| > Article 2 has a whole lot of pre-prints with data in the citations This is yet another news article, written by a journalist (Lynne Peeples, who wrote the other Nature news article you've shared upthread) who is mostly re-hashing her previous article. Did you read it or follow the citations? This is an excellent example of hearsay: if you don't take the time to read the citations in detail, you won't realize what you're missing. Most of the citations here are same citations in the previous Nature news article. Only citations 4-8 deal with the question of masks' impact on transmission (the remainder are for other questions, like whether vaccinated people can be infected). Of the papers in citations 4-8, two are new. Both are based on mathematical models using self-reported survey data and/or state-level case data. I don't know how good these papers are, but all studies of this form are low-quality medical evidence. Unfortunately, bad journalists can re-hash the same crappy studies faster than skilled people can debunk their work. > Talking with friends who are virologists, they all seem to agree masks help. That's meaningless. You can find a sample of scientists to support pretty much anything. > What's wrong with... https://journals.plos.org/plosone/article?id=10.1371/journal... So many things. The paper uses survey responses (= bad data), and tries to correlate it with state-level infection curves (= blurry data), and only does it for a month-by-month difference for every month between April and September 2020, when cases were falling across all of north america. It sets arbitrary thresholds for "high cases" and "high mask wearing". It doesn't control for confounding factors, like other policies the states in question might have enacted. This is a terrible paper. I cannot believe PLOS One published this. It is embarrassing. > https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7883189/#__ffn_... This is not a paper, it's a review. It presents no data. It summarizes the authors' opinions on other papers. |
We don't have so much about COVID 19. On the community level it looks promising for me, the papers are flawed but coming out.
What I am missing ... where is the other side of the coin. All models are wrong but some are useful. The particle simulations are wrong, but pretty useful (and I don't see why COVID should behave differently). What model do you base your assumption that masks don't work? Is there research that supports your claims? All science is bad science :) Some is useful.
> survey responses (= bad data)? So any research based on survey responses is bad? It's a standard method in policy research. What data would you use to show the community effect of mask wearing?
I'm usually listening critically to experts in a field (not to dentists or surgeons), it seems people who claim masks don't work are not virologists and have not worked with the virus (COVID19): https://en.wikipedia.org/wiki/Christian_Drosten https://en.wikipedia.org/wiki/Sandra_Ciesek
Both strong in the pro mask camp. Are there virologists working on COVID 19 (in the lab) that are on your side of the argument?