The Peter Attia Drive - #117 - Stanley Perlman, M.D., Ph.D.： Insights from a coronavirus expert on COVID-19

00:00:00.000 Hey everyone, welcome to the drive podcast. I'm your host, Peter Atiyah. This podcast,

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00:00:41.740 head over to peteratiyahmd.com forward slash subscribe. Now, without further delay,

00:00:47.740 here's today's episode. I guess this week is Stanley Perlman. Stanley is a professor of microbiology and

00:00:55.240 immunology along with being a professor of pediatrics and the chair of virology at the

00:01:00.480 University of Iowa. Stanley has researched coronaviruses for nearly four decades and his

00:01:06.380 lab is currently using mouse models for SARS-CoV-1 and SARS-CoV-2 to better understand the more severe

00:01:14.180 diseases that affect humans. I've wanted to talk with Stanley for a few months now. Understandably,

00:01:20.080 he has been incredibly busy. We have been part of a collaboration that is working on a longer study,

00:01:26.580 trying to understand the durability of immune response and the impacts of that, which we

00:01:30.840 discussed very briefly at the end of this podcast. So most of our contact has actually been through

00:01:34.640 that, but as we got a little bit of breathing room in and around our other projects, inclusive of

00:01:39.220 the one we're working on together, we decided it made sense to finally sit down and have this

00:01:43.560 discussion, especially as a beautiful extension of the discussion that I already had with David

00:01:48.440 Watkins. So I do recommend that you would listen to these podcasts in that order. The one with David

00:01:54.320 Watkins, of course, goes over the immunology a little bit. Here we talk specifically about

00:01:58.480 coronaviruses, including the sort of common cold coronaviruses. And of course, more importantly,

00:02:04.080 the three versions that really have caused incredible damage to humans, none more so than the one we're in

00:02:09.740 today. In this episode, we talk about a whole bunch of things that, again, just you can probably

00:02:14.680 imagine interest me to no end. When we're talking specifically about SARS-1 and MERS, what did they

00:02:20.780 teach us about this coronavirus? What does our knowledge of this coronavirus today versus what

00:02:26.780 we knew, say, five months ago, tell us about how this story ends? And what do I mean by ending?

00:02:32.780 All of these are topics that we get into, along with a very interesting discussion around the

00:02:36.560 therapeutic side of things, the vaccination side of things, and ultimately what could happen again.

00:02:42.100 So without further delay, I hope you enjoy my conversation with Dr. Stanley.

00:02:52.300 Hey, Stanley, thank you so much for making time to talk today. I've wanted to speak with you for a

00:02:56.500 couple of months now. And I know when we first connected, it was just nuts. And you said,

00:03:01.240 hey, Peter, thanks for reaching out. Can we talk when things calm down a little bit? And I was

00:03:04.700 so gracious, first of all, that you even took the time to respond. And then, of course, now we've been

00:03:09.260 able to work together on a separate project that maybe we'll talk about down the line.

00:03:13.080 But I'll tell you, the reason I reached out in the first place was really the result of something

00:03:17.340 that my research team came to me and said, which was, look, Peter, if you want to understand

00:03:21.060 coronaviruses, you've got to speak to Stanley Perlman. Everybody is an armchair coronavirus

00:03:25.540 expert now, but you actually want to talk to the guy who was studying coronaviruses before they were

00:03:29.840 sexy. And that's Stanley. So before we get maybe into how you became obsessed with coronaviruses,

00:03:35.620 how did you get involved in medicine and immunology per se?

00:03:39.180 Well, I actually started, I obtained a PhD many, many years ago in the areas actually of cell biology

00:03:45.780 and developmental biology and virology. So I did a whole potpourri of training as a PhD student.

00:03:52.540 And then again, during postdoc, and then I went to medical school. So there was a period there where

00:03:58.240 I learned, I didn't do coronavirus research, but I learned how to do research. And so then when I went

00:04:03.720 to medical school, I became interested in pediatrics and in infectious diseases. And I don't know what

00:04:11.300 my plans were exactly when I started medical school, but became really interested in how

00:04:16.460 baby brains interacted with viruses, which was not good. So when babies are getting infected with

00:04:23.160 viruses, especially in utero, it's often has devastating consequences. And I worked with somebody

00:04:29.140 who was really good at thinking about those babies. And I became just interested in research

00:04:34.660 issues around how viruses interact with the brain. So at that time point, I became interested. It

00:04:41.200 turned out that coronaviruses in mice provided a model that could lead to potentially important

00:04:46.920 information. So I went from all the other things that I did and from being a pediatric infectious

00:04:52.440 disease person, part of my training, I also started working with coronaviruses.

00:04:56.720 Now, what was the decision point that had you leave sort of a pure academic track, which you

00:05:03.840 would have been on from your PhD and your postdoc to sort of take that, I don't like to use the term

00:05:08.180 backwards, but I think you sort of get what I mean, take that backward step and go back to something

00:05:12.440 remedial like medical school. In other words, what really drove you to want to have a clinically

00:05:16.540 active research focus? Well, I think there are two things. One, I was interested in,

00:05:22.180 I felt I was getting compartmentalized in a small area of research. I don't think I

00:05:26.580 wanted to be in something that was quite so confined and didn't have too many relevance for

00:05:31.680 general health issues. And the second thing is ironic. I started my PhD at an early age and it

00:05:38.020 was almost like I was looking for a chance to take a little bit of a break. A medical school

00:05:42.700 and residency is more than a little bit of a break, but it was pretty fast. It was a total of

00:05:46.860 starting medical school to finishing fellowship was only six years, which is a long time, but not

00:05:52.260 compared to what most people do for this kind of training. It was a combination of both those

00:05:57.260 things of being wanting to really step back a bit and also wanting to find more relevance for human

00:06:02.780 disease. You're kind of a Doogie Howser because how is it you could do med school and because today

00:06:09.260 med school's four years, pediatric residency's three, and then pediatric infectious disease would

00:06:14.840 add at least two to that, right?

00:06:16.680 Oh, three. It's actually three now, yeah.

00:06:18.520 You'd be talking about a 10-year training program that you did in six.

00:06:22.720 So I was lucky because when I did went to medical school, there was a shortage of doctors and there

00:06:27.300 was one or two programs that allowed people to truncate their medical school training. I went to

00:06:34.040 one in Miami that if you had a PhD, you could basically do the whole thing in 22 months. And what

00:06:40.600 you did is you cut the first year down to six months, the second year down to about three months,

00:06:44.780 did the entire third year, and then you did the fourth year in eight weeks. So at the end of it

00:06:50.440 all, we did everything. And we could do it. The people had PhDs, though. I have to say they took

00:06:55.000 PhDs in whether it be physics or physics to psychology, to biology, to chemistry. So people

00:07:00.980 had different amounts of training. The training was good. The classes were really full of people who

00:07:06.560 were really creative and thinking about things. So it was generally intense, but a very good

00:07:12.000 experience. And you were well-trained at the end. So you did your residency at Boston Children's

00:07:17.500 or fellowship or both? Both, yeah. Both. So at the time, and probably still to this day,

00:07:23.020 Boston Children's Hospital remains easily in the top three in the world, perhaps along with CHOP and

00:07:28.300 SickKids and maybe a few others. So you're at the sort of premier pediatric hospital in the world.

00:07:33.840 You're training with, I guess you're referring to Brazelton as your mentor there?

00:07:38.060 Yeah, yeah. So right, Brazelton, yeah.

00:07:40.160 Yeah, yeah. So tell me more about childhood development. I mean, I don't know much about

00:07:43.820 it, obviously. And it certainly rings a bell when you say that viruses can really wreak havoc.

00:07:47.880 One of the few things I remember from OBGYN is the lengths you would go to to ensure that a mother

00:07:53.500 wasn't infected actively during childbirth.

00:07:57.120 Yeah. So we don't understand everything about this, but certainly viruses that invade the brain

00:08:02.300 during the first trimester really cause devastating loss of neurological function. And the later you go in

00:08:09.040 the pregnancy, the more likely it is to cause less disease. But even when you're infected during

00:08:15.140 delivery, babies infected with certain viruses have hearing problems, visual problems, and even

00:08:21.000 cognitive problems. So the babies, just because they're developing, they're incredibly sensitive to

00:08:26.200 anything that disrupts their development. And when I think about it, the direct relationship to what I

00:08:32.700 later did with research was really not so strong. But it was just the whole notion of could you do

00:08:38.380 anything to prevent these viruses from spreading in the human brain? And then also, the way they do

00:08:45.040 spread within the human brain, could this be something that would be useful for understanding

00:08:49.340 other functions if you did this in an experimentally infected animal? So that's the kind of the way. And

00:08:55.260 then coronaviruses turned out to have this interesting ability to cause

00:08:59.260 demyelination, or which was similar to what we see in multiple sclerosis.

00:09:03.800 So it sort of ended up in a long, roundabout way for my studying this multiple sclerosis-like disease

00:09:09.060 for 20 years before SARS came about.

00:09:12.200 Maybe this is probably just as good a time as any, Stanley, to really give people a bit of the lay of the land on what a

00:09:16.980 coronavirus is. Because anybody listening to this, when they hear coronavirus, they're thinking of SARS-CoV-2.

00:09:22.760 It might be helpful to put that in a much broader context, which is, what does a family of viruses

00:09:27.420 actually mean? When we say the Joneses and the Smiths, we're talking about a family, not Billy Smith

00:09:32.960 necessarily. So what does that look like?

00:09:35.680 So the coronaviruses are like any other set of viruses. Their viruses are put into that category

00:09:43.220 because of what they look like under the microscope, what they look like under the electron microscope,

00:09:48.100 how they make new viruses, the kind of replication strategy, we call it, that they use to make new

00:09:54.200 viruses. In the old days, you might have some serological testing that would tell you about

00:09:59.460 relatedness. I say in the old days, we still use that, of course, but we have genetic ways now to

00:10:04.740 really see how close viruses are. So you put all those things together, and particularly looking under

00:10:09.680 the microscope, we can say coronaviruses have a certain pattern under the microscope.

00:10:14.400 And all viruses that are coronaviruses have those patterns. It doesn't mean that they all can infect

00:10:20.320 people or they all can infect this animal or that animal. They're really very, very different.

00:10:25.740 And the ones that were known before SARS came about really were the experimental ones, like the ones we

00:10:32.540 use, which infected mice. And then also these other coronaviruses that infect swine and cows and cats

00:10:39.940 and dogs. And even now they're finding viruses that are not quite coronaviruses, but are very closely

00:10:45.780 related that affect insects and snakes. So these viruses infect across lots of species. And bats,

00:10:52.040 of course, we know, because that's been made very clear in the COVID-19 outbreak, because that's where

00:10:57.340 this virus undoubtedly started, at least distantly.

00:11:00.360 So is it safe to say that coronaviruses as a family, probably when compared to any other family

00:11:07.540 of viruses, flaviviruses that produce hep C that otherwise would have nothing in common,

00:11:13.060 about the only thing that's true of viruses is they need a host to replicate. Is that about where

00:11:17.100 the similarities end across the broadest discrimination of viruses? Or are there other

00:11:21.600 things that are uniquely, I mean, I guess they all have either DNA or RNA, but typically not both,

00:11:26.200 right? Yeah, except maybe HIV seems to have both.

00:11:30.360 But generally they have one or the other. Depending on the amount of genetic information

00:11:34.580 they have, they can do more or less functions than other viruses. There's these gigantic viruses

00:11:40.600 or these giant viruses, as they're called, that seem to have almost all the material. You need to

00:11:45.760 almost be a cell, they're not a cell, but they have a lot of their own material for making proteins and

00:11:50.540 RNA. Most RNA viruses just have the genetic material for programming the functions needed to reproduce

00:11:57.620 the virus and also make the proteins that cause the structure of the virus, that form the structure

00:12:02.800 of the virus. So those are simpler viruses. Coronaviruses have the unusual characteristic of

00:12:08.740 being huge. So the genetic information of a coronavirus is about four times that of the poliovirus,

00:12:15.360 and yet the virus doesn't seem to do that much more than poliovirus. So a little uncertain exactly

00:12:20.740 why it needs all that genetic information. And when you say huge, Stanley, do you just mean the

00:12:26.000 amount of RNA in it, or do you mean the actual diameter under an electron microscope as well?

00:12:30.660 The amount of RNA in it. Certainly the coronavirus is bigger than the poliovirus,

00:12:34.640 but that's because it has all this genetic material stuffed into the middle of it.

