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GidMK's profile
Health Nerd
Health Nerd
Health Nerd
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@GidMK

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Health NerdVerified account

@GidMK

Epidemiologist. Writer (Guardian, Observer etc). "Well known research trouble-maker". PhDing at @UoW Host of @senscipod Email gidmk.healthnerd@gmail.com he/him

Sydney, New South Wales
theguardian.com/profile/gideon…
Joined November 2015

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    1. Health Nerd‏Verified account @GidMK 14 Oct 2020

      John Ioannidis, of "Most Published Research Findings Are False" fame, has now had his paper on IFR published Let's do one, final, twitter peer-review on the study 1/npic.twitter.com/D24ut4zGJj

      47 replies 320 retweets 836 likes
      Show this thread
    2. Health Nerd‏Verified account @GidMK 14 Oct 2020

      Health Nerd Retweeted Health Nerd

      2/n You can find the study here https://www.who.int/bulletin/online_first/BLT.20.265892.pdf … And my previous threads on it here https://twitter.com/GidMK/status/1283232023402868737?s=20 …https://twitter.com/GidMK/status/1262956011872280577?s=20 …

      Health Nerd added,

      Health NerdVerified account @GidMK
      Today, this new preprint from John Ioannidis (of "Most Published Research Findings Are False" fame) went online Already up to Altmetric of 541 Let's do a rapid peer-review on twitter 1/n pic.twitter.com/aNth3I59Xa
      Show this thread
      2 replies 2 retweets 59 likes
      Show this thread
    3. Health Nerd‏Verified account @GidMK 14 Oct 2020

      3/n I should say at the outset here - the only personal comment I would like to make about Professor Ioannidis is that he is a very smart man who I respect tremendously I will, however, examine the paper, because I think that is what science is all about

      3 replies 1 retweet 116 likes
      Show this thread
      Health Nerd‏Verified account @GidMK 14 Oct 2020

      4/n At first glance, and indeed on deeper reading, it is clear that very little has changed from my previous looks into the paper

      3:50 PM - 14 Oct 2020
      • 58 Likes
      • Jim Andrakakis ⚕️⚕️ Daniel Bastian g 🇺🇸🇫🇷 eec Anjo Heidi Bouman (Niemand) Stelios Lysiotis
      1 reply 0 retweets 58 likes
        1. New conversation
        2. Health Nerd‏Verified account @GidMK 14 Oct 2020

          5/n The methodology is still the same, and the eventual conclusion remains that the median IFR of COVID-19 is 0.27% (originally he estimated 0.26%)pic.twitter.com/kBhIWCEUAL

          3 replies 2 retweets 64 likes
          Show this thread
        3. Health Nerd‏Verified account @GidMK 14 Oct 2020

          6/n The author then concludes that the IFR "tended to be much lower than estimates made earlier in the pandemic", which is odd because his own estimates made earlier in the pandemic (in May) were...lowerpic.twitter.com/7awIA4gEoW

          4 replies 5 retweets 110 likes
          Show this thread
        4. Health Nerd‏Verified account @GidMK 14 Oct 2020

          7/n Indeed, as we can easily see, the resulting low IFR is simply a consequence of the low quality of the review itself and has very little to do with when the estimates were made

          1 reply 5 retweets 92 likes
          Show this thread
        5. Health Nerd‏Verified account @GidMK 14 Oct 2020

          8/n For example, the review does not adhere to PRISMA guidelines (the most basic recommendations for reviews of this kind) which is very strange given that Prof Ioannidis himself is a co-author on the original PRISMA statementpic.twitter.com/fgwRh67bkL

          2 replies 20 retweets 181 likes
          Show this thread
        6. Health Nerd‏Verified account @GidMK 14 Oct 2020

          9/n This has lead to a problematic situation, where there is no rating for study quality, publication bias, and indeed little consideration in the manuscript for how the quality of the published evidence might impact the review

          1 reply 3 retweets 100 likes
          Show this thread
        7. Health Nerd‏Verified account @GidMK 14 Oct 2020

          10/n As we pointed out in our systematic review and meta-analysis of COVID-19 IFR, this is an issue because higher-quality studies tend to show a lower seroprevalence and thus a higher IFR https://www.sciencedirect.com/science/article/pii/S1201971220321809 …pic.twitter.com/Jf2TJH3GVP

