Plain English with Derek Thompson - How the Media Failed Its COVID Test: The Truth Behind the Lab Leak and Masking Debates

Episode Date: March 7, 2023

Today’s episode is a long one: It’s about the debate over media coverage of COVID. Three years after the fateful March of 2020, when it feels like the world shut down for COVID, we are revisiting two of the most contentious debates in this space. No. 1: The lab leak hypothesis; which is the debate over the possibility that COVID originated at a laboratory in China and not, as the official story went, at a wet market in Wuhan. And no. 2: the mask debate. And why a seemingly simple question—do masks work—is so hard to answer. Today’s guests are Dan Engber, a science writer and editor at The Atlantic who has chronicled the ups and downs of the media’s relationship to the lab leak. And Jason Abaluck, a Yale economist who has conducted masking research in Bangladesh. Host: Derek Thompson  Guests: Dan Engber & Jason Abaluck Producer: Devon Manze Learn more about your ad choices. Visit podcastchoices.com/adchoices

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It's about the debate over media coverage of COVID. Three years after a fateful march of 2020, when it felt like the whole world was shutting down, we are revisiting two of the most contentious debates in this space. Number one, the lab leak hypothesis, which is the debate over the possibility that COVID originated at a laboratory in China and not as the official story went at a wet market in Wuhan. And number two, the mask debate,

which touches on a seemingly simple question. Do masks work? Which turns out to be very, very, very hard to answer. So why these topics and why now? The answer is that news in these domains simply won't stop breaking. Last month, the Department of Energy revised its prior assessment and announced that the coronavirus likely did emerge from a laboratory. The FBI shares that assessment. Four other agencies and the National Intelligence Council have come to the opposite conclusion

that COVID-likely started with natural exposure to an infected. animal at perhaps a wet market. So if you're doing the lab leak math at home, the lab leak theory itself is still an underdog trailing five to two among these government institutions, none of which, by the way, have reached their conclusions with a high degree of confidence. The lab leak is interesting to me for two reasons. First, it's a pretty important question. How did a pandemic that has killed millions and millions and millions of people actually start? That's a biggie. Not just because we don't have perfect information, or just because we don't have perfect information, doesn't mean we shouldn't be curious about this. I remember, as a poli-sci major at Northwestern,

I think I took four separate classes about why World War I started, and the answer in every single class was like, no one's really sure, but there's a lot of interesting theories that have informed political science. Well, if we take the Labley theory seriously, as I think we should, it should make us deeply skeptical about many policies that are active in the world, like funding gain of function research, sort of viral engineering, that should it escape the lab, could cause precisely the global catastrophe that we saw, or perhaps something even worse. The second reason the lab leak theory is interesting to me is that this is really, in many ways, a story about the media, how I, we, the press, choose what to cover and choose who to listen to, how we choose

which stories are considered information and which stories are considered misinformation or disinformation. For many months, especially in 2020, in early 2021, a lot of journalists, smart journalists, trying, I think, in many cases to do the right thing, kind of assumed that the lab leak

was a racist conspiracy. In fact, I know many prominent journalists in their outlets simply said, you know, scientists don't take this seriously. Neither should you. But now in 2023, I think if we're being honest and if we're really interested in the truth, the idea that the Lab League was merely discredited racist conspiracy theorizing, that itself was a kind of misinformation.

It was a story that kept readers and audiences from appreciating the actual uncertainty of this important question. There's another story that deserves a reappraisal, and that is the media's treatment of masks. I think it's fair to say the media and the science community have been all over the place on this one. In March 2020, Fauci famously told us we didn't have to wear masks. And then months later, of course, wearing a mask was a marker, maybe the marker of how seriously you took COVID. Some scientists very quickly seemed to revise the estimation of the essential effectiveness of masks. But then a few weeks ago, in February 2023, a meta-analysis of masking research published by the esteemed health organization, Cochran, was widely reported in the media as proving that actually masks do nothing or close to nothing.

And mask mandates do not work, period. End of story. But as you're about to hear, even that review, even that. Even that summary of the evidence is extremely misleading. So, like, what are you supposed to do about all this? Like, the lab leak is neither a fact nor a myth. Masks work, except very often they don't, and asking people to wear masks can work,

except very often it doesn't work at all. You try to keep all this in your head, and it's a mess. It is a mess. journalists sometimes like to clean up a story, make for a simple headline. I think we need to be better at reporting on uncertainty, especially, especially when there is a political or ideological undertow that is pulling us to one side of that story.

When we see a mess, we have to call it a mess. So don't trust people who in their handling of complex questions with imperfect data, do this trick where they manufacture simplistic answers with perfect confidence. Trust people who get in the weeds, trust people who see the mess for what it is, trust people who change their mind

when the evidence changes. Today's guests are Dan Engber, science writer and editor at the Atlantic, who has chronicled the ups and downs of the media's relationship to the lab leak, and Jason Abiluck, a Yale economist who has conducted some of the more famous trials of masking and who, as you're about to hear, has actually not only objected to the Cochrane meta-analysis, the famous Cochran

review, but has actually talked to a member of the Cochran team and just maybe convinced him that he's right. I'm Derek Thompson. This is plain English. Dan Engberg, welcome to the podcast. Thanks for having me. Before we start, a brief story, I don't know if you remember this, but I think you edited the first article that I ever wrote as a professional journalist. No, I'm sorry. You were at Slate. I was an intern at Slate.

I was interested in writing an explainer about how the government knows how many miles we drive every year. Is this an explainer that you have any memory of having edited? I mean, Derek, I edited or written hundreds, possibly thousands of explainer columns. I left no impression. It's a good topic. Congratulations to us both on producing that story. Does the story hold up?

I believe it does hold up. And in a weird way, it kind of connects to what we're going to talk about today, because it's fundamentally about the question of epistemology. How do we know what we know of whether it's miles that Americans drive on roads or exactly where a novel coronavirus originated? So I've been interested in this question for a while. And you, I think, have been one of the most careful journalistic voices on piecing through the evidence on both sides of this question and being really clear about what level of certainty we should have about answering this question. But I want to start with 2020. When did you first start following the lab leak theory?

When do you remember hearing about it, having any emotional reaction to it? So I remember hearing about the work that had been done at the Wuhan Institute of Virology. before I heard about the idea of the lab leak hypothesis, actually. And so I think as, as, you know, most people would, when they hear that in 2020, they go, that's weird. Wait a second. Hold on. How likely is it that this kind of research would be happening in Wuhan, China, of all places,

and now we've got this pandemic unfolding. So actually, that, you know, the blatant coincidence hit me. me first before I was aware that there was kind of this shadow discourse happening about how likely it was. And I will say I was totally tuned out on the politics stuff. Like I wasn't aware of Tom Cotton wrote an op-ed about, you know, saying it was a Chinese bioweapon. All of that stuff got fold in, for me, and I think also we can talk about this for the media, got folded into this sort of like Trump versus the science narrative. about, you know, the China flu and how Trump was blaming all of these failures of his own administration on China.

So I kind of slipped very easily into that story of like this was the thing that was happening, right, in terms of the politics of it. And that was disconnected from any underlying scientific truth. But I still wondered about that coincidence. And I thought, hey, that's really odd. And then I think I kind of, you know, didn't dig too deeply into it until the Nicholson Baker story came out in New York Magazine. And I remember feeling relief that someone had, you know, done that story and gone big on it. And then, of course, that set off a bunch of angry reactions and we went from there. But that was the very end of December 2020, if I remember correctly. And how would you characterize the media's reaction to the lab leak theory in 2020 and early

2021, say just before the Baker piece comes out in New York Magazine? And to my recollection, really crystallizes this sense that despite the fact that in the mainstream media, there hasn't been much talk about taking the lab leak theory seriously, introduces this idea that actually there's been a kind of shadow discourse happening where people have been poking around and asking can we find smoking gun evidence that this came from the Wuhan, from WIV?

Yeah, I mean, my recollection as an editor, you know, editing stories about the pandemic then, was that it was just incorrect. We just knew it was incorrect. It was, you know, there's almost like copy-paste macro you could put into a story if this were an issue. You know, scientists say this is not the case.

