the token economy system and the researcher conditioned tokens in the beginning of the year by pairing tokens with verbal praise and preferred activities and objects. One female participant who was both an ELL and received free/reduced lunch moved schools in the middle of the year. For this participant, we collected data for the first half of the study (i.e., fixed token production schedule and Behavior Rating Inventory of Executive Functioning 2 (BRIEF2) assessment) but did not for the second half of the study (i.e., the variable token production schedule and hypothetical delay discounting assessment). Put simply, we included 17 participants for the fixed token production schedule condition and BRIEF2 (i.e., secondary analysis) but 16 participants for the variable token production schedule condition and the BRIC Task (i.e., primary analysis). Prior to the study, all participants mastered learning money concepts involving bills and coins during math per the second-grade common core standard (2.MD.C.8) and mastered counting to 120 and comparing two two-digit numbers per the first-grade common core standard (1.NBT.A.1 and 1.NBT.B.3, respectively). Setting and Materials The study took place in a public elementary school located in a suburb outside of a large metropolitan area with grades from pre-school to second. All participants were in a second-grade classroom that used a Comprehensive Application for Behavior Analysis to Schooling (CABAS®, Accelerated Independent Learner program; Greer, 1994) model with 18 students, one head teacher, and two teaching assistants. The model incorporates a scientific approach to pedagogy, learning, curriculum, and classroom management, and all instruction is individualized to each student’s repertoire. All token economy sessions took place in the participants’ classroom throughout the day and trade-in took place at the end of each school day. The researchers conducted the BRIC Task at individual tables in the classroom during the school day and teachers completed the BRIEF2 during the same month other measures were collected. Materials for the fixed and variable token production schedule conditions included various tangible prizes for the prize store (i.e., 16 different types of small toys and school supplies), seven plastic prize boxes with numbers 1, 3, 5, 10, 20, 50, and 100 attached, paper money called “criterion cash” with a picture of the school mascot on the tokens (11.0 by 5.6 cm), and token economy data sheets. The researchers also used the Behavior Rating Inventory of Executive Functioning 2 (BRIEF2) Teacher Form as a formal measure of self-regulatory functions (Gioia et al., 2015). Past studies showed that poorer executive functioning skills related to less effective delay of gratification strategies such as more temptation-focused behaviors (Jahromi et al., 2019). The BRIEF2 is an assessment tool designed to be completed by an adult, typically a teacher, who has had extended contact with a child between the ages of 5 and 18 years old. The assessment consists of nine clinical scales (i.e., inhibit, self-monitor, shift, emotional control, initiate, working memory, plan/organize, organization of materials, and monitor) and two validity scales. Using a 3-point Likert-type scale ranging from “Never” to “Often,” teachers reported on how often specific behaviors have been a problem for the student (e.g., “Does not plan ahead for school assignments”). In this study, the researcher used a composite global score. Psychometrically, the BRIEF2 has been reported to have high internal consistency (αs = 0.80–0.98) and test–retest reliability (rs = 0.88 for teachers). The assessment uses normative data with a standardization sample (N = 3,603 total cases) matched by gender, age, ethnicity, and parent education level to US Census statistics (Gioia et al., 2015). In the present study, Cronbach’s alpha for the BRIEF2 was highly reliable (α = 0.94). For the BRIC Task (delay discounting measure), the researcher used PowerPoint slides and a data sheet (Appendix A; from Critchfield & Atteberry, 2003 and Reed & Martens, 2011). Each PowerPoint slide consisted of a written direction, “Would you rather have,” on the top of the screen and had two boxes (7.62 cm X 7.62 cm) underneath it with the two reward values in each box. Each box represented a SSR value and a LLR monetary value. The researchers used the material and data sheet for only 1-month delay due to school closing as a response to the COVID-19 pandemic. Procedure Preference Assessment The researcher used a multiple stimulus without replacement (DeLeon & Iwata, 1996) to identify highly preferred backup reinforcers for the token economy. The researcher rank ordered individual preferences, with the first rank being the most preferred. Once the researcher collected the preference-rank data for each participant, rank orders were averaged across participants. The researcher placed the most preferred item in the box with the highest value and the least preferred item in the box with the lowest value. There were seven boxes, wherein each box represented different costs (i.e., 1, 3, 5, 10, 20, 50, and 100 tokens). Token Economy The researcher conducted the study in a second-grade inclusion classroom using a classwide token economy system. A token economy system was used because tokens can function as an alternative approach to hypothetical choice or money (Reed et al., 2013; Staubitz et al., 2018) and are considered advantageous in that they bridge the delay between behavior and reinforcement (see Hackenberg, 2018)—an important concept in a delay discounting approach to treatment. A recent study that investigated delay discounting with a younger population suggested the need for further investigation in the use of alternative approaches or adaptations for children who may have difficulty understanding hypothetical constructs such as money or delay (Staubitz et al., 2018). Students in classrooms often earn reinforcers and backup reinforcers based on completion or performance—completion means when students earn tokens upon completing a task without consideration for accuracy (e.g., finishing a worksheet) while performance means when students earn tokens depending on completion and accuracy (e.g., completing a worksheet with 100% accuracy). Therefore, the researcher evaluated two different token production schedules, which is the rate at which delivery of tokens are made respective to the number of target behaviors emitted (Hackenberg, 2009; Kazdin & Bootzin, 1972), to evaluate the effects of the different earning schedules on students’ saving and spending behavior. The researcher termed the token production schedule “fixed” for completion because students earned a fixed number of tokens each day while “variable” for performance because the number of tokens earned depended on learning performance that day. Fixed Token Production Schedule. In the fixed token production schedule, each participant received two criterion cash (i.e., tokens) per school day. Each participant received one criterion cash for reading and one for math at the end of each period contingent on completion of all activities for each period. Reading and math periods each lasted approximately 80 min every school day. At the end of each school day 20 min before dismissal time, the researcher called each participant to the prize store contingent on daily assignment completion. Then, the researcher asked, “How many criterion cash do you have today?” After the participant responded with the total number of criterion cash he or she possessed (i.e., remaining criterion cash from previous day plus those earned in the respective days), the researcher let the participant save or spend their criterion cash. If the participant decided to spend, he or she was allowed to select an item in accordance with the price of the item and the tokens the individual had earned. In other words, if the participant had seven criterion cash, he or she had the choice to go to 1, 3, or 5 prize box. Each participant was allowed to purchase one item per day at the end of the day. If the participant decided to save, he or she was allowed to keep the criterion cash earned on the respective day and previous days without exchanging the tokens for a prize. For each participant, the researcher recorded the total number of tokens and the number of tokens spent. The fixed token production schedule was in place for approximately 4 months during the fall semester (September to December). Variable Token Production Schedule. The variable token production schedule procedure was identical to the fixed token production schedule, except that each participant received a variable number of tokens each day depending on the number of learning objectives met. The teachers scripted out the learning objectives for each subject (i.e., reading, writing, and math) prior to the study and modified them depending on each participant’s academic needs. For example, a participant could earn two tokens by demonstrating mastery of adding 2-digit numbers using a number line and expanded form strategy. Each participant received a minimum of 0 tokens and maximum of 10 per day. The variable token production schedule was in place for approximately 3 months during the spring semester (January to mid-March when the school closed due to the COVID-19 lockdown). For each participant, the researcher obtained the mean balance and mean peak point per token production schedule. The mean balance represented an overall number of tokens a participant kept in his/her account reflecting the daily changes in savings or expense, and the mean peak point represented an overall maximum number of tokens a participant accumulated until he/she decided to trade in. The mean balance was calculated by adding the total number of tokens each participant had each day and dividing the sum by the total number of trade-in days. The mean peak point was calculated by adding the “peaks” of each phase and dividing the sum by the total number of trade-in days. The researcher defined a “peak point” as a number that had a smaller preceding and following number in the data string. For example, if a data set showed 2, 4, 6, 8, 4, 6, 8, 10, 2, 4, 6, 2, with each number representing the balance of each day, then the data would have three peaks: 8, 10, 6, and a mean peak point of 8 (range, 6 to 10). Behavior Rating Inventory of Executive Functioning 2 (BRIEF2) Assessment Former teachers of each participant completed the BRIEF2 Teacher Form. The former teachers have had at least 6 months of time spent together during the prior school year. The researcher added the scores for a global score. These scores were translated into normative T scores, which provided information about an individual’s scores relative to the scores to other respondents in the standardization sample (Gioia et al., 2015). Higher global score reflects more problems with self-regulation (Gioia et al., 2015). Brief Intertemporal Choice Task (BRIC Task) The researcher administered the BRIC Task to obtain the indifference point at 1-month delay from the discounting task. The researcher used hypothetical, monetary choices of SSR and LLR and asked each participant a series of questions with binary choices. For each question, the participant was required to choose one of two monetary choices that had a contrasting length of delay and size of reinforcer. The researcher manipulated the amount of SSR values while holding the 1-month LLR delay value constant to determine the points at which each participant changed his or her choice from the LLR to the SSR. There were 22 possible indifference points (Appendix A; from Critchfield & Atteberry, 2003 and Reed & Martens, 2011). All participants started with a binary choice between SSR of $50 and LLR of $100. The researcher provided the vocal antecedent, “Would you rather have $50 right now or $100 in one month?” If the participant chose the $50 available now, the next trial consisted of a smaller amount of money available now against $100 available in one month. However, if the participant chose $100 in one month, the next trial consisted of a larger immediate monetary amount and the delayed $100. The researcher collected data on a data sheet with all possible choices (Appendix A; from Critchfield & Atteberry, 2003 and Reed & Martens, 2011). Then, the researcher derived the subjective value of the $100 (i.e., indifference point) in terms of smaller amount of money available immediately (see Critchfield & Atteberry, 2003; Reed & Martens, 2011). Interobserver Agreement A second observer independently collected data for the purpose of assessing interobserver agreement (IOA) of the delay discounting task. The researchers calculated trial-by-trial IOA by adding the number of binary choices in agreements, dividing by the total number of binary choices of agreements and disagreements and multiplying by 100%. The researchers obtained IOA data for 15 out of 16 BRIC Tasks (94%) with 100% agreement. Results and Discussion Analysis of BRIEF2 and the BRIC Task Table 2 shows the Spearman’s rho correlation among the mean peak point, mean balance, GEC scores, and the indifference point at 1-month delay obtained through the BRIC Task. Given the skewed distribution (i.e., variance was not normally distributed on a bell curve) of the indifference point at 1-month delay and BRIEF2 scores, the researcher conducted a nonparametric Spearman’s rho correlations (rs) to determine whether students with higher mean peak point and mean balance have (a) higher indifference point at 1-month delay and (b) lower BRIEF2 global score. In the fixed token production schedule, there was a significant positive correlation between the indifference point and the mean balance (rs = 0.53, p = 0.04) but marginally significant with the mean peak point (rs = 0.49, p = 0.05). In the variable token production schedule, there was a significant positive correlation between the indifference point and the mean balance (rs = 0.56, p = 0.02) and the mean peak point (rs = 0.59, p = 0.02). Overall, students with higher indifference points were more likely to wait to exchange tokens (i.e., higher mean peak point and mean balance) in both fixed and variable token production schedules. Across both mean peak point and mean balance, the correlation was stronger in the variable token production schedule compared to the fixed schedule. In other words, students who discounted less saved and accrued more, and children’s performance on the BRIC Task had a strong relation with variable token production performances.Table 2 Correlations among mean peak point, mean balance, BRIEF2, and subjective value of $100 at 1-month delay Variable 1 2 3 4 5 6 1. Mean B (Var) 1 2. Mean PP (Var) .80** 1 3. Mean B (Fixed) .55* .73** 1 4. Mean PP (fixed) .67** .76** .96** 1 5. BRIEF2 GEC − .56* − .51* − .59* − .73** 1 6. Subjective value of $100 at 1-month delay .56* .59* .53* 0.49  − 0.27 1 B = Balance, PP peak point, Var variable token production schedule, Fixed fixed token production schedule, BRIEF2 GEC global executive composite score *p < .05, ** p < .01 Students with higher GEC scores (i.e., reported to have more frequent self-regulation problems) were more likely to have a lower mean peak point and mean balance in both fixed and variable token production schedules. In the fixed token production schedule, there was a significant negative correlation between the GEC score and the mean balance (rs = − 0.59, p = 0.01) as well as the mean peak point (rs = − 0.73, p = 0.001). In a variable token production schedule, there was a significant negative correlation between the GEC score and the mean balance (rs = − 0.56, p = 0.02) as well as the mean peak point (rs = − 0.51, p = 0.046). Across both mean peak point and mean balance, the correlation was stronger in the variable token production schedule compared to a fixed schedule. Interestingly, there was not a significant correlation between the indifference point found by the BRIC Task and GEC score (rs = − 0.27, p = 0.31), highlighting that the BRIC Task may capture elements of the delay context unique from other self-regulatory measures. Overall, students with higher GEC scores were more likely to have lower mean peak point and mean balance in both fixed and variable token production schedules. Across both mean peak point and mean balance, the correlation was stronger in the variable token production schedule condition compared to a fixed schedule. In other words, students who have higher self-regulation save and accrue more tokens, and performance on the BRIC Task was highly correlated with variable token production performances. Collectively, higher executive functioning (i.e., better self-regulation) and higher indifference point at 1-month delay maps onto saving more. Mean Peak Point and Mean Balance Figure 1 shows descriptive data on the change of individual participants’ mean balance and peak point when the token production schedule changed from fixed to variable. All students, except for one in the mean peak point and two for mean balance, showed an increase in mean peak point and mean balance when the token production schedule changed from fixed to variable. In a fixed token production schedule, the classwide mean peak point was 12.47 (range 3.57–78.5) and classwide mean balance was 9.77 (range 2.93–51.12). In a variable token production schedule, the classwide mean peak point was 19.20 (range 6–64) and classwide mean balance was 15.70 (range 4.11–33.77).Fig. 1 Individual Change of Mean Peak Point and Mean Balance When Token Production Schedule Changes. Note. This figure shows the individual participant’s change of mean balance and mean peak point when the token production schedule changes from fixed to variable Overall, Study 2 showed that the BRIC Task was a unique evaluation and predicts actual student behavior in token economy systems. Some major findings include: (1) BRIC Task predicts classroom behavior, (2) students who discounted less and had higher self-regulation saved and accrued more tokens, (3) a variable token production schedule better represented saving and spending behavior compared to a fixed token production schedule, and (4) BRIC Task may capture a different element of the delay context than what is tapped by the BRIEF2, which captures a broader range of children’s self-regulation behaviors. General Discussion Delay of rewards is present in many settings including classrooms with younger children (Reed & Martens, 2011). This warrants the need for more translational studies on the application of delay discounting for younger population in applied settings (Staubitz et al., 2018). However, the complex nature of deriving meaningful numbers impedes its widespread use among educators and clinicians (Critchfield & Reed, 2009). The present study attempted to fill the gap in the literature pointed by Staubitz et al. (2018) and introduce a brief assessment of sensitivity to reward delays for children. While other discounting procedures for children show promise in research settings (e.g., Miller, 2019), the current approach leverages a larger body of existing research on the protocol and does not require specific technologies typically afforded to scientists (e.g., survey software). First, the findings from the two studies demonstrated that the delay discounting task at 1-month delay is reliably associated with students’ classroom behavior including on-task behavior and saving and spending of tokens. The results extended the past literature by establishing the association between delay discounting and classroom behavior for younger students (Reed & Martens, 2011). Specifically, the study established an association between the indifference point at 1-month delay and classroom behavior and provided clear avenues for future research. Measuring how children respond to rewards at 1-month delay could function as a proxy to measuring children’s sensitivity to reward delay across different environments since choice making behavior observed in delay discounting is relatively stable across contexts (Odum, 2011a, 2011b). This is not to replace the existing methods to measure delay discounting, but rather add an alternative measure that individuals can use without deriving additional data. The BRIC Task can thereby serve as a valid, alternative tool to measure sensitivity to reward delays. Second, students who discounted less and who were (a) reported by teachers to have higher self-regulation, and (b) saved and accrued more tokens. These findings suggest that hypothetical delay discounting assessments and those from mainstream psychology that capture self-regulation more broadly do show associations with meaningful behavior in applied settings. Critchfield and Kollins (2001) posed a question on whether hypothetical delay discounting assessments translate to or predict observable behaviors reinforced with real rewards. Similar to past studies, (Kirby & Marakovic, 1996; Reed & Martens, 2011; Richards et al., 1999), our findings showed an adequate level of correlation between hypothetical delay discounting task at 1-month delay for children and their responsiveness to delayed classroom rewards in two different token production schedules. Further, to the best of our knowledge, there has not been research that directly tested associations between school-aged children’s spending and saving behavior in token economies and discounting rate and teachers’ reports of self-regulation. Token economies are widely used across educational and clinical settings and have been identified as an effective evidence-based classroom management strategy (Simonsen et al., 2008). This means that the possible application of the findings is extensive. Third, the pattern of descriptive results showed individual changes in response to token production schedule change. Individual students showed higher levels of saving under a variable token production schedule compared to a fixed one. It is possible that students were more motivated to save when they had the opportunity to earn tokens based on their performance. It should be noted that these data were only descriptive. Future studies may want to examine whether factors like student motivation are related to students’ sensitivity to rewards. Implications for Future Research There are several implications for future research. First, the present study suggests the role of the token production schedule or, in other words, response requirements in the preference of SSR or LLR. Past studies showed that preference for the LLR varies across populations and experimental conditions. Some researchers argued that organisms tend to value rewards available sooner rather than later (Hackenberg & Vaidya, 2003; Hyten et al., 1994) and others have argued that students tend to prefer LLR over SSR (DeLeon et al., 2014; Fienup et al., 2011; Ward-Horner et al., 2014). However, some of these studies did not directly manipulate the token production schedule or were not implemented in an applied setting (Hackenberg & Vaidya, 2003; Hyten et al., 1994), and some studies that investigated the response requirements did not use a token economy system (Fienup et al., 2011; Ward-Horner et al., 2014). Thus, future studies should investigate how manipulating the token production schedule in an applied setting affects individuals’ preference for SSR or LLR. From a broader social context, manipulation of the token production schedule may have direct implications on understanding financial decision making. Response requirements for earning a token (i.e., token production schedule) mimic the labor cost required to earn monetary profit. Investigating how different token production schedules map on to individuals’ preference for SSR and LLR may inform us on how these individuals prefer or allocate their responses to saving and spending money. A second implication is the development of an intervention that promotes optimal choice making or behavior consistent with high delay of gratification in educational settings. Previously, researchers have taught individual optimal choice making by immediately delivering large magnitude reinforcers and then progressively increasing the delay across students with developmental disabilities (Vollmer et al., 1999), emotional and behavioral disorders (Staubitz et al., 2020), brain injury (Dixon et al., 2009), and ADHD (Binder et al., 2000). Research also showed that perceived importance of peer and parental attitudes toward saving money help explain children’s saving behavior (Te’eni-Harari, 2016). Given the possible role of peer influence on saving behavior and possibility of teaching optimal choice making behavior, adding a social competition element to this procedure may facilitate the process of improving delayed gratification for individuals with disabilities. For future studies, it may be worth investigating the effects of putting students in teams or competing against the teacher along with the fading procedure on optimal choice making behavior and saving and spending behavior. Third, the BRIC Task may be particularly useful for studying sensitivity to reward delay of younger children because the assessment does not require researchers to exclude participants for analyses. In traditional delay discounting studies, participants not demonstrating a discounting effect (for definition, see Dixon et al., 2006) have been excluded from the final analyses [e.g., a study with adults excluded 15% of data (Critchfield & Atteberry, 2003) and a study with sixth graders only included 56% of data (Reed & Martens, 2011)]. The BRIC Task only involves one delay and does not require the participants to demonstrate a discounting effect. In turn, more participants, especially children beginning to understand the value of saving and long-term benefits (Te’eni-Harari, 2016) and are more likely to show variability in their discounting data, could be included in the analyses of studies relevant to sensitivity to reward delay. Potential Application Ideas One potential use of the brief assessment (BRIC Task) is for educators and clinicians to quantify sensitivity to reward delays or general level of self-regulation without involving complex mathematical equations and knowledge in statistics and software (Motulsky & Christopoulis, 2006). Specifically, our findings suggest that educators working in classrooms with younger populations could use the BRIC Task as a quick measure for individuals’ sensitivity to reward delays or self-regulation. An individual whose indifference point is larger is less sensitive to reward delays. In other words, the larger the indifference point is, the more likely an individual saves tokens for a backup reinforcer and has greater self-regulation. With such information, educators can arrange effective reward systems. If an individual scores higher in the BRIC Task (i.e., higher indifference point), educators could use leaner token production rate which requires greater number of responses to earn a reinforcer. If a student scores lower (i.e., lower indifference point), educators could utilize richer token production rate which requires smaller number of responses to earn a reinforcer and consider using delay fading of LLR to build delay of gratification. Then, educators could systematically fade the number of responses required to earn a reinforcer (i.e., progressively increase the number of responses) to facilitate delay of gratification. These individuals would also be more likely to spend the tokens warranting the need for more frequent token-earn schedule. It should be noted that all phases of the current study were administered and analyzed by the researchers. Therefore, while the BRIC Task has the potential to be applied to other settings, more replications and tests are needed to determine the generalizability of the findings across different applied settings and populations. A future research direction will be to test the social validity of the assessment across practitioners in order to evaluate the ease of use by clinicians and educators. Further, a variable token production schedule (i.e., a schedule that allows individuals to earn tokens on based on performance) is recommended for greater saving behavior. Educators and clinicians should have clients or students earn tokens based on performance rather than completion to encourage saving token behavior. This way, educators can increase token saving, ensure that the client or student comes in contact with the LLR, and potentially enhance delay of gratification in a naturalistic setting. Thus, the saving behavior will come under the control of natural contingencies, facilitating generalization. Limitations The study is not without limitations. First, Study 2 included a small sample size. The study was conducted with 17 students in a single classroom. The small sample size may limit the results obtained from the correlations as well as the generalizability of the findings. However, the goal of the current study was to provide preliminary findings that could inform future research related to classroom behavior and delay discounting in younger children. Despite the small sample size and limitations, the current study provided preliminary findings that could lead to future research with participants recruited across different classrooms and schools. Second, in the classwide token economy procedure, there were limited types of rewards in the prize store. There were 16 types of rewards in total, which resulted in two or three types of items in each prize box. The researcher addressed this limitation by diversifying the colors, shapes, sizes, patterns, and materials of the same item. For example, a yellow pencil used in the preference assessment would represent different colored and patterned pencils. The researcher also rotated the different types of items every two to three days to ensure that the students were not satiated. Moreover, given the natural classroom setting, school holidays and events were inevitable. The class did not have trade-in sessions on these days, and the researchers did not count these days for analysis to keep the data consistent across all students. Further, there were limitations to the implementation of the assessments in Study 2. Initially, the researcher planned to conduct a full hypothetical delay discounting assessment with children but was unable to complete due to school closure as a response to the COVID-19 pandemic. The researchers serendipitously discovered that the 1-month delay can be sufficient enough to predict actual student behavior and inform individuals about school-aged children’s sensitivity to reward delays. While the serendipitous findings are noteworthy, the study would have benefited from doing a full delay discounting assessment. The researchers would have been able to compare the 1-month delay to other delays, further supporting the use of 1-month delay as a proxy for a full delay discounting assessment. Future studies should replicate the procedure with the complete assessment with eight indifference points to compare the delays using the same participant pool. Additionally, in Study 2, the researchers used an average preference instead of individual preferences to identify backup reinforcers preference assessment. Some participants’ lowest-ranked items had a higher cost while some highest-ranked items were lower cost—when examining cost at an individual level. This means that there may have been limited reinforcing value of the backup reinforcers, which means that saving could have been a product of not finding any items valuable. However, 13 out of 17 participants (76%) selected the top-ranked reinforcer as their top-three choices, which means that the top-ranked reinforcer would have had the reinforcing effect for the majority of participants. The remaining four participants (24%) ranked the top-ranked reinforcer as 4th, 6th, 8th, and 8th out of 16 items. The lowest-ranked reinforcer, on the other hand, was selected as the bottom-three choices by only four out of 17 participants (24%), limiting the value of the item associated with low cost. While the top-ranked reinforcer had reinforcing value for most participants, the discrepancy between individual rank ordering and item price should be taken into consideration when interpreting the results. Future studies should also incorporate reinforcer assessments to ensure that preferred items functioned as reinforcers. Another limitation is the lack of treatment fidelity data. Treatment fidelity ensures that the treatment was implemented as planned and eliminates threats to bias (Reichow et al., 2018). Future studies should incorporate a checklist for the token economy and BRIC Task procedures to ensure high levels of treatment fidelity. Also, addition of social validity measure that evaluates teacher preference for the BRIC Task over simple observations would have supplemented the findings regarding the utility of the BRIC Task in educational settings. This way, all consumers of the program contribute to the evaluation of acceptability and viability of the program goals, methods, and outcomes (Schwartz & Baer, 1991). Lastly, implementation of fixed and variable schedule was not systematically manipulated, which may limit the comparison of the two token economy systems. Given that the study was conducted in an educational setting, the researcher implemented the same contingencies across all students in the same class as part of a classwide token economy system. Because the variable token production schedule condition was introduced a few months later, participants may have matured and engaged in more saving behavior since older children save more money compared to younger children (Mischel & Mischel, 1983). Additionally, the fixed token production schedule preceded the variable token production schedule for all participants. This means that the fixed token production schedule could have influenced student responding during the variable token production schedule. To address this problem, future studies should systematically manipulate the system to determine the effects of the different token production schedule on students’ saving and spending behavior. Conclusion Despite the limitations, the two studies demonstrated that the indifference point at 1-month delay can adequately predict classroom behavior and introduced a rapid and brief assessment tool to measure children’s sensitivity to reward delay. The study extended previous research by (a) establishing a translational utility of delay discounting measures to a naturalistic setting, (b) developing an alternative tool that warrants a widened use of delay discounting measures across fields, (c) experimentally demonstrating that children who discount less and have more self-regulation save and accrue more tokens, and (d) comparing the effects of different token production schedule on individual children. The findings may serve as the foundation for the possible future development of an intervention promoting optimal choice for younger population who are at higher risk for poor long-term outcomes. Appendix Example of the BRIC Task Data sheet (from Critchfield & Atteberry, 2003; Reed & Martens, 2011). Note. Republished with permission from John Wiley & Sons. Declarations Conflict of interest We have no known conflict of interest to disclose. Ethical approval We confirm that all procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent The Teachers College, Columbia University IRB board reviewed and approved the study and noted that the informed consent process was not required as the study utilized secondary data. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Amlung M Marsden E Holshausen K Morris V Patel H Vedelago L Naish KR Reed DD McCabe RE Delay discounting as a transdiagnostic process in psychiatric disorders: A meta-analysis JAMA Psychiatry 2019 76 11 1176 1186 10.1001/jamapsychiatry.2019.2102 31461131 Ashby JS Schoon I Webley P Save now, save later? Linkages between saving behavior in adolescence and adulthood European Psychologist 2011 16 3 227 237 10.1027/1016-9040/a000067 Binder LM Dixon MR Ghezzi PM A procedure to teach self-control to children with attention deficit hyperactivity disorder Journal of Applied Behavior Analysis 2000 33 2 233 237 10.1901/jaba.2000.33-233 10885530 Cicchetti DV Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology Psychological Assessment 1994 6 4 284 290 10.1037/1040-3590.6.4.284 Critchfield TS Atteberry T Temporal discounting predicts individual competitive success in a human analogue of group foraging Behavioural Processes 2003 64 3 315 331 10.1016/S0376-6357(03)00129-3 14580701 Critchfield TS Kollins SH Temporal discounting: Basic research and the analysis of socially important behavior Journal of Applied Behavior Analysis 2001 34 1 101 122 10.1901/jaba.2001/34-101 11317983 Critchfield TS Reed DD What are we doing when we translate from quantitative models? The Behavior Analyst 2009 32 2 339 362 10.1007/BF03392197 22478533 Daugherty JR Brase GL Taking time to be healthy: Predicting health behaviors with delay discounting and time perspective Personality and Individual Differences 2010 48 2 202 207 10.1016/j.paid.2009.10.007 DeLeon IG Chase JA Frank-Crawford MA Carreau-Webster AB Triggs MM Bullock CE Jennett HK Distributed and accumulated reinforcement arrangements: Evaluations of efficacy and preference Journal of Applied Behavior Analysis 2014 47 2 293 313 10.1002/jaba.116 24782203 DeLeon IG Iwata BA Evaluation of a multiple-stimulus presentation format for assessing reinforcer preferences Journal of Applied Behavior Analysis 1996 29 4 519 532 10.1901/jaba.1996.29-519 8995834 Dixon MR Jacobs EA Sanders S Contextual control of delay discounting by pathological gamblers Journal of Applied Behavior Analysis 2006 39 4 413 422 10.1901/jaba.2006.173-05 17236338 Dixon MR Tibbetts PA The effects of choice on self-control Journal of Applied Behavior Analysis 2009 42 2 243 252 10.1901/jaba.2009.42-243 19949512 Dougherty DM Charles NE Mathias CW Ryan SR Olvera RL Liang Y Acheson A Delay discounting differentiates pre-adolescents at high and low risk for substance use disorders based on family history Drug and Alcohol Dependence 2014 143 1 105 111 10.1016/j.drugalcdep.2014.07.012 25096271 Fienup DM Ahlers AA Pace G Preference for fluent versus disfluent work schedules Journal of Applied Behavior Analysis 2011 44 4 847 858 10.1901/jaba.2011.44-847 22219534 Gilroy SP Franck CT Hantula DA The discounting model selector: Statistical software for delay discounting applications Journal of the Experimental Analysis of Behavior 2017 107 3 388 401 10.1002/jeab.257 28467023 Gioia, G. A., Isquith, P. K., Guy, S. C., & Kenworthy, L. (2015). Behavior Rating Inventory of Executive Function®, 2nd ed. (BRIEF®2). PAR Inc. Greer RD A systems analysis of the behaviors of schooling Journal of Behavioral Education 1994 4 3 255 264 10.1007/BF01531981 Hackenberg TD Token reinforcement: A review and analysis Journal of the Experimental Analysis of Behavior 2009 91 2 257 286 10.1901/jeab.2009.91-257 19794838 Hackenberg TD Token reinforcement: Translational research and application Journal of Applied Behavior Analysis 2018 51 2 393 435 10.1002/jaba.439 29468686 Hackenberg TD Vaidya M Determinants of pigeons’ choices in token-based self-control procedures Journal of the Experimental Analysis of Behavior 2003 79 2 207 218 10.1901/jeab.2003.79-207 12822687 Hursh SR Roma PG Behavioral economics and the analysis of consumption and choice Managerial and Decision Economics 2016 37 4–5 224 238 10.1002/mde.2724 Hyten C Madden GJ Field DP Exchange delays and impulsive choice in adult humans Journal of the Experimental Analysis of Behavior 1994 62 2 225 233 10.1901/jeab.1994.62-225 7964366 Jahromi LB Chen Y Dakopolos AJ Chorneau A Delay of gratification in preschoolers with and without autism spectrum disorder: Individual differences and links to executive function, emotion regulation, and joint attention Autism 2019 23 7 1720 1731 10.1177/1362361319828678 30795706 Jaroni JL Wright SM Lerman C Epstein LH Relationship between education and delay discounting in smokers Addictive Behaviors 2004 29 6 1171 1175 10.1016/j.addbeh.2004.03.014 15236819 Kazdin AE Bootzin RB The token economy: An evaluative review Journal of Applied Behavior Analysis 1972 5 3 243 372 10.1901/jaba.1972.5-343 Kirby KN Marakovic NN Delay discounting probabilistic rewards: Rates decrease as amounts increase Psychonomic Bulletin and Review 1996 3 1 100 104 10.3758/BF03210748 24214810 Mazur JE Commons ML Mazur JE Nevin JA Rachlin H An adjusting procedure for studying delayed reinforcement Quantitative analyses of behaviour, the effect of delay and of intervening events on reinforcement value 1987 Erlbaum 55 73 Miller JR Comparing rapid assessments of delay discounting with real and hypothetical rewards in children Journal of the Experimental Analysis of Behavior 2019 111 1 48 58 10.1002/jeab.493 30656710 Mischel W Magnusson D Allen VP Delay of gratification as process and as person variable in development Human development: An interactional perspective 1983 Academic Press 149 165 Mischel HN Mischel W The development of children’s knowledge of self-control strategies Child Development 1983 54 3 603 619 10.2307/1130047 Mitchell SH Measures of impulsivity in cigarette smokers and non-smokers Psychopharmacology (berl) 1999 146 4 455 464 10.1007/pl00005491 10550496 Motulsky HJ Christopoulis A Fitting models to biological data using linear and nonlinear regression: A practical guide to curve fitting 2006 GraphPad Software Myerson J Green L Discounting of delayed rewards: Models of individual choice Journal of the Experimental Analysis of Behavior 1995 64 3 263 276 10.1901/jeab.1995.64-263 16812772 Myerson J Green L Warusawitharana M Area under the curve as a measure of discounting Journal of the Experimental Analysis of Behavior 2001 76 2 235 243 10.1901/jeab.2001.76-235 11599641 Odum AL Delay discounting: I'm a k, you're a k Journal of the Experimental Analysis of Behavior 2011 96 3 427 439 10.1901/jeab.2011.96-423 22084499 Odum AL Delay discounting: Trait variable? Behavioural Processes 2011 87 1 1 9 10.1016/j.beproc.2011.02.007 21385637 Reed DD Naudé GP Gelino BW Amlung M Sussman S Behavioral economic considerations of novel addictions and nonaddictive behaviour: Research and analytic methods Cambridge handbook of substance and behavioral addictions 2020 Cambridge University Press 73 86 Reed DD Niileksela CR Kaplan BA Behavioral economics: A tutorial for behavior analysts in practice Behavior Analysis in Practice 2013 6 1 34 54 10.1007/BF03391790 Reed DD Martens BK Temporal discounting predicts student responsiveness to exchange delays in a classroom token system Journal of Applied Behavior Analysis 2011 44 1 1 18 10.1901/jaba.2011.44-1 21541113 Reichow B Barton EE Maggin DM Development and applications of the single-case design risk of bias tool for evaluating single-case design research study reports Research in Developmental Disabilities 2018 79 53 64 10.1016/j.ridd.2018.05.008 29958733 Reynolds B A review of delay-discounting research with humans: Relations to drug use and gambling Behavioural Pharmacology 2006 17 8 651 667 10.1097/FBP.0b013e3280115f99 17110792 Richards JB Zhang L Mitchell SH de Wit H Delay or probability discounting in a model of impulsive behavior: Effect of alcohol Journal of the Experimental Analysis of Behavior 1999 71 2 121 143 10.1901/jeab.1999.71-121 10220927 Roane HS Fisher WW McDonough EM Progressing from programmatic to discovery research: A case example with the overjustification effect Journal of Applied Behavior Analysis 2003 36 1 35 46 10.1901/jaba.2003.36-35 12723865 Schwartz IS Baer DM Social validity assessments: Is current practice state of the art? Journal of Applied Behavior Analysis 1991 24 2 189 204 10.1901/jaba.1991.24-189 1890040 Sherraden MS Johnson L Guo B Elliott W Financial capability in children: Effects of participation in a school-based financial education and savings program Journal of Family and Economic Issues 2011 32 3 385 399 10.1007/s10834-010-9220-5 Simonsen B Fairbanks S Briesch A Myers D Sugai G Evidence-based practices in classroom management: Considerations for research to practice Education and Treatment of Children 2008 31 3 351 380 10.1353/etc.0.0007 Snider SE DeHart WB Epstein LH Bickel WK Does delay discounting predict maladaptive health and financial behaviors in smokers? Health Psychology 2019 38 1 21 28 10.1037/hea0000695 30474996 Sonuga-Barke, E., & Webley, P. (1993). Children’s saving: A study in the development of economic behavior. Routledge. https://doi-org.ezproxy.cul.columbia.edu/10.4324/9781315109824 Staubitz JL Lloyd BP Reed DD A summary of methods for measuring delay discounting in young children The Psychological Record 2018 68 2 239 253 10.1007/s40732-018-0292-1 Staubitz JL Lloyd BP Reed DD Effects of self-control training for elementary students with emotional and behavioral disorders Journal of Applied Behavior Analysis 2020 53 2 857 874 10.1002/jaba.634 31478218 Steinberg L Graham S O’Brien L Woolard J Cauffman E Banich M Age differences in future orientation and delay discounting Child Development 2009 80 1 28 44 10.1111/j.1467-8624.2008.01244.x 19236391 Strickland JC Johnson MW Rejecting impulsivity as a psychological construct: A theoretical, empirical, and sociocultural argument Psychological Review 2020 10.1037/rev0000263 Te'eni-Harari T Financial literacy among children: The role of involvement in saving money Young Consumers 2016 17 2 197 208 10.1108/YC-01-2016-00579 Vollmer TR Borrero JC Lalli JS Daniel D Evaluating self-control and impulsivity in children with severe behavior disorders Journal of Applied Behavior Analysis 1999 32 4 451 466 10.1901/jaba.1999.32-451 10641300 Ward-Horner JC Pittenger A Pace G Fienup DM Effects of reinforcer magnitude and distribution on preference for work schedules Journal of Applied Behavior Analysis 2014 47 3 623 627 10.1002/jaba.133 24825241 Weller RE Cook EW III Avsar KB Cox JE Obese women show greater delay discounting than healthy-weight women Appetite 2008 51 3 563 569 10.1016/j.appet.2008.04.010 18513828 Yoon JH Higgins ST Turning k on its head: Comments on use of an ED50 in delay discounting research Drug and Alcohol Dependence 2008 95 1–2 169 172 10.1016/j.drugalcdep.2007.12.011 18243583
