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==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04487-4
10.1016/j.jval.2022.09.2282
Article
RWD57 Epidemiological Study of the Burden of COVID-19 on Depression in Men (DIM) in Pre- and During COVID-19 Pandemic Using Real-World Data
Sharma A 1
Verma V 2
Pandey S 1
Nayyar A 1
Daral S 1
Kukreja I 1
Chopra A 1
Gaur A 1
Paul K 1
Roy A 1
Khan S 1
Gupta A 1
1Optum, Gurugram, HR, India
2Optum, Gurgaon, HR, India
14 12 2022
12 2022
14 12 2022
25 12 S459S459
Copyright © 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
pmcObjectives
This study aimed to explore the impact of COVID-19 on prevalence and trends in men with depression in the pre- and during the COVID-19 pandemic.
Methods
This retrospective observational study included patients diagnosed with DiM between 1st January 2019 to 31st December 2021 using ICD-10-CM codes from Optum’s de-identified Clinformatics® Data Mart. Year-wise prevalence was calculated for the pre-pandemic (1st January to 31st December 2019) and during pandemic (1st January to 31st December 2020 and 1st January to 31st December 2021) period. Further stratification was done basis age, region, race/ethnicity, and rural-urban setting to observe trends based on unique patients identified with a diagnosis of DiM (cases). Chi-square test was performed to observe significant differences.
Results
Overall, we observed that the prevalence of patients with DiM increased by 7% (2020 vs 2019) and 6% (2021 [second wave] vs 2020 [first wave]). Compared to pre-pandemic (2019), the south-east region saw the most increase (+122%) in cases, followed by the south-west and north-east regions only during the first wave. Age-wise increase in cases was only observed in teenagers (50%) and patients aged 65 to 84 years (8%) during the first wave whereas the increase in cases during the second wave was observed in all age groups (with teenagers and 65-84 years affected the most). Ethnicity-wise, there was an observed increase of 6% in Asians; 4% in Hispanics; 3% in Blacks; and 2% in Whites during the first wave (vs pre-pandemic). A further increase of 15% in Asians; 11% in Hispanics; 6% in Blacks; and 8% in Whites during the second wave (vs the first wave).
Conclusions
Rise in prevalence of DiM was observed in both first and second waves of the COVID-19 pandemic. Impact on teenagers and 65 to 84 years, and Asians and Hispanics was observed the most.
| 0 | PMC9747431 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S459 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2282 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04558-2
10.1016/j.jval.2022.09.2353
Article
RWD128 Exploring the Burden of COVID-19 on Post-Traumatic Stress Disorder (PTSD) in Pre- and During-COVID-19 Pandemic Using Real-World Data
Kukreja I 1
Sharma A 1
Verma V 2
Nayyar A 1
Daral S 1
Gaur A 1
Roy A 1
Pandey S 1
Paul K 1
Chopra A 1
Chawla S 1
Khan S 1
Gupta A 1
1Optum, Gurugram, HR, India
2Optum, Gurgaon, HR, India
14 12 2022
12 2022
14 12 2022
25 12 S474S474
Copyright © 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
pmcObjectives
This study aimed to explore the impact of COVID-19 on patients with PTSD and the burden of resource utilization in the pre- and during the COVID-19 pandemic.
Methods
This retrospective observational study included patients diagnosed with PTSD between 1st January 2018 to 31st December 2020 using ICD-10-CM codes from Optum’s de-identified Clinformatics® Data Mart database. In the study duration, distinct patients were identified and further classified by age, gender, and location of service. To determine the influence in pre- and during COVID-19 for each of the stratification variables, a year-wise comparison was done. Chi-square was performed as test of significance for categorical variables.
Results
Overall we observed the number of PTSD patients increased by 7% (n=206,741) during the pandemic (1st January 2020 – 31st December 2020) vs pre-pandemic (1st January 2019 – 31st December 2019). A significant increase was seen across all age groups (p<.05). In the case of teenagers, PTSD was found to have increased by 22% whereas in adults and the elderly an 8% and 3% increase was seen respectively. When broken down by gender, a significant increase was observed. Females (+9% [n=143,032]) were seen to have been affected more compared to males (+4% [n=63,625]) during the pandemic vs pre-pandemic. In healthcare resources utilization overall, there was an observed 24% increase. For both inpatients and office, PTSD decreased significantly (-3% and -4% respectively) (p<.05); while ER visits, increased only by 1% (p<.05). A significant increase in outpatient and telehealth services was observed (122% and 454% respectively) (p<.05).
Conclusions
An increased exacerbation in PTSD was observed during the pandemic with respect to burden across various stratification and resource utilization; especially in outpatient and telehealth services. Better treatment, psychotherapy and alternative care programs may be required to curb this impact and decrease the overall burden across various care setting.
| 0 | PMC9747432 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S474 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2353 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02651-1
10.1016/j.jval.2022.09.447
Article
EE197 Efficacy and Economic Impact of Metformin Plus Glibenclamide Treatment During the COVID-19 Pandemic in Ecuadorian Outpatients With Type II Diabetes Mellitus
Zambrano R 1
Cabezas M 2
Loor G 1
Aguirre N 2
Miño C 2
1Hospital General Napoleon Córdoba, Chone, Ecuador
2Pontificia Universidad Católica del Ecuador, Quito, Ecuador
14 12 2022
12 2022
14 12 2022
25 12 S91S91
Copyright © 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
pmcObjectives
To assess the efficacy and economic impact, in terms of direct medical costs (DMC), of treating by metformin plus glibenclamide (MG) type II Diabetes Mellitus (T2DM) outpatients in a second level hospital during the COVID19 pandemic in Ecuador.
Methods
Adult T2DM patients treated with MG combination from January to December 2021 were included. Patient chart’s information was collected using a Capture Report Form to evaluate the efficacy and management of these outpatients. Drug and services prices were taken from the National Public Procurement Service, while medical cost estimations were obtained from the National Fare System (2014 and 2019). A Microsoft Excel budget model was developed to calculate the DMC. The study was approved by the Institutional Review Board Ethics Committee.
Results
Thirty-Nine patients were included in the study. After a year of MG treatment, fasting glucose (-58.8 mg/dl; 95% CI -19.7 to -97.9 mg/dl; P=0.004) and glycosylated hemoglobin levels (-1.05%; 95% CI -0.16 to -1.93%; P=0.02) significantly decreased. The MG outpatient treatment had a total annual cost of 110,634.81 USD, yielding an amount of 2,836.79 USD per patient (PP). Medical consultations amounted 1,817.72 USD (205,23 USD PP) and 84.5% of them were for diabetic control (5.5 ± 2.7 consultations PP/year). All patients required hospitalization and emergency care at least once, with corresponding costs of 77,812.73 USD (1,995.20 USD PP) and 3,448.56 USD (88.42 USD PP), respectively.
Conclusions
MG significantly reduced fasting glucose and HbA1c levels, but not according to international recommendations. The management of T2DM patients during COVID-19 had a major economic impact mainly due to complications and prolonged hospital stays.
| 0 | PMC9747433 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S91 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.447 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02279-3
10.1016/j.jval.2022.09.077
Public Health
P65 Impact of COVID-19 on Hospital Screening, Diagnosis and Treatment Activities Among Prostate and Colorectal Cancer Patients in Canada
Lee FSH 1
Halat M 1
Bleibdrey N 2
Zhang S 1
Chalmers R 1
Zimskind D 1
1ZS Associates, Toronto, ON, Canada
2ZS Associates, Hampton, NJ, USA
14 12 2022
12 2022
14 12 2022
25 12 S15S15
Copyright © 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
pmcObjectives
Suspension of cancer screening and treatment programs were instituted to preserve medical resources and protect vulnerable populations. This research aims to investigate the implications of COVID-19 on cancer management and clinical outcomes for patients with prostate and colorectal cancer, two of the most prevalent cancers in Canada.
Methods
Hospital cancer screening, diagnosis, treatment, length of stay, and mortality data among prostate and colorectal cancer patients between April 2017 and March 2021 were obtained from the Canadian Institute for Health Information. Baseline trends were established with data between April 2017 and March 2020 for comparison with data collected during the pandemic between April 2020 and March 2021 using Student’s t-tests. Scenario analyses were performed to assess the incremental capacity requirements needed to restore hospital cancer care capacities to the pre-pandemic levels in Canada.
Results
For prostate cancer, A 12% decrease in hospital diagnoses and a 5.3% decrease in treatment activities were observed during COVID-19 between April 2020 and March 2021. Similarly, a 43% reduction in hospital colonoscopies, 11% decrease in hospital diagnoses and 10% decrease in treatment activities were observed for colorectal cancers. Additionally, a marked reduction in hospital prostate cancer (12%) and colorectal cancer (21%) mortality was observed over the same period. Overall, an estimated 1,438 prostate and 2,494 colorectal cancer cases were undiagnosed, resulting in a total of 620 and 1,487 unperformed treatment activities for prostate and colorectal cancers, respectively, across the nine provinces included in the study in Canada. To clear the backlogs of unperformed treatment procedures in will require an estimated 3%-6% monthly capacity increase over the next 6 months.
Conclusions
A concerted effort from all stakeholders is required to immediately ameliorate the backlogs of cancer detection and treatment activities. Mitigation measures should be implemented to reduce the impact of future interruptions to regular practice.
| 0 | PMC9747434 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S15 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.077 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04463-1
10.1016/j.jval.2022.09.2258
Article
RWD33 Analysis of COVID-19 Vaccine-Related Adverse Events in Adults, Geriatrics and Pediatrics – A Retrospective Study
Roy A 1
Khandelwal H 1
Gupta A 1
Rastogi M 1
Verma V 2
Pandey S 1
Kukreja I 3
Gaur A 1
Chopra A 1
Nayyar A 1
Daral S 1
Sharma A 1
Dawar V 1
1Optum, Gurugram, HR, India
2Optum, Gurgaon, HR, India
3Optum, New Delhi, DL, India
14 12 2022
12 2022
14 12 2022
25 12 S454S454
Copyright © 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
pmcObjectives
Normally, drug discovery (including vaccines) is a long process that may take up to 10 to 15 years. Due to the mortality and contagious nature of the SARS-CoV2 virus, there was a need for the fast-track development and approval of the vaccine. The clinical trials conducted for the development of a vaccine for COVID-19 were of short duration. Therefore, there is a need to evaluate the safety of the vaccine through the analysis of real-world data.Analysis of selected adverse events after COVID-19 vaccination in adults (18 to 64 years), geriatrics (≥65 years), and pediatrics (<18 years).
Methods
Optum’s de-identified Clinformatics® Data Mart database was used to identify the adults, geriatrics, and pediatrics patients who had received vaccination for COVID-19 from 1 Nov 2020 to 30 June 2021. The occurrence of the ICD-10 code for COVID-19 vaccination in the claims database was defined as the index event. These patients were then followed for 10 days to check for the adverse events (listed by the CDC). Patients with a confirmed diagnosis of COVID-19 before vaccination and during the follow-up period were excluded from the study. Patients having the ICD-10 for diseases listed in adverse events were also excluded from the study.
Results
Out of the 845,357 unique patients who received vaccination for COVID-19, 644,707 (76.3%) were adults, 160,799 (∼19.0%) were geriatrics, and 39,851 (∼5%) were pediatrics. The rate of thrombocytopenia was higher in geriatrics (628 and 721 cases per million after 1st and 2nd dose, respectively) as compared with adults (172 and 192 cases per million after 1st and 2nd dose, respectively). Cases for Guillain-Barré Syndrome (GBS), myocarditis, and pericarditis were rare. Further statistical tests will be applied to analyze the level of significance.
Conclusions
Severe reactions after COVID-19 vaccination are rare. A long-term analysis of adverse events should be performed to support these findings.
| 0 | PMC9747435 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S454 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2258 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04359-5
10.1016/j.jval.2022.09.2154
Article
PCR221 Health-Related Quality of Life Among Working Nurses in Hong Kong: The Role of Resilience Under the COVID-19 Pandemic
Wong E
Cheung AWL
Wong AYK
Ma JCH
Sun TKS
Yam CHK
Wong MCY
Miao HY
Yeoh EK
The Chinese University of Hong Kong, Hong Kong, China
14 12 2022
12 2022
14 12 2022
25 12 S432S432
Copyright © 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
pmcObjectives
As the COVID-19 continues to evolve, a sustainable health workforce is important for providing good quality of care. Resilience is therefore crucial for the individual to empower themselves to face the uncertainty, especially under disease outbreaks. This study aimed to explore if resilience plays a significant role on the Health-related Quality of Life (HRQoL) under the COVID-19 pandemic in Hong Kong (HK).
Methods
A cross-sectional survey was conducted between January 2022 and March 2022 among nurses including both public and private sector during the COVID-19 pandemic in HK. The nurses were recruited through the Association of Hong Kong Nursing Staff by email invitation. HRQoL were obtained using the EQ-5D-5L HK and utility index was derived based on the algorithm for local population. The nurses’ self-reported psychological resilience was measured using the Connor-Davidson Resilience Scale (CD-RISC2). Other demographics such as working department, religion and chronic conditions were also obtained. Tobit regression model was used to explore the association between HRQoL and resilience of the nurses.
Results
A total of 1,014 nurses participated in the survey and 856 (84.4%) with full-time employment are included in final analysis. Among the 856 full-time working respondents, the overall mean EQ-5D utility and EQ-VAS were 0.90 (SD=0.13) and 75.1 (SD=14.89), respectively. In the multivariate regression analysis, resilience had a positive association with HRQoL (β = 0.048; 95% CI: 0.040-0.057) while chronic conditions and elder age had negative impacts on the HRQoL with all variables (p < 0.001).
Conclusions
The HRQoL of full-time working nurses is similar to the HK population norms (0.919). Findings showed a statistically significant association between the HRQoL and resilience, age and health status. It also highlights the importance of resilience with contribution to a better HRQoL during the COVID-19 pandemic.
| 0 | PMC9747436 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S432 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2154 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03332-0
10.1016/j.jval.2022.09.1127
Article
EPH206 Strategies to Address Vaccine Hesitancy in Adults: A Systematic Review
Santamaria J 1
Ibrahim IF 2
van der Putten IM 2
Rochau U 1
Kuehne F 3
Stojkov I 1
Pabjan B 4
Siebert U 5
Jahn B 1
1UMIT - University for Health Sciences, Medical Informatics and Technology, Institute of Public Health, Medical Decision Making and Health Technology Assessment, Hall i.T., Austria
2Maastricht University, Maastricht, Netherlands
3UMIT - University for Health Sciences, Medical Informatics and Technology, Institute of Public Health, Medical Decision Making and Health Technology Assessment, Hall in Tirol, Austria
4Institute of Sociology University of Wrocław, Wroclaw, Poland
5UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria; Massachussetts General Hospital, Harvard Medical School, Boston, USA; Harvard T.H. Chan School of Public Health, Boston, USA, Boston, MA, USA
14 12 2022
12 2022
14 12 2022
25 12 S230S231
Copyright © 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
pmcObjectives
To combat the COVID-19 pandemic, vaccination of the population is essential. However, attitudes regarding vaccination can range from full acceptance to absolute refusal. Vaccination hesitancy is complex and context-specific, varying across pandemic phases, country, sociodemographic characteristics, and vaccines. Evidence-based strategies to address vaccine hesitancy behavior are needed. The aim of this systematic review is to identify and assess the effectiveness of strategies in addressing vaccine hesitancy in adults.
Methods
A systematic literature review was conducted in PubMed, Embase, and PsycInfo (2016-2021) building on Jarret´s et al. (2015) review. The review adheres to PRISMA guidelines and uses the Cochrane Risk of Bias Assessment Tool. For data analysis, interventions were categorized into: 1) dialogue-based; 2) educational; 3) incentive-based; 4) recall-based; and 5) multi-component interventions. Outcomes of included interventions were categorized into vaccination coverage rate and behavioral outcomes.
Results
Out of 5,023 retrieved studies, six were included in the review in addition to one study from Jarret´s et al. review and three studies from snowballing. All studies focused on influenza vaccine except one which focused on Hepatitis B. Five studies evaluated educational interventions, two dialogue-based interventions, and three multi-component interventions. Multi-component interventions had a significant effect in increasing the vaccination rate (6.5% to 10.2%). Educational interventions had a positive effect in behavioral outcomes. Comparability of studies was limited due to the heterogeneity in study outcome(s), study designs and target populations.
Conclusions
This review has shown statistically significant results of different strategies in increasing the knowledge and vaccination rates in adults. In a next step, our findings should be contrasted with interventions that may have been implemented during the COVID-19 pandemic to increase vaccination rates. In addition, research is needed to better understand the determinants of vaccine hesitant behavior, which might involve trust in the healthcare system or governmental institutions and their capability to design adequate interventions.
| 0 | PMC9747437 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S230-S231 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1127 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04569-7
10.1016/j.jval.2022.09.2364
Article
RWD139 Impact of the COVID-19 Pandemic on Diagnosis and Cancer-Related Medical Procedures in Brazil
Reis Neto JP 1
Busch J 2
Stefani S 3
1CAPESESP, Rio de Janeiro, Brazil
2Souza Marques University, Rio de Janeiro, RJ, Brazil
3--, Rio de Janeiro, Brazil
14 12 2022
12 2022
14 12 2022
25 12 S476S476
Copyright © 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
pmcObjectives
The COVID-19 pandemic caused disruptions in treatment for cancer. Less is known about its impact on new cancer diagnoses. This study quantifies decreases in medical procedures and new diagnoses of those cancers before and during COVID era.
Methods
Data were sourced (2018–2020) from health plan administrative database, including cancer registrations, in-patient hospitalizations, and outpatient events. Diagnostic testing (colposcopy/pap smear, colonoscopies, mammography), medical oncology access (first specialist appointments and intravenous chemotherapy attendances) and radiation oncology access were also extracted. Using 2018/2019 as baseline (pre-COVID-19), reductions in procedures and new cancer diagnoses in 2020/2021 (COVID-19-Period) were calculated. Cancer-related procedures rates per 100 000 inhabitants and 95% confidence intervals (95% CIs) were estimated between periods. Calculated absolute and percentage differences in annual volume and observed-to-expected volume. For significance, Chi-square tests (Mantel-Haenszel and Fisher's Exact), when p<0.05.
Results
A total of 58,094 health plan beneficiaries in the pre-COVID-19 and 36,405 in the COVID-19-Period were included in the study. Compared to the annual averages in pre-COVID-19, colposcopy in COVID-19-Period decreased by 24.7%, whereas colonoscopies and mammography 19.8% and 17.1, respectively (p<0.05). The new cancers diagnosed rates decreased from 1,168 to 865 per 100,000 inhabitants (p<0.05).
Conclusions
Compared to the pre-pandemic period, the COVID has reduced the number of cancer screening rates, particularly forms of screening like colposcopy, mammography, and colonoscopy with subsequent reductions in new cancer diagnosis This explanation can be multifactorial and may be influenced by the closure of diagnostic services during initial months of pandemic, as well as by the fear of patients to attend medical care. Strategies to ensure that cancer screening and prevention measures should be implemented as soon as possible to avoid, a significant increase in late-stage disease at diagnosis and, consequently, higher cancer morbidity and mortality rates in the near future.
| 0 | PMC9747438 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S476 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2364 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03919-5
10.1016/j.jval.2022.09.1714
Article
HTA257 MOVe-OUT: A Trial of Two Halves – The Impact of Heterogeneity on Cost-Effectiveness Outcomes for COVID-19
McConnell D 1
Mccullagh L 1
Usher C 1
Walsh C 2
Barry M 1
Adams R 1
1National Centre for Pharmacoeconomics, Dublin, Ireland & Discipline of Pharmacology and Therapeutics, Trinity College Dublin, Dublin, Ireland
2Department of Mathematics and Statistics, University of Limerick, Limerick, Ireland & National Centre for Pharmacoeconomics, Dublin, Ireland
14 12 2022
12 2022
14 12 2022
25 12 S346S347
Copyright © 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
pmcObjectives
In the phase 3 MOVe-OUT trial, non-hospitalised, unvaccinated adults with COVID-19 (at risk for severe illness) were randomised to molnupiravir or placebo. Our objective is to investigate the short-term costs and outcomes associated with molnupiravir (versus standard of care (SoC), defined as ‘no systematic treatment’) from the Irish-payer perspective.
Methods
An acute-phase (one-month) decision tree was programmed in R. On entering the model, all patients are at risk of hospitalisation; a proportion are admitted to intensive care units (ICU). Treatment effectiveness was informed by the MOVe-OUT trial, with external data and clinical opinion used to estimate ICU admission risk. Irish direct-medical costs were included. Summary statistics of cost per hospitalisation, ICU admission, and death avoided were calculated; no explicit payer-threshold was considered. One-way sensitivity and probabilistic analyses were performed.
Results
Using the final analysis of MOVe-OUT, it was estimated that treating 1,000 patients with molnupiravir would prevent approximately 30 hospitalisations, 17 ICU admissions, and 11 deaths, at an incremental cost of approximately €147,229 versus SoC, over the one-month horizon (incremental costs €4,977, €8,800 and €12,841 per hospitalisation, ICU admission and death prevented respectively). Among patients recruited during the latter part of MOVe-OUT, no benefit associated with molnupiravir was observed, at an incremental cost of €772,842 per 1,000 patients. The outcomes of ICU admission and death were particularly uncertain due to small event numbers and the additional assumptions required.
Conclusions
This study demonstrates that the clinical evidence provided by the MOVe-OUT trial may be unsuitable to inform comparative and cost effectiveness due to considerable unexplained heterogeneity of treatment effects observed at different time-points. Generalisability of the study results to clinical practice is thus limited, and is likely further compromised given differences in circulating variants and healthcare systems. Additional evidence on the efficacy of molnupiravir is needed to reliably evaluate cost-effectiveness over a lifetime horizon.
| 0 | PMC9747439 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S346-S347 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1714 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03996-1
10.1016/j.jval.2022.09.1791
Article
MSR60 Literature Review of Statistical Methods Comparisons Through Simulations When Using External Control Arm for Regulatory or HTA Submissions
Yue B 1
Lu K 2
Xu S 3
Liao S 4
1BeiGene USA, Inc, Lutz, FL, USA
2BeiGene USA, New Jersey, NJ, USA
3BeiGene, Shanghai, 31, China
4BeiGene, Shanghai, FL, China
14 12 2022
12 2022
14 12 2022
25 12 S361S361
Copyright © 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
pmcObjectives
Using a historical control or external control arm (ECA) to augment or replace a concurrent control arm in a randomized trial is a hot topic given the challenge of patient recruitment in rare diseases or during COVID-19 pandemic. FDA released several draft guidance in 2021 on effectiveness and safety submissions using real-world evidence. While the guidance focuses mainly on elements of study design and data source selection, there is a lack of consensus in the selection of appropriate statistical methods when constructing an ECA. This study aims to discuss rigorous statistical methodology for ECA-supported trial in regulatory or HTA submissions.
Methods
Targeted literature reviews of statistical simulations comparing methods for ECA in statistical journals were performed. The articles compare commonly used ECA-construction and analysis methods were selected and summarized, including but not limited to propensity-score (PS) based- matching, weighting, stratification, and PS plus Bayesian integrated approaches.
Results
Type I error, power, bias, and coverage probability are common criteria used to compare different methods. When imbalances only exist in known baseline covariates and the outcome distribution are the same between the trial concurrent control and ECA, PS method alone or paired with commensurate prior yield almost unbiased estimates, good Type I errors, and coverage probability. PS plus Bayesian approaches have wider interval width and lower power compared with PS only methods. When there is a change in the outcome distribution over time, PS (matching or IPTW) and commensurate prior integrated method yield smallest biases among all methods.
Conclusions
PS and Bayesian integrated methods outperformed the PS only methods in terms of bias and type I error when outcome distribution changed with current trial control. A “sweet spot” that balances all criteria through trial-specific simulations could provide the ideal setting of trial analyses plan based on specific trial design and scenarios.
| 0 | PMC9747440 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S361 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1791 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03374-5
10.1016/j.jval.2022.09.1169
Article
HPR37 Comparing Reimbursement of New Drugs During the COVID-19 Pandemic in Ireland and Scotland
McLoughlin D 1
Dooley B 2
Copeland C 3
1AXIS Healthcare Consulting Ltd, Dublin, Ireland
2AXIS Healthcare Consulting Ltd, Dublin 2, Ireland
3AXIS Healthcare Consulting Ltd, Dublin , D, Ireland
14 12 2022
12 2022
14 12 2022
25 12 S239S239
Copyright © 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
pmcObjectives
Following the onset of the COVID-19 pandemic, the Scottish Medicines Consortium (SMC) suspended monthly meetings from April to August 2020, to support the National Health Service (NHS) Scotland in maintaining essential work. Following the return of meetings, a fast-track process was introduced to expedite reimbursement for certain medicines. Conversely, the Irish health technology assessment (HTA) agency, the National Centre for Pharmacoeconomics (NCPE), continued to assess new reimbursement applications throughout this period, using the two-stage process of a rapid review (RR), followed by full HTA for some medicines. This research explores how these different approaches impacted reimbursement submissions and recommendations during this time.
Methods
A database was developed using published data (from 01/03/2020 to 01/03/2022) on the NCPE, SMC and Irish Health Service Executive (HSE) websites, including;
• Breakdown of submissions received
• Assessment outcomes
• Breakdown of reimbursement recommendations
Data was extracted into Excel® and analysed using summary and descriptive statistics.
Results
SMC advice for 169 medicines were identified (n=89 full submissions; n=36 abbreviated submissions; n=28 non-submissions; n=13 resubmissions; n=3 ultra-orphan assessments). Positive reimbursement recommendations were made for 136 of these medicines (n=68 accepted for use, n=58 accepted for restricted use, n=7 accepted on interim basis, n=3 available under ultra-orphan assessment), with 48 recommendations made using the fast-track process. Contrastingly, the NCPE published 148 RR outcomes and 61 HTA outcomes, with 70 reimbursement recommendations published by the HSE (n=38 positive recommendations, n=11 restricted reimbursement, n=21 reimbursement not recommended).
Conclusions
While a similar number of submissions were assessed by the Irish and Scottish HTA agencies during the COViD-19 period, there was a significantly higher number of positive reimbursement recommendations from the SMC, which may be explained by the SMC fast-track process. This research further explores the reimbursement recommendations for each category of submission and compares the reimbursement timelines for each jurisdiction.
| 0 | PMC9747441 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S239 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1169 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03374-5
10.1016/j.jval.2022.09.1169
Article
HPR37 Comparing Reimbursement of New Drugs During the COVID-19 Pandemic in Ireland and Scotland
McLoughlin D 1
Dooley B 2
Copeland C 3
1AXIS Healthcare Consulting Ltd, Dublin, Ireland
2AXIS Healthcare Consulting Ltd, Dublin 2, Ireland
3AXIS Healthcare Consulting Ltd, Dublin , D, Ireland
14 12 2022
12 2022
14 12 2022
25 12 S239S239
Copyright © 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
pmcObjectives
Following the onset of the COVID-19 pandemic, the Scottish Medicines Consortium (SMC) suspended monthly meetings from April to August 2020, to support the National Health Service (NHS) Scotland in maintaining essential work. Following the return of meetings, a fast-track process was introduced to expedite reimbursement for certain medicines. Conversely, the Irish health technology assessment (HTA) agency, the National Centre for Pharmacoeconomics (NCPE), continued to assess new reimbursement applications throughout this period, using the two-stage process of a rapid review (RR), followed by full HTA for some medicines. This research explores how these different approaches impacted reimbursement submissions and recommendations during this time.
Methods
A database was developed using published data (from 01/03/2020 to 01/03/2022) on the NCPE, SMC and Irish Health Service Executive (HSE) websites, including;
• Breakdown of submissions received
• Assessment outcomes
• Breakdown of reimbursement recommendations
Data was extracted into Excel® and analysed using summary and descriptive statistics.
Results
SMC advice for 169 medicines were identified (n=89 full submissions; n=36 abbreviated submissions; n=28 non-submissions; n=13 resubmissions; n=3 ultra-orphan assessments). Positive reimbursement recommendations were made for 136 of these medicines (n=68 accepted for use, n=58 accepted for restricted use, n=7 accepted on interim basis, n=3 available under ultra-orphan assessment), with 48 recommendations made using the fast-track process. Contrastingly, the NCPE published 148 RR outcomes and 61 HTA outcomes, with 70 reimbursement recommendations published by the HSE (n=38 positive recommendations, n=11 restricted reimbursement, n=21 reimbursement not recommended).
Conclusions
While a similar number of submissions were assessed by the Irish and Scottish HTA agencies during the COViD-19 period, there was a significantly higher number of positive reimbursement recommendations from the SMC, which may be explained by the SMC fast-track process. This research further explores the reimbursement recommendations for each category of submission and compares the reimbursement timelines for each jurisdiction.
| 0 | PMC9747442 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S331 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1637 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02218-5
10.1016/j.jval.2022.09.016
Article
P4 Cost Analysis of Post-COVID-19 Healthcare Consumption in the Netherlands
Fens T 1
Zon SKR 2
Rosmalen JGM 3
Brouwer S 2
van Asselt ADI 4
1University of Groningen,University Medical Center Groningen, Department of Health Sciences & Department of Psychiatry, Groningen, GR, Netherlands
2University of Groningen, University Medical Center Groningen, Department of Health Sciences, Community and Occupational Medicine, Groningen, GR, Netherlands
3University of Groningen,University Medical Center Groningen, Department of Internal Medicine & Department of Psychiatry, Groningen, GR, Netherlands
4University of Groningen,University Medical Center Groningen, Department of Health Sciences & Department of Epidemiology, Groningen, GR, Netherlands
14 12 2022
12 2022
14 12 2022
25 12 S1S2
Copyright © 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
pmcObjectives
In the Netherlands, one out of eight COVID-19 patients suffer from long COVID, burdening the health budget with unknown costs. This study investigated the types of healthcare consumed after COVID-19 and the related costs.
Methods
Data was delivered from the Dutch Lifelines COVID-19 cohort (N=76503), a subcohort consisting of adult participants from the Lifelines prospective population cohort that completed questionnaires on psychological and societal impacts of the pandemic. Health care use in the past three months was assessed in two waves of questionnaires (June 2021 and March 2022). Frequencies and costs of healthcare provider visits, day-treatment in a hospital or other institution (without stay), emergency visits, outpatient appointments, and homecare received were analyzed. The comparisons were made between a non-COVID-19 (control) group, a COVID-19 group, and a long-COVID group. Referent prices from the Dutch healthcare institute were used to facilitate the cost analyses. All costs were inflated into the 2020 cost year.
Results
The results show that for all types of care, people with long- COVID receive the most care, and uninfected controls the least. In the long-COVID group, from the primary care, the care provided by the general practitioners (49%), and physiotherapist (28%) were the most reported, compared to COVID-19 and non-COVID-group, being 33%, 14% and 16%, 7% respectively. All other care, was used by less than 10% of the long- COVID respondents reported.The highest costs per patient are generated from the various health care provider visits in primary care and outpatient appointments in the secondary care. The total extra healthcare costs per six months per person for COVID-19 and long-COVID compared to the non-COVID-19 group are €59 and €123, respectively.
Conclusions
These findings will inform the health authorities about the necessity for new health-budget allocations. Moreover, they represent a validated data source for future economic evaluations.
| 0 | PMC9747443 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S1-S2 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.016 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03453-2
10.1016/j.jval.2022.09.1248
Article
HPR118 An Updated Estimate of the Direct Cost of the COVID-19 Pandemic for the Greek Healthcare System
Athanasakis K 1
Nomikos N 2
Kyriopoulos I 3
Souliotis K 4
1University of West Attica, Athens, Greece
2University of West Attica, Athens, A1, Greece
3London School of Economics and Political Science, London, UK
4University of Peloponnese, Corinth, Greece
14 12 2022
12 2022
14 12 2022
25 12 S253S253
Copyright © 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
pmcObjectives
The COVID-19 pandemic has put enormous pressure on health systems globally, through increased needs for health services and subsequent costs. The purpose of this analysis is to provide an updated estimate of the direct healthcare cost for the management of COVID-19 confirmed cases in Greece.
Methods
Costs were estimated under the health care sector perspective, and include the resources attributed to testing for COVID-19 and to hospitalizations (in a general ward (GW) or in an Intensive Care Unit (ICU)). Resource use data were based on publicly available sources and published literature. Unit prices are those of the third-party payer in Greece. The time horizon of the analysis covers the period from March 2020 to December 2021.
Results
Total direct healthcare expenditure for the management of Covid-19 confirmed cases during the time horizon of the study amount at 1.78 billion €. For the year 2021 only, the cost estimated at 1.43 billion €, which is equal to 14.7% of the annual public healthcare expenditure and 9.1% of total healthcare expenditure in Greece. The majority of costs (almost 1bn €) is attributable to testing, as about 48 billion COVID test have been performed, while the remaining cost refers to hospitalizations (341.7 and 434.8 million € for GW and ICU bed-days respectively). The average cost per case that required GW-hospitalization only was 3,101.6 € whereas the respective cost when ICU-hospitalization was required was 34,538.6 €.
Conclusions
Covid-19 is associated with a substantial disease burden and a significant direct healthcare cost. Apart from the above, however, productivity and welfare losses, which do not fall under the scope of the present analysis, can also be a substantial burden to society.
| 0 | PMC9747444 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S253 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1248 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03453-2
10.1016/j.jval.2022.09.1248
Article
HPR118 An Updated Estimate of the Direct Cost of the COVID-19 Pandemic for the Greek Healthcare System
Athanasakis K 1
Nomikos N 2
Kyriopoulos I 3
Souliotis K 4
1University of West Attica, Athens, Greece
2University of West Attica, Athens, A1, Greece
3London School of Economics and Political Science, London, UK
4University of Peloponnese, Corinth, Greece
14 12 2022
12 2022
14 12 2022
25 12 S253S253
Copyright © 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
pmcObjectives
The COVID-19 pandemic has put enormous pressure on health systems globally, through increased needs for health services and subsequent costs. The purpose of this analysis is to provide an updated estimate of the direct healthcare cost for the management of COVID-19 confirmed cases in Greece.
Methods
Costs were estimated under the health care sector perspective, and include the resources attributed to testing for COVID-19 and to hospitalizations (in a general ward (GW) or in an Intensive Care Unit (ICU)). Resource use data were based on publicly available sources and published literature. Unit prices are those of the third-party payer in Greece. The time horizon of the analysis covers the period from March 2020 to December 2021.
Results
Total direct healthcare expenditure for the management of Covid-19 confirmed cases during the time horizon of the study amount at 1.78 billion €. For the year 2021 only, the cost estimated at 1.43 billion €, which is equal to 14.7% of the annual public healthcare expenditure and 9.1% of total healthcare expenditure in Greece. The majority of costs (almost 1bn €) is attributable to testing, as about 48 billion COVID test have been performed, while the remaining cost refers to hospitalizations (341.7 and 434.8 million € for GW and ICU bed-days respectively). The average cost per case that required GW-hospitalization only was 3,101.6 € whereas the respective cost when ICU-hospitalization was required was 34,538.6 €.
Conclusions
Covid-19 is associated with a substantial disease burden and a significant direct healthcare cost. Apart from the above, however, productivity and welfare losses, which do not fall under the scope of the present analysis, can also be a substantial burden to society.
| 0 | PMC9747445 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S231 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1131 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03453-2
10.1016/j.jval.2022.09.1248
Article
HPR118 An Updated Estimate of the Direct Cost of the COVID-19 Pandemic for the Greek Healthcare System
Athanasakis K 1
Nomikos N 2
Kyriopoulos I 3
Souliotis K 4
1University of West Attica, Athens, Greece
2University of West Attica, Athens, A1, Greece
3London School of Economics and Political Science, London, UK
4University of Peloponnese, Corinth, Greece
14 12 2022
12 2022
14 12 2022
25 12 S253S253
Copyright © 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
pmcObjectives
The COVID-19 pandemic has put enormous pressure on health systems globally, through increased needs for health services and subsequent costs. The purpose of this analysis is to provide an updated estimate of the direct healthcare cost for the management of COVID-19 confirmed cases in Greece.
Methods
Costs were estimated under the health care sector perspective, and include the resources attributed to testing for COVID-19 and to hospitalizations (in a general ward (GW) or in an Intensive Care Unit (ICU)). Resource use data were based on publicly available sources and published literature. Unit prices are those of the third-party payer in Greece. The time horizon of the analysis covers the period from March 2020 to December 2021.
Results
Total direct healthcare expenditure for the management of Covid-19 confirmed cases during the time horizon of the study amount at 1.78 billion €. For the year 2021 only, the cost estimated at 1.43 billion €, which is equal to 14.7% of the annual public healthcare expenditure and 9.1% of total healthcare expenditure in Greece. The majority of costs (almost 1bn €) is attributable to testing, as about 48 billion COVID test have been performed, while the remaining cost refers to hospitalizations (341.7 and 434.8 million € for GW and ICU bed-days respectively). The average cost per case that required GW-hospitalization only was 3,101.6 € whereas the respective cost when ICU-hospitalization was required was 34,538.6 €.
Conclusions
Covid-19 is associated with a substantial disease burden and a significant direct healthcare cost. Apart from the above, however, productivity and welfare losses, which do not fall under the scope of the present analysis, can also be a substantial burden to society.
| 0 | PMC9747446 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S1 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.014 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04110-9
10.1016/j.jval.2022.09.1905
Article
MT31 A Novel Medical Technology for Rapid Molecular Diagnostics (Nicking Enzyme Amplification Reaction [NEAR]) - A Systematic Literature Review, Meta-Analysis
Grys M 1
Pieniazek I 1
Walczak J 1
Debray R 2
Cybulski J 3
Przygodzki P 4
1Arcana Institute, a Certara company, Cracow, MA, Poland
2Abbott Rapid Diagnostics Ltd, Maidenhead, UK
3Abbott Medical Sp. z o.o., Warsaw, Poland
4Abbott Medical Sp. z o.o., Warszawa, Poland
14 12 2022
12 2022
14 12 2022
25 12 S384S384
Copyright © 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
pmcObjectives
The RT-PCR method is often regarded as the "gold standard" method for the detection of SARS-COV-2. A limitation of PCR however, is the ‘time to result’. With a rapid molecular diagnostic test (intervention), results can be obtained much quicker (3-15 minutes). The objective was to to evaluate the diagnostic efficacy of one of the rapid molecular diagnostic tests for the qualitative detection of SARS-CoV-2 (COVID-19) infection, in comparison to RT-PCR.
Methods
We systematically searched EMBASE, Medline and the Cochrane Library through November 31, 2021. All prospective studies on the diagnostic efficacy of the assessed intervention compared with RT-PCR in symptomatic patients were retrieved. Only studies conducted according to the valid protocol recommended by the manufacturer were included: dry swab collected by investigator; samples for intervention and control taken from the same anatomical place; "fresh" samples, tested shortly after collection without freezing.
Results
The meta-analysis of the eligible studies (n=7; 3,493 patients) showed sensitivity of the intervention was 0.956 (95% CI: 0.918 - 0.976) and specificity was 0.995 (95% CI: 0.946-0.999) compared with the RT-PCR. In the subset of studies, which considered patients with no more than 7 days from the onset of symptoms, the sensitivity of the intervention was 0.987 (95% CI: 0.917 - 0.998) and the specificity was 0.989 (95% CI: 0.989 - 0.989) compared with the RT-PCR method.
Conclusions
There is significant unmet need for both a rapid and accurate diagnostic test to detect COVID-19. Thanks to the technology used to obtain an accurate result, clinicians can make evidence-based decisions in a short period of time. Compared to other published systematic reviews (SR), this SR showed that following the updated protocol for the intervention usage the diagnostic efficacy of the intervention increased substantially.
| 0 | PMC9747447 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S384 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1905 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04110-9
10.1016/j.jval.2022.09.1905
Article
MT31 A Novel Medical Technology for Rapid Molecular Diagnostics (Nicking Enzyme Amplification Reaction [NEAR]) - A Systematic Literature Review, Meta-Analysis
Grys M 1
Pieniazek I 1
Walczak J 1
Debray R 2
Cybulski J 3
Przygodzki P 4
1Arcana Institute, a Certara company, Cracow, MA, Poland
2Abbott Rapid Diagnostics Ltd, Maidenhead, UK
3Abbott Medical Sp. z o.o., Warsaw, Poland
4Abbott Medical Sp. z o.o., Warszawa, Poland
14 12 2022
12 2022
14 12 2022
25 12 S384S384
Copyright © 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
pmcObjectives
The RT-PCR method is often regarded as the "gold standard" method for the detection of SARS-COV-2. A limitation of PCR however, is the ‘time to result’. With a rapid molecular diagnostic test (intervention), results can be obtained much quicker (3-15 minutes). The objective was to to evaluate the diagnostic efficacy of one of the rapid molecular diagnostic tests for the qualitative detection of SARS-CoV-2 (COVID-19) infection, in comparison to RT-PCR.
Methods
We systematically searched EMBASE, Medline and the Cochrane Library through November 31, 2021. All prospective studies on the diagnostic efficacy of the assessed intervention compared with RT-PCR in symptomatic patients were retrieved. Only studies conducted according to the valid protocol recommended by the manufacturer were included: dry swab collected by investigator; samples for intervention and control taken from the same anatomical place; "fresh" samples, tested shortly after collection without freezing.
Results
The meta-analysis of the eligible studies (n=7; 3,493 patients) showed sensitivity of the intervention was 0.956 (95% CI: 0.918 - 0.976) and specificity was 0.995 (95% CI: 0.946-0.999) compared with the RT-PCR. In the subset of studies, which considered patients with no more than 7 days from the onset of symptoms, the sensitivity of the intervention was 0.987 (95% CI: 0.917 - 0.998) and the specificity was 0.989 (95% CI: 0.989 - 0.989) compared with the RT-PCR method.
Conclusions
There is significant unmet need for both a rapid and accurate diagnostic test to detect COVID-19. Thanks to the technology used to obtain an accurate result, clinicians can make evidence-based decisions in a short period of time. Compared to other published systematic reviews (SR), this SR showed that following the updated protocol for the intervention usage the diagnostic efficacy of the intervention increased substantially.
| 0 | PMC9747448 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S328 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1619 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04110-9
10.1016/j.jval.2022.09.1905
Article
MT31 A Novel Medical Technology for Rapid Molecular Diagnostics (Nicking Enzyme Amplification Reaction [NEAR]) - A Systematic Literature Review, Meta-Analysis
Grys M 1
Pieniazek I 1
Walczak J 1
Debray R 2
Cybulski J 3
Przygodzki P 4
1Arcana Institute, a Certara company, Cracow, MA, Poland
2Abbott Rapid Diagnostics Ltd, Maidenhead, UK
3Abbott Medical Sp. z o.o., Warsaw, Poland
4Abbott Medical Sp. z o.o., Warszawa, Poland
14 12 2022
12 2022
14 12 2022
25 12 S384S384
Copyright © 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
pmcObjectives
The RT-PCR method is often regarded as the "gold standard" method for the detection of SARS-COV-2. A limitation of PCR however, is the ‘time to result’. With a rapid molecular diagnostic test (intervention), results can be obtained much quicker (3-15 minutes). The objective was to to evaluate the diagnostic efficacy of one of the rapid molecular diagnostic tests for the qualitative detection of SARS-CoV-2 (COVID-19) infection, in comparison to RT-PCR.
Methods
We systematically searched EMBASE, Medline and the Cochrane Library through November 31, 2021. All prospective studies on the diagnostic efficacy of the assessed intervention compared with RT-PCR in symptomatic patients were retrieved. Only studies conducted according to the valid protocol recommended by the manufacturer were included: dry swab collected by investigator; samples for intervention and control taken from the same anatomical place; "fresh" samples, tested shortly after collection without freezing.
Results
The meta-analysis of the eligible studies (n=7; 3,493 patients) showed sensitivity of the intervention was 0.956 (95% CI: 0.918 - 0.976) and specificity was 0.995 (95% CI: 0.946-0.999) compared with the RT-PCR. In the subset of studies, which considered patients with no more than 7 days from the onset of symptoms, the sensitivity of the intervention was 0.987 (95% CI: 0.917 - 0.998) and the specificity was 0.989 (95% CI: 0.989 - 0.989) compared with the RT-PCR method.
Conclusions
There is significant unmet need for both a rapid and accurate diagnostic test to detect COVID-19. Thanks to the technology used to obtain an accurate result, clinicians can make evidence-based decisions in a short period of time. Compared to other published systematic reviews (SR), this SR showed that following the updated protocol for the intervention usage the diagnostic efficacy of the intervention increased substantially.
| 0 | PMC9747449 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S485 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2407 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03556-2
10.1016/j.jval.2022.09.1351
Article
HSD7 Analysis of the Balanced Scorecard's Knowledge and Growth Subdimensions in Health Care Organizations During the COVID-19 Pandemic
Amer F 1
Hammoud S 1
Khatatbeh H 2
Lohner S 2
Boncz I 2
Endrei D 2
1University of Pécs, Pécs, BA, Hungary
2University of Pécs, Pécs, Hungary
14 12 2022
12 2022
14 12 2022
25 12 S274S274
Copyright © 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
pmcObjectives
We intended to review all the knowledge and growth subdimensions used in balanced scorecard (BSC) implementations and then to assess the impact of the pandemic on the knowledge and growth subdimensions at healthcare organizations (HCOs).
Methods
We performed a systematic review in accordance with PRISMA guidelines to find all knowledge and growth key performance indicators (KPIs) used in BSC implementations from the time of inception until October 2020 in PubMed, Embase, Cochrane, Google Scholar databases, and Google's search engine. Second, we searched for independent studies using the resulting knowledge and growth subdimensions with the COVID-19 keyword in Google engine and Google Scholar until June 2021.
Results
106 KPIs were extracted from 36 implementations. Categorizing the KPIs resulted into 2 major-dimensions with 3 subdimensions each. Many studies evaluated healthcare workers’ (HCWs’) knowledge, attitudes, and practices (KAP) at the beginning of the pandemic. HCW adherence to infection control measures is affected by their KAP toward COVID-19. Some studies referred to insufficient knowledge about COVID-19 among nurses. Surgeons were worried about losing their skills after months of lockdown. HCWs were obliged to learn digital health skills and effectively communicate with patients during the pandemic. It was found that publication productivity correlates with factors such as epidemiologic, healthcare system-related, and pre-COVID publication expertise factors. Additionally, the role of technology and information in tackling COVID-19 importance was explained. Telehealth allowed HCWs to provide care for patients without direct physical contact, especially to patients at quarantine, while keeping them safe. Researchers have summarized the technologies emerged to mitigate the threats of COVID-19.
Conclusions
Researchers are encouraged to analyze the pandemic impact on knowledge and growth subdimensions. Healthcare managers need to remain updated with emerging technologies, allocate resources to invest in them, and develop the required skills in HCWs to utilize them properly.
| 0 | PMC9747450 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S274 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1351 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02985-0
10.1016/j.jval.2022.09.781
Article
EE540 Cost-Effectiveness of Vaccines Targeting Infectious Diseases - Has COVID-19 Changed the Landscape?
Pitman R 1
Khurana P 2
1ICON Plc, Dublin, BKM, Ireland
2ICON Plc, Dublin, PA, Ireland
14 12 2022
12 2022
14 12 2022
25 12 S162S162
Copyright © 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
pmcObjectives
To explore the ways in which a pandemic may alter the immediate and ongoing cost-effectiveness assessment of a vaccine, using COVID-19 as an example.
Methods
When gripped by a pandemic of the magnitude and severity of COVID-19, the health impact on individuals and health services, and the economic consequences of the ensuing lockdowns, mean that there is little debate around the cost-effectiveness of vaccines that allowed the return to something approaching a normal existence. With the ongoing need to maintain vaccine coverage, the appearance of new vaccines on the market and a global cost-of-living crisis, these debates are starting to take place, but have the rules changed? What is the nature of the “new normal” and what does it mean for cost-effectiveness analyses of COVID-19 vaccines?
Results
For the first vaccines available, the comparison with no vaccination and the associated health and economic cost mean that even a modestly effective vaccine with a favourable clinical profile would be cost-effective. As the pandemic starts to be controlled and new vaccines arrive comparisons re-centre on existing vaccines. We postulate that the immense strain placed on health services by the pandemic has increased the cost of health care, pushing up the cost of gaining a quality-adjusted life year (QALY), thereby reducing the opportunity cost of funding a new vaccine and so raising the cost-effectiveness threshold. If such revised thresholds were adopted by reimbursement bodies, this would make it harder for vaccines with a lower efficacy to be made cost-effective by a reduction in price alone. If the pandemic has indeed increased the cost of a QALY, then we might further postulate that the cost-effectiveness threshold is now a function of COVID-19 incidence.
Conclusions
This would have consequences beyond interventions targeting COVID-19.
| 0 | PMC9747451 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S162 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.781 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04607-1
10.1016/j.jval.2022.09.2402
Article
SA8 Impact of the COVID-19 Pandemic on Health Care Resource Utilisation and Costs in COPD in England: A Population-Based Study
Ismaila AS 1
Tritton T 2
Han X 1
Holbrook T 2
Numbere B 3
Ford AF 2
Massey L 2
Fu Q 1
Hutchinson FM 4
Birch HJ 5
Leather D 6
Sharma R 5
Compton C 5
Rothnie KJ 5
1Value Evidence and Outcomes, R&D Global Medical GlaxoSmithKline, Collegeville, PA, USA
2Adelphi Real World, Bollington, UK
3Value Evidence and Outcomes, R&D Global Medical, GlaxoSmithKline, London, UK
4Country Medical Office – United Kingdom and Ireland GlaxoSmithKline, Brentford, Middlesex, UK
5Value Evidence and Outcomes, R&D Global Medical, GlaxoSmithKline, Brentford, Middlesex, UK
6Global Medical Affairs, GlaxoSmithKline, London, UK
14 12 2022
12 2022
14 12 2022
25 12 S484S484
Copyright © 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
pmcObjectives
Delivery of medical care for chronic diseases has been disrupted by the COVID-19 pandemic. We describe all-cause and COPD-related healthcare resource utilisation (HCRU) and costs among patients with COPD during the initial period of the COVID-19 pandemic in England.
Methods
This was a retrospective dynamic cohort study of English COPD patients (FEV1/FVC<0.7) aged ≥35 years, for the period from Mar 2018 until Aug 2020 using primary care and linked hospital data. We assessed monthly all-cause and COPD-related HCRU and total direct healthcare costs over the study period and compared the months of the early pandemic (April–Aug 2020) to prior years.
Results
In total, 119,512 COPD patients were included (mean [SD] age: 69.6 [10.6] years, 54.1% males). Mean monthly all-cause face-to-face primary care, secondary care outpatient, and inpatient attendances were lower in April 2020 compared with April 2019, with reductions of 62.8%, 38.5%, and 57.1%, respectively. Mean monthly all-cause telephone primary care consultations increased 211.1% between April 2019 and April 2020. Mean total all-cause healthcare costs were 25.4% lower in April 2020 compared with April 2019. Mean monthly COPD-related face-to-face primary care, secondary care outpatient and hospital attendances, were lower in April 2020 compared with April 2019, with reductions of 78.9%, 25.0% and 60.0%, respectively. Mean monthly COPD-related telephone primary care consultations increased 300.0% between April 2019 and April 2020. Mean total COPD-related healthcare costs were 44.4% lower in April 2020 compared with April 2019. The levels of healthcare interactions following April 2020 did not return to pre-pandemic levels by the end of the observation period.
Conclusions
All-cause and COPD-related primary care and secondary care outpatient attendances and hospital admissions decreased among patients with COPD during the COVID-19 pandemic. Telemedicine became a more frequently used channel for accessing healthcare during the early pandemic for COPD patients. Funding: GSK (214629).
| 0 | PMC9747452 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S484 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2402 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03382-4
10.1016/j.jval.2022.09.1177
Article
HPR45 Medical Quality Indicators Trends During the Coronavirus Pandemic in Israel: Meuhedet Health Services Real Data Analysis and Future Conclusions
Klang S 1
Merling S 2
Regev-Rosenberg S 3
Pugatch M 1
1University of Haifa, Haifa, Israel
2Meuhedet Health Services, Tel-Aviv, TA, Israel
3Meuhedet Health Services, Tel Aviv, Israel
14 12 2022
12 2022
14 12 2022
25 12 S241S241
Copyright © 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
pmcObjectives
This study focuses on examining the changes in quality Indicators in Meuhedet insurers during the three waves of the COVID-19 epidemic between 2020 and 2021, compared to the prior years of 2019 and 2018.
Methods
Meuhedet Health Services is the third-largest HMO in Israel and has about 1.28 million insured citizens, with all their medical data managed through computerized electronic files. The study focuses on examining the changes in specific quality during the 3 waves between 2020 and 2021 while handling the COVID-19 epidemic. The specific quality indicators are:
• early detection in breast cancer
• early detection in colon cancer
• eye test in diabetic population
• cholesterol lab test in diabetic population
• cholesterol lab test in general population ages 55-74
• Rate of Performance of Vaccination against Pneumococcal Disease
• Rate of Performance of Vaccination against Influenza Virus – Ages 65 and above
Results
A significant reduction was observed in all indicators and started immediate with the first wave, while an opposite trend was detected in the 2 vaccination measures. The highest reduction of 4% was observed in diabetic eye test while a 5-6% increase in the performance rate of vaccinations. It seems that patients preferred to stay at home because of fear of COVID-19 contamination. No doubt that the COVID-19 pandemic influenced dramatically on the rate of vaccination. The two vaccines supposed to prevent or reduce the symptoms of the diseases in the respiratory system.
Conclusions
Since new variants of COVID-19 will be part of our lives or even a new pandemic will appear in the next few years, we should learn how to continue living with the pandemic and develop alternative medical services to maintain health states. Digital services, telemedicine, home care, and remote services must gain priority in health medical organizations to prepare for the next pandemic.
| 0 | PMC9747453 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S241 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1177 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04459-X
10.1016/j.jval.2022.09.2254
Article
RWD29 Use of Telemedicine Services and Health Outcomes in Hypertensive Patients in Pre- and Post-COVID-19 Periods in the United States
Daral S 1
Madge V 1
Markan R 1
Chopra A 1
Kukreja I 2
Nayyar A 1
Roy A 1
Gaur A 1
Pandey S 1
Verma V 3
1Optum, Gurugram, HR, India
2Optum, New Delhi, DL, India
3Optum, Gurgaon, HR, India
14 12 2022
12 2022
14 12 2022
25 12 S453S453
Copyright © 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
pmcObjectives
This study examines use of telemedicine services and health outcomes in patients with hypertension (HTN) in pre- and post-COVID 19 periods in the US.
Methods
A retrospective analysis, using Optum® de-identified Electronic Health Record dataset, was done among hypertensive patients on Medicare plans in three different time periods: 1st Jan 2018 - 30th June 2018, 1st Jan - 30th June 2019, and 1st Jan - 30th June 2020 (first two time periods are pre-COVID 19 and the last one is post-COVID 19). The date of first EHR with mention of HTN diagnosis was considered index date. Study participants were categorized into those who used only telemedicine services (Telemedicine group); only other places of service like outpatient, inpatient, or office (Other POS group); and those who used both telemedicine and other places of service (Both POS groups). Patients were followed for 6-months post-index to determine use of anti-HTN medications, resource utilization, and healthcare outcomes.
Results
Fewer than 100 patients in each study period belonged to Telemedicine group. Majority (55%) patients in 2018 (pre-COVID 19) belonged to Other POS group, but in 2020 (post-COVID 19) majority (61%) patients belonged to Both POS group. About 70% patients in each of three groups were prescribed anti-HTN drugs and adherence was >90%. About ∼60% patients in Telemedicine group had 2-6 healthcare encounters while ∼80% in Other POS group and ∼95% in Both POS groups had >6 healthcare encounters during follow-up period. Significantly more patients in Both POS groups received anti-HTN nutritional counseling as compared to other two groups. Also, blood pressure was controlled in significantly higher percentage of patients in Both POS groups as compared to other two groups.
Conclusions
Patients who use telemedicine and other places of service are more likely to receive anti-HTN nutritional counseling and have better blood pressure control.
| 0 | PMC9747454 | NO-CC CODE | 2022-12-15 23:22:00 | no | Value Health. 2022 Dec 14; 25(12):S453 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2254 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04138-9
10.1016/j.jval.2022.09.1933
Article
OP17 Analyzing Health System Resilience From the Perspective of Rare Diseases
Emami SG 1
Lorenzoni V 2
Marinello D 3
Palla I 4
Turchetti G 5
1Scuola Superiore Sant'Anna, Pisa, Italy
2Scuola Superiore Sant’Anna, Pisa, Italy
3European Reference Network, Pisa, Italy
4Scuola Superiore Sant'Anna, Pisa, PI, Italy
5Institute of Management, Scuola Superiore Sant’Anna, Pisa, Italy, Pisa, Italy
14 12 2022
12 2022
14 12 2022
25 12 S389S389
Copyright © 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
pmcObjectives
Health systems resilience (HSR) is generally understood as the capacity to absorb, adapt or transform in order to maintain essential functions when faced shocks. Following the COVID-19 pandemic, the concept of HSR has gained popularity, and there is now greater recognition of the importance of HSR among healthcare professionals and policymakers. A deep understanding of factors affecting HSR and practical strategies to achieve it, is still a matter of debate. Therefore, the present study aims at exploring HSR in the field of rare diseases, a vulnerable group exhibiting unique demands and particular requirements for ongoing care.
Methods
By a scoping review of the literature, we identified 53 characteristics relevant toHSR. by classifying characteristics according to the WHO building blocks, we developed a survey directed to healthcare professionals dealing with rare diseases. The survey aims to understand to which extent each characteristic matters for achieving HSR in this context. After the preliminary development of the survey, comprehensiveness and clarity were assessed, sharing the survey with a restricted group of experts working and not with rare diseases. Based on their feedback, the survey was revised and.
Results
Feedback from the restricted groups was generally positive, and minimal changes were introduced to improve the clarity of the survey and to include specific questions in addition to characteristics found in the literature review (i.e., the importance of being part of a large network dealing with a rare disease). The survey was implemented online and then shared using social media and directly mailing the link to an expert in the treatment of rare diseases.
Conclusions
We expect to figure out a comprehensive set of characteristics that are appropriate to define resilience in the context of rare diseases. Our framework will help to suggest strategies to deal with shocks within such a context effectively.
| 0 | PMC9747455 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S389 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1933 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04512-0
10.1016/j.jval.2022.09.2307
Article
RWD82 Influence of the COVID-19 Pandemic on Patients Receiving Oral Anticoagulants for the Treatment of Non-Valvular Atrial Fibrillation
Comin-Colet J 1
Sicras-Mainar A 2
Pérez Román I 3
Salazar J 4
del Campo Alonso MI 4
Echeto A 4
Vilanova D 4
Delgado O 5
1Hospital Universitari Bellvitge, Barcelona, Spain
2Atrys Health, Barcelona, Spain
3Atrys Health, Madrid, Spain
4Bristol Myers Squibb, Madrid, Spain
5Hospital Universitario Son Espases, Palma de Mallorca, Spain
14 12 2022
12 2022
14 12 2022
25 12 S464S464
Copyright © 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
pmcObjectives
The aim of this study is to evaluate the impact of the COVID-19 pandemic in patients with NVAF receiving anticoagulant treatment with vitamin K antagonists (VKA) or new direct-acting oral anticoagulants (NOAC) in clinical practice in Spain.
Methods
This is an observational and retrospective study based on the electronic medical records of the BIG-PAC® database, which gathers information from 1.8 million individuals in Spain. Prevalent patients were those on treatment with NOAC/VKA on 14/03/2019 (pre-COVID-19 period, PCP) and on 14/03/2020 (COVID-19 period, CP), and were followed up to 12 months. Incident patients were those who started their treatment with NOAC/VKA between 15/03/2019 and 13/03/2020 (PCP) and from 15/03/2020 to 13/03/2021 (CP) and were analyzed only on their first day of treatment. Demographic characteristics, comorbidities, effectiveness, treatment patterns and healthcare resources utilization were compared in the groups of the study.
Results
Prevalent patients amounted to 12,336 patients and 13,342 patients in the PCP and CP, respectively. Regarding incident patients, 1,612 patients and 1,602 patients were included in the PCP and in the CP, respectively. Prevalent patients on treatment with VKA had more cardiovascular events (strokes, episodes of thromboembolism and major bleedings) than those receiving NOAC (PCP: 7.9% vs. 4.2%, p<0.001; CP: 8.3% vs. 3.8%, p<0.001). VKA patients had a 12% higher mortality rate than those on treatment with NOAC (Hazard ratio=0.88 [95% CI: 0.81 – 0.95], p=0.033). In addition, NOAC patients had higher persistence rates after 12 months than VKA patients (PCP: 78.9% vs. 52.1%, p<0.001; CP: 80.3% vs. 49.2%, p<0.001), and overall, required fewer healthcare visits and hospitalizations during the pandemic than those on treatment with VKA.
Conclusions
In comparison to VKA, the use of NOAC in patients with NVAF seems to have reduced the incidence of cardiovascular events and the use of healthcare resources, particularly during the pandemic.
| 0 | PMC9747456 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S464 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2307 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04512-0
10.1016/j.jval.2022.09.2307
Article
RWD82 Influence of the COVID-19 Pandemic on Patients Receiving Oral Anticoagulants for the Treatment of Non-Valvular Atrial Fibrillation
Comin-Colet J 1
Sicras-Mainar A 2
Pérez Román I 3
Salazar J 4
del Campo Alonso MI 4
Echeto A 4
Vilanova D 4
Delgado O 5
1Hospital Universitari Bellvitge, Barcelona, Spain
2Atrys Health, Barcelona, Spain
3Atrys Health, Madrid, Spain
4Bristol Myers Squibb, Madrid, Spain
5Hospital Universitario Son Espases, Palma de Mallorca, Spain
14 12 2022
12 2022
14 12 2022
25 12 S464S464
Copyright © 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
pmcObjectives
The aim of this study is to evaluate the impact of the COVID-19 pandemic in patients with NVAF receiving anticoagulant treatment with vitamin K antagonists (VKA) or new direct-acting oral anticoagulants (NOAC) in clinical practice in Spain.
Methods
This is an observational and retrospective study based on the electronic medical records of the BIG-PAC® database, which gathers information from 1.8 million individuals in Spain. Prevalent patients were those on treatment with NOAC/VKA on 14/03/2019 (pre-COVID-19 period, PCP) and on 14/03/2020 (COVID-19 period, CP), and were followed up to 12 months. Incident patients were those who started their treatment with NOAC/VKA between 15/03/2019 and 13/03/2020 (PCP) and from 15/03/2020 to 13/03/2021 (CP) and were analyzed only on their first day of treatment. Demographic characteristics, comorbidities, effectiveness, treatment patterns and healthcare resources utilization were compared in the groups of the study.
Results
Prevalent patients amounted to 12,336 patients and 13,342 patients in the PCP and CP, respectively. Regarding incident patients, 1,612 patients and 1,602 patients were included in the PCP and in the CP, respectively. Prevalent patients on treatment with VKA had more cardiovascular events (strokes, episodes of thromboembolism and major bleedings) than those receiving NOAC (PCP: 7.9% vs. 4.2%, p<0.001; CP: 8.3% vs. 3.8%, p<0.001). VKA patients had a 12% higher mortality rate than those on treatment with NOAC (Hazard ratio=0.88 [95% CI: 0.81 – 0.95], p=0.033). In addition, NOAC patients had higher persistence rates after 12 months than VKA patients (PCP: 78.9% vs. 52.1%, p<0.001; CP: 80.3% vs. 49.2%, p<0.001), and overall, required fewer healthcare visits and hospitalizations during the pandemic than those on treatment with VKA.
Conclusions
In comparison to VKA, the use of NOAC in patients with NVAF seems to have reduced the incidence of cardiovascular events and the use of healthcare resources, particularly during the pandemic.
| 0 | PMC9747457 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S276 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1362 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04159-6
10.1016/j.jval.2022.09.1954
Article
PCR19 SARS-COV-1 Omicron BA.1 Associated Impact on Quality of Life and Medication Adherence of Multiple Myeloma Patients Treated With Thalidomide or Its Analogues Plus Dexamethasone 1JAN-31MAR2022
Burruss R 1
Kim V 2
Arikian V 3
1Burruss Pharmacy Consulting, Ashland, VA, USA
2University of Maryland, Baltimore, MD, USA
3SUNY Downstate Medical Center, Brooklyn, NY, USA
14 12 2022
12 2022
14 12 2022
25 12 S393S393
Copyright © 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
pmcObjectives
During 1/1/-3/31/2022, SARS-CoV-2 Omicron BA.1 (CoVID-19 OBA.1) was pandemic in USA. Two study objectives are to determine if CoVID-19 OBA.1 was associated with a change in: (1) adherence to thalidomide or its analogues (Ta) plus dexamethasone (TaD) used to treat multiple myeloma (MM) patients serviced by specialty pharmacy medication therapy management (SPMTM) and (2) patient-reported quality of life (QOL).
Methods
A retrospective, observational, pre-/post-design study of MM patient adherence to oral TaD and associated QoL was conducted at beginning of and during CoVID-19 OBA.1 pandemic. Patient assessments (PA) occurred at start of care (SOC) and follow-up (F-U) 7 days before dispenses. PA included EQ-5D-5L QoL metrics. Descriptive statics used to calculate QoL dimensional means before and after starting TaD and then on F-U SPMTM. Differences in means represented patient perceived changes in QoL. The medication possession ratio (MPR) was calculated using the F-U from both the Pre- and During-CoVID-19 OBA.1.
Results
MPR = 0.99 prior to index time and was 0.96 During-CoVID-19 OBA.1 (3.03%). 219 PA were done During-CoVID-19 OBA.1 (94 MM patients, 40 SOC, 179 F-U). Differences in QoL means Pre- vs During-CoVID-19 OBA.1 were: Mobility -0.0036 (0.36%), Self-Care +0.0002 (0.02%), Usual Activities -0.0001 (0.001%), Pain/Discomfort -0.002 (0.2%), Anxiety/Depression +0.0018 (0.18%), Overall Health State +0.0157 (1.57%). Note: “-” = improvement; ”+”=worsened in Dimensions 1-5; “+” = improvement and ”-“ = worsened in Overall Health state. Percentages = absolute values.
Conclusions
During-CoVID-19 MPR decreased by 3.03% compared to Pre-CoVID-19 OBA.1. Pre- and During-CoVID-19 OBA.1 MPR were higher than the industry standard of >0.9.5 Ta have FDA REMS requirements which may have contributed to MPRs being > standard.6 On average, patients reported QoL on Mobility, Self-Care and Anxiety/Depression worsened but improved on Usual Activities and Pain/Discomfort. Over-all Health rating improved slightly. Explanations for worsened QoL metrics are discussed.7 Additional studies are suggested.
| 0 | PMC9747458 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S393 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1954 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02536-0
10.1016/j.jval.2022.09.332
Article
EE80 The Potential Clinical and Economic Benefits of a Next Generation Omicron-Containing (BA.1) Bivalent Sars-Cov-2 Booster Compared to First Generation Prototype Boosters in Germany Assuming BA.4/BA.5 Dominance
Maschio M 1
Schweikert B 2
Ultsch B 3
Cai R 4
Fust K 5
Lee A 5
Nasir A 6
Buck P 6
Van de Velde N 6
Kohli M 5
1Quadrant Health Economics Inc, Guelph, ON, Canada
2ICON, Munich, BY, Germany
3Moderna, Germany GmbH, Munich, Germany
4ICON plc, Amsterdam, Netherlands
5Quadrant Health Economics Inc, Cambridge, ON, Canada
6Moderna, Inc., Cambridge, MA, USA
14 12 2022
12 2022
14 12 2022
25 12 S68S69
Copyright © 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
pmcObjectives
An investigational next-generation bivalent SARS-CoV-2 booster (mRNA-1273.214) demonstrated superior neutralizing antibody titers against Omicron, and higher binding antibody titers against other variants (Alpha, Beta, Gamma, Delta), compared to the original monovalent vaccine (mRNA-1273). Results are consistent for the emerging Omicron sub-lineages BA.4 and BA.5 likely to dominate COVID-19 cases during the Fall 2022 season. Our objective was to estimate the potential incremental benefits of boosting with mRNA-1273.214 in September 2022 in Germany in (a) adults ≥18 years and (b) adults ≥60 years, compared to mRNA-1273.
Methods
We developed a static decision tree model to estimate the annual cases of COVID-19 and their consequences in Germany for 100,000 persons vaccinated with mRNA-1273.214 compared to mRNA-1273. Vaccine effectiveness against symptomatic infection and hospitalization over the 1-year time horizon was estimated using models of neutralizing antibody levels, assuming Omicron variants BA.4 and BA.5 will be predominant. Incidence projections, resource use and health care costs were derived for a German setting.
Results
We estimated there would be 268 hospitalizations and 62 deaths for every 100,000 Germans aged ≥18 years if vaccinated with the monovalent booster. Boosting with the bivalent booster instead of the monovalent would reduce hospitalizations by 27 and deaths by 7 per 100,000 vaccinated. Compared to the mRNA-1273, COVID-19 treatment costs would be reduced by €496,000 per 100,000 persons with bivalent booster use. For adults ≥60 years, use of the bivalent booster would lead to a reduction of 62 hospitalizations, 18 deaths and €1,122,000 in COVID-19 treatment costs for every 100,000 vaccines administered compared to the monovalent booster.
Conclusions
The broad immune response associated with the next generation bivalent vaccine is expected to avert more hospitalizations, deaths, and treatment costs if Omicron BA.4 and BA.5 are circulating in Germany, especially amongst adults aged ≥60 years.
| 0 | PMC9747459 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S68-S69 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.332 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04624-1
10.1016/j.jval.2022.09.2419
Article
SA25 Evolution of the Number of Metastatic Lung Cancer Patients before and during the COVID 19 Pandemic: A French National Hospital Database Analysis
Sano B 1
Petrica N 2
Finas R 2
Rosé M 2
1Alira Health, Aubervilliers, France
2Alira Health, Paris, France
14 12 2022
12 2022
14 12 2022
25 12 S487S487
Copyright © 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
pmcObjectives
Healthcare professionals have emphasized that the COVID-19 pandemic has resulted in significant gaps in the number of new cancer diagnosis. The French HTA estimated that 30,000 cases were undiagnosed in France between March and May 2020.1 Lung cancer is a public health issue as it was responsible for 21% of all cancer deaths in 2018.2 It is associated with a fast progression and metastatic potency. The objective of this study was to describe the recent evolution of the number of patients with metastatic lung cancer (mLC) in France, by considering the patients’ characteristics and health center’s localization.
Methods
This is a retrospective study based on the French national claims hospitals database (PMSI), covering all public and private care centers in France. All hospitalizations from January 2018 to December 2020 with ICD-10 codes for lung cancer (C34) combined with at least one metastasis code (C77, C78, C79) were extracted to identify adult patients with mLC.
Results
Overall, 81,532 mLC patients were identified with a mean age of 66 years (± 10.4), and 34.6% female. Between 2018 and 2020, the number of patients diagnosed for mLC decreased by 21.0% (n=29,697 vs n=23,485). This decrease was different according to the demographic characteristic of patients (23.1% for men vs 16.9% for women; 26.9% for patients aged between 50 and 70 vs 16.9% for patients under 50 and 21.1% for those over 70) and ranging between 16.8% in the Nouvelle-Aquitaine region to 26.8% in the Île-de-France region. Men aged 50-70 years were the sub-population most affected by the decrease in mLC diagnoses in most regions.
Conclusions
This study showed a gap in diagnosis of mLC in 2020 underlining the impact of the COVID-19 pandemic on the hospital care system. This observed gap varied by age, gender and region.
| 0 | PMC9747460 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S487 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2419 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02914-X
10.1016/j.jval.2022.09.710
Article
EE465 Cost-Effectiveness of Sotrovimab for the Treatment of Mild-to-Moderate COVID-19 in Patients at High Risk of Disease Progression in Italy
Piccolo F 1
Tosh J 2
De Boisvilliers S 3
Patel S 2
Patel V 4
1GlaxoSmithKline, Verona, Italy
2Evidera Inc, London, UK
3Evidera PPD, Paris, France
4GlaxoSmithKline, Brentford, UK
14 12 2022
12 2022
14 12 2022
25 12 S147S147
Copyright © 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
pmcObjectives
Sotrovimab is a monoclonal antibody approved in Europe for the treatment of adults and adolescents (age ≥12 years) with COVID-19 who do not require oxygen supplementation and are at increased risk of progressing to severe COVID-19. We assessed the cost-effectiveness of sotrovimab versus standard of care (SOC) as an outpatient treatment for patients (aged ≥18 years, in line with the pivotal COMET-ICE trial) in Italy with mild-to-moderate COVID-19 at high risk of disease progression.
Methods
A Markov cohort model with Discretely Integrated Condition Event simulation followed a cohort of 1,000 patients in 5-year, 10-year and lifetime (100 years) time horizons from an Italian National Health Service perspective. At model development, SOC consisted of treatments such as antipyretics. As sotrovimab was an add-on to SOC, no treatment-related cost was allocated to SOC. Sotrovimab’s treatment effect was obtained from the COMET-ICE trial, which showed a 79% relative risk reduction of all-cause hospitalizations ≥24 hours or death from any cause within 29 days of randomization. Cost, resource use and quality-of-life inputs were obtained from published literature and national/regional tariffs. The model was internally and externally validated.
Results
The sotrovimab cohort was associated with 5-year, 10-year and lifetime quality adjusted life-year (QALY) gains of 143.66, 235.00 and 346.87, respectively, with increased lifetime direct healthcare costs of €2,537,956. Incremental cost-effectiveness ratios versus SOC were €17,667 (5-year), €10,800 (10-year) and €7,317 (lifetime) per QALY. Deterministic sensitivity analysis found that hospitalization rate and treatment cost had the largest impact on the ICER. In probabilistic sensitivity analysis, sotrovimab was cost-effective in 100% of iterations based on a willingness-to-pay threshold of €15,000 per QALY gained.
Conclusions
Sotrovimab was found to be cost-effective versus SOC for early treatment of high-risk patients with COVID-19 in Italy. Funding: GSK (Study 215021) / Vir Biotechnology
| 0 | PMC9747461 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S147 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.710 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04559-4
10.1016/j.jval.2022.09.2354
Article
RWD129 A Comparison of ICU Admission Rate and Related Cost Among Patients Taking Nirmatrelvir and Ritonavir Combination Versus Molnupiravir for Treatment of Mild to Moderate COVID-19 in the US
Kukreja I 1
Gaur A 2
Upadhyay N 2
Bhalani S 2
Gupta A 2
Verma V 3
Pandey S 2
Roy A 4
Nayyar A 2
Daral S 2
Chawla S 2
Mohanty P 2
1Optum, New Delhi, DL, India
2Optum, Gurugram, HR, India
3Optum, Gurgaon, HR, India
4Optum India, Gurgaon, HR, India
14 12 2022
12 2022
14 12 2022
25 12 S474S474
Copyright © 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
pmcObjectives
This study aimed to estimate the ICU admission rate and related cost in patients taking Molnupiravir versus Nirmatrelvir+Ritonavir, the oral antiviral therapies to receive Emergency Use Authorization from the US FDA in December 2021 for the treatment of mild to moderate COVID-19 patients.
Methods
In this retrospective claim data study, Optum’s de-identified Clinformatics® Data Mart Database (Mainly Commercial and Medicare Advantage) is used to identify the patients who have been prescribed Molnupiravir or Nirmatrelvir+Ritonavir with NDC codes. The patient cohort is divided into two groups: one has been prescribed Molnupiravir and the other one has been prescribed Nirmatrelvir+Ritonavir. The patients in this study cohort have both medical and pharmacy claims. The study period is considered from the approval of these drugs, which is December 22nd and 23rd, 2021, to May 31st, 2022. The first fill date of the prescription for Molnupiravir and Nirmatrelvir+Ritonavir is considered the index date. All patients were followed for 30 days post index to look for any ICU admission and its related costs. The data was analyzed, and two tailed t-test and chi square test were applied.
Results
The percentage of patients who have been prescribed Molnupiravir is 25% (N= 4,851), while the patient cohort prescribed with Nirmatrelvir+Ritonavir is 75% (N= 14,479). Patients who have been prescribed Molnupiravir have a significantly higher ICU admission rate (1.2%) than patients who have been prescribed Nirmatrelvir+Ritonavir (0.2%) (P<0.001). The average cost related to ICU admission in patients who have taken Molnupiravir (mean-$15,439) does not show a difference from the cost of ICU admission in patients who have taken Nirmatrelvir+Ritonavir (mean-$13,383) (P = 0.72).
Conclusions
This study shows that the ICU admission rate is noticeably different in the cohort of patients taking Molnupiravir compared to the Nirmatrelvir+Ritonavir combination, where ICU-related costs are almost similar in both the cohorts.
| 0 | PMC9747462 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S474 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2354 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03624-5
10.1016/j.jval.2022.09.1419
Article
HSD76 Analysis of the Balanced Scorecard's External Subdimensions in Health Care Organizations During the COVID-19 Pandemic
Amer F 1
Hammoud S 2
Khatatbeh H 2
Lohner S 2
Boncz I 2
Endrei D 2
1University of Pécs, Pécs, BA, Hungary
2University of Pécs, Pécs, Hungary
14 12 2022
12 2022
14 12 2022
25 12 S288S288
Copyright © 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
pmcObjectives
We intended to review all the external subdimensions used in balanced scorecard (BSC) implementations and then to assess the impact of the pandemic on the external subdimensions at health care organizations (HCOs).
Methods
First, we performed a systematic review in accordance with PRISMA guidelines to find all external key performance indicators (KPIs) used in BSC implementations from the time of inception until October 2020 in PubMed, Embase, Cochrane, Google Scholar databases, and Google's search engine. Second, we searched for independent studies using the resulting external subdimensions with the COVID-19 keyword in Google engine and Google Scholar until June 2021.
Results
Out of 4031 studies, 36 implementations remained. From these, 73 external KPIs were extracted. Categorization of KPIs resulted in 2 major-dimensions. HCO’s building and community under which another 3 subdimensions were defined: privacy, corporate social responsibility (CSR), and market share. HCO’s building was extensively investigated and improved during the pandemic to increase the capacity and decrease the waiting time. However, researchers did not sufficiently investigate the ease of access to HCOs during the pandemic. Moreover, patient privacy was negatively affected in some countries, and due to breaching patient privacy in some countries, this may have stigmatized those patients. The political conflict during the pandemic in the Occupied Palestinian Territories was referred to impose a double epidemic effect on its health system. On the other hand, factors such as exemptions offered by HCO for poor patients, CSR, patient privacy concerns, and HCO market shares in COVID-19 still need more investigation.
Conclusions
Some of the external subdimensions were negatively affected during the pandemic, such as patient privacy, while others were positively affected, such as HCO building. However, researchers are encouraged to perform further assessments of how to improve the patient privacy, CSR and market share subdimensions during the pandemic.
| 0 | PMC9747463 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S288 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1419 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03247-8
10.1016/j.jval.2022.09.1042
Article
EPH121 Future Trends of the COVID-19 Pandemics: What Should We Expect?
Leleu H
Blachier M
Public Health Expertise, Paris, France
14 12 2022
12 2022
14 12 2022
25 12 S214S214
Copyright © 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
pmcObjectives
The COVID-19 pandemic has been a major global health threat since 2020. In France, since March 2020, over 30 million diagnoses of COVID-19 have been made, with likely as many undiagnosed. A lot of hope had been placed on SARS-COV-2 vaccination to control the pandemic, but the appearance of more transmissible and vaccine resistant variants have guaranteed that SARS-COV-2 will remain circulating in the population for the foreseeable future. Indeed, despite high vaccination coverage in France, two third of the COVID-19 diagnoses were made since January 2022, and new immunity-escaping variants are appearing regularly. The future of the pandemic is thus uncertain.
Methods
Using a SARS-COV-2 agent-based model that has been previously validated in the French context, we compared several scenarios, based on new variants emergences and their characteristics, to estimate potential future trends in SARS-COV-2 for 2023. New variants were assumed to appear every 4 months, based on historical trends, with randomly draw characteristics based on previous Omicron variants. Each new variant was assumed to partially escape previous variant’s immunity. The model was calibrated to the French epidemiology until May 2022 and assumed that no new non-pharmaceutical interventions would be put in place in the future and that adults over 65 would be revaccinated every fall.
Results
The model estimated that without new variants, the SARS-COV-2 pandemic would disappear by early 2023. With regular new variant emergence, depending on the contagiosity and immune escape of the variants between 69.5 million and 112.6 million infections could occur in 2023 with 26.4 and 42.8 diagnosed.
Conclusions
Based on the regular emergence of new SARS-COV-2 variant, COVID-19 is likely here to stay for the long-term. Strategies should be adapted for this possibility.
| 0 | PMC9747464 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S214 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1042 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03421-0
10.1016/j.jval.2022.09.1216
Article
HPR86 Sustainability of Healthcare Systems in the Wake of COVID-19: The UK VPAS Case Study
Macaulay R
Precision Advisors, London, UK
14 12 2022
12 2022
14 12 2022
25 12 S248S248
Copyright © 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
pmcObjectives
The 2019 Voluntary Scheme for Branded Medicines Pricing and Access (VPAS) is a 5-year voluntary agreement between the United Kingdom’s Department of Health and Social Care (DHSC) and the Association of the British Pharmaceutical Industry (ABPI) that aims to support pharmaceutical industry innovation alongside ensuring affordability. One key aspect is a cap limiting the growth of the branded medicines bill to a maximum of 2% per annum, which is rebated back by VPAS members if exceeded. The COVID-19 pandemic placed unprecedented pressure on healthcare systems’ expenditure and this research reviews its impact in relation to this medicines expenditure cap.
Methods
Publicly-available DHSC VPAS documentation was screened for forecasted and actual repayment percentages/amounts (on 09-May-2022).
Results
Annually, the DHSC set the repayment percentage for that year and forecast it for the upcoming year. The repayment percentage for 2019 was set at 9.6% and forecasted 14.2% for 2020. The 2020 actual repayment percentage was 5.9% and the 2021 forecast was 9.0%. The 2021 actual repayment percentage was 5.1% and the 2022 forecast was 5.8%. The 2022 actual repayment percentage was 19.1% and the 2023 forecast was 26.0%. However, in January 2022 the DHSC and ABPI announced a one-off amendment to VPAS capping the repayment percentage to 15% for 2022. The magnitude of the repayments under VPAS totaled £845m in 2019, £594m in 2021 and £564m in 2021.
Conclusions
Repayments under VPAS have totaled over £2bn during its first 3 years. Whilst this represent significant savings for the DHSC, this may not be sustainable for industry; a forecast 26% rebate in 2023 could, if realized, amount to over £2 billion in repayments for that year alone. The VPAS expires at the end of 2023 and balancing the post-COVID healthcare budgetary pressures alongside financial implications for industry may pose for some very challenging negotiations.
| 0 | PMC9747465 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S248 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1216 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02841-8
10.1016/j.jval.2022.09.637
Article
EE391 Impact of the COVID-19 Pandemic on the Healthcare Resource Use of People With Newly Diagnosed Mood/Affective Disorder
Junker S 1
Knapp R 1
Hahn P 2
Maywald U 3
Hardtstock F 1
1Cytel Inc., Berlin, Germany
2IPAM e.V., Wismar, Germany
3AOK PLUS, Dresden, Germany
14 12 2022
12 2022
14 12 2022
25 12 S132S132
Copyright © 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
pmcObjectives
Literature suggests an impact of the COVID-19 pandemic on mental health. However, the impact on healthcare resource use (HCRU) among patients newly-diagnosed with mood/affective disorders remains unclear.
Methods
Adults with ≥1 inpatient/outpatient diagnosis of a mood/affective disorder (ICD-10 F30-F39) from 01/01/2018–31/12/2020 were identified from a German claims dataset. A 18-month washout period was applied to ensure incidence of the diagnosis. HCRU outcomes were observed during a 6-month follow-up period. Patients were broken down into two cohorts based on whether their follow-up period fell into the pre-COVID or COVID period (cut-off 01/04/2020); patients with both pre-COVID and COVID periods were excluded.
Results
A total of 132,103 patients were identified (pre-COVID: 97,189; COVID: 34,914). While the mean age was equal in both cohorts (54.1 years), the proportion of females was significantly lower in the COVID cohort (62.5% vs. 63.4%, p=0.002). The share of patients hospitalized in relation to a diagnosis of mood/affective disorder was smaller during the COVID period (14.8% vs. 17.1%, p<0.001), and the average number of related hospital days during follow-up was significantly lower in the COVID cohort (4.96 vs. 5.73 days, p<0.001). The hospitalization rate and number of hospital days were particularly low for patients diagnosed in Q4 2020 (12.9%; 4.53 days). The number of mood/affective disorder-related outpatient visits during the follow-up was similar between both cohorts, except for a remarkably higher number of visits among patients diagnosed in Q2 2020. The proportion of patients with sick leaves was significantly lower in the COVID cohort (37.0% vs. 35.7%, p<0.001), however differences in the number of sick days were not significant (18.1 vs. 17.6 days, p=0.052).
Conclusions
The HCRU of people newly-diagnosed with mood/affective disorders has shifted during the COVID-19 pandemic. Further research is needed to assess the impact of the observed shift on severity and long-term outcomes.
| 0 | PMC9747466 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S132 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.637 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02841-8
10.1016/j.jval.2022.09.637
Article
EE391 Impact of the COVID-19 Pandemic on the Healthcare Resource Use of People With Newly Diagnosed Mood/Affective Disorder
Junker S 1
Knapp R 1
Hahn P 2
Maywald U 3
Hardtstock F 1
1Cytel Inc., Berlin, Germany
2IPAM e.V., Wismar, Germany
3AOK PLUS, Dresden, Germany
14 12 2022
12 2022
14 12 2022
25 12 S132S132
Copyright © 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
pmcObjectives
Literature suggests an impact of the COVID-19 pandemic on mental health. However, the impact on healthcare resource use (HCRU) among patients newly-diagnosed with mood/affective disorders remains unclear.
Methods
Adults with ≥1 inpatient/outpatient diagnosis of a mood/affective disorder (ICD-10 F30-F39) from 01/01/2018–31/12/2020 were identified from a German claims dataset. A 18-month washout period was applied to ensure incidence of the diagnosis. HCRU outcomes were observed during a 6-month follow-up period. Patients were broken down into two cohorts based on whether their follow-up period fell into the pre-COVID or COVID period (cut-off 01/04/2020); patients with both pre-COVID and COVID periods were excluded.
Results
A total of 132,103 patients were identified (pre-COVID: 97,189; COVID: 34,914). While the mean age was equal in both cohorts (54.1 years), the proportion of females was significantly lower in the COVID cohort (62.5% vs. 63.4%, p=0.002). The share of patients hospitalized in relation to a diagnosis of mood/affective disorder was smaller during the COVID period (14.8% vs. 17.1%, p<0.001), and the average number of related hospital days during follow-up was significantly lower in the COVID cohort (4.96 vs. 5.73 days, p<0.001). The hospitalization rate and number of hospital days were particularly low for patients diagnosed in Q4 2020 (12.9%; 4.53 days). The number of mood/affective disorder-related outpatient visits during the follow-up was similar between both cohorts, except for a remarkably higher number of visits among patients diagnosed in Q2 2020. The proportion of patients with sick leaves was significantly lower in the COVID cohort (37.0% vs. 35.7%, p<0.001), however differences in the number of sick days were not significant (18.1 vs. 17.6 days, p=0.052).
Conclusions
The HCRU of people newly-diagnosed with mood/affective disorders has shifted during the COVID-19 pandemic. Further research is needed to assess the impact of the observed shift on severity and long-term outcomes.
| 0 | PMC9747467 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S1 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.015 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02841-8
10.1016/j.jval.2022.09.637
Article
EE391 Impact of the COVID-19 Pandemic on the Healthcare Resource Use of People With Newly Diagnosed Mood/Affective Disorder
Junker S 1
Knapp R 1
Hahn P 2
Maywald U 3
Hardtstock F 1
1Cytel Inc., Berlin, Germany
2IPAM e.V., Wismar, Germany
3AOK PLUS, Dresden, Germany
14 12 2022
12 2022
14 12 2022
25 12 S132S132
Copyright © 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
pmcObjectives
Literature suggests an impact of the COVID-19 pandemic on mental health. However, the impact on healthcare resource use (HCRU) among patients newly-diagnosed with mood/affective disorders remains unclear.
Methods
Adults with ≥1 inpatient/outpatient diagnosis of a mood/affective disorder (ICD-10 F30-F39) from 01/01/2018–31/12/2020 were identified from a German claims dataset. A 18-month washout period was applied to ensure incidence of the diagnosis. HCRU outcomes were observed during a 6-month follow-up period. Patients were broken down into two cohorts based on whether their follow-up period fell into the pre-COVID or COVID period (cut-off 01/04/2020); patients with both pre-COVID and COVID periods were excluded.
Results
A total of 132,103 patients were identified (pre-COVID: 97,189; COVID: 34,914). While the mean age was equal in both cohorts (54.1 years), the proportion of females was significantly lower in the COVID cohort (62.5% vs. 63.4%, p=0.002). The share of patients hospitalized in relation to a diagnosis of mood/affective disorder was smaller during the COVID period (14.8% vs. 17.1%, p<0.001), and the average number of related hospital days during follow-up was significantly lower in the COVID cohort (4.96 vs. 5.73 days, p<0.001). The hospitalization rate and number of hospital days were particularly low for patients diagnosed in Q4 2020 (12.9%; 4.53 days). The number of mood/affective disorder-related outpatient visits during the follow-up was similar between both cohorts, except for a remarkably higher number of visits among patients diagnosed in Q2 2020. The proportion of patients with sick leaves was significantly lower in the COVID cohort (37.0% vs. 35.7%, p<0.001), however differences in the number of sick days were not significant (18.1 vs. 17.6 days, p=0.052).
Conclusions
The HCRU of people newly-diagnosed with mood/affective disorders has shifted during the COVID-19 pandemic. Further research is needed to assess the impact of the observed shift on severity and long-term outcomes.
| 0 | PMC9747468 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S213 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1035 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04308-X
10.1016/j.jval.2022.09.2103
Article
PCR168 The Changing Face of Qualitative Interviewing in Clinical Outcome Assessments Research: Conducting Qualitative Interviews Post COVID-19
Randall J 1
Keith S 2
Clegg J 2
1Clinical Outcomes Solutions, Ltd., Folkestone, KEN, UK
2Clinical Outcomes Solutions, Chicago, IL, USA
14 12 2022
12 2022
14 12 2022
25 12 S423S423
Copyright © 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
pmcObjectives
Qualitative interviews are an important method for collecting in-depth patient experience data. In-person interviews have typically been considered the gold standard by both researchers and regulators. The Covid-19 pandemic curtailed the ability to conduct in-person interviews and necessitated a move to virtual interviews. Therefore, this research was conducted to consider how this may have affected qualitative research and whether this is a viable option to continue to use moving forward.
Methods
Over the past 2 years, the authors have conducted or been involved in over 200 virtual interviews. These have been conducted across a range of indications, and across multiple countries, age groups, and ethnic groups. The authors have compared observations of the quality of the interview and resulting data from these 2 modes of interviewing.
Results
Three main observations were made. First, the quality of the interviews and data collected appears to be equal between both methods. No changes to analysis or reporting were needed to compensate for the change in format. Developing rapport virtually did not affect patients’ willingness to share intimate details about their experiences. Second, virtual interviews appear to have significant benefits for patients by eliminating the risk of infection and the burden of travel. In addition, some patients appeared to feel more comfortable sharing information on sensitive topics and/or embarrassing symptoms when not in a face-to-face environment. Third, because familiarity with technology for video calls was enhanced during the pandemic, patients reported minimal, if any, difficulties joining the interview.
Conclusions
Virtual interviews offer the same quality of data as in-person interviews, reduces burden, mitigates the risks of COVID-19, and have been well accepted by patients and researchers. Regulators appear to be initially responding positively to this approach. It may be that it will become the preferred method for qualitative interviews in this field.
| 0 | PMC9747469 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S423 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2103 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04308-X
10.1016/j.jval.2022.09.2103
Article
PCR168 The Changing Face of Qualitative Interviewing in Clinical Outcome Assessments Research: Conducting Qualitative Interviews Post COVID-19
Randall J 1
Keith S 2
Clegg J 2
1Clinical Outcomes Solutions, Ltd., Folkestone, KEN, UK
2Clinical Outcomes Solutions, Chicago, IL, USA
14 12 2022
12 2022
14 12 2022
25 12 S423S423
Copyright © 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
pmcObjectives
Qualitative interviews are an important method for collecting in-depth patient experience data. In-person interviews have typically been considered the gold standard by both researchers and regulators. The Covid-19 pandemic curtailed the ability to conduct in-person interviews and necessitated a move to virtual interviews. Therefore, this research was conducted to consider how this may have affected qualitative research and whether this is a viable option to continue to use moving forward.
Methods
Over the past 2 years, the authors have conducted or been involved in over 200 virtual interviews. These have been conducted across a range of indications, and across multiple countries, age groups, and ethnic groups. The authors have compared observations of the quality of the interview and resulting data from these 2 modes of interviewing.
Results
Three main observations were made. First, the quality of the interviews and data collected appears to be equal between both methods. No changes to analysis or reporting were needed to compensate for the change in format. Developing rapport virtually did not affect patients’ willingness to share intimate details about their experiences. Second, virtual interviews appear to have significant benefits for patients by eliminating the risk of infection and the burden of travel. In addition, some patients appeared to feel more comfortable sharing information on sensitive topics and/or embarrassing symptoms when not in a face-to-face environment. Third, because familiarity with technology for video calls was enhanced during the pandemic, patients reported minimal, if any, difficulties joining the interview.
Conclusions
Virtual interviews offer the same quality of data as in-person interviews, reduces burden, mitigates the risks of COVID-19, and have been well accepted by patients and researchers. Regulators appear to be initially responding positively to this approach. It may be that it will become the preferred method for qualitative interviews in this field.
| 0 | PMC9747470 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S477 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2367 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02458-5
10.1016/j.jval.2022.09.254
Article
CO178 Cardiovascular, Neurological, and Ocular Complications of COVID-19 Among Indian Patients – A Targeted Literature Review
Krishna A 1
Vhanakalas A 1
Rai MK 2
Gautam R 1
1EVERSANA, Mumbai, MH, India
2EVERSANA, Singapore, Singapore
14 12 2022
12 2022
14 12 2022
25 12 S52S52
Copyright © 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
pmcObjectives
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has had far-reaching health consequences, triggering off a chain of events involving multiple organs. The second wave of COVID-19 was worst in India and severely affected the people. We aimed to analyse the complications of COVID-19 on cardiovascular, neurological, and ocular system in Indian patients.
Methods
The search was conducted in Embase platform using well-defined search strategy to identify studies reporting the complications of COVID-19 in Indian patients from inception of the database to 07 June 2022. Narrative/systematic reviews were excluded.
Results
A total of 1400 citations were retrieved; 38 studies met the inclusion criteria and included in analysis. Included studies were mostly case reports (n=28), retrospective observational (n=5), and prospective observational (n=5) studies. Patients were adults in most studies (97%). Eighteen studies reported ocular complications, with blurred vision, conjunctivitis, endophthalmitis reported by 16.6% of patients each, followed by loss of vision (11.1%). Case reports mentioned retinal vein occlusion, retinal artery occlusion, hyperemia, bilateral panuveitis, ophthalmoplegia, acute bilateral retrobulbar optic neuritis. Thirteen studies reported neurological complications, with headache (38%) being the most common complication, followed by fatigue, seizure and encephalitis (23% each). Case reports described complications such as confusion, depression, anxiety, psychosis, encephalopathy, polyradiculoneuropathy, facial palsy, global aphasia, acute cerebellitis, stroke, cerebral ataxia. Ten studies reported cardiovascular complications, and tachycardia (50%) was the most commonly reported complication, followed by acute coronary syndrome, cardiac injury, and bradycardia (20% each). Case reports mentioned hypertension, ischemic heart disease, pericardial effusion, cardiac tamponade, and congenital heart block as the cardiovascular complications.
Conclusions
This review identified COVID-19 has caused significant complications on the ocular system, followed by neurological and cardiovascular organ system. Identification and reporting of these manifestations of SARS-CoV-2 will help in formulating the guidelines and protocol for early diagnosis and management.
| 0 | PMC9747471 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S52 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.254 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02458-5
10.1016/j.jval.2022.09.254
Article
CO178 Cardiovascular, Neurological, and Ocular Complications of COVID-19 Among Indian Patients – A Targeted Literature Review
Krishna A 1
Vhanakalas A 1
Rai MK 2
Gautam R 1
1EVERSANA, Mumbai, MH, India
2EVERSANA, Singapore, Singapore
14 12 2022
12 2022
14 12 2022
25 12 S52S52
Copyright © 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
pmcObjectives
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has had far-reaching health consequences, triggering off a chain of events involving multiple organs. The second wave of COVID-19 was worst in India and severely affected the people. We aimed to analyse the complications of COVID-19 on cardiovascular, neurological, and ocular system in Indian patients.
Methods
The search was conducted in Embase platform using well-defined search strategy to identify studies reporting the complications of COVID-19 in Indian patients from inception of the database to 07 June 2022. Narrative/systematic reviews were excluded.
Results
A total of 1400 citations were retrieved; 38 studies met the inclusion criteria and included in analysis. Included studies were mostly case reports (n=28), retrospective observational (n=5), and prospective observational (n=5) studies. Patients were adults in most studies (97%). Eighteen studies reported ocular complications, with blurred vision, conjunctivitis, endophthalmitis reported by 16.6% of patients each, followed by loss of vision (11.1%). Case reports mentioned retinal vein occlusion, retinal artery occlusion, hyperemia, bilateral panuveitis, ophthalmoplegia, acute bilateral retrobulbar optic neuritis. Thirteen studies reported neurological complications, with headache (38%) being the most common complication, followed by fatigue, seizure and encephalitis (23% each). Case reports described complications such as confusion, depression, anxiety, psychosis, encephalopathy, polyradiculoneuropathy, facial palsy, global aphasia, acute cerebellitis, stroke, cerebral ataxia. Ten studies reported cardiovascular complications, and tachycardia (50%) was the most commonly reported complication, followed by acute coronary syndrome, cardiac injury, and bradycardia (20% each). Case reports mentioned hypertension, ischemic heart disease, pericardial effusion, cardiac tamponade, and congenital heart block as the cardiovascular complications.
Conclusions
This review identified COVID-19 has caused significant complications on the ocular system, followed by neurological and cardiovascular organ system. Identification and reporting of these manifestations of SARS-CoV-2 will help in formulating the guidelines and protocol for early diagnosis and management.
| 0 | PMC9747472 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S191-S192 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.928 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03538-0
10.1016/j.jval.2022.09.1333
Article
HPR205 Future-Proofing European Regulatory and Market Access Practices Based on Learnings From the COVID-19 Pandemic – Stakeholder Perspectives
Claessens Z 1
Beirne G 2
Decouttere C 1
Vandaele N 1
Huys I 1
Barbier L 2
1KU Leuven, Leuven, Belgium
2KU Leuven, Leuven, VBR, Belgium
14 12 2022
12 2022
14 12 2022
25 12 S270S270
Copyright © 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
pmcObjectives
Many regulatory and market access actions were taken to answer the urgent need for rapid market entry of effective and safe medicines against COVID-19. This study aims to (i) identify actions taken by European regulatory and market access authorities during the pandemic, (ii) identify learnings, and (iii) translate these learnings into recommendations for the future-proofing of regulatory and market access practices.
Methods
Semi-structured interviews were conducted with regulators, policymakers, HTA assessors, payers, and pharmaceutical industry representatives across Europe to elicit their perspectives on regulatory and market access practices during the COVID-19 pandemic. Interviews were transcribed ad verbatim and transcripts analysed via the thematic framework method.
Results
The interviews (n= 10, ongoing) revealed a number of regulatory and market access actions developed and/or applied during the COVID-19 pandemic and respective learnings. Three key actions were identified as having a potential for implementation in day-to-day practice and likely future-proofing it. Firstly, increased interaction during the regulatory reviewing process under the form of a rolling review is deemed favourable for products meeting high unmet medical needs. However, policy stakeholders point out the increased workload of this hands-on approach and limited available resources. Secondly, the increased collaboration between European member states on pricing and reimbursement, referring to the joint procurement agreement, was deemed not only important in the current COVID-19 pandemic but also more and more important in regular practice. Lastly, increased flexibility in clinical trial design would facilitate the conduct and enhance patients’ participation, likely leading to timelier clinical results.
Conclusions
The process from authorization to market access of COVID-19 vaccines and medicines differs from regular practice, with some procedures being adjusted, expedited or newly developed. There is an opportunity to leverage these insights and learnings to help future-proof regulatory and market access practices for medicines in the European Union more holistically.
| 0 | PMC9747473 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S270 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1333 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04290-5
10.1016/j.jval.2022.09.2085
Article
PCR150 Physicians’ Perceptions of the Impact of COVID-19 on Patient Access and Adherence
Cook J 1
Donde S 2
Gilchrist K 1
Pittaoulis M 3
Sapia M 3
1Viatris, Canonsburg, PA, USA
2Viatris, Hatfield, PA, UK
3NERA Economic Consulting, Philadelphia, PA, USA
14 12 2022
12 2022
14 12 2022
25 12 S419S420
Copyright © 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
pmcObjectives
To evaluate physicians’ perceptions of changes in patient access to healthcare during COVID-19 pandemic in the United States (US), United Kingdom (UK), and India.
Methods
A total of 751 physicians across US, UK and India were surveyed between September and October 2021. The survey focused on four areas related to patient access during the pandemic: (1) changes in patient access to health care, (2) changes in patients’ adherence to treatment plans, (3) changes in patients seeking mental health services and (4) changes in physicians’ use of technology or telemedicine.
Results
Of the 751 physicians who participated in the survey, 33.4% were from US (n=251) and 33.2% each were from UK and India (n=250). In all three countries, more than 40% of physicians reported that the patient access problems ranged from “somewhat common” to “very common” before and during COVID-19 restrictions. The major patient access challenge in the US (53%) and India (73%) was avoidance of testing or treatment due to lack of health insurance coverage (government or private) and out-of-pocket expenditures. In the UK, the avoidance of preventative screening tests (37.6%) was illustrated as “somewhat common” problem. Respondents quoted lack of health awareness and knowledge of non-communicable diseases [(average, 62.6%) US, 50.6%; UK, 57.2%; India, 80%], concerns about adverse effects and desire to avoid side effects [(average, 63.9%) US, 57.8%; UK, 64.4%; India, 69.6%] as the major reasons for patients’ nonadherence to prescribed treatment plans. More than 85% of the respondents reported that mental health concerns increased (US, 86%; India and UK, 92% each) during COVID-19. Further, all respondents witnessed a substantial increase in the utilization of telehealth during COVID-19.
Conclusions
Patients from countries of different sizes and healthcare systems may face distinct barriers. Surveying physicians may help to identify patients’ specific needs about better health care access.
| 0 | PMC9747474 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S419-S420 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2085 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04290-5
10.1016/j.jval.2022.09.2085
Article
PCR150 Physicians’ Perceptions of the Impact of COVID-19 on Patient Access and Adherence
Cook J 1
Donde S 2
Gilchrist K 1
Pittaoulis M 3
Sapia M 3
1Viatris, Canonsburg, PA, USA
2Viatris, Hatfield, PA, UK
3NERA Economic Consulting, Philadelphia, PA, USA
14 12 2022
12 2022
14 12 2022
25 12 S419S420
Copyright © 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
pmcObjectives
To evaluate physicians’ perceptions of changes in patient access to healthcare during COVID-19 pandemic in the United States (US), United Kingdom (UK), and India.
Methods
A total of 751 physicians across US, UK and India were surveyed between September and October 2021. The survey focused on four areas related to patient access during the pandemic: (1) changes in patient access to health care, (2) changes in patients’ adherence to treatment plans, (3) changes in patients seeking mental health services and (4) changes in physicians’ use of technology or telemedicine.
Results
Of the 751 physicians who participated in the survey, 33.4% were from US (n=251) and 33.2% each were from UK and India (n=250). In all three countries, more than 40% of physicians reported that the patient access problems ranged from “somewhat common” to “very common” before and during COVID-19 restrictions. The major patient access challenge in the US (53%) and India (73%) was avoidance of testing or treatment due to lack of health insurance coverage (government or private) and out-of-pocket expenditures. In the UK, the avoidance of preventative screening tests (37.6%) was illustrated as “somewhat common” problem. Respondents quoted lack of health awareness and knowledge of non-communicable diseases [(average, 62.6%) US, 50.6%; UK, 57.2%; India, 80%], concerns about adverse effects and desire to avoid side effects [(average, 63.9%) US, 57.8%; UK, 64.4%; India, 69.6%] as the major reasons for patients’ nonadherence to prescribed treatment plans. More than 85% of the respondents reported that mental health concerns increased (US, 86%; India and UK, 92% each) during COVID-19. Further, all respondents witnessed a substantial increase in the utilization of telehealth during COVID-19.
Conclusions
Patients from countries of different sizes and healthcare systems may face distinct barriers. Surveying physicians may help to identify patients’ specific needs about better health care access.
| 0 | PMC9747475 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S491 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2437 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04271-1
10.1016/j.jval.2022.09.2066
Article
PCR131 Resilience, and Positive Parenting in Parents of Children With Autism and Intellectual Disability: Evidence From the Impacts of the COVID-19 Pandemic on Family's Quality of Life and Parent-Child Relationships
Bolbocean C 1
Rhidenour K 2
McCormack M 3
Suter B 3
Holder J 4
1University of Oxford, Oxford, UK
2Baylor University, Waco, TX, USA
3BCM, Houston, TX, USA
4Bridge the Gap SYNGAP, Cypress, TX, USA
14 12 2022
12 2022
14 12 2022
25 12 S416S416
Copyright © 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
pmcObjectives
Family quality of life (FQoL) outcomes collected during the first year of COVID-19 has been combined with 2018 data to estimate the outbreak impact on parental outcomes on a sample of 691 families of children with syndromic autism and intellectual disabilities.
Methods
A total of 120 identical families completed the Beach Center family quality of life Scale - a validated FQoL instrument between 2018 and during the first year of the pandemic as well as reported COVID-19 parental-child outcomes. Multivariate regression models and matching estimators were used to estimate the impact of COVID-19 on FQoL outcomes.
Results
Despite challenges imposed by the COVID-19 outbreak, our study found that FQoL outcomes reported by participating caregivers during the first year of COVID-19 appears to be similar to ratings from the pre-pandemic study. Parents of children in our sample generally displayed a stable functioning trajectory. The COVID-19 pandemic was found to be positively associated with parent-child bonding, relational satisfaction, and increased emotional connection between parents and their children.
Conclusions
Our findings provide evidence of families’ resilience which might explain positive parent-child interactions during COVID-19. Exploring mechanisms which explain how families with autistic and intellectual disability children confront, manage disruptive experiences, and buffer COVID-19 induced stress is a fruitful direction for future research.
| 0 | PMC9747476 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S416 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2066 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04271-1
10.1016/j.jval.2022.09.2066
Article
PCR131 Resilience, and Positive Parenting in Parents of Children With Autism and Intellectual Disability: Evidence From the Impacts of the COVID-19 Pandemic on Family's Quality of Life and Parent-Child Relationships
Bolbocean C 1
Rhidenour K 2
McCormack M 3
Suter B 3
Holder J 4
1University of Oxford, Oxford, UK
2Baylor University, Waco, TX, USA
3BCM, Houston, TX, USA
4Bridge the Gap SYNGAP, Cypress, TX, USA
14 12 2022
12 2022
14 12 2022
25 12 S416S416
Copyright © 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
pmcObjectives
Family quality of life (FQoL) outcomes collected during the first year of COVID-19 has been combined with 2018 data to estimate the outbreak impact on parental outcomes on a sample of 691 families of children with syndromic autism and intellectual disabilities.
Methods
A total of 120 identical families completed the Beach Center family quality of life Scale - a validated FQoL instrument between 2018 and during the first year of the pandemic as well as reported COVID-19 parental-child outcomes. Multivariate regression models and matching estimators were used to estimate the impact of COVID-19 on FQoL outcomes.
Results
Despite challenges imposed by the COVID-19 outbreak, our study found that FQoL outcomes reported by participating caregivers during the first year of COVID-19 appears to be similar to ratings from the pre-pandemic study. Parents of children in our sample generally displayed a stable functioning trajectory. The COVID-19 pandemic was found to be positively associated with parent-child bonding, relational satisfaction, and increased emotional connection between parents and their children.
Conclusions
Our findings provide evidence of families’ resilience which might explain positive parent-child interactions during COVID-19. Exploring mechanisms which explain how families with autistic and intellectual disability children confront, manage disruptive experiences, and buffer COVID-19 induced stress is a fruitful direction for future research.
| 0 | PMC9747477 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S130 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.629 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04395-9
10.1016/j.jval.2022.09.2190
Article
PCR257 Humanistic Burden Pre and Post COVID-19 on Caregivers of Cancer Patients in Japan and China: A NHWS Survey
Tan WH
Grillo A
Chen Y
Woo A
Cerner Enviza, Singapore, Singapore
14 12 2022
12 2022
14 12 2022
25 12 S440S440
Copyright © 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
pmcObjectives
The impact of COVID-19 on Health-Related Quality of Life (HRQoL) of cancer patients is substantial. Less attention has been given to its impact on their caregivers. The objective of this study was to examine the humanistic burden of caregivers of cancer patients in Japan and China, pre- and post-COVID-19.
Methods
This analysis utilized the population-based Japan National Health and Wellness Survey (NHWS) for 2019 (n=30,006), 2020 (n=30,092), 2021 (n=30,015), and the China NHWS in 2017 (n=19,994) and 2020 (n=20,051). Demographic characteristics, HRQoL, work productivity and activity impairment (WPAI) were assessed for caregivers of cancer patients and the general population.
