The Peter Attia Drive - #102 - Michael Osterholm, Ph.D.： COVID-19—Lessons learned, challenges ahead, and reasons for optimism and concern

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

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00:00:41.720 head over to peteratiyahmd.com forward slash subscribe. Now, without further delay,

00:00:47.740 here's today's episode. Welcome back to another special episode of the drive focusing on COVID-19.

00:00:55.580 My guest today is Dr. Michael Osterholm. You may have seen Michael on the Joe Rogan podcast a few

00:01:01.540 weeks ago. I saw him then and was immediately impressed, reached out to him and asked if he'd

00:01:06.040 like to come on our show, which he graciously agreed to. Michael is the director of the Center

00:01:11.480 for Infectious Disease Research and Policy at the University of Minnesota. He's also the author of

00:01:16.560 a book that in many ways foreshadowed this. The book is called Deadliest Enemy, Our War Against

00:01:21.800 Deadly Germs. And in that book in particular, he foreshadows a lot of what we're going through

00:01:26.620 today. Mike and I, in this discussion, talk about everything from our best understanding of

00:01:32.540 what's happening in the United States with respect to the spread and the slowing of the virus,

00:01:39.020 what he's optimistic about, what he's pessimistic about, what he thinks the end state looks like,

00:01:44.920 and what you'd have to believe is true if that is to be altered. We also get into the weeds a little

00:01:50.200 bit on some technical things around supply chain limitations with respect to drugs, with respect

00:01:56.200 to masks, with respect to vaccines. There are a number of things we discuss. And again, I think

00:02:00.960 just for the purpose of simplicity, rather than get into a laundry list of everything we talk about,

00:02:05.720 I think if you've got this far, you're probably interested in hearing it. So without further delay,

00:02:10.160 please enjoy my conversation with Dr. Michael Osterholm.

00:02:18.420 Mike, thank you so much for making time to sit down with us for some time today. And again,

00:02:24.000 I want to thank you because I just know that you are constantly being bombarded by requests. And

00:02:29.680 there's sort of a challenge you have to deal with, which is on the one hand, you want to be able to do

00:02:34.120 your job. But on the other hand, it's somewhat important for people like you doing your job to be

00:02:38.240 able to communicate with the rest of us, what you're seeing, and more importantly, what the

00:02:42.940 implications are and what can be done about it. Well, thank you very much, Peter. It's very good

00:02:46.980 to be with you. And I think that it's venues like yours that serve a very important role in getting

00:02:51.900 information out today. Far too much of what we deal with is in soundbites. It's in three-minute

00:02:57.180 segments. And I think that's really hard to convey the complexities and the overall short-term,

00:03:04.180 long-term view of what's happening here. So I'm really pleased to be with you. Thank you.

00:03:08.240 Well, yeah, you're in the right spot. We're not fans of soundbites here, so we'll get right to it

00:03:12.860 and we'll get deep. So let's start with kind of the 30,000-foot view, which is when we sit here

00:03:19.040 today recording this on March 30th, it feels like an eternity ago that you were on Joe Rogan's podcast

00:03:26.440 doing what I thought was just an excellent job of giving Joe and Joe's audience an overview of what

00:03:33.060 we knew at the time, what we didn't know at the time, what the concerns were. What do you feel

00:03:39.160 more optimistic about relative to that time, which has probably been three weeks? What do you feel less

00:03:44.800 optimistic about? Well, first of all, I think that it's important to understand, as Lewis Carroll once

00:03:52.020 said, if you don't know where you're going, any road will get you there. And I think that one of the

00:03:56.060 things that I've been very concerned about is we don't really know where we're going.

00:03:59.580 And that's not because the virus hasn't given us lots of clues. Just very briefly to take a step

00:04:05.900 back, just to remind everybody where we've been, we've been following this situation very closely

00:04:11.480 since the end of December last year. I have been very actively involved. I was involved with the

00:04:17.100 SARS investigation in 2003, very involved with MERS on the Arabian Peninsula, and have obviously done

00:04:24.360 a lot of work in influenza pandemic preparedness and planning. And so when this first happened,

00:04:29.860 and we saw these cases in Wuhan, it was really to us, oh my, here comes another SARS or MERS-like

00:04:36.280 experience, which actually, in retrospect, those were the easy ones because patients were not becoming

00:04:43.040 highly infectious till the fifth or sixth day of illness. You could identify them quickly, get them

00:04:47.660 into appropriate isolation so you didn't infect others, and we could follow up on their context.

00:04:53.940 But it became very clear to us by the second week of January, what was happening in Wuhan was not SARS

00:04:58.540 and MERS. This was acting much more like an influenza virus in terms of transmission, dynamic,

00:05:04.180 lots of spread very quickly. And so on January 20th, we actually put a document out saying that this was

00:05:10.520 going to be a worldwide pandemic, almost two months before the WHO did. We were convinced we would see

00:05:16.080 spread. On February 3rd, we put out an additional document that said it would probably take until

00:05:20.580 the end of February or early March before we would see cases around the world in any meaningful way,

00:05:26.020 because it just, the transmission of this virus was such that we had a sense even then probably had

00:05:32.340 an incubation period of about five days from infection until the onset of symptoms. And that if it had an

00:05:39.320 R-naught or the number of people that you transmit on an average basis to of about two to 2.4,

00:05:44.900 you go from one to two to four to eight to 16 to 32. And knowing that the cases in China were largely

00:05:52.380 about 80% were not seeking medical care, they were sick, but it wasn't sufficient. We said,

00:05:57.440 you know, it'll probably be the end of February. Well, sure enough, it was. We also put out a document

00:06:01.980 in mid-February saying that when it did start to show up, it would probably hit hotspots, metropolitan

00:06:06.540 areas, because of number one, that's where most of the transportation communication of people from

00:06:12.840 China to the rest of the world would be. Second of all, that's where the population density was high

00:06:18.000 enough so that you would actually see this amplification. Sure enough, as you know now,

00:06:23.060 that's exactly what we've seen. So having said that, it seems that we kind of know what's going

00:06:28.160 on here. And I'll say right now, we're all done with that. I don't know where this virus is going

00:06:32.920 to go next in terms of how long it'll be around. You can make assumptions of what we see with

00:06:38.500 influenza. I think some of those are helpful, but I don't think that they're necessarily definitive.

00:06:43.780 People talk about seasonality. I remind people all the time that we don't see that with the other

00:06:50.380 two coronaviruses. SARS was not seasonality just because it ended in June. It was in a situation where

00:06:56.760 we first understood we had a problem in February. It took us literally several months to figure out this

00:07:02.620 disinfectivity period, get people isolated, stop transmission, get palm civets out of the markets

00:07:08.700 of the Guangdong province, and then it ended it. If you look at MERS, and I've been there standing

00:07:14.180 outside of a hospital in Abu Dhabi when it was 110 degrees and transmission was going on just fine,

00:07:19.160 thank you. It was not at all being halted by the weather. And because, of course, camels are not going

00:07:24.700 to be put down as such, it just continues to transmit on the Arabian Peninsula year-round.

00:07:29.800 And our primary means of dealing with it is just making sure that people don't transmit in the

00:07:35.220 hospital setting. So if you take that, but also take influenza, because this is where people come

00:07:39.880 back on the seasonality piece, and they say, well, you know, it's probably going to be like influenza.

00:07:44.040 We forget that while influenza transmits seasonally in the winter of each northern and southern

00:07:49.800 hemispheres, it transmits year-round in the tropics. It never stops transmitting.

00:07:54.600 If you look at the last 10 influenza pandemics over the last 250 years, two started in the winter,

00:08:00.720 three started in the spring, two started in the summer, and three started in the fall.

00:08:04.660 And every one of them had their big peak six months after the original cases showed up. In 2009,

00:08:11.960 with H1N1, it showed up in mid to late March, and we had a big peak mid-September to mid-October.

00:08:18.840 North America was still warm. So I don't know what it's going to do going forward. But that's where,

00:08:23.880 when you ask me, good news, bad news, I have every reason to believe that it won't stop

00:08:29.480 transmitting in any meaningful way until we get 50 or 60 or 70 percent of the population infected,

00:08:36.020 which means that the bad news is that we are going to have to deal with those cases unless we can

00:08:42.940 suppress them. And we can talk about what the implications that are. If we suppress them, meaning

00:08:48.260 that we do what Wuhan did and the Chinese in Wuhan did of basically shutting down everything in the

00:08:54.660 most draconian manner we've ever seen in modern quarantine history, that means we're going to shut

00:08:59.780 down our country. We'll shut down the economy in any meaningful way. And not just about dollars and

00:09:05.240 cents. Who's going to pick up the garbage? Who's going to basically be firing police? Who's going to do

00:09:09.960 all the things that we count on? I'm pessimistic about the fact that we don't have an easy way out.

00:09:15.200 I like to say that right now we either suppress this and have this implication we talked about

00:09:21.160 and hope that we can suppress it long enough till we get a vaccine, which I don't think will be any

00:09:25.600 sooner than 18 months. Or we let it go willy-nilly and we will bring down healthcare systems. Many

00:09:31.680 thousands to millions of people will die and our healthcare systems will collapse. Or we try to

00:09:36.320 thread the rope through the needle and hit the middle. How do we find a way to have those people who

00:09:41.960 are at lowest risk of having serious disease problems who are at the highest risk of dying

00:09:47.240 be in our workforce, be more public, and handle the issues? So if we can do that, that's good news.

