Science Friday - Should We Trust Election Forecasting, COVID Dreams. Oct 23, 2020, Part 1

Episode Date: October 23, 2020

The first “scientific” election poll was conducted in 1936 by George Gallup, who correctly predicted that Franklin D. Roosevelt would win the presidential election. Since Gallup, our appetite for polls and forecasts has only grown, but watching the needle too closely might have some unintended side effects. Solomon Messing, chief scientist at ACRONYM, a political digital strategy nonprofit, tells us about a study he co-authored that found people are often confused by what forecast numbers mean, and that their confidence in an election’s outcome might depress voter turnout. Sunshine Hillygus, professor of political science and public policy at Duke University, also joins to tell us about the history of polling in the United States. Next up, say you're standing in a crowded room and realizing nobody is wearing a mask. Or a family dog that has passed away protectively guarding grandkids. Maybe having a pleasant get-together with someone you haven’t thought of in years, then suddenly realizing everyone is a little too close, and a little too sick. Do any of these instances sound familiar? A few weeks ago, we asked Science Friday listeners if their dreams have changed since the start of the COVID-19 pandemic. We heard from many listeners who said yes, their dreams have become more vivid, with elements of the pandemic included. A change in dreams due to a crisis is very common, says Deirdre Barrett, a dream researcher and assistant professor of psychology at Harvard University in Cambridge, Massachusetts. When we’re in a dream state, the brain is processing the same things we think about during the day. But when we’re asleep, the parts of our brain that handle logic and speech are damped down. The parts that handle visuals, however, are ramped up. Barrett has been collecting dreams from people all over the world since the start of the pandemic. She says common dream themes range from actually getting the virus, natural disasters and bug attacks. Healthcare workers have regularly reported the highest level of stressful COVID-19 dreams, according to her data. “The typical dream from the healthcare workers is really a full-on nightmare,” Barrett says. “Just as bad as you’d see in war zones.” Barrett joins SciFri producer Kathleen Davis to talk about her research into crisis dreams, and what people can do if they want to experience stressful dreams less often. And, search engine giant Google was served an antitrust lawsuit by the Justice Department this week, which alleges the company abuses its near-monopoly status to harm consumers and competitors. This is the first such action against the company, which, over the last couple decades, has grown into one of the more powerful tech companies in history.  Meanwhile, early data from New York City schools shows a promising picture of what back-to-school in the age of COVID means. Out of more than 16,000 randomly tested students and staff members, only 28 positive results came back—20 from staff members, and eight from students. While COVID-19 cases in K-12 schools across the country are not zero, low rates are the norm so far.  Joining Ira to talk about these stories and other news from the week is Nsikan Akpan, a science editor at National Geographic in Washington, D.C.   Subscribe to this podcast. Plus, to stay updated on all things science, sign up for Science Friday's newsletters.

This is Science Friday. I'm Ira Flato. One of the world's biggest tech giants found itself in legal trouble this week. Google was served an antitrust lawsuit by the U.S. Justice Department. The suit argues the company has unfair business practices, like how it pays other massive tech companies, to be the default search engine on other devices. So what does this all mean? Joining me today to break down this and other news of the week is a Sikon Akpan, Science. editor at National Geographic in Washington. Welcome back, Cicad. Thanks. Thank goodness. It's Friday.

How's it going? Yes, yes. It's been a long week. Tell us what the Justice Department is saying that Google did. So the Justice Department in 11 states say that Google has created an illegal monopoly with its business practices surrounding its search engine. They argue that Google has stifled competition by paying billions of dollars to mobile phone manufacturers like Apple or LG or Motorola or Samsung

to prioritize its search engine and its Chrome browser on those devices. And then on the back end, Google pumps advertisements alongside those search results, right? You know, every time you search for your favorite pizza place, it's going to come up with a suggested result. And that comes with a huge payout. Last year, Google's search revenue was $98 billion, and its ad revenue amounted to almost $135 billion. Wow. So this is a big deal then.

Yeah, this is enormous. I mean, it's not only the first antitrust action against Google, which I should say is technically owned by a company called Alphabet now, but it's also the most consequential antitrust suit against a big tech company since 1998, when the DOJ and 20 states file charges against Microsoft. In that case, the DOJ was charging that Microsoft was providing software bundles, and by doing that, it was stifling competition. Namely, the issue was with its Internet browser on its operating system. So this practice was deemed illegal because Microsoft had made it harder for consumers to install other browsers.

