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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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    Health Nerd‏Verified account @GidMK 30 Aug 2020

    Latest update on our age-stratified IFR for COVID-19 paper is up on Medrxiv now Some additions: - more samples - additional info in tables - improved discussion https://www.medrxiv.org/content/10.1101/2020.07.23.20160895v4 …pic.twitter.com/Bs9gRfRaZe

    8:22 PM - 30 Aug 2020
    • 15 Retweets
    • 39 Likes
    • Patrick Hamilton Hamish Graham Marc Läderach Claudio Tennie Cheryl Δημήτρης Δαλαγιώργος Mika Mäkeläinen john mcclean PD Secure Doors
    5 replies 15 retweets 39 likes
      1. New conversation
      2. Health Nerd‏Verified account @GidMK 30 Aug 2020

        One thing that I haven't noted on twitter before - we give the equation generated by our meta-regression of age and IFR This means that you can calculate the specific IFR expected for any age (although for <10yo the CI is very wide)pic.twitter.com/fCuiIW3ufg

        1 reply 0 retweets 8 likes
        Show this thread
      3. Health Nerd‏Verified account @GidMK 30 Aug 2020

        So, for example, based on our analysis of 26 studies, someone who is age 40 would have an e^(-7.56+0.121*40) = 0.07% risk of death Age 50, it goes up to 0.22% And so on

        2 replies 4 retweets 14 likes
        Show this thread
      4. Health Nerd‏Verified account @GidMK 30 Aug 2020

        Also, as noted before, it really is amazing how much age explains death rates in different places 90% of the variance in overall death rates in these places can be explained by who got COVID-19!pic.twitter.com/Sm5xpQOq9z

        2 replies 5 retweets 21 likes
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      5. End of conversation
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      2. Atomsk's Sanakan‏ @AtomsksSanakan 31 Aug 2020
        Replying to @ottartwain @GidMK

        Belgium is a convenience sample of residual sera, + thus more likely to be non-representative. For example, by over-estimating seroprevalence in older people due to being enriched in patients who came in with COVID-19. England is not a convenience sample https://www.medrxiv.org/content/10.1101/2020.07.23.20160895v4 …pic.twitter.com/jd2pkgM3Ds

        0 replies 0 retweets 1 like
      3. End of conversation
      1. Pieter Peach‏ @DrPieterPeach 31 Aug 2020
        Replying to @GidMK

        Would be interesting to see hospitalisation rates

        0 replies 0 retweets 0 likes
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      1. New conversation
      2. free the young‏ @theripsnorter 1 Sep 2020
        Replying to @GidMK

        Why did you remove the three strategic scenarios based on your findings? Scenario 3 being the best for less total deaths

        1 reply 0 retweets 0 likes
      3. Health Nerd‏Verified account @GidMK 1 Sep 2020
        Replying to @theripsnorter

        We didn't, just put them in the supplementary materials to reduce the length of the text a bit

        1 reply 0 retweets 1 like
      4. Show replies
      1. New conversation
      2. James Wood‏ @JamesGWood_UNSW 1 Sep 2020
        Replying to @GidMK

        Just a note that ideally you should be modelling the hazard as log-linear - CIs in older age (and predictions for those >100) will exceed 1 in the current approach. Just an additional data transform before using same model ... results will be near identical but more valid.

        1 reply 0 retweets 1 like
      3. Bruce Tabor‏ @BruceTabor8 2 Sep 2020
        Replying to @JamesGWood_UNSW @GidMK

        It's not hazard unless you're using survival analysis. I agree log-linear is necessary but it's modeling probability of death (risk). Odds ratios would be preferable to avoid exceeding 1 even with a log-linear scale.

        1 reply 0 retweets 1 like
      4. Show replies

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