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Ewan's avatar

Important piece. It echoes my own frustrations with many public health researchers and policy makers. It really shocked me to learn how little poorly many people working in this area understand the value of randomisation or empiricism generally.

A word in favour of observational studies. Resources devoted to these are not a major issue. Having worked on large community based RCTs in cancer screening (10s of thousands of participants) I would guess that observational studies with routinely collected data would typically be several orders of magnitude cheaper. Of course the RCTs still need to be done! But supporting observational evidence doesn't fundamentally alter the resourcing needed and can generate additional knowledge.

To put it a different way, how many large RCTs are required to arrive at the optimal masking policy? 10? 100? There are so many combinations of mask type, rules for when it can be removed, fitting etc. Head-to-head trials for comparison of all options are probably not possible. The best approach may be to establish the efficacy (or not) of masking with 1 or 2 large RCTs, and then attempt to learn at the margins with observational studies.

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someothercat's avatar

Nice article.

The Bangladesh mask study was debunked by several researchers.

See here for example: https://www.researchgate.net/publication/360320982_The_Bangladesh_Mask_study_a_Bayesian_perspective

So effectively, there are no study conclusively showing that masks are effective...

Which has been clear for over a century to whoever applied the mechanical approach, as in physics classical mechanics ;)

On the other hand, we have loads of conclusive studies on the detrimental (side)-effects of masks.

The only reasonable thing to do at this point would be to forbid masks as a medical intervention against covid (and probably any airborne virus).

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