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==== Front Eur J Clin Nutr Eur J Clin Nutr European Journal of Clinical Nutrition 0954-3007 1476-5640 Nature Publishing Group UK London 1252 10.1038/s41430-022-01252-w Article Prolonged body weight gain, lifestyle changes and health-related quality of life in children during the COVID-19 pandemic lockdown: A follow-up study Azrak María Ángeles 1 http://orcid.org/0000-0001-5738-9473 Fasano María Victoria 12 Avico Ana Julia 1 http://orcid.org/0000-0003-0930-3609 Sala Marisa 1 Casado Carla 1 Padula Marcela 1 Kruger Ana Luz 13 http://orcid.org/0000-0003-2160-9600 Malpeli Agustina 1 http://orcid.org/0000-0001-8987-6348 Andreoli María F. [email protected] 13 1 Instituto de Desarrollo e Investigaciones Pediátricas (IDIP) Prof. Dr. Fernando E. Viteri. HIAEP “Sor María Ludovica” de La Plata - CIC-PBA. La Plata, Buenos Aires, Argentina 2 grid.9499.d 0000 0001 2097 3940 Centro de Matemática de La Plata (CMaLP), Facultad de Ciencias Exactas, UNLP - CIC-PBA. La Plata, Buenos Aires, Argentina 3 grid.423606.5 0000 0001 1945 2152 CONICET. La Plata, Buenos Aires, Argentina 12 12 2022 18 18 7 2022 1 12 2022 1 12 2022 © The Author(s), under exclusive licence to Springer Nature Limited 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Background Further investigation is needed to define the impact of long-term pandemic lockdown in children. Objectives To examine changes in body mass index z-score (zBMI), lifestyle, Health-Related Quality of Life and proportion of overweight or obesity (OW/OB) in 6- to 9-year-old children in Argentina. Methods Observational study with baseline measurements prior to lockdown and follow-up after eight months of strict restrictive measures (November 2020, first visit, n = 144) and after ten months of partial reopening (September 2021, second visit, n = 108). Anthropometric changes from baseline to first visit in lockdown group (LG) were compared with a historical control group (HCG, n = 134). Follow-up visits included anthropometric measures, lifestyle questionnaire and Pediatric Quality of Life Inventory. Results Change in zBMI was higher in LG [median, IQR: 0.46 (−0.00; 0.83)] vs HCG [median, IQR: 0.02 (−0.31; 0.27)]; p < 0.001, particularly in children with pre-existing OW/OB. In LG, zBMI was higher at first and second visit vs baseline (p < 0.001) and in second visit vs first visit for boys (p = 0.037) but not for girls. The proportion of children with OW/OB increased from baseline (43.5%) to first (56.5%) and second visit (58.3%) (p = 0.029). Unlike girls, the proportion of boys with OW/OB increased from baseline to first and second visit (p = 0.045). Change in zBMI was higher in children with less healthy habits (p < 0.001). Conclusions Weight gain continued to increase in boys when lockdown measurements were eased, although sedentary behaviors decreased and quality of life improved, indicating that the effects of pandemic lockdown could be difficult to reverse. Subject terms Obesity Paediatrics https://doi.org/10.13039/501100003285 Ministerio de Salud de la Nación (Ministry Of Health, Argentina) Beca salud Investiga Beca Salud Investiga Azrak María Ángeles Andreoli María F. ==== Body pmcIntroduction To mitigate the spread of the coronavirus disease 2019 (COVID-19), in March 2020 the Argentinian Government decided for strict lockdown measurements that included suspension of in-person schooling and closure of playgrounds, recreational facilities, and non-essential services [1]. Strict lockdown measurements were not eased until November 2020; [2] Argentina suffered one of the most prolonged lockdown periods worldwide [3]. Throughout 2021, the restrictions were gradually reduced and schools reopened partially in March with a hybrid learning pattern that combined equally in-person and online learning, and in September full in-person classes were resumed. It has been suggested that this changing reality may have negative implications especially on children [4–6]. Prior research has indicated that lockdown measurements affected several aspects of lifestyle all over the world: changes in diet, lower physical activity, higher screen time and sleeping disorders were widely reported [7–13]. Besides, children faced a dramatic change in their routine due to school closure, which deprives children from contact with their peers and teachers. Lifestyle changes may also affect Health-Related Quality of Life (HRQoL), a multidimensional measure of health used to assess the individual’s perceptions of the impact of a given condition on health status [14]. A stressful situation such as pandemic lockdown may significantly impact HRQoL [15]. In Argentina, excess weight was already a main nutritional problem before the pandemic according to the last national nutrition survey, affecting 41.1% of 5- to 17-year-old children [16]. The aforementioned changes in lifestyle predict severe consequences with increasing obesity, especially in predisposed individuals. Pre-COVID-19 studies reported that children usually gain more weight during the summer holidays [17–19], and it has been proposed that the pandemic may have exerted a similar effect due to increased time out of school [6, 20]. Based on the weight trend pattern during school time and summer recess, a simulation study predicted an important increase in weight gain during pandemic-induced school closures [21]. Although different studies showed that during the pandemic weight gain and obesity rates increased in children and adolescents [22–26], further investigation is mandatory to define the impact of long-term restrictive measurements, the effect of the progressive relaxation of restrictions and the direct implication of lifestyle changes. Besides, the excess weight gained by children could be difficult to reverse and might contribute to overweight (OW) and obesity (OB) in adulthood [27]. To our knowledge, few prior studies examined the consequences of prolonged lockdown in body weight [28–30]. The objective of this longitudinal study was to examine changes in body weight, lifestyle and HRQoL in children for almost two years after the beginning of the COVID-19 pandemic lockdown in Argentina, where a very long period of strict lockdown was followed by almost one year of gradual opening. Methods Study design The study design can be seen in Fig. 1A. This observational follow-up study was conducted at Instituto de Desarrollo e Investigaciones Pediátricas (IDIP), HIAEP “Sor María Ludovica”, Healthy Children Outpatient Service, La Plata, Argentina. The database of the Institute was searched for children who were 6–to 9-year-old at the beginning of the pandemic. Included were children with available weight and height pre-pandemic (baseline) measurements recorded from December 1st, 2019 until March 10, 2020. Excluded were children who entered puberty and children undergoing chronic diseases that affect growth or weight gain or under pharmacological treatment. Parents of children who met the inclusion criteria were invited for follow-up visits in November 2020 (first visit) and in September 2021 (second visit). Visits included anthropometric measurements and completing a lifestyle questionnaire and the Pediatric Quality of Life Inventory (PedsQL). Anthropometric changes from baseline to 1st visit were compared with a historical control group (HCG) that included children born at least 2 years earlier than the lockdown-exposed children (LG, lockdown group), and did not experience lockdown. In LG, changes in anthropometric measurements were calculated from baseline and between visits. The timing of the 1st and 2nd visit was chosen according to the state of lockdown in Argentina. First visit was settled when strict restrictive measurements ended (November 2020) and 2nd visit occurred before school reopening (September 2021), therefore during this study children did not fully assist to daily in-person classes.Fig. 1 Study design and changes in body weight and BMI z-scores in LG vs HCG. A Study design. B Changes (Δ) in body weight z-score in LG and HCG analyzed by Mann-Whitney test. C Changes in body weight z-score in LG and HCG stratified by baseline weight status, analyzed by robust two-way ANOVA. D Changes in BMI z-score in LG and HCG analyzed by Mann-Whitney test. E Changes in BMI z-score in LG and HCG stratified by baseline weight status, analyzed by robust two-way ANOVA. In all cases ***p < 0.001, *p < 0.05. PedsQL Pediatric Quality of Life Inventory, LG Lockdown group, HCG Historical control group, NW Normoweight, OW/OB Overweight or obesity. Data collection Anthropometric measurements Height was measured by a Harpenden stadiometer (Holtain Ltd., Crosswell, United Kingdom) and weight was measured wearing light clothing using a Systel scale (Argentina). Baseline measurements were retrieved from medical records. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. Children´s height, weight, and BMI values were converted to sex- and age-specific standard deviation scores (z-scores) using WHO AnthroPlus software version 1.0.4 (World Health Organization). A BMI z-score (zBMI) greater than one was defined as OW, and a zBMI greater than two was defined as OB according to the World Health Organization [31]. Lifestyle questionnaire In the 1st visit parents filled out a lifestyle questionnaire about their children´s changes in feeding behavior, sleep and physical activity vs baseline. The questionnaire included 8 closed questions. A lockdown healthy habits score (HHS) was calculated as the sum of the 8 questions using a 4-point scoring system. A cutoff value in the third quartile was chosen to discriminate low and high HHS. The items from the lifestyle questionnaire and the scoring criteria are presented in Suppl. Table 1. In the 2nd visit, parents filled out a similar questionnaire to evaluate changes with respect to 1st visit. Health-Related Quality of Life - Pediatric Quality of Life Inventory (PedsQL) In the 1st and 2nd visit parents and children completed the validated Spanish-Argentina version of PedsQLTM Generic Core Scales 4.0 [32], which includes the child self-report and parent proxy-report forms to assess HRQoL and comprises 4 domains (physical, emotional, social, and school functions) [14]. The items were measured using a 5-point Likert scale. The PedsQL total score was composed of the physical and psychosocial scores. The psychosocial score was composed of the emotional, social and school functioning scores. Ethics The study was approved by the Institutional Committee for the Revision of Research Protocols, IDIP, and conducted according to the Declaration of Helsinki guidelines. Parents or legal tutors signed a written informed consent, children above 8 years old signed a written informed assent. Statistical analyses Sample size was calculated assuming a standard deviation of 0.6 [33], a difference in zBMI between groups of 0.25, 80% statistical power and 5% significance level, leading to a minimal sample size of 91 children per group. Statistical analyses were performed using the R statistical software version 4.0.3. The Kolmogorov-Smirnov test was applied to test normal distribution. Continuous variables with normal distribution are presented as mean (standard deviation [SD]); non-normal variables are reported as median (interquartile range [IQR]) and categorical data are summarized as frequency counts and percentages. Baseline characteristics were compared by t-test or Mann-Whitney for quantitative data and using Chi-squared for qualitative data. Changes in z-scores between groups were assessed by Mann-Whitney and robust two-way mixed model ANOVA when stratified by baseline weight status. Changes over time for the LG group were analyzed by repeated measures ANOVA and 2-way mixed repeated-measures ANOVA when analyzed by sex. Pairwise comparisons were adjusted by Bonferroni method. Changes in proportion of OW/OB were analyzed by Chi-squared test for linear trend. Changes in lifestyle questionnaire were analyzed by Fisher exact test. Differences in PedsQL between 1st and 2nd visit were assessed by Wilcoxon signed rank test. All statistical tests were two-tailed and significance level was set at p < 0.05. Results Baseline characteristics Baseline characteristics of the children can be seen in Table 1. Pre-pandemic data was retrieved from 205 medical records of children who met the inclusion criteria and parents were invited to participate. Of these, 144 agreed and were called for the 1st visit, conforming the LG. Besides, 134 medical records of children with similar characteristics to the LG in terms of sex, age, weight and height before the COVID-19 pandemic were selected for the HCG and data from 2 anthropometric measurements taken with time intervals similar to the LG were collected. Sex differences were not observed in baseline anthropometric characteristics (data not shown).Table 1 Baseline characteristics of the children. HCG (N = 134) LG (N = 144) p-value Male, n (%) 58 (43.3%) 72 (50%) 0.281 Female, n (%) 76 (57.7%) 72 (50%) Age (years) 6.73 (6.06, 7.77) 6.74 (5.97, 7.49) 0.320 Interval between baseline and 1st visit (years) 0.92 (0.80, 1.01) 0.91 (0.79, 0.97) 0.246 Height at baseline (cm) 120 (114, 126) 119 (113.3, 124) 0.228 Body weight at baseline (kg) 23.50 (20.80, 28.85) 24 (20.30, 26.92) 0.535 Body weight z-score at baseline 0.47 (1.16) 0.43 (1.10) 0.431 BMI at baseline (kg/m2) 16.62 (15.55, 18.55) 16.64 (15.49, 18.08) 0.801 BMI z-score at baseline 0.78 (1.09) 0.77 (1.07) 0.814 NW, n (%) 79 (58.9%) 84 (58.3%) 0.999 OW, n (%) 36 (26.9%) 39 (27.1%) OB, n (%) 19 (14.2%) 21 (14.6%) LG Lockdown group, HCG Historical control group, BMI Body Mass Index, NW Normoweight, OW Overweight, OB Obesity. Data are presented as mean (SD) for body weight and BMI z-scores at baseline. Age, interval between baseline and 1st visit and height, body weight and BMI at baseline are presented as median (IQR). Changes in body weight z-score, zBMI and proportion of weight status in LG vs HCG Figure 1 shows that changes (Δ) in body weight z-score (Fig. 1B) and zBMI (Fig. 1D) from baseline to 1st visit were significantly higher in LG vs HCG. Similar differences were observed in absolute weight gain [median, IQR: 3.9 (2.3; 6.4) kg in LG vs 2.5 (1.7; 4.2) kg in HCG, p < 0.001]. Δ-body weight z-score was significantly higher in children with OW or OB (OW/OB) at baseline vs normoweight (NW) children in the LG but not in the HCG (Fig. 1C), and a similar trend was observed in Δ-zBMI (Fig. 1E). No changes in Δ-height z-score were observed in LG vs HCG (p = 0.884). The proportion of children with OW/OB tended to increase from 41.7% at baseline to 52.8% at 1st visit in LG (p = 0.075) and remained unchanged in HCG (41.0% to 42.5%, p = 0.902). Furthermore, the proportion of children with OB increased from 14.6% at baseline to 27.8% at 1st visit in LG (p = 0.009) and remained unchanged in HCG (14.2% to 17.2%, p = 0.510). Longitudinal changes in zBMI and proportion of weight status in LG Of the 144 children that attended the 1st visit, thirty-six did not follow up for the 2nd visit and were not included in this part of the analysis. zBMI was significantly higher at 1st and 2nd visit vs. baseline (Fig. 2A), and similar results were observed in children with OW/OB at baseline vs NW children (data not shown). zBMI was also analyzed considering sex and time as factors. Significant time effect (p < 0.001) and interaction were detected (F (1.87, 196.6) = 4.77, p = 0.011), and pairwise comparison showed that zBMI was significantly different at 1st and 2nd visit for boys and girls vs baseline, and in 2nd vs 1st visit only for boys (Fig. 2B). The proportion of children with OW/OB or OB increased from baseline to 1st and 2nd visit, significantly in boys but not in girls (Fig. 2C, D).Fig. 2 Longitudinal changes in zBMI and proportion of weightstatus in LG. A BMI z-score at baseline, 1st and 2nd visit in children exposed to lockdown in the total sample analyzed by repeated measures ANOVA, pairwise comparisons adjusted by Bonferroni method. B BMI z-score at baseline, 1st and 2nd visit in children exposed to lockdown in girls and boys analyzed by two-way mixed ANOVA, pairwise comparisons adjusted by Bonferroni method. C Proportion of children with overweight or obesity in the total sample and stratified by sex, analyzed by Chi-squared test for trend. D Proportion of children with obesity in the total sample and stratified by sex analyzed by Chi-squared test for trend. In all cases ****p < 0.001, *p < 0.05. Lifestyle changes Lifestyle changes from baseline to 1st visit and from 1st to 2nd visit are depicted in Table 2. At 1st visit most parents reported that their children reduced the intake of snacks, sweetened beverages and sweets, reduced their physical activity, slept more hours and increased leisure screen time. Some changes reversed at 2nd visit: vegetables consumption and physical activity increased, and intake of sweetened beverages, sleeping and leisure screen hours decreased. No sex differences were observed (data not shown). zBMI and its changes were also stratified by baseline weight status and HHS and analyzed by two-way robust ANOVA (Suppl. Table 2). zBMI at 1st and 2nd visit was higher in children with OW/OB at baseline (p < 0.001) and with low HHS (p < 0.01), and ΔzBMI from baseline to 1st visit was higher in children with low HHS (p < 0.001).Table 2 Lifestyle changes. 1st visit 2nd visit (vs baseline) (vs 1st visit) p-value Fruit intake 0.074  No 3 (3%) 0 (0%)  Less 18 (19%) 9 (9%)  The same 40 (42%) 47 (49%)  More 35 (36%) 40 (42%) Vegetables intake 0.005  No 8 (8%) 2 (2%)  Less 25 (26%) 12 (13%)  The same 41 (43%) 43 (45%)  More 22 (23%) 39 (41%) Snacks intake 0.207  More 15 (16%) 6 (6%)  The same 27 (28%) 32 (33%)  Less 39 (41%) 44 (46%)  No 15 (15%) 14 (15%) Sweetened beverages intake 0.019  More 20 (21%) 6 (6%)  The same 27 (28%) 27 (28%)  Less 35 (36%) 41 (43%)  No 14 (15%) 22 (23%) Sweets intake 0.060  More 13 (14%) 15 (16%)  The same 21 (22%) 31 (33%)  Less 44 (46%) 43 (45%)  No 17 (18%) 6 (6%) Physical activity <0.001  Less 56 (59%) 13 (14%)  The same 13 (14%) 23 (24%)  More 26 (27%) 59 (62%) Sleeping 0.003  Less 12 (13%) 26 (27%)  The same 39 (41%) 45 (47%)  More 44 (46%) 24 (25%) Screen hours (leisure) <0.001  More 55 (58%) 20 (21%)  The same 20 (21%) 24 (25%)  Less 20 (21%) 51 (54%) Data are presented as frequency counts (percentages) (Fisher exact test). Health-related quality of life PedsQL scores at 1st and 2nd visit were stratified by weight status (Suppl. Table 3). Children with OW/OB at baseline had lower parent physical and total scores at 2nd visit. PedsQL scores were also stratified by HHS (Table 3). Children with high HHS showed greater self-reported scores and total parent score at 1st visit and higher self-reported physical and total self-reported scores at 2nd visit. All scores except the physical parent score improved from 1st to 2nd visit (Table 4).Table 3 PedsQL scores in children exposed to lockdown stratified by HHS. Low HHS (N = 80) High HHS (N = 43) p-value PedsQL Score - First visit Child  Physical 73.4 (62.5, 85.2) 78.1 (68.8, 93.8) 0.031  Psychosocial 72.7 (56.3, 86.4) 81.8 (70.5, 88.6) 0.043  Total 72.6 (59.2, 84.2) 79.0 (71.7, 89.5) 0.011 Parent  Physical 88.4 (75.0, 93.8) 90.6 (84.4, 98.4) 0.140  Psychosocial 81.8 (72.7, 90.9) 86.4 (80.7, 93.2) 0.065  Total 84.2 (74.4, 89.5) 89.5 (80.3, 94.1) 0.040 PedsQL Score - Second visit Child  Physical 81.3 (75.0, 93.8) 92.2 (81.3, 93.8) 0.022  Psychosocial 87.5 (75.4, 96.7) 93.3 (78.8, 96.7) 0.172  Total 85.9 (76.1, 91.3) 89.7 (82.9, 97.3) 0.043 Parent  Physical 87.5 (78.1, 96.9) 93.8 (82.8, 99.2) 0.195  Psychosocial 90.0 (78.8, 97.9) 94.2 (80.4, 96.7) 0.597  Total 88.3 (80.4; 95.4) 92.2 (83.2; 95.7) 0.264 PedsQL Pediatric Quality of Life Inventory, HHS Healthy Habits Score. Data are presented as median (IQR). Statistical analysis was performed by Mann-Whitney test. Table 4 PedsQL scores in children exposed to lockdown at first and second visits. First visit (N = 91) Second visit (N = 91) p-value Child  Physical 75.0 (62.5, 93.8) 85.9 (77.3, 93.8) <0.001  Psychosocial 79.6 (59.1, 86.4) 90.0 (76.7, 96.7) <0.001  Total 77.0 (63.2, 87.2) 88.0 (78.3, 93.5) <0.001 Parent  Physical 90.6 (77.3, 96.9) 90.6 (80.6, 96.9) 0.179  Psychosocial 84.1 (75.0, 90.9) 90.0 (80.0, 96.7) 0.001  Total 85.5 (77.6, 92.1) 89.1 (82.6, 95.7) 0.009 PedsQL Pediatric Quality of Life Inventory, HHS Healthy Habits Score. Data are presented as median (IQR). Statistical analysis was performed by Wilcoxon signed rank test. Discussion To our knowledge, this is the first longitudinal study showing that weight gain in children during lockdown continued to increase despite the progressive ease of restrictions, although sedentary behaviors decreased and HRQoL improved. Several authors have warned about the risks of greater overweight or obesity due to the change in habits resulting from lockdown [7–12], and several studies have shown that lockdown and school closure increased weight gain and obesity prevalence [11, 34–37]. The current study goes a step further and shows the consequences of long-term lockdown on children´s health. One of the main findings of our study is that the body weight gain during strict COVID-19 lockdown in Argentina of 6- to 9 year-old children exceeded predictions [21] and reports from other populations [22, 24, 34, 38]. A Chinese study reported a yearly change in zBMI from 0.36 in 2019 to 0.55 in 2020 in 6 to 11 year-old children [22] and a Korean study reported a change of 0.219 in six months after school closure [34]. A study conducted in USA showed an absolute weight gain of 2.37 kg between 2019 and 2020 [24] and a recent meta-analysis reported a similar value [38]. Our study shows an absolute weight gain of 4 kg during strict lockdown and a change in zBMI of 0.46, values higher than reports and predictions by a microsimulation model which calculated an increase in zBMI by 0.141 in 6 months of school closure [21]. The long duration of strict lockdown in Argentina (almost 9 months, time elapsed between baseline and 1st visit) could be related to the greater weight gain, since most studies report the effects of 2-to-5 months of lockdown [38]. An important aspect of our study is the comparison with a HCG, which shows that lockdown-exposed children gained significantly more weight than those who did not go through a situation of social isolation. For this purpose, other studies have used data from several years prior to the pandemic [22–24], reaching similar conclusions. Our results also show that weight gain was more prominent in children with pre-existing obesity, who were already affected and vulnerable to excess weight gain, as observed in USA [23, 25] and Germany [39]. The longitudinal evaluation as lockdown measurements were eased and schools partially reopened (10 months between 1st and 2nd visit) revealed that relaxation of restrictive measures were not enough to influence the effects of the lockdown on weight gain. Few studies evaluated the effects of long-term lockdown: a recent study also reported sustained and significant weight gain for one year in Korean children, although schools were fully open for the last six months; [28] another study showed an important weight gain increase the first year of the pandemic followed by a period of stabilization [29] and a retrospective chart review study reported that excessive weight gain in 2020 did not reverse by 2021 [30]. We also observed that boys, unlike girls, continued gaining weight although lockdown measurements were eased. Boys also were more susceptible to weight gain during lockdown in studies in Austrian [40] and Chinese children [22, 41] and Italian adolescents with obesity [35]. The increase in the proportion of children with obesity as a consequence of strict lockdown was significantly high, similar to other reports [22, 24, 26, 42]. When lockdown measurements were eased, the proportion of children with OB continued to increase, particularly boys, in agreement with observations in Chinese adolescents [43]. Clearly, our results exceeded the projections about the impact of the pandemic on childhood obesity [18, 20, 21]. During strict lockdown, children´s screen time increased and physical activity decreased, as shown by our group [7] and others [8–11]. When lockdown measurements were eased, sedentary behaviors decreased. An interesting finding is that children with healthy habits during strict confinement, reflected by the HHS, gained less weight, irrespective of pre-existing OW/OB. Our results also show a reduction in the intake of unhealthy foods such as sweets, sweetened beverages and snacks, while other studies report an increase [8, 13, 37]. Discrepancies could be related to the limitations of the questionnaire, answered by parents, and to limited access related to food insecurity [44]. Our results highlight the importance of a healthy lifestyle for mitigating the consequences of lockdown in children, not only for individuals with obesity. The COVID-19 pandemic lockdown also affected HRQoL, reflected by PedsQL scores. Children with healthy habits had a better quality of life, especially under strict restrictive measures. It was reported that more physical activity and less sedentary time [45], especially screen use [46], are associated with increased HRQoL in children and adolescents. Parents of children with pre-existing OW/OB reported a reduced quality of life, that was not self-perceived by the children. Although we could not assess HRQoL at baseline, physical and psychosocial scores improved as lockdown measurements were eased. Weight gain is closely related to habits such as exercise and diet. During strict lockdown, increased weight gain was concomitant to sedentary behaviors, as reported by others [9–11], and not to consumption of unhealthy foods. When lockdown measurements were eased, weight gain continued to increase in boys, although sedentary behaviors decreased and HRQoL improved, indicating the long-lasting effects of lockdown on body weight. Although no differences were observed in lifestyle changes between boys and girls, previous results from our group show that during lockdown boys spent more time playing screen and online games (p < 0.001 vs girls) [7], in line with reports in Spanish children of greater risk of inadequate physical activity frequency and use of TV and electronic devices in boys [9]. Besides, school exerts a protective influence on children’s sedentary behaviors and weight status [17–19], as children engage in behaviors that lead to increased weight gain when they are not in school [47]. Therefore, school closure for such an extended time may have negative impact on children’s behaviors and consequently weight gain. Prolonged weight gain was previously observed in children after natural disasters: in Japan, elevated BMI was reported 1.5 years after the Great East Japan Earthquake [33, 48]. Besides, the reversion of childhood obesity needs a long follow-up period: multidisciplinary treatment programs can take up to five years to reach a significant weight loss [49]. This study has several limitations. It was conducted on a small sample and only 6- to 9-year-old children were included, who were likely most impacted by school closures and vulnerable to weight changes [22, 23]. Hence, caution must be exercised when interpreting evidence from other populations. Besides, lifestyle changes were parent-reported, and may provide less information than child reports, and changes in the long term could be difficult to remember. Also, lifestyle aspects were reported as changes vs. before lockdown, which limits data collection about time dedicated to physical activity and screen use. Despite these limitations, our work adds knowledge to previous studies about short-term consequences of lockdown. We can conclude that pandemic lockdown increased weight gain and proportion of obesity in children, especially in boys and in those with pre-existing OW/OB. Weight gain continued to increase in boys when lockdown measurements were eased, although sedentary behaviors decreased and HRQoL improved, indicating that the effects of pandemic lockdown could be difficult to reverse. Tackling childhood obesity after the pandemic will not be easy and might require decades to fully reverse current trends. Governments, schools, and families should be encouraged to make efforts not only to prevent childhood obesity but also to ameliorate the effects of pandemic lockdown supporting healthy lifestyle choices. Supplementary information Supplementary information Supplementary information The online version contains supplementary material available at 10.1038/s41430-022-01252-w. Acknowledgements We thank the families, both children and parents and mothers, for their participation and collaboration in the study, even more in these complicated circumstances. We also thank the staff of the Institute of Development and Pediatric Research (IDIP), Sor Maria Ludovica Children´s Hospital, Healthy Children Outpatient Service for their help recruiting volunteers and collecting participant data. Author contributions Acquisition, analysis, or interpretation of data: MAA, AJA, MS, MP, AM, MFA. Organization of data: ALK, CC. Drafting of the manuscript: MFA, MVF. Statistical analysis: MVF. Obtained funding: MAA and MFA. All authors were involved in writing the paper and had final approval of the submitted and published versions. Funding This study (and MAA) was supported by Ministerio de Salud de la Nación, Dirección de Investigación en Salud, Becas Salud Investiga. Data availability The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher. Competing interests The authors declare no competing interests. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. These authors contributed equally: María Ángeles Azrak, María Victoria Fasano. ==== Refs References 1. Decreto Nro. 260/20 AISLAMIENTO SOCIAL PREVENTIVO Y OBLIGATORIO. 2020. Presidencia de la Nación. Argentina. http://servicios.infoleg.gob.ar/infolegInternet/anexos/335000-339999/335741/norma.htm. Accessed 17 June 2022. 2. Decreto Nro. 875/20 AISLAMIENTO SOCIAL PREVENTIVO Y OBLIGATORIO. 2020. Presidencia de la Nación. Argentina. http://servicios.infoleg.gob.ar/infolegInternet/verNorma.do?id=344033. Accessed 17 June 2022. 3. Ise A Villalba S Clementi L Carrizo S Extra long Argentinian lockdown: Revising the energy regime Glob Transit 2021 3 43 54 10.1016/j.glt.2020.12.002 35437517 4. Golberstein E Wen H Miller BF Coronavirus Disease 2019 (COVID-19) and mental health for children and adolescents JAMA Pediatr 2020 174 819 20 10.1001/jamapediatrics.2020.1456 32286618 5. Wang G Zhang Y Zhao J Zhang J Jiang F Mitigate the effects of home confinement on children during the COVID-19 outbreak Lancet 2020 395 945 7 10.1016/S0140-6736(20)30547-X 6. Rundle AG Park Y Herbstman JB Kinsey EW Wang YC COVID-19-related school closings and risk of weight gain among children Obes (Silver Spring) 2020 28 1008 9 10.1002/oby.22813 7. Fasano MV Padula M Azrak MA Avico AJ Sala M Andreoli MF Consequences of lockdown during COVID-19 pandemic in lifestyle and emotional state of children in Argentina Front Pediatr 2021 9 660033 10.3389/fped.2021.660033 34336734 8. Neshteruk CD Zizzi A Suarez L Erickson E Kraus WE Li JS Weight-related behaviors of children with obesity during the COVID-19 pandemic Child Obes 2021 17 371 8 10.1089/chi.2021.0038 33902326 9. Ventura PS, Ortigoza AF, Castillo Y, Bosch Z, Casals S, Girbau C, et al. Children’s Health Habits and COVID-19 Lockdown in Catalonia: Implications for obesity and non-communicable diseases. Nutrients. 2021;13. 10. Ten Velde G Lubrecht J Arayess L van Loo C Hesselink M Reijnders D Physical activity behaviour and screen time in Dutch children during the COVID-19 pandemic: Pre-, during- and post-school closures Pediatr Obes 2021 16 e12779 10.1111/ijpo.12779 33624443 11. Alves JM Yunker AG DeFendis A Xiang AH Page KA BMI status and associations between affect, physical activity and anxiety among U.S. children during COVID-19 Pediatr Obes 2021 16 e12786 10.1111/ijpo.12786 33720550 12. Lopez-Bueno R Lopez-Sanchez GF Casajus JA Calatayud J Gil-Salmeron A Grabovac I Health-related behaviors among school-aged children and adolescents during the Spanish Covid-19 confinement Front Pediatr 2020 8 573 10.3389/fped.2020.00573 33042917 13. Pietrobelli A Pecoraro L Ferruzzi A Heo M Faith M Zoller T Effects of COVID-19 lockdown on lifestyle behaviors in children with obesity living in Verona, Italy: A longitudinal study Obes (Silver Spring) 2020 28 1382 5 10.1002/oby.22861 14. Varni JW Seid M Kurtin PS PedsQL 4.0: Reliability and validity of the Pediatric Quality of Life Inventory version 4.0 generic core scales in healthy and patient populations Med Care 2001 39 800 12 10.1097/00005650-200108000-00006 11468499 15. Nobari H, Fashi M, Eskandari A, Villafaina S, Murillo-Garcia A, Perez-Gomez J. Effect of COVID-19 on health-related quality of life in adolescents and children: A Systematic Review. Int J Environ Res Public Health. 2021;18. 16. 2° Encuesta Nacional de Nutrición y Salud. ENNyS2. Resumen Ejecutivo. 2019. Presidencia de la Nación. Argentina. http://www.msal.gob.ar/images/stories/bes/graficos/0000001565cntennys2_resumen-ejecutivo-2019.pdf. Accessed 17 June 2022. 17. Franckle R Adler R Davison K Accelerated weight gain among children during summer versus school year and related racial/ethnic disparities: a systematic review Prev Chronic Dis 2014 11 E101 10.5888/pcd11.130355 24921899 18. von Hippel PT Workman J From kindergarten through second grade, U.S. children’s obesity prevalence grows only during summer vacations Obes (Silver Spring) 2016 24 2296 2300 10.1002/oby.21613 19. Wang YC Vine S Hsiao A Rundle A Goldsmith J Weight-related behaviors when children are in school versus on summer breaks: does income matter? J Sch Health 2015 85 458 66 10.1111/josh.12274 26032276 20. Workman J. How much may COVID-19 school closures increase childhood obesity? Obesity (Silver Spring). 2020;28:1787. 21. An R. Projecting the impact of the coronavirus disease-19 pandemic on childhood obesity in the United States: A microsimulation model. J Sport Health Sci. 2020;9:302–12. 22. Hu J, Liu J, Wang J, Shen M, Ge W, Shen H, et al. Unfavorable progression of obesity in children and adolescents due to COVID-19 pandemic: A school-based survey in China. Obesity (Silver Spring). 2021;29:1907–15. 23. Lange SJ Kompaniyets L Freedman DS Kraus EM Porter R Blanck HM Longitudinal trends in body mass index before and during the COVID-19 pandemic among persons aged 2-19 Years - United States, 2018-2020 MMWR Morb Mortal Wkly Rep 2021 70 1278 83 10.15585/mmwr.mm7037a3 34529635 24. Woolford SJ Sidell M Li X Else V Young DR Resnicow K Changes in body mass index among children and adolescents during the COVID-19 pandemic JAMA 2021 326 1434 6 10.1001/jama.2021.15036 34448817 25. Brooks CG Spencer JR Sprafka JM Roehl KA Ma J Londhe AA Pediatric BMI changes during COVID-19 pandemic: An electronic health record-based retrospective cohort study EClinicalMedicine 2021 38 101026 10.1016/j.eclinm.2021.101026 34337366 26. Wen J Zhu L Ji C Changes in weight and height among Chinese preschool children during COVID-19 school closures Int J Obes (Lond) 2021 45 2269 73 10.1038/s41366-021-00912-4 34267325 27. Geserick M Vogel M Gausche R Lipek T Spielau U Keller E Acceleration of BMI in early childhood and risk of sustained obesity N. Engl J Med 2018 379 1303 12 10.1056/NEJMoa1803527 30281992 28. Gwag SH Oh YR Ha JW Kang E Nam HK Lee Y Weight changes of children in 1 year during COVID-19 pandemic J Pediatr Endocrinol Metab 2022 35 297 302 34881539 29. Jarnig G, Kerbl R, van Poppel MNM. Change in BMI and fitness among primary school children in Austria: A 24-Month follow-up study of 303 children measured before and during the ongoing COVID-19 Pandemic. Sports (Basel). 2022;10. 30. Miller A, Bochner R, Sohler N, Calixte R, Chan C, Umpaichitra V, et al. Modified body mass index z-scores in children in New York City during the COVID-19 pandemic. Pediatr Obes. 2022;17:e12958. 31. de Onis M Lobstein T Defining obesity risk status in the general childhood population: which cut-offs should we use? Int J Pediatr Obes 2010 5 458 60 10.3109/17477161003615583 20233144 32. Roizen M Rodriguez S Bauer G Medin G Bevilacqua S Varni JW Initial validation of the Argentinean Spanish version of the PedsQL 4.0 Generic Core Scales in children and adolescents with chronic diseases: acceptability and comprehensibility in low-income settings Health Qual Life Outcomes 2008 6 59 10.1186/1477-7525-6-59 18687134 33. Zheng W Yokomichi H Matsubara H Ishikuro M Kikuya M Isojima T Longitudinal changes in body mass index of children affected by the Great East Japan Earthquake Int J Obes (Lond) 2017 41 606 12 10.1038/ijo.2017.6 28093572 34. Kang HM Jeong DC Suh BK Ahn MB The impact of the Coronavirus Disease-2019 pandemic on childhood obesity and Vitamin D status J Korean Med Sci 2021 36 e21 10.3346/jkms.2021.36.e21 33463095 35. Maltoni G Zioutas M Deiana G Biserni GB Pession A Zucchini S Gender differences in weight gain during lockdown due to COVID-19 pandemic in adolescents with obesity Nutr Metab Cardiovasc Dis 2021 31 2181 5 10.1016/j.numecd.2021.03.018 33994065 36. Androutsos O, Perperidi M, Georgiou C, Chouliaras G. Lifestyle Changes and Determinants of Children’s and Adolescents’ Body Weight Increase during the First COVID-19 Lockdown in Greece: The COV-EAT Study. Nutrients. 2021;13. 37. Ruiz-Roso MB, de Carvalho Padilha P, Mantilla-Escalante DC, Ulloa N, Brun P, Acevedo-Correa D, et al. Covid-19 confinement and changes of Adolescent’s dietary trends in Italy, Spain, Chile, Colombia and Brazil. Nutrients. 2020;12. 38. Chang TH, Chen YC, Chen WY, Chen CY, Hsu WY, Chou Y, et al. Weight Gain Associated with COVID-19 Lockdown in Children and Adolescents: A systematic review and meta-analysis. Nutrients. 2021;13. 39. Vogel M Geserick M Gausche R Beger C Poulain T Meigen C Age- and weight group-specific weight gain patterns in children and adolescents during the 15 years before and during the COVID-19 pandemic Int J Obes (Lond) 2022 46 144 52 10.1038/s41366-021-00968-2 34556774 40. Jarnig G Jaunig J Kerbl R Strenger V Haeusler G van Poppel MNM Acceleration in BMI gain following COVID-19 restrictions. A longitudinal study with 7- to 10-year-old primary school children Pediatr Obes 2022 17 e12890 10.1111/ijpo.12890 35083879 41. Ge W, Hu J, Xiao Y, Liang F, Yi L, Zhu R, et al. COVID-19 related childhood bmi increases in China: A health surveillancebased ambispective cohort analysis. Am J Prev Med. 2022;63:647–55. 42. Mulugeta W Desalegn H Solomon S Impact of the COVID-19 pandemic lockdown on weight status and factors associated with weight gain among adults in Massachusetts Clin Obes 2021 11 e12453 10.1111/cob.12453 33855789 43. Yang D Luo C Feng X Qi W Qu S Zhou Y Changes in obesity and lifestyle behaviours during the COVID-19 pandemic in Chinese adolescents: A longitudinal analysis from 2019 to 2020 Pediatr Obes. 2022 17 e12874 10.1111/ijpo.12874 34937132 44. Adams EL Caccavale LJ Smith D Bean MK Food insecurity, the home food environment, and parent feeding practices in the Era of COVID-19 Obes (Silver Spring) 2020 28 2056 63 10.1002/oby.22996 45. Wu XY Han LH Zhang JH Luo S Hu JW Sun K The influence of physical activity, sedentary behavior on health-related quality of life among the general population of children and adolescents: A systematic review PLoS One 2017 12 e0187668 10.1371/journal.pone.0187668 29121640 46. Stiglic N Viner RM Effects of screentime on the health and well-being of children and adolescents: A systematic review of reviews BMJ Open 2019 9 e023191 10.1136/bmjopen-2018-023191 47. Weaver RG Hunt ET Armstrong B Beets MW Brazendale K Turner-McGrievy G COVID-19 leads to accelerated increases in children’s BMI z-Score Gain: An interrupted time-series study Am J Prev Med 2021 61 e161 e169 10.1016/j.amepre.2021.04.007 34148734 48. Isojima T Yokoya S Ono A Kato N Tanaka T Yokomichi H Prolonged elevated body mass index in preschool children after the Great East Japan Earthquake Pediatr Int 2017 59 1002 9 10.1111/ped.13340 28608648 49. Danielsson P Bohlin A Bendito A Svensson A Klaesson S Five-year outpatient programme that provided children with continuous behavioural obesity treatment enjoyed high success rate Acta Paediatr 2016 105 1181 90 10.1111/apa.13360 26859578
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==== Front Environ Manage Environ Manage Environmental Management 0364-152X 1432-1009 Springer US New York 1765 10.1007/s00267-022-01765-x Article Analysis of the Relations Between Forestry Financial Supports and Forest Crimes Sevinç Volkan [email protected] grid.411861.b 0000 0001 0703 3794 Faculty of Science, Department of Statistics, Muğla Sıtkı Koçman University, 48000 Muğla, Turkey 12 12 2022 114 6 9 2022 28 11 2022 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Forest crimes are among the serious threats destroying forests. To prevent the forest crimes there are various solutions proposed, such as fortification of the laws, increasing the penalties, or increasing the public awareness. This article, however, suggests an alternative solution of preventing the forest crimes by investigating the relations between the individual financial supports provided to forest villagers and the levels of various forest crime types in Turkey. The study shows that, when the forest villagers are given financial supports, the levels of illegal logging, illegal transferring of forest products, illegal expansion of private lands into forests, illegal processing of trees, and illegal pasturage crimes decrease significantly. However, the financial supports do not affect the levels of illegal occupation of forestlands crime. Keywords Forest crimes Forestry financial supports Illegal logging Sustainable forestry ==== Body pmcIntroduction Forests are economically and ecologically important natural resources. However, there are many factors damaging the forests and reducing the forest assets. Among these factors, there are human-induced factors as well as natural ones. When the human-induced factors are considered, except for arson and accidental cases like shepherd fires, hunting fires, and traffic accidents, various intentionally committed forest crimes also damage the forests. For this reason, countries take various measures and enact penal laws to prevent the forest crimes for the protection and sustainability of forests. According to a recent report, Interpol has conducted many global police operations against forest crimes over the past decade and these operations resulted in the seizure of more than one million cubic meters of illicit timber, which is worth more than 1.5 billion dollars across Africa, Asia, Europe, and the Americas (Interpol 2021). Brantingham and Brantingham (2017) report that forest crimes generally occur in places with characteristics that favor the opportunity for their occurrence. Additionally, Kitteringham (2010) states that to reduce forest crimes structural changes in the fields of health, education, employment, and environmental management are needed. Lochner and Moretti (2004) studied the effect of education on criminal activity and their results suggested that when the increasing education level decreases the crime levels. Gunes and Elvan (2005) investigated the logging activities in Turkey and concluded that the underlying causes of logging are related to the economic, political, and cultural structures of Turkish society. Similarly, in a study by Gençay and Mercimek (2019), a survey was conducted in Kastamonu province of Turkey to investigate the impact of laws on forest crimes. The study revealed that the crime level decreased when the public had enough information about forest crimes and punishments. Thompson and Magrath (2021), however, state that forestry law enforcement, forestry management, encouraging the local communities are necessary to combat the logging problem. In another study by Setiono and Husein (2005) performed in Indonesia, they state that when logging crime is committed by organized groups, forestry law enforcement approach fails to capture the criminals. To prevent the logging crime, they suggest that the banking system should be made more active to follow and detect the money laundering transactions. Countries may have supporting policies for their certain industrial sectors for various reasons. These supports may be in political or financial forms. According to a report prepared by Tomaselli (2006) and published by United Nations Forum on Forests (UNFF), private funding has been the main source of funding investments in the forestry sector. Additionally, a recent report by the United Nations (UN) states that the COVID-19 pandemic has increased the threats on forest resources and the financial resources. Thus, forests are currently at risk of being reduced. In the report, it is also emphasized that sustainable forest management including adequate financing is the key component of efficient and resilient recovery from COVID-19 (Lang et al. 2021). The European Parliament (EP) reports that in the European Union (EU), however, as there is not a common policy about forestry, forest policy is still a national matter. Nevertheless, many EU measures have an impact on the forests in the member countries or similar countries that are not members. Moreover, the common agricultural policy of the EU is the main source of the funds for the forests within its borders. A measure by the EU covers investment in the development of forested areas and improvement of the viability of forests. Another measure is to provide rewards for forestry, environmental and climate services, and the conservation of forests. A budget of 8.2 billion euros has been allocated for the 2015–2020 period. For reforestation, 27% of the budget was allocated. For more resilient forests and damage prevention, however, 18% of the budget was allocated for each (EP 2021). EU Forest Crime Initiative (EUFCI) in Danube-Carpathian Region covering the countries Bulgaria, Romania, Slovakia, and Ukraine, which exist in close regions to Turkey. (Schlingemann et al. 2021). The study mostly considers the logging crime and one of the results of the study is that the largest portion (64%) of the actors involved in the forest crimes are the local residents and the poor citizens. The second greatest rate (47%) belongs to the small and medium-sized enterprises, the third is the corrupt officials and businesses with a rate of (32%), the forth is the forest staff and guards (20%), the fifth is the organized crimes (18%), and the last belongs to the multinational companies with a rate of 14%. Bösch (2021) performed a quantitative cross-national analysis to investigate institutional quality, economic development, and logging by using logistic regression. The study shows that in a country, the gross domestic product per capita, economic growth, voice and accountability, rule of law, and control of corruption factors have significant effect on logging as well as the physical-geographical characteristics of the country. It should be noted that all forest crimes, except for arson, are committed for economic gain (Koson and Dvoskin 1982). Additionally, vast majority of the studies in the literature regarding forest crimes agree that the main cause of the forest crimes is economic (Şen and Ünal 2011); (Durkaya et al. 2020); (Schlingemann et al. 2021); (Ünal et al. 2021); (Özden and Ayan 2016). Moreover, they also report that the greatest actors in the forest crimes are the local residents and the poor people who make their living mostly from forestry. Research Gap and Motivation of the Study There are many studies in the literature that deal with strengthening laws, increasing penalties or raising public awareness through education in the fight against forest crimes. However, it is worth investigating how forest crimes are affected if financial supports are provided to people living near forests. Turkey is a country that has been providing financial supports to its forest villagers. Thus, it will be interesting to investigate whether any improvement in the economic conditions of forest villagers through financial supports will lead to a decrease in forest crimes in Turkey. Therefore, in this article, we aim to analyze the relations between the financial supports that are provided to forest villagers by the state and various forest crime types in Turkey. In the literature, there is not a previous study analyzing such a relationship. Another novelty of our study is that the studies in the literature about forest crimes are mostly concentrated on illegal logging crime. However, as well as the illegal logging crime, our study also involves the analyses of other forest crime types committed in Turkey, which are illegal transferring of forest products, illegal expansion of private lands into forests, illegal occupation of forestlands, illegal processing of trees, and illegal pasturage crimes. The plan of the article has been shaped as information about the study area, the data, the variables, the forest crimes, the forestry financial supports in Turkey, and information about correlation analysis are provided in Section “Study Area and Data”. Afterwards, the correlation analyses and the findings of the study with the corresponding discussions are presented in Section “Results and Discussion”. Finally, the conclusions related to the overall study are provided in Section “Conclusions”. Study Area and Data The report published by EUFCI regarding the countries in Danube-Carpathian Region indicates that the local residents and the poor people living around the forest areas are the main actors of the forest crimes in the region (Schlingemann et al. 2021). Similarly, Şen and Ünal (2011) reports that the main causes of the forest crimes in Turkey are the people living in rural areas or villages near forests. Additionally, they state that the most important reason for forest crimes in Turkey is the economic reason. In another study performed in Ilgaz province of Turkey, Ünal et al. (2021) report that the forest crimes are directly correlated with low levels of income, lack of awareness of laws, low penalties, and low education levels. Moreover, in a study performed in Black Sea region of Turkey, Durkaya et al. (2020) found that the income and education levels of the people living in the forest villages had a direct effect on the forest crimes committed. The studies show that one of the main causes of the forest crimes in Turkey is the low level of incomes of the people living in the villages near the forest areas. In Turkey, the state supports the forest villagers in forms of financial supports and cooperative credits. Thus, to investigate the relations between the financial supports provided to forest villagers and forest crimes, Turkey is an appropriate area of study. Turkish forests are under the control of the General Directorate of Forestry (GDF), which is a state agency. Turkey has a forest area of 22,993,000 ha as of 2020 and the forest areas cover 29.4% of the country area. There are also private forests, which are less than two thousandths of the whole forest area (GDF 2021a). The map of the forest assets of Turkey for the year 2020 is demonstrated in Fig. 1 (GDF 2021b).Fig. 1 Forest assets map of Turkey as of 2020 As seen in Fig. 1 the GDF was divided in 28 regional directorates of forestry in Turkey as of 2020. However, Hatay and Sinop were established as regional directorates in 2021. Thus, as of 2021, the GDF is divided into 30 regional directorates, which are Adana, Amasya, Ankara, Antalya, Artvin, Balıkesir, Bolu, Bursa, Çanakkale, Denizli, Elazığ, Erzurum, Eskişehir, Giresun, Hatay, Isparta, İstanbul, İzmir, Kahramanmaraş, Kastamonu, Kayseri, Konya, Kütahya, Mersin, Muğla, Sakarya, Sinop, Şanlıurfa, Trabzon, and Zonguldak directorates. The distribution of the forest assets with respect to the regional directorates of forestry in Turkey are demonstrated in Fig. 2, which is based on the data published by GDF (2021a) for the year 2021.Fig. 2 Distribution of the forest assets (ha) of Turkey as of 2021, with respect to the regional directorates of forestry Figure 2 shows that, in Turkey, Amasya, Elazığ, Şanlıurfa, Antalya, Muğla, and İzmir are the first six regions having the largest forest areas, which are more than one million ha. On the other hand, Çanakkale, Artvin, Sinop, Hatay, and Sakarya are the last five regions having the least forest areas, which are less than 600,000 ha. The most common tree species observed in Turkish forests are oak (Quercus) (29.42%), Turkish pine (Pinus brutia) (22.74%), and black pine (Pinus nigra) (18.31%). The annual amounts of wood in the rough production (m3) in Turkey between the years 2010 and 2021 are given in Table 1 (GDF 2021d).Table 1 Yearly wood production of Turkey in 2010–2021 Years Logs of Coniferous Wood (m3) Logs of Non-Coniferous Wood (m3) (except tropical wood) Fuel Wood (m3) 2010 9,501,980 3,066,539 5,395,779 2011 10,440,865 3,141,597 5,083,576 2012 10,744,778 3,679,587 4,824,506 2013 10,848,147 2,819,840 4,486,277 2014 11,307,865 3,615,344 3,943,496 2015 12,807,215 3,830,383 3,767,240 2016 12,715,352 4,294,646 3,657,801 2017 11,486,044 4,035,579 3,269,735 2018 13,918,115 5,162,022 3,667,841 2019 16,252,761 5,860,487 4,192,349 2020 18,087,054 6,664,012 4,047,510 2021 20,917,243 6,818,025 4,115,526 When Table 1 is examined, it is seen that the amounts of coniferous and non-coniferous log productions in 2021 are almost twice the amounts in 2010. The fuel wood production, on the other hand, mostly has a decreasing trend, except for the slight increases in 2019 and 2021. In Turkey, the Gross Domestic Product (GDP) grew by 4.5% and the industrial sector by 6.2% in the first quarter of 2020. However, due to the negative effects of the Covid-19 pandemic, the GDP contracted by 9.9% and the industrial sector by 16.5% in the second quarter of 2020. The GDP of Turkey as of 2020 is $719.955 billion (World Bank 2020). Although 29.4% of Turkey is covered by forests, income from the forest products has 3% contribution to the state treasure. (GDF 2021d). According to the data published by Social Security Institution (SSI) of Turkey, there are 34,579 workers employed in forest-based industries in 2020 (SSI 2021). Forest Crimes and Forestry Financial Supports in Turkey Forest crimes, in general, can be defined as any action harming forest assets or their future and prohibited by laws to protect forests. A report by World Bank (2006) describes the forest crimes as illicit activities such as illegal logging illegal occupation of forestlands, woodlands arson, wildlife poaching, and encroachment on forests (both on public and private ones). The report also states that the corruption caused by forest crimes all over the world is particularly troubling in developing countries. Although the report addresses the weak governance and subsequent poor law enforcement as the main cause of the forest crimes in the world, it also suggests that poverty reduction approaches targeted at forest-dependent populations committing forest crimes are also needed. In another study by Kishor and Belle (2004), which also supports the improved governance solution to reduce forest crimes, international trade in protected species, logging outside concession boundaries or in protected areas, underrating and misclassifying species, timber smuggling, transfer pricing in timber trade, and timber processing without a license are also considered as forest crimes. Contreras-Hermosilla (2002) provides a detailed list and descriptions of various forest crime types. In Turkey, forest crimes and the corresponding punishments are defined and regulated by Turkish Forestry Law (1956) numbered 6831, which was published in the Official Gazette in Turkey on September 8, 1956. According to Turkish Forestry Law (1956), Article 4, there are three types of accepted forest ownership as state forest, forest belonging to public legal entities, and private forest. State forests are owned and controlled by the GDF as well as processing and manufacturing of all kinds of forest products, as mentioned in Article 89 of Turkish Forestry Law (1956). However, Article 6 states that all forest owned by the other parties than the state are still subject to the control of GDF. Turkish Forestry Law (1956) provides detailed descriptions of many kinds of forest crimes with the corresponding prohibitions, punishments, and fines. In this study, there are six types of forest crimes, which were taken into consideration. These crimes are illegal logging of trees, illegally transferring of the forest products, illegally expanding the lands into the forests, illegal occupation of the forestlands, illegal processing of trees, and illegal pasturages in the state forests. The term illegal logging was used in this study in the context of harvesting timber in contravention of the related laws and regulations. Turkish Forestry Law (1956) defines the illegal logging crime in Article 14 asA. “To cut or uproot grown or planted seedlings to damage plantation areas, to choke or wound trees, to cut their branches and tops or to get produce wooden tiles from the trees.” B. “To cut old or young trees or to uproot them or to get tar or bark or resinous wood from them, to cut leaning or overthrown trees or to take or uproot them on produce coal from them.” The crime of illegally transferring of the forest products is described in Article 108 as “anyone who transports, saws, works, accepts, sells, buys, or keeps illegally harvested or collected forest products is punished”. The term forest product refers to all timber and non-timber products that can be obtained from forests. Additionally, Article 42 states “transportations within the forest are realized in routes determined by the forest management. The transportation permits should always be carried and exposed to related personnel when requested.” Thus, according to Article 100, “transporters of any products without marking on them or without transportation permit document (against Article 41) are punished according to Article 108.” The crime of illegally expanding lands refers to the crime of encroachment on both public and private forests as described by World Bank (2006). This type of crime is committed by expanding private lands (usually farming lands) into the forests by either burning or cutting down the trees, trespassing the forest border line. The illegal occupation crime, however, refers to any kind of building or establishment built on forestland by burning or making use the empty places through invasion, as described in Article 17 of Turkish Forestry Law (1956), which brings regulations for both of illegal expanding and illegal occupation crimes. As well as the illegal logging crime, the crime of illegal processing of the trees is also regarded as a crime by Article 14, which refers to using any kinds of products made from illegally obtained timber from forests, for any purpose like producing wooden tiles or coal. Moreover, Article 108 states, “Anyone who transports, saws, works, accepts, sells, buys, or keeps illegally harvested or collected forest products is punished.” The crime of illegal pasturing is defined by Article 19 as “the access of any kind of domestic animal to forest is prohibited. The forest administration only allows grazing for animals suffering from malnutrition in drought regions.” Additionally, it also states, “this permission can be given under the terms and conditions of a given period, for the defined animal species and areas, and with the condition that no damage should be given to the forest.” Similarly, Article 21 states, “the grazing of herds on the state forestlands should be done according to the plans and permission of the forest administration.” Logging from forests depends on strict regulations in Turkey. Turkish Forestry Law (1956) gives some rights to the Turkish citizens that are eligible to be defined as forest villagers. Forest villager documents are given to people who have been residing in a forest village in Turkey for at least one year. The list of the forest villages is determined by Ministry of Agriculture and Forestry (MAF). Forest villagers are permitted to obtain timber and non-timber products from forests condition to necessary permissions. Article 37 states “except logs, poles, mine props, industrial wood, paper wood, fuel wood, fiber wood, stick resin, resinous wood, boxwood, storax included in the annual production program of the state, all other kinds of forest products and residues are allowed to be utilized in determined locations and periods, giving priority to forest villages, development cooperatives, or to neighboring villagers or workers as with the payment of tariff prices.” While getting these permissions, forest villagers have priority in using the forests next to their villages as mentioned in Article 40. It is also necessary to get permission for hunting in forests in Turkey according to Article 80 of Turkish forestry Law (1956). The article states, “the forest officers are authorized to detain the hunted animals and vehicles of individuals hunting in forests, forest lakes and ponds without hunting license and permission obtained from forest administration.” Elvan (2014) provides a detailed examination and explanation of the forest crime types in Turkey within the framework of criminal law. Turkey provides monetary aids to its forest villagers in forms of individual financial support credits or cooperative credits. To benefit from these loans, it is required to be a registered forest villager. The financial supports are provided to the forest villager families within the frame of the law on Supporting the Development of the Forest Villagers numbered 2924. Financial supports are given in two categories as economic and social credits, which are interest-free loans with a maturity of 3–7 years. Only 1 person from each family is given credit for matters other than microcredit projects for housewives. Re-credit can be given to those who pay the entire debt without delay. The social credits are provided for the purposes of roof covering, exterior sheathing, solar water-heating system installation, solid-fuel heating system installation, internal electrical installation for village houses, buying pellet stove, and pellet central heating system installation. The economic credits, on