I don't know if the kids will remember a Netscape. Oh, yeah. On its operating platform. And so as a result, when Microsoft lost this case, they had to split the company in two. And the ironic part is some people say the decision opened up competitiveness. It opened up the markets and allowed companies like Google to ultimately thrive. Well, you know, it's quite obvious that people Google everything. How is Google going to defend itself?

Yeah, Google is not happy. Kent Walker, the company's chief legal officer, described the lawsuit as deeply flawed. and said it would do nothing to help consumers. So I think, you know, Google could claim there's plenty of competition out there, right? You know, they might say, have you heard of Bing? You know, Microsoft's search engine. But I think others, including the DOJ, could say, well, have you heard of Bing? You know, in their suit, the Justice Department presented data that showed that Google has had an 80 to 90% market share in the search engine industry since 2009.

And I think, you know, Google could also say, you know, our service is free. but having a free service doesn't exclude you from antitrust regulation, which was actually the case with Microsoft. Let's quickly move before we go on to another topic in the legal world, and that was a development in the Purdue Pharma epidemic case this week. Tell us what happened there. Right. So OxyContin Maker, Purdue Pharma, they're expected to plead guilty to three criminal charges for its role in the opioid crisis. And then the charges include a conspiracy to defraud the United States and also violating federal anti-kickback laws. But I think that the bigger news from this settlement is that Purdue is going to pay out about $8.3 billion in damages. You might call them damages.

And I think some people are saying that that price point, that settlement, is a little bit low. You know, the drug maker was a primary source of opioids during the crisis and the overdose. crisis led to nearly half a million deaths. So I think there's a real question on whether or not that settlement is enough to help all of those grieving families. Yeah, a lot of issues there. We'll get into more later when we have more time. Let's move quickly to the presidential debate, the last one. We did get some science talk in there. Did we learn anything new, though, about the development, for example, of the coronavirus vaccine? Yeah, it was fascinating. Trump last night said that, you know, there could be an approval within weeks, but there was actually

a really big meeting yesterday held by the FDA and one of its advisory committees. And throughout that meeting, which lasted about eight hours, not only health regulators, but medical academics who were on the call to provide public commentary, you know, really voiced this idea of taking their time with the vaccine approval. So health regulators in particular, have laid out really stringent criteria in terms of approving the COVID-19 vaccine, and they really don't want to rush the process. I think the biggest thing is that they're saying that companies must show that at least half the participants in these trials have two months of data related to their response to the vaccine. And I think that's going to slow things down because, so given that

these trials have only been recruiting participants since the middle of the summer and that, you know, the front-runner candidates, Moderna, Pfizer, AstraZeneca, they require two doses that are spread over a month or two. You know, we're saying, we're looking at maybe November, December, before we even have enough data for emergency use authorization. Let's move on to climate change in the debate because the president said some really weird things about the climate last night, such as windmills causing all these gases to come up out of the ground, solar is not ready. Did you get the idea that he really wasn't talking about climate change much? The president has tended to focus on pollution and in clean air,

rather than focusing on how his policies have sort of rolled back Obama-era regulations that were expanding clean energy. And then I think when you look at Biden's policy, plan, his climate plan. You know, he wants to achieve 100% clean electricity by 2035 and net zero emissions by 2050. You know, Trump left the Paris Agreement. You know, Biden plans to rejoin the Paris Agreement and reinstate emission rules and invest two trillion dollars. You know, Trump made the claim about windmills being potentially dangerous for birds. And I think, you know, anyone who studies birds would tell you that climate change is a much bigger risk to birds. than windmill blades. But I think, you know, there were some really interesting things said about their positions on fossil fuels. You know, I think Trump tried to accuse Biden of not supporting

fracking, which is not true. And I think they both support fracking. In fact, at one point, Trump said he wants to put the vice president in a box with oil, saying he wants to get rid of oil immediately when, in fact, he's talking about a phased rollback of oil. Exactly. I mean, I think Biden sort of has very moderate views when it comes to fossil fields, especially with oil. You know, he promised to stop the Keystone XL pipeline, but he hasn't taken a position on the Dakota Axis pipeline. You know, he's in favor of ending fossil fuel subsidies, but, you know, even last night, he said that he would try to completely end fossil fuels overall. But he didn't really give a timeline for when that might happen. So, I mean, I think with Trump, you're going to see an expansion of fossil fuels, especially with natural gas.