And particularly what I think was missing there, and I take responsibility for this as an editor editing COVID stories at the time, was deep thought about the different shades of what lab leak theory or hypothesis could mean. So again, this was kind of all lumped together into the most extreme version of it. That was easy to dismiss.

that had been dismissed in prominent venues by leading scientists. And that would be kind of the Chinese bioweapon theory of this. So once that was all swirling together in your head and the politics of it made it very easy for that to be one's notion of what LabLeak meant, it just was like you just knew that was just a false narrative, one of many false narratives that were swirling around at that time. And so it was just not something to cover. The Baker piece, I mean, really goes into much more nuance about like what kind of lab accident might have been in play. What was the research that was going on? And even just the history that was, I think, if you hadn't been paying attention, you didn't have this in your head about, you know, lab accidents in recent years or the moratorium on gain of function research that had been put in place.

during the Obama administration. So I just thought it was incredible that Baker brought all that to the fore, told the story of these arguments about the dangers of doing this kind of urology work, and just forced everyone to look at this. I mean, still, I would say it would be another five months or so before really the mainstream media

was looking closely, but that was the first one where it just, at least for me, I was like, okay, I need to actually go beyond my initial thought of, hey, that's a weird coincidence to start taking this very seriously. I'm really glad that you pointed out that the media's reaction to the Lab League early on

was a kind of mess of conflation. There's all these things that you have to sort of keep in the air, that Trump was explicitly anti-China in a way that many liberals found to be racist, number one. Number two, that many Republicans were getting over their skis, that COVID was a bioweapon and that it also was a bioweapon that emerged from a lab. So right there you have the conflation of lab leak equals bioweapon plus lab leak equals normal

virus or not engineered virus that comes out of a lab. And I think that there was a liberal or mainstream media leaning liberal, eagerness to disprove the lab leak hypothesis that was basically just displaced eagerness to reject Chinese racism and bioweapon rumors. but this created a really weird discourse space. I remember in the fall of 2020, I was having a conversation with my wife and her friends. I remember we were in the bathroom.

Her friends were on speakerphone. And we were just having a conversation at the end of like some Friday where my wife and I had made dinner together. And they said, we were talking about conspiracy theories. And they said, Derek, what conspiracy theory do you believe? And I'm not a conspiracy theorist. Like, I just don't dabble in them generally.

All conspiracy theorists say that, by the way. Go on. Okay. And that's going to set up my next thing I'm going to say very well. I said, you know, I have a lot of time for the theory that this virus came from a lab. And the reaction was like, wait, we know you're not racist, but that theory is kind of racist. And my feeling was, you already articulated this. Well, look, it's not racist to say that a good candidate for the emergence of a bat coronavirus

is a local laboratory that studies bad coronaviruses, right? I'm not saying here's the truth and the doubters are a bunch of idiots. I'm saying, we have a crime, and this is a reasonable murder suspect that we should consider in the investigation. But it's really interesting to think back to that period and remember just how strange it was to take the theory seriously. So let's continue the TikTok. The Baker article comes out in New York Magazine. It inspires a pretty fierce backlash among some people. But in the months that follow this approach of, I want to describe this carefully, taking the lab leak

seriously, without saying, I believe it to be true in any kind of like probabilistic, more than 70% kind of way, that became more common among certain journalists. Would you agree? I would. I mean, I wonder if you wouldn't mind doubling back for just a minute, because I actually in this last piece I wrote about the Lab League, this little behind the scenes thing. But I wanted to represent it as having been so politicized from the start that it was, you know, Democrats and Republicans disagreeing fundamentally on this question from the get-go. And then I went back to find, you know, is there a speech that Chuck Schumer gave in 2020 where he was talking about this? And the answer was no. This was something that Republican lawmakers

were talking about a lot, a Republican and, you know, conservative columnists and such. But it's not something that, you know, Democratic lawmakers were talking about. This is, was it was sort of like not Republicans versus Democrats, but Republicans versus the media, basically. And then having been in the media at the time, we were taking our cues from the scientists. So, you know, I edit science stories, work with science journalists who talk to scientists. And so I think what was happening was you were getting a lot of news stories that reflected the quote-unquote scientific consensus. as probed by journalists calling a bunch of people who are scientists who are prominent on Twitter, maybe.

But in any case, and they were being told, there's no doubts here, we know where it came from, and they were reporting that accurately. And then it was the segments of society that are distrustful of elite authority, including scientists who were saying, we don't know if we believe that. So I felt like that was,

I don't know if this is worth bringing up, but I actually, I thought it was interesting that in writing my last piece about this, I realized I had distorted my own, my own memory of what had happened was distorted. I thought it had been like overtly politicized from the get-go.

I think in a sense it was, but not in this, you know, explicit left-right way. It was like this, you know, elite's right way, kind of, which is, I think, a little bit different. And I think important, as it plays out now. But we can go back. I'm sorry to divert.

No, that's really interesting. Let me just dig into that a little bit further. What I said earlier is that a lot of left-leaning people, left-of-centered people in the media, might have conflated their insistence on rejecting Trump racism and downplaying the odds that this was a bio-weapon. They conflated that with discrediting a lab leak entirely. You're saying something that to my ear sounds a little bit different, which is that it's not that the

media was necessarily or exclusively biased against Trump or insistent upon just proving the bio-weapon theory. It's also that the media was taking their cues from scientists who were prominent for whatever reason. Maybe they had the most Twitter followers. Maybe they were the co-authors of whatever was just published in the Lancet the previous month. But they were taking their cues from prominent scientists who were insisting that the lab leak was an improbable, if not impossible theory to explain the pandemic. Is that right? Yeah, I think that's right. And I agree with both parts of it. I mean, I think this was overdetermined, and that's why you got this, you know, effective media blackout on the idea. You had both the political inclinations were lined up with what scientists from Fauci on down were saying. And so, easy to make the judgment then if you're not being careful. Have those scientists recanted in any way?

I know that Fauci in the last few months has said at least something along the lines of we don't know for sure whether this came from a lab. We can't prove for sure that it didn't come from a lab. He seems to have walked back his 2020 position a bit. Is it your sense that those scientists now talk about the question of the lab leak in a slightly different way than they did in 2020 and 21. Yeah, I mean, I think for sure, Fauci is a great example.

But other scientists, too, there's been a lot of cases of, you know, some new piece of information. I remember when it came out that some of the key research that was being done at WIV was being done at biosafety level two instead of three or four. That led to some, you know, prominent scientists saying, you wait a second here.

If I'd known about that, or when the DARPA grant proposal came out, this was a grant proposal that involved WIV that was, you know, outlined experiments that sound, in retrospect, pretty scary. Now, there's no indication that these experiments were actually done, to be clear. But just to have this stuff on paper in official grant documents, I mean, I interviewed scientists who are like, now I'm beginning to say, you know, at the very least, there's such a lack of transparency. here, like, why wouldn't this information have been put out there from the beginning? It's so clearly relevant to the question of pandemic origins. So I just, in the course of reporting on this since whatever, the beginning of 2021, I've heard scientists describe, you know, one said to me, the delta is shrinking. I remember that phrase, meaning his assessed probability of a natural origin versus the laboratory origin, he still felt it was more

likely a natural origin, but the delta is shrinking. So I think about that as the overall trend since the beginning of 2021. What I love about your coverage at the space is that I think you're very good at pointing out how amazingly coincidental both theories are, both the lab leak theory and the national origin theory. And I want to just quote from your last article in the Atlantic, because I think it sums up something very important, very succinctly. Very succinctly. quote, if COVID really started in the lab, one position holds, then it would have to be a pretty amazing coincidence that so many of the earliest infections happened to emerge in and around a venue for the sale of live animals, which just happened to be the exact same sort of place where the first SARS

coronavirus pandemic might have started 20 years ago. But also, if COVID really started in a live animal market, it would have to be a similarly amazing coincidence that the market in question happened to be across the river from the laboratory of the world's leading bat coronavirus researcher, which happened to be running experiments that could, in theory, make coronaviruses more dangerous. Dan, we are in the realm of like crazy unlikely thing one versus crazy and likely thing two, both of which require an extraordinarily unlikely roll the dice for them to cash out in a global pandemic. Right. And we know for a fact that one of those two things, is really just a coincidence.

Do we know for sure that it can either be only natural origin in Wuhan or a lad leak at WIV? Is it conceivable that the actual origin of the pandemic is some category three phenomenon? Frozen fish imports into China. I mean, sure, it's conceivable, but I mean, I'm stuck on those two coincidences personally. So I think it's got to be related to one of those two things. I would also say just, you know, while we're stating where we stand on these things,

you know, I've said in the past, the fact that there are these two enormous coincidences that have to be reckoned with doesn't mean that it's necessarily the evidence is a toss-up, it's a coin flip. There are many other things to take into account. And probably the most significant for me would be what's the history of pandemics? I mean, basically every single one has started with a so-called natural origin, with one possible known exception. So, I mean, if you're using that to decide to judge the tie, tie goes to natural origin, right? And I don't even know if the evidence really is quote unquote tied otherwise.

