BULLSHIT NUMBERS

HERE:

The case numbers are bullshit, at least if you want to measure infection rates. As I’ve been saying for weeks, there are so many selection biases that the numbers tell you NOTHING about the prevalence of the virus in the population, either at a point in time or crucially over time. Indeed, the CDC guidelines could be titled “How to Produce a Wildly Biased Sample”:

This testing protocol could be justified on clinical and diagnostic grounds, but it is a disaster from the perspective of generating data that is useful in shaping policy.

Further, trends in positive test numbers is driven to a considerable degree by . . . a greater number of tests.

The graphs that you see depicting trends deaths or cases across countries over time are bullshit. They are bullshit because the inherit all the flaws of the data discussed above (exacerbated by the fundamentally different data reporting methods across countries), and they almost fail to adjust for population size or demographic characteristics.

Chinese numbers are obviously bullshit. No need to elaborate this point.

The models that are being used to drive (or at least justify) lockdowns are bullshit. Their predictions went from apocalyptic to well, a small fraction of apocalyptic. Sometimes between one day and the next. Models should be evaluated on predictive accuracy. The predictions of these models have proved to be excessively pessimistic, i.e., bullshit.

And don’t buy the line that the lockdowns reduced the death tolls. For one thing, many of the models’ predictions included the effects of social distancing–and still came out way too high. For another, many countries’ death and case rates (above caveats apply) peaked before the lockdowns could have had any effect.

I keep hearing the IHME model referred to as the “top model.” Who says? On what basis? Basically because somebody else said it. And oh, Bill Gates is somehow involved. So that claim is bullshit too.