query: has social distancing had an impact on slowing the spread of COVID-19?

positive: Increased Detection coupled with Social Distancing and Health Capacity Planning Reduce the Burden of COVID-19 Cases and Fatalities: A Proof of Concept Study using a Stochastic Computational Simulation Model Objective: In absence of any vaccine, the Corona Virus Disease 2019 (COVID-19) pandemic is being contained through a non-pharmaceutical measure termed Social Distancing (SD). However, whether SD alone is enough to flatten the epidemic curve is debatable. Using a Stochastic Computational Simulation Model, we investigated the impact of increasing SD, hospital beds and COVID-19 detection rates in preventing COVID-19 cases and fatalities. Research Design and Methods: The Stochastic Simulation Model was built using the EpiModel package in R. As a proof of concept study, we ran the simulation on Kasaragod, the most affected district in Kerala. We added 3 compartments to the SEIR model to obtain a SEIQHRF (Susceptible-Exposed-Infectious-Quarantined-Hospitalised-Recovered-Fatal) model. Results: Implementing SD only delayed the appearance of peak prevalence of COVID-19 cases. Doubling of hospital beds could not reduce the fatal cases probably due to its overwhelming number compared to the hospital beds. Increasing detection rates could significantly flatten the curve and reduce the peak prevalence of cases (increasing detection rate by 5 times could reduce case number to half). Conclusions: An effective strategy to contain the epidemic spread of COVID-19 in India is to increase detection rates in combination with SD measures and increase in hospital beds.

positive: The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study BACKGROUND: In December, 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus, emerged in Wuhan, China. Since then, the city of Wuhan has taken unprecedented measures in response to the outbreak, including extended school and workplace closures. We aimed to estimate the effects of physical distancing measures on the progression of the COVID-19 epidemic, hoping to provide some insights for the rest of the world. METHODS: To examine how changes in population mixing have affected outbreak progression in Wuhan, we used synthetic location-specific contact patterns in Wuhan and adapted these in the presence of school closures, extended workplace closures, and a reduction in mixing in the general community. Using these matrices and the latest estimates of the epidemiological parameters of the Wuhan outbreak, we simulated the ongoing trajectory of an outbreak in Wuhan using an age-structured susceptible-exposed-infected-removed (SEIR) model for several physical distancing measures. We fitted the latest estimates of epidemic parameters from a transmission model to data on local and internationally exported cases from Wuhan in an age-structured epidemic framework and investigated the age distribution of cases. We also simulated lifting of the control measures by allowing people to return to work in a phased-in way and looked at the effects of returning to work at different stages of the underlying outbreak (at the beginning of March or April). FINDINGS: Our projections show that physical distancing measures were most effective if the staggered return to work was at the beginning of April; this reduced the median number of infections by more than 92% (IQR 66-97) and 24% (13-90) in mid-2020 and end-2020, respectively. There are benefits to sustaining these measures until April in terms of delaying and reducing the height of the peak, median epidemic size at end-2020, and affording health-care systems more time to expand and respond. However, the modelled effects of physical distancing measures vary by the duration of infectiousness and the role school children have in the epidemic. INTERPRETATION: Restrictions on activities in Wuhan, if maintained until April, would probably help to delay the epidemic peak. Our projections suggest that premature and sudden lifting of interventions could lead to an earlier secondary peak, which could be flattened by relaxing the interventions gradually. However, there are limitations to our analysis, including large uncertainties around estimates of R0 and the duration of infectiousness. FUNDING: Bill & Melinda Gates Foundation, National Institute for Health Research, Wellcome Trust, and Health Data Research UK.

positive: Evaluating the effectiveness of social distancing interventions against COVID-19 SARS-CoV-2 has infected over 140,000 people as of March 14, 2020. We use a mathematical model to investigate the effectiveness of social distancing interventions lasting six weeks in a middle-sized city in the US. We explore four social distancing strategies by reducing the contacts of adults over 60 years old, adults over 60 years old and children, all adults (25, 75 or 95% compliance), and everyone in the population. Our results suggest that social distancing interventions can avert cases by 20% and hospitalizations and deaths by 90% even with modest compliance within adults as long as the intervention is kept in place, but the epidemic is set to rebound once the intervention is lifted. Our models suggest that social distancing interventions will buy crucial time but need to occur in conjunction with testing and contact tracing of all suspected cases to mitigate transmission of SARS-CoV-2.

positive: Modeling the dynamics of COVID19 spread during and after social distancing Non-pharmaceutical intervention measures, such as social distancing, have so far been the only means to slow the spread of COVID19. In the United States, strict social distancing has resulted in different types infection dynamics. In some states, such as New York, extensive infection spread was followed by a pronounced decline of infection levels. In other states, such as California, less infection spread occurred before strict social distancing, and a different pattern was observed. Instead of a pronounced infection decline, a long-lasting plateau is evident, characterized by similar daily new infection levels. While these plateau dynamics cannot be readily reproduced with standard SIR infection models, we show that network models, in which individuals and their social contacts are explicitly tracked, can reproduce the plateau if network connections are cut due to social distancing measures. The reason is that in networks characterized by a degree of 2D spatial structure, infection tends to spread quadratically with time, but as edges are randomly removed, the infection spreads along nearly one-dimensional infection "corridors", resulting in plateau dynamics. Interestingly, the plateau dynamics are predicted to eventually transition into an infection decline phase without any further increase in social distancing measures. Additionally, the models suggest that a potential second wave becomes significantly less pronounced if social distancing is only relaxed once the dynamics have transitioned to the decline phase. The network models analyzed here allow us to interpret and reconcile different infection dynamics during social distancing observed in various US states.

positive: Transmission of Respiratory Infectious Diseases between Neighboring Cities using Agent-based Model and Compartmental Model We formulate an agent-based model and a compartmental model (SEIR) that simulate the spread of a respiratory infectious disease between two neighboring cities. We consider preventive measures such as implementation of social distancing and lockdown in a city, as well as the effect of protective gears or practices. The chance of travelling to another city and within the city during lockdown, and initial percentage of exposed and infected individuals on both cities influence the increase in the number of newly-infected individuals on both models. Our simulations show that (i) increase in exposed individuals results in increase in number of new infections, hence the need for increased testing-isolation efforts; (ii) protection level of 75-100% effectiveness impedes disease transmission; (iii) travelling within city or to other city can be an option given that strict preventive measures (e.g., non-pharmaceutical interventions) are observed; and (iv) the ideal set-up for neighboring cities is to implement lockdown when there is high risk of disease local transmission while individuals observe social distancing, maximizing protective measures, and isolating those that are exposed. The results of the agent-based and compartmental models show similar qualitative dynamics; the differences are due to different spatio-temporal heterogeneity and stochasticity. These models can aid decision makers in designing infectious disease-related policies to protect individuals while continuing population movement.

positive: Early transmission dynamics of COVID-19 in a southern hemisphere setting: Lima-Peru: February 29th-March 30th, 2020 The COVID-19 pandemic that emerged in Wuhan China has generated substantial morbidity and mortality impact around the world during the last four months. The daily trend in reported cases has been rapidly rising in Latin America since March 2020 with the great majority of the cases reported in Brazil followed by Peru as of April 15th, 2020. Although Peru implemented a range of social distancing measures soon after the confirmation of its first case on March 6th, 2020, the daily number of new COVID-19 cases continues to accumulate in this country. We assessed the early COVID-19 transmission dynamics and the effect of social distancing interventions in Lima, Peru. We estimated the reproduction number, R, during the early transmission phase in Lima from the daily series of imported and autochthonous cases by the date of symptoms onset as of March 30th, 2020. We also assessed the effect of social distancing interventions in Lima by generating short-term forecasts grounded on the early transmission dynamics before interventions were put in place. Prior to the implementation of the social distancing measures in Lima, the local incidence curve by the date of symptoms onset displays near exponential growth dynamics with the mean scaling of growth parameter, p, estimated at 0.9 (95%CI: 0.9,1.0) and the reproduction number at 2.3 (95% CI: 2.0, 2.5). Our analysis indicates that school closures and other social distancing interventions have helped slow down the spread of the novel coronavirus, with the nearly exponential growth trend shifting to an approximately linear growth trend soon after the broad scale social distancing interventions were put in place by the government. While the interventions appear to have slowed the transmission rate in Lima, the number of new COVID-19 cases continue to accumulate, highlighting the need to strengthen social distancing and active case finding efforts to mitigate disease transmission in the region.

positive: Modelling the impact of control measures against the COVID-19 pandemic in Viet Nam Objectives: Health care system of many countries are facing a surging burden of COVID-19. Although Vietnam has successfully controlled the COVID-19 pandemic to date, there is a sign of initial community transmission. An estimate of possible scenarios to prepare health resources in the future is needed. We used modelling methods to estimate impacts of mitigation measures on the COVID-19 pandemic in Vietnam. Methods: SEIR model built in the COVIDSIM1.1 tool was adopted using available data for estimation. The herd immunization scenario was with no intervention implemented. Other scenarios consisted of isolation and social distancing at different levels (25%, 50%, 75% and 10%, 20%, 30%, respectively). Outcomes include epidemic apex, daily new and cumulative cases, deaths, hospitalized patients and ICU beds needed. Results: By April 8, 2020, there would be 465 infected cases with COVID-19 in Viet Nam, of those 50% were detected. Cumulatively, there would be 1,400 cases and 30 deaths by end of 2020, if 75% of cases was detected and isolated, and 30% of social distancing could be maintained. The most effective intervention scenario is the detection and isolation of 75% infected cases and reduction of 10% social contacts. This will require an expansion of testing capacity at health facilities and in the community, posing a challenge to identify high-risk groups to prioritized testing. Conclusions: In a localized epidemic setting, the expansion of testing should be the key measure to control the epidemic. Social distancing plays a significant role to prevent further transmission to the community.

positive: COVID-19 data analysis and modeling in Palestine We estimate an actual number of infected cases in Palestine based on the 18-day effect from infection to death. We find that the number of cases in April 22 varies between 506 and 2 026 infected cases. We also focus on the reproductive number in Palestine based on population dynamics with two SEIR models. Dataset is from 5 March to 22 April 2020. With a transmission rate equal to 4.55 106, on May 22, the simulations predict 11 014 total infected cases in the optimistic scenario and 113 171 in the worst one. The crest of the pandemic is from 22 to 27 May 2020. The reproductive number R0 is equal to 1.54 for a fixed fraction of 0.6 of symptomatic cases that are reported and for a removal rate of 7. Palestinian COVID-19 mortality number is equal to 6 per million. It is small compared to countries neighboring Palestine. The infected number is equal to 88.4 per million, which is less than most of its neighbors. The basic reproduction number is still greater than 1. Changes to the transmission rate (over time) would be advisable, to fall R0 below the critical threshold.

positive: A simplified model for expected development of the SARS-CoV-2 (Corona) spread in Germany and US after social distancing Widespread opinions and discussion exist regarding the efficiency of social distancing after crucial spread of the SARS-CoV-2 virus during the actual Covid-19 pandemic. While Germany has released a federal law that prohibits any type of direct contact for more than 2 people other countries including the US released curfews. People are now wondering whether these measures are helpful to stop or hamper the Covid-19 pandemic and to limit the spread of the new corona virus. A quantitative statement on this question depends on many parameters that are difficult to grasp mathematically and cannot therefore be made conclusively (they include consistent adherence to the measures decided, the estimated number of unreported cases, the possible limitation by test capacities, possible mutations of the virus, etc ...). However, it turns out that a reduction in the actual daily new infection rate (actual daily growth rate of reported cases, in short: infection rate) from the current value of 30-35% in the US to 10% would be extremely effective in stopping the spread of the virus. The severe restrictions in Germany which closed any public events, schools and universities a week ago might already have contributed to a reduction of the growth rate of reported cases below 30%.

positive: Insufficient social distancing may be related to a future COVID-19 outbreak in Ijui-Brazil: Predictions of further social interventions. The coronavirus disease that initiates in 2019 (COVID-19) has proven to be highly contagious since it became pandemic quickly and nowadays presents higher transmission rates worldwide, including small Brazilian cities, as Ijui. Located in the northwestern of the State of Rio Grande do Sul (RS) with 83,475 inhabitants, Ijui was selected to receive a population-based survey divided into four steps separated by 15 days each that involved 1,750 subjects. Subjects were tested for the presence of antibodies against coronavirus (SARS CoV-2) and answered questions about social distance adherence, daily routine, comorbidities, and sociodemographic characteristics. In parallel, the local government registered the official COVID-19 cases in Ijui. In this study, we demonstrated the levels of social distancing adherence and the beginning of COVID-19 community transmission in Ijui and showed some predictions for cases, hospitalization, and deaths. We concluded that the insufficient social distancing registered in the population-based study might be related to the rapid increase of COVID-19 cases in Ijui. Our study predicts a closer outbreak of community infection of COVID-19, which could be avoided or attenuated if the levels of the social distancing in the population increase in the next weeks.

positive: A first study on the impact of current and future control measures on the spread of COVID-19 in Germany The novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe, with about 571,700 confirmed cases and about 26,500 deaths as of March 28th, 2020. We present here the preliminary results of a mathematical study directed at informing on the possible application or lifting of control measures in Germany. The developed mathematical models allow to study the spread of COVID-19 among the population in Germany and to asses the impact of non-pharmaceutical interventions. The overall goal is to suggest strategies for the mitigation of the current outbreak, slowing down the spread of the virus and thus reducing the peak in daily diagnosed cases, the demand for hospitalization or intensive care units admissions, and eventually fatalities.

positive: The impacts of simultaneous disease intervention decisions on epidemic outcomes Abstract Mathematical models of the interplay between disease dynamics and human behavioural dynamics can improve our understanding of how diseases spread when individuals adapt their behaviour in response to an epidemic. Accounting for behavioural mechanisms that determine uptake of infectious disease interventions such as vaccination and non-pharmaceutical interventions (NPIs) can significantly alter predicted health outcomes in a population. However, most previous approaches that model interactions between human behaviour and disease dynamics have modelled behaviour of these two interventions separately. Here, we develop and analyze an agent based network model to gain insights into how behaviour toward both interventions interact adaptively with disease dynamics (and therefore, indirectly, with one another) during the course of a single epidemic where an SIRV infection spreads through a contact network. In the model, individuals decide to become vaccinated and/or practice NPIs based on perceived infection prevalence (locally or globally) and on what other individuals in the network are doing. We find that introducing adaptive NPI behaviour lowers vaccine uptake on account of behavioural feedbacks, and also decreases epidemic final size. When transmission rates are low, NPIs alone are as effective in reducing epidemic final size as NPIs and vaccination combined. Also, NPIs can compensate for delays in vaccine availability by hindering early disease spread, decreasing epidemic size significantly compared to the case where NPI behaviour does not adapt to mitigate early surges in infection prevalence. We also find that including adaptive NPI behaviour strongly mitigates the vaccine behavioural feedbacks that would otherwise result in higher vaccine uptake at lower vaccine efficacy as predicted by most previous models, and the same feedbacks cause epidemic final size to remain approximately constant across a broad range of values for vaccine efficacy. Finally, when individuals use local information about others’ behaviour and infection prevalence, instead of population-level information, infection is controlled more efficiently through ring vaccination, and this is reflected in the time evolution of pair correlations on the network. This model shows that accounting for both adaptive NPI behaviour and adaptive vaccinating behaviour regarding social effects and infection prevalence can result in qualitatively different predictions than if only one type of adaptive behaviour is modelled.

positive: COVID-19 Pandemic Response Simulation: Impact of Non-pharmaceutical Interventions on Ending Lockdowns As many federal and state governments are starting to ease restrictions on non-pharmaceutical interventions (NPIs) used to flatten the curve, we developed an agent-based simulation to model the incidence of COVID-19 in King County, WA under several scenarios. While NPIs were effective in flattening the curve, any relaxation of social distancing strategies yielded a second wave. Even if daily confirmed cases dropped to one digit, daily incidence can peak again to 874 cases without import cases. Therefore, policy makers should be very cautious in reopening society.

positive: Understanding the Impact of Face Mask Usage Through Epidemic Simulation of Large Social Networks Evidence from the 2003 SARS epidemic and 2009 H1N1 pandemic shows that face masks can be an effective non-pharmaceutical intervention in minimizing the spread of airborne viruses. Recent studies have shown that using face masks is correlated to an individual’s age and gender, where females and older adults are more likely to wear a mask than males or youths. There are only a few studies quantifying the impact of using face masks to slow the spread of an epidemic at the population level, and even fewer studies that model their impact in a population where the use of face masks depends upon the age and gender of the population. We use a state-of-the-art agent-based simulation to model the use of face masks and quantify their impact on three levels of an influenza epidemic and compare different mitigation scenarios. These scenarios involve changing the demographics of mask usage, the adoption of mask usage in relation to a perceived threat level, and the combination of masks with other non-pharmaceutical interventions such as hand washing and social distancing. Our results shows that face masks alone have limited impact on the spread of influenza. However, when face masks are combined with other interventions such as hand sanitizer, they can be more effective. We also observe that monitoring social internet systems can be a useful technique to measure compliance. We conclude that educating the public on the effectiveness of masks to increase compliance can reduce morbidity and mortality.

positive: A pandemic influenza modeling and visualization tool Abstract The National Strategy for Pandemic Influenza outlines a plan for community response to a potential pandemic. In this outline, state and local communities are charged with enhancing their preparedness. In order to help public health officials better understand these charges, we have developed a visual analytics toolkit (PanViz) for analyzing the effect of decision measures implemented during a simulated pandemic influenza scenario. Spread vectors based on the point of origin and distance traveled over time are calculated and the factors of age distribution and population density are taken into effect. Healthcare officials are able to explore the effects of the pandemic on the population through a geographical spatiotemporal view, moving forward and backward through time and inserting decision points at various days to determine the impact. Linked statistical displays are also shown, providing county level summaries of data in terms of the number of sick, hospitalized and dead as a result of the outbreak. Currently, this tool has been deployed in Indiana State Department of Health planning and preparedness exercises, and as an educational tool for demonstrating the impact of social distancing strategies during the recent H1N1 (swine flu) outbreak.

positive: Timing of Community Mitigation and Changes in Reported COVID-19 and Community Mobility - Four U.S. Metropolitan Areas, February 26-April 1, 2020. Community mitigation activities (also referred to as nonpharmaceutical interventions) are actions that persons and communities can take to slow the spread of infectious diseases. Mitigation strategies include personal protective measures (e.g., handwashing, cough etiquette, and face coverings) that persons can use at home or while in community settings; social distancing (e.g., maintaining physical distance between persons in community settings and staying at home); and environmental surface cleaning at home and in community settings, such as schools or workplaces. Actions such as social distancing are especially critical when medical countermeasures such as vaccines or therapeutics are not available. Although voluntary adoption of social distancing by the public and community organizations is possible, public policy can enhance implementation. The CDC Community Mitigation Framework (1) recommends a phased approach to implementation at the community level, as evidence of community spread of disease increases or begins to decrease and according to severity. This report presents initial data from the metropolitan areas of San Francisco, California; Seattle, Washington; New Orleans, Louisiana; and New York City, New York* to describe the relationship between timing of public policy measures, community mobility (a proxy measure for social distancing), and temporal trends in reported coronavirus disease 2019 (COVID-19) cases. Community mobility in all four locations declined from February 26, 2020 to April 1, 2020, decreasing with each policy issued and as case counts increased. This report suggests that public policy measures are an important tool to support social distancing and provides some very early indications that these measures might help slow the spread of COVID-19.

positive: Early transmission dynamics of COVID-19 in a southern hemisphere setting: Lima-Peru: February 29(th)–March 30(th), 2020. The COVID-19 pandemic that emerged in Wuhan China has generated substantial morbidity and mortality impact around the world during the last four months. The daily trend in reported cases has been rapidly rising in Latin America since March 2020 with the great majority of the cases reported in Brazil followed by Peru as of April 15(th), 2020. Although Peru implemented a range of social distancing measures soon after the confirmation of its first case on March 6(th), 2020, the daily number of new COVID-19 cases continues to accumulate in this country. We assessed the early COVID-19 transmission dynamics and the effect of social distancing interventions in Lima, Peru. We estimated the reproduction number, R, during the early transmission phase in Lima from the daily series of imported and autochthonous cases by the date of symptoms onset as of March 30(th), 2020. We also assessed the effect of social distancing interventions in Lima by generating short-term forecasts grounded on the early transmission dynamics before interventions were put in place. Prior to the implementation of the social distancing measures in Lima, the local incidence curve by the date of symptoms onset displays near exponential growth dynamics with the mean scaling of growth parameter, p, estimated at 0.9 (95%CI: 0.9,1.0) and the reproduction number at 2.3 (95% CI: 2.0, 2.5). Our analysis indicates that school closures and other social distancing interventions have helped slow down the spread of the novel coronavirus, with the nearly exponential growth trend shifting to an approximately linear growth trend soon after the broad scale social distancing interventions were put in place by the government. While the interventions appear to have slowed the transmission rate in Lima, the number of new COVID-19 cases continue to accumulate, highlighting the need to strengthen social distancing and active case finding efforts to mitigate disease transmission in the region.

positive: Suppression of Groups Intermingling as Appealing Option For Flattening and Delaying the Epidemiological Curve While Allowing Economic and Social Life at Bearable Level During COVID-19 Pandemic In this work, we simulate the COVID-19 pandemic dynamics in a population modeled as a network of groups wherein infection can propagate both via intra-group and via inter-group interactions. Our results emphasize the importance of diminishing the inter-group infections in the effort of substantial flattening and delaying of the epi(demiologic) curve with concomitant mitigation of disastrous economy and social consequences. To exemplify with a limiting case, splitting a population into m (say, 5 or 10) noninteracting groups while keeping intra-group interaction unchanged yields a stretched epidemiologic curve having the maximum number of daily infections reduced and postponed in time by the same factor $m$ (5 or 10). More generally, our study suggests a practical approach to fight against SARS-CoV-2 virus spread based on population splitting into groups and minimizing intermingling between them. This strategy can be pursued by large-scale infrastructure reorganization of activity at different levels in big logistic units (e.g., large productive networks, factories, enterprises, warehouses, schools, (seasonal) harvest work). Importantly, unlike total lockdwon strategy, the proposed approach prevents economic ruin and keeps social life at a more bearable level than distancing everyone from anyone. Last but not least, the declaration, for the first time in Europe, that COVID-19 epidemic ended in the two million people Slovenia may be taken as confirming the advantage of the strategy proposed in this paper.

positive: The effect of social distance measures on COVID-19 epidemics in Europe: an interrupted time series analysis Following the introduction of unprecedented “stay-at-home” national policies, the COVID-19 pandemic recently started declining in Europe. Our research aims were to characterize the changepoint in the flow of the COVID-19 epidemic in each European country and to evaluate the association of the level of social distancing with the observed decline in the national epidemics. Interrupted time series analyses were conducted in 28 European countries. Social distance index was calculated based on Google Community Mobility Reports. Changepoints were estimated by threshold regression, national findings were analyzed by Poisson regression, and the effect of social distancing in mixed effects Poisson regression model. Our findings identified the most probable changepoints in 28 European countries. Before changepoint, incidence of new COVID-19 cases grew by 24% per day on average. From the changepoint, this growth rate was reduced to 0.9%, 0.3% increase, and to 0.7% and 1.7% decrease by increasing social distancing quartiles. The beneficial effect of higher social distance quartiles (i.e., turning the increase into decline) was statistically significant for the fourth quartile. Notably, many countries in lower quartiles also achieved a flat epidemic curve. In these countries, other plausible COVID-19 containment measures could contribute to controlling the first wave of the disease. The association of social distance quartiles with viral spread could also be hindered by local bottlenecks in infection control. Our results allow for moderate optimism related to the gradual lifting of social distance measures in the general population, and call for specific attention to the protection of focal micro-societies enriching high-risk elderly subjects, including nursing homes and chronic care facilities.

positive: Orthogonal Functions for Evaluating Social Distancing Impact on CoVID-19 Spread Early CoVID-19 growth often obeys: N{t}=N/Iexp[+K/ot], with K/o=[(ln2)/(t/dbl)], where t/dbl is the pandemic doubling time, prior to society-wide Social Distancing. Previously, we modeled Social Distancing with t/dbl as a linear function of time, where N[t]=1exp[+K/A t/(1+ gamma/o t)] is used here. Additional parameters besides {K/o,gamma/o} are needed to better model different rho[t]=dN[t]/dt shapes. Thus, a new Orthogonal Function Model [OFM] is developed here using these orthogonal function series: N(Z) = sum[m=0,M/F] g/m L/m(Z) exp[-Z] , R(Z) = sum[m=0,M/F] c/m L/m(Z) exp[-Z] , where N(Z) and Z[t] form an implicit N[t]=N(Z[t]) function, giving: G/o = [K/A / gamma/o ] , Z[t] = +[ G/o / (1+ gamma/ot) ] , rho[t] = [ gamma/o / G/o ] (Z^2) R(Z) , with L/m(Z) being the Laguerre Polynomials. At large M/F values, nearly arbitrary functions for N[t] and rho[t]=dN[t]/dt can be accommodated. How to determine {K/A, gamma/o} and the {g/m; m=(0,+M/F)} constants from any given N(Z) dataset is derived, with rho[t] set by: c/(M/F - k) = sum[m=0,k] g/m . The bing.com USA CoVID-19 data was analyzed using M/F=(0,1,2) in the OFM. All results agreed to within about 10 percent, showing model robustness. Averaging over all these predictions gives the following overall estimates for the number of USA CoVID-19 cases at the pandemic end: = 5,009,677 (+/-) 269,450 (data to 5/3/20), and = 4,422,803 (+/-) 162,580 (data to 6/7/20), which compares the pre- and post-early May bing.com revisions. The CoVID-19 pandemic in Italy was examined next. The M/F=2 limit was inadequate to model the Italy rho[t] pandemic tail. Thus, regions with a quick CoVID-19 pandemic shutoff may have additional Social Distancing factors operating, beyond what can be easily modeled by just progressively lengthening pandemic doubling times (with 13 Figures).

positive: Spatial Network based model forecasting transmission and control of COVID-19 The SARS-CoV-2 driven infectious novel coronavirus disease (COVID-19) has been declared a pandemic by virtue of its brutal impact on the world in terms of loss on human life, health, economy, and other crucial resources. With the aim to explore more about its aspects, we adopted the SEIQRD (Susceptible-Exposed-Infected-Quarantine-Recovered-Death) pandemic spread with a time delay on the heterogeneous population and geography in this work. Focusing on the spatial heterogeneity, the entire population of interest in a region is divided into small distinct geographical sub regions, which interact by means of migration networks across boundaries. Utilizing the estimations of the time delay differential equations based model, we analyzed the spread dynamics of disease in a region and its sub regions. The model based numerical outcomes are validated from real time available data for India. We computed the approximate peak infection in forward time and relative timespan when disease outspread halts. To further evaluate the influence of the delay on the long term system dynamics, the sensitivity analysis is performed on time delay. The most crucial parameter, basic reproduction number R0 and its time-dependent generalization, has been estimated at both regional and sub regional levels. The impact of the most significant lockdown measure that has been implemented in India to contain the pandemic spread has been extensively studied by considering no lockdown scenario. A suggestion based on outcomes, for a bit relaxed lockdown, followed by an extended period of strict social distancing as one of the most effective control measures to manage COVID-19 spread is provided for India.

positive: Study of Non-Pharmacological Interventions on COVID-19 Spread COVID-19 disease has emerged as one of the life threatening threat to the society. It is caused by a novel beta coronavirus. It began as unidentified pneumonia of unknown aetiology in Wuhan City, Hubei province in China emerged in December 2019. No vaccine has been produced till now. Mathematical models are used to study impact of different measures used to decrease pandemic. Mathematical models have been designed to estimate the numbers of spreaders in different scenarios in the present manuscript. In the present manuscript, three different mathematical models have been proposed with different scenarios such as screening, quarantine and NPIs for estimating number of virus spreaders. the analysis shows that the numbers of COVID-19 patients will be more without screening the peoples coming from other countries. Since, every people suffering with COVID-19 disease are spreaders. The screening and quarantine with NPIs have been implemented to study their impact on the spreaders. It has been found that NPI measures are able to reduce number of spreaders. The NPI measures reduces the growth of the spread function and providing decision makers more time to prepare with in dealing of the disease.

positive: Effect of the social distancing measures on the spread of COVID-19 in 10 highly infected countries From the end of 2019, an unprecedented novel coronavirus, which was named COVID-19 by the World Health Organization (WHO) emerged from Wuhan city, China. Despite rigorous global containment and quarantine efforts, the incidence of COVID-19 has continued to rise, with over 4 million confirmed-cases and over 300,000 deaths worldwide until mid-May. This study aims to present the effect of the promulgation of social distancing measures on the spread of COVID-19 in the cases of 10 highly infected countries. The authors focus on the statistics of the COVID-19 confirmed-cases and deaths in 10 highly infected countries, including The U.S., Spain, Italy, The U.K., France, Germany, Russia, Turkey, Iran and China, and the response to the pandemic of these countries in the period from January 11 to May 2, 2020. The relationships between the social distancing measures and the statistics of COVID-19 confirmed-cases and deaths were analyzed in order to elucidate the effectiveness of the social distancing measures on the spread of COVID-19 in 10 highly infected countries. The results showed it took1-4 weeks since the highest level of social distancing measures promulgation until the daily confirmed-cases and deaths showed signs of decreasing. The effectiveness of the social distancing measures on the spread of COVID-19 was different between the 10 focused countries. This variation is due to the difference in the levels of promulgated social distancing measures, as well as the difference in the COVID-19 spread situation at the time of promulgation between the countries.

positive: Impact of policy interventions and social distancing on SARS-CoV-2 transmission in the United States Background: Policymakers have employed various non-pharmaceutical interventions (NPIs) such as stay-at-home orders and school closures to limit the spread of Coronavirus disease (COVID-19). However, these measures are not without cost, and careful analysis is critical to quantify their impact on disease spread and guide future initiatives. This study aims to measure the impact of NPIs on the effective reproductive number (Rt) and other COVID-19 outcomes in U.S. states. Methods: In order to standardize the stage of disease spread in each state, this study analyzes the weeks immediately after each state reached 500 cases. The primary outcomes were average Rt in the week following 500 cases and doubling time from 500 to 1000 cases. Linear and logistic regressions were performed in R to assess the impact of various NPIs while controlling for population density, GDP, and certain health metrics. This analysis was repeated for deaths with doubling time from 50 to 100 deaths and included several healthcare infrastructure control variables. Results: States that had a stay-at-home order in place at the time of their 500th case are associated with lower average Rt the following week compared to states without a stay-at-home order (p < 0.001) and are significantly less likely to have an Rt>1 (OR 0.07, 95% CI 0.01 to 0.37, p = 0.004). These states also experienced a significantly longer doubling time from 500 to 1000 cases (HR 0.35, 95% CI 0.17 to 0.72, p = 0.004). States in the highest quartile of average time spent at home were also slower to reach 1000 cases than those in the lowest quartile (HR 0.18, 95% CI 0.06 to 0.53, p = 0.002). Discussion: Few studies have analyzed the effect of statewide stay-at-home orders, school closures, and other social distancing measures in the U.S., which has faced the largest COVID-19 case burden. States with stay-at-home orders have a 93% decrease in the odds of having a positive Rt at a standardized point in disease burden. States that plan to scale back such measures should carefully monitor transmission metrics. Key words: COVID-19, SARS-CoV-2, Coronavirus, Public Policy, Social Distancing, Non-pharmaceutical Interventions, Stay-at-home Order, Shelter-in-place.

positive: Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria This work examines the impact of various non-pharmaceutical control measures (government and personal) on the population dynamics of the novel coronavirus disease 2019 (COVID-19) in Lagos, Nigeria, using an appropriately formulated mathematical model. Using the available data, since its first reported case on 16 March 2020, we seek to develop a predicative tool for the cumulative number of reported cases and the number of active cases in Lagos; we also estimate the basic reproduction number of the disease outbreak in the aforementioned State in Nigeria. Using numerical simulations, we show the effect of control measures, specifically the common social distancing, use of face mask and case detection (via contact tracing and subsequent testings) on the dynamics of COVID-19. We also provide forecasts for the cumulative number of reported cases and active cases for different levels of the control measures being implemented. Numerical simulations of the model show that if at least 55% of the population comply with the social distancing regulation with about 55% of the population effectively making use of face masks while in public, the disease will eventually die out in the population and that, if we can step up the case detection rate for symptomatic individuals to about 0.8 per day, with about 55% of the population complying with the social distancing regulations, it will lead to a great decrease in the incidence (and prevalence) of COVID-19.

positive: Enabling and Enforcing Social Distancing Measures using Smart City and ITS Infrastructures: A COVID-19 Use Case Internet of Things is a revolutionary domain that has the caliber to impact our lives and bring significant changes to the world. Several IoT applications have been envisioned to facilitate data driven and smart application for the user. Smart City and Intelligent Transportation System (ITS) offer a futuristic vision of smart, secure and safe experience to the end user, and at the same time efficiently manage the sparse resources and optimize the efficiency of city operations. However, outbreaks and pandemics like COVID-19 have revealed limitations of the existing deployments, therefore, architecture, applications and technology systems need to be developed for swift and timely enforcement of guidelines, rules and government orders to contain such future outbreaks. This work outlines novel architecture, potential use-cases and some future directions in developing such applications using Smart City and ITS.

positive: Will COVID-19 pandemic diminish by summer-monsoon in India? Lesson from the first lockdown The novel Coronavirus (2019-nCoV) was identified in Wuhan, Hubei Province, China, in December 2019 and has created a medical emergency worldwide. It has spread rapidly to multiple countries and has been declared a pandemic by the World Health Organization. In India, it is already reported more than 18 thousand cases and more than 600 deaths due to Coronavirus disease 2019 (COVID-19) till April 20, 2020. Previous studies on various viral infections like influenza have supported an epidemiological hypothesis that the cold and dry (low absolute humidity) environments favor the survival and spread of droplet-mediated viral diseases. These viral transmissions found attenuated in warm and humid (high absolute humidity) environments. However, the role of temperature, humidity, and absolute humidity in the transmission of COVID-19 has not yet been well established. Therefore the study to investigate the meteorological condition for incidence and spread of COVID-19 infection, to predict the epidemiology of the infectious disease, and to provide a scientific basis for prevention and control measures against the new disease is required for India. In this work, we analyze the local weather patterns of the Indian region affected by the COVID-19 virus for March and April months, 2020. We have investigated the effect of meteorological parameters like Temperature, relative humidity, and absolute humidity on the rate of spread of COVID-19 using daily confirm cases in India. We have used daily averaged meteorological data for the last three years (2017-2019) for March and April month and the same for the year 2020 for March 1 to April 15. We found a positive association (Pearsons r=0.56) between temperature and daily COVID-19 cases over India. We found a negative association of humidity (RH and AH) with daily COVID-19 Cases (Persons r=-0.62, -0.37). We have also investigated the role of aerosol in spreading the pandemic across India because its possible airborne nature. For this, we have investigated the association of aerosols (AOD) and other pollutions (NO2) with COVID-19 cases during the study period and also during the first lockdown period (25 March-15 April) in India. We found a negative association in March when there were few cases, but in April, it shows positive association when the number of cases is more (for AOD it was r=-0.41 and r=0.28 respectively). During the lockdown period, aerosols (AOD) and other pollutants (NO2; an indicator of PM2.5) reduced sharply with a percentage drop of about 36 and 37, respectively. This reduction may have reduced the risk for COVID-19 through air transmission due to the unavailability of aerosol particles as a base. HYSPLIT forward trajectory model also shows that surface aerosols may travel up to 4 km according to wind and direction within three h of its generation. If coronavirus becomes airborne as suggested by many studies, then it may have a higher risk of transmission by aerosols particles. So relaxing in the lockdown and environmental rules in terms of pollutant emissions from power plants, factories, and other facilities would be a wrong choice and could result in more COVID-19 incidences and deaths in India. Therefore the current study, although limited, suggests that it is doubtful that the spread of COVID-19 would slow down in India due to meteorological factors, like high temperature and high humidity. Because a large number of cases have already been reported in the range of high Tem, high Relative, and high absolute humidity regions of India. Thus our results in no way suggest that COVID-19 would not spread in warm, humid regions or during summer/monsoon. So effective public health interventions should be implemented across India to slow down the transmission of COVID-19. If COVID-19 is indeed sensitive to environmental factors, it could be tested in the coming summer-monsoon for India. So the only summer is not going to help India until monsoon is coming. Only government mitigations strategies would be helpful, whether its lockdown, aggressive and strategic testing, medical facilities, imposing social distancing, encouraging to use face mask or monitoring by a mobile application (Aarogya Setu).

positive: Anticipating the novel coronavirus disease (COVID-19) pandemic The infectious novel coronavirus disease COVID-19 outbreak has been declared as a public health emergency of international concern, and later as an epidemic. To date, this outbreak has infected more than one million people and killed over fifty thousand people across the world. In most countries, the COVID-19 incidence curve rises sharply in a short span of time, suggesting a transition from a disease free (or low-burden disease) equilibrium state to a sustained infected (or high-burden disease) state. Such a transition from one stable state to another state in a relatively short span of time is often termed as a critical transition. Critical transitions can be, in general, successfully forecasted using many statistical measures such as return rate, variance and lag-1 autocorrelation. Here, we report an empirical test of this forecasting on the COVID-19 data sets for nine countries including India, China and the United States. For most of the data sets, an increase in autocorrelation and a decrease in return rate predict the onset of a critical transition. Our analysis suggests two key features in predicting the COVID-19 incidence curve for a specific country: a) the timing of strict social distancing and/or lockdown interventions implemented, and b) the fraction of a nation's population being affected by COVID-19 at the time of implementation of these interventions. Further, using satellite data of nitrogen dioxide which is emitted predominantly as a result of anthropogenic activities, as an indicator of lockdown policy, we find that in countries where the lockdown was implemented early and strictly have been successful in reducing the extent of transmission of the virus. These results hold important implications for designing effective strategies to control the spread of infectious pandemics.

positive: Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus A pandemic of a novel Coronavirus emerged in December of 2019 (COVID-19), causing devastating public health impact across the world. In the absence of a safe and effective vaccine or antivirals, strategies for controlling and mitigating the burden of the pandemic are focused on non-pharmaceutical interventions, such as social-distancing, contact-tracing, quarantine, isolation, and the use of face-masks in public. We develop a new mathematical model for assessing the population-level impact of the aforementioned control and mitigation strategies. Rigorous analysis of the model shows that the disease-free equilibrium is locally-asymptotically stable if a certain epidemiological threshold, known as the reproduction number (denoted by âc), is less than unity. Simulations of the model, using data relevant to COVID-19 transmission dynamics in the US state of New York and the entire US, show that the pandemic burden will peak in mid and late April, respectively. The worst-case scenario projections for cumulative mortality (based on the baseline levels of anti-COVID non-pharmaceutical interventions considered in the study) decrease dramatically by 80% and 64%, respectively, if the strict social-distancing measures implemented are maintained until the end of May or June, 2020. The duration and timing of the relaxation or termination of the strict social-distancing measures are crucially-important in determining the future trajectory of the COVID-19 pandemic. This study shows that early termination of the strict social-distancing measures could trigger a devastating second wave with burden similar to those projected before the onset of the strict social-distancing measures were implemented. The use of efficacious face-masks (such as surgical masks, with estimated efficacy ≥ 70%) in public could lead to the elimination of the pandemic if at least 70% of the residents of New York state use such masks in public consistently (nationwide, a compliance of at least 80% will be required using such masks). The use of low efficacy masks, such as cloth masks (of estimated efficacy less than 30%), could also lead to significant reduction of COVID-19 burden (albeit, they are not able to lead to elimination). Combining low efficacy masks with improved levels of the other anti-COVID-19 intervention strategies can lead to the elimination of the pandemic. This study emphasizes the important role social-distancing plays in curtailing the burden of COVID-19. Increases in the adherence level of social-distancing protocols result in dramatic reduction of the burden of the pandemic, and the timely implementation of social-distancing measures in numerous states of the US may have averted a catastrophic outcome with respect to the burden of COVID-19. Using face-masks in public (including the low efficacy cloth masks) is very useful in minimizing community transmission and burden of COVID-19, provided their coverage level is high. The masks coverage needed to eliminate COVID-19 decreases if the masks-based intervention is combined with the strict social-distancing strategy.

positive: COVID-19 trend in Bangladesh: deviation from epidemiological model and critical analysis of the possible factors Background: Since its first report on March 08, COVID-19 positive cases and number of deaths are increasing in Bangladesh. In the first month of COVID-19 infection, incidence of daily positive cases did follow the susceptible, infected and recovered (SIR) based predictions we reported in April, but started to deviate in the following month. COVID-19 transmission and disease progression depends on multifaceted determinants e.g. viral genetics, host immunity, social distancing, co-morbidity, socio-demographic and environmental parameters. Therefore deviation in confirmed cases from predicted model may appear and warrant thorough investigation. In this short report, we tried to demonstrate and analyze the possible factors associated with the deviation which included preventive intervention strategies, socioeconomic capabilities, climatic and meteorological indexes, acquired immunity of Bangladeshi population, demographic characteristics, health indicators and food habits. Findings: The key factor responsible for the deviation was found to be the number of tests performed. Having population with low median age, young age groups are being mostly infected. Low prevalence of non-communicable diseases among them and strong immunity compared to the elderly might have kept most of them asymptomatic with silent recovery. Warm temperature, humidity and UV index of Bangladesh during this summer period might have contributed to the slow progression of infection. Longer daylight mediated immunity, fresh air circulations and ventilation, less density in rural areas and certain food habits perhaps helped the large number of populations to restrict the infection. Conclusion: Despite all these helpful determinants in Bangladesh, person to person contact is still the leading risk factor for COVID-19 transmission. Infection may increase rapidly if safe distance and preventive measures are not strictly followed while resuming the normal social and work life. A global second wave may hit in many countries in autumn and as well as in Bangladesh in mid-October when winter starts to approach. Strong collaborative action plans, strategies and implementation are needed immediately to prevent catastrophe.

positive: Suppression of Groups Intermingling as Appealing Option For Flattening and Delaying the Epidemiologic Curve While Allowing Economic and Social Life at Bearable Level During COVID-19 Pandemic In this work, we simulate the COVID-19 pandemic dynamics in a population modeled as a network of groups wherein infection can propagate both via intra-group and via inter-group interactions. Our results emphasize the importance of diminishing the inter-group infections in the effort of substantial flattening and delaying of the epi(demiologic) curve with concomitant mitigation of disastrous economy and social consequences. To exemplify with a limiting case, splitting a population into m (say, 5 or 10) noninteracting groups while keeping intra-group interaction unchanged yields a stretched epidemiologic curve having the maximum number of daily infections reduced and postponed in time by the same factor m (5 or 10). More generally, our study suggests a practical approach to fight against SARS-CoV-2 virus spread based on population splitting into groups and minimizing intermingling between them. This strategy can be pursued by large-scale infrastructure reorganization of activity at different levels in big logistic units (e.g., large productive networks, factories, enterprises, warehouses, schools, (seasonal) harvest work). Importantly, unlike total lockdwon strategy, the proposed approach prevents economic ruin and keeps social life at a more bearable level than distancing everyone from anyone.

positive: Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study BACKGROUND: The isolation of symptomatic cases and tracing of contacts has been used as an early COVID-19 containment measure in many countries, with additional physical distancing measures also introduced as outbreaks have grown. To maintain control of infection while also reducing disruption to populations, there is a need to understand what combination of measures-including novel digital tracing approaches and less intensive physical distancing-might be required to reduce transmission. We aimed to estimate the reduction in transmission under different control measures across settings and how many contacts would be quarantined per day in different strategies for a given level of symptomatic case incidence. METHODS: For this mathematical modelling study, we used a model of individual-level transmission stratified by setting (household, work, school, or other) based on BBC Pandemic data from 40â162 UK participants. We simulated the effect of a range of different testing, isolation, tracing, and physical distancing scenarios. Under optimistic but plausible assumptions, we estimated reduction in the effective reproduction number and the number of contacts that would be newly quarantined each day under different strategies. RESULTS: We estimated that combined isolation and tracing strategies would reduce transmission more than mass testing or self-isolation alone: mean transmission reduction of 2% for mass random testing of 5% of the population each week, 29% for self-isolation alone of symptomatic cases within the household, 35% for self-isolation alone outside the household, 37% for self-isolation plus household quarantine, 64% for self-isolation and household quarantine with the addition of manual contact tracing of all contacts, 57% with the addition of manual tracing of acquaintances only, and 47% with the addition of app-based tracing only. If limits were placed on gatherings outside of home, school, or work, then manual contact tracing of acquaintances alone could have an effect on transmission reduction similar to that of detailed contact tracing. In a scenario where 1000 new symptomatic cases that met the definition to trigger contact tracing occurred per day, we estimated that, in most contact tracing strategies, 15â000-41â000 contacts would be newly quarantined each day. INTERPRETATION: Consistent with previous modelling studies and country-specific COVID-19 responses to date, our analysis estimated that a high proportion of cases would need to self-isolate and a high proportion of their contacts to be successfully traced to ensure an effective reproduction number lower than 1 in the absence of other measures. If combined with moderate physical distancing measures, self-isolation and contact tracing would be more likely to achieve control of severe acute respiratory syndrome coronavirus 2 transmission. FUNDING: Wellcome Trust, UK Engineering and Physical Sciences Research Council, European Commission, Royal Society, Medical Research Council.

positive: Nigeria and Italy Divergences in Coronavirus Experience: Impact of Population Density BACKGROUND: The reports and information on coronavirus are not conspicuously emphasising the possible impact of population density on the explanation of difference in rapid spread and fatality due to the disease and not much has been done on bicountry comparisons. OBJECTIVE: The study examined the impact of population density on the spread of COVID-19 pandemic in two sociodemographic divergent countries. METHODS: The study conducted a scoping review of published and unpublished articles including blogs on incidences and fatalities of COVID-19. The analysis followed qualitative description and quantitative presentation of the findings using only frequency distribution, percentages, and graphs. RESULTS: The two countries shared similar experience of “importation” of COVID-19, but while different states ordered partial lockdown in Nigeria, it was an immediate total lockdown in Italy. The physician/patient ratio is high in Italy (1 : 328) but low in Nigeria (1 : 2500), while population density is 221 in Nigeria and 206 in Italy. Daily change in incidence rate reduced to below 20% after 51 and 30 days of COVID-19 first incidence in Italy and Nigeria, respectively. Fatality rate has plummeted to below 10% after the 66(th) day in Italy but has not been stabilised in Nigeria. CONCLUSION: The authors upheld both governments' recommending measures that tilted towards personal hand-hygienic practices and social distancing. Authors suggested that if Italy with its high physician/patient ratio and lower population density compared to Nigeria could suffer high fatality from COVID-19 pandemic under four weeks, then Nigeria with its low physician/patient ratio and higher population density should prepare to face harder time if the pandemic persists.

positive: Causal Impact of Masks, Policies, Behavior on Early Covid-19 Pandemic in the U.S. This paper evaluates the dynamic impact of various policies, such as school, business, and restaurant closures, adopted by the US states on the growth rates of confirmed Covid-19 cases and social distancing behavior measured by Google Mobility Reports, where we take into consideration of people's voluntarily behavioral response to new information of transmission risks. Using the US state-level data, our analysis finds that both policies and information on transmission risks are important determinants of people's social distancing behavior, and shows that a change in policies explains a large fraction of observed changes in social distancing behavior. Our counterfactual experiments indicate that removing all policies on April 1st of 2020 would have lead to 30 to 200 times more additional cases by late May. Removing only the non-essential businesses closures (while maintaining restrictions on movie theaters and restaurants) would have increased the weekly growth rate of cases between -0.02 and 0.06 and would have lead to -10% to 40% more cases by late May. Finally, nationally mandating face masks for employees on April 1st would have reduced the case growth rate by 0.1-0.25. This leads to 30% to 57% fewer reported cases by late May, which translates into, roughly, 30-57 thousand saved lives.

positive: The Immediate Effect of COVID-19 Policies on Social Distancing Behavior in the United States In the absence of a vaccine and effective antiviral medications, most of the non-pharmaceutical interventions focus on reducing social contact rates through different social distancing policies. However, the effectiveness of different policies and their relative impact vis-a-vis that of mechanisms driven by public awareness and voluntary actions have not been studied. This is crucial since in most places we observe significant reductions in social interaction before any policy was implemented. Variations in types and effective dates of different social distancing policies across different states in the US create a natural experiment to study the causal impact of each policy during the early stage of the outbreak. Using these policy variations and the aggregate human mobility and location trends published by Google for the month of March 2020, we employ a quasi-experimental approach to measure the impact of six common policies on people's presence at home and their mobility in different types of public places. Our results rank six common social distancing policies based on the magnitude and significance of their impact, beyond what has already been achieved through voluntary actions. They show that while strong policies such as statewide stay home mandate and non-essential business closure have strong causal impacts on reducing social interactions, most of the expected impact of more lenient policies (such as large gathering ban and school closure mandates) are already reaped from non-policy mechanisms such as voluntary actions and public awareness.

positive: Modeling the early phase of the Belgian COVID-19 epidemic using a stochastic compartmental model and studying its implied future trajectories Following the onset of the ongoing COVID-19 pandemic throughout the world, a large fraction of the global population is or has been under strict measures of physical distancing and quarantine, with many countries being in partial or full lockdown. These measures are imposed in order to reduce the spread of the disease and to lift the pressure on healthcare systems. Estimating the impact of such interventions as well as monitoring the gradual relaxing of these stringent measures is quintessential to understand how resurgence of the COVID-19 epidemic can be controlled for in the future. In this paper we use a stochastic age-structured discrete time compartmental model to describe the transmission of COVID-19 in Belgium. Our model explicitly accounts for age-structure by integrating data on social contacts to (i) assess the impact of the lockdown as implemented on March 13, 2020 on the number of new hospitalizations in Belgium; (ii) conduct a scenario analysis estimating the impact of possible exit strategies on potential future COVID-19 waves. More specifically, the aforementioned model is fitted to hospital admission data, data on the daily number of COVID-19 deaths and serial serological survey data informing the (sero)prevalence of the disease in the population while relying on a Bayesian MCMC approach. Our age-structured stochastic model describes the observed outbreak data well, both in terms of hospitalizations as well as COVID-19 related deaths in the Belgian population. Despite an extensive exploration of various projections for the future course of the epidemic, based on the impact of adherence to measures of physical distancing and a potential increase in contacts as a result of the relaxation of the stringent lockdown measures, a lot of uncertainty remains about the evolution of the epidemic in the next months.

positive: Characterizing super-spreading events and age-specific infectivity of COVID-19 transmission in Georgia, USA As the current COVID-19 pandemic continues to impact countries around the globe, refining our understanding of its transmission dynamics and the effectiveness of interventions is imperative. In particular, it is essential to obtain a firmer grasp on the effect of social distancing, potential individual-level heterogeneities in transmission such as age-specific infectivity, and impact of super-spreading. To this end, it is important to exploit multiple data streams that are becoming abundantly available during the pandemic. In this paper, we formulate an individual-level spatio-temporal mechanistic framework to statistically integrate case data with geo-location data and aggregate mobility data, enabling a more granular understanding of the transmission dynamics of COVID-19. We analyze reported cases from surveillance data, between March and early May 2020, in five (urban and rural) counties in the State of Georgia USA. We estimate natural history parameters of COVID-19 and infer unobserved quantities including infection times and transmission paths using Bayesian data-augmentation techniques. First, our results show that the overall median reproductive number was 2.88 (with 95% C.I. [1.85, 4.9]) before the state-wide shelter-in-place order issued in early April, and the effective reproductive number was reduced to below 1 about two weeks by the order. Super-spreading appears to be widespread across space and time, and it may have a particularly important role in driving the outbreak in the rural area and increasing importance towards later stages of outbreaks in both urban and rural settings. Overall, about 2% of cases may have directly infected 20% of all infections. We estimate that the infected children and younger adults (<60 years old) may be 2.38 [1.30, 3.51] times more transmissible than infected elderly (>=60), and the former may be the main driver of super-spreading. Through the synthesis of multiple data streams using our transmission modelling framework, our results enforce and improve our understanding of the natural history and transmission dynamics of COVID-19. More importantly, we reveal the roles of age-specific infectivity and characterize systematic variations and associated risk factors of super-spreading. These have important implications for the planning of relaxing social distancing and, more generally, designing optimal control measures.

positive: Universal Features of Epidemic Models Under Social Distancing Guidelines Different epidemiological models, from the classical SIR system to more sophisticated ones involving population compartments for socially distanced, quarantined, infection aware, asymptomatic infected, and other individuals, share some remarkable dynamic characteristics when contact rates are subject to periodic or one-shot changes. In simple pulsed isolation policies, a linear relationship is found among optimal start time and duration for reduction of the infected peak. If a single interval social distancing starts too early or too late it will be ineffective with respect to decreasing the peak of infection. On the other hand, the nonlinearity of epidemic models leads to non-monotone behavior of the peak of infected population under periodic relaxation policies. This observation led us to hypothesize that an additional single interval social distancing at a proper time can significantly decrease the infected peak of periodic policies, and we verified this improvement.

positive: The impact of containment measures and air temperature on mitigating the transmission of COVID-19: a novel data-based comprehensive modeling analysis Background The COVID-19 is spreading worldwide, early non-pharmaceutical Interventions (NPIs) is crucial for mitigating COVID-19 epidemic. We aim to evaluate the impact of containment measures and the epidemic features of COVID-19 under social NPIs in Mainland China. Methods Under the strict social NPIs, the spreading pattern of COVID-19 in China has changed into mostly clustered intra-household or intro-acquaintance transmission, and we established a stochastic NPIs model, named ScEIQRsh to fit the epidemic and NPIs data of each province in China. Results This ScEIQRsh model could be well fitted with both the reported number of accumulative confirmed cases and epidemiological survey (EPS)-based quarantined cases of each province in China. We found that the median transmission rate of COVID-19 among acquaintances was 10.22 (IQR 8.47, 12.35) across Mainland China and the COVID-19 spreading was prevented by NPIs implementation within 25-30 days. Among NPIs, measures to diminish contactable susceptible (Sc), such as staying home, travel constraint etc. and measures to avoid delay of diagnosis and hospitalized isolation ({eta}) were more effective than EPS-based quarantine ({kappa},{rho} or surveyQ). Upon the fitted models, the proportion of asymptomatic infectors was determined to be 14.88% (IQR 8.17%, 25.37%). The median incubation period and communicable period of COVID-19 under NPIs were 4.16 (IQR 3.60, 4.71) and 6.77 (IQR 4.53, 10.36) days respectively, and the median time from exposed to being contagious was 2.39 (IQR 2.26, 2.56) days. Besides, we identified that the optimal temperature for COVID-19 spreading was in the range of 5{degrees}C-14{degrees}C. Conclusion This study provided useful suggestions about NPI strategy for the prevention of COVID-19 spreading, which should be helpful for the control of COVID-19, as well as other similar infectious disease.

positive: The first three months of the COVID-19 epidemic: Epidemiological evidence for two separate strains of SARS-CoV-2 viruses spreading and implications for prevention strategies About one month after the COVID-19 epidemic peaked in Mainland China and SARS-CoV-2 migrated from China westward to Europe and then the U.S., the epidemiological data begin to provide important insights into the risks associated with the disease and the effectiveness of intervention strategies. Like other respiratory diseases, including the 2003 SARS epidemic, the virus remains only about two months in any given population, yet the peak incidence and the lethality can vary. The data suggest that at least two strains of the 2020 SARS-CoV-2 virus have evolved during its migration from Mainland China to Europe. South Korea, Iran, and Italy were hit by the more dangerous "SKII" variant. While the epidemic in China is about to end, and in Europe about to level off, the course of the epidemic in the younger US population is still increasing and the peak level will likely depend on which of the strains has entered the US first. The same models that help us to understand the epidemic also help us to choose prevention strategies. While containment merely prolongs the time the disease circulates until the proportion of immune people is high enough for "herd immunity", reducing disease severity, either by vaccination or by early treatment of complications, is the best strategy against a respiratory virus disease.

positive: Causal Impact of Masks, Policies, Behavior on Early Covid-19 Pandemic in the U.S This paper evaluates the dynamic impact of various policies adopted by US states on the growth rates of confirmed Covid-19 cases and deaths as well as social distancing behavior measured by Google Mobility Reports, where we take into consideration people's voluntarily behavioral response to new information of transmission risks. Our analysis finds that both policies and information on transmission risks are important determinants of Covid-19 cases and deaths and shows that a change in policies explains a large fraction of observed changes in social distancing behavior. Our counterfactual experiments suggest that nationally mandating face masks for employees on April 1st could have reduced the growth rate of cases and deaths by more than 10 percentage points in late April, and could have led to as much as 17 to 55 percent less deaths nationally by the end of May, which roughly translates into 17 to 55 thousand saved lives. Our estimates imply that removing non-essential business closures (while maintaining school closures, restrictions on movie theaters and restaurants) could have led to -20 to 60 percent more cases and deaths by the end of May. We also find that, without stay-at-home orders, cases would have been larger by 25 to 170 percent, which implies that 0.5 to 3.4 million more Americans could have been infected if stay-at-home orders had not been implemented. Finally, not having implemented any policies could have led to at least a 7 fold increase with an uninformative upper bound in cases (and deaths) by the end of May in the US, with considerable uncertainty over the effects of school closures, which had little cross-sectional variation.

positive: Mathematical Model with Social Distancing Parameter for Early Estimation of COVID-19 Spread COVID-19 is well known to everyone in the world. It has spread around the world. No vaccine or antiviral treatment is available till now. COVID-19 patients are increasing day by day. All countries have adopted social distancing as a preventive measure to reduce spread. It becomes necessary to estimate the number of peoples going to be affected with COVID-19 in advance so that necessary arrangements can be done. Mathematical models are used to provide early disease estimation based on limited parameters. In the present manuscript, a novel mathematical model with a social distancing parameter has been proposed to provide early COVID-19 spread estimation. The model has been validated with real data set. It has been observed that the proposed model is more accurate in spread estimation.

positive: Spreading of COVID-19 in Brazil: Impacts and uncertainties in social distancing strategies Brazil's continental dimension poses a challenge to the control of the spread of COVID-19. Due to the country specific scenario of high social and demographic heterogeneity, combined with limited testing capacity, lack of reliable data, under-reporting of cases, and restricted testing policy, the focus of this study is twofold: (i) to develop a generalized SEIRD model that implicitly takes into account the quarantine measures, and (ii) to estimate the response of the COVID-19 spread dynamics to perturbations/uncertainties. By investigating the projections of cumulative numbers of confirmed and death cases, as well as the effective reproduction number, we show that the model parameter related to social distancing measures is one of the most influential along all stages of the disease spread and the most influential after the infection peak. Due to such importance in the outcomes, different relaxation strategies of social distancing measures are investigated in order to determine which strategies are viable and less hazardous to the population. The results highlight the need of keeping social distancing policies to control the disease spread. Specifically, the considered scenario of abrupt social distancing relaxation implemented after the occurrence of the peak of positively diagnosed cases can prolong the epidemic, with a significant increase of the projected numbers of confirmed and death cases. An even worse scenario could occur if the quarantine relaxation policy is implemented before evidence of the epidemiological control, indicating the importance of the proper choice of when to start relaxing social distancing measures.

positive: A single holiday was the turning point of the COVID-19 policy of Israel Background: The impact of COVID-19 has been profound, and the public health challenge seem to be the most serious regarding respiratory viruses since the 1918 H1N1 influenza pandemic. In the absence of effective vaccine or biomedical treatment, the basic rules of public health measures have not changed, namely public distancing. Methods: We analyzed epidemiological investigation reports during the first month of the outbreak in Israel. In addition, we present a deterministic compartment model and simulations of several scenarios emphasizing quarantine and isolation policies given their efficiency. Results: We identify an abrupt change from controlled epidemic regime to an exponential growth (R_0= 2.19) in light of the actual policy-makers decisions and public behavior in Israel. Our analysis show that before the abrupt change, the new cases trend was due to returning citizens infected abroad. The abrupt change followed a holiday in which social distancing was clearly inefficient and many public gatherings were held. We further discuss three different modeled scenarios of quarantine efficiency: high-, medium-, and low-efficiency. Conclusions: Israel early lessons show that there is no allowance to compromise with the directive of social distancing. Even before the onset of the pandemic in Israel, fine-tuned but determined early decisions were taken by policy makers to monitor flight arrivals from Covid-19 affected regions and to limit public gatherings. Our analysis show that one particular holiday has shifted the occurrence curve from controlled regime to exponential growth. Therefore, even a short lapse in public responsiveness can have a dramatic effect.

positive: A sub-national analysis of the rate of transmission of COVID-19 in Italy Italy was the first European country to experience sustained local transmission of COVID-19. As of 1st May 2020, the Italian health authorities reported 28,238 deaths nationally. To control the epidemic, the Italian government implemented a suite of non-pharmaceutical interventions (NPIs), including school and university closures, social distancing and full lockdown involving banning of public gatherings and non essential movement. In this report, we model the effect of NPIs on transmission using data on average mobility. We estimate that the average reproduction number (a measure of transmission intensity) is currently below one for all Italian regions, and significantly so for the majority of the regions. Despite the large number of deaths, the proportion of population that has been infected by SARS-CoV-2 (the attack rate) is far from the herd immunity threshold in all Italian regions, with the highest attack rate observed in Lombardy (13.18% [10.66%-16.70%]). Italy is set to relax the currently implemented NPIs from 4th May 2020. Given the control achieved by NPIs, we consider three scenarios for the next 8 weeks: a scenario in which mobility remains the same as during the lockdown, a scenario in which mobility returns to pre-lockdown levels by 20%, and a scenario in which mobility returns to pre-lockdown levels by 40%. The scenarios explored assume that mobility is scaled evenly across all dimensions, that behaviour stays the same as before NPIs were implemented, that no pharmaceutical interventions are introduced, and it does not include transmission reduction from contact tracing, testing and the isolation of confirmed or suspected cases. New interventions, such as enhanced testing and contact tracing are going to be introduced and will likely contribute to reductions in transmission; therefore our estimates should be viewed as pessimistic projections. We find that, in the absence of additional interventions, even a 20% return to pre-lockdown mobility could lead to a resurgence in the number of deaths far greater than experienced in the current wave in several regions. Future increases in the number of deaths will lag behind the increase in transmission intensity and so a second wave will not be immediately apparent from just monitoring of the daily number of deaths. Our results suggest that SARS-CoV-2 transmission as well as mobility should be closely monitored in the next weeks and months. To compensate for the increase in mobility that will occur due to the relaxation of the currently implemented NPIs, adherence to the recommended social distancing measures alongside enhanced community surveillance including swab testing, contact tracing and the early isolation of infections are of paramount importance to reduce the risk of resurgence in transmission.

positive: Quantifying the role of social distancing, personal protection and case detection in mitigating COVID-19 outbreak in Ontario, Canada Public health interventions have been implemented to mitigate the spread of coronavirus disease 2019 (COVID-19) in Ontario, Canada; however, the quantification of their effectiveness remains to be done and is important to determine if some of the social distancing measures can be relaxed without resulting in a second wave. We aim to equip local public health decision- and policy-makers with mathematical model-based quantification of implemented public health measures and estimation of the trend of COVID-19 in Ontario to inform future actions in terms of outbreak control and de-escalation of social distancing. Our estimates confirm that (1) social distancing measures have helped mitigate transmission by reducing daily infection contact rate, but the disease transmission probability per contact remains as high as 0.145 and case detection rate was so low that the effective reproduction number remained higher than the threshold for disease control until the closure of non-essential business in the Province; (2) improvement in case detection rate and closure of non-essential business had resulted in further reduction of the effective control number to under the threshold. We predict the number of confirmed cases according to different control efficacies including a combination of reducing further contact rates and transmission probability per contact. We show that improved case detection rate plays a decisive role to reduce the effective reproduction number, and there is still much room in terms of improving personal protection measures to compensate for the strict social distancing measures.

positive: Evaluation of the potential incidence of COVID-19 and effectiveness of contention measures in Spain: a data-driven approach Our society is currently experiencing an unprecedented challenge, managing and containing an outbreak of a new coronavirus disease known as COVID-19. While China - were the outbreak started - seems to have been able to contain the growth of the epidemic, different outbreaks are nowadays being detected in multiple countries. Much is currently unknown about the natural history of the disease, such as a possible asymptomatic spreading or the role of age in both the susceptibility and mortality of the disease. Nonetheless, authorities have to take action and implement contention measures, even if not everything is known. To facilitate this task, we have studied the effect of different containment strategies that can be put into effect. Our work specifically refers to the situation in Spain as of February 28th, 2020, where a few dozens of cases have been detected. We implemented an SEIR-metapopulation model that allows tracing explicitly the spatial spread of the disease through data-driven stochastic simulations. Our results are in line with the most recent recommendations from the World Health Organization, namely, that the best strategy is the early detection and isolation of individuals with symptoms, followed by interventions and public recommendations aimed at reducing the transmissibility of the disease, which although not efficacious for disease eradication, would produce as a second-order effect a delay of several days in the raise of the number of infected cases

positive: Impact assessment of non-pharmaceutical interventions against coronavirus disease 2019 and influenza in Hong Kong: an observational study BACKGROUND: A range of public health measures have been implemented to suppress local transmission of coronavirus disease 2019 (COVID-19) in Hong Kong. We examined the effect of these interventions and behavioural changes of the public on the incidence of COVID-19, as well as on influenza virus infections, which might share some aspects of transmission dynamics with COVID-19. METHODS: We analysed data on laboratory-confirmed COVID-19 cases, influenza surveillance data in outpatients of all ages, and influenza hospitalisations in children. We estimated the daily effective reproduction number (R(t)) for COVID-19 and influenza A H1N1 to estimate changes in transmissibility over time. Attitudes towards COVID-19 and changes in population behaviours were reviewed through three telephone surveys done on Jan 20–23, Feb 11–14, and March 10–13, 2020. FINDINGS: COVID-19 transmissibility measured by R(t) has remained at approximately 1 for 8 weeks in Hong Kong. Influenza transmission declined substantially after the implementation of social distancing measures and changes in population behaviours in late January, with a 44% (95% CI 34–53%) reduction in transmissibility in the community, from an estimated R(t) of 1·28 (95% CI 1·26–1·30) before the start of the school closures to 0·72 (0·70–0·74) during the closure weeks. Similarly, a 33% (24–43%) reduction in transmissibility was seen based on paediatric hospitalisation rates, from an R(t) of 1·10 (1·06–1·12) before the start of the school closures to 0·73 (0·68–0·77) after school closures. Among respondents to the surveys, 74·5%, 97·5%, and 98·8% reported wearing masks when going out, and 61·3%, 90·2%, and 85·1% reported avoiding crowded places in surveys 1 (n=1008), 2 (n=1000), and 3 (n=1005), respectively. INTERPRETATION: Our study shows that non-pharmaceutical interventions (including border restrictions, quarantine and isolation, distancing, and changes in population behaviour) were associated with reduced transmission of COVID-19 in Hong Kong, and are also likely to have substantially reduced influenza transmission in early February, 2020. FUNDING: Health and Medical Research Fund, Hong Kong.

positive: Predictions, role of interventions and effects of a historic national lockdown in India's response to the COVID-19 pandemic: data science call to arms Importance: India has taken strong and early public health measures for arresting the spread of the COVID-19 epidemic. With only 536 COVID-19 cases and 11 fatalities, India - a democracy of 1.34 billion people - took the historic decision of a 21-day national lockdown on March 25. The lockdown was further extended to May 3, soon after the analysis of this paper was completed. Objective: To study the short- and long-term impact of an initial 21-day lockdown on the total number of COVID-19 cases in India compared to other less severe non-pharmaceutical interventions using epidemiological forecasting models and Bayesian estimation algorithms; to compare effects of hypothetical durations of lockdown from an epidemiological perspective; to study alternative explanations for slower growth rate of the virus outbreak in India, including exploring the association of the number of cases and average monthly temperature; and finally, to outline the pivotal role of reliable and transparent data, reproducible data science methods, tools and products as we reopen the country and prepare for a post lock-down phase of the pandemic. Design, Setting, and Participants: We use the daily data on the number of COVID-19 cases, of recovered and of deaths from March 1 until April 7, 2020 from the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). Additionally, we use COVID-19 incidence counts data from Kaggle and the monthly average temperature of major cities across the world from Wikipedia. Main Outcome and Measures: The current time-series data on daily proportions of cases and removed (recovered and death combined) from India are analyzed using an extended version of the standard SIR (susceptible, infected, and removed) model. The eSIR model incorporates time-varying transmission rates that help us predict the effect of lockdown compared to other hypothetical interventions on the number of cases at future time points. A Markov Chain Monte Carlo implementation of this model provided predicted proportions of the cases at future time points along with credible intervals (CI). Results: Our predicted cumulative number of COVID-19 cases in India on April 30 assuming a 1-week delay in people's adherence to a 21-day lockdown (March 25 - April 14) and a gradual, moderate resumption of daily activities after April 14 is 9,181 with upper 95% CI of 72,245. In comparison, the predicted cumulative number of cases under "no intervention" and "social distancing and travel bans without lockdown" are 358 thousand and 46 thousand (upper 95% CI of nearly 2.3 million and 0.3 million) respectively. An effective lockdown can prevent roughly 343 thousand (upper 95% CI 1.8 million) and 2.4 million (upper 95% CI 38.4 million) COVID-19 cases nationwide compared to social distancing alone by May 15 and June 15, respectively. When comparing a 21-day lockdown with a hypothetical lockdown of longer duration, we find that 28-, 42-, and 56-day lockdowns can approximately prevent 238 thousand (upper 95% CI 2.3 million), 622 thousand (upper 95% CI 4.3 million), 781 thousand (upper 95% CI 4.6 million) cases by June 15, respectively. We find some suggestive evidence that the COVID-19 incidence rates worldwide are negatively associated with temperature in a crude unadjusted analysis with Pearson correlation estimates [95% confidence interval] between average monthly temperature and total monthly incidence around the world being -0.185 [-0.548, 0.236] for January, -0.110 [-0.362, 0.157] for February, and -0.173 [-0.314, -0.026] for March. Conclusions and Relevance: The lockdown, if implemented correctly in the end, has a high chance of reducing the total number of COVID-19 cases in the short term, and buy India invaluable time to prepare its healthcare and disease monitoring system. Our analysis shows we need to have some measures of suppression in place after the lockdown for the best outcome. We cannot heavily rely on the hypothetical prevention governed by meteorological factors such as temperature based on current evidence. From an epidemiological perspective, a longer lockdown between 42-56 days is preferable. However, the lockdown comes at a tremendous price to social and economic health through a contagion process not dissimilar to that of the coronavirus itself. Data can play a defining role as we design post-lockdown testing, reopening and resource allocation strategies. Software: Our contribution to data science includes an interactive and dynamic app (covind19.org) with short- and long-term projections updated daily that can help inform policy and practice related to COVID-19 in India. Anyone can visualize the observed data for India and create predictions under hypothetical scenarios with quantification of uncertainties. We make our prediction codes freely available (https://github.com/umich-cphds/cov-ind-19) for reproducible science and for other COVID-19 affected countries to use them for their prediction and data visualization work.

positive: Protocol for an Observational Study on the Effects of Social Distancing on Influenza-Like Illness and COVID-19 The novel coronavirus disease (COVID-19) is a highly contagious respiratory disease that was first detected in Wuhan, China in December 2019, and has since spread around the globe, claiming more than 69,000 lives by the time this protocol is written. It has been widely acknowledged that the most effective public policy to mitigate the pandemic is \emph{social and physical distancing}: keeping at least six feet away from people, working from home, closing non-essential businesses, etc. There have been a lot of anecdotal evidences suggesting that social distancing has a causal effect on disease mitigation; however, few studies have investigated the effect of social distancing on disease mitigation in a transparent and statistically-sound manner. We propose to perform an optimal non-bipartite matching to pair counties with similar observed covariates but vastly different average social distancing scores during the first week (March 16th through Match 22nd) of President's \emph{15 Days to Slow the Spread} campaign. We have produced a total of $302$ pairs of two U.S. counties with good covariate balance on a total of $16$ important variables. Our primary outcome will be the average observed illness collected by Kinsa Inc. two weeks after the intervention period. Although the observed illness does not directly measure COVID-19, it reflects a real-time aspect of the pandemic, and unlike confirmed cases, it is much less confounded by counties' testing capabilities. We also consider observed illness three weeks after the intervention period as a secondary outcome. We will test a proportional treatment effect using a randomization-based test with covariance adjustment and conduct a sensitivity analysis.

positive: Social distancing: A non-pharmacological intervention for COVID-19. Social distancing is one of the non-pharmacological measures to contain the infection of COVID-19. At this point in time, no vaccine is available to prevent the infection, no effective drugs are available to prevent and treat the disease, and none of the communities have acquired herd immunity. Various models have shown positive impact of social distancing, provided its implementation on vast majority of the population over a long period of time. Its effect is manifold. Besides flattening the curve, it impacts the political, fiscal, social, economic aspects of the society, along with socially vulnerable and economically underprivileged population. It becomes obsolete after the population develops herd immunity subsequent to widespread infection in the community, or after effective mass immunisation or specific drugs for its control, cure and prevention are available widely.

positive: Analysis and Prediction of the COVID-19 outbreak in Pakistan In this study, we estimate the severity of the COVID-19 outbreak in Pakistan prior to and after lockdown restrictions were eased. We also project the epidemic curve considering realistic quarantine, social distancing, and possible medication scenarios. We use a deterministic epidemic model that includes asymptomatic, quarantined, isolated, and medicated population compartments for our analysis. We calculate the basic reproduction number R0 for the pre and post lockdown periods, noting that during this time, no medication was available. The pre-lock down the value of R0 is estimated to be 1.07, and the post lockdown value is estimated to be 1.86. We use this analysis to project the epidemic curve for a variety of lockdown, social distancing, and medication scenarios. We note that if no substantial efforts are made to contain the epidemic, it will peak in mid of September, with the maximum projected active cases being close to 700,000. In a realistic, best-case scenario, we project that the epidemic peaks in early to mid-July with the maximum active cases being around 120000.We note that social distancing measures and medication, if available, will help flatten the curve, however without the reintroduction of further lockdown, it would be very difficult to bring R0 below 1. Our study strongly supports the recent WHO recommendation of reintroducing lockdowns to control the epidemic.

positive: Building resilience against biological hazards and pandemics: COVID-19 and its implications for the Sendai Framework Abstract 2020 has become the year of coping with COVID-19. This year was to be the “super year” for sustainability, a year of strengthening global actions to accelerate the transformations required for achieving the 2030 agenda. We argue that 2020 can and must be a year of both. Thus we call for more utilisation of the health-emergency disaster risk management (Health-EDRM) framework to complement current responses to COVID-19 and the patent risk of similar phenomena in the future. To make our case, we examine current responses to COVID-19 and their implications for the SFDRR. We argue that current mechanisms and strategies for disaster resilience, as outlined in the SFDRR, can enhance responses to epidemics or global pandemics such as COVID-19. In this regard, we make several general and DRR-specific recommendations. These recommendations concern knowledge and science provision in understanding disaster and health-related emergency risks, the extension of disaster risk governance to manage both disaster risks and potential health-emergencies, particularly for humanitarian coordination aspects; and the strengthening of community-level preparedness and response.

positive: Evaluating the Effectiveness of Social Distancing Interventions to Delay or Flatten the Epidemic Curve of Coronavirus Disease By April 2, 2020, >1 million persons worldwide were infected with severe acute respiratory syndrome coronavirus 2. We used a mathematical model to investigate the effectiveness of social distancing interventions in a mid-sized city. Interventions reduced contacts of adults >60 years of age, adults 20-59 years of age, and children <19 years of age for 6 weeks. Our results suggest interventions started earlier in the epidemic delay the epidemic curve and interventions started later flatten the epidemic curve. We noted that, while social distancing interventions were in place, 20% of new cases and most hospitalizations and deaths were averted, even with modest reductions in contact among adults. However, when interventions ended, the epidemic rebounded. Our models suggest that social distancing can provide crucial time to increase healthcare capacity but must occur in conjunction with testing and contact tracing of all suspected cases to mitigate virus transmission.

positive: Impact of social distancing measures for preventing coronavirus disease 2019 : A systematic review and meta-analysis protocol Abstract Introduction: Social distancing measures (SDMs) protect public health from the outbreak of coronavirus disease 2019 (COVID-19). However, the impact of SDMs has been inconsistent and unclear. This study aims to assess the effects of SDMs (e.g. isolation, quarantine) for reducing the transmission of COVID-19. Methods and analysis: We will conduct a systematic review meta-analysis research of both randomised controlled trials and non-randomised controlled trials. We will search MEDLINE, EMBASE, Allied & Complementary Medicine, COVID-19 Research and WHO database on COVID-19 for primary studies assessing the enablers and barriers associated with SDMs, and will be reported in accordance with PRISMA statement. The PRISMA-P checklist will be used while preparing this protocol. We will use Joanna Briggs Institute guidelines (JBI Critical Appraisal Checklists) to assess the methodological qualities and synthesised performing thematic analysis. Two reviewers will independently screen the papers and extracted data. If sufficient data are available, the random-effects model for meta-analysis will be performed to measure the effect size of SDMs or the strengths of relationships. To assess the heterogeneity of effects, I2 together with the observed effects (Q-value, with degrees of freedom) will be used to provide the true effects in the analysis. Ethics and dissemination: Ethics approval and consent will not be required for this systematic review of the literature as it does not involve human participation. We will be able to disseminate the study findings using the following strategies: we will be publishing at least one paper in peer-reviewed journals, and an abstract will be presented at suitable national/international conferences or workshops. We will also share important information with public health authorities as well as with the World Health Organization.

positive: No Place Like Home: A Cross-National Assessment of the Efficacy of Social Distancing during the COVID-19 Pandemic. BACKGROUND In the absence of a cure in the time of pandemics, social distancing measures seem to be the most effective intervention to slow down the spread of disease. Various simulation-based studies have been conducted in the past to investigate the effectiveness of such measures. While those studies unanimously confirm the mitigating effect of social distancing on the disease spread, the reported effectiveness varies from 10% to more than 90% reduction in the number of infections. This level of uncertainty is mostly due to the complex dynamics of epidemics and their time-variant parameters. A real transactional data, however, can reduce the uncertainty and provide a less noisy picture of social distancing effectiveness. OBJECTIVE In this paper, we integrate multiple transactional data sets (GPS mobility data from Google and Apple as well as disease statistics data from ECDC) to study the role of social distancing policies in 26 countries wherein the transmission rate of the COVID-19 pandemic is analyzed over the course of five weeks. METHODS Relying on the SIR model and official COVID-19 reports, we first calculated the weekly transmission rate (β) of the coronavirus disease in 26 countries for five consecutive weeks. Then we integrated that with the Google's and Apple's mobility data sets for the same time frame and used a machine learning approach to investigate the relationship between mobility factors and β values. RESULTS Gradient Boosted Trees (GBT) regression analysis showed that changes in mobility patterns, resulted from social distancing policies, explain around 47% of the variation in the disease transmission rate. CONCLUSIONS Consistent with simulation-based studies, real cross-national transactional data confirms the effectiveness of social distancing interventions in slowing down the spread of the disease. Apart from providing less noisy and more generalizable support for the whole social distancing idea, we provide specific insights for public health policy-makers as to what locations should be given a higher priority for enforcing social distancing measures. CLINICALTRIAL

positive: Transmission Dynamics of COVID-19 and Impact on Public Health Policy In this work we construct a mathematical model for the transmission and spread of coronavirus disease 2019 or COVID-19. Our model features delay terms to account for (a) the time lapse or latency period between contracting the disease and displaying symptoms, and (b) the time lag in testing patients for the virus due to the limited numbers of testing facilities currently available. We find that the delay introduces a significant disparity between the actual and reported time-trajectories of cases in a particular region. Specifically, the reported case histories lag the actual histories by a few days. Hence, to minimize the spread of the disease, lockdowns and similarly drastic social isolation measures need to be imposed some time before the reported figures are approaching their peak values. We then account for the social reality that lockdowns can only be of a limited duration in view of practical considerations. We find that the most effective interval for imposing such a limited-time lockdown is one where the midpoint of the lockdown period coincides with the actual peak of the spread of the disease in the absence of the lockdown. We further show that the true effectivity of imposing a lockdown may be misrepresented and grossly underestimated by the reported case trajectories in the days following the action.

positive: Predictions for COVID-19 outbreak in India using Epidemiological models COVID-19 data from India is compared against several countries as well as key states in the US with a major outbreak, and it is found that the basic reproduction number R_0 for India is in the expected range of 1.4-3.9. Further, the rate of growth of infections in India is very close to that in Washington and California. Exponential and classic susceptible-infected-recovered (SIR) models based on available data are used to make short and long-term predictions on a daily basis. Based on the SIR model, it is estimated that India will enter equilibrium by the end of May 2020 with the final epidemic size of approximately 13,000. However, this estimation will be invalid if India enters the stage of community transmission. The impact of social distancing, again with the assumption of no community transmission, is also assessed by comparing data from different geographical locations.

positive: Can the COVID-19 epidemic be controlled on the basis of daily test reports? This paper studies if and to which extent COVID-19 epidemics can be controlled by authorities taking decisions on public health measures on the basis of daily reports of swab test results, active cases and total cases. A suitably simplified process model is derived to support the controllability analysis, highlighting the presence of very significant time delay; the model is validated with data from several outbreaks. The analysis shows that suppression strategies can be effective if strong enough and enacted early on. It also shows how mitigation strategies can fail because of the combination of delay, unstable dynamics, and uncertainty in the feedback loop; approximate conditions based on the theory of limitation of linear control are given for feedback control to be feasible.

positive: Timing of Community Mitigation and Changes in Reported COVID-19 and Community Mobility - Four U.S. Metropolitan Areas, February 26-April 1, 2020 Community mitigation activities (also referred to as nonpharmaceutical interventions) are actions that persons and communities can take to slow the spread of infectious diseases. Mitigation strategies include personal protective measures (e.g., handwashing, cough etiquette, and face coverings) that persons can use at home or while in community settings; social distancing (e.g., maintaining physical distance between persons in community settings and staying at home); and environmental surface cleaning at home and in community settings, such as schools or workplaces. Actions such as social distancing are especially critical when medical countermeasures such as vaccines or therapeutics are not available. Although voluntary adoption of social distancing by the public and community organizations is possible, public policy can enhance implementation. The CDC Community Mitigation Framework (1) recommends a phased approach to implementation at the community level, as evidence of community spread of disease increases or begins to decrease and according to severity. This report presents initial data from the metropolitan areas of San Francisco, California; Seattle, Washington; New Orleans, Louisiana; and New York City, New York* to describe the relationship between timing of public policy measures, community mobility (a proxy measure for social distancing), and temporal trends in reported coronavirus disease 2019 (COVID-19) cases. Community mobility in all four locations declined from February 26, 2020 to April 1, 2020, decreasing with each policy issued and as case counts increased. This report suggests that public policy measures are an important tool to support social distancing and provides some very early indications that these measures might help slow the spread of COVID-19.

positive: Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus A pandemic of a novel Coronavirus emerged in December of 2019 (COVID-19), causing devastating public health impact across the world. In the absence of a safe and effective vaccine or antivirals, strategies for controlling and mitigating the burden of the pandemic are focused on non-pharmaceutical interventions, such as social-distancing, contact-tracing, quarantine, isolation, and the use of face-masks in public. We develop a new mathematical model for assessing the population-level impact of the aforementioned control and mitigation strategies. Rigorous analysis of the model shows that the disease-free equilibrium is locally-asymptotically stable if a certain epidemiological threshold, known as the reproduction number (denoted by [Formula: see text]), is less than unity. Simulations of the model, using data relevant to COVID-19 transmission dynamics in the US state of New York and the entire US, show that the pandemic burden will peak in mid and late April, respectively. The worst-case scenario projections for cumulative mortality (based on the baseline levels of anti-COVID non-pharmaceutical interventions considered in the study) decrease dramatically by 80% and 64%, respectively, if the strict social-distancing measures implemented are maintained until the end of May or June, 2020. The duration and timing of the relaxation or termination of the strict social-distancing measures are crucially-important in determining the future trajectory of the COVID-19 pandemic. This study shows that early termination of the strict social-distancing measures could trigger a devastating second wave with burden similar to those projected before the onset of the strict social-distancing measures were implemented. The use of efficacious face-masks (such as surgical masks, with estimated efficacy [Formula: see text] 70%) in public could lead to the elimination of the pandemic if at least 70% of the residents of New York state use such masks in public consistently (nationwide, a compliance of at least 80% will be required using such masks). The use of low efficacy masks, such as cloth masks (of estimated efficacy less than 30%), could also lead to significant reduction of COVID-19 burden (albeit, they are not able to lead to elimination). Combining low efficacy masks with improved levels of the other anti-COVID-19 intervention strategies can lead to the elimination of the pandemic. This study emphasizes the important role social-distancing plays in curtailing the burden of COVID-19. Increases in the adherence level of social-distancing protocols result in dramatic reduction of the burden of the pandemic, and the timely implementation of social-distancing measures in numerous states of the US may have averted a catastrophic outcome with respect to the burden of COVID-19. Using face-masks in public (including the low efficacy cloth masks) is very useful in minimizing community transmission and burden of COVID-19, provided their coverage level is high. The masks coverage needed to eliminate COVID-19 decreases if the masks-based intervention is combined with the strict social-distancing strategy.

positive: Proactive social distancing mitigates COVID-19 outbreaks within a month across 58 mainland China cities In early 2020, cities across China enacted strict social distancing measures to contain emerging coronavirus (COVID-19) outbreaks. We estimated the speed with which these measures contained community transmission in each of 58 Chinese cities. On average, containment was achieved 7.83 days (SD 6.79 days) after the implementation of social distancing interventions, with an average reduction in the reproduction number (R(t)) of 54.3% (SD 17.6%) over that time period. A single day delay in the implementation of social distancing led to a 2.41 (95% CI: 0.97, 3.86) day delay in containment. Swift social distancing interventions may thus achieve rapid containment of newly emerging COVID-19 outbreaks.

positive: COVID-19 social distancing in the Kingdom of Saudi Arabia: Bold measures in the face of political, economic, social and religious challenges Abstract Social distancing at its various levels has been a key measure to mitigate the transmission of COVID-19. The implementation of strict measures for social distancing is challenging, including in the Kingdom of Saudi Arabia (KSA) due to its level of urbanizations, its social and religious norms and its annual hosting of high visibility international religious mass gatherings. KSA started introducing decisive social distancing measures early before the first case of COVID-19 was confirmed in the Kingdom. These ranged from suspension or cancelations of religious, entertainment and sporting mass gatherings and events such as the Umrah, shutting of educational establishments and mosques and postponing all non-essential gatherings, to imposing a partial curfew. These measures were taken in spite of their socio-economic, political and religious challenges in the interest of public and global health. The effect of these actions on the epidemic curve of the Kingdom and on the global fight against COVID-19 remains to be seen. However, given the current COVID-19 situation, further bold and probably unpopular measures are likely to be introduced in the future.

positive: Coronavirus Covid-19 spreading in Italy: optimizing an epidemiological model with dynamic social distancing through Differential Evolution The aim of this paper consists in the application of a recent epidemiological model, namely SEIR with Social Distancing (SEIR--SD), extended here through the definition of a social distancing function varying over time, to assess the situation related to the spreading of the coronavirus Covid--19 in Italy and in two of its most important regions, i.e., Lombardy and Campania. To profitably use this model, the most suitable values of its parameters must be found. The estimation of the SEIR--SD model parameters takes place here through the use of Differential Evolution, a heuristic optimization technique. In this way, we are able to evaluate for each of the three above-mentioned scenarios the daily number of infectious cases from today until the end of virus spreading, the day(s) in which this number will be at its highest peak, and the day in which the infected cases will become very close to zero.

positive: The Impact of Public Safety Measures on the Spread of COVID-19 in the United States Assessed By Causal Model-Based Projections of the Pandemic The novel coronavirus, SARS-CoV-2, and the disease it causes, COVID-19 was declared a pandemic on March 11, 2020 by the World Health Organization. Since then, the disease has spread all over the world, with the United States becoming the country with the highest number of cases. Governments around the world have undertaken varying degrees of public safety measures, including recommendations and ad campaigns for improved hygiene practices, enacting social distancing requirements and limiting large public gatherings, and stay-at-home orders and lockdowns. In the United States, while the response has varied greatly from state to state, we clearly see that the effect of these public safety measures is significant and, if these measures continue to remain in effect, or are expanded to a nationwide lockdown, the pandemic can be controlled and the disease likely overcome with mitigated consequences. In this paper, we model the spread of the novel coronavirus using a causal model. We find that, with continued lockdown measures, the United States can, according to this model, limit the total number of infections to ~1.35 million and the total number of deaths to ~72 thousand. A 60 day lockdown can save countless lives.

positive: COVID-19, Australia: Epidemiology Report 10 (Reporting week to 23:59 AEST 5 April 2020) Confirmed cases in Australia notified up to 5 April 2020: Notifications = 5,805; Deaths = 33. Notifications in Australia remain predominantly among people with recent overseas travel, with some locally-acquired cases being detected. Most locally-acquired cases are able to be linked back to a confirmed case, with a small portion unable to be epidemiologically link. The distribution of overseas-acquired cases to locally acquired cases varies by jurisdiction. Early indications are that reduction in international travel, domestic movement, social distancing measures and public health action are slowing the spread of the disease. Internationally, cases continue to increase, with high rates of increase observed in the European region and the United States of America. The epidemiology differs from country to country depending not only on the disease, but also on differences in case detection, testing and implemented public health measures.

positive: Early transmission dynamics of COVID-19 in Chile: From sub-exponential ascending growth dynamics to a stationary disease wave, March-April, 2020 The COVID-19 pandemic reached Latin America in February 2020, with the first case in Chile identified on March 3rd, 2020. Since then Chile has accumulated a total of 14365 cases as of April 28th, 2020. We estimate the reproduction number during the early transmission phase in Chile and study the effectiveness of control interventions by conducting short-term forecasts based on early transmission dynamics of COVID-19. The incidence curve displays sub-exponential growth dynamics with the scaling of growth parameter, p, estimated at 0.8 (95% CI: 0.7, 0.8) and the reproduction number estimated at 1.6 (95% CI: 1.5, 1.6). The sub-epidemic model indicates a stationary wave of stable epidemic size. Our current findings point to sustained transmission of SARS-CoV-2 in Chile. While the social distancing interventions have slowed the virus spread, the number of new COVID-19 cases continue to accrue, underscoring the need for persistent social distancing efforts to control the epidemic.

positive: COVID-19 herd immunity strategies: walking an elusive and dangerous tightrope The rapid growth in cases of COVID-19 has threatened to overwhelm healthcare systems in multiple countries. In response, severely affected countries have had to consider a range of public health strategies achieved by implementing non-pharmaceutical interventions. Broadly, these strategies have fallen into two categories: i) “mitigation”, which aims to achieve herd immunity by allowing the SARS-CoV-2 virus to spread through the population while mitigating disease burden, and ii) “suppression”, aiming to drastically reduce SARS-CoV-2 transmission rates and halt endogenous transmission in the target population. Using an age-structured transmission model, parameterised to simulate SARS-CoV-2 transmission in the UK, we assessed the prospects of success using both of these approaches. We simulated a range of different non-pharmaceutical intervention scenarios incorporating social distancing applied to differing age groups. We found that it is possible to suppress SARS-CoV-2 transmission if social distancing measures are sustained at a sufficient level for a period of months. Our modelling did not support achieving herd immunity as a practical objective, requiring an unlikely balancing of multiple poorly-defined forces. Specifically, we found that: i) social distancing must initially reduce the transmission rate to within a narrow range, ii) to compensate for susceptible depletion, the extent of social distancing must be vary over time in a precise but unfeasible way, and iii) social distancing must be maintained for a long duration (over 6 months).

positive: Unknown unknowns – COVID-19 and potential global mortality COVID-19 (SARS-CoV-2) is currently a global pandemic. This paper will attempt to estimate global infection rates and potential resultant mortality in the absence of effective treatment and/or vaccination. Calculations are based on World Health Organisation data from Wuhan in China: 14% of infected cases are severe, 5% require intensive care and 4% die. Estimated infection rates and mortality rates at the level of continents and some individual countries (when these are of sufficient size) are tabulated. This pandemic may cause close to half a billion deaths, i.e. 6% of the global population – and potentially more. At the risk of sounding sensational, but with a sober sense of realism, healthcare risks being plunged into the Middle-Ages if the public do not do their part. Infection cannot occur in the absence of contact. The only way to mitigate these numbers is to apply social distancing and take the standard precautions so frequently reiterated by Public Health: hand washing, avoid touching the face and so on. These measures are crucial as the human cost is going to be unthinkable even in the best-case scenarios that epidemiologists are modelling.

positive: Restarting after COVID-19: A Data-driven Evaluation of Opening Scenarios To contain the COVID-19 pandemic, several governments introduced strict Non-Pharmaceutical Interventions (NPI) that restricted movement, public gatherings, national and international travel, and shut down large parts of the economy. Yet, the impact of the enforcement and subsequent loosening of these policies on the spread of COVID-19 is not well understood. Accordingly, we measure the impact of NPI on mitigating disease spread by exploiting the spatio-temporal variations in policy measures across the 16 states of Germany. This quasi-experiment identifies each policy's effect on reducing disease spread. We adapt the SEIR (Susceptible-Exposed-Infected-Recovered) model for disease propagation to include data on daily confirmed cases, intra- and inter-state movement, and social distancing. By combining the model with measures of policy contributions on mobility reduction, we forecast scenarios for relaxing various types of NPIs. Our model finds that, in Germany, policies that mandated contact restrictions (e.g., movement in public space limited to two persons or people co-living), initial business closures (e.g., restaurant closures), stay-at-home orders (e.g., prohibition of non-essential trips), non-essential services (e.g., florists, museums) and retail outlet closures led to the sharpest drops in movement within and across states. Contact restrictions were the most effective at lowering infection rates, while border closures had only minimal effects at mitigating the spread of the disease, even though cross-border travel might have played a role in seeding the disease in the population. We believe that a deeper understanding of the policy effects on mitigating the spread of COVID-19 allows a more accurate forecast of the disease spread when NPIs are (partially) loosened, and thus also better informs policymakers towards making appropriate decisions.

positive: Are we #stayinghome to Flatten the Curve? The recent spread of COVID-19 across the U.S. led to concerted efforts by states to ``flatten the curve" through the adoption of stay-at-home mandates that encourage individuals to reduce travel and maintain social distance and indeed using data on travel activity we find that residents start reducing mobility early in most states. Combining data on changes in travel activity with COVID-19 health outcomes and variation in state policy adoption, we characterize the direct impact of stay-at-home mandates on mobility and social distancing and link these behavioral changes to health benefits. We find evidence of dramatic declines in mobility nationwide prior to the adoption of statewide mandates. Despite these early reductions, we find that statewide stay-at-home policies induced "mandate effects" of between 4.1 and 5.9 percentage point declines relative to pre-COVID-19 levels for the first four states to introduce such policies. These effects persist when considering all states' mandates and alternate estimation strategies that account for states' differences in travel behavior prior to policy adoption. Using previous changes in mobility, we find significant effects on current mortality, with 1% reductions in visits to non-essential businesses weeks prior being associated with 9.2 fewer deaths per 100 million per day, corresponding with over 74,000 lives saved nationwide and resulting economic benefits between $249-$745 billion for observed behavioral changes in March and April. Observed reductions in mobility indeed contribute to flattening the curve and reduce the strain on the medical system during those two months. Our findings provide evidence that statewide stay-at-home ordinances induce additional social distancing, and ultimately attenuate the negative health consequences of COVID-19, revealing themselves as important policy tools in the fight against pandemic. Further, substantial reductions in mobility prior to state-level policies convey important policy implications.

positive: Predictive Modeling on the Number of Covid-19 Death Toll in the United States Considering the Effects of Coronavirus-Related Changes and Covid-19 Recovered Cases COVID-19 is caused by a coronavirus called SARS-CoV-2. Many countries around the world implemented their own policies and restrictions designed to limit the spread of Covid-19 in recent months. Businesses and schools transitioned into working and learning remotely. In the United States, many states were under strict orders to stay home at least in the month of April. In recent weeks, there are some significant changes related restrictions include social-distancing, reopening states, and staying-at-home orders. The United States surpassed 2 million coronavirus cases on Monday, June 15, 2020 less than five months after the first case was confirmed in the country. The virus has killed at least 115,000 people in the United States as of Monday, June 15, 2020, according to data from Johns Hopkins University. With the recent easing of coronavirus-related restrictions and changes on business and social activity such as stay-at-home, social distancing since late May 2020 hoping to restore economic and business activities, new Covid-19 outbreaks are on the rise in many states across the country. Some researchers expressed concern that the process of easing restrictions and relaxing stay-at-home orders too soon could quickly surge the number of infected Covid-19 cases as well as the death toll in the United States. Some of these increases, however, could be due to more testing sites in the communities while others may be are the results of easing restrictions due to recent reopening and changed policies, though the number of daily death toll does not appear to be going down in recent days due to Covid-19 in the U.S. This raises the challenging question: * How can policy decision-makers and community leaders make the decision to implement public policies and restrictions and keep or lift staying-at-home orders of ongoing Covid-19 pandemic for their communities in a scientific way? In this study, we aim to develop models addressing the effects of recent Covid-19 related changes in the communities such as reopening states, practicing social-distancing, and staying-at-home orders. Our models account for the fact that changes to these policies which can lead to a surge of coronavius cases and deaths, especially in the United States. Specifically, in this paper we develop a novel generalized mathematical model and several explicit models considering the effects of recent reopening states, staying-at-home orders and social-distancing practice of different communities along with a set of selected indicators such as the total number of coronavirus recovered and new cases that can estimate the daily death toll and total number of deaths in the United States related to Covid-19 virus. We compare the modeling results among the developed models based on several existing criteria. The model also can be used to predict the number of death toll in Italy and the United Kingdom (UK). The results show very encouraging predictability for the proposed models in this study. The model predicts that 128,500 to 140,100 people in the United States will have died of Covid-19 by July 4, 2020. The model also predicts that between 137,900 and 154,000 people will have died of Covid-19 by July 31, and 148,500 to 169,700 will have died by the end of August 2020, as a result of the SARS-CoV-2 coronavirus that causes COVID-19 based on the Covid-19 death data available on June 13, 2020. The model also predicts that 34,900 to 37,200 people in Italy will have died of Covid-19 by July 4, and 36,900 to 40,400 people will have died by the end of August based on the data available on June 13, 2020. The model also predicts that between 43,500 and 46,700 people in the United Kingdom will have died of Covid-19 by July 4, and 48,700 to 51,900 people will have died by the end of August, as a result of the SARS-CoV-2 coronavirus that causes COVID-19 based on the data available on June 13, 2020. The model can serve as a framework to help policy makers a scientific approach in quantifying decision-makings related to Covid-19 affairs.

positive: Estimating unobserved SARS-CoV-2 infections in the United States By March 2020, COVID-19 led to thousands of deaths and disrupted economic activity worldwide. As a result of narrow case definitions and limited capacity for testing, the number of unobserved SARS-CoV-2 infections during its initial invasion of the US remains unknown. We developed an approach for estimating the number of unobserved infections based on data that are commonly available shortly after the emergence of a new infectious disease. The logic of our approach is, in essence, that there are bounds on the amount of exponential growth of new infections that can occur during the first few weeks after imported cases start appearing. Applying that logic to data on imported cases and local deaths in the US through March 12, we estimated that 22,876 (95% posterior predictive interval: 7,451 - 53,044) infections occurred in the US by this date. By comparing the model's predictions of symptomatic infections to local cases reported over time, we obtained daily estimates of the proportion of symptomatic infections detected by surveillance. This revealed that detection of symptomatic infections decreased throughout February as exponential growth of infections outpaced increases in testing. Between February 21 and March 12, we estimated an increase in detection of symptomatic infections, which was strongly correlated (median: 0.97, 95% PPI: 0.85 - 0.98) with increases in testing. These results suggest that testing was a major limiting factor in assessing the extent of SARS-CoV-2 transmission during its initial invasion of the US.

positive: The Effect of Stay-at-Home Orders on COVID-19 Infections in the United States Background In March and April 2020, public health authorities in the United States acted to mitigate transmission of and hospitalizations from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). These actions were not coordinated at the national level, which raises the question of what might have happened if they were. It also creates an opportunity to use spatial and temporal variation to measure their effect with greater accuracy. Methods We combine publicly available data sources on the timing of stay-at-home orders and daily confirmed COVID-19 cases at the county level in the United States (N = 132,048). We then derive from the classic SIR model a two-way fixed-effects model and apply it to the data with controls for unmeasured differences between counties and over time. This enables us to estimate the effect of stay-at-home orders while accounting for local variation in factors like health systems and demographics, and temporal variation in national mitigation actions, access to tests, or exposure to media reports that could influence the course of the disease. Findings Mean county-level daily growth in COVID-19 infections peaked at 17.2% just before stay-at-home orders were issued. Two way fixed-effects regression estimates suggest that orders were associated with a 3.8 percentage point (95% CI 0.7 to 8.6) reduction in the growth rate after one week and an 8.6 percentage point (3.0 to 14.1) reduction after two weeks. By day 22 the reduction (18.2 percentage points, 12.3 to 24.0) had surpassed the growth at the peak, indicating that growth had turned negative and the number of new daily infections was beginning to decline. A hypothetical national stay-at-home order issued on March 13, 2020 when a national emergency was declared might have reduced cumulative county infections by 62.3%, and might have helped to reverse exponential growth in the disease by April 5. Interpretation Although stay-at-home orders impose great costs to society, delayed responses and piecemeal application of these orders generate similar costs without obtaining the full potential benefits suggested by this analysis. The results here suggest that a coordinated nationwide stay-at-home order may have reduced by hundreds of thousands the current number of infections and by thousands the total number of deaths from COVID-19. Future efforts in the United States and elsewhere to control pandemics should coordinate stay-at-home orders at the national level, especially for diseases for which local spread has already occurred and testing availability is delayed. Since stay-at-home orders reduce infection growth rates, early implementation when infection counts are still low would be most beneficial.

positive: Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China This study models local and cross-city transmissions of the novel coronavirus in China between January 19 and February 29, 2020. We examine the role of various socioeconomic mediating factors, including public health measures that encourage social distancing in local communities. Weather characteristics 2 weeks prior are used as instrumental variables for causal inference. Stringent quarantines, city lockdowns, and local public health measures imposed in late January significantly decreased the virus transmission rate. The virus spread was contained by the middle of February. Population outflow from the outbreak source region posed a higher risk to the destination regions than other factors, including geographic proximity and similarity in economic conditions. We quantify the effects of different public health measures in reducing the number of infections through counterfactual analyses. Over 1.4 million infections and 56,000 deaths may have been avoided as a result of the national and provincial public health measures imposed in late January in China.

positive: Determining the optimal strategy for reopening schools, work and society in the UK: balancing earlier opening and the impact of test and trace strategies with the risk of occurrence of a secondary COVID-19 pandemic wave Background In order to slow down the spread of SARS-CoV-2, the virus causing the COVID-19 pandemic, the UK government has imposed strict physical distancing (lockdown) measures including school 'dismissals' since 23 March 2020. As evidence is emerging that these measures may have slowed the spread of the pandemic, it is important to assess the impact of any changes in strategy, including scenarios for school reopening and broader relaxation of social distancing. This work uses an individual-based model to predict the impact of a suite of possible strategies to reopen schools in the UK, including that currently proposed by the UK government. Methods We use Covasim, a stochastic agent-based model for transmission of COVID-19, calibrated to the UK epidemic. The model describes individuals' contact networks stratified as household, school, work and community layers, and uses demographic and epidemiological data from the UK. We simulate a range of different school reopening strategies with a society-wide relaxation of lockdown measures and in the presence of different non-pharmaceutical interventions, to estimate the number of new infections, cumulative cases and deaths, as well as the effective reproduction number with different strategies. To account for uncertainties within the stochastic simulation, we also simulated different levels of infectiousness of children and young adults under 20 years old compared to older ages. Findings We found that with increased levels of testing of people (between 25% and 72% of symptomatic people tested at some point during an active COVID-19 infection depending on scenarios) and effective contact-tracing and isolation for infected individuals, an epidemic rebound may be prevented across all reopening scenarios, with the effective reproduction number (R) remaining below one and the cumulative number of new infections and deaths significantly lower than they would be if testing did not increase. If UK schools reopen in phases from June 2020, prevention of a second wave would require testing 51% of symptomatic infections, tracing of 40% of their contacts, and isolation of symptomatic and diagnosed cases. However, without such measures, reopening of schools together with gradual relaxing of the lockdown measures are likely to induce a secondary pandemic wave, as are other scenarios for reopening. When infectiousness of <20 year olds was varied from 100% to 50% of that of older ages, our findings remained unchanged. Interpretation To prevent a secondary COVID-19 wave, relaxation of social distancing including reopening schools in the UK must be implemented alongside an active large-scale population-wide testing of symptomatic individuals and effective tracing of their contacts, followed by isolation of symptomatic and diagnosed individuals. Such combined measures have a greater likelihood of controlling the transmission of SARS-CoV-2 and preventing a large number of COVID-19 deaths than reopening schools and society with the current level of implementation of testing and isolation of infected individuals.

positive: Social distancing during the COVID-19 pandemic: Staying home save lives

positive: Epidemics on networks: Reducing disease transmission using health emergency declarations and peer communication Understanding individual decisions in a world where communications and information move instantly via cell phones and the internet, contributes to the development and implementation of policies aimed at stopping or ameliorating the spread of diseases. In this manuscript, the role of official social network perturbations generated by public health officials to slow down or stop a disease outbreak are studied over distinct classes of static social networks. The dynamics are stochastic in nature with individuals (nodes) being assigned fixed levels of education or wealth. Nodes may change their epidemiological status from susceptible, to infected and to recovered. Most importantly, it is assumed that when the prevalence reaches a pre-determined threshold level, [Formula: see text] , information, called awareness in our framework, starts to spread, a process triggered by public health authorities. Information is assumed to spread over the same static network and whether or not one becomes a temporary informer, is a function of his/her level of education or wealth and epidemiological status. Stochastic simulations show that threshold selection [Formula: see text] and the value of the average basic reproduction number impact the final epidemic size differentially. For the Erdős-Rényi and Small-world networks, an optimal choice for [Formula: see text] that minimize the final epidemic size can be identified under some conditions while for Scale-free networks this is not case.

positive: The effect of social distance measures on COVID-19 epidemics in Europe: an interrupted time series analysis Following the introduction of unprecedented "stay-at-home" national policies, the COVID-19 pandemic recently started declining in Europe. Our research aims were to characterize the changepoint in the flow of the COVID-19 epidemic in each European country and to evaluate the association of the level of social distancing with the observed decline in the national epidemics. Interrupted time series analyses were conducted in 28 European countries. Social distance index was calculated based on Google Community Mobility Reports. Changepoints were estimated by threshold regression, national findings were analyzed by Poisson regression, and the effect of social distancing in mixed effects Poisson regression model. Our findings identified the most probable changepoints in 28 European countries. Before changepoint, incidence of new COVID-19 cases grew by 24% per day on average. From the changepoint, this growth rate was reduced to 0.9%, 0.3% increase, and to 0.7% and 1.7% decrease by increasing social distancing quartiles. The beneficial effect of higher social distance quartiles (i.e., turning the increase into decline) was statistically significant for the fourth quartile. Notably, many countries in lower quartiles also achieved a flat epidemic curve. In these countries, other plausible COVID-19 containment measures could contribute to controlling the first wave of the disease. The association of social distance quartiles with viral spread could also be hindered by local bottlenecks in infection control. Our results allow for moderate optimism related to the gradual lifting of social distance measures in the general population, and call for specific attention to the protection of focal micro-societies enriching high-risk elderly subjects, including nursing homes and chronic care facilities.

positive: Impact of school closures for COVID-19 on the US health-care workforce and net mortality: a modelling study BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is leading to social (physical) distancing policies worldwide, including in the USA. Some of the first actions taken by governments are the closing of schools. The evidence that mandatory school closures reduce the number of cases and, ultimately, mortality comes from experience with influenza or from models that do not include the effect of school closure on the health-care labour force. The potential benefits from school closures need to be weighed against costs of health-care worker absenteeism associated with additional child-care obligations. In this study, we aimed to measure child-care obligations for US health-care workers arising from school closures when these are used as a social distancing measure. We then assessed how important the contribution of health-care workers would have to be in reducing mortality for their absenteeism due to child-care obligations to undo the benefits of school closures in reducing the number of cases. METHODS: For this modelling analysis, we used data from the monthly releases of the US Current Population Survey to characterise the family structure and probable within-household child-care options of US health-care workers. We accounted for the occupation within the health-care sector, state, and household structure to identify the segments of the health-care workforce that are most exposed to child-care obligations from school closures. We used these estimates to identify the critical level at which the importance of health-care labour supply in increasing the survival probability of a patient with COVID-19 would undo the benefits of school closures and ultimately increase cumulative mortality. FINDINGS: Between January, 2018, and January, 2020, the US Current Population Survey included information on more than 3·1 million individuals across 1·3 million households. We found that the US health-care sector has some of the highest child-care obligations in the USA, with 28·8% (95% CI 28·5–29·1) of the health-care workforce needing to provide care for children aged 3–12 years. Assuming non-working adults or a sibling aged 13 years or older can provide child care, 15·0% (14·8–15·2) of the health-care workforce would still be in need of child care during a school closure. We observed substantial variation within the health-care system. We estimated that, combined with reasonable parameters for COVID-19 such as a 15·0% case reduction from school closings and 2·0% baseline mortality rate, a 15·0% decrease in the health-care labour force would need to decrease the survival probability per percent health-care worker lost by 17·6% for a school closure to increase cumulative mortality. Our model estimates that if the infection mortality rate of COVID-19 increases from 2·00% to 2·35% when the health-care workforce declines by 15·0%, school closures could lead to a greater number of deaths than they prevent. INTERPRETATION: School closures come with many trade-offs, and can create unintended child-care obligations. Our results suggest that the potential contagion prevention from school closures needs to be carefully weighted with the potential loss of health-care workers from the standpoint of reducing cumulative mortality due to COVID-19, in the absence of mitigating measures. FUNDING: None.

positive: Mathematical modeling of COVID-19 containment strategies with considerations for limited medical resources The outbreak of SARS-CoV-2 in China has spread around the world, infecting millions and causing governments to implement strict policies to counteract the spread of the disease. One of the most effective strategies in reducing the severity of the pandemic is social distancing, where members of the population systematically reduce their interactions with others to limit the transmission rate of the virus. However, the implementation of social distancing can be difficult and costly, making it imperative that both policy makers and the citizenry understand the potential benefits if done correctly and the risks if not. In this work, a mathematical model is developed to study the effects of social distancing on the spread of the SARS-CoV-2 virus in Canada. The model is based upon a standard epidemiological SEIRD model that has been stratified to directly incorporate the proportion of individuals who are following social distancing protocols. The model parameters characterizing the disease are estimated from current epidemiological data on COVID-19 using machine learning techniques. The results of the model show that social distancing policies in Canada have already saved thousands of lives and that the prolonged adherence to social distancing guidelines could save thousands more. Importantly, our model indicates that social distancing can significantly delay the onset of infection peaks, allowing more time for the production of a vaccine or additional medical resources. Furthermore, our results stress the importance of easing social distancing restrictions gradually, rather than all at once, in order to prevent a second wave of infections. Model results are compared to the current capacity of the Canadian healthcare system by examining the current and future number of ventilators available for use, emphasizing the need for the increased production of additional medical resources.

positive: Early transmission dynamics of COVID-19 in a southern hemisphere setting: Lima-Peru: February 29th–March 30th, 2020. The COVID-19 pandemic that emerged in Wuhan China has generated substantial morbidity and mortality impact around the world during the last four months. The daily trend in reported cases has been rapidly rising in Latin America since March 2020 with the great majority of the cases reported in Brazil followed by Peru as of April 15th, 2020. Although Peru implemented a range of social distancing measures soon after the confirmation of its first case on March 6th, 2020, the daily number of new COVID-19 cases continues to accumulate in this country. We assessed the early COVID-19 transmission dynamics and the effect of social distancing interventions in Lima, Peru. We estimated the reproduction number, R, during the early transmission phase in Lima from the daily series of imported and autochthonous cases by the date of symptoms onset as of March 30th, 2020. We also assessed the effect of social distancing interventions in Lima by generating short-term forecasts grounded on the early transmission dynamics before interventions were put in place. Prior to the implementation of the social distancing measures in Lima, the local incidence curve by the date of symptoms onset displays near exponential growth dynamics with the mean scaling of growth parameter, p, estimated at 0.9 (95%CI: 0.9,1.0) and the reproduction number at 2.3 (95% CI: 2.0, 2.5). Our analysis indicates that school closures and other social distancing interventions have helped slow down the spread of the novel coronavirus, with the nearly exponential growth trend shifting to an approximately linear growth trend soon after the broad scale social distancing interventions were put in place by the government. While the interventions appear to have slowed the transmission rate in Lima, the number of new COVID-19 cases continue to accumulate, highlighting the need to strengthen social distancing and active case finding efforts to mitigate disease transmission in the region.

positive: Forecasting the Worldwide Spread of COVID-19 based on Logistic Model and SEIR Model Background: With the outbreak of coronavirus disease 2019 (COVID-19), a sudden case increase in late February 2020 led to deep concern globally. Italy, South Korea, Iran, France, Germany, Spain, the US and Japan are probably the countries with the most severe outbreaks. Collecting epidemiological data and predicting epidemic trends are important for the development and measurement of public intervention strategies. Epidemic prediction results yielded by different mathematical models are inconsistent; therefore, we sought to compare different models and their prediction results to generate objective conclusions. Methods: We used the number of cases reported from January 23 to March 20, 2020, to estimate the possible spread size and peak time of COVID-19, especially in 8 high-risk countries. The logistic growth model, basic SEIR model and adjusted SEIR model were adopted for prediction. Given that different model inputs may infer different model outputs, we implemented three model predictions with three scenarios of epidemic development. Results: When comparing all 8 countries short-term prediction results and peak predictions, the differences among the models were relatively large. The logistic growth model estimated a smaller epidemic size than the basic SERI model did; however, once we added parameters that considered the effects of public health interventions and control measures, the adjusted SERI model results demonstrated a considerably rapid deceleration of epidemic development. Our results demonstrated that contact rate, quarantine scale, and the initial quarantine time and length are important factors in controlling epidemic size and length. Conclusions: We demonstrated a comparative assessment of the predictions of the COVID-19 outbreak in eight high-risk countries using multiple methods. By forecasting epidemic size and peak time as well as simulating the effects of public health interventions, the intent of this paper is to help clarify the transmission dynamics of COVID-19 and recommend operation suggestions to slow down the epidemic. It is suggested that the quick detection of cases, sufficient implementation of quarantine and public self-protection behaviors are critical to slow down the epidemic.

positive: Prediction of the Peak, Effect of Intervention and Total Infected by the Coronavirus Disease in India We study the effect of the coronavirus disease 2019 (COVID-19) in India using the SEIR compartmental model. After it's outbreak in Wuhan, China, it has been imported to India which is a densely populated country. India is fighting against this disease by ensuring nationwide social distancing. We estimate the infection rate to be 0.258 using a least square method with Poisson noise and estimate the reproduction number to be 2.58. We approximate the peak of the epidemic to be August 11, 2020. We estimate that a 25% drop in infection rate will delay the peak by 38 days for a 1 month intervention period. We estimate that the total individuals infected in India will be approximately 9% of the total population.

positive: Controlling epidemic spread by social distancing: Do it well or not at all BACKGROUND: Existing epidemiological models have largely tended to neglect the impact of individual behaviour on the dynamics of diseases. However, awareness of the presence of illness can cause people to change their behaviour by, for example, staying at home and avoiding social contacts. Such changes can be used to control epidemics but they exact an economic cost. Our aim is to study the costs and benefits of using individual-based social distancing undertaken by healthy individuals as a form of control. METHODS: Our model is a standard SIR model superimposed on a spatial network, without and with addition of small-world interactions. Disease spread is controlled by allowing susceptible individuals to temporarily reduce their social contacts in response to the presence of infection within their local neighbourhood. We ascribe an economic cost to the loss of social contacts, and weigh this against the economic benefit gained by reducing the impact of the epidemic. We study the sensitivity of the results to two key parameters, the individuals’ attitude to risk and the size of the awareness neighbourhood. RESULTS: Depending on the characteristics of the epidemic and on the relative economic importance of making contacts versus avoiding infection, the optimal control is one of two extremes: either to adopt a highly cautious control, thereby suppressing the epidemic quickly by drastically reducing contacts as soon as disease is detected; or else to forego control and allow the epidemic to run its course. The worst outcome arises when control is attempted, but not cautiously enough to cause the epidemic to be suppressed. The next main result comes from comparing the size of the neighbourhood of which individuals are aware to that of the neighbourhood within which transmission can occur. The control works best when these sizes match and is particularly ineffective when the awareness neighbourhood is smaller than the infection neighbourhood. The results are robust with respect to inclusion of long-range, small-world links which destroy the spatial structure, regardless of whether individuals can or cannot control them. However, addition of many non-local links eventually makes control ineffective. CONCLUSIONS: These results have implications for the design of control strategies using social distancing: a control that is too weak or based upon inaccurate knowledge, may give a worse outcome than doing nothing.

positive: Temporal rise in the proportion of both younger adults and older adolescents among COVID-19 cases in Germany: evidence of lesser adherence to social distancing practices? BACKGROUND: There is uncertainty about the role of different age groups in propagating the SARS-CoV-2 epidemics in different countries, particularly under current social distancing practices. METHODS: We used the Robert Koch Institute data on weekly COVID-19 cases in different age groups in Germany. To minimize the effect of changes in healthcare seeking behavior (e.g. for older adults) and testing practices, we included the following eight 5-year age groups in the analyses: 10–14y through 45–49y. For each age group g, we considered the proportion PL(g) of individuals in age group g among all detected cases aged 10–49y during weeks 13–14, 2020 (later period), as well as corresponding proportion PE(g) for weeks 10–11, 2020 (early period), and defined the relative risk RR(g) for the age group g to be the ratio RR(g) = PL(g)/PE(g). For each pair of age groups g1, g2, a higher value of RR(g1) compared to RR(g2), or, alternatively, a value above 1 for the odds ratio OR(g1, g2) = RR(g1)/RR(g2) for a COVID-19 case to be in group g1 vs. g2 for the later vs. early periods is interpreted as the relative increase in the population incidence of SARS-Cov-2 in the age group g1 compared to g2 for the later vs. early period. RESULTS: The relative risk RR(g) was highest for individuals aged 20–24y (RR=1.4(95% CI (1.27,1.55))), followed by individuals aged 15–19y (RR=1.14(0.99,1.32)), aged 30–34y (RR=1.07(0.99,1.16)), aged 25–29y (RR= 1.06(0.98,1.15)), aged 35–39y (RR=0.95(0.87,1.03)), aged 40–44y (RR=0.9(0.83,0.98)), aged 45–49y (RR=0.83(0.77,0.89)) and aged 10–14y (RR=0.78(0.64,0.95)). For the age group 20–24y, the odds ratio relative to any other age group for a case to be during the later vs. early period was significantly above 1. For the age group 15–19y, the odds ratio relative to any other age group either above 35y or 10–14y for a case to be during the later vs. early period was significantly above 1. CONCLUSIONS: The observed relative increase with time in the prevalence of individuals aged 15–34y (particularly those aged 20–24y) among detected COVID-19 cases in Germany is unlikely to be explained by increases in the likelihood of seeking medical care or the likelihood of being tested for individuals in those age groups compared to individuals aged 35–49y or 10–14y, and should be indicative of the actual increase in the prevalence of individuals aged 15–34y among SARS-CoV-2 infections in the German population. That increase likely reflects elevated mixing among individuals aged 15–34y (particularly those aged 20–24y) compared to other age groups, possibly due to lesser adherence to social distancing practices.

positive: Assessing the effect of global travel and contact reductions to mitigate the COVID-19 pandemic and resurgence Travel and physical distancing interventions have been implemented across the World to mitigate the COVID-19 pandemic, but studies are needed to quantify the effectiveness of these measures across regions and time. Timely population mobility data were obtained to measure travel and contact reductions in 135 countries or territories. During the 10 weeks of March 22 - May 30, 2020, domestic travel in study regions has dramatically reduced to a median of 59% (interquartile range [IQR] 43% - 73%) of normal levels seen before the outbreak, with international travel down to 26% (IQR 12% - 35%). If these travel and physical distancing interventions had not been deployed across the World, the cumulative number of cases might have shown a 97-fold (IQR 79 - 116) increase, as of May 31, 2020. However, effectiveness differed by the duration and intensity of interventions and relaxation scenarios, with variations in case severity seen across populations, regions, and seasons.

positive: Short-term Forecasts of the COVID-19 Epidemic in Guangdong and Zhejiang, China: February 13–23, 2020 The ongoing COVID-19 epidemic continues to spread within and outside of China, despite several social distancing measures implemented by the Chinese government. Limited epidemiological data are available, and recent changes in case definition and reporting further complicate our understanding of the impact of the epidemic, particularly in the epidemic’s epicenter. Here we use previously validated phenomenological models to generate short-term forecasts of cumulative reported cases in Guangdong and Zhejiang, China. Using daily reported cumulative case data up until 13 February 2020 from the National Health Commission of China, we report 5- and 10-day ahead forecasts of cumulative case reports. Specifically, we generate forecasts using a generalized logistic growth model, the Richards growth model, and a sub-epidemic wave model, which have each been previously used to forecast outbreaks due to different infectious diseases. Forecasts from each of the models suggest the outbreaks may be nearing extinction in both Guangdong and Zhejiang; however, the sub-epidemic model predictions also include the potential for further sustained transmission, particularly in Zhejiang. Our 10-day forecasts across the three models predict an additional 65–81 cases (upper bounds: 169–507) in Guangdong and an additional 44–354 (upper bounds: 141–875) cases in Zhejiang by February 23, 2020. In the best-case scenario, current data suggest that transmission in both provinces is slowing down.

positive: Model of a Testing-and-Quarantine Strategy to Slow-Down the COVID-19 Outbreak in Guadeloupe Using a stochastic epidemic model explicitly considering the entire population of Guadeloupe (1), we explore the domain of solutions presenting an efficient slowing down of the COVID-19 epidemic spread during the post-containment period. The considered model parameters are the basic reproduction number R0 to simulate the effects of social distancing, the time delay {delta}TQ elapsed between the detection of a symptomatic person and her/his placement in quarantine to suppress her/his contagiousness, and the number Na of asymptomatic people tested positively and isolated. We show that acceptable solutions are obtained for a wide range of parameter values. Thanks to a good control of the initial epidemic spread resulting from an early containment and efficient communication by the sanitary and administrative authorities, the present situation corresponds to a pre-epidemic state. The most safe solutions are a combinations of social distancing, numerous testing to perform a systematic isolation of symptomatic patients and guided detection of asymptomatic people in the entourage of localised symptomatic patients.

positive: Quantifying Projected Impact of Social Distancing Policies on COVID-19 Outcomes in the US Current social distancing measures to impede COVID-19 (such as shelter-in-place) are economically unsustainable in the long term. Models are needed to understand the implications of possible relaxation options for these measures. We report such models, together with corresponding parameter estimation techniques and prediction outcomes, borrowing insights from another domain; namely, information cascades. Our models assume that the containment of the virus into isolated locales is no longer possible. Instead, we explore options that reduce the rate of spread. We predict COVID-19 contagion trends in different geographic regions under a"what if"scenario to understand the effects of potential policy decisions on regional trends. Our model allows experimentation with other policies that, we hope, can contribute to socially viable outcomes both in terms of health system capacity and economic impact. We apply our model to over 30 highly impacted states in the US and publish the results at https://covid19predictions.csl.illinois.edu/

positive: COVID-19 and social distancing AIM: COVID-19 has spread rapidly worldwide since it began, greatly affecting peoples' lives, social economies and medical systems. At present, little is known about the disease, and vaccines are still under development. Therefore, in the face of severe outbreaks, previous effective experience can help people better protect themselves and their families. The aim of this article is to discuss the social distancing measures for COVID-19. SUBJECTS AND METHODS: Literature and document search. RESULTS: Recent research and a novel coronavirus pneumonia prediction model revealed social distancing measures and wearing masks are required to mitigate hospital system overload and prevent pathogen exposure. After a series of social distancing measures, there are 309 cities with zero cases and 34 cities with confirmed cases in China as of April 13, 2020. CONCLUSION: From China's experience with novel coronavirus pneumonia, we know that social distancing is the most effective measure at present. We need to win more time to allow limited medical resources to save lives.

positive: Transmission dynamics of the COVID-19 epidemic in India, and evaluating the impact of asymptomatic carriers and role of expanded testing in the lockdown exit strategy: a modelling approach Background: The coronavirus disease 2019 (COVID-19) has caused over 3 200 000 cases and 230 000 deaths as on 2 May 2020, and has quickly become an unprecedented global health threat. India, with its unique challenges in fighting this pandemic, imposed one of the worlds strictest and largest population-wide lockdown on 25 March 2020. Here, we estimated key epidemiological parameters and evaluated the effect of control measures on the COVID-19 epidemic in India and its states. Through a modeling approach that accounted for asymptomatics, we assessed the impact of lockdown relaxation and increased testing. Methods: We estimated the basic reproduction number and effective reproduction number at a national and state level in India after adjusting for imported cases and reporting lag using established statistical methods, using time-series data from 4 March to 25 April 2020. Using a dynamic SEIR-QDPA model fitted to data from India, we forecasted the size and temporality of the ongoing first wave while accounting for the interventions in place. We used the model to simulate lockdown relaxation under various scenarios to evaluate its effect on the size and temporality of the second wave. We also evaluated the feasibility of increased testing as a containment strategy after restrictions are relaxed and its impact on the epidemic size and resumption of socio-economic activities, while taking into account the changes in transmission dynamics brought about by asymptomatic carriers. Findings: The median delay from symptom onset to detection (reporting lag) was estimated to be 2{middle dot}68 days (95% CI 2{middle dot}00-3{middle dot}00) with an IQR of 2{middle dot}03 days (95% CI 1{middle dot}00-3{middle dot}00). The R0 for India was estimated to be 2{middle dot}083 (95% CI 2{middle dot}044-2{middle dot}122 ; R2 = 0{middle dot}972), while the Rt gradually down trended from 1{middle dot}665 (95%CI 1{middle dot}539-1{middle dot}789) on 30 March to 1{middle dot}159 (95% CI 1{middle dot}128-1{middle dot}189) on 21 April. 60{middle dot}7% of confirmed COVID-19 cases in our sample were found to be asymptomatic. We observed that delaying the lockdown relaxation increases the time to new rise in active cases after the relaxation in a linear fashion. If lockdown was reintroduced after a fixed relaxation period, the magnitude of the second peak could be reduced by delaying the relaxation and decreasing the duration of relaxation. These benefits were greater in case of a gradual relaxation as compared to a sudden lifting of lockdown. We found that detecting a higher proportion of cases through testing significantly decreases the total infections. This positive impact of testing progressively increased at higher transmission rates when restrictions were relaxed. We found that similar containment targets could be achieved by both, a combination of high testing and less social restrictions, and a combination of lower testing with intensive social distancing. Interpretation: The nationwide social distancing interventions in India since 25 March have reduced the effective transmission levels, though sub-threshold Rt remains to be achieved. If lockdown is to be extended, additional benefits for mitigating the second wave can be achieved if it is extended farther after the peak of active cases has passed. Intensive social distancing is inherently enough to contain the epidemic, however, testing will play a pivotal role in the lockdown exit strategy by impeding the epidemic growth enough to allow for a greater resumption of socio-economic activities, thus minimizing the social and economic fallout resulting from severe restrictions. Considering that asymptomatics play an undeniable role in the transmission of COVID-19, dependence on presence of symptoms for control strategies, behavioural changes and testing should be reduced.

positive: SIRNet: Understanding Social Distancing Measures with Hybrid Neural Network Model for COVID-19 Infectious Spread The SARS-CoV-2 infectious outbreak has rapidly spread across the globe and precipitated varying policies to effectuate physical distancing to ameliorate its impact. In this study, we propose a new hybrid machine learning model, SIRNet, for forecasting the spread of the COVID-19 pandemic that couples with the epidemiological models. We use categorized spatiotemporally explicit cellphone mobility data as surrogate markers for physical distancing, along with population weighted density and other local data points. We demonstrate at varying geographical granularity that the spectrum of physical distancing options currently being discussed among policy leaders have epidemiologically significant differences in consequences, ranging from viral extinction to near complete population prevalence. The current mobility inflection points vary across geographical regions. Experimental results from SIRNet establish preliminary bounds on such localized mobility that asymptotically induce containment. The model can support in studying non-pharmacological interventions and approaches that minimize societal collateral damage and control mechanisms for an extended period of time.

positive: World governments should protect their population from COVID-19 pandemic using Italy and Lombardy as precursor The COVID-19 pandemic is spreading worldwide. Italy emerged early on as the country with the largest outbreak outside Asia. The outbreak in Northern Italy demonstrates that it is fundamental to contain the virus' spread at a very early stage of diffusion. At later stages, no containment measure, even if strict, can prevent the saturation of the hospitals and of the intensive care units in any country. Here we show that it is possible to predict when the intensive care units will saturate, within a few days from the first cases of COVID-19 intensive care patients. Using early counts of intensive care patients, we predict the saturation for Lombardy, Italy. Governments should use the Italian precursor to control the outbreak of COVID-19 and prevent the saturation of their intensive care units to protect their population.

positive: Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world Social distancing and isolation have been widely introduced to counter the COVID-19 pandemic. Adverse social, psychological and economic consequences of a complete or near-complete lockdown demand the development of more moderate contact-reduction policies. Adopting a social network approach, we evaluate the effectiveness of three distancing strategies designed to keep the curve flat and aid compliance in a post-lockdown world. These are: limiting interaction to a few repeated contacts akin to forming social bubbles; seeking similarity across contacts; and strengthening communities via triadic strategies. We simulate stochastic infection curves incorporating core elements from infection models, ideal-type social network models and statistical relational event models. We demonstrate that a strategic social network-based reduction of contact strongly enhances the effectiveness of social distancing measures while keeping risks lower. We provide scientific evidence for effective social distancing that can be applied in public health messaging and that can mitigate negative consequences of social isolation.

positive: Impacts of Early Interventions on the Age-Specific Incidence of COVID-19 in New York, Los Angeles, Daegu and Nairobi Background COVID-19 has caused an unprecedented public health crisis and economic shock to the global economy. While many countries were affected, regions with an older population and weaker public health interventions tended to suffer more morbidity and mortality. Here we model and quantify the age-specific incidence of COVID-19 in four pandemic cities under different interventions. Methods We developed an age-specific and multiple-stage susceptible-exposed-infected-recovered-hospitalized-quarantined-dead (SEIR-HQD) dynamical systems model expanded from the more basic SEIR model by incorporating location- and age-specific contact matrices to estimate the outcomes of COVID-19. Utilizing latest estimates of epidemiological parameters and demographic data, we model the potential effects of various interventions in four representative cities with different population structures - New York, Los Angeles, Daegu and Nairobi. We compared the effects of different interventions in the age-structure populations specific to each city. These policy options are then applied to determine the potential for effective containment. We model these dynamic policy scenarios to assess the risks of less-stringent social distancing, as has been proposed by those arguing to enhance economic activity over public health and safety. Finally, we explored the health impacts of different policy action timelines to understand the benefits of early interventions. Findings We find the spread of COVID-19 to be dramatically different in the regions modeled, with the primary drivers the variation of population age structures, and the dynamics of interactions of the younger demographics, whose higher interaction rates can lead to increasing transmission rates across these communities. A city with younger citizens may also have fewer hospitalized cases and deaths. Our modeling quantifies the value of early interventions, which avoided an additional 5%, 16%, 37% and 43% of the infections in Daegu, Nairobi, New York and Los Angeles, respectively, compared to what has been observed in the four cities. The finding is clear: in the absence of pharmaceutical options, delaying strict social policy interventions has resulted in substantial public health cost. This modeling can, and will, be applied to other cities and regions, and conducted in conjunction with other health insults, such as exposure to air pollution. Critically, we find that school closures, working from home, and reduction in other mobility were most beneficial for younger population (0-19 years old), middle-age (20-59 years old) population and older population (60 years and older), respectively across each city. Specifically, school closure avoided 25%, 18%, 16% and 12% of the infections for the population under 20 years old in Daegu, Los Angeles, New York and Nairobi, respectively. A 50% and 80% population working from home policy avoids 8% and 15% of the infections. Reduction in mobility was more effective than the working from home strategy. Any single social distancing policy if enacted alone can delay the spread of COVID-19 but was unable to totally suppress the infection. Coordinated policy action can be highly effective. Increasing the quarantine rate to 10% of infectious cases was more effective than strict social distancing alone in this study, although together they can suppress 80% of the epidemic. A combination of moderate social distancing and quarantine strategies was able to avoid 99% of the infections. Interpretation Moderate social distancing together with high quarantine rates was effective in each of the four cities. COVID-19 caused more deaths and hospitalization in cities with an ageing population than those with a younger population. However, in the cities with a younger population, there is a clear need to implement a social distancing strategy that is even more strict due to the higher transmission rates among younger people. Cities with more older people should prepare more hospital beds and healthcare facilities to save people who are in critical conditions. Cities with ageing population should take targeted action for the elderly to avoid the severe impacts on the vulnerable populations. Increasing quarantine rate is an effective strategy to avoid the substantial infection while also does not influence the economy fiercely. We recommend countries or regions experiencing, or likely to experience the rapid spread of COVID-19, to implement combination of multiple strategies in the early stage of the breakout which can avoid over 90% of infected cases.

positive: How to evaluate the success of the COVID-19 measures implemented by the Norwegian government by analyzing changes in doubling time Doubling Time (DT) is typically calculated for growth curves that show exponential growth, such as the cumulative number of COVID-19 cases day by day. DT represents the time it takes before the number of COVID-19 cases, in a certain country or area, doubles. Throughout the ongoing COVID-19 outbreak, DT values are continually changing. These changes are influenced by the measures that are recommended by the health authorities and implemented by governments. After the governmental shutdowns of Nordic Countries that were announced around the 12th of March 2020, I followed the development of the DT in the region. Governments put in place measure never before experienced during peace time; home working, closed schools and kindergartens, travel bans and social distancing. But does it work? The initial set of results following the shutdown are encouraging, demonstrating a trend towards slower growth; however, this could be reversed if the measures that are in place now are abandoned too early. Premature optimism can be very costly. This paper explains how to monitor growth in real time and evaluate whether the implemented measures are successful.

positive: D(2)EA: Depict the Epidemic Picture of COVID-19 The outbreak of coronavirus disease 2019 (COVID-19) has aroused a global alert. To release social panic and guide future schedules, this article proposes a novel mathematical model, the Delay Differential Epidemic Analyzer (D(2)EA), to analyze the dynamics of epidemic and forecast its future trends. Based on the traditional Susceptible-Exposed-Infectious-Recovered (SEIR) model, the D(2)EA model innovatively introduces a set of quarantine states and applies both ordinary differential equations and delay differential equations to describe the transition between two states. Potential variations of practical factors are further considered to reveal the true epidemic picture. In the experiment part, we use the D(2)EA model to simulate the epidemic in Hubei Province. Fitting to the collected real data as non-linear optimization, the D(2)EA model forecasts that the accumulated confirmed infected cases in Hubei Province will reach the peak at the end of February and then steady down. We also evaluate the effectiveness of the quarantine measures and schedule the date to reopen Hubei Province.

positive: COVID-19 epidemic in Malaysia: Impact of lock-down on infection dynamics COVID-19 epidemic in Malaysia started as a small wave of 22 cases in January 2020 through imported cases. It was followed by a bigger wave mainly from local transmissions resulting in 651 cases. The following wave saw unexpectedly three digit number of daily cases following a mass gathering urged the government to choose a more stringent measure. A limited lock-down approach called Movement Control Order (MCO) was immediately initiated to the whole country as a way to suppress the epidemic trajectory. The lock-down causes a major socio-economic disruption thus the ability to forecast the infection dynamic is urgently required to assist the government on timely decisions. Limited testing capacity and limited epidemiological data complicate the understanding of the future infection dynamic of the COVID-19 epidemic. Three different epidemic forecasting models was used to generate forecasts of COVID-19 cases in Malaysia using daily reported cumulative case data up until 1st April 2020 from the Malaysia Ministry of Health. The forecasts were generated using a Curve Fitting Model with Probability Density Function and Skewness Effect, the SIR Model, and a System Dynamic Model. Method one based on curve fitting with probability density function estimated that the peak will be on 19th April 2020 with an estimation of 5,637 infected persons. Method two based on SIR Model estimated that the peak will be on 20th - 31st May 2020 if Movement Contro (MCO) is in place with an estimation of 630,000 to 800,000 infected persons. Method three based on System Dynamic Model estimated that the peak will be on 17th May 2020 with an estimation of 22,421 infected persons. Forecasts from each of model suggested the epidemic may peak between middle of April to end of May 2020. Keywords: COVID-19, Infection dynamic, Prediction Modeling, SIR, System Learning, Lock-down

positive: Business disruptions from social distancing Social distancing interventions can be effective against epidemics but are potentially detrimental for the economy. Businesses that rely heavily on face-to-face communication or close physical proximity when producing a product or providing a service are particularly vulnerable. There is, however, no systematic evidence about the role of human interactions across different lines of business and about which will be the most limited by social distancing. Here we provide theory-based measures of the reliance of U.S. businesses on human interaction, detailed by industry and geographic location. We find that 49 million workers work in occupations that rely heavily on face-to-face communication or require close physical proximity to other workers. Our model suggests that when businesses are forced to reduce worker contacts by half, they need a 12 percent wage subsidy to compensate for the disruption in communication. Retail, hotels and restaurants, arts and entertainment and schools are the most affected sectors. Our results can help target fiscal assistance to businesses that are most disrupted by social distancing.

positive: Isolation and contact tracing can tip the scale to containment of COVID-19 in populations with social distancing Background: Novel coronavirus (SARS-CoV-2) has extended its range of transmission in all parts of the world, with substantial variation in rates of transmission and severity of associated disease. Many countries have implemented social distancing as a measure to control further spread. Methods: We evaluate whether and under which conditions containment or slowing down COVID-19 epidemics are possible by isolation and contact tracing in settings with various levels of social distancing. We use a stochastic transmission model in which every person generates novel infections according to a probability distribution that is affected by the incubation period distribution (time from infection to symptoms), distribution of the latent period (time from infection to onset of infectiousness), and overall transmissibility. The model distinguishes between close contacts (e.g., within a household) and other contacts in the population. Social distancing affects the number of contacts outside but not within the household. Findings: The proportion of asymptomatic or unascertained cases has a strong impact on the controllability of the disease. If the proportion of asymptomatic infections is larger than 30%, contact tracing and isolation cannot achieve containment for an R0 of 2.5. Achieving containment by social distancing requires a reduction of numbers of non-household contacts by around 90%. Depending on the realized level of contact reduction, tracing and isolation of only household contacts, or of household and non-household contacts are necessary to reduce the effective reproduction number to below 1. A combination of social distancing with isolation and contact tracing leads to synergistic effects that increase the prospect of containment. Interpretation: Isolation and contact tracing can be an effective means to slow down epidemics, but only if the majority of cases are ascertained. In a situation with social distancing, contact tracing can act synergistically and tip the scale towards containment, and can therefore be a tool for controlling COVID-19 epidemics as part of an exit strategy from current lockdown measures.

positive: Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus A novel Coronavirus pandemic emerged in December of 2019, causing devastating public health impact across the world. In the absence of a safe and effective vaccine or antiviral, strategies for mitigating the burden of the pandemic are focused on non-pharmaceutical interventions, such as social-distancing, contact-tracing, quarantine, isolation and the use of face-masks in public. We develop a new mathematical model for assessing the population-level impact of these mitigation strategies. Simulations of the model, using data relevant to COVID-19 transmission in New York state and the entire US, show that the pandemic will peak in mid and late April, respectively. The worst-case scenario projections for cumulative mortality (based on the baseline levels of anti-COVID non-pharmaceutical interventions considered in the study) in New York State and the entire US decrease dramatically by 80% and 64%, respectively, if the strict social-distancing measures implemented are maintained until the end of May or June, 2020. This study shows that early termination of strict social-distancing could trigger a devastating second wave with burden similar to that projected before the onset of strict social-distance. The use of efficacious face-masks (efficacy greater than 70%) could lead to the elimination of the pandemic if at least 70% of the residents of New York state use such masks consistently (nationwide, a compliance of at least 80% will be required using such masks). The use of low efficacy masks, such as cloth masks (of efficacy less than 30%), could also lead to significant reduction of COVID-19 burden (albeit, they are not able to lead to elimination). Combining low efficacy masks with improved levels of other anti-COVID-19 intervention measures can lead to elimination of the pandemic. The mask coverage needed to eliminate COVID-19 decreases if mask-use is combined with strict social-distancing.

positive: COVID-19 control in China during mass population movements at New Year

positive: COVID19 - The need for Public Health in a time of emergency

positive: Predicting the impact of asymptomatic transmission, non-pharmaceutical intervention and testing on the spread of COVID19 COVID19 We introduce a novel mathematical model to analyze the effect of removing non-pharmaceutical interventions on the spread of COVID19 as a function of disease testing rate. We find that relaxing interventions has a strong impact on the size of the epidemic peak as a function of intervention re- moval time. We show that it is essential for predictive models to explicitly capture transmission from asymptomatic carriers and important to obtain precise information on asymptomatic transmission by testing. The asymptomatic reservoir, reported to account for as much as 85% of transmission, will contribute to resurgence of the epidemic if public health interventions are removed too soon. Use of more basic models that fail to capture asymptomatic transmission can result in large errors in predicted clinical caseload or in fitted epidemiological parameters and, therefore, may be unreliable in estimating the risk of a second wave based on the timing of terminated interventions.