00:12:38.660 Can you put it in context for us? If you take the genetic material contained within a typical

00:12:42.780 coronavirus, how does it stack up against a human gene? I mean, the listener might not understand what

00:12:48.140 base pairs look like or how many kilodaltons we're talking about, but just contextualize it in some

00:12:52.480 way. Well, let me see how I can do that. Because it's big for a virus, a gene. If you took genes and

00:12:59.860 laid them side by side, it could be equivalent to 15 human genes laid side by side in terms of length,

00:13:07.060 but human genes have variable length. So if it was a longer human gene, it could be fewer of those

00:13:12.760 for the viral genome. This particular virus codes around probably about 25 or so different

00:13:20.080 proteins, varying size. A lot of them are pretty small. So it's a lot of information, but it's not

00:13:26.940 compared to the human genome, which has 20,000 genes. It's a very tiny amount when you think about 25.

00:13:34.560 And does it, like human DNA, contain coding and non-coding segments alike that are just as important?

00:13:41.720 No. Human DNA contains both non-coding sequences within genes and non-coding sequences outside,

00:13:50.700 and the vast majority of the human genome is not for coding. With a virus, the vast majority is for

00:13:56.560 coding. There may be stretches here and there that are spacers, as it were, between genes, but they're

00:14:03.280 real in a minority. So the strict answer to your question is yes, there's parts that are non-coding,

00:14:08.540 but it's a tiny fraction compared to the amount that actually codes for genes.

00:14:13.540 Just to go down the path of some speculation, do we have a sense of what the evolutionary pressure

00:14:18.960 was for coronavirus? I've never really stopped to think about it, but it always struck me as viruses,

00:14:25.260 unlike bacteria, don't really serve a useful purpose. I mean, it's true that maybe most of them

00:14:30.440 don't directly harm us, but if you eradicated this planet of bacteria, we would all die pretty quickly.

00:14:37.020 We live in a very healthy symbiotic relationship despite a pathologic relationship with a small

00:14:42.120 few of them. But if I could conduct a thought experiment and remove every virus from this

00:14:47.900 universe, wouldn't the world just keep ticking along fine? Or is there something I'm missing about

00:14:52.100 their function? Well, I don't think you're right. We have lots of great examples. For example,

00:14:57.380 in the ocean, there's zillions of viruses that interact with bacteria. I would bet if you took

00:15:02.700 that interaction away that there would be a problem. And people talk about even in the human

00:15:08.200 gut, there's all these viruses that people find. Some of them, I think, interact with those commensal

00:15:13.280 bacteria and are useful. Whether they're absolutely necessary, I don't think we know as much as we do

00:15:20.120 about commensal bacterias, which are really important for human life and animal life. But I would bet

00:15:26.320 if you took away all the viruses in the world, sure, you'd eliminate some of the ones that cause

00:15:31.980 human disease or non-human animal disease. But I think you might get away from others that

00:15:37.600 are actually beneficial. Yeah. So there might be some knockoff effect where they're helping

00:15:42.440 something that's second order to us. They're helping the bacteria that are helping us or helping some

00:15:47.740 other distant organism that's way down the plankton sub chain that I haven't considered fully.

00:15:53.500 I think that that's a possibility. And then bacteriophage on bacteria are going to be even

00:15:59.020 different than the ones directly on human cells. But there may even be animal viruses that have

00:16:04.040 roles that we don't understand very well that are important. I know there's some animal viruses that

00:16:09.820 interact. Insects have a relationship with each other and the animal viruses have an important part in

00:16:15.620 maintaining some of the developmental patterns in those insects. I can't tell you,

00:16:20.060 I know that some of them are wasps, but I can't tell you more if I remember. But there's definitely

00:16:24.820 viruses that without which there would be problems. So I'm sure you're tired of telling this, but I

00:16:30.460 think everyone should know this by now. But if not, why does it derive the name coronavirus? What is

00:16:36.280 the corona referring to? If you look under the electron microscope, it has these projections from the

00:16:42.040 surface of the virus that look like either the corona of the sun or the corona of the crown.

00:16:47.840 So I think the first people who saw it under the electron microscope decided to name it based on

00:16:53.280 that. You have to have a little imagination, but it's not so far off. And of course, this is relevant

00:16:58.560 when we start to talk about the immune response to it, because the immune response is particularly

00:17:03.820 strong when it comes to certain parts of the viral code. And we'll probably come back and talk

00:17:09.000 about spike proteins and things like that. So when did these coronaviruses show up in terms of our

00:17:15.680 understanding of common colds? I think we identified the first one in the 1930s and 40s

00:17:22.260 for chicken. That's what I remember, that the infectious bronchitis virus was found in chickens.

00:17:27.660 And then in the 1960s, people identified viruses that caused the common cold that had the same kind

00:17:36.140 of appearance as the infectious bronchitis virus. And I think by then we knew something about some of the

00:17:41.840 pig viruses as well. So the human, it was isolated from people with colds and had the same structure

00:17:48.540 as coronaviruses and chickens and pigs. So that's how they knew it was in the coronavirus family.

00:17:55.300 Is it the exception or the rule, Stanley, that a virus that infects humans also has an animal host?

00:18:02.360 I think I would say it can go either way so much that it's hard to make a strong conclusion.

00:18:09.980 Viruses like measles virus infects only people. Smallpox only infects people. That's why we can

00:18:16.600 eliminate them from human populations in theory. Viruses or the coronaviruses mostly seem to be able

00:18:24.700 to infect other animals as well. But the virus that I worked with for years in the lab, mouse hepatitis

00:18:31.120 virus was a mouse virus. And I don't think it affected anything but mice. The human viruses,

00:18:36.540 even now, so we're seeing that SARS-CoV-2, the cause of COVID-19, can infect animals. So humans can

00:18:43.260 infect these other animals by spreading the virus. SARS-CoV certainly infected other animals. MERS-CoV

00:18:50.240 is really a camel virus. So by definition, it infects other animals. The human common cold coronaviruses,

00:18:57.320 at least one of them can infect other animals. And I don't know, one of them probably came from bats,

00:19:04.220 but I don't know if they can infect bats. So I think coronaviruses usually can go across species,

00:19:10.120 but I don't think always. And other viruses often can go across species, but not always. And

00:19:15.660 it's really going to play, as I was saying, into the ability to eliminate a virus from the human

00:19:20.640 population.

00:19:21.300 So if you're keeping track of all the things that make a virus difficult for us as a species,

00:19:28.080 so if you're trying to build a super virus, having the ability to go into an animal host is an

00:19:32.960 important feature of that. Because you can basically, quote unquote, hide outside of the

00:19:38.540 humans for a while, even while a large population of the humans are either vaccinated or acquiring

00:19:43.280 natural immunity or even approaching herd immunity. And you can effectively lay dormant outside of the

00:19:49.020 humans for a while.

00:19:50.520 Maybe. When you think about different viruses, certainly that's true for West Nile virus. If

00:19:54.640 we have the best vaccine in the world, we still have West Nile virus floating around with birds and

00:19:59.820 other animals. Of course, West Nile virus really isn't a human virus. It's a virus that ended up in

00:20:05.280 humans at the end, but it wasn't really the intent, as it were, of the virus to infect humans.

00:20:10.600 Others, like measles, did just fine with infecting everybody and having huge amounts of herd immunity,

00:20:16.600 and still every three years or less coming out and infecting human populations again.

00:20:21.900 Is that because the R-naught of measles was just so high that it was like you just had one little

00:20:27.480 crack in the dam and it was a disaster, whereas for most things like influenza or even coronaviruses,

00:20:33.960 the R-naught is an order of magnitude lower?

00:20:36.260 Yeah, I think that that certainly contributes to it. With measles, you had five people out of a hundred

00:20:40.940 not vaccinated or not resistant to the virus. Those people would get infected if you put them

00:20:46.100 in a room with somebody who was positive for the measles virus. Same thing is true for smallpox too,

00:20:51.760 where it spread out an animal host. Others, I don't know, for other, polio, I don't think of polio as

00:20:59.200 having much of another animal host. I think that it continues to be in human populations, mostly because

00:21:05.220 poor vaccination and because we use live attenuated vaccine that ended up in the water and either

00:21:12.240 mutates or doesn't mutate, but it's not gone. And so where did those viruses come from? If they

00:21:17.060 never had an animal host, where did they evolve? Well, I think they did initially have an animal

00:21:21.960 host. So measles is thought to evolve from winter pest, which affects animals in Africa. You see,

00:21:29.080 that's the other thing about the animal host is if you evolve from an animal host, the virus evolved

00:21:33.360 from animal host, but then change so much to infect humans, they may not be able to then cause an

00:21:39.500 infection in the animal host. So these, like the SARS-CoV-2 that causes COVID-19, we don't really

00:21:45.160 know what it would do if you put it back in bats. No one's going to try, but I don't know if a bat

00:21:50.040 would be infected by it because it may have changed enough, even in the little bit of time it's been

00:21:53.840 out of the bat. So it can't infect the bat very well anymore. Wow. That's really interesting. So it

00:21:58.360 ping pongs back and forth until it finds a more favorable host. I mean, this would suggest from an

00:22:03.320 evolutionary fitness standpoint that if it starts in an animal, comes to a human, stays in a human,

00:22:09.020 it must find the human on some level, a more desirable host. I don't know, but that's making

00:22:14.600 the virus a little more anthropomorphic than it might be needed. If it's in humans, it may never

00:22:20.300 see a bat again. So it's not that it's more desirable hosts, but that's a fair point. Yeah. 0.99

00:22:25.440 Humans, bats don't interact that much, even though they interact more than maybe desirable given these

00:22:30.900 viruses. But it's not like the virus can look around and say, oh, there's a bat. I think I'll...

00:22:34.960 Yeah. Let me go try that out again and see how it compares to this.

00:22:37.540 Yeah.

00:22:38.040 Last question on this topic. Tell me a little bit about HIV. I'm just not a student of my immunology.

00:22:43.060 Is HIV a virus that is now believed to have evolved? I mean, I know back, I remember a million years ago,

00:22:48.060 people said, oh, it came from this monkey or that monkey. Do we have a very clear sense of the

00:22:51.880 lineage of HIV? I think it's beyond what I know well. I think that we have a very strong sense

00:22:57.960 that it came from non-human primates. I think we may know more exactly, but what I read periodically

00:23:04.800 is some studies, it seems like the virus was in human populations or identified way before its

00:23:10.340 first obvious entry into people who became HIV infected. So I think it's clearly from non-human 0.94

00:23:16.240 primates, but the exact details, I don't know. But I think some people do. And some of these sources,

00:23:21.300 like some non-human primates have an HIV-like virus that's pretty close.

00:23:27.380 Let's go into the, let's say it's the late nineties. So it's pre-SARS. You're working

00:23:32.020 hard on coronaviruses. At that point in time, is it, am I doing the math right that there are

00:23:36.740 basically sort of four endemic coronaviruses that are not especially severe, but just circulate

00:23:43.180 through humans causing annoying respiratory infections year after year? Is that directionally

00:23:49.180 the lay of the land? It's actually only two in the mid nineties because two of them

00:23:53.040 discovered after SARS in 2004 or so. Wow. Which were the two that came along and that

00:23:57.900 were there in the nineties? 2290 and OC43. Okay. And what did we know about people's

00:24:06.080 immune response to them? I mean, did anybody ever say, Hey, we should vaccinate against these

00:24:10.040 or was it, they're not that interesting. They don't make people that sick. Who cares?

00:24:13.640 Yeah, it was more of the latter appropriately. So if you're going to spend a huge amount of money

00:24:18.120 and we know that huge amounts of money are involved in making a vaccine, why would you

00:24:22.000 spend it on a cold virus? People get cold. It's annoying. The other thing is that really

00:24:27.140 that may be relevant to the thing about COVID-19 is that people who got these cold viruses, they

00:24:32.360 could be reinfected. So they could be reinfected a year later. And that's what the papers we were

00:24:38.700 talking about earlier really talk about is that the immune response may be, if you have a mild

00:24:43.840 infection, you may have a more transient immune response. Yeah. There are three or four papers

00:24:49.120 that I can't wait to dive into and we're going to do it. I just want to make sure the listener

00:24:52.560 doesn't get too lost in what we're talking about. But actually, if you're listening to this now and

00:24:57.000 you have not listened to the interview with David Watkins, this would be a great time to hit pause,

00:25:02.440 go back and do that. Because in that discussion, we really do the immunology

00:25:06.400 tour de force. And we explain the difference between the innate immune system, the adaptive

00:25:11.400 immune system, and the two branches of the adaptive immune system, the humoral system, which relies on

00:25:17.020 B cells and their antibodies, and the cellular system, which relies on T cells. And I have a very

00:25:23.180 strong suspicion that very soon Stanley and I are going to get into some of the weeds around the B

00:25:29.020 cells versus the T cells. And again, I don't think you can educate yourself enough on this topic if you

00:25:34.040 want to truly understand what's going on with these viruses. Bringing it back to the late 90s,

00:25:38.560 tell me what your interest was at that time. So obviously, you're a scholar, you're doing

00:25:44.040 incredible work. Did you think at that point in time, gosh, these coronaviruses aren't that

00:25:49.140 interesting. They're not really a threat to humans. They're not really a threat to my patients in the

00:25:53.400 way other viruses are. Even RSV would be more of a threat to children. Whooping cough would be more of

00:25:58.840 a threat to children. What is it that kept you in this, at the time, relatively benign virus?

