Last week I presented to the WHO Guidelines Development Group. It was targeted towards infectious disease epidemiologists, but many folks have asked me to share the presentation.
So, here's a video discussion. Read the thread below to see each slide. 1/
The evidence that WHO relies on for its mask guidelines has many problems. For instance, the meta-analysis they sponsored only has 3 non-healthcare studies, 1 of which is wrongly categorized, and one of which is under-powered. None studied COVID-19.
The review had three studies of SARS-CoV-2 in healthcare, but largely ignored them, by using inappropriate statistical techniques. (See the tiny weights in the right-most column.)
We didn't expect it our article make much of a difference, frankly. We're just data scientists, in our niche area of deep learning. Our most popular post, introducing @math_rachel's Natural Language Processing course, is our only post ever that has topped 100k unique readers
The extensive coverage of so many topics in this paper is only possible because of the breadth of expertise of our international author team, including epidemiology, biostatistics, aerosol science, sociology, infectious disease, computational modeling, data science, and more.
Want to take your mask wearing to the next level, and maximize the protection to yourself, in addition to protecting those around you? Here's some tips... 1/
Protecting yourself is harder than protecting those around you, because the droplets which are ejected when unmasked people speak evaporate quickly and are hard to filter.
Here's a mask my mother-in-law made with some great protective features.
There's a small long pocket at the back which is open at both ends. I use a small piece of rolled up aluminum foil in it. This is used to provide a moldable nose clip which helps minimize the gaps around my nose, like a surgical mask.
The paper is the first to report results of real source control experiments with COVID-19 patients, so it's important. It only used 4 patients, which isn't great, but it's a fairly simple mechanical test so hopefully the results will hold in larger samples.
Here's the key table. Note that these are logarithms (base 10), so we need to "undo" that with 10^x to get the actual viral load. "ND" means "not detected"; ie the viral load was zero, or too small to be detectable. As you see, 2 times the cotton mask blocked so much it was "ND"
We've just completed a 19-author analysis of the effectiveness of mask wearing, with 84 references. To explain what the science shows, I teamed up with the wonderful Prof @trishgreenhalgh CBE, who just led a British Medical Journal study on this. (thread)
Our team's review of the literature found substantial evidence in favor of widespread mask use to reduce community transmission, based on droplet dynamics, mask material analysis, efficacy studies, and behavioral studies. Here's our paper: up.fm/masks
The key insight is that most discussions assume that the purpose of the mask is to protect the wearer, since this is what all doctors learn about in medical school. But actually masks work *far* better at blocking the infection at the source. This is called "source control"
Get the scientific evidence, quotes from experts, DIY recipes for homemade masks, media coverage, and everything you need to know about why we should all make a mask, and wear it when in public. Masks4All.co
Folks are sharing this chart, from the paper "High Temperature and High Humidity Reduce the Transmission of COVID-19", & are saying that the claims of the paper are rubbish, because this isn't showing a strong correlation.
The chart does, indeed, not show a strong correlation. If this chart was the basis for the conclusion of the paper ("High Temperature Humidity Reduces Transmission") then it would, indeed, be rubbish.
But that's not the basis. The paper has bad visualization, not bad modeling.
The paper is actually based on a rather heroic effort of careful contact tracing and analysis of chains of 105 contacts across each of 100 cities. It's thanks to China's massive investment in tracing, starting Jan 20.
The impact is already clear. In Italy, 10 days ago, all was fine. Now it's not. 432 medical tents have been set up. 16 million people are on lock-down.
By the time the impact in your community is clearly visible, you've missed your best opportunity. 2/
If you are in a position of authority, you should be doing everything you can to avoid the need for groups of people to get together (provide sick leave; make meetings virtual; cancel events or make them online; etc...)
For everyone else, here's a list of things to do: 3/