COVID-19 Diagnosis and Viral Load Reporting: A Theory of Overdiagnosis and Undertesting

The ongoing discourse about COVID-19 testing revolves around undertesting (i.e., insufficient testing capacity relative to demand). An important yet little studied systematic issue is overdiagnosis (i.e., positive diagnoses for patients with negligible viral loads): recent evidence shows U.S. laboratories have adopted a hyper-sensitive diagnosis criterion for COVID-19 testing, such that up to an estimated 90% of positive diagnoses are for minuscule virus loads. Motivated by this situation, we develop a theory of testing for COVID-19 that explains both undertesting and overdiagnosis. We show that a laboratory has an incentive to inflate the diagnosis criterion, which generates a higher diagnosis-driven demand as a result of contact-tracing efforts, albeit while dampening demand from disease transmission. An inflated diagnosis criterion prompts the laboratory to build a higher testing capacity, which may not fully absorb the inflated demand, so undertesting arises. Finally, we examine a social planner’s problem of whether to mandate the laboratory to report viral load along with its diagnosis, such that a physician or contact tracer can make informed triage decisions. The social planner may prefer not to mandate viral load reporting, because it induces a higher testing capacity and may help reduce disease transmission.