Results
Caregivers in Japan and China displayed worse health outcomes, both pre- and post-COVID, compared to the general population. In the latest data, a higher proportion of caregivers exhibited symptoms of depression or anxiety (e.g., General Anxiety Disorder-7 [GAD-7]≥10: Japan: 15.8% vs. 7.6%; China: 20.2% vs. 6.5%). Caregivers also have lower HRQoL (e.g., Mental Component Summary [MCS]: Japan: 44.97 vs. 48.91; China: 46.80 vs. 49.17) and higher WPAI (e.g., Total Work Productivity: Japan: 33.98% vs. 20.95%; China: 38.88% vs. 22.98%) than the general population. In both the general population and caregivers, there were minimal changes in health outcomes pre- and post-COVID-19. However, in Japan, absenteeism was significantly lower after COVID-19 (13.22% in 2019 vs. 6.85% in 2020 vs. 7.97% in 2021, P<0.05). There is also an increase in MCS (44.60 in 2017 vs. 48.80 in 2020, P<0.01) after COVID-19 in China.
Conclusions
In Japan and China, the humanistic burden of caregivers of cancer patients remained consistently higher than the general population regardless of the COVID-19 pandemic, highlighting the unmet needs for caregivers. Interestingly, this study indicated that changes in lifestyle under COVID-19 (e.g., flexible work-from-home arrangements) could potentially alleviate the humanistic burden for caregivers.
| 0 | PMC9747478 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S440 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2190 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04395-9
10.1016/j.jval.2022.09.2190
Article
PCR257 Humanistic Burden Pre and Post COVID-19 on Caregivers of Cancer Patients in Japan and China: A NHWS Survey
Tan WH
Grillo A
Chen Y
Woo A
Cerner Enviza, Singapore, Singapore
14 12 2022
12 2022
14 12 2022
25 12 S440S440
Copyright © 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
pmcObjectives
The impact of COVID-19 on Health-Related Quality of Life (HRQoL) of cancer patients is substantial. Less attention has been given to its impact on their caregivers. The objective of this study was to examine the humanistic burden of caregivers of cancer patients in Japan and China, pre- and post-COVID-19.
Methods
This analysis utilized the population-based Japan National Health and Wellness Survey (NHWS) for 2019 (n=30,006), 2020 (n=30,092), 2021 (n=30,015), and the China NHWS in 2017 (n=19,994) and 2020 (n=20,051). Demographic characteristics, HRQoL, work productivity and activity impairment (WPAI) were assessed for caregivers of cancer patients and the general population.
Results
Caregivers in Japan and China displayed worse health outcomes, both pre- and post-COVID, compared to the general population. In the latest data, a higher proportion of caregivers exhibited symptoms of depression or anxiety (e.g., General Anxiety Disorder-7 [GAD-7]≥10: Japan: 15.8% vs. 7.6%; China: 20.2% vs. 6.5%). Caregivers also have lower HRQoL (e.g., Mental Component Summary [MCS]: Japan: 44.97 vs. 48.91; China: 46.80 vs. 49.17) and higher WPAI (e.g., Total Work Productivity: Japan: 33.98% vs. 20.95%; China: 38.88% vs. 22.98%) than the general population. In both the general population and caregivers, there were minimal changes in health outcomes pre- and post-COVID-19. However, in Japan, absenteeism was significantly lower after COVID-19 (13.22% in 2019 vs. 6.85% in 2020 vs. 7.97% in 2021, P<0.05). There is also an increase in MCS (44.60 in 2017 vs. 48.80 in 2020, P<0.01) after COVID-19 in China.
Conclusions
In Japan and China, the humanistic burden of caregivers of cancer patients remained consistently higher than the general population regardless of the COVID-19 pandemic, highlighting the unmet needs for caregivers. Interestingly, this study indicated that changes in lifestyle under COVID-19 (e.g., flexible work-from-home arrangements) could potentially alleviate the humanistic burden for caregivers.
| 0 | PMC9747479 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S16 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.079 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04490-4
10.1016/j.jval.2022.09.2285
Article
RWD60 Exploring the Burden of COVID-19 on Eating Disorders Spectrum (Types of Eating Disorders) in Pre- and During-COVID-19 Pandemic Using Real-World Data
Verma V 1
Verma N 2
Gaur A 2
Paul K 2
Chopra A 2
Daral S 2
Nayyar A 2
Kukreja I 2
Roy A 2
Pandey S 2
Anand S 2
Chawla S 1
Gupta A 2
1Optum, Gurgaon, HR, India
2Optum, Gurugram, HR, India
14 12 2022
12 2022
14 12 2022
25 12 S460S460
Copyright © 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
pmcObjectives
This study aimed to explore the impact of COVID-19 on patients with eating spectrum disorders and the burden of resource utilization in the pre- and during COVID-19 pandemic.
Methods
This retrospective observational study included patients diagnosed with anorexia, bulimia, and other eating disorders (OED) between 1st January 2018 to 31st December 2021 using ICD-10-CM codes from Optum’s de-identified Clinformatics Data Mart database. In this duration, distinct patients were identified and further classified by age, gender, and place of service. To determine the influence in pre- and during COVID-19 for each of the stratification variables, a year-wise comparison was done. Chi-square test of significance was performed for categorical variables.
Results
We observed the number of anorexia and bulimia cases among patients with eating spectrum disorders increased significantly during the pandemic (1st January 2020 – 31st December 2020) (p<.01). In the case of teenagers and adults, anorexia was found to have increased by 20% and 5%, respectively, while OED was found to have increased by 6% and 2%, respectively during pandemic. When stratified by gender, only anorexia (females [21%], men [10%] and OED (females [26%], males [18%] showed a substantial increase during the pandemic. Healthcare resources utilization: for inpatients, anorexia and OED increased significantly (10% and 3%), bulimia decreased significantly (5%); for office visits, anorexia increased significantly (3%), bulimia and OED decreased significantly (8% and 3%). Anorexia, bulimia, and OED showed a significant increase in outpatient visits (71%, 68%, 76% respectively); and in telehealth services (2,152%; 1,924%; and 1,727% respectively) (p<.01).
Conclusions
An increased exacerbation in eating spectrum disorder was observed during the pandemic, especially in telehealth services. With the increase in cases, health care resource utilization across various settings is pressed. Better treatment and programs may be required to curb this impact and decrease the overall burden.
| 0 | PMC9747480 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S460 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2285 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03230-2
10.1016/j.jval.2022.09.1025
Article
EPH104 Valuing the Impact of Incorporating an Acellular Hexavalent Vaccine in the National Vaccination Scheme of Peru in the Context of COVID-19
Seinfeld J 1
Sobrevilla A 1
Rosales ML 1
Ibañez M 1
Munayco C 1
Londono S 2
1Videnza Consultores, Lima, Peru
2Sanofi, Bogota, CUN, Colombia
14 12 2022
12 2022
14 12 2022
25 12 S211S211
Copyright © 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
pmcObjectives
COVID-19 affected regular vaccination schedules reducing Vaccine Coverage Rates (VCRs). This study evaluates the impact of incorporating an acellular hexavalent vaccine into the National Vaccination Scheme (NVS) of Peru in terms of several factors, including expected positive impact on VCRs and resulting economic benefits from a more efficient burden control.
Methods
Four scenarios were evaluated. The current scheme of a whole-cell pentavalent (DTwP-Hib-HepB)+IPV/OPV and alternative scheme of an acellular hexavalent (DTaP-IPV-Hib-HepB) were compared under 2 vaccination strategies: conventional (institution based) and alternative (institution and additional vaccination modalities). VCRs, adverse events (AEs), healthcare management and logistic costs were evaluated over a 2-year horizon and disease cases over a 5-year horizon. Current VCRs were modeled using Monte Carlo simulations based on current vaccination patterns. VCRs under alternative scheme and vaccination strategies were derived based on published literature. AE rates were obtained from previous studies. Markov modelling was used to estimate disease cases using local epidemiological data. Healthcare management costs were obtained through micro-costing and logistical costs by replicating the logistical chain of five representative regions.
Results
VCRs would increase 9.4%–14.3% with hexavalent vaccine and 3.1% with alternative strategy. A reduction of around 25 p.p. in AE and 5.7%–8.7% in disease cases would occur with hexavalent vaccination. Although, there would be a reduction of 33–38%, 4%–8% and 81% in AE, disease, and logistic costs categories respectively, overall costs would increase by 6.7%–12.8% with hexavalent vaccination. Additionally, cost per protected child and VCR p.p. obtained would be reduced by around 5%.
Conclusions
Introducing a hexavalent vaccine into the Peru NVS represents an opportunity to close VCR gaps generated by COVID-19, mitigating the risk of disease outbreaks that could bring further costs. Reduced costs per protected child and per VCR p.p. achieved with a hexavalent vaccine, implies an efficient use of resources and better value for money.
| 0 | PMC9747481 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S211 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1025 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03533-1
10.1016/j.jval.2022.09.1328
Article
HPR200 The Impact of Community Pharmacies on Regional Equity in Access to Professional Rapid Antigen Testing for SARS-COV-2 in Portugal
Guerreiro J 1
Teixeira I 2
Romano S 1
Mansinho J 1
Pereira R 1
Teixeira Rodrigues A 3
1Centre for Health Evaluation & Research, National Association of Pharmacies (CEFAR-IS/ANF), Lisboa, Portugal
2Centre for Health Evaluation & Research, National Association of Pharmacies (CEFAR-IS/ANF), Lisboa, 11, Portugal
3University of Minho, Braga, Portugal
14 12 2022
12 2022
14 12 2022
25 12 S269S269
Copyright © 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
pmcObjectives
COVID-19 was declared a global pandemic in March 2020. Several public health measures were adopted to reduce the risk of individual transmission improving early detection and isolation of new cases, such as a 100% reimbursement of SARS-CoV-2 professional rapid antigen detection testing (Ag-RDT) to the population at clinical pathology laboratories, community pharmacies and other authorized entities. This study aimed to evaluate the increase in the capacity of professional Ag-RDT offered by the integration of community pharmacies into the NHS testing strategy and compare the equity level in the access to testing with and without the pharmacies’ participation.
Methods
Analytical study based on the average distance (Kms) of the population, to the nearest Ag-RDT site and the average number of weekly hours available to perform the service, per 1,000 inhabitants, by municipality and for the 3 groups (pharmacies, labs and other structures) by January 31st, 2022. To assess equity, Lorenz curves and Gini index were calculated for both indicators. Analysis and results were stratified by subgroups (population density, aging index and per capita purchasing power index).
Results
A total of 1369 (65.1%) pharmacies, 679 (32.3%) laboratories and 56 (2.7%) entities were providing free SARS-CoV-2 Ag-RDT. For the distribution of distances, Gini index reduced from 0.50 to 0.42 (-16.8%) with the inclusion of pharmacies. The Gini index for the distribution of weekly hours of access reduced from 0.42 to 0.26 with the inclusion of pharmacies (-39%). This reduction was higher in municipalities with lower population density (-43.3%), higher aging index (-51.3%) and lower per capita purchasing power index (-54.6%).
Conclusions
Results suggest that pharmacies can improve the national territory coverage in the access indicators studied. Without pharmacies, the provision of the Ag-RDT service to the population would have a territory coverage with significant gaps, increasing inequalities in population groups that are already more vulnerable.
| 0 | PMC9747482 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S269 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1328 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03297-1
10.1016/j.jval.2022.09.1092
Article
EPH171 Delivery Outcomes in the United States Among Women With Commercial or Medicaid Insurance During the COVID-19 Pandemic
Brady B
Packnett E
Palmer LA
Merative, Cambridge, MA, USA
14 12 2022
12 2022
14 12 2022
25 12 S224S224
Copyright © 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
pmcObjectives
This analysis utilized two administrative claims databases to examine reported associations between COVID-19 infection and adverse delivery outcomes.
Methods
Women aged 15-50 with a delivery in 2020 were identified in the MarketScan Commercial or Multi-state Medicaid Databases. The index date was the last delivery claim in 2020 and women were continuously enrolled for the prior 280 days (pregnancy period). Diagnoses of COVID-19 and other conditions associated with negative delivery outcomes (diabetes, hypertension, and hemorrhage) were assessed over the pregnancy period among subsets of women with evidence of pre-term, early/threatened labor, or suspected maternal demise (defined as continuous eligibility for <8 or <43 days post-delivery).
Results
Women with pre-term vs. full term birth – commercial 3.0% vs. 2.3% (p<0.0001) and Medicaid 2.8% vs. 2.4% (p=0.0017) – and early/threated labor vs. not – commercial 2.8% vs. 2.3% (p<0.0001) and Medicaid 2.7% vs. 2.3% (p=0.0007) – were significantly more likely to have a COVID-19 diagnosis. Women with pre-term birth and early/threatened labor also had significantly increased comorbidity burden during pregnancy. There were no differences in the rate of COVID-19 or comorbidity diagnoses between women with and without suspected maternal demise the commercial database. Conversely rates of COVID-19 infection were significantly higher among women with suspected maternal demise compared to those without in the Medicaid database at both the 8 day (9.0% of deaths had a COVID-19 diagnosis compared to 2.3% of live women (p<0.0001)) and 43 day cutoffs (4.6% and 1.8% respectively (p<0.0001)).
Conclusions
This claims-based analysis parallels prior reports indicating correlation between adverse delivery outcomes and COVID-19 infection. Findings for pre-term birth and early/threated labor subgroups are confounded by comorbidity burden. Conversely, comorbidity burden is not driving the correlation between COVID-19 infection and death in the Medicaid data; due to the seriousness of the outcome, additional research that includes mortality data is certainly warranted.
| 0 | PMC9747483 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S224 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1092 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03191-6
10.1016/j.jval.2022.09.986
Article
EPH64 Public Health Impact of COVID-19 in French Ambulatory Patients With at Least One Risk Factor for Severe Disease
Supiot R 1
Millier A 1
Benyounes K 2
Machuron V 2
Le Lay K 2
Sivignon M 1
Leboucher C 3
Blein C 1
Raffi F 4
1Creativ-Ceutical, Paris, France
2Roche, Boulogne-Billancourt, France
3Creativ-Ceutical, Lyon, 69, France
4CHU Nantes, Nantes, France
14 12 2022
12 2022
14 12 2022
25 12 S203S203
Copyright © 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
pmcObjectives
In the fight against the pandemic, it was essential to join forces with professionals to better understand the resources involved in the care ecosystem. A public health impact model was developed to estimate the health and economic burden of COVID-19, to support future choices of resource allocations and to allow comparison with other diseases.
Methods
A Markov model was used to estimate life years, costs, number of hospitalisations, number of deaths and long/prolonged COVID forms over a time horizon of 2 years. Data from the literature suggest that the age of patients can affect the risk of hospitalisation and the risk of death during hospitalisation, hence the model was stratified by age group. The hospitalisation probabilities were derived from a Temporary Use Authorisation cohort, and the hospitalisation stays characteristics were derived from the French national hospital discharge database. Several scenarios were conducted.
Results
Over the model time horizon and in a situation where patients were not treated, the number of hospitalisations reached 256 per 1,000 patients in the acute phase and 382 per 1,000 patients overall. The number of deaths in the acute phase was 37 per 1,000 patients, and the number of long/prolonged COVID forms reached 407 per 1,000 patients. These translated into a reduction of 0.7 days of life per patient in the acute phase (versus the maximum lifetime during the acute phase: 30.4 days), with an average cost of €1,578, and a reduction of 27 days of life over the time horizon (versus the maximum lifetime during the whole simulation considering natural mortality: 2 years and 15.8 days), with an average cost of €4,280.
Conclusions
This study shows that the health and economic burden is considerable especially for the elderly and/or unvaccinated and goes beyond the acute phase because of the effects and consequences of the long/prolonged COVID forms.
| 0 | PMC9747484 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S203 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.986 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03191-6
10.1016/j.jval.2022.09.986
Article
EPH64 Public Health Impact of COVID-19 in French Ambulatory Patients With at Least One Risk Factor for Severe Disease
Supiot R 1
Millier A 1
Benyounes K 2
Machuron V 2
Le Lay K 2
Sivignon M 1
Leboucher C 3
Blein C 1
Raffi F 4
1Creativ-Ceutical, Paris, France
2Roche, Boulogne-Billancourt, France
3Creativ-Ceutical, Lyon, 69, France
4CHU Nantes, Nantes, France
14 12 2022
12 2022
14 12 2022
25 12 S203S203
Copyright © 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
pmcObjectives
In the fight against the pandemic, it was essential to join forces with professionals to better understand the resources involved in the care ecosystem. A public health impact model was developed to estimate the health and economic burden of COVID-19, to support future choices of resource allocations and to allow comparison with other diseases.
Methods
A Markov model was used to estimate life years, costs, number of hospitalisations, number of deaths and long/prolonged COVID forms over a time horizon of 2 years. Data from the literature suggest that the age of patients can affect the risk of hospitalisation and the risk of death during hospitalisation, hence the model was stratified by age group. The hospitalisation probabilities were derived from a Temporary Use Authorisation cohort, and the hospitalisation stays characteristics were derived from the French national hospital discharge database. Several scenarios were conducted.
Results
Over the model time horizon and in a situation where patients were not treated, the number of hospitalisations reached 256 per 1,000 patients in the acute phase and 382 per 1,000 patients overall. The number of deaths in the acute phase was 37 per 1,000 patients, and the number of long/prolonged COVID forms reached 407 per 1,000 patients. These translated into a reduction of 0.7 days of life per patient in the acute phase (versus the maximum lifetime during the acute phase: 30.4 days), with an average cost of €1,578, and a reduction of 27 days of life over the time horizon (versus the maximum lifetime during the whole simulation considering natural mortality: 2 years and 15.8 days), with an average cost of €4,280.
Conclusions
This study shows that the health and economic burden is considerable especially for the elderly and/or unvaccinated and goes beyond the acute phase because of the effects and consequences of the long/prolonged COVID forms.
| 0 | PMC9747485 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S470 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2336 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04528-4
10.1016/j.jval.2022.09.2323
Article
RWD98 Variation in COVID-19 Length of Stay Due to Social Factors in the US – Estimation Using Integration of CDC/ATSDR's Social Vulnerability Index (SVI) and Healthcare Claims Data
Nayyar A 1
Raj U 1
Rastogi M 1
Daral S 1
Verma V 2
Gaur A 1
Kukreja I 3
Pandey S 1
Chopra A 1
Roy A 1
Sethi A 1
Dawar V 1
1Optum, Gurugram, HR, India
2Optum, Gurgaon, HR, India
3Optum, New Delhi, DL, India
14 12 2022
12 2022
14 12 2022
25 12 S467S468
Copyright © 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
pmcObjectives
This study explored the variation in COVID-19 related average length of stay by Social Vulnerability Index (SVI) of patients in the US
Methods
This study included patients diagnosed with COVID-19 infection between 1st March 2020 to 28th Feb 2021 with ICD-10-CM recorded in Optum’s de-identified Clinformatics® Data Mart Database. Only the patients having continuous eligibility of 3-months post (follow-up period) the first diagnosis of COVID-19 (index date) were included in the study. Zip code (if available) closest to the COVID-19 diagnosis index of those patients were joined with the Minority Health SVI (mhSVI) file to map patients’ SVI score ranging from 0 to 1. We have estimated the average length of stay across the four patient groups, categorized based on SVI score (Group 1 (least vulnerable): 0-0.25; Group 2: 0.251-50; Group 3: 0.501-.75; Group 4 (highly vulnerable): 0.751-1) and have applied the Wilcoxon statistical test to analyze the level of significance in cost variation across the four SVI groups. Further, we will also be looking at the region-wise trends in length of stay across the four groups.
Results
Among 120,501 patients diagnosed with COVID-19, we were able to map the SVI score for 98% of patients. We observed a significant longer length of stay for patients as we moved from group 1 (8.5 days) to group 4 (9.7 days). The estimated length of hospitalization significantly increased by 8%, 9%, and 13% respectively from group 2 to group 4 when compared to group 1.
Conclusions
Vulnerable patients had more impact of COVID-19 as compared to less vulnerable group. Significant variation in length of stay might be correlated with difficult access to healthcare, severe COVID-19 presentation, and more co-morbid conditions. This study helps to determine the gaps in healthcare resource allocation as well as supports planning and preparedness for pandemic.
| 0 | PMC9747486 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S467-S468 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2323 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04528-4
10.1016/j.jval.2022.09.2323
Article
RWD98 Variation in COVID-19 Length of Stay Due to Social Factors in the US – Estimation Using Integration of CDC/ATSDR's Social Vulnerability Index (SVI) and Healthcare Claims Data
Nayyar A 1
Raj U 1
Rastogi M 1
Daral S 1
Verma V 2
Gaur A 1
Kukreja I 3
Pandey S 1
Chopra A 1
Roy A 1
Sethi A 1
Dawar V 1
1Optum, Gurugram, HR, India
2Optum, Gurgaon, HR, India
3Optum, New Delhi, DL, India
14 12 2022
12 2022
14 12 2022
25 12 S467S468
Copyright © 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
pmcObjectives
This study explored the variation in COVID-19 related average length of stay by Social Vulnerability Index (SVI) of patients in the US
Methods
This study included patients diagnosed with COVID-19 infection between 1st March 2020 to 28th Feb 2021 with ICD-10-CM recorded in Optum’s de-identified Clinformatics® Data Mart Database. Only the patients having continuous eligibility of 3-months post (follow-up period) the first diagnosis of COVID-19 (index date) were included in the study. Zip code (if available) closest to the COVID-19 diagnosis index of those patients were joined with the Minority Health SVI (mhSVI) file to map patients’ SVI score ranging from 0 to 1. We have estimated the average length of stay across the four patient groups, categorized based on SVI score (Group 1 (least vulnerable): 0-0.25; Group 2: 0.251-50; Group 3: 0.501-.75; Group 4 (highly vulnerable): 0.751-1) and have applied the Wilcoxon statistical test to analyze the level of significance in cost variation across the four SVI groups. Further, we will also be looking at the region-wise trends in length of stay across the four groups.
Results
Among 120,501 patients diagnosed with COVID-19, we were able to map the SVI score for 98% of patients. We observed a significant longer length of stay for patients as we moved from group 1 (8.5 days) to group 4 (9.7 days). The estimated length of hospitalization significantly increased by 8%, 9%, and 13% respectively from group 2 to group 4 when compared to group 1.
Conclusions
Vulnerable patients had more impact of COVID-19 as compared to less vulnerable group. Significant variation in length of stay might be correlated with difficult access to healthcare, severe COVID-19 presentation, and more co-morbid conditions. This study helps to determine the gaps in healthcare resource allocation as well as supports planning and preparedness for pandemic.
| 0 | PMC9747487 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S238 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1162 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04528-4
10.1016/j.jval.2022.09.2323
Article
RWD98 Variation in COVID-19 Length of Stay Due to Social Factors in the US – Estimation Using Integration of CDC/ATSDR's Social Vulnerability Index (SVI) and Healthcare Claims Data
Nayyar A 1
Raj U 1
Rastogi M 1
Daral S 1
Verma V 2
Gaur A 1
Kukreja I 3
Pandey S 1
Chopra A 1
Roy A 1
Sethi A 1
Dawar V 1
1Optum, Gurugram, HR, India
2Optum, Gurgaon, HR, India
3Optum, New Delhi, DL, India
14 12 2022
12 2022
14 12 2022
25 12 S467S468
Copyright © 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
pmcObjectives
This study explored the variation in COVID-19 related average length of stay by Social Vulnerability Index (SVI) of patients in the US
Methods
This study included patients diagnosed with COVID-19 infection between 1st March 2020 to 28th Feb 2021 with ICD-10-CM recorded in Optum’s de-identified Clinformatics® Data Mart Database. Only the patients having continuous eligibility of 3-months post (follow-up period) the first diagnosis of COVID-19 (index date) were included in the study. Zip code (if available) closest to the COVID-19 diagnosis index of those patients were joined with the Minority Health SVI (mhSVI) file to map patients’ SVI score ranging from 0 to 1. We have estimated the average length of stay across the four patient groups, categorized based on SVI score (Group 1 (least vulnerable): 0-0.25; Group 2: 0.251-50; Group 3: 0.501-.75; Group 4 (highly vulnerable): 0.751-1) and have applied the Wilcoxon statistical test to analyze the level of significance in cost variation across the four SVI groups. Further, we will also be looking at the region-wise trends in length of stay across the four groups.
Results
Among 120,501 patients diagnosed with COVID-19, we were able to map the SVI score for 98% of patients. We observed a significant longer length of stay for patients as we moved from group 1 (8.5 days) to group 4 (9.7 days). The estimated length of hospitalization significantly increased by 8%, 9%, and 13% respectively from group 2 to group 4 when compared to group 1.
Conclusions
Vulnerable patients had more impact of COVID-19 as compared to less vulnerable group. Significant variation in length of stay might be correlated with difficult access to healthcare, severe COVID-19 presentation, and more co-morbid conditions. This study helps to determine the gaps in healthcare resource allocation as well as supports planning and preparedness for pandemic.
| 0 | PMC9747488 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S306-S307 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1514 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03576-8
10.1016/j.jval.2022.09.1371
Article
HSD27 Constrained Optimization Model to Estimate Best Booster Allocation Strategy to Minimize Hospital Bed-Days Under a Fixed Healthcare Budget
Kapoor R 1
Standaert B 2
Nolan T 3
Pezalla EJ 4
Arnetorp S 5
Bergenheim K 6
Bungey G 7
Darroch-Thompson D 8
Gani R 7
Meeraus W 9
Okumura L 10
Sutton K 11
Tichy E 12
Yokota R 13
Demarteau N 14
1Evidera, Singapore, Singapore
2University Hasselt, Hasselt, Belgium
3University of Melbourne, Melbourne, VIC, Australia
4Enlightenment Bioconsult, LLC, Daytona Beach, FL, USA
5AstraZeneca, Gothenberg, Sweden
6AstraZeneca, Gothenburg, Sweden
7Evidera, London, UK
8AstraZeneca, Shanghai, China
9AstraZeneca, Cambridge, UK
10AstraZeneca, São Paulo, Brazil
11Evidera, Melbourne, Australia
12Evidera, Budapest, Hungary
13AstraZeneca, Liberec, Czech Republic
14Evidera, Brussels, Belgium
14 12 2022
12 2022
14 12 2022
25 12 S278S278
Copyright © 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
pmcObjectives
COVID-19 vaccine boosters are available in many countries. Public health policymakers face difficult choices over which booster brand to recommend, given limited budgets and the need to maximize health gains. Here, we provide a conceptual model to identify the best booster strategies for age-identified subpopulations under different conditions.
Methods
A constrained optimization model with an objective function to minimize bed-days was developed that varied population proportion receiving different booster options by age, to identify the best booster strategy that minimized bed-days with a constraint of maximum healthcare expenditure of US$2.10/person. It included a 3-month decision-tree model to calculate bed-days, with the following health states: healthy/asymptomatic; mild (not hospitalized); moderate (general ward); severe (intensive care unit [ICU], no mechanical ventilation); critical (requiring mechanical ventilation); and death. Medical resource utilization (MRU) costs and hospital bed-days were calculated for each health state. The base country was Brazil. Three booster options, B1 (US$1), B2 (US$2), and no-booster (NB, US$0) were considered. Based on real-world effectiveness estimates, B1 and B2 were assumed to be 55% and 75% effective against mild/moderate COVID-19, respectively. Both reduced severe/critical COVID-19 by 90%. The target population was adults eligible for boosters, stratified by age.
Results
The best booster strategy identified recommended 100% coverage of those eligible, with B1 for population <70 years and B2 for population ≥70 years. Compared with NB, bed-days were reduced by 75%, hospitalizations by 68%, and ICU admissions by 90% leading to a 60% reduction in total costs (81% reduction in MRU costs). Within individual age-groups, costs were reduced by 57%-66% based on the age-specific disease risk.
Conclusions
A constrained optimization model identifies the best age-specific booster allocation strategy to minimize hospital bed-days across different age groups without exceeding a predefined budget. Decision-makers could use this method to achieve the best possible health outcomes when healthcare resources are limited.
| 0 | PMC9747489 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S278 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1371 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03716-0
10.1016/j.jval.2022.09.1511
Article
HTA51 Challenges and Opportunities of Health Technology Assessment in Older Adult Immunization
van Dorst P 1
Van der Schans J 2
de Waure C 3
Largeron N 4
Roberts C 5
Beck E 6
Postma MJ 1
Boersma C 7
1University of Groningen, University Medical Center Groningen, Groningen, UT, Netherlands
2University of Groningen, Faculty of Economics and Business, Unit of Economics, Econometrics and Finance, Groningen, Netherlands
3Università Cattolica del Sacro Cuore, Rome, Italy
4Sanofi, Reading, UK
5Merck & Co., Inc., North Wales, PA, USA
6GSK, Wavre, Belgium
7University of Groningen, University Medical Center Groningen, Zeist, UT, Netherlands
14 12 2022
12 2022
14 12 2022
25 12 S306S306
Copyright © 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
pmcObjectives
Vaccination is paramount to reduce the health and economic impact of vaccine preventable diseases (VPDs), but are mainly focused on the immunization of children where COVID-19 demonstrated the importance of considering other age groups too. Providing healthcare decision makers with evidence-based assessments and recommendations is crucial but health technology assessments (HTAs) of older adult vaccination might be challenging.
Methods
Drawing upon the review of relevant literature and recent study cases, an expert panel elaborated on a list of HTA challenges and recommendations for older adult vaccination that could be instrumental to foster implementation of lifelong immunization.
Results
Five challenges were identified for older adult vaccination: i) population characteristics, including immunosenescence, waning rates, comorbidities, changing functional status, and frailty; ii) limited surveillance data, causing a knowledge gap between population characteristics and vaccine effectiveness; iii) uncertainty in health economic value assessments - as a spill-over of the first two challenges; iv) prioritization of sub-groups might not align with health equity principles; and v) vaccination acceptance/hesitancy could prevent attaining optimal vaccination coverage and population benefits. Five concrete recommendations were issued in response to abovementioned challenges: i) introduce specific adult working groups within NITAGs as in the UK and US; ii) develop standardized/transferrable assessment methods adapted for older adults vaccination; iii) filling evidence gaps by the design of inclusive surveillance systems; iv) strengthen transparency of assessments to improve trust within healthcare and the society; and v) establish dedicated budget plans for prevention so that policy decisions – supported by adequate HTAs - can be implemented, inclusive older adults vaccination.
Conclusions
Global interest in strengthening evidence-based policymaking for vaccination is increasing. It is therefore the right time to rethink how HTA could serve in fostering older adults’ vaccination and to convey the message that implementing preventive measures and promoting lifelong immunization programs are instrumental to secure healthcare systems’ sustainability.
| 0 | PMC9747490 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S306 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1511 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02280-X
10.1016/j.jval.2022.09.078
Article
P66 Understanding of Post-COVID Conditions (PCC) and Related Burden of Illness
Guisinger A 1
Misra Y 2
Czworka D 3
Pham S 2
Rousculp M 4
1AESARA, Fort Myers, FL, USA
2AESARA, Chapel Hill, NC, USA
3Novavax, Inc., Gaithersburg, MD, USA
4Novavax, Inc., Cary, NC, USA
14 12 2022
12 2022
14 12 2022
25 12 S15S16
Copyright © 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
pmcObjectives
Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogen, is a multi-organ disease with a broad spectrum of manifestations.1-2 Long-term complications following SARS-CoV-2 infection, known as post-COVID conditions (PCC) or ‘long COVID’, are important to understand due to their significant burden on healthcare systems and patients.3 PCC may affect individuals differently, manifesting as a sequela of symptoms that can vary in duration and severity.4-5 Additionally, little is known about the risk factors of PCC, making it difficult to describe those more likely to develop PCC. A targeted literature review was conducted to elucidate understanding of PCC and impact on patient health-related quality of life (HRQoL) from a global perspective.
Methods
PubMed was searched using terms describing PCC for global, English-language studies (2020-2022). Included studies reported any relationship between patient HRQoL and PCC. Single-case reports were excluded.
Results
From 349 identified publications, 37 underwent full-text review; 20 met inclusion criteria1-3,6-22 (17 excluded). Median follow-up time was 15 weeks, with most studies (85%) including follow-up of at least 12 weeks. Most studies attributed the symptoms of PCC to a decrease in HRQoL. Fatigue was the most reported symptom, followed by other neurological and psychological symptoms (e.g., headache, sleep disturbances, cognitive impairment, loss of taste and smell, vision and hearing changes, impaired mobility, anxiety/depression). Cardiopulmonary and digestive symptoms were also reported in all studies. Almost all studies stated the need to understand risk factors causing symptoms of PCC to better characterize HRQoL.
Conclusions
This study revealed the diverse symptomatic burden and negative impact on HRQoL in patients with PCC. More research is needed to understand the risk factors and evolving complexity and long-term impact of PCC to ultimately guide global prevention and treatment of COVID-19. *Note: references are available upon request and will be included with the ISPOR presentation.
| 0 | PMC9747491 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S15-S16 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.078 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02280-X
10.1016/j.jval.2022.09.078
Article
P66 Understanding of Post-COVID Conditions (PCC) and Related Burden of Illness
Guisinger A 1
Misra Y 2
Czworka D 3
Pham S 2
Rousculp M 4
1AESARA, Fort Myers, FL, USA
2AESARA, Chapel Hill, NC, USA
3Novavax, Inc., Gaithersburg, MD, USA
4Novavax, Inc., Cary, NC, USA
14 12 2022
12 2022
14 12 2022
25 12 S15S16
Copyright © 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
pmcObjectives
Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogen, is a multi-organ disease with a broad spectrum of manifestations.1-2 Long-term complications following SARS-CoV-2 infection, known as post-COVID conditions (PCC) or ‘long COVID’, are important to understand due to their significant burden on healthcare systems and patients.3 PCC may affect individuals differently, manifesting as a sequela of symptoms that can vary in duration and severity.4-5 Additionally, little is known about the risk factors of PCC, making it difficult to describe those more likely to develop PCC. A targeted literature review was conducted to elucidate understanding of PCC and impact on patient health-related quality of life (HRQoL) from a global perspective.
Methods
PubMed was searched using terms describing PCC for global, English-language studies (2020-2022). Included studies reported any relationship between patient HRQoL and PCC. Single-case reports were excluded.
Results
From 349 identified publications, 37 underwent full-text review; 20 met inclusion criteria1-3,6-22 (17 excluded). Median follow-up time was 15 weeks, with most studies (85%) including follow-up of at least 12 weeks. Most studies attributed the symptoms of PCC to a decrease in HRQoL. Fatigue was the most reported symptom, followed by other neurological and psychological symptoms (e.g., headache, sleep disturbances, cognitive impairment, loss of taste and smell, vision and hearing changes, impaired mobility, anxiety/depression). Cardiopulmonary and digestive symptoms were also reported in all studies. Almost all studies stated the need to understand risk factors causing symptoms of PCC to better characterize HRQoL.
Conclusions
This study revealed the diverse symptomatic burden and negative impact on HRQoL in patients with PCC. More research is needed to understand the risk factors and evolving complexity and long-term impact of PCC to ultimately guide global prevention and treatment of COVID-19. *Note: references are available upon request and will be included with the ISPOR presentation.
| 0 | PMC9747492 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S493 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2448 | oa_other |
==== Front
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Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02917-5
10.1016/j.jval.2022.09.713
Article
EE468 Healthcare Resource Utilisation and Costs Associated With the Management of Hospitalised COVID-19 Patients in England
Patel V 1
Beecroft S 2
Birch HJ 1
Gibbons D 1
Hall G 3
Heaton D 2
Marston X 2
Lipunova N 4
Oliyide A 1
Wallace J 2
1GlaxoSmithKline, Brentford, UK
2Open Health, Runcorn, UK
3Gillian Hall Epidemiology Ltd, London, UK
4Open Health, London, UK
14 12 2022
12 2022
14 12 2022
25 12 S147S148
Copyright © 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
pmcObjectives
The COVID-19 pandemic has placed significant strain on healthcare resources, particularly in the management of patients requiring hospitalisation for severe disease. We describe resource use and costs associated with the management of hospitalised COVID-19 patients during the pandemic in England.
Methods
This retrospective observational study utilised data from the Hospital Episode Statistics database. Patients with COVID-19 (ICD-10 code U07.1) as the primary reason for hospital admission between 1st January 2020 to 30th September 2021 and who were at high risk of severe COVID-19 (aged ≥55 years, or aged ≥12 years with specified comorbidities) were included. Hospital costs were derived from National Health Service Reference Costs 2019–2020. Analyses were stratified into pandemic wave one (1st January – 31st May 2020), wave two (1st June 2020 – 24th April 2021), and wave three (25th April – 30th September 2021).
Results
The analysis identified 66,723 eligible patients during wave one, 181,479 patients during wave two, and 39,917 patients during wave three. Total admission costs per patient declined over the three waves, with mean (standard deviation [SD]) total costs per admission of £5,862 (£14,024), £5,077 (£11,647), and £4,383 (£8,468) for wave 1, wave 2, and wave 3, respectively. The length of hospital stay per admission also declined across the three waves, with mean (SD) of 12.00 (14.59), 11.00 (13.16), and 7.00 (8.41) days for wave 1, wave 2, and wave 3, respectively. The proportion of patients admitted to critical care was similar across the three waves (wave one, 12.2%; wave two, 12.0%; wave three, 12.8%), while the proportion who died in hospital declined (wave one, 33.98%; wave two, 24.24%; wave three, 11.32%).
Conclusions
COVID-19 continues to represent a substantial cost and resource burden to patients and hospital services across England, although per-patient costs have declined over the course of the pandemic. Funding GSK (Study 217379).
| 0 | PMC9747493 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S147-S148 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.713 | oa_other |
==== Front
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Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02972-2
10.1016/j.jval.2022.09.768
Article
EE527 Cost-Effectiveness and Budget Impact Analysis of Remdesivir for the Treatment of COVID-19 in Greece
Athanasakis K 1
Nomikos N 2
Tsoulas C 3
Zisis K 2
1University of West Attica, Athens, Greece
2Institute for Health Economics, Athens, Greece
3Gilead Sciences Hellas, Athens, A1, Greece
14 12 2022
12 2022
14 12 2022
25 12 S159S159
Copyright © 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
pmcObjectives
Remdesivir was developed as an intravenous antiviral treatment for hospitalized patients with moderate and severe Covid-19 and has been approved for emergency use in several countries including Europe. The objective is to perform a cost-effectiveness analysis of treatment with remdesivir in combination with standard of care (SoC) in hospitalized Covid-19 adult patients requiring supplemental oxygen in Greece versus SoC.
Methods
A projected cohort-based model with a time horizon of 50 years formed the basis of the analysis. The model was populated with country-specific data. Clinical data were sourced from the ACTT-1 trial, cost data were sourced from literature, while resource use data were elicited from experts’ opinion through structured interviews. The analysis was conducted from a third-party payer perspective. Costs refer to year 2020. Both costs and outcomes were discounted at 3% per annum.
Results
Remdesivir in combination with SOC was found to offer more LYg and QALYs compared to SoC (18.17 versus 16.72 and 13.80 versus 12.69 respectively). In addition, patients treated with remdesivir had 0.87, 1.49 and 1.37 less days of hospital stay in the general ward, intensive care unit (ICU) and ICU with mechanical invasive ventilation (MIV) settings respectively compared to patients treated only with SoC. Patients receiving remdesivir were estimated to incur savings of €1,742 compared to SoC. The ICER of remdesivir was estimated at -4,290.9 per QALY gained against SoC.
Conclusions
Remdesivir was found to be cost effective (dominating) in the Greek environment, as the treatment led not only to better clinical outcomes, but also in savings for the third payer. In addition, less length of hospital stay due to remdesivir can release hospital beds, especially crucial ICU beds, in times of pandemic outbreak.
| 0 | PMC9747494 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S159 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.768 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02972-2
10.1016/j.jval.2022.09.768
Article
EE527 Cost-Effectiveness and Budget Impact Analysis of Remdesivir for the Treatment of COVID-19 in Greece
Athanasakis K 1
Nomikos N 2
Tsoulas C 3
Zisis K 2
1University of West Attica, Athens, Greece
2Institute for Health Economics, Athens, Greece
3Gilead Sciences Hellas, Athens, A1, Greece
14 12 2022
12 2022
14 12 2022
25 12 S159S159
Copyright © 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
pmcObjectives
Remdesivir was developed as an intravenous antiviral treatment for hospitalized patients with moderate and severe Covid-19 and has been approved for emergency use in several countries including Europe. The objective is to perform a cost-effectiveness analysis of treatment with remdesivir in combination with standard of care (SoC) in hospitalized Covid-19 adult patients requiring supplemental oxygen in Greece versus SoC.
Methods
A projected cohort-based model with a time horizon of 50 years formed the basis of the analysis. The model was populated with country-specific data. Clinical data were sourced from the ACTT-1 trial, cost data were sourced from literature, while resource use data were elicited from experts’ opinion through structured interviews. The analysis was conducted from a third-party payer perspective. Costs refer to year 2020. Both costs and outcomes were discounted at 3% per annum.
Results
Remdesivir in combination with SOC was found to offer more LYg and QALYs compared to SoC (18.17 versus 16.72 and 13.80 versus 12.69 respectively). In addition, patients treated with remdesivir had 0.87, 1.49 and 1.37 less days of hospital stay in the general ward, intensive care unit (ICU) and ICU with mechanical invasive ventilation (MIV) settings respectively compared to patients treated only with SoC. Patients receiving remdesivir were estimated to incur savings of €1,742 compared to SoC. The ICER of remdesivir was estimated at -4,290.9 per QALY gained against SoC.
Conclusions
Remdesivir was found to be cost effective (dominating) in the Greek environment, as the treatment led not only to better clinical outcomes, but also in savings for the third payer. In addition, less length of hospital stay due to remdesivir can release hospital beds, especially crucial ICU beds, in times of pandemic outbreak.
| 0 | PMC9747495 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S373 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1850 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04525-9
10.1016/j.jval.2022.09.2320
Article
RWD95 Exploring the Burden of COVID-19 on Suicides and Suicidal Attempts (SSA) in Pre- and During-COVID-19 Pandemic Using Real-World Data
Gaur A 1
Paul K 1
Sharma A 1
Verma V 2
Chopra A 1
Roy A 1
Nayyar A 1
Pandey S 1
Daral S 1
Kukreja I 1
1Optum, Gurugram, HR, India
2Optum, Gurgaon, HR, India
14 12 2022
12 2022
14 12 2022
25 12 S467S467
Copyright © 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
pmcObjectives
This study aimed to explore the impact of COVID-19 on patients with SSA and the burden of resource utilization in the pre- and during the COVID-19 pandemic.
Methods
This retrospective observational study included patients diagnosed with SSA between 1st January 2019 to 31st December 2020 using ICD-10-CM codes from Optum’s de-identified Clinformatics® Data Mart. In the study duration, distinct patients were identified and further classified by age, gender, and location of service. To determine the influence in pre- and during COVID-19 for each of the stratification variables, a year-wise comparison was done. Chi-square test was performed to check the significance of categorical variables.
Results
Overall we observed the number of SSA patients increased by 2% (n=266,329) during the pandemic (1st January 2020 – 31st December 2020). A significant increase was seen across all age groups (p<.01). In the case of teenagers, SSA was found to have increased by 80% whereas in adults and elderly an 15% and 8% increase was seen respectively during pandemic (p<.01). When stratified by gender, a significant increase was observed only in females (+9% [n=174,647]) where in males (-3% [n=91,573]) decrease was observed during pandemic. In healthcare resources utilization overall, there was an observed 12% increase during pandemic. For inpatients, office, and outpatient, SSA decreased significantly (-4%, -8%, and -1% respectively) during pandemic (p<.01). A significant increase in outpatient and telehealth services was observed (34% and 1,299% respectively) (p<.01).
Conclusions
An increased exacerbation in SSA was observed during the pandemic with telehealth and outpatient services being impacted the highest. This may be attributed to facing near-death scenarios, and the loss of loved ones amongst other factors. With the increase in cases, health care resource utilization across various settings is pressed. Better treatment and programs may be required to curb this impact and decrease the overall burden.
| 0 | PMC9747496 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S467 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2320 | oa_other |
==== Front
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Value Health
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1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02434-2
10.1016/j.jval.2022.09.230
Article
CO153 Mind-Body Modalities for Healthcare Workers in the COVID-19 Pandemic
Kwon CY 1
Lee B 2
1Dongeui University, Busan, Korea, Republic of (South)
2Korea Institute of Oriental Medicine, Daejeon, South Korea
14 12 2022
12 2022
14 12 2022
25 12 S48S48
Copyright © 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
pmcObjectives
The objective of this systematic review was to investigate the role of mind-body modalities (MBMs) in managing the mental health of healthcare workers (HCWs) during the coronavirus disease of 2019 (COVID-19) pandemic.
Methods
Six electronic databases were comprehensively searched (Jan 2019 to Sep 2021), to find original prospective quantitative intervention studies of MBMs for HCWs. MBMs defined in this study included meditation, mindfulness-based intervention, autogenic training, yoga, tai chi, qigong, breathing exercises, music therapy, guided imagery, biofeedback, prayer, and faith-based techniques. The primary outcome was the level of perceived stress. The methodological quality of the included studies was assessed using the corresponding assessment tools including the Cochrane Collaboration risk of bias tool. If there were 2 or more controlled clinical trials with the same outcome measures, a meta-analysis was performed.
Results
Total 18 relevant studies including 5 randomized controlled trials were included. In the results of meta-analysis, MBMs significantly improved the perceived stress (standardized mean difference, −0.37; 95% confidence intervals, −0.53 to −0.21), depression (−0.29; −0.45 to −0.12), and anxiety (−0.43; −0.59 to −0.27) of HCWs. Subgroup analysis showed that yoga- and music-based interventions had the largest effect size on the perceived stress. Moreover, some MBMs had significant benefits on burnout, insomnia, mindfulness, self-compassion, quality of life, resilience, and well-being, but not on psychological trauma and self-efficacy of HCWs. Despite of the promising results, the methodological quality of the included studies was not optimal.
Conclusions
According to our findings, there was evidence that some MBMs including yoga- and music-based interventions are helpful for improvement for perceived stress of HCWs during the COVID-19 pandemic. Promising potential benefits of MBMs were also observed for some other mental health outcomes. However, owing to poor methodological quality and heterogeneity of interventions and outcomes of the included studies, further high-quality clinical trials are needed on this topic.
| 0 | PMC9747497 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S48 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.230 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04278-4
10.1016/j.jval.2022.09.2073
Article
PCR138 Association of SARS-CoV-2 Omicron Ba.1 on Adherence to Oral Tetrabenazine Congener and Quality of Life of Patients Diagnosed With Huntington's Disease With Chorea or Tardive Dyskinesia on the Service of a USA Specialty Pharmacy
Burruss R 1
Alhabashi R 2
Arikian V 3
1Burruss Pharmacy Consulting, Ashland, VA, USA
2University of Maryland, Baltimore, MD, USA
3SUNY Downstate Medical Center, Brooklyn, NY, USA
14 12 2022
12 2022
14 12 2022
25 12 S417S417
Copyright © 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
pmcObjectives
During 1/1/-3/31/2022, SARS-CoV-2 Omicron BA.1 (CoVID-19 OBA.1) was pandemic in USA. Two study objectives are to determine if CoVID-19 OBA.1 was associated with a change in: (1) adherence to oral tetrabenazine analogue (TBZa) used to treat Huntington's Disease with chorea (HDc) or Tardive Dyskinesia (TDD) patients serviced by specialty pharmacy's medication therapy management program (SPMTM) and (2) patient-reported quality of life (QOL).
Methods
A retrospective, observational, pre-/post-design study of HDc,TDD patient adherence to oral TBZa and associated QoL was conducted at beginning of and during CoVID-19 OBA.1 pandemic. Patient assessments (PA) occurred at start of care (SOC) and follow-up (F-U) 7 days before dispenses. PA included EQ-5D-5L QoL metrics. Descriptive statics used to calculate QoL dimensional means before and after starting TDZa and then on F-U SPMTM. Differences in means represented patient perceived changes in QoL. The medication possession ratio (MPR) was calculated using the F-U from both the Pre- and During-CoVID-19 OBA.1.
Results
MPR = 0.96 prior to index time and was 0.93 During-CoVID-19 OBA.1 (3.1%). 238 PA were done During-CoVID-19 OBA.1 (280 HDc,TDD patients, 22 SOC, 250 F-U). Differences in QoL means Pre- vs During-CoVID-19 OBA.1 were: Mobility +0.0081 (0.81%), Self-Care +0.002 (0.2%), Usual Activities -0.0022 (0.22%), Pain/Discomfort -0.0103 (1.03%), Anxiety/Depression -0.0089 (0.89%), Overall Health State -0.07 (0.09%). Note: “-” = improvement; ”+”=worsened in Dimensions 1-5; “+” = improvement and ”-“ = worsened in Overall Health state. Percentages = absolute values.
Conclusions
MPR decreased by 3.1% compared to Pre-CoVID-19 OBA.1. Pre- and During-CoVID-19 OBA.1 MPR were higher than the industry standard of >0.9.5 On average, patients reported Mobility and Self-Care worsened but improved on Usual Activities, Pain/Discomfort and Anxiety/Depression dimensions of EQ-5D-5L. Over-all Health rating improved slightly by 0.09%. Explanations for worsened QoL metrics are discussed.7 Additional studies are suggested.
| 0 | PMC9747498 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S417 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2073 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04631-9
10.1016/j.jval.2022.09.2426
Article
SA32 Adapting PROs Evaluation to COVID Context – The Case of ASCEND Study
Moital I 1
Bras D 2
Portugal S 3
Lourenço V 4
Bento C 5
1Novartis Farma Portugal, LISBON, Portugal
2Novartis Farma Portugal, Porto Salvo, Portugal
3Faculdade de Economia e Centro de Estudos Socais da Universidade de Coimbra, Coimbra, Portugal
4Centro de Estudos Socais da Universidade de Coimbra, Coimbra, Portugal
5Hospitais da Universidade de Coimbra, Department of Clinical Hematology, Coimbra, Portugal, Coimbra, Portugal
14 12 2022
12 2022
14 12 2022
25 12 S489S489
Copyright © 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
pmcObjectives
Covid-19 pandemic imposed changes on disease management and follow-up namely with reduction on number of clinical appointments and use of telemedicine. Sickle cell disease (SCD) is a genetic blood disorder that is characterized by painful episodes caused by vaso-occlusion, with a significant impact on Quality of Life (QoL). This abstract aims to describe the adaptation of ASCEND study from a Face to Face (F2F) methodology to a fully digital patient reported outcome (PRO) study and its impact on SCD patients’ recruitment, based on clinicians and patients’ representatives feedback. The primary objective of ASCEND study is to characterize the physical impact of SCD on patients, through collection of PROs. The study also aims to characterize SCD patients’ demographics and clinical history, as well as to describe the social and emotional impact of SCD on patients and SCD patient pathway in the healthcare system.
Methods
ASCEND is non-interventional cross-sectional study of 2 cohorts of SCD adult patients. The study sample is 200 (recruited by hospitals) + 50 patients (recruited by the patient association - APPDH). Due to COVID pandemic, all study procedures (informed consent, clinical and PRO collection) will be exclusively done with digital resources. PRO questionnaires include both EQ-5D-5L and ASCQ-Me (Pain Episodes Frequency and Severity). Selected Portuguese patients and Social Studies investigators participated in the validation process.
Results
The study was initiated in February 2022. Recruitment rates were 16%, 19%, 22% and 23% from month 1 to month 4. The study is actively recruiting (84% patients; 99,4% PROs completeness rate). Final study results are expected by the end of 2022.
Conclusions
ASCEND methodology changes revealed to be very enriching. Although digital data collection can be seen as a challenge for patient participation, the recruitment and completeness rate for this study showed the positive impact digital tools can have on study execution.
| 0 | PMC9747499 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S489 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2426 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)02333-6
10.1016/j.jval.2022.09.129
Article
CO50 Efficacy and Safety of Itolizumab for the Treatment of Coronavirus Disease (COVID-19): A Systematic Literature Review
Gurram NS 1
Vagicharla RB 2
Rayapureddy G 2
Kummari P 2
Pulleddula K 2
Mir J 3
Sharma S 1
Tanushree C 4
Kohli IS 1
Goyal R 5
Aggarwal A 6
Chakrawarthy M 6
1IQVIA, Gurugram, India
2IQVIA, Bengaluru, India
3IQVIA, Baramulla, JK, India
4IQVIA, Kochi, India
5IQVIA, Thane, India
6IQVIA, Gurugram, HR, India
14 12 2022
12 2022
14 12 2022
25 12 S26S27
Copyright © 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
pmcObjectives
Coronavirus disease (COVID-19) is an infectious disease that leads to a hyperinflammatory state known as cytokine release syndrome. Itolizumab (ALZUMAbTM, Biocon India) is a humanized recombinant anti-CD6 monoclonal antibody that reduces serum levels of Interleukin 6 (IL-6), tumor necrosis factor-alpha (TNF-α), and interferon-gamma (INF-γ). This study aims to evaluate the efficacy and safety of itolizumab in COVID-19 patients.
Methods
MEDLINE and EMBASE via OVID SP platform were searched through June, 2022 for studies assessing the efficacy and safety of Itolizumab in Covid-19 patients. No restriction regarding the year of publication was applied. Two reviewers independently searched for articles and extracted data, resolving differences through consensus.
Results
Of 43 identified studies, five were included (one randomized controlled trial, three single-arm trials, and one observational study). Kumar et al. 2021 reported no deaths in best supportive care (BSC) plus itolizumab arm compared to BSC alone arm (p=0.0296; 95% CI = -0.3 [-0.61, -0.08]). Similarly, the combination therapy showed improvements in SpO2 (p=0.0296), PaO2 (p=0.0296) and decreased levels of IL-6 (43 vs 212 pg/ml; p=0.0296), TNF-α (9 vs 39 pg/ml; p=0.0253), when compared with BSC alone arm. Likewise, single-arm studies of itolizumab reported a reduction in IL-6: 28.3 pg/mL to 25.9 pg/mL (Diaz et al. 2020), 290.2 pg/mL to 183.1 pg/mL (Saavedra et al. 2020), and 116.3 and 78.8 (Caballero et al. 2020). Frequent serious adverse events associated with itolizumab were pericardial effusion, hypothyroidism, and airway hyper-reactivity. Gore et al. 2020 reported an improved SpO2 from 88% to 96%.
Conclusions
Itolizumab demonstrated promising therapeutic activity in reducing hyperinflammatory states in COVID-19 patients along with an acceptable safety profile. Further studies in larger populations are needed to ascertain the therapeutic benefit of itolizumab in COVID-19.
| 0 | PMC9747500 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S26-S27 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.129 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03443-X
10.1016/j.jval.2022.09.1238
Article
HPR108 Impact of COVID-19 Pandemic on the Decision Process of the Italian Medicine Agency: A Quantitative Assessment
Fiorentino F 1
Canali B 2
Candelora L 2
Halmos T 3
La Malfa P 2
Massara F 2
Vassallo C 2
Urbinati D 2
1IQVIA, Milan, Italy
2IQVIA, Milan, MI, Italy
3IQVIA, London, WSX, UK
14 12 2022
12 2022
14 12 2022
25 12 S251S252
Copyright © 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
pmcObjectives
The aim of this study is to assess Covid-19 pandemic impact on drugs’ time to market (TTM) in Italy, defined as the time from the pricing and reimbursement (P&R) dossier evaluation by the Technical Scientific Commission (CTS) to the publication of P&R resolution in the Italian Official Journal.
Methods
The study included all the new active substances, excluding vaccines, that received a positive opinion from the Committee for Medicinal Products for Human Use (CHMP) between January 2015 and September 2021 and that completed the Italian negotiation pathway. Drugs were clustered into three period groups (Pre-Covid, Partially-Covid and Fully-Covid) according to their negotiation process start and end date. Firstly, kernel density graphs were drawn to visually inspect differences among the three periods. Secondly, descriptive statistics by period and two-sample tests were performed to evaluate the potential role of co-variates influencing TTM. Thirdly, an inferential analysis was performed by implementing a nearest-neighbor matching estimator based on the identified relevant co-variates.
Results
Of the 375 drugs receiving a positive opinion in the scrutinized period, 305 were included in the analysis, of which 179, 71 and 55 in the Pre-Covid, Partially-Covid and Fully-Covid period, respectively. Overall, TTM was 317.8 days (SD=219.6), ranging from 237.5 (SD=127.6) days in the Fully-Covid period, to 280.1 (SD=144.5) days in the Pre-Covid period and to 474.9 days (SD=331.6) in the Partially-Covid period. From the matching analysis, Covid-19 impact resulted statistically significant (p<0.01): the average treatment effect of the Partially-Covid period and Fully-Covid period versus the Pre-Covid period was estimated at +138.3 days and -44.8 days, respectively.
Conclusions
This study showed that Covid-19 pandemic had a significant impact on drugs TTM in Italy, first lengthening the drugs’ time to Italian market, and then reducing it, underlining the temporary shock for the Italian regulator facing extraordinary epidemiological circumstances.
| 0 | PMC9747501 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S251-S252 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1238 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03682-8
10.1016/j.jval.2022.09.1477
Article
HTA17 Cost-Effectiveness Analysis of Tocilizumab for The Treatment of COVID-19 in Hospitalised Patients on Corticosteroids, From the Italian NHS Perspective
Jovanoski N 1
Dario A 2
1F. Hoffmann-La Roche, Neuchatel, NE, Switzerland
2Roche S.p.A., Monza, MB, Italy
14 12 2022
12 2022
14 12 2022
25 12 S299S299
Copyright © 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
pmcObjectives
The objective of this analysis is to assess the cost-effectiveness (CE) of tocilizumab plus usual care versus usual care alone for the treatment of Coronavirus Disease 19 (COVID-19) in hospitalised patients on corticosteroids, requiring supplemental oxygen or mechanical ventilation and having a c-reative protein (CRP) level ≥75mg/L.
Methods
The cost-effectiveness model (CE model) sources results from RECOVERY, a phase III, multi-center, randomized clinical trial sponsored by the University of Oxford. It models the acute phase of the COVID-19 infection through a decision tree and the rest of life through a Markov model. It uses this approach because treatment and its associated outcomes are realised over a short-term period while still allowing it to consider the long-term consequences of COVID-19 on healthcare costs and quality of life. At the start of the acute phase, all patients are hospitalised. As patients should be on oxygen support to be eligible for tocilizumab, patients start on either supplemental oxygen, non-invasive ventilation or mechanical ventilation. Patients can proceed to higher levels of oxygen support while they are in hospital and can leave the acute phase either alive or dead. In the second phase, the model assumes that all patients enter the Markov model without health issues. The perspective of the analysis is that of the Italian public payer.
Results
The model estimates an incremental gain of 0.813 quality-adjusted life years (QALYs) and 0.919 life years (LY), at a cost saving of €-1,105. Overall, tocilizumab is dominant versus usual care (i.e. leads to higher QALYs and lower costs).
Conclusions
The cost-effectiveness model shows that the value of tocilizumab plus usual care is driven by preventing a percentage of patients from proceeding to higher levels of respiratory support in comparison to the support at baseline, and reduction in the probability of death while in hospital.
| 0 | PMC9747502 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S299 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1477 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03161-8
10.1016/j.jval.2022.09.956
Article
EPH34 Long COVID Symptoms and Diagnosis in Primary Care: A Cohort Study Using the Thin Database Including Unstructured Text
Shah A 1
Dhalla S 2
Subramanian A 3
Ford E 4
Haroon S 3
Kuan V 1
Nirantharakumar K 3
1University College London, London, UK
2The Health Improvement Network (THIN), Cegedim, North Harrow, LON, UK
3University of Birmingham, Birmingham, LON, UK
4Brighton and Sussex Medical School, Brighton, UK
14 12 2022
12 2022
14 12 2022
25 12 S197S197
Copyright © 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
Long COVID is a widely recognised consequence of COVID-19 infection, but there is currently little information about the symptoms that patients present with in primary care, as these are typically recorded only in free text clinical notes.
Objectives
To compare the occurrence of symptoms in patients with and without a history of COVID-19 infection.
Methods
We used data from the The Health Improvement Network (THIN, a Cegedim Database). We included patients aged 18 or over registered with participating practices in England, Scotland or Wales. We compared COVID-19 cases (defined by Read-coded diagnoses) with unexposed controls. We extracted baseline and symptom information from both the Read codes and free text, which was analysed by natural language processing. We calculated hazard ratios (adjusted for age, sex, baseline medical conditions and prior record of symptoms) for each of 89 symptoms from 12 weeks after the COVID-19 diagnosis.
Results
We compared 10,229 patients with confirmed COVID-19 and 22,654 unexposed controls. Patients had a mean age of 52.4 years and 62.5% were female. Around 80% of the symptom mentions in the primary care were only in the free text. A wide range of symptoms were associated with previous COVID-19 infection, including shortness of breath (hazard ratio (HR) 3.2, 95% confidence interval (CI) 2.8, 3.5), chest pain (HR 2.35, 95% CI 2.03, 2.72) and fatigue (HR 3.4, 95% CI 3.0, 3.8). There were 603 free text entries of ‘Long Covid’, but none recorded using Read codes.
Conclusions
These preliminary results show that there are numerous symptoms which are more commonly recorded after COVID-19 infection. There is a lack of structured recording of symptoms and Long COVID diagnoses, showing the importance of free text in health records for studying these topics
| 0 | PMC9747514 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S197 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.956 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03161-8
10.1016/j.jval.2022.09.956
Article
EPH34 Long COVID Symptoms and Diagnosis in Primary Care: A Cohort Study Using the Thin Database Including Unstructured Text
Shah A 1
Dhalla S 2
Subramanian A 3
Ford E 4
Haroon S 3
Kuan V 1
Nirantharakumar K 3
1University College London, London, UK
2The Health Improvement Network (THIN), Cegedim, North Harrow, LON, UK
3University of Birmingham, Birmingham, LON, UK
4Brighton and Sussex Medical School, Brighton, UK
14 12 2022
12 2022
14 12 2022
25 12 S197S197
Copyright © 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
Long COVID is a widely recognised consequence of COVID-19 infection, but there is currently little information about the symptoms that patients present with in primary care, as these are typically recorded only in free text clinical notes.
Objectives
To compare the occurrence of symptoms in patients with and without a history of COVID-19 infection.
Methods
We used data from the The Health Improvement Network (THIN, a Cegedim Database). We included patients aged 18 or over registered with participating practices in England, Scotland or Wales. We compared COVID-19 cases (defined by Read-coded diagnoses) with unexposed controls. We extracted baseline and symptom information from both the Read codes and free text, which was analysed by natural language processing. We calculated hazard ratios (adjusted for age, sex, baseline medical conditions and prior record of symptoms) for each of 89 symptoms from 12 weeks after the COVID-19 diagnosis.
Results
We compared 10,229 patients with confirmed COVID-19 and 22,654 unexposed controls. Patients had a mean age of 52.4 years and 62.5% were female. Around 80% of the symptom mentions in the primary care were only in the free text. A wide range of symptoms were associated with previous COVID-19 infection, including shortness of breath (hazard ratio (HR) 3.2, 95% confidence interval (CI) 2.8, 3.5), chest pain (HR 2.35, 95% CI 2.03, 2.72) and fatigue (HR 3.4, 95% CI 3.0, 3.8). There were 603 free text entries of ‘Long Covid’, but none recorded using Read codes.
Conclusions
These preliminary results show that there are numerous symptoms which are more commonly recorded after COVID-19 infection. There is a lack of structured recording of symptoms and Long COVID diagnoses, showing the importance of free text in health records for studying these topics
| 0 | PMC9747515 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S193 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.936 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03329-0
10.1016/j.jval.2022.09.1124
Article
EPH203 Estimating the Impact of COVID-19 Pandemic on Gynaecology Treatment in England
Sloan R 1
Morris E 2
Walworth R 2
King R 3
Marsland A 3
Bray BD 3
Pearson-Stuttard J 3
1Lane Clark & Peacock, Winchester, HAM, UK
2Royal College of Obstetricians and Gynaecologists, London, UK
3Lane Clark & Peacock, London, UK
14 12 2022
12 2022
14 12 2022
25 12 S230S230
Copyright © 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
pmcObjectives
The Covid-19 pandemic had a large and lasting impact on healthcare systems. This impact has been felt unequally by geography and speciality. Redeployment of gynaecological healthcare professionals over the pandemic has further impacted the delay in elective care. We aimed to: characterise the overall gynaecology waiting list by geography, estimate the number of additional patients who would have sought care had the pandemic not occurred (‘hidden referrals’) and identify how hospital care for gynaecological conditions has changed since the pandemic.
Methods
We used publicly available National Health Service data to estimate the number of known patients on the gynaecology waiting lists at small geographical level from April 2018 to January 2021 across England. We estimated the number hidden referrals by calculating the number of fewer referrals to treatment during the pandemic compared to 2019. We used NHS admission and outpatient data to identify the trends in admissions pre and post pandemic by condition.
Results
The gynaecology waiting list has increased at the fastest rate of all specialities in England (60% increase) rising to nearly 460,000 as of 31 January 2022. We estimated a further 400,000 hidden referrals still to join the waiting list. There were significant geographical disparities, with the largest number of waits in North West England (over 1,000 per 100,000 population). Urogynaecological conditions appeared to be most impacted by the pandemic with a 60% reduction in admissions for prolapse or incontinence compared to 55% or less for other gynaecological conditions.
Conclusions
Gynaecology waiting lists have increased substantially across the UK, with large inequalities geographically. Policy change is required to address geographical disparity and prioritise gynaecology as a speciality to limit the widening of these inequalities.
| 0 | PMC9747516 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S230 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1124 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04498-9
10.1016/j.jval.2022.09.2293
Article
RWD68 Characteristics/Comorbidities of Vaccinated and Unvaccinated Patients With COVID-19
Roy A 1
Markan R 1
Kumar S 1
Verma V 2
Kukreja I 3
Gaur A 1
Chopra A 1
Nayyar A 1
Daral S 1
Pandey S 1
Mohanty P 1
Aswal D 1
1Optum, Gurugram, HR, India
2Optum, Gurgaon, HR, India
3Optum, New Delhi, DL, India
14 12 2022
12 2022
14 12 2022
25 12 S461S461
Copyright © 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
pmcObjectives
The objective of this study is to analyze the comorbidities and Charlson Comorbidity Index (CCI) among the vaccinated and unvaccinated COVID-19 patients.
Methods
In this retrospective study, Optum’s de-identified Clinformatics® Data Mart database was used to identify all the patients above 18 years who underwent treatment for COVID-19 in the US between 1 Jan 2021 to 30 Sep 2021. The occurrence of the ICD-10 code for COVID-19 infection in the claims database was defined as the index event. The Charlson Comorbidity Index (CCI) score and top comorbid conditions were checked in the vaccinated and unvaccinated patient cohort during the 6 months pre-index period. The CCI score predicts the ten-year mortality for a patient who may have a range of comorbid conditions and each condition is assigned a score of 1,2,3 or 6, depending on the risk of dying associated with each one.
Results
Out of 277,319 COVID-19 patients, 274,165 (98.9%) were unvaccinated while 3,154 (1.1%) were fully vaccinated patients. In the unvaccinated cohort, 54% of the patients were females and 46% were males as compared to 56% females and 44% males in the vaccinated cohort. 16% of unvaccinated patients and 12% of vaccinated patients had a Charlson Comorbidity Index (CCI) score >=5. In both cohorts, endocrinal diseases, CVS diseases, and musculoskeletal diseases are the top 3 comorbidities. Further statistical tests will be applied to analyze the level of significance.
Conclusions
Patients with a CCI score of >=5 are more in the unvaccinated cohort as compared to the vaccinated cohort. Further analysis of mortality data and CCI scores is required to substantiate the effectiveness of vaccines.
| 0 | PMC9747518 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S461 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.2293 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03691-9
10.1016/j.jval.2022.09.1486
Article
HTA26 Health Technology Assessment (HTA) Methods for Monoclonal Antibodies for Treatment and Prevention of COVID-19
Warttig S
Ling C
RTI Health Solutions, Manchester, LAN, UK
14 12 2022
12 2022
14 12 2022
25 12 S301S301
Copyright © 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
pmcObjectives
To research HTA procedures used to assess COVID-19 technologies in US, Canada, and EU5; to assess whether HTA procedures for COVID-19 technologies differ from established HTA procedures for that country and which COVID-19 monoclonal antibodies (mAb) have been assessed.
Methods
Information relating to HTA procedures, mAbs, and outcomes (if available) were identified and extracted from each agency’s website and qualitatively assessed.
Results
Two countries with decentralized HTA procedures (Italy, Spain) were excluded from analysis. Five countries have HTA agencies assessing COVID-19 technologies. Adapted HTA procedures are used by three (NICE, CADTH, ICER), and procedures are unclear for two (HAS, G-BA) it is unclear what procedures are used. Of nine mAbs available for treatment and prevention of COVID-19, four are the subject of HTA:
• Casirivimab & Imdevimab: HAS (published; early access granted), CADTH (published; unable to make a decision), NICE (in progress), G-BA (in progress)
• Lenzilumab: NICE (in progress)
• Sotrovimab: HAS (published; opinion in favor of reimbursement), CADTH (published; no decision) NICE (in progress), G-BA (in progress)
• Tocilizumab: NICE (in progress), CADTH (published; no decision)
No HTAs were identified for the remaining five mAbs: bebtelovimab, bamlanivimab & etesevimab, regdanvimab, sarilumab, and tixagevimab & cilgavimab.
Conclusions
Agencies are applying HTA procedures to COVID-19 technologies. Assessments, particularly for COVID-19 mAbs, will face challenges. Differing trial designs, definitions and outcomes, and a lack of standard-of-care treatments early in the pandemic may render estimates of comparative effectiveness invalid. Clinical and cost-effectiveness estimates will be affected by a number of other factors, including trial timing, prevalence of variants and their susceptibility to different mAbs, and the proportion of patients remaining vulnerable to severe disease after vaccine rollout. These variables may not be captured in traditional trial-based evidence, rendering HTA reliant on real-world evidence, and HTA decisions may lack longevity and will require frequent updates.
| 0 | PMC9747519 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S301 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1486 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04163-8
10.1016/j.jval.2022.09.1958
Article
PCR23 Humanistic Burden and Mental Conditions Among Cancer Patients Before and During the COVID-19 Pandemic in Japan and China
Tan WH 1
Chen Y 1
Gao M 2
Woo A 1
1Cerner Enviza, Singapore, Singapore
2Cerner Enviza, Shanghai, China
14 12 2022
12 2022
14 12 2022
25 12 S394S394
Copyright © 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
pmcObjectives
The COVID-19 pandemic has imposed substantial disruptions in many aspects of daily life. These impacts could be particularly worse for certain at-risk populations such as cancer patients. In this study, we assessed the humanistic burden and prevalence of mental conditions among cancer patients during the COVID-19 pandemic in Asian countries.
Methods
This study utilized the Internet-based National Health and Wellness Survey (NHWS) conducted in Japan and China. Specifically, we included respondents from the Japan NHWS in 2019 (n=30,006), 2020 (n=30,092), 2021 (n=30,015), and the China NHWS in 2017 (n=19,994) and 2020 (n=20,051). Cancer patients were identified based on self-reported physician diagnosis, including any type of solid tumors and hematologic cancers. For both cancer patients and the general population, bivariate analyses were used to compare demographic characteristics, Health-related Quality of Life (HRQoL), work productivity and activity impairment (WPAI), and prevalence of mental conditions before (2017, 2019), during (2020), and after (2021) COVID-19 outbreak.
Results
We observed statistically significant improvements in some aspects of HRQoL and mental conditions among cancer patients during the COVID-19 period in both countries. In Japan, there were significant decreases in depressive symptoms (Patient Health Questionnaire-9 [PHQ-9]≥10) and depression diagnoses (4.6% in 2019 vs 4.5% in 2020 vs. 2.7% in 2021, p<0.01). In addition, we found increases in some HRQoL measures and decreases in WPAI among cancer patients. In China, we also observed a significant decrease in depression diagnoses (18.9% in 2017 vs. 14.0% in 2020, p<0.05) among cancer patients. There were statistically significant albeit marginal improvements in some HRQoL measures; however, there was an increase in absenteeism.
Conclusions
Contrary to our expectations, this study indicated improvements in HRQoL and depression under the COVID-19 pandemic. Nevertheless, the effect on WPAI was different between Japan and China, likely owing to differences in COVID-related policies between the two countries.
| 0 | PMC9747520 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S394 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1958 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)04163-8
10.1016/j.jval.2022.09.1958
Article
PCR23 Humanistic Burden and Mental Conditions Among Cancer Patients Before and During the COVID-19 Pandemic in Japan and China
Tan WH 1
Chen Y 1
Gao M 2
Woo A 1
1Cerner Enviza, Singapore, Singapore
2Cerner Enviza, Shanghai, China
14 12 2022
12 2022
14 12 2022
25 12 S394S394
Copyright © 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
pmcObjectives
The COVID-19 pandemic has imposed substantial disruptions in many aspects of daily life. These impacts could be particularly worse for certain at-risk populations such as cancer patients. In this study, we assessed the humanistic burden and prevalence of mental conditions among cancer patients during the COVID-19 pandemic in Asian countries.
Methods
This study utilized the Internet-based National Health and Wellness Survey (NHWS) conducted in Japan and China. Specifically, we included respondents from the Japan NHWS in 2019 (n=30,006), 2020 (n=30,092), 2021 (n=30,015), and the China NHWS in 2017 (n=19,994) and 2020 (n=20,051). Cancer patients were identified based on self-reported physician diagnosis, including any type of solid tumors and hematologic cancers. For both cancer patients and the general population, bivariate analyses were used to compare demographic characteristics, Health-related Quality of Life (HRQoL), work productivity and activity impairment (WPAI), and prevalence of mental conditions before (2017, 2019), during (2020), and after (2021) COVID-19 outbreak.
Results
We observed statistically significant improvements in some aspects of HRQoL and mental conditions among cancer patients during the COVID-19 period in both countries. In Japan, there were significant decreases in depressive symptoms (Patient Health Questionnaire-9 [PHQ-9]≥10) and depression diagnoses (4.6% in 2019 vs 4.5% in 2020 vs. 2.7% in 2021, p<0.01). In addition, we found increases in some HRQoL measures and decreases in WPAI among cancer patients. In China, we also observed a significant decrease in depression diagnoses (18.9% in 2017 vs. 14.0% in 2020, p<0.05) among cancer patients. There were statistically significant albeit marginal improvements in some HRQoL measures; however, there was an increase in absenteeism.
Conclusions
Contrary to our expectations, this study indicated improvements in HRQoL and depression under the COVID-19 pandemic. Nevertheless, the effect on WPAI was different between Japan and China, likely owing to differences in COVID-related policies between the two countries.
| 0 | PMC9747521 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S204 | latin-1 | Value Health | 2,022 | 10.1016/j.jval.2022.09.988 | oa_other |
==== Front
Value Health
Value Health
Value in Health
1098-3015
1524-4733
Published by Elsevier Inc.
S1098-3015(22)03250-8
10.1016/j.jval.2022.09.1045
Article
EPH124 Prediction Model to Evaluate the Impact of a Next Generation Bivalent Omicron-Containing COVID-19 Booster (MRNA.1273.214) on Hospitalizations in Adults in Germany
Müller A 1
Ultsch B 2
Nasir A 3
Certejan T 3
Buck P 3
Ben A 4
Raths J 5
Wahler S 6
Van de Velde N 3
1Analytic Services GmbH, Munich, Germany
2Moderna, Germany GmbH, Munich, Germany
3Moderna, Inc., Cambridge, MA, USA
4Cordee Consulting, Tel Aviv, Israel
5Cordee Consulting, Geneva, Switzerland
6St. Bernward GmbH, Hamburg, Germany
14 12 2022
12 2022
14 12 2022
25 12 S215S215
Copyright © 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.
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pmcObjectives
The COVID-19 pandemic challenges healthcare systems globally. Models support decision-makers in optimizing vaccination strategies. Our objective was to estimate COVID-19 related hospital admissions in the upcoming Winter 2022/2023 season assuming BA.4/BA.5 as dominant variants. We modeled the effects of a candidate bivalent vaccine in adults compared to no additional booster campaign in Fall or boosting with first generation vaccines.
Methods
We developed a cohort model using vaccination and hospitalization data published by Germany’s Robert Koch Institute. To account for waning vaccine-induced immunity, we modeled the decrease in neutralizing antibody titers attributed to BA.4/BA.5 by relating in-vitro neutralization titers to protection from infection based on previous studies. This approach is conservative given that bivalent vaccines have shown a slower decline in titers compared to monovalent vaccines. Coverage was assumed identical to the first booster campaign, with a rapid roll out over 6 weeks starting in September 2022, and outcomes reported for the period September-December.
Results
Without an additional booster campaign in the Fall, average population protection rates could drop to 24.7% (range 21.2-28.1%) leading to 214,247 hospital admissions, and weekly hospitalizations reaching 21,472. Using first generation prototype boosters, we project 163,301 hospital admissions and a weekly peak of 14,887, which represent reductions of 24% and 31%, respectively. Based on recent neutralizing antibody results, using a bivalent booster could reduce the number of hospitalizations down to 147,392 with peak weekly admissions of 13,018, which represent reductions of 31% and 39% compared to no booster. Results will be updated as more data become available.
Conclusions
Assuming BA.4/BA.5 are dominant variants during Winter 2022/2023, using a next generation bivalent vaccine within a condensed 6-week period beginning September 2022 would prevent a significant amount of hospital admissions in Germany, as well as lower the peak in weekly hospitalization rates, compared to monovalent vaccines.
| 0 | PMC9747523 | NO-CC CODE | 2022-12-15 23:22:01 | no | Value Health. 2022 Dec 14; 25(12):S215 | utf-8 | Value Health | 2,022 | 10.1016/j.jval.2022.09.1045 | oa_other |
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Indian J Pediatr
Indian J Pediatr
Indian Journal of Pediatrics
0019-5456
0973-7693
Springer India New Delhi
4417
10.1007/s12098-022-04417-4
Scientific Letter
Intravenous Immunoglobulin and Methylprednisolone Refractory Multisystem Inflammatory Syndrome in Children (MIS-C) in Steroid-Dependent Nephrotic Syndrome Following Rituximab
http://orcid.org/0000-0003-3273-6218
Pal Priyankar [email protected]
Ghosh Saugat
Chaudhuri Kaustabh
Sinha Rajiv
Department of Pediatrics, Apollo Hospitals, Kolkata, West Bengal India
14 12 2022
11
9 8 2022
21 11 2022
© The Author(s), under exclusive licence to Dr. K C Chaudhuri Foundation 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.
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pmcTo the Editor: A 9-y-old male, known steroid-dependent nephrotic syndrome patient, on alternate-day prednisolone, and having received rituximab 10 d back, presented with high fever and maculopapular rashes for 2 d. On admission, he was in shock, which was diagnosed as septic shock. Fluid resuscitation and inotropes were started. 2D echo revealed global dyskinesia of the heart and an ejection fraction (EF) 40%. COVID IgG level was 8719.6 (cutoff < 60 AU/mL), NT-proBNP was 26202 pg/mL (< 300 pg/mL), D-dimer was 6252.7 ng/mL (< 500 ng/mL), ferritin was 1595 ng/mL (< 150 ng/mL), IL-6 was 743.9 pg/mL (< 43 pg/mL), CRP was 26.5 mg/dL, and procalcitonin was 27.4 ng/mL. Cultures were negative.
The diagnosis was revised to MIS-C; IVIg 1 g/kg and methylprednisolone 10 mg/kg were initiated, but fever spikes persisted with hypotension, and the EF lowered to 20%. Methylprednisolone was increased to 1 g/d but on day 3, platelets dropped to 45000/cmm and ferritin elevated to 16585, INR 3.5, SGPT 4540 IU/L, and creatinine 2.1 mg/dL. Considering a refractory hypercytokinemic state with multiorgan dysfunction, he was administered the IL-6 inhibitor tocilizumab IV, 8 mg/kg. Fever and inflammatory markers decreased, and EF improved to 50% over the next 3 d.
Post-COVID MIS-C is a life-threatening condition; IVIg and steroids being the mainstays of treatment, with an overall good prognosis if diagnosed and treated rapidly. The data over the last 2 y showed that patients on rituximab fared poorly following COVID-19 infection [1], but there are no reports on the severity of MIS-C in post-Rituximab patients. Our patient received rituximab, which induces trogocytosis of B-cells, resulting in acute production and release of IL-6 [2]. IL-6 concentrations are elevated in critically ill MIS-C patients, and hence is implicated in diagnosis, prognosis, and more importantly, the use of tocilizumab in treatment [3, 4].
Our patient had stormy presentation with cardiogenic shock on day 2 of fever, showed rapidly increasing severity in spite of IVIg and steroids, and finally responded to tocilizumab. This is the first reported case of post-rituximab MIS-C.
Declarations
Conflict of Interest
None.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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References
1. Andersen KM, Bates BA, Rashidi ES et al; National COVID Cohort Collaborative Consortium. Long-term use of immunosuppressive medicines and in-hospital COVID-19 outcomes: a retrospective cohort study using data from the National COVID Cohort Collaborative. Lancet Rheumatol. 2022;4:e33–e41.
2. Jones JD Hamilton BJ Skopelja S Rigby WF Induction of interleukin-6 production by rituximab in human B cells Arthritis Rheumatol 2014 66 2938 2946 10.1002/art.38798 25080282
3. Diaz F, Bustos BR, Yagnam F, et al. Comparison of interleukin-6 plasma concentration in multisystem inflammatory syndrome in children associated with SARS-CoV-2 and pediatric sepsis. Front Pediatr. 2021;9:756083.
4. Balasubramanian S Nagendran TM Ramachandran B Ramanan AV Hyper-inflammatory syndrome in a child with COVID-19 treated successfully with intravenous immunoglobulin and tocilizumab Indian Pediatr 2020 57 681 683 10.1007/s13312-020-1901-z 32393681
| 36513884 | PMC9747530 | NO-CC CODE | 2022-12-15 23:22:01 | no | Indian J Pediatr. 2022 Dec 14;:1 | utf-8 | Indian J Pediatr | 2,022 | 10.1007/s12098-022-04417-4 | oa_other |
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Tech Coloproctol
Tech Coloproctol
Techniques in Coloproctology
1123-6337
1128-045X
Springer International Publishing Cham
2743
10.1007/s10151-022-02743-5
Correspondence
Telemedicine in proctology through public communication platforms: comfort or danger zone?
Zacharis G. 1
Dedopoulou P. 1
http://orcid.org/0000-0002-7762-5733
Seretis C. [email protected]
12
1 grid.412458.e Department of General Surgery, St Andreas General Hospital of Patras, Patras, Greece
2 grid.7372.1 0000 0000 8809 1613 Warwick Medical School, University of Warwick, Coventry, UK
14 12 2022
11
26 11 2022
6 12 2022
© 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.
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pmcDear Sir,
We read with great interest the study entitled “Use of telemedicine in the postoperative assessment of proctological patients: a case–control study”, by Gaj, et al. [1], describing the implementation and associated benefits of the popular “WhatsApp” application for follow-up purposes after proctological procedures. Although we strongly agree that the incorporation of modern technology in the framework of telemedicine is of paramount importance, particularly in the post-COVID-19 era, having similar positive experience from our host institutions, we would like to point out the existence of some relevant, potentially hazardous, medico-legal implications.
Even though the authors correctly obtained ethical approval from their unit and also informed consent from the patients, we strongly believe that the use of a public platform for sharing patients’ private data, even in the context of strict communication between patient and surgeon, could lead to serious legal incidents if the material is potentially subject to data breach/hacking/unintentional leak to third parties. In our opinion, the providers of the social media/public communication platforms themselves, in the event of sharing such types of strictly personal information, should be consulted and relevant documentation should be included in the study information leaflets and patient consent forms. The latter is a minimum safety barrier to ensure legal cover for the surgeons and their institutions, as well as a safety net for protection of patients’ privacy. We strongly believe that telemedicine in any form should only be conducted through dedicated institutional platforms and software, ideally within the medical facilities themselves, in order to avoid potential data protection issues.
Funding
None required.
Declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval
None required.
Informed consent
Not required.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
Reference
1. Gaj F Peracchini M Passannanti D Quaresima S Giovanardi F Lai Q Use of telemedicine in the postoperative assessment of proctological patients: a case-control study Tech Coloproctol 2022 10.1007/s10151-022-02723-9
| 36513840 | PMC9747531 | NO-CC CODE | 2022-12-15 23:22:01 | no | Tech Coloproctol. 2022 Dec 14;:1 | utf-8 | Tech Coloproctol | 2,022 | 10.1007/s10151-022-02743-5 | oa_other |
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J Educ Change
Journal of Educational Change
1389-2843
1573-1812
Springer Netherlands Dordrecht
9475
10.1007/s10833-022-09475-1
Article
The limits of the “system of schools” approach: Superintendent perspectives on change efforts in U.S. Catholic school systems
http://orcid.org/0000-0002-4715-0650
Miller Andrew F. [email protected]
1
Reyes John 2
Wyttenbach Melodie 2
Ezeugwu Gilbert 3
1 grid.208226.c 0000 0004 0444 7053 Department of Educational Leadership and Higher Education, Boston College Lynch School of Education and Human Development, Campion Hall 205, 140 Commonwealth Avenue, Chestnut Hill, MA 02467 USA
2 grid.208226.c 0000 0004 0444 7053 Roche Center for Catholic Education, Boston College, Chestnut Hill, MA 02467 USA
3 grid.208226.c 0000 0004 0444 7053 Department of Teaching, Curriculum, and Society, Boston College Lynch School of Education and Human Development, Chestnut Hill, MA 02467 USA
14 12 2022
128
23 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.
Catholic schooling in the United States is suffering from a persistent enrollment crisis that has triggered the need for system-wide organizational reforms. However, most of the changes that the sector has experienced has taken place in individual schools making decisions about how to operationally sustain their individual school community. In this article, we present findings from a qualitative analysis of 26 superintendents of (arch)diocesan Catholic school systems in order to better understand why there has been an absence of system-level change in the Catholic sector in the U.S. at a time when systems thinking has started to spread throughout other sectors domestically and internationally. We show through the findings presented in this paper that many Catholic school systems in the United States do not sustain system-level change because they rely on a decentralized “system of schools” organizational form that superintendents believe limits the possibility for sector-wide organizational reform. We highlight in this paper the ways superintendents are forced to navigate these organizational and political limitations and suggest what the implications of this limited possibility for system-level change are for the Catholic sector and other similarly organized sectors.
Keywords
Organizational change
System-level change
Catholic school systems
Superintendents as change agents
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pmcEducational leaders in the Catholic sector in the United States (U.S.) have been engaged for the past 40 years in debates about how to exit a period of sustained organizational and institutional decline (Hamilton, 2008; Miserandino, 2019; Saroki & Levenick, 2009). This contemporary period of decline, following the sector achieving a peak of over five million students enrolled in Catholic elementary and secondary schools during the 1960s, has been caused by multiple factors including people’s institutional disaffiliation from the Catholic Church after revelations of the Church’s ongoing sexual abuse crises (D’Antonio et al., 2013). The primary signals of this period of decline have been persistent trends of declining enrollment numbers and increasing school closures in the U.S. (Murnane & Reardon, 2018). These trends have not fully reversed even after Catholic schools saw minor increases in enrollment during the 2020–2021 academic year (National Catholic Educational Association [NCEA], n.d.). In the 2021–2022 academic year, though there were still more PreK-12 schools operated by the Roman Catholic Church in the U.S. than any other private school provider, there were just under 1.6 million students attending just under 6000 Catholic schools in the U.S. (Irwin et al., 2021).
As stated in a widely-cited report released by the private philanthropic organization Foundations and Donors Interested in Catholic Activities [FADICA], the reality facing Catholic schools in the U.S. in this period of decline is thatMost schools are confronting similar problems, even though their contexts and responses are different. Catholic schools all across the country are struggling to remain viable and compete in a crowded marketplace. Schools are looking to boost enrollment, remain affordable to lower-income and all students, and continue to provide a high-quality education and faith formation for which Catholic schools are known. (FADICA, 2020, p. 18)
One common attempt to solve the sector’s crisis promoted by many Catholic sector advocates and policymakers has been to identify what makes Catholic schools in the U.S. distinct from other sectors and providers (e.g., Brinig & Garnett, 2014; Porter-Magee et al., 2022). Though there continues to be no consistent evidence that Catholic schools either generate or significantly contribute to better academic and nonacademic student learning outcomes than their public school counterparts (Miller et al., 2022; Marks, 2009), there is some recent evidence published in both peer-reviewed journals and in advocacy-oriented gray literature that parent satisfaction with Catholic schools among both Catholic and non-Catholic parents has been consistently positive (FADICA & National Catholic Educational Association [NCEA], 2018; Henderson et al., 2021; Wodon, 2022). For Catholic education policy advocates, findings like these suggest the solution to the sector’s organizational crisis may lie in identifying what local communities are doing to stabilize and grow student enrollments (O’Keefe & Goldschmidt, 2014).
Similarly, another common approach to solving the sector’s organizational crisis found in research reports published by nonprofit organizations advocating for Catholic school reform has been to examine the organizational models employed by individual thriving and failing Catholic schools (FADICA, 2015, 2020; Ozar & Weitzel-O’Neill, 2012). It has long been the case that Catholic elementary schools, 65% of which employ a parish governance model in which parish priests retain significant operational authority over school decision-making, close more frequently than Catholic secondary schools, more than 80% of which are governed by diocesan or private boards with significant organizational autonomy (NCEA, n.d.). Catholic school philanthropists looking to put money behind effective school organizational models have started to assume that this over-reliance on parish governance models in Catholic elementary schools has been a central factor in the sector’s organizational declines, or as Smarick and Robson (2015) argued in a report published by The Philanthropy Roundtable, “There is considerable consensus today that the traditional Catholic school run by the local church is unsustainable in many places…Changing the way Catholic schools are organized, operated, and governed means overturning more than a century’s worth of practice” (pp. 36–37). This commonly held perspective in the Catholic education philanthropic community has influenced the development and implementation of new governance and leadership models for Catholic elementary schools throughout the U.S. designed to be as operationally and fiscally sustainable as many Catholic secondary schools have been (Cooper & D’Agustino, 2014; DeFiore, 2014; O’Keefe & Scheopner, 2007; Walch, 2014).
At a time when Catholic school advocates and system leaders have suggested the sector lacks the organizational capacity to help most Catholic elementary schools survive this period of decline (FADICA, 2015, 2020), it is notable that both of these common approaches to solving the sector’s crisis emphasize individual school change management processes. Because of the dominance of these two approaches in the field, though, there has been considerably more research conducted on local reform initiatives in distinct school communities and environments in the U.S. (FADICA, 2020; Goldschmidt & Walsh, 2013) than on the effectiveness or structure of the regional (arch)diocesan school systems in which Catholic elementary schools governed by parishes are embedded (Neumerski & Cohen, 2019; O’Keefe & Goldschmidt, 2014). These (arch)diocesan systems are similar in structure to the local public school districts and charter management organizations they geographically border; for example, almost all (arch)diocesan systems contain superintendents who serve as chief executive officers of the various elementary and secondary schools that call themselves Catholic in a given (arch)diocesan region. But unlike contemporary systems-level change research in the U.S. detailing the ways public school systems have contributed to educational change processes in the individual schools connected through those systems (e.g., Finnigan & Daly, 2016; Peurach et al., 2019), to this point there has been little peer-reviewed research examining the dynamics within and across (arch)diocesan systems that either contribute to or hinder the possibility for systemic or local organizational changes to take root. Where this research has been conducted, it has tended to be published by philanthropic and advocacy organizations interested in addressing organizational problems in Catholic schools.
Therefore, in this article, we attempt to address this gap in the literature by providing an initial answer to the following research question: according to system-level leaders in U.S. Catholic school systems, what are the organizational conditions in those systems and what capacity do those systems have to initiate or sustain educational change?
To answer this question, this article presents an empirical analysis of the perspectives of superintendents of (arch)diocesan school systems in order to demonstrate how “typical” system-level leaders of Catholic school systems make sense of the capacity their systems have to support the kinds of educational reforms and change management processes Catholic school advocates have encouraged these leaders to pursue. In response to our research question, we first demonstrate how superintendents described their (arch)diocesan systems and highlight the opportunities they claimed to have been afforded as system-level leaders to create or sustain continuous improvement initiatives that would benefit multiple schools in their (arch)diocesan systems. We then show how (arch)diocesan system capacity for system-wide change has been constrained by complex micropolitical dynamics in these (arch)diocesan networks and how perceptions of the unchangeability of these dynamics has further constrained superintendents’ political will within these systems to attempt system-wide, mission-aligned reform initiatives that might enhance the operational vitality of all schools in that system. We ultimately argue in this paper that, according to superintendents, the desire to maintain an intentionally decentralized, “system of schools” approach to system organization has foreclosed the ability of (arch)diocesan systems to initiate system-wide educational change processes. We conclude this paper with a brief discussion of the research, practice, and policy implications of the limited horizon for system-wide educational change in the Catholic sector in the U.S.
Empirical and theoretical grounding
To help us make sense of how superintendents perceived the organization of (arch)diocesan school systems and the capacity these systems have for sustaining educational change over time, our analysis was informed by empirical research about the state of Catholic elementary and secondary schools in the U.S. as well as conceptual and theoretical perspectives cutting across the fields of educational leadership (e.g., Spillane et al., 2019), educational policy (e.g., Marsh et al., 2021), and educational change (e.g., Daly & Finnigan, 2016).
Empirical research on Catholic Schools in the U.S.
The Roman Catholic Church currently operates one of the largest networks of primary and secondary schools in the world and has been throughout its history committed to creating and sustaining educational organizations wherever it has an institutional presence (Miller, 2007). But despite recent theological and philosophical traditions that have attempted to articulate universal normative theories of what constitutes Catholic education (e.g., Groome, 2022; Whittle, 2017, 2018), the practice of Catholic schooling has tended to be distinct in each nation. As Grace and O’Keefe (2007) pointed out in their introduction to the International Handbook of Catholic Education: Challenges for School Systems in the 21st Century, contemporary Catholic school systems are necessarily shaped both by the institutional dynamics of the local Catholic Church in a given country and the distinct legal, organizational, and political conditions in each nation where these schools are operated.
In the U.S., Catholic elementary and secondary schools are legally private entities that maintain private governance structures and do not receive direct federal subsidy or financing. The nearly 6,000 individual Catholic schools in the U.S. are geographically divided into 175 regional (arch)dioceses led by (arch)bishops appointed by central Catholic Church authorities and are frequently classified by the governance models put in place to provide oversight of the day-to-day operations of individual schools: parish/interparish (governed directly by parish organizations run by pastors appointed by bishops), diocesan (governed directly by central diocesan authorities), or private (governed by boards of specified or limited jurisdiction) (FADICA, 2015, 2020).
These regionally organized, privately run Catholic school systems have been one of the largest and oldest non-public schooling options for families in many municipalities in the U.S. (Wodon, 2022). For that reason, there has been an established tradition in U.S. Catholic education research of investigating the outcomes generated in Catholic school systems compared to the outcomes generated in public school districts (e.g., Davies & Quirke, 2007; Freeman & Berends, 2016; Hallinan & Kubitschek, 2012). This mostly quantitative research has never been able to demonstrate the existence of a universal “Catholic school effect” on student outcomes attributable to all Catholic schools within the sector (Miller et al., 2022; Figlio, 2021), but the assumption that a “Catholic school effect” exists has reinforced for many Catholic school policy advocates the idea that Catholic school closures will have negative impacts on students, local communities, and the American populace more broadly (e.g., Brinig & Garnett, 2014). These ideas have subsequently led to a notable contemporary trend among Catholic sector researchers, policymakers, and stakeholders to focus empirical inquiry on determining what organizational and leadership conditions in individual Catholic schools will keep these schools operationally sustainable (e.g., Curtin et al., 2010; Grace & O’Keefe, 2007; Haney & O’Keefe, 2009; Ozar & Wetizel-O’Neill, 2012). While this trend does not encapsulate the interests of all contemporary Catholic education researchers in the field, where there is still considerable emphasis on the curricular and spiritual dimensions of Catholic schooling (e.g., Franchi & Davis, 2021; Groome, 2022), organizational questions have become a primary focus of research that attempts to account for the sector’s viability compared to other sectors against which it competes in the current educational policy moment in the U.S. (Miller et al., 2022; Neumerski & Cohen, 2019).
Much of this organizational change management research in Catholic schools has been found in reports of research, only some of which have gone through the process of peer review, that detail local policy and practice innovations designed to transition individual Catholic elementary schools away from single-parish models (currently 54% of all schools, 65% of elementary schools) toward diocesan or private models (currently 34% of all schools, 22% of elementary schools) (e.g., FADICA, 2015, 2020; Goldschmidt & Walsh, 2013; Miserandino, 2019; O’Keefe & Goldschmidt, 2014; Smarick & Robson, 2015). Most of this contemporary Catholic school governance research has been descriptive and exploratory and has not tended to evaluate different governance models that have emerged in particular contexts. And unlike research in Catholic secondary schools in the late twentieth century that documented the organizational effectiveness of the emerging trend toward president-principal leadership models and that subsequently called for the widespread adoption of this model (e.g., Dygert, 2000), contemporary Catholic school governance research has also tended to stop short of becoming prescriptive or proscriptive of the kinds of organizational reforms contemporary Catholic elementary school leaders should pursue. For example, the Foundations and Donors Interested in Catholic Activities released two widely cited reports containing a two-axis matrix of governance/leadership organizational forms Catholic schools could adopt, but the authors noted that no single location on the matrix was inherently preferable to any other location (FADICA, 2015, 2020).
It is also notable that while there has been significant contemporary research on Catholic school governance, this research has almost exclusively framed educational change decision-making as something happening within individual school communities (Ozar & Weitzel-O’Neill, 2012). (Arch)diocesan school systems in the U.S. contain superintendents, central offices, and centralized services that mirror the public district systems to which they are frequently compared in sector effects research (Cattaro & Cooper, 2007). But unlike the recent systems research conducted in the public sector in the U.S. described in more detail in the next section (e.g., Neumerski & Cohen, 2019; Spillane et al., 2019), relatively little research has adequately accounted for system-wide organizational conditions that contribute to, shape, or inform individual Catholic school capacity to sustain educational change processes or initiatives. Therefore, this study is intended to help the field better understand the distinct system infrastructures that are present within the Catholic sector according to system-level leaders in order to better understand how these systems function.
Conceptual and theoretical perspectives on educational system building
There has been a long tradition within international educational change research communities considering whether or how school systems matter to the process of educational change (e.g., Malone, 2020; Møller, 2009; Stoll, 2006). The variety of institutional and organizational arrangements in primary/secondary schooling across nations has resulted in a necessary diversity of templates and frameworks for making sense of system-level change (Thomson & Blackmore, 2006). For example, Lingard et al. (2021) have shown how nations that prioritize top-down accountability politics in education have tended to be associated with a desire to scale-up large systems of schools aligned to those accountability demands. Similarly, many educational change researchers and theorists have approached thinking about system-level educational changes in light of distinct national or regional approaches toward the need for school systems, such as Kvalsund’s (2009) examination of the tensions present in Norway’s national system between centralized and decentralized approaches and Rincón-Gallardo’s (2020) theorization of educational change as social movement in decentralized local school communities in the global south. One of the only common emphases in system-level research in this field has been to examine whether system infrastructure and capacity align so that a system can work toward its student learning and formation goals (Stoll, 2020).
Many contemporary educational systems scholars in the U.S. have emphasized the importance of focusing on school systems rather than individual schools when investigating the possibility of educational change because as Finnigan and Daly (2016) remarked, “The limited success of the last decade of high-stakes accountability policies at the school level suggests both an urgent need for action and a need to reconsider the system (or school district) as the leverage point for improvement” (p. 2). This branch of educational change research in the U.S. has shown that while attempts to rationalize teaching practice to generate desired outcomes have not been universally successful (Mehta, 2013), school-level reform goals have over the course of the past three decades become more tightly coupled to district-level educational policy goals (Yurkofsky, 2020). These educational systems perspectives have demonstrated how districts have created normative, social, and policy environments in which individual schools work toward these goals and posited that the success of a school’s educational change efforts are best interpreted in relationship to the success of district-wide educational changes (Peurach et al., 2019; Trujillo, 2016). According to these scholars, educational systems matter not only because the large-scale contemporary educational policy goals in the U.S. have not been met by individual school-level changes, but also because the diverse ways district systems are organized influence and shape how school and system leaders work toward change (Finnigan & Daly, 2016; Peurach et al., 2019; Smylie, 2016).
Subsequently, in order to make sense of how educational systems matter, this contemporary educational systems research in the U.S. has tended to investigate relationships between and among two distinct features of educational systems: (1) the form of district organization, comprised of the people, structures, and goals of the system itself; and (2) the function of district organization, or the way system-level leaders navigate the mediating role systems play between schools and educational policy goals (Daly & Finnigan, 2016). For example, Peurach et al. (2019) assessed how different categories of system forms defined by distinct system infrastructures (e.g., managerial systems that have top-down bureaucratic structures) interact to accomplish similar policy functions (e.g., increasing the quality of instruction). Similarly, Marsh et al. (2021) tracked the process of governance change in portfolio-managed school systems in the U.S. emphasizing how individual school types within the portfolio ended up having similar organizational forms (e.g., actors, strategies, organizational structure, control systems, core values) and functions depending on the organizational dynamics of the particular portfolio-managed district. By investigating these intra- and inter-system organizational dynamics, these organizational and institutional perspectives have afforded these researchers a way to tame the complexity of educational change processes that occur within and across the schools embedded within larger U.S. systems.
While not inclusive of all international perspectives of whether or how systems-level change matters, our research on the capacity and design of U.S. Catholic school systems was most directly informed by this particular community of U.S. educational systems researchers working at the intersection of U.S. educational policy, K-12 educational leadership, and organizational/institutional scholarship. These particular, nationally specific organizational and institutional perspectives on the centrality of educational systems in educational change allowed us to account for how the Catholic sector currently pursues educational change across its various (arch)diocesan systems. In particular, these perspectives provided us with a set of conceptual and theoretical lenses that allowed us to better address the way Catholic school superintendents navigate change management in (arch)diocesan systems that have tended to focus on school-by-school reform efforts. As described in more detail below, we employed these lenses in order to detail the form and function of (arch)diocesan systems as described by superintendents in a more complex and nuanced way than currently found in much research on the organization and impact of the Catholic school sector in the U.S.
Methods of data collection and analysis
This article presents findings drawn from an exploratory, qualitative study (Merriam & Tisdell, 2015; Miles et al., 2018) examining the relationship of Catholic school governance to Catholic sector educational change initiatives. Throughout multiple phases of this study, our research team has conducted data collection and analysis focused on answering our central research question (what are the organizational conditions in (arch)diocesan school systems and how do these conditions constrain/enhance the system’s capacity for educational change?) from the perspective of both school-level and system-level leadership. In this paper, we highlight the perspectives of system-level leaders (e.g., superintendents, secretaries of education), who provide operational and organizational oversight over schools within an (arch)diocesan system, in order to examine the distinct viewpoint system-level leaders may have when posed questions related to system infrastructure, capacity, and change management.
In particular, this article presents an analysis of the perspectives of 26 Catholic system superintendents collected from interviews conducted with these participants during the summer of 2021 (see Table 1). These 26 participants were purposively sampled from the population of (arch)diocesan superintendents in the U.S. The participants were recruited based on the following criteria: (a) they had served as system leaders in Catholic education for at least one full academic year; (b) they had first-hand experience with systemic educational change initiatives in either their current or a former (arch)diocesan system; and (c) they had some experience providing oversight over a variety of the Catholic school governance models described in more detail in the previous section (parish/interparish, diocesan, private). The participating superintendents led dioceses that represented 1613 schools, 492,584 students served (30% of all students in Catholic schools), 15% of all diocesan school systems, and eight of the top 20 largest diocesan school systems by enrollment throughout the U.S. according to the most recent NCEA data (NCEA, n.d.). As Table 1 shows, the organizational and demographic composition of the (arch)diocesan systems these superintendents led are consistent with national trends (NCEA, n.d.). Recruited superintendents were invited to participate in individual, 60-min interviews about organizational structures and educational change and how they approach their role as superintendent within their (arch)diocese. Protocols for the interviews were semi-structured in order for the study to gather their emic perspectives of system capacity and infrastructure and system-level decision-making/leadership. All interviews were audio recorded and transcribed.
Data analysis
Interview transcripts were uploaded into qualitative coding software and were initially analyzed using an open coding process (Miles et al., 2018) designed to identify the dominant empirical trends across all 26 interviews. Each research team member conducted an initial review of each interview transcript resulting in a list of over 60 codes informed by the literature on Catholic school systems and educational change described above. We grouped individual codes into three clusters to synthesize the topical content of each interview (examples in parentheses): forms of (arch)diocesan organization (e.g., centralization, networks of schools, system of schools vs. school system, governance models); opportunities/capacities for change (e.g., presence of change infrastructure, presence of continuous improvement planning, absence of common goals); and micropolitical dynamics in (arch)diocesan systems (e.g., pastor-principal tension, bishop-superintendent tension, donor influence). Our research team met over the course of three consensual coding sessions to reduce these initial open codes within each cluster to eliminate redundancies and to clarify code meanings.
In order to make sense of emergent themes and patterns related to superintendent perceptions not initially brought to light through this topical open coding process, we engaged in analytical memo writing and iterative rounds of axial coding (Merriam & Tisdell, 2015; Miles et al., 2018; Yin, 2014). Analytical memos allowed us to track emerging themes within and across the three topical clusters and helped to identify patterns in the ways superintendents perceived the relative importance of these three topical clusters to their current work as leaders of Catholic school systems. Through this memo-writing phase, we identified four separate kinds of superintendent perceptions: (a) their perspective on how and why their system has come to be structured in a certain way; (b) their perspective on how the different aspects of their system interact; (c) their perspective on what these interactions suggest about the possibility for system-wide reform; and (d) their perspective on whether or not their system is designed to help them reach long-term change management goals. We subsequently engaged in iterative rounds of axial coding (Miles et al., 2018) in which we re-analyzed interview transcripts in light of these four kinds of superintendent perspectives. During this axial coding, we also looked both for discrepancies and moments of consistency across superintendent interview transcripts to test the trustworthiness of the themes emerging in the data related to our overarching research questions.
After these rounds of open and axial coding and analytical memo writing, we developed a set of four assertions about the extent to which organizational conditions in regional (arch)diocesan school systems account for contemporary educational change efforts in U.S. Catholic school systems. These assertions are presented as a series of four themes in the findings section below. Prior to presenting these findings, a few methodological limitations should be noted. Though the demographic and organizational features of the (arch)diocesan systems our participants led were consistent with national trends, we do not claim that the perspectives of the individuals interviewed are necessarily representative of all U.S. Catholic school or system leaders. Rather, these 26 superintendents provided us grounded insight from superintendents currently doing the “typical” work of Catholic school system leadership and highlighted how people in these positions have perceived educational change in the Catholic sector during a period of ongoing sector-wide crises. It should also be noted that these superintendents were interviewed during the summer of 2021, when organizational decision-making continued to primarily be focused on preparing for changes to COVID-19 pandemic regulations. We encouraged our participants to distinguish between what may have been unique about their COVID decision-making compared to the way decision-making occurred prior to the onset of the pandemic, but often this kind of distinction was impossible for superintendents to make. Given these and other potential methodological limitations, our research team also engaged in a series of member checks of the analytical themes presented in the findings in this article with our superintendent participants to evaluate the trustworthiness of our conclusions.
Findings
As stated briefly in the introduction to this article, findings from our interviews with the 26 superintendent participants in this study suggested that the capacity for system-level leaders to enact system-wide continuous improvements in regional (arch)diocesan school systems in the U.S. has been constrained by the organizational dynamics that exist in most (arch)diocesan school systems. Because there has been a commitment to maintaining what superintendents refer to as a “system of schools” infrastructure in U.S. (arch)diocesan school systems, superintendents claimed they have been left little organizational or institutional space to function in the way more centrally designed school systems have been designed.
In this section, we present the four themes that emerged during our analysis of the interview data that led us to this argument about the prospects for the continuous improvement of (arch)diocesan systems in the U.S.: (1) superintendents believed Catholic school systems were necessarily decentralized because of their design as “systems of schools” rather than “school systems;” (2) superintendents believed there were implicit and explicit ways the various parts of their systems continually reinforced this “system of schools” design; (3) superintendents believed this “system of schools” design infrastructure directed their work toward navigating micropolitical dynamics rather than addressing systemic issues; and therefore (4) superintendents believed there was little capacity for any desired system-wide reform because of the self-reinforcing nature of this “system of schools” infrastructure. As described in our methods section above, these four findings represent the most common trends that emerged during our analysis of superintendents’ perspectives on (arch)diocesan system organizational conditions.
“A system of schools:” The decentralized organization of Catholic School systems
Contemporary educational system theories emerging in the U.S. public school context have stressed the importance of identifying the structure and organization of complex educational systems in order to make sense of the kinds of educational change capacities those systems will have (e.g., Finnigan & Daly, 2016). Informed by this perspective, we analyzed the interview data for the way superintendents described their (arch)diocesan school systems and the way the particular network arrangements across schools within the system tended to function. The interview data suggested to us that unlike the increasingly heterogeneous approaches to educational system building that have been identified in public school systems (e.g., Peurach et al., 2019), superintendents reported to us that there has been a common organizational infrastructure in most regional (arch)diocesan Catholic school systems in the U.S., the “system of schools” approach, even when there has been considerable variation in how this infrastructure has been used.
The superintendents we interviewed perceived the design of their school systems to be intentionally decentralized, maximizing the authority and responsibility of school-level leaders for site-based management with few powers reserved for central office staff. These superintendents all led centrally organized offices with structures similar to public school district models, but each of the 26 superintendents believed their (arch)diocesan systems were not intended to function systemically in the way more managerial, bureaucratic public systems have been designed. According to these superintendents, a preference for school-by-school reform was an inherent part of how the Catholic sector functions because of a systemic adherence to the principle of subsidiarity, or the notion that decisions are best made when made by the most local competent governing authority (Miller, 2007). In fact, having systems informed by the principle of subsidiarity meant superintendents expressed hesitancy toward even referring to the systems they run as “systems,” or as one superintendent remarked,Well, we've always been a system of schools rather than a school system. And we always pride ourselves on that. We do not coordinate curriculum. Even to the school calendar, we don’t have the same calendar in every place. We have a common contract. That’s another new thing we have, a teacher contract that our salaries are set from [the diocese]. [The diocese] makes the decisions on the salary increases. Yeah, I don’t necessarily feel like that’s been a good thing. Now, we’ve never been that way...I really believe as much as decisions are made at the local level, the vitality of the schools will thrive and not be imposed from [the diocese]. But I'm not saying to do that.
