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

Adam Burns; Alexander Gutfraind

To evaluate this NPI, our model computationally simulates outbreaks of influenza and COVID -19 in school settings, and then looks at the effect of symptom-based isolation policies. The benefit of using a model is the ability to clarify and quantify the possible effects of many different policy choices. Our work builds upon numerous previous studies that have applied mathematical models to model influenza transmission in schools (see e.g. [15] [16] [17] [18] [19] [20] [21] ). Several studies also modeled non-pharmaceutical interventions such as closures but not absenteeism policies [19, [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] ). We performed a systematic analysis of studies that evaluated isolation policies by using a broad search on PubMed. We found a variety of policies involving isolation of infected individuals, particularly isolation for a fixed interval following diagnosis. For example, the large modeling consortium on pandemic influenza [18] assumed students with influenza symptoms would isolate themselves but did not examine the duration of isolation. We also found several comprehensive computational studies of school closures and isolation of infected students (e.g. [18, 33] ), but did not find evaluation of policies that would reduce transmission caused by infectious students returning from home. A related policy of symptom monitoring, that isolates contacts once they show symptoms, has been examined computationally and shown to be sufficient for controlling certain outbreaks [34] .