Overdiagnosis and Undertesting for Infectious Diseases

Abstract

The ongoing discourse about COVID-19 testing revolves around undertesting (i.e., insufficient testing capacity relative to demand). Another 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 highly sensitive diagnosis criteria, such that up to an estimated 90% of positive diagnoses are for minuscule viral loads. Motivated by this situation, we develop a theory of diagnostic testing for infectious diseases that explains both undertesting and overdiagnosis. We show that a laboratory has an incentive to inflate its 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 that the laboratory report the viral load along with its diagnosis, so that a physician or contact tracer can make informed triage decisions. Our results show the social planner may choose not to mandate viral-load reporting initially; this choice induces a higher testing capacity and can help reduce disease transmission.

Keywords: Infectious diseases, diagnostic testing, testing capacity, viral load reporting

JEL Classification: I11, I18, D21