00:09:53.960 If we can't, the rest of it's pretty bad news. Mike, the numbers you just rattled off as sort

00:09:59.160 of potential projections, is that worldwide or was that a domestic figure? That's in the United States.

00:10:04.600 I mean, if you look at, you know, do the math and just a little over 300 million people,

00:10:09.560 if you're talking about 60% of those infected, you're talking 170 to 175 million people.

00:10:16.080 If you talk about 80% of those having relatively milder illness, now you're talking 20% that are

00:10:22.780 going to have some illness that will likely require hospitalization. If you then take that down to even

00:10:28.200 one or 2% of those who might die, you can just do the simple math and you realize we're talking about

00:10:33.820 millions. And that's what I don't think people understand yet, is that this virus is going to

00:10:38.660 keep going. It is very much like an influenza virus in that regard. It will go until it finds enough

00:10:44.500 immune people that shut it down, meaning they don't let transmission continue. And that's what

00:10:49.500 I don't think people are prepared to understand yet, is that they think that these waves are going

00:10:53.400 to happen over the next two to three weeks and then we're done. Just remind people that right now in

00:10:57.880 China, here we are, the end of March, this clearly was present in China in mid to late November.

00:11:06.640 And we're still seeing transmissions out in China, even with these draconian measures to

00:11:10.980 limit transmission. There are people in the Wuhan area who've not been out of their house in 15 weeks,

00:11:15.720 and yet we still see cases occurring. So this is going to happen here where it'll be months and

00:11:21.360 months potentially of transmission. And I hate the thought of the fact that one of the primary ways that

00:11:27.100 when you limit that transmission is just enough people get infected and develop immunity.

00:11:31.840 I might add one good news piece on the immunity piece. This is an important one.

00:11:35.640 I think we can say with more certainty that there probably is durable immunity, at least for the

00:11:41.380 short term. And what I mean by that is there was a study completed and published last week

00:11:46.020 using macaque monkeys, and they infected a group of them with the virus. They all came down with kind of

00:11:52.660 classic coronavirus-like illness. They then waited until they fully recovered. They re-challenged them

00:11:58.880 a month later, and all of them were protected against un-re-challenged. None of them got infected

00:12:03.100 again. And just to make sure I know what the re-challenge implied, were they PCR negative,

00:12:08.920 IgG positive, IgM negative?

00:12:11.000 Yes, they were. I can't say they're IgM negative. I'd have to go back and look at that.

00:12:15.800 But they were definitely IgG positive and PCR negative.

00:12:19.620 Yep. And so we have evidence clearly, and they didn't just do PCR, they did culture too.

00:12:24.680 So they actually were actually looking for the actual virus.

00:12:27.940 In other words, they weren't just looking for surface protein.

00:12:30.920 No, no, exactly. And so I think this study really gave us more hope that there really is

00:12:36.000 durable immunity, at least in the short term. I can't say it's going to be years and years.

00:12:39.760 I know that if you have short-term immunity, oftentimes that bodes well for a long-term

00:12:44.380 immunity picture. So that's actually an important positive step, that these are going to be people

00:12:49.540 who will be, as I call, kind of the human immunologic rods in the virus reaction. They

00:12:54.820 will slow it down. And today, they could be the people that could be out there in the world,

00:12:59.180 not worried about getting infected, and also would not infect others.

00:13:03.240 Yeah. I was having a discussion with one of the members of my team today,

00:13:06.580 and anyone who's ever worked with me knows I play this game called the What You Have

00:13:10.540 to Believe game, which is sort of a way to probe the limits of what biology could tell us.

00:13:17.740 So we got a little deep in the weeds on this, and I said, look, imagine for a moment two extreme

00:13:23.020 scenarios. Scenario one is this particular coronavirus, SARS-CoV-2, is a total nothing burger.

00:13:30.620 It's just another respiratory virus. It's getting a lot of attention right now. But the reality of it

00:13:37.300 is, when it all plays out and everybody gets infected, it's going to have a mortality that's

00:13:42.780 equal to or less than influenza, et cetera, et cetera. If that is true, how would you explain

00:13:48.200 the current data through that paradigm? And we walk through it. But at the other end of the spectrum,

00:13:52.540 I said, what if it's worse? What if it's the virus that could wipe our civilization off the map?

00:13:57.780 Again, I don't think either of these extremes are correct, but it became a good illustration of

00:14:03.000 what would have to be true? What do you have to believe if SARS-CoV-2 and COVID-19 will eradicate

00:14:09.860 our species? Well, you'd have to believe the following. One, there is no long-term immunity.

00:14:15.500 Two, each successive infection is worse than the previous one. And three, no effective treatments

00:14:22.640 will be developed. If those three things are true, this would be the virus that eradicates our species.

00:14:27.800 Fortunately, I don't believe any of those are true. And you're making a very compelling case

00:14:32.020 for at least the first of those not being true. And by the way, they would all have to be true

00:14:35.940 for the scenario I just described. So I take that as some good news.

00:14:39.700 I do want to ask, I mean, it literally just came out, I think, 20 minutes ago. Did you happen to see

00:14:43.840 that Lancet paper that came out going over the revised numbers in China in terms of case fatality?

00:14:51.180 I have not seen that one. I have seen a similar one, but help me, maybe it is the same one I've seen.

00:14:55.360 Well, so this one basically took the original case fatality rate of 1.38%, but followed it up and

00:15:02.900 added a whole bunch of more people to the denominator that were previously in the unconfirmed

00:15:08.220 bucket. So you took a bunch of people that were unconfirmed, you've now gone on to confirm them.

00:15:12.360 And the case fatality rate now looks to be 0.66%. Again, largely on the basis of not

00:15:20.680 subtracting mortality, but adding denominators. Does that surprise you? And what do you think

00:15:28.240 the CFR looks like if one could truly measure all the people that are in that category of having an

00:15:37.120 infection, but not being either clinically significant enough to warrant attention or

00:15:42.220 simply falling through the cracks due to socioeconomic factors, testing limitations,

00:15:46.380 et cetera? Yeah. Let me take two pieces of information and go at that. First one is you're

00:15:52.680 absolutely correct. It's a numerator denominator issue. Now, the challenge I think in adding to the

00:15:58.440 denominator is that you can add quite a bit to that and drive the overall case fatality rate or CFR

00:16:05.600 down. But what we're also missing is the number of people in the numerator. And our contacts in

00:16:12.800 Wuhan during that time period, who were pretty reliable, actually concluded in their assessment

00:16:19.420 that probably six to eight people were dying every day outside a hospital that were not being counted,

00:16:25.980 meaning that they were not being tested. And if you weren't tested, you weren't counted.

00:16:29.060 And so think about this. If you have a case fatality rate of 1%, 1 over 100, and you suddenly add 100 more

00:16:39.380 people to that, you now have a case fatality rate of 0.5 per 100, okay, half of what it was.

00:16:45.960 On the other hand, if you have that same 200, you added 100 more, doubled it, but you also add 10 more

00:16:53.720 people who died who weren't counted, only 10. Now you're looking at 11 over 200, and you're now at

00:17:00.500 5% plus. So the numerator is actually more sensitive in terms of impacting the rate than is the

00:17:07.000 denominator. And so one of the challenges that we've had is what is that overall numerator and how many

00:17:15.380 cases were missed? These have been well written up, these cases. So I don't know what it is, but let me

00:17:21.040 tell you what I think is important now. We've known this, I think, from early on in China,

00:17:27.100 that these comorbidities we talk about, these other underlying conditions play a very important

00:17:31.780 role. We've known about that with influenza for years, that comorbidities can affect you in several

00:17:37.380 ways. One, of course, is the occurrence of acute respiratory distress syndrome, or ARDS, and the

00:17:43.540 cytokine storm picture. In some cases, there appears to be kind of a myocarditis-type picture that can

00:17:49.240 occur. And of course, there's always secondary bacterial pneumonias, but I'm not even going to

00:17:52.980 count those in there because that, in a sense, is something we can often deal with with antibiotics.

00:17:58.720 But what happened in China was, is if you look at the overall case fatality rate by age, we saw this

00:18:05.740 exorbitant rate in those over age 65 who were male. Well, if you look closely in China, almost 70%

00:18:14.240 of men over age 65 smoked, and less than 2% of women over that same age group. So right there, you could

00:18:22.140 have an impact on that situation because smoking has always been associated with a worse outcome with

00:18:29.400 these kind of viruses. And ironically, the other risk factors, essential hypertension was also seen as a

00:18:35.420 risk factor for a bad outcome. But beyond that, there wasn't much else. Obesity, which has been highly

00:18:41.160 associated with bad outcomes, is actually quite rare in the older population of China. It's primarily

00:18:46.960 under age 30, where there are starting to see a real epidemic there. Well, okay, let's fast forward

00:18:52.400 to the United States. We are now getting data out of New York. We're seeing an increased number of

00:18:58.320 severe illnesses and deaths in people between the ages of 25 and 50. And almost to a T, the risk factor

00:19:06.440 appears to be obesity. 45% of our population over age 50 is considered moderate to severely obese today.

