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Impact of school reopening on pandemic spread: A case study using an agent-based model for COVID-19

Infectious Disease Modelling 2021年第1期6卷 839-847页

作者： Hanisha Tatapudi Tapas K.Das Department of Industrial and Management System Engineering University of South FloridaTampaFLUSA

This article examines the impact of partial/full reopening of school/college campuses on the spread of a pandemic using COVID-19 as a case study.The study uses an agent-based simulation model that replicates community spread in an urban region of U.S.A.via daily social mixing of susceptible and infected individuals.Data representing population demographics,SARS-CoV-2 epidemiology,and social interventions guides the model's behavior,which is calibrated and validated using data reported by the government.The model indicates a modest but significant increase(8.15%)in the total number of reported cases in the region for a complete(100%)reopening compared to keeping schools and colleges fully virtual.For partial returns of 75%and 50%,the percent increases in the number of reported cases are shown to be small(2.87%and 1.26%,respectively)and statistically insignificant.The AB model also predicts that relaxing the stringency of the school safety protocol for sanitizing,use of mask,social distancing,testing,and quarantining and thus allowing the school transmission coefficient to double may result in a small increase in the number of reported infected cases(2.14%).Hence for pandemic outbreaks from viruses with similar characteristics as for SARS-CoV-2,keeping the schools and colleges open with a modest campus safety protocol and in-person attendance below a certain threshold may be advisable.

关键词： COVID-19 SARS-CoV-2 Agent-based simulation model school reopening school transmission rate Age-specific impact

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Social distancing and testing as optimal strategies against the spread of COVID-19 in the Rio Grande Valley of Texas

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Infectious Disease Modelling 2021年第1期6卷 729-742页

作者： Kristina P.Vatcheva Josef Sifuentes Tamer Oraby Jose Campo Maldonado Timothy Huber María Cristina Villalobos school of Mathematical&Statistical Sciences University of Texas Rio Grande ValleyBrownsvilleTX78520USA school of Mathematical&Statistical Sciences University of Texas Rio Grande ValleyEdinburgTX78539USA school of Medicine The University of Texas Rio Grande ValleyEdinburgTX78539USA

At the beginning of August 2020,the Rio Grande Valley(RGV)of Texas experienced a rapid increase of coronavirus disease 2019(abbreviated as COVID-19)cases and deaths.This study aims to determine the optimal levels of effective social distancing and testing to slow the virus spread at the outset of the pandemic.We use an age-stratified eight compartment epidemiological model to depict COVID-19 transmission in the community and within households.With a simulated 120-day outbreak period data we obtain a post 180-days period optimal control strategy solution.Our results show that easing social distancing between adults by the end of the 180-day period requires very strict testing a month later and then daily testing rates of 5%followed by isolation of positive cases.Relaxing social distancing rates in adults from 50%to 25%requires both children and seniors to maintain social distancing rates of 50%for nearly the entire period while maintaining maximum testing rates of children and seniors for 150 of the 180 days considered in this model.Children have higher contact rates which leads to transmission based on our model,emphasizing the need for caution when considering school reopenings.

关键词： COVID-19 Mathematical modeling Optimal control Rio Grande Valley(RGV) Testing and social distancing school reopening

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