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Modelling the impact of presemester testing on COVID-19 outbreaks in university campuses

OBJECTIVES: Universities are exploring strategies to mitigate the spread of COVID-19 prior to reopening their campuses. National guidelines do not currently recommend testing students prior to campus arrival. However, the impact of presemester testing has not been studied. DESIGN: Dynamic SARS-CoV-2...

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Autores principales: Rennert, Lior, Kalbaugh, Corey Andrew, Shi, Lu, McMahan, Christopher
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7745453/
https://www.ncbi.nlm.nih.gov/pubmed/33323447
http://dx.doi.org/10.1136/bmjopen-2020-042578
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author Rennert, Lior
Kalbaugh, Corey Andrew
Shi, Lu
McMahan, Christopher
author_facet Rennert, Lior
Kalbaugh, Corey Andrew
Shi, Lu
McMahan, Christopher
author_sort Rennert, Lior
collection PubMed
description OBJECTIVES: Universities are exploring strategies to mitigate the spread of COVID-19 prior to reopening their campuses. National guidelines do not currently recommend testing students prior to campus arrival. However, the impact of presemester testing has not been studied. DESIGN: Dynamic SARS-CoV-2 transmission models are used to explore the effects of three presemester testing interventions. INTERVENTIONS: Testing of students 0, 1 and 2 times prior to campus arrival. PRIMARY OUTCOMES: Number of active infections and time until isolation bed capacity is reached. SETTING: We set on-campus and off-campus populations to 7500 and 17 500 students, respectively. We assumed 2% prevalence of active cases at the semester start, and that one-third of infected students will be detected and isolated throughout the semester. Isolation bed capacity was set at 500. We varied disease transmission rates (R(0)=1.5, 2, 3, 4) to represent the effectiveness of mitigation strategies throughout the semester. RESULTS: Without presemester screening, peak number of active infections ranged from 4114 under effective mitigation strategies (R(0)=1.5) to 10 481 under ineffective mitigation strategies (R(0)=4), and exhausted isolation bed capacity within 10 (R(0)=4) to 25 days (R(0)=1.5). Mandating at least one test prior to campus arrival delayed the timing and reduced the size of the peak, while delaying the time until isolation bed capacity was reached. Testing twice in conjunction with effective mitigation strategies (R(0)=1.5) was the only scenario that did not exhaust isolation bed capacity during the semester. CONCLUSIONS: Presemester screening is necessary to avert early and large surges of active COVID-19 infections. Therefore, we recommend testing within 1 week prior to and on campus return. While this strategy is sufficient for delaying the timing of the peak outbreak, presemester testing would need to be implemented in conjunction with effective mitigation strategies to significantly reduce outbreak size and preserve isolation bed capacity.
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spelling pubmed-77454532020-12-17 Modelling the impact of presemester testing on COVID-19 outbreaks in university campuses Rennert, Lior Kalbaugh, Corey Andrew Shi, Lu McMahan, Christopher BMJ Open Infectious Diseases OBJECTIVES: Universities are exploring strategies to mitigate the spread of COVID-19 prior to reopening their campuses. National guidelines do not currently recommend testing students prior to campus arrival. However, the impact of presemester testing has not been studied. DESIGN: Dynamic SARS-CoV-2 transmission models are used to explore the effects of three presemester testing interventions. INTERVENTIONS: Testing of students 0, 1 and 2 times prior to campus arrival. PRIMARY OUTCOMES: Number of active infections and time until isolation bed capacity is reached. SETTING: We set on-campus and off-campus populations to 7500 and 17 500 students, respectively. We assumed 2% prevalence of active cases at the semester start, and that one-third of infected students will be detected and isolated throughout the semester. Isolation bed capacity was set at 500. We varied disease transmission rates (R(0)=1.5, 2, 3, 4) to represent the effectiveness of mitigation strategies throughout the semester. RESULTS: Without presemester screening, peak number of active infections ranged from 4114 under effective mitigation strategies (R(0)=1.5) to 10 481 under ineffective mitigation strategies (R(0)=4), and exhausted isolation bed capacity within 10 (R(0)=4) to 25 days (R(0)=1.5). Mandating at least one test prior to campus arrival delayed the timing and reduced the size of the peak, while delaying the time until isolation bed capacity was reached. Testing twice in conjunction with effective mitigation strategies (R(0)=1.5) was the only scenario that did not exhaust isolation bed capacity during the semester. CONCLUSIONS: Presemester screening is necessary to avert early and large surges of active COVID-19 infections. Therefore, we recommend testing within 1 week prior to and on campus return. While this strategy is sufficient for delaying the timing of the peak outbreak, presemester testing would need to be implemented in conjunction with effective mitigation strategies to significantly reduce outbreak size and preserve isolation bed capacity. BMJ Publishing Group 2020-12-15 /pmc/articles/PMC7745453/ /pubmed/33323447 http://dx.doi.org/10.1136/bmjopen-2020-042578 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Infectious Diseases
Rennert, Lior
Kalbaugh, Corey Andrew
Shi, Lu
McMahan, Christopher
Modelling the impact of presemester testing on COVID-19 outbreaks in university campuses
title Modelling the impact of presemester testing on COVID-19 outbreaks in university campuses
title_full Modelling the impact of presemester testing on COVID-19 outbreaks in university campuses
title_fullStr Modelling the impact of presemester testing on COVID-19 outbreaks in university campuses
title_full_unstemmed Modelling the impact of presemester testing on COVID-19 outbreaks in university campuses
title_short Modelling the impact of presemester testing on COVID-19 outbreaks in university campuses
title_sort modelling the impact of presemester testing on covid-19 outbreaks in university campuses
topic Infectious Diseases
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7745453/
https://www.ncbi.nlm.nih.gov/pubmed/33323447
http://dx.doi.org/10.1136/bmjopen-2020-042578
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