00:26:05.680 Was it, help me understand, was it kept you in a field that ultimately turned out to be a very

00:26:09.600 productive decision? At the time, we were interested mostly in this mouse virus and

00:26:14.200 the human disease multiple sclerosis. So thinking about how does a virus go into the brain, end up in

00:26:20.940 the cells that make myelin, which are the sheets in the brain that cover the axons. And how does the

00:26:27.380 virus end up there? And then once the host realizes that the virus is there, how does it manage to

00:26:34.940 destroy tissue while it's eliminating the virus? How come the virus, the immune response, can't figure

00:26:41.660 out how to rid the cells of virus without also destroying the cells themselves and destroying the

00:26:48.240 function of their cells? So that's what I became interested in. That's what I was really studying.

00:26:52.240 How does this occur? What kind of immune responses were elicited by the virus? What mattered the most?

00:26:58.820 What caused demyelination and what caused remyelination, which is the process of getting

00:27:03.300 myelin back and which is in people with multiple sclerosis is the period when they have remissions

00:27:09.000 after relapsing and permissing or after relapsing have disease and they get better again for a bit of

00:27:15.260 time. For people who have some form where they get better to a large extent, how is that occurring as well?

00:27:21.780 So we were using the virus to try to study that.

00:27:25.020 But to be clear, was your personal interest at that time more in, this is a virus that helps us

00:27:30.720 understand a disease like MS, where we can understand the demyelination, remyelination process?

00:27:36.920 Or was it more, I think from a pediatric and a neurobiological development standpoint,

00:27:42.440 I want to make sure I understand what's happening in trimester one that is potentially injuring a

00:27:48.640 child's brain? Those two aren't necessarily mutually exclusive, but were you bent more towards one

00:27:53.360 than the other?

00:27:54.460 I think that by the mid-90s, I was thinking much more about the first. How does a virus infecting

00:27:59.460 the brain, how is it cleared? Why does clearance always involve tissue destruction? Why is that

00:28:05.180 happening like that?

00:28:06.520 So you're basically now becoming a neurobiologist with a background in immunology, virology,

00:28:11.260 and pediatrics.

00:28:11.920 Well, at that point, I became a neurobiologist with a background in virology and cell biology. I

00:28:18.740 didn't really start doing immunology till the early 90s, 1990s. So then we were doing some of it,

00:28:25.940 yes. The virus preceded my doing immunology.

00:28:30.220 So tell me what's going on when SARS hits. What is it? I can't even remember exactly. Was this 2002,

00:28:35.860 2003?

00:28:36.160 The end of 2002 became a big deal in 2003, and then it was eliminated in July, 2003 for

00:28:42.980 all intents and purposes.

00:28:44.840 So tell us the story in some detail. I think for many people, it's, I mean, I remember it because

00:28:49.080 there was a component that was in Toronto. I grew up in Toronto. I wasn't living there at the time,

00:28:53.740 but just that sort of perked my ears. But at the same time, I was in residency. So I was so sleep

00:28:59.320 deprived. If I could drive home without crashing, that was an accomplishment. So it's not like I was

00:29:04.060 really paying attention either. But can you give us sort of a really detailed account of where this

00:29:08.800 virus came from, how it emerged, and what impact it had on you and how it may have shifted your

00:29:12.740 thinking?

00:29:13.880 Yeah. So the way it emerged, we heard about this virus that was causing a respiratory disease in

00:29:20.600 southern China. And initially, we all thought this was going to be a kind of flu virus because flu

00:29:25.840 viruses, we know, initiate, often start in southern China, particularly in the city of Guangzhou,

00:29:31.580 which is across the bay from Hong Kong. So we heard about these viruses. And then it became

00:29:36.740 clear that they were a coronavirus. This was isolated by several laboratories. What we learned

00:29:41.960 in retrospect is that they actually came from a live animal market in Guangzhou. And this was a place

00:29:48.920 where animals were all put together for sale for food and other purposes. And so there were bats along

00:29:55.200 with other exotic live animals. And we learned that the coronavirus, the SARS coronavirus, was almost

00:30:02.380 certainly a bat virus that spread to these other animals. And the virus rapidly adapted to these other

00:30:07.840 animals and sometimes infected human handlers of that market. So people were actually handling the

00:30:13.420 animals to sell them. And many of those became sick. Many developed subclinical disease. And we know

00:30:20.700 that up to a third of the handlers actually had antibodies to SARS-CoV. So we know that this was

00:30:25.740 going back and forth a lot. Then we know that some of the time it spread to mainland China. How many

00:30:32.000 times that occurred, we don't know. Whether it was exactly the same virus that we study in the lab,

00:30:36.980 I don't think we really know that well. The reason that this became really, was brought to the world's

00:30:42.600 attention is that a single animal handler became ill enough to see a physician. The physician

00:30:48.560 actually became quite ill, didn't go home, rather went to a Hong Kong hotel. And at that point,

00:30:55.640 it was really sick and spread the virus to the other people on the floor. And they all went to

00:31:01.060 their homes. And that's how the virus ended up spreading around the world, because of this one

00:31:05.780 physician who ended up going to Hong Kong. Whether this would have occurred anyway is an open question,

00:31:12.260 of course. The main set of events was a single event. And that's why the virus seemed to start from a

00:31:18.280 single point source. Now, help me understand something. I think most people listening to

00:31:22.700 this are now familiar with R-naught, but we'll explain it again. What was the R-naught of that

00:31:28.340 SARS virus? In retrospect, I guess, what do we believe it was? How transmissible was it?

00:31:33.080 Yeah. So this is a good question, because the official numbers has an R-naught of about two to 0.86

00:31:38.920 three, which means that a single person will infect two to three people. So clearly, as you can see,

00:31:44.040 without even thinking about it very hard, if a virus starts with one person, then infects two,

00:31:49.460 and then each of those infects two more people, you now have four infections, they infect two,

00:31:54.020 you get eight. So you can quickly get up to high numbers by this exponential growth.

00:31:59.540 And we'll hit pause there for one sec. Just to put that in the context, earlier, for example,

00:32:04.180 you talked a lot about measles. Measles has an R-naught probably north of 10, correct?

00:32:08.880 Yeah, around 15. I mean, that's about as high as they come. I mean, that's an explosive

00:32:14.220 exponential multiplier. At the other end of the spectrum, today, HIV's R-naught would be

00:32:21.340 less than one. Yeah. And I think that HIV is a little different because it's not a respiratory

00:32:26.440 spread. Yeah. So let's use another respiratory example. What would be a low R-naught? Well,

00:32:31.420 let's use the other coronaviruses. If you take those other coronaviruses, they're one to two at most,

00:32:35.800 right? Exactly. So one person infects someone else on the average. This is on the average,

00:32:40.720 of course. So going back to now SARS, sorry to interrupt you there, but now you've got

00:32:44.680 a two to three R-naught. So this is quite a spreading virus. This physician goes to the hotel,

00:32:51.360 he gets a bunch of people potentially sick. And obviously now that can take the virus around the

00:32:56.860 world because presumably people at hotels are going to go back someplace, right?

00:33:00.000 Yeah. So I think that the R-naught of two to three though may be misleading because there's 0.99

00:33:07.000 no question that the R-naught on the average was two to three, but it consisted of spread within the

00:33:13.420 hospital. Spread occurred much more readily. SARS was a virus that really caused pneumonia and not

00:33:19.140 much more. So the virus didn't readily spread from one person to another until that first person was

00:33:25.480 pretty ill. And then if that person went in the hospital and you now started, as it were,

00:33:30.580 mucking up their lung fluids so that virus was now released into the air by procedures, either

00:33:37.000 intubation or suctioning or whatever else needed to be done, then the R-naught factor would be much 1.00

00:33:43.120 more than two or three. And the community, because this is a deep pneumonia, it really isn't that

00:33:48.360 contagious. So I think that if we split it up, those 8,000 cases would be an average of two to three

00:33:54.180 with quite a range depending on where the virus was acquired. And I think the other lesson we have

00:33:59.720 to take away from SARS is it gets widely quoted as having a 10% mortality rate. But again, how could

00:34:07.660 we possibly say that when we don't know the total number of cases? That might be the case fatality

00:34:12.800 rate. I mean, case fatality rate is not that interesting. It's the infection fatality rate that

00:34:18.180 really matters. And it's certainly possible, isn't it? That many more people had it. Even let's say

00:34:24.780 there was five times the number of people who actually had the illness, but didn't come down

00:34:30.140 with a severe enough version that they warranted hospitalization or testing. You would all of a

00:34:35.860 sudden say, technically the mortality of this is 2%, which is still absolutely devastating virus.

00:34:41.320 But it's not the devastation of... When you hear 10% mortality, I mean, that's literally like playing

00:34:47.180 Russian roulette.

00:34:48.640 That's the way that I think about it. But it was very hard at the time finding patients who are

00:34:52.920 asymptomatic and were infected. So the thinking was that anybody who became infected actually became

00:34:58.460 symptomatic. What you say makes perfect sense. But I'll tell you another story. So the next coronavirus

00:35:04.280 that came upon us was the MERS coronavirus, the Middle East respiratory coronavirus. And this is a disease

00:35:10.340 that's very similar to SARS and being a deep lung disease. This disease, the mortality is billed at

00:35:18.800 35%. So really terrible. And it's different though. So what you just talked about, the 2002 to 2003

00:35:26.560 virus that started in a market in Southern China, who has the same name as the current virus we're

00:35:32.440 talking about, but we refer to them as SARS-1 and SARS-2, they're in the same beta family, which we

00:35:38.200 didn't really get into. Do you want to take a minute to explain that? Because MERS is a slightly

00:35:42.360 different subdivision of the family. Can you help people understand that nuance?

00:35:46.560 Yeah. So it's all very similar. They're all in the same general group of coronaviruses and within

00:35:52.940 the same subgroup of coronaviruses, but they're slightly different in their genome organization

00:35:58.340 and in some of their coding. So they're put into a separate category.

00:36:02.240 So it's a coronavirus. Before we knew so much about from sequence, they would have been considered

00:36:07.820 the same type of coronavirus, but it's different enough. So we classify it a little differently.

00:36:12.620 What that means is it's a little more distant from the SARS coronavirus. So there's less thinking

00:36:19.640 that one could actually provide immune protection from the other. Though in fact, there's some cross

00:36:25.060 reactivity. MERS coronavirus is recognized in part by SARS coronavirus sera from people who survive.

00:36:31.700 But they're close. It's like your third cousin instead of your first cousin. It's pretty close,

00:36:36.940 but not as close. And this will obviously be interesting when we come back to this discussion

00:36:42.100 of cross-immunity. And basically that's probably the biggest difference as opposed to a functional

00:36:47.100 difference about the virulence or the potential for virulence, correct?

00:36:50.620 Right. Right.

00:36:52.240 Okay. So again, let's now pick it back up. It's what, is it 2009 when MERS came along?

00:36:56.660 Well, MERS and camels probably came along at least in 1983, but in people, it was found

00:37:03.360 in 2012. And that's the earliest cases. There's a few mysteries about MERS coronavirus. Why

00:37:10.240 is it only in the Arabian Peninsula?

00:37:13.160 So tell me about that. Did people, and when I say people, I really mean scientists. I'm sure

00:37:17.100 the population wasn't wandering around thinking about this, but did scientists appreciate that

00:37:21.420 there was a coronavirus in camels in the eighties from the early eighties? Was that something

00:37:27.980 appreciated?

00:37:29.080 Nope. This was absolutely not appreciated because in camels, these coronaviruses cause the common cold.

00:37:36.640 So that's why nobody would care. Camel gets a cold. You don't even know. He goes to camel

00:37:41.000 Walgreen and you never hear about him again. So what do we think accounts for the virus jumping

00:37:48.920 quite literally from a camel to a human in call it 2012-ish?

00:37:54.140 We don't know. The virus had been in camels since the late 80s and probably earlier. It worked

00:37:59.480 earlier. And we know it doesn't jump in Africa or other parts of Asia. So this is a real mystery

00:38:05.660 in this virus. Why is it only in the Arabian Peninsula?

00:38:08.700 When you look at the MERS virus in the camels, it's still the same in the Arabian Peninsula versus

00:38:16.040 other camels? Hard to know. It may be subtly different in parts of Africa where there's no

00:38:22.180 MERS, but we have a lot of trouble saying that those differences account for the fact that there's

00:38:27.320 basically no cases in Africa. And you have these cases in Saudi Arabia rising all the time now.

