’FALSE POSITIVE’ ANTIBODY CONFUSION: there are 2 different types. 1) Classical false positive rate is when true negative people test +, aka 1-Specificity. 2) Another is low POSITIVE PREDICTIVE VALUE, due to low prevalence. CDC is worried about latter.

2) For context, CDC today proposed avoiding antibody tests for *individual* assessment of immunity. It’s not the immunity itself, it’s that a lot of + test results are not real due to a low PPV, which is % of POSITIVE TEST RESULTS that are ACTUALLY TRUE+. https://twitter.com/drericding/status/1265625581187747847

3) In epidemiology of testing screening, not just sensitivity% & specificity% important, but *PPV* (Positive Predictive Value - % of Tested+ who are actually True+) is even more key. But what happens if you screen everyone randomly, such as mass antibody testing, PPV gets weird.

4) weird happens when you mass-screen in population w/ few #COVID19 infected (ie antibody for all) is that PPV % value can be *super low* despite semi-good sens/spec if low prev. Let’s do the math why even sensitivity=100% & specificity=95% can yield bad PPV...