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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 20 Apr 2020

      Hey #epitwitter, can anyone explain something to me? I honestly don't understand why you would normalize to the population from a sample of COVID-19 serological tests. The reason we extrapolate in this way is to gain an idea of the population prevalence...

      1 reply 5 retweets 18 likes
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      Health Nerd‏Verified account @GidMK 20 Apr 2020

      (cont)...but in this case, we KNOW that COVID-19 is likely to be clustered. Unless your normalization for the population assumes a very uneven spread by design, presumably all you're ever going to do is overestimate the proportion of people who've been infected?

      10:35 PM - 20 Apr 2020
      • 3 Retweets
      • 10 Likes
      • Tian Leesa 'soapy clean hands' Klich, MSc 🇨🇦 Carter Blunt Lozzi 💙 Boo Radley Disorder (((Violet MD MSc FAAP))) Kyle Wolf 💧 Ian "Department of Diseasology" 🍩 Musgrave Raquel Hirsch
      3 replies 3 retweets 10 likes
        1. Health Nerd‏Verified account @GidMK 21 Apr 2020

          So far no good answer that I can see. Infectious disease epis, any thoughts? @trentyarwood @peripatetical @aetiology

          1 reply 1 retweet 1 like
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        2. Sam Horwich‏ @samhorwich 20 Apr 2020
          Replying to @GidMK

          that's a good point-- the assumption would be that cases are not clustered within the region because they reflect spread before recognition of outbreak. The adjustment made in the Santa Clara serology study, based on the/ethnicity/zip code, made the crude rate nearly double 👀

          1 reply 0 retweets 1 like
        3. Health Nerd‏Verified account @GidMK 20 Apr 2020
          Replying to @samhorwich

          Indeed. I personally don't see the logic - it seems to me that it's very unlikely that there has been even community spread, but that's the main assumption when adjusting in this way. It works for things like diabetes, but for infectious disease outbreaks?

          0 replies 0 retweets 1 like
        4. End of conversation
        1. New conversation
        2. Dr. Naomh Gallagher‏ @naomhgallagher 20 Apr 2020
          Replying to @GidMK

          I think it would only ever attempt to estimate disease history in specific populations, so ignoring the vulnerable groups and using subgroups to make the estimates cohort specific. Though the bigger problem here is finding a robust antibody test!

          1 reply 0 retweets 0 likes
        3. Health Nerd‏Verified account @GidMK 20 Apr 2020
          Replying to @naomhgallagher

          That makes sense to me with a mature epidemic, with months of disease spread, but I just can't see the logic if your confirmed case number is less than 0.1% of the population. Seems an easy way to wildly bias your results to me

          1 reply 0 retweets 0 likes
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