positive: The Impact of Social Distancing on COVID19 Spread: State of Georgia Case Study As the COVID19 spread in the US continues to grow, local and state officials face difficult decisions about when and how to transition to a new normal. We developed an agent-based simulation model to project the infection spread; outcomes include the number of COVID19 infections and resulting severe outcomes, and the need for hospital capacity under social distancing, particularly, shelter-in-place and voluntary quarantine. We populated the model using COVID19-specific parameters for the natural history of the disease and data from Georgia on the agents interactions and demographics. The simulation study covered a six-month period, testing different social distancing scenarios, including baselines (no-intervention or school closure only) and combinations of shelter-in-place and voluntary quarantine with different timelines and compliance levels. The outcomes are compared at the state and community levels. Main outcomes are the number and percentage of cumulative and daily new and symptomatic and asymptomatic infections, hospitalizations, and deaths; COVID19-related demand for hospital beds, ICU beds, and ventilators. Results: The combined intervention of shelter-in-place followed by voluntary quarantine reduced peak infections from 180,000 under no intervention and 120,000 under school closure, respectively, to below 80,000, and delayed the peak from April to June or later. Increasing shelter-in-place duration from four to five weeks yielded 3-14% and 4-6% decrease in cumulative infection and fatality rates, respectively. Regardless of the shelter-in-place duration, increasing voluntary quarantine compliance decreased daily new infections from almost 80,000 to 50,000, and decreased cumulative infection rate by 50%. The total number of fatalities ranged from 6,150 to 17,900 under different scenarios. Peak infection date varied across scenarios and counties; on average, increasing shelter-in-place duration delayed the peak day by 7 days across counties. The peak percentage is similar across rural and urban counties. Region D is estimated to have the highest COVID19-related healthcare needs with 7,357 hospital beds, 1,141 ICU beds, and 558 ventilators. Conclusions and Relevance Shelter-in-place followed by voluntary quarantine substantially reduce COVID19 infections, healthcare resource needs, and severe outcomes; delay the peak; and enable better preparedness. Time of the peak is projected to vary across locations, enabling reallocation of health system capacity.

positive: Reactive Social distancing in a SIR model of epidemics such as COVID-19 A model of reactive social distancing in epidemics is proposed, in which the infection rate changes with the number infected. The final-size equation for the total number that the epidemic will infect can be derived analytically, as can the peak infection proportion. This model could assist planners during for example the COVID-19 pandemic.

positive: Strong Effects of Population Density and Social Characteristics on Distribution of COVID-19 Infections in the United States Coronavirus disease 2019 (Covid-19) has devastated global populations and has had a large impact in the United States with the number of infections and deaths growing exponentially. Using a smooth generalized additive model with quasipoisson counts for total infections and deaths, we developed a county-level predictive model that included population demographics, social characteristics, social distancing, and testing data. This model strongly predicted the actual US distribution of Covid-19, accounting for 94.8% of spatial-temporal variation in total infections and 99.3% in Covid-19 related fatalities from March 15, 2020. US counties with higher population density, poverty index, civilian population, and minorities, especially African Americans had a higher number of confirmed infections adjusted for county population. Social distancing measured by the change in the rate of human encounter per km2 relative to pre-covid-19 national average was associated with slower rate of Covid-19 infections, whereas higher testing was associated with higher number of infections. The number of people infected was increasing, however, the rate of increase in new infections was starting to show signs of plateauing starting from the second week of April. Our model projects 2.11 million people to test positive for Covid-19 and 122,951 fatalities by June 1, 2020. Importantly, our model suggests strong social differences in the infections and deaths across US communities, and inequities in areas with larger African American minorities and higher poverty index expected to show higher rates of Covid-19 infections and deaths. Preventive steps including social distancing and community closures have been a cornerstone in stopping the transmission and potentially reducing the spread of the disease. Crucial knowledge of the role of social characteristics in the disease transmission is essential to understand current disease distribution, predict future distribution, and plan additional preventive steps.

positive: Phase transitions and control measures for network epidemics caused by infections with presymptomatic, asymptomatic,and symptomatic stages We investigate phase transitions associated with three control methods for epidemics on small world networks. Motivated by the behavior of SARS-CoV-2, we construct a theoretical SIR model of a virus that exhibits presymptomatic, asymptomatic, and symptomatic stages in two possible pathways. Using agent-based simulations on small world networks, we observe phase transitions for epidemic spread related to: 1) Global social distancing with a fixed probability of adherence. 2) Individually initiated social isolation when a threshold number of contacts are infected. 3) Viral shedding rate. The primary driver of total number of infections is the viral shedding rate, with probability of social distancing being the next critical factor. Individually initiated social isolation was effective when initiated in response to a single infected contact. For each of these control measures, the total number of infections exhibits a sharp phase transition as the strength of the measure is varied.

positive: Impact of population movement on the spread of 2019-nCoV in China Since Dec 2019, China has experienced an outbreak caused by a novel coronavirus, 2019-nCoV. A travel ban was implemented for Wuhan, Hubei on Jan 23 to slow down the outbreak. We found a significant positive correlation between population influx from Wuhan and confirmed cases in other cities across China (R(2) = 0.85, P < 0.001), especially cities in Hubei (R(2) = 0.88, P < 0.001). Removing the travel restriction would have increased 118% (91%–172%) of the overall cases for the coming week, and a travel ban taken three days or a week earlier would have reduced 47% (26%–58%) and 83% (78%–89%) of the early cases. We would expect a 61% (48%–92%) increase of overall cumulative cases without any restrictions on returning residents, and 11% (8%–16%) increase if the travel ban stays in place for Hubei. Cities from Yangtze River Delta, Pearl River Delta, and Capital Economic Circle regions are at higher risk.

positive: Get the News Out Loudly and Quickly: The Influence of the Media on Limiting Emerging Infectious Disease Outbreaks During outbreaks of infectious diseases with high morbidity and mortality, individuals closely follow media reports of the outbreak. Many will attempt to minimize contacts with other individuals in order to protect themselves from infection and possibly death. This process is called social distancing. Social distancing strategies include restricting socializing and travel, and using barrier protections. We use modeling to show that for short-term outbreaks, social distancing can have a large influence on reducing outbreak morbidity and mortality. In particular, public health agencies working together with the media can significantly reduce the severity of an outbreak by providing timely accounts of new infections and deaths. Our models show that the most effective strategy to reduce infections is to provide this information as early as possible, though providing it well into the course of the outbreak can still have a significant effect. However, our models for long-term outbreaks indicate that reporting historic infection data can result in more infections than with no reporting at all. We examine three types of media influence and we illustrate the media influence with a simulated outbreak of a generic emerging infectious disease in a small city. Social distancing can never be complete; however, for a spectrum of outbreaks, we show that leaving isolation (stopping applying social distancing measures) for up to 4 hours each day has modest effect on the overall morbidity and mortality.

positive: COVID-19 related social distancing measures and reduction in city mobility In the absence of any pharmacological intervention, one approach to slowing the COVID-19 pandemic is reducing the contact rate in the population through social distancing. Governments the world over have instituted different measures to increase social distancing but information on their effectiveness in reducing mobility is lacking. We analyzed the mobility data from 41 cities to look at the effect of these interventions. The median mobility across cities on March 2, 2020 was 100% (IQR: 94%, 107%), which decreased to a median of 10% (IQR: 7%, 17%) on March 26, 2020. We found that the mobility decreased on average by 3.4% (95%CI: 3.3%, 3.6%) per day from March 2 through March 26. Social distancing measures decreased the mobility by an additional 23% (95%CI: 20%, 27%). Our study provides initial evidence for the reduction in mobility in cities instituting social distancing measures.

positive: Estimating the impact of COVID-19 control measures using a Bayesian model of physical distancing Extensive physical distancing measures are currently the primary intervention against coronavirus disease 2019 (COVID-19) worldwide. It is therefore urgent to estimate the impact such measures are having. We introduce a Bayesian epidemiological model in which a proportion of individuals are willing and able to participate in distancing measures, with the timing of these measures informed by survey data on attitudes to distancing and COVID-19.We fit our model to reported COVID-19 cases in British Columbia, Canada, using an observation model that accounts for both underestimation and the delay between symptom onset and reporting. We estimate the impact that physical distancing (also known as social distancing)has had on the contact rate and examine the projected impact of relaxing distancing measures. We find that distancing has had a strong impact, consistent with declines in reported cases and in hospitalization and intensive care unit numbers. We estimate that approximately 0.78 (0.66-0.89 90% CI) of contacts have been removed for individuals in British Columbia practising physical distancing and that this fraction is above the threshold of 0.45 at which prevalence is expected to grow. However, relaxing distancing measures beyond this threshold re-starts rapid exponential growth. Because the extent of underestimation is unknown, the data are consistent with a wide range in the prevalence of COVID-19 in the population; changes to testing criteria over time introduce additional uncertainty. Our projections indicate that intermittent distancing measures - if sufficiently strong and robustly followed - could control COVID-19 transmission, but that if distancing measures are relaxed too much, the epidemic curve would grow to high prevalence.

positive: Public perspectives on social distancing and other protective measures in Europe: a cross-sectional survey study during the COVID-19 pandemic Objectives: The extent to which people implement government-issued protective measures is critical in preventing further spread of coronavirus disease 2019 (COVID-19) caused by coronavirus SARS-CoV-2. Our study aimed to evaluate the public belief in the effectiveness of protective measures, the reported implementation of these measures in daily life, and to identify communication channels used to acquire relevant information on COVID-19 in European countries. Design: A cross-sectional online survey available in multiple languages was disseminated on social media starting March 19th, 2020. After five days, we computed descriptive statistics for countries with more than 500 respondents. Each day, we compiled and categorized community containment measures enacted in each country by stringency (stage I-IV). Response collection continued for one week to explore possible dynamics as containment strategies intensified. Participants: In total, 9,796 adults responded, of whom 8,611 resided in the Netherlands (stage III), 604 in Germany (stage III), and 581 in Italy (stage IV). An additional 1,365 respondents completed the survey in the following week. Results: Participants indicated support for governmental measures related to avoiding social gatherings, selective closure of public places, and hand hygiene and respiratory measures (range for all measures: 95.0%-99.7%). Respondents from the Netherlands were less likely to consider a complete social lockdown effective (59.2%), compared to respondents in Germany (76.6%) or Italy (87.2%). Italian residents did not only apply enforced social distancing measures more frequently (range: 90.2%-99.3%, German and Dutch residents: 67.5%-97.0%), but also self-initiated hygienic and social distancing behaviors (range: 36.3%-96.6%, German and Dutch residents: 28.3%-95.7%). Respondents largely reported being sufficiently informed about the COVID-19 outbreak and about behaviors to avoid infection (range across countries: 90.2%-91.1%). Information channels most commonly reported included television (range: 53.0%-82.0%), newspapers (range: 31.0%-63.0%), official health websites (range: 39.0%-54.1%), and social media (range: 40.0%-55.8%). We observed no major changes in answers over time. Conclusions: In European countries, the degree of public belief in the effectiveness of protective measures was high and residents reported to be sufficiently informed by various communication channels. In March 2020, implementation of enacted and self-initiated measures differed between countries and were highest among Italian respondents, who were subjected to the most elaborate measures of social lockdown and greatest COVID-19 burden in Europe.

positive: Social Distancing 2.0 with Privacy-Preserving Contact Tracing to Avoid a Second Wave of COVID-19 How to avoid a second wave of COVID-19 after reopening the economy is a pressing question. The extremely high basic reproductive number $R_0$ (5.7 to 6.4, shown in new studies) of SARS-CoV-2 further complicates the challenge. Here we assess effects of Social distancing 2.0, i.e. proximity alert (to maintain inter-personal distance) plus privacy-preserving contact tracing. To solve the dual task, we develop an open source mobile app. The app uses a Bluetooth-based, decentralized contact tracing platform over which the anonymous user ID cannot be linked by the government or a third party. Modeling results show that a 50\% adoption rate of Social distancing 2.0, with privacy-preserving contact tracing, would suffice to decrease the $R_0$ to less than 1 and prevent the resurgence of COVID-19 epidemic.

positive: Little Risk of the COVID-19 Resurgence on Students in China (outside Hubei) Caused by School Reopening Objective: School reopening has not yet started in China where the COVID-19 outbreak has reached ending stage, largely due to a great concern about COVID-19 infections on students. We attempted to quantitatively evaluate the risk of COVID-19 infections on students caused by school reopening. Study design: We collected the data of the numbers of teachers, population size and newly confirmed COVID-19 cases in the past 14 days in typical provinces/cities of China, and then analyzed the risk of COVID-19 infections in schools with respect to each province/city. Methods: A step-by-step procedure was explored to calculate the probability of COVID-19 infections on students as transmitted from infected teachers. Two critical assumptions for analysis were proposed: (i) only locally generated cases were counted while imported cases were omitted; (ii) the secondary attack rate of the COVID-19 virus in schools is similar to that in households in China, ranging from 3-10%. Results: The probability of COVID-19 resurgence within one week on students of primary, middle and high schools in China (outside Hubei) is extremely low (<0.2%) in each province/city, and such probability can be updated daily and weekly based on the newly confirmed cases in the past 14 days. In some areas without newly confirmed cases in the past 14 days, the risk is zero. Conclusions: Our work provides guidance for local governments to make risk level-based policies for school reopening. Currently, the risk of COVID-19 infections on students is extremely low in China (outside Hubei) and therefore school reopening can be initiated without the endanger of infections on students.

positive: Act early, save lives: managing COVID-19 in Greece Abstract Objectives: To assess the impact of the implemented social distancing interventions (SD) in Greece. Study Design: A dynamic, discrete time, stochastic individual-based model was developed to simulate COVID-19 transmission. Methods: We fit the transmission model to the observed trends in deaths and ICU beds use. Results: If Greece had not implemented the SD measures, the healthcare system would have been overwhelmed between 30 March and 4 of April. Additionally, the SD interventions averted 4360 deaths and prevent the healthcare system from overwhelmed. Conclusions: The fast reflexes of the Greek government limit the burden of the Covid-19 outbreak.

positive: Potential roles of social distancing in mitigating the spread of coronavirus disease 2019 (COVID-19) in South Korea On January 20, 2020, the first COVID-19 case was confirmed in South Korea. After a rapid outbreak, the number of incident cases has been consistently decreasing since early March; this decrease has been widely attributed to its intensive testing. We report here on the likely role of social distancing in reducing transmission in South Korea. Our analysis suggests that transmission may still be persisting in some regions.

positive: The effect of non-pharmaceutical interventions (NPIs) on the spread of COVID-19 pandemic in Japan: A modeling study Non-pharmaceutical interventions (NPIs) are founded to be effective to delay epidemic spread and to reduce the number of patients. Moderate NPIs took in Japan seemed to have reduced the COVID-19 patients and to lower death rates, thus, effects of those NPIs are worthy of investigation. We used open source data and divided the data into three periods: Jan 22 to Feb 25 (Period I), Feb 26 to Apr 6 (Period II), and Apr 7 to May 14 (Period III). We developed the SIRD model and applied the Monte Carlo Simulation to estimate a combination of optimal results, including the peak of infected cases, the peak date, and R0. For Period I, the estimated peak infected cases were smaller than the observed ones, the peak date was earlier than the observed one, and the R0 was about 4.66. For the other two periods, the estimated cases were more, and the peak dates were earlier than the observed ones. The R0 was 2.50 in Period II, and 1.79 in Period III. NPIs took in Japan might have reduced more than 50% of the daily contacts per people compared to that before COVID-19. Owing to the effects of NPIs, the Japanese society had avoided collapse of medical service. Nevertheless, the capacity of daily RT-PCR may have restricted the reported confirmed cases.

positive: Targeted adaptive isolation strategy for Covid-19 pandemic We investigate the effects of social distancing in controlling the impact of the COVID-19 epidemic using a simple susceptible-infected-removed epidemic model. We show that an alternative or complementary approach based on targeted isolation of the vulnerable sub-population may provide a more efficient and robust strategy at a lower economic and social cost within a shorter timeframe resulting in a collectively immune population.

positive: COVID-19 spreading in Rio de Janeiro, Brazil: do the policies of social isolation really work? The recent Coronavirus has been spreading through all the world fastly. In this work we focus on the evolution of the COVID-19 in one of the most populous Brazilian states, namely the Rio de Janeiro state. The first case was reported in March 5, 2020, thus we have a considerable amount of available data to make a good analysis. We study the dynamics of COVID-19 through a Susceptible-Infectious-Quarantined-Recovered (SIQR) model with an additional mechanism that represents the implementation of public policies of social isolation. Based on the data collected from the Rio de Janeiro state Department of Health from March 5, 2020 through April 26, 2020, we observed that the implementation of social distancing policies changed the initial exponential growth to a sub-exponential one. The SIQR model with the above-mentioned mechanism is capable of reproducing the data of confirmed cases in Rio de Janeiro, and it explains how that change occurred. The model also predicts an important mitigation effect, namely the flattening effect, i.e., the considerably decrease of the maximum number of confirmed cases. Through the results of the model, this effect can be directly related to the social isolation policies. Finally, we consider the relaxation of such policies, and discuss about the ideal period of time to release people to return to their activities.

positive: Analysis of Effectiveness of Quarantine Measures in Controlling COVID-19 COVID-19 has created an interesting discourse among the people of the world particularly regarding preventive measures of infectious diseases. In this paper, the authors forecast the spread of the Corona virus outbreak and study how the reduction of transmission rates influences its decline. The paper makes use of the SIR (Susceptible Infected Recovered) Model which is a deterministic model used in the field of epidemiology-based on differential equations derived from sections of the population. The Basic Reproduction Number (Ro) represents the criticality of the epidemic in numeric terms. Forecasting an epidemic provides insights about the geographic spreading of the disease and the case incidences required to better inform intervention strategists about situations that may occur during the outbreak. Through this research paper, the authors wish to provide an insight into the impact of control measures on the pandemic. By drawing a comparison of three countries and their quarantine measures, observations on the decline of the outbreak are made. Authors intend to guide the intervention strategies of under-resourced countries like India and aid in the overall containment of the outbreak.

positive: Quantifying early COVID-19 outbreak transmission in South Africa and exploring vaccine efficacy scenarios Background: COVID-19 has emerged and spread at great speed globally and has presented one of the greatest public health challenges in modern times with no proven cure or vac-cine. Africa is still early in this epidemic, therefore the spectrum of disease severity is not yet clear. Methods: We used a mathematical model to fit to the observed cases of COVID-19 in South Africa to estimate the basic reproductive number and critical vaccination coverages to con-trol the disease for different hypothetical vaccine efficacy scenarios. We also estimated the percentage reduction in effective contacts due to the social distancing measures imple-mented. Results: Early model estimates show that COVID-19 outbreak in South Africa had a basic reproductive number of 2.95 (95% credible interval [CrI] 2.83-3.33). A vaccine with 70% effi-cacy had the capacity to contain COVID-19 outbreak but at very higher vaccination cover-age 94.44% (95% Crl 92.44-99.92%) with a vaccine of 100% efficacy requiring 66.10% (95% Crl 64.72-69.95%) coverage. Social distancing measures put in place have so far reduced the number of social contacts by 80.31% (95% Crl 79.76-80.85%). Conclusions: Findings suggest a highly efficacious vaccine would have been required to con-tain COVID-19 in South Africa. Therefore, the current social distancing measures to reduce contacts will remain key in controlling the infection in the absence of vaccines and other therapeutics.

positive: On the benefits of flattening the curve: A perspective The many variations on a graphic illustrating the impact of non-pharmaceutical measures to mitigate pandemic influenza that have appeared in recent news reports about COVID-19 suggest a need to better explain the mechanism by which social distancing reduces the spread of infectious diseases. And some reports understate one benefit of reducing the frequency or proximity of interpersonal encounters, a reduction in the total number of infections. In hopes that understanding will increase compliance, we describe how social distancing (a) reduces the peak incidence of infections, (b) delays the occurrence of this peak, and (c) reduces the total number of infections during epidemics. In view of the extraordinary efforts underway to identify existing medications that are active against SARS-CoV-2 and to develop new antiviral drugs, vaccines and antibody therapies, any of which may have community-level effects, we also describe how pharmaceutical interventions affect transmission.

positive: The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application BACKGROUND: A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in China in December 2019. There is limited support for many of its key epidemiologic features, including the incubation period for clinical disease (coronavirus disease 2019 [COVID-19]), which has important implications for surveillance and control activities. OBJECTIVE: To estimate the length of the incubation period of COVID-19 and describe its public health implications. DESIGN: Pooled analysis of confirmed COVID-19 cases reported between 4 January 2020 and 24 February 2020. SETTING: News reports and press releases from 50 provinces, regions, and countries outside Wuhan, Hubei province, China. PARTICIPANTS: Persons with confirmed SARS-CoV-2 infection outside Hubei province, China. MEASUREMENTS: Patient demographic characteristics and dates and times of possible exposure, symptom onset, fever onset, and hospitalization. RESULTS: There were 181 confirmed cases with identifiable exposure and symptom onset windows to estimate the incubation period of COVID-19. The median incubation period was estimated to be 5.1 days (95% CI, 4.5 to 5.8 days), and 97.5% of those who develop symptoms will do so within 11.5 days (CI, 8.2 to 15.6 days) of infection. These estimates imply that, under conservative assumptions, 101 out of every 10 000 cases (99th percentile, 482) will develop symptoms after 14 days of active monitoring or quarantine. LIMITATION: Publicly reported cases may overrepresent severe cases, the incubation period for which may differ from that of mild cases. CONCLUSION: This work provides additional evidence for a median incubation period for COVID-19 of approximately 5 days, similar to SARS. Our results support current proposals for the length of quarantine or active monitoring of persons potentially exposed to SARS-CoV-2, although longer monitoring periods might be justified in extreme cases. PRIMARY FUNDING SOURCE: U.S. Centers for Disease Control and Prevention, National Institute of Allergy and Infectious Diseases, National Institute of General Medical Sciences, and Alexander von Humboldt Foundation.

positive: Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK Background: To mitigate and slow the spread of COVID-19, many countries have adopted unprecedented physical distancing policies, including the UK. We evaluate whether these measures might be sufficient to control the epidemic by estimating their impact on the reproduction number (R0, the average number of secondary cases generated per case). Methods: We asked a representative sample of UK adults about their contact patterns on the previous day. The questionnaire documents the age and location of contacts and as well as a measure of their intimacy (whether physical contact was made or not). In addition, we asked about adherence to different physical distancing measures. The first surveys were sent on Tuesday 24th March, one day after a “lockdown” was implemented across the UK. We compared measured contact patterns during the lockdown to patterns of social contact made during a non-epidemic period. By comparing these, we estimated the change in reproduction number as a consequence of the physical distancing measures imposed. We used a meta-analysis of published estimates to inform our estimates of the reproduction number before interventions were put in place. Findings: We found a 73% reduction in the average daily number of contacts observed per participant (from 10.2 to 2.9). This would be sufficient to reduce R0 from 2.6 prior to lockdown to 0.62 (95% confidence interval [CI] 0.37 - 0.89) after the lockdown, based on all types of contact and 0.37 (95% CI = 0.22 - 0.53) for physical contacts only. Interpretation: The physical distancing measures adopted by the UK public have substantially reduced contact levels and will likely lead to a substantial impact and a decline in cases in the coming weeks. However, this projected decline in incidence will not occur immediately as there are significant delays between infection, the onset of symptomatic disease and hospitalisation, as well as further delays to these events being reported. Tracking behavioural change can give a more rapid assessment of the impact of physical distancing measures than routine epidemiological surveillance.

positive: Cost-effectiveness Analysis of Antiepidemic Policies and Global Situation Assessment of COVID-19 With a two-layer contact-dispersion model and data in China, we analyze the cost-effectiveness of three types of antiepidemic measures for COVID-19: regular epidemiological control, local social interaction control, and inter-city travel restriction. We find that: 1) intercity travel restriction has minimal or even negative effect compared to the other two at the national level; 2) the time of reaching turning point is independent of the current number of cases, and only related to the enforcement stringency of epidemiological control and social interaction control measures; 3) strong enforcement at the early stage is the only opportunity to maximize both antiepidemic effectiveness and cost-effectiveness; 4) mediocre stringency of social interaction measures is the worst choice. Subsequently, we cluster countries/regions into four groups based on their control measures and provide situation assessment and policy suggestions for each group.

positive: Impact of small-area lockdowns for the control of the COVID-19 pandemic Background Countries confronting the COVID-19 pandemic are implementing different social distancing strategies. We evaluated the impact of small-area lockdowns in Chile, aimed to reduce viral transmission while minimizing the population disrupted. The effectiveness of this intervention on the outbreak control is unknown. Methods A natural experiment assessing the impact of small-area lockdowns between February 15th and April 25th, 2020. We used mobility data and official governmental reports to compare regions with small-area lockdowns versus regions without. The primary outcome was the mean difference in the effective reproductive number (Re) of COVID-19. Secondary outcomes were changes in mobility indicators. We used quasi-experimental methods for the analysis and examined the impact of other concurrent public health interventions to disentangle their effects. Results Small-area lockdown produced a sizable reduction in human mobility, equivalent to an 11.4% reduction (95%CI -14.4% to -8.38%) in public transport and similar effects in other mobility indicators. Ten days after implementation, the small-area lockdown produced a reduction of the effective reproductive number (Re) of 0.86 (95%CI -1.70 to -0.02). School and university closures, implemented earlier, led to a 40% reduction in urban mobility. Closure of educational institutions resulted in an even greater Re reduction compared with small-area lockdowns. Conclusions Small-area lockdowns produced a reduction in mobility and viral transmission, but the effects were smaller than the early closures of schools and universities. Small-area lockdowns may have a relevant supporting role in reducing SARS-CoV-2 transmission and could be useful for countries considering scaling-down stricter social distancing interventions.

positive: Modeling the Effective Control Strategy for Transmission Dynamics of Global Pandemic COVID-19 The novel coronavirus disease (namely COVID-19) has taken attention because of its deadliness across the globe, causing a massive death as well as critical situation around the world. It is an infectious disease which is caused by newly discovered coronavirus. Our study demonstrates with a nonlinear model of this devastating COVID-19 which narrates transmission from human-to-human in the society. Pontryagin Maximum principle has also been applied in order to obtain optimal control strategies where the maintenance of social distancing is the major control. The target of this study is to find out the most fruitful control measures of averting coronavirus infection and eventually, curtailed of the COVID-19 transmission among people. The model is investigated analytically by using most familiar necessary conditions of Pontryagin maximum principle. Furthermore, numerical simulations have been performed to illustrate the analytical results. The analysis reveals that implementation of educational campaign, social distancing and developing human immune system are the major factors which can be able to plunge the scenario of becoming infected.

positive: COVID-19 Control Strategies and Intervention Effects in Resource Limited Settings: A Modeling Study Background Many countries with weaker health systems are struggling to put together a coherent strategy against the COVID-19 epidemic. We explored COVID-19 control strategies that could offer the greatest benefit in resource limited settings. Methods Using an age-structured SEIR model, we explored the effects of COVID-19 control interventions--a lockdown, physical distancing measures, and active case finding (testing and isolation, contact tracing and quarantine)-- implemented individually and in combination to control a hypothetical COVID-19 epidemic in Kathmandu (population 2.6 million), Nepal. Results A month-long lockdown that is currently in place in Nepal will delay peak demand for hospital beds by 36 days, as compared to a base scenario of no interventions (peak demand at 108 days (IQR 97-119); a 2 month long lockdown will delay it by 74 days, without any difference in annual mortality, or healthcare demand volume. Year-long physical distancing measures will reduce peak demand to 36% (IQR 23%-46%) and annual morality to 67% (IQR 48%-77%) of base scenario. Following a month long lockdown with ongoing physical distancing measures and an active case finding intervention that detects 5% of the daily infection burden could reduce projected morality and peak demand by more than 99%. Interpretation Limited resources settings are best served by a combination of early and aggressive case finding with ongoing physical distancing measures to control the COVID-19 epidemic. A lockdown may be helpful until combination interventions can be put in place but is unlikely to reduce annual mortality or healthcare demand.

positive: Taking the inner route: spatial and demographic factors affecting vulnerability to COVID-19 among 604 cities from inner São Paulo State, Brazil Even though the impact of COVID-19 in metropolitan areas has been extensively studied, the geographic spread to smaller cities is also of great concern. We conducted an ecological study aimed at identifying predictors of early introduction, incidence rates of COVID-19 and mortality (up to 8 May 2020) among 604 municipalities in inner São Paulo State, Brazil. Socio-demographic indexes, road distance to the state capital and a classification of regional relevance were included in predictive models for time to COVID-19 introduction (Cox regression), incidence and mortality rates (zero-inflated binomial negative regression). In multivariable analyses, greater demographic density and higher classification of regional relevance were associated with both early introduction and increased rates of COVID-19 incidence and mortality. Other predictive factors varied, but distance from the State Capital (São Paulo City) was negatively associated with time-to-introduction and with incidence rates of COVID-19. Our results reinforce the hypothesis of two patterns of geographical spread of SARS-Cov-2 infection: one that is spatial (from the metropolitan area into the inner state) and another which is hierarchical (from urban centres of regional relevance to smaller and less connected municipalities). Those findings may apply to other settings, especially in developing and highly heterogeneous countries, and point to a potential benefit from strengthening non-pharmaceutical control strategies in areas of greater risk.

positive: Can informal social distancing interventions minimize demand for antiviral treatment during a severe pandemic? BACKGROUND: In the case of a pandemic, individuals may alter their behaviour. A dynamic model incorporating social distancing can provide a mechanism to consider complex scenarios to support decisions regarding antiviral stockpile size while considering uncertainty around behavioural interventions. We have examined the impact of social distancing measures on the demand for limited healthcare resources such as antiviral drugs from a central stockpile during a severe pandemic. METHODS: We used an existing age-structured model for pandemic influenza in Canada and biologically plausible scenarios for severe influenza transmission within the population. We incorporated data from published reports regarding stated intentions to change behaviour during a pandemic as well as the magnitude and duration of time that individuals expected to maintain the behavioural change. We ran simulations for all combinations of parameter values to identify the projected antiviral requirements in each scenario. RESULTS: With 12 weeks of distancing, the effect is relatively small for the lowest R0 of 1.6 with a projected stockpile to treat 25.6% being required (IQR = 21.7 – 28.7%) unless the proportion of people involved (81%) and magnitude of the behaviour change is large (69% reduction in contacts). If 24 weeks of distancing occurs, with only a low to moderate reduction in contacts (38% or less), it is not possible to bring treatment requirements below 20% regardless of what proportion of the population engages in distancing measures when transmissibility is high (R0 = 2.0; stockpile size = 31%, IQR = 29.2 – 33.5%). CONCLUSIONS: Our results demonstrate that the magnitude and duration of social distancing behaviours during a severe pandemic have an impact on the need for antiviral drugs. However, significant investments over a long period of time (>16 weeks) are required to decrease the need for antiviral treatment to below 10% of the total population for a highly transmissible viral strain (R0 > 1.8). Encouraging individuals to adopt behaviours that decrease their daily contact rate can help to control the spread of the virus until a vaccine becomes available however; relying on these measures to justify stockpiling fewer courses of treatment will not be sufficient in the case of a severe pandemic.

positive: Impact of population movement on the spread of 2019-nCoV in China Since Dec 2019, China has experienced an outbreak caused by a novel coronavirus, 2019-nCoV. A travel ban was implemented for Wuhan, Hubei on Jan 23 to slow down the outbreak. We found a significant positive correlation between population influx from Wuhan and confirmed cases in other cities across China (R2 = 0.85, P < 0.001), especially cities in Hubei (R2 = 0.88, P < 0.001). Removing the travel restriction would have increased 118% (91%-172%) of the overall cases for the coming week, and a travel ban taken three days or a week earlier would have reduced 47% (26%-58%) and 83% (78%-89%) of the early cases. We would expect a 61% (48%-92%) increase of overall cumulative cases without any restrictions on returning residents, and 11% (8%-16%) increase if the travel ban stays in place for Hubei. Cities from Yangtze River Delta, Pearl River Delta, and Capital Economic Circle regions are at higher risk.

positive: Forecasting COVID 19 growth in India using Susceptible-Infected-Recovered (S.I.R) model This work covers the analysis of the COVID 19 spread in different countries and dealing the main feature of COVID 19 growth, which is the spread due to the social-contact structure, which is governed by the parameter \b{eta}. The dependency of this parameter \b{eta} on the transmission level in society gives a sense of the effectiveness of the measures taken for social distancing. A separate algorithm is hardcoded in python using Scipy which learns the social-contact structure and gives a suitable value for \b{eta}, which has a major impact on the outcome of the result. Forecasting for the epidemic spread in India was done, and it was found that the strictness at which social distancing in India is done, is insufficient for the growth of COVID 19.

positive: COVID-19 infection and recovery in various countries: Modeling the dynamics and evaluating the non-pharmaceutical mitigation scenarios The coronavirus disease 2019 (COVID-19) pandemic radically impacts our lives, while the transmission/infection and recovery dynamics of COVID-19 remain obscure. A time-dependent Susceptible, Exposed, Infectious, and Recovered (SEIR) model was proposed and applied to fit and then predict the time series of COVID-19 evolution observed in the last three months (till 3/22/2020) in various provinces and metropolises in China. The model results revealed the space dependent transmission/infection rate and the significant spatiotemporal variation in the recovery rate, likely due to the continuous improvement of screening techniques and public hospital systems, as well as full city lockdowns in China. The validated SEIR model was then applied to predict COVID-19 evolution in United States, Italy, Japan, and South Korea which have responded differently to monitoring and mitigating COVID-19 so far, although these predictions contain high uncertainty due to the intrinsic change of the maximum infected population and the infection/recovery rates within the different countries. In addition, a stochastic model based on the random walk particle tracking scheme, analogous to a mixing-limited bimolecular reaction model, was developed to evaluate non-pharmaceutical strategies to mitigate COVID-19 spread. Preliminary tests using the stochastic model showed that self-quarantine may not be as efficient as strict social distancing in slowing COVID-19 spread, if not all of the infected people can be promptly diagnosed and quarantined.

positive: Flattening the curve and the effect of atypical events on mitigation measures in Mexico: a modeling perspective On 23 and 30 March 2020 the Mexican Federal government implemented social distancing measures to mitigate the COVID-19 epidemic. We use a mathematical model to explore atypical transmission events within the confinement period, triggered by the timing and strength of short time perturbations of social distancing. We show that social distancing measures were successful in achieving a significant reduction of the effective contact rate in the early weeks of the intervention. However, "flattening the curve" had an undesirable effect, since the epidemic peak was delayed too far, almost to the government preset day for lifting restrictions (01 June 2020). If the peak indeed occurs in late May or early June, then the events of children's day and mother's day may either generate a later peak (worst case scenario), a long plateau with relatively constant but high incidence (middle case scenario) or the same peak date as in the original baseline epidemic curve, but with a post-peak interval of slower decay.

positive: The impact of early social distancing at COVID-19 Outbreak in the largest Metropolitan Area of Brazil. We evaluated the impact of early social distancing on the COVID-19 transmission in the Sao Paulo metropolitan area. Using an age-stratified SEIR model, we determined the time-dependent reproductive number, and forecasted the ICU beds necessary to tackle this epidemic. Within 60 days, these measures might prevent 89,133 deaths.

positive: Local risk perception enhances epidemic control As infectious disease outbreaks emerge, public health agencies often enact vaccination and social distancing measures to slow transmission. Their success depends on not only strategies and resources, but also public adherence. Individual willingness to take precautions may be influenced by global factors, such as news media, or local factors, such as infected family members or friends. Here, we compare three modes of epidemiological decision-making in the midst of a growing outbreak using network-based mathematical models that capture plausible heterogeneity in human contact patterns. Individuals decide whether to adopt a recommended intervention based on overall disease prevalence, the proportion of social contacts infected, or the number of social contacts infected. While all strategies can substantially mitigate transmission, vaccinating (or self isolating) based on the number of infected acquaintances is expected to prevent the most infections while requiring the fewest intervention resources. Unlike the other strategies, it has a substantial herd effect, providing indirect protection to a large fraction of the population.

positive: Modelling the impact of reducing control measures on the COVID-19 pandemic in a low transmission setting Aims: We assessed COVID-19 epidemic risks associated with relaxing a set of physical distancing restrictions in the state of Victoria, Australia - a setting with low community transmission - in line with a national framework that aims to balance sequential policy relaxations with longer-term public health and economic need. Methods: An agent-based model, Covasim, was calibrated to the local COVID-19 epidemiological and policy environment. Contact networks were modelled to capture transmission risks in households, schools and workplaces, and a variety of community spaces (e.g. public transport, parks, bars, cafes/restaurants) and activities (e.g. community or professional sports, large events). Policy changes that could prevent or reduce transmission in specific locations (e.g. opening/closing businesses) were modelled in the context of interventions that included testing, contact tracing (including via a smartphone app), and quarantine. Results: Policy changes leading to the gathering of large, unstructured groups with unknown individuals (e.g. bars opening, increased public transport use) posed the greatest risk, while policy changes leading to smaller, structured gatherings with known individuals (e.g. small social gatherings) posed least risk. In the model, epidemic impact following some policy changes took more than two months to occur. Model outcomes support continuation of working from home policies to reduce public transport use, and risk mitigation strategies in the context of social venues opening, such as >30% population-uptake of a contact-tracing app, physical distancing policies within venues reducing transmissibility by >40%, or patron identification records being kept to enable >60% contact tracing. Conclusions: In a low transmission setting, care should be taken to avoid lifting sequential COVID-19 policy restrictions within short time periods, as it could take more than two months to detect the consequences of any changes. These findings have implications for other settings with low community transmission where governments are beginning to lift restrictions.

positive: Elementary spatial structures and dispersion of COVID-19: health geography directing responses to public health emergency in Sao Paulo State, Brazil Public health policies to contain the spread of COVID-19 rely mainly on non-pharmacological measures. Those measures, especially social distancing, are a challenge for developing countries, such as Brazil. In Sao Paulo, the most populous state in Brazil (45 million inhabitants), most COVID-19 cases up to April 18th were reported in the Capital and metropolitan area. However, the inner municipalities, where 20 million people live, are also at risk. As governmental authorities discuss the loosening of measures for restricting population mobility, it is urgent to analyze the routes of dispersion of COVID-19 in those municipalities. In this ecological study, we use geographical models of population mobility as patterns for spread of SARS-Cov-2 infection. Based on surveillance data, we identify two patterns: one by contiguous diffusion from the capital metropolitan area and other that is hierarchical, with long-distance spread through major highways to cities of regional relevance. We also modelled the impact of social distancing strategies in the most relevant cities, and estimated a beneficial effect in each and every setting studied. This acknowledgement can provide real-time responses to support public health strategies.

positive: Dynamics of the COVID-19 pandemic in India Understanding the dynamics of the COVID-19 pandemic is crucial for improved control and social distancing strategies. To that effect, we have employed the susceptible-exposed-infectious-recovered model, refined by contact tracing and hospitalization data from Indian provinces Kerala, Delhi, Maharashtra, and West Bengal, as well as from overall India. We have performed a sensitivity analysis to identify the most crucial input parameters, and we have calibrated the model to describe the data as best as possible. Short-term predictions reveal an increasing and worrying trend of COVID-19 cases for all four provinces and India as a whole, while long-term predictions also reveal the possibility of oscillatory dynamics. Our research thus leaves the option open that COVID-19 might become a seasonal occurrence. We also simulate and discuss the impact of media on the dynamics of the COVID-19 pandemic.

positive: Decline in global COVID-19 transmission We analyzed COVID-19 data through April 16, 2020 using a partially observed Markov process. Our method uses a hybrid deterministic and stochastic formalism that allows for time variable transmission rates and detection probabilities. The model was fit using iterated particle filtering to case count and death count time series from 51 countries. We found evidence for a declining transmission rate in 42 of the 51 examined countries. Of those 42 countries 34 have significant evidence for subcritical transmission rates, although the decline in new cases are relatively slow compared to the initial growth rates. This suggests that global scale social distancing efforts to slow the spread of COVID-19 are effective although they need to be strengthened in many regions and maintained in others to avoid further resurgence of COVID-19. The slow decline also suggests alternative strategies to control the virus are needed before social distancing efforts are partially relaxed.

positive: Mathematical modelling of COVID-19 transmission and mitigation strategies in the population of Ontario, Canada BACKGROUND: Physical-distancing interventions are being used in Canada to slow the spread of severe acute respiratory syndrome coronavirus 2, but it is not clear how effective they will be. We evaluated how different nonpharmaceutical interventions could be used to control the coronavirus disease 2019 (COVID-19) pandemic and reduce the burden on the health care system. METHODS: We used an age-structured compartmental model of COVID-19 transmission in the population of Ontario, Canada. We compared a base case with limited testing, isolation and quarantine to scenarios with the following: enhanced case finding, restrictive physical-distancing measures, or a combination of enhanced case finding and less restrictive physical distancing. Interventions were either implemented for fixed durations or dynamically cycled on and off, based on projected occupancy of intensive care unit (ICU) beds. We present medians and credible intervals from 100 replicates per scenario using a 2-year time horizon. RESULTS: We estimated that 56% (95% credible interval 42%-63%) of the Ontario population would be infected over the course of the epidemic in the base case. At the epidemic peak, we projected 107 000 (95% credible interval 60 760-149 000) cases in hospital (non-ICU) and 55 500 (95% credible interval 32 700-75 200) cases in ICU. For fixed-duration scenarios, all interventions were projected to delay and reduce the height of the epidemic peak relative to the base case, with restrictive physical distancing estimated to have the greatest effect. Longer duration interventions were more effective. Dynamic interventions were projected to reduce the proportion of the population infected at the end of the 2-year period and could reduce the median number of cases in ICU below current estimates of Ontario's ICU capacity. INTERPRETATION: Without substantial physical distancing or a combination of moderate physical distancing with enhanced case finding, we project that ICU resources would be overwhelmed. Dynamic physical distancing could maintain health-system capacity and also allow periodic psychological and economic respite for populations.

positive: Low-Impact Social Distancing Interventions to Mitigate Local Epidemics of SARS-CoV-2 Background After many jurisdictions have implemented intensive social distancing to suppress SARS-CoV-2 transmission, the challenge now is to mitigate the ongoing COVID-19 epidemic without overburdening economic and social activities. This report explores low-impact interventions to mitigate SARS-CoV-2 with a minimum of social and economic disruption. Methods An agent-based model simulated the population of King County, Washington, with agents that interact in homes, schools, workplaces, and other community sites. SARS-CoV-2 transmission probabilities were estimated by fitting simulated to observed hospital admissions from February-May 2020. Interventions considered were (a) encouraging telecommuting; (b) reducing contacts to seniors and nursing home residents; (c) modest reductions to contacts outside of the home; (d) encouraging self-isolation of persons with COVID-19 symptoms; (e) rapid testing and household quarantining. Results Individual interventions are not expected to have a large impact on COVID-19 hospitalizations. No intervention reduced COVID-19 hospitalizations by more than 12.7% (95% confidence interval [CI], 12.0% to 13.3%). Removing all interventions would result in nearly 42,000 COVID-19 hospitalizations between June 2020 and January 2021, with peak hospital occupancy exceeding available beds 6-fold. Combining the interventions is predicted to reduce total hospitalizations by 48% (95% CI, 47-49%), with peak COVID-19 hospital occupancy of 70% of total beds. Targeted school closures can further reduce the peak occupancy. Conclusions Combining low-impact interventions may mitigate the course of the COVID-19 epidemic, keeping hospital burden within the capacity of the healthcare system. Under this approach SARS-CoV-2 can spread through the community, moving toward herd immunity, while minimizing social and economic disruption.

positive: Impact of intervention on the spread of COVID-19 in India: A model based study The outbreak of corona virus disease 2019 (COVID-19), caused by the virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already created emergency situations in almost every country of the world. The disease spreads all over the world within a very short period of time after its first identification in Wuhan, China in December, 2019. In India, the outbreaks starts on $2^{nd}$ March, 2020 and after that the cases are increasing exponentially. Very high population density, the unavailability of specific medicines or vaccines, insufficient evidences regarding the transmission mechanism of the disease also make it difficult to fight against the disease properly in India. Mathematical models have been used to predict the disease dynamics and also to assess the efficiency of the intervention strategies in reducing the disease burden. In this work, we propose a mathematical model to describe the disease transmission mechanism between the individuals. We consider the initial phase of the outbreak situation in India and our proposed model is fitted to the daily cumulative new reported cases during the period $2^{nd}$ March, 2020 to $24^{th}$ March, 2020. We estimate the basic reproduction number $(R_0)$, effective reproduction number (R(t)) and epidemic doubling time from the incidence data for the above-mentioned period. We further assess the effect of preventive measures such as spread of awareness, lock-down, proper hand sanitization, etc. in reducing the new cases. Two intervention scenarios are considered depending on the variability of the intervention strength over the period of implementation. Our study suggests that higher intervention effort is required to control the disease outbreak within a shorter period of time in India. Moreover, our analysis reveals that the strength of the intervention should be strengthened over the time to eradicate the disease effectively.

positive: Several countries in one: a mathematical modeling analysis for COVID-19 in inner Brazil Early 2020 and the world experiences its very first pandemic of globalized era. A novel coronavirus, SARS-Cov-2, is the causative agent of severe pneumonia and rapidly spread through many nations, crashing health systems. In Brazil, the emergence of local epidemics in major metropolitan areas is a concern. In a huge and heterogeneous country, with regional disparities and climate diversity, several factors can modulate the dynamics of COVID-19. What should be the scenario for an inner Brazil and what can we do to control infection transmission in each one of these locations? In this paper, a mathematical model was developed to simulate disease transmission among individuals in several scenarios, differing by the intensity and type of control measures. Mitigation strategies rely on social distancing of all individuals, and detection and isolation of infected ones. The model shows that control effort varies among cities. The social distancing is the most efficient method to control disease transmission but improving detection and isolation of infected individuals can help loosening this mitigation strategy.

positive: On the airborne aspect of COVID-19 coronovirus It is a widely accepted view that COVID 19 is either transmitted via surface contamination or via close contact of an un-infected person with an infected person. Surface contamination usually happens when infected water droplets from exhalation/sneeze/cough of COVID sick person settle on nearby surfaces. To curb this, social distancing and good hand hygiene advise is advocated by World health Organization (WHO). We argue that COVID 19 coronovirus can also be airborne in a puff cloud loaded with infected droplets generated by COVID sick person. An elementary calculation shows that a $5~\mu m$ respiratory infected droplet can remain suspended for about 9.0 minutes and a $2~\mu m$ droplet can remain suspended for about an hour! And social distancing advise of 3 feet by WHO and 6 feet by CDC (Centers for Disease Control and Prevention) may not be sufficient in some circumstances as discussed in the text.

positive: COVID-19 attack rate increases with city size The current outbreak of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health and economic threat to interconnected human societies. Until a vaccine is developed, strategies for controlling the outbreak rely on aggressive social distancing. These measures largely disconnect the social network fabric of human societies, especially in urban areas. Here, we estimate the growth rates and reproductive numbers of COVID-19 in US cities from March 14th through March 19th to reveal a power-law scaling relationship to city population size. This means that COVID-19 is spreading faster on average in larger cities with the additional implication that, in an uncontrolled outbreak, larger fractions of the population are expected to become infected in more populous urban areas. We discuss the implications of these observations for controlling the COVID-19 outbreak, emphasizing the need to implement more aggressive distancing policies in larger cities while also preserving socioeconomic activity.

positive: Only strict quarantine measures can curb the coronavirus disease (COVID-19) outbreak in Italy, 2020 Several Italian towns are under lockdown to contain the COVID-19 outbreak. The level of transmission reduction required for physical distancing interventions to mitigate the epidemic is a crucial question. We show that very high adherence to community quarantine (total stay-home policy) and a small household size is necessary for curbing the outbreak in a locked-down town. The larger the household size and amount of time in the public, the longer the lockdown period needed.

positive: Impact of Timing of and Adherence to Social Distancing Measures on COVID-19 Burden in the US: A Simulation Modeling Approach BACKGROUND: Across the U.S., various social distancing measures were implemented to control COVID-19 pandemic. However, there is uncertainty in the effectiveness of such measures for specific regions with varying population demographics and different levels of adherence to social distancing. The objective of this paper is to determine the impact of social distancing measures in unique regions. METHODS: We developed COVid-19 Agent-based simulation Model (COVAM), an agent-based simulation model (ABM) that represents the social network and interactions among the people in a region considering population demographics, limited testing availability, imported infections from outside of the region, asymptomatic disease transmission, and adherence to social distancing measures. We adopted COVAM to represent COVID-19-associated events in Dane County, Wisconsin, Milwaukee metropolitan area, and New York City (NYC). We used COVAM to evaluate the impact of three different aspects of social distancing: 1) Adherence to social distancing measures; 2) timing of implementing social distancing; and 3) timing of easing social distancing. RESULTS: We found that the timing of social distancing and adherence level had a major effect on COVID-19 occurrence. For example, in NYC, implementing social distancing measures on March 5, 2020 instead of March 12, 2020 would have reduced the total number of confirmed cases from 191,984 to 43,968 as of May 30, whereas a 1-week delay in implementing such measures could have increased the number of confirmed cases to 1,299,420. Easing social distancing measures on June 1, 2020 instead of June 15, 2020 in NYC would increase the total number of confirmed cases from 275,587 to 379,858 as of July 31. CONCLUSION: The timing of implementing social distancing measures, adherence to the measures, and timing of their easing have major effects on the number of COVID-19 cases. PRIMARY FUNDING SOURCE: National Institute of Allergy and Infectious Diseases Institute

positive: The SARS-CoV-2 epidemic outbreak: a review of plausible scenarios of containment and mitigation for Mexico We present here several variants of a mathematical model to explore three main issues related to SARS-CoV-2 spread in scenarios similar to those present in Mexico and elsewhere in Latin America. We explore the consequences for travel inside a given region, in this case Mexico, particularly focusing on airplane transportation but attempting to give a gross approximation to terrestrial movement since this is the main form of population movement across geographical areas in the country; then we proceed to study the effect of behavioral changes required to lower transmission by lowering the contact rate and infection probability and lastly, we explore the consequences of disease spread in a population subject to social isolation.These models are not suitable for predictive purposes although some rough predictions can be extracted from them. They are presented as a tool that can serve to explore plausible scenarios of spread and impact, effectiveness and consequences of contention and mitigation policies. Given the early stage at which the epidemic is at the date of writing in Mexico, we hope these ideas can be helpful for the understanding of the importance of isolation, social distancing and screening of the general population.

positive: A feedback SIR (fSIR) model highlights advantages and limitations of infection-based social distancing Transmission rates in epidemic outbreaks vary over time depending on the societal and government response to infections and mortality data, as evidenced in the course of the COVID-19 pandemic. Following a mean field approach that models individuals like molecules in a well-mixed solution, I derive a modified SIR model in which the average daily contacts between susceptible and infected population are reduced based on the known infection levels, capturing the effects of social distancing policies. This approach yields a time-varying reproduction number that is continuously adjusted based on infection information through a negative-feedback term that is equivalent to Holling type II functions in ecology and Hill functions in chemistry and molecular biology. This feedback-adjustment of the transmission rate causes a structural reduction in infection peak, and simulations indicate that such reduction persists even in the presence of information delays. Simulations also show that a distancing policy based on infection data may substantially extend the duration of an epidemic. If the distancing rate is linearly proportional to infections, this model adds a single parameter to the original SIR, making it useful to illustrate the effects of social distancing enforced based on awareness of infections.

positive: Social Distancing Has Merely Stabilized COVID-19 in the US Social distancing measures, with varying degrees of restriction, have been imposed around the world in order to stem the spread of COVID-19. In this work we analyze the effect of current social distancing measures in the United States. We quantify the reduction in doubling rate, by state, that is associated with social distancing. We find that social distancing is associated with a statistically-significant reduction in the doubling rate for all but three states. At the same time, we do not find significant evidence that social distancing has resulted in a reduction in the number of daily confirmed cases. Instead, social distancing has merely stabilized the spread of the disease. We provide an illustration of our findings for each state, including point estimates of the effective reproduction number, R, both with and without social distancing. We also discuss the policy implications of our findings.

positive: Effects of social distancing and isolation on epidemic spreading: a dynamical density functional theory model For preventing the spread of epidemics such as the coronavirus disease COVID-19, social distancing and the isolation of infected persons are crucial. However, existing reaction-diffusion equations for epidemic spreading are incapable of describing these effects. We present an extended model for disease spread based on combining an SIR model with a dynamical density functional theory where social distancing and isolation of infected persons are explicitly taken into account. The model shows interesting nonequilibrium phase separation associated with a reduction of the number of infections, and allows for new insights into the control of pandemics.

positive: A model-based evaluation of the efficacy of COVID-19 social distancing, testing and hospital triage policies We present a stochastic compartmental network model of SARS-CoV-2 and COVID-19 exploring the effects of policy choices in three domains: social distancing, hospital triaging, and testing. We distinguished between high-risk and low-risk members of the population, and modeled differences in social interactions due to context, risk level, infection status, and testing status. The model incorporates many of the currently important characteristics of the disease, including overcapacity in the healthcare system and uncertainties surrounding the proportion and transmission potential of asymptomatic cases. We compared current policy guidelines from public health agencies with alternative options, and investigated the effects of policy decisions on the overall proportion of COVID-19-related deaths. Our results support current policies to contain the outbreak but also suggest possible refinements, including emphasizing the need to reduce public, random contacts more than private contacts, and testing low-risk symptomatic individuals before high-risk symptomatic individuals. Our model furthermore points to interactions among the three policy domains; the efficacy of a particular policy choice depends on other implemented policies. Finally, our results provide an explanation for why societies like Germany, with lower average rates of social contact, are more successful at containing the outbreak than highly social societies such as Italy, despite the implementation of similar policy measures.

positive: Intervention strategies against COVID-19 and their estimated impact on Swedish healthcare capacity Objectives: During March 2020, the COVID-19 pandemic has rapidly spread globally, and non-pharmaceutical interventions are being used to reduce both the load on the healthcare system as well as overall mortality. Design: Individual-based transmission modelling using Swedish demographic and Geographical Information System data and conservative COVID-19 epidemiological parameters. Setting: Sweden Participants: A model to simulate all 10.09 million Swedish residents. Interventions: 5 different non-pharmaceutical public-health interventions including the mitigation strategy of the Swedish government as of 10 April; isolation of the entire household of confirmed cases; closure of schools and non-essential businesses with or without strict social distancing; and strict social distancing with closure of schools and non-essential businesses. Main outcome measures: Estimated acute care and intensive care hospitalisations, COVID-19 attributable deaths, and infections among healthcare workers from 10 April until 29 June. Findings: Our model for Sweden shows that, under conservative epidemiological parameter estimates, the current Swedish public-health strategy will result in a peak intensive-care load in May that exceeds pre-pandemic capacity by over 40-fold, with a median mortality of 96,000 (95% CI 52,000 to 183,000). The most stringent public-health measures examined are predicted to reduce mortality by approximately three-fold. Intensive-care load at the peak could be reduced by over two-fold with a shorter period at peak pandemic capacity. Conclusions: Our results predict that, under conservative epidemiological parameter estimates, current measures in Sweden will result in at least 40-fold over-subscription of pre-pandemic Swedish intensive care capacity, with 15.8 percent of Swedish healthcare workers unable to work at the pandemic peak. Modifications to ICU admission criteria from international norms would further increase mortality.

positive: A decision support system for optimizing the cost of social distancing in order to stop the spread of COVID-19 Currently there are many attempts around the world to use computers, smartphones, tablets and other electronic devices in order to stop the spread of COVID-19. Most of these attempts focus on collecting information about infected people, in order to help healthy people avoid contact with them. However, social distancing decisions are still taken by the governments empirically. That is, the authorities do not have an automated tool to recommend which decisions to make in order to maximize social distancing and to minimize the impact for the economy. In this paper we address the aforementioned problem and we design an algorithm that provides social distancing methods (i.e., what schools, shops, factories, etc. to close) that are efficient (i.e., that help reduce the spread of the virus) and have low impact on the economy. On short: a) we propose several models (i.e., combinatorial optimization problems); b) we show some theoretical results regarding the computational complexity of the formulated problems; c) we give an algorithm for the most complex of the previously formulated problems; d) we implement and test our algorithm; and e) we show an integer linear program formulation for our problem.

positive: Flattening the curve before it flattens us: hospital critical care capacity limits and mortality from novel coronavirus (SARS-CoV2) cases in US counties ABSTRACT Background As of March 26, 2020, the United States had the highest number of confirmed cases of Novel Coronavirus (COVID-19) of any country in the world. Hospital critical care is perhaps the most important medical system choke point in terms of preventing deaths in a disaster scenario such as the current COVID-19 pandemic. We therefore brought together previously established disease modeling estimates of the growth of the COVID-19 epidemic in the US under various social distancing contact reduction assumptions, with local estimates of the potential critical care surge response across all US counties. Methods Estimates of spatio-temporal COVID-19 demand and medical system critical care supply were calculated for all continental US counties. These estimates were statistically summarized and mapped for US counties, regions and urban versus non-urban areas. Estimates of COVID-19 infections and patients needing critical care were calculated from March 24, 2020 to April 24, 2020 for three different estimated population levels - 0%, 25%, and 50% - of contact reduction (through actions such as social distancing). Multiple national public and private datasets were linked and harmonized in order to calculate county-level critical care bed counts that included currently available beds and those that could be made available under four surge response scenarios - very low, low, medium, and high - as well as excess deaths stemming from inaccessible critical care. Results Surge response scenarios ranged from a very low total supply 77,588 critical care beds to a high total of 278,850 critical care beds. Over the four week study period, excess deaths from inaccessible critical care ranged from 24,688 in the very low response scenario to 13,268 in the high response scenario. Northeastern and urban counties were projected to be most affected by excess deaths due to critical care shortages, and counties in New York, Colorado, and Virginia were projected to exceed their critical care bed limits despite high levels of COVID-19 contact reduction. Over the four week study period, an estimated 12,203-19,594 excess deaths stemming from inaccessible critical care could be averted through greater preventive actions such as travel restrictions, publicly imposed contact precautions, greater availability of rapid testing for COVID-19, social distancing, self-isolation when sick, and similar interventions. An estimated 4,029-11,420 excess deaths stemming from inaccessible critical care could be averted through aggressive critical care surge response and preparations, including high clearance of ICU and non-ICU critical care beds and extraordinary measures like using a single ventilator for multiple patients. Conclusions Unless the epidemic curve of COVID-19 cases is flattened over an extended period of time, the US COVID-19 epidemic will cause a shortage of critical care beds and drive up otherwise preventable deaths. The findings here support value of preventive actions to flatten the epidemic curve, as well as the value of exercising extraordinary surge capacity measures to increase access to hospital critical care for severely ill COVID-19 patients.

positive: COVID-19: towards controlling of a pandemic

positive: Outbreak analysis with a logistic growth model shows COVID-19 suppression dynamics in China China experienced an outbreak of a novel coronavirus, SARS-CoV2, from mid-January till mid-March 2020. Here we review the curves of epidemic growth and decline of the virus in China using a phenomenological logistic growth model to summarize the dynamics of the outbreak using three parameters that characterize the epidemic's timing, rate and peak. During the initial phase, the number of cases doubled every 2.7 (range 2.2 - 4.4) days. The rate of increase in the number of reported cases peaked approximately 10 days after suppression measures were started on 23-25 January 2020. The peak in the number of reported sick cases occurred on average 18 days after the start of measures. From the time of starting measures till the peak, the number of cases increased by a factor 38.5 in the province Hubei, and by a factor 9.5 for all of China (range: 6.2-20.4 in the other provinces). Complete suppression took up to 2 months (range: 23-57d.), during which period severe restrictions, social distancing measures, testing and isolation of cases were in place. The suppression of the disease in China has been successful, acting as a beacon of hope for countries outside China where the epidemic is still in a phase of increase and authorities need to decide their course of action.

positive: Investigating duration and intensity of Covid-19 social-distancing strategies The exponential character of the recent Covid-19 outbreak requires a change in strategy from containment to mitigation. Meanwhile, most countries apply social distancing with the objective to keep the number of critical cases below the capabilities of the health care system. Due to the novelty and rapid spread of the virus, an a priori assessment of this strategy was not possible. In this study, we present a model-based systems analysis to assess the effectiveness of social distancing measures in terms of intensity and duration of application. Results show a super-linear scaling between intensity (percent contact reduction) and required duration of application to have an added value (lower fatality rate). This holds true for an effective reproduction of R > 1 and is reverted for R < 1. If R is not reduced below 1, secondary effects of required long-term isolation are likely to unravel the added value of disease mitigation. We recommend an extinction strategy implemented by intense countermeasures.

positive: Forecasting COVID-19 impact in India using pandemic waves Nonlinear Growth Models The ongoing pandemic of the coronavirus disease 2019 (COVID-19) started in China and devastated a vast majority of countries. In India, COVID-19 cases are steadily increasing since January 30, 2020, and the government-imposed lockdown across the country to curtail community transmission. COVID-19 forecasts have played an important role in capturing the probability of infection and the basic reproduction rate. In this study, we predicted some trajectories of trajectories associated with COVID-19 in the coming days in India using an Auto-regression integrated moving average model (ARIMA) and Richards model. By the end of April 2020, the incidence of new cases is predicted to be 5200 (95% CI: 4650 to 6002) through the ARIMA model versus be 6378 (95% CI: 4904 to 7851) Richard model. We estimated that there would be a total of 197 (95% CI: 118 to 277) deaths and drop down in the recovery rates will reach around 501 (95% CI: 245 to 758) by the end of April 2020. These estimates can help to strengthen the implementation of strategies to increase the health system capacity and enactment of social distancing measures all over India.

positive: A Decision Analytic Approach for Social Distancing Policies During the COVID-19 Pandemic The COVID-19 pandemic has become a crucial public health issue in many countries including the United States. In the absence of the right vaccine strain and sufficient antiviral stockpiles on hand, nonpharmaceutical interventions have become valuable public health tools at the early stages of the pandemic and they are employed by many countries across the globe. These interventions are designed to increase social distancing between individuals to reduce the transmission of the virus and eventually dampen the burden on the healthcare system. The virus transmissibility is a function of the average number of contacts individuals have in their communities and it is highly dependent on population density and daily mobility patterns, along with other social factors. These show significant variation across the United States. In this article, we study the effectiveness of social distancing measures in communities with different population density. Specifically, first we show how the empirical estimation of reproduction number differs for two completely different states, thus the experience of the COVID-19 outbreak is drastically different, suggesting different outbreak growth rates in practice. Second, we develop an age-structured compartmental model for simulating the disease spread to demonstrate the variation in the observed outbreak characteristics. We find that early trigger and late trigger options present a trade-off between the peak magnitude and the overall death toll of the outbreak which may also vary across different populations.

positive: Dynamic causal modelling of COVID-19 This technical report describes a dynamic causal model of the spread of coronavirus through a population. The model is based upon ensemble or population dynamics that generate outcomes, like new cases and deaths over time. The purpose of this model is to quantify the uncertainty that attends predictions of relevant outcomes. By assuming suitable conditional dependencies, one can model the effects of interventions (e.g., social distancing) and differences among populations (e.g., herd immunity) to predict what might happen in different circumstances. Technically, this model leverages state-of-the-art variational (Bayesian) model inversion and comparison procedures, originally developed to characterise the responses of neuronal ensembles to perturbations. Here, this modelling is applied to epidemiological populations to illustrate the kind of inferences that are supported and how the model per se can be optimised given timeseries data. Although the purpose of this paper is to describe a modelling protocol, the results illustrate some interesting perspectives on the current pandemic; for example, the nonlinear effects of herd immunity that speak to a self-organised mitigation process.

positive: An age-structured epidemiological model of the Belgian COVID-19 epidemic COVID-19 has prompted many countries to implement extensive social distancing to stop the rapid spread of the virus, in order to prevent overloading health care systems. Yet, the main epidemic parameters of this virus are not well understood. In the absence of broad testing or serological surveillance, it is hard to evaluate or predict the impact of different strategies to exit implemented lock-down measures. An age-structured epidemiological model was developed, which distinguishes between the younger versus older population (e.g. < 65 and >= 65). Because the illness severity is markedly different for these two populations, such a separation is necessary then estimating the model based on death and hospitalization incidence data. The model was applied to data of the Belgian epidemic and used to predict how the epidemic would react to a relaxing of social distancing measures.

positive: Modeling and forecasting the early evolution of the Covid-19 pandemic in Brazil We model and forecast the early evolution of the COVID-19 pandemic in Brazil using Brazilian recent data from February 25, 2020 to March 30, 2020. This early period accounts for unawareness of the epidemiological characteristics of the disease in a new territory, sub-notification of the real numbers of infected people and the timely introduction of social distancing policies to flatten the spread of the disease. We use two variations of the SIR model and we include a parameter that comprises the effects of social distancing measures. Short and long term forecasts show that the social distancing policy imposed by the government is able to flatten the pattern of infection of the COVID-19. However, our results also show that if this policy does not last enough time, it is only able to shift the peak of infection into the future keeping the value of the peak in almost the same value. Furthermore, our long term simulations forecast the optimal date to end the policy. Finally, we show that the proportion of asymptomatic individuals affects the amplitude of the peak of symptomatic infected, suggesting that it is important to test the population.

positive: Inter nation social lockdown versus medical care against COVID-19, a mild environmental insight with special reference to India Infection by coronavirus (CoV-19) has led to emergence of a pandemic called as Coronavirus Disease (COVID-19) that has so far affected about 210 countries. The dynamic data indicate that the pandemic by CoV-19 so far has infected 2,403,963 individuals, and among these 624,698 have recovered while, it has been fatal for 165,229. Without much experience, currently, the medicines that are clinically being evaluated for COVID-19 include chloroquine, hydroxychloroquine, azithromycin, tocilizumab, lopinavir, ritonavir, tocilizumab and corticosteroids. Therefore, countries such as Italy, USA, Spain and France with the most advanced health care system are partially successful to control CoV-19 infection. India being the 2nd largest populous country, where, the healthcare system is underdeveloped, major portion of population follow unhygienic lifestyle, is able to restrict the rate of both infection and death of its citizens from COVID-19. India has followed an early and a very strict social distancing by lockdown and has issued advisory to clean hands regularly by soap and/or by alcohol based sterilizers. Rolling data on the global index of the CoV infection is 13,306, and the index of some countries such as USA (66,148), Italy (175,055), Spain (210,126), France (83,363) and Switzerland (262,122) is high. The index of India has remained very low (161) so far, mainly due to early implementation of social lockdown, social distancing, and sanitizing hands. However, articles on social lockdown as a preventive measure against COVID-19 in PubMed are scanty. It has been observed that social lockdown has also drastic impacts on the environment especially on reduction of NO2 and CO2 emission. Slow infection rate under strict social distancing will offer time to researchers to come up with exact medicines/vaccines against CoV-19. Therefore, it is concluded that stringent social distancing via lockdown is highly important to control COVID-19 and also to contribute for self-regeneration of nature.

positive: Effectiveness of isolation, testing, contact tracing and physical distancing on reducing transmission of SARS-CoV-2 in different settings Isolation of symptomatic cases and tracing of contacts has been used as an early COVID-19 containment measure in many countries, with additional physical distancing measures also introduced as outbreaks have grown. To maintain control of infection while also reducing disruption to populations, there is a need to understand what combination of measures - including novel digital tracing approaches and less intensive physical distancing - may be required to reduce transmission. Using a model of individual-level transmission stratified by setting (household, work, school, other) based on BBC Pandemic data from 40,162 UK participants, we simulated the impact of a range of different testing, isolation, tracing and physical distancing scenarios. As well as estimating reduction in effective reproduction number, we estimated, for a given level of COVID-19 incidence, the number of contacts that would be newly quarantined each day under different strategies. Under optimistic but plausible assumptions, we estimated that combined testing and tracing strategies would reduce transmission more than mass testing or self-isolation alone (50-65% compared to 2-30%). If limits are placed on gatherings outside of home/school/work (e.g. maximum of 4 daily contacts in other settings), then manual contact tracing of acquaintances only could have a similar effect on transmission reduction as detailed contact tracing. In a scenario where there were 10,000 new symptomatic cases per day, we estimated in most contact tracing strategies, 140,000 to 390,000 contacts would be newly quarantined each day. Consistent with previous modelling studies and country-specific COVID-19 responses to date, our analysis estimates that a high proportion of cases would need to self-isolate and a high proportion of their contacts to be successfully traced to ensure an effective reproduction number that is below one in the absence of other measures. If combined with moderate physical distancing measures, self-isolation and contact tracing would be more likely to achieve control.

positive: On the impact of early non-pharmaceutical interventions as containment strategies against the COVID-19 pandemic Background The novel coronavirus SARS-CoV-2 (COVID-19) emerged in December 2019 in Wuhan, China and has spread since then to around 210 countries and territories by April 2020. Consequently, countries have adopted physical distance measures in an attempt to mitigate the uncontrolled spread of the virus. A critical question for policymakers to inform evidence-based practice is if and how physical distance measures slowed the propagation of COVID-19 in the early phase of the pandemic. Methods This study aims to quantify the effects of physical distance mitigation measures on the propagation of the COVID-19 pandemic. Data from John Hopkins University on confirmed cases and testing data from the Our World in Data were used in an interrupted time series analysis to estimate the effects of physical distance measures on the growth rates of the pandemic in 12 countries of Asia, Africa, and Europe. Findings We found that physical distance measures produced a significant decrease in the growth rates of the COVID-19 pandemic in five countries (Austria, Belgium, Italy, Malaysia, and South Korea). The test-positivity rate was significant in understanding the slowing growth rate of COVID-19 cases caused by the mitigation measures, as it provides important context that is missing from analysis based only on confirmed case data. Interpretation Physical distance interventions effectively slowed the progression of the COVID-19 pandemic. The results of this study could inform infectious disease mitigation policies based on physical distance measures by quantifying the differential health outcomes of a pandemic with and without physical distance interventions.

positive: Impact of climate and public health interventions on the COVID-19 pandemic: a prospective cohort study BACKGROUND: It is unclear whether seasonal changes, school closures or other public health interventions will result in a slowdown of the current coronavirus disease 2019 (COVID-19) pandemic. We aimed to determine whether epidemic growth is globally associated with climate or public health interventions intended to reduce transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We performed a prospective cohort study of all 144 geopolitical areas worldwide (375 609 cases) with at least 10 COVID-19 cases and local transmission by Mar. 20, 2020, excluding China, South Korea, Iran and Italy. Using weighted random-effects regression, we determined the association between epidemic growth (expressed as ratios of rate ratios [RRR] comparing cumulative counts of COVID-19 cases on Mar. 27, 2020, with cumulative counts on Mar. 20, 2020) and latitude, temperature, humidity, school closures, restrictions of mass gatherings, and measures of social distancing during an exposure period 14 days previously (Mar. 7 to 13, 2020). RESULTS: In univariate analyses, there were no associations of epidemic growth with latitude and temperature, but weak negative associations with relative humidity (RRR per 10% 0.91, 95% confidence interval [CI] 0.85-0.96) and absolute humidity (RRR per 5 g/m3 0.92, 95% CI 0.85-0.99). Strong associations were found for restrictions of mass gatherings (RRR 0.65, 95% CI 0.53-0.79), school closures (RRR 0.63, 95% CI 0.52-0.78) and measures of social distancing (RRR 0.62, 95% CI 0.45-0.85). In a multivariable model, there was a strong association with the number of implemented public health interventions (p for trend = 0.001), whereas the association with absolute humidity was no longer significant. INTERPRETATION: Epidemic growth of COVID-19 was not associated with latitude and temperature, but may be associated weakly with relative or absolute humidity. Conversely, public health interventions were strongly associated with reduced epidemic growth.

positive: Mitigating COVID-19 outbreak via high testing capacity and strong transmission-intervention in the United States Most models of the COVID-19 pandemic in the United States do not consider geographic variation, and their relevance to public policies is not straightforward. We developed a mathematical model that characterizes infections by state and incorporates inflows and outflows of interstate travelers. Modeling reveals that curbing interstate travel when the disease is already widespread will make little difference. Meanwhile, increased testing capacity (facilitating early identification of infected people and quick isolation) and strict social-distancing and self-quarantine rules are effective in abating the outbreak. The modeling has also produced state-specific information. For example, for New York and Michigan, isolation of persons exposed to the virus needs to be imposed within 2 days to prevent a broad outbreak, whereas for other states this period can be 3.6 days. This model could be used to determine resources needed before safely lifting state policies on social distancing.

positive: Interplay of social distancing and border restrictions for pandemics (COVID-19) via the epidemic Renormalisation Group framework We demonstrate that the epidemic renormalisation group approach to pandemics provides an effective and simple way to investigate the dynamics of disease transmission and spreading across different regions of the world. The framework also allows for reliable projections on the impact of travel limitations and social distancing measures on global epidemic spread. We test and calibrate it on reported cases while unveiling the mechanism that governs the delay in the relative peaks of newly infected cases among different regions of the globe. We discover that social distancing measures are more effective than travel limitations across borders in delaying the epidemic peak. We further provide the link to compartmental models such as the simplistic and time-honoured SIR-like models. We also show how to generalise the framework to account for the interactions across several regions of the world, replacing or complementing large scale simulations.

positive: Fever and mobility data indicate social distancing has reduced incidence of communicable disease in the United States In March of 2020, many U.S. state governments encouraged or mandated restrictions on social interactions to slow the spread of COVID-19, the disease caused by the novel coronavirus SARS-CoV-2 that has spread to nearly 180 countries. Estimating the effectiveness of these social-distancing strategies is challenging because surveillance of COVID-19 has been limited, with tests generally being prioritized for high-risk or hospitalized cases according to temporally and regionally varying criteria. Here we show that reductions in mobility across U.S. counties with at least 100 confirmed cases of COVID-19 led to reductions in fever incidences, as captured by smart thermometers, after a mean lag of 6.5 days ($90\%$ within 3--10 days) that is consistent with the incubation period of COVID-19. Furthermore, counties with larger decreases in mobility subsequently achieved greater reductions in fevers ($p<0.01$), with the notable exception of New York City and its immediate vicinity. These results indicate that social distancing has reduced the transmission of influenza like illnesses, including COVID 19, and support social distancing as an effective strategy for slowing the spread of COVID-19.

positive: COVID-19 Modelling: the Effects of Social Distancing The purpose of this article is to reach all those who find it difficult to become well informed about the repercussions of a lockdown strategy to tackle the COVID-19 pandemic and to spark discussion and thought. Here we use simple stochastic simulations to evaluate different approaches taken to tackle the crisis, along with the efficiency they will hold and the number of casualties they may incur. It is clear that the less strict the social distancing the more time it will take for life to return to normal, and the more lives will be at risk. This is shown through simulations formed by an open sourced code, which allows evaluation of the outcomes from different intervention scenarios or conditions.

positive: Reacting to outbreaks at neighboring localities We study the dynamics of epidemics in a networked metapopulation model. In each subpopulation, representing a locality, disease propagates according to a modified susceptible-exposed-infected-recovered (SEIR) dynamics. We assume that individuals reduce their number of contacts as a function of the weighted sum of cumulative number of cases within the locality and in neighboring localities. The susceptible and exposed (pre-symptomatic and infectious) individuals are allowed to travel between localities undetected. To investigate the combined effects of mobility and contact reduction on disease progression within interconnected localities, we consider a scenario with two localities where disease originates in one and is exported to the neighboring locality via travel of undetected pre-symptomatic individuals. We associate the behavior change at the disease-importing locality due to the outbreak size at the origin with the level of preparedness of the locality. Our results show that restricting mobility is valuable if the importing locality is increasing its level of preparedness with respect to the outbreak size at the origin. Moreover, increased levels of preparedness can yield lower total outbreak size by further reducing the outbreak size at the importing locality, even when the response at the origin is weak. Our results highlight that public health decisions on social distancing at localities with less severe outbreaks should strongly account for potential impact of neighbouring localities with a poor response to the outbreak rather than localities with successful responses.

positive: Analysis of the mitigation strategies for COVID-19: from mathematical modelling perspective In this article, a mathematical model for the transmission of COVID-19 disease is formulated and analysed. It is shown that the model exhibits a backward bifurcation at R0 = 1 when recovered individuals do not develop a permanent immunity for the disease. In the absence of reinfection, it is proved that the model is without backward bifurcation and the disease free equilibrium is globally asymptotically stable for R0 < 1. By using available data, the model is validated and parameter values are estimated. The sensitivity of the value of R0 to changes in any of the parameter values involved in its formula is analysed. Moreover, various mitigation strategies are investigated using the proposed model and it is observed that the asymptomatic infectious group of individuals may play a major role in the re-emergence of the disease in the future. Therefore, it is recommended that in the absence of vaccination, countries need to develop capacities to detect and isolate at least 30% of the asymptomatic infectious group of individuals while treating in isolation at least 50% of symptomatic patients to control the disease.

positive: COVID-ABS: An Agent-Based Model of COVID-19 Epidemic to Simulate Health and Economic Effects of Social Distancing Interventions The COVID-19 pandemic due to the SARS-CoV-2 coronavirus has directly impacted the public health and economy worldwide. To overcome this problem, countries have adopted different policies and non-pharmaceutical interventions for controlling the spread of the virus. This paper proposes the COVID-ABS, a new SEIR (Susceptible-Exposed-Infected-Recovered) agent-based model that aims to simulate the pandemic dynamics using a society of agents emulating people, business and government. Seven different scenarios of social distancing interventions were analyzed, with varying epidemiological and economic effects: (1) do nothing, (2) lockdown, (3) conditional lockdown, (4) vertical isolation, (5) partial isolation, (6) use of face masks, and (7) use of face masks together with 50% of adhesion to social isolation. In the impossibility of implementing scenarios with lockdown, which present the lowest number of deaths and highest impact on the economy, scenarios combining the use of face masks and partial isolation can be the more realistic for implementation in terms of social cooperation. The COVID-ABS model was implemented in Python programming language, with source code publicly available. The model can be easily extended to other societies by changing the input parameters, as well as allowing the creation of a multitude of other scenarios. Therefore, it is a useful tool to assist politicians and health authorities to plan their actions against the COVID-19 epidemic.

positive: Optimal timing for social distancing during an epidemic Social distancing is an effective way to contain the spread of a contagious disease, particularly when facing a novel pathogen and no pharmacological interventions are available. In such cases, conventional wisdom suggests that social distancing measures should be introduced as soon as possible after the beginning of an outbreak to more effectively mitigate the spread of the disease. Using a simple epidemiological model we show that, however, there is in fact an optimal time to initiate a temporal social distancing intervention if the goal is to reduce the final epidemic size or flatten the epidemic curve. The optimal timing depends strongly on the effective reproduction number (R0) of the disease, such that as the R0 increases, the optimal time decreases non-linearly. Additionally, if pharmacological interventions (e.g., a vaccine) become available at some point during the epidemic, the sooner these interventions become available the sooner social distancing should be initiated to maximize its effectiveness. Although based on a simple model, we hope that these insights inspire further investigations within the context of more complex and data-driven epidemiological models, and can ultimately help decision makers to improve temporal social distancing policies to mitigate the spread of epidemics.

positive: Healthcare impact of COVID-19 epidemic in India: A stochastic mathematical model Background: In India, the SARS-CoV2 COVID-19 epidemic has grown to 1,251 cases and 32 deaths as on 30 Mar 2020. The healthcare impact of the epidemic in India was studied with a stochastic mathematical model. Methods: A compartmental SEIR model was developed, in which the flow of individuals through compartments is modeled using a set of differential equations. Different scenarios were modeled with 1000 runs of Monte Carlo simulation each using MATLAB. Hospitalization, ICU requirements and deaths were modeled on SimVoi software. The impact of Non-Pharmacological Interventions (NPI) including social distancing and lockdown on checking the epidemic was estimated. Results: Uninterrupted epidemic in India would have resulted in over 364 million cases and 1.56 million deaths with peak by mid-July. As per the model, at growth rate of 1.15, India is likely to reach approximately 3 million cases by 25 May, implying 125,455 (±18,034) hospitalizations, 26,130 (±3,298) ICU admissions and 13,447 (±1,819) deaths. This would overwhelm India's healthcare system. The model shows that with immediate institution of NPIs, the epidemic might still be checked by mid-April 2020. It would then result in 241,974 (±33,735) total infections, 10,214 (±1,649) hospitalizations, 2,121 (±334) ICU admissions and 1,081(±169) deaths. Conclusion: At current growth rate of epidemic, India's healthcare resources will be overwhelmed by end-May. With the immediate institution of NPIs, total cases, hospitalizations, ICU requirements and deaths can be reduced by almost 90%.

positive: A fundamental model and predictions for the spread of the COVID-19 epidemic The spread of the novel coronavirus is characterized by two phases: (I) a natural exponential growth phase that occurs in the absence of intervention and (II) a regulated growth phase that is affected by enforcing social distancing and isolation. We have developed a fundamental spreading model for the COVID-19 epidemic that has two parameters: the community transmission rate and a metric describing the degree of isolation and social distancing in a given community or region (country, state, county, or city). These two parameters are calibrated to data from the community, so the model uncertainty depends on the quality of the data and ability to test for COVID-19. The model shows that social distancing significantly reduces the epidemic spread and flattens the curve. The model predicts well the spreading trajectory and peak time of new infections for a community of any size and provides an upper estimate for the total number of infections and daily new infection rate for weeks into the future, providing the vital information and lead time needed to prepare for and mitigate the epidemic. The theory has immediate and far-reaching applications for ongoing outbreaks or similar future outbreaks of other emergent infectious diseases.

positive: Nowcasting and Forecasting the Spread of COVID-19 and Healthcare Demand In Turkey, A Modelling Study Abstract Background: A new type of coronavirus (later named Sars-Cov-2) drew attention on 31 December 2019 after the reporting of 27 unidentified pneumonia cases detected in Wuhan, China to the World Health Organization (WHO). Rapid progression of the COVID-19 pandemic has revealed the necessity of epidemic modeling studies to evaluate the course of the epidemic and its burden on the health system. This study aims to estimate the total number of infected people, evaluate the consequences of social interventions on the healthcare system and predict the expected number of cases, intensive care needs, hospitalizations and mortality rates in Turkey according to possible scenarios via the SEIR-based epidemic modeling method. Methods: This study was carried out in three dimensions. In the first, the actual number of people infected in the community has been estimated using the number of deaths in Turkey. In the second, the expected total numbers of infected people, total deaths, total hospitalizations, and intensive care unit (ICU) bed needs have been predicted in case of no intervention. In third, the distribution of the expected number of infected people and deaths, ICU and non-ICU bed needs over time has predicted based on SEIR modeling. A simulator (TURKSAS) has been developed and predictions made in 4 scenarios for Turkey. Results: According to deaths, the estimated number of infected people in Turkey on March 21 was 123,030. In the case of no intervention (1st scenario), the expected total number of infected people is 72,091,595, the total number of deaths is 445,956, the attack rate is 88.1%, the mortality ratio is 0.54%. The ICU bed capacity in Turkey is expected to exceed 4.4-fold and non-ICU bed capacity exceeds 3.21-fold. In 2nd and 3rd scenarios according to the calculations made by considering the social compliance rates of the NPIs, the value of R0 is estimated to decrease from 3 to 1.38 level. Compliance with NPIs makes a 94,303 difference in the expected number of deaths. In both scenarios, the predicted peak value of occupied ICU and non-ICU beds remains below Turkey healthcare capacity. While this study conducted, curfew for >65 and <20 age groups were in force in Turkey. If the curfew is declared for the 21-64 age population (4th scenario), the R0 value drops below 1 (0.98), the expected deaths are 14,230 and the peak values of daily ICU and non-ICU bed demand are below the healthcare capacity. Discussion: Modeling epidemics with assumptions supported by scientific literature and establishing decision support systems based on objective criteria is an important requirement. According to scientific data for the population of Turkey, the situation is not expected to be of worse than predictions presented in the second dimension. Predictions show that 16 million people can be prevented from being infected and 100,000 deaths can be prevented by full compliance with the measures taken. Complete control of the pandemic is possible by keeping R0 below 1. For this, additional evidence-based measures are needed.

positive: Spatial super-spreaders and super-susceptibles in human movement networks As lockdowns and stay-at-home orders start to be lifted across the globe, governments are struggling to establish effective and practical guidelines to reopen their economies. In dense urban environments with people returning to work and public transportation resuming full capacity, enforcing strict social distancing measures will be extremely challenging, if not practically impossible. Governments are thus paying close attention to particular locations that may become the next cluster of disease spreading. Indeed, certain places, like some people, can be"super-spreaders."Is a bustling train station in a central business district more or less susceptible and vulnerable as compared to teeming bus interchanges in the suburbs? Here, we propose a quantitative and systematic framework to identify spatial super-spreaders and the novel concept of super-susceptibles, i.e. respectively, places most likely to contribute to disease spread or to people contracting it. Our proposed data-analytic framework is based on the daily-aggregated ridership data of public transport in Singapore. By constructing the directed and weighted human movement networks and integrating human flow intensity with two neighborhood diversity metrics, we are able to pinpoint super-spreader and super-susceptible locations. Our results reveal that most super-spreaders are also super-susceptibles and that counterintuitively, busy peripheral bus interchanges are riskier places than crowded central train stations. Our analysis is based on data from Singapore, but can be readily adapted and extended for any other major urban center. It therefore serves as a useful framework for devising targeted and cost-effective preventive measures for urban planning and epidemiological preparedness.

positive: If long-term suppression is not possible, how do we minimize mortality for COVID-19 and other emerging infectious disease outbreaks? If COVID-19 containment policies fail and social distancing measures cannot be sustained until vaccines becomes available, the next best approach is to use interventions that reduce mortality and prevent excess infections while allowing low-risk individuals to acquire immunity through natural infection until population level immunity is achieved. In such a situation, allowing some infections to occur in lower-risk groups might lead to an overall greater reduction in mortality than trying to protect everyone equally.

positive: Investigating time, strength, and duration of measures in controlling the spread of COVID-19 using a networked meta-population model Policy makers around the world are facing unprecedented challenges in making decisions on when and what degrees of measures should be implemented to tackle the COVID-19 pandemic. Here, using a nationwide mobile phone dataset, we developed a networked meta-population model to simulate the impact of intervention in controlling the spread of the virus in China by varying the effectiveness of transmission reduction and the timing of intervention start and relaxation. We estimated basic reproduction number and transition probabilities between health states based on reported cases. Our model demonstrates that both the time of initiating an intervention and its effectiveness had a very large impact on controlling the epidemic, and the current Chinese intense social distancing intervention has reduced the impact substantially but would have been even more effective had it started earlier. The optimal duration of the control measures to avoid resurgence was estimated to be 2 months, although would need to be longer under less effective controls. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11071-020-05769-2) contains supplementary material, which is available to authorized users.

positive: Vertical social distancing policy is ineffective to contain the COVID-19 pandemic Considering numerical simulations, this study shows that the so-called vertical social distancing health policy is ineffective to contain the COVID-19 pandemic. We present the SEIR-Net model, for a network of social group interactions, as a development of the classic mathematical model of SEIR epidemics (Susceptible-Exposed-Infected (symptomatic and asymptomatic)-Removed). In the SEIR-Net model, we can simulate social contacts between groups divided by age groups and analyze different strategies of social distancing. In the vertical distancing policy, only older people are distanced, whereas in the horizontal distancing policy all age groups adhere to social distancing. These two scenarios are compared to a control scenario in which no intervention is made to distance people. The vertical distancing scenario is almost as bad as the control, both in terms of people infected and in the acceleration of cases. On the other hand, horizontal distancing, if applied with the same intensity in all age groups, significantly reduces the total infected people "flattening the disease growth curve". Our analysis considers the city of Belo Horizonte, Minas Gerais State, Brazil, but similar conclusions apply to other cities as well. Code implementation of the model in R-language is provided in the supplementary material.

positive: Spread of the Novel Coronavirus (SARS-CoV-2): Modeling and Simulation of Control Strategies The coronavirus disease 2019 (COVID-19) is spreading throughout the world and all healthcare systems are loaded beyond its capacity. The virus is named as SARS-CoV-2. In this situation, rational decisions need to be made on how the care is provided for patients with COVID-19. The Incidence report, general symptoms and readily available testing kits, different control strategies, the basic compartmental model, and some of the current research on the epidemiology of the disease are discussed and previously published models are reviewed. Modeling this disease helps in understanding the spread, and predict its future to evaluate different control strategies (Social Distancing, Contact Tracing and Hospitalization). Compartmental modeling framework is used in this work. The non-linear equations are formulated and fitted to the cumulative case and mortality data. Analytical analysis along with uncertainty analysis and sensitivity analysis is performed, and the conditions to achieve disease free equilibrium is evaluated. Finally, Different control strategies are simulated to show their importance. This paper aims to shows the advantage of mathematical modeling and their simulations in times like now, during which the COVID-19 spreading like wildfire. It also includes Pre-symptomatic and asymptomatic individuals in the modeling. The simulations are performed for the model fit to Cumulative Case and Mortality data in the United States of America. The Reproduction number is found to be 2.71914.

positive: Comparative Analysis of COVID-19 Transmission Patterns in Three Chinese Regions vs. South Korea,Italy and Iran Background: The outbreak of Coronavirus 2019 (COVID-19) began in January 2020 in the city of Wuhan (Hubei province, China). It took about 2 months for China to get this infectious disease under control in its epicenter at Wuhan. Since February 2020, COVID-19 has been spreading around the world, becoming widespread in a number of countries. The timing and nature of government actions in response to the pandemic has varied from country to country, and their role in affecting the spread of the disease has been debated. Method: The present study proposed a modified susceptible-exposed-infected-removed model (SEIR) model to perform a comparative analysis of the temporal progress of disease spread in six regions worldwide: three Chinese regions (Zhejiang, Guangdong and Xinjiang) vs. three countries (South Korea, Italy and Iran). For each region we developed detailed timelines of reported infections and outcomes, along with government-implemented measures to enforce social distancing. Simulations of the imposition of strong social distancing measures were used to evaluate the impact that these measures might have had on the duration and severity of COVID-19 outbreaks in the three countries. Results: The main results of this study are as follows: (a) an empirical COVID-19 growth law provides an excellent fit to the disease data in all study regions and potentially could be of more general validity; (b) significant differences exist in the spread characteristics of the disease among the three regions of China and between the three regions of China and the three countries; (c) under the control measures implemented in the Chinese regions (including the immediate quarantine of infected patients and their close contacts, and considerable restrictions on social contacts), the transmission rate of COVID-19 followed a modified normal distribution function, and it reached its peak after 1 to 2 days and then was reduced to zero 11, 11 and 18 days after a 1st-Level Response to Major Public Health Emergency was declared in Zhejiang, Guangdong and Xinjiang, respectively; moreover, the epidemic control times in Zhejiang, Guangdong and Xinjiang showed that the epidemic reached an "inflection point" after 9, 12 and 17 days, respectively, after a 1st-Level Response was issued; (d) an empirical COVID-19 law provided an excellent fit to the disease data in the six study regions, and the law can be potentially of more general validity; and (e) the curves of infected cases in South Korea, Italy and Iran would had been significantly flattened and shrunken at a relatively earlier stage of the epidemic if similar preventive measures as in the Chinese regions had been also taken in the above three countries on February 25th, February 25th and March 8th, respectively: the simulated maximum number of infected individuals in South Korea, Italy and Iran would had been 4480 cases (March 9th, 2020), 2335 cases (March 10th) and 6969 cases (March 20th), instead of the actual (reported) numbers of 7212 cases (March 9th), 8514 cases (March 10th, 2020) and 11466 cases (March 20th), respectively; moreover, up to March 29th, the simulated reduction in the accumulated number of infected cases would be 1585 for South Korea, 93490 for Italy and 23213 for Iran, respectively, accounting for 16.41% (South Korea), 95.70% (Italy) and 60.59% (Iran) of the accumulated number of actual reported infected cases. Conclusions: The implemented measures in China were very effective for controlling the spread of COVID-19. These measures should be taken as early as possible, including the early identification of all infection sources and eliminating transmission pathways. Subsequently, the number of infected cases can be controlled at a low level, and existing medical resources could be sufficient for maintaining higher cure rates and lower mortality rate compared to the current situations in these countries. The proposed model can account for these prevention and control measures by properly adjusting its parameters, it computes the corresponding variations in disease transmission rate during the outbreak period, and it can provide valuable information for public health decision-making purposes.

positive: Human agency and infection rates: implications for social distancing during epidemics Social distancing is an important measure in controlling epidemics. This paper presents a simple theoretical model focussed on the implications of the wide range in interaction rates between individuals, both within the workplace and in the social setting. The model is based on well-mixed populations and so is not intended for studying geographic spread. The model shows that epidemic growth rate is largely determined by the upper interactivity quantiles of society, implying that the most efficient methods of epidemic control are interaction capping approaches rather than overall reductions in interaction. The theoretical model can also be applied to look at the dynamics of epidemic progression under various scenarios. The theoretical model suggests that with no intervention herd immunity would be achieved with a lower overall infection rate than if variation in interaction rate is ignored, because by this stage almost all the most interactive members of society would have had the infection; however the overall mortality with such an approach is very high. Scenarios for mitigation and suppression suggest that, by using interactivity capping, it should be possible to control an epidemic without extreme sanctions on the majority of the population if R0 of the uncontrolled infection is 2.4. However to control the infection rate to a specific level will always require the switching on and off of measures and for this reason eradication is likely to be a less costly policy in the long run. While social distancing alone can be used for eradication it is not be a good mechanism on its own to prevent reinfection. The use of robust testing, quarantining, and contact tracing would strengthen any social distancing measures, speed up eradication, and be a better tool for prevention of infection or reinfection.

positive: Estimating the number of SARS-CoV-2 infections and the impact of social distancing in the United States Understanding the number of individuals who have been infected with the novel coronavirus SARS-CoV-2, and the extent to which social distancing policies have been effective at limiting its spread, are critical for effective policy going forward. Here we present estimates of the extent to which confirmed cases in the United States undercount the true number of infections, and analyze how effective social distancing measures have been at mitigating or suppressing the virus. Our analysis uses a Bayesian model of COVID-19 fatalities with a likelihood based on an underlying differential equation model of the epidemic. We provide analysis for four states with significant epidemics: California, Florida, New York, and Washington. Our short-term forecasts suggest that these states may be following somewhat different trajectories for growth of the number of cases and fatalities.

positive: Fighting against the common enemy of COVID-19: a practice of building a community with a shared future for mankind The outbreak of coronavirus disease 2019 (COVID-19) has caused more than 80 813 confirmed cases in all provinces of China, and 21 110 cases reported in 93 countries of six continents as of 7 March 2020 since middle December 2019. Due to biological nature of the novel coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with faster spreading and unknown transmission pattern, it makes us in a difficulty position to contain the disease transmission globally. To date, we have found it is one of the greatest challenges to human beings in fighting against COVID-19 in the history, because SARS-CoV-2 is different from SARS-CoV and MERS-CoV in terms of biological features and transmissibility, and also found the containment strategies including the non-pharmaceutical public health measures implemented in China are effective and successful. In order to prevent a potential pandemic-level outbreak of COVID-19, we, as a community of shared future for mankind, recommend for all international leaders to support preparedness in low and middle income countries especially, take strong global interventions by using old approaches or new tools, mobilize global resources to equip hospital facilities and supplies to protect noisome infections and to provide personal protective tools such as facemask to general population, and quickly initiate research projects on drug and vaccine development. We also recommend for the international community to develop better coordination, cooperation, and strong solidarity in the joint efforts of fighting against COVID-19 spreading recommended by the joint mission report of the WHO-China experts, against violating the International Health Regulation (WHO, 2005), and against stigmatization, in order to eventually win the battle against our common enemy — COVID-19.

positive: Intervention Serology and Interaction Substitution: Modeling the Role of ‘Shield Immunity’ in Reducing COVID-19 Epidemic Spread The COVID-19 pandemic has precipitated a global crisis, with more than 690,000 confirmed cases and more than 33,000 confirmed deaths globally as of March 30, 2020 [1–4]. At present twOfficentral public health control strategies have emerged: mitigation and suppression (e.g, [5]). Both strategies focus on reducing new infections by reducing interactions (and both raise questions of sustainability and long-term tactics). Complementary to those approaches, here we develop and analyze an epidemiological intervention model that leverages serological tests [6, 7] to identify and deploy recovered individuals as focal points for sustaining safer interactions via interaction substitution, i.e., to develop what we term ‘shield immunity’ at the population scale. Recovered individuals, in the present context, represent those who have developed protective, antibodies to SARS-CoV-2 and are no longer shedding virus [8]. The objective of a shield immunity strategy is to help sustain the interactions necessary for the functioning of essential goods and services (including but not limited to tending to the elderly [9], hospital care, schools, and food supply) while decreasing the probability of transmission during such essential interactions. We show that a shield immunity approach may significantly reduce the length and reduce the overall burden of an outbreak, and can work synergistically with social distancing. The present model highlights the value of serological testing as part of intervention strategies, in addition to its well recognized roles in estimating prevalence [10, 11] and in the potential development of plasma-based therapies [12–15].

positive: Predictions of COVID-19 dynamics in the UK: short-term forecasting and analysis of potential exit strategies Background: Efforts to suppress transmission of SARS-CoV-2 in the UK have seen non-pharmaceutical interventions being invoked. The most severe measures to date include all restaurants, pubs and cafes being ordered to close on 20th March, followed by a "stay at home" order on the 23rd March and the closure of all non-essential retail outlets for an indefinite period. Government agencies are presently analysing how best to develop an exit strategy from these measures and to determine how the epidemic may progress once measures are lifted. Mathematical models are currently providing short and long term forecasts regarding the future course of the COVID-19 outbreak in the UK to support evidence-based policymaking. Methods: We present a deterministic, age-structured transmission model that uses real-time data on confirmed cases requiring hospital care and mortality to provide up-to-date predictions on epidemic spread in ten regions of the UK. We simulated a suite of scenarios to assess the impact of differing approaches to relaxing social distancing measures from 7th May 2020, on the estimated number of patients requiring inpatient and critical care treatment, and deaths. With regard to future epidemic outcomes, we investigated the impact of reducing compliance, ongoing shielding of elder age groups, reapplying stringent social distancing measures using region based triggers and the role of asymptomatic transmission. Findings: We find that significant relaxation of social distancing measures on 7th May can lead to a rapid resurgence of COVID-19 disease and the health system being quickly overwhelmed by a sizeable, second epidemic wave. In all considered age-shielding based strategies, we projected serious demand on critical care resources during the course of the pandemic. The reintroduction and release of strict measures on a regional basis, based on ICU bed occupancy, results in a long epidemic tail, until the second half of 2021, but ensures that the health service is protected by reintroducing social distancing measures for all individuals in a region when required. Conclusions: Our work supports the decision to apply stringent non-pharmaceutical measures in March 2020 to suppress the epidemic. We provide strong evidence to support the need for a cautious, measured approach to relaxation of lockdown measures, to protect the most vulnerable members of society and support the health service through subduing demand on hospital beds, in particular bed occupancy in intensive care units.

positive: A model for COVID-19 with isolation, quarantine and testing as control measures In this article we propose a compartmental model for the dynamics of Coronavirus Disease 2019 (COVID-19). We take into account the presence of asymptomatic infections and the main policies that have been adopted so far to contain the epidemic: isolation (or social distancing) of a portion of the population, quarantine for confirmed cases and testing. We model isolation by separating the population in two groups: one composed by key-workers that keep working during the pandemic and have a usual contact rate, and a second group consisting of people that are enforced/recommended to stay at home. We refer to quarantine as strict isolation, and it is applied to confirmed infected cases. In the proposed model, the proportion of people in isolation, the level of contact reduction and the testing rate are control parameters that can vary in time, representing policies that evolve in different stages. We obtain an explicit expression for the basic reproduction number R0 in terms of the parameters of the disease and of the control policies. In this way we can quantify the effect that isolation and testing have in the evolution of the epidemic. We present a series of simulations to illustrate different realistic scenarios. From the expression of R0 and the simulations we conclude that isolation (social distancing) and testing among asymptomatic cases are fundamental actions to control the epidemic, and the stricter these measures are and the sooner they are implemented, the more lives can be saved. Additionally, we show that people that remain in isolation significantly reduce their probability of contagion, so risk groups should be recommended to maintain a low contact rate during the course of the epidemic.

positive: Comparative Impact of Individual Quarantine vs. Active Monitoring of Contacts for the Mitigation of COVID-19: a modelling study BACKGROUND: Voluntary individual quarantine and voluntary active monitoring of contacts are core disease control strategies for emerging infectious diseases, such as COVID-19. Given the impact of quarantine on resources and individual liberty, it is vital to assess under what conditions individual quarantine can more effectively control COVID-19 than active monitoring. As an epidemic grows, it is also important to consider when these interventions are no longer feasible, and broader mitigation measures must be implemented. METHODS: To estimate the comparative efficacy of these case-based interventions to control COVID-19, we fit a stochastic branching model to reported parameters for the dynamics of the disease. Specifically, we fit to the incubation period distribution and each of two sets of the serial interval distribution: a shorter one with a mean serial interval of 4.8 days and a longer one with a mean of 7.5 days. To assess variable resource settings, we consider two feasibility settings: a high feasibility setting with 90% of contacts traced, a half-day average delay in tracing and symptom recognition, and 90% effective isolation; and low feasibility setting with 50% of contacts traced, a two-day average delay, and 50% effective isolation. FINDINGS: Our results suggest that individual quarantine in high feasibility settings where at least three-quarters of infected contacts are individually quarantined contains an outbreak of COVID-19 with a short serial interval (4.8 days) 84% of the time. However, in settings where this performance is unrealistically high and the outbreak continues to grow, so too will the burden of the number of contacts traced for active monitoring or quarantine. When resources are prioritized for scalable interventions such as social distancing, we show active monitoring or individual quarantine of high-risk contacts can contribute synergistically to mitigation efforts. INTERPRETATION: Our model highlights the urgent need for more data on the serial interval and the extent of presymptomatic transmission in order to make data-driven policy decisions regarding the cost-benefit comparisons of individual quarantine vs. active monitoring of contacts. To the extent these interventions can be implemented they can help mitigate the spread of COVID-19.

positive: Transmission of SARS-CoV-2 in Georgia, USA, 2020 Objective: SARS-CoV-2 has significantly impacted Georgia, USA including two major hotspots, Metro Atlanta and Dougherty County in southwestern Georgia. With government deliberations about relaxing social distancing measures, it is important to understand the trajectory of the epidemic in the state of Georgia. Methods: We collected daily cumulative incidence of confirmed COVID-19 cases in Georgia. We estimated the reproductive number (Re) of the COVID-19 epidemic on April 18 and May 2 by characterizing the initial growth phase of the epidemic using the generalized-growth model. Results: The data presents a sub-exponential growth pattern in the cumulative incidence curves. On April 18, 2020, Re was estimated as 1.20 (95% CI: 1.10, 1.20) for the state of Georgia, 1.10 (95% CI: 1.00, 1.20) for Dougherty County, and 1.20 (95% CI: 1.10, 1.20) for Metro Atlanta. Extending our analysis to May 2, 2020, Re estimates decreased to 1.10 (95% CI: 1.10, 1.10) for the state of Georgia, 1.00 (95% CI: 1.00, 1.10) for Dougherty County, and 1.10 (95% CI: 1.10, 1.10) for Metro Atlanta. Conclusions: Transmission appeared to be decreasing after the implementation of social distancing measures. However, these results should be interpreted with caution when considering relaxing control measures due to low testing rates.

positive: Mathematical modeling of COVID-19 transmission and mitigation strategies in the population of Ontario, Canada Background: We evaluated how non-pharmaceutical interventions could be used to control the COVID-19 pandemic and reduce the burden on the healthcare system Methods: Using an age-structured compartmental model of COVID-19 transmission in the population of Ontario, Canada, we compared a base case with limited testing, isolation, and quarantine to scenarios with: enhanced case finding;restrictive social distancing measures;or a combination of enhanced case finding and less restrictive social distancing Interventions were either implemented for fixed durations or dynamically cycled on and off, based on projected ICU bed occupancy We present median and credible intervals (CrI) from 100 replicates per scenario using a two-year time horizon Results: We estimated that 56% (95% CrI: 42-63%) of the Ontario population would be infected over the course of the epidemic in the base case At the epidemic peak, we projected 107,000 (95% CrI: 60,760-149,000) cases in hospital and 55,500 (95% CrI: 32,700-75,200) cases in ICU For fixed duration scenarios, all interventions were projected to delay and reduce the height of the epidemic peak relative to the base case, with restrictive social distancing estimated to have the greatest effect Longer duration interventions were more effective Dynamic interventions were projected to reduce the proportion of the population infected at the end of the two-year period Dynamic social distancing interventions could reduce the median number of cases in ICU below current estimates of Ontario's ICU capacity Interpretation: Without significant social distancing or a combination of moderate social distancing with enhanced case finding, we project that ICU resources would be overwhelmed Dynamic social distancing could maintain health system capacity and also allow periodic psychological and economic respite for populations ### Competing Interest Statement The authors have declared no competing interest ### Funding Statement The research was supported by a grant to DNF from the Canadians Institutes for Health Research (2019 COVID-19 rapid researching funding OV4-170360) ### Author Declarations All relevant ethical guidelines have been followed;any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials gov I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance) Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable Yes Data are available from the corresponding author on request

positive: COVID-19 mathematical model reopening scenarios for Sao Paulo - Brazil The objective of the current investigation was to produce a generalized computational model to predict consequences of various reopening scenarios on COVID-19 infections rates and available hospital resources in Sao Paulo - Brazil. We were able to use the Susceptible-Exposed-Infected-Recovered (SEIR) model to fit both accumulated death data and corrected accumulated cases data associated with COVID-19 for both Brazil and the state of Sao Paulo. In addition, we were able to simulate the consequences of reopening under different possible scenarios in Brazil, in special for the state of Sao Paulo. The model was able to provide a predicted scenario in which reopening could occur with minimal impact on human life considering people careful behavior in combination with continued social distancing measures.

positive: The effect of multiple interventions to balance healthcare demand for controlling COVID-19 outbreaks: a modelling study Background Recent outbreak of a novel coronavirus disease 2019 (COVID-19) has led a rapid global spread around the world. For controlling COVID-19 outbreaks, many countries have implemented two non-pharmaceutical interventions: suppression like immediate lock-downsin cities at epicentre of outbreak; or mitigation that slows down but not stopping epidemic for reducing peak healthcare demand. Both interventions have apparent pros and cons; the effectiveness of any one intervention in isolation is limited. It is crucial but hard to know how and when to take which level of interventions tailored to the specific situation in each country. We aimed to conduct a feasibility study for robustly accessing the effect of multiple interventions to control the number and distribution of infections, growth of deaths, peaks and lengths of COVID-19 breakouts in the UK and other European countries, accounting for balance of healthcare demand. Methods We developed a model to attempt to infer the impact of mitigation, suppression and multiple rolling interventions for controlling COVID-19 outbreaks in the UK. Our model assumed that each intervention has equivalent effect on the reproduction number R across countries and over time; where its intensity was presented by average-number contacts with susceptible individuals as infectious individuals; early immediate intensive intervention led to increased health need and social anxiety. We considered two important features: direct link between Exposed and Recovered population, and practical healthcare demand by separation of infections into mild, moderate and critical cases. Our model was fitted and calibrated with date on cases of COVID-19 in Wuhan to estimate how suppression intervention impacted on the number and distribution of infections, growth of deaths over time during January 2020, and April 2020. We combined the calibrated model with data on the cases of COVID-19 in London and non-London regions in the UK during February 2020 and April 2020 to estimate the number and distribution of infections, growth of deaths, and healthcare demand by using multiple interventions. We applied the calibrated model to the prediction of infection and healthcare resource changes in other 6 European countries based on actual measures they have implemented during this period. Findings We estimated given that 1) By the date (5th March 2020) of the first report death in the UK, around 7499 people would have already been infected with the virus. After taking suppression on 23rd March, the peak of infection in the UK would have occurred between 28th March and 4th April 2020; the peak of death would have occurred between 18th April and 24th April 2020. 2) By 29th April, no significant collapse of health system in the UK have occurred, where there have been sufficient hospital beds for severe and critical cases. But in the Europe, Italy, Spain and France have experienced a 3 weeks period of shortage of hospital beds for severe and critical cases, leading to many deaths outside hospitals. 3) One optimal strategy to control COVID-19 outbreaks in the UK is to take region-level specific intervention. If taking suppression with very high intensity in London from 23rd March 2020 for 100 days, and 3 weeks rolling intervention between very high intensity and high intensity in non-London regions. The total infections and deaths in the UK were limited to 9.3 million and 143 thousand; the peak time of healthcare demand was due to the 96th day (12th May, 2020), where it needs hospital beds for 68.9 thousand severe and critical cases. 4) If taking a simultaneous 3 weeks rolling intervention between very high intensity and high intensity in all regions of the UK, the total infections and deaths increased slightly to 10 million and 154 thousand; the peak time of healthcare occurs at the 97th day (13th May, 2020), where it needs equivalent hospital beds for severe and critical cases of 73.5 thousand. 5) If too early releasing intervention intensity above moderate level and simultaneously implemented them in all regions of the UK, there would be a risk of second wave, where the total infections and deaths in the UK possibly reached to 23.4 million and 897 thousand. Interpretation: Considering social and economic costs in controlling COVID-19 outbreaks, long-term suppression is not economically viable. Our finding suggests that rolling intervention is an optimal strategy to effectively and efficiently control COVID-19 outbreaks in the UK and potential other countries for balancing healthcare demand and morality ratio. As for huge difference of population density and social distancing between different regions in the UK, it is more appropriate to implement regional level specific intervention with varied intensities and maintenance periods. We suggest an intervention strategy to the UK that take a consistent suppression in London for 100 days and 3 weeks rolling intervention in other regions. This strategy would reduce the overall infections and deaths of COVID-19 outbreaks, and balance healthcare demand in the UK.

positive: Review and analysis of current responses to COVID-19 in Indonesia: Period of January to March 2020 Abstract The world is under pressure from the novel COVID-19 pandemic. Indonesia is the fourth most populous country in the world and predicted to be affected significantly over a longer time period. Our paper aims to provide detailed reporting and analyses of the present rapid responses to COVID-19, between January and March 2020, in Indonesia. We particularly highlight responses taken by the governments, non-government organisations and the community. We outline gaps and limitations in the responses, based on our rapid analysis of media contents, from government speeches and reports, social and mass media platforms. We present five recommendations toward more rapid, effective, and comprehensive responses.

positive: Mobility traces and spreading of COVID-19 We use human mobility models, for which we are experts, and attach a virus infection dynamics to it, for which we are not experts but have taken it from the literature, including recent publications. This results in a virus spreading dynamics model. The results should be verified, but because of the current time pressure, we publish them in their current state. Recommendations for improvement are welcome. We come to the following conclusions: 1. Complete lockdown works. About 10 days after lockdown, the infection dynamics dies down. This assumes that lockdown is complete, which can be guaranteed in the simulation, but not in reality. Still, it gives strong support to the argument that it is never too late for complete lockdown. 2. As a rule of thumb, we would suggest complete lockdown no later than once 10% of hospital capacities available for COVID-19 are in use, and possibly much earlier. This is based on the following insights: a. Even after lockdown, the infection dynamics continues at home, leading to another tripling of the cases before the dynamics is slowed. b. There will be many critical cases coming from people who were infected before lockdown. Because of the exponential growth dynamics, their number will be large. c. Researchers with more detailed disease progression models should improve upon these statements. 3. Our simulations say that complete removal of infections at child care, primary schools, workplaces and during leisure activities will not be enough to sufficiently slow down the infection dynamics. It would have been better, but still not sufficient, if initiated earlier. 4. Infections in public transport play an important role. In the simulations shown later, removing infections in the public transport system reduces the infection speed and the height of the peak by approximately 20%. Evidently, this depends on the infection parameters, which are not well known. -- This does not point to reducing public transport capacities as a reaction to the reduced demand, but rather use it for lower densities of passengers and thus reduced infection rates. 5. In our simulations, removal of infections at child care, primary schools, workplaces, leisure activities, and in public transport may barely have been sufficient to control the infection dynamics if implemented early on. Now according to our simulations it is too late for this, and (even) harsher measures will have to be initiated until possibly a return to such a restrictive, but still somewhat functional regime will again be possible. Evidently, all of these results have to be taken with care. They are based on preliminary infection parameters taken from the literature, used inside a model that has more transport/movement details than all others that we are aware of but still not enough to describe all aspects of reality, and suffer from having to write computer code under time pressure. Optimally, they should be confirmed independently. Short of that, given current knowledge we believe that they provide justification for "complete lockdown" at the latest when about 10% of available hospital capacities for COVID-19 are in use (and possibly earlier; we are no experts of hospital capabilities). What was not investigated in detail in our simulations was contact tracing, i.e. tracking down the infection chains and moving all people along infection chains into quarantine. The case of Singapore has so far shown that this may be successful. Preliminary simulation of that tactic shows that it is difficult to implement for COVID-19, since the incubation time is rather long, people are contagious before they feel sick, or maybe never feel sufficiently sick at all. We will investigate in future work if and how contact tracing can be used together with a restrictive, but not totally locked down regime. When opening up after lockdown, it would be important to know the true fraction of people who are already immune, since that would slow down the infection dynamics by itself. For Wuhan, the currently available numbers report that only about 0.1% of the population was infected, which would be very far away from "herd immunity". However, there have been and still may be many unknown infections.

positive: Effects of Population Co-location Reduction on Cross-county Transmission Risk of COVID-19 in the United States The rapid spread of COVID-19 in the United States has imposed a major threat to public health, the real economy, and human well-being. With the absence of effective vaccines, the preventive actions of social distancing and travel reduction are recognized as essential non-pharmacologic approaches to control the spread of COVID-19. Prior studies demonstrated that human movement and mobility drove the spatiotemporal distribution of COVID-19 in China. Little is known, however, about the patterns and effects of co-location reduction on cross-county transmission risk of COVID-19. This study utilizes Facebook co-location data for all counties in the United States from March to early May 2020. The analysis examines the synchronicity and time lag between travel reduction and pandemic growth trajectory to evaluate the efficacy of social distancing in ceasing the population co-location probabilities, and subsequently the growth in weekly new cases. The results show that the mitigation effects of co-location reduction appear in the growth of weekly new cases with one week of delay. Furthermore, significant segregation is found among different county groups which are categorized based on numbers of cases. The results suggest that within-group co-location probabilities remain stable, and social distancing policies primarily resulted in reduced cross-group co-location probabilities (due to travel reduction from counties with large number of cases to counties with low numbers of cases). These findings could have important practical implications for local governments to inform their intervention measures for monitoring and reducing the spread of COVID-19, as well as for adoption in future pandemics. Public policy, economic forecasting, and epidemic modeling need to account for population co-location patterns in evaluating transmission risk of COVID-19 across counties.

positive: COVID-19 Epidemic in Switzerland: Growth Prediction and Containment Strategy Using Artificial Intelligence and Big Data Using a previously developed agent-based artificial intelligence simulation platform (EnerPol) coupled with Big Data, the evolution and containment of COVID-19 in Switzerland is examined. The EnerPol platform has been used in a broad range of case studies in different sectors in all of Europe, USA, Japan, South Korea and sub Saharan Africa over the last 10 years. In the present study, the entire Swiss population (8.57 million people), including cross-border commuters, and the entire Swiss public and private transport network that is simulated to assess transmission of the COVID-19 virus. The individual contacts within the population, and possible transmission pathways, are established from a simulation of daily activities that are calibrated with micro-census data. Various governmental interventions with regards to closures and social distancing are also implemented. The epidemiology of the COVID-19 virus is based on publicly available statistical data and adapted to Swiss demographics. The predictions estimate that between 22 February and 11 April 2020, there will be 720 deaths from 83300 COVID-19 cases, and 73300 will have recovered; our preliminary variability in these estimates is about 21% over the aforementioned period. In the absence of governmental intervention, 42.7% of the Swiss population would have been infected by 25 April 2020 compared to our prediction of a 1% infection over this time period, saving thousands of lives. It is argued that future scenarios regarding relaxation of the lockdown should be carefully simulated, as by 19 April 2020, there will still remain a substantial number of infected individuals, who could retrigger a second spread of COVID-19. Through the use of a digital tool, such as Enerpol, to evaluate in a data-driven manner the impacts of various policy scenarios, the most effective measures to mitigate a spread of COVID-19 can be devised while we await the deployment of large-scale vaccination for the population globally. By tailoring the spatio-temporal characteristics of the spread to match the capacity of local healthcare facilities, appropriate logistic needs can be determined, in order not to overwhelm the health care services across the country.

positive: Social distancing: A non-pharmacological intervention for COVID-19 Social distancing is one of the non-pharmacological measures to contain the infection of COVID-19. At this point in time, no vaccine is available to prevent the infection, no effective drugs are available to prevent and treat the disease, and none of the communities have acquired herd immunity. Various models have shown positive impact of social distancing, provided its implementation on vast majority of the population over a long period of time. Its effect is manifold. Besides flattening the curve, it impacts the political, fiscal, social, economic aspects of the society, along with socially vulnerable and economically underprivileged population. It becomes obsolete after the population develops herd immunity subsequent to widespread infection in the community, or after effective mass immunisation or specific drugs for its control, cure and prevention are available widely.

positive: Significant Relaxation of SARS-CoV-2-Targeted Non-Pharmaceutical Interventions Will Result in Profound Mortality: A New York State Modelling Study Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is the most significant global health crisis of the 21(st) century. The aim of this study was to develop a model to estimate the effect of undocumented infections, seasonal infectivity, immunity, and non-pharmaceutical interventions (NPIs), such as social distancing, on the transmission, morbidity, and mortality of SARS-CoV-2 in New York State (NYS). Simulations revealed dramatic infectivity driven by undocumented infections, and a peak basic reproductive number in NYS of 5.7. NPIs have been effective, and relaxation >50% will result in tens-of-thousands more deaths. Endemic infection is likely to occur in the absence of profound sustained immunity. As a result, until an effective vaccine or other effective pharmaceutical intervention is developed, it will be critical to not reduce NPIs >50% below current levels. This study establishes fundamental characteristics of SARS-CoV-2 transmission, which can help policymakers navigate combating this virus in the coming years.

positive: Novel Coronavirus in Cape Town Informal Settlements: Feasibility of Using Informal Dwelling Outlines to Identify High Risk Areas for COVID-19 Transmission From A Social Distancing Perspective BACKGROUND: The challenges faced by the Global South during the coronavirus disease (COVID-19) pandemic are compounded by the presence of informal settlements, which are typically densely populated and lacking in formalized sanitation infrastructure. Social distancing measures in informal settlements may be difficult to implement due to the density and layout of settlements. This study measures the distance between dwellings in informal settlements in Cape Town to identify the risk of COVID-19 transmission. OBJECTIVE: The aim of this paper is to determine if social distancing measures are achievable in informal settlements in Cape Town, using two settlements as an example. We will first examine the distance between dwellings and their first, second, and third nearest neighbors and then identify clusters of dwellings in which residents would be unable to effectively practice social isolation due to the close proximity of their homes. METHODS: Dwellings in the settlements of Masiphumelele and Klipfontein Glebe were extracted from a geographic information system data set of outlines of all informal dwellings in Cape Town. The distance to each dwelling’s first, second, and third nearest neighbors was calculated for each settlement. A social distance measure of 2 m was used (buffer of 1 m, as dwellings less than 2 m apart are joined) to identify clusters of dwellings that are unable to effectively practice social distancing in each settlement. RESULTS: The distance to each dwelling’s first 3 nearest neighbors illustrates that the settlement of Masiphumelele is constructed in a denser fashion as compared to the Klipfontein Glebe settlement. This implies that implementing social distancing will likely be more challenging in Masiphumelele than in Klipfontein Glebe. However, using a 2-m social distancing measure, it was demonstrated that large portions of Klipfontein Glebe would also be unable to effectively implement social distancing. CONCLUSIONS: Effectively implementing social distancing may be a challenge in informal settlements due to their density. This paper uses dwelling outlines for informal settlements in the city of Cape Town to demonstrate that with a 2 m measure, effective social distancing will be challenging.

positive: Strong Social Distancing Measures In The United States Reduced The COVID-19 Growth Rate. State and local governments imposed social distancing measures in March and April of 2020 to contain the spread of novel coronavirus disease 2019 (COVID-19). These included large event bans, school closures, closures of entertainment venues, gyms, bars, and restaurant dining areas, and shelter-in-place orders (SIPOs). We evaluated the impact of these measures on the growth rate of confirmed COVID-19 cases across US counties between March 1, 2020 and April 27, 2020. An event-study design allowed each policy's impact on COVID-19 case growth to evolve over time. Adoption of government-imposed social distancing measures reduced the daily growth rate by 5.4 percentage points after 1-5 days, 6.8 after 6-10 days, 8.2 after 11-15 days, and 9.1 after 16-20 days. Holding the amount of voluntary social distancing constant, these results imply 10 times greater spread by April 27 without SIPOs (10 million cases) and more than 35 times greater spread without any of the four measures (35 million). Our paper illustrates the potential danger of exponential spread in the absence of interventions, providing relevant information to strategies for restarting economic activity. [Editor's Note: This Fast Track Ahead Of Print article is the accepted version of the peer-reviewed manuscript. The final edited version will appear in an upcoming issue of Health Affairs.].

positive: Mobile phone location data reveal the effect and geographic variation of social distancing on the spread of the COVID-19 epidemic The emergence of SARS-CoV-2 and the coronavirus infectious disease (COVID-19) has become a pandemic. Social (physical) distancing is a key non-pharmacologic control measure to reduce the transmission rate of SARS-COV-2, but high-level adherence is needed. Using daily travel distance and stay-at-home time derived from large-scale anonymous mobile phone location data provided by Descartes Labs and SafeGraph, we quantify the degree to which social distancing mandates have been followed in the U.S. and its effect on growth of COVID-19 cases. The correlation between the COVID-19 growth rate and travel distance decay rate and dwell time at home change rate was -0.586 (95% CI: -0.742 ~ -0.370) and 0.526 (95% CI: 0.293 ~ 0.700), respectively. Increases in state-specific doubling time of total cases ranged from 1.04 ~ 6.86 days to 3.66 ~ 30.29 days after social distancing orders were put in place, consistent with mechanistic epidemic prediction models. Social distancing mandates reduce the spread of COVID-19 when they are followed.

positive: A stochastic, individual-based model for the evaluation of the impact of non-pharmacological interventions on COVID-19 transmission in Slovakia The COVID-19 pandemic represents one of the most significant healthcare challenges that humanity faces. We developed a stochastic, individual-based model of transmission of COVID-19 in Slovakia. The proposed model is based on current clinical knowledge of the disease and takes into account the age structure of the population, distribution of the population into the households, interactions within the municipalities, and interaction among the individuals travelling between municipalities. Furthermore, the model incorporates the effect of age-dependent severity of COVID-19 and realistic trajectories of patients through the healthcare system. We assess the impact of the governmental non-pharmacological interventions, such as population-wide social distancing, social distancing within specific subsets of population, reduction of travel between the municipalities, and self-quarantining of the infected individuals. We also evaluate the impact of relaxing of strict restrictions, efficacy of the simple state feedback-based restrictions in controlling the outbreak, and the effect of superspreaders on the disease dynamics. Our simulations show that non-pharmacological interventions reduce the number of infected individuals and the number of fatalities, especially when the social distancing of particularly susceptible subgroups of the population is employed along with case isolation.

positive: Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China Intense non-pharmaceutical interventions were put in place in China to stop transmission of the novel coronavirus disease (COVID-19). As transmission intensifies in other countries, the interplay between age, contact patterns, social distancing, susceptibility to infection, and COVID-19 dynamics remains unclear. To answer these questions, we analyze contact surveys data for Wuhan and Shanghai before and during the outbreak and contact tracing information from Hunan Province. Daily contacts were reduced 7-8-fold during the COVID-19 social distancing period, with most interactions restricted to the household. We find that children 0-14 years are less susceptible to SARS-CoV-2 infection than adults 15-64 years of age (odd ratio 0.34, 95%CI 0.24-0.49), while in contrast, individuals over 65 years are more susceptible to infection (odd ratio 1.47, 95%CI: 1.12-1.92). Based on these data, we build a transmission model to study the impact of social distancing and school closure on transmission. We find that social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. While proactive school closures cannot interrupt transmission on their own, they can reduce peak incidence by 40-60% and delay the epidemic.

positive: Differential impacts of contact tracing and lockdowns on outbreak size in COVID-19 model applied to China Rapid growth of the COVID-19 epidemic in China induced extensive efforts of contact tracing and social-distancing/lockdowns, which quickly contained the outbreak and has been replicated to varying degrees around the world. We construct a novel infectious disease model incorporating these distinct quarantine measures (contact tracing and self-quarantine) as reactionary interventions dependent on current infection levels. Derivation of the final outbreak size leads to a simple inverse proportionality relationship with self-quarantine rate, revealing a fundamental principle of exponentially increasing cumulative cases when delaying mass quarantine or lockdown measures beyond a critical time period. In contrast, contact tracing results in a proportional reduction in reproduction number, flattening the epidemic curve but only having sizable impact on final size when a large proportion of contacts are "perfectly" traced. We fit the mathematical model to data from China on reported cases and quarantined contacts, finding that lockdowns had an overwhelming influence on outbreak size and duration, whereas contact tracing played a role in reducing peak number of infected. Sensitivity analysis and simulations under different re-opening scenarios illustrate the differential effects that responsive contact tracing and lockdowns can have on current and second wave outbreaks.

positive: Mobility patterns of the Portuguese population during the COVID-19 pandemic SARS-CoV-2 emerged in late 2019. Since then, it has spread to several countries, becoming classified as a pandemic. So far, there is no definitive treatment or vaccine, so the best solution is to prevent transmission between individuals through social distancing. However, it is difficult to measure the effectiveness of these distancing measures. Therefore, this study uses data from Google COVID-19 Community Mobility Reports to try to understand the mobility patterns of the Portuguese population during the COVID-19 pandemic. In this study, the Rt value was modeled for Portugal. Also, the changepoint was calculated for the population mobility patterns. Thus, the change in the mobility pattern was used to understand the impact of social distancing measures on the dissemination of COVID-19. As a result, it can be stated that the initial Rt value in Portugal was very close to 3, falling to values close to 1 after 25 days. Social isolation measures were adopted quickly. Furthermore, it was observed that public transport was avoided during the pandemic. Finally, until the emergence of a vaccine or an effective treatment, this will be the new normal and it must be understood that new patterns of mobility, social interaction, and hygiene must be adapted to this new reality.

positive: Impacts of State-Level Policies on Social Distancing in the United States Using Aggregated Mobility Data during the COVID-19 Pandemic Social distancing has emerged as the primary mitigation strategy to combat the COVID-19 pandemic in the United States. However, large-scale evaluation of the public's response to social distancing campaigns has been lacking. We used anonymized and aggregated mobility data from Google Location History users to estimate the impact of social distancing recommendations on bulk mobility among users who have opted into this service. We found that state-of-emergency declarations resulted in approximately a 10% reduction in time spent away from places of residence. Implementation of one or more social distancing policies resulted in an additional 25% reduction in mobility the following week. Subsequent shelter-in-place mandates provided an additional 29% reduction. Our findings provide evidence that state-wide mandates are effective in promoting social distancing within this study group.

positive: The effect of travel restrictions on the spread of the 2019 novel coronavirus (2019-nCoV) outbreak Motivated by the rapid spread of a novel coronavirus (2019-nCoV) in Mainland China, we use a global metapopulation disease transmission model to project the impact of both domestic and international travel limitations on the national and international spread of the epidemic. The model is calibrated on the evidence of internationally imported cases before the implementation of the travel quarantine of Wuhan. By assuming a generation time of 7.5 days, the reproduction number is estimated to be 2.4 [90% CI 2.2–2.6]. The median estimate for number of cases before the travel ban implementation on January 23, 2020 is 58,956 [90% CI 40,759 – 87,471] in Wuhan and 3,491 [90% CI 1,924 – 7,360] in other locations in Mainland China. The model shows that as of January 23, most Chinese cities had already received a considerable number of infected cases, and the travel quarantine delays the overall epidemic progression by only 3 to 5 days. The travel quarantine has a more marked effect at the international scale, where we estimate the number of case importations to be reduced by 80% until the end of February. Modeling results also indicate that sustained 90% travel restrictions to and from Mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.

positive: Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK BACKGROUND: To mitigate and slow the spread of COVID-19, many countries have adopted unprecedented physical distancing policies, including the UK. We evaluate whether these measures might be sufficient to control the epidemic by estimating their impact on the reproduction number (R0, the average number of secondary cases generated per case). METHODS: We asked a representative sample of UK adults about their contact patterns on the previous day. The questionnaire was conducted online via email recruitment and documents the age and location of contacts and a measure of their intimacy (whether physical contact was made or not). In addition, we asked about adherence to different physical distancing measures. The first surveys were sent on Tuesday, 24 March, 1 day after a "lockdown" was implemented across the UK. We compared measured contact patterns during the "lockdown" to patterns of social contact made during a non-epidemic period. By comparing these, we estimated the change in reproduction number as a consequence of the physical distancing measures imposed. We used a meta-analysis of published estimates to inform our estimates of the reproduction number before interventions were put in place. RESULTS: We found a 74% reduction in the average daily number of contacts observed per participant (from 10.8 to 2.8). This would be sufficient to reduce R0 from 2.6 prior to lockdown to 0.62 (95% confidence interval [CI] 0.37-0.89) after the lockdown, based on all types of contact and 0.37 (95% CI = 0.22-0.53) for physical (skin to skin) contacts only. CONCLUSIONS: The physical distancing measures adopted by the UK public have substantially reduced contact levels and will likely lead to a substantial impact and a decline in cases in the coming weeks. However, this projected decline in incidence will not occur immediately as there are significant delays between infection, the onset of symptomatic disease, and hospitalisation, as well as further delays to these events being reported. Tracking behavioural change can give a more rapid assessment of the impact of physical distancing measures than routine epidemiological surveillance.

positive: Social distancing measures to control the COVID-19 pandemic: potential impacts and challenges in Brazil. The COVID-19 pandemic has challenged researchers and policy makers to identify public safety measures forpreventing the collapse of healthcare systems and reducingdeaths. This narrative review summarizes the available evidence on the impact of social distancing measures on the epidemic and discusses the implementation of these measures in Brazil. Articles on the effect of social distancing on COVID-19 were selected from the PubMed, medRXiv and bioRvix databases. Federal and state legislation was analyzed to summarize the strategies implemented in Brazil. Social distancing measures adopted by the population appear effective, particularly when implemented in conjunction with the isolation of cases and quarantining of contacts. Therefore, social distancing measures, and social protection policies to guarantee the sustainability of these measures, should be implemented. To control COVID-19 in Brazil, it is also crucial that epidemiological monitoring is strengthened at all three levels of the Brazilian National Health System (SUS). This includes evaluating and usingsupplementary indicators to monitor the progression of the pandemic and the effect of the control measures, increasing testing capacity, and making disaggregated notificationsand testing resultstransparentand broadly available.

positive: Full lockdown policies in Western Europe countries have no evident impacts on the COVID-19 epidemic. This phenomenological study assesses the impacts of full lockdown strategies applied in Italy, France, Spain and United Kingdom, on the slowdown of the 2020 COVID-19 outbreak. Comparing the trajectory of the epidemic before and after the lockdown, we find no evidence of any discontinuity in the growth rate, doubling time, and reproduction number trends. Extrapolating pre-lockdown growth rate trends, we provide estimates of the death toll in the absence of any lockdown policies, and show that these strategies might not have saved any life in western Europe. We also show that neighboring countries applying less restrictive social distancing measures (as opposed to police-enforced home containment) experience a very similar time evolution of the epidemic.

positive: The effect of control strategies that reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China BACKGROUND: In December 2019, a novel strain of SARS-CoV-2 emerged in Wuhan, China. Since then, the city of Wuhan has taken unprecedented measures and efforts in response to the outbreak. METHODS: We quantified the effects of control measures on population contact patterns in Wuhan, China, to assess their effects on the progression of the outbreak. We included the latest estimates of epidemic parameters from a transmission model fitted to data on local and internationally exported cases from Wuhan in the age-structured epidemic framework. Further, we looked at the age-distribution of cases. Lastly, we simulated lifting of the control measures by allowing people to return to work in a phased-in way, and looked at the effects of returning to work at different stages of the underlying outbreak. FINDINGS: Changes in mixing patterns may have contributed to reducing the number of infections in mid-2020 by 92% (interquartile range: 66-97%). There are benefits to sustaining these measures until April in terms of reducing the height of the peak, overall epidemic size in mid-2020 and probability that a second peak may occur after return to work. However, the modelled effects of social distancing measures vary by the duration of infectiousness and the role school children play in the epidemic. INTERPRETATION: Restrictions on activities in Wuhan, if maintained until April, would likely contribute to the reduction and delay the epidemic size and peak, respectively. However, there are some limitations to the analysis, including large uncertainties around estimates of R0 and the duration of infectiousness.

positive: Estimating the number of COVID-19-related infections, deaths and hospitalizations in Iran under different physical distancing and isolation scenarios: A compartmental mathematical modeling Background: Iran is one of the countries that has been overwhelmed with COVID-19. We aimed to estimate the total number of COVID-19 related infections, deaths, and hospitalizations in Iran under different physical distancing and isolation scenarios. Methods: We developed a Susceptible-Exposed-Infected-Removed (SEIR) model, parameterized to the COVID-19 pandemic in Iran. We used the model to quantify the magnitude of the outbreak in Iran and assess the effectiveness of isolation and physical distancing under five different scenarios (A: 0% isolation, through E: 40% isolation of all infected cases). We used Monte-Carlo simulation to calculate the 95% uncertainty intervals (UI). Findings: Under scenario A, we estimated 5,196,000 (UI 1,753,000 - 10,220,000) infections to happen till mid-June with 966,000 (UI 467,800 - 1,702,000) hospitalizations and 111,000 (UI 53,400 - 200,000) deaths. Successful implantation of scenario E would reduce the number of infections by 90% (i.e. 550,000) and change the epidemic peak from 66,000 on June 9th to 9,400 on March 1st. Scenario E also reduces the hospitalizations by 92% (i.e. 74,500), and deaths by 93% (i.e. 7,800). Interpretation: With no approved vaccination or therapy, we found physical distancing and isolation that includes public awareness and case-finding/isolation of 40% of infected people can reduce the burden of COVID-19 in Iran by 90% by mid-June.

positive: Estimates of regional infectivity of COVID-19 in the United Kingdom following imposition of social distancing measures We describe regional variation in the reproduction number of SARS-CoV-2 infections observed using publicly reported data in the UK, with a view to understanding both if there are clear hot spots in viral spread in the country, or if there are any clear spatial patterns. We estimate that the viral replication number remains slightly above 1 overall but that its trend is to decrease, based on case data up to the 8 April. This suggests the peak of the first wave of COVID-19 patients is imminent. We find that there is significant regional variation in different regions of the UK and that this is changing over time. Within England currently the reproductive ratio is lowest in the Midlands (1.11 95% CI 1.07; 1.14), and highest in the North East of England (1.38 95% CI 1.33-1.42). It remains unclear whether the overall reduction in the reproductive number is a result of social distancing measures, due to the long and variable time delays between infection and positive detection of cases. As we move forwards, if we are to prevent further outbreaks, it is critical that we can both reduce the time taken for detection and improve our ability to predict the regional spread of outbreaks

positive: The effect of non-pharmaceutical interventions on COVID-19 cases, deaths and demand for hospital services in the UK: a modelling study Background Non-pharmaceutical interventions have been implemented to reduce transmission of SARS-CoV-2 in the UK. Projecting the size of an unmitigated epidemic and the potential effect of different control measures has been critical to support evidence-based policymaking during the early stages of the epidemic. Methods We used a stochastic age-structured transmission model to explore a range of intervention scenarios, including the introduction of school closures, social distancing, shielding of elderly groups, self-isolation of symptomatic cases, and extreme "lockdown"-type restrictions. We simulated different durations of interventions and triggers for introduction, as well as combinations of interventions. For each scenario, we projected estimated new cases over time, patients requiring inpatient and critical care (intensive care unit, ICU) treatment, and deaths. Findings We found that mitigation measures aimed at reducing transmission would likely have decreased the reproduction number, but not sufficiently to prevent ICU demand from exceeding NHS availability. To keep ICU bed demand below capacity in the model, more extreme restrictions were necessary. In a scenario where "lockdown"-type interventions were put in place to reduce transmission, these interventions would need to be in place for a large proportion of the coming year in order to prevent healthcare demand exceeding availability. Interpretation The characteristics of SARS-CoV-2 mean that extreme measures are likely required to bring the epidemic under control and to prevent very large numbers of deaths and an excess of demand on hospital beds, especially those in ICUs.

positive: Scenario analysis of non-pharmaceutical interventions on global COVID-19 transmissions This paper introduces a dynamic panel SIR (DP-SIR) model to investigate the impact of non-pharmaceutical interventions (NPIs) on the COVID-19 transmission dynamics with panel data from 9 countries across the globe. By constructing scenarios with different combinations of NPIs, our empirical findings suggest that countries may avoid the lockdown policy with imposing school closure, mask wearing and centralized quarantine to reach similar outcomes on controlling the COVID-19 infection. Our results also suggest that, as of April 4th, 2020, certain countries such as the U.S. and Singapore may require additional measures of NPIs in order to control disease transmissions more effectively, while other countries may cautiously consider to gradually lift some NPIs to mitigate the costs to the overall economy.

positive: Pandemic Politics: Timing State-Level Social Distancing Responses to COVID-19 Social distancing policies are critical but economically painful measures to flatten the curve against emergent infectious diseases. As the novel coronavirus that causes COVID-19 spread throughout the United States in early 2020, the federal government issued social distancing recommendations but left to the states the most difficult and consequential decisions restricting behavior, such as canceling events, closing schools and businesses, and issuing stay-at-home orders. We present an original dataset of state-level social distancing policy responses to the epidemic and explore how political partisanship, COVID-19 caseload, and policy diffusion explain the timing of governors' decisions to mandate social distancing. An event history analysis of five social distancing policies across all fifty states reveals the most important predictors are political: all else equal, Republican governors and governors from states with more Trump supporters were slower to adopt social distancing policies. These delays are likely to produce significant, on-going harm to public health.

positive: Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China Intense nonpharmaceutical interventions were put in place in China to stop transmission of the novel coronavirus disease 2019 (COVID-19). As transmission intensifies in other countries, the interplay between age, contact patterns, social distancing, susceptibility to infection, and COVID-19 dynamics remains unclear. To answer these questions, we analyze contact survey data for Wuhan and Shanghai before and during the outbreak and contact-tracing information from Hunan province. Daily contacts were reduced seven- to eightfold during the COVID-19 social distancing period, with most interactions restricted to the household. We find that children 0 to 14 years of age are less susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection than adults 15 to 64 years of age (odds ratio 0.34, 95% confidence interval 0.24 to 0.49), whereas individuals more than 65 years of age are more susceptible to infection (odds ratio 1.47, 95% confidence interval 1.12 to 1.92). Based on these data, we built a transmission model to study the impact of social distancing and school closure on transmission. We find that social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. Although proactive school closures cannot interrupt transmission on their own, they can reduce peak incidence by 40 to 60% and delay the epidemic.

positive: Predicting social distancing index during COVID-19 outbreak through online search engines trends Online-available information has been considered an accessory tool to estimate epidemiology and collect data on diseases and population behavior patterns. This study aimed to explore the potential use of Google and YouTube relative search volume to predict social distancing index in Brazil during COVID-19 outbreak and verify the correlation between social distancing measures with the course of the epidemic. Data concerning the social distancing index, epidemiological data on COVID-19 in Brazil and the search engines trends for Coronavirus were retrieved from online databases. Multiple linear regression was performed and resulted in a statistically significant model evidencing that Google and YouTube relative search volumes are predictors of the social distancing index. The Spearman correlation test revealed a weak correlation between social distancing measures and the course of the COVID-19 epidemic. Health authorities can apply these data to define the proper timing and location for practicing appropriate risk communication strategies.

positive: COVID-19 most vulnerable Mexican cities lack the public health infrastructure to face the pandemic: a new temporally-explicit model Recently, a wide array of epidemiological models has been developed to guide public health actors in containing the rapid dissemination of the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), cause of COVID-19. Despite their usefulness, many epidemiological models recently developed to understand the spread of SARS-CoV-2 and infection rates of COVID-19 fall short as they ignore human mobility, limiting our understanding of the spread of the disease, together with the vulnerability of population centers in a broad scale. We developed a new temporally-explicit model and simulated several social distancing scenarios to predict the vulnerability to COVID-19 of 50 Mexican cities that are interconnected by their air transportation network. Additionally, we assessed the sufficiency of the public health infrastructure in the focal cities to face the pandemic over time. Based on our model, we show that the most important cities within the Mexican air transportation network are the most vulnerable to COVID-19, with all assessed public health infrastructure being insufficient to face the modeled scenario for the pandemic after 100 days. Despite these alarming findings, our results show that social distancing could dramatically decrease the total number of infected people (77% drop-off for the 45% distancing scenario when contrasted with no distancing), flattening the growth of infection rate. Thus, we consider that this study provides useful information that may help decision-makers to timely implement health policies to anticipate and lessen the impact of the current pandemic in Mexico.

positive: A hybrid multi-scale model of COVID-19 transmission dynamics to assess the potential of non-pharmaceutical interventions Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus that emerged in Wuhan, China in December 2019. It has caused a global outbreak which represents a major threat to global health. Public health resorted to non-pharmaceutical interventions such as social distancing and lockdown to slow down the spread of the pandemic. However, the effect of each of these measures remains hard to quantify. We design a multi-scale model that simulates the transmission dynamics of COVID-19. We describe the motion of individual agents using a social force model. Each agent can be either susceptible, infected, quarantined, immunized or deceased. The model considers both mechanisms of direct and indirect transmission. We parameterize the model to reproduce the early dynamics of disease spread in Italy. We show that panic situations increase the risk of infection transmission in crowds despite social distancing measures. Next, we reveal that pre-symptomatic transmission accelerates the onset of the exponential growth of cases. After that, we demonstrate that the persistence of SARS-CoV-2 on hard surfaces determines the number of cases reached during the peak of the epidemic. Then, we show that the restricted movement of the individuals flattens the epidemic curve. Finally, model predictions suggest that measures stricter than social distancing and lockdown were used to control the epidemic in Wuhan, China.

positive: CIRD-F: Spread and Influence of COVID-19 in China The outbreak of coronavirus disease 2019 (COVID-19) has been spreading rapidly in China and the Chinese government took a series of policies to control the epidemic. Therefore, it will be helpful to predict the tendency of the epidemic and analyze the influence of official policies. Existing models for prediction, such as cabin models and individual-based models, are either oversimplified or too meticulous, and the influence of the epidemic was studied much more than that of official policies. To predict the epidemic tendency, we consider four groups of people, and establish a propagation dynamics model. We also create a negative feedback to quantify the public vigilance to the epidemic. We evaluate the tendency of epidemic in Hubei and China except Hubei separately to predict the situation of the whole country. Experiments show that the epidemic will terminate around 17 March 2020 and the final number of cumulative infections will be about 78 191 (prediction interval, 74 872 to 82 474). By changing the parameters of the model accordingly, we demonstrate the control effect of the policies of the government on the epidemic situation, which can reduce about 68% possible infections. At the same time, we use the capital asset pricing model with dummy variable to evaluate the effects of the epidemic and official policies on the revenue of multiple industries.