00:38:33.200 And when you say Africa, do you include North Africa? Were there any cases that arose in Egypt or

00:38:38.440 Algeria, Libya, Morocco? Yes.

00:38:42.040 They did not occur in those places? Yeah. Camels are infected there, but people are not.

00:38:47.160 Oh, wow. Because a lot of people would sort of say, look, I mean, if something happens in Saudi

00:38:50.820 Arabia, it would be just as likely to happen in Iran or Egypt. I mean, even though they're 0.66

00:38:55.660 technically belonging to different continents, they're very similar geographically. But you're

00:39:00.200 saying no, there was a really hard line distinguishing that. And we don't to this day have

00:39:05.700 a sense of what allowed that jump. Yeah, we don't know. The fact is not only

00:39:11.200 occurred in 2012, but it's occurring once or twice a week now. Because people are coming in

00:39:16.220 who actually have no contact with camels and are coming into the hospital with MERS. They often have

00:39:22.880 comorbidities. They're older or they might have diabetes, but otherwise they don't even have contact

00:39:27.120 with camels. And they have to get it from a camel, but not clear how. So wait a minute. That was my next

00:39:32.120 question. Do we know that it can or cannot spread human to human? Once a person gets it from its most

00:39:37.660 likely source of transmission, which is a camel, can one person infect another? Yeah. So this is

00:39:43.180 where the R-naught factor becomes important again, because the official number for MERS is somewhere

00:39:48.420 between zero and four. I think outside of hospitals, it's probably near to 0.35, 0.5, somewhere in that low

00:39:55.000 range. So it means it's not impossible, but all you need is somebody to be infected and happen to

00:40:01.860 infect someone else who's highly susceptible. And that highly susceptible person will then appear at

00:40:06.660 the hospital not having had any contact with a camel. And that zero to four, which is such a broad range,

00:40:13.480 I've read that as the official range, it's so broad as to be unhelpful. That's really the camel R-naught. 1.00

00:40:18.960 That's the spread from camel to human. And then as you said, human to human transmission is probably

00:40:25.340 going to occur in the hospital. And so MERS becomes the scariest of them all just on mortality because

00:40:32.080 the official numbers are basically it killed a third of the people that were infected. It's about

00:40:36.800 almost 900 deaths out of call it 2,500 confirmed cases. That's about as scary as any virus, maybe outside

00:40:45.980 of Ebola. But again, the absolute numbers are so low, the transmissibility human to human doesn't

00:40:53.840 seem as high, especially when you consider that the scariest viruses are ones that are transmitted

00:40:58.200 from asymptomatic people, right? Yeah. So this one, like SARS, is mostly transmitted from people who have 0.88

00:41:04.040 lung disease already, who have severe lung disease. I don't think the R-naught is actually camel to camel. 0.99

00:41:09.360 I don't think it takes that into consideration. Rather, what it takes into consideration is the

00:41:13.840 hospital spread. It's like SARS and so much hospital spread. And that's been basically not stopped

00:41:19.520 completely because as my friends in Saudi Arabia say, somebody comes in with this disease, we think

00:41:25.400 about it quickly, but we may not think about it in every case quickly enough. So there may be still

00:41:30.760 some spread within the hospital. So nosocomial spread, which you're referring to in hospital spread,

00:41:35.880 is a big problem because you just don't have it on the front of your mind that every person who shows up

00:41:41.960 in respiratory distress could have this. And therefore, A, potentially the healthcare workers

00:41:46.860 themselves can be infected because it's not just the proximity, but it's the type of procedures that

00:41:51.180 are being done. When you put a breathing tube in somebody, you're really creating an effective portal

00:41:56.220 for the virus to get to you. And then obviously we know how infections like that can spread through

00:42:01.900 intensive care units and such. Yeah, that's exactly right. That's exactly why it's a problem.

00:42:07.220 So why did this not turn into even an epidemic within the Arabian Peninsula? I mean, you did

00:42:15.280 mention that we still see a few cases each year, but 2,500 confirmed cases directionally makes it not

00:42:21.900 even a sort of an epidemic really, let alone a pandemic. Why do you think this just wasn't something

00:42:28.280 that spread despite its potential for devastation at the mortality level? Because I think that that

00:42:34.080 R0 of 0.3 really makes it not possible or not likely. There's plenty of cases with MERS where

00:42:40.220 people went back to a relatively poor country after having been a worker in Saudi Arabia, were found

00:42:46.080 to be infected and infected nobody. So that nobody became ill from that patient, even though they

00:42:51.220 weren't really looked at. That's as opposed to Korea where there's that one patient who infected 186

00:42:56.280 people. So there was really a confluence of lots of bad luck for that to have occurred.

00:43:01.300 And then going back to SARS-CoV-1, what basically accounts for the eradication of that? Call it

00:43:09.960 in 2003, 2004. The combination of there being no reservoir. So it's not like camels, which could

00:43:17.160 continue introducing to human populations. And the fact that because you weren't contagious till you

00:43:23.240 were sick, it was easy to look at somebody and say, aha, that person has SARS. We're going to stick

00:43:27.580 him in the room by himself, take care of him and make sure he infects nobody else. Then you would

00:43:32.900 stop the disease. It's a classic kind of quarantining, identification and quarantining that we talk about

00:43:38.260 over time with COVID-19. But it was really feasible with SARS when you're talking about a total of 8,000

00:43:44.320 cases around the world. I mean, Stanley, to hear you tell the story this way, it's just, it's like a bad

00:43:50.540 movie. Because you could be lulled into a false sense of confidence by the time MERS blows over.

00:43:57.080 You can say, hey, okay, I got it. You've got a few of these coronaviruses. They cause a bunch of

00:44:02.040 colds. You get a runny nose in the summer, but it's really nothing. And yeah, it's true. Two really

00:44:07.160 bad actors showed up that on a virus to virus level can really hurt their host, but they're nothing to

00:44:13.840 really be afraid of. In the case of SARS-1, it has two things that make it really friendly to humans.

00:44:21.420 One, it can't bounce back and forth between humans and animals. And two, you don't really spread it.

00:44:27.700 You're very unlikely to spread it if you're not symptomatic. You don't have to shut the world down,

00:44:33.540 but not only that, you get to isolate people when they're sick and treat them before they treat

00:44:38.660 others. So the virus really gave up two big potential superpowers. In the case of MERS,

00:44:44.260 sure, it lives in animals and it's never going to leave those animals, but it has such a poor

00:44:49.620 ability to spread between humans almost under any circumstance, unless you're probably sticking a

00:44:53.940 breathing tube in them, that it was just so easy to contain. If the story stopped there, you'd say

00:45:00.060 coronaviruses are just not a threat to us. Yeah. So I think some people in the field more than me said,

00:45:07.120 let's go look at coronaviruses in bats. And so what they did is they found other coronaviruses,

00:45:14.340 and it was actually for a scientific reason, a different one than just searching for the viruses.

00:45:18.860 We were trying to figure out where did the SARS coronavirus really begin? So people went and looked

00:45:23.760 at bat colonies throughout China, since that's where SARS began, and asked, can we find other bats,

00:45:32.000 other bat viruses that are more similar to SARS-CoV than the ones we know about right this minute?

00:45:37.120 Because we could isolate the virus in the wet markets in Guangzhou, but we didn't know where

00:45:42.600 they came from exactly, which kind of bats. And it was just a trick finding it in bats. And so,

00:45:48.700 but while doing that, people found other viruses that could, in theory, enter a human cell by using

00:45:55.540 the same kind of mechanism that SARS-CoV used to enter human cells. So there was some people who were

00:46:02.680 saying, there were a lot of people, some people in the field who were saying, well, we potentially have

00:46:07.120 more of a problem because there may be other ways to infect people, but there may be other viruses that

00:46:13.340 can infect people. And so I think there was a concern that this could happen again. And MERS is the same

00:46:19.080 thing. We haven't identified the exact precursor to MERS in bats, but there's clearly viruses that look

00:46:25.020 like the MERS coronavirus in bats. And so if they were able to use the human receptor and didn't take

00:46:30.800 too much adaptation to infect humans, then you can imagine the same thing occurring with MERS sometimes

00:46:36.420 in the future, occurring again with SARS-CoV-like viruses. So you're right, in 2015, we were thinking

00:46:43.080 these viruses really caused bad pneumonia, but it's going to be like influenza H5N1. It's going to have

00:46:49.540 very, very, very little human to human spread and mostly animal to human spread. Is there a necessary

00:46:56.880 relationship that says the viruses like MERS that are incredibly deadly if you get them,

00:47:05.340 just luck is on our side and they don't have much transmissibility, or is that simply luck so far

00:47:11.400 and there's no reason to suggest teleologically that that has to be the case? In other words,

00:47:16.480 you could imagine a scenario where you take something that has the transmissibility of

00:47:22.340 SARS-CoV-2, which we'll get to and explain why it is much more of a headache than SARS-CoV-1 or MERS.

00:47:28.760 If you take the transmissibility of that, which is both, and primarily is a factor of the fact that

00:47:33.580 it can spread before you're symptomatic, coupled with the actual pathology of MERS, which I want to

00:47:40.800 contrast with these viruses, I mean, that's a double whammy. You can really get into a dangerous

00:47:46.580 situation. Not that this hasn't been a disaster, but it could be a 5X disaster. Is there anything

00:47:53.480 that tells us that's unlikely because of this feature of the biology of the virus?

00:47:58.360 I don't think there's anything that's unlikely. I don't think there's anything about the feature of

00:48:03.880 the virus. I think about this as SARS-CoV-2 being a mixture of the common cold coronavirus

00:48:09.080 and then a mix of plus either SARS or MERS coronavirus in the lungs. So that's why you

00:48:15.320 have the transmissibility and the severe disease because it does both. But when you think about

00:48:19.720 other bad diseases, like even in the epidemic flu in 1918, that really did about the same thing.

00:48:25.920 It was very, very, very transmissible and it killed about a few percent of the people infected.

00:48:31.000 But if you infect everybody and you kill three percent or four percent, you're killing a lot 0.74

00:48:35.320 of people. So that's what this virus is doing also because it's transmissible so readily because it

00:48:42.160 behaves like a common cold coronavirus. That rate of lethality is not super high, but the denominator

00:48:49.040 is so huge that you have a lot of people dying from it. Is there something about the pathology of this

00:48:54.460 virus? How does it differ? I mean, when you think about SARS-1 and MERS, that let's just say

00:49:00.840 directionally those numbers are right in terms of the denominator wasn't bigger than we think and

00:49:05.280 you're killing basically one in 10 or one in three people infected. What did the virus actually do in

00:49:11.040 the lungs that would render people so helpless? Yeah, I think it's the same thing that SARS-CoV-2

00:49:16.780 does in the lungs. In those people who get severe disease, I think we don't really understand what's

00:49:21.900 going on. We think that there's lots of virus in the lungs and we think there's a very strong and

00:49:27.000 probably inappropriate immune response that's causing much of the damage that we see in lungs.

00:49:32.660 So it's a combination of those two features. That's why people are, from the beginning with

00:49:37.140 SARS, people are trying to figure out a way to both limit virus replication and also decrease the host

00:49:43.760 immune response so that you don't have this extra result of an exuberant immune response.

00:49:49.480 Do the other two viruses, SARS-1 and MERS, do they also gain entry through the ACE2 receptor or did

00:49:56.440 they use a different receptor to enter the pneumocyte? Well, SARS uses the same receptor. MERS uses a

00:50:03.340 different receptor. One thing that's really curious is SARS doesn't affect the upper airway to a

00:50:07.940 appreciable extent, even though it uses the same receptor. There's also one of the common cold

00:50:12.720 coronaviruses, NL63, uses ACE2, only affects the upper airway and doesn't affect the lungs than the

00:50:18.860 appreciable extent. And that could also account for the change in transmissibility because if you are

00:50:24.180 only infecting the lower airway, you're probably less transmissible than SARS-CoV-2, which can infect

00:50:30.980 both. Exactly. Exactly. That's why SARS was not so contagious because it only stayed in the deep

00:50:37.720 lungs until you went to the hospital and had that tube put down for breathing or some other procedure

00:50:42.900 done. So do you think that SARS-1 and MERS were so much more lethal than SARS-2 because they elicited

00:50:51.620 a greater immune response once they infected the lung or because they caused greater pneumocyte damage

00:50:58.040 when they infected the lung? I think that it's actually because they all cause the same amount

00:51:02.980 of damage or pretty similar, but you have this huge denominator in SARS-CoV-2 of people who have mild

00:51:08.240 disease. So I think that if one way to look at these numbers, and this is not a perfect calculation,

00:51:14.220 but if you have with SARS-CoV-2, MERS-CoV-2, there were a hundred people infected. They all get

00:51:19.540 some variability, some variation in pneumonia, and you have a certain mortality rate ranging from 10%

00:51:26.340 to 30%. SARS-CoV-2, of those hundred people, maybe 20 of them are going to get the lung disease. The other

00:51:33.880 18 are going to be asymptomatic, subclinical, have a cold, have something in the upper respiratory

00:51:38.900 tract. If you now take that 20% as your denominator and divide the 6% mortality that we're seeing,

00:51:46.820 the 5% mortality, I don't know what the number is exactly, but let's say 5% by 20%, you have a 25% 0.96

00:51:53.520 mortality, which is near to SARS-CoV-2.

