SurviveCovid-19 - An Educational Game to Facilitate Habituation of Social Distancing and Other Health Measures for Covid-19 Pandemic

AbstractTo ensure the safe operation of schools, workplaces, nursing homes, and other businesses during COVID-19 pandemic there is an urgent need to develop cost-effective public health strategies. Here we focus on the cruise industry which was hit early by the COVID-19 pandemic, with more than 40 cruise ships reporting COVID-19 infections. We apply mathematical modeling to assess the impact of testing strategies together with social distancing protocols on the spread of the novel coronavirus during ocean cruises using an individual-level stochastic model of the transmission dynamics of COVID-19. We model the contact network, the potential importation of cases arising during shore excursions, the temporal course of infectivity at the individual level, the effects of social distancing strategies, different testing scenarios characterized by the test’s sensitivity profile, and testing frequency. Our findings indicate that PCR testing at embarkation and daily testing of all individuals aboard, together with increased social distancing and other public health measures, should allow for rapid detection and isolation of COVID-19 infections and dramatically reducing the probability of onboard COVID-19 community spread. In contrast, relying only on PCR testing at embarkation would not be sufficient to avert outbreaks, even when implementing substantial levels of social distancing measures.

Download Full-text

Mask-wearing and social distancing: Evidence from a video-observational and natural-experimental study of public space behavior during the COVID-19 pandemic

10.31234/osf.io/ep8jg ◽

2021 ◽

Author(s):

Lasse Suonperä Liebst ◽

Peter Ejbye-Ernst ◽

Marijn de Bruin ◽

Josephine Thomas ◽

Marie Rosenkrantz Lindegaard

Keyword(s):

Public Space ◽

Experimental Approach ◽

Observational Evidence ◽

Protective Measure ◽

Social Distancing ◽

Health Measures ◽

Sense Of Security ◽

False Sense ◽

Dutch Cities ◽

Natural Experimental Study

Background: Face masks have been widely employed as a personal protective measure during the COVID-19 pandemic. However, concerns remain that masks create a false sense of security that reduces adherence to other public health measures, including social distancing. Purpose: This paper tested whether mask-wearing was negatively associated with social distancing compliance. Methods: In two studies, we combined video-observational records of public mask-wearing in two Dutch cities with a natural-experimental approach to evaluate the effect of an area-based mask mandate. Results: We found no observational evidence of an association between mask-wearing and social distancing (Study 1: p = .398; Study 2: p = .511), but found a positive link between crowding and social distancing violations (Study 1: p < .001; Study 2: p < .001). Our natural-experimental analysis showed that an area-based mask mandate did not significantly affect social distancing or crowding levels (Study 2: p = .781 and p = .126, respectively). Conclusions: Our results alleviate the concern that mask use reduces social distancing compliance or increases crowding levels. On the other hand, crowding reduction may be a viable strategy to mitigate social distancing violations.

Download Full-text

Situating ‘careful surveillance’

International Journal of Cultural Studies ◽

10.1177/1367877921997450 ◽

2021 ◽

pp. 136787792199745

Author(s):

Mark Andrejevic ◽

Hugh Davies ◽

Ruth DeSouza ◽

Larissa Hjorth ◽

Ingrid Richardson

Keyword(s):

Public Health ◽

Public Space ◽

Social Care ◽

Cultural Practices ◽

Contact Tracing ◽

Social Distancing ◽

Health Measures ◽

Relationship Of ◽

The Impact ◽

The Relationship

In this article we explore preliminary findings from the study COVIDSafe and Beyond: Perceptions and Practices conducted in Australia in 2020. The study involved a survey followed by interviews, and aimed to capture the dynamic ways in which members of the Australian public perceive the impact of Covid practices – especially public health measures like the introduction of physical and social distancing, compulsory mask wearing, and contact tracing. In the rescripting of public space, different notions of formal and informal surveillance, along with different textures of mediated and social care, appeared. In this article, we explore perceptions around divergent forms of surveillance across social, technological, governmental modes, and the relationship of surveillance to care in our media and cultural practices. What does it mean to care for self and others during a pandemic? How does care get enacted in, and through, media interfaces and public interaction?

Download Full-text

A compendium of evidence related to ‘social distancing’measure in view of the spread of COVID-19 pandemic

Healthline ◽

10.51957/healthline_141_2020 ◽

2020 ◽

Vol 11 (2) ◽

pp. 120-124

Author(s):

Anuradha Shah ◽

Kunal Shah

Keyword(s):

Public Health ◽

Close Contact ◽

Physical Distance ◽

Physical Contact ◽

Definitive Treatment ◽

Infected Person ◽

Social Distancing ◽

Influenza Pandemics ◽

Health Measures

With no definitive treatment in place to date for the COVID-19 pandemic, reliance on public health measures is of utmost importance. Social distancing requires maintaining a physical distance of at least one meter between people and reducing the number of times people come into close contact with each other. Modeling evidence from past influenza pandemics and current experiences with COVID-19 indicates the role of SD in delaying the spread of the virus by reducing the probability that uninfected person will come into physical contact with an infected person.