positive: How long does a lockdown need to be? Social distancing, often in the form of lockdown, has been adopted by many countries as a way to contrast the spreading of COVID-19. We discuss the temporal aspects of social distancing in contrasting an epidemic diffusion. We argue that a strategy based uniquely on social distancing requires to maintain the relative measures for a very long time, while a more articulate strategy, which also uses early detection and prompt isolation, can be both more efficient on reducing the epidemic peak and allow to relax the social distancing measures after a much shorter time. We consider in more detail the situation in Italy, simulating the effect of different strategies through a recently introduced SIR-type epidemiological model. The short answer to the question in the title is:"it depends on what else you do".

positive: Strong policies control the spread of COVID-19 in China OBJECTIVE: The coronavirus disease 2019 (COVID-19) outbroke in Wuhan, Hubei Province, China, affecting more than 200 countries and regions. This study aimed to predict the development of the epidemic with specific interventional policies applied in China and evaluate their effectiveness. METHODS: COVID-19 data of Hubei Province and the next five most affected provinces were collected from daily case reports of COVID-19 on the Health Committee official website of these provinces. The number of current cases, defined as the number of confirmed cases minus the number of cured cases and those who have died, was examined in this study. A modified Susceptible-Exposed-Infectious- Removed (SEIR) model was used to assess the effects of interventional policies on the epidemic. In this study, January 28 was day zero of the model. RESULTS: The results of the modified SEIR model showed that the number of current cases in Hubei and Zhejiang provinces tended to be stabilized after 70 days and after 60 days in the four other provinces. The predicted number of current cases without policy intervention was shown to far exceed that with policy intervention. The estimated number of COVID-19 cases in Hubei Province with policy intervention was predicted to peak at 51,222, whereas that without policy intervention was predicted to reach 157,721. CONCLUSION: Based on the results of the model, strong interventional policies were found to be vital components of epidemic control. Applying such policies is likely to shorten the duration of the epidemic and reduce the number of new cases. This article is protected by copyright. All rights reserved.

positive: Temporal rise in the proportion of younger adults and older adolescents among COVID-19 cases in Germany: evidence of lesser adherence to social distancing practices? Background: There is uncertainty about the role of different age groups in propagating the SARS-CoV-2 epidemics in different countries. Methods: We used the Koch Institute data on COVID-19 cases in Germany. To minimize the effect of changes in healthcare seeking behavior and testing practices, we included the following 5-year age groups in the analyses: 10-14y through 45-49y. For each age group g, we considered the proportion PL(g) of individuals in age group g among all detected cases aged 10-49y during weeks 13-14, 2020 (later period), as well as corresponding proportion PE(g) for weeks 10-11, 2020 (early period), and the relative risk RR(g)=PL(g)/PE(g). For each pair of age groups g1,g2, a higher value of RR(g1) compared to RR(g2) is interpreted as the relative increase in the population incidence of SARS-Cov-2 for g1 compared to g2 for the later vs. early period. Results: The relative risk was highest for individuals aged 20-24y (RR=1.4(95% CI (1.27,1.55))), followed by individuals aged 15-19y (RR=1.14(0.99,1.32)), aged 30-34y (RR= 1.07(0.99,1.16)), aged 25-29y (RR= 1.06(0.98,1.15)), aged 35-39y (RR=0.95(0.87,1.03)), aged 40-44y (RR=0.9(0.83,0.98)), aged 45-49y (RR=0.83(0.77,0.89)) and aged 10-14y (RR=0.78(0.64,0.95)). Conclusions: The observed relative increase with time in the prevalence of individuals aged 15-34y (particularly those aged 20-24y) among COVID-19 cases is unlikely to be explained by increases in the likelihood of seeking medical care/being tested for individuals in those age groups compared to individuals aged 35-49y or 10-14y, suggesting an actual increase in the prevalence of individuals aged 15-34y among SARS-CoV-2 infections in the German population. That increase likely reflects elevated mixing among individuals aged 15-34y (particularly those aged 20-24y) compared to other age groups, possibly due to lesser adherence to social distancing practices.

positive: The Effect of Large-Scale Anti-Contagion Policies on the Coronavirus (COVID-19) Pandemic Governments around the world are responding to the novel coronavirus (COVID-19) pandemic with unprecedented policies designed to slow the growth rate of infections. Many actions, such as closing schools and restricting populations to their homes, impose large and visible costs on society. In contrast, the benefits of these policies, in the form of infections that did not occur, cannot be directly observed and are currently understood through process-based simulations. Here, we compile new data on 1,659 local, regional, and national anti-contagion policies recently deployed in the ongoing pandemic across localities in China, South Korea, Iran, Italy, France, and the United States (US). We then apply reduced-form econometric methods, commonly used to measure the effect of policies on economic growth, to empirically evaluate the effect that these anti-contagion policies have had on the growth rate of infections. In the absence of any policy actions, we estimate that early infections of COVID-19 exhibit exponential growth rates of roughly 42% per day. We find that anti-contagion policies collectively have had significant effects slowing this growth. Our results suggest that similar policies may have different impacts on different populations, but we obtain consistent evidence that the policy packages now deployed are achieving large, beneficial, and measurable health outcomes. We estimate that, to date, current policies have already prevented or delayed on the order of 62 million infections across these six countries. These findings may help inform whether or when these ongoing policies should be lifted or intensified, and they can support decision-making in the other 180+ countries where COVID-19 has been reported.

positive: Demographic science aids in understanding the spread and fatality rates of COVID-19 Governments around the world must rapidly mobilize and make difficult policy decisions to mitigate the COVID-19 pandemic. Because deaths have been concentrated at older ages, we highlight the important role of demography, particularly how the age structure of a population may help explain differences in fatality rates across countries and how transmission unfolds. We examine the role of age structure in deaths thus far in Italy and South Korea and illustrate how the pandemic could unfold in populations with similar population sizes but different age structures, showing a dramatically higher burden of mortality in countries with older versus younger populations. This powerful interaction of demography and current age-specific mortality for COVID-19 suggests that social distancing and other policies to slow transmission should consider both the age composition of local and national contexts as well as the social connectedness of older and younger generations. We also call for countries to provide case and fatality data disaggregated by age and sex to improve real-time targeted nowcasting.

positive: Effects of social distancing on the spreading of COVID-19 inferred from mobile phone data A better understanding of how the COVID-19 epidemic responds to social distancing efforts is required for the control of future outbreaks and to calibrate partial lock-downs. We present quantitative relationships between key parameters characterizing the COVID-19 epidemiology and social distancing efforts of nine selected European countries. Epidemiological parameters were extracted from the number of daily deaths data, while mitigation efforts are estimated from mobile phone tracking data. The decrease of the basic reproductive number (R0) as well as the duration of the initial exponential expansion phase of the epidemic strongly correlates with the magnitude of mobility reduction. Utilizing these relationships we decipher the relative impact of the timing and the extent of social distancing on the total death burden of the epidemic.

positive: Assessing the potential impact of COVID-19 in Brazil: Mobility, Morbidity and the burden on the Health Care System The two largest Brazilian cities, Rio de Janeiro and Sao Paulo, have declared community transmission of COVID-19 on mid March, 2020. In this study we estimated the most vulnerable areas in Brazil for COVID-19, both in terms of risk of introduction and risk of mortality associated with social vulnerability. We explore the most likely routes of spread through the country, from the already exposed cities, according to human mobility statistics. The resulting maps should help authorities in their efforts to prioritize actions and if resource allocation to mitigate the effects of the pandemic.

positive: Strong Social Distancing Measures In The United States Reduced The COVID-19 Growth Rate State and local governments imposed social distancing measures in March and April 2020 to contain the spread of the novel coronavirus disease (COVID-19). These measures included bans on large social gatherings; school closures; closures of entertainment venues, gyms, bars, and restaurant dining areas; and shelter-in-place orders. We evaluated the impact of these measures on the growth rate of confirmed COVID-19 cases across US counties between March 1, 2020, and April 27, 2020. An event study design allowed each policy's impact on COVID-19 case growth to evolve over time. Adoption of government-imposed social distancing measures reduced the daily growth rate of confirmed COVID-19 cases by 5.4 percentage points after one to five days, 6.8 percentage points after six to ten days, 8.2 percentage points after eleven to fifteen days, and 9.1 percentage points after sixteen to twenty days. Holding the amount of voluntary social distancing constant, these results imply that there would have been ten times greater spread of COVID-19 by April 27 without shelter-in-place orders (ten million cases) and more than thirty-five times greater spread without any of the four measures (thirty-five million cases). Our article illustrates the potential danger of exponential spread in the absence of interventions, providing information relevant to strategies for restarting economic activity.

positive: Strong Social Distancing Measures In The United States Reduced The COVID-19 Growth Rate State and local governments imposed social distancing measures in March and April of 2020 to contain the spread of novel coronavirus disease 2019 (COVID-19). These included large event bans, school closures, closures of entertainment venues, gyms, bars, and restaurant dining areas, and shelter-in-place orders (SIPOs). We evaluated the impact of these measures on the growth rate of confirmed COVID-19 cases across US counties between March 1, 2020 and April 27, 2020. An event-study design allowed each policy's impact on COVID-19 case growth to evolve over time. Adoption of government-imposed social distancing measures reduced the daily growth rate by 5.4 percentage points after 1-5 days, 6.8 after 6-10 days, 8.2 after 11-15 days, and 9.1 after 16-20 days. Holding the amount of voluntary social distancing constant, these results imply 10 times greater spread by April 27 without SIPOs (10 million cases) and more than 35 times greater spread without any of the four measures (35 million). Our paper illustrates the potential danger of exponential spread in the absence of interventions, providing relevant information to strategies for restarting economic activity. [Editor's Note: This Fast Track Ahead Of Print article is the accepted version of the peer-reviewed manuscript. The final edited version will appear in an upcoming issue of Health Affairs.].

positive: Observed mobility behavior data reveal social distancing inertia The research team has utilized an integrated dataset, consisting of anonymized location data, COVID-19 case data, and census population information, to study the impact of COVID-19 on human mobility. The study revealed that statistics related to social distancing, namely trip rate, miles traveled per person, and percentage of population staying at home have all showed an unexpected trend, which we named social distancing inertia. The trends showed that as soon as COVID-19 cases were observed, the statistics started improving, regardless of government actions. This suggests that a portion of population who could and were willing to practice social distancing voluntarily and naturally reacted to the emergence of COVID-19 cases. However, after about two weeks, the statistics saturated and stopped improving, despite the continuous rise in COVID-19 cases. The study suggests that there is a natural behavior inertia toward social distancing, which puts a limit on the extent of improvement in the social-distancing-related statistics. The national data showed that the inertia phenomenon is universal, happening in all the U.S. states and for all the studied statistics. The U.S. states showed a synchronized trend, regardless of the timeline of their statewide COVID-19 case spreads or government orders.

positive: SOCRATES: An online tool leveraging a social contact data sharing initiative to assess mitigation strategies for COVID-19 Objective: Establishing a social contact data sharing initiative and an interactive tool to assess mitigation strategies for COVID-19. Results: We organized data sharing of published social contact surveys via online repositories and formatting guidelines. We analyzed this social contact data in terms of weighted social contact matrices, next generation matrices, relative incidence and R0. We incorporated location-specific isolation measures (e.g. school closure or telework) and capture their effect on transmission dynamics. All methods have been implemented in an online application based on R Shiny and applied to COVID-19 with age-specific susceptibility and infectiousness. Using our online tool with the available social contact data, we illustrate that social distancing could have a considerable impact on reducing transmission for COVID-19. The effect itself depends on assumptions made about disease-specific characteristics and the choice of intervention(s). Keywords: social contact data, user interface, transmission dynamics, infectious diseases, epidemics, social distancing, behavioral changes, data sharing initiative, open-source, COVID-19

positive: Quantifying what could have been – the impact of the Australian and New Zealand governments’ response to COVID-19 The Australian and New Zealand governments both initiated strict social distancing measures in response to the COVID-19 pandemic in late March. It remains difficult to quantify the impact this had in reducing the spread of the virus. Bayesian structural time series model provide a model to quantify the scenario in which these government-level interventions were not placed. Our models predict these strict social distancing measures caused a 79% and 61% reduction in the daily cases of COVID-19 across Australia and New Zealand respectively. This provides both evidence and impetus for governments considering similar measures in response to COVID-19 and other pandemics.

positive: Mandatory social distancing associated with increased doubling time: an example using hyperlocal data In a hyperlocal analysis of doubling time of COVID-19, we found that a county that implemented mandatory social distancing and other measures to reduce spread of infection saw an earlier increase in doubling time than surrounding counties.

positive: The impact of a nation-wide lockdown on COVID-19 transmissibility in Italy On March 10, 2020, Italy imposed a national lockdown to curtail the spread of COVID-19. Here we estimate that, fourteen days after the implementation of the strategy, the net reproduction number has dropped below the epidemic threshold - estimated range 0.4-0.7. Our findings provide a timeline of the effectiveness of the implemented lockdown, which is relevant for a large number of countries that followed Italy in enforcing similar measures.

positive: Forecasting the Spread of COVID-19 under Different Reopening Strategies We combine COVID-19 case data with demographic and mobility data to estimate a modified susceptible-infected-recovered (SIR) model for the spread of this disease in the United States. We find that the incidence of infectious COVID-19 individuals has a concave effect on contagion, as would be expected if people have inter-related social networks. We also demonstrate that social distancing and population density have large effects on the rate of contagion. The social distancing in late March and April substantially reduced the number of COVID-19 cases. However, the concave contagion pattern means that when social distancing measures are lifted, the growth rate is considerable but will not be exponential as predicted by standard SIR models. Furthermore, counties with the lowest population density could likely avoid high levels of contagion even with no social distancing. We forecast rates of new cases for COVID-19 under different social distancing norms and find that if social distancing is eliminated there will be a massive increase in the cases of COVID-19, about double what would occur if the US only restored to 50% of the way to normalcy.

positive: Second waves, social distancing, and the spread of COVID-19 across America We recently described a dynamic causal model of a COVID-19 outbreak within a single region. Here, we combine several of these (epidemic) models to create a (pandemic) model of viral spread among regions. Our focus is on a second wave of new cases that may result from loss of immunity--and the exchange of people between regions--and how mortality rates can be ameliorated under different strategic responses. In particular, we consider hard or soft social distancing strategies predicated on national (Federal) or regional (State) estimates of the prevalence of infection in the population. The modelling is demonstrated using timeseries of new cases and deaths from the United States to estimate the parameters of a factorial (compartmental) epidemiological model of each State and, crucially, coupling between States. Using Bayesian model reduction, we identify the effective connectivity between States that best explains the initial phases of the outbreak in the United States. Using the ensuing posterior parameter estimates, we then evaluate the likely outcomes of different policies in terms of mortality, working days lost due to lockdown and demands upon critical care. The provisional results of this modelling suggest that social distancing and loss of immunity are the two key factors that underwrite a return to endemic equilibrium.

positive: Predicting COVID-19 spread and public health needs to contain the pandemic in West-Africa The novel coronavirus (COVID-19) pandemic is causing devastating demographic, social, and economic damage globally. Understanding current patterns of the pandemic spread and forecasting its long-term trajectory is essential in guiding policies aimed at curtailing the pandemic. This is particularly important in regions with weak economies and fragile health care systems such as West-Africa. We formulate and use a deterministic compartmental model to (i) assess the current patterns of COVID-19 spread in West-Africa, (ii) evaluate the impact of currently implemented control measures, and (iii) predict the future course of the pandemic with and without currently implemented and additional control measures in West-Africa. An analytical expression for the threshold level of control measures (involving a reduction in the effective contact rate) required to eliminate the pandemic is computed. Considering currently applied health control measures, numerical simulations of the model using baseline parameter values estimated from West-African COVID-19 data project a 60% reduction in the daily number of cases when the epidemic attains its peak. More reduction in the number of cases will be achieved if additional public health control measures that result in a reduction in the effective contact rate are implemented. We found out that disease elimination is difficult when more asymptomatic individuals contribute in transmission or are not identified and isolated in a timely manner. However, maintaining a baseline level of asymptomatic isolation and a low transmission rate will lead to a significant reduction in the number of daily cases when the pandemic peaks. For example, at the baseline level of asymptomatic isolation, at least a 53% reduction in the transmission rate is required for disease elimination, while disease elimination is also possible if asymptomatic individuals are identified and isolated within 2 days (after the incubation period). Combining two or more measures is better for disease control, e.g., if asymptomatic humans are contact traced or identified and isolated in less than 3 days then only about a 31% reduction in the disease transmission rate is required for disease elimination. Furthermore, we showed that the currently implemented measures caused the time-dependent effective reproduction number to reduce by approximately 37% from February 28, to August 24, 2020. We conclude that COVID-19 elimination requires more control measures than what is currently being applied inWest-Africa and that mass testing and contact tracing in order to identify and isolate asymptomatic individuals early is very important in curtailing the burden of the pandemic.

positive: No Place Like Home: Cross-National Data Analysis of the Efficacy of Social Distancing During the COVID-19 Pandemic BACKGROUND: In the absence of a cure in the time of a pandemic, social distancing measures seem to be the most effective intervention to slow the spread of disease. Various simulation-based studies have been conducted to investigate the effectiveness of these measures. While those studies unanimously confirm the mitigating effect of social distancing on disease spread, the reported effectiveness varies from 10% to more than 90% reduction in the number of infections. This level of uncertainty is mostly due to the complex dynamics of epidemics and their time-variant parameters. However, real transactional data can reduce uncertainty and provide a less noisy picture of the effectiveness of social distancing. OBJECTIVE: The aim of this paper was to integrate multiple transactional data sets (GPS mobility data from Google and Apple as well as disease statistics from the European Centre for Disease Prevention and Control) to study the role of social distancing policies in 26 countries and analyze the transmission rate of the coronavirus disease (COVID-19) pandemic over the course of 5 weeks. METHODS: Relying on the susceptible-infected-recovered (SIR) model and official COVID-19 reports, we first calculated the weekly transmission rate (ß) of COVID-19 in 26 countries for 5 consecutive weeks. Then, we integrated these data with the Google and Apple mobility data sets for the same time frame and used a machine learning approach to investigate the relationship between the mobility factors and ß values. RESULTS: Gradient boosted trees regression analysis showed that changes in mobility patterns resulting from social distancing policies explain approximately 47% of the variation in the disease transmission rates. CONCLUSIONS: Consistent with simulation-based studies, real cross-national transactional data confirms the effectiveness of social distancing interventions in slowing the spread of COVID-19. In addition to providing less noisy and more generalizable support for the idea of social distancing, we provide specific insights for public health policy makers regarding locations that should be given higher priority for enforcing social distancing measures.

positive: Examining the effect of social distancing on the compound growth rate of COVID-19 at the county level (United States) using statistical analyses and a random forest machine learning model OBJECTIVES: The goal of the present work is to investigate trends among US counties and coronavirus disease 2019 (COVID-19) growth rates in relation to the existence of shelter-in-place (SIP) orders in that county. STUDY DESIGN: This is a prospective cohort study. METHODS: Compound growth rates were calculated using cumulative confirmed COVID-19 cases from January 21, 2020, to March 31, 2020, in all 3139 US counties. Compound growth was chosen as it gives a single number that can be used in machine learning to represent the speed of virus spread during defined time intervals. Statistical analyses and a random forest machine learning model were used to analyze the data for differences in counties with and without SIP orders. RESULTS: Statistical analyses revealed that the March 16 presidential recommendation (limiting gatherings to ≤10 people) lowered the compound growth rate of COVID-19 for all counties in the US by 6.6%, and the counties that implemented SIP after March 16 had a further reduction of 7.8% compared with the counties that did not implement SIP after March 16. A random forest machine learning model was built to predict compound growth rate after a SIP order and was found to have an accuracy of 92.3%. The random forest found that population, longitude, and population per square mile were the most important features when predicting the effect of SIP. CONCLUSIONS: SIP orders were found to be effective at reducing the growth rate of COVID-19 cases in the US. Counties with a large population or a high population density were found to benefit the most from a SIP order.

positive: Effects of Government Mandated Social Distancing Measures on Cumulative Incidence of COVID-19 in the United States and its Most Populated Cities COVID-19, caused by the SARS-CoV-2 virus, has quickly spread throughout the world, necessitating assessment of the most effective containment methods. Very little research exists on the effects of social distancing measures on this pandemic. The purpose of this study was to examine the effects of government implemented social distancing measures on the cumulative incidence rates of COVID-19 in the United States on a state level, and in the 25 most populated cities, while adjusting for socio-demographic risk factors. The social distancing variables assessed in this study were: days to closing of non-essential business; days to stay home orders; days to restrictions on gathering, days to restaurant closings and days to school closing. Using negative binomial regression, adjusted rate ratios and 95% confidence intervals were calculated comparing two levels of a binary variable: above median value, and median value and below for days to implementing a social distancing measure. For city level data, the effects of these social distancing variables were also assessed in high (above median value) vs low (median value and below) population density cities. For the state level analysis, days to school closing was associated with cumulative incidence, with an adjusted rate ratio of 1.59 (95% CI:1.03,2.44), p=0.04 at 35 days. Some results were counterintuitive, including inverse associations between cumulative incidence and days to closure of non-essential business and restrictions on gatherings. This finding is likely due to reverse causality, where locations with slower growth rates initially chose not to implement measures, and later implemented measures when they absolutely needed to respond to increasing rates of infection. Effects of social distancing measures seemed to vary by population density in cities. Our results suggest that the effect of social distancing measures may differ between states and cities and between locations with different population densities. States and cities need individual approaches to containment of an epidemic, with an awareness of their own structure in terms of crowding and socio-economic variables. In an effort to reduce infection rates, cities may want to implement social distancing in advance of state mandates.

positive: COVID-19 Outbreak in Oman: Model-Driven Impact Analysis and Challenges Motivated by the rapid spread of COVID-19 all across the globe, we have performed simulations of a system dynamic epidemic spread model in different possible situations. The simulation, not only captures the model dynamic of the spread of the virus, but also, takes care of population and mobility data. The model is calibrated based on epidemic data and events specifically of Sultanate of Oman, which can easily be generalized. The simulation results are quite disturbing, indicating that, during a process of stringent social distancing and testing strategies, a small perturbation can lead to quite undesirable outcomes. The simulation results, although consistent in expected outcomes across changing parameters' values, also indicate a substantial mismatch with real numbers. An analysis of what can be the reason of this mismatch is also performed. Within these contradictions, for Oman, regarding the eradication of epidemic, the future is not extremely alarming.

positive: Risk for COVID-19 Resurgence Related to Duration and Effectiveness of Physical Distancing in Ontario, Canada

positive: Public Health Measures to Slow Community Spread of Coronavirus Disease 2019

positive: Sustaining Social Distancing Policies to Prevent a Dangerous Second Peak of COVID-19 Outbreak Governments around the world have enacted strict social distancing policies in order to slow the spread of COVID-19. The next step is figuring out when to relax these restrictions and to what degree. Our results predict potentially disastrous implications of ending these policies too soon, based on projections made from a Susceptible-Exposed-Infectious-Removed (SEIR) epidemic model. Even when infection rates appear to be slowing down or decreasing, prematurely returning to "business as usual" produces a severe second peak far worse than the first. Furthermore, such a second peak is made more likely when very severe restrictions are initially enacted. Only an appropriately measured and committed set of restrictions can appropriately control COVID-19 outbreak levels.

positive: Chopping the tail: how preventing superspreading can help to maintain COVID-19 control Disease transmission is notoriously heterogeneous, and SARS-CoV-2 is no exception. A skewed distribution where few individuals or events are responsible for the majority of transmission can result in explosive, superspreading events, which produce rapid and volatile epidemic dynamics, especially early or late in epidemics. Anticipating and preventing superspreading events can produce large reductions in overall transmission rates. Here, we present a compartmental (SEIR) epidemiological model framework for estimating transmission parameters from multiple imperfectly observed data streams, including reported cases, deaths, and mobile phone-based mobility that incorporates individual-level heterogeneity in transmission using previous estimates for SARS-CoV-1 and SARS-CoV-2. We parameterize the model for COVID-19 epidemic dynamics by estimating a time-varying transmission rate that incorporates the impact of non-pharmaceutical intervention strategies that change over time, in five epidemiologically distinct settings—Los Angeles and Santa Clara Counties, California; Seattle (King County), Washington; Atlanta (Dekalb and Fulton Counties), Georgia; and Miami (Miami-Dade County), Florida. We find the effective reproduction number [Formula: see text] dropped below 1 rapidly following social distancing orders in mid-March, 2020 and remained there into June in Santa Clara County and Seattle, but climbed above 1 in late May in Los Angeles, Miami, and Atlanta, and has trended upward in all locations since April. With the fitted model, we ask: how does truncating the tail of the individual-level transmission rate distribution affect epidemic dynamics and control? We find interventions that truncate the transmission rate distribution while partially relaxing social distancing are broadly effective, with impacts on epidemic growth on par with the strongest population-wide social distancing observed in April, 2020. Given that social distancing interventions will be needed to maintain epidemic control until a vaccine becomes widely available, “chopping off the tail” to reduce the probability of superspreading events presents a promising option to alleviate the need for extreme general social distancing.

positive: Mathematical modelling of COVID-19 transmission and mitigation strategies in the population of Ontario, Canada. BACKGROUND Physical-distancing interventions are being used in Canada to slow the spread of severe acute respiratory syndrome coronavirus 2, but it is not clear how effective they will be. We evaluated how different nonpharmaceutical interventions could be used to control the coronavirus disease 2019 (COVID-19) pandemic and reduce the burden on the health care system. METHODS We used an age-structured compartmental model of COVID-19 transmission in the population of Ontario, Canada. We compared a base case with limited testing, isolation and quarantine to scenarios with the following: enhanced case finding, restrictive physical-distancing measures, or a combination of enhanced case finding and less restrictive physical distancing. Interventions were either implemented for fixed durations or dynamically cycled on and off, based on projected occupancy of intensive care unit (ICU) beds. We present medians and credible intervals from 100 replicates per scenario using a 2-year time horizon. RESULTS We estimated that 56% (95% credible interval 42%-63%) of the Ontario population would be infected over the course of the epidemic in the base case. At the epidemic peak, we projected 107 000 (95% credible interval 60 760-149 000) cases in hospital (non-ICU) and 55 500 (95% credible interval 32 700-75 200) cases in ICU. For fixed-duration scenarios, all interventions were projected to delay and reduce the height of the epidemic peak relative to the base case, with restrictive physical distancing estimated to have the greatest effect. Longer duration interventions were more effective. Dynamic interventions were projected to reduce the proportion of the population infected at the end of the 2-year period and could reduce the median number of cases in ICU below current estimates of Ontario's ICU capacity. INTERPRETATION Without substantial physical distancing or a combination of moderate physical distancing with enhanced case finding, we project that ICU resources would be overwhelmed. Dynamic physical distancing could maintain health-system capacity and also allow periodic psychological andeconomic respite for populations.

positive: The effectiveness of non-pharmaceutical interventions in containing epidemics: a rapid review of the literature and quantitative assessment The number of confirmed COVID-19 cases has rapidly increased since discovery of the disease in December 2019. In the absence of medical countermeasures to stop the spread of the disease (i.e. vaccines), countries have responded by implementing a suite of non-pharmaceutical interventions (NPIS) to contain and mitigate COVID-19. Individual NPIs range in intensity (e.g. from lockdown to public health campaigns on personal hygiene), as does their impact on reducing disease transmission. This study uses a rapid review approach and investigates evidence from previous epidemic outbreaks to provide a quantitative assessment of the effectiveness of key NPIs used by countries to combat the COVID-19 pandemic. Results from the study are designed to help countries enhance their policy response as well as inform transition strategies by identifying which policies should be relaxed and which should not.

positive: COVID-19 Growth Rate Decreases with Social Capital Background: Social capital has been associated with many public health variables including mortality, obesity, diabetes, and sexually-transmitted disease rates. However, the relationship of social capital to the spread of infectious disease like COVID-19 is lacking. The COVID-19 pandemic presents an unprecedented threat to global health and economy, for which control strategies have relied on aggressive social distancing. However, an understanding of how social capital is related to changes in human mobility patterns for adherence to social distancing is lacking. Objective: This study examines the association between state- and county-level social capital indices and community health indices in the United States, and the growth rate of COVID-19 cases. It also examines changes in human mobility. Methods: Using publicly available state- and county-specific time series data for COVID-19 cases from March 13 to March 31, we used exponential fits to determine growth rate. We obtained publicly available mobility change data, originally measured from GPS-enabled mobile devices. The design was then state- and county-level correlation analysis with social capital and community health indices from the Social Capital Project (United States Senate). Results: In bivariate linear correlation analyses, we find social capital and community health indices were negatively associated with COVID-19 growth rates at both the state and county levels. The correlation was strongest at the county level for the community health index: a one-unit increase in the county community health index was associated with a decrease in the COVID-19 growth rate exponent by 0.045. In further bivariate correlation analyses, we find that social capital indices were negatively associated with retail/recreation movement and positively associated with residential movement. That is, an increase in social capital is correlated with slower COVID-19 infection spread and more adherence to social distancing protocols. Conclusion: Our results indicate the potential benefit of incorporating social capital concepts in planning policies to control the spread of COVID-19, e.g. different social distancing requirements in different communities. The results also indicate a need for further research into this potentially causal relationship, including examining interventions to increase social capital, community health, and institutional health.

positive: The impact of COVID-19 control measures on social contacts and transmission in Kenyan informal settlements Background Many low- and middle-income countries have implemented control measures against coronavirus disease 2019 (COVID-19). However, it is not clear to what extent these measures explain the low numbers of recorded COVID-19 cases and deaths in Africa. One of the main aims of control measures is to reduce respiratory pathogen transmission through direct contact with others. In this study we collect contact data from residents of informal settlements around Nairobi, Kenya to assess if control measures have changed contact patterns, and estimate the impact of changes on the basic reproduction number (R0). Methods We conducted a social contact survey with 213 residents of five informal settlements around Nairobi in early May 2020, four weeks after the Kenyan government introduced enhanced physical distancing measures and a curfew between 7pm and 5am. Respondents were asked to report all direct physical and non-physical contacts made the previous day, alongside a questionnaire asking about the social and economic impact of COVID-19 and control measures. We examined contact patterns by demographic factors, including socioeconomic status. We described the impact of COVID-19 and control measures on income and food security. We compared contact patterns during control measures to patterns from non-pandemic periods to estimate the change in R0. Findings We estimate that control measures reduced physical and non-physical contacts, reducing the R0 from around 2.6 to between 0.5 and 0.7, depending on the pre-COVID-19 comparison matrix used. Masks were worn by at least one person in 92% of contacts. Respondents in the poorest socioeconomic quintile reported 1.5 times more contacts than those in the richest. 86% of respondents reported a total or partial loss of income due to COVID-19, and 74% reported eating less or skipping meals due to having too little money for food. Interpretation COVID-19 control measures have had a large impact on direct contacts and therefore transmission, but have also caused considerable economic and food insecurity. Reductions in R0 are consistent with the linear epidemic growth in Kenya and other sub-Saharan African countries that implemented similar, early control measures. However, negative and inequitable impacts on economic and food security may mean control measures are not sustainable in the longer term.

positive: Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study BACKGROUND: Within 4 months of COVID-19 first being reported in the USA, it spread to every state and to more than 90% of all counties. During this period, the US COVID-19 response was highly decentralised, with stay-at-home directives issued by state and local officials, subject to varying levels of enforcement. The absence of a centralised policy and timeline combined with the complex dynamics of human mobility and the variable intensity of local outbreaks makes assessing the effect of large-scale social distancing on COVID-19 transmission in the USA a challenge. METHODS: We used daily mobility data derived from aggregated and anonymised cell (mobile) phone data, provided by Teralytics (Zürich, Switzerland) from Jan 1 to April 20, 2020, to capture real-time trends in movement patterns for each US county, and used these data to generate a social distancing metric. We used epidemiological data to compute the COVID-19 growth rate ratio for a given county on a given day. Using these metrics, we evaluated how social distancing, measured by the relative change in mobility, affected the rate of new infections in the 25 counties in the USA with the highest number of confirmed cases on April 16, 2020, by fitting a statistical model for each county. FINDINGS: Our analysis revealed that mobility patterns are strongly correlated with decreased COVID-19 case growth rates for the most affected counties in the USA, with Pearson correlation coefficients above 0·7 for 20 of the 25 counties evaluated. Additionally, the effect of changes in mobility patterns, which dropped by 35-63% relative to the normal conditions, on COVID-19 transmission are not likely to be perceptible for 9-12 days, and potentially up to 3 weeks, which is consistent with the incubation time of severe acute respiratory syndrome coronavirus 2 plus additional time for reporting. We also show evidence that behavioural changes were already underway in many US counties days to weeks before state-level or local-level stay-at-home policies were implemented, implying that individuals anticipated public health directives where social distancing was adopted, despite a mixed political message. INTERPRETATION: This study strongly supports a role of social distancing as an effective way to mitigate COVID-19 transmission in the USA. Until a COVID-19 vaccine is widely available, social distancing will remain one of the primary measures to combat disease spread, and these findings should serve to support more timely policy making around social distancing in the USA in the future. FUNDING: None.

positive: Monitoring social distancing and SARS-CoV-2 transmission in Brazil using cell phone mobility data Social distancing measures have emerged as the predominant intervention for containing the spread of COVID-19, but evaluating adherence and effectiveness remains a challenge. We assessed the relationship between aggregated mobility data collected from mobile phone users and the time-dependent reproduction number R(t), using severe acute respiratory illness (SARI) cases reported by Sao Paulo and Rio de Janeiro. We found that the proportion of individuals staying home all day (isolation index) had a strong inverse correlation with R(t) (rho<-0.7) and was predictive of COVID-19 transmissibility (p<0.0001). Furthermore, indexs of 46.7% had the highest accuracy (93.9%) to predict R(t) below one. This metric can be monitored in real time to assess adherence to social distancing measures and predict their effectiveness for controlling SARS-CoV-2 transmission.

positive: Nigeria and Italy Divergences in Coronavirus Experience: Impact of Population Density Background: The reports and information on coronavirus are not conspicuously emphasising the possible impact of population density on the explanation of difference in rapid spread and fatality due to the disease and not much has been done on bicountry comparisons. Objective: The study examined the impact of population density on the spread of COVID-19 pandemic in two sociodemographic divergent countries. Methods: The study conducted a scoping review of published and unpublished articles including blogs on incidences and fatalities of COVID-19. The analysis followed qualitative description and quantitative presentation of the findings using only frequency distribution, percentages, and graphs. Results: The two countries shared similar experience of "importation" of COVID-19, but while different states ordered partial lockdown in Nigeria, it was an immediate total lockdown in Italy. The physician/patient ratio is high in Italy (1 : 328) but low in Nigeria (1 : 2500), while population density is 221 in Nigeria and 206 in Italy. Daily change in incidence rate reduced to below 20% after 51 and 30 days of COVID-19 first incidence in Italy and Nigeria, respectively. Fatality rate has plummeted to below 10% after the 66th day in Italy but has not been stabilised in Nigeria. Conclusion: The authors upheld both governments' recommending measures that tilted towards personal hand-hygienic practices and social distancing. Authors suggested that if Italy with its high physician/patient ratio and lower population density compared to Nigeria could suffer high fatality from COVID-19 pandemic under four weeks, then Nigeria with its low physician/patient ratio and higher population density should prepare to face harder time if the pandemic persists.

positive: Physical distancing interventions and incidence of coronavirus disease 2019: natural experiment in 149 countries OBJECTIVE: To evaluate the association between physical distancing interventions and incidence of coronavirus disease 2019 (covid-19) globally. DESIGN: Natural experiment using interrupted time series analysis, with results synthesised using meta-analysis. SETTING: 149 countries or regions, with data on daily reported cases of covid-19 from the European Centre for Disease Prevention and Control and data on the physical distancing policies from the Oxford covid-19 Government Response Tracker. PARTICIPANTS: Individual countries or regions that implemented one of the five physical distancing interventions (closures of schools, workplaces, and public transport, restrictions on mass gatherings and public events, and restrictions on movement (lockdowns)) between 1 January and 30 May 2020. MAIN OUTCOME MEASURE: Incidence rate ratios (IRRs) of covid-19 before and after implementation of physical distancing interventions, estimated using data to 30 May 2020 or 30 days post-intervention, whichever occurred first. IRRs were synthesised across countries using random effects meta-analysis. RESULTS: On average, implementation of any physical distancing intervention was associated with an overall reduction in covid-19 incidence of 13% (IRR 0.87, 95% confidence interval 0.85 to 0.89; n=149 countries). Closure of public transport was not associated with any additional reduction in covid-19 incidence when the other four physical distancing interventions were in place (pooled IRR with and without public transport closure was 0.85, 0.82 to 0.88; n=72, and 0.87, 0.84 to 0.91; n=32, respectively). Data from 11 countries also suggested similar overall effectiveness (pooled IRR 0.85, 0.81 to 0.89) when school closures, workplace closures, and restrictions on mass gatherings were in place. In terms of sequence of interventions, earlier implementation of lockdown was associated with a larger reduction in covid-19 incidence (pooled IRR 0.86, 0.84 to 0.89; n=105) compared with a delayed implementation of lockdown after other physical distancing interventions were in place (pooled IRR 0.90, 0.87 to 0.94; n=41). CONCLUSIONS: Physical distancing interventions were associated with reductions in the incidence of covid-19 globally. No evidence was found of an additional effect of public transport closure when the other four physical distancing measures were in place. Earlier implementation of lockdown was associated with a larger reduction in the incidence of covid-19. These findings might support policy decisions as countries prepare to impose or lift physical distancing measures in current or future epidemic waves.

positive: Study of Epidemiological Characteristics and In-silico Analysis of the Effect of Interventions in the SARS-CoV-2 Epidemic in India After SARS-CoV-2 set foot in India, the Government took a number of steps to limit the spread of the disease in the country. This study involves assessing how the disease affected the population in the initial days of the epidemic. Data was collected from government-controlled and crowdsourced websites and analysed. Studying age and sex parameters of 413 Indian COVID-19 patients, the median age of the affected individuals was found to be 36 years (IQR, 25-54) with 20-39 years males being the most affected group. The number of affected males (66.34%) was more than that of the females (33.66%). Using Susceptible-Infected- Removed (SIR) model, the range of contact rate (β) of India was calculated and the role of public health interventions was assessed. If current contact rate continues, India may have 5583 to 13785 active cases at the end of 21 days lockdown.

positive: Estimating the Effect of Social Distancing Interventions on COVID-19 in the United States Since its global emergence in 2020, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused multiple epidemics in the United States. Because medical treatments for the virus are still emerging and a vaccine is not yet available, state and local governments have sought to limit its spread by enacting various social distancing interventions such as school closures and lockdown, but the effectiveness of these interventions is unknown. We applied an established, semi-mechanistic Bayesian hierarchical model of these interventions on SARS-CoV-2 spread in Europe to the United States. We estimated the effect of interventions across all states, contrasted the estimated reproduction number, Rt , for each state before and after lockdown, and contrasted predicted future fatalities with actual fatalities as a check on the model's validity. Overall, school closures and lockdown are the only interventions modeled that have a reliable impact on Rt , and lockdown appears to have played a key role in reducing Rt below 1.0. We conclude that reversal of lockdown, without implementation of additional, equally effective interventions, will enable continued, sustained transmission of SARS-CoV-2 in the United States.

positive: The Effectiveness of Targeted Quarantine for Minimising Impact of COVID-19 We model the extent to which age targeted quarantine can be used to reduce ICU admissions caused by novel coronavirus COVID-19. Using demographic data from New Zealand, we demonstrate that lowering the age threshold for quarantine to 50 years of age reduces ICU admissions drastically, and show that for sufficiently strict isolation protocols, isolating one third of the countries population for a total of 6 months is sufficient to avoid overwhelming ICU capacity throughout the entire course of the epidemic. Similar results are expected to hold for other countries, though some minor adaption will be required based on local age demographics and hospital facilities.

positive: Effect of non-pharmaceutical interventions for containing the COVID-19 outbreak in China BACKGROUND: The COVID-19 outbreak containment strategies in China based on non-pharmaceutical interventions (NPIs) appear to be effective. Quantitative research is still needed however to assess the efficacy of different candidate NPIs and their timings to guide ongoing and future responses to epidemics of this emerging disease across the World. METHODS: We built a travel network-based susceptible-exposed-infectious-removed (SEIR) model to simulate the outbreak across cities in mainland China. We used epidemiological parameters estimated for the early stage of outbreak in Wuhan to parameterise the transmission before NPIs were implemented. To quantify the relative effect of various NPIs, daily changes of delay from illness onset to the first reported case in each county were used as a proxy for the improvement of case identification and isolation across the outbreak. Historical and near-real time human movement data, obtained from Baidu location-based service, were used to derive the intensity of travel restrictions and contact reductions across China. The model and outputs were validated using daily reported case numbers, with a series of sensitivity analyses conducted. RESULTS: We estimated that there were a total of 114,325 COVID-19 cases (interquartile range [IQR] 76,776 – 164,576) in mainland China as of February 29, 2020, and these were highly correlated (p<0.001, R(2)=0.86) with reported incidence. Without NPIs, the number of COVID-19 cases would likely have shown a 67-fold increase (IQR: 44 – 94), with the effectiveness of different interventions varying. The early detection and isolation of cases was estimated to prevent more infections than travel restrictions and contact reductions, but integrated NPIs would achieve the strongest and most rapid effect. If NPIs could have been conducted one week, two weeks, or three weeks earlier in China, cases could have been reduced by 66%, 86%, and 95%, respectively, together with significantly reducing the number of affected areas. However, if NPIs were conducted one week, two weeks, or three weeks later, the number of cases could have shown a 3-fold, 7-fold, and 18-fold increase across China, respectively. Results also suggest that the social distancing intervention should be continued for the next few months in China to prevent case numbers increasing again after travel restrictions were lifted on February 17, 2020. CONCLUSION: The NPIs deployed in China appear to be effectively containing the COVID-19 outbreak, but the efficacy of the different interventions varied, with the early case detection and contact reduction being the most effective. Moreover, deploying the NPIs early is also important to prevent further spread. Early and integrated NPI strategies should be prepared, adopted and adjusted to minimize health, social and economic impacts in affected regions around the World.

positive: Initial Model for Impact of Social Distancing on CoVID-19 Spread The initial stages of the CoVID-19 coronavirus pandemic all around the world exhibit a nearly exponential rise in the number of infections with time. Planners, governments, and agencies are scrambling to figure out "How much? How bad?" and how to effectively treat the potentially large numbers of simultaneously sick people. Modeling the CoVID-19 pandemic using an exponential rise implicitly assumes a nearly unlimited population of uninfected persons ("dilute pandemic"). Once a significant fraction of the population is infected ("saturated pandemic"), an exponential growth no longer applies. A new model is developed here, which modifies the standard exponential growth function to account for factors such as Social Distancing. A Social Mitigation Parameter [SMP] /s is introduced to account for these types of society-wide changes, which can modify the standard exponential growth function, as follows: N(t)= No exp[ +Ko t/(1 + /s t)] . The doubling-time t/dbl=(ln2)/Ko can also be used to substitute for Ko, giving a {t/dbl, /s} parameter pair for comparing to actual CoVID-19 data. This model shows how the number of CoVID-19 infections can self-limit before reaching a saturated pandemic level. It also provides estimates for: (a) the timing of the pandemic peak, (b) the maximum number of new daily cases that would be expected, and (c) the expected total number of CoVID-19 cases. This model shows fairly good agreement with the presently available CoVID-19 pandemic data for several individual States, and the for the USA as a whole (6 Figures), as well as for various countries around the World (9 Figures). An augmented model with two Mitigation Parameters, /s and {beta}/s, is also developed, which can give better agreement with the daily new CoVID-19 data. Data-to-model comparisons also indicate that using /s by itself likely provides a worst-case estimate, while using both /s and {beta}/s likely provides a best-case estimate for the CoVID-19 spread.

positive: Synchronized travel restrictions across cities can be effective in COVID-19 control Mobility control measures are of crucial importance for public health planning in combating the COVID-19 pandemic. Previous studies established the impact of population outflow from Wuhan on the spatial spread of coronavirus in China and hinted the impact of the other three mobility patterns, i.e., population outflow from Hubei province excluding Wuhan, population inflow from cities outside Hubei, and intra-city population movement. However, the overall impact of all mobility patterns, or the impact of the different timing of mobility restriction intervention, are not systematically analyzed. Here we apply the cumulative confirmed cases and mobility data of 350 Chinese cities outside Hubei to explore the relationships between all mobility patterns and epidemic spread, and estimate the impact of local travel restrictions, both in terms of level and timing, on the epidemic control based on mobility change. The relationships were identified by using Pearson correlation analysis and stepwise multivariable linear regression, while scenario simulation was used to estimate the mobility change caused by local travel restrictions. Our analysis shows that: (1) all mobility patterns correlated with the spread of the coronavirus in Chinese cities outside Hubei, while the corrleations droppd with the implemetation of travel restrictions; (2) the cumulative confirmed cases in two weeks after the Wuhan lockdown was mainly brought by three patterns of inter-city population movement, while those in the third and fourth weeks after was significantly influenced by the number of intra-city population movement; (3) the local travel restrictions imposed by cities outside Hubei have averted 1,960 (95%PI: 1,474-2,447) more infections, taking 22.4% (95%PI: 16.8%-27.9%) of confirmed ones, in two weeks after the Wuhan lockdown, while more synchronized implementation would further decrease the number of confirmed cases in the same period by 15.7% (95%PI:15.4%-16.0%) or 1,378 (95%PI: 1,353-1,402) cases; and (4) local travel restrictions on different mobility patterns have different degrees of protection on cities with or without initial confirmed cases until the Wuhan lockdown. Our results prove the effectiveness of local travel restrictions and highlight the importance of synchronized implementation of mobility control across cities in mitigating the COVID-19 transmission.

positive: The Effect of Social Distancing on the Reach of an Epidemic in Social Networks How does social distancing affect the reach of an epidemic in social networks? We present Monte Carlo simulation results of a Susceptible- Infected-Removed (SIR) model on a network, where individuals are limited in the number of other people they can interact with. While increased social distancing always reduces the spread of an infectious disease, the magnitude varies greatly depending on the topology of the social network. Our results also reveal the importance of coordination at the global level. In particular, the public health benefits from social distancing to a group (e.g., a country) may be completely undone if that group maintains connections with outside groups that are not social distancing.

positive: The demand for inpatient and ICU beds for COVID-19 in the US: lessons from Chinese cities BACKGROUND: Sustained spread of SARS-CoV-2 has happened in major US cities. Capacity needs in Chinese cities could inform the planning of local healthcare resources. METHODS: We described the intensive care unit (ICU) and inpatient bed needs for confirmed COVID-19 patients in two Chinese cities (Wuhan and Guangzhou) from January 10 to February 29, 2020, and compared the timing of disease control measures in relation to the timing of SARS-CoV-2 community spread. We estimated the peak ICU bed needs in US cities if a Wuhan-like outbreak occurs. RESULTS: In Wuhan, strict disease control measures were implemented six weeks after sustained local transmission of SARS-CoV-2. Between January 10 and February 29, COVID-19 patients accounted for an average of 637 ICU patients and 3,454 serious inpatients on each day. During the epidemic peak, 19,425 patients (24.5 per 10,000 adults) were hospitalized, 9,689 (12.2 per 10,000 adults) were considered to be in serious condition, and 2,087 patients (2.6 per 10,000 adults) needed critical care per day. In Guangzhou, strict disease control measures were implemented within one week of case importation. Between January 24 and February 29, COVID-19 accounted for an average of 9 ICU patients and 20 inpatients on each day. During the epidemic peak, 15 patients were in critical condition, and 38 were classified as serious. If a Wuhan-like outbreak were to happen in a US city, the need for healthcare resources may be higher in cities with a higher prevalence of vulnerable populations. CONCLUSION: Even after the lockdown of Wuhan on January 23, the number of seriously ill COVID-19 patients continued to rise, exceeding local hospitalization and ICU capacities for at least a month. Plans are urgently needed to mitigate the effect of COVID-19 outbreaks on the local healthcare system in US cities.

positive: Optimal strategies for quarantine stopping in France. General expected patterns of strategies focusing on contact between age groups Due to the COVID-19 pandemic, many countries have implemented a complete lock-down of their population that may not be sustainable for long. To identify the best strategy to replace this full lock-down, sophisticated models that rely on mobility data have been developed. In this study, using the example of France as a case-study, we develop a simple model considering contacts between age classes to derive the general impact of partial lock-down strategies targeted at specific age groups. We found that epidemic suppression can only be achieved by targeting isolation of young and middle age groups with high efficiency. All other strategies tested result in a flatter epidemic curve, with outcomes in (e.g. mortality and health system over-capacity) dependent of the age groups targeted and the isolation efficiency. Targeting only the elderly can decrease the expected mortality burden, but in proportions lower than more integrative strategies involving several age groups. While not aiming to provide quantitative forecasts, our study shows the benefits and constraints of different partial lock-down strategies, which could help guide decision-making.

positive: Short-term forecasts and long-term mitigation evaluations for the COVID-19 epidemic in Hubei Province, China As an emerging infectious disease, the 2019 coronavirus disease (COVID-19) has developed into a global pandemic. During the initial spreading of the virus in China, we demonstrated the ensemble Kalman filter performed well as a short-term predictor of the daily cases reported in Wuhan City. Second, we used an individual-level network-based model to reconstruct the epidemic dynamics in Hubei Province at its early stage and examine the effectiveness of non-pharmaceutical interventions on the epidemic spreading with various scenarios. Our simulation results show that without continued control measures, the epidemic in Hubei Province could have become persistent. Only by continuing to decrease the infection rate through 1) protective measures and 2) social distancing can the actual epidemic trajectory that happened in Hubei Province be reconstructed in simulation. Finally, we simulate the COVID-19 transmission with non-Markovian processes and show how these models produce different epidemic trajectories, compared to those obtained with Markov processes. Since recent studies show that COVID-19 epidemiological parameters do not follow exponential distributions leading to Markov processes, future works need to focus on non-Markovian models to better capture the COVID-19 spreading trajectories. In addition, shortening the infectious period via early case identification and isolation can slow the epidemic spreading significantly.

positive: Effects of Proactive Social Distancing on COVID-19 Outbreaks in 58 Cities, China Cities across China implemented stringent social distancing measures in early 2020 to curb coronavirus disease outbreaks. We estimated the speed with which these measures contained transmission in cities. A 1-day delay in implementing social distancing resulted in a containment delay of 2.41 (95% CI 0.97-3.86) days.

positive: Epidemic Models for Personalised COVID-19 Isolation and Exit Policies Using Clinical Risk Predictions Background: In mid April 2020, with more than 2.5 billion people in the world following social distancing measures due to COVID-19, governments are considering relaxing lock-down. We combined individual clinical risk predictions with epidemic modelling to examine simulations of isolation and exit policies. Methods: We developed a method to include personalised risk predictions in epidemic models based on data science principles. We extended a standard susceptible-exposed-infected-removed (SEIR) model to account for predictions of severity, defined by the risk of an individual needing intensive care in case of infection. We studied example isolation policies using simulations with the risk-extended epidemic model, using COVID-19 data and estimates in France as of mid April 2020 (4 000 patients in ICU, around 7 250 total ICU beds occupied at the peak of the outbreak, 0.5% percent of patients requiring ICU upon infection). We considered scenarios varying in the discrimination performance of a risk prediction model, in the degree of social distancing, and in the severity rate upon infection. Confidence intervals were obtained using an Approximate Bayesian Computation approach. The framework may be used with other epidemic models, with other risk predictions, and for other epidemic outbreaks. Findings: Based on the data for France as of mid April 2020, simulations indicated that an exit policy considering clinical risk predictions starting on May 11, as planned by the government, could enable to immediately relax restrictions for an extra 10% (6 700 000 people) or more of the lowest-risk population, and consequently relax the restrictions on the remaining population up to two times (or several months) faster, with only a small proportion of the population remaining in isolation for an extended period of time -- while abiding to the current ICU capacity. In contrast, implementing the same exit policy without risk predictions would exceed the ICU capacity by a multiple. Sensitivity analyses showed that when the assumed percentage of severe patients among the population decreased, or the prediction model discrimination improved, or ICU capacity increased, policies based on risk models had a greater impact on the results of epidemic simulations. At the same time, sensitivity analyses also showed that differential isolation policies require that higher risk individuals comply with recommended restrictions. In general, our simulations showed that risk prediction models could always improve policy effectiveness, keeping everything else constant, in line with value of information arguments, even for models with moderate discrimination power. Interpretation: Clinical risk prediction models should be considered to manage outbreaks using a framework as the one developed. They can inform personalised isolation policies, for example by gradually restricting (relaxing) isolation from the highest (lowest) to the lowest (highest) predicted risk individuals, when such policies are considered. This may lead to both safer and faster outcomes than what can be achieved without such prediction models. They enable personalisation of policies, which are known to improve effectiveness in other non-healthcare contexts.

positive: An Optimal Predictive Control Strategy for COVID-19 (SARS-CoV-2) Social Distancing Policies in Brazil The global COVID-19 pandemic (SARS-CoV-2 virus) is the defining health crisis of our century. Due to the absence of vaccines and drugs that can help to fight it, the world solution to control the spread has been to consider public social distance measures that avoids the saturation of the health system. In this context, we investigate a Model Predictive Control (MPC) framework to determine the time and duration of social distancing policies. We use Brazilian data in the period from March to May of 2020. The available data regarding the number of infected individuals and deaths suffers from sub-notification due to the absence of mass tests and the relevant presence of the asymptomatic individuals. We estimate variations of the SIR model using an uncertainty-weighted Least-Squares criterion that considers both nominal and inconsistent-data conditions. Moreover, we add to our versions of the SIR model an additional dynamic state variable to mimic the response of the population to the social distancing policies determined by the government that affects the speed of COVID-19 transmission. Our control framework is within a mixed-logical formalism, since the decision variable is forcefully binary (the existence or the absence of social distance policy). A dwell-time constraint is included to avoid harsh shifting between these two states. Finally, we present simulation results to illustrate how such optimal control policy would operate. These results point out that no social distancing should be relaxed before mid August 2020. If relaxations are necessary, they should not be performed before the beginning this date and should be in small periods, no longer than 25 days. This paradigm would proceed roughly until January/2021. The second peak of infections, which has a forecast to the beginning of October, can be reduced if the periods of no-isolation days are shortened.

positive: Commentary on Ferguson, et al., “Impact of Non-pharmaceutical Interventions (NPIs) to Reduce COVID-19 Mortality and Healthcare Demand” A recent manuscript (Ferguson et al. in Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand, Imperial College COVID-19 Response Team, London, 2020. https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf) from Imperial College modelers examining ways to mitigate and control the spread of COVID-19 has attracted much attention. In this paper, we will discuss a coarse taxonomy of models and explore the context and significance of the Imperial College and other models in contributing to the analysis of COVID-19.

positive: Studying the progress of COVID-19 outbreak in India using SIRD model We explore a standard epidemiological model, known as the SIRD model, to study the COVID-19 infection in India, and a few other countries around the world. We use (a) the stable cumulative infection of various countries and (b) the number of infection versus the tests carried out to evaluate the model. The time-dependent infection rate is set in the model to obtain the best fit with the available data. The model is simulated aiming to project the probable features of the infection in India, various Indian states, and other countries. India imposed an early lockdown to contain the infection that can be treated by its healthcare system. We find that with the current infection rate and containment measures, the total active infection in India would be maximum at the end of June or beginning of July 2020. With proper containment measures in the infected zones and social distancing, the infection is expected to fall considerably from August. If the containment measures are relaxed before the arrival of the peak infection, more people from the susceptible population will fall sick as the infection is expected to see a three-fold rise at the peak. If the relaxation is given a month after the peak infection, a second peak with a moderate infection will follow. However, a gradual relaxation applied well ahead of peak infection, leads to a two-fold increase in the peak infection. The projection of the model is highly sensitive to the choice of the parameters and the available data. Our model provides a semi-quantitative overview of the progression of COVID-19 in India, with model projections reasonably replicating the current progress. However, since the pandemic is an ongoing dynamic phenomenon, the reported results are subjected to regular updates in consonance with the acquired real data.

positive: Public perceptions and experiences of social distancing and social isolation during the COVID-19 pandemic: A UK-based focus group study OBJECTIVE: Explore the perceptions and experiences of the UK public of social distancing and social isolation measures related to the COVID-19 pandemic. DESIGN: Qualitative study comprising five focus groups carried out online during the early stages of the UK's social distancing and isolation measures (5-12 days post lockdown). SETTING: Online video-conferencing PARTICIPANTS: 27 participants, all UK residents aged 18 years and older, representing a range of gender, ethnic, age and occupational backgrounds. RESULTS: The social distancing and isolation associated with COVID-19 policy has had having substantial negative impacts on the mental health and wellbeing of the UK public within a short time of policy implementation. It has disproportionately negatively affected those in low-paid or precarious employment. Practical social and economic losses - the loss of (in-person) social interaction, loss of income and loss of structure and routine - led to psychological and emotional 'losses' - the loss of motivation, loss of meaning, and loss of self-worth. Participants reported high adherence to distancing and isolation guidelines but reported seeing or hearing of non-adherence in others. A central concern for participants was the uncertainty duration of the measures, and their ability to cope longer-term. Some participants felt they would have lingering concerns over social contact while others were eager to return to high levels of social activity. CONCLUSIONS: A rapid response is necessary in terms of public health programming to mitigate the mental health impacts of COVID-19 social distancing and isolation. Initial high levels of support for, and adherence to, social distancing and isolation is likely to wane over time, particularly where end dates are uncertain. Social distancing and isolation 'exit strategies' must account for the fact that, although some individuals will voluntarily or habitually continue to socially distance, others will seek high levels of social engagement as soon as possible.

positive: Guidelines for preventing respiratory illness in older adults aged 60 years and above living in long-term care: A rapid review of clinical practice guidelines Background: The overall objective of this rapid review was to identify infection protection and control recommendations from published clinical practice guidelines (CPGs) for adults aged 60 years and older in long-term care settings Methods: Comprehensive searches in MEDLINE, EMBASE, the Cochrane Library, and relevant CPG publishers/repositories were carried out in early March 2020. Title/abstract and full-text screening, data abstraction, and quality appraisal (AGREE-II) were carried out by single reviewers. Results: A total of 17 relevant CPGs were identified, published in the USA (n=8), Canada (n=6), Australia (n=2), and the United Kingdom (n=1). All of the CPGs dealt with infection control in long-term care facilities (LTCF) and addressed various types of viral respiratory infections (e.g., influenza, COVID-19, severe acute respiratory syndrome). Ten or more CPGs recommended the following infection control measures in LTCF: hand hygiene (n=13), wearing personal protective equipment (n=13), social distancing or isolation (n=13), disinfecting surfaces (n=12), droplet precautions (n=12), surveillance and evaluation (n=11), and using diagnostic testing to confirm illness (n=10). While only two or more CPGs recommended these infection control measures: policies and procedures for visitors, staff and/or residents (n=9), respiratory hygiene/cough etiquette (n=9), providing supplies (n=9), staff and/or residents education (n=8), increasing communication (n=6), consulting or notifying health professionals (n=6), appropriate ventilation practices (n=2), and cohorting equipment (n=2). Ten CPGs also addressed management of viral respiratory infections in LTCF and recommended antiviral chemoprophylaxis (n=10) and one CPG recommended early mobilization of residents. Conclusion: The recommendations from current guidelines overall seem to support environmental measures for infection prevention and antiviral chemoprophylaxis for infection management as the most appropriate first-line response to viral respiratory illness in long-term care.

positive: Mitigation and herd immunity strategy for COVID-19 is likely to fail On the basis of a semi-realistic SIR microsimulation for Germany and Poland, we show that the R0 parameter interval for which the COVID-19 epidemic stays overcritical but below the capacity limit of the health care system to reach herd immunity is so narrow that a successful implementation of this strategy is likely to fail. Our microsimulation is based on official census data and involves household composition and age distribution as the main population structure variables. Outside household contacts are characterised by an out-reproduction number R* which is the only free parameter of the model. For a subcritical domain we compute the time till extinction and prevalence as a function of the initial number of infected individuals and R*. For the Polish city of Wroclaw we also discuss the combined impact of testing coverage and contact reduction. For both countries we estimate R* for disease progression until 20th of March 2020.

positive: Data-Driven Study of the COVID-19 Pandemic via Age-Structured Modelling and Prediction of the Health System Failure in Brazil amid Diverse Intervention Strategies In this work we propose a data-driven age-structured census-based SIRD-like epidemiological model capable of forecasting the spread of COVID-19 in Brazil. We model the current scenario of closed schools and universities, social distancing of individuals above sixty years old and voluntary home quarantine to show that it led to a considerable reduction in the number of infections as compared with a scenario without any control measures. Notwithstanding, our model predicts that the current measures are not enough to avoid overloading the health system, since the demand for intensive care units will soon surpass the number available. We also show that an urgent intense quarantine might be the only solution to avoid this scenario and, consequently, minimize the number of severe cases and deaths. On the other hand, we demonstrate that the early relaxation of the undergoing isolation measures would lead to an increase of millions of infections in a short period of time and the consecutive collapse of the health system.

positive: Changes in Subway Ridership in Response to COVID-19 in Seoul, South Korea: Implications for Social Distancing Introduction While numerous episodes of Coronavirus disease 2019 (COVID-19) infection and subsequent government announcements in South Korea were accompanied by widespread social distancing efforts by the people, it is unclear whether these episodes and government announcements were actually influential in improving social distancing, or whether the level of response among different demographic groups varied. Methods Data were downloaded from Seoul Data Open Plaza, and changes in the number of passengers on the Seoul Metropolitan Subway network between January 1, 2020, and March 31, 2020, were used to assess the extent to which people in Seoul practiced social distancing. Five events regarding COVID-19 that received wide public attention between January and March 2020 were identified and the changes in the number of passengers before and after each event were analyzed. Also, similar analyses were performed for 16 stations that were specific in either the age or purpose of the visit of the passengers. Results Compared to the third week of January 2020 (January 13-19), the mean daily number of passengers in all stations decreased by 2,984,857.4 or 40.6% by the first week of March (March 2-8). The percentage decrease in individual stations between this period was not significantly different between “young” and “old” stations (46.3% vs. 49.2%; p = 0.551) but was significantly smaller in “work” stations than in “leisure” stations (36.2% vs. 51.6%; p = 0.021). Of the five events, the first reported death due to COVID-19 in South Korea and the identification of a mass infection cluster in Daegu on February 20 were accompanied by the greatest decrease of the mean daily number of passengers (1,352,153.3 or 20.8%), while the first mass infection in Seoul on March 10 and the announcement of aggressive social distancing campaign on March 22 were accompanied by an increase in the number of passengers. Conclusions The number of subway passengers in Seoul decreased markedly during late February but slowly increased afterward, suggesting decreasing levels of risk perception and adherence to social distancing. Understanding the differing patterns of subway use by age or purpose of the visit may guide policymakers and the general public in shaping their future response to the current pandemic.

positive: Can we contain the COVID-19 outbreak with the same measures as for SARS? Summary The severe acute respiratory syndrome (SARS) outbreak in 2003 resulted in more than 8000 cases and 800 deaths. SARS was eventually contained by means of syndromic surveillance, prompt isolation of patients, strict enforcement of quarantine of all contacts, and in some areas top-down enforcement of community quarantine. By interrupting all human-to-human transmission, SARS was effectively eradicated. By contrast, by Feb 28, 2020, within a matter of 2 months since the beginning of the outbreak of coronavirus disease 2019 (COVID-19), more than 82 000 confirmed cases of COVID-19 have been reported with more than 2800 deaths. Although there are striking similarities between SARS and COVID-19, the differences in the virus characteristics will ultimately determine whether the same measures for SARS will also be successful for COVID-19. COVID-19 differs from SARS in terms of infectious period, transmissibility, clinical severity, and extent of community spread. Even if traditional public health measures are not able to fully contain the outbreak of COVID-19, they will still be effective in reducing peak incidence and global deaths. Exportations to other countries need not result in rapid large-scale outbreaks, if countries have the political will to rapidly implement countermeasures.

positive: Compliance and containment in social distancing: mathematical modeling of COVID-19 across townships In the early development of COVID-19, large-scale preventive measures, such as border control and air travel restrictions, were implemented to slow international and domestic transmissions. When these measures were in full effect, new cases of infection would be primarily induced by community spread, such as the human interaction within and between neighboring cities and towns, which is generally known as the meso-scale. Existing studies of COVID-19 using mathematical models are unable to accommodate the need for meso-scale modeling, because of the unavailability of COVID-19 data at this scale and the different timings of local intervention policies. In this respect, we propose a meso-scale mathematical model of COVID-19 using town-level infection data in the state of Connecticut. We consider the spatial interaction in terms of the inter-town travel in the model. Based on the developed model, we evaluated how different strengths of social distancing policy enforcement may impact future epidemic curves based on two evaluative metrics: compliance and containment. The developed model and the simulation results will establish the foundation for community-level assessment and better preparation for COVID-19.

positive: Impact assessment of non-pharmaceutical interventions against coronavirus disease 2019 and influenza in Hong Kong: an observational study BACKGROUND: A range of public health measures have been implemented to suppress local transmission of coronavirus disease 2019 (COVID-19) in Hong Kong. We examined the effect of these interventions and behavioural changes of the public on the incidence of COVID-19, as well as on influenza virus infections, which might share some aspects of transmission dynamics with COVID-19. METHODS: We analysed data on laboratory-confirmed COVID-19 cases, influenza surveillance data in outpatients of all ages, and influenza hospitalisations in children. We estimated the daily effective reproduction number (Rt) for COVID-19 and influenza A H1N1 to estimate changes in transmissibility over time. Attitudes towards COVID-19 and changes in population behaviours were reviewed through three telephone surveys done on Jan 20-23, Feb 11-14, and March 10-13, 2020. FINDINGS: COVID-19 transmissibility measured by Rt has remained at approximately 1 for 8 weeks in Hong Kong. Influenza transmission declined substantially after the implementation of social distancing measures and changes in population behaviours in late January, with a 44% (95% CI 34-53%) reduction in transmissibility in the community, from an estimated Rt of 1·28 (95% CI 1·26-1·30) before the start of the school closures to 0·72 (0·70-0·74) during the closure weeks. Similarly, a 33% (24-43%) reduction in transmissibility was seen based on paediatric hospitalisation rates, from an Rt of 1·10 (1·06-1·12) before the start of the school closures to 0·73 (0·68-0·77) after school closures. Among respondents to the surveys, 74·5%, 97·5%, and 98·8% reported wearing masks when going out, and 61·3%, 90·2%, and 85·1% reported avoiding crowded places in surveys 1 (n=1008), 2 (n=1000), and 3 (n=1005), respectively. INTERPRETATION: Our study shows that non-pharmaceutical interventions (including border restrictions, quarantine and isolation, distancing, and changes in population behaviour) were associated with reduced transmission of COVID-19 in Hong Kong, and are also likely to have substantially reduced influenza transmission in early February, 2020. FUNDING: Health and Medical Research Fund, Hong Kong.

positive: Association of County-Level Socioeconomic and Political Characteristics with Engagement in Social Distancing for COVID-19 The U.S. is the epicenter of the coronavirus disease 2019 (COVID-19) pandemic. In response, governments have implemented measures to slow transmission through "social distancing." However, the practice of social distancing may depend on prevailing socioeconomic conditions and beliefs. Using 15-17 million anonymized cell phone records, we find that lower per capita income and greater Republican orientation were associated with significantly reduced social distancing among U.S. counties. These associations persisted after adjusting for county-level sociodemographic and labor market characteristics as well as state fixed effects. These results may help policymakers and health professionals identify communities that are most vulnerable to transmission and direct resources and communications accordingly.

positive: Effects of the COVID-19 Pandemic on Population Mobility under Mild Policies: Causal Evidence from Sweden Sweden has adopted far less restrictive social distancing policies than most countries following the COVID-19 pandemic. This paper uses data on all mobile phone users, from one major Swedish mobile phone network, to examine the impact of the Coronavirus outbreak under the Swedish mild recommendations and restrictions regime on individual mobility and if changes in geographical mobility vary over different socio-economic strata. Having access to data for January-March in both 2019 and 2020 enables the estimation of causal effects of the COVID-19 outbreak by adopting a Difference-in-Differences research design. The paper reaches four main conclusions: (i) The daytime population in residential areas increased significantly (64 percent average increase); (ii) The daytime presence in industrial and commercial areas decreased significantly (33 percent average decrease); (iii) The distance individuals move from their homes during a day was substantially reduced (38 percent decrease in the maximum distance moved and 36 percent increase in share of individuals who move less than one kilometer from home); (iv) Similar reductions in mobility were found for residents in areas with different socioeconomic and demographic characteristics. These results show that mild government policies can compel people to adopt social distancing behavior.

positive: How will country-based mitigation measures influence the course of the COVID-19 epidemic?

positive: The Impact of Social Distancing on TheCourse of The Covid-19 Pandemic in FourEuropean Countries In this article the mortality data from four European countries arising from the Covid-19 pandemic is modelled using logistic functions. The countries chosen for examination are Spain, Italy, France and the UK. They have been selected because in each the pandemic is advanced, mortality high and any prospect of containment has passed. They have also been selected because in each social distancing has been used in an attempt to reduce peak daily mortality with relatively strict enforcement following a defined date. The choices of data set and model type is justified. The impact, if any, of social distancing is examined.

positive: Estimating the impact of physical distancing measures in containing COVID-19: an empirical analysis Background Epidemic modelling studies predict that physical distancing is critical in containing COVID-19. However, few empirical studies have validated this finding. Our study evaluates the effectiveness of different physical distancing measures in controlling viral transmission. Methods We identified three distinct physical distancing measures with varying intensity and implemented at different times - international travel controls, restrictions on mass gatherings, and lockdown-type measures - based on the Oxford COVID-19 Government Response Tracker. We also estimated the time-varying reproduction number (Rt) for 142 countries and tracked Rt temporally for two weeks following the 100th reported case in each country. We regressed Rt on the physical distancing measures and other control variables (income, population density, age structure, and temperature) and performed several robustness checks to validate our findings. Findings Complete travel bans and all forms of lockdown-type measures have been effective in reducing average Rt over the 14 days following the 100th case. Recommended stay-at-home advisories and partial lockdowns are as effective as complete lockdowns in outbreak control. However, these measures have to be implemented early to be effective. Lockdown-type measures should be instituted two weeks before the 100th case and travel bans about a week before detection of the first case. Interpretation A combination of physical distancing measures, if implemented early, can be effective in containing COVID-19 - tight border controls to limit importation of cases, encouraging physical distancing, moderately stringent measures such as working from home, and a full lockdown in the case of a probable uncontrolled outbreak.

positive: Impact of control strategies on COVID-19 pandemic and the SIR model based forecasting in Bangladesh. COVID-19 is transmitting worldwide drastically and infected nearly two and half million of people sofar. Till date 2144 cases of COVID-19 is confirmed in Bangladesh till 18th April though the stage-3/4 transmission is not validated yet. To project the final infection numbers in Bangladesh we used the SIR mathematical model. We also tried to demonstrate the impact of control strategies like social distancing on the COVID-19 transmission. Due to large population and socio-economic characteristics, we assumed 60% social distancing and lockdown can be possible. Assuming that, the predicated final size of infections will be 3782558 on the 92th day from the first infections. To estimate the impact of social distancing we assumed eight different scenarios, the predicted results confirmed the positive impact of this type of control strategies suggesting that by strict social distancing and lockdown, COVID-19 infection can be under control and then the infection cases will steadily decrease down to zero.

positive: Social distancing, population density, and spread of COVID-19 in England: a longitudinal study BACKGROUND: The UK government introduced social distancing measures between 16-22 March 2020, aiming to slow down transmission of COVID-19. AIM: To explore the spreading of COVID-19 in relation to population density after the introduction of social distancing measures. DESIGN & SETTING: Longitudinal design with 5-weekly COVID-19 incidence rates per 100 000 people for 149 English Upper Tier Local Authorities (UTLAs), between 16 March and 19 April 2020. METHOD: Multivariable multilevel model to analyse weekly incidence rates per 100 000 people; time was level-1 unit and UTLA level-2 unit. Population density was divided into quartiles. The model included an interaction between week and population density. Potential confounders were percentage aged ≥65, percentage non-white British, and percentage in two highest classes of the National Statistics Socioeconomic Classification. Co-variates were male life expectancy at birth, and COVID-19 prevalence rate per 100 000 people on March 15. Confounders and co-variates were standardised around the mean. RESULTS: Incidence rates per 100 000 people peaked in the week of March 30-April 5, showing higher adjusted incidence rate per 100 000 people (46.2; 95% confidence interval [CI] = 40.6 to 51.8) in most densely populated ULTAs (quartile 4) than in less densely populated ULTAs (quartile 1: 33.3, 95% CI = 27.4 to 37.2; quartile 2: 35.9, 95% CI = 31.6 to 40.1). Thereafter, incidence rate dropped in the most densely populated ULTAs resulting in rate of 22.4 (95% CI = 16.9 to 28.0) in the week of April 13-19; this was lower than in quartiles 1, 2, and 3, respectively 31.4 (95% CI = 26.5 to 36.3), 34.2 (95% CI = 29.9 to 38.5), and 43.2 (95% CI = 39.0 to 47.4). CONCLUSION: After the introduction of social distancing measures, the incidence rates per 100 000 people dropped stronger in most densely populated ULTAs.

positive: COVID-19 in Colombia endpoints. Are we different, like Europe? Abstract The infection by the new coronavirus (SARS-CoV-2) has taken the dimension of a pandemic, affecting more than 160 countries in a few weeks. In Colombia, despite the implementation of the rules established by the national government, exists an elevate concern both for mortality and for the limited capacity of the health system to respond effectively to the needs of patients infected. For Colombia, assuming a case fatality rate among people infected with SARS-CoV-2 of 0.6% (average data from the information reported for Latin American countries for March 18) (Table 1), the number of deaths, in one or two weeks, could be 16 and 243, respectively. These estimates differ markedly from those documented in countries such as Spain and Italy, in which COVID-19 case fatality rates exceed 8% (case of Italy) and from the percentage of patients who have required intensive care, which has ranged from 9% to 11% of patients in Mediterranean European countries. These differences could be explained due to: a) the percentage of the population at risk (individuals older than 60 years); b) a higher epidemiological exposure to viral respiratory infections associated with more frequent exposure to them, due to geographic and climatic conditions; c) less spread of the virus by location in the tropical zone; and d) earlier preventive measures to contain the spread of SARS-CoV-2 infection. Therefore, it is possible to establish that the situation in this country will be different from in European Mediterranean and that Colombia could have different endpoints from Spain and Italy.

positive: A framework for identifying regional outbreak and spread of COVID-19 from one-minute population-wide surveys Coronavirus infection spreads in clusters and therefore early identification of these clusters is critical for slowing down the spread of the virus. Here, we propose that daily population-wide surveys that assess the development of symptoms caused by the virus could serve as a strategic and valuable tool for identifying such clusters to inform epidemiologists, public health officials, and policy makers. We show preliminary results from a survey of over 38,000 Israelis and call for an international consortium to extend this concept in order to develop predictive models. We expect such data to allow: Faster detection of spreading zones and patients; Obtaining a current snapshot of the number of people in each area who have developed symptoms; Predicting future spreading zones several days before an outbreak occurs; Evaluating the effectiveness of the various social distancing measures taken, and their contribution to reduce the number of symptomatic people. Such information can provide a valuable tool for decision makers to decide which areas need strengthening of social distancing measures and which areas can be relieved. Researchers from the U.S, Spain, and Italy have adopted our approach and we are collaborating to further improve it. We call with urgency for other countries to join this international consortium, and to share methods and data collected from these daily, simple, one-minute surveys.

positive: Mandatory Social Distancing Associated With Increased Doubling Time: An Example Using Hyperlocal Data

positive: Accounting for underreporting in mathematical modelling of transmission and control of COVID-19 in Iran BACKGROUND: Iran has been the hardest hit country by the outbreak of SARS-CoV-2 in the Middle East with 74,877 confirmed cases and 4,683 deaths as of 15 April 2020. With a relatively high case fatality ratio and limited testing capacity, the number of confirmed cases reported is suspected to suffer from significant under-reporting. Therefore, understanding the transmission dynamics of COVID-19 and assessing the effectiveness of the interventions that have taken place in Iran while accounting for the uncertain level of underreporting is of critical importance. We use a mathematical epidemic model utilizing official confirmed data and estimates of underreporting to understand how transmission in Iran has been changing between February and April 2020. METHODS: We developed a compartmental transmission model to estimate the effective reproduction number and its fluctuations since the beginning of the outbreak in Iran. We associate the variations in the effective reproduction number with a timeline of interventions and national events. The estimation method also accounts for the underreporting due to low case ascertainment by estimating the percentage of symptomatic cases using delay adjusted case fatality ratio based on the distribution of the delay from hospitalization to death. FINDINGS: Our estimates of the effective reproduction number ranged from 0.66 to 1.73 between February and April 2020, with a median of 1.16. We estimate a reduction in the effective reproduction number during this period, from 1.73 (95% CI 1.60-1.87) on 1 March 2020 to 0.69 (95% CI 0.68-0.70) on 15 April 2020, due to various non-pharmaceutical interventions including school closures, a ban on public gatherings including sports and religious events, and full or partial closure of non-essential businesses. Based on these estimates and given that a near complete containment is no longer feasible, it is likely that the outbreak may continue until the end of the 2020 if the current level of physical distancing and interventions continue and no effective vaccination or therapeutic are developed and made widely available. INTERPRETATION: The series of non-pharmaceutical interventions and the public compliance that took place in Iran are found to be effective in slowing down the speed of the spread of COVID-19 within the studied time period. However, we argue that if the impact of underreporting is overlooked, the estimated transmission and control dynamics could mislead the public health decisions, policy makers, and general public especially in the earlier stages of the outbreak. FUNDING: Nil.

positive: COVID-19 pandemic scenario in India compared to China and rest of the world: a data driven and model analysis The COVID-19 is a rapidly spreading respiratory illness caused with the infection of SARS-CoV-2. The COVID-19 data from India was compared with China and rest of the world. The average values of daily growth rate (DGR), case recovery rate (CRR), case fatality rate (CFR), serial interval (SI) of COVID-19 in India was 17%, 8.25%, and 1.87%, and 5.76 days respectively, as of April 9, 2020. The data driven estimates of basic reproduction number (R0), average reproduction number (R) and effective reproduction number (Re) were 1.03, 1.73, and 1.35, respectively. The results of exponential and SIR model showed higher estimates of R0, R and Re. The data driven as well as estimated COVID-19 cases reflect the growing nature of the epidemic in India and world excluding China, whereas the same in China reveal the involved population became infected with the disease and moved into the recovered stage. The epidemic size of India was estimated to be ~30,284 (as of April 15, 2020 with 12,370 infectious cases) with an estimated end of the epidemic on June 9, 2020. The Re values in India before and after lockdown were 1.62 and 1.37 respectively, with SI 5.52 days and 5.98 days, respectively, as of April 17, 2020, reflecting the effectiveness of lockdown strategies. Beyond April 17, 2020, our estimate of 24,431 COVID-19 infected cases with lockdown is 78% lower compared to the 112,042 case estimates in absence of lockdown, on April 27, 2020. To early end of the COVID-19 epidemic, strong social distancing is important.

positive: Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study BACKGROUND: Non-pharmaceutical interventions have been implemented to reduce transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the UK. Projecting the size of an unmitigated epidemic and the potential effect of different control measures has been crucial to support evidence-based policy making during the early stages of the epidemic. This study assesses the potential impact of different control measures for mitigating the burden of COVID-19 in the UK. METHODS: We used a stochastic age-structured transmission model to explore a range of intervention scenarios, tracking 66·4 million people aggregated to 186 county-level administrative units in England, Wales, Scotland, and Northern Ireland. The four base interventions modelled were school closures, physical distancing, shielding of people aged 70 years or older, and self-isolation of symptomatic cases. We also modelled the combination of these interventions, as well as a programme of intensive interventions with phased lockdown-type restrictions that substantially limited contacts outside of the home for repeated periods. We simulated different triggers for the introduction of interventions, and estimated the impact of varying adherence to interventions across counties. For each scenario, we projected estimated new cases over time, patients requiring inpatient and critical care (ie, admission to the intensive care units [ICU]) treatment, and deaths, and compared the effect of each intervention on the basic reproduction number, R(0). FINDINGS: We projected a median unmitigated burden of 23 million (95% prediction interval 13–30) clinical cases and 350 000 deaths (170 000–480 000) due to COVID-19 in the UK by December, 2021. We found that the four base interventions were each likely to decrease R(0), but not sufficiently to prevent ICU demand from exceeding health service capacity. The combined intervention was more effective at reducing R(0), but only lockdown periods were sufficient to bring R(0) near or below 1; the most stringent lockdown scenario resulted in a projected 120 000 cases (46 000–700 000) and 50 000 deaths (9300–160 000). Intensive interventions with lockdown periods would need to be in place for a large proportion of the coming year to prevent health-care demand exceeding availability. INTERPRETATION: The characteristics of SARS-CoV-2 mean that extreme measures are probably required to bring the epidemic under control and to prevent very large numbers of deaths and an excess of demand on hospital beds, especially those in ICUs. FUNDING: Medical Research Council.

positive: An international comparison of the second derivative of COVID-19 deaths after implementation of social distancing measures This work compares deaths for confirmed COVID-19 cases in China to eight other countries, Italy, Spain, France, USA, UK, Germany, Netherlands and South Korea. After implementing varying intensities and timing of social distancing measures, several appear to be converging onto the decline in the daily growth rate of deaths, or relative second derivative of total deaths, seen in China after the implementation an aggressive social distancing policy. By calculating future trajectories in these countries based on the observed Chinese fatality statistics, an estimate of the total deaths and maximum daily death rates over a defined period of time is made. Our lower bound estimate for the United Kingdom based on the real data approximates the lower bound estimate of the recent modelling study of Ferguson et al. [1]. These results suggest there may be a threshold of effective public health intervention. Our method of viewing the data may be helpful in monitoring the course of the epidemic, judging the effectiveness of implementation, and monitoring the relaxation of social distancing.

positive: Optimal control of the COVID-19 pandemic with non-pharmaceutical interventions The COVID-19 pandemic has forced societies across the world to resort to social distancing to slow the spread of the SARS-CoV-2 virus. Due to the economic impacts of social distancing, there is growing desire to relax these measures. To characterize a range of possible strategies for control and to understand their consequences, we performed an optimal control analysis of a mathematical model of SARS-CoV-2 transmission. Given that the pandemic is already underway and controls have already been initiated, we calibrated our model to data from the US and focused our analysis on optimal controls from May 2020 through December 2021. We found that a major factor that differentiates strategies that prioritize lives saved versus reduced time under control is how quickly control is relaxed once social distancing restrictions expire in May 2020. Strategies that maintain control at a high level until summer 2020 allow for tapering of control thereafter and minimal deaths, whereas strategies that relax control in the short term lead to fewer options for control later and a higher likelihood of exceeding hospital capacity. Our results also highlight that the potential scope for controlling COVID-19 until a vaccine is available depends on epidemiological parameters about which there is still considerable uncertainty, including the basic reproduction number and the effectiveness of social distancing. In light of those uncertainties, our results do not constitute a quantitative forecast and instead provide a qualitative portrayal of possible outcomes from alternative approaches to control.

positive: Importance of Social Distancing: Modeling the spread of 2019-nCoV using Susceptible-Infected-Quarantined-Recovered-t model Background The Novel Coronavirus that originated in Wuhan, Hubei, China, has raised global concerns and has been declared a pandemic. The infection shows the primary symptoms of pneumonia and has an incubation period, with the majority of people showing symptoms within 14 days. Online Social Networks are the closest simulations of real-world networks and have similar topology characteristics. This article simulates the spread and control of the nCoV-19 using the SIQR-t model to highlight the importance of self-quarantine and exercise of proper health care as a method to prevent the spread of the virus. Method The article uses the Susceptible-Infected-Quarantined-Recovered model with modification, introducing 14 different Infected states depending on the number of days the host has been carrying the infection. We simulate the spread of 2019-nCoV on human interaction similar graph taken from Online Social Network Epinions, of about 75000 nodes, similar to a small town or settlement. The infection rates depend on the sanitation and cleanliness these people exercise. Results When people practice self-quarantine and hygiene, aided by the governmental efforts of testing and quarantine, the cumulative number of affected people fall drastically. The decrease is apparent in time-based simulations of the spread received from the study. Conclusion The 2019-nCoV is a highly infectious zoonotic virus. It has spread like a pandemic, and governments across the world have launched quarantines. The results of the SIQR-t model indicate that hygiene and social-distancing can reduce its impact and sharply decrease the infection scale. Individual efforts are key to the control.

positive: Social distancing to slow the U.S. COVID-19 epidemic: an interrupted time-series analysis Background: Social distancing measures to address the U.S. COVID-19 epidemic may have significant health, social, and economic impacts. Objective: To estimate the mean change in state-level COVID-19 epidemic growth before versus after the implementation of statewide social distancing measures. Design: Interrupted time-series analysis. Setting: United States. Measurements: Our primary exposure was time in relation to implementation of the first statewide social distancing measure. The pre-implementation period began 14 days prior to implementation and included up to 3 days after implementation to account for incubation. Post-implementation began 4 days after, up to and including March 30. Our primary outcome was the COVID-19 growth rate, calculated as the log of daily COVID-19 cases minus the log of daily COVID-19 cases on the prior day. Results: All states applied some form of statewide social distancing between March 10-27. The mean daily COVID-19 growth rate decreased beginning four days after implementation of the first statewide social distancing measures, by an additional 0.8% per day; 95% CI, -1.4% to -0.2%; P=0.002). This reduction corresponds to an increase in doubling time of the epidemic from 3.3 days (before) to 5.0 days (at 14 days after implementation). Limitations: Potential bias due to the aggregate nature of the ecological data, potential confounding by contemporaneous changes (e.g., increases in testing), and potential underestimation of social distancing due to spillovers across neighboring states. Conclusion: Statewide social distancing measures were associated with a decrease in U.S. COVID-19 epidemic growth. Based on the size of the epidemic at the time of implementation in each state, social distancing measures were associated with a decrease of 3,090 cases at 7 days, and 68,255 cases at 14 days, after implementation.

positive: Quantifying social distancing arising from pandemic influenza Local epidemic curves during the 1918–1919 influenza pandemic were often characterized by multiple epidemic waves. Identifying the underlying cause(s) of such waves may help manage future pandemics. We investigate the hypothesis that these waves were caused by people avoiding potentially infectious contacts—a behaviour termed ‘social distancing’. We estimate the effective disease reproduction number and from it infer the maximum degree of social distancing that occurred during the course of the multiple-wave epidemic in Sydney, Australia. We estimate that, on average across the city, people reduced their infectious contact rate by as much as 38%, and that this was sufficient to explain the multiple waves of this epidemic. The basic reproduction number, R(0), was estimated to be in the range of 1.6–2.0 with a preferred estimate of 1.8, in line with other recent estimates for the 1918–1919 influenza pandemic. The data are also consistent with a high proportion (more than 90%) of the population being initially susceptible to clinical infection, and the proportion of infections that were asymptomatic (if this occurs) being no higher than approximately 9%. The observed clinical attack rate of 36.6% was substantially lower than the 59% expected based on the estimated value of R(0), implying that approximately 22% of the population were spared from clinical infection. This reduction in the clinical attack rate translates to an estimated 260 per 100 000 lives having been saved, and suggests that social distancing interventions could play a major role in mitigating the public health impact of future influenza pandemics.

positive: Open Data Resources for Fighting COVID-19 We provide an insight into the open data resources pertinent to the study of the spread of Covid-19 pandemic and its control. We identify the variables required to analyze fundamental aspects like seasonal behaviour, regional mortality rates, and effectiveness of government measures. Open data resources, along with data-driven methodologies, provide many opportunities to improve the response of the different administrations to the virus. We describe the present limitations and difficulties encountered in most of the open-data resources. To facilitate the access to the main open-data portals and resources, we identify the most relevant institutions, at a world scale, providing Covid-19 information and/or auxiliary variables (demographics, mobility, etc.). We also describe several open resources to access Covid-19 data-sets at a country-wide level (i.e. China, Italy, Spain, France, Germany, U.S., etc.). In an attempt to facilitate the rapid response to the study of the seasonal behaviour of Covid-19, we enumerate the main open resources in terms of weather and climate variables. CONCO-Team: The authors of this paper belong to the CONtrol COvid-19 Team, which is composed of different researches from universities of Spain, Italy, France, Germany, United Kingdom and Argentina. The main goal of CONCO-Team is to develop data-driven methods for the better understanding and control of the pandemic.

positive: A modified SEIR model to predict the COVID-19 outbreak in Spain and Italy: simulating control scenarios and multi-scale epidemics After the spread of SARS-CoV-2 epidemic out of China, evolution in the pandemic worldwide shows dramatic differences among countries. In Europe, the situation of Italy first and later Spain has generated great concern, and despite other countries show better prospects, large uncertainties yet remain on the future evolution and the efficacy of containment, mitigation or attack strategies. Here we applied a modified SEIR compartmental model accounting for the spread of infection during the latent period, in which we also incorporate effects of varying proportions of containment. We fit data to quarantined populations in order to account for the uncertainties in case reporting and study the scenario projections for the 17 individual regions (CCAA). Results indicate that with data for March 23, the epidemics follow an evolution similar to the isolation of 1,5 percent of the population and if there were no effects of intervention actions it might reach a maximum of over 1.4M infected around April 27. The effect on the epidemics of the ongoing partial confinement measures is yet unknown (an update of results with data until March 31st is included), but increasing the isolation around ten times more could drastically reduce the peak to over 100k cases by early April, while each day of delay in taking this hard containment scenario represents a 90 percent increase of the infected population at the peak. Dynamics at the sub aggregated levels of CCAA show epidemics at the different levels of progression with the most worrying situation in Madrid an Catalonia. Increasing alpha values up to 10 times, in addition to a drastic reduction in clinical cases, would also more than halve the number of deaths. Updates for March 31st simulations indicate a substantial reduction in burden is underway. A similar approach conducted for Italy pre- and post-interventions also begins to suggest substantial reduction in both infected and deaths has been achieved, showing the efficacy of drastic social distancing interventions.

positive: Modelling transmission and control of the COVID-19 pandemic in Australia We develop an agent-based model for a fine-grained computational simulation of the ongoing COVID-19 pandemic in Australia. This model is calibrated to reproduce key characteristics of COVID-19 transmission. An important calibration outcome is the age-dependent fraction of symptomatic cases, with this fraction for children found to be one-fifth of such fraction for adults. We apply the model to compare several intervention strategies, including restrictions on international air travel, case isolation, home quarantine, social distancing with varying levels of compliance, and school closures. School closures are not found to bring decisive benefits, unless coupled with high level of social distancing compliance. We report several trade-offs, and an important transition across the levels of social distancing compliance, in the range between 70% and 80% levels, with compliance at the 90% level found to control the disease within 13--14 weeks, when coupled with effective case isolation and international travel restrictions.

positive: Effects of Proactive Social Distancing on COVID-19 Outbreaks in 58 Cities, China. Cities across China implemented stringent social distancing measures in early 2020 to curb coronavirus disease outbreaks. We estimated the speed with which these measures contained transmission in cities. A 1-day delay in implementing social distancing resulted in a containment delay of 2.41 (95% CI 0.97-3.86) days.

positive: A path out of COVID-19 quarantine: an analysis of policy scenarios In this work we present an analysis of the two major strategies currently implemented around the world in the fight against COVID-19: Social distancing & shelter-in-place measures to protect the susceptible, and testing & contact-tracing to identify, isolate and treat the infected. The majority of countries have principally relied on the former; we consider the examples of Italy, Canada and the United States. By fitting a disease transmission model to daily case report data, we infer that in each of the three countries, the current level of national shutdown is equivalent to about half the population being under quarantine. We demonstrate that in the absence of other measures, scaling back social distancing in such a way as to prevent a second wave will take prohibitively long. In contrast, South Korea, a country that has managed to control and suppress its outbreak principally through mass testing and contact tracing, and has only instated a partial shutdown. For all four countries, we estimate the level of testing which would be required to allow a complete exit from shutdown and a full lifting of social distancing measures, without a resurgence of COVID-19. We find that a "brute-force" approach of untargeted universal testing requires an average testing rate of once every 36 to 48 hours for every individual, depending on the country. If testing is combined with contact tracing, and/or if tests are able to identify latent infection, then an average rate of once every 4 to 5 days is sufficient.

positive: Effect of the social distancing measures on the spread of COVID-19 in 10 highly infected countries Abstract From the end of 2019, an unprecedented novel coronavirus, which was named COVID-19 by the World Health Organization (WHO) emerged from Wuhan city, China. Despite rigorous global containment and quarantine efforts, the incidence of COVID-19 has continued to rise, with over 4 million confirmed-cases and over 300,000 deaths worldwide until mid-May. This study aims to present the effect of the promulgation of social distancing measures on the spread of COVID-19 in the cases of 10 highly infected countries. The authors focus on the statistics of the COVID-19 confirmed-cases and deaths in 10 highly infected countries, including The U.S., Spain, Italy, The U.K., France, Germany, Russia, Turkey, Iran and China, and the response to the pandemic of these countries in the period from January 11 to May 2, 2020. The relationships between the social distancing measures and the statistics of COVID-19 confirmed-cases and deaths were analyzed in order to elucidate the effectiveness of the social distancing measures on the spread of COVID-19 in 10 highly infected countries. The results showed it took1–4 weeks since the highest level of social distancing measures promulgation until the daily confirmed-cases and deaths showed signs of decreasing. The effectiveness of the social distancing measures on the spread of COVID-19 was different between the 10 focused countries. This variation is due to the difference in the levels of promulgated social distancing measures, as well as the difference in the COVID-19 spread situation at the time of promulgation between the countries.

positive: Evaluating the Efficacy of Stay-At-Home Orders: Does Timing Matter? BACKGROUND: The many economic, psychological, and social consequences of pandemics and social distancing measures create an urgent need to determine the efficacy of non-pharmaceutical interventions (NPIs), and especially those considered most stringent, such as stay-at-home and self-isolation mandates. This study focuses specifically on the efficacy of stay-at-home orders, both nationally and internationally, in the control of COVID-19. METHODS: We conducted an observational analysis from April to May 2020 and included countries and US states with known stay-at-home orders. Our primary exposure was the time between the date of the first reported case of COVID-19 to an implemented stay-at-home mandate for each region. Our primary outcomes were the time from the first reported case to the highest number of daily cases and daily deaths. We conducted simple linear regression analyses, controlling for the case rate of the outbreak. RESULTS: For US states and countries, a larger number of days between the first reported case and stay-at-home mandates was associated with a longer time to reach the peak daily case and death counts. The largest effect was among regions classified as the latest 10% to implement a mandate, which in the US, predicted an extra 35.3 days to the peak number of cases (95 % CI: 18.2, 52.5), and 38.3 days to the peak number of deaths (95 % CI: 23.6, 53.0). CONCLUSIONS: Our study supports the potential beneficial effect of earlier stay-at-home mandates, by shortening the time to peak case and death counts for US states and countries. Regions in which mandates were implemented late experienced a prolonged duration to reaching both peak daily case and death counts.

positive: Quantitative Relationship between Population Mobility and COVID-19 Growth Rate based on 14 Countries This study develops a framework for quantification of the impact of changes in population mobility due to social distancing on the COVID-19 infection growth rate. Using the Susceptible-Infected-Recovered (SIR) epidemiological model we establish that under some mild assumptions the growth rate of COVID-19 deaths is a time-delayed approximation of the growth rate of COVID-19 infections. We then hypothesize that the growth rate of COVID-19 infections is a function of population mobility, which leads to a statistical model that predicts the growth rate of COVID-19 deaths as a delayed function of population mobility. The parameters of the statistical model directly reveal the growth rate of infections, the mobility-dependent transmission rate, the mobility-independent recovery rate, and the critical mobility, below which COVID-19 growth rate becomes negative. We fitted the proposed statistical model on publicly available data from 14 countries where daily death counts exceeded 100 for more than 3 days as of May 6th, 2020. The publicly available Google Mobility Index (GMI) was used as a measure of population mobility at the country level. Our results show that the growth rate of COVID-19 deaths can be accurately estimated 20 days ahead as a quadratic function of the transit category of GMI (adjusted R-squared = 0.784). The estimated 95% confidence interval for the critical mobility is in the range between 36.1% and 47.6% of the pre-COVID-19 mobility. This result indicates that a significant reduction in population mobility is needed to reverse the growth of COVID-19 epidemic. Moreover, the quantitative relationship established herein suggests that a readily available, population-level metric such as GMI can be a useful indicator of the course of COVID-19 epidemic.

positive: COVID-19–We urgently need to start developing an exit strategy Abstract Aim The purpose of this perspective is to review the options countries have to exit the draconian “lock downs” in a carefully staged manner. Methods Experts from different countries experiencing Corona Virus Infectious Disease 2019 (COVID-19) review evidence and country specific approaches and results of their interventions. Results Three key factors are important: 1. Reintroduction from countries with ongoing community transmission; 2. The need for extensive testing capacity and widespread community testing, and 3. Adequate supply of personal protective equipment, PPE, to protect health care workers. Lifting social distancing is discussed at length. How to open manufacturing, construction and logistics. The opening og higher educational institutions and schools. The use of electronic surveillance is discussed. Conclusion Each country has to decide what is the best path forward. However, we can learn from each other and the approach is in reality very similar.

positive: The relative power of individual distancing efforts and public policies to curb the COVID-19 epidemics Lockdown curbs the COVID-19 epidemics but at huge costs. Public debates question its impact ompared with reliance on individual responsibility. We aim at understanding how rationally chosen self-protective behavior impacts the spread of the epidemics. We want to, first, assess the value of lockdown compared to a counterfactual that incorporates self-protection efforts under unknown disease prevalence; and second, assess how individual behavior modify the epidemic dynamics when mandatory policies are relaxed. We couple an SLIAR model, that includes asymptomatic transmission, with utility maximization: Individuals trade off economic and wellbeing costs from physical distancing with a lower infection risk. Effort depends on risk aversion, perceptions, and the value of contacts. In a Nash equilibrium, individual uncoordinated efforts yield average contact intensity, which drives epidemic transmission. Equilibrium effort differs markedly from constant, stochastic or proportional contacts reduction. It adjusts to reported cases in a way that creates a slightly decreasing plateau in epidemic prevalence. Calibration on French data shows that the number of deaths with no lockdown but equilibrium efforts is only 1/6 to 1/10 of the number predicted with business-as-usual. However, lockdown saves at least 50% more lives than individual efforts alone. Prolonged weaker restrictions prevent an exponential rebound. Public policies post-lockdown have a limited impact as they partly crowd out individual efforts. Compulsory mask wearing helps resume activity but has no impact on the epidemic. Communication that increases risk salience is more effective.

positive: Impact of Social Distancing Measures on COVID-19 Healthcare Demand in Central Texas A novel coronavirus (SARS-CoV-2) emerged in Wuhan, China in late 2019 and rapidly spread worldwide. In the absence of effective antiviral drugs and vaccines, well-targeted social distancing measures are essential for mitigating the COVID-19 pandemic, reducing strain on local health systems, and preventing mortality. Here, we provide a quantitative assessment of the efficacy of social distancing to slow COVID-19 transmission and reduce hospital surge, depending on the timing and extent of the measures imposed for a metropolitan region and its health care systems. We built a granular mathematical model of COVID-19 transmission that incorporated age-specific and risk-stratified heterogeneity, estimates for the transmission, and severity of COVID-19 using current best evidence. We performed thousands of stochastic simulations of COVID-19 transmission in the Austin-Round Rock Metropolitan Area to project the impact of school closures coupled with social distancing measures that were estimated to reduce non-household contacts by 0%, 25%, 50%, 75% or 90%. We compare early versus late implementation and estimate the number of COVID-19 hospitalizations, ICU patients, ventilator needs and deaths through mid-August, 2020. We queried local emergency services and hospital systems to estimate total hospital bed, ICU, and ventilator capacity for the region. We expected COVID-19 hospital beds and ICU requirements would surpass local capacity by mid-May if no intervention was taken. Assuming a four-day epidemic doubling time, school closures alone would be expected to reduce peak hospitalizations by only 18% and cumulative deaths by less than 3%. Immediate social distancing measures that reduced non-household contacts by over 75%, such as stay-at-home orders and closing of non-essential businesses, would be required to ensure that COVID-19 cases do not overwhelm local hospital surge capacity. Peak ICU bed demand prior to mid August 2020 would be expected to be reduced from 2,121 (95% CI: 2,018-2,208) with no intervention to 698 (95% CI: 204-1,100) with 75% social distancing and 136 (95% CI: 38-308) with 90% social distancing; current ICU bed capacity was estimated at 680. A two-week delay in implementation of such measures is projected to accelerate a local ICU bed shortage by four weeks. School closures alone hardly impact the epidemic curve. Immediate social distancing measures that reduce non-household contacts by over 75% were required to ensure that COVID-19 cases do not overwhelm local hospital surge capacity. These findings helped inform the Stay Home-Work Safe order enacted by the city of Austin, Texas on March 24, 2020 as a means of mitigating the emerging COVID-19 epidemic.

positive: Projections for novel coronavirus (COVID-19) and evaluation of epidemic response strategies for India BACKGROUND: The World Health Organization on 11 March 2020, declared COVID-19 as a pandemic. India initiated social distancing measures to combat the epidemic of COVID-19. The course of the epidemic of COVID-19 for India was predicted using stochastic probability–based mathematical modeling. METHODS: Data synthesis for the top few countries affected was studied for various factors affecting the epidemic. For projections of infected cases for India, the modified susceptible-exposed-infectious-removed/recovered framework modified for the effect of social distancing (Rho) was used. Simulation was carried out for 10,000 runs using python. Projections for infected cases and hospitalization requirement were estimated. RESULTS: The epidemic curve will peak in the third week of June in India with 17,525,869 and 2,153,200 infected people with reproduction number of 1.8 and Rho of 0.7 and 0.6, respectively. Compared with the baseline scenario of no social distancing, for transmissibility with R0 = 1.8, the reduction in infections due to social distancing measure is 78% (Rho = 0.7) and 97% (Rho = 0.6). Similarly for R0 = 2.2 and 2.4, the reduction in infected numbers slightly lowers to 62% and 66% with Rho = 0.7 and 92% and 75% with Rho = 0.6, respectively. With R0 = 1.8 and Rho = 0.6, the Intensive Care Unit (ICU) bed requirement is 107,660, whereas if transmissibility is high, the ICU bed requirement would increase to 1,994,682. CONCLUSIONS: The social distancing measures seem to have been working for India in absence of treatment in sight for COVID-19. Although with the government's response strategy of social distancing, the peak of the epidemic is extended giving more months for preparedness to the country; however, the sustainability of these measures is uncertain.

positive: Modeling the Transmission of Respiratory Infectious Diseases in Mass Transportation Systems Mass transportation is one of the areas that are badly hit by respiratory infectious disease outbreaks due to moderate to high exposure risk to pathogens brought about by the interaction among commuters. Here, we formulate agent-based models that simulate the spread of a respiratory infectious disease in a train wagon in the Manila Light Rail Transit System, and in a 49-seater public utility bus. We consider preventive measures such as implementation of social distancing, and limitation of interaction or movement among the commuters to investigate how these measures will inhibit disease transmission. We also consider the effect of protective gears and practices, crowd density, and prevalence of disease in the community on the possible number of newly-infected individuals. Our simulations show that (i) individuals must have protection with more than 90% effectiveness to inhibit transmission of the disease; (ii) social or physical distancing by more than 1m distance reduces the risk of being infected; (iii) minimizing movement or interaction with other passengers reduces the risk of transmission by 50%; (iv) passenger capacity should be less than 10-50% of the maximum seating capacity to reduce the number of infections depending on the level of imposed social distancing and passenger interaction; (v) vehicles with greater number of occupied seating capacity generate higher number of infections but vehicles with smaller dimensions have faster disease transmissions; and (vi) ideal set-up for a 24-seater train wagon (49-seater bus) is to allow a maximum of 12 (24) passengers, with little to no interaction among passengers, with social distancing of more than 1m distance apart, and each person has a protection with 90% effectiveness as much as possible. These results can aid policy makers in determining optimal strategies to minimize infections while maintaining transportation services during pandemics or disease outbreaks.

positive: Evaluation of effects of public health interventions on COVID-19 transmission for Pakistan: A mathematical simulation study Background: In an effort to contain the COVID-19 epidemic, many governments across the world have enforced lockdown or social distancing measures. Several outbreak models have been developed to investigate the effects of different public health strategies for COVID-19, but they have not been developed for Pakistan and other South East Asian countries, where a large proportion of global population resides. Methods: We developed a stochastic individual contact model by extending the widely-used Susceptible-Infectious-Recovered (SIR) compartment model with additional compartments to model both anticipated mitigating effects of public health intervention strategies for Pakistan. We estimated the projected spread, number of hospitalizations, and case fatalities under no intervention and four increasingly stringent public health strategies of social distancing and self-isolation at the national and provincial levels of Pakistan. Results: Our analysis shows that without any public health interventions the expected number of cumulative case fatalities is 671,596 in Pakistan with the virus is expected to peak in terms of the number of required ICU-hospitalizations at 198,593 persons by the end of the June 2020. The estimated total numbers of cumulative case fatalities are lower for other public health strategies with strict social distancing showing the lowest number of deaths at 1,588 (Self-isolation: n=341,359; Flexible social distancing strategy: n=3,995; and Exit strategy: n=28,214). The lowest number of required ICU-hospitalization is also estimated for strict social distancing strategy (n=266 persons at the end of May 2020). Generally, the simulated effects of the different public health strategies at the provincial-level were similar to the national-level with strict social distancing showing the fewest number of case fatalities and ICU-hospitalizations. Conclusion: Our results indicate that case fatalities and ICU-hospitalizations for Pakistan will be high without any public health interventions. While strict social distancing can potentially prevent a large number of deaths and ICU-hospitalizations, the government faces an important dilemma of potentially severe economic downfall. Consideration of a temporary strict social distancing strategy with gradual return of the lower-risk Pakistani population, as simulated in our exit strategy scenario, may an effective compromise between public health and economy of Pakistani population.

positive: School Opening Delay Effect on Transmission Dynamics of Coronavirus Disease 2019 in Korea: Based on Mathematical Modeling and Simulation Study BACKGROUND: Nonpharmaceutical intervention strategy is significantly important to mitigate the coronavirus disease 2019 (COVID-19) spread. One of the interventions implemented by the government is a school closure. The Ministry of Education decided to postpone the school opening from March 2 to April 6 to minimize epidemic size. We aimed to quantify the school closure effect on the COVID-19 epidemic. METHODS: The potential effects of school opening were measured using a mathematical model considering two age groups: children (aged 19 years and younger) and adults (aged over 19). Based on susceptible-exposed-infectious-recovered model, isolation and behavior-changed susceptible individuals are additionally considered. The transmission parameters were estimated from the laboratory confirmed data reported by the Korea Centers for Disease Control and Prevention from February 16 to March 22. The model was extended with estimated parameters and estimated the expected number of confirmed cases as the transmission rate increased after school opening. RESULTS: Assuming the transmission rate between children group would be increasing 10 fold after the schools open, approximately additional 60 cases are expected to occur from March 2 to March 9, and approximately additional 100 children cases are expected from March 9 to March 23. After March 23, the number of expected cases for children is 28.4 for 7 days and 33.6 for 14 days. CONCLUSION: The simulation results show that the government could reduce at least 200 cases, with two announcements by the Ministry of education. After March 23, although the possibility of massive transmission in the children's age group is lower, group transmission is possible to occur.

positive: A dynamic modeling tool for estimating healthcare demand from the COVID19 epidemic and evaluating population-wide interventions Objectives. Public health officials need tools to assist with anticipating the healthcare resources required to confront the SARS-COV-2 pandemic. We built a modeling tool to aid practicing public health officials with estimating healthcare demand from the pandemic in their jurisdictions and to evaluate the potential impacts of population-wide social-distancing interventions. Methods. The tool uses a SEIR compartmental model to project the local spread of the pandemic. Users input case counts, healthcare resources, and select intervention strategies to evaluate. Outputs include the number of infections and deaths with and without intervention, and the demand for hospital and critical care beds and ventilators relative to existing capacity. We illustrate the tool using data from three regions of Chile. Results. Our scenarios indicate a surge in COVID-19 patients could overwhelm Chilean hospitals by June, peaking in July or August at 6 to 50 times the current supply of beds and ventilators. A lockdown strategy or combination of case isolation, home quarantine, social distancing of individuals greater than 70 years, and telework interventions may keep treatment demand below capacity. Conclusions. Aggressive interventions can avert substantial morbidity and mortality from COVID-19. Our tool permits rapid evaluation of locally-applicable policy scenarios and updating of results as new data become available.

positive: Modeling the impact of social distancing, testing, contact tracing and household quarantine on second-wave scenarios of the COVID-19 epidemic The new coronavirus disease 2019 (COVID-19) has required the implementation of severe mobility restrictions and social distancing measures worldwide. While these measures have been proven effective in abating the epidemic in several countries, it is important to estimate the effectiveness of testing and tracing strategies to avoid a potential second wave of the COVID-19 epidemic. We integrate highly detailed (anonymized, privacy-enhanced) mobility data from mobile devices, with census and demographic data to build a detailed agent-based model to describe the transmission dynamics of SARS-CoV-2 in the Boston metropolitan area. We find that enforcing strict social distancing followed by a policy based on a robust level of testing, contact-tracing and household quarantine, could keep the disease at a level that does not exceed the capacity of the health care system. Assuming the identification of 50% of the symptomatic infections, and the tracing of 40% of their contacts and households, which corresponds to about 9% of individuals quarantined, the ensuing reduction in transmission allows the reopening of economic activities while attaining a manageable impact on the health care system. Our results show that a response system based on enhanced testing and contact tracing can play a major role in relaxing social distancing interventions in the absence of herd immunity against SARS-CoV-2.

positive: Estimates of the ongoing need for social distancing and control measures post-"lockdown" from trajectories of COVID-19 cases and mortality. By 21st April 2020 COVID_19 had caused more than 2m cases across more than 200 countries. The majority of countries with significant outbreaks introduced social distancing or "lockdown" measures to reduce viral transmission. The key question now in many countries is when, how, and to what extent these measures can be lifted. By fitting regression models to publically available data on daily numbers of newly-confirmed cases and mortality, trajectories, doubling times and reproduction number (R0) were estimated both before and under the control measures. These data ran up to 21st April 2020, and covered 67 countries that had provided sufficient data for modelling. The estimates of R0, before lockdown, based on these data were broadly consistent with those previously published at between 2.0 and 3.7 in the countries with the largest number of cases available for analysis (USA, Italy, Spain, France and UK). There was little evidence to suggest that the restrictions had reduced R far below 1 in many places, with Spain having the most rapid reductions - R0 0.71 (95%CI 0.65-0.78) based on cases and 0.81 (95%CI 0.77-0.85) based on mortality. Intermittent lockdown has been proposed as a means of controlling the outbreak while allowing periods of increase freedom and economic activity. These data suggest that few countries could have even one week per month unrestricted without seeing resurgence of the epidemic. Similarly, restoring 20% of the activity that has been prevented by the lockdowns looks difficult to reconcile with preventing the resurgence of the disease in most countries.

positive: Transitioning out of the Coronavirus Lockdown: A Framework for Zone-Based Social Distancing In the face of elevated pandemic risk, is it necessary to completely lock down the population, imposing extreme social distancing? Canonical epidemiological models suggest this may be unavoidable for months at a time, despite the heavy social and human cost of physically isolating people. Alternatively, people could retreat into socially or economically defined defensive zones, with more interactions inside their zone than across zones. Starting from a complete lockdown, zones could facilitate responsible reopening of education, government, and firms, as a well-implemented structure can dramatically slow the diffusion of the disease. This paper provides a framework for understanding and evaluating the effectiveness of zones for social distancing.

positive: Dynamic Modeling to Identify Mitigation Strategies for Covid-19 Pandemic Relevant pandemic-spread scenario simulations provide guiding principles for containment and mitigation policy developments. Here we devise a simple model to predict the effectiveness of different mitigation strategies. The model consists of a set of simple differential equations considering the population size, reported and unreported infections, reported and unreported recoveries and the number of Covid-19-inflicted deaths. For simplification, we assume that Covid-19 survivors are immune (e.g. mutations are not considered) and that the virus can only be passed on by persons with undetected infections. While the latter assumption is a simplification (it is neglected that e.g. hospital staff may be infected by detected patients with symptoms), it was introduced here to keep the model as simple as possible. Moreover, the current version of the model does not account for age-dependent differences in the death rates, but considers higher mortality rates due to temporary shortage of intensive care units. Some of the model parameters have been fitted to the reported cases outside of China1 from January 22 to March 12 of the 2020 Covid-19 pandemic. The other parameters were chosen in a plausible range to the best of our knowledge. We compared infection rates, the total number of people getting infected and the number of deaths in six different scenarios. Social distancing or increased testing can contain or drastically reduce the infections and the predicted number of deaths when compared to a situation without mitigation. We find that mass-testing alone and subsequent isolation of detected cases can be an effective mitigation strategy, alone and in combination with social distancing. However, unless one assumes that the virus can be globally defeated by reducing the number of infected persons to zero, testing must be upheld, albeit at reduced intensity, to prevent subsequent waves of infection. The model suggests that testing strategies can be equally effective as social distancing, though at much lower economical costs. We discuss how our mathematical model may help to devise an optimal mix of mitigation strategies against the Covid-19 pandemic. The website corona-lab.ch provides an interactive simulation tool based on the presented model.

positive: Public health interventions in India slowed the spread of COVID-19 epidemic dynamics Background The government of India implemented social distancing interventions to contain the COVID-19 epidemic. However, effects on epidemic dynamics are yet to be understood. Methods Rates of laboratory-confirmed COVID-19 infections per day and effective reproduction number (Rt) were estimated for 4 periods (Pre-lockdown and Lockdown Phases 1 to 3) according to nationally implemented phased interventions. Adoption of these interventions was estimated using Google mobility data. Estimates at the national level and for 12 Indian states most affected by COVID-19 are presented. Findings Daily case rates ranged from 0.03 to 30.05/10 million people across 4 discrete periods in India. From May 4-17, 2020, the National Capital Territory (NCT) of Delhi had the highest case rate (222/10 million people/day), whereas Kerala had the lowest (2.18/10 million/day). Average Rt was 1.99 (95% CI 1.93-2.06) for India; it ranged from 1.38 to 2.78, decreasing over time. Median mobility in India decreased in all contact domains, with the lowest being 21% in retail/recreation (95% CI 13-46%), except home which increased to 129% (95% CI 117-132%) compared to the 100% baseline value. Interpretation The Indian government imposed strict contact mitigation, followed by a phased relaxation, which slowed the spread of COVID-19 epidemic progression in India. The identified daily COVID-19 case rates and Rt will aid national and state governments in formulating ongoing COVID-19 containment plans. Furthermore, these findings may inform COVID-19 public health policy in developing countries with similar settings to India. Funding Non-funded.

positive: Social Distancing is Effective at Mitigating COVID-19 Transmission in the United States COVID-19 is present in every state and over 90 percent of all counties in the United States. Decentralized government efforts to reduce spread, combined with the complex dynamics of human mobility and the variable intensity of local outbreaks makes assessing the effect of large-scale social distancing on COVID-19 transmission in the U.S. is a challenge. We generate a novel metric to represent social distancing behavior derived from mobile phone data, and examine its relationship with COVID-19 case reports at the county level. Our analysis reveals that social distancing is strongly correlated with decreased COVID-19 case growth rates for the 25 most affected counties in the United States, with a lag period consistent with the incubation time of SARS-CoV-2. We also demonstrate evidence that social distancing was already under way in many U.S. counties before county and state-level policies were implemented. This study strongly supports social distancing as an effective way to mitigate COVID-19 transmission in the United States.

positive: Inter nation social lockdown versus medical care against COVID-19, a mild environmental insight with special reference to India Abstract Infection by coronavirus (CoV-19) has led to emergence of a pandemic called as Coronavirus Disease (COVID-19) that has so far affected about 210 countries. The dynamic data indicate that the pandemic by CoV-19 so far has infected 2,403,963 individuals, and among these 624,698 have recovered while, it has been fatal for 165,229. Without much experience, currently, the medicines that are clinically being evaluated for COVID-19 include chloroquine, hydroxychloroquine, azithromycin, tocilizumab, lopinavir, ritonavir, tocilizumab and corticosteroids. Therefore, countries such as Italy, USA, Spain and France with the most advanced health care system are partially successful to control CoV-19 infection. India being the 2nd largest populous country, where, the healthcare system is underdeveloped, major portion of population follow unhygienic lifestyle, is able to restrict the rate of both infection and death of its citizens from COVID-19. India has followed an early and a very strict social distancing by lockdown and has issued advisory to clean hands regularly by soap and/or by alcohol based sterilizers. Rolling data on the global index of the CoV infection is 13,306, and the index of some countries such as USA (66,148), Italy (175,055), Spain (210,126), France (83,363) and Switzerland (262,122) is high. The index of India has remained very low (161) so far, mainly due to early implementation of social lockdown, social distancing, and sanitizing hands. However, articles on social lockdown as a preventive measure against COVID-19 in PubMed are scanty. It has been observed that social lockdown has also drastic impacts on the environment especially on reduction of NO2 and CO2 emission. Slow infection rate under strict social distancing will offer time to researchers to come up with exact medicines/vaccines against CoV-19. Therefore, it is concluded that stringent social distancing via lockdown is highly important to control COVID-19 and also to contribute for self-regeneration of nature.

positive: Non-pharmaceutical interventions for the prevention of respiratory tract infections during Hajj pilgrimage Summary Overcrowding during the yearly Hajj mass gatherings is associated with increased risk of spreading infectious diseases, particularly respiratory diseases. Non-pharmaceutical interventions (e.g., hand hygiene, wearing face masks, social distancing) are known to reduce the spread of respiratory viruses from person to person and are therefore recommended to pilgrims by public health agencies. The implementation of effective public health policies and recommendations involves evaluating the adherence to and effectiveness of these measures in the specific context of the Hajj. This review summarizes the evidence related to the effectiveness of non-pharmaceutical interventions in preventing the spread of respiratory infectious diseases during the Hajj. Overall, although hand hygiene compliance is high among pilgrims, face mask use and social distancing remain difficult challenges. Data about the effectiveness of these measures at the Hajj are limited, and results are contradictory, highlighting the need for future large-scale studies.

positive: Derivation of the effective reproduction number R for COVID-19 in relation to mobility restrictions and confinement The spread of COVID-19 is posing an unprecedented threat to health systems worldwide[1]. The fast propagation of the disease combined with the existence of covert contagions by asymptomatic individuals make the controlling of this disease particularly challenging. The key parameter to track the progression of the epidemics is the effective reproduction number R, defined as the number of secondary infections generated by an infected individual[2]. The suppression of the epidemics is directly related to this value, and is attained when R<1.Here, we find an analytical expression for R as a function of mobility restrictions and confinement measures, using an epidemic model tailored for COVID-19. This expression for R is an extremely useful tool to design containment policies that are able to suppress the epidemics. We applied our epidemic model for the case of Spain, successfully forecasting both the observed incidence in each region and the overload of the health system. The expression for R allowed us to determine the precise reduction of mobility kappa_0 needed to bend the curve of epidemic incidence, which turned out to be kappa_0 ≈ 0.7. This value, for the case of Spain, translates to a total lockdown with the exception of the mobility associated to essential services, a policy that was finally enforced on March 28.

positive: Social distancing strategies for curbing the COVID-19 epidemic The SARS-CoV-2 pandemic is straining healthcare resources worldwide, prompting social distancing measures to reduce transmission intensity. The amount of social distancing needed to curb the SARS-CoV-2 epidemic in the context of seasonally varying transmission remains unclear. Using a mathematical model, we assessed that one-time interventions will be insufficient to maintain COVID-19 prevalence within the critical care capacity of the United States. Seasonal variation in transmission will facilitate epidemic control during the summer months but could lead to an intense resurgence in the autumn. Intermittent distancing measures can maintain control of the epidemic, but without other interventions, these measures may be necessary into 2022. Increasing critical care capacity could reduce the duration of the SARS-CoV-2 epidemic while ensuring that critically ill patients receive appropriate care.

positive: Impact of relaxing Covid-19 social distancing measures on rural North Wales: a simulation analysis Background: Social distancing policies aimed to limit Covid-19 are gradually being relaxed as nationally reported peaks in incident cases are passed. Population density is an important driver of national incidence rates; however peak incidences in rural regions may lag national figures by several weeks. We aimed to forecast the impact of relaxed social distancing rules on rural North Wales. Methods: Daily data on the deaths of people with a positive test for Covid-19 were obtained from Public Health Wales and the UK Government. Sigmoidal growth functions were fitted by non-linear least squares and model averaging used to extrapolate mortality over time. The dates of peak mortality incidences for North Wales, Wales and the UK; and the percentage predicted maximum mortality (as of 7th May 2020) were estimated. Results: The peak daily death rates in Wales and the UK were estimated to have occurred on the 14/04/2020 and 15/04/2020, respectively. For North Wales, this occurred on the 07/05/2020, corresponding to the date of analysis. The number of deaths reported in North Wales represents 31% of the predicted total cumulative number, compared with 71% and 60% for Wales and the UK, respectively. Conclusion: Policies governing the movement of people in the gradual release from lockdown are likely to impact significantly on areas -principally rural in nature- where cases of Covid-19, deaths and immunity are likely to be much lower than in populated areas. This is particularly difficult to manage across jurisdictions, such as between England and Wales, and in popular holiday destinations.

positive: Instantaneous R calculation for COVID-19 epidemic in Brazil COVID-19 pandemic represents a major challenge to health systems of all countries. Brazilian regions habe been showing marked di[ff]erences in onset and number of cases. Health authorities instituted widespread social distancing and lockdown measures but their implementation has also varied. The authors used data on con[fi]rmed cases of COVID-19 in Brazil and its states to calculate the value of instantaneous reproduction number at these regions. The results show a reduction of instantaneous reproduction number with time, probably due to social distancing measures put in place in the last weeks by brazillian authorities. It seems logical to maintain restrictions to social contact until the epidemic peak has occurred in Brazil.

positive: Social network-based distancing strategies to flatten the COVID 19 curve in a post-lockdown world Social distancing and isolation have been introduced widely to counter the COVID-19 pandemic. However, more moderate contact reduction policies become desirable owing to adverse social, psychological, and economic consequences of a complete or near-complete lockdown. Adopting a social network approach, we evaluate the effectiveness of three targeted distancing strategies designed to 'keep the curve flat' and aid compliance in a post-lockdown world. These are limiting interaction to a few repeated contacts, seeking similarity across contacts, and strengthening communities via triadic strategies. We simulate stochastic infection curves that incorporate core elements from infection models, ideal-type social network models, and statistical relational event models. We demonstrate that strategic reduction of contact can strongly increase the efficiency of social distancing measures, introducing the possibility of allowing some social contact while keeping risks low. This approach provides nuanced insights to policy makers for effective social distancing that can mitigate negative consequences of social isolation.

positive: Modeling the Effects of Non-PharmaceuticalInterventions on COVID-19 Spread in Kenya Mathematical modeling of non-pharmaceutical interventions (NPIs) of COVID-19 in Kenya is presented. An SEIR compartment model is considered with additional compartments of hospitalized population whose condition is severe or critical and also the fatalities compartment. The basic reproduction number (R_0) is computed by next generation matrix approach and later expressed as a time-dependent function so as to incorporate the NPIs into the model. The resulting system of ordinary differential equations (ODEs) are solved using fourth-order and fifth-order Runge-Kutta methods. Different intervention scenarios are considered and results show that, implementation of closure of education insitutions, curfew and partial lockdown yield predicted delayed peaks of the overall infections, severe cases and fatalities and subsequently containement of the pandemic in the country.

positive: Modeling, state estimation, and optimal control for the US COVID-19 outbreak The novel coronavirus SARS-CoV-2 and resulting COVID-19 disease have had an unprecedented spread and continue to cause an increasing number of fatalities worldwide. While vaccines are still under development, social distancing, extensive testing, and quarantining of confirmed infected subjects remain the most effective measures to contain the pandemic. These measures carry a significant socioeconomic cost. In this work, we introduce a novel optimization-based decision-making framework for managing the COVID-19 outbreak in the US. This includes modeling the dynamics of affected populations, estimating the model parameters and hidden states from data, and an optimal control strategy for sequencing social distancing and testing events such that the number of infections is minimized. The analysis of our extensive computational efforts reveals that social distancing and quarantining are most effective when implemented early, with quarantining of confirmed infected subjects having a much higher impact. Further, we find that “on-off” policies alternating between strict social distancing and relaxing such restrictions can be effective at “flattening” the curve while likely minimizing social and economic cost.

positive: The effect of COVID-19 and subsequent social distancing on travel behavior Abstract The spread of the COVID-19 virus has resulted in unprecedented measures restricting travel and activity participation in many countries. Social distancing, i.e., reducing interactions between individuals in order to slow down the spread of the virus, has become the new norm. In this viewpoint I will discuss the potential implications of social distancing on daily travel patterns. Avoiding social contact might completely change the number and types of out-of-home activities people perform, and how people reach these activities. It can be expected that the demand for travel will reduce and that people will travel less by public transport. Social distancing might negatively affect subjective well-being and health status, as it might result in social isolation and limited physical activity. As a result, walking and cycling, recreationally or utilitarian, can be important ways to maintain satisfactory levels of health and well-being. Policymakers and planners should consequently try to encourage active travel, while public transport operators should focus on creating ways to safely use public transport.

positive: Spread of COVID-19 through Georgia, USA. Near-term projections and impacts of social distancing via a metapopulation model Epidemiological forecasts of COVID-19 spread at the country and/or state level have helped shape public health interventions. However, such models leave a scale-gap between the spatial resolution of actionable information (i.e. the county or city level) and that of modeled viral spread. States and nations are not spatially homogeneous and different areas may vary in disease risk and severity. For example, COVID-19 has age-stratified risk. Similarly, ICU units, PPE and other vital equipment are not equally distributed within states. Here, we implement a county-level epidemiological framework to assess and forecast COVID-19 spread through Georgia, where 1,933 people have died from COVID-19 and 44,638 cases have been documented as of May 27, 2020. We find that county-level forecasts trained on heterogeneity due to clustered events can continue to predict epidemic spread over multi-week periods, potentially serving efforts to prepare medical resources, manage supply chains, and develop targeted public health interventions. We find that the premature removal of physical (social) distancing could lead to rapid increases in cases or the emergence of sustained plateaus of elevated fatalities.

positive: A Social Network Model of the COVID-19 Pandemic In the COVID-19 coronavirus pandemic, currently vaccines and specific anti-viral treatment are not yet available. Thus, preventing viral transmission by case isolation, quarantine, and social distancing is essential to slowing its spread. Here we model social networks using weighted graphs, where vertices represent individuals and edges represent contact. As public health measures are implemented, connectivity in the graph decreases, resulting in lower effective reproductive numbers, and reduced viral transmission. For COVID-19, model parameters were derived from the coronavirus epidemic in China, validated by epidemic data in Italy, then applied to the United States. We calculate that, in the U.S., the public is able to contain viral transmission by limiting the average number of contacts per person to less than 7 unique individuals over each 5 day period. This increases the average social distance between individuals to 10 degrees of separation.

positive: Isolation, quarantine, social distancing and community containment: pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak Public health measures were decisive in controlling the SARS epidemic in 2003. Isolation is the separation of ill persons from non-infected persons. Quarantine is movement restriction, often with fever surveillance, of contacts when it is not evident whether they have been infected but are not yet symptomatic or have not been infected. Community containment includes measures that range from increasing social distancing to community-wide quarantine. Whether these measures will be sufficient to control 2019-nCoV depends on addressing some unanswered questions.

positive: The impact of long-term non-pharmaceutical interventions on COVID-19 epidemic dynamics and control Non-pharmaceutical interventions to combat COVID-19 transmission have worked to slow the spread of the epidemic but can have high socio-economic costs. It is critical we understand the efficacy of non-pharmaceutical interventions to choose a safe exit strategy. Many current models are not suitable for assessing exit strategies because they do not account for epidemic resurgence when social distancing ends prematurely (e.g., statistical curve fits) nor permit scenario exploration in specific locations. We developed an SEIR-type mechanistic epidemiological model of COVID-19 dynamics to explore temporally variable non-pharmaceutical interventions. We provide an interactive tool and code to estimate the transmission parameter, β, and the effective reproduction number, [Formula: see text]. We fit the model to Santa Clara County, California, where an early epidemic start date and early shelter-in-place orders could provide a model for other regions. As of April 22, 2020, we estimate an R(E) of 0.982 (95% CI: 0.849 – 1.107) in Santa Clara County. After June 1 (the end-date for Santa Clara County shelter-in-place as of April 27), we estimate a shift to partial social distancing, combined with rigorous testing and isolation of symptomatic individuals, is a viable alternative to indefinitely maintaining shelter-in-place. We also estimate that if Santa Clara County had waited one week longer before issuing shelter-in-place orders, 95 additional people would have died by April 22 (95% CI: 7 – 283). Given early life-saving shelter-in-place orders in Santa Clara County, longer-term moderate social distancing and testing and isolation of symptomatic individuals have the potential to contain the size and toll of the COVID-19 pandemic in Santa Clara County, and may be effective in other locations.

positive: Using VERA to explain the impact of social distancing on the spread of COVID-19 COVID-19 continues to spread across the country and around the world. Current strategies for managing the spread of COVID-19 include social distancing. We present VERA, an interactive AI tool, that first enables users to specify conceptual models of the impact of social distancing on the spread of COVID-19. Then, VERA automatically spawns agent-based simulations from the conceptual models, and, given a data set, automatically fills in the values of the simulation parameters from the data. Next, the user can view the simulation results, and, if needed, revise the simulation parameters and run another experimental trial, or build an alternative conceptual model. We describe the use VERA to develop a SIR model for the spread of COVID-19 and its relationship with healthcare capacity.

positive: Predictions, role of interventions and effects of a historic national lockdown in India's response to the COVID-19 pandemic: data science call to arms With only 536 cases and 11 fatalities, India took the historic decision of a 21-day national lockdown on March 25 The lockdown was first extended to May 3 soon after the analysis of this paper was completed, and then to May 18 while this paper was being revised In this paper, we use a Bayesian extension of the Susceptible-Infected-Removed (eSIR) model designed for intervention forecasting to study the short- and long-term impact of an initial 21-day lockdown on the total number of COVID-19 infections in India compared to other less severe non-pharmaceutical interventions We compare effects of hypothetical durations of lockdown on reducing the number of active and new infections We find that the lockdown, if implemented correctly, can reduce the total number of cases in the short term, and buy India invaluable time to prepare its healthcare and disease-monitoring system Our analysis shows we need to have some measures of suppression in place after the lockdown for increased benefit (as measured by reduction in the number of cases) A longer lockdown between 42-56 days is preferable to substantially "flatten the curve" when compared to 21-28 days of lockdown Our models focus solely on projecting the number of COVID-19 infections and, thus, inform policymakers about one aspect of this multi-faceted decision-making problem We conclude with a discussion on the pivotal role of increased testing, reliable and transparent data, proper uncertainty quantification, accurate interpretation of forecasting models, reproducible data science methods and tools that can enable data-driven policymaking during a pandemic Our software products are available at covind19 org

positive: Social distancing alters the clinical course of COVID-19 in young adults: A comparative cohort study BACKGROUND: Social distancing and stringent hygiene seem effective in reducing the number of transmitted virus particles, and therefore the infectivity, of coronavirus disease 2019 (COVID-19) and could alter the mode of transmission of the disease. However, it is not known if such practices can change the clinical course in infected individuals. METHODS: We prospectively studied an outbreak of COVID-19 in Switzerland among a population of 508 predominantly male soldiers with a median age of 21 years. We followed the number of infections in two spatially separated cohorts with almost identical baseline characteristics with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) before and after implementation of stringent social distancing. RESULTS: Of the 354 soldiers infected prior to the implementation of social distancing, 30% fell ill from COVID-19. While no soldier in a group of 154, in which infections appeared after implementation of social distancing, developed COVID-19 despite the detection of viral RNA in the nose and virus-specific antibodies within this group. CONCLUSIONS: Social distancing not only can slow the spread of SARS-CoV-2 in a cohort of young, healthy adults but can also prevent the outbreak of COVID-19 while still inducing an immune response and colonizing nasal passages. Viral inoculum during infection or mode of transmission may be key factors determining the clinical course of COVID-19.

positive: U.S. county level analysis to determine If social distancing slowed the spread of COVID-19 OBJECTIVE. To analyze the effectiveness of social distancing in the United States (U.S.). METHODS. A novel cell-phone ping data was used to quantify the measures of social distancing by all U.S. counties. RESULTS. Using a difference-in-difference approach results show that social distancing has been effective in slowing the spread of COVID-19. CONCLUSIONS. As policymakers face the very difficult question of the necessity and effectiveness of social distancing across the U.S., counties where the policies have been imposed have effectively increased social distancing and have seen slowing the spread of COVID-19. These results might help policymakers to make the public understand the risks and benefits of the lockdown.

positive: Data-driven modeling reveals a universal dynamic underlying the COVID-19 pandemic under social distancing We show that the COVID-19 pandemic under social distancing exhibits universal dynamics. The cumulative numbers of both infections and deaths quickly cross over from exponential growth at early times to a longer period of power law growth, before eventually slowing. In agreement with a recent statistical forecasting model by the IHME, we show that this dynamics is well described by the erf function. Using this functional form, we perform a data collapse across countries and US states with very different population characteristics and social distancing policies, confirming the universal behavior of the COVID-19 outbreak. We show that the predictive power of statistical models is limited until a few days before curves flatten, forecast deaths and infections assuming current policies continue and compare our predictions to the IHME models. We present simulations showing this universal dynamics is consistent with disease transmission on scale-free networks and random networks with non-Markovian transmission dynamics.

positive: The effectiveness of full and partial travel bans against COVID-19 spread in Australia for travellers from China. Australia implemented a travel ban on China on February 1st 2020. Partial lifting of the ban is being considered, given the decline in incidence of COVID-19 in China. We modelled three scenarios to test the impact of travel bans on epidemic control in Australia. Scenario one was no ban, scenario two was the current ban, scenario three was a partial lifting of the current ban to allow over 100,000 university students to enter Australia, but not tourists. We used disease incidence data from China and air travel passenger movements between China and Australia, derived from incoming passenger arrival cards. We estimated the true incidence of disease in China using data on expected proportion of under-ascertainment of cases. We used an age specific deterministic model divided in 18 age stratified groups to model the epidemic in each scenario. The modelled epidemic with the full ban fitted the observed incidence of cases well. The modelled epidemic of the current ban predicts 57 cases on March 6th in Australia, compared to 66 observed on this date. The modelled impact without a travel ban implemented on February the 1st shows the epidemic would continue for more than a year resulting in more than 2000 cases and about 400 deaths. The impact of a partial lifting of a ban is minimal, and may be safe to consider. Travel restrictions were highly effective for containing the COVID-19 epidemic in Australia and averted a much larger epidemic. The epidemic is still containable if other measures are used in tandem as cases surge in other countries. This research can inform decisions on placing or lifting travel bans as a control measure for the COVID-19 epidemic.

positive: Modelling the potential impact of social distancing on the COVID-19 epidemic in South Africa The novel coronavirus (COVID-19) pandemic continues to be a global health problem whose impact has been significantly felt in South Africa. Social distancing has been touted as the best form of response in managing a rapid increase in the number of infected cases. In this paper, we present a deterministic model to model the impact of social distancing on the transmission dynamics of COVID-19 in South Africa. The model is fitted to the currently available data on the cumulative number of infected cases and a scenario analysis on different levels of social distancing are presented. The results show a continued rise in the number of cases in the lock down period with the current levels of social distancing albeit at a lower rate. The model shows that the number of cases will rise to above 4000 cases by the end of the lockdown. The model also looks at the impact of relaxing the social distancing measures after the initial announcement of the lock down measures. A relaxation of the social distancing by 2% can result in a 23% rise in the number of cumulative cases while on the other hand increasing the levels of social distancing by 2% would reduce the number of cumulative cases by about 18%. These results have implications on the management and policy direction in the early phases of the epidemic.

positive: Effect of preventive actions and health care factors in controlling the outbreaks of COVID-19 pandemic With the insurgence of the COVID-19 pandemic, a large number of people died in the past several months, and the situation is ongoing with increasing panic and vulnerability. Due to the lack of drugs and prophylaxis against COVID-19, most of the countries are now relying on preventive measures focusing on maintaining social distance. However, this social distancing can create global socio-economic threats and psychological disorders. Therefore, these control measures need to have an assessment to evaluate their potential in containing the situation. In this study, we analyzed the outcome of COVID-19 in response to control measures, health care facilities, and prevalent diseases. Based on our findings, the number of COVID-19 deaths found to reduce with increased medical personnel and hospital beds. We found 0.23, 0.16, and 0.21 as the measurement of non-linear relationship between COVID-19 case fatality and number of physicians, nurses and midwives, and hospital beds and these relationships are highly significant with p-value of 0.000007, 0.0046, and 0.0196, respectively. Importantly, we observed a significant correlation between the reduction of COVID-19 cases and the earliness of preventive initiation. As a result, enhancing health care facilities as well as imposing those control measures in a short time could be valuable to prevent the currently raging COVID-19 pandemic. The apathy of taking immediate health care action from the nations has identified as one of the critical reasons to make the circumstances worst. Gambia, Nicaragua, Burundi, Namibia, and Nepal have marked in a state of danger based on the comparative study towards the health care action for the top twenty burdening and least affected countries. Interestingly, no association in most diseases except for few cases has found between the comorbidities and severity of COVID-19, which warranted further investigation at the pathobiological level. We believe that this study could provide a guide for future COVID-19 research.

positive: Further analysis of the impact of distancing upon the COVID-19 pandemic This paper questions various claims from the paper "Social distancing strategies for curbing the COVID-19 epidemic" by Kissler, Tedijanto, Lipsitch, and Grad: most importantly, the claim that China's "intense" distancing measures achieved only a 60% reduction in R0.

positive: Optimal Control applied to a SEIR model of 2019-nCoV with social distancing Does the implementation of social distancing measures have merit in controlling the spread of the novel coronavirus? In this study, we develop a mathematical model to explore the effect of social distancing on new disease infections. Mathematical analyses of our model indicate that successful eradication of the disease is strongly dependent on the chosen preventive measure. Numerical computations of the model solution demonstrate that the ability to flatten the curve becomes easier as social distancing is strictly enforced. Based on our model, we also formulate an optimal control problem and solve it using Pontryagin's Maximum Principle and an efficient numerical iterative method. Our numerical results of an optimal 2019-nCoV treatment protocol that yields a minimum disease burden from this disease indicates that social distancing is vitally important.

positive: The Effectiveness of Social Distancing in Mitigating COVID-19 Spread: a modelling analysis Background The novel coronavirus COVID19 has been classified by the World Health Organisation as a pandemic due to its worldwide spread. The ability of countries to contain and control transmission is critical in the absence of a vaccine. We evaluated a range of social distancing measures to determine which strategies are most effective in reducing the peak daily infection rate, and consequential pressure on the health care system. Methods Using COVID19 transmission data from the outbreak source in Hubei Province, China, collected prior to activation of containment measures, we adapted an established individual based simulation model of the city of Newcastle, Australia, population 272,409. Simulation of virus transmission in this community model without interventions provided a baseline from which to compare alternative social distancing strategies. The infection history of each individual was determined, as was the time infected. From this model generated data, the rate of growth in cases, the magnitude of the epidemic peak, and the outbreak duration were obtained. Findings The application of all four social distancing interventions: school closure, workplace non-attendance, increased case isolation, and community contact reduction is highly effective in flattening the epidemic curve, reducing the maximum daily case numbers, and lengthening outbreak duration. These were also found to be effective even after 10 weeks delay from index case arrivals. The most effective single intervention was found to be increasing case isolation, to 100 percent of children and 90 percent of adults. Interpretation As strong social distancing intervention strategies had the most effect in reducing the epidemic peak, this strategy may be considered when weaker strategies are first tried and found to be less effective. Questions arise as to the duration of strong social distancing measures, given they are highly disruptive to society. Tradeoffs may need to be made between the effectiveness of social distancing strategies and population willingness to adhere to them.

positive: Social distancing, population density, and spread of COVID-19 in England: a longitudinal study. BACKGROUND The UK government introduced social distancing measures between 16-22 March 2020, aiming to slow down transmission of COVID-19. AIM To explore the spreading of COVID-19 in relation to population density after the introduction of social distancing measures. DESIGN & SETTING Longitudinal design with 5-weekly COVID-19 incidence rates per 100 000 people for 149 English Upper Tier Local Authorities (UTLAs), between 16 March and 19 April 2020. METHOD Multivariable multilevel model to analyse weekly incidence rates per 100 000 people; time was level-1 unit and UTLA level-2 unit. Population density was divided into quartiles. The model included an interaction between week and population density. Potential confounders were percentage aged ≥65, percentage non-white British, and percentage in two highest classes of the National Statistics Socioeconomic Classification. Co-variates were male life expectancy at birth, and COVID-19 prevalence rate per 100 000 people on March 15. Confounders and co-variates were standardised around the mean. RESULTS Incidence rates per 100 000 people peaked in the week of March 30-April 5, showing higher adjusted incidence rate per 100 000 people (46.2; 95% confidence interval [CI] = 40.6 to 51.8) in most densely populated ULTAs (quartile 4) than in less densely populated ULTAs (quartile 1: 33.3, 95% CI = 27.4 to 37.2; quartile 2: 35.9, 95% CI = 31.6 to 40.1). Thereafter, incidence rate dropped in the most densely populated ULTAs resulting in rate of 22.4 (95% CI = 16.9 to 28.0) in the week of April 13-19; this was lower than in quartiles 1, 2, and 3, respectively 31.4 (95% CI = 26.5 to 36.3), 34.2 (95% CI = 29.9 to 38.5), and 43.2 (95% CI = 39.0 to 47.4). CONCLUSION After the introduction of social distancing measures, the incidence rates per 100 000 people dropped stronger in most densely populated ULTAs.

