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Background: A pandemic of coronavirus disease 2019 (COVID-19) emerged and affected most of the world in early 2020. To inform effective public health measures we conducted a knowledge, attitude and practice (KAP) survey among a Hausa Muslim society in Nigeria in March 2020. Methods: The study is an analytic cross-sectional survey with questionnaires administered to the general population including Health Care Workers (HCW) in Kano, Nigeria. Participants were recruited by convenience sampling following informed consent. The percentage of KAP scores were categorized as good and poor. Independent predictors of good knowledge of COVID 19 were ascertained using a binary logistic regression model. Results: The questionnaire was administered among urban 32.8%, peri-urban dwellers 32.4%, and to online participants 34.8%. The peri-urban and urban participants were given paper questionnaires. There were 886 study participants with mean age 28.58yrs [SD:10.25] (Interquartile range [IQR]:22yrs–32yrs), males 55.4% with 57.3% having had or were in tertiary education. Most participants were students 40% and civil servants 20%. The overall mean [standard deviation (SD)] for knowledge, attitude and practice scores expressed in percentage was 65.38%[SD15.90], 71.45% [SD14.10], and 65.04% [SD17.02] respectively. Out of the respondents, 270(30.47%) had good knowledge (GK), 158(17.8%) had good attitude (GA), and 230(25.96%) had good practice (GP) using cut-off scores of 75%, 86.5%, and 75% respectively. Over 48% did not agree COVID-19 originated from animals while 60% perceived the pandemic to be due to God's punishment. Also, 36% thought it was a man-made virus. When rating fear, most respondents [63.5%] had marked fear i.e. ≥ 7 out of 10 and 56% admitted to modifying their habits recently in fear of contracting the virus. As regards attitude to religious norms, 77.77% agreed on cancellation of the lesser pilgrimage as a measure to curb the spread of the disease while 23.64% admitted that greater pilgrimage (Hajj) should proceed despite the persistence of the ongoing pandemic. About 50% of the respondents insisted on attending Friday congregational prayers despite social distancing. One in four people still harbored stigma towards a person who has recovered from the virus. 28% felt some races are more at risk of the disease though 66% mentioned always practicing social distancing from persons coughing or sneezing. Almost 70% of respondents said they were willing to accept a vaccine with 39% saying they would be willing to pay for it if not publicly funded. In univariate analysis increasing age and having been ever married were associated with GK while tertiary education was associated with GA [Odds Ratio; 95% Confidence Interval] 2.66(1.79–3.95). Independent positive predictors of GK were those who were or had ever been married, those who had marked fear of COVID-19, and had modified their habits in the last three months. Those who had non-tertiary education and had the questionnaire administered as paper rather than online version had GK but age was not a predictor. Conclusion: Knowledge of transmission and preventive measures should be improved in the general population cognizant of cultural norms and Islamic practices. The study highlights the importance of considering belief systems and perception in developing control measures against COVID-19. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has caused severe health and economic impacts globally. Strategies to safely reopen economies, travel and trade are a high priority. Until a reliable vaccine is available, non-pharmaceutical techniques are the only available means of disease control. In this paper, we aim to evaluate the extent to which social distancing (SD) and facemask (FM) use can mitigate the transmission of COVID-19 when restrictions are lifted. We used a microsimulation activity-based model for Sydney Greater Metropolitan Area, to evaluate the power of SD and FM in controlling the pandemic under numerous scenarios. The hypothetical scenarios are designed to picture feasible futures under different assumptions. Assuming that the isolation of infected cases and the quarantining of close contacts are in place, different numerical tests are conducted and a full factorial two-way MANOVA test is used to evaluate the effectiveness of the FM and SD control strategies. The main and interactive effects of the containment strategies are evaluated by the total number of infections, percentage of infections reduction, the time it takes to get the pandemic under control, and the intensity of active cases. [ABSTRACT FROM AUTHOR]

