#106 - Amesh Adalja, M.D.： Comparing COVID-19 to past pandemics, preparing for the future, and reasons for optimism
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Summary
Dr. Amesh Adalja is a senior scholar at the Johns Hopkins Center for Health Security. He has long been focused on pandemic preparedness and emerging work on infectious disease, biosecurity, and national security for many years, long before this pandemic entered our consciousness. In this episode, we discuss the similarities and differences between the coronavirus pandemic and previous pandemics, and what we can learn from them.
Transcript
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Hey everyone, welcome to the drive podcast. I'm your host, Peter Atiyah. This podcast,
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head over to peteratiyahmd.com forward slash subscribe. Now, without further delay, here's
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today's episode. Welcome back to another special episode of the COVID-19 series of the drive.
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Joining me today is Dr. Amesh Adalja. Amesh is a senior scholar at the Johns Hopkins Center for
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Health Security. He has long been focused on pandemic preparedness and emerging work on
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infectious disease, biosecurity, et cetera, for many years long before this coronavirus entered
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our consciousness. I wanted to talk with Amesh for a couple of reasons. One, I'd heard him on
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other interviews, particularly the one with Sam Harris. Also, I'd seen him in interviews,
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read some of his work, and just found him to be a very thoughtful guy who could put the
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coronavirus pandemic in the context of all the previous pandemics, and not just the ones that
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are immediately in our recollective memories, such as SARS, MERS, H1N1, but even going back a little
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bit further than that. This is a very brief discussion. He was incredibly busy. We were very
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fortunate to get 40 minutes of his time between other interviews, but we do cover quite a bit of
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ground and certainly everything I was hoping to speak with, which is a bit of a more clear history
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of when this virus likely emerged, how it came here, and what we know about it relative to other
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coronaviruses. We talk a lot about what the plan forward should be, and we end with really what he
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is most optimistic about. So though this interview is relatively short for the standards of interviews
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that I do, like I said, it's about 40 minutes. I think we cover a lot, and there's no question I would
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like to have Amesh back. I do think it is really just an inevitability that we will once again
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face a pandemic, and whether it's a coronavirus or another virus is probably less the point here,
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but unquestionably, there are things that we could do better the next time we're faced with this. So
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without further delay, please enjoy my conversation with Dr. Amesh Adalja.
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Amesh, thank you so much for making time to speak this afternoon. I know you're incredibly busy,
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and we were lucky to sort of catch you in between interviews and television appearances. So thanks
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very much. I'll just sort of jump right to it. I reached out to you because I was very interested
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in your perspective on the historical similarities and differences between this pandemic and previous
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ones. Maybe just briefly tell us a little bit about your background and why it is that you're
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not just someone who came to be interested in this in the past three months. So I'm an infectious
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disease emergency medicine and critical care physician who's focused his entire career basically on the
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issue of pandemic preparedness, pandemic prediction, infectious disease and national security, emerging
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infectious disease. Even from the time when I was a trainee, that's basically all I focused. And I work at a
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think tank that's devoted to this issue. And I've been there basically full time since 2010 or so, but
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I've been there since 2008 working on this. I published on pandemic prediction on what the
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characteristics of certain pathogens that cause pandemics would be on H1N1, on Ebola, on agents of
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bioterrorism. So I really focused and tried to niche myself into this aspect of infectious disease in
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medicine. So this is an outbreak that had been on my radar before it hit headlines. And I've been
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following it almost the way people follow sports teams that they like. Tell me a little bit about
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what you thought in call it December when we, at least in the West, saw the first report of the
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case in China. What was your intuition at the time? At that time, I was trying to take what the
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Chinese were saying at face value, meaning that they had learned from the lessons of SARS about
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transparency and were going to do this in a different manner. And they did produce the virus
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sequence very quickly that allowed diagnostic tests and vaccine development to start. And we were able to
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identify a novel coronavirus. But initially, a lot of the reports were saying this is something that was
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animal to human, really tied to wet markets in Wuhan, that there wasn't evidence of human to human
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spread. There were no deaths yet. But I did think that 41 patients getting something from one animal at one
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market really seemed very odd to me, that that seemed to be too much. So I was a little bit skeptical that
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this was just an animal to human event, unless there was something different going on, or there were
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multiple animals that were infected and infected multiple people. But as soon as I saw the first
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paper, and that was the Lancet paper, where they showed the first case got ill on December 1st,
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and he had no contact with the market, that told me that we were dealing with a transmissible
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human to human respiratory virus, and that this was going to be a pathogen that was going to spread
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and not be containable, and that we were going to have to get ready. I had a lot of questions about
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the case fatality ratio, the hospitalization rate, which I still have. But I knew at that point,
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when you had a virus that spreads efficiently between human to humans through the respiratory
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route, you really have to prepare for this being everywhere, especially when you know that this
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had a head start at least spreading since mid-November in China, and nobody knew about it until late
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December. So that gave a virus a very big head start and could have been anywhere by the time we
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actually knew it was, as soon as we discovered that it actually existed.
