Our paper, "An evidence review of face masks against COVID-19", written by a cross-disciplinary team of 19 international experts, was published in the Proceedings of the National Academy of Sciences today.

No time for the paper? Then read this thread!
pnas.org/content/118/4/…
The paper, which includes 141 references (yes, I read every one of them!) argues that we should increase focus on a previously overlooked aspect of mask usage: mask wearing by infectious people ("source control"), rather than only mask wearing by susceptible people ("PPE") Image
Masks have been used to help control respiratory pandemics for at least 600 years. Wu Lien-Teh (the "Plague Fighter") showed the world the importance of masks nearly 100 years ago, doing detailed studies over many years.

Sadly, his work became largely forgotten in the west Image
Unfortunately, it's impossible to study the impact of masks as source control using the gold standard: a "randomized controlled trial". That's because you can't really tell whether a mask wearer infects others or not. So we developed a new framework to study this topic Image
There are a number of very strong multivariate population-levels studies that are strongly suggestive of the impact of mask wearing. Particularly that of @ChrisLefflerMD et al
ajtmh.org/content/journa… Image
We were lucky enough to have one of the world's top aerosol scientists, Prof Vladimir Zdimal, on our team, who helped explain how masks can block infectious particles, and the impact of aerosols Image
Personally, the studies I found most compelling are those that simply physically showed that masks literally block the ejection of respiratory particles Image
We were lucky enough to have @zeynep and @HeleneMarivdW on the team, who explained the sociological considerations around mask wearing, including looking at risk compensation behavior Image
We wrote the first version of this paper back in April, and it became the most viewed paper of all time on any topic, on preprints.org.

One key section we've added since that time is "Further Research" - that's a lot we still don't (but need to!) know Image
We should all wear a mask.

pnas.org/content/118/4/… Image
Thanks too all my great co-authors, @arimoin, @larrychu, @zeynep, @lexfridman, @austinvhuang, @Hernandez_Danny, @ArneDelft, @HeleneMarivdW, @AmyPricePhD, @reshamas, Z. Li, C. Ramirez, L. Tang, V. Zdimal, C. Bax, G. Watson & V. Tang

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More from @jeremyphoward

20 Oct
Wow. Schools being told they're not allowed to use air purifiers bought by parents, because they're "not needed" based on an "audit".

BUT the audit was done when schools were closed. So they haven't actually measured CO2 with students present! 1/🧵
theguardian.com/australia-news…
Principals are being told that air purifiers could make air quality worse if not maintained properly.
But Prof Lidia Morawska says it's "strongly recommended that schools that do not have ventilation systems capable of keeping indoor particles down be equipped with air purifiers"
If you're wondering who Lidia Morawska is - she's one of the world's top experts on safe air and COVID.
abc.net.au/news/2021-09-1…
Read 13 tweets
18 Oct
It's so easy nowadays to throw together a statistical test on a computer. But software doesn't help much with study design and interpretation.

In today's post I look at what can go wrong. 🧵
fast.ai/2021/10/17/con…
A recent review paper about Long Covid in kids was widely discussed in the press. The headlines were reassuring...
journals.lww.com/pidj/Abstract/… Image
...but as it turns out, the paper didn't really say what the headlines claimed.

(Although I did see an author of the paper making the headline claims on social media and in videos.) Image
Read 21 tweets
4 Feb
I’m hearing comments that Grid AI (Lightning) seem to have copied fastai's API without credit, and claimed to have invented it.

We wrote a paper about our design; it's great it's inspiring others.

Claiming credit for other's work? NOT great 1/

mdpi.com/2078-2489/11/2…
PyTorch Lightning is a new deep learning library, released in mid-2019. The same team launched "Flash", a higher level library, this week.

fastai was launched in 2017, based on extensive research.

As you can see, they look *very* similar. ImageImage
The quote below is from the Flash launch post (h/t @tomcocobrico). It is very clearly not true.

fastai's focus has always been simple inference, fine-tuning, and customization of state of the art models on new data in a matter of minutes.

Read 20 tweets

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