the other hand, are provided for buffalo breeding, sheep breeding, beekeeping, mushroom cultivation, medical and aromatic plant cultivation, greenhouse, viticulture, and fruit growing. In addition, the economic credits are provided also as micro-credits for housewives and limited contributions for purchasing tractors. The financial credits provided to the forest villagers are not given in the form of grants in equal amounts, but in the form of interest-free repayment loans having certain upper limits that families can use based on their demands, which is the most important advance of these credits. While benefiting from the interest-free financial loans distributed in the specified areas, families are requested to document their expenditures in the relevant areas. The numbers of the families, who are forest villagers, given financial support credits and the total amounts provided to them in 1997–2021 are presented in Table 2 and graphed in Fig. 3. The financial support amounts (in Turkish lira – TL) in Table 2, are adjusted values with respect to the deflator coefficient for the year 2021.Table 2 The numbers of the families given financial support credits and the total amounts (TL) provided in 1997–2021 The Numbers of the Families Given Financial Support Credits Total Amounts Provided (TL) 1997 1812 28,979,731 1998 575 23,138,049 1999 1584 64,569,314 2000 2307 74,235,939 2001 1408 42,892,645 2002 2066 62,920,505 2003 2530 102,705,644 2004 3708 152,271,904 2005 5334 185,533,864 2006 9264 173,625,055 2007 17,629 142,211,630 2008 22,912 133,992,247 2009 22,681 137,177,372 2010 27,232 163,601,434 2011 21,577 180,446,865 2012 17,875 165,980,567 2013 21,081 339,912,316 2014 12,538 251,063,581 2015 10,421 253,167,294 2016 12,309 305,343,475 2017 10,303 258,591,460 2018 8519 216,693,262 2019 9341 238,963,158 2020 9248 270,516,678 2021 11,127 346,912,639 Fig. 3 Time serios plot of the logarithms of the numbers of the families given financial support credits and the logarithms of the total amounts (TL) they receive in 1997–2021 In Fig. 3, due to the scale differences of the numbers in the two data sets, the logarithms of the scores in the data set were taken. When Fig. 3 is examined it is seen that the financial supports (TL) provided to the forest villager families have an increasing pattern between 1997 and 2021. On the other hand, it is observed that the number of families benefiting from these resources increased until 2010, but after this year, a general downward trend continued until 2020, with slight increases in 2013 and 2016. There exist some ground truthing studies, which were performed to investigate the effectiveness of the forestry financial supports in the selected forest villages, such as Önal and Bekiroğlu (2011) performing a study to determine the socioeconomic results of the financial supports provided to the forest villagers in Turkey between the years 1999–2008. They chose the study area as Şile town of İstanbul province, and they interviewed the forest villagers residing in this area and conducted surveys. They applied the surveys to a group of 117 villagers who were randomly selected from the 30 forest villages in this area. The results of the study suggest that the financial forestry supports (provided under the title ORKÖY project) are useful in sustainable management of forest resources in the study area. In other words, the financial supports provided increased the welfare levels of the forest villagers and decreased their dependency on the forests. In another study concerning the ground truthing about the financial supports provided to the forest villagers, Çiray and Ünal (2021) evaluated the results of these projects in the years 2000–2019. They carried out the study in Kütahya province of Turkey by visiting 179 forest villagers, who were provided financial supports, from 32 forest villages located in this area. They used face-to-face survey and in-depth interview methods. They report that 43.6% of the participants stated that they were partially satisfied from such financial supports, 44.7 of them declared that they had no idea. However, 94% of the participants stated that the milk, fattening, and solar energy projects, which were realized by means of the financial supports, were the right (i.e. useful) choices. Similarly, Albayrak (2021) performed a field study among the forest villagers in Artvin, Turkey. The study, which covers Yusufeli, Şavşat, and Ardanuç towns of Artvin province, was carried out between April 2002 and September 2021 by interviewing 12 people forestry villagers, who had migrated to the big cities but later returned to their villages because of the Covid-19 pandemic. The forestry villagers stated that, in the past, they had met their fuel and roofing needs with the help of the provided forestry financial supports and they wanted the supports to be continued. Moreover, Coşgun (2021) performed an analysis of the solar power plant supports in the forest villages in the western Mediterranean region of Turkey, which covers Antalya, Burdur, and Isparta provinces. The aim of the solar power plant implementations is to reduce firewood consumption. The study was carried out on 629 forest villagers living in 100 randomly selected villages from a total of 152 villages and benefiting from solar power plant supports. The findings of the analysis suggest that the solar power plants installed reduces the firewood consumption of the forest villagers. Data and Variables The data consist of the numbers of the crime cases belonging to the dependent variables illegal logging, illegal transferring of forest products, illegal expansion of private lands into forests, illegal occupation of forestlands, illegal processing of trees, illegal pasturages, and the independent variable financial supports provided to forest villager families in 1997–2021. The data were recorded and published by the GDF (2021c). The crime records are based on the number of the forest crime cases caught by forest protection guards employed by the GDF. The definitions and explanations regarding the variables used in the study are provided in Table 3.Table 3 The variables used in the study Variables Definitions The Dependent Variables (Forest Crimes) Illegal logging The annual number of illegal logging crime cases. Illegal transferring of forest products The annual number of the crime cases of illegal transferring of wood products. Illegal expansion of private lands into forests The annual number of the crime cases of illegally expanding private lands into forests through encroachment. Illegal occupation of forestlands The annual number of the crime cases of illegal occupation of lands in forests by building structures for settlement or business. Illegal processing of trees The annual number of the crime cases of illegal processing of trees by producing every kind of wooden items. Illegal pasturages The annual number of the detected illegal pasturage cases. The Independent Variable Financial supports The annual number of the forest villager families that are provided individual financial support credits by the Turkish State. It would be useful to draw the time series plots of the variables to observe their behaviors in the years 1997–2021. Thus, the numbers of the forest villager families that were provided financial support credits by the state and the numbers of the illegal logging, illegal transferring of forest products, illegal expansion of private lands into forests, illegal occupation of forestlands, illegal processing of trees, and illegal pasturage crime cases recorded in Turkey in 1997–2021 are presented in Table 4 and graphed in Fig. 4.Table 4 The data set used in the study Years Financial Supports Illegal Logging Illegal Transferring of Forest Products Illegal Expansion of Private Lands into Forests Illegal Occupation of Forestlands Illegal Processing of Trees Illegal Pasturages 1997 1812 16,184 5741 5130 2340 2310 7131 1998 575 15,044 5911 5429 2375 2140 6385 1999 1584 12,138 4085 5384 3038 1746 3771 2000 2307 11,357 3666 4529 3773 1405 5250 2001 1408 10,963 3529 5258 5080 1554 3281 2002 2066 10,222 4378 5008 3987 1084 3051 2003 2530 10,771 4436 3886 3248 1747 2726 2004 3708 8472 3246 3573 2830 697 3720 2005 5334 7332 2767 3981 3484 624 3758 2006 9264 5956 2052 2837 2446 399 3035 2007 17,629 6028 1900 2836 2292 288 3356 2008 22,912 5020 1651 2393 2185 313 2733 2009 22,681 4946 1692 2283 2437 299 2066 2010 27,232 4114 1339 3019 4089 300 1952 2011 21,577 3742 841 2337 2947 213 1448 2012 17,875 4149 1017 2013 2963 178 1711 2013 21,081 3620 892 1930 2623 169 1684 2014 12,538 3519 689 2209 2628 133 1571 2015 10,421 2944 708 1971 2103 82 1005 2016 12,309 2891 658 2332 2996 68 1032 2017 10,303 2993 802 2473 2241 68 1067 2018 8519 2880 670 3465 3221 58 818 2019 9341 3356 706 3550 3549 96 834 2020 9248 4532 786 5096 4642 92 962 2021 11,127 4047 548 6043 5987 88 802 Fig. 4 The numbers of the families receiving financial supports and the numbers of the forest crime cases in Turkey for the years 1997–2021 When Fig. 4 is examined, in general, it can be said that the number of the families being provided individual financial supports follows an increasing pattern until 2010 except some decreases in certain years such as 1998, 2001, 2009. After 2010, however, the number of the families receiving financial supports has a decreasing trend with slight increases in 2013 and 2016 until the year 2018. The numbers of the families seem to have an increasing trend again after 2018. The probable reasons for the sharp decreases in the financial supports provided by the state in the years 2001, 2008, 2014, and 2018 are the economic crises experienced in Turkey during these years. In fact, the 2018 crisis was a global economic crisis that also affected Turkey. In 2014, however there was a dramatic loss in the exchange rate of the Turkish lira (TL) against the United States Dollar (USD), which caused a serious decrease in the purchasing power of the TL. Thus, less amount of money was put into circulation, to prevent the TL from losing its value more. In general, the crime of illegal logging displays a decreasing pattern between 1997 and 2018 except for the little increases in 2003, 2007, 2012, and 2014. The most important reason for the extraordinary increase in 2014 is that there was a considerable decrease in the value of the TL against the USD in 2014, which is followed by a sharp increase in the interest rates. This situation caused a serious decrease in the purchasing power of Turkish citizens. After 2018, however, there is an extraordinary increase in the illegally logging crime level reaching its peak in 2020. Afterwards, the crime levels seem to have a decreasing trend. Meanwhile the increase in the year of 2020 is notable. This increase can be explained by the conditions due to the Covid-19 pandemic, which started in this year. One possible condition for this extraordinary increase can be given as the curfews, which prevented people from working and caused a dramatic decrease in incomes. In addition, the curfews also caused less security controls in the forests, which caused criminals to act more freely than usual (Lang et al 2021); (GDF 2021d). It can also be seen that the crime case numbers of illegal transferring of forest products have some little peak points in the years of 1998, 2003, and 2017. However, the case numbers visibly fluctuate between the years 1997 and 2007. On the other hand, they remain almost linear with a slightly decreasing trend afterwards. Moreover, it is also possible to see that the case numbers belonging to the crime of illegal expansion of private lands into forests fluctuate in a slightly decreasing way with small peaks and troughs between 1997 and 2012. The case numbers remain almost steady between 2012 and 2017. However, they quickly increase afterwards, reaching its peak in 2021. Meanwhile, the sharp increase in 2020, the beginning of the Covid-19 pandemic, is also noticeable for this type of crime. When the crime graph of illegal occupation of forest lands is analyzed, a rapid upward trend is observed from 1997 to 2001. Afterwards, with a slight increase in 2005, there is a decreasing trend until 2008. In the following years, there is not much fluctuation until 2017, except for the small increase in 2016. However, after 2017, a sharp increase occurred for this type of crime and reached its peak in 2021. As for the crime of illegal processing of trees, although the numbers of cases of this type of crime fluctuated slightly, creating two small peaks in 1997 and 2003, it is seen that they decreased after 2003 and remained almost at the same level until 2021. When it comes to the number of illegal pasturage numbers crime, it is observed that they experienced a rapid decline from 1997 to 1999. However, they increased rapidly afterwards and peaked in 2000. Afterwards, they decrease rapidly until 2003. After this year, with two peaks observed in 2004 and 2005, they show a decreasing trend until 2021 with an approximately flat pattern. The total numbers of the cases for all forest crime types, which were encountered in the regional directorates of forestry and reported by GDF (2021d) for the year 2020, are presented in Fig. 5.Fig. 5 The total numbers of the forest crimes seen in the regional directorates of forest in Turkey as of 2020 Figure 5 shows that the highest numbers of forest crimes are seen in Amasya, Sakarya, Adana, Kahramanmaraş, Antalya, and İzmir regions, which have forest crime cases over one thousand. However, the crime levels are seen the least in Çanakkale, Kütahya, and Ankara regions, which have cases less than 250. It can be expected that the level of crimes will be higher in the regions having larger forest areas. However, when Fig. 2 and Fig. 5 are examined together, this expectation appears to be not realistic. For example, although Amasya directorate has the largest forest area and the highest level of crimes, Elazığ, for example, has the second largest forest area but considerably low level of crimes. Similarly, Sakarya has a smaller forest area compared to the other directorates, but the level of the forest crimes is remarkably high in this directorate. A more realistic explanation for the differences observed in the distribution of these crimes by region is that, as stated in the 2021 activity prepared by the GDF, the number of protection officers has been increased in the regions where forest assets and forest crimes are intense, and a more intense observation activity has been carried out in cooperation with the headmen in the forest villages (GDF 2021e). As far as the reliability of the data is concerned, apparently, the GDF provides data about various forest crimes including illegal logging in Turkey, which are provided in Section “Forest crimes and forestry financial supports in Turkey”. Thus, it is evident that there is a certain amount of illegal logging in Turkey. However, in some international studies, such as Li et al. (2008), it is reported that the estimated share of the illegally logged industrial round wood in Turkey is 0% as of 2004. Additionally, a report by the United Nations Economic Commission for Europe (UNECE) published in 2006 notes that Turkish forest law enforcement, governess, guarding and controlling system against forest crimes are strong and strict for long time, thus, illegal logging and associated forest crimes are not at high levels. Additionally, it also reports the rates of illegal logging for commercial use is quite low and not a significant issue to international trade (UNECE 2006). Correlation Coefficient Correlation coefficient measures the degree and the direction of the linear relation between two variables. A significant correlation coefficient also indicates a dependency relation between the variables for which it is calculated. There are various measures to calculate correlation coefficient such as Pearson and Spearman correlation coefficients. Pearson correlation coefficient is a parametric method, while Spearman correlation coefficient is a nonparametric measure of correlation. Pearson correlation coefficient requires some assumptions before it is calculated. These assumptions are linearity, continuous-level variables, homoscedasticity, normality, absence of outliers and independence. To test whether the normality assumption required by Pearson correlation coefficient holds for the variables employed in the study, Table 5 presents the variables having a normal distribution, and the ones not normally distributed.Table 5 Normality test results of the variables (α = 0.05) Variables Kolmogorov–Smirnov Statistic P-value Normally Distributed Illegal logging 0.221 0.010 No Illegal transferring of forest products 0.194 0.022 No Illegal expansion of private lands into forests 0.154 0.126 Yes Illegal occupation of forestlands 0.158 0.105 Yes Illegal processing of trees 0.276 0.010 No Illegal pasturages 0.148 0.150 Yes Financial supports 0.125 0.150 Yes It is apparent in Table 5 that not every variable has a normal distribution, such as the variables illegal logging, illegal transferring of forest products, and illegal processing of trees. To check another assumption of Pearson correlation coefficient of absence of outliers, Table 6 demonstrates the outlier analysis results of the data. The outlier analysis was performed based on a nonparametric approach, which is interquartile range, as a common measure for all the variables; as it has already been shown that there are variables in the data set having non-normal distributions.Table 6 Outlier analysis results of the variables Variables N Q1 Q3 Interquartile Range Outlier – Year Illegal logging 25 3569.5 10496.5 6927 None Illegal transferring of forest products 25 747 3597.5 2850.5 None Illegal expansion of private lands into forests 25 2334.5 5052 2717.5 None Illegal occupation of forestlands 25 2406 3661 1255 5987 – (2021) Illegal processing of trees 25 94 1244.5 1150.5 None Illegal pasturages 25 1049.5 3538 2488.5 None Financial supports 25 2418.5 17752 15333.5 None Table 6 shows that the variable named illegal occupation of forestlands has an outlier value as 5987 belonging to the year of 2021. Additionally, to check the homoscedasticity assumption before using Pearson correlation coefficient, Table 7 presents the homoscedasticity test results between the independent variable financial supports and the dependent variables.Table 7 Homoscedasticity test results of the variables (α = 0.05) Dependent Variables Independent Variable Bonett’s Statistic P-value Homoscedasticity Illegal logging Financial supports 9.98 0.002 No Illegal transferring of forest products 35.25 0 No Illegal expansion of private lands into forests 45.74 0 No Illegal occupation of forestlands 60.58 0 No Illegal processing of trees 77.38 0 No Illegal pasturages 34.62 0 No When Table 7 is examined, it is seen that there is no homoscedasticity between the independent variable financial supports and any dependent variable. It is evident that, the assumptions of normality and absence of outliers failed for some variables. Moreover, homoscedasticity assumption failed for all the variables. Furthermore, when a correlation coefficient is to be calculated between two time series, Pearson correlation coefficient cannot be used directly, as it is appropriate for independent data. However, time series data is usually dependent on time. Thus, these results indicate that Pearson correlation coefficient is not an appropriate measure to use for the variables employed in the study. Spearman correlation coefficient, however, is a nonparametric method, which does not require any normal distribution or the other assumptions required by Pearson correlation coefficient except the linearity assumption. Thus, it can be an alternative to Pearson correlation coefficient, when its assumptions are not met. Therefore, in this study, Spearman correlation coefficient was adopted to analyze the relations between forestry financial supports and the forest crimes listed in Table 3. While calculating Spearman correlation (rs) for two variables X and Y, firstly they are converted to ranks as R(X) and R(Y). Then, Pearson correlation (ρ) formula is used to calculate the correlation between the ranked variables. Spearman correlation coefficient is calculated as follows.1 rs=ρRXRY=CovRX,RYσRXσRY where rs denotes Spearman correlation coefficient, Cov[R(X), R(Y)] is the covariance of the ranked variables, σR(X) and σR(Y) are the standard deviations of the ranked variables R(X) and R(Y) respectively. Just like Pearson correlation coefficient, Spearman correlation coefficient also varies between −1 and +1. Results and Discussion Spearman correlation coefficient gives the degree and the direction of the linear relation between two variables, for which it is calculated. To see the pattern of the relations between the dependent variables illegal logging, illegal transferring of forest products, illegal expansion of private lands into forests, illegal occupation of forestlands, illegal processing of trees, illegal pasturages and the independent variable financial supports, the corresponding scatterplot diagrams are presented in Fig. 6.Fig. 6 Scatterplot diagrams between the dependent variables and the independent variable provided in Table 3 When Fig. 6 is examined, it is seen that the pattern of the relation between each dependent variable and the independent variable is roughly linear with a decreasing tendency except the dependent variable named illegal occupation of forestlands. Moreover, it is apparent that illegal occupation of forestlands variable has an outlier value, which is reported also by the test results presented in Table 6. However, as Spearman correlation coefficient is robust to the possible outliers, the detected outlier was not removed from the data set. Thus, the correlation analysis results between the independent variable financial supports and the dependent variables under consideration are presented in Table 8 depending on Spearman correlation coefficient.Table 8 Correlation analysis results of the variables (α = 0.05) Dependent Variables Independent Variable Spearman Correlation Coefficient P-value Significance Illegal logging Financial supports −0.631 0.001 Yes Illegal transferring of forest products −0.6 0.002 Yes Illegal expansion of private lands into forests −0.762 0 Yes Illegal occupation of forestlands −0.256 0.216 No Illegal processing of trees −0.563 0.003 Yes Illegal pasturages −0.504 0.01 Yes As seen in Table 8, Spearman correlation coefficient between the numbers of illegal logging cases and the numbers of the families receiving financial supports was calculated as −0.631 with a p-value of 0.001, which is less than α = 0.05. Thus, the calculated correlation coefficient indicates a moderate level of significant negative correlation between the variables under consideration. Therefore, it can be concluded that the financial supports provided to the forest villager families seem to help reducing the illegal logging crime levels. One of the possible reasons to explain this situation may be the fact that the financial supports provided to the forest villager families also cover the monetary aids given for heating and cooking facilities using coal, gas, electric (including solar), or legally purchased wood. The finding that financial supports helps reducing the illegal logging activity is supported by many studies, such as Gençay and Mercimek (2019), who suggest that the best way of preventing forest crimes are to increase the income of the people and reduce their need for forests and forest resources. Similarly, Alemagi and Kozak (2010) count poverty among the causes of the illegal logging activities in Cambodia. They also report that some employment was provided to villagers to curb illegal logging. On the other hand, in a study performed by Daşdemir and Köse (2021), which examined the effects of financial supports and informational and training-consulting services in İstanbul region, they suggest that these activities decreased the levels of legal and illegal logging cases; however, they did not have any effects on forest growing and other forest crimes. As far as the crime of illegal transferring of forest products and the financial supports are considered, Spearman correlation coefficient was calculated as −0.6 for these variables with a p-value of 0.002. The calculated p-value is less than α = 0.05, which means the calculated negative correlation coefficient is significant. Thus, it turns out that the financial supports provided reduce the crime of illegal transferring of forest products as well as the crime of illegal logging. When it comes to the variables of illegal expansion of private lands into forests and financial supports, Spearman correlation coefficient was calculated as −0.762 with a p-value of 0. As the p-value is quite smaller than α = 0.05, there seems to be a strong significant negative correlation between the number of the financial supports provided and the number of the crime cases of illegal expansion of private lands into forests. In addition, it turned out that the financial supports provided were most beneficial in reducing the number of cases belonging to this type of forest crime. Speaking of the variables of illegal occupation of forestlands and financial supports, Spearman correlation coefficient was calculated as −0.256 with a p-value of 0.216, which is quite greater than α = 0.05. Therefore, it appears that, there is not a significant correlation between financial supports and illegal occupation of forestlands variables. When the variables illegal processing of trees and financial supports are concerned, Spearman correlation coefficient was calculated as −0.563 with a p-value of 0.003. Therefore, it can be said that there is a significant and moderately strong negative correlation between financial supports and illegal processing of trees variables. For illegal pasturages and financial supports variables, the calculated Spearman correlation coefficient is −0.504 with a p-value of 0.01, which implies a significant negative correlation and a moderate dependency between these variables. Thus, it is again possible to comment that the provided financial supports significantly reduce the number of illegal pasturages. Conclusions In conclusion, the overall results of our study suggest that except for the crime of illegal occupation of forestlands, the financial supports provided to the forest villager families in Turkey significantly reduce the levels of illegal logging, illegal transferring of forest products, illegal expansion of private lands into forests, illegal processing of trees, and illegal pasturage crimes. Therefore, it is possible to conclude that the financial support provided has not been successful in stopping the crime of occupation of forest areas, which is a relatively “more profitable” type of crime. Since, when the criminals commit this crime, they acquire lands or buildings in forest areas without paying any price. This study can be repeated in other countries, where the same or different types of financial supports are provided to people living in the settlements near forests, to observe whether they change the levels of the forest crimes committed. Thus, it would also be possible to make comparisons among the behaviors of the criminals in different countries. Author Contributions The sole author of this manuscript is solely responsible for all the contributions made in the manuscript. Data availability The data used in this study is provided in a tabular form within the article. Compliance with Ethical Standards Conflict of Interest The author declares no competing interests. Consent to Participate The sole author of this manuscript consents to participate. Consent to Publish The sole author of this manuscript consents to publish. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Albayrak L Return to the Village During the Pandemic; Developments in the Economic and Cultural Structure of the Rural, Example of Artvin (in Turkish) Erzincan Üniversitesi Sos Bilimler Enstitüsü Derg 2021 14 20. Bölge Bilimi ve Planlama Kongresi Özel Sayısı 63 75 Alemagi D Kozak RA Illegal logging in Cameroon: Causes and the path forward For Policy Econ 2010 12 8 554 561 10.1016/j.forpol.2010.07.008 Bösch M (2021) Institutional quality, economic development and logging: a quantitative cross-national analysis. European J Forest Res 140(5):1049–1064 Brantingham PL, Brantingham PJ (2017) Environment, routine, and situation: Toward a pattern theory of crime. In: Routine activity and rational choice (pp. 259–294). Routledge Contreras-Hermosilla A Law compliance in the forestry sector: an overview 2002 Washington, DC World Bank 48 Coşgun U Economic analysis in social responsibility projects of forest villages (case of the western Mediterranean region) Eurasia J For Sci 2021 9 3 160 174 Çiray İ Ünal HE Analysis of the Application Results of the Loans Given by ORKÖY in Kütahya Central District Forest Villages (2000-2019) (in Turkish) Eurasia J For Sci 2021 9 3 246 258 10.31195/ejejfs.998708 Daşdemir İ, Köse M (2021). The Impact of ORKÖY Activities on Sustainable Forest Management in İstanbul Province, Turkey. Small-scale Forestry, 1-26. Durkaya B Kaptan S Durkaya A Socio-economic and cultural sources of conflict between forest villagers and forest; a case study from Black Sea Region, Turkey Crime, Law Soc Change 2020 74 2 155 173 10.1007/s10611-020-09883-5 Elvan OD Forest offences in 21st Century Turkey (with the example for the offender and trial period of use of the forests in Istanbul) Int J Law, Crime Justice 2014 42 4 324 339 10.1016/j.ijlcj.2014.04.002 EP (2021) https://www.europarl.europa.eu/factsheets/en/sheet/105/the-european-union-and-forests GDF 2020 Türkiye Orman Varlığı, T.C 2021 Ankara, Turkey Tarım ve Orman Bakanlığı Orman Genel Müdürlüğü Orman İdaresi ve Planlama Dairesi Başkanlığı, OGM Ofset GDF (2021b) 2020 Türkiye Orman Varlığı Haritası.jpg, https://www.ogm.gov.tr/tr/ormanlarimiz/Turkiye-Orman-Varligi GDF (2021c) https://www.ogm.gov.tr/tr/e-kutuphane/resmi-istatistikler GDF (2021d) https://www.ogm.gov.tr/tr/e-kutuphane-sitesi/FaaliyetRaporu/Orman%20Genel%20M%C3%BCd%C3%BCrl%C3%BC%C4%9F%C3%BC%202021%20Y%C4%B1l%C4%B1%20Faaliyet%20Raporu.pdf GDF (2021e) https://www.ogm.gov.tr/tr/e-kutuphane-sitesi/FaaliyetRaporu/Orman%20Genel%20M%C3%BCd%C3%BCrl%C3%BC%C4%9F%C3%BC%202021%20Y%C4%B1l%C4%B1%20Faaliyet%20Raporu.pdf Gençay G Mercimek A Public consciousness and influence of law on forest crimes: Insights from Kastamonu, Turkey For Policy Econ 2019 106 101978 10.1016/j.forpol.2019.101978 Gunes Y Elvan OD Illegal logging activities in Turkey Environ Manag 2005 36 2 220 229 10.1007/s00267-003-0107-1 Interpol (2021) https://www.interpol.int/en/News-and-Events/News/2020/Forestry-crime-targeting-the-most-lucrative-of-environmental-crimes Kishor N Belle A Does improved governance contribute to sustainable forest management? J Sustain Forestry 2004 19 1-3 55 79 10.1300/J091v19n01_04 Kitteringham G (2010) Environmental Crime Control. In The Professional Protection Officer, 151–160. Oxford, England: Butterworth-Heinemann. Koson DF Dvoskin JOEL Arson: A diagnostic study Bull Am Acad Psychiatry Law 1982 10 1 39 49 7139133 Lang Y, Gondo P, Moeini-Meybodi H (2021) Financing sustainable forest management: a key component of sustainable COVID-19 recovery. United Nations Department of Economic and Social Affairs, Decade of Action, Policy Brief No: 88 Li R Buongiorno J Turner JA Zhu S Prestemon J Long-term effects of eliminating illegal logging on the world forest industries, trade, and inventory For Policy Econ 2008 10 7-8 480 490 10.1016/j.forpol.2008.04.003 Lochner L Moretti E The effect of education on crime: Evidence from prison inmates, arrests, and self-reports Am economic Rev 2004 94 1 155 189 10.1257/000282804322970751 Önal P Bekiroğlu S Studies on the Effectiveness of Various ORKOY Village Development Projects in Forest Villages: İstanbul-Şile Case (in Turkish) J Fac Forestry Istanb Univ 2011 61 2 53 66 Özden S Ayan S Forest crimes as a threat to sustainable forest management Sibirskij Lesnoj Zurnal\Siberian J For Sci 2016 4 49 55 Schlingemann L De Bortoli I Favilli F Egerer H Musco E Lucas T Lucius I Combating Wildlife and forest Crime in the Danube-Carpathian region 2021 Brussels, Belgium World Wide Fund for Nature (WWF) Setiono B, Husein Y (2005) Fighting forest crime and promoting prudent banking for sustainable forest management. Centre for International Forestry Research (CIFOR) Occasional Paper No, 44. SSI (2021) http://www.sgk.gov.tr/wps/portal/sgk/tr/kurumsal/istatistik/sgk_istatistik_yilliklari Şen G Ünal S A Research on reasons of forest crimes: Karadere forests administration model Artvin Çoruh Üniversitesi Orman Fakültesi Derg 2011 4 1 41 51 Thompson ST Magrath WB Preventing logging For Policy Econ 2021 128 102479 10.1016/j.forpol.2021.102479 Tomaselli I Brief study on funding and finance for forestry and forest-based sector 2006 Curitiba, Brazil UNFF–United Nations Forum on Forests Turkish Forestry Law (1956) https://www.lawsturkey.com/law/forest-law-6831 UNECE (2006) https://unece.org/fileadmin/DAM/timber/mis/market/market-64/turkey.pdf Ünal E., Birben Ü, OD Elvan (2021). Public perception of forest crimes: The case of Ilgaz Province in Turkey. Crime, Law and Social Change, 1–20 World Bank Strengthening forest law enforcement and governance - addressing a systemic constraint to sustainable development. Report No. 36638-GLB 2006 Washington D.C The World Bank World Bank (2020) https://data.worldbank.org/indicator/NY.GDP.MKTP.CD?locations=TR
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==== Front J Gastrointest Surg J Gastrointest Surg Journal of Gastrointestinal Surgery 1091-255X 1873-4626 Springer US New York 5551 10.1007/s11605-022-05551-2 Original Article Liver Venous Deprivation Versus Portal Vein Embolization Before Major Hepatectomy for Colorectal Liver Metastases: A Retrospective Comparison of Short- and Medium-Term Outcomes Cassese Gianluca 1 Troisi Roberto Ivan 1 Khayat Salah 2 Benoudifa Bachir 3 Quenet Francois 4 Guiu Boris 3 Panaro Fabrizio [email protected] 2 1 grid.4691.a 0000 0001 0790 385X Department of Clinical Medicine and Surgery, Division of Minimally Invasive and Robotic HPB Surgery and Transplantation Service, University of Naples “Federico II”, Naples, Italy 2 grid.157868.5 0000 0000 9961 060X Department of Digestive Surgery and Liver Transplantation, Montpellier University Hospital, Montpellier, France 3 grid.157868.5 0000 0000 9961 060X Department of Diagnostic and Interventional Radiology, Montpellier University Hospital, Montpellier, France 4 Department of Surgical Oncology, Montpellier Oncologic Institute – ICM, Montpellier, France 12 12 2022 110 25 4 2022 18 11 2022 © The Society for Surgery of the Alimentary Tract 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Background Liver venous deprivation (LVD) is a recent radiological technique performed to induce hypertrophy of the future liver remnant. Medium-term results of major hepatectomy after LVD have never been compared with the actual standard of care, portal vein embolization (PVE). Methods We retrospectively compared data from 33 consecutive patients who had undergone LVD (n = 17) or PVE (n = 16) prior to a right hemi-hepatectomy or right extended hepatectomy indicated for colorectal liver metastases (CRLM) between May 2015 and December 2019. Results The 1-year and 3-year overall survival (OS) rates in the LVD group were 81.3% (95% confidence interval [CI]: 72–90) and 54.7% (95% CI: 46–63), respectively, against 85% (95% CI: 69–101) and 77.4% (95% CI: 54–100) in the PVE group; the differences were not statistically significant (p = 0.64). The median disease-free survival (DFS) rate was also comparable: 6 months (95% CI: 4–7) in the LVD group and 12 months (95% CI: 1.5–13) in the PVE group (p = 0.29). The overall intra-operative and post-operative complication rates were similar between the two groups. The mean daily kinetic growth rate (KGR) was found to be higher after LVD than after PVE (0.2% vs. 0.1%, p = 0.05; 10 cc/day vs. 4.8 cc/day, p = 0.03), as was the mean increase in future liver remnant volume (FLR-V) (49% vs. 27%, p = 0.01). Conclusions The LVD technique is well tolerated in patients undergoing right hemi-hepatectomy or right extended hepatectomy for CRLM. When compared with the PVE technique, the LVD technique has similar peri-operative and medium-term outcomes, but higher KGR and FLR-V increase. Keywords Liver venous deprivation Portal vein embolization Major hepatectomy Future liver remnant ==== Body pmcIntroduction Colorectal cancer (CRC) is the third most frequent cause of cancer death worldwide, and approximately 25–30% of patients diagnosed with CRC develop liver metastases.1,2 Liver resection is considered the cornerstone treatment for colorectal liver metastases (CRLM), achieving 5-year survival rates higher than 50%, showing low morbidity and mortality in highly experienced centers.3,4 With the evolutions in medicine and surgery, the indications for the surgical treatment of CRLM have expanded in recent years.5 Unfortunately, until now, only about 25% of all CRLM patients are susceptible to undergo resection.6 Though parenchymal-sparing hepatectomy (PSH) is considered the standard of care strategy for CRLM, many patients need to undergo major hepatectomy because of their large tumor size or the relationship between the tumor and the main vascular structures.7 Owing to inadequate future liver remnant volume (FLR-V), less than 25% of patients are eligible for major hepatectomy at the time of cancer diagnosis.8 This is because a major hepatectomy can cause post-hepatectomy liver failure (PHLF), which is the leading cause of death after the resection of three or more liver segments.9 Therefore, to minimize the risk of PHLF, sufficient FLR-V must therefore be preserved.10 It is generally accepted that PHLF is likely to occur in patients whose FLR-V is less than 25% of the total volume of a normal liver or 30% of a fatty liver, who have had multiple courses of chemotherapy or who have 40% of a liver with cholestasis or cirrhosis.11 To optimize the FLR, several techniques have been developed to induce liver hypertrophy. Since its introduction in 1984 by Makuuchi et al., portal vein embolization (PVE) has been considered the standard technique for inducing FLR increase.12,13 However, PVE does not always induce sufficient and rapid hypertrophy: Up to 20% of treated patients are still unfit for completion surgery after a relatively long time (4–6 weeks) following the procedure due to insufficient FLR increase or tumor progression.14 To overcome these limitations, a new interventional radiological technique was described in 2016: hepatic venous deprivation (LVD).15 It consists of the simultaneous embolization of the portal vein and one or two hepatic veins (extended liver venous deprivation) in order to increase the damage to the contralateral liver and further induce hypertrophy of the FLR (approximate kinetic growth rate = 16 ± 7 cc/day, according to the initial reports).16,17 The first comparative data regarding the volume and functional increase of FLR were recently published, showing a greater regeneration after LVD than after PVE.18 The impact of LVD on hepatic recurrence (HR) and medium-term results after CLRM resection remains unclear. Furthermore, no studies have evaluated the early intra- and post-operative results after right hemi-hepatectomy and right trisectionectomy in CRLM patients in this setting. This retrospective study was therefore carried out to compare the short- and medium-term outcomes of major hepatectomy after LVD with those after PVE. Materials and Methods Study Design This was a single-institution retrospective study conducted according to the Strengthening and Reporting of Observational Studies in Epidemiology (STROBE) guidelines of the EQUATOR network.19 Informed consent was obtained prior to the radiological and surgical procedures. This study was approved by the Institutional Ethics Committee of the University Hospital of Montpellier (IRB-MTP_2020_04_202000444). Patients Data from patients who underwent consecutive LVD prior to right hemi-hepatectomy or right extended hepatectomy (trisectionectomy) for colorectal cancer metastases at the University Hospital of Montpellier between May 2015 and December 2019 were retrospectively collected and analyzed. Patients with liver cirrhosis were excluded from this study. The flowchart of the study is shown in Fig. 1. The choice of the therapeutic management of each of the included patients was taken after a previous discussion during a multidisciplinary oncology meeting. The decision to perform a liver augmentation procedure was based on the FLR volume and/or functional assessment using mebrophenin Tc-99 m scintigraphy. The radiological procedure was performed when the expected FLR was < 25% in the normal liver, < 30% in the liver that had undergone chemotherapy, or < 40% in cases of underlying liver disease (cholestasis), and when the Tc99m mebrophenin extraction was < 2.69%/min/m2. When both the volume and function of the FLR were insufficient, or when liver scintigraphy was not available, LVD was performed instead of PVE alone due to the fact that LVD showed a greater volumetric increase. Patient follow-up after LVD was based on contrast computed tomography (CT) and Tc99m-mebrofenin scintigraphy performed weekly after the procedure. Radiological and surgical procedures, as well as patient management, were performed by the same team in the same facility.Fig. 1 Flow chart: diagram of patients’ selection for the retrospective study; LVD: liver venous deprivation; PVE: portal vein embolization; eLVD: extended liver deprivation (portal vein embolization + right and middle hepatic vein embolization); CRLM: colorectal liver metastases To compare the results obtained with LVD, data were retrospectively collected from consecutive patients who underwent the same type of liver resection for CRLM after PVE during the same time period. Radiological Procedure The LVD technique has previously been described in detail.15 Summarily, the right hepatic vein (and accessory vein, when present) was cannulated through trans-hepatic access under ultrasound guidance using a B1-stick technique.20 Initial PVE was performed through right trans-hepatic access. The right portal vessels were embolized using n-butyl cyanoacrylate and lipiodol (ratio 1:6). The micro guidewire placed in the hepatic vein(s) was then used to position an Amplatzer II vascular plug (75% opening). The plug was positioned at a distance of approximately 2 cm from the ostium of the inferior vena cava (IVC) to reduce the risk of plug overlength. Finally, all distal venous branches were embolized using a mixture of n-butyl cyanoacrylate and lipiodol (ratio 1:6). Eight patients also underwent embolization of the middle hepatic vein, a procedure called extended liver deprivation (eLVD). The decision to embolize the middle hepatic vein was made by the radiologist based on the size of the FLR, type of surgery, and anatomical characteristics of the hepatic vein circulation. Surgical Intervention Patients either underwent laparotomic right hemi-hepatectomy (segments 5–8), according to the Brisbane classification of liver resections, or extended right hepatectomy (trisectorectomy).21 An intra-operative ultrasound was performed to confirm the surgical feasibility of the procedure and to guide the resection. The right hepatic artery and portal vein were systematically ligated and dissected before parenchymal sectioning using an anterior approach. The hepatic veins were closed and divided using a vascular stapler; the Amplatzer-type plug did not prove to be an obstacle in this regard. If necessary, a Pringle maneuver with intermittent clamping or selective right portal vein control was performed. Post-Operative Follow-up Post-operative follow-up data were analyzed. Post-operative complications were classified according to the Clavien–Dindo classification.22 PHLF, post-hepatectomy bile leakage (PHBL), and post-hepatectomy hemorrhage (PHH) were diagnosed and classified according to the International Study Group of Liver Surgery (ISGLS) guidelines.23–25 Ascites was defined following the International Ascites Club definition.26 Synchronous metastases were defined, according to the Expert Group on OncoSurgery Management of Liver Metastases group (EGOSLIM) definition, as metastases detected by pre-operative screening or during resection of the primary tumor.27 All patients were examined within one month after discharge from the surgery department and underwent clinical, biological, and imaging evaluations every 3 months after discharge for the first two years, according to the oncological protocols. Outpatients’ controls were scheduled every 12 months if no relapse was found. In case of tumor recurrence, the case was re-examined by a multidisciplinary team (MDT) with the aim of carrying out curative treatment as much as possible. Hypertrophy Parameters The volume share of the FLR (FLR-V%) was calculated from manual reconstruction using the formula described by Vauthey et al.28: FLR-V share = FLR-V/(eTLV − TV) × 100, where eTLV = –794.41 + 1267.28 × body surface area. To compare hypertrophy responses, the kinetic growth rate (KGR) was calculated as the percentage growth per day [degree of hypertrophy (DH) at the first post-procedural volume assessment (%)/elapsed interval from the radiological procedure (days)], as well as in volume (cc) growth per day, that is, (FLR-V after intervention – FLR-V prior to intervention)/time elapsed.29 The degree of hypertrophy was calculated using the following formula30,31: post-proceduralFLR-V%-pre-proceduralFLR-V% The increase in the FRL-V% was calculated using the following formula: FLRincrease=FLRinterstage-FLRbaseline×100%. Volumes were compared with the last imaging exam performed before surgery. Statistical Analysis and Endpoints Continuous data were expressed as mean and standard deviation (SD) or median and interquartile range (IQR), depending on whether they had a normal distribution or not. Group comparisons were performed using Student’s T test or Wilcoxon’s rank test, depending on the distribution of the variable. Categorical data were expressed as frequencies and associated percentages. Comparisons between groups were performed using Pearson’s chi-squared test or Fisher’s exact test, depending on the expected value of the variable of interest.32 The primary endpoints were the overall survival (OS) and disease-free survival (DFS) rates. Secondary endpoints were peri-operative complications. All survival analyses were performed using the Kaplan–Meier method to calculate the median and 95% confidence interval (CI), and comparisons were performed using the log-rank method. The median follow-up was analyzed using the inverse Kaplan–Meier method. Statistical analysis was conducted using the software Statistical Package for Social Sciences (SPSS) software (version 26.0). Results Patients’ Characteristics We retrospectively reviewed data from 17 consecutive patients who underwent LVD and 16 who underwent PVE prior to right hemi-hepatectomy or right extended hepatectomy (trisectionectomy) for CRLM. The mean age of the patients was 58.9 years (± 9.6). All LVD patients underwent chemotherapy (CT) prior to the liver surgery, against only 12 PVE patients. Among the LVD patients, 13 (77%) received neoadjuvant CT and 4 (23%) underwent a conversion surgery. Table 1 lists the different CT schemes used and the responses of the patients to the schemes. Fourteen patients additionally received post-operative CT (82.3%). No statistically significant differences were found in the pre-operative characteristics of the two groups. The patients’ and tumor characteristics are shown in Table 1. Regarding patients who underwent PVE, four (25%) had undergone previous hepatic surgery and two (12.5%) had undergone thermal ablation. The overall median follow-up period was 26 months (95% CI: 17–29).Table 1 Patients’characteristics LVD (n = 17) PVE (n = 16) p-value Age (mean, SD) 58.9 (9.6) 65.2 (9.5) 0.81 Sex, M/F (%) 13/4 (76/24) 7/9 (44/56) 0.16 Primary tumor localization, n(%)   Right colon 5 (29.5) 4 (25) 0.41   Left colon 11(64.5) 8 (50) 0.37   Rectum 1 (5.8) 4 (25) 0.13   Tumor size, median in mm (IQR25–75) 40 (21–52.5) 29 (18–67) 0.97   Tumor nodules, median (IQR25–75) 2 (1–4.5) 2 (1–5) 0.68 KRAS mutational status, n (%)   Mutated 7 (41.1) 6 (37.5) 0.73   Wild type 10 (58.8) 10 (62.5) BRAF mutational status, n (%)   Mutated 2 (11.7) 0 (0) 0.48   Wild type 15 (88.3) 16 (100) Liver metastasis presentation, n (%)   Synchronous 14 (82.3) 12 (75) 0.23   Metachronous 3 (17.5) 4 (25) 0.56 First CRC stadium, n (%)   T1N1M0 1 (5.8) 0 (0)   T3N0M0 1 (5.8) 2 (12.5)   T3N1M1 4 (23.5) 3 (18.7)   T3N2M1 7 (41.1) 7 (43.7)   T4N1M0 2 (11.7) 2 (12.5)   T4N2M1 2 (11.7) 4 (25) Chemotherapy before surgery, n (%) 17 (100) 12 (75) 0.12 Response to pre-operative chemotherapy according to RECIST criteria, n (%)   Partial Response 5 (29.5) 5 (31.2) 0.90   Stable Disease 12 (70) 11 (68.7) 0.87   Chemotherapy cycles before liver surgery (median, IQR25–75) 6 (4–14) 7 (1.2–9.5) 0.81 First-line chemotherapy schemes, n (%) 17 12   FOLFOX 1 (6) 2 (16.6)   FOLFIRI 3 (17.5) 2 (16.6)   FOLFIRI + CETUXIMAB 3 (17.5) 2 (16.6)   FOLFIRINOX 4 (24) 2 (16.6)   FOLFOXIRI + BEVACIZUMAB 3 (17.5) 0 (0)   FOLFOX + BEVACIZUMAB 2 (12) 2 (16.6)   FOLFIRI + BEVACIZUMAB 1 (6) 2 (16.6) Second-line chemotherapies, n (%) 6 5   FOLFOXIRI + BEVACIZUMAB 1 (16.6) 2 (40)   FOLFOXIRI + CETUXIMAB 2 (33.3) 3 (60)   5FU + BEVACIZUMAB 1 (16.6) 0 (0)   FOLFOX 1 (16.6) 0 (0)   FOLFIRI + BEVACIZUMAB 1 (16.6) 0 (0) Third-line chemotherapy, n (%) 1 0   FOLFIRI + BEVACIZUMAB 1 (100) 0 (0)   Post-chemotherapy fibrosis or steatosis > 60% 2 (11.7) 1 (6.2) 0.58   Previous liver resection 9 (52.9) 4 (25) 0.20   Previous percutaneous thermal ablation 5 (29.4) 2 (12.5) 0.23   Time between CT and Surgery (median, IQR25–75) 64 (59.5–90) 30 (8–70) 0.53   Time between LVD/PVE and Surgery (mean, SD) 47,3 (37.7) 56,5 ( 54.3) 0.37   Trisectionectomies 8 (47) 5 (31.2) 0.35 KRAS, Kirsten rat sarcoma gene; BRAF, B-RAF proto-oncogene; RECIST, response evaluation criteria in solid tumors; CT, chemotherapy; FOLFOX, folinic acid, 5-fluorouracil, oxaliplatin; FOLFIRI, folinic acid, 5-fluorouracil, irinotecan; FOLFIRINOX, folinic acid, 5-fluorouracil, oxaliplatin, irinotecan; EGFR, epidermal growth factor receptor; IQR, interquartile range; SD, standard deviation Survival Analysis The 1-year and 3-year overall survival (OS) rates were respectively 81.3% (95% CI: 72–90) and 54.7% (95% CI: 46–63) in the LVD group, and 85% (95% CI: 69–100) and 77.4% (95% CI: 54–99) in the PVE group (Fig. 2B). There were no statistically significant differences between the two populations (p = 0.64). The median disease-free survival (DFS) rates in the LVD group and PVE group were 6 months (95% CI: 4–7) and 12 months (CI 95%: 1.5–13), respectively. The 1-year DFS rates in the two groups were 53% (95% CI: 39–67) and 6.3% (95% CI: 0.3–12.3), respectively; meanwhile the 3-year DFS rates were 44% (95% CI: 30–58) and 0 (Fig. 2A). There were no statistically significant differences between the two populations (p = 0.29).Fig. 2 Disease-free survival (A) and overall survival (B) of patients undergoing LVD or PVE before right or right extended hepatectomy. m: months Hepatic recurrence occurred in nine patients (52.9%) in the LVD group and five patients in the PVE group (31.2%). In the LVD group, two patients developed pulmonary progression, two developed lumbo-aortic lymph node metastasis, and one developed peritoneal carcinosis. Six patients died during the follow-up period; however, the causes of the deaths were not related to post-operative or post-procedural events. Among the patients, four experienced pulmonary progression. Secondary Endpoints The median time between the LVD procedure and surgery was 39 days (IQR25-75: 25–56). No patient experienced serious complications after the radiological procedure, and all 17 patients underwent surgery after LVD. The successful resection rate for the LVD procedure was 100%. Regarding intra-operative outcomes, no statistically significant differences were observed between the two groups. The mean duration of the intervention was 327 min (± 93) in PVE patients and 288 min (± 62) in LVD patients. Both the estimated amount of intra-operative blood loss and the number of blood transfusions were comparable between the two groups (median, 500 vs. 700 cc and 1 vs. 0, respectively). Post-operative complications occurred in eight patients (47%) in the LVD group and eight patients as in the PVE group (50%). Following the Clavien–Dindo classification of complications, in the LVD group, two patients had grade I complications, five had grade II complications, and one had a grade III complication, requiring endoscopic retrograde cholangiopancreatography (ERCP) with sphincterotomy. In particular, seven patients had post-hepatectomy hemorrhage (41%), all of grade A according to ISGLS; one patient experienced a bile leakage (5%); three patients developed grade A PHLF (17%); and three patients developed post-operative grade A ascites (23.5%). It should be noted that the incidence of post-hepatectomy hemorrhage was significantly higher in LVD patients (p = 0.04), although they were all grade I complications. Conversely, the number of serious complications (defined as belonging to at least grade III of the Clavien–Dindo classification) was higher in the group of PVE patients (4 vs. 1, p = 0.07). The results of the univariate analysis of intra-operative and post-operative complications are shown in Table 2.Table 2 Secondary outcomes LVD PVE p-value Delay procedure/surgery, median (IQR25–75) 39 (± 31) 36 (± 27) 0.97 Intraoperative bleedings, median (IQR25–75) 700 (350–1450) 500 (400–1050) 0.85 Intraoperative transfusions, median (IQR25–75) 0 (0–2) 1 (0–3) 0.27 Operative duration, mean (± SD) 288 (± 62) 327 (± 93) 0.17 Post-operative complications, n (%) 8 (47) 8 (50) 0.72 PHLF, n (%) 3 (17.6) 3 (18.7) 0.86 Clavien-Dindo ≥ III, n (%) 1 (5.8) 4 (25) 0.07 PHH, n (%) 7 (41.1) 1 (6.2) 0.04 PHBL, n (%) 1 (5.8) 3 (18.7) 0.22 PHA, n (%) 4 (23.5) 3 (18.7) 0.57 Hepatic recurrence 9 (52.7) 5 (31.2) 0.20 IQR, interquartile range; PHLF, post-hepatectomy