Jordan: Almost three months ago to the day we had a professor on this program and he was wrong. So my first question is just basically like, how terrified should I be?
David: Is not at all an acceptable answer? I think not at all is probably the most accurate answer.
Jordan: It is a welcome answer.
David: Yeah.
Jordan: We had them back a month later. Not in spite of the fact that he was wrong, but because of it. He was right on other things, but he was still wrong on some. And today, two months later, we’ll have him back again to discuss how, in his area of study, being wrong is just the cost of doing business. And we’ll talk about how that works when people like me put them on the spot and ask for certainty when there isn’t any. So here’s how he was wrong. Along came a virus that first became a story, and then the story. And people like me who asked questions for a living wanted answers. So what happened? We turned scientists in to media experts. And those are two very different jobs. We asked them to guess, to predict, and they got some things wrong. Because their work is based on the data they have. When they get more data, their outlook changes. It would be kinder of me here to say that their models and projections get revised or evolve, but really they were wrong. But that’s how their job works. I suck at science and I still know that that’s the process: Hypothesis, testing, revision, et cetera. But the way my business works, we’re not built for that. Especially not anymore, and definitely not in the middle of a rapidly unfolding global disaster. We want to know how contagious this is, how deadly this is, how bad it will be. And we want to know that the same way we want to know who will win the election or the Stanley cup. The question here is: What can we learn about being wrong from the process of discovering this virus? What can this teach us about the relationship between media and science? Can a slow motion crisis help us all get better at understanding how experts approach complex subjects? What do we know now about COVID-19 that will help us get things right going forward? And what could we still be wrong about? And we will ask the expert just as soon as Claire gives us the news.
Claire: Well, Prime Minister Justin Trudeau has announced a $350 million emergency community support fund. This is meant to help charities and nonprofits that are helping vulnerable people during this time. He also announced that companies who want to apply to the wage subsidy program, which opens next Monday, can get an estimate of how much money they’ll be able to claim using an online calculator. Well, Quebec has become the first province in the country to hit more than 1000 deaths from COVID-19, and about 850 of those happened in longterm care homes. Premier Francois Legault says the issue of staffing shortages of these places is slowly being fixed. In Manitoba, Premier Brian Pallister says he’s taking a 25% pay cut as he pushes for cuts in the public sector. He’s asking those workers to accept reduced hours and temporary layoffs so that the government can redirect spending to healthcare for the time being. As of Tuesday evening, 38,422 cases of COVID-19 in Canada with 1,910 deaths.
Jordan: I’m Jordan Heath Rawlings, this is The Big Story. Dr. David Fisman is a professor of epidemiology at the Dalla Lana School of Public Health at the University of Toronto. He’s also one of our favourite guests to talk to. Hi, Dr Fisman.
David: Hi, this is a favourite podcast of mine, so thank you.
Jordan: No worries. We wanted to talk about being wrong today and you tell me first, you’re an expert. How many times have you been wrong about COVID-19 since this virus emerged?
David: I think, in terms of very big mistakes, I can think of three off the top of my head and there are probably more. I think one of them was aired publicly on your podcast back whenever we started doing this, I think might be early February, when I said I really didn’t think this was going to take off and be a big thing, that I thought they would likely contain it in China. So, that turned out to be incorrect. And in fact, thinking about it, I think I’m up to at least four times that I’ve been extremely wrong about this, which I think mostly have to do with anchoring on prior experience with SARS. And thinking that this really would be another SARS coronavirus and would play out the same way as SARS-1 did. The first big mistake, which perhaps I’m not entirely on the hook for, was regarding this as something that was most likely a relatively noncommunicable disease centred around a point source outbreak in China. And I think that just reflects having, having read the available literature at that time. This is sort of mid to late January when early estimates of the reproduction number of this disease were starting to come out. And what you saw at that time were estimates that the reproduction number was 0.3, which is what you’d see for disease without epidemic potential. But at that time, and I think we talked about this on a podcast, you were also seeing these funny reports of big clusters, for example, in hospitals. It seemed to be person to person transmitted. And I thought, well, that sounds an awful lot like SARS. And of course it’s turned out that this is much more transmissible on average than I would have thought at that time. Big mistake number two, again, related to anchoring on experience with SARS and thinking, well, with SARS, we managed to control that disease without even having a lab test. And we did that because for the most part SARS seemed to be very transmissible only in certain special situations like in hospitals. And my expectation was that that was what this would be. The sort of things we’re seeing in longterm care facilities in Ontario right now are the sort of thing that I expected us to see exclusively with this disease, that it would not be that transmissible outside of congregate settings, but inside hospitals, jails, longterm care it would be. And in fact, it’s proved to be highly transmissible in both settings. Big mistake number three, I sort of feel like I should be doing this in a hair shirt with a dish full of ashes on my head.
