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Projecting Quarantine Utilization During a Pandemic.
Li, Wenrui; Kolaczyk, Eric D; White, Laura F.
Affiliation
  • Li W; Wenrui Li is with the Department of Mathematics and Statistics, Boston University, Boston, MA. Eric D. Kolaczyk is with the Department of Mathematics and Statistics and the Hariri Institute for Computing, Boston University. Laura F. White is with the Department of Biostatistics, Boston University.
  • Kolaczyk ED; Wenrui Li is with the Department of Mathematics and Statistics, Boston University, Boston, MA. Eric D. Kolaczyk is with the Department of Mathematics and Statistics and the Hariri Institute for Computing, Boston University. Laura F. White is with the Department of Biostatistics, Boston University.
  • White LF; Wenrui Li is with the Department of Mathematics and Statistics, Boston University, Boston, MA. Eric D. Kolaczyk is with the Department of Mathematics and Statistics and the Hariri Institute for Computing, Boston University. Laura F. White is with the Department of Biostatistics, Boston University.
Am J Public Health ; 112(2): 277-283, 2022 02.
Article in En | MEDLINE | ID: mdl-35080960
ABSTRACT
Objectives. To develop an approach to project quarantine needs during an outbreak, particularly for communally housed individuals who interact with outside individuals. Methods. We developed a method that uses basic surveillance data to do short-term projections of future quarantine needs. The development of this method was rigorous, but it is conceptually simple and easy to implement and allows one to anticipate potential superspreading events. We demonstrate how this method can be used with data from the fall 2020 semester of a large urban university in Boston, Massachusetts, that provided quarantine housing for students living on campus in response to the COVID-19 pandemic. Our approach accounted for potentially infectious interactions between individuals living in university housing and those who did not. Results. Our approach was able to accurately project 10-day-ahead quarantine utilization for on-campus students in a large urban university. Our projections were most accurate when we anticipated weekend superspreading events around holidays. Conclusions. We provide an easy-to-use software tool to project quarantine utilization for institutions that can account for mixing with outside populations. This software tool has potential application for universities, corrections facilities, and the military. (Am J Public Health. 2022;112(2)277-283. https//doi.org/10.2105/AJPH.2021.306573).
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Software / Quarantine / Forecasting Type of study: Prognostic_studies Limits: Humans Country/Region as subject: America do norte Language: En Year: 2022 Type: Article

Full text: 1 Database: MEDLINE Main subject: Software / Quarantine / Forecasting Type of study: Prognostic_studies Limits: Humans Country/Region as subject: America do norte Language: En Year: 2022 Type: Article