True prevalence of long-COVID in a nationwide, population cohort study Abstract Long-COVID prevalence estimates vary widely and should take account of symptoms that would have occurred anyway. Here we determine the prevalence of symptoms attributable to SARS-CoV-2 infection, taking account of background rates and confounding, in a nationwide population cohort study of 198,096 Scottish adults. 98,666 (49.8%) had symptomatic laboratory-confirmed SARS-CoV-2 infections and 99,430 (50.2%) were age-, sex-, and socioeconomically-matched and never-infected. While 41,775 (64.5%) reported at least one symptom 6 months following SARS-CoV-2 infection, this was also true of 34,600 (50.8%) of those never-infected. The crude prevalence of one or more symptom attributable to SARS-CoV-2 infection was 13.8% (13.2%,14.3%), 12.8% (11.9%,13.6%), and 16.3% (14.4%,18.2%) at 6, 12, and 18 months respectively. Following adjustment for potential confounders, these figures were 6.6% (6.3%, 6.9%), 6.5% (6.0%, 6.9%) and 10.4% (9.1%, 11.6%) respectively. Long-COVID is characterised by a wide range of symptoms that, apart from altered taste and smell, are non-specific. Care should be taken in attributing symptoms to previous SARS-CoV-2 infection. https://www.nature.com/articles/s41467-023-43661-w
All this shows is counting symptoms is not a helpful or valid way of assessing whether someone has long covid. Surely they should realise by now that this has to be combined with a measure of severity and frequency of the symptoms and impact on ability to function.
Perhaps knowing the true prevalence will encourage the Scottish government to spend money on research? I would post a "roll on floor laughing " emoji here if I could find one.
Add on top of that, that it's not possible to claim a group as never-infected anymore unless you do a really deep analysis including extremely extensive testing, which both are never done. One could at least analyse a subset of patients to see how valuable ones method is, but I guess that would require effort…
Only a load of complete idiots would suggest doing what they have done. Maybe it is relevant that they come from a 'School of Health and Wellbeing' rather than a Medical School. Maybe they just assume everyone is really well deep down.
But unfortunately we also see medical doctors do this in their research (like Wyller), and they are taken seriously by others. And when said others are believed to be good at methodology in their own field it becomes a real mess.
But they don't have to be. This is not a requirement, otherwise the flu would not be a concern, and it obviously is. It's literally been an issue over the last few years how hard it is to tell COVID apart from many other common infections precisely because they simply cause many of the common symptoms of illness. This things where common has become synonymous with "not a concern" is just plain weird. One of the most common early symptom of cancer is fatigue. Initial HIV infection is pretty close to a flu or cold and then it causes non-specific symptoms as well. This entire model is just plain misguided, makes no sense at all. And Long Covid was not defined on simply having symptoms after COVID, it's defined as symptoms that affect quality of life, reduce functionality, even disable people, making them unable to work and function normally. This is not a serious study, and that's not even counting the fact that "not infected" doesn't exist anymore as a control group. They're entirely ignoring asymptomatic spread.
I recall Jonathan welcoming the study on fatigue at Aberdeen University*. Given the percentage of people who have a smart phone, presumably it should be possible to monitor the activity levels of a representative sample of people with a long covid diagnosis and thereby estimate the prevalence of long covid associated disability? Estimating pre & post pandemic levels of fatigue, & how much is ME/CFS, seems difficult. https://www.s4me.info/threads/uk-ab...e-understanding-of-fatigue.33400/#post-475995