00:51:56.360 So just let me make sure I understand that. Are you saying it's more the law of large numbers and we

00:52:01.340 have such a big denominator with SARS-CoV-2 that you're going to normalize more, or are you

00:52:06.080 comparing case fatality to case fatality, whereas I'm thinking of it as the IFR as opposed to the

00:52:12.480 CFR for SARS? Because I think the IFR of SARS-CoV-2 is very population dependent, but I think it's much

00:52:20.260 closer to 1% to 2% than the initial numbers that people feared of 5% to 10%, which would put it more

00:52:27.000 in the ballpark of SARS-CoV-2. That's the way I used to think about it when this first started.

00:52:32.280 In January and February, the mortality rate was 2.8%. And now if you look at anything official,

00:52:37.960 it's near to 5% to 6%. So what you say makes perfect sense, it should be near to 1% to 2%,

00:52:43.280 but it's been hard to prove that by all the official numbers. So what I was saying more is that if the

00:52:50.660 mortality rate in SARS and MERS, out of everybody who was sick, all had pneumonia. And of those

00:52:58.500 people, some number died. In SARS-CoV-2, if only one out of five people or less actually get pneumonia,

00:53:06.060 then the fraction that died, if you use that same fraction who died over that 20%, you basically are

00:53:13.240 multiplying your number by five. So if your number is 5%, then it goes up to 25%. If it's 3%,

00:53:19.040 goes up to 15%. So where we are exactly, I don't know, but it may be that the upper transmission is

00:53:25.680 the readily transmissibility of the virus is what's really making the number so huge and that everything

00:53:32.320 else it's doing is consistent with what SARS and MERS did if you confine yourself to just looking at the

00:53:37.800 lower respiratory tract disease. Now, this is something that might be a little bit outside of

00:53:42.780 what you've studied, but I'll ask anyway. One of the lingering questions, there are so many

00:53:47.620 that I have comes down to the survivors. I mean, obviously we think a lot about the mortality of

00:53:53.640 this, but if you take a person who gets infected and they're not asymptomatic, so we know that a lot

00:53:58.900 of people kind of don't even know they've got SARS-CoV-2 and the only reason you figure it out is

00:54:03.620 after the fact, serologic analysis tells us that they did. But there's a non-trivial amount of people

00:54:09.080 who get sick as hell and they get what they would describe as the worst cold of their life.

00:54:13.560 I have at least two friends I can think of in this situation who three months later can barely

00:54:19.940 run a nine minute mile again and they're slowly getting back in shape. When I did a quick check

00:54:25.660 on this, looking at the SARS-MERS patient follow-up data, I didn't find a heck of a lot that told me

00:54:32.140 about long-term lung function. Do you know much about this? And I would imagine that there's now

00:54:36.440 more of an interest to go back and assess that than there was three months ago when I tried to look

00:54:40.940 this up. Yeah. Even before this all occurred, I asked my friends in Saudi Arabia about follow-up

00:54:45.920 on the MERS patients. And I could never get information as to what exactly was going on.

00:54:51.200 I suspect that they had problems, whether they be forever or a few months is unclear, especially

00:54:58.420 since your friends were younger and fitter. If the MERS, particularly MERS, if it's mostly older

00:55:04.720 people, people with diabetes, people who have comorbidities, they may take them longer to get back

00:55:10.320 to baseline. It's probably not going to be running miles. I suspect it'll take a while to get back.

00:55:16.360 I don't know how much fibrosis was at the end of it all, how much permanent damage there was.

00:55:21.320 I suspect that there was a fair bit, but you always have it. You know, like in SARS, people

00:55:26.580 always talk about neurological disease without actually ever finding the virus in the brain.

00:55:31.820 And then it was attributed to being on ventilators and corticosteroids for long periods of time,

00:55:37.440 contributing to cognitive dysfunction. And occasionally the virus was in the brain.

00:55:42.580 So it's all a mix that's hard to really sort out what the major components are, because there's

00:55:48.040 several things that contribute to the outcomes. Well, based on your knowledge of coronaviruses and

00:55:53.640 your knowledge in particular, their impact on the brain, do you think that there are plausible

00:55:59.240 mechanisms by which, even for those who recover from SARS, there could be lasting neurologic impact

00:56:06.980 that is not the byproduct of hypoxia or vent head, pump head, any of the other more mechanical

00:56:14.840 or other physiologic accounts? In other words, do you believe that there is a plausible scenario by

00:56:19.380 which the virus could have residual neurologic value?

00:56:22.700 We can't find any evidence of the virus in the brain, but it seems less likely that it's

00:56:28.120 direct virus infection.

00:56:30.020 What about an immune response?

00:56:31.420 Yeah, that's what I was going to say. If you take a disease like Kawasaki's in children,

00:56:35.380 we know that that's a disease that is mediated by some sort of immune response. We don't know

00:56:40.920 if it seems here like COVID-19 is somehow provoking this response in this very, very small subset of

00:56:47.720 children. That certainly leads to consequences in the heart, long-term consequences, or it can.

00:56:54.060 So you can certainly imagine scenarios like that. How often this occurs and what's going on exactly,

00:56:59.860 I don't think we know.

00:57:01.340 So between the resolution, so to speak, of MERS and where we were, call it a year ago today,

00:57:08.660 Stanley, where was your head at with respect to the big one? Were you in the camp that said,

00:57:14.760 yeah, I've carved out a pretty nice niche here. I'm going to be studying coronaviruses forever.

00:57:19.180 Or was there a part of you that said, this is a threat to national security, to the world?

00:57:23.220 There's a pandemic brewing here. I mean, how did you think this could unfold?

00:57:27.140 I certainly wasn't smart enough to predict that there was going to be a pandemic.

00:57:30.340 As I said, some of my friends were worried about additional infections in humans. I don't know that

00:57:34.960 anyone would have predicted a pandemic like this one.

00:57:38.740 I want to pause you there for a second. Why? I mean, not that I did, but I want to push on that for a

00:57:43.780 moment. All the ingredients were there. I was going to say is the Department of Defense

00:57:48.120 in 2010 or 11 put out a report about possible emerging viruses as being really the major threat.

00:57:55.200 Coronaviruses were on that list.

00:57:57.020 And Bill Gates talked about this. I mean, it's become a very well-known

00:57:59.940 TED talk that is, it's painful to watch now because of how accurate it was. So you have,

00:58:05.960 you have these two examples of viruses that have enormous potential to cause harm,

00:58:10.940 but fortunately for us at the time, they just don't spread well. A few tweaks, i.e. infection

00:58:17.680 of the upper respiratory tract and a slower onset to symptoms would easily double your R-naught.

00:58:24.980 But okay, fair enough. I'll stop coming down on, I'm joking, of course, stop coming down on you guys

00:58:29.400 for not thinking this could happen. But so let's fast forward now to when did you first hear about

00:58:35.280 the outbreak in China? I mean, I'm assuming it was early December, late November?

00:58:38.480 No, I don't think it started quite that early. I would say late December. The first cases,

00:58:44.000 official cases were in December. We think there may have been some in November, but

00:58:47.240 I think that the people in China, scientists and doctors in China knew something was going on in

00:58:52.400 December. And then it was eventually reported very early January. So I think we knew a few weeks

00:58:57.980 early. But even then, we didn't really know how much human to human transmission there was.

00:59:03.180 Now, I have to say that at the time, given the number of cases, we should have guessed

00:59:06.620 that something unusual was going on. But to the SARS epidemic, we had these cases and lots of people

00:59:12.380 were infected. And we didn't really know how the spread was occurring. And at the time, by early

00:59:18.600 January or mid-January, we had 800 cases in the world. So it didn't seem to be extraordinarily

00:59:24.760 different from these other viruses. Maybe if we had had more information about what was going on

00:59:30.120 in Wuhan, we would have realized, aha, this is doing something that's different than what SARS and

00:59:35.220 MERS did. But we didn't have that information. When did it become clear to you personally that

00:59:42.460 this was going to be a much bigger problem than SARS and MERS ever were?

00:59:47.980 Funny you ask that, because I remember in December, when we really didn't know anything

00:59:51.400 about human to human transmission, I spoke to my friends in China. And I got off the phone and

00:59:55.920 told my wife, this is a big deal. So I'm not sure what I was basing that on, because it wasn't so

01:00:00.700 much evidence of human to human transmission. It was pretty clear to me then that this was going to

01:00:05.580 be a major problem. At that time, could you have predicted it would have been this big an issue?

01:00:11.580 I don't think so. Mostly because all the previous diseases had remained geographically confined.

01:00:18.960 So SARS was really a disease in China with a little spread around the world. MERS was really a disease

01:00:24.320 in the Arabian Peninsula with that one case in spreading, infecting several people in Korea.

01:00:30.800 But this one, you know, and maybe the dynamics of everything are so different. People spread travel

01:00:36.240 from Wuhan much more frequently because people have more money. So they fly more, they take the train

01:00:41.540 more. So that helped the spread a lot. And of course, this is transmissible. The other thing is that we had

01:00:47.180 gone through some of this with H5N1. So in the late 1990s, people were saying, all we need to do is have

01:00:52.520 this to be transmittable and it'd be a disaster because we don't really have good immune responses

01:00:57.220 to it. And it never happened. So yeah, what happened in 2009 with H5N1? Because the skeptics

01:01:04.100 would say, hey, we don't need to worry about this SARS-CoV-2. The last time we cried that the sky was

01:01:09.900 falling, it didn't fall. Right. So that was H1N1 in 2009. And that started off as a lethal disease

01:01:17.620 was identified in Mexico. It seemed to have a high lethality, but it's more cases became

01:01:22.520 clear, identified. It's clear that it didn't. It just was lots of cases and very little mortality.

01:01:28.460 It was basically influenza.

01:01:30.220 It was influenza. It was just a variant of influenza. It wasn't H5N1, which causes a severe pneumonia.

01:01:37.320 H5N1 is the 1919?

01:01:39.260 No, H5N1 is the one that's never made it to human populations to an appreciable extent.

01:01:45.480 Ah, pure swine. 1.00

01:01:47.940 Yeah, it's mostly pigs and birds, but it kills birds and most flu doesn't kill birds. So the

01:01:53.120 concern was that it would change to infect, to be transmissible human to human, but it never did.

01:01:59.900 So same thing with thinking about coronaviruses. They hadn't done this so far. We certainly thought

01:02:05.460 they could do it. But this is an interesting question is how do you prepare for a pandemic

01:02:11.180 that you don't have? Because it's something I've been asked about and thought about. So you're

01:02:17.220 sitting there in 2005 and SARS goes away. How do you decide what kind of resources you're going to put

01:02:23.600 developing antivirals, developing vaccines against SARS, a disease that doesn't exist anymore?

01:02:29.680 The way the American system is set up for this, if you have a good idea and you propose to the NIH,

01:02:35.700 you have a good chance of getting funding. But on the other hand, if you're competing against other

01:02:39.880 grants that make more compelling arguments for funding and deal with diseases that are actually

01:02:45.640 present, they're going to look better to a study section. So you have to figure out a way to identify

01:02:51.120 a disease that could be a problem without going overboard and using lots of resources for diseases

01:02:57.440 that never will be a problem.

01:02:59.540 I mean, it seems that you'd want to structure it in a way that says, look, there are some

01:03:03.080 no regret moves here for any viral infection. And then there are some things that are going to

01:03:10.300 be very specific. So for example, not that this is an NIH question, but what would a national stockpile

01:03:17.260 of PPE need to look like? What would an electronic infrastructure for contact tracing need to look like?

01:03:24.880 What would a national stash of reagents to develop serologic and PCR testing need to look like?

