10/n The study only tested two groups: healthcare workers and people on dialysis Now, Ioannidis excludes any testing on healthcare workers, but dialysis patients are...fine?pic.twitter.com/4tYTh4dwNT
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21/n The Spain example is even more of a problem because the ENE-COVID (the rigorous study) implies an IFR in Barcelona of ~1% The survey of pregnant women implies ~.5% Guess which one is used?pic.twitter.com/1JO5aNfrbV
22/n Now, all of this collinearity is particularly troubling for that 0.27% estimate that I mentioned way back at the start of the thread
23/n If we get average the collinear results - where we've included the same study or the same sample multiple times - the median jumps immediately to 0.35% That's quite a bit higher!
24/n But there are more corrections to be made. In several places, the IFR that is in this paper does not match the IFR calculated by the study authors
25/n For example, Geneva. The original authors calculated an IFR of 0.64%, but this is downgraded to 0.45% in the paperpic.twitter.com/lEEG7LPjez
26/n And this is not the only example. Another study tested over three weeks and found seroprevalence of 3.85%, then 8.36%, then 1.46%. Overall 3.53% The 8.36% figure is used, giving 5x more infections than the study itself found, and the lowest IFR possiblepic.twitter.com/ZeC8arsL7P
27/n Taking all this into account, let's look at the IFRs for only those studies using representative population samples that were correctly calculated
28/n Here's the revised table. The lowest IFR is, again, Ioannidis' own study, at 0.18%. Nearly half of the estimates are above 1%, and they range all the way up to 1.63% (!)pic.twitter.com/7xU7DGrq2Q
29/n Somehow, for the third time running, there are innumerable decisions made in the paper that seem to only ever push down the IFR, rather than produce the best estimate
30/n As I've outlined, there are also a number of simple errors that make this very problematic as an estimate of the IFR (or the IFR range) for COVID-19
31/n All that being said, the discussion is now MUCH better, and really engages with some of the things I (and others) discussed in previous threads. Too much to go over here, but well worth a read
32/n Ioannidis has also now included some of the government-conducted studies in the paper, which is good to seepic.twitter.com/VRLXEr8geQ
33/n All in all, some definite improvements, but a lot of things still in the paper that are really hard to reconcile with best practice
34/n The one thing I would point out - this from earlier in the thread is a classic example of moving the goalposts. The influenza comparison was clearly wrong, so now we have another comparison which is bad but slightly less wronghttps://twitter.com/GidMK/status/1283232032085032961?s=20 …
35/n imo much better practice would be to acknowledge that COVID-19 is probably substantially more lethal than influenza, but that quantifying this difference is somewhat challenging
36/n Also, another statement that is incorrect and has remained in each version - that disadvantaged populations/settings are uncommon exceptions in the global landscape This remains simply untruepic.twitter.com/8M8QjQ6ZWv
37/n Also, you can find my personal best estimate in the paper that @LeaMerone and I authored on IFR here. A reasonable guess for most areas seems to be 0.5-0.8%https://www.medrxiv.org/content/10.1101/2020.05.03.20089854v4 …
38/n Another addition, this thread goes through some of the headaches with the paper that have remained through every version TL:DR - it's not systematic! https://twitter.com/AVG_Joseph96/status/1283236273558294528?s=20 …
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