This common description of systems across the Catholic sector in the U.S. has led these superintendents to assume that decentralized, school-level decision-making should be prioritized over more centralized, system-wide decision-making.
Subsequently, superintendents described how they have designed their central offices to prioritize the local needs of the geographically diverse urban, rural, and suburban school communities served in various schools within their systems. Despite the shared “system of schools” approach compelling each superintendent to find ways to meet local school needs, there was no other common trend across the 26 (arch)dioceses about the design, organization, or function of their system offices, or as summarized by one superintendent, “It's not one size fits all…what we're trying to build here is a menu of options.” Some offices allowed individual schools to make independent decisions on curricular materials whereas others provided stricter guidelines of what kinds of curricular materials were acceptable; some offices allowed schools to make independent school calendar decisions whereas others mandated common calendars; some offices mandated a common salary scale, whereas others only provided loose guidelines for how much different professionals should generally be compensated. According to superintendents, intentionally decentralized system design tended to result in a lack of clarity or consistency about which organizational decisions within given (arch)dioceses would be made centrally or locally.
Similarly, we found this commitment to decentralization and maintaining a “system of schools” resulted in superintendents intentionally deferring to local decision-makers. In reflecting on why this deference to local stakeholders persisted, one superintendent commented,You get this group of people that are local people, they’re going to know who the local banker is. They’re going to know who the real estate agent is and who the president of the local hospital is. They’ll go to them for money.
According to superintendents, this commitment to decentralization across system infrastructures created a common balance of power in the Catholic sector in the U.S. empowering local school decision-makers and engendering a willingness among system-level leaders to defer to local concerns out of respect for subsidiarity.
“We try to find a balance:” The current limits on system-wide reform
Recent research into decentralized, loosely networked public and private educational systems in the U.S. has shown the capacity for these systems to create and sustain system-wide reforms (Peurach et al., 2019; Spillane et al., 2019; Yurkofsky et al., 2020). Therefore, having identified the common decentralized “system of schools” approach in regional (arch)diocesan systems in the U.S., it became necessary to understand from superintendents’ perspective whether this common system organization supported system-wide change or continuous improvement efforts. The data revealed that while all 26 superintendents we interviewed had been granted specific authorities to attempt some forms of centralized, system-wide change management, none of the superintendents felt empowered to use this system-wide authority to do anything other than maintain the preexisting (arch)diocesan organizational preferences for decentralization and local control. Rather, though many Catholic school reform advocates have encouraged the setting of intentional boundaries between local/school-level and central/system-level decision-making (FADICA, 2015, 2020), superintendents revealed that the only centralized organizational mechanisms that existed across (arch)diocesan system offices were those that emerged when local school needs exceeded local school capacity.
Partly as a function of leading (arch)diocesan central offices that had formal organizational structures, all superintendents retained some centralized organizational authority that allowed for some forms of system-level continuous improvement. These superintendents perceived an implicit mandate to implement continuous improvement policies in cases of limited school leader capacity, or as one superintendent mentioned,We [the central schools office] try to find a balance of that where there are particular things we think are really important, and we’re going to stress those, and we’re going to mandate those. There are other things where I think we can be either “It’s not the right time to be heavy-handed” or “It really can be up to the school how they look at it.”
Similarly, another superintendent talked at length about finding ways to convince other stakeholders of the efficiency of centralizing certain organizational policy areas that school leaders had not been able to individually solve, like budget and human resources management:At the end of the day, there are some times that decisions just need to be made, and that’s leadership, right? It’s absolutely ensuring that balance. Sometimes, some of the finance or HR, the protocol, so to speak, or policies are seen as top down, and I know that. And because I have such a good relationship with my schools and our principals, and they’ll be like, “Hey, wait a minute!” But then, we engage in a dialogue. It’s just I think a healthy approach.
These superintendents found they were allowed and encouraged to enact system-wide policy changes on behalf of the continuous improvement of the individual schools in their systems. Yet since these superintendents also noted that there were no formal guidelines for when they could exercise this authority, they tended only to use this policymaking authority at times when school-level leadership was incapable of ensuring school viability or when they could demonstrate that local decision-making had been insufficient.
In addition, consistent with the principle of subsidiarity being perceived by superintendents as core to their system’s identity, the superintendents we interviewed tended to only proactively enact this system-wide responsibility when such action would not threaten the pre-existing local patterns of decision-making. As mentioned at the outset of this paper, there is an emerging trend in U.S. Catholic schools research calling into question the efficiency and effectiveness of the parish-based governance model, suggesting parish-based governance is an organizational form positioned for a sector-wide overhaul. Yet our data suggest none of our participants felt empowered to abandon the parish-model of elementary school governance in their (arch)diocesan systems, or as a representative comment from another superintendent put it:We know that for the most part, depending on the leadership of the parish, the parish system is probably one of the best in terms of community building, creating a system with two lungs, the parish and school. They're supportive of each other. They're involved in each other's community lives. We know that that's a great system, but there are limitations. There are times when the leadership of the parish might not have any educational background, which is often, and maybe doesn't get some of the educational-instructional pieces. How do we take the best of the parish but still ensure that there's a baseline of operational standards and a centralized vision and curriculum and all those things moving forward? That's our goal, is to just try to balance and engage laity and engage the presbyterate and a centralized system that is challenging in creating a vision, but also supportive in getting there. That's all.
As illustrated here, what superintendents described was in essence an assumed mandate to maintain parish-based elementary school structures in their (arch)dioceses because they perceived these organizational forms as an inextricable part of Catholic education.
Therefore, rather than employ their limited but real system-wide change capacities to make system-wide changes, these superintendents used these capacities to try to enhance schools’ individual efficacy. For example, one superintendent explained that in their experience in their (arch)diocese, parish-based governance models have been made to be effective once superintendents use centralized powers in particular ways:You can use the parish model and not have the pastor be the king of the kingdom. I have found that, while pastors often invoke canon law, canon law is actually grayer than you think it is, and so much depends upon the philosophy and disposition of the local ordinary as to how canon law is defined and enacted within a particular diocese. In [our (arch)diocese], most of our schools were still parish affiliated, but we were still able to innovate and govern within that model because not every parish school looks the same.
This response highlights how the superintendents we interviewed felt empowered to pursue innovations using centralized authority when those innovations did not challenge the foundational organizational forms as understood by these superintendents.
Yet superintendents also frequently described the ways that this mandate to maintain school-by-school change management only worked when individual school leaders or parish leaders were themselves effective. As one superintendent commented, “When principals are really, really competent, independent, I'm okay with that. I think my concern is that when they're not and they're trying to be independent that's where I have, so I would like to have more control.” Most superintendents acknowledged that even when there was evidence that individual leaders were not effectively addressing organizational crises in their schools, they did not have a mandate to attempt system-wide innovative solutions that would change the intentionally decentralized balance away from school-based decision-making. They had the authority to lead for change, but only when it worked to allow individual schools to find a path towards individual success.
These findings reveal an unresolved tension between superintendents’ latent capacity for certain system-wide educational reforms and superintendents’ perception that they could not direct this capacity toward initiating systemic changes even when they thought such changes would be desirable. Even when superintendents were provided the capacity to initiate system-wide change efforts, the 26 superintendents we interviewed revealed that system-level leaders in regional (arch)diocesan systems are compelled to maintain the intentionally decentralized infrastructure of (arch)diocesan systems in the Catholic sector.
“Trying to convince them:” The system-level micropolitical negotiations of Catholic school superintendents
Some contemporary U.S. educational systems researchers have suggested that navigating/managing micropolitical dynamics is a necessary responsibility for system-level leaders to take on in order to more effectively use the authority they’ve been given to sustain system-wide change initiatives (e.g., Marsh et al., 2021). Informed by this perspective and having established how superintendents perceived the limits on their capacity to enact system-wide continuous improvement efforts, we analyzed our data to determine how Catholic school superintendents navigated the micropolitical dynamics that existed in the (arch)diocesan systems in which they worked. Our findings revealed that these 26 Catholic school superintendents devoted a considerable portion of their time to three particular micropolitical dynamics: (1) the selection and placement of priests to serve as pastors at parish-based Catholic schools; (2) the composition of decision-making bodies impacting schools at the (arch)diocesan and local levels; and (3) the choice of an (arch)bishop to make Catholic schooling one of their focal policy areas among other (arch)diocesan offices and services. However, unlike research demonstrating how navigating micropolitical dynamics has catalyzed more effective system-wide change management in certain systems, we found these Catholic system superintendents believed navigating these micropolitical dynamics reduced the time they had available to pursue system-wide school support initiatives.
Most superintendents felt compelled to focus their office’s efforts on developing high quality school-level leaders since they understood that school-level leaders would be primarily responsible for leading educational change in their systems. While some Catholic school superintendents had received the authority to oversee principal evaluation, professional development, and recruitment processes, most Catholic school principal hiring is still led by pastors who lead parish-based schools (FADICA, 2015, 2020; Goldschmidt & Walsh, 2013; NCEA, n.d.). In the absence of the ability to make direct decisions about who gets to be a leader in a parish-based school, superintendents turned to trying to influence who gets assigned to be a pastor in a given parish, or as one superintendent mentioned when reflecting on principal hiring, We’ve been trying to convince [the bishop] that you need to place a pastor in the parish who wants a school...and we’ve been trying to convince them that the principal is the educational leader. The pastor is the pastoral leader.
The authorities granted to (arch)bishops under Canon Law (the institutional governing procedures of the Roman Catholic Church) prevented superintendents from choosing pastors. Therefore, superintendents felt they had no choice but to attempt to assert influence over pastor recruitment and selection in order to have some role in the process of principal recruitment and selection. Subsequently, a considerable amount of these superintendents’ time had to be devoted to navigating the micropolitical dynamics within (arch)diocesan offices responsible for making decisions about who gets to be a pastor of a parish that contains a school.
Similarly, even in cases where pastors did not have authority over principal hiring, superintendents had to spend time navigating decisions about who would sit on the boards or committees governing those schools. Informed by the emerging consensus calling for wide-scale reforms of the parish governance model (FADICA, 2015, 2020; Smarick & Robson, 2015), many (arch)dioceses have taken steps to create advisory boards or boards of limited jurisdiction over one or multiple schools in their (arch)dioceses containing leaders with educational and financial expertise who could theoretically manage a school’s organizational decision-making more effectively than pastors without that expertise (Ozar & Weitzel-O’Neill, 2012). Yet one superintendent we interviewed noted that even in his (arch)diocese, devoted to making such system-wide organizational reforms possible, tensions existed when it came to board appointments:The way [this school’s charter] is written is a committee-based structure. The only pastoral representation would be the bishop, the vicar general as members, and then they can appoint a pastor or a priest representative to the board. The previous board, to be honest with you, there were more priests than there were lay people. I just said, ‘that’s not going to work,’ to the Bishop. If you want to really engage the laity to make decisions, you need to rethink that structure.
The superintendents we interviewed recognized that appointing people with particular organizational expertise to school boards could allow schools to be governed more effectively. But they also noted that the effectiveness of these boards was in direct relationship to whether the people deciding who gets to sit on the board share an interest in the school’s long-term continuous improvement. Just as superintendents had to spend time navigating pastor appointment to ensure parish-based schools were set up for success, (arch)diocesan micropolitical arrangements around board appointment and composition were another major area superintendents had to spend time navigating.
Finally, superintendents perceived that their success as a system leader was directly impacted by the extent to which their (arch)bishop made Catholic schooling a policy priority. The Catholic Church globally has long expressed its commitment to operating Catholic elementary and secondary schools (Whittle, 2017) and most (arch)bishops in the U.S. remain dedicated to having the Catholic schools in their (arch)diocese continue to operate (Cattaro & Cooper, 2007; Miller, 2007). Consistent with these perspectives, the superintendents we interviewed shared positive statements about the level of support they received from their (arch)bishops. But the superintendents we interviewed mentioned their roles were more challenging to navigate the lower Catholic schooling’s placement among the multiple policy areas for which their (arch)bishops were held responsible. The following superintendent’s comments about (arch)bishop investment in (arch)diocesan Catholic schools is representative of the way the superintendents we interviewed made sense of this particular micropolitical dynamic:My bishop, first of all, is a real champion of Catholic education, and really has invested a lot into it and not just financially, but has invested a lot of concern and care and commitment into Catholic education. He is also not an educator. There’s a lot that he doesn’t know, and so that leads him down a few different paths.
To a great extent, the central role of the (arch)bishop in articulating and executing policy priorities for the Catholic church in his (arch)diocese displaced a given superintendent’s ability to set organizational or educational policy goals for the school system itself. Therefore, we found that superintendents not only had to spend time finding ways to influence the micropolitical dynamics that appointed people to school leadership roles but also the dynamics that determined whether Catholic schooling would play a prominent role in a given (arch)bishop’s policy priorities.
“Just trying to keep schools open:” The insufficiency of the current model for system-wide reform
As we mentioned at the outset of this paper, many Catholic sector reform advocates have long held that system-wide reform is necessary if regional (arch)diocesan systems are going to survive in the current competitive inter-sector school choice era in the U.S. (e.g., Smarick & Robson, 2015). But as detailed in the previous three clusters of findings, superintendents across the 26 (arch)diocesan school systems we investigated revealed how common organizational infrastructures and micropolitical arrangements worked together to limit their ability as system-level leaders to initiate system-wide reform or continuous improvement. In light of the presence of public and private systems in the U.S. that are structured in a similarly decentralized way but have been able to effectively initiate and sustain system-wide continuous improvement efforts (e.g., Peurach et al., 2019), it became necessary to address how superintendents perceived the prospect for the kind of system-wide reform that Catholic sector advocates believe to be necessary but that our findings suggest have limited capacity to currently succeed. In this final findings section, we present the central division that was revealed in our data between more hopeful and less hopeful superintendent perspectives on the possibility for system-wide reform.
All superintendents agreed that (arch)diocesan organizational and micropolitical dynamics stymied system-wide school reform efforts, but some believed coalitions in favor of system-wide reform could be forged. One superintendent shared the following anecdote about an attempt at more widespread (arch)diocesan school centralization prior to his time as superintendent:I was reading an article last night and it was an old article about when [the now-closed centralized network in our diocese], when the diocese pulled back from those, and the former superintendent who has, obviously, done an amazing or had done an amazing job, her comment was, “I really think the only way for Catholic schools to survive is if they’re completely independent from a diocese without the, because so much can change when a Bishop changes.” And so anyway, I mean, I’m not there yet. I still have a lot of faith and confidence that there are a lot of people that are interested in empowering the laity to make really good decisions, and there’s really good bishops out there.
Though the conditions in this particular diocese and this particular attempt at regional centralization were unique, superintendents shared similar stories in which they believed stakeholder relationships could be forged despite the micropolitical constraints induced by some (arch)diocesan leadership structures.
For example, since there was a perception that superintendents could not enact cross-school policy until local school leaders were ready to support these changes, some superintendents described building coalitions among principals to prepare for change. When describing how they manage the expectations of principals who know that they have ultimate site-based decision-making authority but who also respond well to attempts at system-wide policy implementation, one superintendent mentioned that,I think they think it's an obligation, and, "I would not be involved in it, because all of my partner principals or colleague principals are involved, and I would look like a lost sheep not doing something." So, I think they feel there's peer pressure that we didn't necessarily create, that's created among themselves. And, people are happy when we ask them to share, "What your school is doing around that theme?"
While most superintendents did not have the authority to mandate policies they believed would benefit schools, they believed that finding ways to convince principals to collectively pursue continuous improvement in certain strategic areas would create the right conditions for organizational change. This approach is consistent with what Peurach et al. (2019) have defined as a more networked approach to system building and does not tend to necessitate centralized system authority, even though it does require a shared, system-wide mission. Our superintendent participants assumed that encouraging principals as a group to push for change would be a major lever to establish a new culture among local-level decision-makers in (arch)dioceses that were unlikely to de-emphasize the primacy of decentralized decision-making.
Similarly, some superintendents believed they could build these coalitions by appealing to a sense of shared responsibility among (arch)diocesan stakeholders. Rather than accept that a “system of schools” approach was inherent in their system’s form or function, some superintendents described how they have encouraged new or different approaches to talking about their systems, or as one superintendent expressed it:“We are a system of schools. We’re not a school system.” That was their old saw. I don’t know if people in other parts of the country like to say those things. I find myself bristling and fighting against that all the time. Not that it’s not exactly true, but I think it’s more nuanced than that, and I like the comparison of us to a cluster of islands. We look separate on the surface, but truthfully, we're all the Church of [diocese]. We're all connected by certain things way down under the surface, so I use that metaphor sometimes to say that we need to not only acknowledge and benefit from those connections, but maybe build bridges to one another to connect our islands here to strengthen the great thing that we have.
Despite the “system of schools” approach being the dominant approach, some superintendents we interviewed remained hopeful they could use their role to encourage more people in their system to abandon this common sense understanding of how (arch)diocesan systems functioned.
This hopefulness expressed by some superintendents is consistent with contemporary U.S. educational systems building theories that have suggested decentralized system designs do not inherently foreclose the possibility of system-wide reforms being initiated if the political will to create and sustain system-wide change can be fostered among key stakeholder groups (Marsh et al., 2021; Neumerski & Cohen, 2019; Yurkofsky, 2020). According to these superintendents, the possibility existed to use coalition building tactics to change the organizational infrastructure and micropolitical dynamics of (arch)dioceses as the highest leverage strategy to create system-wide sector reform.
Yet most of the 26 superintendents we interviewed believed that organizational leadership conditions across (arch)diocesan systems within the sector fundamentally limited this political will from being fostered, or as one superintendent said, “The culture of a whole diocese, and maybe the broader church, is, ‘That's not how we've done things in the past, so we don't need to do anything differently right now.’” Superintendents with this more frequently expressed pessimistic view believed the absence of the ability to foster political will for change ensured that (arch)diocesan systems would not change. And in the absence of changing organizational conditions, superintendents would go back to doing the work that they have been tasked with doing, namely keeping as many schools open as can possibly stay open with no system-wide strategy to achieve this goal, or as another superintendent reflected,Somehow I believe that if our bishops were to empower [and] affirm the superintendents more, more would be settled at that level. Just as we affirm our principals, there’s more localized decision-making because people see that level of oversight present at their school. … I think if the bishops were to really talk about what superintendents are doing, that it would empower them to not to do crazy things, because we don’t have time for crazy things. We’re just trying to keep schools open today.
None of the superintendents we interviewed believed they were powerless leaders in their (arch)diocesan systems. But most accepted that they were powerless to change ingrained organizational leadership conditions, subsequently foreclosing the opportunity to pursue system-wide reforms. There is also not yet sufficient evidence to assess whether the more optimistic superintendents we interviewed would be successful in their coalition-building strategies to see if it is in fact possible to move toward system-wide reform by generating the right political will.
Discussion
In the previous section, we showed how current Catholic school superintendents made sense of the form and function of the (arch)diocesan school systems in which they worked in order to identify what capacities, if any, existed at the system-level to support the kinds of changes for which many Catholic sector advocates have lobbied the sector to pursue. Catholic education in the U.S. remains in a period of organizational crisis in the early 2020s because long-term declines in student enrollment in Catholic elementary schools have structurally threatened the sustainability of the sector (NCEA, n.d.). While one common assumption held by Catholic education stakeholders is that this structural crisis has persisted because practitioners in the field have not been willing to innovate or experiment with new organizational forms (Smarick & Robson, 2015), change has happened in the field. Individual Catholic schools have attempted several educational changes over the course of the past 30 years, some of which have succeeded in establishing new forms of school leadership, governance, and operational management that contribute to school sustainability (e.g., Goldschmidt & Walsh, 2013; Ozar & Weitzel-O’Neill, 2012).
Yet as our findings suggest, policymakers and philanthropists invested in keeping Catholic schools opened have continued to advocate for system-level/sector-wide reform because there has continued to be a pronounced lack of system-level educational change efforts that have been pursued within or across (arch)diocesan systems. We set out in this paper to examine the experiences of Catholic school superintendents in order to make sense of the possibilities for system-level organizational change in the Catholic sector, if any, and to try to better understand what limits have been placed on these system-level educational change efforts.
In the interviews we conducted with 26 geographically representative (arch)diocesan superintendents, we found that, consistent with previous educational systems research in public and private systems in the U.S. (e.g., Marsh et al., 2021; Peurach et al., 2019), the function and form of (arch)diocesan systems mutually reinforced each other to produce certain intended outcomes. Our findings confirmed that because of the intentionally decentralized, “system of schools” design of (arch)diocesan school systems, these systems limited the possibility for centralized, system-level policymaking and prioritized local, school-level decision-making. In contrast to what Catholic sector policy stakeholders have advocated, the superintendents who participated in this study did not expect to be able to mandate system-level, sector-wide educational change initiatives because they perceived a responsibility to maintain a decentralized, “system of schools” form and function even when they had been granted some measure of centralized policymaking authority.
According to these superintendents, we should not expect Catholic systems to function like other, more centralized educational systems because Catholic school systems were not designed to be systems in the first place. Central offices, in their experience, have existed merely to step in when local decision-making fails. Yet it is notable that our findings did not reveal superintendents grappling with the possibility of system-level continuous improvement efforts that have been successful in similarly decentralized public and private school systems. Our findings suggest that leaders of Catholic systems believe decentralized “system of school” organizational designs prevent system-wide reform and proceed in their work from this central organizational premise/assumption. Rather than challenge or push back against this common sense, we found that superintendents spent more effort in status quo maintenance rather than attempting or considering a more radical reinvention of organizational forms.
In addition, we also found that the relationship between system form and function only partially accounted for the limited possibility of accomplishing system-level change efforts in the Catholic sector. Superintendents explained in these interviews that their inability to use the centralized policymaking authority they retained in many cases was as much a result of the lack of political will to pursue sector-wide, system-level change as a result of the intentionally decentralized organizational forms that prevailed in the sector. Unlike many contemporary educational change efforts in public education in the U.S. which have broadly embraced the importance of systems-thinking (e.g., Chenoweth, 2021; Daly & Finnigan, 2016), the superintendents we interviewed described a sector in which systems-thinking has either not yet been encouraged or has been firmly rejected depending on the individual conditions of the particular (arch)diocese.
The Catholic school sector in the U.S. has historically emphasized its ability to efficiently operate a large network of elementary and secondary schools and to generate positive short- and long-term educational opportunities for students in their schools, particularly low-income students and students of color (Bryk et al., 1993; Coleman et al., 1982; Freeman & Berends, 2016). While there is no definitive contemporary evidence that unequivocally supports these claims (Miller et al., 2022; Marks, 2009), Catholic school educators and advocates have continued to be motivated to sustain the operations of these schools and systems because of their commitment to this social justice tradition (FADICA, 2015, 2020; O’Keefe & Goldschmidt, 2014; Neumerski & Cohen, 2019).
What this paper has attempted to show, though, is that in order to continue operating schools consistent with that organizational identity Catholic school systems would have to develop more effective system-level infrastructure and capacity within (arch)diocesan school systems than what currently exists. Our findings ultimately suggest that the current system infrastructure of the Catholic sector, with a lack of clear roles and responsibilities for system-level superintendents and an intentionally decentralized system of schools approach to system design, is antithetical to the kinds of changes that the system currently requires despite there still being some relationship-driven opportunities for productive changes in particular (arch)diocesan contexts.
While the findings presented in this paper were not surprising in light of educational systems theories that suggest a predictable fit between the organizational form and function of educational systems, these findings were surprising in the way they revealed how Catholic system superintendents have become resigned to the organizational and political foreclosure of the possibility for the kind of change that could have transformational system-wide impact. Though these 26 superintendents provided illustrative examples of the organizational and political tensions Catholic school superintendents face, it should also be noted these findings are not exhaustive of system-level educational change perspectives across the entire Catholic sector. Yet these findings do provide additional evidence that, unlike the way Catholic schools marketed themselves as being more effective than public schools throughout the COVID pandemic (e.g., McGurn, 2021), the Catholic sector has routinely struggled as much if not more than the public sector to address core organizational infrastructure issues on its path to accomplish its stated goals. Indeed, our findings that system leaders are incentivized to maintain an organizational status quo where most schools are governed by parishes ultimately support the claims made by contemporary Catholic school reform advocates that this organizational form will remain the most vulnerable governance form in Catholic systems since new system capacities to improve or reform it seem unlikely to develop under current system conditions (e.g., FADICA, 2015, 2020; Smarick & Robson, 2015).
Future research should continue to examine not only what educational changes seem to be desired by sector advocates pursuing educational change in Catholic schooling, but also whether the organizational conditions across schools, (arch)diocesan systems, and networks will allow this sector to continue achieving these goals.
Conclusion and next steps
The superintendents we interviewed remained optimistic educational change initiatives could be designed that would solve the immediate organizational crises faced by most schools in their (arch)diocesan systems, even if those changes were not system-wide. Therefore we conclude this paper with several implications from this research that could help the field of Catholic education research, practice, and policymaking sort through these issues.
First, systems-level change research and practice in Catholic education should more intentionally embrace the systems-thinking trends that have risen in popularity in the public sector. Researchers working at the intersection of educational policy, educational leadership, and education reform have begun to categorize both the variety of educational system types that exist and the diversity of school type within distinct system infrastructure (Peurach et al., 2019). While this system-level research has attempted to find out how these diverse school and system types have functioned to achieve contemporary policy goals, such as creating more equitable effective learning environments across multiple schools, this research highlights the lack of a monolithic school or system form in the public sector (e.g., Osborn & Langhorne, 2018). There has been a contemporary trend in certain (arch)dioceses to allow private educational management organizations to run school networks of formerly parish-based elementary schools (Smarick & Robson, 2015). It has been documented that several (arch)dioceses have begun to experiment with these kinds of networks so (arch)diocesan and school-level partners can shift operational and managerial school leadership tasks to outside partners who have more capacity to effectively do this work (FADICA, 2020), a key example being the Partnership Schools in Cleveland and New York City (Porter-Magee, 2019). But other than research into the long-standing Nativity Miguel and Cristo Rey urban education secondary school networks (Miller et al., 2022), from which several of these emerging networks have taken inspiration, very little peer reviewed research has been published about the organization or effectiveness of these networks among Catholic elementary schools and their relationship to systems-level change in the sector or in the (arch)dioceses to which these networks are connected. Further research must be conducted to assess how these networked systems function and whether or not organizational change is more sustainable given the particular type of system-adjacent educational change that can be fostered in them.
The findings we have presented in this paper have also suggested that system-level leaders in the Catholic sector still tend to essentialize what constitutes a Catholic school system in the U.S. despite the emergence of these new organizational infrastructures within and across (arch)diocesan schools and systems. Therefore, our future research with school- and system-level leaders in the Catholic sector intends to better understand how these distinct organizational forms have emerged in different (arch)dioceses from the perspectives of school and systems leaders who have experience with them. In addition, we intend to examine the extent to which political and institutional conditions like those we have described in this paper have contributed to or limited the effectiveness of these new organizational forms.
The findings and analyses presented in this paper have indicated our superintendent participants believed there was little current opportunity for pursuing systems-level change within their offices as currently structured. Therefore, our future research questions must also consider what professional roles and responsibilities Catholic school superintendents and system-level leaders should have according to the perspectives of different Catholic sector stakeholders (e.g., school leaders, system leaders, and policy advocates) in light of these diverse, heterogeneous organizational forms present in contemporary U.S. Catholic school systems.
In light of the commitment the superintendents we interviewed had for preparing school leaders to work in Catholic elementary schools in their (arch)diocesan systems, research and practice related to educational change in the Catholic sector must do a better job of establishing grounded theories for what kinds of leadership are needed in certain system types. Though it goes beyond the scope of this paper, superintendents talked extensively about the need to prepare the “right” kinds of leaders. But there was no universally shared definitions of what counts as “right” across all superintendents despite the consensus among researchers in the field of Catholic education about what high quality school leadership should look like (Boyle, 2016; Ozar & Weitzel-O’Neill, 2012). If superintendents continue to focus their time and energy in finding leaders who can accept the responsibility of managing a school that is individually held accountable for its own continuous improvement with little centralized support, then a better working theory of school leadership preparation for this decentralized, “system of schools” organizational form needs to be developed in schools, (arch)diocesan systems, and in research on leading educational change in the Catholic sector.
Ultimately, our findings suggested to us that any successful educational change initiative in the Catholic sector will have to be located somewhere between the school-by-school reform strategies (that have been repeatedly attempted in the sector but have not led to sustainable sector-wide change) and system-level change efforts (which, as we have established in this paper, have little likelihood of being accomplished given the prevailing “system of schools” approach). This conclusion is consistent with contemporary educational change scholarship that has asserted the importance of designing systems that balance centralized and decentralized approaches. Yet the unexpected commitment of stakeholders in these fairly decentralized U.S. (arch)diocesan systems to organizational dynamics that exacerbate rather than alleviate their core organizational crises suggests the need for ongoing renegotiation and revision of system design even when all stakeholders assume that the “right” balance has been achieved. The system dynamics we have revealed in this paper, though, suggest that even sectors like U.S. (arch)diocesan systems that have been granted the relative autonomy to pursue system redesign at their own discretion are bound up in institutional and organizational commitments which make this kind of system redesign an unlikely endeavor.
Appendix
See Table 1Table 1 (Arch)dioceses represented in study
NCEA region Student enrollment of (Arch)dioceses represented Total number of schools in (Arch)dioceses represented Superintendents included in sample
Great Lakes 167,405 550 7 (6 male, 1 female)
Mideast 166,198 508 6 (5 male, 1 female)
New England 26,100 113 3 (3 male, 0 female)
Plains 46,692 167 2 (1 male, 1 female)
Southeast 33,985 106 3 (1 male, 2 female)
West/Far West 52,204 169 5 (2 male, 3 female)
Total 492,584 1613 26 (17 male, 9 female)
Declarations
Conflict of interest
We have no known conflict of interest to disclose.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9747533 | NO-CC CODE | 2022-12-15 23:22:01 | no | J Educ Change. 2022 Dec 14;:1-28 | utf-8 | null | null | null | oa_other |
==== Front
J Bus Psychol
J Bus Psychol
Journal of Business and Psychology
0889-3268
1573-353X
Springer US New York
9865
10.1007/s10869-022-09865-5
Original Paper
Stratification or Polarization: a Qualitative Study of the Formation of Status-Based Subgroups in China
http://orcid.org/0000-0002-2551-2569
Zhang Yue 1
Liang Qiaozhuan [email protected]
2
Deng Wei 3
1 grid.440588.5 0000 0001 0307 1240 School of Public Policy and Administration, Northwestern Polytechnical University, Xi’an, 710018 China
2 grid.43169.39 0000 0001 0599 1243 School of Management, Xi’an Jiaotong University, Xi’an, 710018 China
3 grid.440588.5 0000 0001 0307 1240 School of Management, Northwestern Polytechnical University, Xi’an, 710018 China
14 12 2022
128
23 11 2022
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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.
Researchers continue to debate about how high-status and low-status members will divide into subgroups. The purpose of this research is to enrich the faultline, subgroup, and status literature by specifying how and why status-based subgroups (i.e., subgroups based on status positions) are formed within a team. This research employed a grounded theory approach and conducted interviews with 111 individuals distributed over 21 work teams in Chinese highly competitive industries. The results identify two typical formation patterns of the status-based subgroup: vertical stratification that indicates team members vertically split into different subgroups along status hierarchies, and horizontal polarization that indicates team members at the same status horizontally divided into different subgroups. Furthermore, the results distinguish different sources for the formation of stratified and polarized status-based subgroups. This study expands faultline and subgroup literature by identifying multiple formation patterns and sources of status-based subgroup, and contributes to status literature by clarifying how high-status and low-status members will bound together or split within a work team.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10869-022-09865-5.
Keywords
Status-based subgroup
Subgroup formation patterns
Subgroup formation sources
Grounded theory approach
http://dx.doi.org/10.13039/501100001809 National Natural Science Foundation of China 72202177 72202179 72201207 Zhang Yue Deng Wei Social Science Foundation of Shaanxi ProvinceD5170210088 Zhang Yue http://dx.doi.org/10.13039/501100012226 Fundamental Research Funds for the Central Universities D5000210968 Zhang Yue Soft Science Research Program in Shaanxi Province2022KRM003 Zhang Yue
==== Body
pmcIntroduction
“Birds of a feather flock together.” (Interview #T7Sup1).
“People in the workplace must follow the law of the jungle, and two tigers cannot live on the same mountain.” (Interview # T137Sup1).
Status hierarchy is an inevitable and ubiquitous aspect of group life (Berger et al., 1980; Bunderson et al., 2016; Ridgeway, 1997). Status position confers symbolic and material resources provided by the organization, such as pay, perquisites, prestige (Galperin et al., 2011), formal power (Aquino et al., 1999), authority, and autonomy (Aquino & Douglas, 2003). In this sense, status hierarchy can facilitate unequal distribution of resources within a team by concentrating necessities in the hands of only a few high-status members (e.g., group leaders). Most low-status members do not have the authority to take the resources they desire alone (e.g., subordinates) (Sidanius & Pratto, 1993). Given the status hierarchy and the unequal distribution of limited resources within a team, team members will find it more difficult to focus on mutual gains. Instead, high-status members are likely to expect to exert their resource dominance, while low-status members will focus on protecting their interests. To achieve their personal goals, it is possible for both high-status and low-status members to find collaborators and form subgroups within the team. Because by forming small subgroups, more resources can be acquired at a lower cost than those obtained by individuals (Olson, 2009). Mannix (1993) also stressed that unequal status balanced groups were more likely to form coalitions and distribute the resource pool to subgroup members. However, there remains considerable debate about how team members form status-based subgroup (i.e., subgroups based on status)? Do they develop subgroups with members at a similar status level? Or do they choose to build subgroups across different status levels?
To date, scholars in faultline and subgroup research adopted the social dominance perspective and largely agreed that status-based subgroups were likely to be formed by being vertically differentiated along status hierarchies (e.g., Carton and Cummings, 2012; Ren et al., 2015; Van der Kamp et al., 2012). In contrast, inspired by competition exclusion perspective (Abramsky & Sellah, 1982), another stream of literature questioned the one-side view (e.g., Bunderson et al., 2016; Chattopadhyay et al., 2010; Groysberg et al., 2011; Jehn & Bezrukova, 2010) and showed a high probability that status-based subgroup may be formed in another way (i.e., horizontal polarization).
Motivated by inconsistent views, this research intended to provide a more complete picture of how high-status and low-status team members would separate into status-based subgroups, and why they choose different strategies when develop status-based subgroups. First, we distinguished between two types of status-based subgroup according to their interaction patterns: stratification (i.e., team members at different status levels vertically split into different subgroups, whereas team members at a similar status level horizontally join in the same subgroup) and polarization (i.e., team members at a similar status level horizontally split into different subgroups, whereas team members at different status levels vertically join in the same subgroup). By developing a typology framework of the status-based subgroup, this research will enrich the subgroup formation patterns that are discussed in team faultlines and subgroup literature. Second, this research distinguished the sources of creating different types of status-based subgroup. Thus, it contributes to status literature by deepening our understanding of the motivators of interactions among members at similar or dissimilar statuses.
Theoretical Grounding
Status-Based Subgroup Formation in Social Dominance Perspective
A long tradition of research in subgroup literature have suggested (Carton & Cummings, 2012) subgroups arise from faultlines (i.e., hypothetical dividing lines that may split a team into homogeneous subgroups based on one or more attributes, Lau & Murnighan, 1998). That is, individuals perceive other members as belonging to their own subgroup if they share similar attributes (i.e., on the same side of the faultline), and dissimilar individuals will be divided into different subgroups (i.e., on different sides of the faultline). Accordingly, scholars in subgroup research largely agree that status-based subgroups would be formed in a single way: distinct status-based subgroups are differentiated along hierarchies according to differences in status levels (i.e., hierarchical stratification) (e.g., Carton and Cummings, 2012; Ren et al., 2015; Van der Kamp et al., 2012). This stream of research was congruent with research in status differentiation and stratification, building on social dominance theory (Levin et al., 2002; Sidanius & Pratto, 1999), and clearly announced a typical way of subgroup formation: hierarchical stratification. For example, Ames and Flynn (2007) found that, when threatened by low-status subordinates, high-status leaders were likely to take aggressive, defensive, or non-constructive actions to resist low-status members and to maintain their dominance. Mannix (1993) and Levine and Moreland (1998) confirmed that high-status members usually form coalitions to extend their competitive advantage in resources. They only bring resources to a subset of group members in their own collation while depriving others of a lower status. Similarly, van Dijk and van Engen (2013) suggested that high-status members may opt to suppress low-status members by withholding information and resources, thereby continue maintaining their high status. Given a hierarchical stratification of status, low-status team members also have the intention to form a subgroup and compete with those occupying high-status positions. For example, Antino et al. (2019) suggested that perceived status threats prompt high-status and low-status subgroups to manipulate the social construction of status relationships, which in turn exacerbates status conflicts between high-status and low-status members. Aquino and Douglas (2003) demonstrated that people at the bottom of the hierarchy often respond competitively to high-status people that threaten to undermine their already precarious social positions. Therefore, the subgroup literature has clearly announced that status-based subgroups are formed in the typical way of hierarchical stratification. However, are status-based subgroups only formed in this single way?
Status-Based Subgroup Formation and Competition Exclusion Perspective
Another stream of research focusing on the dyadic interaction among members at similar or dissimilar statuses may indicate another possible way of status-based subgroup formation. For example, according to ecological niche and competition exclusion theory (Abramsky & Sellah, 1982), an ecological niche characterizes the position of a species within an ecosystem. Species on the same ecological niche have similar habitat requirements and play a similar functional role in an ecosystem, thus resulting in strong competition between these species. Inspired by this perspective, some scholars noticed that team members at an equal status position occupy the same organizational niche, and they examined the competition and split between high-status members. For example, Jehn and Bezrukova (2010), Groysberg et al. (2011), Chattopadhyay et al. (2010), and Bunderson et al. (2016) have demonstrated that a group with multiple high-status members would experience polarization over leadership and inevitable competition or confrontation. Indeed, Overbeck et al. (2005) explained that high-status individuals may have difficulties in cooperation because they are competing for scarce resources. Meanwhile, drawing on theory related to dominance complementarity (Tiedens & Fragale, 2003), high-status are likely to choose to make alliances with low-status members to gain more support in the competition.
In sum, there are two underexplored yet highly important questions about status-based subgroup formation: Are there multiple types of status-based subgroups, and what are the interaction patterns of these types of status-based subgroups? Previous subgroup literature that drawn on social dominance perspective has clearly announced a typical way of subgroup formation: team members at a similar status level join in the same subgroup, while team members at different status levels split into different subgroups. In contrast, inspired by competition exclusion perspective, another stream of research showed a high probability that team members at a similar status would experience a horizontal split, while team members at different status levels join together. Although this stream of research did not directly focus on the status-based subgroup formation, it questioned the findings in subgroup literature and enlightened researchers to consider multiple ways of status-based subgroup formation. However, existing literature has offered far less attention to these competing perspectives and has not tried to distinguish between them under an integrated framework.
Why are status-based subgroups formed in different patterns? Previous research has pointed out that status-based subgroups are likely to exist when a clear hierarchy of subgroups is already in place and also when the team is experiencing resource scarcity (Carton & Cummings, 2012). These sources apply to status-based subgroups that formed based on both social dominance perspective (Dijk & van Engen, 2013; Levine & Moreland, 1998; Mannix, 1993) and competition exclusion perspective (Overbeck et al., 2005). However, these sources cannot fully explain why status-based subgroups are formed in different ways. Therefore, important implications are likely to arise from distinguishing the differences between the sources of different types of status-based subgroups.
This omission might be particularly problematic in organizations with obvious status hierarchies and teams containing multiple high-status members. In these environments, status-based subgroup formation can be pervasive (Carton & Cummings, 2012). Without defining and distinguishing between different types of status-subgroup formation, the status-based interaction will remain somewhat ambiguous. Consequently, we cannot provide appropriate implications to manage status-based subgroup formation. Thus, we hope to address this gap. We employed the grounded-theory approach to develop a typology framework of the status-based subgroup. In this framework, we sufficiently depict the multiple formation patterns of different types of status-based subgroups and uncovered why team members form status-based subgroups in different ways. We hope to open new research avenues by suggesting that future scholarship consider diversified ways of status-based subgroup formation.
Methodology
Research Design
In this study, we employed the grounded-theory approach to develop an integrated framework about how and why different types of status-based subgroups are formed, for two reasons. First, existing subgroup literature has largely agreed that status-based subgroups are formed in a single way: hierarchical stratification. But literature that drawn on competition exclusion perspective has inspired us that status-based subgroups were likely to be formed in another way. Given the lack of research detecting and comparing multiple formation patterns of the status-based subgroup, and limited literature exploring the sources of status-based subgroup formation, we used the grounded-theory to elaborate existing subgroup theory (Edmondson & McManus, 2007) by exploring the question of (1) are there multiple types of status-based subgroups, and what are the interaction patterns of these types of status-based subgroups? and (2) why are status-based subgroups formed in different ways? Second, the grounded-theory approach aligned well with our interpretive approach because we are particularly interested in comprehending perceived subgroup formation within a team as experienced by team members from their own perspective, and its purpose is to produce theories and opinions on how people subjectively explain reality (Glaser et al., 1968). To observe the formation patterns and sources of status-based subgroups, we conducted an inductive qualitative study by using the grounded-theory approach.
Interview and Sampling Technique
We conducted semi-structured in-depth interviews because they effectively uncovered people’s perceptions of the formation of status-based subgroups. Interviews were carried out in a specific order. The first phase was the individual interviews with particular team members. We designed the phase 1 interviews to explore individuals’ experiences of the status-subgroup formation, addressing our first research question: “Are there multiple types of status-based subgroups, and what are the interaction patterns of these types of status-based subgroups?” and the second question: “Why do individuals choose to develop status-based subgroup in different ways?” Individual participants in this phase discussed whether they experience status-based subgroup formation in their work teams and what the interaction features of these status-based subgroups are, and generally provided their personal reasons for forming status-based subgroups. The insight from phase 1 led us to design the second phase team interviews to validate the specific types of status-based subgroups in phase 1 and to further explore the team-level sources of status-based subgroup formation. Thus, in the second phase of interviews, we concentrated on addressing the research question: “Why do teams divide into status-based subgroups in different patterns?”.
At this phase, we identified individual participants via a resume database search with the help of a headhunting company. We asked a manager of the headhunting company to conduct a random sample selection from company’s resume inventory. Random sampling contributes to reduce bias in the selecting process and examine the views of different interviewees which helps to establish “ecological validity” (Lee, 1999: 152). The manager of the headhunting company selected and invited 80 people to take part in the research about status-based subgroup formation, 56 of whom allowed us to contact them. I started by briefly introducing the purpose of this study and asking interviewees whether they are willing to increase our understanding of what types of status-based subgroups exist in work teams and why these types of status-based subgroups are formed. Finally, 32 participants from 23 teams agreed to be deeply interviewed. After collecting and developing the interview material, we identified two typical types of status-based subgroups (stratified status-based subgroups or polarized status-based subgroups), and observed important premises for the formation of status-based subgroups. These findings constituted the foundation and a direction to proceed with the phase 2 team interviews.
We used responses from phase 1 to design the sampling approach for phase 2 team interviews by evaluating when status-based subgroups were most likely to occur. For example, the phase 1 data analysis suggested that status-based subgroups were more likely to be formed when team members had to compete for finite resources. Thus, we included teams that satisfied the following requirements: (1) we sampled work teams from small-sized enterprises (less than 300 employees) in highly competitive industries, because small-sized enterprises in highly competitive industries are subject to more severe resource constraints in the current environment and do not have easy access to external resources. (2) We sampled traditional work teams with relatively low skill differentiation and faced highly competitive and interdependent tasks (e.g., marketing, R&D, and project department), because when team members hold similar skill and function, they are likely to compete for a similar type of finite resource. Moreover, the data analysis of phase 1 interview suggests that status-based subgroups are more likely to be formed when a clear hierarchy of formal status is already in place and when there are multiple leaders in the team. Therefore, (3) we sampled traditional work teams that already had a clear hierarchy of formal positions (or authority) and included more than two superiors in higher formal hierarchical positions. The formal hierarchical position is a typical indicator of status in the organizational behavior literature (Aquino et al., 1999; Galperin et al., 2011). Because when an individual is assigned a formal position in a team, her/his rights and privileges change with a higher position, and she/he may enjoy access to more rewards and more recognition (Shelly & Webster, 1997). (4) We sampled ongoing teams with relatively high temporal stability (more than 1 year, Hollenbeck et al., 2012), because team members need enough time to interact and know each other and then they may choose to form status-based subgroup based on shared experiences.
It is important to note that, in phase 1, most individual interviewees reported the formation of stratified status-based subgroups or polarized status-based subgroups within their teams and these teams meet the above criteria. Therefore, we traced the teams which these individual interviewees were from, and tried to include all team members in these teams in the phase 2 team interviews. Eighteen teams involved in phase 1 interviews were selected for the phase 2 interviews (3 teams were excluded because of not fitting our research interest, 2 teams were excluded because of failing to trace back the team sample). To enrich our sample, we added another 3 teams in phase 2 team interviews. Finally, there are 111 participants (36 team leaders and 75 employees) distributed over 21 teams attending the phase 2 team interviews. The average team member participation rate was 82.2% (111/135). The average team size was 6.43 (the average number of high-status members was 2.14, and the average number of low-status members was 4.29). These team samples are from various industries (e.g., new energy, financial services, and IT service) and consist of various departments (e.g., R&D, marketing, and project department) facing high competition pressure. According to Hollenbeck’s team typology (2012), these team samples can be described as ranking relatively low in skill differentiation, but ranking relatively high in authority differentiation and temporal stability. A total of 3806 min was devoted to interviews. With the two phases of interviews, the research portrayed a more accurate and valid picture of the formation of status-based subgroups within teams.
All interviewees spoke in Chinese. The semi-structured interviews contained several major sections: (1) general background information on the individual and a description of the work and the composition of their departments; (2) attitudes about the status arrangement in their organizations (e.g., the stability, legitimacy, and permeability of status); (3) whether they perceive status-based subgroup formations in their departments; (4) how subgroups are formed based on hierarchical status; (5) how team members interact within and between status-based subgroups; and (6) the sources of the status-based subgroup formations. Interviews ranged from 30 min to 1.5 h. The majority of interviews (41, 36.93%) were conducted face-to-face at the interviewee’ places of operation in 2020–2022. Taking into account of COVID-19 epidemic prevention and geographical distance, we conducted 70 interviews online by using Wechat social media. The online interviews were tape-recorded and transcribed (Table 1).Table 1 Descriptive data of focus team
Focus team Industry Department Team members that participated in interviews Interview time (min) Status-based subgroup type
Team 1 Medical treatment Surgeon 2 superiors and 5 subordinates (7/7)1 207 Stratified
Team 2 New energy Operations and supply chain 2 superiors and 4 subordinates (6/6) 211 Polarized
Team 3 New energy Marketing 1 superior and 3 subordinates (4/6) 123 Polarized
Team 4 Environment protection Technical inspection 1 superior and 2 subordinates (3/5) 91 Polarized
Team 5 Dyeing Operations and supply chain 3 superiors and 5 subordinates (8/8) 248 Stratified
Team 6 Shipborne service Marketing 1 superior and 3 subordinates (4/5) 147 Polarized
Team 7 Cotton spinning Marketing 2 superiors and 4 subordinates (6/6) 184 Stratified
Team 8 Financial services Project 1 superior and 3 subordinates (4/7) 148 Polarized
Team 9 Energy Operations and supply chain 2 superiors and 3 subordinates (5/5) 182 Stratified
Team 10 Pharmaceuticals R&D 2 superiors and 2 subordinates (4/4) 133 Stratified
Team 11 Insurance Marketing 1 superior and 4 subordinates (5/6) 203 Polarized
Team 12 IT service R&D 2 superiors and 5 subordinates (7/7) 254 Stratified
Team 13 Appliance Marketing 3 superiors and 3 subordinates (6/7) 155 Polarized
Team 14 Media Project 1 superior and 3 subordinates (4/5) 157 Stratified
Team 15 Consulting Consultant 1 superior and 3 subordinates (4/6) 179 Polarized
Team 16 Tobacco Marketing 2 superiors and 4 subordinates (6/6) 192 Polarized
Team 17 Tobacco Production 2 superiors and 5 subordinates (7/7) 231 Stratified
Team 18 Real estate Marketing 2 superiors and 3 subordinates (5/8) 143 Stratified
Team 19 Real estate Investment 2 superiors and 5 subordinates (7/11) 277 Stratified
Team 20 Construction Marketing 1 superior and 3 subordinates (4/6) 188 Polarized
Team 21 Construction Project management 2 superior and 3 subordinates (5/7) 153 Stratified
1the numbers in parentheses refer to (number of interviewed members/number of all team members)
Data Analysis
Procedure
I followed the procedure for developing grounded theory (Glaser et al., 1968; Strauss & Corbin, 1998). Our data analysis proceeded in three phases: (1) first-order, informant-centric codes which adopt the open coding approach, included selection, categorization, and marking direct statements; (2) second-order codes assemble the first-order codes into more theoretical perceptions, (3) theoretical codes which involved further condensing the second-order codes into more universal theories and concepts.
Rigor
We conducted weekly meetings with the research team. The first author developed a preliminary coding system based on 32 interviews in phase 1 interview. After the phase 2 interview, the research team discussed the emerging codes extensively and refined the coding system. The first and third authors conducted the coding separately according to the refined coding system. The initial agreement between the coders was 89.2%, with differences occurring at category margins. We further discussed these differences to reach a coding agreement. We pursued credibility by adherence to grounded theory processes and procedures and created a trail by keeping all data and a detailed description of the research process.
Within-Team Agreement and Reliability
Since the phase 2 team interviews covered each team member, we drew conclusions relying on the assumption that team members’ descriptions reflect a shared perception of status-based subgroup formation. To verify the within-team agreement and reliability of status-based subgroup types in each team, we developed a simple questionnaire based on the phase 1 interview and assessed the average interrater agreement coefficients (rwg, ICC 1, and ICC 2). We asked all interviewed team members involved in the phase 2 interview to rate the extent to which they feel the team fits the description of the stratified and polarized status-based subgroup. For example, “There is a clear hierarchy within the team, separating the team into low-status and high-status subgroups. (Items for stratified status-based subgroup formation)”; and “The team has been divided into several subgroups leading by different high-status members (e.g., a manager and a deputy manager). (Items for polarized status-based subgroup formation).” The mean values of rwg were 0.83 for stratified status-based subgroup formation and 0.84 for polarized status-based subgroup formation, which indicate a high level of agreement within the team. ICC 1 was 0.21 for stratified status-based subgroup formation and 0.24 for polarized status-based subgroup formation, and ICC 2 was 0.70 for stratified status-based subgroup formation and 0.73 for polarized status-based subgroup formation, which suggest that a significant part of the variance was due to team membership. All these coefficients verified the within-team agreement and reliability of status-based subgroup types.
Step 1: Open Coding of Segments (First-Order Coding)
We initiated first-order coding through focusing on interviewing records and ascertaining words, lines, or paragraphs reflecting how interviewees perceived the formation of status-based subgroups. When the codes appeared, we compared text units and started classifying and labeling similar groups of text (Glaser et al., 1968). The initial codes contained a series of themes, including the interaction patterns between high-status and low-status members, the orientations in forming status-based subgroups, and so forth (see the second column in Table 2). As we used constant comparative methods (Glaser, 1978), we identified concepts that repeatedly emerged in our data or developed a new code if it was distinct in analysis. As the last step, we labeled the first-order codes to provide data-based perspectives, which would eventually turn into our second-order themes (Strauss & Corbin, 1998). In this way, our first-order codes integrate both the original data and our preliminary explanation of the data. Through this process, we developed 54 first-order codes.
Step 2: Axial Coding into Higher-Order Themes (Second-Order Coding)
The second-order codes synthesizing first-order segments and clustered them into more general themes to develop, correlate, and segregate categories. Again, we used the method of continuous comparison, condensing 54 first-order codes into 20 s-order themes (the third column in Table 2). Sixteen of these themes pertained to the sources for forming status-based subgroups, and four of these themes pertained to the interaction patterns when forming status-based subgroups.
Step 3: Identifying Overarching Types of Status-Based Subgroups (Theoretical Coding)
In the final stage, we conducted theoretical coding (Glaser, 1978: 72), abstracting the second-order themes into higher-order theoretical themes (Glaser et al., 1968). The earlier phase of our analysis consisted of searching for common properties across second-order codes, deconstructing second-order codes into the formation patterns and formation sources of status-based subgroups, and mapping sequential relationships among them. Finally, we transformed the second-order codes into two types of status-based subgroups: stratified status-based subgroup and polarized status-based subgroup, thus converting the previously stationary and independent dimensions into a comprehensive grounded theory model. The Appendix presents the data structure.
Findings
In this section, we build a typology framework of status-based subgroups. This framework answers two questions: (1) are there multiple types of status-based subgroups, and what are the interaction patterns of these types of status-based subgroups? (2) Why are status-based subgroup formed in different ways? More specifically, we are interested in why do individuals choose to develop status-based subgroup in different ways (i.e., individual-level sources)? And why do teams divide into status-based subgroups in different patterns (i.e., team-level sources)? To answer these questions, first, we identified two types of status-based subgroup (stratified and polarized status-based subgroup) that emerged through the analysis; this typology helps build the infrastructure of the following analysis and helps explain differences in the formation patterns of status-based subgroups. Then, we specify the individual-level and the team-level sources of each type of status-based subgroup formation. These sources describe why team members employ different tactics when forming status-based subgroups (see Fig. 1). Fig. 1 The roadmap of findings
Typology of the Status-Based Subgroup: Stratified and Polarized Status-Based Subgroup
As we analyzed our data, we recognized that status-based subgroups could be developed in two different ways. Figure 2 illustrates how two different types of status-based subgroups emerged from our data. Fig. 2 The typology framework of status-based subgroup
Stratified Status-Based Subgroup
Our analysis revealed that team members are likely to adopt a tactic of splitting up vertically (i.e., team members at different status levels split into different subgroups) and joining up horizontally (i.e., team members at a similar status level join in the same subgroup) to form status-based subgroups within a team, which we call the stratified status-based subgroup. An example is shown in the left side of Fig. 3, in a simulated team with six members, high-status members A and B united to form a subgroup, while low-status members C, D, E, and F join up to form another subgroup. In this case, members in the same subgroup share a similar status level, while distinct subgroups are differentiated along hierarchies according to differences in status, creating a disparity in status levels across subgroups. Fig. 3 Comparation between the configurations of stratified status-based subgroup and polarized status-based subgroup
The stratified status-based subgroups were often interpreted by the interviews as “interest blocs” (#T5Sup1), “class rivalries” (#T7Sup1), “alliances” (#T10Sup1), and “coalitions” (#T12Sub3). One superior of a marketing department described the high-status subgroup forms based on the horizontal cooperation among superiors, said, “A few VPs and I (i.e., a supervisor) are the backbones of the whole department. We trusted and supported each other, and controlled the core business channels of the department.” Moreover, the high-status subgroup is found to dominate and suppress the low-status subgroups by controlling over the key resources, leading to a clear hierarchy of subgroups in a team. The team superior added, “We prevent the subordinates from having access to these relationships and channels, and they just need to deal with some basic work” (#T7Sup1). An employee in this team confirmed that “The superior leaders developed a solid coalition. It’s hard for our people at grass-roots to get into the coalition, and the only way to keep competitive is to cooperate with my co-workers.” (#T7Sub4). In this team, the formation pattern of status-based subgroup manifests as that the superiors and the subordinates are vertically divided into different subgroups according to differences in status (see the left part of Fig. 3). When such hierarchical stratification subgroups are formed, teams are centralized around dominant subgroups (consisting of high-status members) that have a concentration of resources. We use the term “stratified” to describe the status-based subgroup with high intragroup status similarity and high intergroup status differences. Proposition 1a: Stratified status-based subgroups are formed by vertical splitting between members at different status levels and horizontal uniting between members at a similar status level.
Polarized Status-Based Subgroup
In contrast to the stratified status-based subgroup described above, many samples show another common tacit for forming the status-based subgroup. Some team members will take the tactic of splitting up horizontally (i.e., team members at a similar status level split into different subgroups) and joining up vertically (i.e., team members at different status levels join in the same subgroup) to form status-based subgroups, which we call the polarized status-based subgroup. For example, as shown in the right side of Fig. 3, in a simulated team with six members, the high-status member A joins up with two low-status members C and D to form a subgroup; similarly, another high-status member B joins up with two low-status members E and F to form another subgroup. In this case, all team members are divided into two different subgroups around the two high-status members A and B (acting as the pole of each subgroup).
The interviews often interpreted the polarized status-based subgroups as “taking sides” (#T3Sub1), “opposing camps” (#T6Sup1), and “factions” (#T20Sub1). A typical interaction pattern of polarized status-based subgroups is that team members at similar position levels are divided into opposing subgroups. For example, a team leader said, “We (i.e., the two superiors) lead different subgroups in the department. The subgroup that takes on bigger projects will have a bigger voice. Market competition is just like jungle survival, where the legitimacy belongs to the victor, while losers are always in the wrong” (#T20Sup1). Meanwhile, another notable interaction pattern of polarized status-based subgroups is that intra-subgroup linkages are likely to be built across people at different status. One employee provided a typical example, “Some newcomers are labeled as ‘a leader's follower’ as soon as they join the team because a man cannot serve two masters. In our department, Nie and I follow Mr. Yang (i.e., the director of the department) whereas the others follow Mr. Sun (i.e., the vice director of the department).” He added, “The two bosses often set themselves against each other…If we want to get a foothold in our department, we have to find a capable backer. Mr. Yang will give priority to us when providing training opportunities, and we will give him some inside information during private dinners” (#T15Sup3). In these cases, the status-based subgroup formation pattern involves a “tiger fighting” (#T16Sub3) between two leaders in the department, and subordinates “taking sides” (#T4Sub2) with one of the leaders. Team members are polarized around a few high-status members (acting as the pole of a subgroup) and divide into subgroups with equal power. Therefore, we use the term “polarized” to describe such kind of status-based subgroup.Proposition 1b: Polarized status-based subgroups are formed by horizontal splitting between members at a similar status level and vertical uniting between members at different status levels.
The Relationship Between Stratified and Polarized Status-Based Subgroups
In the static perspective, the existences of stratified and polarized status-based subgroups are almost mutually exclusive, which means that it is unlikely for them to coexist within a team. Figure 4 illustrates the distribution of interview cases focusing on stratified and polarized status-based subgroups. The top-left matrix in Fig. 4 contains eleven interviewed teams (e.g., teams 1, 5, 7, 9, 10, 12, 14, 17, 18, 19, 21) only representing the formation of the stratified status-based subgroups (i.e., subgroups are formed by splitting up horizontally and joining up vertically). The bottom-right matrix in Fig. 4 contains another ten interviewed teams (e.g., teams 2, 3, 4, 6, 8, 11, 13, 15, 16, 20) only describing the formation of the polarized status-based subgroups (i.e., subgroups are formed by splitting up horizontally and joining up vertically). This distribution indicates that a work team experiencing status-based subgroup formation is divided into status-based subgroups either in the form of stratification or in the form of polarization. Stratified and polarized status-based subgroups are unlikely to coexist within a team at the same time.1Fig. 4 Sample distribution
Although our analysis revealed that stratified and polarized status-based subgroups are not likely to coexist at the same time, it is interesting that some interviewees mentioned that these two types of status-based subgroups may transform into each other in the long run. For example, the formation of stratified status-based subgroups is not stable, as one supervisor said, “Everyone knows that we are using each other for utilitarian purposes, but when our goals and interests diverge, the alliance may not last forever” (#T10Sup2). A supervisor experiencing the formation of polarized status-based subgroups talked about the possibility of mutual transformation between stratified and polarized status-based subgroups, “Indeed, the current competition and separation between Mr. Li and me will not seriously damage our relationship. We will not fall out in resource competition. There is an old saying that goes ‘After a long period of division, there will always be a union.’ Therefore, I can't rule out the possibility of our cooperation in the future” (#T13Sup2).
The Sources of the Status-Based Subgroup Formation
The Individual Level Source: Individual’s Orientations About Resource
Our research suggests that the formation of stratified status-based subgroups is primarily motivated by the orientation of maintaining the existing resources within the subgroup. High-status members guard against challenges from low-status members by controlling existing access to core resources, while low-status members strive to prevent their resources from being further deprived by high-status members. For example, when being asked about why the supervisors form status-based subgroups with people at equally high status, one manager explained, “We can’t sit in a superior position without holding core resources in our hands. So, this exclusion of low-status members is also the last resort” (#T9Sup1). Indeed, the “strong alliances” (#T10Sup1) among high-status members help them control core resources and maintain advantages. To deal with this situation, grass roots employees have to form low-status subgroups, and one employee explained, “We are allying to face the same enemy (i.e., high-status members). This is an efficient way not to be marginalized and to prevent those senior staffs from stealing our core technology” (#T12Sub2). These cases show that when low-status members aim at defending themselves from further resource deprivation, they tend to “group together for warmth” (#T7Sub1) by developing a low-status subgroup. Proposition 2a: The formation of stratified status-based subgroups is motivated by individual’s resource-maintenance orientation.
According to our results, the formation of polarized status-based subgroups is primarily oriented with seeking more resources. Aiming at gaining more resources and competitive advantage, high-status members are likely to take the initiative to form subgroups and win the support from their subordinates. As one team leader stated that, “People in the workplace must follow the law of the jungle, and two tigers cannot live on the same mountain. Equally high-status members may compete with each other for positions of leadership or material benefits…I have to show my influence by winning more support from my subordinates. The alliance across hierarchies can help me gain competitiveness” (#T13Sup1). Another team leader confirmed that, “We (i.e., the manager and the deputy manager of the department) are both ambitious people, and we are not content with the status quo. Thus, we compete in seeking more talents and more material support by forming cliques” (#T13Sup2). For low-status members, their resource-seeking orientation will boost their upward mobility and encourage them to cling to those at higher status positions, because high-status members are able to open doors and bring immediate resource benefits for them. As an employee in a Tobacco company described, “As a newcomer here, I lack the internal resources, such as technical support and critical information…Actually, we (i.e., the low-status employees) are competitors on certain aspects, thus my peers are unlikely to share their resources with me… Guo (i.e., the director of the department) extended the olive branch to me, so I joined his camp without a second thought. With his support, I can get access to key resources that I cannot get by myself” (T16Sub6). These cases indicate that when most team members are oriented with resource-seeking, multiple individual resource seekers at a similar status will be involved in aggressive zero-sum contests (Bendersky & Hays, 2012), leading to horizontal splitting within the same status group. Meanwhile, the resource-seeking orientation will give rise to the vertical cooperation between high-status and low-status members.Proposition 2b: The formation of polarized status-based subgroups is motivated by individual’s resource-seeking orientation.
The First Team Level Source: Distribution of Team Members’ Characteristics
In the following part, we will look into how the joint distribution of team members’ status and objectives/resource types will shape the formation patterns of status-based subgroups (see Fig. 5). Fig. 5 The distribution of team member’s characteristics and the formation of status-based subgroups
The Joint Distribution Between Status and Objective
Our results revealed that a team is likely to be divided into stratified status-based subgroups when members at different status levels have opposing objectives (i.e., vertical dissimilarity) while members at a similar status level have consistent objectives (i.e., horizontal similarity) (see Fig. 5a). These two features often emerge together in interviews describing the formation of stratified status-based subgroups, as one employee explained, “The deviations of objectives separate us (i.e., subordinates) from the superiors. We seek more deviations and possibilities, and they seek to maintain the status quo” (#T14Sub2). This description shows the separation of objectives between people at different status levels. A senior staff provided more details, “When it comes to the change on the assessment system, our leaders will not back down, because once the rules are changed, we will lose altogether. I know that the demands and ideas of the subordinates are opposed to ours, but we will not let their plans for change succeed…Birds of a feather flock together. In most cases, people on the same hierarchical status levels enjoy the same benefits in the system, share similar goals, and can exchange equal resources, which is the essential reason for status differentiation” (#T7Sup1). This evidence confirmed that team members at equal status are more likely to generate common objectives related to systematic changes. Chung and his colleagues (2000) argue that individuals tend to cooperate to gain mutual benefits when sharing equal status and consistent goals. However, high- and low-status team members tend to generate opposite objectives because of their misaligned interests. In this case, to maintain the dominance, the high-status group will align to suppress the low-status group (Galperin et al., 2011). Therefore, the opposition of objectives among members at different status levels and the consistency of objectives among members at a similar status level (an aligned distribution between status and objective) combined to breed stratified status-based subgroups.Proposition 3a: When the distributions of status levels and objectives are aligned among team members (i.e., members at different status levels have opposing objectives while members at a similar status level have consistent objectives), a team is likely to be divided into several stratified status-based subgroups.
Our results revealed that a team is likely to be divided into polarized status-based subgroups when members at different status levels have consistent objectives (i.e., vertical similarity) while members at a similar status level have opposing objectives (i.e., horizontal dissimilarity). An employee provided a typical scenario of these two distribution features, “The two bosses had different objectives in the decision about selecting the consulting agency. Finally, we were asked to take a stand. I supported Mr. Yang (i.e., one of the superiors), and I thought Mr. Yang's plan was more promising…Finally, we form two opposing subgroups led by two leaders respectively.” (#T8Sub2). This example shows that the opposing objectives between high-status individuals lead to the separation between them. Overbeck and his colleagues (2005) provide the reason that high-status individuals may have strong expectations and self-awareness, which may reduce their willingness to engage in information sharing, teamwork, group decision-making, and integration. A supervisor confirmed that “The contradictions of business objectives between the deputy manager and me is the main reason for the formation of the so-called polarized subgroups…Each of us has supporters, leading to further horizontal splitting within the department.” (T13Sup2). High-status people have a strong intention to build strong relationships with submissive low-status members who share similar objective with them (Chun & Choi, 2014; Peiró & Meliá, 2003). Therefore, the opposition of objectives among members at a similar status level and the consistency of objectives among members at different status levels (a crisscrossed distribution between status and objective) jointly act on the formation of polarized status-based subgroups (see Fig. 5b).Proposition 3b: When the distributions of status levels and objectives are crisscrossed among team members (i.e., members at different status levels have consistent objectives while members at a similar status level have opposing objectives), a team is likely to be divided into several polarized status-based subgroups.
The Joint Distribution Between Status and Resource Types
The results of theoretical coding identified two joint causes for the formation of stratified status-based subgroups: the overlapping of resources among members at different status levels (i.e., vertical similarity) and the complementarity of resources among members at a similar status level (i.e., horizontal dissimilarity) (see Fig. 5c). A supervisor provided the reason for his formation of high-status subgroup, said, “All the information they (i.e., subordinates) have is readily available to us, so it doesn’t make sense to enlist their support” (#T5Sup1). This example shows that when the resource of high-status members is overlapped with the resource of low-status members, they will lose their appeal to each other. Thus, it is unlikely to form a subgroup across the status hierarchy. The supervisor added why he developed a high-status subgroup with senior staff, “Sun (i.e., a project manager) has developed a solid relationship with officials in the URA, which is a scarce resource, and I (i.e., a senior engineer) hold the discretion of project approval. So, our cooperation is a strong combination” (#T5Sup1). In this case, the supervisor chooses to cooperate with members at the same status level who have heterogeneous resources that are not available to the supervisor himself. And this finding also applies to the formation of the low-status subgroup. An employee said that “Li, Liu, and I (i.e., subordinates) are highly complementary in technical skills. We developed a gold partnership that can compete with the high-status subgroup” (#T9Sub5). Cropanzano (2005) argue that resource complementarity is the foundation of interpersonal cooperation. Therefore, the overlapping of resources among members at different status levels and the complementarity of resources among members at a similar status level, which indicates a crisscrossed distribution between status and resource types, could combine to give rise to the formation of stratified status-based subgroups.Proposition 4a: When the distributions of status levels and resource types are crisscrossed among team members (i.e., members at different status levels have overlapping resources while members at a similar status level have complementary and heterogeneous resources), a team is likely to be divided into several stratified status-based subgroups.
According to our data, a team is likely to be divided into polarized status-based subgroups when members at a similar status level have overlapping resources (i.e., horizontal similarity) while members at different status levels have complementary resources (i.e., vertical dissimilarity) (see Fig. 5d). Several employees described that the resource (e.g., skills and sales channels) overlap among people at the same status level lead to the horizontal polarization of subgroups. For example, an employee said that “There are two competing subgroups in our department. Each of the subgroups are leaded by a key person…My boss (i.e., the manager of the department) and Wang (i.e., the deputy manager of the department) are responsible for market expending, and both of them are highly skilled at dealing with difficult clients. They are unconvinced of each other” (#T16Sub1). Another employee from new energy industry also described, “If two men ride on a horse, one must ride behind. In our department, both of the leaders have good marketing skills and sales channels, so they are reluctant to give up this piece of meat (i.e., the market), which finally led to the current situation of ‘tiger fight” (#T3Sub1). These cases showed that team members at equal status process similar resources (e.g., skills and sales channels). Porath et al. (2008) found that when group members possess expertise and skills in the same domain, they will threaten the status of each other, leading to aggressive behavior or avoidance among them. In addition, when choosing their followers, high-status members show remarkable focus on low-status individuals who possess complementary resources (Gruenfeld et al., 2008). The interviewees said that “When my boss gets the contract, he still needs me (i.e., a subordinate) to confirm the legality of the contract based on my expertise. He also needs Cui (i.e., a subordinate) to keep an eye on the progress of the project. Once we enter the clique, we are on the same boat.” (#T16Sub1) and “They only draw in people with utility value, and technical staffs are the most sought-after” (#T3Sub1). In sum, the overlapping of resources among members at a similar status level and the complementarity of resources among members at different status levels, which indicates an aligned distribution between status and resource types, could combine to give rise to the formation of polarized status-based subgroups.Proposition 4b: When the distributions of status levels and resource types are aligned among team members (i.e., members at different status levels have complementary and heterogeneous resources while members at a similar status level have overlapping resources), a team is likely to be divided into several polarized status-based subgroups.
The Second Team Level Source: Features of Team Status Structure
TAJFEL and Turner (1979) suggest that there are three aspects that shaping the character of a status structure: the stability of status (i.e., the extent to which a particular status structure is changeable), the legitimacy of status (i.e., the extent to the high- and low-status groups accept the status structure as appropriate, proper, and just), and the permeability of group boundaries (i.e., the extent to which group members can change their group membership). These characters will influence low-status members’ actions and tactics in interacting with high-status members.
As shown in our results, when the stability of status, the legitimacy of status, and the permeability of group boundaries are at a lower level, a team is likely to be divided into stratified status-based subgroups. When being asked about the attitude toward the stability of the status structure, a technical staff predicted that a challenge about the status hierarchy was coming soon in his department. He said, “The status ranking is changing. Team members have gotten used to ranking on the basis of seniority or titles. But with the shuffling of technology in the media industry, knowledge of new media operations is becoming more and more important, and the senior staff will be challenged by our new forces, who are equipped with experiences in new media operations. The status ranking will be inevitably rearranged within the team. And this instable circumstance provides us (i.e., the subordinates) with an opportunity to compete with the higher status staffs” (#T14Sub2). This description shows that unstable status provides more opportunities for low-status members to compete with high-status members, increasing the likelihood of a divide along status hierarchy (i.e., the formation of stratified status-based subgroups). In addition, when talking about the sources of stratified status-based subgroup formation, an employee stressed the role of status legitimacy, said, “This vertical division (i.e., the formation of stratified status-based subgroups) is due to the unconvincing of their status. Our young people believe that we are more qualified for the leader position than the incumbents. So we choose to challenge their position, and aim at replace them (i.e., the superiors) one day in the future” (#T19Sub6). An illegitimate status ranking is likely to be challenged by the low-status subgroup, resulting in hierarchical conflict between the high- and low-status subgroups. Last, the stratified status-based subgroups are likely to be formed when the group boundaries between the high-status group and the low-status group are impermeable. An employee in a state-owned construction company stated that, “In a state-owned company, it is impossible for a nobody to have a quick promotion. Those who outrank us have tried their best to block our promotion channel and we (i.e., the subordinates) do not have access to become one of them…The hierarchical system was increasingly consolidated… The only thing we (i.e., the subordinates) can do is to bound together and keep a distance from them (i.e., the superiors)” (#T21Sub3). The impermeability of status blocked upward mobility of low-status members and strengthened the stratification along status order, leading to the formation of stratified status-based subgroup. Bettencourt et al. (2001) summarize that members of a low-status group favor their own in-group rather than the high-status out-group when the status structure is perceived as unstable, illegitimate, and impermeable. Accordingly, stratified status-based subgroups will form under a lower level of status stability, status legitimacy, and group permeability.Proposition 5a: When there is a lower level of status stability, status legitimacy, and group permeability, a team is likely to be divided into several stratified status-based subgroups.
As we considered our data, we also explored the roles played by characters of status in the polarized status-based subgroup formation. We interviewed high- and low-status members that experiencing polarized status-based subgroup formation to gather their perspectives on status structures. Their statements indicate that a stable status structure lead to the formation of polarized status-based subgroups. For example, one of the interviewees stated, “The opposing camps are forming in my department…In most cases, hierarchical structures are based on formal position in firms, thus we all default to this status ranking… It is unlikely to overturn this ranking because the people at high-status is empowered by the institutional system…Therefore, as a normal employee, I cannot gain the organization resource by myself, and the best way for us to survive in the department is to join a leader’s subgroup” (#T3Sub1). In addition, our results also revealed the importance of status legitimacy in forming polarized status-based subgroups. For example, an employee stated, “People at leadership positions usually have core competencies, either in terms of personal skills or external resources…. There’s no doubt that Yang is a competent leader, so I choose to follow him…However, it is inevitable for two competent and respected leaders to develop their own inner circles within the team” (#T11Sub1). Beyond high status stability and legitimacy, permeable group boundaries also serve as important drivers for polarized status-based subgroup formation. An employee explained, “Our firm has developed a clear promotion system. Thus, there is hope for everyone at the ground level to become a key figure. The difference in rank is not a barrier between the leaders and us. Full with the hope, I admire the key figures and desire to be one of them. I am willing to follow a leader and learn from him” (#T8Sub3). This case shows that low-status members with permeable group boundaries tend to associate with high-status group, especially when the status structure is perceived to be stable and legitimate. Accordingly, polarized status-based subgroups are likely to form when the status structure is perceived as stable, illegitimate, and permeable.Proposition 5b: When there is a higher level of status stability, status legitimacy, and group permeability, a team is likely to be divided into several polarized status-based subgroups.
Discussion
Researchers have inconsistent perspectives on how status-based subgroups are formed within a team. In this study, we aimed to develop a typology framework of the status-based subgroup by employing a grounded theory approach and conducting two phases of interviews. The collected data of the individual interviews (phase one) allowed us to indicate the individuals’ experiences of status-subgroup formation. Individual interviews were the basis for obtaining the initial identification of different types of status-based subgroup formation, and providing the individual-level causes of status-based subgroup formation. Subsequently, the insight from the phase one led us to design the team interviews (phase two). We traced the teams where the individual interviewees were from and included all team members in these teams in phase two. The team interviews validated the specific types of status-based subgroup at the team level and distinguished the team-level causes between different types of status-based subgroup. Our data demonstrate that the status-based subgroups are typically formed in two ways: vertical stratification and horizontal polarization. We illustrate the distinction between the stratified and the polarized status-based subgroup, including the formation patterns and the formation sources of these subgroups. Our participants’ descriptions open the door to a deeper understanding of status-based subgroup formation.
Two Formation Patterns of Status-Based Subgroup
The primary contribution of the current study is the typology framework of the status-based subgroup. This contribution builds on depicting a more complete picture of how high/low-status members will divide into subgroups. Our study indicates that in a team composed of multiple members with high status and multiple members with low status, team members may divide into status-based subgroups in two typical patterns. On the one hand, the stratified status-based subgroups are formed by vertical splitting between members at different status levels and horizontal uniting between members at a similar status level. This formation pattern of the status-based subgroup we found does accord with the depiction of subgroup formation patterns in faultline and subgroup literature (Carton & Cummings, 2012; Lau & Murnighan, 1998). Researchers in this area suggest that subgroups arise from faultlines (i.e., hypothetical dividing lines that may split a team into homogeneous subgroups based on one or more attributes, Lau & Murnighan, 1998). That is, individuals perceive other members as belonging to their own subgroup if they are on the same side of status faultline, and individuals at dissimilar status will be divided into different subgroups (i.e., on different sides of status faultline), leading to team members being differentiated vertically along status hierarchies (Carton & Cummings, 2012). Prior faultline and subgroup literature has generally assumed that this is the most possible formation pattern of subgroup formation (Carton & Cummings, 2012; Van der Kamp et al., 2012).
In addition, we complement existing faultline and subgroup literature by providing empirical support for another type of status-based subgroup: polarized status-based subgroup, which is formed by horizontal splitting between members at a similar status level and vertical uniting between members at different status levels. When a team is divided into polarized status-based subgroups, multiple high-status members will lead different subgroups respectively, while low-status members will choose to follow one of these leaders. This type of status-based subgroup formation can be informed by competition exclusion perspective, which emphasizes that people with equal status may adopt competitive strategies aimed at obtaining higher status or more resources, and, consequently, leading to horizontal polarization between those with equal status (Bunderson et al., 2016; Chattopadhyay et al., 2010; Groysberg et al., 2011). But this perspective received far less attention in faultline and subgroup literature. Therefore, we offer new insight into the way of status-based subgroup formation, and we extend the existing subgroup literature by demonstrating that status-based subgroups can be formed in two different structure patterns: vertical stratification or horizontal polarization. We provide a basis for future research to consider differentiated structure patterns when studying subgroup formation.
Different Sources of the Stratified and Polarized Status-Based Subgroup Formations
Furthermore, this paper also contributes by investigating the sources of subgroup formation. Previous work of subgroup has already focused on why subgroups are formed and investigated the role that team structure (e.g., faultline distance, Bezrukova et al., 2009; stability and size of subgroups, Carton & Cummings, 2012), and team atmosphere (e.g., cultural misalignment, Bezrukova, et al., 2012; team identification, Jehn & Bezrukova, 2010) in subgroup formation or activation. Although these elements predict the rise and fall of subgroups, they cannot tell us why status-based subgroups will form in different structure patterns, considering multi-level (i.e., individual-level and team-level) sources may have important implications for understanding the development of stratified or polarized status-based subgroups.
Individual-Level Source: Team Member’s Orientation Toward Resources
At the individual level, we distinguished different motivations of individuals for the formation of stratified or polarized status-based subgroups. Prior studies suggested that people’s forming status-based subgroups are motivated by the ambition of creating and enforcing hierarchies (Carton & Cummings, 2012; Van der Kamp et al., 2012). However, our results suggest that we can delve deeper into the sources of status-based subgroup formation by looking into individuals’ orientations toward resources. Past research has consistently shown that the quest for resources is a fundamental human motive (Mannix, 1993). Interestingly, we found that the formations of stratified and polarized status-based subgroups are respectively motivated by different orientations toward resources. On the one hand, we find that the formation of stratified status-based subgroups is motivated by resource-maintenance orientation. Resource-maintenance orientation indicates that high-status members attempt to hold on to their dominant position in controlling access to finite resources, and low-status members aim to maintaining their resources and resist further loss of their remaining resources. On the other hand, our data suggest that the formation of polarized status-based subgroups is motivated by resource-seeking orientation. Resource-seeking orientation indicates that most individuals within a team focus their attention on obtaining more resources from the organization than others. By emphasizing the essential roles of individuals’ orientations toward resources, the current study can provide a deeper insight into understanding differences in sources of stratified and polarized status-based subgroup formation.
The First Team-Level Source: the Distribution of Team Members’ Characteristics
Specifically, at the team level, an important contribution is to provide greater insight into how the distribution of team members’ characteristics will shape the formation patterns of status-based subgroups. Prior studies have suggested that status-based subgroups can exist when a disparity distribution in hierarchical status is already in place (Carton & Cummings, 2012). However, only focusing on the distribution of status cannot sufficiently predict whether status-based subgroups will be formed by vertical stratification or horizontal polarization. Much remains to be learned about the role played by the distribution of multiple characteristics in shaping status-based subgroup formation patterns. In this case, the current study takes a step further to examine the joint distribution between status and other characteristics (i.e., objectives and resource types). This study shows the strong influence of the joint distribution between status and objective in forming stratified and polarized status-based subgroups. According to the interviewees’ detailed descriptions, when the distributions of status levels and objectives are aligned among team members, a team is likely to be divided into stratified status-based subgroups. That is, when members at a similar status share the same objective, they are more likely to bond together. And when members at different statuses hold opposing objectives, they will divide vertically into different subgroups. The result we found aligned with studies in subgroup formation, which have generally suggested that subgroups are typically formed according to the divisions of team members’ characteristics (Carton & Cummings, 2012; Lau & Murnighan, 1998). In particular, an alignment of multiple characteristics (i.e., status levels and objectives) may heighten the possibility of subgroup formation (Lau & Murnighan, 1998), because, based on similarity-attraction-paradigm (Byrne, 1971), scholars believe that similar members intend to form a homogeneous subgroup, while dissimilar members will divide into different subgroups. For example, Ellis et al. (2013) suggested that when objectives or goals are directly pitted against one another in a team, the team is more likely to split into different subgroups with distinct objectives. Moreover, when status levels are aligned with members’ objectives in the same way, status cues will be more prevalent, and one’s status subgroup identity will be more salient because similar objectives serve as the symbols of status rank. For example, the high-status group usually holds the objective of maintaining institutional inertia, while the low-status group has the objective of changing existing rules.
But what will happen if the distribution of status levels is not aligned with members’ objectives? Our data indicate that when the distributions of status levels and objectives are crisscrossed among team members (i.e., members at different status levels have consistent objectives while members at a similar status level have opposing objectives), a team is likely to be divided into polarized status-based subgroups. This finding indicates that opposing objectives will trigger competition and division among people with equal status. In contrast, objective consistency will facilitate a vertical alliance between high-status and low-status members. In sum, our findings suggest that the joint distribution of status level and objective is an effective reagent to detect the formation of stratified or polarized status-based subgroups.
Our study also demonstrated that the joint distribution of status and resource types effectively distinguishes the formation of stratified and polarized status-based subgroups. We find that when the distributions of status levels and resource types are aligned among team members (i.e., members at different status levels have complementary and heterogeneous resources while members at a similar status level have overlapping resources), a team is likely to be divided into several polarized status-based subgroups. This finding contrasts with what we find in the joint distribution of status and objective, which means the similarity-attraction-paradigm (Byrne, 1971) does not work for the alignment between status levels and resource types. When people with equal status possess overlapping kinds of resources, their interaction can be especially contentious because one person’s claim to resource potentially threatens or challenge another person’s status, leading to spirals of aggressive behavior or avoidance among them. In contrast, when members at different statuses possess different resources, high-status and low-status members can complement each other by exchanging diversified resources, and thus developing vertical cooperation between them.
We also found that when the distributions of status levels and resource types are crisscrossed among team members (i.e., members at different status levels have overlapping resources while members at a similar status level have complementary and heterogeneous resources), a team is likely to be divided into several stratified status-based subgroups. Because when members with equal status possess resources in different domains, they can proclaim their dominance in different domains, reducing the need to compete with each other and increasing the possibility for their horizontal cooperation. Our findings challenged the similarity-attraction-paradigm (Byrne, 1971) by showing that the similarity in status and resource types will lead to similarity-exclusion instead of similarity-attraction. Our results suggest that individuals prefer their peers to be equipped with heterogeneous rather than homogeneous resources, because differentiated resources help to reduce competition and threaten among team members and add to the opportunity of exchanging complementary resources.
In sum, we find that the interaction patterns of status-based subgroup cannot be determined by the distribution of a single attribute of status, instead, they are shaped by the joint distributions of multiple types of attributes (i.e., status-objective and status-resource type). Harrison and Klein’s (2007) have distinguished three types of diversity: separation, variety, and disparity. Inserting our research into their typology, status difference indicates disparity: vertical difference that privileges a few over many; objective difference indicates separation: horizontal distance along a particular opinion, reflecting disagreement or opposition; resource type difference indicates variety: differences in kind or category. Therefore, team member’s status, objective, and resource type are important and typical attributes in diversity literature. However, researchers did not fully detect the joint functions of the three types of attributes. Carton and Cummings (2012) focused on each single type of diversity and argued that disparity-based faultlines (e.g., status-based faultlines) are most likely to trigger subgroups in the pattern of stratification. We extend their research by focusing on the joint distribution of multiple types of diversity. Our findings show that the joint distribution between status (disparity) and objective (separation) and the joint distribution between status (disparity) and resource type (variety) shapes different structure patterns (stratification or polarization) of status-based subgroups. We encourage more research on the joint function among three diversity types.
The Second Team-Level Source: the Features of Team Status Structure
At the team level, another contribution is to illustrate how features of team status structure (i.e., the stability of status, the legitimacy of status, and the permeability of group boundaries) will influence the formation of stratified and polarized status-based subgroups. Scholars have noticed that features of team status structure are likely to influence low-status members’ actions and tactics in interacting with high-status members. Therefore, we proposed that considering the features of team status structure can provide a deeper level of insight into the formation of status-based subgroups. Our results show that a lower level of status stability, status legitimacy, and group permeability is likely to give rise to the formation of stratified status-based subgroups. In contrast, when there is a higher level of status stability, status legitimacy, and group permeability, a team is likely to be divided into several polarized status-based subgroups. These findings can be informed by social identity theory (Tajfel & Turner, 1979). Tajfel and Turner (1979) found that when the status structure is perceived as unstable and illegitimate, and group boundaries are impermeable, low-status groups may adopt collective strategies to compete with high-status groups. Accordingly, high-status and low-status members are likely to divide vertically into stratified status-based subgroups.
In contrast, when the status structure is perceived as stable and legitimate, and group boundaries are permeable, studies provide evidences that high-status groups showed in-group bias, while low-status groups showed favoritism toward the high-status group and adopted an individual upward mobility strategy to join up with high-status members. In this case, status-based subgroups are likely to be formed in the patterns of horizontal polarization among people with equal status and vertically uniting among people at different status levels (i.e., polarized status-based subgroup formation). Therefore, our results validate the social identity theory and elaborate the theory by clarifying how features of team status structure will shape the formation patterns of the status-based subgroup.
In general, we specified the individual-level and the team-level sources of each type of status-based subgroup formation. Subgroup formation represents a subgroup level of analysis, that is, between the individual and team levels (Meyer et al., 2015). On one hand, subgroups are formed from team individuals, and individual’s preferences determined whom will they choose as their within-subgroup cooperators. On the other hand, subgroup formation is triggered by the characteristic distributions and status features of all team members, which are conceptualized at the team level of analysis. Therefore, both individual-level and team-level causes are critical to the subgroup-level outcomes (i.e., the formation of stratified and polarization status-based subgroups). We ultimately tie individual-level and team-level causes to subgroup-level outcomes and these observations show that there is much to learn from taking a multilevel approach to study the formation of subgroups.
Limitations
Although the purpose of our study is to provide “local interpretations of a phenomenon” (Harrison & Corley, 2011: 410), questions about the “trustworthiness” and “generalizability” of the findings still arise. Our sampling strategy necessarily limits to whom the findings can be generalized. The current study was conducted in the Chinese context, in which the “collectivism” culture is highly valued (Hofstede, 1991). Under this culture, the Chinese organizations often develop a highly hierarchical status frame, and forming small cliques is a popular trend. All these elements combine to give rise to the status-based subgroup formation. We agree that theories developed in Chinese context cannot be universally applied to another (Hofstede, 1991). However, knowledge, regardless of its origin, should be applied worldwide when feasible (Tjosvold et al., 2001). Thus, we begin to think about how to transferred the theory outside the Chinese context, such as in western societies (Lincoln & Guba, 1985). Status subgroup formation share many critical features with alliance and faction that applied in Western context. Notably, alliance and faction represent subgroups that have been formed for gaining valued resources, which is in line with the goal of status-subgroup formation (Levine & Moreland, 1998; Li & Hambrick, 2005). The western context strengthens the interaction between cooperation and competition (Deutsch, 1973). The cooperate needs of team members lead to cooperation within factions, whereas competitive needs of team members lead to separation between factions. Along this line, future research can deeply look into how the cooperate and competitive need interdependence drives team members to use status as basis for developing subgroups. We believe that it will be a promising way to broaden our model beyond the Chinese context. In addition, our grounded-theory approach was based on a relatively small sample (21 team samples that covered 111 individuals), which may also lead to the question of “generalizability.” Future research can address this problem by further developing the measurements of the focusing constructs in our framework (e.g., stratified and polarized status-based subgroup formation, and individual’s orientation toward resources), and then quantitatively testing this framework with large team-level samples.
Second, the current study examines the subgroup as an enduring and static property. However, this approach neglects that change and evolvement are inherent to subgroups over time. Our results demonstrate that the formations of stratified and polarized status-based subgroups are not stable. Some interviewees mentioned that these two types of subgroup might transform into each other in the long run. However, restricted by our sample, we did not detailly detect the dynamic process of subgroup evolvement. Meister et al. (2020) have introduced a temporal lens to the subgroup literature and called for the dynamic conceptualization of the subgroup phenomena. Therefore, future research will provide unique insights into the dynamic process of subgroup formation or the transformation between stratified or polarized status-based subgroups.
Third, this study focuses on the formation stage of the status-based subgroup. Future research is encouraged to extend this line of research by exploring how the stratified and polarized status-based subgroups will impact team effectiveness in different ways. For example, on the one hand, the formation of stratified status-based subgroups is likely to improve the effectiveness of teams that face routine tasks, because a stratified status structure maintains the unity of commands and ensures that the commands are delivered quickly and executed smoothly. On the other hand, the formation of polarized status-based subgroup is likely to improve the effectiveness of teams that face creative tasks, because the horizontal competition between subgroups will boost the collision of diversified ideals, creating new managerial solutions or technical innovation.
Practical Implications
Our study also has important practical implications that deserve to be discussed. Managers need to be aware that the division of teams into status-based subgroups has become a common phenomenon in the workplace, especially when organizations are structured in a hierarchy and are experiencing resource limitations. The formation of status-based subgroups will greatly shape the interaction and resource allocation among team members at different status, which will ultimately affect team efficiency. Therefore, more attentions should be paid to the management of status-based subgroup formation. Our typology of status-based subgroup allows organizations and managers to keep alert to the formation of status-based subgroups and to distinguish between different patterns of status-based subgroups: vertical stratification vs. horizontal polarization. This distinction makes a certain sense, because managers could suit the remedy to the case when interfering the formation of each type of status-based subgroup. More detailed remedies are illustrated in the following passage.
Moreover, our results allow managers to know how to effectively intervene in the formation of both types of status-based subgroups. Combining our results regarding the sources of the formation of stratified and polarized status-based subgroups, there are multilevel elements that managers should consider. First, at the individual level, managers can promote or suppress the formation of stratified and polarized status-based subgroup by cultivating team members’ specific orientation toward resources (i.e., resource-maintenance orientation vs. resource-seeking orientation). More specifically, managers can alleviate staffs’ resource-seeking needs by clearly clarifying the rule of resource allocation. Once the rule breaks the link between resource allocation and status hierarchy, it will reduce staffs’ tendency to form status-based subgroups.
Second, at the team level, managers can manipulate the formation of stratified or polarized status-based subgroups by elaborating the team composition (i.e., the joint distribution of team members’ status levels, objectives, and resource types) when building a work team. For example, if the manager hires people in the same work position (i.e., status) with similar social resources, it is more likely to trigger the formation of polarized status-based subgroups, but impede the formation of stratified status-based subgroups. If the manager sets congruent task objective for team members at all status, neither the stratified nor the polarized status-based subgroup will emerge in the team.
Third, managers may interfere the formation of status-based subgroup by adjusting the status characteristics. For example, if a manager is aiming at impeding the formation of stratified status-based subgroup, he/she can assign internal roles and responsibilities according to the work position (i.e., status) and set clear paths for promotion. In this way, team members can have a clear understanding of the stability, legitimacy, and permeability of status order, thus providing teams with a legitimate sensemaking status structure that increases fairness perceptions and diminishes the possibility of stratified status-based subgroup formation.
Conclusion
This qualitative study provides new insights into how and why status-based subgroups are formed within a team. Specifically, our findings open new pathways to understand the subgroup formation by revealing two important formation patterns of the status-based subgroups: vertical stratification and horizontal polarization. This study also extends subgroup literature by delving deeper into the individual-level and team-level sources of status-based subgroup formation and clarifies the distinctions between sources of the stratified and polarized status-based subgroup formation.
Appendix 1
Table 2 Data structure
Quotes from interviews (examples) First-order codes Second-order codes Aggregate themes
“……, so, we (i.e., superiors) usually don't play with them (i.e., subordinates).”
“The superior leaders developed a solid coalition. It’s hard for our people at grass-roots to get into the coalition.”
High-status members are socially isolated from low-status members Members at different status levels split up vertically Stratified status-based subgroup
“These managers may be worried about being replaced by us (i.e., subordinates),
so there are few opportunities for us to perform and our values are not recognized.”
High-status members restrict career development for low-status members
“We prevent the subordinates from having access to these relationships and channels,
and they just need to deal with some basic work.”
“We prevent the subordinates from having access to these relationships
and channels, and they just need to deal with some basic work.”
High-status members monopolize (relationships/ channels) resources over low-status members
“They (i.e., superiors) don't even forget to take advantage of us (i.e., subordinates) in such trivial matters as bonus distribution.” High-status members exploit the financial interests of low-status members
“We just want to do our own thing. We (i.e., subordinates)
don't want to get too involved with them (i.e., superiors) in private.”
Low-status members avoid high-status members
“We have to get the leaders to acknowledge our importance.
Technology is our core competency. We often give them a hard time by refusing
to share the latest algorithms with them during the product development process.”
Low-status members block (technical/ knowledge) resources to high-status members
“Our information sources are numerous and diverse. Interoperability between us (i.e., superiors)
can create more value for both of us.”
Information resources are shared among high-status members Members at a similar status level join up horizontally
“A few VPs and I are the backbone of the whole department.
We trusted each other and controlled the core business channels of the department.”
“A few VPs and I (i.e., a supervisor) are the backbones of the whole department.
We trusted each other and controlled the core business channels of the department.”
High-status members jointly control resources
Mutual trust and support among high-status members
“Our grassroots employees understand each other's difficulties,
and I empathize with what he is going through.
So, I will not watch the fire from the shore, but help him through the difficult times.”
“the only way to keep competitive is to cooperate with my co-workers.”
Mutual trust and support among low-status members
“If everyone is going to compete for business resources,
the team will be hard to manage. We can’t sit in a superior position without
holding core resources in our hands. So, this exclusion is also a last resort.”
High-status members work together to maintain resources Members are oriented with maintaining existing resources
“We need to stick together and never compromise on changes to the promotion system.
That's the only way to keep us current position.
A retreat makes things worse.”
“We are allying to face the same enemy (i.e., high-status members).
This is an efficient way not to be marginalized and to prevent those senior staffs from stealing our core technology.”
“The meat is taken away by them (i.e., the superiors),
and we are unable to drink the soup if we don't hold a subgroup.”
Low-status members work together to resist resource threats
“there is a saying goes ‘Inequality rather than want is the cause of trouble’.
I don't think the leaders are performing to match the current payment.”
There is disagreement between high-status and low-status members over the pay distribution scheme Aligned distribution between status and objectives (Members at different status levels have opposing objectives)
“The current assignment of tasks is unreasonable. Why should we (i.e., subordinates)
only be assigned low-skilled basic work. We can do more than that.”
There is disagreement between high-status and low-status members over the task assignment plan
“We can't agree on a system for performance evaluation and promotion,
and those at the top only make systems that benefit themselves.”
“The deviations of objectives separate us (i.e., subordinates) from the superiors.
We seek more deviations and possibilities and they seek to maintain the status quo.”
There is disagreement between high-status and low-status members over system change
“We (i.e., superiors) always hit it off, and we're very strict about
big strategic arrangements and we prefer more conservative plans.”
High-status members are aligned in their strategic orientations Aligned distribution between status and objectives (Members at a similar status level have consistent objectives)
“We are the only ones capable of opening up the market,
because we have the resources and experience to match this task.”
High-status members are aligned in their task objectives
“When it comes to the change on the assessment system,
our leaders will not back down, because once the rules are changed,
we will lose altogether. I know that the demands and ideas of the subordinates are opposed to ours,
but we will not let their plans for change succeed…Birds of a feather flock together.
In most cases, people on the same hierarchical status levels enjoy the same benefits in the system,
share similar goals, and can exchange equal resources, which is the essential reason for status differentiation”
High-status members are aligned in their system claims
“We young stuffs are united because we all want the same thing,
we all want to be promoted without seniority.”
Low-status members are aligned in their (promotion/ compensation) system claims
“We are pragmatic and want to make every business perfect from the beginning to the end.
This is a precious opportunity for us to grow.”
Low-status members are aligned in their task objectives
“Although several of our newcomers are at the grass-roots level, in fact,
many of the key technical problems are solved by us. I am confident that our knowledge is more cutting-edge than the senior staffs.”
High-status members and low-status members have overlapping skills Crisscrossed distribution between status and resource types (Members at different status levels have overlapping resources)
“All the information they (i.e., subordinates) have is readily available to us, so it doesn’t make sense to enlist their support.” High-status members and low-status members have overlapping information
“He had worked in a government department and knew many government officials;
and I have been in business for many years, so my business resources are very rich.”
“Sun (i.e., a project manager) has developed a solid relationship with officials in the URA,
which is a scarce resource, and I (i.e., a senior engineer) hold the discretion of project approval. So, our cooperation is a strong combination.”
High-status members have complementary social relationships Crisscrossed distribution between status and resource types
(Members at a similar status level have complementary resources)
“We work well together. Wang has great social skills and can help us maintain channel relationships.
And my technical skills can help us develop a more accurate product strategy.”
High-status members have complementary skills
“Li, Liu and I (i.e., subordinates) are highly complementary in technical skills.
We developed a gold partnership that are able to compete with the high-status subgroup.”
Low-status members have complementary skills
“The high-status group will be challenged by our new forces,
who are equipped with experiences in new media operations.
The status ranking will be inevitably rearranged within the team.”
The status ranking faces a challenge Lower level of status stability
“The status ranking is changing. Team members have gotten used to ranking on the basis of seniority or titles.
But with the shuffling of technology in the media industry,
knowledge of new media operations is becoming more and more important,
and the senior staff will be challenged by our new forces,
who are equipped with experiences in new media operations.
The status ranking will be inevitably rearranged within the team. And this instable circumstance provides us
(i.e., the subordinates) with an opportunity to compete with the higher status staffs”
The status ranking is changing
“They (i.e., team leaders) are at the superior position because of the dividend of their age,
not because of their competence. In fact, many young people are very hard-working and very talented. If we have more space to develop, we will perform even better.”
Formal status is not congruent with competence Lower level of status legitimacy
“This vertical division (i.e., the formation of stratified status-based subgroups)
is due to unconvincing of their status.
Young people believe that they are more qualified for the leader position than the incumbents.”
Formal status is unconvincing
“We (i.e., the subordinates) are better suited for senior positions, as salesman than them (i.e., the superiors).”
“If the company removes these barriers for newcomers, then we will see more young people in senior positions.”
Formal status arrangement is not proper
“In a state-owned company, it is impossible for a nobody to have a quick promotion. Those who outrank us have tried their best to block our promotion channel and we (i.e., the subordinates) do not have access to become one of them…what we can do is close ranks…The hierarchical system was increasingly consolidated.” Low-status members do not have the opportunity to join high-status group Lower level of group permeability
“The project I (i.e., the manager of the department) got must have followed up with my supporters.”
“Some newcomers are labeled as ‘someone's follower’ as soon as they join the team because a man cannot serve two masters.
For example, in our department, we either follow Mr. Yang (i.e., the director of the department) or Mr. Sun (i.e., the vice director of the department).
Nie and I followed Mr. Yang from the very beginning…If we want to get a foothold in our department,
we have to find a capable backer. Mr. Yang will give priority to us when providing training opportunities,
and we will give him some inside information during private dinners.”
High-status members share (relationship/ channel/ task/ financial/ information) resources with low-status members Members at a different status level join up horizontally Polarized status-based subgroup formation
“Some newcomers are labeled as ‘someone's follower’ as soon as they join the team because a man cannot serve two masters.
For example, in our department, we either follow Mr. Yang or Mr. Sun. Nie and I followed Mr. Yang from the very beginning.”
Low-status members provide (technical/human) resources to high-status members
“The company takes full advantage of the catfish effect. The vice manager (i.e., superiors)
and I both exist to compete. Our funding budget and share of projects are allocated based on last quarter's performance,
so we have to think about how to win over each other at all times.”
“We (i.e., the two superiors) lead different subgroups in the department.
The subgroup that takes bigger projects will have a bigger voice.
Market competition is just like jungle survival, where the legitimacy belongs to the victor, while losers are always in the wrong.”
High-status members compete for resources Members at a similar status level split up horizontally
“The two bosses often set themselves against each other.” High-status members do not cooperate with each other
“Each of us looks after our own house. New employees didn't have the resources I (i.e., a subordinate) needed.” Low-status members do not cooperate with each other
“I am not satisfied with the status quo. I hope to have greater development space
and achieve higher rank. But I couldn't do it alone. I had to find a capable backer.”
Access to more (status/ financial/ channel/ human) resources Members are oriented with seeking more resources
“Finally, we were asked to take a stand. I supported Mr. Yang (i.e., a superior),
and I (i.e., a subordinate) thought his plan is more promising.”
“Each of us has supporters, leading to further horizontal splitting within the department.”
High-status members and low-status members are aligned in their task objectives Crisscrossed distribution between status and objectives
(Members at different status levels have consistent objectives)
“Li, Zhou (i.e., subordinates), and I (i.e., a superior)
all agree that the development of the western market is necessary,
and we are all working together to achieve this goal.”
High-status members and low-status members are aligned in their thinking on development
“It is challenger to be a leader, especially when the deputy has his own ideas,
and we always have different ideas in strategic decision making.”
“The contradictions of business objectives between the deputy manager and me is the main reason for the formation of the polarized subgroups.”
High-status members are not aligned in their strategic orientations Crisscrossed distribution between status and objectives
(Members at a similar status level have opposing objectives)
“The two bosses had different objectives about finding a consulting agency to cooperate with…Finally,
we form two opposing subgroups leaded by two leaders respectively.”
High-status members are not aligned in their task objectives
“As locals, they (i.e., subordinates) have a lot of potential local connections,
which is very valuable to me (i.e., a superior). I also made a lot of business contacts through the MPA program.”
High-status members and low-status members have complementary social relationships Aligned distribution between status and resource types
(Members at different status levels have complementary resources)
“Yang (i.e., a superior) always has a voice in the company,
and even big bosses have to give him face because he controls core channels and relationships. These are exactly what we (i.e., subordinates) need.”
High-status members and low-status members have complementary marketing channels
“Cai (i.e., a subordinate) graduated from a relevant professional college and has a solid professional foundation in engineering cost;
Wu (i.e., a subordinate) has legal related knowledge; as their leader,
I have excellent external communication and coordination skills. We are a very good and complementary combination.”
High-status members and low-status members have complementary skills
“He (i.e., a superior) will definitely give priority to us (i.e., subordinates)
when providing training opportunities, and we will give him some inside information during private dinners.”
High-status members and low-status members have complementary information
“We (i.e., superiors) are acquainted with our clients. Who can successfully take the project depends
on who has a closer relationship with the client. So we all focus on customer relationship maintenance.”
High-status members have overlapping social relationships Aligned distribution between status and resource types
(Members at a similar status level have overlapping resources)
“We (i.e., the manager and the vice manager of the department)
are competing in the business of docking heat companies.”
High-status members have overlapping marketing channels
“The most fundamental reason of my (i.e., the manager of the department) confrontation
with Lee (i.e., the vice manager of the department) is that both of us specialize in thermal energy conversion technology.”
High-status members have overlapping skills
“Sun, Liu and I are all responsible for sales, and this part of the job is replaceable,
so the competition among our peers is fierce. Only by constantly exercising our sales skills and opening up the customer market can we stand out.”
Low-status members have overlapping skills
“In most cases, hierarchical structures are based on formal position in firms…
It is unlikely to overturn this ranking because the payment and the power are determined by the level of formal position.”
The status hierarchy based on formal position will not change Higher level of status stability
“The formal position arrangement comes from organization institution,
so it is as stable as the institution.”
The status hierarchy based on formal position is as stable as the institution
“People at leadership positions usually have core competencies,
either in terms of personal skills or external resources”
Formal status is congruent with competence Higher level of status legitimacy
“I treat my followers as in-group members,
and every one of them trusted me with their confidences…
I don't think the difference in rank will be a barrier between us, and they will become me in the future if they keep working toward a target.”
High-status members treat low-status members as in-group members Higher level of group permeability
“I have a promising future in this company, and I belief I will be one of them (i.e., team leaders).” Low-status members have the opportunity to join high-status group
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 32 KB)
Author Contribution
Yue Zhang conducted the interviews, did the analysis, and drafted the manuscript; Qiaozhuan Liang helped to develop the theoretical model; and Wei Deng participated in interviews and collated all materials.
Funding
This study was supported by the National Natural Science Foundation of China (Grant No. 72202177, No. 72201207, No. 72202179), Shaanxi Social Science Foundation (Grant No. D5170210088), Soft Science Research Program in Shaanxi Province (Grant No. 2022KRM003), the Fundamental Research Funds for the Central Universities (Grant No. D5000210968).
Data Availability
The datasets analyzed during the current study are not publicly available due the privacy protection of the interviewee but are available from the corresponding author on reasonable request.
Declarations
Ethics Approval
Not applicable.
Consent for Publication
Informed consent was obtained from all individual participants included in the study.
Conflict of Interest
The authors declare no competing interests.
1 The top-right and bottom-left quadrants of Fig. 4 show another two special cases. The top-right quadrant indicates that all team members (both high and low-status members) are independent individuals. Thus, no subgroup form in this case. The bottom-left quadrant depicts that only a single subgroup is formed, involving part of high-status members and part of low-status members, while other team members are excluded from the subgroup. In phase 1, three samples (individual #24, #30, #31) reported this situation. The single subgroup acts as “a single compact galaxy” in a work team, and “other team members who are excluded from the galaxy are like the stars scattered in the universe” (#24). However, since our research interest is in how teams divide into multiple subgroups, we excluded these samples in the phase 2 team interviews.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
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| 0 | PMC9747534 | NO-CC CODE | 2022-12-15 23:22:01 | no | J Bus Psychol. 2022 Dec 14;:1-28 | utf-8 | J Bus Psychol | 2,022 | 10.1007/s10869-022-09865-5 | oa_other |
==== Front
Support Care Cancer
Support Care Cancer
Supportive Care in Cancer
0941-4355
1433-7339
Springer Berlin Heidelberg Berlin/Heidelberg
7465
10.1007/s00520-022-07465-w
Research
Barriers and facilitators to early-stage lung cancer care in the USA: a qualitative study
Herb Joshua [email protected]
1
Friedman Hannah 2
Shrestha Sachita 3
Kent Erin E. 234
Stitzenberg Karyn 14
Haithcock Benjamin 5
Mody Gita N. 45
1 grid.10698.36 0000000122483208 Division of Surgical Oncology, Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
2 grid.10698.36 0000000122483208 Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
3 grid.10698.36 0000000122483208 Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
4 grid.10698.36 0000000122483208 Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
5 grid.10698.36 0000000122483208 Department of Surgery, Division of Cardiothoracic Surgery, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
14 12 2022
2023
31 1 2123 5 2022
9 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.
Purpose
Improved outcomes in lung cancer treatment are seen in high-volume academic centers, making it important to understand barriers to accessing care at such institutions. Few qualitative studies examine the barriers and facilitators to early-stage lung cancer care at US academic institutions.
Methods
Adult patients with suspected or diagnosed early-stage non-small cell lung cancer presenting to a multidisciplinary lung cancer clinic at a US academic institution over a 6-month period beginning in 2019 were purposively sampled for semi-structured interviews. Semi-structured interviews were conducted and a qualitative content analysis was performed using the framework method. Themes relating to barriers and facilitators to lung cancer care were identified through iterative team-based coding.
Results
The 26 participants had a mean age of 62 years (SD: 8.4 years) and were majority female (62%), white (77%), and urban (85%). We identified 6 major themes: trust with providers and health systems are valued by patients; financial toxicity negatively influenced the diagnostic and treatment experience; social constraints magnified other barriers; patient self-advocacy as a facilitator of care access; provider advocacy could overcome other barriers; care coordination and good communication were important to patients.
Conclusions
We have identified several barriers and facilitators to lung cancer care at an academic center in the US. These factors need to be addressed to improve quality of care among lung cancer patients. Further work will examine our findings in a community setting to understand if our findings are generalizable to patients who do not access a tertiary cancer care center.
Keywords
Qualitative research
Lung cancer
Barriers
Access to care
http://dx.doi.org/10.13039/100000133 Agency for Healthcare Research and Quality 5T32 HS000032 Herb Joshua issue-copyright-statement© Springer-Verlag GmbH Germany, part of Springer Nature 2023
==== Body
pmcIntroduction
Lung cancer is the leading cause of cancer-related fatalities nationally, making improvement in early diagnosis and treatment a critical need [1]. Furthermore, there are widely recognized disparities in survival amongst patients with early-stage non-small cell lung cancer (NSCLC). While the underlying issues are multifactorial, one driver of these inequalities may be inadequate access to definitive treatment, particularly surgical resection [2, 3]. Patients from racial and ethnic minority groups, rural areas, and lower socioeconomic status are among those who are least likely to access and receive treatment of lung cancer [2]. While complex interventions such as race-specific patient-centered navigation demonstrate improvements in treatment rates in trial settings [4], gaps in access to comprehensive thoracic and other surgical oncologic care are still present nationally [5, 6].
Secondary analyses of administrative data and other population-based cohort studies lack evaluation of barriers to lung cancer access from the patient perspective. Qualitative inquiry, when coupled with a theoretical framework for understanding the barriers to treatment, may help determine areas for further work focused on reducing disparities in care. One such framework is the Anderson Model of Total Patient Delay, which defines four care intervals (appraisal, help-seeking, diagnosis, and pretreatment) where barriers may exist to accessing care [7]. Prior qualitative work using the Anderson Model to evaluate patient perceived barriers to diagnosis of lung cancer identified poor relationship with providers, lack of access to care, and lack of awareness of lung cancer symptoms and treatment as major barriers [8]. Additional studies out of Australia have supported these findings [9–11]. However, these studies recruited from a range of health settings, and were conducted in a nation with a universal public insurance system, where barriers to care in those populations may differ from those in the American health care system.
