MONITORING SARS-COV-2 TRANSMISSION AND PREVALENCE IN POPULATIONS UNDER REPEATED TESTING
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Abstract
We describe a repeat SARS-CoV-2 testing model for monitoring and containing outbreaks in a residential community. The analysis is motivated by the Ohio State University (OSU)’s approach to monitoring disease at its Columbus, Ohio campus during the COVID-19 epidemic in autumn 2020. The model is simple, yet flexible enough to accommodate changes in behavior over time and to eliminate bias due to a nonrandom testing scheme. Model parameters are estimated from individual results of weekly SARS-CoV-2 testing of residents. Model output serves several purposes, including estimating the effective reproduction number and monitoring prevalence to help inform isolation and quarantine bed capacity. An extended version of the model is also considered where the residential population (on-campus students) is assumed to interact with another population for whom the testing regime is more relaxed and possibly less frequent (off-campus students or instructional faculty and staff). To illustrate the model application, we analyze both the synthetic data as well as the actual student SARS-CoV-2 testing data collected at OSU Columbus campus.
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SciScore for 10.1101/2021.06.22.21259342: (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 and data.
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 …
SciScore for 10.1101/2021.06.22.21259342: (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 and data.
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.
Results from scite Reference Check: We found no unreliable references.
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