10/n As the authors note, compliance was pretty poor. Lots of people were told to wear masks, but didn't Hard to say what this means for an individual wearing a mask 24/7pic.twitter.com/2vnN12EpVI
Epidemiologist. Writer (Guardian, Observer etc). "Well known research trouble-maker". PhDing at @UoW Host of @senscipod Email gidmk.healthnerd@gmail.com he/him
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10/n As the authors note, compliance was pretty poor. Lots of people were told to wear masks, but didn't Hard to say what this means for an individual wearing a mask 24/7pic.twitter.com/2vnN12EpVI
11/n Moreover, there was a lot of social distancing already going on in Denmark at the time - this means that we can't really say that MASKS are ineffective but rather than masks didn't reduce infection numbers significantly on top of social distancingpic.twitter.com/ciSXYlyR3n
12/n Again, this is not a minor point - masks may indeed not reduce infection numbers much during lockdown, but that doesn't say a lot about their effectiveness at other times
13/n Ok, a technical addition that is nevertheless important. The authors do not report correcting their result for the test sensitivity and specificity of their serology test
14/n Serology tests are used to find antibodies, and they are (as all tests are) imperfect So, usually we correct for the imperfections to get a better estimate of the true number of people with antibodies
15/n In this case, the study found that 1.8% of people in the mask group had antibodies, compared to 2.1% of people in the non-mask group But those are just the RAW figurespic.twitter.com/NtiZuV9Uml
16/n If we use the Rogen-Gladen estimator, which is a pretty standard correction for test characteristics, we see instead that 1.59% and 1.95% of people in masks/no masks were probably infected, respectivelypic.twitter.com/d4rPZ5kJVw
That's the result for per-protocol analysis where participants with missing baseline antibody tests are included (wrong as study period was towards the end of the first wave). The raw estimates for the sensitivity analysis where those participants were excluded are 1.4%/1.8%.pic.twitter.com/1GPYs34urC
Sure, but that doesn't correct for test characteristics it corrects for the possibility that they included people who they shouldn't have in the study
Correct, that's why I think you should run the correction on those numbers from the sensitivity analysis, not their main numbers.
Oh right. Yes, but either way it doesn't make a difference to the OR, and it reduces the number below the powered figure
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