8/n A reduction in risk of infection of 20% would be a bit meaningless to the individual but HUGE at a population level, so this is not a minor point
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9/n The study also DOESN'T show that WEARING A MASK is ineffective. It showed that PROVIDING MASKS AND TELLING PEOPLE TO WEAR THEM was ineffective ON TOP OF SOCIAL DISTANCING
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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
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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
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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
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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
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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
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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
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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
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17/n This sounds like a minor point, but it actually isn't - if only 1.59%/1.95% of people were infected, it means that the study was underpowered for its main analysis, and thus we can't conclude much from the results
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18/n Sorry, small correction - I used the final totals of 1.8% and 2.1% not the actual antibody numbers of 1.6% and 1.7% in that calculation. If you apply the correction properly, you get 1.56% masks and 2.09% non-masks
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19/n For some context, to find a difference this small, the study would've needed to recruit about 24,000 people, or 12,000 in each group, which is about 4x as big
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