00:19:14.780 This, that one risk factor. On top of that, renal disease has been shown in the past to be associated

00:19:19.980 with bad outcomes. 700,000 Americans are living alive today with in-stage renal disease. And when you

00:19:26.760 start adding up all these comorbidities that we uniquely have, in part because of lifestyle or because

00:19:32.240 we happen to have a healthcare system that's able to keep us alive and with the right drugs and so

00:19:36.740 forth. So we don't really know when you put this virus here, what it's going to do. A good example of

00:19:44.640 that is the difference between Korea and Italy. Korea right now has actually just climbed over 1%. It had

00:19:52.720 been below that. And part of that was a function is the big outbreak that they initially had that they

00:19:59.620 worked up extensively in the thousands of people within this religious sect. The median age of that

00:20:05.340 group was 43. So, you know, right there, you had a younger population that surely would have had a

00:20:11.720 lower case fatality rate. You go to Italy, and right now about 80% of their cases are over age 80

00:20:17.460 with underlying health problems. And they have an 8% case fatality rate. So I think that one of the

00:20:23.560 things we're going to find with case fatality is going to be really country by country dependent.

00:20:27.960 It's going to matter where the virus is circulating and what age group. And it's going to matter in a

00:20:33.780 large part as to what the underlying health conditions are. In China, there's almost nothing

00:20:39.280 ever called a nursing home or long-term care facility. People are cared for in the home.

00:20:45.620 In the United States, right now, we're sitting in a powder keg of long-term care facilities for which

00:20:50.040 for years we've neglected them in terms of infection control. I can't tell you how many long-term care

00:20:55.440 facilities we have right here in Minnesota, they couldn't find one in N95 in their house if they

00:20:59.980 needed to. Not one, N95. I think that we actually stand the risk over the course of the next several

00:21:06.220 months of seeing it probably one of the highest case fatality rates in the world right here.

00:21:11.260 That's the first point of what I would say. The second part, though, you deal with this every day.

00:21:15.680 Every flu season, you are constantly confronted with this increased occurrence of illnesses,

00:21:21.560 et cetera. And even during the 2009 H1N1 situation, even in a bad H3N2 year in older people,

00:21:31.320 nobody, nobody reports what's happening, what's happening now in places like New York

00:21:35.200 and Detroit and Atlanta and Seattle. And so I think that what's happening here actually matches up with

00:21:45.420 the severity that we believe it really is occurring. I've come to the point in my old age that when

00:21:50.820 something walks like a duck, looks like a duck and quacks like a duck, I think it's probably a duck.

00:21:56.320 What would you put on the floor as the estimate for the CFR in a fully diluted sample? Do you think

00:22:03.620 that there's a scenario under which the CFR is 0.1%? Again, fully diluted, meaning you actually know all

00:22:09.400 the infected people. Or do you think that that's really just a pipe dream and the best case scenario

00:22:13.600 is closer to 0.4, 0.5? That's a pipe dream to me. And I think it's going to be in the

00:22:18.740 1 to 2.5 range. And I think that it's going to be heavily influenced by those who are over age 65,

00:22:27.320 70. And I think it's going to be influenced by the frequency of obesity in the younger age group in that

00:22:33.260 regard. Mike, I've never wanted someone to be wrong more than I want you to be wrong. Because

00:22:39.040 if the CFR is 1 to 2% in the United States, and you're right about the spread of this virus,

00:22:48.500 the implication of that is more Americans will die from disinfection in the next 12 months than

00:22:54.420 will die of all other causes combined. And I am absolutely on your side with this one. You will

00:23:01.000 get no argument from me. I hope I'm wrong. I would welcome that opportunity to be wrong.

00:23:05.620 I just look at what's happening right now. I look at indirect indicators. A good example right now,

00:23:12.680 today, the New York Police Department reported out over 900 police officers in New York are infected

00:23:19.300 right now. 13% of the workforce is out. They just had their third death today in police officers.

00:23:26.840 And when you start looking at that, and this is just getting started, when you start looking at that

00:23:32.100 and compare that to a bad flu season, which you and I have to deal with far too often,

00:23:37.160 with a vaccine on top of it, by the way. And we know what happens. Look at this one. This one

00:23:42.960 has that potential, I think, to be in the 1 to 2. I don't think this at all is going to be like 1918,

00:23:48.400 because that was so unique in how it took out 18 to 30-year-olds. This one's not doing that.

00:23:53.980 This is going to clearly be associated with age and underlying health issues. But in some ways,

00:23:59.300 we are a population that is highly vulnerable because of all the other lifestyle and health

00:24:06.740 conditions that occur in our group. So I think that that's where I'm very concerned about it and

00:24:12.180 would agree with you 100% on what you just said. Can I just say, on a given week in New York City,

00:24:17.820 in the past, 100 people die a day in New York. Right now, we're averaging close to 150 a day

00:24:26.780 just dying from COVID-19. Think about that. If we're going to play that what if game a moment ago,

00:24:34.600 what if this is something that is, quote unquote, only going to result in fewer than 100,000 lives

00:24:43.700 lost in the United States, which again, still seems for most people struggling to understand

00:24:48.920 what non-linearity means, we're a little over 2,000 deaths today. So even to propose that this

00:24:54.740 could be capped at 100,000, it seems very extreme. But I think you would agree that if only 100,000

00:25:02.060 Americans were to die before this thing was completely contained, you would consider that a victory.

00:25:07.420 Absolutely.

00:25:08.660 What has to be true for that to happen? What are the things that have to happen

00:25:13.500 scientifically, policy-wise, in terms of personal behavior responsibility? What are the suite of

00:25:19.920 things that must be true if that number is to stay below 100,000 in the next year?

00:25:25.440 I think two things. One is, we have to basically suppress transmission as much as we can,

00:25:32.100 which I don't think is doable. And I say that because it would mean a Wuhan-like shutdown.

00:25:38.740 And I just don't think as a country we can sustain that. I think even, and I don't want to equate

00:25:44.900 this in dollars and cents. I had an op-ed piece in the New York Times over the weekend, which I said,

00:25:50.400 this is not a choice between saving lives and costing the economy. We have to look at,

00:25:55.360 it's a combination of both. And we need people to carry on every day. I mean, I look at you. I mean,

00:26:00.440 I don't want anything to happen to you for a lot of reasons, but one of them is you're a very key

00:26:04.640 healthcare provider. You got to do your job. You can't shut down. We can't shut down. I mean,

00:26:09.780 when's the last time you saw anybody do remote work to pick up garbage? If you live in New York

00:26:14.320 City, guess what? Elevator operators, maintenance people are really important because if you can't

00:26:18.800 get up to the 40th floor, you shut down a part of the city that's really important. So I could go

00:26:23.720 through a laundry list of whether it's foods, you know, people who provide our food, et cetera.

00:26:27.600 So we've got to preserve that part of it. But at the same time, I worry that what's going to

00:26:32.980 happen is an acceleration of deaths due to the failing of the healthcare system. Right now,

00:26:38.420 keeping people alive on ventilators, having intensive care medicine does make a difference.

00:26:44.580 Not for every case, but it makes a difference. But once you go off the edge of the cliff,

00:26:49.120 where it's now no longer do you have a ventilator available, you have to wait for someone

00:26:53.820 to go off a vent and you have to make a choice to take them off. When you start running out of the

00:26:58.880 critical supplies, one of the things that we've been working on in our center for the last year

00:27:03.680 and a half has been looking at a very acute critical drug shortages, meaning these are drugs

00:27:09.800 you need right now or in the next several hours where people die. What's on the crash cart? What's

00:27:14.160 in the intensive care unit? What's in the ER? We came up with a list of 156 drugs, which we have

00:27:19.540 vetted with all the major medical groups, the intensivists, et cetera. Of these 156, all of them are

00:27:26.180 generic, all of them. Of those, almost 85% are made outside the United States. And of those,

00:27:33.780 many of them are made in China. We are just beginning to feel the severe supply chain collision

00:27:41.540 that's going to occur here in the next several weeks with increased number of cases of severe

00:27:46.300 disease and these drugs that we need. Because in China, the supply chains, which were still thin,

00:27:52.560 were filled just before this outbreak started. And there's about two to three months worth of

00:27:58.160 supply in the chain, but there was nothing that came in the backside of it. So we're just about

00:28:03.500 done. So if you add this on, Peter, this also then means now you got to deal with that situation on top

00:28:10.200 of it. And if our healthcare system can't take care of these people, or we have acute shortages of what

00:28:15.780 we need to provide the care we have been providing, then the case fatality rate is going to go way up.

00:28:22.280 It's going to go up. And that's, I think, a real challenge.

00:28:25.460 So just to be clear, you're not saying that we're going to run out of pick your favorite candidate

00:28:30.560 drug that I want to eventually talk about with you, remdesivir versus hydroxychloroquine,

00:28:35.760 et cetera. You're saying epinephrine, norepinephrine, vasopressin, paralytics,

00:28:42.300 the type of medicine we all take for granted that you need to run an ICU.

00:28:46.200 But even take something as simple as antibiotics. When you're sitting in an ICU for three and a half

00:28:51.240 weeks, the chance of developing a nosocomial infection as a result of being there-

00:28:55.160 It's pretty much guaranteed.

00:28:56.440 It's almost guaranteed. So if you don't have the antibiotics anymore, guess what? 85% of all of

00:29:01.260 our key antibiotics right now are made outside the United States. Ironically, you know the two areas

00:29:06.880 that have the most production capability? China and the Lombardi region of Italy.

00:29:12.300 Can you imagine that?