          3 replies 12 retweets 138 likes
          Show this thread
        8. Health Nerd‏Verified account @GidMK 14 Oct 2020

          11/n (Interestingly, Ioannidis cites our study but gets the numbers wrong, in what is distressingly something of a trend in the paper generally - we actually estimated 0.68% in the published paper which came out recently)pic.twitter.com/63z3Mw61uS

          4 replies 11 retweets 117 likes
          Show this thread
        9. Health Nerd‏Verified account @GidMK 14 Oct 2020

          12/n We can see the issue with non-adherence to PRISMA in the methods section. These are clearly not the search terms used, as entering them into these databases results in 100,000s of resultspic.twitter.com/hElvwBf2rj

          3 replies 1 retweet 87 likes
          Show this thread
        10. Health Nerd‏Verified account @GidMK 14 Oct 2020

          13/n There are also still clear numeric errors remaining from previous versions of the study. For example, this number from a paper looking at people going to hospital in New York should read 44%, and not 47%pic.twitter.com/Q2lUREo20f

          2 replies 3 retweets 77 likes
          Show this thread
        11. Health Nerd‏Verified account @GidMK 14 Oct 2020

          14/n And there are new errors as well. In this study of blood donors in Rhode Island, the authors estimate a seropositivity of 0.6%, while the review paper has 3.9% insteadpic.twitter.com/MvF6e9Psgd

          1 reply 2 retweets 88 likes
          Show this thread
        12. Health Nerd‏Verified account @GidMK 14 Oct 2020

          15/n But by far and away, the biggest error in the text is simply to do with using clearly inappropriate samples to estimate population prevalence This is a fundamental flaw in the paper, and really something of a basic epidemiological mistake

          1 reply 10 retweets 139 likes
          Show this thread
        13. Health Nerd‏Verified account @GidMK 14 Oct 2020

          16/n Some of these studies are just so clearly inappropriate to infer a population estimate that it doesn't really require explaining. Samples of a single business in a city, or inpatient dialysis unitspic.twitter.com/CTWnw0Fbjf

          1 reply 9 retweets 102 likes
          Show this thread
        14. Health Nerd‏Verified account @GidMK 14 Oct 2020

          18/n Then we have blood donors, who again may give an erroneous result. These are people who, DURING A PANDEMIC are happy to go out and about and give blood. It is quite possible that they are MORE likely to have been infected than the general population!pic.twitter.com/0ME5x1br1B

          4 replies 5 retweets 101 likes
          Show this thread
        15. Health Nerd‏Verified account @GidMK 14 Oct 2020

          18.5/n There are also a lot of included studies from places in which there is almost certainly an enormous undercount of deaths For example, India, where the official death counts may represent a substantial underestimatehttps://www.bmj.com/content/370/bmj.m2859 …

          2 replies 11 retweets 91 likes
          Show this thread
        16. Health Nerd‏Verified account @GidMK 14 Oct 2020

          19/n A very basic, reasonable thing to do would be to conduct a sensitivity analysis excluding these biased estimates, to see what happens when you only use representative population estimates Which we can do

          1 reply 1 retweet 80 likes
          Show this thread
        17. Health Nerd‏Verified account @GidMK 14 Oct 2020

          20/n If we take the median of only these somewhat good-quality studies (some of them still aren't great, but at least they're not clearly inappropriate), we get a value of 0.5% Double the estimate of 0.27%pic.twitter.com/tQSICfngT9

          2 replies 13 retweets 111 likes
          Show this thread
        18. Health Nerd‏Verified account @GidMK 14 Oct 2020

          21/n I thought at this point I'd briefly look at blood donor studies, because they are an interesting case study The author argues that these should be included because, due to "healthy volunteer bias", at worse any estimate should bias the IFR results upwardspic.twitter.com/zfMeDdKKgn

          2 replies 2 retweets 59 likes
          Show this thread
        19. Health Nerd‏Verified account @GidMK 14 Oct 2020

          22/n Well, we can now actually test this theory and see if it is true. Enough studies have been done that we have COVID-19 seroprevalence estimates from BOTH blood donor studies AND representative samples and compare them

          1 reply 2 retweets 60 likes
          Show this thread
        20. Health Nerd‏Verified account @GidMK 14 Oct 2020

