Thanks. Maybe some justification for arguing that the author of the Substack article that Matt linked to was blowing at least some smoke out of his arse.
However, maybe some justification also for some of their points, this one in particular:
https://purescience.substack.com/p/nih- ... school?s=rFlaw #3: Poor Survey Response and Self Selection
The study was based on an invitation sent to 13,800 school districts. The number of school districts responding to the survey and complying with its requirements was only 61, which corresponds to an abysmal 0.0044 response and inclusion rate! Low survey response rates are very susceptible to self-selection bias - those responding to the survey do not represent the larger population and may be biased.
Even the Pediatrics article graph [Figure 2, page 23] for the correlation between primary and secondary cases for "universal masking" doesn't look particularly impressive - correlation coefficient of, maybe, 0.5? Even more suspect given the "low survey response" rate.
But I think that highlights something that John D suggested - very noisy signal, a great many confounding factors that mask whatever signal might be present. Which is why I argue for looking at the physics of masking, and at the epidemiological models that might be based on them; quite a decent article here on the former from, of all places, Forbes:
https://www.forbes.com/sites/startswith ... 9824755f3c
Clearly a substantial degree of leakage through and out the top of most masks. No doubt that the masks would "work" to limit the dispersion of virons which, in a controlled environment based on known numbers of people infected, would probably give a strong correlation between secondary infections versus masks or no masks. But at what cost? It's the cost-benefit ratio that has, or should have, some bearing on policies and mandates.
However, many people don't seem to have a clue how that is relevant, probably because they don't have much of a clue how models in general work, particularly those related to epidemiology. Bit of a murky and convoluted topic but an essential part seems to be the basic replication rate:
https://en.wikipedia.org/wiki/Basic_reproduction_numberThe most important uses of R0 are determining if an emerging infectious disease can spread in a population and determining what proportion of the population should be immunized through vaccination to eradicate a disease. In commonly used infection models, when R0>1 the infection will be able to start spreading in a population, but not if R0<1.
If masks substantially reduce that R0 number, and below 1, then that would be a policy with a low cost-benefit ratio. However, if the R0 remains well about 1 then the cost-benefit ratio would be substantially higher and, probably, not worth implementing mask policies.
Devils in the details that far too many refuse to face much less grapple with.