liver failure; PHH, post-hepatectomy hemorrhage; PHBL, post-hepatectomy bile leak; PHA, post-hepatectomy ascites Statistically significant p-values are highlighted in Bold Volume Analysis The median pre-procedural tumor volumes were similar in the PVE and LVD groups (100 cc vs. 51 cc, respectively, p = 0.24). The mean FLR-V was 32.2 before PVE and 29.3 before LVD (p = 0.53). However, the mean increase in FLR-V was higher after LVD (49% vs. 27%, p = 0.01). The mean daily KGR was also significantly higher after the LVD procedure (0.2% vs. 0.1%, p = 0.05; 10 cc/day vs. 4.8 cc/day, p = 0.03). All volume analysis data are listed in Table 3.Table 3 Volumetric analysis LVD PVE p-value Pre-procedural tumor volume, median (IQR25–75) 51 (35–121.5) 100 (34–154) 0.37 Pre-procedural FLR-V share %, mean (SD) 29.3 (6.8) 32.2 (9.7) 0.44 TLV gain in cc, mean (SD) 183 (271) 162 (303) 0.82 Pre-operative FLR-V %, mean (SD) 39 (9) 40.5 (11) 0.81 FLR-V increase %, mean (SD) 49 (29) 27 (18) 0.01 KGR % per day, mean (SD) 0.2 (0.2) 0.1 (0.1) 0.05 KGR in cc/day, mean (SD) 10 (8.7) 4.8 (4) 0.03 KGR % per week, mean (SD) 1.45 (1.3) 1.12 (1.1) 0.46 SD, standard deviations; IQR, interquartile range; TLV, total liver volume; FLR-V, future liver remnant volume; KGR, kinetic growth rate Discussion To the best of our knowledge, this is the first comparative study on the short- and medium-term outcomes of right hemi-hepatectomy or right extended hepatectomy after LVD vs. after PVE, specifically for CRLM. Early intra- and post-operative results after LVD are very interesting; no differences were found between the PHLF rates, operative durations, estimated intra-operative blood loss, and biliary leak rates. It is interesting to note, however, that there was a greater number of post-operative bleeding events in patients who underwent LVD prior to surgery, even though all the cases were classified as minor bleeding. This finding could, in theory, be linked to the hemodynamic changes induced by the technique itself: Compared to the PVE, it induces a higher blood flow in the contralateral liver by closing also the hepatic veins. Therefore, it would be interesting in the future to further investigate this aspect as well as validate this finding by carrying out studies with larger samples and more appropriate designs. Our group has published the first comparative study investigating peri-operative outcomes among LVD and PVE patients; however, we did not focus on a specific surgical procedure or on a specific disease (such as hepatocellular carcinomas and cholangiocarcinomas).33 It is well known that including cirrhotic or cholestatic livers, as in the aforementioned study, can negatively affect the homogeneity of the sample and the power of the results. Furthermore, the real role of LVD in patients with cirrhosis remains debatable.34 Regarding the rate of severe post-operative complications, only one Clavien–Dindo grade III event was registered in the LVD group against four events in the PVE group, though the difference was not statistically significant. Furthermore, a greater proportion of patients in the PVE group had previously undergone surgery or thermal ablation; this could have influenced the results. Further comparative studies are required to clarify this finding. Similarly, the preliminary oncological outcomes of LVD in CRLM patients appear to be encouraging, as recently suggested in other studies.35,36 Previous studies have hypothesized negative effects on tumor growth following liver volume augmentation procedures, including PVE.37 However, a recent meta-analysis by Giglio et al. concluded that PVE did not adversely affect cancer outcomes after major hepatectomy in patients with CRLM.38 Furthermore, LVD has some technical peculiarities that could theoretically have other oncological implications (such as blocking the venous return of the diseased liver using Amplatzer-type plugs); however, these deserve further investigations. Herein, no significant differences in the incidence of hepatic recurrence and medium-term OS and DFS rates were found between the PVE and LVD groups. Regarding volume analysis, the mean daily KGR was proven to be significantly higher after LVD than after PVE (0.2% vs. 0.1%, p = 0.05; 10 cc/day vs. 4.8 cc/day, p = 0.03). Similarly, the mean FLR-V increase was higher after LVD (49% vs. 27%, p = 0.01).36,39 These results are in line with previous reports,16,39 but need to be confirmed by larger randomized studies, such as the ongoing DRAGON-1 (NCT04272931) or Hyper-LIV01 (NCT03841305) studies. Furthermore, the mean weekly KGR was lower than 2% in the studied population (1.45 after LVD vs. 1.12 after PVE, p = 0.46): A result that was previously reported to be at risk of PHLF after PVE.31 However, we experienced only 3 cases of PHLF after PVE, and all of them were graded A according to ISGLS. Another important concern arising from our analysis was the time lapse between the LVD procedure and the surgery (39 days). Previous studies have reported that delayed hepatic hypertrophy following PVE may itself be a major cause of cancer recurrences reported during FLR augmentation procedures.40 Similarly, the importance of starting post-operative chemotherapy as soon as possible after surgery is well known, and it is also indirectly correlated with the time to FLR regeneration during the post-operative course. Our data showed a median time between LVD and surgery of 39 days (IQR25–75, 25–56), which is comparable to several PVE reports in the literature.41 Nonetheless, this delay is too long for the procedure to induce faster hypertrophy of the FLR. However, several authors have proposed that this delay could be greatly reduced, as it has been shown that an increase in FLR volume and function occurs as early as seven days after LVD.39 One of the main reasons for the long time delay experienced by the patients examined in this study could be the fact that the LVD technique was just recently introduced; besides, it is being evaluated using the standard of previous studies. That is, volume measurements are performed on days 7 and 21, with the assumption that the growth effect is similar to that of the actual radiological standard of care (the longer the waiting time, the greater the FLR augmentation). As earlier suggested, previous findings encourage a significant reduction of this delay and the application of an ALPPS-like strategy.42 Further studies should focus on the reduction of the time delay when performing LVD procedures to ensure excellent patient tolerance and volumetric growth rate.43 More consistent efforts should also be made to reduce the time of surgery planning, though this is difficult in daily practice given the context of the COVID-19 pandemic characterized by fewer available resources. Finally, the successful resection rate after the LVD was 100%, concurring with a recent study involving 21 patients performed by Kobayashi et al.30 No case of death secondary to post-procedural complications or tumor progression was registered. This study had several limitations. First, its observational and retrospective design, with purely univariate inferential statistics, was due to the small sample size and the number of variables. Because of the recent nature of this technique, few consecutive patients were included in this study; thus, the small sample size could not allow a wider and more detailed analysis of the factors that may play a prognostic role in both OS and DFS. Similarly, the median follow-up time was too short to adequately assess long-term outcomes: An update of the survival data will be needed in the coming years to assess the results after a longer follow-up. Nevertheless, all the oncological and non-oncological results are very encouraging and deserve to be shared to arouse interest and enthusiasm on this still a highly debated topic. Nonetheless, our study had several strengths. A rigorous selection of inclusion and exclusion criteria (with the exclusion of cirrhotic and cholestatic livers) limited our sample size but increased the homogeneity of the sample and the power of these results. Finally, to the best of our knowledge, this is the first study to compare the medium-term outcomes after LVD and PVE in patients undergoing right hepatectomy or trisectionectomy. Conclusion The LVD technique is well tolerated in patients undergoing right hemi-hepatectomy or right extended hepatectomy for CRLM, showing similar peri-operative and medium-term outcomes compared to PVE. It will be important to update the oncological data in the coming years to obtain the results after 5 years of follow-up, with the possible inclusion of new patients. Randomized controlled trials (RCTs) are needed to confirm the benefits of LVD. Declarations Conflict of Interest The authors declare no competing interests. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. Araghi M Arnold M Rutherford MJ Colon and rectal cancer survival in seven high-income countries 2010–2014: variation by age and stage at diagnosis (the ICBP SURVMARK-2 project) Gut. 2021 70 1 114 126 10.1136/gutjnl-2020-320625 32482683 2. Hackl C Neumann P Gerken M Loss M Klinkhammer-Schalke M Schlitt HJ Treatment of colorectal liver metastases in Germany: a ten-year population-based analysis of 5772 cases of primary colorectal adenocarcinoma BMC Cancer. 2014 14 810 10.1186/1471-2407-14-810 25369977 3. House MG Ito H Gönen M Survival after hepatic resection for metastatic colorectal cancer: trends in outcomes for 1,600 patients during two decades at a single institution J Am Coll Surg. 2010 210 5 744 752 10.1016/j.jamcollsurg.2009.12.040 20421043 4. Choti MA Sitzmann JV Tiburi MF Trends in long-term survival following liver resection for hepatic colorectal metastases Ann Surg. 2002 235 6 759 766 10.1097/00000658-200206000-00002 12035031 5. Van Cutsem E Cervantes A Adam R ESMO consensus guidelines for the management of patients with metastatic colorectal cancer Ann Oncol Off J Eur Soc Med Oncol. 2016 27 8 1386 1422 10.1093/annonc/mdw235 6. Cassese G, Han HS, Al Farai A, Guiu B, Troisi RI, Panaro F. Future remnant Liver optimization: preoperative assessment, volume augmentation procedures and management of PVE failure. Minerva Surg. Published online March 25, 2022. 10.23736/S2724-5691.22.09541-7 7. Deng G Li H Jia GQ Parenchymal-sparing versus extended hepatectomy for colorectal liver metastases: a systematic review and meta-analysis Cancer Med. 2019 8 14 6165 6175 10.1002/cam4.2515 31464101 8. Khatri VP Petrelli NJ Belghiti J Extending the frontiers of surgical therapy for hepatic colorectal metastases: is there a limit? J Clin Oncol Off J Am Soc Clin Oncol. 2005 23 33 8490 8499 10.1200/JCO.2004.00.6155 9. Xu F Tang B Jin TQ Dai CL Current status of surgical treatment of colorectal liver metastases World J Clin Cases. 2018 6 14 716 734 10.12998/wjcc.v6.i14.716 30510936 10. Schindl MJ Redhead DN Fearon KCH Garden OJ Wigmore SJ Edinburgh Liver Surgery and Transplantation Experimental Research Group (eLISTER) The value of residual liver volume as a predictor of hepatic dysfunction and infection after major liver resection Gut. 2005 54 2 289 296 10.1136/gut.2004.04652 15647196 11. Clavien PA Petrowsky H DeOliveira ML Graf R Strategies for safer liver surgery and partial liver transplantation N Engl J Med. 2007 356 15 1545 1559 10.1056/NEJMra065156 17429086 12. Makuuchi M Takayasu K Takuma T Preoperative transcatheter embolization of the portal venous branch for patients receiving extended lobectomy due to the bile duct carcinoma J Jpn Pract Surg Soc. 1984 45 12 1558 1564 10.3919/ringe1963.45.1558 13. Aoki T Kubota K Preoperative portal vein embolization for hepatocellular carcinoma: consensus and controversy World J Hepatol. 2016 8 9 439 445 10.4254/wjh.v8.i9.439 27028706 14. Alvarez FA Castaing D Figueroa R Natural history of portal vein embolization before liver resection: a 23-year analysis of intention-to-treat results Surgery. 2018 163 6 1257 1263 10.1016/j.surg.2017.12.027 29502872 15. Guiu B Chevallier P Denys A Simultaneous trans-hepatic portal and hepatic vein embolization before major hepatectomy: the liver venous deprivation technique Eur Radiol. 2016 26 12 4259 4267 10.1007/s00330-016-4291-9 27090112 16. Guiu B Quenet F Escal L Extended liver venous deprivation before major hepatectomy induces marked and very rapid increase in future liver remnant function Eur Radiol. 2017 27 8 3343 3352 10.1007/s00330-017-4744-9 28101681 17. Memeo R Conticchio M Deshayes E Optimization of the future remnant liver: review of the current strategies in Europe Hepatobiliary Surg Nutr. 2021 10 3 350 363 10.21037/hbsn-20-394 34159162 18. Deshayes E Schadde E Piron L Quenet F Guiu B Extended liver venous deprivation leads to a higher increase in liver function that ALPPS in early assessment : a comment to “Sparrelid, E. et al. Dynamic evaluation of liver volume and function in associating liver partition and portal vein ligation for staged hepatectomy Journal of Gastrointestinal Surgery (2017).” J Gastrointest Surg Off J Soc Surg Aliment Tract 2017 21 10 1754 1755 10.1007/s11605-017-3508-9 19. Cuschieri S The STROBE guidelines Saudi J Anaesth. 2019 13 Suppl 1 S31 S34 10.4103/sja.SJA_543_18 30930717 20. Pomerantz BJ Biliary tract interventions Tech Vasc Interv Radiol. 2009 12 2 162 170 10.1053/j.tvir.2009.08.009 19853234 21. The Brisbane 2000 Terminology of liver anatomy and resections. HPB 2000; 2:333–39. HPB. 2002;4(2):99-100. 10.1080/136518202760378489 22. Clavien PA Barkun J de Oliveira ML The Clavien-Dindo classification of surgical complications: five-year experience Ann Surg. 2009 250 2 187 196 10.1097/SLA.0b013e3181b13ca2 19638912 23. Rahbari NN Garden OJ Padbury R Posthepatectomy liver failure: a definition and grading by the International Study Group of Liver Surgery (ISGLS) Surgery. 2011 149 5 713 724 10.1016/j.surg.2010.10.001 21236455 24. Rahbari NN Garden OJ Padbury R Post-hepatectomy haemorrhage: a definition and grading by the International Study Group of Liver Surgery (ISGLS) HPB. 2011 13 8 528 535 10.1111/j.1477-2574.2011.00319.x 21762295 25. Koch M Garden OJ Padbury R Bile leakage after hepatobiliary and pancreatic surgery: a definition and grading of severity by the International Study Group of Liver Surgery Surgery. 2011 149 5 680 688 10.1016/j.surg.2010.12.002 21316725 26. Moore KP Wong F Gines P The management of ascites in cirrhosis: report on the consensus conference of the International Ascites Club Hepatol Baltim Md. 2003 38 1 258 266 10.1053/jhep.2003.50315 27. Adam R de Gramont A Figueras J Managing synchronous liver metastases from colorectal cancer: a multidisciplinary international consensus Cancer Treat Rev. 2015 41 9 729 741 10.1016/j.ctrv.2015.06.006 26417845 28. Vauthey JN Abdalla EK Doherty DA Body surface area and body weight predict total liver volume in Western adults Liver Transplant Off Publ Am Assoc Study Liver Dis Int Liver Transplant Soc. 2002 8 3 233 240 10.1053/jlts.2002.31654 29. Croome KP Hernandez-Alejandro R Parker M Heimbach J Rosen C Nagorney DM Is the liver kinetic growth rate in ALPPS unprecedented when compared with PVE and living donor liver transplant? A multicentre analysis. HPB. 2015 17 6 477 484 10.1111/hpb.12386 25728543 30. Kobayashi K Yamaguchi T Denys A Liver venous deprivation compared to portal vein embolization to induce hypertrophy of the future liver remnant before major hepatectomy: a single center experience Surgery. 2020 167 6 917 923 10.1016/j.surg.2019.12.006 32014304 31. Shindoh J Truty MJ Aloia TA Kinetic growth rate after portal vein embolization predicts posthepatectomy outcomes: toward zero liver-related mortality in patients with colorectal liver metastases and small future liver remnant J Am Coll Surg. 2013 216 2 201 209 10.1016/j.jamcollsurg.2012.10.018 23219349 32. Jung SH Stratified Fisher’s exact test and its sample size calculation Biom J Biom Z. 2014 56 1 129 140 10.1002/bimj.201300048 33. Panaro F Giannone F Riviere B Perioperative impact of liver venous deprivation compared with portal venous embolization in patients undergoing right hepatectomy: preliminary results from the pioneer center Hepatobiliary Surg Nutr. 2019 8 4 329 337 10.21037/hbsn.2019.07.06 31489302 34. Guiu B Herrero A Panaro F Liver venous deprivation: a bright future for liver metastases—but what about hepatocellular carcinoma? Hepatobiliary Surg Nutr. 2021 10 2 270 272 10.21037/hbsn-21-7 33898575 35. Khayat S Cassese G Quenet F Oncological outcomes after liver venous deprivation for colorectal liver metastases: a single center experience Cancers. 2021 13 2 E200 10.3390/cancers13020200 36. Cassese G Troisi RI Khayat S Liver venous deprivation versus associating liver partition and portal vein ligation for staged hepatectomy for colo-rectal liver metastases: a comparison of early and late kinetic growth rates, and perioperative and oncological outcomes Surg Oncol. 2022 43 101812 10.1016/j.suronc.2022.101812 35820263 37. Simoneau E Aljiffry M Salman A Portal vein embolization stimulates tumour growth in patients with colorectal cancer liver metastases HPB. 2012 14 7 461 468 10.1111/j.1477-2574.2012.00476.x 22672548 38. Giglio MC, Giakoustidis A, Draz A, et al. Oncological outcomes of major liver resection following portal vein embolization: a systematic review and meta-analysis. Ann Surg Oncol. 2016;23(11). 10.1245/s10434-016-5264-6 39 Guiu B Quenet F Panaro F Liver venous deprivation versus portal vein embolization before major hepatectomy: future liver remnant volumetric and functional changes Hepatobiliary Surg Nutr. 2020 9 5 564 576 10.21037/hbsn.2020.02.06 33163507 40. Beal IK Anthony S Papadopoulou A Portal vein embolisation prior to hepatic resection for colorectal liver metastases and the effects of periprocedure chemotherapy Br J Radiol. 2006 79 942 473 478 10.1259/bjr/29855825 16714748 41. van Lienden KP van den Esschert JW de Graaf W Portal vein embolization before liver resection: a systematic review Cardiovasc Intervent Radiol. 2013 36 1 25 34 10.1007/s00270-012-0440-y 22806245 42. Laurent C Fernandez B Marichez A Radiological simultaneous portohepatic vein embolization (RASPE) before major hepatectomy: a better way to optimize liver hypertrophy compared to portal vein embolization Ann Surg. 2020 272 2 199 205 10.1097/SLA.0000000000003905 32675481 43. Zhang J Steib CJ New evidence for liver venous deprivation: safety and feasibility for extended liver resections Ann Transl Med. 2020 8 19 1259 10.21037/atm-20-3057 33178791
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==== Front Updates Surg Updates Surg Updates in Surgery 2038-131X 2038-3312 Springer International Publishing Cham 1439 10.1007/s13304-022-01439-7 Original Article Robot-assisted esophagectomy with robot-sewn intrathoracic anastomosis (Ivor Lewis): surgical technique and early results http://orcid.org/0000-0002-2904-2170 Marano Alessandra [email protected] 1 http://orcid.org/0000-0002-0514-501X Salomone Sara 1 http://orcid.org/0000-0002-2475-3475 Pellegrino Luca 2 http://orcid.org/0000-0003-4201-2678 Geretto Paolo 1 http://orcid.org/0000-0001-7676-9658 Robella Manuela 2 http://orcid.org/0000-0002-2431-2020 Borghi Felice 2 1 grid.413179.9 0000 0004 0486 1959 Department of Surgery, General and Oncologic Surgery Unit, Santa Croce e Carle Hospital, Via Michele Coppino 26, 12100 Cuneo, Italy 2 grid.419555.9 0000 0004 1759 7675 Department of Oncologic Surgery, Candiolo Cancer Institute, FPO - IRCCS - Str. Prov. 142, Km 3,95, Candiol, TO Italy 12 12 2022 112 8 9 2022 5 12 2022 © Italian Society of Surgery (SIC) 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Esophagectomy is the selected treatment for nonmetastatic esophageal and esophagogastric junction cancer, although high perioperative morbidity and mortality incur. Robot-assisted minimally invasive esophagectomy (RAMIE) effectively reduces cardiopulmonary complications compared to open esophagectomy and offers a technical advantage, especially for lymph node dissection and intrathoracic anastomosis. This article aims at describing our initial experience of Ivor Lewis RAMIE, focusing on the technique’s main steps and robotic-sewn esophagogastrostomy. Prospectively collected data from all consecutive patients who underwent Ivor Lewis RAMIE for cancer was reviewed. Reconstruction was performed with a gastric conduit pull-up and a robotic-sewn intrathoracic anastomosis. Intraoperative and postoperative complications were recorded as prescribed by the Esophagectomy Complications Consensus Group (ECCG). Thirty patients underwent Ivor Lewis RAMIE with complete mediastinal lymph node dissection and robot-sewn anastomosis. No intraoperative complications nor conversion occurred. Pulmonary complications totaled 26.7%. Anastomotic leakage (ECCG, type III) and conduit necrosis (ECCG, type III) both occurred in one patient (3.3%). Chylothorax appeared in 2 patients (6.7%) (ECCG, Type IIA). Anastomotic stricture, successfully treated with endoscopic dilatations, occurred in 8 cases (26.7%). Median overall postoperative stay was 11 days (range, 6–51 days). 30 day and 90 day mortality was 0%. R0 resection was performed in 96.7% of patients with a median number of 47 retrieved lymph nodes. RAMIE with robot-sewn intrathoracic anastomosis appears to be feasible, safe and effective, with favorable perioperative results. Nevertheless, further high-quality studies are needed to define the best anastomotic technique for Ivor Lewis RAMIE. Supplementary Information The online version contains supplementary material available at 10.1007/s13304-022-01439-7. Keywords Intrathoracic anastomosis RAMIE Ivor-Lewis Robotic Esophageal cancer ==== Body pmcIntroduction Esophagectomy with radical lymphadenectomy combined with multimodal therapy is the main form of curative treatment for patients with nonmetastatic esophageal or gastroesophageal junction (EGJ) cancer [1]. Although several improvements have been achieved in the last decades to enhance recovery and decrease postoperative complications, transthoracic esophagectomy is still an invasive surgical procedure associated with a relatively high morbidity rate even in high-volume centers, mostly in terms of cardiopulmonary complications and anastomotic failure [2]. Moreover, this latter condition is associated with an increased risk of anastomotic stricture, a mortality rate of up to 16% and decreased long-term survival rate [3]. One of the most recent improvements has been the adoption of laparoscopic minimally invasive esophagectomy (MIE). MIE has been shown to be superior compared to open esophagectomy with regards to postoperative outcomes, especially in terms of pulmonary complications, without compromising oncologic safety [4, 5]. In addition, in a thoracoscopic setting, current, sound scientific evidence indicates that intrathoracic anastomosis is associated with a clinically relevant lower leakage rate and improved functional results compared to cervical anastomosis [6]. The creation of an intrathoracic anastomosis is considered quite challenging even during MIE owing to the intrinsic limitations of this technique and so far, no general consensus exists on the optimal anastomosis [7]. Recently, a robotic approach has been implemented to facilitate complex minimally invasive (MI) procedures by combining the optimal advantage of its ergonomics [8]. This technology might be particularly useful for the thoracic stage of Ivor Lewis en-bloc esophagectomy (ILE), especially when a hand-sewn esophagogastrostomy is planned. Indeed, although few studies have reported about hand-sewn intrathoracic anastomosis during Ivor Lewis robot-assisted minimally invasive esophagectomy (RAMIE) using widely varying techniques [9–17], all experiences underlined that the robotic technology provided increased suturing capacity, more precise construction and highly controlled anastomosis in a narrow space. Ivor Lewis RAMIE was implemented by our surgical team in 2019 based on our foregoing experience of traditional open ILE. The aim of this study is to describe the main steps of our technique especially focusing on robot-sewn esophagogastrostomy. Postoperative complications and short-term oncologic outcomes of our initial experience are also analyzed. The following article is presented in accordance with the criteria set out in the Preferred Reporting of Case Series in Surgery (PROCESS) checklist [18]. Materials and methods From April 2019 to February 2022, all consecutive patients with distal esophageal cancer or EGJ cancer who were scheduled for an intent to treat ILE with robot-sewn esophagogastrostomy were included in the study. Preoperative workup included esophagogastroduodenoscopy with biopsy, thoracoabdominal computed tomography (CT), endoscopic ultrasonography, fluorodeoxyglucose-18 positron emission tomography (FDG-PET)/CT in selected cases, cardiopulmonary function examination and assessment of nutritional status. The exclusion criteria ruled out patients with evidence of distant metastasis and prior thoracic surgery. Before treatment, all patients were assessed by an upper gastrointestinal multidisciplinary tumor board to determine optimal treatment, according to the NCCN [1] and National Guidelines [19]. The standard neoadjuvant treatment for patients with esophageal adenocarcinoma was perioperative chemotherapy with FLOT or chemoradiotherapy with CROSS according to primary cancer site [20, 21]. All patients were reassessed 1 month after the completion of treatment with CT scan (and FDG-PET if necessary): in case of objective radiological response patients were scheduled for ILE with curative intent 4–6 weeks after FLOT and 10–12 weeks after CROSS regimen, respectively. All surgical procedures were performed by a single surgeon (F.B.) with long-standing experience in laparoscopic and robotic surgery. The reconstruction was carried out with a gastric conduit pull-up and a robot-sewn intrathoracic anastomosis [14]. The abdominal stage of the surgery was performed using an open, 3D laparoscopic, or a robotic approach. From April 2019 to February 2021 all procedures have been carried out at Santa Croce e Carle Hospital, Cuneo, Italy (a tertiary referral center). In 2020, January the dV®Si™ system in the hospital was replaced by the dV®Xi™ (Intuitive Surgical Inc., Sunnyvale, USA). Prior to this change, the abdominal step of ILE according to our standardized technique (which includes a complete Kocher maneuver, pyloroplasty and feeding jejunostomy creation) would have been quite complex to accomplish with the dV®Si™ system. For this reason, an open or laparoscopic approach was selected taking into consideration the patient’s characteristics (i.e., open approach in case of previous abdominal surgeries) and surgeon’s preference. From May 2021 to February 2022 all surgeries have been performed using the same technique with dV® Xi™ system at Candiolo Cancer Institute, FPO–IRCCS (Candiolo, Torino, Italy), a tertiary referral center where F.B moved. After the Institutional Review Board approval and the signing of a data use agreement, a database of prospectively collected data was created. Patient and treatment-related data were recorded. Intraoperative data included operative time (OT) of the abdominal and thoracic surgical phase and conversion rate. Length of stay (LOS) including the intensive care unit (ICU) hospitalization, reasons for readmission, and 30-day and 90-day mortality were also analyzed. Intraoperative and postoperative complications were recorded according to definitions set by the Esophagectomy Complications Consensus Group (ECCG) [2]. All the patients were treated according to the ERAS program for esophagectomy [22] that can be briefly summarized as follows:Preoperative phase: incentive spirometer 10x/hour and respiratory exercises are prescribed 7 days before surgery, immunonutrition is administered starting 7 days and up to 3 h before surgery, a thoracic epidural catheter is inserted the day before the surgery, thromboprophylaxis and cephazoline 2 g i.v. are administered 12 h and 1 h before surgery, respectively. Intraoperative phase: the patient is intubated with a double-lumen tube, the anesthetic protocol is standardized using a careful goal-directed fluid therapy aimed at avoiding an excessive positive fluid balance, maintenance of normothermia is ensured; pyloroplasty and feeding jejunostomy are always performed, a nasogastric tube (NGT) as well as an active-suction drain in the chest are regularly put in place, while an abdominal passive drain is not routinely positioned. Postoperative phase: the patient is usually extubated in the operating room and transferred to the surgical ward after an observation period in the postoperative recovery room (unless surgery ends in late afternoon in which case the patient is transferred to ICU where extubation is carried out within 12 h), the urinary catheter is removed on postoperative day (POD) 2, NGT is removed at a threshold of about 100–200 mL per day after passing of first flatus, abdominal drain (if present) is removed on POD 2, chest drain is set up without suction (provided pneumothorax is absent) on POD day 2 and removed after diet starts at a threshold of 200 mL per day, enteral nutrition starts on POD day 1 initiated at 10 cc/h and increased to goal, a fluid oral intake is allowed after NGT removal, early mobilization, starting 12 h after surgery, is strongly encouraged. Conduit emptying is generally checked on POD 4–5 with gastrografin swallow and, if guaranteed, a fractional semi-liquid diet starts from the same day. Surgical technique: Ivor Lewis Esophagectomy with intrathoracic robot-sewn anastomosis Abdominal phase The patient is in a supine position with the arms along the body and split legs. To perform the laparoscopy, three 10 mm ports (one sub umbilical for the 3D camera, one along the right and one along the left mid-clavicular line as operating ports) as well as two 5 mm ports (one epigastric and one on the right flank at the anterior axillary line, both for the assistants) are put in place under direct vision (Fig. 1A). dV® Xi™ port layout is shown in Fig. 1B. Four robotic trocars (R1-4, 8 mm) are placed in a horizontal line above or below the umbilicus within 6 cm of each other and an additional 12 mm trocar for the assistant is inserted in the right or left mesogastrium according to patient habitus. A 15° reverse Trendelenburg position is established. The robotic cart is docked from the right side of the patient and the targeting area is identified along the pars flaccida of the lesser omentum. A xifo-supra umbilical incision is performed in the case of an open approach. For the robotic abdominal phase, the dissection is usually performed using an endowristed monopolar cautery hook and bipolar forceps, sometimes we employed a bipolar vessel sealer device (Intuitive Vessel Sealer). In the case of a laparoscopic and open approach an ultrasound device is used.Fig. 1 Trocar placement of the laparoscopic (A) and robotic (B) abdominal phase of the procedure. C camera port, A assistant port, R robot arm Irrespective of the type of surgical approach selected, the abdominal stage of ILE includes the following steps. First, the greater gastric curvature is dissected along the gastrocolic ligament. Next the stomach is mobilized using a medial to lateral approach up to the left crura, carefully sparing the right gastroepiploic arcade. The retrogastric adhesions as well as the short gastric arteries can be dissected and ligated safely. Then a full Kocher maneuver is performed as a rule. The gastro‐hepatic ligament is cut open close to the liver, preserving the right gastric artery, and then upwards to the right crus of the diaphragm. A lymph node dissection along the upper margin of the common hepatic artery (#8a) is subsequently performed up to the celiac axis. The left gastric artery and vein are sectioned at their origins and the lymphadenectomy of station #7, 9 and 11p is completed. Next, the hiatus is slightly enlarged by transecting the right crus of the diaphragm. A 4 cm-wide gastric tube is created on the site of the greater curvature with a 60 mm smart articulating stapler (Signia™, Medtronic, USA), starting at the level of the incisura angularis. After the gastric tube has been prepared, an assessment of its perfusion is performed with indocyanine green (ICG) fluorescence [23]. Hence, the divided stomach is sewn to the end of the divided esophagus and the end of the first stapling line is tagged with a stay suture as a marker. Pyloroplasty is routinely performed digitally in the open approach and with interrupted 4-0 polyglactin 910 (Ethicon Inc. USA) sutures in the MI technique (extramucosal Heineke–Mikulicz pyloroplasty). At the end of the abdominal phase a percutaneous jejunostomy is created and a drain is placed. Thoracic phase Single‐lung ventilation is introduced, and the patient is placed in the left lateral decubitus position, tilted 45° compared to the prone position. For both robotic systems, the cart is docked from the right side of the patient. In addition, three robotic ports are put in place as well as two thoracoscopic ports for the assistant. dV®Si™ port layout for this stage has previously been described [24]. It’s worthy of mention that an additional 5 mm port for the assistant is placed between the intercostal spaces (ICS) 6 and 10, along the posterior axillary line. Figure 2 shows the dV®Xi™ trocar position (three-arms technique) in a slight U shape: robotic arm#1(R1) for the grasper or the bipolar forceps at the ICS 9, robotic arm#2 (R2) for the 30° down scope at the ICS 6, posterior to the posterior axillary line and robotic arm#3 (R3) for the monopolar cautery hook, the needle driver or the clip applier at the ICS 4, anterior to the scapular rim. Furthermore assistant port #1(A1, 12-mm) is located in the ILC 8, and assistant port #2 (A2, 5 mm) between R2 and R3 at the posterior axillary line. The targeting area is identified at the level of the Azygos arch.Fig. 2 Trocar placement of the thoracic phase of the procedure. R robot arm, A assistant port A 7–8 mmHg pneumothorax is then induced. Starting at the anterior side of the esophagus, the parietal pleura is cut from the level of the azygos arch down to the diaphragm where the pulmonary ligament is divided. The azygos arch is then sectioned with robotic Weck Hem-o-lok clips (Teleflex, Morrisville, NC, USA) and a right paratracheal lymphadenectomy is performed. Next, the dissection of the parietal pleura is deepened towards the esophageal hiatus until the aorta becomes exposed. Subsequently, the right vagus nerve is sectioned just below the carina, preserving its bronchial branches. The dissection of the esophagus is extended below the tracheal bifurcation and a Penrose drain is placed around the esophagus to facilitate traction. The dissection of the esophagus is then continued along the pericardium down to the diaphragm and the thoracic duct is clipped with robotic clips. The resection of the esophagus en-bloc with periesophageal, bronchial and subcarinal nodes (stations # 107–111) and the thoracic duct is fully completed from the diaphragm up to the azygos arch. The proximal esophagus is divided using a robotic cautery hook above the level of the azygos vein. At this point, the instruments in R1 and R3 are reversed to be able to carefully pull the esophago-gastric bloc and the gastric conduit up through the hiatus until the marker suture becomes visible. The specimen and conduit thus are disconnected, and the specimen is placed in a plastic bag which will be removed through the enlarged incision of the assistant port. Thereafter, four supportive 4-0 polyglactin 910 (Ethicon Inc. USA) stitches are put in between the mucosae and the muscularis externa layer of the esophagus at the four cardinal points to evert the esophageal mucosae. Next, the proximal esophagus is dilatated using a Foley catheter inflated with 10 cc of sterile water for approximately 2–3 min. After having assessed both gastric conduit and esophageal perfusion with ICG fluorescence, a gastrotomy is performed at the most proximal portion of the conduit, maintaining at least 2 cm of distance from the stapler line. A single-layer robot-sewn esophagogastric anastomosis is performed above the level of the azygos arch with two separate running self-locking barbed sutures (Filbloc® 3/0, Assut Europe, Italy or alternatively V-Loc™ 3/0, Medtronic, USA) that run in the same direction from 3 to 9 o’clock. Of note is the fact that, after having applied the first stitch on the posterior wall we customarily pass the needle back below the first stitch to evert the posterior esophageal and gastric layer and improve their visualization. Once the posterior aspect of the anastomosis is complete, a NGT is placed under direct vision inside the stomach distally to the anastomosis, thus accomplishing the closure of anterior surface. Finally, a few tension release stitches are put in between the mediastinal pleura and seromuscular layer of the gastric tube. The anastomosis is checked for intraoperative leaks with methylene blue and a 28-Fr chest drain is inserted via the R1 robotic trocar, posteriorly to anastomosis, with the apex in the upper chest (Video). Results Between April 2019 and February 2022, 30 patients with resectable esophageal cancer or cancer at the EGJ level underwent curative ILE with mediastinal lymph node dissection and robot-sewn esophagogastrostomy. Baseline characteristics are listed in Table 1. Most of the patients (73.67%) were affected by tumors localized at the EGJ and received neoadjuvant chemotherapy (66.67%). Planned treatment was completed in 27 patients (90%).Table 1 Patient demographics and tumor characteristics n = 30 Age, year median [range] 68 [33–89] Gender, n (%)  M/F 26 (86.7)/4 (13.3) cTNM stage, n (%)  I 1 (3.3)  IIB 2 (6.7)  III 10 (33.3)  IVA 16 (53.3)  IVB 1 (3.3) Physical status of ASA, n (%)  II 15 (50)  III 14 (46.7)  IV 1 (3.3) Tumor location, n (%)  EGJ/Lower esophageal 23 (76.7)/7 (23.3) Histology, n (%)  Adenocarcinoma 27 (90)  Squamous cell carcinoma 1 (3.3)  Mixed Type 2 (6.7) Neoadjuvant therapy, n (%)  Chemotherapy 20 (66.7)  Chemo-radiotherapy 5 (16.7) cTNM stage, Clinical stage according to TNM staging AJCC UICC 8th edition;ASA American Society of Anesthesiologists; EGJ esophagogastric junction Surgical and postoperative data are highlighted in Table 2. A robot-sewn esophagogastrostomy with self-locking barbed 3/0 suture was carried out in all patients. Both dV®Si™and dV®Xi™ systems were used in 9 and 21 patients, respectively. However, all the candidates are considered together because the only difference is related to the type of robotic platform used. The abdominal phase was mostly carried out using a robotic approach (70%). No conversion to open or laparoscopic approach were needed and no intraoperative complications occurred.Table 2 Surgical and postoperative outcomes n = 30 Abdominal approach n (%)  Open/3D laparoscopy/robotic 6 (20)/3 (10)/21 (70) Operative time (min), mean ± sd  Total/thoracic phase 481 ± 49/217 ± 44 Intraoperative complications, n (%) 0 (0) Conversion, n (%)  Thoracic/abdominal phase 0 (0) Overall complications, n (%) 16 (53.3) Cardiac complications, n (%)  Atrial dysrhythmia requiring treatment 2 (6.7) Pulmonary complications, n (%) 8 (26.7)  Pneumonia 3 (10)  Pleural effusion requiring additional draining procedure 3 (10)  Pneumothorax requiring treatment 2 (6.7) Anastomotic leak, n (%)  Type III 1 (3.3) Chyle leak, n (%)  Type IIA 2 (6.7) Gastric conduit necrosis, n (%)  Type III 1 (3.3) Acute delirium, n (%) 1 (3.3) Delayed conduit emptying (NGT drainage > 7 days), n (%) 1 (3.3) Thoracic wound dehiscence, n (%) 1 (3.3) Feeding J-tube complications, n (%) 3 (10) Intrathoracic abscess, n (%) 2 (6.7) Other infections requiring antibiotics, n (%) 1 (3.3) LOS (days) median [range] 11 [6–51] ICU stay (days) median [range] 1 [0–8] Mortality, n (%)  In-Hospital/30 day/ 90 day 0 (0)/0 (0)/0 (0) 30 day hospital re-admission, n (%) 1 (3.3) Anastomotic strictures, n (%) 8 (26.7) Complications are reported according to ECCG (Esophagectomy Complications Consensus Group) Classification LOS Length of stay, ICU Intensive care unit, NGT Nasogastric tube Postoperative complications of some grade occurred in 16 (53.3%) patients. The most commonly observed ones were pulmonary complications (26.7%). Anastomotic leakage occurred in 1 patient (3.3%) (ECCG, Type III) who was primarily treated with endoscopically placed clips (Instinct® Endoscopic Clip, Cook® Medical, USA) and who later required reoperation for repair and drainage. Chylothorax was observed in 2 patients (6.7%) (ECCG, Type IIA). One patient (3.3%) experienced a gastric conduit necrosis on POD 14 (ECCG, Type III) and underwent gastric tube excision and esophagostomy. This was the only case of readmission after patient discharge on POD 7. Intrathoracic abscesses were found in 2 patients without any clinical and radiological evidence of anastomotic leakage. A clinical diagnosis of anastomotic stricture was observed in 8 patients (26.7%) who were successfully treated with endoscopic dilatations. In total, complications requiring reoperation under general anesthesia occurred in 2 patients (6.7%) owing to anastomotic leaks (n = 1) and conduit necrosis (n = 1). The first patient recovered uneventfully while the second died a few months after discharge from SARS-CoV-2 pneumonia. Median LOS was 11 days (range 6–51 days), and median ICU stay was 1 days (range 0–8 days). No mortality either in-hospital or within 90-days postoperatively occurred in this series. The pathologic outcomes are summarized in Table 3. A median of 47 lymph nodes (range 20—81) were harvested. A R0 resection was achieved in all cases but one (96.7%) which presented a potentially positive gastric resection margin. This patient who was affected by an ypT3N3 adenocarcinoma underwent additional systemic chemotherapy. All patients had at least 6 months of follow-up with a median follow-up of 12 months. Median overall survival has not been reached yet.Table 3 Histopathological data n = 30 Oncological Radicality, n (%)  R0/R1 29 (96.7)/1 (3.3) Harvested lymph nodes, median [range] 47 [20–81] pTNM, n (%)  T0N0 1 (3.3)  T0N1 1 (3.3)  T1bN0 2 (6.7)  T2N0 2 (6.7)  T2N3 1 (3.3)  T3N0 4 (13.3)  T3N2 8 (26.7)  T3N3 8 (26.7)  T4N3 3 (10) pTNM, Pathological stage according to TNM staging AJCC UICC 8th edition Discussion In this single-surgeon study report, we present the technical details and initial results of ILE with two field lymph node dissection and robot-sewn intrathoracic anastomosis. This reconstruction proved to be technically feasible and safe. Moreover, the short-term outcomes are promising. Nowadays, the adoption of MI techniques for ILE is becoming more and more widespread. However, to date, a considerable number of intrathoracic reconstructions have been described and there is still no general consensus on the best esophagogastric anastomosis in terms of postoperative complications [7, 25]. This is partly due to the technical challenges encountered when the anastomosis is performed thoracoscopically. Indeed, this approach has some intrinsic disadvantages mainly caused by the mirrored intracorporeal movements of the rigid instruments working in a narrow space, which increase the difficulty in creating the anastomosis itself. Robotic systems have been introduced to further overcome the limitations of thoracoscopy [13]. The wrist-like range of movements provided by this new technology, together with its magnified visualization and precision control may be particularly helpful during ILE, especially for lymph node dissection and intrathoracic anastomosis. With regard to the latter, no standardized technique has been implemented so far but, even though the evidence regarding surgical outcomes is limited, robot-sewn techniques and circular or linear stapling techniques have all proven to be effective options [26]. In our surgical team, the Ivor Lewis procedure with single layer robot-sewn anastomosis is the preferred surgical option for patients undergoing esophagectomy. The well-known robotic benefits together with the adoption of some technical refinements (i.e., supportive stitches) make the hand sewing easier to perform. Nine previous studies [9–17] have reported on widely varying techniques to construct a robot-sewn intrathoracic anastomosis during ILE (Table 4). Differences include patient position, number of robotic arms adopted and especially the anastomosis fashioning in terms of the configuration, method, and type of suture. Therefore, a comparison of these experiences is quite difficult because of the heterogeneity in surgical techniques.Table 4 Literature review Authors, year Study design, n Type of da Vinci® System Patient position (thoracic step) Number of robotic arms employed (thoracic step) Anastomotic configuration Layered suture Suture type Anastomotic leak Gradea, n (%) Cardio-pulmonary complication, n (%) Harvested LNs, mean ± sd or median (range) 30 days mortality, n (%) Anastomotic strictures, n (%) Cerfolio et al. [17], 2013 Retrospective n = 16 Si Left lateral and slightly prone 4 ETS DL: PW (IS and RS) AW: (RS and IS) IS: 3-0 Silk RS: 3-0 PDS 0 (0) 1 (6,3) 18 (15–28) 0 (0) NA Trugeda et al.[18], 2014 Prospective n = 14 Si Prone 3 ETE DL: PW (IS and RS) SL: AW (RS) IS: 2-0 Silk RS: 2-0 V-Loc (Medtronic) 4 (28,5) Grade II, 3 (21,4) Grade III, 1 (7,1) 0 (0) 18 (2–33) 0 (0) 0 (0) Bongiolatti et al.[19], 2016 Retrospective n = 8 Si Prone 3 ETS SL: PW (RS) and AW (IS) IS: ND RS: 3-0 PDS 2 (25) Grade III, 2 (25) 0 (0) 37.6 ± 14.7 0 (0) 0 (0) Egberts et al.[20], 2017 Retrospective n = 52 Si Left lateral tilted 45° to the prone position 4 ETE DL: PW (RS and RS) and AW (RS and IS) IS: Vicryl (Ethicon) RS: Stratafix (Ethicon) 5 (9,6) Grade II, 4 (7,7) Grade III, 1 (1,9) NA 29 (22–65) 3 (5,7) NA Zhanget al.[21], 2018 Prospective n = 26 S Left lateral and slightly prone 4 ETE DL: PW (RS and IS) and AW (RS and RS) IS: 3-0 Vicryl (Ethicon) RS: 3-0 V-loc (Medtronic) 2 (7,7) Grade II, 2 (7,7) 4 (15,4) 19,3 ± 9,2 0 (0) NA De Groot et al.[22], 2020 Prospective n = 68 Si Left lateral tilted 45° to the prone position 3 ETE/ETS SL: PW (RS) and AW (RS) RS: 3-0 V-loc (Medtronic)/3-0 Stratafix (Ethicon) 22 (32) Grade I, 5 (7) Grade II, 7 (10) Grade III, 10 (15) NA NA NA NA Xu et al.[23], 2021 Retrospective n = 43 Si Full lateral position 4 ETS DL: PW (RS) AW (RS) RS: 3-0 Stratafix (Ethicon) and 4-0 Vicryl (Ethicon) 0 (0) 3 (7,0)δ 17,4 ± 6,9 0 (0) 2 (4,7) Peri et al.[24], 2022 Retrospective n = 12 Si Semi-prone position 3 ETE DL: PW (RS) AW (RS and IS) RS: 3-0 V-loc (Medtronic) IS: 3-0 V-loc (Medtronic) 0 (0) NA 32,5 ± 18,3 NA 1 (11,1) Angerhrn et al.[25], 2022 Prospective n = 76 Xi Left semi-prone position 4 ETS SL: PW (RS) AW (RS) RS: Barbed suture 6 (7.9) 65 (85.5) 24.5 (18.5–32) 2 (2.6) NA Our series, 2022 Retrospective n = 30 Si and Xi Left lateral tilted 45° to prone position 3 ETS SL: PW (RS) and AW (RS) RS: 3-0 Filbloc (Assut Europe) or 3-0 V-Loc (Medtronic) 1 (3,3) Grade III, 1 (3,3) 10 (33, 3) 47 (20–81) 0 (0) 8 (26,7) AW anterior wall anastomosis, DL double layer, ETS end-to-side, ETE end-to-end, ETS end-to-side, IS interrupted suture, NA not available, ND not declared, PDS polydiaxone, PW posterior wall anastomosis, RS running suture, SL single layer suture aAnastomosis leak grade according to ECCG (Esophagectomy Complications Consensus Group) Classification In our experience no intraoperative complications occurred, and the 30-day overall complication rate was 53.3%. Pulmonary complications were observed in 26.7% of patients, 10% of whom had pneumonia. These rates are consistent with the ESODATA results of 27.8% published by the ECCG [2]. Moreover, our data supports the low rate of respiratory complications in the prone position during MIE versus open esophagectomies [27]. In this study, robot-sewn anastomosis provided an anastomotic leak rate of 3.3% (n = 1, ECCG, Type III). This finding is consistent with that reported by other similar studies ranging from 0 to 32% (Table 4) and with the average anastomotic insufficiency rate (up to 5.6%) reported by other experiences of Ivor Lewis RAMIE with mechanical intrathoracic anastomosis [8]. Of note is the fact that the ICAN randomized controlled study (in agreement with other not randomized studies [28–30]) has recently shown that in the setting of a MI approach, intrathoracic anastomosis is associated with a clinically relevant lower leakage rate compared to cervical anastomosis. In particular, the overall anastomotic leak rate (ECCG grades 1, 2, and 3) was 12.3% after MIE with intrathoracic anastomosis and 34.1% after MIE with cervical anastomosis [6]. Although routine use of thoracic duct resection remains controversial, it has been recently advocated to extend the thoracic lymphadenectomy with resection of the thoracic duct and its surroundings nodes. This dissection can increase the oncological radicality of esophagectomy since metastatic tumor cells have been detected with an incidence up to 11%. However, the most common complication that has been associated with this procedure is chyle leak [31] that represents one of the challenging problems with regards to esophagectomy with an incidence of 2–10% [2]. A recently published international consensus on RAMIE states that in terms of surgical techniques the thoracic duct resection can indeed be more easily completed thanks to RAMIE [32]. In our study chyle leaks were observed in 6.7% of patients (n = 2, ECCG-Type 2 A) even though the thoracic duct was identified and clipped in 100% of cases. We believe that the presence of secondary thoracic duct lymph flow might be a possible cause. Hence the ligation of the main thoracic duct could be considered effective but only a preventative measure to reduce the incidence of postoperative chylothorax that has a multifactorial etiology. This complication might be reduced by adopting of appropriate energy devices for the mesogastric excision or using an omental flap as well as by performing the abdominal step of the surgery with MI techniques [33]. Moreover, near-infrared fluorescence imaging (NIR-FI) using ICG has been recently proved to be effective in displaying both thoracic duct and its anatomical variations and detecting chyle leakage, which could contribute to narrowing the incidence of postoperative chylothorax [34]. In our series, 26.7% of patients developed a stricture that required at least one dilatation within 90 days of operation. None of those occurred immediately after surgery meaning that it was not a late sequela of apparent or inapparent anastomotic leakage. However, this data is higher than that reported in four similar robotic series [10, 11, 15, 16] although comparison of these results is difficult because of the heterogeneity in surgical techniques. In addition, our result is slightly higher than the stricture rates reaching 18% reported in a meta-analysis of MI ILE including both end-to-end and side-to-side techniques [35]. The robotic system offers some unique advantages in performing a hand-sewn anastomosis by leading to a more precise and controlled reconstruction as confirmed by some groups who are promoting a return to this type of anastomoses [17, 36]. However, the lack of tactile feedback and prolonged tensile effect of the barbed sutures may have contributed to the development of postoperative stricture that occurred especially in the first cases of our series. While a recent network meta-analysis has demonstrated that hand-sewn anastomosis is associated with a higher rate of anastomotic stricture compared to linear-stapled anastomosis (though superior to the circular-stapled one [37]), large, high-quality studies are needed to provide evidence about the anastomotic stricture rate among different anastomosis techniques. Short-term oncological outcomes are listed in Table 3. An R0 resection was achieved in 96.7% of patients with a median number of 47 lymph nodes which is greater than the minimum number of 15 lymph nodes mentioned in NCCN Guidelines [1]. Moreover, the number of harvested lymph nodes in our series supports recent, sound evidence which demonstrates that RAMIE yields more dissected lymph nodes than conventional MIE in patients who received neoadjuvant therapy [38]. Our study had some drawbacks. First, it had a retrospective design. Furthermore, a more consistent series of patients with a longer follow-up period would likely better confirm the oncologic and functional benefits of our technique. Despite these limitations, this article revolves mainly around the current clinical demand for details on how to do a robotic Ivor Lewis esophagogastrectomy. The outcomes of our study suggest that robotic-sewn esophagogastrostomy during ILE seems to be safe and effective, with favorable perioperative results. Nevertheless further evaluation through high quality studies is required to establish the best anastomosis reconstruction for robotic ILE [39]. Supplementary Information Below is the link to the electronic supplementary material.Supplementary file1 (MP4 154048 KB) Acknowledgements The authors thank Mrs. Anna Racca for her significant contribution to revising the manuscript. Author contributions All authors contributed to the study’s conception and design. Literature research and data analysis were performed by Alessandra Marano and Sara Salomone. The first draft of the manuscript was written by Alessandra Marano and Sara Salomone. Luca Pellegrino, Paolo Geretto and Manuela Robella commented on previous versions of the manuscript. Critical revision of the manuscript was performed by Felice Borghi. All authors read and approved the final manuscript. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Data availability All materials are available upon request. Declarations Conflict of interest The authors have no relevant financial or non-financial interests to disclose. Ethical approval This article does not contain any studies with human participants or animals performed by any of the authors. Research involving human participants and/or animals The authors declare that no experiments were performed on humans or animals for this study. Informed consent Written informed consent was obtained from the patients or the family of the patients for the publication of this paper, accompanying images, and video. