[zahlman]

> He wasn't necessarily wrong in all his conclusions, but neither were the other researchers that he rightly criticized for their own statistical gymnastics earlier.

In hindsight, I can't see any plausible argument for an IFR actually anywhere near 1%. So how were the other researchers "not necessarily wrong"? Perhaps their results were justified by the evidence available at the time, but that still doesn't validate the conclusion.

[tripletao]

I mean that in the context of "Most Published Research Findings Are False", he criticized work (unrelated to COVID, since that didn't exist yet) that used incorrect statistical methods even if its final conclusions happened to be correct. He was right to do so, just as Gelman was right to criticize his serosurvey--it's nice when you get the right answer by luck, but that doesn't help you or anyone else get the right answer next time.

It's also hard to determine whether that serosurvey (or any other study) got the right answer. The IFR is typically observed to decrease over the course of a pandemic. For example, the IFR for COVID is much lower now than in 2020 even among unvaccinated patients, since they almost certainly acquired natural immunity in prior infections. So high-quality later surveys showing lower IFR don't say much about the IFR back in 2020.

[mike_hearn]

There were people saying right at the time in 2020 that the 1% IFR was nonsense and far too high. It wasn't something that only became visible in hindsight.

Epidemiology tends to conflate IFR and CFR, that's one of the issues Ioannidis was highlighting in his work. IFR estimates do decline over time but they decline even in the absence of natural immunity buildup, because doctors start becoming aware of more mild cases where the patient recovered without being detected. That leads to a higher number of infections with the same number of fatalities, hence lower IFR computed even retroactively, but there's no biological change happening. It's just a case of data collection limits.

That problem is what motivated the serosurvey. A theoretically perfect serosurvey doesn't have such issues. So, one would expect it to calculate a lower IFR and be a valuable type of study to do well. Part of the background of that work and why it was controversial is large parts of the public health community didn't actually want to know the true IFR because they knew it would be much lower than their initial back-of-the-envelope calculations based on e.g. news reports from China. Surveys like that should have been commissioned by governments at scale, with enough data to resolve any possible complaint, but weren't because public health bodies are just not incentivized that way. Ioannidis didn't play ball and the pro lockdown camp gave him a public beating. I think he was much closer to reality than they were, though. The whole saga spoke to the very warped incentives that come into play the moment you put the word "public" in front of something.

[FabHK]

From what I can gather, the best estimates for pre-vaccine, 2020 Wuhan/Alpha strain IFR are about 0.5% to 0.8%, approaching 1%, depending very much on the age structure (age 75+ had an IFR of 5-15%).

The current effective IFR (very often post-vaccination or post-exposure, and of with weaker strains) is much lower. But a 1% IFR estimate in early 2020 was entirely justified and fairly accurate.

For what it's worth, epidemiologists are well aware of the distinction between IFR, CFR, and CMR (crude mortality rate = deaths/total population), and it is well known that CFR and CMR bracket IFR.