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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Replying to @GidMK
I may be getting it wrong but would you mind checking your calculations? I get 1.07% and 1.51% respectively using the formula above. I use 90.2% for sensitivity and 99.2% for specificity as provided in the paper. [I get 0.65% and 1.11% for the sensitivity analysis of the authors]
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Replying to @MikeDeeeeeee
So, I was slightly off in those numbers, it's actually 1.56% vs 2.09% using the main results and the sens/spec from the internal validation study rather than the manufacturer. You have to take into account that some infections were confirmed by PCRpic.twitter.com/5jpxWkUItP
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So it's 1.8-0.2 = 1.6% for masks and 2.1-0.4 = 1.7% for non-masks, corrected that becomes 1.34% and 1.46%, add back in the PCR (for whom spec is ~100%) and you get 1.54% and 2.06%
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Replying to @GidMK @MikeDeeeeeee
Ugh, just realized it should be 2.1-0.6 for the non-masks, which changes the numbers again to 1.54% vs 1.82%. Same general problem, an estimated 1.68% infected in the study
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Replying to @GidMK
Sorry to be a pain, but can you check your Rogan-Gladen correction and/or the sensitivity/specificity numbers you use? When I use the formula, I get lower true prevalence. In the fully corrected version of yours, I get to 1.04% (masks) and 1.43% (control).
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