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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.
Afiliación
  • Sean M Moore; University of Notre Dame
  • Guido Espana; University of Notre Dame
  • T Alex Perkins; University of Notre Dame
  • Robert M Guido; Moncrief Army Health Clinic, Fort Jackson
  • Joaquin B Jucaban; Moncrief Army Health Clinic, Fort Jackson
  • Tara L Hall; Moncrief Army Health Clinic, Fort Jackson
  • Mark E Huhtanen; United States Army Training Center, Fort Jackson
  • Sheila A Peel; Walter Reed Army Institute of Research
  • Kayvon Modjarrad; Walter Reed Army Institute of Research
  • Shilpa Hakre; Walter Reed Army Institute of Research
  • Paul T Scott; Walter Reed Army Institute of Research
Preprint en En | PREPRINT-MEDRXIV | ID: ppmedrxiv-22282480
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. DisclaimerThe views expressed are those of the authors and should not be construed to represent the positions of the U.S. Army, the Department of Defense, or the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc.
Licencia
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Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Experimental_studies / Observational_studies / Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Preprint
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Experimental_studies / Observational_studies / Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Preprint