Therefore, this study aims to explore the patient-perceived barriers and facilitators to care for suspected or newly diagnosed early-stage NSCLC through semi-structured individual interviews. We anticipate that barriers and facilitators to care will be multi-faceted and fall into several domains: socioeconomic, health system, and geographic.
Patients and methods
Ethics
The study was approved by the institutional review board at the University of North Carolina, and participants provided verbal informed consent prior to interview. The Consolidated Criteria for Reporting Qualitative (CORE-Q) Research checklist was used in the preparation of the manuscript [12].
Setting, eligibility, and recruitment
The study was conducted at the University of North Carolina, a large tertiary public academic referral center and home to the Lineberger Comprehensive Cancer Center, a National Cancer Institute Designated Comprehensive Cancer Center. The institution has a catchment area of all 100 counties in North Carolina, of which approximately 21% of the population lives in a rural area, 51% are Women, and 22% are African-American [13, 14].
Adult patients with a new or suspected diagnosis of early-stage NSCLC were eligible for inclusion in the study. We focused on newly diagnosed patients as they would not yet have established care in the thoracic oncology clinic at our institution. Patients who were diagnosed over 1 year prior to recruitment or were being actively followed for a prior cancer at our institution were not eligible for inclusion. We screened the institutions’ multi-disciplinary thoracic oncology clinic schedules for new patient visits that matched the above criteria. Purposive sampling was performed in order to ensure representation from women, racial/ethnic minorities, and rural patients. We screened the clinic schedules for new patient visits that took place between September 2019 through March 2020. These dates were chosen for screening because this was before major disruptions in patient referrals due to COVID-19. Patients identified through screening were then contacted by phone and invited to participate from August of 2020 through January of 2021. We attempted to contact patients at least two times on separate days. Patients were given the opportunity to reschedule at their convenience. Of the 84 patients who were screened as eligible for the study, 49 (58%) were successfully contacted by telephone, and 26 (31%) agreed to participate.
Interviews
Interviews were conducted from August 2020 through January 2021. An interview guide was developed from prior qualitative work from Bergin and colleagues (2020) [11], and by using The Anderson conceptual model of patient delays to care [7, 11].
Once verbal informed consent was obtained, an audio-recorded semi-structured interview was performed. Phone interviews only were conducted due to the study being performed during the COVID-19 pandemic. We conducted the interviews from a secure workplace location and the participants were instructed to find a secure, quiet place for the phone interview. Other family members and friends were allowed to be present at the time of the interview, but their perspectives were not collected. Participants had no prior relationship with the interviewers, but some participants were former or current patients of the senior author (who was not present during the interviews).
A 27-item semi-structured interview guide was used to conduct the interview (available on request to corresponding author). The interviews began with open-ended questions on the patient’s background and how they were initially diagnosed with lung cancer or suspected lung cancer. Participants were then asked general questions on barriers or facilitators to care they faced throughout the course of their evaluation, diagnosis, and treatment. Additional probing questions were asked for clarification or expansion when appropriate. Participants' sociodemographic characteristics were collected during the phone interviews through close-ended questions. Each interview generally lasted 30–45 min. Participation in this study was voluntary and no incentive was provided for participating in this study except for the final 6 participants recruited later in the study who received a gift card as compensation in order to improve purposive sampling. Once the interviews were completed, the audio recordings were transcribed verbatim using a secure, third-party, service. Participants were not re-contacted, and they did not have the opportunity to review the transcriptions. The transcriptions were uploaded into Dedoose (v8.3) for analysis.
Analysis
Deductive codes were generated using the socioecological framework, the refined Anderson’s model of patient delay, and Khan’s typology of access [7, 15, 16]. Additional codes were inductively generated after reviewing the first 5 interview transcripts with several codes added as needed as emerging themes were identified in subsequent transcripts [17]. Each transcript was coded independently by two investigators (JH and HF) using the final codebook and discrepancies were resolved by discussion and consensus. The transcripts were reanalyzed until no new codes or code groupings were identified. The framework method was broadly followed for the analysis of the interviews [18]. After coding, three authors (GNM, HF, JH) reviewed the coded excerpts independently, writing reflexive memos as needed. Group meetings with four authors (JF, HF, SS, GNM) were then held to discuss and clarify emerging themes. This process was repeated until no new themes emerged. Exemplar quotes to illustrate the emergent themes were selected. Baseline summary statistics of patient characteristics were also computed.
Results
Participants
We interviewed 26 participants. The participants had a mean age of 62 years (SD: 8.4 years) and were majority female (62%), white (77%), and urban (85%) as defined using rural–urban commuting area codes [19]. Eleven (43%) participants self-identified as rural. Most patients had their early-stage lung cancer found incidentally (54%), followed by lung cancer found by CT screening (31%) (Table 1).Table 1 Characteristics of participants
All participants
N = 26
Age, mean (SD), years 67.2 (8.4)
Sex, no. (%)
Male 10 (38%)
Female 16 (62%)
Race, no. (%)
Black 6 (23%)
White 20 (77%)
Rural/urbana, no. (%)
Rural 4 (15%)
Urban 22 (85%)
Self-described rural/urbanb, no. (%)
Rural 11 (43%)
Urban 15 (58%)
Diagnosis method, no. (%)
Incidental 14 (54%)
Screening 8 (31%)
Symptomatic 4 (15%)
aDefined using rural–urban commuting area codes
bPatients were asked to describe their home as being in an urban or rural location
Themes
We identified 6 major themes addressing barriers and facilitators to lung cancer care, as described below. Additional quotes for each theme are listed in Table 2.Table 2 Dominant themes and exemplar quotes from semi-structured interviews
Dominant themes Exemplar quotes*
1 Trust with providers and health systems is important to patients Facilitator: “[They] gave me the percentages, … and … walked me through it step by step and helped me understand everything, so I trusted [them].”so I said, “Let's do it.”’
Barrier: “I don't trust them. I don’t trust them at all... I said to my sister, and I started crying, “Get me outta here. Get me outta here.”
2 Financial toxicity negatively influenced patient experience Facilitator: “… I'm blessed enough that I could afford to go ahead and make that payment. I can’t even imagine what that would be for people who couldn’t.”
Barrier: “Despite the fact that I was paying $600 a month, I had a huge deductible. I told [redacted] that I could not afford any more exams because my health insurance wasn’t paying for it...”
3 Social constraints magnified other barriers Facilitator: “Then we wanted me to come for my treatments Monday through Friday, every day, for my therapy for the lung and cancer. My son had me there”
Barrier: “It was times he [patient’s son] had to take off work. If you're off work so many times, you'll lose your job.”
4 Patient self-advocacy serves as a facilitator of care access Facilitator: “...my primary care physician and Dr. [redacted] made me feel I had some sort of power, some sort of authority in a situation, and in the circumstance that I was in, I felt almost powerless at first. It’s an overwhelming thing to be told you have something growing in your lung when you know you’re a smoker, so it makes you feel like, okay, I don’t have any control over what's happening. A really important part of helping a patient through the process is giving them some sense of control back.”
Barrier: “Like I was just another number. You know what I mean? I felt like I was just another number. That I was gonna hurry up and die anyway. That’s how they did my husband, so I guess that’s how they figured they were gonna do me. I rebelled.”
5 Provider advocacy could overcome other barriers Facilitator: “[The provider] spent time, theirs and their nurse, trying to find me the cheapest place to do this PET scan and the other scan.”
Barrier: “... but nobody had ever asked me if I wanted to check on my lungs. I never did hide the fact that I was a very active smoker and that I had smoked since very young. What the heck? I never thought about checking my lungs either. No doctor had said anything until that moment.”
6 Care coordination and communication was important to patients Facilitator: “I found the system very easy to navigate. I was very pleased because, of course, I was under a fair amount of stress, just the mental worry about this, and it was just like everybody knew what they were doing, gave me clear answers, directions on everything from what we were doing to how to find my way around the hospital, which I had not been in before...”
Barrier: “The parking situation was horrible over there. It took a long time to drive over there and find a parking space and get over there. They were changing locations where the CT-scan was.”
Theme 1: trust with providers and health systems is important to patients
Some patients reported mistrust of the initial providers they saw and/or the health systems with which they interacted. This led them to delay care or seek it elsewhere. Mistrust stemmed from prior negative experiences either through personal, family, or reputation within the community. Some felt mistrust if the cause(s) of their symptoms were not recognized quickly enough or were misdiagnosed. Patients specifically mentioned mistrust in the broader local health system. Some held fatalistic views and cited a lack of personalized care as a reason for seeking care elsewhere. For example, one patient noted, “The other doctors didn’t want to take the time. It’s just one size fits all. You’re just a number...”
Among those reporting good provider relationships, participants frequently cited their trust in their providers as making the process of obtaining a diagnosis or treatment easier. They also expressed considerable gratitude to their providers for facilitating the process. “I never did hide the fact that I was a very active smoker and that I had smoked since very young. What the heck? I never thought about checking my lungs either. No doctor had said anything until that moment.”
Theme 2: financial toxicity negatively influenced patient experience
Many participants discussed their experiences in paying for their care in both positive and negative ways. Some who were in need were able to access and use financial assistance services while others did not hear about them at all. Financial barriers were related to both the high direct and indirect costs of care and occurred even for those who were insured: “Yeah. Well, I’m sure you’re aware that we have the worst healthcare in the world. Despite the fact that I was paying $600 a month, I had a huge deductible.” Notably, several patients felt there was no choice but to pay the high cost of care because the alternative was to risk death. Several participants noted that even following the conclusion of their treatment, they were still suffering from financial strain and related conditions such as unemployment. Among those less financially burdened by the costs of care, several participants expressed gratitude for the socioeconomic position which allowed them to receive care without worry.
Theme 3: social constraints magnified other barriers
Some patients had multiple social barriers to care, including the inability to take time away from work, lack of transportation, family care responsibilities, and lack of family support. Financial and social constraints exacerbated the other difficulties of obtaining treatment. Two participants reported losing their jobs following their diagnosis: “…, my job fired me when they found out I had cancer and would be needing to take their time off.” Participants who depended on family members for transportation to appointments were subsequently dependent on their family member’s schedules, which in turn were also affected by jobs or other obligations. One participant’s older car broke down on the way to one appointment, creating greater logistical and financial difficulties.
Theme 4: patient self-advocacy serves as a facilitator of care access
Several patients reported that in visits with their providers, they repeatedly questioned their initial diagnoses and/or requested referrals to another center for second opinions. Even after a diagnosis of lung cancer had been made, some patients wanted to take part in directing the next steps of their care, particularly with regard to where to go and who to see for treatment. Patients exercised their agency by seeking a second opinion from a physician, conducting independent research online or with other medical personnel, and asking for detailed explanations about the treatment and/or procedure options available.
Conversely, other patients were willing to defer treatment decisions to the provider who made the diagnosis. Religion and faith also appeared as themes that play into a patient’s treatment decision-making process, with one patient noting that they prayed for a good physician to lead the process.
Theme 5: provider advocacy could overcome other barriers
Provider attitude and concern on the importance of finding suspected or confirmed lung cancer influenced patient care-seeking. Several patients reported their providers, particularly primary care physicians, were willing to help patients navigate a complex health system in order to follow up with a specialist or pursue further imaging. For example, primary care physicians would call local providers to help patients find the least expensive options for further testing: “[The provider] spent time, them and their nurse, trying to find me the cheapest place to do this PET scan and the other scan.”
Providers also frequently encouraged patients to follow up even when the patients did not have plans to do so. Patients reported that strong relationships with primary care providers helped them overcome hesitation to seek diagnosis or treatment.
Theme 6: care coordination and communication was important to patients
Poor coordination of care between health systems and within a health system often worked as a barrier. Patients reported not hearing for several weeks or months after being referred for care, often having to reach out themselves. Patients also reported multiple appointments over different days served as a barrier. Poor communication was often related to poor coordination: “They [referring to cancer treatment provider] probably do a lot of good work, I was just one of those who fell through the cracks.” Poor communication led patients to seek care outside of their community. Patients who experienced better coordination had improved engagement with their care and felt they had more timely care:“I was under a fair amount of stress, just the mental worry about this, and it was just like everybody knew what they were doing, gave me clear answers, directions on everything from what we were doing to how to find my way around the hospital, which I had not been in before. I found everything quite accessible and easy to navigate.”
Several coordination services, such as electronic health systems with patient portals (e.g., MyChart with Epic Systems[Madison, WI]) and timely/easy appointment scheduling, were mentioned by patients as facilitating the process of receiving care.
Comment
Lung cancer outcomes are best when the disease is diagnosed and treated at an early stage. Therefore, our objective was to determine the perspective of patients with suspected or confirmed early-stage non-small cell lung cancer on the barriers and facilitators of access to care. We identified several themes related to how patient-level factors including self-advocacy, trust in their health system and providers, and social circumstances can act as barriers and/or facilitators. We also found themes uncovering how system-level factors including care coordination and provider advocacy and communication can impede or improve care.
A strength of this study is that we recruited patient participants presenting to a large academic hospital in the US that serves as the public referral center for the state in order to determine barriers along the pathway to care in these settings. This is the first US-based qualitative study to specifically examine delays in access to care in early-stage lung cancer patients using the Anderson Model. Prior studies in the US population identified from two reviews on delays in cancer care were in populations that differed from ours [7, 8]; one of those focused on patients who refused care and the other on the advanced lung cancer population [20, 21]. Patients in the US face different barriers than patients in countries with universal health care and/or insurance, where other similar studies have taken place [8, 22]. For example in Australia, specialist referrals are driven by general practitioners, who act as gatekeepers, whereas in the US, patients can often self-refer [23]. This suggests that patient self-advocacy may play a larger role in accessing care in the US.
Importantly, relationships with providers is broadly recognized as important in other qualitative studies and was important to patients in our study as well. Trust in their primary care physician played a role in patients’ willingness to follow recommendations for further testing and referral. Similarly, mistrust was apparent when patients reported they were initially misdiagnosed or when patients had prior negative experiences with the provider or health care system. We found that feelings of mistrust extended not only to treating physicians but entire institutions and this was a factor motivating patients to seek care outside of their community, even if it meant delaying their own care. Prior studies have noted that higher health care system mistrust is associated with poorer health, lower rates of cancer screening, treatment, and follow-up [24–26] and so the importance of future research on methods to overcome this issue.
Patient self-advocacy, provider positive attitudes, and care coordination all were reported to act as facilitators or motivators to overcome barriers to treatment in our study. Patients reported their self-advocacy overcame issues such as a misdiagnosis, mistrust or a slow-moving referral process. These findings highlight a different patient attitude than prior qualitative studies, which focus on attitudes such as stoicism and misattribution [8]. Self-advocacy may have been apparent in our study compared to previous studies since we recruited from a group of patients who successfully accessed a tertiary cancer center.
In review of the provider-level factors, several went out of their way to coordinate care for their patients and help overcome barriers to care, particularly financial barriers. This agrees with prior findings noting the importance of the relationship between general practitioners and patients in accessing lung cancer treatments. Additionally, these findings more broadly highlight how care coordination among health systems and providers is critical to help patients navigate the complex US health system throughout the entire process from diagnosis to treatment [27]. One way this could be improved more broadly is through increased patient navigation efforts in the primary care setting [27, 28].
Social and financial barriers to cancer care are widely recognized and were evident from our results as well [8, 29, 30]. Financial toxicity can have significant effects on quality of life and is associated with higher mortality in cancer patients [31, 32]. Our results support these previous findings as several participants mentioned being unable to receive recommended follow-up care due to insurance limitations. The management of financial stresses by patients was variable. Some patients were unaware of established health system resources available to help cover the cost of care. Other patients, despite being aware, did not follow through due to the confusing and complicated processes for receiving the aid. Other patients navigated complex reimbursement processes when insurance providers changed or when dealing with multiple payers (such as the Veterans Affairs health system, Medicare, and charity care). Further efforts to screen patients for possible financial toxicity and navigate patients towards potential resources to lessen this burden in patients with lung cancer should be undertaken [33, 34].
Our findings highlight the important compounding effects of social and financial barriers. For some patients, multiple vulnerabilities had to be overcome in order to make their appointments, such as the combination of a functioning mode of transportation, the family willing to drive them, and the ability for both to be away from work. If any of these fell through then these patients could not make their visits. Further work should aim to better identify patients at high social need and consider interventions to address these needs at all levels of care [30].
Our results have several important implications for lung cancer diagnosis and treatment. First, primary care providers can play a critical role in the treatment process by not only encouraging patients to receive lung cancer screening but also advocating for and increasing patient’s comfort with the health system throughout the time from diagnosis to treatment. Patients who trust their primary care providers can benefit greatly from proactive providers who provide direct referrals to surgeons and oncologists. Second, patients who are vulnerable due to socioeconomic factors could benefit from more direct interventions to identify existing financial need and active navigation programs to help circumvent other common barriers such as transportation and obtaining financial assistance.
Our study had several limitations. First, we sampled a group of patients who successfully accessed a tertiary care center for their lung cancer care. Thus, barriers that patients discussed in our study were not insurmountable, and they may differ among patients who were not able to access tertiary care or surgical care at all. This may be why themes relating geographic access did not emerge as dominant themes despite our expectations. For future work, we aim to partner with community providers to recruit patients from these areas to better understand their barriers to care. Second, our study was limited to a single institution. Further studies in other healthcare systems and other US geographic regions will be important to confirm and extend our work. Additionally, our cohort was limited to predominantly White patients, and the only other racial group included were patients who are Black and so while representative of the state’s population may not be able to extended to immigrants and other minority communities.. Finally, there is the possibility of recall bias for our participants. Our goal was to recruit patients that were diagnosed prior to shutdowns during the COVID-19 pandemic, when typical pathways to care were altered. Thus, we interviewed patients who were potentially, by the time of interview, 1 year from their initial diagnosis to avoid confounding from the impact of COVID-19 on care pathways.
In a qualitative research study of patients with suspected or confirmed early-stage non-small cell lung cancer, we identified several themes from the patient perspective that may act as barriers and/or facilitators to lung cancer care, specifically the importance of patient-provider relationships, good communication, and advocacy as well as coordinated systems to navigate social, financial, and other barriers. The use of open ended interviews provided insight into the patients’ lived experiences that are not apparent in typical large database analyses. These factors need to be addressed to improve quality of care among lung cancer patients. Further work will examine our findings in a community setting to understand if our findings are generalizable to patients who do not access a tertiary cancer care center.
Author contribution
All authors contributed to the study conception and design. Material preparation and data collection were performed by Joshua Herb and Hannah Friedman. Analysis was performed by Joshua Herb, Gita Mody, and Hannah Friedman. The first draft of the manuscript was written by Joshua Herb, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Funding
Dr. Herb was supported by a National Research Service Award Pre-Doctoral/Post-Doctoral Traineeship from the Agency for Healthcare Research and Quality sponsored by the Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Grant No. 5T32 HS000032 during the preparation of this manuscript.
Data availability
Due to the potential for breach of confidentiality, the interview transcripts are not available.
Code availability
N/A.
Declarations
Competing interests
The authors declare no competing interests.
Ethics approval
The study was approved by the institutional review board at the University of North Carolina. This study was performed in line with the Declaration of Helsinki.
Conflict of interest
The authors declare no competing interests.
Informed consent
The study was approved by the institutional review board at the University of North Carolina (IRB #20–1319 – Initial approval 8/25/2020), and informed consent was obtained from all participants.
Consent to participate
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.
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| 36513843 | PMC9747538 | NO-CC CODE | 2022-12-15 23:22:01 | no | Support Care Cancer. 2023 Dec 14; 31(1):21 | utf-8 | Support Care Cancer | 2,022 | 10.1007/s00520-022-07465-w | oa_other |
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Neuropsychiatric symptoms affect most patients with dementia over the course of the disease. They include a wide variety of symptoms from apathy and depression to psychosis, irritability, impulsivity and agitation. These symptoms are associated with significant distress to the patient and caregivers, as well as more rapid progression of dementia, institutionalisation and higher mortality. The first-line management of the neuropsychiatric symptoms of dementia should be non-pharmacological. If medications are required, antipsychotics are commonly chosen. Second-generation antipsychotics such as risperidone, olanzapine, quetiapine and aripiprazole are prescribed more often than first-generation antipsychotics, such as haloperidol. The aim of this review is to provide an update on findings on adverse outcomes and clinical implications of antipsychotic use in dementia. These medications may increase mortality and can be associated with adverse events including pneumonia, cerebrovascular events, parkinsonian symptoms or higher rates of venous thromboembolism. Risks related to antipsychotic use in dementia are moderated by a number of modifiable and non-modifiable factors such as co-prescribing of other medications, medical and psychiatric co-morbidities, and demographics such as age and sex, making individualised treatment decisions challenging. Antipsychotics have further been associated with an increased risk of reliance on long-term care and institutionalisation, and they might not be cost-effective for healthcare systems. Many of these risks can potentially be mitigated by close physical health monitoring of antipsychotic treatment, as well as early withdrawal of pharmacotherapy when clinically possible.
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pmcKey Points
Despite limited efficacy, antipsychotics are the most extensively studied pharmacological treatment for the neuropsychiatric symptoms of dementia.
Antipsychotic use in dementia is associated with the risk of various adverse outcomes ranging from sedation to cerebrovascular events and even death, as well as an increased rate of hospitalisations and institutionalisation.
These risks are moderated by a number of modifiable and non-modifiable factors making individualised treatment decisions challenging.
Introduction
Dementia is a chronic, progressive and incurable syndrome that leads to cognitive and functional decline exceeding that of the natural aging process. The World Health Organization estimates that over 55 million people worldwide live with dementia [1]. That number is growing, and it is predicted that by the year 2050, 132 million people worldwide will be affected [2].
Dementia care requires significant financial expenditure. In 2015 it was estimated to be US$818 billion—the equivalent of 1.1% of the world gross domestic product. Given the predicted increase in dementia cases, this figure is also expected to rise significantly [2]. This increase in prevalence and financial burden, alongside the fact that there is currently no preventative or curative treatment, highlights a global need for effective management of cognitive symptoms, as well as psychiatric and somatic co-morbidities.
Dementia is not only associated with cognitive decline but also with a range of neuropsychiatric symptoms often referred to as behavioural and psychological symptoms of dementia (BPSD) [3]. These require a different management approach to the cognitive decline. Over the course of dementia, 97% of patients experience one or more symptoms of BPSD [4]; the most common is apathy, affecting nearly half of the patients, and other neuropsychiatric symptoms include depression, agitation/aggression, anxiety, sleep disturbances, irritability, changes in appetite, abnormal motor behaviours, delusions, disinhibition and hallucinations [5]. Neuropsychiatric symptoms can cause significant distress to both patients and their caregivers. They are associated with negative outcomes such as functional impairment, dependence on others for support with their activities of daily living and faster cognitive decline leading to advanced dementia, which is associated with further complications like falls, hospitalisations and early institutionalisation [6, 7].
The aetiology of neuropsychiatric symptoms in dementia is multifactorial. Genetic, biological, psychological, social and neuroinflammatory factors have all been suggested to play a role [6, 8, 9]. Neurodegenerative processes of dementia can affect areas of the brain responsible for cognition and emotions. This leads to the breakdown of brain circuitry affecting a person’s ability to interact with their environment, making the patients more vulnerable to internal and external stressors, which, in turn, can affect their functioning, interactions with carers, and manifest as behavioural disturbance [4].
Antipsychotics are commonly prescribed to support the management of agitation and psychosis in dementia, although their use comes with certain risks. In 2005 and 2008 the US Food and Drug Administration (FDA) issued a black box warning due to increased mortality and cerebrovascular events (CVEs) in older adults taking first- and second-generation antipsychotic medications. There are, therefore, no antipsychotics licensed in the USA for the management of agitation and psychosis in dementia [10], while the UK’s National Institute for Health and Care Excellence (NICE) recommends their use only after a thorough assessment of risks and benefits, highlighting that in BPSD, the majority of antipsychotics are used off-label [11].
This narrative review aims to provide an update on the adverse outcomes of the use of antipsychotics in older adults living with dementia and the clinical implications of their use. The authors searched the PubMed MEDLINE database with the terms ‘dementia OR Alzheimer OR Lewy bodies’ and ‘antipsychotic OR antipsychotics’ and ‘side effects OR adverse effects OR adverse outcomes’ for articles published over the last 11 years (July 2011 to July 2022). This 11-year time frame was chosen as studies prior to this period have already been comprehensively reviewed [12–14]. The initial search yielded 796 results. These were reviewed for relevance and cross-references were scrutinized. Articles were included if they studied populations with dementia, use of antipsychotics, adverse treatment outcomes and their clinical implications. Selected articles included randomised controlled trials and observational studies with qualitative outcome measures, as well as reviews, systematic reviews and meta-analyses published within the given timeframe. Excluded were case reports and series, as well as studies without focus on dementia, antipsychotics or their adverse outcomes.
Antipsychotic Medications Used in Dementia
Despite evidence of only a small effect size [3, 4, 10, 15–20], antipsychotics are often the first-line pharmacological treatment for agitation and psychosis in dementia [16]. Although the numbers may vary between countries and patient groups, nearly one in five patients in a 2011–2013 Swedish study on nursing home dementia patients was prescribed an antipsychotic [21]. Data from the UK show that during the first months of the COVID-19 pandemic (March–June 2020), rates of antipsychotic prescriptions increased [22, 23], which may have been associated with changes in routines of the patients, social isolation, or changes in mental health and social services provision. The reduction of face-to-face contact may have further limited the possibility of implementing non-pharmacological interventions.
The second-generation antipsychotic (SGA) risperidone is most commonly prescribed for agitation (40% of patients in a Danish register study [24]) and has been licensed for use in Europe, Canada, New Zealand and Australia for the management of agitation and aggression in dementia [25]. Other antipsychotics used in clinical practice include olanzapine, aripiprazole, quetiapine (SGAs) and, less commonly, haloperidol, a first-generation antipsychotic (FGA). There are some significant pharmacodynamic differences between FGAs and SGAs. FGAs (e.g., haloperidol, zuclopenthixol, flupenthixol, chlorpromazine) act primarily as antagonists of D2 receptors in the brain; this mechanism of action has proven highly effective in managing symptoms of psychosis by acting on the D2 receptors in the mesolimbic system. However, the D2 antagonism of FGAs in other dopaminergic pathways causes side effects, such as extrapyramidal symptoms, emotional numbing and hyperprolactinaemia. SGAs are a more pharmacodynamically diverse group; although SGAs also act on D2 receptors to some degree, different substances from this group present unique receptor profiles including dopamine, histamine, serotonin, muscarinic and adrenergic receptors. Such wide receptor binding properties come with a lower risk of dopaminergic side effects, but are often associated with weight gain, abnormalities in blood glucose and lipid profile, as well as sedation. Additionally, FGAs and many SGAs have been linked to the QTc prolongation on ECG due to interactions with cardiac potassium channels [26, 27].
A 2019 network meta-analysis of placebo-controlled trials with aripiprazole, risperidone, quetiapine and olanzapine use in patients with agitation and psychosis in dementia demonstrated no significant difference between these medications with regard to their clinical effectiveness and adverse outcomes such as death or CVEs [25]. Other studies investigating these antipsychotics have had inconsistent results. In comparison with placebo, olanzapine has not shown effectiveness in improving scores of the Neuropsychiatric Inventory (NPI), Brief Psychiatric Rating Scale (BPRS) or Cohen-Mansfield Agitation Inventory (CMAI) [25]. Findings on the effectiveness of quetiapine have been variable, with one study reporting a statistically significant improvement in BPRS scores [25], whilst other studies found it ineffective [10, 28, 29]. A 2021 systematic review on the use of antipsychotics in dementia found no beneficial effect of quetiapine on agitation and psychosis, and only minimal benefit of use of risperidone for agitation, but not psychosis, when compared to placebo [20]. Risperidone has shown improvement in CMAI scores, focused on agitation, but not in BPRS, which looks at a wider scope of psychiatric symptoms [25, 28]. For SGAs as a group, there is evidence of only a slight reduction of agitation and negligible effect on improving psychosis [20]. Aripiprazole has been found to be ineffective in improving psychotic symptoms of dementia in a 2022 network meta-analysis using the NPI [29]; however, the previous version of this meta-analysis, which assessed outcomes on both psychosis and agitation, reported slight improvement of symptoms in the NPI [25].
Two newer antipsychotic agents have also been evaluated for their efficacy in agitation and psychosis in dementia. Brexpiprazole, a D2–D3 and 5-HT1A partial agonist and 5-HT2A antagonist, has shown a modest therapeutic effect on agitation in patients with Alzheimer’s dementia (AD) during 12-week trials [30, 31]. However, it was associated with frequent side effects such as headaches, insomnia, dizziness, urinary tract infections and somnolence. No significant differences were found for extrapyramidal side effects, suicidality, QT interval prolongation or metabolic side effects, including weight gain, when compared to placebo. Overall, longer observations are necessary to determine whether brexpiprazole is a safer option than the commonly used SGAs.
Pimavanserin (a selective 5-HT2A inverse agonist) is another potential alternative. The FDA has approved it for treatment of psychotic symptoms in patients with dementia and Parkinson’s disease, although it has not been approved in Europe [32, 33]. Pimavanserin may be effective in treating hallucinations and delusions in patients with AD; however, it has no effect on symptoms of BPSD such as apathy, agitation, aggression or disinhibition [34]. A placebo-controlled trial involving 181 nursing home residents with severe dementia [32, 34] reported encouraging short-term results in managing AD-related psychosis, in particular for the more severe subgroup (psychosis score ≥ 12 in Neuropsychiatric Inventory Nursing Home version (NPI-NH)). After 6 weeks of follow-up, 66.7% of patients on pimavanserin 34 mg daily achieved significant NPI-NH psychosis score reductions to less than 6 points, compared to only 32% of placebo controls. After 12 weeks of follow-up, however, 45.5% of both pimavanserin and placebo-treated patients had an NPI-NH score < 6. It is important to note that the incidence of adverse outcomes (such as falls, urinary tract infection, agitation, contusion, aggression or lower respiratory infection) in both groups were similar for placebo and active treatment arms, suggesting good tolerability of pimavanserin in patients with severe dementia [34]. Pimavanserin was further shown to reduce the risk of relapse of psychotic symptoms in a discontinuation trial including patients with dementia-related psychosis, whereby 13% of patients on pimavanserin relapsed versus 28% of those who were switched to placebo after the initial remission of symptoms [35]. This trial was, however, stopped early for efficacy. A longer observation period could have altered the relapse rates in both arms of the trial. Additionally, among the study participants, 15% had Parkinson’s disease, which is not representative of the dementia population. This could have skewed the results in pimavanserin’s favour, given that it has proven efficacy in treating Parkinson’s disease-related psychosis.
Antipsychotic-Related Mortality Risks and its Determinants
The use of antipsychotics in people with dementia is associated with increased all-cause mortality [7, 36–38] and stroke-specific mortality [7]. When compared to monotherapy with other psychotropics, antipsychotics have been found to increase short- and long-term mortality nearly twofold [39].
Type of Antipsychotic and Mortality
FGAs are considered to have a higher mortality risk than SGAs [18], although, Mühlbauer et al. found in their systematic review that the difference in risk between FGAs and SGAs may be smaller than expected, with the relative risk (RR) of death being 1.46 for FGAs and 1.36 for SGAs [20]. Studies on FGAs have been predominantly focused on haloperidol, and there is little evidence of the benefits or harm of other typical antipsychotics. There are certain discrepancies in findings on mortality risk and haloperidol—the above-mentioned work by Mühlbauer et al. found a risk ratio (RR) of 1.88 with 95% confidence interval (CI) 0.65–5.88 suggesting no difference in mortality among older adults with dementia compared to placebo [20], while Ralph et al.’s meta-analysis reported a significant increase of mortality with a hazard ratio (HR) of 2.43 and 95% CI 2.25–2.61 [36]. This has been supported by other studies that found haloperidol to increase mortality compared to placebo [40] and other antipsychotics [18, 36, 39, 41, 42] (HR = 1.71 [36]). The discrepancy may be due to differences in studies included in both metanalyses—Mühlbauer et al. [20] collected data from randomised controlled trials, while Ralph et al. [36] also included information from European databases. One study comparing mortality for patients on FGAs and SGAs found that FGAs were associated with higher mortality due to stroke (6.7%, RR = 1.4), hip fracture (6.6%, RR = 1.3), myocardial infarction (3.5%, RR = 1.2), and ventricular arrhythmia (0.9%, RR = 1.1) [42]. It has, therefore, been concluded that it should be reserved for emergencies and delirium only [18].
SGAs have been found to increase mortality compared to placebo with a number needed to harm (NNH) of 73 [43]. There appears to be no difference in mortality between individually studied antipsychotics [25, 43], but the estimated mortality odds ratio was found to be the highest for olanzapine, followed by quetiapine, aripiprazole and risperidone [43]. Conversely, a case-control study by Maust et al. showed differences in NNH between risperidone (NNH = 27), olanzapine (NNH = 40), quetiapine (NNH = 50) as well as the FGA haloperidol (NNH = 26) [40].
Co-Prescribing of Other Medications and Antipsychotic-Related Mortality
A 2016 meta-analysis of all trials conducted with risperidone in people with dementia showed that co-prescribing of risperidone with anti-inflammatory medications increases risperidone versus placebo mortality risk [44]. Co-prescription of antipsychotics in patients taking antihypertensives, lipid-lowering drugs and antidiabetics including insulin may increase cardiovascular mortality, but is also associated with decreased risk of dying of cancer and infection [24]. Interactions between antipsychotics and other medications (such as antidepressants, opioids, benzodiazepines or cardiological medications) have also been shown to increase mortality among older adults with dementia [24, 45], and this risk increases with the number of interactions (one interaction: HR = 1.68; two or more interactions: HR = 1.96) [45]. The most common interactions are between antipsychotics (risperidone, tiapride and less commonly olanzapine) and cardiological medications (diuretics, beta-blockers, angiotensin-converting enzyme inhibitors, and less commonly calcium antagonists) resulting in decreased blood pressure and falls. Interactions with other psychotropic medications (benzodiazepines, opioids, antidepressants, carbamazepine) may lead to QT prolongation, sedation, cytochrome P450 inhibition and less commonly to anticholinergic effects, seizures and agranulocytosis [45]. Conditions pre-existing dementia, such as diabetes, heart disease and cerebrovascular disease, independently increase the mortality risk for patients taking antipsychotics in an additive manner [38].
It has been further demonstrated that patients with neuropsychiatric symptoms of dementia and co-morbid depression, have lower mortality when taking risperidone in monotherapy, compared to placebo[44]. Although this finding is not consistent—a Danish study by Nielsen et al. on a population of nearly 46,000 dementia patients found that those on various antipsychotics (most prescribed were risperidone, olanzapine, quetiapine, haloperidol, zuclopenthixol and chlorprothixene) with co-morbid psychiatric diagnoses, including depression, and/or somatic co-morbidities, have an increased risk of dying of infection, cardiovascular events and cancers, but not of intentional self-harm [24].
Although the exact mechanisms behind antipsychotic adverse effects are not known, there is evidence of risperidone interacting with immune and cardiac pathways, including selenium, on a cellular level [46, 47]. This highlights the importance of cardiovascular history screening and possible selenium deficiency screening.
Other Antipsychotic-Related Factors and Mortality
There is no consensus on how long the risk of adverse outcomes is increased for those patients, with data ranging from short- [36, 39, 42] to long-term [6, 15, 39]. Mortality may be the highest at the beginning of treatment. In line with previous research [40, 48], one retrospective cohort study demonstrated more than twofold increased mortality risk for antipsychotic initiators versus non-users in the first month of treatment, and significantly lower risks after 3 months (HR = 1.52) and 6 months (HR = 1.24) of follow-up [49]. The same study reported a higher mortality risk for robust versus frail (i.e., low Frailty Index scores) patients on antipsychotics at all three time points. This counterintuitive finding might potentially be related to differences in baseline mortality risks of the evaluated cohorts. Other therapy-independent factors increasing the mortality risk are male sex, younger age at dementia diagnosis, as well as more severe dementia symptoms [24]. Factors increasing antipsychotic-related mortality are summarised in Table 1.Table 1 Factors increasing antipsychotic-related mortality
Male sex [24]
Younger age at dementia diagnosis [24]
Severe dementia symptoms [24]
Robust build (low Frailty Index scores)a [49]
Number of co-morbid somatic conditions (cardiovascular, cancer, infection, diabetes, epilepsy, lower respiratory disease and others) [24, 38]
Co-morbid psychiatric conditions (psychosis, affective disorders, substance misuse, history of self-harm, and others)[24]
Depression co-morbid with agitation or psychosis was associated with lower mortality in risperidone monotherapy [44]
Polypharmacotherapy and drug interactions
– Anti-inflammatory medications, diuretics, ACE-inhibitors, beta-blockers, calcium-blockers, antidepressants, opioids, sedative agents, carbamazepine—all-cause/unspecified mortality [24, 44, 45]
– Antihypertensives, lipid-lowering drugs and antidiabetics including insulin—cardiovascular mortality (protective for death from cancer and infections) [24]
aBased on a retrospective cohort study with potential limitations [49]
ACE-inhibitor angiotensin-converting enzyme inhibitor, FGA first-generation antipsychotic, SGA second-generation antipsychotic
Other Antipsychotic-Related Adverse Events and Their Determinants
Unlike evidence for antipsychotic-related mortality, findings on other adverse outcomes are less consistent and detailed data on the relationship between individual medications, types of dementia and outcomes are often sparse (Table 2).Table 2 Adverse outcomes of antipsychotics use in dementia patients
Consistent findings Inconsistent findings
Cerebrovascular events [6, 7, 25, 28, 29, 50–53]
Pneumonia [6, 54]
Parkinsonian symptomsa [6, 25, 54]
Gait disturbance [6]
Sedation [6, 25, 54]
Venous thromboembolisms [6, 51]
Head injuries and traumatic brain injuriesb [60]
Increased mortality risk [20]
Accelerated cognitive declinec [58]
Cardiac events [51, 52]
Fractures [29, 50, 51, 57]
Fallsd
aWith use of risperidone, but not olanzapine, aripiprazole and quetiapine
bLimited amount of evidence, this outcome is not included in meta-analyses
cPlease note that presence of neuropsychiatric symptoms of dementia can also accelerate cognitive decline[6]
dReports of increased risk [56], no association [28, 50] and reduced risk (for risperidone) [25]
One consistent finding appears to be the association between the use of antipsychotics and CVEs, such as stroke and transient ischaemic attack [6, 7, 25, 28, 29, 50–53]. As a group, they have been found to increase the odds over twofold [50]. Particular agents implicated in an increased risk of CVE are risperidone and olanzapine, while quetiapine and aripiprazole carry risks similar to placebo [25, 28]. The relationship between antipsychotic use and CVE risk is complex and not yet fully understood. Koponen et al. found that the risk of stroke is increased within the first 60 days of use (HR = 2.61), but no significant increase was found after the follow-up period of 265 days [53]. One large naturalistic study on over 10,000 patients with dementia has shown different outcomes depending on whether the antipsychotic (FGA or SGA) was prescribed for psychosis and/or agitation, with an over twofold increased antipsychotic-related risk of CVEs for patients with dementia and psychosis but no agitation (HR = 2.16) [7]. The antipsychotic-related CVE risk was not increased in the patient group with agitation but no psychosis (HR = 1.10), or the group with agitation and psychosis (HR = 0.97). It has been hypothesised that tau protein may be linked to psychotic symptoms in AD as well as a toxic response to reduced brain perfusion, making patients suffering from antipsychotic-related sedation, dehydration or orthostatic hypotension more vulnerable to CVE. Psychosis in dementia is also linked to more advanced small vessel disease and cerebral amyloid angiopathy [7].
Other adverse outcomes associated with antipsychotic use in dementia include risk of extrapyramidal side effects including gait disturbance (with use of FGAs and risperidone, but less commonly olanzapine, aripiprazole, and quetiapine), sedation, venous thromboembolism, and pneumonia [6, 25, 51, 54]. Antipsychotics may be associated with pneumonia due to their effects on D2, cholinergic and histamine receptors, leading to dysphagia (extrapyramidal side effect), sedation, involuntary buccolingual movements (a common symptom of tardive dyskinesia), and xerostomia; all of these factors, combined with changes in pulmonary secretion in older adults may increase the risk of pneumonia [54]. Movement side effects also play an important role in an increased risk of venous thromboembolism events that include deep vein thrombosis and pulmonary embolism—nigrostriatal D2 receptor blockage causing muscle stiffness may lead to physical inactivity, akinesia [55] and prolonged time spent in bed. This, in addition to antipsychotic-related enhanced platelet aggregation and raised anticardiolipin antibodies, promotes blood clot formation [51]. Findings on increased risk of cardiac events, falls and fractures have been variable [25, 28, 29, 50–52, 56, 57]. In case of falls, evidence from four meta-analyses published between 2018 and 2020 vary significantly, with reports of increased risk of falls [56], no association with antipsychotics as a group [50] or individually for haloperidol, olanzapine, quetiapine and risperidone[28], to a reduced risk of falls with risperidone [25].
Dyer et al. found that being prescribed antipsychotics is linked to an accelerated cognitive decline among community-dwelling patients with mild to moderate AD (β coef: 3.89 after 18 months), with the risk even greater for APOE ε4 allele carriers (β coef: 4.96 after 18 months) [58]. Given that neuropsychiatric symptoms of dementia are also associated with more rapid cognitive decline [6] and are proportionate with the severity of AD [59], balancing the risk may complicate clinical decision making. Dyer et al. [58] highlighted, however, that in their study only half of the dementia participants were coded to have BPSD, and those with significant BPSD were excluded from the study.
One large cohort study looked at the association between antipsychotics and head injuries/ traumatic brain injuries [60]. The study reported an increased risk of head injuries among antipsychotic users compared to non-users, with the highest risk during the first 3 months of treatment. Quetiapine users had a higher rate of head injuries than risperidone users, which was attributed to quetiapine being more sedative and having a higher risk of orthostatic hypotension leading to falls.
Little is known about adverse outcomes risk in various types of dementia; however, there is evidence that patients with dementia with Lewy bodies (DLB) or frontotemporal degeneration (FTD) are at even higher risk of antipsychotic side effects. Due to neuroleptic hypersensitivity, DLB patients are more susceptible to extrapyramidal side effects, and in some cases have been associated with irreversible cognitive decline and death. In these patients FGAs are contraindicated, and SGAs such as olanzapine, risperidone and aripiprazole should be avoided due to their potential to worsen motor symptoms. With caution, quetiapine and clozapine can be used [18]. Reviews of literature focused on the management of psychosis in DLB and Parkinson’s disease dementia [61, 62] report positive treatment results using acetylcholinesterase inhibitors and pimavanserin. A 2014 randomised controlled trial on pimavanserin in Parkinson’s disease patients with psychotic symptoms showed favourable clinical outcomes (37% improvement of symptoms in the pimavanserin arm vs. 14% in the placebo arm) without exacerbation of motor symptoms or sedation [63].
The evidence is also scarce for antipsychotic use in patients with FTD other than increased sensitivity to antipsychotics side effects [18], therefore a reasonable solution may be to follow a similar treatment pathway to that for DLB. Although no specific titration or monitoring recommendations for DLB and FTD patients have been published, in these patient groups it is especially important to observe the “start low, go slow” rule.
There has also been limited information on the efficacy and safety of antipsychotics in dementia patients with functional impairment and BPSD. A 2022 systematic review looking into this specific group of patients concluded that due to lack of evidence, no specific treatment recommendations can be made [19].
Finally, the older population remains at a higher risk of the general side effects of antipsychotics due to pharmacokinetic and pharmacodynamic age-related changes such as reduced renal and hepatic clearance and first-pass metabolism, a smaller volume of distribution for hydrophilic medication, and increased risk for lipophilic drugs causing prolonged elimination of some medications. Receptors’ sensitivity to medication can also be altered with progressing age. All of these natural ageing processes make dementia patients more susceptible to side effects such as QT prolongation, weight gain and metabolic syndrome, anticholinergic effects, seizures or orthostatic hypotension [55, 64].
Associations of Adverse Effects of Antipsychotic Medications with Health Service Outcomes
Hospital Treatment
Medications’ adverse outcomes are associated with emergency department presentations, with older adults being three times more likely than younger patients to visit the emergency department due to adverse drug events [65]. Among older adults, those with AD have a higher proportion of visits associated with psychotropic-related adverse drug events compared to non-AD patients (1.04% and 0.43%, respectively). These are mostly associated with antipsychotics and benzodiazepines. Patients with AD seen in the emergency department with psychotropic medication-related adverse events are more likely to be subsequently admitted to hospital compared to non-AD patients. Once admitted, AD patients have on average longer hospitalisations and higher in-hospital mortality [65]. Zakarias et al. have also reported a 55% increase in hospitalisations for patients co-prescribed antipsychotics and benzodiazepines in comparison to antipsychotic monotherapy, but no increase was found for co-prescription of antipsychotics with antidepressants [57]. This study did not, however, investigate the hospitalisation rates of patients not being prescribed antipsychotics.
A Finnish study on AD patients with a 2-year follow-up found that the antipsychotic group (mean age 81.5 years) had spent more days in the hospital compared to the non-antipsychotic group (15 vs. 7 days, respectively) [66]. In this study population, significantly more of the non-antipsychotic group had no hospitalisations at all compared to those on antipsychotics. The antipsychotic group had higher rates of admissions with diagnostic codes for dementia, mental and behavioural disorders, diseases of respiratory, genitourinary and cardiovascular systems, and certain infections. In the as-treated analysis, patients on antipsychotics had more inpatient days due to injuries and poisonings. Seventy percent of the antipsychotic group had caregivers’ care breaks recorded as an additional reason for admission.
Long-Term Care and Institutionalisation
Another concern for patients with dementia is their dependence on long-term care, including admission to a nursing home. There is evidence that treatment with antipsychotic medications significantly increases the risk of reliance on long-term care and institutionalisation. A twofold risk of long-term care dependency has been reported for patients receiving risperidone, melperone, haloperidol or other FGAs in 18-month follow-up; the risk for quetiapine was slightly lower. The rate of nursing home admissions was increased for those taking quetiapine, risperidone, melperone, haloperidol and other FGAs. Other studied SGAs (amisulpride, zotepine, ziprasidone, aripiprazole, sertindole, olanzapine and clozapine) have not been shown to increase the risk of long-term care dependency or nursing home admission [67].
Cost-Effectiveness of Treatment
Huo et al. conducted a systematic review of the cost-effectiveness of pharmacotherapy in persons with dementia [68]. They concluded that neither antipsychotics nor antidepressants, which are commonly used to treat neuropsychiatric symptoms of dementia, were associated with lower healthcare cost. This raises further questions about the rationale for antipsychotic use in older adults with dementia. It is important to note that these findings are based on just two studies that investigated the cost-effectiveness of antipsychotics and antidepressants, published in 2007 and 2013. Given the worldwide economic and healthcare changes since that time, new studies on cost-effectiveness are needed. The health service outcomes are summarised in Table 3.Table 3 Antipsychotic-related health service outcomes
AD patients have more emergency department visits due to medication adverse events than non-AD patients and are more likely to be admitted to the hospital [65]
AD patients with adverse drug events have longer hospitalisations and higher in-hospital mortality compared to non-AD patients [65] and patients who do not take antipsychotics [66]
Co-prescribing benzodiazepines and antipsychotics significantly increases hospitalisation rates compared to antipsychotic monotherapy [57]
Dementia patients taking antipsychotics have higher rates of hospital admissions with infections, diseases of respiratory, genitourinary and cardiovascular systems, as well as mental and behavioural disorders [66]
Treatment with antipsychotics may increase the risk of reliance on long-term care and institutionalisation for patients with dementia [67]
Treatment with antipsychotics does not reduce healthcare costs [68]
AD Alzheimer’s disease
Implications of Antipsychotic Prescribing Practices in People with Dementia
Management of neuropsychiatric symptoms remains one of the main challenges in the treatment of older adults with dementia. Symptoms such as agitation, aggression, impulsivity and irritability are commonly managed with antipsychotics, although it is recommended to explore non-pharmacological interventions and pain management [69] first. Non-pharmacological treatment for BPSD is often referred to as the “eco-bio-psycho-social” approach [4]. Important aspects of this approach are to reduce under- or overstimulation in a person’s environment, re-orientate them to the time, place and circumstances, and build meaningful relationships. Use of reminiscence therapy (bringing back positive memories from the past), validation therapy, aromatherapy, Snoezelen (soothing and stimulating surroundings), and acupuncture are other suggested techniques [4, 70, 71]. Similar to studies on medications, research on the non-pharmacological treatment of BPSD does not provide a clear answer on the single best approach, its choice or implementation. It is often left to individual considerations and preferences of caregivers [4, 71, 72]. Various psychotropic medications have been studied to address the neuropsychiatric symptoms of dementia, including antipsychotics, antidepressants, anticonvulsants (often used as mood stabilizers in psychiatry), benzodiazepines, acetylcholinesterase inhibitors, memantine, dextromethorphan with quinidine, prazosin, cannabinoids and buspirone; however, none of these are considered both safe and effective in addressing agitation and psychotic symptoms in dementia. Although evidence for therapeutic benefits exists for selective serotonin-reuptake inhibitors (SSRIs) and antipsychotics, they address different neuropsychiatric symptoms, and evidence for SSRIs has been inconsistent. A 2011 Cochrane Systematic Review by Seitz et al. on the use of antidepressants for agitation in dementia reported that of five studies comparing SSRIs to placebo, only two showed a reduction of symptoms with use of sertraline and citalopram [73]. Notably, one study included in that review compared the use of citalopram and risperidone and found no difference between these agents in Neurobehavioural Rating Scale scores. A 2018 meta-analysis [74] found that the effectiveness of risperidone and SSRIs versus placebo are comparable (OR 1.96 and 1.61, respectively).
Based on our literature review, there seems to be no single antipsychotic that is considered both safe and effective for the management of agitation and psychosis in dementia (Table 4, “take home messages”). Data on the risk of those serious consequences of treatment are often contradictory [10, 25, 28]. Due to the side effect profiles and mortality risk, many authors recommend using SGAs over FGAs [6, 18, 39, 41, 42, 51, 54]; however, the growing evidence suggests that the difference between these groups may be less significant than previously believed [20]. Clinicians must take an individual approach to prescribing, weighing up potential benefits and risks of individual medications in the context of the patient’s symptoms, circumstances, prescribed medications and co-morbidities. Such a nuanced approach might reduce the risk; however, formal evidence to support decision-making is scarce [18, 25, 28, 50–52]. Antipsychotic use in older adults with dementia is associated with an increased risk of significant adverse events such as stroke or transient ischaemic attacks, venous thromboembolism, pneumonia, head and brain injuries, as well as death. SGAs are also closely related to the risk of metabolic syndrome and cardiovascular risk. Their use, alongside the presence of a severe mental illness, has been included in the QRISK®3 algorithm used in the UK to estimate the 10-year risk of heart attack or stroke. It has been shown that the use of SGAs is associated with a 29% increased cardiovascular risk in women and 15% in men compared to the general population [75]. Although these numbers do not directly refer to the dementia population, they highlight the additional risk for the vulnerable old age group. On the other hand, the neuropsychiatric symptoms of dementia—agitation, depression and psychosis in particular—are associated with rapid dementia progression, institutionalisation and increased mortality [76, 77], therefore, they need to be effectively managed to improve outcomes for the patients.Table 4 Take-home messages on the implications of adverse outcomes associated with antipsychotics in older patients with dementia
The use of antipsychotics in older adults with dementia can reduce agitation, psychosis, and associated distress; however, no medication is considered safe in this population
Antipsychotics are generally associated with an increased risk of mortality and cerebrovascular events
Due to slightly higher risk of mortality and cardiovascular and extrapyramidal side effects compared to second-generation antipsychotics, first-generation antipsychotics should be reserved for emergencies
Antipsychotic-related mortality may be higher at the beginning of treatment, hence a thorough risk-benefit assessment including cardiovascular risk should be conducted before commencing these medications
The risk does, however, remain increased throughout the treatment (evidence for up to 6 years [39]); the need for continuation of antipsychotics should be regularly reviewed and medication ceased as soon as possible. Withdrawing antipsychotic therapy may improve long-term survival and is not associated with relapse of agitation and psychosis
Antipsychotic treatment is associated with higher rates of hospitalisations and dependency on long-term care, including care home admissions
Use of antipsychotics may not be cost-efficient for healthcare systems
Treatment with antipsychotics requires physical health monitoring. In the absence of dementia-specific monitoring requirements, older adults with dementia should follow the same recommendations as the general patient population
Despite the clear risks of using antipsychotics in dementia patients, their risk-benefit balance makes them preferable to other psychotropic medications
Importantly, there is no safe time frame for use of antipsychotics in older adults with dementia—both short-term and long-term prescriptions are potentially harmful [6, 15, 24, 36, 37, 39, 42]. A 2018 systematic review concluded that antipsychotic treatment may be successfully discontinued with little to no difference to overall neuropsychiatric symptoms, adverse events, quality of life and cognitive function. Due to limited data, the effect of discontinuation on mortality could not be established [78].
Regular physical health monitoring may be one of the ways to reduce the risk of adverse events and mortality. The UK’s NICE recommends regular checks of body weight, pulse, blood pressure, ECG (with QTc assessment), screening for the presence of movement disorders, as well as blood tests including full blood count, electrolytes and kidney function tests, liver function tests, lipid profile, HbA1c/blood glucose, and prolactin. Notably, monitoring is more frequent at the beginning of treatment with weekly weight checks over the first 6 weeks, blood test panels, weight check and lifestyle review after the initial 3 months of treatment, and then annually [79]. This guidance has, however, been created for adult patients; older adults may require closer monitoring, depending on individual needs and at the clinician’s discretion. Although there have been multiple studies into the benefits and risks of the use of antipsychotics in dementia patients, there are no validated tools supporting individual decision making, which is an important research area to be explored.
Declarations
Conflict of interest
RS has received research support from Janssen, GSK and Takeda. DA has received research support and/or honoraria from Astra-Zeneca, H. Lundbeck, Novartis Pharmaceuticals and GE Health, and serves as a paid consultant for H. Lundbeck and Axovant. CB has received honoraria and grant funding from Acadia Pharmaceuticals, Lundbeck, Takeda and Axovant pharmaceutical companies. CB leads the Alzheimer’s disease psychosis (ADP) investigators group and has received honoraria from Lundbeck, Lilly, Otusaka and Orion pharmaceutical companies. MR, MT, BC, LV, KT and CM declare no conflicts of interest.
Funding
CM, DA and RS receive salary support from the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, and RS is a NIHR Senior Investigator. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.
Code availability
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Ethics approval
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Availability of data and materials
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Author contributions
MR: Review of literature, interpretation of data, preparation of the manuscript, and critical revision for intellectual content. CM: Article concept and design, interpretation of data, and critical revision of the manuscript for intellectual content. BC, LV, DA, CB, KT, RS: Interpretation of data and critical revision of the manuscript for intellectual content. MT: Critical revision for intellectual content, preparation of the manuscript. All authors approved the manuscript to be published and agree to be accountable for all aspects of the work.
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| 36513918 | PMC9747539 | NO-CC CODE | 2022-12-15 23:22:01 | no | Drugs Aging. 2022 Dec 14;:1-12 | utf-8 | Drugs Aging | 2,022 | 10.1007/s40266-022-00992-5 | oa_other |
==== Front
Int J Sociol Leis
International Journal of the Sociology of Leisure
2520-8683
2520-8691
Springer International Publishing Cham
126
10.1007/s41978-022-00126-6
Original Paper
Consolidating Whiteness in Leisure Places: Answering the Call for a Fourth Wave of Race Research in Leisure Studies
http://orcid.org/0000-0001-7018-7753
Petersen Camille [email protected]
1
Chenault Tiffany Gayle 2
1 grid.189504.1 0000 0004 1936 7558 Department of Sociology, Boston University, Boston, MA USA
2 grid.419433.8 0000 0000 8935 1851 Department of Sociology, Salem State University, Salem, MA USA
14 12 2022
124
7 10 2021
28 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.
The fourth wave of leisure studies challenges researchers to investigate the social construction of race through leisure, in contrast to understanding race as a variable. Floyd (2007) challenged us to think about the future challenges and trends around race and ethnicity in leisure studies. Though significant progress has been made since the 1970s, we still have far to go in assessment of race and ethnicity in leisure. The objective of this manuscript is to answer the call made by Floyd for an anticipated fourth wave task of “understand[ing] how leisure practices create, reinforce, and perpetuate racist practices in contemporary America” (2007, 249). We apply a theoretical framework that centers racism and whiteness, drawn from race scholarship across fields: the sociology of race, Critical Race Theory (CRT), whiteness studies, settler colonialism studies, and Black and Native Studies. We apply this framework to investigate the storytelling at two National Park Service (NPS) monuments which we provide as case studies to analyze how spatialized historical storytelling consolidates structural white supremacy in the parks, despite a rhetoric of inclusivity. Only once we understand how racism and white supremacy are embedded in NPS narratives can we begin to make changes to reduce white supremacist storytelling in leisure practice.
Keywords
National Parks
Settler Colonialism
Whiteness
Race
Recreation
Colorblindness
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pmcFourth wave race research in leisure studies starts from a critical understanding of race as a social construction, uses theory to understand leisure in the broader context, and requires methodological innovation to move beyond the methodological formalism that has characterized the bulk of past race and leisure research (Arai & Kivel, 2009; Bramham, 2002; Pinckney et al., 2019). Notwithstanding critiques of the wave metaphor, we argue that it is imperative to revisit this call for research, in light of current events and the continuing significance of racism and White supremacy in not only US society but in locations across the globe. The first three waves of race research in leisure studies focused primarily on participation disparities between White and non-White populations. Floyd (1998) argues that the marginality hypothesis within the ethnicity paradigm is not only insufficient to explain the problem, but asks the wrong questions based on “biased ideological assumptions” (7) privileging Anglo leisure behaviors as the invisible standard. In contrast, race as a primary focus of the investigation only represented five percent of research in the main leisure studies journals (Floyd et al., 2008). Since the 1970s research on race and ethnicity has grown only slightly in leisure studies, compared to other discussions about race and decolonization in other disciplines. Though leisure scholars have called for the study of race, racism, and Whiteness in leisure studies, research that takes race seriously as an object of investigation, rather than a mere variable, has remained minimal (McDonald, 2009); years after initial calls for research in anticipation of a “fourth wave” of critical leisure studies, scholars are asking again (Arai & Kivel, 2009; Mowatt, 2020). Pinckney et al. (2019) calls for the sociology of leisure to engage with what they term race scholarship rather than race studies, which analyzes race as a variable. Race scholarship, as these scholars define it, is to study race as the central phenomenon being examined; this aligns with the key tenet of CRT and the sociological perspective that race pervades every aspect of everyday and institutional life in the United States and is a central axis of power and domination (Christian, 2019; Crenshaw, 1988; Delgado, 1995; Han, 2008; Hylton, 2005).
Americans started spending more time outdoors during the early months of the pandemic, and national parks and other outdoor recreation areas are experiencing record numbers of visitors now that restrictions are lifted (Coren & Kopf, 2020; Jenkins, 2021; National Park Service, 2021a, b, c, d, e; Outdoor Industry Association, 2021; Rott, 2020; Trust for Public Land, 2021). At the same time as Americans headed outdoors, the world became increasingly aware of police brutality and racial inequities, and realities of systemic racism, injustice, and inequity became more visible in the media. In fact, both the outdoor leisure and public health crises are connected through racism —White people enjoy easier, safer, and more abundant access to green space, compounding how non-White people’s health, wealth, and public safety were disproportionately negatively affected by the pandemic (Bailey & Robin Moon, 2020; Bonilla-Silva, 2020; Embrick & Moore, 2020; Feagin, 1991). At the same time, racism is more visible to more people–Black Lives Matter and #sayhername movements have brought racism to a national conversation after the high-profile murders of George Floyd, Breonna Taylor, and Amaud Aubery. The central park bird-watcher Christian Cooper’s experience brought attention to the hostile environment created by thinking of outdoor leisure as a Whites-only enterprise, and to the ways in which ordinary Whites police the boundaries of leisure places using threats of state violence (the police). Politicians have invoked racism at an international scale to deal with the coronavirus crisis as well as issues like immigration– “China virus” comments spurred anti-Asian hate violence and politicized rhetoric about immigration from “shit hole countries'' spawned zealous border patrol violence against Haitian migrants. Organized white nationalist terror is an officially acknowledged internal threat to homeland security, and communities of color are increasingly under attack by lone gunman preaching theories of White supremacy. And yet, despite rising awareness of racism, today’s common sense understanding of race and racism is confused by colorblindness, the progress narrative used by Whites to argue that society has largely recovered from racism, leaving only a few ‘bad apples’ who perpetrate overt racist violence (Bonilla-Silva, 2003). Colorblindness confounds attempts to address inequity and injustice (and thus promote diversity and inclusion) by minimizing or ignoring the structural nature of racism in American culture and institutions (Bonilla-Silva, 2003; Lipsitz, 2019). The colorblind racism characterizing Whiteness includes social practices of “disavowal” (Mills, 2015; Veracini, 2008) and “colonial unknowing” (King, 2016), which function as “settler moves to innocence” (Tuck & Yang, 2012) that foreclose any serious effort to dismantle White supremacy by denying it even exists in the first place.
According to Floyd (2007), "what is not well understood is how leisure practices create, reinforce, and perpetuate racist practices in contemporary society. And can understandings of race and leisure contribute to the formation of social policies designed to foster constructive engagement and goodwill among different racial and ethnic communities?" (pp. 249–250). If leisure researchers and scholars are to meet the challenge of the study of race in leisure studies, per Floyd’s call, there needs to be an application of race scholarship to understand how racist practices are perpetuated in leisure studies and in leisure practice– scholars should shift to studying structural race and racism instead of ethnic and cultural differences, and suggest strategies for leisure practitioners to utilize (Arai & Kivel, 2009; Floyd, 1998; Kivel et al., 2009; Pinckney et al., 2019; Roberts, 2009). Just as it is addressed in the larger society and in social science research, we must become more “deeply engaged in discussions about the history, status, limitations, and potentialities of this subfield and connect the field of race and ethnicity” (Floyd, 2007:247). The concepts of colorblindness and structural racism counter racial progress narratives (Bonilla-Silva, 1997; Feagin, 2006) and incorporate settler colonialism as structure (Glenn, 2015) in the sociology of race, but the subfield remains limited by lack of sustained engagement with Indigenous and world-systems perspectives which account for the intersections of race and colonialism in the foundational politics of this nation and the international order (Christian, 2019; Fenelon, 2016; Magubane, 2016; Murphy, 2021).
We use concepts of White supremacy, Whiteness, and White nationalism drawing from the sociology of race and ethnicity as well as from other disciplines–critical race theory, history, Black feminist theory, Whiteness studies, Black studies and Native Studies have been influential in the way we understand and use these concepts. Researchers can find the concepts used and defined in the same way across those disciplinary frames and the critical scholarship on race, racism, and whiteness spanning more than a century. Classical sociologist W.E.B. Du Bois began a study of Whiteness as such in the early twentieth century, writing that “whiteness is ownership of the earth, forever and ever, amen!” alluding to the role of capitalism, land and religion in socially constructing the land-as-property identity category of “White” which property law professor Cheryl Harris (1993) would decades later conceptualize as literal property for those who could claim it. White supremacy is a necessary ideology for legitimating genocide, slavery, colonialism and settlement, which were state, corporate, community and individual efforts protected and promoted by European and then American law since 15th-century Discovery Doctrine (Dunbar-Ortiz, 2014; Watson, 2005). White supremacy encompasses religious, scientific, legal, biological, and cultural theories of so-called race; the concept of race is a product of White supremacy (Fields & Fields, 2014; Kendi, 2016). White Nationalism is the ideology of settler colonialism that frames the United States as a White country (Bonilla-Silva, 2000), melting pot (Steinberg, 2007), or a nation of immigrants (Dunbar-Ortiz, 2021). Both covert (for example, in historiography) and overt (for example, in violent extremist hate crime and terrorism) expressions of this ideology are built on a foundation of White supremacist settler colonialism. Today, the explicitly stated idea that the US should be a White country drives hysteria about immigration, abortions, and “CRT” as we speak.
Therefore, national parks and monuments in the United States are anything but “pure” leisure spaces, but rather active sites in the construction and reproduction of the racialized social structure. While our findings are based in the context of the United States and are not generalized outside of the US, white supremacy takes different forms around the colonial-modern world system and the fourth wave theoretical framework can be used to investigate the connections between racism and leisure in any place. Leisure can be conceptualized as a power relation embedded in and productive of the broader systems of race and gender, a social practice that functions to legitimate the status quo through emotional experiences of modern ‘selfhood’ or subjectivity (Bramham, 2002; Rojek, 1985). Much the same has been said about touring leisure places as a “performed art” of “worldmaking and self-fashioning” (Adler, 1989). Rojek (1993) argues that monuments and the wilderness are among four key ‘ways of escape’ (including the beach and the hotel) where subjectivity is constructed through leisure. Thus, in these scholarly and national contexts, it is even more important to investigate the social construction of race in leisure spaces that do national historical storytelling. We ask, how do monuments in the National Park Service (NPS), an institution of the federal government, tell the story of the US? How does this storytelling reflect and reproduce racism in leisure places? What does this mean for our understanding of race in leisure places? In this article, we apply critical race theories to make an empirically based theoretical contribution to making race matter in leisure studies (Rubinstein & Mowatt, 2021), contributing to answering the fourth wave call for studies that investigate the social construction of racial categories and perpetuation of racism in leisure spaces.
National Parks Service (NPS): America’s Best Idea
"National parks are the best idea we ever had. Absolutely American, absolutely democratic, they reflect us at our best rather than our worst." Wallace Stegner, 1983
“For the National Park Service, relevancy, diversity and inclusion defines both a value and a practice for connecting the American public to the nation's shared natural and cultural heritage.” (NPS.gov)
In this section, we discuss the importance of National Parks Service (NPS) and monuments in public life and review some of the research on diversity and inclusion in the NPS. National Parks are important leisure destinations, especially during months of quarantine, stress, racial and economic tension, and isolation from COVID-19 that has led many Americans to escape to the national parks for leisure recreation. The national parks have always been a place of refuge as well as providing social, mental, and physical health benefits for all citizens. The national parks are supposed to be open and welcoming to all citizens, as reflected in the above quotes from the National Parks Service webpage. As restrictions have been lifted, more people are visiting the parks than ever before (Coren & Kopf, 2020). Overwhelming, however, the people who visit and benefit from the national parks have been White. African Americans are 13.4% of the population but represent only 2% of national park visitors (Scott & Lee, 2018). According to recent NPS data, overall, 23% of visitors to the parks are non-white. Research and theoretical perspectives have examined the reasons for the absence and constraints of racial minorities in outdoor spaces and national parks, such as economic resources (Scott & Lee, 2018; Stodolska et al., 2014), geography (Weber & Sultana, 2013), cultural and boundary maintenance (Scott & Lee, 2018), access (Shinew et al., 2004; Stodolska, 1998) discrimination and white racial framing (Mott, 2016). The domination of whiteness goes beyond visitors. The NPS is also the least diverse agency in the federal government (Jacobs & Hotakainen, 2020).
According to Mott (2016: 467), “Arguably, the more our national parks incorporate and value minority history, the more minorities will actually want to visit the parks.” New monuments and parks “should attempt to focus on the historical significance of minorities and minority contributions to society and the national park system as a whole.” The agency has made efforts towards racial diversity, equity, and inclusion to parks through their marketing campaign, hiring employees from diverse racial backgrounds, and training around cultural competency and diversity. In 2017, President Obama issued a Presidential Memorandum entitled “Promoting Diversity and Inclusion in Our National Parks, National Forests, and Other Public Lands and Waters (Whitehouse.gov, 2017). The purpose of this memorandum is for “all Americans” to experience and enjoy public lands so that “all segments of the population” can engage in the decisions of the management of the land, and the federal workforce “is drawn from the rich range of the diversity in our nation.” The memorandum further states how the parks are a “powerful sign of our democratic ideals, these lands belong to all Americans – rich and poor, urban and rural, young and old, from all backgrounds, genders, cultures, religious viewpoints, and walks of life.” However, in the years after this memorandum, the National Parks still have a predominately white clientele. The national parks system's emphasis on diversity and inclusion must go beyond visitors, and employees, but also extend to the stories that they tell America.
In regards to diversity and inclusion drives in outdoor recreation, Anderson et al. (2021) argue that it is worth asking “whether this entails diversifying its participant group profile without necessarily reflecting on the design, delivery, or content of its programming, which might reflect and discretely reinforce norms of the hegemonic group” (540), considering ‘the great outdoors’ has historically been a site of White supremacist violence and exploitation (Ho & Chang, 2021; Murphy, 2021; Walter, 2020). Furthermore, the authors argue that these initiatives betray their own hegemonic Whiteness by framing diversity as an invitation to people of color, implicitly assuming the outdoors is theirs to share (Anderson et al., 2021). Accordingly, the National Park Service desires not just diversity and inclusion but relevancy; the NPS seems to see non-White park participation as an instrumental (rather than transformational) path to institutional survival.
The Whiteness of National Parks
In this section, we explore some of the literature on Whiteness and leisure. For leisure studies to effectively engage with racism and Whiteness, researchers must understand how White supremacy fundamentally structures Whiteness, rather than using individualistic 'White privilege' as the central analytic (Mowatt, 2020; Pulido, 2015). This broader conceptualization of Whiteness as a "social formation to ensure authority and legitimacy" (Mowatt, 2020: 3) beyond mere 'privilege' frames our understanding of the role of leisure places and practices as sites for the construction of White identity based on dominance. Research on Whiteness in leisure studies investigates how power operates through leisure space and practice, in contrast to approaches which obscure the historical and structural nature of racism in favor of class explanations (Rojek, 1985), ethnicity and marginality paradigms (Floyd, 1998), or a race as a taken-for-granted variable (Pinckney et al., 2019). For example, Ho and Chang (2021) explain that Whiteness “refers to a social construct of racial hierarchy as part of the settler colonial structure, and the institutions of power that structure social relations…thus instituting an order that constructs and perpetuates race as an integral part of its function.” McDonald (2009) emphasizes that Whiteness in the fourth wave of leisure studies must be understood as a performative social practice which functions as an ideology.
The ongoing structure of that history tends to be ignored as something in the past, if it is ever brought up. Understanding of the past will help us to move forward. The foundational genocide, forced labor, and segregated participation in the national parks have current impacts on people’s perceptions being that of a white space in which black and brown people are not welcomed. That has been shaped by racially segregated laws and policies. In 1854, the Plessy v. Ferguson case established separate and unequal, dual park systems for whites and non-whites. The segregation laws and culture were still in effect in 1916 when President Woodrow Wilson signed into the law the NPS. One hundred and ten years later, the Civil Rights Act of 1964 (Title X), made public accommodations for integration. Even Dr. Martin Luther King Jr said:“In fact, prior to the 1960s, the fight for equal access to public accommodations had been characterized by a long history of temporary advancements precipitated by protest, followed by legal retrenchments at the hands of lawmakers and the courts. The Civil Rights Bill of 1875 guaranteed all American citizens “full and equal enjoyment of public accommodations,” but was declared unconstitutional by the U.S. Supreme Court in 1883. During the 1880s and 1890s a series of local ordinances and state statutes, known as Jim Crow laws, were issued to further restrict the freedoms of blacks in the South. As the 19th century came to a close, the Supreme Court set the course of Southern race relations for the next 58 years as the 1896 ruling in Plessy v. Ferguson sanctioned the policy of “separate but equal.” Notwithstanding, direct action and legal challenges persisted until the 1954 Supreme Court ruling in Brown v. Board of Education ended legal segregation of public schools, building momentum to continue the fight against the unflinching racist policies of the South.” (King 1963)
This dynamic of reform and retrenchment mentioned by Dr. King has been echoed by critical race scholars in the period after the Civil Rights movement (Bell, 2004; Crenshaw, 1988). The US government made hundreds of treaties guaranteeing land and use rights to Indigenous people since the American Revolution, but through federal policies like Indian Removal, assimilation, and later legal settlements and termination the land Native peoples had physical access to dwindled, despite the maintenance of oral histories and relationships to these places (Deloria, 1969; Moreton-Robinson, 2015; Wolfley, 2016). National Parks, and particularly Monuments and Memorials, fit the definition of “White institutional space” (Moore, 2020), institutions in which patterns of power, values, and identity are structured in terms of hegemonic White (read: colonial modern) racial ideology (Embrick & Moore, 2020). Furthermore, National Parks are state ideological institutions, White spaces that tell the official stories of the nation thus constructing a homogenous national identity, value system, and ideological mindset of what it means to be American (Spracklen, 2013).
National Parks and monuments are situated within the power structures of American society at large. However, as the National Park Service (NPS) desires to attract more diverse and inclusive audiences, we argue that hegemonic narratives of White Supremacist Capitalist Patriarchy (Hooks, 1984) continue to pervade the storytelling in these nationally symbolic places. What can national parks, at the confluence of nature and culture, space and society, teach us about the ways in which race and racism play out in leisure? As tourist destinations which also function to preserve and protect national history, these parks tell an explicitly patriotic, place-based story of the nation. Historical storytelling at each site tells the story of the place to millions of visitors each year, each site framed as a piece of the national story. The NPS manages over 400 individual units, also referred to as “parks” which include national monuments, national memorials, historical parks, national parks, historic sites, national preserves which cover over 80 million acres of land and coastline (nps.gov).
Background
The two sites under study here are monuments and memorials with cultural significance and, like museums, they serve public history and educational functions. Monuments and memorials also cross over different scales and institutions outside of the NPS, with cities and private organizations also taking part in their management and preservation. In addition to time outdoors, national parks and especially monuments and memorials offer historical storytelling. Called public history, collective memory, or mythology, what’s left out of the stories told at nationally significant places is just as important as what is included. Furthermore, because NPS memorials and monuments tell the story of the nation, they also teach national ideologies, narrative justifications for the status quo, which reconcile the contradiction between purported American values of freedom, liberty and happiness and the American reality of excluding and conditionally including (assimilation, tokenism, etc.) non-White people from rights and resources. Both sites were chosen because they occupy distinct and multilayered ‘tourism imaginaries’ (Salazar, 2012), representations of place constructed by a host of experts across hospitality, academic, and government industries and adopted by tourists before they arrive, influencing how visitors make meaning out of the specific place and construct a place-based worldview embedded in the broader social context. These places also hold special significance as national landmarks, they are national heritage sites invoking a national imaginary as well as a tourist imaginary. Florida and The West are both iconic places in the national imaginary, with their touristic imaginaries of wilderness, adventure, conquest and settlement—White settler national origins that comprise the ‘stock stories’ of American culture and society past, present and future.
Why national parks as opposed to other federal settler agencies embedded in white nationalism and white supremacy? National Parks provide visitors with a unique opportunity to learn about history, culture, and global issues through leisure. Visiting different monuments in the park service provides people with primary access to state knowledge resources. The parks’ historical storytelling is even more important since the barring of discussions of history, race, gender, and sexuality in many schools. The National Parks can still tell those cultural and diverse histories. If the voices, power, and the lived experiences of Black, Latinx, Asian, and Native peoples are being denied, then where can people go to learn about those voices and lived experiences? The parks hold possibilities for counter-storytelling that could educate the public about the reasons for reparations, LandBack, and affirmative action through place-based learning that is not based in fantasies of Whiteness. We will return to this idea in the discussion. In this section, we provide a brief background on the parks before we discuss our methods."The purpose of the memorial is to communicate the founding, expansion, preservation, and unification of the United States with colossal statues of Washington, Jefferson, Lincoln, and Theodore Roosevelt." (Gutzon Borglum, NPS.gov)
Over two million people a year visit Mount Rushmore in the Black Hills of South Dakota. South Dakotan state historian Doane Robinson came up with the idea of sculpting historic figures of the west into large pillars of granite to attract tourists to the state (“Historical Letters and Legislation” 2021). Robinson contacted Gutzon Borglum who created the sculpture and design of Mount Rushmore. The 60-foot carvings of the four presidents on granite rocks were picked by Borglum because he believed they represented the important events and ideas in the history of the United States. Started in 1927 and completed in 1941, Mount Rushmore’s mission is to “Commemorate our national history and progress through the visages of George Washington, Thomas Jefferson, Abraham Lincoln and Theodore Roosevelt” (NPS.gov). Mount Rushmore is framed as the ultimate place to see democracy and freedom. Visitors to the park can explore the half of mile Presidential walking trail, enjoy Thomas Jefferson Ice cream, visit the sculptor's museum and attend the evening lighting ceremony.“America Begins Here: Built by the Spanish in St. Augustine to defend Florida and the Atlantic trade route, Castillo de San Marcos National Monument preserves the oldest masonry fortification in the continental United States and interprets more than 450 years of cultural intersections” (Castillo de San Marcos, NPS.gov)
In 2016, about 650,000 visitors toured the Castillo de San Marcos per year and 150,000 more toured the grounds (Korfhage, 2016); a busy Saturday in 2021 averaged 3,500 visitors. School groups are common. The Castillo de San Marcos National Monument is located in the growing tourist town of St Augustine, Florida, which welcomes millions of tourists each year along with a steady flow of new residents. The coquina stone fort was built at the orders of Spanish settlers to defend the strategically placed city and Atlantic slave-trading route from attack by pirates and colonial rivals. Enslaved Africans and Indigenous people were forced to mine the coquina (a wet cement of shells and sand that dries solid) from a quarry on Anastasia Island, transport it, make stones and construct the stone fortress (Palmer, 2002; Coltrain, 2016). After the US acquired Florida through the Transcontinental Treaty of 1819, the name was changed to Fort Marion and the structure served as a prison for Native people incarcerated during the “Indian Wars,” as well as a few confederate soldiers during the Civil War. In 1924 Fort Marion was designated as a national monument under the 1906 antiquities act, and it was not until 1942 that it was renamed the Castillo de San Marcos to reflect the site’s Hispanic heritage. The fort serves today as a landmark and museum; visitors cross the moat and tour the various stone-walled rooms, each containing a different exhibit. Living history means that visitors can also witness and participate in canon firings and various historical reenactments. The museum text is presented in English and Spanish.
Methods
The fourth wave of race research in leisure studies is connected to a critique of the formalist methods which have been hegemonic in the field (Floyd, 1998; Rojek, 1985). Within leisure studies and in other disciplines, scholars have argued for a Foucauldian discourse analysis methodology to investigate how social-political fields, discourses and representations, and institutions reproduce Western European, colonial-modern epistemological and ontological frameworks (definitions of what counts as knowledge and the human) (Moreton-Robinson, 2015; Rojek, 1985; Smith, 1999). Because the fourth wave “contextualizes discussions of race and racism within theoretical frameworks which enable broader discussion of social and structural inequalities, power, ideology and white hegemony” (Arai and Kivel: 464), the case study method is a particularly good methodological fit. The extended case method is a qualitative, sociological research method that puts theory at the center of the analysis. Case studies investigate ‘how’ and ‘why’ questions to understand contemporary events in their own context. Though case study findings are not generalizable, extended case studies require researchers to make conceptual connections that corroborate, extend, or challenge existing theory beyond the specific case (Burawoy, 1998; Yin, 2018).
The authors1 visited each site separately for several hours each and recorded field notes on the monument, park narrative, and spatial experience, supplementing that ethnographic data with narrative data from each park’s website. We use these case studies to apply CRT to the study of national parks and monuments, and in an effort to adequately understand how racism and Whiteness influence leisure spaces in the United States. The unit of analysis for each case is the story, which in the analysis we connect to the broader theoretical and social context. Our use of storytelling as an analytical strategy derives from critical race theorists who argue that storytelling is central not only to the law, but to human experience and cognitive processes. Psychologists and neuroscientists indeed have found evidence through various lines of research, including experimentation with human subjects, that stories promote cognition in children and adults (Mar, 2018). CRT shows how storytelling is both embedded in and functions to serve existing power relations in society. The standard plot lines of American origins tales comprise a stock story, the hegemonic narrative serves as a formula for identity on majority-minority lines and defines in-group reality, serving as a backdrop for personal political opinions and policy decisions as well. Counter-stories represent the silenced, obscured, denied, and hidden histories of out-groups, and they are unwelcome for the very reason that they challenge the one-dimensional and monolithic received wisdoms of the dominant stock story and thus white supremacy (Delgado, 1989; Ewick & Silbey, 1995; Loseke, 2007; Polletta et al., 2011).
Findings
Mount Rushmore National Memorial
"You may as well drop a letter into the world’s postal service without an address or signature, as to send that carved mountain into history without identification."
- Mt Rushmore Sculptor Gutzon Borglum, 1939
Before visitors can walk into Mount Rushmore, they see the presidential silhouette behind the gauntlet of flags which lead to the American presidents: Abraham Lincoln, George Washington, Thomas Jefferson, and Theodore Roosevelt. The design of this popular leisure attraction produces a patriotic inspiration of American greatness. Families and individuals are surrounded by overt and covert symbols that represent a shrine to American democracy; the Presidents and their stories, avenue of flags, ice cream, and the first-generation son-of-immigrants who became a great American sculptor, Gutzon Borglum. To reach the iconic view of Mount Rushmore, visitors have to walk down the Avenue of Flags. Constructed in 1976 for the bi-centennial American celebration, the flags represent all 50 states, Washington D. C., two commonwealths and three territories of the United States. Walking towards the flags, visitors pass a gift shop on the left and the Carver’s Cafe and Ice Cream Shop. Before you see the cafe, there is a sign with a picture of a vanilla ice cream cone, an equal picture and a picture of Thomas Jefferson after the equal picture. The sign reads: “President Jefferson was the principal author of the Declaration of Independence and of the first ice cream recipe in America…Come get a taste of history at the Memorial Ice Cream Shop.” Ice Cream is synonymous with families, fun, summer recreation and being an American. Former President Ronald Reagan signed into law by presidential proclamation that July is National Ice Cream month and July 15th is National Ice Cream Day. At that moment visitors are exposed to the symbolic image of seeing President Jefferson on “the rock”, looking down at the avenue of flags, and knowledge that the recipe for America's favorite dessert came from President Jefferson adds to the national pride and shrine of democracy narratives.
Continuing down the walkway, flags are on both sides of the path. Under each flag is a plaque with the name of the state/territory and the year of admission into the union. The flags are arranged in alphabetical order with the As at the start of the Avenue in the back towards the gift shop and Ice Cream shop and W’s toward the end of the avenue which leads to the Grand View Terrace and Mount Rushmore. The Terrace is the ultimate goal for visitors. From this unimpeded view, visitors are close to the president monument to take pictures and examine the massive structure. That is the main highlight of Mount Rushmore. From the terrace, you can walk down the steps to the amphitheater and visit the Lincoln Borglum Visitor Center. The amphitheater is where people go to see the evening light shows and different programs. The park ranger has evening programs that “focus on the presidents, patriotism, and the nation's history.” The end of the evening program is a film called "Freedom: America's Lasting Legacy” (nps.gov). The center and studio are the two main buildings to visit to learn about Mount Rushmore. Both have exhibits and information with the focus is on the presidents, sculptor, and construction of Mount Rushmore. The narratives throughout the park re-enforces the “shrine of democracy” from the stories of the struggle and challenges the presidents and sculptors all overcame to make their dreams come true.
If visitors do not want to walk down to the amphitheater or visit the Visitor Center, then the other options are to walk the Presidential Trail or Nature trail. Both trails loop behind Mount Rushmore and connect to each other. The popular trail is the Presidential Trail. It’s a short 0.6 mile walk around Mount Rushmore. The trail consists of 422 stairs and is the closest visitors can reach Mount Rushmore without climbing on it. Along the trail, there is information about the presidents. In 2008, a new addition was added to the Presidential Trail. The Lakota, Nakota, and Dakota Heritage Village. The Village consists of three tipis off the trail which operates during limited times during the summer, not all year around. Visitors will find American Indians who are cultural interpreters about their communities. This is the only place in the park that native Americans are a mainstay. The park included the Village to be inclusive and diversify the narrative of Mount Rushmore.
The narrative and placement of Heritage Village are separated and marginalized from the rest of the narratives throughout the memorial. The history, contribution, and story of Native Americans, which is an American story, a story about democracy, gives the impression as an aside story that was added but doesn’t fit into the larger narrative of “Mount Rushmore” as a display of democracy and patriotism. The design and delivery may be transformative because Native American stories are included, but not instructional. Maureen McGee-Ballinger, Chief for Interpretation and Education in the National Park Service stated “Mount Rushmore is attempting to carry out its mission of celebrating the “shrine of democracy” but also incorporate Native American culture as part of the visitor experience. “We strive to provide a broad spectrum of history and messaging,” (McGivney, 2021). The parks have a narrative of the “shrine of democracy” that is void of the colonialism, exclusion, and manifest destiny of democracy in the United States. At the same time, inclusion and diversity wants to be celebrated. The park does not see how both narratives are a part of the story of democracy. Adding the Village sparked many debates and comments from visitors ranging from being glad it was there to the village not fitting into the “theme” (Mt. Rushmore), which is a “celebration of the nation’s constitutional ideals and the great presidents who established, preserved and expanded the union” (Soderlin, 2018). Others believe, “Mount Rushmore should be turned into a Holocaust Museum” (McGiveney, 2021 quoting Phil Two Eagle a member of the Rosebud Sioux Tribe in South Dakota) for the stolen land, destruction, and lives lost of Native American. The park's narratives are thus problematic.
However, the monument and story of Mount Rushmore is framed as a symbol of freedom, hope, and democracy to all US citizens—an American story. Nestled in the Black Hills, which the Lakota Indians called, Paha Sapna, which means “the heart of everything that is” there is Mount Rushmore. Even the original name of the sacred rock “Six Grandfathers” from the Lakota Sioux was changed to Mount Rushmore, because it was assumed it did not have a name and Charles E. Rushmore, a New York Attorney, “named” the mountain. In 1930, the U.S. Board of Geographic Names made Rushmore the official name. Even the sacred rock’s original name was taken away from the original people that named it (Bergman, 2016).
If national parks are our “best idea” and are “absolutely American, absolutely democratic” and reflect our best rather than our worst”, ideally Mount Rushmore represents those sentiments. On the National Park Service, Mount Rushmore page, they describe this monument as.“Majestic figures of George Washington, Thomas Jefferson, Theodore Roosevelt and Abraham Lincoln, surrounded by the beauty of the Black Hills of South Dakota, tell the story of the birth, growth, development and preservation of this country. From the history of the first inhabitants to the diversity of America today, Mount Rushmore brings visitors face to face with the rich heritage we all share.” (“American History, Alive in Stone” 2021)
However, the narrative of Mt. Rushmore that the national park service tells the millions of visitors is an “American (white) perspective”- that ignores the oppression and violence of native Americans and people of color. The story of diversity and the first inhabitants is not told. Having the story as an aside and not incorporated in the main narrative doesn’t tell the full story. Not telling their stories normalizes a narrative of whiteness and white spaces in the norms, policies, and procedures throughout the park (Moore, 2020). The complex history of the “majestic” figures on carved rock gets ignored and disregarded which is a “a principal mechanism of contemporary white institutional space” (Moore, 2020). The stories that are being told shape and instruct not only our sense of the world and who we are, but also reinforces a status quo of whiteness.
Visitors are told stories of the birth and development of our country which the former presidents contributed to shaping freedom and democracy which we all hold dear. Those narratives tell a story which idealizes the “pure and homogeneous spaces” in which white men have controlled and dominated. The four presidents represent the expansion and unification narrative of the US through a manifest density narrative. Manifest Density, legally grounded in Doctrine of Discovery, is the idea that the United States was destined by God to spread democracy and capitalism through expanding their domination over land and people. For example, both George Washington and Thomas Jefferson owned slaves. Washington was known as “Town Destroyer” among the Iroquois, (Cornblatt, 2008) Jefferson laid the groundwork and was the architect of policies for forcefully removing native Americans from their land. Lincoln signed an executive order to hang 38 Dakota in Minnesota for their alleged crimes which became the largest mass execution in U.S. history (Miller-Still, 2020). Teddy Roosevelt in an 1886 speech said, “I don’t go so far as to think that the only good Indians are the dead Indians, but I believe nine out of every 10 are” (DiSilvestro, 2011). Thus, the storytelling and institutional history ignore the ways that racism shaped the “unification, founding, preservation and expansion of America by Washington, Jefferson, Lincoln, and Roosevelt” (National Parks Service, 2015). With Manifest Density the story that visitors hear is framed in a way that ignores how the United States government took the land from the Native American, the understanding of the “rock” that people visit, and the Black Hills as sacred ground, with the irony of celebrating the European who killed and appropriated native land. The silence and hiding of Native American and the Lakota Sioux stories, normalizes and romanticizes a white narrative of America. All of these majestic figures contributed to the violent displacement of Native peoples.
The absence of other voices and narratives supports white supremist practices that become interconnected with the storytelling of Mount Rushmore. The irony of American democracy is the carved faces of the presidents are on stolen land. The battle for the Sioux (Dakota, Lakota and Nakota) and Arapaho to keep fighting over their stolen land has been ongoing. The U.S government signed a treaty with the Lakota-Sioux nation stating the Black Hills were their land in The Fort Laramie Treaty of 1868. Once gold was found in those hills, the treaty didn’t exist. In 1980 the U.S. The Supreme Court, concluding a long-running case brought by the Sioux Nation, confirmed the illegality of the government’s actions, ruling that the Native Americans were entitled to damages for the theft of their land. The government would offer compensation but not give the land back.
The flags are a symbol of a common heritage and ideals. The 56 flags of the United States and territories have a partial meaning about democracy and shared values. Symbols of flag and land are components of culture, identity, nation, and meaning. The imagery of the flags, especially the American flag is “symbolic patriotism”. The symbols have multiple meanings of “patriotism, partisanship, and even racial prejudice.” (Kalmoe & Gross, 2016). The symbol of the flag mirrors social reality, that social reality has a particular meaning based upon similar cultural meanings. Meaning of a particular cultural object lies in the social patterns it reflects” (Griswold, 2008). In other words, there has to be a set of agreed upon, understanding, traditions and beliefs of what the flag means. The meaning of the flag(s) has to be put in the context of the experience to those it represents (Talbert, 2017). Since we are a diverse nation and want to be inclusive, there should also be representation from the Lakota Sioux and other Native Nations’ flags. What is absent from the avenue of flags are the flags and stories of the Lakota Sioux in this space and their land. There is also an invisibleness of the nine native American tribes in South Dakota. If there is a “rich heritage, we all share”, the story and narratives privilege white power, and wealth (Embrick & Moore, 2020). This is told in the name of the “rock,” who is on the rock, and the romanticized imagination of land and “the West.”
The Castillo de San Marcos National Monument
Originally administered by the War Department, the Castillo was designated a national monument in 1924 using the Antiquities Act of 1906, which played a fundamental role in the institutionalizing archaeology as an arm of the state for the specific purpose of maintaining a coherent national narrative of history. Whereas anthropology grew into an academic discipline based on the principle of cultural relativism and pluralism, archaeology was increasingly funded by the government, practiced by amateurs, and supported a concept of culture as linear and evolutionary. Thus, the state-sponsored story of the USA incorporated the false narrative of “savage” and “primitive” Indigenous people, naturally and inevitably supplanted by White settlers through a naturalized process of evolution. The preservation of indigenous sites as national heritage under the Antiquities Act furthered the notion that Native Americans simply died off or vanished, leaving the land and built environment for White settlers to inherit (Colwell-Chanthaphonh, 2005; McLaughlin, 1998). Inside the walls of the fort, this narrative is reflected in the paucity of indigenous stories compared to European ones, and the tropes these stories reproduce. For example, all displays about Indigenous people are through the lens of their incarceration, and they highlight cultural differences and rituals, a move characterized by scholars as “jungle-book” ethnography and “ethnographic entrapment” (Arndt, 2016; Rios, 2011; Small, 2015). Furthermore, the evidence of “Indian Incarceration” presented by the monument in the former prison cells is encased in glass and described as vanishing from the walls due to exposure to the elements, approximating the ‘vanishing Indian’ trope prevalent in white narratives of US history.
While evidence of Indigenous presence is framed as naturally delicate and vanishing, European presence is represented in the natural permanence of stone. The fort today is framed within the broader “Oldest” story of the city as an “enduring Monument,” “North America’s oldest masonry fortification” built “more than 100 years before the United States became a country” (“America Begins Here” 2021). While on the surface the Castillo de San Marcos seems out of step with other National Parks’ ‘wilderness’/nature claims, the monument makes use of nature tropes to make its White nationalist claims, naturalizing white supremacy and white nationalism. Echoing the role of the fort as a symbol of permanence and continued occupation of the land, the fort served as an icon for the city to advertise its 450th celebration to millions of visitors who came to the city one September weekend in 2015. This is an exemplary case of “firsting and lasting,” (O’Brien, 2010) in which place-based historical storytelling is used to draw distinctions between the supposed modernity of Europeans and the supposed primitiveness of Natives, freezing Indigenous peoples (and genocide) in the distant past.
Indeed, throughout the nineteenth century, the fort served as a place for wealthy White tourists to exercise their freedom and mobility vis-a-vis the Indigenous prisoners, who were forced to entertain the tourists with ‘cultural’ performances and make drawings of their experiences as prisoners to be sold as souvenirs. Throughout history, human display has been a method of constructing so-called racial difference between Whites and colonized Indigenous people around the world through leisure, constructing White subjectivity through White supremacist theories of human difference that aided imperialism and colonization (Rony 1996). The fort/prison today offers an embodied leisure experience of colonialism for visitors and is a central landmark in St Augustine tourism providing a grassy lawn and waterfront views. Visitors can pay to enter the park and exhibition space inside but can also use the surrounding space for varieties of leisure and recreation activities as well. During the city’s annual July 4th fireworks, the fort lawn is the primary space for spectators to set up camp to wait for the nighttime show. Without paying to enter, on any day visitors can walk the seawall portion of the structure and access some of the cannons on display. Therefore, the fort provides a leisure space even outside of the interpretive exhibit. Even on the outside, visitors can touch the coquina, imagine themselves firing a cannon, and keep watch over the inlet where pirates and colonial rivals would appear on the horizon. Once inside the park monument, visitors have even more opportunities to embody colonialism through performative individual reenactments, that is, if there isn’t an official reenactment and cannon firing going on already. The top level of the fort invites this kind of interaction with the space by not providing any interpretive material, just cannons and parapets that provide a view seemingly just like the colonists would have seen as they defended the city. Visitors are not invited to imagine themselves as prisoners, and the spaces used for incarceration down below are completely transformed into museum exhibits, breaking the straight line between past and present subjectivity and precluding any easy imaginary embodiment of the Indigenous prisoners. Instead, on the inside of the fort/prison visitors are encouraged to imagine themselves as colonizers in the colonial scene through still-life displays of supposed everyday life, with no replicas of everyday life as a prisoner of White supremacy.
Consolidating this distinction, the exhibits that do tell indigenous stories portray indigenous people as prisoners or cultural relics in the past by focusing on “their culture” and refusing to include living people in the narrative, despite the well-known existence of native descendants of people who were imprisoned there who are members of two federally recognized nations, the Miccosukee and the Seminole. Though the fort applauds its exhibition of indigenous incarceration as part of the fort’s history, the terms of this inclusion must be examined in-depth. Upon entering the museum, one of the first exhibit rooms contains a timeline beginning with European settlement, complete with the flags of each European nation that has possessed the territory (France and England in addition to Spain). The fort museum includes the story of nineteenth century Indian incarceration during the conquest of Florida. However, rather than a true story of US war and genocide, viewers are met with a story of assimilation that asks them to sympathize with the colonizer, in this case General Richard Henry Pratt, known as the creator of the insidious phrase, “To kill the Indian is to save the Man.” He used the fort to experiment with different techniques of power and control, which were later exported around the country in the Indian boarding or residential schools (Barnewolt, 2018; Hayes, 2018). The text of a display narrating this history is instructive:“In 1875 Captain Richard Pratt was assigned to Fort Marion. He had to guard 75 American Indian prisoners. Imagine being taken away from your home and brought to a strange place. People speak a different language and act differently. How do you survive? Pratt began a program of assimilation. He believed that the adoption of white culture, language, and religion were the Indians only chance. An advocate for American Indian education and civil rights, he sought to find a way to accomplish his goals, and his actions led to the beginning of the American Indian schools concept.” (Castillo de San Marcos National Monument, 2016)
In this quote displayed to visitors, the genocidal intent of Indian boarding schools is completely dismissed in favor of a pro-assimilation narrative that portrays Pratt as a benevolent savior. Though it appears on the surface that the viewer is being asked to sympathize with the prisoners, by the end of the paragraph the sympathy lies with Pratt, who is described as an “advocate” in stark contrast to reality. The “kill the Indian to save the man” quote is left out, and there is not even tacit acknowledgment of the wrongdoing at Indian boarding schools.
Current differences in White and Indigenous worldview on the Castillo de San Marcos National Monument became visible in the lead up to the 2013 “Viva Florida 500!” commemoration and the city’s own 450th commemoration in 2015, when activists and members of the Original Miccosukee Simanolee Nation Aboriginal Peoples specifically highlighted the grotesque contradictions of using the former genocidal prison-laboratory as a family leisure destination. A group of Florida Indigenous leaders known as the Council of the Original Miccosukee Simanolee Nation Aboriginal Peoples opposed both commemorations and sent official information packets detailing their opposition in early 2013. Among the specific proposals included in the document is the demand to tear down the fort/prison as “a minimum first step towards honoring of the Aboriginal Indigenous Peoples of this Land…once the fort/prison comes down this will give us all an opportunity to heal from brutal crimes against humanity that were committed by Juan Ponce de Leon, Pedro Menendez de Aviles, and others'' who figure prominently in the storytelling and visual branding of not just the 450th and 500th commemorations, but St Augustine tourism overall. The Council cites the former Mayor of St Augustine stating that he was tired of hearing these kinds of “negative” comments. Responding to 2015 protests on the fort lawn during the 450th, the director of the commemoration retorted that “Native American culture is a huge component of the story” and the Mayor at the time disagreed with protestors as well, arguing that the city was not celebrating the conquistadors but rather the city’s history as a melting pot, though she did note that “founding European settlements in this country was never pretty” (Benk, 2015).
Discussion and Conclusion
Whereas some have insightfully argued that the race and rights framework does not apply to Indigenous Nations (Steinman, 2015) precisely because of the national sovereignty issue, we argue that because colonization was tied to White supremacy through the law starting with Discovery Doctrine, it is essential to understand the role of racist ideology, specifically White nationalism, in the perpetuation of settler colonialism as the structure of US society. Decolonial and antiracist movements and policy projects are not monolithic, there are a variety of approaches under way and there exist divergent ideas within movements and communities on the best path forward. However, we briefly discuss some of the recent approaches and argue that the NPS should not only be aware of but humbly and diligently learn from the centuries-long efforts to resist colonization if they truly desire relevancy, diversity, and inclusion.
The United Nations’ 2007 Declaration on the Rights of Indigenous Peoples acknowledges the international movement for Indigenous sovereignty, against the racialized dispossession inaugurated with Discovery Doctrine and consolidated as US law in the Johnson decision in 1823 (Dunbar-Ortiz, 2019). Some settler states have begun fraught and limited decolonization efforts through biculturalism (Johnson, 2010) or consultation (Youdelis, 2016). Indigenous groups have successfully worked with settler environmental movements on co-management and land return agreements that cross settler-defined borders (Brown, 2022). However, official settler decolonization efforts have so far remained limited in that they have maintained White power structures by paternalistically and sometimes superficially “including” Indigenous people in colonial institutions and governance rather than listening to self-determining Indigenous Nations as coeval sovereigns. This results in coerced if not forced assimilation into the White settler nation-state, which is exactly what Indigenous Aboriginal First Nations are struggling against. In addition to protest movements of the late twentieth century such as the American Indian Movement (AIM), Indigenous Nations have also fought legal battles against the federal government, enacting their status as coeval Nations, rather than US citizens to be included in the settler project (Hampton, 2019).
Today’s LandBack movement is part of a long genealogy of anticolonial struggle. It is a movement for not only land but sovereignty; it is one instantiation of an Indigenous resurgence that has been built on the “collective continuance” of Indigenous civilization despite centuries of US land theft, assimilation and genocide (McKay et al., 2020; Simpson, 2017). An anticolonial movement is not just about territory but about an altogether different ontological relation to land (Goldstein, 2008) citing Mohawk scholar Taiaiake Alfred who argues for restitution rather than reconciliation) and to return Native peoples to the national parks, deconstructing the White fantasy of ‘wilderness’ that never was (Wolfley, 2016). When Indigenous history is ‘included’ as “prehistory” in leisure sites, even though Indigenous people in the case of many national parks live right next door, this amounts to a “denial of coevalness” (Fabian, 2014), positioning White and non-White on unequal footing in time and space. This portrayal of Indigenous peoples and nations as frozen in the past, as inherently not-modern or vanishing, has implications for how sovereignty and tribal existence is negotiated with other nations (the US) (Deloria, 1969; Moreton-Robinson, 2015).
In conclusion, we found a consolidation of settler colonial whiteness and white nationalist narratives through spatialized storytelling about the nation’s history in two iconic national park sites, a monument and a memorial. By 2045 our population is going to be a majority of people of color and the NPS is making a push to be more racially inclusive and to bring in more people of color into the parks. The parks have made efforts through social media, hiring more diverse park rangers, and reaching out to communities that may be excluded. However, our findings indicate that these demographic changes have not been reflected in structural changes, but rather, a greater entrenchment and consolidation of White supremacy through the facade of diversity. We argue that structural work needs to be done to change the National Park Services narratives of monuments and heritage sites. Our case studies demonstrate two different places with similar consolidations of the white spatial imaginary and settler origins narrative, despite the appearance of diversity. The case studies suggest that national park monuments reproduce the false narrative of America as a White nation and settler colonial conquests as morally righteous, and ideology of white supremacy which fuels White nationalist violence and consolidates general ignorance or “colonial unknowing” (King, 2016) that is a characteristic of Whiteness.
Floyd asks not just how leisure reinforces racism, but how “can our understandings of race and leisure contribute to formation of social policies designed to foster constructive engagement and goodwill among different racial and ethnic communities?” (Floyd, 1998: 249). Rojek reminds us that leisure space is an effect of broader systems of legitimation in society, however, that “we all have the power to challenge and redefine the conditions and consciousness which define legitimate leisure behavior” (Rojek, 1985: 178). The national parks could start by making a concerted effort to help the predominantly White guests understand the sites from a different, valid perspective– Mount Rushmore as an “international shrine to White supremacy” (Oglala Dakota activist Nick Tilson of NDN collective, quoted in Estes 2021) and the fort as a disgraceful prison that should be torn down (Council of the Original Miccosukee Simanole Nation Aboriginal Peoples). Thus, NPS sites could play an essential role in acknowledging the foundations of the nation in racism and Settler White Supremacy, helping the public understand calls for reparations and ‘truth and reconciliation,’ processes started by other nations complicit in slavery and genocide. An accurate portrayal of American history by the NPS is absolutely necessary for White people, who like everyone else learn a fraction of US history in schools but additionally lack experiential and intergenerational knowledge of racism that can help to understand the demands of US-based movements like Black Lives Matter and LandBack. Lies and omissions instill a false sense of unfairness in social justice efforts and feed into a politics of aggrieved, embattled ‘White masculinity under attack’ that is not supported by evidence. Leisure, recreation, and public history professionals should foster a deliberate responsibility towards the symbols displayed–their historical and present meanings, as well as the futures they project.
Declarations
Conflicts of Interest
The authors have no conflicts of interest to disclose.
1 The authors’ positionality is that of two women, one is a white woman of working class background and one is an African American woman of middle class background.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9747540 | NO-CC CODE | 2022-12-15 23:22:01 | no | Int J Sociol Leis. 2022 Dec 14;:1-24 | utf-8 | null | null | null | oa_other |
==== Front
Int Ophthalmol
Int Ophthalmol
International Ophthalmology
0165-5701
1573-2630
Springer Netherlands Dordrecht
2612
10.1007/s10792-022-02612-y
Original Paper
Topical cyclosporine versus allergen specific immunotherapy in perennial allergic conjunctivitis
http://orcid.org/0000-0003-1621-994X
Dogan Ceylan Uslu [email protected]
1
http://orcid.org/0000-0002-8028-2647
Tuzer Can [email protected]
2
http://orcid.org/0000-0002-1625-3382
Turker Ibrahim Cagri 1
http://orcid.org/0000-0003-0631-453X
Alkan Abdurrahman Alpaslan [email protected]
3
http://orcid.org/0000-0002-0678-135X
Culha Damla 4
http://orcid.org/0000-0003-3449-5868
Demir Semra [email protected]
2
1 grid.488643.5 0000 0004 5894 3909 Department of Ophthalmology, Sisli Hamidiye Etfal Education and Research Hospital, University of Health Sciences, Cumhuriyet and Demokrasi Avenue, No:1, Istanbul, Turkey
2 grid.9601.e 0000 0001 2166 6619 Division of Allergy and Immunology, Department of Internal Medicine, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkey
3 Derindere Hospital İstanbul, Istanbul, Turkey
4 Lotus Eye Aesthetics & Strabismus Clinic, Halaskargazi Street, Sisli/Istanbul, Turkey
14 12 2022
19
29 8 2022
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.
Purpose
Symptom control in the long-term with less side effects is important in perennial allergic conjunctivitis, since would improve quality of life. This study aimed to assess the clinical efficacies of topical cyclosporin A and subcutaneous allergen immunotherapy (SCIT) in terms of sign control in perennial allergic conjunctivitis.
Methods
This retrospective study included 20 adult patients with perennial allergic conjunctivitis and confirmed sensitization to house dust mites with skin prick test. Patients were assigned to either topical cyclosporine A treatment or SCIT. The participants were followed for 6 months, and signs scores were recorded at 1, 3 and 6 months.
Results
Overall, both cyclosporine and immunotherapy groups showed significant improvements in papillary reaction (p = 0.011 and 0.003, respectively), limbal involvement (p = 0.031 and 0.001), and conjunctival hyperemia (p = 0.001 and p < 0.001) scores during the 6-month follow-up. However, only cyclosporine group showed a significant improvement in corneal involvement scores (p = 0.015) during the study period. When scores at different time points were compared, significant improvement in conjunctival hyperemia was evident at 6 months in both groups when compared to baseline (cyclosporine group, 0.7 ± 0.68 vs. 2.4 ± 0.84, 70.8% decrease, p = 0.01; immunotherapy group, 0.3 ± 0.48 vs. 2.3 ± 0.95, 87.0% decrease, p = 0.004), whereas for limbal involvement such an improvement was only evident in the immunotherapy group (0.1 ± 0.32 vs. 1.3 ± 0.95, 92.3% decrease, p = 0.01).
Conclusions
Allergen immunotherapy and cyclosporin A treatment may provide effective sign relief in perennial allergic conjunctivitis. It may represent an encouraging treatment option particularly for cases with perennial allergic conjunctivitis refractive to other treatments and positive skin prick test to a specific allergen (house dust in the present study). Long-term relief by SCIT would reduce the side effects of polypharmacotherapy. Larger studies with longer follow-up are warranted to confirm our findings.
Keywords
Perennial allergic conjunctivitis
Allergen specific immunotherapy
Cyclosporine A
Symptom relief
==== Body
pmcIntroduction
Allergic conjunctivitis (AC) is a chronic, bilateral ocular surface inflammation with recurrences and relapses. There are four types of AC that are seasonal allergic conjunctivitis (SAC), perennial allergic conjunctivitis (PAC), vernal keratoconjunctivitis, and atopic keratoconjunctivitis. Although the symptoms in the perennial form are similar to the seasonal form, allergic reaction in this form can often be triggered by allergens of organic origin and non-seasonal characteristics [1]. SAC is often characterized by an acute or subacute onset triggered by trees, grass, and weed pollens, and it is more common and may occur during periods of high allergen exposure. On the other hand, PAC tends to be caused by year-round allergens including house dust mites (HDM), some molds or pet danders [2, 3].
The ocular manifestations of SAC and PAC occur due to mast cell degranulation secondary to allergen exposure in susceptible individuals. In both acute and chronic forms, mast cell degranulation leads to the release of inflammatory mediators and activation of enzymatic cascades that produce pro-inflammatory mediators. Additionally, in chronic allergic conditions, a sustained inflammatory response is observed due to mediators such as eosinophils and cytokines [4]. The main sign and symptom of allergic conjunctivitis are conjunctival hyperemia and ocular itching. The disease pathophysiology seems to be related with type 2 inflammatory pathway [5]. However, neurogenic mechanisms also seem to play a role in allergic inflammation and particularly in ocular itch and pain [6].
It has been shown that effective treatment of allergic conjunctivitis and minimizing exposure to specific allergens can improve the quality of life in patients with ocular allergies [7]. To improve the patient's quality of life, it is important to provide rapid, effective and safe treatment against both seasonal and perennial allergens.
The treatment options in PAC include topical and systemic treatment options. While antihistamine and steroid drops are the main treatment in topical treatment, artificial tears can be used in supportive treatment. However, due to the severe side effects of long-term use of topical steroids such as cataract, glaucoma, and local immunosuppression, immunomodulators such as cyclosporine A, which have fewer side effects, have become one of the topical treatment options [8]. Antihistamines, corticosteroids, and leukotriene antagonists can be included in topical treatment as systemic treatment options in cases whose symptoms are more severe, cannot be controlled with topical treatment, or secondary complications are observed.
Allergen immunotherapy is an important treatment option for patients whose symptoms and signs cannot be controlled despite regular pharmacotherapy [9]. Immunotherapy is based on the idea that the body can be desensitized to certain allergens that stimulate the immune system and trigger allergy symptoms. Hyposensitization created by controlled and regular administration of allergens is one of the effective methods that can be used in the treatment of allergic rhinitis, allergic asthma, and allergic conjunctivitis [9]. Allergen immunoterapy administered through sublingual or subcutaneous route has been shown to provide a sustained effect in the long term up to three years even after discontinuation of the treatment [10].