positive: Social distance and SARS memory: impact on the public awareness of 2019 novel coronavirus (COVID-19) outbreak This study examines publicly available online search data in China to investigate the spread of public awareness of the 2019 novel coronavirus (COVID-19) outbreak. We found that cities that suffered from SARS and have greater migration ties to the epicentre, Wuhan, had earlier, stronger and more durable public awareness of the outbreak. Our data indicate that forty-eight such cities developed awareness up to 19 days earlier than 255 comparable cities, giving them an opportunity to better prepare. This study suggests that it is important to consider memory of prior catastrophic events as they will influence the public response to emerging threats.

positive: Local Decision Making for Implementing Social Distancing in Response to Outbreaks. OBJECTIVES Social distancing is the practice of restricting contact among persons to prevent the spread of infection. This study sought to (1) identify key features of preparedness and the primary concerns of local public health officials in deciding to implement social distancing measures and (2) determine whether any particular factor could explain the widespread variation among health departments in responses to past outbreaks. METHODS We conducted an online survey of health departments in the United States in 2015 to understand factors influencing health departments' decision making when choosing whether to implement social distancing measures. We paired survey results with data on area population demographic characteristics and analyzed them with a focus on broad trends. RESULTS Of 600 health departments contacted, 150 (25%) responded. Of these 150 health departments, 63 (42%) indicated that they had implemented social distancing in the past 10 years. Only 10 (7%) health departments had a line-item budget for isolation or quarantine. The most common concern about social distancing was public health impact (n = 62, 41%). Concerns about law, politics, finances, vulnerable populations, and sociocultural issues were each identified by 7% to 10% of health departments. We were unable to clearly predict which factors would influence these decisions. CONCLUSIONS Variations in the decision to implement social distancing are likely the result of differences in organizational authority and resources and in the primary concerns about implementing social distancing. Research and current social distancing guidelines for health departments should address these factors.

positive: Healthcare impact of COVID-19 epidemic in India: A stochastic mathematical model Abstract Background In India, the SARS-CoV-2 COVID-19 epidemic has grown to 1251 cases and 32 deaths as on 30 Mar 2020. The healthcare impact of the epidemic in India was studied using a stochastic mathematical model. Methods A compartmental SEIR model was developed, in which the flow of individuals through compartments is modeled using a set of differential equations. Different scenarios were modeled with 1000 runs of Monte Carlo simulation each using MATLAB. Hospitalization, intensive care unit (ICU) requirements, and deaths were modeled on SimVoi software. The impact of nonpharmacological interventions (NPIs) including social distancing and lockdown on checking the epidemic was estimated. Results Uninterrupted epidemic in India would have resulted in more than 364 million cases and 1.56 million deaths with peak by mid-July. As per the model, at current growth rate of 1.15, India is likely to reach approximately 3 million cases by 25 May, implying 125,455 (±18,034) hospitalizations, 26,130 (±3298) ICU admissions, and 13,447 (±1819) deaths. This would overwhelm India's healthcare system. The model shows that with immediate institution of NPIs, the epidemic might still be checked by mid-April 2020. It would then result in 241,974 (±33,735) total infections, 10,214 (±1649) hospitalizations, 2121 (±334) ICU admissions, and 1081 (±169) deaths. Conclusion At the current growth rate of epidemic, India's healthcare resources will be overwhelmed by the end of May. With the immediate institution of NPIs, total cases, hospitalizations, ICU requirements, and deaths can be reduced by almost 90%.

positive: Public policy and economic dynamics of COVID-19 spread: a mathematical modeling study Summary Background: With the COVID-19 pandemic infecting millions of people, largescale quarantine policies have been enacted across the globe. Understanding how to maximize the effectiveness of these policies while mitigating economic damage is essential. We develop a mathematical model with different levels of population health and economic risk to assess the impact of quarantine measures on deaths, hospitalizations, and economic output. Methods: We combine an extended SEIR model that has multiple levels of health risk and economic vulnerability with disease parameters for the COVID19 pandemic to study the effects of quarantine policies. We examine the dynamics of infectious disease transmission and its economic impact for one year. We populate our model with a baseline of 95.6 % of high-risk people and 85.6 % of low-risk people in quarantine. We use our model to simulate leaving the current quarantine restrictions in place indefinitely. We then assess a policy where quarantine restrictions for lower-risk groups are gradually relaxed. Finally, we simulate relaxing quarantine restrictions more quickly. To compare outbreak outcomes under the same quarantine policies using different disease parameters, we also perform a sensitivity analysis on the contagiousness of infected people, the strictness of social isolation measures, and the amount that public policymakers value the economy in setting quarantine restrictions. Findings: We first consider a baseline scenario with constant quarantine level, finding that in a population of 330,000,000 million, there are 32,023 deaths among those under 60 and 174,682 deaths among those over 60, there is a peak of 189,136 hospitalizations, and the economy relative to the beginning of the quarantine state is 1.4 % smaller. In the scenario where higher-risk people are strictly quarantined, and for others the quarantine is slowly relaxed, there are 63,776 deaths among those under 60, 85,880 deaths among those over 60, a peak of 341,321 hospitalizations, and the economy relative to the beginning of the quarantine state is 6% larger. In the scenario where quarantine is more quickly lifted, there are 25,720 deaths among those under 60, 214,718 deaths among those over 60, a peak of 341,321 hospitalizations, and economic output relative to the beginning of the quarantine state is 4.5 % smaller. Interpretation: Strict restrictions on high-risk patients and a gradual lifting of quarantine for low-risk patients results in a limited number of deaths and lesser economic damage. We recommend this kind of strategy, combined with policies lowering the contagiousness of the disease and making quarantine more tolerable and economically viable for individuals.

positive: Sustainable social distancing through facemask use and testing during the Covid-19 pandemic We investigate how individual protective behaviors, different levels of testing, and isolation influence the transmission and control of the COVID-19 pandemic. Based on an SEIR-type model incorporating asymptomatic but infectious individuals (40%), we show that the pandemic may be readily controllable through a combination of testing, treatment if necessary, and self-isolation after testing positive (TTI) of symptomatic individuals together with social protection (e.g., facemask use, handwashing). When the basic reproduction number, R0, is 2.4, 65% effective social protection alone (35% of the unprotected transmission) brings the R below 1. Alternatively, 20% effective social protection brings the reproduction number below 1.0 so long as 75% of the symptomatic population is covered by TTI within 12 hours of symptom onset. Even with 20% effective social protection, TTI of 1 in 4 symptomatic individuals can substantially 'flatten the curve' cutting the peak daily incidence in half.

positive: Estimating the effect of physical distancing on the COVID-19 pandemic using an urban mobility index Governments around the world are implementing population-wide physical distancing measures in an effort to control transmission of COVID-19, but metrics to evaluate their effectiveness are not readily available. We used a publicly available mobility index based on the relative frequency of trips planned in a popular transit application to evaluate the effect of physical distancing on infection growth rates and reproductive number in 34 states and countries. We found that a 10% decrease in relative mobility in the 2nd week of March was associated with a 11.8% relative decrease (exp(β) = 0.882; 95% CI: 0.822, 0.946) in the average daily growth rate in the fourth week of March and a change in the instantaneous reproductive number of -0.054 (95% CI: 0.097, -0.011) in the same period. Our analysis demonstrates that decreases in urban mobility were predictive of declines in epidemic growth at national or sub-national scales. Mobility metrics offer an appealing method to calibrate population-level physical distancing policy and implementation.

positive: Vertical social distancing policy is ineffective to contain the COVID-19 pandemic. Considering numerical simulations, this study shows that the so-called vertical social distancing health policy is ineffective to contain the COVID-19 pandemic. We present the SEIR-Net model, for a network of social group interactions, as a development of the classic mathematical model of SEIR epidemics (Susceptible-Exposed-Infected (symptomatic and asymptomatic)-Removed). In the SEIR-Net model, we can simulate social contacts between groups divided by age groups and analyze different strategies of social distancing. In the vertical distancing policy, only older people are distanced, whereas in the horizontal distancing policy all age groups adhere to social distancing. These two scenarios are compared to a control scenario in which no intervention is made to distance people. The vertical distancing scenario is almost as bad as the control, both in terms of people infected and in the acceleration of cases. On the other hand, horizontal distancing, if applied with the same intensity in all age groups, significantly reduces the total infected people "flattening the disease growth curve". Our analysis considers the city of Belo Horizonte, Minas Gerais State, Brazil, but similar conclusions apply to other cities as well. Code implementation of the model in R-language is provided in the supplementary material.

positive: Differences in power-law growth over time and indicators of COVID-19 pandemic progression worldwide An automated statistical and error analysis of 45 countries or regions with more than 1000 cases of COVID-19 as of March 28, 2020, has been performed. This study reveals differences in the rate of disease spreading rate over time in different countries. This survey observes that most countries undergo a beginning exponential growth phase, which transitions into a power-law phase, as recently suggested by Ziff and Ziff. Tracking indicators of growth, such as the power-law exponent, are a good indication of the relative danger different countries are in and show when social measures are effective towards slowing the spread. The data compiled here are usefully synthesizing a global picture, identifying country to country variation in spreading, and identifying countries most at risk. This analysis may factor into how best to track the effectiveness of social distancing policies and quarantines in real-time as data is updated each day.

positive: Transmission potential and severity of COVID-19 in South Korea Abstract Objectives Since the first case of 2019 novel coronavirus (COVID-19) identified on Jan 20, 2020 in South Korea, the number of cases rapidly increased, resulting in 6,284 cases including 42 deaths as of March 6, 2020. To examine the growth rate of the outbreak, we aimed to present the first study to report the reproduction number of COVID-19 in South Korea. Methods The daily confirmed cases of COVID-19 in South Korea were extracted from publicly available sources. By using the empirical reporting delay distribution and simulating the generalized growth model, we estimated the effective reproduction number based on the discretized probability distribution of the generation interval. Results We identified four major clusters and estimated the reproduction number at 1.5 (95% CI: 1.4-1.6). In addition, the intrinsic growth rate was estimated at 0.6 (95% CI: 0.6, 0.7) and the scaling of growth parameter was estimated at 0.8 (95% CI: 0.7, 0.8), indicating sub-exponential growth dynamics of COVID-19. The crude case fatality rate is higher among males (1.1%) compared to females (0.4%) and increases with older age. Conclusions Our results indicate early sustained transmission of COVID-19 in South Korea and support the implementation of social distancing measures to rapidly control the outbreak.

positive: A Stratified Model to Quantify the Effects of Containment Policies on the Spread of COVID-19 The SARS-Cov-2 virus is spreading fast all over the world and has already imposed a significant social and economic cost in many countries. Different countries have utilised a variety of containment policies with an emphasis on social distancing as a strategy to stop the spread of COVID-19. Quantifying the effects of such policies in different time-scales and comparing the efficacy of various available policies is of utmost importance for policy-makers in different countries. That is even more important when the policy-makers want to plan for long-term strategies and to weigh each option based on its epidemiological effects and socio-economic costs. In the absence of detailed knowledge of the interactions between individuals in a population and the characteristics of the SARS-Cov-2 virus, quantifying the effects of these policies is very difficult. Hence, there is an immediate need for models that can predict the spread of COVID-19 in a population, without the need for such detailed information. In this manuscript, a method is presented that can be used to predict the spread of COVID-19 in any country and under any containment policy imposed separately on different groups in the population. The method tunes the parameters of a known stratified model based on the available data on the spread of COVID-19. The model includes a set of nonlinear ordinary differential equations and is easy to simulate and easy to understand. As it is presented in this manuscript, the population is divided into age-groups. But given the availability of the data, there is no reason to limit the stratification into only age-groups and we can consider any relevant groups. To estimate the parameters of the model such that it reflects the characteristics of the spread of COVID-19 in a population, the method relies on an optimisation scheme. More specifically, the optimisation scheme estimates the contact rates between different age groups in the population. But a very important and useful feature of the model is that the estimated parameters for one population can be translated and used for any other population with a known age-structure, which in this day and age, includes almost any country or city in the world. Also, it is shown that the method is quite insensitive to the underlying assumptions in the optimisation scheme and also to deliberate or non-deliberate errors that might have occurred in collecting the data. The capabilities of the model are demonstrated using a case study under different containment policies, from an uncontained population to mitigation and suppression policies. Also, we can use the model to quantify the effects of strategies which include switching between different containment policies at pre-determined points in time. The model allows us to quantify the effects of each of these policies on the spread of the disease in a population, in particular, the instantaneous and total numbers of infectious individuals in a population which are important parameters for policy-makers. The simulation results, as explained in the following, provide some insight into various policies and some of the results are possibly counter-intuitive for many people. For example, the model predicts that closing down schools and universities without any other containment policy imposed on older age-groups has almost no impact on the number of patients that might need support-care in hospitals. The method provides an easy-to-use tool to use the information collected on the spread of COVID-19 in a country or region and then use that information in another population which might not have been as widely affected by the disease yet.

positive: Evidence of initial success for China exiting COVID-19 social distancing policy after achieving containment Background: The COVID-19 epidemic was declared a Global Pandemic by WHO on 11 March 2020. By 24 March 2020, over 440,000 cases and almost 20,000 deaths had been reported worldwide. In response to the fast-growing epidemic, which began in the Chinese city of Wuhan, Hubei, China imposed strict social distancing in Wuhan on 23 January 2020 followed closely by similar measures in other provinces. These interventions have impacted economic productivity in China, and the ability of the Chinese economy to resume without restarting the epidemic was not clear. Methods: Using daily reported cases from mainland China and Hong Kong SAR, we estimated transmissibility over time and compared it to daily within-city movement, as a proxy for economic activity. Results: Initially, within-city movement and transmission were very strongly correlated in the five mainland provinces most affected by the epidemic and Beijing. However, that correlation decreased rapidly after the initial sharp fall in transmissibility. In general, towards the end of the study period, the correlation was no longer apparent, despite substantial increases in within-city movement. A similar analysis for Hong Kong shows that intermediate levels of local activity were maintained while avoiding a large outbreak. At the very end of the study period, when China began to experience the re-introduction of a small number of cases from Europe and the United States, there is an apparent up-tick in transmission. Conclusions: Although these results do not preclude future substantial increases in incidence, they suggest that after very intense social distancing (which resulted in containment), China successfully exited its lockdown to some degree. Elsewhere, movement data are being used as proxies for economic activity to assess the impact of interventions. The results presented here illustrate how the eventual decorrelation between transmission and movement is likely a key feature of successful COVID-19 exit strategies.

positive: Applicability of time fractional derivative models for simulating the dynamics and mitigation scenarios of COVID-19 Fractional calculus provides a promising tool for modeling fractional dynamics in computational biology, and this study tests the applicability of fractional-derivative equations (FDEs) for modeling the dynamics and mitigation scenarios of the novel coronavirus for the first time. The coronavirus disease 2019 (COVID-19) pandemic radically impacts our lives, while the evolution dynamics of COVID-19 remain obscure. A time-dependent Susceptible, Exposed, Infectious, and Recovered (SEIR) model was proposed and applied to fit and then predict the time series of COVID-19 evolution observed over the last three months (up to 3/22/2020) in China. The model results revealed that 1) the transmission, infection and recovery dynamics follow the integral-order SEIR model with significant spatiotemporal variations in the recovery rate, likely due to the continuous improvement of screening techniques and public hospital systems, as well as full city lockdowns in China, and 2) the evolution of number of deaths follows the time FDE, likely due to the time memory in the death toll. The validated SEIR model was then applied to predict COVID-19 evolution in the United States, Italy, Japan, and South Korea. In addition, a time FDE model based on the random walk particle tracking scheme, analogous to a mixing-limited bimolecular reaction model, was developed to evaluate non-pharmaceutical strategies to mitigate COVID-19 spread. Preliminary tests using the FDE model showed that self-quarantine may not be as efficient as strict social distancing in slowing COVID-19 spread. Therefore, caution is needed when applying FDEs to model the coronavirus outbreak, since specific COVID-19 kinetics may not exhibit nonlocal behavior. Particularly, the spread of COVID-19 may be affected by the rapid improvement of health care systems which may remove the memory impact in COVID-19 dynamics (resulting in a short-tailed recovery curve), while the death toll and mitigation of COVID-19 can be captured by the time FDEs due to the nonlocal, memory impact in fatality and human activities.

positive: Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK BACKGROUND: To mitigate and slow the spread of COVID-19, many countries have adopted unprecedented physical distancing policies, including the UK. We evaluate whether these measures might be sufficient to control the epidemic by estimating their impact on the reproduction number (R(0), the average number of secondary cases generated per case). METHODS: We asked a representative sample of UK adults about their contact patterns on the previous day. The questionnaire was conducted online via email recruitment and documents the age and location of contacts and a measure of their intimacy (whether physical contact was made or not). In addition, we asked about adherence to different physical distancing measures. The first surveys were sent on Tuesday, 24 March, 1 day after a “lockdown” was implemented across the UK. We compared measured contact patterns during the “lockdown” to patterns of social contact made during a non-epidemic period. By comparing these, we estimated the change in reproduction number as a consequence of the physical distancing measures imposed. We used a meta-analysis of published estimates to inform our estimates of the reproduction number before interventions were put in place. RESULTS: We found a 74% reduction in the average daily number of contacts observed per participant (from 10.8 to 2.8). This would be sufficient to reduce R(0) from 2.6 prior to lockdown to 0.62 (95% confidence interval [CI] 0.37–0.89) after the lockdown, based on all types of contact and 0.37 (95% CI = 0.22–0.53) for physical (skin to skin) contacts only. CONCLUSIONS: The physical distancing measures adopted by the UK public have substantially reduced contact levels and will likely lead to a substantial impact and a decline in cases in the coming weeks. However, this projected decline in incidence will not occur immediately as there are significant delays between infection, the onset of symptomatic disease, and hospitalisation, as well as further delays to these events being reported. Tracking behavioural change can give a more rapid assessment of the impact of physical distancing measures than routine epidemiological surveillance.

positive: Releasing the lockdown in the UK Covid-19 epidemic: a stochastic model Abstract Background In a classic epidemic, the infected population has an early exponential phase, before slowing and fading to its peak. Mitigating interventions may change the exponent during the rising phase and a plateau can replace a peak. With interventions comes the risk that relaxation causes a second-wave. In the UK Covid-19 epidemic, infections cannot be counted, but their influence is seen in the curve of the mortality data. This work simulated social distancing and the lockdown in the UK Covid-19 epidemic to explore strategies for relaxation. Methods Cumulative mortality data was transposed 20 days earlier to identify three doubling periods separated by the 17th March - social distancing, and 23rd March - lockdown. A set of stochastic processes simulated viral transmission between interacting individuals using Covid-19 incubation and illness durations. Social distancing and restrictions on interactions were imposed and later relaxed. Principal Findings Daily mortality data, consistent with that seen in the UK Covid-19 epidemic to 24th April 2020 was simulated. This output predicts that under a lockdown maintained till early July 2020, UK deaths will exceed 31,000, but leave a large susceptible population and a requirement for vaccination or quarantine. An earlier staged relaxation carries a risk of a second-wave. The model allows exploration of strategies for lifting the lockdown. Interpretation Social distancing and the lockdown have had an impressive impact on the UK Covid-19 epidemic and saved lives, caution is now needed in planning its relaxation.

positive: The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study Summary Background In December, 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus, emerged in Wuhan, China. Since then, the city of Wuhan has taken unprecedented measures in response to the outbreak, including extended school and workplace closures. We aimed to estimate the effects of physical distancing measures on the progression of the COVID-19 epidemic, hoping to provide some insights for the rest of the world. Methods To examine how changes in population mixing have affected outbreak progression in Wuhan, we used synthetic location-specific contact patterns in Wuhan and adapted these in the presence of school closures, extended workplace closures, and a reduction in mixing in the general community. Using these matrices and the latest estimates of the epidemiological parameters of the Wuhan outbreak, we simulated the ongoing trajectory of an outbreak in Wuhan using an age-structured susceptible-exposed-infected-removed (SEIR) model for several physical distancing measures. We fitted the latest estimates of epidemic parameters from a transmission model to data on local and internationally exported cases from Wuhan in an age-structured epidemic framework and investigated the age distribution of cases. We also simulated lifting of the control measures by allowing people to return to work in a phased-in way and looked at the effects of returning to work at different stages of the underlying outbreak (at the beginning of March or April). Findings Our projections show that physical distancing measures were most effective if the staggered return to work was at the beginning of April; this reduced the median number of infections by more than 92% (IQR 66–97) and 24% (13–90) in mid-2020 and end-2020, respectively. There are benefits to sustaining these measures until April in terms of delaying and reducing the height of the peak, median epidemic size at end-2020, and affording health-care systems more time to expand and respond. However, the modelled effects of physical distancing measures vary by the duration of infectiousness and the role school children have in the epidemic. Interpretation Restrictions on activities in Wuhan, if maintained until April, would probably help to delay the epidemic peak. Our projections suggest that premature and sudden lifting of interventions could lead to an earlier secondary peak, which could be flattened by relaxing the interventions gradually. However, there are limitations to our analysis, including large uncertainties around estimates of R 0 and the duration of infectiousness. Funding Bill & Melinda Gates Foundation, National Institute for Health Research, Wellcome Trust, and Health Data Research UK.

positive: Causal Estimation of Stay-at-Home Orders on SARS-CoV-2 Transmission Accurately estimating the effectiveness of stay-at-home orders (SHOs) on reducing social contact and disease spread is crucial for mitigating pandemics. Leveraging individual-level location data for 10 million smartphones, we observe that by April 30th---when nine in ten Americans were under a SHO---daily movement had fallen 70% from pre-COVID levels. One-quarter of this decline is causally attributable to SHOs, with wide demographic differences in compliance, most notably by political affiliation. Likely Trump voters reduce movement by 9% following a local SHO, compared to a 21% reduction among their Clinton-voting neighbors, who face similar exposure risks and identical government orders. Linking social distancing behavior with an epidemic model, we estimate that reductions in movement have causally reduced SARS-CoV-2 transmission rates by 49%.

positive: Diminishing Marginal Benefit of Social Distancing in Balancing COVID-19 Medical Demand-to-Supply Social distancing has been adopted as a non-pharmaceutical intervention to prevent the COVID-19 pandemic from overwhelming the medical resources across the United States (US). The catastrophic socio-economic impacts of this intervention could outweigh its benefits if the timing and duration of implementation are left uncontrolled and ill-strategized. Here we investigate the dynamics of social distancing on age-stratified US population and benchmark its effectiveness in reducing the burden on hospital and ICU beds. Our findings highlight the diminishing marginal benefit of social distancing, characterized by a linear decrease in medical demands against an exponentially increasing social distancing duration. We determine an optimal intermittent social-to-no-distancing ratio of 5:1 corresponding to ~80% reduction in healthcare demands; beyond this ratio, benefit of social distancing diminishes to a negligible level. COVID-19 Medical Forecast: https://eece.wustl.edu/chakrabarty-group/covid/

positive: Analysis of the impact of lockdown on the evolution Covid-19 epidemics in Spain Objective: The late 2019 Covid-19 disease outbreak has put the health systems of many countries to the limit of their capacity. The most affected European countries are, so far, Italy and Spain. In both countries (and others), the authorities decreed a lockdown, with local specificities. The objective of this work is to evaluate the impact of the measures undertaken in Spain to deal with the pandemic. Method: We estimated the number of cases and the impact of lockdown on the reproducibility number based on the hospitalization reports. Results: The estimated number of cases shows a sharp increase until the lockdown, followed by a slowing down and then a decrease after full quarantine was implemented. Differences in the basic reproduction ratio are also very significant, dropping from de 5.89 (95% CI: 5.46-7.09) before the lockdown to 0.48 (95% CI: 0.15-1.17) afterwards. Conclusions: Handling a pandemic like Covid-19 is very complex and requires quick decision making. The large differences found in the speed of propagation of the disease show us that being able to implement interventions at the earliest stage is crucial to minimise the impact of a potential infectious threat. Our work also stresses the importance of reliable up to date epidemiological data in order to accurately assess the impact of Public Health policies on viral outbreak.

positive: Two resource distribution strategies for dynamic mitigation of influenza pandemics As recently pointed out by the Institute of Medicine, the existing pandemic containment and mitigation models lack the dynamic decision support capabilities. We present two simulation-based optimization models for developing dynamic predictive resource distribution strategies for cross-regional pandemic outbreaks. In both models, the underlying simulation mimics the disease and population dynamics of the affected regions. The quantity-based optimization model generates a progressive allocation of limited quantities of mitigation resources, including vaccines, antiviral, administration capacities, and social distancing enforcement resources. The budget-based optimization model strives instead allocating a total resource budget. Both models seek to minimize the impact of ongoing outbreaks and the expected impact of potential outbreaks. The models incorporate measures of morbidity, mortality, and social distancing, translated into the societal and economic costs of lost productivity and medical expenses. The models were calibrated using historic pandemic data and implemented on a sample outbreak in Florida, with over four million inhabitants. The quantity-based model was found to be inferior to the budget-based model, which was advantageous in its ability to balance the varying relative cost and effectiveness of individual resources. The models are intended to assist public health policy makers in developing effective distribution policies for mitigation of influenza pandemics.

positive: Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study. BACKGROUND The isolation of symptomatic cases and tracing of contacts has been used as an early COVID-19 containment measure in many countries, with additional physical distancing measures also introduced as outbreaks have grown. To maintain control of infection while also reducing disruption to populations, there is a need to understand what combination of measures-including novel digital tracing approaches and less intensive physical distancing-might be required to reduce transmission. We aimed to estimate the reduction in transmission under different control measures across settings and how many contacts would be quarantined per day in different strategies for a given level of symptomatic case incidence. METHODS For this mathematical modelling study, we used a model of individual-level transmission stratified by setting (household, work, school, or other) based on BBC Pandemic data from 40 162 UK participants. We simulated the effect of a range of different testing, isolation, tracing, and physical distancing scenarios. Under optimistic but plausible assumptions, we estimated reduction in the effective reproduction number and the number of contacts that would be newly quarantined each day under different strategies. RESULTS We estimated that combined isolation and tracing strategies would reduce transmission more than mass testing or self-isolation alone: mean transmission reduction of 2% for mass random testing of 5% of the population each week, 29% for self-isolation alone of symptomatic cases within the household, 35% for self-isolation alone outside the household, 37% for self-isolation plus household quarantine, 64% for self-isolation and household quarantine with the addition of manual contact tracing of all contacts, 57% with the addition of manual tracing of acquaintances only, and 47% with the addition of app-based tracing only. If limits were placed on gatherings outside of home, school, or work, then manual contact tracing of acquaintances alone could have an effect on transmission reduction similar to that of detailed contact tracing. In a scenario where 1000 new symptomatic cases that met the definition to trigger contact tracing occurred per day, we estimated that, in most contact tracing strategies, 15 000-41 000 contacts would be newly quarantined each day. INTERPRETATION Consistent with previous modelling studies and country-specific COVID-19 responses to date, our analysis estimated that a high proportion of cases would need to self-isolate and a high proportion of their contacts to be successfully traced to ensure an effective reproduction number lower than 1 in the absence of other measures. If combined with moderate physical distancing measures, self-isolation and contact tracing would be more likely to achieve control of severe acute respiratory syndrome coronavirus 2 transmission. FUNDING Wellcome Trust, UK Engineering and Physical Sciences Research Council, European Commission, Royal Society, Medical Research Council.

positive: Social Distancing Interventions in the United States: An Exploratory Investigation of Determinants and Impacts Background To combat the Covid-19 pandemic in the United States, many states and Washington DC enacted Stay-at-Home order and nonpharmaceutical mitigation interventions. This study examined the determinants of the timing to implement an intervention. Through an impact analysis, the study explored the effects of the interventions and the potential risks of removing them under the context of reopening the economy. Method A content analysis identified nine types of mitigation interventions and the timing at which states enacted these strategies. A proportional hazard model, a multiple-event survival model, and a random-effect spatial error panel model in conjunction with a robust method analyzing zero-inflated and skewed outcomes were employed in the data analysis. Findings To our knowledge, we provided in this article the first explicit analysis of the timing, determinants, and impacts of mitigation interventions for all states and Washington DC in the United States during the first five weeks of the pandemic. Unlike other studies that evaluate the Stay-at-Home order by using simulated data, the current study employed the real data of various case counts of Covid-19. The study obtained two meritorious findings: (1) states with a higher prevalence of Covid-19 cases per 10,000 population reacted more slowly to the outbreak, suggesting that some states may have missed the optimal timing to prevent the wide spread of the Covid-19 disease; and (2) of nine mitigation measures, three (non-essential business closure, large-gathering bans, and restaurant/bar limitations) showed positive impacts on reducing cumulative cases, new cases, and death rates across states. Interpretation The opposite direction of the prevalence rate on the timing of issuing the mitigation interventions partially explains why the Covid-19 caseload in the U.S. remains high. A swift implementation of social distancing is crucial-the key is not whether such measures should be taken but when. Because there is no preventive vaccine and because there are few potentially effective treatments, recent reductions in new cases and deaths must be due, in large part, to the social interventions delivered by states. The study suggests that the policy of reopening economy needs to be implemented carefully.

positive: Social Distancing Causally Impacts the Spread of SARS-CoV-2: A U.S. Nationwide Event Study Background: To date, no study has examined the effectiveness of social distancing, while controlling for social mobility and social distancing restrictions in the United States. We utilize the quasi-experimental setting created by the nationwide protests precipitated by George Floyd's tragic death on May 25, 2020, to assess the causal impact of social distancing on the spread of SARS-CoV-2. Methods: Our sample period spans from January 22, 2020, to June 20, 2020, and consists of 474,422 county-days representing 3,142 counties from all 50 states and the District of Columbia. To assess the change in COVID-19 case counts following the protests, we employ a differences in differences estimation strategy in a multivariate setting, in which we control for social distancing restrictions and social mobility across counties. We also control for covariates that may influence COVID-19 transmission, and implement placebo tests using a Monte Carlo simulation. Findings: We document a country wide increase of over 3.06 cases per day, per 100,000 population, following the onset of the protests (95%CI: 2.47-3.65), and a further increase of 1.73 cases per day, per 100,000 population, in the counties in which the protests took place (95%CI: 0.59- 2.87). Relative to the week preceding the onset of the protests, this represents a 61.2% country wide increase in COVID-19 cases, and a further 34.6% increase in the protest counties. Interpretation: Our study documents a significant increase in COVID-19 case counts in counties that experienced a protest, and we conclude that social distancing practices causally impact the spread of SARS-CoV-2. The observed effect cannot be explained by changes in social distancing restrictions and social mobility, and placebo tests rule out the possibility that this finding is attributable to chance.

positive: The Changing Face of Orthopedic Education: Searching for the New Reality After COVID-19 Abstract The COVID-19 pandemic has had immediate impact on the practice of medicine and orthopaedic education. As the practice of social distancing has been put into place to help slow the spread of disease as well as to conserve medical supplies and equipment, elective surgery has come to a grinding halt. This dramatic change has forced our leaders to critically evaluate the delivery of education and skills training for our residents, fellows as well as all orthopaedic surgeons. We must continue to develop technologies such as virtual meeting platforms, distance learning, simulation-based training, virtual reality andaugmented reality to augment the new world of orthopaedic education.

positive: Is the impact of social distancing on coronavirus growth rates effective across different settings? A non-parametric and local regression approach to test and compare the growth rate Epidemiologists use mathematical models to predict epidemic trends, and these results are inherently uncertain when parameters are unknown or changing. In other contexts, such as climate, modellers use multi-model ensembles to inform their decision-making: when forecasts align, modellers can be more certain. This paper looks at a sub-set of alternative epidemiological models that focus on the growth rate, and it cautions against relying on the method proposed in (Pike & Saini, 2020): relying on the data for China to calculate future trajectories is likely to be subject to overfitting, a common problem in financial and economic modelling. This paper finds, surprisingly, that the data for China are double-exponential, not exponential; and that different countries are showing a range of different trajectories. The paper proposes using non-parametric and local regression methods to support epidemiologists and policymakers in assessing the relative effectiveness of social distancing policies. All works contained herein are provided free to use worldwide by the author under CC BY 2.0.

positive: COVID-19 outbreak response: a first assessment of mobility changes in Italy following national lockdown Italy is currently experiencing the largest COVID-19 outbreak in Europe so far, with more than 100,000 confirmed cases. Following the identification of the first infections, on February 21, 2020, national authorities have put in place an increasing number of restrictions aimed at containing the outbreak and delaying the epidemic peak. Since March 12, the whole country is under lockdown. Here we provide the first quantitative assessment of the impact of such measures on the mobility and the spatial proximity of Italians, through the analysis of a large-scale dataset on de-identified, geo-located smartphone users. With respect to pre-outbreak averages, we estimate a reduction of 50% of the total trips between Italian provinces, following the lockdown. In the same week, the average users' radius of gyration has declined by about 50% and the average degree of the users' proximity network has dropped by 47% at national level.

positive: Echoes of 2009 H1N1 Influenza Pandemic in the COVID Pandemic Abstract The severe acute respiratory syndrome–related coronavirus-2 (SARS-CoV2) pandemic that has engulfed the globe has had incredible effects on health care systems and economic activity. Social distancing and school closures have played a central role in public health efforts to counter the coronavirus disease 2019 (COVID)-19 pandemic. The most recent global pandemic prior to COVID-19 was the 2009 pandemic, hemagglutinin type 1 and neuraminidase type 1 (H1N1) influenza. The course of events in 2009 offer some rich lessons that could be applied to the current COVID-19 pandemic. This commentary highlights some of the most relevant points and a discussion of possible outcomes of the COVID-19 pandemic. © 2020 Elsevier Inc.

positive: The effect of uncontrolled travelers and social distancing on the spread of novel coronavirus disease (COVID-19) in Colombia

positive: Investigating the Trajectory of the COVID-19 Outbreak in Milwaukee County and Projected Effects of Relaxed Distancing. INTRODUCTION The coronavirus pandemic has placed enormous stresses on health care systems across the United States and internationally. Predictive modeling has been an important tool for projecting utilization rates and surge planning. As the initial outbreak begins to slow, questions are being raised regarding long-term coronavirus mitigation plans. This paper examines the current status of the coronavirus outbreak in Milwaukee County, Wisconsin, and simulates several scenarios where physical distancing measures are removed. METHODS The outbreak's doubling time, reproductive numbers at several points, and incidence curve were calculated to assess outbreak progression. Compartmental models were used to estimate the number of hospitalizations and critically ill patients in Milwaukee County if distancing policies were removed. RESULTS The compartmental models predict a substantial spike in cases and overwhelming medical resource utilization with an abrupt end to social distancing. Partial reduction in social distancing policies would likely result in a smaller spike, with less severe strain on available medical resources. CONCLUSIONS Milwaukee County remains very susceptible to a resurgence of COVID-19 cases. Removing physical distancing policies poses significant risks with regard to resource management.

positive: Social distancing and movement constraint as the most likely factors for COVID-19 outbreak control in Brazil As thousands of new cases of COVID-19 have been confirmed, there is an increasing demand to understand the factors underlying the spread of this disease. Using country-level data, we modeled the early growth in the number of cases for over 480 cities in all Brazilian states. As the main findings, we found that the percentage of people respecting social distancing protocols was the main explanatory factor for the observed growth rate of COVID-19. Those cities that presented the highest spread of the new coronavirus were also those that had lower averages of social distancing. We also underline that total population of cities and connectivity, represented by the city-level importance to the air transportation of people across the country, plays important roles in the dissemination of SARS-CoV-2. Climate and socioeconomic predictors had little contribution to the big-picture scenario. Our results show that different States had high variability in their growth rates, mostly due to quite different public health strategies to retain the outbreak of COVID-19. In spite of all limitations of such a large-scale approach, our results underline that climatic conditions are likely weak limiting factors for the spread of the new coronavirus, and the circulation of people in the city- and country-level are the most responsible factors for the early outbreak of COVID-19 in Brazil. Moreover, we reinforce that social distancing protocols are fundamental to avoid critical scenarios and the collapse of healthcare systems. We also predict that economic-induced decisions for relaxing social distancing might have catastrophic consequences, especially in large cities.

positive: Lockdown exit strategies and risk of a second epidemic peak: a stochastic agent-based model of SARS-CoV-2 epidemic in France Most European countries have responded to the COVID-19 threat by nationwide implementation of barrier measures and lockdown. However, assuming that population immunity will build up through the epidemic, it is likely to rebound once these measures are relaxed, possibly leading to a second or multiple repeated lockdowns. In this report, we present results of epidemiological modelling that has helped inform policy making in France. We used a stochastic agent-based microsimulation model of the COVID-19 epidemic in France, and examined the potential impact of post-quarantine measures, including social distancing, mask-wearing, and shielding of the population the most vulnerable to severe COVID-19 infection, on the disease's cumulative incidence and mortality, and on ICU-bed occupancy. The model calibrated well and variation of model parameter values had little impact on outcome estimates. While quarantine is effective in containing the viral spread, it would be unlikely to prevent a rebound of the epidemic once lifted, regardless of its duration. Both social distancing and mask-wearing, although effective in slowing the epidemic and in reducing mortality, would also be ineffective in ultimately preventing the overwhelming of ICUs and a second lockdown. However, these measures coupled with shielding of vulnerable people would be associated with better outcomes, including lower cumulative incidence, mortality, and maintaining an adequate number of ICU beds to prevent a second lockdown. Benefits would nonetheless be markedly reduced if these measures were not applied by most people or not maintained for a sufficiently long period, as herd immunity progressively establishes in the less vulnerable population.

positive: How we should respond to the Coronavirus SARS-CoV-2 outbreak: A German perspective. BACKGROUND In the early phase of the COVID-19 pandemic Germany missed to set up efficient containment measures. Consequently, the number of cases increased exponentially until a lockdown was implemented to suppress the spread of SARS-CoV-2. Fortunately, Germany has a high capability for coronavirus lab testing and more than 30,000 ICU beds. These capabilities and the lockdown turned out to be an advantage to combat the pandemic and to prevent a health-system overload. AIM The aim was to predict the plateau day of SARS-CoV-2 infections or deaths. RESULTS The effect on the viral spread of the German measures taken and the impact on the peak of new infection cases is shown. By normalizing daily case numbers, the plateau day of the current outbreak in Germany could be calculated to be reached at April 12, 2020 (day 103 of 2020). CONCLUSION Normalized case number curves are helpful to predict the time point at which no further new infections will occur. Upon reaching the plateau day during a lockdown phase, a residual time-period of about 2-3 weeks can be utilized to prepare a safe unlocking period. As can be learned from Asian countries such as South Korea and Taiwan there must be strict rules to keep the risk of infection low. Those include social distancing, face mask wearing in combination with digital contact tracing and serosurveillance studies. Following those rules, a safe dance around the infection curve allows to keep the population at a reduced infection rate.

positive: Robust and optimal predictive control of the COVID-19 outbreak We investigate adaptive strategies to robustly and optimally control the COVID-19 pandemic via social distancing measures based on the example of Germany. Our goal is to minimize the number of fatalities over the course of two years without inducing excessive social costs. We consider a tailored model of the German COVID-19 outbreak with different parameter sets to design and validate our approach. Our analysis reveals that an open-loop optimal control policy can significantly decrease the number of fatalities when compared to simpler policies under the assumption of exact model knowledge. In a more realistic scenario with uncertain data and model mismatch, a feedback strategy that updates the policy weekly using model predictive control (MPC) leads to a reliable performance, even when applied to a validation model with deviant parameters. On top of that, we propose a robust MPC-based feedback policy using interval arithmetic that adapts the social distancing measures cautiously and safely, thus leading to a minimum number of fatalities even if measurements are inaccurate and the infection rates cannot be precisely specified by social distancing. Our theoretical findings support various recent studies by showing that 1) adaptive feedback strategies are required to reliably contain the COVID-19 outbreak, 2) well-designed policies can significantly reduce the number of fatalities compared to simpler ones while keeping the amount of social distancing measures on the same level, and 3) imposing stronger social distancing measures early on is more effective and cheaper in the long run than opening up too soon and restoring stricter measures at a later time.

positive: A hybrid multi-scale model of COVID-19 transmission dynamics to assess the potential of non-pharmaceutical interventions Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus that emerged in Wuhan, China in December 2019. It has caused a global outbreak which represents a major threat to global health. Public health resorted to non-pharmaceutical interventions such as social distancing and lockdown to slow down the spread of the pandemic. However, the effect of each of these measures remains hard to quantify. We design a multi-scale model that simulates the transmission dynamics of COVID-19. We describe the motion of individual agents using a social force model. Each agent can be either susceptible, infected, quarantined, immunized or deceased. The model considers both mechanisms of direct and indirect transmission. We parameterize the model to reproduce the early dynamics of disease spread in Italy. We show that panic situations increase the risk of infection transmission in crowds despite social distancing measures. Next, we suggest that pre-symptomatic transmission could be a significant driver of the infection spread. Then, we show that the restricted movement of the individuals flattens the epidemic curve. Finally, model predictions suggest that measures stricter than social distancing and lockdown were used to control the epidemic in Wuhan, China.

positive: Age-stratified model of the COVID-19 epidemic to analyze the impact of relaxing lockdown measures: nowcasting and forecasting for Switzerland Compartmental models enable the analysis and prediction of an epidemic including the number of infected, hospitalized and deceased individuals in a population. They allow for computational case studies on non-pharmaceutical interventions thereby providing an important basis for policy makers. While research is ongoing on the transmission dynamics of the SARS-CoV-2 coronavirus, it is important to come up with epidemic models that can describe the main stages of the progression of the associated COVID-19 respiratory disease. We propose an age-stratified discrete compartment model as an alternative to differential equation based S-I-R type of models. The model captures the highly age-dependent progression of COVID-19 and is able to describe the day-by-day advancement of an infected individual in a modern health care system. The fully-identified model for Switzerland not only predicts the overall histories of the number of infected, hospitalized and deceased, but also the corresponding age-distributions. The model-based analysis of the outbreak reveals an average infection fatality ratio of 0.4% with a pronounced maximum of 9.5% for those aged [≥]80 years. The predictions for different scenarios of relaxing the soft lockdown indicate a low risk of overloading the hospitals through a second wave of infections. However, there is a hidden risk of a significant increase in the total fatalities (by up to 200%) in case schools reopen with insufficient containment measures in place.

positive: Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study BACKGROUND: Within 4 months of COVID-19 first being reported in the USA, it spread to every state and to more than 90% of all counties. During this period, the US COVID-19 response was highly decentralised, with stay-at-home directives issued by state and local officials, subject to varying levels of enforcement. The absence of a centralised policy and timeline combined with the complex dynamics of human mobility and the variable intensity of local outbreaks makes assessing the effect of large-scale social distancing on COVID-19 transmission in the USA a challenge. METHODS: We used daily mobility data derived from aggregated and anonymised cell (mobile) phone data, provided by Teralytics (Zürich, Switzerland) from Jan 1 to April 20, 2020, to capture real-time trends in movement patterns for each US county, and used these data to generate a social distancing metric. We used epidemiological data to compute the COVID-19 growth rate ratio for a given county on a given day. Using these metrics, we evaluated how social distancing, measured by the relative change in mobility, affected the rate of new infections in the 25 counties in the USA with the highest number of confirmed cases on April 16, 2020, by fitting a statistical model for each county. FINDINGS: Our analysis revealed that mobility patterns are strongly correlated with decreased COVID-19 case growth rates for the most affected counties in the USA, with Pearson correlation coefficients above 0·7 for 20 of the 25 counties evaluated. Additionally, the effect of changes in mobility patterns, which dropped by 35–63% relative to the normal conditions, on COVID-19 transmission are not likely to be perceptible for 9–12 days, and potentially up to 3 weeks, which is consistent with the incubation time of severe acute respiratory syndrome coronavirus 2 plus additional time for reporting. We also show evidence that behavioural changes were already underway in many US counties days to weeks before state-level or local-level stay-at-home policies were implemented, implying that individuals anticipated public health directives where social distancing was adopted, despite a mixed political message. INTERPRETATION: This study strongly supports a role of social distancing as an effective way to mitigate COVID-19 transmission in the USA. Until a COVID-19 vaccine is widely available, social distancing will remain one of the primary measures to combat disease spread, and these findings should serve to support more timely policy making around social distancing in the USA in the future. FUNDING: None.

positive: Maximizing the Calm Before the Storm: Tiered Surgical Response Plan for Novel Coronavirus (COVID-19) Abstract The novel coronavirus (COVID-19) was first diagnosed in Wuhan, China in December 2019 and has now spread throughout the world, being verified by the World Health Organization as a Pandemic on March 11th. This had led to the calling of a national emergency on March 13th in the United States. Many hospitals, healthcare networks, and specifically Departments of Surgery are asking the same questions of how to cope and plan for surge capacity, personnel attrition, novel infrastructure utilization, and resource exhaustion. Herein, we present a tiered plan for surgical department planning based on incident command levels. This includes Acute Care Surgeon deployment (given their critical care training and vertically integrated position in the hospital), recommended infrastructure and transfer utilization, triage principles, and faculty, resident and advanced care practitioner deployment.

positive: Forecasting the scale of the COVID-19 epidemic in Kenya Background The first COVID-19 case in Kenya was confirmed on March 13th, 2020. Here, we provide forecasts for the potential incidence rate, and magnitude, of a COVID-19 epidemic in Kenya based on the observed growth rate and age distribution of confirmed COVID-19 cases observed in China, whilst accounting for the demographic and geographic dissimilarities between China and Kenya. Methods We developed a modelling framework to simulate SARS-CoV-2 transmission in Kenya, KenyaCoV. KenyaCoV was used to simulate SARS-CoV-2 transmission both within, and between, different Kenyan regions and age groups. KenyaCoV was parameterized using a combination of human mobility data between the defined regions, the recent 2019 Kenyan census, and estimates of age group social interaction rates specific to Kenya. Key epidemiological characteristics such as the basic reproductive number and the age-specific rate of developing COVID-19 symptoms after infection with SARS-CoV-2, were adapted for the Kenyan setting from a combination of published estimates and analysis of the age distribution of cases observed in the Chinese outbreak. Results We find that if person-to-person transmission becomes established within Kenya, identifying the role of subclinical, and therefore largely undetected, infected individuals is critical to predicting and containing a very significant epidemic. Depending on the transmission scenario our reproductive number estimates for Kenya range from 1.78 (95% CI 1.44 - 2.14) to 3.46 (95% CI 2.81-4.17). In scenarios where asymptomatic infected individuals are transmitting significantly, we expect a rapidly growing epidemic which cannot be contained only by case isolation. In these scenarios, there is potential for a very high percentage of the population becoming infected (median estimates: >80% over six months), and a significant epidemic of symptomatic COVID-19 cases. Exceptional social distancing measures can slow transmission, flattening the epidemic curve, but the risk of epidemic rebound after lifting restrictions is predicted to be high.

positive: A Modelling Analysis of Strategies for Relaxing COVID-19 Social Distancing Abstract Background: The ability of countries to contain and control COVID-19 virus transmission via social distancing is critical in the absence of a vaccine. Early activation of robust measures has been shown to control the daily infection rate, and consequential pressure on the health care system. As countries begin to control COVID-19 spread an understanding of how to ease social distancing measures to prevent a rebound in cases and deaths is required. Methods: Using COVID-19 transmission data from the outbreak source in Hubei Province, China prior to activation of containment measures, we adapted an established individual-based simulation model of the city of Newcastle, Australia. Simulation of virus transmission in this model, with and without, social distancing measures activated permitted us to quantify social distancing effectiveness. Optimal strategies for relaxing social distancing were determined under two settings: with high numbers of daily cases, as in New York; and where early social distancing activation resulted in limited ongoing transmission, as in Perth, Australia. Findings: In countries where strong social distancing measures were activated after the COVID-19 virus had spread widely, our study found these measures are required to be maintained for significant periods before being eased, to return to a situation where daily case numbers become low. In countries where early responses to the COVID-19 pandemic have been highly successful, as in Australia, we show that a staged relaxation of social distancing prevents a rebound in cases. Interpretation: Modelling studies and direct observation have shown that robust and timely social distancing have the most effect in containing the spread of the COVID-19 virus. Questions arise as to the duration of strong social distancing measures, given they are highly disruptive to society and economic activity. This study demonstrates the necessity of holding robust social distancing in place until COVID-19 virus transmission has significantly decreased, and how they may then be safely eased.

positive: The nexus of travel restriction, air pollution and COVID-19 infection: Investigation from a megacity of the southern China To control and prevent the spread of COVID-19, generalized social distancing measures, such as traffic control and travel restriction acted in China. Previous studies indicated that the traffic conditions had significant influence on the air quality, and which was related to the respiratory diseases. This study aimed to reveal the nexus of travel restriction, air pollution and COVID-19. Shenzhen, one of the top 4 megacities in China was considered as the study area, statistical analysis methods, including linear/nonlinear regression and bivariate correlation was conducted to evaluate the relationship of the traffic and passenger population, travel intensity, NO2, PM10, PM2.5 and the number of COVID-19 confirmed cases. The results suggested that traffic control and travel restriction had a significant correlation with the number of COVID-19 confirmed cases, which shown negative correlation with the traffic intensity of the city, NO2, PM10 and PM2.5 show significant positive correlation with the traffic intensity, traffic control and travel restriction would slow down and prevent the spread of the viruses at the outbreak period. Different study scale might results in different results, thus the research focused on the nexus of traffic control and travel restriction, air pollution and COVID-19 should been enhanced in future, and differentiated epidemic control and prevention measures should be considered according to the different situation of cities as well as countries.

positive: Forecasting the effect of social distancing on COVID-19 autumn-winter outbreak in the metropolitan area of Buenos Aires. Forecasting the extent of the domestic health risk of epidemics by mathematical modeling is a useful tool for evaluating the feasibility of policies for controlling outbreaks. The objective of this study was to develop a time-dependent dynamic simulation model to forecast the COVID-19 autumn-winter outbreak in the metropolitan area of Buenos Aires, and to assess the effect of social distancing on epidemic spread. The model used was the "Susceptible-Exposed-Infectious-Recovered" framework which incorporated appropriate compartments relevant to interventions such as quarantine, isolation and treatment. In a low-intervention scenario including only 2-week isolation for international travelers and their contacts, the model estimated a maximum peak of nearly 90 000 symptomatic cases for early May. For an intervention scenario with mandatory quarantine during a 5-month period, the curve of cases flattened and receded as the proportion of quarantined individuals increased. The maximum peak was expected to appear between May 8 and Jul 8 depending on the quarantine strategy, and the average number of infectious symptomatic cases were 46 840, 30 494, 23 164, 16 179, and 13 196 when 10%, 20%, 30%, 40%, and 50% of the population remained in a 5-month-term continuous quarantine, respectively. Only mandatory quarantine was able to delay the maximum peak of infection and significantly reduce the total number of infected individuals and deaths at a 150-day term. The interruption of the quarantine before 120 days of its beginning could generate an even more serious outbreak 30 days later, and surpass the scarce medical resources available for the intensive care of critically-ill patients.

positive: Modeling the impact of non-pharmaceutical interventions on the dynamics of novel coronavirus with optimal control analysis with a case study Coronavirus disease (COVID-19) is the biggest public health challenge the world is facing in recent days. Since there is no effective vaccine and treatment for this virus, therefore, the only way to mitigate this infection is the implementation of non-pharmaceutical interventions such as social-distancing, community lockdown, quarantine, hospitalization or self-isolation and contact-tracing. In this paper, we develop a mathematical model to explore the transmission dynamics and possible control of the COVID-19 pandemic in Pakistan, one of the Asian countries with a high burden of disease with more than 100,000 confirmed infected cases so far. Initially, a mathematical model without optimal control is formulated and some of the basic necessary analysis of the model, including stability results of the disease-free equilibrium is presented. It is found that the model is stable around the disease-free equilibrium both locally and globally when the basic reproduction number is less than unity. Despite the basic analysis of the model, we further consider the confirmed infected COVID-19 cases documented in Pakistan from March 1 till May 28, 2020 and estimate the model parameters using the least square fitting tools from statistics and probability theory. The results show that the model output is in good agreement with the reported COVID-19 infected cases. The approximate value of the basic reproductive number based on the estimated parameters is [Formula: see text]. The effect of low (or mild), moderate, and comparatively strict control interventions like social-distancing, quarantine rate, (or contact-tracing of suspected people) and hospitalization (or self-isolation) of testing positive COVID-19 cases are shown graphically. It is observed that the most effective strategy to minimize the disease burden is the implementation of maintaining a strict social-distancing and contact-tracing to quarantine the exposed people. Furthermore, we carried out the global sensitivity analysis of the most crucial parameter known as the basic reproduction number using the Latin Hypercube Sampling (LHS) and the partial rank correlation coefficient (PRCC) techniques. The proposed model is then reformulated by adding the time-dependent control variables u(1)(t) for quarantine and u(2)(t) for the hospitalization interventions and present the necessary optimality conditions using the optimal control theory and Pontryagin’s maximum principle. Finally, the impact of constant and optimal control interventions on infected individuals is compared graphically.

positive: Analyzing the World-Wide Impact of Public Health Interventions on the Transmission Dynamics of COVID-19 We analyze changes in the reproduction number, R, of COVID-19 in response to public health interventions. Our results indicate that public health measures undertaken in China reduced R from 1.5 in January to 0.4 in mid-March 2020. They also suggest, however, the limitations of isolation, quarantine, and large-scale attempts to limit travel. While the world-wide reproduction number briefly dropped below 1 as China implemented extensive public health measures, the introduction of the virus to other nations swiftly led to an increasing world-wide average value of R. In Italy, the nation hardest-hit following China, social distancing measures brought the local value of R down from 3.71 to 2.51. Nonetheless, the value of R in Italy persisted at levels well above 1, allowing for ongoing transmission. By mid-March 2020, as COVID-19 spread in areas without extensive public health interventions in place, the world-wide value of R increased to a level similar to that of late January.

positive: Investigating the Impact of Asymptomatic Carriers on COVID-19 Transmission Coronavirus disease 2019 (COVID-19) is a novel human respiratory disease caused by the SARS-CoV-2 virus. Asymptomatic carriers of the virus display no clinical symptoms but are known to be contagious. Recent evidence reveals that this sub-population, as well as persons with mild, represent a major contributor in the propagation of COVID-19. The asymptomatic sub-population frequently escapes detection by public health surveillance systems. Because of this, the currently accepted estimates of the basic reproduction number (Ro) of the virus are inaccurate. It is unlikely that a pathogen can blanket the planet in three months with an Ro in the vicinity of 3, as reported in the literature. In this manuscript, we present a mathematical model taking into account asymptomatic carriers. Our results indicate that an initial value of the effective reproduction number could range from 5.5 to 25.4, with a point estimate of 15.4, assuming mean parameters. The first three weeks of the model exhibit exponential growth, which is in agreement with average case data collected from thirteen countries with universal health care and robust communicable disease surveillance systems; the average rate of growth in the number of reported cases is 23.3% per day during this period.

positive: SHELTER IN PLACE ORDER CONTAINED COVID-19 GROWTH RATE IN GREECE Background: The Greek authorities implemented the strong social distancing measures within the first few weeks after the first confirmed case of the virus to curtail the COVID-19 growth rate. Objectives: To estimate the effect of the two-stage strong social distancing measures, the closure of all non-essential shopping centers and businesses on March 16 and the shelter in place orders (SIPOs) on March 23 on the COVID-19 growth rate in Greece Methods: We obtained data on COVID-19 cases in Greece from February 26th through May 4th from publicly available sources. An interrupted time-series regression analysis was used to estimate the effect of the measures on the exponential growth of confirmed COVID-19 cases, controlling for the number of daily testing, and weekly fixed-effects. Results: The growth rate of the COVID-19 cases in the pre-policies implementation period was positive as expected (p=0.003). Based on the estimates of the interrupted time-series, our results indicate that the SIPO on March 23 significantly slowed the growth rate of COVID-19 in Greece (p=0.04). However, we did not find evidence on the effectiveness of standalone and partial measures such as the non-essential business closures implemented on March 16 on the COVID-19 spread reduction. Discussion: The combined social distancing measures implemented by the Greek authorities within the first few weeks after the first confirmed case of the virus reduced the COVID-19 growth rate. These findings provide evidence and highlight the effectiveness of these measures to flatten the curve and to slow the spread of the virus.

positive: Modeling of COVID-19 Pandemic and Scenarios for Containment The impact of COVID-19 pandemic on the global health and world's economy have been profound and unseen since the Spanish flu of 1918-19. As of now, many countries have been severely affected, partly because of slow responses to the crisis, ill-preparedness of their health system, and the fragile health infrastructure and the shortage of protective equipment. This note evaluates various scenarios, based on an estimation of number of identified and unidentified infected cases, and examines the effectiveness of different policy responses to contain this pandemic. Our result, based on an estimation of the model for Iran, show that in many instances the number of unidentified cases, including asymptomatic individuals, could be much bigger than the reported numbers. The results confirm that in such circumstances, social distancing alone cannot be an effective policy unless a large portion of the population confine themselves for an extended period of time, which is not only difficult to implement, but it could also prove extremely costly and damaging to the economy. An alternative policy, this note argues, is to couple effective social distancing with extensive testing, even to those who are asymptomatic, and isolate the identified cases actively. Otherwise, many lives will be lost, and the health system will collapse, adding to the ongoing economic troubles that many countries have started to encounter.

positive: Centralized and decentralized isolation strategies and their impact on the COVID-19 pandemic dynamics The infectious diseases are spreading due to human interactions enabled by various social networks. Therefore, when a new pathogen such as SARS-CoV-2 causes an outbreak, the non-pharmaceutical isolation strategies (e.g., social distancing) are the only possible response to disrupt its spreading. To this end, we introduce the new epidemic model (SICARS) and compare the centralized (C), decentralized (D), and combined (C+D) social distancing strategies, and analyze their efficiency to control the dynamics of COVID-19 on heterogeneous complex networks. Our analysis shows that the centralized social distancing is necessary to minimize the pandemic spreading. The decentralized strategy is insufficient when used alone, but offers the best results when combined with the centralized one. Indeed, the (C+D) is the most efficient isolation strategy at mitigating the network superspreaders and reducing the highest node degrees to less than 10% of their initial values. Our results also indicate that stronger social distancing, e.g., cutting 75% of social ties, can reduce the outbreak by 75% for the C isolation, by 33% for the D isolation, and by 87% for the (C+D) isolation strategy. Finally, we study the impact of proactive versus reactive isolation strategies, as well as their delayed enforcement. We find that the reactive response to the pandemic is less efficient, and delaying the adoption of isolation measures by over one month (since the outbreak onset in a region) can have alarming effects; thus, our study contributes to an understanding of the COVID-19 pandemic both in space and time. We believe our investigations have a high social relevance as they provide insights into understanding how different degrees of social distancing can reduce the peak infection ratio substantially; this can make the COVID-19 pandemic easier to understand and control over an extended period of time.

positive: Spread of Covid-19 in the United States is controlled As of May 1, 2020, the number of cases of Covid-19 in the US passed 1,062,446, interventions to slow down the spread of Covid-19 curtailed most social activities. Meanwhile, an economic crisis and resistance to the strict intervention measures are rising. Some researchers proposed intermittent social distancing that may drive the outbreak of Covid-19 into 2022. Questions arise about whether we should maintain or relax quarantine measures. We developed novel artificial intelligence and causal inference integrated methods for real-time prediction and control of nonlinear epidemic systems. We estimated that the peak time of the Covid-19 in the US would be April 24, 2020 and its outbreak in the US will be over by the end of July and reach 1,551,901 cases. We evaluated the impact of relaxing the current interventions for reopening economy on the spread of Covid-19. We provide tools for balancing the risks of workers and reopening economy.

positive: Modeling Epidemics Spreading on Social Contact Networks. Social contact networks and the way people interact with each other are the key factors that impact on epidemics spreading. However, it is challenging to model the behavior of epidemics based on social contact networks due to their high dynamics. Traditional models such as susceptible-infected-recovered (SIR) model ignore the crowding or protection effect and thus has some unrealistic assumption. In this paper, we consider the crowding or protection effect and develop a novel model called improved SIR model. Then, we use both deterministic and stochastic models to characterize the dynamics of epidemics on social contact networks. The results from both simulations and real data set conclude that the epidemics are more likely to outbreak on social contact networks with higher average degree. We also present some potential immunization strategies, such as random set immunization, dominating set immunization, and high degree set immunization to further prove the conclusion.

positive: Influence of countries adopted policies for COVID-19 reduction under the view of the airborne transmission framework Daily new cases dataset since January 2020 were used to search for evidences of SARS-CoV-2 community transmission as the main nowadays cause of constant infection rates among countries. Despite traditional forms of transmission of this virus (droplets and aerosols in medical facilities), new evidence suggests aerosols forming patterns in the atmosphere as a main factor of community transmission outside medical spaces. Following these findings, this research focused on comparing some countries and the adopted policy used as preventive framework for virus community transmission. Countries social distancing policy aspect, of one to two meters of physical distance, was statistically analyzed from January to early May 2020, and countries were divided into those implementing only social physical distance and those implementing distancing with additional transmission isolation (with masks and city disinfection). Correlating countries social distancing policy adoption with other preventive measures such as social isolation and COVID-19 testing, a new indicator results, derived from SIR models and Weibull parameterization, show that only social physical distance measure could act as a factor for SARS-CoV-2 transmission with respect to atmosphere carrier potential. In this sense, the type of social distancing framework adopted by some countries without additional measures might represent a main model for the constant reproductive spread patterns of SARS-CoV-2 within the community transmission. Finally, the findings have important implications for the policy making to be adopted globally as well as individual-scale preventive methods.

positive: Extensions of the SEIR Model for the Analysis of Tailored Social Distancing and Tracing Approaches to Cope with COVID-19 In the context of the COVID-19 pandemic, governments worldwide face the challenge of designing tailored measures of epidemic control to provide reliable health protection while allowing more societal and economic activity. In this paper, we propose an extension of the epidemiological SEIR model to enable a detailed analysis of commonly discussed tailored measures of epidemic control - among them group-specific protection and the use of tracing apps. We introduce groups into the SEIR model that may differ both, in their underlying parameters as well as in their behavioral response to public health interventions. We allow for different infectiousness parameters within and across groups, different asymptomatic, hospitalization, and lethality rates, as well as different take-up rates of tracing apps. Our results visualize the sharp trade-offs between different goals of epidemic control, namely a low death toll, avoiding overload of the health system, and a short duration of the epidemic. We show that a combination of tailored mechanisms, e.g., the protection of vulnerable groups together with a “trace & isolate” approach, can be effective in preventing a high death toll. Protection of vulnerable groups without further measures requires unrealistically strict isolation. A key insight is that high compliance is critical for the effectiveness of a “trace & isolate” approach. Our model allows to analyze the interplay of group-specific social distancing and tracing also beyond our case study in scenarios with a large number of groups reflecting, e.g., sectoral, regional, or age differentiation and group-specific take-up rates for tracing apps.

positive: Modeling serological testing to inform relaxation of social distancing for COVID-19 control The value of serological testing to inform the public health response to the SARS-CoV-2 pandemic is debated. Using a transmission model, we examined how serology can be implemented to allow seropositive individuals to resume more normal levels of social interaction while offsetting the risks. We simulated the use of widespread serological testing with realistic assay characteristics, in which seropositive individuals partially restore their social contacts and act as immunological ‘shields’. If social distancing is relaxed by 50% at the same time that quarterly serological screening is initiated, approximately 120,000 deaths could be averted and a quarter of the US population could be released from social distancing in the first year of the epidemic, compared to a scenario without serological testing. This strategy has the potential to substantially flatten the COVID-19 epidemic curve while also allowing a substantial number of individuals to safely return to social and economic interactions.

positive: The differential impact of physical distancing strategies on social contacts relevant for the spread of COVID-19 Physical distancing measures are intended to mitigate the spread of COVID-19. However, the impact these measures have on social contact and disease transmission patterns remains unclear. We ran the first comparative contact survey (N=53,708) across eight countries (Belgium, France, Germany, Italy, Netherlands, Spain, United Kingdom, United States) for the period March 13 - April 13, 2020. Our results show that social contact numbers mainly decreased after governments issued physical distancing guidelines rather than after announcing national lockdown measures. Compared to pre-COVID levels, social contact numbers decreased by 48% - 85% across countries. Except in Italy, these reductions were smaller than those observed in Wuhan (China). However, they sufficed to bring the R0 below one in almost every context considered. Finally, in all countries studied, the numbers of contacts decreased more rapidly among older people than among younger people, indicating higher levels of protection for groups at greater risk.

positive: Human Mobility Restrictions and the Spread of the Novel Coronavirus (2019-nCoV) in China We quantify the causal impact of human mobility restrictions, particularly the lockdown of the city of Wuhan on January 23, 2020, on the containment and delay of the spread of the Novel Coronavirus (2019-nCoV). We employ a set of difference-in-differences (DID) estimations to disentangle the lockdown effect on human mobility reductions from other confounding effects including panic effect, virus effect, and the Spring Festival effect. We find that the lockdown of Wuhan reduced inflow into Wuhan by 76.64%, outflows from Wuhan by 56.35%, and within-Wuhan movements by 54.15%. We also estimate the dynamic effects of up to 22 lagged population inflows from Wuhan and other Hubei cities, the epicenter of the 2019-nCoV outbreak, on the destination cities' new infection cases. We find, using simulations with these estimates, that the lockdown of the city of Wuhan on January 23, 2020 contributed significantly to reducing the total infection cases outside of Wuhan, even with the social distancing measures later imposed by other cities. We find that the COVID-19 cases would be 64.81% higher in the 347 Chinese cities outside Hubei province, and 52.64% higher in the 16 non-Wuhan cities inside Hubei, in the counterfactual world in which the city of Wuhan were not locked down from January 23, 2020. We also find that there were substantial undocumented infection cases in the early days of the 2019-nCoV outbreak in Wuhan and other cities of Hubei province, but over time, the gap between the officially reported cases and our estimated "actual" cases narrows significantly. We also find evidence that enhanced social distancing policies in the 63 Chinese cities outside Hubei province are effective in reducing the impact of population inflows from the epicenter cities in Hubei province on the spread of 2019-nCoV virus in the destination cities elsewhere.

positive: Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts BACKGROUND: Isolation of cases and contact tracing is used to control outbreaks of infectious diseases, and has been used for coronavirus disease 2019 (COVID-19). Whether this strategy will achieve control depends on characteristics of both the pathogen and the response. Here we use a mathematical model to assess if isolation and contact tracing are able to control onwards transmission from imported cases of COVID-19. METHODS: We developed a stochastic transmission model, parameterised to the COVID-19 outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-like pathogen. We considered scenarios that varied in the number of initial cases, the basic reproduction number (R(0)), the delay from symptom onset to isolation, the probability that contacts were traced, the proportion of transmission that occurred before symptom onset, and the proportion of subclinical infections. We assumed isolation prevented all further transmission in the model. Outbreaks were deemed controlled if transmission ended within 12 weeks or before 5000 cases in total. We measured the success of controlling outbreaks using isolation and contact tracing, and quantified the weekly maximum number of cases traced to measure feasibility of public health effort. FINDINGS: Simulated outbreaks starting with five initial cases, an R(0) of 1·5, and 0% transmission before symptom onset could be controlled even with low contact tracing probability; however, the probability of controlling an outbreak decreased with the number of initial cases, when R(0) was 2·5 or 3·5 and with more transmission before symptom onset. Across different initial numbers of cases, the majority of scenarios with an R(0) of 1·5 were controllable with less than 50% of contacts successfully traced. To control the majority of outbreaks, for R(0) of 2·5 more than 70% of contacts had to be traced, and for an R(0) of 3·5 more than 90% of contacts had to be traced. The delay between symptom onset and isolation had the largest role in determining whether an outbreak was controllable when R(0) was 1·5. For R(0) values of 2·5 or 3·5, if there were 40 initial cases, contact tracing and isolation were only potentially feasible when less than 1% of transmission occurred before symptom onset. INTERPRETATION: In most scenarios, highly effective contact tracing and case isolation is enough to control a new outbreak of COVID-19 within 3 months. The probability of control decreases with long delays from symptom onset to isolation, fewer cases ascertained by contact tracing, and increasing transmission before symptoms. This model can be modified to reflect updated transmission characteristics and more specific definitions of outbreak control to assess the potential success of local response efforts. FUNDING: Wellcome Trust, Global Challenges Research Fund, and Health Data Research UK.

positive: Comparison of SARS-CoV-2 Exit Strategies Building Blocks We consider and compare various exit strategy building blocks and key measures to mitigate the current SARS-CoV-2 pandemic, some already proposed as well as improvements we suggest. Our comparison is based on a computerized simulation integrating accumulated SARS-CoV-2 epidemiological knowledge. Our results stress the importance of immediate on-symptom isolation of suspected cases and household members, and the beneficial effects of prompt testing capacity. Our findings expose significant epidemic-suppression differences among strategies with seemingly similar economic cost stressing the importance of not just the portion of population and business that is released, but also the pattern. The most effective building blocks are the ones that integrate several base strategies - they allow to release large portions of the population while still achieving diminishing viral spread. However, it may come with a price on somewhat more complex schemes. For example, our simulations indicate that dividing the population into two groups completely released except for taking turns on a long weekend (Fri-Tue) self-isolation once every two weeks, while protecting the 5% most sensitive population would reduce R below 1 even if ten percent of the population does not follow it. We further simulate the contrasting approach of a stratified population release in a hope to achieve herd immunity, which for the time being seems inferior to other suggested building blocks. Knowing the tradeoff between building blocks could help optimize exit strategies to be more effective and suitable for a particular area or country, while maximizing human life as well as economic value. Given our results, we believe that pandemic can be controlled within a reasonable amount of time and at a reasonable socio-economic burden.

positive: Transmission potential of COVID-19 in Iran We estimated the reproduction number of 2020 Iranian COVID-19 epidemic using two different methods: R0 was estimated at 4.4 (95% CI, 3.9, 4.9) (generalized growth model) and 3.50 (1.28, 8.14) (epidemic doubling time) (February 19 - March 1) while the effective R was estimated at 1.55 (1.06, 2.57) (March 6-19).

positive: Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study BACKGROUND: The coronavirus disease 2019 (COVID-19) epidemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), began in Wuhan city, Hubei province, in December, 2019, and has spread throughout China. Understanding the evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy. METHODS: We collected individual information from official public sources on laboratory-confirmed cases reported outside Hubei in mainland China for the period of Jan 19 to Feb 17, 2020. We used the date of the fourth revision of the case definition (Jan 27) to divide the epidemic into two time periods (Dec 24 to Jan 27, and Jan 28 to Feb 17) as the date of symptom onset. We estimated trends in the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (R(t)) at the provincial level. FINDINGS: We collected data on 8579 cases from 30 provinces. The median age of cases was 44 years (33–56), with an increasing proportion of cases in younger age groups and in elderly people (ie, aged >64 years) as the epidemic progressed. The mean time from symptom onset to hospital admission decreased from 4·4 days (95% CI 0·0–14·0) for the period of Dec 24 to Jan 27, to 2·6 days (0·0–9·0) for the period of Jan 28 to Feb 17. The mean incubation period for the entire period was estimated at 5·2 days (1·8–12·4) and the mean serial interval at 5·1 days (1·3–11·6). The epidemic dynamics in provinces outside Hubei were highly variable but consistently included a mixture of case importations and local transmission. We estimated that the epidemic was self-sustained for less than 3 weeks, with mean Rt reaching peaks between 1·08 (95% CI 0·74–1·54) in Shenzhen city of Guangdong province and 1·71 (1·32–2·17) in Shandong province. In all the locations for which we had sufficient data coverage of Rt, Rt was estimated to be below the epidemic threshold (ie, <1) after Jan 30. INTERPRETATION: Our estimates of the incubation period and serial interval were similar, suggesting an early peak of infectiousness, with possible transmission before the onset of symptoms. Our results also indicate that, as the epidemic progressed, infectious individuals were isolated more quickly, thus shortening the window of transmission in the community. Overall, our findings indicate that strict containment measures, movement restrictions, and increased awareness of the population might have contributed to interrupt local transmission of SARS-CoV-2 outside Hubei province. FUNDING: National Science Fund for Distinguished Young Scholars, National Institute of General Medical Sciences, and European Commission Horizon 2020.

positive: Initial impacts of global risk mitigation measures taken during the combatting of the COVID-19 pandemic Abstract This paper presents an analysis of risk mitigation measures taken by countries around the world facing the current COVID-19 outbreak. In light of the current pandemic the authors collated and clustered (using harmonised terminology) the risk mitigation measures taken around the globe in the combat to contain, and since March 11 2020, to limit the spread of the SARS-CoV-2 virus known to cause the Coronavirus disease 2019 (COVID-19). This overview gathers lessons learnt, providing an update on the current knowledge for authorities, sectors and first responders on the effectiveness of said measures, and may allow enhanced prevention, preparedness and response for future outbreaks. Various measures such as mobility restrictions, physical distancing, hygienic measures, socio-economic restrictions, communication and international support mechanisms have been clustered and are reviewed in terms of the nature of the actions taken and their qualitative early-perceived impact. At the time of writing, it is still too premature to express the quantitative effectiveness of each risk mitigation cluster, but it seems that the best mitigation results are reported when applying a combination of voluntary and enforceable measures.

positive: COVID-19: One-month impact of the French lockdown on the epidemic burden On March 16 2020, French authorities ordered a large scale lockdown to counter the COVID-19 epidemic wave rising in the country, stopping non-essential economic, educational, and entertainment activities, maintaining mainly food retailers and healthcare institutions. One month later, the number of new hospitalizations and ICU admissions had reached a plateau and were beginning a slow descent. We developed a spatialized, deterministic, age-structured, and compartmental SARS-CoV-2 transmission model able to reproduce the pre-lockdown dynamic of the epidemic in each of the 13 French metropolitan regions. Thanks to this model, we estimate, at regional and national levels, the total number of hospitalizations, ICU admissions, hospital beds requirements (hospitalization and ICU), and hospital deaths which may have been prevented by this massive and unprecedented intervention in France. If no control measures had been set up, between March 19 and April 19 2020, our analysis shows that almost 23% of the French population would have been affected by COVID-19 (14.8 million individuals). Hence, the French lockdown prevented 587,730 hospitalizations and 140,320 ICU admissions at the national level. The total number of ICU beds required to treat patients in critical conditions would have been 104,550, far higher than the maximum French ICU capacity. This first month of lockdown also permitted to avoid 61,739 hospital deaths, corresponding to a 83.5% reduction of the total number of predicted deaths. Our analysis shows that in absence of any control measures, the COVID-19 epidemic would have had a critical morbidity and mortality burden in France, overwhelming in a matter of weeks French hospital capacities.

positive: The impact of social distancing and epicenter lockdown on the COVID-19 epidemic in mainland China: A data-driven SEIQR model study The outbreak of coronavirus disease 2019 (COVID-19) which originated in Wuhan, China, constitutes a public health emergency of international concern with a very high risk of spread and impact at the global level. We developed data-driven susceptible-exposed-infectious-quarantine-recovered (SEIQR) models to simulate the epidemic with the interventions of social distancing and epicenter lockdown. Population migration data combined with officially reported data were used to estimate model parameters, and then calculated the daily exported infected individuals by estimating the daily infected ratio and daily susceptible population size. As of Jan 01, 2020, the estimated initial number of latently infected individuals was 380.1 (95%-CI: 379.8~381.0). With 30 days of substantial social distancing, the reproductive number in Wuhan and Hubei was reduced from 2.2 (95%-CI: 1.4~3.9) to 1.58 (95%-CI: 1.34~2.07), and in other provinces from 2.56 (95%-CI: 2.43~2.63) to 1.65 (95%-CI: 1.56~1.76). We found that earlier intervention of social distancing could significantly limit the epidemic in mainland China. The number of infections could be reduced up to 98.9%, and the number of deaths could be reduced by up to 99.3% as of Feb 23, 2020. However, earlier epicenter lockdown would partially neutralize this favorable effect. Because it would cause in situ deteriorating, which overwhelms the improvement out of the epicenter. To minimize the epidemic size and death, stepwise implementation of social distancing in the epicenter city first, then in the province, and later the whole nation without the epicenter lockdown would be practical and cost-effective.

positive: Evaluation of Turkish social distancing measures on the spread of COVID-19 The coronavirus disease (COVID-19) affecting across the globe. The government of different countries has adopted various policies to contain this epidemic and the most common were social distancing and lockdown. We use a simple log-linear model with intercept and trend break to evaluate whether the measures are effective preventing/slowing down the spread of the disease in Turkey. We estimate the model parameters from the Johns Hopkins University (2020) epidemic data between 15th March and 16th April 2020. Our analysis revealed that the measures can slow down the outbreak. We can reduce the epidemic size and prolong the time to arrive at the epidemic peak by seriously following the measures suggested by the authorities.

positive: No time for dilemma: mass gatherings must be suspended

positive: Size and timescale of epidemics in the SIR framework The most important features to assess the severity of an epidemic are its size and its timescale. We discuss these features in a systematic way in the context of SIR and SIR-type models. We investigate in detail how the size and timescale of the epidemic can be changed by acting on the parameters characterizing the model. Using these results and having as guideline the COVID-19 epidemic in Italy, we compare the efficiency of different containment strategies for contrasting an epidemic diffusion such as social distancing, lockdown, tracing, early detection and isolation.

positive: A Statistical Model for Quantifying the Needed Duration of Social Distancing for the COVID-19 Pandemic Understanding the effectiveness of strategies such as social distancing is a central question in attempts to control the COVID-19 pandemic. A key unknown in social distancing strategies is the duration of time for which such strategies are needed. Answering this question requires an accurate model of the transmission trajectory. A challenge in fitting such a model is the limited COVID-19 case data available from a given location. To overcome this challenge, we propose fitting a model of SARS-CoV-2 transmission jointly across multiple locations. We apply the model to COVID-19 case data from Spain, UK, Germany, France, Denmark, and New York to estimate the time needed for social distancing to end to be around October 2020. Our method is not specific to COVID-19, and it can also be applied to future pandemics.

positive: Mathematical Modeling and Analysis of COVID-19 pandemic in Nigeria A novel Coronavirus (COVID-19), caused by SARS-CoV-2, emerged from the Wuhan city of China at the end of 2019, causing devastating public health and socio-economic burden around the world. In the absence of a safe and effective vaccine or antiviral for use in humans, control and mitigation efforts against COVID-19 are focussed on using non-pharmaceutical interventions (aimed at reducing community transmission of COVID-19), such as social (physical)-distancing, community lockdown, use of face masks in public, isolation and contact tracing of confirmed cases and quarantine of people suspected of being exposed to COVID-19. We developed a mathematical model for understanding the transmission dynamics and control of COVID-19 in Nigeria, one of the main epicenters of COVID-19 in Africa. Rigorous analysis of the Kermack-McKendrick-type compartmental epidemic model we developed, which takes the form of a deterministic system of nonlinear differential equations, reveal that the model has a continuum of disease-free equilibria which is locally-asymptotically stable whenever a certain epidemiological threshold, called the it control reproduction (denoted by Rc), is less than unity. The epidemiological implication of this result is that the pandemic can be effectively controlled (or even eliminated) in Nigeria if the control strategies implemented can bring (and maintain) the epidemiological threshold (Rc) to a value less than unity. The model, which was parametrized using COVID-19 data published by Nigeria Centre for Disease Control (NCDC), was used to assess the community-wide impact of various control and mitigation strategies in the entire Nigerian nation, as well as in two states (Kano and Lagos) within the Nigerian federation and the Federal Capital Territory (FCT Abuja). It was shown that, for the worst-case scenario where social-distancing, lockdown and other community transmission reduction measures are not implemented, Nigeria would have recorded a devastatingly high COVID-19 mortality by April 2021 (in hundreds of thousands). It was, however, shown that COVID-19 can be effectively controlled using social-distancing measures provided its effectiveness level is at least moderate. Although the use of face masks in the public can significantly reduce COVID-19 in Nigeria, its use as a sole intervention strategy may fail to lead to the realistic elimination of the disease (since such elimination requires unrealistic high compliance in face mask usage in the public, in the range of 80% to 95%). COVID-19 elimination is feasible in both the entire Nigerian nation, and the States of Kano and Lagos, as well as the FCT, if the public face masks use strategy (using mask with moderate efficacy, and moderate compliance in its usage) is complemented with a social-distancing strategy. The lockdown measures implemented in Nigeria on March 30, 2020 need to be maintained for at least three to four months to lead to the effective containment of COVID-19 outbreaks in the country. Relaxing, or fully lifting, the lockdown measures sooner, in an effort to re-open the economy or the country, may trigger a deadly second wave of the pandemic.

positive: Enacting national social distancing policies corresponds with dramatic reduction in COVID19 infection rates The outbreak the SARS-CoV-2 (CoV-2) virus has resulted in over 2.5 million cases of COVID19, greatly stressing global healthcare infrastructure. Lacking medical prophylactic measures to combat disease spread, many nations have adopted social distancing policies in order to mitigate transmission of CoV-2. While mathematical models have suggested the efficacy of social distancing to curb the spread of CoV-2, there is a lack of systematic studies to quantify the real-world efficacy of these approaches. Here, we quantify the spread rate of COVID19 before and after national social distancing measures were implemented in 26 nations and compare this to the changes in COVID19 spread rate over equivalent time periods in 27 nations that did not enact social distancing policies. We find that social distancing policies significantly reduced the COVID19 spread rate. Using mixed linear regression models we estimate that social distancing policies reduced the spread of COVID19 by 66%. These data suggest that social distancing policies may be a powerful tool to prevent spread of COVID19 in real-world scenarios.

positive: How high and long will the COVID-19 wave be? A data-driven approach to model and predict the COVID-19 epidemic and the required capacity for the German health system Background an objective: In March 2020 the SARS-CoV-2 outbreak has been declared as global pandemic. Most countries have implemented numerous social distancing measures in order to limit its transmission and control the outbreak. This study aims to describe the impact of these control measures on the spread of the disease for Italy and Germany, forecast the epidemic trend of COVID-19 in both countries and estimate the medical capacity requirements in terms of hospital beds and intensive care units (ICUs) for optimal clinical treatment of severe and critical COVID-19 patients, for the Germany health system. Methods: We used an exponential decline function to model the trajectory of the daily growth rate of infections in Italy and Germany. A linear regression of the logarithmic growth rate functions of different stages allowed to describe the impact of the social distancing measures leading to a faster decline of the growth rate in both countries. We used the linear model to predict the number of diagnosed and fatal COVID-19 cases from April 10th until May 31st. For Germany we estimated the required daily number of hospital beds and intensive care units (ICU) using clinical observations on the average lengths of a hospital stay for the severe and critical COVID-19 patients. Results: Analyzing the data from Germany and Italy allowed us to identify changes in the trajectory of the growth rate of infection most likely resulted from the various social distancing measures implemented. In Italy a stronger decline in the growth rate was observed around the week of March 17th, whereas for Germany the stronger decline occurred approximately a week later (the week of March 23rd). Under the assumption that the impact of the measures will last, the total size of the outbreak can be estimated to 155,000 cases in Germany (range 140,000-180,000) and to 185,000 cases in Italy (range 175,000-200,000). For Germany the total number of deaths until May 31st is calculated to 3,850 (range 3,500-4,450). Based on the projected number of new COVID-19 cases we expect that the hospital capacity requirements for severe and critical cases in Germany will decline from the 2nd week of April onwards from 13,500 to ~2500 hospital beds (range 1500-4300) and from 2500 to ~500 ICU beds in early May (range 300-800). Conclusion: The modeling effort presented here provides a valuable framework to capture the impact of the social distancing measures on the COVID-19 epidemic in European countries and to forecast the future trend of daily COVID-19 cases. It provides a tool for medical authorities in Germany and other countries to help inform the required hospital capacity of the health care system. Germany appears to be in the middle of the (first) COVID-19 outbreak wave and the German health system is well prepared to handle it with the available capacities.

positive: Differential Effects of Intervention Timing on COVID-19 Spread in the United States Assessing the effects of early non-pharmaceutical interventions(1–5) on COVID-19 spread in the United States is crucial for understanding and planning future control measures to combat the ongoing pandemic(6–10). Here we use county-level observations of reported infections and deaths(11), in conjunction with human mobility data(12) and a metapopulation transmission model(13,14), to quantify changes of disease transmission rates in US counties from March 15, 2020 to May 3, 2020. We find significant reductions of the basic reproductive numbers in major metropolitan areas in association with social distancing and other control measures. Counterfactual simulations indicate that, had these same control measures been implemented just 1–2 weeks earlier, a substantial number of cases and deaths could have been averted. Specifically, nationwide, 56.5% [95% Cl: 48.1%−65.9%] of reported infections and 54.0% [95% Cl: 43.6%−63.8%] of reported deaths as of May 3, 2020 could have been avoided if the same control measures had been implemented just one week earlier. We also examine the effects of delays in re-implementing social distancing following a relaxation of control measures. A longer response time results in a stronger rebound of infections and death. Our findings underscore the importance of early intervention and aggressive response in controlling the COVID-19 pandemic.

positive: The Benefits and Costs of Using Social Distancing to Flatten the Curve for COVID-19 We examine the net benefits of social distancing to slow the spread of COVID-19 in USA. Social distancing saves lives but imposes large costs on society due to reduced economic activity. We use epidemiological and economic forecasting to perform a rapid benefit–cost analysis of controlling the COVID-19 outbreak. Assuming that social distancing measures can substantially reduce contacts among individuals, we find net benefits of about $5.2 trillion in our benchmark case. We examine the magnitude of the critical parameters that might imply negative net benefits, including the value of statistical life and the discount rate. A key unknown factor is the speed of economic recovery with and without social distancing measures in place. A series of robustness checks also highlight the key role of the value of mortality risk reductions and discounting in the analysis and point to a need for effective economic stimulus when the outbreak has passed.

positive: Initial Simulation of SARS-CoV2 Spread and Intervention Effects in the Continental US Here we use a metapopulation model applied at county resolution to simulate the spread and growth of COVID-19 incidence in the continental United States. We calibrate the model against county-level incidence data collected between February 21, 2020 and March 13, 2020, and estimate epidemiological parameters including the fraction of undocumented infections and their contagiousness1. Using the calibrated model, we project the outbreak in the continental US for 180 days after March 13, 2020, and evaluate the effects of social distancing and travel restrictions on the outbreak.

positive: COVID-19 and the Social Distancing Paradox: dangers and solutions Background: Without proven effect treatments and vaccines, Social Distancing is the key protection factor against COVID-19. Social distancing alone should have been enough to protect again the virus, yet things have gone very differently, with a big mismatch between theory and practice. What are the reasons? A big problem is that there is no actual social distancing data, and the corresponding people behavior in a pandemic is unknown. We collect the world-first dataset on social distancing during the COVID-19 outbreak, so to see for the first time how people really implement social distancing, identify dangers of the current situation, and find solutions against this and future pandemics. Methods: Using a sensor-based social distancing belt we collected social distance data from people in Italy for over two months during the most critical COVID-19 outbreak. Additionally, we investigated if and how wearing various Personal Protection Equipment, like masks, influences social distancing. Results: Without masks, people adopt a counter-intuitively dangerous strategy, a paradox that could explain the relative lack of effectiveness of social distancing. Using masks radically changes the situation, breaking the paradoxical behavior and leading to a safe social distance behavior. In shortage of masks, DIY (Do It Yourself) masks can also be used: even without filtering protection, they provide social distancing protection. Goggles should be recommended for general use, as they give an extra powerful safety boost. Generic Public Health policies and media campaigns do not work well on social distancing: explicit focus on the behavioral problems of necessary mobility are needed.

positive: Real-time monitoring the transmission potential of COVID-19 in Singapore, March 2020 BACKGROUND: As of March 31, 2020 the ongoing COVID-19 epidemic that started in China in December 2019 is now generating local transmission around the world. The geographic heterogeneity and associated intervention strategies highlight the need to monitor in real time the transmission potential of COVID-19. Singapore provides a unique case example for monitoring transmission, as there have been multiple disease clusters, yet transmission remains relatively continued. METHODS: Here we estimate the effective reproduction number, R(t), of COVID-19 in Singapore from the publicly available daily case series of imported and autochthonous cases by date of symptoms onset, after adjusting the local cases for reporting delays as of March 17, 2020. We also derive the reproduction number from the distribution of cluster sizes using a branching process analysis that accounts for truncation of case counts. RESULTS: The local incidence curve displays sub-exponential growth dynamics, with the reproduction number following a declining trend and reaching an estimate at 0.7 (95% CI: 0.3, 1.0) during the first transmission wave by February 14, 2020 while the overall R based on the cluster size distribution as of March 17, 2020 was estimated at 0.6 (95% CI: 0.4, 1.02). The overall mean reporting delay was estimated at 6.4 days (95% CI: 5.8, 6.9), but it was shorter among imported cases compared to local cases (mean 4.3 vs. 7.6 days, Wilcoxon test, p<0.001). CONCLUSION: The trajectory of the reproduction number in Singapore underscores the significant effects of successful containment efforts in Singapore, but it also suggests the need to sustain social distancing and active case finding efforts to stomp out all active chains of transmission.

positive: Epidemiological and Clinical Aspects of COVID-19; a Narrative Review There are significant misconceptions and many obstacles in the way of illuminating the epidemiological and clinical aspects of COVID-19 as a new emerging epidemic. In addition, usefulness of some evidence published in the context of the recent epidemic for decision making in clinic as well as public health is questionable. However, misinterpreting or ignoring strong evidence in clinical practice and public health probably results in less effective and somehow more harmful decisions for individuals as well as subgroups in general populations of countries in the initial stages of this epidemic. Accordingly, our narrative review appraised epidemiological and clinical aspects of the disease including genetic diversity of coronavirus genus, mode of transmission, incubation period, infectivity, pathogenicity, virulence, immunogenicity, diagnosis, surveillance, clinical case management and also successful measures for preventing its spread in some communities.

positive: How will this continue? Modelling interactions between the COVID-19 pandemic and policy responses Much of the uncertainty about the progression of the COVID-19 pandemic stems from questions about when and how non-pharmaceutical interventions (NPI) by governments, in particular social distancing measures, are implemented, to what extent the population complies with these measures, and how compliance changes through time. Further uncertainty comes from a lack of knowledge of the potential effects of removing interventions once the epidemic is declining. By combining an epidemiological model of COVID-19 for the United Kingdom with simple sub-models for these societal processes, this study aims to shed light on the conceivable trajectories that the pandemic might follow over the next 1.5 years. We show strong improvements in outcomes if governments review NPI more frequently whereas, in comparison, the stability of compliance has surprisingly small effects on cumulative mortality. Assuming that mortality does considerably increase once a country's hospital capacity is breached, we show that the inherent randomness of societal processes can lead to a wide range of possible outcomes, both in terms of disease dynamics and mortality, even when the principles according to which policy and population operate are identical.. Our model is easily modified to take other aspects of the socio-pandemic interaction into account.

positive: Patterns of the COVID19 epidemic spread around the world: exponential vs power laws We have analyzed the COVID19 epidemic data of more than 174 countries (excluding China) in the period between January 22 and March 28, 2020. We found that some countries (such as the US, the UK, and Canada) follow an exponential epidemic growth, while others (like Italy and several other European countries) show a power law like growth. At the same time, regardless of the best fitting law, most countries can be shown to follow a trajectory similar to that of Italy, but with varying degrees of delay. We found that countries with ``younger" epidemics tend to exhibit more exponential like behavior, while countries that are closer behind Italy tend to follow a power law growth. We hypothesize that there is a universal growth pattern of this infection that starts off as exponential and subsequently becomes more power law like. Although it cannot be excluded that this growth pattern is a consequence of social distancing measures, an alternative explanation is that it is an intrinsic epidemic growth law, dictated by a spatially distributed community structure, where the growth in individual highly mixed communities is exponential but the longer term, local geographical spread (in the absence of global mixing) results in a power-law. This is supported by computer simulations of a metapopulation model that gives rise to predictions about the growth dynamics that are consistent with correlations found in the epidemiological data. Therefore, seeing a deviation from straight exponential growth may not be a consequence of working non-pharmaceutical interventions (except for, perhaps, restricting the air travel). Instead, this is a normal course of raging infection spread. On the practical side, this cautions us against overly optimistic interpretations of the countries epidemic development and emphasizes the need to continue improving the compliance with social distancing behavior recommendations.

positive: Examining the Effect of Social Distancing on the Compound Growth Rate of SARS-CoV-2 at the County Level (United States) Using Statistical Analyses and a Random Forest Machine Learning Model Abstract Objectives The goal of the present work is to investigate trends among US counties and COVID-19 growth rate in relation to the existence of shelter in place (SIP) orders in that county. Study Design Prospective cohort study. Methods Compound growth rates were calculated using cumulative confirmed COVID-19 cases from January 21, 2020, to March 31, 2020 in all 3,139 US counties. Compound growth was chosen as it gives a single number that can be used in machine learning to represent speed of virus spread during defined time intervals. Statistical analyses and a random forest machine learning model were used to analyze the data for differences in counties with and without shelter in place orders. Results Statistical analyses revealed that the March 16 presidential recommendation (limiting gatherings to < 10 people) lowered the compound growth rate of COVID-19 for all counties in the US by 6.6%, and the counties that implemented SIP after March 16 had a further reduction of 7.8% over the counties with no SIP after March 16. A random forest machine learning model was built to predict compound growth rate after a SIP order and was found to have an accuracy of 92.3%. The random forest found that population, longitude, and population per square mile were the most important features when predicting the effect of SIP. Conclusions Shelter in place orders were found to be effective at reducing the growth rate of COVID-19 cases in the US. Counties with a large population or a high population density were found to benefit the most from a shelter in place order.

positive: A Mathematical Model Approach for Prevention and Intervention Measures of the COVID-19 Pandemic in Uganda The human-infecting corona virus disease (COVID-19) caused by the novel severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) was declared a global pandemic on March 11th, 2020. Current human deaths due to the infection have raised the threat globally with only 1 African country free of Virus (Lesotho) as of May 6th, 2020. Different countries have adopted different interventions at different stages of the outbreak, with social distancing being the first option while lock down the preferred option for flattening the curve at the peak of the pandemic. Lock down is aimed at adherence to social distancing, preserve the health system and improve survival. We propose a Susceptible-Exposed-Infected-Expected recoveries (SEIR) mathematical model to study the impact of a variety of prevention and control strategies Uganda has applied since the eruption of the pandemic in the country. We analyze the model using available data to find the infection-free, endemic/infection steady states and the basic reproduction number. In addition, a sensitivity analysis done shows that the transmission rate and the rate at which persons acquire the virus, have a positive influence on the basic reproduction number. On other hand the rate of evacuation by rescue ambulance greatly reduces the reproduction number. The results have potential to inform the impact and effect of early strict interventions including lock down in resource limited settings and social distancing

positive: How long will social distancing take to work? Experts weigh in on Canada's COVID-19 response.

positive: Social Isolation as a predictor for mortality: Implications for COVID-19 prognosis The health benefits of social support have been widely documented. However, the social distancing practices from the COVID-19 pandemic is causing social disruption on a grand scale, potentially causing poor health outcomes. Through Google Trends analysis, we found a COVID-19-related surge in interest surrounding loneliness. We assessed if social isolation and loneliness increase the risk for all-cause and cardiovascular disease (CVD) mortality (ICD-10: I00-I99) and used the data to create a conceptual framework. Using the 10-year overall and cardiovascular mortality follow-up data (n = 12,019) from the National Health and Nutrition Examination Survey (1999-2008), we conducted survival analyses and found that individuals who experience social isolation or loneliness have a significantly higher likelihood of overall and CVD mortality than those without support. These effects generally remained strong with further adjustment for NHANES-detected health and demographic differences showing the need to address COVID-19 related loneliness through increasing social nearing.

positive: Social interventions can lower COVID-19 deaths in middle-income countries A novel pandemic coronavirus disease (COVID-19) was first detected in late 2019 in Wuhan (China)1,2. COVID-19 has caused 77 national governments worldwide to impose a lockdown in part or all their countries, as of April 4, 20203. The United States and the United Kingdom estimated the effectiveness of non-pharmaceutical interventions to reduce COVID-19 deaths, but there is less evidence to support choice of control measures in middle-income countries4. We used Colombia, an upper-middle income country, as a case-study to assess the effect of social interventions to suppress or mitigate the COVID-19 pandemic. Here we show that a combination of social distancing interventions, triggered by critical care admissions, can suppress and mitigate the peak of COVID-19, resulting in less critical care use, hospitalizations, and deaths. We found, through a mathematical simulation model, that a one-time social intervention may delay the number of critical care admissions and deaths related to the COVID-19 pandemic. However, a series of social interventions (social and work distance and school closures) over a period of a year can reduce the expected burden of COVID-19, however, these interventions imply long periods of lockdown. Colombia would prevent up to 97% of COVID-19 deaths using these triggered series of interventions during the first year. Our analyses could be used by decision-makers from other middle-income countries with similar demographics and contact patterns to Colombia to reduce COVID-19 critical care admissions and deaths in their jurisdictions.

positive: Influence of wind and relative humidity on the social distancing effectiveness to prevent COVID-19 airborne transmission: A numerical study It has been confirmed that the coronavirus disease 2019 (COVID-19) can transmit through droplets created when an infected human coughs or sneezes. Accordingly, 1.83-m (6-feet) social distancing is advised to reduce the spread of the disease among humans. This is based on the assumption that no air circulation exists around people. However, it is not well investigated whether the ambient wind and relative humidity (RH) will cause SARS-CoV-2 laden droplets to transport farther in the air, making the current social distancing policy insufficient. To provide evidence and insight into the “social distancing” guidelines, a validated computational fluid-particle dynamics (CFPD) model was employed to simulate the transient transport, condensation/evaporation, and deposition of SARS-CoV-2 laden droplets emitted by coughs, with different environmental wind velocities and RHs. Initial droplet diameters range from 2 to 2000 μm, and the wind velocities range from 0 to 16 km/h, representing different wind forces from calm air to moderate breeze. The comparison between a steady-state wind and a gust with a constant frequency has also been performed. Ambient RHs are 40% and 99.5%. The distances between the two virtual humans are 1.83 m and 3.05 m (6 feet and 10 feet). The facial covering effect on reducing the airborne transmission of the cough droplets has also been evaluated. Numerical results indicate that the ambient wind will enhance the complexity of the secondary flows with recirculation between the two virtual humans. Microdroplets follow the airflow streamlines well and deposit on both human bodies and head regions, even with the 3.05-m (10-feet) separation distance. The rest of the microdroplets can transport in the air farther than 3.05 m (10 feet) due to wind convection, causing a potential health risk to nearby people. High RH will increase the droplet sizes due to the hygroscopic growth effect, which increases the deposition fractions on both humans and the ground. With the complex environmental wind and RH conditions, the 6-feet social distancing policy may not be sufficient to protect the inter-person aerosol transmission, since the suspending micro-droplets were influenced by convection effects and can be transported from the human coughs/sneezes to the other human in less than 5 s. Thus, due to the complex real-world environmental ventilation conditions, a social distance longer than 6 feet needs to be considered. Wearing masks should also be recommended for both infected and healthy humans to reduce the airborne cough droplet numbers.

positive: School closure and management practices during coronavirus outbreaks including COVID-19: a rapid systematic review In response to the coronavirus disease 2019 (COVID-19) pandemic, 107 countries had implemented national school closures by March 18, 2020. It is unknown whether school measures are effective in coronavirus outbreaks (eg, due to severe acute respiratory syndrome [SARS], Middle East respiratory syndrome, or COVID-19). We undertook a systematic review by searching three electronic databases to identify what is known about the effectiveness of school closures and other school social distancing practices during coronavirus outbreaks. We included 16 of 616 identified articles. School closures were deployed rapidly across mainland China and Hong Kong for COVID-19. However, there are no data on the relative contribution of school closures to transmission control. Data from the SARS outbreak in mainland China, Hong Kong, and Singapore suggest that school closures did not contribute to the control of the epidemic. Modelling studies of SARS produced conflicting results. Recent modelling studies of COVID-19 predict that school closures alone would prevent only 2-4% of deaths, much less than other social distancing interventions. Policy makers need to be aware of the equivocal evidence when considering school closures for COVID-19, and that combinations of social distancing measures should be considered. Other less disruptive social distancing interventions in schools require further consideration if restrictive social distancing policies are implemented for long periods.

positive: Modeling, state estimation, and optimal control for the US COVID-19 outbreak The novel coronavirus SARS-CoV-2 and resulting COVID-19 disease have had an unprecedented spread and continue to cause an increasing number of fatalities worldwide. While vaccines are still under development, social distancing, extensive testing, and quarantining of confirmed infected subjects remain the most effective measures to contain the pandemic. These measures carry a significant socioeconomic cost. In this work, we introduce a novel optimization-based decision-making framework for managing the COVID-19 outbreak in the US. This includes modeling the dynamics of affected populations, estimating the model parameters and hidden states from data, and an optimal control strategy for sequencing social distancing and testing events such that the number of infections is minimized. The analysis of our extensive computational efforts reveals that social distancing and quarantining are most effective when implemented early, with quarantining of confirmed infected subjects having a much higher impact. Further, we find that "on-off" policies alternating between strict social distancing and relaxing such restrictions can be effective at "flattening" the curve while likely minimizing social and economic cost.

positive: The projected impact of mitigation and suppression strategies on the COVID-19 epidemic in Senegal: A modelling study Background: Physical distancing measures that reduce social contacts have formed a key part of national COVID-19 containment and mitigation strategies. Many Sub-Saharan African nations are now facing increasing numbers of cases of COVID-19 and there is a need to understand what levels of measures may be required to successfully reduce transmission. Methods: We collated epidemiological data along with information on key COVID-19 specific response policies and health system capacity estimates for services needed to treat COVID-19 patients in Senegal. We calibrated an age-structured SEIR model to these data to capture transmission dynamics accounting for demography, contact patterns, hospital capacity and disease severity. We simulated the impact of mitigation and suppression strategies focussed on reducing social contact rates. Results: Senegal acted promptly to contain the spread of SARS-CoV-2 and as a result has reduced the reproduction number from 1.9 (95% CI 1.7-2.2) to 1.3 (95% CI 1.2-1.5), which has slowed but not fully interrupted transmission. We estimate that continued spread is likely to peak in October, and to overwhelm the healthcare system with an estimated 77,400 deaths(95% CI 55,270-100,700). Further reductions in contact rates to suppress transmission (Rt<1) could significantly reduce this burden on healthcare services and improve overall health outcomes. Conclusions: Our results demonstrate that Senegal has already significantly reduced transmission. Enhanced physical distancing measures and rapid scale up of hospital capacity is likely to be needed to reduce mortality and protect healthcare infrastructure from high levels of demand.

positive: Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study BACKGROUND: Non-pharmaceutical interventions have been implemented to reduce transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the UK. Projecting the size of an unmitigated epidemic and the potential effect of different control measures has been crucial to support evidence-based policy making during the early stages of the epidemic. This study assesses the potential impact of different control measures for mitigating the burden of COVID-19 in the UK. METHODS: We used a stochastic age-structured transmission model to explore a range of intervention scenarios, tracking 66·4 million people aggregated to 186 county-level administrative units in England, Wales, Scotland, and Northern Ireland. The four base interventions modelled were school closures, physical distancing, shielding of people aged 70 years or older, and self-isolation of symptomatic cases. We also modelled the combination of these interventions, as well as a programme of intensive interventions with phased lockdown-type restrictions that substantially limited contacts outside of the home for repeated periods. We simulated different triggers for the introduction of interventions, and estimated the impact of varying adherence to interventions across counties. For each scenario, we projected estimated new cases over time, patients requiring inpatient and critical care (ie, admission to the intensive care units [ICU]) treatment, and deaths, and compared the effect of each intervention on the basic reproduction number, R0. FINDINGS: We projected a median unmitigated burden of 23 million (95% prediction interval 13-30) clinical cases and 350â000 deaths (170â000-480â000) due to COVID-19 in the UK by December, 2021. We found that the four base interventions were each likely to decrease R0, but not sufficiently to prevent ICU demand from exceeding health service capacity. The combined intervention was more effective at reducing R0, but only lockdown periods were sufficient to bring R0 near or below 1; the most stringent lockdown scenario resulted in a projected 120â000 cases (46â000-700â000) and 50â000 deaths (9300-160â000). Intensive interventions with lockdown periods would need to be in place for a large proportion of the coming year to prevent health-care demand exceeding availability. INTERPRETATION: The characteristics of SARS-CoV-2 mean that extreme measures are probably required to bring the epidemic under control and to prevent very large numbers of deaths and an excess of demand on hospital beds, especially those in ICUs. FUNDING: Medical Research Council.

positive: The impact of physical distancing measures against COVID-19 transmission on contacts and mixing patterns in the Netherlands: repeated cross-sectional surveys Background During the current pandemic of coronavirus (COVID-19) many countries have taken drastic measures to reduce transmission of SARS-CoV2. The measures often include physical distancing that aims to reduce the number of contacts in the population. Little is known about the actual reduction in number of contacts as a consequence of physical distancing measures. Methods In the Netherlands, a cross-sectional survey was carried out in 2016/2017 in which 8179 participants retrospectively reported the number, age and gender of different persons they had contacted (spoken to in person or touched) during the previous day. The survey was repeated among 2830 of the original participants, using the same questionnaire, in March and April 2020 after physical distancing measures had been implemented. Results The average number of contacts in the community was reduced from on average 12.5 (interquartile range: 2-17) to 3.7 (interquartile range: 0-4) different persons per participant, a reduction of 71% (95% confidence interval: 71-71). The reduction in the number of community contacts was highest for children and adolescents (between 5 and 20 years) and smallest for elderly persons of 80 years and older. The reduction in the effective number of total contacts, measured as the largest eigenvalue of the matrix with community and household contacts, was 62% (95% confidence interval: 48 - 72). Conclusion The substantial reduction in contacts has contributed greatly in halting the COVID-19 epidemic. This reduction was unevenly distributed over age groups, household sizes and occupations. These findings offer guidance for the lifting of age-group targeted measures.

positive: A novel COVID-19 epidemiological model with explicit susceptible and asymptomatic isolation compartments reveals unexpected consequences of timing social distancing Motivated by the current COVID-19 epidemic, this work introduces an epidemiological model in which separate compartments are used for susceptible and asymptomatic "socially distant" populations. Distancing directives are represented by rates of flow into these compartments, as well as by a reduction in contacts that lessens disease transmission. The dynamical behavior of this system is analyzed, under various different rate control strategies, and the sensitivity of the basic reproduction number to various parameters is studied. One of the striking features of this model is the existence of a critical implementation delay in issuing separation mandates: while a delay of about four weeks does not have an appreciable effect, issuing mandates after this critical time results in a far greater incidence of infection. In other words, there is a nontrivial but tight "window of opportunity" for commencing social distancing. Different relaxation strategies are also simulated, with surprising results. Periodic relaxation policies suggest a schedule which may significantly inhibit peak infective load, but that this schedule is very sensitive to parameter values and the schedule's frequency. Further, we considered the impact of steadily reducing social distancing measures over time. We find that a too-sudden reopening of society may negate the progress achieved under initial distancing guidelines, if not carefully designed.

positive: Evaluating the Effectiveness of Social Distancing Interventions to Delay or Flatten the Epidemic Curve of Coronavirus Disease. By April 2, 2020, >1 million persons worldwide were infected with severe acute respiratory syndrome coronavirus 2. We used a mathematical model to investigate the effectiveness of social distancing interventions in a mid-sized city. Interventions reduced contacts of adults >60 years of age, adults 20-59 years of age, and children <19 years of age for 6 weeks. Our results suggest interventions started earlier in the epidemic delay the epidemic curve and interventions started later flatten the epidemic curve. We noted that, while social distancing interventions were in place, 20% of new cases and most hospitalizations and deaths were averted, even with modest reductions in contact among adults. However, when interventions ended, the epidemic rebounded. Our models suggest that social distancing can provide crucial time to increase healthcare capacity but must occur in conjunction with testing and contact tracing of all suspected cases to mitigate virus transmission.

positive: Age-structured impact of social distancing on the COVID-19 epidemic in India The outbreak of the novel coronavirus, COVID-19, has been declared a pandemic by the WHO. The structures of social contact critically determine the spread of the infection and, in the absence of vaccines, the control of these structures through large-scale social distancing measures appears to be the most effective means of mitigation. Here we use an age-structured SIR model with social contact matrices obtained from surveys and Bayesian imputation to study the progress of the COVID-19 epidemic in India. The basic reproductive ratio R0 and its time-dependent generalization are computed based on case data, age distribution and social contact structure. The impact of social distancing measures - workplace non-attendance, school closure, lockdown - and their efficacy with durations are then investigated. A three-week lockdown is found insufficient to prevent a resurgence and, instead, protocols of sustained lockdown with periodic relaxation are suggested. Forecasts are provided for the reduction in age-structured morbidity and mortality as a result of these measures. Our study underlines the importance of age and social contact structures in assessing the country-specific impact of mitigatory social distancing.

positive: Predict the next moves of COVID-19: reveal the temperate and tropical countries scenario The spread of COVID-19 engulfs almost all the countries and territories of the planet, and infections and fatality are increasing rapidly. The first epi-center of its' massive spread was in Wuhan, Hubei province, China having a temperate weather, but the spread has got an unprecedented momentum in European temperate countries mainly in Italy and Spain (as of March 30, 2020). However, Malaysia and Singapore and the neighboring tropical countries of China got relatively low spread and fatality that created a research interest on whether there are potential impacts of weather condition on COVID-19 spread. Adopting the SIR (Susceptible Infected Removed) deviated model to predict potential cases and death in the coming days from COVID-19 was done using the secondary and official sources of data. This study shows that COVID-19 spread and fatality tend to be high across the world but compared to tropical countries, it is going to be incredibly high in the temperate countries having lower temperature (7-16°C) and humidity (80-90%) in last March. However, some literature predicted that this might not to be true, rather irrespective of weather conditions there might be a continuous spread and death. Moreover, a large number of asymptotic COVID-19 carrier in both temperate and tropical countries may re-outbreak in the coming winter. Therefore, a comprehensive global program with the leadership of WHO for testing of entire population of the world is required, which will be very useful for the individual states to take proper political action, social movement and medical services.

positive: Voluntary Cyclical Distancing: A potential alternative to constant level mandatory social distancing, relying on an 'infection weather report' COVID-19 has significantly changed our daily lives. Stay-at-home orders and forced closings of all non-essential businesses has had a significant impact on our economy. While it is important to ensure that the healthcare system is not overwhelmed, there are many questions that remain about the efficacy of extreme social distancing, and whether there are alternatives to mandatory lockdowns. This paper analyzes the utility of various levels of social distancing, and suggests an alternative approach using voluntary distancing informed by an infectious load index or 'infection weather report.'

positive: Early Mandated Social Distancing is a Strong Predictor of Reduction in Highest Number of New COVID-19 cases per Day within Various Geographic Regions Mandated social distancing has been globally applied to limit the spread of corona virus disease 2019 (COVID-19) from highly pathogenic severe acute respiratory syndrome (SARS) -associated coronavirus 2 (SARS-CoV-2). The benefit of this community-based intervention in limiting COVID-19 has not been proven nor quantified. We examined the effect of timing of mandated social distancing on the rate of COVID-19 in 119 geographic regions derived from 41 states within United States and 78 countries. We found that highest number of new COVID-19 cases per day per million persons was significantly associated with total number of COVID-19 cases per million persons on the day before mandated social distancing (Beta;=0.66, p<0.0001). Our findings suggest that the initiation of mandated social distancing for each doubling in number of existing COVID-19 cases would result in eventual peak with 58% higher number of COVID-19 infections per day. Subgroup analysis on those regions where the highest number of new COVID-19 cases per day have peaked increased Beta to .85 (p<0.0001). We demonstrate that initiating mandated social distancing at a 10 times smaller number of COVID-19 cases will reduce the number of daily new COVID-19 cases at peak by 80% highlighting the importance of this community-based intervention.

positive: Expected impact of lockdown in Île-de-France and possible exit strategies More than half of the global population is currently under strict forms of social distancing, with more than 90 countries in lockdown, including France. Estimating the expected impact of the lockdown, and the potential effectiveness of different exit strategies is critical to inform decision makers on the management of the COVID-19 health crisis. We use a stochastic age-structured transmission model integrating data on age profile and social contacts in the Île-de-France region to (i) assess the current epidemic situation, (ii) evaluate the expected impact of the lockdown implemented in France on March 17, 2020, and (iii) estimate the effectiveness of possible exit strategies. The model is calibrated on hospital admission data of the region before lockdown and validated on syndromic and virological surveillance data. Different types and durations of social distancing interventions are simulated, including a progressive lifting of the lockdown targeted on specific classes of individuals (e.g. allowing a larger proportion of the population to go to work, while protecting the elderly), and large-scale testing. We estimate the basic reproductive number at 3.0 [2.8, 3.2] (95% confidence interval) prior to lockdown and the population infected by COVID-19 as of April 5 to be in the range 1% to 6%. The average number of contacts is predicted to be reduced by 80% during lockdown, leading to a substantial reduction of the reproductive number (RLD = 0.68 [0.62-0.73]). Under these conditions, the epidemic curve reaches ICU system capacity and slowly decreases during lockdown. Lifting the lockdown with no exit strategy would lead to a second wave largely overwhelming the healthcare system. Extensive case-finding, testing and isolation are required to envision social distancing strategies that gradually relax current constraints (larger fraction of individuals going back to work, progressive reopening of activities), while keeping schools closed and seniors isolated. As France faces the first wave of COVID-19 pandemic in lockdown, intensive forms of social distancing are required in the upcoming months due to the currently low population immunity. Extensive case-finding and isolation would allow the partial release of the socio-economic pressure caused by extreme measures, while avoiding healthcare demand exceeding capacity. Response planning needs to urgently prioritize the logistics and capacity for these interventions.

positive: Modelling the SARS-CoV-2 first epidemic wave in Greece: social contact patterns and impact assessment of social distancing interventions. In Greece, a nationwide lockdown to mitigate the transmission of SARS-CoV-2 was imposed on March 23, 2020. As by the end of April the first epidemic wave is waning, it is important to assess the infection attack rate and quantify the impact of physical distancing. We implemented a survey to assess social mixing patterns before the epidemic and during lockdown. We estimated R0 from surveillance data and assessed its decline as a result of physical distancing based on social contacts data. We applied a Susceptible-Exposed-Infectious-Recovered model to estimate the infection attack rate and the infection fatality ratio (IFR). As multiple social distancing measures were implemented simultaneously (schools/work/leisure), we assessed their overall impact as well as their relative contribution. R0 was estimated 2.38 (95%CI: 2.01,2.80). By April 26th, the infection attack rate was 0.12% (95% CrI: 0.06%,0.26%) and the IFR 1.12% (95% CrI: 0.55%,2.31%). During lockdown, daily contacts were reduced by 86.9% and the effective reproduction number reached 0.46 (95% CrI: 0.35,0.57). The reduction in R0 attributed to lockdown was 81.0% (95% CrI: 71.8%,86.0%) whereas the reduction attributed to each measure separately ranged between 10%-24%. We assessed scenarios with less disruptive social distancing measures as well as scenarios where measures are partially lifted after lockdown. This is the first impact assessment of the first wave of SARS-CoV-2 in a European country. It suggests that only multiple measures implemented simultaneously could reduce R0 below 1. Measuring social mixing patterns can be a tool for real-time monitoring of the epidemic potential.

positive: Impact of self-imposed prevention measures and short-term government intervention on mitigating and delaying a COVID-19 epidemic Background: With new cases of COVID-19 surging around the world, many countries have to prepare for moving beyond the containment phase. Prediction of the effectiveness of non-case-based interventions for mitigating, delaying or preventing the epidemic is urgent, especially for countries affected by the ongoing seasonal influenza activity. Methods: We developed a transmission model to evaluate the impact of self-imposed prevention measures (handwashing, mask-wearing, and social distancing) due to the spread of COVID-19 awareness and of short-term government-imposed social distancing on the peak number of diagnoses, attack rate and time until the peak number of diagnoses. Findings: For fast awareness spread in the population, self-imposed measures can significantly reduce the attack rate, diminish and postpone the peak number of diagnoses. A large epidemic can be prevented if the efficacy of these measures exceeds 50%. For slow awareness spread, self-imposed measures reduce the peak number of diagnoses and attack rate but do not affect the timing of the peak. Early implementation of short-term government interventions can only delay the peak (by at most 7 months for a 3-month intervention). Interpretation: Handwashing, mask-wearing and social distancing as a reaction to information dissemination about COVID-19 can be effective strategies to mitigate and delay the epidemic. We stress the importance of rapidly spreading awareness on the use of these self-imposed prevention measures in the population. Early-initiated short-term government-imposed social distancing can buy time for healthcare systems to prepare for an increasing COVID-19 burden. Keywords: SARS-CoV-2, COVID-19, mathematical model, prevention measures, mitigation, epidemic control, disease awareness, social distancing, handwashing, mask-wearing

positive: Quantifying what could have been - The impact of the Australian and New Zealand governments' response to COVID-19 BACKGROUND: The Australian and New Zealand governments both initiated strict social distancing measures in response to the COVID-19 pandemic in late March. It remains difficult to quantify the impact this had in reducing the spread of the virus. METHODS: Bayesian structural time series model provide a model to quantify the scenario in which these government-level interventions were not placed. Our models predict these strict social distancing measures caused a 79% and 61% reduction in the daily cases of COVID-19 across Australia and New Zealand respectively. CONCLUSION: This provides both evidence and impetus for governments considering similar measures in response to COVID-19 and other pandemics.

positive: A dynamic modeling tool for estimating healthcare demand from the COVID19 epidemic and evaluating population-wide interventions OBJECTIVES: Public health officials need tools to assist with anticipating the healthcare resources required to confront the SARS-COV-2 pandemic. We built a modeling tool to aid practicing public health officials with estimating healthcare demand from the pandemic in their jurisdictions and to evaluate the potential impacts of population-wide social-distancing interventions. METHODS: The tool uses a SEIR compartmental model to project the pandemic’s local spread. Users input case counts, healthcare resources, and select intervention strategies to evaluate. Outputs include the number of infections and deaths with and without intervention, and the demand for hospital and critical care beds and ventilators relative to existing capacity. We illustrate the tool using data from three regions of Chile. RESULTS: Our scenarios indicate a surge in COVID-19 patients could overwhelm Chilean hospitals by June, peaking in July or August at 6 to 50 times the current supply of beds and ventilators. A lockdown strategy or combination of case isolation, home quarantine, social distancing of individuals >70 years, and telework interventions may keep treatment demand below capacity. CONCLUSIONS: Aggressive interventions can avert substantial morbidity and mortality from COVID-19. Our tool permits rapid evaluation of locally-applicable policy scenarios and updating of results as new data become available.

positive: COVID-19, Australia: Epidemiology Report 10 (Reporting week to 23:59 AEST 5 April 2020). Confirmed cases in Australia notified up to 5 April 2020: Notifications = 5,805; Deaths = 33. Notifications in Australia remain predominantly among people with recent overseas travel, with some locally-acquired cases being detected. Most locally-acquired cases are able to be linked back to a confirmed case, with a small portion unable to be epidemiologically link. The distribution of overseas-acquired cases to locally acquired cases varies by jurisdiction. Early indications are that reduction in international travel, domestic movement, social distancing measures and public health action are slowing the spread of the disease. Internationally, cases continue to increase, with high rates of increase observed in the European region and the United States of America. The epidemiology differs from country to country depending not only on the disease, but also on differences in case detection, testing and implemented public health measures.

positive: Pandemic influenza in Papua New Guinea: a modelling study comparison with pandemic spread in a developed country OBJECTIVES: The possible occurrence of a highly pathogenic influenza strain is of concern to health authorities worldwide. It is known that during past influenza pandemics developing countries have experienced considerably higher death rates compared with developed countries. Furthermore, many developing countries lack appropriate pandemic preparedness plans. Mathematical modelling studies to guide the development of such plans are largely focused on predicting pandemic influenza spread in developed nations. However, intervention strategies shown by modelling studies to be highly effective for developed countries give limited guidance as to the impact which an influenza pandemic may have on low-income countries given different demographics and resource constraints. To address this, an individual-based model of a Papua New Guinean (PNG) community was created and used to simulate the spread of a novel influenza strain. The results were compared with those obtained from a comparable Australian model. DESIGN: A modelling study. SETTING: The towns of Madang in PNG (population ∼35 000) and Albany (population ∼30 000) in Australia. OUTCOME MEASURES: Daily and cumulative illness attack rates in both models following introduction of a novel influenza strain into a naive population, for an unmitigated scenario and two social distancing intervention scenarios. RESULTS: The unmitigated scenario indicated an approximately 50% higher attack rate in PNG compared with the Australian model. The two social distancing-based interventions strategies were 60–70% less effective in a PNG setting compared with an Australian setting. CONCLUSIONS: This study provides further evidence that an influenza pandemic occurring in a low-income country such as PNG may have a greater impact than one occurring in a developed country, and that PNG-feasible interventions may be substantially less effective. The larger average household size in PNG, the larger proportion of the population under 18 and greater community-wide contact all contribute to this feature.

positive: What does simple power law kinetics tell about our response to coronavirus pandemic? Coronavirus pandemic of 2019-2020 has already affected over a million people and caused over 50,000 deaths worldwide (as on April 3, 2020). Roughly half of the world population has been asked to work from home and practice social distancing as the search for a vaccine continues. Though government interventions such as lockdown and social distancing are theoretically useful, its debatable whether such interventions are effective in flattening the curve, which is ceasing or reducing the growth of infection in control populations. In this article, I present a simple power law model that enables a comparison of countries in time windows of 14 days since first coronavirus related death is reported in that country. It therefore provides means to access the efficacy of above interventions.

positive: School closure and management practices during coronavirus outbreaks including COVID-19: a rapid systematic review In response to the coronavirus disease 2019 (COVID-19) pandemic, 107 countries had implemented national school closures by March 18, 2020. It is unknown whether school measures are effective in coronavirus outbreaks (eg, due to severe acute respiratory syndrome [SARS], Middle East respiratory syndrome, or COVID-19). We undertook a systematic review by searching three electronic databases to identify what is known about the effectiveness of school closures and other school social distancing practices during coronavirus outbreaks. We included 16 of 616 identified articles. School closures were deployed rapidly across mainland China and Hong Kong for COVID-19. However, there are no data on the relative contribution of school closures to transmission control. Data from the SARS outbreak in mainland China, Hong Kong, and Singapore suggest that school closures did not contribute to the control of the epidemic. Modelling studies of SARS produced conflicting results. Recent modelling studies of COVID-19 predict that school closures alone would prevent only 2–4% of deaths, much less than other social distancing interventions. Policy makers need to be aware of the equivocal evidence when considering school closures for COVID-19, and that combinations of social distancing measures should be considered. Other less disruptive social distancing interventions in schools require further consideration if restrictive social distancing policies are implemented for long periods.

positive: COVID-19, Australia: Epidemiology Report 11 (Reporting week to 23:59 AEST 12 April 2020). Confirmed cases in Australia notified up to 12 April 2020: notifications = 6,394; deaths = 46. The reduction in international travel and domestic movement, social distancing measures and public health action have likely slowed the spread of the disease. Notifications in Australia remain predominantly among people with recent overseas travel, with some locally-acquired cases being detected. Most locally-acquired cases are able to be linked back to a confirmed case, with a small portion unable to be epidemiologically linked. The distribution of overseas-acquired cases to locally acquired cases varies by jurisdiction. Internationally, cases continue to increase. The rates of increase have started to slow in several regions, although it is too soon to tell whether this trend will be sustained. The epidemiology differs from country to country depending not only on the disease, but also on differences in case detection, testing and implemented public health measures.

positive: State-by-State prediction of likely COVID-19 scenarios in the United States and assessment of the role of testing and control measures Due to the heterogeneity among the States in the US, predicting COVID-19 trends and quantitatively assessing the effects of government testing capability and control measures need to be done via a State-by-State approach. We develop a comprehensive model for COVID-19 incorporating time delays and population movements. With key parameter values determined by empirical data, the model enables the most likely epidemic scenarios to be predicted for each State, which are indicative of whether testing services and control measures are vigorous enough to contain the disease. We find that government control measures play a more important role than testing in suppressing the epidemic. The vast disparities in the epidemic trends among the States imply the need for long-term placement of control measures to fully contain COVID-19.

positive: Minimising intra-hospital transmission of COVID-19: the role of social distancing

positive: Age profile of susceptibility, mixing, and social distancing shape the dynamics of the novel coronavirus disease 2019 outbreak in China Strict interventions were successful to control the novel coronavirus (COVID-19) outbreak in China. As transmission intensifies in other countries, the interplay between age, contact patterns, social distancing, susceptibility to infection and disease, and COVID-19 dynamics remains unclear. To answer these questions, we analyze contact surveys data for Wuhan and Shanghai before and during the outbreak and contact tracing information from Hunan Province. Daily contacts were reduced 7-9 fold during the COVID-19 social distancing period, with most interactions restricted to the household. Children 0-14 years were 59% (95% CI 7-82%) less susceptible than individuals 65 years and over. A transmission model calibrated against these data indicates that social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. While proactive school closures cannot interrupt transmission on their own, they reduce peak incidence by half and delay the epidemic. These findings can help guide global intervention policies.

positive: Network model and analysis of the spread of Covid-19 with social distancing The first mitigation response to the Covid-19 pandemic was to limit person-to-person interaction as much as possible. This was implemented by the temporary closing of many workplaces and people were required to follow social distancing. Networks are a great way to represent interactions among people and the temporary severing of these interactions. Here, we present a network model of human-human interactions that could be mediators of disease spread. The nodes of this network are individuals and different types of edges denote family cliques, workplace interactions, interactions arising from essential needs, and social interactions. Each individual can be in one of four states: susceptible, infected, immune, and dead. The network and the disease parameters are informed by the existing literature on Covid-19. Using this model, we simulate the spread of an infectious disease in the presence of various mitigation scenarios. For example, lockdown is implemented by deleting edges that denote non-essential interactions. We validate the simulation results with the real data by matching the basic and effective reproduction numbers during different phases of the spread. We also simulate different possibilities of the slow lifting of the lockdown by varying the transmission rate as facilities are slowly opened but people follow prevention measures like wearing masks etc. We make predictions on the probability and intensity of a second wave of infection in each of these scenarios.

positive: Projection of COVID-19 Cases and Deaths in the US as Individual States Re-open May 4,2020 In March and April 2020, control measures enforcing social distancing and restricting individual movement and contact were adopted across the United States in an effort to slow the spread and growth of COVID-19. However, a number of states have now begun to ease these restrictions. Here, we evaluate the effects of loosening stay-at-home orders on COVID-19 incidence and related outcomes. We use a metapopulation model applied at county resolution to simulate the spread and growth of COVID-19 incidence in the United States. We calibrate the model against county-level daily case and death data collected from February 21, 2020 to May 2, 2020, and project the outbreak in 3,142 US counties for 6 weeks into the future. Projections for daily reported cases, daily new infections (both reported and unreported), new and cumulative hospital bed demand, ICU bed and ventilator demand, as well as daily mortality, are generated. We observe a rebound in COVID-19 incidence and deaths beginning in late May, approximately 2 to 4 weeks after states begin to reopen. Importantly, the lag between infection acquisition and case confirmation, coupled with insufficient broader testing and contact tracing, will mask any rebound and exponential growth of the COVID-19 until it is well underway.

positive: A deductive approach to modeling the spread of COVID-19 Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), previously known as 2019-nCoV, is responsible for the atypical pneumonia pandemic designated as Coronavirus Disease 2019 (COVID-19). The confirmed number of cases continues to grow exponentially reaching 492,000 people in 175 countries as of March 25, 2020. 22,169 people (~4.5%) infected with SARS-COV-2 virus have died. We have developed an exponential regression model using the COVID-19 case data (Jan 22 - Mar 22, 2020). Our primary model uses designated Phase 1 countries, who exceed 2500 cases on Mar 22. The model is then applied to Phase 2 countries: those that escaped the initial Phase 1 global expansion of COVID-19. With the exception of stabilizing countries (South Korea, Japan, and Iran) all Phase 1 countries are growing exponentially, as per I2500(t)=120.4 × e0.238t, with a rate, r = 0.238 ± 0.068. Excluding China, the BRICS developing nations and Australia are in Phase 2. Case data from Phase 2 countries are following the model derived from Phase 1 countries. In the absence of measures employed to flatten the curve including social distancing, quarantine, and healthcare expansion, our model projects over 274,000 cases and 12,300 deaths in the US by Mar 31. India can expect 123,000 cases by April 16. By flattening the curve to the growth rate of stabilizing countries (r = 0.044 ± 0.062), the US would prevent 8,500 deaths by Mar 31, and India would prevent 5,500 deaths by April 16.

positive: Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus A pandemic of a novel Coronavirus emerged in December of 2019 (COVID-19), causing devastating public health impact across the world. In the absence of a safe and effective vaccine or antivirals, strategies for con- trolling and mitigating the burden of the pandemic are focused on non-pharmaceutical interventions, such as social-distancing, contact-tracing, quarantine, isolation and the use of face-masks in public. We develop a new mathematical model for assessing the population-level impact of the aforementioned control and mitigation strategies. Rigorous analysis of the model shows that the disease-free equilibrium is locally-asymptotically stable if a certain epidemiological threshold, known as the reproduction number (denoted by Rc), is less than unity. This equilibrium is globally-asymptotically stable, for a special case of the model where quarantined-susceptible individuals do not acquire COVID-19 infection during quarantine, when Rc is less than unity. The epidemiological consequence of this theoretical result is that, the community-wide implementation of control interventions that can bring (and maintain) Rc to a value less than unity will lead to the effective control (or elimination) of COVID-19 in the community. Simulations of the model, using data relevant to COVID-19 transmission dynamics in the US state of New York and the entire US, show that the pandemic burden will peak in mid and late April, respectively. The worst-case scenario projections for cumulative mortality (based on baseline levels of interventions) are 105, 100 for New York state and 164, 000 for the entire US by the end of the pandemic. These numbers dramatically decreased by 80% and 64%, respectively, if adherence to strict social-distancing measures is improved and maintained until the end of May or June. The duration and timing of the relaxation or termination of the strict social-distancing measures are crucially important in determining the future trajectory of the COVID-19 pandemic. This study shows that early termination of the strict social-distancing measures could trigger a devastating second wave with burden similar to those projected before the onset of the strict social-distance measures were implemented. The use of efficacious face-masks (such as surgical masks, with estimated efficacy ≥ 70%) in public could lead to the elimination of the pandemic if at least 70% of the residents of New York state use such masks in public consistently (nationwide, a compliance of at least 80% will be required using such masks). The use of low efficacy masks, such as cloth masks (of estimated efficacy less than 30%), could also lead to significant reduction of COVID-19 burden (albeit, they are not able to lead to elimination). Combining low efficacy masks with improved levels of the other anti-COVID-19 intervention strategies can lead to the elimination of the pandemic. This study emphasizes the important role social-distancing plays in curtailing the burden of COVID-19. Increases in the adherence level of social-distancing protocols result in dramatic reduction of the burden of the pandemic, and the timely implementation of social-distancing measures in numerous states of the US may have averted a catastrophic outcome with respect to the burden of COVID-19. Using face-masks in public (including the low efficacy cloth masks) is very useful in minimizing community transmission and burden of COVID-19, provided their coverage level is high. The masks coverage needed to eliminate COVID-19 decreases if the masks-based intervention is combined with the strict social-distancing strategy.

positive: Impact assessment of non-pharmaceutical interventions against COVID-19 and influenza in Hong Kong: an observational study Background: A range of public health measures have been implemented to delay and reduce local transmission of COVID-19 in Hong Kong, and there have been major changes in behaviours of the general public. We examined the effect of these interventions and behavioral changes on the incidence of COVID-19 as well as on influenza virus infections which may share some aspects of transmission dynamics with COVID-19. Methods: We reviewed policy interventions and measured changes in population behaviours through two telephone surveys, on January 20-23 and February 11-14. We analysed data on laboratory-confirmed COVID-19 cases, influenza surveillance data in outpatients of all ages, and influenza hospitalisations in children. We estimated the daily effective reproduction number (R_t), for COVID-19 and influenza A(H1N1). Findings: COVID-19 transmissibility has remained at or below 1, indicating successful containment to date. Influenza transmission declined substantially after the implementation of social distancing measures and changes in population behaviours in late January, with a 44% (95% confidence interval, CI: 34% to 53%) reduction in transmissibility in the community, and a 33% (95% CI: 24% to 43%) reduction in transmissibility based on paediatric hospitalization rates. In the two surveys we estimated that 74.5% and 97.5% of the general adult population wore masks when going out, and 61.3% and 90.2% avoided going to crowded places, respectively. Implications: Containment measures, social distancing measures and changes in population behaviour have successfully prevented spread of COVID-19. The social distancing measures and behavioural changes led to a substantial reduction in influenza transmission in early February 2020. However, it may be challenging to avoid fatigue and sustain these measures and population behaviours as COVID-19 continues to spread globally. Funding: Health and Medical Research Fund, Hong Kong

positive: Impact of climate and public health interventions on the COVID-19 pandemic: A prospective cohort study. BACKGROUND It is unclear whether seasonal changes, school closures or other public health interventions will result in a slowdown of the current coronavirus disease 2019 (COVID-19) pandemic. We aimed to determine whether epidemic growth is globally associated with climate or public health interventions intended to reduce transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS We performed a prospective cohort study of all 144 geopolitical areas worldwide (375 609 cases) with at least 10 COVID-19 cases and local transmission by Mar. 20, 2020, excluding China, South Korea, Iran and Italy. Using weighted random-effects regression, we determined the association between epidemic growth (expressed as ratios of rate ratios [RRR] comparing cumulative counts of COVID-19 cases on Mar. 27, 2020, with cumulative counts on Mar. 20, 2020) and latitude, temperature, humidity, school closures, restrictions of mass gatherings, and measures of social distancing during an exposure period 14 days previously (Mar. 7 to 13, 2020). RESULTS In univariate analyses, there were few or no associations of epidemic growth with latitude and temperature, but weak negative associations with relative humidity (RRR per 10% 0.91, 95% confidence interval [CI] 0.85-0.96) and absolute humidity (RRR per 5 g/m3 0.92, 95% CI 0.85-0.99). Strong associations were found for restrictions of mass gatherings (RRR 0.65, 95% CI 0.53-0.79), school closures (RRR 0.63, 95% CI 0.52-0.78) and measures of social distancing (RRR 0.62, 95% CI 0.45-0.85). In a multivariable model, there was a strong association with the number of implemented public health interventions (p for trend = 0.001), whereas the association with absolute humidity was no longer significant. INTERPRETATION Epidemic growth of COVID-19 was not associated with latitude and temperature, but may be associated weakly with relative or absolute humidity. Conversely, public health interventions were strongly associated with reduced epidemic growth.

positive: The effect of human mobility and control measures on the COVID-19 epidemic in China The ongoing COVID-19 outbreak has expanded rapidly throughout China. Major behavioral, clinical, and state interventions are underway currently to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, have affected COVID-19 spread in China. We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was well explained by human mobility data. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases are still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China have substantially mitigated the spread of COVID-19.

positive: A model for COVID-19 with isolation, quarantine and testing as control measures In this article we propose a compartmental model for the dynamics of Coronavirus Disease 2019 (COVID-19). We take into account the presence of asymptomatic infections and the main policies that have been adopted so far to contain the epidemic: isolation (or social distancing) of a portion of the population, quarantine for confirmed cases and testing. We model isolation by separating the population in two groups: one composed by key-workers that keep working during the pandemic and have a usual contact rate, and a second group consisting of people that are enforced/recommended to stay at home. We refer to quarantine as strict isolation, and it is applied to confirmed infected cases. In the proposed model, the proportion of people in isolation, the level of contact reduction and the testing rate are control parameters that can vary in time, representing policies that evolve in different stages. We obtain an explicit expression for the basic reproduction number $\mathcal{R}_0$ in terms of the parameters of the disease and of the control policies. In this way we can quantify the effect that isolation and testing have in the evolution of the epidemic. We present a series of simulations to illustrate different realistic scenarios. From the expression of $\mathcal{R}_0$ and the simulations we conclude that isolation (social distancing) and testing among asymptomatic cases are fundamental actions to control the epidemic, {and the stricter these measures are and the sooner they are implemented,} the more lives can be saved. Additionally, we show that people that remain in isolation significantly reduce their probability of contagion, so risk groups should be recommended to maintain a low contact rate during the course of the epidemic.

positive: The December 2019 New Corona Virus (SARS-CoV-2) Outbreak: A Behavioral Infectious Disease Policy Model It is critical to understand the impact of distinct policy interventions to the ongoing December 2019 coronavirus (SARS-CoV-2) pandemic. We develop a flexible behavioral, dynamic, and sectorial epidemic policy model comprising both endogenous virus transmission and public health and citizen responses. Applicable to the full epidemic cycle including resurgence, the model allows exploring the multivariate impact of distinct policy interventions, including general and targeted testing and social contact reduction efforts. Calibrating the model to the early SARS-CoV-2 outbreak at the level of continents, we demonstrate how early, rapid, and extensive buildup of testing and social contact reduction efforts interplay to suppress the outbreak. Next, applying the model within hypothetical contexts we demonstrate how: i) sociodemographic variation in vulnerability to the virus affects overall reported and actual outbreak patterns; ii) feasible timing of deconfinement depends on earlier responses to the outbreak; and, iii) targeted approaches help suppress resurgent outbreaks and their various impacts. Finally, given the importance of broad support of outbreak control efforts, across public health experts, policymakers, volunteers, media, and citizens, we make the model also accessible in the form of a free web-based management flight simulator.

positive: Which Measures are Effective in Containing COVID-19?Empirical Research Based on Prevention and Control Cases in China Various epidemic prevention and control measures aimed at reducing person-to-person contact has paid a certain cost while controlling the epidemic. So accurate evaluation of these measures helps to maximize the effectiveness of prevention and control while minimizing social costs. In this paper, we develop the model in Dirk Brockmann and Dirk Helbing (2013) to theoretically explain the impact mechanism of traffic control and social distancing measures on the spread of the epidemic, and empirically tests the effect of the two measures in China at the present stage using econometric approach. We found that both traffic control and social distancing measures have played a very good role in controlling the development of the epidemic. Nationally, social distancing measures are better than traffic control measures; the two measures are complementary and their combined action will play a better epidemic prevention effect; Traffic control and social distancing do not work everywhere. Traffic control only works in cities with higher GDP per capita and population size, while fails in cities with lower GDP per capita and population size. In cities with lower population size, social distancing becomes inoperative; the rapid and accurate transmission of information, a higher protection awareness of the public, and a stronger confidence of residents in epidemic prevention can promote the realization of the measure effects. The findings above verify the effectiveness and correctness of the measures implemented in China at present, at the same time, we propose that it is necessary to fully consider the respective characteristics of the two measures, cooperating and complementing each other; what's more, measures should be formulated according to the city's own situation, achieving precise epidemic prevention; Finally, we should increase the transparency of information, improve protection awareness of the public, guide emotions of the public in a proper way, enhancing public confidence.

positive: Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy In Italy, 128,948 confirmed cases and 15,887 deaths of people who tested positive for SARS-CoV-2 were registered as of 5 April 2020. Ending the global SARS-CoV-2 pandemic requires implementation of multiple population-wide strategies, including social distancing, testing and contact tracing. We propose a new model that predicts the course of the epidemic to help plan an effective control strategy. The model considers eight stages of infection: susceptible (S), infected (I), diagnosed (D), ailing (A), recognized (R), threatened (T), healed (H) and extinct (E), collectively termed SIDARTHE. Our SIDARTHE model discriminates between infected individuals depending on whether they have been diagnosed and on the severity of their symptoms. The distinction between diagnosed and non-diagnosed individuals is important because the former are typically isolated and hence less likely to spread the infection. This delineation also helps to explain misperceptions of the case fatality rate and of the epidemic spread. We compare simulation results with real data on the COVID-19 epidemic in Italy, and we model possible scenarios of implementation of countermeasures. Our results demonstrate that restrictive social-distancing measures will need to be combined with widespread testing and contact tracing to end the ongoing COVID-19 pandemic.

positive: The association between age, COVID-19 symptoms, and social distancing behavior in the United States BACKGROUND: Public health authorities recommend that people practice social distancing, especially if they have symptoms of coronavirus disease (COVID-19), or are older and more at risk of serious illness if they become infected. We test the hypothesis that these groups are following these recommendations and are more likely to undertake social distancing. METHODS: We conducted an open online survey of 4,676 U.S. adults aged 18 and older between April 4 and April 7, 2020. We model the effects of age and common COVID-19 symptoms in the last two weeks on going out of the home for non-healthcare reasons the day before taking the survey, using a logistic model and the number of close contacts (within 6 feet) that respondents had with non-household members, using a Poisson count model. Our models control for several covariates, including other flu-like symptoms, sex, education, income, whether the respondent worked in February, household size, population density in the respondent’s ZIP code, state fixed effects, and the day of completion of the survey. We also weight our analyses to make the sample representative of the U.S. adult population. FINDINGS: About 52 percent of the adult United States population went out of their home the previous day. On average, adults had close contact with 1.9 non-household members. We find that having at least one COVID-19 symptom (fever, dry cough, or shortness of breath) increased the likelihood of going out the previous day and having additional close contacts with non-household members; however, the estimates were not statistically significant. When disaggregating our analysis by COVID-19 symptoms, we find no strong evidence of greater social distancing by people with a fever or cough in the last two weeks, but we do find that those who experienced shortness of breath have fewer close contacts, with an incidence rate ratio (IRR) of 0.49 (95% CI: 0.30–0.78). Having other flu-like symptoms reduces the odds of going out by 0.32 (95% CI: 0.18–0.60) and the incidence rate of having close contacts by 42 percent (IRR = 0.58; 95% CI: 0.38–0.88). We find that older people are just as likely to leave their homes as younger people, but people over the age of 50 had less than half the predicted number of close contacts than those who were younger than 30. Our approach has the limitation that the survey sample is self-selected. Our findings may therefore be subject to selection bias that is not adequately controlled for by weighting. In addition, the possibility exists of confounding of the results due to omitted variable bias. CONCLUSIONS: We provide evidence that older people are having significantly fewer close contacts than younger people, which is in line with the public health authorities’ recommendations. We also find that people experiencing shortness of breath are practicing more intense social distancing. However, we find that those with two other common COVID-19 symptoms, fever and dry cough, are not engaging in greater social distancing, suggesting that increased targeting on relevant symptoms, and messaging, may be required.

positive: Transmission potential of COVID-19 in South Korea Since the first identified individual of 2019 novel coronavirus (COVID-19) infection on Jan 20, 2020 in South Korea, the number of confirmed cases rapidly increased. As of Feb 26, 2020, 1,261 cases of COVID-19 including 12 deaths were confirmed in South Korea. Using the incidence data of COVID-19, we estimate the reproduction number at 1.5 (95% CI: 1.4-1.6), which indicates sustained transmission and support the implementation of social distancing measures to rapidly control the outbreak.