Public health and social interventions are critical to mitigate the spread of the coronavirus disease 2019 (COVID-19) pandemic. Ethiopia has implemented a variety of public health and social measures to control the pandemic. This study aimed to assess social distancing and public health preventive practices of government employees in response to COVID-19. A cross-sectional study was conducted among 1,573 government employees selected from 46 public institutions located in Addis Ababa. Data were collected from 8th to 19th June 2020 using a paper-based self-administered questionnaire and analyzed using SPSS version 23.0. Descriptive statistics were used to summarize the data. Binary logistic regression analyses were used to identify factors associated with outcome variables (perceived effectiveness of facemask wearing to prevent coronavirus infection, and COVID-19 testing). Majority of the participants reported facemask wearing (96%), avoiding close contact with people including handshaking (94.8%), consistently followed government recommendations (95.6%), frequent handwashing (94.5%), practiced physical distancing (89.5%), avoided mass gatherings and crowded places (88.1%), restricting movement and travelling (71.8%), and stayed home (35.6%). More than 80% of the participants perceived that consistently wearing a facemask is highly effective in preventing coronavirus infection. Respondents from Oromia perceived less about the effectiveness of wearing facemask in preventing coronavirus infection (adjusted OR = 0.27, 95% CI:0.17–0.45). About 19% of the respondents reported that they had ever tested for COVID-19. Respondents between 40–49 years old (adjusted OR = 0.41, 95% CI:0.22–0.76) and 50–66 years (adjusted OR = 0.43, 95% CI:0.19–0.95) were less likely tested for coronavirus than the younger age groups. Similarly, respondents from Oromia were less likely to test for coronavirus (adjusted OR = 0.26, 95% CI:0.12–0.56) than those from national level. Participants who were sure about the availability of COVID-19 testing were more likely to test for coronavirus. About 57% of the respondents perceived that the policy measures in response to the pandemic were inadequate. The findings showed higher social distancing and preventive practices among the government employees in response to COVID-19. Rules and regulations imposed by the government should be enforced and people should properly apply wearing facemasks, frequent handwashing, social and physical distancing measures as a comprehensive package of COVID-19 prevention and control strategies. [ABSTRACT FROM AUTHOR]

The purpose of this work is to provide an effective social distance monitoring solution in low light environments in a pandemic situation. The raging coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus has brought a global crisis with its deadly spread all over the world. In the absence of an effective treatment and vaccine the efforts to control this pandemic strictly rely on personal preventive actions, e.g., handwashing, face mask usage, environmental cleaning, and most importantly on social distancing which is the only expedient approach to cope with this situation. Low light environments can become a problem in the spread of disease because of people's night gatherings. Especially, in summers when the global temperature is at its peak, the situation can become more critical. Mostly, in cities where people have congested homes and no proper air cross-system is available. So, they find ways to get out of their homes with their families during the night to take fresh air. In such a situation, it is necessary to take effective measures to monitor the safety distance criteria to avoid more positive cases and to control the death toll. In this paper, a deep learning-based solution is proposed for the above-stated problem. The proposed framework utilizes the you only look once v4 (YOLO v4) model for real-time object detection and the social distance measuring approach is introduced with a single motionless time of flight (ToF) camera. The risk factor is indicated based on the calculated distance and safety distance violations are highlighted. Experimental results show that the proposed model exhibits good performance with 97.84% mean average precision (mAP) score and the observed mean absolute error (MAE) between actual and measured social distance values is 1.01 cm. [ABSTRACT FROM AUTHOR]

As COVID-19 is rapidly unfolding in the United States, it is important to understand how individuals perceive the health and economic risks of the pandemic. In the absence of a readily available medical treatment, any strategy to contain the virus in the US will depend on the behavioral response of US residents. In this paper, we study individual's perceptions on COVID-19 and social distancing during the week of March 10–16, 2020, a week when COVID-19 was officially declared to be a pandemic by WHO and when new infections in the US were more than doubling every three days. Using a nationally representative sample of 5,414 respondents 18+ years of age from the Understanding America Study (UAS), we find that perceptions about COVID-19 health risks and economic consequences in the US population were largely pessimistic and highly variable by age and education. US residents who are young and do not have a college degree perceived a lower risk of getting infected but a higher probability of running out of money than others. Most individuals reported taking some steps to distance themselves from others but important differences emerge by gender and by source of information on COVID-19. Using state and day fixed-effect regressions, we show that perceptions of the health risks closely followed the number of COVID-19 cases in the country, and perceptions of the economic consequences and the prevalence of social distancing were driven upwards by both national and state-level cases. Unless addressed by effective health communication that reaches individuals across all social strata, variations in perceptions about COVID-19 epidemic raise concerns about the ability of the US to implement and sustain the widespread and restrictive policies that are required to curtail the pandemic. [ABSTRACT FROM AUTHOR]

Among over 200 COVID-19 affected countries, some are fighting to "flatten the curve", while some others are considering reopening after lockdown. It remains unclear how different reopening strategies obstruct the local virus containment and impact the economy. We develop a model with travelers across heterogeneous epicenters. A low-risk area attempts to safely reopen utilizing internal policies, such as social distancing and contact tracing, and external policies, including capacity quota, quarantine, and tests. Simulations based on the COVID-19 scenario show that external policies differ in efficacy. They can substitute each other and complement internal policies. Simultaneous relaxation of both channels may lead to a new wave of COVID-19 and large economic costs. This work highlights the importance of quantitative assessment prior to implementing reopening strategies. [ABSTRACT FROM AUTHOR]

