27/n There are also still, after many revisions, studies that have been excluded inappropriately from the estimates This study from Italy, for example, which produces an estimate of 7% (!) for IFR in the regionpic.twitter.com/41OGhRzSoN
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39/n Sorry, typo in tweet 37 - should read an IFR SUBSTANTIALLY *higher*, not lower. The SEROPREVALENCE is lower (at ~2%) which implies an IFR of ~1.2%
40/n Oh, on an unrelated sidenote, it's quite funny that the author spends some time arguing that using a median is more appropriate than doing a R-E meta-analysis (as @LeaMerone and I did), so I quickly calculated the median for our study and it is higher at 0.79% for IFR
pic.twitter.com/QTkJKNzMnb
Hallo, the unroll you asked for: @GidMK: John Ioannidis, of "Most Published Research Findings Are False" fame, has now had his paper on IFR published… https://threadreaderapp.com/thread/1316511734115385344.html … See you soon. 
Ioannidis' initial guess of low mortality assumed only 1% of the population would be infected! He's been trying to avoid admitting that error ever since. That's why he's focusing on the IFR instead.
"... assume ... that 1% of the U.S. population gets infected (about 3.3 million people), this would translate to about 10,000 deaths."https://www.statnews.com/2020/03/17/a-fiasco-in-the-making-as-the-coronavirus-pandemic-takes-hold-we-are-making-decisions-without-reliable-data/ …
Have you written to the publication? This is quite disturbing to me. I mean, what is the peer review process for, if not to identify and fix these things before final publication. Perhaps I'm a little naive, but...
This was peer reviewed. @gidmk is just wrong.
You're just running cover.
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