00:29:13.220 You couldn't make that up.

00:29:14.440 You couldn't make it up, but you couldn't. And so, I mean, there's something we're looking at.

00:29:18.080 So I think that, you know, the question is relative. If we had ideal intensive care availability,

00:29:23.980 we could maintain the system. We could take that kind of that spigot of cases and regulate them

00:29:30.940 enough so that they didn't overflow the healthcare system. They just appeared. I like to say if we have

00:29:36.760 100 cases of the disease today and they all hit the healthcare system, that's one outcome. What if

00:29:42.940 you have 100 and they hit the healthcare system 10 a week for 10 weeks? That's another outcome.

00:29:47.540 If we could do that, if we could thread that needle with our rope, then we'd be okay. But I don't think

00:29:52.900 we're going to be able to do that.

00:29:54.460 Do you think we have a pretty good handle on what it's going to take to protect healthcare workers? Do we

00:30:00.020 understand what amount of PPE is necessary first and foremost? And then secondly, of course, can we

00:30:07.520 meet that need? Can we meet the demand of that? Starting with the first question,

00:30:12.040 do we actually know what it takes to protect doctors, nurses, respiratory therapists, and

00:30:16.260 everybody who works in a hospital from the cafeteria to the parking garage?

00:30:19.880 Yeah. I think we know. I don't think we talk about it very well. And we have people who are in

00:30:25.000 denial about it. I've spent my career working on both coronaviruses and influenza.

00:30:30.020 I can tell you, we have absolute certainty today, no question about it, that influenza virus is in

00:30:35.620 part transmitted by aerosols. These are the smaller particles, smaller than five nanometer

00:30:40.720 particles. And people assume when we talk about airborne transmission, we're talking about something

00:30:45.560 that's many, many yards away. And they actually forget that aerosols are produced just where droplets

00:30:52.120 are, right in that first six feet area. And so if you're that close, if you have a surgical mask on,

00:30:57.880 you surely can do a lot to minimize the number of droplets you come in contact with. But that

00:31:02.900 doesn't take into account the aerosol. Where there's droplets, there's aerosols. Where there's

00:31:06.940 aerosols, there may not be droplets, but people have assumed it's droplets or then it's aerosols

00:31:11.380 somewhere else. And so I think from a respiratory protection standpoint, one of the challenges we had

00:31:16.120 in China with well close to 4,000 healthcare workers infected, right now in Italy, there's well over

00:31:22.440 5,600 healthcare workers who have been infected. Now, some of them obviously got infected off the

00:31:26.980 job, but many of them were on job. And respiratory protection was a key factor in each one. And so I

00:31:35.040 today feel incredibly incompetent, incapable, and frankly, sad that there are going to be many healthcare

00:31:42.980 workers who are going to risk their lives to help with this, who will not have N95 respirator,

00:31:48.900 which they need to have, because we just don't have enough. We won't. And when I keep hearing about

00:31:53.460 this additional production, the White House continues to talk about that. They never give

00:31:58.220 you the numbers of what we estimate we'll need versus what's being produced. And it's so far short,

00:32:04.420 it's not laughable because that would imply something funny. There's nothing funny about it.

00:32:08.840 But the bottom line message is that we're going to have a lot of healthcare workers who are going to be

00:32:13.440 exposed and infected with this virus because of that.

00:32:16.340 What is the number, Mike? What would we need?

00:32:18.820 I don't know. I think this is where, again, we have a PPE challenge here, particularly with N95s,

00:32:25.540 that was even much more severe than they had in China. Or to that extent, in Italy, they did

00:32:31.740 several unique things, which I don't know if we'll do here. You may have heard, but in several of the

00:32:36.600 really high volume wards in Milan, they had COVID-infected healthcare workers working. If they weren't that

00:32:45.020 sick, they were working. They went in without masks, et cetera, because they didn't have them.

00:32:50.040 And so I don't know what we'll do here, but I do believe we'll have a real challenge with this.

00:32:54.680 Now, some will say, well, and this is what I find very frustrating is we have to stick with the

00:33:00.280 science. And what happened was CDC, to their credit, about two weeks ago, issued new guidelines for the

00:33:07.180 use of PPE, respiratory protection. But what they said was, if you don't have N95s, then use masks.

00:33:15.380 But a number of administrators and some scientists have come forward and said, CDC changed their

00:33:20.560 recommendations saying you don't have to use respirators anymore. You can use masks, meaning

00:33:24.700 it's just droplet. That's not what they said. And so I think that today for a healthcare worker,

00:33:30.160 they just at least have to know what they're getting into. I think many of them will still go to work.

00:33:34.760 I mean, the camaraderie, and you know what it's like to be in that kind of setting.

00:33:39.600 These are some of the most amazing heroes in the world. We don't send our soldiers into war

00:33:45.260 without some kind of protective equipment or without bullets in their guns. We send healthcare

00:33:51.080 workers into this viral battle, and we're going to be sending them in without bullets or without

00:33:56.820 protective equipment. And that to me is really sad, but that's what it's going to have to take.

00:34:01.740 That's going to be a big question as to what happens there.

00:34:05.340 So really, we have a problem on multiple fronts. We have a problem on the supportive drug front.

00:34:10.620 We have a problem on the treatment drug front, which I want to come back to in a moment.

00:34:14.680 We have a problem on the people who are going to administer care. We potentially have a problem

00:34:20.980 on the number of ventilators and actual beds, et cetera. So is it a largely irrelevant academic

00:34:26.980 exercise to understand which of those things becomes the first failure because it varies so

00:34:32.520 much, presumably by city hospital geography, that it ought to be an all hands on deck for all of them?

00:34:38.040 I mean, is there a model here where we pick the 10 cities that are either in the throes of hell or

00:34:43.800 we know are about to be, and we start relocating healthcare workers to those areas if that's the

00:34:49.000 thing that we believe is going to be the bottleneck first? Of course, that would only make sense

00:34:52.580 if you could provide them with the necessary PPE. Otherwise, you're losing your soldiers

00:34:57.560 in battle unnecessarily without an appropriate risk to benefit trade-off. How do we think about

00:35:03.980 this? I mean, I haven't spent a lot of time truly thinking about this at the full macro level of what

00:35:09.520 the White House would hopefully be thinking about this. But I mean, what is the model? What can we

00:35:14.080 learn from the successes and failures of any other pandemic?

00:35:18.200 Well, first of all, let me just say you articulated it beautifully. You hit on every

00:35:23.380 major piece. Let me just give some kind of relevant information. I'll give you a sense.

00:35:28.640 Right now, the largest manufacturer in the United States of N95s is 3M. They can produce 35 million

00:35:37.180 N95s a month. They're trying to wrap that up to get maybe 5% to 7% more out of their machines,

00:35:42.900 okay? You just don't build these machines overnight. So even when you hear other companies talk about how

00:35:47.680 they're going to double or triple whatever production it is, be very skeptical because

00:35:52.500 these are machines that are really very, very sophisticated pieces of equipment. I mean,

00:35:58.380 for example, with an N95, most people don't realize that piece of white in front of you is not paper.

00:36:04.160 It's a matrix that was actually poured and dried. And it has a unique electrostatic charge on it,

00:36:09.940 et cetera, so you can get air through, but not virus. It's a very sophisticated thing.

00:36:13.820 Well, they've produced 35 million a month. They've been doing it since

00:36:17.680 late January, and we met with them and said, this is going to be a pandemic.

00:36:21.020 There's one hospital in New York alone, just one, that used 2 million N95s last month in that month,

00:36:27.600 2 million in their institution. Now, you start to do the math where we have basically about 35 million

00:36:35.460 of these in the strategic national stockpile. That's it. You start looking at the volume we'd need

00:36:42.420 of 400 million or more of these N95 just to get through the first couple of months. And you start

00:36:48.880 looking at the shortfall. That's where I have a problem is just, let's just be honest, okay?

00:36:53.900 I'm not trying to blame anybody. We're all to blame everybody. Why are we so ill-prepared?

00:36:59.060 But healthcare workers have to know. A statement I made earlier about one of the former defense

00:37:04.020 secretary said, when you go to war, you can't go to war with what you want. You have to go to war with

00:37:07.860 what you have. And so to understand how do we best protect healthcare workers, I think this is a key.

00:37:13.820 And let me give you an example. If we can't protect them because we don't have N95s, what are the other

00:37:19.720 things you can do? One is we should start forming wards, large wards, where basically we have 18 or 20

00:37:27.080 patients on one ward, and you never leave the contaminated zone. And at that point, rather than

00:37:33.580 often dawning outside every room and having to throw that away, what do you do? Second of all,

00:37:40.080 what can you do to reuse these? We're publishing an article this week on our website with 3M support,

00:37:46.240 and I mean, not financial, but their intellectual support of what are the techniques we can actually

00:37:51.180 use that will maintain the integrity of these N95s, but they can be reused so that we can decontaminate

00:37:57.620 them. We're working on that right now. Next is, what can we do to get infected healthcare workers

00:38:03.280 back? If I had to ask right now for one gift we could give healthcare workers is serology.

