scholarly journals Quantifying the Effects of Social Distancing on the Spread of COVID-19

2021 ◽  
Vol 18 (11) ◽  
pp. 5566
Author(s):  
Talal Daghriri ◽  
Ozlem Ozmen
Keyword(s):  
Complex Adaptive System ◽  
Linear Equations ◽  
The United States ◽  
The Other ◽  
Contact Tracing ◽  
Human Society ◽  
Infection Rates ◽  
Agent Based ◽  
Social Distancing ◽  
Modeling Studies

This paper studies the interplay between social distancing and the spread of the COVID-19 disease—a global pandemic that has affected most of the world’s population. Our goals are to (1) to observe the correlation between the strictness of social distancing policies and the spread of disease and (2) to determine the optimal adoption level of social distancing policies. The earliest instances of the virus were found in China, and the virus has reached the United States with devastating consequences. Other countries severely affected by the pandemic are Brazil, Russia, the United Kingdom, Spain, India, Italy, and France. Although it is impossible to stop it, it is possible to slow down its spread to reduce its impact on the society and economy. Governments around the world have deployed various policies to reduce the virus spread in response to the pandemic. To assess the effectiveness of these policies, the system’s dynamics of the society needs to be analyzed, which is generally not possible with mathematical linear equations or Monte Carlo methods because human society is a complex adaptive system with continuous feedback loops. Because of the challenges with the other methods, we chose agent-based methods to conduct our study. Moreover, recent agent-based modeling studies for the COVID-19 pandemic show significant promise in assisting decision-makers in managing the crisis by applying policies such as social distancing, disease testing, contact tracing, home isolation, emergency hospitalization, and travel prevention to reduce infection rates. Based on modeling studies conducted in Imperial College, increasing levels of interventions could slow the spread of disease and infection. We ran the model with six different percentages of social distancing while keeping the other parameters constant. The results show that social distancing affects the spread of COVID-19 significantly, in turn decreasing the spread of disease and infection rates when implemented at higher levels. We also validated these results by using the behavior space tool with ten experiments with varying social distancing levels. We conclude that applying and increasing social distancing policy levels leads to a significant reduction in infection spread and the number of deaths. Both experiments show that infection rates are reduced drastically when social distancing intervention is implemented between 80% to 100%.

scholarly journals Quantifying the Effects of Social Distancing on the Spread of COVID-19

2020 ◽  
Author(s):  
Talal Daghriri ◽  
Ozlem Ozmen
Keyword(s):  
The United States ◽  
Contact Tracing ◽  
World Population ◽  
Human Society ◽  
Infection Rates ◽  
Agent Based ◽  
Social Distancing ◽  
Modeling Studies ◽  
The Social ◽  
The World

AbstractThis paper studies the interplay between the social distancing and the spread of COVID-19 disease—a widely spread pandemic that has affected nearly most of the world population. Starting in China, the virus has reached the United States of America with devastating consequences. Other countries severely affected by the pandemic are Brazil, Russia, United Kingdom, Spain, India, Italy, and France. Even though it is not possible to eliminate the spread of the virus from the world or any other country, it might be possible to reduce its effect by decreasing the number of infected people. Implementing such policies needs a good understanding of the system’s dynamics, generally not possible with mathematical linear equations or Monte Carlo methods because human society is a complex adaptive system with complex and continuous feedback loops. As a result, we use agent-based methods to conduct our study. Moreover, recent agent-based modeling studies for the COVID-19 pandemic show significant promise assisting decision-makers in managing the crisis through applying some policies such as social distancing, disease testing, contact tracing, home isolation, providing good emergency and hospitalization strategies, and preventing traveling would lead to reducing the infection rates. Based on imperial college modeling studies that prove increasing levels of interventions could slow down the spread of disease and infection cases as much as possible, and taking into account that social distancing policy is considered to be the most important factor that was recommended to follow. Our proposed model is designed to test if increasing the social distancing policies strictness can slow down the spread of disease significantly or not, and find out what is the required safe level of social distancing. So, the model was run six times, with six different percentages of social distancing with keeping the other parameters levels fixed for all experiments. The results of our study show that social distancing affects the spread of COVID19 significantly, where the spread of disease and infection rates decrease once social distancing procedures are implemented at higher levels. Also, the behavior space tool was used to run ten experiments with different levels of social distancing, which supported the previous results. We concluded that applying and increasing social distancing policy levels led to significantly reduced infection rates, which result in decreasing deaths. Both types of experiments prove that infection rates are reduced dramatically when the level of social distancing intervention is implemented between 80% to 100%.