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Alessandra Marano and Sara Salomone contributed equally to this article and are joint first authors. ==== Refs References 1. NCCN. Esophageal and esophagogastric junction cancers Version 4.2022—September 7, 2022. 2022. Avaible at:https://www.nccn.org/professionals/physician_gls/pdf/esophageal.pdf. 2. Low DE Kuppusamy MK Alderson D Cecconello I Chang AC Darling G Davies A D’Journo XB Gisbertz SS Griffin SM Hardwick R Hoelscher A Hofstetter W Jobe B Kitagawa Y Law S Mariette C Maynard N Morse CR Nafteux P Pera M Pramesh CS Puig S Reynolds JV Schroeder W Smithers M Wijnhoven BPL Benchmarking complications associated with esophagectomy Ann Surg 2019 269 291 298 10.1097/sla.0000000000002611 29206677 3. Gujjuri RR Kamarajah SK Markar SR Effect of anastomotic leaks on long-term survival after oesophagectomy for oesophageal cancer: systematic review and meta-analysis Dis Esophagus 2021 10.1093/dote/doaa085 4. Straatman J van der Wielen N Cuesta MA Daams F Roig Garcia J Bonavina L Rosman C van Berge Henegouwen MI Gisbertz SS van der Peet DL Minimally invasive versus open esophageal resection: three-year follow-up of the previously reported randomized controlled trial: the TIME trial Ann Surg 2017 266 232 236 10.1097/sla.0000000000002171 28187044 5. Nuytens F Dabakuyo-Yonli TS Meunier B Gagnière J Collet D D'Journo XB Brigand C Perniceni T Carrère N Mabrut JY Msika S Peschaud F Prudhomme M Markar SR Piessen G Five-year survival outcomes of hybrid minimally invasive esophagectomy in esophageal cancer: results of the MIRO randomized clinical trial JAMA Surg 2021 156 323 332 10.1001/jamasurg.2020.7081 33595631 6. van Workum F Verstegen MHP Klarenbeek BR Bouwense SAW van Berge Henegouwen MI Daams F Gisbertz SS Hannink G Haveman JW Heisterkamp J Jansen W Kouwenhoven EA van Lanschot JJB Nieuwenhuijzen GAP van der Peet DL Polat F Ubels S Wijnhoven BPL Rovers MM Rosman C Intrathoracic vs cervical anastomosis after totally or hybrid minimally invasive esophagectomy for esophageal cancer: a randomized clinical trial JAMA Surg 2021 156 601 610 10.1001/jamasurg.2021.1555 33978698 7. Schröder W Raptis DA Schmidt HM Gisbertz SS Moons J Asti E Luyer MDP Hölscher AH Schneider PM van Berge Henegouwen MI Nafteux P Nilsson M Räsanen J Palazzo F Mercer S Bonavina L Nieuwenhuijzen GAP Wijjnhoven BPL Pattyn P Grimminger PP Bruns CJ Gutschow CA Anastomotic techniques and associated morbidity in total minimally invasive transthoracic esophagectomy: results from the esobenchmark database Ann Surg 2019 270 820 826 10.1097/sla.0000000000003538 31634181 8. Hosoda K Niihara M Harada H Yamashita K Hiki N Robot-assisted minimally invasive esophagectomy for esophageal cancer: meticulous surgery minimizing postoperative complications Ann Gastroenterol Surg 2020 4 608 617 10.1002/ags3.12390 33319150 9. Cerfolio RJ Bryant AS Hawn MT Technical aspects and early results of robotic esophagectomy with chest anastomosis J Thorac Cardiovasc Surg 2013 145 90 96 10.1016/j.jtcvs.2012.04.022 22910197 10. Trugeda S Fernández-Díaz MJ Rodríguez-Sanjuán JC Palazuelos CM Fernández-Escalante C Gómez-Fleitas M Initial results of robot-assisted Ivor-Lewis oesophagectomy with intrathoracic hand-sewn anastomosis in the prone position Int J Med Robot 2014 10 397 403 10.1002/rcs.1587 24782293 11. Bongiolatti S Annecchiarico M Di Marino M Boffi B Borgianni S Gonfiotti A Voltolini L Coratti A Robot-sewn Ivor-Lewis anastomosis: preliminary experience and technical details Int J Med Robot 2016 12 421 426 10.1002/rcs.1705 26415613 12. Egberts JH Stein H Aselmann H Hendricks A Becker T Fully robotic da Vinci Ivor-Lewis esophagectomy in four-arm technique-problems and solutions Dis Esophagus 2017 30 1 9 10.1093/dote/dox098 13. Zhang Y Xiang J Han Y Huang M Hang J Abbas AE Li H Initial experience of robot-assisted Ivor-Lewis esophagectomy: 61 consecutive cases from a single Chinese institution Dis Esophagus 2018 10.1093/dote/doy048 14. de Groot EM Möller T Kingma BF Grimminger PP Becker T van Hillegersberg R Egberts JH Ruurda JP Technical details of the hand-sewn and circular-stapled anastomosis in robot-assisted minimally invasive esophagectomy Dis Esophagus 2020 10.1093/dote/doaa055 15. Xu ZJ Zhuo ZG Song TN Li G Alai GH Shen X Yao P Lin YD Pretreatment-assisted robot intrathoracic layered anastomosis: our exploration in Ivor-Lewis esophagectomy J Thorac Dis 2021 13 4349 4359 10.21037/jtd-21-438 34422361 16. Peri A Furbetta N Viganò J Pugliese L Di Franco G Latteri FS Mineo N Bruno FC Gallo V Morelli L Pietrabissa A Technical details for a robot-assisted hand-sewn esophago-gastric anastomosis during minimally invasive Ivor Lewis esophagectomy Surg Endosc 2022 36 1675 1682 10.1007/s00464-021-08715-4 34499220 17. Angehrn FV Neuschütz KJ Fourie L Wilhelm A Däster S Ackermann C von Flüe M Steinemann DC Bolli M From open Ivor Lewis esophagectomy to a hybrid robotic-assisted thoracoscopic approach: a single-center experience over two decades Langenbecks Arch Surg 2022 407 1421 1430 10.1007/s00423-022-02497-6 35332369 18. Agha RA Borrelli MR Farwana R Koshy K Fowler AJ Orgill DP The PROCESS 2018 statement: updating consensus preferred reporting of CasE series in surgery (PROCESS) guidelines Int J Surg 2018 60 279 282 10.1016/j.ijsu.2018.10.031 30359781 19. AIOM. Guidelines of gastric and esophago-gastric cancer. 2020. Avaible at: https://www.aiom.it/en/linee-guida-aiom/. 20. Shapiro J van Lanschot JJB Hulshof M van Hagen P van Berge Henegouwen MI Wijnhoven BPL van Laarhoven HWM Nieuwenhuijzen GAP Hospers GAP Bonenkamp JJ Cuesta MA Blaisse RJB Busch ORC Ten Kate FJW Creemers GM Punt CJA Plukker JTM Verheul HMW Bilgen EJS van Dekken H van der Sangen MJC Rozema T Biermann K Beukema JC Piet AHM van Rij CM Reinders JG Tilanus HW Steyerberg EW van der Gaast A Neoadjuvant chemoradiotherapy plus surgery versus surgery alone for oesophageal or junctional cancer (CROSS): long-term results of a randomised controlled trial Lancet Oncol 2015 16 1090 1098 10.1016/s1470-2045(15)00040-6 26254683 21. Al-Batran SE Homann N Pauligk C Goetze TO Meiler J Kasper S Kopp HG Mayer F Haag GM Luley K Lindig U Schmiegel W Pohl M Stoehlmacher J Folprecht G Probst S Prasnikar N Fischbach W Mahlberg R Trojan J Koenigsmann M Martens UM Thuss-Patience P Egger M Block A Heinemann V Illerhaus G Moehler M Schenk M Kullmann F Behringer DM Heike M Pink D Teschendorf C Löhr C Bernhard H Schuch G Rethwisch V von Weikersthal LF Hartmann JT Kneba M Daum S Schulmann K Weniger J Belle S Gaiser T Oduncu FS Güntner M Hozaeel W Reichart A Jäger E Kraus T Mönig S Bechstein WO Schuler M Schmalenberg H Hofheinz RD Perioperative chemotherapy with fluorouracil plus leucovorin, oxaliplatin, and docetaxel versus fluorouracil or capecitabine plus cisplatin and epirubicin for locally advanced, resectable gastric or gastro-oesophageal junction adenocarcinoma (FLOT4): a randomised, phase 2/3 trial Lancet 2019 393 1948 1957 10.1016/s0140-6736(18)32557-1 30982686 22. Low DE Allum W De Manzoni G Ferri L Immanuel A Kuppusamy M Law S Lindblad M Maynard N Neal J Pramesh CS Scott M Mark Smithers B Addor V Ljungqvist O Guidelines for perioperative care in esophagectomy: enhanced recovery after surgery (ERAS(®)) society recommendations World J Surg 2019 43 299 330 10.1007/s00268-018-4786-4 30276441 23. de Groot EM Kuiper GM van der Veen A Fourie L Goense L van der Horst S van den Berg JW van Hillegersberg R Ruurda JP Indocyanine green fluorescence in robot-assisted minimally invasive esophagectomy with intrathoracic anastomosis: a prospective study Updates Surg 2022 10.1007/s13304-022-01329-y 24. Marano A Palagi S Pellegrino L Borghi F Robotic intraoperative tracheobronchial repair during minimally invasive 3-stage esophagectomy J Chest Surg 2021 54 154 157 10.5090/jcs.20.055 33115977 25. Bonavina L Progress in the esophagogastric anastomosis and the challenges of minimally invasive thoracoscopic surgery Ann Transl Med 2021 9 907 10.21037/atm.2020.03.66 34164541 26. Plat VD Stam WT Schoonmade LJ Heineman DJ van der Peet DL Daams F Implementation of robot-assisted Ivor Lewis procedure: robotic hand-sewn, linear or circular technique? Am J Surg 2020 220 62 68 10.1016/j.amjsurg.2019.11.031 31796219 27. van der Sluis PC van der Horst S May AM Schippers C Brosens LAA Joore HCA Kroese CC Haj Mohammad N Mook S Vleggaar FP BorelRinkes IHM Ruurda JP van Hillegersberg R Robot-assisted minimally invasive thoraco laparoscopic esophagectomy versus open transthoracic esophagectomy for resectable esophageal cancer: a randomized controlled Trial Ann Surg 2019 269 621 630 10.1097/sla.0000000000003031 30308612 28. van Workum F Slaman AE van Berge Henegouwen MI Gisbertz SS Kouwenhoven EA van Det MJ van den Wildenberg FJH Polat F Luyer MDP Nieuwenhuijzen GAP Rosman C Propensity score-matched analysis comparing minimally invasive Ivor Lewis versus minimally invasive Mckeown esophagectomy Ann Surg 2020 271 128 133 10.1097/sla.0000000000002982 30102633 29. Gooszen JAH Goense L Gisbertz SS Ruurda JP van Hillegersberg R van Berge Henegouwen MI Intrathoracic versus cervical anastomosis and predictors of anastomotic leakage after oesophagectomy for cancer Br J Surg 2018 105 552 560 10.1002/bjs.10728 29412450 30. van Workum F van der Maas J van den Wildenberg FJ Polat F Kouwenhoven EA van Det MJ Nieuwenhuijzen GA Luyer MD Rosman C Improved functional results after minimally invasive esophagectomy: intrathoracic versus cervical anastomosis Ann Thorac Surg 2017 103 267 273 10.1016/j.athoracsur.2016.07.010 27677565 31. Defize IL Gorgels SMC Mazza E Schurink B Strignano P Catalano G Brosens LAA Chiusa L Bleys R Mook S Meijer GJ Romagnoli R Ruurda JP van Hillegersberg R The presence of metastatic thoracic duct lymph nodes in western esophageal cancer patients: a multinational observational study Ann Thorac Surg 2022 113 429 435 10.1016/j.athoracsur.2021.02.041 33676903 32. Li B Yang Y Toker A Yu B Kang CH Abbas G Soukiasian HJ Li H Daiko H Jiang H Fu J Yi J Kernstine K Migliore M Bouvet M Ricciardi S Chao YK Kim YH Wang Y Yu Z Abbas AE Sarkaria IS Li Z International consensus statement on robot-assisted minimally invasive esophagectomy (RAMIE) J Thorac Dis 2020 12 7387 7401 10.21037/jtd-20-1945 33447428 33. Dezube AR Kucukak S De León LE Kostopanagiotou K Jaklitsch MT Wee JO Risk of chyle leak after robotic versus video-assisted thoracoscopic esophagectomy Surg Endosc 2021 10.1007/s00464-021-08410-4 34. Yang F Gao J Cheng S Li H He K Zhou J Chen K Wang Z Yang F Zhang Z Li J Zhou Z Chi C Li Y Wang J Near-infrared fluorescence imaging of thoracic duct in minimally invasive esophagectomy Dis Esophagus 2022 10.1093/dote/doac049 35. van Workum F Berkelmans GH Klarenbeek BR Nieuwenhuijzen GAP Luyer MDP Rosman C McKeown or Ivor Lewis totally minimally invasive esophagectomy for cancer of the esophagus and gastroesophageal junction: systematic review and meta-analysis J Thorac Dis 2017 9 S826 S833 10.21037/jtd.2017.03.173 28815080 36. Bergmann J Lehmann-Dorl B Witt L Aselmann H Using the da vinci X® - system for esophageal surgery Jsls 2022 10.4293/jsls.2022.00018 37. Kamarajah SK Bundred JR Singh P Pasquali S Griffiths EA Anastomotic techniques for oesophagectomy for malignancy: systematic review and network meta-analysis BJS Open 2020 4 563 576 10.1002/bjs5.50298 32445431 38. Yang Y Li B Yi J Hua R Chen H Tan L Li H He Y Guo X Sun Y Yu B Li Z Robot-assisted versus conventional minimally invasive esophagectomy for resectable esophageal squamous cell carcinoma: early results of a multicenter randomized controlled trial: the RAMIE trial Ann Surg 2021 10.1097/sla.0000000000005023 39. Rebecchi F Ugliono E Allaix ME Morino M Why pay more for robot in esophageal cancer surgery? Updates Surg 2022 10.1007/s13304-022-01351-0
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==== Front Cognit Ther Res Cognit Ther Res Cognitive Therapy and Research 0147-5916 1573-2819 Springer US New York 10338 10.1007/s10608-022-10338-5 Original Article Acceptability and Outcomes of Transdiagnostic Guided Self-help Bibliotherapy for Internalizing Disorder Symptoms in Adults: A Fully Remote Nationwide Open Trial http://orcid.org/0000-0002-8882-0243 Lorenzo-Luaces Lorenzo [email protected] Howard Jacqueline De Jesús-Romero Robinson Peipert Allison Buss John F. Lind Colton Botts Kassandra Starvaggi Isabella grid.411377.7 0000 0001 0790 959X Indiana University-Bloomington, Bloomington, IN 47405 USA 12 12 2022 114 17 10 2022 © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Introduction Doing What Matters in Times of Stress (DWM) is a five-module transdiagnostic guided self-help (GSH) intervention developed by the World Health Organization, originally in a group-based format. In a sample of individuals recruited from across the United States, we conducted an open trial to study the feasibility and acceptability of an adaptation of DWM in which guidance was provided individually and remotely via phone and videoconferencing. Methods We assessed internalizing symptoms, psychological well-being, work and social functioning, usability of the intervention, and emotion regulation over the course of 6 weeks. Results A total of 263 individuals completed our screening. Of those, 75.29% (n = 198) qualified for the intervention. We reached most participants who qualified (71.21%, n = 141) via phone to schedule a GSH session. Most of those scheduled attended a study session (84.4%, n = 119), and most of those who attended a session completed more than half the treatment (84.03%, n = 100). Retention rates were comparable to meta-analytic estimates of dropout rates in GSH. Participants showed improvement on internalizing symptoms, psychological well-being, work and social functioning, usability of the intervention, and emotion regulation. Conclusion DWM is a freely available, seemingly efficacious transdiagnostic intervention for internalizing disorder symptoms. Supplementary Information The online version contains supplementary material available at 10.1007/s10608-022-10338-5. Keywords Transdiagnostic CBT Internalizing symptoms Depression Anxiety Self-help http://dx.doi.org/10.13039/100000025 National Institute of Mental Health T32 MH103213-06 T32 MH103213-06 T32 MH103213-06 De Jesús-Romero Robinson Peipert Allison Buss John F. http://dx.doi.org/10.13039/100019274 National Institute of Mental Health and Neurosciences T32 MH103213-06 Starvaggi Isabella http://dx.doi.org/10.13039/100006108 National Center for Advancing Translational Sciences KL2TR002530 UL1TR002529 Lorenzo-Luaces Lorenzo ==== Body pmcInternalizing disorder symptoms such as depression and anxiety are among the leading causes of disability worldwide (Kotov et al., 2017; Whiteford et al., 2013). Most individuals with internalizing disorder symptoms prefer, and are more likely to adhere to (Swift et al., 2017), treatment with psychological interventions than with medications (Löwe et al., 2006; McHugh et al., 2013). The most well-researched psychological interventions available for internalizing disorders are cognitive–behavioral therapies (CBTs; Lorenzo-Luaces, 2018; Lorenzo-Luaces, et al. 2021a; Cuijpers et al., 2019). CBTs are a family of interventions that aim to change behavior, cognition, and meta-cognition via the use of cognitive, behavioral, and more recently acceptance and mindfulness-based interventions (DeRubeis & Lorenzo-Luaces, 2017; Hofmann & Hayes, 2019). Despite the existence of CBTs and other effective interventions, the burden of internalizing disorders has not decreased in the past four decades and most individuals still do not receive treatment (Jorm et al., 2017; Kazdin & Blase, 2011). To increase the dissemination of psychological interventions, researchers have developed self-help approaches to the treatment of internalizing disorder symptoms. Self-help provides much of the same content as do individual psychological interventions (e.g., psychoeducation about stress, coping skills), but the content is delivered via websites or internet/phone applications (Lorenzo-Luaces et al., 2018a, b; Wasil et al., 2021b), books (i.e., bibliotherapy; De Jesús-Romero et al., 2022), other formats such as group lessons (Dolan et al., 2021), or some combination of these. In unguided self-help, an individual uses the self-help material by themselves. In guided self-help (GSH), an individual uses self-help material with a professional or paraprofessional promoting adherence to the material along with emotional support. GSH-CBT appears to be roughly comparable to face-to-face CBT in its efficacy and both GSH-CBT, and individual face-to-face CBT is more effective than unguided self-help (Cuijpers et al., 2019). Given that GSH-CBT does not require the presence of a highly trained professional, it may be more scalable than face-to-face psychotherapy and therefore may have greater potential to reduce the public health burden of psychopathology (Kazdin & Blase, 2011). Despite the promise of GSH-CBT approaches, there are numerous barriers to their widespread adoption. Many popular books and apps have little to no research supporting their efficacy (Wasil et al., 2020). Those that are empirically supported are usually not available to the general public or to most clinicians (Wasil et al., 2021b) and clinicians do not frequently use GSH approaches (Peipert et al., 2022a, b). Even those interventions that both have been studied and are freely available are often not very accessible (e.g., they are written at a very high reading level; Martinez et al., 2008). Beyond its scalability, the acceptability of an intervention may be a factor determining its successful dissemination (Michie et al., 2011). Wolf (1978) was one of the first to define acceptability, although they used the terms “social validity” and “social importance,” referring to the extent that an intervention introduces changes consistent with a client or society’s goals, deemed appropriate to use, and satisfactory to the client. Although GSH-CBT appears to have roughly equal outcomes to face-to-face individual CBT, it tends to be less acceptable to patients as evidenced by higher rates of dropout after treatment initiation (Cuijpers et al., 2019). Researchers have tried a number of strategies to increase the acceptability of GSH-CBT while maintaining its scalability, including changing the modality of the guidance (e.g., using text messages or e-mail instead of video calls), adjusting the dose of guidance, using eCoaches with varying qualifications (e.g., paraprofessionals versus experienced psychotherapists), and comparing synchronous versus asynchronous communication modes (Baumeister et al., 2014). By and large, the literature supports the importance of guidance in self-help CBT for achieving better outcomes and engagement, but does not provide strong support for other ways of increasing acceptability (Bur et al., 2022; Furukawa et al., 2021). Doing What Matters in Times of Stress (DWM), previously called Self-Help Plus, is a GSH-CBT developed by the World Health Organization (WHO) based on principles of acceptance and commitment therapy (ACT), a form of CBT (Hofmann & Hayes, 2019). Originally, DWM consisted of five group-based psychoeducation sessions delivered through pre-recorded audio materials with a corresponding print guide. Two small trials supported the efficacy and feasibility of DWM (Tol et al., 2018a, b). In a subsequent cluster randomized controlled trial (RCT) of Sudanese refugees in Uganda (Tol et al., 2020), 694 women from 14 villages were randomized to DWM or enhanced care as usual care (eCAU), which consisted of brief psychoeducation plus the provision of referrals. After 6 weeks, individuals in DWM reported lower rates of internalizing distress [standardized mean difference (SMD) = 0.72] and higher levels of psychological well-being (SMD = 0.51). In a preventive RCT with refugees and asylum seekers (N = 459), DWM appeared effective in reducing mental health symptoms among individuals with no mental health diagnosis, but did not predict a lower incidence of mental health diagnoses at a long-term follow-up (Purgato et al., 2021). A more recent RCT (N = 642) supported the preventive effects of DWM versus eCAU for Syrian refugees in Turkey (Acarturk et al., 2022). Taken together, these data support the efficacy of DWM as a group-based mindfulness and acceptance-focused GSH-CBT. Because DWM is made freely available by the WHO (https://www.who.int/publications/i/item/9789240003927) and was developed at an accessible reading level (approximately fourth grade), it has the potential to be a widely scalable intervention. Following the COVID-19 pandemic, several translations of the DWM booklet were made available online. Given the logistic difficulties associated with group-based GSH-CBT (e.g., COVID-19 risk associated with gathering), the WHO adapted the DWM intervention materials such that they could be delivered remotely via telephone or videoconferencing. We conducted an open trial aiming to test the feasibility of conducting GSH-CBT using DWM with individual online coaching, instead of group-based meetings, for individuals across the United States. To our knowledge, this is the first published study of DWM implementation in the US. We assessed the acceptability of the intervention as evidenced by engagement with the guidance in GSH-CBT, self-reported usability, and self-reported satisfaction. In addition to tracking feasibility and acceptability of the intervention, we assessed internalizing symptoms, well-being, and purported emotion regulation mechanisms of change: cognitive reappraisal and expressive suppression (Aldao & Nolen-Hoeksema, 2010). We also measured quality of life and work and social functioning, which may be less responsive to psychosocial intervention than internalizing symptoms (Lorenzo-Luaces & Amsterdam, 2018; Peipert et al., 2022a, b). Methods This study was approved by Indiana University’s Institutional Review Board. Participant recruitment began October 17, 2020, and ended February 21, 2022. All recruitment was conducted online and all participants provided informed consent for the study. The study was registered on ClinicalTrials.gov on July 1, 2021 (NCT04870099). Participants Participants were adults (ages 18+) living in the United States who were recruited from social media platforms, primarily Facebook, as well as Instagram and Twitter. We promoted the study by writing a post in our lab’s social media accounts directed to individuals “struggling with stress, depression, or anxiety.” The post contained a survey link and a flyer describing major components of the study (e.g., the compensation rate). Given the limited reach of our lab’s webpage, we used the paid features of the above social media platforms to promote the post. We sought to recruit participants using very minimal entry criteria. The only criterion for entry was the presence of at least mild psychological distress, as evidenced by a score ≥ 6 on the six-item Kessler Psychological Distress Scale (K6; see “K6” below). The only criterion for exclusion was the presence of recurrent death ideation/suicidality, which we initially operationalized as a score ≥ 1 (i.e., “several days”) on item nine of the Patient Health Questionnaire-9 (PHQ-9; “thoughts that you would be better off dead or of hurting yourself”). We subsequently modified the suicidality criteria to exclude participants who scored ≥ 2 (i.e., “more than half the days”), thus allowing a PHQ-9 item nine score of one. We made this change given that our early data suggested that most individuals who were excluded from the study based on the original criterion only had infrequent death/suicidal ideation. Participants who were excluded on the basis of suicidality, regardless of how it was operationalized, were given resources for emergencies as well as for finding outpatient treatment providers. Valid Respondents Given that we conducted this study over the internet and across the United States, there was a possibility of fraudulent responses, including automated bots. To identify fraudulent respondents, we operationalized “bot-like” or fraudulent behavior as (a) responding that appeared implausibly fast (e.g., completing the roughly 100-question intake in 5 min or less), (b) filling out the study screening at a time in which we were not actively promoting the study, (c) providing duplicate contact information across entries (e.g., the same home address or e-mail), (d) providing seemingly fake contact information (e.g., the name “Deez Nutz”), or (e) other behavior that may be indicative of fraudulent responding (e.g., answers to questions that were actually “hidden” from survey participants), including inconsistent responding to survey items. Out of 486 “clicks” on our screening survey link, we deemed that 12.55% (n = 61) were fraudulent respondents. Of the purportedly human respondents (n = 425), 162 individuals did not complete the screening survey, for a total of 263 individuals fully screened for trial entry (see Fig. 1).Fig. 1 Trial progression for individuals on a trial of transdiagnostic guided self-help for internalizing distress Intervention DWM is a five-chapter booklet that discusses principles of ACT and CBT, namely mindfulness (here called “grounding”), cognitive distancing (“unhooking”), value-based behavioral activation (“acting on your values”), gratitude (“being kind”), and acceptance (“making room”). Participants were given the option of reading a digital version of the DWM booklet, though most (88.89%) opted to receive the printed booklet by mail. Eligible participants were assigned an “eCoach” and contacted within a week of their qualification for the study. eCoaches The eCoaches were undergraduate/post-baccalaureate (JH, CL, and KB) and graduate students (RDJR, AP, and JB) at the beginning of the study. All were young adults and all were completing degrees in psychology. None of them had experience with ACT, though two had completed an introductory practicum in CBT prior to the start of the study (AP and RDJR). The undergraduate/post-baccalaureate eCoaches completed a four-hour training covering common mental disorders, principles of CBT, and technology-assisted GSH-CBT. All eCoaches (i.e., graduate and undergraduate students) completed a four-hour training over the course of four weeks that included reading the DWM booklet, completing the WHO’s EQUIP training (EQUIP), reading a chapter on “basic helping skills” from the WHO’s Problem Management Plus (PM+) guide, and reading a DWM-specific training manual provided by the WHO. Part of the training involved a safety plan for dealing with emergent suicidality. The safety plan involved administering the Columbia Suicide Severity Rating Scale (CSSRS; Posner et al., 2008) and giving crisis referrals for individuals who had acute suicidal ideation. The eCoaches also had to “pass” a roleplay with the principal investigator (LL-L). Beyond passing the role-play with the PI, competence was not assessed systematically nor was adherence. For all interactions with participants, eCoaches were given semi-structured scripts. There were no statistically significant differences between the eCoaches in rates of study retention or changes any study outcome (ps > 0.09; see “Appendix”). Guidance The first communication for the study was an onboarding or “welcome” call in which participants were provided information about the study, given a chance to ask questions, and asked to schedule three to six individual weekly sessions over a 6-week period. We let participants schedule fewer than six sessions aiming to maximize engagement for participants who thought six sessions would be too burdensome. During the welcome call, eCoaches helped participants create a plan to use the guide, primarily via a short exercise of mental contrasting with implementation intentions. As part of the exercise, eCoaches helped participants identify how they wanted to use the guide, predict effects of using the guide, identify potential obstacles to adhering to the guide, and brainstorm potential solutions for the predicted obstacles. Subsequent meetings also followed a semi-structured script. The guidance meetings began by asking participants to confirm they are still available to meet as well as to confirm their understanding of study confidentiality. The eCoaches ensured that study measures had been filled out and used a principle of measurement-based care: reviewing changes in internalizing symptoms, well-being, and emotion regulation with participants. Next, eCoaches assessed adherence to the reading, which was typically scheduled as one chapter per week. If the participant was able to use the guide with no or only a few challenges, they were praised for their efforts, asked about whether they practiced the specific exercises described in the chapter, and asked to comment on what they noticed about practicing the exercises. If the user was not able to use the guide, the eCoaches were instructed to show empathy and understanding and to review the participant’s plan to use the book, including whether it adequately addresses challenges the participant encountered. Regardless of whether participants were able to read the book or not, if they were still interested in participating, the eCoach confirmed the next appointment. The PI provided weekly, as well as ad-hoc, supervision. Supervision focused on using concrete behavioral strategies (e.g., problem-solving) for promoting adherence to the intervention and dealing with resistance by using principles of motivational interviewing. Outcome Measures The main outcome measures we used to assess efficacy, potential mechanisms, acceptability, and feasibility are described below. All survey questionnaires were administered online using RedCap. For each survey questionnaire, we present a measure of internal consistency omega (ω), which is interpreted in the same manner as Cronbach’s α but may have more desirable psychometric properties (Flora, 2020). Acceptability and Feasibility We report the number of participants who (1) completed our baseline assessment, (2) qualified for the study, (3) we were able to reach for an onboarding call, (4) completed one session of GSH-CBT, (5) completed more than 50% of the scheduled assessments, and (6) completed the post-treatment (week 6) assessments. In addition to these metrics, we administered the Systems Usability Scale (SUS; Brooke et al., 1996), a brief measure for assessing the usability of given systems (e.g., websites). The SUS has ten items and is rated on a five-point scale with responses ranging from 0 (“strongly agree”) to 4 (“strongly disagree”). Scale scores are multiplied by 2.5 to produce scores ranging from 0 to 100. Prior work supports the reliability and validity of the SUS (Lewis, 2018). We administered the SUS at week 6, but we also administered a slightly modified version of the SUS at baseline to control for between-individual differences (e.g., the tendency to give high ratings). Participants were asked to rate the usability of the book at baseline “based on the small amount of information [they] have on the study.” In the current study, the baseline scores on the SUS appeared internally consistent (ω = 0.85, 95% CI 0.81–0.89). K6 The K6 (Kessler et al., 2002) is a six-item self-report scale that measures internalizing distress (e.g., nervousness, depression). Its items are rated on a scale of 0 (“none of the time”) to 4 (“all of the time”), producing scores ranging from 0 to 24 where higher scores indicate greater psychological distress. Previous studies support the reliability and validity of the K6 (Batterham et al., 2018; Staples et al., 2019) and it has previously been used as an outcome measure in GSH-CBT studies (Lorenzo-Luaces et al., 2018a, b). A score of 13 indicates “severe” symptoms of internalizing distress. In the current study, the baseline scores on the K6 appeared internally consistent (ω = 0.7, 95% CI 0.62–0.79). The K6 was administered at baseline and every week thereafter, up to the week 6 post-treatment assessment. WHO Well-Being Index (WHO-5) The WHO-5 (Topp et al., 2015) is a five-item self-report scale that measures subjective well-being, an aspect of positive mental health. Its items are rated on a scale of 0 (“at no time”) to 5 (“all of the time”). The raw total scores (0 to 25) are multiplied by 4, producing final scores ranging from 0 to 100, where higher scores indicate greater well-being. Prior work supports the reliability and validity of the WHO-5 (Topp et al., 2015), and it has previously been studied as an outcome measure in GSH-CBT studies (Tol et al., 2020). A score of 50 is considered a useful cutoff for screening for major depression. In the current study, the baseline scores on the WHO-5 appeared internally consistent (ω = 0.79, 95% CI 0.73–0.86). The WHO-5 was administered at baseline and every week thereafter, up to the week 6 post-treatment assessment. Work and Social Adjustment Scale (WSAS) The WSAS (Mundt et al., 2002) is a five-item self-report measure that assesses impairment in work, relationships, household, and leisure activities as a result of a specific problem; in our study we queried the effect of “stress” on functioning (e.g., “[b]ecause of my stress my ability to form and maintain close relationships with others, including those I live with, is impaired”). Each item is rated on a nine-point Likert ranging from zero (“not at all”) to eight (“very severely”), producing scores ranging from zero to 40 where higher scores indicate greater impairment. Scores over 10 and over 20 are considered to indicate moderate and severe impairment, respectively. Prior work supports the reliability and validity of the WSAS across various patient populations (Zahra et al., 2014). In the current study, the baseline scores on the WSAS appeared internally consistent (ω = 0.82, 95% CI 0.77–0.87). Emotion Regulation Scale (ERQ) The ERQ (Gross & John, 2003) is a ten-item self-report measure of individual differences in the use of two emotion regulation strategies: cognitive reappraisal (ERQ-reappraisal; items 1, 3, 5, 6, 8, and 10) and expressive suppression (ERQ-suppression; items 2, 4, 6, and 9). Prior work supports the reliability and validity of the ERQ in community samples (Preece et al., 2019, 2021). The ERQ items are rated on a seven-point Likert scale with responses ranging from 1 (“strongly disagree”) to 7 (“strongly agree”). We averaged item scores to produce final scores on the same metric of the original items (i.e., 1 to 7) in order to make the ERQ-reappraisal and ERQ-suppression subscales (with differing numbers of items) comparable. In the current study, the baseline scores on the ERQ-reappraisal (ω = 0.83, 95% CI 0.77–0.88) and ERQ-suppression appeared internally consistent (ω = 0.87, 95% CI 0.83–0.91). The ERQ was administered at baseline and every week thereafter, up to the week 6 post-treatment assessment. Other Assessments We also administered (1) the PROMIS Depression Short Form (also known as the Cross-Cutting DSM Severity Measure for Depression; American Psychiatric Association, 2013), an eight-item self-report measure of depression symptoms that produces scores ranging from 8 to 40, and (2) the Alcohol Use Disorder Identification Test (AUDIT; Allen et al., 1997), a self-report screening scale for problematic drinking that produces scores ranging from 0 to 40, and (3) a single-item measure of self-rated health (Jylhä, 2009) assessed on a five-point scale. Prior work supports the reliability and validity of both the PROMIS (Cella et al., 2010, 2019; Pilkonis et al., 2014) and the AUDIT (Meneses-Gaya et al., 2009). We included these measures to provide a better characterization of the sample, for example, regarding the specific types of internalizing distress experienced (i.e., depression versus other), comorbid externalizing symptoms (alcohol being the most common type of externalizing disorder), as well as physical health and somatoform symptoms (Brissette et al., 2003). An additional rationale for including these assessments is that these variables have been found to predict treatment outcomes (Kessler et al., 2017). Sample Size Justification and Power We initially powered the trial to be able to detect a statistically significant difference in engagement relative to the 65.1% engagement rate reported in Van Ballegoojien et al.’s (2014) meta-analysis. We used an online (https://sample-size.net/sample-size-conf-interval-proportion/) calculator (Kohn & Senyak, 2021) to estimate the sample size required to test for a statistically significant difference between a sample proportion and the expected value (i.e., 65.1%) at a p value < .05. This analysis suggested we needed to recruit at least 95 individuals to have an adequately powered acceptability trial. We ultimately recruited more participants than was necessary (n = 141) partially due to uncertainty about our ability to retain all individuals. In addition, this was possible because the PI (LL-L) obtained additional funding for an extension assessing the effects of GSH-CBT on natural language metrics of social media data. That subcomponent of the study (i.e., whether GSH-CBT produces effects detectable via social media) is not being used in the current analysis. We used G*Power 3.1 (Faul et al., 2007) to estimate what magnitude of within-person changes we had adequate powered to detect in our 141-participant sample. The results of this analysis suggested that we could detect small-to-medium within-person changes (d = 0.25, at p < .05 and power of 80%) with the achieved sample size (i.e., n = 141). Analytic Strategy All analyses were conducted in R version 4.1.2 (see R Core Team, 2013) using the R Studio Graphic User Interface. All code and deidentified data are available on the Open Science Foundation (OSF) site (https://osf.io/j32uw/). First, we report the percentage of participants who progressed from beginning the survey to the end of the study. We followed an intent-to-treat (ITT) approach, analyzing data from all individuals who reached the onboarding call to confirm trial participation. Multiverse Analysis of Engagement There are at least two other definitions of trial entry possible in online trials like ours. One is less conservative, considering to be true study subjects only those individuals who completed at least one post-baseline assessment after the baseline eligibility survey. The other is more conservative, considering to be true study participants all individuals who qualified for the study regardless of whether or not they were reachable following the baseline eligibility survey. We also analyzed two different definitions of trial completion: completing 100% of the scheduled GSH-CBT sessions, and completing at least 50% of the scheduled GSH-CBT sessions. Given variability in how study entry and completion could be defined, we conducted a “multiverse” analysis to assess the acceptability of the intervention (see Steegen et al., 2016). In a multiverse analysis, a researcher conducts and presents all possible ways of analyzing data (i.e., here, the engagement rate). Multiverse analysis has been recommended as a way of increasing transparency in psychological sciences by presenting readers multiple versions of the data, as opposed to simply presenting the analyses that give the result with the most favorable effects. We chose a non-inferiority margin of 10% to determine if observed engagement rates were equivalent to the rates from the meta-analysis. Demographics and Change Over Time We report baseline demographic and clinical characteristics by presenting means and standard deviations for continuous variables and percentages for categorical variables (see Table 1). To assess the preliminary efficacy of the intervention, we conducted mixed regression models using the lme4 (Bates et al., 2015) and lmerTest (Kuznetsova et al., 2017) packages in R to regress internalizing symptoms (K6), well-being (WHO-5), ERQ-reappraisal, and ERQ-suppression on time in GSH-CBT. We coded the time variable by dividing each week by six, the total number of weeks in the study. This creates a variable ranging from 0 to 1 (e.g., week 1 is 0.17, week 2 is 0.33, week 3 is 0.50, etc.) where a one-point increase in “time” represents change from baseline to the end of treatment. We calculated effect sizes for the results of these mixed models by using the framework proposed by Feingold (2009) wherein estimated change over the course of the intervention is divided by the baseline standard deviation of the measure. Additionally, we assessed pre–post change in the perceived usability of DWM (i.e., the SUS score) as well as in psychosocial functioning (i.e., WSAS) by conducting a paired-sample t-test comparing the scores at baseline with the scores at week 6. We calculated the effect size of pre-post change in the SUS and WSAS by dividing change in these measures by the standard deviation of their change scores. We calculated 95% confidence intervals (CIs) for both of these d-type effect sizes by using the “cohen.d.ci” function in the psych package in R (Revelle, 2016).Table 1 Sociodemographic and clinical features of 141 individuals in a trial of transdiagnostic guided self-help Characteristic N N = 141 Age (years) 138 40.36 (13.95) Age onset distress 141 16.47 (9.54) Distress (K6: 0–24) 141 10.99 (3.59) Well-being (WHO5: 0–100) 139 29.55 (14.65) Functioning (WSAS: 0–40) 141 22.48 (8.77) Usability (SUS: 0–100) 135 71.94 (13.59) Reappraisal (ERQ: 1–7) 136 4.21 (1.14) Suppression (ERQ:1–7) 138 3.71 (1.33) Predicted satisfaction 139 6.88 (2.03) Depression (PROMIS: 8–40) 136 23.97 (5.83) Alcohol use (AUDIT: 0–40) 139 2.91 (3.69) Health (1–5) 140  Excellent 6 (4.3%)  Good 56 (40%)  Average 58 (41%)  Poor/terrible 20 (14%) Gender identity 141  Male/TGNC 21 (15%)  Female 120 (85%) Race/ethnicity 141  Non-Hispanic White 110 (78%)  Non-Hispanic Black 5 (3.5%)  Hispanic 11 (7.8%)  Asian 8 (5.7%)  Other/multiracial 7 (5.0%) Married or dating 141  Single 52 (37%)  Married or dating 89 (63%) Unemployed 141  Employed 101 (72%)  Unemployed 40 (28%) Antidepressant use 141  Current or past 100 (71%)  Never 41 (29%) Educational attainment 141  HS diploma or lower 5 (3.5%)  Some college 30 (21%)  Associate's degree 17 (12%)  Bachelor's degree 49 (35%)  Master's degree 31 (22%)  Postgraduate 9 (6.4%) Income 140  < $15,000 18 (13%)  $15,000–$24,999 8 (5.7%)  $25,000–$34,999 15 (11%)  $35,000–$49,999 11 (7.9%)  $50,000–$74,999 31 (22%)  $75,000–$99,999 26 (19%)  $100,000–$149,999 23 (16%)  $150,000–$199,999 8 (5.7%) 1Mean (SD); n (%) K6 Kessler 6 Scale for Psychological Distress, WHO-5 WHO Well-being Index 5, ERQ Emotion Regulation Questionnaire, WSAS Work and Social Adjustment Scale, SUS Systems Usability Scale, TGNC transgender or gender non-conforming, HS high school In our analyses of the SUS and WSAS, we used a last-observation carried forward (LOCF) imputation approach to deal with missing session-six scores. In our analyses of the K6, WHO-5, and ERQ, we used hierarchical linear modeling (HLM) to handle missing data (Hox, 2000). We refer to these analyses as the “LOCF-imputed” data. Missing Data Imputation Missing data in demographic covariates was minimal, with most individuals providing complete information for most variables. A maximum of six individuals did not fully answer the SUS (4.3%). There was more longitudinal data missing for the K6, WHO-5, and ERQ related to dropout or missing assessments, up to a maximum of 33.3%, over the course of the intervention. Additionally, several WSAS and SUS ratings were also missing, as not all participants completed the week 6 assessment. To address missing data, including missing outcome data, we imputed all missing data using a machine learning algorithm: non-parametric missing value imputation using random forests, with the R package missForest (Stekhoven & Bühlmann, 2012). To preserve the association between the variables (Ginkel et al., 2020), we did not pre-process variables and only minimally recoded them (see OSF). Imputation models that use multiple variables are preferred to LOCF-type imputation models like the one we describe above (Kenward & Molenberghs, 2009; Lachin, 2016). The variables in the imputation model included baseline to week 6 data on the K6, WHO-5, ERQ, WSAS, SUS, PROMIS depression severity, and baseline demographic and clinical data including age, gender, race, marital status, unemployment status, education, income, self-rated health, antidepressant history, and the age at which participants first struggled with internalizing disorder symptoms. We refer to these data as the RF-imputation data. For all of the analyses described above, we present the random forest imputation (RF-imputation) results and the LOCF-imputed results. Results Feasibility A total of 425 individuals started our screening survey, of whom 263 completed it (61.88%). Of these, 198 met our entry criteria. A large number (n = 32, 49.23%) of those who did not meet the entry criteria had symptoms that were too mild (i.e., K6 < 6). A similarly large number did not meet the criteria because of the suicidality exclusion (n = 32, 49.23%). One participant was excluded for not responding to the item probing suicidality. Of the 198 participants who qualified for the study, we were able to reach 141 individuals for an onboarding call (71.21%) to confirm participation. Of those, 119 (84.4%) initiated GSH. Of participants who we reached for an onboarding call, 100 (70.92%) completed at least half of scheduled sessions. 97 (68.79%) Individuals attended the post-treatment assessment. We conducted the “multiverse” analysis calculating the retention rates from all possible definitions of those who entered the study (i.e., qualified, n = 198; reached for onboarding call, n = 141; initiated GSH, n = 119) as well as the two definitions of those who completed the study (i.e., who attended the post-treatment assessment n = 97, or who completed at least half of agreed-upon sessions n = 100). Overall, four of the six engagement rates we calculated were non-inferior to the 65.1% engagement rate from the meta-analysis by Van Ballegooijen et al. (2014) and one was inconclusive (see Fig. 2).Fig. 2 Multiverse analysis of engagement rates for different definitions of trial entry and trial completion for participants undergoing transdiagnostic guided self-help CBT Sample Demographics Most participants in the sample identified as cisgender women. Although different income categories were relatively well represented, the sample was somewhat more educated than one would be expect of a representative US sample (see Table 1). On average, participants reported struggling with internalizing disorder symptoms very early in life (M = 16.47, SD = 9.54). Although our internalizing symptom entry criterion was relatively low (K6 ≥ 6), the average participant reported internalizing distress scores substantially higher than the cutoff (K6: M = 10.99, SD = 3.59), as well as relatively low well-being (WHO-5: M = 29.55, SD = 14.65). Attesting to the clinical severity of our sample, 131 (92.91%) of individuals met the WSAS cutoff for moderate impairment, 125 (88.65%) individuals met the WHO-5 cutoff for depression screening, 87 (61.7%) met the PROMIS depression cutoff for moderate depression, 88 (62.41%) met the WSAS cutoff for severe impairment, and 40 (28.37%) met the K6 cutoff for severe distress. Acceptability After reading the consent, participants’ expectations of the usability of DWM were relatively high (RF-imputed: M = 72.18, SD = 13.41; LOCF-imputed: M = 71.94, SD = 13.59). About two thirds of individuals reported scores of 68 or higher (RF-imputed: 62.41%, LOCF-imputed: 60.74%). After 6 weeks of DWM, acceptability (RF-imputed: M = 84.1, SD = 8.599; LOCF-imputed: M = 84.43, SD = 10.17) increased substantially [RF-imputation: Mdiff = 11.89, t(140) = 11.16, p < .001; LOCF-imputed: Mdiff = 8.259, t(134) = 8.088, p < .001; see Table 2]. Of those queried at week 6, almost all reported the intervention was usable (i.e., SUS ≥ 68; RF-imputed: 94.33%, LOCF-imputed: 91.75%).Table 2 Standardized mean differences (SMDs) of within-person changes for 141 participants with internalizing distress treated with transdiagnostic guided self-help CBT Outcome LCI (RF) SMD (RF) UCI (RF) LCI (LOCF) SMD (LOCF) UCI (LOCF) Internalizing (K6)  − 1.42  − 1.21  − 0.99  − 1.52  − 1.30  − 1.08 Well-being (WHO-5) 0.68 0.88 1.07 0.74 0.94 1.14 Reappraisal (ERQ) 0.54 0.73 0.92 0.60 0.79 0.98 Suppression (ERQ)  − 0.50  − 0.33  − 0.16  − 0.55  − 0.38  − 0.21 Functioning (WSAS)  − 1.18  − 0.98  − 0.78  − 0.88  − 0.70  − 0.51 Usability (SUS) 0.74 0.93 1.13 0.51 0.70 0.88 Satisfaction 0.74 0.94 1.14 0.54 0.72 0.91 LCI lower 95% confidence interval, UCI upper 95% confidence interval, RF random forest imputation, LOCF last observation carried forward imputation, K6 Kessler 6 Scale for Psychological Distress, WHO-5 WHO Well-being Index 5, ERQ Emotion Regulation Questionnaire, WSAS Work and Social Adjustment Scale, SUS Systems Usability Scale Symptom Reduction Over the course of GSH-CBT, there were large reductions in internalizing disorder symptoms [RF-imputation: B =  − 4.37, SE = 0.29, t(140) =  − 14.96, p < .001; LOCF-imputed: B =  − 4.67, SE = 0.4, t(94.38) =  − 11.77, p < .001]. Similarly, over the course of GSH-CBT, there were large improvements in well-being [RF-imputation: B = 12.7, SE = 1.44, t(140) = 8.8, p < .001; LOCF-imputed: B = 13.8, SE = 1.95, t(107.4) = 7.055, p < 0.001]. From baseline to the post-treatment assessment, there were improvements in work and social functioning [RF-imputation: Mdiff =  − 7.87, t(140) =  − 11.91, p < 0.001; LOCF-imputed: Mdiff =  − 5.48, t(140) =  − 8.256, p < 0.001]. These changes were large in magnitude (see Table 2; Fig. 3). There were no reports of treatment-emergent suicidality.Fig. 3 Changes in a internalizing distress, b well-being, c cognitive reappraisal, and d expressive suppression in 141 individuals in GSH-CBT Emotion Regulation Compared to nationally representative samples (Preece et al., 2021), participants in our study had relatively low levels of self-reported reappraisal use (RF-imputation: M = 4.2, SD = 1.12; LOCF-imputed: M = 4.21, SD = 1.14) but average levels of suppression use (RF-imputation: M = 3.73, SD = 1.32; LOCF-imputed: M = 3.71, SD = 1.33). Over the course of GSH-CBT, there were large increases in cognitive reappraisal use (RF-imputation: B = 0.823, SE = 0.078, t(140) = 10.59, p < .001; LOCF-imputed: B = 0.891, SE = 0.11, t(93.11) = 8.399, p < .001]. The reductions in expressive suppression were more modest [RF-imputation: B =  − 0.437, SE = 0.09, t(140) =  − 4.867, p < .001; LOCF-imputed: B =  − 0.513, SE = 0.12, t(101) =  − 4.339, p < .001; see Table 2]. Discussion We conducted a fully remote nationwide clinical trial to assess the feasibility, acceptability, and preliminary efficacy of DWM, a GSH-CBT, in a United States sample. Our results demonstrate that DWM can be delivered in a fully remote fashion, consistent with other studies suggesting that nationwide recruitment of individuals with internalizing symptoms is feasible (Arean et al., 2016). Our multiverse analysis suggested that we were able to retain anywhere from 48 to 79% of individuals. The most conservative retention estimate (48%) was calculated with study entry defined as simply qualifying for the study after completing the baseline survey and study completion defined as completing more than 50% of scheduled GSH-CBT sessions. This conservative approach suggested that we lost half of study participants to dropout, resulting in lower retention rates than we might expect based on meta-analyses of GSH-CBT. All other definitions of retention rate that we tested suggested yielded comparable with or higher than in prior work (70–79%). Nonetheless, we observed that with every “step” in the process of engaging individuals in GSH-CBT, there was a sizeable reduction in participants who remained engaged with the intervention. This has also been observed in studies of individual face-to-face psychotherapy (Krendl & Lorenzo-Luaces, 2021). These findings imply that in order to maximize the reach of GSH-CBT, we need to reduce as many of the barriers of its initiation as possible (e.g., shorter screening times, more relaxed entry criteria). While human engagement generally facilitates desired outcomes and promotes adherence to self-help approaches like bibliotherapy or internet-based treatment (Cuijpers et al., 2019), requiring human engagement (e.g., as in reaching the welcome call for the current trial) may actually be a barrier for some individuals. Over the 6-week study period, individuals who engaged in the DWM GSH-CBT reported very large decreases in internalizing distress, large increases in well-being, large improvements in functioning, and improved perceptions of the usability of the intervention. Additionally, we also found that participants experienced large increases in cognitive reappraisal and medium decreases in expressive suppression. These findings continue to underscore the promise of GSH-CBT to address the burden of untreated psychopathology. For example, it may be beneficial to target dissemination of self-help CBT material at individuals currently on waiting lists for more traditional psychological services (Peipert et al., 2022a, b). The level of attrition we reported underscores the need to optimize engagement in GSH-CBT. Given that human support has been the only replicable predictor of engagement in GSH-CBT (Bur et al., 2022; Cavanagh et al., 2010; Furukawa et al., 2021), it would behoove the field to explore ways of optimizing the human element of GSH-CBT. For example, in face-to-face CBT, greater session frequency (e.g., twice-weekly instead of once-weekly) improves outcomes (Bruijniks et al., 2020). It is possible that increasing the level of engagement in GSH-CBT may improve outcomes or engagement. In our study, most dropout occurred after individuals qualified for the study when they could not be reached for an onboarding call. The moment in which individuals seek psychological services may be a moment when they are most receptive for such services, and waiting time following that moment (e.g., the wait for the onboarding call) may represent an engagement obstacle (Krendl & Lorenzo-Luaces, 2021). One promising way to increase engagement, then, may be to immediately make very brief interventions, such as single-session interventions (SSIs), immediately available to treatment seekers. SSIs have been widely studied for youth psychopathology (Schleider & Weisz, 2017), and emerging research supports their use in adults (Wasil et al., 2021a, b, c). A logical future direction is to study the combination of SSI and other forms of GSH-CBT in a “stepped care” fashion (Lorenzo-Luaces et al., 2017) to investigate whether immediate access to an SSI increases subsequent engagement with treatment (the GSH-CBT). Given individual differences in engagement and response to these interventions, it will also be worthwhile to explore predictors of engagement and response that could be used for the purposes of risk stratification (Lorenzo-Luaces et al., 2017, 2020; Lorenzo-Luaces et al., 2021b). Male gender seems to be a predictor of low engagement, as does lower education level and younger age (Karyotaki et al., 2015). Future larger-scale studies should explore a greater number of potential predictors (Kessler et al., 2017). Another option, then, may be to target GSH-CBT efforts at the individuals most likely to adhere to them, allocating treatment resources on the basis of expected engagement. The major limitation of the current study is its lack of a control group; however, the changes we observed in the K6 and WHO-5 were of the same magnitude as in the large trial by Tol et al. (2020). An RCT is nonetheless warranted, because it is possible that the observed changes in symptoms and emotion regulation are attributable to the natural passage of time, placebo effects, or participant characteristics. Another limitation is that the sample consisted primarily of women. The formative work by the WHO regarding DWM also saw difficulty with recruiting men (Tol et al., 2020). Men are less likely to meet the criteria for internalizing distress than women, and large-scale studies suggest that even when men have internalizing distress, they are substantially less likely to seek treatment when compared to women (Rayner et al., 2021). In addition, non-Hispanic Black, Hispanic, Asian, and other racial–ethnic minority individuals were underrepresented relative to the general US population. Although these individuals were underrepresented in our sample, a meta-analysis by our group (De Jesús-Romero & Lorenzo-Luaces, 2002) suggests that these rates of representation of racial-ethnic diversity in our trial are consistent with other trials of digital interventions. Future work should explore how to increase the engagement of cisgender men and racial–ethnic minoritized individuals in GSH studies. Finally, we measured the acceptability of the intervention by using (1) self-rated usability, (2) self-rated satisfaction, and (3) compliance with the guidance. Thus, a limitation of the study is that we did not measure acceptability of the ACT-based content nor did we systematically address adherence or engagement with the GSH-CBT material (e.g., reading comprehension, percent of time practicing mindfulness). Several strengths of the study are worth discussing. First, we recruited individuals from all over the US to maximize generalizability. Additionally, we used very relaxed entry criteria to maximize the representativeness of our sample (Lorenzo-Luaces et al., 2018a, b). We measured a variety of outcomes including a transdiagnostic measure of mental health disorder symptoms, two features of emotion regulation, aspects of positive mental health functioning like well-being and functioning, and explicit assessments of participants’ perceptions of the usability of the intervention as well as their satisfaction with it. Almost all participants had moderate functional impairment, most met cut-off criteria for disorder screening in the various measures we used to characterize psychopathology, and about two thirds met the criterion for severe impairment on the WSAS. These results suggest we were able to recruit individuals with relatively severe clinical profiles. Interestingly, during the intervention, participants reported more change in cognitive reappraisal than in expressive suppression. Cognitive reappraisal is a basic emotion regulation strategy that is the equivalent of cognitive restructuring in CBT (Lorenzo-Luaces et al., 2015, 2016). In most forms of CBT, restructuring is a recommended way of reducing cognitive distortions to improve mood but is not formally addressed by DWM or ACT-based interventions except via distancing or defusion exercises. Expressive suppression is analogous to the idea of experiential avoidance in ACT and antithetical to acceptance (Hofmann & Asmundson, 2008). Thus, it was unexpected that suppression changed less than reappraisal. It may be that a more direct measure of ACT-relevant processes would capture change better than the ERQ. However, in the larger DWM trial by the WHO, improvement in an ACT-specific measure in DWM versus treatment as usual was relatively modest (d = 0.42; Tol et al., 2020) and not maintained over a follow-up period (d = 0.09). One possibility is that DWM may facilitate symptom change through processes other than those implied by the ACT model. Process-outcome research clarifying the association between changes in emotion regulation and changes in symptoms is needed, including exploration of alternative processes that may explain changes in DWM such as normalization of distress, working alliance, behavioral activation, or other potential mechanisms. The efficacy of GSH-CBT is well established relative to control conditions and, to some extent, relative to individual therapy (Cuijpers et al., 2019). The areas of uncertainty remaining in relation to GSH-CBT include its dissemination in real world settings, best staging practices for GSH-CBT relative to other treatments, identifying who engages and responds to these interventions, and isolating mechanisms though which these interventions achieve their effects. Supplementary Information Below is the link to the electronic supplementary material.Supplementaryfile1 (DOCX 48 kb) Author Contributions Conceptualization: LL-L, JH; Data curation: LL-L, JH, IS; Formal analysis: LL-L, IS; Funding acquisition: LL-L; Investigation: LL-L, JH, RDJ-R, AP, JB, CL, KB, IS; Methodology: LL-L; Project administration: LL-L, JH; Resources: LL-L; Software: LL-L, IS; Supervision: LL-L; Validation: LL-L; Visualization: LL-L; Writing—original draft: LL-L; Writing—review and editing: LL-L, JH, RDJ-R, AP, JB, CL, KB, IS. Funding This research was partially funded by the National Institute of Mental Health Grant Number T32 MH103213-06 which provided support for Peipert, De Jesús-Romero, Buss, and Starvaggi and Grant Numbers KL2TR002530 and UL1TR002529 (A. Shekhar, PI) from the National Institutes of Health, National Center for Advancing Translational Sciences, Clinical and Translational Sciences Award which provided support for Professor Lorenzo-Luaces. The work was also supported the 2020 Global Mental Health Fellowship through the APA and IUPsys. Declarations Conflict of Interest Professor Lorenzo-Luaces has received consulting fees from Happify Health, Inc. who had no role in the current research. Jacqueline Howard, Robinson De Jesús-Romero, Allison Peipert, John Buss, Colton Lind, Kassandra Botts Isabella Starvaggi declare that they have no conflict of interest. Research Involving Human Participants and/or Animals All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional and/or National Research Committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Indiana University IRB. Informed Consent Informed consent was obtained from all individual participants included in the study. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References Acarturk C Uygun E Ilkkursun Z Carswell K Tedeschi F Batu M Eskici S Kurt G Anttila M Au T Effectiveness of a WHO self-help psychological intervention for preventing mental disorders among Syrian refugees in Turkey: A randomized controlled trial World Psychiatry 2022 21 1 88 95 10.1002/wps.20939 35015365 Aldao A Nolen-Hoeksema S Specificity of cognitive emotion regulation strategies: A transdiagnostic examination Behaviour Research and Therapy 2010 48 10 974 983 10.1016/j.brat.2010.06.002 20591413 Allen JP Litten RZ Fertig JB Babor T A review of research on the Alcohol Use Disorders Identification Test (AUDIT) Alcoholism: Clinical and Experimental Research 1997 21 4 613 619 10.1111/j.1530-0277.1997.tb03811.x 9194913 American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders: DSM-5 (5th ed.). American Psychiatric Publishing. Arean PA Hallgren KA Jordan JT Gazzaley A Atkins DC Heagerty PJ Anguera JA The use and effectiveness of mobile apps for depression: Results from a fully remote clinical trial Journal of Medical Internet Research 2016 18 12 e6482 10.2196/jmir.6482 Bates, D., Kliegl, R., Vasishth, S., & Baayen, H. (2015). Parsimonious mixed models. arXiv Preprint arXiv:1506.04967 Batterham P Sunderland M Slade T Calear A Carragher N Assessing distress in the community: Psychometric properties and crosswalk comparison of eight measures of psychological distress Psychological Medicine 2018 48 8 1316 1324 10.1017/S0033291717002835 28967345 Baumeister H Reichler L Munzinger M Lin J The impact of guidance on Internet-based mental health interventions—A systematic review Internet Interventions 2014 1 4 205 215 10.1016/j.invent.2014.08.003 Brissette I Leventhal H Leventhal EA Observer ratings of health and sickness: Can other people tell us anything about our health that we don’t already know? Health Psychology 2003 22 5 471 10.1037/0278-6133.22.5.471 14570530 Brooke J SUS: A quick and dirty usability scale Usability Evaluation in Industry 1996 189 194 4 7 Bruijniks SJ Lemmens LH Hollon SD Peeters FP Cuijpers P Arntz A Dingemanse P Willems L Van Oppen P Twisk JW The effects of once- versus twice-weekly sessions on psychotherapy outcomes in depressed patients The British Journal of Psychiatry 2020 216 4 222 230 10.1192/bjp.2019.265 32029012 Bur OT Krieger T Moritz S Klein JP Berger T Optimizing the context of support of web-based self-help in individuals with mild to moderate depressive symptoms: A randomized full factorial trial Behaviour Research and Therapy 2022 152 104070 10.1016/j.brat.2022.104070 35306266 Cavanagh K Turn on, tune in and (don’t) drop out: Engagement, adherence, attrition, and alliance with Internet-based interventions Oxford Guide to Low Intensity CBT Interventions 2010 227 232 Cella D Choi SW Condon DM Schalet B Hays RD Rothrock NE Yount S Cook KF Gershon RC Amtmann D PROMIS adult health profiles: Efficient short-form measures of seven health domains Value in Health 2019 22 5 537 544 10.1016/j.jval.2019.02.004 31104731 Cella D Riley W Stone A Rothrock N Reeve B Yount S Amtmann D Bode R Buysse D Choi S The patient-reported outcomes measurement information system (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008 Journal of Clinical Epidemiology 2010 63 11 1179 1194 10.1016/j.jclinepi.2010.04.011 20685078 Cuijpers P Noma H Karyotaki E Cipriani A Furukawa TA Effectiveness and acceptability of cognitive behavior therapy delivery formats in adults with depression: A network meta-analysis JAMA Psychiatry 2019 76 7 700 707 10.1001/jamapsychiatry.2019.0268 30994877 De Jesús-Romero, R., & Lorenzo-Luaces, L. (2002). Representation of racial and ethnic diversity in clinical trials of Internet-based self-help treatments for depression. Presented at the 2022 Society of Consulting Psychology. De Jesús-Romero R Wasil A Lorenzo-Luaces L Willingness to use internet-based versus bibliotherapy interventions in a representative U.S. Sample: Cross-sectional survey study JMIR Formative Research 2022 6 8 e39508 10.2196/39508 36001373 de Meneses-Gaya C Zuardi AW Loureiro SR Crippa JAS Alcohol Use Disorders Identification Test (AUDIT): An updated systematic review of psychometric properties Psychology and Neuroscience 2009 2 1 83 10.3922/j.psns.2009.1.12 DeRubeis RJ Lorenzo-Luaces L Recognizing that truth is unattainable and attending to the most informative research evidence Psychotherapy Research 2017 27 1 33 35 10.1080/10503307.2016.1252072 27884096 Dolan N Simmonds-Buckley M Kellett S Siddell E Delgadillo J Effectiveness of stress control large group psychoeducation for anxiety and depression: Systematic review and meta-analysis British Journal of Clinical Psychology 2021 60 3 375 399 10.1111/bjc.12288 33822376 Faul F Erdfelder E Lang A-G Buchner A G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences Behavior Research Methods 2007 39 2 175 191 10.3758/BF03193146 17695343 Feingold A Effect sizes for growth-modeling analysis for controlled clinical trials in the same metric as for classical analysis Psychological Methods 2009 14 1 43 10.1037/a0014699 19271847 Flora DB Your coefficient alpha is probably wrong, but which coefficient omega is right? A tutorial on using r to obtain better reliability estimates Advances in Methods and Practices in Psychological Science 2020 3 4 484 501 10.1177/2515245920951747 Furukawa TA Suganuma A Ostinelli EG Andersson G Beevers CG Shumake J Berger T Boele FW Buntrock C Carlbring P Dismantling, optimising, and personalising Internet cognitive behavioural therapy for depression: A systematic review and component network meta-analysis using individual participant data The Lancet Psychiatry 2021 8 6 500 511 10.1016/S2215-0366(21)00077-8 33957075 Gross JJ John OP Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being Journal of Personality and Social Psychology 2003 85 2 348 10.1037/0022-3514.85.2.348 12916575 Hofmann SG Asmundson GJ Acceptance and mindfulness-based therapy: New wave or old hat? Clinical Psychology Review 2008 28 1 1 16 10.1016/j.cpr.2007.09.003 17904260 Hofmann SG Hayes SC The future of intervention science: Process-based therapy Clinical Psychological Science 2019 7 1 37 50 10.1177/2167702618772296 30713811 Hox, J. J. (2000). Multilevel analysis of grouped and longitudinal data. In Modeling longitudinal and multilevel data: Practical issues, applied approaches, and specific examples. Routledge. Jorm AF Patten SB Brugha TS Mojtabai R Has increased provision of treatment reduced the prevalence of common mental disorders? Review of the evidence from four countries World Psychiatry 2017 16 1 90 99 10.1002/wps.20388 28127925 Jylhä M What is self-rated health and why does it predict mortality? Towards a unified conceptual model Social Science and Medicine 2009 69 3 307 316 10.1016/j.socscimed.2009.05.013 19520474 Karyotaki E Kleiboer A Smit F Turner DT Pastor AM Andersson G Berger T Botella C Breton J Carlbring P Predictors of treatment dropout in self-guided web-based interventions for depression: An ‘individual patient data’ meta-analysis Psychological Medicine 2015 45 13 2717 2726 10.1017/S0033291715000665 25881626 Kazdin AE Blase SL Rebooting psychotherapy research and practice to reduce the burden of mental illness Perspectives on Psychological Science 2011 6 1 21 37 10.1177/1745691610393527 26162113 Kenward MG Molenberghs G Last observation carried forward: A crystal ball? Journal of Biopharmaceutical Statistics 2009 19 5 872 888 10.1080/10543400903105406 20183449 Kessler RC Andrews G Colpe LJ Hiripi E Mroczek DK Normand S-L Walters EE Zaslavsky AM Short screening scales to monitor population prevalences and trends in non-specific psychological distress Psychological Medicine 2002 32 6 959 976 10.1017/S0033291702006074 12214795 Kessler RC Van Loo H Wardenaar K Bossarte R Brenner L Ebert D de Jonge P Nierenberg A Rosellini A Sampson N Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder Epidemiology and Psychiatric Sciences 2017 26 1 22 36 10.1017/S2045796016000020 26810628 Kohn, M. A., & Senyak, J. (2021, December 20). Sample size calculators. UCSF CTSI. Retrieved December 28, 2021, from https://www.sample-size.net/ Kotov R Krueger RF Watson D Achenbach TM Althoff RR Bagby RM Brown TA Carpenter WT Caspi A Clark LA The hierarchical taxonomy of psychopathology (HiTOP): A dimensional alternative to traditional nosologies Journal of Abnormal Psychology 2017 126 4 454 10.1037/abn0000258 28333488 Krendl AC Lorenzo-Luaces L Identifying peaks in attrition after clients initiate mental health treatment in a university training clinic Psychological Services 2021 19 519 526 10.1037/ser0000469 34166028 Kuznetsova A Brockhoff PB Christensen RH lmerTest package: Tests in linear mixed effects models Journal of Statistical Software 2017 82 1 26 10.18637/jss.v082.i13 Lachin JM Fallacies of last observation carried forward analyses Clinical Trials 2016 13 2 161 168 10.1177/1740774515602688 26400875 Lewis JR The system usability scale: Past, present, and future International Journal of Human–Computer Interaction 2018 34 7 577 590 10.1080/10447318.2018.1455307 Lorenzo-Luaces L The evidence for cognitive behavioral therapy JAMA 2018 319 8 831 832 10.1001/jama.2017.20826 29486024 Lorenzo-Luaces L Amsterdam JD Effects of venlafaxine versus lithium monotherapy on quality of life in bipolar II major depressive disorder: Findings from a double-blind randomized controlled trial Psychiatry Research 2018 259 455 459 10.1016/j.psychres.2017.11.025 29136600 Lorenzo-Luaces L DeRubeis RJ van Straten A Tiemens B A prognostic index (PI) as a moderator of outcomes in the treatment of depression: A proof of concept combining multiple variables to inform risk-stratified stepped care models Journal of Affective Disorders 2017 213 78 85 10.1016/j.jad.2017.02.010 28199892 Lorenzo-Luaces L German RE DeRubeis RJ It’s complicated: The relation between cognitive change procedures, cognitive change, and symptom change in cognitive therapy for depression Clinical Psychology Review 2015 41 3 15 10.1016/j.cpr.2014.12.003 25595660 Lorenzo-Luaces L Johns E Keefe JR The generalizability of randomized controlled trials of self-guided Internet-based cognitive behavioral therapy for depressive symptoms: Systematic review and meta-regression analysis Journal of Medical Internet Research 2018 20 11 e10113 10.2196/10113 30413400 Lorenzo-Luaces L Keefe JR DeRubeis RJ Cognitive–behavioral therapy: Nature and relation to non-cognitive behavioral therapy Behavior Therapy 2016 47 6 785 803 10.1016/j.beth.2016.02.012 27993333 Lorenzo-Luaces, L., Lemmens, L. H., Keefe, J. R., Cuijpers, P., & Bockting, C. L. (2021a). The efficacy of cognitive behavioral therapy for emotional disorders. In Handbook of cognitive behavioral therapy: Overview and approaches (Vol. 1, pp. 51–89). American Psychological Association. Lorenzo-Luaces L Peipert A Romero De Jesús R Rutter LA Rodriguez-Quintana N Personalized medicine and cognitive behavioral therapies for depression: Small effects, big problems, and bigger data International Journal of Cognitive Therapy 2021 14 1 59 85 10.1007/s41811-020-00094-3 Lorenzo-Luaces L Rodriguez-Quintana N Riley TN Weisz JR A placebo prognostic index (PI) as a moderator of outcomes in the treatment of adolescent depression: Could it inform risk-stratification in treatment with cognitive–behavioral therapy, fluoxetine, or their combination? Psychotherapy Research 2020 31 1 5 18 10.1080/10503307.2020.1747657 32223373 Lorenzo-Luaces L Zimmerman M Cuijpers P Are studies of psychotherapies for depression more or less generalizable than studies of antidepressants? Journal of Affective Disorders 2018 234 8 13 10.1016/j.jad.2018.02.066 29522947 Löwe B Schulz U Gräfe K Wilke S Medical patients’ attitudes toward emotional problems and their treatment Journal of General Internal Medicine 2006 21 1 39 45 10.1111/j.1525-1497.2005.0266.x 16423121 Martinez R Whitfield G Dafters R Williams C Can people read self-help manuals for depression? A challenge for the stepped care model and book prescription schemes Behavioural and Cognitive Psychotherapy 2008 36 1 89 97 10.1017/S1352465807004067 McHugh RK Whitton SW Peckham AD Welge JA Otto MW Patient preference for psychological vs pharmacologic treatment of psychiatric disorders: A meta-analytic review The Journal of Clinical Psychiatry 2013 74 6 13979 10.4088/JCP.12r07757 Michie S Van Stralen MM West R The behaviour change wheel: A new method for characterising and designing behaviour change interventions Implementation Science 2011 6 1 1 12 10.1186/1748-5908-6-42 21208425 Mundt JC Marks IM Shear MK Greist JM The Work and Social Adjustment Scale: A simple measure of impairment in functioning The British Journal of Psychiatry 2002 180 5 461 464 10.1192/bjp.180.5.461 11983645 Peipert A Krendl AC Lorenzo-Luaces L Waiting lists for psychotherapy and provider attitudes toward low-intensity treatments as potential interventions: Survey study JMIR Formative Research 2022 6 9 e39787 10.2196/39787 36112400 Peipert A Rodriguez-Quintana N Lorenzo-Luaces L Outcomes of student trainee-delivered cognitive behavioral therapy (CBT) on internalizing symptoms, CBT skills, and life satisfaction International Journal of Cognitive Therapy 2022 15 1 94 113 10.1007/s41811-022-00131-3 36211599 Pilkonis PA Yu L Dodds NE Johnston KL Maihoefer CC Lawrence SM Validation of the depression item bank from the patient-reported outcomes measurement information system (PROMIS) in a three-month observational study Journal of Psychiatric Research 2014 56 112 119 10.1016/j.jpsychires.2014.05.010 24931848 Posner, K., Brent, D., Lucas, C., Gould, M., Stanley, B., Brown, G., Fisher, P., Zelazny, J., Burke, A., Oquendo, M., et al. (2008). Columbia Suicide Severity Rating Scale (C-SSRS) (p. 10). Columbia University Medical Center. Preece DA Becerra R Hasking P McEvoy PM Boyes M Sauer-Zavala S Chen W Gross JJ The Emotion Regulation Questionnaire: Psychometric properties and relations with affective symptoms in a United States general community sample Journal of Affective Disorders 2021 284 27 30 10.1016/j.jad.2021.01.071 33582429 Preece DA Becerra R Robinson K Gross JJ The Emotion Regulation Questionnaire: Psychometric properties in general community samples Journal of Personality Assessment 2019 102 3 348 356 10.1080/00223891.2018.1564319 30714818 Purgato M Carswell K Tedeschi F Acarturk C Anttila M Au T Bajbouj M Baumgartner J Biondi M Churchill R Effectiveness of self-help plus in preventing mental disorders in refugees and asylum seekers in Western Europe: A multinational randomized controlled trial Psychotherapy and Psychosomatics 2021 90 6 403 414 10.1159/000517504 34350902 Rayner C Coleman JR Purves KL Carr E Cheesman R Davies MR Delgadillo J Hübel C Krebs G Peel AJ Sociodemographic factors associated with treatment-seeking and treatment receipt: Cross-sectional analysis of UK Biobank participants with lifetime generalised anxiety or major depressive disorder BJPsych Open 2021 7 6 e216 10.1192/bjo.2021.1012 R Core Team. (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing. Revelle W How to: Use the psych package for factor analysis and data reduction 2016 Northwestern University Schleider JL Weisz JR Little treatments, promising effects? Meta-analysis of single-session interventions for youth psychiatric problems Journal of the American Academy of Child and Adolescent Psychiatry 2017 56 2 107 115 10.1016/j.jaac.2016.11.007 28117056 Staples LG Dear BF Gandy M Fogliati V Fogliati R Karin E Nielssen O Titov N Psychometric properties and clinical utility of brief measures of depression, anxiety, and general distress: The PHQ-2, GAD-2, and K-6 General Hospital Psychiatry 2019 56 13 18 10.1016/j.genhosppsych.2018.11.003 30508772 Steegen S Tuerlinckx F Gelman A Vanpaemel W Increasing transparency through a multiverse analysis Perspectives on Psychological Science 2016 11 5 702 712 10.1177/1745691616658637 27694465 Stekhoven DJ Bühlmann P MissForest—Non-parametric missing value imputation for mixed-type data Bioinformatics 2012 28 1 112 118 10.1093/bioinformatics/btr597 22039212 Swift JK Greenberg RP Tompkins KA Parkin SR Treatment refusal and premature termination in psychotherapy, pharmacotherapy, and their combination: A meta-analysis of head-to-head comparisons Psychotherapy 2017 54 1 47 10.1037/pst0000104 28263651 Tol WA Augustinavicius J Carswell K Brown F Adaku A Leku M García-Moreno C Ventevogel P White R Van Ommeren M Translation, adaptation, and pilot of a guided self-help intervention to reduce psychological distress in South Sudanese refugees in Uganda Global Mental Health 2018 5 e25 10.1017/gmh.2018.14 30128161 Tol WA Augustinavicius J Carswell K Leku MR Adaku A Brown FL García-Moreno C Ventevogel P White RG Kogan CS Feasibility of a guided self-help intervention to reduce psychological distress in South Sudanese refugee women in Uganda World Psychiatry 2018 17 2 234 10.1002/wps.20537 29856552 Tol WA Leku MR Lakin DP Carswell K Augustinavicius J Adaku A Au TM Brown FL Bryant RA Garcia-Moreno C Guided self-help to reduce psychological distress in South Sudanese female refugees in Uganda: A cluster randomised trial The Lancet Global Health 2020 8 2 e254 e263 10.1016/S2214-109X(19)30504-2 31981556 Topp CW Østergaard SD Søndergaard S Bech P The WHO-5 Well-Being Index: A systematic review of the literature Psychotherapy and Psychosomatics 2015 84 3 167 176 10.1159/000376585 25831962 Van Ballegooijen W Cuijpers P Van Straten A Karyotaki E Andersson G Smit JH Riper H Adherence to Internet-based and face-to-face cognitive behavioural therapy for depression: A meta-analysis PLoS ONE 2014 9 7 e100674 10.1371/journal.pone.0100674 25029507 van Ginkel JR Linting M Rippe RC van der Voort A Rebutting existing misconceptions about multiple imputation as a method for handling missing data Journal of Personality Assessment 2020 102 3 297 308 10.1080/00223891.2018.1530680 30657714 Wasil AR Gillespie S Patel R Petre A Venturo-Conerly KE Shingleton RM Weisz JR DeRubeis RJ Reassessing evidence-based content in popular smartphone apps for depression and anxiety: Developing and applying user-adjusted analyses Journal of Consulting and Clinical Psychology 2020 88 11 983 993 10.1037/ccp0000604 32881542 Wasil AR Gillespie S Schell T Lorenzo-Luaces L DeRubeis RJ Estimating the real-world usage of mobile apps for mental health: Development and application of two novel metrics World Psychiatry 2021 20 1 137 10.1002/wps.20827 33432761 Wasil AR Palermo E Lorenzo-Luaces L DeRubeis R Is there an app for that? An overview of popular mental health and wellness apps Cognitive Behavioural Practice 2021 10.31234/osf.io/su4ar Wasil AR Taylor ME Franzen RE Steinberg JS DeRubeis RJ Promoting graduate student mental health during COVID-19: Acceptability, feasibility, and perceived utility of an online single-session intervention Frontiers in Psychology 2021 12 1167 10.3389/fpsyg.2021.569785 Whiteford HA Degenhardt L Rehm J Baxter AJ Ferrari AJ Erskine HE Charlson FJ Norman RE Flaxman AD Johns N Global burden of disease attributable to mental and substance use disorders: Findings from the Global Burden of Disease Study 2010 The Lancet 2013 382 9904 1575 1586 10.1016/S0140-6736(13)61611-6 Wolf MM Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart Journal of Applied Behavior Analysis 1978 11 2 203 214 10.1901/jaba.1978.11-203 16795590 Zahra D Qureshi A Henley W Taylor R Quinn C Pooler J Hardy G Newbold A Byng R The Work and Social Adjustment Scale: Reliability, sensitivity and value International Journal of Psychiatry in Clinical Practice 2014 18 2 131 138 10.3109/13651501.2014.894072 24527886
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==== Front OPSEARCH OPSEARCH 0030-3887 0975-0320 Springer India New Delhi 619 10.1007/s12597-022-00619-8 Application Article Estimating the hospitality efficiency in Mexico using Data Envelopment Analysis http://orcid.org/0000-0002-9944-8475 Flegl Martin [email protected] 1 http://orcid.org/0000-0002-2942-8153 Cerón-Monroy Hazael 2 http://orcid.org/0000-0003-2723-7289 Krejčí Igor 3 http://orcid.org/0000-0003-0606-354X Jablonský Josef 4 1 grid.419886.a 0000 0001 2203 4701 School of Engineering and Sciences, Tecnologico de Monterrey, Calle del Puente #222, 14380 Mexico City, Mexico 2 grid.418275.d 0000 0001 2165 8782 Mexico Anahuac University, Instituto Politecnico Nacional, Mexico City, Mexico 3 grid.15866.3c 0000 0001 2238 631X Faculty of Economics and Management, Czech University of Life Sciences Prague, Prague, Czech Republic 4 grid.266283.b 0000 0001 1956 7785 Faculty of Informatics and Statistics, Prague University of Economics and Business, Prague, Czech Republic 12 12 2022 129 26 11 2022 © The Author(s), under exclusive licence to Operational Research Society of India 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Tourism has been an important source of income and employment for Mexico, and the economic numbers generated by the tourism have been increasing during last 2 decades. However, the question is how much more tourism capacity can Mexico offer? Therefore, it is necessary to search areas with lower hospitality performance to secure tourism growth and create adequate decision-making strategies. In this article, we constructed Data Envelopment Analysis model to estimate the hospitality efficiency of 32 Mexican states during a period from 1992 to 2018. Such a long period creates a unique insight of Mexican tourism. The results revealed high efficiency regarding national tourism, whereas the efficiency is low with respect to international tourism. This may not be unconnected with the fact that international tourism is centered in coastal states, whereas national tourism is mainly located in the in-land states. Such differences create opportunities to target better marketing strategies from the Mexican government. Keywords Data Envelopment Analysis Development strategy Mexico Tourism Window analysis ==== Body pmcIntroduction Tourism generated US$1482 billion in 2019 [1], representing 10.3% of global GDP, 6.8% of global exports, and 28.3% of global services exports [2]. Its direct impact also accounted for 330 million employments and US$948 billion capital investment (4.8% of total investment) [2]. During 2019, international tourist arrivals registered 1460 million worldwide, 14.7% of visits to the Americas [1]. In this context, Mexico counted 45 million international tourists and US$24.5 billion in international tourism arrivals, ranking 7th and 16th places respectively among countries in the world [3]. Tourism is an activity that is preferably measured by the number of national and international tourists who arrive at a certain destination. However, these arrivals are influenced by various aspects that limit or drive them. One of the most important driving factors in the tourism industry is the reputation of each tourist destination. According to Coelho and Gosling [4], the reputation of a touristic destination is influenced by four main factors: (1) communication (social media, internet, touristic guides), (2) individual consumers’ evaluations, (3) local specific experiences, and (4) time that creates reputation over a longer period. Tourist arrivals can also be influenced by dangerous situations that negatively affect the perception of tourist destinations. Sánchez Mendoza [5] points out that the proximity of these violent or dangerous events for tourists determines the perception of fear of a threat or danger. The tourism industry includes different economic sub-sectors considered as characteristic activities like hospitality (accommodation services for visitors), transportation, food and beverage serving activities, travel agencies and other reservation services activities, cultural activities and sports and recreational activities [6]. Hospitality sector equals to 3.7% of the global GDP, which also represents 35.9% of the global touristic GDP [2]. In Mexico, the hospitality sector represents 2.5% of the total GDP and 29.2% of the total tourism GDP in the country [7]. In Mexico, during the last two decades, the arrival of national and international tourists has increased, as well as the offer of services. The GDP of hospitality went from US$ 16.084 constant (2013 = 100) billion in 1992 to US$ 20.284 constant (2013 = 100) billion in 2018, i.e., a growth of 28% during that period [8]. Employment in the hospitality sector grew by 33.8% from 148,713 people in 1993 to 198,977 in 2018 [8]. Similarly, the arrival of national tourists in hotel rooms grew from 7.4 to 27.1 million, while the arrival of international tourists grew from 34.7 to 100.4 million in the same period [9]. Hospitality infrastructure can be measured as the number of disposable rooms. Mexico has approximately 23,700 hotels, with an average of 646,304 available rooms daily in 2019, while in 1992, it was only 275,441. In 2019, 10 out of 32 Mexican states concentrated around 53% of all the hotels and 57% of hotel rooms in Mexico [9]. Although tourism generates significant revenues, a large percentage of these revenues is sent to the hotels’ international investors or gained by the local rich individuals, but only a few revenues belong to poor neighbours [10]. Therefore, it is important for the government to optimize resource allocation to tourism development, i.e., to foster tourism activities. Hospitality efficiency is an important aspect of tourism research. The level of contribution of the hospitality industry depends on the production factors acting efficiently to improve profitability and market position [11], and in the case of Mexico to increase the number of tourists in the states of the country. The technical efficiency of hospitality is a comparative measure of how effectively it processes inputs to produce outputs in relation to its production possibility frontier, which represents its maximum potential for doing so. Technically, a hospitality unit can be ineffective if it operates below the boundary [12]. Efficiency in the hospitality industry must be based on the identification of new markets and products. Alberca and Parte [13] suggested that hotels should diversify their offerings according to the market, because tourist demand is based on more differentiated needs and expectations. Through this strategy, hotels can reach higher levels of efficiency since their demand will not be linked to specific seasons. Cázarez and Schütze [14] demonstrated that hotel organizations that use information obtained from online social networks to develop new products or services to reach new markets are increasing their efficiency. As most of the countries all around the world are affected by the Covid-19 pandemic situation, it is crucial to search for policies of how to rescue the touristic industry. In this light, Mexico was identified among the 13 most vulnerable countries according to the tourism industry post-pandemic recovery, due to its orientation on international travellers and a high presence of tourism in the national economy [15]. The current situation is represented by the lack of economic resources due to the closure of economic activities in many countries. That is why governments must effectively use their resources and target their support effectively. Therefore, it is important to apply advanced tools to determine leverage points for their policies. The article's objective consists of evaluating the efficiency of the hospitality industry in the 32 states of Mexico. To have a complex view, the analysis is based on the infrastructure (number of rooms available) each of the states has, the arrival of national and international tourists, and their length of stay for 1992–2018. This longitudinal analysis enables us to obtain a precise picture of tourism development in Mexico and its regions. Efficiency and performance analysis in tourism Efficiency in tourism is an important indicator for measuring the level and quality of tourism development. That is why such analyses have attracted considerable research attention. Many quantitative and statistical methods can be applied to evaluate the efficiency and performance in tourism. For the benchmarking techniques, the frontier analysis has become the most noteworthy approach in the tourism and hospitality literature. Data Envelopment Analysis (DEA) is a non-parametric modeling technique that belongs to the most often used methods for assessing the efficiency and performance of the set of decision making [16, 17] with successful applications in various industries. De La Hoz et al. [18] evaluated academic efficiency of 256 engineering programs at Colombian universities. Flegl et al. [19] applied DEA to observe the production and investment efficiency of 1672 municipalities in the Mexican food industry. Chopra and Ramachandran [20] used DEA model to analyze water sector performance in 11 states in India. Linh Le et al. [21] investigated the total factor productivity growth and environmental efficiency of the agricultural sector in East Asian countries for the period from 2002 to 2010. Jablonsky [22] assessed countries’ performance at the 2016 Summer Olympic Games with respect to the resources each country can spent. Vikas and Bansal [23] evaluated efficiency of 22 Indian oil and gas sector during 2013–2017 period. In tourism, the DEA has been applied to evaluate regional differences, the efficiency of the hotel industry, or to determine the influential factors in the tourism industry [24]. At the hospitality level, summarized in Table 1, Oliveira et al. [25] analyzed the impact of hotel quality (star rating) on the efficiency of 84 hotels in the Algarve, Portugal. Barros et al. [26] used the DEA to estimate the efficiency of operational activities of 15 Portuguese hotel groups. Hathroubi et al. [27] evaluated performance of 42 Tunisian hotels considering their environmental managerial practices to enhance their competitiveness. Higuerey et al. [11] measure efficiency and productivity of 147 hotels in Ecuador considering their quality and geographical location.Table 1 A review of the literature on efficiency and performance assessment in tourism using DEA Authors DMUs Period Inputs Outputs Barros et al. [26] 15 Hotel groups, Portugal 1998–2005 Full-time workers; book value of property; Operational costs Sales; number of guests Castilho et al. [35] 22 Countries, Latin America and Caribbean 1995–2016 CO2 emissions; GDP; Corne [28] 16 Conurbations, France 2013 Uniform value of 1 Occupancy rate; revenue per available room Hathroubi et al. [27] 42 Thotels, Tunisia 2010 Number of hotel stars; Cleaning personnel; Service personnel; Management personnel; Number of rooms; Number of beds Arrivals; nights slept Higuerey et al. [11] 147 Hotels, Ecuador 2013–2017 Total personnel; Non-current assets; Consumption Revenue Huang et al. [65] 31 Forest parks provinces, China 2009–2018 Tour guide; Staff Tourists; tourism revenue; social tourism employment Liu et al. [29] 53 Coastal cities, China 2003–2013 Tourism wastewater discharge; Tourism exhaust emissions; Tourism solid waste emissions; Nearshore seawater quality Tourism energy consumption; total tourism revenue; total number of tourists Niavis and Tsiotas [36] 37 Coastal regions, Mediterranean 2015–2017 Bed capacity; Attractions capacity; Beaches capacity; Labor capacity Total demand Oliveira et al. [25] 84 Hotels, Algarve, Portugal 2005–2007 Number of rooms; Number of employees; Food & beverage capacity; Other costs Total revenue Oukil et al. [33] 58 Hotels, Oman 2013 Number of beds; Salary of employees Annual revenue; number of guests; number of nights; occupancy rate Song and Li [31] 31 Provinces, China 2011–2016 Fixed assets investment; Employment figures; Number of scenic spots; Environmental governance investment Total tourists received; revenue of tourism enterprises Wang et al. [32] 30 Provinces, China 2011–2016 Number of tourism industry’s employees; Number of travel agencies; Number of star-rated hotels; Number of A-class scenic spots Tourism arrival; tourist receipt At the national and regional level, Corne [28] applied Data Envelopment Analysis to analyze efficiency in the French hospitality sector in 16 conurbations to identify possible improvement in the sector. Similarly, Liu et al. [29] evaluated the efficiency of 53 Chinese coastal cities from 2003 to 2013 to explore regional differences, whereas Chaabouni [30] investigated the tourism efficiency and its determinants in 31 provinces in China over the period 2008–2013. Song and Li [31] estimated the efficiency of the Chinese tourism industry from the sustainability point of view to increase tourist attraction, whereas Wang et al. [32] used a super-DEA model to evaluate the tourism efficiency of 30 provinces in China. Furthermore, Oukil et al. [33] applied DEA methodology to examine efficiency in the hotel industry in Oman to identify variables explaining inefficiency in the industry. Flegl et al. [34] analyzed the hospitality efficiency in 67 main touristic centers in Mexico regarding national and international tourism. Castilho et al. [35] observed the impact of tourism on the eco-efficiency of 22 Latin American and Caribbean countries, and Niavis and Tsiotas [36] used the DEA to evaluate the performance of 37 Mediterranean regions. Efficiency and performance analysis in Mexican tourism Nurmatov et al. [24] observed that the DEA applications in tourism are mainly concentrated in Europe and Asia regions, with negligible attention in Latin America. Up to our knowledge, the DEA analysis has been very little used to assess the efficiency and performance in Mexican tourism (Table 2). Camacho [37] used the DEA to determine the efficiency of 81 touristic destinations in attracting domestic and foreign tourists during the period 2000–2010. Cázares and Schütze [14] applied the DEA method to measure the online social network efficiency and their effect on new tourism products in Mazatlán, México. The analysis of the hospitality efficiency in 67 touristic centres made by Flegl et al. [34] found significant differences between foreign and national tourism efficiency. Finally, Kido-Cruz et al. [38] analyzed the technical efficiency of 59 Mexican municipalities and its impact on the poverty index. They concluded that these two variables are unrelated.Table 2 A review of the literature on efficiency and performance assessment in tourism using DEA in Mexico Authors DMUs Period Inputs Outputs Camacho [37] 3 Groups of destinations 81 touristic destinations, Mexico 2000–2010 Number of temporary accommodation rooms; number food and beverages enterprises Number of national tourists; number of foreign tourists Cázares and Schütze [14] 13 Hotels in Mazatlán México 2012–2013 Online social network Number of new products Flegl et al. [34] 67 Touristic centers, Mexico 1992–2017 Number of one, two, three, four and five-star hotel rooms Tourists’ nights Kido-Cruz et al. [38] 59 Touristic municipalities, Mexico 2005 Number of available hotel rooms Occupancy rooms; number of tourists staying in hotel; average stay Materials and methods Data Envelopment Analysis Data Envelopment Analysis (DEA) allows to evaluate the set of homogeneous decision-making units (DMU) regarding their capabilities to convert multiple inputs into multiple outputs [39]. Each DMU consumes m different inputs to produce s different outputs. The development of the DEA model theory started with the pioneering work [40]. The model formulated in their paper assumes constant returns to scale production technology. It is further referenced as CCR model. The linearized version of the CCR output-oriented model for the evaluation of the DMU0 is formulated as follows: Minimize1 q=∑i=1mvixi0 subject to2 ∑i=1mvixij-∑r=1sμryrj≥0,j=1,2,…,n.∑r=1sμryr0=1,μr,vi≥ε where xij is the quantity of the input i of the DMUj, yrj is the amount of the output r of the DMUj, and μr and vi are the weights (multipliers) of the inputs and outputs, and ε is a non-Archimedean constant necessary to eliminate zero weights of the inputs and outputs. DMU0 is efficient if q=1, i.e., there is no other DMU that produces more outputs with the same combination of inputs. Whereas DMU is inefficient if q>1. Window analysis To measure DMUs productivity over a longer period, the Windows Analysis (WA) approach can be used. This approach works on the principle of moving averages to detect DMUs performance trends over time [41]. The performance of a DMU in a particular period is compared to its performance in other periods, in addition to the performance of other DMUs. Therefore, there is n.k DMU in each window, where n is the number of DMUs in a given period (it must be the same in all periods) and k is the width of each window (same for all windows). This feature increases the discriminatory capacity of the DEA model, as the total number of T periods is divided into series of overlapped periods (windows), each with a width kk<T leading to n.k DMUs. The first window has n.k DMUs for periods 1,⋯,k, the second period has n.k DMUs and periods 2,⋯,k+1, and so on, until the last window has n.k DMUs and periods T-k+1,⋯,T. In total, there are T-k+1 separate analyses where each analysis examines n.k DMUs. An important factor is the determination of the size of the window. If the window is too narrow, there may not be enough DMUs which leads to a low power of model discrimination. Conversely, a too wide window can yield misleading results due to significant changes occurring during periods covered by each window [39]. Therefore, the size of the window should consider the structure of the DEA model and the characteristics of the analysed area. The attractivity of a tourist destination can be significantly affected by negative reports by the media [4, 42]. The negative reputation reported by media can be linked to international conflicts, acts of terrorism, criminality, natural disasters or health concerns. There is no consensus about the length of the recovery time from each reported case. This recovery can range from several months to several years depending on the magnitude of each incident and the tourist’s personality type [43]. To minimize the effects of short-term negative events that would cause high volatility in the results obtained, the length of the window was selected as k=24 (two-year window). Data For the analysis, we used data from the DATATUR database (Secretariat of Tourism, 2018). Monthly data related to hospitality activities of 32 Mexican states were collected for the period from 1992 to 2018 (i.e., 27 years or 324 months). According to Lee et al. [44] and Oliani et al. [45], the quality and capacity of hotels’ infrastructure (among others) play an important role in tourism. However, the quality of hospitality service and establishments are rarely used in the tourism analyses [24]. The star rating is commonly used to express the level of hotel quality [25, 28]. Therefore, to include the quality and capacity of the hospitality service in each state, we selected the following variables as the inputs of the DEA model: Number of one-star hotel rooms, number of two-star hotel rooms, number of three-star hotel rooms, number of four-star hotels room, and number of five-star hotel rooms. So, the increase of the inputs does not necessarily correspond with the investment as the construction of the one-star hotel room represents significantly lower costs in comparison with the higher quality rooms. Higher efficiency could represent the proper mix of rooms, which would fit the demand of the tourist for the specific region. The objective of the hospitality sector is usually to maximize the occupancy rate and, consequently, their revenues. That is why the DEA analysis usually includes occupancy rate, tourists’ arrivals, and related revenues per available room as outputs [27–30]. However, the absolute number of tourists’ arrivals and the occupancy rate avoid reflecting the number of nights tourists stay in each destination. Instead, the output part of the constructed DEA model is represented by tourists’ nights (TN), which can be expressed as3 TN=tourists'arrivals*averagenumberofnights. Including the average number of nights each tourist stays in the model corresponds to the approach presented by Oukil et al. [33] or Hathroubi et al. [27]. The complete dataset is available in Flegl and Cerón-Monroy [46]. Tourism is an activity that is characterized by having months with a greater influx for reasons of already established holiday periods and climatic issues. Therefore, it is necessary to make a seasonal adjustment that eliminates the fluctuation that obscures the trend-cycle component of the series as much as possible [47]. The moving averages is the seasonal adjustment method used in this article. It consists in estimating coefficients that capture the difference between the real value of each month and the 12-month average value around the real value, i.e., 6 months ago and 6 months ahead. Each monthly observation has an adjustment coefficient which must be averaged with all the coefficients of all the years to have a single seasonal adjustment factor (Fi) for each month throughout the study period.Fi=∑j=1nfj(RV1/∑i=112RV-6,-5,⋯-1.RV+1,..