Download Full-text

Isolation, quarantine, social distancing and community containment: pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak

Journal of Travel Medicine ◽

10.1093/jtm/taaa020 ◽

2020 ◽

Vol 27 (2) ◽

Cited By ~ 477

Author(s):

A Wilder-Smith ◽

D O Freedman

Keyword(s):

Public Health ◽

Pivotal Role ◽

The Novel ◽

Movement Restriction ◽

Social Distancing ◽

Health Measures ◽

Novel Coronavirus

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.

Download Full-text

Mathematical models and the coronavirus, COVID-19

Colombia Medica ◽

10.25100/cm.v51i2.4277 ◽

2020 ◽

Author(s):

Elvia Karina Grillo Ardila ◽

Luis Eduardo Bravo Ocaña ◽

Rodrigo Guerrero ◽

Julián Santaella-Tenorio

Keyword(s):

Public Health ◽

Mathematical Models ◽

Health Systems ◽

Public Policies ◽

Virus Spread ◽

Social Distancing ◽

Health Measures ◽

Sociocultural Contexts ◽

The Difference

Currently, there are several mathematical models that have been developed to understand the dynamics of COVID-19 infection. However, the difference in the sociocultural contexts between countries requires the specific adjustment of these estimates to each scenario. This article analyses the main elements used for the construction of models from epidemiological patterns, to describe the interaction, explain the dynamics of infection and recovery, and to predict possible scenarios that may arise with the introduction of public health measures such as social distancing and quarantines, specifically in the case of the pandemic unleashed by the new SARS-CoV-2/COVID-19 virus. Comment: Mathematical models are highly relevant for making objective and effective decisions to control and eradicate the disease. These models used for COVID-19 have supported and will continue to provide information for the selection and implementation of programs and public policies that prevent associated complications, reduce the speed of the virus spread and minimize the occurrence of severe cases of the disease that may collapse health systems.

Download Full-text

Mathematical Parameters of the COVID-19 Epidemic in Brazil and Evaluation of the Impact of Different Public Health Measures

Biology ◽

10.3390/biology9080220 ◽

2020 ◽

Vol 9 (8) ◽

pp. 220 ◽

Cited By ~ 3

Author(s):

Renato M. Cotta ◽

Carolina P. Naveira-Cotta ◽

Pierre Magal

Keyword(s):

Public Health ◽

Initial Conditions ◽

Transmission Rate ◽

Time Variable ◽

Health Interventions ◽

Public Health Interventions ◽

Problem Model ◽

Social Distancing ◽

Health Measures ◽

The Impact

A SIRU-type epidemic model is employed for the prediction of the COVID-19 epidemy evolution in Brazil, and analyze the influence of public health measures on simulating the control of this infectious disease. The proposed model allows for a time variable functional form of both the transmission rate and the fraction of asymptomatic infectious individuals that become reported symptomatic individuals, to reflect public health interventions, towards the epidemy control. An exponential analytical behavior for the accumulated reported cases evolution is assumed at the onset of the epidemy, for explicitly estimating initial conditions, while a Bayesian inference approach is adopted for the estimation of parameters by employing the direct problem model with the data from the first phase of the epidemy evolution, represented by the time series for the reported cases of infected individuals. The evolution of the COVID-19 epidemy in China is considered for validation purposes, by taking the first part of the dataset of accumulated reported infectious individuals to estimate the related parameters, and retaining the rest of the evolution data for direct comparison with the predicted results. Then, the available data on reported cases in Brazil from 15 February until 29 March, is used for estimating parameters and then predicting the first phase of the epidemy evolution from these initial conditions. The data for the reported cases in Brazil from 30 March until 23 April are reserved for validation of the model. Then, public health interventions are simulated, aimed at evaluating the effects on the disease spreading, by acting on both the transmission rate and the fraction of the total number of the symptomatic infectious individuals, considering time variable exponential behaviors for these two parameters. This first constructed model provides fairly accurate predictions up to day 65 below 5% relative deviation, when the data starts detaching from the theoretical curve. From the simulated public health intervention measures through five different scenarios, it was observed that a combination of careful control of the social distancing relaxation and improved sanitary habits, together with more intensive testing for isolation of symptomatic cases, is essential to achieve the overall control of the disease and avoid a second more strict social distancing intervention. Finally, the full dataset available by the completion of the present work is employed in redefining the model to yield updated epidemy evolution estimates.

Download Full-text

Following Health Measures in the Pandemic: A Matter of Values?

Frontiers in Psychology ◽

10.3389/fpsyg.2021.731799 ◽

2021 ◽

Vol 12 ◽

Author(s):

Carolin Schuster

Keyword(s):

Health Behaviors ◽

Motivational Factors ◽

The Other ◽

Policy Support ◽

Perceived Efficacy ◽

Social Distancing ◽

Health Measures ◽

Other Hand ◽

Self Interest ◽

Experimental Effect

Three studies (N = 887) tested the hypothesis that value consistency predicts intended coronavirus disease-2019 (COVID-19) health behaviors and overrides other utility-based motivational factors. Accordingly, Study 1 showed that intentions of social distancing were higher if it was perceived as more value-consistent. The higher value consistency, the less self-interest inconsistency, and the perceived efficacy of social distancing mattered for intentions. On the other hand, Study 2 failed to induce value consistency experimentally. However, correlative results show a moderation pattern similar to Study 1 regarding social distancing intentions, policy support, and devaluation of transgressors. In Study 3, higher value consistency of vaccination reduced the experimental effect of prosocial efficacy but not the effect of self-interest efficacy of the vaccine. The findings are discussed regarding theoretical implications for the interplay of values and utility in motivation. In addition, implications for the potentially ambivalent effects of appealing to values to increase compliance are discussed.

