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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. Josh Ketter‏ @sangfroyd 31 Aug 2020
      Replying to @GidMK

      I read that, but no mention of any adjustments for AB undercount bias And the 4 wk time didn't account for overlap with fatalities from infections post-measurement date Why didn't you use fatalities by "date of death" instead of date of report? You could nix your extra 7 days

      1 reply 0 retweets 0 likes
    2. Josh Ketter‏ @sangfroyd 31 Aug 2020
      Replying to @sangfroyd @GidMK

      Basically all your IFR estimates are higher than the leading papers for the studies you cite. Most were written before we knew how quickly AB's go below detectable levels (particularly in asympto's) Did you reach out to the rep's for these studies to compare your IFR calc?

      1 reply 0 retweets 0 likes
    3. Health Nerd‏Verified account @GidMK 31 Aug 2020
      Replying to @sangfroyd

      That's actually not true. In some cases ours are lower (i.e. Geneva), depends on how they calculated IFR. AB undercount is something of a concern, but as we note it is built into the sensitivity calculations for many tests and therefore in many cases already accounted for

      1 reply 0 retweets 0 likes
    4. Josh Ketter‏ @sangfroyd 31 Aug 2020
      Replying to @GidMK

      Geneva looks practically the same - 0.64% https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(20)30584-3/fulltext … Others are 60-100% higher. i.e. Sweden Doing a secondary sensitivity analysis for AB vs. adjusting for it as a primary median are very different. You did it for fatalities, but not AB, which creates large bias.

      1 reply 0 retweets 0 likes
    5. Health Nerd‏Verified account @GidMK 31 Aug 2020
      Replying to @sangfroyd

      Some are indeed higher - as I said, it depends on how IFR was calculated in those papers. We used a standard methodology which was elucidated in the paper for all calculations

      1 reply 0 retweets 0 likes
    6. Health Nerd‏Verified account @GidMK 31 Aug 2020
      Replying to @GidMK @sangfroyd

      As for "large bias", I have no idea what you mean. As I said, the AB issue is in many cases built into the sensitivity assumptions of the ELISA used in most serology programs - it's not necessary to adjust for this again in the analysis as we note

      1 reply 0 retweets 0 likes
    7. Josh Ketter‏ @sangfroyd 31 Aug 2020
      Replying to @GidMK

      It's not in all ELISA's and is very under-represented if sampled during height of the curve. +AB type & decay rates not adjusted for at all If you plotted your imputed IFR's compared to the median IFR's of those studies, the delta is rather large for the 5 that I checked.

      1 reply 0 retweets 0 likes
    8. Health Nerd‏Verified account @GidMK 31 Aug 2020
      Replying to @sangfroyd

      Sure, but describing that as "bias" is a leading statement. I would argue that taking deaths from an ongoing epidemic is "biased" in and of itself And yes, absolutely! One reason why we did not include samples taken during the height of the curve 😉

      1 reply 0 retweets 0 likes
    9. Health Nerd‏Verified account @GidMK 31 Aug 2020
      Replying to @GidMK @sangfroyd

      And, again, decay rate is usually part of sensitivity calculations. We're going around in circles here

      1 reply 0 retweets 0 likes
    10. Josh Ketter‏ @sangfroyd 31 Aug 2020
      Replying to @GidMK

      That's not correct - decay rate was unknown when the sens & spec were provided They are relative to & dependent on the sampling timeframes against the curves Did you examine this? Many studies actually adjust for these. Yours is one of the few who didn't

      1 reply 0 retweets 0 likes
      Health Nerd‏Verified account @GidMK 31 Aug 2020
      Replying to @sangfroyd

      I have no idea what you mean by "were provided", we cited a number of very recent studies on exactly this point. I also don't think you've actually understood the point about test sensitivity here

      10:43 PM - 31 Aug 2020
      2 replies 0 retweets 0 likes
        1. New conversation
        2. Health Nerd‏Verified account @GidMK 31 Aug 2020
          Replying to @GidMK @sangfroyd

          From recent evidence, we know that ELISA sensitivity is ~80% i.e. https://www.bmj.com/content/370/bmj.m2516 … What you're suggesting, as far as I can tell, is that there is an ADDITIONAL element, aside from the 20% false negatives we already know about, that would be missed by the ELISA

          1 reply 0 retweets 1 like
        3. Josh Ketter‏ @sangfroyd 31 Aug 2020
          Replying to @GidMK

          Correct. Obviously depends on the exact test used. But generally it's the % of infections that have decayed by the measurement date, and therefore changes the weighting of decay, similar to how true prev effects PPV. This is relative to each community & their point on curve

          1 reply 0 retweets 0 likes
        4. Show replies
        1. New conversation
        2. Josh Ketter‏ @sangfroyd 31 Aug 2020
          Replying to @GidMK

          Sens & Spec "Provided by the Manufacturers" I didn't see the source provided in the Appendix or Supp Materials, it may be there, just didn't see it. The point is, whether you're in month 6 and have lost X% AB's or week 3 and haven't dev as much, matters. You didn't adj for it

          1 reply 0 retweets 0 likes
        3. Health Nerd‏Verified account @GidMK 31 Aug 2020
          Replying to @sangfroyd

          We're really going around in circles here. To put it another way - you calculate test sensitivity using PCR +ve cases as your benchmark, then testing serology several months later. Thus, the reduction in ABs is ~already accounted for in test sensitivity calculations~

          2 replies 0 retweets 0 likes
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