But that's just, that's the backdrop here. and I think that is also contributed to the attitudes in 2020 and attitudes today among scientists, right? Like, we know this story. It's a story we've heard before and the evidence is consistent with that story, so why not? Aside from the fact that, as you said, almost every pandemic for which we have

a high degree of confidence in the origin, the story is always human, excuse me, animal to human spillover. other than that, what do you consider the most persuasive facts or maybe even most interesting rumor that should make a reasonable person lean toward this pandemic started from natural spillover from a wild animal? Okay, aside from that fact, which I do think is a very significant fact, right? Again, it's going back to that coincidence, this market. should, it's, this could, you know, everyone agrees, even people who think it, um, started in a lab, everyone agrees that this market was one of the first, if not the first major cluster of infections,

right? So, um, that's fine. You know, maybe a scientist left work infected with, um, the coronavirus and then went to pick up some groceries at the market. Like it's, you can, you can tell that story. But again, like, this is a market. where we have photos of these wild animals, live wild animals for sale from 2019 from a study that was a paper that was published subsequent, much subsequent to the start of the pandemic. There are many other places in the city

where that first big outbreak could have happened. You know, we don't think about in the, since then, we haven't thought in the U.S. about, you know, market, big markets as being a place, as the place where super spreader events happen. We think about it as like conference centers or concert venues or restaurants or bars or airplanes or whatever.

Those are the stories we keep hearing. So why was it a market selling live animals in Wuhan? I find that the most compelling part of this, aside from, again, the long history. And on the other hand, what would you say is the single most compelling fact or most interesting rumor that might make a reasonable person, let me be careful here,

either lean toward the lab leak theory or dramatically increase in their own minds the odds that this was a lab leak. I mentioned the DARPA proposal before. I don't know how useful that is in particular, because again, we don't know that those experiments were ever carried out. But I do think as an elaboration on the mere fact of there being research on bat coronaviruses in Wuhan a thousand miles away from caves

where closely related viruses were found. And we know that samples were carried from those caves back to Wuhan. So we have all that stuff. We also have all this evidence that experiments were being done at that institution to tinker with the viruses. you know, see what happens? What if you combine this bat coronavirus with that one or with, you know, some element of the MERS virus? So we just, again, we don't have any evidence that such experiments were done using viruses that could conceivably be a precursor to SARS-CoV-2, the one that caused the pandemic. So there's no direct evidence that research was being done of the type that could lead to the pandemic. But there's lots of evidence that research that's kind

in the realm of mixing and matching viruses was being done right there. So I find that just, again, going past the initial giant coincidence thing, that extension of it, I find worrisome, to say the least. I really like the way that you set up those coincidences, and it makes me think,

you know, John Stewart had a very famous segment on the late show with Stephen Colbert, where he put forth his theory for why, he thinks the lab leak idea is probable. And he said, I'm butchering it, but I think this is an okay summary, if you hear that there's an outbreak of chocolatey-goey goodness from Hershey, Pennsylvania, you have to be an idiot to not rule in the fact that it came from the big chocolate factory at Hershey. But what you're saying is actually, actually like takes that joke metaphor and usefully edits it. It's more like we have an outbreak of gooey, chocolatey good

from the nation of Switzerland. And like, there's many possible points of origin, whether it's lint or Nestle, Toblerone, there's a bunch of different chocolate factories that would be absolutely ideal candidates for the origin of an outbreak of chocolate gooiness. What you're saying is, it seems to me, Wuhan has these two points of origin

that one might reasonably rule in, a research facility that researched exactly these kind of viruses and a wet lab, a wet market that we know from the history of pandemics is a plausible place of origin for viruses that spill over from a bat to a pangolin to a human. So, I mean, I actually hadn't thought of it in exactly these terms, but it's more like the chocolate outbreak came from Switzerland than the chocolate the outbreak came from Hershey, Pennsylvania. Yeah, I don't think that got distracted. by all the different chocolate manufacturers you mentioned. But just to complicate it a little bit, two things.

First of all, it's not like there are 100 wet markets like the Huanon market in Wuhan. There's a small handful that were known to be trafficking in these sorts of animals. So I think that's important to just to kind of build out in your mind an understanding of what kind of coincidence this would be if it didn't actually start there. Similarly, the Wuhan Institute of Ferrology is not the only place in the city where potentially dangerous research might have been carried out. In fact, though the details are mysterious and classified, it has been said or has been reported that when the Department of Energy updated its assessment of the source of the pandemic and said with low confidence,

that they think it's a lab leak. That had to do with some idea that it took place at a different lab, a branch of the Chinese CDC, I think, which is rather close to the market, I'm told. So this is sort of like a quality of this whole conversation is that as soon as you can sort of say, oh, well, there are these two big coincidences,

and then everything gets parsed a step further, and now it's complicated, and now maybe it's not this institution, research institution, it's this one, which is not really across the river and so on and so forth. I think that the overall structure of the debate is still the same, two big coincidences. But I'm just bringing this up.

I don't know how to work this into your chocolate analogy, but I do think it starts to get complicated pretty quickly when you start adding in these other pieces of information. Yeah, I'm going to stick with the Switzerland metaphor because what you're basically saying is like there's a bunch of chocolate manufacturers in the analogy, right? There's a bunch of different plausible origins for this virus in the same city. And that just makes it difficult, especially in the absence of anything approaching an agreeable and open Chinese government to arrive at a final truth.

I want to bring in that as the last piece of evidence. Do you consider the reluctance of the Chinese government to play ball a useful piece of evidence for either side of this debate? I don't. I don't. And I will say that from the beginning, it has seemed to me not great from China's perspective for the answer to come out in either direction. I mean, as we said before, like if SARS won started 20, stars one started 20 years ago, possibly through a wet market like this. And now it's happened again. And this time it's, killed millions and millions of people. Like, why the hell was this allowed? Like, who's responsible for that? So it's not like the natural origin has the Chinese government off the hook for this.

So it seems to me that leaving it undetermined is probably the best possible outcome as far as China is concerned. So that has always been my assumption for what's going on here, that there's really no interest in resolve it one way or another. It doesn't look good either way. So why do it? Why let the studies happen? Put on your media professor hat, you're teaching a class at wherever, Columbia,

Medell, about the lessons that responsible young journalists should take from the lab leak fracas. What's the lesson? That is a fantastic question. And I think it goes back to, you know, there are some easy lessons I could, I'm tempted to draw. But I really want to grapple with the fact that, again, you're a science journalist in summer 2020. You want to know what's the thinking on this. And every scientist you call tells you the same thing. Like, how are you supposed to arrive at the, you know, do you then call Tom Cotton? Like, it just doesn't make sense.

You want to report the science of this. it's really tricky and I would say because of that and this may be self-interestier but I'm not, I have trouble blaming science journalists at least as much as

maybe I ought to it's tough like there's a lot of interesting work on this was done by this rag tag group of independent researchers communicating on Twitter through anonymous handles. As putting on my journalism professor hat,

am I going to tell students to reach out to, you know, lab leak seeker 10 on Twitter? You don't know who the person is. You're going to quote them. It's tricky. I mean, I think the lesson here, as far as I'm concerned, is more about what we do next, which is continuing to cover this, doing accountability journalism about the lack of transparency from the start, about the lack of transparency that still exists,

not entirely due to a Chinese cover-up of some kind, but also due to the lack of transparency in terms of what was happening here. I mean, I think we're going to find out in a couple days when these hearings start in the house. There's probably going to be a lot of crazy shit thrown around at those hearings. But I think there are substantive questions about what ideas were taken seriously behind closed doors and how those conversations related or didn't relate to what was said in public by, you know, science officials within the administration and by scientists in the know. That's a really interesting lesson.

