@jeffcliff@DutchBoomerMan@pyrate@Emotenomics@FreeinTX@Ghislaine@bonifartius@bot Selection bias. The most libtarded people I know don't even test unless they're super sick. Childhood symptomatic expression was always low. This is unironically more likely related to VRIDS or whatever the technical term is (the V is for vaccine).
But really it's a matter of patient self filtering bias. Someone who is ill enough to go to a doctor with COVID symptoms, likely after testing. Those people are not 100% of all infections. Probably like 1%.
@jeffcliff@DutchBoomerMan@pyrate@Emotenomics@FreeinTX@Ghislaine@bonifartius@bot >again; you're saying *8,000* different studies work work on who shows up to their doctor without bothering to read them. I am saying that. Can you explain to me how you can affirm a negative without measuring it? After you do this, I'd like you to inform me of when you plan to convert to Christianity.
@jeffcliff@DutchBoomerMan@pyrate@Emotenomics@FreeinTX@Ghislaine@bonifartius@bot >so you agree that the proving the process by which these 8000 are generated is a similar problem as proving the nonexistence of god I do not. Prove that symptomatic expression in children is higher by several orders of magnitude than it was a year or two back, prove that the average infected person visits the doctor rather than riding it out, prove the number of asymptomatic infections, and prove the numbers support your level of concern.
In short, I don't think most viruses are harmless for everyone, even the common 'low risk' ones. I went to a Pox party as a kid and infected a few kids with my gift of chickenpox. Several children would die annually from chickenpox induced pneumonia prior to its vaccine rollout, yet it was still considered a "fairly harmless disease" at that time. I have never argued against "long COVID", but only around the prevalence of long symptoms vs short and asymptomatic infections.
@jeffcliff@DutchBoomerMan@pyrate@Emotenomics@FreeinTX@Ghislaine@bonifartius@bot But let's actually address what you're saying for fairness. I found the source of this (below), which is a meta analysis published in Nature. Meta analysis are, as you know, the gold standard in statistical review. They are also only as useful as their source material. Be mindful of agenda driven journalists, piss be upon them, who phrase things to shape opinions. >The literature search yielded 8373 publications, of which 21 studies met the inclusion criteria, and a total of 80,071 children and adolescents were included. Okay, now at 21 from 8,373 studies >The prevalence of long-COVID was 25.24%, and the most prevalent clinical manifestations were mood symptoms (16.50%), fatigue (9.66%), and sleep disorders (8.42%). Not to be too dismissive, but these sound like normal behaviors in children and teens. Staying up late and being tired because of Fortnight and telling your libtarded single mother that it's the long COVID is actually a possibility. As is simply being a teen/kid. This also does not address the prevalence of long COVID vs standard, mild, asymptomatic expressions. That it's being at least acknowledged is GOOD IMO, because many viruses have intermediate or longer term effects and we should know about them to plan accordingly.
@jeffcliff@DutchBoomerMan@pyrate@Emotenomics@FreeinTX@Ghislaine@bonifartius@bot it holds for people who require medical intervention for COVID, which is a small subset of the people who become sick and test, which is a smaller subset of the people who become infected with mild symptoms, which is a smaller subset of the people who had asymptomatic infections.
It was only possible to perform meta-analyses of O.R.s comparing cases and controls for 13 symptoms (mood, fatigue, headache, dyspnea, concentration problems, anosmia/ageusia, loss of appetite, rhinitis, myalgia/arthralgia, cough, fever, sore throat, and nausea/vomiting) (Fig. 4). When compared to controls, children with long-COVID had a higher risk of persistent dyspnea (OR 2.69; 95% CI 2.30–3.14, I2 0%), anosmia/ageusia (OR 10.68; 95% CI 2.48, 46.03, I2 0%), and/or fever (OR 2.23; 95% CI 1.2–4.07, I2 12%). There was significant heterogeneity for 4 out of the 13 meta-analyses (Fig. 4). The controls were chosen in a very different way among studies, which might have introduced significant heterogeneity. The following were the different definitions of controls, children and adolescents with: (1) other infections (e.g., common cold, pharyngotonsillitis, gastrointestinal, urinary tract infections, pneumonia of bacteria or unknown origin)17; (2) no antibodies testing24 mixed with other infections17; (3) a negative antibody test29, (4) a negative rtPCR test among symptomatic children35; and (5) children who did not have a positive test recorded in the database15 (Supplementary Fig. 2). The adjustments among studies also varied. Several studies adjusted their OR by age, sex, ethnicity, socioeconomic status, and comorbidities35. However, age and sex15 only adjusted for sex, only for age17, did not adjust, or by OR without adjusting previous conditions
Quality of incoming data is okay, but obviously mushed on a few areas (in my non-expert opinion). I'll ask Doc and see what he thinks.