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Jason Abaluck Profile picture
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1 Sep, 14 tweets, 3 min read
With dozens of researchers at Yale, Stanford, Berkeley and IPA and several other organizations, we ran a cluster randomized trial involving almost 350,000 people and 600 villages in Bangladesh to assess the impact of community masking on COVID.
We conducted an intervention that increased mask-wearing by 29 percentage points using the techniques described here:
With this 29 percentage point increase in mask-wearing, we saw a 9% drop in serologically confirmed COVID.
The reduction was larger in villages where we (randomly) used surgical masks than those where we used cloth masks; in surgical mask villages, we saw a 12% reduction in COVID overall and a 35% reduction among those aged 60+. Image
Since severe morbidity and mortality are concentrated among the elderly, this suggests that community-wide masking can be an extremely effective tool to combat COVID.
If going from 13/100 to 42/100 people wearing masks leads to reductions of the magnitudes above, near universal mask-wearing (as is possible with enforced mandates in some areas) might lead to substantially larger reductions.
As noted, we find especially convincing evidence that surgical masks are effective. Cloth masks reduce COVID symptoms, but the effect we find on symptomatic infections (confirmed via blood tests) is driven by surgical masks.
Cloth masks are likely better than nothing, but surgical masks or masks with higher filtration efficiency should be preferred to cloth masks where available.
A longer discussion of our intervention is available here, along with the underlying working paper: poverty-action.org/study/impact-m…
In subsequent posts, which I'll link here when available, I'll say more about how our study fits into the existing literature, as well as caveats and policy implications.
In the next few weeks, we'll post a public GitHub package with all of our data and analysis (with identifiers removed).
Some follow-ups: I should note that the PIs on this project were myself and @mushfiq_econ (economists at Yale), @Kwong_Laura, Steve Luby and Ashley Styczynski, epidemiologists and environmental scientists at Stanford (and in Laura's case, now Berkeley!).
The promised thread on how this fits into the existing literature is here:
The promised policy / cost-benefit analysis thread is here:

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More from @Jabaluck

Jason Abaluck Profile picture
13 Sep
This is a very important point -- masks prevent COVID and are valuable in places where many people are dying of COVID. Currently, this is many places.

However, that doesn't mean that a cost-benefit analysis suggests, "everyone should wear masks until COVID is eradicated"
The value of masks in places where nearly everyone is vaccinated is clearly lower. Caution is necessary since, in many parts of the world, the vaccines being used have lower efficacy than in the US, meaning that masks likely have value on top of vaccines.
Additionally, masks may prevent breakthrough cases which may eventually spread to unvaccinated people. However, I haven't seen a quantitative calculation of the magnitude of this benefit -- it may be small.
Read 10 tweets
Jason Abaluck Profile picture
5 Sep
An intuitive way to grasp the effectiveness of masks: extrapolating from our results, every 600 people who wear masks for a year in public areas prevents 1 person from dying of COVID given status quo death rates in the US.
Note that this is *taking into account current vaccination rates in the US*. Despite the availability of vaccines in the US, the weekly death rate is higher than at any point prior to November 2020.
Here is how I arrived at this number. Our study shows that inducing a 30 pp increase in mask-use prevented 35% of COVID cases among the elderly.
Read 15 tweets
Jason Abaluck Profile picture
5 Sep
Academics need to engage with people spreading dangerous misinformation, especially under the guise of technical jargon.

If you do not respond, no one will and the world will be less informed.

The kind of engagement @jhausdorfer wants is *not possible* on the needed scale.
The idea that we should patiently educate the aggressively ignorant sounds laudable, but it practically means disengagement. How many who liked the above post consistently attempt to do this? They might try once, but they'll give up because it's too time-consuming.
Here is the thread:


Here is my response:


Note that the original post received a fair amount of attention. This is not a case where signal-boosting is a concern.
Read 18 tweets
Jason Abaluck Profile picture
3 Sep
For those keeping track at home, this is definitely not what a confidence interval is. A 95% CI is a function of the data such that, given the data generating process with an unknown true parameter, the CI constructed in this way will contain the true parameter 95% of the time.
The idea that all values in a 95% CI are equally likely is preposterous. If one were instead constructing Bayesian credibility intervals, you do not need a gaussian prior to rule this out.
In the Bayesian problem, this would represent an absurd corner case where the data was completely uninformative about the underlying parameter within a specified range. I can't imagine how this would be a reasonable model of the situation at hand.
Read 5 tweets
Jason Abaluck Profile picture
3 Sep
To frame this as "mask advocates" vs. "vaccine advocates" is to thoroughly miss the point.

Everyone on earth with access to vaccines should get vaccinated.

Masks are also a powerful tool against COVID, and you've misunderstood what our study says about them.
@MartinKuldorff
Firstly, our study does not say that masks can only prevent 11% of COVID. Our study says that our intervention -- which raised surgical mask-wearing from 13% to 43% -- prevented 11% of COVID cases, and 35% among age 60+.
To put the point on your own terms -- if you vaccinated 30% of the population, would you prevent 35% of cases age 60+?
Read 14 tweets
Jason Abaluck Profile picture
1 Sep
I do agree that vaccines are probably even more effective than masks but there are three very important subtleties here that make the 11% way too conservative @ProfEmilyOster.
First, the 11% comes from a 30% increase in mask-use. The IV estimate (naively scaling things linearly) would thus be more like a 37% reduction in COVID from going from zero to universal masking.
Second, we find much larger effects among the elderly (a 35% reduction among 60+ without the above scaling). This suggests that the total reduction in morbidity and mortality from universal masking may be considerably larger than even the 37% number, perhaps more than 50%.
Read 4 tweets

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