Here’s an article about testing for COVID-19 which reveals the press, irrespective of political bias, is still in the dark about screening for this disease, or broadly any disease. The piece is written rather awkwardly, but what its trying to say is that the Abbott ID NOW test is 85% sensitive. This means that 85% of those who have the virus will test positive, the remaining 15% will be missed. The press fails to understand that a test 85% sensitive will also test positive in 15% of the population that doesn’t have the virus – ie, they will be false positives. Thus, if you screen large population which includes only a small number of patients who are infected you will be inundated with false positives. Suppose you screen 1 million subjects 1% of whom have the disease, you’ll get 8500 true positives and 148,000 false positives. If 10% have the disease there will be 85,000 true positives and 135,000 false positives. Only minimal skill at arithmetic is needed to see the problem. Scribblers wake up!

If you want to dig into this subject google Bayes theorem.