+6/12n where Fi = Seasonality month factor, fj = seasonality month factor per year, i = month, j = year, RV = Real value. Models Three different models were constructed: (1) overall model, where the output side of the DEA model includes the total number of tourists; (2) international model, which only includes data for the international tourists’ arrivals to Mexico; and (3) national model, which includes data for the national tourists’ arrivals. The advantage of the DEA methodology is the possibility of benchmarking DMUs of different sizes and locations if the homogeneity requirement is not violated [39, 48]. Although we evaluate Mexican states of different sizes and locations, the homogeneity is not violated as all operate on the same market (Mexico) and use the same type of inputs (technology). This consideration is alike to Chaabouni [30], who applied DEA to investigate the tourism efficiency of Chinese provinces, Corne [28] and the analysis of the French administrative departments or Liu et al. [29], who assessed the eco-efficiency of Chinese coastal cities. Considering the operation of the Window Analysis method, 768 DMUs were available in each window, resulting in 20,736 analyses in total (n=32 states, k=24 width of the window, 27 years). This ensured sufficient discriminatory ability of the model [48]. Further, the output-oriented DEA model was used as the analysis aims to provide the optimal number of arrivals (TN) rather than to optimize the inputs structure of the model in each state. First, obtaining information about a target TN can be useful for decision-making strategies in attracting more tourists. Second, cutting the overall capacity (i.e., closing hotels) will likely lead to only short-term efficiency improvements, as the states may lack the capacity in the future. Finally, the CCR model was selected because we do not consider competition among the 32 Mexican states, as the Mexican Secretary of Tourism (SECTUR) develop economic activities in each state to encourage tourism to be competitive at a national and international level. Results The DEA model allows the maximum output to be set in a virtual way with the corresponding input. In this case, if the states of Mexico have an average number of rooms available per day and receive a greater flow of tourists, they will be efficient, otherwise, they will be inefficient. Table 6 presents the data for 1992 and 2018 of the inputs and outputs by state. We can observe that the available rooms grew by 130%, national tourists by 189% and international tourists by 265% between these two periods. There are significant differences in the growth rates among the states, as well as there are several states (Colima, Durango, Guerrero, Michoacán, and Oaxaca) with a negative rate in the case of international tourists. With the data for the selected period, the efficiency levels are highlighted considering the model, that is, with the total number of tourists. Subsequently, the results are presented for the arrival of national tourists and the arrival of international tourists. Overall model The average overall efficiency of the hospitality sector in Mexico during the period 1992–2018 was 65.02% with a standard deviation (SD) of 12.98%, where 17 states were evaluated above the average (Table 3). The best evaluated state is Quintana Roo with an average efficiency of 88.25% (SD 8.19%), followed by Sonora (74.71%, SD 10.99%), Colima (74.41%, SD 12.52%), Puebla (74.09%, SD 12.19%) and Coahuila (73.54%, SD 17.72%). Contrary, the lowest efficiency of the hospitality sector is observed in Estado de México (51.29%, SD 10.32%), Baja California (52.61%, SD 11.25%), Aguascalientes (55.60%, SD 10.12%), Morelos (56.60%, SD 15.13%) and Veracruz (57.57%, SD 11.45%).Table 3 Hospitality efficiency of Mexican states, overall model 1992–2018 State Efficiency Rank State Efficiency Rank State Efficiency Rank Aguascalientes 55.60% 30 Guanajuato 58.52% 26 Quintana Roo 88.25% 1 Baja California 52.61% 31 Guerrero 64.25% 17 San Luis Potosí 62.83% 18 Baja California Sur 68.03% 12 Hidalgo 72.04% 6 Sinaloa 69.44% 10 Campeche 71.56% 7 Jalisco 60.18% 23 Sonora 74.71% 2 Chiapas 67.49% 13 Michoacán 70.13% 9 Tabasco 61.77% 21 Chihuahua 66.14% 14 Morelos 56.60% 29 Tamaulipas 71.14% 8 Ciudad de México 65.65% 15 Nayarit 62.59% 19 Tlaxcala 61.90% 20 Coahuila 73.54% 5 Nuevo León 59.13% 24 Veracruz 57.57% 28 Colima 74.41% 3 Oaxaca 65.45% 16 Yucatán 59.09% 25 Durango 61.55% 22 Puebla 74.09% 4 Zacatecas 69.39% 11 Estado de México 51.29% 32 Querétaro 57.89% 27 MEXICO 65.02% – Figure 1 displays the evolution of the efficiency throughout the whole period. We can observe an initial drop in the overall efficiency during the year 1995, where the average efficiency from March to November in the entire Mexico was 61.20%, compared to the same period in 1994 with the efficiency of 71.53%. After the recovery of the hospitality sector in 1996 and 1997, the efficiency of the whole sector had a decreasing tendency during the following decade. At the end of this decade, the hospitality sector had an average efficiency of 54.41% from January 2005 to December 2006 (the lowest efficiency was recorded in April 2005 of 47.86%). After this period, the sector recovered during the following year, with the peak in March of 2008 (77.89%). The following decade presented a slight constant decrease, followed by a slight growth in the last year 2018. During this decade, the results indicate a significant drop in efficiency in May 2009 (50.11%, − 19.94% compared to April 2009) due to the peak of the H1N1 pandemic [49], which was recovered immediately in the next month, mainly thanks to the promptly implemented actions against the spread of the pandemic [50].Fig. 1 Average hospitality efficiency of Mexican states, comparison of overall, national and international models, 1992–2018 Table 7 (in appendix) divides the average efficiency of all 32 Mexican states into nine 3-year-long periods to capture the variation in the hospitality efficiency on the period-to-period basis. The highest stability of the hospitality efficiency is observed in case of the best evaluated Quintana Roo, which average efficiency is 88.25% has remained mainly steady during the whole period with an average change from period-to-period of − 0.49% and SD of 3.66%. Sonora, as the second-best evaluated state with the efficiency of 74.71% reported the period-to-period volatility of 6.92% and, what is more, its average efficiency has grown by an average of 1.66%. The biggest positive period-to-period average change is linked to Nayarit (+ 5.09%) with the highest volatility of 22.23%. However, this is due to the huge drop of − 37.65% in its efficiency from 1995–1997 to 1998–2000, which was recovered in the following two periods. On the other hand, the biggest negative change can be observed in case of Tamaulipas (− 5.08%) with SD of 10.96%, Morelos (− 4.91%, SD 10.33%), Campeche (− 4.33%, SD 12.09%) and Baja California (− 4.31%, SD 7.03%). Finally, Guerrero represents the state with almost zero average period-to-period change of -0.01% (SD 10.68%). International tourists As the results of the analysis show differences across the analyzed period, we can also assume that similar differences can be observed considering the tourists’ origin. In the case of international tourists, the average efficiency of all 32 states for the entire period was 27.42% with SD of 3.25% (Table 4). The average efficiency is − 37.6% below the efficiency in the overall model, but, on the other hand, the sector is more stable (SD lower by − 9.73%). Several similarities can be observed in the evolution of efficiency. We can also observe the drop in the efficiency during the year 1995 (27.64% in 1995 compared to 30.88% in 1994), which represented a relative change of − 10.49% (slightly less compared to the overall model). Then, a similar decade of efficiency decrease can also be observed. However, the hospitality sector recovered from this decrease at the beginning of 2006, a year earlier than in the overall model (Fig. 1). Further, the results show the significant drop in the efficiency in May 2009 (14.60%, − 12.76% compared to April 2009), which was recovered in the following months, as in the overall model, but in a slower pace. International tourists returned slower after the H1N1 pandemic than the national tourists, which would be linked to students' return to class in May 2009 and the cancelation of the suspension of non-essential activities [49]. The following decade showed a stable level of efficiency around 26.07% with SD of 1.83%.Table 4 Hospitality efficiency of Mexican states, international tourists 1992–2018 State Efficiency Rank State Efficiency Rank State Efficiency Rank Aguascalientes 15.35% 21 Guanajuato 12.82% 26 Quintana Roo 86.86% 1 Baja California 46.87% 5 Guerrero 16.99% 20 San Luis Potosí 19.11% 18 Baja California Sur 59.07% 2 Hidalgo 8.49% 31 Sinaloa 37.24% 7 Campeche 49.23% 4 Jalisco 35.59% 10 Sonora 33.71% 12 Chiapas 55.05% 3 Michoacán 14.58% 23 Tabasco 12.23% 27 Chihuahua 22.10% 15 Morelos 9.71% 28 Tamaulipas 20.82% 16 Ciudad de México 33.17% 13 Nayarit 45.18% 6 Tlaxcala 15.24% 22 Coahuila 37.08% 9 Nuevo León 14.42% 25 Veracruz 9.70% 29 Colima 18.04% 19 Oaxaca 34.85% 11 Yucatán 37.21% 8 Durango 8.60% 30 Puebla 31.65% 14 Zacatecas 19.86% 17 Estado de México 14.46% 24 Querétaro 5.96% 32 MEXICO 27.42% - The best evaluated state in the case of international tourists is Quintana Roo (86.86%), Baja California Sur (59.07%), Chiapas (55.05%), Campeche (49.23%) and Baja California (46.87%), as these states include the most important touristic destinations in Mexico. On the other hand, the lowest efficiency is reported in Querétaro (5.96%), Hidalgo (8.49%), Durango (8.60%), Veracruz (9.70%) and Morelos (9.71%), which represent mainly in-land states. This phenomenon was also observed by Flegl et al. [34] in their analysis of touristic centers in Mexico. Considering the period-to-period changes (Table 8), the lowest volatility in the hospitality efficiency is observed in the case of the worst evaluated state Querétaro with the average period-to-period change of + 0.20% and SD 1.29%, followed by Guanajuato with − 1.42% (SD 3.03%), Morelos (− 0.04%, SD 3.63%) and Nuevo León (− 0.13%, SD 3.63%). All these states belong within the states with the lowest efficiency (Table 4). This result indicates that regardless of changes in the tourism industry, the hospitality sector in these states has not shown any progress toward international tourists. On the other hand, Coahuila (+ 6.95%, SD 20.09%), Nayarit (+ 5.45%, SD 35.34%) and Tlaxcala (+ 3.89%, 14.54%) represent states with the highest period-to-period growth across the evaluated period. However, it is also important to mention that the growth is not linear, but a higher volatility is observed. Finally, Chiapas (− 5.51%, SD 12.86%), Yucatán (− 4.54%, SD 9.28%) and Durango (− 3.99%, SD 11.05%) reported the largest average period-to-period decrease in hospitality efficiency among all states. The efficiency of the entire hospitality sector in the international model decreased by − 0.54%. National tourists The hospitality efficiency in the case of the national tourists shows completely different level compared to the international tourists. The average level of efficiency in the whole Mexico is 65.22% with SD of 5.58% (Table 5), which is higher by 38.22% compared to the international model. The lower variation can be linked to a lower dependence of national tourism to a few specific touristic locations. The evolution of the efficiency throughout the evaluated period follows the overall efficiency in the sector (Fig. 1). The most significant difference between the overall and national models is the efficiency level before the drop in 2005–2006. The model indicates that the average efficiency in the national model before this drop in 2004 was 67.96%. However, from January 2005 to December 2006, the average efficiency in the sector dropped to 54.04% (− 13.92%), with the lowest efficiency of 48.49% recorded between January and March 2006. Two reasons can explain this: (1) the loss of competitiveness reflected in the decrease in tourist stay [51], and (2) the lack of convergence of public tourism policies that used to involve 14 public agencies [52]. After this period, during the sexennial period 2006–2012, the sector recovered with a peak in March 2008 (77.89%). The hospitality sector recovered in 2007, a year later compared to the international tourists. The rest of the analyzed period follows the trend of the overall model.Table 5 Hospitality efficiency of Mexican states, national model 1992–2018 Touristic center Efficiency Rank Touristic center Efficiency Rank Touristic center Efficiency Rank Aguascalientes 58.28% 26 Guanajuato 62.04% 21 Quintana Roo 58.41% 25 Baja California 41.44% 32 Guerrero 75.11% 4 San Luis Potosí 68.72% 15 Baja California Sur 53.95% 30 Hidalgo 73.25% 7 Sinaloa 65.68% 16 Campeche 69.11% 12 Jalisco 56.95% 27 Sonora 73.35% 6 Chiapas 60.55% 23 Michoacán 71.19% 10 Tabasco 65.20% 17 Chihuahua 69.06% 13 Morelos 63.74% 19 Tamaulipas 71.62% 9 Ciudad de México 68.93% 14 Nayarit 56.69% 28 Tlaxcala 64.64% 18 Coahuila 77.09% 2 Nuevo León 77.19% 1 Veracruz 60.48% 24 Colima 76.76% 3 Oaxaca 60.80% 22 Yucatán 54.37% 29 Durango 63.68% 20 Puebla 73.05% 8 Zacatecas 70.93% 11 Estado de México 52.84% 31 Querétaro 73.84% 5 MEXICO 65.22% - The best evaluated states are Nuevo León (77.19%), Coahuila (77.09%), Colima (76.76%), Guerrero (75.11%) and Querétaro (73.84%). First, we do not observe big differences between the best evaluated states as in the international model. As a result, efficiency is not concentrated in a few main states with the main tourist attractions, but the hospitality sector shows a better distribution across the whole country. Second, the best evaluated states are the in-land states, which is opposite to the international model. This leads to the observation that the worst evaluated states are Baja California (41.44%), Estado de México (52.84%), Baja California Sur (53.95%), Yucatán (54.37%) and Nayarit (56.69%). Most of these states were within the best evaluated in the international model, which highlights the different priorities of international and intranational tourists (Table 4). Further, the results do not indicate any state with very high stability over the period-to-period changes. The best evaluated state is Guerrero, with average volatility (SD) of 4.96% and an average growth of + 1.59%. In the previous model, Querétaro presented a volatility of only 1.29%. The highest growth of efficiency can be observed in the case of Nayarit (+ 4.54%, SD 10.90%), Sonora (2.07%, SD 11.12%) and Colima (1.76%, SD 7.35%). Only five more states have a positive average period-to-period change, but these averages are close to zero. Most of the states thus report negative average period-to-period changes. The biggest drop in the efficiency has Campeche (− 5.29%, SD 11.82%), Morelos (− 4.91%, SD 8.20%) and Tamaulipas (− 4.43%, SD 10.55%). As a result, the whole hospitality sector decreased by average − 1.38%. All period-to-period efficiencies are presented in Table 9. Discussion This research focused on the state level to provide quantitative elements for decision-making in the tourism sector. It should be noted that decisions in the tourism activity and the allocation of resources to increase the efficiency depend largely on the Federation and statal entities. The results obtained from the DEA models indicate significant differences between the regions and national and international tourism. More precisely, the average efficiency linked to international tourism is 27.42% (− 37.6% below the efficiency in the overall model), compared to the average efficiency 65.22% in the case of national tourism. What is more, the most efficient states for international tourism are mainly coastal states (Quintana Roo, Baja California Sur, Chiapas, Campeche and Baja California), whereas the lowest efficiency is mainly observed in the in-land states (Querétaro, Hidalgo, Durango, Veracruz and Morelos). Identifying such differences is crucial considering two factors. First, as very little attention has historically been paid to the tourism performance and efficiency analysis in Latin America [24], the results may indicate a pattern for the rest of the region. Such a conclusion can be supported by previous research in the industry. For example, Higuerey et al. [11] observed that the most efficient hotels in Ecuador during 2013–2017 are located in zones with tourist attractions and activities. Flegl et al. [34] observed a similar pattern of the national and international tourism efficiency levels in the case of 67 main touristic centers in Mexico. In both cases, the conclusions correspond to the presented analysis in the article. However, more analysis in the hospitality sector must be done to confirm this pattern. In this case, the analysis can be replicated in other countries as the model does not include any country-specific variables. Second, the analysis provides a valuable information about the development of the hospitality industry over a long period (27 years or 324 months). Thus, the calculated efficiency covers important national and international events (crises), such as the global economic crisis in 2008 and the H1N1 pandemic in 2009, which provides worthy information about the industry behavior. For example, in the case of the H1N1 pandemic, the analysis detected: (1) such an event has a negative effect on the whole tourism sector with a similar effect on both national and international tourism. However, (2) international tourism takes more time to return to its pre-crisis level compared to national tourism (Fig. 1). The recovery time depends on the magnitude of the event and can vary from one month to 93 months [53] and also depends on the taken strategies to reduce the negative consequences of such a crisis [54]. Such information is worthy, for example, for the current Covid-19 post-pandemic recovery of the tourism industry, as a similar pattern can be expected. Mexico is one of the most vulnerable countries as the industry depends on international arrivals [15]. Therefore, Quintana Roo, Baja California Sur, Chiapas, Campeche and Baja California can serve as a benchmark for the rest of the industry due to the high concentration of the tourists’ arrivals in these states. Such observation is not unusual as some destinations can be highly preferred by tourists. For example, Oukil et al. [33] found the high level of efficiency concentrated mainly in Muscat, the capital of Oman, Corne [28] showed that Paris is a benchmark for the whole French hospitality sector, while Liu et al. [29] observed that highly efficient Chinese coastal cities are concentrated in two main regions. In this case, it is important to refer to the elements that have traditionally influenced the level of tourism in Mexico. The study carried out by Madrid and Cerón [55] observed six dimensions that influence achieving the maximum tourist performance of a destination: the tourist vocation of the destination, strategic planning and sustainability, infrastructure, governance, visitor satisfaction and security. The evidence of the analysis points out that there is an efficiency gap as the number of rooms available in the hospitality sector is not properly linked to the arrival of national and international tourists in some destinations. This observation results in lower efficiency and possible problems in the post-pandemic recovery. Therefore, to minimize the efficiency gap between the high and low efficient states, it is necessary to prepare strategies to attract in-land touristic areas for international tourists. The government plays the crucial role in addressing these challenging issues [56], as the cooperation between national, regional and local governments is essential in this process [57, 58]. For Mexico, this goes along with the Tourism Sector Program 2019–2024 of the Mexican government [59]. One of the five main projects for this period aims at regionalization of tourism, to strengthen tourism within the whole country to make it more equal.1 The calculated weights in the DEA models revealed that international tourists highly prefer five-star hotels (77.70%), whereas the national tourist have no clear preference. The development in lower efficient states should align their hospitality structure to this evidence. Each state must decide who their primary target is, whether national or international tourists, and find the optimal mix of hotels. Further, to close the efficiency gap between the states and minimize the period-to-period volatility in the efficiency observed in some states, it is also necessary to continue with the planned regional infrastructure projects such as the Mayan Train in the Southern states of Mexico (Tabasco, Chiapas, Campeche, Yucatán and Quintana Roo), the Transítsmico Train in the states of Oaxaca and Veracruz, which will compete with the Panama Canal; the Toluca—Mexico City commuter rail in the State of Mexico and Mexico City, among others, in order to achieve a more inclusive and sustainable tourism [59]. For example, in the case of the Mayan Train, Tabasco (international efficiency 12.23%, Table 4), Campeche (49.23%) and Yucatán (37.21%) can benefit from the connection with Chiapas (60.55%) and Quintana Roo (86.86%) to increase the flow of tourists in the region. Such projects can help with the development of the communities around the main tourist centres. As Holzner [60] and Ranjan et al. [61] pointed out, it is recommendable to invest apart from tourism specific also into traditional infrastructure, which can be used by both the tourism sector and the manufacturing sector. So, the Mayan Train connection can help Chiapas and Quintana Roo to overcome the post-pandemic recovery in a faster pace and maintain its efficiency level. Similarly, the efficiency gap between the high and low efficient states can also be minimized by focusing on the local cultural specifics of each state. Oukil et al. [33] argue that the effect of cultural attractions appears among the most influential factors in tourists’ attractions. The cultural factor includes traditional villages, world heritage, museums, archaeological and religious sites, crafts, among others. Therefore, SECTUR should target its marketing operations in less efficient states (including small touristic centers) to promote their cultural history and traditions. However, such specific marketing operations must be cautiously planned and discussed with local authorities, as, for example, local problems in small municipalities can put barriers in promoting local touristic activities [62]. Similarly, it is important to consider the insecurity situation in several states (touristic centers), as the effect of the marketing operations can be easily neutralized by negative publicity due to local criminality [42]. Destination’s image is one of the crucial factors for tourists’ destination loyalty [63], which is the key element in marketing strategies [64]. Conclusions The article presents the results of the efficiency analysis in the Mexican hospitality sector. The DEA Window Analysis model was constructed for 32 Mexican states covering a period of 324 months from 1992 to 2018. The analysis concludes that: Significant differences exist between the states with respect to their overall efficiency, as well as regarding the volatility across the analyzed period. Moreover, significant differences in the national and international tourism are observed. In this case, the international tourism is mainly concentrated in only a few coastal states, resulting in very low overall hospitality efficiency. On the other hand, national tourism is not characterized by such concentration in the coastal states, as it is rather in-land oriented. This different characteristic results in higher overall hospitality efficiency. Finally, the analysis indicates that international tourism recovers slower from crisis events, which should be considered in creation post-crisis strategies in the industry as Mexico mainly depends on international arrivals. Therefore, in future research, it is required to extend the analysis to other activities that are considered touristic according to the Tourism Satellite Account [7], such as food and beverage activities, transport or travel agencies, in order to have a better overview of the efficiency of the Mexican tourism sector and aim correctly the decision-making strategies in attracting more tourists’ arrivals. Appendix See Tables 6, 7, 8, and 9. Table 6 Evolution of disponible rooms, national tourists and international tourists per state, averages 1992 and 2018 Disponible rooms National tourists International tourists State 1992 2018 % Growth 1992 2018 % Growth 1992 2018 % Growth Aguascalientes 2260 5981 165 305,502 776,976 154 12,007 69,135 476 Baja California 10,046 17,904 78 1,290,452 2,372,793 84 633,169 1,303,216 106 Baja California Sur 5287 21,986 316 298,464 1,012,001 239 312,391 2,103,594 573 Campeche 2358 7838 232 378,387 1,171,459 210 54,741 361,338 560 Chiapas 4829 20,633 327 601,818 3,780,088 528 264,731 460,342 74 Chihuahua 8959 20,685 131 2,351,017 4,328,301 84 196,554 201,828 3 Ciudad de México 35,882 51,344 43 3,525,332 9,389,468 166 1,065,765 2,192,233 106 Coahuila 4133 11,951 189 736,893 1,704,103 131 72,069 167,649 133 Colima 4330 6938 60 495,408 1,247,550 152 61,744 46,909 − 24 Durango 2696 4035 50 559,559 787,183 41 12,699 6,323 − 50 Estado de México 6160 14,995 143 942,502 3,180,900 237 45,055 271,674 503 Guanajuato 6962 23,981 244 1,073,136 5,547,899 417 71,919 163,016 127 Guerrero 22,531 30,042 33 1,852,192 8,422,423 355 543,331 242,623 − 55 Hidalgo 3187 8236 158 782,933 2,671,357 241 13,437 15,103 12 Jalisco 31,890 56,320 77 3,100,632 7,459,736 141 529,107 1,555,282 194 Michoacán 9648 15,321 59 1,954,143 3,034,138 55 87,730 45,955 − 48 Morelos 4827 10,327 114 922,433 1,801,462 95 41,703 146,889 252 Nayarit 4601 21,162 360 408,590 2,076,787 408 12,991 845,485 6,408 Nuevo León 5674 16,674 194 969,241 2,647,319 173 125,225 523,214 318 Oaxaca 7146 18,016 152 777,913 3,298,730 324 279,827 267,768 − 4 Puebla 5633 20,043 256 928,110 5,459,126 488 84,082 781,107 829 Querétaro 3188 13,340 318 617,179 2,404,900 290 14,765 109,707 643 Quintana Roo 22,036 97,233 341 583,661 3,489,547 498 1,799,375 13,185,860 633 San Luis Potosí 3910 10,087 158 628,602 1,874,179 198 70,454 151,593 115 Aguascalientes 2260 5981 165 305,502 776,976 154 12,007 69,135 476 Baja California 10,046 17,904 78 1,290,452 2,372,793 84 633,169 1,303,216 106 Baja California Sur 5287 21,986 316 298,464 1,012,001 239 312,391 2,103,594 573 Campeche 2358 7838 232 378,387 1,171,459 210 54,741 361,338 560 Chiapas 4829 20,633 327 601,818 3,780,088 528 264,731 460,342 74 Chihuahua 8959 20,685 131 2,351,017 4,328,301 84 196,554 201,828 3 Ciudad de México 35,882 51,344 43 3,525,332 9,389,468 166 1,065,765 2,192,233 106 Coahuila 4133 11,951 189 736,893 1,704,103 131 72,069 167,649 133 Total 275,441 632,668 130 34,767,270 100,444,598 189 7,426,104 27,092,754 265 Table 7 Hospitality efficiency by period, overall model 1992–1994 1995–1997 1998–2000 2001–2003 2004–2006 2007–2009 2010–2012 2013–2015 2016–2018 Aguascalientes 54.79% 43.95% 48.60% 68.15% 61.72% 56.08% 51.78% 49.78% 65.52% Baja California 69.79% 57.25% 60.78% 56.55% 45.58% 53.14% 50.96% 44.14% 35.27% Baja California Sur 63.43% 68.16% 57.67% 48.74% 69.95% 79.59% 76.52% 74.44% 73.74% Campeche 82.19% 87.44% 81.16% 78.72% 56.65% 71.22% 72.56% 66.61% 47.54% Chiapas 70.84% 67.40% 62.34% 64.53% 63.89% 73.38% 80.37% 62.84% 61.79% Chihuahua 82.81% 73.07% 74.17% 67.25% 50.19% 76.89% 71.11% 48.42% 51.39% Ciudad de México 60.52% 67.21% 64.49% 68.85% 60.52% 69.94% 79.31% 63.60% 56.38% Coahuila 89.88% 71.27% 63.95% 53.86% 45.93% 73.85% 66.34% 82.71% 88.65% Colima 70.31% 68.07% 83.75% 74.69% 64.23% 78.90% 81.71% 70.66% 77.38% Durango 87.39% 79.73% 62.76% 40.89% 30.54% 63.76% 75.90% 55.28% 57.72% Estado de México 68.69% 54.26% 52.08% 44.68% 39.57% 58.97% 53.74% 44.27% 45.32% Guanajuato 82.74% 60.92% 65.12% 55.99% 50.32% 55.20% 55.82% 49.07% 51.46% Guerrero 66.20% 56.16% 59.81% 49.50% 68.04% 76.16% 73.14% 61.47% 66.32% Hidalgo 84.68% 78.23% 87.67% 70.55% 47.65% 50.68% 68.61% 84.28% 76.03% Jalisco 60.16% 59.64% 71.41% 59.73% 48.42% 66.83% 64.53% 59.33% 51.57% Michoacán 85.39% 71.82% 67.49% 69.28% 74.67% 80.45% 69.16% 54.60% 58.33% Morelos 81.69% 64.20% 72.33% 57.01% 43.73% 53.98% 48.11% 45.91% 42.42% Nayarit 49.89% 55.07% 17.42% 49.50% 68.45% 64.92% 74.17% 65.11% 90.64% Nuevo León 71.90% 51.75% 63.99% 62.41% 51.23% 61.47% 51.31% 56.60% 61.51% Oaxaca 78.38% 68.45% 59.93% 57.55% 51.15% 69.73% 72.55% 64.98% 66.37% Puebla 75.43% 60.20% 73.39% 82.10% 61.42% 72.40% 72.15% 83.19% 86.49% Querétaro 79.51% 50.83% 57.83% 59.73% 41.09% 55.04% 59.59% 65.47% 51.96% Quintana Roo 90.23% 93.36% 87.21% 87.35% 91.01% 87.33% 84.12% 87.26% 86.35% San Luis Potosí 74.53% 57.20% 59.67% 64.93% 46.44% 59.48% 56.67% 65.95% 80.64% Sinaloa 83.48% 64.99% 62.60% 50.05% 58.08% 82.36% 80.66% 72.28% 70.48% Sonora 77.73% 73.83% 75.97% 70.30% 70.53% 67.86% 70.78% 74.36% 90.99% Tabasco 65.38% 64.41% 58.49% 69.78% 58.23% 65.96% 70.15% 58.73% 44.83% Tamaulipas 81.42% 79.36% 61.56% – – 74.70% 60.35% 69.42% 69.16% Tlaxcala 78.62% 51.75% 66.90% 58.38% 58.94% 54.97% 50.51% 56.77% 80.30% Veracruz 69.23% 61.83% 64.17% 58.45% 43.32% 63.29% 60.68% 46.87% 50.30% Yucatán 78.07% 58.93% – – 47.02% 62.69% 64.97% 52.91% 49.03% Zacatecas 80.38% 67.61% 71.97% 54.76% 62.83% 72.92% 75.54% 62.76% 75.77% MEXICO 74.87% 65.26% 66.22% 62.04% 55.79% 67.11% 67.00% 62.50% 64.43% Table 8 Hospitality efficiency by period, international model 1992–1994 1995–1997 1998–2000 2001–2003 2004–2006 2007–2009 2010–2012 2013–2015 2016–2018 Aguascalientes 7.49% 4.65% 6.72% 11.97% 19.56% 13.34% 22.16% 29.20% 23.08% Baja California 53.93% 48.59% 60.81% 43.30% 45.26% 51.05% 48.78% 34.18% 35.95% Baja California Sur 57.15% 65.64% 56.92% 14.00% 57.97% 74.76% 71.32% 64.98% 68.90% Campeche 59.29% 76.86% 56.04% 64.80% 31.79% 39.57% 32.66% 46.49% 35.58% Chiapas 75.96% 70.05% 53.97% 49.60% 71.63% 63.66% 47.79% 30.89% 31.91% Chihuahua 25.38% 18.94% 24.43% 27.08% 25.62% 31.78% 23.18% 12.44% 10.03% Ciudad de México 32.72% 32.40% 36.88% 39.52% 33.92% 36.92% 35.13% 26.00% 25.08% Coahuila 18.59% 22.01% 26.76% 15.92% 9.91% 55.68% 39.85% 50.39% 74.22% Colima 26.74% 28.19% 25.18% 18.16% 15.28% 19.98% 12.13% 7.93% 8.76% Durango 33.81% 4.23% 5.15% 5.02% 5.17% 9.23% 4.28% 8.64% 1.85% Estado de México 17.65% 12.76% 17.08% 13.18% 9.01% 13.72% 29.42% 8.66% 8.62% Guanajuato 19.76% 16.35% 17.90% 10.66% 10.19% 11.58% 9.62% 10.89% 8.41% Guerrero 28.41% 26.04% 30.01% 19.02% 16.29% 12.76% 11.01% 6.67% 7.08% Hidalgo 25.69% 2.41% 2.11% 3.38% 5.82% 12.25% 15.69% 3.33% 3.99% Jalisco 31.15% 36.56% 48.81% 39.95% 32.69% 41.82% 34.40% 27.46% 27.49% Michoacán 16.86% 13.16% 11.39% 11.62% 32.16% 24.10% 10.21% 5.52% 6.21% Morelos 11.63% 14.69% 10.21% 4.98% 6.89% 8.51% 11.20% 7.97% 11.33% Nayarit 33.60% 58.44% 0.74% 45.10% 64.32% 43.87% 27.32% 32.75% 77.22% Nuevo León 16.35% 11.86% 15.44% 16.29% 13.00% 15.88% 10.74% 14.89% 15.29% Oaxaca 55.51% 49.45% 41.49% 27.73% 29.43% 34.34% 28.75% 19.63% 27.33% Puebla 16.92% 15.28% 27.00% 40.32% 27.10% 39.25% 41.11% 39.34% 38.52% Querétaro 4.36% 3.43% 5.30% 4.97% 6.61% 7.23% 7.93% 7.90% 5.94% Quintana Roo 88.95% 93.04% 84.92% 82.29% 91.00% 86.44% 83.85% 85.86% 85.43% San Luis Potosí 13.70% 8.01% 5.75% 7.16% 10.27% 18.51% 35.18% 44.27% 29.15% Sinaloa 47.28% 38.89% 42.75% 23.05% 32.61% 45.81% 42.17% 27.79% 34.77% Sonora 25.60% 44.84% 23.59% 35.61% 46.40% 24.64% 31.93% 39.29% 31.51% Tabasco 12.70% 12.23% 9.60% 12.59% 10.98% 10.87% 14.55% 17.49% 9.04% Tamaulipas 14.67% 30.45% 19.06% – – 15.98% 2.25% 44.36% 16.23% Tlaxcala 12.34% 7.82% 23.20% 14.74% 15.04% 6.51% 4.94% 9.11% 43.44% Veracruz 15.93% 10.53% 8.81% 6.93% 9.49% 10.30% 16.59% 6.33% 2.41% Yucatán 72.78% 55.42% – – 26.77% 34.47% 25.66% 23.99% 21.41% Zacatecas 32.17% 12.42% 11.35% 9.14% 26.52% 24.00% 28.74% 13.44% 20.97% MEXICO 31.41% 29.55% 26.93% 24.17% 26.87% 29.25% 26.91% 25.25% 26.47% Table 9 Hospitality efficiency by period, national model 1992–1994 1995–1997 1998–2000 2001–2003 2004–2006 2007–2009 2010–2012 2013–2015 2016–2018 Aguascalientes 60.98% 54.96% 55.68% 72.36% 65.09% 56.11% 50.30% 46.38% 62.64% Baja California 56.38% 43.36% 43.05% 47.09% 36.70% 42.51% 40.50% 38.06% 25.34% Baja California Sur 46.18% 48.06% 33.93% 84.32% 62.12% 67.50% 48.34% 56.80% 38.27% Campeche 82.06% 87.39% 78.38% 74.72% 56.89% 69.88% 73.27% 59.67% 39.76% Chiapas 57.79% 52.31% 48.85% 59.67% 59.52% 70.24% 76.91% 61.05% 58.65% Chihuahua 82.51% 85.45% 75.53% 71.95% 54.49% 77.33% 71.15% 49.45% 53.71% Ciudad de México 61.98% 77.33% 62.72% 74.07% 69.25% 73.28% 80.79% 67.00% 54.00% Coahuila 91.16% 79.87% 66.23% 75.81% 68.80% 74.15% 63.13% 80.53% 85.92% Colima 65.09% 63.25% 81.94% 83.36% 78.08% 78.59% 82.09% 79.29% 79.19% Durango 87.26% 81.66% 63.97% 47.37% 33.85% 65.42% 77.56% 56.22% 59.78% Estado de México 66.94% 54.78% 52.41% 49.32% 44.75% 62.19% 49.91% 48.27% 47.01% Guanajuato 81.00% 65.63% 69.74% 63.41% 57.61% 57.25% 58.08% 52.44% 53.18% Guerrero 69.72% 68.40% 66.48% 69.11% 78.07% 82.96% 80.37% 75.60% 82.43% Hidalgo 84.02% 82.51% 88.46% 73.92% 51.77% 50.90% 67.57% 84.10% 75.98% Jalisco 60.24% 61.99% 61.94% 56.54% 48.59% 60.42% 58.41% 59.17% 45.24% Michoacán 85.32% 75.63% 69.95% 70.52% 75.02% 80.60% 69.11% 56.04% 58.53% Morelos 81.66% 73.20% 76.91% 71.07% 56.49% 65.65% 53.75% 52.59% 42.35% Nayarit 42.28% 37.83% 23.59% 41.87% 57.93% 61.76% 72.82% 71.90% 78.58% Nuevo León 91.26% 78.25% 87.53% 82.07% 68.34% 76.25% 62.12% 70.74% 78.20% Oaxaca 59.82% 58.98% 51.69% 58.40% 50.71% 65.93% 70.59% 67.32% 63.79% Puebla 75.67% 63.34% 71.42% 82.80% 66.61% 66.81% 65.79% 81.99% 83.01% Querétaro 82.85% 76.28% 74.33% 84.86% 64.46% 72.59% 70.10% 77.57% 61.52% Quintana Roo 66.16% 65.99% 72.69% 64.13% 47.53% 53.98% 47.26% 51.94% 56.02% San Luis Potosí 81.93% 76.60% 72.97% 76.52% 54.91% 62.24% 52.53% 61.08% 79.66% Sinaloa 74.66% 57.64% 50.07% 55.75% 59.99% 77.25% 72.80% 77.77% 65.19% Sonora 74.26% 63.88% 80.35% 70.79% 63.16% 71.16% 72.36% 73.37% 90.80% Tabasco 70.48% 67.24% 62.88% 76.49% 63.26% 67.13% 73.81% 59.79% 45.74% Tamaulipas 81.39% 80.27% 61.71% – – 73.21% 61.65% 69.60% 70.72% Tlaxcala 78.92% 56.91% 67.11% 62.97% 64.98% 58.61% 54.25% 59.03% 78.97% Veracruz 72.46% 66.06% 65.44% 67.27% 48.89% 64.37% 60.00% 47.71% 52.11% Yucatán 50.84% 42.53% – – 52.98% 66.59% 67.42% 53.29% 46.90% Zacatecas 78.88% 70.27% 74.87% 62.26% 64.40% 71.58% 73.03% 65.19% 77.88% MEXICO 71.94% 66.18% 65.84% 67.52% 58.68% 66.80% 64.93% 62.84% 62.22% Author contributions MF: involved in conceptualization, data curation, methodology, software, formal analysis and writing—original draft; HC-M: involved in conceptualization, methodology, formal analysis and writing—original draft; IK: contributed in writing—review & editing and visualization; and JJ: involved in methodology and writing—review & editing. Funding The authors did not receive support from any organization for the submitted work and have no relevant financial or non-financial interests to disclose. Declarations Conflict of interest The authors declare that they have no conflict of interest. 1 The project is related to the regionalization policy that will be extended to the entire country, so that tourism activity is more balanced [59]. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ==== Refs References 1. WTO World tourism barometer 2020 Madrid World Tourism Organization 2. WTTC and Oxford Economics: Travel and tourism global economic impact and trends 2020. World Travel and Tourism Council and Oxford Economics, England. Available at https://wttc.org/Portals/0/Documents/Reports/2020/Global%20Economic%20Impact%20Trends%202020.pdf?ver=2021-02-25-183118-360 (2020). Accessed 14 May 2021 3. BANXICO: Estadísticas. Balanza de Pagos. Viajeros internacionales ingresos. [Sistema de Información Económica]. México: Banxico. https://bit.ly/34XV4o4 (2021). Accessed 17 May 2021 4. Coelho MF Gosling M Em busca da definição de reputação de destinos turísticos: significados e temas associados a partir da visão de profissionais Rev. Tur. Análise 2015 26 2 262 281 10.11606/issn.1984-4867.v26i2p262-281 5. Sánchez Mendoza VV Escenarios Turísticos e Inseguridad en el Turismo Rev. Lat. Am. Tur. 2015 1 1 61 75 6. UN and WTO: Tourism satellite account: recommended methodological framework 2008. Rev. 1. Luxembourg: United Nations and world tourism organization, Commission of the European Communities, Eurostat and OCDE, (2010) 7. INEGI: Cuenta Satélite del Turismo de México, 2019. Instituto Nacional de Estadística y Geografía, [Comunicado de prensa número 642/20]. Aguascalientes, México: INEGI. https://www.datatur.sectur.gob.mx/SitePages/ProductoDestacado3.aspx (2020). Accessed 15 Dec 2021 8. INEGI: Cuentas Nacionales. Producto interno bruto trimestral, base 2013, en valores básicos. Instituto Nacional de Estadística y Geografía, [Banco de información económica]. México: INEGI. https://www.inegi.org.mx/sistemas/bie/ (2021). Accessed 15 May 2021 9. DATATUR: Compendio Estadístico 2019 de la Actividad Ho​​telera. Available at: https://www.datatur.sectur.gob.mx/SitePages/ActividadHotelera.aspx (2020). Accessed 2 Apr 2021 10. Ely PA Selling Mexico: marketing and tourism values Tour. Manag. Perspect. 2013 8 80 89 10.1016/j.tmp.2013.07.003 11. Higuerey A Viñan-Merecí C Malo-Montoya Z Martínez-Fernández VA Data Envelopment Analysis (DEA) for measuring the efficiency of the hotel industry in Ecuador Sustainability 2020 12 4 1590 10.3390/su12041590 12. Barros CP Measuring efficiency in the hotel sector Ann. Tour. Res. 2005 32 2 456 477 10.1016/j.annals.2004.07.011 13. Alberca P Parte L Evaluación de la eficiencia y la productividad en el sector hotelero español: Un análisis regional Investig. Eur. Dir. Econ. 2013 19 2 102 111 10.1016/j.iedee.2012.10.004 14. Cázares M Schütze O Trujillo L Schütze O Maldonado Y Valle P An application of data envelopment analysis to the performance assessment of online social networks usage in Mazatlán hotel organizations Numerical and evolutionary optimization—NEO 2017 2019 Cham Springer 295 310 15. Salinas Fernández JA Guaita Martínez JM Martín Martín JM An analysis of the competitiveness of the tourism industry in a context of economic recovery following the COVID19 pandemic Technol. Forecast. Soc. Chang. 2022 174 121301 10.1016/j.techfore.2021.121301 16. Assaf AG Tsionas MG A review of research into performance modeling in tourism research—Launching the Annals of Tourism Research curated collection on performance modeling in tourism research Ann. Tour. Res. 2019 76 266 277 10.1016/j.annals.2019.04.010 17. Emrouznejad A Yang G-L A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016 Socioecon. Plan. Sci. 2018 61 4 8 10.1016/j.seps.2017.01.008 18. De La Hoz E Zuluaga R Mendoza A Assessing and classification of academic efficiency in engineering teaching programs J. Effic. Responsib. Educ. Sci. 2021 14 1 41 52 10.7160/eriesj.2021.140104 19. Flegl M Jiménez Bandala CA Sánchez-Juárez I Matus E Analysis of production and investment efficiency in the Mexican food industry: Application of two-stage DEA Czech J. Food Sci. 2022 40 2 109 117 10.17221/172/2021-CJFS 20. Chopra A Ramachandran P Multidimensional analysis of water sector performance in India: an index approach Opsearch 2020 58 109 124 10.1007/s12597-020-00476-3 21. Le Linh T Lee P-P Chung Peng K Chung RH Evaluation of total factor productivity and environmental efficiency of agriculture in nine East Asian countries Agric. Econ. 2019 65 6 249 258 22. Jablonsky J Ranking of countries in sporting events using two-stage Data Envelopment Analysis models: a case of Summer Olympic Games 2016 CEJOR 2018 26 951 966 10.1007/s10100-018-0537-8 23. Vikas V Bansal R Efficiency evaluation of Indian oil and gas sector: Data Envelopment Analysis Int. J. Emerg. Mark. 2019 14 2 362 378 10.1108/IJoEM-01-2018-0016 24. Nurmatov R Fernandez Lopez XL Coto Millan PP Tourism, hospitality, and DEA: where do we come from and where do we go? Int. J. Hosp. Manag. 2021 95 102883 10.1016/j.ijhm.2021.102883 25. Oliveira R Pedro MI Marques RC Efficiency and its determinants in Portuguese hotels in the Algarve Tour. Manag. 2013 36 641 649 10.1016/j.tourman.2012.06.009 26. Barros CP Botti L Peypoch N Solonandrasana B Managerial efficiency and hospitality industry: the Portuguese case Appl. Econ. 2011 43 22 2895 2905 10.1080/00036840802600145 27. Hathroubi S Peypoch N Robinot E Technical efficiency and environmental management: the Tunisian case J. Hosp. Tour. Manag. 2014 21 27 33 10.1016/j.jhtm.2014.03.002 28. Corne A Benchmarking and tourism efficiency in France Tour. Manag. 2015 51 91 95 10.1016/j.tourman.2015.05.006 29. Liu J Zhang J Fu Z Tourism eco-efficiency of Chinese coastal cities—analysis based on the DEA-Tobit model Ocean Coast. Manag. 2017 148 164 170 10.1016/j.ocecoaman.2017.08.003 30. Chaabouni S China's regional tourism efficiency: a two-stage double bootstrap data envelopment analysis J. Destin. Mark. Manag. 2019 11 183 191 10.1016/j.jdmm.2017.09.002 31. Song M Li H Estimating the efficiency of a sustainable Chinese tourism industry using bootstrap technology rectification Technol. Forecast. Soc. Chang. 2019 143 45 54 10.1016/j.techfore.2019.03.008 32. Wang Z Liu Q Xu J Fujiki Y Evolution characteristics of the spatial network structure of tourism efficiency in China: a province-level analysis J. Destin. Mark. Manag. 2020 18 100509 10.1016/j.jdmm.2020.100509 33. Oukil A Channouf N Al-Zaidi A Performance evaluation of the hotel industry in an emerging tourism destination: the case of Oman J. Hosp. Tour. Manag. 2016 29 60 68 10.1016/j.jhtm.2016.05.003 34. Flegl M Rangel B Mendoza D Analysis of hospitality efficiency in the main Mexican touristic centers Rev. Latinoam. Investig. Soc. 2020 3 2 16 35 35. Castilho D Fuinhas JA Marques AC The impacts of the tourism sector on the eco-efficiency of the Latin American and Caribbean countries Socioecon. Plann. Sci. 2021 78 101089 10.1016/j.seps.2021.101089 36. Niavis S Tsiotas D Assessing the tourism performance of the Mediterranean coastal destinations: a combined efficiency and effectiveness approach J. Destin. Mark. Manag. 2019 14 100379 10.1016/j.jdmm.2019.100379 37. Camacho, C.C.: Eficiencia y productividad de los destinos turísticos preferenciales de México y Michoacán: Un análisis a través de la frontera de datos DEA y el Índice Malmquist, 2000–2010. [PhD Thesis] Repositorio Institucional de la Universidad Michoacana de San Nicolás de Hidalgo http://bibliotecavirtual.dgb.umich.mx:8083/xmlui/handle/DGB_UMICH/958 (2012) 38. Kido-Cruz A Cruz-Pérez JP Ortiz-Zavala A Turismo y pobreza: Un análisis de la envolvente de datos para municipios en México Inquiet. Empres. 2021 21 2 85 95 10.19053/01211048.12334 39. Cooper W Seiford L Zhu J Handbook on Data Envelopment Analysis 2011 New York Springer 40. Charnes A Cooper W Rhodes E Measuring the efficiency of decision making units Eur. J. Oper. Res. 1978 2 6 429 444 10.1016/0377-2217(78)90138-8 41. Cooper W Seiford L Tone K Data Envelopment Analysis: a comprehensive text with models, applications, references, and DEA-solver software 2007 New York Springer 42. Aula P Harmaakorpi V An innovative Milieu—a view on regional reputation building: case study of the Lahti Urban region Reg. Stud. 2008 42 4 523 538 10.1080/00343400701543207 43. Kapuściński G Richards B News framing effects on destination risk perception Tour. Manag. 2016 57 234 244 10.1016/j.tourman.2016.06.017 44. Lee CF Huang H-I Yeh H-R Developing an evaluation model for destination attractiveness: sustainable forest recreation tourism in Taiwan J. Sustain. Tour. 2010 18 6 811 828 10.1080/09669581003690478 45. Oliani LGN Rossi GB Gervasoni VC What are the attractiveness factors that influence the choice of a tourist destination—a study of Brazilian tourist Consumer Chin. Bus. Rev. 2011 10 4 286 293 46. Flegl, M., Cerón-Monroy, H.: Mexican hospitality sector indicators 1992–2018. Figshare. Dataset. 10.6084/m9.figshare.19210188.v1 (2022) 47. Guerrero VM Desestacionalización de series de tiempo económicas: introducción a la metodología Comer. Exter. 1990 40 11 1035 1046 48. Dyson RG Allen R Camanho AS Podinovski VV Sarrico CS Shale EA Pitfalls and protocols in DEA Eur. J. Oper. Res. 2001 132 245 259 10.1016/S0377-2217(00)00149-1 49. Echevarría-Zuno S Mejía-Aranguré JM Mar-Obeso AJ Grajales-Muñiz C Robles-Pérez E González-León M Ortega-Alvarez MC Gonzalez-Bonilla C Rascón-Pacheco RA Borja-Aburto VH Infection and death from influenza A H1N1 virus in Mexico: a retrospective analysis Lancet 2009 374 9707 2072 2079 10.1016/S0140-6736(09)61638-X 19913290 50. Cordova-Villalobos JA Macias AE Hernandez-Avila M Dominguez-Cherit G Lopez-Gatell H Alpuche-Aranda C Ponce de León-Rosales S The 2009 pandemic in Mexico: experience and lessons regarding national preparedness policies for seasonal and epidemic influenza Gac. Med. Mex. 2017 153 1 102 110 28128812 51. SECTUR: Programa Sectorial de Turismo 2001–2006, Secretaría de Turismo. Available at https://cedocvirtual.sectur.gob.mx/janium/Documentos/000817Pri0000.pdf (2001). Accessed 20 Mar 2021 52. SECTUR: Programa Sectorial de Turismo 2007–2012, Secretaría de Turismo. Available at https://www.dof.gob.mx/nota_detalle.php?codigo=5028631&fecha=18/01/2008 (2006). Accessed 20 Mar 2021 53. Liu-Lastres B Mariska D Tan X Ying T Can post-disaster tourism development improve destination livelihoods? A case study of Aceh, Indonesia J. Destin. Mark. Manag. 2020 18 100510 10.1016/j.jdmm.2020.100510 54. Raki A Nayer D Nazifi A Alexander M Seyfi S Tourism recovery strategies during major crises: the role of proactivity Ann. Tour. Res. 2021 90 103144 10.1016/j.annals.2021.103144 55. Madrid, F.F., Cerón, M.H.: Medición de la incidencia de los apoyos gubernamentales en el desempeño turístico de destinos seleccionados: los Convenios de Coordinación en materia de Reasignación de Recursos en México. Anuario Turismo y Sociedad, XIV, 197–215, (2013) 56. Wan YKP Li X Lau VM-C Dioko L Destination governance in times of crisis and the role of public-private partnerships in tourism recovery from Covid-19: the case of Macao J. Hosp. Tour. Manag. 2022 51 218 228 10.1016/j.jhtm.2022.03.012 57. Vargas A Covid-19 crisis: a new model of tourism governance for a new time Worldw. Hosp. Tour. Themes 2020 12 6 691 699 10.1108/WHATT-07-2020-0066 58. Wardman JK Recalibrating pandemic risk leadership: thirteen crisis ready strategies for COVID-19 J. Risk Res. 2020 23 7–8 1092 1120 10.1080/13669877.2020.1842989 59. SECTUR: Programa Sectorial de Turismo 2019–2024, Secretaría de Turismo, Datatur: Subsecretaría de Planeación y Política Turístico. Available at https://www.gob.mx/sectur/prensa/estrategia-nacional-de-turismo-2019-2024-tendra-un-sentido-democratico-miguel-torruco (2020). Accessed 14 Feb 2021 60. Holzner M Tourism and economic development: the beach disease? Tour. Manag. 2011 32 4 922 933 10.1016/j.tourman.2010.08.007 61. Ranjan R Chatterjee P Chakraborty S Performance evaluation of Indian states in tourism using an integrated PROMETHEE-GAIA approach Opsearch 2016 53 63 84 10.1007/s12597-015-0225-6 62. Méndez Méndez A García Romero A de la Cruz Serrano Santos-Olmo MA Ibarra García V Determinantes sociales de la viabilidad del turismo alternativo en Atlautla, una comunidad rural del Centro de México Investig. Geogr. 2016 90 119 134 63. Cossío-Silva F-J Revilla-Camacho M-Á Vega-Vázquez M The tourist loyalty index: a new indicator for measuring tourist destination loyalty? J. Innov. Knowl. 2019 4 2 71 77 10.1016/j.jik.2017.10.003 64. Chen C-F Chen F-S Experience quality, perceived value, satisfaction and behavioral intentions for heritage tourists Tour. Manag. 2010 31 1 29 35 10.1016/j.tourman.2009.02.008 65. Huang X-J An R Yu M-M He F-F Tourism efficiency decomposition and assessment of forest parks in China using dynamic network Data Envelopment Analysis J. Clean. Prod. 2022 363 132405 10.1016/j.jclepro.2022.132405
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==== Front Ann Surg Oncol Ann Surg Oncol Annals of Surgical Oncology 1068-9265 1534-4681 Springer International Publishing Cham 12936 10.1245/s10434-022-12936-9 Translational Research Human Parvovirus B19 May Be a Risk Factor in Myasthenia Gravis with Thymoma Gong Li MD, PhD 1 Tian Jing MD 1 Zhang Yan MBBS 1 Feng Zheng MD 2 Wang Qiannan MD 1 Wang Yan MD, PhD 3 Zhang Fuqin MBBS 1 Zhang Wei MD, PhD [email protected] 1 Huang Gaosheng MD, PhD [email protected] 14 1 grid.233520.5 0000 0004 1761 4404 Department of Pathology, Helmholtz Sina-German Research Laboratory for Cancer, Tangdu Hospital, Air Force Medical University, Xi’an, People’s Republic of China 2 grid.233520.5 0000 0004 1761 4404 Department of Thoracic Surgery, Tangdu Hospital, Air Force Medical University, Xi’an, People’s Republic of China 3 grid.233520.5 0000 0004 1761 4404 Department of Stomatology, Tangdu Hospital, Air Force Medical University, Xi’an, People’s Republic of China 4 grid.233520.5 0000 0004 1761 4404 State Key Laboratory of Cancer Biology, Department of Pathology, Xijing Hospital, Air Force Medical University, Xi’an, People’s Republic of China 12 12 2022 110 13 7 2022 22 11 2022 © Society of Surgical Oncology 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Purpose Our previous studies have demonstrated that human parvovirus B19 (B19V) is involved in the pathogenesis of thymic hyperplasia-associated myasthenia gravis (MG). However, more cases need to be assessed to further elucidate the relationship between this virus and thymoma-associated MG. Materials and Methods The clinicopathological characteristics, presence of B19V DNA, and B19V VP2 capsid protein expression of 708 cases of thymomas were investigated using nested polymerase chain reaction (PCR), TaqMan quantitative (q) PCR, immunohistochemistry, fluorescent multiplex immunohistochemistry, and electron microscopy. Results Patients with MG or ectopic germinal centers (GCs) were significantly younger than those without MG (P < 0.0001) or GCs (P = 0.0001). Moreover, significantly more GCs were detected in thymomas associated with MG than in those without MG (P < 0.0001). The results of nested PCR and TaqMan qPCR were consistent, and B19V DNA positivity was only associated with presence of GCs (P = 0.011). Immunohistochemically, positive staining was primarily detected in neoplastic thymic epithelial cells (TECs) and ectopic GCs. The positive rate of B19V VP2 was significantly higher in thymoma with MG or GCs than in thymoma without MG (P = 0.004) or GCs (P = 0.006). Electron microscopy showed B19V particles in the nuclei of neoplastic TECs and B cells from GCs. Conclusions We conclude that the pathogenesis of MG is closely associated with the presence of GCs, and B19V infection is plausibly an essential contributor to formation of ectopic GCs in thymoma. To the best of the authors’ knowledge, this is the first study to elucidate the role of B19V in thymoma-associated MG and provide new ideas for exploring the etiopathogenic mechanism of MG. Supplementary Information The online version contains supplementary material available at 10.1245/s10434-022-12936-9. the Natural Science Research Project of Shaanxi ProvinceNo. 2022JM-497 ==== Body pmcMyasthenia gravis (MG) is an autoimmune disease characterized by skeletal muscle fatigue and is directly mediated by different autoantibodies against various components of the neuromuscular junction, primarily the anti-acetylcholine receptor (anti-AChR) antibody. The thymus of individuals with MG contains numerous B-lymphocytes producing antibodies. Thymic abnormalities including thymic hyperplasia and thymoma may contribute to the pathophysiology of MG, in view of the fact that > 80% of patients with early-onset MG present thymic hyperplasia, particularly thymic follicular hyperplasia with ectopic germinal centers (GCs), and 10–15% of MG patients present with comorbid thymoma.1,2 Thymic hyperplasia is characterized by the organization of B-lymphocytes into ectopic GCs or their distribution throughout the thymic medulla. Thymic follicular hyperplasia with GCs significantly contributes to MG pathogenesis.3,4 Thymoma is the most frequent anterior mediastinal tumor originating from thymic epithelial cells (TECs) in adults. Histologically, it is primarily classified in accordance with World Health Organization (WHO) guidelines as type A, AB, B1, B2, and B3 thymoma in addition to other rare types. In general, immature T cells are the most common cell types in thymoma, while B cells are present in small numbers and are less prominent in the thymus. However, ectopic GCs resulting from B-cell infiltration are usually found in thymoma during routine pathological diagnosis; this phenomenon attracts our interest. Similarly, Lefeuvre et al. have reported that presence of GCs in thymoma is a risk factor facilitating the evaluation of the risk of MG,5 but the cause of GCs formation has not been elucidated. In general, chronic inflammation of the thymus caused by a viral or bacterial infection may trigger the development of autoimmunity, generally by activating the host immune system and molecular mimicry, thereby contributing to the pathogenesis of MG. Some studies have demonstrated that intrathymus Epstein–Barr virus (EBV) infection is an environmental risk factor for MG.6,7 However, an increasing number of studies have reported a lack of evidence for EBV infection in the thymus of patients with MG.8-10 Hence, the role of EBV in the pathogenesis of MG remains controversial. Human parvovirus B19 (B19V) is a small, nonenveloped, single-stranded DNA virus that is a member of the genus Erythroparvovirus in the family Parvoviridae.11 It has been reported that B19V is associated with various autoimmune diseases, including systemic lupus erythematosus, Hashimoto’s thyroiditis, and rheumatoid arthritis.12-15 We have previously reported that B19V is closely associated with thymic B-cell hyperplasia, the presence of GCs, and thymic hyperplasia-associated MG. Moreover, the B19V DNA or B19V capsid proteins VP1 and VP2 have been detected in only a few cases of thymoma as the control group.16 Simultaneously, anti-B19V IgG antibodies are associated with MG in the serum of patients with thymoma.17 Based on the aforementioned findings and the vast diagnostic resources available on thymoma, we aim to investigate the clinicopathological characteristics of thymoma, especially the presence of GCs, the expression of human B19V DNA and protein in thymoma, and its association with MG. Materials and Methods Tissue Samples A total of 708 surgically resected specimens with thymoma were retrieved from the Department of Pathology between January 2014 and December 2019. The study protocol was approved by the Medical Ethics Commission of Tangdu Hospital. Informed verbal or written consent was obtained from all patients before surgery. Sixty-six cases of normal thymus tissues were obtained as controls from thymic tissue surgically resected for intrathoracic nodular goiter, congenital heart disease, and thymic cyst. All samples were fixed in 10% neutral formalin and embedded in paraffin. All sections with thymoma were carefully reviewed and diagnosed by three pathologists in accordance with WHO guidelines. Furthermore, their clinicopathological data including sex, age, presence of GCs, and occurrence of MG were documented. MG was clinically diagnosed by physicians, primarily on the basis of the following characteristics: typical clinical manifestation, positive response to cholinesterase inhibitors, and decreased response to repetitive electrical stimulation of the motor nerve. DNA Extraction, Nested PCR, and TaqMan qPCR Five 5-µm-thick tissue sections obtained from representative paraffin blocks were deparaffinized in xylene and rehydrated in a graded ethanol series. Subsequently, genomic DNA was extracted using the TIANamp FFPE DNA Kit (Tiangen, DP331, China) in accordance with the manufacturer’s instructions and stored at − 20 °C until use. Nested PCR was performed to amplify a region of the B19V genome as previously described.15 Finally, the PCR products were visualized by electrophoresis using a 4% polyacrylamide gel, and a band at 173 bp was considered to indicate a positive reaction. TaqMan qPCR was performed as described by Knoll Antje et al.18 using a method calibrated on the basis of serial plasmid dilutions and tested with an international B19V standard to confirm the results of nested PCR. The sequences for two sets of primers and probes were from two conserved regions of the B19V genome coding for NS1 and VP2 proteins. Amplification was performed in a 20 µL reaction volume using 2× TaqMan Fast qPCR Master Mix (Sangon Biotech, Shanghai, B639274).The two reactions were carried out separately on a Cobas Z 480 system (Roche, USA). A sharp exponential rise of the sigmoid curve compared with the relative horizontal line was considered to indicate positive amplification in fluorescence. Nested PCR and TaqMan qPCR were performed in triplicate and included negative and positive controls. Immunohistochemical Staining Immunohistochemistry (IHC) was performed according to the manufacturer’s instructions, and included primary antibodies against mouse anti-B19V VP2 (1:50, Clone R92F6, Merck Millipore/Abcam, USA/UK), CD20 (L26, MXB®, China; 1:400, Clone EP459Y, Abcam, UK), CK19 (A53-B/A2.26, MXB®, China), CD4 (SP35, MXB®, China), and Ki-67 (MIB-1, MXB®, China). Brown staining of nuclei indicated positivity toward B19V VP2. Double immunoenzyme staining was performed for CD20, CK19, CD4, and B19V VP2 to identify the exact phenotype of B19V VP2-positive cells. Red staining of nuclei indicated positivity toward B19V VP2, and brown coloration at the cell membrane indicated positivity for CD20, CK19, and CD4. Fluorescent Multiplex Immunohistochemistry To further highlight cells with B19V VP2 positivity, two cases of thymoma were analyzed using an AlphaTSA Multiplex IHC Kit (Alpha X Biotech CO., LTD, Beijing, China) according to the manufacturer’s manual. The main procedures were as follows: first, after the slides were deparaffinized in xylene, rehydrated in graded alcohol, washed in distilled water, and retrieved in EDTA buffer, the slides were blocked using antibody diluent/block; second, the slides were incubated with primary antibody for 1 h and AlphaX Polymerase HRP Ms+Rb for 10 min at 37 °C; third, the fluorescent dyes included in the kit were used for visualization. After each cycle of staining, heat-induced epitope retrieval was performed to remove the former antibodies. The labeling of CK19, CD20, and B19V VP2 was completed using the methods described above. Finally, the slides were counterstained with DAPI for 5 min and enclosed in Antifade Mounting Medium. The correspondence between primary antibodies and fluorophores was CK19 (XTSA520, Green), CD20 (XTSA570, Red), and B19V VP2 (XTSA690, White). ISH for Epstein–Barr Virus (EBV) To determine whether EBV infection occurs in the thymus of MG patients, EBV was detected via ISH for EBV-encoded RNA (EBER) as gold standard,19 using the Slide Denaturation & Hybridization System (ThermoBrite, S500-24, USA) in accordance with the manufacturer’s instructions (ZSGB-BIO, ISH-7001, China). EBER staining was considered positive if granular, brown reaction products were found in the nucleus. EBER-positive nasal NK/T-cell lymphoma tissue was used as a positive control. Electron Microscopy To provide more evidence for B19V infection in thymoma associated with MG, we randomly selected five diffusely and strongly positive cases of thymoma and two cases of thymoma negative for B19V VP2 to determine the presence of B19V in TECs and/or B cells by electron microscopy. In detail, a piece of tissue approximately 1 mm × 1 mm × 1 mm in size from the paraffin-embedded tissue was first obtained. Then, the tissue was sequentially deparaffinized in xylene, rehydrated in a graded ethanol series, and washed in PB buffer. Finally, the cells were fixed in 4% glutaraldehyde buffer for transmission electron microscopy (Hitachi, HT7800, Japan). Statistical Analysis Data were analyzed using IBM SPSS 25.0 software for