Symptom-Based Isolation Policies: Evidence from a Mathematical Model of Outbreaks of Influenza and COVID-19

Adam Burns; Alexander Gutfraind

Following calibration, we evaluated the effect symptom-based isolation policies would have on influenza and COVID-19 outbreaks. We also considered alternative scenarios with larger schools (140 students per grade), higher compliance, vaccination and others described below. For COVID-19, we calibrated the transmission parameter to give a higher 50% attack rate and used symptom and shedding rates estimated for SARS-Cov-2 (Appendix A). Because there is conflicting data on the rates of fever symptoms with this infection, we considered two scenarios: a conservative where just 50% of the cases experience and detect fever, and a higher 88% (cf. [47] [48] [49] and [50, 51] , respectively). To ensure that the results are robust to uncertainty parameter values, we then simulated the epidemic 500 times per scenario, with substantially different values for parameters such as the start day in the year, contact rate between cohorts and others, and reported the median and the interquartile ranges (see Appendix B for details). All modeling and statistical analysis used the RStudio Integrated Development for R. RStudio, Inc., Boston,