positive: Lessons drawn from China and South Korea for managing COVID-19 epidemic: insights from a comparative modeling study We conducted a comparative study of COVID-19 epidemic in three different settings: mainland China, the Guangdong province of China and South Korea, by formulating two disease transmission dynamics models incorporating epidemic characteristics and setting-specific interventions, and fitting the models to multi-source data to identify initial and effective reproduction numbers and evaluate effectiveness of interventions. We estimated the initial basic reproduction number for South Korea, the Guangdong province and mainland China as 2.6 (95% confidence interval (CI): (2.5, 2.7)), 3.0 (95%CI: (2.6, 3.3)) and 3.8 (95%CI: (3.5,4.2)), respectively, given a serial interval with mean of 5 days with standard deviation of 3 days. We found that the effective reproduction number for the Guangdong province and mainland China has fallen below the threshold 1 since February 8th and 18th respectively, while the effective reproduction number for South Korea remains high, suggesting that the interventions implemented need to be enhanced in order to halt further infections. We also project the epidemic trend in South Korea under different scenarios where a portion or the entirety of the integrated package of interventions in China is used. We show that a coherent and integrated approach with stringent public health interventions is the key to the success of containing the epidemic in China and specially its provinces outside its epicenter, and we show that this approach can also be effective to mitigate the burden of the COVID-19 epidemic in South Korea. The experience of outbreak control in mainland China should be a guiding reference for the rest of the world including South Korea.

positive: Effect of social distancing on COVID-19 incidence and mortality in the US Social distancing policies were implemented in most US states as a containment strategy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The effectiveness of these policy interventions on morbidity and mortality remains unknown. Our analysis examined the associations between statewide policies and objective measures of social distancing, and objective social distancing and COVID-19 incidence and mortality. We used nationwide, de-identified smartphone GPS data to estimate county-level social distancing. COVID-19 incidence and mortality data were from the Johns Hopkins Coronavirus Resource Center. Generalized linear mixed models were used to estimate incidence rate ratios (IRRs) and 95% confidence intervals (CIs) for the association between objective social distancing and COVID-19 incidence and mortality. Stay-at-home orders were associated with a 35% increase in social distancing. Higher social distancing was associated with a 29% reduction in COVID-19 incidence (adjusted IRR 0.71; 95% CI 0.57–0.87) and a 35% reduction in COVID-19 mortality (adjusted IRR 0.65; 95% CI 0.55–0.76). These findings provide evidence to inform ongoing national discussions on the effectiveness of these public health measures and the potential implications of returning to normal social activity.

positive: The timing of one-shot interventions for epidemic control The apparent early success in China's large-scale intervention to control the COVID-19 epidemic has led to interest in whether other countries can replicate it as well as concerns about a resurgence of the epidemic if or when China relaxes the interventions. In this paper we look at the impact of a single short-term intervention on an epidemic. We see that if an intervention cannot be sustained long-term, it has the greatest impact if it is imposed once infection levels have become large enough that there is an appreciable number of infections present. For minimising the total number infected it should start close to the peak so that there is no rebound once the intervention is stopped, while to minimise the peak prevalence, it should start earlier, allowing two peaks of comparable size rather than one very large peak. In populations with distinct subgroups, synchronized interventions are less effective than targeting the interventions in each sub-population separately. We do not attempt to clearly determine what makes an intervention sustainable or not. We believe that is a policy question. If an intervention is sustainable, it should be kept in place. Our intent is to offer insight into how best to time an intervention whose impact on society is too great to maintain.

positive: Scientific and ethical basis for social-distancing interventions against COVID-19

positive: Augmenting contact matrices with time-use data for fine-grained intervention modelling of disease dynamics: A modelling analysis Background: Social distancing is an important public health intervention to reduce or interrupt the sustained community transmission of emerging infectious pathogens, such as SARS-CoV-2 during the coronavirus disease 2019 (COVID-19) pandemic. We aimed to explore the impact on the epidemic curve of fewer contacts when individuals reduce the time they spend on selected daily activities. Methods: We combined the large-scale empirical data of a social contact survey and a time-use survey to estimate contact matrices by age group (0-15, 16-24, 25-44, 45-64, 65+) and daily activity (work, schooling, transportation, and four leisure activities: social visits, bar/cafe/restaurant visits, park visits, and non-essential shopping). We assumed that reductions in time are proportional to reductions in contacts. The derived matrices were then applied in an age-structured dynamic-transmission model of COVID-19 to explore the effects. Findings: The relative reductions in the derived contact matrices were highest when closing schools (in ages 0-14 years), workplaces (15-64 years), and stopping social visits (65+ years). For COVID-19, the closure of workplaces, schools, and stopping social visits had the largest impact on reducing the epidemic curve and delaying its peak, while the predicted impact of fewer contacts in parks, bars/cafes/restaurants, and non-essential shopping were minimal. Interpretation: We successfully augmented contact matrices with time-use data to predict the highest impact of social distancing measures from reduced contacts when spending less time at work, school, and on social visits. Although the predicted impact from other leisure activities with potential for close physical contact were minimal, changes in mixing patterns and time-use immediately after re-allowing social activities may pose increased short-term transmission risks, especially in potentially crowded environments indoors.

positive: DOUBLE POWER LAW FOR COVID-19: PREDICTION OF NEW CASES AND DEATH RATES IN ITALY AND SPAIN The novel corona virus SARS-CoV-2 appeared at the end of 2019, spreading rapidly and causing a severe respiratory syndrome (COVID-19) with high mortality (2-5%). Until a vaccine or therapy is found, the most effective method of prophylaxis has been to minimize transmission via rigorous social distancing and seclusion of all but essential workers. Such measures, implemented at different times and to varying degrees worldwide, have reduced the rate of transmission compared with early phases of the pandemic, resulting in flattening of the curve followed by a gradual reduction in mortality after >6 weeks of rigorous social distancing measures. The cost of rigorous social distancing has been seen in radically reduced economic activity, job losses, disruption of schooling and social institutions. A key question facing policy makers and individuals is when to resume normal economic and social activity in the face of persistent community transmission of SARS-CoV-2 . To help address this question, we have developed a model that accurately describes the entire transmission and mortality curves in Italy and Spain, two hard-hit countries that have maintained severe social distancing measures for over 2 months. Our model quantitatively describes the rapid rise and slow decay of new cases and deaths observed under stringent social distancing (the long tail effect). We predict that even when social distancing is rigorously maintained, the number of COVID-19 deaths after peak mortality may be 2-3 times larger than the total number of deaths up to the peak. Our model has important policy implications for countries currently debating how to ease social distancing measures.

positive: On the benefits of flattening the curve: A perspective() The many variations on a graphic illustrating the impact of non-pharmaceutical measures to mitigate pandemic influenza that have appeared in recent news reports about COVID-19 suggest a need to better explain the mechanism by which social distancing reduces the spread of infectious diseases. And some reports understate one benefit of reducing the frequency or proximity of interpersonal encounters, a reduction in the total number of infections. In hopes that understanding will increase compliance, we describe how social distancing a) reduces the peak incidence of infections, b) delays the occurrence of this peak, and c) reduces the total number of infections during epidemics. In view of the extraordinary efforts underway to identify existing medications that are active against SARS-CoV-2 and to develop new antiviral drugs, vaccines and antibody therapies, any of which may have community-level effects, we also describe how pharmaceutical interventions affect transmission.

positive: COVID-19 social distancing in the Kingdom of Saudi Arabia: Bold measures in the face of political, economic, social and religious challenges Social distancing at its various levels has been a key measure to mitigate the transmission of COVID-19. The implementation of strict measures for social distancing is challenging, including in the Kingdom of Saudi Arabia (KSA) due to its level of urbanization, its social and religious norms and its annual hosting of high visibility international religious mass gatherings. KSA started introducing decisive social distancing measures early before the first case of COVID-19 was confirmed in the Kingdom. These ranged from suspension or cancelations of religious, entertainment and sporting mass gatherings and events such as the Umrah, temporary closure of educational establishments and mosques and postponing all non-essential gatherings, to imposing a curfew. These measures were taken in spite of their socio-economic, political and religious challenges in the interest of public and global health. The effect of these actions on the epidemic curve of the Kingdom and on the global fight against COVID-19 remains to be seen. However, given the current COVID-19 situation, further bold and probably unpopular measures are likely to be introduced in the future.

negative: Analysis of COVID-19 transmission: Low risk of presymptomatic spread?

negative: Senior Medical Students in the COVID‐19 Response: An Opportunity to Be Proactive On March 13th, the United States (US) declared the novel coronavirus (COVID-19) pandemic a national emergency. By March 18th , according to the Centers for Disease Control and Prevention, COVID-19 had spread to all 50 US states, with 7,038 cases and 97 deaths.1 The trajectory of cases mirrors that of Italy, where doctors are forced to consider who is more deserving of a ventilator.2 In response, social distancing measures are being promoted across the US in the hopes of slowing the growth in new cases, i.e. "flattening the curve." This could maintain the demand for acute care within the healthcare system's capacity to treat.3 Travel has been curtailed, conferences and concerts cancelled, and schools and universities have moved students off campus and classes online. Medical schools are following suit, with added motivators. In canceling classes and rotations, medical schools hope to: promote social distancing, limit the risk of students contracting the virus, limit the number of healthcare workers who might spread the virus to unaffected patients, minimize the teaching burden on frontline providers, and preserve personal protective equipment (PPE) for essential personnel. These are logical reasons for removing students from hospitals. But, despite our best efforts, there may come a point in the US when, as is set to happen in Italy, medical demand outpaces medical capacity.2 If the same happens here, is there a plan in place for incorporating senior medical students into emergency relief efforts?

negative: Full spectrum of COVID-19 severity still being depicted

negative: Predicting Whom to Test is More Important Than More Tests - Modeling the Impact of Testing on the Spread of COVID-19 Virus By True Positive Rate Estimation I estimate plausible true positive (TP) rates for the number of COVID-19 tests per day, most relevant when the number of test is on the same order of magnitude as number of infected persons. I then modify a standard SEIR model to model current growth patterns and detection rates in South Korea and New York state. Although reducing transmission rates have the largest impact, increasing TP rates by ~10% in New York can have an impact equal to adding tens of thousands of new tests per day. Increasing both TP rates and tests per day together can have significant impacts and likely be more easily sustained than social distancing restrictions. Systematic and standardized data collection, even beyond contact tracking, should be ongoing and quickly made available for research teams to maximize the efficacy of testing.

negative: Cultural orientation, power, belief in conspiracy theories, and intentions to reduce the spread of COVID-19 The current study investigated cultural and psychological factors associated with intentions to reduce the spread of COVID-19. Participants (n = 704) completed measures of individualism-collectivism, belief in conspiracy theories about COVID-19, feelings of powerlessness, and intentions to engage in behaviours that reduce the spread of COVID-19. Results revealed that vertical individualism negatively predicted intentions to engage in social distancing, directly and indirectly through both belief in COVID-19 conspiracy theories and feelings of powerlessness. Vertical collectivism positively predicted social distancing intentions directly. Horizontal collectivism positively predicted social distancing intentions indirectly through feelings of powerlessness. Finally, horizontal collectivism positively predicted hygiene-related intentions both directly and indirectly through lower feelings of powerlessness. These findings suggest that promoting collectivism may be a way to increase engagement with efforts to reduce the spread of COVID-19. They also highlight the importance of examining the interplay between culture and both personal feelings (powerlessness) and information consumption (conspiracy theories) during times of crisis.

negative: Global trends in research related to social media in psychology: mapping and bibliometric analysis BACKGROUND: Social media, defined as interactive Web applications, have been on the rise globally, particularly among adults. The objective of this study was to investigate the trend of the literature related to the most used social network worldwide (i.e. Facebook, Twitter, LinkedIn, Snapchat, and Instagram) in the field of psychology. Specifically, this study will assess the growth in publications, citation analysis, international collaboration, author productivity, emerging topics and the mapping of frequent terms in publications pertaining to social media in the field of psychology. METHODS: Publications related to social media in the field of psychology published between 2004 and 2014 were obtained from the Web of Science. The records extracted were analysed for bibliometric characteristics such as the growth in publications, citation analysis, international collaboration, emerging topics and the mapping of frequent terms in publications pertaining to social media in the field of psychology. VOSviewer v.1.6.5 was used to construct scientific maps. RESULTS: Overall, 959 publications were retrieved during the period between 2004 and 2015. The number of research publications in social media in the field of psychology showed a steady upward growth. Publications from the USA accounted for 57.14% of the total publications and the highest h-index (48).The most common document type was research articles (873; 91.03%). Over 99.06% of the publications were published in English. Computers in Human Behavior was the most prolific journal. The University of Wisconsin–Madison ranked first in terms of the total publications (n = 39). A visualisation analysis showed that personality psychology, experimental psychology, psychological risk factors, and developmental psychology were continual concerns of the research. CONCLUSIONS: This is the first study reporting the global trends in the research related to social media in the psychology field. Based on the raw data from the Web of Science, publication characteristics such as quality and quantity were assessed using bibliometric techniques over 12 years. The USA and its institutions play a dominant role in this topic. The most preferred topics related to social media in psychology are personality psychology, experimental psychology, psychological risk factors, and developmental psychology.

negative: Protecting the psychological health of children through effective communication about COVID-19

negative: 'Distancers' and 'non-distancers'? The potential social psychological impact of moralizing COVID-19 mitigating practices on sustained behaviour change COVID-19 mitigating practices such as 'hand-washing', 'social distancing', or 'social isolating' are constructed as 'moral imperatives', required to avert harm to oneself and others. Adherence to COVID-19 mitigating practices is presently high among the general public, and stringent lockdown measures supported by legal and policy intervention have facilitated this. In the coming months, however, as rules are being relaxed and individuals become less strict, and thus, the ambiguity in policy increases, the maintenance of recommended social distancing norms will rely on more informal social interactional processes. We argue that the moralization of these practices, twinned with relaxations of policy, may likely cause interactional tension between those individuals who do vs. those who do not uphold social distancing in the coming months: that is, derogation of those who adhere strictly to COVID-19 mitigating practices and group polarization between 'distancers' and 'non-distancers'. In this paper, we explore how and why these processes might come to pass, their impact on an overall societal response to COVID-19, and the need to factor such processes into decisions regarding how to lift restrictions.

negative: The Zincins: Collagen Fiber Processing and Degradation This chapter discusses the zinc-containing metalloendoproteinases. These enzymes remodel the stroma during development and around tissues that have been injured or stressed. Section 1 describes the three major classes of metalloproteases, their metal ion cofactors, their functions in biology, and the metzincin catalytic mechanism in procollagen and stromal protein processing. Section 2 describes the astacin and adamalysin metzincin subclasses and how they process procollagen to tropocollagen. Section 3 describes the matrilysin metzincin subclass and their roles in collagen and stromal tissue degradation and in enamel synthesis.

negative: A new factor influencing pathogen detection by molecular assay in children with both mild and severe hand, foot, and mouth disease Abstract This study aimed to find novel information concerning pathogen detection and some probable coinfection factors in hand, foot, and mouth disease (HFMD). In this study, 1104 clinically diagnosed HFMD patients were included. Enterovirus 71 (EV71), coxsackievirus A16 (CA16), and 14 different respiratory pathogens were examined from nasopharyngeal swabs using polymerase chain reaction (PCR) or reverse transcriptase PCR (RT-PCR). To evaluate the immune activation in HFMD patients, 8 cytokines and IgM antibodies to EV71 and CA16 from mild and severe patients were detected. Our results indicated that the severity of HFMD may affect the pathogen detection. The lower positive rates of enterovirus and respiratory viruses in severe HFMD cases by RT-PCR were probably related to stronger immune response. Therefore, immunological tests such as ELISA are essential supplements to PCR or RT-PCR in order to increase pathogen diagnosis in HFMD, especially in severe cases.

negative: The impact of the Covid-19 pandemic in the precipitation of intimate partner violence Intimate Partner Violence (IPV) is a global pandemic and many have been victims of it long before Covid-19. International organizations have documented an increase in IPV reports during the current pandemic, raising awareness of the potential causes for such an increase. Reflecting on risk factors associated with IPV, and the underlying need of the perpetrators to exert control over the victims, it becomes increasingly important to understand how the current policies of social distancing, self-isolation, and lockdown can precipitate episodes of IPV. Furthermore, access to specialized services and health care can be compromised, and health care professionals face new challenges and demands imposed by the pandemic while managing IPV cases. This article begins by examining the main risk factors more commonly associated with IPV in the literature. It proceeds by reflecting on how these risk factors may be exacerbated during the Covid-19 pandemic, which can explain the increased number of reports. Finally, it emphasizes the new challenges faced by health care professionals, while assisting IPV victims during the pandemic and provides possible recommendations on actions to implement during and beyond the Covid-19 pandemic to prevent such cases.

negative: Intimate partner violence crisis in the COVID-19 pandemic: how can radiologists make a difference? • The COVID-19 crisis resulted in a variety of physical and mental health issues beyond the viral infection itself, as indicated by an increase in domestic violence. • Radiologists should be aware of typical intimate partner violence (IPV) injury patterns, actively ask potential IPV victims about the cause of injury, and be familiar with support systems for IPV victims of their institutions. • Emergency and radiology departments should review their protocols for identifying and supporting IPV victims, and train their staff to work together to implement these measures during and beyond the COVID-19 crisis.

negative: An emerging cyberinfrastructure for biodefense pathogen and pathogen–host data The NIAID-funded Biodefense Proteomics Resource Center (RC) provides storage, dissemination, visualization and analysis capabilities for the experimental data deposited by seven Proteomics Research Centers (PRCs). The data and its publication is to support researchers working to discover candidates for the next generation of vaccines, therapeutics and diagnostics against NIAID's Category A, B and C priority pathogens. The data includes transcriptional profiles, protein profiles, protein structural data and host–pathogen protein interactions, in the context of the pathogen life cycle in vivo and in vitro. The database has stored and supported host or pathogen data derived from Bacillus, Brucella, Cryptosporidium, Salmonella, SARS, Toxoplasma, Vibrio and Yersinia, human tissue libraries, and mouse macrophages. These publicly available data cover diverse data types such as mass spectrometry, yeast two-hybrid (Y2H), gene expression profiles, X-ray and NMR determined protein structures and protein expression clones. The growing database covers over 23 000 unique genes/proteins from different experiments and organisms. All of the genes/proteins are annotated and integrated across experiments using UniProt Knowledgebase (UniProtKB) accession numbers. The web-interface for the database enables searching, querying and downloading at the level of experiment, group and individual gene(s)/protein(s) via UniProtKB accession numbers or protein function keywords. The system is accessible at http://www.proteomicsresource.org/.

negative: Study of knowledge, attitude, anxiety & perceived mental healthcare need in Indian population during COVID-19 pandemic Abstract Novel Corona Virus Disease (COVID-19) originating from China has rapidly crossed borders, infecting people throughout the whole world. This phenomenon has led to a massive public reaction; the media has been reporting continuously across borders to keep all informed about the pandemic situation. All these things are creating a lot of concern for people leading to heightened levels of anxiety. Pandemics can lead to heightened levels of stress; Anxiety is a common response to any stressful situation. This study attempted to assess the knowledge, attitude, anxiety experience, and perceived mental healthcare need among adult Indian population during the COVID-19 pandemic. An online survey was conducted using a semi-structured questionnaire using a non-probability snowball sampling technique. A total of 662 responses were received. The responders had a moderate level of knowledge about the COVID-19 infection and adequate knowledge about its preventive aspects. The attitude towards COVID-19 showed peoples' willingness to follow government guidelines on quarantine and social distancing. The anxiety levels identified in the study were high. More than 80 % of the people were preoccupied with the thoughts of COVID-19 and 72 % reported the need to use gloves, and sanitizers. In this study, sleep difficulties, paranoia about acquiring COVID-19 infection and distress related social media were reported in 12.5 %, 37.8 %, and 36.4 % participants respectively. The perceived mental healthcare need was seen in more than 80 % of participants. There is a need to intensify the awareness and address the mental health issues of people during this COVID-19 pandemic.

negative: Genetic diversity and evolution of SARS-CoV-2 Abstract COVID-19 is a viral respiratory illness caused by a new coronavirus called SARS-CoV-2. The World Health Organization declared the SARS-CoV-2 outbreak a global public health emergency. We performed genetic analyses of eighty-six complete or near-complete genomes of SARS-CoV-2 and revealed many mutations and deletions on coding and non-coding regions. These observations provided evidence of the genetic diversity and rapid evolution of this novel coronavirus.

negative: Exploring the Effect of 2019-nCoV Containment Policies on Crime: The Case of Los Angeles The global spread of 2019-nCoV, a new virus belonging to the coronavirus family, forced national and local governments to apply different sets of measures aimed at containing its outbreak. Los Angeles has been one of the first cities in the United States to declare the state of emergency on March 4th, progressively issuing stronger policies involving--among the others--social distancing, the prohibition of crowded private and public gatherings and closure of leisure premises. These interventions highly disrupt and modify daily activities and habits, urban mobility and micro-level interactions between citizens. One of the many social phenomena that could be influenced by such measures is crime. Exploiting public data on crime in Los Angeles, and relying on routine activity and pattern theories of crime, this work investigates whether and how new coronavirus containment policies have an impact on crime trends in a metropolis using Bayesian structural time-series (BSTS) models. The article specifically focuses on nine urban crime categories, daily monitored from January 1st 2017 to March 28th 2020. The analyses have been updated bi-weekly (up to March 16\ts{th} and up to March 28\ts{th} 2020) to dynamically assess the short-term effects of mild and hard interventions to shed light on how crime adapts to such structural modification of the environment. The results show that overall crime in Las Angeles is significantly decreasing, as well as robbery, shoplifting, theft and battery. No significant effect has been found for stolen vehicle, burglary, assault with deadly weapon, intimate partner violence and homicide. In the last section of this article, policy implications are also discussed.

negative: Association of national Bacille Calmette-Guerin vaccination policy with COVID-19 epidemiology: an ecological study in 78 countries A possible association between national Bacille Calmette-Guerin (BCG) vaccination policy and lower COVID-19 incidence has been suggested in some preprint papers. Using publicly accessible databases, I explored associations of national BCG vaccination policy with COVID-19 epidemiology in 78 countries. Data collection was conducted from April 25 to May 5, 2020. I compared countries that have a current universal BCG vaccination policy (BCG countries), with countries that currently lack such a policy (non-BCG countries). The mixed effect model revealed national BCG policy decreases in the country-specific risk of death by COVID-19, correspond to odds ratio of 0.446 (95% confidence intervals 0.323 - 0.614, P =1x10-5). In BCG countries, the case increase rate was attenuated marginally by 25.4% (95% CI 3.0 to 42.7, P=0.029) as compared with those of the non-BCG countries. Although the protective mechanism of BCG vaccination against COVID-19 remains unknown, further laboratory and clinical research should be warranted.

negative: The Vascular Surgery Covid-19 Collaborative (VASCC)

negative: The consequences of the COVID-19 pandemic on mental health and implications for clinical practice

negative: Impact of Nutrition and Diet on COVID-19 Infection and Implications for Kidney Health and Kidney Disease Management

negative: COVID-19, Australia: Epidemiology Report 15 (Reporting week to 23:59 AEST 10 May 2020). Confirmed cases in Australia notified up to 10 May 2020: notifications = 6,971; deaths = 98. The incidence of new cases of COVID-19 has reduced dramatically since a peak in mid-March. The reduction in international travel, social distancing measures and public health action have likely been effective in slowing the spread of the disease, in the Australian community. Cases of COVID-19 continue to be notified by jurisdictions, albeit at a slowed rate. Testing rates over the past week have increased markedly, with a very low proportion of people testing positive. These low rates of detection are indicative of low levels of COVID-19 transmission. It is important that testing rates and community adherence to public health measures remain high to support the continued suppression of the virus, particularly in vulnerable high-risk groups and settings. In the past reporting week new cases in Australia are mostly considered to be locally acquired, consistent with the drop in international travel. Most locally-acquired cases can be linked back to a known case or cluster. Although the proportion of locally-acquired cases has increased, the overall rate of cases, regardless of place of acquisition, continues to decrease. The crude case fatality rate in Australia remains low (1.4%), compared with the WHO reported global rate (6.9%). The low case fatality rate is likely reflective of high case detection and high quality of health care services in Australia. Deaths from COVID-19 in Australia have occurred predominantly among the elderly and those with comorbidities, with no deaths occurring in those under 40 years. The highest rate of COVID-19 continues to be among people aged 60-79 years, with a third of these cases associated with several outbreaks linked to cruise ships. The lowest rate of disease is in young children, a pattern reflected in international reports. Internationally, cases continue to increase, with some areas such as Brazil and India showing a dramatic rise in reported cases. Although some low-income countries have currently reported few cases, it is possible that this is due to limited diagnostic and public health capacity, and may not be reflective of disease occurrence.

negative: COVID-19: What Should Interventional Radiologists Know and What Can They Do? The outbreak of coronavirus disease 2019 (COVID-19) in late December 2019 in Wuhan, China, has been characterized as a “pandemic” by the World Health Organization and has resulted in 81,603 confirmed cases in China, among the 334,981 cases confirmed in 189 countries as of 09:00 am, March 24, 2020 (China central standard time). During the past 3 months, hundreds of thousands of Chinese health care workers, including interventional radiologists (IRs), have been fighting this battle against the horrifying COVID-19 disease. As IRs, what should we know and what can we do when facing this challenge? This paper shares the experience we have gone through.

negative: Economic impact of government interventions during the COVID-19 pandemic: International evidence from financial markets The outbreak of COVID-19 pandemic came as a rare, unprecedented event and governments around the globe scrambled with emergency actions including social distancing measures, public awareness programs, testing and quarantining policies, and income support packages. In this paper, we examine the expected economic impact of government actions by analyzing the effect of such actions on stock market returns. Using daily data from January 22 to April 17, 2020 from 77 countries, we find announcements of government social distancing measures have a direct negative effect on stock market returns due to their adverse effect on economic activity, while an indirect positive effect through the reduction in COVID-19 confirmed cases. Government announcements regarding public awareness programs, testing and quarantining policies, and income support packages largely result in positive market returns. Our findings have important policy implications, primarily by showing that government social distancing measures have both positive and negative economic impact.

negative: A review of the 2019 Novel Coronavirus (COVID-19) based on current evidence Abstract The pneumonia caused by novel coronavirus (SARS-CoV-2) in Wuhan, China in December 2019 is a highly contagious disease. The World Health Organization (WHO) has declared the ongoing outbreak as a global public health emergency. Currently, the research on novel coronavirus is still in the primary stage. Based on the current published evidence, we systematically summarizes the epidemiology, clinical characteristics, diagnosis, treatment and prevention of knowledge surrounding COVID-19. This review in the hope of helping the public effectively recognize and deal with the 2019 novel coronavirus (SARS-CoV-2), and providing a reference for future studies.

negative: Does Eating Chicken Feet With Pickled Peppers Cause Avian Influenza? Observational Case Study on Chinese Social Media During the Avian Influenza A (H7N9) Outbreak BACKGROUND: A hot topic on the relationship between a popular avian-origin food and avian influenza occurred on social media during the outbreak of the emerging avian influenza A (H7N9). The misinformation generated from this topic had caused great confusion and public concern. OBJECTIVE: Our goals were to analyze the trend and contents of the relevant posts during the outbreak. We also aimed to understand the characteristics of the misinformation and to provide suggestions to reduce public misconception on social media during the emerging disease outbreak. METHODS: The original microblog posts were collected from China’s Sina Weibo and Tencent Weibo using a combination of keywords between April 1, 2013 and June 2, 2013. We analyzed the weekly and daily trend of the relevant posts. Content analyses were applied to categorize the posts into 4 types with unified sorting criteria. The posts’ characteristics and geographic locations were also analyzed in each category. We conducted further analysis on the top 5 most popular misleading posts. RESULTS: A total of 1680 original microblog posts on the topic were retrieved and 341 (20.30%) of these posts were categorized as misleading messages. The number of relevant posts had not increased much during the first 2 weeks but rose to a high level in the next 2 weeks after the sudden increase in number of reported cases at the beginning of week 3. The posts under “misleading messages” occurred and increased from the beginning of week 3, but their daily posting number decreased when the daily number of posts under “refuting messages” outnumbered them. The microbloggers of the misleading posts had the lowest mean rank of followers and previous posts, but their posts had a highest mean rank of posts. The proportion of “misleading messages” in places with no reported cases was significantly higher than that in the epidemic areas (23.6% vs 13.8%). The popular misleading posts appeared to be short and consisted of personal narratives, which were easily disseminated on social media. CONCLUSIONS: Our findings suggested the importance of responding to common questions and misconceptions on social media platforms from the beginning of disease outbreaks. Authorities need to release clear and reliable information related to the popular topics early on. The microbloggers posting correct information should be empowered and their posts could be promoted to clarify false information. Equal importance should be attached to clarify misinformation in both the outbreak and nonoutbreak areas.

negative: Cancer and COVID-19; how do we manage cancer optimally through a public health crisis?

negative: El síndrome respiratorio agudo grave: primera pandemia del siglo XXI

negative: Post-exposure Prophylaxis or Preemptive Therapy for SARS-Coronavirus-2: Study Protocol for a Pragmatic Randomized Controlled Trial Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in December 2019 causing the coronavirus disease 2019 (COVID-19) pandemic. Currently, there are a lack of evidence-based therapies to prevent COVID-19 following exposure, or to prevent worsening of symptoms following confirmed infection. We describe the design of a clinical trial of hydroxychloroquine for post-exposure prophylaxis and pre-emptive therapy for COVID-19. Methods: We will conduct two nested multicenter international double-blind randomized placebo-controlled clinical trials of hydroxychloroquine for: 1) post-exposure prophylaxis (PEP) of asymptomatic household contacts or healthcare workers exposed to COVID-19 within the past four days, and 2) pre-emptive therapy (PET) for symptomatic outpatients with COVID-19 with a total symptom duration of less than 4 days. We will recruit 1500 patients for each the PEP and PET trials. Participants will be randomized 1:1 to receive 5 days of hydroxychloroquine or placebo. The primary PEP trial outcome will be the incidence of symptomatic COVID-19 disease. The primary PET trial outcome will be an ordinal scale of disease severity (not hospitalized; hospitalized without intensive care, hospitalization with intensive care, or death). Participant screening, informed consent, and follow up will be exclusively internet-based with appropriate regulatory and research ethics board approvals in Canada and the United States. Discussion: These complementary randomized control trials are innovatively designed and adequately powered to rapidly answer urgent questions regarding the effectiveness of hydroxychloroquine to reduce transmission and disease severity of COVID-19 during a pandemic. In-person participant follow-up will not be conducted in order to facilitate social distancing strategies and reduce risks of exposure to study personnel. Innovative trial approaches are needed to urgently assess therapeutic options to mitigate the global impact of this pandemic. Trials Registration: clinicaltrials.gov (NCT04308668); 16 March 2020.

negative: Managing the social amplification of risk: a simulation of interacting actors A central problem in managing risk is dealing with social processes that either exaggerate or understate it. A longstanding approach to understanding such processes has been the social amplification of risk framework. But this implies that some true level of risk becomes distorted in social actors’ perceptions. Many risk events are characterised by such uncertainties, disagreements and changes in scientific knowledge that it becomes unreasonable to speak of a true level of risk. The most we can often say in such cases is that different groups believe each other to be either amplifying or attenuating a risk. This inherent subjectivity raises the question as to whether risk managers can expect any particular kinds of outcome to emerge. This question is the basis for a case study of zoonotic disease outbreaks using systems dynamics as a modelling medium. The model shows that processes suggested in the social amplification of risk framework produce polarised risk responses among different actors, but that the subjectivity magnifies this polarisation considerably. As this subjectivity takes more complex forms it leaves problematic residues at the end of a disease outbreak, such as an indefinite drop in economic activity and an indefinite increase in anxiety.

negative: The Israel Society for Neuroscience 19th Annual Meeting Eilat, Dec. 12 - 14, 2010 www.isfn.org.il: Abstracts

negative: Maintenance Hemodialysis and Coronavirus Disease 2019 (COVID-19): Saving Lives With Caution, Care, and Courage

negative: Initial human transmission dynamics of the pandemic (H1N1) 2009 virus in North America Background Between 5 and 25 April 2009, pandemic (H1N1) 2009 caused a substantial, severe outbreak in Mexico, and subsequently developed into the first global pandemic in 41 years. We determined the reproduction number of pandemic (H1N1) 2009 by analyzing the dynamics of the complete case series in Mexico City during this early period. Methods We analyzed three mutually exclusive datasets from Mexico City Distrito Federal which constituted all suspect cases from 15 March to 25 April: confirmed pandemic (H1N1) 2009 infections, non‐pandemic influenza A infections and patients who tested negative for influenza. We estimated the initial reproduction number from 497 suspect cases identified prior to 20 April, using a novel contact network methodology incorporating dates of symptom onset and hospitalization, variation in contact rates, extrinsic sociological factors, and uncertainties in underreporting and disease progression. We tested the robustness of this estimate using both the subset of laboratory‐confirmed pandemic (H1N1) 2009 infections and an extended case series through 25 April, adjusted for suspected ascertainment bias. Results The initial reproduction number (95% confidence interval range) for this novel virus is 1·51 (1·32–1·71) based on suspected cases and 1·43 (1·29–1·57) based on confirmed cases before 20 April. The longer time series (through 25 April) yielded a higher estimate of 2·04 (1·84–2·25), which reduced to 1·44 (1·38–1·51) after correction for ascertainment bias. Conclusions The estimated transmission characteristics of pandemic (H1N1) 2009 suggest that pharmaceutical and non‐pharmaceutical mitigation measures may appreciably limit its spread prior the development of an effective vaccine.

negative: [Analysis on the epidemic factors for the Corona Virus Disease]. Since December 2019, corona virus disease 2019 (COVID-19) , an emerging infection disease occurred in Wuhan, has spread in the mainland China. The epidemic factors on the basis of knowledge of SARS-CoV-2 were discussed in this paper. This puts a lot of pressure on clinical resources and care. SARS-CoV-2 is a novel corona virus, the onset of COVID-19 is slow, and the pathogenesis of SARS-CoV-2 remains unclear and may lead to multiple organ damage. These put a lot of pressure on clinical resources and care. Source of infection including the patients, asymptomatic carrier and patients in the incubation period are contagious. It is difficult to control source of infection. Routes of SARS-CoV-2 transmission are diversified and the main routes of transmission for COVID-19 are droplet transmission and close contact transmission. All population have susceptibility to SARS-CoV-2. Social factors such population movements and aggregation accelerated the spread of SARS-CoV-2. The Chinese government's adopted measures are positive and effective, and are accepted by the expert group from the World Health Organization. However, it will be a long-term hard work in the future to seriously summarize and think deeply to achieve public health security in China.

negative: Physical distancing or social distancing: that is the question

negative: Rethinking the First COVID-19 Death in Turkey.

negative: Social-distancing effectiveness tracking of the COVID-19 hotspot Stockholm Background: The COVID-19 outbreak in Stockholm, Sweden, is characterized by a near-absence of governmental interventions and high fatalities in the care home population. This study analyses the outbreak and the social-distancing effectiveness timeline in the general population and the care homes. Methods: A novel distributed-compartmental, time-variant epidemiological model was designed specifically for COVID-19 transmission characteristics, featuring a/pre/symptomatic transmission, a non-linear hospital model, a weakly-coupled sub-model for the care-home population, and parametrized continuous social-distancing functions. The model parameters and the social-distancing timelines are determined by randomization and Monte-Carlo simulations analysing real-world data. Findings: Despite a high initial reproduction number (3.29) and the near-absence of governmental interventions, the model quantitated that the transmission rate in the general population was suppressed by 73%, and in the care homes by 79%. The measures in the care homes took effect 4.8 days delayed; and if applied 4 or 8 days earlier, the fatalities could have been reduced by 63.2% or 89.9%. The infected population is estimated to 16.2% (June 10). An expected underestimation of population immunity by antibody studies is confirmed. The infection fatality ratio extrapolates to 0.61% (peak: 1.34%). The model indicates a seasonal effect which effectively suppressed a new rise. An analysed large-scale public event had no large influence. The asymptomatic ratio was determined to 35%. Interpretation: The proposed model and methods have proven to analyse a COVID-19 outbreak and to re-construct the social-distancing behaviour with unprecedented accuracy, confirming even minor details indicated by mobility-data analysis, and are applicable to other regions and other emerging infectious diseases of similar transmission characteristics. The self-regulation of the population in Stockholm, influenced by advices by the authorities, was able to suppress a COVID-19 outbreak to a level far beyond that the stringency index of governmental interventions suggests. Proper timing of effective measures in the care homes is important to reduce fatalities.

negative: Disease experts call for nationwide closure of U.S. schools and businesses to slow coronavirus Infectious disease experts across the United States are calling for tougher enforcement of social distancing measures to slow the spread of the coronavirus behind the COVID-19 pandemic, including a nationwide closure of schools and nonessential businesses Such a move would go beyond the spotty closures now in place in some states and major cities

negative: Quantifying the social distancing privilege gap: a longitudinal study of smartphone movement Background: In response to the coronavirus pandemic, social distancing became a widely deployed countermeasure in March 2020. We examined whether healthier and wealthier places more successfully implemented social distancing. Methods: Mobile device location data were used to quantify declines in movement by county (n=2,633) in the United States of America, comparing April 15-17 (n=65,544,268 traces) to baseline of February 17 - March 7. Negative binomial regression was used to estimate gradients of privilege across eleven healthcare and economic indicators, adjusting for rurality and stay-at-home mandates. External validation used separate venue-specific data from Google Location Services. Findings: Counties without stay-at-home orders showed a mobility decline of -52.3% (95% CI: -50.3%, -54.3%), slightly less than the decline in mandated areas (-60.8%; 95% CI: -60.0%, -61.6%). Strong linear gradients in privilege were observed. After adjusting for rurality and stay-at-home orders, counties in the highest quintile of social distancing mobility restriction had: 52% less uninsured, 47% more primary care providers, 29% more exercise space, 27% less food insecurity, 26% less child poverty, 17% higher incomes, 14% less overcrowding, 9.6% more racial segregation, 8.2% less youth, 7.4% more elderly, and 6.2% less influenza vaccination, compared to least social distancing areas. Interpretation: Healthier and wealthier counties displayed a social distancing privilege gap, measured via smartphone mobility change. Structural inequities in this key countermeasure will influence immunity, and disease incidence and mortality.

negative: Innate Immune Responses in Ventilator-Associated Pneumonia Ventilator-associated pneumonia (VAP) is a common complication of mechanical ventilation, resulting in substantial morbidity, mortality, and health care cost. Early upper airway colonization by pathogenic bacteria and microaspiration are the primary pathogenic events leading to VAP. Patients at risk for VAP have defects in structural/mechanical defenses of the respiratory tract. In addition, critical illness, including sepsis, trauma, and postoperative states, is associated with profound defects in both innate and acquired antibacterial immunity, influencing antimicrobial effector functions of both leukocytes and structural/parenchymal cells. Factors present within the lung microenvironment, including alveolar stretch, cyclical atelectasis, changes in oxygen tension, and respiratory tract microbiota, substantially impact antibacterial host responses. Mechanisms accounting for dysregulated immune homeostasis are incompletely understood, but likely involve: (1) alterations in the balance of pro- and anti-inflammatory cytokines; (2) changes in pathogen recognition receptor and G-protein coupled receptor expression and downstream signaling cascades; and (3) dysregulated cell death responses. Antibiotics and preventive strategies are the mainstay of therapy in patients with VAP. However, novel approaches are needed to reverse immunological reprogramming that occurs during critical illness and/or mechanical ventilation, and to identify patients who are most likely to benefit from immunomodulatory therapy.

negative: Sentiment analysis of Social Media Response on the Covid19 outbreak

negative: Bacterial resistance: A sensitive issue Complexity of the challenge and containment strategy in Europe Abstract The development of antimicrobial agents has been a key achievement of modern medicine. However, their overuse has led to an increasing incidence of infections due to antibiotic-resistant microorganisms. Quantitative figures on the current economic and health impact of antimicrobial resistance are scant, but it is clearly a growing challenge that requires timely action. That action should be at the educational, ethical, economic and political level. An important first step would be to increase public awareness and willingness to take the necessary measures to curb resistance. Hence, studies are needed that would provide solid, quantitative data on the societal impact of antibiotic resistance. This review discusses the complexity of resistance, identifies its main drivers and proposes measures to contain it on a European scale.

negative: Strategies to Promote Social Connections Among Older Adults During ‘Social Distancing’ Restrictions Older age and medical comorbidity are factors associated with more severe illness and risk of death due to COVID-19 infection. Social distancing is an important public health strategy for controlling the spread of the virus and minimizing its impact on the older adult population. It comes at a cost, however. Loneliness is associated with myriad adverse health outcomes, one of which is impaired immune functioning, which adds even greater risk for corona virus infection, complications and death. Older adults, therefore, are at compound risk, making effective management of loneliness and social isolation in our older patients a high priority target for preventive intervention. In this paper, we describe a cognitive-behavioral framework for social connectedness, including evidence-informed strategies clinicians can use to help patients develop a ‘Connections Plan’ to stay connected and promote their social, mental, and physical health during ‘social distancing’ restrictions. This set of strategies can be provided during brief (30 minute) telephone sessions and is analogous to creating a ‘Safety Plan’ for suicide risk. The approach is illustrated with three case examples.

negative: Impact of Social Vulnerability on COVID-19 Incidence and Outcomes in the United States Importance: Prior pandemics have disparately affected socially vulnerable communities. Whether regional variations in social vulnerability to disasters influence COVID-19 outcomes and incidence in the U.S. is unknown. Objective: To examine the association of Social Vulnerability Index (SVI), a percentile-based measure of county-level social vulnerability to disasters, and its sub-components (socioeconomic status, household composition, minority status, and housing type/transportation accessibility) with the case fatality rate (CFR) and incidence of COVID-19. Design: Ecological study of counties with at least 50 confirmed COVID-19 cases as of April 4th, 2020. Generalized linear mixed-effects models with state-level clustering were applied to estimate county-level associations of overall SVI and its sub-component scores with COVID-19 CFR (deaths/100 cases) and incidence (cases/1000 population), adjusting for population percentage aged >65 years, and for comorbidities using the average Hierarchical Condition Category (HCC) score. Counties with high SVI (≥median) and high CFR (≥median) were identified. Setting: Population-based study of U.S. county-level data. Participants: U.S. counties with at least 50 confirmed COVID-19 cases. Main outcomes and measures: COVID-19 CFR and incidence. Results: Data from 433 counties including 283,256 cases and 6,644 deaths were analyzed. Median SVI was 0.46 [Range: 0.01-1.00], and median CFR and incidence were 1.9% [Range: 0-13.3] and 1.2 per 1000 people [Range: 0.6-38.8], respectively. Higher SVI, indicative of greater social vulnerability, was associated with higher CFR (RR: 1.19 [1.05, 1.34], p=0.005, per-1% increase), an association that strengthened after adjustment for age>65 years and comorbidities (RR: 1.63 [1.38, 1.91], p<0.001), and was further confirmed in a sensitivity analysis limited to six states with the highest testing levels. Although the association between overall SVI and COVID-19 incidence was not significant, the SVI sub-components of socioeconomic status and minority status were both predictors of higher incidence and CFR. A combination of high SVI (≥0.46) and high adjusted CFR (≥2.3%) was observed in 28.9% of counties. Conclusions and Relevance: Social vulnerability is associated with higher COVID-19 case fatality. High social vulnerability and CFR coexist in more than 1 in 4 U.S. counties. These counties should be targeted by public policy interventions to help alleviate the pandemic burden on the most vulnerable population.

negative: Public Interest in Preventive Measures of Coronavirus Disease 2019 Associated With Timely Issuance of Statewide Stay-at-Home Orders INTRODUCTION: One method of monitoring public preparedness is through measuring public interest in preventive measures. The objective of this study was to analyze public interest in the coronavirus disease 2019 (COVID-19) preventive measures and to identify variables associated with timely stay-at-home (SAH) orders issued by governors. METHODS: State-level search volume was collected from Google Trends. Average preventive measure interest was calculated for the query terms "hand sanitizer," "hand washing," "social distancing," and "COVID testing." We then calculated the delay in statewide SAH orders from March 1, 2020, to the date of issuance and by-state presidential voting percentage. Bivariate correlations were computed to assess the relationship between interest in preventive measures and SAH order delay. RESULTS: The correlation between average preventive measure interest and length of time before the SAH order was placed was -0.47. Average preventive measure interest was also inversely related to voting for a Republican presidential nominee in the 2016 election (R = -0.75), the latter of which was positively associated with longer delays in SAH orders (R = 0.48). CONCLUSIONS: States with greater public interest in COVID-19 preventive measures were inversely related to governor issuance of timely SAH orders. Increasing public interest in preventive measures may slow the spread of the virus that causes COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), by improving preparedness.

negative: Aspects médico-psychologiques relatifs à l’épidémie de coronavirus (Covid-19) : l’apport de la théorie de la détection du signal et du concept de lieu de contrôle

negative: Using smartphones and wearable devices to monitor behavioural changes during COVID-19 Background In the absence of a vaccine or effective treatment for COVID-19, countries have adopted Non-Pharmaceutical Interventions (NPIs) such as social distancing and full lockdown. An objective and quantitative means of monitoring the impact and response of these interventions at a local level is urgently required. Here we explore the utility of the recently developed open-source mobile health platform RADAR-base as a toolbox to test the effect and response to NPIs aimed at limiting the spread of COVID-19. Methods We included 1062 participants recruited in Italy, Spain, Denmark, the UK, and the Netherlands. We derived features from the phone and wearable device for length of time spent at home, distance travelled from home, heart rate, sleep, and patterns of phone use. We visualised data using time series plots and performed statistical tests to assess differences in behaviour during baseline, pre-, and post-lockdown periods. Findings We found significant changes in behaviours between baseline/pre-lockdown and post-lockdown for all features except total sleep duration. In general, participants spent more time at home, travelled much less, and were more active on their phones, interacting with others by using social apps. Nevertheless, the response across nations differed with Denmark showing attenuated changes in behaviour. Interpretation Differences in the extracted features by country may reflect variations in communication and implementation of different NPIs as well as cultural differences. We have demonstrated that generalised open-source mobile health monitoring platforms such as RADAR-base which leverages data from wearables and mobile technologies are valuable tools for helping understand the behavioural impact of public health interventions implemented in response to infectious outbreaks such as COVID-19.

negative: When will the battle against novel coronavirus end in Wuhan: a SEIR modeling analysis Recent outbreak of 2019-nCoV in Wuhan raised serious public health concerns. By February 15, 2020 in Wuhan, the total number of confirmed infection cases has reached 37,914, and the number of deaths has reached 1123, accounting for 56.9% of the total confirmed cases and 73.7% of the total deaths in China. People are eager to know when the epidemic will be completely controlled and when people's work and life will be on the right track. In this study we analyzed the epidemic dynamics and trend of 2019-nCoV in Wuhan by using the data after the closure of Wuhan city till February 12, 2020 based on the SEIR modeling method. The optimal parameters were estimated as R0=1.44 (interquartile range: 1.40-1.47)，TI=14 (interquartile range: 14-14) and TE=3.0 (interquartile range: 2.8-3.1). Based on these parameters, the number of infected individuals in Wuhan city may reach the peak around February 19 at about 45,000 people. Once entering March, the epidemic would gradually decline, and end around the late March. It is worth noting that the above prediction is based on the assumption that the number of susceptible population N = 200,000 will not increase. If the epidemic situation is not properly controlled, the peak of infected number can be further increased and the peak time will be a little postponed. It was expected that the epidemic would subside in early March, and disappear gradually towards the late March.

negative: Correlation between universal BCG vaccination policy and reduced morbidity and mortality for COVID-19: an epidemiological study COVID-19 has spread to most countries in the world. Puzzlingly, the impact of the disease is different in different countries. These differences are attributed to differences in cultural norms, mitigation efforts, and health infrastructure. Here we propose that national differences in COVID-19 impact could be partially explained by the different national policies respect to Bacillus Calmette-Guerin (BCG) childhood vaccination. BCG vaccination has been reported to offer broad protection to respiratory infections. We compared large number of countries BCG vaccination policies with the morbidity and mortality for COVID-19. We found that countries without universal policies of BCG vaccination (Italy, Nederland, USA) have been more severely affected compared to countries with universal and long-standing BCG policies. Countries that have a late start of universal BCG policy (Iran, 1984) had high mortality, consistent with the idea that BCG protects the vaccinated elderly population. We also found that BCG vaccination also reduced the number of reported COVID-19 cases in a country. The combination of reduced morbidity and mortality makes BCG vaccination a potential new tool in the fight against COVID-19.

negative: Lay perspectives on social distancing and other official recommendations and regulations in the time of COVID-19: a qualitative study of social media posts BACKGROUND: COVID-19 caused by a new form of coronavirus (SARS-CoV-2) first appeared in China end of 2019 and quickly spread to all counties of the world. To slow down the spread of the virus and to limit the pressure on the health care systems, different regulations and recommendations have been implemented by authorities, comprising amongst others the closure of all entertainment venues and social distancing. These measures have received mixed reactions, particularly from young individuals, with many not following available advice. Drawing on the information in social media discussion forums, the present study explores the reasons why people ignore the orders and recommendations of the authorities and why the authorities are unable to produce a shared sense of inclusion concerning protective measures against the COVID-19 outbreak. METHODS: Three open-access social media forums (Reddit, Twitter, and YouTube comments) were systematically searched with respect to COVID-19-related beliefs, attitudes, and behaviours of individuals. The data was retrieved in the first 3 weeks of March 2020. Qualitative document analysis and qualitative content analysis were used as the methodical approach. The data was reviewed by all authors and jointly interpreted to minimise inconsistencies. RESULTS: The study reveals that reasons such as information pollution on social media, the persistence of uncertainty about the rapidly spreading virus, the impact of the social environment on the individual, and fear of unemployment associated with inequality in the distribution of income lead people to ignore the orders and recommendations of the authorities. The findings suggest that government representatives and politicians could not produce a shared sense of inclusion concerning protective measures against the COVID-19 outbreak, due to not building trust among the public and taking concrete economic steps to satisfy them. CONCLUSION: In uncertain crises, transparency in the presentation of information and government policies emerge as influential determinants in creating social susceptibility and solidarity. The differences between social classes constitute one of the important factors that affect the decision-making mechanisms of individuals in determining the necessary steps to be undertaken in times of crisis.

negative: COVID-19 : caractéristiques cliniques, biologiques et radiologiques chez l’adulte, la femme enceinte et l’enfant. Une mise au point au cœur de la pandémie The spread of the new coronavirus SARS-CoV-2, discovered in China in January 2020, led to a pandemic as early as March 2020, forcing every health care system in the affected countries to adapt quickly. In order to better address this major health crisis, which has given rise to numerous scientific publications, we have synthesized the main original clinical studies to facilitate the day-to-day management of patients with COVID-19. We detail the early signs and progression of the disease as well as the different clinical forms, including extra-pulmonary, as known at the beginning of this pandemic. We focus on clinical, biological and CT markers predictive of severity or mortality. Finally, we discuss the impact of SARS-CoV-2 infection in populations suspected to be at high risk of severe forms.

negative: Measuring voluntary social distancing behavior during the COVID-19 pandemic Staying home is an important part of the effort to contain COVID-19 and limit deaths. Every state in the United States has enacted policies to encourage distancing and staying home. An important question is how these policies interact with individuals voluntary responses to COVID-19 cases and deaths. We find evidence of a non-trivial voluntary response to local and nationally reported COVID-19 cases and deaths.

negative: In the midst of the perfect storm: swift public health actions needed in order to increase societal safety during the COVID-19 pandemic The phenomenal speed of COVID-19 has subjected the public health professionals worldwide to struggle to subdue the spread of the disease and its impact of the affected societies. The limited biomedical and epidemiological understanding of COVID-19 along with the lack of vaccines and therapeutics have led to the reception of draconian measures from the societal safety domain, limiting human interaction through social distancing. Grounded on the adopted approaches, interventions in sero-prevalence studies, mobilisation of the primary health care (PHC) sector, as well as target socially vulnerable groups should be taken into consideration by heath authorities.

negative: Disposable masks: Disinfection and sterilization for reuse, and non-certified manufacturing, in the face of shortages during the COVID-19 pandemic The COVID-19 pandemic is posing a huge global health threat. To deal with this problem, in addition to research and work in the medical field, the main health measures being taken in the workplace and at home involve the establishment of safety protocols, which include distance measures, hygiene and the use of personal protective equipment, such as masks, etc. The WHO still does not recommend the use of masks for the general population. However, their successful use in China, South Korea and the Czech Republic has encouraged their widespread use, and the shortage that already existed. This has caused that companies and individuals are looking at the best way to reuse them, and to manufacture, homemade or not, of non-certified masks. This paper is based on two objectives: to consult the scientific literature to identify the main strategies for disinfecting them, and to determine the effectiveness of non-certified disposable masks. A rapid review has been conducted in which the main publications and other information available online have been analyzed. Results showed that the most promising methods are those that use hydrogen peroxide vapor, ultraviolet radiation, moist heat, dry heat and ozone gas. Soapy water, alcohol, bleach immersion, ethylene oxide, ionizing radiation, microwave, high temperature, autoclave or steam are not fully recommended. Regarding the effectiveness of surgical masks compared to PPE, the former have been seen to be slightly less effective than PPE. As for other types of masks the effectiveness of homemade or non-certified masks is very low.

negative: Quantifying interpersonal contact in the United States during the spread of COVID-19: first results from the Berkeley Interpersonal Contact Study By the start of April 2020, the majority of people living in the United States were under orders to dramatically restrict their daily activities in order to reduce transmission of the virus that can cause COVID-19. These strong social distancing measures will be effective in controlling the spread of the virus only if they are able to reduce the amount of close interpersonal contact in a population. It is therefore crucial for researchers and policymakers to empirically measure the extent to which these policies have actually reduced interpersonal interaction. We created the Berkeley Interpersonal Contact Study (BICS) to help achieve this goal. Here, we report the first set of BICS results, based on data collected in the United States between March 22, 2020 and April 8, 2020. We find evidence that rates of interpersonal contact have greatly been reduced at all ages in the United States.

negative: Timing of non-pharmaceutical interventions to mitigate COVID-19 transmission and their effects on mobility: A cross-country analysis Non-pharmaceutical interventions (NPIs) that encourage physical distancing can decrease and delay the transmission of COVID-19. They have been implemented globally during the pandemic, however, the specific NPIs implemented and the timing of interventions has varied widely. We validated two published datasets on the implementation of NPIs globally. The health and socioeconomic factors associated with delay in implementation of NPIs was analyzed using fractional logit and probit models, and beta regression models. The probability of timely NPI implementation by a country was analyzed using a probit model. The effects of these interventions on mobility changes using Google social mobility reports, were analyzed with propensity score matching methods. Three NPIs were analyzed: national school closure, national lockdown, and global travel ban. Countries with higher incomes, larger populations, and better health preparedness measures had greater delays in implementation. Countries with greater population density, more democratic political systems, lower case detection capacity, and later arrival of first cases were more likely to implement NPIs. Implementation of lockdowns significantly reduced physical mobility. Mobility was further reduced when lockdowns were enforced with curfews or fines, or were more strictly defined. National school closures did not significantly change mobility. The implementation of NPIs is a global public good during pandemics, and the international community needs to address constraints and design incentives so countries implement NPIs in a timely manner. Further analysis is needed on the effect of NPI variations on mobility and transmission, and their associated costs.

negative: Social distancing for covid-19: is 2 metres far enough?

negative: A Tale of Two Communities: Characterizing Reddit Response to COVID-19 through /r/China_Flu and /r/Coronavirus The COVID-19 pandemic has deeply impacted people's lives around the globe. During the extended lockdowns caused by the pandemic, online communities are crucial for people to access information and share experiences. In particular, two"new"communities have emerged on Reddit: /r/China_flu and /r/Coronavirus. By studying activities and users in these two communities, we provide a characterization of people's responses to COVID-19 on Reddit. First, we find that user activity peaks around March 17, when the World Health Organization (WHO) announced COVID-19 as a pandemic. Shortly after that, the activity levels of both communities have been declining week by week. We further illustrate the central role of these two communities in the emergence of COVID-related communities. Second, we study the differences between these two communities. /r/Coronavirus is recommended as the official community for COVID-19 on Reddit, while /r/China_flu adopts a loose moderation practice. As a result, we observe that these two communities are gradually growing apart and more extremism is being found in /r/China_flu. Finally, we examine the spillover effect of the COVID-19 pandemic on user activity across the entire Reddit platform. Our results show significant changes in user activities outside COVID-related communities. In subreddits related to finance, food, and countries/cities, user activity is recovering to the pre-pandemic level in late April and May as countries reopen, but subreddits related to travel and sports remain highly impacted and show lower activity levels than the pre-pandemic period. Our work highlights the strength of Reddit as a source for understanding public reactions to COVID-19 and the importance of content moderation on the Internet during a pandemic.

negative: Chest CT features and their role in COVID-19 Abstract Since December 2019, the novel coronavirus disease (COVID-19) has spread rapidly throughout China. This article reviews the chest CT features of COVID-19 and analyzes the role of chest CT in this health emergency.

negative: The 45th Annual Meeting of the European Society for Blood and Marrow Transplantation: Physicians – Poster Session

negative: Exercise and Fitness in the age of social distancing during the COVID-19 Pandemic

negative: Commentary: COVID-19 in patients with diabetes

negative: Preliminary Estimates of the Prevalence of Selected Underlying Health Conditions Among Patients with Coronavirus Disease 2019 — United States, February 12–March 28, 2020 On March 11, 2020, the World Health Organization declared Coronavirus Disease 2019 (COVID-19) a pandemic (1). As of March 28, 2020, a total of 571,678 confirmed COVID-19 cases and 26,494 deaths have been reported worldwide (2). Reports from China and Italy suggest that risk factors for severe disease include older age and the presence of at least one of several underlying health conditions (3,4). U.S. older adults, including those aged ≥65 years and particularly those aged ≥85 years, also appear to be at higher risk for severe COVID-19-associated outcomes; however, data describing underlying health conditions among U.S. COVID-19 patients have not yet been reported (5). As of March 28, 2020, U.S. states and territories have reported 122,653 U.S. COVID-19 cases to CDC, including 7,162 (5.8%) for whom data on underlying health conditions and other known risk factors for severe outcomes from respiratory infections were reported. Among these 7,162 cases, 2,692 (37.6%) patients had one or more underlying health condition or risk factor, and 4,470 (62.4%) had none of these conditions reported. The percentage of COVID-19 patients with at least one underlying health condition or risk factor was higher among those requiring intensive care unit (ICU) admission (358 of 457, 78%) and those requiring hospitalization without ICU admission (732 of 1,037, 71%) than that among those who were not hospitalized (1,388 of 5,143, 27%). The most commonly reported conditions were diabetes mellitus, chronic lung disease, and cardiovascular disease. These preliminary findings suggest that in the United States, persons with underlying health conditions or other recognized risk factors for severe outcomes from respiratory infections appear to be at a higher risk for severe disease from COVID-19 than are persons without these conditions.

negative: Coronavirus disease (COVID-19) Community Testing Team in Scotland: A 14-day review, 6 to 20 February 2020 In response to the outbreak of COVID-19, we set up a team to carry out sampling in the community. This enabled individuals to remain in self-isolation in their own homes and to prevent healthcare settings and services from being overwhelmed by admissions for sampling of suspected cases. There is evidence that this is a cost effective, safe and necessary service to complement COVID-19 testing in hospitals.

negative: Novel approaches to estimate compliance with lockdown measures in the COVID-19 pandemic

negative: Sudden Death from Pulmonary Causes This chapter seeks to survey many of the common pathological entities identified in the lungs at autopsy and the potential role of pulmonary disease in formulating an opinion regarding the cause of death. Appreciation of pulmonary pathology in the medicolegal context is important as it frequently contributes to the immediate or underlying mechanisms of death. The primacy of the lungs in breathing and their coordinated function with the cardiovascular system means that pulmonary failure can rapidly compromise tissue oxygenation and body chemistry, leading to an alteration in blood pH, hypoxic damage to downstream tissues and ultimately multiorgan failure and death. Moreover, given that the lungs have direct contact with the environment through inhalation and receive approximately 50% of the cardiac output with each beat of the heart, they may be adversely affected by hazardous agents from the outside world or other pathologic processes not primarily located in the lungs. The range of topics discussed herein is limited by design to deaths due to disease and largely foregoes discussion of more forensically relevant issues relating to toxicology or trauma. Furthermore, the content and format of this chapter is not intended to be encyclopedic, but rather attempts to highlight selected issues regarding pulmonary disease of potential relevance to surgical or forensic pathologists who perform medicolegal postmortem examinations.

negative: Important considerations regarding the future management of Coronavirus (COVID-19)

negative: Family violence and COVID‐19: Increased vulnerability and reduced options for support Family violence refers to threatening or other violent behaviour within families that may be physical, sexual, psychological, or economic, and can include child abuse and intimate partner violence (Peterman et al. 2020, van Gelder et al. 2020). Family violence during pandemics is associated with a range of factors including economic stress, disaster-related instability, increased exposure to exploitative relationships, and reduced options for support (Peterman et al. 2020). Due to the social isolation measures implemented across the globe to help reduce the spread of COVID-19, people living in volatile situations of family violence are restricted to their homes. Social isolation exacerbates personal and collective vulnerabilities while limiting accessible and familiar support options (van Gelder et al. 2020). In many countries, including Australia, we have already seen an increase in demand for domestic violence services and reports of increased risk for children not attending schools (Duncan, 2020); a pattern similar to previous episodes of social isolation associated with epidemics and pandemics (Boddy, Young & O'Leary 2020).

negative: Informational needs assessment of non‐Hodgkin lymphoma survivors and their physicians

negative: The pandemic of social media panic travels faster than the COVID-19 outbreak

negative: The Benefits and Costs of Social Distancing in Rich and Poor Countries Social distancing is the primary policy prescription for combating the COVID-19 pandemic, and has been widely adopted in Europe and North America. We estimate the value of disease avoidance using an epidemiological model that projects the spread of COVID-19 across rich and poor countries. Social distancing measures that"flatten the curve"of the disease to bring demand within the capacity of healthcare systems are predicted to save many lives in high-income countries, such that practically any economic cost is worth bearing. These social distancing policies are estimated to be less effective in poor countries with younger populations less susceptible to COVID-19, and more limited healthcare systems, which were overwhelmed before the pandemic. Moreover, social distancing lowers disease risk by limiting people's economic opportunities. Poorer people are less willing to make those economic sacrifices. They place relatively greater value on their livelihood concerns compared to contracting COVID-19. Not only are the epidemiological and economic benefits of social distancing much smaller in poorer countries, such policies may exact a heavy toll on the poorest and most vulnerable. Workers in the informal sector lack the resources and social protections to isolate themselves and sacrifice economic opportunities until the virus passes. By limiting their ability to earn a living, social distancing can lead to an increase in hunger, deprivation, and related mortality and morbidity. Rather than a blanket adoption of social distancing measures, we advocate for the exploration of alternative harm-reduction strategies, including universal mask adoption and increased hygiene measures.

negative: Continuous monitoring of changes in plasma nitrite following cerebral ischemia in a rabbit embolic stroke model. In this proof-of-concept study, we investigated direct, continuous monitoring of plasma nitrite as an indicator of cerebral ischemia following clot embolization of rabbits via an indwelling carotid catheter. Two groups of rabbits were studied to compare the effects of embolization on nitrite levels. In the control group, blood was continuously obtained from a jugular venous catheter. The blood was immediately passed through an ultrafiltration filter; the filtrate was chemically reduced to convert free nitrite to nitric oxide (NO) and then measured using a NO-specific electrode. In the embolized group, after a baseline nitrite level was achieved, blood clots were injected into the brain via the carotid artery catheter, and then nitrite levels were continuously measured from jugular venous blood. The stroke group showed a significantly greater increase in nitrite as compared to controls (p=0.017). Using the area-under-the-curve (AUC) method, results reached statistical significance (p<0.05) within 3 min of embolization. In embolized rabbits, NO(2) levels increased 424±256% compared to baseline. This study shows that nitrite can be measured immediately following a stroke and that our system measures nitrite independent of the extent of the stroke. This study provides evidence for the feasibility of using nitrite as a marker of ischemic stroke.

negative: Risk Management of COVID-19 by Universities in China Short-term Forecasts of the COVID-19 Epidemic in Guangdong and Zhejiang, China: February 13–23, 2020 The rapid spread of new coronaviruses throughout China and the world in 2019–2020 has had a great impact on China’s economic and social development As the backbone of Chinese society, Chinese universities have made significant contributions to emergency risk management Such contributions have been made primarily in the following areas: alumni resource collection, medical rescue and emergency management, mental health maintenance, control of staff mobility, and innovation in online education models Through the support of these methods, Chinese universities have played a positive role in the prevention and control of the epidemic situation However, they also face the problems of alumni’s economic development difficulties, the risk of deadly infection to medical rescue teams and health workers, infection of teachers and students, and the unsatisfactory application of information technology in resolving the crisis In response to these risks and emergency problems, we propose some corresponding solutions for public dissemination, including issues related to medical security, emergency research, professional assistance, positive communication, and hierarchical information-based teaching The ongoing COVID-19 epidemic continues to spread within and outside of China, despite several social distancing measures implemented by the Chinese government Limited epidemiological data are available, and recent changes in case definition and reporting further complicate our understanding of the impact of the epidemic, particularly in the epidemic’s epicenter Here we use previously validated phenomenological models to generate short-term forecasts of cumulative reported cases in Guangdong and Zhejiang, China Using daily reported cumulative case data up until 13 February 2020 from the National Health Commission of China, we report 5- and 10-day ahead forecasts of cumulative case reports Specifically, we generate forecasts using a generalized logistic growth model, the Richards growth model, and a sub-epidemic wave model, which have each been previously used to forecast outbreaks due to different infectious diseases Forecasts from each of the models suggest the outbreaks may be nearing extinction in both Guangdong and Zhejiang;however, the sub-epidemic model predictions also include the potential for further sustained transmission, particularly in Zhejiang Our 10-day forecasts across the three models predict an additional 65–81 cases (upper bounds: 169–507) in Guangdong and an additional 44–354 (upper bounds: 141–875) cases in Zhejiang by February 23, 2020 In the best-case scenario, current data suggest that transmission in both provinces is slowing down

negative: Chinese immigrant parents’ vaccination decision making for children: a qualitative analysis BACKGROUND: While immunization coverage rates for childhood routine vaccines in Hong Kong are almost 100%, the uptake rates of optional vaccines remain suboptimal. Understanding parental decision-making for children’s vaccination is important, particularly among minority groups who are most vulnerable and underserved. This study explored how a subsample of new immigrant mothers from mainland China, a rapidly-growing subpopulation in Hong Kong, made decisions on various childhood and adolescent vaccines for their offspring, and identified key influences affecting their decision making. METHODS: Semi-structured in-depth interviews were conducted with 23 Chinese new immigrant mothers recruited by purposive sampling. All interviews were audio-taped, transcribed and analyzed using a Grounded Theory approach. RESULTS: Participants’ conversation revealed five underlying themes which influenced parents’ vaccination decision-making: (1) Institutional factors, (2) Insufficient vaccination knowledge and advice, (3) Affective impacts on motivation, (4) Vaccination barriers, and (5) Social influences. The role of social norms appeared overwhelmingly salient influencing parents’ vaccination decision making. Institutional factors shaped parent’s perceptions of vaccination necessity. Fear of vaccine-targeted diseases was a key motivating factor for parents adopting vaccination. Insufficient knowledge about vaccines and targeted diseases, lack of advice from health professionals and, if provided, suspicions regarding the motivations for such advice were common issues. Vaccination cost was a major barrier for many new immigrant parents. CONCLUSIONS: Social norms play a key role influencing parental vaccination decision-making. Insight gained from this study will help inform healthcare providers in vaccination communication and policymakers in future vaccination programme.

negative: COVID-19, Australia: Epidemiology Report 11 (Reporting week to 23:59 AEST 12 April 2020) Confirmed cases in Australia notified up to 12 April 2020: notifications = 6,394; deaths = 46. The reduction in international travel and domestic movement, social distancing measures and public health action have likely slowed the spread of the disease. Notifications in Australia remain predominantly among people with recent overseas travel, with some locally-acquired cases being detected. Most locally-acquired cases are able to be linked back to a confirmed case, with a small portion unable to be epidemiologically linked. The distribution of overseas-acquired cases to locally acquired cases varies by jurisdiction. Internationally, cases continue to increase. The rates of increase have started to slow in several regions, although it is too soon to tell whether this trend will be sustained. The epidemiology differs from country to country depending not only on the disease, but also on differences in case detection, testing and implemented public health measures.

negative: Stratégies de gestion de l’impact du confinement sur le sommeil : une synthèse d’experts Résumé En plus de l’impact psychologique du confinement et de l’épidémie, il existe des répercussions sur le sommeil qu’il faut prendre en compte par la mise en place de stratégies adaptées afin de maintenir un bon état de santé mental et de santé général. Le confinement peut désorganiser le sommeil en impactant, d’une part, les rythmes circadiens par une diminution de l’intensité des synchroniseurs extérieurs et, d’autre part, peut favoriser l’insomnie dans cette période de stress aigu. Enfin, le confinement peut être source d’une privation de sommeil chez ceux qui sont en première ligne et qui gèrent la crise. De plus, chez les enfants/adolescents le confinement peut également déstructurer les journées et ainsi avoir un impact sur la santé en générale. Pour cela, il est important de mettre en place certaines stratégies de préventions de ces perturbations de sommeil afin d’atténuer l’impact psychologique, infectieux et faire face de manière optimale à cette situation que nous vivons tous. Summary In addition to the psychological impact of quarantine, there are sleep disturbances that must be taken into account by implementing appropriate strategies in order to maintain good mental and general health. Quarantine can disrupt sleep first in impacting circadian rhythms by decreasing the intensity of zeitgebers, second can promote insomnia in this period of acute stress and third can be a source of sleep deprivation in those on the front line and managing the crisis. In addition, in children/adolescents, confinement can also destructure the days and thus have an impact on overall health. For this, it is important to put in place strategies to prevent these sleep disturbances in order to reduce the psychological, infectious impact and deal optimally with this situation that we are all experiencing.

negative: Social network theory in the behavioural sciences: potential applications Social network theory has made major contributions to our understanding of human social organisation but has found relatively little application in the field of animal behaviour. In this review, we identify several broad research areas where the networks approach could greatly enhance our understanding of social patterns and processes in animals. The network theory provides a quantitative framework that can be used to characterise social structure both at the level of the individual and the population. These novel quantitative variables may provide a new tool in addressing key questions in behavioural ecology particularly in relation to the evolution of social organisation and the impact of social structure on evolutionary processes. For example, network measures could be used to compare social networks of different species or populations making full use of the comparative approach. However, the networks approach can in principle go beyond identifying structural patterns and also can help with the understanding of processes within animal populations such as disease transmission and information transfer. Finally, understanding the pattern of interactions in the network (i.e. who is connected to whom) can also shed some light on the evolution of behavioural strategies.

negative: Abstracts from the 37th Annual Meeting of the Society of General Internal Medicine

negative: COVID-19: The forgotten priorities of the pandemic Abstract The zoonotic virus now named SARS-CoV-2 first infected humans in China, and COVID-19 has rapidly become pandemic. To mitigate its impact on societies, health systems and economies, countries have adopted non-pharmacological preventive practices such as ‘spatial’ or ‘social’ distancing, the use of protective masks, and handwashing; these have been widely implemented. However, measures aimed at protecting physical health and healthcare systems have side-effects that might have a big impact on individuals’ wellbeing. As the pandemic reaches low- and middle-income countries, weaker health systems, limited resources and the lower socioeconomic status of their populations make halting the pandemic more challenging. In this article, we explore the impact of COVID-19 and its prevention measures on the wellbeing of vulnerable populations. Special attention must be given to homeless, indigenous, migrant and imprisoned populations, as well as people living with disabilities and the elderly. More than just resolute governmental action will be required to overcome the pandemic. Links between science and political actions have to be strengthened. Fighting COVID-19 is a collective endeavour and community action, on a global scale, is of paramount importance.

negative: Modelling input-output flows of severe acute respiratory syndrome in mainland China BACKGROUND: Severe acute respiratory syndrome (SARS) originated in China in 2002, and it spread to 26 provinces in mainland China and 32 countries across five continents in a matter of months. This outbreak resulted in 774 deaths. However, the spatial features and potential determinants of SARS input-output flows remain unclear. METHODS: We used an adjusted spatial interaction model to examine the spatial effects and potential factors associated with SARS input-output flows. RESULTS: The presence of origin-based spatial dependence positively affected SARS input-output flows from the neighbours of the origin regions. Two components of the input-output flows, migrant and hospitalization flows, exhibited distinctive features. The origin-based and destination-based spatial dependence positively affected migrant flows (i.e., due to those seeking jobs) from the neighbours of origin and destination locations. Similarly, the destination-based spatial dependence also positively affected hospitalization flows (i.e., due to those seeking treatment) from the neighbours of destination regions. However, the origin-to-destination based spatial dependence negatively affected hospitalisation flows from the neighbours of origin-to-destination regions. The direct effects accounted for 78 % of the SARS input-output flows, which was 3.56-fold greater than the indirect effects. Differences in regional income drove the SARS input-output flows. Therefore, urban income had a positive effect, whereas rural income had a negative effect. Total interregional flows increased by 3.54 % with a 1 % increase in urban income, and intraregional flows increased by 8.35 %. In contrast, the total interregional flows decreased by 3.38 % with a 1 % increase in rural income, and intraregional flows declined by 2.29 %. Railway capacity, per person gross domestic product (PGDP), urban rate and the law of distance decay also affected the input-output flows. CONCLUSIONS: Our results confirm that the SARS input-output flows presented significant geographic spatial heterogeneity and spatial effects. Income differences were the major cause of the flows between pairs of regions. Railway capacity, PGDP, and urban rate also played important roles. These findings provide valuable information for the Chinese government to control the future spread of nationwide epidemics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12889-016-2867-6) contains supplementary material, which is available to authorized users.

negative: The phenotypic changes of Î³Î´ T cells in COVID-19 patients A novel pneumonia-associated respiratory syndrome named coronavirus disease-2019 (COVID-19), which caused by SARS-CoV-2 and broken in Wuhan, China in the end of 2019. Unfortunately, there is no specific antiviral agent or vaccine available to treat SARS-CoV-2 infections. Also, information regarding the immunological characteristics in COVID-19 patients remains limited. Here we collected the blood samples from 18 healthy donors (HD) and 38 COVID-19 patients to analyze changes in {gamma}{delta} T cells. In comparison to HD, the {gamma}{delta} T cells percentage was decreased. {gamma}{delta} T cells are able to immediately respond to SARS-CoV-2 infection and upregulate the activation marker CD25. In addition, the increased expression of CD4 in {gamma}{delta} T cells may serve as a biomarker for the assessment of SARS-CoV-2 infection.

negative: Statistical Explorations and Univariate Timeseries Analysis on COVID-19 Datasets to Understand the Trend of Disease Spreading and Death “Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)”, the novel coronavirus, is responsible for the ongoing worldwide pandemic. “World Health Organization (WHO)” assigned an “International Classification of Diseases (ICD)” code—“COVID-19”-as the name of the new disease. Coronaviruses are generally transferred by people and many diverse species of animals, including birds and mammals such as cattle, camels, cats, and bats. Infrequently, the coronavirus can be transferred from animals to humans, and then propagate among people, such as with “Middle East Respiratory Syndrome (MERS-CoV)”, “Severe Acute Respiratory Syndrome (SARS-CoV)”, and now with this new virus, namely “SARS-CoV-2”, or human coronavirus. Its rapid spreading has sent billions of people into lockdown as health services struggle to cope up. The COVID-19 outbreak comes along with an exponential growth of new infections, as well as a growing death count. A major goal to limit the further exponential spreading is to slow down the transmission rate, which is denoted by a “spread factor (f)”, and we proposed an algorithm in this study for analyzing the same. This paper addresses the potential of data science to assess the risk factors correlated with COVID-19, after analyzing existing datasets available in “ourworldindata.org (Oxford University database)”, and newly simulated datasets, following the analysis of different univariate “Long Short Term Memory (LSTM)” models for forecasting new cases and resulting deaths. The result shows that vanilla, stacked, and bidirectional LSTM models outperformed multilayer LSTM models. Besides, we discuss the findings related to the statistical analysis on simulated datasets. For correlation analysis, we included features, such as external temperature, rainfall, sunshine, population, infected cases, death, country, population, area, and population density of the past three months—January, February, and March in 2020. For univariate timeseries forecasting using LSTM, we used datasets from 1 January 2020, to 22 April 2020.

negative: A complex minuet: behaviour change at the large scale Sara E Davies Unknown

negative: A systematic review of lopinavir therapy for SARS coronavirus and MERS coronavirus—A possible reference for coronavirus disease‐19 treatment option In the past few decades, coronaviruses have risen as a global threat to public health. Currently, the outbreak of coronavirus disease‐19 (COVID‐19) from Wuhan caused a worldwide panic. There are no specific antiviral therapies for COVID‐19. However, there are agents that were used during the severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) epidemics. We could learn from SARS and MERS. Lopinavir (LPV) is an effective agent that inhibits the protease activity of coronavirus. In this review, we discuss the literature on the efficacy of LPV in vitro and in vivo, especially in patients with SARS and MERS, so that we might clarify the potential for the use of LPV in patients with COVID‐19.

negative: Global surveillance, travel, and trade during a pandemic Pandemics have had very important consequences in human history. Lots of people lost their lives and countries have been intensively affected in terms of socioeconomic problems. Unfortunately, avoidance of pandemics and limiting the spread are still currently not always possible. Maybe the most important factor for this is the increasing frequency of traveling. Increasing airline traveling rate also increases the rate of spread. Global organizations like the World Health Organization and United Nations are trying to play a supreme role over the countries. Pandemics do not have borders; therefore, efforts should be given globally, definition of pandemic should be established as soon as possible, and protective measures should be shared with countries. If these are not done, severe health consequences and serious economic problems are inevitable.

negative: Disease spreading with social distancing: a prevention strategy in disordered multiplex networks The continue emerging of diseases that have the potential to become threats at local and global scales, such as influenza A(H1N1), SARS, MERS, and COVID-19, makes it relevant to keep designing models of disease propagation and strategies to prevent or mitigate their effects in populations. Since isolated systems are very rare to find in any context, specially in human contact networks, here we examine the susceptible-infected-recovered model of disease spreading in a multiplex network formed by two distinct networks or layers that are interconnected through a fraction $q$ of shared individuals. We model the interactions between individuals in each layer through a weighted network, because person-to-person interactions are diverse (or disordered); weights represent the contact times of these interactions and we use a distribution of contact times to assign an individual disorder to each layer. Using branching theory supported by simulations, we study a social distancing strategy where we reduce the average contact time in one layer (or in both of them, if necessary). We find a set of disorder parameters - associated with average contact times - that prevents a disease from becoming an epidemic. When the disease is very likely to spread, the system is always in an epidemic phase, regardless of the disorder parameters and the fraction of shared nodes. However we find that it is still possible to protect a giant component of susceptible individuals, which is crucial to keep the functionality of the system composed by the two interconnected layers.

negative: Identifying airborne transmission as the dominant route for the spread of COVID-19 Various mitigation measures have been implemented to fight the coronavirus disease 2019 (COVID-19) pandemic, including widely adopted social distancing and mandated face covering. However, assessing the effectiveness of those intervention practices hinges on the understanding of virus transmission, which remains uncertain. Here we show that airborne transmission is highly virulent and represents the dominant route to spread the disease. By analyzing the trend and mitigation measures in Wuhan, China, Italy, and New York City, from January 23 to May 9, 2020, we illustrate that the impacts of mitigation measures are discernable from the trends of the pandemic. Our analysis reveals that the difference with and without mandated face covering represents the determinant in shaping the pandemic trends in the three epicenters. This protective measure alone significantly reduced the number of infections, that is, by over 78,000 in Italy from April 6 to May 9 and over 66,000 in New York City from April 17 to May 9. Other mitigation measures, such as social distancing implemented in the United States, are insufficient by themselves in protecting the public. We conclude that wearing of face masks in public corresponds to the most effective means to prevent interhuman transmission, and this inexpensive practice, in conjunction with simultaneous social distancing, quarantine, and contact tracing, represents the most likely fighting opportunity to stop the COVID-19 pandemic. Our work also highlights the fact that sound science is essential in decision-making for the current and future public health pandemics.

negative: Post-exposure prophylaxis or pre-emptive therapy for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): study protocol for a pragmatic randomized-controlled trial BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in December 2019 causing the coronavirus disease (COVID-19) pandemic. Currently, there is a lack of evidence-based therapies to prevent COVID-19 following exposure to the virus, or to prevent worsening of symptoms following confirmed infection. We describe the design of a clinical trial of hydroxychloroquine for post-exposure prophylaxis (PEP) and pre-emptive therapy (PET) for COVID-19. METHODS: We will conduct two nested multicentre international double-blind randomized placebo-controlled clinical trials of hydroxychloroquine for: 1) PEP of asymptomatic household contacts or healthcare workers exposed to COVID-19 within the past four days, and 2) PET for symptomatic outpatients with COVID-19 showing symptoms for less than four days. We will recruit 1,500 patients each for the PEP and PET trials. Participants will be randomized 1:1 to receive five days of hydroxychloroquine or placebo. The primary PEP trial outcome will be the incidence of symptomatic COVID-19. The primary PET trial outcome will be an ordinal scale of disease severity (not hospitalized, hospitalized without intensive care, hospitalization with intensive care, or death). Participant screening, informed consent, and follow-up will be exclusively internet-based with appropriate regulatory and research ethics board approvals in Canada and the United States. DISCUSSION: These complementary randomized-controlled trials are innovatively designed and adequately powered to rapidly answer urgent questions regarding the effectiveness of hydroxychloroquine to reduce virus transmission and disease severity of COVID-19 during a pandemic. In-person participant follow-up will not be conducted to facilitate social distancing strategies and reduce risks of exposure to study personnel. Innovative trial approaches are needed to urgently assess therapeutic options to mitigate the global impact of this pandemic. TRIALS REGISTRATION: clinicaltrials.gov (NCT04308668); registered 16 March, 2020.

negative: COVID-19 Outbreak, Social Response, and Early Economic Effects: A Global VAR Analysis of Cross-Country Interdependencies The COVID-19 pandemic underscored the importance of countries' interconnections in understanding and reacting to the spread of the virus. This paper uses a global model with a sample of 41 countries to study the interdependencies between COVID-19 health shocks, populations' risk perceptions about the disease, and their social distancing responses; it also provides some early evidence about potential economic effects. Social networks are a central component in understanding the international transmission. We exploit a dataset on existing social connections across country borders, made available by Facebook, and show that social networks help explain not only the spread of the disease, but also cross-country spillovers in risk perceptions and in social behavior. Social distancing responses across countries are measured based on aggregated mobility tracking indicators, obtained from Google Mobility Reports. We estimate a Global VAR (GVAR) model, which allows for endogeneity of each health, social, and economic, domestic variable, and for a dependence of domestic variables on country-specific foreign aggregates, which depend in turn on the matrix of social connections. Our empirical results highlight the importance of cross-country interdependencies and social networks. Risk perceptions and social responses are affected by experiences abroad, with Italy and the U.S. playing large roles in our sample. The social distancing responses to domestic health shocks are heterogeneous across countries, but they share some similarities: they adjust only gradually and with delay, hence displaying adaptive behavior. Early indicators are suggestive of unemployment consequences that vary widely across countries, depending on their labor market characteristics. Unemployment is particularly responsive to health shocks in the U.S. and Spain, while the fluctuations are attenuated almost everywhere else.

negative: Orthopaedic Surgical Selection and Inpatient Paradigms During the Coronavirus (COVID-19) Pandemic The novel coronavirus pandemic, also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has placed an immense strain on healthcare systems across the entire world. Consequently, multiple federal and state governments have placed restrictions on hospitals such as limiting "elective surgery" and recommending social or physical distancing. We review the literature on several areas that have been affected including surgical selection, inpatient care, and physician well-being. These areas affecting inpatient paradigms include surgical priority, physical or social distancing, file sharing for online clinical communications, and physician wellness. During this crisis, it is important that orthopaedic departments place an emphasis on personnel safety and slowing the spread of the virus so that the department can still maintain vital functions. Physical distancing and emerging technologies such as inpatient telemedicine and online file sharing applications can enable orthopaedic programs to still function while attempting to protect medical staff and patients from the novel coronavirus spread. This literature review sought to provide evidence-based guidance to orthopaedic departments during an unprecedented time. Orthopaedic surgeons should follow the Centers for Disease Control and Prevention guidelines, wear personal protective equipment (PPE) when appropriate, have teams created using physical distancing, understand the department's policy on elective surgery, and engage in routines which enhance physician wellness.

negative: Nelfinavir inhibits replication of severe acute respiratory syndrome coronavirus 2 in vitro In December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, Hubei Province, China. No specific treatment has been established against coronavirus disease-2019 (COVID-19) so far. Therefore, it is urgently needed to identify effective antiviral agents for the treatment of this disease, and several approved drugs such as lopinavir have been evaluated. Here, we report that nelfinavir, an HIV-1 protease inhibitor, potently inhibits replication of SARS-CoV-2. The effective concentrations for 50% and 90% inhibition (EC50 and EC90) of nelfinavir were 1.13 µM and 1.76 µM respectively, the lowest of the nine HIV-1 protease inhibitors including lopinavir. The trough and peak serum concentrations of nelfinavir were three to six times higher than EC50 of this drug. These results suggest that nelfinavir is a potential candidate drug for the treatment of COVID-19 and should be assessed in patients with COVID-19.

negative: Experience with Social Distancing Early in the COVID-19 Pandemic in the United States: Implications for Public Health Messaging Our goal is to inform ongoing public health policy on the design and communication of COVID-19 social distancing measures to maximize compliance. We assessed the US publics early experience with the COVID-19 crisis during the period when shelter-in-place orders were widely implemented to understand non-compliance with those orders, sentiment about the crisis, and to compare across age categories associated with different levels of risk. We posted our survey on Twitter, Facebook, and NextDoor on March 14th to March 23rd that included 21 questions including demographics, impact on daily life, actions taken, and difficulties faced. We analyzed the free-text responses to the impact question using LIWC, a computational natural language processing tool, and performed a thematic content analysis of the reasons people gave for non-compliance with social distancing orders. Stanford Universitys IRB approved the study. In 9 days, we collected a total of 20,734 responses. 6,573 individuals provided a response (≥30 words) to the question, Tell us how the coronavirus crisis is impacting your life. Our data (Figure 1) show that younger people (18-31) are more emotionally negative, self-centered, and less concerned with family, while middle-aged people are group-oriented (32-44) and focused on family (32-64) (all p values < .05 corrected for multiple comparisons). Unsurprisingly, the oldest and most at-risk group (65+) are more focused on biological terms (e.g., health-related topics), but were surprisingly low in anxiety and high in emotionally positive terms relative to those at lower risk. We also content-analyzed 7,355 responses (kappas > .75) to the question, What are the reasons you are not self-isolating more? Of these participants, 39.8% reported not being compliant, with the youngest group (18-31) having the lowest compliance rate (52.4%) compared to the other age groups (all > 60%; all p values < .01). Table 1 describes the seven primary themes for non-compliance. Non-essential work requirements, concerns about mental and physical health, and the belief that other precautions were sufficient were the most common reasons, although other rationales included wanting to continue everyday activities and beliefs that society is over-reacting. Childcare was an important concern for a subset of respondents. Overall, our findings suggest that public health messages should focus on young people and 1) address their negative affect, 2) refocus their self-orientation by emphasizing the importance of individual behavior to group-level health outcomes, and 3) target the specific rationales that different people have regarding the pandemic to maximize compliance with social distancing.

negative: The Impact of Social Distancing on the Transmission of Influenza Virus, South Korea, 2020

negative: Lack of Antiviral Activity of Darunavir against SARS-CoV-2 Given the high need and the absence of specific antivirals for treatment of COVID-19 (the disease caused by severe acute respiratory syndrome-associated coronavirus-2 [SARS-CoV-2]), human immunodeficiency virus (HIV) protease inhibitors are being considered as therapeutic alternatives. Prezcobix/Rezolsta is a fixed-dose combination of 800 mg of the HIV protease inhibitor darunavir (DRV) and 150 mg cobicistat, a CYP3A4 inhibitor, which is indicated in combination with other antiretroviral agents for the treatment of HIV infection. There are currently no definitive data on the safety and efficacy of DRV/cobicistat for treatment of COVID-19. The in vitro antiviral activity of darunavir against a clinical isolate from a patient infected with SARS-CoV-2 was assessed. DRV showed no activity against SARS-CoV-2 at clinically relevant concentrations (EC50 >100 μM). Remdesivir, used as a positive control, showed potent antiviral activity (EC50 = 0.38 μM). Overall, the data do not support the use of DRV for treatment of COVID-19.

negative: Targeting COVID-19 interventions towards migrants in humanitarian settings

negative: COVID-19 Pandemic: Power Law Spread and Flattening of the Curve In this paper, we analyze the real-time infection data of COVID-19 epidemic for nine nations. Our analysis is up to May 04, 2020. South Korea, China, Italy, France, Spain, and Germany have either flattened or close to flattening their epidemic curves. USA and Japan have transitioned to a linear regime, while India is still in a power-law phase. We argue that the transition from an exponential regime to a succession of power-law regimes is a good indicator for flattening of the epidemic curve. We also argue that lockdowns, long-term community transmission, and the transmission by asymptomatic carriers traveling long distances may be inducing the power-law growth of the epidemic.

negative: How Might Social Distancing Impact Gay, Bisexual, Queer, Trans and Two-Spirit Men in Canada?

negative: The site of origin of the 1918 influenza pandemic and its public health implications

negative: Telemental health comes into its own with social distancing Telepsychiatry, telemental health, telepsychology, teletherapy — whatever you call it, it is now required in the era of the coronavirus/COVID‐19 pandemic. “We should be doing it immediately; the more, the better,” said Robert Caudill, M.D., a member of the American Psychiatric Association's Committee on Telepsychiatry. “It's exploded in the past week, obviously,” he told CABL in a Zoom interview on March 23. But he thinks it should be the norm.

negative: Social Distancing During the COVID‐19 Pandemic: Who Are the Present and Future Non‐compliers? Social distancing is an effective means for containing the spread of COVID‐19, but only so if we all participate. Who are the individuals who are the least likely to adhere to social distancing recommendations, presently and in the long‐term? Such knowledge is important for policymakers looking to sustain the public's buy‐in to social distancing. Using survey data from sample U.S. residents (n = 1,449), we show that some demographic factors (gender, age, race, political party) help predict intent to adhere to social distancing. Yet demographic factors are relatively poor predictors compared to individual attitudes and media diets. We argue that public officials should make efforts to inform and persuade the public of the importance of social distancing, targeting mediums like TV and radio where audiences are less likely to currently engage in social distancing or are less likely to envision themselves sustaining strict social distancing for several weeks or months. This article is protected by copyright. All rights reserved.

negative: COVID-19: Projecting the impact in Rohingya refugee camps and beyond Background: COVID-19 could have even more dire consequences among refugees living in camps than in general populations. Bangladesh has confirmed COVID-19 cases and hosts almost 1 million Rohingya refugees from Myanmar with 600,000 concentrated in Kutupalong-Balukhali Expansion Site. Projections of the potential COVID-19 infection burden, epidemic speed, and healthcare needs in such settings are critical to inform preparedness planning. Methods: To explore the potential impact of the introduction of SARS-CoV-2 in Kutupalong-Balukhali Expansion Site, we used a stochastic disease transmission model with parameters derived from emerging literature. We considered three scenarios with different assumptions about the transmission potential of SARS-CoV-2. We estimated the number and daily rate of infections, hospitalizations, deaths, and healthcare needs expected under each scenario. Findings: A large-scale outbreak is highly likely after a single introduction of the virus into the camp across scenarios with 65-95% of simulations leading to at least 1,000 infections. Estimated infections range from 119-504 between low and high transmission scenarios in the first 30 days; and between 424,798 and 543,647 in 12 months. Hospitalization needs exceeded the existing hospitalization capacity of 340 beds after 58-139 days between the low and high transmission scenarios. Estimated deaths range from 1,647-2,109 between low and high transmission scenarios. Interpretation: A COVID-19 epidemic in a refugee settlement may have profound consequences, requiring unrealistically large increases in healthcare capacity and infrastructure. Detailed and realistic planning for the worst in Kutupalong-Balukhali and all refugee camps worldwide must begin now. Plans should consider novel and radical strategies to reduce infectious contacts and fill health worker gaps while recognizing that refugees may not have access to national health systems. As global resources to fight this pandemic become scarce, displaced persons must not be forgotten.

negative: Kallikrein 13: a new player in coronaviral infections Human coronavirus HKU1 (HCoV-HKU1) is associated with respiratory disease and is prevalent worldwide, but in vitro model for virus replication is lacking. Interaction between the coronaviral spike (S) protein and its receptor is the major determinant of virus tissue and host specificity, but virus entry is a complex process requiring a concerted action of multiple cellular elements. Here, we show that KLK13 is required for the infection of the human respiratory epithelium and is sufficient to mediate the entry of HCoV-HKU1 to non-permissive RD cells. We also demonstrated HCoV-HKU1 S protein cleavage by KLK13 in the S1/S2 region, proving that KLK13 is the priming enzyme for this virus. Summarizing, we show for the first time that protease distribution and specificity predetermines the tissue and cell specificity of the virus and may also regulate interspecies transmission. It is also of importance that presented data may be relevant for the emerging coronaviruses, including SARS-CoV-2 and may help to understand the differences in their zoonotic potential.

negative: A rate equation approach to model the denaturation or replication behavior of the SARS coronavirus As a newly emerging virus, little is known about the SARS coronavirus, whose outbreak has brought away several hundred people’s lives over the world in the year of 2003 and is seriously imperiling the human health. Revealing the denaturation and replication mechanisms of SARS coronavirus has great importance for successfully fighting SARS. However, experiments related to SARS coronavirus are extremely dangerous and therefore restricted only to certain specific labs with high safety standard. Clearly, predicting the behaviors of SARS coronavirus in a wide variety of environmental conditions, which are not easily accessible, are thus critically necessary. In this study, we proposed to quantify the survival time of SARS coronavirus either in vitro or in vivo, through introducing thermal rate process models established from the well-known Arrhenius law. The complex physical and chemical behaviors of the SARS coronavirus can then be attributed to its activation energy, frequency factor, damage function as well as the surrounding environmental conditions. Based on the first data on stability and resistance of SARS coronavirus measured by members of WHO laboratory network, the rate coefficients involved in the above equations were estimated for the first time. Predictions on the survival time of SARS coronavirus in different temperature scale were then performed. It was found theoretically that, such survival time falls in an extremely wide range, say from several seconds in high temperature to an almost infinitely long time in a low temperature environment, which has already or is being supported by the currently available tests data. Applications of the present theory to interpret several existing phenomena were presented and their implementations in developing new technical ways for SARS prevention and clinical therapy were discussed. Uncertainties involved in the theoretical models were also analyzed and predicted. Parametric studies were performed to test the effects of the rate coefficients to the survival time of SARS coronavirus. Some important factors, which can significantly vary the denaturation or replication process of SARS coronavirus were pointed out. Through regulating the parameters involved in the equation, certain potential therapies either through drug delivery or engineering approach to treat the SARS disease can possibly be established. Extension of the present model for further studies was also suggested. This study opens a new theoretical way for probing into the complex behaviors of SARS coronavirus. Modellierung der Denaturierung oder Repliziryng von SARS-Korona-Viren Zusammenfassung Der Kenntnisstand über die Eigenschaften des in 2003 neu aufgetretenen SARS Korona Virus, der einige Hundert Menschenleben gekostet hat, ist relativ gering. Die Ermittlung des Denaturierungs- und Replizierungsmechanismuses des SARS Virus ist für seine Bekämpfung von hoher Bedeutung. Experimentelle Untersuchungen an diesem extrem gefährlichen Virus dürfen nur durch Laboratorien mit einem hohen Sicherheitsstandard erfolgen. Die Vorhersage des Verhaltens des SARS Virus in unterschiedlichen Umgebungsbedingungen ist dabei erforderlich. In der vorliegenden Studie wird die überlebensdauer des Virus unter Labor- und realen Bedingungen durch Anwendung der bekannten Arrhenius-Beziehung für temperaturabhängige Vorgänge ermittelt. Das physikalische und chemische Verhalten des SARS Virus wird anhand der zugrundeliegenden Modell- Parameter beschrieben. Basierend auf den ersten Messungen von Mitgliedern des WHO-laboratory-network über die Stabilität und Widerstandsfähigkeit des Virus wurden erstmalig die Geschwindigkeitskoeffizienten des Berechnungsmodells bestimmt. Vorhersagen der Überlebensdauer des SARS-Virus unter unterschiedlichen Temperaturbedingungen wurden ausgeführt. Das sich hieraus ergebende, sehr unterschiedliche Ausmaß der Überlebensfähigkeit in Abhängigkeit der Umgebungstemperatur ist durch den Vergleich mit verfügbaren experimentellen Ergebnissen bestätigt worden. Die Anwendung der vorgestellten Modellierung zur Interpretation realer Phänomene und zur Entwicklung technischer Maßnahmen zur Vorbeugung und klinischen Therapierung von SARS wird diskutiert. Der Einfluß von Unsicherheiten des Modells wird analysiert und abgeschätzt. Parametrische Studien sind durchgeführt worden, um den Einfluß der Geschwindigkeitskoeffizienten auf die Überlebensdauer des SARS Virus darzustellen. Einige wichtige Einflußgrößen auf die Denaturierung und Replikationsfähigkeit des SARS Virus werden aufgezeigt. Durch eine Variation der Modellparameter kann die potentielle Wirksamkeit medikamentöser oder physikalischer Therapien abgeschätzt werden. Erweiterungsmöglichkeiten des vorgestellten Modells werden vorgeschlagen. Die vorliegende Studie ermöglicht neue, theoretische Vorgehensweisen zur Untersuchung des komplexen Verhaltensmusters des SARS Virus.

negative: La comunicación científica y el acceso abierto en la contención de enfermedades: El caso del Coronavirus novel 2019 (2019-nCoV)

negative: COVID-19, Australia: Epidemiology Report 14 (Reporting week to 23:59 AEST 3 May 2020) Confirmed cases in Australia notified up to 03 May 2020: notifications = 6,784; deaths = 89. The reduction in international travel and domestic movement, social distancing measures and public health action have likely slowed the spread of COVID-19 in Australia. Currently new notifications in Australia are mostly considered to be locally-acquired with some cases still reported among people with recent overseas travel. Most locally-acquired cases can be linked back to a confirmed case or known cluster, with a small portion unable to be epidemiologically linked to another case. The ratio of overseas-acquired cases to locally-acquired cases varies by jurisdiction. The crude case fatality rate (CFR) in Australia remains low (1.3%) compared to the World Health Organization's globally-reported rate (7.1%) and to other comparable high-income countries such as the United States of America (5.7%) and the United Kingdom (15.4%). The lower CFR in Australia is likely reflective of high case ascertainment including detection of mild cases. Internationally, cases continue to increase. The rates of increase have started to slow in several regions, although it is too soon to tell whether this trend will be sustained.

negative: Biopsychopharmacosocial approach to assess impact of social distancing and isolation on mental health in older adults. It is impossible to predict or comprehend the impact of the ongoing COVID-19 pandemic. The UK Government's advice for vulnerable people, including older adults, to move towards self-isolation and social distancing is likely to reduce rates of transmission, the risk of severe illness and the impact on the acute health services. Although justified and necessary, this process of isolation is likely to have a negative impact on the mental health of these vulnerable groups, especially older people. It will become increasingly important for community health professionals to assess subtle changes in older persons' mental health, as the duration of this period of isolation remains unclear. The biopsychopharmacosocial model provides one method of assessing mental health and planning health and social care needs. This article hopes to guide community health professionals through the specifics of this assessment model in relation to the growing COVID-19 pandemic.

negative: Sustaining the economy under partial lockdown: A pandemic centric approach As the world fights to contain and control the spread of the Novel Coronavirus, countries are imposing severe measures from restrictions on travel and social gatherings to complete lockdowns. Lockdowns, though effective in controlling the virus spread, leaves a massive economic impact. In a country like India with 21.9 % of its population below the poverty line, lockdowns have a direct impact on the livelihood of a large part of the population. Our approach conforms to healthcare and state practices of reducing human to human contact, by optimizing the lockdown strategy. We propose resuming economic activities while keeping healthcare facilities from being overwhelmed. We model the coronavirus pandemic as SEIR dynamic model for a set of states as nodes with certain population and analyze the model output before and after complete lockdown. Social distancing that people would willingly follow, in the no lockdown situation is modeled as being influenced with the knowledge of the current number of infection by imitating Granovetter threshold model. We then provide optimal lockdown policy solutions for the duration of ten weeks using NSGA-II optimization algorithm. While there are many studies that focus on modelling the transmission of COVID-19, ours is one of the few attempts to strike a balance between number of infections and economic operations.

negative: Novel Coronavirus (COVID-19) Knowledge and Perceptions: A Survey of Healthcare Workers Background: During the first week of March, the surge of coronavirus disease 2019 (COVID-19) cases reached over 100 countries with more than 100,000 cases. Healthcare authorities have already initiated awareness and preparedness activities beyond borders. A poor understanding of the disease among healthcare workers (HCWs) may result in delayed treatment and the rapid spread of infection. This study aimed to investigate the knowledge and perceptions of HCWs about COVID-19. Methods: A cross-sectional, web-based study was conducted among HCWs about COVID-19 during the first week of March 2020. A 23-item survey instrument was developed and distributed randomly to HCWs using social media; it required 5 minutes to complete. A chi-square test was used to investigate the level of association among variables at the significance level of p<0.05. Results: Of 529 participants, a total of 453 HCWs completed the survey (response rate: 85.6%); 51.6% were males, 32.1% were aged 25-34 years, and most were doctors (30.2%) and medical students (29.6%). Regarding COVID-19, most of the participants used social media to obtain information (61%), and a significant proportion of HCWs had poor knowledge of its transmission (61%) and symptom onset (63.6%) and showed positive perceptions of COVID-19 prevention and control. Factors such as age and profession were associated with inadequate knowledge and poor perception of COVID-19. Conclusion: As the global threat of COVID-19 continues to emerge, it is critical to improve the knowledge and perceptions of HCWs. Educational interventions are urgently needed to reach HCWs beyond borders, and further studies are warranted.

negative: Clinical Distancing and Mitigation of Coronavirus Disease 2019 Social distancing as a technique to limit transmission of infectious disease has come into common parlance following the arrival and rapid spread of a novel coronavirus disease around the world in 2019 and 2020. But in the face of an emerging pandemic threat, it is crucial that we start to apply these principles to the clinic, the emergency department, and the hospital ward. We propose that this dynamic situation calls for a parallel “Clinical Distancing” in which we as a medical culture go against many of our fundamental instincts and, at least in the short term, begin to reduce unnecessary patient-care contacts for the benefit of our patients and our ability to continue to provide care to those who need it most. In this commentary, we provide specific recommendations for the rapid implementation of clinical distancing techniques.

negative: Postdigital Brave New World and Its Educational Implications

negative: Analyzing situational awareness through public opinion to predict adoption of social distancing amid pandemic COVID‐19 COVID‐19 pandemic has affected over 100 countries in a matter of weeks. People's response toward social distancing in the emerging pandemic is uncertain. In this study, we evaluated the influence of information (formal and informal) sources on situational awareness of the public for adopting health‐protective behaviors such as social distancing. For this purpose, a questionnaire‐based survey was conducted. The hypothesis proposed suggests that adoption of social distancing practices is an outcome of situational awareness which is achieved by the information sources. Results suggest that information sources, formal (P = .001) and informal (P = 0.007) were found to be significantly related to perceived understanding. Findings also indicate that social distancing is significantly influenced by situational awareness, P = .000. It can, therefore, be concluded that an increase in situational awareness in times of public health crisis using formal information sources can significantly increase the adoption of protective health behavior and in turn contain the spread of infectious diseases.

negative: Lights and shadows of COVID-19, Technology and Industry 4.0 Scientific discoveries and technologies played a significant role in the digital revolution that occurred over the last years. But what is their role in the turmoil brought by the current pandemic? The aim of this paper is to show how digital technologies are operating during this first phase of the spreading of COVID-19. The study analyses and debates the current and potential role of digital technologies, focusing on their influence in the industrial and social fields. More specifically we used the blogging platform"Medium", which has seen an exponential growth in its production of articles over the last couple of months. Even if different from esteemed scientific sources, this platform provides a structure that suits our analysis. We searched how many times digital technologies are mentioned in articles regarding Coronavirus and, after collecting these articles, we collected page tags (comparable to"keywords"in scientific articles) and classified them (technology tags and non-technology tags), to create a graph showing the relation between them. This network allowed us to acknowledge and picture how technologies are currently debated. This was the starting point to discuss the key implications for an imminent future, and question about the impact on industry, society and labour market. What are the opportunities or threats of using technologies of Industry 4.0? Which are the needs rising because of the pandemic and how can technologies help in their fulfillment? How will the industrial scenario change after this pandemic? How will the labour market be affected? How can technologies be advantageous in the emerging social challenges?

negative: Annotation: The COVID-19 pandemic and clinical orthopaedic and trauma surgery Abstract This article provides a brief overview of the current COVID-19 pandemic crisis and the impact on trauma and orthopaedic surgeons. The principles of protect, avoid, restrict and abbreviate are recommended. Coordination of response, communication and support are also important. The versatility of orthopaedic surgeons lends them to having an important role.

negative: Lockdowns to Contain COVID-19 Increase Risk and Severity of Mosquito-Borne Disease Outbreaks Many countries are implementing lockdown measures to slow the COVID-19 pandemic, putting more than a third of the world's population under restrictions. The scale of such lockdowns is unprecedented, and while some effects of lockdowns are readily apparent, it is less clear what effects they may have on outbreaks of serious communicable diseases. We examine the impact of these lockdowns on outbreaks of mosquito-borne diseases. Using an agent-based model and simulations, we find that the risk and severity of such outbreaks is much greater under lockdown conditions, with the number of infected people doubling in some cases. This increase in number of cases varies by different mosquito-borne diseases, and is significantly higher for diseases spread by day-biting mosquitoes. We analysed various intervention strategies and found that during lockdowns, decentralised strategies such as insecticide-treated nets and indoor residual spraying are more effective than centralised strategies.

negative: Coronavirus questions that will not go away: interrogating urban and socio-spatial implications of COVID-19 measures The highly contagious coronavirus and the rapid spread of COVID-19 disease have generated a global public health crisis, which is being addressed at various local and global scales through social distancing measures and guidelines. This is coupled with debates about the nature of living and working patterns through intensive utilisation of information and telecommunication technologies, leading to the social and institutional acceptability of these patterns as the ‘new normal.’ The primary objective of this article is to instigate a discourse about the potential contribution of architecture and urban design and planning in generating knowledge that responds to pressing questions about future considerations of post pandemic architecture and urbanism. Methodologically, the discussion is based on a trans-disciplinary framework, which is utilised for conceptual analysis and is operationalized by identifying and discoursing design and planning implications. The article underscores relevant factors; originates insights for areas where future research will be critically needed, through key areas: a) Issues related to urban dynamics are delineated from the perspective of urban and human geography, urban design and planning, and transportation engineering; b) Questions that pertain to socio-spatial implications and urban space/ urban life dialectics stem from the field of environmental psychology; and c) Deliberations about new environments that accommodate new living/working styles supervene from ethnographical and anthropological perspectives. The article concludes with an outlook that captures key aspects of the needed synergy between architectural and urban education, research, and practice and public health in a post pandemic virtual and global world.

negative: A simulation model for policy decision analysis: a case of pandemic influenza on a university campus Pandemic influenza preparedness plans strongly focus on efficient mitigation strategies including social distancing, logistics and medical response. These strategies are formed by multiple decision makers before a pandemic outbreak and during the pandemic in local communities, states and nation-wide. In this paper, we model the spread of pandemic influenza in a local community, a university, and evaluate the mitigation policies. Since the development of an appropriate vaccine requires a significant amount of time and available antiviral quantities can only cover a relatively small proportion of the population, university decision makers will first focus on non-pharmaceutical interventions. These interventions include social distancing and isolation. The disease spread is modelled as differential equations-based compartmental model. The system is simulated for multiple non-pharmaceutical interventions such as social distancing including suspending university operations, evacuating dorms and isolation of infected individuals on campus. Although the model is built based on the preparedness plan of one of the biggest universities in the world, Arizona State University, it can easily be generalized for other colleges and universities. The policies and the decisions are tested by several simulation runs and evaluations of the mitigation strategies are presented in the paper.

negative: Mitigating disruptions, and scalability of radiation oncology physics work during the COVID-19 pandemic PURPOSE: The COVID-19 pandemic has led to disorder in work and livelihood of a majority of the modern world. In this work, we review its major impacts on procedures and workflow of clinical physics tasks, and suggest alternate pathways to avoid major disruption or discontinuity of physics tasks in the context of small, medium, and large radiation oncology clinics. We also evaluate scalability of medical physics under the stress of "social distancing". METHODS: Three models of facilities characterized by the number of clinical physicists, daily patient throughput, and equipment were identified for this purpose. For identical objectives of continuity of clinical operations, with constraints such as social distancing and unavailability of staff due to system strain, however with the possibility of remote operations, the performance of these models was investigated. General clinical tasks requiring on-site personnel presence or otherwise were evaluated to determine the scalability of the three models at this point in the course of disease spread within their surroundings. RESULTS: The clinical physics tasks within three models could be divided into two categories. The former, which requires individual presence, include safety-sensitive radiation delivery, high dose per fraction treatments, brachytherapy procedures, fulfilling state and nuclear regulatory commission's requirements, etc. The latter, which can be handled through remote means, include dose planning, physics plan review and supervision of quality assurance, general troubleshooting, etc. CONCLUSION: At the current level of disease in the United States, all three models have sustained major system stress in continuing reduced operation. However, the small clinic model may not perform if either the current level of infections is maintained for long or staff becomes unavailable due to health issues. With abundance, and diversity of innovative resources, medium and large clinic models can sustain further for physics-related radiotherapy services.

negative: Estimating the number of SARS-CoV-2 infections in the United States We apply a model developed by The COVID-19 Response Team [S. Flaxman, S. Mishra, A. Gandy, et al., ''Estimating the number of infections and the impact of non- pharmaceutical interventions on COVID-19 in 11 European countries,'' tech. rep., Imperial College London, 2020.] to estimate the total number of SARS-CoV-2 infections in the United States. Across the United States we estimate as of April 18, 2020 the fraction of the population infected was 4.6% [3.6%, 5.8%], 21 times the portion of the population with a positive test result. Excluding New York state, which we estimate accounts for over half of infections in the United States, we estimate an infection rate of 2.3% [2.1%, 2.8%]. We include the timing of each state's implementation of interventions including encouraging social distancing, closing schools, banning public events, and a lockdown / stay-at-home order. We assume fatalities are reported correctly and infer the number and timing of infections based on the infection fatality rate measured in populations that were tested universally for SARS-CoV-2. Underreporting of deaths would drive our estimates to be too low. Reporting of deaths on the wrong day could drive errors in either direction. This model does not include effects of herd immunity; in states where the estimated infection rate is very high - namely, New York - our estimates may be too high.

negative: Time to Leverage Health System Collaborations: Supporting Nursing Facilities Through the COVID-19 Pandemic

negative: Early impact of the COVID-19 pandemic and social distancing measures on routine childhood vaccinations in England, January to April 2020 Electronic health records were used to assess the early impact of COVID-19 on routine childhood vaccination in England to 26 April 2020. MMR vaccination counts fell from February 2020, and in the three weeks after introduction of social distancing measures were 19.8% lower (95% CI -20.7 to -18.9%) than the same period in 2019, before improving in mid-April. A gradual decline in hexavalent vaccination counts throughout 2020 was not accentuated on introduction of social distancing.

negative: The socio-economic determinants of the coronavirus disease (COVID-19) pandemic The magnitude of the coronavirus disease (COVID-19) pandemic has an enormous impact on the social life and the economic activities in almost every country in the world. Besides the biological and epidemiological factors, a multitude of social and economic criteria also govern the extent of the coronavirus disease spread in the population. Consequently, there is an active debate regarding the critical socio-economic determinants that contribute to the resulting pandemic. In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 35 determinants, describing a diverse set of socio-economic characteristics, in explaining the coronavirus pandemic outcome.

negative: The impossibility of social distancing among the urban poor: the case of an Indian slum in the times of COVID-19 As cases of COVID-19 were rising in India and the country’s political leadership instituted a nationwide lockdown, one of the authors of this article received a timely invitation from a friend–a government official–to make rounds with him and his team to various neighbourhoods within the metropolitan city of Bangalore. The team consisted of members working in healthcare, municipal corporation, and local police, and was tasked with ensuring that the government enacted measures of social distancing were being observed by local residents in public spaces. The author witnessed, in real time, the ways in which residents were engaging with the containment measures that were instituted as part of the political leadership’s attempt to flatten the curve of COVID-19. What was observed in an urban slum was particularly poignant and illuminating. The observations captured how, for residents of the urban slum, social distancing is more an aspiration than an attainable reality. Indeed, social distancing is impossible if such a protocol does not come with concomitant economic support targeted to the most socially vulnerable in society.

negative: Impact of Disasters and Disaster Risk Management in Singapore: A Case Study of Singapore’s Experience in Fighting the SARS Epidemic Singapore is vulnerable to both natural and man-made disasters alongside its remarkable economic growth. One of the most significant disasters in recent history was the Severe Acute Respiratory Syndrome (SARS) epidemic in 2003. The SARS outbreak was eventually contained through a series of risk mitigating measures introduced by the Singapore government. This would not be possible without the engagement and responsiveness of the general public. This chapter begins with a description of Singapore’s historical disaster profiles, the policy and legal framework in the all-hazard management approach. We use a case study to highlight the disaster impacts and insights drawn from Singapore’s risk management experience with specific references to the SARS epidemic. The implications from the SARS focus on four areas: staying vigilant at the community level, remaining flexible in a national command structure, the demand for surge capacity, and collaborative governance at regional level. This chapter concludes with a presence of the flexible command structure on both the way and the extent it was utilized.

negative: Playing into Stereotypes: Engaging Millennials and Generation Z in the COVID-19 Pandemic Response

negative: Community responses during the early phase of the COVID-19 epidemic in Hong Kong: risk perception, information exposure and preventive measures Background: Community responses are important for outbreak management during the early phase when non-pharmaceutical interventions are the major preventive options. Therefore, this study aims to examine the psychological and behavioral responses of the community during the early phase of the COVID-19 epidemic in Hong Kong. Method: A cross-sectional online survey was launched within 36 hours after confirmed COVID-19 cases were first reported. Councilors of all 452 district council constituency areas were approached for survey dissemination. Respondent demographics, anxiety level, risk perception, sources to retrieve COVID-19 information, actual adoption and perceived efficacy of precautionary measures were collected. Result: Analysis from 1715 complete responses indicated high perceived susceptibility (89%) and high perceived severity (97%). Most respondents were worried about COVID-19 (97%), and had their daily routines disrupted (slightly/greatly: 98%). The anxiety level, measured by the Hospital Anxiety and Depression Scale, was borderline abnormal (9.01). Nearly all respondents were alert to the disease progression (99.5%). The most trusted information sources were doctors (84%), followed by broadcast (57%) and newspaper (54%), but they were not common information sources (doctor: 5%; broadcast: 34%; newspaper: 40%). Only 16% respondents found official websites reliable. Enhanced personal hygiene practices and travel avoidance to China were frequently adopted (>77%) and considered effective (>90%). The adoption of social-distancing measures was lower (39%-88%), and their drivers for greater adoption include: being female (adjusted odds ratio [aOR]:1.27), living in the New Territories (aOR:1.32-1.55), perceived as having good understanding of COVID-19 (aOR:1.84) and being more anxious (aOR:1.07). Discussion: Risk perception towards COVID-19 in the community was high. Most respondents are alert to the disease progression, and adopt self-protective measures. This study contributes by examining the psycho-behavioral responses of hosts, in addition to the largely studied mechanistic aspects, during the early phase of the current COVID-19 epidemic. The timely psychological and behavioral assessment of the community is useful to inform subsequent interventions and risk communication strategies as the epidemic progresses.

negative: COVID-19 and pets: When pandemic meets panic Abstract As the novel coronavirus outbreak spreads globally with devastating effects on human health, pets are also becoming unnecessary victims amidst the pandemic panic. Many have been reluctantly left home alone by owners who have been forced to temporarily evacuate their homes. And, although no evidence exists to indicate that they can either transmit the virus or develop its associated coronavirus disease 2019 (COVID-19), fear among the public that pets might play a role in spreading COVID-19 has resulted in pets being abandoned or even killed. This article outlines some of the ways in which the current pandemic has negatively impacted the welfare of pets. It also highlights the relationships between animal, human, and environmental health, as well as the importance of taking a collaborative transdisciplinary One Health approach to help prevent future COVID-19 outbreaks.

negative: Experimental Treatment with Favipiravir for COVID-19: An Open-Label Control Study Abstract An outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and its caused coronavirus disease 2019 (COVID-19) has been reported in China since December 2019. More than 16% of patients developed acute respiratory distress syndrome, and the fatality ratio was about 1%–2%. No specific treatment has been reported. Herein, we examine the effects of Favipiravir (FPV) versus Lopinavir (LPV)/ritonavir (RTV) for the treatment of COVID-19. Patients with laboratory-confirmed COVID-19 who received oral FPV (Day 1: 1600 mg twice daily; Days 2–14: 600 mg twice daily) plus interferon (IFN)-α by aerosol inhalation (5 million U twice daily) were included in the FPV arm of this study, whereas patients who were treated with LPV/RTV (Days 1–14: 400 mg/100 mg twice daily) plus IFN-α by aerosol inhalation (5 million U twice daily) were included in the control arm. Changes in chest computed tomography (CT), viral clearance, and drug safety were compared between the two groups. For the 35 patients enrolled in the FPV arm and the 45 patients in the control arm, all baseline characteristics were comparable between the two arms. A shorter viral clearance time was found for the FPV arm versus the control arm (median (interquartile range, IQR), 4 (2.5–9) d versus 11 (8–13) d, P < 0.001). The FPV arm also showed significant improvement in chest imaging compared with the control arm, with an improvement rate of 91.43% versus 62.22% (P = 0.004). After adjustment for potential confounders, the FPV arm also showed a significantly higher improvement rate in chest imaging. Multivariable Cox regression showed that FPV was independently associated with faster viral clearance. In addition, fewer adverse reactions were found in the FPV arm than in the control arm. In this open-label nonrandomized control study, FPV showed significantly better treatment effects on COVID-19 in terms of disease progression and viral clearance; if causal, these results should be important information for establishing standard treatment guidelines to combat the SARS-CoV-2 infection.

negative: COVID-19, Australia: Epidemiology Report 16 (Reporting week to 23:59 AEST 17 May 2020). Confirmed cases in Australia notified up to 17 May 2020: notifications = 7,075; deaths = 100. The incidence of new cases of COVID-19 has reduced dramatically since a peak in mid-March. Social distancing measures, public health action and the reduction in international travel have likely been effective in slowing the spread of the disease, in the Australian community. Testing rates over the past week have increased markedly, with a continued very low proportion of people testing positive. These low rates of detection are indicative of low levels of COVID-19 transmission. It is important that testing rates and community adherence to public health measures remain high to support the continued suppression of the virus, particularly in vulnerable high-risk groups and settings. New cases of COVID-19 are currently being reported by by only some jurisdictions, albeit at relatively low rates. Although case numbers are low, new cases tend to still be a mix of overseas-acquired and locally-acquired infections. Most locally-acquired cases can be linked back to a known case or cluster. Although the proportion of locally-acquired cases has increased, the overall rate of new cases, regardless of place of acquisition, continues to decrease. The crude case fatality rate in Australia remains low (1.4%), compared with the WHO reported global rate (6.9%). The low case fatality rate is likely reflective of high case detection and high quality of health care services in Australia. Deaths from COVID-19 in Australia have occurred predominantly among the elderly and those with comorbidities, with no deaths occurring in those under 40 years. The highest rate of COVID-19 continues to be among people aged 60-79 years. One third of all cases in this age group have been associated with several outbreaks linked to cruise ships. The lowest rate of disease is in young children, a pattern reflected in international reports. Internationally, while the number of new cases each day remains relatively stable at the global level, some areas such as Brazil and India are showing a dramatic rise in reported cases. Although some low-income countries have so far reported few cases, it is possible that this is due to limited diagnostic and public health capacity, and may not be reflective of true disease incidence.

negative: The passage of time during the UK Covid-19 lockdown. In March 2020, in response to the Covid-19 pandemic, the UK Government imposed social and physical distancing measures on the population. These lockdown measures caused significant changes to all aspects of daily life. The current study examined how the passage of time was distorted during the lockdown period. Using an online questionnaire, day and week passage of time judgments were collected. In addition, measures of affect, task load and satisfaction with current levels of social interaction were taken. The results show that over 80% of participants experienced distortion to the passage of time during lockdown in comparison with normal. The passage of time during the day was predicted by age, stress, task load and satisfaction with current levels of social interaction. A slowing of the passage of time was associated with increasing age, increasing stress, reduced task load and reduced satisfaction with current levels of social interaction. Only age and satisfaction with current levels of social interaction predicted passage of time across a week. Again, increasing age and reduced satisfaction with levels of social interaction were associated with a slowing of the passage of time. These findings demonstrate that significant changes to daily life have a significant impact on our experience of time, with younger, more socially satisfied people more likely to experience time as passing more quickly during the lockdown.

negative: The SARS-CoV-2 pandemic impact on rhinology research: A survey of the American Rhinologic Society BACKGROUND: The COVID-19 pandemic has radically shifted healthcare operations within hospitals and universities across the globe. However, the effect of the COVID-19 pandemic on research endeavors and clinical trials is unclear. OBJECTIVE: This study investigates the impact of the COVID-19 pandemic on basic science and clinical research within the rhinology community. METHODS: A cross-sectional study was designed utilizing an 8-question survey to identify changes to rhinology research. Questions evaluated the impact of the COVID-19 pandemic on administrative research support and staffing, basic science research, clinical trials and resident research involvement. RESULTS: Seventy-one participants responded to the survey (8.5% response rate). Most respondents noted changes in IACUC/IRB approval (faster, 33%; slower, 31%). Of those who employed laboratory personnel, 64% were able to continue staff employment with full salary. The majority of animal research and in vitro studies were halted (64% and 56%, respectively), but animal care and cell line maintenance were allowed to continue. Clinical trial enrollment was most commonly limited to COVID derived studies (51%). Forty-seven percent of respondents noted increased resident research participation. CONCLUSION: The rapid spread of the SARS-CoV-2 virus has markedly impacted rhinology-related research. Maintaining safe workplace practices as restrictions are lifted will hopefully mitigate the spread of the virus and allow research productivity to resume.

negative: Modelling the propagation of social response during a disease outbreak. Epidemic trajectories and associated social responses vary widely between populations, with severe reactions sometimes observed. When confronted with fatal or novel pathogens, people exhibit a variety of behaviours from anxiety to hoarding of medical supplies, overwhelming medical infrastructure and rioting. We developed a coupled network approach to understanding and predicting social response. We couple the disease spread and panic spread processes and model them through local interactions between agents. The social contagion process depends on the prevalence of the disease, its perceived risk and a global media signal. We verify the model by analysing the spread of disease and social response during the 2009 H1N1 outbreak in Mexico City and 2003 severe acute respiratory syndrome and 2009 H1N1 outbreaks in Hong Kong, accurately predicting population-level behaviour. This kind of empirically validated model is critical to exploring strategies for public health intervention, increasing our ability to anticipate the response to infectious disease outbreaks.

negative: Impacts of Social and Economic Factors on the Transmission of Coronavirus Disease 2019 (COVID-19) in China This paper examines the role of various socioeconomic factors in mediating the local and cross-city transmissions of the novel coronavirus 2019 (COVID-19) in China. We implement a machine learning approach to select instrumental variables that strongly predict virus transmission among the rich exogenous weather characteristics. Our 2SLS estimates show that the stringent quarantine, massive lockdown and other public health measures imposed in late January significantly reduced the transmission rate of COVID-19. By early February, the virus spread had been contained. While many socioeconomic factors mediate the virus spread, a robust government response since late January played a determinant role in the containment of the virus. We also demonstrate that the actual population flow from the outbreak source poses a higher risk to the destination than other factors such as geographic proximity and similarity in economic conditions. The results have rich implications for ongoing global efforts in containment of COVID-19.

negative: The COVID-19 Pandemic and its Impact on Substance Use: Implications for Prevention and Treatment The COVID-19 pandemic has brought major challenges to healthcare systems and public health policies globally, as it requires novel treatment and prevention strategies to adapt for the impact of the pandemic. Individuals with substance user disorders (SUD) are at risk population for contamination due to multiple factors – attributable to their clinical, psychological and psychosocial conditions. Moreover, social and economic changes caused by the pandemic, along with the traditional difficulties regarding treatment access and adherence – will certainly worsen during this period, therefore aggravate their condition. In addition, this population are potential vectors of transmission. In that sense, specific strategies for prevention and treatment must be discussed. health care professionals dealing with SUD must be aware of the risks and challenges they will meet during and after the COVID-19 outbreak. Addiction care must be reinforced, instead of postponed, in order to avoid complications of both SUD and COVID-19 and to prevent the transmission of coronavirus.

negative: The Impact of Social Media on Panic During the COVID-19 Pandemic in Iraqi Kurdistan: Online Questionnaire Study BACKGROUND: In the first few months of 2020, information and news reports about the coronavirus disease (COVID-19) were rapidly published and shared on social media and social networking sites. While the field of infodemiology has studied information patterns on the Web and in social media for at least 18 years, the COVID-19 pandemic has been referred to as the first social media infodemic. However, there is limited evidence about whether and how the social media infodemic has spread panic and affected the mental health of social media users. OBJECTIVE: The aim of this study is to determine how social media affects self-reported mental health and the spread of panic about COVID-19 in the Kurdistan Region of Iraq. METHODS: To carry out this study, an online questionnaire was prepared and conducted in Iraqi Kurdistan, and a total of 516 social media users were sampled. This study deployed a content analysis method for data analysis. Correspondingly, data were analyzed using SPSS software. RESULTS: Participants reported that social media has a significant impact on spreading fear and panic related to the COVID-19 outbreak in Iraqi Kurdistan, with a potential negative influence on people’s mental health and psychological well-being. Facebook was the most used social media network for spreading panic about the COVID-19 outbreak in Iraq. We found a significant positive statistical correlation between self-reported social media use and the spread of panic related to COVID-19 (R=.8701). Our results showed that the majority of youths aged 18-35 years are facing psychological anxiety. CONCLUSIONS: During lockdown, people are using social media platforms to gain information about COVID-19. The nature of the impact of social media panic among people varies depending on an individual's gender, age, and level of education. Social media has played a key role in spreading anxiety about the COVID-19 outbreak in Iraqi Kurdistan.

negative: Exploring the Determinants of Perceived Risk of Middle East Respiratory Syndrome (MERS) in Korea The world is turning into a risky society. Although modernization based on the developments in science and technology has increased individuals’ well-being and wealth, the perceived risk toward the complex technological system has increased. In a risky society, social accidents amplify the existing fear among individuals. It is generally assumed that each value, perception, and resource influences the fear of risk. However, very few studies have tested these three factors together within an integrated causal model. Therefore, the present study aimed to examine the determinants that influence the perceived risk in cases of Middle East Respiratory Syndrome (MERS), a deadly epidemic disease, in Korea. Based on the theoretical model, we analyzed the survey data collected from respondents (N = 814) in Korea. After controlling for variables such as sociodemographic characteristics, we examined how three competing factors, i.e., value, perception, and resource, influence the perceived risk of MERS. The analysis showed that trust and vulnerability variables in the perception factor, health state, and perceived knowledge in the resource factor had a significant impact on the perceived risk of MERS.

negative: Discovering drugs to treat coronavirus disease 2019 (COVID-19). The SARS-CoV-2 virus emerged in December 2019 and then spread rapidly worldwide, particularly to China, Japan, and South Korea. Scientists are endeavoring to find antivirals specific to the virus. Several drugs such as chloroquine, arbidol, remdesivir, and favipiravir are currently undergoing clinical studies to test their efficacy and safety in the treatment of coronavirus disease 2019 (COVID-19) in China; some promising results have been achieved thus far. This article summarizes agents with potential efficacy against SARS-CoV-2.

negative: New approximations, and policy implications, from a delayed dynamic model of a fast pandemic We study an SEIQR (Susceptible-Exposed-Infectious-Quarantined-Recovered) model for an infectious disease, with time delays for latency and an asymptomatic phase. For fast pandemics where nobody has prior immunity and everyone has immunity after recovery, the SEIQR model decouples into two nonlinear delay differential equations (DDEs) with five parameters. One parameter is set to unity by scaling time. The subcase of perfect quarantining and zero self-recovery before quarantine, with two free parameters, is examined first. The method of multiple scales yields a hyperbolic tangent solution; and a long-wave approximation yields a first order ordinary differential equation (ODE). With imperfect quarantining and nonzero self-recovery, the long-wave approximation is a second order ODE. These three approximations each capture the full outbreak, from infinitesimal initiation to final saturation. Low-dimensional dynamics in the DDEs is demonstrated using a six state non-delayed reduced order model obtained by Galerkin projection. Numerical solutions from the reduced order model match the DDE over a range of parameter choices and initial conditions. Finally, stability analysis and numerics show how correctly executed time-varying social distancing, within the present model, can cut the number of affected people by almost half. Alternatively, faster detection followed by near-certain quarantining can potentially be even more effective.

negative: A Multicentre Study of 2019 Novel Coronavirus Disease Outcomes of Cancer Patients in Wuhan, China Background: At present, there is a global pandemic of coronavirus disease 2019 (COVID-19) pneumonia. Two previous case series from China have suggested that cancer patients are at a higher risk of COVID-19 pneumonia, but the reports were limited by small numbers and few clinical information. Objective: To study clinical characteristics and outcomes of cancer patients infected with COVID-19. Design: Retrospective study. Setting: Four designated COVID-16 hospitals in Wuhan, Hubei province, China. Participants: Medical records of 67 cancer patients admitted to hospitals between Jan 5, 2020 to Feb 18, 2020 were included. Measurements: Demographic, clinical, laboratory, radiological and treatment data were collected. Survival data of the cohort was cut-off on Mar 10, 2020. Results: Of the 67 patients (median age: 66 years), the median age of patients who had severe illness was older than that of patients who had mild symptoms (P<0.001). Forty-three (64.2%) patients had other concurrent chronic diseases, and the proportion of severe patients had co-morbidities was higher than patients with mild disease (P=0.004). Twenty-three (34.3%) patients were still at the anticancer treatment phase, but no tumour progression and recurrence was observed for all the patients during the treatment of COVID-19 pneumonia. About 70% of these patients had fever (n=53, 79.1%) and/or cough (n=50, 74.6%). Lymphocytopenia was the main laboratory finding accompanying increased C-reactive protein and procalcitonin in cancer patients, especially in severe cases. By Mar 10, 2020, 18 (26.9%) patients died from COVID-19, and 39 (58.2%) patients have been discharged. The median age of survivors was younger than that of deaths (P=0.014). Lung cancer (n=15, 22.4%) with COVID-19 was the most common cancer type and accounted for the highest proportion COVID-19 resulted deaths (33.3%, 5/15). We observed a tendency that patients at the follow-up phase had a better prognosis than that at anticancer treatment phase (P=0.095). Limitation: This is a retrospective study with only 67 cases from four hospitals. And some specific clinical information was insufficient. Conclusion: This study showed COVID-19 patients with cancer seem to have a higher proportion of severe cases and poorer prognosis. The tendency of poor prognosis was more obvious in patients at anticancer treatment phase. We should pay more intensive attentions to cancer patients infected with COVID-19.

negative: Understanding the COVID19 Outbreak: A Comparative Data Analytics and Study The Coronavirus, also known as the COVID-19 virus, has emerged in Wuhan China since late November 2019. Since that time, it has been spreading at large-scale until today all around the world. It is currently recognized as the world's most viral and severe epidemic spread in the last twenty years, as compared to Ebola 2014, MERS 2012, and SARS 2003. Despite being still in the middle of the outbreak, there is an urgent need to understand the impact of COVID-19. The objective is to clarify how it was spread so fast in a short time worldwide in unprecedented fashion. This paper represents a first initiative to achieve this goal, and it provides a comprehensive analytical study about the Coronavirus. The contribution of this paper consists in providing descriptive and predictive models that give insights into COVID-19 impact through the analysis of extensive data updated daily for the outbreak in all countries. We aim at answering several open questions: How does COVID-19 spread around the world? What is its impact in terms of confirmed and death cases at the continent, region, and country levels? How does its severity compare with other epidemic outbreaks, including Ebola 2014, MERS 2012, and SARS 2003? Is there a correlation between the number of confirmed cases and death cases? We present a comprehensive analytics visualization to address the questions mentioned above. To the best of our knowledge, this is the first systematic analytical papers that pave the way towards a better understanding of COVID-19. The analytical dashboards and collected data of this study are available online [1].

negative: In-store epidemic behavior: scale development and validation Epidemics of infectious diseases have accompanied humans for a long time and, depending on the scale, cause various undesirable social and economic consequences. During the ongoing COVID-19 pandemic, governments of many countries impose restrictions to inhibit spreading of infection. Isolation and limiting interpersonal contacts are particularly recommended actions. Adhering to the rule of isolation may involve restrictions in freedom during daily activities, such as shopping. The aim of the study was to develop a scale of in-store pandemic behavior. The whole process involved 3 stages: qualitative inquiry, scale purification and scale validation, which were based on 3 studies: 1 qualitative (20 in-depth interviews) 2 two quantitative (373 and 584 respondents, respectively), and allowed to identify 8 factors. Following, a theoretical model was created to investigate the impact of in-store infection threat on identified variables. All identified factors significantly correlated with the in-store infection threat which reiterates the importance of providing information revealing the true scale of the pandemic and not leaving space for individuals to create subjective probability judgments. The developed scale can help counteract disinformation and assess consumer behavior compliance and understanding of the official recommendations imposed by governments, enabling more efficient educational efforts.

negative: Spatial Visualization of Cluster-Specific COVID-19 Transmission Network in South Korea During the Early Epidemic Phase Background Coronavirus disease 2019 (COVID-19) has been rapidly spreading throughout China and other countries including South Korea. As of March 12, 2020, a total number of 7,869 cases and 66 deaths had been documented in South Korea. Although the first confirmed case in South Korea was identified on January 20, 2020, the number of confirmed cases showed a rapid growth on February 19, 2020 with a total number of 1,261 cases with 12 deaths based on the Korea Centers for Disease Control and Prevention (KCDC). Method Using the data of confirmed cases of COVID-19 in South Korea that are publicly available from the KCDC, this paper aims to create spatial visualizations of COVID-19 transmission between January 20, 2020 and February 19, 2020. Results Using spatial visualization, this paper identified two early transmission clusters in South Korea (Daegu cluster and capital area cluster). Using a degree-weighted centrality measure, this paper proposes potential super-spreaders of the virus in the visualized clusters. Conclusion Compared to various epidemiological measures such as the basic reproduction number, spatial visualizations of the cluster-specific transmission networks and the proposed centrality measure may be more useful to characterize super-spreaders and the spread of the virus especially in the early epidemic phase.

negative: Impact of mitigating interventions and temperature on the instantaneous reproduction number in the COVID-19 epidemic among 30 US metropolitan areas Background: After more than three months into the coronavirus disease (COVID-19) epidemic, over 170,000 people had died worldwide. The current study aims to evaluate how mitigating interventions affected the epidemic process in the 30 largest metropolitan areas in the US and whether temperature played a role in the epidemic process. Methods: Publicly available COVID-19 cases and deaths data and weather data were analyzed at the metropolitan level. The time-varying reproductive numbers were used to explore the trends. Results: We found that virus transmissibility, measured by instantaneous reproduction number (Rt), had declined significantly since the end of March for all areas and almost all of them reached a Rt of 1 or below by April 15, 2020. Cities with warm temperature tended to have a lower peak Rt than that of cities with cold temperature. However, large geographic variations exist. Conclusions: Though the end of epidemic of COVID-19 is near, temperature may have some weak effects on the virus transmission, and the return of the coronavirus outbreak is still possible.

negative: Generalized logistic growth modeling of the COVID-19 outbreak in 29 provinces in China and in the rest of the world Background: the COVID-19 has been successfully contained in China but is spreading all over the world. We use phenomenological models to dissect the development of the epidemics in China and the impact of the drastic control measures both at the aggregate level and within each province. We use the experience from China to analyze the calibration results on Japan, South Korea, Iran, Italy and Europe, and make future scenario projections. Methods: we calibrate the logistic growth model, the generalized logistic growth model, the generalized growth model and the generalized Richards model to the reported number of infected cases from Jan. 19 to March 10 for the whole of China, 29 provinces in China, four severely affected countries and Europe as a whole. The different models provide upper and lower bounds of our scenario predictions. Results: We quantitatively document four phases of the outbreak in China with a detailed analysis on the heterogenous situations across provinces. Based on Chinese experience, we identify a high risk in Japan with estimated total confirmed cases as of March 25 being 1574 (95% CI: [880, 2372]), and 5669 (95% CI: [988, 11340]) by June. For South Korea, we expect the number of infected cases to approach the ceiling, 7928 (95% CI: [6341, 9754]), in 20 days. We estimate 0.15% (95% CI: [0.03%, 0.30%]) of Italian population to be infected in a positive scenario. We would expect 114867 people infected in Europe in 10 days, in a negative but probable scenario, corresponding to 0.015% European population. Conclusions: The extreme containment measures implemented by China were very effective with some instructive variations across provinces. For other countries, it is almost inevitable to see the continuation of the outbreak in the coming months. Japan and Italy are in serious situations with no short-term end to the outbreak to be expected. There is a significant risk concerning the upcoming July 2020 Summer Olympics in Tokyo. Iran's situation is highly uncertain with unclear and negative future scenarios, while South Korea is approaching the end of the outbreak. Both Europe and the USA are at early stages of the outbreak, posing significant health and economic risks to the world in absence of serious measures.

negative: COVID-19 and Bangladesh: Challenges and How to Address Them As the coronavirus outbreak quickly surges worldwide, many countries are adopting non-therapeutic preventive measures, which include travel bans, remote office activities, country lockdown, and most importantly, social distancing. However, these measures face challenges in Bangladesh, a lower-middle-income economy with one of the world's densest populations. Social distancing is difficult in many areas of the country, and with the minimal resources the country has, it would be extremely challenging to implement the mitigation measures. Mobile sanitization facilities and temporary quarantine sites and healthcare facilities could help mitigate the impact of the pandemic at a local level. A prompt, supportive, and empathic collaboration between the Government, citizens, and health experts, along with international assistance, can enable the country to minimize the impact of the pandemic.

negative: The Impact of School Closure for COVID-19 on the US Healthcare Workforce and the Net Mortality Effects Background COVID-19 is leading to the implementation of social distancing policies around the world and in the United States, including school closures. The evidence that mandatory school closures reduce cases and ultimately mortality mostly comes from experience with influenza or from models that do not include the impact of school closure on the healthcare labor supply or the role of the healthcare labor force in reducing the per infection mortality from the pathogen. There is considerable uncertainty of the incremental effect of school closures on transmission and lives saved from school closures. The likely, but uncertain, benefits from school closure need to be weighed against uncertain, and seldom quantified, costs of healthcare worker absenteeism associated with additional child care obligations. Methods We analyze data from the US Current Population Survey to measure the potential child care obligations for US healthcare workers that will need to be addressed if school closures are employed as a social distancing measure. We account for the occupation within the healthcare sector, state, and household structure to identify the segments of the healthcare labor force that are most exposed to child care obligations from school closures. We use these estimates to identify the critical level for the importance of healthcare labor supply in increasing a patient's COVID-19 survival probability that would undo the benefits of school closures and ultimately increase cumulative mortality. Findings The US healthcare sector has some of the highest child care obligations in the United States. 29% of healthcare provider households must provide care for children 3-12. Assuming non-working adults or a sibling 13 years old or older can provide child care, leaves 15% of healthcare provider households in need of childcare during a school closure, while 7% of healthcare households are single-parent households. We document the substantial variation within the healthcare system. For example, 35% of medical assistants and 31% of nursing, psychiatric, and home health aide households have child care obligations, while only 24% of emergency medical personnel have childcare obligations. Child care obligations can vary between states by over 10 percentage points. A 15% decline in the healthcare labor force, combined with reasonable parameters for COVID-19 such as a 15% case reduction from school closings and 2% baseline mortality rate implies that a 15% loss in the healthcare labor force must decrease the survival probability per percent healthcare worker lost by 17.6% for a school closure to increase cumulative mortality. This means that the per infection mortality rate cannot increase from 2% to 2.35% when the healthcare workforce declines by 15%; otherwise, school closures will lead to a greater number of deaths than they prevent. For school closures to unambiguously provide a net reduction in COVID-19 mortality with these parameters, the school closures must reduce cases by over 25%. Conclusion School closures come with many tradeoffs. Setting aside economic costs, school closures implemented to reduce COVID-19 spread create unintended childcare obligations, which are particularly large in healthcare occupations. Detailed data are provided to help public health officials make informed decisions about the tradeoffs associated with closing schools. The results suggest that it is unclear if the potential contagion prevention from school closures justifies the potential loss of healthcare workers from the standpoint of reducing cummulative mortality.

negative: Consequences of physical distancing emanating from the COVID-19 pandemic: An australian perspective The sobering reality of the COVID-19 pandemic is that it has brought people together at home at a time when we want them apart in the community. This will bring both benefits and challenges. It will affect people differently based upon their age, health status, resilience, family support structures, and socio-economic background. This article will assess the impact in high income countries like Australia, where the initial wave of infection placed the elderly at the greatest risk of death whilst the protective measures of physical distancing, self-isolation, increased awareness of hygiene practices, and school closures with distance learning has had considerable impact on children and families acutely and may have ramifications for years to come.