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Based on that, do you think it's possible that this virus was in the United States, potentially even
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This is a little bit of a controversy. I do know that with past novel coronaviruses that have been
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discovered, like HKU1, which isn't one that people think about, but it is one that was
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discovered post-SARS, it was everywhere as soon as they found it. This one, it doesn't appear that,
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at least that there wasn't widespread presence of it before maybe January. However, I don't rule out
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the possibility that it could have been mixed in our flu and cold season, maybe a sporadic case here
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were there that was mild, that didn't get diagnosed, but it doesn't appear, at least from
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the phylogenetics, the genetics of the virus that we're seeing from both New York and
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Washington, that this was around before that. But I do think it's going to be important to go back and
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look at bank samples and look at people to see if there were cases. I don't think there were a lot of
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them. I think we would have noticed if there were a lot of them, but I think there may have been sporadic
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cases that were mixed into flu and cold season. But it's an open question, and I think it's a good
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hypothesis, and I think it's something that deserves a lot more attention. At what point,
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Amesh, were you becoming convinced that this was going to enter the U.S. in a manner that was going
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to pose real difficulty for the country? So I knew it was going to enter the United States almost from
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the onset, as soon as we knew that this was transmitting between human to human, that this
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wasn't going to be containable, just like when H1N1 appeared in 2009 and was found in Mexico, that we
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knew that this wasn't going to be something that would spare the United States. What I wasn't quite
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attuned to was how difficult it would be to contain in the United States, because I, like many of us,
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believe that our diagnostic testing and our case finding and our contact tracing would have been
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really much better than it was. But the fact was, we didn't know who had this, who didn't have it. Our
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testing made it much harder to actually do that, and we weren't even testing mild cases, and those mild
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cases are arguably more contagious than the severe cases. So that let this slip from something that was
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potentially controllable and wouldn't have been a problem or a major problem, not putting cities
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like New York City under the stress that they're under, to one that became completely unmanageable
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because we basically were allowing this virus to have about two months of unabated spread in the
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United States. And that's something that most of us did not think would happen because we thought
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that we were much more resilient to these types of infections than we really were. And I think that's,
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it didn't have to be that way, but that's basically how it turned out.
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When you go back and look at the history of not just the other coronaviruses, which have gotten a
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lot of airtime lately, of course, most people, even if they don't remember the ins and outs of SARS and
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MERS, they're certainly familiar enough. But when you go back even further and look at some of the
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flus that occurred in Asia, Hong Kong in the 1950s, 60s, and of course, going back even further to the
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Spanish flu of 1918 to 1920, what are some of the similarities that you see with this novel
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coronavirus? And of course, I'll contrast that in a moment with what the differences are. And the
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point of this exercise is less about just abstract history, but more to understand what we can learn.
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Sure. So if you go back to 1957 and 1968, these were pandemics that were marked by the emergence of
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a novel flu virus that spread around the world very rapidly. And if you look at the United States
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experience of 1957 and 1968, about 100,000 people died from that, which is a substantial number because
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on record right now, the worst flu season we've had outside of 57 and 68 has really been 2017,
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2018, where about 80,000 people or so may have died. So these were severe outbreaks. And flu has a lot
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of similarities with coronavirus, but there are some differences. So one thing is, you know,
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they both are transmitted through the respiratory route. They both have symptoms that are included
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coughing and sneezing and sore throat and muscle aches and pains and fever. So they have a lot of
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overlap clinically. And I think that because of the way they spread and their symptoms, you can look at
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their spread and there's a lot of analogies that you can draw. But what I would say is with flu is
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sometimes it's difficult because people have already taken flu and put it into their own risk
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of daily life, that they know that there's going to be maybe 30,000 to 50,000, 60,000 people who die
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every year. So even during a pandemic like 1957 and 1968, most people still carried on because
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this was still a flu virus. And the same thing happened to an extent with 2009 H1N1, especially
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when we realized that its case fatality ratio was actually less than seasonal flu, even though it
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infected 61 million Americans, led to a lot of hospitalizations and put hospitals into distress.
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It wasn't that deadly. So people kind of took it in stride. This is something that's a little bit
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different because it's on top of flu. It's additive to flu. I think that's one of my pet peeves of the
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media coverage is sometimes they try to compare it to flu. But you remember that we're already going
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to have 40,000 to 50,000 deaths from flu. And this is on top of that. I do think that influenza gets a
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short shrift by people because it's something that they take for granted and don't realize the burden of
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infection that it has. And that influenza still, even today, remains the biggest pandemic threat
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that we face. If you think about some of the influenza viruses like avian influenza, they have
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case fatality ratios of about 65%. That's too much for the world to bear. So if one of those, like H7N9,
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became able to efficiently transmit from humans, that's a totally different type of pandemic that
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we're talking about than what we're dealing with today. And I think that's important. And maybe that's
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why I seem a little bit more optimistic than most people are a little bit more measured when I'm
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talking about this, because in my mind, I'm thinking about avian influenza and what that kind of a
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pandemic would represent. And I used to say that this is kind of a trial run because it's only, it's less
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than 1% case fatality rate, maybe as low as 0.3 case fatality rate. But we didn't do that great of a job
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with it in terms of diagnostic testing and hospital capacity and personal protective equipment. So that's
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magnified this. And that's the human factor that's magnified what the virus could do. And I think
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that's an important point to make. And that's how I would kind of leave it is that you have certain
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ways to think about this using flu as an analogy. But I do think that I'm a little more worried about
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our pandemic resiliency based on how badly we've handled a 1% case fatality rate pandemic virus,
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where you've got cascading decisions by governors in states and countries all around the world that
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really have magnified the damage that the virus has done. One other question I want to ask before we
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leave the historical, which is the sort of ebbing and flowing recurrences that occurred back in some
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of these other pandemics, where it's easy to sort of think of them as this was the impact on the
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United States, but not realizing, well, actually it had a different impact on this city versus that
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city. And they were not just different in terms of the strain they put on the healthcare system or
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even the mortality rate, but even temporally, they could be separated by quite a period of time.