01:03:34.600 So we don't know what the gene sequence is, but the moment we know the gene sequence,

01:03:38.700 wouldn't it be great if we could hit go and actually deliver a million tests a day and not

01:03:46.100 talk about it for three months and not do it? Those strike me as just a no regret moves. You don't need

01:03:51.380 to know a single thing about what's coming other than it is infectious. It's the little stuff. It's

01:03:57.060 the nasal swabs. It's the reagents. It's all the stuff I just said. And about 20 other things I've

01:04:02.280 been thinking about that kind of, I really hope that when this is said and done, this doesn't get

01:04:06.880 forgotten because it's not a staggering investment. When you consider what we spend on healthcare and

01:04:12.620 defense, which are disproportionate to any other country by a log order and oftentimes by two log

01:04:18.580 orders per capita, you put a few billion dollars into this type of resource and you consider it

01:04:24.800 more vital than you would consider our national surplus of oil or other things. For example,

01:04:30.620 most people I would assume know this, but if not, we keep an enormous supply of oil on hand.

01:04:36.520 If the world shut down and we couldn't get a drop of oil from anyone in the world, we would at least

01:04:42.100 have, I don't know, I don't remember these stats, but probably a 60 to 90 day supply of complete

01:04:47.600 independence on oil, maybe more than that. And that's just a national defense imperative. So

01:04:52.320 this should easily be in that front. The other thing on the therapeutic side, I would say is

01:04:56.920 don't we already have enough evidence to suggest that at least one avenue to treatment is immune

01:05:03.900 modulating therapy. So maybe not antiviral because that can be quite specific, but all of these diseases

01:05:09.900 have an enormous component of an overactive immune response, which we'll discuss. And therefore having a

01:05:16.340 huge stockpile of immune modulating drugs to be appropriately dosed also strikes me as a no

01:05:23.020 brainer, right? Yeah. Yeah. No, you could argue that. I'm not sure that these diseases are all the

01:05:28.580 same in terms of the cytokine storm type activity, but they may be close enough so that your point is

01:05:35.480 well taken. They are similar enough so that that would be a reasonable thing to do is to have those on

01:05:41.720 hand. I think that's what Bill Gates was probably talking about more than specific drugs against

01:05:47.120 specific viruses, because you don't really know those so well. Think about it. So the whole stuff

01:05:52.500 with ventilators and all that, that was really poorly done. Testing, I think once we know, you're

01:05:58.720 right about nasopharyngeal swabs and mechanics of being able to do the testing, the actual identification

01:06:04.100 of targets for like RTP, PR are not that hard. I mean, that probably took four days to figure out.

01:06:10.900 But it took longer to scale up. I mean, I think that's the point, right? It's not no, I mean,

01:06:15.020 the virus was sequenced January 11th or 12th, wasn't it? Yeah. Yeah. Early in that, actually.

01:06:20.100 It's just scaling up the ability to do testing. So anybody who says, well, come on, it would be

01:06:25.700 crazy to have $3 billion invested in that on the off chance that the virus doesn't even make it out

01:06:31.440 of China, to which the answer would be, did you look at what happened to the US economy? It's called a

01:06:35.800 hedge. This is what sophisticated companies do. Sophisticated companies hedge their bets. And if

01:06:42.160 the answer is every time a really scary virus emerges in China, we have to spend $3 billion to

01:06:47.780 be ready for it to land here. But guess what? We don't have to shut our economy down as a result.

01:06:52.960 We can instead mitigate 90% of that damage. I mean, that's the wisest investment that could ever be

01:06:58.280 made. But I'll get off the soapbox now because nobody wants to hear me rant about that stuff. I want

01:07:02.740 to get back to kind of the interesting biology on this stuff. So let's now go back and talk about

01:07:08.160 these four viruses that cause us nothing more than nuisance when we get colds. Do they have any

01:07:14.200 seasonal variability to them, by the way? Are they winter viruses, summer viruses, or does it matter?

01:07:19.020 They tend to not be summer viruses and they tend to be more winter, early spring viruses.

01:07:23.960 What determines that, by the way? Is that simply a function of being close to each other in the winter

01:07:28.040 and spreading it? Or is it actually a property of the virus?

01:07:30.520 Yeah, we used to think it was that. But as we know more, I don't know the answer to that. I know

01:07:35.080 that some of these respiratory viruses are more active in the late fall, winter, and others in

01:07:40.660 the winter, early spring. And I don't know why there's a difference. I don't think anyone else

01:07:44.720 really knows either. We know these viruses are usually happier when it's a little cooler and a

01:07:48.860 little drier. But that wouldn't explain why one virus did well in November, another one did better in

01:07:54.280 March. Interesting. And then from an immune response, why is it that these viruses haven't

01:08:03.440 basically become irrelevant in the sense that we all eventually get them and we all develop immunity

01:08:08.860 and we're sort of done? That's really the question about all common cold viruses, whether

01:08:13.340 they be corona or otherwise. So why do you actually get reinfected? I don't think we understand it very

01:08:18.880 well. We know that there's an antibody response to these viruses. It seems to wane. It goes away.

01:08:24.400 We know that you need a specific kind of antibody, the IgA response, that seems to help. We don't have

01:08:30.060 that much information about IgA responses. They seem to wane as well. The T cell response is the other

01:08:35.920 part of the immune system that you mentioned earlier. We don't know that much about the T cell

01:08:40.720 response in common cold coronaviruses. Before all this began, we didn't think that was a big deal

01:08:46.040 because common colds usually go away in a few days before you actually have a T cell response.

01:08:51.420 So we don't know why virus immunity wanes. We know there's such huge differences. Smallpox you

01:08:58.260 can detect. And people had smallpox in 1918. In 1995, they still had antibody responses that were

01:09:04.540 measurable. Here we have these common cold coronaviruses. A year later, they've waned. And

01:09:09.840 a couple of years later, they're probably almost gone. So we don't really understand that. That's

01:09:14.800 really a key question. And it both impacts the ability to people to be reinfected by

01:09:20.180 SARS-CoV-2. It impacts the vaccine responses, impacts general herd immunity as we try to get

01:09:26.380 rid of this virus. So really important for not knowing. There probably hasn't been a case of a

01:09:31.880 coronavirus before where we've cared enough about herd immunity to talk about it. But do you mind

01:09:36.880 explaining to folks what you're talking about with herd immunity, specifically with respect to SARS-CoV-2

01:09:40.880 and what it means? Well, herd immunity is really the other side of what you were talking about,

01:09:45.760 the R0 factor. So if the herd immunity means if you have a virus that's extremely contagious,

01:09:52.420 for people who are susceptible to be protected from the infection, you have to have most of the people

01:09:58.460 around them be resistant to the virus. So to put this in a different context, if somebody who's

01:10:04.060 infected with whether it be SARS-CoV-2 or measles or anything else comes into a room,

01:10:08.860 and they're spreading virus, the virus is going to land in various places. Some of it will land on

01:10:14.460 the floor. Some of it might land on somebody's hands and could, in theory, infect that person.

01:10:20.480 But if that person is immune to the virus, it doesn't matter. The virus can land on that person's

01:10:25.880 hands and then that person can touch his face, but he won't get infected or he won't get diseased

01:10:30.580 anyway. But if that person is susceptible, then he will. So then if that person is susceptible,

01:10:36.280 he could then spread it to other people in this proverbial large room if they all stayed together

01:10:40.940 for several days. Now, if you take a situation where you have an extremely contagious virus,

01:10:46.300 so in that room of 100 people, I was saying before with measles, as five of them are susceptible,

01:10:51.780 the virus might spread to 25, 30 people from that one susceptible person. And then of that 5%,

01:10:57.900 maybe one or more of those people will become infected. If you have a virus like SARS-CoV-2,

01:11:03.920 which has a lower R0 factor, then at that same 100 people, if they're five are susceptible,

01:11:09.640 the odds are it will not get to the point of infecting one of those five people.

01:11:14.580 So herd immunity is that ratio, the fraction of people who are immune to a disease. For measles,

01:11:21.340 the number is said to be 95%. If you don't have that 95%, then measles can infect people who are

01:11:28.320 susceptible. For most common viruses, it's around 60 or 70%. So that's the number that people are

01:11:34.880 really looking at in terms of immunization or infection with SARS-CoV-2 to protect the general

01:11:41.480 population. It's not the same as being immunized or having the previous infection, you're still

01:11:46.680 susceptible. But it just means that it's much more likely the virus won't spread. And if you get sick,

01:11:52.100 it's unlikely you'll spread it to that 30% of the population that has never seen the virus.

01:11:57.720 So that's why it matters. Yeah. And there's a very non-linear but monotonic inverse relationship

01:12:04.920 between R0 and herd immunity, which I can't believe I actually just said all that. It's basically math

01:12:09.380 speak for the higher the R0, the higher the need for herd immunity, but the relationship gets there

01:12:18.200 non-linearly. I don't have a non-math way to say that, but the example you gave is a good one,

01:12:23.760 which is, and I said inverse, it's actually not inverse, it's direct. The R0 for measles is very

01:12:29.500 high and the herd immunity threshold is very high, 95%. Going down to an R0 of two to three,

01:12:37.100 you have a herd immunity threshold of 60 to 70%. Now, do you believe that based on everything we know

01:12:43.580 today, and that includes potentially there being many more asymptomatic people who are infected and

01:12:50.760 who have gotten over the infection than we previously believed, do you believe that the

01:12:54.780 threshold for herd immunity is still as high as 60 to 70% for SARS-CoV-2, or do you think that it

01:13:00.560 could be as low as 20 to 30%? Well, I think it's still going to be 60 to 70%. It's just that there's

01:13:06.540 a higher percentage of people who have immunity already. So in other words, you're saying, yeah,

01:13:12.200 it's becomes a bit of an academic or a moot point because it might be that of those 60 to 70% who

01:13:17.900 have to be infected for herd immunity, two thirds of them don't even know they were infected, but

01:13:21.620 they actually were from an immune. Okay. Fair, fair point. Yeah. So is there much genetic drift in

01:13:26.820 these viruses? The way, like influenza, I think most people know, hey, I got to get a flu shot every year,

01:13:30.980 but what they might not understand is the reason they're getting the flu shot is probably less

01:13:36.400 because their immune system forgets what influenza looked like and more because influenza looks different

01:13:41.300 every year. How much do these coronaviruses genetically drift to use the lingo?

01:13:47.000 So far, we haven't had evidence that this one drifts. I think when you look at the other viruses,

01:13:52.280 one of them seems to vary quite a bit. OC43 seems to have different variants. A lot of the others don't

01:13:58.000 seem to change that much. SARS was adapting to human populations, so it changed, but if it had stayed

01:14:04.500 around, I don't know that it would have changed much. MERS is clearly a camel virus. So any drift you see is 0.97

01:14:10.320 what happens in camels, not in people. Again, both for MERS and the human, the other coronaviruses is

01:14:16.020 not really, well, except for OC43, I don't think there's huge effects on immunity. This virus is

01:14:21.880 really, there's certainly lots of talk about changes in the virus and becoming more brilliant or more

01:14:27.300 weaker or more attenuated, but there's really no evidence so far that says this virus has changed in

01:14:33.140 a way that makes it unlikely a vaccine will work, unlikely that a previous infection won't protect

01:14:38.560 you from a second infection. There may be reasons why it won't, but it won't be because the virus is

01:14:43.800 changing so far. That's an important point. I think we want to kind of reiterate that, right? Which is

01:14:48.200 the doomsday scenario would be a virus that retains its virulence, but constantly drifts enough

01:14:54.480 genetically that your immune system never recognizes it again, but it retains all of its bad properties.

01:15:00.340 I mean, that's a disaster. If you had a new version of a deadly virus show up every year,

01:15:05.000 it could hurt you just as badly, but somehow its genetic drifting created a different coat

01:15:11.100 on it, a different set of antigens. And every year your immune system was caught off guard. That would

01:15:15.880 be very painful. And what you're saying is, hey, we don't have evidence of either of those things

01:15:19.940 happening, that it's genetically becoming more or frankly, less harmful of equal, if not more

01:15:25.560 importance, that it's not becoming a different immune animal as time goes on, at least in the

01:15:31.960 very short window we've studied it. But again, it's helpful to go back and look at these other

01:15:36.620 coronaviruses that you've studied because they've given us a lot of insight, right?

01:15:40.540 Yeah, exactly. The immunity, when you have a mild infection, just do not develop great immunity.

01:15:46.060 So let's double click on that. You've said already part of that. I want to make sure I understood it.

01:15:50.220 Part of it is the innate system, just for whatever reason, doesn't seem to do much. You've already

01:15:56.320 talked about how a lot of times with at least the common coronaviruses, they might not even stick

01:16:03.220 around long enough to develop a T cell response. Can you say a bit more about the adaptive humoral

01:16:09.480 system? What do we know about the IgM and IgG? Which again, if you haven't listened to the interview

01:16:16.500 and the discussion with David Watkins, I think this would be a great time to go back and make sure

01:16:20.540 you familiarize yourself with that so that we don't have to go into the details of what those

01:16:24.140 things mean. But six months after a person has a common coronavirus, do you still see evidence of

01:16:31.320 at least the IgG? Yes.

