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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

      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
    2. 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
    3. 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
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    4. 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
    5. 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
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    6. 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
    7. 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
    8. 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
    9. Josh Ketter‏ @sangfroyd 15 Oct 2020
      Replying to @GidMK

      To be clear, there's really only 1 real error you pointed out; 44 vs 47% The rest are reference gaps which were disclaimed in the header The other items are less "errors" and more subjective disagreements you have w/ Ioannidis on his inclusion criteria

      1 reply 0 retweets 0 likes
    10. Josh Ketter‏ @sangfroyd 15 Oct 2020
      Replying to @sangfroyd @GidMK

      Moreover your IFR meta was significantly higher due to 2 errors: 1) Your elongated death window (capturing fatalities from infections beyond the sample dates) 2) Not fully accounting for the AB decay curve *ELISA only captures a point in time Later studies underestimate seroppic.twitter.com/DypPoYJnA8

      2 replies 0 retweets 0 likes
      Health Nerd‏Verified account @GidMK 15 Oct 2020
      Replying to @sangfroyd

      Actually, in my newer review we look more carefully at the death lag and conclude that in fact it should be longer in most situations. We also look at the AB delay curve issue more thoroughlyhttps://www.medrxiv.org/content/10.1101/2020.07.23.20160895v6 …

      1:16 PM - 15 Oct 2020
      2 replies 0 retweets 1 like
        1. New conversation
        2. Health Nerd‏Verified account @GidMK 15 Oct 2020
          Replying to @GidMK @sangfroyd

          It is not true to say that later studies underestimate seroprevalence, if only because there aren't really any 'later' studies thus far. Even though there's a lag for publication, virtually all seroprevalence studies were conducted between March and July

          1 reply 0 retweets 0 likes
        3. Nick Douvis‏ @MedHatDentist 11 Nov 2020
          Replying to @GidMK @sangfroyd

          But wasn’t his article submitted in May and thus other studies after would not be included? Your thread also seems to confirm my viewpoint that LTC need more restrictions and retirees go out less. How do school closures make any sense with huge age difference in IFR?

          0 replies 0 retweets 0 likes
        4. End of conversation
        1. Katy McConkey‏ @KatyMcconkey 15 Oct 2020
          Replying to @GidMK @sangfroyd

          How long is the death lag?

          0 replies 0 retweets 0 likes
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