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Is that something that also applies here in your opinion?
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I do think so. We have this tendency to think of a pandemic as a homogenous
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wave over the whole world or even a country, but it's actually many small outbreaks together. And
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everybody's on a different timescale based upon when the virus was introduced into that area,
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what their population density is, what their hospital capacity is, what demographic got infected.
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So you aren't going to see synchronous outbreaks. They're going to be a little bit staggered.
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And there's going to be differences on, for example, when did somebody do social distancing?
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When did someone not do social distancing? How do they vary between this state and that state?
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That's also going to impact the trajectory of the outbreak. You might see places like I'm sitting
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here in Pittsburgh right now, which hasn't had a bad experience with this virus yet, but we've had
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the opportunity to learn from New York and Seattle and San Francisco. And that's gauged the way that
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we've dealt with testing and hospital capacity. So our outbreak is going to be different because we've
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learned from them and we don't have the population density issue. So I do think there is going to be
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ebbing and flowing, especially with social distancing varying and maybe lifting in certain
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places of the country and not lifting in other places. And you may find that this virus is going
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to have some degree of seasonality. I don't think it will have complete full seasonality because
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there's so many people that are susceptible to it, but you may see this come back in successive
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waves. And remember, there are four other coronaviruses that circulate every year and cause
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about 25% of our colds. This is something that I suspect will be the fifth one that does that. And
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it looks like it has an intermediate severity. It's not as severe as SARS, for example, which has a
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case fatality ratio of about 10%, but it doesn't seem to be as mild as the other four coronaviruses.
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So I do think you're going to see ebbing and flowing, especially as social distancing changes
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across the country until we have a vaccine. And is it your view that this will now be a fifth
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coronavirus that will fit into the mix and it's never really going to go away? In the way that
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at least SARS and MERS, because of their severity, they don't really factor into that recurrent cycle
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we see every year. I do think this is going to be the fifth seasonal coronavirus. And I would say
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with SARS and MERS, it's not just that they were more severe, which they are, it's that they're poorly
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transmissible from human to human. They are mostly zoonotic or meaning animal to human transmission. So SARS
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from palm civet cats, Middle East respiratory syndrome emerged from camels. So that's something that's really
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limited to their spread. It's only those individuals who are in contact with those animals that are really
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at risk. And when you look at their outbreaks, they're very specialized. They're happening in healthcare
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facilities with poor infection control, and it doesn't really sustain itself in the human population.
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Whereas if you look at the other four coronaviruses, the ones that cause common colds, they are ubiquitous.
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They transmit very easy. They have a mild spectrum of illness, which allows people to go about their
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daily life and spread. And this new novel coronavirus does appear to be more like them in
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terms of their transmissibility. So that's why I think that this will be the fifth seasonal coronavirus
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until there's a vaccine. Do you think a vaccine is going to be specific to this coronavirus? Or do you
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think that it will be more geared towards all coronaviruses to cover not just this one, but perhaps
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others that will potentially emerge, a SARS-CoV-3 that's five years away?
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Right now, vaccine development is premised on making something specific to the specific
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immunogenic protein that the immune system recognizes for this virus. So it will be specific
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to that. But I do suspect you might see some cross-reactivity between the vaccine for this
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SARS-CoV-2 and other related coronaviruses. Maybe the SARS-CoV-2 clusters in something called the beta
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coronaviruses. Maybe the vaccine will work against all beta coronaviruses, but it would be great if it
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worked against all coronaviruses and we had a pan-coronavirus vaccine. We might get something like that
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because coronaviruses are different than, for example, influenza, which has been very hard to
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make a universal flu vaccine. The coronaviruses in general tend to be much more stable, even though
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there's some diversity among them. And we might have cross-protection, which would be useful to
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take other threats like Middle East Respiratory Syndrome and the original SARS off the table as well.
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When H1N1 hit, you sort of alluded to this briefly, the case fatality rate was initially deemed to be
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much higher. It was only once we appreciated how prevalent it was that the case fatality rate
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came so far down. I believe in the end, it's less than 0.1%, correct?
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What is your real assessment now? And again, you can only be speculating at this point,
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I understand. But what do you think is the true case fatality rate of SARS-CoV-2 specifically?
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And if you want to answer that, by the way, in terms of, I think that the CFR is going to be this for
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people over 60 and this for people under 60, and it blends out to this, I mean, answer it any way
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you see fit. So the CFR has been really hard to calculate because we have a severity bias because
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testing has been so heterogeneous around countries. So what I do is try to look at a place that's
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tested extensively and use that as kind of a barometer. And right now, it used to be South
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Korea that tested, and now it seems to be Germany is doing the best testing. And you're also looking at
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modeling studies. So some of the modeling studies from Imperial College put the case fatality ratio at
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0.66%. Germany looks like it's at a 0.3 something percent.
