Abstra
It is well-known that widespread testing of people with a low probability of having the disease at issue will lead to high levels of false positives, even with accurate tests (Skittrall et al. 2020; Bokhorst et al. 2012; Dinnes et al. 2021; Madrigal et al. 2020). This has been described as the “false positive paradox” (Flender 2019). It’s a paradox because even quite accurate tests can lead to high levels of false positives when used widely in a population with low actual prevalence of a given disease.
For example, Skittrall et al. 2020 calculated that hypothetically screening 100,000 people chosen randomly from the general UK population in June 2020 would result in 25 times more false positives than true positives (50 false positives and 2 true positives), even with a test thought to have a very high 99.95% specificity.
Widespread screening during previous outbreaks and pandemics has generally not been recommended because of the potential for high false positives. The Center for Disease Control (CDC)’s 2004 guidance from the SARS pandemic (CDC 2004), for example, stated: “To decrease the possibility of a false-positive result, testing should be limited to patients with a high index of suspicion for having SARS-CoV disease.”