Jordan: But you’re not alone in this. And that’s what we’re talking about today.
David: And in fact, if I can be a little bit salty, what really pisses me off right now is people hating on the Chief Public Health Officer of Canada, Theresa Tam, Dr Theresa Tam, who I think has done a phenomenal job. Because she has acknowledged that she is learning and changing her views as the science changes. And if you give me a choice between someone who says, you know, I know now stuff that I didn’t know a month ago and I’m going to adapt accordingly, versus someone who says, well, dammit, I’m still right about what I said a month ago and I’m going to go down with the ship, I will take the person who can adapt as information changes every single time. The next way in which I was wrong, which I think is related to one and two, is we didn’t have a lab test for SARS. So when people started describing a lot of mild disease in folks who were testing PCR positive, I think I was anchoring on experience with SARS and thinking, well, you know, during SARS we didn’t have a lab test. These kinds of people were probably still there during SARS. But we could never have found them because we didn’t have a lab test, and now we do. So again, very heavily anchoring on my experience with SARS. My next real mistake, and I think to date this has been the last thing that I know of that I’ve been wrong on, that I’m kind of very regretful of– I’m sure I have many mistakes in my future– but this was thinking that the Chinese had contained the outbreak. And again, very locked into the idea that this was like SARS, and this goes into mid-February, around the same time as the Diamond Princess stuff is happening, where I was modelling the Wuhan outbreak and forecasting it, and actually it turned out that my forecasts were right. Which is looking at what was happening to the epidemic in Hubei, you could see by early February that the Chinese were starting to bend to the curve downwards, and you could project– by mid-February, you could project that that thing was going to be pretty much done by early March, which it was. The difficulty was that I didn’t understand what was happening with exportation of cases. And the wake up call for me was in late February, me and my collaborator, Ashleigh Tuite, when– I think it was around February 19th, in quick succession, it was reported that there was a case in Vancouver who had traveled from Iran and had been tested in an emergency room by a doctor who had ignored guidelines on testing. This physician had found that this person who’d never been in China, had come straight from Iran, tested positive for COVID. And at the same time, BNO News, which is a website that I follow for COVID reporting, reported that there were new cases in Lebanon and United Arab Emirates, which had also originated in Iran. So I think Ashleigh and I kind of looked at each other and sort of said, Whoa, you know, this is like when this all started out, a bunch of of UK investigators said, you know, there’s no way China has 40 cases because we’re seeing cases in Thailand and Japan, and I think South Korea possibly was the other one. There’s no way you have a 40 case outbreak, but you’re exporting cases from your country abroad. So the Iran stuff was that all over again. You know, there’s no way– Iran I think at the time, had 55 cases officially, and there’s no way you have 55 cases, but you’re exporting disease around the world. And the very next day, Bahrain, Oman, Iraq, I believe Afghanistan and one or two other countries that I’m forgetting, said that they too had cases exported from Iran. And Ashleigh did some quick back of the envelope math with that, she had access to travel volumes, and the estimate you’d come up with, based on the number of travels coming up and travellers coming out of Iran, is that around must have 23,000 cases.