negative: Adolescents’ Motivations to Engage in Social Distancing during the COVID-19 Pandemic: Associations with Mental and Social Health Abstract Purpose Reducing the spread of infection during the COVID-19 pandemic prompted recommendations for individuals to socially distance. Little is known about the extent to which youth are socially distancing, what motivations underlie their social distancing, and how these motivations are connected with amount of social distancing, mental health, and social health. Using a large sample of adolescents from across the US, this study examined adolescents’ motivations for social distancing, their engagement in social distancing, and their mental and social health. Methods Data were collected March 29th and 30th 2020, two-weeks after COVID-19 was declared a national emergency in the US. The sample consisted of 683 adolescents recruited using social media. A series of multiple linear regressions examined unique associations among adolescents’ motivations to engage in social distancing, perceived amount of social distancing, anxiety symptoms, depressive symptoms, burdensomeness, and belongingness. Results Almost all respondents (98.1%) reported engaging in at least a little social distancing. The most commonly reported motivations for social distancing concerned social responsibility and not wanting others to get sick. Motivations concerning state or city lockdowns, parental rules, and social responsibility were associated with greater social distancing, whereas motivations concerning no alternatives were associated with less social distancing. Specific motivations for social distancing were differentially associated with adolescents’ anxiety symptoms, depressive symptoms, burdensomeness, and belongingness. Conclusions Understanding adolescents’ motivations to engage in social distancing may inform strategies to increase social distancing engagement, reduce pathogen transmission, and identify individual differences in mental and social health during the COVID-19 pandemic.

negative: Impact of essential workers in the context of social distancing for epidemic control Many governments have responded to the ongoing COVID-19 pandemic by imposing social policies that restrict interactions outside of the home, resulting in a large fraction of the workforce either working from home or not working. However, to maintain essential services, a substantial number of workers are not subject to these limitations, and maintain many of their pre-intervention interactions. To explore how interactions among such "essential" workers, and between essential workers and the rest of the population, impact disease risk and the effectiveness of pandemic control, we evaluated several models of essential worker interactions within a standard epidemiology framework. The models were designed to correspond to key characteristics of, respectively, cashiers, factory employees, and healthcare workers. We find in all three models that essential workers are at substantially elevated risk of infection compared to the rest of the population, and that increasing the numbers of essential workers necessitates the imposition of more stringent interaction controls on the rest of the population in order to manage the pandemic. However, different archetypes of essential workers differ in both their individual probability of infection and impact on the broader pandemic, highlighting the need to understand and target for intervention the specific risks faced by different groups of essential workers.

negative: Correlates of symptoms of anxiety and depression and mental wellbeing associated with COVID-19: a cross-sectional study of UK-based respondents BACKGROUND: The aim was to assess the impact of COVID-19 self-isolation/social distancing on mental health, and potential correlates, among a sample of the UK population. METHODS: A cross-sectional study. Mental health was measured using the Beck Anxiety and Depression Inventory. Mental wellbeing was measured using The Short Warwick-Edinburgh Mental Well-being Scale. Data collected on predictors included sex, age, marital status, employment, annual income, region, current smoking, current alcohol consumption, physical multimorbidity, any physical symptoms experienced during self-isolation/social distancing, and the number of days of self-isolation/social distancing. The association between potential predictors and poor mental health was studied using a multivariable logistic regression. RESULTS: 932 participants were included. Factors associated with poor mental health were sex (reference: male; female: OR=1.89, 95%CI=1.34-2.68), age (18-24 years: reference;45-54 years: OR=0.27, 95%CI=0.14-0.53; 55-64 years: OR=0.24, 95%CI=0.12-0.47; 65-74years: OR=0.10, 95% CI=0.05-0.22; and ≥75years: OR=0.08,95% CI=0.03-0.24),annual income (<£15,000: reference; £25,000-<£40,000: OR=0.54, 95% CI=0.31-0.93; £40,000-<£60,000: OR=0.39, 95% CI=0.22-0.69; and ≥£60,000: OR=0.38, 95% CI=0.21-0.67), current smoking (yes: OR=2.59, 95%CI=1.62-4.20), and physical multimorbidity (OR=2.35, 95%CI=1.61-3.46). CONCLUSIONS: In this sample of UK adults self-isolating/social distancing females, younger age groups, those with a lower annual income, current smokers and those with physical multimorbidity were associated with higher levels of poor mental health.

negative: Conduites addictives: faits cliniques* Résumé Malgré les fréquentes comorbidités psychiatriques, le trouble de l’usage de substance doit être appréhendé comme une pathologie autonome par ses déterminants, sa sémiologie et ses modalités évolutives spontanées ou sous traitement. De multiples produits de synthèse sont désormais accessibles via internet : associé à la créativité des chimistes cela a participé à l'émergence de pratiques inédites allant du chemsex au purple drank. Les conduites addictives résultent d’un ensemble de facteurs individuels (vulnérabilités biologique et psychique) et contextuels (disponibilité et banalisation du toxique dans l’environnement). Les pathologies mentales autres sont des facteurs de vulnérabilité à la pathologie addictive, tout comme les conduites addictives peuvent révéler une pathologie émotionnelle ou psychotique. Le médecin se doit d’entendre l’impuissance du malade face au besoin irrépressible de consommer (craving) et proposer une thérapeutique qui peut être chimique (y compris traitement de substitution) et psychologique. Dans la majorité des cas un accompagnement social s’impose pour corriger les effets désocialisants du trouble de l’usage de substances ou des comportements addictifs. Abstract Despite the frequency of psychiatric comorbidities, substance use disorder must be understood as an autonomous pathology due to its own determinants, semiology and possibilities of evolution, either spontaneous or under treatment. The ease of access to multiple synthetic products via the Internet combined with the creativity of chemists are contributing to the emergence of novel practices ranging from chemsex to purple drank. Addictive behaviours result from a combination of individual factors (biological and psychological vulnerability) and contextual factors (availability and triviality of the toxicant in the environment). Other mental disorders are factors of vulnerability to addictive pathology as well as the addictive behaviours can reveal an emotional or psychotic pathology. The physician needs to hear the patient powerlessness hidden behind the craving and propose a therapy that may be chemical (including substitution treatment) and psychological. Most of the time, social support is necessary to correct the desocializing effects of substance use disorder or addictive behaviours.

negative: Precautions and recommendations for orthodontic settings during the COVID-19 outbreak: A review Introduction: Coronavirus disease 2019 (COVID-19) is contagious disease caused by the SARS-CoV-2 virus. It emerged as a global pandemic early in 2020, affecting more than 2000 countries and territories. The infection is highly contagious with disease transmission reported from asymptomatic carriers, including children. It spreads through person-to-person contact, via aerosol and droplets. The practice of social distancing - maintaining a distance of 1 - 2 meters or 6 feet -- between people has been widely recommended to slow or halt the spread. This places orthodontists at high risk of acquiring and transmitting the infection. The objective of this review is to report to orthodontists on the emergence, epidemiology, risks, and precautions during disease crisis. This should help increase awareness, reinforce infection control and prevent cross-transmission within the orthodontic facility. Methods: A comprehensive literature review of English and non-English articles was performed in March, 2020 using (CORD-19 2020) dataset, PubMed, MEDLINE, Scopus, and Google Scholar to search for infection control and disease transmission in orthodontics. Results: This review emphasizes minimizing aerosol production and reinforcing strict infection control measures. Compliance with highest level of personal protection and restriction of treatment to emergency cases is recommended during the outbreak. Surface disinfection, adequate ventilation, and decontamination of instruments and supplies following the guidelines is required. Conclusion: Reinforcing strict infection control measures and minimizing personal contact and aerosol production are keys to prevent contamination within the orthodontic settings. Although no cases of COVID-19 cross-transmission within a dental facility have been reported, the risk exists and the disease is still emerging. Further studies are required.

negative: Understanding the Impact of COVID-19 on Latino Sexual Minority Men in a US HIV Hot Spot

negative: Coupling infectious diseases, human preventive behavior, and networks – A conceptual framework for epidemic modeling Human-disease interactions involve the transmission of infectious diseases among individuals and the practice of preventive behavior by individuals. Both infectious diseases and preventive behavior diffuse simultaneously through human networks and interact with one another, but few existing models have coupled them together. This article proposes a conceptual framework to fill this knowledge gap and illustrates the model establishment. The conceptual model consists of two networks and two diffusion processes. The two networks include: an infection network that transmits diseases and a communication network that channels inter-personal influence regarding preventive behavior. Both networks are composed of same individuals but different types of interactions. This article further introduces modeling approaches to formulize such a framework, including the individual-based modeling approach, network theory, disease transmission models and behavioral models. An illustrative model was implemented to simulate a coupled-diffusion process during an influenza epidemic. The simulation outcomes suggest that the transmission probability of a disease and the structure of infection network have profound effects on the dynamics of coupled-diffusion. The results imply that current models may underestimate disease transmissibility parameters, because human preventive behavior has not been considered. This issue calls for a new interdisciplinary study that incorporates theories from epidemiology, social science, behavioral science, and health psychology.

negative: PCR sequencing of the spike genes of geographically and chronologically distinct human coronaviruses 229E Abstract A reverse transcription nested PCR (RT-PCR) sequencing methodology was developed and used to generate sequence data from the spike genes of three geographically and chronologically distinct human coronaviruses 229E. These three coronaviruses were isolated originally from the USA in the 1960s (human coronavirus 229E strain ATCC VR-74), the UK in the 1990s (human coronavirus 229E LRI 281) and Ghana (human coronavirus 229E A162). Upon translation and alignment with the published spike protein sequence of human coronavirus 229E ‘LP’ (isolated in the UK in the 1970s), it was found that variation within the translated protein sequences was rather limited. In particular, minimal variation was observed between the translated spike protein sequence of human coronaviruses 229E LP and ATCC VR-74 (1/1012 amino acid differences), whilst most variation was observed between the translated spike protein sequence of human coronaviruses 229E LP and A162 (47/1012 amino acid changes). Further, the translated spike protein sequence of human coronavirus 229E A162 showed three clusters of amino acid changes, situated within the 5′ half of the translated spike protein sequence.

negative: The economic cost of coronavirus lockdowns ▪ Widespread lockdowns and social distancing in economies affected by the coronavirus outbreak are set to cause a massive negative short‐term impact on consumer spending and GDP. ▪ A large chunk of consumer spending is discretionary and so is very sensitive to being postponed or lost completely due to quarantines and social distancing. ▪ The early evidence from China supports the idea that up‐front effects will be large, with retail sales down 20% y/y in January–February and industrial output over 13% lower, thanks to widespread factory closures. ▪ We estimate that a three‐week lockdown affecting 50%–90% of a population would cut consumption in the three–month period featuring such a lockdown by 5%–8%, a six‐week lockdown by 9%–16%, and a 12‐week lockdown would slash it by 18%–32%. ▪ Full‐year effects depend on how quickly postponed consumption revives as outbreaks come under control. But even quick recoveries imply big full‐year losses: An initial 18% slump in consumption would still imply a full‐year loss of 9%, even if spending recovered to pre‐pandemic levels in four quarters. If recovery took eight quarters, the full‐year loss would be an enormous 14%.

negative: Suicide in the Time of COVID‐19: A Perfect Storm

negative: [Epidemic trend of corona virus disease 2019 (COVID-19) in mainland China] Objective: In order to master the epidemic trend of corona virus disease 2019 (COVID-19) and evaluate the effect of prevention and control, we evaluate the epidemic dynamics of COVID-19 in mainland China, Hubei province, Wuhan city and other provinces outside Hubei from January 16 to February 14, 2020. Methods: We collected the daily number of new confirmed COVID-19 cases by nucleic acid detection reported by the National Health Commission from January 16, 2020 to February 14, 2020. The analysis includes the epidemic curve of the new confirmed cases, multiple of the new confirmed cases for period-over-period, multiple of the new confirmed cases for fixed-base, and the period-over-period growth rate of the new confirmed cases. Results: From January 16 to February 14, 2020, the cumulative number of new confirmed cases of COVID-19 in mainland China was 50 031, including 37 930 in Hubei province, 22 883 in Wuhan city and 12 101 in other provinces outside Hubei. The peak of the number of new confirmed cases in other provinces outside Hubei was from January 31 to February 4, 2020, and the peak of new confirmed cases in Wuhan city and Hubei province was from February 5 to February 9, 2020. The number of new confirmed cases in other provinces outside Hubei showed a significant decline (23% compared with the peak) from February 5 to February 9, 2020, while the number of new confirmed cases in Wuhan city (30% compared with the peak) and Hubei Province (37% compared with the peak) decreased significantly from February 10 to February 14, 2020. Conclusion: The epidemic prevention and control measures taken by the state and governments at all levels have shown very significant effects, effectively curbing the spread of the COVID-19 epidemic in China.

negative: Genetic evolution analysis of 2019 novel coronavirus and coronavirus from other species The Corona Virus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a Public Health Emergency of International Concern. However, so far, there are still controversies about the source of the virus and its intermediate host. Here, we found the novel coronavirus was closely related to coronaviruses derived from five wild animals, including Paguma larvata, Paradoxurus hermaphroditus, Civet, Aselliscus stoliczkanus and Rhinolophus sinicus, and was in the same branch of the phylogenetic tree. However, genome and ORF1a homology show that the virus is not the same coronavirus as the coronavirus derived from these five animals, whereas the virus has the highest homology with Bat coronavirus isolate RaTG13.

negative: British Society of Gastroenterology guidance for management of inflammatory bowel disease during the COVID-19 pandemic The COVID-19 pandemic is putting unprecedented pressures on healthcare systems globally. Early insights have been made possible by rapid sharing of data from China and Italy. In the UK, we have rapidly mobilised inflammatory bowel disease (IBD) centres in order that preparations can be made to protect our patients and the clinical services they rely on. This is a novel coronavirus; much is unknown as to how it will affect people with IBD. We also lack information about the impact of different immunosuppressive medications. To address this uncertainty, the British Society of Gastroenterology (BSG) COVID-19 IBD Working Group has used the best available data and expert opinion to generate a risk grid that groups patients into highest, moderate and lowest risk categories. This grid allows patients to be instructed to follow the UK government’s advice for shielding, stringent and standard advice regarding social distancing, respectively. Further considerations are given to service provision, medical and surgical therapy, endoscopy, imaging and clinical trials.

negative: Recommendations for ‘responsible behaviour’ is not a sufficient policy tool in public health emergencies

negative: A Critical Appraisal of COVID-19 in Malaysia and Beyond When the first report of COVID-19 appeared in December 2019 from Wuhan, China, the world unknowingly perceived this as another flu-like illness. Many were surprised at the extreme steps that China had subsequently taken to seal Wuhan from the rest of the world. However, by February 2020, the SARS-CoV-2 virus, which causes COVID-19, had spread so quickly across the globe that the World Health Organization officially declared COVID-19 a pandemic. COVID-19 is not the first pandemic the world has seen, so what makes it so unique in Malaysia, is discussed to avoid a future coronacoma.

negative: Correlates of symptoms of anxiety and depression and mental wellbeing associated with COVID-19: a cross-sectional study of UK-based respondents Background: The aim was to assess the impact of COVID-19 self-isolation/social distancing on mental health, and potential correlates, among a sample of the UK population. Methods: A cross-sectional study. Mental health was measured using the Beck Anxiety and Depression Inventory. Mental wellbeing was measured using The Short Warwick-Edinburgh Mental Well-being Scale. Data collected on predictors included sex, age, marital status, employment, annual income, region, current smoking, current alcohol consumption, physical multimorbidity, any physical symptoms experienced during self-isolation/social distancing, and the number of days of self-isolation/social distancing. The association between potential predictors and poor mental health was studied using a multivariable logistic regression. Results: 932 participants were included. Factors associated with poor mental health were sex (reference: male; female: OR=1.89, 95%CI=1.34-2.68), age (18-24 years: reference;45-54 years: OR=0.27, 95%CI=0.14-0.53; 55-64 years: OR=0.24, 95%CI=0.12-0.47; 65-74years: OR=0.10, 95% CI=0.05-0.22; and ≥75years: OR=0.08,95% CI=0.03-0.24),annual income (<£15,000: reference; £25,000-<£40,000: OR=0.54, 95% CI=0.31-0.93; £40,000-<£60,000: OR=0.39, 95% CI=0.22-0.69; and ≥£60,000: OR=0.38, 95% CI=0.21-0.67), current smoking (yes: OR=2.59, 95%CI=1.62-4.20), and physical multimorbidity (OR=2.35, 95%CI=1.61-3.46). Conclusions: In this sample of UK adults self-isolating/social distancing females, younger age groups, those with a lower annual income, current smokers and those with physical multimorbidity were associated with higher levels of poor mental health.

negative: Is one- or two-meters social distancing enough for COVID-19?

negative: Public Exposure to Live Animals, Behavioural Change, and Support in Containment Measures in response to COVID-19 Outbreak: a population-based cross sectional survey in China Background In response to the COVID-19 outbreak, we aimed to investigate behavioural change on exposure to live animals before and during the outbreak, and public support and confidence for governmental containment measures. Methods A population-based cross-sectional telephone survey via random dialing was conducted in Wuhan (the epicentre) and Shanghai (an affected city with imported cases) between 1 and 10 February, 2020. 510 residents in Wuhan and 501 residents in Shanghai were randomly sampled. Differences of outcome measures were compared before and during the outbreak, and between two cities. Findings Proportion of respondents visiting wet markets at usual was 23.3% (119/510) in Wuhan and 20.4% (102/501) in Shanghai. During the outbreak, it decreased to 3.1% (16) in Wuhan (p<0.001), and 4.4% (22) in Shanghai (p<0.001). Proportion of those consuming wild animal products declined from 10.2% (52) to 0.6% (3) in Wuhan (p<0.001), and from 5.2% (26) to 0.8% (4) in Shanghai (p<0.001). 79.0% (403) of respondents in Wuhan and 66.9% (335) of respondents in Shanghai supported permanent closure of wet markets (P<0.001). 95% and 92% of respondents supported banning wild animal trade and quarantining Wuhan, and 75% were confident towards containment measures. Females and the more educated were more supportive for the above containment measures. Interpretation The public responded quickly to the outbreak, and reduced exposure to live animals, especially in Wuhan. With high public support in containment measures, better regulation of wet markets and healthy diets should be promoted.

negative: Social distancing, social justice, and risk during the COVID-19 pandemic Social distancing is an important and necessary measure to help arrest the spread of SARS-CoV-2 during the COVID-19 pandemic. However, it does place persons who are socially or politically marginalized, including those who are of lower socio-economic status, at risk of further harms. In other words, marginalized or disadvantaged persons are at risk of both contracting SARS-CoV-2 and the risk of harms that may come about because of the social distancing measures themselves. Finally, a third layer of risk faced by marginalized persons would be the overuse of utility (i.e., maximize the benefit of resource x) as the primary ethics principle upon which to make allocation decisions, since oftentimes it is resource-intensive to help those in positions of social marginality. This three-fold risk of harm to which marginalized persons are subjected runs counter to the very notion of social justice that underpins public health. Social distancing in a socially just manner requires dialoguing with affected populations and providing social supports to marginalized persons, regardless of the associated costs.

negative: Reducing SARS-CoV-2 transmission in the UK: A behavioural science approach to identifying options for increasing adherence to social distancing and shielding vulnerable people PURPOSE: To describe and discuss a systematic method for producing a very rapid response (3 days) to a UK government policy question in the context of reducing SARS-CoV-2 transmission. METHODS: A group of behavioural and social scientists advising the UK government on COVID-19 contributed to the analysis and writing of advice through the Government Office for Science. The question was as follows: What are the options for increasing adherence to social distancing (staying at home except for essential journeys and work) and shielding vulnerable people (keeping them at home and away from others)? This was prior to social distancing legislation being implemented. The first two authors produced a draft, based on analysis of the current government guidance and the application of the Behaviour Change Wheel (BCW) framework to identify and evaluate the options. RESULTS: For promoting social distancing, 10 options were identified for improving adherence. They covered improvements in ways of achieving the BCW intervention types of education, persuasion, incentivization, and coercion. For promoting shielding of vulnerable people, four options were identified covering the BCW intervention types of incentivization, coercion, and enablement. CONCLUSIONS: Responding to policymakers very rapidly as has been necessary during the COVID-19 pandemic can be facilitated by using a framework to structure the thinking and reporting of multidisciplinary academics and policymakers.

negative: Keeping the Country Positive during the COVID 19 Pandemic: Evidence from India

negative: COVID-19 and the impact of social determinants of health

negative: Socioeconomic, geographic and climatic risk factors for canine parvovirus infection and euthanasia in Australia Abstract Infection of canids with canine parvovirus (CPV) can result in severe, often fatal disease. This study aimed to examine climatic, socioeconomic and geographic risk factors for CPV infection and CPV-associated euthanasia in Australia. Australian veterinary hospital responses (534; 23.5 %) to a national veterinary survey of CPV case occurrences and euthanasias in 2016 were used. Severe caseloads (>40 cases per annum) were reported by 26 (11 %) hospitals (median 60 cases; IQR 50–110). Case reporting, case numbers, and without-treatment euthanasia were significantly associated with disadvantage across all Socio-Economic Index for Areas quintiles (p < 0.0001) – the greater the disadvantage, the more reports. Strong negative correlations were found between case numbers and the Index of Relative Socioeconomic Disadvantage (rSP = –0.3357, p < 0.0001) and also between euthanasia and the Index of Education and Occupation (rSP = –0.3762, p < 0.0001). Hospitals in more remote areas were also more likely to report cases and to euthanize without treatment (p < 0.0001). Of the climate variables, temperature of the hottest month was most strongly positively correlated with case numbers (rSP = 0.421, p < 0.0001), and lower annual rainfall was associated with more case-reporting hospitals (p < 0.0001). These results confirm that socioeconomic disadvantage is a significant risk-factor for CPV infection and outcome, and high temperature may also contribute to risk.

negative: Social Distancing against COVID-19: Implication for the Control of Influenza Social distancing has been adopted as one of basic protective measures against coronavirus disease 2019 (COVID-19). During 2019-2020 season, influenza epidemic period was exceptionally short and epidemic peak was low in comparison with previous seasons in Korea. Influenza epidemic pattern was bimodal in 2016-2017 and 2018-2019 seasons, however, influenza viruses have rarely been circulating in spring, 2020 in Korea. Although multiple factors could affect the size of influenza epidemic, extensive application of nonpharmaceutical interventions including mask wearing and social distancing in response to COVID-19 seems to be a major factor of reduced influenza epidemic. Social distancing measures with high feasibility and high acceptability should be implemented even if severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines are developed in the future. Establishment of guideline for workplace social distancing is needed and it would contribute to reduce disease burden of influenza, especially in vaccine mismatch year.

negative: Current status and progress of 2019 novel coronavirus pneumonia/ 中华危重病急救医学 Recently, the 2019 novel coronavirus (2019-nCoV) pneumonia outbroke in Wuhan and rapidly spread to all over China and even the world. Because of the strong infectivity and various clinical symptoms, it has brought certain difficulties to the epidemic prevention and control. Currently there is no specific drug for 2019-nCoV. Previous drugs used to treat other coronaviruses may be effective, but further clinical trials remain needed. We reviewed literature on the epidemiology, etiology, clinical manifestations, imaging manifestations, laboratory examination, diagnosis, complications, treatment and outcome of 2019-nCoV pneumonia.

negative: COVID-19 social distancing and sexual activity in a sample of the British Public BACKGROUND: On 23rd March 2020 the UK government released self-isolation guidance to reduce the risk of transmission of SARS-Cov-2. The influence such guidance has on sexual activity is not known. AIM: To investigate levels and correlates of sexual activity during COVID-19 self-isolation in a sample of the UK public. METHODS: This paper presents pre-planned interim analyses of data from a cross-sectional epidemiological study, administered through an online survey. OUTCOMES: Sexual activity was measured using the following question: “On average after self-isolating how many times have you engaged in sexual activity weekly?” Demographic and clinical data was collected, including sex, age, marital status, employment, annual household income, region, current smoking status, current alcohol consumption, number of chronic physical conditions, number of chronic psychiatric conditions, any physical symptom experienced during self-isolation, and number of days of self-isolation. The association between several factors (independent variables) and sexual activity (dependent variable) was studied using a multivariable logistic regression model. RESULTS: 868 individuals were included in this study. There were 63.1% of women, and 21.8% of adults who were aged between 25 and 34 years. During self-isolation, 39.9% of the population reported engaging in sexual activity at least once per week. Variables significantly associated with sexual activity (dependent variable) were being male, a younger age, being married or in a domestic partnership, consuming alcohol, and a higher number of days of self-isolation/social distancing. CLINICAL IMPLICATIONS: In this sample of 868 UK adults self-isolating owing to the COVID-19 pandemic the prevalence of sexual activity was lower than 40%. Those reporting particularly low levels of sexual activity included females, older adults, those not married, and those who abstain from alcohol consumption. STRENGTH AND LIMITATIONS: This is the first study to investigate sexual activity during the UK COVID-19 self-isolation/social distancing. Participants were asked to self-report their sexual activity potentially introducing self-reporting bias into the findings. Second, analyses were cross-sectional and thus it is not possible to determine trajectories of sexual activity during the current pandemic. CONCLUSION: Interventions to promote health and wellbeing during the COVID-19 pandemic should consider positive sexual health messages in mitigating the detrimental health consequences in relation to self-isolation and should target those with the lowest levels of sexual activity.

negative: Social Distancing—What Would It Mean for It to Work?

negative: Analysing the Combined Health, Social and Economic Impacts of the Corovanvirus Pandemic Using Agent-Based Social Simulation During the COVID-19 crisis there have been many difficult decisions governments and other decision makers had to make. E.g. do we go for a total lock down or keep schools open? How many people and which people should be tested? Although there are many good models from e.g. epidemiologists on the spread of the virus under certain conditions, these models do not directly translate into the interventions that can be taken by government. Neither can these models contribute to understand the economic and/or social consequences of the interventions. However, effective and sustainable solutions need to take into account this combination of factors. In this paper, we propose an agent-based social simulation tool, ASSOCC, that supports decision makers understand possible consequences of policy interventions, but exploring the combined social, health and economic consequences of these interventions.

negative: Perspectives on monoclonal antibody therapy as potential therapeutic intervention for Coronavirus disease-19 (COVID-19). Last decade witnessed the outbreak of many life-threatening human pathogens including Nipah, Ebola, Chikungunya, Zika, Middle East respiratory syndrome coronavirus (MERS-CoV), Severe Acute respiratory syndrome coronavirus (SARS-CoV) and more recently novel coronavirus (2019-nCoV or SARS-CoV-2). The disease condition associated with novel coronavirus, referred to as Coronavirus disease (COVID-19). The emergence of novel coronavirus in 2019 in Wuhan, China marked the third highly pathogenic coronavirus infecting humans in the 21st century. The continuing emergence of coronaviruses at regular intervals poses a significant threat to human health and economy. Ironically, even after a decade of research on coronavirus, still there are no licensed vaccines or therapeutic agents to treat coronavirus infection which highlights an urgent need to develop effective vaccines or post-exposure prophylaxis to prevent future epidemics. Several clinical, genetic and epidemiological features of COVID-19 resemble SARS-CoV infection. Hence, the research advancements on SARS-CoV treatment might help scientific community in quick understanding of this virus pathogenesis and develop effective therapeutic/prophylactic agents to treat and prevent this infection. Monoclonal antibodies represent the major class of biotherapeutics for passive immunotherapy to fight against viral infection. The therapeutic potential of monoclonal antibodies has been well recognized in the treatment of many diseases. Here, we summarize the potential monoclonal antibody based therapeutic intervention for COVID-19 by considering the existing knowledge on the neutralizing monoclonal antibodies against similar coronaviruses SARS-CoV and MERS-CoV. Further research on COVID-19 pathogenesis could identify appropriate therapeutic targets to develop specific anti-virals against this newly emerging pathogen.

negative: Estimating cost-benefit of quarantine length for COVID-19 mitigation Background: The international community has been put in an unprecedented situation by the COVID-19 pandemic. Creating models to describe and quantify alternative mitigation strategies becomes increasingly urgent. Methods: In this study, we propose an agent-based model of disease transmission in a society divided into closely connected families, workplaces, and social groups. This allows us to discuss mitigation strategies, including targeted quarantine measures. Results: We find that workplace and more diffuse social contacts are roughly equally important to disease spread, and that an effective lockdown must target both. We examine the cost-benefit of replacing a lockdown with tracing and quarantining contacts of the infected. Quarantine can contribute substantially to mitigation, even if it has short duration and is done within households. When reopening society, testing and quarantining is a strategy that is much cheaper in terms of lost workdays than a long lockdown of workplaces. Conclusions: A targeted quarantine strategy is quite efficient with only 5 days of quarantine, and its relative effect increases when supplemented with other measures that reduce disease transmission.

negative: Dynamic change process of target genes by RT-PCR testing of SARS-Cov-2 during the course of a Coronavirus Disease 2019 patient Abstract We report the dynamic change process of target genes by RT-PCR testing of SARS-Cov-2 during the course of a COVID-19 patient: from successive negative results to successive single positive nucleocapsid gene, to two positive target genes (orf1ab and nucleocapsid) by RT-PCR testing of SARS-Cov-2, and describe the diagnosis, clinical course, and management of the case. In this case, negative results of RT-PCR testing was not excluded to diagnose a suspected COVID-19 patient, clinical signs and symptoms, other laboratory findings, and chest CT images should be taken into account for the absence of enough positive evidence. This case highlights the importance of successive sampling and testing SARS-Cov-2 by RT-PCR as well as the increased value of single positive target gene from pending to positive in two specimens to diagnose laboratory-confirmed COVID-19.

negative: Health and Economy in COVID-19 Era: A Plan for Reconstituting Long-Term Economic Security COVID-19 is a rapidly evolving pandemic, which represents a multifaceted global threat. Given the economic consequences, most researchers agree that social distancing measures are an effective strategy relative to the cost. Previous studies indicate that community size as well as viral population risk groups should be considered in forming an effective targeted social distancing strategy. The resultant delay in the occurrence of infections in order to support vaccine development has been shown to be an effective policy. However, a return to normalcy from the current situation would require policy intervention that transforms the American economy along with continued targeted social distancing and the use of medical science as a tool to facilitate gradual personal interactions of low-risk individuals. We believe that the adoption of rapid IgG testing would be best suitable for widespread population-level screening as part of a comprehensive plan for incrementally rebuilding the in-person workforce. As such, this crisis represents an opportunity for the United States to increase automation of the manufacturing sector, shrink supply chains, and create higher-level jobs in order to reduce the dependency on other countries for critical supplies. This economic transition to better utilize technology along with reconstruction of the workforce could improve the standard of living for many Americans as well as better prepare the US for future pandemics.

negative: Pathological findings of COVID-19 associated with acute respiratory distress syndrome

negative: Promoting public health legal preparedness for emergencies: review of current trends and their relevance in light of the Ebola crisis BACKGROUND: Public health legal preparedness (PHLP) for emergencies is a core component of the health system response. However, the implementation of health legal preparedness differs between low- and middle-income countries (LMIC) and developed countries. OBJECTIVE: This paper examines recent trends regarding public health legal preparedness for emergencies and discusses its role in the recent Ebola outbreak. DESIGN: A rigorous literature review was conducted using eight electronic databases as well as Google Scholar. The results encompassed peer-reviewed English articles, reports, theses, and position papers dating from 2011 to 2014. Earlier articles concerning regulatory actions were also examined. RESULTS: The importance of PHLP has grown during the past decade and focuses mainly on infection–disease scenarios. Amid LMICs, it mostly refers to application of international regulations, whereas in developed states, it focuses on independent legislation and creation of conditions optimal to promoting an effective emergency management. Among developed countries, the United States’ utilisation of health legal preparedness is the most advanced, including the creation of a model comprising four elements: law, competencies, information, and coordination. Only limited research has been conducted in this field to date. Nevertheless, in both developed and developing states, studies that focused on regulations and laws activated in health systems during emergencies, identified inconsistency and incoherence. The Ebola outbreak plaguing West Africa since 2014 has global implications, challenges and paralleling results, that were identified in this review. CONCLUSIONS: The review has shown the need to broaden international regulations, to deepen reciprocity between countries, and to consider LMICs health capacities, in order to strengthen the national health security. Adopting elements of the health legal preparedness model is recommended.

negative: The effects of injection of bovine vaccine into a human digit: a case report BACKGROUND: The incidence of needlestick injuries in farmers and veterinary surgeons is significant and the consequences of such an injection can be serious. CASE PRESENTATION: We report accidental injection of bovine vaccine into the base of the little finger. This resulted in increased pressure in the flexor sheath causing signs and symptoms of ischemia. Amputation of the digit was required despite repeated surgical debridement and decompression. CONCLUSION: There have been previous reports of injection of oil-based vaccines into the human hand resulting in granulomatous inflammation or sterile abscess and causing morbidity and tissue loss. Self-injection with veterinary vaccines is an occupational hazard for farmers and veterinary surgeons. Injection of vaccine into a closed compartment such as the human finger can have serious sequelae including loss of the injected digit. These injuries are not to be underestimated. Early debridement and irrigation of the injected area with decompression is likely to give the best outcome. Frequent review is necessary after the first procedure because repeat operations may be required.

negative: Impact on the endoplasmic reticulum and Golgi apparatus of turnip mosaic virus infection. The impact of turnip mosaic virus (TuMV) infection on the endomembranes of the host early secretory pathway was investigated using an infectious clone that has been engineered for tagging viral membrane structures with a fluorescent protein fused to the viral protein 6K(2). TuMV infection led to the amalgamation of the endoplasmic reticulum (ER), Golgi apparatus, COPII coatamers, and chloroplasts into a perinuclear globular structure that also contained viral proteins. One consequence of TuMV infection was that protein secretion was blocked at the ER-Golgi interface. Fluorescence recovery after photobleaching (FRAP) experiments indicated that the perinuclear structure cannot be restocked in viral components but was dynamically connected to the bulk of the Golgi apparatus and the ER. Experiments with 6K(2) fused to photoactivable green fluorescent protein (GFP) showed that production of motile peripheral 6K(2) vesicles was functionally linked to the perinuclear structure. Disruption of the early secretory pathway did not prevent the formation of the perinuclear globular structure, enhanced the clustering of peripheral 6K(2) vesicles with COPII coatamers, and led to inhibition of cell-to-cell virus movement. This suggests that a functional secretory pathway is not required for the formation of the TuMV perinuclear globular structure and peripheral vesicles but is needed for successful viral intercellular propagation.

negative: Between Geography and Demography: Key Interdependencies and Exit Mechanisms for Covid-19 We develop a minimalist compartmental model to analyze policies on mobility restriction in Italy during the Covid-19 outbreak. Our findings show that a early lockdowns barely shift the epidemic in time: moreover, beyond a critical value of the lockdown strength, an epidemic that seems to be quelled fully recovers after lifting the restrictions. We investigate the effects on lockdown scenarios and exit mechanisms by introducing heterogeneities in the model. In particular, we consider Italian regions as separate administrative entities in which social interactions through different age classes occur. We find that, due to the sparsity of the mobility matrix, epidemics developed independently in different regions once the outbreak starts. Moreover, after the epidemics ha started, the influence of contacts with other regions becomes soon irrelevant. Sparsity accounts for the observed delays across different regions. Analogous arguments would apply to the international borders. We also show how disregarding the structure of social contacts could lead to severe underestimation of the post-lockdown effects. Nevertheless, age class based mechanisms can help to mitigate rebound effects with milder strategies. Finally, we point out that our results can be generalized beyond this particular model by providing a description of the effects of key parameters on non-medical mitigation strategies for epidemics.

negative: Coronavirus contact-tracing apps: can they slow the spread of COVID-19?

negative: Loneliness and social isolation during the COVID-19 pandemic Loneliness and social isolation are associated with adverse physical and psychological consequences which are particularly prevalent in older persons. During this unprecedented time of the COVID-19 pandemic, we must follow social distancing guidelines to protect ourselves and to reduce the spread of coronavirus. At the same time, it is crucial to maintain social connections with each other, especially with older persons, to help cope and reduce the negative consequences of loneliness and social isolation. It is important to develop new strategies (e.g. virtual health care and new government policy) to address loneliness and social isolation among older adults for the post-pandemic era.

negative: Early career psychiatrists’ perspectives on the mental health impact and care of the COVID-19 pandemic across the world Abstract The emergence of mental health (MH) problems during a pandemic is extremely common, though difficult to address due to the complexities of pandemics and the little evidence about the epidemiology of pandemic-related MH problems and the potential interventions to tackle them. Little attention has been devoted so far to this topic from policymakers, stakeholders and researchers, what could be due to a lack of replicable, scalable and applicable frameworks to plan, develop and deliver MH care during pandemics. As a response, we have attempted to develop a conceptual framework (CF) that could guide the development, implementation, and evaluation of MH interventions during the ongoing COVID-19 pandemic. This CF was developed by early career psychiatrists, from 16 countries that cover all the WHO regions. Their opinions were elicited via semi-structured questionnaire. They were asked to provide their views about the current MH situation of their countries, existing myths and misinformation, and the possible resources available. They were also asked to propose solutions and approaches to provide accessible and affordable care. The CF’s were prepared based on the extant literature and the views expressed; they illustrate the epidemiology of MH issues, preparedness plans, stage-specific plans/innovative solutions, opportunities to integrate those plans and probable outcomes at policy level. This CF can serve as a technical guide for future research in pandemic. It can be used to monitor trends and to optimize efforts and to develop evidence based MH interventions. However further research focusing on the individual components of this framework is needed.

negative: Lessons learned during the COVID-19 pandemic: a single institution radiology chief resident experience Coronavirus Disease 2019 (COVID-19) has posed incredible new challenges for radiology residency programs, including resident training under tenuous and uncertain conditions, barriers to communication, deployment-induced anxiety, and social isolation. Chief residents and program leadership play a critical role in guiding radiology residents through these unprecedented times. Best practices and creative approaches experienced in a single institution's residency program located in New York City are shared in an effort to encourage other programs struggling with similar obstacles to prioritize resident education and wellness.

negative: The psychological impact of quarantine and how to reduce it: rapid review of the evidence The December, 2019 coronavirus disease outbreak has seen many countries ask people who have potentially come into contact with the infection to isolate themselves at home or in a dedicated quarantine facility. Decisions on how to apply quarantine should be based on the best available evidence. We did a Review of the psychological impact of quarantine using three electronic databases. Of 3166 papers found, 24 are included in this Review. Most reviewed studies reported negative psychological effects including post-traumatic stress symptoms, confusion, and anger. Stressors included longer quarantine duration, infection fears, frustration, boredom, inadequate supplies, inadequate information, financial loss, and stigma. Some researchers have suggested long-lasting effects. In situations where quarantine is deemed necessary, officials should quarantine individuals for no longer than required, provide clear rationale for quarantine and information about protocols, and ensure sufficient supplies are provided. Appeals to altruism by reminding the public about the benefits of quarantine to wider society can be favourable.

negative: In reply: Physical distancing or social distancing: that is the question

negative: Can Testing Ease Social Distancing Measures? Future Evolution of COVID-19 in NYC The"New York State on Pause"executive order came into effect on March 22 with the goal of ensuring adequate social distancing to alleviate the spread of COVID-19. Pause will remain effective in New York City in some form until early June. We use a compartmentalized model to study the effects of testing capacity and social distancing measures on the evolution of the pandemic in the"post-Pause"period in the City. We find that testing capacity must increase dramatically if it is to counterbalance even relatively small relaxations in social distancing measures in the immediate post-Pause period. In particular, if the City performs 20,000 tests per day and relaxes the social distancing measures to the pre-Pause norms, then the total number of deaths by the end of September can reach 250,000. By keeping the social distancing measures to somewhere halfway between the pre- and in-Pause norms and performing 100,000 tests per day, the total number of deaths by the end of September can be kept at around 27,000. Going back to the pre-Pause social distancing norms quickly must be accompanied by an exorbitant testing capacity, if one is to suppress excessive deaths. If the City is to go back to the"pre-Pause"social distancing norms in the immediate post-Pause period and keep the total number of deaths by the end of September at around 35,000, then it should be performing 500,000 tests per day. Our findings have important implications on the magnitude of the testing capacity the City needs as it relaxes the social distancing measures to reopen its economy.

negative: Relational ethical approaches to the COVID-19 pandemic Key ethical challenges for healthcare workers arising from the COVID-19 pandemic are identified: isolation and social distancing, duty of care and fair access to treatment. The paper argues for a relational approach to ethics which includes solidarity, relational autonomy, duty, equity, trust and reciprocity as core values. The needs of the poor and socially disadvantaged are highlighted. Relational autonomy and solidarity are explored in relation to isolation and social distancing. Reciprocity is discussed with reference to healthcare workers' duty of care and its limits. Priority setting and access to treatment raise ethical issues of utility and equity. Difficult ethical dilemmas around triage, do not resuscitate decisions, and withholding and withdrawing treatment are discussed in the light of recently published guidelines. The paper concludes with the hope for a wider discussion of relational ethics and a glimpse of a future after the pandemic has subsided.

negative: Orthopaedic Surgical Selection and Inpatient Paradigms During the Coronavirus (COVID-19) Pandemic The novel coronavirus pandemic, also known as SARS-CoV-2, has placed an immense strain on healthcare systems across the entire world. Consequently, multiple federal and state governments have placed restrictions on hospitals such as limiting “elective surgery” and recommending social or physical distancing. We review the literature on several areas that have been affected including surgical selection, inpatient care, and physician well-being. These areas affecting inpatient paradigms include surgical priority, physical or social distancing, file sharing for online clinical communications, and physician wellness. During this crisis, it is important that orthopaedic departments place an emphasis on personnel safety and slowing the spread of the virus so that the department can still maintain vital functions. Physical distancing and emerging technologies such as inpatient telemedicine and online file sharing applications can enable orthopaedic programs to still function while attempting to protect medical staff and patients from the novel coronavirus spread. This literature review sought to provide evidence-based guidance to orthopaedic departments during an unprecedented time. Orthopaedic surgeons should follow the Centers for Disease Control and Prevention guidelines, wear PPE when appropriate, have teams created using physical distancing, understand the department's policy on elective surgery, and engage in routines which enhance physician wellness.

negative: COVID-19: Global radiation oncology’s targeted response for pandemic preparedness Abstract As the global COVID-19 pandemic escalates there is a need within radiation oncology to work to support our patients in the best way possible. Measures are required to reduce infection spread between patients and within the workforce. Departments need contingency planning to create capacity and continue essential treatments despite a reduced workforce. The #radonc community held an urgent online journal club on Twitter in March 2020 to discuss these issues and create some consensus on crucial next steps. There were 121 global contributors. This document summarises these discussions around themes of infection prevention, rationalisation of workload and working practice in the presence of infection.

negative: Establishing Telemedicine in an Academic Total Joint Arthroplasty Practice: Needs and Opportunities Highlighted by the COVID-19 Pandemic Abstract The COVID-19 pandemic has prompted rapid restructuring of the healthcare system in an effort to stop the spread of the virus and to treat patients who are acutely ill with COVID-19, while continuing to provide outpatient care for the remainder of patients. To help control spread of this pandemic, many centers have boosted telemedicine capability to care for patients who would typically be seen in person in outpatient settings, including total joint arthroplasty clinics. We review key components relevant to the establishment and effective use of telemedicine, focused on patient education, practice logistics, technological considerations, and sensitive patient health information–associated compliance factors, which are necessary to provide care remotely for total joint arthroplasty patients.

negative: Infectious disease and economics: The case for considering multi-sectoral impacts Beyond the public health impacts of regional or global emerging and endemic infectious disease events lay wider socioeconomic consequences that are often not considered in risk or impact assessments. With rapid and extensive international travel and trade, such events can elicit economic shock waves far beyond the realm of traditional health sectors and original geographical range of a pathogen. While private sector organizations are impacted indirectly by these disease events, they are under-recognized yet effective stakeholders that can provide critical information, resources, and key partnerships to public and private health systems in response to and in preparation for potential infectious disease events and their socioeconomic consequences.

negative: Delaying the COVID-19 epidemic in Australia: Evaluating the effectiveness of international travel bans Following the outbreak of novel Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) or COVID-19 in Wuhan, China late 2019, different countries have put in place interventions such as travel ban, proper hygiene, and social distancing to slow the spread of this novel virus. We evaluated the effects of travel bans in the Australia context and projected the epidemic until May 2020. Our modelling results closely align with observed cases in Australia indicating the need for maintaining or improving on the control measures to slow down the virus.

negative: Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys Establishing how many people have already been infected by SARS-CoV-2 is an urgent priority for controlling the COVID-19 pandemic. Patchy virological testing has hampered interpretation of confirmed case counts, and unknown rates of asymptomatic and mild infections make it challenging to develop evidence-based public health policies. Serological tests that identify past infection can be used to estimate cumulative incidence, but the relative accuracy and robustness of various sampling strategies has been unclear. Here, we used a flexible framework that integrates uncertainty from test characteristics, sample size, and heterogeneity in seroprevalence across tested subpopulations to compare estimates from sampling schemes. Using the same framework and making the assumption that serological positivity indicates immune protection, we propagated these estimates and uncertainty through dynamical models to assess the uncertainty in the epidemiological parameters needed to evaluate public health interventions. We examined the relative accuracy of convenience samples versus structured surveys to estimate population seroprevalence, and found that sampling schemes informed by demographics and contact networks outperform uniform sampling. The framework can be adapted to optimize the design of serological surveys given particular test characteristics and capacity, population demography, sampling strategy, and modeling approach, and can be tailored to support decision-making around introducing or removing interventions.

negative: Predicting the receptor-binding domain usage of the coronavirus based on kmer frequency on spike protein

negative: Psychological Outcomes Associated with Stay-at-Home Orders and the Perceived Impact of COVID-19 on Daily Life The COVID-19 pandemic has resulted in the widespread implementation of extraordinary physical distancing interventions (e.g., stay-at-home orders) to slow the spread of the virus. Although vital, these interventions may be socially and economically disruptive, contributing to adverse psychological outcomes. This study examined relations of both stay-at-home orders and the perceived impact of COVID-19 on daily life to psychological outcomes (depression, health anxiety, financial worry, social support, and loneliness) in a nationwide U.S. community adult sample (N = 500; 47% women, mean age = 40). Participants completed questionnaires assessing psychological outcomes, stay-at-home order status, and COVID-19’s impact on their daily life. Being under a stay-at-home order was associated with greater health anxiety, financial worry, and loneliness. Moreover, the perceived impact of COVID-19 on daily life was positively associated with health anxiety, financial worry, and social support, but negatively associated with loneliness. Findings highlight the importance of social connection to mitigate negative psychological consequences of the COVID-19 pandemic.

negative: An Evaluation of Publicly Available Deep Learning Based Commercial Information Retrieval Systems to search Biomedical Articles related to COVID-19 The COVID-19 pandemic has resulted in a tremendous need for access to the latest scientific information, primarily through the use of text mining and search tools. This has led to both corpora for biomedical articles related to COVID-19 (such as the CORD-19 corpus (Wang et al., 2020)) as well as search engines to query such data. While most research in search engines is performed in the academic field of information retrieval (IR), most academic search engines--though rigorously evaluated--are sparsely utilized, while major commercial web search engines (e.g., Google, Bing) dominate. This relates to COVID-19 because it can be expected that commercial search engines deployed for the pandemic will gain much higher traction than those produced in academic labs, and thus leads to questions about the empirical performance of these search tools. This paper seeks to empirically evaluate two such commercial search engines for COVID-19, produced by Google and Amazon, in comparison to the more academic prototypes evaluated in the context of the TREC-COVID track (Roberts et al., 2020). To ensure a fair comparison, we limit the number of documents in the retrieved runs and also annotate additional documents. We find that the top-performing system from TREC-COVID on bpref metric performed the best among the different systems evaluated in this study on all the metrics.

negative: A Genomic Survey of SARS-CoV-2 Reveals Multiple Introductions into Northern California without a Predominant Lineage The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 has spread globally, resulting in >300,000 reported cases worldwide as of March 21st, 2020. Here we investigate the genetic diversity and genomic epidemiology of SARS-CoV-2 in Northern California using samples from returning travelers, cruise ship passengers, and cases of community transmission with unclear infection sources. Virus genomes were sampled from 29 patients diagnosed with COVID-19 infection from Feb 3rd through Mar 15th. Phylogenetic analyses revealed at least 8 different SARS-CoV-2 lineages, suggesting multiple independent introductions of the virus into the state. Virus genomes from passengers on two consecutive excursions of the Grand Princess cruise ship clustered with those from an established epidemic in Washington State, including the WA1 genome representing the first reported case in the United States on January 19th. We also detected evidence for presumptive transmission of SARS-CoV-2 lineages from one community to another. These findings suggest that cryptic transmission of SARS-CoV-2 in Northern California to date is characterized by multiple transmission chains that originate via distinct introductions from international and interstate travel, rather than widespread community transmission of a single predominant lineage. Rapid testing and contact tracing, social distancing, and travel restrictions are measures that will help to slow SARS-CoV-2 spread in California and other regions of the USA.

negative: Modeling the Impact of Nationwide BCG Vaccine Recommendations on COVID-19 Transmission, Severity, and Mortality COVID-19 was declared as pandemic on 11th March 2020 by WHO. There are apparent dissimilarities in incidence and mortality of COVID-19 cases in different parts of world. Developing countries in Asia and Africa with fragile health system have shown lower incidence and mortality compared to developed countries with superior health system in Europe and America. Most countries in Asia and Africa have national BCG vaccination program while Europe and America do not have such program, or have ceased it. At present, there is no known therapy to treat COVID-19 disease. There is no vaccine available currently to prevent COVID- 19 disease. As mathematical modelling is ideal for predicting the rate of disease transmission as well as evaluating efficacy of possible public health prevention measures, we have created a mathematical model with seven compartments to understand nationwide BCG vaccine recommendation on COVID-19 transmission, severity and mortality. We have computed two basic reproduction number, one at vaccine free equilibrium point and other at non-vaccine free equilibrium point and carried out local stability, sensitivity and numerical analysis. Our result showed that individuals with BCG vaccinations have lower risk of getting COVID-19 infection, shorter hospital stays, and increased rate of recovery. Furthermore, countries with long-standing universal BCG vaccination policies have reduced incidence, mortality, and severity of COVID-19. Further research will focus on exploring the immediate benefits of vaccination to healthcare workers and patients as well as benefits of BCG re-vaccination.

negative: Reducing SARS‐CoV‐2 transmission in the UK: A behavioural science approach to identifying options for increasing adherence to social distancing and shielding vulnerable people PURPOSE: To describe and discuss a systematic method for producing a very rapid response (3 days) to a UK government policy question in the context of reducing SARS‐CoV‐2 transmission. METHODS: A group of behavioural and social scientists advising the UK government on COVID‐19 contributed to the analysis and writing of advice through the Government Office for Science. The question was as follows: What are the options for increasing adherence to social distancing (staying at home except for essential journeys and work) and shielding vulnerable people (keeping them at home and away from others)? This was prior to social distancing legislation being implemented. The first two authors produced a draft, based on analysis of the current government guidance and the application of the Behaviour Change Wheel (BCW) framework to identify and evaluate the options. RESULTS: For promoting social distancing, 10 options were identified for improving adherence. They covered improvements in ways of achieving the BCW intervention types of education, persuasion, incentivization, and coercion. For promoting shielding of vulnerable people, four options were identified covering the BCW intervention types of incentivization, coercion, and enablement. CONCLUSIONS: Responding to policymakers very rapidly as has been necessary during the COVID‐19 pandemic can be facilitated by using a framework to structure the thinking and reporting of multidisciplinary academics and policymakers.

negative: The COVID-19 pandemic in the USA: what might we expect?

negative: Associations Between State Public Health Agency Structure and Pace and Extent of Implementation of Social Distancing Control Measures. OBJECTIVE To assess associations between state public health agency governance and timing and extent of implementation of social distancing control measures during COVID-19 response. DESIGN State public health agencies were stratified by governance, and data on timing and extent of social distancing were collected from the Institute for Health Metrics and Evaluation. Multinomial logistic regression and time-to-event analyses were conducted to quantify impacts of governance structure on timing and extent of social distancing. SETTING State health departments in the United States. RESULTS States operating under centralized public health governance structures enacted social distancing 4 days after decentralized states and had a 73% reduced likelihood of enacting a social distancing policy (hazard ratio = 0.27; 95% CI, 0.08 to 0.86). CONCLUSION State health department governance structure may have implications on timing and extent of social distancing control measures implemented during a public health emergency.

negative: Cybercare 2.0: meeting the challenge of the global burden of disease in 2030 In this paper, we propose to advance and transform today’s healthcare system using a model of networked health care called Cybercare. Cybercare means “health care in cyberspace” — for example, doctors consulting with patients via videoconferencing across a distributed network; or patients receiving care locally — in neighborhoods, “minute clinics,” and homes — using information technologies such as telemedicine, smartphones, and wearable sensors to link to tertiary medical specialists. This model contrasts with traditional health care, in which patients travel (often a great distance) to receive care from providers in a central hospital. The Cybercare model shifts health care provision from hospital to home; from specialist to generalist; and from treatment to prevention. Cybercare employs advanced technology to deliver services efficiently across the distributed network — for example, using telemedicine, wearable sensors and cell phones to link patients to specialists and upload their medical data in near-real time; using information technology (IT) to rapidly detect, track, and contain the spread of a global pandemic; or using cell phones to manage medical care in a disaster situation. Cybercare uses seven “pillars” of technology to provide medical care: genomics; telemedicine; robotics; simulation, including virtual and augmented reality; artificial intelligence (AI), including intelligent agents; the electronic medical record (EMR); and smartphones. All these technologies are evolving and blending. The technologies are integrated functionally because they underlie the Cybercare network, and/or form part of the care for patients using that distributed network. Moving health care provision to a networked, distributed model will save money, improve outcomes, facilitate access, improve security, increase patient and provider satisfaction, and may mitigate the international global burden of disease. In this paper we discuss how Cybercare is being implemented now, and envision its growth by 2030.

negative: Un mundo, una salud: la epidemia por el nuevo coronavirus COVID-19

negative: National Governance of Public Health Responses in a Pandemic? The world is currently facing the worst pandemic in a century and we were caught unprepared. COVID-19 has proven highly contagious and with severe consequences that are still unfolding. As of 16 April 2020, there were over 2 million confirmed cases and over 136,000 related deaths reported worldwide. Over 1 million of those confirmed cases were in the preceding 14 days, with the USA accounting for nearly half of those. Furthermore, the International Monetary Fund (IMF) is now warning that the world is about to suffer the worst economic recession since the Great Depression in the 1920s.

negative: Willingness to Accept Tradeoffs among Covid-19 Cases, Social-Distancing Restrictions, and Economic Impact: A Nationwide US Study We designed a discrete-choice experiment to quantify the extent to which US adults would accept greater risk of infection with SARS-CoV-2 in return for lifting social-distancing restrictions and diminishing the economic impact of the COVID-19 pandemic. 5953 adults representing all 50 states had 4 distinctly different preference patterns. About 37% were risk minimizers reluctant to accept any increases in risk of contracting the virus. Another group (26%) was primarily concerned about time required for economic recovery, accepting increases in COVID-19 risk levels up to 16% to shorten recovery from 3 to 2 years. The remaining two groups diverged on the relative importance of reopening nonessential businesses. The larger group (26%) strongly preferred delaying reopening while the smaller group (13%) would accept COVID-19 risks well beyond 20% to avoid a delay in reopening. Political affiliation, race, household income and employment status were predictive of group membership.

negative: The Socio-Economic Implications of the Coronavirus and COVID-19 Pandemic: A Review Abstract The COVID-19 pandemic has resulted in over 1.4 million confirmed cases and over 83,000 deaths globally. It has also sparked fears of an impending economic crisis and recession. Social distancing, self-isolation and travel restrictions forced a decrease in the workforce across all economic sectors and caused many jobs to be lost. Schools have closed down, and the need of commodities and manufactured products has decreased. In contrast, the need for medical supplies has significantly increased. The food sector has also seen a great demand due to panic-buying and stockpiling of food products. In response to this global outbreak, we summarise the socio-economic effects of COVID-19 on individual aspects of the world economy.

negative: Practical insights for paediatric otolaryngology surgical cases and performing microlaryngobronchoscopy during the COVID-19 pandemic Abstract Paediatric otolaryngology practice involves examining and operating in anatomical locations with high levels of aerosol generation and transmission of COVID-19 to treating clinicians, especially from the asymptomatic patient populations including children. During the COVID-19 pandemic all emergent otolaryngological conditions affecting the airway, oral, and nasal cavities should be managed medically where possible and any operating deferred. We present guidelines for operating on paediatric otolaryngological patients when necessary during the COVID-19 pandemic, and incorporate experience gathered during microlaryngobronchoscopy on a COVID-19 positive infant at our institution.

negative: Comparison of risk factors for viral and nonviral asthma exacerbations

negative: Use of Plant Viruses for Delivery of Vaccine Epitopes

negative: The impact of non-pharmaceutical interventions for 2009 H1N1 influenza on travel intentions: A model of goal-directed behavior Theoretically, in the tourism context this study introduced a new concept of non-pharmaceutical intervention (NPI) for influenza, and tested the impact of NPI on the behavioral intention of potential international tourists. This study also extended the model of goal-directed behavior (MGB) by incorporating the new concepts of NPI, and the perception of 2009 H1N1. The model found that desire, perceived behavioral control, frequency of past behavior, and non-pharmaceutical interventions predicted tourists’ intention but perceptions of 2009 H1N1 had nil effect on desire and intention. Personal non-pharmaceutical interventions were theorized as adaptive behavior of tourists intending to travel during a pandemic which should be supported by tourism operators on a system-wide basis. Practically, this study dealt with the issue of influenza 2009 H1N1 with the study findings and implications providing government agencies, tourism marketers, policy-makers, transport systems, and hospitality services with important suggestions for NPI and international tourism during pandemics.

negative: Saudi Arabia`s measures to curb the COVID-19 outbreak: temporary suspension of the Umrah pilgrimage

negative: Balancing Health Privacy, Health Information Exchange and Research in the Context of the COVID-19 Pandemic The novel coronavirus COVID-19 infection poses serious challenges to the healthcare system that are being addressed through the creation of new unique and advanced systems of care with disjointed care processes (telehealth screening, drive-through specimen collection, remote testing, telehealth management, etc.) However, our current regulations on the flows of information for clinical care and research are antiquated and often conflict at the state and federal level. This paper discusses proposed changes to privacy regulations such as the Health Insurance Portability and Accountability act (HIPAA) designed to let health information seamlessly and frictionlessly flow between the health entities that need to collaborate on treatment of patients and, also, allow it to flow to researchers trying to understand how to limit its impacts.

negative: Agile Requirements Engineering and Software Planning for a Digital Health Platform to Engage the Effects of Isolation Caused by Social Distancing: Case Study BACKGROUND: Social distancing and shielding measures have been put in place to reduce social interaction and slow the transmission of the coronavirus disease (COVID-19). For older people, self-isolation presents particular challenges for mental health and social relationships. As time progresses, continued social distancing could have a compounding impact on these concerns. OBJECTIVE: This project aims to provide a tool for older people and their families and peers to improve their well-being and health during and after regulated social distancing. First, we will evaluate the tool's feasibility, acceptability, and usability to encourage positive nutrition, enhance physical activity, and enable virtual interaction while social distancing. Second, we will be implementing the app to provide an online community to assist families and peer groups in maintaining contact with older people using goal setting. Anonymized data from the app will be aggregated with other real-world data sources to develop a machine learning algorithm to improve the identification of patients with COVID-19 and track for real time use by health systems. METHODS: Development of this project is occurring at the time of publication, and therefore, a case study design was selected to provide a systematic means of capturing software engineering in progress. The app development framework for software design was based on agile methods. The evaluation of the app's feasibility, acceptability and usability shall be conducted using Public Health England's guidance on evaluating digital health products, Bandura's model of health promotion, the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework and the Nonadoption, Abandonment and Challenges to the Scale-up, Spread and Suitability (NASSS) framework. RESULTS: Making use of a pre-existing software framework for health behavior change, a proof of concept was developed, and a multistage app development and deployment for the solution was created. Grant submissions to fund the project and study execution have been sought at the time of publication, and prediscovery iteration of the solution has begun. Ethical approval for a feasibility study design is being sought. CONCLUSIONS: This case study lays the foundations for future app development to combat mental and societal issues arising from social distancing measures. The app will be tested and evaluated in future studies to allow continuous improvement of the app. This novel contribution will provide an evidence-based exemplar for future app development in the space of social isolation and loneliness.

negative: Human Genomic Loci Important in Common Infectious Diseases: Role of High-Throughput Sequencing and Genome-Wide Association Studies HIV/AIDS, tuberculosis (TB), and malaria are 3 major global public health threats that undermine development in many resource-poor settings. Recently, the notion that positive selection during epidemics or longer periods of exposure to common infectious diseases may have had a major effect in modifying the constitution of the human genome is being interrogated at a large scale in many populations around the world. This positive selection from infectious diseases increases power to detect associations in genome-wide association studies (GWASs). High-throughput sequencing (HTS) has transformed both the management of infectious diseases and continues to enable large-scale functional characterization of host resistance/susceptibility alleles and loci; a paradigm shift from single candidate gene studies. Application of genome sequencing technologies and genomics has enabled us to interrogate the host-pathogen interface for improving human health. Human populations are constantly locked in evolutionary arms races with pathogens; therefore, identification of common infectious disease-associated genomic variants/markers is important in therapeutic, vaccine development, and screening susceptible individuals in a population. This review describes a range of host-pathogen genomic loci that have been associated with disease susceptibility and resistant patterns in the era of HTS. We further highlight potential opportunities for these genetic markers.

negative: Prevention of household transmission crucial to stop the catastrophic spread of COVID-19 in cities After weeks under lockdown, metropolitan areas fighting the spread of COVID-19 aim to balance public health goals with social and economic standards for well-being. Mathematical models of disease transmission seeking to evaluate mitigation strategies must assess the possible impacts of social distancing, economic lockdowns and other measures. However, obscure relations between model parameters and real-world phenomena complicate such analyses. Here, we use a high-resolution metapopulation model of Guadalajara (GDL, Western Mexico) to represent daily mobility patterns driven by economic activities and their relation to epidemic growth. Given the prominence of essential activities in the city's economy, we find that strategies aiming to mitigate the risk of out-of-home interactions are insufficient to stop the catastrophic spread of COVID-19. Using baseline reproduction numbers R0 = [2.5, 3.0] in the absence of interventions, our simulations suggest that household transmission alone can make Rt ~ 1, and is estimated to drive 70 {+/-} 15% of current epidemic growth. This sets an upper bound for the impact of mobility-based interventions, which are unlikely to lower Rt below 1.3 and must be complemented with aggressive campaigns for early case detection and isolation. As laboratory testing and health services become insufficient to meet demand in GDL and most other cities, we propose that cities facilitate guidelines and equipment to help people curb spreading within their own homes. Postponing these actions will increase their economic cost and decrease their potential returns.

negative: Climatic influences on the worldwide spread of SARS-CoV-2 The rapid global spread of the novel, pathogenic, SARS-CoV-2 causing the severe acute respiratory disease COVID-19, becomes a major health problem worldwide and pose the need for international predictive programs. Given the lack of both specific drugs and an efficient preventive vaccine, the expectation that SARS-CoV-2 transmission rate might decrease in temperate regions during summer, dominated the social scene. Here, we attempted a prediction of the worldwide spread of the infections based on climatic data, expressed by 19 bioclimatic variables. The calculated probability maps shown that potential areas of infection follow a shift from the Tropical to Temperate and Mediterranean Bioclimatic regions, and back to the Tropics again. Maps show an increased probability of infections in Europe, followed by an expansion covering areas of the Middle East and Northern Africa, as well as Eastern coastal areas of North America, South-Eastern coastal areas of Latin America and two areas of Southern Australia, and later return to areas of Southeastern Asia, in a manner similar to that of influenza strains (H3N2). Our approach may therefore be of value for the worldwide spread of SARS-CoV-2, suggesting an optimistic scenario of asynchronous seasonal global outbreaks, like other viral respiratory diseases. Consequently, we suggest the incorporation of a climatic impact in the design and implementation of public health policies. Maps of our model are available (constantly updated up to the saturation of the model) at: https://navaak.shinyapps.io/CVRisk/.

negative: Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China Background: The 2019 coronavirus disease (COVID-19) epidemic is a public health emergency of international concern and poses a challenge to psychological resilience. Research data are needed to develop evidence-driven strategies to reduce adverse psychological impacts and psychiatric symptoms during the epidemic. The aim of this study was to survey the general public in China to better understand their levels of psychological impact, anxiety, depression, and stress during the initial stage of the COVID-19 outbreak. The data will be used for future reference. Methods: From 31 January to 2 February 2020, we conducted an online survey using snowball sampling techniques. The online survey collected information on demographic data, physical symptoms in the past 14 days, contact history with COVID-19, knowledge and concerns about COVID-19, precautionary measures against COVID-19, and additional information required with respect to COVID-19. Psychological impact was assessed by the Impact of Event Scale-Revised (IES-R), and mental health status was assessed by the Depression, Anxiety and Stress Scale (DASS-21). Results: This study included 1210 respondents from 194 cities in China. In total, 53.8% of respondents rated the psychological impact of the outbreak as moderate or severe; 16.5% reported moderate to severe depressive symptoms; 28.8% reported moderate to severe anxiety symptoms; and 8.1% reported moderate to severe stress levels. Most respondents spent 20–24 h per day at home (84.7%); were worried about their family members contracting COVID-19 (75.2%); and were satisfied with the amount of health information available (75.1%). Female gender, student status, specific physical symptoms (e.g., myalgia, dizziness, coryza), and poor self-rated health status were significantly associated with a greater psychological impact of the outbreak and higher levels of stress, anxiety, and depression (p < 0.05). Specific up-to-date and accurate health information (e.g., treatment, local outbreak situation) and particular precautionary measures (e.g., hand hygiene, wearing a mask) were associated with a lower psychological impact of the outbreak and lower levels of stress, anxiety, and depression (p < 0.05). Conclusions: During the initial phase of the COVID-19 outbreak in China, more than half of the respondents rated the psychological impact as moderate-to-severe, and about one-third reported moderate-to-severe anxiety. Our findings identify factors associated with a lower level of psychological impact and better mental health status that can be used to formulate psychological interventions to improve the mental health of vulnerable groups during the COVID-19 epidemic.

negative: SurviveCovid-19 -- A Game for Improving Awareness of Social Distancing and Health Measures for Covid-19 Pandemic Pandemics have threatened human race many a times. One of the most important tasks during a pandemic is to bring awareness among people. Bringing awareness contributes a lot in controlling any pandemic. Covid-19 has been causing severe loss to the human race. Considering the mode of spread and the level of severity of this disease, it is extremely important to make people aware of various safety precautions such as using sanitizers and masks and maintaining social distancing, that are to be followed to prevent the disease and break the chain of spread. This mode of educating individuals about the disease is being widely carried out as announcements through online or physical awareness campaigns, advertisements in the media and so on. The younger generations in the present day spend considerably more time on mobile phones and games. However, there are very few mobile applications or games, aimed to bring awareness about a pandemic, which is much lesser in case of Covid-19. Also, considering the lockdown scenario across the world, games also act as a good pass time indoors. Hence, we propose a 2D survival based game, SurviveCovid-19, aimed to educate people about safety precautions to be taken for Covid-19 outside their homes, by incorporating social distancing and usage of masks and sanitizers in the game. SurviveCovid-19 has been designed as an Android based mobile game and has been evaluated through a remote qualitative user survey, with 20 volunteers. The results of the survey are promising with all the questions of survey having mean value greater than 3.6.

negative: Creative Production of ‘COVID‐19 Social Distancing’ Narratives on Social Media This paper offers an insight into the role of young people in shifting risk perception of the current global pandemic, COVID‐19, via social distancing narratives on social media. Young people are creatively and affectively supporting the social distancing initiatives in Brunei Darussalam through the use of social media platforms such as Instagram, Twitter, and Tik Tok. Using qualitative content analysis (QCA) data of social media content by Bruneian youth, this paper reveals the localised and contextualised creative production of five ‘social distancing’ narratives as a response to the national and global concerns in times of a global pandemic: narrative of fear; narrative of responsibility; narrative of annoyance; narrative of fun; and narrative of resistance. This paper reflects on three key socio‐cultural reconfigurations that have broader implications beyond the COVID‐19 crisis: new youth spatialities and social engagements; youth leadership in development; and consideration of social participation and reach in risk communication.

negative: Easing social distancing index after COVID-19 pandemic Abstract Context Easing social distancing (ESD) is a global public health issue in post-pandemic period of COVID-19 and requires a simple index for real time assessment. Objective We aimed to develop a simple index for ESD to quantify the impacts of social distancing for reducing confirmed infected cases, optimal triage and care of patients for recovery, and critical care capacity for reducing death from COVID-19. Design, Setting, and Participants Data on the retrospective cohort of 185 countries with reported numbers on confirmed cases, recovery, and death from COVID-19 were retrieved from publicity available repository. Up to May 31, a total of 5,844,136 confirmed cases, 2,639,961 recovered, and 327,487 deaths were reported globally. Main Outcome Measures The ESD index measured by cumulative number of COVID-19 cases and recovery and case-fatality rate. Results We developed a simple index for the guidance of easing social distancing (ESD). If the ESD index is less than 1, ESD would be considered. The global ESD index declined from 3.87 at peak in March to 1.35 by the end of May, consisting of 56.76% countries/regions (105/185) with the ESD lower than one. Conclusion and Relevance This simple ESD index provides a quantitative assessment on whether and when to ease social distancing from local to global community.

negative: Future of COVID-19 in Italy: A mathematical perspective We have proposed an SEIR compartmental mathematical model. The prime objective of this study is to analyze and forecast the pandemic in Italy for the upcoming months. The basic reproduction number has been calculated. Based on the current situation in Italy, in this paper, we will estimate the possible time for the end of the pandemic in the country. The impact of lockdown and rapid isolation on the spread of the pandemic are also discussed. Further, we have studied four of the most pandemic affected regions in Italy. Using the proposed model, a prediction has been made about the duration of pandemic in these regions. The variation in the basic reproduction number corresponding to the sensitive parameters of the model is also examined.

negative: Adapting palliative radiation therapy for bone metastases during the Covid-19 pandemic: GEMO position paper The current health crisis caused by COVID-19 is a challenge for oncology treatment, especially when it comes to radiotherapy. Cancer patients are already known to be very fragile and COVID-19 brings about the risk of severe respiratory complications. In order to treat patients safely while protecting medical teams, the entire health care system must optimize the way it approaches prevention and treatment at a time when social distancing is key to stemming this pandemic. All indications and treatment modalities must be re-discussed. This is particularly the case for radiotherapy of bone metastases for which it is possible to reduce the number of sessions, the frequency of transport and the complexity of treatments. These changes will have to be discussed according to the organization of each radiotherapy department and the health situation, while medical teams must remain vigilant about the risks of complications of bone metastases, particularly spinal metastases. In this short piece, the members of the GEMO (the European Study Group of Bone Metastases) offer a number of recommendations to achieve the above objectives, both in general and in relation to five of the most common situations on radiation therapy for bone metastases.

negative: The Covid19Impact Survey: Assessing the Pulse of the COVID-19 Pandemic in Spain via 24 questions In this paper, we describe the results of analyzing a large-scale survey, called the Covid19Impact survey, to assess citizens feedback on four areas related to the COVID-19 pandemic in Spain: social contact behavior, financial impact, working situation and health status. A total of 24 questions cover the areas of demographics, their home situation, social contact behavior, personal economic impact, their workplace situation and their health. The survey was responded to by 156,614 participants between the evening of March 28th and April 2nd, 2020. Such a large response enables us to gain new insights, as well as an unprecedented glimpse at respondents personal experiences and concerns during the current COVID-19 pandemic. From the analysis, we draw several implications for the design of public policies related to the management of the COVID-19 pandemic.

negative: Conducting phase 1 cancer clinical trials during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)–related disease pandemic

negative: Behavioural change models for infectious disease transmission: a systematic review (2010–2015) We review behavioural change models (BCMs) for infectious disease transmission in humans. Following the Cochrane collaboration guidelines and the PRISMA statement, our systematic search and selection yielded 178 papers covering the period 2010–2015. We observe an increasing trend in published BCMs, frequently coupled to (re)emergence events, and propose a categorization by distinguishing how information translates into preventive actions. Behaviour is usually captured by introducing information as a dynamic parameter (76/178) or by introducing an economic objective function, either with (26/178) or without (37/178) imitation. Approaches using information thresholds (29/178) and exogenous behaviour formation (16/178) are also popular. We further classify according to disease, prevention measure, transmission model (with 81/178 population, 6/178 metapopulation and 91/178 individual-level models) and the way prevention impacts transmission. We highlight the minority (15%) of studies that use any real-life data for parametrization or validation and note that BCMs increasingly use social media data and generally incorporate multiple sources of information (16/178), multiple types of information (17/178) or both (9/178). We conclude that individual-level models are increasingly used and useful to model behaviour changes. Despite recent advancements, we remain concerned that most models are purely theoretical and lack representative data and a validation process.

negative: Role of modelling in COVID-19 policy development Models have played an important role in policy development to address the COVID-19 outbreak from its emergence in China to the current global pandemic. Early projections of international spread influenced travel restrictions and border closures. Model projections based on the virus’s infectiousness demonstrated its pandemic potential, which guided the global response to and prepared countries for increases in hospitalisations and deaths. Tracking the impact of distancing and movement policies and behaviour changes has been critical in evaluating these decisions. Models have provided insights into the epidemiological differences between higher and lower income countries, as well as vulnerable population groups within countries to help design fit-for-purpose policies. Economic evaluation and policies have combined epidemic models and traditional economic models to address the economic consequences of COVID-19, which have informed policy calls for easing restrictions. Social contact and mobility models have allowed evaluation of the pathways to safely relax mobility restrictions and distancing measures. Finally, models can consider future end-game scenarios, including how suppression can be achieved and the impact of different vaccination strategies.

negative: GIS-based spatial modeling of COVID-19 incidence rate in the continental United States Abstract During the first 90 days of the COVID-19 outbreak in the United States, over 675,000 confirmed cases of the disease have been announced, posing unprecedented socioeconomic burden to the country. Due to inadequate research on geographic modeling of COVID-19, we investigated county-level variations of disease incidence across the continental United States. We compiled a geodatabase of 35 environmental, socioeconomic, topographic, and demographic variables that could explain the spatial variability of disease incidence. Further, we employed spatial lag and spatial error models to investigate spatial dependence and geographically weighted regression (GWR) and multiscale GWR (MGWR) models to locally examine spatial non-stationarity. The results suggested that even though incorporating spatial autocorrelation could significantly improve the performance of the global ordinary least square model; these models still represent a significantly poor performance compared to the local models. Moreover, MGWR could explain the highest variations (adj. R2: 68.1%) with the lowest AICc compared to the others. Mapping the effects of significant explanatory variables (i.e., income inequality, median household income, the proportion of black females, and the proportion of nurse practitioners) on spatial variability of COVID-19 incidence rates using MGWR could provide useful insights to policymakers for targeted interventions.

negative: Editorial JTH 16 –The Coronavirus Disease COVID-19 and implications for transport and health

negative: Retweeting for COVID-19: Consensus building, information sharing, dissent, and lockdown life Purpose: Public attitudes towards COVID-19 and social distancing are critical in reducing its spread. It is therefore important to understand public reactions, information dissemination and consensus building in all major forms, including social media. This article investigates important issues reflected on Twitter. Design/methodology/approach: A thematic analysis of the most retweeted English-language tweets on Twitter mentioning COVID-19 during March 10-29, 2020. Findings: The main themes identified for the 87 qualifying tweets accounting for 14 million retweets were: lockdown life; attitude towards social restrictions; politics; safety messages; people with COVID-19; support for key workers; work; and COVID-19 facts/news. Research limitations/implications: Twitter played many positive roles, mainly through unofficial tweets. Users shared social distancing information, helped build support for social distancing, criticised government responses, expressed support for key workers, and helped each other to cope with social isolation. A few popular tweets not supporting social distancing show that government messages sometimes failed. Practical implications: Public health campaigns in future may consider encouraging grass roots social web activity to support campaign goals. At a methodological level, analysing retweet counts emphasised politics and ignored practical implementation issues. Originality/value: This is the first qualitative analysis of general COVID-19-related retweeting.

negative: COVID-19 Risk Assessment Tool: Dual application of risk communication and risk governance Abstract Risk awareness is the best way to prevent and slow-down the transmission of the COVID-19 pandemic. Risk awareness is achieved through communication of risk assessment. Effective risk communication is an important measure to control the infodemic. Most risk assessment tools focus on either tracking the affected patients or diagnosing a probable health condition through symptoms. RIKA India introduces an innovative Risk Assessment Tool which goes beyond the symptom detection and patient tracking. It includes four factors in assessment of risk: Health, Behaviour, Exposure and Social Policy. Each of these four factors have sub-factors which help to assess the overall risk in a more comprehensive way and also present it to the user in a simplified way. The paper discusses the importance of the Risk Assessment Tool for awareness generation and decision making. Further, the datasets generated through the tool have been analysed to understand the key intervention areas for COVID-19 response and management.

negative: Social distancing in covid-19: what are the mental health implications?

negative: Contact structure, mobility, environmental impact and behaviour: the importance of social forces to infectious disease dynamics and disease ecology. Human factors, including contact structure, movement, impact on the environment and patterns of behaviour, can have significant influence on the emergence of novel infectious diseases and the transmission and amplification of established ones. As anthropogenic climate change alters natural systems and global economic forces drive land-use and land-cover change, it becomes increasingly important to understand both the ecological and social factors that impact infectious disease outcomes for human populations. While the field of disease ecology explicitly studies the ecological aspects of infectious disease transmission, the effects of the social context on zoonotic pathogen spillover and subsequent human-to-human transmission are comparatively neglected in the literature. The social sciences encompass a variety of disciplines and frameworks for understanding infectious diseases; however, here we focus on four primary areas of social systems that quantitatively and qualitatively contribute to infectious diseases as social-ecological systems. These areas are social mixing and structure, space and mobility, geography and environmental impact, and behaviour and behaviour change. Incorporation of these social factors requires empirical studies for parametrization, phenomena characterization and integrated theoretical modelling of social-ecological interactions. The social-ecological system that dictates infectious disease dynamics is a complex system rich in interacting variables with dynamically significant heterogeneous properties. Future discussions about infectious disease spillover and transmission in human populations need to address the social context that affects particular disease systems by identifying and measuring qualitatively important drivers.This article is part of the themed issue 'Opening the black box: re-examining the ecology and evolution of parasite transmission'.

negative: A Noncooperative Game Analysis for Controlling COVID-19 Outbreak COVID-19 is a global epidemic. Till now, there is no remedy for this epidemic. However, isolation and social distancing are seemed to be effective to control this pandemic. In this paper, we provide an analytical model on the effectiveness of the sustainable lockdown policy that accommodates both isolation and social distancing features of the individuals. To promote social distancing, we analyze a noncooperative game environment that provides an incentive for maintaining social distancing. Furthermore, the sustainability of the lockdown policy is also interpreted with the help of a game-theoretic incentive model for maintaining social distancing. Finally, an extensive numerical analysis is provided to study the impact of maintaining a social-distancing measure to prevent the Covid-19 outbreak. Numerical results show that the individual incentive increases more than 85% with an increasing percentage of home isolation from 25% to 100% for all considered scenarios. The numerical results also demonstrate that in a particular percentage of home isolation, the individual incentive decreases with an increasing number of individuals.

negative: Full genome viral sequences inform patterns of SARS-CoV-2 spread into and within Israel Full genome sequences are increasingly used to track the geographic spread and transmission dynamics of viral pathogens. Here, with a focus on Israel, we sequenced 212 SARS-CoV-2 sequences and use them to perform a comprehensive analysis to trace the origins and spread of the virus. A phylogenetic analysis including thousands of globally sampled sequences allowed us to infer multiple independent introductions into Israel, followed by local transmission. Returning travelers from the U.S. contributed dramatically more to viral spread relative to their proportion in incoming infected travelers. Using phylodynamic analysis, we estimated that the basic reproduction number of the virus was initially around ~2.0-2.6, dropping by two-thirds following the implementation of social distancing measures. A comparison between reported and model-estimated case numbers indicated high levels of transmission heterogeneity in SARS-CoV-2 spread, with between 1-10% of infected individuals resulting in 80% of secondary infections. Overall, our findings underscore the ability of this virus to efficiently transmit between and within countries, as well as demonstrate the effectiveness of social distancing measures for reducing its spread.

negative: Research on the Influence of Effective Distance Between Cities on the Cross-regional Transmission of COVID-19 The COVID-19 epidemic in China has been effectively controlled. It is of great significance to study the law of cross-regional spread of the epidemic, for the prevention and control of the COVID-19 in the future in China and other countries or regions. In this study, the cross-regional connection intensity between cities was characterized based on the probability and the effective distance of the shortest path tree, and the empirical analysis was carried out based on the high-frequency data such as the cases of COVID 19 outbreaks. It is concluded that the higher the intensity of inter-city connection, the larger scale the cross-regional spread of the epidemic.

negative: Demographic, etiological, and histological pulmonary analysis of patients with acute respiratory failure: a study of 19 years of autopsies INTRODUCTION: Acute respiratory failure has been one of the most important causes of death in intensive care units, and certain aspects of its pulmonary pathology are currently unknown. OBJECTIVES: The objective was to describe the demographic data, etiology, and pulmonary histopathological findings of different diseases in the autopsies of patients with acute respiratory failure. METHOD: Autopsies of 4,710 patients with acute respiratory failure from 1990 to 2008 were reviewed, and the following data were obtained: age, sex, and major associated diseases. The pulmonary histopathology was categorized as diffuse alveolar damage, pulmonary edema, alveolar hemorrhage, and lymphoplasmacytic interstitial pneumonia. The odds ratio of the concordance between the major associated diseases and specific autopsy findings was calculated using logistic regression. RESULTS: Bacterial bronchopneumonia was present in 33.9% of the cases and cancer in 28.1%. The pulmonary histopathology showed diffuse alveolar damage in 40.7% (1,917) of the cases. A multivariate analysis showed a significant and powerful association between diffuse alveolar damage and bronchopneumonia, HIV/AIDS, sepsis, and septic shock, between liver cirrhosis and pulmonary embolism, between pulmonary edema and acute myocardial infarction, between dilated cardiomyopathy and cancer, between alveolar hemorrhage and bronchopneumonia and pulmonary embolism, and between lymphoplasmacytic interstitial pneumonia and HIV/AIDS and liver cirrhosis. CONCLUSIONS: Bronchopneumonia was the most common diagnosis in these cases. The most prevalent pulmonary histopathological pattern was diffuse alveolar damage, which was associated with different inflammatory conditions. Further studies are necessary to elucidate the complete pathophysiological mechanisms involved with each disease and the development of acute respiratory failure.

negative: Twitter discussions and emotions about COVID-19 pandemic: a machine learning approach The objective of the study is to examine coronavirus disease (COVID-19) related discussions, concerns, and sentiments that emerged from tweets posted by Twitter users. We analyze 4 million Twitter messages related to the COVID-19 pandemic using a list of 25 hashtags such as"coronavirus,""COVID-19,""quarantine"from March 1 to April 21 in 2020. We use a machine learning approach, Latent Dirichlet Allocation (LDA), to identify popular unigram, bigrams, salient topics and themes, and sentiments in the collected Tweets. Popular unigrams include"virus,""lockdown,"and"quarantine."Popular bigrams include"COVID-19,""stay home,""corona virus,""social distancing,"and"new cases."We identify 13 discussion topics and categorize them into five different themes, such as"public health measures to slow the spread of COVID-19,""social stigma associated with COVID-19,""coronavirus news cases and deaths,""COVID-19 in the United States,"and"coronavirus cases in the rest of the world". Across all identified topics, the dominant sentiments for the spread of coronavirus are anticipation that measures that can be taken, followed by a mixed feeling of trust, anger, and fear for different topics. The public reveals a significant feeling of fear when they discuss the coronavirus new cases and deaths than other topics. The study shows that Twitter data and machine learning approaches can be leveraged for infodemiology study by studying the evolving public discussions and sentiments during the COVID-19. Real-time monitoring and assessment of the Twitter discussion and concerns can be promising for public health emergency responses and planning. Already emerged pandemic fear, stigma, and mental health concerns may continue to influence public trust when there occurs a second wave of COVID-19 or a new surge of the imminent pandemic.

negative: A Data-Driven Network Model for the Emerging COVID-19 Epidemics in Wuhan, Toronto and Italy The ongoing Coronavirus Disease 2019 (COVID-19) pandemic threatens the health of humans and causes great economic losses. Predictive modelling and forecasting the epidemic trends are essential for developing countermeasures to mitigate this pandemic. We develop a network model, where each node represents an individual and the edges represent contacts between individuals where the infection can spread. The individuals are classified based on the number of contacts they have each day (their node degrees) and their infection status. The transmission network model was respectively fitted to the reported data for the COVID-19 epidemic in Wuhan (China), Toronto (Canada), and the Italian Republic using a Markov Chain Monte Carlo (MCMC) optimization algorithm. Our model fits all three regions well with narrow confidence intervals and could be adapted to simulate other megacities or regions. The model projections on the role of containment strategies can help inform public health authorities to plan control measures.

negative: COVID-19 and rationally layered social distancing

negative: Public perceptions of non-pharmaceutical interventions for reducing transmission of respiratory infection: systematic review and synthesis of qualitative studies BACKGROUND: Non-pharmaceutical public health interventions may provide simple, low-cost, effective ways of minimising the transmission and impact of acute respiratory infections in pandemic and non-pandemic contexts. Understanding what influences the uptake of non-pharmaceutical interventions such as hand and respiratory hygiene, mask wearing and social distancing could help to inform the development of effective public health advice messages. The aim of this synthesis was to explore public perceptions of non-pharmaceutical interventions that aim to reduce the transmission of acute respiratory infections. METHODS: Five online databases (MEDLINE, PsycINFO, CINAHL, EMBASE and Web of Science) were systematically searched. Reference lists of articles were also examined. We selected papers that used a qualitative research design to explore perceptions and beliefs about non-pharmaceutical interventions to reduce transmission of acute respiratory infections. We excluded papers that only explored how health professionals or children viewed non-pharmaceutical respiratory infection control. Three authors performed data extraction and assessment of study quality. Thematic analysis and components of meta-ethnography were adopted to synthesise findings. RESULTS: Seventeen articles from 16 studies in 9 countries were identified and reviewed. Seven key themes were identified: perceived benefits of non-pharmaceutical interventions, perceived disadvantages of non-pharmaceutical interventions, personal and cultural beliefs about infection transmission, diagnostic uncertainty in emerging respiratory infections, perceived vulnerability to infection, anxiety about emerging respiratory infections and communications about emerging respiratory infections. The synthesis showed that some aspects of non-pharmaceutical respiratory infection control (particularly hand and respiratory hygiene) were viewed as familiar and socially responsible actions to take. There was ambivalence about adopting isolation and personal distancing behaviours in some contexts due to their perceived adverse impact and potential to attract social stigma. Common perceived barriers included beliefs about infection transmission, personal vulnerability to respiratory infection and concerns about self-diagnosis in emerging respiratory infections. CONCLUSIONS: People actively evaluate non-pharmaceutical interventions in terms of their perceived necessity, efficacy, acceptability, and feasibility. To enhance uptake, it will be necessary to address key barriers, such as beliefs about infection transmission, rejection of personal risk of infection and concern about the potential costs and stigma associated with some interventions.

negative: Analyzing situational awareness through public opinion to predict adoption of social distancing amid pandemic COVID-19 COVID-19 pandemic has affected over 100 countries in a matter of weeks. People's response toward social distancing in the emerging pandemic is uncertain. In this study, we evaluated the influence of information (formal and informal) sources on situational awareness of the public for adopting health-protective behaviors such as social distancing. For this purpose, a questionnaire-based survey was conducted. The hypothesis proposed suggests that adoption of social distancing practices is an outcome of situational awareness which is achieved by the information sources. Results suggest that information sources, formal (P = .001) and informal (P = 0.007) were found to be significantly related to perceived understanding. Findings also indicate that social distancing is significantly influenced by situational awareness, P = .000. It can, therefore, be concluded that an increase in situational awareness in times of public health crisis using formal information sources can significantly increase the adoption of protective health behavior and in turn contain the spread of infectious diseases.

negative: Containing COVID-19 outside the isolation ward: the impact of an infection control bundle on environmental contamination and transmission in a cohorted general ward BACKGROUND: During an ongoing outbreak of COVID-19, unsuspected cases may be housed outside of dedicated isolation wards. AIM: At a Singaporean tertiary hospital, individuals with clinical syndromes compatible with COVID-19 but no epidemiologic risk were placed in cohorted general wards for COVID-19 testing. To mitigate risk, an infection control bundle was implemented comprising infrastructural enhancements, improved personal-protective-equipment (PPE), and social distancing. We assessed the impact on environmental contamination and transmission. METHOD: Upon detection of a case of COVID-19 in the dedicated general ward, patients and healthcare workers (HCWs) contacts were identified. All patient and staff-close contacts were placed on 14-day phone surveillance and followed-up for 28 days; symptomatic contacts were tested. Environmental samples were also obtained. FINDINGS: Over a 3-month period, 28 unsuspected cases of COVID-19 were contained in the dedicated general ward. In 5 of the 28 cases, sampling of the patient's environment yielded SARS-CoV-2; index cases who required supplemental oxygen had higher odds of environmental contamination (p=0.01). A total of 253 staff close-contacts and 45 patient close-contacts were identified; only 3 HCWs (1.2%, 3/253) required quarantine. On 28-day follow-up, no patient-to-HCW transmission was documented; only one symptomatic patient close-contact tested positive. CONCLUSION: Our institution successfully implemented an intervention bundle to mitigate COVID-19 transmission in a multi-bedded cohorted general ward setting.

negative: Comparison of distance measures in spatial analytical modeling for health service planning BACKGROUND: Several methodological approaches have been used to estimate distance in health service research. In this study, focusing on cardiac catheterization services, Euclidean, Manhattan, and the less widely known Minkowski distance metrics are used to estimate distances from patient residence to hospital. Distance metrics typically produce less accurate estimates than actual measurements, but each metric provides a single model of travel over a given network. Therefore, distance metrics, unlike actual measurements, can be directly used in spatial analytical modeling. Euclidean distance is most often used, but unlikely the most appropriate metric. Minkowski distance is a more promising method. Distances estimated with each metric are contrasted with road distance and travel time measurements, and an optimized Minkowski distance is implemented in spatial analytical modeling. METHODS: Road distance and travel time are calculated from the postal code of residence of each patient undergoing cardiac catheterization to the pertinent hospital. The Minkowski metric is optimized, to approximate travel time and road distance, respectively. Distance estimates and distance measurements are then compared using descriptive statistics and visual mapping methods. The optimized Minkowski metric is implemented, via the spatial weight matrix, in a spatial regression model identifying socio-economic factors significantly associated with cardiac catheterization. RESULTS: The Minkowski coefficient that best approximates road distance is 1.54; 1.31 best approximates travel time. The latter is also a good predictor of road distance, thus providing the best single model of travel from patient's residence to hospital. The Euclidean metric and the optimal Minkowski metric are alternatively implemented in the regression model, and the results compared. The Minkowski method produces more reliable results than the traditional Euclidean metric. CONCLUSION: Road distance and travel time measurements are the most accurate estimates, but cannot be directly implemented in spatial analytical modeling. Euclidean distance tends to underestimate road distance and travel time; Manhattan distance tends to overestimate both. The optimized Minkowski distance partially overcomes their shortcomings; it provides a single model of travel over the network. The method is flexible, suitable for analytical modeling, and more accurate than the traditional metrics; its use ultimately increases the reliability of spatial analytical models.

negative: Modern approaches to understanding stress and disease susceptibility: A review with special emphasis on respiratory disease Studies in animals and humans link both physical and psychological stress with an increased incidence and severity of respiratory infections. For this manuscript we define stress as the physiological responses an individual undergoes while adjusting to a continually changing environment. It is known that stressors of various types (psychological/physical) can alter the physiological levels of certain hormones, chemokines and cytokines. These alterations send information to the central nervous system to take necessary action which then sends messages to appropriate organs/tissues/cells to respond. These messages can either activate or suppress the immune system as needed and failure to compensate for this by the body can lead to serious health-related problems. Little is known how stress affects disease susceptibility, yet understanding this mechanism is important for developing effective treatments, and for improving health and food quality. The current review focuses on (a) the effects of psychological stressors in humans and animals, (b) various methodologies employed to understand stress responses and their outcomes, and (c) the current status of the attempts to correlate stress and disease with respiratory disease as model system. The methodologies included in this review span traditional epidemiological, behavioral and immunological studies to current high throughput genomic, proteomic, metabolomic/metabonomic approaches. With the advent of various newer omics and bioinformatics methodologies we postulate that it will become feasible to understand the mechanisms through which stress can influence disease onset. Although the literature in this area is limited because of the infancy of this research area, the objective of this review is to illustrate the power of new approaches to address complex biological questions. These new approaches will also aid in our understanding how these processes are related to the dynamics and kinetics of changes in expression of multiple genes at various levels.

negative: Perception of emergent epidemic of COVID-2019 / SARS CoV-2 on the Polish Internet Problem: Due to the spread of SARS CoV-2 virus infection and COVID-2019 disease, there is an urgent need to analyze COVID-2019 epidemic perception in Poland. This would enable authorities for preparation of specific actions minimizing public health and economic risks. Methods: We study the perception of COVID-2019 epidemic in Polish society using quantitative analysis of its digital footprints on the Internet (on Twitter, Google, YouTube, Wikipedia and electronic media represented by Event Registry) from January 2020 to 12.03.2020 (before and after official introduction to Poland on 04.03.2020). To this end we utilize data mining, social network analysis, natural language processing techniques. Each examined internet platform was analyzed for representativeness and composition of the target group. Results: We identified three major cluster of the interest before disease introduction on the topic COVID-2019: China- and Italy-related peaks on all platforms, as well as a peak on social media related to the recent special law on combating COVID-2019. Besides, there was a peak in interest on the day of officially confirmed introduction as well as an exponential increase of interest when the Polish government declared war against disease with a massive mitigation program. From sociolingistic perspective, we found that concepts and issues of threat, fear and prevention prevailed before introduction. After introduction, practical concepts about disease and epidemic dominate. Twitter reflected the clear, structural division of the Polish political sphere. We were able to identify potential sources of misinformation as well as key actors (especially early adopters) and influencers. Conclusions: Traditional and social media not only reflect reality, but also create it. Polish authorities, having a reliable analysis of the perception of the problem, could optimally prepare and manage the social dimension of the current epidemic and future ones. Due to filter bubbles observed on Twitter, public information campaigns might have less impact on society than expected. For greater penetration, it might be necessary to diversify information channels to reach as many people as possible which might already be happening. Moreover, it might be necessary to prevent the spread of disinformation, which is now possible due to the special law on combating COVID-2019.

negative: Les professionnels de santé face à la pandémie de la maladie à coronavirus (COVID-19): quels risques pour leur santé mentale? RÉSUMÉ Objectifs: La pandémie de la maladie à coronavirus (COVID-19) a provoqué une crise sanitaire majeure et mis en quarantaine la moitié de la population planétaire. En France, elle a provoqué une réorganisation en urgence de l’offre de soins mobilisant les soignants dans un climat d’incertitude. L'objectif du présent article est de faire le point sur les risques associés à l’exposition des soignants au COVID-19 pour leur santé mentale. Méthodes: Les auteurs ont conduit une revue de la littérature internationale tenant compte des données des précédentes épidémies (SARS-CoV-1, H1N1) et des données plus récentes concernant le COVID-19. Résultats: Les caractéristiques de cette pandémie (rapidité de diffusion, connaissances incertaines, sévérité, morts de soignants) ont installé un climat anxiogène. Des facteurs organisationnels peuvent être source de stress : déficit d’équipement de protection individuel, réaffectation de postes, manque de communication, manque de matériels de soins, bouleversement de la vie quotidienne familiale et sociale. D’autres facteurs de risque sont identifiés comme l’absence de soutien, la crainte de contaminer un proche, l’isolement ou la stigmatisation sociale, le haut niveau de stress au travail, ou les patterns d’attachement insécure. Les soignants ont ainsi un risque augmenté d’anxiété, de dépression, d’épuisement, d’addiction et de trouble de stress post-traumatique. Conclusions: Cette crise sanitaire devrait nous aider à mieux comprendre la vulnérabilité des soignants à la souffrance psychologique afin de renforcer les stratégies de prévention primaire et la formation aux enjeux psychologiques des soins, de la relation, et de la gestion des situations de crises sanitaires. ABSTRACT Objectives: The coronavirus disease 2019 (COVID-19) pandemic has caused major sanitary crisis worldwide. Half of the world has been placed in quarantine. In France, this large-scale health crisis urgently triggered the restructuring and reorganization of health service delivery to support emergency services, medical intensive care units and continuing care units. Health professionals mobilized all their resources to provide emergency aid in a general climate of uncertainty. Concerns about the mental health, psychological adjustment, and recovery of health care workers treating and caring for patients with COVID-19 are now arising. The goal of the present article is to provide an up-to-date information on potential mental health risks associated with exposure of health professionals to the COVID-19 pandemic. Methods: Authors performed a narrative review identifying relevant results in the scientific and medical literature considering previous epidemics of 2003 (SARS-CoV-1) and 2009 (H1N1) with the more recent data about the COVID-19 pandemic. We highlighted most relevant data concerning the disease characteristics, the organizational factors and personal factors that may contribute to developing psychological distress and other mental health symptoms. Results: The disease characteristics of the current COVID-19 pandemic provoked a generalized climate of wariness and uncertainty, particularly among health professionals, due to a range of causes such as the rapid spread of COVID-19, the severity of symptoms it can cause in a segment of infected individuals, the lack of knowledge of the disease, and deaths among health professionals. Stress may also be caused by organizational factors, such as depletion of personal protection equipment, concern about not being able to provide competent care if deployed to new area, concern about rapidly changing information, lack of access to up-to-date information and communication, lack of specific drugs, the shortage of ventilators and intensive care unit beds necessary to care for the surge of critically ill patients, and significant change in their daily social and family life. Further risk factors have been identified, including feelings of being inadequately supported, concerns about health of self, fear of taking home infection to family members or others, and not having rapid access to testing through occupational health if needed, being isolated, feelings of uncertainty and social stigmatization, overwhelming workload, or insecure attachment. Additionally, we discussed positive social and organizational factors that contribute to enhance resilience in the face of the pandemic. There is a consensus in all the relevant literature that health care professionals are at an increased risk of high levels of stress, anxiety, depression, burnout, addiction and post-traumatic stress disorder, which could have long-term psychological implications. Conclusions: In the long run, this tragic health crisis should significantly enhance our understanding of the mental health risk factors among the health care professionals facing the COVID-19 pandemic. Reporting information such as this is essential to plan future prevention strategies. Protecting health care professionals is indeed an important component of public health measures to address large-scale health crisis. Thus, interventions to promote mental well-being in health care professionals exposed to COVID-19 need to be immediately implemented, and to strengthen prevention and response strategies by training health care professionals on mental help and crisis management.

negative: Docetaxel induces moderate ovarian toxicity in mice, primarily affecting granulosa cells of early growing follicles Advances in cancer therapy have focused attention on the quality of life of cancer survivors. Since infertility is a major concern following chemotherapy, it is important to characterize the drug-specific damage to the reproductive system to help find appropriate protective strategies. This study investigates the damage on neonatal mouse ovary maintained in vitro for 6 days, and exposed for 24 h (on Day 2) to clinically relevant doses of Docetaxel (DOC; low: 0.1 µM, mid: 1 µM, high: 10 µM). Furthermore, the study explores the putative protective action exerted by Tri-iodothyronine (T3; 10(−7) M). At the end of culture, morphological analyses and follicle counts showed that DOC negatively impacts on early growing follicles, decreasing primary follicle number and severely affecting health at the transitional and primary stages. Poor follicle health was mainly due to effects on granulosa cells, indicating that the effects of DOC on oocytes were likely to be secondary to granulosa cell damage. DOC damages growing follicles specifically, with no direct effect on the primordial follicle reserve. Immunostaining and western blotting showed that DOC induces activation of intrinsic, type II apoptosis in ovarian somatic cells; increasing the levels of cleaved caspase 3, cleaved caspase 8, Bax and cleaved poly(ADP-ribose) polymerase, while also inducing movement of cytochrome C from mitochondria into the cytosol. T3 did not prevent the damage induced by the low dose of DOC. These results demonstrated that DOC induces a gonadotoxic effect on the mouse ovary through induction of somatic cell apoptosis, with no evidence of direct effects on the oocyte, and that the damaging effect is not mitigated by T3.

negative: Viral Upper Respiratory Tract Infection and Otitis Media Complication in Young Children

negative: Synthesis, Binding and Antiviral Properties of Potent Core-Extended Naphthalene Diimides Targeting the HIV-1 Long Terminal Repeat Promoter G-Quadruplexes [Image: see text] We have previously reported that stabilization of the G-quadruplex structures in the HIV-1 long terminal repeat (LTR) promoter suppresses viral transcription. Here we sought to develop new G-quadruplex ligands to be exploited as antiviral compounds by enhancing binding toward the viral G-quadruplex structures. We synthesized naphthalene diimide derivatives with a lateral expansion of the aromatic core. The new compounds were able to bind/stabilize the G-quadruplex to a high extent, and some of them displayed clear-cut selectivity toward the viral G-quadruplexes with respect to the human telomeric G-quadruplexes. This feature translated into low nanomolar anti-HIV-1 activity toward two viral strains and encouraging selectivity indexes. The selectivity depended on specific recognition of LTR loop residues; the mechanism of action was ascribed to inhibition of LTR promoter activity in cells. This is the first example of G-quadruplex ligands that show increased selectivity toward the viral G-quadruplexes and display remarkable antiviral activity.

negative: Key Ethical Issues Discussed at CDC-Sponsored International, Regional Meetings to Explore Cultural Perspectives and Contexts on Pandemic Influenza Preparedness and Response Background: Recognizing the importance of having a broad exploration of how cultural perspectives may shape thinking about ethical considerations, the Centers for Disease Control and Prevention (CDC) funded four regional meetings in Africa, Asia, Latin America, and the Eastern Mediterranean to explore these perspectives relevant to pandemic influenza preparedness and response. The meetings were attended by 168 health professionals, scientists, academics, ethicists, religious leaders, and other community members representing 40 countries in these regions. Methods: We reviewed the meeting reports, notes and stories and mapped outcomes to the key ethical challenges for pandemic influenza response described in the World Health Organization’s (WHO’s) guidance, Ethical Considerations in Developing a Public Health Response to Pandemic Influenza: transparency and public engagement, allocation of resources, social distancing, obligations to and of healthcare workers, and international collaboration. Results: The important role of transparency and public engagement were widely accepted among participants. However, there was general agreement that no "one size fits all" approach to allocating resources can address the variety of economic, cultural and other contextual factors that must be taken into account. The importance of social distancing as a tool to limit disease transmission was also recognized, but the difficulties associated with this measure were acknowledged. There was agreement that healthcare workers often have competing obligations and that government has a responsibility to assist healthcare workers in doing their job by providing appropriate training and equipment. Finally, there was agreement about the importance of international collaboration for combating global health threats. Conclusion: Although some cultural differences in the values that frame pandemic preparedness and response efforts were observed, participants generally agreed on the key ethical principles discussed in the WHO’s guidance. Most significantly the input gathered from these regional meetings pointed to the important role that procedural ethics can play in bringing people and countries together to respond to the shared health threat posed by a pandemic influenza despite the existence of cultural differences.

negative: Acute Respiratory Distress Syndrome as an Organ Phenotype of Vascular Microthrombotic Disease: Based on Hemostatic Theory and Endothelial Molecular Pathogenesis Acute respiratory distress syndrome (ARDS) is a life-threatening noncardiogenic circulatory disorder of the lungs associated with critical illnesses such as sepsis, trauma, and immune and collagen vascular disease. Its mortality rate is marginally improved with the best supportive care. The demise occurs due to progressive pulmonary hypoxia and multi-organ dysfunction syndrome (MODS) with severe inflammation. Complement activation is a part of immune response against pathogen or insult in which membrane attack complex (MAC) is formed and eliminates microbes. If complement regulatory protein such as endothelial CD59 is underexpressed, MAC may also cause pulmonary vascular injury to the innocent bystander endothelial cell of host and provokes endotheliopathy that causes inflammation and pulmonary vascular microthrombosis, leading to ARDS. Its pathogenesis is based on a novel “two-path unifying theory” of hemostasis and “two-activation theory of the endothelium” promoting molecular pathogenesis. Endotheliopathy activates two independent molecular pathways: inflammatory and microthrombotic. The former triggers the release inflammatory cytokines and the latter promotes exocytosis of unusually large von Willebrand factor multimers (ULVWF) and platelet activation. Inflammatory pathway initiates inflammation, but microthrombotic pathway more seriously produces “microthrombi strings” composed of platelet-ULVWF complexes, which become anchored on the injured endothelial cells, and causes disseminated intravascular microthrombosis (DIT). DIT is a hemostatic disease due to lone activation of ULVWF path without activated tissue factor path. It leads to endotheliopathy-associated vascular microthrombotic disease (EA-VMTD), which orchestrates consumptive thrombocytopenia, microangiopathic hemolytic anemia, and MODS. Thrombotic thrombocytopenic purpura (TTP)-like syndrome is the hematologic phenotype of EA-VMTD. ARDS is one of organ phenotypes among MODS associated with TTP-like syndrome. The most effective treatment of ARDS can be achieved by counteracting the activated microthrombotic pathway based on two novel hemostatic theories.

negative: When Stay-at-Home Orders Leave Victims Unsafe at Home: Exploring the Risk and Consequences of Intimate Partner Violence during the COVID-19 Pandemic The novel coronavirus pandemic (hereafter COVID-19) is likely to have unprecedented impacts on the incidence and impacts of crime and violence globally. This includes impacts to the risk, consequences, and decision-making of women experiencing violence by an intimate partner (hereafter IPV). Most importantly, the COVID-19 pandemic, and its impact on the risk of IPV is likely to differentially impact vulnerable populations, including minority women and those with long histories of victimization and mental health issues. This review paper explores the potential short- and long-term implications of COVID-19 on the risk of IPV, highlighting some of the most recent preliminary data. The economic impact of the COVID-19 pandemic, record levels of male unemployment, added stressors in the home, including the care and home schooling of children, and the social distancing measures required by the epidemiological response, may serve to undermine the decades of progress made in keeping women and children safe at home. Victim police reporting, help-seeking decisions, and social service utilization during the pandemic are likely to be impacted by stay-at-home orders and social distancing requirements. The paper concludes with a discussion of the implications for providing safety planning and self-care for victims and their children.

negative: Neurological Complications in Critically Ill Patients

negative: Social prescribing: a 'natural' community-based solution. This paper discusses social prescribing as part of the wider NHS England universal personalised care model, and it describes how community nurses can engage with social prescribing systems to support community resilience. A case study based on the example of gardening, as a nature-based social prescription provided by the RHS Bridgewater Wellbeing Garden, is provided to illustrate the scope, reach and impact of non-medical, salutogenic approaches for community practitioners. The authors argue that social prescribing and, in particular, nature-based solutions, such as gardening, can be used as a non-medical asset-based approach by all health professionals working in the community as a way to promote health and wellbeing. They consider how the negative impact of social distancing resulting from COVID-19 restrictions could be diluted through collaboration between a holistic, social prescribing system and community staff. The paper presents a unique perspective on how community nurses can collaborate with link workers through social prescribing to help combat social isolation and anxiety and support resilience.

negative: Transmission potential of the novel coronavirus (COVID-19) onboard the Diamond Princess Cruises Ship, 2020 An outbreak of COVID-19 developed aboard the Princess Cruises Ship during January-February 2020. Using mathematical modeling and time-series incidence data describing the trajectory of the outbreak among passengers and crew members, we characterize how the transmission potential varied over the course of the outbreak. Our estimate of the mean reproduction number in the confined setting reached values as high as ~11, which is higher than mean estimates reported from community-level transmission dynamics in China and Singapore (approximate range: 1.1-7). Our findings suggest that Rt decreased substantially compared to values during the early phase after the Japanese government implemented an enhanced quarantine control. Most recent estimates of Rt reached values largely below the epidemic threshold, indicating that a secondary outbreak of the novel coronavirus was unlikely to occur aboard the Diamond Princess Ship.

negative: Rehabilitation Response in Pandemics The WHO declared a pandemic due to the serious health risk posed by Coronavirus disease (COVID-19). The number of infected cases is on the rise globally with escalating human, economic and societal costs. COVID-19 survivors may suffer a range of clinical, functional and psychological impairments, resulting in disabilities. Many are amenable to rehabilitation intervention. The current focus of COVID-19 management is on public health measures and acute management. As patients transfer to sub-acute care or discharged to the community, rehabilitation services need to have a number of organizational and operational models in place to provide safe effective care for patients and health professionals. There is need for global action by professional organizations in developing a structured rehabilitation approach for international response to disasters, including pandemics. This report proposes development of a ‘Rehabilitation Response Plan’ to enable the International Society of Physical and Rehabilitation Medicine, to provide crucial leadership and governance role in liaison and coordination with the WHO (and other stakeholders), to provide rehabilitation input during current and future pandemics. The key considerations include following categories: Governance, Coordination, Communication, Evaluation, and Care-continuum. These will strengthen rehabilitation, assist in the effective delivery of services, provide advocacy, and an international coordinated perspective.

negative: Managing Healthcare Worker Wellbeing in an Australian Emergency Department during The COVID‐19 Pandemic

negative: Assessing the interactions between COVID-19 and influenza in the United States The 2019–2020 influenza sentinel surveillance data exhibits unexpected trends. Typical influenza seasons have a small herald wave, followed by a decrease due to school closure during holidays, and then a main post-holiday peak that is significantly larger than the pre-holiday wave. During the 2019–2020 influenza season, influenza-like illness data in the United States appears to have a markedly lower main epidemic peak compared to what would be expected based on the pre-holiday peak. We hypothesize that the 2019–2020 influenza season does have a lower than expected burden and that this deflation is due to a behavioral or ecological interaction with COVID-19. We apply an intervention analysis to assess if this influenza season deviates from expectations, then we compare multiple hypothesized drivers of the decrease in influenza in a spatiotemporal regression model. Lastly, we develop a mechanistic metapopulation model, incorporating transmission reduction that scales with COVID-19 risk perception. We find that the 2019–2020 ILI season is smaller and decreases earlier than expected based on prior influenza seasons, and that the increase in COVID-19 risk perception is associated with this decrease. Additionally, we find that a 5% average reduction in transmission is sufficient to reproduce the observed flu dynamics. We propose that precautionary behaviors driven by COVID-19 risk perception or increased isolation driven by undetected COVID-19 spread dampened the influenza season. We suggest that when surveillance for a novel pathogen is limited, surveillance streams of co-circulating infections may provide a signal.

negative: Anaesthesia and COVID-19: infection control Summary The world is currently facing an unprecedented healthcare crisis caused by a pandemic novel beta coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The pathogen is spread by human-to-human transmission via droplets exposure and contact transfer, causing mild symptoms in the majority of cases, but critical illness, bilateral viral pneumonia, and acute respiratory distress syndrome (ARDS) in a minority. Currently, controlling infection to prevent the spread of SARS-CoV-2 is the primary public healthcare intervention used. The pace of transmission and global scale of SARS-CoV-2 infections has implications for strategic oversight, resource management, and responsiveness in infection control. This article presents a summary of learning points in epidemiological infection control from the SARS epidemic, alongside a review of evidence connecting current understanding of the virologic and environmental contamination properties of SARS-CoV-2. We present suggestions for how personal protective equipment policies relate to the viral pandemic context and how the risk of transmission by and to anaesthetists, intensivists, and other healthcare workers can be minimised.

negative: Infections: The Emergency of the New Millennium The New Millennium opened with alarming data on infections and antimicrobial resistance. Viral infections (SARS, MERS-CoV, Zika, Chikungunya, West Nile, Ebola virus infection, etc.) emerged or re-emerged with threatening outbreaks. However, viral emerging infections in some instances represented marginally a concern for developed countries that were just lapped by them. Currently, the new emergency is represented by antimicrobial resistance in bacterial infections, that is, a matter of extreme importance in developed and developing countries, where this issue has become a top priority for global policy makers and public health authorities. New mechanisms of resistance continue to emerge and spread globally, threatening our ability to treat common infections. The overuse and misuse of antimicrobials both in the human and animal field, and their dispersion in the environment pose a risk for selection of mechanisms of resistance of germs. Some settings, like the healthcare facilities, where the use of antimicrobials is obviously intense and infection prevention and control can be poor, represent the reservoir for multidrug-resistant organisms and, sometimes, the melting pot for pan-resistant strains.

negative: Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period It is urgent to understand the future of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) transmission. We used estimates of seasonality, immunity, and cross-immunity for betacoronaviruses OC43 and HKU1 from time series data from the USA to inform a model of SARS-CoV-2 transmission. We projected that recurrent wintertime outbreaks of SARS-CoV-2 will probably occur after the initial, most severe pandemic wave. Absent other interventions, a key metric for the success of social distancing is whether critical care capacities are exceeded. To avoid this, prolonged or intermittent social distancing may be necessary into 2022. Additional interventions, including expanded critical care capacity and an effective therapeutic, would improve the success of intermittent distancing and hasten the acquisition of herd immunity. Longitudinal serological studies are urgently needed to determine the extent and duration of immunity to SARS-CoV-2. Even in the event of apparent elimination, SARS-CoV-2 surveillance should be maintained since a resurgence in contagion could be possible as late as 2024.

negative: A Tempo-geographic Analysis of Global COVID-19 Epidemic Outside of China BACKGROUND: Understanding the global epidemic trends, geographic distribution, and transmission patterns of COVID-19 contribute to providing timely information for the global response of the epidemic. This study aims to understand the global pandemic geospatial patterns and trends and identify new epicenters requiring urgent attention. METHODS: Data on COVID-19 between 31(st) Dec. 2019 and 14(th) Mar. 2020 was included. The epidemic trend was analyzed using joinpoint regressions; the growth of affected countries was by descriptive analysis; and the global distribution and transmission trend by spatial analysis. FINDINGS: The number of new cases in the regions outside of China slowly increased before 24(th) Feb. and rapidly accelerated after 24(th) Feb. Compared to China, other affected countries experienced a longer duration of a slow increase at the early stage and rapid growth at the latter stages. The first apparent increase in the number of affected countries occurred from 23(rd) Jan to 1(st) Feb, and the second apparent increase started from 25(th) Feb. The fist COVID-19 cases reported by countries from 28(th) Feb. were mainly imported from Europe. The geographic distribution changed from single-center (13(th) Jan. - 20(th) Feb.) to multi-centers pattern (20(th) Feb. – 14(th) Mar.). More countries were affected with COVID-19 and developed local transmission. INTERPRETATION: The joinpoint regression and geospatial analysis indicated a multi-center pandemic of COVID-19. Strategies to prevent the new multiple centers as well as prevent ongoing transmission are needed. FUNDING: NIH.

negative: Covid-19: Brazil's president rallies supporters against social distancing.

negative: AN INTERACTIVE COVID-19 MOBILITY IMPACT AND SOCIAL DISTANCING ANALYSIS PLATFORM The research team has utilized privacy-protected mobile device location data, integrated with COVID-19 case data and census population data, to produce a COVID-19 impact analysis platform that can inform users about the effects of COVID-19 spread and government orders on mobility and social distancing. The platform is being updated daily, to continuously inform decision-makers about the impacts of COVID-19 on their communities using an interactive analytical tool. The research team has processed anonymized mobile device location data to identify trips and produced a set of variables including social distancing index, percentage of people staying at home, visits to work and non-work locations, out-of-town trips, and trip distance. The results are aggregated to county and state levels to protect privacy and scaled to the entire population of each county and state. The research team are making their data and findings, which are updated daily and go back to January 1, 2020, for benchmarking, available to the public in order to help public officials make informed decisions. This paper presents a summary of the platform and describes the methodology used to process data and produce the platform metrics.

negative: Brief History of Pandemics (Pandemics Throughout History) Intermittent outbreaks of infectious diseases have had profound and lasting effects on societies throughout history. Those events have powerfully shaped the economic, political, and social aspects of human civilization, with their effects often lasting for centuries. Epidemic outbreaks have defined some of the basic tenets of modern medicine, pushing the scientific community to develop principles of epidemiology, prevention, immunization, and antimicrobial treatments. This chapter outlines some of the most notable outbreaks that took place in human history and are relevant for a better understanding of the rest of the material. Starting with religious texts, which heavily reference plagues, this chapter establishes the fundamentals for our understanding of the scope, social, medical, and psychological impact that some pandemics effected on civilization, including the Black Death (a plague outbreak from the fourteenth century), the Spanish Flu of 1918, and the more recent outbreaks in the twenty-first century, including SARS, Ebola, and Zika.

negative: Rethinking how we care for our patients in a time of social distancing Online consultations

negative: Afectación clínica y sintomatológica en pacientes mayores de 65 años por COVID-19

negative: Covid-19: Brazil's president rallies supporters against social distancing

negative: Coronavirus spreads The deadly virus that emerged in Wuhan, China, may be much more contagious than initially thought. Jessica Hamzelou reports

negative: Utility of Substandard Face Mask Options for Health Care Workers During the COVID-19 Pandemic

negative: Covid-19: social distancing or social isolation?

negative: A predictive decision-aid methodology for dynamic mitigation of influenza pandemics In a recent report, the Institute of Medicine has stressed the need for dynamic mitigation strategies for pandemic influenza. In response to the need, we have developed a simulation-based optimization methodology for generating dynamic predictive mitigation strategies for pandemic outbreaks affecting several regions. Our methodology can accommodate varying virus and population dynamics. It progressively allocates a limited budget to procure vaccines and antivirals, capacities for their administration, and resources required to enforce social distancing. The methodology uses measures of morbidity, mortality, and social distancing, which are translated into the costs of lost productivity and medical services. The simulation model was calibrated using historic pandemic data. We illustrate the use of our methodology on a mock outbreak involving over four million people residing in four major population centers in Florida, USA. A sensitivity analysis is presented to estimate the impact of changes in the budget availability and variability of some of the critical parameters of mitigation strategies. The methodology is intended to assist public health policy makers.

negative: Physical Distancing in COVID-19 May Exacerbate Experiences of Social Isolation among People Living with HIV

negative: Community Responses during Early Phase of COVID-19 Epidemic, Hong Kong During the early phase of the coronavirus disease epidemic in Hong Kong, 1,715 survey respondents reported high levels of perceived risk, mild anxiety, and adoption of personal-hygiene, travel-avoidance, and social-distancing measures. Widely adopted individual precautionary measures, coupled with early government actions, might slow transmission early in the outbreak.

negative: A Vision-based Social Distancing and Critical Density Detection System for COVID-19 Social distancing has been proven as an effective measure against the spread of the infectious COronaVIrus Disease 2019 (COVID-19). However, individuals are not used to tracking the required 6-feet (2-meters) distance between themselves and their surroundings. An active surveillance system capable of detecting distances between individuals and warning them can slow down the spread of the deadly disease. Furthermore, measuring social density in a region of interest (ROI) and modulating inflow can decrease social distancing violation occurrence chance. On the other hand, recording data and labeling individuals who do not follow the measures will breach individuals' rights in free-societies. Here we propose an Artificial Intelligence (AI) based real-time social distancing detection and warning system considering four important ethical factors: (1) the system should never record/cache data, (2) the warnings should not target the individuals, (3) no human supervisor should be in the detection/warning loop, and (4) the code should be open-source and accessible to the public. Against this backdrop, we propose using a monocular camera and deep learning-based real-time object detectors to measure social distancing. If a violation is detected, a non-intrusive audio-visual warning signal is emitted without targeting the individual who breached the social distancing measure. Also, if the social density is over a critical value, the system sends a control signal to modulate inflow into the ROI. We tested the proposed method across real-world datasets to measure its generality and performance. The proposed method is ready for deployment, and our code is open-sourced.

negative: Substance misuse during COVID-19: protecting people who use drugs

negative: The EMPOWER-SUSTAIN e-Health Intervention to improve patient activation and self-management behaviours among individuals with Metabolic Syndrome in primary care: study protocol for a pilot randomised controlled trial BACKGROUND: Epidemiological studies conducted in various parts of the world have clearly demonstrated that metabolic syndrome (MetS) is an increasing global health problem, not only in Western societies but also in Asian populations. Web-based and mobile phone-based self-management applications have been proven to be effective in improving self-management behaviour of patients with MetS components (i.e., diabetes or hypertension). However, evidence is lacking in terms of their effectiveness specifically for patients with MetS. The aim of this pilot study is to evaluate the feasibility and potential effectiveness of the EMPOWER-SUSTAIN Self-Management e-Health Intervention in improving activation and self-management behaviours among patients with MetS. This paper presents the study protocol. METHODS: A pilot randomised controlled trial will be conducted in a university primary care clinic. A total of 232 patients aged 18–60 years with MetS will be recruited; 116 will be randomised to receive the EMPOWER-SUSTAIN intervention for 6 months, and another 116 patients will continue with usual care. The EMPOWER-SUSTAIN intervention is a multifaceted chronic disease management strategy based on the Chronic Care Model and persuasive technology theory. It consists of training primary care physicians, nurses and patients to use the EMPOWER-SUSTAIN web-based self-management mobile app, strengthening the patient–physician relationship and reinforcing the use of relevant clinical practice guidelines to guide management and prescribing. The primary outcome is the mean change in patient activation score using the Patient Activation Measure short form Malay version (PAM-13-M) questionnaire. The secondary outcomes include the changes in waist circumference, body mass index, blood pressure, patient physical activity level, eating behaviour, perception of chronic illness care, satisfaction with patient–physician interaction, and perceived absolute 10-year cardiovascular disease risk. Feasibility of implementing the intervention will be evaluated. This includes acceptability of the intervention, estimating the likely rate of participant recruitment and retention, appropriateness of the outcome measures, calculation of sample size, and the intervention’s potential effectiveness. CONCLUSION: To our knowledge, this is the first study in Malaysia that aims to determine the feasibility of a multifaceted e-health intervention, as well as to indicate more useful aspects of this intervention for further exploration in a larger trial. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04120779. Registered on 9 October 2019, protocol version 1.

negative: Optimal frequency setting of metro services in the age of COVID-19 distancing measures Public transport is one of the most disrupted sectors of the COVID-19 pandemic with reported ridership drops up to 90% in majorly affected countries. As many government authorities strive to partially resume activities, public transport operators are in an urgent need for models that can evaluate the impact of different social distancing policies on operational and passenger-related costs. In this study, we introduce a mixed-integer quadratic programming model for the redesign of public transport services considering the operational, passenger, and revenue loss-related costs by evaluating the effects of different social distancing policies. Our model is applied at the metro network of Washington D.C. and provides optimal redistribution of vehicles across lines for different social distancing scenarios. This model can be used as a decision support tool by other policymakers and public transport operators that are in need of evaluating the costs related to the implementation of different social distancing policies.

negative: Potential effect of blood purification therapy in reducing cytokine storm as a late complication of critically ill COVID-19

negative: Quantifying human mobility behavior changes in response to non-pharmaceutical interventions during the COVID-19 outbreak in the United States Ever since the first case of the novel coronavirus disease (COVID-19) was confirmed in Wuhan, China, social distancing has been promoted worldwide, including the United States. It is one of the major community mitigation strategies, also known as non-pharmaceutical interventions. However, our understanding is remaining limited in how people practice social distancing. In this study, we construct a Social Distancing Index (SDI) to evaluate people's mobility pattern changes along with the spread of COVID-19. We utilize an integrated dataset of mobile device location data for the contiguous United States plus Alaska and Hawaii over a 100-day period from January 1, 2020 to April 9, 2020. The major findings are: 1) the declaration of the national emergency concerning the COVID-19 outbreak greatly encouraged social distancing and the mandatory stay-at-home orders in most states further strengthened the practice; 2) the states with more confirmed cases have taken more active and timely responses in practicing social distancing; 3) people in the states with fewer confirmed cases did not pay much attention to maintaining social distancing and some states, e.g., Wyoming, North Dakota, and Montana, already began to practice less social distancing despite the high increasing speed of confirmed cases; 4) some counties with the highest infection rates are not performing much social distancing, e.g., Randolph County and Dougherty County in Georgia, and some counties began to practice less social distancing right after the increasing speed of confirmed cases went down, e.g., in Blaine County, Idaho, which may be dangerous as well.

negative: Racial segregation, testing sites access, and COVID-19 incidence rate in Massachusetts, USA The U.S. has merely 4% of the world population but 25% of the world's COVID-19 cases. Massachusetts has been in the leading position of total cases since the outbreak in the U.S. Racial residential segregation is a fundamental cause of racial disparities in health. Moreover, disparities of access to health care have a large impact on COVID-19 cases. Thus, this study estimates racial segregation and disparities in testing sites access and employs economic, demographic, and transportation variables at the city/town level in Massachusetts. Spatial regression models are applied to evaluate the relationships between COVID-19 incidence rate and related variables. This is the first study to apply spatial analysis methods across neighborhoods in the U.S. to examine the COVID-19 incidence rate. The findings are: 1) residential segregations of Hispanic and Non-Hispanic Black/African Americans have a significantly positive association with COVID-19 incidence rate, indicating the higher susceptibility of COIVD-19 infections among minority; 2) The Black has the shortest drive time to testing sites, followed by Hispanic, Asian, and Whites. The drive time to testing sites is significantly negatively associated with the COVID-19 incidence rate, implying the importance of testing location being accessed by all populations; 3) Poverty rate and road density are significant explanatory variables. Importantly, overcrowding represented by more than one person per room is a significant variable found to be positively associated with COVID-19 incidence rate, suggesting the effectiveness of social distancing for reducing infection; 4) Different from previous studies, elderly population rate is not statistically significant with incidence rate because the elderly population in Massachusetts is less distributed in the hot spot regions of COVID-19 infections. The findings in this study provide useful insights for policymakers to propose new strategies to contain the COVID-19 transmissions in Massachusetts.

negative: Assessing the Impact of the COVID-19 Pandemic and Accompanying Mitigation Efforts on Older Adults

negative: Mental Wellbeing of Nursing Staff during the COVID-19 Outbreak: A Cultural Perspective

negative: Social distancing across vulnerability, race, politics, and employment: How different Americans changed behaviors before and after major COVID-19 policy announcements Background: As states reopen in May 2020, the United States is still trying to curb the spread of the COVID-19 pandemic. To appropriately design policies and anticipate behavioral change, it is important to understand how different Americans' social distancing behavior shifts in relation to policy announcements according to individual characteristics, and community vulnerability. Methods: This cross-sectional study used Unacast's social distancing data from February 24th - May 10th, 2020 to study how social distancing changed before and after: 1) The World Health Organization's declaration of a global pandemic, 2) White House announcement of "Opening Up America Again" (OUAA) guidelines, and 3) the week of April 27 when several states reopened. To measure intention to social distance, we assessed the difference between weekday and weekend behavior as more individuals have more control over weekend leisure time. To investigate social distancing's sensitivity to different population characteristics, we compared social distancing time-series data across county vulnerability as measured by the COVID-19 Community Vulnerability Index (CCVI) which defines vulnerability across socioeconomic, household composition, minority status, epidemiological, and healthcare-system related factors. We also compared social distancing across population groupings by race, 2016 presidential election voting choice, and employment sectors. Results: Movement reduced significantly throughout March reaching peak reduction on April 12th (-56.1%) prior the enactment of any reopening policies. Shifts in social distancing began after major announcements but prior to specific applied policies: Following the WHO declaration, national social distancing significantly increased on weekdays and weekends (-18.6% and -41.3% decline in mobility, respectively). Social distancing significantly declined on weekdays and weekends after OUAA guidelines (i.e. before state reopening) (+1.1% and +5.3% increase in mobility, respectively) with additional significant decline after state reopening (+10.0% and +20.9% increase in mobility, respectively). Social distancing was significantly greater on weekends than weekdays throughout March, however, the trend reversed by early May with significantly less social distancing on weekends, suggesting a shift in intent to social distance during leisure time. In general, vulnerable counties social distanced less than non-vulnerable counties, and had a greater difference between weekday and weekend behavior until state reopening. This may be driven by structural barriers that vulnerable communities face, such as higher rates of employment in particular sectors. At all time periods studied, the average black individual in the US social distanced significantly more than the average white individual, and the average 2016 Clinton voter social distanced significantly more than the average 2016 Trump voter. Social distancing behavior differed across industries with three clusters of employment sectors. Conclusion: Both signaling of a policy change and implementation of a policy are important factors that seem to influence social distancing. Behaviors shifted with national announcements prior to mandates, though social distancing further declined nationwide as the first states reopened. The variation in behavioral drivers including vulnerability, race, political affiliation, and employment industry demonstrates the need for targeted policy messaging and interventions tailored to address specific barriers for improved social distancing and mitigation.

negative: Spring in London with Covid-19: a personal view. This is a personal view from London as the Covid-19 pandemic continues to spread here and the situation changes from day to day. As such it can only be a snapshot caught in time; it is not a diary of events. The Coronavirus Act 2020 gives Government enormous powers and was passed by Parliament in one day of debate immediately before it closed early for the Easter break. In March, the government imposed a "lockdown: the closure of all" but "essential" businesses and people other than essential workers must work from home but are allowed out for exercise and food shopping but must maintain 2 m apart, the "social distancing rule". The aim is to suppress the spread of the virus, reduce the death toll and "protect the National Health Service (NHS)" which needed time to empty wards and expand its intensive care unit (ICU) capability to deal with an expected influx of thousands of very sick patients. I discuss whether this strategy is working, how and why it has rapidly been altered to respond to criticism. Why was the Government so slow to seek the help of private laboratories to assist with testing? Why was the personal protective equipment (PPE) guidance altered only after criticism? I look at the impact of the lockdown on the UK economy, the changes to practice of medicine and speeding of scientific research. Cooperating with the lockdown has its price; is it harming the health and mental health of children, people living in households with potentially abusive partners or parents and those who are disabled or financially desperate? Is the cure worse than the disease? The Economy is being devastated by the lockdown and each day of lockdown it is worse. Is litigation being seeded even now by the pandemic? Notwithstanding unprecedented Government financial help many businesses are on the edge of collapse, people will lose their jobs and pensioners income. The winners include pharmacies, supermarkets, online food retailers, Amazon, online apps, providers of video games, services, streaming and scientific research laboratories, manufacturers of testing kits, ventilators, hand sanitisers, coffins, undertakers, etc. The British public is cooperating with lockdown but are we less productive at home? Parents with babies and children often child minders, school, grandparents or paid help which is not now available. Will current reliance on video-conferencing and video calls permanently change the way we work and will we need smaller city offices? Will we travel less? Will medical and legal practice and civil and criminal trials be generally carried out remotely? Will social distancing with self-isolation and job losses and business failures fuel depression? Is Covid-19 comparable to past epidemics like the Plague and Spanish flu?

negative: Physiology in Perspective: In a World of Social Distancing

negative: Adoption and impact of non-pharmaceutical interventions for COVID-19 Background: Several non-pharmaceutical interventions (NPIs) have been implemented across the world to control the coronavirus disease (COVID-19) pandemic. Social distancing (SD) interventions applied so far have included school closures, remote working and quarantine. These measures have been shown to have large impacts on pandemic influenza transmission. However, there has been comparatively little examination of such measures for COVID-19. Methods: We examined the existing literature, and collated data, on implementation of NPIs to examine their effects on the COVID-19 pandemic so far. Data on NPIs were collected from official government websites as well as from media sources. Results: Measures such as travel restrictions have been implemented in multiple countries and appears to have slowed the geographic spread of COVID-19 and reduced initial case numbers. We find that, due to the relatively sparse information on the differences with and without interventions, it is difficult to quantitatively assess the efficacy of many interventions. Similarly, whilst the comparison to other pandemic diseases such as influenza can be helpful, there are key differences that could affect the efficacy of similar NPIs. Conclusions: The timely implementation of control measures is key to their success and must strike a balance between early enough application to reduce the peak of the epidemic and ensuring that they can be feasibly maintained for an appropriate duration. Such measures can have large societal impacts and they need to be appropriately justified to the population. As the pandemic of COVID-19 progresses, quantifying the impact of interventions will be a vital consideration for the appropriate use of mitigation strategies.

negative: Textile Masks and Surface Covers—A Spray Simulation Method and a “Universal Droplet Reduction Model” Against Respiratory Pandemics The main form of COVID-19 transmission is via “oral-respiratory droplet contamination” (droplet: very small drop of liquid) produced when individuals talk, sneeze, or cough. In hospitals, health-care workers wear facemasks as a minimum medical “droplet precaution” to protect themselves. Due to the shortage of masks during the pandemic, priority is given to hospitals for their distribution. As a result, the availability/use of medical masks is discouraged for the public. However, for asymptomatic individuals, not wearing masks in public could easily cause the spread of COVID-19. The prevention of “environmental droplet contamination” (EnvDC) from coughing/sneezing/speech is fundamental to reducing transmission. As an immediate solution to promote “public droplet safety,” we assessed household textiles to quantify their potential as effective environmental droplet barriers (EDBs). The synchronized implementation of a universal “community droplet reduction solution” is discussed as a model against COVID-19. Using a bacterial-suspension spray simulation model of droplet ejection (mimicking a sneeze), we quantified the extent by which widely available clothing fabrics reduce the dispersion of droplets onto surfaces within 1.8 m, the minimum distance recommended for COVID-19 “social distancing.” All textiles reduced the number of droplets reaching surfaces, restricting their dispersion to <30 cm, when used as single layers. When used as double-layers, textiles were as effective as medical mask/surgical-cloth materials, reducing droplet dispersion to <10 cm, and the area of circumferential contamination to ~0.3%. The synchronized implementation of EDBs as a “community droplet reduction solution” (i.e., face covers/scarfs/masks and surface covers) will reduce COVID-19 EnvDC and thus the risk of transmitting/acquiring COVID-19.

negative: Perceived vulnerability to COVID-19 infection from event attendance: Results from Louisiana, USA, two weeks preceding the national emergency declaration In response to the mounting threat of COVID-19, we added questions to an ongoing food preference study held at Louisiana State University from March 3-12 of 2020. We asked 356 participants: (1) In your opinion, how likely is it that the spread of COVID-19 (the coronavirus) will cause a public health crisis in the United States? (2) How concerned are you that you will contract COVID-19 by attending events on campus? Participants' estimates of an impending national health crisis increased significantly during the study's second week (March 9-12) while concern about personally contracting COVID-19 from attending campus events increased only marginally during the study's final days. We find those expressing a higher likelihood of an impending national crisis were more concerned about contracting COVID-19 by attending campus events, suggesting a possible transmission from perceptions of national-level events to perceived personal vulnerability via local exposure. However, about 30% of participants perceived that COVID-19 would likely cause a public health crisis yet did not express concern about contracting COVID-19 from event attendance. These participants were significantly more likely to be younger students who agreed to participate in response to recruitment using same-day flyer distribution. Women expressed a higher likelihood of an emerging national health crisis, although they were not more concerned than men that attending campus events would result in virus contraction. Other groups (e.g., white, students younger than 25, highest income group) displayed similar concern about a national-level crisis, yet were significantly less concerned about contracting COVID-19 from attending campus events than others. Also, participants randomly assigned to information emphasizing the national impacts of food waste expressed significantly greater concern of contracting COVID-19 by attending campus events. These results provide some initial insight about how people perceived national and personal risks in the early stages of the COVID-19 crisis in Louisiana.

negative: Inbred Strain Variant Database (ISVdb): A Repository for Probabilistically Informed Sequence Differences Among the Collaborative Cross Strains and Their Founders The Collaborative Cross (CC) is a panel of recently established multiparental recombinant inbred mouse strains. For the CC, as for any multiparental population (MPP), effective experimental design and analysis benefit from detailed knowledge of the genetic differences between strains. Such differences can be directly determined by sequencing, but until now whole-genome sequencing was not publicly available for individual CC strains. An alternative and complementary approach is to infer genetic differences by combining two pieces of information: probabilistic estimates of the CC haplotype mosaic from a custom genotyping array, and probabilistic variant calls from sequencing of the CC founders. The computation for this inference, especially when performed genome-wide, can be intricate and time-consuming, requiring the researcher to generate nontrivial and potentially error-prone scripts. To provide standardized, easy-to-access CC sequence information, we have developed the Inbred Strain Variant Database (ISVdb). The ISVdb provides, for all the exonic variants from the Sanger Institute mouse sequencing dataset, direct sequence information for CC founders and, critically, the imputed sequence information for CC strains. Notably, the ISVdb also: (1) provides predicted variant consequence metadata; (2) allows rapid simulation of F1 populations; and (3) preserves imputation uncertainty, which will allow imputed data to be refined in the future as additional sequencing and genotyping data are collected. The ISVdb information is housed in an SQL database and is easily accessible through a custom online interface (http://isvdb.unc.edu), reducing the analytic burden on any researcher using the CC.

negative: Mathematical Analysis of the Ross–Macdonald Model with Quarantine People infected with malaria may receive less mosquito bites when they are treated in well-equipped hospitals or follow doctors’ advice for reducing exposure to mosquitoes at home. This quarantine-like intervention measure is especially feasible in countries and areas approaching malaria elimination. Motivated by mathematical models with quarantine for directly transmitted diseases, we develop a mosquito-borne disease model where imperfect quarantine is considered to mitigate the disease transmission from infected humans to susceptible mosquitoes. The basic reproduction number [Formula: see text] is computed and the model equilibria and their stabilities are analyzed when the incidence rate is standard or bilinear. In particular, the model system may undergo a subcritical (backward) bifurcation at [Formula: see text] when standard incidence is adopted, whereas the disease-free equilibrium is globally asymptotically stable as [Formula: see text] and the unique endemic equilibrium is locally asymptotically stable as [Formula: see text] when the infection incidence is bilinear. Numerical simulations suggest that the quarantine strategy can play an important role in decreasing malaria transmission. The success of quarantine mainly relies on the reduction of bites on quarantined individuals.

negative: COVID-19: Facemask use prevalence in international airports in Asia, Europe and the Americas, March 2020

negative: Responding to global infectious disease outbreaks: Lessons from SARS on the role of risk perception, communication and management With increased globalisation comes the likelihood that infectious disease appearing in one country will spread rapidly to another, severe acute respiratory syndrome (SARS) being a recent example. However, although SARS infected some 10,000 individuals, killing around 1000, it did not lead to the devastating health impact that many feared, but a rather disproportionate economic impact. The disproportionate scale and nature of this impact has caused concern that outbreaks of more serious disease could cause catastrophic impacts on the global economy. Understanding factors that led to the impact of SARS might help to deal with the possible impact and management of such other infectious disease outbreaks. In this respect, the role of risk—its perception, communication and management—is critical. This paper looks at the role that risk, and especially the perception of risk, its communication and management, played in driving the economic impact of SARS. It considers the public and public health response to SARS, the role of the media and official organisations, and proposes policy and research priorities for establishing a system to better deal with the next global infectious disease outbreak. It is concluded that the potential for the rapid spread of infectious disease is not necessarily a greater threat than it has always been, but the effect that an outbreak can have on the economy is, which requires further research and policy development.

negative: Abstracts from the 11th International Congress of Behavioral Medicine

negative: Exit strategies: optimising feasible surveillance for detection, elimination and ongoing prevention of COVID-19 community transmission Background Following successful implementation of strong containment measures by the community, Australia is now close to the point of eliminating detectable community transmission of COVID-19. We aimed to develop an efficient, rapid and scalable surveillance strategy for detecting all remaining COVID-19 community transmission through exhaustive identification of every active transmission chain. We also identified measures to enable early detection and effective management of any reintroduction of transmission once containment measures are lifted to ensure strong containment measures do not need to be reinstated. Methods We compared efficiency and sensitivity to detect community transmission chains through testing of: hospital cases; primary care fever and cough patients; or asymptomatic community members, using surveillance evaluation methods and mathematical modelling, varying testing capacities and prevalence of COVID-19 and non-COVID-19 fever and cough, and the reproduction number. System requirements for increasing testing to allow exhaustive identification of all transmission chains, and then enable complete follow-up of all cases and contacts within each chain, were assessed per million population. Findings Assuming 20% of cases are asymptomatic and all symptomatic COVID-19 cases present to primary care, with high transmission (R=2.2) there are a median of 13 unrecognised community cases (5 infectious) when a transmission chain is identified through hospital surveillance versus 3 unrecognised cases (1 infectious) through primary care surveillance. 3 unrecognised community upstream community cases themselves are estimated to generate a further 22-33 contacts requiring follow-up. The unrecognised community cases rise to 5 if only 50% of symptomatic cases present to primary care. Screening for asymptomatic disease in the community cannot exhaustively identify all transmission under any of the scenarios assessed. The additional capacity required to screen all fever and cough primary care patients would be approximately 2,000 tests/million population per week using 1/16 pooling of samples. Interpretation Screening all syndromic fever and cough primary care presentations, in combination with exhaustive and meticulous case and contact identification and management, enables appropriate early detection and elimination of community transmission of COVID-19. If testing capacity is limited, interventions such as pooling allow increased case detection, even given reduced test sensitivity. Wider identification and testing of all upstream contacts, (i.e. potential sources of infection for identified cases, and their related transmission chains) is critical, and to be done exhaustively requires more resources than downstream contact tracing. The most important factor in determining the performance of such a surveillance system is community participation in screening and follow up, and as such, appropriate community engagement, messaging and support to encourage presentation and compliance is essential. We provide operational guidance on implementing such a system.

negative: Knowledge and Beliefs towards Universal Safety Precautions to flatten the curve during Novel Coronavirus Disease (nCOVID-19) Pandemic among general Public in India: Explorations from a National Perspective Background: The novel Coronavirus disease (COVID-19) is being considered as the most serious health threat that the world has never witnessed in the recent times and significantly affecting the daily routine of mankind by emerging as a global pandemic. Yet, as there is no treatment nor a vaccine that was approved so far, universal safety precautions (USPs) and mitigating strategies are the only way to deal with this emergency crisis. However, knowledge and beliefs towards USPs among the general public in countries such as India with a large population are lacking. Methods: A prospective, cross-sectional, web-based online survey was conducted among the general public in India during March 2020. A 20-items self-administered survey questionnaire was developed and randomly distributed among the public using google document forms through social media networks. Descriptive statistics were used in representing the study characteristics, and the Chi-square test was used in assessing the associations among the study variables with a p-value of < 0.05 was considered as statistically significant. Results: Of 1287 participants, 1117 have given their consent of willingness and completed the questionnaire with a response rate of 86.8%. The mean age of the study participants was 28.8 ± 10.9 years, where the majority of them belong to the age category <25 years, and sex was equally distributed. Based upon the socio-demographic information, the majority were post-graduates (32.9%), professional job holders (45%) and belonged to the upper-middle (40%) economic class. Overall, the knowledge and beliefs towards USPs and mitigating strategies among participants varied between moderate to high, with statistically significant associations with their socio-demographic characteristics. Conclusions: Although the knowledge and beliefs of the general public in India towards USPs are encouraging, there is a need for long-term educational interventions as the dynamics and severity of COVID-19 have been changing day-by-day rapidly. The findings of this study could guide the public health authorities in making and implementing decisions to combat this pandemic. Keywords: Coronavirus, COVID-19, outbreak, Pandemic, universal precautions, SARS-CoV-2.