The use of immunotherapy has increased in recent years due to the side effects caused by the long-term use of topical or systemic agents. Immunotherapy may not only reduce the need for pharmacotherapy but may also reduce the symptoms of allergy seen during attacks and play a preventive role in the emergence of asthma or new allergy types. It has been observed that immunotherapy reduces sensitivity to allergens in the long term and its effect continues after hyposensitization [11, 12]. In this study, we aimed to compare the effects of topical cyclosporine treatment and allergen immunotherapy treatment on allergic signs in patients with perennial allergic conjunctivitis who were sensitized to house dust mite.
Methods
Study design
This retrospective study conducted at Department of Ophthalmology, Gaziosmanpaşa Training and Research Hospital and Division of Allergy and Clinical Immunology, Department of Internal Medicine, Istanbul Faculty of Medicine, Istanbul University. The study adhered to the tenets of the Declaration of Helsinki and received approval from the ethics committee of Gaziosmanpaşa Training and Research Hospital. Informed consent was obtained from all participants.
Subject eligibility criteria
Adult patients who were followed up in the Department of Ophthalmology for more than 24 months with the diagnosis of PAC were referred to the adult Allergy and Clinical Immunology Clinic to be evaluated by skin prick tests (SPTs). SPT with common inhalant allergens including house dust mites (Dermatophagoides pteronyssinus, Dermatophagoides farinea), molds (Aspergillus fumigatus, Alternaria alternata) and pollens [Grasses (Velvet grass, Orchard grass, Rye grass, Timothy grass, Kentucky blue grass, Meadow fescue), Artemisia vulgaris, Chenopodium album, Olea europaea, Urtica dioica, Plantago lanceolata, Betula alba] (Allergopharma®, Reinbek, Germany) were performed as described in detail in previously published studies [13, 14]. Sensitizations in all patients were confirmed by a positive (≥ 3 mm mean wheal response) SPT. PAC patients only having a sensitization to house dust mites were included in the study. Co-sensitization to inhalant allergens other than house dust mites (Dermatophagoides pteronyssinus and/or Dermatophagoides farinea) was an exclusion criteria. The following patients were also excluded from the study: those who (1) had co-existing ocular diseases such as glaucoma, uveitis, ocular infection, ocular surface disease or had a history of a ocular surgery; (2) had uncontrolled asthma, systemic autoimmune disease or active malignancy; (3) reported hypersensitivity to cyclosporine; (4) were pregnant; (5) needed to wear contact lens during the treatment period; (6) used topical or systemic concomitant medications including corticosteroids, NSAIDs, anticholinergics, immunosuppressives; (7) had a history of cyclosporine treatment or immunotherapy for allergic conjunctivitis. The patients were selected from whom were not using the other routine topical therapies for at least 1 month.
Study protocol and clinical assessments
Twenty patients who were found to be sensitive to house dust mites as a result of the skin test divided into two groups. Patients in Group 1 used cyclosporine (Restasis®) only at a dosage of one drop per eye twice daily with an interval of 12 h between drops in both eyes and patients in Group 2 were treated with subcutaneous immunotherapy as in described below for 7 weeks. 1st, 3rd, and 6th month signs’ of the participants were evaluated from medical records. The four signs, papillary reaction, limbal involvement, corneal involvement, and conjunctival hyperemia were graded using the 4-point system (0, none; 1, mild; 2, moderate; and 3 severe) as defined by Uchio et al. [15] and similar to the system used in the study by Dudeja et al. [16]; and the groups were compared using this scoring system. The upper and lower extreme scores were as follows: for upper tarsal papillae, 0 indicates no papillae and 3 indicates predominance of Giant papillae; for limbal activity, 0 indicates no activity and 3 indicates the presence of Horner-Trantas dots; for corneal involvement, 0 indicates intact corneal epithelium and 3 indicates diffuse punctate keratopathy; for conjunctival hyperemia, 0 indicates absence of dilated blood vessels in conjunctiva and 3 indicates generalized dilation of blood vessels.
Subcutaneous immunotherapy (SCIT)
A cluster (accelerated) SCIT protocol lasting 7 weeks was applied to 10 subjects. Three injections were administered once a week during the initial two weeks. The following two weeks, two injections were performed on the treatment days every week. During the subsequent three weeks, only one injection was applied every week. The final dose of immunotherapy reached 1 ml of 5,000 TU at the end of the incremental protocol. The maintenance therapy was administered with 1 ml dose of 5,000 TU monthly as of the incremental protocol. The subjects were observed at least 30 min after every injection due to the risk of allergic reactions under the full emergency resuscitation equipment.
Statistical analysis
In addition to descriptive statistical methods (mean, standard deviation) in the evaluation of the data, the distribution of the variables was examined with the Shapiro–Wilk normality test, the Friedman Test was used for the time comparisons of the non-normally distributed variables and Wilcoxon Signed Ranks test was used for comparison of paired groups. The relations between categorical variables were analyzed using the Chi-square test. The significance level was taken as 95% and the results for p-value, which is equal to and lower than 0.05, were interpreted as statistically significant. For multiple comparisons, Bonferroni correction was also used. All statistical analyses were performed by IBM SPSS Statistics software (Version 27).
Results
Twenty patients who were followed up in the department of ophthalmology for PAC were included in the study. The study was carried out in 2 groups (age- and gender-matched individuals). There was no statistically significant difference between the groups in terms of age, gender (p > 0.05). Table 1 shows the participants’ demographic characteristics. Table 1 Demographic features
Cyclosporine Immunotherapy P value
Mean ± SD/n(%) Mean ± SD/n(%)
Age 29.5 ± 3.92 28.1 ± 3.99 0.439†
Gender Male 3 (%30) 4 (%40) 1.000††
Female 7 (%70) 6 (%60)
SD Standart deviation
The statistical significance level was P < 0.05 for '††' and '†'
In the study; the initial, 1st, 3rd, and 6th month findings of the relevant parameters (papillary reaction, limbal involvement, corneal involvement, conjunctival hyperemia) of the 2 groups under cyclosporine and immunotherapy treatment were evaluated, and whether there was a difference between repeated measurements of the mentioned parameters for each treatment group was examined (Table 2, Fig. 1). According to the results shown in Table 2, papillary reaction, limbal involvement, and conjunctival hyperemia levels of the patients who received cyclosporine or immunotherapy treatment showed a statistically significant decrease in the later stages of the treatment (p < 0.05). Table 2 The difference of repeated measurements
Baseline (Mean ± SD) 1th month (Mean ± SD) 3rd month (Mean ± SD) 6th month (Mean ± SD) p value†
Papillary reaction C 1.2 ± 0.92 1.2 ± 0.92 0,8 ± 0,63 0.5 ± 0.53 0.011*
I 1.3 ± 0,82 1.3 ± 0.82 0.6 ± 0.7 0.3 ± 0.48 0.003*
Limbal involvement C 1.2 ± 0.92 1.1 ± 0.74 0.7 ± 0.68 0.4 ± 0.52 0.031*
I 1.3 ± 0.95 1.2 ± 0.92 0.6 ± 0.52 0.1 ± 0.32 0.001*
Corneal involvement C 1 ± 0.82 0.9 ± 0.99 0.4 ± 0.52 0.2 ± 0.42 0.015*
I 1.1 ± 0.88 1 ± 0.94 0.6 ± 0.7 0.4 ± 0.52 0.16
Conjunctival hyperemia C 2.4 ± 0.84 2.2 ± 0.92 1.6 ± 0.7 0.7 ± 0.68 0.001*
I 2.3 ± 0.95 2.3 ± 0.95 1.5 ± 0.53 0.3 ± 0.48 < 0.001*
C Cyclosporine, I Immunotherapy
The statistical significance level was P < 0.05 for “*”
Fig. 1 The difference of repeated measurements
While there was no difference between repeated measurements in corneal involvement levels in the group receiving immunotherapy treatment (p > 0.05), corneal involvement levels were statistically significantly decreased in patients receiving cyclosporine treatment (p < 0.05).
According to the results in Table 2, the measurements at the end of the treatment periods were compared with the baseline levels for the groups in which a significant difference was found between repeated measurements, and the results are given in Table 3.Table 3 The pairwise comparison
Cyclosporine Immunotherapy
Papillary reaction Baseline/1th month†† 0.998 0.998
Baseline/3rd month†† 0.102 0.038
Baseline/6th month†† 0.034 0.026
Limbal involvement Baseline/1th month†† 0.655 0.564
Baseline/3rd month†† 0.18 0.034
Baseline/6th month†† 0.066 0.01*
Corneal involvement Baseline/1th month†† 0.783 –
Baseline/3rd month†† 0.034 –
Baseline/6th month†† 0.038 –
Conjunctival hyperemia Baseline/1th month†† 0.603 0.998
Baseline/3rd month†† 0.071 0.062
Baseline/6th month†† 0.01* 0.004*
*p < 0.02 was considered as statistically significant for the pairwise comparisons (Bonferroni multiple comparison)
In the cyclosporine and immunotherapy groups, the conjunctival hyperemia showed statistically significant differences both in the later stages of the treatment (Table 2) and at the 6th month of the treatment compared to the baseline (Table 3) (p < 0.02).
In both groups, although the limbal involvement decreased in the later stages of the treatment (Table 2), there was no statistically significant difference in Group 1 (Table 3) (p > 0.02) while immunotherapy group showed a statistically significant difference compared to the baseline level at the 6th month (Table 3) (p < 0.02).
Although the corneal involvement levels in the cyclosporin group decreased in the later stages of the treatment (Table 2), there was no statistically significant difference compared to the baseline level at the 6th month (Table 3) (p > 0.02).
In both cyclosporine and immunotherapy groups, the sign of papillary reaction showed a statistically significant decrease in the later stages of treatment (Table 2), but no statistically significant difference was found at the 6th month compared to the baseline level (Table 3) (p > 0.02).
Discussion
This study compared clinical efficacy of two treatment modalities (cyclosporin A and immunotherapy) in perennial allergic conjunctivitis and found almost similar efficacy in terms of sign improvement during 6-month follow-up period. To the best of our knowledge, this study is the first comparing these to treatment types in perennial allergic conjunctivitis.
Large number of studies provided evidence on the use of cyclosporin in the treatment of allergic conjunctivitis cases. A meta-analysis with seven eligible studies examined the benefits of topical cyclosporine in a spectrum of allergic conjunctivitis types [2]. The studies compared cyclosporin treatment with placebo and found significant reductions in sign and symptom scores in association with cyclosporin use beyond 2 weeks [2]. In addition, steroid sparing effect of cyclosporin treatment was evident [2]. Most of the evidence on the effectiveness of cyclosporin treatment comes from severe allergic conjunctivitis cases, mainly vernal keratoconjunctivitis. A recent meta-analysis including 27 studies examined different medical treatments in 1749 vernal keratoconjunctivitis cases. The most frequently used drugs were mast cell stabilizers, cyclosporine, and tacrolimus. Significant symptom/sign improvements were found in association with cyclosporin treatment as well as mast cell stabilizers, tacrolimus, and other less frequently used treatments [17]. A recent randomized controlled trial confirmed the significant benefits of cyclosporine A in pediatric vernal keratoconjunctivitis in terms of both sign/symptom improvement and rescue medication requirement [18]. Similar findings were obtained in an Indian study [19]. Beneficial effects of cyclosporin treatment sign/symptom improvement as well as steroid sparing effects- has been consistently demonstrated in patients with severe keratoconjunctivitis [18–23]. Findings of the present study in association with cyclosporin use indicating improvements in most signs are in line with the findings of those previous studies.
The benefits of another immunomodulator agent tacrolimus have also been demonstrated in allergic conjunctivitis. The study by Shoji et al. examined topical tacrolimus in chronic allergic conjunctival disease with and without atopic dermatitis and found equal effectiveness at 6 months of treatment [24]. Cyclosporin and tacrolimus seem to have equal effectiveness in severe keratoconjunctivitis [25], whereas tacrolimus was found to be more effective in cyclosporin resistant cases [26]. In addition, the benefit of combined immunomodulator treatment (cyclosporin plus tacrolimus) has also been demonstrated in patients with severe vernal keratoconjunctivitis [27].
Allergen immunotherapy is considered an effective and safe treatment modality for patients moderate to severe refractory ocular allergic disease and demonstrated sensitization to a specific allergen, which may provide long-term relief [28]. Allergen immunotherapy can be administered via subcutaneous, sublingual, and transcutaneous routes in ocular allergy [28–33], although the latter has been rarely reported [29]. In a recent guideline, immunotherapy is considered the only currently available treatment targeting disease pathophysiology in allergic rhino conjunctivitis, thus exhibiting a disease-modifying effect [14]. It is recommended for both seasonal and perennial allergic rhino conjunctivitis for short-term benefit [14]. Both sublingual and subcutaneous routes may be used, usually based on the preference of the patient, with similar efficacy and compliance [30, 31, 33], although sublingual for may be more cost effective [34]. Subcutaneous route has been considered the traditional gold standard administration route for allergen immunotherapy by some authors [28] and this route is the only preferable option in Turkey.
Several recent studies have demonstrated the safety and efficacy of allergen immunotherapy in nasal and ocular allergy. A recent study examined the efficacy and safety of allergen immunotherapy in allergic conjunctivitis [30] in patients with positive skin prick test results. Both subcutaneous and sublingual routes were used in the study, and they were compared. No significant difference was found between the two routes. Significant improvements were found in both groups in terms of symptom relief, reduction in total IgE levels, and wheal diameter of skin prick test. Both treatments were well tolerated with no serious adverse events. A 2019 study examined the efficacy of immunotherapy in perennial form of allergic rhinitis [35]. The study by Tizro et al. used accelerated subcutaneous rush allergen immunotherapy in patients with perennial allergic rhinitis and found significant changes in terms of symptom and quality of life improvement as well as a significant reduction in IgE levels. Findings of the present study are in line with those of previous studies, where significant improvements were found in most sign scores in the immunotherapy group.
Findings of this study have several implications for clinical practice. Effective symptom control has the potential to improve quality of life in allergic conjunctivitis [7]. However, symptom control in perennial allergic conjunctivitis is usually challenging, particularly for treatment refractive cases since effective treatment and avoidance of allergens are necessary all year round. In addition, inadequately managed perennial allergic conjunctivitis can cause dry eye, corneal involvement with chronic inflammatory reaction, and impaired tear film quality [36]. The objectives of the management of perennial allergic conjunctivitis are to prevent ocular surface injury and improve quality of life as well as to provide effective symptom control. Long-term use of topical/systemic polypharmacotherapy has the potential for untoward side effects. For example, long-term use of steroids has the potential to cause cataract and glaucoma. Although cyclosporin A, the other option for the treatment of refractive and/or severe cases, does not usually have severe side effects, its long term use may cause stinging/burning sensation due to the preservative used in the solution; and even molluscum contagiosum, papilloma virus, and herpes virus infections have been reported in association with its long-term use [37]. On the other hand, allergen specific immunotherapy represents an option for treatment refractory cases. Immunotherapy may particularly be useful in perennial allergic conjunctivitis owing to its relatively rapid and sustained effect following hypo-sensitization [11, 12], which has the potential to reduce the need for pharmacotherapy to avoid their side effects as well as to decrease the severity of symptoms and to prevent the development of new sensitizations to aeroallergens. We suggest that allergen immunotherapy can be initiated early in treatment resistant cases to prevent development of asthma, and to improve patient compliance and quality of life. However, immunotherapy should be done under close supervision since it rarely causes life-threatening allergic reactions.
This study has several limitations. The small sample size does limit the generalization of the findings. In addition, a longer follow-up period could have been appropriate to see the clinical effects of SCIT. However, the accelerated SCIT protocol reduced the travel times and hospital visits during the COVID-19 pandemic and provided a faster improvement in allergy symptoms of the patients [38]. In addition, we believe that the absence of symptom evaluation is another limitation. The study was retrospective in nature and a validated instrument was not being used routinely in our institution. In addition, the routine questioning of the symptoms and incorporating them into the study was not possible during the study period since the evaluation of patient history was mostly unsatisfactory during the Covid pandemic. Similarly, post-treatment IgE levels could not be obtained due to the pandemic conditions, although pre-treatment values were available. Changes in IgE levels could contribute to the study and absence may also be regarded as a limitation.
In conclusion, the findings of this study suggest that allergen immunotherapy and cyclosporin A treatment may provide effective sign relief in perennial allergic conjunctivitis. Thus, it may represent a viable treatment option for treatment refractive perennial allergic conjunctivitis cases with positive skin test result for a specific allergen (house dust in the present study), where sign control in the long-term and reduction of the side effects of polypharmacotherapy is particularly important. Large studies with longer follow-up are warranted.
Acknowledgements
None.
Author’s contribution
Design of the study (C.U.D., C.T., İ.Ç.T., D.Ç., A.A.A., S.D.); conduct of the study (C.U.D., C.T., İ.Ç.T., D. Ç., A.A.A., S.D.); collection and management of data (C.U.D., C.T., İ.Ç.T., D. Ç., A.A.A , S.D.); analysis and interpretation of data (C.U.D., C.T., İ.Ç.T., DÇ D. Ç., A.A.A , S.D.); preparation of manuscript (C.U.D., C.T., İ.Ç.T., D. Ç., A.A.A , S.D.); review or approval of manuscript (C.U.D., C.T., İ.Ç.T., D. Ç., A.A.A, S.D.).
Funding
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
Declarations
Conflict of interest
The authors declare no conflict of interest. We have no financial disclosures to report.
Ethical approval
This clinical study is adhered to the tenets of the Declaration of Helsinki and its later amendments and was approved by the Local Ethics Committee of Gaziosmanpaşa Training and Research Hospital, İstanbul, Turkey.
Consent to participate
Informed consent was obtained from all participants included in the study.
Consent for publication
All participants have provided consent for publication.
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.
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| 36513916 | PMC9747541 | NO-CC CODE | 2022-12-15 23:22:01 | no | Int Ophthalmol. 2022 Dec 14;:1-9 | utf-8 | Int Ophthalmol | 2,022 | 10.1007/s10792-022-02612-y | oa_other |
==== Front
J Child Adolesc Trauma
J Child Adolesc Trauma
Journal of Child & Adolescent Trauma
1936-1521
1936-153X
Springer International Publishing Cham
502
10.1007/s40653-022-00502-0
Original Article
Associations between Adverse Childhood Experiences and Pandemic-Related Stress and the Impact on Adolescent Mental Health during the COVID-19 Pandemic
http://orcid.org/0000-0003-3112-018X
Verlenden Jorge [email protected]
1
Kaczkowski Wojciech 1
Li Jingjing 1
Hertz Marci 1
Anderson Kayla N. 2
Bacon Sarah 3
Dittus Patricia 1
1 grid.416738.f 0000 0001 2163 0069 Centers for Disease Control and Prevention (CDC), National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Division of Adolescent and School Health (CDC/NCHHSTP/DASH), Atlanta, GA USA
2 grid.453275.2 0000 0004 0431 4904 Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, Division of Violence Prevention (CDC/NCIPC/DVP), Atlanta, GA USA
3 grid.453275.2 0000 0004 0431 4904 Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, Office of Strategy and Innovation (CDC/NCIPC/OSI), Atlanta, GA USA
14 12 2022
115
16 11 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.
Vulnerabilities of adolescents during times of crisis have been previously identified, but little research has investigated the compounding effects of lifetime adversities and pandemic-related stress on adolescent mental health. This study uses adolescent self-report data to model relationships between stress exposures and indicators of poor mental health from the longitudinal COVID Experiences (CovEx) Surveys. These surveys were administered online in English to U.S. adolescents ages 13–19 using the NORC AmeriSpeak® panel, a probability-based panel designed to be representative of the U.S. household population. Two waves of data were collected (Wave 1: October–November 2020, n = 727; Wave 2: March–May 2021, n = 569). Measures included demographics, adverse childhood experiences (ACEs, 8 items), pandemic-related stress (Pandemic-Related Stress Index [PRSI], 7 items), and depression symptoms (Patient Health Questionnaire for Adolescents [PHQ-A], 9 items). Path analyses were conducted to examine pathways between Wave 1 ACEs, Wave 1 PRSI, and Wave 2 PHQ with covariates of sex and race/ethnicity. Females had higher ACEs, PRSI, and PHQ scores than males. The PRSI score at Wave 1 was positively associated with the PHQ at Wave 2 (b = 0.29, SE = 0.14, p < 0.001). ACEs at Wave 1 were positively associated with PRSI at Wave 1 (b = 0.31, SE = 0.03, p < 0.001) and with PHQ at Wave 2 (b = 0.32, SE = 0.12, p < 0.001). The direct effect of ACEs on PHQ (b = 0.23, SE = 0.12, p < 0.001) remained significant even after accounting for the indirect effect of pandemic-related stress (b = 0.09, SE = 0.05, p < 0.001). Pandemic-related stress had a direct, adverse impact on adolescent depressive symptoms and demonstrates a compounding effect of childhood adversity and pandemic-related stress on depression. Findings can aid the design of interventions that promote mental health and support adolescent coping and recovery.
Supplementary Information
The online version contains supplementary material available at 10.1007/s40653-022-00502-0.
Keywords
Adolescents
Adverse childhood experiences
Stress
COVID-19 pandemic
Depression
Health
Mental health
==== Body
pmcThe COVID-19 pandemic has caused widespread disruptions and significant stress for millions of people, including children and adolescents (Hertz et al., 2021; Krause et al., 2022; McKnight-Eily et al., 2021; Meade, 2021). In 2020, the American Psychological Association (APA) warned about the potential long-term physical and mental health impact of pandemic-related stress, reporting that adolescents and young adults were showing unprecedented stress levels (American Psychological Association, 2020). Vulnerabilities of young populations during public health emergencies, such as natural disasters and significant outbreaks of infectious disease, have been previously identified (Fothergill & Peek, 2021; Lori, 2008; Masten & Narayan, 2012). However, little research has investigated the pre-pandemic factors that might intensify pandemic-related stressors, such as parental job loss, household illness, and worsened relationships, resulting in negative mental health outcomes (Stinson et al., 2021). To address this gap, we examine the impact of exposure to adverse childhood experiences (ACEs), together with pandemic-related stressors, on symptoms of depression among adolescents ages 13 to 19 to inform prevention and intervention strategies accordingly.
Risk for Children and Adolescents during and after Public Health Emergencies
Children and adolescents have specific developmental needs and characteristics that can place them at unique and heightened risk for negative health outcomes during public health emergencies. These can include, for example, differences from adults in physiology; behavioral, cognitive, and emotional development; and dependence on others for basic needs provision (Fothergill & Peek, 2021; Krug et al., 2015; Lai & La Greca, 2020; Lori, 2008; Masten & Narayan, 2012). Additional contextual and situational factors can contribute to negative outcomes for children and adolescents during public health emergencies, including the degree of exposure and proximity to crisis; extent of community disruption; family stressors, such as job, housing, and food insecurity; and experience with personal loss, including loss of life, property, or routines (Briere & Scott, 2015; Furr et al., 2010; Kinner & Borschmann, 2017; Osofsky et al., 2015).
Some subpopulations already disproportionately experience poor mental health outcomes due to the structural and social inequities that influence the quality and safety of where they live, work, and play (Braveman, 2014; Compton & Shim, 2015; Cooper et al., 2018; Harris et al., 2020). These inequities are often exacerbated by public health emergencies, creating compounded inequities and amplifying risks for some children and adolescents, including those who identify as sexual and gender minorities; are from historically marginalized racial and ethnic groups; have a disability; or live in poverty (Hoffman & Kruczek, 2011; Kronenberg et al., 2010; Okonkwo et al., 2020; Shim, 2020; Shim & Starks, 2021). This suggests that children and adolescents who have experienced inequities prior to a public health emergency may be at increased risk for poor mental health-related outcomes following an emergency.
Risks to Mental Health
Many children and adolescents who have experienced public health emergencies show emotional adjustment reactions including regression of behaviors from a prior developmental stage, somatic symptoms, and bereavement; many are also at increased risk for experiencing chronic mental health symptoms (Fothergill & Peek, 2021; Masten & Osofsky, 2010). Stress exposures caused by public health emergencies have been consistently linked to elevated depression, anxiety, and traumatic-stress-related pathology in children and adolescents, especially in situations where there is a significant loss of life (Fothergill & Peek, 2021; Furr et al., 2010; Mills et al., 2020; Osofsky et al., 2015; Tang et al., 2014).
Public health emergencies can also result in disruptions to support systems (e.g., school, community, peer, family), which can erode feelings of safety and impact the psychological functioning of children and adolescents (Fothergill & Peek, 2021; Lai & La Greca, 2020). Since the outbreak of the novel coronavirus and subsequent declaration of COVID-19 as a global pandemic, many children and adolescents have directly experienced an array of disruptions, including widescale school closures, loss of health services, social isolation, and deaths of family members, any of which might result in increased risk for negative mental health outcomes (Krause et al., 2022; Meade, 2021; Verlenden et al., 2021).
Elevated risks due to Previous Adversity
Previous exposure to ACEs can exacerbate the risk for poor mental health outcomes during public health emergencies (Oldfield et al., 2018; Whaley et al., 2020). ACEs are preventable, potentially traumatic events that occur in childhood (aged 0–17 years), such as neglect, experiencing or witnessing violence, and having a family member attempt or die by suicide (Ports et al., 2020). ACEs may also include aspects of a child’s environment that can undermine their sense of safety, stability, and bonding, such as growing up in a household with substance use or mental health problems, or instability due to parental separation or incarceration of a parent, sibling, or other members of the household (Ford et al., 2014; LeMoult et al., 2020; Merrick et al., 2018; Ports et al., 2020).
Unfortunately, ACEs are common. Approximately two-thirds of adults in the general US population have had at least one type of ACE; one in six had 4 or more ACEs (Merrick et al., 2018). ACEs often occur together (Brown et al., 2019; Bussemakers, et al., 2019) and are associated with a range of less optimal health, behavioral, and social outcomes across the lifespan (Merrick et al., 2019; Mills et al., 2020). For example, individuals who have ACEs have higher rates of anxiety and depression symptoms (Sheffler et al., 2020), and a cumulative dose–response relationship exists between the number of ACEs and lifetime prevalence of depressive disorders (Clements-Nolle et al., 2018; LeMoult et al., 2020; Merrick et al., 2019). Exposure to ACEs may also exacerbate inequities in health, social, and economic outcomes across generations (Dominguez & Brown, 2022; Lensch et al., 2021; Shonkoff et al., 2021).
Depression in Adolescence
Depression is a serious condition that negatively affects how a person feels, thinks, and acts (American Psychiatric Assocation, 2022; Malhi & Mann, 2018). Symptoms of depression can vary from mild to severe and can include having a depressed mood, loss of interest in activities, appetite changes, fatigue, agitation or fidgetiness, feelings of unworthiness and guilt, difficulty concentrating, and thoughts of suicide (American Psychiatric Assocation, 2022). Depression is a leading mental health concern for adolescents. It is associated with a range of adverse outcomes, including increased risk for substance use problems, suicidality, academic difficulties, poor physical health, as well as other mental disorders (Bethell et al., 2019; Bitsko et al., 2022; Jones et al., 2016, 2022; Katon et al., 2010). According to 2020 data examining past year depression, approximately 17% of U.S. adolescents had at least one major depressive episode during the past year (2019) with prevalence higher among adolescent females (25.2%) compared to males (9.2%; Substance Abuse & Mental Health Services Administration, 2020). Other national data have also indicated that the prevalence of depression among adolescents had risen significantly in the years before the pandemic (Lebrun-Harris et al., 2022). See Mental Health Surveillance Among Children — United States, 2013–2019 | MMWR (cdc.gov) for a comprehensive overview of children and adolescent mental health surveillance and for prevalence estimates from before the pandemic (Bitsko et al., 2022).
Research suggests that symptoms and rates of depression among adolescents have increased during the pandemic (Chaabane et al., 2021; Zolopa et al., 2022). For example, a cohort study of adolescents that assessed changes in symptoms of mental disorders from before and during the pandemic identified increases in depression from July 2019 to May 2020, especially among females (Hawes et al., 2021). Additionally, a national syndromic surveillance data analysis found increases in emergency department visits related to depressive disorders in 2021 compared to 2019 among adolescent females aged 12–17 years (Radhakrishnan et al., 2022).
Considering evidence of the rising rates of depression among adolescents before and during the pandemic, as well as the long-term health risks associated with depression, it is important to understand factors that may contribute to increases in depression during the pandemic to guide public health response to the ongoing children’s mental health crisis (Shim et al., 2022). Specifically, the identification of potential causal pathways can inform the development of programming to ameliorate or reduce risk and facilitate more positive trajectories and support; guide allocation of needed resources for early intervention to allay symptoms; and facilitate implementation of mental health promotion and prevention initiatives (Mendelson & Tandon, 2016; Morina et al., 2017; Tang et al., 2014).
Examining Effects of Public Health Emergencies on Adolescent Mental Health
Public health emergencies influence the proximal and distal systems within which adolescents exist and interact, including home, schools, jobs, neighborhoods, society, and social support networks (Hoffman & Kruczek, 2011; Layne et al., 2010; Pynoos et al., 2014). As such, understanding the impact of a public health emergency on adolescent mental health involves consideration of direct and indirect effects as well as contexts particularly relevant to adolescent development (Bronfenbrenner & Morris, 2007; Hoffman & Kruczek, 2011; Spencer et al., 1997; Stern et al., 2021). Amidst the COVID-19 pandemic, for example, education, employment, health, safety, and travel mandates resulted in disruptions that may have amplified stress and adversity in some ways, yet reduced them in others (Brown et al., 2020; Krause et al., 2022; Prime et al., 2020). As such, the impact of a public health emergency such as the COVID-19 pandemic on adolescent mental health must be assessed in terms of social and community contexts, factoring in appraisals of stress and support and considering unfolding effects across time (Fothergill & Peek, 2021; Lori, 2008; Masten & Narayan, 2012).
To date, limited research has attempted to investigate the mental health impact of the pandemic on adolescents by considering contexts, systems, phenomenological perspectives, and compound effects (Shim et al., 2022). To address this need, we use longitudinal data from a nationwide sample of adolescents ages 13 to 19 to develop an index of pandemic-related stress experiences, identifying temporal-specific, episodic stressors. We then use the index to examine direct and indirect relationships among adolescent reports of ACEs, pandemic-related stress experiences, and depressive symptomology. We also consider the extent to which sex at birth and race/ethnicity influence associations and risk of depression.
Methods
Setting, Procedures, and Participants
The COVID Experiences Study (CovEx) included the administration of longitudinally designed surveys to adolescents 13–19 years of age (at Wave 1) using the National Opinion Research Center’s (NORC) at the University of Chicago AmeriSpeak® Panel, a probability-based panel of approximately 40,000 households. Two waves of survey data were collected to capture the experiences of adolescents during the COVID-19 pandemic and to examine the impact of COVID-19 on their health and well-being over time. Surveys were administered online or via telephone, with Wave 1 surveys fielded October 16—November 6, 2020 and Wave 2 surveys fielded April 2—May 7, 2021. This activity was reviewed by CDC and conducted consistent with applicable federal law and CDC policy; see 45 C.F.R. part 46; 21 C.F.R. part 56; 42 U.S.C. Section 241(d), 5 U.S.C. Section 552a, 44 U.S.C. Section 3501 et seq. 45 C.F.R. part 46; 21 C.F.R. part 56. The study was also reviewed and approved by the Institutional Review Board of NORC at the University of Chicago.
Adolescents were recruited for participation in the study using three AmeriSpeak sources: 1) adolescents ages 18–19 were recruited from the NORC AmeriSpeak® Panel, 2) adolescents ages 13–17 who had been previously recruited from AmeriSpeak® Panel households to join the AmeriSpeak® Teen Panel, and 3) adolescents ages 13–17 living in AmeriSpeak® Panel households who had not joined the AmeriSpeak® Teen Panel. A parent or legal guardian provided consent for adolescents 13–17 years of age, and each adolescent participant assented. Adolescents ages 18–19 years consented for themselves. Only one adolescent per household was eligible for selection (random within household sampling). All adolescents that completed the Wave 1 survey (NW1 = 727) were invited to participate in the follow-up Wave 2 survey (78.3% completion rate, NW2 = 569) resulting in an attrition rate of 21.7%. All adolescents re-assented before beginning the follow-up survey. We found no significant demographic differences between Wave 1 and 2 participants. After restricting to participants responding at both waves, the final analytical sample size is 569. Path analyses were conducted with list-wise deletion. See Table 1 for characteristics of the analytic sample.Table 1 Demographic characteristics of study sample and properties of main study variables (N = 569)
Study Sample (unweighted)
n %
Sex at Birtha
Male 265 46.6
Female 300 52.7
Age
13–14 162 28.5
15–17 312 54.8
18–19 95 16.7
Race/Ethnicity
White, non-Hispanic 308 54.1
Black, non-Hispanic 70 12.3
Hispanic/Latinx 121 21.3
All Other races, non-Hispanicb 70 12.3
Sexual Identityc
Lesbian/Gay 15 2.6
Straight/Heterosexual 454 79.8
Bisexual 58 10.2
Another identity /Unsure 40 7.0
Annual Household Income
≤ $34,999 159 27.9
$35,000-$49,999 71 12.5
$50,000-$74,999 111 19.5
$75,000-$99,999 77 13.5
≥ $100,000 151 26.5
M SD
ACEsd Wave 1 (n = 478) 1.30 1.72
PRSIe score Wave 1 (n = 569) 1.73 1.43
PHQ-Af Wave 2 (n = 556) 6.01 4.79
Sample drawn from the nationwide, longitudinal COVID Experiences Study (CovEx) of Adolescents 13–19 years of age (at Wave 1, October—November 2020) using the National Opinion Research Center’s (NORC) at the University of Chicago AmeriSpeak® and AmeriSpeak Teen® panels. Table shows unweighted frequencies and row percentages for demographic characteristics based on Wave 1 report and means (M) and Standard Deviations (SD) of main study variables
aAdolescents reported sex at birth in response to the survey question: “What sex were you assigned at birth, on your original birth certificate?”
bAll Other races category includes Asian, American Indian or Alaska Native, Native Hawaiian or Pacific Islander, some other race, or selected more than one race category
cAdolescents were asked “Which of the following best represents how you think of yourself?” and provided the following response options: “Lesbian or gay; straight, that is, not lesbian or gay; bisexual; something else; and I don’t know the answer.”
dAdverse Childhood Experiences (ACEs) were based on eight Wave 1 survey items for which adolescent respondents identified whether they experienced any of the following at any point since they were born: (1) physical abuse; (2) emotional abuse; (3) sexual violence; (4) witnessing intimate partner violence; (5) parental divorce; (6) family member serving time in jail; (7) family member with a mental health condition; (8) family member with a substance use problem. Sum scores with a range of 0 to 8 were used to indicate ACEs exposure to date (Wave 1)
ePandemic-Related Stress Index (PRSI) includes seven items assessing stress exposure during the pandemic in the following areas: (1) family/parent job loss, (2) economic insecurity, (3) worsened family/household relationships, (4) lack of support from friends, (5) COVID-19 personal illness, (6) COVID-19 family member illness, and (7) missed health care when needed. Responses are dichotomized with a sum score calculated (range = 0 to 7). A higher sum score indicates accumulation of more pandemic-related stress experiences at Wave 1
fPatient Health Questionnaire Adolescent (PHQ-A) responses at Wave 2 of survey administration (April—May 2021) were used to assess depressive symptomology, measuring number and frequency of symptoms experienced in the past 14 days (response options: 0,1, or 2 days; 3–6 days, 7–14 days), with each item response coded as 0, 1, or 2 respectively. Higher sum score indicates experiencing more symptoms of depression and greater frequency of symptoms in the past two weeks
Measures
Demographic Covariates
Considering empirical support of differences by sex in the prevalence of internalizing conditions among youth and in the manifestation of effects of ACEs and stress on mental health, we included sex at birth as a covariate (Hogye et al., 2022; Merrick et al., 2018). Adolescents reported sex at birth in response to the survey question: “What sex were you assigned at birth on your original birth certificate?” Gender identity and sexual orientation were not included as covariates in this study. Although differences in experiences of adversity and stress across gender and sexual orientation are salient, especially among adolescents who identify as transgender and among adolescents who identify as lesbian, gay, or bisexual (Brown et al., 2019; Craig et al., 2020), investigating such differences was outside the scope of the analysis conducted.
Adolescent race/ethnicity was also included as a covariate. Race/ethnicity was based on information gathered during the initial recruitment of adolescent participants into the AmeriSpeak® and AmeriSpeak Teen® national panels. Adolescents self-reported their Hispanic ethnicity and race, which were categorized as White, non-Hispanic; Black, non-Hispanic; Hispanic/Latinx; or another race non-Hispanic inclusive of Asian, American Indian or Alaska Native, Native Hawaiian or Pacific Islander, some other race, or selection of more than one race category.
Adverse Childhood Experiences (ACEs)
We used eight Wave 1 survey items to assess exposure to ACEs, which are broadly aligned with the core ACEs constructs included in the Behavioral Risk Factor Surveillance System (BRFSS) ACEs module (Merrick et al., 2019), and the Youth Risk Behavior Survey (YRBS; Anderson et al., 2022). Similar ACEs questions have been used in other research involving adolescents (Clements-Nolle et al., 2018; Lensch et al., 2021). For this study, each adolescent respondent identified whether they experienced any of the following at any point since they were born: (1) physical abuse by any perpetrator; (2) emotional abuse by a household member; (3) sexual violence by any perpetrator; (4) witnessing intimate partner violence; (5) parental divorce; (6) family member serving time in jail; (7) family member with a mental health condition; (8) family member with a substance use problem. Sum scores ranging from 0 to 8 were used to indicate ACEs exposure to date (Wave 1).
Pandemic-Related Stress Index (PRSI)
We developed the pandemic-related stress index (hereafter PRSI) to assess stressors experienced within the timeframe of the COVID-19 pandemic at Wave 1. While creating the PRSI, we evaluated all Wave 1 survey items from the CovEx survey of adolescents (ni = 92) for their potential as indicators of pandemic-related stress exposure in the following domains: material, relational, social/societal, health services, education, COVID-19, and stress appraisal. Items that did not measure experiences related to pandemic-related stress were omitted from consideration (ni = 68), as were items with high missingness and skipping patterns (ni = 7), items that did not align with the specified timeframe (ni = 3), and items with relatively low principal component loadings and Cronbach’s alphas (ni = 12). As part of the index development process, we implemented a principal components analysis (PCA) to reduce the number of variables in the index while preserving as much information as possible. Since most of our index items were binary, we conducted a logistic PCA, which does not require a matrix factorization but instead uses projections of the natural parameters from the saturated model (Landgraf, 2016; Landgraf & Lee, 2015). Figure A1 illustrates the process of item selection and exclusion.
The final PRSI includes 7 items assessing stress exposure during the pandemic in the following areas: (1) family/parent job loss, (2) economic insecurity, (3) worsened family/household relationships, (4) lack of support from friends, (5) COVID-19 personal illness, (6) COVID-19 family member illness, and (7) missed health care when needed. Responses are dichotomized with a sum score calculated (range = 0 to 7). A higher sum score indicates accumulation of more pandemic-related stress experiences at Wave 1. See Appendix A for supplementary information related to PRSI development.
Patient Health Questionnaire for Adolescents (PHQ-A)
The PHQ-A is a nine-item mental health screening instrument validated for use among adolescents to identify risk for depression (Johnson et al., 2002). Criteria align with the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5®) diagnosis of depressive disorders. As a screening instrument for depression, the PHQ-A has demonstrated satisfactory specificity, sensitivity, diagnostic agreement, and overall diagnostic accuracy (i.e., positive and negative predictive power) when compared to comprehensive diagnostic interview tools (e.g., Diagnostic Interview Schedule for Children) and has been used widely in research and health care settings (Kroenke et al., 2009). Adolescent responses to PHQ-A items at Wave 2 of survey administration were used to assess depressive symptomology, measuring the number and frequency of symptoms experienced in the past 14 days (response options: 0 days; 1 or 2 days; 3–6 days; 7–14 days); the scale showed good internal consistency (α = 0.92). Sum scores ranged from 0 to 18.
Analysis
Descriptive statistics, Pearson correlations, and Cronbach’s alpha estimates were obtained for all variables, using SAS version 9.4. For the hypothesized model (Fig. 1), path analysis was used to examine the associations between ACEs (Wave 1), pandemic-related stress (PRSI, Wave 1), and depressive symptoms (PHQ-A, Wave 2). Covariates included sex assigned at birth (male as referent) and race/ethnicity (White as referent). For the goodness of fit analyses, the model chi-square (χ2), the comparative fit index (CFI), and the root mean square error of approximation (RMSEA) were used (Kline, 2015). The χ2 assesses overall fit and the discrepancy between the sample and the fitted covariance matrices, with non-significant χ2 values (p > 0.05) indicating good model fit. The CFI values range from 0 to 1, with higher values indicating better fit. The RMSEA values range from 0 to 1, with smaller values indicating better model fit. The CFI ≥ 0.95 and the RMSEA ≤ 0.08 are generally recommended as cut-off points indicating acceptable model fit (Hu & Bentler, 1999).Fig. 1 Conceptual model depicting hypothesized relationships of Adverse Childhood Experiences (ACEs) and Pandemic-Related Stress Index (PRSI) reported at Wave 1(W1), and symptoms of depression at Wave 2 (W2) (PHQ-A). The conceptual model depicts hypothesized relationships and directionality of relationships among predictor variables and the outcome of outcome of interest. W1 ACEs reflects adolescent reported exposure to experiences of early adversity. W1 PRSI reflects adolescent reported pandemic-related stress exposures. W2 PHQ-A reflects depression symptoms reported by adolescents. Wave 1 data were collected October—November 2020 and Wave 2 data were collected April—May 2021. Covariates include sex (i.e., sex assigned at birth) and race/ethnicity (i.e., Black non-Hispanic, Hispanic/Latinx, White non-Hispanic, and all Other Races including Asian, American Indian or Alaska Native, Native Hawaiian or Pacific Islander, some other race, or selected more than one race category). Variables drawn from the nationwide, longitudinal COVID Experiences Study (CovEx) of Adolescents 13–19 years of age using the National Opinion Research Center’s (NORC) at the University of Chicago AmeriSpeak® and AmeriSpeak Teen® panels
Results
Descriptives
Table 1 describes unweighted demographic characteristics of the analyzed sample based on Wave 1 data, including adolescents’ sex assigned at birth, age, race and ethnicity, sexual identity, and annual household income. The participant sample was evenly distributed by sex with 52.7% indicating sex at birth as female. Most participants (54.8%) were between the ages of 15 and 17 years, 28.5% were 13–14 years of age, 16.7% were 18–19 years. Over half (54.1%) of the sample identified as White non-Hispanic, 21.3% as Hispanic/Latinx, 12.3% Black non-Hispanic, and 12.3% another race non-Hispanic.
Table 2 provides item-level frequencies reported at Wave 1 for ACEs and for the pandemic-related stress index (PRSI). For ACEs, percentages ranged from 3.5% (“sexual violence”) to 30.0% (“parental divorce”); for the PRSI percentages ranged from 14.5% (“worsened family/household relationships”) to 40.6% (“family/parent job loss”). Table 3 provides item-level frequencies for the PHQ-A at Wave 2 that indicate the presence of depressive symptoms in the past 14 days. The percentage of adolescents indicating persistence of depressive symptom for 7–14 days ranged from 6.7% (“thoughts that you would be better off dead, or of hurting yourself”) to 21.3% (“feeling tired or having little energy”). Table 4 provides Pearson correlations, means, and standard deviations for all variables and covariates in the model. The three model variables (i.e., ACEs, PRSI, PHQ-A) were positively and significantly correlated. They were also correlated with the sex covariate, with women more likely to report ACEs and pandemic-related stressors at Wave 1 and depressive symptoms at Wave 2. See supplemental tables in Appendix A for additional bivariate results, including associations among demographic characteristics and each of the three model variables.Table 2 Descriptive Statistics of Wave 1 Adverse Childhood Experiences (ACEs) and Pandemic-Related Stress Index (PRSI) Items (N = 569)
No Yes
N % N %
Adverse Childhood Experiencesa
ACE 1. Parental divorce 383 70.0 164 30.0
ACE 2. Family member serving time in jail 401 75.5 130 24.5
ACE 3. Family member with a mental health condition 449 83.0 92 17.0
ACE 4. Witnessing intimate partner violence 432 80.1 107 19.9
ACE 5. Emotional abuse 523 96.3 20 3.7
ACE 6. Sexual violence 525 96.5 19 3.5
ACE 7. Physical abuse 489 88.9 61 11.1
ACE 8. Family member with a substance misuse problem 466 84.6 85 15.4
Pandemic Related Stress Indexb
PRSI 1. Family/ parent job loss 312 59.4 213 40.6
PRSI 2. Economic insecurity 348 61.7 216 38.3
PRSI 3. Worsened family/ household relationships 482 85.5 82 14.5
PRSI 4. Lack of support from friends 415 73.1 153 26.9
PRSI 5. COVID-19 Personal illness 420 79.8 106 20.2
PRSI 6. COVID-19 Family member illness 473 83.6 93 16.4
PRSI 7. Missed health care when needed 445 78.2 123 21.7
Table shows unweighted frequencies and row percentages based on response to items from Wave 1 survey administration (October—November 2020) of the nationwide, longitudinal COVID Experiences Study (CovEx) of Adolescents 13–19 years of age administered using the National Opinion Research Center’s (NORC) at the University of Chicago AmeriSpeak® and AmeriSpeak Teen® panels
aAdverse Childhood Experiences (ACEs) were based on eight Wave 1 survey items for which adolescent respondents identified whether they experienced any of the following at any point since they were born: (1) physical abuse; (2) emotional abuse; (3) sexual violence; (4) witnessing intimate partner violence; (5) parental divorce; (6) family member serving time in jail; (7) family member with a mental health condition; (8) family member with a substance use problem
bPandemic-Related Stress Index (PRSI) includes seven items assessing stress exposure during the pandemic in the following areas: (1) family/parent job loss, (2) economic insecurity, (3) worsened family/household relationships, (4) lack of support from friends, (5) COVID-19 personal illness, (6) COVID-19 family member illness, and (7) missed health care when needed
Table 3 Descriptive statistics of wave 2 patient health questionnaire for adolescents (PHQ-A) item responses (N = 569)
Response option groupings
0 days 1 or 2 days; or
3 to 6 days 7 to 14 days
PHQ-Aa Items N % N % N %
PHQ-A 1. Feeling down, depressed, or hopeless 226 39.9 282 49.7 59 10.4
PHQ-A 2. Trouble falling or staying asleep, or sleeping too much 185 32.7 265 46.8 116 20.5
PHQ-A 3. Feeling tired or having little energy 142 25.0 304 53.6 121 21.3
PHQ-A 4. Poor appetite or overeating 247 43.9 228 40.5 88 15.6
PHQ-A 5. Feeling bad about yourself or that you are a failure or have let yourself or your family down 259 45.9 217 38.5 88 15.6
PHQ-A 6. Trouble concentrating on things, such as reading the newspaper or watching television 283 49.9 214 37.7 70 12.3
PHQ-A 7. Little interest or pleasure in doing things 247 43.6 251 44.3 68 12.0
PHQ-A 8. Moving or speaking so slowly that other people could have noticed. Or the opposite being so fidgety or restless 371 65.7 147 26.0 47 8.3
PHQ-A 9. Thoughts that you would be better off dead, or of hurting yourself 419 74.2 108 19.1 38 6.7
Table shows unweighted frequencies and row percentages based on response to items from Wave 2 survey administration (April—May 2021) of the nationwide, longitudinal COVID Experiences Study (CovEx) of Adolescents 13–19 years of age administered using the National Opinion Research Center’s (NORC) at the University of Chicago AmeriSpeak® and AmeriSpeak Teen® panels
aPatient Health Questionnaire Adolescent (PHQ-A) responses at Wave 2 of survey administration were used to assess depressive symptomology measuring number and frequency of symptoms experienced in the past 14 days (response options: 0 days; 1 or 2 days; 3–6 days; 7–14 days), with each item response coded as 0 (O days), 1 (1 or 2 days; 3 to 6 days), or 2 (7 to 14 days)
Table 4 Zero-order correlations for study variables
1 2 3 4 5
1. ACEsa Wave 1 –
2. PRSIb Wave 1 0.37* –
3. PHQ-Ac Wave 2 0.37* 0.39* –
4. Sex -0.16* -0.11* -0.24* –
5. Race/ Ethnicity -0.04 -0.08 -0.05 -0.01 –
M 1.30 1.73 6.01 – –
SD 1.72 1.43 4.79 – –
Variables drawn from the nationwide, longitudinal COVID Experiences Study (CovEx) of Adolescents 13–19 years of age (at Wave 1, October—November 2020) using the National Opinion Research Center’s (NORC) at the University of Chicago AmeriSpeak® and AmeriSpeak Teen® panels. Table shows zero-order correlations with * indicating p < 0.001
aAdverse Childhood Experiences (ACEs) were based on eight Wave 1 survey items for which adolescent respondents identified whether they experienced any of the following at any point since they were born: (1) physical abuse; (2) emotional abuse; (3) sexual violence; (4) witnessing intimate partner violence; (5) parental divorce; (6) family member serving time in jail; (7) family member with a mental health condition; (8) family member with a substance use problem. Sum scores with a range of 0 to 8 were used to indicate ACEs exposure to date (Wave 1)
bPandemic-Related Stress Index (PRSI) includes seven items assessing stress exposure during the pandemic in the following areas: (1) family/parent job loss, (2) economic insecurity, (3) worsened family/household relationships, (4) lack of support from friends, (5) COVID-19 personal illness, (6) COVID-19 family member illness, and (7) missed health care when needed. Responses are dichotomized with a sum score calculated (range = 0 to 7). A higher sum score indicates accumulation of more pandemic-related stress experiences at Wave 1
cPatient Health Questionnaire Adolescent (PHQ-A) responses at Wave 2 of survey administration (April—May 2021) were used to assess depressive symptomology, measuring number and frequency of symptoms experienced in the past 14 days
Path Analysis
Overall, tests of the measurement model demonstrated a good fit to the data, χ2(5) = 6.62 p = 0.03, CFI = 0.96, RMSEA = 0.05 (90% CI = 0.01, 0.09). While the χ2 was statistically significant, research shows that the χ2 is highly sensitive to changes in sample size and tends to be statistically significant for models with larger sample sizes, or more than 300 cases. Also, the relatively high CFI (≥ 0.95) and low RMSEA (≤ 0.08) indicated acceptable model fit.
Figure 2 depicts the path analysis model with standardized estimates. ACEs were positively and significantly related to PRSI scores (b = 0.31, SE = 0.03, p < 0.001), meaning that a 1-standardized unit increase in ACEs was associated with a 0.31-standardized unit increase in PRSI scores. PRSI scores were positively and significantly related to subsequently reported depressive symptoms on the PHQ (b = 0.29, SE = 0.14, p < 0.001), meaning that a 1-standardized unit increase in PRSI scores was associated with a 0.29-standardized unit increase in PHQ scores at Wave 2. The direct association between ACEs and depressive symptoms on the PHQ remained statistically significant (b = 0.23, SE = 0.12, p < 0.001), even after accounting for the indirect effect of PRSI scores (b = 0.09, SE = 0.05, p < 0.001). Therefore, the total effect of ACEs on depressive symptoms was 0.32. The Pandemic-related stress, therefore, partially explained the relationship between ACEs and depressive symptoms.Fig. 2 Path analysis model illustrating relationships among Adverse Childhood Experiences (ACEs), Pandemic-Related Stress Index (PRSI) reported at Wave 1 (W1), and symptoms of depression (PHQ-A) at Wave 2 (W2) with Standardized Estimates. The path model describes the tested direct and indirect relationships and directionality of relationships among predictor variables and the outcome of interest with * indicating p < 0.01 and ** indicating p < 0.001. W1 ACEs reflects Adverse Childhood Experiences reported by adolescents at Wave 1. W1 PRSI reflects adolescent reported pandemic-related stress based on scores on the Pandemic-Related Stress Index and reported by adolescents at Wave 1. Wave 1 data were collected October—November 2020 and Wave 2 data were collected April—May 2021. Covariates include sex (i.e., sex assigned at birth) and race/ethnicity. Sex was modeled as a bivariate variable (female vs. male). Race/ethnicity was modeled twice: first as Black non-Hispanic vs. White non-Hispanic, second as White non-Hispanic vs. all Other races/ethnicities. As both models had similar nonsignificant results, only White non-Hispanic vs. all Other race/ethnicities results are reported in Fig. 2. Variables drawn from the nationwide, longitudinal COVID Experiences Study (CovEx) of Adolescents 13–19 years of age (at Wave 1, October—November 2020) using the National Opinion Research Center’s (NORC) at the University of Chicago AmeriSpeak® and AmeriSpeak Teen® panels
Regarding the covariates, sex assigned at birth was significantly associated with ACEs (b =—0.15, SE = 0.14, p < 0.001), PRSI scores (b =—0.10, SE = 0.11, p < 0.01), and PHQ scores (b =—0.23, SE = 0.39, p < 0.001). In other words, we found that adolescent females were more likely to report ACEs, pandemic-related stressors, and depressive symptoms, and that these sex differences contributed significantly to the model. Race/ethnicity was not significantly associated with any variables in the model.
Discussion
To our knowledge, this is the first study to examine associations between ACEs, pandemic-related stress exposures, and symptoms of depression among a nationwide cohort of adolescents ages 13 to 19. We also expand the literature to date in developing and applying a pandemic-related stress index (PRSI). The findings strongly support hypothesized causal relationships between ACEs, pandemic-related stress, and subsequent report of depressive symptoms. Path models revealed significant direct effects of pandemic-related stress and of ACEs reported at Wave 1 on depressive symptoms reported at Wave 2, suggesting the possibility of a causal association. ACEs also have a significant indirect effect on depressive symptoms via pandemic-related stress. In addition, we found that females reported higher rates of ACEs, pandemic-related stress, and depressive symptoms than males. Overall, the findings highlight a synergistic effect on depressive symptoms produced by pandemic-related stress and ACEs directly and indirectly.
Our findings align with a body of research showing associations between exposure to acute, episodic stress during public health emergencies and increased risk for children and adolescents to experience the symptoms of mental health conditions, including depression (Kronenberg et al., 2010; Masten & Osofsky, 2010; Osofsky et al., 2015; Rubens et al., 2018; Tang et al., 2014). When youth experience acute stress events (e.g., conflict, instability, illness) in developmentally relevant contexts (e.g., peer, family), depression can ensue via the main effect of stress or via various vulnerabilities interacting with the rise in stress through stress amplification processes (Furr et al., 2010; Masten, 2021; Masten & Narayan, 2012; Tang et al., 2014). Using path analysis, we identified a strong temporal relationship between pandemic-related stressors, including family/parent job loss, economic insecurity, worsened family/household relationships, lack of support from friends, personal or family COVID-19 illness, and absence of needed health care and depressive symptomology. This finding also supports current research pointing to the potential negative impact of pandemic-related stress on adolescent mental health (Hertz et al., 2021; Jones et al., 2022; Krause et al., 2022; Leeb et al., 2020) with disruptions in schooling and family situations precipitating rapid accumulation of stress events for many adolescents.
Our findings also demonstrate the mental health vulnerabilities of adolescent populations who have experienced ACEs; there was a direct association between the accumulation of ACEs and depressive symptoms. This finding aligns with previous literature suggesting that ACEs are associated with poor mental health across the lifespan (Merrick et al., 2019; Nurius et al., 2015). Moreover, results show a synergistic effect between ACEs and pandemic-related stress that may increase the risk for depressive symptoms among adolescents during the pandemic. This finding indicates longitudinal compounding risks due to pandemic-related stress for adolescents who have experienced ACEs. While the literature on ACEs, episodic stress, and depressive symptomology is limited, a pre-pandemic study of college students found not only that ACEs predicted worsening mental health over a semester, but also that stressors accrued during the semester mediated the relationship between ACEs and mental health and suicide-related outcomes (Karatekin, 2018; Osofsky et al., 2015; Tang et al., 2014).
In this study, female adolescents had higher reported ACEs, pandemic-related stress, and depressive symptoms, and these sex differences contributed significantly to the tested path model. Sex differences in adolescent depression have been identified previously with females having a higher incidence of major depressive disorder (MDD) and a more chronic course of depression than males (Avenevoli et al., 2015; Jones et al., 2016; Lewis et al., 2020). Likewise, there is evidence of sex differences in exposure to different types of ACEs with females reporting more complex and varied history of childhood adversities and a greater incident of sexual violence than males (Haahr-Pedersen et al., 2020). Our findings suggest the possibility that at least some effects on depressive symptoms may be attributable to sex differences; however, further research is needed to understand differential experiences of adversity and pandemic-related stress by sex as well as different symptomology reported by females and males in adolescence, especially following public health emergencies.
We did not find any racial/ethnic differences in the analysis, indicating that the observed associations between ACEs, pandemic-related stress, and depressive symptoms were similar across these subpopulations. This finding suggests that ACEs and pandemic-related stress may have a universal impact on depression symptomatology regardless of race and ethnicity. However, this does not preclude the possibility that individuals in different racial and ethnic groups may experience ACEs, pandemic-related stress, and depressive symptomatology differently, and that some groups may be at greater risk for these challenges because of the social and structural conditions in which people live, work, and play (Merrick et al., 2018; Ports et al., 2020; Vanderminden et al., 2019). Our relatively small sample size possibly prevented us from detecting differences across racial and ethnic minority subgroups. For the same reason, we could not incorporate social determinants of health such as experiences of racism and discrimination into this analysis. However, we recognize that the presence of ongoing adversities and stress for adolescents who have historically experienced (and may continue to experience) marginalization, stigma, and discrimination amidst the pandemic needs further investigation. Racial/ethnic minorities, LGBTQI + youth, American Indian/Alaska Native youth, and youth with disabilities often face a disproportionate burden of stress, have less access to healthcare, and experience environmental and attitudinal barriers to accessing supports, which can adversely affect mental health (Compton & Shim, 2015; Shim, 2020; Shim & Starks, 2021).
Limitations
The findings of the present study are not without limitations. First, ACE exposures could vary in intensity, frequency, duration, and developmental timing. Each ACE was also given equal weight in creating a summed score; while this is a standard approach, it is not without limitations (Holden et al., 2020; Ports et al., 2020). Second, we retrofitted PRSI items using existing survey items. Thus, items included in the PRSI might not be theoretically exhaustive. We were also limited to binary items and used a logistic PCA, an innovative but not yet fully developed methodology, to develop the index. Some items had suboptimal logistic PCA loadings (see Appendix for details) and were excluded during the dimension reduction process of the index development. As such, the current form of the PRSI will likely benefit from additional use and testing to better ascertain its applicability outside this study. Third, information biases such as social desirability, recall, and/or self-report biases might exist. For example, previous studies have identified gender differences in patterns of self-reporting on traits associated with internalizing disorders, including depression, which can lead to overestimation of sex differences (Lindsey et al., 2017; Navarro et al., 2020; Van Beek et al., 2012). Fourth, loss to follow-up between waves, survey skipping patterns, and item-level missingness leads to potential selection bias and low data power for including more covariates. However, the significant and theory-aligned relationships found between ACEs, pandemic stress, and depressive symptoms, are sufficiently robust to be interpreted for practical implications. Finally, due to the methodological approach, the data used in this study were unweighted. Although participants were sampled from a nationwide, probability-based panel, the sample was predominately white and heterosexual, findings may not be generalizable to the broader adolescent population.
Implications
Deleterious effects of pandemic stress on adolescents call for urgent action, particularly for adolescents with higher pandemic-related stress and the presence of ACEs. This need may also be particularly salient for females. One immediate need is to identify adolescents needing clinical treatment and ensure linkage to developmentally and culturally relevant services for depression and high stress. Clinical screening might occur during primary care wellness visits and check-ups, sports physicals, or other health care appointments, supporting the ability of clinicians to make timely referrals to cognitive-behavioral therapy (CBT), trauma-focused CBT, and interpersonal psychotherapy as needed (American Psychological Association, 2019; Kairys et al., 2020; Stanley et al., 2009).
However, mental and behavioral health services are not equitably distributed across demographic subpopulations and may not be available for those with disproportionate need (Hodgkinson et al., 2017; Kairys et al., 2020). A robust and comprehensive infrastructure across all youth-serving systems that incorporates developmental monitoring and appropriately used screening processes could facilitate more equitable and transparent identification of adolescents in need of services with the ultimate goal of the provision of needed services (Harris et al., 2020; Vaivada et al., 2022). Schools play a critical role in providing social support, universal mental health programming, early intervention services, and mental health care (Hoover & Bostic, 2021). Application of a comprehensive, multi-tiered system of supports that incorporates trauma-informed approaches; health education inclusive of social-emotional learning and mental health education; early intervention programming; and linkage to health services has shown promise as a framework for supporting the mental health of children and adolescents in school and in facilitating connection to needed supports (Herbers et al., 2021). However, providing schools with adequate resources to facilitate comprehensive mental health programming is imperative for initiatives to be effective (Cummings et al., 2022; U.S. Department of Education, 2021).
Foundationally, establishing safe and supportive environments in child-serving spaces may help assuage the negative impact of pandemic stress while also benefiting those who have experienced ACEs by establishing an environment for healthy recovery and development (Kataoka et al., 2018; Overstreet & Chafouleas, 2016). In particular, connectedness to family and school has been identified as an important buffer to stress, and school-based initiatives that promote connectedness and family engagement have shown promise for supporting and protecting adolescent mental health (Areba et al., 2021; Blackwell et al., 2022; Hertz et al., 2021; Steiner et al., 2019). School-based approaches to creating safe and supportive environments, fostering connectedness, and preventing and mitigating the harms of ACEs are available, as are trainings to help improve understanding of ACEs and ACEs prevention for others who work with youth; see Preventing ACEs (Centers for Disease Control and Prevention, 2019a, b; Filia et al., 2021). Likewise, community-based mentoring, bystander training, and community initiatives that promote prosocial relationships and reduce stigma around help-seeking for mental health challenges or substance use disorders are among the strategies that offer a venue for the community to be a source of connection and resilience for young people (Li et al., 2021; Mendelson & Tandon, 2016; Pfefferbaum et al., 2019).
Finally, ongoing surveillance of the impact of stress due to public health emergencies is critically important to understand both immediate and long-term effects and to elucidate factors related to emotional adjustments extending over time (Pfefferbaum et al., 2012). Grounded in frameworks for research on children’s reactions to public health emergencies, factoring in the role of family challenges, parental and peer relationships, and proximity of exposures, the development of the PRSI might serve as a foundation for on-going assessment of stressors experienced by adolescents amidst the COVID-19 pandemic and for future public health emergencies, with the goal of identifying needed services, supports, and interventions.
Conclusion
The current study is among the first to examine specific longitudinal pathways between pandemic stress, ACEs, and mental health among U.S. adolescents, using nationwide samples collected between 2020 and 2021. Overall, our findings highlight the utility of examining pandemic-related stress among adolescents to better understand the degree of its negative impact on mental health. This work lays a solid foundation for further research by revealing an important mechanism linking ACEs and pandemic stress to subsequent depression among adolescents, both directly and synergistically. Findings point to the critical importance of tailoring and scaling up primary, tertiary, and secondary prevention for reducing risks for mental disorder as well as treatment interventions for mental illness to accommodate new challenges brought on by the pandemic, which were compounded by existing adversities. Systems that work to prevent and mitigate the harms of ACEs and other forms of stress at the family, community, and societal level are needed to reduce the adolescent mental health crisis and build strong, healthy communities where youth and families can thrive.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 43 KB)
Author Contribution
As co-lead authors, Drs. Verlenden, Kaczkowski, and Li conceptualized and designed the study, drafted the initial manuscript, and reviewed and revised all subsequent versions of the manuscript. Drs. Kaczkowski and Li completed and validated all analyses. Drs. Anderson, Bacon, and Ms. Hertz reviewed and revised the initial manuscript, contributing essential content based on subject matter expertise. Dr. Dittus provided scientific guidance throughout the conceptualization, design and implementation of the study as well as reviewed and revised the manuscript. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.
Data Availability
Data are not currently publically available; however, data will become available by request on CDC's Division of Adolescent and School Health's website in the future. https://www.cdc.gov/healthyyouth/about/index.htm
Declarations
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.
Potential Conflicts of Interest
The authors have no conflicts of interest relevant to this article to disclose.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9747542 | NO-CC CODE | 2022-12-15 23:22:02 | no | J Child Adolesc Trauma. 2022 Dec 14;:1-15 | utf-8 | J Child Adolesc Trauma | 2,022 | 10.1007/s40653-022-00502-0 | oa_other |
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Int J Radiat Oncol Biol Phys
Int J Radiat Oncol Biol Phys
International Journal of Radiation Oncology, Biology, Physics
0360-3016
1879-355X
Elsevier Inc.
S0360-3016(22)03342-9
10.1016/j.ijrobp.2022.09.051
Meta-analysis of Low-Dose Irradiation for COVID-19
In Regard to Kolahdouzan et al.
Li Zheng MD, PhD
Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, China, Lanzhou Heavy Ion Hospital, Lanzhou, China
Hu Yue MSN
Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
Li Qiang PhD ⁎
Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, China, Lanzhou Heavy Ion Hospital, Lanzhou, China
⁎ Corresponding author: Qiang Li, PhD, 509 Nanchang Road, Lanzhou 730000, China. Telephone: +86-931-4969316; Fax: +86-931-8272100.
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Elsevier Inc.
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pmcTo the Editor:
With great enthusiasm, we read the article by Kolahdouzan et al1 recently published in the Red Journal. The authors performed a systematic review and meta-analysis to synthesize the evidence of low-dose whole lung irradiation for treatment of COVID-19 pneumonia. It is a significant breakthrough for this controversial subject,2 , 3 because meta-analysis is an effective method to resolve clinical disputes and reach a final conclusion. However, several issues should be noted as potential pitfalls leading to biases, which are opposed by the Cochrane collaboration.
First, this study searched only 2 databases: PubMed and Scopus. However, to minimize bias, the Cochrane Handbook for Systematic Reviews of Interventions suggested that comprehensive search sources should be used for study identification.4 Therefore, some other important databases should also be searched, such as the Cochrane Library, Web of Science, Embase, and the COVID-19 Open Research Dataset (CORD-19).
Second, both free-text and subject headings (eg, Medical Subject Headings (MeSH) and Emtree) should be used according to the Cochrane handbook.4 However, the subject search was not found in the authors’ search strategy as exhibited in the article or supplementary material.
Third, “unpublished studies” was listed as an excluded criterion by the authors in the study selection. However, it is important for minimizing bias to find out about unpublished studies and include their results in a systematic review when eligible and appropriate.4 , 5
Fourth, the authors synthesized the data from different types of study designs in their Figure 3 (meta-analysis of overall survival rate). To test the credibility of the results, a sensitivity analysis should be performed by removing the studies without a control group. Actually, the clinical and methodological heterogeneity could be resolved by appropriate subgroup analysis based on crucial factors such as the grade of COVID-19 severity, radiation regimens, and the type of study design (including random or not).
Fifth, the grading of recommendations assessment, development and evaluation tool should be used for all important outcomes in the meta-analysis, according to the recommendation of the Cochrane collaboration.4 , 6 However, there is no grading of recommendations assessment, development and evaluation analysis in the present article.
We believe that addressing these issues would be beneficial to further enhance the value of the study. Moreover, several eligible and crucial studies have been published7, 8, 9, 10 that were not analyzed in the article. Therefore, a timely, updated meta-analysis should be carried out to provide more determinate evidence for decision making and for ongoing clinical trials.
Disclosures: Zheng Li, Yue Hu, and Qiang Li developed the conception and design. All authors investigated, analyzed and synthesized the supporting data/references of the key viewpoints. All authors participated in discussion of the key viewpoints in order to form the ultimate consensus. Zheng Li and Yue Hu wrote the initial draft. Qiang Li revised the manuscript. All authors reviewed and approved the final manuscript.
Funding: This work was supported by the National Natural Science Foundation of China (Grant No. 11875299).
Zheng Li and Yue Hu contributed equally to this work.
==== Refs
References
1 Kolahdouzan K Chavoshi M Bayani R Darzikolaee NM. Low-dose whole lung irradiation for treatment of COVID-19 pneumonia: A systematic review and meta-analysis Int J Radiat Oncol Biol Phys 113 2022 946 959 35537577
2 Salomaa S Bouffler SD Atkinson MJ Cardis E Hamada N. Is there any supportive evidence for low dose radiotherapy for COVID-19 pneumonia? Int J Radiat Biol 96 2020 1228 1235 32579043
3 Tharmalingam H Díez P Tsang Y Hawksley A Conibear J Thiruthaneeswaran N. Personal view: Low-dose lung radiotherapy for COVID-19 pneumonia—The atypical science and the unknown collateral consequence Clin Oncol (R Coll Radiol) 32 2020 497 500 32536559
4 Higgins JPT Thomas J Chandler J Cochrane Handbook for Systematic Reviews of Interventions 2022 Cochrane Version 6.3. Updated February 2022. Available at: www.training.cochrane.org/handbook Accessed August 2, 2022
5 Guyatt GH Oxman AD Montori V GRADE guidelines: 5. Rating the quality of evidence—publication bias J Clin Epidemiol 64 2011 1277 1282 21802904
6 Guyatt GH Oxman AD Vist GE GRADE: An emerging consensus on rating quality of evidence and strength of recommendations BMJ 336 2008 924 926 18436948
7 Saleh M Sharma K Shah J A pilot phase Ib/II study of whole-lung low dose radiation therapy (LDRT) for the treatment of severe COVID-19 pneumonia: First experience from Africa PLoS One 17 2022 e0270594
8 Sanmamed N Alcantara P Gómez S Low-dose radiation therapy in the management of COVID-19 pneumonia (LOWRAD-Cov19): Final results of a prospective phase I-II trial Radiother Oncol 171 2022 25 29 35367528
9 Singh P Mandal A Singh D Interim analysis of impact of adding low dose pulmonary radiotherapy to moderate COVID-19 pneumonia patients: IMpaCt-RT study Front Oncol 12 2022 822902
10 Magrini SM Tomasini D Focà E Low-dose lung radiotherapy for COVID-19-related pneumonia: Preliminary results of the Italian mono-institutional COLOR-19 trial In Vivo 36 2022 1959 1965 35738608
| 0 | PMC9747668 | NO-CC CODE | 2022-12-15 23:23:25 | no | Int J Radiat Oncol Biol Phys. 2023 Jan 1; 115(1):251-252 | utf-8 | Int J Radiat Oncol Biol Phys | 2,022 | 10.1016/j.ijrobp.2022.09.051 | oa_other |
==== Front
Int J Radiat Oncol Biol Phys
Int J Radiat Oncol Biol Phys
International Journal of Radiation Oncology, Biology, Physics
0360-3016
1879-355X
Elsevier Inc.
S0360-3016(22)03343-0
10.1016/j.ijrobp.2022.09.053
Comments
In Reply to Li et al.
Darzikolaee Nima Mousavi MD
Department of Radiation Oncology, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
Radiation Oncology Research Center, Cancer Research Institute, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
Bayani Reyhaneh MD
Radiation Oncology Research Center, Cancer Research Institute, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
Radiation Oncology Research Center, Cancer Research Institute, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
Chavoshi Mohammadreza MD
Department of Radiology, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
Kolahdouzan Kasra MD
Department of Radiation Oncology, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
Radiation Oncology Research Center, Cancer Research Institute, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
14 12 2022
1 1 2023
14 12 2022
115 1 252253
© 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.
==== Body
pmcWe thank Li et al for their comments1 on our article “Low-Dose Whole Lung Irradiation for Treatment of COVID-19 Pneumonia: A Systematic Review and Meta-Analysis.”2 The authors note important issues that we will respond to in this letter.
First, as we mentioned in the article, our search included studies that were published before February 2022; the studies noted by the authors as not having been included in our systematic review all were published after this time point. Also, the final results of the LOWRAD-Cov19 trial3 were detected during the peer review process of our manuscript and were subsequently included in the final publication.
Second, regarding the search strategy of our study, we chose the 2 most robust databases (PubMed and Scopus), and there have been no missing articles associated with COVID-19 whole lung irradiation (WLI) published until our last search date. Moreover, both MeSH and free-text terms were used for our search.
Third, all ongoing trials on the subject that were registered at clinicaltrials.gov were presented as a supplementary table. We are also very eager to find out the results of these trials so that an updated meta-analysis might bring more light to the matter after the publication of these studies.
Fourth, performing a sensitivity analysis for the overall survival rate outcome would have been futile, because it is not a comparative outcome and merely reports the rate of surviving patients who received WLI.
Fifth, considering the risk of bias, imprecision, inconsistency, indirectness, and publication bias as per grading of recommendations, assessment, development and evaluations certainty assessment requirements,4 the upcoming results of the ongoing trials are likely to affect the confidence in the estimates of effect for the outcomes reported in our meta-analysis, and therefore, the quality of evidence might not be higher than moderate.5 We clearly stated these factors within the article.
Finally, we should once again emphasize that our meta-analysis did not demonstrate a significant benefit of WLI for COVID-19 patients with moderate to severe pneumonia, and therefore, it does not support evidence for routine implementation of WLI in this population. Similar to Li et al, we believe that an updated meta-analysis after the publication of the major trials in this regard might provide new information, although it is very unlikely to change the current COVID-19 management strategies with the major vaccination programs and novel therapeutics available.
Disclosures: none.
==== Refs
References
1 Li Z Hu Y Li Q In regard to Koulahdouzan et al Int J Radiat Oncol Biol Phys 115 2023 251 252
2 Kolahdouzan K Chavoshi M Bayani R Darzikolaee NM. Low-dose whole lung irradiation for treatment of COVID-19 pneumonia: A systematic review and meta-analysis Int J Radiat Oncol Biol Phys 113 2022 946 959 35537577
3 Sanmamed N Alcantara P Gómez S Low-dose radiation therapy in the management of COVID-19 pneumonia (LOWRAD-Cov19): Final results of a prospective phase I-II trial Radiother Oncol 171 2022 25 29 35367528
4 Higgins JPT Thomas J Chandler J Cochrane Handbook for Systematic Reviews of Interventions 2022 Cochrane Chichester (UK) Version 6.3. Available at: http://www.training.cochrane.org/handbook Accessed August 22, 2022
5 Guyatt GH Oxman AD Vist GE GRADE: An emerging consensus on rating quality of evidence and strength of recommendations BMJ 336 2008 924 926 18436948
| 0 | PMC9747670 | NO-CC CODE | 2022-12-15 23:23:25 | no | Int J Radiat Oncol Biol Phys. 2023 Jan 1; 115(1):252-253 | utf-8 | Int J Radiat Oncol Biol Phys | 2,022 | 10.1016/j.ijrobp.2022.09.053 | oa_other |
==== Front
Journal of Building Engineering
2352-7102
2352-7102
The Authors. Published by Elsevier Ltd.
S2352-7102(22)01655-2
10.1016/j.jobe.2022.105649
105649
Article
Natural ventilation as a healthy habit during the first wave of the COVID-19 pandemic: An analysis of the frequency of window opening in Spanish homes
Navas-Martín Miguel Ángel a
Cuerdo-Vilches Teresa b∗
a Escuela Nacional de Sanidad (ENS), Instituto de Salud Carlos III (ISCIII), Spain
b Instituto de ciencias de la construcción Eduardo Torroja (IETcc), Consejo Superior de Investigaciones Científicas (CSIC), Spain
∗ Corresponding author. Instituto de ciencias de la construcción Eduardo Torroja (IETcc), CSIC, C/ Serrano Galvache 4, 28033, Madrid, Spain.
14 12 2022
14 12 2022
10564911 8 2022
18 10 2022
28 11 2022
© 2022 The Authors. Published by Elsevier Ltd.
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.
Since SARS-CoV-2 spread worldwide in early 2020, many countries established lockdowns for protection. With a main transmission by aerosols, ventilation was promoted. This article analyses natural ventilation of Spanish housing during the spring 2020. An online questionnaire was launched, obtaining for this study 1502 responses. The comparative window opening before and during confinement and households, dwellings and home activity variables, were analysed. The binary logistic regression model before pandemic, indicated that ventilating properly related to: a worse perceived IAQ (OR = 1.56); thermal adaptation measures, especially those that prefer to open/close windows (OR = 1.45); not having heating system (OR = 1.15); and using power to heat water (OR = 1.60). For the confinement period, the model highlighted: being an employee (OR = 1.88); using heavy clothing in the home (OR = 2.36); and again, open/close windows for adaptation (OR = 2.24). According to specific tasks in quarantine, frequent ventilation was boosted by: an increasing use of oven (OR = 14.81); and alteration of work-habits (OR = 2.70), sport-habits (OR = 1.79), and outdoor-activities (OR = 1.60). Thus, an adequate natural ventilation pattern during the quarantine linked to low environmental comfort in general, by virtue of indoor air quality. This is corroborated by less acoustic-thermal insulation, worse indicators of heating use, and the adaptive response to opening/closing windows when external temperature changed.
Keywords
Housing
Confinement
Quarantine
Habit
Health risk
Survey
Indoor air quality
IAQ
IEQ
Indoor environmental quality
==== Body
pmc1 Introduction
On March 11, 2019, the World Health Organization communicated the situation of pandemic due to the increase in the number of cases of COVID-19 [1]. With the WHO declaration of health emergency caused by a new coronavirus, most countries carried out mobility restrictions [2]. Spain was one of the most affected countries in Europe by SARS-CoV-2 [3]. On March 14, the Spanish Government declared a State of Alarm with a series of measures to protect the health and safety of citizens [4].
Among the main non-pharmacological measures that many countries opted for, physical distancing, isolation and quarantine highlighted. Quarantine was in some countries mandatory or at least suggested as voluntary [5]. In Spain, a strict confinement was chosen, coinciding with the first wave of the pandemic. The Spaniards had to adapt to the new circumstances of confinement, altering their routines, time allocation and habits in their homes [6].
Until an epidemic occurs, little information is available, and therefore it is necessary to adopt measures to improve diagnostic methods, improve treatment efficiency, analyse transmission patterns and define quarantine and isolation and any other social protective strategies, mainly for infected patients [7].
One of the controversies that originated between the WHO and the scientific community was the lack of consensus and approval about the routes of contagion by air [8]. In April 2021, through a guide of recommendations, the WHO recommended the ventilation control in buildings to improve indoor air quality and avoid the risk of contagion by COVID-19 [9].
In Spain, the Ministry of Health recommended during the first wave: physical distancing; avoiding hand contact with eyes, nose and mouth; hand washing; use of disposable handkerchiefs; and coughing or sneezing over the cubital fossa [10]. During the third wave, the 6 M information campaign included more ventilation among the recommendations, promoting outdoor activities and window opening [11].
Natural ventilation of interior spaces is the most primitive and widespread way of eliminating all kinds of indoor pathogens of any nature, in these environments. With the introduction of outside air, that contained in the closed space is renewed, boosting the old one outdoors [12].
Depending on how the air indoors is replaced by new one, ventilation can be defined as natural (directly by opening holes to the outside, and by simple or combined action of temperature or pressure changes between outside and inside), mechanical (using inlet and/or outlet fans, which carry the air through ducts, previously passing through filters and other elements for its adaptation), or hybrid, as a mixture of the two previous ones, depending on the indoor and outdoor environmental conditions. The last two are controlled ventilation systems, and are usually integrated into the Heating, Ventilating and Air Conditioned (HVAC) system for non-residential buildings.
In Spain, the Technical Building Code (CTE) includes the basic aspects of ventilation, in its Basic Document HS3 [13]. It is mandatory to achieve air quality inside domestic spaces; not only in living spaces, but also in waste warehouses, storage rooms, garages, and parking lots. Also, the Regulation of Thermal Installations of Buildings (RITE) establishes these characteristics for non-residential buildings [14]. This current regulation had a more effective development in 2006, when indoor air quality began to be taken into account. Previously, regulations were not so demanding, and certainly not in homes. The revolution in terms of this aspect of habitability, the IAQ, was not until the current regulations. In it, hybrid and mechanical ventilation systems for homes were also detailed. These new requirements avoided delegating ventilation exclusively to the occupants of the spaces, but in these ventilation systems. However, Spanish homes were built almost entirely before this regulation saw the light, and therefore, they lack these systems [15].
Therefore, in almost the total of the Spanish cases, to achieve ventilation inside, it is necessary to rely on the user's criteria. Thus, the air quality depends on the frequency with which windows are opened/closed, the time that they are kept open, the intensity of use inside, the gap dimensions, and the volume of indoor environment, for instance.
During the pandemic evolution, different international organizations began to establish recommendations to ensure adequate ventilation. This preventive measure against COVID-19 was spread not only for residential buildings, but focusing on natural ventilation for domestic environments [16]. The existence of poorly-ventilated residential spaces not only affected virus transmission among cohabitants. Also, contagions crossed the spatial barriers of the home, due to air drafts between dwellings and even buildings. It produced the so-called super-contagious events, especially virulent in more densely populated cities, with compact building typologies [17].
Housing and its importance and impact on the occupants’ health are widely documented [[18], [19], [20]]. Even so, some studies carried out during the COVID-19 pandemic, delved into the importance of the habitability aspects of the home during this period. They deepened specifically during the quarantine in social distancing, and in physical health, including mental [21]. Many of them were based on reviews of existing literature to highlight the importance of indoor environmental quality. In particular, the air quality in these environments stood out [22], both for the well-being of cohabitants, and to demonstrate a lower transmission of COVID-19 in the home.
However, few studies have been able to establish in situ measurements in dwellings during this period, due to circumstances of social isolation. Although the interest and relevance of these studies should not be denied, others were able to reach the population through online questionnaires.
Among the few COVID-19 studies that addressed housing characteristics, some highlighted the concern of cohabitants and ventilation throughout the pandemic. According to a study in China, at the beginning of the outbreak, 92.4% of the sampling opened windows to ventilate more frequently than usual [23]. In another study in England, during late 2020, 58.5% of respondents opened windows frequently/very frequently in the previous 7 days [24]. At the beginning of 2021, in a multi-country study of people teleworking from home, 86.2% of respondents from UK and 94.3% from Italy declared to have opened windows to ventilate [25].
This study is the only one at the national level (and of the few internationally developed) that tried to respond to the general behaviour of the Spanish population in confinement, specifically approaching its relationship with domestic spaces and their environmental characteristics. The research questions for this analysis were established in two stages: 1) what were the sociodemographic households’ characteristics, and the dwelling features, from adequately ventilated homes (in terms of frequency of window opening) before the pandemic, and 2) what aspects influenced, and/or what circumstances led those who ventilated poorly before the pandemic, to improve the frequency of opening windows during the confinement, that is, to change this habit, to reach an adequately ventilation.
2 Materials and methods
To carry out this work, a non-probabilistic cross-sectional study was carried out in households during the first wave of the pandemic in Spain. Specifically, the data collection took place between April 30 and June 22, 2020, which also coincided with the State of Alarm period decreed by the Government of Spain, in which the population was confined to their homes.
2.1 Data collection
For data collection, the SurveyMonkey® online platform was used, through a questionnaire with 58 questions grouped into 18 blocks, about participants, characteristics of their home and habits of use of domestic space.
The selection of participants was carried out through an intentional non-probabilistic sampling. Through various means of dissemination, such as the institutional website, email, social networks and the media, a call was made for their participation. Likewise, for dissemination by email, a list of contacts was created using the web scraping technique, which made it possible to obtain contacts from neighbourhood associations, neighbourhood networks and city councils throughout the national territory. Also, participants were asked to share the link with other people for further dissemination.
The only inclusion criterion was that the participants were of legal age and that the survey would be completed by a single member of the household. To do this, informed consent was provided in the questionnaire, in addition to providing information on the scope of the study.
The study was approved by the Ethics Committee from the Spanish National Research Council (CSIC, in Spanish) with favourable report number 057/2020. This organization also funded the project.
2.2 Study design
A descriptive study is presented, determining the number of responses specially for the dependent variables, such as ventilation frequencies before and during quarantine. As a cross-sectional study, the responses for “before” and “during pandemic” periods were based on the same sampling, and facilitated through the same online questionnaire. Statistical analysis included bivariate crosses to establish significant explanatory relationships around the ventilation habits prior to the COVID-19 pandemic, as well as positive habit-changes, produced during the confinement of the first wave of coronavirus. Likewise, in order to test the multivariate explanatory relationships, three binary logistic regression models were carried out whose dependent variables. They were, respectively: first, adequate ventilation before pandemic; and second and third (based on usual poor ventilation), the event of improving ventilation to adequate, during confinement. The second analysis related general explanatory variables, and the third is specific on lockdown-relative activities and habits. The dependent variables were established as dichotomous dummy ones. To carry out the statistical analysis, the program SPSS in its version 28 was used. The general structure of the study design is graphically described in Fig. 1 .Fig. 1 Graphical description of the study design, covering a comparative natural ventilation analysis through window opening in two periods. The analysis included the relationships drawn with continuous lines, since the discontinuous ones did not seem relevant for a causal analysis, except for the mere sampling description in percentages.
Fig. 1
Fig. 1 shows the ventilation habits before pandemic, and the proportion of participant homes that maintained, worsened or improved these habits. Continuous stripes in arrows show the relations analysed in this manuscript, whilst discontinuous ones were not, given the poor contribution to the general analysis (by a negligible contribution).
2.3 Selected variables
To determine this analysis on ventilation as a habit, the question on the frequency of opening/closing windows was taken as the dependent variable, compared between “before” and “during” (in reference to confinement). The possible original answers were distributed on a Likert-type scale with five categories: from “continually closed”, “sometimes a week”, “once a day”, “several times a day”, and “continually open”. These original categories and their relative responses were regrouped so that there remained only two: the first three were grouped as “poor ventilation”, and the last two, as “adequate ventilation”.
The selected independent or explanatory variables, a total of twenty-eight, extracted from the 58 questions of the questionnaire, were grouped into six groups or fields to which they refer. These are listed in Table 1 .Table 1 Selection of independent variables for the analysis on compared residential natural ventilation frequency (before/during quarantine).
Table 1Topics or fields Variables
Participant's and household's characteristics Age, Gender, completed level of studies, current job situation, number of cohabitants, living with minors, living with elders (+65)
Home features Housing type, tenure regime, useable floor area, own external space, dwelling orientation, perceived indoor air quality, perceived lighting quality, perceived noise insulation
Thermal comfort perception and habits related to use of energy at home Habitual clothing in the home, thermal sensation indoors (comfort), thermal preference indoors, thermal adaptation measures, type of heating system, energy source of domestic hot water, Comparative use of household appliances and devices
Teleworking and spaces intended for this activity (only for “during confinement") Type of teleworking space, qualities of the teleworking space perceived as adequate
Other activities during lockdown (only for “during lockdown”) Alteration of habits at home
Desire for home improvement (only for “during confinement”) Desire to improve aspects of the home; desire for changes in housing (grouping of aspects); Satisfaction with the home (in essential aspects, or those related to design and construction).
First, a selection of participants' and households’ characteristics was made, such as age, gender, level of studies, job situation, cohabitants, and if minors or elders were present at home.
Second, the main home features were asked, as: housing type, tenure regime, useable floor area, availability, of own external space, dwelling orientation, perceived indoor air quality, perceived lighting quality, and perceived noise insulation.
Third, questions about thermal sensation and preferences, thermal adaptation and adaptation, were included, as well as questions about the compared energy expenditure (before and during pandemic) through housing thermal facilities, appliances and devices.
Fourth, only for the case of “during confinement”, variables related to habit changes, such as “clothing change” (specially before/after going outside), “eat”, “sleep”, “do some physical activity”, “leisure”, “domestic chores”, “care of someone else”, etc., and also for teleworking, were asked for.
Finally, variables related to the desire of housing improvement, were added, after the reflection of being confined, and the permanent exposition to the indoor environment, also specifically for the “during confinement” period.
2.4 Data treatment and analysis
Due to the methodology followed by this study (based on the online data collection of the initial questionnaire), and its own length (with 58 questions), the questions were mostly developed with qualitative or categorical answers, to avoid abandonment of the questionnaire by the participants due to tiredness or boredom.
Depending on the nature of the answers, they were structured in Likert-type scales, number scales, or simply in alternative answers. Those related to the alteration of habits, perceived adequacy of teleworking spaces, or in general, satisfaction with housing, allowed multiple responses, so their treatment was either by category (as an independent variable), or by regrouping the responses for later analysis (as in the case of satisfaction with the home, or the desire to improve it).
The categories are exposed in each table, according to the respective analysis. For multivariate analysis, the categories of some independent variables had to be regrouped, in order to facilitate the statistical relations among them and the dependent one, applying for each case, homogeneity criteria.
3 Results
For this study, 1502 valid responses were obtained, regarding the frequency of natural ventilation by opening windows in the home, both on a regular basis (before confinement and during it).
Once the dependent variables for ventilation frequency before and during the pandemic were prepared, the frequency distributions were observed to get a first idea of how households behaved, in terms of opening and closing windows, to facilitate natural ventilation. Fig. 1 above, exposed the relative proportions (percentages) of home ventilation, before and during pandemic. The proportions of properly ventilated housing almost did not change in the two periods, so it seemed more interesting to reflect in this study the poor-ventilated homes, and how they changed or maintained their habits, and possible reasons based in the different sociodemographic and dwelling features for “before pandemic” period (Table 2 ) and “during pandemic” (Table 3 ), when confinement-related activity changes also happened (Table 4 ).Table 2 Bivariate significant relations among independent variables and natural-ventilation frequency before COVID-19 pandemic.
Table 2Variable Ventilation frequency before COVID-19 pandemic
Total Poor ventilation N (%row) Adequate ventilation N (%row) p*
General 1502 836 (55.7) 666 (44.3)
Participant's and household's characteristics
Current job situation
Enterpreneur/self-employed 231 (20.6) 120 (51.9) 111 (48.1) 0.029
Employee 893 (79.4) 535 (59.9) 358 (40.1)
Living with elders (65+) 0.028
No 1276 (85.4) 725 (56.8) 551 (43.2)
Yes 219 (14.6) 107 (48.9) 112 (51.1)
Living with minors 0.019
No 957 (64.0) 511 (53.4) 446 (46.6)
Yes 538 (36.0) 321 (59.7) 217 (40.3)
Living with minors (6–11 years old) 0.006
No 1265 (84.6) 685 (54.2) 580 (45.8)
Yes 230 (15.4) 147 (63.9) 83 (36.1)
Home features
Dwelling type 0.031
Flat 1095 (73.3) 627 (57.3) 468 (42.7)
House 398 (26.7) 203 (51.0) 195 (49.0)
Own external space 0.019
No 462 (30.8) 278 (60.2) 184 (39.8)
Yes 1040 (69.2) 558 (53.7) 482 (46.3)
Orientation: West 0.006
No 1204 (80.2) 649 (53.9) 555 (46.1)
Yes 298 (19.8) 187 (62.8) 111 (37.2)
Perceived Indoor Air Quality (IAQ) 0.000
Very bad/bad/regular 198 (13.3) 106 (53.5) 92 (46.5)
Good 733 (49.3) 448 (61.1) 285 (38.9)
Very good 556 (37.4) 276 (49.6) 280 (50.4)
Perceived lighting quality 0.000
No/little adequate 94 (6.3) 51 (54.3) 43 (45.7)
Adequate 506 (33.8) (61.1) 285 (38.9)
Very adequate 544 (36.4) 276 (49.6) 280 (50.4)
Totally adequate 352 (23.5) 164 (46.6) 188 (53.4)
Thermal comfort perception and habits related to use of energy at home
Habitual clothing in the home 0.012
Light 393 (26.5) 206 (52.4) 187 (47.6)
Normal 900 (60.7) 499 (55.4) 401 (44.6)
Heavy 190 (12.8) 124 (65.3) 66 (34.7)
Thermal preferences indoors 0.000
Heater 294 (19.9) 175 (59.7) 118 (40.3)
No change 958 (65.0) 549 (53.7) 409 (42.7)
Cooler 222 (15.1) 106 (47.7) 116 (52.3)
Thermal adaptation measures 0.000
Cloths change 866 (59.0) 506 (58.4) 360 (41.6)
Open/Close windows 425 (28.9) 195 (45.9) 230 (54.1)
Turn on/off heating system 178 (12.1) 119 (66.9) 59 (33.1)
Heating System 0.000
None 168 (11.2) 38 (22.6) 130 (77.4)
Individual (by room/dwelling) 1091 (72.6) 643 (58.9) 448 (41.1)
Collective (by building, district, etc) 243 (12.1) 155 (63.8) 88 (36.2)
Energy source of Domestic Hot Water 0.000
Natural gas 842 (66.6) 522 (62.0) 320 (38.0)
Power 310 (24.5) 138 (44.5) 172 (55.5)
Gasoil 112 (8.9) 66 (58.9) 46 (41.1)
*p value for the chi-square test of the relations of among household's characteristics and home features with the window opening before COVID-19 pandemic. A p < 0.05 implies a significant relationship. Bolds indicate the direction of the significant relation.
Table 3 Bivariate significant relations ventilation frequency during COVID-19 pandemic (after a usual poor ventilation), and general independent variables.
Table 3Variable Homes with poor ventilation before COVID-19 pandemic, having during it …
Total … poor ventilation N (%row) … adequate ventilation N (%row) p*
General 827 335 (40.5) 492 (59.5)
Participant's and household's characteristics
Current job situation <0.001
Enterpreneur/self-employed 118 (18.2) 62 (52.5) 56 (47.5)
Employee 530 (81.8) 190 (35.8) 340 (64.2)
Living with elders (65+) 0.011
No 118 (18.2) 279 (38.8) 440 (61.2)
Yes 530 (81.8) 54 (51.9) 50 (48.1)
Home features
Dwelling type <0.001
Flat 623 (75.8) 231 (37.1) 392 (62.9)
House 199 (24.2) 101 (50.8) 98 (49.2)
Own external space 0.026
No 276 (33.4) 97 (35.1) 179 (64.9)
Yes 551 (66.6) 238 (43.2) 313 (56.8)
Orientation: West 0.013
No 640 (77.4) 274 (42.8) 366 (57.2)
Yes 187 (22.6) 61 (32.6) 126 (67.4)
Thermal comfort perception and habits related to use of energy at home
Habitual clothing in the home 0.018
Light 204 (24.9) 78 (38.2) 126 (61.8)
Normal 494 (60.2) 217 (43.9) 277 (56.1)
Heavy 122 (14.9) 37 (30.3) 85 (69.7)
Thermal preferences indoors 0.018
Heater 174 (21.2) 72 (41.4) 102 (58.6)
No change 542 (66.0) 230 (42.4) 312 (57.6)
Cooler 105 (12.8) 31 (29.5) 74 (70.5)
Thermal adaptation measures <0.001
Cloths change 501 (61.7) 210 (41.9) 291 (58.1)
Open/Close windows 194 (23.9) 57 (29.4) 137 (70.6)
Turn on/off heat system 117 (14.4) 61 (52.1) 56 (47.9)
Use frequency of Heating system in confinement <0.001
Never/barely 225 (28.8) 69 (30.7) 156 (69.3)
Only if necessary 389 (49.8) 177 (45.5) 212 (54.5)
Frequently/continuously 167 (21.4) 74 (44.3) 93 (55.7)
*p value for the chi-square test of the relations of among households' characteristics and home features, with the window opening during pandemic after a poor ventilation on the basis. A p < 0.05 implies a significant relationship. Bolds indicate the direction of the significant relation.
Table 4 Bivariate significant relations among ventilation frequency during pandemic (after a usual poor ventilation) and independent variables (activity, habits, comfort and environmental quality).
Table 4Variable Homes with poor ventilation before COVID-19 pandemic, having during it …
Total … poor ventilation N (%row) … adequate ventilation N (%row) p*
General 827 335 (40.5) 492 (59.5)
Teleworking and spaces intended for this activity
Type of teleworking space 0.004
Itinerant or occasional shared space 400 (65.0) 133 (33.3) 267 (66.8)
Previous shared or exclusive space 215 (35.0) 97 (45.1) 118 (54.9)
Adequate room size 0.009
No 382 (46.2) 173 (45.3) 209 (54.7)
Yes 445 (53.8) 162 (36.4) 283 (63.6)
Adequate surface finishing 0.014
No 504 (60.9) 221 (43.8) 283 (56.2)
Yes 323 (39.1) 114 (35.3) 209 (64.7)
Other activities during confinement
Compared use of stoves <0.001
Less use than usual 5 (0.6) 2 (40.0) 3 (60.0)
Same us as usual 296 (35.8) 150 (50.7) 146 (49.3)
More use than usual 525 (63.6) 182 (34.7) 343 (65.3)
Compared use of oven <0.001
Less use than usual 17 (2.1) 11 (64.7) 6 (35.3)
Same use as usual 286 (35.4) 146 (51.0) 140 (49.0)
More use than usual 504 (62.5) 169 (33.5) 335 (66.5)
Compared use of kitchen robot <0.001
Less use than usual 31 (5.7) 15 (48.4) 16 (51.6)
Same use as usual 298 (54.7) 145 (48.7) 153 (51.3)
More use than usual 216 (39.6) 70 (32.4) 146 (67.6)
Alteration of habits at home
Work No 172 (20.8) 83 (48.3) 89 (51.7) 0.020
Yes 655 (79.2) 252 (38.5) 403 (61.5)
Cleaning No 409 (49.5) 188 (46.0) 221 (54.0) 0.002
Yes 418 (50.5) 147 (35.2) 271 (64.8)
Domestic chores No 385 (46.6) 178 (46.2) 207 (53.8) 0.002
Yes 442 (53.4) 157 (35.5) 285 (64.5)
Clothing change No 453 (54.8) 204 (45.0) 249 (55.0) 0.004
Yes 374 (45.2) 131 (35.0) 243 (65.0)
Sports No 310 (37.5) 149 (48.1) 161 (51.9) <0.001
Yes 517 (62.5) 186 (36.0) 331 (64.0)
Enjoy the external space 0.013
No 534 (64.6) 233 (43.6) 301 (56.4)
Yes 293 (35.4) 102 (34.8) 191 (65.2)
Desire for home improvement
Desire for insulation improvement 0.016
No 472 (57.1) 208 (44.1) 264 (55.9)
Yes 355 (42.9) 127 (35.8) 228 (64.2)
Changes in housing (5+) 0.003
No 126 (15.2) 66 (52.4) 60 (47.6)
Yes 701 (84.8) 269 (38.4) 432 (61.6)
Home satisfaction (essential features) <0.001
No 705 (85.2) 268 (38.0) 437 (62.0)
Yes 122 (14.8) 67 (54.9) 55 (45.1)
*p value for the chi-square test of the relations of among activities, habits and environmental parameters with the window opening during pandemic after a poor ventilation on the basis. A p < 0.05 implies a significant relationship. Bolds indicate the direction of the significant relation.
Before pandemic, 55.7% of sampling ventilated poorly, and 44.3% did it properly. From those how ventilated adequately before, just 2.3% worsened this habit. But, from usual poor-ventilated homes, un 59.5% improved their habit during confinement, but the remaining 40.5% kept their bad ventilation patterns.
After observing the compared dependent variables, a decision on the bivariate analysis and the way to compare the ventilation behaviours (before and during lockdown) was made. The reason was to show, as far as possible, the most relevant behaviour changes between those two stages, and give some explanations on the potential causes that could origin them. Finally, two models were exposed, one for each stage, based on significant bivariate relations between independent variables, and dependent ones (ventilation frequency before and during lockdown), to explore in a deeper way and contrast those relations, by the respective multivariate logistic regressions.
3.1 Descriptive analysis: ventilation frequency before/during pandemic
In the questionnaire offered to the participating households, the compared frequency of opening windows before and during confinement, showed a disparate behaviour. As can be seen in Fig. 1, the households that responded to “before pandemic” (n = 1502), showed a deficient ventilation frequency in 55.7% of the cases (n = 836), while 44.3% ventilated properly (n = 666). However, when resorting to the answers obtained about the period in confinement (“during”), the households modified their behaviour in a significant percentage. Indeed, 23.7% declared poor ventilation, whilst homes practising it properly increased to 76.3%.
To analyse in more detail the dynamic and changing behaviour of the homes, a further approximation was made. Observing what percentages changed their behaviour (positive or negative), and what proportion did not change their natural ventilation habits. In this sense, among those who habitually ventilated well (n = 666), only 2.3% ventilated worse during quarantine, while 97.7% maintained their habits. However, the greatest change occurred in those homes that habitually ventilated badly. Of them, 59.5% changed their ventilation habits towards an adequate frequency, while 40.5% maintained their poor habit.
Observing these answers, it seemed interesting to delve into what aspects led homes to ventilate well on a regular basis, and, among those who habitually ventilated poorly. In other words, what led them to change their habits towards healthier natural ventilation frequencies, and more auspicious, opening windows.
3.2 Bivariate relations with the ventilation frequency before pandemic
The results obtained for the contingency tables or bivariate crosses using the dependent variable “ventilation frequency before COVID-19 pandemic” are presented below. The results that expressed significant relationships with the explanatory and independent variables are presented in Table 2.
Chi-square tests are implemented to find significant relations between each of the independent variables and the dependent one. P-value<0.05 implies significant relation.
As shown in Table 2, the usual natural ventilation frequency variable (before the pandemic) was significantly related to multiple independent variables. In the first place, with respect to the characteristics of the participants and households, the variables that showed a significant relationship were the current work situation, as well as certain configurations of the household, such as the presence of people over 65, and the coexistence of minors, and within them, minors between 6 and 11 years. The current employment situation was significantly related. The worst ventilators were those with paid employment (59.9% vs. 40.1%). The self-employed/businessmen, were who ventilated more frequently on a regular basis.
Regarding the configuration of the home, living with older people was related to adequate ventilation (51.1% vs 48.9%), while minors were related to poor ventilation (59.9% vs 40.3%). This same relationship also occurred specifically for the age group of minors between 6 and 11 years of age (63.9% vs. 36.1%).
On the characteristics of the home, significant relationships were obtained between the usual frequency of ventilation before the pandemic and the type of home, the existence of its own outdoor space, orientation to the west, and the perceived indoor air and lighting qualities. Regarding the detailed relationships, an adequate frequency of ventilation on a regular basis was related to single-family homes (49.0% vs 51.0), with having their own outdoor spaces (46.3% vs 53.7%), with not having a west orientation in the home (62.8% vs 37.2%), and with polarized perceptions of indoor air quality lighting, being either poor/inadequate, or very good/very adequate.
In relation to the perception of thermal comfort and the habits linked to the use of domestic energy, adequate ventilation was associated with light (47.6%) and normal clothing (44.6%), with the desire to have a cooler environment in the home (52.3%), not having a heating system (77.4%), and power energy sources to heat water for domestic use (55.5%), compared to fuel sources (gasoil or natural gas).
3.3 Bivariate relations with the ventilation frequency during pandemic
Once the bivariate relationships based on the frequency of opening windows on a regular basis (before the pandemic) were established, the ventilation frequency variable during confinement was created, especially for those homes that ventilated poorly before. This variable was done in order to observe the positive habit-change carried out by the households, just in this quarantine period, and the explanatory variables that could be associated with such change. The relations are shown in Table 3 for independent variables linked to households’ and housing characteristics, comfort and use of energy, and in Table 4, for activities, alteration of habits, and desire of housing improvement, all in a context of COVID-19 lockdown.
Chi-square tests were implemented to find significant relations between each of the independent variables and the dependent one. P-value<0.05 implied significant relation.
The positive change towards a better frequency of natural ventilation was associated, in terms of characteristics of participants and households, with being an employee (64.2% vs 35.8%), and with not living with people over 65 years old (61.2% vs. 38.8%).
Regarding the dwelling characteristics, the change towards a better ventilation frequency showed significant relationships with the type of dwelling relative to the floor (62.9% vs 37.1%), to not having outdoor space (64.9% vs 35.1%), and to have orientation to the west (67.4% vs. 32.6%).
In relation to the perception of thermal comfort and habits related to the energy use, the improvement in the compared ventilation frequency was associated with cooler clothing (61.8% vs 38.2%) or warmer than usual (69.7% vs 30.3%), in a polarized way. It was also related to having a thermal preference of wanting a slightly cooler environment (70.5% vs 29.5%).
Regarding the priority adaptation measures chosen by households when feeling uncomfortable, improved ventilation was associated with using the opening/closing of windows as an activity to regulate indoor thermal comfort (70.6% vs 29.4%). Lastly, regarding the frequency of use of the heating system in confinement, those who changed their habit declared using this system not at all or rarely (69.3% vs 30.7%).
Table 4 below specifies the independent explanatory variables that established a significant relationship with those who habitually ventilated badly, and during confinement changed (or not) their behaviour patterns in that regard.
Chi-square tests were implemented to find significant relations between each of the independent variables and the dependent one. P-value<0.05 implied significant relation.
Regarding the activities carried out in the domestic space, the improvement in natural ventilation habits was associated with teleworking in non-exclusive spaces, but itinerant or circumstantially shared (66.8% vs 33.3%), as well as with teleworking spaces of dimensions appropriate (63.6% vs. 36.4%), and with good surface finishes (64.7% vs. 35.3%). In addition, the increased use of stoves (65.3% vs 34.7%), oven (66.5% vs 33.5%), and food processor (67.6% vs 32.4%), was also related to an increase in the frequency of natural ventilation.
According to the alteration of habits in the home, those households that improved their ventilation habits were significantly related to having declared alterations during confinement, in relation to: working habits (61.5% vs 38.5%), cleaning the home (64.8% vs. 35.2%), doing other home chores (64.5% vs. 35.5%), clothing change (65.0% vs. 35.0%), playing sports (64.0% vs. 36.0%), and enjoying outdoor space (65.2% vs. 34.8%).
Finally, about the desire to improve the home, the increase in opening windows was associated with the desire to improve insulation in general (64.2% vs 35.8%), with the desire for changes in the home (at least 5) (61.6% vs 38.4%), and with the lack of satisfaction in the home, in relation to non-modifiable design and construction characteristics (62.0% vs 38.0%).
3.4 Multivariate model for the dependent variable “ventilation frequency before pandemic”
The mathematical formula that expresses a probability with a logit model, allows to establish an algebraic relation among a probability and certain categorical variables, as follows:p=1(1+e−(α+βx))=1(1+e−z)
Where:
p: probability for the event to occur (being the event the success (value = 1) for the dependent variable).
α: constant of the straight line “z” (for the entire population, or sample's universe).
β: Coefficient for each of the independent explanatory variables (also for universe),
x: the value for the explanatory variable.
For the sampling, greek letters usually are changed by latin ones:p=1(1+e−(a+bx))=1(1+e−z)
a: constant of the straight line “z” (for the sampling).
b: Coefficient for each independent explanatory variable (also for the sampling).
Following this expression, for each multivariate model, coefficients b (b1, b2, b3, etc) are given in the subsequent tables, for each independent-variable categories. Also, correlation coefficients obtained for each model are included at the end of the respective table.
In the hypothesis established for the first model, the dummy dependent variable “frequency of opening windows before the pandemic” presented the success case (1) for the category “adequate ventilation”. Table 5 reflects the results of the binary logistic regression model, based on the independent variables that showed significant relationships in the previous bivariate analysis.Table 5 Odd Ratios (ORs) for the model on the dependent variable “frequency of opening windows before the pandemic”.
Table 5Variable Model parameters
B Sig. eb
Current job situation
Enterpreneur/self-employed 0.192 0.281 1.212
Employee – –
Living with elders (65+)
No – 0.092 –
Yes 0.399 1.491
Living with minors
No 0.077 0.668 1.080
Yes – –
Living with minors (6–11 years old)
No 0.390 0.105 1.477
Yes – –
Dwelling type
Flat 0.218 0.268 1.244
House – –
Own external space
No – 0.213 –
Yes 0.207 1.230
Orientation: West
No 0.239 0.190 1.270
Yes – –
Perceived Indoor Air Quality (IAQ) <0.001**
Very bad/bad/regular – –
Good −0.443 0.048* 0.642
Very good 0.156 0.529 1.169
Perceived lighting quality 0.070
No/little adequate – –
Adequate −0.128 0.690 0.880
Very adequate −0.060 0.854 0.941
Totally adequate 0.388 0.269 1.474
Habitual clothing in the home 0.458
Light 0.327 0.220 1.387
Normal 0.253 0.274 1.288
Heavy – –
Thermal preferences indoors 0.302
Heater – –
No change −0.109 0.587 0.896
Cooler 0.214 0.418 1.238
Thermal adaptation measures 0.021*
Cloths change – –
Open/Close windows 0.369 0.024* 1.446
Turn on/off heating system −0.303 0.236 0.739
Heating System <0.001**
None 0.138 <0.001** 1.147
Individual (by room/dwelling) 0.138 0.077 0.138
Collective (by building, district, etc) – –
Energy source of Domestic Hot Water 0.032*
Natural gas – –
Power 0.467 0.009** 1.596
Gasoil 0.149 0.596 1.160
Sensitivity and specificity Sensitivity Specificity
40.1 85.0
Statistics of Model Adjust −2 log verosimil. R2 Cox and Snell R2 Nagelkerke
1151.268 0.116 0.156
*The level of significance is set at *Ns < 0.05, and **Ns < 0.01, for a CI ≥ 95%. Bolds indicate the significant relation.
Table 5 shows the results of the regression for the dependent variable “frequency of opening windows before the pandemic”.
As for the variables related to the characteristics of the participants and the households that showed significant relationships in the bivariate relationships, they did not show multivariate relationships in the model. In relation to the dwelling characteristics, only the perceived indoor air quality showed a significant relationship, at the variable level. At the category level, only “good” air quality showed to be significant. The relation shown by the OR (0.642) meant that a good perception of perceived indoor air quality had 64.2% chance of ventilating adequately, with respect to homes perceiving very bad/bad/regular air quality.
The variable group related to comfort and energy use, was the one that showed the most relationship with the frequency of opening windows. One of them was the variable of thermal adaptation measures, which offered a significant relationship at the variable level, while its significant category was opening/closing windows (1.446). For every two households that changed clothes as a priority measure for thermal adaptation and adequately ventilated, there were three opening and closing the windows adequately to adapt the dwelling. The next variable associated was the heating system, both at a variable level, and for the category of “no heating system” (OR 1.147), where for every 10 homes with collective heating and adequate ventilation, simultaneously there were more than 11 homes without heating, ventilating with similar frequencies. Finally, of this group of variables, the energy source for heating domestic hot water (DHW) also showed a significant relationship at the variable level, and at the category level, for electrical energy. Therefore, according to the OR obtained (1.596), for every five households that used natural gas to heat water and ventilate adequately, there were eight households using electricity and ventilating in the same way. This category obtained the highest logit of the entire model, showing the strongest relationship.
