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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 Feb 28

      Problem is, by its nature this research is pretty exploratory. Most studies enroll people who are engaged and interested, and thus the population is very selected

      1 reply 0 retweets 16 likes
      Show this thread
    2. Health Nerd‏Verified account @GidMK Feb 28

      For example, one of the best sources of information is the COVID Symptom Study, which uses an app to log details. By their very nature, apps exclude some people from using them https://covid.joinzoe.com/about 

      2 replies 0 retweets 13 likes
      Show this thread
    3. Health Nerd‏Verified account @GidMK Feb 28

      Some of my research shows this for chronic disease - lots of people stop using apps even if they are beneficial, and this pattern is non-random https://www.jmir.org/2020/9/e20283/ 

      1 reply 1 retweet 19 likes
      Show this thread
    4. Health Nerd‏Verified account @GidMK Feb 28

      What we'd need to really understand the prevalence of #LongCovid in populations is to enroll a large group of people - including asymptomatic cases and people who don't have COVID - and follow them over time to see what happens

      3 replies 4 retweets 28 likes
      Show this thread
    5. Health Nerd‏Verified account @GidMK Feb 28

      We'd also need to try and get data from pretty much everyone at every time point, because it's likely that those who drop out are different to those who don't in ways that may be all but impossible to measure

      1 reply 0 retweets 17 likes
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    6. Health Nerd‏Verified account @GidMK Feb 28

      Unfortunately, that's really hard to do, so we are left to interpret the observational data that gives us, at best, a biased view of the situation

      1 reply 0 retweets 13 likes
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    7. Health Nerd‏Verified account @GidMK Feb 28

      Whenever you see a proportion being proposed (i.e. 1 in 20 people have Long COVID) it's important to understand the denominator Is it everyone? Only those in one study? Who did that study enroll?

      1 reply 0 retweets 19 likes
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    8. Health Nerd‏Verified account @GidMK Feb 28

      Important note - it's possible I've missed a large prospective study that does answer this question, I've tried to look but please do let me know if one has been published

      2 replies 0 retweets 13 likes
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    9. Health Nerd‏Verified account @GidMK Feb 28

      Important note #2 - this bias could easily bias the results IN BOTH DIRECTIONS, meaning that there could be less or far more #LongCovid than reported. There are reasonable arguments both ways!

      4 replies 1 retweet 30 likes
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    10. Dr Nisreen Alwan  🌻‏Verified account @Dr2NisreenAlwan Feb 28
      Replying to @GidMK

      There are estimates from random samples of population prevalence surveys & from follow up of (almost) all outpatients testing +ve. Based on these, the prevalence in adults is between 10-25% at around 3 months from onset, obviously with varying degrees of disability & severity.

      3 replies 8 retweets 27 likes
      Health Nerd‏Verified account @GidMK Feb 28
      Replying to @Dr2NisreenAlwan

      Interesting! Published somewhere?

      11:53 PM - 28 Feb 2021
      1 reply 0 retweets 0 likes
        1. New conversation
        2. Dr Nisreen Alwan  🌻‏Verified account @Dr2NisreenAlwan Feb 28
          Replying to @GidMK

          Yes of course. We’re doing a systematic review on prevalence of LC atm. I have tweeted such studies over the last months.

          2 replies 0 retweets 8 likes
        3. Health Nerd‏Verified account @GidMK Feb 28
          Replying to @Dr2NisreenAlwan

          Amazing! I look forward to the review 🙂

          0 replies 0 retweets 1 like
        4. End of conversation

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