00:38:09.420 I'd like to test as many healthcare workers as I could for antibody and having the discussion we

00:38:14.520 just had on the ability to know that somebody's likely protected, then I would know also that

00:38:20.440 these are the people that are the safest to put back into harm's way. If we did a lot of things like

00:38:25.500 that, I think we could really mitigate the risk for healthcare workers. But what we can't do is just

00:38:30.460 administratively say, well, the CDC has made this recommendation, ignoring that there are things

00:38:36.700 we must do and can do. And you and I both know that this is a numerator denominator world we live

00:38:42.700 in when it gets to rates, but it's a numerator world when that person that dies is your colleague,

00:38:48.100 when that person is somebody who worked for you, when that person is somebody who day after day was

00:38:53.580 there with you, bedside, holding hands, doing the kind of skilled work, that is so tough on these

00:39:00.640 people. And so we also have to understand the mental health issues. And if we neglect that,

00:39:05.660 I mean, I already know healthcare workers who literally go home and cry all the way home to

00:39:09.880 work after they just finished another 14 hour shift. And I think that's another area that I've

00:39:15.020 not heard anybody really talking about much is this is just like battlefield trauma. We've got to start

00:39:20.400 helping them right now. If we're going to maintain three or four or five months worth of activity

00:39:24.340 here, we can't count on these people to do this day in and day out with more help. Protect them first,

00:39:30.480 support them second, and understand them and care about them third. And they all have to be part of

00:39:35.500 the picture. Mike, I want to go back to something you said a second ago with respect to testing.

00:39:40.860 Do we have a sense where we are now? I mean, it seems that we've done probably in the neighborhood

00:39:45.880 of 800,000 tests in the United States in total. I don't know the breakdown of how many of those are

00:39:51.000 PCR versus antibody, but does that sound about right to you? It does. Absolutely. Yes, it does. Yep.

00:39:56.620 Okay. So tell me the status of PCR. Is Roche providing the majority of these tests?

00:40:04.540 Yeah. I actually commented this also in my op-ed piece in the New York Times. Again, if there's an

00:40:10.100 operative set of words in this whole entire experience, it's supply chain, supply chain,

00:40:15.180 supply chains. Just like in real estate, it's location, location, location. We have changed our

00:40:22.400 world. In 2003, when SARS occurred, China was not a big player in manufacturing the world. Supply

00:40:27.440 chains weren't that critical to what happened in China. Well, it turns out today, supply chains are

00:40:32.960 everything, including for testing. And I'll add the perfect storm here. One, the world basically is

00:40:40.180 on fire. Everybody wants these reagents for whether it's PCR, whether it's antigen detection, whether

00:40:47.060 it's serology. Number two, guess where a lot of the reagents were being made? China. Number three,

00:40:53.720 now we bring those two together and we're encouraging people to even do more testing.

00:40:58.920 And you know what? Within a couple of weeks, we're going to actually see an implosion of testing. Right

00:41:04.060 now in Minnesota, we are so limited in our public health lab to test. If we don't have more

00:41:08.460 reagents in tomorrow, we're done. We can't test anymore. Commercial companies have been putting

00:41:12.640 together great packages to sell for testing. But what they haven't given you is how deep is their

00:41:19.180 inventory of resources for reagents. And they're not. It used to be we filled the reagent pool with

00:41:25.200 a garden hose. Then we realized we needed a fire hose and now we needed a damn water tunnel. And we're

00:41:32.420 not going to have it. So it's just at the time we need more testing. We're actually going to,

00:41:36.420 and I've seen these people get on talk shows and they sit there and say, oh, we'll just test our

00:41:40.600 way out of this. They don't have a clue about a supply chain issue. And so I think this is a huge

00:41:46.260 issue that you raise. And it's one that we're going to do less instead of more. And that seems

00:41:51.820 counterintuitive, but it's what's going to happen. So based on that, the idea that we should hope for

00:41:57.380 the best scenario where everybody gets PCR to detect and then antibody to follow. I mean,

00:42:03.440 that's a pipe dream. If we're going to be reagent limited instead, it's going to be a bit of a pick

00:42:09.060 your poison. And if you're lucky to get any test, if that's the setting, which it sounds like based

00:42:15.480 on the reagent shortfall, we're going to get to that place. What other methods can be used? For

00:42:22.300 example, could we rely on temperature changes? Can we rely on any other sort of biometric as a way

00:42:29.440 to take patients who are suspected positive, but not yet confirmed and enact policy around that?

00:42:37.660 This is where we're going to get creative. And this is ironically where things like 1918 are

00:42:42.700 instructive. We're back to the future, you might say. First of all, we want to know when the virus

00:42:50.420 is in our communities and when it's doing harm. And we have a system in this country called

00:42:55.660 influenza-like illness surveillance or syndromic surveillance. We have set up in a whole series of

00:43:00.840 randomly chosen physicians' offices around the country. And we survey it every week to every

00:43:08.160 several times a week during the flu season to give us an idea of, you know, if you have this

00:43:12.880 constellation of signs and symptoms, it's probably highly suggestive of flu and this is what's going

00:43:17.860 on. Well, it was very interesting in New York City, flu had started to wind down by early February to

00:43:25.440 mid-February and was actually coming down. All of a sudden in the end of February, boom, up goes the

00:43:31.640 number. And it goes and it goes and it goes long before anybody was test positive. And guess what?

00:43:37.540 It was COVID-19. We see the same thing here in Minneapolis. We just saw that thing go up about

00:43:42.660 two and a half weeks ago and it started going up again. So I feel confident that we can monitor

00:43:48.040 enough illness in the community this way and other means that we have that we can tell people it's

00:43:54.100 time to put the pedal to the metal. Okay, it's happening. We got to shut it down the best we can.

00:44:00.460 And so I think that's the kind of methods that public health is going to be reverting to.

00:44:04.820 But you raise a good point. What can I do for any one patient? And I think the only thing we have

00:44:09.880 going for is season-wise right now is if they are sick with an influenza-like illness, it's likely

00:44:16.240 not influenza because we don't see it circulating right now. And we can test for that and we haven't

00:44:20.800 seen it. So I think you have to assume that they're a COVID-infected patient and go with that.

00:44:26.400 But it's going to create challenges. I mean, one of the things we're concerned about right now

00:44:30.420 is in Minnesota, our priority is testing first sick individuals who are in the hospital. Are they

00:44:36.540 really infected or not? The second thing is to test healthcare workers who are sick,

00:44:41.020 whether they're in the hospital or not, because we want them to work or not.

00:44:44.380 And the third thing is testing workers in long-term care. That's all we have the ability to test for

00:44:50.400 right now because we don't have any other real agents. And I said that we may run out tomorrow.

00:44:54.480 So we're all going to be finding ourselves, I think, in different scenarios. And as much as we hear

00:44:58.960 this good news about the new point-of-care test coming out from Abbott and things like that,

00:45:03.460 we welcome all the tests. Just make sure you have reagents to go with them. And that's where

00:45:07.820 the challenge is. Yeah. So your fear is that this Abbott test could be technically a wonderful test,

00:45:12.980 but it might only be able to do a million tests in total before the supply chain falls apart.

00:45:18.620 Exactly. You nailed it. That's exactly it. And we have been talking to the companies at some length.

00:45:24.020 And remember, when Abbott says a million, they could tell me 10 million.

00:45:28.780 It's over what time period?

00:45:30.100 But it's over a whole world too. And that's the problem we have right now. You could not buy

00:45:35.700 a Roche PCR machine right now anywhere in the world. The Chinese went and bought them all up

00:45:40.800 14 weeks ago. You can't buy one in the United States. As soon as they saw what was happening,

00:45:45.600 they bought every machine they could. And so we're in a global market for these tests too.

00:45:50.920 And it's not just the US. And that's another reason why this is such a unique event is because

00:45:55.620 it is a global house on fire where everybody wants reagent water and the truck can only deliver so

00:46:02.100 much. Yeah. I mean, gee, I hate saying such stupid glib things, but I really feel like we're playing

00:46:09.120 chess, not checkers. I say this all the time. I say, we got to stop playing this. Like I play

00:46:14.420 checkers with my 10-year-old grandson, which I'm lucky if I beat him in one move down the board.

00:46:18.760 Yeah. Yeah. Yeah. It just seems like, I may have missaid it, but I think you know what I meant.

00:46:22.320 No, I know. You were right. You said it right. Yeah. We're playing checkers. We're playing one

00:46:26.080 move ahead. And the speed with which this is moving, again, to borrow from Wayne Gretzky,

00:46:32.920 right, we have to go where the puck is going, not where the puck is. And it seems like every time,

00:46:38.260 every step we take is going towards where the puck is. But in the case of a viral pandemic,

00:46:44.640 the puck moves faster than it moves in any other game. And you're really on your heels when you're just

00:46:50.740 going where the puck is, as opposed to anticipating where it's going.

00:46:54.560 And that's another really important point is, you know, we plan for catastrophes,

00:46:58.840 but we typically plan for a hurricane or an earthquake or a tsunami, one region,

00:47:04.880 and then we get into recovery right away. Not that it's not devastating, but you know, FEMA

00:47:09.580 can't be in all 50 states at once and do the magnificent job that we're seeing in New York.

00:47:15.280 And frankly, many of us fear that you don't want to be on the tail end of this outbreak where you

00:47:20.500 are one of the latter cities to break, because by that time, a lot of the resources are going to be

00:47:25.480 used. And even those that aren't going to be used up where they can be moved, like if additional

00:47:30.640 ventilators, if you can move them from place to place, it's still going to be a challenge because

00:47:35.200 you will have used so many of the critical things like drugs and so forth. And so where you place

00:47:40.300 yourself in this outbreak right now, as bad as New York is, they have the benefit of where at least

00:47:45.500 now, like Seattle, they got more resources than most other places will likely get.

