Why even a super-accurate Covid-19 test can fail

The persistent shortfall in genetic and antibody testing for the Covid-19 coronavirus in the United States remains a major hurdle to understanding — and controlling — the pandemic. There are new tests every week both to detect the new coronavirus and antibodies to the coronavirus.

Yet the bigger challenge isn’t the tests themselves, but the entire endeavor of calculating the prevalence of a brand new infectious disease like Covid-19.

This explainer at Vox shows the math behind why the prevalence of the disease influences the chances of a correct test result.

For patients getting tested, the main concern is how to interpret the outcome: If I test negative with an RT-PCR genetic test, what are the chances I actually have the virus? Or if I test positive with an antibody test, does it actually mean I have the antibodies? It turns out that the answers to these questions don’t just hinge on the accuracy of the test. ‘Mathematically, the way that works out, that actually depends on how many people in your area have Covid,’ Eleanor Murray, an assistant professor of epidemiology at the Boston University School of Public Health, said.