Peter McCullough on health: what the evidence says · JRE #1747
SUBJECT: HEALTH
Not a true/false call. Every claim is logged with its sources; read the exhibits below.
we just walked in, we have asymptomatic testing, that if we get a positive, the chances that that positive is false positive is 97%. 97%. And that is if you're asymptomatic.
What the evidence says 01 / RECORD
McCullough claimed that a positive COVID-19 test in an asymptomatic person has a 97% chance of being a false positive. Manufacturer validation data reviewed in peer-reviewed literature show RT-PCR assays for SARS-CoV-2 typically report specificity near 100%, meaning the test itself produces a false positive result in only a small fraction of cases, not 97%. Figures like 97% (or similarly large numbers) arise from a different calculation: the positive predictive value (PPV) in low-prevalence screening settings, where even a highly specific test yields a high proportion of false positives among all positives simply because true infections are rare in the tested population. A 2021 analysis in the Journal of Occupational and Environmental Medicine illustrates this, showing PPV can fall to roughly 32% at 1% prevalence and to about 4.5% at 0.1% prevalence, a mathematical artifact of low pretest probability rather than evidence that the test itself is wrong most of the time. Conflating a low-prevalence PPV effect with the test's intrinsic false-positive rate, as the claim does, is a well-documented statistical error. The claim is misleading: it misstates a real epidemiological phenomenon (declining PPV at low prevalence) as if it were the test's error rate, producing an alarmist and inaccurate figure.