Diagnosis of COVID-19 may be based on clinical observations, laboratory findings, and epidemiological linkage.1 Underscoring this diagnosis is accurate data from laboratory tests: this can make the difference between a false positive based on the clinical findings that are attributable to another cause, or a false negative based on lack of clinical findings that are attributable to SARS-CoV-2 viral infection, the causal agent for COVID-19. We conducted a simulation depicting how predictive values vary in the face of unknown data surrounding test sensitivity, specificity, and reported cases. in the USA. There are two main implications of our findings. First, the prevalence of COVID-19 in the tested population is likely inflated: clinical disease attributable to other sources of infection such as influenza, or other respiratory viruses, is a plausible explanation. Second, we should be less alarmed by not being able to trace chain of transmission for many who test positive early in this pandemic when population prevalence is low.