Jordan: Each of those mistakes, that you just listed kind of goes from one to the other based on what we knew at the time. And when we talked about having you back on, this is kind of what we discussed. And I wanted to ask, in your world, how common is it when a new virus emerges to have to operate in that atmosphere of not knowing anything and making a mistake and then figuring out that you were wrong and going back to the drawing board and et cetera, et cetera?
David: It’s very common, and I think that, you know, I’ve done this a few times now, we’ve done this– Ebola is not a new virus, but we’ve had– in 2015 for example, you had Ebola, which I think in most publications was regarded as a disease that had a reproduction number less than one, which causes scary clusters, but it doesn’t cause epidemics. All of a sudden you have Ebola causes a big epidemic in West Africa with 30,000 people infected. So I’ll say, that was sort of a new emergence. With Ebola, with H1N1, with SARS, I think with all of these viruses, it’s like, you know, I don’t know if you remember the old Donald Rumsfeld thing about the known unknowns and the unknown unknowns? So you could actually use that here. The known unknowns, what you know is going to change over time, are things like case fatality versus infection fatality. So as this is run on how lethal the virus is, the view on that has sort of changed. I mean, the initial Chinese estimates were 1% and then they published something in mid-February that said it was 2.4% and I remember at the end of February or so, getting asked by a lot of journalists looking at global data saying, Wow, the case fatalities gone all the way up to 3.4%. Is this virus getting deadlier? And now of course, the global case fatality is around 7%. And it’s not that the virus is getting deadlier, it doesn’t work that way. What happens with case fatality is the deaths and case identification happen in a disjointed way. So the cases rack up faster than the deaths rack up. Which always means that you’re going to see case fatality go up with time because it takes people a while to die. It takes much longer to die than it does to get infected and have symptoms. So that’s quite predictable. The other thing that’s quite predictable that you saw with H1N1, is going from case fatality, which is the fraction of deaths among recognized cases, to infection fatality, which is deaths among all infections, recognized or unrecognized. Your case fatality is going to get read as an infection fatality ratio, and it’s going to fall over time as people start to see more and more infections. And you see that happening now and it’s led to some weird conversations, including some from extensively knowledgeable public health professionals who have said, well, this is really just like flu. Flu is like this, which it’s not. And I think in a couple of years time, we’ll probably be at the end and we’ll be expert on this virus and we’ll realize what a journey it’s been. But wow. In terms of an experience that humbles you, this has really been that.
Jordan: Well, and the last time you dealt with something like this, during SARS, the media climate was different, there was no social media, and you’ve been pretty immersed in social media, at least at points, during this. And the process you just described to me of a slow evolution of what we know about this virus, how have you seen that play out on social media? Does it work with the way social media is built?
David: You know, I mean, social media, I think. Has been a double edged sword. And Twitter, for example, has been great in terms of endowing blue check marks upon all these epidemiologists and I think that’s terrific as an attempt to sort of show people– point towards credible information sources. So from that point of view, I’ve learned a lot from social media. I’ve learned a lot from social media. I’ve also learned a lot, as an epidemiologist, from media. Because it’s kind of like this hive mind, you’ve got all these different people asking different questions, and so if you’re open to others on social media who approach you with questions, if you’re open to reporters questions, often kind of inquisitive, intelligent people point you in directions that you weren’t really thinking of going, that force you to go look things up. And you learn. So to me, net, you know, I’m still on Twitter, although sometimes I reconsider that. To me, it’s been a way to sort of share epidemiologic teaching, understanding information as we get it. And then of course, it’s also got that kind of weird toxic conflict generating thing going on, which I think particularly as people get less scared of this, as it looks like social distancing, physical distance since done its part, you see some of the preexisting kind of fracture lines starting to reemerge the most. The most distressing of those from me right now, is the political stuff. Which is, as people have sort of calmed down and decided that they’re not all going to die and this isn’t the apocalypse, you see kind of– and Dr Tam’s work is an example of this, our work’s an example of this– folks sort of scoring political points on decisions that were made in real time without the advantage of hindsight and saying, well, now, now we’re two months on and don’t you see we should have done this at the time? You know that, that’s nice. We all– I mean, it’s the Kierkegaard line that you live life forward and understand it backwards. And I think it’s the same thing with managing an epidemic. You know, you have to manage it forward. You don’t have the luxury of waiting two months for things to unfold and then saying, you know, we’ll decide at that point. I think, I think that approach to be brutally frank, has characterized some of the less positive aspects of Ontario’s Public Health response. Where you, where you’ve seen senior public health officials say, well, you know, we’re not sure yet, so we’re not going to make that call. You have to make the calls in real time or people die.