Windows (SPSS Inc., Chicago, IL, USA). Differences in clinical parameters between groups were analyzed using Pearson’s chi-squared test and Fisher’s exact test. A two-tailed P value < 0.05 was considered to indicate statistically significant difference. Results Clinicopathological Characteristics of 708 Cases of Thymoma In total, 708 patients with thymoma, including 361 men and 347 women aged 15–77 years (mean age, 52 years; peak, 50–59 years), were recruited from seven provinces in China. Among these, 416 patients were aged ≥ 50 years, and 292 patients were aged < 50 years (Supplementary Table 1; Fig. 1A). The most common histological subtypes of thymoma were AB, B2, B1, B3, and A, accounting for 35.6% (252/708), 28.4% (201/708), 16% (113/708), 8.6% (61/708), and 8.6% (61/708) of the cases, respectively (Supplementary Table 2; Fig. 1B). MG occurred in 33.2% (235/708) of all the thymoma patients; these patients (52.8%, 124/235) were significantly younger than those without MG (35.5%, 168/473) (P < 0.0001) (Supplementary Table 3; Fig. 2). MG occurrence peaked at 40–49 years (Supplementary Table 1; Fig. 1A). Furthermore, the incidence ratio was highest for type B2 thymoma among all subtypes (47.2%, 111/235) (Supplementary Table 2; Fig. 1B). Ectopic GCs were detected in 238 cases (33.6%, 238/708) and were localized in intratumor and/or tumor-adjacent thymus tissues. The GCs occurrence ratio was highest for type B2 thymoma (42.4%, 101/238). Furthermore, patients with GCs (51.3%, 122/238) were significantly younger than those without GCs (36.2%, 170/470) (P = 0.0001). The presence of GCs in thymoma patients with MG comorbidity (51.1%, 120/235) was significantly higher than in those without MG (25%, 118/473) (P < 0.0001) (Supplementary Table 3; Figs. 1B and 2). These results indicated that both MG and GCs primarily occurred among thymoma patients aged < 50 years and that MG was associated with presence of ectopic GCs.Fig. 1 Percentage of patients with and without each parameter in different age groups and subtypes of thymoma. A peak was observed for patients with thymoma, thymoma-associated MG, and presence of GCs in the 50–59, 40–49, and 40–49 year groups, respectively (A); a peak was observed for patients with thymoma-associated MG, GCs, B19V DNA positivity, and B19V VP2 positivity in type B2 thymoma (B) Fig. 2 Differences in clinical parameters in thymoma patients with and without MG, GCs, and B19V DNA amplification. Patients with MG or ectopic GCs were significantly younger than those without MG (P < 0.0001) or GCs (P = 0.0001). In addition, significantly more GCs were detected in thymoma patients with MG than in those without MG (P < 0.0001). The positivity rate of B19V DNA was only associated with presence of GCs (P = 0.011). The positivity rate of B19V VP2 was significantly higher in thymoma patients with MG or GCs than in those without MG (P = 0.004) or GCs (P = 0.006) Detection of B19V DNA through Nested PCR and TaqMan qPCR A DNA fragment (predicted size 173 bp) corresponding to B19V DNA was amplified as a marker of B19V infection in 38 (5.4%) of 708 thymomas (Supplementary Tables 1, 2; Supplementary Fig. 1); however, no such fragment was amplified in 66 normal thymus tissue samples. Furthermore, the positivity rate of B19V DNA was significantly higher in thymoma harboring GCs (8.4%, 20/238) than among those without GCs (3.8%, 18/470) (P = 0.011) (Supplementary Table 3; Fig. 2). However, no significant difference was noted in MG, sex, or age of the patients (Supplementary Tables 3, 4; Fig. 2). These results indicated that B19V DNA was only associated with presence of ectopic GCs. In other words, B19V infection in the thymus potentially contributed to the formation of ectopic GCs, subsequently inducing MG. The results of TaqMan qPCR were consistent with those of nested PCR. In detail, 38 cases with nested PCR positive amplification were positive for the VP2 genomic region but negative for the NS1 genomic region. However, 66 normal thymus tissue samples were negative for the VP2 and NS1 genomic regions. Detection of B19V VP2 Proteins via IHC and Fluorescent Multiplex IHC IHC staining results demonstrated that 135 thymoma specimens (19.1%, 135/708) were positive for B19V VP2, with positive staining primarily observed in neoplastic TECs and ectopic GCs located in tumors and/or tumor-adjacent thymic tissues (Supplementary Tables 1, 2; Figs. 1 and 3). Of course, only thymomas with neoplastic TEC staining were considered positive. Moreover, the positivity ratio was highest for type B2 thymoma, followed by types B1, B3, and AB thymoma (Supplementary Table 2; Fig. 1B). However, only neoplastic TECs from type A thymoma were negative (Fig. 4A), as were 66 samples of normal thymus tissue. In addition, the positivity rate was significantly higher in thymoma with MG (25.1%, 59/235) than in thymoma without MG (16.1%, 76/473) (P = 0.004). Similarly, the positivity rate was significantly higher in thymoma patients with GCs (24.8%, 59/238) than in those without GCs (16.2%, 76/470) (P = 0.006) (Supplementary Table 3; Fig. 2). The positivity rate was slightly, but not significantly, higher among patients aged < 50 years (22.3%, 65/292) than among those aged ≥ 50 years (16.83%, 70/416) (P = 0.070). Furthermore, no significant difference in sex was observed (P = 0.118). However, the positivity ratio of B19V VP2 was not associated with positivity (23.7%, 9/38) or negativity (18.8%, 126/670) for B19V DNA (P = 0.457) (Supplementary Table 4). These results indicate that B19V VP2 is associated with MG and/or presence of GCs, further indicating that B19V infection in the thymus potentially contributes to the formation of ectopic GCs, subsequently promoting MG pathogenesis.Fig. 3 Expression and cellular distribution of B19V VP2 protein in different subtypes of thymomas and germinal centers (GCs). The nuclei positive for the B19V VP2 protein were mainly found in ectopic GCs (A, 100×; B, 400×) and neoplastic TECs in the different subtypes of thymoma: type B1 (C, 400×), type B2 (D, 400×), type B3 (E, 400×), and type AB (F, 400×) Fig. 4 Results of IHC, double-labeled IHC, and ISH. Neoplastic TECs from type A thymoma were negative for B19V VP2 (A, 400×). Double-labeled immunohistochemical staining for CD20, CK19, CD4, and B19V VP2 showed that the nuclei of B cells from ectopic GCs (B, 400×) and neoplastic TECs (C, 400×) were strongly and diffusely positive for B19V VP2. Simultaneously, the cell membrane of B cells from ectopic GCs and neoplastic TECs was positive for CD20 (B, 400×) and CK19 (C, 400×) but negative for CD4 (D, 400×). In addition, no positive cases were obtained for EBER (E, 400×), the positive control of EBER (F, 400×) Double-labeled immunohistochemical staining using CD20, CK19, CD4, and B19V VP2 showed that the nuclei of B cells from ectopic GCs and neoplastic TECs were strongly positive for B19V VP2. Simultaneously, the cell membranes of B cells from ectopic GCs and neoplastic TECs were positive for CD20 (Fig. 4B) and CK19 (Fig. 4C), respectively, but negative for CD4 (Fig. 4D). However, only a very few thymus reticular epithelial cells were weakly positive for B19V VP2 in normal thymus tissues. Similarly, the results of fluorescent multiplex IHC were consistent with those of double-labeled immunohistochemical staining using CD20, CK19, and B19V VP2 (Fig. 5A–J).Fig. 5 Results of fluorescent multiplex IHC. Similarly, the results of fluorescent multiplex IHC were consistent with those of double-labeled immunohistochemical staining using CD20, CK19, and B19V VP2 (A–J). Namely, the nuclei of B cells (C) and neoplastic TECs (H) were positive for B19V VP2. Simultaneously, the cell membrane of B cells from ectopic GCs and neoplastic TECs was positive for CD20 (B, G) and CK19 (A, F), respectively. Panels E and J showed that some cells were positive for both B19V VP2 and CD20, and other cells were positive for both B19V VP2 and CK19 Detection of EBV via ISH To elucidate whether EBV infection exists in thymoma tissues, we observed the expression of EBER in 708 thymoma samples via ISH. The results demonstrated that none of the cases were positive for EBER compared with the positive control (Fig. 4E, F). Electron Microscopy Electron microscopy showed the presence of B19V particles (diameter range 19.7–25.6 nm) in the nuclei of TECs and B cells from GCs in all five cases of thymoma with diffuse and strong positivity for B19V VP2 (Fig. 6A–F) but not in two cases of thymoma with immunohistochemical negativity for B19V VP2 (Fig. 6G–I), confirming B19V infection.Fig. 6 Electron microscopy of seven cases of thymoma. B19V particles were found in the nuclei of TECs (A, ×21.0k; B, ×70.0k; C, ×170k) and B cells (D, ×21.0k; E, ×70.0k; F, ×170k) from GCs in five thymomas that were diffusely and strongly positive for B19V VP2, but no B19V particles were found in the nuclei of TECs (G, ×21.0k; H, ×170k; I, ×170k) in two thymomas that were immunohistochemically negative for B19V VP2, further confirming the presence of B19V infection Discussion Thymic abnormalities including thymic hyperplasia and thymoma play a crucial role in MG pathogenesis, and approximately 30% of patients with thymoma have comorbid MG; however, this rate varies widely from 17% to 67%.20,21 Recently, Lefeuvre et al. reported an extraordinarily high rate (78.7%) of MG among patients with thymoma. Moreover, 58.8% of the patients presented ectopic GCs. Thus, they conclude that the presence of ectopic GCs is a potential risk factor for MG occurrence.5 In this study, we found that the positivity rate of MG was 33.2% in thymoma, which is consistent with that reported in most studies. Simultaneously, we noticed that the presence of GCs in patients with MG comorbidity (51.1%) was significantly higher than in those without MG (25%), confirming the above conclusion. Namely, the presence of ectopic GCs may contribute to the occurrence of thymoma-associated MG. In addition, we found that patients with MG or GCs were significantly younger than those without MG or GCs. More interestingly, type B2 thymoma registered the highest incidence ratio of MG and GCs among all types of thymoma. However, the causes of abnormal B-cell proliferation and the formation of ectopic GCs in thymoma remain unknown. This is the primary feature of target organs characterized by chronic inflammation with B-cell infiltration, especially ectopic GCs formation, in numerous organ-specific autoimmune diseases, and it is also a significant feature of the thymus of MG patients.22,23 Infection with pathogens such as viruses or bacteria is the primary factor leading to chronic thymus inflammation. EBV is one of the most concerning viruses in the literature regarding the correlation between viruses and MG with thymus abnormalities, but the role of EBV in the pathogenesis of MG remains controversial.6-10 Thus, in this study, we mainly explored the role of B19V, a virus playing a similar role to EBV in autoimmune diseases, in thymoma, and further investigated EBV status. B19V was first discovered by Cossart et al. in 1975.24 However, its effect on humans can be traced back hundreds or even thousands of years.25 Moreover, despite their strong erythroid tropism and related acute disease association, B19V RNA or capsid proteins have been reported in many other nonerythroid tissues, including thymus tissues.13-16 The expression of B19V in the above tissues was also associated with specific changes in the expression of inflammatory genes, demonstrating that persistent B19V expression can impact the cellular microenvironment. In addition, an increasing number of studies have demonstrated that B19V is associated with various autoimmune diseases.12-15 Simultaneously, based on our previous findings, including the relationship between anti-B19V IgG antibodies in the serum of patients with thymoma and MG and the presence of B19V DNA and B19V VP2 in a few cases of thymoma,16,17 we performed further research with an abundant number of samples using nested PCR, TaqMan qPCR, immunohistochemistry, fluorescent multiplex immunohistochemistry, and electron microscopy. The results demonstrated that the pathogenesis of MG is closely associated with the presence of GCs, and B19V infection is a plausible essential contributor to formation of ectopic GCs in thymoma. Concordant with the results of a previous study that virus RNA might persist in lymphoid tissue accompanied by ongoing proliferation of GCs,26 we found the presence of both B19V DNA and protein in the proliferative GCs of thymoma-associated MG. These results further indicate that B19V infection might cause B-cell proliferation and formation of ectopic GCs, subsequently leading to thymoma-associated MG. Moreover, it has recently been reported that formation of GCs markedly antagonizes other viral infections, such as influenza vaccines and coronavirus disease 2019 (COVID-19) antibodies.27-29 Thus, B19V infection of B cells and ectopic GCs in the thymus with MG provides another robust example of the association between viral infection and formation of GCs and extends current understanding of the pathogenesis of this autoimmune disease. Surprisingly, neoplastic TECs from type A thymoma displayed negative staining for B19V VP2; however, types B2, B1, B3, and AB thymoma were positive, and the results were confirmed by electron microscopy. Moreover, the positivity ratio peaked for type B2 thymoma, followed by types B1, B3, and AB thymoma. These results indicate that B19V VP2 expression is primarily associated with thymoma originating in cortical epithelial cells. In other words, B19V potentially affects TECs in addition to B cells in ectopic GCs. However, further studies are required to elucidate the underlying mechanism. Of course, our studies present some unexplained results and limitations. For example, B19V messenger RNA (mRNA) expression levels were not provided in the study. In fact, we have tried our best to observe it by various methods described in literature, but they do not seem feasible. In addition, the positivity rate of B19V DNA and protein expression is inconsistent. We speculate that there may be two possible explanations. One is that this may be due to clearance of B19V owing to superinfection with a second virus or because of the persistence of viral antigens in lymphoid tissues during the immunological memory phase, as previously described by Wietzke et al. and Klenerman et al.30,31 The other is that B19V may cause MG only when viral replication and/or load reaches a certain threshold. In fact, this phenomenon was noted not only in studies of B19V but also in those of other viruses, especially hepatitis B virus.32-37 Thus, more research is required to elucidate this phenomenon. In conclusion, this study shows that B19V infection may cause B-cell proliferation and formation of ectopic GCs, subsequently leading to thymoma-associated MG. To the best of the authors’ knowledge, this is the first report of the presence of B19V in TECs and ectopic GCs, revealing an unrecognized etiopathogenic mechanism for thymoma-associated MG. However, further studies are required to elucidate the role of B19V in thymic abnormalities with MG. Supplementary Information Below is the link to the electronic supplementary material.Supplementary file1 (DOC 104 kb) Acknowledgment This work was supported by the Natural Science Research Project of Shaanxi Province (no. 2022JM-497) Disclosure The authors have declared no conflicts of interests. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Li Gong and Jing Tian have been equally contributed to the work. ==== Refs References 1. Leite MI Jones M Ströbel P Myasthenia gravis thymus: complement vulnerability of epithelial and myoid cells, complement attack on them, and correlations with autoantibody status Am J Pathol. 2007 171 893 905 10.2353/ajpath.2007.070240 17675582 2. Cavalcante P Bernasconi P Mantegazza R Autoimmune mechanisms in myasthenia gravis Curr Opin Neurol. 2012 25 621 629 10.1097/WCO.0b013e328357a829 22941261 3. Berrih-Aknin S Ruhlmann N Bismuth J CCL21 overexpressed on lymphatic vessels drives thymic hyperplasia in myasthenia Ann Neurol. 2009 66 521 531 10.1002/ana.21628 19847900 4. Fujii Y Monden Y Nakahara K Hashimoto J Kawashima Y Antibody to acetylcholine receptor in myasthenia gravis: production by lymphocytes from thymus or thymoma Neurology. 1984 34 1182 1186 10.1212/WNL.34.9.1182 6611521 5. Lefeuvre CM Payet CA Fayet OM Risk factors associated with myasthenia gravis in thymoma patients: The potential role of thymic germinal centers J Autoimmun. 2020 106 102337 10.1016/j.jaut.2019.102337 31594658 6. Cavalcante P Maggi L Colleoni L Inflammation and epstein-barr virus infection are common features of myasthenia gravis thymus: possible roles in pathogenesis Autoimmune Dis. 2011 2011 213092 21961056 7. Cavalcante P Serafini B Rosicarelli B Epstein-Barr virus persistence and reactivation in myasthenia gravis thymus Ann Neurol. 2010 67 726 738 20517934 8. Meyer M Höls AK Liersch B Lack of evidence for Epstein-Barr virus infection in myasthenia gravis thymus Ann Neurol. 2011 70 515 518 10.1002/ana.22522 21905083 9. Kakalacheva K Maurer MA Tackenberg B Münz C Willcox N Lünemann JD Intrathymic Epstein-Barr virus infection is not a prominent feature of myasthenia gravis Ann Neurol. 2011 70 508 514 10.1002/ana.22488 21905082 10. Jing F Wei D Wang D Lack of Epstein-Barr virus infection in Chinese myasthenia gravis patients Acta Neurol Scand. 2013 128 345 350 23668247 11. Cotmore SF Agbandje-McKenna M Chiorini JA The family Parvoviridae Arch Virol. 2014 159 1239 1247 10.1007/s00705-013-1914-1 24212889 12. Hsu TC Tsay GJ Human parvovirus B19 infection in patients with systemic lupus erythematosus Rheumatology (Oxford). 2001 40 152 157 10.1093/rheumatology/40.2.152 11257151 13. Takahashi Y Murai C Shibata S Human parvovirus B19 as a causative agent for rheumatoid arthritis Proc Natl Acad Sci USA 1998 95 8227 8232 10.1073/pnas.95.14.8227 9653169 14. Adamson LA Fowler LJ Clare-Salzler MJ Hobbs JA Parvovirus B19 infection in Hashimoto’s thyroiditis, papillary thyroid carcinoma, and anaplastic thyroid carcinoma Thyroid. 2011 21 411 417 10.1089/thy.2010.0307 21190433 15. Wang J Zhang W Liu H Parvovirus B19 infection associated with Hashimoto’s thyroiditis in adults J Infect. 2010 60 360 370 10.1016/j.jinf.2010.02.006 20153771 16. Gong L Li Y Li X Detection of human parvovirus B19 infection in the thymus of patients with thymic hyperplasia-associated myasthenia gravis Clin Microbiol Infect. 2019 25 109.e7 e12 10.1016/j.cmi.2018.03.036 17. Jia X Gong L Zhang J Detection of IgM and IgG antibodies to human parvovirus B19 in sera of patients with thymoma-associated myasthenia gravis Viral Immunol. 2021 34 4 213 217 10.1089/vim.2020.0126 33124969 18. Knöll A Louwen F Kochanowski B Parvovirus B19 infection in pregnancy: quantitative viral DNA analysis using a kinetic fluorescence detection system (TaqMan qPCR) J Med Virol. 2002 67 259 266 10.1002/jmv.2216 11992588 19. Gulley ML Tang W Laboratory assays for Epstein-Barr virus-related disease J Mol Diagn. 2008 10 279 292 10.2353/jmoldx.2008.080023 18556771 20. Padda SK Yao X Antonicelli A Paraneoplastic syndromes and thymic malignancies: an examination of the International Thymic Malignancy Interest Group Retrospective Database J Thorac Oncol. 2018 13 436 446 10.1016/j.jtho.2017.11.118 29191778 21. Maggi G Casadio C Cavallo A Cianci R Molinatti M Ruffini E Thymoma: results of 241 operated cases Ann Thorac Surg. 1991 51 152 156 10.1016/0003-4975(91)90478-9 1985561 22. Cron MA Maillard S Villegas J Thymus involvement in early-onset myasthenia gravis Ann N Y Acad Sci. 2018 1412 137 145 10.1111/nyas.13519 29125185 23. Truffault F de Montpreville V Eymard B Sharshar T Le Panse R Berrih-Aknin S Thymic germinal centers and corticosteroids in myasthenia gravis: an immunopathological study in 1035 cases and a critical review Clin Rev Allergy Immunol. 2017 52 108 124 10.1007/s12016-016-8558-3 27273086 24. Cossart YE Field AM Cant B Widdows D Parvovirus-like particles in human sera The Lancet 1975 305 72 73 10.1016/S0140-6736(75)91074-0 25. Mühlemann B Margaryan A Damgaard PB Ancient human parvovirus B19 in Eurasia reveals its long-term association with humans Proc Natl Acad Sci USA 2018 115 7557 7562 10.1073/pnas.1804921115 29967156 26. Tian M Hua Z Hong S B Cell-intrinsic MyD88 signaling promotes initial cell proliferation and differentiation to enhance the germinal center response to a virus-like particle J Immunol. 2018 200 937 948 10.4049/jimmunol.1701067 29282308 27. Turner JS Zhou JQ Han J Human germinal centres engage memory and naive B cells after influenza vaccination Nature. 2020 586 127 132 10.1038/s41586-020-2711-0 32866963 28. Kaneko N Kuo HH Boucau J Loss of Bcl-6-expressing T follicular helper cells and germinal centers in COVID-19 Cell. 2020 183 143 157.e13 10.1016/j.cell.2020.08.025 32877699 29. Fallet B Hao Y Florova M Chronic viral infection promotes efficient germinal center B cell responses Cell Rep. 2020 30 1013 1026.e7 10.1016/j.celrep.2019.12.023 31995746 30. Wietzke P Schott P Braun F Mihm S Ramadori G Clearance of HCV RNA in a chronic hepatitis C virus-infected patient during acute hepatitis B virus superinfection Liver. 1999 19 348 353 10.1111/j.1478-3231.1999.tb00060.x 10459635 31. Klenerman P Hengartner H Zinkernagel RM A non-retroviral RNA virus persists in DNA form Nature. 1997 390 298 301 10.1038/36876 9384383 32. Ye X Li T Zhang R Comprehensive analysis of hepatitis B virus infections in blood donors in southern China that are surface antigen positive but nucleic acid testing negative Transfusion. 2020 60 1476 1482 10.1111/trf.15824 32358842 33. Arase Y Suzuki F Suzuki Y Long-term presence of HBV in the sera of chronic hepatitis B patients with HBsAg seroclearance Intervirology. 2007 50 161 165 10.1159/000098958 17259734 34. Lee HS Yoon JH Kim CY Frequent reactivations of anti-HBe-positive chronic hepatitis B in patients with no demonstrable HBV DNA in serum by polymerase chain reaction Korean J Intern Med. 1995 10 103 107 10.3904/kjim.1995.10.2.103 7495767 35. Moestrup T Hansson BG Widell A Blomberg J Nordenfelt E Hepatitis B virus-DNA in the serum of patients followed-up longitudinally with acute and chronic hepatitis B J Med Virol. 1985 17 337 344 10.1002/jmv.1890170406 4078560 36. Kido S Ito Y Nishimura N Kajita Y Ozaki T Human parvovirus B19-associated thrombocytopenic purpura Acta Paediatr Jpn. 1998 40 486 488 10.1111/j.1442-200X.1998.tb01975.x 9821713 37. Rao SP Miller ST Cohen BJ Transient aplastic crisis in patients with sickle cell disease. B19 parvovirus studies during a 7-year period Am J Dis Child. 1992 146 1328 30 10.1001/archpedi.1992.02160230086025 1415073
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==== Front Financ Res Lett Financ Res Lett Finance Research Letters 1544-6123 1544-6131 Elsevier Inc. S1544-6123(22)00721-8 10.1016/j.frl.2022.103545 103545 Article COVID-19 and risk spillovers of China's major financial markets: Evidence from time-varying variance decomposition and wavelet coherence analysis Xie Qiwei a Cheng Lu a Liu Ranran a Zheng Xiaolong b Li Jingyu a⁎ a School of Economics and Management, Beijing University of Technology, Beijing 100124, China b Institute of Automation, Chinese Academy of Sciences, Beijing 100000, China ⁎ Corresponding author at: Assistant Professor, School of Economics and Management, Beijing University of Technology, No.100, Pingleyuan, Chaoyang District, Beijing 100124, China. 29 11 2022 3 2023 29 11 2022 52 103545103545 17 12 2020 23 11 2022 23 11 2022 © 2022 Elsevier Inc. All rights reserved. 2022 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. COVID-19 has influenced financial markets drastically; however, this influence has received little attention, particularly in China. This study investigates risk spillovers across China's financial and shipping markets through dynamic spillover measures based on time-varying parameter vector autoregression and generalized forecast error variance decompositions. Stock, fund, and futures markets are identified as major risk senders, whereas other markets are identified as major risk receivers. Surprisingly, bonds, gold, and shipping are safe havens that facilitate portfolio optimization. Furthermore, using wavelet coherence analysis, we find that the coherence between dynamic total spillover and COVID-19 varies across time and frequency domains. Keywords COVID-19 Risk spillovers Generalized forecast error variance decompositions Wavelet coherence analysis China's financial markets ==== Body pmc1 Introduction The widespread transmission of a novel coronavirus (COVID-19) led to the declaration of a pandemic on March 11, 2020, which severely affected the economy in multiple ways, including increasing unemployment, investors’ concerns, and risk aversion; decreasing global aviation activities and ship transportation; interrupting the supply chain; and reducing international trade (Amankwah, 2020; Choquet and Lefebvre, 2021; Couch et al., 2020; El Baz and Ruel, 2020; Le et al., 2020; Sun et al., 2021). All of these factors affected financial market stability. Unemployment reduced income, thereby reducing financial market investments. In particular, the decline in aviation activities triggered a massive decline in energy demand, and the drop in ship transportation caused an inventory squeeze, thereby affecting commodity futures markets. Meanwhile, the banking system has increased credit allocation to revive enterprises hurt by reduced international trade and supply chain disruptions. Thus, banks’ credit risks rose due to the poor performance of companies supported during COVID-19 (Zhu et al., 2021). Moreover, negative sentiment caused by COVID-19 encouraged investors to switch markets (Broadstock et al., 2020). Recent literature has analyzed the pandemic's effects on financial markets from multiple perspectives. Some literature describes the pandemic's impact on one financial asset: risk spillovers and stock market herding (Bouri et al., 2021; Samitas et al., 2022a; Li et al., 2021). Researchers also found a long-term increase in bank defaults and nonperforming loans (Polyzos et al., 2021), overshooting in the Eurobonds market (Sene et al., 2020), and instability in the global and “B&R” initiative forex markets (Wei et al., 2020). Other studies focused on financial assets. For example, Samitas et al. (2022b) investigated volatility spillover in wine, stocks, bonds, gold, shipping, etc. Furthermore, Samitas et al. (2022c) found that timber and water hedge shipping risk during COVID-19. However, risk spillovers across China's financial and shipping markets have received little attention in the literature. Chinese financial markets are rapidly developing and becoming influential in global financial markets (Fang et al., 2021; Cao and Xie, 2022). The shipping market played an irreplaceable role in global supply chains and international trade, thereby affecting financial markets (Gong et al., 2020; Yang et al., 2022). The Chinese economy was affected by the COVID-19 pandemic (Kim et al., 2021) in multiple ways, including an increase in unemployment and risk aversion, the interruption of supply chains, and a reduction in international trade, thereby generating risk spillover across Chinese financial and shipping markets (Dai et al., 2022; Mensi et al., 2021; Si et al., 2021). This study examines risk spillovers across China's financial markets and shipping market during COVID-19. It offers three contributions. First, this is the first study to quantitatively analyze risk spillovers across China's major financial markets during COVID-19. Second, we also consider the shipping market. It supplements the literature that has rarely considered this market. Third, using sentiment indexes reflecting public attention and panic regarding COVID-19 (Fang et al., 2020; Ji et al., 2019), we show that the pandemic has affected the dynamic total spillover across China's major financial and shipping markets in different frequencies. The remainder of this study is as follows: Section 2 presents the methodology. Section 3 introduces the data. Section 4 discusses empirical results, and Section 5 concludes. 2 Methodology This section describes the methodologies employed to study the coherence between COVID-19 and risk spillovers across China's financial and shipping markets. First, risk spillovers are calculated through dynamic spillover measures based on a time-varying parameter vector autoregression (TVP-VAR) model and generalized forecast error variance decompositions (GFEVD). Second, wavelet coherence analysis verifies the correlation between the pandemic and dynamic total spillover. 2.1 Spillover estimation based on TVP-VAR and GFEVD Following Antonakakis and Gabauer (2017), we employ a stationary TVP-VAR with time-varying returns:(1) Yt=βtYt−1+εtεt∼N(0,St), (2) βt=βt−1+ωtωt∼N(0,Rt), (3) Yt=Atεt−1+εt, where Yt, εt, and ω t are N X 1 vectors, and At, St, β t, and Rt are N X N matrices. According to Diebold and Yilmaz (2012), J. Li et al. (2021), Li et al. (2022), the h-step error variance in forecasting variable i due to shocks on variable j can be written as follows:(4) γ∼ij,tg(h)=∑t=1h−1Ψij,t2,g∑t=1N∑t=1h−1Ψij,t2,g With γ˜ij,tg(h) denotes the h-step ahead GFEVD, γij,tg(h)=Sij,t−12Ah,t∑tεij,t ∑t the covariance matrix for the error εij,t and ∑j=1Nγ˜ij,tg(h)=1, ∑i,j=1Nγ˜ij,tN(h)=N. The total spillover index of all the markets is defined as follows:(5) TStg(h)=∑i,j=1,i≠jNγ˜ij,tg(h)∑j=1Nγ˜ij,tg(h)×100 The “to,” “from,” and net spillovers indexes are defined as follows, respectively:(6) NSj←i,tg(h)=∑j=1,i≠jNγ∼ji,tg(h)∑j=1Nγ∼ji,tg(h)×100 (7) NSi←j,tg(h)=∑j=1,i≠jNγ˜ij,tg(h)∑i=1Nγ˜ij,tg(h)×100 (8) NSi,tg=NSj←i,tg(h)−NSi←j,tg(h) 2.2 Wavelet coherence analysis Following Grinsted et al. (2004), we defined the wavelet coherence of two-time series as follows:(9) Rn2(s)=|S(s−1WnXY(s))|2S(s−1|WnX(s)|2)·S(s−1|WnY(s)|2) where S is a smoothing operator and can be written as:(10) S(W)=Sscale(Stime(Wn(s))) where Sscale denotes smoothing along the wavelet scale axis and Stime smoothing in time. The Morlet wavelet is given as follows:(11) Stime(W)|s=(Wn(s)*c1−t22s2) (12) Sscale(W)|n=(Wn(s)*c2∏(0.6s))|n where c1 and c2 are normalization constants and Π is the rectangle function. The factor of 0.6 is the empirically determined scale decorrelation length for the Morlet wavelet (Grinsted et al., 2004). 3 Data and preliminary analysis We collect data on China's major financial and shipping markets from January 20, 2020, to May 26, 2022, from the WIND database. Table 1 lists indices and their descriptions.Table 1 Products and introductions. Table 1No Markets Indices Descriptions 1 Stock CSI 300 Index The CSI 300 Index is a representative Chinese stock index that reflects market changes. 2 Fund CSI Fund Index The CSI Open-end Fund Index includes all open-end funds, except currency and capital-guaranteed funds. 3 Bond CSI Aggregate Bond Index The CSI Aggregate Bond Index includes treasury, financial, and corporate bonds from interbank and Shanghai and Shenzhen Stock Exchange bond markets. 4 Interbank Shanghai Interbank Offered Rate Interbank lending rate hikes reveal a banking sector liquidity shortage. 5 Forex US Dollar/RMB Spot Exchange Rate The rise and fall of the US Dollar/RMB spot exchange rate affects import and export trade and economic structure. 6 Futures Total Commodity Index The Wind Commodities Index includes precious metals, nonferrous metals, petrochemicals, grains, energy, oil, and fats. 7 Gold AU9995 Spot Price The AU9995 is circulated among industrial companies, and its changes can reflect China's stock market. 8 Shipping China Dry Bulk Freight Index The China Dry Bulk Freight Index reflects China's bulk commodity transportation market. Notes: Following Corbet et al. (2021); Hong et al. (2010); Qin et al. (2018); Yao et al. (2020); Zhang et al. (2020), and Zhu et al. (2020), we selected eight indices in Table 1 as the proxy variables to represent the stock, fund, bond, interbank, forex, futures, gold, and shipping markets, respectively. Fig. 1 displays all market returns. During the sample period, all market returns are volatile. Therefore, stock, interbank, and forex markets have negative mean returns under COVID-19, whereas other markets have positive ones (Table 2 ). Meanwhile, the interbank market is the most volatile, with a standard deviation of 5.113. All markets have different skewness and high kurtosis (>3), thereby indicating high-peak and fat-tail phenomena. The Augmented Dickey–Fuller (ADF) test proves that the data are stationary.Fig. 1 Returns of Chinese financial and shipping markets. Fig 1 Table 2 Products and introductions. Table 2 Mean Min. Max. Std. Dev. Skewness Kurtosis ADF Stock −0.007 −5.068 5.513 1.321 −0.346 4.623 −9.352⁎⁎⁎ Fund 0.019 −2.343 1.880 0.655 −0.493 3.808 −8.805⁎⁎⁎ Bond 0.018 −0.437 0.949 0.083 2.418 34.775 −6.940⁎⁎⁎ Interbank −0.072 −35.435 20.108 5.113 −0.432 8.811 −10.756⁎⁎⁎ Forex −0.003 −1.436 1.026 0.257 −0.298 8.995 −7.303⁎⁎⁎ Futures 0.059 −5.260 5.309 1.348 −0.286 4.710 −7.631⁎⁎⁎ Gold 0.027 −6.254 5.188 1.004 −0.579 7.583 −8.741⁎⁎⁎ Shipping 0.138 −10.407 23.546 2.277 2.049 23.666 −6.294⁎⁎⁎ Notes: Table 2 displays the statistical information for the return series of financial and shipping markets, including Mean, Min, Max, Std. Dev, Skewness, Kurtosis, and ADF. *, **, and *** denote significance at the 5%, 1%, and 0.1% levels. 4 Empirical results 4.1 Spillover across the markets First, we discuss the dynamic total spillover of China's major financial and shipping markets. Fig. 2 shows that after human-to-human transmission was confirmed on January 20, 2020, dynamic total spillover increased and peaked (peak value = 53.832) on February 10, 2020. With anti-epidemic measures in place, risk spillover gradually decreased, even lower than pre-pandemic levels (Dai et al., 2022; Dai and Zhu, 2022). From February 24, 2022, the dynamic total spillover increased again and peaked at 30.64 on March 17, 2022. This is likely because the Federal Reserve rate hike raised concerns about increased market volatility and decreased market liquidity. Furthermore, it is partly attributed to the Russia–Ukraine war, which induced turbulence in the international energy market, raised uncertainties in global financial markets, and increased risk spillovers in China's markets.Fig. 2 Dynamic total spillover across China's major financial and shipping markets. Fig 2 According to Fig. 3 and Table 3 , the stock, fund, and futures markets are the senders of net risk spillovers, whereas other markets are receivers. Huge transaction scale and high leverage in stock, fund, and futures markets amplify senders’ shock risks (El-Alaoui et al., 2018). Meanwhile, receivers benefit from the positive returns of bond, gold, and shipping markets, which are considered safe-haven assets to some extent.Fig. 3 Net spillovers across China's financial and shipping markets. Notes: Positive net spillover value means its corresponding market is a risk sender, whereas a negative one indicates that it is a risk receiver. Fig 3 Table 3 To, from, and net spillovers across all markets. Table 3 Stock Fund Bond Interbank Forex Futures Gold Shipping From Stock 43.96 37.95 1.25 1.08 6.07 7.04 1.93 0.72 56.04 Fund 39.06 45.25 0.46 1.22 4.71 6.63 2.31 0.34 54.75 Bond 3.53 2.02 80.30 1.67 1.46 1.82 3.42 5.78 19.70 Interbank 2.32 2.18 2.10 89.02 0.77 0.78 1.04 1.79 10.98 ForEx 9.63 7.12 1.50 0.78 69.76 5.97 3.69 1.54 30.24 Futures 8.61 7.69 1.10 0.42 4.54 66.67 9.67 1.30 33.33 Gold 3.20 3.57 2.24 0.46 3.89 12.60 73.08 0.96 26.92 Shipping 0.84 0.53 5.57 1.15 1.79 1.68 1.21 87.22 12.78 To 67.19 61.07 14.21 6.78 23.23 36.52 23.29 12.43 244.73 Net 11.15 6.33 −5.49 −4.20 −7.01 3.19 −3.63 −0.35 TS=30.59 Notes: This table shows financial and shipping markets risk spillovers. “To” denotes spillovers from variable i to all variables j except diagonal. “From” represents off-diagonal spillovers from variables j to i. Finally, “To” minus “From” equals the value of “Net” spillover. Positive net spillover value indicates that its corresponding market is a risk sender, whereas a negative one indicates that it is a risk receiver. The bond market is characterized as fixed income, and its price fluctuation is weakly or negatively correlated with the economic cycle, stock market, and other major assets during COVID-19, thereby allowing risk diversification. Combined with lasting negative net risk spillovers (Fig. 3), its role as a safe-haven asset is stable (Choudhury et al., 2022). Investors buy gold to hedge against high inflation caused by massive currency issuance during the pandemic. However, Fig. 3 shows that net risk spillovers received by gold decreased from March 11, 2020, to March 24, 2020, and February 11, 2022, to March 11, 2022, thereby indicating that gold's role as a safe haven has diminished due to the gold spot market being largely affected by oil shocks (Salisu et al., 2020; Wang et al., 2020). The former reduction of net risk spillover is attributed to the decreased demand for oil during COVID-19 and a failed oil production deal between Organization of the Petroleum Exporting Countries and Russia, whereas the latter arises from energy market uncertainty caused by the Russia–Ukraine war. Even though gold is considered a safe-haven asset (Bouri et al., 2021; Das et al., 2020), its hedge effect is not permanent. Similarly, the shipping market's role has changed from receiver to sender after February 2021, thereby indicating that its role as a safe haven has diminished. The rapid recovery of US import demand and lack of resources and information in the supply chain have accumulated shipping market risk in China and spillover to other financial markets. Therefore, investors should carefully evaluate whether to use it as a safe-haven asset. Additionally, stock and fund markets have the largest “to” spillovers (39.06 and 37.95, respectively), thereby indicating their close association during the crisis (Table 3). The main reason is probably that the stock position rose to approximately 80% in stock funds after the revised version of Measures for the Administration of the Operations of Publicly Offered Securities Investment Funds issued by China Securities Regulatory Commission on August 8th, 2015, in China (Wang and Wang, 2018), thereby causing information spillover (Kim et al., 2016). Furthermore, the biggest risk spillover (9.63) to the forex market comes from the stock market (Li et al., 2021). China's leadership in stabilizing the pandemic and economic recovery increased investor confidence, caused a surge in foreign capital in China, and boosted demand for RMB in the forex market. This study could be beneficial for policymakers and investors. Policymakers must notice strong dynamic interactions between two markets, such as, stock–futures pair. For investors, we evidenced that bond, gold, and shipping markets are safe-haven assets, but their roles differ. In the dynamic term, the bond market remains a stable safe haven. However, gold and shipping markets have a strong hedge effect at the beginning of the pandemic, but it diminishes afterward. 4.2 Relationship between the COVID-19 pandemic and dynamic total spillover Using wavelet coherence analysis (Gulerce and Unal, 2016) in time and frequency domains, we examine the relationship between dynamic total spillover across markets and COVID-19 represented by “XG” and “YQ” (Baidu indexes of “Xinguan” and “Yiqing”), which reflect public attention and panic regarding the pandemic, respectively. Fig. 4 shows the estimated wavelet coherence for dynamic total spillover and XG (YQ), thereby demonstrating that the pandemic affects all markets’ dynamic total spillover. Table 4 summarizes the periods when dynamic total spillover and COVID-19 are highly correlated based on Fig. 4.Fig. 4 (a) “XG” and dynamic total spillover (b) “YQ” and dynamic total spillover. Wavelet coherence between dynamic total spillover and different Baidu index. Notes: Following Grinsted et al. (2004), we standardized the data by (A - mean (A)) /sdev (A). The horizontal axis shows time (January 20, 2020, – May 26, 2022), whereas the vertical axis shows frequency (from 1 (1 day) to 16 (over 16 days)). The black contour shows 5% significance. Warm color indicates strong comovements, whereas cold (blue) indicates weak comovements. Fig 4 Table 4 The period and frequency cycle of strong comovements between the dynamic total spillover and COVID-19 and corresponding events. Table 4No Strong comovements between COVID-19 and the dynamic total spillover Corresponding event COVID-19 (“XG”) COVID-19 (“YQ”) Period Frequency band Period Frequency band 1 2/20/2020–4/9/2020 9–16 2/20/2020–6/2/2020 11–58 Events 1, 2, 3, 4 2 10/16/2020–3/1/2021 32–48 10/23/2020–4/12/2021 32–48 Events 5, 6, 8, 10 3 5/10/2021–3/15/2022 37–90 3/22/2021–2/10/2022 54–102 4 12/30/2021–4/6/2022 3–16 12/22/2021–4/6/2022 3–14 Events 7, 9, 11 Notes: Figures 4(a) and (b) show strong comovements between dynamic total spillover and COVID-19 (represented by “XG” and “YQ”), respectively. On the left side of Table 4, the four periods when dynamic total spillover and COVID-19 (“XG”)  are highly correlated (see Fig. 4(a)) are detailed. Similarly, strong comovements between dynamic total spillover and COVID-19 (“YQ”)  can be obtained (see Fig. 4(b) and Table 4). The right side of the table lists serial numbers of iconic events from each period (see Table A.1). For the XG test, strong comovements for dynamic total spillover and XG appeared four times with different frequency cycles (Table 4). The first strong comovement indicated that the sudden outbreak of the pandemic increased panic, which induced risk dependency among financial markets in the short term (9–16 days), until the pandemic stabilized in early April 2020 due to anti-pandemic measures. The second and third strong coherences are attributed to the slowdown of global economic trends, continued rate hikes, and geopolitical conflict (Tables 4 and A.1), which caused long-term turbulence across all markets (32–48 and 37–90 days, respectively). The fourth strong comovement is due to the large-scale pandemic outbreak in Xi'an, Jilin, and Shanghai (China's financial center). It caused market concerns and short-term risk spillovers across all markets (3–16 days). YQ yields similar results. Investors should note that the frequency cycle (short or long term) varies with strong comovement between the outbreak of COVID-19 and dynamic total spillover. Our results suggest that the early COVID-19 outbreak and recent large, localized epidemic had short-term coherence. Meanwhile, the slowdown of global economic trends, continued rate hikes, and political conflicts induce high dependency in the long run. 5 Conclusion This study examines risk spillovers between China's financial and shipping markets during COVID-19. We found net risk spillovers from stock, fund, and futures markets due to significant transaction scales and high leverage. During the pandemic, bond, gold, and shipping markets are still considered safe havens. However, gold and shipping markets’ role as safe-haven assets weakened and disappeared afterward, thereby suggesting that investors should not pursue them blindly. Moreover, we examine the coherence between dynamic total spillover and COVID-19 in frequency and time domains. The early COVID-19 outbreak and recent large, localized epidemic have short-term magnitude coherence. Meanwhile, the long-term correlation is caused by global economic slowdown, rate hikes, and political conflicts. Our results could help with portfolio optimization, policymaking, and risk management. CRediT authorship contribution statement Qiwei Xie: Conceptualization, Methodology, Software, Formal analysis, Writing – original draft, Funding acquisition, Resources. Lu Cheng: Writing – review & editing, Data curation, Formal analysis, Investigation. Ranran Liu: Methodology, Data curation, Formal analysis, Writing – original draft. Xiaolong Zheng: Data curation, Software, Visualization, Validation, Resources. Jingyu Li: Methodology, Supervision, Writing – review & editing, Validation, Funding acquisition, Project administration, Resources. Declarations of Competing Interest None Appendix Table A.1 Table A.1 List of major pandemic events. Table A2No. Time Major event 1 1/23/2020 Wuhan lockdown 2 3/12/2020 China's National Health Commission declared that the epidemic had passed an inflection point 3 3/15/2020 The Federal Reserve cut interest rates to zero 4 4/20/2020 WTI crude futures plunged into negative territory 5 12/31/2020 In 2020, the global economic trend slowed to −3.3%, which is the lowest since World War II 6 9/22/2021 Increase in Fed rate hike expectations 7 12/23/2021 Xi'an lockdown 8 2/24/2022 Russia–Ukraine war 9 3/14/2022 Jilin lockdown 10 3/17/2022 The Fed raised rates by 25 basis points 11 3/28/2022 Shanghai lockdown Data availability Data will be made available on request. Acknowledgments This work is supported by the National Natural Science Foundation of China (grant no. 72201012), the Open research fund in 2020, Stata Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, China Postdoctoral Science Foundation (grant no. 2020M680281), Beijing Postdoctoral Research Foundation (grant no. 2021-zz-168), and Beijing 10.13039/501100004826 Natural Science Foundation (grant no. 9202002). ==== Refs References Amankwah-Amoah J. Note: mayday, mayday, mayday! Responding to environmental shocks: insights on global airlines' responses to COVID-19 Transp. Res. Part E Logist. Transp. Rev. 143 2020 102098 10.1016/j.tre.2020.102098 Antonakakis N. Gabauer D. Refined measures of dynamic connectedness based on TVP-VAR Mpra Pap 2017 Bouri E. Cepni O. Gabauer D. Gupta R. Return connectedness across asset classes around the COVID-19 outbreak Int. Rev. Financ. Anal. 73 2021 101646 10.1016/jirfa.2020.101646 Broadstock D.C. Chan K. Cheng L.T.W. Wang X. The role of ESG performance during times of financial crisis: evidence from COVID-19 in China Finance Res. Lett. 2020 101716 10.1016/j.frl.2020.101716c Cao G. Xie W. Asymmetric dynamic spillover effect between cryptocurrency and China's financial market: evidence from TVP-VAR based connectedness approach Finance Res. Lett. 2022 103070 10.1016/j.frl.2022.103070 Choquet A. Sam-Lefebvre A. Ports closed to cruise ships in the context of COVID-19: what choices are there for coastal states? Ann. Tour. Res. 86 2021 103066 10.1016/j.annals.2020.103066 Choudhury T. Kinateder H. Neupane B. Gold, bonds, and epidemics: a safe haven study Finance Res. Lett. 102978 2022 10.1016/j.frl.2022.102978 Corbet S. Hou Y.(Greg) Hu Y. Oxley L. Xu D. Pandemic-related financial market volatility spillovers: evidence from the Chinese COVID-19 epicentre Int. Rev. Econ. Finance 71 2021 55 81 10.1016/jiref.2020.06.022 Couch K.A. Fairlie R.W. Xu H. Early evidence of the impacts of COVID-19 on minority unemployment J. Public Econ. 192 2020 104287 10.1016/jjpubeco.2020.104287 Dai Z. Zhu H. Time-varying spillover effects and investment strategies between WTI crude oil, natural gas and Chinese stock markets related to belt and road initiative Energy Econ 108 2022 105883 10.1016/j.eneco.2022.105883 Dai Z. Zhu H. Zhang X. Dynamic spillover effects and portfolio strategies between crude oil, gold and Chinese stock markets related to new energy vehicle Energy Econ 109 2022 105959 10.1016/j.eneco.2022.105959 Das D. Le Roux C.L. Jana R.K. Dutta A. Does bitcoin hedge crude oil implied volatility and structural shocks? A comparison with gold, commodity and the US Dollar Finance Res. Lett. 36 2020 101335 10.1016/j.frl.2019.101335 Diebold F.X. Yilmaz K. Better to give than to receive: predictive directional measurement of volatility spillovers Int. J. Forecast. 28 2012 57 66 10.1016/jijforecast.2011.02.006 El-Alaoui A.O. Bacha O.I. Masih M. Asutay M. Does low leverage minimise the impact of financial shocks? New optimisation strategies using Islamic stock screening for European portfolios J. Int. Financ. Mark. Inst. Money 57 2018 160 184 10.1016/j.intfin.2018.07.007 El Baz J. Ruel S. Can supply chain risk management practices mitigate the disruption impacts on supply chains’ resilience and robustness? Evidence from an empirical survey in a COVID-19 outbreak era Int. J. Prod. Econ. 2020 107972 10.1016/jijpe.2020.107972 Fang J. Gozgor G. Lau C.-K.M. Lu Z. The impact of Baidu index sentiment on the volatility of China's stock markets Finance Res. Lett. 32 2020 101099 10.1016/j.frl.2019.01.011 Fang Y. Jing Z. Shi Y. Zhao Y. Financial spillovers and spillbacks: new evidence from China and G7 countries Econ. Model. 94 2021 184 200 10.1016/Zj.econmod.2020.09.022 Gong Y. Li K.X. Chen S.-.L. Shi W. Contagion risk between the shipping freight and stock markets: evidence from the recent US-China trade war Transp. Res. Part E Logist. Transp. Rev. 136 2020 101900 10.1016/j.tre.2020.101900 Grinsted A. Moore J.C. Jevrejeva S. Application of the cross wavelet transform and wavelet coherence to geophysical time series Nonlinear Process. Geophys. 11 2004 561 566 10.5194/npg-11-561-2004 Gulerce M. Unal G. Using wavelet analysis to uncover the co-movement behavior of multiple energy commodity prices Int. J. Wavelets, Multiresol. Inf. Process. 14 2016 1650047 10.1142/S0219691316500478 Hong Y. Lin H. Wang S. Modeling the dynamics of Chinese spot interest rates J. Bank. Finance 34 2010 1047 1061 10.1016/j.jbankfin.2009.11.002 Ji Q. Li J. Sun X. Measuring the interdependence between investor sentiment and crude oil returns: new evidence from the CFTC's disaggregated reports Finance Res. Lett. 30 2019 420 425 10.1016/j.frl.2019.02.005 Kim H.-.Y. Kwon O. Oh G. A causality between fund performance and stock market Phys. A Stat. Mech. Appl. 443 2016 439 450 10.1016/j.physa.2015.08.041 Kim J. Kim J. Wang Y. Uncertainty risks and strategic reaction of restaurant firms amid COVID-19: evidence from China Int. J. Hosp. Manag. 92 2021 102752 10.1016/j.ijhm.2020.102752 Le T.H. Do H.X. Nguyen D.K. Sensoy A. Covid-19 pandemic and tail-dependency networks of financial assets Finance Res. Lett. 2020 101800 10.1016/j.frl.2020.101800 Li J. Cheng L. Zheng X. Wang F.-.Y. Analyzing the stock volatility spillovers in Chinese financial and economic sectors IEEE Trans. Comput. Soc. Syst. 2021 1 16 10.1109/TCSS.2021.3134487 Li J. Liu R. Yao Y. Xie Q. Time-frequency volatility spillovers across the international crude oil market and Chinese major energy futures markets: evidence from COVID-19 Resour. Policy 77 2022 102646 10.1016/j.resourpol.2022.102646 Li X. Li B. Wei G. Bai L. Wei Y. Liang C. Return connectedness among commodity and financial assets during the COVID-19 pandemic: evidence from China and the US Resour. Policy 73 2021 10.1016/j.resourpol.2021.102166 Li Y. Zhuang X. Wang J. Dong Z. Analysis of the impact of COVID-19 pandemic on G20 stock markets North Am. J. Econ. Financ. 58 2021 101530 10.1016/j.najef.2021.101530 Mensi W. Al Rababa'a A.R. Vo X.V. Kang S.H. Asymmetric spillover and network connectedness between crude oil, gold, and Chinese sector stock markets Energy Econ 98 2021 105262 10.1016/j.eneco.2021.105262 Polyzos S. Samitas A. Kampouris I. Economic stimulus through bank regulation: government responses to the COVID-19 crisis J. Int. Financ. Mark. Inst. Money 75 2021 101444 10.1016/j.intfin.2021.101444 Qin J. Ge J. Lu X. The effectiveness of the monetary policy in China: new evidence from long-range cross-correlation analysis and the components of multifractality Phys. A Stat. Mech. Appl. 506 2018 1026 1037 10.1016/j.physa.2018.04.068 Salisu A.A. Vo X.V. Lawal A. Hedging oil price risk with gold during COVID-19 pandemic Resour. Policy 2020 101897 10.1016/j.resourpol.2020.101897 Samitas A. Kampouris E. Polyzos S. Covid-19 pandemic and spillover effects in stock markets: a financial network approach Int. Rev. Financ. Anal. 80 2022 102005 10.1016/j.irfa.2021.102005 Samitas A. Papathanasiou S. Koutsokostas D. Kampouris E. Volatility spillovers between fine wine and major global markets during COVID-19: a portfolio hedging strategy for investors Int. Rev. Econ. Finance 78 2022 10.1016/jiref.2022.01.009 Samitas A. Papathanasiou S. Koutsokostas D. Kampouris E. Are timber and water investments safe-havens? A volatility spillover approach and portfolio hedging strategies for investors Finance Res. Lett. 2022 102657 10.1016/j.frl.2021.102657 Sene B. Mbengue M.L. Allaya M.M. Overshooting of sovereign emerging Eurobond yields in the context of COVID-19 Finance Res. Lett. 2020 101746 10.1016/j.frl.2020.101746 Si D.-.K. Li X.-.L. Xu X. Fang Y. The risk spillover effect of the COVID-19 pandemic on energy sector: evidence from China Energy Econ 102 2021 105498 10.10167/j.eneco.2021.105498 Sun Y. Bao Q. Lu Z. Coronavirus (Covid-19) outbreak, investor sentiment, and medical portfolio: evidence from China, Hong Kong, Korea, Japan, and US Pacific-Basin Finance J. 65 2021 101463 10.1016/j.pacfin.2020.101463 Wang H.-.Y. Wang T.-.T. Multifractal analysis of the Chinese stock, bond and fund markets Phys. A Stat. Mech. Appl. 512 2018 280 292 10.1016/j.physa.2018.08.067 Wang J. Sun X. Li J. How do sovereign credit default swap spreads behave under extreme oil price movements? Evidence from G7 and BRICS countries Finance Res. Lett. 34 2020 101350 10.1016/j.frl.2019.101350 Wei Z. Luo Y. Huang Z. Guo K. Spillover effects of RMB exchange rate among B&R countries: before and during COVID-19 event Finance Res. Lett. 37 2020 101782 10.1016/j.frl.2020.101782 Yang J. Ge Y.-.E. Li K.X. Measuring volatility spillover effects in dry bulk shipping market Transp. Policy. 2022 10.1016/j.tranpol.2022.01.018 Yao Y. Li J. Sun X. Measuring the risk of Chinese Fintech industry: evidence from the stock index Finance Res. Lett. 2020 101564 10.1016/j.frl.2020.101564 Zhang Y. Wang M. Xiong X. Zou G. Volatility spillovers between stock, bond, oil, and gold with portfolio implications: evidence from China Finance Res. Lett. 2020 101786 10.1016/j.frl.2020.101786 Zhu H. Meng L. Ge Y. Hau L. Dependent relationships between Chinese commodity markets and the international financial market: evidence from quantile time-frequency analysis North Am. J. Econ. Finance 54 2020 101256 10.1016/j.najef.2020.101256 Zhu X. Wei L. Li J. A two-stage general approach to aggregate multiple bank risks Finance Res. Lett. 2021 101688 10.1016/j.frl.2020.101688
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