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Yeah, doing antibody testing to try and understand. So I do think it's probably in that range,
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probably in the 0.3 to 0.66. I say that with some confidence, but it may drift lower or higher
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depending upon how much severity bias is in the samples. And it's very hard. We probably won't
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truly know until we do retrospective studies looking at antibodies to understand how prevalent it is.
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And there's differences amongst that because that's an average number. If you're above 80,
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your case fatality ratio may be as high as 15%. If you're eight years old, your case fatality ratio
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may be 0%. So I think it's important to remember that these are average numbers and it's not
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every person carries that risk. Some people will have much, much higher risks and some people will
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have lower risks. And I think that's sometimes lost in nuance when you try to come up with one number.
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Absolutely. Yeah. Blending that is, you know, there's lots of glib examples of how
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you can drown in an average of three inches of water. Of course, if you're walking across a river
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that has vacillating depth, because you're again, kind of a veteran of this, what do you think was
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sort of the over slash underdoing of some of the predictions that came out in this sort of gen one
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models that showed up in sort of February where they were saying, look, this is something that is
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going to infect 200 million Americans. It's going to kill two to 4 million Americans. Do you think
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that that type of modeling historically has ever shown to be accurate? Or do you think that, yes,
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that was accurate and it's the measures that are in place that are going to hopefully prevent that
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from happening? Because it seems less likely now that we're heading in the direction of those types
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of doomsday scenarios. But again, it's hard to know how much of that is in response to the measures that
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have been enacted versus predictions that were predicated on poorly understood things, including
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what the are not was. I think that models you have to realize have assumptions built into them and you
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have to look at those assumptions because just a small difference in the assumption can lead to a big
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change on the end of it. And what I would think, at least from my understanding of many of the
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models, is that the hospitalization rate was probably overstated. Because we know, for example, that the
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diagnosis that we're talking about in any given city or town are likely understated by a factor of at least
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maybe 10. And I can say that from my own practice when I order the test and don't order the test. There's many
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patients I think have the disease and I don't order the test. So there clearly is a severity bias in who gets
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tested. And then I think you see this idea of 15 to 20% getting admitted to the hospital. I think that
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that doesn't necessarily mean everybody of the people that get infected, maybe that's 40% of the
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population over time, that 15 to 20% of those individuals get admitted. It's more like of the
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40% of the population that get infected, the ones who go to an emergency department, 15 to 20% get
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admitted. And maybe the real hospitalization rate is 5%. If you look at, for example, Westchester
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County's data, which I haven't looked at lately, but the last time I looked, they did a lot of heavy
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testing in that part of New York State, because they had that outbreak in New Rochelle. And their
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hospitalization rate was around 5%, a little bit less than 5% the last time I calculated it.
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And that changes, that gives you a major change from going down from 20% to 5% in terms of what your
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ventilator needs are, what your ICU bed capacity needs are, and what the case fatality ratio is going to be,
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if you look at what the hospitalization rate is. And I think that that's, at least one of my
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criticisms of some of the models, the hospitalization rate was set too high, and that they were taking
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too big of a fraction, using the wrong denominator, I think, to come up with what their case fatality
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ratios are, what their ICU bed needs would be, and what their mechanical ventilation needs would be.
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And that happens, because models have lots of assumption in them, and they should be used as tools,
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they're not ironclad. And I think that sometimes that gets lost in the press reporting of them,
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they get looked at as if they are the truth, and they need to be revised. And when you have real
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data from real hospitals and real people, it should supplant what you're using with the model.
00:21:34.760
So if your model is not matching reality, then I think you need to either change the assumptions
00:21:38.320
on the model or actually look at reality. These are tools, and all models are going to be wrong.
00:21:43.260
Some of them are going to be useful, and some of them are not going to be useful.
00:21:46.660
I agree. I think it's, unfortunately, the press sometimes views corrections of models as a sign of
00:21:52.120
weakness as opposed to a necessary part of the evolution of utilizing the tool as you described
00:21:56.380
it. We've talked a little bit about this being a dress rehearsal for what is coming unquestionably
00:22:03.560
at some point, very likely in our lifetimes, which is another pandemic, another virus, and potentially
00:22:10.180
one that could be much more devastating. You used an example of viruses that are typically
00:22:16.080
transmitted only from animals to humans that can potentially be much more catastrophic.
00:22:22.420
But if those viruses ever figure out how to go human to human, they spread much more.
00:22:27.880
What is your view on the role of local versus central government in dealing with that? Can't imagine
00:22:37.540
there isn't a role for both, but I feel personally very confused when I try to, you sometimes play the
00:22:43.820
game. If I were czar for a day, what would I do different? But the reality of it is, it's easy
00:22:47.580
to play armchair quarterback. I'm not really sure I know what the federal government should be doing
00:22:52.420
in this situation versus the state governments and local governments.
00:22:57.420
So this is something that's pretty unique to the United States because we have a system of
00:23:00.560
a federal government with states and locals having most of the power. And it's especially true in
00:23:05.660
public health because most of the public health powers are vested at the local and state level.