In March of this year, COVID-19 was declared a pandemic, and it continues to threaten public health. This global health crisis imposes limitations on daily movements, which have deteriorated every sector in our society. Understanding public reactions to the virus and the non-pharmaceutical interventions should be of great help to fight COVID-19 in a strategic way. We aim to provide tangible evidence of the human mobility trends by comparing the day-by-day variations across the U.S. from January 2020 to early April 2020. Large-scale public mobility at an aggregated level is observed by leveraging mobile device location data and the measures related to social distancing. Our study captures spatial and temporal heterogeneity as well as the sociodemographic variations and teleworking trends regarding the pandemic propagation and the non-pharmaceutical mobility interventions. All metrics adapted capture decreased public movements after the national emergency declaration. The population staying home has increased in all states before the stay-at-home mandates implemented and becomes more stable after the order with a smaller range of fluctuation. The public had been taking active responses, voluntarily staying home more, to the in-state confirmed cases while the stay-at-home orders stabilize the variations. As the estimated teleworking rates also continue to incline throughout the study period, the teleworking trend can be another driving factor for the growing stay-at-home population. We confirm that there exists overall mobility heterogeneity between the income or population density groups. The study suggests that public mobility trends are in line with the government message urging to stay home. We anticipate our data-driven analysis offers integrated perspectives and serves as evidence to raise public awareness and, consequently, reinforce the importance of social distancing while assisting policymakers. [ABSTRACT FROM AUTHOR]

In response to the outbreak of the coronavirus disease 2019 (Covid-19), governments worldwide have introduced multiple restriction policies, known as non-pharmaceutical interventions (NPIs). However, the relative impact of control measures and the long-term causal contribution of each NPI are still a topic of debate. We present a method to rigorously study the effectiveness of interventions on the rate of the time-varying reproduction number Rt and on human mobility, considered here as a proxy measure of policy adherence and social distancing. We frame our model using a causal inference approach to quantify the impact of five governmental interventions introduced until June 2020 to control the outbreak in 113 countries: confinement, school closure, mask wearing, cultural closure, and work restrictions. Our results indicate that mobility changes are more accurately predicted when compared to reproduction number. All NPIs, except for mask wearing, significantly affected human mobility trends. From these, schools and cultural closure mandates showed the largest effect on social distancing. We also found that closing schools, issuing face mask usage, and work-from-home mandates also caused a persistent reduction on Rt after their initiation, which was not observed with the other social distancing measures. Our results are robust and consistent across different model specifications and can shed more light on the impact of individual NPIs. [ABSTRACT FROM AUTHOR]

We study changes in social distancing and government policy in response to local outbreaks during the COVID-19 pandemic. Using aggregated county-level data from approximately 20 million smartphones in the United States, we show that social distancing behaviors have responded to local outbreaks: a 1% increase in new cases (deaths) is associated with a 3% (11%) increase in social distancing intensity. Responsiveness is reinforced by the presence of public measures restricting movements, but remains significant in their absence. Responsiveness is higher in high-income, more educated, or Democrat-leaning counties, and in counties with low health insurance coverage. By contrast, social capital and vulnerability to infection are strongly associated with more social distancing but not with more responsiveness. Our results point to the importance of politics, trust and reciprocity for compliance with social distancing, while material constraints are more critical for being responsive to new risks such as the emergence of variants. [ABSTRACT FROM AUTHOR]

What types of public health messages are effective at changing people's beliefs and intentions to practice social distancing to slow the spread of COVID-19? We conducted two randomized experiments in summer 2020 that assigned respondents to read a public health message and then measured their beliefs and behavioral intentions across a wide variety of outcomes. Using both a convenience sample and a pre-registered replication with a nationally representative sample of Americans, we find that a message that reframes not social distancing as recklessness rather than bravery and a message that highlights the need for everyone to take action to protect one another are the most effective at increasing beliefs and intentions related to social distancing. These results provide an evidentiary basis for building effective public health campaigns to increase social distancing during flu pandemics. [ABSTRACT FROM AUTHOR]

