Arguing with these people will get you nowhere.
False Positive Rate – a PCT RNA test of high sensitivity and tolerant specificity is designed for purposes of mercy – to not miss diagnostic cases. This is done specifically to minimize suffering from missed illness. However, it is well established that tests of such design may also produce false positive outcomes as part of their assay design. When a population is tested by PCR tests, and 99% of that population is well, then there will be a high number of false positives arising from the testing of that population, even and especially compared to false negatives. In addition, beside the issue of test design, is the reality that testing labs may suffer from laxity in procedure, kit contamination or employee error or malfeasance. All of these factors combine into what is known as a ‘False Positive Rate’ for a particular set of tests.
If we have a 1% rate of false positives, inside a population which is testing at 1% prevalence, in theory almost all of the positives being detected, are indeed false. As of late August the US was conducting on average about 680,000 tests per day. A 2.3% false positive rate would yield 15,640 false positives per day. The average positives detected during that same time was around 45,000 positives per day. Thus, potentially 35% of those reported positives in late August 2020, were indeed false. A study by Cohen and Kessel, updated and re-printed 18 August 2020, cited a measured median false positive rate of 2.3% for Covid RT-PCR testing. They confirmed the reality that “the likely sources of these false positives (contamination, human error) are more directly connected to laboratory practices and layouts than to which particular assay is used.”