One thing that I took from it is that it's hard as a journalist to keep in mind two things. One, your sources are smarter than you. They know more than you. You have to rely on them. But also, they're not smarter than God. People with PhDs and fancy resumes are just people. And people are wrong all the time. And consensus within industries or disciplines can be wrong all the time.

and you can be captured by sources. The same way we're familiar with the fact that some writers are captured by their audience. Their audience expects them to be, I don't know, anti-trans. And so all they do is write just bullshit about being anti-trans. I'm reminded of two different events that I'm not trying to directly analogize to the question of the Lab League. But there are a lot of reporters around 2003 who I think were captured by their sources around the issue of the Iraq War. And they reported that WMDs existed because there were, a lot of people in the Bush administration,

around the Bush administration, who were going to tell them that. And if that's what your roster of sources was, then you were just going to hear one message over and over and over again. You could be captured by those sources to report that which was not true. To a certain extent, in my own closer to home,

in my own sort of domain in economic analysis, it was something close to an article of faith in mid to late 2021, that inflation was just not a serious problem, that it was going to go away very quickly, that it wasn't going to pose much of a problem to people, that it wasn't going to get that high, that there were just a few blips in terms of supply chains,

but everything was going to come down to normal relatively quickly. And the next year, 2022, inflation and rising interest rates were probably the most important phenomenon in economics. And you could create a roster, a bank of really, really smart academic voices who for whatever reason, their rooting interests in Joe Biden, the fact they were a little bit more left-leaning,

they were a little bit more captured by MMT, just did not believe that the U.S. was anywhere near an inflation crisis. And I think it's really hard and important to remember that even the people that you talk to as sources, even they feel kind of like little gods when you're reaching out to them to dig yourself out of ignorance for peace, they can be catastrophically wrong as well.

It might just be an important piece of intellectual humility to keep on your shoulder. I think that's exactly right. I mean, I think there's even a specific way which this relates to science journalism so that if I were putting on my science journalism

professor hat, which is a little different from just journalism professor in general, there is this way in which there is kind of an ideology among science journalists that they hold in alignment with many of their sources that you should follow the science. There's an elision between small S and big S science, right? And this gets, you know, really snagged on political divides as well, especially in recent years. But even leaving the politics out of it, you know, there's this, the difference between science communication and science reporting can kind of fade. And one can get confused about

is what I'm doing good for science as opposed to getting at the truth. One can forget that science, capital as science, which your sources are almost always representing, is an institution of its own accord that needs to be held to account that has its own motivations and its own biases. So I think, again, putting all the sub-politics aside, putting China out of it, there was in the background, this sense that the idea that scientists caused the pandemic is bad for science. That's like, you know, it's in the same world as anti-vaccine sentiments. It's like fanning the flames of conspiracy theorists that say, you know, that don't want us to listen to science. And so as a science journalist, I think a lot of science journalists feel like that's part of the mission of their job to promote rational thinking. And rational thinking in this case is aligned with what the scientists are saying and what's in the best interests of further study.

And like I think in 2020 probably there was an idea of not science got us into this mess, but we need to be as sciencey as possible to get us out of this mess. Like, we need those vaccines. We need to figure out as soon as this is over. We need to use science to figure out how to prevent the next one. So the idea that, oh, the scientists who are trying to prevent pandemics, because that's what the research we're talking about was about, they actually caused the problem. I think it's just sort of on this deep level politics aside

went against the core beliefs and inclinations of most of the journalists who are covering that question. So I totally agree with you. breaking out of that mindset is crucial. And not just in covering, you know, pandemic origins, but in doing any science coverage, you need to understand that you're, you know, it's not a big business,

but it's kind of like a big business in a lot of ways. Science is hard. It's a, it's the simplistic, but unfortunately, entirely true conclusion. You cannot just be so much of a contrarian that you become a crank, but you also just cannot simply believe someone by virtue of the fact that they have credentials with more initials than you have. It's a very, very difficult thing to get right.

The truth is changing constantly. And that at the end of the day is what this episode is about. Dan Engber, thank you so much. Thanks a lot for having me, Derek. That was Daniel Engber, writer and editor at The Atlantic. And next up, we have Jason Abiluck of Yale University. Jason Abeluk, welcome to the podcast. Great to be here.

Jason, before we talk about masks, tell me a little bit about what it is that you study at Yale. Sure. So I'm a professor of economics at the Yale School of Management. Most of my work is in the areas of health economics and public policy. So I do a lot of work about different ways that we can evaluate the quality of people's choices and how we can design institutions like health insurance markets, for example, in light of the fact that people often might not be well-informed about what impact choosing different health insurance plans would have on their health outcomes. So questions of that nature. When people sort of make mistakes, how can we design institutions that still work well in light of mistakes?

And what is your recollection of the conventional wisdom in 2020 around masks? Because to me, when I think back, and I do not pretend to have perfect recollection about that incredibly chaotic year, this is a really chaotic question to answer. My recollection is at the WHO and Fauci came out initially in the middle of March and said, you know, masks, not so sure that they work. And then for some reason, within three to six months, the fact that masks did work became an article of faith among people that share my general ideology and proclivities. And then later you had this backlash among people, some of whom are firmly in the science community, who said, nope, masks actually don't work at all. And all you people covering your face or participating in

some kind of apocalypse cult. What is your own memory of the pendulum swinging on the mask issue during the pandemic? So I can tell you a few stories about what I was involved in in 2020, but I think the way you described it sounds about right that the pendulum swung back and forth many times. But basically, my introduction to this, I think in March of 2020, when there were maybe a few dozen cases of COVID in the United States, one of my colleagues came up to me and was like, Jason, there's this debate, you know, on Twitter about whether people should start wearing masks about COVID. Like, what do you think about this? And my initial response was something like,

well, you know, we probably should, like in the sense that it's a super low cost thing. It's like at the time, I didn't realize, you know, COVID would be endemic and this would go on for years. At the time, there was some possibility that's like, oh, there's just going to be this wave of cases over the next six months and, you know, maybe we should wear masks to do something about this. And the idea was, well, it's super low cost. It might be effective. Why not? So then I sort of started to look into it a little bit in March and April of 2020. And I looked at some of the existing evidence, which I believe actually included an earlier version of the Cochran Report, the Coch Review, which was an article, basically a summary article written. And there were several

summary articles. And I might, by the way, be misremembering whether it was a Cocker review or other similar reviews. But basically, the upshot of those reviews was typically that, like, there's been a bunch of studies of masking in hospitals and in what's called community settings. And in hospitals, they would do things like, oh, let's randomize people to surgical or cloth masks, or let's randomize them to N95 or surgical mass. And typically, they would find, yes, when we gave people the higher quality masks, they were more protective. against, in those cases, like influenza. Then there were community studies.

And the consensus in most of these articles at the time was something like, well, masks worn by people in hospitals work and community mask wearing doesn't work. And that's kind of a weird thing. And it's like, what does it mean to even say like community mask wearing doesn't work? Like what were they basing that on? And what they were typically basing that on were studies that would do things like, oh, you know, we went to a college campus and we wanted to see if math, were protective against influenza.

So we did a randomized experiment where we took people in the intervention group and we sent them masks and we gave them instructions about how, you know, mask and protect you against influenza. And we said, hey, can you wear this mask during the flu season? And typically they would do those studies and they would find, hey, there's no difference between the people we sent masks and the people we didn't send masks. Now, when I looked at this initially, my reaction was like, well, it's kind of a lot. of a weird study because they don't tell us how many people actually wore mass.

So given that masks were effective in hospitals, presumably they'd be effective in the community as well if people actually wore them. And in these studies, they just don't wear them. But of course, now that we have this COVID epidemic that's going to kill millions of millions of people, you know, people will actually wear masks and that would be protective. So I actually wrote this paper in March and April of 2020, where I was like, look, I don't think that a lot of these existing studies actually tell us much about mass. So what we're going to do is compare, you know, countries with historical mass norms like Japan or Taiwan.

And we're going to see if COVID is spreading at a different rate in those countries. And the answer was, yeah, it seems to be spreading more slowly in the countries that have historical mass norms, although, of course, things are difficult. Why is it difficult? There's many reasons. One reason. It's really difficult is because those countries might be different in lots of other respects, right? So it's like in Japan, sure, they wear masks, but also maybe they do more testing and maybe

they do more contact tracing and all these things like maybe they were just more cautious and all these things could have led to slower spread. So it's not totally clear that was attributable to mass, but there was some indirect evidence that it was. So that was kind of the early 2020 period. I wrote that paper. I actually went to the Yale COVID Task Force. my colleague and I, and we were like, hey, why don't we put out an announcement that suggests

in light of this that, you know, we would recommend that people start wearing masks as COVID is spreading in the U.S. So this was, I believe, in late in March of 2020. And the Yale COVID task force, there were two groups there. There were epidemiologists who were like, yeah, this seems like a pretty reasonable idea. And then there were clinicians who were like, you, economists, this is crazy. Like, the FDA would never approve this. given the existing evidence. We can't recommend the people wear masks that the FDA would never prove it.