Jordan: But then you might be wrong.
David: Then you might be wrong. Right. You might. But what you have to do is you have to make the best decision you can with the information that you have in your hand at the time that you have to make the decision. You know, some of this is also, there are the unknown unknowns and the known–I guess it’s not really an unknown– there were things we knew would happen. So for example, we were modelling out what happens if you delay social distancing and make it reactive rather than proactive. And speaking to media to try to get the word out that, you know, if we delay until our ICUs, are full and then institute social distance saying what’s going to happen is what’s happened in Italy and Madrid and France and the UK and in New York, is our ICUs are going to collapse. Because the lags baked into this disease system are such that by imposing social distancing today, you impact today’s transmissions, which aren’t going to show up in the ICU for another three weeks, which means you have a full three weeks worth of transmissions and exponential growth coming at your ICU. And that’s how you wind up with mass graves and you know, a thousand deaths a day kind of scenarios, like many cities have experienced. So, you know, we anticipated, and we were writing at the time, that if people social distance and this works, we’re going to be criticized post-hoc for telling people that they needed to act to avert catastrophe, because a catastrophe won’t happen, and then people will say, you overreacted. So that was entirely anticipate it. And indeed, I think we have that in an article we put in the Globe and Mail and in mid March. That you know, people are going to hate on us for saying, Oh, you big dummies, we did all this, we closed down society, and then nothing happened. But to be frank, I mean, that sort of inversion of causality is very familiar to us in public health. You know, we get it from anti-vaxxers who say, why are we vaccinating? There’s no measles. We get it from, you know, the unpasteurized milk partisans who say, why are you pasteurizing milk? Nobody gets bovine tuberculosis or brucellosis anymore. You know, there’s this version of causality which is very familiar in public health. So you expect that to come in terms of the modelling.
Jordan: What is, and I’m not asking you to make any predictions, but what is the next thing we could be wrong about? Like what are we still trying to figure out and making assumptions about that we just don’t know?
David: There are a couple of things. One is, interestingly, there does seem to be a bit of a North-South gradient and severity of this thing, more than I would have expected. So Southern Italy seems to be hit less hard than Northern Italy, despite having an older population, because young people go North. Florida has been less hard hits so far, than the US Northeast, which I wouldn’t have expected given the older population in Florida. So I think something that I may yet be wrong on relates to the impact of seasonality on this virus. Environmental conditions, UV radiation, humidity, warmth. We may get more of a break than I’m expecting over the summer. But, you know, time will tell. We shall see. I think we’re going to screw up– either us or others– we’re going to screw up predictably, you know, in the coming weeks in terms of trying to rush standing down from physical distancing. I think there’s a lot of pent up psychological-economic pressure to declare victory and get back to life as normal. And I don’t know who it will be, whether it’ll be us in Ontario, it will be someone, will rush that too much, without having sufficient infrastructure in place to really know what’s going on in the community. And we’ll wind up in kind of a New York or an Italy situation, either over the summer or next fall. I’m pretty sure that’s coming. And I hope it’s not us in Ontario, I hope it’s not anyone, but I think it’ll be someone. I think that the issue of possibly taking away physical distancing too fast speaks to the importance of really good surveillance. And I think that has to be the next project. You know, so far we’ve been pretty good at finding this in places where it does a lot of damage. Looking in, you know, sick people who are hospitalized and finding the virus, looking in nursing homes where people are dying and finding the virus. I think what we’re going to have to do in the coming weeks is get a lot better at looking for this out in the wider community.
Jordan: What would that look like? To go and test people? Are people going to come to my house and test me? Will I be told to show up at a testing site? Like what does it look like as we try to do that surveillance in reopen?
