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Designing the Safe Reopening of US Towns Through High‐Resolution Agent‐Based Modeling

ABSTRACT: Abstract As COVID‐19 vaccine is being rolled out in the US, public health authorities are gradually reopening the economy. To date, there is no consensus on a common approach among local authorities. Here, a high‐resolution agent‐based model is proposed to examine the interplay between the increased immunity afforded by the vaccine roll‐out and the transmission risks associated with reopening efforts. The model faithfully reproduces the demographics, spatial layout, and mobility patterns of the town of New Rochelle, NY — representative of the urban fabric of the US. Model predictions warrant caution in the reopening under the current rate at which people are being vaccinated, whereby increasing access to social gatherings in leisure locations and households at a 1% daily rate can lead to a 28% increase in the fatality rate within the next three months. The vaccine roll‐out plays a crucial role on the safety of reopening: doubling the current vaccination rate is predicted to be sufficient for safe, rapid reopening. As COVID‐19 vaccine is rolling out, the economy is gradually reopening. This study offers scientific backing for the ongoing debate regarding the safety of reopening efforts via a high‐resolution computational model of a US town. Computational results suggest that the current vaccination rate can only support careful reopening. A swift return to normalcy would require at least doubling the vaccination speed.

SUBMITTER: Truszkowska A

PROVIDER: S-EPMC8420460 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe COVID-19 pandemic has induced historic educational disruptions. In December 2020, at least two-thirds of US public school students were not attending full-time in-person education. The Biden Administration has expressed that reopening schools is a priority.ObjectiveTo compare risks of SARS-COV-2 transmission in schools across different school-based prevention strategies and levels of community transmission.DesignWe developed an agent-based network model to simulate transmission in elementary and high school communities, including home, school, and inter-household interactions.SettingWe parameterized school structure based on average US classrooms, with elementary schools of 638 students and high schools of 1,451 students. We varied daily community incidence from 1 to 100 cases per 100,000 population. Patients (or Participants). We simulated students, faculty/staff, and adult household members.InterventionsWe evaluated isolation of symptomatic individuals, quarantine of an infected individual's contacts, reduced class sizes, alternative schedules, staff vaccination, and weekly asymptomatic screening.MeasurementsWe projected transmission among students, staff and families during one month following introduction of a single infection into a school. We also calculated the number of infections expected for a typical 8-week quarter, contingent on community incidence rate.ResultsSchool transmission risk varies according to student age and community incidence and is substantially reduced with effective, consistent mitigation measures. Nevertheless, when transmission occurs, it may be difficult to detect without regular, frequent testing due to the subclinical nature of most infections in children. Teacher vaccination can reduce transmission to staff, while asymptomatic screening both improves understanding of local circumstances and reduces transmission, facilitating five-day schedules at full classroom capacity.LimitationsThere is uncertainty about susceptibility and infectiousness of children and low precision regarding the effectiveness of specific prevention measures, particularly with emergence of new variants.ConclusionWith controlled community transmission and moderate school-based prevention measures, elementary schools can open with few in-school transmissions, while high schools require more intensive mitigation. Asymptomatic screening can both reduce transmission and provide useful information for decision-makers.

Project description:BackgroundThe COVID-19 pandemic has induced historic educational disruptions. In April 2021, about 40% of U.S. public school students were not offered full-time in-person education.ObjectiveTo assess the risk for SARS-CoV-2 transmission in schools.DesignAn agent-based network model was developed to simulate transmission in elementary and high school communities, including home, school, and interhousehold interactions.SettingSchool structure was parametrized to reflect average U.S. classrooms, with elementary schools of 638 students and high schools of 1451 students. Daily local incidence was varied from 1 to 100 cases per 100 000 persons.ParticipantsStudents, faculty, staff, and adult household members.InterventionIsolation of symptomatic individuals, quarantine of an infected individual's contacts, reduced class sizes, alternative schedules, staff vaccination, and weekly asymptomatic screening.MeasurementsTransmission was projected among students, staff, and families after a single infection in school and over an 8-week quarter, contingent on local incidence.ResultsSchool transmission varies according to student age and local incidence and is substantially reduced with mitigation measures. Nevertheless, when transmission occurs, it may be difficult to detect without regular testing because of the subclinical nature of most children's infections. Teacher vaccination can reduce transmission to staff, and asymptomatic screening improves understanding of local circumstances and reduces transmission.LimitationUncertainty exists about the susceptibility and infectiousness of children, and precision is low regarding the effectiveness of specific countermeasures, particularly with new variants.ConclusionWith controlled community transmission and moderate mitigation, elementary schools can open safety, but high schools require more intensive mitigation. Asymptomatic screening can facilitate reopening at higher local incidence while minimizing transmission risk.Primary funding sourceCenters for Disease Control and Prevention through the Council of State and Territorial Epidemiologists, National Institute of Allergy and Infectious Diseases, National Institute on Drug Abuse, and Facebook.

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Designing the Safe Reopening of US Towns Through High‐Resolution Agent‐Based Modeling

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