00:47:50.240 Mike, I've spoken to many people about the situation around vaccines, including a number of people

00:47:57.200 sort of off the record who work in biotech companies. I've spoken with at least three CEOs of

00:48:03.420 biotech companies off the record. Without exception, no one has been able to give me a scenario under

00:48:10.740 which a vaccine is available inside of 12 months. Can you explain from your point of view why you

00:48:17.360 think that that's likely and why you're saying, look, we're not going to have a vaccine until 2021?

00:48:23.900 I always come back and clarify, I could make a vaccine tonight for this. I could, even with my

00:48:30.300 simplistic knowledge of this issue, but the question is, would it be safe and effective?

00:48:35.420 And that's what's key. So I think from an effectiveness standpoint, I do think we can

00:48:40.940 probably find something that will be effective even if temporarily, meaning it's not permanent

00:48:46.060 long-term protection, but something that might require boosters. We don't really know that yet.

00:48:51.200 The whole T cell, B cell combination of immunity with coronavirus is still a question.

00:48:56.140 I'm more optimistic about that. Where I think is going to hold us up a lot is safety. In the 2003

00:49:03.840 SARS vaccine work, there was some real challenges that developed with the animals with something

00:49:09.440 called antibody-dependent enhancement, ADE, where if you made just a little bit of antibody,

00:49:15.160 that was bad because then when you got infected with the real thing, you had this antibody-dependent

00:49:21.580 enhancement that was a shock-like picture and was a real challenge. And that's exactly what happened

00:49:26.160 with the dengue vaccine in the Philippines that got pulled two years ago, was that that vaccine

00:49:31.100 had an ADE component to it that nobody had appreciated. And because we have a history with this vaccine

00:49:37.900 with ADE, I think that no regulatory agency, at least in North America or EU, is going to license

00:49:46.480 that without substantial safety data. And if that occurs at, let's just say even one per 10 to one

00:49:53.060 per hundred thousand population, think how many people you have to study before you can actually

00:49:58.840 know, is there an increased risk or not? And if this was a really common side effect, three or four

00:50:05.260 or 5% got it, that would be a much easier situation to study. So I think that there will surely be pressure

00:50:11.820 to get it evaluated and licensed and made as soon as possible. But right now, I think the ADE thing is

00:50:19.800 one that's going to hang over its head and regulators are going to make certain that we have enough data

00:50:24.420 to at least begin to address it. What's the technical reason for that, Mike? Because that's not something

00:50:29.500 that we see with influenza, for example. No, we don't. In fact, it's more of a flavivirus type issue

00:50:35.260 and the coronavirus as we've seen it, where basically this whole immune system set up. I mean,

00:50:39.900 in a sense, it's somewhat like dengue hemorrhagic fever, where you've been infected with one strain

00:50:44.460 and then you have the second strain infection that has enough cross protection, but not sufficient

00:50:49.140 to fully protect you. And so it really is an immunologic phenomena. This is part of why hep C

00:50:55.580 vaccination has never really been successful as well. Isn't hep C also a flavivirus? Yeah, I think

00:51:01.400 that's also, but it's exactly one of the reasons why it's been a problem. So I think that's going to be

00:51:05.260 a challenge. But let me just say there's one other challenge that I think people haven't thought

00:51:08.920 about yet. And that is, again, the supply chain thing, where we just assume anybody can do anything

00:51:15.040 because we got something. Vaccines take manufacturing capacity. Right now, there is no big manufacturing

00:51:22.800 capacity sitting out there empty, waiting for some unknown virus to attack us and then cause for a need

00:51:30.220 for a major vaccine program. And so right now, the only players, there's one single one player in this

00:51:37.340 entire effort that even has the capacity to manufacture this in any meaningful way. All the

00:51:43.860 other ones are smaller startup companies that are bringing some good science to the table, but they

00:51:48.900 all are likely acquisition type issues, where if they got the product, they get bought by a big company

00:51:54.360 and move on. And relatively speaking, the big companies have not gotten involved.

00:51:59.000 And I think that we have to also look at how do you make enough of this vaccine for millions and

00:52:05.120 millions and millions of people? And how long would that take? I remind people that Ebola vaccine,

00:52:11.120 which was heavily funded by the defense industry in both the United States and Canada because of the

00:52:16.700 concern about a bioweapon use. And so therefore, when it came into the quote unquote Ebola battlefield

00:52:24.060 in 2015, a lot of work had been done on it already. And it still took almost four years to get that

00:52:31.440 thing licensed with the data that it had and the ability to provide manufacturing dynamics, et cetera.

00:52:38.360 So I think if we do everything we possibly can here and we can show it's effective, a relative sense

00:52:44.860 of safety, being able to find the manufacturing capacity, we're still talking 18 months, I think,

00:52:50.900 at the earliest. And that's not because people aren't going to be working 26 hours a day. It's

00:52:55.900 just, that's what it takes. Yeah. I mean, I think another just point to make that and drive it home

00:53:01.000 is just looking at Shingrix. When we came out with a much improved vaccine for shingles, I don't know

00:53:07.180 if you recall, but you couldn't get that vaccine for your patients over 50. I'm one of the high risk

00:53:12.480 people. I'm an old guy. I know that. Yeah. We had a really hard time getting that vaccine for our

00:53:18.540 patients. It took, many of them needed to wait six months to get it. And obviously it's a fraction

00:53:23.720 of the demand. So it's just worth sort of contemplating that. And, and I think the other

00:53:28.320 thing that, you know, I want to go from this vaccine discussion into the sort of the antivirals,

00:53:32.380 you know, I read a really interesting statistic the other day that I actually, I guess I knew it was

00:53:37.380 not great. I didn't know it was this bad, but it looked at sort of antiviral drug development from

00:53:42.480 about 1963 until present or thereabouts. It was a couple of years old, a little over,

00:53:49.280 oh, I don't know. I want to say in the neighborhood of 5,000 antiviral inhibitors were proposed in the

00:53:55.020 scientific literature, but only 90 of these nine zero were approved for final use over about a 55

00:54:02.200 to 60 year period. And by the way, of those 90, about 40 were for HIV. So again, I'm not minimizing.

00:54:09.480 Yeah. Yeah. So if you took HIV out of this, we're talking about maybe 50 drugs developed with any

00:54:16.400 efficacy and safety to warrant approval in a 55, 60 year period of time. What does that tell you?

00:54:22.720 Well, I'll tell you what it tells me is I hearken back to when I was in medical school and I went to

00:54:28.280 NIH to spend some time there and I was in an immunology lab. And I just remember a lecture one

00:54:34.220 day that left such an impression on me, which was, and this was immunology through the lens of cancer.

00:54:38.740 But the point was the T cell biology is so robust. T cells are so amazing at what they do that they

00:54:47.640 save us from all these viruses that otherwise we'd be hosed from as evidenced by how few we have in

00:54:55.000 terms of effective antiviral drugs. In other words, if not for the fact that we had a competent immune

00:55:00.500 system that could fight off most viruses, we'd be doomed because our hit rate of developing drugs to

00:55:06.720 stop viruses is actually pathetic compared to our ability to stop bacteria.

00:55:11.760 No, you're absolutely right. The good fortune, I think, is we are today in a better place in part

00:55:17.080 because of the research that HIV led us into and gave us a better sense of how to do research. But I

00:55:23.580 would absolutely agree with you. Anybody thinks this is a slam dunk, it's not. And I worry about the fact

00:55:30.160 that we've already made judgments to a certain degree about what works and doesn't work. I happen

00:55:35.180 to chair four different major work groups for WHO on what they call the R&D roadmaps for epidemic

00:55:42.580 diseases, Ebola, Laos and Nipa and Zika. Early on, Ebola vaccine was moving along fine. We were overseeing

00:55:50.100 that, but the therapeutics were still a question. And everybody had assumed ZMAP, a monoclonal antibody,

00:55:56.080 was the drug. If you didn't use ZMAP, it was almost unethical. Finally, in this most recent

00:56:02.040 outbreak in the DRC, a randomized control trial was set up and ZMAP didn't even finish in the top

00:56:08.280 five drugs. And it was one of those ones where when you realize, wow, we've been using this for

00:56:14.220 years with the assumption thereof, I hope that we have very effective drugs in this current regimen

00:56:21.280 approach with the COVID-19 disease, but I don't know that we do. And I think as you so well know,

00:56:27.740 we have two kinds of drugs. The Coroquine, for example, are immunologic modulators,

00:56:32.880 toll-like receptor modulators. Whereas if we have people dying from a myocarditis type picture,

00:56:40.420 well, that's a whole different situation. We may actually cause problem using Coroquine. So I think

00:56:46.100 that we just don't know yet. And I hope we have multiple fronts to deal with this, but the answers

00:56:52.400 are far from there yet. They're just far from being there. I want to come back to the antiviral

00:56:57.540 in a sec, but I want to pick up on a thread there, which is, this is now the second time you've

00:57:02.040 mentioned it. Basically, we're so early in this and we're still back on our heels. I feel like a boxer

00:57:08.240 who's been punched in the head so hard. I'm having a hard time thinking about counterpunching. All I'm

00:57:12.660 thinking about doing is not getting hit again. We haven't really done the analysis on the survivors

00:57:18.620 yet. We don't understand how much lingering myocarditis is out there. We don't understand

00:57:23.960 how much lingering kidney disease is out there. We don't understand how much lingering lung disease

00:57:29.620 remains in terms of fibrosis or permanent destruction of a subset of the pneumocytes. Is there anything that

00:57:36.660 you've learned from SARS and MERS about the survivors that we can take as a potential proxy for

00:57:45.520 long-term view on the health of the survivors? I can't say from a clinical standpoint, I know that.