scholarly journals Evaluation of reopening strategies for educational institutions during COVID-19 through agent based simulation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ujjal K. Mukherjee ◽  
Subhonmesh Bose ◽  
Anton Ivanov ◽  
Sebastian Souyris ◽  
Sridhar Seshadri ◽  
...  
Keyword(s):  
Analytical Model ◽  
Contact Tracing ◽  
Educational Institutions ◽  
Model Parameters ◽  
Infection Rates ◽  
Agent Based ◽  
Social Distancing ◽  
Preventative Measures ◽  
Agent Based Simulations ◽  
Population Ratio

AbstractMany educational institutions have partially or fully closed all operations to cope with the challenges of the ongoing COVID-19 pandemic. In this paper, we explore strategies that such institutions can adopt to conduct safe reopening and resume operations during the pandemic. The research is motivated by the University of Illinois at Urbana-Champaign’s (UIUC’s) SHIELD program, which is a set of policies and strategies, including rapid saliva-based COVID-19 screening, for ensuring safety of students, faculty and staff to conduct in-person operations, at least partially. Specifically, we study how rapid bulk testing, contact tracing and preventative measures such as mask wearing, sanitization, and enforcement of social distancing can allow institutions to manage the epidemic spread. This work combines the power of analytical epidemic modeling, data analysis and agent-based simulations to derive policy insights. We develop an analytical model that takes into account the asymptomatic transmission of COVID-19, the effect of isolation via testing (both in bulk and through contact tracing) and the rate of contacts among people within and outside the institution. Next, we use data from the UIUC SHIELD program and 85 other universities to estimate parameters that describe the analytical model. Using the estimated parameters, we finally conduct agent-based simulations with various model parameters to evaluate testing and reopening strategies. The parameter estimates from UIUC and other universities show similar trends. For example, infection rates at various institutions grow rapidly in certain months and this growth correlates positively with infection rates in counties where the universities are located. Infection rates are also shown to be negatively correlated with testing rates at the institutions. Through agent-based simulations, we demonstrate that the key to designing an effective reopening strategy is a combination of rapid bulk testing and effective preventative measures such as mask wearing and social distancing. Multiple other factors help to reduce infection load, such as efficient contact tracing, reduced delay between testing and result revelation, tests with less false negatives and targeted testing of high-risk class among others. This paper contributes to the nascent literature on combating the COVID-19 pandemic and is especially relevant for educational institutions and similarly large organizations. We contribute by providing an analytical model that can be used to estimate key parameters from data, which in turn can be used to simulate the effect of different strategies for reopening. We quantify the relative effect of different strategies such as bulk testing, contact tracing, reduced infectivity and contact rates in the context of educational institutions. Specifically, we show that for the estimated average base infectivity of 0.025 ($$R_0 = 1.82$$ R 0 = 1.82 ), a daily number of tests to population ratio T/N of 0.2, i.e., once a week testing for all individuals, is a good indicative threshold. However, this test to population ratio is sensitive to external infectivities, internal and external mobilities, delay in getting results after testing, and measures related to mask wearing and sanitization, which affect the base infection rate.

scholarly journals SAFE REOPENING STRATEGIES FOR EDUCATIONAL INSTITUTIONS DURING COVID-19: A DATA-DRIVEN AGENT-BASED APPROACH

2020 ◽  
Author(s):  
Ujjal K mukherjee ◽  
Subhonmesh Bose ◽  
Anton Ivanov ◽  
Sebastian Souyris ◽  
Sridhar Seshadri ◽  
...  
Keyword(s):  
Analytical Model ◽  
Contact Tracing ◽  
Educational Institutions ◽  
Model Parameters ◽  
Infection Rates ◽  
Agent Based ◽  
Social Distancing ◽  
Preventative Measures ◽  
Agent Based Simulations ◽  
Population Ratio

