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GidMK's profile
Health Nerd
Health Nerd
Health Nerd
Verified account
@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 19 May 2020

      3/n What did the study consist of? Well, the aim is to estimate the infection-fatality rate (IFR) of #COVID19 using seroprevalence (antibody test) studies The methodology here is not ideal at first glancepic.twitter.com/9d9V7qmTys

      6 replies 18 retweets 148 likes
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    2. Health Nerd‏Verified account @GidMK 19 May 2020

      4/n What's the issue? Well, if you want to estimate a number like this from published data you want your search and appraisal methods to be SYSTEMATIC Hence, systematic review

      2 replies 15 retweets 221 likes
      Show this thread
    3. Health Nerd‏Verified account @GidMK 19 May 2020

      5/n Instead, what we appear to have here is an opaque search methodology, little information on how inclusion/exclusion criteria were applied (and no real justification for those criteria)pic.twitter.com/35EYmKMBFE

      2 replies 22 retweets 224 likes
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    4. Health Nerd‏Verified account @GidMK 19 May 2020

      6/n For example, seroprevalence studies including healthcare workers were excluded, because the samples are biased, but studies including blood donors were not, even though these are arguably even more biased That's a strange inconsistency

      5 replies 23 retweets 306 likes
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    5. Health Nerd‏Verified account @GidMK 19 May 2020

      7/n Studies only described in the media were excluded, but this appears to have included government reports as well Again, there's no justification for this and it is REALLY WEIRD to exclude government reports (they're doing most of the testing!)

      3 replies 17 retweets 261 likes
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    6. Health Nerd‏Verified account @GidMK 19 May 2020

      8/n Moving on, the study then calculated an inferred IFR, if the authors hadn't already done so. The calculation is crude, but not entirely wrong However, there's an issue - the estimates were then 'adjusted'

      1 reply 10 retweets 139 likes
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    7. Health Nerd‏Verified account @GidMK 19 May 2020

      9/n Spefically, the IFR estimates were cut by 10-20% depending on whether they included different antibody tests or not I had a look at the reference here, and it definitely doesn't support such a blanket judgementpic.twitter.com/AYzDRR5suk

      1 reply 15 retweets 173 likes
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    8. Health Nerd‏Verified account @GidMK 19 May 2020

      10/n Ok, so, on to the results This table is basically the crux of the review. 12 included studies, with "corrected" IFR ranging from 0.02-0.4% MUCH lower than most published estimatespic.twitter.com/hDyd9YQgOL

      3 replies 17 retweets 150 likes
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    9. Health Nerd‏Verified account @GidMK 19 May 2020

      11/n A colleague and I did a systematic review and meta-analysis of published estimates of IFR and came to an aggregated estimate of 0.74% (0.51-0.97%) so this is a bit of a surprise to me https://www.medrxiv.org/content/10.1101/2020.05.03.20089854v2.article-metrics … What's happening here?

      7 replies 82 retweets 352 likes
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    10. Brian Dell‏ @Brian_Dell 19 May 2020
      Replying to @GidMK

      Your analysis includes just two, Santa Clara & Gangelt, serological studies. If that’s all you are going to look at of course no surprise.

      1 reply 0 retweets 1 like
      Health Nerd‏Verified account @GidMK 19 May 2020
      Replying to @Brian_Dell

      Actually, we included the NYC data in that analysis, I'm going to update sometime this weekend with a few more serology studies as well (the estimate does not change substantially)

      10:31 PM - 19 May 2020
      2 replies 0 retweets 0 likes
        1. Brian Dell‏ @Brian_Dell 19 May 2020
          Replying to @GidMK

          Why isn’t NYC considered an “observational” study?

          0 replies 0 retweets 0 likes
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        1. P@cman‏ @Pcman32554064 20 May 2020
          Replying to @GidMK @Brian_Dell

          why dont you also remove the model studies?

          0 replies 0 retweets 0 likes
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