To illustrate how patient risk and clinical costs are driven by false-positive and false-negative results.
Molecular, antigen, and antibody testing are the mainstay to identify infected patients and fight the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To evaluate the test methods, sensitivity (percent positive agreement [PPA]) and specificity (percent negative agreement [PNA]) are the most common metrics utilized, followed by the positive and negative predictive value-the probability that a positive or negative test result represents a true positive or negative patient. The number, probability, and cost of false results are driven by combinations of prevalence, PPA, and PNA of the individual test selected by the laboratory.
Molecular and antigen tests that detect the presence of the virus are relevant in the acute phase only. Serologic assays detect antibodies to SARS-CoV-2 in the recovering and recovered phase. Each testing methodology has its advantages and disadvantages.
We demonstrate the value of reporting probability of false-positive results, probability of false-negative results, and costs to patients and health care. These risk metrics can be calculated from the risk drivers of PPA and PNA combined with estimates of prevalence, cost, and Reff number (people infected by 1 positive SARS-CoV-2 carrier).