AbstractMany educational institutions have partially or fully closed all operations to cope with the challenges of the ongoing COVID-19 pandemic. In this paper, we explore strategies that such institutions can adopt to conduct safe reopening and resume operations during the pandemic. The research is motivated by the University of Illinois at Urbana-Champaign’s (UIUC’s) SHIELD program, (https://www.uillinois.edu/shield), which is a set of policies and strategies, including rapid saliva-based COVID-19 screening, for ensuring safety of students, faculty and staff to conduct in-person operations, at least partially. Specifically, we study how rapid bulk testing, contact tracing and preventative measures such as mask wearing, sanitization, and enforcement of social distancing can allow institutions to manage the epidemic spread.Research DesignThis work combines the power of analytical epidemic modeling, data analysis and agent-based simulations to derive policy insights. We develop an analytical model that takes into account the asymptomatic transmission of COVID-19, the effect of isolation via testing (both in bulk and through contact tracing) and the rate of contacts among people within and outside the institution. Next, we use data from the UIUC SHIELD program and 85 other universities to estimate parameters that describe the analytical model. Using the estimated parameters, we finally conduct agent-based simulations with various model parameters to evaluate testing and reopening strategies.ResultsThe parameter estimates from UIUC and other universities show similar trends. For example, infection rates at various institutions grow rapidly in certain months and this growth correlates positively with infection rates in counties where the universities are located. Infection rates are also shown to be negatively correlated with testing rates at the institutions. Through agent-based simulations, we demonstrate that the key to designing an effective reopening strategy is a combination of rapid bulk testing and effective preventative measures such as mask wearing and social distancing. Multiple other factors help to reduce infection load, such as efficient contact tracing, reduced delay between testing and result revelation, tests with less false negatives and targeted testing of high-risk class among others.ContributionsThis paper contributes to the nascent literature on combating the COVID-19 pandemic and is especially relevant for educational institutions and similarly large organizations. We contribute by providing an analytical model that can be used to estimate key parameters from data, which in turn can be used to simulate the effect of different strategies for reopening. We quantify the relative effect of different strategies such as bulk testing, contact tracing, reduced infectivity and contact rates in the context of educational institutions. Specifically, we show that for the estimated average base infectivity of 0.025 (R0 = 1.82), a daily number of tests to population ratio T/N of 0.2, i.e., once a week testing for all individuals, is a good indicative threshold. However, this test to population ratio is sensitive to external infectivities, internal and external mobilities, delay in getting results after testing, and measures related to mask wearing and sanitization, which affect the base infectivity.

scholarly journals COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society

2021 ◽  
pp. 0272989X2110030
Author(s):  
Serin Lee ◽  
Zelda B. Zabinsky ◽  
Judith N. Wasserheit ◽  
Stephen M. Kofsky ◽  
Shan Liu
Keyword(s):  
Large City ◽  
Face Mask ◽  
School Closure ◽  
Contact Tracing ◽  
The Novel ◽  
Agent Based ◽  
Social Distancing ◽  
Variable Compliance ◽  
Novel Coronavirus ◽  
Nonpharmaceutical Interventions

As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021.

scholarly journals How effective was Newfoundland & Labrador’s travel ban to prevent the spread of COVID-19? An agent-based analysis

2021 ◽  
Author(s):  
Dionne M. Aleman ◽  
Benjamin Z. Tham ◽  
Sean J. Wagner ◽  
Justin Semelhago ◽  
Asghar Mohammadi ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Spatial Location ◽  
Contact Tracing ◽  
Infection Rates ◽  
Case Scenario ◽  
Agent Based ◽  
Individual Level ◽  
Transmission Rates ◽  
Imported Cases ◽  
The Uk