Many factors play a role in outcomes of an emerging highly contagious disease such as COVID-19. Identification and better understanding of these factors are critical in planning and implementation of effective response strategies during such public health crises. The objective of this study is to examine the impact of factors related to social distancing, human mobility, enforcement strategies, hospital capacity, and testing capacity on COVID-19 outcomes within counties located in District of Columbia as well as the states of Maryland and Virginia. Longitudinal data have been used in the analysis to model county-level COVID-19 infection and mortality rates. These data include big location-based service data, which were collected from anonymized mobile devices and characterize various social distancing and human mobility measures within the study area during the pandemic. The results provide empirical evidence that lower rates of COVID-19 infection and mortality are linked with increased levels of social distancing and reduced levels of travel—particularly by public transit modes. Other preventive strategies and polices also prove to be influential in COVID-19 outcomes. Most notably, lower COVID-19 infection and mortality rates are linked with stricter enforcement policies and more severe penalties for violating stay-at-home orders. Further, policies that allow gradual relaxation of social distancing measures and travel restrictions as well as those requiring usage of a face mask are related to lower rates of COVID-19 infections and deaths. Additionally, increased access to ventilators and Intensive Care Unit (ICU) beds, which represent hospital capacity, are linked with lower COVID-19 mortality rates. On the other hand, gaps in testing capacity are related to higher rates of COVID-19 infection. The results also provide empirical evidence for reports suggesting that certain minority groups such as African Americans and Hispanics are disproportionately affected by the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Background: Novel viral pandemics present significant challenges to global public health. Non-pharmaceutical interventions (e.g. social distancing) are an important means through which to control the transmission of such viruses. One of the key factors determining the effectiveness of such measures is the level of public adherence to them. Research to date has focused on quantitative exploration of adherence and non-adherence, with a relative lack of qualitative exploration of the reasons for non-adherence. Objective: To explore participants' perceptions of non-adherence to COVID-19 policy measures by self and others in the UK, focusing on perceived reasons for non-adherence. Methods: Qualitative study comprising 12 focus groups conducted via video-conferencing between 25th September and 13th November 2020. Participants were 51 UK residents aged 18 and above, reflecting a range of ages, genders and race/ethnicities. Data were analysed using a thematic approach. Results: Participants reported seeing an increase in non-adherence in others over the course of the pandemic. Reports of non-adherence in self were lower than reports of non-adherence in others. Analysis revealed six main themes related to participants' reported reasons for non-adherence in self and others: (1) 'Alert fatigue' (where people find it difficult to follow, or switch off from, information about frequently changing rules or advice) (2) Inconsistent rules (3) Lack of trust in government (4) Learned Helplessness (5) Resistance and rebelliousness (6)The impact of vaccines on risk perception. Participants perceived a number of systemic failures (e.g. unclear policy, untrustworthy policymakers) to strongly contribute to two forms non-adherence—violations and errors. Conclusion: Findings suggest that latent and systemic failures—in the form of policy decisions that are commonly experienced as too changeable, inconsistent and confusing, and policy makers that are commonly perceived as untrustworthy–may play a significant role in creating the conditions that enable or encourage non-adherence. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (CoViD-19), with the fatality rate in elder (60 years old or more) being much higher than young (60 years old or less) patients, was declared a pandemic by the World Health Organization on March 11, 2020. A mathematical model considering young and elder subpopulations under different fatality rates was formulated based on the natural history of CoViD-19 to study the transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The model considered susceptible, exposed, asymptomatic, pre-symptomatic, mild CoViD-19, severe CoViD-19, and recovered compartments, besides compartments of isolated individuals and those who were caught by test. This model was applied to study the epidemiological scenario resulting from the adoption of quarantine (isolation or lockdown) in many countries to control the rapid propagation of CoViD-19. We chose as examples the isolation adopted in São Paulo State (Brazil) in the early phase but not at the beginning of the epidemic, and the lockdown implemented in Spain when the number of severe CoViD-19 cases was increasing rapidly. Based on the data collected from São Paulo State and Spain, the model parameters were evaluated, and we obtained a higher estimation for the basic reproduction number R0 (9.24 for São Paulo State, and 8 for Spain) compared to the currently accepted estimation of R0 around 2 using the SEIR (susceptible, exposed, infectious, and recovered compartments) model. In comparison with the lockdown in Spain, the relatively early adoption of the isolation in São Paulo State resulted in enlarging the period of the first wave of the epidemic and delaying its peak. The model allowed to explain the flattening of the epidemic curves by quarantine when associated with the protective measures (face mask, washing hands with alcohol and gel, and social distancing) adopted by the population. The description of the epidemic under quarantine and protections can be a background to foreseen the epidemiological scenarios from the release strategies, which can help guide public health policies by decision-makers. [ABSTRACT FROM AUTHOR]