00:23:09.040
And the federal government is more of a coordinator. Even the CDC can't actually get involved in
00:23:14.300
something unless they're asked by a state. So you will often see differences and heterogeneity
00:23:19.340
between recommendations from maybe one county to the next or even, and definitely from one state to
00:23:24.080
the next. And sometimes that can be confusing. I do think that I'm generally supportive of local
00:23:29.380
health departments being the ones running it because they actually know their community and they know
00:23:32.680
their capacities. They know where their gaps are and they're able to really be on the ground with the
00:23:38.060
people and able to do great things when it comes to stopping an outbreak. But often what we find
00:23:43.520
is local health departments aren't appropriately resourced. And you've got one person doing four
00:23:47.000
different roles in a small town's health department, and that can be very constraining. And what you need
00:23:51.880
to really do is have those local health departments actually operating the way that they should be
00:23:56.520
and thought of as part of the whole pandemic response apparatus. Whereas many people think of just
00:24:02.020
the CDC, the NIH, and parts of the Health and Human Services Department as the main
00:24:06.040
pandemic apparatus, but it's actually the local health departments that do all that case finding
00:24:10.620
and isolation and talk to the public and deal with hospital capacity levels. It's the local health
00:24:15.640
departments. So I can't overstate how important local health departments are. And I do think that
00:24:20.500
that system works well, but you do need to have federal leadership to kind of guide the nation as a
00:24:25.760
whole on what to expect and what's going on. And I think that's sort of been missing a lot during this
00:24:30.260
outbreak compared to other outbreaks. And because of that, you've seen governors at state health
00:24:35.280
departments take on roles that they usually haven't taken, where they've deferred much more to federal
00:24:39.300
experts, not the powers, but the guidance and looking to them to set the tone. And I think now
00:24:45.080
we're finding governors basically stepping into that role for the most part, and even mayors in some
00:24:49.620
places. And I think that can be confusing to a member of the general public, because they don't
00:24:53.320
know who to believe, especially if there's conflicting information. You have a press that's constantly
00:24:57.340
trying to pit one governor against another governor against the federal government. And that makes it much
00:25:01.540
harder. But I do think that when the process works well with local, state, and federal government all
00:25:06.020
in step, all doing the appropriate roles, I do think it works pretty well. You have a locally managed,
00:25:12.140
federally coordinated response, which I think is the best way to think about how it would be ideally
00:25:16.740
done. Is it safe to say that testing is really something that like, if you go back in time and maybe
00:25:22.060
change one thing, if we're sitting here and it's January 12th, and we now have the sequence of this virus,
00:25:27.700
would that have potentially been one of the more important things for the federal government for
00:25:32.460
that centralized piece of government to have put in place? The CDC could have said, look, we're going
00:25:37.660
to make this the highest priority. Because it strikes me as that's something very difficult to be done
00:25:42.380
in a decentralized manner. Right. So what happened was the CDC put out guidance on who should be tested,
00:25:48.440
which basically was taken as gospel by the state health departments. And that included
00:25:51.900
only people that had traveled to China in the last 14 days, as well as someone had had to
00:25:57.620
have lower respiratory tract symptoms, you couldn't have just had a sore throat, you had
00:26:02.320
to have evidence that maybe you had pneumonia to be tested. So we weren't testing mild cases,
00:26:06.300
and we weren't testing people that hadn't come to China. That was a federal decision. And I think
00:26:10.700
that could have been done better and allowed much more latitude. Because you can remember that first
00:26:14.820
case in California that didn't have traveled to China, they the hospital had to actually fight
00:26:18.840
to get that test run. And there were many cases like that all over the country. And if you look at
00:26:24.360
New York's epidemiology, their introduction of the virus was not from China, it was from Europe.
00:26:29.600
And that slips through the type of testing algorithm. So I do think that there could have
00:26:34.500
been at the beginning, an idea that somebody could have said, this is a respiratory virus,
00:26:38.060
it has many overlapping symptoms with common colds and flus, you should think about this in your
00:26:42.240
patients. And we are going to allow testing to be done. If you have certain risk factors for this,
00:26:47.920
and they shouldn't just be restricted to you having severe disease or having traveled to China,
00:26:52.880
that would have changed the way that the general public and clinicians would have thought about
00:26:56.420
this. The other thing is, is that there were bureaucratic wrangles that paradoxically,
00:27:00.560
once a public health emergency was declared, they were unable to make diagnostic tests as freely
00:27:05.380
available as would have been if there wasn't a public health emergency made. So for example,
00:27:08.980
you had university labs and big commercial labs not being able to make a test, even the CDC's test
00:27:13.120
had to go through FDA emergency use authorization before it could be distributed to the states.
00:27:17.300
So there were a lot of bureaucratic hiccups that created a problem that compounded the testing
00:27:22.240
protocol with the scarcity of tests and a delay in getting testing kits everywhere. And then
00:27:26.860
we still have shortages of reagents and nasal swabs, and we're still not to where we need to be with
00:27:31.920
testing. And not to get too far ahead of ourselves, but do you get the impression that the response to
00:27:38.300
this is serious enough that it will now be taken more seriously to have kind of that type of emergency
00:27:45.000
response ready five years from now when people have long forgotten about this?
