Abstract
While sensitivity and specificity are important characteristics for any diagnostic test, the influence of prevalence is equally, if not more, important when such tests are used in community screening. We review the concepts of positive/negative predictive values (PPV/NPV) and how disease prevalence affects false positive/negative rates. In low-prevalence situations, the PPV decreases drastically. We demonstrate how using two tests in an orthogonal fashion can be especially beneficial in low-prevalence settings and greatly improve the PPV of the diagnostic test results.
Highlights
In a low-disease prevalence population, using one point-of-care tests (POCTs) on its own will generate more false positive results than when used in a higher-prevalence situation. This is especially challenging as the disease prevalence of COVID-19 varies greatly between and within populations
The difference in prevalence can occur even between different locations within the same country, as one UK study [25] showed that healthcare workers had an 11 times higher hazard ratio for COVID-19 than the general community
Tracking the prevalence of COVID-19 is complicated by asymptomatic cases of COVID-19
Summary
Several factors are important to consider in the community screening of COVID-19: the turnaround time of test results, the sensitivity of the assay, the frequency of testing, and the prevalence of the disease in the population. Many rapid SARS-CoV-2 tests (antigen, RT-PCR, and antibody tests) are available to assist in the screening and management of COVID-19. This means that in a population with a low disease prevalence, a positive result is confounded by a greater percentage of false positive cases It is only when disease prevalence is at least 1.4%/3.1%/2.3% for the antigen/molecular/antibody POCTs that. This is especially important when testing the general population who are largely asymptomatic and when disease prevalence is low
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