00:57:52.780 SARS was a one in and out. There surely were over 7,000, some survivors, and how much subsequent morbidity

00:58:00.500 that they had with that, I can't tell you. The one thing I can tell you, which I think is another observation,

00:58:05.740 but hopefully a positive observation, is that having done all the work in the Middle East,

00:58:11.400 on the Arabian Peninsula, unlike with SARS, where once the palm civets were taken out of the market,

00:58:16.960 humans weren't getting pinged anymore with the virus. They stopped it. With MERS, those camels keep

00:58:22.960 transmitting and transmitting. And people who come from herds where they're close to those animals,

00:58:28.100 those are the same animals that infected them that they go back to. And it turns out that I'm not aware

00:58:33.340 of anyone since 2012, almost eight years, who have been infected, going back into a high, relatively high

00:58:43.380 infection rate in their own animals, have ever gotten reinfected. Again, the assumption that I think we have

00:58:49.420 to be careful about, does that mean they're really protected or not? But we haven't seen that again.

00:58:54.180 So that's probably the only takeaway I can come with, but it doesn't answer the very important question

00:58:59.500 you're asking, what is that residual? What's it all about? And even understanding for certain what

00:59:05.320 got us into this situation with underlying comorbidities. I mean, I'd like to understand

00:59:09.160 more, why do certain comorbidities actually predispose you to a bad outcome? What is it about

00:59:14.480 that? Yeah, I was going to ask you, what do you think, for example, in, I mean, type 2 diabetes makes

00:59:18.760 a bit more sense, but what about type 1 diabetes where there still seems to be an increased risk? And

00:59:22.860 that's especially concerning for young people. Exactly. I don't know that. And of course,

00:59:27.040 that's going to be overlaid with obesity. So then you're going to have both issues operating

00:59:32.000 at the same time. How much of that is compromised lung capacity? How much of it is actually the

00:59:38.020 diabetes? That's what's really unclear. What about immune compromise? What do we know about

00:59:42.980 immune suppressed patients? We've actually tried to get more information from the Chinese on that.

00:59:48.980 We've actually made formal requests for that information. And all we get back is saying is that

00:59:53.540 they didn't see any big increase in immune compromised people, whether they were surviving

00:59:58.780 cancer patients who may have been predisposed to an immune compromised condition, et cetera.

01:00:05.160 No one has reported out of the Chinese data. I've not seen it out of the data from Italy,

01:00:10.620 other than to say, what do you mean by immune compromised? You're over 80. What does that mean?

01:00:15.220 But from a clinical standpoint, not someone who would actually, we'd classify as immune compromised.

01:00:20.320 I've seen nothing on HIV AIDS, for example, nothing that suggests HIV status puts you at a higher risk

01:00:26.380 at all. Yeah. Again, this is yet another point on the list of things that differentiates this from

01:00:33.060 influenza. If we're looking for ways to contrast this, again, it's hyperimmunity, immune paralysis

01:00:39.920 versus not especially immunogenic to the same extent. I mean, there's just so many things that make

01:00:45.420 this different that as more and more time goes on, the more and more I feel we do ourselves a

01:00:49.420 disservice trying to compare these two. And it's understandable why we do, but it could potentially

01:00:54.300 mislead us if we continue to use influenza. Yeah. And you raise a very good point about,

01:00:59.280 I use influenza from a transmission model, but I don't think clinically you can. And one of the

01:01:03.080 areas we ran into that was with kids. When you look at kids today, there is pretty compelling

01:01:08.280 evidence now out of studies that were done in China that the kids do get infected at the same rate

01:01:12.720 that the adults do, but they just don't show clinical signs and symptoms, which is just the

01:01:17.780 opposite with influenza. Kids become little viral reactors in school. They transmit to everybody,

01:01:22.900 including their parents and their older sibs, and they're sick. And so there is an example of a

01:01:28.820 difference right there where what's happening with influenza in kids is not the same thing that's

01:01:33.900 happening with COVID-19 in kids. Mike, have you given any thought to the notion that you alluded to

01:01:40.180 at the outset that you estimated R-naught was somewhere between 2 and 2.4? We tend to talk about

01:01:46.160 R-naught as though it's a blended number between the symptomatic and the asymptomatic spreaders.

01:01:50.960 Is there any utility in trying to think of R-naught as separate and potentially assuming that the

01:01:55.900 symptomatic people might have a higher R-naught, although that doesn't necessarily have to be the

01:02:00.180 case? Again, you're asking a great epidemiologic question because we're having that debate right now

01:02:05.020 in a sense. You know, I've always said R-naught really didn't apply to MERS and SARS because these

01:02:10.520 super spreaders were so important. You could have 5 patients, 6 patients, 10 patients didn't transmit

01:02:16.960 to anybody even when people let their guard down and didn't do good infection control. And then

01:02:22.380 somebody could come in and wow. I was involved with helping the follow-up investigation at Samsung

01:02:27.740 Medical Center in Seoul in 2015 when an individual came back from the Middle East to Seoul and they

01:02:35.540 actually were infected. They went to hospital A. Another patient was in hospital A. That person

01:02:42.420 infected that other patient who then upon discharge went over to hospital B, i.e. Samsung Medical Center,

01:02:48.240 and transmitted in one afternoon in an emergency room, 60 some people. I mean, that was dynamic.

01:02:54.180 And just to be clear, this is a property of the host, not the virus because it's the same virus.

01:03:00.320 Exactly. You're right. Same virus. Same virus. Okay. And so to say that the R-naught in a situation

01:03:06.600 like that is kind of like saying your head's in the freezer, your feet are in the oven, but on average,

01:03:10.380 your temperature is just right. It doesn't make sense. So I've always challenged the R-naught because I

01:03:15.480 think that it was way, way, way out on the curve. In some cases, we saw lots of transmission.

01:03:21.060 Well, I think with this disease, we have a hybrid. In fact, there's a great article in today's LA Times,

01:03:26.900 I urge you to go look at it, highlighting a major event that happened at a choir in Seattle.

01:03:32.660 I saw it. If I recall, 60 people in the choir showed up to practice.

01:03:37.020 Yes.

01:03:37.240 45 have gone on to test positive. Two have died. They were, one was 80, one was 83,

01:03:43.560 three are in the hospital. So yes, there was something strange about that.

01:03:46.720 So, you know, we have these events like that. And I think that we've had more of those than we care

01:03:51.280 to realize. But on the other hand, we also have, I think, the regular transmission. And what was

01:03:56.260 really fascinating about that, Christian Drosin and his group in Munich have followed up on individuals

01:04:02.000 there who were part of this early outbreak associated with somebody who'd flown from Wuhan,

01:04:06.520 China to a car manufacturing location in Germany, was supposedly mildly ill, asymptomatic,

01:04:12.800 transmitted. Okay. Well, they followed up on a group of these contacts and they said, okay,

01:04:17.260 as soon as you get the first symptom, call us, which they did. And they have a series of patients

01:04:22.220 that they literally have blood, urine, feces, throat swabs, nasal swabs, et cetera, in the earliest

01:04:30.040 hours. And these people were just getting sick and they were getting progressively sick over time.

01:04:35.500 But what they found with the virus in the throat was fascinating. And this is on culture now,

01:04:39.660 but not just PCR. The virus level in the throats of these people were about a thousand times what

01:04:46.240 they see with SARS at its highest level. And this was right at the very first moments that they were

01:04:52.380 just showing clinical symptoms. And if you follow those cases, the virus level drops precipitously

01:04:58.280 over each day, day four or five, it's really much lower. Now, clearly before that, and their hypothesis

01:05:05.280 is that these virus levels may have been higher on day minus one, day minus two, but they weren't

01:05:09.960 coughing or they weren't sneezing. So you can say, well, they may not have been as infectious,

01:05:14.140 but to see that kind of virus level, just breathing, creating the aerosols. And people

01:05:18.720 want to understand an aerosol. I tell them there's two things to understand it by. Next time you're in

01:05:22.960 your house and sunlight is peering through a window and you see all that dust floating there and you

01:05:26.960 think, oh, my house is dusty. Those are aerosols. That's just from us talking. That's from us

01:05:30.760 breathing. That's what goes on in your house. The second thing is next time you're at a shopping

01:05:34.880 center, hopefully they open up and you are in a department store, you're three aisles,

01:05:39.740 four aisles away from the perfume section. You can still smell it. It's an aerosol. So I think that

01:05:44.920 breathing and just the talking would put that out there. So I think that rather than call it

01:05:50.220 asymptomatic, we kind of call this pre-symptomatic, meaning that they're going to get sick, but they may

01:05:55.980 be infectious beforehand. And this is not a surprise. We see this with influenza all the time.