I think with Biden, he sees the value in using natural gas as a transition to clean energy, but he's definitely not pulling back on fossil fuels as fast as some progressives might want him to do. Let's move on to COVID and kids because there was some really interesting news. Specifically, we got testing data that showed. a lower number than expected of cases in New York City schools. Out of more than 16,000 tests of kids and staff members, only 28 positive came back. Tell us what we're learning from this data.

I think the result is expected in a way, because we do know that COVID-19 doesn't strike kids quite as fervently as it strikes adults. I do question some of the methods with the studies. We know that a negative test on one day doesn't necessarily mean that you will test negative tomorrow or the day after. And so I think to really conduct one of these studies, you would have to be conducting constant surveillance in the schools to make sure that the children aren't catching coronavirus. Another big thing is that we know that most cases in children are asymptomatic, right? and that might say something about, you know, how much virus is in their bodies.

So that's another reason why screening on one day might miss a case. And we have a story that we came out with last week that shows that the virus seems to have a tendency of hiding out in children's guts rather than in their noses. So depending on how they were testing kids, you know, if you were doing a nasal swab, you might be missing cases in children versus. if you were testing their stool. So I do just have, I guess, questions about how those studies were conducted. Yeah. So you need to have more studies and done better. There was a study out, I've just heard about this morning,

that said that kids are carriers more than we think they are. Yeah, and that's what we would expect normally from a respiratory virus like the coronavirus. I mean, kids tend to be primary what we call vectors of disease, carriers of, the disease. I think thankfully, what we've seen with the coronavirus is that kids are, you know, much less likely to suffer from, you know, the worst harmful impacts of COVID-19. Although, you know, and this brings us back to the debate, you know, last night President Trump made the claim that, you know, 99.9% of young people recover from the virus and 99% of people overall recover from the virus. And I mean, And what he was referring to there is mortality.

You know, he's referring to deaths. And that's true. I mean, COVID-19 does only kill about 1% of the people that catch it. But, you know, we're seeing that patients are dealing with chronic disease, you know, depending on which hospital you look at, you know, we're talking, you know, from 10% to 70% to 80% of patients that are hospitalized are dealing with symptoms months after they've caught the virus. and maybe we're missing a lot of those long-term symptoms because, you know, we're not actively screening people's poop, you know, people's stool. Yeah, okay, we'll be following a lot more of that because that is the future of where we're

going is more testing and getting kids back into school. Thank you, Sikkan. Of course, anytime. Seekon Akpan, Science Editor at National Geographic in Washington. We're going to take a break and when we come back, we'll talk about a possible downside of seeing election forecasts. This is Science Friday. I'm Irafledo. If you're anything like me, you have been spending a lot of time looking at polling data and

election forecasts, but maybe you don't totally trust them. After 2016, I was so badly burned that I no longer put much weight into election forecast. So I watch other sources to make up my mind. That was Rochelle from Bluffton, South Carolina, commenting on our Vox Pop app. We had asked you how much weight you put on polls and election forecast these days, and some of you still have a good deal of confidence in them, but more are skeptical. I don't trust election forecast much since the 2016 election, and I think that that actually illustrates one of the big reasons why,

which is that it doesn't even mandare in the U.S. if a candidate wins the populace. vote. I don't always believe election forecasts because I think some people are too embarrassed to tell pollsters who they're really voting for. No, I don't put a lot of weight on the forecast. The forecasts are paid for by people who have an agenda. There's just not enough neutrality being displayed across the board. That was Alicia from Amsterdam, Steve from Sacramento, and Arnold from Santa Barbara. As Rochelle and Alicia mentioned, after 2016, some people lost faith in the numbers

because most forecasts have given Clinton strong odds, and yet we know she lost. Joining me as sci-fi producer Ella Fedder to talk about how we got here, the unintended side effects of election forecasting, and why trusting those numbers a little less might be a good thing. Hi, Ella, welcome.

Hi, Ira. Thanks for having. So what got you interested in the downsides of election forecasting? So like a lot of people, I have been visiting 538 a lot recently, for anyone who's not familiar. 538 is the website that Nate Silver started in 2008. It covers politics. It has a data focus. And it's most famous for its election forecasts.