00:27:49.140
I hope so. I think this is something that's going to leave a mark on society. This hasn't happened in
00:27:53.740
modern times, not during the 68 or 57 pandemics. And it did happen in 1918, but that's not in
00:27:58.920
anybody's living memory anymore. So I do think that this is something that people will remember,
00:28:03.580
and they'll remember the costs that they personally had to incur filing for unemployment for the first
00:28:07.800
time. All of that type of stuff is going to hopefully push the public to demand that pandemic
00:28:13.900
preparedness be taken seriously so this doesn't happen again, and that this should be a
00:28:17.760
priority. This should be something that's in a candidate's campaign literature. This is what I
00:28:21.980
think about pandemic preparedness, and it always should have been. But we've gone through this cycle
00:28:25.700
for a long, long time. You can think about anthrax in 2001, bird flu scares in 2005,
00:28:31.440
the H1N1 pandemic in 2009, Ebola in 2013, 2014, Zika right after that. We've had multiple types of
00:28:39.480
episodes, and you get this cycle where everybody runs to fund this reactively, and then it goes from
00:28:45.640
the headlines, and no one remembers it. And then the same cycle happens. They cut positions at the
00:28:51.060
National Security Council when there's nothing going on. They do lots of things that make us
00:28:54.740
less resilient to pandemics, not realizing that this is a perpetual threat, just like
00:28:58.220
any other national security concern, that you have to be prepared for this at all times. And you have to
00:29:03.080
actually think about it that way, and fund it that way, and have the proper personnel, even between
00:29:07.100
pandemics and between outbreaks. But you are optimistic that this time, I mean, just based on the
00:29:12.520
economic consequences of this, even if not one more person were to die in the United States,
00:29:17.560
which means, frankly, let's be clear, if not one more person died in the United States as of today,
00:29:22.780
this would not be a major source of mortality. This would still be a rounding error compared to
00:29:27.760
influenza. But you're just saying the economic consequences of this have been so severe that
00:29:32.800
you're optimistic that we're not going to walk away from this one in 18 months and sort of forget about
00:29:37.340
it and do all the wrong stuff all over again. Yeah, I do suspect we're going to have
00:29:41.420
many more deaths, probably closer to that 60,000. I do think that the fact that this outbreak touched
00:29:47.120
people personally in a way that Ebola did not, the way that Zika did not, the way even that H1N1
00:29:52.000
did not. H1N1 actually engendered complacency because only about 12,000 Americans died, and then
00:29:56.960
people said we all overreacted to H1N1. So I think this is actually something that every American is
00:30:03.080
feeling right now because of the economic shutdown, the stay-at-home orders, all of that, the fact that they
00:30:08.420
had to adjust their entire life, this is something that's been extremely disruptive. And I think that
00:30:13.000
hopefully the public remembers that when they vote, and when they ask their policymakers about
00:30:17.360
what their plans are for the future, that pandemic preparedness becomes something that is a platform
00:30:21.800
issue now. Based on where we are, what do you think is the right strategy in, for example, a place like
00:30:29.700
New York versus a place like, you could pick any city you like, whether it be Pittsburgh, Houston,
00:30:34.660
cities where it's been nowhere near that. I mean, how would you start to think about changing any of
00:30:41.220
the policy, or is the answer until we have more testing, we can't make any more decisions?
00:30:47.500
I do think based on modeling, if these assumptions are valid, and what's going on in the ground in
00:30:53.100
hospitals, you can start to see this heterogeneity across the country. And not every place is going to
00:30:57.960
be New York City. Not every place has that population density or hospitals that are at the brink all the
00:31:02.720
time. So I do think that there are places where you can start to think about relaxing some of the
00:31:08.160
social distancing recommendations, as well as the economic shutdowns, especially things like
00:31:12.340
elective surgeries at hospitals and opening clinics at hospitals. I think that already needs to happen,
00:31:17.460
especially so in places where they're not inundated, because you're going to get other
00:31:21.140
health consequences that are not captured by the models, which are really measurable and will pay for
00:31:25.940
down the road. I do think you can look right now at the governor's lists of what is an essential or a
00:31:31.420
life-sustaining business and what is not, and look at who they're granting exemptions to and try to be
00:31:35.200
a little bit broader about that. Think about looking to see what your school system is like,
00:31:39.240
and can you open schools in a safe manner right now based on what the conditions are in your area?
00:31:43.700
Because even the whole closure of schools was very controversial and not supported by everybody
00:31:47.900
in my field. So there are things that you can do. And I do think it's not going to be one size
00:31:52.180
fits all. It's going to be dependent on what's going on locally, how much transmission do you have,
00:31:56.360
what is the antibody status of your population, what's your hospital capacity,
00:32:00.200
and what is your ability to do diagnostic testing? Do you have the new rapid test
00:32:04.220
available in many different places? All of that can help condition how we get back to normal or a
00:32:09.460
new normal, because I do think that things like mass gatherings are going to be very hard to have
00:32:13.840
for some time until we have a vaccine, because I think a mass gathering is kind of can put a town
00:32:18.500
over the edge if they get multiple episodes of transmission at a mass gathering. But I do think
00:32:22.720
that we can start taking steps, and I hope that we start doing it, because this cost is something
00:32:26.700
that is measurable, and it increases every day. And I do think that there are going to be consequences
00:32:31.520
that are not captured by our models, which are really only focused on coronavirus.