Background: Since the start of the global COVID-19 pandemic, countries have been mirroring each other's policies to mitigate the spread of the virus. Whether current measures alone will lead to behavioral change such as social distancing, washing hands, and wearing a facemask is not well understood. The objective of this study is to better understand individual variation in behavioral responses to COVID-19 by exploring the influence of beliefs, motivations and policy measures on public health behaviors. We do so by comparing The Netherlands and Flanders, the Dutch speaking part of Belgium. Methods and findings: Our final sample included 2,637 respondents from The Netherlands and 1,678 from Flanders. The data was nationally representative along three dimensions: age, gender, and household income in both countries. Our key outcome variables of interest were beliefs about policy effectiveness; stated reasons for complying with public rules; and changes in behavior. For control variables, we included a number of measures of how severe the respondent believed Covid-19 to be and a number of negative side effects that the person may have experienced: loneliness, boredom, anxiety, and conflicts with friends and neighbors. Finally, we controlled for socio-demographic factors: age, gender, income (categorical), education (categorical) and the presence of Covid-19 risk factors (diabetes, high blood pressure, heart disease, asthma, allergies). The dependent variable for each of the estimation models is dichotomous, so we used Probit models to predict the probability of engaging in a given behavior. We found that motivations, beliefs about the effectiveness of measures, and pre-pandemic behavior play an important role. The Dutch were more likely to wash their hands than the Flemish (15.4%, p<0.01), visit family (15.5%, p <.01), run errands (12.0%, p<0.05) or go to large closed spaces such as a shopping mall (21.2%, p<0.01). The Dutch were significantly less likely to wear a mask (87.6%, p<0.01). We also found that beliefs about the virus, psychological effects of the virus, as well as pre-pandemic behavior play a role in adherence to recommendations. Conclusions: Our results suggest that policymakers should consider behavioral motivations specific to their country in their COVID-19 strategies. In addition, the belief that a policy is effective significantly increased the probability of the behavior, so policy measures should be accompanied by public health campaigns to increase adherence. [ABSTRACT FROM AUTHOR]

The Covid-19 disease has caused a world-wide pandemic with more than 60 million positive cases and more than 1.4 million deaths by the end of November 2020. As long as effective medical treatment and vaccination are not available, non-pharmaceutical interventions such as social distancing, self-isolation and quarantine as well as far-reaching shutdowns of economic activity and public life are the only available strategies to prevent the virus from spreading. These interventions must meet conflicting requirements where some objectives, like the minimization of disease-related deaths or the impact on health systems, demand for stronger counter-measures, while others, such as social and economic costs, call for weaker counter-measures. Therefore, finding the optimal compromise of counter-measures requires the solution of a multi-objective optimization problem that is based on accurate prediction of future infection spreading for all combinations of counter-measures under consideration. We present a strategy for construction and solution of such a multi-objective optimization problem with real-world applicability. The strategy is based on a micro-model allowing for accurate prediction via a realistic combination of person-centric data-driven human mobility and behavior, stochastic infection models and disease progression models including micro-level inclusion of governmental intervention strategies. For this micro-model, a surrogate macro-model is constructed and validated that is much less computationally expensive and can therefore be used in the core of a numerical solver for the multi-objective optimization problem. The resulting set of optimal compromises between counter-measures (Pareto front) is discussed and its meaning for policy decisions is outlined. [ABSTRACT FROM AUTHOR]

Background: COVID-19 vaccines are approved, vaccination campaigns are launched, and worldwide return to normality seems within close reach. Nevertheless, concerns about the safety of COVID-19 vaccines arose, due to their fast emergency approval. In fact, the problem of antibody-dependent enhancement was raised in the context of COVID-19 vaccines. Methods and findings: We introduce a complex extension of the model underlying the pandemic preparedness tool CovidSim 1.1 (http://covidsim.eu/) to optimize vaccination strategies with regard to the onset of campaigns, vaccination coverage, vaccination schedules, vaccination rates, and efficiency of vaccines. Vaccines are not assumed to immunize perfectly. Some individuals fail to immunize, some reach only partial immunity, and—importantly—some develop antibody-dependent enhancement, which increases the likelihood of developing symptomatic and severe episodes (associated with higher case fatality) upon infection. Only a fraction of the population will be vaccinated, reflecting vaccination hesitancy or contraindications. The model is intended to facilitate decision making by exploring ranges of parameters rather than to be fitted by empirical data. We parameterized the model to reflect the situation in Germany and predict increasing incidence (and prevalence) in early 2021 followed by a decline by summer. Assuming contact reductions (curfews, social distancing, etc.) to be lifted in summer, disease incidence will peak again. Fast vaccine deployment contributes to reduce disease incidence in the first quarter of 2021, and delay the epidemic outbreak after the summer season. Higher vaccination coverage results in a delayed and reduced epidemic peak. A coverage of 75%–80% is necessary to prevent an epidemic peak without further drastic contact reductions. Conclusions: With the vaccine becoming available, compliance with contact reductions is likely to fade. To prevent further economic damage from COVID-19, high levels of immunization need to be reached before next year's flu season, and vaccination strategies and disease management need to be flexibly adjusted. The predictive model can serve as a refined decision support tool for COVID-19 management. [ABSTRACT FROM AUTHOR]

