So, firstly, we know from quite a bit of research that a significant fraction of people who recover from COVID-19 experience symptoms long-term. Plenty of research demonstrating this i.e.https://www.medrxiv.org/content/10.1101/2020.10.19.20214494v2 …
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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
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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
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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/
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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 happensShow this thread -
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
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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
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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?
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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
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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!Show this thread
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