00:32:36.320
Yeah, it's an interesting point you raised there with respect to mass gatherings. I mean,
00:32:38.840
I think the German data, which just came out basically last night, would suggest that it's really the mass
00:32:45.960
gatherings that are disproportionately driving the spread versus two people having dinner at a restaurant.
00:32:52.100
Is it your view that there's really something quite devastating about concerts and live sporting
00:32:58.260
events that is not necessarily captured in going to the grocery store?
00:33:03.520
Yeah, a mass gathering brings people from wide geographic areas. If you think about,
00:33:08.240
I live in Pittsburgh, and there are Steeler fans that come from everywhere in the country to watch a
00:33:12.360
Steeler game, and then they go back to their hometowns. That's a way you can disperse things. And
00:33:17.040
sporting games are not people sitting quietly with just one person. They are social gatherings,
00:33:22.260
where people are yelling and screaming and eating and drinking, and all types of things that a virus
00:33:27.620
would look at as an easy way to get from one person to another. We know that when people shout and
00:33:31.900
scream, they make particles come out of their mouth. That can transmit. We've seen this at choir
00:33:36.040
practice, for example, with this coronavirus. Just think of that. It's at a football stadium, and you can
00:33:41.280
imagine how these types of things can transmit. I do think that mass gatherings, because of the density,
00:33:46.160
because of the fact that people come from different geographic regions, and then just
00:33:49.500
disperse, are a particular problem when it comes to communicable infectious diseases. And we see this
00:33:54.060
every year with, for example, religious pilgrimages to Saudi Arabia, where they make sure that you have
00:33:58.560
this type of vaccination. They have a whole division of the World Health Organization devoted to mass
00:34:03.180
gatherings, because we know what their role is in spreading infectious diseases. And I think that's going
00:34:07.220
to be something that's going to be a challenge to have until there is a vaccine.
00:34:11.600
And I want to go back to something you said about HKU1. Tell folks a little bit more about that
00:34:15.600
coronavirus and the concern it gives you. It's less of a concern than it gives me now,
00:34:20.420
but it's more of understanding what happens with coronaviruses. So go back to 2003, and SARS is the
00:34:27.140
first coronavirus that really hits the map as a pandemic threat, before they're thought of as
00:34:31.100
common cold viruses. Now everyone's on the lookout for any new coronavirus. And what they do is,
00:34:35.540
in Hong Kong, HKU stands for Hong Kong University, they find a novel coronavirus in some individuals
00:34:41.580
that had pneumonia. And they start looking, they find more. They actually look at bank samples that
00:34:46.240
were negative for SARS, positive for HKU. They look in other countries, they find HKU1. They actually
00:34:51.760
find it in Cleveland. In the proportion of patients that were hospitalized for coronavirus, HKU is
00:34:56.600
disproportionately found, even in patients who died or were on ventilators. And it was basically
00:35:01.120
everywhere you looked. That's interesting, because it kind of flew under the radar, because no one knew it
00:35:06.260
was there, because we do such a poor job at testing for respiratory viruses. Many times people go to
00:35:11.140
the doctor and they say, oh, you've got some virus. We don't know which one, but you're going to get
00:35:14.220
better. And that's even the case for pneumonias, because most people don't get a specific microbiologic
00:35:18.820
diagnosis of their pneumonia. So we really have this biological dark matter everywhere. And I initially
00:35:23.760
thought maybe this coronavirus was around, hidden in our cold and flu season. It clearly was hidden in
00:35:29.120
China's cold and flu season since at least November. But it doesn't appear, at least from what I've seen
00:35:33.540
now, that there was much burden of that in the United States prior to 2020, that this might have
00:35:38.560
been something that really only began in earnest in January. But I would not be surprised if you find
00:35:43.620
a bank sample that there were cases in December that were mixed in, just like with HKU1. But I do
00:35:48.660
think we would have noticed if there was a lot of these people getting really ill and ending up on
00:35:53.020
ventilators and were flu negative and negative for everything else. At least enough of them would have
00:35:58.340
raised some alarm bells, I would hope. But I do think it's an important lesson to think about with a
00:36:03.100
virus that can spread surreptitiously and you don't know about it because our diagnostic curiosity is
00:36:08.540
so bad for many infectious disease syndromes. Yeah, that's a nice way of putting it, poor
00:36:13.320
diagnostic curiosity. Have you been following the sort of natural experiment that's going on in
00:36:18.040
Sweden? Natural experiment meaning there's no randomization, but rather Sweden has sort of
00:36:22.260
elected to not shut down to the extent that other European and Scandinavian countries have.
00:36:28.180
Have you paid attention to the transmissibility in Sweden or do you have any comments on it?
00:36:32.780
I've looked a little bit at what Sweden's doing where they're trying to pursue a herd immunity
00:36:36.280
strategy. And I do think that you're going to see more cases there, which is what they're
00:36:40.260
aiming for. I'm just worried because their per capita ICU bed numbers are not very high. And that's
00:36:45.800
what we're really worried about is do you put an ICU into crisis? Do you have problems with ventilators?
