Community Incidence Patterns Drive the Risk of SARS-CoV-2 Outbreaks and Alter Intervention Impacts in a High-Risk Institutional Setting.

Sean M. Moore,Guido Espana,T. Alex Perkins, Robert M. Guido,Joaquin B. Jucaban,Tara L. Hall,Mark E. Huhtanen,Sheila A. Peel,Kayvon Modjarrad,Shilpa Hakre,Paul T. Scott

Epidemics（2023）SCI 2区

Univ Notre Dame

Cited 2|Views3

Abstract

Optimization of control measures for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in high-risk institutional settings (e.g., prisons, nursing homes, or military bases) depends on how transmission dynamics in the broader community influence outbreak risk locally. We calibrated an individual-based transmission model of a military training camp to the number of RT-PCR positive trainees throughout 2020 and 2021. The predicted number of infected new arrivals closely followed adjusted national incidence and increased early outbreak risk after accounting for vaccination coverage, masking compliance, and virus variants. Outbreak size was strongly correlated with the predicted number of off-base infections among staff during training camp. In addition, off-base infections reduced the impact of arrival screening and masking, while the number of infectious trainees upon arrival reduced the impact of vaccination and staff testing. Our results highlight the importance of outside incidence patterns for modulating risk and the optimal mixture of control measures in institutional settings.

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Key words

SARS-CoV-2,COVID-19,Agent-based model,Epidemiology,Disease dynamics,High-risk settings,Forecasting

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