And also, they were like, but we know they're important in hospitals. And if you recommend everyone wear masks, then we're not going to be able to have masks for people in hospitals. So we were like, okay, what about if we recommend they wear cloth masks so that they still have enough masks for people in hospitals, although surgical masks are really cheap to produce. Anyway, so we got some people to sign on to like a statement,

like everyone should wear a cloth mask. That was like April of 2020. I think by, you know, May or June, like there was this rapid shift in sort of the conventional wisdom about this, where all the public health agencies went from basically being like, oh, you know, we're skeptical of mass to basically saying like, oh, actually, this is something like we're going to start recommending everyone wore it and that sort of like changed the polarization. And then for, I'd say, the next like year and a half, that was the conventional wisdom among public health agencies.

I still think that is mostly the conventional wisdom that they've kind of public health agencies, if you talk to people like the World Health Organization or whatever or the Center for Disease Control, they're still pretty much, yeah, mass are probably pretty effective against COVID. Although I agree with you. There are some people like the authors of the Cochran report who are, you know, epidemiologists and legitimate scientists who have reached a different conclusion, although we can talk about. Let's talk more about why. Let's hold the Cochran review for a few more minutes. I want to ask you about this study that you did in Bangladesh. Tell me about the study.

Tell me briefly why this study was importantly different than the community studies that you have just blasted in the last few minutes. And what did you find in the Bangladesh study? Yeah, okay. So there are a few major differences. So basically what we did, first of all, is we went to Bangladesh. We went to 600 villages. And in 300 of those villages, we did a really intensive campaign to try to get people to wear masks. So we sent everyone in masks, we gave information about masks,

but then we also worked with a bunch of community leaders like imams and like village leaders to try to promote mask wearing. And maybe most importantly of all, we had people walking around in every village in crowded public areas and in mosque saying, hey, suppose you see someone who's not wearing a mask, walk up to them and be like, hey, here's a mask. Can you please put this on? Right. So it's not like they're arresting them or something, but they're just applying social pressure.

They're being like, hey, can you please put this on? if people say no, they say no, but like there's not that much militant resistance to mask wearing. So most people say yes. Okay. So we did this experiment. How is this different from what came before? First way it's different is we actually observed whether people wore masks in crowded public areas. So we can see if we changed their behavior.

In our initial pilots, we didn't change their behavior very much because we just sent the masks and gave them information. And mask wearing increased by something like nine percentage points. which is actually high relative to other studies that have done similar stuff. There was one study in Kenya that found like a one percentage point increase from giving people information in handing out mass. So we found like a 9% point increase. But then we're like, we need to do more than this.

So then we started doing the people walking around asking people to wear masks. That got us to a 30 percentage point increase. Okay. So that's a pretty appreciable increase. So what else is different about this study relative to all the other ones I was talking about, including my own earlier study? well, it was randomized. So I mentioned before the problem that it's like Japan, Taiwan, et cetera.

We see lots of mask wearing, but they might do lots of other things differently. In these villages in Bangladesh, the 300 villages where we did this campaign, those were randomly chosen. There's one thing that's systematically different about those villages, which is we did this campaign to get a bunch of people to wear masks. Okay? So then we could see what's the impact of mask wearing? And the answer is we saw basically a 10% decline in COVID. symptoms and we did blood tests to see it was actually COVID and we also saw 10% decline in what's called symptomatic seropositivity. So people who are symptomatic for COVID and also their

blood was seropositive for COVID. So what does 10% mean, by the way? How do we interpret that magnitude? So we're saying a 30 percentage point increase in mask use led to a 10% decline in COVID. So how do you extrapolate that to what if everybody wore masks, right? It's not completely obvious, but a back of the envelope, simple thing to do is just to like assume everything scales. So if 30% wearing masks you 10%, maybe 100% is about three times, maybe you get like a 30% decline in COVID infections. Is a reasonable conclusion to draw from this study? Because I know that there are some mass skeptics that read your study and they say,

okay, it took Jason and his team an unbelievable amount of money. You guys got millions of dollars from Gibwell. It took you an unbelievable amount of money, extraordinary amounts of enforcement, like annoying amounts of enforcement. You're there on the streets pointing at people saying, ah, mask, up, mask. And all of this, all of this only increased mask wearing by 20, 30%. I mean, that's not, that suggests that the typical mask policy is not,

not going to be very successful. So how do you feel about the critique of this study that says that the effect size is not large enough to prove to us that the average mask mandate is going to do anything? Yeah. So first of all, it's a really good question. So one thing we need to keep in mind is so one takeaway, you might be like, oh, well, it's just impossible or it's really hard to get people to wear masks. But of course, we know that there are some places where lots of people wear masks. So first of all, it's like Japan, like almost everyone wears masks. Now you might say, okay, fine. In countries with historical mass norms, it's possible, but it's just too hard everywhere else. But even in the United States, there were places that had really, really high compliance

with mask use. There are places where 90% of people were wearing masks in 2020 and in 2021. Now, it's important to draw the distinction between, can you change? change behavior and how many people do with it. So what is hard about doing this type of study that we did and what is a major deficiency of the earlier studies is getting people who aren't motivated on their own to wear masks to change their behavior. That requires doing something. Now, that's something might be that you mandate masks.

You make it a rule with different kinds of enforcement. Like in the United States, a lot of states mandated mask wearing. What did that mean? typically if they saw you in public not wearing a mask, you know, it's not like they're arresting you and dragging you to jail immediately. It's kind of like this recommended thing that's variably enforced, right? Like maybe in the post office, they say, hey, sir, please put on a mask. And if you're just adamant that you won't, then they say, please leave and they'll take you out. Right. So those kinds of things do, if you have a church or a post office or whatever

public area and you ask people to please put on masks, most people actually comply with that. So what we're trying to do in these studies is to figure out the answer to two separate but both important questions. One question is just what would happen if people actually did comply and wear masks? And then a second question is like what kinds of things are actually effective for getting people to wear masks in practice? So my answer to the second question first is if people actually did wear masks, yeah, you probably get something like what we found in this study. It's if it in public areas, people wore masks. Now, that doesn't mean you wear it in 95, 24 hours a day, right? You go home, you're probably not wearing a mask, right? What we see in the study is this 30% point

increase in wearing masks in the mosque and wearing mask in the crowded market and things of that nature, right? So if people wear masks in these public areas, but not necessarily at home or anything, you know, you get this 30% decline in COVID in the medium term. Now, what does that mean? You know, that's actually complicated because one thing we can revisit is okay, you know, you have this 30% decline. One thing that might happen is, R was greater than one before. Now the rate of transmission is less than one. And so instead of COVID spreading to everyone, it doesn't spread to anyone because

they've ever wore masks all the time. Or alternatively, it's so contagious, it still spreads everyone. And then our mass doing anything, let's revisit that question. That's an important question. Okay. So one question is, what are the long-term impacts of this 30% decline? But the question we posed a moment ago was, what about other policies to try to get people to increase mask use? And my answer is, well, it really depends.

It's like if Alabama today said, hey, we're recommending everyone wear masks, nothing's going to happen. It does nothing, right? But on the other hand, if, you know, we have another respiratory pandemic and tomorrow, you know, in two years there's new COVID. And New York State is like, hey, new COVID is killing a tremendous number of people. we recommend that everyone put back on masks, like probably you get reasonably high compliance, at least among the people who aren't politically resistant. And there's a further point, which is even today, what about symptomatic people? If you're coughing and sneezing and you have to go out in public, maybe you should be wearing a mask. What about the elderly people,

people with comorbidies? Maybe they should still be wearing masks. So we definitely still want to understand if when you successfully wear a mask it works. And I think our study strongly suggests in light of especially some additional other evidence from all the other studies that like it probably does. Two rapid fire questions about this study before we get to the Cochrane meta-analysis, which was the subject of all these news stories for the last few weeks. Question number one, there was a difference in your study in the effect size for older people versus younger people. And it's hard, or at least my read of your study, says that it's hard to explain exactly what happened there.