Yep. It's sort of a go-to place for a lot of people. I cannot stop refreshing it. But this year, I noticed that they've completely revamped the, way that they present their presidential forecast. So in 2016, at the top of the page, they just gave you the goods right away. They gave you Clinton and Trump's chances of winning, which is why people were going there. This year, at the very top, there are no numbers, just words. Yeah, I just pulled this up. And of course, right now as we record this on the morning of Wednesday,

it says Biden is favored to win the election, and there are lots of colored maps, mostly blue. Yeah, you have to scroll down further to get any numbers, and when they give them to you, there's a lot of text explaining exactly what they mean. And if you're still feeling lost, 538 even added a cartoon fox with glasses named 5E Fox, who pops in with little explanations and tips,

like 5E Fox reminds us not to count the underdog out. So it's pretty clear looking at this that 538 is just trying very, very hard to avoid what happened in 2016. Donald Trump has been elected the 45th president of the United States, which leaves us just one question. How the heck did it happen? What went wrong with the numbers, the predictions, that polls that suggested a late surge for Clinton?

What did everybody get wrong? I mean, the polls were just wrong. Just the numbers. After 2016, a lot of people were very unhappy with the pollsters saying, hey, you know, we trusted you, you told us Clinton would win. The New York Times had given Clinton an 85% chance of winning. Huffington Post put her chances at 98%. So people have written at length about what exactly went wrong in 2016. Some of it had to do with the polls and the models themselves.

Like one of the big takeaways was that they needed to better account for education level. But some of the problem was with how people were reading the numbers. 538, for example, they actually gave Trump a roughly 30% chance of winning by the end, which is a nearly one in three chance. Those were decent odds. But I remember talking to some friends before the election. And it seemed like they understood these numbers very differently. They saw 30% for Trump and read it as a Clinton landslide. You know, I think a lot of us thought that.

Yeah. I mean, it was a common misperception, even for people who understood these numbers. I think 538 is trying to account for that this time. Well, first, they've updated their model. They talk a bit about what they've changed. But they've also redesigned this page to try to prevent some of the common misunderstandings. But there's research suggesting that the problem with forecasting might go a lot deeper to the very existence of forecasts and how we behave when we think we know how an election is going to turn out.

Aha. So there is history here. There always is. We've been obsessed with knowing how elections are going to turn out for a long, long time. We've been trying to predict them forever. We cannot help ourselves. But the pivotal moment for so-called scientific polling in the United States was in 1936. The Literary Digest Fiasco is a favorite for every public opinion professor to teach in class.

Sunshine Hillegas is a professor of political science and public policy at Duke University. The literary digest had sent out millions of requests and had a quite adequate job of predicting election results in the past. But in 1936, they sent this out. They got the results back and predicted the FDR would lose in a landslide. Instead, Franklin Roosevelt won in the most resounding victory in U.S. history. 60% of the popular vote, 98% of the electoral college. which meant that literary digest had botched this spectacularly. The problem with, even though they had millions of ballots that were returned, the problem is that they sent ballots out to people who were subscribers to literary digest.

They also supplemented that with car owners. So it turns out, right, that this is not a random sample of the electorate. These tend to be people who were more Republican. And so the results just got it wrong. But if I remember my history correctly, somebody did get it right, didn't they? Indeed, this was a big moment for someone named George Gallup, whose name you probably recognized, Gallup was the inventor of the Gallup poll. Absolutely, absolutely.

Gallup introduced what is called quota sampling, essentially looking at the demographic characteristics of the sample as it came in. in quota sampling, instead of just polling, you know, people who own cars, you try to pull across a good range of people, different ages, genders, ethnicities, you're trying to represent the national demographics. It's not perfect. We know now that that quota sampling can also lead us astray. There's a saying demography is not destiny. You know, not all women vote Democratic, that, you know, if you make a sample that looks like the population across a set of demographics, that you can still get the wrong answer. But in 1936, George Gallup did not get the wrong answer. He got it right

and then he got it right again in 1940 and in 1944. And since Gallup, our appetite for polls and forecasts has only grown. But there's always been this tension between us really wanting to know what's going to happen, and at the same time, being pretty skeptical that pollsters actually know what they're talking about. I mean, they don't always get it right. And then in 2008, along comes Nate Silver, predicting the results of the presidential and Senate races nearly perfectly on his website, 538. Because he did so well in 2008, he becomes this sort of this figure. Solomon Messing is chief scientist at acronym and an affiliated researcher at Georgetown. And a legend kind of develops around 538.

And again, in 2012, he predicts the election very, very well. And what happens is over the years, for each election, the public, journalists, more and more people start going to 538 to get a sense. of what's happening in the race. After 2008, not only do you see the rise of Nate Silver's reputation as this stellar wonderkind forecaster, you also start to see a change in how polls are communicated to the public. So traditionally, a news outlet would pay for a poll and then come back and say that based on this poll, we estimate that X percent of people are going to vote for this candidate, Y percent for that candidate, with some margin of air.