          23/n For example, in England an ongoing study on blood donors by PHE estimates that 8.5% of the population has developed antibodies to COVID-19 However, the ONS with their massive randomized study puts the figure at 6% insteadpic.twitter.com/ocnYbQoazk

          1 reply 3 retweets 70 likes
          Show this thread
        21. Health Nerd‏Verified account @GidMK 14 Oct 2020

          24/n In Denmark, a robust population estimate put the figure at 1.1%, while their blood donor study estimates 1.9% have been infected previouslypic.twitter.com/BT1eqgjtuT

          4 replies 3 retweets 64 likes
          Show this thread
        22. Health Nerd‏Verified account @GidMK 14 Oct 2020

          25/n Indeed, in every location where both a non-probabilistic, convenience sample has been taken (not just blood donors) AS WELL AS a well-done population estimate, the convenience sample overestimates the seroprevalence

          3 replies 4 retweets 91 likes
          Show this thread
        23. Health Nerd‏Verified account @GidMK 14 Oct 2020

          26/n We have a new paper that we're working on that suggests that using such estimates will usually overstate the true seroprevalence by a factor of about 2x Which means the true IFR would be double the number computed from such studies

          1 reply 4 retweets 74 likes
          Show this thread
        24. Health Nerd‏Verified account @GidMK 14 Oct 2020

          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

          3 replies 3 retweets 63 likes
          Show this thread
        25. Health Nerd‏Verified account @GidMK 14 Oct 2020

          29/n Similarly, there are numerous country-wide efforts not looked at in any way, such as the large population studies conducted in Italy (150,000 participants) and Portugal (2,300 participants)pic.twitter.com/Ur07B0QRpM

          2 replies 1 retweet 56 likes
          Show this thread
        26. Health Nerd‏Verified account @GidMK 14 Oct 2020

          30/n And while there is a very brief discussion of the variation in IFR by region, the main component (age) - as we have demonstrated - was barely addressed, with the author instead focusing on vague speculation about healthcare systemshttps://www.medrxiv.org/content/10.1101/2020.07.23.20160895v6 …

          1 reply 1 retweet 59 likes
          Show this thread
        27. Health Nerd‏Verified account @GidMK 14 Oct 2020

          31/n We can actually see how age of those infected impacts IFR quite neatly from some of the studies in this review Qatar (0.01%) and Spain (1.15%) look very different, right?pic.twitter.com/kwAOJ4QzCX

          2 replies 2 retweets 63 likes
          Show this thread
        28. Health Nerd‏Verified account @GidMK 14 Oct 2020

          Health Nerd Retweeted Health Nerd

          32/n Wrong! In fact, the difference here is entirely explained by age! In Qatar, infections have mostly been limited to the immigrant worker population (<40 years), with this group representing more than 50% of infectionshttps://twitter.com/GidMK/status/1300938689535565824?s=20 …

          Health Nerd added,

          Health NerdVerified account @GidMK
          Replying to @Brian_Orak @greg_travis and 2 others
          Yes indeed, and actually this is quite well explained by our recent meta-analysis of IFR by age: https://www.medrxiv.org/content/10.1101/2020.07.23.20160895v4 … If you use the predicted IFRs here, Qatar is actually a touch higher than expected given that >50% of their infections are <40yo
          2 replies 3 retweets 82 likes
          Show this thread
        29. Health Nerd‏Verified account @GidMK 14 Oct 2020

          33/n Since this group is at a very low risk of death from COVID-19, the population IFR is MUCH lower than in Spain, where infections among the elderly have been much more common

          1 reply 2 retweets 42 likes
          Show this thread
        30. Health Nerd‏Verified account @GidMK 14 Oct 2020

          34/n All of these errors are a shame, because to a certain extent I agree with the author IFR is NOT a fixed category. In the metaregression linked above in the thread, we demonstrated that ~90% of variation in IFR between regions was probably due to the age of those infected!pic.twitter.com/fj0k5oyW2B

          2 replies 10 retweets 69 likes
          Show this thread
        31. Health Nerd‏Verified account @GidMK 14 Oct 2020

          35/n Unfortunately, Prof Ioannidis appears not to have read this study, but if you are interested here is the preprint version to perusehttps://www.medrxiv.org/content/10.1101/2020.07.23.20160895v6 …

          1 reply 3 retweets 57 likes
          Show this thread
        32. Show replies

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