AbstractBackgroundTo prevent the spread of COVID-19 in Newfoundland & Labrador (NL), NL implemented a wide travel ban in May 2020. We estimate the effectiveness of this travel ban using a customized agent-based simulation (ABS).MethodsWe built an individual-level ABS to simulate the movements and behaviors of every member of the NL population, including arriving and departing travellers. The model considers individual properties (spatial location, age, comorbidities) and movements between environments, as well as age-based disease transmission with pre-symptomatic, symptomatic, and asymptomatic transmission rates. We examine low, medium, and high travel volume, traveller infection rates, and traveller quarantine compliance rates to determine the effect of travellers on COVID spread, and the ability of contact tracing to contain outbreaks.ResultsInfected travellers increased COVID cases by 2-52x (8-96x) times and peak hospitalizations by 2-49x (8-94x), with (without) contact tracing. Although contact tracing was highly effective at reducing spread, it was insufficient to stop outbreaks caused by travellers in even the best-case scenario, and the likelihood of exceeding contact tracing capacity was a concern in most scenarios. Quarantine compliance had only a small impact on COVID spread; travel volume and infection rate drove spread.InterpretationNL’s travel ban was likely a critically important intervention to prevent COVID spread. Even a small number of infected travellers can play a significant role in introducing new chains of transmission, resulting in exponential community spread and significant increases in hospitalizations, while outpacing contact tracing capabilities. With the presence of more transmissible variants, e.g., the UK variant, prevention of imported cases is even more critical.

scholarly journals The Effect of Social Distancing and Personal Protective Equipment on the Outbreak of SARS-COVID-2: An Agent-Based Modeling Approach

2021 ◽  
Author(s):  
Sohrab Effati ◽  
Eman Tavakoli
Keyword(s):  
Personal Protective Equipment ◽  
Disease Outbreaks ◽  
Agent Based Modeling ◽  
Control Measures ◽  
Protective Equipment ◽  
Human Society ◽  
Agent Based ◽  
Social Distancing ◽  
Contagious Diseases ◽  
Biological Phenomena

Abstract Biological phenomena such as disease outbreaks can be modeled as a subset of natural phenomena. Coronaviruses, first identified in the 1960s, are contagious diseases being constantly in the area of research and modeling in human society. The latest version of this group, SARS-COVID-2, has caused the Coronavirus disease one of the greatest pandemics in recent years. Due to the nature of this disease, being aware of the ways of transmission and how to prevent it, including social distancing and the use of personal protective equipment (PPE) to improve the general condition of society is of particular importance. In this study, dynamic systems (Susceptible, Exposed, Infected, Asymptomatic, and Recovered individuals as SEIAR), control systems, and Agent-based modeling (ABM) were used to forecast the behavior of the SARS-COVID-2 virus in the community. The numerical results display the undeniable impact of adhering to hygiene protocols. A significant decline in the number of people with the Coronavirus disease, after applying the control measures, indicates their remarkable impact on reducing the disease peak. Moreover, the result of the Agent-based simulation, which is in four ideal cases, show a significant reduction in the number of death as well.

scholarly journals The COVID States Project #26: Trajectory of COVID-19-related behaviors

2021 ◽  
Author(s):  
David Lazer ◽  
Mauricio Santillana ◽  
Roy H. Perlis ◽  
Alexi Quintana ◽  
Katherine Ognyanova ◽  
...  
Keyword(s):  
State Level ◽  
The United States ◽  
Contact Tracing ◽  
Upper Midwest ◽  
Social Distancing ◽  
Current State ◽  
Change Behavior ◽  
Current Prevalence ◽  
The Us ◽  
National Trends

The current state of the COVID-19 pandemic in the United States is dire, with circumstances in the Upper Midwest particularly grim. In contrast, multiple countries around the world have shown that temporary changes in human behavior and consistent precautions, such as effective testing, contact tracing, and isolation, can slow transmission of COVID-19, allowing local economies to remain open and societal activities to approach normalcy as of today. These include island countries such as New Zealand, Taiwan, Iceland and Australia, and continental countries such as Norway, Uruguay, Thailand, Finland, and South Korea. These successes demonstrate that coordinated action to change behavior can control the pandemic. In this report, we evaluate how the human behaviors that have been shown to inhibit the spread of COVID-19 have evolved across the US since April, 2020.Our report is based on surveys that the COVID States Project has been conducting approximately every month since April in all 50 US states plus the District of Columbia. We address four primary questions:1) What are the national trends in social distancing behaviors and mask wearing since April?2) What are the trends among particular population subsets?3) What are the trends across individual states plus DC?4) What is the relationship, at the state level, between social distancing behaviors and mask wearing with the current prevalence of COVID-19?

scholarly journals A path out of COVID-19 quarantine: an analysis of policy scenarios