Maybe older people were more conscientious because they were at higher risk. But does that gap make you concerned about confounders that you can't explain in this study, that something else happened that's just not being captured by the variables that you've talked about? I mean, I find that gap, especially concerning. I agree with you, there's many possible explanations we could give for why it happened, include many that have nothing to do with confounds or anything like that. Like it could be, for example, it could be elderly people wear masks at similar rates,

but what happened was that elderly people have like fewer social connections. So wearing a mask is more likely to sort of cut off the transmission vectors. And therefore, it has a bigger impact on their likelihood of getting COVID. Or it could be that elderly people are more vulnerable to low viral loads. And so, and that's mass, you know, turn low into nothing or whatever, and then it prevents them from getting COVID. Or it could be that elderly people, we actually couldn't observe by age. We could have in retrospect, I wish we did, but we didn't observe by age, whether the elderly

people just increased mass use by more. That's certainly another possible explanation. But it's an interesting finding because, you know, obviously the elderly bear, the bulk of the morbidity and the mortality from COVID. So if it is generally true, for example, the explanation I gave earlier that elderly people get infected by low viral loads and masks prevent that, then that would be a huge thing to know. But I think from the study, it's hard to, like, we would want sort of multiple studies of this type before we concluded that, yes, masks are definitely more effective in the elderly or something

like that. Second follow-up question, when we say masks, most people are referring to a bunch of different things. Some people wear bandanas, some people wear cloth masks, some people wear surgical masks, some people were N95s, some people were K-N-95s. What is just briefly, because I really do want to get to the Conkwin stuff in a second, what's the difference? Is there a major difference between these categories that we use the noun mask for? So in terms of the effectiveness, so in our study, we had in one third of the treatment village's cloth masks, and in two thirds we had surgical mass. We find stronger evidence for the effectiveness of surgical masks, although both cloth and surgical mass appear to have reduced symptoms.

we have a much more precise estimate for the impact on the blood test of COVID for surgical masks. For cloth masks, it's actually, it's just imprecise. So we can't rule out that they're about as effective as surgical masks. But from other studies like studies in hospitals, it seems like surgical masks are better, also from just laboratory studies, from people cough into a petri dish. In our study originally, the reason we did both surgical and cloth, surgical are actually cheaper. But people at the time, this was, you know, 2021, especially, in countries like Bangladesh, they sort of regarded surgical masks as these cheap throwaway masks.

And so we were worried that people wouldn't bother. They would wear the surgical mask once and throw it out and they keep the cloth masks. In fact, we found they wore the surgical masks as much or more. So it's not really, that wasn't really a concern. So like if you can, higher quality masks are more productive when you're looking for protection. And by the way, another point I should make that I realize we haven't made yet. We haven't talked about like what I think are the actual policy consequences of this. or anything. But just to be clear, I'm not saying, oh, mass work, therefore everyone should be wearing masks all the time, everywhere they go everywhere in the world. Like, there's a different

question of when are mask mandates called for. You know, COVID fatality rates are 20 times lower in the U.S. than they were in like July of 2021. They're 40 times lower globally. That makes a big difference to the cost-benefit analysis of when we need mandates. But anyway. And we're going to get to the difference between masks, do they work as a product and mask mandates should they be implemented as a policy at the very end of our conversation. But all right, let's finally turn to the Cochrane meta-analysis, this famous or infamous meta-analysis that was reported in the New York Times, probably most prominently in a column by Brett Stevens, an opinion columnist for the Times under the headline, The Mask Mandates Did Nothing. Will Any Lessons be

learned? He quotes journalists saying that masks don't make any difference, full stop. He quotes co-authors of this meta-analysis saying that masks make no difference, none of it. Tell me, let's go into it this way. What is the question that the Cochran analysis was trying to answer, and why do you think the studies that it used don't provide a high-quality answer to that question? Absolutely. So there's a difference between the question they were trying to answer and the question they did answer.

So it's hard for me to speak to the question they were trying to answer from some of the quotes in the study and some of the quotes I've seen publicly from the authors. By the way, I have some anecdotes about that. I've now spoken at length to one of the authors and I'm trying to speak to others. So we'll get to that in a moment. But from their public comments, it seems like they wanted to get at this question of basically are masks effective against COVID. If a person wears a mask, does it make them less likely to be infected? if a population wears the mask, does it slow the, or wears masks more,

doesn't slow the spread of cope. That's not the question they answered because the vast majority of the studies that they are summarizing are the studies that I was talking about earlier, which are the studies that, for example, send people on a college campus mass. And they ask, hey, please, like, wear this mask

during flu season. And then they don't check if you actually wear the mask. And can I just jump in here? Because you pointed me to a couple of studies that make this point very, very clear. There's a famous Danish study, which was often used in the media to suggest that mask interventions did not work. When those researchers reached out to the participants, they found that fewer than half of the masking group said they, quote, wore the mask as recommended. End quote.

There was a study in Uganda, 2022, that when researchers called the participants by phone, 97% said they, quote, always or sometimes wore a mask. But these researchers also observed people in Uganda on the street, and only 1.1% of the people they observed were seen wearing masks correctly. That suggests that the share of people saying they wore masks versus the share actually wearing them correctly was a factor of 88. 88 times more were likely to say on the phone they were wearing masks than actually were. It's very difficult in studies like this to know what you are actually measuring, because what you are measuring is a failure of adherence and a failure of self-reporting rather than a failure of a product. In terms of policy, we'll get to that in a second.

But I was very motivated by that finding. Back to you. So I totally agree with you. I would say there are three big deficiencies of the Danish study in this regard. So the first deficiency is exactly what you mentioned. That it's like probably, yes, you know, whatever, half the people said they wore masks. But, you know, we know that self-reports vastly overstate the fraction of people who actually wear masks. Now, the second thing about the data study is if you actually look at their bottom line,

they find that there was like 18% less COVID in the treatment group than the control group, right? Now, that's not a statistically significant difference. You know, in science, we care a lot about statistical significance for good reason. because if it's an insignificant thing, it could have just happened by chance. But what you absolutely should not infer from that study is like, oh, the mass didn't do anything. Because just the best estimate they have, granted being very imprecise, is pretty similar to what we end up arriving at in the Bangladesh study. Now, why is it more imprecise? Well, because the sample size was much smaller and because probably they got a lot fewer people to actually wear masks.

Okay. So what's the, what should we infer from this? Well, if anything, we should say, here's one very imprecise signal that suggests potentially similar effects to what we see in the Bangladesh study, not like, oh, mass don't work. That would be a crazy inference to draw from this because even the imprecise point estimate suggests that mass work. And of course, the true effect would have been considerably larger if you think that only a small fraction of the people in the treatment group actually were masks. So that's like the second deficiency. The third issue with this study, relative to our study in Bangladesh, is that it is only designed to figure out of mass protect individuals. It doesn't tell you even in principle if mass prevent symptomatic individuals,

or if mass prevent infected individuals from transmitting the virus to others. Our study in Bangladesh where we increase mass growing at the village level identifies the joint effect of mass. protecting individuals and preventing them from transmitting the virus. So even in principle, if all the other problems were solved, the study in Denmark can only get the protective effect, which nonetheless, you know, very imprecisely suggests might be there. But this highlights another answer to your question earlier of why is this hard? Well, it's hard because as common as COVID is, most people over any several month period are not infected with COVID.

