MONITORING SARS-COV-2 TRANSMISSION AND PREVALENCE IN POPULATIONS UNDER REPEATED TESTING

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.