Background: Given the economic and social divide that exists in South Africa, it is critical to manage the health response of its residents to the Covid-19 pandemic within the different socio-economic contexts that define the lived realities of individuals. Objective: The objective of this study is to analyse the Covid-19 preventive behaviour and the socio-economic drivers behind the health-response behaviour. Data: The study employs data from waves 1 and 2 of South Africa's nationally representative National Income Dynamics Study (NIDS)—Coronavirus Rapid Mobile Survey (CRAM). The nationally representative panel data has a sample of 7073 individuals in Wave 1 and 5676 individuals in Wave 2. Methods: The study uses bivariate statistics, concentration indices and multivariate estimation techniques, ranging from a probit, control-function approach, special-regressor method and seemingly unrelated regression to account for endogeneity while identifying the drivers of the response behaviour. Findings: The findings indicate enhanced behavioural responsiveness to Covid-19. Preventive behaviour is evolving over time; the use of face mask has overtaken handwashing as the most utilised preventive measure. Other measures, like social distancing, avoiding close contact, avoiding big groups and staying at home, have declined between the two periods of the study. There is increased risk perception with significant concentration among the higher income groups, the educated and older respondents. Our findings validate the health-belief model, with perceived risk, self-efficacy, perceived awareness and barriers to preventive strategy adoption identified as significant drivers of health-response behaviour. Measures such as social distancing, avoiding close contact, and the use of sanitisers are practised more by the rich and educated, but not by the low-income respondents. Conclusion: The respondents from lower socio-economic backgrounds are associated with optimism bias and face barriers to the adoption of preventive strategies. This requires targeted policy attention in order to make response behaviour effective. [ABSTRACT FROM AUTHOR]

Introduction: With over 500 000 infections and nearly 12 000 deaths, South Africa (SA) is the African epicenter of the current Coronavirus (COVID-19) pandemic. SA has implemented a 5-stage Risk-Adjusted Strategy which includes a phased national lockdown, requiring social distancing, frequent hand washing and wearing face masks. Strict adherence to this strategy is crucial to reducing COVID-19 transmission, flattening the curve, and preventing resurgence. As part of the 22-country International Citizens Project COVID-19 (ICPcovid), this study aimed to describe the SA adherence to the Risk-Adjusted Strategy and identify determinants of adherence. Method: During 24 April-15 May 2020, people were electronically invited, through social media platforms and a text blast, to complete an online survey, accessible via www.icpcovid.com. The survey investigated COVID-19 testing and preventative adherence measures, then used logistic regression analysis to identify predictors of adherence. Results: There were 951 participants, with 731(76.9%) 25 to 54 years. Most (672;70.7%) were female, and 705(74.1%) had a university degree. Since the epidemic started, 529(55.6%) and 436(45.9%) participants stated they were eating healthier and taking more vitamins, respectively. Only 82(8.6%) had been COVID-19 tested, and 1(1.2%) tested positive. In public, 905(95.2%) socially distanced, however 99(10.4%) participants had recently attended meetings with over ten people. Regular hand washing was practiced by 907(95.4%) participants, 774(81.4%) wore face masks and 854(89.8%) stayed home when they experienced flu-like symptoms. The odds of adhering to the guidelines were lower among men versus women (AOR 0.72, 95% confidence interval [CI] = 0.528, 0.971) and those who had flu-like symptoms (AOR 0.42, 95% CI = 0.277, 0.628). In contrast, increased odds were reported for those who reported increased vitamin intake (AOR 1.37, 95% CI = 1.044,1.798), and were either cohabiting or married (AOR 1.39, 95% CI = 1.042,1.847). Conclusion: Despite high reported adherence, face mask use and symptomatic individuals not self-isolating, were areas for improvement. However, these factors cannot solely account for SA's increasing COVID-19 cases. Larger general population studies are needed to identify other adherence predictors for a strengthened SA COVID-19 response. While the government must continue to educate the entire population on preventative measures, provide personal protective equipment and stress the importance of adherence, there also needs to be implementation of prioritised prevention strategies for men and single individuals to address their demonstrated lower adherence. [ABSTRACT FROM AUTHOR]

