It appears to be a combination of some of these factors, along with others not mentioned here. Ibn Khaldun’s analysis appears to be a good foundation to go off. [Thread]
I am yet to find a fully convincing account of what caused the emergence of the two contrasting schools of Ahl Al-\u1e24ad\u012bth in the \u1e24ij\u0101z and Ahl Al-Ra'\u012b in Al-K\u016bfa.
— Amir Aboguddah \u0623\u0645\u064a\u0631 \u0623\u0628\u0648\u063a\u062f\u0629 (@Amir_Aboguddah) January 20, 2021
My issue with the accounts are as follows:
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Normally I enjoy the high standards of journalism in @guardian . Not today as disappointed with misleading headline that suggest infections are spreading fastest in children. It'll worry parents/teachers & I doubt most readers will unpick the
The latest REACT1 report shows prevalence of infection in ALL age groups has fallen, including children aged 5-12 from 1.59% in Round 8 to 0.86% in Round 9a. The authors of REACT1 report also (wisely) didn't try to interpret the prevalence figures.
If this were a research trial you wouldn't place much weight on the age differences in % prevalence because of the wide confidence intervals, i.e. differences weren't statistically significant.
3/
I've previously tweeted on the challenges (& dangers) of interpreting surveillance data. One would need lots more contextual info to make sense of it & arrive at sound
Undoubtedly some will extrapolate from the prevalence of infection figures in children to other settings i.e. schools based on the headline. I'd advise caution as there is a real risk of over-interpretation through extrapolation of limited data. Association is not causation.
5/
The latest REACT1 report shows prevalence of infection in ALL age groups has fallen, including children aged 5-12 from 1.59% in Round 8 to 0.86% in Round 9a. The authors of REACT1 report also (wisely) didn't try to interpret the prevalence figures.
If this were a research trial you wouldn't place much weight on the age differences in % prevalence because of the wide confidence intervals, i.e. differences weren't statistically significant.
3/
I've previously tweeted on the challenges (& dangers) of interpreting surveillance data. One would need lots more contextual info to make sense of it & arrive at sound
Misinterpretation of surveillance data is a serious issue. Surveillance data needs to come with a warning label - Open to biases - interpret with caution! Some may not realize that surveillance often does not measure all infection, it's a proxy for actual disease incidence.
— Andrew Lee (@andrewleedr) February 14, 2021
1/
Undoubtedly some will extrapolate from the prevalence of infection figures in children to other settings i.e. schools based on the headline. I'd advise caution as there is a real risk of over-interpretation through extrapolation of limited data. Association is not causation.
5/