Since masks is such a hot topic right now, I thought it was worth revisiting this story about a coronavirus outbreak among recruits at Fort Benning. (Ft. Benning Story) This significant outbreak occurred notwithstanding the fact that the recruits had enforced mask-wearing and social distancing. Yet infections still occurred, fortunately all asymptomatic and mild.
And here is the Center for Evidence-Based Medicine at Oxford University again cautioning that there is not evidence to support a benefit for masking alone in stopping community spread, or for that matter, health care worker transmission, of respiratory viruses. They note that politics is being used to cover up for the lack of evidence. Interestingly, they also list several pending clinical trials to test the benefits of masks. When those trials are complete, if they don’t find benefit, we will see if the mask brigade drops its insistence on 24 by 7 wearing. (CEBM Statement)
And while we are talking about the CEBM, here is a nice primer they put together on coronaviruses. (CEBM Primer)
And while we are talking about prestigious research groups and their mask reviews, the federal Agency for Healthcare Research & Quality updated its “surveillance”, or ongoing, mask evidence review, looking at one recent new study, and finding no reason to change its conclusion that “the strength of evidence for masks in community settings for prevention of SARS-CoV-2 infection is insufficient.” And just so you understand how pathetic the modeling studies the Dictator cites are, they aren’t even viewed as research that merits any consideration for purposes of this review. (AHRQ Review)
This is kind of an interesting study, one of many trying to ascertain factors related to cases, mortality or transmissibility. (JAMA Article) The authors examined 211 counties representing about 55% of the US population and compared temperature, population density and social distancing to ascertain any relationship to transmissibility. The authors appropriately note that transmissibility is not likely the same across wide geographic areas, but if you don’t adjust for testing policy variation and for undetected cases you are not getting a realistic answer on transmissibility, which is a measure of how the number of cases changes over time. In addition, the social distancing was solely based on cell phone distance measurements, which presumed to account for visits to non-essential businesses. That is also pretty worthless, especially since the single biggest piece of transmission occurs among households. So not the soundest methodology, but that seems pretty common in regard to coronavirus research. They found that all three primary variables were associated with transmissibility, inversely in the case of temperature and social distancing and positively in the case of population density. Given the weak approach to social distancing measurement, it isn’t surprising that they found it to have the strongest relationship with lower transmissibility.
New Zealand is getting all kinds of pats on the back for pursuing a suicidal policy of completely suppressing the virus and cutting itself and its economy off from the rest of the world. Really smart when you are a tourism and trade driven economy. But since the epidemic is supposedly over there, at least until the next person arrives at the country, these researchers did an examination of the characteristics of this very limited outbreak. (Medrxiv Paper) The country had 1499 cases, as far as it knows. Because of extensive contact tracing, the authors had a very rich data set. There were few cases in children under 10, children rarely transmitted to others and were less likely to be infected by an index case. Children were more likely to get infected once schools closed, since there was more transmission at home. Asymptomatic cases infected fewer people than those with real illness. 20% of adults were responsible for 65% to 85% of all spread infections.