False Positives

One of the astounding things during this whole Covid-19 pandemic is just how misleading the statistics are, that are being reported. The worst metric and the one used to drive public policy in Oregon at least is reported cases. There are several reasons why you should be skeptical.

Reported cases are not based on random samples and therefore do not tell you anything about the population. The number of reported cases is a function of the number of people tested. The people that are tested are self-selected, not randomly selected. This means that sick people are oversampled, and the actual infection rate in the population is probably lower than reported.

Testing is pretty reliable but not perfect. If you assume a 10% rate for false positives and a 15% rate for false negatives and then plug in an infection rate of 4.5% into a Bayesian model, it shows that about 78% of positive test results are false positives. In other words, if you test positive, there is a 78% probability that you do not have Covid-19. The New York Times published similar information here. It makes one wonder if the concept of “asymptomatic cases” isn’t being used to cover up a very low infection rate. 

Finally, because the number of reported cases closely correlates to testing, the number of cases can be manipulated by testing policies. If a Governor wants it to look like her policies are working to stem the tide of infections, all she would need to do is test fewer people. 

The use and reporting of bad statistics and wrong and conflicting information indicates the need for reform in managing pandemics. That should probably be done at the Federal level. 

Link: NY TIMES: Up to 90% Who’ve Tested COVID-Positive Wrongly Diagnosed! TRUTH: A Whole Lot Worse! 

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