So if you do a study where you monitor people for a couple months, it's not like 70% of people are going to get COVID. It's like, oh, you know, maybe one to two percent are going to get COVID. And then if you do an intervention such that you increase mask wearing by even the 30 percentage points that we manage to get, how much of that COVID do you think you're going to be preventing? Well, maybe you prevent a tenth of that. So now you've gone from one and a half percent to, you know, a tenth of that zero point one five. And then you actually have to do that. You actually have to do blood tests and not everyone is going to consent to have their blood drawn. So now you get an even smaller number. So you need a really giant sample if you're going to detect any impact

of any policy. So look, you have done the mask research. I have not. You have now spoken to the Cochran authors. I am so interested to know how that conversation went, because at least in terms of their statements in the media, they seem very clear on what their position is, which is that masks don't work. The end. You're telling me the exact opposite thesis. So how did this conversation go? Okay. So I've now spoken to one of them and I'm trying to schedule a call. There's the lead author, Tom Jefferson, who I have not spoken to yet, who is the main one making these remarks. But I will hopefully speak with them in the next few days. Maybe we'll do a two-minute addendum if you need an update on that. But for the author that I did speak with, so first I'll tell you the way

expected the conversation to go before it went, which is when I was in grad school, I had a professor Jerry Hausman. And Jerry Hausman told us the story where he's like, when there's a Nobel Prize winner, Clive Granger. And he met with Clive Granger and they had this technical dispute. And Jerry Haasman was like, yeah, we had one of these long drawn out academic conversations where I pounded him into the ground. Right. And I was like, I was like, uh-oh, this is good. But in fact, it was the exact opposite. So I talked to the guy from the Cocker report. And I was like, hey, here's what I think the issues are and he's like, yeah, those are really good points. And I was like, oh, and I was like, would you be willing to co-author and editorial like making these points that's

sort of the, the Cockren Review, I keep talking at the Cockerman Report. We'll just stick with that. I like that more. The Cocker Report has, that, you know, it's been misinterpreted in the press coverage and it's kind of the conclusion that mass don't work just isn't warranted given the studies you've included. And he was like, yeah, sure, I'd be having to sign odds to that. Wait, this feels like breaking news. This feels like breaking news. an author of the Cochrane Report slash Cochran meta-analysis is about to co-author an op-ed with you, saying that the report broadly interpreted by the media and quoted by some of the lead authors of the report, saying that Mass Managed to work, he's about to say it didn't actually show that?

Yeah, I feel like now you have me worried, making such a big deal of it, where it makes me worried that he's going to, like, hear this podcast. This is coming out Tuesday morning, I think. That is the plan right now. I sent him a draft. We're chatting more at five, so hopefully that'll happen. Jeez, well, it is for, listen, it's 237 p.m. Eastern Standard Time on Monday. We'll see what happens tomorrow and if he responds to that email by saying, never mind.

So give me a sense of what you think the smartest mask critics get wrong. Because I'll say this. We emailed. I talked to an. aerosol researcher, Professor Jimenez, about how masks actually work. The fact that he's very persuaded by the lab reports that, look, if COVID is an aerosolized disease and we know clearly that masks reduce aerosols going in and out, masks just, they have to work. This has to be an issue of adherence rather than an issue of public policy. So I wrote this up and I got a really nice

response, frankly, from some conservatives and some mass skeptics. And I got what I would characterize is a really not very nice response from some mask critics and mask skeptics. I would say there were two kinds of criticism of my attempt to synthesize some of your research. One line of criticism was that perfect mask adherence in a community is kind of like telling everyone they have to just like, like, trying to, like, banning sugar or, like, mandating that babies eat broccoli, or mandating that people just sort of fast when the sun is out every single day. It is, it's not that those things won't be, won't, like, reduce weight. It's that it's almost impossible to enforce. So why are we even keeping in the arsenal of public policy interventions,

something that we broadly understand to be unenforceable? Let's start with that. Do you, do you agree with the contention that maybe masks work, but mask mandates don't? And we should just acknowledge that that's the state of the world. Yeah. So let me first just draw a distinction between if everybody wore masks, what mask mandates do and what the studies in the Cochran Review do, which is the studies in the Cochran Review, it's like, oh, we're going to send people masks and give them information. We know that that has very little impact on that here. What about mask mandates. Mask mandates, I would say, that is one name for a wide variety of different things that sometimes increase mask use and sometimes don't. Like when airlines are like, hey, please put on a mask

or we'll kick you off the plane, they're really good at getting people to wear masks. When the post office is like, hey, please put on a mask or we'll kick you out, they're really good at getting people to wear mass. If the governor of a state is like, hey, we're recommending that everyone put on masks, you're not going to get to 100 percent, right? Like there's going to be resistance depending on the state. You know, it might. might be that you get in some states very little effect and in some states more of an effect. Like one study I saw just a correlational study looking across states. It has its own deficiencies suggested maybe like a 25 percentage point increase in mask wearing from mask mandates.

That's comparable to what we saw from our intervention in Bangladesh. So my view is not mask mandates don't do anything. They sometimes get people to wear mask more, but it's hard like at a national or a state level to suddenly change norms and get and get every person to wear mass. Now, there is nonetheless the question of like I think there are things depend on the underlying objective circumstances. If there were new respiratory disease that were five times as deadly as COVID, I would predict, you know, people would see their relatives dropping dead. They would want to do something about it. Now, it might be just because the way politics have worked that the U.S. would be weird. In Alabama, they still wouldn't wear mass.

but, you know, in most of the world, people would pretty rapidly adopt masks if there were a situation like that with such high fatality rates. So I think the answer is, you know, depends on the circumstance. It's certainly possible sometimes to get people to wear masks. And I mean, I don't think the analogy with like vegetables is even not great. Maybe for infants, it's kind of weird. But it's like, you know, we do research. We try to figure out what foods are healthy. I bet that people eat a lot more vegetables than they would if there had never been any research showing.

that, you know, vegetables were healthy and help you live longer and how you have your heart and dying some cancer and everything. And it's like, you know, that's why we do the research to figure out what it does, not because we think that tomorrow everyone is suddenly going to start eating only vegetables, even and not even because we necessarily think they should do that, because we want to know what should they do in different circumstances. The other objection that I've heard from the mass skeptics is that they look at a country like, say, Japan. And you talked about how, you know, you look at the COVID transmission rates in the West, in Europe, in the U.S., and you compare it to Japan and Taiwan in 2000,

and it's not even close. It's astonishing how much more it was transmitting in the West. But then Amicron comes around, and Japan, Taiwan, Hong Kong, they definitely had Ammocrine waves, even despite the fact that, and look, I'm not on the ground in Hong Kong, Taiwan, but I'm guessing that there was still a decent amount of mass adherence. Do you have even a stylized story in your head of how, these things can both be true. It's so funny, because I often see this argument on Twitter, and then I'm like, okay, so when I see an argument like this, my instinct is to be like, well, you know, let me look

at the numbers and try to do a comparison. So it's like, so then I like look up the fatality rates and it's like vastly lower in Japan than the United States. If you look at like how many people have died of COVID per capita, I'm trying to remember offhand. I'll probably get it wrong, but maybe it was like five times lower, 10 times lower. something in Japan than the United States. So it's like, are we saying that if everyone wore masks, no one would ever get COVID? Like, no, what the studies say is that it probably protects you.

And now we can come, we haven't spoken much about the question of the long-term consequences yet where I think there really is a lot of uncertainty about a number of factors of how, of what the long-term consequences of more mask wearing is. But like, I think the conclusion that, hey, these East Asian countries, the inclusion we drew in 2020, the East Asian countries had slower COVID growth is born out even more so today when you look at the long-term fatalities for the countries that had historical mask-wearing norms.

Let's get to that right now. In the article that I wrote for the Atlantic, I concluded going through all this mask research by saying, you know, there's still a cloud of uncertainty here, but we have to make discreet and irreversible decisions sometimes, even in clouds of uncertainty. So I'm just going to tell readers what I'm going to do. And what I'm going to do is, especially during periods of high COVID transmission,

and I would not necessarily consider this moment to be one of them, I'm going to wear N95 masks in public indoor spaces. Furthermore, I think that Washington, D.C., northwest Washington, D.C., which is my neighborhood, would probably benefit from a mask mandate because I have observed the social norm of mask wearing in my neighborhood, and there are a lot of high-quality masks worn well in this area, and I would expect that if more people wore high-quality masks well, that it would probably reduce levels of transmission within this neighborhood,

even as I suspect that you're right, that mask-mandate policies are not going to do much in, you know, Alabama. What are the risks? What are some of the costs that are important to consider when we're evaluating mask mandates as a public policy? Because, you know, you and I have both said a couple times now. Like, this is not something that's risk-free, and I've written about, you know, all these debates about masks and schools,

Tell me about some of the costs that are most top of mind to you when you think about masks as not a product, but as public policy. Let me first rewind to April of 2020, where I was trying to convince the epidemiologists, the ones who were reticent to recommend masks wearing. One of the biggest arguments they made was, oh, if we recommend that people wear masks, they will think they are fully protected and they won't socially distance anymore. And what we think they really need to do is socially distance, which I thought was a very interesting argument. In Bangladesh, we actually found the opposite. We found that in the villages

where we did the mass promotion, they socially distanced more. We think we can separate the effects. We talked about that. That's a separate issue. But so, but I mean, there's, it's, I think that's an open question. It might vary across context. There's different effects that go in different directions. I'd be surprised if the risk compensation were enough to outweigh the direct effect. Like in many settings, like with like seatbelts and airbags, this is something people have brought in economics, it's called a peltsman effect, that it's like, oh, you know, you, because you wear a seatbelt, you're not driving as carefully because you know you're protected. It's like, maybe that happens a little bit on the margin, but probably people are going to be

safe for wearing seatbelts and not wearing seatbelts. So yeah, okay, that's one thing, but that was the big issue like during large COVID waves. More generally, what are the costs? I mean, the biggest, most prevalent cost is just, it's kind of uncomfortable to wear a mask, right? I don't mean to be poo-pooing that. Like, it's like, how big. would the benefit have to be for it to be worth, you know, wearing a mask in, first, in like, public areas, suppose you're just going there for a few hours, right, during the day. You know, you're going to a mall or something and you're going to wear a mask in that mall. It's like, well, if you get the equivalent of, you know, $100 worth of benefit, it's probably

worthwhile to do it. You would probably do it for $100. But if you get $3 worth of benefit, maybe you'd just be like, no, I'd rather be comfortable. I don't want to wear a mask. So it is really important the magnitude of the benefits. So when I was saying earlier, you know, fatalities from COVID are 20 times lower than they were in July of 2021. You know, if the magnitude of the benefit was $100 in July of 2021, now it's $5. So that changes things, right?