Yeah, that's how I remember the history of polling. But there's something kind of dissatisfying about that kind of information. I mean, in this country, you can get the most votes and still lose an election. So what people really want to know isn't just the vote chair, but who's going to win? We call that probabilistic forecasting, where they give you the actual chances a given candidate will win. And that's what Nate Silver does for us. He takes a bunch of polls and calculates those odds. That forecast is designed to do a bunch of really good things.

That provides a number that accounts for the complexity of the electoral college, and it attempts to count for polling air. We love this kind of aggregated, probabilistic polling data. But in August, Solomon and two co-authors published a study suggesting this could have some potentially serious side effects. They were inspired by the 2016 election. Like many of your listeners probably, we were pretty shocked by Trump's victory in 2016. you know, 100 million voters stayed home in that election. And we know from anecdotal accounts that some people did so because of this widespread consensus that Clinton was kind of destined to win.

You know, why go out and vote if the outcome of the election is already decided? And so the researchers wondered just how much could these forecasts affect voter behavior? And did it matter how the numbers were presented? So they ran a study where they told people about a hypothetical Senate race, and they shared the results of some imaginary polling data in one of two ways, either as a vote share or as a chance of winning. So, for example, a participant might hear something like candidate A is predicted to get 55% of the votes plus minus 2% margin of error, or they might hear that candidate A has an 87% chance of winning. The first one talks about the number of votes, and the second one talks about the chance of winning. Exactly. But this is key.

Both of those numbers are based on the same data. They're equally accurate. The difference was in how that information was reported to the study participants, so whether they saw vote share or chances of winning. And those numbers, they sounded pretty different. Like, let's take some real data from 2016. and the national election, at the same time that 538 was giving Clinton approximately 70% chance of winning, they also predicted she'd get about 48% of the popular vote. And that's based on the same model.

But those two numbers feel very different. Absolutely. I think part of it is just that one is a bigger number. I think we're sometimes our lizard brains are as simple as that. But another reason might be that people, they're just used to hearing election stats in a population. particular way. We've had 50 years of experience consuming or covering vote share. And it's confusing to folks who don't have a degree in statistics. And even folks who do have a degree in statistics, I probably had too much confidence that Clinton would win in 2016. And that confusion,

it came through in the study. When we ran our study, 40% of the participants seemed to confuse vote share and probability, at least when they were trying to tell us what vote share and probability was likely to be for an election. So someone hears that Clinton has a 70% chance of winning and thinks, wow, she's going to get 70% of the votes, which obviously that would be a landslide if that's what that number really meant, which it does not. And that's the problem, because that's what I thought when I went to the site also. I understand. understand the confusion here. Yeah. I think it's a common misunderstanding. And I think even when you know what these numbers mean, part of your brain still responds that way. So that's one problem.

But what the researchers really wanted to know was does any of this actually matter? You know, does seeing a forecast affect voter behavior? I have to break in. We'll be back with more on the effects of election forecasting with producer Ella Fedder and our guest Solomon Messing after this break. I'm Ira Flato. This is Science Friday from WNYC Studios. In case you just joined us, we're back with sci-fi producer Ella Fedder, talking about the effects of election forecasting. Back to you, Ella. Thanks, Sarah.

So when we left off, the researchers had found that sometimes people are confused by forecast numbers, and that seeing a probabilistic forecast where they give you a candidate's chances of winning, that can make us feel more confident about the outcome of an election. But the real question was, does this actually affect voter behavior? We ran another study. And this was an election game. So this was an online game where people could vote for a team, you know, kind of like a political party,

and win some money if their team got the most votes. The catch was that voting had a cost. Just like in real life, you know, you're taking time out of your day. You have to wait in lines and so on. In the game, you had to pay a dollar to vote. And what the researchers found, makes a lot of sense. People are less likely to vote when they see a forecast suggesting an electoral blowout.

We didn't see this decline, this equivalent decline in response to the vote share. So in this game, seeing forecast depressed voter turnout, but only when they saw probabilistic forecast. But a game is not real life. So next, the researchers looked at real world data. historical surveys from American National Election Studies. They happened to ask this question about whether or not you're confident that the winner of the upcoming election will win by a lot. And so we looked at 2016 and compared it to the last four presidential elections, people were much more confident in 2016 that the winner would win by quite a bit.