3.5 Multivariate model for the dependent variable “ventilation frequency during pandemic”
Following the formula established in subsection 3.4, the hypothesis established for the second and third models, had the dummy dependent variable “frequency of opening windows during the lockdown”, which presented the success case (1) for the category “adequate ventilation”. Table 6 reflects the results of the binary logistic regression model, with the independent variables that showed significant relationships in the previous bivariate analysis, related to general variables.Table 6 Odd Ratios (ORs) for the dependent variable “frequency of opening windows in confinement, having been poor before pandemic. General variables”.
Table 6Variable Model parameters
B Sig. eb
Current job situation
Enterpreneur/self-employed – –
Employee 0.632 0.006** 1.880
Living with elders (65+) 0.056
No 0.620 1.859
Yes – –
Dwelling type 0.171
Flat 0.304 1.355
House – –
Own external space 0.630
No 0.097 1.102
Yes – –
Orientation: West
No – –
Yes 0.353 0.107 1.423
Habitual clothing in the home 0.024*
Light – –
Normal 0.211 0.328 1.234
Heavy 0.857 0.007** 2.356
Thermal preferences indoors 0.315
Heater – –
No change −0.034 0.885 0.967
Cooler 0.409 0.240 1.506
Thermal adaptation measures <0.001**
Cloths change – –
Open/Close windows 0.806 <0.001** 2.239
Turn on/off heating system −0.351 0.188 0.704
Use frequency of Heating System 0.093
Never/barely 0.445 0.081 1.561
Only if necessary 0.004 0.987 1.004
Frenquently/Continuously – –
Sensitivity and specificity Sensitivity Specificity
84.2 35.3
Statistics of Model Adjust −2 log verosimil. R2 Cox and Snell R2 Nagelkerke
747.559 0.092 0.124
*The level of significance is set at *Ns < 0.05, and **Ns < 0.01, for a CI ≥ 95%. Bolds indicate the significant relation.
Among the general variables, or characteristics of households and dwellings, one of those that were significantly associated was the current employment situation. For each home with the presence of self-employed workers or entrepreneurs ventilating adequately, there were almost twice as many in which there were employees ventilating the same way.
In the subgroup of housing comfort and energy aspects, two variables showed a significant relationship. One of them was the usual clothing at home, where the category that reflected this relationship was warm clothing (OR 2.356). This indicator establishes that for each cohabiting nucleus that used light clothing and ventilated adequately, there were almost 2.5 households dressing warmly when ventilating in the same way. This logit was the largest of the multivariate relationship table during the pandemic, in terms of overall independent variables (Table 6).
As the last significant variable in this table, the one related to the thermal adaptation measures was shown. In this case, the OR (2.239) indicates that for each household that opted for a change of clothes to adapt thermally by ventilating adequately, more than twice as many households resorted to opening/closing windows for the same purpose, with a similar frequency. This category also presented one of the highest logits in significant relationships.
Below, Table 7 represents those relations maintained among dependent variable “window opening frequency during confinement, being poor ventilated before”, with independent variables linked to activities and habit changes associated to be confined, such as teleworking compared use of kitchen appliances, habit changes and desire of housing improvement.Table 7 Odd Ratios (ORs) for the model on the dependent variable “frequency of opening windows during confinement, having been poor, before the pandemic. Variables related to activities and habits in confinement”.
Table 7Variable Model parameters
B Sig. eb
Type of teleworking space
Itinerant or occasional shared space 0.418 0.077 1.519
Previous shared or exclusive space – –
Adequate room size
No – 0.489 –
Yes 0.180 1.197
Adequate surface finishing
No – 0.925 –
Yes 0.022 1.022
Compared use of stoves 0.127
Less use than usual 22.355 1.000 5 × 109
Same us as usual −0.594 0.042 0.552
More use than usual – –
Compared use of oven 0.008**
Less use than usual – –
Same use as usual 1.962 0.127 7.114
More use than usual 2.695 0.039* 14.809
Compared use of kitchen robot 0.322
Less use than usual 0.939 0.156 2.557
Same use as usual 0.239 0.366 1.270
More use than usual – – –
Work
No 0.990 0.017* 2.691
Yes – – –
Cleaning
No – –
Yes 0.250 0.340 1.284
Domestic chores
No – –
Yes 0.088 0.756 1.092
Clothing change
No 0.233 0.310 1.263
Yes – – –
Sports
No – –
Yes 0.584 0.013* 1.793
Enjoy the external space
No – –
Yes 0.470 0.043* 1.600
Desire for insulation improvement
No – –
Yes 0.332 0.169 1.394
Changes in housing (5 or more)
No – –
Yes 0.265 0.589 1.303
Home satisfaction (essential features)
No – –
Yes 0.185 0.706 1.203
Sensitivity and specificity Sensitivity Especificity
40.6 84.0
Statistics of Model Adjust −2 log verosimil. R2 Cox and Snell R2 Nagelkerke
495.096 0.122 0.165
*The level of significance is set at *Ns < 0.05, and **Ns < 0.01, for a CI ≥ 95%. Bolds indicate the significant relation.
This third logistic regression model, the second for the variable of frequency of opening windows during quarantine (for households that had poor ventilation before), focused on the relationships with variables of activities or habits linked to confinement itself. Specifically, the multivariate relationships that were significant were: the compared use of the oven, the alteration of the habit related to work, sports, and enjoying the outside environment.
The comparative use of the oven presented significance as a variable, but also at the level of the category “more use than usual”, whose logit far exceeded all those of the observed models. Indeed, with an OR = 14,809, for each household that used the oven in confinement less than usual, ventilating adequately, 14 households used more the oven, with the same frequency of window opening.
Regarding the perception of habit alteration during lockdown, those households that declared seeing the work aspect altered were 2.7 times more than those that did not declare it, belonging in both cases to the cases that ventilated adequately.
Likewise, those who declared that their sporting habit had changed accounted for almost 2 (1793) times more households than those who did not declare it, both cases being households ventilating with adequate frequency.
Lastly, those households that stated that their habits of enjoying outdoor activities (in outdoor space) had been altered and that they ventilated frequently, were 1.6 times more than those that, ventilating in the same way, did not observe changes in terms of the relationship with the external environment.
Similarly, those who declared that their sport habit had changed accounted for almost 2 (1793) times more households than those who did not declare it, both cases being households ventilating with adequate frequency.
4 Discussion
Observing the bivariate relationships, workers who could stay at home longer in the dwelling, presented adequate ventilation frequencies, compared to those who working as employees. The presence of older people and minors was related to frequencies poor window opening, which could be explained by a matter of security in the home, especially when it comes to avoiding accidents [26].
On a regular basis, the most frequent window opening was related to the dwelling type, specifically single-family homes. Flats were related to poor ventilation.
Dwellings with a total or partial orientation with a west component tended to ventilate less regularly. Taking into account the Spanish latitude, it could be presumed that there is a certain bias in this response, where a house with a west component is usually not sunny until the afternoon, so they are cold houses, and therefore, they required more heating than a house with a south or east component, for instance Ref. [27]. Therefore, if there was a higher demand for heating, opening windows could be avoided to be more energy efficient.
Among homes that ventilated the best, there were those with the greatest need to ventilate (due to humidity or charged environment) and those who already considered their indoor air to be of high quality, perhaps as an effect of their own habit of often opening windows [28]. The relationship with the quality of perceived general lighting (both natural and artificial) was related in a polarized way with the frequency of natural ventilation. This may be due to the fact that those who opened the windows more could be either homes that had a greater need to illuminate their rooms, or those in which the effect of opening the windows resulted in high-quality lighting or to enjoy the view [[29], [30], [31], [32]].
Those who habitually ventilated the most tended to dress lightly or normally, compared to those who dressed warmly at home. This may be related to the hypothesis of bias due to the pre-pandemic winter period, which, together with colder dwellings (due to orientation, due to lack of sunlight due to the building's own or remote obstacles, or for other reasons), and in its case due to a greater need for heating, they bundled up and therefore avoided opening windows so as not to have greater thermal demands. Those with better natural ventilation frequencies did not use fossil energy to heat water; instead used power energy.
When observing the ventilation frequency response in confinement of those who had habitually ventilated poorly, some reasoning was altered by what such a radical and disruptive change in activity and habits entailed [6]. As an example of this, in this period of confinement those who ventilated the best were those who were employed by others. As was mentioned in the pre-pandemic period, although self-employed or entrepreneurs, being able to remain teleworking at home, could be the ones who ventilated the most, those who did not do so before the pandemic did not do so during confinement. But those who usually worked outside, by staying at home teleworking, ventilated more, as highlighted relevant international organizations as International Labour Organization (ILO) [33].
Another of the relationships that were altered with the frequency of natural ventilation was that of the existence of people over 65 at home, which was related to less ventilation. Although during confinement it was advised to ventilate homes, the fear of contagion among the elderly, as a vulnerable group, by COVID-19, or by other types of viruses, such as colds, or flu, could lead to closing the windows.
During confinement the most ventilated homes were the flats, because they had a greater relationship with the outside world. Those dwellings without their own outdoor space ventilated more adequately during confinement. This could be due to a need for outside contact, as well as a higher level of overcrowding.
This greater presence of the cohabitants in the home could make the orientation of the west component, together with the progressive entry of spring, make it more necessary to ventilate frequently than for other orientations.
Only those who were in thermal comfort were related to poor ventilation. This can be explained by the use of heating, since those who used heating the most, ventilated poorly. However, the relationship of ventilating frequently was maintained between those who chose it as a priority adaptation measure and those who preferred to be cooler.
The largest opening of windows occurred in teleworking spaces shared circumstantially or itinerant. This could be explained by a greater presence of cohabitants (because of care, above all) in spaces of this nature. However, those accustomed to teleworking, or to using exclusive spaces in the home for these tasks, did not ventilate well beforehand.
These hypotheses about the most open and largest spaces, and with a greater presence of cohabitants, are confirmed by the fact that the households most satisfied with the size of the teleworking space were the ones that ventilated the best. Similarly, those with better surface finishes, also ventilated better, which can also be related to this type of space, traditionally more social, more cared for, and thus, more pleasant to stay working, as were halls and living rooms [34,35].
With respect to other activities during confinement, increased culinary activity (what reflected the increasing demand on domestic energy supply in lockdown) [36], was related to a higher frequency of ventilation during confinement. This opens the possibility that it was not only due to the greater presence of cohabitants, but also due to the need to exchange air with the outside, also due to the effect of the heat produced, in the case of the oven, or due to the odours generated (which would explain, for example, the case of kitchen robots) [37].
Some of the behavioural changes that have been linked to a greater frequency of opening windows, such as work and lack of contact with nature, warranted more ventilation. But also, the alteration of domestic tasks, including cleaning, in addition to having to ventilate to release possible chemical products, among others, also needed ventilation.
People who want more insulation in their home ventilated more frequently, and those who want 5 or more aspects to change in the dwelling ventilated less frequently. This could be related to urban environments, with smaller flats, where families lived in a higher proportion of rent, and presented less capacity for change in design and construction aspects [38].
In the logistic regression model, the strongest relationships were established for the perception of good air quality, measures of thermal adaptation, and energy aspects, such as the unavailability of heating and the electrical source of energy for hot water. This confirms that the adequate opening of windows on a regular basis, that is, in an almost cultural or intrinsic way to the habit of ventilating, depends not only on having a good perception of air quality (in terms of air that is not stale, odourless or charged), but also of its traditionally intrinsic but inverse relation to thermal comfort. Since, if this depended on a demand solved with a heating system, opening the windows would waste energy by losing previously treated air in the exchange with the outside [37]. This could be solved with an increase in hybrid air conditioning systems (hot/cold) and mechanical or hybrid ventilation incorporated in the system, so that they do not have to choose between thermal comfort and indoor air quality [39].
The thermal adaptation of opening/closing windows is an option that was positioned contrary to turning the heating on or off, or using clothing to self-regulate thermal comfort [40]. Lastly, the perception of energy efficiency, it seemed to extend to the ways of consuming energy to heat water for domestic use, since those fuel sources interfered with the opening of windows.
As for the regression models related to the period of confinement, forced residence in the dwelling, which translated into teleworking for many households, also generally altered the way of ventilating. Clothing also affected, since those who warmed up more opened the windows more, so it is understood, together with the multivariate relationship of the adaptation measures, that those households that regulated opening and closing windows had no problem staying warm. more if necessary, and they opened despite the thermal comfort. There is therefore a different discourse for homes that mainly opt for achieving thermal comfort, and for those focused on ventilation and air quality. This debate has been very important for the re-conceptualization of Spanish regulations in terms of energy and health, which has traditionally focused on the progressive search for energy savings and efficiency in the home, while gradually losing air permeability when leaving sealing the newest projects. The latest regulatory revisions have taken both aspects into account, and propose mechanical or hybrid ventilation systems, so as to compensate for the greater thermal insulation of both opaque enclosures and opening systems, including carpentry [13,14]. However, the big problem persists in existing homes [12] which, as already mentioned, in Spain are more than 90%, with poor levels of thermal comfort and insulation [15], and that, despite being candidates for national and European fundings [41,42], many of them are limited to technical responses of insulation from the outside, and/or change of windows, but they do not solve the problem of air infiltrations, nor the control by ventilation systems that ensure a correct balance with possible support air conditioning equipment.
Although it is necessary to tend not to depend on energy, on the other hand, the support of systems that guarantee the well-being and health of people, especially vulnerable groups, translates into responding to moments of thermal discomfort, to avoid problems not only from thermal discomfort, but also from energy poverty, especially in the face of expectations such as the scenarios foreseen for 2050 by the IPCC [43]. In this framework, and under the Sustainable Development Goals established by the United Nations (UN), some coupled with air conditioning systems and other new proposals based not only on natural ventilation have been suggested during the pandemic, as a less expensive alternative both in the initial investment and in its performance and maintenance, in order to also support initiatives with a lower economic, energy and environmental impact [44], although these solutions must be adapted to the type of space, and to the needs derived from the climatic environments of each place, paying attention to noise and any other energy expenditures associated [45]. Extreme weather events, such as heat and cold waves are affecting severely the countries of southern Europe, including Spain [46]. In this sense, problems such as energy poverty can only get worse, and faced with this potentially increased problem, only technically and energy efficient solutions can be offered, if possible supported by renewable and clean energies, and with mechanically controlled ventilation support (or hybrids), which regulate the quality of the indoor air, so that people do not have to choose between thermal comfort and air quality, nor having to leave it in the hands of the presence and/or will of people, subject to cultural or behavioural issues [47].
The study has several limitations. In the first place, the selection of participants was made for convenience and therefore was not representative. On the other hand, the outbreak of the pandemic was abrupt and disruptive. The need to be able to count on the testimonies and opinions of people during the first wave, together with the problem of being able to carry out research face-to-face, gave it a great exploratory value, since there were also very few studies that addressed confinement during the initial phase of the pandemic, and in particular, bearing in mind that the home was the main refuge of the population.
Second, the very nature of studies based on online questionnaires, since not all people had access to the Internet. Although, in the case of Spain, 95.3% of the Spanish population in 2020 of households had Internet access [48].
Thirdly, the dependent variable related to poor and adequate ventilation was a qualitative or categorical variable constructed from five original categories corresponding to the frequency of opening/closing windows, which was requested both for the “before” of the confinement, as for the “during” (lockdown). These categories were: “Continuously open”, “Several times a day”, “Once a day”, “Sometimes a week”, “Continuously closed”. The authors understand that this variable has limitations due to its qualitative nature, since the ideal situation would have been to be able to count on monitored data, or to have made a specific questionnaire on ventilation (at least, with some questions on frequency in terms of time opened, distribution in weekdays/weekends, etc). However, authors also understand that this basic information, combined with other data on thermal comfort, energy consumption, and behavioural and sociodemographic patterns, could offer valuable information corresponding to a crucial moment in the life of Spanish households and their adaptive capacity to extreme events, such as a general lockdown.
Other limitation was not to consider external environmental aspects, such as meteorological events or noise annoyance to explain potential causes to window opening/closing patterns. This fact is based on two reasons: first, the overall character of this questionnaire, with no specific questions about window-related aspects; and second, the level of external noise decreased during pandemic, so the noise annoyance in this case seemed not to be relevant in this period. But obviously, those aspects usually affect households’ patterns on window opening.
The last limitation is derived from the lack of mechanical/hybrid ventilation systems in the most of the Spanish current housing stock. For this reason, indications on the many advantages of these kind of systems, such as to control airborne SARS-CoV-2 transmission, have not been included in this manuscript. Nevertheless, this advantage and many others have to be highlighted, encouraging their installation, to control the indoor air quality.
5 Conclusions
Opening the windows is a simple action, but obeys a complex reflection, based on multiple potential reasons, just like the fact of not opening them. It is not just a behavioural or cultural issue. The reasons that may lead a home to open the windows more or less frequently may not even be intuitive, or not entirely, being conditioned by the need or the culture of natural ventilation. A poor air quality, adaptive thermal measures, the lack of heating systems, and the sources to heat water, were reasons to determine the window opening frequency.
However, the disruptive event of home confinement due to COVID-19, implied a change in routines and habits, and a significant increase in the presence of all members at home at the same time (even sharing spaces for a protection, care, surveillance or need). With this, the criteria of indoor environmental quality, specially ventilation, were also conditioned by the presence of people, as well as by the deprivation of contact with the outside and nature.
This led to value the windows as elements of connection with that exterior and with natural elements (gardens, parks or nearby trees), which were altered according to the need for contact of the cohabitants, also subject to the needs of thermal comfort and changing weather. The very presence of people also led to opening the windows to compensate the lack of fresh air, promoting exchange air with the outside. The concentration of activities indoors, especially those requiring a higher level of concentration, and the generation of greater thermal loads (especially latent, such as sports), or others that physically require air drafts to speed up its completion (such as surface cleaning, for example), also affected this natural ventilation pattern.
But one of the most underlying issues is how natural ventilation is subject to criteria for the use of thermal energy, above all, and to the perception of comfort and how each home uses thermal adaptive options. These issues would be solved, at least to a large extent, if hybrid or mechanical ventilation systems would be integrated into hot/cold air conditioning systems in the homes, as required in the most recent building regulations. However, this is not reflected in the existing residential stock, almost entirely prior to these regulations, and which can only be ventilated naturally. For these cases, a comprehensive rehabilitation strategy is needed, that also integrate, when necessary, controlled ventilation mechanisms to ensure indoor air quality.
Funding
This research was funded by 10.13039/501100003339 Consejo Superior de Investigaciones Científicas (CSIC) , grant num-ber 202060E225, entitled: “Proyecto sobre confinamiento social (COVID-19), vivienda y habitabi-lidad [COVID-HAB]”.
Credit author statement
All authors contributed to the design and implementation of the research, to the analysis of the results and to the writing of the manuscript.
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
The data that has been used is confidential.
Acknowledgements
The authors want to thank the CIBERESP of the Instituto de Salud Carlos III (Spain) for access to the online data collection platform in this study. Also, they appreciate the contribution from Aplica Coop. with the data analysis.
==== Refs
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| 0 | PMC9747684 | NO-CC CODE | 2022-12-15 23:23:24 | no | 2022 Dec 14;:105649 | utf-8 | null | null | null | oa_other |
==== Front
Environ Res
Environ Res
Environmental Research
0013-9351
1096-0953
Elsevier Inc.
S0013-9351(22)02394-5
10.1016/j.envres.2022.115067
115067
Article
Cross-sectional associations of maternal PFAS exposure on SARS-CoV-2 IgG antibody levels during pregnancy
Kaur Kirtan a
Lesseur Corina a
Chen Lixian a
Andra Syam S. a
Narasimhan Srinivasan a
Pulivarthi Divya a
Midya Vishal a
Ma Yula a
Ibroci Erona b
Gigase Frederieke b
Lieber Molly c
Lieb Whitney c
Janevic Teresa cd
De Witte Lotje D. b
Bergink Veerle b
Rommel Anna-Sophie b
Chen Jia a∗
a Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
b Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
c Department of Obstetrics, Gynecology and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
d Department of Population Health Science & Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
∗ Corresponding author.
14 12 2022
14 12 2022
1150679 10 2022
9 12 2022
13 12 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.
Background
Perfluoroalkylated substances (PFAS) are man-made, persistent organic compounds with immune-modulating potentials. Given that pregnancy itself represents an altered state of immunity, PFAS exposure-related immunotoxicity is an important variable to consider in SARS-CoV-2 infection during pregnancy as it may further affect humoral immune responses.
Aim
To investigate the relationship between maternal plasma PFAS concentrations and SARS-CoV-2 antibody levels in a NYC-based pregnancy cohort.
Methods
Maternal plasma was collected from 72 SARS-CoV-2 IgG + participants of the Generation C Study, a birth cohort established at the beginning of the COVID-19 pandemic in New York City. Maternal SARS-CoV-2 anti-spike IgG antibody levels were measured using ELISA. A panel of 16 PFAS congeners were measured in maternal plasma using a targeted UHPLC-MS/MS-based assay. Spearman correlations and linear regressions were employed to explore associations between maternal IgG antibody levels and plasma PFAS concentrations. Weighted quantile sum (WQS) regression was also used to evaluate mixture effects of PFAS. Models were adjusted for maternal age, gestational age at which SARS-CoV-2 IgG titer was measured, COVID-19 vaccination status prior to IgG titer measurement, maternal race/ethnicity, parity, type of insurance and pre-pregnancy BMI.
Results
Our study population is ethnically diverse with an average maternal age of 32 years. Of the 16 PFAS congeners measured, nine were detected in more than 60% samples. Importantly, all nine congeners were negatively correlated with SARS-CoV-2 anti-spike IgG antibody levels; n-PFOA and PFHxS, PFHpS, and PFHxA reached statistical significance (p < 0.05) in multivariable analyses. When we examined the mixture effects using WQS, a quartile increase in the PFAS mixture-index was significantly associated with lower maternal IgG antibody titers (beta [95% CI] = −0.35 [-0.52, −0.17]). PFHxA was the top contributor to the overall mixture effect.
Conclusions
Our study results support the notion that PFAS, including short-chain emerging PFAS, act as immunosuppressants during pregnancy. Whether such compromised immune activity leads to downstream health effects, such as the severity of COVID-19 symptoms, adverse obstetric outcomes or neonatal immune responses remains to be investigated.
Keywords
PFAS
SARS-CoV-2 IgG
COVID19
Immunotoxicity
Pregnancy
==== Body
pmc1 Introduction
Per-/Poly-Fluoroalkyl Substances (PFAS) are persistent organic compounds that are resistant to degradation due to their stable structure (De Silva et al., 2020; Wang et al., 2017). These man-made compounds are ubiquitous in the environment (i.e., soil, groundwater) and in consumer goods (i.e., food packaging, textiles, non-stick cookware). Thus, humans are continuously exposed through contaminated drinking water and consumer products (Agency for Toxic Substances and Disease Registry - ATSDR 2020; Centers for Disease Control – CDC, 2019; Worley et al., 2018). Although the long-chain (i.e., congeners with a carbon-backbone greater than seven carbons, such as PFOA and PFOS) “legacy” PFAS have been voluntarily phased out by industrial manufacturers, short-chain or emerging PFAS (i.e., GenX, PFBS) are now readily used as replacements (Ateia et al., 2019; Kaboré et al., 2018; Wang et al., 2017). Short-chain PFAS are rising in detection frequency in drinking water and in human biological samples (Kaboré et al., 2018). Despite having shorter half-lives than their legacy counterparts (Xu et al., 2020), emerging PFAS still demonstrate deleterious effects to human health, ranging from metabolic perturbation to carcinogenic potential (Chang et al., 2022; Coperchini et al., 2020; Shearer et al., 2021).
Given the influence of the immune system on a myriad of organs and tissues, the immunotoxic impact of PFAS exposure is a chief public health concern and has been investigated over the past decade (Grandjean et al., 2012; Grandjean et al., 2017; Grandjean et al., 2017; Meng et al., 2018; National Toxicology Program, 2016; Stein et al., 2016; Zhang et al., 2015 National Toxicology). These studies have established that elevated PFAS exposure reduces humoral immune responses (Smith and Cunningham-Rundles, 2019). In the midst of the emerging COVID-19 pandemic, worsened clinical outcome of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection has been linked with elevated PFAS exposure in a Danish population-based cohort (Grandjean et al., 2020). More recently, two other studies reported that individuals from PFAS-polluted regions in China and Italy demonstrated a greater risk of COVID-19 infection susceptibility and mortality (Catelan et al., 2021; Ji et al., 2021). The link between higher PFAS exposure and the risk of worsened COVID-19 prognosis is also under investigation by the CDC, which published a statement in conjunction with the ATSDR, underscoring the need for further research on this topic (ATSDR 2020). The statement recognizes that high levels of PFAS exposure may affect immune function, antibody responses to vaccines and COVID-19 severity (Looker et al., 2014; National Toxicology Program – NTP, 2016).
Pregnancy represents an altered state of immunity and SARS-CoV-2 infection can further modify the immune system, therefore PFAS exposure is an important variable to consider given that it has been shown to suppress immune responses (Granum et al., 2013). Pregnant individuals infected with SARS-CoV-2 appear to have compromised SARS-CoV-2-specific placental antibody transfer and altered glycosylation profiles (Ateyo, 2021). Compared to non-pregnant individuals, pregnant individuals have lower SARS-CoV-2 antibody titers after the first dose of the vaccine (Ateyo, 2021). Pregnant individuals who were infected with SARS-CoV-2 earlier in pregnancy demonstrate a greater IgG response (Buckley, 2022). Due to its novel nature, the long-term health implications of COVID-19 are not fully understood. Elevated maternal PFAS exposure during the perinatal time period may further impact COVID-19-related health outcomes.
As of the end of September 2022, more than 94 million COVID-19 cases and upwards of 1 million deaths have been attributed to SARS-CoV-2 infection in the US alone, and over 225,000 cases and 300 deaths were amongst pregnant individuals (CDC Data Tracker, 2022). More than two million people have been infected in New York City (NYC) by SARS-CoV-2 as of September 2022 (Tracking Coronavirus in New York: Latest Map and Case Count, 2022). To explore the impacts of gestational SARS-CoV-2 infection in pregnancy, The Generation C (Gen C) cohort was established in 2020 at the Mount Sinai Hospital in NYC (CDC grant 75D30120C08186). Our pilot study presented here leveraged a subset of the on-going Gen C study to investigate possible links between PFAS exposure and immune responses to SARS-CoV-2 infection in pregnant women.
2 Methods
2.1 Study population
The Gen C cohort study was established in April 2020 to investigate the effects of SARS-CoV-2 infection during pregnancy on birth outcomes as described in detail previously (Janevic et al., 2022; Lesseur et al., 2022; Molenaar et al., 2022). This cohort recruited 3121 pregnant participants in NYC from the Mount Sinai Health System (MSHS) between April 20, 2020 and February 24, 2022. As a part of routine obstetrical care, enrolled participants provided blood samples in each trimester. Maternal plasma samples were collected between April 23, 2020 and May 21, 2021. Past SARS-CoV-2 infection was confirmed via serological SARS-CoV-2 IgG antibody test (described in section 2.3) and electronic medical record (EMR) review. Vaccination history was ascertained through the EMR of the MSHS, which is linked to the New York Citywide Immunization Registry (CIR) and consolidates all immunization information across NYC into a centralized database (further details can be found in the supplemental section). Pre-pregnancy BMI was gathered from EMR review and race/ethnicity were self-reported in participant questionnaires. All participants provided written informed consent as per the institutional review board (IRB) at the Icahn School of Medicine at Mount Sinai (protocol IRB-20-03352, April 15, 2020). This pilot study included 72 participants who were SARS-CoV-2 IgG anti-spike protein positive (IgG+). These participants were enrolled in the early phase of the study, i.e. between April 2020 and May 2021, and had plasma samples available for PFAS measurements. Amongst this subset, seven individuals received at least one dose of the COVID-19 vaccine before blood collection.
2.2 Maternal plasma PFAS measurements
Maternal plasma, stored at −80 °C, was used to quantify a panel of 16 PFAS congeners [Supplemental Table 1] at the Icahn School of Medicine at Mount Sinai's Human Health Exposure Analysis Resource (HHEAR) Targeted Analysis Laboratory, a continuation of Children's Health Exposure Analysis Resource (CHEAR) (Balshaw et al., 2017). A low-volume (100 μL) and high-sensitivity (0.2 ng/mL median Limit of Detection - LOD) targeted assay using isotope-dilution liquid chromatography with tandem mass spectrometry (LC-MS/MS) was followed based on a CDC method (Kato et al., 2018) with modifications (Coggan et al., 2019; Reagen et al., 2008). The assay includes the most widely studied PFAS (n-PFOS, Sm-PFOS, n-PFOA, PFHxS, PFDA, PFNA), emerging PFAS (PFBS, PFHpS, PFHpA, PFHxA, PFUndA, PFDoDA), and replacements (such as N-EtFOSAA, N-MeFOSAA, among others) (Poothong et al., 2017). Additional analytical details are provided in the supplementary section. Matrix-based LODs were determined using a laboratory QC serum pool (product # BP2525100) from Fisher Scientific (Hampton, NH, USA), which ranged from 0.04 to 0.8 ng/mL for the study PFAS congeners. Quality controls (QCs) included in this study were experimental blanks (reagent-and matrix-based), matrix spikes in the range of assay validation, NIST standard reference material (SRM 1957: Organic Contaminants in Non-Fortified Hu et al., 2019: Organic Contaminants in Fortified Human Serum), and archived proficiency testing material. HHEAR/CHEAR includes additional internal quality assurance and QC protocols, including pooled sample analysis to assess analytical precision (Kannan et al., 2021). The Mount Sinai HHEAR/CHEAR Network Laboratory Hub has participated and qualified in proficiency testing programs for PFAS in serum by G-EQUAS (http://www.g-equas.de/) (Göen et al., 2012) and CTQ-AMAP (https://www.inspq.qc.ca/en/ctq/eqas/amap/description) (CTQ, AMAP: AMAP Ring Test for Persistent Organic Pollutants in Hu et al., 2019 , CTQ, 2022).
2.3 SARS-CoV-2 IgG antibody quantification
Serological testing for IgG antibodies against the SARS-CoV-2 spike (S) protein, an enzyme-linked immunosorbent assay (ELISA) developed at the Icahn School of Medicine at Mount Sinai (Stadlbauer et al., 2020) was used. IgG antibodies were measured in the same maternal plasma samples in which PFAS were measured during pregnancy.
2.4 Statistical analyses
The analyses were conducted in two stages; first, multiple linear regression models were used to assess the associations between maternal SARS-CoV-2 IgG antibody titers and individual PFAS congener concentrations in maternal plasma. Second, weighted quantile sum (WQS) regression was implemented to account for the joint mixture effects of the individual PFAS pollutants using the “gWQS: generalized Weighted Quantile Sum regression” package in R (Carrico et al., 2015; Czarnota et al., 2015; Renzetti et al., 2016). Both the linear and WQS regression models were adjusted for maternal age, gestational age at which SARS-CoV-2 IgG titer was measured, COVID-19 vaccination status prior to IgG titer measurement, maternal race/ethnicity, parity, type of insurance and pre-pregnancy BMI. The covariates were selected as they have been associated with PFAS exposure in previous studies (Boronow et al., 2019; Nelson, 2012).
PFAS concentrations below LOD were imputed by the formula LOD/(√2). Further, PFAS analytes that were below LOD in more than 40% samples were excluded from analyses; thus the final analytical panel includes nine PFAS congeners (PFOS, PFHxA, PFHxS, n-PFOA, PFHpS, PFDA, PFNA, PFBS, PFUnDA). Maternal plasma-PFAS concentrations and SARS-CoV-2 spike IgG antibody titer values were log10-transformed prior to running statistical analysis models due to skewed distributions. Correlations between maternal PFAS concentrations and IgG titers were assessed using Spearman correlations. All analyses were performed in R version 4.2.0 (R Core Team, 2022). Any two-tailed p-value <0.05 is considered statistically significant.
3 Results
Sociodemographic and clinical characteristics of the of 72 Gen C participants in the current study are shown in Table 1 . Our NYC-based study population is comprised of 38.9% White, 29.2% Hispanic and 22.2% Black participants, which is reflective of the catchment area of our health system. A large fraction of our study participants had obesity (45.8%) prior to pregnancy and were nulliparous (51.4%) with an average age of 32.9 years at delivery. On average, blood samples were collected at 27 weeks of gestation to measure SARS-CoV-2 spike IgG titers, which varied widely with an average titer of 1060 arbitrary antibody units (AU) per milliliter (SD: 1480 AU/mL, range: 50–64,000 AU/mL).Table 1 Sociodemographic and clinical characteristics of our study population.
Table 1 n (%) Mean (SD) [Range]
Maternal characteristics
Age at delivery (years) 32.9 (4.6) [24–46]
BMI (kg/m2) 30.4 (7.9) [18.9–59.8]
SARS-CoV-2 Spike IgG titer 1060 (1408) [50–64,000]
Gestational age at blood draw (weeks) 27 (10.8) [4.7–39.9]
BMI category
Normal 18 (25%)
Overweight 21 (29.2%)
Obese 33 (45.8%)
Race ethnicity
White 28 (38.9%)
Hispanic 21 (29.2%)
Black 16 (22.2%)
Asian 3 (4.2%)
Other 4 (5.6%)
Parity
Multiparous 35 (48.6%)
Nulliparous 37 (51.4%)
Delivery mode
C-Section 28 (38.9%)
Vaginal 43 (59.7%)
Insurance Category
Private 48 (66.7%)
Public 22 (30.6%)
No insurance 2 (2.7%)
Infant characteristics
Gestational age at delivery (weeks) 38.4 (2.1) [32.1–41.6]
Birthweight (g) 3138.4 (539.9) [1545–4090]
Infant sex
Female 43 (59.7%)
Male 29 (40.3%)
Categorical variables are frequencies and percentages (%). Continuous variables summarized with mean (standard deviation) and [range].
The summary statistics of plasma-PFAS concentrations from the 72 participants are shown in Table 2 . Out of the 16 total PFAS congeners measured, nine were detected in more than 60% of the study samples; three of them (i.e., PFOS, PFHxA and PFHxS) were detected in all samples. We compared the levels detected in our study population with those reported in 977 female participants in 2017–2018 cycle of National Health and Nutrition Examination Survey (NHANES) [Table 2]. While levels of “legacy” PFAS, such as PFOA and PFOS, in our study population were lower than those of NHANES (median: 0.91 vs. 1.27 ng/mL, respectively for PFOA; 0.41 vs. 3.30 ng/mL, respectively for PFOS), median levels of the “emerging” PFAS, such as PFHxS (0.23 ng/mL) and PFBS (0.38 ng/mL) were higher in comparison to below LOD levels of both compounds reported in NHANES. Among the nine congeners detected in a majority of our study samples, several of them demonstrated mostly positive, moderate correlations (rho > |0.20|), as shown by the Spearman correlation coefficients in Fig. 1 . The only exception is between PFNA and PFUnDA, which were negatively correlated. We also examined associations between IgG levels and potential confounding variables including pre-pregnancy BMI, infant sex and race/ethnicity in bivariate analyses. No significant associations were observed for these variables [Supplementary Fig. 1].Table 2 Summary statistics of the levels of PFAS (ng/mL) in maternal plasma (n = 72; 2020–2021) from our study population and in comparison to levels reported in NHANES female serum (n = 977, survey years 2017–2018).
Table 2PFAS Congener Gen C Maternal Plasma (n = 72) NHANESc Female Serum (n = 977)
LOD % <LOD Mean SD Min. Median Max. Median
PFOSa 0.2 0 1.84 1.13 1.52 0.41 6.15 3.30
PFHxA 0.1 0 0.32 0.24 0.16 0.23 1.62 < LOD
PFHxS 0.04 0 0.46 0.28 0.15 0.39 1.29 0.80
n-PFOA 0.2 1.4 1.10 0.60 0.14 0.91 2.96 1.27
PFHPS 0.04 5.6 0.10 0.04 0.03 0.10 0.24 0.20
PFDA 0.1 8.3 0.49 0.22 0.07 0.45 1.02 0.20
PFNA 0.2 15.3 0.51 0.40 0.14 0.40 1.81 0.40
PFBS 0.2 20.8 0.39 0.23 0.14 0.38 1.32 < LODb
PFUnDA 0.3 22.2 0.56 0.38 0.21 0.42 2.03 0.10
a Sum of linear (n-PFOS) and branched (Sm-PFOS) isomers of PFOS.
b Data only listed for years 2013–2014, n = 1136 females for PFBS.
c Data from CDC Exposure Report, 2021 (www.cdc.gov/exposurereport).
Fig. 1 Spearman correlations between nine PFAS in final analytical panel measured in maternal plasma. Spearman coefficient (rho) with p-value <0.05 are displayed in the corresponding block.
Fig. 1
Linear regression models reported in Table 3 demonstrate the relationship between maternal plasma PFAS levels and SARS-CoV-2 IgG titers. These models are adjusted for maternal age, gestational age at which SARS-CoV-2 IgG titer was measured, COVID-19 vaccination status prior to IgG titer measurement, maternal race/ethnicity, parity, type of insurance and pre-pregnancy BMI. The beta estimates for all nine PFAS congeners are negative, indicating inverse associations between PFAS and IgG levels. For four out of the nine PFAS (n-PFOA, PFHxS, PFHpS and PFHxA), the associations are statistically significance (p < 0.05).Table 3 Associations between maternal SARS-CoV-2 anti-spike IgG titers and PFAS exposure.
Table 3PFAS Congener Beta SE p-value 95%CI
Linear Regression of Individual PFAS
n-PFOA −0.62 0.25 0.017* (-1.11, −0.12)
PFHxS −0.68 0.25 0.008* (-1.18, −0.18)
PFHpS −0.81 0.31 0.011* (-1.42, −0.19)
PFHxA −0.54 0.25 0.037* (-1.04, −0.04)
PFNA −0.22 0.20 0.269 (-0.62, 0.18)
PFOS −0.33 0.26 0.209 (-0.85, 0.20)
PFUnDA −0.20 0.22 0.388 (-0.63, 0.25)
PFBS −0.24 0.25 0.339 (-0.74, 0.26)
PFDA −0.15 0.22 0.490 (-0.60, 0.29)
WQS regression of PFAS Mixture
PFAS Mixture −0.35 0.09 0.0003* (-0.52, −0.17)
SE: standard error; CI: confidence intervals.
*p-value <0.05.
Linear and WQS regression models are both adjusted for maternal age, gestational age at which SARS-CoV-2 IgG titer was measured, COVID-19 vaccination status prior to IgG titer measurement, maternal race/ethnicity, parity, type of insurance and pre-pregnancy BMI.
We also examined the mixture effect of PFAS using a WQS regression model to account for simultaneous co-pollutant exposures. This model demonstrated that a quartile increase in the plasma PFAS mixture index is associated with reduced maternal IgG antibody titer (beta [95% CI] = −0.35 [−0.52, −0.17]) [Table 3]. Fig. 2 depicts the contribution of individual PFAS congeners to the overall mixture index, where PFHxA had the highest weight among all the other PFAS.Fig. 2 WQS regression model weights of each individual PFAS contributing to the overall co-pollutant mixture effect (Beta [95% CI] = −0.35 [-0.52, −0.17], p-value = 0.0003) in the index. The black dotted line shows the selection threshold (1/9). Adjusted for maternal age, gestational age at which SARS-CoV-2 IgG titer was measured, COVID-19 vaccination status prior to IgG titer measurement, maternal race/ethnicity, parity, type of insurance and pre-pregnancy BMI.
Fig. 2
4 Discussion
PFAS exposure-induced immunotoxicity has been documented for years within the literature in both animal and epidemiological studies (Gaballah et al., 2020; Granum et al., 2013; Shane et al., 2020; Stein et al., 2016; Timmermann et al., 2020). Most recently, studies in human populations have demonstrated that COVID-19 may be exacerbated by increasing levels of PFAS exposure (Catelan et al., 2021; Grandjean et al., 2020; Ji et al., 2021). Although these studies have elucidated a link between SARS-CoV-2 clinical severity and PFAS exposure, no study to date has investigated such an effect in a pregnant population. To our best knowledge, this is the first study to examine the relationship between maternal plasma-PFAS concentrations and SARS-CoV-2 spike IgG antibody titers in pregnant individuals. Since pregnancy is an immune-altered state, exposure to immune-altering toxicants (i.e., PFAS) may pose a greater threat during gestation.
The exposure levels of legacy PFAS in our study population are lower than the general US population in 2017–2018 as reported in the latest NHANES survey data (CDC Data Tracker, 2022). As per the ATSDR, blood-PFOA and -PFOS levels have declined by more than 70% and 85%, respectively, between 1999 and 2018. This may be attributed to the EPA PFOA Stewardship Program to promote voluntary industrial phase-out of legacy PFAS (2010/15 PFOA Stewardship Program: Guidance on Reporting Emissions and Product Content 2006; Kato et al., 2011). However, manufacturers have replaced long-chain with short-chain PFAS (i.e., GenX, PFBS), and there is a concurrent rise in exposure to these new-age PFAS congeners of which toxicity is less known (Calafat et al., 2019; Hu et al., 2019; Kato et al., 2011). Hu et al., reported in 2019 that tap water samples collected from 1989 to 1990 from a nationwide prospective cohort of US women found legacy PFAS, PFOA, n-PFOS, Sm-PFOS, PFHxS as well as emerging PFAS (i.e., PFNA) were significant predictors of plasma PFAS concentrations (Hu et al., 2019). In our study population, we have similarly observed higher levels of emerging PFAS in maternal plasma when compared to historical NHANES levels.
The analytical panel of nine PFAS congeners (n-PFOA, PFHxS, PFHpS, PFHxA, PFNA, n-PFOS, PFUnDA, PFBS, PFDA) measured in our study population demonstrate negative associations with SARS-CoV-2 IgG levels. This finding is in line with multiple previous studies that have found inverse associations between PFAS exposure and IgG antibody level in other infectious diseases (Abraham et al., 2020; Goudarzi et al., 2017; Liu et al., 2020; Looker et al., 2014; Timmermann et al., 2020) and implicates PFAS as immunomodulators and immunosuppressants. The results of our linear regression models also demonstrate similar findings for four PFAS congeners, n-PFOA, PFHxS, PFHpS and PFHxA; notably three of them are short-chain PFAS that can also impact immune responses. Timmermann et al., reported that elevated PFAS serum concentration were associated with decrements in measles antibody concentrations and higher morbidity, and that a doubling of both serum-PFOS and serum-PFDA was associated with lower measles antibody concentrations in children who received a measles vaccine (Timmermann et al., 2020). Immunosuppressive effects of prenatal exposure to PFOS and PFHxS were associated with increased childhood infections (Goudarzi et al., 2017). It is also important to point out that innate immune responses following natural infection are also attenuated by PFAS exposure and associated with a higher burden of persistent infections (Bulka et al., 2021). Both legacy and emerging PFAS demonstrated immunotoxicity in these studies.
Of note, our WQS regression model reveals that PFHxA contributes most to the overall mixture effect, which is also significantly associated with lower maternal SARS-CoV-2 IgG antibody titers. PFHpS, PFHxS and PFOS are lesser contributors to the mixture effect. Within the literature, the three PFAS identified in our WQS model have been found to potentially impact a myriad of health parameters. Liu et al., found that PFHxS and PFHxA perturb human mesenchymal stem cells and adipogenic differentiation (Liu et al., 2020). PFHxS has been associated with immunosuppression in childhood (Goudarzi et al., 2017) and correlated with thyroid autoantibodies in cases of congenital hypothyroidism (Kim et al., 2016). Low-dose PFHxS exposure was also found to be associated with higher prospective odds of actual infertility (Vélez et al., 2015). PFHxA is a persistent short-chain fluorinated organic compound in the environment making dietary exposure a concern due to its accumulation in fruits and vegetables (Felizeter et al., 2012, 2014; Krippner et al., 2014). Only two epidemiologic studies report significant associations with serum PFHxA, one found an inverse association with testosterone levels in teenage boys (Zhou et al., 2016) and a positive association with biomarkers of thyroid autoimmune disease in a Chinese population (Li et al., 2017). Our results and the aforementioned studies suggest that the emerging PFAS can play a varied role in health outcomes and should be investigated further, especially when considering the multifaceted physiological influence of the immune system.
Because the current study population consists of Gen C participants recruited early in the pandemic (April 2020–March 2021) only seven of our participants had received one dose of the vaccine prior to blood collection. While we adjusted for vaccine status in our statistical models, we also performed sensitivity analysis by excluding these seven individuals and observed no significant differences [Supplementary Table 2 and Supplementary Fig. 2]. PFAS have been detected in cord blood serum as well as breast milk, indicating they are transferred from mother to fetus (Chen et al., 2017; Mamsen et al., 2019; Needham et al., 2011; Sunderland et al., 2019; Wang et al., 2019). Prior cohort studies of the Faroese fishery population, where dietary PFAS exposure is higher than other populations (Grandjean et al., 2017a, 2017b, 2012; Eriksson et al., 2013) have found that antibody titers to routine childhood vaccines (i.e., tetanus, diphtheria, measles) fell below the clinical level of protection during childhood in association with higher PFAS exposure, and these effects persisted into adolescence despite booster shot administration (Grandjean et al., 2017b). We plan to investigate the effects of PFAS exposure on COVID-19 vaccine efficacy in our full cohort where the power is sufficient.
We acknowledge some notable limitations in this study. First, this is a small study of only 72 individuals, thus the power of the study is limited and the interpretation of our study results warrants caution until it can be validated in a larger population. However, our results are in line with the literature indicating PFAS-related immunotoxicity and also reflect the increasing exposure to short-chain PFAS. Second, the timing of maternal infection during pregnancy was difficult to precisely deduce given the nature of early pandemic quarantining, testing availability and the ambiguity of infection symptoms. Though we could not precisely pinpoint the amount of time elapsed between infection or vaccination and the collection of the plasma sample for IgG titer measurements, we would expect that this interval would be randomly distributed over the time-course of IgG levels. This would be more likely to drive the PFAS-IgG association towards the null given that IgG levels rise sharply within days after infection, reaching peaks in two weeks before waning (Ruggero, 2021). Third, plasma-PFAS and IgG were measured cross-sectionally and may not precisely depict PFAS exposure at the time of infection. However, PFAS are generally stable within the human body, with half-lives ranging typically between 3 and 5 years (Olsen et al., 2007). Lastly, some potential confounders (i.e., breastfeeding history, socioeconomic status) were incomplete within this population and were therefore not accounted for in our analyses. However, we did include other covariates such as parity and the type of insurance as proxy measures to account for potential confounding.
5 Conclusion
This pilot study is the first to demonstrate that maternal PFAS exposure may negatively impact maternal SARS-CoV-2 IgG antibody titers following SARS-CoV-2 infection during pregnancy. This study adds to the weight-of-evidence that PFAS, including the short-chain “emerging” congeners, are immunotoxic. Whether such an exposure may influence disease progression/severity for the mother or antibody transfer in utero upon infection leading to an immunomodulatory impact on the offspring warrants further investigation.
Credit author statement
K.K. and J.C. were involved in study conceptualization. K.K., J.C., A.S.R. and S.S.A. were involved in funding acquisition and methodology. S.S.A., S.N. and D.P. were involved in performing experiments. Formal data analyses were carried out by K.K., C.L. and V.M. For the Gen C population, E.I., F.G., M.L. were involved in data curation. T.J., W.L., L.D.D.W., V.B., A.S.R. and J.C. were involved in supervising the Gen C study. K.K. was responsible for manuscript original writing and preparation with support from L.C. and J.C. Manuscript critical review and editing was done by J.C., C.L., T.J., S.S.A. and A.S.R. All authors read and approved of the final manuscript.
Funding
This project was partially supported by the CDC (BAA 75D30120C08186) for the Gen C study. The NIEHS Human Health Exposure Analysis Resource (HHEAR) NIH 2U2CES026561 funded the PFAS measurements, which were carried out within the Senator Frank R. Lautenberg Environmental Health Sciences Laboratory at the Icahn School of Medicine at Mount Sinai. The NIEHS T32HD049311 funded K. Kaur.
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.
Appendix A Supplementary data
The following is the Supplementary data to this article:Multimedia component 1
Multimedia component 1
Data availability
Data will be made available on request.
Acknowledgements
The authors thank the Gen C team, especially Sophie Orn, for collecting and processing biospecimens; Dr. Florian Krammer and his laboratory members for the COVID-19 antibody assay and results; the Chen lab members for their lab support and data feedback (Drs. James Wetmur, Hachem Saddiki and Qian Li); the HHEARS's program manager; Tracy Spangler for assisting in the application process; and the CDC's COVID-19 response and epidemiology task force and Pregnancy and Infant Linked Outcomes Team (PILOT).
Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.envres.2022.115067.
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| 0 | PMC9747685 | NO-CC CODE | 2022-12-16 23:21:33 | no | Environ Res. 2023 Feb 15; 219:115067 | utf-8 | Environ Res | 2,022 | 10.1016/j.envres.2022.115067 | oa_other |
==== Front
Int J Biol Macromol
Int J Biol Macromol
International Journal of Biological Macromolecules
0141-8130
1879-0003
Published by Elsevier B.V.
S0141-8130(22)03022-7
10.1016/j.ijbiomac.2022.12.120
Article
Human antibody BD-218 has broad neutralizing activity against concerning variants of SARS-CoV-2
Wang Bo a1
Xu Hua a1
Liang Zi-teng b1
Zhao Tian-ning a
Zhang Xin a
Peng Tian-bo a
Wang You-chun b
Su Xiao-dong a⁎
a State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China
b Division of HIV/AIDS and Sex-transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC), WHO Collaborating Center for Standardization and Evaluation of Biologicals, Beijing, China
⁎ Corresponding author.
1 These authors contributed equally: Bo Wang, Hua Xu, Zi-teng Liang.
14 12 2022
14 12 2022
27 8 2022
10 12 2022
12 12 2022
© 2022 Published by Elsevier B.V.
2022
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As SARS-CoV-2 variants of concern (VOC) reduce the effectiveness of existing anti-COVID therapeutics, it is increasingly critical to identify highly potent neutralizing antibodies (nAbs) that bind to conserved regions across multiple variants, especially beta, delta, and omicron variants. Using single-cell sequencing with biochemical methods and pseudo-typed virus neutralization experiments, here we report the characterization of a potent nAb BD-218, identified from an early screen of patients recovering from the original virus. We have determined the cryo-EM structure of the BD-218/spike protein complex to define its epitope in detail, which revealed that BD-218 interacts with a novel epitope on the receptor-binding domain (RBD) of the spike protein. We concluded that BD-218 is a highly effective and broadly active nAb against SARS-CoV-2 variants with promising potential for therapeutic development.
Keywords
SARS-CoV-2
Neutralizing antibody
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pmc1 Introduction
The ongoing COVID-19 pandemic caused by SARS-CoV-2 has been spreading globally [1] for almost three years, leading to the emergence of different virus mutants over time. Emerging SARS-CoV-2 variants of concern (VOCs) have developed resistance to neutralizing antibodies, including some clinical antibodies that are used as therapeutics. Mutations on the receptor-binding domain (RBD) of the spike protein have likely led to increased transmissibility and a partial escape from humoral immunity induced by vaccines made from the original strain of SARS-CoV-2 [2], [3], [4]. The most widely circulating omicron variant has 15 mutations of the RBD [5], [6], in particular, L452 substitutions have led to omicron sublineages with higher transmission advantage over previously-emerged variants [7]. Although three to four doses of vaccines have been reported to be limited effective on delta and omicron variants [8], [9], [10], controlling this pandemic has been remaining a critical issue.
To restrict the further spread of variants and hospitalization rate, efforts to improve vaccine effectiveness—such as maximizing vaccine uptake with at least three doses [11] and improving vaccine design should continue. Alongside these efforts, effective therapeutics against severe disease namely, SARS-CoV-2 nAbs, which have shown promising therapeutic efficacy for COVID-19 patients should continue to be developed. With the emergence of increasingly transmissible variants, like delta and omicron variants [7], the need for continued screening and characterization of more nAbs has correspondingly increased. Research into nAbs will aid in the development of broad vaccine design against concerning variants; furthermore, the lessons learned from SARS-CoV-2 can also be applied to the fight against other emerging, infectious pathogens.
Here, we have characterized a series of potent nAbs in detail from previously recovered COVID-19 patients [12], [13], one of which is BD-218. Surface plasmon resonance (SPR) experiments showed strong affinities between BD-218 and the RBDs of several circulating variants. Moreover, we identified that BD-218 could efficiently neutralize pseudo-typed viruses with different circulated and circulating mutations. We further investigated the mechanism by which BD-218 targets the circulating variants' RBDs by solving their cryo-EM complex structure and comparing it with nine antibody-based drugs or reported potent antibodies. Together, our results demonstrated that BD-218 recognizes a novel and robust epitope within concerning variants and has strong potential as a broad-spectrum nAb drug to treat COVID-19.
2 Materials and methods
2.1 Protein expression and purification
The spike protein (S-6P: S-HexaPro) expression construct was obtained from Dr. Junyu Xiao's lab; it encodes the spike ectodomain (residues 1–1208) with six stabilizing Pro substitutions (F817P, A892P, A899P, A942P, K986P, and V987P) and a ‘GSAS’ substitution at the furin cleavage site (residues 682–685), as previously described [13]. The S-6P plasmid was transfected into HEK293F cells at a cell density of 106 cells/mL and expressed for four days. The S-6P protein was purified using the Ni-NTA resin followed by the Superose 6 Increase 10/300 gel filtration column (Cytiva, Marlborough, MA, USA), and eluted using the final buffer containing 25 mM Tris (pH 8.0) and 150 mM NaCl.
The BD-218 Fab heavy chain and light chain sequences were cloned into pcDNA3.1 plasmids with a signal peptide and C-terminal His6-tag. Plasmids with the heavy chain and light chain were mixed at a 1:1 ratio and transfected into HEK293F cells using polythylenimine. After incubation for four days, the conditioned media were collected, concentrated, and exchanged into the binding buffer containing 25 mM Tris (pH 8.0) and 150 mM NaCl. The BD-218 Fab was then purified using the Ni-NTA resin and Superdex 200 Increase column (Cytiva).
2.2 Cryo-EM sample preparation and data collection
Holey‑carbon gold grids (Quantifoil, R1.2/1.3) were glow-discharged for 45 s using a Solarus 950 Plasma Cleaner (Gatan Inc., Berwyn, PA, USA) with a 4:1 O2/H2 ratio. We sufficiently mixed 4 μL S-6P (~0.2 mg/mL) and 0.5 μL BD-218 Fab (1.2 mg/mL) at room temperature, and then quickly applied the mixture onto the glow-discharged grids. The grids were then blotted with filter paper (Whatman No. 1) at 4 °C and 100 % humidity and injected onto liquid ethane using a Vitrobot Mark IV System (Thermo Fisher Scientific, Inc., Waltham, MA, USA). The grids were first screened using a 200 kV Talos Arctica transmission electron microscope equipped with a Ceta camera (Thermo Fisher Scientific, Inc.). Data collection was carried out using a Titan Krios electron microscope (Thermo Fisher Scientific, Inc.) operated at 300 kV. Movies were recorded on a K2 Summit direct electron detector (Gatan Inc.) using SerialEM software [14], in the super-resolution mode at a nominal magnification of 130,000 and an exposure rate of 7.125 e−/Å2/s. The defocus range was set from −0.7 to −1.5 μm. The micrographs were dose-fractioned into 32 frames with a total exposure time of 8 s and a total electron exposure of 57 e−/Å2.
2.3 Cryo-EM data processing
The workflow of data processing is shown in Supplementary Fig. S1. Motion correction with 4633 stacks was carried out using MotionCor2 [15], and all movies were binned 2-fold, resulting in a pixel size of 1.055 Å/pixel. The defocus values were estimated with the Gctf program [16]. A total of 417,369 particles were auto-picked using the AutoPick node in Relion 3.1, with the EMD-30374 map as a reference [17], and then subjected to 2D classification without symmetry restriction, which yielded 297,084 good particles. The good particles were selected and subjected to heterogeneous refinement using cryoSPARC [18]. The good particles were further selected and subjected to non-uniform without symmetry, resulting in a three-dimensional reconstruction of the whole structure and a map with an average resolution of 3.74 Å. To improve the map quality for the interface between the S-6P protein of SARS-CoV-2 and BD-218, the dataset was subject to focused refinement with an adapted mask on the region of the RBD/BD-218 sub-complex. Finally, the dataset was re-centered on the interface between RBD and BD-218, resulting in a local refinement map with an average resolution of 4.01 Å. The resolution was estimated with the gold-standard Fourier shell correlation 0.143 criteria [19] with high resolution noise substitution.
2.4 Model building and structure refinement
For structure building of the S-6P protein with BD-218, an initial model was first obtained from the PDB as a template (PDB ID: 6xm4). The template was flexibly fitted into the whole cryo-EM map of the complex using UCSF Chimera [20]. Additionally, a Fab model and an RBD model, generated as templates from our previous work, were docked into the local refined map. Finally, all coordinates were merged with the S-6P protein and further manually adjusted using Coot [21]. Each residue of the complex was manually checked, and real space refinement was performed in Phenix [22]. Statistics associated with data collection, 3D reconstruction, and model building are summarized in Supplementary Table S1.
2.5 Surface plasmon resonance
A Biacore T200 (Cytiva) was used to measure and compare the dissociation coefficients between antibodies and the RBD of SARS-CoV-2 and its mutants. Fabs of BD-218 were captured to 200–300 RU on a Series S Sensor Chip CM5 (Cytiva). Next, serial 2-fold dilutions of SARS-CoV-2 RBD and mutants were injected, with concentrations from 20 to 0.63 nM. All proteins were exchanged into running buffer containing 10 mM HEPES (pH 7.4), 150 mM NaCl, 3 mM EDTA, and 0.005 % (v/v) P20. The final data were processed using the Biacore Evaluation Software and fitted to a 1:1 binding model.
2.6 Pseudo-typed virus neutralization assay
The pseudo-typed virus neutralization assays were performed using Huh-7 cell lines. Pseudo-typed viruses were prepared as previously described [12]. Various concentrations of antibodies (3-fold serial dilution using DMEM) were mixed with the same volume of SARS-CoV-2 pseudo-typed virus in a 96-well plate. The mixture was incubated for 1 h at 37 °C and supplied with 5 % CO2. Pre-mixed Huh-7 cells were added to all wells and incubated for 24 h at 37 °C and supplied with 5 % CO2. After incubation, the supernatants were removed, and D-Luciferin reagent (Invitrogen, Waltham, MA, USA) was added to each well; luciferase activity was measured using an EnSight microplate spectrophotometer (PerkinElmer, Waltham, MA, USA). The inhibition rate was calculated by comparing the OD value to the negative and positive control wells. The EC50 values were determined with a four-parameter logistic regression using Origin (OriginLab).
3 Results
3.1 BD-218 strongly binds to RBDs and potently neutralizes spike proteins of concerning variants
The third complementarity-determining region of the heavy chain (CDR-H3) of BD-218 is encoded by the VH4–34 lineage gene, which is an essential germline gene in humans [23]. Sequence alignment analysis reveals that BD-218 is not conserved with other previously reported high-efficiency nAbs or antibody-based drugs against SARS-CoV-2 (Fig. 1A,B). The non-conserved sequence of BD-218 may lead to a different epitope on the RBD. As we previously reported, BD-218 was a high-efficiency antibody against the wildtype of SARS-CoV-2 (Cao et al., 2020). To evaluate BD-218's activity against global variants of concern, such as the alpha, beta, delta, and other variants [24], SPR experiments were carried out to measure the binding affinity between BD-218 and these major variants. As expected, BD-218 binds to the RBD of variants with high affinity; we observed a very small KD value of 0.16 nM with the delta variant, which was similar to those observed with the wildtype, gamma, and kappa variants (Fig. 1C). Additionally, to evaluate the capacity of BD-218 to neutralize lentiviral particles pseudo-typed with several variants' spike proteins, we performed neutralization assays with pseudo-virus expressing wildtype, and several other variants of concern. Consistent with SPR results, the BD-218 displayed significant potency against the delta spike-based pseudo-virus (EC50 of 0.145 μg/mL), as well as the wildtype, gamma, and kappa variants (Fig. 1D). Furthermore, the latest omicron sublineages pseudo-typed viruses were also used to detect the neutralization activity of BD-218. neutralization capacity of BD-218 against omicron variants decreased marginally but remained strong compared to most other nAbs in the pseudo-typed viral neutralization assay investigations (Fig. 1D). For example, BD-218 could neutralize the BA.5, the most widely circulating omicron sublineage in the world. Moreover, BD-218 can also provide neutralizing activity to the BF.7 starin, which is widespreading in China. Although BD-218 cannot neutralize omicron sublineage XBB, it might be used with other highly active nAbs to offer higher and more general neutralizing activity.Fig. 1 BD-218 strongly binds to receptor binding domains (RBDs) and potently neutralizes spike proteins of major SARS-CoV-2 variants. A and B. Sequence alignment of heavy chain and light chain CDR regions within BD-218, DXP-604, LY-CoV555, LY-CoV016, REGN-10933, REGN-10987, AZD-8895, AZD-1061, VIR-7831, and BD-368-2. C. Surface plasmon resonance sensorgrams of neutralizing antibodies binding to the RBD of wildtype, gamma, delta, delta plus, and kappa variants. All analyses were performed using serial two-fold dilutions of purified RBDs as the analyte, starting from 20 nM to 0.625 nM. D. Neutralization potency of BD-218 on wildtype, gamma, delta, kappa and some circulated and circulating omicron sublineage of SARS-CoV-2 pseudo-typed virus. The yellow color indicates the neutralization activity fell slightly, and the red color indicates the neutralization activity decreased significantly. Data were obtained from a representative neutralization experiment, which contains three replicates. Data are represented as mean ± SD. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 1
3.2 The structural binding mechanism of BD-218 neutralizes concerning variants efficiently
To investigate the molecular mechanism by which BD-218 neutralizes SARS-CoV-2, we determined the complex structure of the nAb BD-218 Fab form with the S-HexaPro (S-6P) protein of SARS-CoV-2 using the single particle method, at an overall resolution of 3.74 Å (Fig. 2A, Supplementary Fig. S1, and Supplementary Table S1). The spike protein exhibited an asymmetric conformation, consistent with previous observations [13], [25], with one RBD in an ‘up’ conformation bound to BD-218, and two RBDs in a ‘down’ conformation in the complex structure (Fig. 2A). This complex structure suggests that the binding of a single BD-218 to the RBD in the ‘up’ state prevents this ‘up’ RBD from binding to ACE2. Together, our data have shown that BD-218 retains broad neutralization activity against concerning variants.Fig. 2 Structural basis of BD-218 bound to spike protein. A. Cryo-EM structure of the S-6P trimer in complex with BD-218 Fab reconstructed at 3.74 Å. The three RBDs are highlighted as follows: ‘up’ in orange and ‘down’ in green and purple-blue. The fragment variable (Fv) region of BD-218 is shown in grey (light chain) and salmon pink (heavy chain).. B. Schematic of BD-218 bound to SARS-CoV-2 spike protein., including the interaction between BD-218 Fab and the RBD is shown. BD-218 is shown in the cartoon, whereas RBD is shown in the spheres view. Main regions in BD-218 that interact with RBD are highlighted using thicker ribbons. C. Interactions between CDRH1, CDRH2, and RBD. A dashed line indicates major interactions. D. Interactions between CDRL3 and RBD. E. Schematic shows the two hydrophobic cores on RBD that are recognized by BD-218. The red color indicates hydrophobic surface, and the white color indicates hydrophilic surface. F. Superimposition of the structure of RBD in the S-6P/BD-218 complex and the RBD/ACE2 complex (PDB: 6m0j). BD-218 would inhibit ACE2 binding to the RBD via VH. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 2
BD-218's broad neutralization activity indicates that the antibody recognizes a conserved region in the RBD of the different variants. To find out the structural basis of the BD-218/RBD binding interface in detail, we used local refinement to account for the conformational dynamics of BD-218 relative to the RBD and obtained a cryo-EM reconstruction of this binding interface with 4.01 Å resolution (Fig. 2B-D). BD-218 recognizes an epitope towards the center of the spike protein trimer, which sterically hinders BD-218 from binding to the ‘down’ RBDs by the adjacent protomer (Fig. 2B).
We have adopted the RBD nomenclature defined by Dejnirattsai et al. [26], in which the antibody-binding sites of the RBD were divided into six groups: left shoulder, neck, right shoulder, left flank, chest, and right flank. BD-218 binds to the neck of the RBD. The epitope of BD-218 overlaps with the ACE2 binding sites on the RBD to a large extent (Figs. 2C,D and 3A). Consistent with our neutralization assay analyses, BD-218 can competitively inhibit the ‘up’ RBD conformation from binding to ACE2. Three regions in BD-218 are primarily involved in interacting with the RBD: heavy chains CDRH1 and CDRH2, and light chain CDRL3 (Fig. 2B). Among the prominent interactions, D31 on CDRH1 forms hydrogen bonds with Y453 of RBD, D50 of CDRH2 contacts Y489 on RBD, and S92 of CDRL3 interacts with S477 of RBD via its hydroxy group (Fig. 2C and D). The aromatic residues of the RBD are particularly crucial for the recognition between BD-218 and RBD. The aromatic groups of Y505 and Y453 are recognized by CDRH1, and the aromatic group of Y489 is involved in the interaction with CDRH2 (Fig. 2C). BD-218 recognizes two hydrophobic cores on the RBD, which are formed by the hydrophobic residues mentioned above via hydrophobic interactions (Fig. 2E). Furthermore, a structural superimposition of the S-6P/BD-218 and RBD/ACE2 complexes reveals a notable clash between the variable domain on the heavy chain (VH) of the BD-218 Fab and ACE2 (Fig. 2F). Additionally, we noted substitutions on the RBD that are likely to lead to viral immune system evasion, such as L452R and E484K. The L452R substitution leads to increased transmissibility in the majority of omicron lineages; it breaks down the hydrophobic core of the RBD, which disrupts the hydrophobic interaction between antibodies and the RBD. The E484K substitution breaks the salt bridge interaction between antibodies and the RBD. However, BD-218 recognizes the RBD independently of L452 and E484; therefore, the neutralization capacity of BD-218 is not affected by the concerning variants with these substitutions. The complex structure reveals the epitope of BD-218 and provides further atomic insights into the critical interactions between BD-218 and the RBD.Fig. 3 The conserved epitope of BD-218 compared to other potent neutralizing antibodies. A. Multiple sequence alignment showing the epitope footprints of BD-218 and other antibody drugs on the SARS-CoV-2 RBD highlighted in dark cyan. Red circle below the alignment indicates hACE2 contact residues on the SARS-CoV-2 RBD. Yellow inverted triangles indicate mutated sites on the RBD that have been reported in concerning variants. B. Combinations of BD-218 with REGN-10987, AZD1061, VIR7831, and BD-368-2, respectively, without spatial overlaps. BD-218 is shown in red cartoon and RBD is shown in orange surface form. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 3
3.3 BD-218 has potent neutralization capability due to its recognition of a novel epitope compared with other high-efficiency nAbs
The cryo-EM structure of BD-218 with the spike protein reveals several conserved residues among the concerning variants as compared with previously reported high-efficiency nAbs and commercial antibodies. The main binding site of BD-218 consists of Y453, L455, F456, F486, N487, and Y489 (Fig. 3A); these residues are also recognized by many other potent nAbs, as well as ACE2 (Fig. 3A). These residues constitute a conserved recognition site and play a major role in the recognition of the RBD by BD-218 through hydrogen bonding and hydrophobic interactions. It is worth noting that, unlike other potent nAbs or commercial antibodies, BD-218 did not recognize the reported substituted residues on the RBD in different variants, including the omicron variant. Consequently, different reported mutations of concerning variants have minor impacts on the binding activity of BD-218 to the RBD, and the conserved amino acids contribute to a robust neutralization capability of BD-218.
In addition to the conserved recognition site, a novel amino acid combination contributes to the BD-218's potent binding activity. Unlike many other reported nAbs, BD-218 relies not only on the heavy chain to recognize the RBD but also on the light chain to provide a larger junction area. Y453 and C488 were recognized by the heavy chain of BD-218, while T478 was bound by the light chain of BD-218. The combination of these three amino acids has rarely been reported (Fig. 3A), and provides multiple hydrogen bond interactions with the antibody, causing BD-218 to bind a different location relative to reported nAbs. Furthermore, the conserved F486 and Y489 residues offer strong hydrophobic interactions with BD-218 (Figs. 2C,E and 3A). Combined, this novel combination and conserved recognition site demonstrate a potent neutralization activity for BD-218.
We defined the novel epitope of BD-218 through further structural analysis. The BD-218 recognition site is very similar to REGN-10933, which is an antibody-drug that has received emergency use authorization (EUA) from the FDA. Both antibodies primarily recognize Y453, L455, F456, F486, N487, and Y489. Like REGN-10933, this conserved epitope allows BD-218 to strengthen its neutralizing activity by pairing with other potent neutralizing antibodies. Therefore, we carried out structure superimpositions, which indicated that BD-218 could pair with REGN-10987, AZD1061, VIR7831, and BD-368-2, without steric hindrance (Fig. 3B).
4 Conclusion and discussion
We have characterized BD-218, obtained from screenings of recovered COVID-19 patients, as a potent nAb with broad activity against concerning variants of SARS-CoV-2. Structural analysis and biochemistry experiments demonstrated that BD-218 could block the ‘up’ RBD conformation, thereby exerting a potent neutralization effect, thus offering its potential use as an antibody-drug against currently circulating and other emerging SARS-CoV-2 variants.
An ideal anti-SARS-CoV-2 antibody would be resistant to viral escape, and highly protective through viral neutralization and antibody effector functions. Potent nAbs against SARS-CoV-2 were identified from recovered patients [12], [13], [27], [28], [29]. Among these previously screened antibodies, BD-218 performs effectively to neutralize the RBD of wildtype and major variants, including the widespread omicron variants [5], [6], [12], [30]. Most highly potent neutralizing antibodies recognize and bind to the left shoulder and neck of the RBD, which is also the ACE2 binding site [31], [32]; however, the high-frequency substitutions L452R and E484K that occur in many variants are also located on the neck and left shoulder. Therefore, concerning variants are likely to reduce the neutralizing activity of nAbs that recognize the neck and left shoulder of the RBD. Alternatively, BD-218 recognizes a different part of the neck and shoulder on the back of the RBD (Fig. 2A); since this recognition site is dominated by Y453, T478, and C488, the epitope of BD-218 involves neither L452 nor E484. Consequently, antibodies that bind to the neck position on the back of the RBD will not be affected by variants, in contrast to some VH3-53/66 germline-encoded antibodies. Although BD-218 is unable to neutralize a few omicron sublineages such as XBB, it might be paired with other highly active nAbs to offer higher and more general neutralizing efficacy.
BD-218 and some potent nAbs against SARS-CoV-2 recognize a conserved site of the RBD. There was no residue substitution and deletion reported on the conserved site, even in the omicron variant (Fig. 3A). Subsequently, antibodies like BD-218 that recognize these residues could provide potent neutralizing activity against concerning variants of SARS-CoV-2. Furthermore, this conserved site could also guide vaccine design and optimization. Robust vaccines could be developed based on the sequence and structure of the conserved epitope, which could result in increased circulation of nAbs like BD-218 that recognize this conserved site.
Data and materials availability
The cryo-EM structure of the BD-218 Fab complex with S-6P has been deposited in the PDB with accession code 8GNH, and its map was deposited in the EMDB with accession code EMD-34164.
CRediT authorship contribution statement
Bo Wang: Data curation, Methodology, Formal analysis, Writing – original draft. Hua Xu: Data curation, Methodology, Formal analysis. Zi-teng Liang: Validation, Investigation. Tian-ning Zhao: Validation, Investigation. Tian-bo Peng: Data curation. You-chun Wang: Conceptualization. Xiao-dong Su: Conceptualization, Funding acquisition, 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.
Appendix A Supplementary data
Supplementary material
Image 1
Data availability
Data will be made available on request.
Acknowledgments
We would like to thank the National Center for Protein Sciences at Peking University in Beijing, China, for assistance with SPR assays. We thank the cryo-EM platform of Peking University for help with data collection. This project was supported by the 10.13039/501100012166 National Key Research and Development Program of China (2021YFC2301301 to X.D.S, and 2021YFC2301402 to X.D.S), the 10.13039/100007225 Ministry of Science and Technology of China (2020YFC0848700), and the Qidong-SLS Innovation Fund (Both to X.D.S). Special thanks to Drs. Xiaoliang Xie, Junyu Xiao, and Yunlong Cao, for providing plasmid and IgG samples of the antibodies.
Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.ijbiomac.2022.12.120.
==== Refs
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| 0 | PMC9747686 | NO-CC CODE | 2022-12-15 23:22:03 | no | Int J Biol Macromol. 2022 Dec 14; doi: 10.1016/j.ijbiomac.2022.12.120 | utf-8 | Int J Biol Macromol | 2,022 | 10.1016/j.ijbiomac.2022.12.120 | oa_other |
==== Front
Disabil Health J
Disabil Health J
Disability and Health Journal
1936-6574
1876-7583
Elsevier Inc.
S1936-6574(22)00192-3
10.1016/j.dhjo.2022.101429
101429
Original Article
How Has COVID-19 Impacted Disability Employment?
Ne’eman Ari ab∗
Maestas Nicole PhD cd
a PhD Program in Health Policy, Harvard Graduate School of Arts & Sciences, Cambridge, MA, USA
b Lurie Institute for Disability Policy, Brandeis University, Waltham, MA, USA
c Department of Health Care Policy, Harvard Medical School, Harvard University, Boston, MA
d National Bureau of Economic Research, Cambridge, MA
∗ Corresponding Author: 24 Marshall St. Somerville, MA 02145 732.763.5530
14 12 2022
14 12 2022
10142929 7 2022
6 12 2022
7 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
While the COVID-19 public health emergency has had disastrous health impacts for people with disabilities, it remains unclear what impact the associated economic recession and subsequent recovery have had on disability employment.
Objective
We evaluated employment trends for people with and without disabilities over the course of the COVID-19 recession and subsequent economic recovery, both overall and by occupational category (essential, non-essential, teleworkable, non-teleworkable, frontline, non-frontline).
Methods
We made use of data from the nationally representative Current Population Survey. Linear probability models were used to estimate percent changes in employment-to-population ratios and identify differences between disabled and non-disabled employment in each quarter broadly and within specific occupational categories.
Results
As the COVID-19 recession began in Q2 2020, people with disabilities experienced employment losses that were proportionately similar to those experienced by people without disabilities. However, during the subsequent economic recovery, the employment rate of people with disabilities grew more quickly in Q4 2021 through Q2 2022, driven by increased labor force participation. These employment gains have been concentrated in teleworkable, essential, and non-frontline occupations.
Conclusion
Our findings suggest that people with disabilities are disproportionately benefiting from the rapid recovery from the initial economic contraction at the start of the pandemic.
Key Words
COVID-19
Economic Inclusion
Disability Employment
Telework
==== Body
pmcIntroduction
The COVID-19 public health emergency has presented serious challenges for people with disabilities (PWD). While the health impacts of COVID-19 have been negative, it remains unclear how the pandemic has impacted disability employment.1 , 2 There are strong arguments for both positive and negative effects. Like other marginalized groups, PWD experience employment discrimination, placing them at greater risk of job loss during recessions.3 PWD in frontline jobs may have chosen to quit to protect their health. At the same time, PWD have long been more likely to work from home, and therefore the pandemic-induced shift to telework may have created new employment opportunities by making it easier for people with disabilities to telework.4 In addition, tightening labor markets during the economic recovery may have contributed to employment gains for PWD. Recent labor market trends have important implications for the health and welfare of PWD. Prior work has documented that employment is associated with improved health outcomes, both for PWD and the general public.5 , 6
Analyses of previous recessions find that PWD are at greater risk of job loss during periods of economic contraction.7 , 8 During the Great Recession (2007-2009), PWD experienced a much greater decline in employment9 and greater underemployment.10 The Great Recession also induced large numbers of SSDI applications and awards that would not otherwise have been filed.11 Prior work has found that PWD had a longer recovery from the Great Recession than their non-disabled counterparts.12
Houtenville, Paul, and Brucker (2021) documented comparable percentage decreases in employment for people with and without disabilities from February 2020 to April 2020, the crucial early months of the pandemic during which most job losses took place and the economic recession occurred.13 In contrast, Schur, Rodgers, and Kruse (2021) found that PWD experienced worse employment losses than non-disabled people over the course of 2020, although PWD with college degrees had recovered and even exceeded pre-COVID-19 employment levels by year’s end.12 As these studies focused on the initial months of the COVID-19 pandemic, little is understood about the trajectory of disability employment in subsequent years.
Just as overall labor market trends may mask considerable heterogeneity by disability status (i.e., people with and without disabilities), they also fail to capture heterogeneity by occupational type in particular occupational categories likely to be differentially impacted by the pandemic, such as essential and frontline workers or workers in teleworkable professions. Analyses early in the pandemic indicated that drops in employment were more severe in occupations not conducive to telework.14 Subsequent analyses confirmed that workers in occupations suitable for telework were less likely to lose their jobs through at least the end of 2020.15 Making use of large-scale surveys, Barrero, Bloom, and Davis (2021) predicted that telework arrangements may quadruple (from 5 to 20 percent of full workdays) in the post-COVID-19 era.16 Though telework has long been highlighted by the Employment Equal Opportunity Commission (EEOC) as a potential reasonable accommodation for workers with disabilities, its availability in any given employment setting is dependent on both the nature of job requirements (which determine whether such an accommodation is “reasonable” and does not constitute an “undue burden” to employers) and employer compliance with disability rights law.17 At the same time, disabled workers may not reap the full benefit of the expansion in telework availability if they are concentrated in industries and occupations that are not conducive to it and lack the opportunity to shift into telework-friendly employment. Consistent with this concern, Kruse et al. (2018) documented that PWD were less likely than non-disabled people to telework during the early period of the COVID-19 recession, owing largely to occupational differences between disabled and non-disabled workers.18
In the several years preceding the COVID-19 recession, disability employment had begun rising—in both absolute and relative terms. This historic reversal of the decades-long decline in disability employment emerged following the recovery from the Great Recession. During prior recessions, the employment rate of disabled workers tended not to recover to pre-recession levels, reinforcing a long-term downward trend in employment.7 , 8 , 19
Given this context, it is important to evaluate whether workers with disabilities are benefiting from the rapid recovery from the COVID-19 recession to the same extent as workers without disabilities, recovering more rapidly, more slowly, or not recovering at all. Should the pre-Great Recession downward employment trend reassert itself in the aftermath of COVID-19, this would represent a step backwards for efforts to integrate PWD into the workforce. Alternatively, if employment for PWD is recovering at the same or greater rate as that of persons without disabilities, it might suggest the return of the upward employment trend documented prior to COVID-19. To explore these issues, we examined employment trends for PWD and non-disabled people during and after the COVID-19 recession making use of data from the Current Population Survey.
Methods
Data
The Current Population Survey (CPS) is a nationally representative survey of approximately 60,000 households conducted by the Bureau of Labor Statistics for the purpose of reporting monthly unemployment and labor force statistics. When households enter the CPS, they are surveyed for four consecutive months, not surveyed for the next eight months, and then surveyed again for four months before rotating out of the CPS. The CPS collects information on respondent disability status through the use of a standard six-question sequence inquiring about: a) hearing difficulty, b) vision difficulty, c) cognitive difficulty, d) ambulatory difficulty, e) self-care difficulty, and f) independent living difficulty. Respondents who report any of these difficulties are classified as disabled for the purposes of our analyses, consistent with their intended use and established norms for disability policy research. We use data from the CPS monthly files from July 2008 to June 2022, though our primary analyses begin in July 2012. Our time period of interest is the COVID-19 public health emergency, spanning from Q1 2020 to Q2 2022.
Outcome Variables
We collapse the individual-level data to the month- or quarter-level to calculate employment-to-population ratios separately for PWD and non-disabled people. This month-level data is used in our regressions; the quarter-level data is used in our plots. To calculate the employment-to-population ratio for each disability status group (PWD, non-disabled), the numerator is the number of employed and “at work” persons in the disability status group in a given month/quarter while the denominator is the total number of persons ages 18-64 in the disability status group in the same month/quarter. We make use of employed at work as our outcome in order to address a misclassification issue that BLS indicated resulted in furloughed workers inaccurately classified as employed but not at work (rather than unemployed on temporary layoff) in the first few months of the pandemic.20 We do this for the sample as a whole and by occupation type. The occupation types are teleworkable/non-teleworkable, essential/non-essential, and frontline/non-frontline. We classify occupations as essential or non-essential based on the Department of Homeland Security’s “Identifying Critical Infrastructure During COVID-19” guidelines.21 Our definition of teleworkable jobs comes from Dingel and Neiman (2020).22 Frontline jobs are those that are essential and not teleworkable.
Covariates
As we describe below, we incorporate demographic control variables in our regression analyses to account for baseline differences between persons with and without disabilities and to capture shifts over time in the demographic composition of people with and without disabilities arising from the pandemic. Since our data are structured at the monthly level, covariates are constructed as the percentage of people in each disability status group with a particular demographic characteristic in each month. Demographic characteristics are: age group (18-34, 35-49, and 50-64), sex, race/ethnicity (white, Black, Hispanic, or other), and educational attainment (no Bachelor’s degree or Bachelor’s degree).
Analyses
Focusing on the months surrounding the COVID-19 public health emergency, we set Q1 2019 as the reference quarter rather than Q1 2020 (the immediate pre-COVID-19 quarter). We do so for two reasons. First, Q1 2020 includes March 2020 when the pandemic began. Second, in Q1 2020 PWD in non-essential occupations experienced a sudden and anomalous increase in their employment-to-population ratio (equal to a 12.3% increase relative to Q1 2019, see Table 2 , col. 3). Since this sudden increase is an outlier relative to the pre-COVID-19 trend and likely represents sampling noise, making use of Q1 2020 as a reference quarter could yield a misleading estimate of the percentage change in disabled employment due to COVID-19 (in particular, overstating their employment loss during the early months of the pandemic). To address this, we make use of the same quarter one year earlier, which appears in line with the pre-COVID-19 trend. In Appendix B, we confirm that the use of Q1 2020 as a reference quarter would yield anomalous results relative to other specifications and show that our findings are robust to a broad range of reference quarters immediately preceding the COVID-19 pandemic.Table 2 Logged Employment Outcome: Coefficients for Disability x Quarter Interactions, By Occupational Category
Table 2 (1) (2) (3) (4) (5) (6) (7)
Employed Essential Non-Ess. Teleworkable Non-Tele. Frontline Non-Front.
Disabled -0.640*** -0.756*** -0.374 -1.233*** -0.217 -0.344 -0.900***
(0.208) (0.225) (0.284) (0.282) (0.277) (0.262) (0.256)
Disabled X Q1 2020 0.0302 -0.00919 0.123*** 0.0554** 0.00440 -0.0326 0.0886***
(0.0196) (0.0218) (0.0319) (0.0240) (0.0294) (0.0313) (0.0232)
Disabled X Q2 2020 -0.00226 -0.0346 0.0684 0.0562 -0.0419 -0.0799 0.0742
(0.0724) (0.0649) (0.102) (0.0617) (0.111) (0.0904) (0.0716)
Disabled X Q3 2020 -0.0437 -0.0448 -0.0469 0.0145 -0.0733 -0.0853 -0.00192
(0.0510) (0.0514) (0.0652) (0.0519) (0.0703) (0.0631) (0.0530)
Disabled X Q4 2020 -0.00244 -0.00215 -0.0121 0.0255 -0.0183 -0.0213 0.0196
(0.0254) (0.0309) (0.0427) (0.0480) (0.0380) (0.0441) (0.0412)
Disabled X Q1 2021 -0.00237 -0.0251 0.0486 0.0632 -0.0362 -0.0561 0.0524
(0.0413) (0.0403) (0.0608) (0.0510) (0.0584) (0.0520) (0.0498)
Disabled X Q2 2021 0.00570 -0.0112 0.0456 0.0789** -0.0322 -0.0396 0.0512
(0.0326) (0.0343) (0.0486) (0.0345) (0.0480) (0.0444) (0.0330)
Disabled X Q3 2021 0.0545 0.0699 0.0180 0.130** 0.00392 0.0239 0.0821
(0.0497) (0.0509) (0.0603) (0.0559) (0.0609) (0.0532) (0.0548)
Disabled X Q4 2021 0.0933** 0.0885** 0.103* 0.181*** 0.0399 0.0201 0.161***
(0.0380) (0.0378) (0.0556) (0.0408) (0.0570) (0.0534) (0.0436)
Disabled X Q1 2022 0.0969** 0.106** 0.0743 0.215*** 0.0212 -0.00696 0.190***
(0.0400) (0.0495) (0.0524) (0.0467) (0.0532) (0.0676) (0.0441)
Disabled X Q2 2022 0.124*** 0.141*** 0.0787 0.186*** 0.0736** 0.0750** 0.169***
(0.0278) (0.0300) (0.0512) (0.0383) (0.0365) (0.0365) (0.0355)
Constant -1.331** -1.116 -3.886*** -1.653 -2.433*** -2.290*** -1.874*
(0.660) (0.785) (0.880) (1.181) (0.793) (0.794) (0.954)
Observations 240 240 240 240 240 240 240
Notes: * p < 0.10, ** p < 0.05, *** p < 0.01 Standard errors in parentheses. Interaction coefficients are relative to Q1 2019. Models include demographic controls for age, gender, race, and education attainment of Bachelor’s degree and are weighted by working age (18-64) population size, as calculated from CPS data. Essential jobs are based on Department of Homeland Security’s “Identifying Critical Infrastructure During COVID-19” guidelines. Our definition of teleworkable jobs comes from Dingel and Neiman 2020. Frontline jobs are those that are essential and not teleworkable.
We first present key demographic statistics for the disabled and non-disabled populations before (Q1 2019, our reference quarter), during (Q2 2020), and after (Q2 2022) the COVID-19 recession. We use t-tests to determine whether there were significant differences in the number and composition of people reporting disabilities across time.
To analyze employment trends in the quarters surrounding the COVID-19 recession, we first plot the percent difference relative to Q1 2019 in the employment-to-population ratio from Q1 2018 to Q1 2022, separately by disability status group. We next estimate the percent change in the employment-to-population ratio for PWD relative to those without disabilities by month, using the following specification:(1) ln(EPOPtd)=α+πD+∑qγqQt+∑qβq(Qt×D)+δ′Xtd+εtd
The dependent variable EPOPtd is the employment-to-population ratio in month t for disability status group d. We take its natural log since the logarithm approximates percent changes and therefore accounts for the very different employment levels across the disabled and nondisabled groups. Qt is a series of indicator variables for quarters across the study period (omitting the reference quarter Q1 2019). D is an indicator variable taking the value 1 when the monthly employment-to-population ratio observation is for disabled workers and 0 when it is for non-disabled workers. Xtd is the set of group-specific, time-varying demographic covariates described above. The terms Qt×D are interactions between each quarter and disability status group. The coefficients of interest are the βq coefficients, which measure the percent difference in the employment-to-population ratio relative to Q1 2019 for PWD relative to those without. All models are estimated using ordinary least squares, and we make use of heteroskedastic-robust standard errors and the sampling weights provided by the CPS. We also use Equation 1 to estimate relative changes in disability employment in essential/non-essential, frontline/non-frontline, and teleworkable/non-teleworkable occupations. In these specifications, the numerator of the dependent variable is the number of PWD employed in essential, non-essential, frontline, non-frontline, teleworkable, or non-teleworkable occupations, and the denominator is the same as before.
Results
Sample Statistics
We first explore the possibility of shifts in the composition of the disabled sample before, during, and after the COVID-19 recession. Panel A of Table 1 shows that the proportion of PWD dropped from 7.58% in Q1 2019 to 7.20% in Q2 2020 before increasing to 8.12% in Q2 2022. This decline corresponds to the disruption in the CPS’s typical sampling procedures at the start of the pandemic.23 Table 1 Sample Statistics Before, During, and After COVID Recession
Table 1Panel A
Percentage of total population Percentage employed at work
Before During After Conditional Before on disability During Status After
2019:Q1 2020:Q2 2022:Q2 2019:Q1 2020:Q2 2022:Q2
Any Disability (%) 7.58 7.20 *** 8.12 *** 29.24 24.95 *** 32.79 ***
Hearing difficulty 1.43 1.40 1.52 ** 49.34 42.64 *** 48.39
Vision difficulty 1.13 0.95 *** 1.16 38.22 30.21 *** 37.68
Difficulty remembering 2.99 2.80 *** 3.65 *** 22.27 19.70 *** 30.32 ***
Physical difficulty 3.98 3.54 *** 3.78 *** 18.76 14.83 *** 19.42
Disability limiting mobility 2.52 2.45 2.75 *** 11.66 7.77 *** 12.11
Personal care limitation 1.18 1.13 1.22 9.27 6.58 *** 9.87
Panel B
Working Age Population (in millions) With Disability No Disability
15.0 14.2 *** 16.1 *** 182.4 182.9 182.3
Age
Mean age 47.33 46.76*** 46.71 *** 40.27 40.36 40.34
18-34 (%) 21.71 24.41*** 23.46 *** 38.64 38.38 38.08 ***
35-49 (%) 24.18 23.35 24.39 31.48 31.54 32.02 ***
50-64 (%) 54.11 52.24*** 52.15 *** 29.88 30.08 29.90
Sex
Female (%) 51.07 49.20*** 51.07 50.80 50.85 50.37 **
Race
White, Non-Hispanic (%) 63.62 62.55 63.82 59.34 58.81*** 57.83 ***
Black, Non-Hispanic (%) 16.32 16.13 15.14 ** 12.31 12.45 12.56 *
Hispanic (%) 13.29 15.28*** 14.64 *** 18.96 19.15 19.87 ***
Education
Bachelor’s degree (%) 15.60 16.04 17.34 *** 35.41 37.43*** 36.91 ***
Employment Outcomes
Employed at Work (%) 29.24 24.95*** 32.79 *** 74.48 63.38*** 74.02 ***
Labor Force Participation (%) 34.26 34.45 38.00 *** 79.79 77.25*** 79.53 *
Unemployed (%) 9.36 18.42*** 8.23 * 3.92 12.46*** 3.29 ***
Occupational Category
Management, Business, Science, and Arts (%) 31.20 36.07*** 35.50 *** 41.50 46.28*** 42.83 ***
Service (%) 22.06 17.24*** 18.89 *** 16.30 13.13*** 15.91 **
Sales and Office (%) 23.29 21.87 21.35 ** 20.97 19.55*** 19.00 ***
Natural Resources, Construction, and Maintenance (%) 9.36 10.50 8.17 * 9.34 9.08* 9.37
Production, Transportation, and Material Moving (%) 14.10 14.32 16.62 *** 11.89 11.96 12.89 ***
Notes: Statistically significant difference relative to 2019:Q1 at * p < 0.10, ** p < 0.05, *** p < 0.01.
Panel B of Table 1 also shows that, from Q1 2019 to Q2 2022, there was an increase in the number of working-age PWD identified by the CPS of over one million persons. In contrast, non-disabled people had a statistically identical number of working-age adults in Q2 2022 as in Q1 2019. The increase in the number of disabled respondents is economically significant and might be attributable to either increasing disability rates during the pandemic or sampling bias. Panel B also shows shifts in the demographic composition of both the disabled and non-disabled samples, both of which became more educated and more Hispanic. The disabled sample also became younger. Nonetheless, these demographic shifts do not appear to be substantively large. We control for these demographic covariates in our subsequent analysis and include additional information demonstrating that these demographic compositional changes do not explain our subsequent findings in our limitations section.
We also present in Panel B of Table 1 information on employment outcomes for both the PWD and non-disabled sample. Both groups saw sharp drops in the percentage of persons employed-at-work in Q2 2020. However, while the non-disabled employed-at-work percentages were still 0.46 percentage points below pre-recession levels in Q2 2022, PWD had achieved a 3.55 percentage point increase relative to their pre-recession position. Labor force participation (those working or actively looking for work) remained constant for PWD during the recession while it dropped for non-disabled people. PWD also fared better during the recovery. By Q2 2022 the labor force participation of PWD had risen 3.74 percentage points from its level in Q1 2019. In contrast, labor force participation for non-disabled people remained lower. In Appendix C, we show that disabled labor force participation has risen to the highest levels seen since the six-question disability sequence was added to the CPS in 2008. Unsurprisingly, both PWD and non-disabled people experienced significant increases in their unemployment rates in Q2 2020, with the rate nearly doubling for PWD and more than tripling for the non-disabled. However, both groups saw declines in unemployment rates relative to pre-COVID-19 rates by Q2 2022. Finally, we also observe similar occupational shifts for the two groups over the study period.
We next examine whether PWD had faster employment changes in percent terms than non-disabled people during and after the COVID-19 recession. Figure 1 shows the unadjusted percent change in the quarterly employment-to-population ratio for PWD and non-disabled people, relative to Q1 2019. As the pandemic took hold in Q2 2020, the employment rate for both PWD and non-disabled people fell sharply, by over 10 percent. As employment began to recover in Q3 and Q4 2020, PWD and non-disabled employment recovered at the same pace. Then beginning in Q2 2021, the employment rate of PWD grew at a faster rate than that of non-disabled people. The employment rate of PWD recovered to its pre-recession level by Q2 2021 and has since surpassed that level by approximately 10 percent. In contrast, the employment rate of non-disabled people recovered to its pre-recession level two quarters later (in Q4 2021) where it has since remained.Figure 1 Notes: Authors' calculations from Current Population Survey (CPS) microdata. Confidence intervals constructed using standard error of percent change, per U.S. Census Bureau guidance.
Figure 1
We then examine these same trends within particular categories of employment, in order to better understand what parts of the economy have driven the faster pace of disabled employment growth. Figure 2 displays trends for PWD and non-disabled people by employment type, showing that the faster relative employment growth experienced by PWD is concentrated in certain sectors of the economy. These figures show that the relative employment growth experienced by PWD was heavily concentrated in teleworkable, essential, and non-frontline occupations. The particularly strong employment growth in teleworkable occupations suggests that the expansion in telework that took place during the COVID-19 public health emergency may have had a positive impact on disability employment, raising the potential for long-term structural changes in the post-COVID-19 economy that may facilitate greater inclusion of PWD into the workforce.Figure 2 Notes: Authors' calculations from Current Population Survey (CPS) microdata. Confidence intervals constructed using standard error of percent change, per U.S. Census Bureau guidance.
Figure 2
Table 2 quantifies these patterns by presenting regression coefficients from estimation of Equation 1 by linear regression, which allows us to control for demographic covariates. Each column represents a different model where the dependent variable in Column 1 is the overall employment-to-population ratio and the dependent variables in the subsequent columns are the employment-to-population ratios for each employment type (e.g., essential, teleworkable, frontline). The coefficients of interest are from the interaction of quarter-year with an indicator for disability status. The estimates in column 1 confirm the overall patterns in Figure 1: There was no statistically significant difference between the employment rate for PWD and non-disabled persons (relative to the reference quarter of Q1 2019) for any of the quarters during 2020. While short of statistical significance, relative employment growth for PWD increased in Q2 and Q3 of 2021. By Q4 2021, Q1 2022, and Q2 2022, the disabled employment-to-population ratio was significantly greater than that for non-disabled people at a p<0.05 level. The coefficient for the interaction term for Q2 2022 indicates that PWD experienced approximately 12.4% more growth from Q1 2019 to Q2 2022 than non-disabled people during the same period.
We next explore differences in employment trends by employment type for PWD and non-disabled people. Columns 2 and 3 present estimates for relative employment growth in essential and non-essential occupations, respectively. In column 2, we see that there is no statistically significant difference between the employment trends of PWD and non-disabled people in essential occupations through Q3 2021. But in Q4 2021 through Q2 2022, we see evidence of faster growth in essential employment for PWD, exceeding that of non-disabled people by approximately 14.1% (from Q1 2019 to Q2 2022). In column 3, we find little evidence of differential growth in non-essential occupations for PWD compared to non-disabled people.
We also examine differences in employment between PWD and non-disabled people by whether an occupational category is amenable to telework. Columns 4 and 5 present estimates for relative employment growth in teleworkable and non-teleworkable occupations, respectively. In column 4, we see that PWD saw much faster employment growth in teleworkable professions than non-disabled people did, beginning in Q2 2021 and increasing through Q2 2022, by which time the employment of PWD had outpaced that of non-disabled people by approximately 18.6%. In contrast, column 5 shows more modest greater employment growth of approximately 7.4% in non-teleworkable occupations, manifesting only in the most recent quarter (Q2 2022). Lastly, columns 6 and 7 present the coefficients for frontline and non-frontline employment, respectively. Column 6 shows a similarly modest recent difference in the rate of growth in frontline employment of approximately 7.5% (again, present only in Q2 2022) while column 7 shows that PWD saw significantly more employment growth in non-frontline positions than did non-disabled people in the last three quarters of our study period, Q4 2021 through Q2 2022, with employment of PWD growing approximately 16.9% more from Q1 2019 to Q2 2022 than employment of non-disabled people.
Our findings show that employment growth for PWD began to outpace that of non-disabled people in percentage terms in Q4 2021, Q1 2022 and Q2 2022. These trends emerged even earlier for teleworkable professions where employment growth of PWD exceeded that of non-disabled people as early as Q3 2021. Faster employment growth for PWD were concentrated in essential, teleworkable, and non-frontline jobs. These shifts appear to be driven by rising labor force participation of PWD rather than changes in the unemployment rate (see Figures C2 and F2 in Appendices C and F, respectively). If this trend is sustained, it suggests the possibility of returning to the pre-COVID-19 steady increases in disability employment. It may also indicate that the shift towards remote work may present opportunities for a long-awaited improvement in disability employment outcomes post-COVID-19.
Discussion
Limitations
Prior work has found that the 6-question sequence used by the CPS fails to classify as disabled some groups of people with disabilities who are enrolled in income support programs and not in the labor force, biasing up the measured rate of employment among PWD.24 However, this issue would not affect our analysis of changes in employment during the COVID-19 public health emergency as long as the question bias remains constant over the study period.
For individuals who first entered the CPS during COVID-19, the CPS has no information about their pre-COVID-19 employment status, making it impossible for us to evaluate if they became unemployed due to COVID-19 or if their prior employment was in an industry of interest for a specific analysis. It is only possible to observe pre-COVID-19 employment status for those who were in their 5th through 8th month in the sample between March 2020 and February 2021. To address this, we used a common population denominator across occupational sectors. However, this did not allow us to distinguish between improved employment outcomes for jobseekers within a particular occupational category as compared to shifts between occupational categories.
In March 2020, the CPS suspended in-person interviewing due to the risks posed by COVID-19. Though in-person interviews resumed months later, response rates for the CPS have declined over the course of the pandemic.23 This raises the possibility that the disabled population identified by the CPS after COVID-19 may be systematically different than that identified during COVID-19. To address this, we made use of demographic controls via multivariate regression, as reflected above. We report the specification with demographic controls as our primary analysis and report the results of the unadjusted specification in Appendix A, in which our main findings persist. We also conduct regressions using demographic characteristics as the dependent variable with the same specification as our primary analyses (see Appendix D). The compositional shifts in demographics that we do identify are not large enough or timed at points likely to explain our main findings.
We do find that the percentage of PWD in the sample during the first year of the pandemic fell by 5 percent compared to Q1 2019 (see Figures D1 and D2 in Appendix D). While some of the drop in 2020 may be attributable to excess COVID-19 mortality among people with disabilities, the declines are too large to be attributable to this alone (particularly taking into account that many such deaths took place in congregate settings outside the CPS sampling frame.) It is more likely that the drop reflects a temporary sampling bias due to the disruption of the CPS’s typical interviewing procedures.
Beginning in Q2 2021, this was followed by an above-average rate of disability in our sample during the economic recovery in 2021 and 2022. In the initial months, the reversal may have been due to make-up disability questions being asked in subsequent waves of people who missed their 1st or 5th months in sample. However, since then the rising prevalence of Long COVID and other new sources of disability signal that the increase may reflect an actual increase in the number of PWD, suggesting that PWD’s improved labor force participation is the result of an influx of new PWD with comparably mild impairments, more social and professional capital, and a greater attachment to the labor force. Though Long COVID’s impact on employment trends is typically thought of in terms of reduced aggregate labor supply25 when comparing employment trends of PWD and non-disabled people this may materialize in the form of an increase in disabled employment trends. Alternatively, prior work indicates that individuals’ willingness to report their disability status may be influenced by workplace and social factors.26 If employees became more willing to acknowledge a disability in order to obtain a telework arrangement or other reasonable accommodations they may have also become more willing to report their disability to the CPS.
Discussion
In marked contrast to the recovery from the Great Recession, where PWD saw greater job loss and a slower recovery than their non-disabled counterparts9 , 12, PWD appear to have had similar employment losses compared to their non-disabled counterparts during the COVID-19 recession. However, during the recovery, PWD experienced considerably faster employment growth, reaching pre-Recession levels before their non-disabled counterparts and then exceeding them.
Our paper is the first we are aware of to examine the employment trends of PWD in the COVID-19 economic recovery. The disabled employment-to-population ratio in Q2 2022 is significantly higher than it was three years earlier, despite COVID-19’s considerable disruptions. This appears to be attributable to a significant increase in labor force participation for PWD. Our findings suggest that recovery from the COVID-19 recession has brought PWD into the labor force though it remains unclear to what extent this may have been influenced by an influx of newly disabled persons due to the pandemic.
Closer examination of the occupations where disabled employment growth has exceeded that of non-disabled suggests that these trends are not solely attributable to tight labor markets but may also be shaped by the structural shifts in the workforce brought about by COVID-19, in particular the shift towards telework. Despite the devastating impact COVID-19 has had on the disability community, it may open opportunities for making progress on one of disability policy’s most difficult problems: the failure to integrate PWD into the workplace. The economic recovery appears to have encouraged PWD who had previously left (or never entered) the workforce to find employment. Moreover, the expansion in telework may have shifted the frontier of plausible employment opportunities for PWD, creating new occupational targets for vocational rehabilitation.
Though telework has long been recognized as a potential reasonable accommodation, the frequency with which it was made use of during the pandemic and gains in familiarity and comfort with telework technology during the post-COVID-19 era suggest that telework may be feasible under more circumstances than previously thought – potentially impacting employers’ obligation to offer it to workers with disabilities when requested as a reasonable accommodation.27 It remains unclear how permanent the shift towards telework will be. In order to sustain this progress, it is particularly important that employers retain flexibility for PWD as they develop return-to-work protocols. Civil rights enforcement bodies like the EEOC can encourage this flexibility by carefully monitoring employer behavior as return-to-work efforts proceed to ensure that workers have access to appropriate reasonable accommodations. We also note recent guidance from the federal government clarifying that persons with Long COVID may qualify for protections under disability rights law.28 , 29
Conclusion
While PWD have suffered disproportionate harms from COVID-19, our findings suggest that the public health emergency has created unprecedented improvements in their labor market position. Future research should carefully monitor these trends with the goal of understanding their sustainability and the policies that may accelerate or attenuate them. Improving PWD’s labor force participation is a longstanding goal of disability policymaking and advocacy. If PWD can benefit long term from COVID-19-induced shifts in employer practices, they may be able to achieve progress on one of the most elusive frontiers for disability inclusion: integration into the American workplace.
Funder Acknowledgment
This line of study was supported in part by a grant from the National
Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR) for the
Rehabilitation Research and Training Center on Employment Policy: Center for Disability
inclusive Employment Policy Research, Grant No. 90RTEM0006-01-00. NIDILRR is a Center
within the Administration for Community Living (ACL), Department of Health & Human
Services. Ari Ne’eman’s effort was also supported by the National Institute of Mental Health of
the National Institutes of Health under Award Number T32MH019733.
Disclaimer
The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health, NIDILRR, the federal government or any other funder.
Conflict of Interest Statement
Ari Ne’eman reports consulting income within the last twelve months from the Service Employees International Union, Inclusa, CareSource and the Department of Health and Human Services Office of Civil Rights. The data presented here was not collected as part of his duties for any of these entities, including the Department of Health and Human Services, and the research, analysis, findings, and conclusions were not reviewed by them nor do they necessarily represent their views.
Appendix A Supplementary data
The following is/are the supplementary data to this article:
Acknowledgment
The authors wish to thank Hailey Elizabeth Clark and Kevin Mitchell
Friedman for exemplary support throughout the project.
Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.dhjo.2022.101429.
==== Refs
References
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2 Yuan Yan. COVID-19 Cases and Hospitalizations Among Medicare Beneficiaries With and Without Disabilities—United States, January 1, 2020–November 20, 2021 MMWR. Morbidity and Mortality Weekly Report 71 2022
3 Ameri Mason Schur Lisa Adya Meera Scott Bentley F. McKay Patrick Douglas Kruse The disability employment puzzle: A field experiment on employer hiring behavior ILR Review 71 2 2018 329 364
4 Schur Lisa A. Mason Ameri Douglas Kruse Telework after COVID: a “silver lining” for workers with disabilities? Journal of occupational rehabilitation 30 4 2020 521 536 33156435
5 van der Noordt Maaike IJzelenberg Helma Droomers Mariël Karin I. Proper. "Health effects of employment: a systematic review of prospective studies Occupational and environmental medicine 71 10 2014 730 736
6 For a summary of this large literature, see: Goodman, Nanette. 2015. “The impact of employment on the health status and health care costs of working-age people with disabilities.” Lead Center Policy Brief.
7 Burkhauser, Richard V, Mary C Daly, Andrew J Houtenville, and Nigar Nargis. 2001. “Economic outcomes of working-age people with disabilities over the business cycle: An examination of the 1980s and 1990s.” Federal Reserve Bank of San Francisco.
8 Burkhauser Richard V. Stapleton David C. A review of the evidence and its implications for policy change The decline in employment of people with disabilities: A policy puzzle 2003 369 405
9 Kaye H Stephen Impact of the 2007-09 recession on workers with disabilities Monthly Lab. Rev. 133 2010 19
10 Fogg Neeta P. Harrington Paul E. McMahon Brian T. The underemployment of persons with disabilities during the Great Recession The Rehabilitation Professional 19 1 2011 3 10
11 Maestas Nicole Mullen Kathleen J. Alexander Strand The effect of economic conditions on the disability insurance program: Evidence from the great recession Journal of Public Economics 199 2021 104410
12 Schur, Lisa, Yana Rodgers, and Douglas L Kruse. 2021. “COVID-19 and employment losses for workers with disabilities: An intersectional approach.” Available at SSRN 3788319.
13 Houtenville Andrew J. Paul Shreya Brucker Debra L. Changes in the employment status of people with and without disabilities in the United States during the COVID-19 pandemic Archives of Physical Medicine and Rehabilitation 102 7 2021 1420 1423 33839102
14 Dey Matthew Frazis Harley Loewenstein Mark A. Sun Hugette Ability to work from home Monthly Labor Review 1–19 2020
15 Dey Matthew Frazis Harley Piccone David S. Jr. Loewenstein Mark A. Teleworking and lost work during the pandemic: new evidence from the CPS Monthly Lab. Rev. 144 2021 1
16 Barrero, Jose Maria, Nicholas Bloom, and Steven J Davis. 2021. Why working from home will stick. Technical report. National Bureau of Economic Research.
17 U.S. Equal Employment Opportunity Commission Work at home/Telework as a reasonable accommodation Technical report 2003
18 Kruse Douglas Park So Ri Yana van der Meulen RodgersSchur Lisa Disability and remote work during the pandemic with implications for cancer survivors Journal of Cancer Survivorship 16 1 2022 183 199 35107797
19 Stapleton, David C, Andrew J Houtenville, Robert R Weathers II, Richard V Burkhauser, and Lord Kelvin. 2009. “Purpose, overview, and key conclusions.” Counting Working-Age People with Disabilities: What Current Data Tell Us and Options for Improvement, Andrew J. Houtenville, David C. Stapleton, Robert R. Weathers II, Richard V. Burkhauser, eds. Kalamazoo, MI: WE Upjohn Institute for Employment Research, 1–26.
20 U.S. Bureau of Labor Statistics. “Effects of COVID-19 Pandemic on the Employment Situation News Release and Data.” September 1, 2022. https://www.bls.gov/covid19/effects-of-covid-19-pandemic-and-response-on-the-employment-situation-news-release.htm.
21 Department of Homeland Security Identifying critical infrastructure during COVID-19 Technical report 2020
22 Dingel Jonathan I. Neiman Brent How many jobs can be done at home? Journal of Public Economics 189 2020 104235
23 McIllece, JJ. 2020. “COVID-19 and the current population survey: Response rates and estimation bias.” US Bureau of Labor Statistics 20.
24 Burkhauser Richard V. Houtenville Andrew J. Jennifer R. Tennant. Capturing the elusive working-age population with disabilities: Reconciling conflicting social success estimates from the Current Population Survey and American Community Survey Journal of Disability Policy Studies 24 4 2014 195 205
25 Bach, Katie. 2022. Is ’long COVID’ worsening the labor shortage? Technical report. The Brookings Institution.
26 Baker Michael Stabile Mark Deri Catherine What do self-reported, objective, measures of health measure? Journal of Human Resources 39 4 2004 1067 1093
27 Kalmbach Baylee. A COVID Silver Lining? How Telework May Be a Reasonable Accommodation After All U. Cin. L. Rev. 90 2021 1294
28 HHS Office for Civil Rights. “Guidance on “Long COVID” as a Disability Under the ADA, Section 504, and Section 1557.” July 26, 2021. https://www.hhs.gov/civil-rights/for-providers/civil-rights-covid19/guidance-long-covid-disability/index.html.
29 U.S. Equal Employment Opportunity Commission. “What You Should Know About COVID-19 and the ADA, the Rehabilitation Act, and Other EEO Laws.” July 12, 2022. https://www.eeoc.gov/wysk/what-you-should-know-about-covid-19-and-ada-rehabilitation-act-and-other-eeo-laws.
| 0 | PMC9747687 | NO-CC CODE | 2022-12-15 23:22:03 | no | Disabil Health J. 2022 Dec 14;:101429 | utf-8 | Disabil Health J | 2,022 | 10.1016/j.dhjo.2022.101429 | oa_other |
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Int J Disaster Risk Reduct
Int J Disaster Risk Reduct
International Journal of Disaster Risk Reduction
2212-4209
Elsevier Ltd.