David: Well, my best bet– I think we can do it in a couple of different ways. And here’s, here’s my current top three and then I’ll add in a fourth one that’s weird, just cause I think you’re an appreciative audience for the weird stuff. That’s why it’s so fun to talk to you. So I think probably, if I– you know, let’s channel the Barenaked Ladies– if I had $1 million, or let’s say, several hundred million dollars, a lot of political power, what would I do? My surveillance regimen would be Walmart parking lot surveillance. And not to single at Walmart, but somewhere where there’s big box stores and a broad cross section of Canadian society goes there as a destination to buy stuff. Because that’s where you can get lots of different people from lots of parts, you know, lots of socioeconomic groups, male, female, young, old, what have you. And right now it would be particularly easy because people are lined up to get into the stores, but you could still do this in a parking lot. You could swab, say, every 10th person going into the Walmart in your– in one neighbourhood, you could pool those swabs so that you save on reagent, the chemicals we use to do the testing, and you could look at what percentage of these pools around Toronto, around Ontario, around Canada, what percentage of pools in different parts of the country are turning up positive for the virus. So that would be a good way, with sort of broad geographic range– there are ethical issues there. You know, if one in– say we’re testing 10 pooled swabs, I don’t necessarily know which of those 10 people is testing positive for COVID. And maybe some folks are going to say, well, you really do need to know because they could be at risk for getting quite sick. So I think you would want to have the lawyers look at that one. But that would be one way to get broad coverage across the country in a minimally invasive and intrusive way, when people are going out anyway. Another possibility, which I think we should be doing anyway, and we’re not doing universally, and I think it’s a mistake, is hospital admission screening. Anyone who’s going into a hospital, whether you fell down the stairs and broke your leg, whether you had a stroke, whether, you know, whatever reason for going into the hospital, whether you’re having a baby, you get swabbed, and we look for COVID. Both to protect you, and to protect the other patients and healthcare workers you’re going to encounter, but also as an index of how much of this stuff is there out there in the community. You know, if you’re coming in for a car accident, you’re not coming in because you have a new lung disease that could be covered. So if we test a lot of those folks, that’s going to give us an indirect index of how much of this stuff is there in the wide world. The third big resource in terms of surveillance is making use of existing research cohorts that are out there. One example here in Toronto is there’s something called Project Target Kids. There are a thousand families in Toronto who have agreed to be part of an ongoing health research study, and those folks are willing to get swabbed for COVID, one grownup, and one kid per household per week. That gives you, especially if we reopened schools and if kids are out in playgrounds, that helps us both know what disease activity looks like in young grownups, the parents, but also very importantly in the kids who don’t seem to get sick from this, but who may be important transmitters of this virus. I say maybe because we don’t know because no one’s really doing much research on kids. We’ll also probably see a lot more testing related to serology, to immunity, to prevalence of antibody. How commonly do people, if you take their blood, how commonly do they have evidence that they were infected and recovered and are now immune? That’s another way for us to basically recalibrate our models to how far along into this epidemic are we? And it also has the potential to allow us to identify immune cohorts who may be safe to work. You know, if we have lots of immune health care workers, those folks can probably work in the ICU with a fair bit of peace of mind. They’ve already been infected and now they’re immune. They’re not going to get it, and they’re also not going to pass it on to their patients, at least in the near future. And then just to get into the weird stuff because it’s fun. How about sewage? Folks in the US have been using this and I’m aware of an effort in Germany just starting up. Coronaviruses seem to get– their RNA comes out in our poop and goes into the sewers. And so folks have shown that you can actually quantitate the amount of a SARS coronavirus 2 in sewage, and it’s a pretty good indicator of how much disease activity you have in your community. It’s kind of like the parking lot surveillance, without the parking lot, we just put the bucket down the sewer. It’s technically challenging, because obviously there’s a lot of different living critters or formerly living critters in sewage. So, it’s a little bit of a needle in the haystack problem. But it does have potential in it is actually being used and could potentially across the country provide an index of, you know, is COVID coming back? Is it re-surging? Are those virus levels in the sewage going up really fast? And that might allow us, if we could do it quickly, it would give us a jump on resurgent epidemics.