00:36:50.320
And I think it will be really instructive to see if they can get through this because I know they
00:36:54.420
have a steep curve of infections, but it's all going to depend upon who's getting sick and how well
00:36:59.220
they can sequester their high risk groups, which I think is very daunting and challenging. I'm all
00:37:02.720
for cocooning the elderly and those with other medical conditions, but I know it's very challenging
00:37:06.960
because they have to interact with other people to get their food, to do other things. And that can
00:37:11.600
be really challenging. So I do think that everybody's eyes are on Sweden to see if this type of thing
00:37:15.700
can work. But I'm worried about how challenging it might be for them because there is that group of
00:37:21.020
people that are going to get hospitalized and could put a hospital into crisis.
00:37:23.880
Last thing I want to ask you is what role do you think masks are going to play as we start to
00:37:29.020
slowly ease restrictions in the coming months? Do you think that we kind of got off to a bad start
00:37:34.940
on understanding the potential benefit of an N95 mask for people in public who are otherwise at
00:37:40.660
relatively low risk? So this is controversial in my field and I tend to be someone who's not
00:37:45.780
someone supportive of masks by the public and especially not N95 masks, which I think are in short
00:37:51.320
supply, unclear whether the public can actually bear wearing them for a long period of time because
00:37:55.920
they're not comfortable to wear. And really what we saw in the beginning was a recommendation to not
00:38:02.180
wear masks for the general public because it wasn't going to protect you from getting infected to one
00:38:06.280
that's transitioned to wear a mask so that you don't infect other people. So I would say if someone
00:38:10.400
is sick, if they have a cough, if they have a fever, if they're sneezing or a sore throat, they should
00:38:15.660
be wearing a mask when they're out in public. Question is, are people who are asymptomatic, having no
00:38:20.580
symptoms, how transmissible are they if they don't wear a mask? And this is an open question, but the
00:38:27.240
CDC made a recommendation for people to use homemade masks in that event. And I'm not sure how well those
00:38:32.280
homemade masks prevent you from spreading it if you are one of those asymptomatic persons because they
00:38:36.560
don't even stop the coughs and sneezes very well based on some studies that have been published. So
00:38:41.060
I'm someone who doesn't necessarily think that these masks are going to be very beneficial and they
00:38:45.760
could be paradoxically negative because people may then refrain from washing their hands as much.
00:38:51.300
They may not social distance as much. They may contaminate other people with their mask if they
00:38:55.160
don't store it properly or wash it. So I have a lot of concerns about masks, but I think that this is a
00:39:00.020
decision that's going to be made on a political basis. And there is enough scientific controversy
00:39:04.460
that I think politicians may use it as a way to move forward in a way that allows us to open schools,
00:39:09.600
open businesses up if they have people wearing masks. But I'm not sure if we'll get much benefit from them.
00:39:14.360
But it is something that's going to be an object of controversy for some time in the field.
00:39:21.540
I would say that I'm most optimistic about the fact that we have seen plateauing in New York,
00:39:26.080
Seattle, California. We've heard about, for example, California actually taking ventilators
00:39:30.440
and giving them to other states. We've heard about Washington State dismantling their field
00:39:34.600
hospital that they made that did not see any patients. We've heard about Washington returning
00:39:39.000
ventilators, strategic national stockpile. All of that makes me very optimistic that we will be
00:39:44.340
able to meet the challenge of this virus without putting any of our hospitals into crisis,
00:39:48.400
that this is going to be a severe challenge for this country, but it's not something that
00:39:51.900
is going to break the country. And it's not going to be cataclysmic. So all of those types of things,
00:39:58.740
which are not well reported, the fact that ventilators are going back to the stockpile or
00:40:02.180
that field hospitals are closing. I think that makes me optimistic because there is a narrative
00:40:06.200
that's rightly focused on areas like New York and New Orleans and Chicago and Detroit.
00:40:10.880
But you also have to tell the good stories that there are places that were preparing for a surge
00:40:15.240
and now they're downsizing their nursing staff because less people came. So I think that that's
00:40:19.300
an important part to know that it's not going to be doom and gloom in every place and that we need to
00:40:22.860
help New York and New Orleans and Detroit and Chicago get through this. But not every city is going to
00:40:27.460
have that experience. We're going to learn from those experiences. And I think hopefully we'll get to
00:40:31.400
a better pandemic resiliency position after this. So I am generally more optimistic than most people in my field,
00:40:38.400
Mesh, thank you very much for all your insight today. I'd like to reserve the right to sort of
00:40:43.560
invite you back when the dust has settled and we have much more time to talk about what a true
00:40:47.520
preparedness strategy would look like. Because again, I do have a significant fear that as visceral
00:40:54.120
and palpable and disturbing as all of this is today, both in terms of the physical suffering,
00:40:59.960
but the fear, the economic devastation, that we're a species that is relatively hardwired to have
00:41:05.460
remarkable amnesia. I don't know. I think it would be an unmitigated disaster if two years from now
00:41:11.880
we're sitting here and this is not at all a topic of discussion and someone like you is not able to
00:41:18.580
command the type of audience of policymakers to do what's necessary. So anyway, I hope that we can
00:41:25.100
have that longer discussion when there are fewer fires burning, but when I think the stakes are equally
00:41:29.640
high. Thank you. Thank you for listening to this week's episode of The Drive. If you're interested
00:41:36.120
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