S2212-4209(22)00714-2
10.1016/j.ijdrr.2022.103495
103495
Article
A county-level analysis of association between social vulnerability and COVID-19 cases in Khuzestan Province, Iran
Arvin Mahmoud a
Bazrafkan Shahram b
Beiki Parisa c
Sharifi Ayyoob d∗
a Department of Human Geography, Faculty of Geography, University of Tehran, Iran
b Department of Human Geography and Spatial Planning, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran
c Department of Geography, Central Tehran Branch, Islamic Azad University, Tehran, Iran
d Hiroshima University, ،The IDEC Institute, the Graduate School of Humanities and Social Science, and the Network for Education and Research on Peace and Sustainability (NERPS), Japan
∗ Corresponding author. 1Kagamiyama, Higashi-Hiroshima City Hiroshima, 739-8530, Japan.
14 12 2022
1 2023
14 12 2022
84 103495103495
5 7 2022
11 12 2022
11 12 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.
Social vulnerability is related to the differential abilities of socio-economic groups to withstand and respond to the adverse impacts of hazards and stressors. COVID-19, as a human risk, is influenced by and contributes to social vulnerability. The purpose of this study was to examine the association between social vulnerability and the prevalence of COVID-19 infection in the counties of Khuzestan province, Iran. To determine the social vulnerability of the counties in the Khuzestan province, decision-making techniques and geographic information systems were employed. Also, the Pearson correlation was used to examine the relationship between the two variables. The findings indicate that Ahvaz county and the province's northeastern counties have the highest levels of social vulnerability. There was no significant link between the social vulnerability index of the counties and the rate of COVID-19 cases (per 1000 persons). We argue that all counties in the province should implement and pursue COVID-19 control programs and policies. This is particularly essential for counties with greater rates of social vulnerability and COVID-19 cases.
Keywords
Social vulnerability
COVID-19
Multi-criteria decision making techniques
Community resilience
GIS
Urban resilience
==== Body
pmc1 Introduction
The COVID-19 pandemic has triggered a global public health disaster [1]. According to the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU), over 648 million cases of the disease have been reported worldwide, as of December 10, 2022. High incidence and mortality rates, unknown nature of the disease, lack of a definitive treatment solution, travel and social distancing restrictions, financial losses, fear of COVID-19 transmission, and increased stress were some of the major issues that faced of human society after the spread of COVID-19, especially in vulnerable groups [2].
The World Health Organization (WHO) proclaimed COVID-19 a pandemic on March 11, 2020, after evaluating the global case count and issuing early regulatory directives to execute healthcare measures against the new disease. Social distancing, mask use, and disinfectant use were all promoted as the main measures for reducing the occurrence of COVID-19 [3]; [4]. According to research, disasters, economic shocks, and other disturbances affect various segments of society in markedly different ways [5]; [6]. Indeed, pandemics and other natural and man-made hazards disproportionately harm the most vulnerable persons and communities [7] [8,9]. The Centers for Disease Control and Prevention (CDC) uses ‘social vulnerability’ to determine which communities are more vulnerable to adverse events such as disasters triggered by natural hazards or disease outbreaks [10]. The degree to which a society can prepare for and respond to a natural or man-made hazards, such as a hurricanes, chemical spills, or disease outbreaks, is defined as social vulnerability [11]. Social vulnerability is determined by the social, economic, demographic, and geographic aspects that influence risk exposure, as well as the capacity of society to cope with risk [12]. The socio-economic conditions, disability, population composition (by age, race, and ethnic origin), housing status, family structure, social security, and public health situation are all considered indicators of social vulnerability [13]. Social vulnerability has a substantial impact on mortality and health outcomes as well [14]. It is anchored in social systems that result in unequal risk exposure and social problems [15].
Over the last decade, research efforts have shifted toward socio-environmental vulnerabilities as a result of their relationship with geophysical and human risks. With the emergence of the COVID-19 pandemic, there has been renewed attention to the association between social vulnerability and pandemics [16]; [8,[17], [18], [19], [20], [21]]. Additionally, researchers have attempted to develop COVID-19-specific vulnerability indicators. Since the outbreak began, the number of studies demonstrating the detrimental impacts of COVID-19 on socially vulnerable individuals has expanded tremendously [22]. Several early studies examined the relationship between social vulnerability and COVID-19 mortality in the United States. Khazanchi et al. [19]; using a Poisson-like regression approach and examining the cities that feature different socio-economic groups, types of housing, and transportation infrastructure distribution, discovered that those who live in counties with the highest social vulnerability face an increased risk of infection and mortality [19]. In another study, Nayak used a linear model to assess 433 US counties and discovered that high levels of social vulnerability were associated with greater COVID-19 mortality [23]. Additionally, Kim and Bostwick found a positive association between the percentage of black residents in the Chicago Census tracts and social vulnerability. Further, they discovered that spatial clusters of social vulnerability are connected with an increased risk of death from COVID-19. Moreover, other studies have revealed a strong correlation between social vulnerability and COVID-19 mortality in the United States [11]. Also, there is evidence that COVID-19 has a greater impact on ethnic and racial minorities, the elderly, and those who are socially and economically disadvantaged [24]. Numerous studies have established that African Americans have a greater rate of incidence and mortality than non-Hispanic whites [25,26][27].
Existing literature clearly shows that the COVID-19 pandemic has resulted in an increase in inequality in different societies, especially among vulnerable groups [[28], [29], [30]]. Moreover, one of the tangible effects of the COVID-19 pandemic, as mentioned, has been the changes in the economic status of urban communities, especially in developing countries. These changesdirectly affect the workers and suppliers of the private sector, who are among the most vulnerable groups. Indeed, social distancing and/or quarantine measures to contain COVID-19 have disrupted various economic activities. The pandemic and measures developed to control it have disproportionately impacted some socio-economic groups with limited planning, coping, and recovery capacities. These include, for instance, minorities and those employed in the informal sector [[31], [32], [33]].
Existing literature demonstrates that socially vulnerable people are more prone to disasters and that social disparities foster illness transmission, complicating efforts to manage the pandemic. Indeed, existing social disparities increase vulnerable and marginalized populations' risk of illness and mortality from COVID-19 [34]. The social sphere and social vulnerability are critical components of COVID-19 research. Accordingly, the study of social factors is critical for responding to this risk. Empirical evidence related to social vulnerabilities in the context of the pandemic has been reported for different countries, including the United States and developing countries such as India [35,36], Brazil [7,37], Philippines [38], and Palestine [39]. However, no study has been conducted in Iran or Khuzestan region to examine the association between social vulnerability and COVID-19 cases or deaths.
Iran was one of the first epicenters of the COVID-19 in the Middle East, and, like many other countries, it has gone through multiple waves of the pandemic [40,41]. Khuzestan province, located in southwestern Iran, has one of the greatest concentrations of COVID-19 [42]; [43]; [44]. Like other provinces in Iran and developing countries, Khuzestan faces the issue of social inequality. Lack of infrastructure in villages and distant locations, high unemployment in suburban areas, and high prevalence of poverty in cities and villages are some of the most critical issues. These issues make it challenging to deal with natural and man-made hazards. . The Province, as one of the most populous provinces of Iran, is located in a multi-hazard area and suffers much damage due to various hazards such as floods, earthquakes, landslides, and dust. These multiple hazards have affected the socioeconomic conditions of residents in cities and villages [45]. The province is exposed to numerous natural hazards and is one of the most deprived provinces of Iram. It has a high unemployment rate, and the occurrence of adverse events (e.g., the COVID-19 pandemic) has worsened its unfavorable conditions, especially for deprived groups. Assessing the province's social conditions and addressing vulnerabilities are essential for developing policies and programs to battle the crisis and increase the province's overall resilience. Therefore, this study aimed to examine the association between social vulnerability and the COVID-19 cases in the province by developing a methodology based on Multi-criteria Decision Making (MCDM) and geographic information systems. In other words, we wanted to examine in there is an association between social vulnerability and the prevalence of COVID-19 in the province. We investigate the vulnerability of the counties in Khuzestan Province and explore the relationship between the composite index of social vulnerability and the COVID-19 incidence rate. Our findings could provide planners with a clearer view of the impacts of social vulnerability on the COVID-19 in the field of planning and implementation.
2 Theoretical framework
2.1 Social vulnerability
The concept of vulnerability has been used since the 1970s, especially in studies of crisis management, development, and the environment [46]. Vulnerability is the degree to which a system is prone to damage and cannot adapt to the harmful effects of a change. Different viewpoints on social-ecological system vulnerability show that vulnerability is affected by the expansion or weakening of the elastic characteristics of social and ecological elements, affecting the system's ability to adapt to incoming shocks [47]. Vulnerability is divided into internal vulnerability (ability to cope with new conditions) and external vulnerability (linked to being exposed to risks). External vulnerability mainly refers to the structural dimensions of vulnerability and risk, and the concept of internal vulnerability is associated with the measures needed to deal with economic-social and environmental changes. External vulnerability is often more highlighted, while internal vulnerability is difficult to identify and measure [48]. Thus, it can be argued that vulnerability refers to conditions that, due to physical, social, economic, and environmental factors, determine and increase the ability of societies against damage caused by hazards [49][50].
Social factors play an important role in reducing or increasing human vulnerability. The issue of social vulnerability to hazards received more attention from researchers in the 1970s, when they realized that vulnerability can include, in addition to the physical dimension, social and economic factors that affect the resilience of society [51]. Accordingly, social vulnerability refers to socio-demographic factors that affect society's ability to respond to and recover from stressful factors at the community level, such as epidemics and natural disasters [52]. Social vulnerability refers to a condition when certain individuals or communities have limited ability to mitigate, absorb, recover from, and adapt to threats and disasters. It is a combination of factors that determine people's living standards and includes livelihood, wealth, and other assets that are endangered by identifiable events in nature and society [53]. The increased social vulnerability could undermine community resilience [54][55]. Studies conducted around the world have shown that different groups of people tend to show varying degrees of vulnerability to hazards depending on their standard of living and social and economic situation in different parts of the world. Assessing the social vulnerability of human settlements against hazards, as one of the basic indicators in risk assessment, has a special place in the crisis management cycle, and without an awareness of the social and economic situation of the residents, it is not possible to assess their vulnerability to hazards. Different techniques including statistical analysis and geographic information systems (GIS) have been used to measure and evaluate social vulnerability indicators. For instance, Ebert et al. [56] evaluated social vulnerability using ground sampling and spatial measurements through satellite images and GIS data. Moreover, Armaș et al. (2013) used a multi-criteria analysis model to assess the social vulnerability of Bucharest [57]. Furthermore, principal component analysis (PCA) and geographic information systems (GIS) were used to measure social vulnerability to floods [58], earthquakes [59], and COVID-19 pandemic [35,60]. The analytic hierarchy process (AHP) and geographic information systems were also used to investigate social vulnerability against COVID-19 [39] and local Spearman's rank correlation coefficient was employed to measure the relationship between social vulnerability and COVID-19 [34]. A review of the methods used in related studies shows that the social vulnerability index was not calculated as a composite index. Besides, weighting techniques have not been used due to the different impacts of the indicators.
2.2 Social vulnerability and COVID-19
The rapid spread of the new coronavirus (COVID-19) has brought devastating impacts and damages to countries around the world and created new challenges to achieving sustainability [61]. Initially, COVID-19 was misleadingly named the ‘great equalizer’, meaning that everyone is equally vulnerable to the virus, and people's economic activity, infection rates, deaths, etc. Are similarly affected regardless of their social status [62]. However, empirical evidence has shown that although the impact of COVID-19 has been widespread, not all regions or social groups have been equally affected by this epidemic [63,64]. COVID-19 widely affects socioeconomic activities, work life, and food systems [65]. The analysis of infection and mortality rates has shown that specific individual and spatial characteristics, income levels, and social positions of people, especially multidimensional vulnerability criteria are associated with a higher or lower probability of infection with the COVID-19 virus [66][67]. Accordingly, the COVID-19 pandemic has had major impacts on life everywhere, but some countries and communities have been affected disproportionately [68]. When disasters of any kind occur, socially vulnerable people are at the greatest risk. People who live in vulnerable situations include people facing systematic deprivation and those who have been discriminated against depending on socio-demographiccharactersitics such as age, gender, faith, physical ability, ethnicity, and income. . Moreover, people who live in inappropriate housing, are exposed to unfavorable environmental conditions, and are at climatic risk are more socially vulnerable [69].
Reports of morbidity and mortality from COVID-19 show higher rates among racial/ethnic minorities, older adults, low-income groups, and less educated people [70]. For example, crowded and poor districts, where minorities are overrepresented, render social distancing orders designed to control the spread of the virus less practical and increase the risk of infection. Vulnerable groups inadvertently reside in unfavorable and overcrowded neighborhoods. As a result, they are often more exposed to health risks and have limited ability to comply with health and sanitation measures [30]. Furthermore, due to their unique economic conditions, vulnerable communities cannot afford to stay home and respect social distancing measures [64]; [71].
Therefore, the COVID-19 epidemic has not only caused a public health emergency but has also led to major economic and social crises, with unequal distribution of its consequences throughout economies and societies [72]. Moreover, studies have confirmed that social inequalities during pandemics cause the risk of unequal distribution of the disease among the population. Furthermore, the unavailability of resources and difficulties in access to basic health or preventive information increase social inequalities during pandemics [29,30]. As a result, socially vulnerable people experience higher exposure to health risks and are more likely to be negatively impacted [73]. People who live in vulnerable conditions are exposed to significantly exacerbated inequality gaps caused by the pandemic and are more likely to suffer from possible negative and long-term physical, socio-economic, and psychological health consequences [28].
3 materials and methods
This is a multi-criteria study that utilized MCDM and correlation methods. SPSS and ArcGIS software programs were employed to analyze the data. In this section, we first briefly introduce the study area and then explain the data and analysis methods.
3-1 study area
Khuzestan province, with an area of 632,528 km2, is located in southwestern Iran and northwest of the Persian Gulf (Fig. 1 ) [74]. The province's altitude ranges from 0 to 3740 m. Also, the climate varies from cold in the north to warm in the south [75]. According to the Statistical Center of Iran (2016), the province consists of 27 counties and 54 cities, and the total population is 4,700,000 [42]. It is one of the provinces that has been greatly affected by COVID-19 due to its business relations with other countries and daily work migrations across this province. Like many provinces of Iran, it has left behind five COVID-19 peaks. Due to the absence of effective policies and planning measures, the province is exposed to many hazards, especially dust, environmental changes, and climate change. Some parts of the province are more deprived, and there are economic and social inequalities between cities and villages and between different urban areas [76]. These inequalities, at the time of adverse events, result in varying degrees of vulnerability and resilience among different groups.Fig. 1 Location of khuzestan province.
Fig. 1
According to the statistics of 2021, the marginal population of Khuzestan Province is 1,747,739 persons, accounting for 37% of the province's population. As mentioned, the marginal population lives in the cities, especially Ahvaz. A large part of the population living in marginal areas are people who migrated to cities due to social and spatial inequalities [77].
3.2 Data
This research relies on secondary data and primary data obtained via expert surveys.
The dataset in this study included social vulnerability data and COVID-19 data. The social vulnerability data were collected from the 2016 Census of Khuzestan Province, the Statistical Yearbook of Khuzestan Province (2017), and the economic, social and cultural report of Khuzestan Province (2016–2017). As this study aimed to assess vulnerability at the county scale, the indicators were measured for different counties across the province. The data collected for the counties were used as the raw matrix in the decision-making model. In the first stage, the indicators with different (incremental and decremental) scales and different intervals were standardized.
The COVID-19 data were recorded separately for cities and villages by Ahvaz Jundishapur University of Medical Sciences, which is theCOVID-19 management center in the province. The data for the cities and villages were normalized in the form of the COVID-19 infection rate per 1000 people for each county. Considering the number of COVID-19 peaks and given the data accessibility issues, the statistics of COVID-19 patients were prepared for a year from October 2020 to September 2021. We used a longitudinal approacc [1],.
3.3 Research indicators
Indicators are statistical tools applied to describe complicated social concepts in scientific analysis. Scientific and accurate indicators that account for a wide range of individual and group differences are the foundation of social vulnerability research. Due to the complexity and dynamic nature of the social vulnerability, there are multiple indicators in this scope. Therefore researchers have employed different indicators based on the needs of their projects. The crucial point is to identify those key indicators that accurately indicate changes.
Context and local conditions are critical in the selection process of social vulnerability indicators. In the United States, one of the indicators is the percentage of foreign-language speakers [10]. Muslim communities have been identified as vulnerable groups in developing countries such as India [35], whereas in Iran, households supported by Relief Foundationsappear to be an indicator of household living conditions; relief foundations are institutions set up in some countries to identify and assist vulnerable families. Therefore, the families and individuals whom these institutions support do not have the appropriate socio-economic conditions to deal with risks [78].
Fatemi et al. [79] have identified the most important social vulnerability indicators in Iran, including gender, demographic features, socio-economic conditions, disability and special needs, and public resource availability. They stated that these indicators provide an accurate assessment of society's vulnerability to technological hazards and man-made disasters, particularly in developing countries such as Iran.
Based on the existing literature and considering the context-specific conditions, the indicators listed in Table 1 were used in this study. A brief description of each indicator is provided in the remainder of this section.Table 1 Indicators and variables of social vulnerability.
Table 1Indicator Variable Effect
Age Rate of the elderly over 65 years Increasing
Economic Rate of population dependency Increasing
The per capita income Decreasing
The unemployment rate Increasing
Education Total literacy rate Decreasing
Female literacy rate Decreasing
Population Population density index Increasing
Female population Increasing
Households dimension Increasing
Female-headed households Increasing
Rural population Increasing
Rural households Increasing
Social Security Households supported by the Relief Committee Increasing
Rate of pension households Increasing
Residence Number of inhabited villages Increasing
Rate of rural households with safe water Decreasing
Number of villages per 100 square kilometers Increasing
Rate of villages under 20 households Increasing
Rate of residential units with two households and more Increasing
Income and poverty are critical drivers in the field of social vulnerability. Income can affect other indicators such as education, job type, overcrowding, vehicle and homeownership, and unemployment. Additionally, low education levels contribute to poverty, overcrowding, unemployment, income inequality, and marginalization [80]. Women face greater limits and have less access to resources than men, especially in developing countries. These lead to more poverty and risk vulnerability [81]. Increase in female-headed households can also increase social vulnerability [5] [82]. Weak socio-economic conditions and the quality of housing units show the state of public health affected by disasters. Unemployment is associated with an increase in vulnerability during times of crisis and disaster [79]. Poverty and lack of access to resources affect the vulnerability of individuals and households. Unemployment exacerbates the difficulty of low-income households remaining quarantined, thereby increasing their vulnerability. Those with low socio-economic conditions may not be able to afford to buy disposable face masks. Moreover, they may also be unable to wash reusable cloth masks and rely on public laundry, which increases the exposure risk [1]. Education level is directly related to risk awareness and comprehension. Education plays a significant role in reducing vulnerability since it has an effect on people's awareness and understanding of disasters. Individuals with a low degree of education frequently face economic difficulties. Additionally, low levels of education decrease an individual's sense of control over health choices, which might be associated with poor health outcomes [13]. Houses that are unsafe and crowded make social distancing measures, health care, and proper access to water ineffective. Thus, crowded households with large families sharing rooms may be unsuitable for social isolation and social distancing, increasing the risk of COVID-19 transmission at home [83]. Social vulnerability is significantly related to demographic characteristics such as female population, age, and households with a disabled member. In addition, children under the age of 14 and people over the age of 65 (at opposite ends of the age range) have a relatively limited potential for self-protection during adverse events [84]. The elderly are also likely to be more vulnerable to adverse events. Due to their physical state and lack of adequate immunological responses, they face difficulties in coping with and responding to adverse events, including pandemics. Woolf et al. [85] noted that being 65 or older is a significant risk factor for COVID-19 mortality [85]. A high rate of dependency also leads to increased social vulnerability [38]. The dependency ratio is calculated based on the percentage of the population under the age of 16 and over the age of 65, along with people with physical disabilities, relative to the population between the ages of 16 and 65. Indeed, this is the ratio of unemployed to employed people, which reflects the pressures on the employed people in a society. Households with a significant number of dependents confront numerous difficulties due to their limited financial opportunities [86]. The households dimension index quantifies the impact of poor housing conditions on vulnerability [87]. This is because larger households will have a greater number of dependent members (economically inactive) [88].
Population density could be a risk factor by increasing risk exposure. When natural or human hazards occur, higher population densities could result in increased losses due to inefficient management and planning [89,90]. In developing country cities, population density is also considered an important factor in the outbreak of COVID-19, and avoiding situations with higher population densities is an essential requirement for limiting the prevalence of COVID-19 [91]. Moreover, an increase in the number of inhabited villages within a geographical region complicates service delivery and relief activities, which may result in increased vulnerability. The number of villages per 100 square kilometers frequently challenges the provision of effective products and services in rural areas, resulting in rural vulnerability and limited access to sanitation [35]. Rural populations in the Khuzestan province have insufficient access to public services, health care, and infrastructure. Furthermore, rural households face undesirable employment, income, and education conditions. Dintwa et al. [92] stated that rural areas in Botswana have a greater vulnerability ratio and a lower capacity for risk management than urban areas [92].
Table 1. Indicators and variables developed to assess the social vulnerability of the counties in Khuzestan province.
3.4 The analysis process
The overall process is shown in Fig. 2 . First, the sum of indicators for each county was calculated using the decision-making model as a variable in the correlation analysis. The analysis was performed in two stages. In the first stage we ranked the 27 counties in Khuzestan province based on the 19 indicators listed in Table 1. In the second stage, the final result of the ranking model is used as the first variable, and the rate of COVID-19 cases per 1000 persons is used as the second variable. Indeed, counties and indicators were included as options and criteria in the raw matrix, respectively, and then prioritization and ranking were performed. We employed the complex proportional assessment (COPRAS) method, which is further discussed later, to rank the counties. In addition, the decision-making trial and evaluation laboratory (DEMATEL) method was used to determine the indicators' weights. We asked ten subject-matter experts to complete the DEMATEL questionnaire. Employing non-experts in decision-making processes creates complications and decreases efficiency. Therefore, the group of decision-makers included managers and researchers with expertise in geography, urban planning, and crisis management. They have been working on the subject for over a decade and are well aware of effective variables and indicators of social vulnerability. We purposefully selected specialists through face-to-face meetings and in-depth discussions with relevant individuals. It should be noted that during the three months, five questionnaires were physically distributed in the area, and five questionnaires were sent online to related researchers.Fig. 2 Flowchart of methods used for the purpose of this research.
Fig. 2
In the second stage, the Pearson correlation was used to determine the relationship between the integrated social vulnerability index and the rate of COVID-19 cases. The Pearson correlation has been previously utilized to evaluate the relationship between social vulnerability and COVID-19 [35]. The relationship between social vulnerability and the rate of COVID-19 cases in this study is correlational, indicating whether the rate of COVID-19 cases is higher in the counties with a high level of vulnerability. The Pearson correlation coefficient is used to determine the correlation between two variables when both are on a ratio scale and interval scale. This study's data are on a ratio scale.
According to Alkan and Kahraman [93]; MCDM procedures efficiently resolve complicated situations using a variety of criteria. Due to the nature of the social vulnerability, using multi-criteria decision making is a recurring method [[94], [95], [96], [97], [98]] [99]. Multi-criteria decision making methods such as analytic hierarchy process (AHP), analytical network process (ANP), best-worst method (BWM), the technique for order of preference by similarity to ideal solution (TOPSIS), and vlse kriterijumsk optimizacija kompromisno resenje (VIKOR) have been exploited in COVID-19 studies [[100], [101], [102], [103], [104]][105]. For instance, Malakar [4] assessed social vulnerability to COVID-19 using MCDM methodologies (fuzzy AHP and fuzzy TOPSIS).
The use of mixed methods is a new approach in the MCDM and MCDA [106]. So, DEMATEL approach for weighting criteria was combined with COPRAS method for ranking choices as will be further discussed below [107,108] [109].
Geographically weighted regression (GWR) and exploratory factor analysis (EFA) have been utilized in related studies. GWR was not practicable due to the small number of units (county), and in EFA, the summary and classification of indicators encountered mistakes. The advantage of MCDM analysis is that it provides acceptable results even when the number of available options is limited. Moreover, variations in the relative importance of the indicators result in different outcomes.
DEMATEL Method.
DEMATEL method is implemented in steps as follows:Step 1 Forming direct connection matrix
To form a direct connection matrix, experts' opinions are applied, and then, to form the total matrix, the opinions of all experts are taken into account. Therefore, a direct connection matrix is formed using the verbal concepts defined in Table 2 .Table 2 Quantitative values equivalent to the verbal concepts of the initial matrix.
Table 2Verbal Concepts Quantitative Values
No Impact 0
Very little impact 1
Low impact 2
Strong Impact 3
Very strong impact 4
Step 2 Normalizing the direct connection matrix:
To normalize the matrix, (1), (2) are employed:(1) Hij=zijr
R is obtained from the following one:(2) r=max1≤i≤n
Step 3 Calculating the total connection matrix:
After calculating the above matrices, the fuzzy total connection matrix is obtained according to Formula (3):(3) T=limk→+∞(H1+H2+…+Hk)=H×(I−H)−1
Where, I is the identity matrix in formula (3).
Step 4 Calculating the sum of the rows and columns of the matrix
The sum of rows and columns is obtained according to (4), (5):(4) (D)n×1=[∑j=1nTij]n×1
(5) (R)1×n=[∑i=1nTij]1×n
Where, D and R are n * 1 and 1 * n matrices, respectively.
Step 5 Calculating the weights of influence and the effectiveness of the criteria
The relative importance of the criteria is calculated using formula (6):(6) wj=[(Di+Ri)2+(Di−Ri)2]12
Step 6 Normalizing the weights of the criteria
The weights obtained from the previous step can be normalized using formula (7) (LIU & WU, 2004)(7) W‾j=Wj∑j=1nWj
COPRAS Method.
The COPRAS method was first proposed in 1996 by Zavadskas and Kaklauskas at Vilnius Gediminas Technical University [110]. The COPRAS method is implemented in steps as follows:
Step 1 Forming a matrix
The COPRAS method begins by defining the weights for each criterion. The choice matrix is a two-dimensional matrix that contains both options and criteria. Additionally, the matrix contains a column indicating the weight assigned to each criterion. To complete the matrix values, we calculated the value of each criterion independently for each option and entered it in the appropriate location.
Step 2 Forming a collective decision matrix
This phase entails the aggregation of opinions, which can be accomplished using the arithmetic mean.
Step 3 Forming a weighted matrix
To weigh the decision-making matrix, multiply the values of each option by their weight and divide by their sum. The weighted decision-making matrix is constructed using the following formula:(8) dij=qi∑j=1nxijxij
Where, qi is the weight assigned to each criterion, and xij is the value assigned to each option for each criterion.
Step 4 Calculating the value of positive and negative criteria
Then, the positive and negative criteria are discovered and separated. While increasing the value of a positive or consistent criterion raises its desirability, increasing the value of a negative criterion diminishes its desirability. After determining the positive and negative criteria, it is necessary to establish their final values. Formula (9) is used to calculate the indexes Sj + and Sj-for this purpose.(9) dijSj−=∑zi=−dijSj+=∑zi=+dij
Step 5 Calculating the final value of options
The algebraic sum of positive and negative values is calculated independently using Formula (10). Formula (10) is used to determine the final value of each option (Q) in the final step:(10) Qj=Sj++smin−∑j−1nsj−sj−∑j−1nsmin−smin−=sj++∑i=1nsj−sj−∑i=1n1sj−
Sj + is the algebraic total of the positive requirements for each option in Formula 10, whereas Sj - is the algebraic sum of the negative criteria for each option. In this section, the number 1 is divided by Sj- and then the value of Q for each option is computed using the preceding formula. The Q value represents the relative importance and weight of each option in terms of the criteria. A high value indicates the significance and desirability of the majority of alternatives.
4 Results
As mentioned in the previous section, the weights were determined using DEMATEL method. The weights acquired are shown in Table 3 . The population density index is the most significantly weighted, followed by the households dimension, unemployment rate, female-headed households, and female population. These weights show the indicators' priority and significance to experts. As each indicator's weight increases, its impact on the county's social vulnerability increases accordingly.Table 3 Weights determined by DEMATEL Method.
Table 3Indicator Weight
Population Density 0.0713
Households Dimension 0.0702
Unemployment Rate 0.0670
Female-headed Households 0.0655
Rural Households 0.0628
Rate of Pension Households 0.0621
Households Supported by the Relief Committee 0.0599
Rate of Residential Units with two Households and More 0.0584
Literacy Rate 0.0541
Rate of Population Dependency 0.0493
Rural Population Density 0.0489
Elderly over 65 Years 0.0486
Number of villages per 100 Square Kilometers 0.0469
Number of Inhabited Villages 0.0465
Rate of Rural Households with Safe Water 0.0426
Rate of villages under 20 Households 0.0386
The per capita income 0.0383
Female Literacy Rate 0.0374
Female Population 0.0319
The generated weights were used in the COPRAS model. The COPRAS model divides indicators into two categories: positive and negative. Positive signs contribute to an increase in vulnerability, whereas negative indicators contribute to a decrease in vulnerability. The total literacy rate, per capita income, the proportion of rural households with safe water, and the female literacy rate were exerted as negative indicators in this study, while 15 additional factors were utilized as positive indicators in the COPRAS model. The COPRAS model's final output is shown in Table 4 . The most vulnerable county is Ahvaz, followed by Indika, Dezful, Izeh, Baghmalek, Shadegan, Lali, Ramhormoz, Shushtar, Shush, Karun, Hamidiyeh, Dashte Azadegan, Behbahan, Abadan, Andimeshk, Bavi, Bandar Mahshahr, Ramshir, Masjed Soleiman, Gotvand, Hoveyzeh, Aghajari, Khorramshahr, Haftkol, Omidieh, and Hindijan.Table 4 Ranking of the Counties based on Social Vulnerability Indicators.
Table 4County Q Rank
Ahvaz 0.0584 1
Andika 0.0489 2
Dezful 0.0477 3
Izeh 0.0466 4
Baghmalek 0.0418 5
Shadegan 0.0416 6
Lali 0.0405 7
Ramhormoz 0.0404 8
Shushtar 0.0384 9
Shush 0.0383 10
Karun 0.0382 11
Hamidiyeh 0.0374 12
Dashte-Azadegan 0.0357 13
Behbahan 0.0355 14
Abadan 0.0346 15
Andimeshk 0.0346 16
Bavy 0.0345 17
Bandar-e-Mahshahr 0.0338 18
Ramshir 0.0337 19
Masjed-Soleiman 0.0320 20
Gotvand 0.0317 21
Hoveyzeh 0.0315 22
Aghajari 0.0310 23
Khorramshahr 0.0308 24
Haftkel 0.0292 25
Omidiyeh 0.0270 26
Hendijan 0.0263 27
According to the integrated vulnerability index, the counties of Khuzestan province are classified into five classes (Fig. 3 ). Ahvaz is the first-level county. Andika, Dezful, and Izeh are the second level. The counties of Baghmalek, Ramhormoz, Shadegan, and Lali are on the third level. Behbahan, Ramshir, Bandar-e-Mahshahr, Abadan, Karun, Bavy, Hamidiyeh, Shushtar, Dashte-Azadegan, Shush, and Andimeshk are located on the fourth level. Haftkel, Masjed-Soleiman, Gotvand, Hoveyzeh, Omidiyeh, Aghajari, Khorramshahr, and Hendijan comprise the last level.Fig. 3 Spatial display of social vulnerability in the counties of khuzestan province.
Fig. 3
The COVID-19 data of Khuzestan counties were utilized to investigate the relationship between vulnerability and the rate of COVID-19 cases. The raw COVID-19 data and the rate of cases per 1000 people are shown in Table 5 .Table 5 COVID-19 data in counties of khuzestan province.
Table 5County Rate of Covid-19 Cases Ratio per 1000
Omidiyeh 7390 80
Andika 2553 54
Andimeshk 11,111 65
Ahvaz 78,312 60
Izeh 11,920 60
Abadan 24,442 82
Aghajari 2121 120
Baghmalek 7390 70
Bavy 5189 54
Bandar-e-Mahshahr 15,853 54
Behbahan 22,318 124
Hamidiyeh 2152 40
Khorramshahr 16,259 95
Dezful 29,096 66
Dashte-Azadegan 7862 73
Ramshir 3899 72
Ramhormoz 10,694 94
Shadegan 12,002 87
Shush 5956 29
Shushtar 23,198 121
Karun 4350 41
Gotvand 5178 79
Lali 2770 73
Msjed-Soleiman 11,536 102
Haftkel 3729 169
Hendijan 3668 95
Hoveyzeh 1547 40
According to the results of the Pearson correlation test (Table 6 ), there is no statistically significant correlation between the integrated social vulnerability index and the rate of COVID-19 cases, as the sig value exceeds 0.05. Fig. 4 shows the county-level social vulnerability and the rate of COVID-19 cases in Khuzestan province.Table 6 Pearson correlation between social vulnerability and the rate of COVID-19 cases.
Table 6 Covid-19 Cases Rate (per 1000 people)
Integrated index of social vulnerability Pearson Correlation −.355
Sig. (2-tailed) .069
N 27
Fig. 4 Distribution of social vulnerability and the rate of COVID-19 cases in the counties of Khuzestan province.
Fig. 4
5 Discussion
Assessment and comprehension of the impact of COVID-19 on social vulnerability at the local and regional levels will help develop resilience programs [34]. Besides, addressing inequality is the first step in improving sustainability and risk management approaches during COVID-19 [73]. The purpose of this study was to determine social vulnerability in the counties of Khuzestan province and to investigate its relationship to the COVID-19 cases rate. To address the first research objective, the multi-criteria decision-making approach was used for ranking the counties and an integrated social vulnerability index was developed for each county According to the findings of the multi-criteria decision-making process, Ahvaz county (the province's capital) and counties in the province's east have the highest levels of social vulnerability. Additionally, the counties' conditions varies in terms of COVID-19 cases. To address the second objective of the research, the Pearson correlation was used The most notable finding is that no relationship exists between counties' level of social vulnerability and the rate of COVID-19 cases. This indicates that COVID-19 spread does not correlate with the rate of social vulnerability. Ahvaz county ranked first in terms of social vulnerability. Ahvaz County's vulnerability is exacerbated byits high population density and a high share of poor and marginalized neighborhoods. Indeed, while the county has a high proportion of urban residents, a significant proportion of them live in poverty. These residents have migrated from other villages and cities to the province. Furthermore, Ahvaz city, with 20 marginalized neighborhoods, has the most marginalized areas in Iran. These marginalized neighborhoods are characterized by the lack of water and energy infrastructure, inadequate sanitation, high unemployment rate, lack of educational services, and the lack of healthcare facilities. Besides, most of the residents in these neighborhoods are engaged in informal jobs, including people who work at home or on the street, daily wage workers, and service workers who work in other people's houses [31]. COVID-19 has directly and severely affected the employees and workers in this sector [111]. Omidiji et al. [112] stated that the COVID-19 virus increases the vulnerability of people from disadvantaged classes, especially in informal settlements and slums. Due to the significant rural population in the northeastern counties of Khuzestan province, the level of social vulnerability has increased since villagers in the province face worse conditions in terms of employment, access to services and facilities, and exposure to hazards (especially natural hazards). As a result of the large number of villages in some counties, such as Indika, Bagh-Malek, and Dezful, as well as suburbs in others, like Ahvaz, Mahshahr, and Abadan, there is no significant difference in social vulnerability index scores between the counties.
Our findings contradict Neelon et al. [1]; Khazanchi et al. [19]; and Karaye & Horney [10] in the United States, as well as Sarkar & Chouhan [35] in India. They discovered that counties that were more socially vulnerable had a higher rate of COVID-19 cases. Social vulnerability varies according to context. These contradictory results could be attributed to the varying socioeconomic conditions in different countries. For example, in the United States, language groups and minorities (blacks) have worse conditions and a higher rate of COVID-19 [18,[24], [113], [114]]. Whereas, in developing countries such as India, more low-income households live in harsher conditions than in Iran [35] [36]. In the case of Khuzestan province, it was found that all ethnic groups face similar living conditions and comparable levels of social vulnerability.
Additionally, one of the distinctions between this research and others is the list of indicators used for analysis. The research indicators have been chosen in accordance with the Iranian context and considering data availability. Differences in the indicators lead to variations in the outcomes. Inadequate data access, as well as the complexity associated with calculating social vulnerability indicators, are among the challenges confronting social vulnerability studies in Iran [79]. COVID-19 first spread among groups with a higher economic and social status in the case of Iran, especially in Khuzestan Province. Thus, the neighborhoods and urban areas with higher economic and social status reported a higher number of COVID-19 patients [115,116]. Previous studies have also reported a higher rate of Covid-19 among people with middle and high income in richer countries with higher interpersonal interactionsat work and more frequent trips inside and outside the country [117,118].
The major cities and provincial capitals were the first to be hit with COVID-19 in Iran. It then gradually spread to surrounding cities and villages. Accordinglyection rates were initially high in the capital of Khuzestan province but quickly grew in all villages and cities within a few months.
A review of the experiences and the available data indicate that the marginal and deprived groups, especially in Khuzestan as a multi-hazard province, and those who had less economic and social power have suffered the most damage from natural disasters such as floods and earthquakes. Although this research indicates that social vulnerability does not result in increased COVID-19 rates, the COVID-19 outbreak has impacted vulnerable areas, including suburban neighborhoods with informal jobs, residents of worn-out neighborhoods, and villagers whose livelihoods are reliant on urban areas.
It has been also well-recognized that vulnerable people have fewer opportunities to work remotely [119] and their jobs mostly require physical presence. According to Das et al. [60]; residents in slums and informal settlements worldwide are the most vulnerable to COVID-19. In general, the social vulnerability of disadvantaged groups prevents them from complying with social distancing regulations [73] because these groups do not have enough income and savings and are forced to go to work or work on the streets to sustain their livelihood. Previous studies have shown that income is a key factor in compliance with social distancing measures [120].
The COVID-19 outbreak has created many challenges for people in poor areas and vulnerable groups in Iran and Khuzestan Province. Marginal areas and urban slums sometimes face many environmental health problems due to distance from urban services or poor urban infrastructure. Due to the lack of sanitary items such as masks, gloves, and disinfectants and the high price of these items, the poor, the needy, and disadvantaged social groups cannot access them easily. Socially vulnerable groups such as street vendors, kids involved in child labor, beggars, garbage collectors, drug addicts, and homeless people are more likely to be exposed to the virus and spread it among other community members. Due to the high costs of medical services and insurance coverage problems, the deprived and needy classes usually have fewer visits to the doctor than the rich. It makes them more vulnerable, especially against COVID-19.
6 Conclusion
This research is one of the first in Iran to examine links between social vulnerability and COVID-19. The social vulnerability was measured quantitatively in 27 counties of Khuzestan province, and then its relationship with the COVID-19 rate was explored. The findings indicate that counties' social vulnerability varies little according to their rural and suburban population densities, and counties with a high total population density and a low rural population density are more vulnerable. There is a non-significant negative correlation between the level of social vulnerability in counties and the COVID-19 rate.
The findings demonstrate that COVID-19 is a complex issue that varies according to various factors, including management and planning policies, social behaviors, and participation in coping programs. Other areas of vulnerability can be assessed by utilizing decision-making models and indicators, particularly residential indicators. The research findings can also be applied to administration and policy-making, providing managers with an insights on the impact of residents' socio-economic conditions and COVID-19 rates. The rate of COVID-19 cases in the province is unrelated to the integrated social vulnerability index, and all counties must adhere to protocols and health regulations. Given that quarantine conditions and mobility restrictions have been implemented in all counties, those with a higher degree of social vulnerability require more attention. The province's authorities should provide special support packages to such groups. Among the populations targeted by support programs are families covered by institutions, working children, drug addicts, street sweepers, the homeless, female-headed households, informal workers, and day laborers. According to the research findings, specific support measures should be implemented for counties with high rates of rural population, such as Andika and Izeh, as well as counties with high rates of informal settlements, such as Ahvaz, Mahshahr, Abadan, and Khorramshahr. In the counties where the number and distribution of settlements are high, and access is difficult, the provision of sanitary items and medical equipment related to COVID-19, and the establishment of temporary health monitoring centers are among the measures that are needed to control new waves of the pandemic.
Since this study adopted a spatial and location-based perspective and addressed challenges faced by deprived and marginal areas, the following preventive and support measures could be taken into account:- Adopting appropriate decision-making process for the accurate identification of counties, slums, and the outskirts that need to be prioritized in efforts aimed at controlling the COVID-19 infection,
- Making effective context-sensitive decisions to provide support and health services (e.g., provision of disinfection equipment, masks, gloves, and disinfectants, payment of subsistence aid, and distribution of health items and health aid) for families living in poor neighborhoods and on the outskirts of counties,
- Increasing spatial justice and expanding the coverage of urban services to residential areas with less access to municipal services.
- Targeted subsidy payments to low-income groups, especially female heads of households and people who are not covered by social and medical insurance.
The findings of this study can contribute to the growing knowledge of social vulnerability. The study used objective indicators and existing data to measure social vulnerability and the COVID-19 incidence rate. Using objective data results in fewer errors than self-reported and subjective data. The present study also measured social vulnerability as a composite index and addressed it as a variable. It also addressed residential distribution indicators (population distribution) as one of the indicators for measuring social vulnerability because the spread of settlements and population makes it difficult to access services, especially in rural areas. Moreover, like other related research projects, this study reflected social inequalities and deprivations that existed before the COVID-19 crisis [69].
It should be acknowledged that this research had some limitations. First, it was impossible to evaluate the relationship between social vulnerability and the COVID-19 rate across all of the province's cities and rural areas due to the difficulty of acquiring data on social vulnerability per city and village. Such detailed analysis could have provided a better analysis of the vulnerability conditions. Second, not all urban and rural areas have equal access to COVID-19 test laboratories. Accordingly, the number of reported cases in some areas may be less than the real numbers. Third, and related to the previous point, COVID-19 test reports contain some statistical inaccuracies. Fourth, it was not possible to access the land use layers for a detailed examination of the level of access to services, especially healthcare services. Fifth, it was not possible to separate the data into urban and rural parts and measure the relationship between the research variables for rural and urban areas separately. Finally, access to information at the individual level was not possible. The condition of infected individuals is a better indicator of the relationship between socio-economic status and COVID-19 cases.
It is recommended that future studies examine the relationship between social vulnerability and COVID-19 mortality rates at more granular levels. Social vulnerability should be assessed using variables such as the prevalence of informal employment, the population of informal settlements, and the rate of car ownership. To obtain more accurate measurements, the COVID-19 rate should be investigated separately for urban and rural populations and based on slum and suburb locations. The socio-economic aspects and access levels are evaluated more favorably at smaller scales [113].
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.
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| 0 | PMC9747688 | NO-CC CODE | 2022-12-15 23:23:24 | no | Int J Disaster Risk Reduct. 2023 Jan 14; 84:103495 | utf-8 | Int J Disaster Risk Reduct | 2,022 | 10.1016/j.ijdrr.2022.103495 | oa_other |
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Int J Disaster Risk Reduct
Int J Disaster Risk Reduct
International Journal of Disaster Risk Reduction
2212-4209
Published by Elsevier Ltd.
S2212-4209(22)00708-7
10.1016/j.ijdrr.2022.103489
103489
Article
Passenger's perception about city buses in the aftermath of COVID 19: Experience from Guwahati city, India
Deb Saikat a∗
Hinge Gilbert b
a Civil Engineering Programme, Assam Down Town University, Guwahati, Assam, India
b Department of Civil Engineering, National Institute of Technology, Durgapur, West Bengal, India
∗ Corresponding author. Civil Engineering Programme, Assam Downtown University, Assam, 781026, India.
14 12 2022
1 2 2023
14 12 2022
85 103489103489
3 6 2022
7 12 2022
7 12 2022
© 2022 Published by Elsevier Ltd.
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 COVID-19 epidemic has affected public transport in various cities worldwide, including Guwahati city in India, where a 59.09% decline in the ridership of city bus services occurred in autumn 2021. The present work aims to investigate the impact of COVID-19 on travelers' perception and identify the parameters associated with the user's dissatisfaction for improving bus service in Guwahati city. In addition, the study also estimated the revenue loss of bus services due to this pandemic. This was carried out based on survey data from travelers in pre-covid (January 2019) situation, unlocked with 50% seating capacity (November 2020), and unlocked with 100% seat capacity plus some limited amount of standee (January 2021) situation. Results showed an increase in the number of users' priorities in post covid compared to pre covid conditions. Factors such as comfort, fairness, reliability & convenience, and safety are the priority areas of users' pre covid. Whereas bus service attribute such as vehicle condition & hygiene emerged as an additional priority of users post covid. Unfortunately, the bus service in the city performed poorly in terms of hygiene, leading to the shifting of the user to other modes of transport. The poor condition of the vehicles is another major factor that made the users to discard the bus service. This led to huge financial losses of the public transit authorities. The cost analysis result showed that the city bus operators faced a financial loss due to the COVID19 outbreak. The average wage of the drivers reduced from 780 Rs./day to 339 Rs./day in the first unlock phase and 476 Rs./day in the second unlock phase. The present study discusses the introduction of the new route in the city, regular cleaning, regular servicing of the buses, and other recommendations to improve the bus service in Guwahati city.
Graphical abstract
Image 1
Keywords
COVID19
Guwahati
Perception
Cost analysis
Bus service
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pmc1 Introduction
In December 2019, the outbreak of Coronavirus disease, also known as COVID-19 began in Wuhan, China, and spread rapidly across many countries. The outbreak of the disease was declared as a pandemic by the World Health Organization in March 2020, with China, Italy, Spain, India, and the United States being the most hit. While other epidemics such as Ebola, SARS, or MERS occurred in previous decades, the global economy and society were not confronted with a significant and detrimental impact as caused by covid 19 [1,2]. Many countries have taken various measures to discourage physical interaction to delay the spread of the virus. These steps can be defined as ‘social distancing’ and are particularly effective for diseases such as COVID-19 that are transferred by coughing or sneezing or even exhale of air droplet by the infected person [3]. As a result of this outbreak, many people are temporarily unemployed or have a job from home. This decreased travel demand led to huge reductions in car traffic and public transport in many countries [4,5]. The COVID-19 epidemic has resulted in a worldwide drop in transportation ridership. Urban travel worldwide has fallen, but not consistently for all modes: as survey-based data demonstrate, public transit has been the most affected among the several other modes of urban transportation [6]. This is, of course, just a temporary situation, and we would assume that the demand for outside the home and travel will increase again when the regulation is lifted. At present, the social distancing norms are started to be relaxed, but recent reports of different COVID-19 variants have increased concern that could lead to new waves of social distance in the near future. Moreover, when social distancing laws no longer apply impacting engagement in events and travel, there can still be concerns of social interaction because of the fear of the COVID-19. The government-imposed quarantine measures have significantly reduced travel opportunities across the world and within the country also [7]. Eventually, it will lead to more use of the private vehicles, which will further deteriorate the prevailing traffic conditions. And it is expected that the ridership of the public transport will further reduce with the occurrence of a new wave of COVID-19.
Therefore, it felt necessary to investigate the loss of ridership due to the Covid-19 so that necessary steps could be taken to increase the ridership of the public transport. To increase the ridership, it is required for the policy makers to understand what users are expecting from the transit service and whether there are any differences in the perception of the users between pre-covid and post covid situation. Thus, for successful policy creation and management of transport systems, a clear understanding of the people's travel habits and perceptions of public transit modes during COVID-19 outbreak are required so that necessary steps could be taken to improve the service quality of public transit with respect to this recent Corona situation. The objectives of this study are set as below:1 To estimate the ridership loss and revenue loss of the city bus service due to the COVID-19 situation.
2 To investigate the users' perception of public transport service in post covid situation and compare it with the pre-covid situation.
3 Understanding the importance of different parameters associated with the dissatisfaction of the users.
2 Literature review
The speedy transmission of the COVID-19 virus, which in several weeks has become an international epidemic, has now been due to the hypermobility in our present way of living, globalization, and Wuhan's connectedness and accessibility [8]. The COVID-19 pandemic has since evolved quickly, ranging from a huge fall in air travel to a never before seen increases in teleworking and its implications on lifestyles and travel around the world [1,8]. Public transportation are most affected mode of transport among the other transportation modes [6]. In some cases, this was accompanied by a reduced service supply and aggravated by the perception that public transport is a more risky option than private or personal transport, due to the closer contact between the individuals in vehicles and as well as stations [9].
Millions of people utilize public transport vehicles every day; they often carry passengers above their capacity, particularly during peak time in morning and evening. This could help to transmit infections among users of public transport [9]. A number of articles have found a strong correlation between early stage mobility data for human beings and the spread of viruses [7] and travel restrictions have played an important role in slowing or minimizing virus spread through various cities. In the course of COVID-19, epidemiologists encourage social distance, which means they should be roughly six feet (or 2 m) or more from one other, like they did in past epidemics and pandemics. Clearly, such measure contradicts the idea of public transport. In view of the fact discussed above, several countries have advised its citizens to avoid public transportation as much as possible. The policy regarding the public transportation in different countries are given in Table 1 :Table 1 The policy regarding the public transportation in different countries in Covid period.
Table 1Country Policy
United Kingdom Avoiding public transportation completely whenever possible and using of alternative modes were encouraged, permitted the use of public transport for essential travel only [9].
In the later stage physical distancing is maintained in the bus stops by marking 2 m spot for passenger to wait. In London many major city-center roads was made closed for the cars to provide more space for pedestrians, cyclists and buses to support the recovery process [10].
Australia Buses and trains were made to run with a considerably lower number passengers than the seating capacity [9].
In the later stage bus and trains were made to run with seating capacity by mandating face mask. Hand sanitizer were made available at all bus and train stations [10].
China During the initial phase, Wuhan metro was shut down for two months, Subway system in Beijing was strictly monitored for non compliance of the face masks. Bus capacity is lowered to only 50% in certain places in China, allowing all bus seats to be used while cameras monitor compliance with their capacity [9].
India Completely closed the public transport system during the first Phase of Covid 19 [11]
Just after the lockdown the public transport resumes with a lower occupancy and mandatory use of face mask. Gradually all it was tried to bring the public transport back to normal by Establish protocols and enforcement measures [12].
Spain Completely closed during initial phase, in some of the cities public transport resumes after the initial lockdown with 30–50% occupancy, mandatory use of face mask. To offset these capacity restrictions, the city is installing emergency bike lanes and develop an inexpensive bicycle model to be manufactured locally as part of the city's economic recovery plan [10]
These policies regarding the public transport have greatly caused serious financial loses of the public transport. For example, Munawar et al. [13] found that the transport sector in the Australia is facing a serious financial loss as the mode share of public transport has dropped nearly 80%. In public transit, people are at highest risk of infectious diseases if they settle or stand closer [14]. These vehicles can be a considerable source of micro-organisms if passengers are coughing and sneezing without covering their mouths [14]. According to epidemiology research, social distancing, internal cleaning and sanitation of public transport vehicles are one of the usual measures provided by the authorities to stop the spread of the micro-organism in the public transport vehicles. In many cities public transport vehicles are disinfected regularly and social distancing norms are followed by allowing lesser number of passengers. It has been found that, the spread of the virus could be controlled with an obligatory usage of masks at public space [9] and this has been reflected in the policy making of public transport in different countries during the Covid-19 outbreak. While it has been found that the use of crowded public transport vehicles may be associated with the acquisition of infectious diseases, these findings are not supportive of the effectiveness of the suspension of mass urban transport systems as a counter-pandemic in reducing or slowing the spread. This is because the risk of spread associated with public transport is relevantly lower than the risk associated with household exposure [15]. Moreover, the spread of the virus could be considerably reduced using the face mask as evident from the previous literatures. However, it is quite expected that choice riders of the public transport modes will shift to other modes preferably private vehicles if no measures have been taken to improve the service quality of public transport [16].
Covid 19 has also impacted the transport sector in India and the public transport are the most affected one which in terms affected a larger number of populations. This is increasingly important in rising economies like India, where a major proportion of society is captive of public transport. Most of the public transport users are found to prefer private vehicles over the public transport mode [4,17] and the recovery of users base of public transport will take longer time due to the fear of Covid 19 [18]. A move from public transport to other private transport modes, as the danger of infection is apparent higher, would worsen current problems of congestion, pollution and casualties within the urban areas due to large imbalances in demand and supplies of urban transport. Since the COVID-19 outbreak, limited findings of research [4,[17], [18], [19]] on the passenger transport system have been available to date and limit the possibility for a complete policymaking process. Therefore, it is necessary to understand users’ needs and expectation from the public transport in the current scenario. During the early stages of the outbreak, Zhang et al. [20] reported the reactions of people in Japan. Some other research focused on behavior changes and related interventions [7]. It can therefore be noted that only a few attempts have been made to monitor behavioral changes since the COVID-19 outbreak, in particular in the area of travel related activities.
From above discussion it is quite evident that after the pandemic also the ridership of public transport will continue to decrease unless serious measures are taken to drastically change the policies for public transport modes. Moreover, no studies till date have compared the pre-covid perception of the users with post-covid situation. This is important as this study will open a different dimension for the policy makers to explore how users’ perceptions are changing in this situation. It will help to adopt suitable policies to mitigate the situation.
3 Study area
Guwahati is selected as a study area for this work. The population of Guwahati is 957,352 as per 2011 Census. In Guwahati, among the registered vehicles, the numbers of two wheelers are found to be highest with a proportion of 52.5% followed by car with a proportion of 27.8% [21]. The proportion of the buses is found to be lowest with a percentage share of 2.7%. Moreover, the average annual growth rate of car and motorized two wheelers are 12.06% and 11.19% while the growth rate of buses is only 2.03% [21]. With the increase in the population of the city, travel demand of the city has increased enormously.
A passenger occupancy survey was carried out on October 2019 (pre-covid) using video photographic survey in different locations (mainly bus stops) of Guwahati city. The bus stops/locations were selected based on the stratified random sampling. In Guwahati, currently buses run on a total no of 16 bus routes. All the prominent bus stops along these routes were listed first.. In this way, a total number of 87 prominent bus stops were identified. From each bus route randomly 2 bus stops were selected for actual survey. The common bus stops across different routes were considered only single time So, a total number of 32 bus stops were considered for the survey. The survey was conducted for a period of 7 days from 7AM to 7PM. Only representative sample (15 min of survey data in each hour) is taken during the occupancy survey. From every location, the occupancy data for all the vehicle types were extracted from the videos taken. This data roughly gives an idea about the average occupancy of different class of motorized vehicles. A similar type of survey was also conducted on November 2021 to have an idea about the occupancy in post-covid situation. The details of the bus routes along with the selected bus stops for the survey is showing in Fig. 1 and Table 2 .Fig. 1 City bus routes in Guwahati.
Fig. 1
Table 2 Bus stops considered for the survey along different routes in Guwahati.
Table 2Bus Route number From (Bus stop no) To (Bus stop no) Via (Bus stop no) Bus stops/points considered for survey
1 26 5 25, 21, 20, 19, 34, 10, 9, 8, 7, 6 8, 21
2 18 5 19, 30, 34, 10, 12, 7, 6, 5 18, 34
3 28 5 19, 30, 34, 12, 8, 7 28, 12
4 5 24 7, 8, 12, 10, 34, 32, 33 32, 33
5 5 21 7, 8, 10, 34, 31, 20 5, 31
6 24 3 26, 28, 32, 34, 10, 9, 8, 7 9, 3
7 5 33 7, 12, 16, 22, 23 7, 22
8 4 33 7, 8, 9, 10, 34, 31, 19, 23 4, 23
12 33 17 24, 29, 4, 7, 8, 11, 13, 15 11, 17
18 4 26 26, 29 26, 29
19 19 5 16, 15, 13, 8, 7 13, 16
21 8 24 11, 13, 15, 19, 20, 23 20, 24
23 5 24 7, 8, 10, 34, 30, 19, 23 10, 30
24 8 1 2 1, 2
27 4 27 6, 7, 13, 21, 25 25, 27
29 5 24 6, 7, 14, 13, 19, 23 14, 19
The percentage share of different motorized modes in terms of total passengers carried in pre and post covid situation is shown in Fig. 2 . Among the motorized modes, 22% of the passengers use city buses, 29% use motorized two-wheeler (MTW), 31% use car and 17% use intermediate public transport (IPT) services. The mode share of the city buses stood at 9% after the COVID-19 relaxation and the mode share of private car and MTWs have considerable increased. It indicates a massive ridership decline of 59.09% for the city buses. For this reason, traffic congestion has become a part of the city post COVID situation. Therefore, it is essential to improve the service quality of city buses to attract users.Fig. 2 share of different motorized modes in terms of total passengers' carried in pre-covid and post-covid situation.
Fig. 2
Guwahati is a non-metro city. Apart from the IPT modes, city buses are only the public transportation mode available in the city. Therefore, city buses play an important role in transporting a large number of people within the city. A total road length of 171.6 km is covered by city bus route network in the city. Currently a total number of 753 buses are operated in the municipal area (based on the data collected from regional transport office). The ridership of the city buses is continuously reducing and recent break of the COVID-19 has tremendously affected the ridership base of the city buses. Due to spread of the COVID-19, Indian Govt. announced a complete lockdown for 21 days starting from 25th March 2020 [11]. But this lockdown was extended till 7th June 2020 due to the further spreading of the virus. The lockdown measures were started to be relaxed in a phased manner from 8th June 2020 [22]. And the city bus operation in Guwahati started from 16th August 2020 with only 50% seating capacity and with mandating all the COVID-19 protocols (social distancing, mandatory use of face masks etc.). The bus service resumed after nearly 144 days of complete halt. During this time bus operators faced a huge financial loss. After repeated objections from different transport authorities, finally, Assam Govt. allowed to carry passenger up to full seating capacity plus some restricted quantity of standee passenger (one third of seating capacity) on 9th October 2020 [23]. But after this measure also, users are reluctant to use the buses. In maximum of the cases buses remains empty. Therefore, it felt necessary to investigate how users are perceiving the bus service after the COVID-19 situation so that necessary measures could be taken to make the bus service attractive for the users.
4 Methodology
4.1 Data collection
Data were collected from both the primary and secondary sources. The data requirement for the study is given in Table 3 .Table 3 Data requirements for the study.
Table 3Data Category Parameters to be Collected Data Type Data Collection Technique
Revenue Losses of the buses Average daily revenue collection of buses Secondary source regional transport offices, and several private transport operators
Wages of drivers, ticket collectors and helpers Primary Survey By interviewing staffs of the buses
Fuel price and maintenance cost Secondary source regional transport offices, and several private transport operators
Users' Perception data – Primary Survey Questionnaire Survey
4.1.1 Data collection corresponding to revenue loss of the bus
Average daily revenue collection of the buses was collected by secondary sources (regional transport offices, and several private transport operators). Wages of the staffs, fuel prices and maintenance cost contributed to the expenditure of the buses. In the city buses in Guwahati apart from the driver, one ticket collector and one helper are assigned. The wages of these three categories of the workers varies. Generally, the drivers are provided with highest wage followed by the ticket collector. The wages of the helpers are found to be considerably low. The data related to wages of the different workers are collected using a primary survey by interviewing the staffs of the buses.
The wage related information during pre-covid situation was primarily collected from the staffs but that data is validated from the operators too. The revenue collection and expenditure related data from the operators were collected from their offices. These offices for various areas are situated at the starting point of the routes/common parking lots of the buses. The surveyor initially collected the data from several operators regarding personal information (name and contact number) revenue collection of the buses, maintenance cost, cost of fuel etc. In this survey, the wage related information was also asked. But the wages provided by the operators were approximate value of total wage of all the staffs and it was also stated that the wages vary depending on the skill and experience of the staffs. The surveyor further took permission from the operators to have some interactions with the staffs so that the exact information regarding the wages could be collected. The wage related information was collected from the staff in the specific transport offices only so that somewhat sincere response can be gathered from the staffs. For this primary survey 200 buses were selected randomly and the staffs of the selected buses were interviewed to collect the information regarding their wages. The surveyor first initiated a friendly talk with the staffs and state the purpose of data collection and after that, the information regarding the wages were asked. The data was collected using random sampling method. The survey data were collected on three different time periods, pre-covid (January 2019) situation, unlock with 50% seating capacity (November 2020) and unlock with 100% seat capacity plus some restricted amount of standee (January 2021) situation.
4.1.2 Users’ perception data
Users’ perception data was collected through a questionnaire survey. It is not possible to interview the whole population of the study area for the questionnaire survey. Therefore, it is necessary to calculate the sample size for the survey. The minimum size of the sample is calculated as per Eq. (1) [24]:(1) n≥N[1+N−1P(1−P)(dzα/2)2]−1
where.
n is the minimum sample size to be considered.
N is the population of the city.
P is the quality characteristics which are to be measured. For neutral cases or where no previous experience exists then the value of P is taken as 0.5 [24].
d is the margin of error which is taken as 5%
zα/2=1.96 for 95% confidence interval
As per the 2011 census data, the population of Guwahati is 957,352. The minimum sample size is determined on the basis of Eq. (1) and found to be 385. Considering the minimum sample size, a total number of 650 and 470 valid responses were collected for the questionnaire survey before and after COVID-19 situation respectively.
The purpose of the questionnaire survey was to gather information about the users’ perception of the bus service. Therefore, the current users of the bus service and the users having a previous city bus experience were interviewed for the survey. The survey was conducted on various locations of the city. The locations include bus stops and other places like markets, parks, offices etc. which are accessible by bus service. The questionnaire survey was conducted using face to face interview method and by online method (through google forms).
The respondents for the fact-to-face survey were selected based on voluntary response sampling. For face-to-face interview, some users in each bus stops/on board were approached and stated the purpose of the survey. Then their willingness to participate in the survey were asked. Around 40% of the users stated their willingness to took part in the survey. In this way a total number of 750 survey sheets were distributed and collected after sometime. From this response sheet, only 300 responses (incomplete responses, uniform types of responses were not considered) were found to be valid. The response rate for the face-to-face survey was found to be 40%.
The online survey was conducted using google form. For the online survey, different offices/educational institutes along the bus routes were visited and the form was shared with some of the higher authorities. For online survey, different offices, schools/universities were selected based on random sampling method. The purpose of the survey was stated and along with that it is requested to share with their colleagues/friends. The respondents for the survey were selected based on snowball sampling. A total number of 57 offices/educational institutes were visited and survey form was shared. In this way a total number of 843 survey responses were collected among which only 350 responses were found to be valid for further analysis.
After the relaxation of the lockdown norms another survey was conducted and a total number of 470 valid responses (170 responses through face-to-face interview and 300 responses through online survey) were collected. The face-to-face interview was conducted on board as well as different bus stops. A total number of 550 survey sheets were distributed and collected. After verification it was found that only 170 responses were valid (with a response rate of 31%). For the online survey, the same respondents were contacted who took part in the online survey in the previous instance of survey before covid-19. A total number of 300 valid responses were collected with a response rate of 35%.
The attributes of the questionnaire survey were finalized by conducting a preliminary survey. The preliminary survey was conducted in pre-covid situation. The preliminary survey could be considered as a normal conversation between the two passengers rather than a traditional survey. The preliminary survey was conducted on board. Therefore, the survey respondents were the city bus users. A total number of 102 respondents were interviewed for the survey. Among the 70 respondents, 35 respondents were found to be school/college going students (less than 25 years of age), 54 respondents were the normal working-class people and 11 respondents were found to belong in a higher age group (may be more than or near about 60). Out of 102 respondents, a total number of 40 respondents were female passengers. Among these 40 female users, 15 were completing the trip for their school or universities, 25 respondents were the normal office goers. Each respondent was requested in the preliminary survey to state the attributes effecting their level of satisfaction. Based on their stated responses the attributes for the final survey were fixed. The questionnaire survey consists of two parts. In the first part the respondents were requested to answer various questions related to the socioeconomic and demographic variables. In the second part, the respondents were requested to rate various statements corresponding to different attribute of the bus service based on their perception. The respondents were requested to rate the statements in 9-point scale where 1 indicates that they are completely disagreeing with the statement and 9 indicates that they are completely agreeing with the statement. The questionnaire survey was conducted in two time periods, just before the spread of COVID-19 (December 2019) and after the complete relaxation of COVID-19 precautionary measures (September 2021).
4.2 Tools and techniques used
4.2.1 Paired sample t-test
We perform paired t-test to determine whether the mean value of user's perception attribute before COVID 19 is statistically difference from the mean value of user's perception attribute after COVID 19. The test was carried out under the null hypothesis that there is no difference in mean value of all the attribute before and after COVID 19. A 95% confidence interval was considered during the analysis. Paired t-test is a widely used statistical test; hence it is not discussed in detail. For detail, the reader may refer to Ref. [25].
4.2.2 Factor analysis
Factor analysis is used to analyze the user's perception data. Factor analysis is a two-step procedure, i.e., Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). EFA is used to know the number of unobservable summary variables or factors which are needed to explain the correlations between variables [26] and the link between the latent factors and observed variables [26]. Therefore, the objective of the EFA is to reduce the number of variables (data reduction) and to identify the relationship between observed variables and the latent factors. EFA is used when the researcher does not have any idea about the number of underlying factors and their structural relationship with the observed. EFA is used to determine the numbers of latent factors which affect the observed variables. CFA was used to verify and confirm the structural relationship between the latent variables and the observed variables [13, 16] through the different goodness of fit statistics values [8, 13]. The researcher must have specific knowledge of the total number of factors and the relationship between observed variables and the latent factor prior to the CFA model [13, 16]. Therefore, before conducting CFA, EFA is to be conducted. Two types of outcomes are estimated from the CFA analysis: factor loadings and factor scores [7, 10]. EFA and CFA was conducted using STATA 14 software.
5 Results
5.1 Revenue collection and expenditure of the buses
Average revenue collection/day/bus was estimated from the revenue collection data collected from regional transport offices and from several private transport operators. It could be seen from Table 4 that the average wages of the bus staffs (driver, ticket collector and helper) reduced considerably after COVID-19. In Guwahati city, the wages of the bus staffs are not fixed. The wages depend on the total number of runs they made in each day. As the number of passengers have considerably reduced after the spreading of the COVID-19, therefore buses made very few runs between different stations. This leads to the reduction in their wages. Average revenue collection/day/bus have reduced tremendously post COVID-19 outbreak compared to pre COVID-19 period. Moreover, it is also found that there is a slight improvement in the revenue collection after the 2nd unlock phase compared to the 1st unlock. The improvement of the revenue collection in the second unlock phase indicate that the users of the buses increase slightly compared to the 1st unlock phase. But compared to pre covid situation, that improvement is very marginal. In this regard it is very much essential to understand the users concern about the city bus service so that necessary action could be taken to improve the user base.Table 4 Revenue collection and expenditure of the buses.
Table 4Items Before COVID-19 Lockdown (Rs.) 1st Unlock with 50% Seat Capacity (Rs.) 2nd Unlock With 100% Seat Capacity Plus Restricted amount of Standee (Rs.)
Average revenue collection/day/bus 6122 3205 3805
Average wages of driver/day/bus 780 339 476
Average wages of ticket collector/day/bus 592 273 353
Average wages of helper/day/bus 391 215 245
Fuel price and maintenance cost/day/bus 2237 1807 2035
Average additional expenditure in lieu of Covid-19 0 50 50
Profit/bus/day 2122 521 646
Revenue loss/bus/day – 1601 1476
5.2 Preliminary data analysis of questionnaire data
Reliability of the data set is checked after collecting the data using Cronbach's alpha value. Cronbach's alpha value indicates the internal consistency of the data as a group. A Cronbach's alpha value of more than 0.7 indicates a reasonable consistency of the data. For both the pre covid and post covid data set the Cronbach's alpha value were found to be more than 0.9 which indicate that the data sets are highly consistent to proceed with further analysis. The socioeconomic characteristics of the respondents are shown in Table 5 .Table 5 Socioeconomic characteristics of the respondents.
Table 5Socioeconomic characteristics of the respondents Percentage of the total surveyed data (%) pre-covid Percentage of the total surveyed data (%) post-covid
Gender Male 47.8 54
Female 52.2 46
Monthly income in Rupees Less than 10,000 (Group 1) 37.2 36.2
10,000–15,000 (Group 2) 34.2 31.3
15,000–20,000 (Group 3) 12.8 16.6
20,000–25,000 (Group 4) 6.1 9.4
More than 25,000 (Group 5) 9.4 6.5
Age (years) Less than 25 (Group 1) 20.6 21
25–40 (Group 2) 55.5 54
40–55 (Group 3) 22.2 23
Over 55 (Group 4) 1.7 2
In Pre-covid situation, the samples included 311 male respondents and 339 female respondents. In post covid situation, a total number of 254 male respondents and 216 female respondents took part in the survey. In both the time period, maximum of the city bus users belongs to the income group 1 and 2. The qualitative attributes of the questionnaire survey are given in Table 6 .Table 6 Service quality attributes.
Table 6Qualitative attributes Assigned code to the perception data set Average values of user perception ratings before COVID-19 Average values of user perception ratings after COVID-19
Buses are well maintained a1 4.5 3.8
Seats are generally clean a2 4.5 3.5
Seats are comfortable and sufficient leg room is provided a3 5.2 5.1
Doors and windows are in proper working condition a4 4.6 4.4
Vehicles are odor free and clean a5 4.2 3.0
While standing sufficient distance is maintained from the fellow passengers a6 3.5 3.2
Seats are available while travelling in the buses a7 3.5 5.6
Staffs are well behaved a8 4.5 5.5
Some reserved seats are provided for women and older people a9 4.2 5.7
Very few breakdowns of the vehicles are experienced during journey a10 5.5 5.6
Adequate travel speed is maintained a11 4.2 4.4
Buses are punctual a12 4.6 3.5
When you are travelling with the bus you know exactly when you reached your destination a13 4.0 3.5
You know how much you have to wait for the bus in a particular bus stop a14 4.5 3.7
Bus service is Consistent irrespective of the situation a15 5.3 4.5
Bus fares are justifiable a16 6.0 6.2
Bus fares are fixed for all the buses a17 6.5 6.7
Bus service could be easily accessed from your location a18 4.5 4.7
You feel safe while travelling through bus with respect to theft and other mishaps a19 4.5 4.7
Buses run safely maintaining all the traffic rules a20 6.5 6.4
Bus stops are safe and tidy a21 4.6 4.5
Adequate time is provided for boarding and alighting a22 4.7 5.5
Overall satisfaction 5.2 4.3
The statement a1 is rated below after the COVID-19. It may be due to the fact that bus service was closed for nearly 144 days in Guwahati. Within that period no revenue was generated by the buses. Therefore, during that period very little or no maintenance works were carried out which disrupts the swift operation of the buses. Statement a2 and a5 are also rated considerably below after the COVID-19. Though after the COVID-19 lockdown some cleaning work was initiated by the buses after each run and that are continued till now. But covid 19 has inflict some sense of hygiene and cleanliness in the mind of the users. Therefore, the cleanliness and hygiene of the buses become an important parameter for the users. After the covid 19, though the buses may look more clean and hygiene compare to the pre covid situation but it was not able to meet up with the users level of expectation.
Statement a3, a4, a10, a11, a16, a17, a18, a19, a20, and a21 are rated similar before and after COVID-19 lockdown as there were no changes in those particular attributes of the buses before and after COVID-19. Statement a6 is also rated very closely before and after COVID-19. Before COVID-19 during the peak hours' buses became overly crowded and this fact led to low rating of this particular attribute. After the relaxation of COVID-19 norms though very little passengers are allowed after the seats are full but passengers felt uncomfortable in the buses due to the proximity of other passengers. For this reason, this attribute is rated very low after the COVID-19. Statement a7 is rated better after the COVID-19, because after the relaxation of COVID-19 norms very less people are allowed after the seats are full and many users opted for other mode of transport. These two factors lead to more availability of the seats. Moreover, as the user base of the buses reduces considerably, therefore the attitudes of the staffs of the buses changed considerably after the reopening of the bus service which leads to a higher rating of the statement a8 after the COVID-19. In Guwahati, as per the Govt. norms some of the seats were reserved for the older people and female passengers. But before the COVID-19, due to overly crowding of the buses in some of the routes, this norm was not strictly followed. After the COVID-19, as the buses remain empty in most of the time, the norm is now strictly followed. Moreover, some new buses are introduced by the Govt. only for the female users and older people. That's why the statement a9 is rated higher after the COVID-19. Statements a12, a13, a14, a15 is rated below than the pre covid situation. This is because, as the users base of the buses reduced considerably post covid, therefore, buses tend to wait in a particular stop for a considerable period of time just to catch some more passengers. This leads to increase the journey time and therefore will reduce the consistency of the buses. The punctuality of buses (a12) is defined on the basis of users' perception regarding arrival of buses in each stop. All the users may not have the information regarding the official bus schedule, but they have some perception regarding the arrival and departure of buses from each station. They perceive this punctuality from their experience of day-to-day travel and by comparing the travel time with the travel time required by para transit or other mode of transport.
Gender wise distribution of the users’ ratings on overall satisfaction is indicated in Table 7 . 26.8% of the male respondents in pre covid situation and 34.8% male respondents in post covid situation were found to provide a rating of 4 or below on overall satisfaction. For the female respondents, these values were found to be 52.2% in pre covid situation and 58.4% in post covid situation. 27.9% of male respondents in pre covid situation and 41.7% male respondents in post covid situation were found to be provided a neutral rating. On the other hand, in pre covid situation 26.6% of the female respondents and 27.7% female respondents in post covid situation provided a neutral rating value. 45.3% of the male respondents in pre covid situation and 23.5% of the male respondents in post covid situation were found to be satisfied with the bus service (provided a rating of 6 or more). But for the female respondents, these values were found to be 21.3% and 13.8% respectively for pre and post covid situation. Percentage of female respondents were found to be more before the neutral ratings while the percentage of male respondents were more after the neutral rating. This indicates that the female respondents are less satisfied with respect to the male respondents.Table 7 Gender wise distribution of the users’ ratings on overall satisfaction.
Table 7Time Period Sex Distribution of users' ratings on the overall satisfaction of the bus service (%)
1 2 3 4 5 6 7 8 9
Pre covid Male 1.2 0.0 3.5 22.1 27.9 27.9 5.8 11.6 0.0
Female 4.3 3.2 13.8 30.9 26.6 13.8 3.2 4.3 0.0
Post covid Male 2.6 10.4 6.1 15.7 41.7 15.7 5.2 2.0 0.6
Female 3.1 1.5 20.0 33.8 27.7 7.7 4.6 1.0 0.5
Age wise distribution of the users’ ratings on overall satisfaction of the bus service is indicated in Table 8 . In pre covid situation, 39% respondents of the age group 1 provided a rating of 4 or below, 31.7% of respondents provided a neutral rating while 29.3% of the respondents provided a rating of 6 or more. 39.4% of the respondents provided a rating of 4 or below, 24.7% provided a neutral rating and 35.9% of the respondents provided a rating of 6 or more among the users belonging to age group 2. For the respondents belonging to age group 3, these percentage values were found to be 57.1%, 7.1% and 35.8%. For the respondents belonging to age group 4 these percentage values were found to be 30%, 20% and 50%. Therefore, it can be said that with increasing age the dissatisfaction of the users increases.Table 8 Age wise distribution of the users’ ratings on overall satisfaction.
Table 8Time period Age Groups Distribution of users' ratings on the overall satisfaction of the bus service (%)
1 2 3 4 5 6 7 8 9
Pre covid 1 0.0 3.7 8.5 26.8 31.7 20.7 2.4 6.1 0.0
2 2.9 2.0 8.6 25.9 24.7 21.0 6.2 8.6 0.0
3 7.1 0.0 14.3 35.7 7.1 14.3 7.1 14.3 0.0
4 0.0 0.0 0.0 30.0 20.0 40.0 10.0 0.0 0.0
Post covid 1 4.2 6.9 6.9 26.4 33.3 15.3 1.4 4.2 1.4
2 2.7 9.6 8.2 20.5 39.7 13.7 5.5 0.0 0.0
3 0.0 4.0 4.0 12.0 44.0 24.0 12.0 0.0 0.0
4 10.3 8.5 20.5 30.3 21.7 8.7 0.0 0.0 0.0
For the respondents of age group 1 in post covid situation, 44.4% provided a rating of 4 or below, 33.3% provided a neutral rating and 22.3% provided a rating of 6 or more. For the respondents of age group 2 these values were 41%, 39.7% and 19.3% respectively. For the respondents belonging to age group 3, these values were found to be 20%, 44% and 36%. For the respondents belonging to age group 4, these values were 69.6%, 21.7% and 8.7%.
Income wise distribution of the users’ ratings on overall satisfaction of the bus service is indicated in Table 9 . The percentage of respondents provided ratings of 4 or less are 43.3%, 20.9%, 47.8%, 45.5% and 82.3% respectively for income group 1, 2, 3, 4 and 5 in pre covid situation. In post covid situation these are found to be 49%, 27%, 54%, 62.5% and 70.9% respectively for income group 1, 2, 3, 4 and 5. It indicates that users in post covid situation poorly perceived the bus service in comparison to pre covid situation.Table 9 Income wise distribution of the users’ ratings on overall satisfaction.
Table 9Time period Income groups Distribution of users' ratings on the overall satisfaction of the bus service (%)
1 2 3 4 5 6 7 8 9
Pre covid 1 0.0 3.0 10.4 29.9 28.4 20.9 3.0 4.5 0.0
2 0.0 1.6 3.2 16.1 24.2 32.3 9.7 12.9 0.0
3 0.0 0.0 13.0 34.8 34.8 8.7 8.7 0 0.0
4 10.5 7.7 9.1 18.2 45.5 9.1 0.0 0.0 0.0
5 12.6 9.1 13.5 47.1 11.8 5.9 0.0 0 0.0
Post covid 1 3.4 6.9 7.8 30.9 28.8 10.3 3.4 6.0 2.5
2 0.0 8.1 5.4 13.5 40.5 10.8 8.7 9.5 3.5
3 2.6 10.3 2.6 38.5 25.6 20.5 0.0 0.0 0.0
4 3.7 14.8 3.7 40.3 22.2 7.4 6.5 1.5 0.0
5 4.2 8.3 14.6 43.8 20.8 8.3 0.0 0.0 0.0
Correlations among the different variables are checked using Variance Inflation Factor (VIF). VIF represents the amount of variance of a regressor explained by the remaining regressors present in the regression model due to correlation among them [27]. Different cut-off values for the VIF have been suggested by different researcher depending on the nature of the study. In this study, the cut-off value of the VIF is considered as 2 [28] i.e. the variable with a VIF value greater than 2 is highly correlated with the remaining variables. For pre covid situation it is found that all the variables included in the questionnaire have a VIF value more than 2. Therefore, it could be said that all the variables are highly correlated. For post covid data, it is found that except bus fare (a16) all the variables are highly correlated. It indicates that most of the variables are highly correlated and unsuitable for regression. For this reason, factor analysis is performed to represent the highly correlated variables with a smaller number of variables.
5.3 Paired sample t-test
The mean and standard deviation value of each attribute are shown in Table 10 . From Table 10, it can be seen that the t value and p value of every attribute is very small (p < 0.05), hence the null hypothesis was rejected. Thus, the difference in mean value of user's perception before COVID 19 is statistically significance from the mean value of user's perception attribute after COVID 19.Table 10 Paired sample t-test statistics.
Table 10Attributes Average values of user perception ratings before COVID-19 Standard Deviation Average values of user perception ratings after COVID-19 Standard Deviation t statistics degree of freedom std error of difference p value
a1 4.5 0.52 3.8 0.91 16.27 1118 0.043 0.0001
a2 4.5 1.01 3.5 1.02 16.28 1118 0.061 0.0001
a3 5.2 0.77 5.1 0.9 1.997 1118 0.05 0.0461
a4 4.6 0.79 4.4 0.92 3.9 1118 0.051 0.0001
a5 4.2 0.81 3 1.1 21.0261 1118 0.057 0.0001
a6 3.5 0.73 3.2 0.62 7.2225 1118 0.042 0.0001
a7 3.5 0.62 5.6 0.54 59.00079 1118 0.036 0.0001
a8 4.5 0.86 5.5 0.84 19.39 1118 0.052 0.0001
a9 4.2 0.53 5.7 0.83 36.846 1118 0.041 0.0001
a10 5.5 0.76 5.6 0.46 2.536 1118 0.039 0.013
a11 4.2 0.62 4.4 0.84 4.584 1118 0.044 0.0001
a12 4.6 0.73 3.5 0.26 31.262 1118 0.035 0.0001
a13 4 0.78 3.5 0.73 10.874 1118 0.046 0.0001
a14 4.5 0.56 3.7 0.85 18.97 1118 0.042 0.0001
a15 5.3 0.6 4.5 0.57 22.486 1118 0.036 0.0001
a16 6 0.73 6.2 0.82 4.295 1118 0.047 0.0001
a17 6.5 0.62 6.7 1.09 3.889 1118 0.51 0.0001
a18 4.5 0.87 4.7 0.53 4.425 1118 0.045 0.0001
a19 4.5 0.69 4.7 0.77 4.558 1118 0.044 0.0001
a20 6.5 0.57 6.4 0.84 2.372 1118 0.042 0.0178
a21 4.6 0.63 4.5 0.72 2.468 1118 0.041 0.0137
a22 4.7 0.57 5.5 0.76 20.128 1118 0.04 0.0001
5.4 Factor analysis
For Pre covid situation, all the variable are analyzed using factor analysis and for post covid situation all the variable except a16 are used for factor analysis. Factor analysis is performed to find the factors which affect users’ perception. For pre covid situation, four latent factors with eigenvalues greater than one [29] were extracted from the 23 correlated attributes which explained 75.7% of the total variance. For post covid situation, five latent factors with eigenvalues greater than one [29] were extracted from the 22 correlated attributes on the city bus service which explained 77.5% of the total variance. Before conducting EFA sample adequacy have been checked by Kaiser-Meyer-Olkin (KMO) tests. The KMO estimates the ratio of the squared correlation between variables to the squared partial correlation between variables [30]. When the KMO is near 0, it is difficult to extract a factor and when the KMO is near 1, a factor or factors can probably be extracted. For an acceptable sample adequacy, the KMO value should be more than 0.5 [31]. The tests statistics values are found to be more than 0.9 for both the cases. For both the cases, EFA was conducted separately. EFA also indicated the possible relationship between the factors and observed variables. Based on the results obtained from the EFA, CFA was conducted. The EFA aims at reducing (data reduction) the number of variables and defining the relations between observed and latent factors. EFA is conducted using IBM SPSS 20 software. In SPSS, different extraction methods for the EFA analysis are there-principal components, principal axis factoring, unweighted least squares, maximum likelihood etc. Principal components is the default extraction method in SPSS and it extracts uncorrelated linear combinations of the variables. As the data set was highly correlated, therefore principal components was used as extraction method for the EFA to extract uncorrelated factor. After extracting the factors, factor rotation is necessary to better fit the data. The most commonly used method is varimax. Varimax is an orthogonal rotation method that tends to produce factor loading that are either very high or very low, making it easier to match each item with a single factor. For this reason, varimax rotation technique was used.
The factor structure for the CFA analysis is shown in Fig. 3 for pre covid situation and in Fig. 4 for post covid situation. In both the figures, the square boxes represent different observable variables, the oval shapes represent latent factors. The values written beside the single arrowed lines represent standardized factor loadings. Square of these factor loading represent correlation coefficient between the latent factor and observed variables. The values shown beside the small round shapes are standardized error variance which represent unexplained portion of the variance. Four factors namely comfort, fairness, reliability and safety have been extracted from the attributes in Pre-covid situation. Five factors extracted from the attributes in post covid situation are vehicle condition and hygiene, comfort, Reliability & convenience, fairness, and safety.Fig. 3 CFA analysis of the perception data for pre COVID-19 situation.
Fig. 3
Fig. 4 CFA analysis of the perception data for post COVID-19 situation.
Fig. 4
Four factors namely comfort, fairness, reliability and safety have been extracted from the attributes in Pre-covid situation. Ten attributes (a1 to a10) are grouped under factor comfort as users relate these attributes with a comfortable journey. For example, attribute a1 relates to the maintenance of the vehicle. If the vehicle is well maintained, it would be visually appealing as well as comfortable to ride. Attribute a2 and a4 are related to the cleanliness of the vehicle and seats. But these two attributes are also grouped under factor comfort as users perceive that cleanliness and odor free journey will make their ride more comfortable. Good behavior of the staffs inflicts confident among the passengers and hence make their ride more comfortable. For this reason, this attribute is also grouped under factor comfort. Doors and windows in proper working condition is very necessary during the adverse weather conditions, winter seasons etc. Therefore, condition of the windows and doors (a4) are necessary for a comfortable ride of the users. Attributes a11, a12, a15, a16 and a18 are grouped under factor reliability & convenience. Adequate travel speed (a11) and punctuality of the buses (a12) are very much necessary for the convenient of the users. Moreover, maintaining punctuality makes the buses more reliable. Therefore, these two attributes grouped under factor reliability and convenience. Similarly, Consistency of the service (a15), accessibility of the service (a18) also makes the ride more reliable. One thing could be noticed that, the attribute a16 (bus fares are justifiable) also fall under the factor reliability and convenience. It may be due to the fact that a reasonable fare will make the bus service more affordable for the users and hence it will make the service more convenient for the users. Attributes a13, a14 and a17 fall under factor fairness. Attribute a17 (bus fares are fixed for all the buses) indicates the consistency of the bus fare. A good performance of this attribute indicate that the bus fares are fixed for different routes irrespective of the buses and any time period. Therefore, this factor is grouped under fairness. Attribute a13 (When you are travelling with the bus you know exactly when you reached your destination) indicates that the passengers are well informed about their journey time i.e., they know exactly when they will reach their destination if the ride the bus. Therefore, this attribute is also grouped under factor fairness. Similarly, attribute a14 (You know how much you have to wait for the bus in a particular bus stop) is also grouped under factor fairness. Attribute a19, a20, a21, and a21 are grouped under factor safety as they relate to the safety of the passengers and the bus ride.
The factor structure for the post Covid situation is found to be different from the pre covid situation as the users may perceive the attributes differently. Five factors extracted from the attributes in post covid situation are vehicle condition and hygiene, comfort, Reliability & convenience, fairness, and safety. Attributes a1, a2, a4, and a5 grouped under factor vehicle condition and hygiene. Attribute a2 and a5 relate to the cleanliness of the vehicle and seats while attributes a1 and a4 relate to the condition of the vehicle. In pre covid situation, all these attributes were grouped under factor comfort but for the post covid situation users view these attributes separately than from the pre covid era as the importance of cleanliness and hygiene have greatly increased in post covid situation. Attributes a3, a6, a7, a8, and a9 grouped under factor comfort as all these attributes relate to the comfort of the users. The attributes under factor safety, and fairness remain same in both the pre and post covid situation. It is to be noted that, attribute a16 (Bus fares are justifiable) is not included in the factor structure of post covid situation as this attribute is seen as a separate entity in post covid situation.
Comparative fit index (CFI), chi-square to degrees of freedom ratio (χ2/d.f.), standardized root mean squared residual (SRMR), root mean squared error of approximation (RMSEA), and coefficient of determination (CD) values were used to check the goodness of fit for the proposed CFA model. The CFI, χ2/d.f., SRMR, RMSEA, and CD values for the model representing pre-covid situation are found to be 0.911, 2.23, 0.069, 0.067, and 0.998 and for the post covid situation these values are found to be 0.921, 2.66, 0.058, 0.071 and 0.987. All these mentioned values are found to be within their limit [32,33]. Therefore, it can be said that the proposed CFA models fits the data well. The internal consistency of the variables within the factors (i.e. reliability of the proposed factor structures) were checked using factor loading values, composite reliability (CR) values, and average variance extracted (AVE) values. Factor loadings, composite reliability, and average variance extracted values should be more than 0.5, 0.7, and 0.5 respectively for a reasonable internal consistency of the variables [31]. From Fig. 3, Fig. 4 it is found that all the factor loading values are more than 0.5. The composite reliability and average variance extracted values are shown in Table 7. It is found that composite reliability and average variance extracted values are within their acceptable limits. Therefore, it can be said that the reliabilities of the proposed CFA models are acceptable.
Discriminant validity of the factor is checked by comparing maximum shared variance (MSV) and average shared variance (ASV) with the AVE values. The MSV and AVE values are reported in Table 11 . It is found that MSV and ASV values are lesser than AVE values which indicates that there does not exist any problems regarding discriminant validity of the factors.Table 11 Values of the composite reliability and average variance extracted of the latent factors.
Table 11CFA model for Pre covid data set CFA model for post covid data set
Latent factors CR AVE MSV ASV Latent factors CR AVE MSV ASV
Safety 0.86 0.60 0.21 0.18 Safety 0.89 0.67 0.41 0.31
Comfort 0.92 0.54 0.26 0.23 Comfort 0.85 0.53 0.41 0.35
Reliability & Convenience 0.81 0.52 0.26 0.18 Reliability & Convenience 0.87 0.58 0.38 0.32
Fairness 0.77 0.53 0.23 0.16 Fairness 0.79 0.55 0.28 0.22
Vehicle condition & Hygiene 0.94 0.80 0.39 0.32
5.5 Relative importance of the factors
The relative importance of the factors on overall satisfaction is estimated using path analysis. Path analysis and hierarchical regression (HR) are the two most commonly used methods to analyze if the variable of interest explained a statistically significant amount of variance in a model. HR is commonly used when a model's variance is explained by predictor variables that correlate with each other. As there are negligible intercorrelation among the factors, path analysis rather than hierarchical regression analysis was used in this study. Moreover, in the mentioned section, path analysis is conducted to estimate the relative weight of all the factors which is indicative of their relative importance over the overall satisfaction of the users. HR in this case may not serve the purpose of this study. Therefore, it was not used in this section. In the path analysis, factors scores have been used as independent variables and the overall satisfaction as dependent variable. The path analysis for pre covid (a) and post covid (b) is shown in Fig. 5 respectively. The values shown beside the single arrowed lines are the coefficient values indicating relative importance of the factors on overall satisfaction. The values shown beside the small round shapes are the standardized error variance which represent unexplained portion of the variance. From Fig. 5(a) and (b) it could be said that the unexplained portion of the variance in pre-covid situation is 0.11 and in post covid situation is 0.15. Therefore, 89% of variance in the pre covid situation and 85% variance in post covid situation can be explained by the factors.Fig. 5 Relative importance of the factors.
Fig. 5
For pre covid situation Reliability & Convenience is found to be most important factor followed by safety, comfort, and Fairness. But for the post covid situation, the most important factor is found to be Vehicle Condition & Hygiene. It indicates that the users after the covid 19 breakdown are more concerned with the vehicle condition and hygiene than the other factors. In the path analysis of the post covid analysis the bus fares (a16) is also included. The input variable for the bus fares are the data obtained from the questionnaire survey. In pre covid situation the bus fare (a16) was found to have strong correlation with other variables. For this reason, bus fare was included in the factor analysis of pre covid data. Factor analysis of the correlated data indicates that the bus fare fall under the factor reliability and convenience. For post covid data, it is found that except bus fare (a16) all the variables are highly correlated. It indicates that most of the variables are highly correlated and unsuitable for regression. For this reason, factor analysis is performed on all the 21 variables except a16. In post covid situation users perceived a16 as a separate entity. This may be due to the fact that, during the covid situation many people have lost their jobs and many people were forced to do the same job with lesser payment. And after that time period also, due to the increase in petrol prices in India there were frequent changes in the bus fare. For this reason bus fare is included in the path analysis in post covid situation. The relative importance of the bus fares is found to be low which indicate that the users are willing to pay more for a better service which can also be observed by the responses of users provided in Table 4. As vehicle condition and hygiene is found to be very important for the users in post covid situation, therefore, this factor should be improved to increase the users base of the city buses.
6 Discussion
In India, a major portion of the users are dependent on public transit. Therefore, a modal shift of the users from public transit to private vehicles will create many problems like pollution, congestion etc. In this regard some studies [4,17,18] have highlighted the impact of COVID-19 on the ridership of the public transport in India. Research findings showed that the public is in favor of personal vehicle compared to public vehicle during the early stages of COVID-19 [4]. Poor vehicle condition & hygiene could be a reason of this user's choice as evident from this study. From the previous literatures [18,19] it is also found that the fear of pandemic has greatly impacted people travel decision-decision and it will affect the ridership of the public transport even in the absence of restrictive measures. Dandapat et al. [4] found that an expected delayed recovery of the ridership of public transport post-COVID era. This is also evident from the study area where a massive decline of 59.09% of the ridership observes in the absence of restrictive measures. Similarly, Gajendran [17] reported a drop of shared mobility by 35% compared to the normal condition due to the fear of contact with unknown people. But till now no comparative studies of users' perceptions in pre and post covid situations are available as far as our best knowledge which limit the complete policy making process for the public transport users. A comparative study is necessary to highlight the changing behavior and priorities of users after the covid situation so that necessary action could be taken. Therefore, this study will open a new dimension in the area of public transport policy making and will be helpful for taking necessary action to recover the declining public transport sector in developing economic.
7 Conclusion and recommendations
COVID-19 has greatly affected the travel demand of the people which marked a huge dent on the public transit sector. Public transit authorities faced a huge financial loss which is also evident from this study. A cost analysis of the city buses indicate that the city bus operators faced a financial loss due to the COVID19 outbreak and it affects greatly to the livelihood of many workers associated with the city bus service. It has been found that the average profit of the buses reduced from 2122 Rs/day/buses to 521 Rs./day/buses in first unlock phase and 646 Rs./day/bus in second unlock phase. The average wage of the drivers reduced from 780 Rs./day to 339 Rs./day in first unlock phase and 476 Rs./day in second unlock phase. This loss in wage is not only limited to the drivers but extended to other workers associated with the buses. Loss in the average profit margin of the buses could be attributed to local travel restrictions imposed by the authorities and negative perception of the city bus users toward the bus service. The ridership of city buses has declined to 9% (in post covid situation) from 22% (pre covid situation). Therefore, in this study, the users’ perceptions in both pre covid and post covid situation were analyzed. It has been found that the users perception varies significantly in both the situation. Ridership decline is found to be a major issue in the post covid situation. Before the COVID-19 outbreak, users perceive vehicle condition and hygiene as an integral part of their comfort but in the wake of corona outbreak users tend to give more importance to the vehicle condition and hygiene than the other factors. Bus service in the city seem to have performed very poorly in this respect which may lead to shifting of users towards other mode of transport. Safety and reliability & convenience is also found to be important for the users. Under performing factors can be improved by improving the attributes associated with them. Some of the recommendations to improve the bus service in the city are as follows:• The most important factor in post covid situation is found to be vehicle condition and hygiene. This particular factor can be improved by making the buses clean and visually attractive for the passengers. Cleaning should be carried out after each run. Some incentive should be provided to the staffs of the buses for cleaning and maintaining the buses. Grievance box should be there in every buses so that users can put up their grievances. Staffs as well as passengers should be informed regarding various public transport healthy practices through different awareness program.
• Safety of the buses is also found to be important. Safety measures need to be increased in the bus stops, and within the buses. The drivers of the city buses should be instructed to avoid rash driving. Moreover, utmost care and vigilance should be there during the boarding and alighting process. Driver needs to start the vehicle only after successful boarding and alighting process.
• The bus service needs to follow a fixed arrival and departure time. This can be achieved by minimizing the unnecessary delays between the bus stops. The servicing of the buses should be done within the stipulated time to avoid any unnecessary breakdowns during the journey. The bus service should be consistent and easily accessible. To make the bus service more accessible some new routes can be introduced. Otherwise, the existing bus routes can be made more accessible by regulating the para transit services in the city. For example, in Guwahati city E-Rickshaw services are unregulated. This service can be made regulated so that they can act as a feeder to the public transport.
• Number of buses should be increased to prevent the overcrowding during busy hours. This can be achieved by introducing additional buses during peak hours. The staffs may be provided adequate training in respect of their behavioral aspect towards passengers. Seating arrangements may be redesigned to make it more comfortable. From the preliminary data analysis, it is also found that the female users and people with relatively higher ages are not so satisfied with the service. Therefore, some additional buses could be introduced in the city keeping in mind about the female users and people with higher ages.
• It is recommended to publish the bus fare and schedule of buses on different routes through posters, banners etc. in the buses and bus stops. Another way of sharing the information is total digitalization of the buses through development and implementation tools such as automated fare-collection systems, secure wayfinding and protocol app within terminal etc.
8 Future scope
This study is based on users' perception data. User perception of the service is not same for all the users. It differs between individuals and different market segments based on socioeconomic variables. Therefore, it would be advantageous to study in detail about the effect of demographic and socioeconomic characteristics of the passengers on their perception of the service to make the service more appealing across different groups. These effect of the users' socio-economic characteristics on perception was not discussed in detail in the article. Users' perception data can be collected in different ways (for example: face-to-face interview method, online data collection, data collection through mobile app etc.) and there may be variation of the data collected by different methods which will need further analysis and discussion. Moreover, the condition of the city buses will not be same throughout an entire day. For example, in peak hours the buses may be very crowdy but during the odd hours the buses may remain mostly empty. This type of condition will lead to temporal variation in users’ satisfaction which is also not discussed in this article. In this regard, it is felt that certain aspects of the city bus service deserve further studies. Some of them are mentioned below:• This temporal variability in the user's satisfaction can be studied in future to make the transit service more effective.
• Effect of users' socio economic and demographic characteristics on users' satisfaction may be studied in future.
• Effect of different data collection technique on the quality of collected data may be studied in future for better understanding about the different data collection technique.
Funding
No external funding is received in this study.
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.
Appendix A Supplementary data
The following is the Supplementary data to this article:Multimedia component 1
Multimedia component 1
Data availability
Data will be made available on request.
Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.ijdrr.2022.103489.
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| 0 | PMC9747689 | NO-CC CODE | 2022-12-16 23:21:40 | no | Int J Disaster Risk Reduct. 2023 Feb 1; 85:103489 | utf-8 | Int J Disaster Risk Reduct | 2,022 | 10.1016/j.ijdrr.2022.103489 | oa_other |
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Journal of Corporate Finance
0929-1199
0929-1199
Elsevier B.V.
S0929-1199(22)00183-3
10.1016/j.jcorpfin.2022.102340
102340
Article
A shot in the arm: Economic support packages and firm performance during COVID-19
Igan Deniz a12
Mirzaei Ali b⁎
Moore Tomoe c
a Monetary and Economic Department, Bank for International Settlements, Basel, Switzerland
b Finance Department, School of Business Administration, American University of Sharjah, PO Box 26666, Sharjah, United Arab Emirates
c Department of Economics and Finance, Brunel University London, Uxbridge, Middlesex UB8 3PH, UK
⁎ Corresponding author.
1 Centre for Economic Policy Research, London, UK.
2 The authors are grateful for their useful comments to the Editor, two anonymous reviewers, participants in seminars at the BIS and the IMF, Santiago Acosta-Ormaeachea, Martin Cihak, Moeti Damane, Andres Fernandez-Martin, Petr Jakubik, Paolo Mauro, and Egon Zakrajsek. The views expressed here are those of the authors and do not necessarily represent the views of the BIS.
14 12 2022
14 12 2022
1023409 4 2021
1 12 2022
7 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.
We use firm-level data to provide some early evidence on the effectiveness of COVID-19 economic policy packages. Our empirical strategy relies on the varying degree of vulnerability to the pandemic across industries. We find a robust association of fiscal support with changes in firm performance indicators (as measured by sales-to-assets ratio, profit margin, interest coverage ratio as well as probability of default) in pandemic-prone sectors. We also observe marginal effects of monetary policy on the sales-to-assets ratio and of foreign exchange intervention on the interest coverage ratio in the hardest-hit firms. These results broadly survive a battery of exercises to address endogeneity. Additionally, we show that firms with a better financial position are more likely to take advantage of the support packages to withstand the pandemic shock. Overall, this preliminary evidence suggests that policy interventions have bought time for the hardest-hit industries, by supporting turnover and improving liquidity.
Keywords
Economic support
Pandemic-prone
COVID-19
Policy effectiveness
Editor: Dr K Hankins
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pmc1 Introduction
COVID-19 prompted authorization and implementation of large economic policy packages around the world, understandably so since a crisis like no other necessitated a response like no other. These packages involved a combination of fiscal, monetary, financial, and capital-account policies. An important question for academics and policymakers alike is how effective these measures have been, especially by helping those sectors most in need.
In this paper, we use firm-level data to provide some answers to this question. Our empirical strategy relies on the varying degree of vulnerability to the pandemic across industries. Firms operating in sectors that rely more on face-to-face interactions when producing goods or providing services are contact-intensive, and thus have a larger portion of jobs that cannot be done at home. As a result, they are more vulnerable to non-pharmaceutical interventions (such as social distancing or lockdown measures) that aim to stop or slow the spread of the virus. By the same token, economic policy support would aim to target these worst-hit industries. Contrary to standard economic crises, stimulating real activity in a crisis like COVID-19 is not only more challenging – given the complex nature of the shock combining supply, demand and uncertainty factors – but could also be undesirable, in particular for the contact-intensive sectors as this would go against the needed public health containment measures. That said, economic policies would try to curb the Keynesian feedback loop triggered by the abrupt and substantial loss of income in firms due to the shock, i.e. to minimize spillovers and dislocation costs associated with business failures as well to ensure that liquidity is sufficient enough to avoid unnecessary bankruptcies. One yardstick of success then is whether policy actions have given more of a lift to these sectors relative to others, especially with respect to supporting firms' liquidity and capital.
To measure how prone different firms are to non-pharmaceutical interventions, we rely on a proxy, namely, “distancing” measures that have been developed in the wake of the pandemic (Kóren and Petö, 2020; Dingel and Neiman, 2020; Hensvik et al., 2020) and utilized also by other researchers (e.g., Pagano et al., 2020; Laeven, 2022). These measures capture the degree to which jobs require customer contact, teamwork, etc. at the sectoral level, as the share of workers in contact-intensive occupations. We first confirm that firms in sectors with higher distancing indices performed worse than the others in the same country, and especially so when the pandemic hit to their country was more severe (as captured by the stringency of the lockdown measures, which is highly correlated with the reported number of COVID-19 cases and deaths).
We then examine whether performance metrics (efficiency, profitability, liquidity, and survival) in firms operating in more pandemic-prone sectors have fared better during the first year of the pandemic (2020), if they were located in countries that deployed more comprehensive economic support packages (covering fiscal, monetary and foreign exchange). In other words, if economic policies during the COVID-19 crisis portray an effective action in response to the pandemic, we would expect this to be reflected in relatively better performance by firms that are more pandemic-prone compared to those that are less so. Our main specification, thus, focuses on the cross-sectional differences in firm performance depending on how sensitive to distancing a sector is, controlling for sector and country fixed effects as well as firm observables such as size, age and cash flow.
We find a robust positive association of fiscal support with efficiency and profitability in pandemic-prone sectors: sales-to-assets ratio (i.e. efficiency) and profit margin in firms that are more sensitive to distancing have grown faster when the fiscal support is larger. Furthermore, we observe positive effects of fiscal packages on firm liquidity and survival: interest coverage ratio (i.e. liquidity) increased while probability of default decreased disproportionately more in pandemic-prone sectors.
Economically, moving from a country at the 10th percentile of the distribution of fiscal support (for example, Sri Lanka) to a country at the 90th percentile (for example, Germany), the change in sales-to-asset ratio of firms in more pandemic-prone sectors is about 2% more than their less pandemic-sensitive counterparts from 2019 to 2020. This is consistent with Laeven and Valencia (2013), who report that fiscal policy disproportionately boosted the growth of firms that were more dependent on external financing in the context of the global financial crisis. Aghion et al. (2014) also find that counter-cyclical fiscal policy supported the growth of manufacturing industries across 17 OECD countries over the period 1980–2005.
Additionally, we find that monetary support is marginally associated with an improvement in the sales-to-assets ratio. Prior to the COVID-19 outbreak, monetary policy stance in major economies was already accommodative, raising questions about central banks' ability to confront the next shock (Gagnon and Collins, 2019). It appears that further easing has proved to be still effective in improving revenues for firms that were hit hardest by the pandemic. In this respect, the monetary policy transmission mechanism seems to have remained functional during the pandemic, as opposed to the case of the global financial crisis when banks were capital constrained and the lending channel was substantially weakened (Laeven and Valencia, 2013).
By contrast, we do not find a robust significant relationship between monetary policy easing and the other firm performance indicators such as liquidity and probability of default. This is in line with the argument that monetary policy may not be particularly well-suited to deal with the implications of COVID-19 because of unsuitability of monetary policy in addressing supply-side shocks and the difficulty to target support to specific sectors that are affected first and foremost by non-pharmaceutical interventions (Chen et al., 2020).
Foreign exchange interventions appear to arrest the decline of interest coverage ratio during the pandemic for the hardest-hit (although this finding is not as robust as those on fiscal and monetary policy measures). One plausible explanation for this finding may be that liquidity in pandemic-prone sectors such as recreation services and tourism are highly responsive to changes in the value of the domestic currency against foreign currencies.
Our findings are robust to a battery of checks, including various strategies to address endogeneity issues and using alternative measures of distancing. We also verify that the results are broadly unbiased to the extent that we remove certain sectors or industries from the sample. Additional analysis suggests that support packages are generally more effective in larger firms and firms entering the crisis with better liquidity, profitability and capital positions. The latter finding provides some comfort that policy interventions in response to this entirely exogenous shock may not have been distortive.
Our paper is linked to two strands of the literature. Firstly, it relates to those studies investigating the effect of a crisis on corporate performance. Many recent additions to this strand examine the real impact of the 2008–09 global financial crisis (see, among others, Duchin et al., 2010; González, 2015; Demirgüç-Kunt et al., 2020), adding to studies that look more broadly at banking crises and sudden stops. Given that the COVID-19 crisis is still unfolding, researchers have so far mostly examined the impact of the pandemic on stock market performance (e.g., Alfaro et al., 2020; Remelli and Wagner 2020; Fahlenbrach et al., 2021). Rather closely related to our analysis, Pagano et al. (2020) find that the impact of COVID-19 on stock performance was more severe for firms that operate in sectors that are more vulnerable to social distancing. Ding et al. (2021) report that the adverse impact of the pandemic on stock returns is more pronounced for those firms that have more anti-takeover devices, lower social and corporate responsibility scores, and that depend more heavily on global supply chains. Papanikolaou and Schmidt (2020) reveal that expected revenue growth of those sectors in which a higher fraction of the workforce is not able to work remotely declined significantly during the COVID-19 pandemic. Glover et al. (2020) document that the impact of the COVID-19 pandemic is more serious among younger generations working in vulnerable sectors. Our analysis adds to these studies by providing early evidence that balance sheet and income indicators also show that the pandemic has taken a heavier toll on firms operating in sectors that are more sensitive to distancing.
Secondly, we contribute to the literature that assesses the effectiveness of government policy measures during a crisis (see, for instance in the context of the global financial crisis, Laeven and Valencia, 2013; Norden et al., 2013). By focusing on the differences across sectors, we also build on studies investigating the channel through which the real effect of a crisis materializes. See, for example, Claessens et al. (2012), Chaney et al. (2012), Chodorow-Reich (2014) and Giroud and Mueller (2017) with regard to the global financial crisis, and Leibovici et al. (2020) and Laeven (2022) with regard to COVID-19. Our study differs from these papers since it focuses on the effectiveness of government economic policies during the COVID-19 pandemic, rather than the transmission of the shock itself, by testing whether firms in pandemic-prone sectors performed disproportionately better, if they are domiciled in countries with more comprehensive or larger economic support packages. Closely related to our analysis, Demirgüç-Kunt et al. (2021) examine the impact of policy measures taken in response to the COVID-19 pandemic but only on the performance of the banking sector. They find that, while policy interventions in the form of liquidity support, borrower assistance and monetary easing, in general, mitigate the adverse impact of the crisis, this is not the case for all banks, nor in all circumstances.
The rest of the paper is organized as follows. Section 2 summarizes the potential channels through which policy support could help firm performance in the hardest-hit sectors. Section 3 lays out the methodology and the data. Section 4 presents the findings. Section 5 concludes.
2 Potential transmission channels
2.1 Fiscal support
Fiscal support packages implemented during the pandemic aimed to support businesses and households at a time economic activity was intentionally curtailed to slow the spread of the virus and allay the burden on public health systems. Specific measures included tax cuts, cash handouts, and social welfare payments on the demand side and tax relief measures and guarantees for access to credit on the supply side (Padhan and Prabheesh, 2021).
There are various ways fiscal measures could help firms. First, corporate tax breaks could lessen the decline of profitability. Tax payment deferral is a common measure, in particular, in less developed countries (OECD, 2020a). Yet, this has limited benefit to the pandemic-prone sectors, as they have hardly generated profits and rather suffered from losses. In this instance, alternative measures such as loss carry-back tax provisions can be more effective (OECD, 2020a; Makin and Layton, 2021). This allows firms to claim the losses against taxable profits in previous years, which potentially reduces the losses incurred during the pandemic. Such provisions have been introduced in some countries for the 2020 tax year.
Second, temporary increases in thresholds for low-value asset write-offs and depreciation allowances could mitigate the decline of investment, since they effectively reduce the tax liability of firms. The benefit should be felt across all sectors. However, if the contact-intensive sectors have to alter their business structure in order to survive the pandemic and if this requires investment, then this support should be more advantageous to these sectors. For instance, restaurants may adapt their services away from in-person dining and toward takeaway and delivery of food, or redesign the layout of the premises to maintain distance among customers. Such changes necessitate new investment and could be supported by investment incentives through temporary changes in the tax code. They would help maintain sales and liquidity.
Third, direct government subsidies such as furlough schemes curb the massive employment loss due to lockdowns. Many countries have helped the hardest-hit sectors retain their workers by providing income support to employees whose working hours have been curtailed or who have been temporarily laid off (OECD, 2020b). The scheme enables firms to maintain the match with their employees and to preserve workers' talent and experience. It also deters a deterioration on the production side, since firms are able to quickly resume operations when the lockdown is eased.
Fourth, many heavily affected businesses have experienced a sharp decline in liquidity. The most common instrument to deal with this decline, especially among developed countries, has been loan guarantee schemes, where the government guarantees all or part of the bank loans granted to eligible businesses (OECD, 2020a). Other measures have included interest-free loans and cash grants. These measures are typically able to target or prioritize those businesses adversely affected by the pandemic, alleviating cash flow difficulties, enabling firms pay suppliers or creditors and, hence, avoid default or bankruptcy.