01:16:34.220 And do you know how often it is basically binding, non-binding? Do you have a sense of what the

01:16:41.300 functionality of that IgG is? Is it neutralizing fully necessarily?

01:16:45.720 Not necessarily. I think the human volunteer studies are best answers for that, for the

01:16:50.480 common cold coronaviruses. And they show that immunity is there, it's measured by neutralizing

01:16:55.260 antibody, and then it wanes with time. And that a year later, it's there and may not prevent shedding.

01:17:01.360 It's still, I think it sounds remarkably like what I think we're going to hear about with COVID-19

01:17:06.500 and immunity when people have mild infections or asymptomatic.

01:17:10.800 Now, we've talked about this paper that came out, God, I think it's been maybe three weeks ago.

01:17:16.020 Alex Setti was the senior author on it, 2020 cell paper that looked at 20 patients who recovered

01:17:23.300 from COVID-19. And I believe about two thirds of them actually had a CD8 T cell response and a CD4

01:17:32.840 response that kind of correlated with that. The point being, they looked to have been at least

01:17:38.000 partially aided in their response to SARS-CoV-2 from T cells that looked like they had been sensitized

01:17:45.060 by other coronaviruses. Now, this was a small study, and this was based on in vitro assays.

01:17:51.860 Can you explain that study a little bit, or at least the idea behind it? Because it's an incredibly

01:17:56.720 interesting idea, and it has clinical relevance if this turns out to be true.

01:18:00.400 Yeah, so I think this is one of actually several studies. This is the only published one, I think,

01:18:05.740 that shows that people who have never seen the virus have some sort of T cell response to SARS-CoV-2.

01:18:13.160 Now, there are some caveats when I read this paper that make me pause in drawing too strong a conclusion.

01:18:19.120 One is that in most of these papers, the way T cell responses are measured is not by functionality,

01:18:24.340 but rather by being activated in a certain way. And these activations, to my mind,

01:18:30.120 are a surrogate for actual functionality. And the functionality was not well demonstrated in any of

01:18:36.060 these studies. You may see a little functionality, but it's not the major point. Second thing is the

01:18:41.900 targets for these viruses, for the T cell response, is not the usual response that you get in terms of

01:18:47.760 targets. And you see after the wild type infection, the SARS-CoV-2 infection. And because of this

01:18:53.600 difference, it makes it also a little unclear to me where this response is coming from. So you can

01:18:58.560 say, okay, that doesn't matter. It's still from a common cold coronavirus. But then when people go

01:19:03.200 back and look at the sequence of the common cold coronaviruses for the same targets, there's actually

01:19:08.420 very little homology with T cell responses that are recognized in these patients who have never seen

01:19:15.300 SARS-CoV-2. So altogether, on one hand, you could say, well, maybe this is something that's important.

01:19:21.100 Maybe it contributes to protection, pathogenicity. On the other hand, it's a little odd because it's

01:19:27.800 mostly measured by activation, not necessarily by function. And that may matter. And it's also

01:19:33.520 targets are not totally clear how that's working. So maybe it's something that's not completely clear

01:19:39.120 yet. So I'm a bit confused by that, Stanley, because if we were doing this on the B cell side,

01:19:44.780 which is where we normally would, you would do an in vitro assay and demonstrate the presence of

01:19:52.120 neutralizing antibodies, not just binding, but neutralizing. And that would give us great

01:19:56.920 confidence that the B cell response would translate from the in vitro finding to the

01:20:02.380 in viva finding. Is that correct? I agree with you completely, yes.

01:20:06.240 So we can do comparable T cell assays where we actually look at killing function and not just

01:20:13.100 signaling functions and things like that, right? Yeah. And this isn't really signaling. This is

01:20:18.340 a protein, what was measured with proteins that come up if a cell has been activated at all.

01:20:25.560 So this is not killing assays, not even making cytokines, which are my preferred way of doing this

01:20:31.860 because it's easier. Yeah. So that's what I was going to say. Usually when you look at typical

01:20:35.860 studies that are looking at, say, response to flu vaccination, they look at cytokine response

01:20:40.520 on the T cell. So do you know if studies are looking to do that? Because that just seems to

01:20:46.260 be a very obvious thing to want to ask at this point. Well, for the people who are naive, who've

01:20:51.200 never seen the virus and who have these assays done, T cell responses are done, but they're,

01:20:55.600 they're very, very low levels of activity. So the amount of cytokine produced are extremely low

01:21:01.980 or non-existent. So you just wonder, part of the issues, we do some of these assays and

01:21:07.660 you can do it very well, but the level of the background, as it were, is approaching what

01:21:14.260 we're seeing in some of these patients. So I think jury's just out on how important it is and

01:21:19.620 what it means. To me, it's really interesting. It kind of doesn't go with what we used to see,

01:21:25.440 what we've seen in MERS patients, where we don't really see much of a background,

01:21:29.440 much evidence of cross-reactivity, but we didn't actually do the surrogate assays,

01:21:33.540 these assays for activation. And there may be a temporal component. In other words,

01:21:37.960 it could be that let's assume that on average, a person gets one year of quasi protection from a

01:21:44.980 given coronavirus until it can infect them again. You now have a hundred people who are in various

01:21:51.280 stages along a continuum of that recovery from pick your favorite endemic coronavirus. And then

01:21:58.400 they all at one day get infected with SARS-CoV-2. Well, presumably there's also a strength and a

01:22:04.160 decline of immune response. So even though they would all have some immune response lingering,

01:22:10.240 some memory of immune response to the benign coronavirus, they could technically mount very

01:22:15.720 different responses to the much more feared SARS-CoV-2 simply as a function of how far they are out

01:22:23.180 from their initial infection, correct? I think that's a different layer because it assumes that

01:22:27.160 there's something there. That's correct. If there's something there. Yes, absolutely. This

01:22:30.520 is a totally second layer. Do you think there are other viruses or other vaccines that could provide

01:22:36.560 cross-reactivity? I don't think provide cross-reactivity. There's of course these ideas that

01:22:42.120 you should immunize everybody with attenuated polio virus because that'll activate the immune system

01:22:47.520 and that'll give you some protection. You should do something like that BCG, which we use for

01:22:53.060 immunization against tuberculosis, whether they have any effect. People are suggesting this and I

01:22:58.200 think they're in trials even. But in terms of specificity of getting at the coronaviruses, I don't

01:23:03.520 think so. The BCG one's worth probably explaining a little bit to people because it got so much

01:23:08.400 attention. I think the other one that got quite a bit of attention was MMR. There's a very famous

01:23:12.960 graph that a friend of mine sent me that said, hey, the entire pandemic and the mortality profile,

01:23:20.780 which basically hockey sticks above 50 can be explained by exposure to MMR. People below 50

01:23:27.500 uniformly had MMR vaccination. People above 50, it's much more spotty. And the further you get from 50,

01:23:35.000 the less likely you were to have an MMR vaccine. And that explains it. Now I can go on why I don't

01:23:42.680 believe that's the case, but I'd rather hear your views on whether that is or is not likely.

01:23:46.240 I think it's actually contrary to what one might think because those of us who are over 50 had...

01:23:52.400 You actually got the real virus.

01:23:53.840 Yeah, the real and fell three of those infections. So I don't consider myself resistant. In fact,

01:23:58.840 almost everybody my age had all three of those viruses. Everybody certainly had measles and mumps.

01:24:04.820 German measles may have been less frequent.

01:24:07.640 But from an immunologic perspective, Stanley, is there any reason to believe

01:24:12.080 that your memory T cells and B cells to measles, mumps, and or rubella would offer you some

01:24:19.760 protection against this particular coronavirus? Is there any evidence that they offer protection

01:24:23.720 against other coronaviruses? No, I can say that. No one's looked very, very hard,

01:24:29.240 but there's no reason to think that it would. If there was anything like that, we would all have

01:24:33.780 some preexisting immunity to the virus that's way higher than what we're talking about.

01:24:38.660 I'll just tell you why I'm also quite skeptical of the BCG claim, which is not to say that in

01:24:44.620 certain cases, maybe there's an anecdote that it works. I mean, obviously one of the first examples

01:24:49.160 of cancer immunotherapy came out of an understanding of the Cooley's toxins that sort of came out of this

01:24:56.960 idea of BCG. But the reality of it is BCG has never shown enough specificity to be a viable

01:25:02.500 immunotherapy against cancer. And it's for that reason, I guess, even if that's overly simplistic,

01:25:07.360 that I really doubt that BCG could have a meaningful impact on a virus because it requires

01:25:13.120 just as much immune specificity as it does for the immune system to attack cancer.

01:25:18.260 Yeah. And there's other agents. So we've worked with agents that turn on interferon.

01:25:22.960 And I think if you give interferon at the wrong time in these infections, you may make people worse.

01:25:27.600 So if you were exposed to COVID-19 and you had a very good exposure right now,

01:25:31.960 and I gave you one of these agents that turn on interferon, that may well help you.

01:25:35.240 Because before you really get an infection, if we jazz up your immune system, that may help you

01:25:41.260 do better with the virus. Once it gets going, that probably isn't true. There's all these issues

01:25:46.800 that one could imagine that if you jazzed up the immune system with BCG, that it could help you if

01:25:52.580 you got it right the right day and then you were exposed to COVID-19. But I wouldn't want to be

01:25:57.320 inoculated with BCG just for fun with the possibility that in the next two days, I get exposed to the virus.

01:26:03.460 You provided a much more elegant description of how you might possibly benefit from it

01:26:09.180 in a Hail Mary, pure luck standpoint, but how mechanistically it just doesn't even make sense.

01:26:15.320 And you're right, by the way, I think the broader point I would take away from your comment is

01:26:18.760 there's a really interesting way to think about this from a targeted therapeutic standpoint.

01:26:23.120 When you think about the sophistication with which we try to treat other diseases with multiple

01:26:27.780 lines of defense, this is a great example of, one, going back to everything I said before about

01:26:34.140 when I was on my rant about how would you begin to prepare for the next time a pandemic comes back,

01:26:39.300 it's all that stuff. On the therapeutic side, I think it's being more thoughtful about

01:26:43.680 what the strategies are. The moment we identify those early cases and say, boy, this is a disease

01:26:49.600 that typically, like influenza, is a little bit more of an immune paralysis disease.

01:26:54.280 At least at one point here, you're seeing this hyperactivated immune sense. So early treatment

01:26:59.940 is antiviral with immune amplifier. Late treatment is immune modulator, antivirals long since gone,

01:27:06.760 and respiratory support starts to matter. You can start to really be more sophisticated in how you

01:27:10.860 think of these things. And I think that's probably something that people are starting to think about

01:27:15.020 now. And I suspect that a lot of the clinical trials now will focus on more partitioning. So we

01:27:20.040 don't just think of it as drug X, good or bad, drug Y, good or bad. We don't have this sort of

01:27:25.340 nonsense binary thinking. I agree with you completely because that's exactly the way I 0.95

01:27:30.100 think about this disease is that you need antiviral therapy early on and then maybe an immune modulator

01:27:36.720 later. And in terms of immune activator, if you just catch it just at the right time, maybe that

01:27:42.580 would help. I think it's actually going to be the same for severe flu, like the H5N1. I think the

01:27:47.600 same scenario applies. The other thing you point out is that with different patients in different

01:27:53.800 disease courses, one has to be ready to modulate therapy. And this is one of the things that I'd

01:28:00.220 love to have that we don't have, which are biomarkers for different stages of disease.

01:28:04.920 Well, I think for so many diseases, we know that something works well. And then we do large studies

01:28:11.100 and we find that, you know, it didn't work as well as we think. But if you go back, you say,

01:28:15.160 within this population, if we could have identified it first, that would be the people

01:28:20.360 who would have responded to this particular therapy. That's one of the reasons that some

01:28:25.740 therapies work that don't work that you might think would work. Because if 20% of people fall

01:28:31.300 in a category of benefiting from it, if you treat 100%, you dilute all the benefit.

01:28:36.640 Exactly. Exactly.

01:28:38.520 That's such an interesting idea. What do you think some of those biomarkers could look like?

01:28:42.560 There's some obvious ones. When a patient's in cytokine storm, you can measure the cytokines.

01:28:47.720 But if you could go deeper than that, and you could look at the proteome, and you could look

01:28:51.880 at metabolomics, or look at the gut, or something like, where do you think the answer could lie?

01:28:57.440 Okay. So there's two parts of the question. First one is, what would you sample? Because

01:29:01.160 the ideal person to be sampled is that person who comes in like your friend who had trouble running,

01:29:06.600 who didn't feel well. And I don't think he progressed to having disease enough to get him in the

01:29:11.720 hospital?

01:29:12.680 Nope. Yeah. Young, healthy guy in his maybe early 40s. And yeah, never hospitalized,

01:29:17.060 but sick as a dog for two weeks.

