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August 11, 2022

6/17/2022 9:35:00 AM
Testing Our Way Into A Pandemic, Part 2

Dear Editor;
A diagnostic test is only as useful as its predictive value, that is, how reliably the test indicates who is sick and who is not. That makes sense!
Three metrics comprise a test's predictive value: (1) sensitivity, i.e., the percentage of people who test positive and really do have the specific disease which the test is assessing ("True Positive"); (2) specificity, i.e., the percentage of people who test negative and really do not have the specific disease which the test is assessing ("True Negative"); and (3) disease prevalence, i.e., the proportion of a population infected with a specific disease at a given time.
Ideally, diagnostic tests would be 100% accurate in both sensitivity and specificity, always giving either true positives or true negatives. Apart from culturing a pathogen à la Koch's Postulates, 100% accuracy is difficult, if not impossible, to achieve. Thus, "False Positive" or "False Negative" labels are assigned to inaccurate results. I briefly discussed issues affecting the COVID-19 PCR test accuracy in my previous Letter to the Editor (May 12).
Moving to the third metric, the disease prevalence of COVID-19, even during surges, has been relatively low. That probably comes as a surprise to most people who have been terrorized by the "cases, cases, cases" narrative for over two years. Indeed, the J&J and Moderna vaccine trials found disease prevalence of 0.5% and 0.6%, respectively, even with the latter trial comprised of participants selected to be at higher risk of exposure.
Now, here's the dirty little secret: When disease prevalence is low, false positives are very high. This is called the "False Positive Paradox," and herein lies the colossal problem with mass testing of asymptomatic people during this COVID-19 epoch. The math isn't difficult, but I'm limited to 500 words here.
Even if I conservatively say the disease prevalence is 1% (not 0.5% or 0.6% as cited above by actual studies), and I very generously say the PCR test sensitivity and specificity are both 99%, that results in a false positive rate of 50%. That means that of all the positive PCR test results, 50% of those were not actually positive. That's a coin toss!
But the situation is actually far worse. The PCR (and antigen) tests are not even close to 99% accurate. Lab analysis of the CDC's PCR test found 70% specificity and 80% sensitivity (using sequencing to verify PCR amplicons). This increases the rate of false positives to 97%. Even the FDA (surprisingly) warned in 2020 that up to 96% of positive tests in mass screening programs could be false positives because of the low disease prevalence. Shockingly, experts have called the PCR test the "Gold Standard" for COVID-19 diagnosis. Good grief!
Mass testing has led to catastrophically high levels of false positives. This is "Diagnostics 101" stuff. But this is not just about errors in case counting. It also corrupts hospitalization and death causal data. Something is rotten in the state of Denmark!
Mary Lepinske
Dodgeville, WI

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