5 ms·
tl;dr- There wasn't really a conundrum to explain related to mask-effectiveness at different levels. Rather, it's more like a lack of good data, as prior stud
by _Nat_ 5y ago
tl;dr- There wasn't really a conundrum to explain related to mask-effectiveness at different levels. Rather, it's more like a lack of good data, as prior studies being cited were ridiculously weak.
---
This seems like a largely helpful characterization.
However:
> So they are left with a conundrum that places which use surgical masks seem to be better off, whereas randomized control studies of surgical masks show little to no benefit. This is what they try to explain with a mathematical model.
There wasn't really a conundrum. When the study writes:
> Moreover, randomized clinical trials show inconsistent or inconclusive results, with some studies reporting only a marginal benefit or no effect of mask use (5, 6).
, the two studies they cite with inconclusive data are ridiculously weak.
The first one (their "5") is [https://academic.oup.com/jid/article/201/4/491/861190 https://academic.oup.com/jid/article/201/4/491/861190]. This was published in 2010, with data from 2006-to-2007, for "influenza-like illness" (not SARS-CoV-2, nor even influenza (explained below)). Apparently they asked students living in the dorms to do certain behaviors for weeks at a time. They concluded:
> Conclusions: These findings suggest that face masks and hand hygiene may reduce respiratory illnesses in shared living settings and mitigate the impact of the influenza A(H1N1) pandemic.
And if that sounds inconclusive, yeah.. their study was ridiculously under-powered. In fact:
> This study has several limitations. First, influenza incidence was low, so it is likely that most ILI cases were not associated with influenza infection, even though the study was conducted during the influenza season.
So not only were they not writing about COVID, apparently the authors argue that most of the cases probably weren't even influenza. There're other huge problems with this study too.
The second one (their "6") is [https://pubmed.ncbi.nlm.nih.gov/33205991/ https://pubmed.ncbi.nlm.nih.gov/33205991/]. This study assigned subjects a recommendation to wear masks -- presumably some who were recommended to wear masks didn't, while some who weren't recommended to wear masks did.
Even then, their statistical analysis was very noisy:
> Although the difference observed was not statistically significant, the 95% CIs are compatible with a 46% reduction to a 23% increase in infection.
And their stated limitations:
> Limitation: Inconclusive results, missing data, variable adherence, patient-reported findings on home tests, no blinding, and no assessment of whether masks could decrease disease transmission from mask wearers to others.
Point being that there's not really a conundrum related to things not fitting together so much as a simple lack of good data.
- ComodoHacker 5y agoThe problem is people are not lab mice, you can't purposefully expose a test group to a virus to get clean data. So you either have to work with noisy data (as the previous studies you criticize) or turn to modelling (as this study does). This doesn't negate their value in either case. No need to be so picky.
- _Nat_ 5y agoIn the absence of good data, the fallback is a position of ignorance -- not acceptance of bad data. The prior studies were neither well-done nor directly relevant. As such, they didn't constitute good evidence on the topic of mask-wearing for the recent pandemic. The proper understanding would then be that the effectiveness of masks was little informed by such studies.