5/n Some of the more inappropriate statements have at last been removed, such as the age-related stuff and the incorrect citation of the case-fatality rate of influenza Good!
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16/n For example, the ENE-COVID and Brazilian studies, which sampled entire countries by region, are only summed up as a single valuepic.twitter.com/6295tiG91O
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17/n On the other hand, several studies that sampled multiple regions (but found MUCH lower IFRs) in other places are split up by area I cannot see any explanation for this in the paperpic.twitter.com/sdMyr7qGCo
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18/n On top of this, we've got another problem - collinearity The basic issue is that you shouldn't lump multiple samples of the same group of people together into one study
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19/n But now, in the study we have Wuhan (A), Wuhan (B), and Hubei (not Wuhan) It's very poor statistical practice to lump all these estimates together like this
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20/n Similarly, we have two estimates from Spain. One is the ENE-COVID study, a rigorous randomized seroprevalence study that is the envy of the world The other is a non-random sample of pregnant women at one place in Barcelona These are given EQUAL WEIGHTS in the analysispic.twitter.com/j2r5CLKGlj
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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
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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
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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!
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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
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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
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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
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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
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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
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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
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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
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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
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32/n Ioannidis has also now included some of the government-conducted studies in the paper, which is good to seepic.twitter.com/VRLXEr8geQ
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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
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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 …
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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
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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
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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 …Show this thread -
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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