Finally, subsidies to consumers for consumption of certain goods and services could also help the suppliers of such goods and services. This can target the hardest-hit sectors, for example, some governments provided subsidies for eating out or domestic travel.
In general, the delivery speed of support should be a key consideration. For instance, countries may find it timelier to provide loan guarantees, business grants, or wage subsidies rather than tax measures. The effect of the latter is only felt at the end of the tax year. In order to achieve prompt delivery, fiscal aid may also be provided broadly across all sectors rather than targeting certain sectors, but then this is subject to taxation of regular profit. This would imply that adversely affected firms are able to keep the full amount of support by documenting the hit to their profits, while the firms whose economic circumstances have been affected the least would return some of the support via the tax system (Mankiw, 2020; Marron, 2020).
There is, however, potentially an unintended side effect of fiscal support. Higher public debt fueled by the pandemic may harm business and household confidence, creating uncertainty about how public debt would be repaid (OECD, 2020a). To the extent that firms perceive higher public debt to imply higher corporate taxes in the future, it would be reflected as a negative repercussion on the firms' performance. Note also that wage subsidy programs implemented in some countries may prove to be an innovative yet extremely costly way of sustaining business activities and employment, accelerating government debt. Besides, this support may simply delay the inevitable re-deployment of labor away from unviable firms and may not bring about a particular benefit to the vulnerable firms.
2.2 Other policy support
With other policy actions such as monetary easing and foreign exchange intervention, unlike fiscal support, the channels of transmission are not as clear. This is partly because it is difficult to target or prioritize specific sectors or firms that have been bruised by the pandemic. Nevertheless, there is some scope for these measures to alleviate the adverse effect of COVID on these sectors.
Expansionary monetary policy may mitigate the effects of COVID-19 on the hardest-hit sectors if firms in these sectors come under pressure from a tightening of credit conditions. For instance, a fall in interest rates may enable vulnerable sectors to ease liquidity concerns and reduce the probability of default.
During the pandemic period, most economies have experienced exchange rate volatility and often intervened in the foreign exchange market. Vulnerable firms engaged in tourism or international trade may disproportionately benefit from such intervention, mitigating a decline of profits and strengthening the ability to meet debt obligations.
3 Methodology and data
3.1 Empirical strategy
Our main empirical strategy is to examine whether firms in industries that are more pandemic-prone perform disproportionately better during the COVID-19 outbreak, if they happen to be located in countries that have larger government support packages. In other words, if policy measures are to help shield firm performance, then one would expect them to have a larger effect on sectors where a significant share of employment is affected by social distancing measures. This inference can be empirically tested by estimating an econometric model in which the effect of government policies on firms is allowed to differ depending on how pandemic-prone is the industry to which the firm belongs.3 Thus, our model specification is given by:(1) ∆yic,COVID=ϑj+ϑc+∅.Distancingj×Policyc+τ.Xic,Pre+εic,COVID
where i stands for firm, j for sector, and c for country. This is a cross-sectional regression where ∆y ic, COVID is the measure of change in performance indicators for firm i in country c between 2020—the latest data available—and 2019—a year prior. Following Claessens et al. (2012), we use the changes in firm-level performance indicators. Given that COVID-19 began to spread in many countries and was declared a pandemic in 2020Q1, the pattern of change in performance indicators is deemed to be due to the pandemic.
We employ four firm performance indicators: (i) change in asset turnover [∆(SaleA)], as measured by the sales-to-total-assets ratio; (ii) change in profit margin [∆(ProfM)], as measured by the net-profit-to-total-revenue ratio; (iii) change in interest coverage [∆(IntrC)], as measured by earnings before interest and tax divided by interest expenses; and (iv) change in probability of default [∆(ProbD)], as measured by the default risk of publicly listed firms by quantitatively analyzing numerous covariates (see Section 3.2 for the details).
Following Claessens et al. (2012), we employ the changes in sales-to-asset ratio and profit margin to investigate the impact of economic support packages on firm efficiency and profitability. In addition, crises have severe effects on firms' financial health in two aspects (Carletti et al., 2020): draining cash generation and liquidity that is necessary for functioning of firms and evaporating capital. Since during the public health crisis firms find it difficult to generate cash and thus could be expected to default on some obligations, we use the interest coverage ratio to determine whether policy measures help a company to pay interest on its outstanding debt. Also, following Gaganis et al. (2020) and Igan et al. (2022), we consider whether a firm will be able to continue operations, i.e. the probability of default. This captures the likelihood of a default over a particular time horizon, reflecting not only the market-based and accounting-based firm-specific attributes but also the macro-financial environment (Duan et al., 2012). Overall, the first three variables intend to gauge whether government policies help firms in maintaining cash flow and, hence, improving liquidity, and the fourth variable aims to capture the impact on firm survival.
Policyc is a vector of variables that represent the economic support package in country c. We employ three policy variables: (i) cumulative fiscal support expressed in percentage of GDP, (ii) cumulative change in the monetary policy rate expressed in basis points, and (iii) interventions in foreign exchange markets with 0 for no intervention and 1 for intervention. All policy measures are computed over the period January 31st, 2020 (week 1) to December 4th, 2020 (week 43). We investigate the change in the performance of firms over the period 2019–2020 in response to government polices during the period from January to December 2020. We believe that this period represents the most important initial stage of the spread of the crisis, when countries declared the bulk of their policy packages. This is also the period of the collapse of international trade due to non-pharmaceutical public health interventions such as full (or partial) lockdowns and turmoil in financial markets as expectations were quickly revised to take the impact of the pandemic fallout on the global economy into account.
Distancingj is industry j's degree of sensitivity to a pandemic, computed as the share of industry employment affected by social distancing at the three-digit NAICS level (created by Kóren and Petö, 2020; we describe this proxy further in the following subsection).
Xic, Pre is a vector of firm-level explanatory variables, computed as of 2019. Note that, because of the pure cross-sectional nature of our empirical strategy, we enter all firm-level control variables as pre-determined (as do Laeven and Valencia, 2013). We first consider the following five variables: (i) size (Size), measured as the natural log of total assets; (ii) age (Age), calculated by subtracting the firm's incorporation year from 2020; (iii) cash holdings (CashA), computed as the ratio of cash and cash equivalents to total assets; (iv) investment in R&D (RD_A), measured by the ratio of R&D investment to total assets; and (v) a dummy for private firms (Private). These controls are informed by the literature on the determinants of firm performance. Small firms tend to perform worse than their larger counterparts during a crisis (Gandhi and Lustig, 2015). Younger firms face more constraints (Beck et al., 2006; D'Souza et al., 2017). Firms with larger cash holdings tend to be more resilient during a crisis whilst firms with better growth potential tend to invest more in R&D (Bates et al., 2009). Finally, privately-held firms may be different from their listed counterparts along the dimensions we investigate. For instance, Hall et al. (2014) document that public companies hold less cash given their greater access to capital markets as compared to privately-held firms. In addition to these five variables, we also include lags of the following variables as additional regressors: (vi) SaleA, to control for efficiency in generating revenue for a given level of assets; (vii) ROA, to control for pre-crisis differences in levels of profitability; (viii) IntrC, to control for ability to cover current interest payments with available earnings; and (ix) EqitA, to control for leverage given that more highly leveraged firms may face difficulty raising funds during a crisis (Giroud and Mueller, 2019). Overall, all these nine firm-level control variables are rather common in the literature (e.g., Burns et al. 2017; Barbiero et al., 2020; Demirgüç-Kunt et al., 2020).
The main variable of interest is the interaction term Distancing j × Policy c. The coefficient ∅ measures the difference between performance in pandemic-prone sectors in countries with high and low economic support packages. A positive and significant point estimate of ∅ indicates that the vulnerable industries in countries with higher levels of government economic response did not suffer as much from the pandemic. Note, though, that we expect a negative ∅for the probability of default.
ϑj refers to a vector of sectoral dummies (at three-digit NAICS level) to control for sector-specific factors that could affect cross-sector performance differentials. ϑ c are country dummies that account for time-invariant country-specific features that might drive cross-country differences in firm activity, such as the institutional environment. This set of fixed effects absorbs all observable and unobservable time-invariant variations across sectors and countries. Also, they subsume the direct level effects of social distancing and economic policies, namely the Distancing and Policy variables in Eq. (1). By including this set of fixed effects, our identification is obtained by looking at the differential performance of two otherwise identical firms operating in more versus less pandemic-prone sectors.
Eq. (1) is estimated with ordinary least squares (OLS). Residuals from OLS estimations may be correlated across countries, resulting in biased standard errors. Thus, following Demirgüç-Kunt et al. (2020), we cluster standard errors at the country level. An advantage of our empirical strategy is that it incorporates information about heterogeneity across countries in initiating and implementing economic support packages.
One concern is that Eq. (1) is subject to the problem of endogeneity. First, any association between government policies and firm performance may be attributable to omitted variables. Or, it could be that the effect of a particular policy is attributed to another because of their simultaneous implementation. Second, firm performance during a crisis may affect policy responses to the crisis, indicating the possibility of reverse causality.
Our empirical setup provides some leeway in alleviating these two endogeneity issues. By including all policy measures at once, we reduce the issue of simultaneity while our use of sector and country fixed effects mitigates the issue of omitted variable bias. In addition, we control for other potential channels through which policy measures may affect firm performance so as to gain more confidence that distancing remains a relevant channel for policy measures to influence firm performance. Also noteworthy is that endogeneity may even play against the chances to reject the null hypothesis: countries that are affected more by COVID-19 — that is, where pandemic-prone sectors are large and fare particularly bad — may be more likely to deploy large policy packages, giving rise to a negative correlation (which is the opposite of what we find). Nevertheless, we admit that the issue of endogeneity may continue to exist, hence we address this point by conducting several exercises in Section 4.2.4
3.2 Data sources
Applying the empirical strategy laid out in Section 3.1 requires measures of firm performance, sectoral pandemic sensitivity, and economic policy actions. This subsection describes the process of compiling these data.
3.2.1 Firm performance
Firm-level data come from the ORBIS database by Bureau Van Dijk, which provides information on balance sheets and income statements for more than 40 million listed and private companies from more than 100 countries worldwide. As one of the most comprehensive databases of firm-level information, it has been increasingly used in academic research (e.g. Frijns et al., 2016; Baumohl et al., 2019; Demirgüç-Kunt et al., 2020; Barbiero et al., 2020; Cathcart et al., 2020).
We obtain data for 2019 and 2020 (the latest year available at the time of conducting this analysis). This enables us to calculate the change in firm performance during the COVID-19 pandemic. We initially select all firms that belong to the nonfinancial corporate sector, excluding financial firms (identified as firms with NAICS2017 code of 52). We drop firms in sectors with no data on the distancing variable, which are “management of companies and corporations,” “public administration,” and “unclassified establishments” (NAICS2017 codes of 55, 92 and 99, respectively). Also, countries with no data on all of the policy measures of interest are excluded. In addition, we drop offshore financial centers. Following Demirgüç-Kunt et al. (2020), we further restrict our sample to countries with a minimum of 20 firms (with available information for 2020). Last but not least, we drop the United States to avoid any mechanical endogeneity between this variable and firm performance since U.S. data are used to construct the distancing variable.5 Given our interest in evaluating the effectiveness of policy measures in improving firm performance during COVID-19, we focus our baseline analysis on firms that are present in both before and during the crisis. We thus clean the dataset further by excluding all firms with no data available on sales as well as on our main firm-level control variables. This means we focus on the effects of policy measures on the intensive margin only.
As a result, 28,915 firms from 80 countries survive the filtering criteria.6 The number of firms for each country is in Table S1 in the Online Supplementary Appendix (OSA). Note that, after imposing all the criteria, we end up with one country (Mongolia) with less than 20 firms. We confirm the robustness of our results to excluding this country. The number of firms in our dataset varies by country. On average, each country has about 361 firms with available data. We reduce the influence of outliers by winsorizing all dependent variables at the 1st and 99th percentiles.
Following Gaganis et al. (2020) and Igan et al. (2022), the data on probability of default is from the Credit Research Initiative (CRI) of the National University of Singapore. We use a prediction horizon of 1 month. Note that the data on probability of default is not available for all 80 countries and/or 28,915 firms. We have data only for 10,023 firms.
3.2.2 Pandemic sensitivity
Kóren and Petö (2020) estimate each sector's contact intensity, using pre-pandemic data from the Occupational Information Network (O*NET) survey. Specifically, they use information for 809 occupations from the 2010 Standard Occupational Classification System to compute, for each NAICS three-digit code, the share of workers whose job requires a high level of three occupational characteristics: customer contact, teamwork and physical presence.7 They end up reporting two proxies. The first one is a measure of “communication” intensity that incorporates teamwork-intensive and customer-facing activities. The second proxy, “overall” incorporates the physical presence dimension to the first.
In our baseline, we use communication intensity as the metric for Distancing. This arguably captures the nature of non-pharmaceutical interventions put in place in response to COVID-19 due to the fact that shelter-in-place or stay-at-home orders were gradually lifted allowing industries that primarily rely on physical presence (e.g., construction, factories) to get back to work whilst travel restrictions, bans on public gatherings and specific business closures (e.g., gyms and restaurants) remained. We confirm the general robustness of our results to the use of “overall” index. We assume that distancing is an intrinsic characteristic of a sector and, thus, indices derived using U.S. data can be used for the same sector across all countries.
3.2.3 Policy measures
The data source for policy responses is the IMF's Policy Tracker.8 Launched right around the time COVID-19 was declared a pandemic by the WHO on March 11, 2020, this tracker relies on responses by individual country teams to a survey designed by IMF staff. The survey seeks responses on all policy actions taken by the authorities in a country covering fiscal, monetary, external, and financial policies. The survey includes the size of the intervention for fiscal or monetary policy actions. For external and financial policies, information is gathered as a binary variable, with 0 denoting no action and + 1 an intervention.9
In our analysis, we use three policy measures: (i) FIS, cumulative fiscal support expressed in percentage of GDP, (ii) MP_BP, cumulative change in the monetary policy rate expressed in basis points, and (iii) FXI, the interventions in foreign exchange markets. All policy measures are computed over the period January 31, 2020 (week 1) to December 4, 2020 (week 43) to overlap with the firm-level data we have.
The intensity of economic support packages varies considerably (see Figs. S1a and S1b in the OSA for more details). By including countries with no or less strong policy responses as well as those with proactive intervention in our dataset, we reduce concerns that the results may be driven by selection bias.
One shortcoming of this database is the lack of granularity as to the exact measures implemented, in particular, under the fiscal support packages. While a more in-depth analysis would be desirable, it would be better conducted in a set of relatively homogeneous country sample (if not, within a single country). We leave this for future research. That said, we do confirm the robustness of our findings using policy measures from alternative sources (see Section 4.4).
3.2.4 Other variables
Additional data are retrieved from standard databases such as the World Bank's World Development Indicators (WDI). Appendix Table A1 provides the details, in addition to those pertaining to the construction of the main variables that we employ in the analysis.
3.3 Descriptive statistics
Table 1 shows the summary statistics of change in the asset turnover ratio [∆(SaleA)], change in profit margin [∆(ProfM)], change in the interest coverage ratio [∆(IntrC)] and change in the probability of default [∆(ProbD)] over the period from 2019 to 2020. The relation between firm performance and Distancing at the sector level is presented in Panel A. Retail Trade (NAICS 44–45) and Health Care and Social Assistance (NAICS 62) have the highest share of communication-intensive jobs, exceeding 50%. This is followed by Art, Entertainment, and Recreation (NAICS 71) and Accommodation and Food Services (NAICS 72) at around 40 to 44%. These two sectors suffered from the largest decline in sales to asset by 20 to 24% and also in profit margin, dropping by 18 to 24%. We observe the same pattern for the other two indicators of firm performance, change in interest coverage ratio and probability of default, for these two sectors. This heterogeneity across sectors is important to understand the effect of the pandemic and associated policy measures.Table 1 Summary statistics.
Table 1Panel A: Change in firm performance and distancing by sector
NAICS (2d) NAICS (3d) Sub sector Change in firm performance
Sector Obs ∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD) Distancing
11 113–115 3 Agriculture, Forestry, Fishing and Hunting 178 −0.042 −0.020 −3.054 −0.011 0.147
21 211–213 3 Mining, Quarrying, and Oil and Gas Extraction 1012 −0.060 −0.030 −2.146 0.004 0.196
22 221 1 Utilities 1013 −0.044 −0.003 1.548 0.002 0.200
23 236–238 3 Construction 1022 −0.065 −0.021 −1.966 0.002 0.164
31–33 311–339 20 Manufacturing 14,504 −0.073 −0.006 1.188 0.002 0.100
42 423–425 3 Wholesale Trade 2039 −0.108 −0.009 −3.900 0.002 0.154
44–45 441–454 12 Retail Trade 978 −0.152 −0.020 1.016 0.007 0.642
48–49 481–493 9 Transportation and Warehousing 1038 −0.106 −0.050 1.427 0.003 0.134
51 511–519 6 Information 1683 −0.071 −0.022 −3.334 0.002 0.146
53 531–533 3 Real Estate and Rental and Leasing 1293 −0.029 −0.088 −0.952 0.005 0.216
54 541 1 Professional, Scientific, and Technical Services 2016 −0.091 −0.009 −2.038 −0.0001 0.120
56 561–562 2 Administrative and Support and Waste Management … 901 −0.150 −0.042 −6.801 0.008 0.264
61 611 1 Educational Services 126 −0.149 −0.056 −7.885 0.0004 0.190
62 621–624 4 Health Care and Social Assistance 298 −0.084 −0.018 −3.995 0.005 0.596
71 711–713 3 Arts, Entertainment, and Recreation 234 −0.200 −0.179 −14.364 0.003 0.405
72 721–722 2 Accommodation and Food Services 458 −0.239 −0.238 −17.783 0.011 0.440
81 811–813 3 Other Services (except Public Administration) 122 −0.119 −0.064 −11.221 0.005 0.351
Panel B: Summary statistics of main variables
Variable Obs Mean Std p25 Median p75
Change in firm performance (∆yic,COVID)
∆(SaleA) 28,915 −0.08 0.25 −0.16 −0.05 0.02
sectors more pandemic prone 13,694 −0.10 0.27 −0.17 −0.05 0.01
sectors less pandemic prone 15,221 −0.07 0.22 −0.15 −0.05 0.03
∆(ProfM) 26,993 −0.02 0.17 −0.05 −0.001 0.03
sectors more pandemic prone 12,484 −0.04 0.20 −0.07 −0.01 0.03
sectors less pandemic prone 14,509 −0.01 0.15 −0.04 −0.01 0.04
∆(IntrC) 27,845 −0.73 63.94 −4.55 0.02 4.62
sectors more pandemic prone 13,099 −3.29 61.04 −5.59 −0.33 3.17
sectors less pandemic prone 14,746 1.54 66.33 −3.76 0.39 5.92
∆(ProbD) 10,023 0.002 0.04 −0.002 0.001 0.01
sectors more pandemic prone 4748 0.004 0.03 −0.001 0.001 0.01
sectors less pandemic prone 5275 0.001 0.04 −0.003 0.0003 0.01
Pandemic-pronej
Distancing 79 0.16 0.13 0.09 0.11 0.16
Policyc
FIS (% of GDP) 80 11.62 10.29 6.1 6.1 14.6
MP_BP (−1*basis point/100) 80 0.71 1.09 0.15 0.3 1.15
FXI 80 0.24 0.43 0 0 0
Controls (Xic,Pre)
Size (log) 28,915 11.64 2.25 9.98 11.5 13.13
Age (log) 28,915 3.17 0.77 2.71 3.09 3.66
CashA 28,915 0.13 0.14 0.03 0.09 0.18
RD_A 28,915 0.02 0.04 0 0 0.02
Private (dummy) 28,915 0.05 0.22 0 0 0
SaleA 28,915 0.87 0.85 0.41 0.71 1.09
ROA (%) 28,915 2.70 13.62 0.31 3.84 8.31
IntrC 28,915 38.09 117.42 0.81 4.49 19.89
EqitA 28,915 0.49 0.37 0.35 0.52 0.68
The summary statistics for the main variables used in the regression analysis are shown in Panel B, Table 1. The sectors are classified as more pandemic-prone (i.e. greater than cross-country median) and less pandemic-prone (i.e. less than median) for the four dependent variables capturing firm performance. Among others, the mean values clearly indicate lower sales, profit margins, and interest coverage and higher probability of default for sectors that are more vulnerable.
4 Empirical findings
Before presenting our baseline results, we first show that the adverse impact of COVID-19 on firm performance is indeed more pronounced for pandemic-prone sectors. This is to validate the hypothesis that pandemic-sensitive sectors suffered more and, hence, needed support more.
Applying a variation of Eq. (1), Table 2 shows the impact of the pandemic. Column 1 displays a negative significant sign on the coefficient of Distancing when the dependent variable is ∆(SaleA). It implies that a decline in sales to be more noticeable for those sectors that are intrinsically more sensitive to social distancing. This result is supportive of a significant channel captured by Distancing, being consistent with Kóren and Petö (2020). For the profit margin,∆(ProM), the coefficient in column 2 is also negative and significant. It is a plausible result in that firms in pandemic-prone sectors are unable to generate profit, whilst experiencing a drop in sales, possibly being forced to cut profit margins in order to survive the pandemic. We observe a negative significant sign for the change in the ratio of earnings to interest expenses, ∆(IntC) in column 3 and a positive significant sign for the probability of default, ∆(ProD) in column 4. The pandemic has not only drained liquidity but has also increased the probability of default in vulnerable firms.Table 2 Social distancing and firm performance during COVID-19.
Table 2 Without interaction Interacted with COVID-19 severity
∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD) ∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD)
(1) (2) (3) (4) (5) (6) (7) (8)
Distancingj −0.122*** −0.124*** −1.190*** 0.014*
(−6.499) (−13.098) (−8.142) (1.900)
Distancingj x Covid_Severityc −0.002* −0.002*** −0.015 0.001***
(−1.771) (−2.901) (−1.427) (3.334)
Controlsic,pre (Size, Age, CashA, RD_A, Private, SaleA, ROA, IntrC, EqitA) √ √ √ √ √ √ √ √
Constant 0.019 −0.039*** 0.365** −0.016* 0.011 −0.061 −0.293 −0.025***
(0.814) (−3.009) (2.561) (−1.871) (0.470) (−1.327) (−0.681) (−2.744)
Sector FEs N N N N Y Y Y Y
Country FEs Y Y Y Y Y Y Y Y
# Countries 80 80 80 80 80 80 80 80
# Sectors 79 79 79 79 79 79 79 79
N 28,915 26,993 27,841 10,023 28,860 26,941 27,791 10,023
Adj. R2 0.154 0.096 0.080 0.024 0.175 0.142 0.093 0.035
This table reports the results estimating ∆yic, COVID = ϑc + ∅ . Distancingj + τ. Xic, Pre + εic, COVID and ∆yic, COVID = ϑj + ϑc + ∅ . Distancingj × Covid_Severityc + τ. Xic, Pre + εic, COVID where i stands for firm, j for sector, and c for country. ∆yic, COVID is the change in performance ratios for firm i in country c between 2020 and 2019. We use, alternatively, change in asset turnover ratio [∆(SaleA)], change in profit margin [∆(ProfM)], change in interest coverage ratio [∆(IntrC)], and change in probability of default [∆(ProbD)]. Distancingj is industry j's degree of sensitivity to a pandemic from Kóren and Petö (2020). Covid_Severityc is a proxy for severity of COVID-19 in country c, using the Oxford stringency index. Xic, Pre is a vector of firm-level explanatory variables, computed as of 2019. We include sector fixed effects (ϑj) in Columns 5–8 at the three-digit NAICS level as well as country fixed effects (ϑc) in all regressions. See Appendix, Table A1 for detailed definition of variables. Regressions are estimated using OLS. The statistical inferences are based on clustered standard errors at the country level (associated t-values reported in parentheses). ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.
In columns 5–8, Distancing j is interacted with COVID_Severity c, that is, the country-level severity of the lockdown measures in response to the pandemic. This is a composite measure based on nine response indicators including school closures, workplace closures, and travel bans, rescaled to a value from 0 to 100 with the score 100 being the strictest (Hale et al., 2020). Although the sign on the interaction coefficients is identical, the coefficients are less significant both statistically and in terms of magnitude when compared with those in columns 1–4.10 The implication is that more weight is placed on the vulnerability of the specific sectors, rather than the exposure to the pandemic at the country level, when explaining firm performance. Indeed, this is a reasonable outcome: sectors such as tourism and airlines are severely affected, whereas others such as information technology end up even benefiting from social distancing. This phenomenon is common across countries.11
4.1 Baseline results
Having observed the negative performance of pandemic-prone sectors in Table 2, we explore whether these industries are the ones that benefited more from economic support measures. We specifically examine whether the support measures alleviate the severity of the pandemic's impact on firm performance by interacting the policy measures with the distancing proxy. In Table 3 , all policy measures are simultaneously included.Table 3 Social distancing and firm performance during COVID-19: Baseline results.
Table 3 ∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD)
(1) (2) (3) (4)
Distancingj x FISc 0.003** 0.001** 0.030*** −0.001**
(2.369) (2.321) (2.795) (−2.500)
Distancingj x MP_BPc 0.031* 0.023 0.169 −0.004
(1.922) (1.649) (1.186) (−0.813)
Distancingj x FXIc −0.011 0.026 0.736** −0.010
(−0.255) (0.978) (2.043) (−1.518)
Controlsic,pre (Size, Age, CashA, RD_A, Private, SaleA, ROA, IntrC, EqitA) √ √ √ √
Constant 0.008 −0.067 −0.443 −0.022**
(0.303) (−1.446) (−0.967) (−2.493)
Sector FEs Y Y Y Y
Country FEs Y Y Y Y
# Countries 80 80 80 80
# Sectors 79 79 79 79
N 28,915 26,993 27,841 10,023
Adj. R2 0.175 0.142 0.093 0.035
Differential in firm performance (%)
Distancingj x FISc 2.03 0.68 20.29 −0.68
This table reports the results estimating ∆yic, COVID = ϑj + ϑc + ∅ . Distancingj × Policyc + τ. Xic, Pre + εic, COVID where i stands for firm, j for sector, and c for country. ∆yic, COVID is the change in performance ratios for firm i in country c between 2020 and 2019. We use, alternatively, change in asset turnover ratio [∆(SaleA)], change in profit margin [∆(ProfM)], change in interest coverage ratio [∆(IntrC)], and change in probability of default [∆(ProbD)]. Policyc is a vector of variables representing government economic support packages in country c. Distancingj is industry j's degree of sensitivity to a pandemic from Kóren and Petö (2020). Xic, Pre is a vector of firm-level explanatory variables, computed as of 2019. We include sector fixed effects (ϑj) at the three-digit NAICS level as well as country fixed effects (ϑc) in all regressions. See Appendix, Table A1 for detailed definition of variables. Regressions are estimated using OLS. The statistical inferences are based on clustered standard errors at the country level (associated t-values reported in parentheses). ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.
Overall, we find evidence of a positive impact of fiscal policy during the pandemic for vulnerable sectors, and indeed, fiscal support appears to be working as intended by policymakers.12 Fiscal policy is statistically significant in all four cases (columns 1–4) at the 5% or 1% level, improving sales, profit margins, and liquidity position and, at the same time, decreasing the probability of insolvency for vulnerable sectors, holding other policy variables constant. This is consistent with the findings reported in studies analyzing the global financial crisis episode (e.g. Aghion et al., 2014; Claessens et al., 2012; Laeven and Valencia, 2013).
Monetary policy easing appears to have been effective in supporting sales revenue, though at the marginal significance level of 10% (column 1). Note that the various robustness tests conducted in the subsequent subsections reveal a clearer effect of monetary policy on firm performance. In this respect, the functioning of monetary policy transmission appears to be, at least, preserved during the pandemic. This is in contrast with the case of the global financial crisis, when bank balance sheet constraints substantially weakened monetary policy transmission (Van den Heuvel, 2009), and attests to the importance of advances in prudential regulation and deleveraging that allowed banks face the pandemic shock in much better shape than they did the subprime mortgage shock.
Foreign exchange intervention seems to have mitigated the decline of interest coverage during the pandemic (column 3). One of the possible explanations of this outcome may be the fact that the earnings of pandemic-prone sectors such as tourism are receptive to changes in the value of the domestic currency against foreign currencies. By limiting excessive volatility in the exchange rate, FXI may have protected earnings and kept interest expenses in check (especially if part of the debt is denominated in foreign currency). In this respect, the positive sign on the coefficient of profit margin (∆(ProfM)) is consistent, though it is insignificant.
Sales and interest coverage appear to be more responsive to policy measures, whereas the profit margin and the probability of default seem to respond only to fiscal measures. This may be explained as follows: during the pandemic, there is little scope for raising margins for those vulnerable firms, culminating in smaller response to other policy support than to specific fiscal instruments such as tax payment deferral or loss carry-back tax provisions that may have a direct impact on the profit margin. Similarly, default is not an unlikely outcome for vulnerable firms, in particular, for those with high levels of debt that were accumulated before the pandemic. Fiscal measures such as loan guarantee schemes, interest-free loans, or cash grants may have effectively mitigated the risk of default.13
A natural question is whether these statistically significant results translate into economic significance. We provide some analysis on this based on the magnitude of coefficients reported in Table 3. For a sector with the average vulnerability to the pandemic (corresponding to a Distancing index value of 0.16), an increase in fiscal support by one standard deviation or 10.29 — nearly the equivalent of increasing fiscal support from the level of Argentina (5.6) to that of the UK (16.1) — would have led to an improvement in the change in sales-to-asset ratio during the pandemic by 0.49%. For retail trade, which carries the greatest vulnerability to the pandemic, the improvement would be 1.98%. Table A2 in the Appendix extends this analysis across the spectrum of pandemic vulnerability and presents the estimated effect of one standard deviation increase in economic support on the change in firm performance for sectors at different percentiles of the distancing index. We find that the policy impact is indeed larger for more pandemic-prone sectors. A one standard-deviation increase in fiscal (monetary) support is associated with an improvement in the change in sales-to-asset ratio of 0.86% (0.95%) for the more pandemic-prone sectors (at the 90th percentile, such as Accommodation and Food), compared to only 0.22% (0.24%) for less pandemic-prone sectors (at the 10th percentile, for example, Manufacturing).
To provide further context, the estimated values for the differential in firm performance between most and least pandemic-prone sectors are shown at the bottom of Table 3 (Differential in firm performance) for fiscal support (the measure that appears to robustly influence).14 Let's focus on the sales-to-assets ratio. The estimation results in column 1 of Table 3 suggest that a firm from an industry at the 90th percentile of distancing would have a change in sales-to-assets that is 2.05 percentage points higher than a firm from a sector that is at the 10th percentile of distancing, if it were located in a country that is at the 90th percentile in fiscal support compared to a country at the 10th percentile. Similarly, the estimation results in column 4 of Table 3 suggest that, relative to less pandemic-prone sectors (at the 10th percentile), the probability of default in more pandemic-sensitive sectors (at the 90th percentile) is around 0.68 percentage points less in a country that launched significant fiscal support (at the 90th percentile) than in a country with a limited fiscal support (at the 10th percentile). Note that both differentials in changes in the sales-to-asset ratio and the probability of default are not negligible, compared to the average rates of change in SaleA and ProbD during the pandemic (which are −8.26% and 0.22%, respectively).
The baseline result is based on the cumulative interventions over the course of 2020 and their impact on outcomes for all of 2020. As an extension, we exploit the differences in timing by decomposing the intervention period after the onset of the pandemic in 2020Q1 into quarterly intervals: Q2, Q3, and Q4. The results are shown in Table 4 . It is noteworthy, though not surprising, that the impact is not monotonic: the initial impact of fiscal support is stronger based on the relatively large magnitudes of coefficients in Q2 as compared with those in Q3 and Q4 (which are pretty close to those of the baseline presented in Table 3). The differences are, however, negligible for monetary policy and foreign exchange intervention.Table 4 Social distancing, economic support packages, and firm performance during COVID-19 pandemic: Q2 vs. Q3 vs. Q4.
Table 4 Support packages in Q2, 2020 Support packages in Q3, 2020 Support packages in Q4, 2020
∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD) ∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD) ∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)
Distancingj x FISc 0.180*** 0.026 1.262*** −0.027* 0.003** 0.001 0.027** −0.001** 0.003** 0.001** 0.028** −0.001**
(5.333) (0.748) (2.823) (−1.999) (2.306) (1.508) (2.419) (−2.506) (2.301) (2.283) (2.598) (−2.436)
Distancingj x MP_BPc 0.035* 0.021 0.244 −0.003 0.038* 0.024 0.242 −0.004 0.031* 0.024* 0.176 −0.004
(1.740) (1.248) (1.622) (−0.636) (1.895) (1.457) (1.490) (−0.802) (1.921) (1.701) (1.210) (−0.812)
Distancingj x FXIc −0.068* −0.009 0.222 −0.005 −0.048 −0.005 0.420 −0.010 −0.014 0.014 0.603 −0.009
(−1.740) (−0.316) (0.681) (−0.602) (−1.284) (−0.171) (1.094) (−1.489) (−0.340) (0.497) (1.639) (−1.457)
Controlsic,pre (Size, Age, CashA, RD_A, Private, SaleA, ROA, IntrC, EqitA) √ √ √ √ √ √ √ √ √ √ √ √
Constant 0.016 −0.063 −0.361 −0.023** 0.015 −0.062 −0.383 −0.023** 0.009 −0.065 −0.422 −0.022**
(0.592) (−1.366) (−0.800) (−2.568) (0.551) (−1.350) (−0.837) (−2.593) (0.325) (−1.402) (−0.920) (−2.494)
Sector FEs Y Y Y Y Y Y Y Y Y Y Y Y
Country FEs Y Y Y Y Y Y Y Y Y Y Y Y
# Countries 80 80 80 80 80 80 80 80 80 80 80 80
# Sectors 79 79 79 79 79 79 79 79 79 79 79 79
N 28,915 26,993 27,841 10,023 28,915 26,993 27,841 10,023 28,915 26,993 27,841 10,023
Adj. R2 0.176 0.142 0.093 0.034 0.176 0.142 0.093 0.035 0.175 0.142 0.093 0.035
This table reports the results estimating ∆yic, COVID = ϑj + ϑc + ∅ . Distancingj × Policyc + τ. Xic, Pre + εic, COVID where i stands for firm, j for sector, and c for country. ∆yic, COVID is the change in performance ratios for firm i in country c between 2020 and 2019. We use, alternatively, change in asset turnover ratio [∆(SaleA)], change in profit margin [∆(ProfM)], change in interest coverage ratio [∆(IntrC)], and change in probability of default [∆(ProbD)]. Policyc is a vector of variables representing government economic support packages in country c, launched either in Q2, Q3 or Q4, 2020. Distancingj is industry j's degree of sensitivity to a pandemic from Kóren and Petö (2020). Xic, Pre is a vector of firm-level explanatory variables, computed as of 2019. We include sector fixed effects (ϑj) at the three-digit NAICS level as well as country fixed effects (ϑc) in all regressions. See Appendix, Table A1 for detailed definition of variables. Regressions are estimated using OLS. The statistical inferences are based on clustered standard errors at the country level (associated t-values reported in parentheses). ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.
The larger impact of early fiscal intervention on the overall 2020 outcomes is consistent with the notion that the speed of delivery matters (see Section 2.1). Providing a lifeline to the worst-hit firms immediately helps them find ways to adjust to the shock before any deterioration in financial performance sets in. The non-monotonic pattern being visible for fiscal support but not for other policy support also speaks to the feasibility of tailoring measures to those in need: monetary easing and foreign exchange intervention are indirect and less likely to facilitate adjustment by those hit hardest so it makes little difference when they are implemented. That said, the non-monotonic impact finding for fiscal policy could also be an indication that the choice of fiscal measures is consequential: those faster to implement are also the ones that deliver more bang for the buck. We leave the question of whether timing or design of fiscal support packages matters more to future research.
4.2 Endogeneity issues
The key challenges to our identification strategy are the two usual endogeneity problems: omitted variable bias and reverse causality. We conduct several exercises to address them.
4.2.1 Omitted variable bias
The established positive correlation between economic support and firm performance is in line with our hypothesis, which suggests that government policies during the pandemic have provided life support for hardest-hit firms. Yet, the support packages may automatically pick up the effects of some country-level and/or sectoral-level latent variables that could also affect firm performance (Hyytinen and Toivanen, 2005). For instance, countries more open to trade and cross-border capital flows may launch more economic support given their larger exposure to the negative shocks and the broader lift to the economy cushions firms' performance, and this may, in turn, lead to a spurious positive association between support packages and firm outcomes. To address the omitted variable bias, we evaluate the significance of such variables by controlling for observable characteristics – especially at the country/industry level – that may affect firms' performance.
Following the existing literature, we consider two sets of characteristics. The first set includes those that are related to firm activities through country characteristics (Other country characteristics). These include five variables classified into four groups of a) pandemic resilience, b) channels of transmission, c) bank stability, and d) macroeconomic stability (see, for example, Claessens et al., 2010; Martin and Nagler, 2020; Igan et al., 2022). These country-specific features are interacted with Distancing.a) Pandemic resilience: We consider the overall vulnerability of a country to the pandemic by utilizing the variable of private health expenditure per capita (HealE). Higher spending can reasonably be interpreted as greater resilience, to the extent that it captures ease of access to health services and a widespread healthcare infrastructure. Data are collected from the World Health Organisation as reported by the World Bank.
b) Channels of transmission: Previous research has highlighted the role of real and financial channels through which a crisis can spread across countries. While arguably less applicable to the case of COVID-19 given the different nature of the shock, these channels may still matter in the transmission of the economic effects. For instance, given restrictions imposed on movement across and within borders, supply can be disrupted and countries that are more connected to global value chains may feel the effects more profoundly. We consider two variables: (i) foreign direct investment (FDI), as a proxy for financial interconnectedness, and (ii) total exports and imports in % of GDP (Trade), as a proxy for a country's economic integration with the rest of the world. Data are retrieved from the World Bank.
c) Bank stability: The health of bank balance sheets could be an amplifier of the economic shocks. In order to capture bank health, we include the ratio of non-performing loans to total loans (NPL). Data come from the World Bank.
d) Macroeconomic stability: We capture the general macroeconomic stability of a country by including inflation (Inflation). Data are collected from the WDI.15
Other channels of propagation emphasized in the literature involve liquidity constraints and sensitivity to consumer demand in non-financial firms.16 Hence, as a second set of characteristics, we consider the effect of these two sectoral characteristics, which may interact particularly with financial policy measures. It follows that we control for sectoral characteristics by interacting the variables of external financial dependence (FinDep) and demand sensitivity (DemSen) of individual sectors, respectively, with the policy variables. We use the Rajan and Zingales (1998) index for external finance dependence and an index of sensitivity to demand shocks based on the stock price response to the September 11 shock, as computed by Tong and Wei (2008). We examine the extent to which policy measures affect firm performance through these two potential channels.
In Table 5 , we present the model by controlling for interactions of both country and sector characteristics simultaneously. The main results are close to those in the baseline reported in Table 3 in terms of the sign, magnitude, and significance of the coefficients (or even better with more significant coefficients). This highlights that pandemic-prone firms disproportionately benefit from fiscal support, in general.Table 5 Addressing omitted variable bias: Controlling for other country and sector characteristics.
Table 5 ∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD)
(1) (2) (3) (4)
Distancingj x FISc 0.004*** 0.002** 0.023** −0.001**
(3.116) (2.144) (2.026) (−2.485)
Distancingj x MP_BPc 0.035** 0.020 0.246* −0.013***
(2.403) (1.288) (1.670) (−3.078)
Distancingj x FXIc 0.001 0.042 0.894** −0.013
(0.015) (1.337) (2.157) (−1.317)
Other country characteristics
Distancingj x HealEc −0.000 −0.000** −0.001 −0.000
(−0.445) (−2.582) (−1.523) (−0.881)
Distancingj x FDIc 0.002 −0.001 −0.001 −0.000
(0.901) (−0.982) (−0.098) (−0.816)
Distancingj x Tradec 0.002 0.001 0.032 −0.000
(0.658) (0.320) (1.074) (−0.132)
Distancingj x NPLc −0.001 0.002 −0.023* 0.000
(−0.784) (1.576) (−1.850) (0.703)
Distancingj x Inflationc −0.014 0.008 −0.166 0.002
(−0.619) (0.353) (−0.834) (0.306)
Other sector characteristics −0.098** −0.028 −0.138 0.004
FinDepj x FISc (−2.613) (−0.686) (−0.291) (0.369)
FinDepj x MP_BPc 0.022 0.014 0.435 −0.009
(0.668) (0.511) (1.641) (−1.660)
FinDepj x FXIc −0.004*** −0.004 −0.042 −0.000
(−2.844) (−1.151) (−1.494) (−0.577)
DemSenj x FISc 0.001* 0.000 0.003 −0.000
(1.815) (0.982) (1.228) (−0.420)
DemSenj x MP_BPc 0.004 −0.002 −0.008 −0.003
(1.500) (−0.644) (−0.408) (−1.474)
DemSenj x FXIc 0.001 0.003 0.027 0.008***
(0.291) (0.822) (0.322) (3.045)
Controlsic,pre (Size, Age, CashA, RD_A, Private, SaleA, ROA, IntrC, EqitA) √ √ √ √
Constant −0.145** −0.199*** −2.160*** 0.028
(−2.541) (−4.552) (−4.890) (1.482)
Sector FEs (4-digit level) Y Y Y Y
Country FEs Y Y Y Y
# Countries 80 80 80 80
# Sectors 79 79 79 79
N 25,581 23,884 24,648 9039
Adj. R2 0.174 0.155 0.098 0.033
This table reports the results estimating ∆yic, COVID = ϑj + ϑc + ∅ . Distancingj × Policyc + τ. Xic, Pre + ∇ . Zijc, Pre + εic, COVID where i stands for firm, j for sector, and c for country. ∆yic, COVID is the change in performance ratios for firm i in country c between 2020 and 2019. We use, alternatively, change in asset turnover ratio [∆(SaleA)], change in profit margin [∆(ProfM)], change in interest coverage ratio [∆(IntrC)], and change in probability of default [∆(ProbD)]. Policyc is a vector of variables representing government economic support packages in country c. Distancingj is industry j's degree of sensitivity to a pandemic from Kóren and Petö (2020). Xic, Pre is a vector of firm-level explanatory variables, computed as of 2019. Zijc, Pre is a vector of country-specific or sector-specific (interacted with Distancing or Policy variables) new control variables. We include sector fixed effects (ϑj) at the three-digit NAICS level as well as country fixed effects (ϑc) in all regressions. See Appendix, Table A1 for detailed definition of variables. Regressions are estimated using OLS. The statistical inferences are based on clustered standard errors at the country level (associated t-values reported in parentheses). ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.
Contrary to previous studies (e.g. Aghion et al., 2014; Laeven and Valencia, 2013), we do not find much of a significant effect of fiscal support on firms that are more dependent on external finance and firms that are more demand sensitive. A plausible interpretation of this result is that, in the context of the COVID-19 shock's impact on firm performance and survival, the main channel through which fiscal support helped is the alleviation of and facilitation of adjustment to the impact of non-pharmaceutical interventions rather than an easing of financial constraints or protection against a general drop in aggregate demand. This result manifests itself that the fiscal support is rather successful in targeting the vulnerable sectors caused by the pandemic.
Expansionary monetary policy continues to put a floor on sales and mitigates the risk of default. The latter result is new relative to the baseline in Table 3 and a plausible outcome as monetary policy easing can relieve debt service pressures. The impact of FXI on ∆(IntrC) is still attributable to differences across sectors in terms of how vulnerable they are to distancing rather than other sectoral characteristics (column 3). As before, the liquidity position in vulnerable sectors improves when there is intervention in the foreign exchange market.
While these control variables account for a reasonable amount of country- and sector-specific information, they may not entirely capture all relevant factors. Then, our results may still be biased due to unobservable variables that may be correlated with support packages and subsequently with firm performance. We make selection on these observable factors to determine the likelihood that our estimates are being driven by unobserved heterogeneity across countries and sectors. The results also remain intact in this exercise (See Table S5 together with the related discussion in the Online Supplementary Appendix (OSA)).
4.2.2 Reverse causality
Even if the COVID-19 shock is exogenous, the reaction of policymakers may not be random (Demirgüç-Kunt et al., 2021). For instance, companies, especially large ones, that were adversely affected by the pandemic and associated lockdown measures may be more likely to be supported by the government.
To deal with this endogeneity concern, we apply three different strategies. First, we drop the top 3 pandemic-prone industries in each country from our sample. The underlying idea is that the most vulnerable sectors in a country may be the ones to influence government policies. Second, we exclude large firms (firms with revenue greater than USD 5 billion) from the dataset. If activities of firms determine the degree of government intervention, then this would be more likely to be the case with large influential firms. By contrast, one may expect that smaller firms are more vulnerable to COVID-19 and, thus, may benefit more from government policies, rather than the other way round. Finally, we remove countries with a high share of pandemic-prone sectors to the GDP. This is because the reverse causality effect should be in tandem with the size of vulnerable industries relative to the overall size of the economy (Levintal, 2013). In other words, one would expect a larger reverse causality bias in countries where the pandemic-prone sectors constitute a significant portion of GDP. We measure this share as Sharec=∑j=1nDistancingj×ValuAj/GDPc where ValuA is value added of sector j computed as the sum of earnings before taxes, depreciation and labor expense (Laeven and Valencia, 2013). ValAdd j/GDP c is measured for year 2019. We then remove countries in the 75th percentile of Share.
The results are in Table 6 and resonate with those in the baseline reported in Table 3. Removing the top 3 pandemic-prone sectors (columns 1–4), largest firms (columns 5–8) or countries with a high share of pandemic-prone sectors (columns 9–12) do not alter the findings and, actually, in some cases deliver larger and more statistically significant coefficients.Table 6 Addressing reverse causality.
Table 6 Removing top 3 pandemic-prone sectors Removing large firms Removing countries with a high share of pandemic-prone sectors to GDP
∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD) ∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD) ∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)
Distancingj x FISc 0.003* 0.002** 0.027*** −0.001** 0.003** 0.001** 0.031*** −0.001** 0.004** 0.001** 0.035*** −0.001***
(1.794) (2.561) (2.692) (−2.517) (2.400) (2.318) (2.978) (−2.513) (2.571) (2.025) (4.473) (−5.276)
Distancingj x MP_BPc 0.033* 0.028* 0.193 −0.001 0.032* 0.023 0.171 −0.004 0.035* 0.029** 0.122 −0.007
(1.761) (1.981) (1.391) (−0.279) (1.986) (1.655) (1.200) (−0.826) (1.810) (2.064) (0.864) (−1.098)
Distancingj x FXIc −0.025 0.028 0.794** −0.016** −0.010 0.027 0.749** −0.010 −0.001 0.019 1.302*** −0.015*
(−0.572) (1.000) (2.010) (−2.100) (−0.243) (0.995) (2.076) (−1.549) (−0.014) (0.636) (4.523) (−1.786)
Controlsic,pre (Size, Age, CashA, RD_A, Private, SaleA, ROA, IntrC, EqitA) √ √ √ √ √ √ √ √ √ √ √ √
Constant 0.011 −0.066 −0.451 −0.022** 0.006 −0.067 −0.434 −0.022** 0.021 −0.067 −0.629 −0.004
(0.391) (−1.415) (−0.989) (−2.570) (0.214) (−1.442) (−0.950) (−2.572) (0.719) (−1.428) (−1.398) (−0.445)
Sector FEs Y Y Y Y Y Y Y Y Y Y Y Y
Country FEs Y Y Y Y Y Y Y Y Y Y Y Y
# Countries 80 80 80 80 80 80 80 80 63 63 63 63
# Sectors 76 76 76 76 79 79 79 79 79 79 79 79
N 28,775 26,858 27,709 9950 28,825 26,904 27,751 9980 24,246 22,867 23,308 7632
Adj. R2 0.173 0.142 0.093 0.035 0.175 0.142 0.093 0.035 0.169 0.135 0.088 0.039
This table reports the results estimating ∆yic, COVID = ϑj + ϑc + ∅ . Distancingj × Policyc + τ. Xic, Pre + εic, COVID where i stands for firm, j for sector, and c for country. ∆yic, COVID is the change in performance ratios for firm i in country c between 2020 and 2019. We use, alternatively, change in asset turnover ratio [∆(SaleA)], change in profit margin [∆(ProfM)], change in interest coverage ratio [∆(IntrC)], and change in probability of default [∆(ProbD)]. Policyc is a vector of variables representing government economic support packages in country c. Distancingj is industry j's degree of sensitivity to a pandemic from Kóren and Petö (2020). Xic, Pre is a vector of firm-level explanatory variables, computed as of 2019. We include sector fixed effects (ϑj) at the three-digit NAICS level as well as country fixed effects (ϑc) in all regressions. See Appendix, Table A1 for detailed definition of variables. Regressions are estimated using OLS. The statistical inferences are based on clustered standard errors at the country level (associated t-values reported in parentheses). ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.
To address any remaining endogeneity issue, we utilize the shock components for each policy as instruments. We also use a proxy for the quality of the institutional environment to further orthogonalize the policy response. The details of the instrumental-variable (IV) strategy are in the Online Supplementary Appendix (OSA) together with the result in Table S6 in OSA. We find that fiscal support relates positively and statistically significantly to the performance of pandemic-prone sectors, with a magnitude which is even larger than that reported in Table 3 for the OLS case. Overall, the IV estimator supports our baseline results.
To sum up, in this subsection, we have conducted a number of exercises to verify that the association we unveiled in Table 3 between economic support packages and firm performance during COVID-19 can reasonably be considered to not suffer from omitted variable bias and reverse causality.17
4.3 Additional analyses
Next, we investigate whether pre-COVID firm characteristics influence the link between policies and performance during COVID-19. This is of interest to shed some more light on how different policies could be having an impact on different firms.
We focus on four firm characteristics commonly-studied in the literature (Giroud and Mueller, 2017). The first is size, and the other three relate to liquidity constraints and leverage. On the one hand, because of the adverse impact of COVID-19 on revenues and free cash flow, one may expect that smaller firms and firms with less cash, more leverage and less profitability to be more vulnerable and, thus, benefit more from economic support policies. On the other hand, larger firms and those with stronger financial positions may be better situated to utilize the lifelines provided by the policy measures, including by spreading out the fixed costs and taking advantage of economies of scale.
In related research, Ding et al. (2021) find that stock prices of firms entering the COVID-19 crisis with a better position in terms of cash holdings, leverage, and profitability performed relatively better during the crisis. Fahlenbrach et al. (2021) report that financial flexibility (proxied, for example, by cash holdings) is one of the factors explaining why some firms performed better during COVID-19. Laeven (2022) finds that large firms and firms with cash buffers were better able to absorb the pandemic shock. Carletti et al. (2020) also report that distress in terms of book value of equity is more frequent for small and medium-sized enterprises and for firms with high pre-COVID leverage.18
Table 7 shows the results obtained by re-estimating the baseline specifications of Table 3 with respect to pre-crisis firm size (Panel A), cash holdings (Panel B), profitability (Panel C), and leverage (Panel D). Columns 1–4 (5–8) in all four panels include only the firms that are below (above) the sample median value with respect to the firm characteristic in question.Table 7 Heterogeneity in firms' size and financial positions entering the pandemic.
Table 7 (<Mdn.) (>Mdn.)
∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD) ∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD)
(1) (2) (3) (4) (5) (6) (7) (8)
Panel A: Size
Distancingj x FISc 0.002 0.002 0.026 −0.001 0.004*** 0.001 0.031*** −0.001***
(1.020) (1.446) (1.507) (−0.847) (3.070) (1.391) (3.190) (−3.379)
Distancingj x MP_BPc 0.026 0.028*** 0.108 −0.005 0.037** 0.023 0.253 −0.003
(1.031) (2.726) (0.642) (−0.688) (2.127) (1.024) (1.412) (−0.705)
Distancingj x FXIc −0.010 0.046 0.940** −0.021** −0.015 −0.002 0.418 0.003
(−0.174) (1.043) (1.996) (−2.040) (−0.346) (−0.037) (1.271) (0.321)
N 14,440 13,237 13,630 2361 14,475 13,756 14,211 7662
Adj. R2 0.155 0.122 0.096 0.080 0.231 0.183 0.091 0.045
Panel B: Cash
Distancingj x FISc 0.003 0.001 0.021* −0.001** 0.004*** 0.001 0.044*** −0.001***
(1.016) (1.362) (1.937) (−2.165) (3.622) (1.514) (3.028) (−2.793)
Distancingj x MP_BPc 0.021 0.038** 0.178 −0.003 0.058** −0.016 0.035 −0.005
(1.077) (2.535) (1.053) (−0.523) (2.471) (−0.763) (0.136) (−1.056)
Distancingj x FXIc 0.009 −0.001 0.546 −0.018 −0.036 0.073* 0.892* −0.001
(0.217) (−0.035) (1.422) (−1.533) (−0.499) (1.966) (1.915) (−0.128)
N 14,446 13,162 14,065 3903 14,469 13,831 13,776 6120
Adj. R2 0.168 0.158 0.088 0.059 0.181 0.134 0.100 0.012
Panel C: Profitability (ROA)
Distancingj x FISc 0.002 0.002 0.011 −0.001** 0.005*** 0.001 0.046*** −0.0002
(1.452) (1.582) (0.845) (−2.703) (2.666) (1.216) (3.536) (−1.399)
Distancingj x MP_BPc 0.031 0.027 0.010 −0.007 0.035 0.016 0.433** −0.001
(1.414) (1.462) (0.080) (−0.721) (1.198) (1.223) (2.171) (−0.673)
Distancingj x FXIc 0.010 0.014 0.661** −0.019 −0.032 0.046 0.700 −0.003
(0.240) (0.342) (2.389) (−1.475) (−0.526) (1.498) (1.248) (−0.611)
N 14,471 12,929 13,904 4798 14,444 14,064 13,937 5225
Adj. R2 0.162 0.158 0.095 0.052 0.190 0.140 0.097 0.040
Panel D: Leverage (EqitA)
Distancingj x FISc 0.002 0.000 0.003 −0.001** 0.007*** 0.003*** 0.090*** −0.001***
(0.939) (0.313) (0.297) (−2.128) (8.007) (2.933) (4.885) (−3.037)
Distancingj x MP_BPc 0.028 0.018 0.020 0.003 0.054** 0.039** 0.526** −0.009**
(1.368) (1.333) (0.159) (0.718) (2.463) (2.040) (2.347) (−2.086)
Distancingj x FXIc −0.030 0.003 0.758** −0.016 0.012 0.031 0.431 −0.007*
(−0.676) (0.084) (2.521) (−1.214) (0.200) (1.061) (0.685) (−1.975)
N 14,708 13,739 14,467 4913 14,207 13,254 13,374 5110
Adj. R2 0.179 0.166 0.095 0.052 0.181 0.128 0.100 0.021
All regressions
Controlsic,pre (Size, Age, CashA, RD_A, Private, SaleA, ROA, IntrC, EqitA) √ √ √ √ √ √ √ √
Sector FEs Y Y Y Y Y Y Y Y
Country FEs Y Y Y Y Y Y Y Y
# Countries 80 80 80 80 80 80 80 80
# Sectors 79 79 79 79 79 79 79 79
This table reports the results estimating ∆yic, COVID = ϑj + ϑc + ∅ . Distancingj × Policyc + τ. Xic, Pre + εic, COVID where i stands for firm, j for sector, and c for country. ∆yic, COVID is the change in performance ratios for firm i in country c between 2020 and 2019. We use, alternatively, change in asset turnover ratio [∆(SaleA)], change in profit margin [∆(ProfM)], change in interest coverage ratio [∆(IntrC)], and change in probability of default [∆(ProbD)]. Each panel displays the results obtained by running the regression in a subsample determined by the median value of various pre-crisis financial variables. Policyc is a vector of variables representing government economic support packages in country c. Distancingj is industry j's degree of sensitivity to a pandemic from Kóren and Petö (2020). Xic, Pre is a vector of firm-level explanatory variables, computed as of 2019. We include sector fixed effects (ϑj) at the three-digit NAICS level as well as country fixed effects (ϑc) in all regressions. See Appendix, Table A1 for detailed definition of variables. Regressions are estimated using OLS. The statistical inferences are based on clustered standard errors at the country level (associated t-values reported in parentheses). ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.
Larger firms benefit more from fiscal support (see the significant coefficient on the interaction for FIS in column 5, 7, and 8 of Panel A). Yet, smaller firms benefit more from foreign exchange intervention (see the significant coefficient on the interaction for FXI in columns 3 and 4). Monetary policy easing seems to exert a favorable effect on smaller firms by raising profits (column 2) and on larger firms by increasing sales (column 5).
Firms with a low pre-COVID level of cash holdings appear to have improved ability to meet debt obligations and lowered risk of insolvency due to fiscal support, given the significant coefficient on the interaction for FIS in columns 3 and 4 of Panel B in Table 7. For firms with more cash holdings, the results echo those for larger firms in Panel A: both fiscal and monetary support help, with significant coefficients on the interaction terms for FIS (column 5, 7, and 8) and MP_BP (column 5).
Panel C suggests that firms in the higher profitability group seem to benefit from fiscal and, to a lesser degree, from monetary support more than their lower-profitability counterparts do (see column 5 and 7, where the interaction terms are highly significant). Similar to the case for smaller firms in Panel A, however, foreign exchange intervention seems to help firms with lower profitability service their debt (see column 3).
Looking at Panel D, there is a clear distinction between more versus less leveraged firms. Predominantly, economic policy packages favor the latter, in particular both fiscal and monetary policy measures help improve firm performance. By contrast, less leveraged firms appear to only benefit from foreign exchange intervention through a better interest coverage ratio (column 3) and from fiscal support through a lower probability of default (column 4).
While a more thorough examination is left for future research, taken together, these results seem to point to a need for firms to have a certain level of financial health to be able to seize the lifeline provided by fiscal and, perhaps to a somewhat lesser extent, monetary policy measures. FXI, by contrast, appears to help smaller, less healthy firms stay afloat.19 These differences could speak to the feasibility of targeting fiscal support, albeit with some leakage, to firms that have a better chance of surviving the crisis.20 It might also be an inevitable outcome due to, for instance, structural changes brought by the pandemic, favoring digitization and economies of scale.
4.4 Other robustness tests
We conduct several further robustness tests in order to ascertain the baseline results in Table 3. The details of the tests, results, and related discussions are in the OSA, where alternative data sources for policy response to COVID-19 are examined in Table S7A, an alternative proxy for pandemic sensitivity is explored in Table S7B, the baseline model is re-estimated with the weighted least square method and by excluding critical sectors in Table S7C, and the specification is expanded with additional firm-specific variables in Table S7D. The main findings remain broadly the same.
5 Conclusion
In this paper, we use firm-level data to provide some early evidence on the effectiveness of COVID-19 economic policy packages. Our empirical strategy relies on the varying degree of vulnerability to the pandemic across industries. If policy actions have worked as intended, they would give a lift to pandemic-prone sectors.
After confirming that firms in sectors with higher distancing indices performed worse than the others in the same country, we find a robust positive association of fiscal support with growth in the sales-to-assets ratio, profit margin, interest coverage ratio and probability of default in pandemic-prone sectors: firms that are more sensitive to distancing have performed better when the fiscal support is larger. There is also some evidence that monetary easing has been associated with improved sales and foreign exchange intervention with increased interest coverage ratio for the hardest-hit firms. The evidence also indicates that fiscal support packages are more effective than other policies during the COVID-19 pandemic.
Thus, this early evidence seems to suggest that policy interventions have bought time for the hardest-hit industries, by supporting sales and improving liquidity, and especially for firms that entered the crisis with healthier financial positions. This is cautiously encouraging news for policymakers: giving a helping hand in response to exogenous shocks may suffer less from concerns about misallocation of resources and moral hazard. As for corporate managers, there is perhaps some lessons to be learned in terms of building resilience and financial soundness in good times, since these qualities may be crucial not only to be able to survive a crisis itself but also to be able to benefit from policy support, assuming any would be provided.
Uncited references
Bilir et al., 2019
Claessens et al., 2021
Ramelli and Wagner, 2020
Appendix A Appendix
Table A1 Variable definitions and sources.
Table A1Variable Definition Source
Change in firm performance (∆yic,COVID)
∆(SaleA) The change in a bank sale to asset ratio (SaleA) between 2019 and 2020, calculated as ∆(SaleA) = (SaleA20-SaleA19). SaleA is an asset turnover ratio, which measures the efficiency of a company's assets to generate revenue or sales. Bureau van Dijk, ORBIS, and own calculation.
∆(ProfM) The change in a bank profit margin (ProfM) between 2019 and 2020, calculated as ∆(ProfM) = (ProfM20-ProfM19). Profit margin is a measure of profitability where it is calculated as the net profit as a share of the revenue. “
∆(IntrC) The change in a bank interest coverage ratio (IntrC) between 2019 and 2020, calculated as ∆(IntrC) = (IntrC20-IntrC19). Interest coverage ratio is a company's ability to meet its debt obligations. The interest coverage ratio is calculated by dividing a company's earnings before interest and taxes by its interest expense. “
∆(ProbD) The change in indicator of probability of default (ProbD) between Dec. 2019 and Dec. 2020. ProbD reflects the default risk of publicly listed firms by quantitatively analyzing numerous covariates that cover market-based and accounting-based firm-specific attributes, as well as macro-financial factors. We use a prediction for horizon of 1 month. Higher figures denote higher risk. Credit Research Initiative – CRI, National University of Singapore.
Pandemic-pronej
Distancing Kóren and Petö' (2020) sectoral pandemic-prone proxy, using data from O*NETZ. It represents share of worker whose job requires a high level of teamwork and customer contact. Kóren and Petö document that US industries are different when it comes to reliance on teamwork and customer contact in their operations. This proxy suggests that firms in economic sectors with a high degree of such pandemic-prone proxy are particularly vulnerable to social distancing. Kóren and Petö (2020)
Policyc
FIS Fiscal policy: Cumulative fiscal support package (% of GDP) from January to December 2020 (week 1 to week 43). IMF, and own calculation.
MP_BP Monetary policy: cumulative change in basis points from January to December 2020 times (−1) divided by 100. “
FXI Foreign exchange intervention (0 = No, 1 = Yes): cumulative from January to December 2020. “
Controlsic,pre
Size Natural logarithm of a firm total assets in 2019. Bureau van Dijk, ORBIS, and own calculation.
Age Firm age measured by logarithm of subtracting the firm's year of incorporation from year 2020. “
CashA Firm cash assets to total assets ratio in 2019. “
RD_A Research and development expenditure divided by total assets in 2019. “
Private (dummy) A dummy variable that takes value 1 if the firm is a private firm, and 0 otherwise. “
SaleA Firm sales to total assets ratio in 2019. “
ROA Return on assets, which is defined as profit before tax as a percentage of average assets of a bank, in 2019. “
IntrC Interest coverage ratio is earnings before interest and taxes (EBIT) to interest expenses ratio in 2019. It determines how easily a company can pay interest on its outstanding debt. “
EqitA The ratio of shareholder fund (equity) to total assets of a firm in 2019. “
Other variables
Covid_Severity The country-level severity of the lockdown measures in response to the pandemic. This is a composite measure of the scale of school closures, workplace closures and travel bans based on the data on the 31st December 2020. The indicator is normalised to be from 0 to 100 with the score100 being the strictest. Hale et al. (2020).
HealE Current private expenditures on health per capita expressed in international dollars at purchasing power parity in year 2019. World Bank - WDI.
FDI Foreign direct investment, which refers to direct investment equity flows in the reporting economy, as % of GDP in year 2019. “
Trade Total exports and imports as % of GDP in year 2019. “
NPL The ratio of a country bank nonperforming loans to total gross loans in year 2019. “
Inflation Inflation, measured by consumer price index, which is defined as the yearly change in the prices of a basket of goods and services in year 2019. “
FinDep External financial dependence of U.S. firms by 3-digit SIC codes. This is an industry-level median of the ratio of capital expenditures minus cash flow over capital expenditures. Cash flow is defined as the sum of funds from operations, decreases in inventories, decreases in receivables, and increases in payables. Capital expenditures include net acquisitions of fixed assets. Source: Rajan and Zingales (1998). Tong and Wei (2008).
DemSen Demand sensitivity is a sector-level index on the sensitivity to demand shocks, based on stocks' response to the 9/11/2001 shock. “
OverA The ratio of a company's overheads cost (other operating expenses) to its total assets in year 2019. Bureau van Dijk, ORBIS, and own calculation.
CashFlowA The ratio of a company's cash flow to its total assets in year 2019. “
Tobin's Q Total market value of common equity divided by total book value of assets in year 2019. “
Table A2 Magnitude of estimates
Table A2 Fiscal policy (FIS) Monetary policy (MP_BP) Foreign exchange policy (FXI)
Percentile Distancing ∆(SaleA) ∆(ProfM) ∆(IntrC) ∆(ProbD) ∆(SaleA) ∆(IntrC)
(1) (2) (3) (4) (5) (6)
10th 0.07 0.22 0.07 2.16 −0.07 0.24 2.22
25th 0.09 0.28 0.09 2.78 −0.09 0.30 2.85
50th 0.11 0.34 0.11 3.40 −0.11 0.37 3.48
75th 0.16 0.49 0.16 4.94 −0.16 0.54 5.06
90th 0.28 0.86 0.29 8.64 −0.29 0.95 8.86
Marginal effects (in %) of economic supporting packages on firm performance at different levels of distancing. Calculations are based on estimated coefficients from Table 3 and at the 10th, 25th, 50th, 75th, and 90th of distancing.
Appendix B Supplementary data
Supplementary material
Image 1
Data availability
Data will be made available on request.
3 This approach is an augmentation of the literature that examines the relationship between government intervention and firm performance during a financial crisis (see, for example, Norden et al., 2013 and Laeven and Valencia, 2013).
4 Arguably, our use of firm-level data, with distancing measured at the sectoral level, also introduces some degree of separation. While it is plausible that policies are more likely to be enacted where pandemic-prone sectors make up a larger portion of the economy, it is unlikely that government policy responds only to the performance of a particular firm in a pandemic-prone sector. Indeed, the correlation between policies and average distancing of firms in a given country is at most 7% (between distancing proxy and fiscal policy variable; for other policies, the correlation is less than 3%).
5 Kóren and Petö (2020) use U.S. firm data to establish the benchmark of an industry's pandemic sensitivity. One may argue that this proxy could be endogenous to the performance of U.S. firms. Therefore, following other studies that apply the Rajan and Zingales (1998) approach such as Igan and Mirzaei (2020), we drop U.S. firms from all regressions. Yet, for completeness, we check the robustness of the findings to also including U.S. firms. See Section 4.2.
6 We acknowledge that the sample of firms we study is biased toward larger firms as almost all firms (about 95%) reporting 2020 data are listed firms. Thus, we are conservative when interpreting our results, as we cannot analyze the overall effect of policy measures on the performance of small and medium-sized enterprises during COVID-19.
7 Some industries will have high scores in all three dimensions while others may have high scores only in one. For instance, most manufacturing requires physical presence but not necessarily face-to-face customer contact.
8 Available at https://www.imf.org/en/Topics/imf-and-covid19/Policy-Responses-to-COVID-19.
9 The survey gathers, in addition to foreign exchange market intervention, information on capital flow management and broader financial policy actions such as loan forbearance and debt moratoria. We do not include these in our analysis given that there is not enough variation across countries to tease out any differential effects.
10 Note that, in the specifications in columns 5–8, we include sector fixed effects. Hence, the coefficient on distancing itself is absorbed.
11 As a separate exercise, we run a regression of policy measures without interacting them with Distancing and then with the interactions so that we can see the direct impact of policy measures on firm performance. The results are in Table S2 together with the relevant discussion in the Online Supplementary Appendix (OSA).
12 We also run a regression with two indicators of real activity as dependent variables: change in ‘the number of employees’ and change in ‘value added’. The results are consistent with those using financial performance indicators as dependent variables and are shown in Table S3 in the OSA.
13 Due to differences in number of observations across our four dependent variables, it is worth confirming the validity of the findings in the restricted sample (that is, only the firms with non-missing observations for all variables). Table S4 columns 1–4 in the OSA indicate that our main findings remain broadly unchanged, except for the case where profit margin is the dependent variable.
14 These are calculated as ∅[(Distancing90th − Distancing10th)(Policy90th − Policy10th)]. See Eq. (1) for further elaboration on the variables and the coefficients.
16 See, for instance, Tong and Wei (2008), who examine how the subprime crisis spilled over to the real economy and find that these two channels indeed explain the differential negative impact on stock prices during the global financial crisis.
17 Recall that we exclude the United States due to potential reverse causality. The results obtained when we include the US data are in Table S4, columns 5–8 in the OSA and are almost identical to those in Table 3.
18 Although the nature of the shock is very different, these findings are in line with those reported in studies looking at the 2008 financial crisis (e.g., Duchin et al., 2010 find that the decline in investment is greatest for firms that have low cash reserves and are financially more constrained).
19 One of the possible reasons that FXI helps smaller firms in pandemic-prone sectors more than it does larger ones could be that smaller firms do not have in place mechanisms and resources that could protect them from exchange rate fluctuations, e.g. hedging instruments or diversification of operations, that larger firms might have.
20 The finding that larger firms benefit more could also be due to their stronger influence on the government. Igan et al. (2021), for instance, show in the context of the Payroll Protection Program enacted in the United States in response to COVID-19 that larger firms were more likely to lobby the government and at the same time obtained larger loans under the program. To the extent that lobbying conveys information about the specific needs of the firms allowing fiscal support to be more tailored, the effects of fiscal support could be more significant.
Appendix B Supplementary data to this article can be found online at https://doi.org/10.1016/j.jcorpfin.2022.102340.
15 One of the important country-level variables that may affect firm performance is the sovereign debt-to-GDP ratio. The ability of a country in diminishing the adverse impact of a crisis on corporate activity and risk may be related to its level of debt (Martin and Nagler, 2020). However, Benmelech and Tzur-Ilan (2020) show that debt-to-GDP is positively related to fiscal spending during COVID-19. Indeed, we face high correlation (more than 0.8) between the sovereign debt ratio and the size of the fiscal response to the crisis. The correlation further increases to 0.9 when interacted with distancing. There are other likely control variables one could consider, such as the share of population aged 65+ and the number of hospital beds. However, due to the problem of multicollinearity as indicated by a large variance inflation factor (VIF), we have to be selective and exclude all these potential control variables from the baseline model.
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J Sport Health Sci
J Sport Health Sci
Journal of Sport and Health Science
2095-2546
2213-2961
Published by Elsevier B.V. on behalf of Shanghai University of Sport.
S2095-2546(22)00123-5
10.1016/j.jshs.2022.12.009
Commentary
Physical activity, COVID-19, and Respiratory comorbidities: The good, the bad, and the ugly
Dinh-Xuan Anh-Tuan a⁎
Hua-Huy Thông a
Günther Sven a
a Lung Function & Respiratory Physiology Units, Department of Respiratory Physiology and Sleep Medicine, Assistance Publique – Hôpitaux de Paris, Cochin & George Pompidou Hospitals, University Paris Cité, France
⁎ Corresponding author:
14 12 2022
14 12 2022
4 8 2022
25 10 2022
1 12 2022
© 2022 Published by Elsevier B.V. on behalf of Shanghai University of Sport.
2022
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pmcAlmost 3 years after the outbreak of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for the coronavirus disease 2019 (COVID-19) that has caused more than 6 million deaths worldwide, (1) the pandemic continues to persist and hamper our daily lives. There are at least 2 main reasons explaining why we still struggle to terminate this pandemic. First, novel variants of concern of SARS-CoV-2 unceasingly emerge despite almost 12 billion doses of vaccine being administered to date. (1,2) Second, our lack of understanding of the underlying biological mechanisms leading to post-acute sequelae of COVID-19 (PASC) or long COVID, contributes to the lingering effects of the pandemic. (3) Due to the airborne nature of SARS-CoV-2, the respiratory system is the most frequently impacted as the viral spike protein readily binds to the ubiquitous Angiotensin-converting enzyme 2 (ACE-2) lung cell membrane receptors. As with all acute lung injuries, the question relating to long-term lung function arose for all COVID-19 patients irrespective of the initial severity of the disease. We recently published a systematic review identifying 1578 publications reporting pulmonary function tests (PFTs) after the acute phase of the disease. (4) Following initial screening, the main results from 39 studies that measured and discussed the possible underlying lung abnormalities at various time points, were included in a systematic analysis .4 Based on the results of these studies, we identified 3 common features were when measuring PFTs at rest in COVID-19 survivors: (i) the existence of obstructive pattern, (ii) restrictive pattern, and (iii) lung gas exchange impairment. (5, 6, 7) Integrative responses to physical exercise, e.g., measuring 6-min walking distance or performing cardiopulmonary exercise test (CPET), have also been performed, but unfortunately, only in a limited number of investigations which consistently showed direct relationship between abnormal spirometry results and impaired cardiopulmonary exercise testing. (8,9) The main parameter used to define bronchial obstructive pattern was the ratio of forced expiratory volume in 1 s (FEV1) over forced vital capacity (FVC). (4) Restrictive patterns were diagnosed by either a reduction of total lung capacity (TLC) or the combination of a low FVC with a high FEV1/FVC ratio, in cases when TLC could not be measured. In some studies, reduced residual volume (RV) was also considered as part of the restrictive pattern. (4) Lung gas exchange was mostly assessed using the single breath carbon monoxide lung diffusing capacity (DLCO) test. (5, 6, 7) The earliest time point of evaluation after the acute phase of the disease was 1 month, with most studies reporting PFTs between 6 weeks to 4 months, and few reporting results at 6 months after discharge or onset of the disease. (4, 5, 6, 7, 8, 9) A common feature emerging from all studies was the relatively high prevalence of reduced DLCO reported in 40% to 65 % of patients as compared with the medium to high prevalence of restrictive pattern and the exceptionally low prevalence of obstructive pattern. (4, 5, 6, 7, 8, 9) The high prevalence of altered DLCO found at the onset of the disease, or 1 month after discharge, results from ongoing residual inflammation related to the initial lung injury. However, the persistent low values of DLCO at 3 and 6 months, even in patients with normalized chest computed tomography (CT) results, raise concern (10) as various pathophysiological mechanisms might account for the abnormal lung gas exchange in patients following exposure to COVID-19. (11) Unlike most pulmonary function parameters, e.g., FEV1, FVC and TLC, which are directly measured during respiratory maneuvers, DLCO is calculated as a product of the accessible alveolar volume (VA) and the transfer coefficient Carbon monoxide transfer coefficient (KCO). As a result, altered DLCOs in patients following COVID-19 (4, 5, 6, 7, 8, 9) can occur through a reduction of VA, or KCO, or both. (12) Deciphering between VA and KCO as the cause for the reduced DLCO is crucial for the determination of the underlying COVID-19-related structural and/or functional changes of the lung. (11) Several mechanisms can account for an impaired pulmonary gas exchange resulting in hypoxemia in patients with COVID-19, including pneumonia and acute respiratory distress syndrome (ARDS) during the acute phase, and pulmonary fibrosis as a long-term consequence of either pneumonia or COVID-19-related ARDS (CARDS). (13) Patients with “classical” ARDS not related to COVID-19, consistently have severe clinical symptoms when lung mechanics are markedly impaired. In other words, ARDS patients with the lowest oxygenation level are also those who have the worst lung mechanics and the highest pulmonary shunt. By contrast, lung mechanics are relatively preserved in patients with CARDS even in cases of profound hypoxemia. (14) This difference in lung mechanics between ARDS and CARDS patients suggests different mechanisms for pulmonary shunt in patients with COVID-1911, 13 with chaotic architecture of the lung capillary vascular bed characterizing the so-called “intussusceptive angiogenesis”, and the presence of multiple pulmonary micro-thrombotic lesions. (15) Such an association suggests a co-occurrence of abnormal lung extracellular matrix remodeling and pulmonary vascular dysfunction in severely ill COVID-19 patients, which is likely related to immunological failure to control and negate the viral infection by SARS-CoV-2. (16) Excessive inflammation in response to contiguous infection of alveolar epithelial and capillary endothelial cells, coagulation defects, and uncontrolled neutrophilic activation potentially contribute to structural and functional changes of the alveolar-capillary units leading to impaired gas exchange and hypoxemia. Among patients infected by SARS-CoV-2, complications are greater in elderly individuals, especially those with underlying chronic comorbidities including diabetes and obesity. (17)
One remarkable and common feature of the various types of impaired lung function above medical conditions is that they are frequently associated with, and aggravated by, physical inactivity. (18) There is a global trend towards an older, obese, and physically inactive demographics that will likely continue for the near future. As for other physiological functions, innate and adaptive immunity declines with age, a process termed immunosenescence. (19) The association of immunosenescence with inflammaging, an age-related low-grade inflammation seen in elderly people may aggravate, but also be aggravated by SARS-CoV-2 infection. (20) The mechanisms underlying obesity are complex and diverse but physical inactivity certainly contributes to its worsening over time, creating a vicious circle. Importantly, obesity and physical inactivity increase the risk for hypertension, type 2 diabetes, and cardiovascular disease, three of the most important risk factors for the development of severe COVID-19. Finally, obesity and associated-metabolic syndrome, in conjunction with a lack of physical activity cause systemic inflammation and adversely affect immune function and host defense in a way that mimics immunosenescence. (21) The existing data suggest that physical activity is associated with decreased COVID-19 cases and deaths. (22) Furthermore, we suggest that moderate physical activity with low intensity exercise, that can be initiated at the level of 1-3 metabolic equivalent of tasks or equivalent, should be part of COVID-19 patients’ rehabilitation programs. (23) This will allow monitoring of respiratory functional improvement over time and to understand better the mechanisms underlying PASC. (4) We hope that the scientific community will eventually find the way to halt the COVID-19 pandemic. However, we are uncertain on how to prevent PASC becoming another chronic disease that will be added to an already long list of debilitating conditions, e.g., hypertension, type 2 diabetes, obesity, and cardiopulmonary disease. Carefully designed muscular cardiopulmonary rehabilitation programs through physical activity must be part of the solution to prevent and combat these chronic conditions.
Authors’ contributions
ATDX has conceptualized and written the manuscript; THH and SG have conceptualized the manuscript. All authors have read and approved the final version of this manuscript, and agree with the order of presentation of the authors.
Competing interests
The authors declare that they have no competing interests.
==== Refs
References
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2 Callaway E. Heavily mutated Omicron variant puts scientists on alert Nature 600 2021 21 10.1038/d41586-021-03552-w 34824381
3 Marshall M. The four most urgent questions about long COVID Nature 594 2021 168 170 34108700
4 Antoniou KM Vasarmidi E Russell AM European Respiratory Society statement on long COVID-19 follow-up Eur Respir J 60 2022 2102174 10.1183/13993003.02174-2021
5 Patel K Straudi S Yee Sien N Fayed N Melvin JL Sivan M Applying the WHO ICF framework to the outcome measures used in the evaluation of long-term clinical outcomes in coronavirus outbreaks Int J Environ Res Public Health 17 2020 6476 10.3390/ijerph17186476 32899534
6 Torres-Castro R Vasconcello-Castillo L Alsina-Restoy X Respiratory function in patients post-infection by COVID-19: A systematic review and meta-analysis Pulmonology 27 2021 328 337 33262076
7 So M Kabata H Fukunaga K Takagi H Kuno T. Radiological and functional lung sequelae of COVID-19: A systematic review and meta-analysis BMC Pulm Med 21 2021 97 10.1186/s12890-021-01463-0 33752639
8 Raman B Cassar MP Tunnicliffe EM Medium-term effects of SARS-CoV-2 infection on multiple vital organs, exercise capacity, cognition, quality of life and mental health, post-hospital discharge EClinicalMedicine 31 2021 100683 10.1016/j.eclinm.2020.100683
9 Debeaumont D Boujibar F Ferrand-Devouge E Cardiopulmonary exercise testing to assess persistent symptoms at 6 months in people with COVID-19 who survived hospitalization: A pilot study Phys Ther 101 2021 pzab099 10.1093/ptj/pzab099 33735374
10 Chapman DG Badal T King GG Thamrin C. Caution in interpretation of abnormal carbon monoxide diffusion capacity in COVID-19 patients Eur Respir J 57 2021 2003263 10.1183/13993003.03263-2020
11 Laveneziana P Straus C Meiners S. How and to what extent immunological responses to SARS-CoV-2 shape pulmonary function in COVID-19 patients Front Physiol 12 2021 628288 10.3389/fphys.2021.628288
12 Hughes JMB Pride NB. Examination of the carbon monoxide diffusing capacity (DLCO) in relation to its KCO and VA components Am J Respir Crit Care Med 186 2012 132 139 22538804
13 Kolb M Dinh-Xuan AT Brochard L. Guideline-directed management of COVID-19: Do's and Don'ts Eur Respir J 57 2021 2100753 10.1183/13993003.00753-2021
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 32228035
15 Ackermann M Mentzer SJ Kolb M Jonigk D. Inflammation and intussusceptive angiogenesis in COVID-19: Everything in and out of flow Eur Respir J 56 2020 2003147 10.1183/13993003.03147-2020
16 Ackermann M Verleden SE Kuehnel M Pulmonary vascular endothelialitis, thrombosis, and angiogenesis in Covid-19 N Engl J Med 383 2020 120 128 32437596
17 Pijls BG Jolani S Atherley A Demographic risk factors for COVID-19 infection, severity, ICU admission and death: A meta-analysis of 59 studies BMJ Open 11 2021 e044640 10.1136/bmjopen-2020-044640
18 Nieman DC. Coronavirus disease-2019: A tocsin to our aging, unfit, corpulent, and immunodeficient society J Sport Health Sci 9 2020 293 301 32389882
19 Xu W Wong G Hwang YY Larbi A. The untwining of immunosenescence and aging Semin Immunopathol 42 2020 559 572 33165716
20 Chen Y Klein SL Garibaldi BT Aging in COVID-19: Vulnerability, immunity and intervention Ageing Res Rev 65 2021 101205 10.1016/j.arr.2020.101205
21 Máčová L Bičíková M Hampl R. Endocrine risk factors for COVID-19 in context of aging Physiol Res 70 2 2021 S153 S159 Suppl. 34913349
22 Cunningham GB. Physical activity and its relationship with COVID-19 cases and deaths: Analysis of U.S. counties J Sport Health Sci 10 2021 570 576 33775882
23 Barker-Davies RM O'Sullivan O Senaratne KPP The Stanford Hall consensus statement for post-COVID-19 rehabilitation Br J Sports Med 54 2020 949 959 32475821
| 0 | PMC9747691 | NO-CC CODE | 2022-12-15 23:22:03 | no | J Sport Health Sci. 2022 Dec 14; doi: 10.1016/j.jshs.2022.12.009 | utf-8 | J Sport Health Sci | 2,022 | 10.1016/j.jshs.2022.12.009 | oa_other |
==== Front
Vaccine
Vaccine
Vaccine
0264-410X
1873-2518
Elsevier Ltd.
S0264-410X(22)01532-8
10.1016/j.vaccine.2022.12.018
Article
Association Between Caregiver Opposition to Topical Fluoride and COVID-19 Vaccines
Saini Sapna J. a⁎
Carle Adam C. bcd
Forsyth Anna R. a
Chi Donald L. aef
a Department of Pediatric Dentistry, University of Washington School of Dentistry, 6222 NE 74th St #8158, Seattle, WA 98115, USA
b James M. Anderson Center for Health Systems Excellence, Cincinnati Children’s Hospital Medical Center, 3333 Burnet Ave., MLC 7014, Cincinnati, OH 45229-3039, USA
c Department of Pediatrics, University of Cincinnati College of Medicine, 3230 Eden Ave, Cincinnati, OH 45267, USA
d Department of Psychology, University of Cincinnati College of Arts and Sciences, 155 B Arts & Sciences Hall, Cincinnati, OH 45221, USA
e Department of Oral Health Sciences, University of Washington, 1959 NE Pacific Street, Box 357475, Seattle, WA 98195, USA
f Department of Health Systems and Population Health, University of Washington, 1959 NE Pacific St., Box 357660, Seattle, WA, 98195, USA
⁎ Corresponding author at: 34621 8th AVE SW, Federal Way, WA 98023.
14 12 2022
14 12 2022
3 9 2022
7 12 2022
8 12 2022
© 2022 Elsevier Ltd. 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.
Purpose
Caregivers who oppose topical fluoride may be opposed to other preventive treatments, including COVID-19 vaccines. The study objective was to examine the association between caregiver opposition to topical fluoride and COVID-19 vaccines.
Methods
The study took place at the University of Washington in Seattle, WA. English-speaking caregivers of children aged <18 years were eligible to participate. An 85-item REDCap survey was administered from February to September 2021. The predictor variable was topical fluoride opposition (no/yes). The outcome was COVID-19 vaccine opposition (no/yes). The models included the following covariates: child and caregiver age; caregiver race and ethnicity, education level, insurance type, parenting style, political ideology, and religiosity; and household income. Logistic regression models generated odds ratios (OR) and 95% confidence intervals (α=0.05).
Results
Six-hundred-fifty-one caregivers participated, and 403 caregivers with complete data were included in the final regression model. Mean child age was 8.5 years (SD 4.2), mean caregiver age was 42.1 years (SD 9.1), 53.0% of caregivers were female, 57.3% self-reported as white, and 65.5% were insured by Medicaid. There was a significant positive association between topical fluoride and COVID-19 vaccine opposition (OR=3.13; 95% CI: 1.87, 5.25; p<0.001). Other factors associated with COVID-19 vaccine opposition included conservative political views (OR=2.77; 95% CI: 1.26, 6.08; p<0.011) and lower education (OR=3.47; 95% CI: 1.44, 8.38; p<0.006).
Conclusions
Caregivers opposed to topical fluoride in dental settings were significantly more likely to oppose COVID-19 vaccines for their child. Future research should identify ways to address both topical fluoride and vaccine opposition to prevent diseases in children.
==== Body
pmc1 Introduction
Vaccines help prevent and reduce transmission and severity of infectious diseases like severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but many parents and caregivers are vaccine hesitant or opposed to childhood vaccines. Although vaccine hesitancy and opposition are long-standing public health challenges, the development of vaccines for children targeting the novel coronavirus disease 2019 (COVID-19) have put the issue at the center of preventive care decision making in recent years. The COVID-19 vaccine was authorized for emergency use by the United States (U.S.) Food and Drug Administration (FDA) initially in May 2021 for adolescents ages 12 to 15 years and then in November 2021 for children ages 5 through 11 years [1], [2]. The vaccine most recently became available in June 2022 for children 6 months through 5 years old [3]. As of July 2022, data from the U.S. Centers for Disease Control and Prevention indicate that 30.5% of eligible children ages 5 to 11 years old and 60.4% of children ages 12 to 17 years old in the U.S. are fully vaccinated against COVID-19 [4]. Even smaller proportions of children under age 5, who are now eligible for the COVID-19 vaccine, are likely to be vaccinated [5]. Consequently, pediatric COVID-19 prevalence in the U.S. remains high. Of the total cumulative COVID-19 cases in the U.S., 18.6% are attributed to children [5], [6]. As individuals under the age of 18 comprise approximately 22.1% of the total population in the U.S., this is an essential group to vaccinate [6], [7]. These relatively low rates of vaccination highlight the importance of understanding why caregivers are hesitant and/or opposed to childhood vaccines.
The reasons for vaccine hesitancy and opposition are multifactorial. Consistent with past research on non-COVID-19 childhood immunizations, recent studies suggest that COVID-19 vaccine hesitancy and opposition may stem from similar beliefs, such as distrust in vaccine safety and efficacy, fear of adverse reactions or unknown long-term effects, low perceived severity of COVID-19 in children, and growing distrust of medical and healthcare providers [5], [8]. Surveys of U.S. caregivers also indicate that COVID-19 vaccination intention and acceptability for children is lower among caregivers with less formal education, a conservative political ideology, and at least at the outset of the pandemic among non-white racial and ethnic groups [9], [10]. Racial disparities persist, particularly among Black populations, leaving minoritized caregivers more hesitant about the COVID-19 vaccine compared to caregivers from other racial subgroups [5], [11].
Analogous to the way in which vaccines prevent systemic diseases, fluoride helps prevent dental caries (tooth decay or cavities). Recent evidence affirms the effectiveness of topical fluoride in reducing the incidence of dental caries in high-risk children [12]. Yet one study found that 13% of caregivers opposed topical fluoride treatment for their children during dental care visits and even larger proportions are likely to be hesitant about topical fluoride [13]. Drawing on the vaccination hesitancy literature, topical fluoride hesitancy is defined as a delay in acceptance, thoughts of refusal, or refusal of topical fluoride despite availability [14]. Although the caries risk of children whose caregivers refuse topical fluoride has not yet been formally studied, anecdotal evidence suggests that a substantial proportion of these children are not at low risk for caries and may have high levels of untreated, preventable tooth decay [15].
Previous work reported a significant association between opposition of topical fluoride and childhood vaccines, but there has been no recent research, especially during the COVID-19 pandemic [16]. The goals of the current study were to (1) evaluate whether caregiver opposition to topical fluoride was specifically associated with opposition to COVID-19 vaccines and (2) identify other factors associated with COVID-19 vaccine opposition. Knowledge gleaned from this study is expected to support development of public health and chairside strategies addressing caregiver opposition to preventive care for their children.
2 Materials and methods
2.1 Study Design, Population and Procedures
A single-site, observational cross-sectional study was conducted at the at the University of Washington Center for Pediatric Dentistry (UW CPD) in Seattle, Washington. All English-speaking parents and caregivers of children aged <18 years who were current UW CPD patients of record were eligible to participate. An 85-item electronic survey created through Research Electronic Data Capture (REDCap) was administered. Caregivers were approached by study staff during routine patient care visits, defined as a dental checkup or treatment visit, and were asked to participate in the voluntary study. Participant recruitment took place between February 1, 2021 and September 30, 2021. A priori, a Monte Carlo simulation study was conducted and a proposed sample size of 500 caregivers was estimated to provide sufficient power for our measurement model. Participants could take the survey on their own electronic device, or a study-provided tablet. One caregiver per household was permitted to participate. For participants with multiple children, the index child was specified as the participant’s youngest child. Informed consent for the study was requested through the electronic survey and obtained from participating caregivers prior to enrollment. All survey questions were optional, and participants could discontinue the survey at any time. If the survey could not be completed during their child’s visit, participants were given the option to securely access and complete the survey later. All participants who submitted an electronic survey were entered into a raffle for the chance to win a prize, including an Apple iPad, a pair of Philips Sonicare toothbrushes, a $150 Amazon gift card, one of two $75 Amazon gift cards, or a $50 Target gift card, as a thank you for participation. The study was approved by the University of Washington Institutional Review Board.
2.2 Survey Development
Survey development was informed by formative qualitative research conducted with caregivers that focused on understanding the causes of topical fluoride opposition [15]. The survey included questions on oral health knowledge, beliefs and reasons for opposition to topical fluoride, and beliefs about and opposition to COVID-19 vaccines. The goal of these items was to understand reasons why caregivers were opposed to topical fluoride and COVID-19 vaccines but were not the focus of the current analyses. The survey was initially evaluated with caregivers using cognitive interviewing methods, pre-tested with caregivers and dentists, revised, and finalized. A final copy of the 85-item survey is available (see Supplemental Materials – Appendix A).
2.3 Predictor Variable
The predictor variable was whether the caregiver expressed any opposition to topical fluoride. Topical fluoride was defined, and examples provided. Caregivers were asked, “On a scale of 0 to 10 with ‘0’ being ‘not at all opposed’ and ‘10’ being ‘totally opposed,’ how opposed are you to topical fluoride for your children?” Responses were recoded into a binary variable with those indicating no opposition (0) versus those indicating any opposition (≥1). This is consistent with published conceptualizations of topical fluoride opposition [13].
2.4 Outcome Variable
The outcome variable was whether the caregiver expressed any opposition to COVID-19 vaccines. Caregivers were asked “On a scale of 0 to 10 with ‘0’ being ‘not at all opposed’ and ‘10’ being ‘totally opposed,’ how opposed are you to a COVID-19 vaccine for your child/children?” Consistent with our predictor variable, responses were recoded into a binary variable with those indicating no opposition (0) versus those indicating any opposition (≥1).
2.5 Covariates
The following caregiver-reported variables were model covariates: referent child age; caregiver age, gender, race, ethnicity, education level, referent child dental insurance type; parenting style, political ideology, religiosity; and household income.
Both child age and caregiver age were reported in years. Caregiver gender was included as male (reference group), female, non-binary, or other [17]. Caregiver race was included as white (reference group) or non-white based on caregivers’ self-reported race in one or more categories adopted from the U.S. Census Bureau classification (white, Black, Asian, American Indian or Alaskan Native, Native Hawaiian or other Pacific Islander, other) [18]. We included caregiver ethnicity as either non-Hispanic (reference group) or Hispanic. Caregiver education categories were: high school diploma or less, some college, four-year college degree, or more than a four-year degree [19]. The four-year college degree group served as the reference group. Child dental insurance type was included as: private insurance (reference group), insured by Medicaid, or no insurance [20]. We included caregiver parenting style using caregivers’ responses to an item from the Parenting Sense of Competence Scale [21]. This item asked whether caregivers Strongly Agreed or Agreed (reference group) or Strongly Disagreed or Disagreed with the statement, “Children are likely to grow up happy and healthy without much intervention from their parents.” Caregiver political ideology was included as: conservative or very conservative, moderate, or liberal or very liberal; with liberal or very liberal serving as the reference group [22]. We included caregiver religiosity (“how important is religion in your life”) as very important, somewhat important, not too important, or not at all important; with not too important or not at all important serving as the reference group [23]. Finally, we included annual household income using four categories from the Behavioral Risk Factor Surveillance System Questionnaire: <$25,000, $25,000 to <$50,000, $50,000 to <$75,000, and ≥ $75,000. Greater than or equal to $75,000 served as the reference group [24].
2.6 Statistical Analyses
Descriptive statistics and frequencies were generated to describe the study population and were reported as means and percentages. Multiple variable logistic regression models were used to evaluate the unadjusted and covariate-adjusted relationship between caregiver opposition to topical fluoride for their children and that caregiver’s opposition to the COVID-19 vaccine for their children. The regression models produced odds ratios (OR) and 95% confidence intervals (CI). We adopted an a priori model building approach in which all covariates were conceptualized as being associated with COVID-19 vaccine opposition, and therefore all covariates were included in the final regression model. We treated probability values less than 0.05 as statistically significant. All analyses were conducted using Stata version 15.0 statistical software.
3 Results
3.1 Participant Demographics
A total of 651 caregivers responded to the survey. We excluded 248 caregivers because of missing data on any of the study variables, resulting in a final analytical sample of 403 caregivers (Table 1 ). Of the survey respondents, the mean age of the referent child was 8.48 years (SD 4.2), the mean age of caregivers was 42.1 years (SD 9.1), 53.0% of caregivers were female, 57.3% were white, 52.2% completed a four-year degree or more, and 65.5% of the referent children were insured by Medicaid. About 12.7% of caregivers reporting being politically very conservative or conservative and 45.9% were liberal or very liberal.Table 1 Description of Sociodemographic Characteristics of Caregivers Who Participated in a Survey Study on Topical Fluoride Opposition at the University of Washington (N=403)
Overall Topical Fluoride Opposition COVID-19 Vaccine Opposition
Mean (SD)% Not OpposedMean (SD)% OpposedMean (SD)% Not OpposedMean (SD)% OpposedMean (SD)%
Child Age 8.48 (4.2) 8.5(4.1) 8.4 (4.5) 9.0 (4.2) 7.8 (4.2)
Caregiver Age 42.1 (9.1) 42.2 (9.1) 41.8 (8.9) 43.3 (8.4) 40.4 (9.7)
Gender
Male 47.0 46.7 47.7 44.7 50.0
Female 53.0 53.3 52.3 55.3 50.0
Race
White 57.3 63.6 40.4 67.4 43.9
Non-White 42.6 36.4 59.6 32.6 56.1
Ethnicity
Hispanic 13.4 13.6 12.8 12.2 15.0
Non-Hispanic 86.6 86.4 87.2 87.8 85.0
Education Level
High School Equivalent or Less 14.6 14.6 14.7 9.1 22.0
Some College/Two Year Degree 33.3 31.6 37.6 31.3 35.8
Four-Year Degree 25.1 23.8 28.4 25.2 24.9
More Than Four Years 27.1 29.9 19.3 34.4 17.3
Child Dental Insurance Type
Private 29.0 31.6 22.0 33.9 22.5
Medicaid/Public 65.5 63.3 71.6 61.3 71.1
No Insurance 1.0 1.4 0 1.7 0
Other 4.5 3.7 6.4 3.0 6.4
Parenting Style
Involved 19.1 17.7 22.9 17.4 21.4
Not Involved 80.9 82.3 77.1 82.6 78.6
Political Ideology
Very Conservative/Conservative 12.7 10.9 17.4 8.3 18.5
Moderate 41.4 39.5 46.8 33.5 52.0
Very Liberal/Liberal 45.9 49.7 35.8 58.3 29.5
Religiosity
Very Important 32.8 30.3 39.5 26.1 41.6
Somewhat Important 25.8 24.5 29.4 23.5 28.9
Not Very/Not Important 41.4 45.2 31.2 50.4 29.5
Annual Household Income
<$25,000 14.1 11.9 20.2 13.5 15.0
$25,000-$50,000 24.1 20.8 33.0 18.3 31.8
$50,000-$75,000 19.9 21.1 16.5 20.0 19.7
≥$75,000 41.9 46.3 30.3 48.3 33.5
p-values <0.05 highlighted in boldface
3.2 Opposition to Topical Fluoride and COVID-19 Vaccines
One-hundred-ninety-four caregivers (32%) expressed opposition to topical fluoride and 235 (46%) expressed opposition to the COVID-19 vaccine. The survey responses for caregivers who expressed opposition to topical fluoride had a median of 0 and an interquartile range of 0 to 3. The survey responses for caregivers who expressed opposition to the COVID-19 vaccine had a median of 0 and an interquartile range of 0 to 5. Table 2 presents the bivariate relationships between COVID-19 vaccine opposition and each covariate. There was a significant association between topical fluoride opposition and COVID-19 vaccine opposition (OR=3.52; 95% CI: 2.22, 5.58; p<0.001). After adjusting for covariates, caregivers who opposed topical fluoride were 3.13 times as likely to oppose COVID-19 vaccines for their child (95% CI: 1.87, 5.25; p<0.001) compared to those that did not oppose topical fluoride (Table 3 ).Table 2 Bivariate Regression Coefficients Between Any COVID-19 Vaccine Opposition and Each Covariate in the Final Adjusted Regression Model (N=403)
Unadjusted Odds Ratio (95% CI) p-Value
Topical Fluoride Opposition
Opposed 3.52 (2.22-5.58) <0.001
Not Opposed* - -
Child Age (Years) 0.93 (0.89-0.98) 0.01
Caregiver Age (Years) 0.96 (0.94-0.99) 0.002
Gender
Male* - -
Female 0.80 (0.50-1.27) 0.34
Race
White* - -
Non-White 2.64 (1.75-3.97) <0.001
Ethnicity
Hispanic 1.28 (0.72-2.27) 0.41
Non-Hispanic* - -
Education Level
High School Equivalent or Less 4.77 (2.42-9.39) <0.001
Some College/Two Year Degree College 2.27 (1.32-3.89) 0.003
Four-Year Degree 1.95 (1.10-3.47) 0.02
More Than Four Years* - -
Child Dental Insurance Type
Private* - -
Medicaid/Public 1.74 (1.11-2.75) 0.02
Other 2.00 (0.80-5.02) 0.14
Parenting Style
Involved 1.29 (0.79-2.13) 0.31
Not Involved* - -
Political Ideology
Very Conservative/Conservative 4.43 (2.30-8.50) <0.001
Moderate 3.07 (1.97-4.78) <0.001
Very Liberal/Liberal* - -
Religiosity
Very Important 2.73 (1.70-4.39) <0.001
Somewhat Important 2.11 (1.27-3.49) 0.004
Not Very/Not Important* - -
Annual Household Income
<$25,000 1.61 (0.87-2.96) 0.13
$25,000-$50,000 2.51 (1.50-4.18) <0.001
$50,000-$75,000 1.41 (0.82-2.44) 0.21
≥$75,000 - -
p-values <0.05 highlighted in boldface.
* Reference Group
Table 3 Covariate-Adjusted Regression Model for Surveyed Caregivers Demonstrating Any COVID-19 Vaccine Opposition (N=403)
Unadjusted Odds Ratio (95% CI) p-Value
Topical Fluoride Opposition
Opposed 3.13 (1.87-5.25) <0.001
Not Opposed* - -
Child Age (Years) 0.94 (0.89-1.00) 0.06
Caregiver Age (Years) 0.98 (0.96-1.01) 0.29
Gender
Male* - -
Female 0.67 (0.38-1.19) 0.17
Race
White* - -
Non-White 1.55 (0.94-2.54 0.09
Ethnicity
Hispanic 0.82 (0.42-1.60) 0.56
Non-Hispanic* - -
Education Level
High School Equivalent or Less 3.47 (1.44-8.38) 0.01
Some College/Two Year Degree College 1.85 (0.97-3.53) 0.06
Four-Year Degree 1.80 (0.92-3.52) 0.09
More Than Four Years* - -
Child Dental Insurance Type
Private* - -
Medicaid/Public 1.15 (0.62-2.12) 0.66
Other 1.24 (0.39-3.93) 0.71
Parenting Style
Involved 1.27 (0.72-2.26) 0.41
Not Involved* - -
Political Ideology
Very Conservative/Conservative 2.77 (1.26-6.08) 0.01
Moderate 2.03 (1.20-3.44) 0.01
Very Liberal/Liberal* - -
Religiosity
Very Important 1.28 (0.69-2.36) 0.44
Somewhat Important 1.37 (0.76-2.48) 0.30
Not Very/Not Important* - -
Annual Household Income
<$25,000 0.58 (0.25-1.33) 0.20
$25,000-$50,000 1.05 (0.53-2.06) 0.89
$50,000-$75,000 0.81 (0.41-1.60) 0.55
≥$75,000 - -
p-values <0.05 highlighted in boldface
* Reference Group
3.3 Model Covariates and Opposition to COVID-19 Vaccines
In the covariate-adjusted regression model, two covariates were significantly associated with caregiver opposition to the COVID-19 vaccine: education level and self-reported political ideology. Compared to caregivers who complete more than four years of college, an education level of a high school diploma or less was significantly associated with COVID-19 vaccine opposition (OR=3.47; 95% CI: 1.44, 8.38; p<0.006). Having a moderate or conservative political ideology was also significantly correlated with COVID-19 vaccine opposition compared to parents who were liberal or very liberal (OR=2.03; 95% CI: 1.20, 3.44; p<0.008 and OR=2.77; 95% CI: 1.26, 6.08; p<0.011 respectively). Child or caregiver’s age, gender, ethnicity, dental insurance type, parenting style, religiosity, and annual household income were not significantly associated with COVID-19 vaccine opposition in the covariate-adjusted regression model.
4 Discussion
In this observational cross-sectional study, we evaluated the association between caregivers’ opposition to topical fluoride and to the COVID-19 vaccine. There were two main findings: (1) there was a significant positive association between caregiver opposition to topical fluoride in dental settings and opposition to COVID-19 vaccination for children; and (2) caregivers’ education level and conservative political ideology were other factors associated with opposition to the COVID-19 vaccine.
The first finding is that caregiver opposition to topical fluoride is significantly associated with opposition to COVID-19 vaccines. Besides prior work indicating a significant association between topical fluoride opposition and opposition to general childhood immunizations, there is no other published material to which we can compare our current findings [25]. Caregivers who are concerned about topical fluoride may generally be more hesitant or opposed to other preventive care offered during healthcare visits [25], [26]. While hesitancy may be fluid and variable, and thus amenable to a behavioral intervention, opposition to topical fluoride and COVID-19 vaccines are thought to be more rigid and may be more difficult to change [13], [27] Concerns underlying attitudes about topical fluoride and COVID-19 vaccines may be rooted in fears about safety and perceived long-term health impacts on children [5], [8], [26], [28], [29]. Opposition to preventive measures may also be an indicator of lower health literacy among caregivers, reinforcing the need for targeted public health efforts to reduce childhood diseases [29], [30], [31], [32]. Future research should identify the specific mechanisms by which opposition to topical fluoride and COVID-19 vaccines are linked.
The second finding from our study is that other factors, including education level and political ideology, were significantly associated with caregiver COVID-19 vaccine opposition. This is consistent with previous research on reasons for COVID-19 vaccine hesitancy and opposition [5], [9], [11], [32]. Regarding education level, we found that caregivers who had a high school diploma or less were more likely to oppose COVID-19 vaccines for their children than those who had completed more than four years of college. Current data show that adults in the U.S. who remain unvaccinated against COVID-19 generally have a lower level of formal education [9], [11], [31], [32]. Caregivers who are unvaccinated and demonstrate hesitancy about the COVID-19 vaccine for themselves also report that they are less likely to vaccinate their child [33]. However, vaccine hesitancy may be dynamic. A recent study reported drops in hesitancy associated with COVID-19 vaccination roll outs for children in China [34]. Regarding political ideology, the COVID-19 vaccine has been politicized in the U.S., which has influenced vaccination rates [11], [35], [36]. Specifically, individuals who self-identify as politically conservative are more opposed to COVID-19 vaccines, which is consistent with our findings [36], [37], [38]. Because of the influence politics have had on the pandemic, it is necessary to understand opposition patterns among political conservatives and how mistrust and doubt in science, healthcare and experts affect a caregiver’s decision to oppose COVID-19 vaccines for their child [39], [40].
One finding from our study that warrants additional attention is how COVID-19 vaccine opposition is associated with self-reported race. As shown in Table 2, the bivariate relationship between caregiver race and COVID-19 vaccine opposition was statistically significant whereby non-whites were significantly more likely to be opposed to the COVID-19 vaccine for their children than white caregivers. However, in our covariate-adjusted model, race failed to achieve statistical significance. Past research has reported significant differences in hesitancy and opposition to the COVID-19 vaccine by race [9], [10], [11]. Our findings suggest that the effect of race may be partly driven by other factors. More specifically, attitudes about COVID-19 vaccination may be influenced by longstanding health disparities and distrust in the healthcare system rooted in historical injustices, rather than opposition to the COVID-19 vaccine itself [39], [41]. Additional research is needed on how race can influence caregiver acceptance of preventive treatments like vaccines and topical fluoride.
Our study has important implications for health education and clinical practice. First, improving communication strategies between healthcare providers and caregivers is essential to address gaps in preventive care and improve health outcomes for children. A targeted approach to improve acceptability of treatments like topical fluoride and vaccines could involve training of health professional students on how to deploy effective communication strategies [42]. This training would equip future providers with strategies on how to engage with caregivers in open-ended conversations about important preventive care topics without judgement [13], [42], [43], [44]. These conversations could help build trust between caregivers and providers [43], [44]. A starting point to such conversations is understanding the reasons why caregivers are opposed to preventive care, like topical fluoride. This knowledge is critical in understanding barriers to acceptance of preventive treatment and can guide effective communication approaches with caregivers. Use of screening tools could help providers identify hesitant caregivers and indicate reasons for hesitancy [13].
Given the caregivers’ role in making health decisions for children, topical fluoride opposition may be a bellwether for future challenges [45]. For example, in dentistry, the use of amalgam, at one time a common filling material used to treat the sequelae of tooth decay, has substantially declined in the past decade [46]. This stemmed from concerns about perceived environmental and health effects of mercury in amalgams [47]. Though dental amalgam is proven to be safe and effective for use in children, its use has largely been phased out in most of Europe and the U.S. because of caregiver concerns and opposition [48], [49]. Topical fluoride opposition in dental settings today may lead to a similar phenomenon in the future, leaving children at high-risk for caries even more susceptible to dental disease if dentistry were to lose fluoride as a preventive strategy [13], [16], [26]. Untreated dental disease in high-risk children is further exacerbated by inequitable access to dental coverage [50]. As caregiver acceptance of preventive health interventions evolves, it is important to address underlying oppositional factors [51].
There are four main study limitations. First, our participants include a convenience sample of caregivers at a single site. Our findings may not be representative beyond the population studied and caution in generalization of our findings is warranted. Second, there may be common risk factors associated with both topical fluoride and COVID-19 vaccine opposition that were not directly tested. The common risk factor approach is an alternative conceptual model that could be used to identify the factors related to both topical fluoride and COVID-19 vaccine opposition [16], [52]. Third, hesitancy is a continuous phenomenon and opposition may not be binary as modeled in our study. Future work should continue to elucidate the complex relationship between hesitancy and opposition. Fourth, nearly one-third of survey participants were excluded from the regression analyses because of missing data, which may affect both internal and external generalizability of findings. Participants with missing data on at least one other question, but not COVID-19 vaccine opposition or topical fluoride opposition, were significantly more likely to express opposition to each (OR=2.1 and 2.0, respectively). This suggests that missing data were not completely missing at random. Future research should continue to identify ways to reduce missing data in health surveys.
5 Conclusions
The following conclusions can be drawn from the findings of this study:1. Caregiver topical fluoride opposition in dental settings was significantly associated with COVID-19 vaccine opposition for their children, even after adjusting for other variables.
2. Caregiver educational level and self-reported political ideology were also significantly associated with COVID-19 vaccine opposition in the covariate-adjusted regression model.
3. Additional research is needed to develop clinical interventions, including tailored and evidence-based communication strategies and a clinical screening tool for fluoride opposition.
Data Availability
Data will be made available on request.
Funding
This work was supported by the U.S. National Institute of Dental and Craniofacial Research (Grant No. R01DE026741, 2018-2022) and the American Academy of Pediatric Dentistry Graduate Student Research Award (2022).
CRediT authorship contribution statement
Sapna J. Saini: Conceptualization, Methodology, Investigation, Writing – original draft, Writing – review & editing, Visualization, Project administration. Adam C. Carle: Methodology, Software, Validation, Formal analysis, Data curation, Writing – review & editing. Anna R. Forsyth: Writing – review & editing. Donald L. Chi: Conceptualization, Methodology, Writing – original draft, Writing – review & editing, Supervision, Funding acquisition.
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.
Acknowledgements
The authors would like to thank all study staff members at the University of Washington who helped initiate this study and volunteers who helped administer surveys at the University of Washington’s Center for Pediatric Dentistry. The authors would also like to thank all survey participants for their valuable time and contribution to this study.
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