My question is fairly simple: There is a COVID-19 antibody test with a worst-case specificity of 98%, meaning that it yields potentially up to 2% false positives.
While that number is not bad it is problematic when the expected true positive rate is in the same range as the possible false positives: We end up with huge uncertainties.
My question is simply whether this false positive rate is random or a systematic error, i.e. whether false positive samples would be false positives again if tested a second time. Alternatively: Are there other tests which have different false positives? In both cases one could simply re-test original positives and achieve a very good combined specificity.