01:29:18.860 Right. So that's a person you'd like to do a test on and say, okay, is he going to progress or not?

01:29:23.940 Clearly, in his case, we'd want something to say, he's sick, but he's not going to progress because

01:29:28.440 he didn't progress. So that's a person who you might not want to do anything for. On the other

01:29:33.620 hand, he may look exactly like someone who has diabetes and 60 in terms of how poorly he felt.

01:29:39.200 And so what you'd want, you'd need a marker, not only for severity, but you wanted something that

01:29:43.720 would distinguish between the two of them and that you could sample easily in the blood because

01:29:47.620 your friend would not have wanted to undergo some sort of lung measurement because it would have

01:29:52.260 been way more invasive than the sickness he felt. So that's why you come back. I think you can come

01:29:58.280 back to things like cytokines and metabolic products. The problem up till now has been that you can see an

01:30:04.840 increase in cytokine X in people who are going to be sick and not increase in people who are going

01:30:09.820 to do better. But when you put them all together, it's not like you have populations that are very

01:30:15.380 high versus very low. You have ones that have a range of X to Y and the other one would have the

01:30:20.740 range of 0.75 X to 1.5 X. So you...

01:30:25.840 It seems to be a problem that is set up perfectly for some type of machine learning because everything

01:30:33.660 you said is correct. And then as you also alluded to, there's another layer here, which is we know

01:30:40.280 quite a bit about the epidemiology. All things equal, a 40-year-old without a single pre-existing

01:30:45.540 condition, you're going to weigh that input differently than a 60-year-old with no pre-existing

01:30:51.820 conditions or a 40-year-old with type 2 diabetes versus a 60-year... They all have a very different

01:30:57.360 physiologic age, even if their chronologic ages are similar. And so when you start to factor in

01:31:02.820 that, plus some of these signatures, plus the temporal nature of the signature, when am I getting

01:31:09.700 this? I think there is an amazing opportunity for information and data scientists to help prepare

01:31:16.860 us for how we will think about this when it happens the next time.

01:31:19.680 Yeah. And so what you need out of this is you need, as we've talked about for some of the projects

01:31:25.420 we've talked about, what you'd ideally like to do is you'd like to take people, sample them every

01:31:30.260 couple of days, see what their numbers look like, put them in this machine learning model that you're

01:31:36.120 talking about. And then if you had enough money so you can measure all these different cytokines,

01:31:40.700 you might say, okay, this person has this block of markers that say he's going to get sick,

01:31:45.600 whether it be the 40-year-old, because the 40-year-old can get sick, or whether it be an

01:31:49.780 older person. And you put the other point you make about the epidemiology on top of that,

01:31:55.440 and maybe you would not even bother testing the 40-year-old because the odds of his getting sicker

01:32:00.260 and meriting all the cost and use of resource is not worth it. We're not there yet in terms of

01:32:05.660 thinking about which markers are best. And also, how do you actually do this? How do you actually do a

01:32:11.520 study where you can help a person by getting serial testing and seeing which way he or she

01:32:16.260 is going in terms of disease? But that would be the ideal way, because that person, if you saw

01:32:21.200 signs of things going badly, maybe that's the person you'd use either remdesivir or hopefully

01:32:26.260 an oral form of remdesivir, stop the virus in its tracks, maybe give an immune activator. Again,

01:32:33.640 unclear, I think if you give an immune activator to some people, it'll be deleterious,

01:32:37.800 so it has to be done so carefully. There are two last topics I want to get to,

01:32:42.400 one being how we would study the durability of immune response, which is effectively the most

01:32:48.540 jugular question out there today. I mean, if we're going to think about this through the lens of

01:32:53.700 vaccination, and we're going to think about this through the lens of herd immunity, natural or

01:32:57.380 otherwise, we better figure out exactly what's going to happen to these people who get infected

01:33:01.960 and what superpowers they do or don't have in the future. Before I do that, though,

01:33:06.340 I want to go back to one thing we kind of alluded to very briefly, and then skipped ahead, which was

01:33:11.200 that paper that came out kind of recently. Matt Ridley is the journalist who wrote about it,

01:33:15.580 I think in the Wall Street Journal, but he refers to the paper by Zahn that came out, I think in

01:33:19.740 April, that argued basically, the virus may not have come from the wet market the way we think it does.

01:33:28.020 I know that we've been sending each other so many papers back and forth over the last few weeks.

01:33:31.720 Did you have a chance to look at that paper?

01:33:33.080 I think so. It's the one that says, there's a bunch of these, so I'm not sure I have the

01:33:38.480 Ridley one in mind. The one that says it was released accidentally from the Wuhan lab, or the one

01:33:44.420 that says it was- No, the one that said it was basically so genetically stable, it was really, it's

01:33:50.220 mostly a person-to-person transmission. So I think it basically said, look, this is mostly a person-to-person

01:33:55.380 transmission. And I think it said, if it came out of animals, it was so long ago that we don't know

01:34:01.080 about it. It basically argues that the narrative that this came from an animal source to a human

01:34:07.220 source in somewhere between October, November, December of last year is not correct. Had you seen this

01:34:12.320 paper?

01:34:13.020 No, I don't know that paper then.

01:34:14.640 Okay. All right. We won't dive into that too much.

01:34:17.280 The point is well taken that it is remarkably fit for humans. I don't know about the first part of the

01:34:23.020 conclusion, you know, that it came out earlier, but it is remarkably fit.

01:34:26.720 Yeah. I mean, I think they basically looked at the amount of genetic drift that occurred and said,

01:34:31.780 it's, I read it, I think four weeks ago. So I'm a little rusty on it, other than a few notes I took

01:34:36.580 that were somewhat cryptic. But I think the argument was, look, this has probably been in

01:34:39.760 humans longer than we think. I'll re-forward it to you after just for the purpose of pure interest.

01:34:45.080 So how do we figure out how long people are going to, because it might not be that interesting how much

01:34:50.200 immunity people have to regular common cold coronavirus, but it's going to be pretty darn interesting to know

01:34:55.220 how long people are going to have immunity to this virus. I mean, we've already at a minimum

01:34:59.940 seen close to 10 million people infected worldwide with this virus. Personally, I think that's a gross

01:35:07.320 underestimate of how many people have been affected. I think it's probably closer to 100 million people

01:35:13.380 have been infected. But regardless, the durability of their immune response has to be one of the most

01:35:20.900 important questions we understand. How would we do that? Yeah, so just doing the things we're doing.

01:35:26.480 People who are infected, measuring their antibody responses, if we can measuring their T cell responses.

01:35:31.980 The odds are that we're going to see waning immunity for people at mild disease. That's who we're

01:35:36.680 hearing over and over again. And that's what's been true for other coronavirus infections.

01:35:40.740 And what will the implication of that be? Will the implication then be that no matter how successful

01:35:45.800 a vaccine is, it's going to need to be an annual vaccine? There's two goals. One is to protect the

01:35:51.360 individual who's vaccinated from getting severe pneumonia. And that may actually occur already.

01:35:57.960 So that may be whether immunity wanes or not, that person may never get severe pneumonia. The other issue

01:36:03.900 which is equally important is how much immunity do you need to prevent shedding, to prevent

01:36:09.080 transmissibility to other people. And that's the one that I think is really unknown and to me is more

01:36:14.920 important. Not important to the individual, but to society. To me, that's the jugular question that

01:36:20.420 decides what do economies look like when we have subsequent waves of this? Because I did something

01:36:25.760 on Instagram a few weeks ago where I did a kind of Q&A with my son who's five. And he asked a very

01:36:31.640 honest question, which is when is this virus going to be gone? And it was an interesting discussion to

01:36:36.120 explain to him, actually, it's never going to be gone. This virus is never going away. There is

01:36:41.740 nothing about this virus that suggests it's ever going away. And so now the question is how do we

01:36:46.500 coexist with this virus? So even putting aside future pandemics, which could be much worse,

01:36:53.620 for example, an increase in the lethality while preserving the transmissibility of SARS-CoV-2

01:36:59.600 would be devastating. But just coping with this, if another one never shows up,

01:37:05.280 we have to understand this question, especially if the vaccines are somewhat risky. One thing that

01:37:11.740 doesn't get a lot of discussion is how much risk is going to be posed by vaccines. There's a reason

01:37:17.340 they never come up with RSV vaccines. It's a lot harder from a safe perspective to make an RSV

01:37:23.420 vaccine, unlike an influenza vaccine. So if everything is going to be a risk trade-off, right? And we're

01:37:29.400 going to decide you might not want to vaccinate everybody with a SARS-CoV-2 vaccine if the risk

01:37:35.320 is slightly higher than we deem acceptable. So then you have to do a cost benefit analysis. And then to

01:37:41.240 your point, which I think is even more important is, okay, what does the secondary shedding look like?

01:37:46.420 What do these other factors look like? It's hard for me to imagine a world that's fully functioning

01:37:51.340 without these questions resolved. Right. That's really the key question. The other hand,

01:37:55.980 though, if you get to a point where there's enough herd immunity or that a hundred million

01:38:00.740 turns into a six billion, people have seen the infection. So nobody gets pneumonia anymore. It

01:38:06.940 turns into a common cold. Then there may be enough of a balance between the virus mutating a little to

01:38:13.640 become a better common cold and no longer causing the pneumonia. But that's the point. It requires a

01:38:20.020 mutation, doesn't it, Stanley? Yeah, yeah, yeah. We don't have the memory like we do with measles

01:38:25.900 and polio and smallpox to truly generate herd immunity. In fact, we've never generated herd

01:38:30.760 immunity to influenza commonly. In that case, of course, it's because of the genetic drift. And so

01:38:35.520 isn't it a bit of a misnomer to suggest that we could ever have herd immunity to SARS-CoV-2,

01:38:42.060 let's just say, if we knew that the immune response was gone after a year?

01:38:45.880 The question is, what is the immune response being gone?

01:38:48.960 Yeah, a sufficient immune response. I mean, it becomes a sliding scale of efficacy, correct?

01:38:53.220 Yeah, yeah, yeah. That's right. But if you have enough immune response to protect you from

01:38:58.400 pneumonia, then the question is, how much shedding do you have? When we talk about studies, I was

01:39:04.780 thinking about this a little while ago. The simplest study would be to take some human volunteers,

01:39:10.340 give them a common cold coronavirus, and then a year later, come back and do the exact experiment

01:39:15.800 that was done in the 80s, measure, do they get a cold? If you reinfect them a year later,

01:39:20.760 do they get a cold? And how much shedding do they have? We know they shed, but if you are a 0.99

01:39:25.460 naive person with a cold, you shed 10 to the 8th, and now you shed 10 to the 3rd, and it doesn't

01:39:30.180 matter. Yeah, then it doesn't matter. Yeah. Well, and of course here, so again, I completely agree

01:39:34.960 with you that that's the single most important question. But the other thing is, I don't have

01:39:40.000 my fingers crossed that this is perfect because of that upper respiratory part of this. So you said,

01:39:44.520 well, what if you don't get the severe pneumonia before? Well, it turns out the severe pneumonia

01:39:48.700 that came with SARS-1 and MERS isn't really what was the problem. I mean, that was the problem for

01:39:53.960 the individual, but that was not the problem for society. The problem for society was the upper

01:39:58.260 respiratory part. That's what we're seeing in SARS, or the lack thereof. And that might be what's

01:40:03.600 making SARS-CoV-2 such a problem. Yeah, that's right. Anyway, Stanley, as you can tell, we can talk

01:40:09.020 about this for days, but I want to honor our commitment to get you out of here in a certain time.

01:40:13.780 So I look forward to talking with you again very soon as we continue to work on the project we're

01:40:18.140 working on with David and a group of other really amazing people. But thank you for your time and

01:40:23.660 your generosity of insight. Anything else, any last thoughts you have on either this particular

01:40:28.080 pandemic or just coronaviruses in general? No, I think the key thing we talked about is

01:40:32.860 how do you prevent this in the future? We're going to muddle our way through this one. We're going to do,

01:40:37.520 we'll get to points, I think, where we'll have antivirals, I hope. Vaccines, even with the

01:40:42.980 caveats that we talked about that should work. How long they'll work, I don't know. Whether people

01:40:47.880 actually agree to be vaccinated is another issue we didn't really talk about. And then for safety,

01:40:53.660 I mean, all these things we're going to know very quickly because we have to do it quickly.

01:40:58.060 Well, that means we're going to have to talk again.

01:41:00.220 Okay.

01:41:01.000 Thanks, Stanley.

01:41:02.220 Okay. Thanks, Peter.

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The Peter Attia Drive - June 29, 2020

#117 - Stanley Perlman, M.D., Ph.D.： Insights from a coronavirus expert on COVID-19

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