Download Full-text

Flexible, Freely Available Stochastic Individual Contact Model for Exploring COVID-19 Intervention and Control Strategies: Development and Simulation (Preprint)

10.2196/preprints.18965 ◽

2020 ◽

Cited By ~ 4

Author(s):

Timothy Churches ◽

Louisa Jorm

Keyword(s):

Public Health ◽

Open Source ◽

Health Interventions ◽

Social Distancing ◽

The Public ◽

Epidemic Curve ◽

Health Measures ◽

Local Areas ◽

Individual Contact ◽

Sydney Australia

BACKGROUND Throughout March 2020, leaders in countries across the world were making crucial decisions about how and when to implement public health interventions to combat the coronavirus disease (COVID-19). They urgently needed tools to help them to explore what will work best in their specific circumstances of epidemic size and spread, and feasible intervention scenarios. OBJECTIVE We sought to rapidly develop a flexible, freely available simulation model for use by modelers and researchers to allow investigation of how various public health interventions implemented at various time points might change the shape of the COVID-19 epidemic curve. METHODS “COVOID” (COVID-19 Open-Source Infection Dynamics) is a stochastic individual contact model (ICM), which extends the ICMs provided by the open-source EpiModel package for the R statistical computing environment. To demonstrate its use and inform urgent decisions on March 30, 2020, we modeled similar intervention scenarios to those reported by other investigators using various model types, as well as novel scenarios. The scenarios involved isolation of cases, moderate social distancing, and stricter population “lockdowns” enacted over varying time periods in a hypothetical population of 100,000 people. On April 30, 2020, we simulated the epidemic curve for the three contiguous local areas (population 287,344) in eastern Sydney, Australia that recorded 5.3% of Australian cases of COVID-19 through to April 30, 2020, under five different intervention scenarios and compared the modeled predictions with the observed epidemic curve for these areas. RESULTS COVOID allocates each member of a population to one of seven compartments. The number of times individuals in the various compartments interact with each other and their probability of transmitting infection at each interaction can be varied to simulate the effects of interventions. Using COVOID on March 30, 2020, we were able to replicate the epidemic response patterns to specific social distancing intervention scenarios reported by others. The simulated curve for three local areas of Sydney from March 1 to April 30, 2020, was similar to the observed epidemic curve in terms of peak numbers of cases, total numbers of cases, and duration under a scenario representing the public health measures that were actually enacted, including case isolation and ramp-up of testing and social distancing measures. CONCLUSIONS COVOID allows rapid modeling of many potential intervention scenarios, can be tailored to diverse settings, and requires only standard computing infrastructure. It replicates the epidemic curves produced by other models that require highly detailed population-level data, and its predicted epidemic curve, using parameters simulating the public health measures that were enacted, was similar in form to that actually observed in Sydney, Australia. Our team and collaborators are currently developing an extended open-source COVOID package comprising of a suite of tools to explore intervention scenarios using several categories of models.

Download Full-text

Sociodemographic and Psychological Correlates of Compliance with the COVID-19 Public Health Measures in France

Canadian Journal of Political Science ◽

10.1017/s0008423920000335 ◽

2020 ◽

Vol 53 (2) ◽

pp. 253-258 ◽

Cited By ~ 13

Author(s):

Sylvain Brouard ◽

Pavlos Vasilopoulos ◽

Michael Becher

Keyword(s):

Public Health ◽

Individual Differences ◽

Mortality Rates ◽

Election Study ◽

Daily Lives ◽

Social Distancing ◽

Health Measures ◽

Psychological Correlates ◽

The World ◽

Using Data

The COVID-19 disease was first identified in Wuhan, China, in December 2019, having since spread rapidly across the world. The infection and mortality rates of the disease have forced governments to implement a wave of public health measures. Depending on the context, these range from the implementation of simple hygienic rules to measures such as social distancing or lockdowns that cause major disruptions in citizens’ daily lives. The success of these crucial public health measures rests on the public's willingness to comply. However, individual differences in following the official public health recommendations for stopping the spread of COVID-19 have not yet to our knowledge been assessed. This study aims to fill this gap by assessing the sociodemographic and psychological correlates of implementing public health recommendations that aim to halt the COVID-19 pandemic. We investigate these associations in the context of France, one of the countries that has been most severely affected by the pandemic, and which ended up under a nationwide lockdown on March 17. In the next sections we describe our theoretical expectations over the associations between sociodemographics, personality, ideology, and emotions with abiding by the COVID-19 public health measures. We then test these hypotheses using data from the French Election Study.

Download Full-text