So my general view of public policy is, hey, we should do calculations to see if the benefits would see the cost. Now, these calculations are very, very hard to do. as soon as you sit down and you try to actually quantify cost and benefits, what you find is you have to make lots and lots of assumptions for which you don't have good data. And one response that people have to this is anyone who does a calculation, everyone yells at them because everyone's like, oh, look, your assumption about X, Y, and Z is not supported.

And I disagree with you about this, this and that. But guess what? The alternative to doing a calculation is making shit up and guessing. And that is worse. That is even harder than making assumptions and trying to do a calculation. So my view is, you know, we should sit down. So what are the costs you talked about? For elderly people, or for most people, maybe the biggest cost is just mask wearing is uncomfortable.

Now, the other, in some settings, what we worry about is communication. So, for example, if you're wearing masks in classrooms, does that make it harder to speak? If the teacher is wearing a mask, can you not hear them as well? If the students are wearing a mask, are they less able to focus? Like if you're wearing masks in an indoor business area, is it harder to focus, so you're less productive? I honestly think we just have poor quality evidence on these questions. We just don't know much about how big those costs are. And then, of course, in younger children, you worry about various developmental things.

Where, again, we just have poor quality evidence, and we don't know much about the magnitude of the cost. So I think we know more about the magnitude of the benefits, but only in the medium term. The long-term benefits are hard to assess for reasons we can get into. Earlier in the episode, I had my colleague, Dan Engber, who's a science journalist, who's written a lot about the lab leak. And we talked a little bit about how the media's treatment of the lab leak in the last three years is an interesting lesson for science writers and journalists in dealing with clouds of uncertainty, not ruling out candidates, not ruling out stories simply because they seem like they might be racist or it seems like it might give credence to a side that you don't belong to or that it seems like it might undercut the benefit of science. It might have been hard for scientists in 2020 to say that actually maybe this pandemic started because of scientists making a mistake.

That might have been a hard thing for some people to admit. I'd love to ask you a similar question, which is what you think the debate about masking reveals about the way science and scientific communication is conducted today. Do you see ways in which this fight that we're having, not you and I, but that we as a country you're having,

this way that this fight is a microcosm of a really important story about how science works in America. My view is, I don't think there's anyone making like an obvious mistake. My view is kind of that like doing science properly is really, really difficult. There are lots and lots of things you can get wrong.

And so when you have like a highly politicized topic like masking, the world is always just going to be flooded with bullshit and the signal from the, like the actual signal from the truth is always going to be kind of weak. And what happens is like maybe over the very long span of history as more research accumulates and everything, then eventually sort of people figure out what's what. But it's just kind of the nature of things that like doing science properly is really, really difficult. And there's just a lot of subtle distinctions that are going to get lost in any political discussion so you don't journalists have a have a super hard job too. So, so like it's not something where

it's like, oh man, everyone's being so stupid. Why don't they just do this? It's kind of like, yeah, that's the way the world is going to be when you have a highly politicized issue. It's just really, really hard to figure out what the truth is. One thing I would say is there are certain communities that have like really good norms and it's those norms that sort of allow science to progress over the long term. Like there are communities where, and I would say like I think, I think like people who do, I consider my field of being what's called like applied microeconomics. Like we try to do empirical research and we try to design studies to sort of tease out the truth of things. I think it actually has very good norms in the sense that if you go to a seminar in our

field, of course, you know, everyone is political. It's not like people are perfectly objective and can get away from all the kinds of things you're talking about. But there's just a norm that it's like, you know, we're really trying to figure out what's true. Right. And so if someone has sort of like a counterintuitive result on like a hot button political issue. The questions aren't like, how dare you say this or I can't believe you would say this. It's like the questions are really going to be focused on like technical questions of methods. Like could you do this to maybe, maybe you should do this additional check because it might suggest whether this thing went wrong or you could get this additional data to try to do that. So I think there are some communities like that.

And the more of those there are, the better. And like one thing journalists can try to do is to like figure out where those communities are and try to get a little bit of signal from those. But you guys don't have an easy job because, of course, you know, there's a very hard meta problem in the world of how do you decide who has expertise and who you're to listen to and that's hard to do. A part of me wants to make fun of you for, you know, like saying, like, you know, microeconomist, colon, the world should be much more like the field of microeconomics. At the same time, in all honesty, and this is not just like, you know, blowing smoke up your

I'm in a lot of different communities on Twitter. I dabble in politics Twitter, I dabble in COVID Twitter, I dabble in entertainment Twitter and media Twitter. Economics and Finance Twitter is one of the best bubbles to be in. And I don't know why the people, at least that I follow in that space, are so not perfectly unideological, but so curious about understanding problems with numbers. Like, it's a lot of people posting graphs of the direction of used car inflation and saying,

what do you think that is? And then there's, like, a list of theories. And then some of them get retweeted. And then someone's like, actually, I don't think that this theory holds because, if you refer back to something that Abilock wrote in, like, 2020, it actually turns out that you got, like, it's a lot of numbers detectives that are kind of just trying to, like, be little, you know, number of Sherlock Holmes and solve numbers mysteries. And that leads to some problems.

You know, the economics Twitter misses a ton of shit and has a ton of problems, but it's better along this vector, I think, than a lot of alternative communities. Last question for you, you said, you know, studying this is hard, figuring out exactly how masks work and how especially they work in community settings is really hard. What do we need more of for this question to be easy? So I think one thing that I would like to generally see more of in the world, and I think that public health agencies as currently structured are not well equipped to handle, is sort of like rapidly funded, but very large scale experiments. So similar to what we did in Bangladesh for masks, but it's like

there's similar kinds of things you could do for ventilation and for all these other things that we really just have not done because like public health agencies are not equipped to do these in the short run. And they're kind of ill-equipped to do them in the long run too. So we got the funding for our experiment just from a private funder give well. And it's like, you know, we managed to convince them. It's like they're trying to do good in the world. We managed to convince them that this was a useful source of funds. But it's like if we had tried to get that funding from the National Institutes of aging, the NIA, you know, it would have taken a four-year application or something like that before any funds materialized.

So I think setting up agencies that basically encourage two things. One is making decisions quickly. So instead of being like you apply and in two years you might get some funding, being like there are certain types of problems where we need to respond more quickly. And second, funding more like large scale projects instead of like a hundred smaller projects. So instead of like 100 people being like, oh, I need $100,000 so I can spend this year doing, I'm going to try to survey people and do this sort of like, I know it's not the best study,

but at least it'll be kind of suggestive, doing more things which are like, no, we're going to get 100 people together to do the best possible study, to really get the best data to answer this question. I think that is like, there are much higher returns to doing like the large scale, ambitious thing that collects the right data and really answers the question you care about, as opposed to writing many, many low-quality studies that don't necessarily have data on the outcome you care about and aren't necessarily designed to answer the right question. And then doing what the calculator review did

and saying, oh, let's aggregate up 100 of those studies or something instead of doing a handful of the studies that are really well designed to do that. Yeah, more speed, less bullshit, more big studies. That seems like a pretty interesting and promising formula for the future science. Jason Abilick, thank you very, very much. Yeah, this was great. Thank you for having me. Thank you for listening.

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