Interpreting a COVID-19 Test Result
2020
Viral RNA tests for COVID-19, using reverse transcriptase polymerase chain reaction (RT-PCR), rely on samples obtained from the respiratory tract by nasopharyngeal swab. Testing for COVID-19 theoretically could "identify infected individuals who can then be isolated to reduce spread, allow contact tracing for exposed individuals, and provide knowledge of regional and national rates of infection to inform public health interventions." However, how to interpret test results with respect to individual patient results is not straightforward.
This article adopts a Bayesian perspective to demonstrate the influence of the prior probability of COVID-19, the sensitivity (i.e., the probability of a positive test conditional on disease presence), and the specificity (i.e., the probability of a negative test conditional on disease absence) on the post-test probability of disease. They quantitatively demonstrate this influence through two case scenarios, using well-designed graphics to depict the conceptual basis behind test interpretation. Of particular relevance to educators is this interactive graphic.
In addition, the authors point out the challenges due to lack of a “gold-standard” for evaluating the performance of COVID-19 tests and illustrate how the origin of estimates of "sensitivity" can introduce bias.
Interpreting a COVID-19 Test Result
Source:
Watson J, Whiting PF, Brush JE. Interpreting a COVID-19 Test Result. BMJ 2020; 369. https://doi.org/10.1136/bmj.m1808