negative: Agents infectieux émergents Résumé De nombreuses maladies infectieuses émergentes ou ré-émergentes sont survenues au cours des dernières décennies, certaines posant des problèmes de santé publique majeurs. SRAS, MERS-CoV, grippe aviaire hautement pathogène A(H5N1), MERS-CoV, maladie à virus Ebola ont été très préoccupants en raison de la virulence, de la mortalité, des modalités de transmission, de l’impact sur la transmission maternofœtale (Zika). La prise de conscience de ces émergences a conduit les autorités sanitaires à élaborer des plans et des recommandations, d’imaginer de nouvelles organisations des systèmes de soins de manière à identifier tout cas de maladie infectieuse émergente hautement transmissible virulente pour isolement immédiat et prise en charge adéquate. Abstract Emergence of many emerging or re-emerging infectious diseases have occurred over the past decade, some of which are major public threat. SARS, MERS-CoV, highly pathogenic avian influenza A(H5N1), Ebola virus disease have raised concerns because of their virulence, their mortality, and/or their modality of transmission, or their impact on maternofoetal transmission (Zika virus). The witness of these emergences have conducted health authorities to have policies and plans and to imagine new organizations for health systems in order to identify any case of highly communicable virulent disease for immediate isolation, and adequate management.

negative: Does COVID-19 Spread Through Droplets Alone?

negative: Epidemiological study of novel coronavirus (COVID-19) We report a statistical analysis of some highly infected countries by the novel coronavirus (COVID-19). The cumulative infected data were fitted with various growth models (e.g. Logistic equation, Weibull equation and Hill equation) and obtained the power index of top ten highly infected countries. The newly infected data were fitted with Gaussian distribution with the peak at ~40 days for the countries whose infection curves are seem to be saturated. The similarity in growth kinetics of infected people of different countries provides first-hand guidelines to take proper precautions to minimize human damage.

negative: CoronaVis: A Real-time COVID-19 Tweets Data Analyzer and Data Repository Due to the nature of the data and public interaction, twitter is becoming more and more useful to understand and model various events. The goal of CoronaVis is to use tweets as the information shared by the people to visualize topic modeling, study subjectivity, and to model the human emotions during the COVID-19 pandemic. The main objective is to explore the psychology and behavior of the societies at large which can assist in managing the economic and social crisis during the ongoing pandemic as well as the after-effects of it. The novel coronavirus (COVID-19) pandemic forced people to stay at home to reduce the spread of the virus by maintaining social distancing. However, social media is keeping people connected both locally and globally. People are sharing information (e.g. personal opinions, some facts, news, status, etc.) on social media platforms which can be helpful to understand the various public behavior such as emotions, sentiments, and mobility during the ongoing pandemic. In this work, we develop a live application to observe the tweets on COVID-19 generated from the USA. In this paper, we have generated various data analytics over a period of time to study the changes in topics, subjectivity, and human emotions. We also share a cleaned and processed dataset named CoronaVis Twitter dataset (focused on the United States) available to the research community at https://github.com/mykabir/COVID19. This will enable the community to find more useful insights and create different applications and models to fight with COVID-19 pandemic and future pandemics as well.

negative: Effectiveness and Compliance to Social Distancing During COVID-19 In the absence of pharmaceutical interventions to curb the spread of COVID-19, countries relied on a number of nonpharmaceutical interventions to fight the first wave of the pandemic. The most prevalent one has been stay-at-home orders, whose the goal is to limit the physical contact between people, which consequently will reduce the number of secondary infections generated. In this work, we use a detailed set of mobility data to evaluate the impact that these interventions had on alleviating the spread of the virus in the US as measured through the COVID-19-related deaths. To establish this impact, we use the notion of Granger causality between two time-series. We show that there is a unidirectional Granger causality, from the median percentage of time spent daily at home to the daily number of COVID-19-related deaths with a lag of 2 weeks. We further analyze the mobility patterns at the census block level to identify which parts of the population might encounter difficulties in adhering and complying with social distancing measures. This information is important, since it can consequently drive interventions that aim at helping these parts of the population.

negative: Social Distancing against COVID-19: Implication for the Control of Influenza Social distancing has been adopted as one of basic protective measures against coronavirus disease 2019 (COVID-19). During 2019–2020 season, influenza epidemic period was exceptionally short and epidemic peak was low in comparison with previous seasons in Korea. Influenza epidemic pattern was bimodal in 2016–2017 and 2018–2019 seasons, however, influenza viruses have rarely been circulating in spring, 2020 in Korea. Although multiple factors could affect the size of influenza epidemic, extensive application of nonpharmaceutical interventions including mask wearing and social distancing in response to COVID-19 seems to be a major factor of reduced influenza epidemic. Social distancing measures with high feasibility and high acceptability should be implemented even if severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines are developed in the future. Establishment of guideline for workplace social distancing is needed and it would contribute to reduce disease burden of influenza, especially in vaccine mismatch year.

negative: Low serum 25-hydroxyvitamin D levels are associated with increased risk of viral coinfections in wheezing children

negative: Coronavirus: Hotspot on coronavirus disease 2019 in India The novel coronavirus disease (COVID-19) or also known as the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been recognized as the cause of respiratory infection in Wuhan, Hubei Province, China, in late December 2019. As of April 5, 2020, this epidemic had spread to worldwide with 12,03,485 confirmed cases, including 62,000 deaths. The World Health Organization has declared it a Global Public Health Crisis. Coronavirus causes respiratory illness coughing, sneezing, breathlessness, and fever including pneumonia. The disease is transmitted person to person through infected droplets. At present, the research on novel coronavirus is still in the primary stage. Based on the published study, we thoroughly summarize the history and origin, microbiology and taxonomy, mode of transmissions, target receptor, clinical features, diagnosis, prevention, and treatment about COVID-19. This short report writes in hope for providing platform to community and researcher dealings against with the novel coronavirus and providing a reference for further studies.

negative: COVID-19, City Lockdown, and Air Pollution: Evidence from China The rapid spread of COVID-19 is a global public health challenge. To prevent the escalation of its transmission, China locked down one-third of its cities and strictly restricted human mobility and economic activities. Using timely and comprehensive air quality data in China, we show that these counter-COVID-19 measures led to remarkable improvement in air quality. Within weeks, the Air Quality Index and PM2.5 concentrations were brought down by 25%. The effects are larger in colder, richer, and more industrialized cities. We estimate that such improvement would avert 24,000 to 36,000 premature deaths from air pollution on a monthly basis.

negative: On the evolutionary epidemiology of SARS-CoV-2 There is no doubt that the novel coronavirus SARS-CoV-2 that causes COVID-19 is mutating and thus has the potential to adapt during the current pandemic. Whether this evolution will lead to changes in the transmission, the duration, or the severity of the disease is not clear. This has led to considerable scientific and media debate, from raising alarms about evolutionary change to dismissing it. Here we review what little is currently known about the evolution of SARS-CoV-2 and extend existing evolutionary theory to consider how selection might be acting upon the virus during the COVID-19 pandemic. While there is currently no definitive evidence that SARS-CoV-2 is undergoing further adaptation, continued, evidence-based, analysis of evolutionary change is important so that public health measures can be adjusted in response to substantive changes in the infectivity or severity of COVID-19.

negative: Trading Privacy for the Greater Social Good: How Did America React During COVID-19? Digital contact tracing and analysis of social distancing from smartphone location data are two prime examples of non-therapeutic interventions used in many countries to mitigate the impact of the COVID-19 pandemic. While many understand the importance of trading personal privacy for the public good, others have been alarmed at the potential for surveillance via measures enabled through location tracking on smartphones. In our research, we analyzed massive yet atomic individual-level location data containing over 22 billion records from ten Blue (Democratic) and ten Red (Republican) cities in the U.S., based on which we present, herein, some of the first evidence of how Americans responded to the increasing concerns that government authorities, the private sector, and public health experts might use individual-level location data to track the COVID-19 spread. First, we found a significant decreasing trend of mobile-app location-sharing opt-out. Whereas areas with more Democrats were more privacy-concerned than areas with more Republicans before the advent of the COVID-19 pandemic, there was a significant decrease in the overall opt-out rates after COVID-19, and this effect was more salient among Democratic than Republican cities. Second, people who practiced social distancing (i.e., those who traveled less and interacted with fewer close contacts during the pandemic) were also less likely to opt-out, whereas the converse was true for people who practiced less social-distancing. This relationship also was more salient among Democratic than Republican cities. Third, high-income populations and males, compared with low-income populations and females, were more privacy-conscientious and more likely to opt-out of location tracking.

negative: The geographic spread of COVID-19 correlates with structure of social networks as measured by Facebook We use anonymized and aggregated data from Facebook to show that areas with stronger social ties to two early COVID-19"hotspots"(Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March 30, 2020. These relationships hold after controlling for geographic distance to the hotspots as well as for the income and population density of the regions. These results suggest that data from online social networks may prove useful to epidemiologists and others hoping to forecast the spread of communicable diseases such as COVID-19.

negative: A case report of neonatal COVID-19 infection in China ;Clinical Infectious Diseases ;Oxford Academic Abstract In December 2019, the 2019 novel coronavirus disease (COVID-19) caused by SARS-CoV-2 emerged in China and now has spread in many countries Pregnant women are susceptible population of COVID-19 which are more likely to have complications and even progresse to severe illness We report a case of neonatal COVID-19 infection in China with pharyngeal swabs tested positive by rRT-PCR assay 36 hours after birth However, whether the case is a vertical transmission from mother to child remains to be confirmed

negative: SOCRATES: an online tool leveraging a social contact data sharing initiative to assess mitigation strategies for COVID-19 OBJECTIVE: Establishing a social contact data sharing initiative and an interactive tool to assess mitigation strategies for COVID-19. RESULTS: We organized data sharing of published social contact surveys via online repositories and formatting guidelines. We analyzed this social contact data in terms of weighted social contact matrices, next generation matrices, relative incidence and R[Formula: see text] . We incorporated location-specific physical distancing measures (e.g. school closure or at work) and capture their effect on transmission dynamics. All methods have been implemented in an online application based on R Shiny and applied to COVID-19 with age-specific susceptibility and infectiousness. Using our online tool with the available social contact data, we illustrate that physical distancing could have a considerable impact on reducing transmission for COVID-19. The effect itself depends on assumptions made about disease-specific characteristics and the choice of intervention(s).

negative: Cognitive biases operating behind the rejection of government safety advisories during COVID19 Pandemic

negative: Defining high-value information for COVID-19 decision-making Initial projections from the first generation of COVID-19 models focused public attention on worst-case scenarios in the absence of decisive policy action. These underscored the imperative for strong and immediate measures to slow the spread of infection. In the coming weeks, however, as policymakers continue enlisting models to inform decisions on COVID-19, answers to the most difficult and pressing policy questions will be much more sensitive to underlying uncertainties. In this study, we demonstrate a model-based approach to assessing the potential value of reducing critical uncertainties most salient to COVID-19 decision-making and discuss priorities for acquiring new data to reduce these uncertainties. We demonstrate how information about the impact of non-pharmaceutical interventions could narrow prediction intervals around hospitalizations over the next few weeks, while information about the prevalence of undetected cases could narrow prediction intervals around the timing and height of the peak of the epidemic.

negative: A pandemic of Body, Mind, and Spirit: The Burden of “Social Distancing” in Rural Communities During an Era of Heightened Suicide Risk

negative: Battle against novel coronavirus 2019-nCoV: International commitment to develop worldwide informing campaigns

negative: Data-driven modeling reveals a universal dynamic underlying the COVID-19 pandemic under social distancing. We show that the COVID-19 pandemic under social distancing exhibits universal dynamics. The cumulative numbers of both infections and deaths quickly cross over from exponential growth at early times to a longer period of power law growth, before eventually slowing. In agreement with a recent statistical forecasting model by the IHME, we show that this dynamics is well described by the erf function. Using this functional form, we perform a data collapse across countries and US states with very different population characteristics and social distancing policies, confirming the universal behavior of the COVID-19 outbreak. We show that the predictive power of statistical models is limited until a few days before curves flatten, forecast deaths and infections assuming current policies continue and compare our predictions to the IHME models. We present simulations showing this universal dynamics is consistent with disease transmission on scale-free networks and random networks with non-Markovian transmission dynamics.

negative: Environmental perspective of COVID-19 Abstract The outbreak of COVID-19 has caused concerns globally. On 30 January WHO has declared it as a global health emergency. The easy spread of this virus made people to wear a mask as precautionary route, use gloves and hand sanitizer on a daily basis that resulted in generation of a massive amount of medical wastes in the environment. Millions of people have been put on lockdown in order to reduce the transmission of the virus. This epidemic has also changed the people's life style; caused extensive job losses and threatened the sustenance of millions of people, as businesses have shut down to control the spread of virus. All over the world, flights have been canceled and transport systems have been closed. Overall, the economic activities have been stopped and stock markets dropped along with the falling carbon emission. However, the lock down of the COVID-19 pandemic caused the air quality in many cities across the globe to improve and drop in water pollutions in some parts of the world.

negative: Public Opinion Polarization by Individual Revenue from the Social Preference Theory Social conflicts occur frequently during the social transition period and the polarization of public opinion happens occasionally. By introducing the social preference theory, the target of this paper is to reveal the micro-interaction mechanism of public opinion polarization. Firstly, we divide the social preferences of Internet users (network nodes) into three categories: egoistic, altruistic, and fair preferences, and adopt the revenue function to define the benefits obtained by individuals with different preferences among their interaction process so as to analyze their decision-making behaviors driven by the revenue. Secondly, the revenue function is used to judge the exit rules of nodes in a network, and then a dynamic network of spreading public opinion with the node (individual) exit mechanism is built based on a BA scale-free network. Subsequently, the influences of different social preferences, as well as individual revenue on the effect of public opinion polarization, are analyzed through simulation experiments. The simulation results show that (1) Different social preferences demonstrate different influences on the evolution of public opinions, (2) Individuals tend to interact with ones with different preferences, (3) The network with a single preference or a high aggregation is more likely to form public opinion polarization. Finally, the practicability and effectiveness of the proposed model are verified by a real case.

negative: Mapping county-level mobility pattern changes in the United States in response to COVID-19 To contain the Coronavirus disease (COVID-19) pandemic, one of the non-pharmacological epidemic control measures in response to the COVID-19 outbreak is reducing the transmission rate of SARS-COV-2 in the population through (physical) social distancing. An interactive web-based mapping platform that provides timely quantitative information on how people in different counties and states reacted to the social distancing guidelines was developed with the support of the National Science Foundation (NSF). It integrates geographic information systems (GIS) and daily updated human mobility statistical patterns derived from large-scale anonymized and aggregated smartphone location big data at the county-level in the United States, and aims to increase risk awareness of the public, support governmental decision-making, and help enhance community responses to the COVID-19 outbreak.

negative: Perceptions and behavioural responses of the general public during the COVID-19 pandemic: A cross-sectional survey of UK Adults Objective: To examine risk perceptions and behavioural responses of the UK adult population during the early phase of the COVID-19 epidemic in the UK. Design: A cross-sectional survey Setting: Conducted with a nationally representative sample of UK adults within 48 hours of the UK Government advising the public to stop non-essential contact with others and all unnecessary travel. Participants: 2,108 adults living in the UK aged 18 years and over. Data were collected between March 17 and 18 2020. Main outcome measures: Descriptive statistics for all survey questions, including the number of respondents and the weighted percentages. Logistic regression was used to identify sociodemographic variation in: (1) adoption of social-distancing measures, (2) ability to work from home, and (3) willingness and (4) ability to self-isolate. Results Overall, 1,992 (94.2%) respondents reported taking at least one preventive measure: 85.8% washed their hands with soap more frequently; 56.5% avoided crowded areas and 54.5% avoided social events. Adoption of social-distancing measures was higher in those aged over 70 compared to younger adults aged 18 to 34 years (aOR:1.9; 95% CI:1.1 to 3.4). Those with the lowest household income were six times less likely to be able to work from home (aOR:0.16; 95% CI:0.09 to 0.26) and three times less likely to be able to self-isolate (aOR:0.31; 95% CI:0.16 to 0.58). Ability to self-isolate was also lower in black and minority ethnic groups (aOR:0.47; 95% CI:0.27 to 0.82). Willingness to self-isolate was high across all respondents. Conclusions The ability to adopt and comply with certain NPIs is lower in the most economically disadvantaged in society. Governments must implement appropriate social and economic policies to mitigate this. By incorporating these differences in NPIs among socio-economic subpopulations into mathematical models of COVID-19 transmission dynamics, our modelling of epidemic outcomes and response to COVID-19 can be improved.

negative: [An increased neutrophil/lymphocyte ratio is an early warning signal of severe COVID-19]. OBJECTIVE To identify the biomarkers as early warning signals for severe COVID-19. METHODS We retrospectively analyzed the clinical data of 63 patients with COVID- 19 from Hubei Provincial Hospital of Integrated Chinese and Western Medicine, including 32 moderate cases and 31 severe cases. The demographic data, underlying diseases, clinical manifestations and laboratory test results were compared between the two groups. Logistic regression analysis was performed to identify the factors that predicted the severity of COVID-19. The receiver- operating characteristic curve (ROC) of neutrophil/lymphocyte ratio (NLR) was calculated, and the area under the curve (AUC) was determined to estimate the optimal threshold of NLR for predicting severe cases of COVID-19. RESULTS The patients with moderate and server COVID-19 showed significant differences in the rate of diabetes, NLR, serum amyloid A (SSA), C-reactive protein (CRP) and serum albumin (ALB) levels (P < 0.05). The co- morbidity of diabetes, NLR, SSA and CRP were found to positively correlate and ALB to inversely correlate with the severity of COVID-19 (P < 0.05). Multivariate logistic regression analysis showed that NLR was an independent risk factor for severe COVID-19 (OR=1.264, 95% CI: 1.046-1.526, P=0.015) with an AUC of 0.831 (95% CI: 0.730-0.932), an optimal diagnostic threshold of 4.795, a sensitivity of 0.839, and a specificity of 0.750. CONCLUSIONS An increased NLR can serve as an early warning signal of severe COVID-19.

negative: Coronavirus disease 2019 (COVID-19): current status and future perspectives ABSTRACT Coronavirus disease 2019 (COVID-19) originated in the city of Wuhan, Hubei Province, Central China, and has spread quickly to 72 countries to date. COVID-19 is caused by a novel coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [previously provisionally known as 2019 novel coronavirus (2019-nCoV)]. At present, the newly identified SARS-CoV-2 has caused a large number of deaths with tens of thousands of confirmed cases worldwide, posing a serious threat to public health. However, there are no clinically approved vaccines or specific therapeutic drugs available for COVID-19. Intensive research on the newly emerged SARS-CoV-2 is urgently needed to elucidate the pathogenic mechanisms and epidemiological characteristics and to identify potential drug targets, which will contribute to the development of effective prevention and treatment strategies. Hence, this review will focus on recent progress regarding the structure of SARS-CoV-2 and the characteristics of COVID-19, such as the aetiology, pathogenesis and epidemiological characteristics.

negative: Suppression of innate antiviral response by severe acute respiratory syndrome coronavirus M protein is mediated through the first transmembrane domain Coronaviruses have developed various measures to evade innate immunity. We have previously shown that severe acute respiratory syndrome (SARS) coronavirus M protein suppresses type I interferon (IFN) production by impeding the formation of functional TRAF3-containing complex. In this study, we demonstrate that the IFN-antagonizing activity is specific to SARS coronavirus M protein and is mediated through its first transmembrane domain (TM1) located at the N terminus. M protein from human coronavirus HKU1 does not inhibit IFN production. Whereas N-linked glycosylation of SARS coronavirus M protein has no influence on IFN antagonism, TM1 is indispensable for the suppression of IFN production. TM1 targets SARS coronavirus M protein and heterologous proteins to the Golgi apparatus, yet Golgi localization is required but not sufficient for IFN antagonism. Mechanistically, TM1 is capable of binding with RIG-I, TRAF3, TBK1 and IKKε, and preventing the interaction of TRAF3 with its downstream effectors. Our work defines the molecular architecture of SARS coronavirus M protein required for suppression of innate antiviral response.

negative: Minimizing intra-hospital transmission of COVID-19: the role of social distancing

negative: Using Partial Differential Equation with Google Mobility Data to Model COVID-19 in Arizona The outbreak of COVID-19 disrupts the life of many people in the world. The state of Arizona in the U.S. emerges as one of the country's newest COVID-19 hot spots. Accurate forecasting for COVID-19 cases will help governments to implement necessary measures and convince more people to take personal precautions to combat the virus. It is difficult to accurately predict the COVID-19 cases due to many human factors involved. This paper aims to provide a forecasting model for COVID-19 cases with the help of human activity data from the Google Community Mobility Reports. To achieve this goal, a specific partial differential equation (PDE) is developed and validated with the COVID-19 data from the New York Times at the county level in the state of Arizona in the U.S. The proposed model describes the combined effects of transboundary spread among county clusters in Arizona and human actives on the transmission of COVID-19. The results show that the prediction accuracy of this model is well acceptable (above 94\%). Furthermore, we study the effectiveness of human precautions such as wearing face masks and practicing social distancing on the decrease of COVID-19 cases at the local level. The localized analytical results can be used to help to slow down the spread of COVID-19 in Arizona. To the best of our knowledge, this work is the first attempt to apply PDE models on COVID-19 prediction with the Google Community Mobility Reports.

negative: Inferring Infection Patterns Based on a Connectivity Map of Host Transcriptional Responses Host responses to infections represent an important pathogenicity determiner, and delineation of host responses can elucidate pathogenesis processes and inform the development of anti-infection therapies. Low cost, high throughput, easy quantitation, and rich descriptions have made gene expression profiling generated by DNA microarrays an optimal approach for describing host transcriptional responses (HTRs). However, efforts to characterize the landscape of HTRs to diverse pathogens are far from offering a comprehensive view. Here, we developed an HTR Connectivity Map based on systematic assessment of pairwise similarities of HTRs to 50 clinically important human pathogens using 1353 gene-expression profiles generated from >60 human cells/tissues. These 50 pathogens were further partitioned into eight robust “HTR communities” (i.e., groups with more consensus internal HTR similarities). These communities showed enrichment in specific infection attributes and differential gene expression patterns. Using query signatures of HTRs to external pathogens, we demonstrated four distinct modes of HTR associations among different pathogens types/class, and validated the reliability of the HTR community divisions for differentiating and categorizing pathogens from a host-oriented perspective. These findings provide a first-generation HTR Connectivity Map of 50 diverse pathogens, and demonstrate the potential for using annotated HTR community to detect functional associations among infectious pathogens.

negative: Using psychoneuroimmunity against COVID-19 Abstract The worldwide outbreak of coronavirus disease 2019 (COVID-19) raises concerns of widespread panic and anxiety in individuals subjected to the real or perceived threat of the virus. Compared to general populations, patients who are institutionalized in a closed unit are also very vulnerable to COVID-19 infection and complications. This crisis touched on difficult issues of not only psychiatric care and ethics, but also psychological impacts to psychiatric care givers. In this Viewpoint, we address both physical and biopsychosocial aspects of this infection, as well as the psychoneuroimmunity of preventive strategies of healthy lifestyle, regular exercise, balanced nutrition, quality sleep and a strong connection with people. Social distancing and wearing masks might help us from pathogen exposure, yet such these measures also prevent us from expressing compassion and friendliness. Therefore, all forms of psychological support should be routinely implemented not only to consider psychological resilience but also to enhance psychoneuroimmunity against COVID-19.

negative: Shaping Ethical Guidelines for an Influenza Pandemic This chapter describes the process of shaping ethical guidelines for an influenza pandemic by the North Carolina Institute of Medicine (NC IOM)/North Carolina Department of Public Health (NCDPH) Task Force. The author discusses the threat of a pandemic in the twenty-first century, comparing a potential pandemic with past flu pandemics as well as the Severe Acute Respiratory Syndrome (SARS) outbreak in Canada and parts of Asia. Also discussed are the ways in which influenza would spread, be treated, and hopefully contained. Addressed are the ways in which one becomes ethically prepared for an influenza pandemic, as well as the challenges to incorporating ethical guidelines in preparations. Tong also addresses the role of a duty/obligation/responsibility to work by health care personnel, the role of volunteers, and when health care personnel may refuse to treat someone. Also taken into consideration are such issues as the distribution of food and vaccines, quarantines, work stoppage, both physical and social infrastructure, the role of military and police forces, and the effect of a pandemic, isolation, and quarantine on various industries. Tong shows the complicated nature of working on a task force and the complexity of incorporating ethics into logistical planning.

negative: Coronavirus disease 2019 (COVID-19) pandemic: Review of guidelines for resuming non-urgent imaging and procedures in radiology during Phase II Since the spread of the coronavirus disease 2019 (COVID-19) was designated as a pandemic by the World Health Organization, health care systems have been forced to adapt rapidly to defer less urgent care during the crisis. The United States (U.S.) has adopted a four-phase approach to decreasing and then resuming non-essential work. Through strong restrictive measures, Phase I slowed the spread of disease, allowing states to safely diagnose, isolate, and treat patients with COVID-19. In support of social distancing measures, non-urgent studies were postponed, and this created a backlog. Now, as states transition to Phase II, restrictions on non-essential activities will ease, and radiology departments must re-establish care while continuing to mitigate the risk of COVID-19 transmission all while accommodating this backlog. In this article, we propose a roadmap that incorporates the current practice guidelines and subject matter consensus statements for the phased reopening of non-urgent and elective radiology services. This roadmap will focus on operationalizing these recommendations for patient care and workforce management. Tiered systems are proposed for the prioritization of elective procedures, with physician-to-physician communication encouraged. Infection control methods, provision of personal protective equipment (PPE), and physical distancing measures are highlighted. Finally, changes in hours of operation, hiring strategies, and remote reading services are discussed for their potential to ease the transition to normal operations.

negative: A model to forecast regional demand for COVID-19 related hospital beds COVID-19 threatens to overwhelm hospital facilities throughout the United States. We created an interactive, quantitative model that forecasts demand for COVID-19 related hospitalization based on county-level population characteristics, data from the literature on COVID-19, and data from online repositories. Using this information as well as user inputs, the model estimates a time series of demand for intensive care beds and acute care beds as well as the availability of those beds. The online model is designed to be intuitive and interactive so that local leaders with limited technical or epidemiological expertise may make decisions based on a variety of scenarios. This complements high-level models designed for public consumption and technically sophisticated models designed for use by epidemiologists. The model is actively being used by several academic medical centers and policy makers, and we believe that broader access will continue to aid community and hospital leaders in their response to COVID-19. Link to online model: https://surf.stanford.edu/covid-19-tools/covid-19/

negative: The psychological impact of COVID-19 pandemic on the general population of Saudi Arabia BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging infection causing a widely spread pandemic of Coronavirus disease 2019 (COVID-19). The current COVID-2019 pandemic is prompting fear of falling sick, dying, helplessness and stigma, urgent and timely understanding of mental health status is needed to help the community. Our investigation designed to survey the general population in Saudi Arabia to assess the degree of psychological impact during the pandemic. METHODS: During the early stage of the outbreak, we conducted an online-based survey using a snowballing sample technique. The surveys collected data about several aspects of participant sociodemographic, knowledge, concerns, psychological impact, and mental health status. We assessed the psychological impact and mental health status using the Impact of Event Scale-Revised (IES-R), and the Depression, Anxiety, and Stress Scale (DASS-21). RESULTS: Our survey recruited 1160 respondents of the general public of Saudi Arabia. Of them, 23.6% reported moderate or severe psychological impact of the outbreak, 28.3%,24%, and 22.3% reported moderate to severe depressive, anxiety, and stress symptoms, respectively. Females reported IES-R (B: 5.46, 95% CI: 3.61 to 7.31) and DASS subscales B coefficient ranged from 1.65 to 2.63, along with high-school students, working in the medical field, and poor self-reported health status was significantly associated with a high level of IES-R and DASS scales (p < .05). Experiencing breathing difficulty and dizziness showed a stronger association with higher IES-R and DASS subscales than other somatic symptoms (e.g., headache and fever);(p < .001). Respondents who practiced specific preventative measures (e.g., hand washing, social distancing) demonstrated a protective effect against stress, anxiety, and depression symptoms. Social distancing appeared to be protective on stress and anxiety subscales (B: -1.49, 95% CI: −2.79 to −0.19),(B: -1.53, 95% CI: −2.50 to −0.57),respectively; and hand hygiene on depression subscale (B: -2.43, 95% CI: −4.44 to −0.42). CONCLUSION: Throughout the early stage of the COVID-19 outbreak in Saudi Arabia, the results showed that nearly one-fourth of the sampled general population experienced moderate to severe psychological impact. Following specific precautionary measures appeared to have a protective effect on the individual's mental health. Our findings can be used to construct psychological interventions directed toward vulnerable populations and to implement public mental health strategies in the early stages of the outbreak.

negative: COVID-19—does social distancing include species distancing?

negative: Coronavirus disease 2019 (COVID-19) pandemic and pregnancy The current coronavirus disease 2019 (COVID-19) pneumonia pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading globally at an accelerated rate, with a basic reproduction number (R0) of 2–2.5, indicating that 2–3 persons will be infected from an index patient. A serious public health emergency, it is particularly deadly in vulnerable populations and communities in which healthcare providers are insufficiently prepared to manage the infection. As of March 16, 2020, there are more than 180,000 confirmed cases of COVID-19 worldwide, with more than 7000 related deaths. The SARS-CoV-2 virus has been isolated from asymptomatic individuals, and affected patients continue to be infectious 2 weeks after cessation of symptoms. The substantial morbidity and socioeconomic impact have necessitated drastic measures across all continents, including nationwide lockdowns and border closures. Pregnant women and their fetuses represent a high-risk population during infectious disease outbreaks. To date, the outcomes of 55 pregnant women infected with COVID-19 and 46 neonates have been reported in the literature, with no definite evidence of vertical transmission. Physiological and mechanical changes in pregnancy increase susceptibility to infections in general, particularly when the cardiorespiratory system is affected, and encourage rapid progression to respiratory failure in the gravida. Furthermore, the pregnancy bias toward T-helper 2 (Th2) system dominance, which protects the fetus, leaves the mother vulnerable to viral infections, which are more effectively contained by the Th1 system. These unique challenges mandate an integrated approach to pregnancies affected by SARS-CoV-2. Here we present a review of COVID-19 in pregnancy, bringing together the various factors integral to the understanding of pathophysiology and susceptibility, diagnostic challenges with real-time reverse transcription polymerase chain reaction (RT-PCR) assays, therapeutic controversies, intrauterine transmission, and maternal−fetal complications. We discuss the latest options in antiviral therapy and vaccine development, including the novel use of chloroquine in the management of COVID-19. Fetal surveillance, in view of the predisposition to growth restriction and special considerations during labor and delivery, is addressed. In addition, we focus on keeping frontline obstetric care providers safe while continuing to provide essential services. Our clinical service model is built around the principles of workplace segregation, responsible social distancing, containment of cross-infection to healthcare providers, judicious use of personal protective equipment, and telemedicine. Our aim is to share a framework that can be adopted by tertiary maternity units managing pregnant women in the flux of a pandemic while maintaining the safety of the patient and healthcare provider at its core.

negative: Defining Facets of Social Distancing during the COVID-19 Pandemic: Twitter Analysis Social distancing has been one of the primary mitigation strategies in the United States to control the spread of novel coronavirus disease (COVID-19) and can be viewed as a multi-faceted public health measure. Using Twitter data, we aim to (1) define and quantify the prevalence and evolution of facets of social distancing during the COVID-19 pandemic in the US in a spatiotemporal context and (2) examine the most amplified tweets among social distancing facets. We analyzed a total of 259,529 unique tweets containing "coronavirus" from 115,485 unique users between January 23, 2020 and March 24, 2020 that were identified by the Twitter API as English and U.S.-based. Tweets containing specified keywords (determined a priori) were grouped into six social distancing facets: implementation, purpose, social disruption, adaptation, positive emotions, and negative emotions. Tweets about social disruptiveness were most retweeted, and implementation tweets were most favorited. Social distancing tweets became overall more prevalent in the U.S. from late January to March but were not geographically uniform. In January and February, facets of social distancing appeared in Los Angeles, San Francisco, and Seattle, which were among the first cities impacted by the COVID-19 outbreak. Tweets related to the "implementation" and "negative emotions" facets of social distancing largely dominated in combination with topics of "social disruption" and "adaptation", albeit to a lesser degree. Social distancing can be defined in terms of facets that respond and represent certain moments and events in a pandemic, including travel restrictions and rising COVID-19 case counts. For example, in February, Miami, FL had a low volume of social distancing tweets but grew in March which corresponded with the rise of COVID-19 cases in the city. This suggests that overall volume of social distancing tweets can reflect the relative case count in respective locations.

negative: COVID-19, school closures, and child poverty: a social crisis in the making

negative: A data first approach to modelling Covid-19 The primary data for Covid-19 pandemic is in the form of time series for the number of confirmed, recovered and dead cases. This data is updated every day and is available for most countries from multiple sources. In this work we present a two step procedure for model fitting to Covid-19 data. In the first step, time dependent transmission coefficients are constructed directly from the data and, in the second step, measures of those (minimum, maximum, mean, median etc.,) are used to set priors for fitting models to data. We call this approach a "data driven approach" or "data first approach". This scheme is complementary to Bayesian approach and can be used with or without that for parameter estimation. We use the procedure to fit a set of SIR and SIRD models, with time dependent contact rate, to Covid-19 data for a set of 45 most affected countries. We find that SIR and SIRD models with constant transmission coefficients cannot fit Covid-19 data for most countries (mainly because social distancing, lockdown etc., make those time dependent). We find that any time dependent contact rate, which falls gradually with time, can help to fit SIR and SIRD models for most of the countries. We also present constraints on transmission coefficients and basic reproduction number R0~ as well as effective reproduction number R(t). The main contributions of our work are as follows. (1) presenting a two step procedure for model fitting to Covid-19 data (2) constraining transmission coefficients as well as R0~ and R(t), for a set of most affected countries and (3) releasing a python package PyCov19 that can used to fit a set of compartmental models with time varying coefficients to Covid-19 data.

negative: Mitigation Strategies for Pandemic Influenza A: Balancing Conflicting Policy Objectives Mitigation of a severe influenza pandemic can be achieved using a range of interventions to reduce transmission. Interventions can reduce the impact of an outbreak and buy time until vaccines are developed, but they may have high social and economic costs. The non-linear effect on the epidemic dynamics means that suitable strategies crucially depend on the precise aim of the intervention. National pandemic influenza plans rarely contain clear statements of policy objectives or prioritization of potentially conflicting aims, such as minimizing mortality (depending on the severity of a pandemic) or peak prevalence or limiting the socio-economic burden of contact-reducing interventions. We use epidemiological models of influenza A to investigate how contact-reducing interventions and availability of antiviral drugs or pre-pandemic vaccines contribute to achieving particular policy objectives. Our analyses show that the ideal strategy depends on the aim of an intervention and that the achievement of one policy objective may preclude success with others, e.g., constraining peak demand for public health resources may lengthen the duration of the epidemic and hence its economic and social impact. Constraining total case numbers can be achieved by a range of strategies, whereas strategies which additionally constrain peak demand for services require a more sophisticated intervention. If, for example, there are multiple objectives which must be achieved prior to the availability of a pandemic vaccine (i.e., a time-limited intervention), our analysis shows that interventions should be implemented several weeks into the epidemic, not at the very start. This observation is shown to be robust across a range of constraints and for uncertainty in estimates of both R(0) and the timing of vaccine availability. These analyses highlight the need for more precise statements of policy objectives and their assumed consequences when planning and implementing strategies to mitigate the impact of an influenza pandemic.

negative: 2264. The Burden of Respiratory Viral Illness in HIV-Infected Patients BACKGROUND: Among individuals living with human immunodeficiency virus (HIV), pulmonary complications are the most frequent cause of morbidity and mortality. Although bacterial and fungal pathogens are well-described etiologies of lung disease, the role of respiratory viruses remains poorly understood. We sought to describe the burden of respiratory viral illness in HIV-infected inpatients admitted to our tertiary care center. METHODS: All HIV-infected inpatients from August 2015 to March 2018 were approached if they presented with respiratory symptoms, defined as cough, dyspnea, sore throat, rhinorrhea, wheezing, or stridor. Eighty patients were enrolled. After obtaining informed consent, nasopharyngeal swabs and blood were collected. If the subject underwent bronchoscopy per the treating physician, excess bronchoalveolar lavage (BAL) sample was collected. Demographic and clinical data were recorded for each subject. Multiplex PCR testing of all respiratory samples was performed. RESULTS: Of the 70 HIV-infected patients that have undergone complete analysis, 23 (33%) tested positive for respiratory viruses. Of these, 11 (48%) were positive for rhinovirus, 3 were positive for influenza A (13%), 2 for parainfluenza 3 (9%), 2 for coronavirus (9%), and one each tested positive for adenovirus, parainfluenza 4, respiratory syncytial virus and influenza B. One patient had co-infection with rhinovirus and human metapneumovirus. Patients infected with a respiratory virus had severe illness as nearly half (10/23; 48%) required intensive care, 5 (22%) required mechanical ventilation, 4 (17%) were discharged to a higher level of care, and 3 (13%) died. CONCLUSION: The role of respiratory viruses on the lung health of HIV-infected patients is poorly defined. In this study, respiratory viruses were identified in over a third of HIV-infected inpatients, representing a substantial disease burden. Moreover, these patients demonstrated significant disease severity. Given these findings, there is a need for future studies of viral infections in HIV-infected individuals to elucidate mechanisms of susceptibility to reduce the burden of pulmonary morbidity in this vulnerable population. DISCLOSURES: All authors: No reported disclosures.

negative: New regulatory strategies to manage medicines shortages in Europe Abstract Medicine shortages have been spreading in European countries. In many cases, the unavailability of medicinal products has a substantial impact on the capability of National Healthcare Systems in ensuring the continuity of care. Shortages originate from multifactorial causes. In particular, they can be due to supply-related factors (e.g., manufacturing issues, regulatory issues, logistics, distribution) and demand-related ones (e.g., fluctuating drug demand, parallel market, tendering, price and reimbursement policies). However, some extraordinary geopolitical events (e.g., Brexit) may also affect medicines’ availability. The capability of European Regulatory Authorities and other stakeholders, which are involved in the pharmaceutical distribution chain and the healthcare assistance services, to define suitable problem-solving strategies has been limited for years by the fragmentation of the European regulatory framework, starting from the lack of a univocal definition of a medicine shortage. Only in 2019, the EMA and HMA joint task force released the first harmonized “shortage” definition in the European Economic Area (EEA) and guidance on public communication. This manuscript aims to review the current European regulatory framework on medicine shortages. To support the activities of regulators, manufacturers and other healthcare professionals, an algorithm was also proposed to be used as a harmonized procedure to determine the shortage/unavailability impact on public health and to rationalize the problem-solving strategies adopted in all different settings.

negative: Coronavirus Disease 2019 (COVID-19): we shall overcome

negative: Social Media and COVID-19: Can Social Distancing be Quantified without Measuring Human Movements? The COVID-19 outbreak has posed significant threats to international health and the economy. In the absence of treatment for this virus, public health officials asked the public to practice social distancing to reduce the number of physical contacts. However, quantifying social distancing is a challenging task and current methods are based on human movements. We propose a time and cost-effective approach to measure how people practice social distancing. This study proposes a new method based on utilizing the frequency of hashtags supporting and encouraging social distancing for measuring social distancing. We have identified 18 related hashtags and tracked their trends between Jan and May 2020. Our evaluation results show that there is a strong correlation (P<0.05) between our findings and the Google social distancing report.

negative: COVID-19: emergency medicine perspectives from Hong Kong

negative: Interaction rituals and ‘social distancing’: New haptic trajectories and touching from a distance in the time of COVID-19 Previous research in the social sciences has shown that haptic interaction rituals are critical for maintaining social relationships. However, during the coronavirus (COVID-19) pandemic, ‘social distancing’ was encouraged in order to avoid the spread of disease. Drawing on data from self-ethnography as well as publicly available resources, in this study we explore some new, locally negotiated haptic trajectories to accomplish interaction rituals in the time of coronavirus. First, we present self-ethnographic observations of distancing in face-to-face encounters from our everyday lives. Second, utilizing methods of microanalysis of naturally occurring interaction, we investigate video recordings of the embodied negotiation of space and touch among politicians. We analyze three different ways in which politicians negotiate transitional moves in this haptic ritual when one party initiates a handshake: repairing, declining and apologizing. Our analysis shows that politicians adapt their entire bodies in conjunction with talk, gestures and laughter not only to accomplish the greeting but also to remedy the potentially face-threatening situation of not getting the greeting right. This research has implications for better understanding the spontaneous ability of human beings to invent new ways of engaging with each other. Moreover, it adds to our knowledge of how the materiality of human bodies can impact forms of sociality.

negative: Fatalism in the context of COVID-19: Perceiving coronavirus as a death sentence predicts reluctance to perform recommended preventative behaviors() To manage the spread of coronavirus, health entities have urged the public to take preventative measures such as social distancing and handwashing. Yet, many appear reluctant to take these measures. Research is needed to understand factors underlying such reluctance, with the aim of developing targeted health interventions. We identify associating coronavirus with death as one such factor. 590 participants completed surveys in mid-March 2020, which included attitudes toward coronavirus, preventative behavioral intentions, and sociodemographic factors. Associating coronavirus with death negatively predicted intentions to perform preventative behaviors. Further, associating coronavirus with death was not evenly distributed throughout the sample and was related with a number of sociodemographic factors including age, race, and availability of sick leave. Following recommended preventative measures to slow the spread of coronavirus appears to relate to the degree to which people associate coronavirus with death. These findings can be used by public health researchers and practitioners to identify those for whom targeted health communication and interventions would be most beneficial, as well as to frame health messaging in ways that combat fatalism.

negative: Letter to the editor: Headline stress disorder caused by Netnews during the outbreak of COVID‐19

negative: Understanding Economic and Health Factors Impacting the Spread of COVID-19 Disease The rapid spread of the Coronavirus 2019 disease (COVID-19) had drastically impacted life all over the world. While some economies are actively recovering from this pestilence, others are experiencing fast and consistent disease spread, compelling governments to impose social distancing measures that have put a halt on routines, especially in densely-populated areas. Aiming at bringing more light on key economic and public health factors affecting the disease spread, this initial study utilizes a quantitative statistical analysis based on the most recent publicly-available COVID-19 datasets. The study had shown and explained multiple significant relationships between the COVID-19 data and other country-level statistics. We have also identified and statistically profiled four major country-level clusters with relation to different aspects of COVID-19 development and country-level economic and health indicators. Specifically, this study has identified potential COVID-19 under-reporting traits as well as various economic factors that impact COVID-19 Diagnosis, Reporting, and Treatment. Based on the country clusters, we have also described the four disease development scenarios, which are tightly knit to country-level economic and public health factors. Finally, we have highlighted the potential limitation of reporting and measuring COVID-19 and provided recommendations on further in-depth quantitative research.

negative: How many COVID-19 cases could have been prevented in the US if its interventions were as effective as those in China and South Korea? The COVID-19 pandemic has forced governments to take measures to contain the spread of the disease; however, the effects have varied significantly from one country to another contingent on governments' responses. Countries that have flattened their coronavirus curves prove that interventions can bring COVID-19 under control. These achievements hold lessons, such as the strict social distancing and coordinated efforts of all government levels in China and massive testing in South Korea, for other countries battling the coronavirus around the world. In this work, we attempt to estimate how many COVID-19 cases could have been prevented in the United States (US) when compared with the US's actual number of cases assuming that on a certain date, the US took China-like or South Korea-like interventions and that these interventions would have been as effective in the US as in China and South Korea. We found that if that date was at the early stage of the outbreak (March 10), more than 99% (1.15 million) fewer infected cases could be expected by the end of the epidemic. This number decreases to 66.03% and 73.06% fewer infected cases with the China-like scenario and the South Korea-like scenario, respectively, if actions were taken on April 1, highlighting the need to respond quickly and effectively to fight the virus. Furthermore, we found that although interventions in both China and South Korea allowed the COVID-19 outbreak to be managed, the epidemic could still oscillate without strict large-scale lockdown measures, as shown in South Korea. Our results demonstrate that early effective interventions can save considerably more people from infection and provide a worldwide alert regard the need for swift response.

negative: A Cross-Domain Approach to Analyzing the Short-Run Impact of COVID-19 on the U.S. Electricity Sector The novel coronavirus disease (COVID-19) has rapidly spread around the globe in 2020, with the U.S. becoming the epicenter of COVID-19 cases since late March. As the U.S. begins to gradually resume economic activity, it is imperative for policymakers and power system operators to take a scientific approach to understanding and predicting the impact on the electricity sector. Here, we release a first-of-its-kind cross-domain open-access data hub, integrating data from across all existing U.S. wholesale electricity markets with COVID-19 case, weather, cellular location, and satellite imaging data. Leveraging cross-domain insights from public health and mobility data, we uncover a significant reduction in electricity consumption across that is strongly correlated with the rise in the number of COVID-19 cases, degree of social distancing, and level of commercial activity.

negative: Rapid and accurate identification of COVID-19 infection through machine learning based on clinical available blood test results Since the sudden outbreak of coronavirus disease 2019 (COVID-19), it has rapidly evolved into a momentous global health concern. Due to the lack of constructive information on the pathogenesis of COVID-19 and specific treatment, it highlights the importance of early diagnosis and timely treatment. In this study, 11 key blood indices were extracted through random forest algorithm to build the final assistant discrimination tool from 49 clinical available blood test data which were derived by commercial blood test equipments. The method presented robust outcome to accurately identify COVID-19 from a variety of suspected patients with similar CT information or similar symptoms, with accuracy of 0.9795 and 0.9697 for the cross-validation set and test set, respectively. The tool also demonstrated its outstanding performance on an external validation set that was completely independent of the modeling process, with sensitivity, specificity, and overall accuracy of 0.9512, 0.9697, and 0.9595, respectively. Besides, 24 samples from overseas infected patients with COVID-19 were used to make an in-depth clinical assessment with accuracy of 0.9167. After multiple verification, the reliability and repeatability of the tool has been fully evaluated, and it has the potential to develop into an emerging technology to identify COVID-19 and lower the burden of global public health. The proposed tool is well-suited to carry out preliminary assessment of suspected patients and help them to get timely treatment and quarantine suggestion. The assistant tool is now available online at http://lishuyan.lzu.edu.cn/COVID2019_2/.

negative: Impact of social distancing during COVID-19 pandemic on crime in Los Angeles and Indianapolis Governments have implemented social distancing measures to address the ongoing COVID-19 pandemic. The measures include instructions that individuals maintain social distance when in public, school closures, limitations on gatherings and business operations, and instructions to remain at home. Social distancing may have an impact on the volume and distribution of crime. Crimes such as residential burglary may decrease as a byproduct of increased guardianship over personal space and property. Crimes such as domestic violence may increase because of extended periods of contact between potential offenders and victims. Understanding the impact of social distancing on crime is critical for ensuring the safety of police and government capacity to deal with the evolving crisis. Understanding how social distancing policies impact crime may also provide insights into whether people are complying with public health measures. Examination of the most recently available data from both Los Angeles, CA, and Indianapolis, IN, shows that social distancing has had a statistically significant impact on a few specific crime types. However, the overall effect is notably less than might be expected given the scale of the disruption to social and economic life.

negative: ACE2 receptor polymorphism: susceptibility to SARS-CoV-2, hypertension, multi-organ failure, and COVID-19 disease outcome Abstract The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has emerged in Chinese people in December 2019 and has currently spread worldwide causing the COVID-19 pandemic with more than 150,000 deaths. In order for a SARS-CoV like virus circulating in wild life for a very long time to infect the index case-patient, a number of conditions must be met, foremost among which is the encounter with humans and the presence in homo sapiens of a cellular receptor allowing the virus to bind. Recently it was shown that the SARS-CoV-2 spike protein, binds to the human angiotensin I converting enzyme 2 (ACE2). This molecule is a peptidase expressed at the surface of lung epithelial cells and other tissues, that regulates the renin-angiotensin-aldosterone system. Humans are not equal with respect to the expression levels of the cellular ACE2. Moreover, ACE2 polymorphisms were recently described in human populations. Here we review the most recent evidence that ACE2 expression and/or polymorphism could influence both the susceptibility of people to SARS-CoV-2 infection and the outcome of the COVID-19 disease. Further exploration of the relationship between the virus, the peptidase function of ACE2 and the levels of angiotensin II in SARS-CoV-2 infected patients should help to better understand the pathophysiology of the disease and the multi-organ failures observed in severe COVID-19 cases, particularly heart failure.

negative: The price of anarchy in mobility-driven contagion dynamics. Public policy and individual incentives determine the patterns of human mobility through transportation networks. In the event of a health emergency, the pursuit of maximum social or individual utility may lead to conflicting objectives in the routing strategies of network users. Individuals tend to avoid exposure so as to minimize the risk of contagion, whereas policymakers aim at coordinated behaviour that maximizes the social welfare. Here, we study agent-driven contagion dynamics through transportation networks, coupled to the adoption of either selfish- or policy-driven rerouting strategies. In analogy with the concept of price of anarchy in transportation networks subject to congestion, we show that maximizing individual utility leads to a loss of welfare for the social group, measured here by the total population infected after an epidemic outbreak.

negative: Perspectives on the death investigation during the COVID-19 pandemic Abstract The pandemic of COVID-19 caused by 2019-nCoV outbreaks in most of the countries, which has subsequently spread rapidly and become a pandemic worldwide. Due to the strong infectivity of COVID-19 and lack of experience of performing an autopsy to infectious disease-induced death, the pandemic created some challenges for forensic practitioners. In this article, we summarize the experience of how we handle the confirmed or suspected infectious cases, and give some perspectives for the future.

negative: iGPCR-Drug: A Web Server for Predicting Interaction between GPCRs and Drugs in Cellular Networking Involved in many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, G-protein-coupled receptors (GPCRs) are among the most frequent targets of therapeutic drugs. It is time-consuming and expensive to determine whether a drug and a GPCR are to interact with each other in a cellular network purely by means of experimental techniques. Although some computational methods were developed in this regard based on the knowledge of the 3D (dimensional) structure of protein, unfortunately their usage is quite limited because the 3D structures for most GPCRs are still unknown. To overcome the situation, a sequence-based classifier, called “iGPCR-drug”, was developed to predict the interactions between GPCRs and drugs in cellular networking. In the predictor, the drug compound is formulated by a 2D (dimensional) fingerprint via a 256D vector, GPCR by the PseAAC (pseudo amino acid composition) generated with the grey model theory, and the prediction engine is operated by the fuzzy K-nearest neighbour algorithm. Moreover, a user-friendly web-server for iGPCR-drug was established at http://www.jci-bioinfo.cn/iGPCR-Drug/. For the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated math equations presented in this paper just for its integrity. The overall success rate achieved by iGPCR-drug via the jackknife test was 85.5%, which is remarkably higher than the rate by the existing peer method developed in 2010 although no web server was ever established for it. It is anticipated that iGPCR-Drug may become a useful high throughput tool for both basic research and drug development, and that the approach presented here can also be extended to study other drug – target interaction networks.

negative: Coronavirus SARS‐CoV‐2: filtering fact from fiction in the infodemic: Q&A with virologist Professor Urs Greber As the severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) continues to spread across the world, and the associated lung disease COVID-19 remains difficult to treat, information from media and private communication flows at high speed, often through unfiltered channels. Much of this information is speculative, as it derives from preliminary and inconclusive studies, and creates confusion as well as anxiety. This phenomenon was recently labelled as "infodemic" by the World Health Organization.

negative: Fear can be more harmful than the severe acute respiratory syndrome coronavirus 2 in controlling the corona virus disease 2019 epidemic The current corona virus disease 2019 outbreak caused by severe acute respiratory syndrome coronavirus 2 started in Wuhan, China in December 2019 and has put the world on alert. To safeguard Chinese citizens and to strengthen global health security, China has made great efforts to control the epidemic. Many in the global community have joined China to limit the epidemic. However, discrimination and prejudice driven by fear or misinformation have been flowing globally, superseding evidence and jeopardizing the anti-severe acute respiratory syndrome coronavirus 2 efforts. We analyze this phenomenon and its underlying causes and suggest practical solutions.

negative: A Human-Pathogen SEIR-P Model for COVID-19 Outbreak under different intervention scenarios in Kenya This work describes the mathematical modelling and dynamics of a novel Coronavirus disease 2019 (COVID-19) in Kenya. The mathematical model assumes Human-Human infection as well as Human-Pathogen interaction. Using the SEIR (Susceptible-Exposed-Infected-Recovered) compartmental model with additional component of the pathogen,we simulated the dynamics of COVID-19 outbreak and impact of different control measures. The resulting system of ordinary differential equations (ODEs) are directly solved using a combination of fourth and fifth-order Runge-Kutta methods. Simulation results indicate that non-pharmaceutical measures such as school closure, social distancing and movement restriction emphatically flatten the epidemic peak curve hence leading to a smaller number of overall disease cases.

negative: Potential impact of Covid-19 response measures on invasive pneumococcal disease in England and Wales In January 2020, the United Kingdom (UK) removed one of the two infant doses of the 13-valent pneumococcal conjugate vaccine (PCV13), leaving a single priming dose at 3 months and a 12 month booster. We modelled the potential impact on invasive pneumococcal disease (IPD) of a drop in PCV13 coverage associated with the restrictions on non-essential health care visits introduced to combat COVID-19 in the UK on 23 March 2020. Using a previously published model of pneumococcal transmission in England and Wales we simulated the impact of reducing PCV13 coverage by 50% for 3 months from 23 March without subsequent catch-up vaccination. To implement social distancing, we reduced mixing between and within age-groups by either 10% or 50%. In a sensitivity analysis we explored the effect of complete cessation of PCV13 vaccination during the lockdown and of extending its duration to 6 months. Annual numbers of IPD cases predicted by the model under different vaccination and lockdown scenarios with uncertainty intervals (UI) generated from the minimum and maximum values of the model predictions using 500 parameter sets with values within a pre-specified range of the maximum likelihood set. The model predicted that any increase in IPD cases from a reduction in PCV13 coverage would be more than offset by a reduction in pneumococcal transmission due to social distancing, with a net reduction in cumulative IPD cases (UI -1,479, -1,061, all ages) over the next five years. Similar results were obtained in the sensitivity analysis, though with a greater reduction with a 6 month lockdown. COVID-19 social distancing measures are predicted to have had a profound effect on pneumococcal transmission resulting in a reduction in pneumococcal carriage prevalence and IPD incidence over the first two years after the lockdown. Carriage studies will be informative in confirming the predicted impact of the social distancing measures after they have been lifted.

negative: Protecting older adults during social distancing.

negative: A graph-based evidence synthesis approach to detecting outbreak clusters: An application to dog rabies Early assessment of infectious disease outbreaks is key to implementing timely and effective control measures. In particular, rapidly recognising whether infected individuals stem from a single outbreak sustained by local transmission, or from repeated introductions, is crucial to adopt effective interventions. In this study, we introduce a new framework for combining several data streams, e.g. temporal, spatial and genetic data, to identify clusters of related cases of an infectious disease. Our method explicitly accounts for underreporting, and allows incorporating preexisting information about the disease, such as its serial interval, spatial kernel, and mutation rate. We define, for each data stream, a graph connecting all cases, with edges weighted by the corresponding pairwise distance between cases. Each graph is then pruned by removing distances greater than a given cutoff, defined based on preexisting information on the disease and assumptions on the reporting rate. The pruned graphs corresponding to different data streams are then merged by intersection to combine all data types; connected components define clusters of cases related for all types of data. Estimates of the reproduction number (the average number of secondary cases infected by an infectious individual in a large population), and the rate of importation of the disease into the population, are also derived. We test our approach on simulated data and illustrate it using data on dog rabies in Central African Republic. We show that the outbreak clusters identified using our method are consistent with structures previously identified by more complex, computationally intensive approaches.

negative: Social Media Use During Social Distancing.

negative: Abstracts from the 36th Annual Meeting of the Society of General Internal Medicine

negative: What Is the Optimal Therapy for Patients with H5N1 Influenza? In a 2007 article in PLoS Medicine [10], Holger J. Schünemann and colleagues described a new process used by the World Health Organization for rapidly developing clinical management guidelines in emergency situations. These situations include outbreaks of emerging infectious diseases. The authors discussed how they developed such a “rapid advice” guideline for the pharmacological management of avian influenza A (H5N1) virus infection. The guideline recommends giving the antiviral drug oseltamivir at a dose of 75 mg twice daily for five days. In this Debate, Nicholas White argues that such dosing is inadequate, Robert Webster and Elena Govorkova say that combination antiviral therapy should be used, and Tim Uyeki reminds us that clinical care of patients with H5N1 entails much more than antiviral treatment. These issues may also apply to therapy of patients hospitalized with severe disease due to novel swine-origin influenza A (H1N1) virus infection.

negative: Coronavirus disease (COVID-19) – impact on vaccine preventable diseases

negative: Modeling COVID19 mortality in the US: Community context and mobility matter The United States has become an epicenter for the coronavirus disease 2019 (COVID-19) pandemic. However, communities have been unequally affected and evidence is growing that social determinants of health may be exacerbating the pandemic. Furthermore, the impact and timing of social distancing at the community level have yet to be fully explored. We investigated the relative associations between COVID-19 mortality and social distancing, sociodemographic makeup, economic vulnerabilities, and comorbidities in 24 counties surrounding 7 major metropolitan areas in the US using a flexible and robust time series modeling approach. We found that counties with poorer health and less wealth were associated with higher daily mortality rates compared to counties with fewer economic vulnerabilities and fewer pre-existing health conditions. Declines in mobility were associated with up to 15% lower mortality rates relative to pre-social distancing levels of mobility, but effects were lagged between 25-30 days. While we cannot estimate causal impact, this study provides insight into the association of social distancing on community mortality while accounting for key community factors. For full transparency and reproducibility, we provide all data and code used in this study.

negative: Testing Case Number of Coronavirus Disease 2019 in China with Newcomb-Benford Law The coronavirus disease 2019 bursted out about two months ago in Wuhan has caused the death of more than a thousand people. China is fighting hard against the epidemics with the helps from all over the world. On the other hand, there appear to be doubts on the reported case number. In this article, we propose a test of the reported case number of coronavirus disease 2019 in China with Newcomb-Benford law. We find a $p$-value of $92.8\%$ in favour that the cumulative case numbers abide by the Newcomb-Benford law. Even though the reported case number can be lower than the real number of affected people due to various reasons, this test does not seem to indicate the detection of frauds.

negative: News from the front: Excess mortality and life expectancy in two major epicentres of the COVID-19 pandemic in Italy Existing studies commonly rely on national official reports to estimate the impact of COVID-19 on population health and human life. However, relying on national reports is problematic because classification and estimation of COVID-19 mortality are not consistent across countries. Likewise, delay coronavirus test results and shortage of testing kits can result in undercounting of coronavirus deaths. To overcome these problems, this study exploits all cause daily death registrations data provide by the Italian Statistical Office (ISTAT) from 1st January to 4th April 2020. This allows us to: 1) calculate excess mortality in 2020 compared to the years 2015 to 2019; and 2) estimate life expectancy on a seasonal and annual basis. We focus our analysis on Bergamo and Brescia, the two hardest hit provinces in Lombardy, northern Italy. Given the clustering nature of the epidemic, focusing on the areas with high concentration of severe illness and deaths allows us to capture the true impact of COVID-19 on mortality and life expectancy, which are likely to be underestimated in the national level data. We find that on the period 1 Jan to 4 April 2020, seasonal life expectancy in Bergamo reduced by around 8.1 and 6.5 years compared to 2019 for men and women respectively (4.5 and 3.4 years in Brescia). The drop in period life expectancy for 2020 may total up to 3 years in the case of men and 2 years in the case of women. Such a sharp decrease in life expectancy has not been experienced in modern history since the Second World War. This study shows that, in the absence of public health interventions to reduce the spread of the virus, COVID-19 has set life expectancy in Bergamo and Brescia back to the Italian life expectancy of 15 years ago.

negative: Midwives in a pandemic: A call for solidarity and compassion

negative: 2019-novel coronavirus outbreak: A new challenge OBJECTIVES: Following the public health emergency declared by the World Health Organization and the recent outbreak by 2019-nCoV in China and through other 29 countries, we aimed to summarize the clinical aspects of novel beta-coronavirus infection and its possible clinical presentations together with suggested therapeutic algorithms for patients who may require antibiotic treatment. METHODS: We reviewed the currently available literature of microbiologically confirmed infections by 2019-ConV (or COVID-19) occurred at the time of writing (13 February 2020). A literature search was performed using the PubMed database and the Cochrane library. Search terms included "novel coronavirus" or "2019-nCoV" or “COVID-19”. RESULTS: Published cases occurred mostly in males (age ranged from 8 to 92). Cardiovascular, digestive and endocrine system diseases were commonly reported, except previous chronic pulmonary diseases (e.g., COPD, asthma, bronchiectasis) that were surprisingly underreported. Fever was presented in all the case series available, flanked by cough, dyspnea, myalgias and fatigue. Multiple bilateral lobular and subsegmental areas of consolidation or bilateral ground-glass opacities were the main reported radiological features of 2019-nCoV, at least in the early phases of disease. CONCLUSIONS: The new 2019-nCoV epidemics is mainly associated with respiratory disease and few extrapulmonary signs. However, there is a low rate of associated pre-existing respiratory comorbidities.

negative: The COVID-19 pandemic: implications for the cytology laboratory The coronavirus disease 2019 (COVID-19) is a pandemic caused by the SARS-CoV-2 virus. The infection has predominantly respiratory transmission and is transmitted through large droplets or aerosols, and less commonly by contact with infected surfaces or fomites. The alarming spread of the infection and the severe clinical disease that it may cause have led to the widespread institution of social distancing measures. Because of repeated exposure to potentially infectious patients and specimens, health care and laboratory personnel are particularly susceptible to contract COVID-19. This review paper provides an assessment of the current state of knowledge about the disease and its pathology, and the potential presence of the virus in cytology specimens. It also discusses the measures that cytology laboratories can take to function during the pandemic, and minimize the risk to their personnel, trainees, and pathologists. In addition, it explores potential means to continue to educate trainees during the COVID-19 pandemic.

negative: The Potential Role of Social Media Platforms in Community Awareness of Antibiotic Use in the Gulf Cooperation Council States: Luxury or Necessity? The increasing emergence and spread of antimicrobial resistance (AMR) is a serious public health issue. Increasing the awareness of the general public about appropriate antibiotic use is a key factor for combating this issue. Several public media campaigns worldwide have been launched; however, such campaigns can be costly and the outcomes are variable and difficult to assess. Social media platforms, including Twitter, Facebook, and YouTube, are now frequently utilized to address health-related issues. In many geographical locations, such as the countries of the Gulf Cooperation Council (GCC) States (Saudi Arabia, United Arab Emirates, Kuwait, Oman, Qatar, and Bahrain), these platforms are becoming increasingly popular. The socioeconomic status of the GCC states and their reliable communication and networking infrastructure has allowed the penetration and scalability of these platforms in the region. This might explain why the Saudi Ministry of Health is using social media platforms alongside various other media platforms in a large-scale public awareness campaign to educate at-risk communities about the recently emerged Middle East respiratory syndrome coronavirus (MERS-CoV). This paper discusses the potential for using social media tools as cost-efficient and mass education platforms to raise awareness of appropriate antibiotic use in the general public and in the medical communities of the Arabian Peninsula.

negative: Imaging of lung inflammation during severe influenza A: H1N1

negative: Universal Masking is Urgent in the COVID-19 Pandemic: SEIR and Agent Based Models, Empirical Validation, Policy Recommendations We present two models for the COVID-19 pandemic predicting the impact of universal face mask wearing upon the spread of the SARS-CoV-2 virus--one employing a stochastic dynamic network based compartmental SEIR (susceptible-exposed-infectious-recovered) approach, and the other employing individual ABM (agent-based modelling) Monte Carlo simulation--indicating (1) significant impact under (near) universal masking when at least 80% of a population is wearing masks, versus minimal impact when only 50% or less of the population is wearing masks, and (2) significant impact when universal masking is adopted early, by Day 50 of a regional outbreak, versus minimal impact when universal masking is adopted late. These effects hold even at the lower filtering rates of homemade masks. To validate these theoretical models, we compare their predictions against a new empirical data set we have collected that includes whether regions have universal masking cultures or policies, their daily case growth rates, and their percentage reduction from peak daily case growth rates. Results show a near perfect correlation between early universal masking and successful suppression of daily case growth rates and/or reduction from peak daily case growth rates, as predicted by our theoretical simulations. Our theoretical and empirical results argue for urgent implementation of universal masking. As governments plan how to exit societal lockdowns, it is emerging as a key NPI; a"mouth-and-nose lockdown"is far more sustainable than a"full body lockdown", on economic, social, and mental health axes. An interactive visualization of the ABM simulation is at http://dek.ai/masks4all. We recommend immediate mask wearing recommendations, official guidelines for correct use, and awareness campaigns to shift masking mindsets away from pure self-protection, towards aspirational goals of responsibly protecting one's community.

negative: Phase I study demonstrates safety and tolerability of radiofrequency ablation (RFA) of the anal mucosa. BACKGROUND Anal carcinoma is increasing in high-risk populations. Dysplasia is often distributed throughout the anal mucosa, and focal ablative techniques have high rates of recurrence. METHODS With the goal of eradicating dysplasia from the entire anal mucosa, we conducted a phase I dose-ranging study to determine the safety and tolerability of radiofrequency ablation (RFA). HIV-infected individuals with high-grade anal intraepithelial neoplasia underwent RFA of the anal mucosa. Patient-reported procedural and postprocedural symptoms were recorded, and mucosal healing was visually assessed. RESULTS Four groups of 3 subjects each were treated with incrementally increasing numbers of RF pulses (1-3) applied to a single area of anal mucosa. Two or three doses of 12 J/cm2 were found to have acceptable patient tolerance and healing of the mucosa within 4 weeks of ablation. Using these doses, 2 groups underwent ablation of 180° of contiguous mucosa. Subjects experienced a loss of 1 to 3 days of daily activities of living, 7 to 14 days of postprocedure symptoms, and mucosal healing within 4 weeks. One subject in the first treatment group had the procedure aborted due to severe procedural pain. CONCLUSIONS The study provides evidence of the safety and tolerability of anal RFA of 180° of contiguous mucosa in a single procedure and will allow future RFA efficacy studies in the treatment of anal dysplasia.

negative: COVID-19 randomised trial protocols: rapid publication without barriers

negative: Sepsis and septic shock: endothelial molecular pathogenesis associated with vascular microthrombotic disease In addition to protective “immune response”, sepsis is characterized by destructive “endothelial response” of the host, leading to endotheliopathy and its molecular dysfunction. Complement activation generates membrane attack complex (MAC). MAC causes channel formation to the cell membrane of pathogen, leading to death of microorganisms. In the host, MAC also may induce channel formation to innocent bystander endothelial cells (ECs) and ECs cannot be protected. This provokes endotheliopathy, which activates two independent molecular pathways: inflammatory and microthrombotic. Activated inflammatory pathway promotes the release of inflammatory cytokines and triggers inflammation. Activated microthrombotic pathway mediates platelet activation and exocytosis of unusually large von Willebrand factor multimers (ULVWF) from ECs and initiates microthrombogenesis. Excessively released ULVWF become anchored to ECs as long elongated strings and recruit activated platelets to assemble platelet-ULVWF complexes and form “microthrombi”. These microthrombi strings trigger disseminated intravascular microthrombosis (DIT), which is the underlying pathology of endotheliopathy-associated vascular microthrombotic disease (EA-VMTD). Sepsis-induced endotheliopathy promotes inflammation and DIT. Inflammation produces inflammatory response and DIT orchestrates consumptive thrombocytopenia, microangiopathic hemolytic anemia, and multiorgan dysfunction syndrome (MODS). Systemic inflammatory response syndrome (SIRS) is a combined phenotype of inflammation and endotheliopathy-associated (EA)-VMTD. Successful therapeutic design for sepsis can be achieved by counteracting the pathologic microthrombogenesis.

negative: Epidemiological impact of SARS-CoV-2 vaccination: mathematical modeling analyses Background: Several SARS-CoV-2 vaccine candidates are currently in the pipeline. This study aims to inform SARS-CoV-2 vaccine development, licensure, decision-making, and implementation by determining key preferred vaccine product characteristics and associated population-level impact. Methods: Vaccination impact was assessed at various efficacies using an age-structured mathematical model describing SARS-CoV-2 transmission and disease progression, with application for China. Results: A prophylactic vaccine with efficacy against acquisition (VEs) of ≥70% is needed to eliminate this infection. A vaccine with VEs <70% will still have a major impact, and may control the infection if it reduces infectiousness or infection duration among those vaccinated who acquire the infection, or alternatively if supplemented with a moderate social-distancing intervention (<20% reduction in contact rate), or complemented with herd immunity. Vaccination is cost-effective. For a vaccine with VEs of 50%, number of vaccinations needed to avert one infection is only 2.4, one severe disease case is 25.5, one critical disease case is 33.2, and one death is 65.1. Gains in effectiveness are achieved by initially prioritizing those ≥60 years. Probability of a major outbreak is virtually zero with a vaccine with VEs ≥70%, regardless of number of virus introductions. Yet, an increase in social contact rate among those vaccinated (behavior compensation) can undermine vaccine impact. Conclusions: Even a partially-efficacious vaccine can offer a fundamental solution to control SARS-CoV-2 infection and at high cost-effectiveness. In addition to the primary endpoint on infection acquisition, developers should assess natural history and disease progression outcomes and/or proxy biomarkers, since such secondary endpoints may prove critical in licensure, decision-making, and vaccine impact.

negative: COVID-19, Australia: Epidemiology Report 16 (Reporting week to 23:59 AEST 17 May 2020) Confirmed cases in Australia notified up to 17 May 2020: notifications = 7,075; deaths = 100. The incidence of new cases of COVID-19 has reduced dramatically since a peak in mid-March. Social distancing measures, public health action and the reduction in international travel have likely been effective in slowing the spread of the disease, in the Australian community. Testing rates over the past week have increased markedly, with a continued very low proportion of people testing positive. These low rates of detection are indicative of low levels of COVID-19 transmission. It is important that testing rates and community adherence to public health measures remain high to support the continued suppression of the virus, particularly in vulnerable high-risk groups and settings. New cases of COVID-19 are currently being reported by by only some jurisdictions, albeit at relatively low rates. Although case numbers are low, new cases tend to still be a mix of overseas-acquired and locally-acquired infections. Most locally-acquired cases can be linked back to a known case or cluster. Although the proportion of locally-acquired cases has increased, the overall rate of new cases, regardless of place of acquisition, continues to decrease. The crude case fatality rate in Australia remains low (1.4%), compared with the WHO reported global rate (6.9%). The low case fatality rate is likely reflective of high case detection and high quality of health care services in Australia. Deaths from COVID-19 in Australia have occurred predominantly among the elderly and those with comorbidities, with no deaths occurring in those under 40 years. The highest rate of COVID-19 continues to be among people aged 60-79 years. One third of all cases in this age group have been associated with several outbreaks linked to cruise ships. The lowest rate of disease is in young children, a pattern reflected in international reports. Internationally, while the number of new cases each day remains relatively stable at the global level, some areas such as Brazil and India are showing a dramatic rise in reported cases. Although some low-income countries have so far reported few cases, it is possible that this is due to limited diagnostic and public health capacity, and may not be reflective of true disease incidence.

negative: Unprecedented pandemic, unprecedented shift, and unprecedented opportunity The COVID‐19 pandemic is currently spreading across the world in an unprecedented way. “Social distancing” has become the latest buzzword in the headlines of media covering the COVID‐19 pandemic As a result, the widely implemented social distancing measures has generated one unprecedented shift that pushes various types of human social interactions from dominantly offline to dominantly online. This becomes a “new normal” in our daily life. For our research community of studying technology‐related behavior, the COVID‐19 pandemic provides an unprecedented opportunity to join the worldwide efforts to fight against the current pandemic and Human Behavior and Emerging Technologies calls for studies examining how humans behavior with emerging technologies in extreme events such as the COVID‐19 pandemic.

negative: The passage of time during the UK Covid-19 lockdown In March 2020, in response to the Covid-19 pandemic, the UK Government imposed social and physical distancing measures on the population. These lockdown measures caused significant changes to all aspects of daily life. The current study examined how the passage of time was distorted during the lockdown period. Using an online questionnaire, day and week passage of time judgments were collected. In addition, measures of affect, task load and satisfaction with current levels of social interaction were taken. The results show that over 80% of participants experienced distortion to the passage of time during lockdown in comparison with normal. The passage of time during the day was predicted by age, stress, task load and satisfaction with current levels of social interaction. A slowing of the passage of time was associated with increasing age, increasing stress, reduced task load and reduced satisfaction with current levels of social interaction. Only age and satisfaction with current levels of social interaction predicted passage of time across a week. Again, increasing age and reduced satisfaction with levels of social interaction were associated with a slowing of the passage of time. These findings demonstrate that significant changes to daily life have a significant impact on our experience of time, with younger, more socially satisfied people more likely to experience time as passing more quickly during the lockdown.

negative: The potential impact of COVID-19-related disruption on tuberculosis burden Before the COVID-19 pandemic, over 4000 people were dying from tuberculosis (TB) every day [1]. As with past emergencies [2], the impact of COVID-19 on TB outcomes is a serious cause for concern [3] but is currently unknown. Health systems overload, due to high numbers of COVID-19 cases, as well as interventions necessary to limit the transmission of SARS-CoV-2, could result in severe reductions in health service availability and access for the detection and treatment of TB cases [4]. However, physical distancing interventions could also limit Mycobacterium tuberculosis transmission outside of households, where most transmission occurs [5]. This has not been adequately explored in existing work [6–8], and it is currently unclear whether social distancing could compensate for disruptions in TB services, and what the impact of these combined COVID-19 disruption effects on TB burden is likely to be.

negative: Social Isolation as a Means of Reducing Dysfunctional Coronavirus Anxiety and Increasing Psychoneuroimmunity

negative: When Blackness Does Not Fade After a Pandemic: An Appeal to Acknowledge the Unequal Burden of Social Isolation Social distancing is one of the few tools that the everyman has to combat the Coronavirus disease. However, for those who are subject to racialized stereotypes about work productivity, educational ability, and other assumptions, the choice to socially distance can have many unintended consequences. This article is an appeal to our posterity, inviting a conversation about how we will remember the Coronavirus’ impact on our lives. Will we selectively provide compassion for the racial groups we perceive more favorable when this is over? Or will we play favorites when it is time to pick up the pieces? This article provides scenarios and commentary on how social distancing could affect Black American populations – regardless of income or socioeconomic status. It argues that history has not been kind to Black Americans who have bought into mass national causes, and that there is an opportunity here to act differently.

negative: Potential benefits and limitations of various strategies to mitigate the impact of an influenza pandemic Abstract The recent avian influenza outbreaks underscore the importance of improving our preparedness for an impending influenza pandemic. Various strategies, including pharmaceutical interventions (such as vaccines and antivirals) and nonpharmaceutical interventions (such as quarantine, isolation, and social distancing) may be implemented to mitigate the impact of a pandemic. It is necessary to understand the potential benefits and limitations of each strategy to determine the most appropriate strategies to be implemented. In this article, each strategy is reviewed to define its potential benefits and limitations during a pandemic. Vaccines are probably the most effective measure to reduce morbidity and mortality. However, vaccines are not likely to be available at an early stage of a pandemic. The supply of vaccines is most likely to be insufficient due to limited worldwide production capacity. Antivirals, particularly neuraminidase inhibitors, are expected to be effective against a pandemic influenza strain and are the only available pharmaceutical intervention until enough vaccines are produced. Shortage of supply and high cost is still a major limiting factor in amassing large stockpiles of neuraminidase inhibitors. The possible emergence of resistant strains should also be considered. Nonpharmaceutical interventions can be effective in preventing the spread of the virus under certain conditions. The effectiveness of nonpharmaceutical interventions depends on how influenza viruses are transmitted. There are still significant gaps in the scientific evidence of the way in which influenza viruses are transmitted. Further studies should be conducted to define the basic transmission patterns of influenza viruses.

negative: The Potential Impact of Interruptions to HIV Services: A Modelling Case Study for South Africa The numbers of deaths caused by HIV could increase substantially if the COVID-19 epidemic leads to interruptions in the availability of HIV services. We compare publicly available scenarios for COVID-19 mortality with predicted additional HIV-related mortality based on assumptions about possible interruptions in HIV programs. An interruption in the supply of ART for 40% of those on ART for 3 months could cause a number of deaths on the same order of magnitude as the number that are anticipated to be saved from COVID-19 through social distancing measures. In contrast, if the disruption can be managed such that the supply and usage of ART is maintained, the increase in AIDS deaths would be limited to 1% over five years, although this could still be accompanied by substantial increases in new HIV infections if there are reductions in VMMC, oral PrEP use, and condom availability.

negative: Usefulness of Hydrogel-Coated Coils in Embolization of Pulmonary Arteriovenous Malformations. PURPOSE To evaluate the usefulness of hydrogel-coated coils for preventing recanalization after coil embolization of pulmonary arteriovenous malformations (PAVMs). MATERIALS AND METHODS Thirty-seven consecutive patients with 57 untreated PAVMs underwent coil embolization with hydrogel-coated coils between January 2013 and Jun 2017. The mean age was 49 years (range 9-83 years), and there were seven male patients and 30 female patients. The median size of the feeding artery was 3.7 mm (range 1.5-6.1 mm), and the median size of the venous sac was 9.3 mm (range 2.6-36.6 mm). For all PAVM, embolization was attempted using 0.018-in. hydrogel-coated coils with or without other coils (0.0135-0.018-in. bare platinum coils and fibered platinum coils). Technical success rate, recanalization rate, and complications were evaluated. Technical success was defined as completion of embolization using hydrogel-coated coils. Recanalization was evaluated with time-resolved magnetic resonance angiography and/or pulmonary angiography. RESULTS In 56 of 57 PAVMs, embolization was successfully performed with hydrogel-coated coils. Therefore, the technical success rate was 98% (56/57). The number of PAVMs at risk was 56, 42, 18, and 12 at 0, 12, 24, and 36 months, respectively. There was no recanalization with a mean follow-up period of 19 months (range 2-47 months) in 56 PAVMs embolized with hydrogel-coated coils. There were no major complications. As a minor complication, local pain was observed in 8 of 43 sessions (19%) after embolization. CONCLUSIONS Hydrogel-coated coils may be useful for preventing recanalization after the embolization of PAVMs.

negative: A study of non-prescription usage of antibiotics in the upper respiratory tract infections in the urban population

negative: How Social Distancing Brought Us Closer as a BME Community

negative: Modeling COVID-19 and Its Impacts on U.S. Immigration and Customs Enforcement (ICE) Detention Facilities, 2020 U.S. Immigration and Customs Enforcement (ICE) facilities house thousands of undocumented immigrants in environments discordant with the public health recommendations to reduce the transmission of 2019 novel coronavirus (COVID-19). Using ICE detainee population data obtained from the ICE Enforcement and Removal Operations (ERO) website as of March 2, 2020, we implemented a simple stochastic susceptible-exposed-infected-recovered model to estimate the rate of COVID-19 transmission within 111 ICE detention facilities and then examined impacts on regional hospital intensive care unit (ICU) capacity. Models considered three scenarios of transmission (optimistic, moderate, pessimistic) over 30-, 60-, and 90-day time horizons across a range of facility sizes. We found that 72% of individuals are expected to be infected by day 90 under the optimistic scenario (R0 = 2.5), while nearly 100% of individuals are expected to be infected by day 90 under a more pessimistic (R0 = 7) scenario. Although asynchronous outbreaks are more likely, day 90 estimates provide an approximation of total positive cases after all ICE facility outbreaks. We determined that, in the most optimistic scenario, coronavirus outbreaks among a minimum of 65 ICE facilities (59%) would overwhelm ICU beds within a 10-mile radius and outbreaks among a minimum of 8 ICE facilities (7%) would overwhelm local ICU beds within a 50-mile radius over a 90-day period, provided every ICU bed was made available for sick detainees. As policymakers seek to rapidly implement interventions that ensure the continued availability of life-saving medical resources across the USA, they may be overlooking the pressing need to slow the spread of COVID-19 infection in ICE’s detention facilities. Preventing the rapid spread necessitates intervention measures such as granting ICE detainees widespread release from an unsafe environment by returning them to the community. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11524-020-00441-x) contains supplementary material, which is available to authorized users.

negative: Coronavirus disease 2019: The harms of exaggerated information and non‐evidence‐based measures The evolving coronavirus disease 2019 (COVID-19) epidemic1 is certainly cause for concern. Proper communication and optimal decision-making is an ongoing challenge, as data evolve. The challenge is compounded, however, by exaggerated information. This can lead to inappropriate actions. It is important to differentiate promptly the true epidemic from an epidemic of false claims and potentially harmful actions.

negative: Including the public in pandemic planning: a deliberative approach BACKGROUND: Against a background of pandemic threat posed by SARS and avian H5N1 influenza, this study used deliberative forums to elucidate informed community perspectives on aspects of pandemic planning. METHODS: Two deliberative forums were carried out with members of the South Australian community. The forums were supported by a qualitative study with adults and youths, systematic reviews of the literature and the involvement of an extended group of academic experts and policy makers. The forum discussions were recorded with simultaneous transcription and analysed thematically. RESULTS: Participants allocated scarce resources of antiviral drugs and pandemic vaccine based on a desire to preserve society function in a time of crisis. Participants were divided on the acceptability of social distancing and quarantine measures. However, should such measures be adopted, they thought that reasonable financial, household and psychological support was essential. In addition, provided such support was present, the participants, in general, were willing to impose strict sanctions on those who violated quarantine and social distancing measures. CONCLUSIONS: The recommendations from the forums suggest that the implementation of pandemic plans in a severe pandemic will be challenging, but not impossible. Implementation may be more successful if the public is engaged in pandemic planning before a pandemic, effective communication of key points is practiced before and during a pandemic and if judicious use is made of supportive measures to assist those in quarantine or affected by social isolation measures.

negative: Non-COVID-19 Deaths After Social Distancing in Norway Lay persons and policy makers have speculated on how the imposition of social distancing to reduce SARS CoV-2 (severe acute respiratory syndrome coronavirus 2) infection has affected non-COVID-19 (coronavirus disease of 2019) deaths. No rigorous estimation of the effect appears in the scholarly literature. We use time-series methods to compare non-COVID-19 deaths observed in Norway before and during the epidemic to those expected from non-COVID-19 deaths in Sweden as well as from the history of Norwegian mortality trends. We find that in the first 8 weeks after the divergence between Swedish and Norwegian policies (the only period for which dependable data can be had) approximately 650 fewer Norwegians died than expected.

negative: 2019 CIS Annual Meeting: Immune Deficiency & Dysregulation North American Conference

negative: Literature-related discovery: Potential treatments and preventatives for SARS Abstract Literature-related discovery (LRD) is the linking of two or more previously disjoint concepts in order to produce novel, interesting, plausible, and intelligible connections (i.e., potential discovery). LRD has been used to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications. Severe acute respiratory syndrome (SARS) was the first pandemic of the 21st century. SARS was eventually controlled through increased hygienic measures (e.g., face mask protection, frequent hand washing, living quarter disinfection), travel restrictions, and quarantine. According to recent reviews of SARS, none of the drugs that were used during the pandemic worked. For the present paper, SARS was selected as the first application of LRD to an infectious disease. The main goal of this research was to identify non-drug non-surgical treatments that would 1) prevent the occurrence, or 2) reduce the progression rate, or 3) stop/reverse the progression of SARS. The MeSH taxonomy of Medline was used to restrict potential discoveries to selected semantic classes, and to identify potential discoveries efficiently. To enhance the volume of potential discovery, databases were used in addition to Medline. These included the Science Citation Index (SCI) and, in contrast to previous work, a full text database. Because of the richness of the full text, ‘surgical’ queries were developed that targeted the exact types of potential discovery of interest while eliminating clutter more efficiently.

negative: The trajectory of loneliness in response to COVID-19 Social distancing and "stay-at-home" orders are essential to contain the coronavirus outbreak (COVID-19), but there is concern that these measures will increase feelings of loneliness, particularly in vulnerable groups. The present study examined change in loneliness in response to the social restriction measures taken to control the coronavirus spread. A nationwide sample of American adults (N = 1,545; 45% women; ages 18 to 98, M = 53.68, SD = 15.63) was assessed on three occasions: in late January/early February 2020 (before the outbreak), in late March (during the President's initial "15 Days to Slow the Spread" campaign), and in late April (during the "stay-at-home" policies of most states). Contrary to expectations, there were no significant mean-level changes in loneliness across the three assessments (d = .04, p > .05). In fact, respondents perceived increased support from others over the follow-up period (d = .19, p < .01). Older adults reported less loneliness overall compared to younger age groups but had an increase in loneliness during the acute phase of the outbreak (d = .14, p < .05). Their loneliness, however, leveled off after the issuance of stay-at-home orders. Individuals living alone and those with at least one chronic condition reported feeling lonelier at baseline but did not increase in loneliness during the implementation of social distancing measures. Despite some detrimental impact on vulnerable individuals, in the present sample, there was no large increase in loneliness but remarkable resilience in response to COVID-19. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

negative: Protease inhibitors broadly effective against feline, ferret and mink coronaviruses Abstract Ferret and mink coronaviruses typically cause catarrhal diarrhea in ferrets and minks, respectively. In recent years, however, systemic fatal coronavirus infection has emerged in ferrets, which resembles feline infectious peritonitis (FIP) in cats. FIP is a highly fatal systemic disease caused by a virulent feline coronavirus infection in cats. Despite the importance of coronavirus infections in these animals, there are no effective commercial vaccines or antiviral drugs available for these infections. We have previously reported the efficacy of a protease inhibitor in cats with FIP, demonstrating that a virally encoded 3C-like protease (3CLpro) is a valid target for antiviral drug development for coronavirus infections. In this study, we extended our previous work on coronavirus inhibitors and investigated the structure-activity relationships of a focused library of protease inhibitors for ferret and mink 3CLpro. Using the fluorescence resonance energy transfer assay, we identified potent inhibitors broadly effective against feline, ferret and mink coronavirus 3CLpro. Multiple amino acid sequence analysis and modelling of 3CLpro of ferret and mink coronaviruses were conducted to probe the structural basis for these findings. The results of this study provide support for further research to develop broad-spectrum antiviral agents for multiple coronavirus infections. To the best of our knowledge, this is the first report on small molecule inhibitors of ferret and mink coronaviruses.

negative: Evidence-Based Medicine in the Intensive Care Unit

negative: Using Google Trends to Examine the Spatio-Temporal Incidence and Behavioral Patterns of Dengue Disease: A Case Study in Metropolitan Manila, Philippines Dengue is a major public health concern and an economic burden in the Philippines. Despite the country’s improved dengue surveillance, it still suffers from various setbacks and needs to be complemented with alternative approaches. Previous studies have demonstrated the potential of Internet-based surveillance such as Google Dengue Trends (GDT) in supplementing current epidemiological methods for predicting future dengue outbreaks and patterns. With this, our study has two objectives: (1) assess the temporal relationship of weekly GDT and dengue incidence in Metropolitan Manila from 2009–2014; and (2) examine the health-seeking behavior based on dengue-related search queries of the population. The study collated the population statistics and reported dengue cases in Metropolitan Manila from respective government agencies to calculate the dengue incidence (DI) on a weekly basis for the entire region and annually per city. Data processing of GDT and dengue incidence was performed by conducting an ‘adjustment’ and scaling procedures, respectively, and further analyzed for correlation and cross-correlation analyses using Pearson’s correlation. The relative search volume of the term ‘dengue’ and top dengue-related search queries in Metropolitan Manila were obtained and organized from the Google Trends platform. Afterwards, a thematic analysis was employed, and word clouds were generated to examine the health behavior of the population. Results showed that weekly temporal GDT pattern are closely similar to the weekly DI pattern in Metropolitan Manila. Further analysis showed that GDT has a moderate and positive association with DI when adjusted or scaled, respectively. Cross-correlation analysis revealed a delayed effect where GDT leads DI by 1–2 weeks. Thematic analysis of dengue-related search queries indicated 5 categories namely; (a) dengue, (b) sign and symptoms of dengue, (c) treatment and prevention, (d) mosquito, and (e) other diseases. The majority of the search queries were classified in ‘signs and symptoms’ which indicate the health-seeking behavior of the population towards the disease. Therefore, GDT can be utilized to complement traditional disease surveillance methods combined with other factors that could potentially identify dengue hotspots and help in public health decisions.

negative: Serology characteristics of SARS-CoV-2 infection since the exposure and post symptoms onset Background Timely diagnosis of SARS-CoV-2 infection is the prerequisite for treatment and preventive quarantine. The serology characteristics and complement diagnosis value of antibody test to RNA test needs to be demonstrated. Method A patient cohort study was conducted at the first affiliated hospital of Zhejiang University, China. Serial sera of COVID-19 patients were collected and total antibody (Ab), IgM and IgG antibody against SARS-CoV-2 were detected. The antibody dynamics during the infection were described. Results The seroconversion rate for Ab, IgM and IgG in COVID-19 patients was 98.8% (79/80), 93.8% (75/80) and 93.8% (75/80), respectively. The first detectible serology marker is total antibody and followed by IgM and IgG, with a median seroconversion time of 15, 18 and 20 day post exposure (d.p.e) or 9, 10 and 12 days post onset, separately. The antibody levels increased rapidly since 6 d.p.o and accompanied with the decline of viral load. For patients in the early stage of illness (0-7d.p.o),Ab showed the highest sensitivity (64.1%) compared to the IgM and IgG (33.3% for both, p<0.001). The sensitivities of Ab, IgM and IgG detection increased to 100%, 96.7% and 93.3% two weeks later, respectively. Conclusions Typical acute antibody response is induced during the SARS-CoV-2 infection. The serology testing provides important complementation to RNA test for pathogenic specific diagnosis and helpful information to evaluate the adapted immunity status of patient. It should be strongly recommended to apply well-validated antibody tests in the clinical management and public health practice to improve the control of COVID-19 infection.

negative: Intrinsic growth rules of patients infected, dead and recovered with 2019 novel coronavirus in mainland China An outbreak of a novel coronavirus (SARS-CoV-2)-infected pneumonia (COVID-19) was first diagnosed in Wuhan, China, in December 2019 and then spread rapidly to other regions. We collected the time series data of the cumulative number of confirmed infected, dead, and cured cases from the health commissions in 31 provinces in mainland China. A descriptive model in a logistic form was formulated to infer the intrinsic epidemic rules of COVID-19, which illustrates robustness spatially and temporally. Our model is robust (R2>0.95) to depict the intrinsic growth rule for the cumulative number of confirmed infected, dead, and cured cases in 31 provinces in mainland China. Furthermore, we compared the intrinsic epidemic rules of COVID-19 in Hubei with that of severe acute respiratory syndrome (SARS) in Beijing, which was obtained from the Ministry of Public Health of China in 2003. We found that the infected case is the earliest to be saturated and has the lowest semi-saturation period compared with deaths and cured cases for both COVID-19 and SARS. All the three types of SARS cases are later to saturate and have longer semi-saturation period than that of COVID-19. Despite the virus caused SARS (SARS-CoV) and the virus caused COVID-19 (SARS-CoV-2) are homologous, the duration of the outbreak would be shorter for COVID-19.

negative: An Interactive Data Visualization and Analytics Tool to Evaluate Mobility and Sociability Trends During COVID-19 The COVID-19 outbreak has dramatically changed travel behavior in affected cities. The C2SMART research team has been investigating the impact of COVID-19 on mobility and sociability. New York City (NYC) and Seattle, two of the cities most affected by COVID-19 in the U.S. were included in our initial study. An all-in-one dashboard with data mining and cloud computing capabilities was developed for interactive data analytics and visualization to facilitate the understanding of the impact of the outbreak and corresponding policies such as social distancing on transportation systems. This platform is updated regularly and continues to evolve with the addition of new data, impact metrics, and visualizations to assist public and decision-makers to make informed decisions. This paper presents the architecture of the COVID related mobility data dashboard and preliminary mobility and sociability metrics for NYC and Seattle.

negative: Multilingual chief complaint classification for syndromic surveillance: An experiment with Chinese chief complaints Abstract Purpose Syndromic surveillance is aimed at early detection of disease outbreaks. An important data source for syndromic surveillance is free-text chief complaints (CCs), which may be recorded in different languages. For automated syndromic surveillance, CCs must be classified into predefined syndromic categories to facilitate subsequent data aggregation and analysis. Despite the fact that syndromic surveillance is largely an international effort, existing CC classification systems do not provide adequate support for processing CCs recorded in non-English languages. This paper reports a multilingual CC classification effort, focusing on CCs recorded in Chinese. Methods We propose a novel Chinese CC classification system leveraging a Chinese-English translation module and an existing English CC classification approach. A set of 470 Chinese key phrases was extracted from about one million Chinese CC records using statistical methods. Based on the extracted key phrases, the system translates Chinese text into English and classifies the translated CCs to syndromic categories using an existing English CC classification system. Results Compared to alternative approaches using a bilingual dictionary and a general-purpose machine translation system, our approach performs significantly better in terms of positive predictive value (PPV or precision), sensitivity (recall), specificity, and F measure (the harmonic mean of PPV and sensitivity), based on a computational experiment using real-world CC records. Conclusions Our design provides satisfactory performance in classifying Chinese CCs into syndromic categories for public health surveillance. The overall design of our system also points out a potentially fruitful direction for multilingual CC systems that need to handle languages beyond English and Chinese.

negative: Predicting Drug-Target Interaction Networks Based on Functional Groups and Biological Features BACKGROUND: Study of drug-target interaction networks is an important topic for drug development. It is both time-consuming and costly to determine compound-protein interactions or potential drug-target interactions by experiments alone. As a complement, the in silico prediction methods can provide us with very useful information in a timely manner. METHODS/PRINCIPAL FINDINGS: To realize this, drug compounds are encoded with functional groups and proteins encoded by biological features including biochemical and physicochemical properties. The optimal feature selection procedures are adopted by means of the mRMR (Maximum Relevance Minimum Redundancy) method. Instead of classifying the proteins as a whole family, target proteins are divided into four groups: enzymes, ion channels, G-protein- coupled receptors and nuclear receptors. Thus, four independent predictors are established using the Nearest Neighbor algorithm as their operation engine, with each to predict the interactions between drugs and one of the four protein groups. As a result, the overall success rates by the jackknife cross-validation tests achieved with the four predictors are 85.48%, 80.78%, 78.49%, and 85.66%, respectively. CONCLUSION/SIGNIFICANCE: Our results indicate that the network prediction system thus established is quite promising and encouraging.

negative: The impact of testing and infection prevention and control strategies on within-hospital transmission dynamics of COVID-19 in English hospitals Nosocomial transmission of SARS-CoV-2 is a key concern and evaluating the effect of testing and infection prevention control strategies is essential for guiding policy in this area. Using a within-hospital SEIR transition model of SARS-CoV-2 in a typical UK hospital, we predict that approximately 20% of infections in inpatients, and 89% of infections in HCWs were due to nosocomial transmission. Placing suspected COVID-19 patients in single rooms or bays has the potential to reduce hospital-acquired infections in patients by up to 80%. Periodic testing of HCWs has a smaller effect on the patient-burden of COVID-19 but would considerably reduce infection in HCWs by as much as 64% and result in only a small proportion of staff absences (approximately 1% per day). This is considerably fewer than currently observed due to suspected COVID-19 and self-isolation.

negative: COVID-19: How to Relax Social Distancing If You Must Following the April 16, 2020 release of the Opening Up America Again guidelines for relaxing COVID-19 social distancing policies, local leaders are concerned about future pandemic waves and lack robust strategies for tracking and suppressing transmission. Here, we present a framework for monitoring COVID-19 hospitalization data to project risks and trigger shelter-in-place orders to prevent overwhelming healthcare surges while minimizing the duration of costly lockdowns. Assuming the relaxation of social distancing increases the risk of infection ten-fold, the optimal strategy for Austin, Texas--the fastest-growing large city in the US--will trigger a total of 135 [90% prediction interval: 126-141] days of sheltering, allow schools to open in the fall, and result in an expected 2929 deaths [90% prediction interval: 2837-3026] by September 2021, which is 29% the annual mortality rate. In the months ahead, policy makers are likely to face difficult choices and the extent of public restraint and cocooning of vulnerable populations may save or cost thousands of lives.

negative: Estimating the presymptomatic transmission of COVID19 using incubation period and serial interval data We estimated the fraction and timing of presymptomatic transmissions of COVID19 with mathematical models combining the available data of the incubation period and serial interval. We found that up to 79.7% transmissions could be presymptomatic among the imported cases in China outside Wuhan. The average timing of presymptomatic transmissions is 3.8 days (SD = 6.1) before the symptom onset, which is much earlier than previously assumed.

negative: Detection and isolation of asymptomatic individuals can make the difference in COVID-19 epidemic management Mathematical modeling of infectious diseases is a powerful tool for the design of management policies and a fundamental part of the arsenal currently deployed to deal with the COVID-19 pandemic. Here we present a compartmental model for the disease that can provide healthcare burden parameters allowing to infer possible containment and suppression strategies, explicitly including asymptomatic individuals. The main conclusion of our work is that efficient and timely detection and isolation of these asymptomatic individuals can have dramatic effects on the effective reproduction number and healthcare burden parameters. This intervention can provide a valuable tool complementary to other non-pharmaceutical interventions to contain the epidemic.

negative: Coronavirus Disease 2019 and Educational Engagement

negative: Grief During the COVID-19 Pandemic: Considerations for Palliative Care Providers Abstract The COVID-19 pandemic is anticipated to continue spreading widely across the globe throughout 2020. To mitigate the devastating impact of COVID-19, social distancing and visitor restrictions in healthcare facilities have been widely implemented. Such policies and practices, along with the direct impact of the spread of COVID-19, complicate issues of grief that are relevant to medical providers. We describe the relationship of the COVID-19 pandemic to anticipatory grief, disenfranchised grief, and complicated grief for individuals, families, and their providers. Further, we provide discussion regarding countering this grief through communication, advance care planning, and self-care practices. We provide resources for healthcare providers, in addition to calling on palliative care providers to consider their own role as a resource to other specialties during this public health emergency.

negative: Coronavirus Disease 2019 (COVID-19) Pneumonia in a Hemodialysis Patient Coronavirus disease 2019 (COVID-19) is a highly infective disease caused by the severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2). Previous studies of the COVID-19 pneumonia outbreak were based on information from the general population. Limited data are available for hemodialysis patients with COVID-19 pneumonia. This report describes the clinical characteristics of COVID-19 in an in-center hemodialysis patient, as well as our experience in implementing steps to prevent the spread of COVID-19 pneumonia among in-center hemodialysis patients. The diagnosis, infection control, and treatment of COVID-19 in hemodialysis patients are discussed in this report, and we conclude with recommendations for how a dialysis facility can respond to COVID-19 based on our experiences.

negative: COVID-19 epidemic: Power law spread and flattening of the curve In this paper, we analyze the real-time infection data of COVID-19 epidemic for nine nations. Our analysis is up to 7 April 2020. For China and South Korea, who have already flattened their infection curves, the number of infected individuals (I(t)) exhibits power-law behavior before flattening of the curve. Italy has transitioned to the power-law regime for some time. For the other six nations-USA, Spain, Germany, France, Japan, and India-a power-law regime is beginning to appear after exponential growth. We argue that the transition from an exponential regime to a power-law regime may act as an indicator for flattening of the epidemic curve. We also argue that long-term community transmission and/or the transmission by asymptomatic carriers traveling long distances may be inducing the power-law growth of the epidemic.

negative: Interventions to mitigate early spread of SARS-CoV-2 in Singapore: a modelling study BACKGROUND: Since the coronavirus disease 2019 outbreak began in the Chinese city of Wuhan on Dec 31, 2019, 68 imported cases and 175 locally acquired infections have been reported in Singapore. We aimed to investigate options for early intervention in Singapore should local containment (eg, preventing disease spread through contact tracing efforts) be unsuccessful. METHODS: We adapted an influenza epidemic simulation model to estimate the likelihood of human-to-human transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a simulated Singaporean population. Using this model, we estimated the cumulative number of SARS-CoV-2 infections at 80 days, after detection of 100 cases of community transmission, under three infectivity scenarios (basic reproduction number [R(0)] of 1·5, 2·0, or 2·5) and assuming 7·5% of infections are asymptomatic. We first ran the model assuming no intervention was in place (baseline scenario), and then assessed the effect of four intervention scenarios compared with a baseline scenario on the size and progression of the outbreak for each R(0) value. These scenarios included isolation measures for infected individuals and quarantining of family members (hereafter referred to as quarantine); quarantine plus school closure; quarantine plus workplace distancing; and quarantine, school closure, and workplace distancing (hereafter referred to as the combined intervention). We also did sensitivity analyses by altering the asymptomatic fraction of infections (22·7%, 30·0%, 40·0%, and 50·0%) to compare outbreak sizes under the same control measures. FINDINGS: For the baseline scenario, when R(0) was 1·5, the median cumulative number of infections at day 80 was 279 000 (IQR 245 000–320 000), corresponding to 7·4% (IQR 6·5–8·5) of the resident population of Singapore. The median number of infections increased with higher infectivity: 727 000 cases (670 000–776 000) when R(0) was 2·0, corresponding to 19·3% (17·8–20·6) of the Singaporean population, and 1 207 000 cases (1 164 000–1 249 000) when R(0) was 2·5, corresponding to 32% (30·9–33·1) of the Singaporean population. Compared with the baseline scenario, the combined intervention was the most effective, reducing the estimated median number of infections by 99·3% (IQR 92·6–99·9) when R(0) was 1·5, by 93·0% (81·5–99·7) when R(0) was 2·0, and by 78·2% (59·0 −94·4) when R(0) was 2·5. Assuming increasing asymptomatic fractions up to 50·0%, up to 277 000 infections were estimated to occur at day 80 with the combined intervention relative to 1800 for the baseline at R(0) of 1·5. INTERPRETATION: Implementing the combined intervention of quarantining infected individuals and their family members, workplace distancing, and school closure once community transmission has been detected could substantially reduce the number of SARS-CoV-2 infections. We therefore recommend immediate deployment of this strategy if local secondary transmission is confirmed within Singapore. However, quarantine and workplace distancing should be prioritised over school closure because at this early stage, symptomatic children have higher withdrawal rates from school than do symptomatic adults from work. At higher asymptomatic proportions, intervention effectiveness might be substantially reduced requiring the need for effective case management and treatments, and preventive measures such as vaccines. FUNDING: Singapore Ministry of Health, Singapore Population Health Improvement Centre.

negative: IMPACT OF COVID-19 PANDEMIC ON MENTAL HEALTH OF MEDICAL STUDENTS:A CROSS-SECTIONAL STUDY USING GAD-7 AND PHQ-9 QUESTIONNAIRES Aim: to evaluate anxiety and depression disorders among medical students during COVID-19 pandemic. Methods: cross-sectional study of medical students conducted in May 2020 with questionnaires regarding social and demographic status and GAD-7 for anxiety and PHQ-9 for depression questionnaires. Results: participated 340 (97.98%) students. Average GAD-7 score was 9.18 (M = 9.18; SD = 4.75); average PHQ-9 score was 12.72 (M = 12.72; SD = 6.62). Results indicate a positive significant relationship between GAD-7 and females, and social distancing affecting finances. Using cut-off score of 10 for GAD-7, 157 (46.17%) students were identified with moderated or severe symptoms of anxiety. For PHQ-9 score, using cut-off of 10, 219 (64.41%) students were identified with moderate or severe symptoms of depression; results indicate a positive significant relationship between PHQ-9 and females and between social distancing affecting finances. Conclusion: analysis demonstrated a higher prevalence of moderated and severe anxiety and depression symptoms among medical students during COVID-19 pandemic, significantly among women and on medical students relating financial impairment related to COVID-19 epidemic.

negative: Performance of fabrics for home-made masks against spread of respiratory infection through droplets: a quantitative mechanistic study Respiratory infections may spread through droplets, airborne particles, and aerosols from infected individuals through coughing, sneezing, and speaking. In the case of Coronavirus Disease 2019 (COVID-19), droplet spread can occur from symptomatic as well as pre-symptomatic and asymptomatic persons. The U.S. Centers for Disease Control and Prevention (CDC) has therefore recently recommended home-made cloth face coverings for use by the general public in areas of significant community-based transmission. Because medical masks and N95 respirators are in short supply, these are to be reserved for healthcare workers. There is, however, little information on the effectiveness of home-made face coverings in reducing droplet dissemination. Here, we ascertained the performance of ten different fabrics, ranging from cotton to silk, in blocking high velocity droplets, using a 3-layered commercial medical mask as a benchmark material. We also assessed their breathability and ability to soak water. We reason that the materials should be as breathable as possible, without compromising blocking efficiency, to reduce air flow through the sides of the mask since such flow would defeat the purpose of the mask. We found that most home fabrics substantially block droplets, even as a single layer. With two layers, blocking performance can reach that of surgical mask without significantly compromising breathability. Furthermore, we observed that home fabrics are hydrophilic to varying degrees, and hence soak water. In contrast, medical masks are hydrophobic, and tend to repel water. Incoming droplets are thus soaked and 'held back' by home fabrics, which might offer an as of yet untapped and understudied advantage of home-made cloth masks. Overall, our study suggests that most double-layered cloth face coverings may help reduce droplet transmission of respiratory infections.

negative: A disconnected policy network: The UK's response to the Sierra Leone Ebola epidemic Abstract This paper investigates whether the inclusion of social scientists in the UK policy network that responded to the Ebola crisis in Sierra Leone (2013–16) was a transformational moment in the use of interdisciplinary research. In contrast to the existing literature, that relies heavily on qualitative accounts of the epidemic and ethnography, this study tests the dynamics of the connections between critical actors with quantitative network analysis. This novel approach explores how individuals are embedded in social relationships and how this may affect the production and use of evidence. The meso-level analysis, conducted between March and June 2019, is based on the traces of individuals' engagement found in secondary sources. Source material includes policy and strategy documents, committee papers, meeting minutes and personal correspondence. Social network analysis software, UCINet, was used to analyse the data and Netdraw for the visualisation of the network. Far from being one cohesive community of experts and government officials, the network of 134 people was weakly held together by a handful of super-connectors. Social scientists’ poor connections to the government embedded biomedical community may explain why they were most successful when they framed their expertise in terms of widely accepted concepts. The whole network was geographically and racially almost entirely isolated from those affected by or directly responding to the crisis in West Africa. Nonetheless, the case was made for interdisciplinarity and the value of social science in emergency preparedness and response. The challenge now is moving from the rhetoric to action on complex infectious disease outbreaks in ways that value all perspectives equally.

negative: 2019 Novel Coronavirus Disease (COVID-19): Paving the Road for Rapid Detection and Point-of-Care Diagnostics We believe a point-of-care (PoC) device for the rapid detection of the 2019 novel Coronavirus (SARS-CoV-2) is crucial and urgently needed. With this perspective, we give suggestions regarding a potential candidate for the rapid detection of the coronavirus disease 2019 (COVID-19), as well as factors for the preparedness and response to the outbreak of the COVID-19.

negative: The International Health Regulations: The Governing Framework for Global Health Security.

negative: Social preparedness in response to spatial distancing measures for aged care during COVID-19

negative: Community pharmacists and communication in the time of COVID-19: Applying the health belief model Abstract The emergence of the novel coronavirus disease (COVID-19) pandemic presents an unprecedented health communications challenge. Healthcare providers should reinforce behaviors that limit the spread of the pandemic, including social distancing and remaining in the home whenever possible. Formal communications toolkits may not be prepared in a timely fashion. Community pharmacists can reinforce mitigation behaviors by applying the health belief model (HBM). This commentary provides an overview of the HBM and offers suggestions on how community pharmacists can use it as a guide to patient communication in these uncertain contexts.

negative: Effectiveness of Testing, Tracing, Social Distancing and Hygiene in Tackling Covid-19 in India: A System Dynamics Model We present a System Dynamics (SD) model of the Covid-19 pandemic spread in India. The detailed age-structured compartment-based model endogenously captures various disease transmission pathways, expanding significantly from the standard SEIR model. The model is customized for India by using the appropriate population pyramid, contact rate matrices, external arrivals (as per actual data), and a few other calibrated fractions based on the reported cases of Covid-19 in India. Also, we have explicitly modeled, using independent time-variant levers, the effects of testing, contact tracing, isolating Covid-positive patients, quarantining, use of mask/better hygiene practices, social distancing through contact rate reductions at distinct zones of home(H), work(W), school(S) and other(O) locations. Simulation results show that, even after an extended lock-down, some non-trivial number of infections (even asymptomatic) will be left and the pandemic will resurface. Only tools that work against the pandemic is high rate of testing of those who show Covid-19 like symptoms, isolating them if they are positive and contact tracing all contacts of positive patients and quarantining them, in combination with use of face masks and personal hygiene. A wide range of combination of effectiveness of contact tracing, isolation, quarantining and personal hygiene measures help minimize the pandemic impact and some imperfections in implementation of one measure can be compensated by better implementation of other measures.

negative: Predictors of Mental Health during the early Covid-19 Pandemic in the US: role of economic concerns, health worries and social distancing Objective: To assess mental health in the US adult population in the Covid-19 pandemic and explore the roles of economic concerns, health worries and social distancing in shaping mental health outcomes. Methods: We analyze online survey data from the "Understanding America Study" (UAS) that is representative of the US adult population and covers the period of March 10-31st 2020 (sample size: 6436). Results: About 29% (CI:27.4-.30.4%) of the US adult population reported some depression/anxiety symptoms over the study period, with symptoms deteriorating over the month of March. Worsening mental health was most strongly associated with concerns about the economic consequences of the pandemic, while concerns about the potential impact of the virus on respondents' own health and the practice of social distancing also predicted the presence of depression and anxiety symptoms, albeit less strongly. Conclusions: Our findings point towards a major mental health crisis unfolding simultaneously with the pandemic in the US. They also highlight the importance of economic countermeasures and social policy for mitigating the impact of Covid-19 on adult mental health in the US over and above an effective public health response.

negative: Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in European countries: technical description update Following the emergence of a novel coronavirus (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions including case isolation, the closure of schools and universities, banning of mass gatherings and/or public events, and most recently, wide-scale social distancing including local and national lockdowns. In this technical update, we extend a semi-mechanistic Bayesian hierarchical model that infers the impact of these interventions and estimates the number of infections over time. Our methods assume that changes in the reproductive number - a measure of transmission - are an immediate response to these interventions being implemented rather than broader gradual changes in behaviour. Our model estimates these changes by calculating backwards from temporal data on observed to estimate the number of infections and rate of transmission that occurred several weeks prior, allowing for a probabilistic time lag between infection and death. In this update we extend our original model [Flaxman, Mishra, Gandy et al 2020, Report #13, Imperial College London] to include (a) population saturation effects, (b) prior uncertainty on the infection fatality ratio, (c) a more balanced prior on intervention effects and (d) partial pooling of the lockdown intervention covariate. We also (e) included another 3 countries (Greece, the Netherlands and Portugal). The model code is available at https://github.com/ImperialCollegeLondon/covid19model/ We are now reporting the results of our updated model online at https://mrc-ide.github.io/covid19estimates/ We estimated parameters jointly for all M=14 countries in a single hierarchical model. Inference is performed in the probabilistic programming language Stan using an adaptive Hamiltonian Monte Carlo (HMC) sampler.

negative: Hitting the reset button for hospitality research in times of crisis: Covid19 and beyond

negative: Agile Requirements Engineering and Software Planning for a Digital Health Platform to Engage the Effects of Isolation Caused by Social Distancing: Case Study BACKGROUND: Social distancing and shielding measures have been put in place to reduce social interaction and slow the transmission of the coronavirus disease (COVID-19). For older people, self-isolation presents particular challenges for mental health and social relationships. As time progresses, continued social distancing could have a compounding impact on these concerns. OBJECTIVE: This project aims to provide a tool for older people and their families and peers to improve their well-being and health during and after regulated social distancing. First, we will evaluate the tool’s feasibility, acceptability, and usability to encourage positive nutrition, enhance physical activity, and enable virtual interaction while social distancing. Second, we will be implementing the app to provide an online community to assist families and peer groups in maintaining contact with older people using goal setting. Anonymized data from the app will be aggregated with other real-world data sources to develop a machine learning algorithm to improve the identification of patients with COVID-19 and track for real time use by health systems. METHODS: Development of this project is occurring at the time of publication, and therefore, a case study design was selected to provide a systematic means of capturing software engineering in progress. The app development framework for software design was based on agile methods. The evaluation of the app’s feasibility, acceptability and usability shall be conducted using Public Health England's guidance on evaluating digital health products, Bandura’s model of health promotion, the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework and the Nonadoption, Abandonment and Challenges to the Scale-up, Spread and Suitability (NASSS) framework. RESULTS: Making use of a pre-existing software framework for health behavior change, a proof of concept was developed, and a multistage app development and deployment for the solution was created. Grant submissions to fund the project and study execution have been sought at the time of publication, and prediscovery iteration of the solution has begun. Ethical approval for a feasibility study design is being sought. CONCLUSIONS: This case study lays the foundations for future app development to combat mental and societal issues arising from social distancing measures. The app will be tested and evaluated in future studies to allow continuous improvement of the app. This novel contribution will provide an evidence-based exemplar for future app development in the space of social isolation and loneliness.

negative: Risk factors for severe corona virus disease 2019 (COVID-19) patients : a systematic review and meta analysis Importance: With the increasing number of infections for COVID-19, the global health resources are deficient. At present, we don't have specific medicines or vaccines against novel coronavirus pneumonia (NCP) and our assessment of risk factors for patients with severe pneumonia was limited. In order to maximize the use of limited medical resources, we should distinguish between mild and severe patients as early as possible. Objective: To systematically review the evidence of risk factors for severe corona virus disease 2019 (COVID-19) patients. Evidence Review: We conducted a comprehensive search for primary literature in both Chinese and English electronic bibliographic data bases including China National Knowledge Infrastructure (CNKI), Wanfang, Weipu, Chinese Biomedicine Literature Database (CBM-SinoMed), MEDLINE (via PubMed), EMBASE, Cochrane Central Register, and Web of science. The American agency for health research and quality (AHRQ) tool were used for assessing risk of bias. Mata-analysis was undertaken using STATA version 15.0. Results: 20 articles (N=4062 participants) were eligible for this systematic review and meta-analysis. First in this review and meta-analysis, we found that elderly male patients with a high body mass index, high breathing rate and a combination of underlying diseases (such as hypertension, diabetes, cardiovascular disease, and chronic obstructive pulmonary disease) were more likely to develop into critically ill patients. second, compared with ordinary patients, severe patients had more significant symptom such as fever and dyspnea. Besides, the laboratory test results of severe patients had more abnormal than non-severe patients, such as the elevated levels of white-cell counts, liver enzymes, lactate dehydrogenase, creatine kinase, c-reactive protein and procalcitonin, etc, while the decreased levels of lymphocytes and albumin, etc. Interpretation: This is the first systematic review investigating the risk factors for severe corona virus disease 2019 (COVID-19) patients. The findings are presented and discussed by different clinical characteristics. Therefore, our review may provide guidance for clinical decision-making and optimizes resource allocation.

negative: Critical Reflections on COVID-19 Communication Efforts Targeting Adolescents and Young Adults

negative: Pulmonary Pathology of Early-Phase 2019 Novel Coronavirus (COVID-19) Pneumonia in Two Patients With Lung Cancer Abstract There is currently a lack of pathologic data on the novel coronavirus (severe acute respiratory syndrome coronavirus 2) pneumonia, or coronavirus disease 2019 (COVID-19), from autopsy or biopsy. Two patients who recently underwent lung lobectomies for adenocarcinoma were retrospectively found to have had COVID-19 at the time of the operation. These two cases thus provide important first opportunities to study the pathology of COVID-19. Pathologic examinations revealed that apart from the tumors, the lungs of both patients exhibited edema, proteinaceous exudate, focal reactive hyperplasia of pneumocytes with patchy inflammatory cellular infiltration, and multinucleated giant cells. Hyaline membranes were not prominent. Because both patients did not exhibit symptoms of pneumonia at the time of operation, these changes likely represent an early phase of the lung pathology of COVID-19 pneumonia.

negative: Correlation between PCR Examination Rate among the Population and the Containment of Pandemic of COVID-19 We investigated the relation between PCR examination rate among population and the success of containment of COVID-19. Although there was moderate negative correlation, the effect cannot be separated from that of Gross Domestic Product per capita (GDP), which may well be related to the strict compliance to social distancing. Close inspection of individual countries suggested that the social distancing is the largest factor to achieve containment, and the contribution of broad PCR tests is smaller.

negative: Neighborhood income and physical distancing during the COVID-19 pandemic in the U.S. Introduction: Although physical distancing has been the primary strategy to reduce the spread of COVID-19 in the U.S., people's ability to distance may vary by socioeconomic characteristics, leading to higher transmission risk in low-income neighborhoods. Methods: We used mobility data from a large, anonymized sample of smartphone users to assess the relationship between neighborhood median household income and physical distancing during the COVID-19 epidemic. We assessed changes in several behaviors including: spending the day entirely at home; working outside the home; and visits to supermarkets, parks, hospitals, and other locations. We also assessed differences in effects of state policies on physical distancing across neighborhood income levels. Results: We found a strong gradient between neighborhood income and physical distancing. Compared to January and February 2020, the proportion of individuals spending the day entirely at home in April 2020 increased by 10.9 percentage points in low-income neighborhoods and by 27.1 percentage points in high-income neighborhoods. During April 2020, people in low-income neighborhoods were more likely to work outside the home, compared to people in higher-income neighborhoods, but not more likely to visit non-work locations. State physical distancing orders were associated with a 1.5 percentage-point increase (95% CI [0.9, 2.1], p < 0.001) in staying home in low-income neighborhoods and a 2.4 percentage point increase (95% CI [1.4, 3.4], p < 0.001) in high-income neighborhoods. Discussion: People in lower-income neighborhoods have faced barriers to physical distancing, particularly the need to work outside the home. State physical distancing policies have not mitigated these disparities.

negative: ‘Distancers’ and ‘non‐distancers’? The potential social psychological impact of moralizing COVID‐19 mitigating practices on sustained behaviour change COVID‐19 mitigating practices such as ‘hand‐washing’, ‘social distancing’, or ‘social isolating’ are constructed as ‘moral imperatives’, required to avert harm to oneself and others. Adherence to COVID‐19 mitigating practices is presently high among the general public, and stringent lockdown measures supported by legal and policy intervention have facilitated this. In the coming months, however, as rules are being relaxed and individuals become less strict, and thus, the ambiguity in policy increases, the maintenance of recommended social distancing norms will rely on more informal social interactional processes. We argue that the moralization of these practices, twinned with relaxations of policy, may likely cause interactional tension between those individuals who do vs. those who do not uphold social distancing in the coming months: that is, derogation of those who adhere strictly to COVID‐19 mitigating practices and group polarization between ‘distancers’ and ‘non‐distancers’. In this paper, we explore how and why these processes might come to pass, their impact on an overall societal response to COVID‐19, and the need to factor such processes into decisions regarding how to lift restrictions.

negative: Spontaneous social distancing in response to a simulated epidemic: a virtual experiment. BACKGROUND Studies of social distancing during epidemics have found that the strength of the response can have a decisive impact on the outcome. In previous work we developed a model of social distancing driven by individuals' risk attitude, a parameter which determines the extent to which social contacts are reduced in response to a given infection level. We showed by simulation that a strong response, driven by a highly cautious risk attitude, can quickly suppress an epidemic. However, a moderately cautious risk attitude gives weak control and, by prolonging the epidemic without reducing its impact, may yield a worse outcome than doing nothing. In real societies, social distancing may arise spontaneously from individual choices rather than being imposed centrally. There is little data available about this as opportunistic data collection during epidemics is difficult. Our study uses a simulated epidemic in a computer game setting to measure the social distancing response. METHODS Two hundred thirty participants played a computer game simulating an epidemic on a spatial network. The player controls one individual in a population of 2500 (with others controlled by computer) and decides how many others to contact each day. To mimic real-world trade-offs, the player is motivated to make contact by being rewarded with points, while simultaneously being deterred by the threat of infection. Participants completed a questionnaire regarding psychological measures of health protection motivation. Finally, simulations were used to compare the experimentally-observed response to epidemics with no response. RESULTS Participants reduced contacts in response to infection in a manner consistent with our model of social distancing. The experimentally observed response was too weak to halt epidemics quickly, resulting in a somewhat reduced attack rate and a substantially reduced peak attack rate, but longer duration and fewer social contacts, compared to no response. Little correlation was observed between participants' risk attitudes and the psychological measures. CONCLUSIONS Our cognitive model of social distancing matches responses to a simulated epidemic. If these responses indicate real world behaviour, spontaneous social distancing can be expected to reduce peak attack rates. However, additional measures are needed if it is important to stop an epidemic quickly.

negative: How Do We Balance Tensions Between COVID-19 Public Health Responses and Stigma Mitigation? Learning from HIV Research

negative: Reconstruction of Transmission Pairs for novel Coronavirus Disease 2019 (COVID-19) in mainland China: Estimation of Super-spreading Events, Serial Interval, and Hazard of Infection BACKGROUND: Knowledge on the epidemiological features and transmission patterns of COVID-19 is accumulating. Detailed line-list data with household settings can advance the understanding of COVID-19 transmission dynamics. METHODS: A unique database with detailed demographic characteristics, travel history, social relationships, and epidemiological timelines for 1,407 transmission pairs that formed 643 transmission clusters in mainland China was reconstructed from 9,120 COVID-19 confirmed cases reported during January 15 - February 29, 2020. Statistical model fittings were used to identify the super-spreaders and estimate serial interval distributions. Age and gender-stratified hazard of infection were estimated for household versus non-household transmissions. RESULTS: There were 34 primary cases identified as super-spreaders, with 5 super-spreading events occurred within households. Mean and standard deviation of serial intervals were estimated as 5.0 (95% CrI: 4.4, 5.5) and 5.2 (95% CrI: 4.9, 5.7) days for household transmissions and 5.2 (95% CrI: 4.6, 5.8) and 5.3 (95% CrI: 4.9, 5.7) days for non-household transmissions, respectively. Hazard of being infected outside of households is higher for age between 18 and 64 years, whereas hazard of being infected within households is higher for young and old people. CONCLUSIONS: Non-negligible frequency of super-spreading events, short serial intervals, and a higher risk of being infected outside of households for male people of working age indicate a significant barrier to the identification and management of COVID-19 cases, which requires enhanced non-pharmaceutical interventions to mitigate this pandemic.

negative: ELM—the database of eukaryotic linear motifs Linear motifs are short, evolutionarily plastic components of regulatory proteins and provide low-affinity interaction interfaces. These compact modules play central roles in mediating every aspect of the regulatory functionality of the cell. They are particularly prominent in mediating cell signaling, controlling protein turnover and directing protein localization. Given their importance, our understanding of motifs is surprisingly limited, largely as a result of the difficulty of discovery, both experimentally and computationally. The Eukaryotic Linear Motif (ELM) resource at http://elm.eu.org provides the biological community with a comprehensive database of known experimentally validated motifs, and an exploratory tool to discover putative linear motifs in user-submitted protein sequences. The current update of the ELM database comprises 1800 annotated motif instances representing 170 distinct functional classes, including approximately 500 novel instances and 24 novel classes. Several older motif class entries have been also revisited, improving annotation and adding novel instances. Furthermore, addition of full-text search capabilities, an enhanced interface and simplified batch download has improved the overall accessibility of the ELM data. The motif discovery portion of the ELM resource has added conservation, and structural attributes have been incorporated to aid users to discriminate biologically relevant motifs from stochastically occurring non-functional instances.

negative: Global epidemiology, pathogenesis, immune response, diagnosis, treatment, economic and psychological impact, challenges, and future prevention of COVID-19: A scoping review Background: Globally, the novel coronavirus, is a public health problem causing respiratory infections. Since the outbreak of severe acute and Middle East respiratory syndromes coronavirus was not reported to cause human infections. Now, it become an epidemic proportion with growing number of cases and deaths. Methods: A scoping review was conducted following the methodological framework. In this scoping review, 50 records published before 28 March, 2020 were included and discussed to better understand the current epidemiology, pathogenesis, immunological response, diagnosis, evasion mechanisms and suggested strategies to boost the immune system, challenges, treatment, and future preventions of the virus. PubMed, BioRxiv, MedRxiv, Global Health and google scholars were searched comprehensively for articles, preprints, grey literatures, reports, websites, conference proceedings and expert information. Studies conducted in human and published in the English language were included in the analysis. All the findings and statements of the review regarding the outbreak are based on published information as listed in citations. Results: We identified 360 records, of which 50 studies met the inclusion criteria. We synthesized the data from the included records and dig out the deep insights of them and pooled into this review. The burden of the outbreak is worsening due to overcrowding, presence of asymptomatic carriers, scarcity of test kits, the immune escaping ability of the virus and lack of awareness. Conclusions and recommendations: Due to the fast-spreading nature of COVID-19 the prevention and control strategies become challenging. It is imposing social, psychological, and socio-economic impacts. We recommended that following social distancing, isolation suspects, using personal protective equipment, health education and introducing handwashing practices, avoiding contact with animals, vaccine development and treatment for controlling and prevention.

negative: Clinician Wellness During the COVID-19 Pandemic: Extraordinary Times and Unusual Challenges for the Allergist/Immunologist The global spread of coronavirus disease 2019 (COVID-19) has caused sudden and dramatic societal changes. The allergy/immunology community has quickly responded by mobilizing practice adjustments and embracing new paradigms of care to protect patients and staff from severe acute respiratory syndrome coronavirus 2 exposure. Social distancing is key to slowing contagion but adds to complexity of care and increases isolation and anxiety. Uncertainty exists across a new COVID-19 reality, and clinician well-being may be an underappreciated priority. Wellness incorporates mental, physical, and spiritual health to protect against burnout, which impairs both coping and caregiving abilities. Understanding the stressors that COVID-19 is placing on clinicians can assist in recognizing what is needed to return to a point of wellness. Clinicians can leverage easily accessible tools, including the Strength-Focused and Meaning-Oriented Approach to Resilience and Transformation approach, wellness apps, mindfulness, and gratitude. Realizing early warning signs of anxiety, depression, substance abuse, and posttraumatic stress disorder is important to access safe and confidential resources. Implementing wellness strategies can improve flexibility, resilience, and outlook. Historical parallels demonstrate that perseverance is as inevitable as pandemics and that we need not navigate this unprecedented time alone.

negative: Social Support and Response to AIDS and Severe Acute Respiratory Syndrome Negative public reactions to emerging infectious diseases can adversely affect population health. We assessed whether social support was associated with knowledge of, worry about, and attitudes towards AIDS and severe acute respiratory syndrome. Our findings suggest that social support may be central to our understanding of public responses to emerging infectious diseases.

negative: Effect of Mitigation Measures on the Spreading of COVID-19 in Hard-Hit States State government-mandated social distancing measures have helped to slow down the growth of the COVID-19 pandemic in the United States. Current predictive models of the development of COVID-19, especially after mitigation efforts, are largely based on extrapolating the data from other countries. Since most states enforced stay-at-home orders towards the end of March, their effect should be reflected in the death and infection counts at the end of April. Using the data available until April 25th, we investigate the change in the infection rate due to the mitigation efforts, and project death and infection counts until September, 2020, for some of the most heavily impacted states: New York, New Jersey, Michigan, Massachusetts, Illinois and Louisiana. We find that with the current mitigation efforts five of those six states reduce their reproduction number to a value less than one, stopping the exponential growth of the pandemic. We also projected different scenarios after the mitigation is relaxed. Analysis for other states can be found at https://covid19projection.org/.

negative: Teicoplanin potently blocks the cell entry of 2019-nCoV Since December 2019, the outbreak of a new coronavirus, named 2019-nCoV, has greatly threatened the public health in China and raised great concerns worldwide. No specific treatment for this infection is currently available. We previously reported that teicoplanin, a glycopeptide antibiotic which has routinely been used in the clinic to treat bacterial infection with low toxicity, significantly inhibits the invasion of cells by Ebola virus, SARS-CoV and MERS-CoV, via specifically inhibiting the activity of cathepsin L. Here, we tested the efficacy of teicoplanin against 2019-nCoV virus infection and found that teicoplanin potently prevents the entrance of 2019-nCoV-Spike-pseudoviruses into the cytoplasm, with an IC50 of 1.66 μM. Although the inhibitory effect upon the replication of wildtype viruses ex vivo and in vivo remains to be determined, our preliminary result indicates that the potential antiviral activity of teicoplanin could be applied for the treatment of 2019-nCoV virus infection.

negative: Novel astroviruses in insectivorous bats. Bats are increasingly recognized to harbor a wide range of viruses, and in most instances these viruses appear to establish long-term persistence in these animals. They are the reservoir of a number of human zoonotic diseases including Nipah, Ebola, and severe acute respiratory syndrome. We report the identification of novel groups of astroviruses in apparently healthy insectivorous bats found in Hong Kong, in particular, bats belonging to the genera Miniopterus and Myotis. Astroviruses are important causes of diarrhea in many animal species, including humans. Many of the bat astroviruses form distinct phylogenetic clusters in the genus Mamastrovirus within the family Astroviridae. Virus detection rates of 36% to 100% and 50% to 70% were found in Miniopterus magnater and Miniopterus pusillus bats, respectively, captured within a single bat habitat during four consecutive visits spanning 1 year. There was high genetic diversity of viruses in bats found within this single habitat. Some bat astroviruses may be phylogenetically related to human astroviruses, and further studies with a wider range of bat species in different geographic locations are warranted. These findings are likely to provide new insights into the ecology and evolution of astroviruses and reinforce the role of bats as a reservoir of viruses with potential to pose a zoonotic threat to human health.

negative: Understanding the impact of the COVID-19 pandemic on well-being and virtual care for people living with dementia and care partners living in the community The COVID-19 pandemic has necessitated public health measures that have impacted the provision of care for people living with dementia and their families. Additionally, the isolation that results from social distancing may be harming well-being for families, as formal and informal supports become less accessible. For those with living with dementia and experiencing agitation, social distancing may be even harder to maintain, or social distancing could potentially aggravate dementia-related neuropsychiatric symptoms. To understand the lived experience of social and physical distancing during the COVID-19 pandemic in Canada we remotely interviewed 21 participants who normally attend a dementia specialty clinic in Calgary, Alberta, during a period where essential businesses were closed and healthcare had abruptly transitioned to telemedicine. The impacts of the public health measures in response to the pandemic emerged in three main categories of experience: 1) personal; 2) health services; and 3) health status (of both person living with dementia and care partner). This in-depth understanding of the needs and experiences of the pandemic for people living with dementia suggests that innovative means are urgently needed to facilitate provision of remote medicine and also social interaction and integration.

negative: Chinese Public Attention to COVID-19 Epidemic: Based on Social Media Background: Since the new coronavirus epidemic in China in December 2019, information and discussions about COVID-19 have spread rapidly on the Internet and have quickly become the focus of worldwide attention, especially on social media. Objective: This study aims to investigate and analyze the public's attention to COVID-19-related events in China at the beginning of the COVID-19 epidemic in China (December 31, 2019, to February 20, 2020) through the Sina Microblog hot search list. Methods: We collected topics related to the COVID-19 epidemic on the Sina Microblog hot search list from December 31, 2019, to February 20, 2020 and described the trend of public attention on COVID-19 epidemic-related topics. ROST CM6.0 (ROST Content Mining System Version 6.0) was used to analyze the collected text for word segmentation, word frequency, and sentiment analysis. We further described the hot topic keywords and sentiment trends of public attention. We used VOSviewer to implement a visual cluster analysis of hot keywords and build a social network of public opinion content. Results: The study has four main findings. First, we analyzed the changing trend of the public's attention to the COVID-19 epidemic, which can be divided into three stages. Second, the hot topic keywords of public attention at each stage are slightly different. In addition, the emotional tendency of the public toward the COVID-19 epidemic-related hot topics has changed from negative to neutral, with negative emotions weakening and positive emotions increasing as a whole. Finally, we divided the COVID-19 topics with the most public concern into five categories: (1) new COVID-19 epidemics and their impact; (2) frontline reporting of the epidemic and prevention and control measures; (3) expert interpretation and discussion on the source of infection; (4) medical services on the frontline of the epidemic; and (5) focus on the global epidemic and the search for suspected cases. Conclusions: This is the first study of public attention on the COVID-19 epidemic using a Chinese social media platform (i.e., Sina Microblog). Our study found that social media (e.g., Sina Microblog) can be used to measure public attention to public health emergencies. During the epidemic of the novel coronavirus, a large amount of information about the COVID-19 epidemic was disseminated on Sina Microblog and received widespread public attention. We have learned about the hotspots of public concern regarding the COVID-19 epidemic. These findings can help the government and health departments better communicate with the public on health and translate public health needs into practice to create targeted measures to prevent and control the spread of COVID-19. Keywords: COVID-19; Sina Microblog; Public attention; Social media; China; Public health emergency

negative: In vitro activity of R 61837, a new antirhinovirus compound R 61837 or 3-methoxy-6-[4-(3-methylphenyl)-1-piperazinyl]pyridazine is a new and potent inhibitor of rhinoviruses at concentrations not inhibitory to HeLa cell growth. Different rhinovirus serotypes varied widely in their susceptibility to the antiviral agent. The MICs for 50% CPE reduction ranged from 0.004 to 15 µg/ml. The yields of the most susceptible serotypes were reduced by a factor of 1,000 to 10,000 after single round high multiplicity infections in presence of low concentrations of the compound. The inactivation of some but not all serotypes in a time-, concentration- and temperature-dependent way by R 61837 indicated a direct interaction between the drug and the viral particles. The antiviral activity of the compound was confirmed in the human target cells for rhinoviruses by experiments using nasal polyp explant cultures.

negative: Editorial: EAERE, ERE and the Research Challenges of the Coronavirus Pandemic

negative: Introduction to Computer Network Vulnerabilities System vulnerabilities are weaknesses in the software or hardware on a server or a client that can be exploited by a determined intruder to gain access to or shut down a network. Donald Pipkin defines system vulnerability as a condition, a weakness of or an absence of security procedure, or technical, physical, or other controls that could be exploited by a threat [1].

negative: Lack of sufficient public space can limit the effectiveness of COVID-19's social distancing measures One of the primary strategies of slowing down the COVID-19 pandemic has been the establishment of social distancing rules that recommend keeping a buffer distance between individuals, and this has proven effective in helping in reducing the basic reproduction number [R 0] . However, social distancing rules have put the use of public spaces in densely populated places under strain, and this is especially important as some of the most virulent outbreaks of the COVID-19 pandemic have been in compact cities. It is therefore fundamental to take into account each neighbourhood's morphological characteristics and the potential population densities each street, square or park can accommodate under such new regulations in order to effectively enforce social distancing rules. Otherwise, certain areas may be rapidly overwhelmed by crowds with citizens unable to maintain the minimum safe distance between individuals. In this paper, we develop a method to identify the potential public space accessibility if social distancing rules are followed and we apply it to three global and highly affected by COVID-19 cities. Our research finds that, at micro level there are important inequalities between neighbourhoods, so people will struggle to comply with social distancing rules and consequently it will make controlling infection rates more difficult.

negative: Active surveillance for suspected COVID-19 cases in inpatients with information technology

negative: What are the risks of COVID-19 infection in pregnant women?

negative: Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world. Social distancing and isolation have been widely introduced to counter the COVID-19 pandemic. Adverse social, psychological and economic consequences of a complete or near-complete lockdown demand the development of more moderate contact-reduction policies. Adopting a social network approach, we evaluate the effectiveness of three distancing strategies designed to keep the curve flat and aid compliance in a post-lockdown world. These are: limiting interaction to a few repeated contacts akin to forming social bubbles; seeking similarity across contacts; and strengthening communities via triadic strategies. We simulate stochastic infection curves incorporating core elements from infection models, ideal-type social network models and statistical relational event models. We demonstrate that a strategic social network-based reduction of contact strongly enhances the effectiveness of social distancing measures while keeping risks lower. We provide scientific evidence for effective social distancing that can be applied in public health messaging and that can mitigate negative consequences of social isolation.

negative: Disease Transmission and Networks While epidemiological models have traditionally assumed that diseases spread by the mass action principle, actual contact networks within social groups do not meet this assumption. Theoretical models have shown that disease dynamics could vary considerably under different types of contact networks, but these models face challenges in terms of their evaluation due to the difficulty of collecting empirical data. The honeybee colony with its elaborate social organization and large repertoire of diseases provides an ideal setting to explore how the structure of the contact network contributes to the transmission of a disease.

negative: Pandemic Influenza Planning in the United States from a Health Disparities Perspective We explored how different socioeconomic and racial/ethnic groups in the United States might fare in an influenza pandemic on the basis of social factors that shape exposure, vulnerability to influenza virus, and timeliness and adequacy of treatment. We discuss policies that might differentially affect social groups’ risk for illness or death. Our purpose is not to establish the precise magnitude of disparities likely to occur; rather, it is to call attention to avoidable disparities that can be expected in the absence of systematic attention to differential social risks in pandemic preparedness plans. Policy makers at the federal, state, and local levels should consider potential sources of socioeconomic and racial/ethnic disparities during a pandemic and formulate specific plans to minimize these disparities.

negative: [Consideration and prevention for the aerosol transmission of 2019 novel coronavirus]. Novel coronavirus pneumonia broke out from Wuhan, and spreading to the whole nation and world since Dec, 2019. It is now the critical stage to fight against the virus. Previous epidemiological investigations and animal experiments suggest aerosol could perform as virus transmitter. Based on the clinical observation, the possibility of aerosol transmission of 2019 novel coronavirus has aroused a lot of attention. This study focuses on the feature of aerosol transmission, and the pathogens involved in. We analyzed the possibility of aerosol transmission for the novel coronavirus. Relevant strategies to prevent novel coronavirus pneumonia are established, serving as references to the medical personnel and general public during their work or daily life. ( Chin J Ophthalmol, 2020, 56: ).

negative: A data-driven network model for the emerging COVID-19 epidemics in Wuhan, Toronto and Italy The ongoing Coronavirus Disease 2019 (COVID-19) pandemic threatens the health of humans and causes great economic losses. Predictive modelling and forecasting the epidemic trends are essential for developing countermeasures to mitigate this pandemic. We develop a network model, where each node represents an individual and the edges represent contacts between individuals where the infection can spread. The individuals are classified based on the number of contacts they have each day (their node degrees) and their infection status. The transmission network model was respectively fitted to the reported data for the COVID-19 epidemic in Wuhan (China), Toronto (Canada), and the Italian Republic using a Markov Chain Monte Carlo (MCMC) optimization algorithm. Our model fits all three regions well with narrow confidence intervals and could be adapted to simulate other megacities or regions. The model projections on the role of containment strategies can help inform public health authorities to plan control measures.

negative: Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro

negative: Wider collateral damage to children in the UK because of the social distancing measures designed to reduce the impact of COVID-19 in adults

negative: Kitchen Spectroscopy: Shining a (UV) Light on Everyday Objects Fluorescent objects often lead to a sense of joy and intrigue. While the current COVID-19 pandemic limits the synthesis of “glowy things” like quantum dots, many household objects fluoresce, providing an opportunity to brighten your day while learning fundamental chemistry.

negative: Adolescents' Motivations to Engage in Social Distancing During the COVID-19 Pandemic: Associations With Mental and Social Health PURPOSE: Reducing the spread of infection during the COVID-19 pandemic prompted recommendations for individuals to socially distance. Little is known about the extent to which youth are socially distancing, what motivations underlie their social distancing, and how these motivations are connected with amount of social distancing, mental health, and social health. Using a large sample of adolescents from across the United States, this study examined adolescents' motivations for social distancing, their engagement in social distancing, and their mental and social health. METHODS: Data were collected on March 29th and 30th, 2020, two weeks after COVID-19 was declared a national emergency in the United States. The sample consisted of 683 adolescents recruited using social media. A series of multiple linear regressions examined unique associations among adolescents' motivations to engage in social distancing, perceived amount of social distancing, anxiety symptoms, depressive symptoms, burdensomeness, and belongingness. RESULTS: Almost all respondents (98.1%) reported engaging in at least a little social distancing. The most commonly reported motivations for social distancing concerned social responsibility and not wanting others to get sick. Motivations concerning state or city lockdowns, parental rules, and social responsibility were associated with greater social distancing, whereas motivations concerning no alternatives were associated with less social distancing. Specific motivations for social distancing were differentially associated with adolescents' anxiety symptoms, depressive symptoms, burdensomeness, and belongingness. CONCLUSIONS: Understanding adolescents' motivations to engage in social distancing may inform strategies to increase social distancing engagement, reduce pathogen transmission, and identify individual differences in mental and social health during the COVID-19 pandemic.

negative: Evolving epidemiology of novel coronavirus diseases 2019 and possible interruption of local transmission outside Hubei Province in China: a descriptive and modeling study Background The COVID-19 epidemic originated in Wuhan City of Hubei Province in December 2019 and has spread throughout China. Understanding the fast evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy. Methods We collected individual information on 8,579 laboratory-confirmed cases from official publically sources reported outside Hubei in mainland China, as of February 17, 2020. We estimated the temporal variation of the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level. Results The median age of the cases was 44 years, with an increasing of cases in younger age groups and the elderly as the epidemic progressed. The delay from symptom onset to hospital admission decreased from 4.4 days (95%CI: 0.0-14.0) until January 27 to 2.6 days (0.0-9.0) from January 28 to February 17. The mean incubation period was estimated at 5.2 days (1.8-12.4) and the mean serial interval at 5.1 days (1.3-11.6). The epidemic dynamics in provinces outside Hubei was highly variable, but consistently included a mix of case importations and local transmission. We estimate that the epidemic was self-sustained for less than three weeks with Rt reaching peaks between 1.40 (1.04-1.85) in Shenzhen City of Guangdong Province and 2.17 (1.69-2.76) in Shandong Province. In all the analyzed locations (n=10) Rt was estimated to be below the epidemic threshold since the end of January. Conclusion Our findings suggest that the strict containment measures and movement restrictions in place may contribute to the interruption of local COVID-19 transmission outside Hubei Province. The shorter serial interval estimated here implies that transmissibility is not as high as initial estimates suggested.