Those folks were also 2 to 3 percent less likely to vote. This one issue isn't necessarily going to make or break an election. For one, Solomon points out that the people who are obsessively looking at forecasts, they're probably the kind of people who are going to vote anyway. The question is really whether these forecasts reach other voters. But also, as one of the studies critics pointed out, this effective forecasting, it's most powerful when a candidate has a really big lead. And when that's the case, something that slightly depresses voter turnout,

it's less likely to change the outcome of the election. Still, there are places where this problem is taken very seriously. France, Canada, Mexico, some other countries have passed laws actually banning publishing polls in the immediate lead-up to elections. Though note that some of these laws were subsequently struck down for infringing on free speech. Or, you know, they just weren't practical in the age of the internet. So election forecasts in this country probably not going away anytime soon. But after 2016, it seems like some people are approaching election forecasts with more skepticism. And that might be a good thing. And certainly after this report, I am one of those people.

Thank you, Ella Fetter. Very interesting stuff. It was fascinating to learn about. Thanks for having me. I guess we're a sunshine higgis, a professor of political science and public policy, and director of the initiative on survey methodology at Duke University. Solomon Messing, Chief Scientist at Acronym and affiliated researcher at Georgetown. We contacted Nate Silver for an interview, but we did not hear back by the time of this recording.

This is Science Friday. I'm Iraflato. Have your dreams gotten stranger since the start of the COVID-19 pandemic? Some people's dreams have become nightmares or downright weird. Sci-Fri producer Kathleen Davis is one of those people. she's been seeing what you listeners have to say and has been talking with dream experts, and she's here to tell us what she's found. Hi, Kathleen. Hey there. So you've been having weird dreams, huh? Yeah, I have. I feel like my dreams are a lot more vivid than they used to be, and I'm dreaming about things that seem both really weird, and at the same time,

I'm thinking they're probably tied a little bit to the pandemic. All right, give me an idea like what? Well, I had one a few weeks ago. where I was kind of in this Mad Max scenario and I was in this group of survivalists and the leader of my group was this girl who I went to middle school with who I really don't think I've thought about in over a decade. So that was very weird.

Wow, that is very strange. And I've heard from a lot of friends and family who are also experiencing similar things. So a few weeks ago, we put out this call on the Science Friday Voxpop app. And here's what some of our listeners told us about their dreams. I have had a number of dreams where I am in a social setting or a someone's home or something

like that and suddenly realize that no one is wearing masks and they're not maintaining social distance. I wake up feeling very anxious and unsettled after that. I have recently started having nightmares where I'm in a crowded room and I'm usually at a school gathering or some kind of convention where there's hundreds of people. And at first, I'm totally unbeknownst that I'm in a pandemic. And then a few minutes into the dream where I'm in this crowded room, I notice that every single person is not wearing a mask and I begin to panic. Since the pandemic began, I have been dreaming a lot more and been dreaming about people

and places I haven't thought about in years, like not since childhood. But the biggest is starting in April, my dreams started having sound in them. And previous to this, I never had any sound in any of my dreams. Those were listeners, Rob from Fairfax, Jennifer from Anchorage, and Tyler from Atlanta. Thank you to everybody who left us messages. We wish we could play all of your calls. We sure do. Now, okay, tell us what the experts have to say about this. Yeah, so I spoke to Dr. Deirdre Barrett, who is a psychologist and a dream researcher at Harvard University in Cambridge. She's also the author of the new book, Pandemic Dreams, that is all about this topic. So I started by asking her why it seems like so many of us are having strange dreams right now.

Well, any crisis tends to stir up our dream life that's been ongoing since the start of the pandemic. But most crises make us lose sleep, if anything. And especially at the start of the pandemic when so many people were furloughed or sent home from school, people were actually catching up on sleep somewhat. So at the very start of the pandemic, I heard lots of people saying that they just had lots more dream recall than usual and more bizarre dreams and more vivid dreams. Dream life just blipped way up at the very start. And I think it has dropped back down as people are caught up on sleep and some people are doing their commutes again. to something that's above our average, but not like before the pandemic. What is happening in the brain that processes what's going on in the world and then

turns that into a dream? I think dreams are basically just thinking in a different brain state, different electrical activity, different biochemicals, but we're still concerned with all of our usual fears, hopes, dreams, work stuff, personal stuff. But our brain is in a state where our visual areas are much more active, even than we're awake. Our emotional areas are a little more active. And areas that are associated with logical linear reasoning are damped down a lot. So we're thinking in this very imagery-laden emotional state,