2020 ◽  
Author(s):  
Lia Humphrey ◽  
Edward W. Thommes ◽  
Roie Fields ◽  
Naseem Hakim ◽  
Ayman Chit ◽  
...  
Keyword(s):  
Latent Infection ◽  
Average Rate ◽  
The United States ◽  
Contact Tracing ◽  
Brute Force ◽  
Social Distancing ◽  
Testing Rate ◽  
Universal Testing ◽  
The World ◽  
Brute Force Approach

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.Significance StatementWe demonstrate how current quarantine measures can be lifted after the current pandemic wave by large-scale, frequent-testing and contact tracing on the remaining susceptible populations. We present an analysis of the two major strategies currently implemented around the world against COVID-19: Social distancing & shelter-in-place measures to protect the susceptible, and testing & contact-tracing to identify, isolate and treat the infected. 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.

scholarly journals Identifying airborne transmission as the dominant route for the spread of COVID-19

2020 ◽  
Vol 117 (26) ◽  
pp. 14857-14863 ◽  
Author(s):  
Renyi Zhang ◽  
Yixin Li ◽  
Annie L. Zhang ◽  
Yuan Wang ◽  
Mario J. Molina
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Effective Means ◽  
The United States ◽  
Mitigation Measures ◽  
Contact Tracing ◽  
Protective Measure ◽  
Airborne Transmission ◽  
Social Distancing

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 75,000 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.

scholarly journals American Indian/Alaska Native community infrastructure limitations amid the COVID-19 threat

2021 ◽  
Vol 11 (8) ◽  
pp. 62
Author(s):  
Christine Samuel-Nakamura ◽  
Felicia Schanche Hodge
Keyword(s):  
Health Education ◽  
American Indian ◽  
Alaska Native ◽  
Preventive Measures ◽  
Community Education ◽  
The United States ◽  
Telecommunication Networks ◽  
Contact Tracing ◽  
Ecological Approach ◽  
Social Distancing

Objective: The recent SARS-CoV-2 (COVID-19) pandemic that is spreading throughout the nation is a particular threat to American Indian and Alaska Native (AI/AN) communities. The use of recommended methods to prevent or mitigate the spread of the virus, such as hand washing, social distancing, masks, contact tracing and community education is highly problematic at many of these sites. The objective of this paper is to identify and examine structural or cultural barriers to implementing COVID-19 recommendations on select reservation sites.Methods: A qualitative approach that collected and analyzed data from existing sources including newsletter articles, relevant policies and other published reports was instituted in the Spring of 2020. The Centers for Disease Control and Prevention (CDC) policies regarding COVID-19 recommendations to halt the spread of the virus were selected as the standard for COVID-19 prevention, surveillance and mitigation. News articles between March 1, 2020 and December 1, 2020 were identified using various search engines and tribal websites. Information from news resources, including literature reviews, newsletter articles, social media reports, and tribal policy announcements, were gathered and reviewed. Two U.S. southwestern communities are used as examples for the review.Results: Data collected from various sources paint a picture of American Indian communities that lack adequate community infrastructures, and have problems of residential isolation, close living quarters, and contaminated and scarce water supplies. Unsafe or limited water restricts handwashing. Limited informational tools, such as telephone, internet, computer and newsletters, restricted adequate notification of the novel coronavirus to American Indian reservation communities. Often, the lack of a physical home address can create barriers to healthcare accessibility and surveillance, as it limits the identification and access to households. In addition, many traditional cultures of AI/ANs emphasize the interrelatedness of all in nature and thus require an ecological approach to health education and preventive measures, identified as a limitation for COVID-19 surveillance and mitigation.Conclusions: AI/AN communities face a serious threat of contracting COVID-19. Four key infrastructure limitations to effective COVID-19 prevention, surveillance and mitigation were identified: limited access to safe water, deficient telecommunication networks (telephone, internet, and television), housing isolation and shortages, and inadequate medical services – are experienced by many AI/AN communities. Although there are 574 federally recognized tribes in the United States, the two identified in this study subscribe to an ecological approach to health education and preventive measures in that they believe in the interrelatedness of all things in nature. Surveillance questions may be misunderstood or seem invasive and prevention measures (masks, social distancing, and handwashing) may seem to be extreme measures to groups so close to the environment. Together, these present serious barriers to prevention and mitigation of the COVID-19 virus in this underserved population.

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