Objectives: The unprecedented worldwide social distancing response to COVID-19 resulted in a quick reversal of escalating case numbers. Recently, local governments globally have begun to relax social distancing regulations. Using the situation in Manitoba, Canada as an example, we estimated the impact that social distancing relaxation may have on the pandemic. Methods: We fit a mathematical model to empirically estimated numbers of people infected, recovered, and died from COVID-19 in Manitoba. We then explored the impact of social distancing relaxation on: (a) time until near elimination of COVID-19 (< one case per million), (b) time until peak prevalence, (c) proportion of the population infected within one year, (d) peak prevalence, and (e) deaths within one year. Results: Assuming a closed population, near elimination of COVID-19 in Manitoba could have been achieved in 4–6 months (by July or August) if there were no relaxation of social distancing. Relaxing to 15% of pre-COVID effective contacts may extend the local epidemic for more than two years (median 2.1). Relaxation to 50% of pre-COVID effective contacts may result in a peak prevalence of 31–38% of the population, within 3–4 months of initial relaxation. Conclusion: Slight relaxation of social distancing may immensely impact the pandemic duration and expected peak prevalence. Only holding the course with respect to social distancing may have resulted in near elimination before Fall of 2020; relaxing social distancing to 15% of pre-COVID-19 contacts will flatten the epidemic curve but greatly extend the duration of the pandemic. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had tremendous impact on Americans' lives including their personal and social behaviors. While people of all ages are affected in some way by the pandemic, older persons have been far more likely to suffer the most severe health consequences. For this reason, how people have responded to mitigating behaviors to COVID-19 may differ by age. Using a nationally representative sample from the longitudinal data of the Understanding America Study (UAS), we examined differentials in behavioral responses to COVID-19 by age and how they changed over the first three months of the pandemic. Behavioral responses and changes in behavior over time differed by age, type of behaviors and time reference. At the beginning of the pandemic (March, 2020), older and younger people were similar in their likelihood of engaging in preventive personal behaviors when controlling for other influences. As the pandemic progressed, however, older people adopted mitigating personal behavioral changes more than younger people, such that about 1–2 months after the pandemic started, older people were more likely to comply with suggested behaviors and regulations including practicing better hygiene, quarantining, and social distancing. One month into the pandemic, older people were less likely than younger people to engage in two of four risky behaviors. The change in risky behavior over time did not differ by age; but both younger and older people were more likely to engage in risky behaviors after two months. Being female, a member of a racial/ethnic minority group, higher socioeconomic status, having more COVID-19 cases in one's state of residence, a higher perceived risk for infection and dying, and a more left-leaning political orientation were related to adopting more pandemic mitigating behaviors. [ABSTRACT FROM AUTHOR]

At the beginning of the COVID-19 pandemic (10–14 March, 2020) we conducted a survey (n = 1028) of a nationally representative sample (age, sex, and locale) in Poland. Respondents indicated how strong they thought the threat was to themselves, to Poland, and the world. They also described their emotional reactions to the pandemic, which we used to calculate three scores: Anxiety, Hopelessness, and Panic. Respondents also indicated how often they engaged in various coping behaviors and how much they supported different types of economic sacrifice. We used these responses to calculate measures that we labelled as Spread Prevention (e.g., social distancing), Self-preservation (food stockpiling), and Economic Sacrifice (e.g., fighting COVID-19 regardless of the cost). Multiple regression analyses found that perceived threat to self was the most reliable predictor (positive) of emotional reactions and of coping behaviors, and that Anxiety was the most reliable predictor (positive) of Spread prevention and Economic sacrifice. Panic predicted (positively) Self-preservation. A series of mediation analyses found that Anxiety mediated relationships between threat and coping behaviors, and that Panic mediated the relationship between perceived threats and Self-preservation. In addition, we found that scores on all measures, except Panic, increased following the announcement of the first COVID-19 related fatality in Poland, which occurred on the third (middle) day of the study. The mediational relationships we found did not vary as a function of whether the data were collected before or after this announcement. The present results suggest that emotional reactions to perceived threats can serve an instrumental function by providing the motivation to engage in coping behaviors. Such a mechanism complements much research on stress that has focused on how coping mediates threat-emotion relationships. [ABSTRACT FROM AUTHOR]

Doctors and nurses in these weeks and months are busy in the trenches, fighting against a new invisible enemy: Covid-19. Cities are locked down and civilians are besieged in their own homes, to prevent the spreading of the virus. War-related terminology is commonly used to frame the discourse around epidemics and diseases. The discourse around the current epidemic makes use of war-related metaphors too, not only in public discourse and in the media, but also in the tweets written by non-experts of mass communication. We hereby present an analysis of the discourse around #Covid-19, based on a large corpus tweets posted on Twitter during March and April 2020. Using topic modelling we first analyze the topics around which the discourse can be classified. Then, we show that the WAR framing is used to talk about specific topics, such as the virus treatment, but not others, such as the effects of social distancing on the population. We then measure and compare the popularity of the WAR frame to three alternative figurative frames (MONSTER, STORM and TSUNAMI) and a literal frame used as control (FAMILY). The results show that while the FAMILY frame covers a wider portion of the corpus, among the figurative frames WAR, a highly conventional one, is the frame used most frequently. Yet, this frame does not seem to be apt to elaborate the discourse around some aspects involved in the current situation. Therefore, we conclude, in line with previous suggestions, a plethora of framing options—or a metaphor menu—may facilitate the communication of various aspects involved in the Covid-19-related discourse on the social media, and thus support civilians in the expression of their feelings, opinions and beliefs during the current pandemic. [ABSTRACT FROM AUTHOR]

