Reopening universities during the COVID-19 pandemic: A testing strategy to minimize active cases and delay outbreaks
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- Evaluated articles (Rapid Reviews Infectious Diseases)
Abstract
Background
University campuses present an ideal environment for viral spread and are therefore at extreme risk of serving as a hotbed for a COVID-19 outbreak. While active surveillance throughout the semester such as widespread testing, contact tracing, and case isolation, may assist in detecting and preventing early outbreaks, these strategies will not be sufficient should a larger outbreak occur. It is therefore necessary to limit the initial number of active cases at the start of the semester. We examine the impact of pre-semester NAT testing on disease spread in a university setting.
Methods
We implement simple dynamic transmission models of SARS-CoV-2 infection to explore the effects of pre-semester testing strategies on the number of active infections and occupied isolation beds throughout the semester. We assume an infectious period of 3 days and vary R 0 to represent the effectiveness of disease mitigation strategies throughout the semester. We assume the prevalence of active cases at the beginning of the semester is 5%. The sensitivity of the NAT test is set at 90%.
Results
If no pre-semester screening is mandated, the peak number of active infections occurs in under 10 days and the size of the peak is substantial, ranging from 5,000 active infections when effective mitigation strategies ( R 0 = 1.25) are implemented to over 15,000 active infections for less effective strategies ( R 0 = 3). When one NAT test is mandated within one week of campus arrival, effective ( R 0 = 1.25) and less effective ( R 0 = 3) mitigation strategies delay the onset of the peak to 40 days and 17 days, respectively, and result in peak size ranging from 1,000 to over 15,000 active infections. When two NAT tests are mandated, effective ( R 0 = 1.25) and less effective ( R 0 = 3) mitigation strategies delay the onset of the peak through the end of fall semester and 20 days, respectively, and result in peak size ranging from less than 1,000 to over 15,000 active infections. If maximum occupancy of isolation beds is set to 2% of the student population, then isolation beds would only be available for a range of 1 in 2 confirmed cases ( R 0 = 1.25) to 1 in 40 confirmed cases ( R 0 = 3) before maximum occupancy is reached.
Conclusion
Even with highly effective mitigation strategies throughout the semester, inadequate pre-semester testing will lead to early and large surges of the disease and result in universities quickly reaching their isolation bed capacity. We therefore recommend NAT testing within one week of campus return. While this strategy is sufficient for delaying the timing of the outbreak, pre-semester testing would need to be implemented in conjunction with effective mitigation strategies to reduce the outbreak size.
Article activity feed
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SciScore for 10.1101/2020.07.06.20147272: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when …
SciScore for 10.1101/2020.07.06.20147272: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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Dominique Gibert
Review 1: "Reopening universities during the COVID-19 pandemic: A testing strategy to minimize active cases and delay outbreaks"
Pre-entry screening of students entering universities for COVID-19 may help limit the spread of COVID-19, but further analysis is warranted to know the true impact. The modeling is too simple for a complex situation, and should take into account other critical factors.
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Mohak Gupta, Rishika Mohanta
Review 2: "Reopening universities during the COVID-19 pandemic: A testing strategy to minimize active cases and delay outbreaks"
Pre-entry screening of students entering universities for COVID-19 may help limit the spread of COVID-19, but further analysis is warranted to know the true impact. The modeling is too simple for a complex situation, and should take into account other critical factors.
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Arthur Reingold
Review 3: "Reopening universities during the COVID-19 pandemic: A testing strategy to minimize active cases and delay outbreaks"
Pre-entry screening of students entering universities for COVID-19 may help limit the spread of COVID-19, but further analysis is warranted to know the true impact. The modeling is too simple for a complex situation, and should take into account other critical factors.
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Strength of evidence
Reviewers: Dominique Gibert (Lyon 1 University) | 📒📒📒 ◻️ ◻️
Mohak Gupta, Rishika Mohanta (All India Institute of Medical Sciences) | 📒📒📒 ◻️ ◻️
Arthur Reingold (UC Berkeley) | 📘📘📘📘📘
Alalli Mériem (SAU-SAMU-SMUR) | 📒📒📒 ◻️ ◻️ -
Allali Mériem
Review 4: "Reopening universities during the COVID-19 pandemic: A testing strategy to minimize active cases and delay outbreaks."
Pre-entry screening of students entering universities for COVID-19 may help limit the spread of COVID-19, but further analysis is warranted to know the true impact. The modeling is too simple for a complex situation, and should take into account other critical factors.
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