negative: Society of Cardiovascular Computed Tomography guidance for use of cardiac computed tomography amidst the COVID-19 pandemic Endorsed by the American College of Cardiology The world is currently suffering through a pandemic outbreak of severe respiratory syndrome coronavirus 2 (SARS-CoV-2) known as Coronavirus Disease 2019 (COVID-19). The United States (US) Centers for Disease Control and Prevention (CDC) currently advises medical facilities to "reschedule non-urgent outpatient visits as necessary". The European Centre for Disease Prevention and Control, the United Kingdom National Health Service and several other international agencies covering Asia, North America and most regions of the world have recommended similar "social distancing" measures. The Society of Cardiovascular Computed Tomography (SCCT) offers guidance for cardiac CT (CCT) practitioners to help implement these international recommendations in order to decrease the risk of COVID-19 transmission in their facilities while deciding on the timing of outpatient and inpatient CCT exams. This document also emphasizes SCCT's commitment to the health and well-being of CCT technologists, imagers, trainees, and research community, as well as the patients served by CCT.

negative: The Efficacy of Contact Tracing for the Containment of the 2019 Novel Coronavirus (COVID-19). Contact tracing is a central public health response to infectious disease outbreaks, especially in the early stages of an outbreak when specific treatments are limited. Importation of novel Coronavirus (COVID-19) from China and elsewhere into the United Kingdom highlights the need to understand the impact of contact tracing as a control measure. Using detailed survey information on social encounters coupled to predictive models, we investigate the likely efficacy of the current UK definition of a close contact (within 2 meters for 15 minutes or more) and the distribution of secondary cases that may go untraced. Taking recent estimates for COVID-19 transmission, we show that less than 1 in 5 cases will generate any subsequent untraced cases, although this comes at a high logistical burden with an average of 36.1 individuals (95th percentiles 0-182) traced per case. Changes to the definition of a close contact can reduce this burden, but with increased risk of untraced cases; we estimate that any definition where close contact requires more than 4 hours of contact is likely to lead to uncontrolled spread.

negative: [Surgical treatment for esophageal cancer during the outbreak of COVID-19]. Since December 2019, unexplained pneumonia has appeared in Wuhan City, Hubei Province, and a new type of coronavirus infection was confirmed as COVID-19. COVID-19 spread rapidly nationwide and abroad. The COVID-19 has brought huge impacts to all the people and walks of life, especially to the medical and health systems. It has also brought great challenges to the treatment of patients with cancer. Esophageal cancer is a common malignant tumor in China and most of the patients are in the middle and advanced stage when diagnosed, with immunosuppressive and poor prognosis. The selection of surgical procedures and perioperative managements of esophageal cancer require all thoracic surgeons work together to figure out a reasonable system of surgical treatment and emergency response.

negative: Does culture matter social distancing under the COVID-19 pandemic? This paper is the first to examine the role of the cultural dimension in practising social distancing across the world. By drawing the data from the Google COVID-19 community mobility reports and the Hofstede cultural factors for 58 countries over the period from 16 February to 29 March 2020, we find that countries with higher ‘Uncertainty Avoidance Index’ predict the lower proportion of people gathering in public such as retail and recreation, grocery and pharmacy, parks, transit stations, workplaces. However, we do not find any predictive factor in having a relationship with the percentage of citizens staying in their residential areas. Our results are robust by adding the control variable as the wealth status, GDP per capita. Hence, this paper suggests some effective communications to contain the COVID-19 pandemic by emphasizing the role of uncertainties.

negative: Psychological Outcomes Associated with Stay-at-Home Orders and the Perceived Impact of COVID-19 on Daily Life The COVID-19 pandemic has resulted in the widespread implementation of extraordinary physical distancing interventions (e.g., stay-at-home orders) to slow the spread of the virus. Although vital, these interventions may be socially and economically disruptive, contributing to adverse psychological outcomes. This study examined relations of both stay-at-home orders and the perceived impact of COVID-19 on daily life to psychological outcomes (depression, health anxiety, financial worry, social support, and loneliness) in a nationwide U.S. community adult sample (N = 500; 47% women, mean age = 40). Participants completed questionnaires assessing psychological outcomes, stay-at-home order status, and COVID-19's impact on their daily life. Being under a stay-at-home order was associated with greater health anxiety, financial worry, and loneliness. Moreover, the perceived impact of COVID-19 on daily life was positively associated with health anxiety, financial worry, and social support, but negatively associated with loneliness. Findings highlight the importance of social connection to mitigate negative psychological consequences of the COVID-19 pandemic.

negative: SARS-CoV-2 pandemic in India: what might we expect?

negative: Social distancing prevents infections, but it can have unintended consequences In response to the coronavirus pandemic, public health officials are asking us to do something that does not come naturally to our very social species: Stay away from each other Such social distancing—avoiding large gatherings and close contact with others—is crucial for slowing the spread of the virus and preventing our health care system from getting overwhelmed But it won’t be easy

negative: Viral evolution Abstract In the last two decades, viruses have been used as model systems to study evolution in short periods of time. Due to their characteristics, virus adapt rapidly to changing conditions, thus allowing the quantification of several evolutionary features under controlled laboratory conditions. Here we review the basic biology of viruses and describe in detail a number of experiments performed with RNA viruses. Particular emphasis is devoted to the interpretation of the experiments and to the involved phenomenology. This analysis sometimes represents the basis to formulate simple evolutionary models that aim at describing the observed dynamics. In other cases, theoretical results have prompted the realization of related experiments, as we discuss. Concepts as fitness loss and fitness recovery, the error threshold, increased mutagenesis, viral sex, or viral competition and interference, are discussed in an empirical framework and from the associated theoretical point of view.

negative: CHALLENGES IN THE FIGHT AGAINST THE COVID-19 PANDEMIC IN UNIVERSITY HOSPITALS

negative: Abstracts for the 29th Annual Meeting of the Japan Neuroscience Society (Neuroscience2006)

negative: Social Distancing as a Health Behavior: County-Level Movement in the United States During the COVID-19 Pandemic Is Associated with Conventional Health Behaviors BACKGROUND: Social distancing—when people limit close contact with others outside their household—is a primary intervention available to combat the COVID-19 pandemic. The importance of social distancing is unlikely to change until effective treatments or vaccines become widely available. However, relatively little is known about how best to promote social distancing. Applying knowledge from social and behavioral research on conventional health behaviors (e.g., smoking, physical activity) to support public health efforts and research on social distancing is promising, but empirical evidence supporting this approach is needed. PURPOSE: We examined whether one type of social distancing behavior—reduced movement outside the home—was associated with conventional health behaviors. METHOD: We examined the association between GPS-derived movement behavior in 2,858 counties in USA from March 1 to April 7, 2020 and the prevalence of county-level indicators influenced by residents’ conventional health behaviors. RESULTS: Changes in movement were associated with conventional health behaviors, and the magnitude of these associations were similar to the associations among the conventional health behaviors. Counties with healthier behaviors—particularly less obesity and greater physical activity—evidenced greater reduction in movement outside the home during the initial phases of the pandemic in the USA. CONCLUSIONS: Social distancing, in the form of reduced movement outside the home, is associated with conventional health behaviors. Existing scientific literature on health behavior and health behavior change can be more confidently used to promote social distancing behaviors during the COVID-19 pandemic.

negative: Cryo-EM structure of infectious bronchitis coronavirus spike protein reveals structural and functional evolution of coronavirus spike proteins As cell-invading molecular machinery, coronavirus spike proteins pose an evolutionary conundrum due to their high divergence. In this study, we determined the cryo-EM structure of avian infectious bronchitis coronavirus (IBV) spike protein from the γ-genus. The trimeric IBV spike ectodomain contains three receptor-binding S1 heads and a trimeric membrane-fusion S2 stalk. While IBV S2 is structurally similar to those from the other genera, IBV S1 possesses structural features that are unique to different other genera, thereby bridging these diverse spikes into an evolutionary spectrum. Specifically, among different genera, the two domains of S1, the N-terminal domain (S1-NTD) and C-terminal domain (S1-CTD), diverge from simpler tertiary structures and quaternary packing to more complex ones, leading to different functions of the spikes in receptor usage and membrane fusion. Based on the above structural and functional comparisons, we propose that the evolutionary spectrum of coronavirus spikes follows the order of α-, δ-, γ-, and β-genus. This study has provided insight into the evolutionary relationships among coronavirus spikes and deepened our understanding of their structural and functional diversity.

negative: “I will never go to Hong Kong again!” How the secondary crisis communication of “Occupy Central” on Weibo shifted to a tourism boycott Social media, an open space for the public's opinion and expression, has become an increasingly essential issue in crisis events, leading to secondary crisis communication. Realizing the potential risk of that, this study took the “Occupy Central” spreading on Weibo as a case, and applied topic clustering and sentiment analysis to examine the sequential characteristics of secondary crisis communication on social media in topics and emotions. Results show that the topics Weibo users discussed shifted from a political event to tourism boycott, with emotions turning increasingly negative. The turning point of such a transfer was aroused group conflicts and negative emotions elicited between people from mainland China and Hong Kong. The results indicate the necessity of emphasizing secondary crisis communication during a crisis due to the dynamic and sequential change of topics and public's emotions, which may result in new crises impacting the tourism destination where the initial crisis occurs.

negative: ElaD, a Deubiquitinating Protease Expressed by E. coli BACKGROUND: Ubiquitin and ubiquitin-like proteins (Ubl) are designed to modify polypeptides in eukaryotes. Covalent binding of ubiquitin or Ubls to substrate proteins can be reversed by specific hydrolases. One particular set of cysteine proteases, the CE clan, which targets ubiquitin and Ubls, has homologs in eukaryotes, prokaryotes, and viruses. FINDINGS: We have cloned and analyzed the E. coli protein elaD, which is distantly related to eukaryotic CE clan members of the ULP/SENP protease family that are specific for SUMO and Nedd8. Previously misannotated as a putative sulfatase/phosphatase, elaD is an efficient and specific deubiquitinating enzyme in vitro. Interestingly, elaD is present in all intestinal pathogenic E. coli strains, but conspicuously absent from extraintestinal pathogenic strains (ExPECs). Further homologs of this protease can be found in Acanthamoeba Polyphaga Mimivirus, and in Alpha-, Beta-and Gammaproteobacteria. CONCLUSION: The expression of ULP/SENP-related hydrolases in bacteria therefore extends to plant pathogens and medically relevant strains of Escherichia coli, Legionella pneumophila, Rickettsiae, Chlamydiae, and Salmonellae, in which the elaD ortholog sseL has recently been identified as a virulence factor with deubiquitinating activity. As a counterpoint, our phylogenetic and functional examination reveals that ancient eukaryotic ULP/SENP proteases also have the potential of ubiquitin-specific hydrolysis, suggesting an early common origin of this peptidase clan.

negative: A Call to Arms, Not to Disarm: The Importance of Psychiatric Care in the Acute Medical Setting During the COVID 19 Pandemic

negative: COVID-19, Mental Health and Aging: A Need for New Knowledge to Bridge Science and Service

negative: Simulation-based Estimation of the Spread of COVID-19 in Iran Background: The 2019 Coronavirus (COVID-19) has turned into a global pandemic with unprecedented challenges for the global community. Understanding the state of the disease and planning for future trajectories relies heavily on data on the spread and mortality. Yet official data coming from various countries are highly unreliable: symptoms similar to common cold in majority of cases and limited screening resources and delayed testing procedures may contribute to under-estimation of the burden of disease. Anecdotal and more limited data are available, but few have systematically combined those with official statistics into a coherent view of the epidemic. This study is a modeling-in-real-time of the emerging outbreak for understanding the state of the disease. Our focus is on the case of the spread of disease in Iran, as one of the epicenters of the disease in the first months of 2020. Method: We develop a simple dynamic model of the epidemic to provide a more reliable picture of the state of the disease based on existing data. Building on the generic SEIR (Susceptible, Exposed, Infected, and Recovered) framework we incorporate two behavioral and logistical considerations. First we capture the endogenous changes in contact rate (average contact per person) as more death are reported. As a result the reproduction number changes endogenously in the model. Second we differentiate reported and true cases by including simple formulations for how only a fraction of cases might be diagnosed, and how that fraction changes in response to epidemic's progression. In estimating the model we use both the official data as well as the discovered infected travelers and unofficial medical community estimates and triangulate these sources to build a more complete picture. Calibration is completed by forming a likelihood function for observing the actual time series data conditional on model parameters, and conducting a Markov Chain Monte Carlo simulations. The model is used to estimate current "true" cases of infection and death. We analyze the future trajectory of the disease under six conditions related to the seasonal effects and policy measures targeting social distancing. Findings: The model closely replicates the past data but also shows the true number of cases is likely far larger. We estimate about 493,000 current infected cases (90% CI: 271K-810K) as of March 20th, 2020. Our estimate for cumulative cases of infection until that date is 916,000 (90% CI: 508K, 1.5M), and for total death is 15,485 (90% CI: 8.4K, 25.8K). These numbers are significantly (more than one order of magnitude) higher than official statistics. The trajectory of the epidemic until the end of June could take various paths depending on the impact of seasonality and policies targeting social distancing. In the most optimistic scenario for seasonal effects, depending on policy measures, 1.6 million Iranians (90% CI: 0.9M-2.6M) are likely to get infected, and death toll will reach about 58,000 cases (90% CI: 32K-97K), while in the more pessimistic scenarios, death toll may exceed 103,000 cases (90% CI: 56K-172K). Implication: Our results suggest that the number of cases and deaths may be over an order of magnitude larger than official statistics in Iran. Absent extended testing capacity other countries may face a significant under-count of existing cases and thus be caught off guard about the actual toll of the epidemic.

negative: How necessary is a fast testkit for mitigation of pandemic flu? It is widely feared that a novel, highly pathogenic, human transmissible influenza virus may evolve that could cause the next global pandemic. Mitigating the spread of such an influenza pandemic would require not only the timely administration of antiviral drugs to those infected, but also the implementation of suitable intervention policies for stunting the spread of the virus. Towards this end, mathematical modelling and simulation studies are crucial as they allow us to evaluate the predicted effectiveness of the various intervention policies before enforcing them. Diagnosis plays a vital role in the overall pandemic management framework by detecting and distinguishing the pathogenic strain from the less threatening seasonal strains and other influenza-like illnesses. This allows treatment and intervention to be deployed effectively, given limited antiviral supplies and other resources. However, the time required to design a fast and accurate testkit for novel strains may limit the role of diagnosis. Herein, we aim to investigate the cost and effectiveness of different diagnostic methods using a stochastic agent-based city-scale model, and then address the issue of whether conventional testing approaches, when used with appropriate intervention policies, can be as effective as fast testkits in containing a pandemic outbreak. We found that for mitigation purposes, fast and accurate testkits are not necessary as long as sufficient medication is given, and are generally recommended only when used with extensive contact tracing and prophylaxis. Additionally, in the event of insufficient medication and fast testkits, the use of slower, conventional testkits together with proper isolation policies while waiting for the diagnostic results can be an equally effective substitute.

negative: Forecasting COVID-19 impact on hospital bed-days, ICU-days, ventilator-days and deaths by US state in the next 4 months Key Points Question: Assuming social distancing measures are maintained, what are the forecasted gaps in available health service resources and number of deaths from the COVID-19 pandemic for each state in the United States? Findings: Using a statistical model, we predict excess demand will be 64,175 (95% UI 7,977 to 251,059) total beds and 17,380 (95% UI 2,432 to 57,955) ICU beds at the peak of COVID-19. Peak ventilator use is predicted to be 19,481 (95% UI 9,767 to 39,674) ventilators. Peak demand will be in the second week of April. We estimate 81,114 (95% UI 38,242 to 162,106) deaths in the United States from COVID-19 over the next 4 months. Meaning: Even with social distancing measures enacted and sustained, the peak demand for hospital services due to the COVID-19 pandemic is likely going to exceed capacity substantially. Alongside the implementation and enforcement of social distancing measures, there is an urgent need to develop and implement plans to reduce non-COVID-19 demand for and temporarily increase capacity of health facilities. Abstract Importance: This study presents the first set of estimates of predicted health service utilization and deaths due to COVID-19 by day for the next 4 months for each state in the US. Objective: To determine the extent and timing of deaths and excess demand for hospital services due to COVID-19 in the US. Design, Setting, and Participants: This study used data on confirmed COVID-19 deaths by day from WHO websites and local and national governments; data on hospital capacity and utilization for US states; and observed COVID-19 utilization data from select locations to develop a statistical model forecasting deaths and hospital utilization against capacity by state for the US over the next 4 months. Exposure(s): COVID-19. Main outcome(s) and measure(s): Deaths, bed and ICU occupancy, and ventilator use. Results: Compared to licensed capacity and average annual occupancy rates, excess demand from COVID-19 at the peak of the pandemic in the second week of April is predicted to be 64,175 (95% UI 7,977 to 251,059) total beds and 17,380 (95% UI 2,432 to 57,955) ICU beds. At the peak of the pandemic, ventilator use is predicted to be 19,481 (95% UI 9,767 to 39,674). The date of peak excess demand by state varies from the second week of April through May. We estimate that there will a total of 81,114 (95% UI 38,242 to 162,106) deaths from COVID-19 over the next 4 months in the US. Deaths from COVID-19 are estimated to drop below 10 deaths per day between May 31 and June 6. Conclusions and Relevance: In addition to a large number of deaths from COVID-19, the epidemic in the US will place a load well beyond the current capacity of hospitals to manage, especially for ICU care. These estimates can help inform the development and implementation of strategies to mitigate this gap, including reducing non-COVID-19 demand for services and temporarily increasing system capacity. These are urgently needed given that peak volumes are estimated to be only three weeks away. The estimated excess demand on hospital systems is predicated on the enactment of social distancing measures in all states that have not done so already within the next week and maintenance of these measures throughout the epidemic, emphasizing the importance of implementing, enforcing, and maintaining these measures to mitigate hospital system overload and prevent deaths.

negative: Analysis on the epidemic factors for the Corona Virus Disease/ 中华预防医学杂志 Since December 2019, corona virus disease 2019 (COVID-19) , an emerging infection disease occurred in Wuhan, has spread in the mainland China. The epidemic factors on the basis of knowledge of SARS-CoV-2 were discussed in this paper. This puts a lot of pressure on clinical resources and care. SARS-CoV-2 is a novel corona virus, the onset of COVID-19 is slow, and the pathogenesis of SARS-CoV-2 remains unclear and may lead to multiple organ damage. These put a lot of pressure on clinical resources and care. Source of infection including the patients, asymptomatic carrier and patients in the incubation period are contagious. It is difficult to control source of infection. Routes of SARS-CoV-2 transmission are diversified and the main routes of transmission for COVID-19 are droplet transmission and close contact transmission. All population have susceptibility to SARS-CoV-2. Social factors such population movements and aggregation accelerated the spread of SARS-CoV-2. The Chinese government’s adopted measures are positive and effective, and are accepted by the expert group from the World Health Organization. However, it will be a long-term hard work in the future to seriously summarize and think deeply to achieve public health security in China.

negative: Insights into the impact of COVID-19 on household travel and activities in Australia – The early days under restrictions When 2020 began, we had no idea what was to unfold globally as we learnt about the Novel-Coronavirus in Wuhan, in the Hubei province of China. As this virus spread rapidly, it became a matter of time before many countries began to implement measures to try and contain the spread of the disease. COVID-19 as it is referred to, resulted in two main approaches to fighting the viral pandemic, either through a progressive set of measures to slow down the number of identified cases designed to ‘flatten the curve’ over time (anticipated to be at least six months), or to attack it by the severest of measures including a total lock-down and/or herding exposure to fast track ‘immunisation’ while we await a vaccine. The paper reports the findings from the first phase of an ongoing survey designed to identify the changing patterns in travel activity of Australian residents as a result of the stage 2 restrictions imposed by the Australian government. The main restrictions, in addition to social distancing of at least 1.5 m, are closure of entry to Australia (except residents returning), and closure of non-essential venues such as night clubs, restaurants, mass attendee sporting events, churches, weddings, and all social gatherings in any circumstance. With some employers encouraging working from home and others requiring it, in addition to job losses, and many children attending school online from home, the implications on travel activity is extreme. We identify the initial impacts associated with the first month of stricter social distancing measures introduced in Australia.

negative: COVID-19: A promising cure for the global panic Abstract The novel Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2, which is the causative agent of a potentially fatal disease that is of great global public health concern. The outbreak of COVID-19 is wreaking havoc worldwide due to inadequate risk assessment regarding the urgency of the situation. The COVID-19 pandemic has entered a dangerous new phase. When compared with SARS and MERS, COVID-19 has spread more rapidly, due to increased globalization and adaptation of the virus in every environment. Slowing the spread of the COVID-19 cases will significantly reduce the strain on the healthcare system of the country by limiting the number of people who are severely sick by COVID-19 and need hospital care. Hence, the recent outburst of COVID-19 highlights an urgent need for therapeutics targeting SARS-CoV-2. Here, we have discussed the structure of virus; varying symptoms among COVID-19, SARS, MERS and common flu; the probable mechanism behind the infection and its immune response. Further, the current treatment options, drugs available, ongoing trials and recent diagnostics for COVID-19 have been discussed. We suggest traditional Indian medicinal plants as possible novel therapeutic approaches, exclusively targeting SARS-CoV-2 and its pathways.

negative: Coronavirus disease 2019 (COVID-19) pandemic: Review of guidelines for resuming non-urgent imaging and procedures in radiology during Phase II. Since the spread of the coronavirus disease 2019 (COVID-19) was designated as a pandemic by the World Health Organization, health care systems have been forced to adapt rapidly to defer less urgent care during the crisis. The United States (U.S.) has adopted a four-phase approach to decreasing and then resuming non-essential work. Through strong restrictive measures, Phase I slowed the spread of disease, allowing states to safely diagnose, isolate, and treat patients with COVID-19. In support of social distancing measures, non-urgent studies were postponed, and this created a backlog. Now, as states transition to Phase II, restrictions on non-essential activities will ease, and radiology departments must re-establish care while continuing to mitigate the risk of COVID-19 transmission all while accommodating this backlog. In this article, we propose a roadmap that incorporates the current practice guidelines and subject matter consensus statements for the phased reopening of non-urgent and elective radiology services. This roadmap will focus on operationalizing these recommendations for patient care and workforce management. Tiered systems are proposed for the prioritization of elective procedures, with physician-to-physician communication encouraged. Infection control methods, provision of personal protective equipment (PPE), and physical distancing measures are highlighted. Finally, changes in hours of operation, hiring strategies, and remote reading services are discussed for their potential to ease the transition to normal operations.

negative: The first confirmed case of COVID-19 in Tanzania: recommendations based on lesson learned from China As the coronavirus disease (COVID-19) takes its course outside China, the number of imported cases to other countries is on the rise. Currently, Tanzania has received the first imported case on 16 March 2020. This letter serves to describe this specific event and put forth a number of recommendations including establishing more testing points, discouraging all forms of public and religious gatherings, and tailoring a unique model for lockdown and social distancing to prevent further spread of the disease. The letter has also suggested ways to further improve the efforts already in place so as to strengthen the prevention and control system.

negative: Psychosocial consequences of infectious diseases Abstract Historically, there has been an exaggerated fear related to infection compared to other conditions. Infection possesses unique characteristics that account for this disproportionate degree of fear: it is transmitted rapidly and invisibly; historically, it has accounted for major morbidity and mortality; old forms re-emerge and new forms emerge; and both the media and society are often in awe. Because, in an outbreak, the patient is both a victim and a vector, and because there exists the potential for infringement of personal rights in order to control an outbreak, infection may be viewed (and has been depicted in popular culture) as a foreign invasion. During recent outbreaks, fear, denial, stigmatization and loss have been recorded in the implicated individuals. Stigmatization and discrimination may further involve ethical correlations, and attempts to adress these issues through activism may also have unwarranted effects. Public health initiatives can address the public's fears by increasing health literacy, which can contribute to reducing stigmatization.

negative: Current status of treatment for 2019 novel coronavirus pneumonia/ 中华微生物学和免疫学杂志 2019 novel coronavirus (2019-nCoV) is a new member of coronavirus family that can cause serious respiratory diseases after the emergence of severe acute respiratory syndrome-coronavirus (SARS-CoV) and middle east respiratory syndrome-coronavirus (MERS-CoV). At present, there is no specific antiviral drug targeting 2019-nCoV. In facing of the increasingly serious epidemic of 2019 novel coronavirus pneumonia and the urgent needs in drug treatment strategies, this paper reviewed the current research situation and progress in antiviral treatment for the newly identified disease.

negative: Chapter 8 Zoonoses in Wildlife Integrating Ecology into Management Abstract Zoonoses in wildlife not only play an important ecological role, but pose significant threats to the health of humans, domestic animals and some endangered species. More than two‐thirds of emerging, or re‐emerging, infectious diseases are thought to originate in wildlife. Despite this, co‐ordinated surveillance schemes are rare, and most efforts at disease control operate at the level of crisis management. This review examines the pathways linking zoonoses in wildlife with infection in other hosts, using examples from a range of key zoonoses, including European bat lyssaviruses and bovine tuberculosis. Ecologically based control, including the management of conditions leading to spill‐overs into target host populations, is likely to be more effective and sustainable than simple reductions in wildlife populations alone.

negative: The Ivory Tower Lost: How College Students Respond Differently than the General Public to the COVID-19 Pandemic Recently, the pandemic of the novel Coronavirus Disease-2019 (COVID-19) has presented governments with ultimate challenges. In the United States, the country with the highest confirmed COVID-19 infection cases, a nationwide social distancing protocol has been implemented by the President. For the first time in a hundred years since the 1918 flu pandemic, the US population is mandated to stay in their households and avoid public contact. As a result, the majority of public venues and services have ceased their operations. Following the closure of the University of Washington on March 7th, more than a thousand colleges and universities in the United States have cancelled in-person classes and campus activities, impacting millions of students. This paper aims to discover the social implications of this unprecedented disruption in our interactive society regarding both the general public and higher education populations by mining people's opinions on social media. We discover several topics embedded in a large number of COVID-19 tweets that represent the most central issues related to the pandemic, which are of great concerns for both college students and the general public. Moreover, we find significant differences between these two groups of Twitter users with respect to the sentiments they expressed towards the COVID-19 issues. To our best knowledge, this is the first social media-based study which focuses on the college student community's demographics and responses to prevalent social issues during a major crisis.

negative: Tabagisme et maladie à coronavirus 2019 (COVID-19)

negative: Use of all cause mortality to quantify the consequences of covid-19 in Nembro, Lombardy: descriptive study OBJECTIVE: To quantify the impact of coronavirus disease 2019 (covid-19) on all cause mortality in Nembro, an Italian city severely affected by the covid-19 pandemic. DESIGN: Descriptive study. SETTING: Nembro, in the Bergamo province of Lombardy, northern Italy. POPULATION: Residents of Nembro. MAIN OUTCOME MEASURES: Monthly all cause mortality between January 2012 and April 2020 (data to 11 April), number of confirmed deaths from covid-19 to 11 April 2020, and weekly absolute number of deaths between 1 January and 4 April across recent years by age group and sex. RESULTS: Nembro had 11 505 residents as of 1 January 2020. Monthly all cause mortality between January 2012 and February 2020 fluctuated around 10 per 1000 person years, with a maximum of 21.5 per 1000 person years. In March 2020, monthly all cause mortality reached a peak of 154.4 per 1000 person years. For the first 11 days in April, this rate decreased to 23.0 per 1000 person years. The observed increase in mortality was driven by the number of deaths among older people (≥65 years), especially men. From the outbreak onset until 11 April 2020, only 85 confirmed deaths from covid-19 in Nembro were recorded, corresponding to about half of the 166 deaths from all causes observed in that period. CONCLUSIONS: The study findings show how covid-19 can have a considerable impact on the health of a small community. Furthermore, the results suggest that the full implications of the covid-19 pandemic can only be completely understood if, in addition to confirmed deaths related to covid-19, consideration is also given to all cause mortality in a given region and time frame.

negative: PepMapper: A Collaborative Web Tool for Mapping Epitopes from Affinity-Selected Peptides Epitope mapping from affinity-selected peptides has become popular in epitope prediction, and correspondingly many Web-based tools have been developed in recent years. However, the performance of these tools varies in different circumstances. To address this problem, we employed an ensemble approach to incorporate two popular Web tools, MimoPro and Pep-3D-Search, together for taking advantages offered by both methods so as to give users more options for their specific purposes of epitope-peptide mapping. The combined operation of Union finds as many associated peptides as possible from both methods, which increases sensitivity in finding potential epitopic regions on a given antigen surface. The combined operation of Intersection achieves to some extent the mutual verification by the two methods and hence increases the likelihood of locating the genuine epitopic region on a given antigen in relation to the interacting peptides. The Consistency between Intersection and Union is an indirect sufficient condition to assess the likelihood of successful peptide-epitope mapping. On average from 27 tests, the combined operations of PepMapper outperformed either MimoPro or Pep-3D-Search alone. Therefore, PepMapper is another multipurpose mapping tool for epitope prediction from affinity-selected peptides. The Web server can be freely accessed at: http://informatics.nenu.edu.cn/PepMapper/

negative: Strict Physical Distancing May Be More Efficient: A Mathematical Argument for Making Lockdowns Count COVID-19 created a global public health and economic emergency. Policymakers acted quickly and decisively to contain the spread of disease through physical distancing measures. However, these measures also impact physical, mental and economic well-being, creating difficult trade-offs. Here we use a simple mathematical model to explore the balance between public health measures and their associated social and economic costs. Across a range of cost-functions and model structures, commitment to intermittent and strict social distancing measures (lockdowns) leads to better overall outcomes than temporally consistent implementation of moderate physical distancing measures. With regard to the trade-offs that policy makers may soon face, our results emphasize that economic and health out comes do not exist in full competition. Compared to consistent moderation, intermittently strict policies can better mitigate the impact of the pandemic on both of these priorities for a range of plausible utility functions.

negative: Pediatric epidemic crisis: Lessons for policy and practice development Abstract Objectives This research study addresses health policy and patient care considerations, and outlines policy and practice implications resulting from a crisis in a pediatric setting. This crisis, an epidemic outbreak of Severe Acute Respiratory Syndrome (SARS), dramatically impacted the delivery of health care in Canada. Despite the passage of time since the last diagnosed case of SARS in April 2004, researchers have warned the global community to be prepared for future outbreaks of SARS or other infectious diseases. Methods Qualitative interviews were conducted with 23 participants representing key stakeholder groups: (a) pediatric patients with probable or suspected SARS, (b) their parents, and (c) health care professionals providing direct care to SARS patients. Results Participants conveyed key areas in which health policy and practice were affected. These included the development of communication strategies for responding to SARS; easing vulnerability among all stakeholders; and the rapid development of practice guidelines. Conclusion Given the continuing threat of current and future airborne viruses with potential for epidemic spread and devastating outcomes, preparedness strategies are certainly needed. Effective strategies in pediatrics include practices that provide family centered care while minimizing disease transmission. Toward this end, lessons learned from previous outbreaks merit consideration and may inform future epidemics.

negative: Social and administrative issues related to the COVID-19 pandemic in Pakistan: better late than never The study critically reviewed Pakistan’s provincial updates of coronavirus disease 2019 (COVID-19) and discussed the current challenges faced by the government in a given context. The coronavirus-associated death tolls have been increasing rapidly in a country. The provincial status of confirmed cases of coronavirus is higher in Punjab, followed by the Sindh, Khyber Pakhtunkhwa (KPK), and Balochistan. The case fatality ratio shows that KPK has a higher ratio, i.e., 5.11%, followed by the Punjab, i.e., 1.82%; Sindh, i.e., 1.80%; Balochistan, i.e., 1.28%; Gilgit-Baltistan, i.e., 0.71%; and Federal territory, i.e., 0.66%. The country has a less testing capacity to identify more suspected coronavirus patients. The study calculated that if we increase five times our testing capacity from the current date, the total registered cases will be reached to 137,370 and death tolls will increase up to 3090. It is highly needed to increase testing capacity across Pakistan in order to minimize the outbreak of coronavirus. The provincial government should follow the Federal Government instructions to contain coronavirus by increasing testing capacities, tracing suspected patients, smart lockdowns, emergency relief to the poor, and vigilant monitoring system.

negative: Tomar medidas preventivas inmediatamente: evidencia de China sobre el COVID-19

negative: Why are pregnant women susceptible to COVID-19? An immunological viewpoint Abstract The 2019 novel coronavirus disease (COVID-19) was first detected in December 2019 and became epidemic in Wuhan, Hubei Province, China. COVID-19 has been rapidly spreading out in China and all over the world. The virus causing COVID-19, SARS-CoV-2 has been known to be genetically similar to severe acute respiratory syndrome coronavirus (SARS-CoV) but distinct from it. Clinical manifestation of COVID-19 can be characterized by mild upper respiratory tract infection, lower respiratory tract infection involving non-life threatening pneumonia, and life-threatening pneumonia with acute respiratory distress syndrome. It affects all age groups, including newborns, to the elders. Particularly, pregnant women may be more susceptible to COVID-19 since pregnant women, in general, are vulnerable to respiratory infection. In pregnant women with COVID-19, there is no evidence for vertical transmission of the virus, but an increased prevalence of preterm deliveries has been noticed. The COVID-19 may alter immune responses at the maternal-fetal interface, and affect the well-being of mothers and infants. In this review, we focused on the reason why pregnant women are more susceptible to COVID-19 and the potential maternal and fetal complications from an immunological viewpoint.

negative: Impact of COVID 19 lockdown on orthopaedic surgeons in India: A survey() BACKGROUND: In the fight against COVID 19, the government of India announced a 3 weeks lockdown of the entire country of 1.3 billion people on 24(th) March 2020. METHODS: One week after the lockdown was announced, we conducted an anonymous online survey of the orthopaedic surgeons in India through social media platforms to assess the impact of the lockdown during COVID 19. The survey had a total of 13 questions with (3–5) options and was designed with an aim to understand the perception and the state of mind of the Orthopaedic surgeons in the lockdown situation. RESULTS: The survey was completed by 611 orthopaedic surgeons from 140 cities in India. There were 22.5% orthopaedic surgeons who said that they were definitely stressed out, and 40.5% who said they were mildly stressed out. As the age decreased, the percentage of orthopaedic surgeons feeling “definitely stressed out” increased. Disruption of life-work balance and uncertainties regarding return to work were other strongly associated factors with the “definitely stressed out” group. CONCLUSION: The psychological impact of the lockdown during COVID 19 on orthopaedic surgeons may become a potential concern that will require addressal through open discussion. LEVEL OF EVIDENCE: diagnostic level 4.

negative: The Twitter Social Mobility Index: Measuring Social Distancing Practices from Geolocated Tweets Social distancing is an important component of the response to the novel Coronavirus (COVID-19) pandemic. Minimizing social interactions and travel reduces the rate at which the infection spreads, and"flattens the curve"such that the medical system can better treat infected individuals. However, it remains unclear how the public will respond to these policies. This paper presents the Twitter Social Mobility Index, a measure of social distancing and travel derived from Twitter data. We use public geolocated Twitter data to measure how much a user travels in a given week. We find a large reduction in travel in the United States after the implementation of social distancing policies, with larger reductions in states that were early adopters and smaller changes in states without policies. Our findings are presented on http://socialmobility.covid19dataresources.org and we will continue to update our analysis during the pandemic.

negative: Biopsychopharmacosocial approach to assess impact of social distancing and isolation on mental health in older adults It is impossible to predict or comprehend the impact of the ongoing COVID-19 pandemic. The UK Government's advice for vulnerable people, including older adults, to move towards self-isolation and social distancing is likely to reduce rates of transmission, the risk of severe illness and the impact on the acute health services. Although justified and necessary, this process of isolation is likely to have a negative impact on the mental health of these vulnerable groups, especially older people. It will become increasingly important for community health professionals to assess subtle changes in older persons' mental health, as the duration of this period of isolation remains unclear. The biopsychopharmacosocial model provides one method of assessing mental health and planning health and social care needs. This article hopes to guide community health professionals through the specifics of this assessment model in relation to the growing COVID-19 pandemic.

negative: Japanese citizens' behavioral changes and preparedness against COVID-19: How effective is Japan's approach of self-restraint? The Japanese government instituted countermeasures against COVID-19, a pneumonia caused by the new coronavirus, in January 2020. Seeking “people's behavioral changes,” in which the government called on the public to take precautionary measures or exercise self-restraint, was one of the important strategies. The purpose of this study is to investigate how and from when Japanese citizens have changed their precautionary behavior under these circumstances, where the government has only requested their cooperation. This study uses micro data from a cross-sectional survey conducted on an online platform of an online research company, based on quota sampling that is representative of the Japanese population. By the end of March 2020, we had recruited a total of 11,342 respondents, aged from 20 to 64 years. About 85% reported practising the social distancing recommended by the government. More females than males and more older than younger participants are supportive of practicing social distancing. Frequent handwashing is conducted by 86 percent of all, 92 percent of female and 87.9 percent of over-40 participants. The most important event influencing these precautionary actions was the infection aboard the Diamond Princess cruise ship, which occurred in early February 2020 (23%). Information from the central and local governments, received by 60% of the participants, was deemed trustworthy by 50%. However, the results also showed that about 20% of the participants were reluctant to implement proper prevention measures. The statistical analysis indicated that the typical characteristics of those people were male, younger (under 30 years old), unmarried, from lower-income households, with a drinking or smoking habit and a higher extraversion score. To prevent the spread of infection in Japan, it is imperative to address these individuals and encourage their behavioral changes using various means to reach and influence them.

negative: Understanding of guidance for acupuncture and moxibustion interventions on COVID-19 (Second edition) issued by CAAM Abstract At present, the situation of global fight against COVID-19 is serious. WHO (World Health Organization)-China Joint Mission fully confirms the success of “China's model” against COVID-19 in the report. In fact, one particular power in “China's model” is acupuncture and moxibustion of traditional Chinese medicine. To better apply “non-pharmaceutic measures”—the external technique of traditional Chinese medicine, in the article, the main content of Guidance for acupuncture and moxibustion interventions on COVID-19 (Second edition) issued by China Association of Acupuncture–Moxibution is introduced and the discussion is stressed on the selection of moxibustion device and the duration of its exertion.

negative: Social and environmental risk factors in the emergence of infectious diseases Fifty years ago, the age-old scourge of infectious disease was receding in the developed world in response to improved public health measures, while the advent of antibiotics, better vaccines, insecticides and improved surveillance held the promise of eradicating residual problems. By the late twentieth century, however, an increase in the emergence and re-emergence of infectious diseases was evident in many parts of the world. This upturn looms as the fourth major transition in human–microbe relationships since the advent of agriculture around 10,000 years ago. About 30 new diseases have been identified, including Legionnaires' disease, human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS), hepatitis C, bovine spongiform encephalopathy (BSE)/variant Creutzfeldt-Jakob disease (vCJD), Nipah virus, several viral hemorrhagic fevers and, most recently, severe acute respiratory syndrome (SARS) and avian influenza. The emergence of these diseases, and resurgence of old ones like tuberculosis and cholera, reflects various changes in human ecology: rural-to-urban migration resulting in high-density peri-urban slums; increasing long-distance mobility and trade; the social disruption of war and conflict; changes in personal behavior; and, increasingly, human-induced global changes, including widespread forest clearance and climate change. Political ignorance, denial and obduracy (as with HIV/AIDS) further compound the risks. The use and misuse of medical technology also pose risks, such as drug-resistant microbes and contaminated equipment or biological medicines. A better understanding of the evolving social dynamics of emerging infectious diseases ought to help us to anticipate and hopefully ameliorate current and future risks.

negative: Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data BACKGROUND: The International Health Regulations outline core requirements to ensure the detection of public health threats of international concern. Assessing the capacity of surveillance systems to detect these threats is crucial for evaluating a country’s ability to meet these requirements. METHODS AND FINDINGS: We propose a framework to evaluate the sensitivity and representativeness of hospital-based surveillance and apply it to severe neurological infectious diseases and fatal respiratory infectious diseases in Bangladesh. We identified cases in selected communities within surveillance hospital catchment areas using key informant and house-to-house surveys and ascertained where cases had sought care. We estimated the probability of surveillance detecting different sized outbreaks by distance from the surveillance hospital and compared characteristics of cases identified in the community and cases attending surveillance hospitals. We estimated that surveillance detected 26% (95% CI 18%–33%) of severe neurological disease cases and 18% (95% CI 16%–21%) of fatal respiratory disease cases residing at 10 km distance from a surveillance hospital. Detection probabilities decreased markedly with distance. The probability of detecting small outbreaks (three cases) dropped below 50% at distances greater than 26 km for severe neurological disease and at distances greater than 7 km for fatal respiratory disease. Characteristics of cases attending surveillance hospitals were largely representative of all cases; however, neurological disease cases aged <5 y or from the lowest socioeconomic group and fatal respiratory disease cases aged ≥60 y were underrepresented. Our estimates of outbreak detection rely on suspected cases that attend a surveillance hospital receiving laboratory confirmation of disease and being reported to the surveillance system. The extent to which this occurs will depend on disease characteristics (e.g., severity and symptom specificity) and surveillance resources. CONCLUSION: We present a new approach to evaluating the sensitivity and representativeness of hospital-based surveillance, making it possible to predict its ability to detect emerging threats.

negative: How Modelling Can Enhance the Analysis of Imperfect Epidemic Data Mathematical models play an increasingly important role in our understanding of the transmission and control of infectious diseases. Here, we present concrete examples illustrating how mathematical models, paired with rigorous statistical methods, are used to parse data of different levels of detail and breadth and estimate key epidemiological parameters (e.g., transmission and its determinants, severity, impact of interventions, drivers of epidemic dynamics) even when these parameters are not directly measurable, when data are limited, and when the epidemic process is only partially observed. Finally, we assess the hurdles to be taken to increase availability and applicability of these approaches in an effort to ultimately enhance their public health impact.

negative: Implications of social distancing in Brazil in the COVID-19 pandemic

negative: Integration of small world networks with multi-agent systems for simulating epidemic spatiotemporal transmission This study proposes an integrated model based on small world network (SWN) and multi-agent system (MAS) for simulating epidemic spatiotemporal transmission. In this model, MAS represents the process of spatiotemporal interactions among individuals, and SWN describes the social relation network among agents. The model is composed of agent attribute definitions, agent movement rules, neighborhoods, construction of social relation network among agents and state transition rules. The construction of social relation network and agent state transition rules is essential for implementing the proposed model. The decay effects of infection “memory”, distance and social relation between agents are introduced into the model, which are unavailable in traditional models. The proposed model is used to simulate the transmission process of flu in Guangzhou City based on the swarm software platform. The integration model has better performance than the traditional SEIR model and the pure MAS based epidemic model. This model has been applied to the simulation of the transmission of epidemics in real geographical environment. The simulation can provide useful information for the understanding, prediction and control of the transmission of epidemics.

negative: The impact of believing you have had COVID-19 on behaviour: Cross-sectional survey Objectives: To investigate whether people who think they have had COVID-19 are less likely to engage in social distancing measures compared with those who think they have not had COVID-19. Design: On-line cross-sectional survey. Setting: Data were collected between 20th and 22nd April. Participants: 6149 participants living in the UK aged 18 years or over. Main outcome measures: Perceived immunity to COVID-19, self-reported adherence to social distancing measures (going out for essential shopping, nonessential shopping, and meeting up with friends/family; total out-of-home activity), worry about COVID-19 and perceived risk of COVID-19 to oneself and people in the UK. Knowledge that cough and high temperature / fever are the main symptoms of COVID-19. Results: In this sample, 1493 people (24.3%) thought they had had COVID-19. Only 245 (4.0%) reported receiving a test result saying they had COVID-19. Reported test results were often incongruent with participants' belief that they had had COVID-19. People who believed that they had had COVID-19 were: more likely to agree that they had some immunity to COVID-19; less likely to report adhering to social distancing measures; less worried about COVID-19; and less likely to know that cough and high temperature / fever are two of the most common symptoms of COVID-19. Conclusions: The number of people in the UK who think they have already had COVID-19 is about twice the rate of current prevalence estimates. People who think that they have had COVID-19 may contribute to transmission of the virus through non-adherence to social distancing measures. Clear communications to this growing group are needed to explain why protective measures continue to be important and to encourage sustained adherence.

negative: Adapting protocols for the care of surgical patients during the COVID-19 pandemic

negative: Disease Detection or Public Opinion Reflection? Content Analysis of Tweets, Other Social Media, and Online Newspapers During the Measles Outbreak in the Netherlands in 2013 BACKGROUND: In May 2013, a measles outbreak began in the Netherlands among Orthodox Protestants who often refuse vaccination for religious reasons. OBJECTIVE: Our aim was to compare the number of messages expressed on Twitter and other social media during the measles outbreak with the number of online news articles and the number of reported measles cases to answer the question if and when social media reflect public opinion patterns versus disease patterns. METHODS: We analyzed measles-related tweets, other social media messages, and online newspaper articles over a 7-month period (April 15 to November 11, 2013) with regard to topic and sentiment. Thematic analysis was used to structure and analyze the topics. RESULTS: There was a stronger correlation between the weekly number of social media messages and the weekly number of online news articles (P<.001 for both tweets and other social media messages) than between the weekly number of social media messages and the weekly number of reported measles cases (P=.003 and P=.048 for tweets and other social media messages, respectively), especially after the summer break. All data sources showed 3 large peaks, possibly triggered by announcements about the measles outbreak by the Dutch National Institute for Public Health and the Environment and statements made by well-known politicians. Most messages informed the public about the measles outbreak (ie, about the number of measles cases) (93/165, 56.4%) followed by messages about preventive measures taken to control the measles spread (47/132, 35.6%). The leading opinion expressed was frustration regarding people who do not vaccinate because of religious reasons (42/88, 48%). CONCLUSIONS: The monitoring of online (social) media might be useful for improving communication policies aiming to preserve vaccination acceptability among the general public. Data extracted from online (social) media provide insight into the opinions that are at a certain moment salient among the public, which enables public health institutes to respond immediately and appropriately to those public concerns. More research is required to develop an automatic coding system that captures content and user’s characteristics that are most relevant to the diseases within the National Immunization Program and related public health events and can inform official responses.

negative: Distinct Viral Clades of SARS‐CoV‐2: Implications for Modeling of Viral Spread Distinct viral clades have a likely impact on COVID‐19 pathogenesis and spread. Sequence analysis from 2310 viral isolates from Nexstrain reveals that residue at 614 of the viral spike protein is changed from a putative ancestral aspartic acid (D) to a glycine (G) between two viral clades. The G strain is predominantly on the East Coast of the United States, and the D strain is predominantly on the West Coast. This mutation of the SARS‐CoV‐2 S protein spike is conserved in coronaviruses. Point mutations in a murine coronavirus spike protein can result in increased virulence through instability of the viral machinery and altered viral to cell membrane fusion. This observation may partially explain the discrepancy in predicted deaths from COVID‐19 between the East Coast and West Coast, and possibly explain that other factors aside from social distance, such as competition between two strains of differing virulence, may be at play. This article is protected by copyright. All rights reserved.

negative: Improving on legacy conferences by moving online Scientific conferences and meetings have an important role in research, but they also suffer from a number of disadvantages: in particular, they can have a massive carbon footprint, they are time-consuming, and the high costs involved in attending can exclude many potential participants. The COVID-19 pandemic has led to the cancellation of many conferences, forcing the scientific community to explore online alternatives. Here, we report on our experiences of organizing an online neuroscience conference, neuromatch, that attracted some 3000 participants and featured two days of talks, debates, panel discussions, and one-on-one meetings facilitated by a matching algorithm. By offering most of the benefits of traditional conferences, several clear advantages, and with fewer of the downsides, we feel that online conferences have the potential to replace many legacy conferences.

negative: Spatiotemporal diffusion of influenza A (H1N1): Starting point and risk factors Influenza constitutes a major challenge to world health authorities due to high transmissibility and the capacity to generate large epidemics. This study aimed to characterize the diffusion process of influenza A (H1N1) by identifying the starting point of the epidemic as well as climatic and sociodemographic factors associated with the occurrence and intensity of transmission of the disease. The study was carried out in the Brazilian state of Paraná, where H1N1 caused the largest impact. The units of spatial and temporal analysis were the municipality of residence of the cases and the epidemiological weeks of the year 2009, respectively. Under the Bayesian paradigm, parametric inference was performed through a two-part spatiotemporal model and the integrated nested Laplace approximation (INLA) algorithm. We identified the most likely starting points through the effective distance measure based on mobility networks. The proposed estimation methodology allowed for rapid and efficient implementation of the spatiotemporal model, and provided evidence of different patterns for chance of occurrence and risk of influenza throughout the epidemiological weeks. The results indicate the capital city of Curitiba as the probable starting point, and showed that the interventions that focus on municipalities with greater migration and density of people, especially those with higher Human Development Indexes (HDIs) and the presence of municipal air and road transport, could play an important role in mitigation of effects of future influenza pandemics on public health. These results provide important information on the process of introduction and spread of influenza, and could contribute to the identification of priority areas for surveillance as well as establishment of strategic measures for disease prevention and control. The proposed model also allows identification of epidemiological weeks with high chance of influenza occurrence, which can be used as a reference criterion for creating an immunization campaign schedule.

negative: Social Media Use During Social Distancing

negative: Genetic variability in the expression of the SARS-CoV-2 host cell entry factors across populations The entry of SARS-CoV-2 into host cells is dependent upon angiotensin-converting enzyme 2 (ACE2), which serves as a functional attachment receptor for the viral spike glycoprotein, and the serine protease TMPRSS2 which allows fusion of the viral and host cell membranes. We devised a quantitative measure to estimate genetic determinants of ACE2 and TMPRSS2 expression and applied this measure to >2,500 individuals. Our data show significant variability in genetic determinants of ACE2 and TMPRSS2 expression among individuals and between populations, and demonstrate a genetic predisposition for lower expression levels of both key viral entry genes in African populations. These data suggest that genetic factors might lead to lower susceptibility for SARS-CoV-2 infection in African populations and that host genetics might help explain inter-individual variability in disease susceptibility and severity of COVID-19.

negative: The Impact of Covid-19 on Community-Based Violence Interventions This paper examines the impact of Covid-19 on community-based violence interventions, especially hospital-based violence interventions and street outreach organizations. Guided by our work in Rochester, New York, we explore how the emergence of covid-19, and the subsequent social restrictions, have hampered the ability of community-based organizations to respond to violence. We also examine ways that community-based organizations can adapt to the challenges associated with Covid-19 and continue providing services to the community.

negative: RAN translation and frameshifting as translational challenges at simple repeats of human neurodegenerative disorders Repeat-associated disorders caused by expansions of short sequences have been classified as coding and noncoding and are thought to be caused by protein gain-of-function and RNA gain-of-function mechanisms, respectively. The boundary between such classifications has recently been blurred by the discovery of repeat-associated non-AUG (RAN) translation reported in spinocerebellar ataxia type 8, myotonic dystrophy type 1, fragile X tremor/ataxia syndrome and C9ORF72 amyotrophic lateral sclerosis and frontotemporal dementia. This noncanonical translation requires no AUG start codon and can initiate in multiple frames of CAG, CGG and GGGGCC repeats of the sense and antisense strands of disease-relevant transcripts. RNA structures formed by the repeats have been suggested as possible triggers; however, the precise mechanism of the translation initiation remains elusive. Templates containing expansions of microsatellites have also been shown to challenge translation elongation, as frameshifting has been recognized across CAG repeats in spinocerebellar ataxia type 3 and Huntington's disease. Determining the critical requirements for RAN translation and frameshifting is essential to decipher the mechanisms that govern these processes. The contribution of unusual translation products to pathogenesis needs to be better understood. In this review, we present current knowledge regarding RAN translation and frameshifting and discuss the proposed mechanisms of translational challenges imposed by simple repeat expansions.

negative: Noninvasive ventilation in acute respiratory failure due to H1N1 influenza: A word of caution

negative: Interplay of global multi-scale human mobility, social distancing, government interventions, and COVID-19 dynamics This work quantifies the impact of interventions to curtail mobility and social interactions in order to control the COVID-19 pandemic. We analyze the change in world-wide mobility at multiple spatio-temporal resolutions -- county, state, country -- using an anonymized aggregate mobility map that captures population flows between geographic cells of size 5 km2. We show that human mobility underwent an abrupt and significant change, partly in response to the interventions, resulting in 87% reduction of international travel and up to 75% reduction of domestic travel. Taking two very different countries sampled from the global spectrum, we observe a maximum reduction of 42% in mobility across different states of the United States (US), and a 68% reduction across the states of India between late March and late April. Since then, there has been an uptick in flows, with the US seeing 53% increase and India up to 38% increase with respect to flows seen during the lockdown. As we overlay this global map with epidemic incidence curves and dates of government interventions, we observe that as case counts rose, mobility fell -- often before stay-at-home orders were issued. Further, in order to understand mixing within a region, we propose a new metric to quantify the effect of social distancing on the basis of mobility. We find that population mixing has decreased considerably as the pandemic has progressed and are able to measure this effect across the world. Finally, we carry out a counterfactual analysis of delaying the lockdown and show that a one week delay would have doubled the reported number of cases in the US and India. To our knowledge, this work is the first to model in near real-time, the interplay of human mobility, epidemic dynamics and public policies across multiple spatial resolutions and at a global scale.

negative: COVID-19: Active measures to support community-dwelling older adults

negative: Slum Health: Arresting COVID-19 and Improving Well-Being in Urban Informal Settlements The informal settlements of the Global South are the least prepared for the pandemic of COVID-19 since basic needs such as water, toilets, sewers, drainage, waste collection, and secure and adequate housing are already in short supply or non-existent. Further, space constraints, violence, and overcrowding in slums make physical distancing and self-quarantine impractical, and the rapid spread of an infection highly likely. Residents of informal settlements are also economically vulnerable during any COVID-19 responses. Any responses to COVID-19 that do not recognize these realities will further jeopardize the survival of large segments of the urban population globally. Most top-down strategies to arrest an infectious disease will likely ignore the often-robust social groups and knowledge that already exist in many slums. Here, we offer a set of practice and policy suggestions that aim to (1) dampen the spread of COVID-19 based on the latest available science, (2) improve the likelihood of medical care for the urban poor whether or not they get infected, and (3) provide economic, social, and physical improvements and protections to the urban poor, including migrants, slum communities, and their residents, that can improve their long-term well-being. Immediate measures to protect residents of urban informal settlements, the homeless, those living in precarious settlements, and the entire population from COVID-19 include the following: (1) institute informal settlements/slum emergency planning committees in every urban informal settlement; (2) apply an immediate moratorium on evictions; (3) provide an immediate guarantee of payments to the poor; (4) immediately train and deploy community health workers; (5) immediately meet Sphere Humanitarian standards for water, sanitation, and hygiene; (6) provide immediate food assistance; (7) develop and implement a solid waste collection strategy; and (8) implement immediately a plan for mobility and health care. Lessons have been learned from earlier pandemics such as HIV and epidemics such as Ebola. They can be applied here. At the same time, the opportunity exists for public health, public administration, international aid, NGOs, and community groups to innovate beyond disaster response and move toward long-term plans.

negative: Socio-environmental exposures and health outcomes among persons with sickle cell disease There is much variability in the expression of sickle cell disease (SCD) and recent works suggest that environmental and social factors may also influence this variability. This paper aims to use geographic information systems technology to examine the association between socio-environmental exposures and health outcomes in all persons who have attended or currently attend the Sickle Cell Unit in Jamaica. Rural patients presented for clinical care at older ages and had less annual visits to clinic. Persons travelled relatively long distances to seek SCD care and those travelling longer had less health maintenance visits. Urban patients had a higher prevalence of significant pain crises (69.4% vs. 55.8%, p value<0.001) and respiratory events (21.2% vs. 14%, p value<0.001). Prevalence of leg ulcers did not vary between rural and urban patients but was higher in males than in females. Females also had lower odds of having respiratory events but there was no sex difference in history of painful crises. Persons with more severe genotypes lived in higher poverty and travelled longer for healthcare services. Persons in areas with higher annual rainfall, higher mean temperatures and living farther from factories had less painful crises and respiratory events. The paper highlights a need for better access to healthcare services for Jamaicans with SCD especially in rural areas of the island. It also reports interesting associations between environmental climatic exposures and health outcomes.

negative: Concerns for activated breathing control (ABC) with breast cancer in the era of COVID-19: Maximizing infection control while minimizing heart dose

negative: SOCRATES: an online tool leveraging a social contact data sharing initiative to assess mitigation strategies for COVID-19 OBJECTIVE: Establishing a social contact data sharing initiative and an interactive tool to assess mitigation strategies for COVID-19. RESULTS: We organized data sharing of published social contact surveys via online repositories and formatting guidelines. We analyzed this social contact data in terms of weighted social contact matrices, next generation matrices, relative incidence and R[Formula: see text]. We incorporated location-specific physical distancing measures (e.g. school closure or at work) and capture their effect on transmission dynamics. All methods have been implemented in an online application based on R Shiny and applied to COVID-19 with age-specific susceptibility and infectiousness. Using our online tool with the available social contact data, we illustrate that physical distancing could have a considerable impact on reducing transmission for COVID-19. The effect itself depends on assumptions made about disease-specific characteristics and the choice of intervention(s).

negative: Dynamics of COVID-19 under social distancing measures are driven by transmission network structure In the absence of pharmaceutical interventions, social distancing is being used worldwide to curb the spread of COVID-19. The impact of these measures has been inconsistent, with some regions rapidly nearing disease elimination and others seeing delayed peaks or nearly flat epidemic curves. Here we build a stochastic epidemic model to examine the effects of COVID-19 clinical progression and transmission network structure on the outcomes of social distancing interventions. We find that the strength of within-household transmission is a critical determinant of success, governing the timing and size of the epidemic peak, the rate of decline, individual risks of infection, and the success of partial relaxation measures. The structure of residual external connections, driven by workforce participation and essential businesses, interacts to determine outcomes. These findings can improve future predictions of the timescale and efficacy of interventions needed to control similar outbreaks, and highlight the need for better quantification and control of household transmission.

negative: A Smartphone enabled Approach to Manage COVID-19 Lockdown and Economic Crisis The emergence of novel COVID-19 causing an overload in health system and high mortality rate. The key priority is to contain the epidemic and prevent the infection rate. In this context, many countries are now in some degree of lockdown to ensure extreme social distancing of entire population and hence slowing down the epidemic spread. Further, authorities use case quarantine strategy and manual second/third contact-tracing to contain the COVID-19 disease. However, manual contact tracing is time consuming and labor-intensive task which tremendously overload public health systems. In this paper, we developed a smartphone-based approach to automatically and widely trace the contacts for confirmed COVID-19 cases. Particularly, contact-tracing approach creates a list of individuals in the vicinity and notifying contacts or officials of confirmed COVID-19 cases. This approach is not only providing awareness to individuals they are in the proximity to the infected area, but also tracks the incidental contacts that the COVID-19 carrier might not recall. Thereafter, we developed a dashboard to provide a plan for government officials on how lockdown/mass quarantine can be safely lifted, and hence tackling the economic crisis. The dashboard used to predict the level of lockdown area based on collected positions and distance measurements of the registered users in the vicinity. The prediction model uses K-means algorithm as an unsupervised machine learning technique for lockdown management.

negative: Time is of the essence: impact of delays on effectiveness of contact tracing for COVID-19 Summary Background With confirmed cases of COVID-19 declining in many countries, lockdown measures are gradually being lifted. However, even if most social distancing measures are continued, other public health measures will be needed to control the epidemic. Contact tracing either via conventional methods or via mobile app technology is central to control strategies during de-escalation of social distancing. It is therefore essential to identify key factors for a contact tracing strategy (CTS) to be successful. Methods We evaluated the impact of timeliness and completeness in various steps of a CTS using a stochastic mathematical model with explicit time delays between time of infection, symptom onset, diagnosis by testing, and isolation. The model also includes tracing of close contacts (e.g. household members) and casual contacts with different delays and coverages. We computed effective reproduction numbers of a CTS (Rcts) for a population with social distancing measures and various scenarios for isolation of index cases and tracing and quarantine of its contacts. Findings In the best-case scenario (testing and tracing delays of 0 days and tracing coverage of 100%) the effective reproduction number will be reduced with 50% from 1.2 (with social distancing only) to 0.6 (Rcts) by contact tracing. A testing delay of 3 days requires tracing delay or coverage to be at most 1 day or at least 80% to keep Rcts below 1, with the Rcts reduction being 15% and 17%, respectively. With a testing delay of 4 days, even the most efficient CTS cannot reach Rcts values below 1. The effect of minimizing tracing delay (e.g., with app-based technology) declines with declining coverage of app use, but app-based tracing remains more effective than conventional contact tracing even with 20% coverage. The proportion of transmissions per index case that can be prevented depending on testing and tracing delay and isolation of index cases ranges from above 80% in the best-case scenario (testing and tracing delays of 0 days) to 40% and 17% with testing delays of 3 and 5 days, respectively. Interpretation Minimizing testing delay is of key importance for the effectiveness of CTS. Optimizing testing and tracing coverage and minimizing tracing delays, for instance with app-based technology further enhances effectiveness of CTS, with a potential to prevent up to 80% of all transmissions. The process of conventional contact tracing should be reviewed and streamlined, while mobile app technology may offer a tool for gaining speed in the process.

negative: Causal empirical estimates suggest COVID-19 transmission rates are highly seasonal Nearly every country is now combating the 2019 novel coronavirus (COVID-19). It has been hypothesized that if COVID-19 exhibits seasonality, changing temperatures in the coming months will shift transmission patterns around the world. Such projections, however, require an estimate of the relationship between COVID-19 and temperature at a global scale, and one that isolates the role of temperature from confounding factors, such as public health capacity. This paper provides the first plausibly causal estimates of the relationship between COVID-19 transmission and local temperature using a global sample comprising of 166,686 confirmed new COVID-19 cases from 134 countries from January 22, 2020 to March 15, 2020. We find robust statistical evidence that a 1°C increase in local temperature reduces transmission by 13% [-21%, -4%, 95%CI]. In contrast, we do not find that specific humidity or precipitation influence transmission. Our statistical approach separates effects of climate variation on COVID-19 transmission from other potentially correlated factors, such as differences in public health responses across countries and heterogeneous population densities. Using constructions of expected seasonal temperatures, we project that changing temperatures between March 2020 and July 2020 will cause COVID-19 transmission to fall by 43% on average for Northern Hemisphere countries and to rise by 71% on average for Southern Hemisphere countries. However, these patterns reverse as the boreal winter approaches, with seasonal temperatures in January 2021 increasing average COVID-19 transmission by 59% relative to March 2020 in northern countries and lowering transmission by 2% in southern countries. These findings suggest that Southern Hemisphere countries should expect greater transmission in the coming months. Moreover, Northern Hemisphere countries face a crucial window of opportunity: if contagion-containing policy interventions can dramatically reduce COVID-19 cases with the aid of the approaching warmer months, it may be possible to avoid a second wave of COVID-19 next winter.

negative: Target Virus or Target Ourselves for COVID-19 Drugs Discovery?-Lessons learned from anti-influenzas virus therapies Abstract The COVID-19 pandemic, after it was reported in December 2019, is a highly contagious and now spreading to over 190 countries, causing a severe public health burden. Currently, there is no vaccine or specific drug to treat COVID-19, which is caused by a novel coronavirus, SARS-2-CoV. For this emergency, the FDA has approved Remdesivir and Hydroxychloroquine for treatment of COVID-19 as Emergency Use Authorization. However, even after this pandemic, COVID-19 may still have a chance to come back. Therefore, we need to come out with new strategies for drug discovery for combating COVID-19 in the future.

negative: Viral models of multiple sclerosis: Neurodegeneration and demyelination in mice infected with Theiler's virus Abstract Multiple sclerosis (MS) is a complex inflammatory disease of unknown etiology that affects the central nervous system (CNS) white matter, and for which no effective cure exists. Indeed, whether the primary event in MS pathology affects myelin or axons of the CNS remains unclear. Animal models are necessary to identify the immunopathological mechanisms involved in MS and to develop novel therapeutic and reparative approaches. Specifically, viral models of chronic demyelination and axonal damage have been used to study the contribution of viruses in human MS, and they have led to important breakthroughs in our understanding of MS pathology. The Theiler's murine encephalomyelitis virus (TMEV) model is one of the most commonly used MS models, although other viral models are also used, including neurotropic strains of mouse hepatitis virus (MHV) that induce chronic inflammatory demyelination with similar histological features to those observed in MS. This review will discuss the immunopathological mechanisms involved in TMEV-induced demyelinating disease (TMEV-IDD). The TMEV model reproduces a chronic progressive disease due to the persistence of the virus for the entire lifespan in susceptible mice. The evolution and significance of the axonal damage and neuroinflammation, the importance of epitope spread from viral to myelin epitopes, the presence of abortive remyelination and the existence of a brain pathology in addition to the classical spinal cord demyelination, are some of the findings that will be discussed in the context of this TMEV-IDD model. Despite their limitations, viral models remain an important tool to study the etiology of MS, and to understand the clinical and pathological variability associated with this disease.

negative: Impact of COVID-19 on transportation in Lagos, Nigeria Abstract The growing number of studies on the impact of COVID-19 is often discussed in the context of developed countries, highlighting a gap in the understanding of how the pandemic is impacting developing countries. This theoretical commentary focuses on the present and long-term impact of COVID-19 on transportation in Lagos State, Nigeria. The paper recognises the effect on transportation in emerging economies, where lockdowns and restrictions on movement may be ineffective, a state with high population density, poor transportation infrastructure and a large informal economy. Adopting the ‘avoid-shift-improve’ framework, this paper presents practical implications for public and private sector policymakers, as they navigate this precarious time and chart a new path for individuals and Nigeria.

negative: Efficacy and safety of Chou-Ling-Dan granules in the treatment of seasonal influenza via combining Western and traditional Chinese medicine: protocol for a multicentre, randomised controlled clinical trial INTRODUCTION: Chou-Ling-Dan (CLD) (Laggerapterodonta) granules are an ethnic herbal medicine from Yunnan province of China. CLD granules have been used for the treatment of inflammatory conditions and feverish diseases in China, including seasonal influenza, but few evidence-based medicine (EBM) clinical studies have been conducted to assess its efficacy and safety in the treatment of influenza. Here, we performed an EBM clinical trial combining Western Chinese medicine and traditional Chinese medicine (TCM) evaluation systems to evaluate the efficacy and safety of CLD granules in the treatment of seasonal influenza. METHODS AND ANALYSIS: The study is designed as a multicentre, randomised, double-blinded, double-simulation, oseltamivir-controlled and placebo-controlled, parallel-design clinical trial. Eligible subjects (n=318) will be allocated after satisfying the criteria (Western medicine). Subjects will be randomised to receive CLD granules, oseltamivir, or a placebo for 5 days of treatment and with follow-up after treatment to record symptoms and signs and to collect pharyngeal/throat swabs and serum samples for detecting the virus and antibodies. At the same time, the syndrome differentiation criteria of TCM, such as tongue body, furred tongue and type of pulse, will be recorded as determined by doctors of both Western and Chinese medicine. Participants will be instructed to comply with the protocol and to keep a daily record of symptoms. The primary and secondary outcomes and safety indicators will be used to evaluate the efficacy and safety of CLD granules in the treatment of seasonal influenza based on both Western Chinese medicine and TCM evaluation systems. ETHICS AND DISSEMINATION: The CLD granules clinical trial will be conducted in accordance with the Declaration of Helsinki and Good Clinical Practice and has been approved by the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University. All participants must provide written informed consent. The results obtained will be disseminated at international medical conferences and in peer-reviewed publications. TRIAL REGISTRATION NUMBER: NCT02662426; Pre-results.

negative: The Visual Social Distancing Problem One of the main and most effective measures to contain the recent viral outbreak is the maintenance of the so-called Social Distancing (SD). To comply with this constraint, workplaces, public institutions, transports and schools will likely adopt restrictions over the minimum inter-personal distance between people. Given this actual scenario, it is crucial to massively measure the compliance to such physical constraint in our life, in order to figure out the reasons of the possible breaks of such distance limitations, and understand if this implies a possible threat given the scene context. All of this, complying with privacy policies and making the measurement acceptable. To this end, we introduce the Visual Social Distancing (VSD) problem, defined as the automatic estimation of the inter-personal distance from an image, and the characterization of the related people aggregations. VSD is pivotal for a non-invasive analysis to whether people comply with the SD restriction, and to provide statistics about the level of safety of specific areas whenever this constraint is violated. We then discuss how VSD relates with previous literature in Social Signal Processing and indicate which existing Computer Vision methods can be used to manage such problem. We conclude with future challenges related to the effectiveness of VSD systems, ethical implications and future application scenarios.

negative: Thrombocytopenia is associated with severe coronavirus disease 2019 (COVID-19) infections: A meta-analysis BACKGROUND: Coronavirus disease 2019 (COVID-19) is a novel infectious disease with lack of established laboratory markers available to evaluate illness severity. In this study, we investigate whether platelet count could differentiate between COVID-19 patients with or without severe disease. Additionally, we evaluate if thrombocytopenia is associated with severe COVID-19. METHODS: An electronic search in Medline, Scopus and Web of Science was performed to identify studies reporting data on platelet count in COVID-19 patients. A meta-analysis was performed, with calculation of weighted mean difference (WMD) of platelet number in COVID-19 patients with or without severe disease and odds ratio (OR) of thrombocytopenia for severe form of COVID-19. RESULTS: Nine studies with 1779 COVID-19 patients, 399 (22.4%) with severe disease, were included in the meta-analysis. The pooled analysis revealed that platelet count was significantly lower in patients with more severe COVID-19 (WMD -31×10(9)/L; 95% CI, from -35 to -29×10(9)/L). A subgroup analysis comparing patients by survival, found an even lower platelet count was observed with mortality (WMD, -48×10(9)/L; 95% CI, -57 to -39×10(9)/L. In the four studies (n=1427) which reported data on rate of thrombocytopenia, a low platelet count was associated with over fivefold enhanced risk of severe COVID-19 (OR, 5.1; 95% CI, 1.8-14.6). CONCLUSIONS: Low platelet count is associated with increased risk of severe disease and mortality in patients with COVID-19, and thus should serve as clinical indicator of worsening illness during hospitalization.

negative: A Comprehensive Literature Review on the Clinical Presentation, and Management of the Pandemic Coronavirus Disease 2019 (COVID-19) Coronavirus disease 2019 (COVID-19) is a declared global pandemic. There are multiple parameters of the clinical course and management of the COVID-19 that need optimization. A hindrance to this development is the vast amount of misinformation present due to scarcely sourced manuscript preprints and social media. This literature review aims to presents accredited and the most current studies pertaining to the basic sciences of SARS-CoV-2, clinical presentation and disease course of COVID-19, public health interventions, and current epidemiological developments. The review on basic sciences aims to clarify the jargon in virology, describe the virion structure of SARS-CoV-2 and present pertinent details relevant to clinical practice. Another component discussed is the brief history on the series of experiments used to explore the origins and evolution of the phylogeny of the viral genome of SARS-CoV-2. Additionally, the clinical and epidemiological differences between COVID-19 and other infections causing outbreaks (SARS, MERS, H1N1) are elucidated. Emphasis is placed on evidence-based medicine to evaluate the frequency of presentation of various symptoms to create a stratification system of the most important epidemiological risk factors for COVID-19. These can be used to triage and expedite risk assessment. Furthermore, the limitations and statistical strength of the diagnostic tools currently in clinical practice are evaluated. Criteria on rapid screening, discharge from hospital and discontinuation of self-quarantine are clarified. Epidemiological factors influencing the rapid rate of spread of the SARS-CoV-2 virus are described. Accurate information pertinent to improving prevention strategies is also discussed. The penultimate portion of the review aims to explain the involvement of micronutrients such as vitamin C and vitamin D in COVID19 treatment and prophylaxis. Furthermore, the biochemistry of the major candidates for novel therapies is briefly reviewed and a summary of their current status in the clinical trials is presented. Lastly, the current scientific data and status of governing bodies such as the Center of Disease Control (CDC) and the WHO on the usage of controversial therapies such as angiotensin-converting enzyme (ACE) inhibitors, nonsteroidal anti-inflammatory drugs (NSAIDs) (Ibuprofen), and corticosteroids usage in COVID-19 are discussed. The composite collection of accredited studies on each of these subtopics of COVID-19 within this review will enable clarification and focus on the current status and direction in the planning of the management of this global pandemic.

negative: Predicting support for non-pharmaceutical interventions during infectious outbreaks: a four region analysis. Non-pharmaceutical interventions (NPIs) are an important public health tool for responding to infectious disease outbreaks, including pandemics. However, little is known about the individual characteristics associated with support for NPIs, or whether they are consistent across regions. This study draws on survey data from four regions--Hong Kong, Singapore, Taiwan, and the United States--collected following the Severe Acute Respiratory Syndrome (SARS) outbreak of 2002-03, and employs regression techniques to estimate predictors of NPI support. It finds that characteristics associated with NPI support vary widely by region, possibly because of cultural variation and prior experience, and that minority groups tend to be less supportive of NPIs when arrest is the consequence of noncompliance. Prior experience of face-mask usage also results in increased support for future usage, as well as other NPIs. Policymakers should be attentive to local preferences and to the application of compulsory interventions. It is speculated here that some public health interventions may serve as 'gateway' exposures to future public health interventions.

negative: Public activities preceding the onset of acute respiratory infection syndromes in adults in England - implications for the use of social distancing to control pandemic respiratory infections. Background: Social distancing measures may reduce the spread of emerging respiratory infections however, there is little empirical data on how exposure to crowded places affects risk of acute respiratory infection. Methods: We used a case-crossover design nested in a community cohort to compare self-reported measures of activities during the week before infection onset and baseline periods. The design eliminates the effect of non-time-varying confounders. Time-varying confounders were addressed by exclusion of illnesses around the Christmas period and seasonal adjustment. Results: 626 participants had paired data from the week before 1005 illnesses and the week before baseline. Each additional day of undertaking the following activities in the prior week was associated with illness onset: Spending more than five minutes in a room with someone (other than a household member) who has a cold (Seasonally adjusted OR 1·15, p=0·003); use of underground trains (1·31, p=0·036); use of supermarkets (1·32, p<0·001); attending a theatre, cinema or concert (1·26, p=0·032); eating out at a café, restaurant or canteen (1·25, p=0·003); and attending parties (1·47, p<0·001). Undertaking the following activities at least once in the previous week was associated with illness onset: using a bus, (aOR 1.48, p=0.049), shopping at small shops (1.9, p<0.002) attending a place of worship (1.81, p=0.005). Conclusions: Exposure to potentially crowded places, public transport and to individuals with a cold increases risk of acquiring circulating acute respiratory infections. This suggests social distancing measures can have an important impact on slowing transmission of emerging respiratory infections.

negative: Trend analysis of the COVID-19 pandemic in China and the rest of the world The recent epidemic of Coronavirus (COVID-19) that started in China has already been "exported" to more than 140 countries in all the continents, evolving in most of them by local spreading. In this contribution we analyze the trends of the cases reported in all the Chinese provinces, as well as in some countries that, until March 15th, 2020, have more than 500 cases reported. Notably and differently from other epidemics, the provinces did not show an exponential phase. The data available at the Johns Hopkins University site seem to fit well an algebraic sub-exponential growing behavior as was pointed out recently. All the provinces show a clear and consistent pattern of slowing down with growing exponent going nearly zero, so it can be said that the epidemic was contained in China. On the other side, the more recent spread in countries like, Italy, Iran, and Spain show a clear exponential growth, as well as other European countries. Even more recently, US -which was one of the first countries to have an individual infected outside China (Jan 21st, 2020)- seems to follow the same path. We calculate the exponential growth of the most affected countries, showing the evolution along time after the first local case. We identify clearly different patterns in the analyzed data and we give interpretations and possible explanations for them. The analysis and conclusions of our study can help countries that, after importing some cases, are not yet in the local spreading phase, or have just started

negative: Chapter 24 Wastewater Treatment and Biosolids Reuse Publisher Summary The primary goal of wastewater treatment is the removal and degradation of organic matter under controlled conditions. This chapter describes the nature and modern treatment of waste water, land applications of waste water, and methods of land applications of biosolids and animal wastes. The amount of organic matter in domestic wastes determines the degree of required biological treatment. Various tests are used to assess the amount of organic matter: biochemical oxygen demand (BOD), chemical oxygen demand (COD), and total organic carbon (TOC). The complete sewage treatment comprises three major steps: primary, secondary, and tertiary treatment. Tertiary treatment processes involving physicochemical processes can be effective in reducing the concentration of pathogens. The treated domestic wastewater may be disposed of via land application for crop irrigation or as a means of additional treatment and disposal through the three basic methods that include low-rate irrigation, overland flow, and high-rate infiltration.

negative: Seeding COVID-19 across sub-Saharan Africa: an analysis of reported importation events across 40 countries Background: The first case of COVID-19 in sub-Saharan Africa (SSA) was reported by Nigeria on February 27, 2020. While case counts in the entire region remain considerably less than those being reported by individual countries in Europe, Asia, and the Americas, SSA countries remain vulnerable to significant COVID morbidity and mortality due to systemic healthcare weaknesses, less financial resources and infrastructure to address the new crisis, and untreated comorbidities. Variation in preparedness and response capacity as well as in data availability has raised concerns about undetected transmission events. Methods: Confirmed cases reported by SSA countries were line-listed to capture epidemiological details related to early transmission events into and within countries. Data were retrieved from publicly available sources, including institutional websites, situation reports, press releases, and social media accounts, with supplementary details obtained from news articles. A data availability score was calculated for each imported case in terms of how many indicators (sex, age, travel history, date of arrival in country, reporting date of confirmation, and how detected) could be identified. We assessed the relationship between time to first importation and overall Global Health Security Index (GHSI) using Cox regression. K-means clustering grouped countries according to healthcare capacity and health and demographic risk factors. Results: A total of 2417 confirmed cases of COVID-19 were reported by 40 countries in sub-Saharan Africa during the 30 days after the first known introduction to the region. Out of the 876 cases for which information was publicly available, 677 (77.3%) were considered importation events. At the regional level, imported cases tended to be male (67.3%), were a median 43.0 years old (Range: 6 weeks - 88 years), and most frequently had recent travel history from Europe (43.3%). The median time to reporting an introduction was 19 days; a country's time to report its first importation was not related to GHSI. Mean data availability scores were lowest for countries that had, on average, the highest case fatality rates, lowest healthcare capacity, and highest probability of premature death due to non-communicable diseases. Conclusion: Countries with systemic, demographic, and pre-existing health vulnerabilities to severe COVID-related morbidity and mortality are less likely to report any cases or are reporting with limited public availability of information. Reporting of information on COVID detection and response efforts, as well as on trends in non-COVID illness and care-seeking behavior, is critical to assessing direct and indirect consequences and capacity needs in resource-constrained settings. Such assessments aid in the ability to make data-driven decisions about interventions, country priorities, and risk assessment.

negative: Conséquences psychopathologiques du confinement Abstract The psychological effects of isolation have already been described in the literature (polar expeditions, submarines, prison). Nevertheless, the scale of confinement implemented during the COVID-19 pandemic is unprecedented. In addition to reviewing the published studies, we need to anticipate the psychological problems that could arise during or at a distance from confinement. We have gone beyond the COVID-19 literature in order to examine the implications of the known consequences of confinement, like boredom, social isolation, stress, or sleep deprivation. Anxiety, post-traumatic stress disorder, depression, suicidal or addictive behaviours, domestic violence are described effects of confinement, but the mechanisms of emergence of these disorders and their interrelationships remain to be studied. For example, what are the mechanisms of emergence of post-traumatic stress disorders in the context of confinement? We also remind the reader of points of vigilance to be kept in mind with regard to eating disorders and hallucinations. Hallucinations are curiously ignored in the literature on confinement, whereas a vast literature links social isolation and hallucinations. As with domestic violence, we need to look for these symptoms in order to enable management. Due to the broad psychopathological consequences, we have to look for these various symptoms to manage them. We quickly summarize the diagnostic and therapeutic approaches already in place, such as telemedicine, which is undergoing rapid development during the COVID-19 crisis.

negative: Can mathematical modelling solve the current Covid-19 crisis? Since COVID-19 transmission started in late January, mathematical modelling has been at the forefront of shaping the decisions around different non-pharmaceutical interventions to confine its’ spread in the UK and worldwide. This Editorial discusses the importance of modelling in understanding Covid-19 spread, highlights different modelling approaches and suggests that while modelling is important, no one model can give all the answers.

negative: Key factors affecting healthcare professionals to adopt knowledge management: The case of infection control departments of Taiwanese hospitals Abstract Facing new infectious diseases that are result of continuous mutation of virus and bacteria and ever advancing communication and medical technologies, infection control professionals (ICPs) in the healthcare industry must be able to obtain instantly the needed knowledge in order to increase efficiency and effectiveness in their practice. The purpose of this study is, after an exhaustive literature review and necessary interviews with specialists in this field, to propose a research framework that explores the factors that affect the ICPs’ willingness to adopt knowledge management (KM) into their tasks and to validate the usefulness of this research framework through a survey study. The research framework includes four constructs that affect infection control professionals’ decision and willingness to introduce and to adopt infection control KM, and they are namely: hospital characteristics, infection control department, external environment, and project planning. The study conducted a survey among ICPs from 425 hospitals in Taiwan. A total of 227 valid questionnaire responses were returned from the ICPs from 90 hospitals. Among these responses, 55.00% are from medical centers and 47.83% are from regional hospitals. After analyzing the responses through the discriminant analysis method, the study found that “Hospital Resource Support,” “Colleagues’ Attitude,” and “Users’ Participation” are the three factors that significantly impact the professionals’ willingness for adopting KM in infection control departments. This study not only provides the healthcare industry an understanding about introduction and impact of KM, which can assist in their decision making, but also emphasizes the importance of use of actual data in the study of research framework for introduction of KM in healthcare industry. Therefore, this study presents important results in both practical and academic aspects.

negative: Why is it difficult to accurately predict the COVID-19 epidemic? Since the COVID-19 outbreak in Wuhan City in December of 2019, numerous model predictions on the COVID-19 epidemics in Wuhan and other parts of China have been reported. These model predictions have shown a wide range of variations. In our study, we demonstrate that nonidentifiability in model calibrations using the confirmed-case data is the main reason for such wide variations. Using the Akaike Information Criterion (AIC) for model selection, we show that an SIR model performs much better than an SEIR model in representing the information contained in the confirmed-case data. This indicates that predictions using more complex models may not be more reliable compared to using a simpler model. We present our model predictions for the COVID-19 epidemic in Wuhan after the lockdown and quarantine of the city on January 23, 2020. We also report our results of modeling the impacts of the strict quarantine measures undertaken in the city after February 7 on the time course of the epidemic, and modeling the potential of a second outbreak after the return-to-work in the city.

negative: Containing the Spread of Coronavirus Disease 2019 (COVID-19): Meteorological Factors and Control Strategies The novel coronavirus disease 2019 (COVID-19) has spread globally and the meteorological factors vary greatly across the world. Understanding the effect of meteorological factors and control strategies on COVID-19 transmission is critical to contain the epidemic. Using individual-level data in mainland China, Hong Kong, and Singapore, and the number of confirmed cases in other regions, we explore the effect of temperature, relative humidity, and control measures on the spread of COVID-19. We found that high temperature mitigates the transmission of the disease. High relative humidity promotes COVID-19 transmission when temperature is low, but tends to reduce transmission when temperature is high. Implementing classical control measures can dramatically slow the spread of the disease. However, due to the occurrence of pre-symptomatic infections, the effect of the measures to shorten onset-to-isolation time is markedly reduced and the importance of contact tracing and quarantine and social distancing increases. The analytic results also highlight the importance of early intervention to contain the spread of COVID-19.

negative: 2019-novel Coronavirus severe adult respiratory distress syndrome in two cases in Italy: An uncommon radiological presentation Abstract Introduction Several recent case reports have described common early chest imaging findings of lung pathology caused by 2019 novel Coronavirus (SARS-COV2) which appear to be similar to those seen previously in SARS-CoV and MERS-CoV infected patients. Objective We present some remarkable imaging findings of the first two patients identified in Italy with COVID-19 infection travelling from Wuhan, China. The follow-up with chest X-Rays and CT scans was also included, showing a progressive adult respiratory distress syndrome (ARDS). Results Moderate to severe progression of the lung infiltrates, with increasing percentage of high-density infiltrates sustained by a bilateral and multi-segmental extension of lung opacities, were seen. During the follow-up, apart from pleural effusions, a tubular and enlarged appearance of pulmonary vessels with a sudden caliber reduction was seen, mainly found in the dichotomic tracts, where the center of a new insurgent pulmonary lesion was seen. It could be an early alert radiological sign to predict initial lung deterioration. Another uncommon element was the presence of mediastinal lymphadenopathy with short-axis oval nodes. Conclusions Although only two patients have been studied, these findings are consistent with the radiological pattern described in literature. Finally, the pulmonary vessels enlargement in areas where new lung infiltrates develop in the follow-up CT scan, could describe an early predictor radiological sign of lung impairment.

negative: ISNI 2010 Abstracts: Tuesday October 26(th), 2010 10th Course of the European School of Neuroimmunology

negative: Social distancing with the Optimal Steps Model With the Covid-19 pandemic an urgent need to simulate social distancing arises. The Optimal Steps Model (OSM) is a pedestrian locomotion model that operationalizes an individual's need for personal space. We present new parameter values for personal space in the Optimal Steps Model to simulate social distancing in the pedestrian dynamics simulator Vadere. Our approach is pragmatic. We consider two use cases: in the first we demand that a set social distance must never be violated. In the second the social distance must be kept only on average. For each use case we conduct simulation studies in a typical bottleneck scenario and measure contact times, that is, violations of the social distance rule. We derive rules of thumb for suitable parameter choices in dependency of the desired social distance. We test the rules of thumb for the social distances 1.5m and 2.0m and observe that the new parameter values indeed lead to the desired social distancing. Thus, the rules of thumb will quickly enable Vadere users to conduct their own studies without understanding the intricacies of the OSM implementation and without extensive parameter adjustment.

negative: Mental Health, Risk Factors, and Social Media Use During the COVID-19 Epidemic and Cordon Sanitaire Among the Community and Health Professionals in Wuhan, China: Cross-Sectional Survey BACKGROUND: The mental health consequences of the coronavirus disease (COVID-19) pandemic, community-wide interventions, and social media use during a pandemic are unclear. The first and most draconian interventions have been implemented in Wuhan, China, and these countermeasures have been increasingly deployed by countries around the world. OBJECTIVE: The aim of this study was to examine risk factors, including the use of social media, for probable anxiety and depression in the community and among health professionals in the epicenter, Wuhan, China. METHODS: We conducted an online survey via WeChat, the most widely used social media platform in China, which was administered to 1577 community-based adults and 214 health professionals in Wuhan. Probable anxiety and probable depression were assessed by the validated Generalized Anxiety Disorder-2 (cutoff ≥3) and Patient Health Questionnaire-2 (cutoff ≥3), respectively. A multivariable logistic regression analysis was used to examine factors associated with probable anxiety and probable depression. RESULTS: Of the 1577 community-based adults, about one-fifth of respondents reported probable anxiety (n=376, 23.84%, 95% CI 21.8-26.0) and probable depression (n=303, 19.21%, 95% CI 17.3-21.2). Similarly, of the 214 health professionals, about one-fifth of surveyed health professionals reported probable anxiety (n=47, 22.0%, 95% CI 16.6-28.1) or probable depression (n=41, 19.2%, 95% CI 14.1-25.1). Around one-third of community-based adults and health professionals spent ≥2 hours daily on COVID-19 news via social media. Close contact with individuals with COVID-19 and spending ≥2 hours daily on COVID-19 news via social media were associated with probable anxiety and depression in community-based adults. Social support was associated with less probable anxiety and depression in both health professionals and community-based adults. CONCLUSIONS: The internet could be harnessed for telemedicine and restoring daily routines, yet caution is warranted toward spending excessive time searching for COVID-19 news on social media given the infodemic and emotional contagion through online social networks. Online platforms may be used to monitor the toll of the pandemic on mental health.

negative: Is Lockdown Bad for Social Anxiety in COVID-19 Regions?: A National Study in The SOR Perspective Lockdown measures have been widely used to control and prevent virus transmission in pandemic regions. However, the psychological effects of lockdown measures have been neglected, and the related theoretical research lags behind the practice. The present study aimed to better understand the mechanism of social anxiety in pandemic regions where the lockdown measures were imposed, based on the conceptual framework of the Stimulus-Organism-Response (SOR). For that, this research investigated how lockdown measures and psychological distance influenced social anxiety in the pandemic region. The Chinese national data was analyzed for the outcome. The results showed that (1) psychological distance mediated the relationship between pandemic COVID-19 severity and social anxiety, (2) lockdown measures buffered the detrimental effect of the COVID-19 pandemic severity on social anxiety, (3) lockdown measures moderated the mediation effect of psychological distancing on social anxiety caused by the COVID-19 pandemic. In conclusion, under the SOR framework, the lockdown measures had a buffer effect on social anxiety in pandemic regions, with the mediating role of psychological distancing.

negative: Evaluating COVID-19 Public Health Messaging in Italy: Self-Reported Compliance and Growing Mental Health Concerns Purpose: The COVID-19 death-rate in Italy continues to climb, surpassing that in every other country. We implement one of the first nationally representative surveys about this unprecedented public health crisis and use it to evaluate the Italian government's public health efforts and citizen responses. Findings: (1) Public health messaging is being heard. At this point, the Italian people understand how to keep themselves and others safe from the SARS-Cov-2 virus. This is true for all population groups we studied, with the partial exception of slightly lower compliance among young adults. Remarkably, even those who do not trust the government, and those who think the government has been untruthful about the crisis mostly believe the public health message and claim to be acting in accordance. (2) The quarantine is beginning to have serious negative effects on the population's mental health. Policy Recommendations: Public health messaging is being heard and understood. The focus now should move from explaining that citizens should stay at home to what they can do at home. We need interventions that make staying at home and following public health protocols more desirable, or possibly even fun. These interventions could include virtual social interactions, such as online social reading activities, classes, exercise routines, among others - all designed to reduce the boredom of being socially isolated for long periods of time and to increase the attractiveness of following public health recommendations. Interventions like these will grow in importance as the crisis wears on around the world, and staying inside wears on people.

negative: Sentinel Event Surveillance to Estimate Total SARS-CoV-2 Infections, United States Human infections with a novel coronavirus (SARS-CoV-2) were first identified via syndromic surveillance in December of 2019 in Wuhan China. Since identification, infections (coronavirus disease-2019; COVID-19) caused by this novel pathogen have spread globally, with more than 180,000 confirmed cases as of March 16, 2020. Effective public health interventions, including social distancing, contact tracing, and isolation/quarantine rely on the rapid and accurate identification of confirmed cases. However, testing capacity (having sufficient tests and laboratory throughput) to support these non-pharmaceutical interventions remains a challenge for containment and mitigation of COVID-19 infections. We undertook a sentinel event strategy (where single health events signal emerging trends) to estimate the incidence of COVID-19 in the US. Data from a recent national conference, the Conservative Political Action Conference, (CPAC) near Washington, DC and from the outbreak in Wuhan, China were used to fit a simple exponential growth model to estimate the total number of incident SARS- CoV-2 infections in the United States on March 1, 2020, and to forecast subsequent infections potentially undetected by current testing strategies. Our analysis and forecasting estimates a total of 54,100 SARS-CoV-2 infections (80 % CI 5,600 to 125,300) have occurred in the United States to March 12, 2020. Our forecast predicts that a very substantial number of infections are undetected, and without extensive and far-reaching non-pharmaceutical interventions, the number of infections should be expected to grow at an exponential rate.

negative: Impact of the COVID-19 Pandemic on Mental Health and Quality of Life among Local Residents in Liaoning Province, China: A Cross-Sectional Study Our study aimed to investigate the immediate impact of the COVID-19 pandemic on mental health and quality of life among local Chinese residents aged ≥18 years in Liaoning Province, mainland China. An online survey was distributed through a social media platform between January and February 2020. Participants completed a modified validated questionnaire that assessed the Impact of Event Scale (IES), indicators of negative mental health impacts, social and family support, and mental health-related lifestyle changes. A total of 263 participants (106 males and 157 females) completed the study. The mean age of the participants was 37.7 ± 14.0 years, and 74.9% had a high level of education. The mean IES score in the participants was 13.6 ± 7.7, reflecting a mild stressful impact. Only 7.6% of participants had an IES score ≥26. The majority of participants (53.3%) did not feel helpless due to the pandemic. On the other hand, 52.1% of participants felt horrified and apprehensive due to the pandemic. Additionally, the majority of participants (57.8–77.9%) received increased support from friends and family members, increased shared feeling and caring with family members and others. In conclusion, the COVID-19 pandemic was associated with mild stressful impact in our sample, even though the COVID-19 pandemic is still ongoing. These findings would need to be verified in larger population studies.

negative: Covid 19. The paradox of social distancing. Before 2020 the term ‘social distancing’ while not new, was barely known. The concept was promoted by the World Health Organisation in 2008 as a public health measure to prevent transmission of influenza, and in various forms it can be identified in reference to epidemics going back hundreds of years. However, in common parlance social distancing is more likely to have been associated with stigma or social class, something with negative connotations, something to be avoided.

negative: Lutte contre les maladies respiratoires chroniques en Afrique : se concerter pour faire passer les programmes dans la pratique

negative: Enabling and Emerging Technologies for Social Distancing: A Comprehensive Survey Social distancing is crucial for preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the closely physical contact between people, we can reduce chances of catching the virus and spreading it to the community. This paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, AI can enable, encourage, and even enforce social distancing. To that end, we provide a fundamental background of social distancing including basic concepts, measurements, models and propose practical scenarios. We then discuss enabling wireless technologies which are especially effective and can be widely adopted in practice to keep distance and monitor people. After that, emerging technologies such as machine learning, computer vision, thermal, ultrasound, etc., are introduced. These technologies open many new solutions and directions to deal with problems in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. Finally, we provide important open issues and challenges (e.g., privacy-preserving, cybersecurity) in implementing social distancing in practice.

negative: Macroeconomic Effect of Infectious Disease Outbreaks Abstract This article highlights the important macroeconomic effects of communicable disease outbreaks, focusing especially on evidence from computablegeneral equilibrium analyses. It illustrates how, in particular, labor supply and behavior change effects have been estimated using retrospective analysis and macroeconomic models.

negative: A relevance and quality-based ranking algorithm applied to evidence-based medicine Abstract Background The amount of information available about millions of different subjects is growing every day. This has led to the birth of new search tools specialized in different domains, because classical information retrieval models have trouble dealing with the special characteristics of some of these domains. Evidence-based Medicine is a case of a complex domain where classical information retrieval models can help search engines retrieve documents by considering the presence or absence of terms, but these must be complemented with other specific strategies which allow retrieving and ranking documents including the best current evidence and methodological quality. Objective The goal is to present a ranking algorithm able to select the best documents for clinicians considering aspects related to the relevance and the quality of said documents. Methods In order to assess the effectiveness of this proposal, an experimental methodology has been followed by using Medline as a data set and the Cochrane Library as a gold standard. Results Applying the evaluation methodology proposed, and after submitting 40 queries on the platform developed, the MAP (Mean Average Precision) obtained was 20.26%. Conclusions Successful results have been achieved with the experiments, improving on other studies, but under different and even more complex circumstances.

negative: Cerebrovascular Accident in a Pediatric Patient Presenting With Influenza Abstract Background Acute ischemic stroke (AIS) in pediatric populations accounts for more than half of pediatric strokes and is associated with significant morbidity and mortality. Pediatric AIS can present with nonspecific symptoms or symptoms that mimic alternate pathology. Case Report A 4-month-old female presented to the emergency department for fever, decreased oral intake, and “limp” appearance after antibiotic administration. She was febrile, tachypneic, and hypoxic. Her skin was mottled with 3-s capillary refill, her anterior fontanelle was tense, and she had mute Babinski reflex bilaterally but was moving all extremities. The patient was hyponatremic, thrombocytopenic, and tested positive for influenza A. A computed tomography scan of the brain revealed an acute infarction involving the right frontal, parietal, temporal, and occipital lobes in addition to hyperdensities concerning for thrombosed cortical veins. The patient was transferred for specialty evaluation and was discharged 2 weeks later on levetiracetam. Why Should an Emergency Physician be Aware of This? Pediatric AIS can present with nonspecific symptoms that mimic alternate pathology. A high level of suspicion is needed so as not to miss the diagnosis of pediatric AIS in the emergency department. A thorough neurologic assessment is warranted, and subtle abnormalities should be investigated further.

negative: Cardiovascular disease and COVID-19 Abstract Background and aims Many patients with coronavirus disease 2019 (COVID-19) have underlying cardiovascular (CV) disease or develop acute cardiac injury during the course of the illness. Adequate understanding of the interplay between COVID-19 and CV disease is required for optimum management of these patients. Methods A literature search was done using PubMed and Google search engines to prepare a narrative review on this topic. Results Respiratory illness is the dominant clinical manifestation of COVID-19; CV involvement occurs much less commonly. Acute cardiac injury, defined as significant elevation of cardiac troponins, is the most commonly reported cardiac abnormality in COVID-19. It occurs in approximately 8–12% of all patients. Direct myocardial injury due to viral involvement of cardiomyocytes and the effect of systemic inflammation appear to be the most common mechanisms responsible for cardiac injury. The information about other CV manifestations in COVID-19 is very limited at present. Nonetheless, it has been consistently shown that the presence of pre-existing CV disease and/or development of acute cardiac injury are associated with significantly worse outcome in these patients. Conclusions Most of the current reports on COVID-19 have only briefly described CV manifestations in these patients. Given the enormous burden posed by this illness and the significant adverse prognostic impact of cardiac involvement, further research is required to understand the incidence, mechanisms, clinical presentation and outcomes of various CV manifestations in COVID-19 patients.

negative: Population-scale testing can suppress the spread of COVID-19 We propose an additional intervention that would contribute to the control of the COVID-19 pandemic, offer more protection for people working in essential jobs, and help guide an eventual reopening of society. The intervention is based on: (1) testing every individual (2) repeatedly, and (3) self-quarantine of infected individuals. Using a standard epidemiological model (SIR), we show here that by identification and isolation of the majority of infectious individuals, including those who may be asymptomatic, the reproduction number R0 of SARS-CoV-2 would be reduced well below 1.0, and the epidemic would collapse. We replicate these observations in a more complex stochastic dynamic model on a social network graph. We also find that the testing regime would be additive to other interventions, and be effective at any level of prevalence. If adopted as a policy, any industrial society could sustain the regime for as long as it takes to find a safe and effective cure or vaccine. Our model also indicates that unlike sampling-based tests, population-scale testing does not need to be very accurate: false negative rates up to 15% could be tolerated if 80% comply with testing every ten days, and false positives can be almost arbitrarily high when a high fraction of the population is already effectively quarantined. Testing at the required scale would be feasible if existing qPCR-based methods are scaled up and multiplexed. A mass produced, low throughput field test kit could also be carried out at home. Economic analysis also supports the feasibility of the approach: current reagent costs for tests are in the range of a dollar or less, and the estimated benefits for population-scale testing are so large that the policy would be cost-effective even if the costs were larger by more than two orders of magnitude. To identify both active and previous infections, both viral RNA and antibodies could be tested. All technologies to build such test kits, and to produce them in the scale required to test the entire world's population exist already. Integrating them, scaling up production, and implementing the testing regime will require resources and planning, but at a scale that is very small compared to the effort that every nation would devote to defending itself against a more traditional foe.

negative: Letter: The Risk of COVID-19 Infection During Neurosurgical Procedures: A Review of Severe Acute Respiratory Distress Syndrome Coronavirus 2 (SARS-CoV-2) Modes of Transmission and Proposed Neurosurgery-Specific Measures for Mitigation

negative: Conditions for a second wave of COVID-19 due to interactions between disease dynamics and social processes In May 2020, many jurisdictions around the world began lifting physical distancing restrictions against the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), giving rise to concerns about a possible second wave of coronavirus disease 2019 (COVID-19). These restrictions were imposed as a collective population response to the presence of COVID-19 in communities. However, lifting restrictions is also a population response to their socio-economic impacts, and is expected to increase COVID-19 cases, in turn. This suggests that the COVID-19 pandemic exemplifies a coupled behaviour-disease system. Here we develop a minimal mathematical model of the interaction between social support for school and workplace closure and the transmission dynamics of SARS-CoV-2. We find that a second wave of COVID-19 occurs across a broad range of plausible model input parameters, on account of instabilities generated by behaviour-disease interactions. We conclude that second waves of COVID-19--should they materialize--can be interpreted as the outcomes of nonlinear interactions between disease dynamics and population behaviour.

negative: Cyberbiosecurity Challenges of Pathogen Genome Databases Pathogen detection, identification, and tracking is shifting from non-molecular methods, DNA fingerprinting methods, and single gene methods to methods relying on whole genomes. Viral Ebola and influenza genome data are being used for real-time tracking, while food-borne bacterial pathogen outbreaks and hospital outbreaks are investigated using whole genomes in the UK, Canada, the USA and the other countries. Also, plant pathogen genomes are starting to be used to investigate plant disease epidemics such as the wheat blast outbreak in Bangladesh. While these genome-based approaches provide never-seen advantages over all previous approaches with regard to public health and biosecurity, they also come with new vulnerabilities and risks with regard to cybersecurity. The more we rely on genome databases, the more likely these databases will become targets for cyber-attacks to interfere with public health and biosecurity systems by compromising their integrity, taking them hostage, or manipulating the data they contain. Also, while there is the potential to collect pathogen genomic data from infected individuals or agricultural and food products during disease outbreaks to improve disease modeling and forecast, how to protect the privacy of individuals, growers, and retailers is another major cyberbiosecurity challenge. As data become linkable to other data sources, individuals and groups become identifiable and potential malicious activities targeting those identified become feasible. Here, we define a number of potential cybersecurity weaknesses in today's pathogen genome databases to raise awareness, and we provide potential solutions to strengthen cyberbiosecurity during the development of the next generation of pathogen genome databases.

negative: Hemodialysis and COVID-19: An Achilles’ Heel in the Pandemic Healthcare Response in the United States

negative: Attitudes, concerns, perceived impact and coping strategies for avian influenza among the first year medical students and interns in Tehran University of Medical Sciences. To study and compare the attitudes, concerns, perceived impact and coping strategies for avian influenza (AI) among the first year medical students (FYMS) and interns in Tehran University of Medical Sciences. This was a cross sectional study carried out on FYMS (n=158) and interns (n=158) in 2008. The data collection tool was a questionnaire containing 37 questions in five parts. The three choices including "agree, disagree and unsure" were considered for all questions. We used Chi-square and Fisher's exact tests for analysis. Most of FYMS and interns (78.2%) believed their health would be depended on the care of their selves. Most of them (95.3%) believed that if they knew avian flu better, they could be more prepared for it. The majority were concerned about risk to their health from their work (62.7%). Most (67.7%) accepted the risk and only 5 (1.6%) would consider stopping work. For non-work concerns, 70.9% were concerned about their spouses/sexual partners and 65.8% about their children. For perceived impact, most (66.5%) believed that they would feel stressed at work and the majority (74.4%) expected an increased workload. FYMS and interns have positive attitudes but major concerns about contracting AI and its relation to medical practice.

negative: Genomic epidemiology of a densely sampled COVID19 outbreak in China Analysis of genetic sequence data from the pandemic SARS Coronavirus 2 can provide insights into epidemic origins, worldwide dispersal, and epidemiological history. With few exceptions, genomic epidemiological analysis has focused on geographically distributed data sets with few isolates in any given location. Here we report an analysis of 20 whole SARS-CoV 2 genomes from a single relatively small and geographically constrained outbreak in Weifang, People's Republic of China. Using Bayesian model-based phylodynamic methods, we estimate the reproduction number for the outbreak to be 1.99(95% CI:1.48-3.14). We further estimate the number of infections through time and compare these estimates to confirmed diagnoses by the Weifang Centers for Disease Control. We find that these estimates are consistent with reported cases and there is unlikely to be a large undiagnosed burden of infection over the period we studied.

negative: Adding the spatial dimension to the social network analysis of an epidemic: Investigation of the 2007 outbreak of equine influenza in Australia Abstract Equine influenza is a highly contagious and widespread viral respiratory disease of horses and other equid species, characterised by fever and a harsh dry cough. In 2007, in the first reported outbreak in Australia, the virus spread through the horse populations of two states within 4 months. Most of the geographic spread occurred within the first 10 days and was associated with the movement of infected horses prior to the implementation of movement controls. This study applies social network analysis to describe spread of equine influenza between horse premises infected in the early outbreak period, identifying spread occurring through a contact network and secondary local spatial spread. Social networks were constructed by combining contact-tracing data on horse movements with a distance matrix between all premises holding horses infected within the first 10 days of the outbreak. These networks were analysed to provide a description of the epidemic, identify premises that were central to disease spread and to estimate the relative proportion of premises infected through infected horse movements and through local spatial spread. We then explored the effect of distance on disease spread by estimating the range of local spread (through direct contact, transmission on fomites and windborne transmission) based on the level of fragmentation in the network and also by directly estimating the shape of the outbreak's spatial transmission kernel. During the first 10 days of this epidemic, 197 horse premises were infected; 70 of these were included in the contact-traced network. Most local spread occurred within 5km. Local spread was estimated to have occurred up to a distance of 15.3km – based on the contact-and-proximity network – and at a very low incidence beyond this distance based on the transmission kernel estimate. Of the 70 premises in the contact network, spread to 14 premises (95% CI: 9, 20 premises) was likely to have occurred through local spatial spread from nearby infected premises, suggesting that 28.3% of spread in the early epidemic period was ‘network-associated’ (95% CI: 25.6, 31.0%). By constructing a ‘maximal network’ of contact and proximity (based on a distance cut-off of 15.3km), 44 spatial clusters were described, and the horse movements that initiated infection in these locations were identified. Characteristics of the combined network, incorporating both spatial and underlying contact relationships between infected premises, explained the high rate of spread, the sequence of cluster formation and the widespread dispersal experienced in the early phase of this epidemic. These results can inform outbreak control planning by guiding the imposition of appropriate control zone diameters around infected premises and the targeting of surveillance and interventions.

negative: Quantifying the Economic Impact of COVID-19 in Mainland China Using Human Mobility Data To contain the pandemic of coronavirus (COVID-19) in Mainland China, the authorities have put in place a series of measures, including quarantines, social distancing, and travel restrictions. While these strategies have effectively dealt with the critical situations of outbreaks, the combination of the pandemic and mobility controls has slowed China's economic growth, resulting in the first quarterly decline of Gross Domestic Product (GDP) since GDP began to be calculated, in 1992. To characterize the potential shrinkage of the domestic economy, from the perspective of mobility, we propose two new economic indicators: the New Venues Created (NVC) and the Volumes of Visits to Venue (V^3), as the complementary measures to domestic investments and consumption activities, using the data of Baidu Maps. The historical records of these two indicators demonstrated strong correlations with the past figures of Chinese GDP, while the status quo has dramatically changed this year, due to the pandemic. We hereby presented a quantitative analysis to project the impact of the pandemic on economies, using the recent trends of NVC and V^3. We found that the most affected sectors would be travel-dependent businesses, such as hotels, educational institutes, and public transportation, while the sectors that are mandatory to human life, such as workplaces, residential areas, restaurants, and shopping sites, have been recovering rapidly. Analysis at the provincial level showed that the self-sufficient and self-sustainable economic regions, with internal supplies, production, and consumption, have recovered faster than those regions relying on global supply chains.

negative: The Relationship Between COVID-19 Infection and Risk Perception, Knowledge, Attitude As Well As Four Non-pharmaceutical Interventions (NPIs) During the Late Period Of The COVID-19 Epidemic In China An Online Cross-sectional Survey of 8158 Adults Background: So far, there has been no published population study on the relationship between COVID19 infection and public risk perception, information source, knowledge, attitude and four nonpharmaceutical interventions(NPI: hand washing, proper coughing habits, social distancing and mask wearing) during the COVID-19 outbreak in China. Methods: An online survey of 8158 Chinese adults between 22 February to 5 March 2020 was conducted. Bivariate associations between categorical variables were examined using Fisher exact test. We also explored the determinants of four NPIs as well as their association with COVID19 infection using logistic regression. Results: Of 8158 adults included, 57 (0.73%) were infected with COVID19. The overwhelming majority of respondents showed a positive attitude (99.2%), positive risk perception (99.9%) and high knowledge levels that were among the strongest predictors of four highly adopted NPIs (hand washing:96.8%; proper coughing: 93.1%; social distancing:87.1%; mask wearing:97.9%). There was an increased risk of COVID19 infection for those who not washing hands (2.28% vs 0.65%; RR=3.53: 95%CI: 1.538.15; P<0.009); not practicing proper coughing (1.79% vs 0.73%; RR=2.44: 95%CI: 1.15-5.15;P=0.026); not practicing social distancing (1.52% vs 0.58%; RR=2.63:95%CI:1.48 4.67; P=0.002); and not wearing a mask (7.41% vs 0.6%; RR=12.38:95%CI:5.81-26.36; P<0.001). For those who did practice all other three NPIs, wearing mask was associated with significantly reduced risk of infection compared to those who did not wear a mask (0.6% vs 16.7%; p=0.035). Similarly, for those who did not practice all or part of the other three NPIs, wearing mask was also associated with significantly reduced risk of infection. In a penalised logistic regression model including all four NPIs, wearing a mask was the only significant predictor of COVID19 infection among four NPIs (OR=7.20; 95%CI:2.2423.11; p<0.001). Conclusions: We found high levels of risk perception, positive attitude, desirable knowledge as well as a high level of adopting four NPIs. The relevant knowledge, risk perception and attitude were strong predictors of adapting the four NPIs. Mask wearing, among four personal NPIs, is the most effective protective measure against COVID19 infection with added preventive effect among those who practised all or part of the other three NPIs.

negative: COVID-19 in Peru: the need to pay attention to the high number of police deaths due to the pandemic

negative: Vulnerable Populations: Weathering the Pandemic Storm

negative: First COVID-19 case in the Rohingya camp in Bangladesh: Needs proper attention

negative: A data-driven model for influenza transmission incorporating media effects Numerous studies have attempted to model the effect of mass media on the transmission of diseases such as influenza; however, quantitative data on media engagement has until recently been difficult to obtain. With the recent explosion of ‘big data’ coming from online social media and the like, large volumes of data on a population’s engagement with mass media during an epidemic are becoming available to researchers. In this study, we combine an online dataset comprising millions of shared messages relating to influenza with traditional surveillance data on flu activity to suggest a functional form for the relationship between the two. Using this data, we present a simple deterministic model for influenza dynamics incorporating media effects, and show that such a model helps explain the dynamics of historical influenza outbreaks. Furthermore, through model selection we show that the proposed media function fits historical data better than other media functions proposed in earlier studies.

negative: Patients with advanced basal cell carcinomas in treatment with sonic hedgehog inhibitors during the coronavirus disease 2019 (COVID-19) period: Management and adherence to treatment

negative: La chirurgie digestive urgente, victime collatérale de la crise du Covid-19?

negative: Peer influence in adolescence: Public-health implications for COVID-19 Abstract The Covid-19 pandemic has resulted in the widespread implementation of social distancing measures. Adhering to social distancing may be particularly challenging for adolescents, for whom interaction with peers is especially important. We argue that young people’s capacity to encourage each other to observe social distancing rules should be harnessed.

negative: Changes in health promoting behavior during COVID-19 physical distancing: Utilizing WHOOP data to Examine Trends in Sleep, Activity, and Cardiovascular Health. The COVID-19 pandemic incited global and unprecedented restrictions on the behavior of society. The aims of this study were to quantify changes to sleep/wake behavior and exercise patterns (e.g., exercise frequency, modality, and intensity), and the subsequent impact on physiological markers of health (e.g., total sleep duration, social jet lag, resting heart rate, and heart rate variability) with the introduction of physical distancing mandates and recommendations. A retrospective analysis of 50,000 subscribers to the WHOOP platform (mean age = 36.6 {+/-} 10.5; 11,956 females, 38,044 males) was conducted covering the period from January 1st, 2020 through May 15th, 2020. In order to make robust comparisons, this time period was separated into a 68 day baseline period and a 67 day physical distancing period - with a total of 6.3 million sleeps and 4.9 million exercise sessions analyzed. As compared to baseline, during physical distancing, all subjects analyzed in this study dedicated more time to sleep (+0.21 hours), fell asleep earlier (-0.43 hours), woke up earlier (-0.29 hours), obtained more sleep (+0.19 hours) and reduced social jet lag (-0.23 hours). Subjects also increased exercise frequency by an average of 1.1% and increased exercise intensity by spending an average of 1.8% more time in the three highest heart rate zones. These changes to sleep and exercise behavior may have contributed to the observed lowered resting heart rate (-0.9 beats per minute) and increased heart rate variability (+1.3 milliseconds) during physical distancing. A potential explanation for these results is that decreases in business hours-based commitments during physical distancing may have resulted in increased opportunity to engage in exercise and prioritize sleep. Therefore, as the COVID-19 pandemic eases, maintenance of certain aspects of physical distancing (e.g., flexibility to work from home) may result in a healthier population.

negative: Insights into Cross-species Evolution of Novel Human Coronavirus 2019-nCoV and Defining Immune Determinants for Vaccine Development Novel Coronavirus (nCoV) outbreak in the city of Wuhan, China during December 2019, has now spread to various countries across the globe triggering a heightened containment effort. This human pathogen is a member of betacoronavirus genus carrying 30 kilobase of single positive-sense RNA genome. Understanding the evolution, zoonotic transmission, and source of this novel virus would help accelerating containment and prevention efforts. The present study reported detailed analysis of 2019-nCoV genome evolution and potential candidate peptides for vaccine development. This nCoV genotype might have been evolved from a bat-CoV by accumulating non-synonymous mutations, indels, and recombination events. Structural proteins Spike (S), and Membrane (M) had extensive mutational changes, whereas Envelope (E) and Nucleocapsid (N) proteins were very conserved suggesting differential selection pressures exerted on 2019-nCoV during evolution. Interestingly, 2019-nCoV Spike protein contains a 39 nucleotide (5’-aAT GGT GTT GAA GGT TTT AAT TGT TAC TTT CCT TTA CAA Tca-3’) sequence insertion, which shares homology to fish genomic sequence of Myripristis murdjan, an abundant fish type in Indo-Pacific Ocean. Furthermore, we identified eight high binding affinity (HBA) CD4 T-cell epitopes in the S, E, M and N proteins, which can be commonly recognized by HLA-DR alleles of Asia and Asia-Pacific Region population. These immunodominant epitopes can be incorporated in universal subunit CoV vaccine. Diverse HLA types and variations in the epitope binding affinity may contribute to the wide range of immunopathological outcomes of circulating virus in humans. Our findings emphasize the requirement for continuous surveillance of CoV strains in live animal markets to better understand the viral adaptation to human host and to develop practical solutions to prevent the emergence of novel pathogenic CoV strains.

negative: The psychological impact of the COVID-19 epidemic on college students in China Abstract A COVID-19 epidemic has been spreading in China and other parts of the world since December 2019. The epidemic has brought not only the risk of death from infection but also unbearable psychological pressure. We sampled college students from Changzhi medical college by using cluster sampling. They responded to a questionnaire packet that included the 7-item Generalized Anxiety Disorder Scale (GAD-7) and those inquiring the participants’ basic information. We received 7,143 responses. Results indicated that 0.9% of the respondents were experiencing severe anxiety, 2.7% moderate anxiety, and 21.3% mild anxiety. Moreover, living in urban areas (OR = 0.810, 95% CI = 0.709 - 0.925), family income stability (OR = 0.726, 95% CI = 0.645 - 0.817) and living with parents (OR = 0.752, 95% CI = 0.596 - 0.950) were protective factors against anxiety. Moreover, having relatives or acquaintances infected with COVID-19 was a risk factor for increasing the anxiety of college students (OR = 3.007, 95% CI = 2.377 - 3.804). Results of correlation analysis indicated that economic effects, and effects on daily life, as well as delays in academic activities, were positively associated with anxiety symptoms (P < .001). However, social support was negatively correlated with the level of anxiety (P < .001). It is suggested that the mental health of college students should be monitored during epidemics.

negative: Opinion de comité de la SOGC – COVID-19 pendant la grossesse

negative: Evaluating the ALERT algorithm for local outbreak onset detection in seasonal infectious disease surveillance data Estimation of epidemic onset timing is an important component of controlling the spread of seasonal infectious diseases within community healthcare sites. The Above Local Elevated Respiratory Illness Threshold (ALERT) algorithm uses a threshold‐based approach to suggest incidence levels that historically have indicated the transition from endemic to epidemic activity. In this paper, we present the first detailed overview of the computational approach underlying the algorithm. In the motivating example section, we evaluate the performance of ALERT in determining the onset of increased respiratory virus incidence using laboratory testing data from the Children's Hospital of Colorado. At a threshold of 10 cases per week, ALERT‐selected intervention periods performed better than the observed hospital site periods (2004/2005–2012/2013) and a CUSUM method. Additional simulation studies show how data properties may effect ALERT performance on novel data. We found that the conditions under which ALERT showed ideal performance generally included high seasonality and low off‐season incidence.

negative: Human monoclonal IgG selection of Plasmodium falciparum for the expression of placental malaria-specific variant surface antigens Pregnancy-associatedPlasmodium falciparum malaria (PAM) is a major cause of morbidity and mortality in African women and their offspring. PAM is characterized by accumulation of infected erythrocytes (IEs) that adhere to chondroitin sulphate A (CSA) in the placental intervillous space. We show here that human monoclonal IgG antibodies with specificity for variant surface antigens (VSA) specifically expressed by CSA-adhering IEs (VSA(PAM)) can be used in vitro to select parasites from nonpregnant donors to express VSA(PAM) and that this selection for VSA(PAM) expression results in preferential transcription of var2csa. The results corroborate current efforts to develop PAM-specific vaccines based on VAR2CSA.

negative: Novel Coronavirus in Cape Town Informal Settlements: Feasibility of Using Informal Dwelling Outlines to Identify High Risk Areas for COVID-19 Transmission From A Social Distancing Perspective BACKGROUND: The challenges faced by the Global South during the coronavirus disease (COVID-19) pandemic are compounded by the presence of informal settlements, which are typically densely populated and lacking in formalized sanitation infrastructure. Social distancing measures in informal settlements may be difficult to implement due to the density and layout of settlements. This study measures the distance between dwellings in informal settlements in Cape Town to identify the risk of COVID-19 transmission. OBJECTIVE: The aim of this paper is to determine if social distancing measures are achievable in informal settlements in Cape Town, using two settlements as an example. We will first examine the distance between dwellings and their first, second, and third nearest neighbors and then identify clusters of dwellings in which residents would be unable to effectively practice social isolation due to the close proximity of their homes. METHODS: Dwellings in the settlements of Masiphumelele and Klipfontein Glebe were extracted from a geographic information system data set of outlines of all informal dwellings in Cape Town. The distance to each dwelling's first, second, and third nearest neighbors was calculated for each settlement. A social distance measure of 2 m was used (buffer of 1 m, as dwellings less than 2 m apart are joined) to identify clusters of dwellings that are unable to effectively practice social distancing in each settlement. RESULTS: The distance to each dwelling's first 3 nearest neighbors illustrates that the settlement of Masiphumelele is constructed in a denser fashion as compared to the Klipfontein Glebe settlement. This implies that implementing social distancing will likely be more challenging in Masiphumelele than in Klipfontein Glebe. However, using a 2-m social distancing measure, it was demonstrated that large portions of Klipfontein Glebe would also be unable to effectively implement social distancing. CONCLUSIONS: Effectively implementing social distancing may be a challenge in informal settlements due to their density. This paper uses dwelling outlines for informal settlements in the city of Cape Town to demonstrate that with a 2 m measure, effective social distancing will be challenging.

negative: Teicoplanin: an alternative drug for the treatment of coronavirus COVID-19? In December 2019, a new coronavirus, named SARS-CoV-2, has emerged from China causing pneumonia outbreaks first in the Wuhan region and have now spread worldwide because of its probable high transmission efficiency. Due to the lack of efficient and specific treatments and the need to contain the epidemic, drug repurposing appears to be the best tool to find therapeutic solution. Chloroquine, remdesivir, lopinavir, ribavirin or ritonavir have shown efficacy to inhibit coronavirus in vitro. Teicoplanin, an antibiotic used to treat staphylococci infection, previously showed efficacy to inhibit the first stage of MERS-coronarivus viral cycle in human cells. This activity is conserved on the SARS-Cov-2, thus placing teicoplanin as a potential treatment for patients with this virus.

negative: The Fellowship Milieu in Adult Cardiothoracic Anesthesiology – fostering psychological wellbeing during the coronavirus crisis

negative: COVID-19 battle during the toughest sanctions against Iran

negative: A War on Two Fronts: Cancer Care in the Time of COVID-19 Initial reports suggest that COVID-19 can be particularly lethal in patients with cancer. This commentary discusses how to balance a delay in cancer diagnosis or treatment against the risk for a potential COVID-19 exposure, mitigate the risks for significant care disruptions associated with social distancing behaviors, and manage the appropriate allocation of limited health care resources in this unprecedented time of health care crisis.

negative: Preparing for the Perpetual Challenges of Pandemics of Coronavirus Infections with Special Focus on SARS-CoV-2 COVID-19, arising from novel, zoonotic coronavirus-2, has gripped the world in a pandemic. The present chapter discusses the current internationally implemented pandemic preparedness strategies succeeding/recommended to curb the COVID-19 threat to humankind. The updated phase-wise categorization of a pandemic as recommended by the WHO is described, and associated innovations in surveillance, response, and medical measures/advisory in practice across the globe are elaborated. From a bird’s eye view, the COVID-19 pandemic management relies on revolutionizing the disease surveillance by incorporating artificial intelligence and data analytics, boosting the response strategies—extensive testing, case isolation, contact tracing, and social distancing—and promoting awareness and access to pharmaceutical and non-pharmaceutical interventions, which are discussed in the present chapter. We also preview the economic bearing of the COVID-19 pandemic.

negative: Computational Approaches to Influenza Surveillance: Beyond Timeliness Several digital data sources and systems have been advanced for use in augmenting traditional influenza surveillance systems. Although timeliness is one of the main advantage of these tools, there are several other recognizable uses and potential impact of these systems on the public and global public health.

negative: Human Mobility during COVID-19 in the Context of Mild Social Distancing: Implications for Technological Interventions The COVID-19 pandemic has brought both tangible and intangible damage to our society. Many researchers studied about its societal impacts in the countries that had implemented strong social distancing measures such as stay-at-home orders. Among them, human mobility has been studied extensively due to its importance in flattening the curve. However, mobility has not been actively studied in the context of mild social distancing. Insufficient understanding of human mobility in diverse contexts might provide limited implications for any technological interventions to alleviate the situation. To this end, we collected a dataset consisting of more than 1M daily smart device users in the third-largest city of South Korea, which has implemented mild social distancing policies. We analyze how COVID-19 shaped human mobility in the city from geographical, socio-economic, and socio-political perspectives. We also examine mobility changes for points of interest and special occasions such as transportation stations and the case of legislative elections. We identify a typology of populations through these analyses as a means to provide design implications for technological interventions. This paper contributes to social sciences through in-depth analyses of human mobility and to the CSCW community with new design challenges and potential implications.

negative: The socio-economic determinants of the coronavirus disease (COVID-19) pandemic The magnitude of the coronavirus disease (COVID-19) pandemic has an enormous impact on the social life and the economic activities in almost every country in the world. Besides the biological and epidemiological factors, a multitude of social and economic criteria also govern the extent of the coronavirus disease spread in the population. Consequently, there is an active debate regarding the critical socio-economic determinants that contribute to the resulting pandemic. In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 29 determinants, describing a diverse set of socio-economic characteristics, in explaining the coronavirus pandemic outcome. We show that the true empirical model behind the coronavirus outcome is constituted only of few determinants, but the extent to which each determinant is able to provide a credible explanation varies between countries due to their heterogeneous socio-economic characteristics. To understand the relationship between the potential determinants in the specification of the true model, we develop the coronavirus determinants Jointness space. In this space, two determinants are connected with each other if they are able to jointly explain the coronavirus outcome. As constructed, the obtained map acts as a bridge between theoretical investigations and empirical observations, and offers an alternate view for the joint importance of the socio-economic determinants when used for developing policies aimed at preventing future epidemic crises.

negative: Les maladies infectieuses émergentes : importance en santé publique, aspects épidémiologiques, déterminants et prévention Résumé À la fin des années 1970 on a parlé « de la fin des maladies infectieuses ». Avec l'apparition du sida et la découverte de nouveaux agents infectieux le « retour des maladies infectieuses » a été prononcé 15 à 20 ans après, donnant naissance aux « infections émergentes ». L'émergence est ce qui « dépasse le niveau moyen, retient l'attention ou sort du lot… ». En terme épidémiologique il s'agit d'une maladie qui apparaît ou dont l'incidence augmente en un lieu donné. Les infections dont l'incidence pourrait augmenter du fait de conditions propices à leur transmission doivent y être ajoutées. Différents scénarios peuvent être proposés selon que la maladie apparaît de novo (sida ou SRAS) ; apparaît là où elle n'existait pas (West Nile aux États-Unis) ; existait sans pouvoir être diagnostiquée de manière précise ou être rattachée à un agent infectieux donné (hépatite C avant la découverte du VHC) ; sort plus ou moins rapidement des fluctuations habituelles (épidémie) ; est causée par un agent dont les conditions de transmission sont propices à sa résurgence (baisse de la couverture vaccinale...). Le bioterrorisme fait partie des scénarios d'émergence. Des modifications qualitatives des agents infectieux (résistance aux anti-infectieux…) peuvent par un mécanisme de sélection donner lieu à des émergences. Les émergences infectieuses résultent de l'interaction entre l'agent, l'hôte et l'environnement qui évolue avec l'activité humaine. La lutte contre les infections émergentes est fondée sur la surveillance, l'expertise microbiologique de haut niveau et la capacité de réponse du système de santé publique. Abstract At the end of the 70s, it was said that eradicating infectious diseases was possible. With the occurrence of AIDS and the discovery of new pathogens the come-back of infectious diseases was noted, 15 to 20 years later, and the concept of emerging infections was defined. An emerging infection is the appearance of a new infection or the increase of its incidence if not new. It also includes infections for which the incidence could increase because of favorable conditions. Several scenarios can be proposed: 1) the appearance of a new infection (AIDS or SARS); 2) the appearance of a known infection where it did not exist previously (West Nile virus infection in the USA); 3) an infection that existed but that was not diagnosed or could not be linked precisely to a particular infectious agent (hepatitis C before the discovery of the hepatitis C virus; 4) a known infection that increases its usual incidence (outbreaks…); 5) infectious diseases for which current conditions may facilitate transmission (decrease of immunization coverage...). The deliberate release of a biological agent is one of the possible scenarios of emergence. Qualitative changes of infectious agents such as the resistance to anti-infectious agents may also contribute, through a selection mechanism, to the emergence of new infectious threat. Emerging infections result from the interaction between the agent, the host, and environment evolving according to human activity. Surveillance, research, laboratory capacity, and an effective public health system are key factors for their control.

negative: Implementing Basic Infection Control Practices in Disaster Situations Infections, troublesome in even optimal health care environments, can be a source of serious and persistent concern for local populations and health care workers during a disaster, and in austere environments such as those found in Iraq and Afghanistan. For these scenarios, it is vital to have standard infection control practices in place and to have them used consistently. Only then will healthcare workers be able to contain the potential spread of disease and improve conditions for those affected.

negative: The Pace and Pulse of the Fight against Coronavirus across the US, A Google Trends Approach The coronavirus pandemic is impacting our lives at unprecedented speed and scale - including how we eat and work, what we worry about, how much we move, and our ability to earn. Google Trends can be used as a proxy for what people are thinking, needing, and planning. We use it to provide both insights into, and potential indicators of, important changes in information-seeking patterns during pandemics like COVID-19. Key questions we address are: (1) What is the relationship between the coronavirus outbreak and internet searches related to healthcare seeking, government support programs, media sources of different ideologies, planning around social activities, travel, and food, and new coronavirus-specific behaviors and concerns?; (2) How does the popularity of search terms differ across states and regions and can we explain these differences?; (3) Can we find distinct, tangible search patterns across states suggestive of policy gaps to inform pandemic response? (4) Does Google Trends data correlate with and potentially precede real-life events? We suggest strategic shifts for policy makers to improve the precision and effectiveness of non-pharmaceutical interventions (NPIs) and recommend the development of a real-time dashboard as a decision-making tool. Methods used include trend analysis of US search data; geographic analyses of the differences in search popularity across US states during March 1st to April 15th, 2020; and Principal Component Analyses (PCA) to extract search patterns across states.

negative: Forecasting influenza epidemics by integrating internet search queries and traditional surveillance data with the support vector machine regression model in Liaoning, from 2011 to 2015 BACKGROUND: Influenza epidemics pose significant social and economic challenges in China. Internet search query data have been identified as a valuable source for the detection of emerging influenza epidemics. However, the selection of the search queries and the adoption of prediction methods are crucial challenges when it comes to improving predictions. The purpose of this study was to explore the application of the Support Vector Machine (SVM) regression model in merging search engine query data and traditional influenza data. METHODS: The official monthly reported number of influenza cases in Liaoning province in China was acquired from the China National Scientific Data Center for Public Health from January 2011 to December 2015. Based on Baidu Index, a publicly available search engine database, search queries potentially related to influenza over the corresponding period were identified. An SVM regression model was built to be used for predictions, and the choice of three parameters (C, γ, ε) in the SVM regression model was determined by leave-one-out cross-validation (LOOCV) during the model construction process. The model’s performance was evaluated by the evaluation metrics including Root Mean Square Error, Root Mean Square Percentage Error and Mean Absolute Percentage Error. RESULTS: In total, 17 search queries related to influenza were generated through the initial query selection approach and were adopted to construct the SVM regression model, including nine queries in the same month, three queries at a lag of one month, one query at a lag of two months and four queries at a lag of three months. The SVM model performed well when with the parameters (C = 2, γ = 0.005, ɛ = 0.0001), based on the ensemble data integrating the influenza surveillance data and Baidu search query data. CONCLUSIONS: The results demonstrated the feasibility of using internet search engine query data as the complementary data source for influenza surveillance and the efficiency of SVM regression model in tracking the influenza epidemics in Liaoning.

negative: Emerging Influenza and Psychosis: An Important Story in Psychological Medicine

negative: COVID-19, Pandemic, and Social Distancing

negative: Positive rate of RT-PCR detection of SARS-CoV-2 infection in 4880 cases from one hospital in Wuhan, China, from Jan to Feb 2020 Abstract Background There’s an outbreak of a novel coronavirus (SARS-CoV-2) infection since December 2019, first in China, and currently with more than 80 thousand confirmed infection globally in 29 countries till March 2, 2020. Identification, isolation and caring for patients early are essential to limit human-to-human transmission including reducing secondary infections among close contacts and health care workers, preventing transmission amplification events. The RT-PCR detection of viral nucleic acid test (NAT) was one of the most quickly established laboratory diagnosis method in a novel viral pandemic, just as in this COVID-19 outbreak. Methods 4880 cases that had respiratory infection symptoms or close contact with COVID-19 patients in hospital in Wuhan, China, were tested for SARS-CoV-2 infection by use of quantitative RT-PCR (qRT-PCR) on samples from the respiratory tract. Positive rates were calculated in groups divided by genders or ages. Results The positive rate was about 38% for the total 4880 specimens. Male and older population had a significant higher positive rates. However, 57% was positive among the specimens from the Fever Clinics. Binary logistic regression analysis showed that age, not gender, was the risk factor for SARS-CoV-2 infection in fever clinics. Conclusions Therefore, we concluded that viral NAT played an important role in identifying SARS-CoV-2 infection.

negative: Interim Analysis of Pandemic Coronavirus Disease 2019 (COVID-19) and the SARS-CoV-2 virus in Latin America and the Caribbean: Morbidity, Mortality and Molecular Testing Trends in the Region Background: The relentless advance of the SARS-CoV-2 virus pandemic has resulted in a significant burden on countries, regardless of their socio-economic conditions. The virus has infected more than 2.5 million people worldwide, causing to date more than 150,000 deaths in over 210 countries. Objective: The aim of this study was to describe the trends in cases, tests and deaths related to novel coronavirus disease (COVID-19) in Latin American and Caribbean (LAC) countries. Methodology: Data were retrieved from the WHO-Coronavirus Disease (COVID-2019) situation reports and the Center for Systems Science and Engineering (CSSE) databases from Johns Hopkins University. Descriptive statistics including death rates, cumulative mortality and incidence rates, as well as testing rates per population at risk were performed. A comparison analysis among countries with [≥]50 confirmed cases was performed from February 26th, 2020 to April 8th, 2020. Results: Brazil had the greatest number of cases and deaths in the region. Panama experienced a rapid increase in the number of confirmed cases with Trinidad and Tobago, Bolivia and Honduras having the highest case fatality rates. Panama and Chile conducted more tests per million inhabitants and more tests per day per million inhabitants, followed by Uruguay and El Salvador. Dominican Republic, Bolivia, Ecuador and Brazil had the highest positive test rates. Conclusions: The COVID-19 disease pandemic caused by the SARS-CoV-2 virus has progressed rapidly in LAC countries. Some countries have been affected more severely than others, with some adopting similar disease control methods to help slow down the spread of the virus. With limited testing and other resources, social distancing is needed to help alleviate the strain on already stretched health systems.

negative: Evolutionary Medicine IV. Evolution and Emergence of Novel Pathogens Abstract This article discusses how evolutionary and ecological factors interact to affect the epidemiology of emerging infectious diseases. It further explains how the nascent field of phylodynamics constructs mathematical models, which link evolution and epidemiology, to study pathogen transmission. To illustrate the importance of considering both evolution and ecology – along with the utility of the phylodynamic approach – when studying novel pathogens, the author considers examples from HIV, influenza, and Ebola.

negative: Involvement of aminopeptidase N (CD13) in infection of human neural cells by human coronavirus 229E. Attachment to a cell surface receptor can be a major determinant of virus tropism. Previous studies have shown that human respiratory coronavirus HCV-229E uses human aminopeptidase N (hAPN [CD13]) as its cellular receptor for infection of lung fibroblasts. Although human coronaviruses are recognized respiratory pathogens, occasional reports have suggested their possible neurotropism. We have previously shown that human neural cells, including glial cells in primary cultures, are susceptible to human coronavirus infection in vitro (A. Bonavia, N. Arbour, V. W. Yong, and P. J. Talbot, J. Virol. 71:800-806, 1997). However, the only reported expression of hAPN in the nervous system is at the level of nerve synapses. Therefore, we asked whether hAPN is utilized as a cellular receptor for infection of these human neural cell lines. Using flow cytometry, we were able to show the expression of hAPN on the surfaces of various human neuronal and glial cell lines that are susceptible to HCV-229E infection. An hAPN-specific monoclonal antibody (WM15), but not control antibody, inhibited the attachment of radiolabeled HCV-229E to astrocytic, neuronal, and oligodendrocytic cell lines. A correlation between the apparent amount of cell surface hAPN and the level of virus attachment was observed. Furthermore, the presence of WM15 inhibited virus infection of these cell lines, as detected by indirect immunofluorescence. These results indicate that hAPN (CD13) is expressed on neuronal and glial cell lines in vitro and serves as the receptor for infection by HCV-229E. This further strengthens the neurotropic potential of this human respiratory virus.

negative: Committed to Health: Key Factors to Improve Users’ Online Engagement through Facebook Health organizations, continuously exposed to public scrutiny due to the social relevance of the services provided, have adopted social media to disseminate information about health but also about themselves, and thus, reducing uncertainty and improving communication. In this context, users’ participation in social media has become one of the main indicators of their effectiveness, highlighting the importance of analyzing which factors enhance online engagement. This research extends the number of variables identified in prior studies and analyzes 19,817 Facebook posts from 126 health organizations. Using multivariate linear regression, explanatory results show that economic and organizational attributes, and factors related to the social media posts, both contribute significantly to explain the engagement reached in social media by those organizations. According to our findings, health organizations are not taking enough advantage of social media to engage with their current and potential users. The dissemination of relevant information using visually attractive formats could help draw the attention of consumers, both to reach a higher commitment with the organization and to create value for society.

negative: Measuring Human and Economic Activity from Satellite Imagery to Support City-Scale Decision-Making during COVID-19 Pandemic The COVID-19 outbreak forced governments worldwide to impose lockdowns and quarantines over their population to prevent virus transmission. As a consequence, there are disruptions in human and economic activities all over the globe. The recovery process is also expected to be rough. Economic activities impact social behaviors, which leave signatures in satellite images that can be automatically detected and classified. Satellite imagery can support the decision-making of analysts and policymakers by providing a different kind of visibility into the unfolding economic changes. Such information can be useful both during the crisis and also as we recover from it. In this work, we use a deep learning approach that combines strategic location sampling and an ensemble of lightweight convolutional neural networks (CNNs) to recognize specific elements in satellite images and compute economic indicators based on it, automatically. This CNN ensemble framework ranked third place in the US Department of Defense xView challenge, the most advanced benchmark for object detection in satellite images. We show the potential of our framework for temporal analysis using the US IARPA Function Map of the World (fMoW) dataset. We also show results on real examples of different sites before and after the COVID-19 outbreak to demonstrate possibilities. Among the future work is the possibility that with a satellite image dataset that samples a region at a weekly (or biweekly) frequency, we can generate more informative temporal signatures that can predict future economic states. Our code is being made available at https://github.com/maups/covid19-satellite-analysis

negative: A Review of Coronavirus Disease-2019 (COVID-19) There is a new public health crises threatening the world with the emergence and spread of 2019 novel coronavirus (2019-nCoV) or the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus originated in bats and was transmitted to humans through yet unknown intermediary animals in Wuhan, Hubei province, China in December 2019. There have been around 96,000 reported cases of coronavirus disease 2019 (COVID-2019) and 3300 reported deaths to date (05/03/2020). The disease is transmitted by inhalation or contact with infected droplets and the incubation period ranges from 2 to 14 d. The symptoms are usually fever, cough, sore throat, breathlessness, fatigue, malaise among others. The disease is mild in most people; in some (usually the elderly and those with comorbidities), it may progress to pneumonia, acute respiratory distress syndrome (ARDS) and multi organ dysfunction. Many people are asymptomatic. The case fatality rate is estimated to range from 2 to 3%. Diagnosis is by demonstration of the virus in respiratory secretions by special molecular tests. Common laboratory findings include normal/ low white cell counts with elevated C-reactive protein (CRP). The computerized tomographic chest scan is usually abnormal even in those with no symptoms or mild disease. Treatment is essentially supportive; role of antiviral agents is yet to be established. Prevention entails home isolation of suspected cases and those with mild illnesses and strict infection control measures at hospitals that include contact and droplet precautions. The virus spreads faster than its two ancestors the SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV), but has lower fatality. The global impact of this new epidemic is yet uncertain.

negative: Functional Fear Predicts Public Health Compliance in the COVID-19 Pandemic In the current context of the global pandemic of coronavirus disease-2019 (COVID-19), health professionals are working with social scientists to inform government policy on how to slow the spread of the virus. An increasing amount of social scientific research has looked at the role of public message framing, for instance, but few studies have thus far examined the role of individual differences in emotional and personality-based variables in predicting virus-mitigating behaviors. In this study, we recruited a large international community sample (N = 324) to complete measures of self-perceived risk of contracting COVID-19, fear of the virus, moral foundations, political orientation, and behavior change in response to the pandemic. Consistently, the only predictor of positive behavior change (e.g., social distancing, improved hand hygiene) was fear of COVID-19, with no effect of politically relevant variables. We discuss these data in relation to the potentially functional nature of fear in global health crises.

negative: COVID-19 pandemic through the lens of a gastroenterology fellow: looking for the silver lining

negative: Assessing Ebola-related web search behaviour: insights and implications from an analytical study of Google Trends-based query volumes BACKGROUND: The 2014 Ebola epidemic in West Africa has attracted public interest worldwide, leading to millions of Ebola-related Internet searches being performed during the period of the epidemic. This study aimed to evaluate and interpret Google search queries for terms related to the Ebola outbreak both at the global level and in all countries where primary cases of Ebola occurred. The study also endeavoured to look at the correlation between the number of overall and weekly web searches and the number of overall and weekly new cases of Ebola. METHODS: Google Trends (GT) was used to explore Internet activity related to Ebola. The study period was from 29 December 2013 to 14 June 2015. Pearson’s correlation was performed to correlate Ebola-related relative search volumes (RSVs) with the number of weekly and overall Ebola cases. Multivariate regression was performed using Ebola-related RSV as a dependent variable, and the overall number of Ebola cases and the Human Development Index were used as predictor variables. RESULTS: The greatest RSV was registered in the three West African countries mainly affected by the Ebola epidemic. The queries varied in the different countries. Both quantitative and qualitative differences between the affected African countries and other Western countries with primary cases were noted, in relation to the different flux volumes and different time courses. In the affected African countries, web query search volumes were mostly concentrated in the capital areas. However, in Western countries, web queries were uniformly distributed over the national territory. In terms of the three countries mainly affected by the Ebola epidemic, the correlation between the number of new weekly cases of Ebola and the weekly GT index varied from weak to moderate. The correlation between the number of Ebola cases registered in all countries during the study period and the GT index was very high. CONCLUSION: Google Trends showed a coarse-grained nature, strongly correlating with global epidemiological data, but was weaker at country level, as it was prone to distortions induced by unbalanced media coverage and the digital divide. Global and local health agencies could usefully exploit GT data to identify disease-related information needs and plan proper communication strategies, particularly in the case of health-threatening events. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40249-015-0090-9) contains supplementary material, which is available to authorized users.

negative: Cancer care in the time of COVID-19—a perspective from Pakistan Across much of the world, cancer care has been sidelined to a variable degree by the global effort against the coronavirus pandemic. This paper discusses the impact of coronavirus infection on cancer diagnosis and treatment in two leading cancer centres in Pakistan. It also describes the effect that preparations for the expected surge in cases in Pakistan over the next few weeks have had on cancer care. There is an urgent need to evaluate the effect of delays in diagnosis and treatment on cancer stage and treatment, and to decide how to minimise these during likely future cycles of lockdown over the coming months and years.