The initial exponential growth rate of an epidemic is an important measure that follows directly from data at hand, commonly used to infer the basic reproduction number. As the growth rates λ(t) of tested positive COVID-19 cases have crossed the threshold in many countries, with negative numbers as surrogate for disease transmission deceleration, lockdowns lifting are linked to the behavior of the momentary reproduction numbers r(t), often called R0. Important to note that this concept alone can be easily misinterpreted as it is bound to many internal assumptions of the underlying model and significantly affected by the assumed recovery period. Here we present our experience, as part of the Basque Country Modeling Task Force (BMTF), in monitoring the development of the COVID-19 epidemic, by considering not only the behaviour of r(t) estimated for the new tested positive cases—significantly affected by the increased testing capacities, but also the momentary growth rates for hospitalizations, ICU admissions, deceased and recovered cases, in assisting the Basque Health Managers and the Basque Government during the lockdown lifting measures. Two different data sets, collected and then refined during the COVID-19 responses, are used as an exercise to estimate the momentary growth rates and reproduction numbers over time in the Basque Country, and the implications of using those concepts to make decisions about easing lockdown and relaxing social distancing measures are discussed. These results are potentially helpful for task forces around the globe which are now struggling to provide real scientific advice for health managers and governments while the lockdown measures are relaxed. [ABSTRACT FROM AUTHOR]

Background: Since the emergence of SARS-CoV-2, the virus that causes coronavirus disease (COVID-19) in late 2019, communities have been required to rapidly adopt community mitigation strategies rarely used before, or only in limited settings. This study aimed to examine the attitudes and beliefs of Australian adults towards the COVID-19 pandemic, and willingness and capacity to engage with these mitigation measures. In addition, we aimed to explore the psychosocial and demographic factors that are associated with adoption of recommended hygiene-related and avoidance-related behaviors. Methods: A national cross-sectional online survey of 1420 Australian adults (18 years and older) was undertaken between the 18 and 24 March 2020. The statistical analysis of the data included univariate and multivariate logistic regression analysis. Findings: The survey of 1420 respondents found 50% (710) of respondents felt COVID-19 would 'somewhat' affect their health if infected and 19% perceived their level of risk as high or very high. 84·9% had performed ≥1 of the three recommended hygiene-related behaviors and 93·4% performed ≥1 of six avoidance-related behaviors over the last one month. Adopting avoidance behaviors was associated with trust in government/authorities (aOR: 6.0, 95% CI 2.6–11·0), higher perceived rating of effectiveness of behaviors (aOR: 4·0, 95% CI: 1·8–8·7), higher levels of perceived ability to adopt social distancing strategies (aOR: 5.0, 95% CI: 1·5–9.3), higher trust in government (aOR: 6.0, 95% CI: 2.6–11.0) and higher level of concern if self-isolated (aOR: 1.8, 95% CI: 1.1–3.0). Interpretation: In the last two months, members of the public have been inundated with messages about hygiene and social (physical) distancing. However, our results indicate that a continued focus on supporting community understanding of the rationale for these strategies, as well as instilling community confidence in their ability to adopt or sustain the recommendations is needed. [ABSTRACT FROM AUTHOR]

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 circumstances in which 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, a total of 11,342 respondents, aged from 20 to 64 years, were recruited. About 85 percent reported practising the social distancing measures recommended by the government including more females than males and more older than younger participants. Frequent handwashing is conducted by 86 percent of all participants, 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 percent). Information from the central and local governments, received by 60 percent of the participants, was deemed trustworthy by 50 percent. However, the results also showed that about 20 percent 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, 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 behavioural changes using various means to reach and influence them. [ABSTRACT FROM AUTHOR]

State government-mandated social distancing measures have helped to slow the growth of the COVID-19 pandemic in the United States. Many of the current predictive models of the development of COVID-19, especially after mitigation efforts, partially rely on extrapolations from data collected in other countries. Since most states enacted stay-at-home orders towards the end of March, the resulting effects of social distancing should be reflected in the death and infection counts by the end of April. Using the data available through April 25th, we investigate the change in the infection rate due to the mitigation efforts and project death and infection counts through 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 have reduced their base reproduction number to a value less than one, stopping the exponential growth of the pandemic. We also project different scenarios after the mitigation is relaxed. [ABSTRACT FROM AUTHOR]