Jordan: Well, speaking to the idea of finally getting tested and getting back out there, the last thing I wanted to ask you about is a timeline for physical distancing, and I wanted to end with this because I saw the paper that you and your colleagues produced, and I’m really hoping that this is another thing that you’re wrong about because, you had potentially up to 2022 in there, and that makes me anxious.
David: Yeah, no, it makes everyone anxious. And again, my colleague, Ashleigh Tuite, has been working on this model and it kind of makes her cry, because–
Jordan: She’s not alone!
David: No, she’s not alone. But you know, what we see is physical distancing works really well, and it probably doesn’t need to be this intense. What’s clear is that it’s the big gatherings that drive this. I don’t know what the threshold is, whether it’s, you know, gatherings of more than 10 or gatherings of more than 50, but the big gatherings have been over represented in all of this. So, but we have to, we have to relax physical distancing for both economic and mental health reasons in the community. But inexorably, if you preserve susceptibility to infection by successfully physical distancing, you get the epidemic coming back, you know, in a couple of weeks to months, depending on how far you’ve pushed it down, and there’s a degree of random chance there, and there may be a degree of seasonality there, but it comes back until we have herd immunity. I do think 18 months is probably an optimistic but realistic timeline for a vaccine. And that, combined with, you know, these safe to work certificates that show people are immune and you know, don’t have to worry about going out and about, although that opens its own ethical can of worms– I think those are going to be the doors out of here. I think immunity is how we get back to a normal society and a lot of that is going to be vaccine-related. Something that was very hopeful that I learned this week is that GSK and Sanofi, which are two big vaccine giants, are actually cooperating on vaccine development, which I’ve never seen before. And I’m hopeful that we’ll have a vaccine faster than one might have expected, but I still think 18 months is a reasonable timeline.
Jordan: That’s not great, but I’ll take it.
David: Sorry. I mean, yeah. The thing with this is, it’s not the apocalypse, right? We’re not going to see societies collapse. They’re terrible things happened in 1918 with that pandemic. We don’t look back on 1918 now as the year of the world ended, we look back on it as the year the first World War ended. So we will come through this. We also can’t flip a switch and go back to November 2019. Right? That’s not an option that’s on the table. There are really three options that are on the table. I mean, one is to sort of let it rip, a la– I was going to say a la Sweden, but I think even Sweden, they’re doing a decent amount of social distancing now. And that’s probably unacceptable to people because of the high death toll, and the loss, many of us will lose loved ones in that scenario. There is, keep physical distancing, keep the lid on until we’ve got a vaccine and only let people kind of creep out of their hidey holes if they have proof of immunity, which they’re not going to have because they haven’t been out there getting exposed. And then there’s some sort of– you know, and keep that on for two years. And then there’s some sort of middle ground, which is that we tighten up social distancing as we need, and then we relax it when we can, and we’re nimble about it and we realize that it may have to be on again off again. To me, that’s the least worst option. Because you know, the apocalypse and going back to November 2019 are unfortunately not –well, it’s fortunate the apocalypse is not on the table, but neither of those is– unfortunately, November 2019 it’s not on the table. So you know, of those three options, I think the middle course is probably the most reasonable. But none of them are pleasing to contemplate.
Jordan: No, but we’ll make the best of it. Thank you for taking the time and walking us through some of the mistakes we’ve all made.
David: Thank you.
Jordan: Dr. David Fisman, Professor of Epidemiology at the Dalla Lana School of Public Health. And that was The Big Story. If you’d like more head to thebigstorypodcast.ca. I have been wrong about many things on this podcast and they’re all archived there. You can also tell me I’m wrong on Twitter at @thebigstoryFPN. And you can of course email us. Any voice memos or any videos or just a regular email, at thebigstorypodcast@rci.rogers.com. Thanks for listening. I’m Jordan Heath Rawlings. We’ll talk tomorrow.
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