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.

The authors have declared no competing interest.

Support for this work was provided by the Defense Health Program, U.S. Department of Defense and was supported by a contract from the U.S. Army Medical Research and Development Command to the University of Notre Dame.

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The University of Notre Dame Institutional Review Board (IRB) of the University of Notre Dame waived ethical approval for this work

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For questions related to the SARS-CoV-2 testing data used for model calibration, contact the Fort Jackson Public Affairs Office at usarmy.jackson.93-sig-bde.mbx.atzj-pao@army.mil. All publicly available data and all code used in this analysis are available at https://github.com/confunguido/prioritizing_interventions_basic_training