> Any number of different things Yes, it can mean lots of different things, potentially, which is why it is useful to look at factors that may have impacted im

> Any number of different things Yes, it can mean lots of different things, potentially, which is why it is useful to look at factors that may have impacted implied IFRs. E.g. is the population you are studying older than the national average (NY: about average for percent above age 65). Is the population unhealthier than average, e.g. looking at obesity rates (NY: significantly lower obesity than the national average). You want to look at how many deaths were in nursing homes vs not, to see if policy decisions meant disproportionate impact in high risk populations (NY: one of states with the lowest percentage of deaths linked to nursing homes). So many factors were either neutral for NY, or suggest that NY's IFR would be lower than the national average. But, one also considers that NY was stretched thin, which no doubt meant non-ideal care for many people, so that likely countered some of the advantages NY had had. You also then want to compare with other serology studies, and the implied IFRs from those studies - are we looking at outlier numbers, or does it generally align? Outliers can help uncover factors that were missed, or flaws in the study itself. And that's the thing, all of the NY numbers have suggested an IFR above 0.5%, potentially upwards of 1%, which is broadly in line with other IFR calculations from other places. > Point being, the Santa Clara study was a lot closer to right than wrong, and dismissing it, and the people involved, because of politics and methodological mistakes is a cheap shot. > When it came out, the media and “experts” were routinely claiming that this virus had a fatality rate as high as 3-5%. So I don’t particularly care if they were off by a factor of 3 (~0.5%); they were much closer to correct than anyone else at the time. This is just flatly wrong. You've conflated case fatality rates with infection fatality rates. The general consensus around the time of the Santa Clara study was that the IFR for the US was most likely in the 0.5% to 1% range. The 3-5% numbers were referring to case fatality rates. In April, I wrote this - https://news.ycombinator.com/item?id=22969994 https://news.ycombinator.com/item?id=22969994 - "The NY study, if it holds up, suggests an IFR in the 0.8-1.0% range for NYC (depending on whether or not you include the additional excess deaths), which is in the range most experts have been assuming (0.5%-1.0% has been a common range that's been tossed around)." You'll note April is also when the Santa Clara antibody study was released. > they were much closer to correct than anyone else at the time If the best science at the time of the Santa Clara study was estimating an IFR of 0.5-1%, and the Santa Clara study estimated 0.12-0.2%, and the current CDC estimate is 0.65%, who was closer to correct? Given this, does that change your stance?