with less verbal thought, but we're still focused on the same things that we are by day. This may be an old wives tale, but I've heard that dreams are in part a way for the body to maybe get rid of some extra worries or extra anxieties. Is there any truth to that? I wish that were true. There was this theory that Francis Crick came up with when he'd done no work on dreams, but because of his DNA work, it got a lot of attention, which other people called the garbage disposal theory of dreams, that we were getting rid of things we didn't need to remember. And there's no evidence that stuff that comes out in dreams is more forgotten. And if anything, people with a lot of anxiety say that having anxious dreams about the same

thing tends to be a feedback loop where having anxious dreams by night makes them more anxious by day, which makes them have more anxious dreams. So no, we're not getting rid of anything. If anything, we're kind of laying down and solidifying memories. Walk me through what kind of patterns you're seeing in people's dreams during this pandemic. What are common themes? Well, there's been some change over time. And near the start of it, I saw that most common dreams were focusing on coming down with the virus.

So I'm having double breathing. I'm spiking a fever. I must have the virus. Then there were clusters of metaphors, and some of them were where natural disasters stand in for whatever's really just happened. A tsunami's coming at the dreamer, earthquake, tornado. So lots of the standard crisis metaphors, but then also I saw lots and lots of bug attack dreams, which seem unique to this.

I think it's partly the pun that we say, I'm coming down with a bug. after a number of weeks of lockdown, I was seeing more dreams about the secondary effects of the pandemic. People who were sheltering at home alone were dreaming about being thrown in prison. And people who were sheltering with family or roommates tended to have these metaphors for crowding or lack of privacy. The whole neighborhood has moved into my house and set up pots so I can't even walk through my room. So lots of those secondary effects were becoming more of the dream anxiety. And then as things reopened, there were bad, back-to-work dreams. It's the first day of work.

And there are all these weird, ill people coughing instead of my usual coworkers. But the anxiety is focused from simply the virus to effects of the lockdown, back to kind of the virus. but the details of how social distancing or forgetting your mask may be what exposes you to it. And just to be clear, people are self-reporting these dreams to you. Is that right? Yes, I have a survey going and it asks for any dreams that you have had about the COVID-19 pandemic. So I'm not saying the bug attacks are metaphors for the pandemic. By definition, if the person has put that dream into the survey, they think it has something to do. with the pandemic.

And as you mentioned a little bit earlier, you've studied people's dreams after other traumatic events, including after 9-11. How do the dreams that you are seeing now compared to dreams that you've seen after other crises? I think the biggest difference is that huge cluster of bug attack dreams that I mentioned. And there's a smaller cluster of invisible monsters that are going to grab the dreamer that I've never seen. Also, there are fewer bad people doing this. There's more stuff that is the bugs or monsters or bad animals or natural disasters.

It's a little bit more focused on dangers of the natural world. Also, I've never noticed a gender difference in reactions, and I did some statistical analysis separately for men versus women. And men were as high on anxiety. But women had elevated rates of anger in their dreams and sadness in their dreams compared to samples from normative times. And also they were dreaming just more unpleasant body sensation stuff that didn't have to do with illness.

And I think this is because women actually are getting impacted by this more. They're doing the majority of the nursing of family members who get sick, the majority of the homeschooling. Women are very disproportionately represented in people who've been laid off since the pandemic started. They tend to be in the less protected, the part-time jobs with no contracts that can lay you off overnight. So women are having probably a worse time with the secondary effects and a broader range of negative emotions. That's fascinating. Are you able to break down your data in terms of maybe profession? I'm curious if you're seeing any difference between the dreams of maybe health care workers versus the general population. Yes. One of the questions in my survey is whether you're a health care worker.

I first opened the survey on March 23rd. The American health care workers didn't look very different than other people. They were just as sort of anxious, oh my God, it's coming for us. But the Italian healthcare workers were already having these horrible traumatic nightmares about trying to get a tube down someone's throat who breathing was so constricted. They couldn't get the tube placed or they had them hooked up to a ventilator and it was coming loose. But basically they had a patient who was dying and they were trying desperately to save their life and they were failing. And then as the pandemic really started hitting parts of the U.S., I started seeing those trauma dreams. And trauma dreams are just really different from other anxiety dreams or nightmares.

