2/n The article in question is a review of face masks. At face value, it's essentially an opinion piece arguing that masks are ineffective ncbi.nlm.nih.gov/pmc/articles/P…
3/n Digging a little bit deeper, some of the stuff in here is pretty obviously wrong. For example, this incorrect statement about 99% mild/asymptomatic is referenced to Worldometers (not a specific graph, just the site)
4/n This excerpt in quotation marks is not a direct quotation, and is given totally out of context from the source article by Fauci et al
5/n So the piece is wrong about COVID-19. But it also appears to be wrong about masks quite a lot
6/n For example, here's a paragraph where it is simply assumed that facemasks cause chronic hypoxemia/hypercapnia. The four references are 3 physiology textbooks and another review piece
7/n The WHO document referenced here was updated December 2020 and now completely contradicts both this assertion and indeed the entire paper
8/n So, I think it's fair to say that this opinion piece probably doesn't represent either a scientific study or even really evidence per se, and it gets a lot wrong about both masks and COVID-19
How did it get published?
9/n Well, the journal itself gives us a hint
The description alone of Medical Hypotheses is pretty interesting stuff
10/n Reading some previous work published by the paper gives you an idea of what kind of "novel, radical" ideas which "would be rejected" elsewhere they sometimes put out
11/n (In the journal's defense, they do also put out lots of less fringe hypotheses, they appear to take seriously the idea of giving everyone's ideas a forum for discussion)
12/n As to the Stanford connection?
Well, the author appears to be a physical therapist at a hospital near Stanford that has an affiliation for teaching purposes with the university
13/n We can split hairs, but I'm not sure this qualifies as saying that the study is produced by Stanford
14/n Anyway, regardless of what you think about masks, the paper has numerous errors and is probably not a useful resource for determining whether to use them or not
15/n None of this has stopped anyone citing the "study" as evidence of anything, of course, because no one checks the facts of things they agree with!
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"Chronic disease has caused COVID-19 deaths, if we didn't have so much diabetes fewer people would've died" - incredibly dumb argument for many reasons, not least that it is true of LITERALLY ALL HUMAN DEATHS
Yes, if we had solved the biggest medical issue of the modern age fewer people would've died of COVID-19
What of it?
I mean, seriously, we've been trying to 'fix' NCDs for decades, and while they are in theory somewhat preventable they are still a large and growing problem in most places in the world
The basic idea here is that we could be either undercounting or overcounting COVID-19 deaths
I think the most likely explanation is some combination of the two
Based on some very careful examinations of death reporting systems, we can say that there are probably some portion of deaths that are recorded as due to COVID-19 but were not caused by the virus
Many places in India had very large initial epidemics, and it has been proposed that some cities (i.e. Mumbai) might have been at or near herd immunity towards the end of last year
The new massive waves even in areas with many infections before raise several possibilities, none of them great
1. reinfections 2. variants 3. large over-ascertainment of past infection
In the US, the exact incidence of COVID-19 infections per week is hard to estimate, but it's probably been about 10% of the whole country infected since January (roughly), for a weekly incidence of ~0.5%
The vaccines used in the US are 80-95% effective, and about 100 million people have been vaccinated in that time period
Fascinating study demonstrating the issues with selection bias in seroprevalence estimates
Using a selected sample of participants, the estimated prevalence of past COVID-19 infection doubled (!) nature.com/articles/s4146…
The study is really interesting. They used an existing representative sample of people aged >30 to estimate the population prevalence of antibodies to SARS-CoV-2
They then added a second group. These were people who had not previously signed up to the existing cohort, but were eligible
An update on this whole bizarre experience - the journal has now published a "typeset" version of the paper, which has deleted the lengthy personal attack
There are quite a number of issues remaining, but this at least is good
The author has now included a slightly odd statement in the appendices. It's worth remembering that the original appendix contained a number of factually inaccurate statements about myself and co-authors
I would also suggest that hurting people's feelings is a bizarrely patronizing thing to say. Defamation of PhD students in published scientific work is about more than "feelings"