They tend to be more realistically, something that's happened by day with just a bit of dreamlike distortion. The typical dream from the average person is an anxiety dream, but not a totally out-of-control nightmare. And the typical dream from the healthcare workers is really a full-on nightmare just as bad as you'd see in war zones. Oh, my gosh. So this year has been such a conflation of crises. I mean, we obviously have COVID, and then we also have these instances of police brutality and then subsequent protests. We've had wildfires. And now we have this presidential election coming up, which for a lot of people is a really

stressful event. I know you've been collecting COVID-specific dreams, but I'm wondering if you've seen any bleed through with these other crises. Definitely. I don't get dreams that are only about the election or only about the Black Lives Matter protests because by definition people are putting in dreams they feel like are about the pandemic. But definitely ones that overlap it. When the demonstrations started, I saw a number of dreams where the demonstrations interacted with fear about social distancing and wearing of masks. And they would be watching a protest and they would be terribly worried for the safety of the protesters, not because of the police violence in most cases, although there were a couple where even that was blended in, like the police were ripping

off their masks or something, but again, the ones turned into this survey were about being afraid of the pandemic. So there were a lot where they were watching protesters, and the fear was that the protesters were going to catch the virus, and they were terribly sad or scared for them. Just a reminder, I'm Kathleen Davis, and this is Science Friday from WNYC Studios. In case you're just joining us, we're talking about how dreams have changed during the COVID-19, pandemic. I'm talking to Dr. Deirdre Barrett. She is a dream researcher at Harvard University in Cambridge, Massachusetts. She's also the author of the new book, Pandemic Dreams. I'm curious, as somebody who has studied crises and the dreams that follow for decades now, how long do you expect people to still

be dealing with COVID-related dreams into the future? If it becomes, you know, not our major health problem, you know, a year from now. We've really got treatments and fairly effective vaccines. Then you would expect to see occasionally I'm getting the virus and occasionally things that seem to kind of flash back to bad things about the secondary effects of shutdown, occasionally for the general populations. But in traumatized populations, kind of 10 to 40 percent keep having awful trauma nightmares for years after. I think we'll see lots and lots of the more intense frontline workers having bad post-traumatic nightmares about COVID for quite some time to come. If people are dealing with an uncomfortable amount of COVID-related dreams, is there

anything that they can do to stop having so many traumatic dreams? Yes, it's actually kind of different for the most traumatized and I'd really recommend that healthcare workers that keep having awful nightmares go to a therapist who specializes in trauma. But for the general public who just feel like they're having more anxiety dreams and those are making their daytime anxiety worse, the best technique, which is simply to think of what you would like to dream about. Maybe there's a person you're not getting to be with. Maybe there's a favorite place that you'd like to visit in your dream tonight. So you want to fall asleep saying,

tonight I want to dream about X. Tonight I want to dream about X. And form a simple visual image in your mind's eye of the person's face or the place or something about the dream you want to have. And in one research study I did, I found that 50% of college students trying to dream on a particular topic succeeded in doing that. So it doesn't work 100% of the time, but it works very frequently. And it's a pleasant way to fall asleep also to be picturing your favorite dream, whether you end up waking up having had it or not. Even just for falling asleep, it crowds out some of the anxious thoughts.

Well, that seems like a great place to wrap things up. Thank you so much. Dr. Deirdre Barrett is a dream researcher at Harvard University in Cambridge, Massachusetts. She's also the author of the book Pandemic Dreams. Thank you so much, Deirdre, for taking time to talk with us today. It was fun. Great interview, Kathleen. I really learned a lot from this. And maybe people who are experiencing these dreams who hear this interview will go seek some counseling now. Yeah. If they're having really chronically stressful dreams, that's sort of. what Dr. Barrett says is the best course of action. And she is still collecting pandemic dreams for her research. And so you can access the survey and read an excerpt from her book Pandemic Dreams

on our website at science friday.com slash dreams. Thank you, Kathleen for bringing us this story. Thanks, Ira. I'm always excited to talk about weird stuff going on in the brain. Producer Kathleen Davis, part of our dream team here at SciFri. One last thing. If you were looking for our book Club Conversation for this week. Keep listening and find it on our podcast feed, or you can visit our website for live stream options. And as always, we put everything you need at ScienceFriady.com slash book club. Charles Burquist is our director. Our producers are Alexa Lim, Christy Taylor, Katie Feather, and Kathleen Davis. You can also email us, our address, SciFri at ScienceFri.com. Have a great weekend. I'm Ira Flato.