01:06:00.780 Whether somebody is truly asymptomatic, never showing discernible signs or symptoms, I think

01:06:06.220 is a question that is, the data really come down harder and harder. In fact, I just reviewed a paper

01:06:12.020 for a major journal from the group in China that found a sizable number of people who are asymptomatic

01:06:17.920 never had reported symptoms where they had more than just PCR data. They actually had culture data

01:06:22.800 and they were pretty loaded too. So I think there is a role for these people. How much they're driving

01:06:27.740 the outbreak? I don't know. But I think we can't ignore that they have to be there. And I do believe

01:06:32.900 we have SARS-like super spreader events, just like the one we just talked about with the chorus.

01:06:39.540 But there's a lot of it that's just efficient transmission.

01:06:43.560 Did we learn anything about what characteristics those super spreaders had that made them super

01:06:49.380 spreaders such that we might be able to identify these people a priori and isolate them better?

01:06:54.340 No. That is, again, a million-dollar question. We haven't, even with all the years of looking at

01:07:00.780 what happens with MERS. And part of the reason is, with MERS, for example, it's not that the virus got

01:07:08.100 less effective in spreading. We just got more effective in early detection and getting these

01:07:13.000 people isolated. The first outbreaks, for example, in the Arabian Peninsula with MERS were largely in

01:07:18.300 dialysis units, where people who were in sick, they were in there for a while, and then classic

01:07:23.520 hospital-associated infections occurred where they transmitted to others. Once they figured that out,

01:07:29.340 and as you alluded to a moment ago, R-naught is a relative term. It refers to in the natural state

01:07:35.700 unaltered, this is who you'd transmit to. But if you have somebody that's just hotter than the devil,

01:07:40.440 but you put them in an isolation room, they should transmit to nobody. Technically,

01:07:43.800 their R-naught should drop to zero, even though if you had them out in the waiting room, their R-naught

01:07:49.080 might be dead. And so I think that's one of the issues with MERS. We can't even tell you for sure

01:07:54.340 because we've just gotten a lot better at making sure they don't transmit. And had these occurred

01:07:59.080 otherwise, like the one happened in Samsung Medical Center, I think we'd see more of these. So I don't

01:08:04.680 think we know yet, but it's a very important point that we do need to understand much better than we do

01:08:09.580 now. How is anyone to be able to model this out given all of these unknowns? So on the one hand,

01:08:16.880 I mean, I think we would all agree forecasting could be helpful because it would be great to know

01:08:21.820 some order of susceptible areas in the country, if not globally. We've talked about it now on a couple

01:08:28.660 of occasions here. We're going to have to allocate resources intelligently. We can't take an approach

01:08:34.220 that says it's going to be all hands on deck simultaneously everywhere because one, we don't

01:08:39.420 have the resources to do it. And two, it doesn't mirror what's going to happen. So it would really

01:08:43.980 be helpful to know that while New York is right now the epicenter of this in the United States,

01:08:48.700 these five cities are next in line. And therefore we should at a national level be ramping them up

01:08:54.740 such that at a local level, they're ready. But how do we do this? I mean, I think my fear is,

01:09:00.340 and we've internally been working on models. We continue to work on models. We're collaborating

01:09:05.240 with people, putting together models and they're beautiful and they're elegant, but ultimately

01:09:09.680 they're wrong. I mean, they just have to be wrong because we don't know the simplest things that the

01:09:15.980 models are very sensitive to such as are not. And I mean, that's by far the most important metric,

01:09:22.500 which of course the problem is it's a single number or a couple of numbers in a model that as you

01:09:29.220 point out is anything but a single number. The average, the example that is often used,

01:09:34.680 the average, you can drown in an average of three inches of water. So just as you can have your feet

01:09:40.600 in a freezer and your head in an oven and still be on average at the right temperature, it's very

01:09:45.680 complicated. And it's not just to say, we don't know what the distribution looks like. We don't know

01:09:50.340 what the probability distribution looks like of these things. So as someone who has studied these

01:09:55.820 things for such a long period of time, are you more or less optimistic that this exercise of

01:10:00.440 projection and modeling is a fool's errand or what do you think we should be doing here?

01:10:05.480 Well, first of all, let me just say, I'm not a modeler. I've had a lot of graduate hours of

01:10:09.760 statistics classes and I ascribe very much to the fact that all models are wrong. Some just provide

01:10:15.600 helpful information. And I've always said that. I've always been, I mean, I had to live through

01:10:21.840 the 2014-15 Ebola situation where WHO came out and modeled it and said, we're going to have 20,000

01:10:29.800 cases and CDC said it could be as high as a million. And it scared the hell out of everybody. And we had

01:10:35.320 to explain the next year why we didn't have a million cases. It was close to 20,000. And just

01:10:40.760 that error by itself created a lot of controversy because it made it look like we were trying to

01:10:45.540 really hype this. I think here, the points you're raising are exactly the ones that we've been

01:10:51.260 looking at carefully to say the variability around this feature is from zero to one. I mean, it's from

01:10:57.660 infinity. And so that one factor is kind of like A plus B plus C plus miracle and you get an answer.

01:11:04.520 And the miracle part just can't be there. Okay. And so I think that that is a challenge. On the other

01:11:09.440 hand, I would say you can theoretically say without knowing if it works like this, this is what will

01:11:15.500 happen. If you were able to suppress it in 85 or 90% of the transmission events, you can have this

01:11:21.400 happen. Or if you do this, you can have that happen. But it can't tell you that's what it's

01:11:26.460 going to be. It can just tell you within the framework of what might it look like. I think

01:11:31.620 you're exactly right. I have gone, my predictions, which I talked about earlier, and I surely don't

01:11:36.960 mean to sit here and sound woe, look at me, but we were right on with this thing all along, right to this

01:11:41.740 point, even to pick in hotspots. And now we can't, I can't tell you for certain what it's going to do

01:11:47.220 because it's beyond the scope of our experience. And we were just modeling the lot intellectually,

01:11:51.840 not statistically, on the flu transmission model, because it looked like that a lot. I think you're

01:11:57.460 asking exactly the right question. What intelligence would give us the information so that we could plan,

01:12:03.380 this is the next front. Two weeks from now, this is where we're going to need to be. This is how much

01:12:06.920 we're going to need to have. And we just don't have it, which is one of the other real shortcomings

01:12:11.500 of our ability to respond. Today, weather forecasters can tell you, you got 80% chance in

01:12:17.100 this region right here of having tornadoes today. I can tell you, I can paint the whole United States

01:12:21.420 and we have 100% chance of having a COVID-19 problem, but I can't tell you exactly much more

01:12:25.500 than that right now. Is there any evidence that this is a globally coordinated effort on intelligence

01:12:30.720 now? Or is everybody still kind of acting like the guy who just got punched in the nose, who's

01:12:37.200 still stinging from the pain and trying to not get hit again to worry about the person sitting in the

01:12:43.800 front row and whether they're drinking a Diet Coke or a Diet Pepsi? Many of us were incredibly

01:12:48.800 disappointed, for lack of a better word, on the WHO in its response. There was a sense that China is

01:12:56.080 going to contain it. The whole world can contain it. And I give great credit to China for what they

01:13:01.180 did, but they didn't contain it. They slowed it down. I surely give them that. But why did they

01:13:06.240 close down all their movie theaters last week again? Why did they remove all the outside reporters to

01:13:13.840 China two weeks ago? I think many of us think that they are in part experiencing some resurgence as

01:13:19.800 they're opening up their economy again, and they don't want anybody to know it. And I know that's a

01:13:23.820 strong statement, but I've talked to a number of people from Asia who would say they tell you the

01:13:28.040 same thing. So when you look at what WHO did, I think they set us back a great deal because they

01:13:33.480 made countries believe if just the few countries that were going to get this would just do the

01:13:37.960 containment work, we could stop it. And we couldn't. Trying to stop this kind of transmission,

01:13:42.680 like trying to stop the wind. And so we held back on a preparedness and gave people excuses not to do

01:13:48.660 it. Now, again, we don't have global leadership in terms of how do we coordinate this? How do the

01:13:54.480 low and middle income countries do with this versus the high income countries? Every country is fighting

01:13:59.900 for the same tools, the same tests, the same N95s. And we don't have a way to globally allocate those

01:14:09.120 in any kind of meaningful way. So the have and have nots are going to fight it out and the haves are going

01:14:14.800 to get more and the have nots are not. The only thing that ironically we have going for us, which

01:14:20.360 is in a sense, a sad commentary, there are a lot less at-risk people living in low-income countries

01:14:26.020 because they already died. And they're not able to be around 80 with long-term renal disease.

01:14:30.560 They died a long time ago. And that's a sad commentary, but in a sense, may do better on

01:14:35.660 case fatality rates overall than we do because they're not going to have that high risk.

01:14:40.180 Yeah. When you, again, this is not a statement of low-income countries. So, but looking in Europe

01:14:45.060 again, when you consider Italy, Spain looking very similar, and then Germany looking different,

01:14:50.120 do you think that the majority of that difference is explained by the underlying health of the

01:14:54.120 population? Do you think more of it is just stochastic bad luck where in Italy and Spain,

01:15:01.120 the regions that got hit first happen to have a greater center of older, more susceptible

01:15:06.480 individuals? Do you think it is an artifact of testing? I mean, how do you explain

01:15:10.000 what are your explanations for potentially those differences?

01:15:13.240 Yeah. I think it's totally artificial. And I think as demographics, if you look at what

01:15:18.560 happened in Italy, it started in the ski areas, but it quickly got into older populations.

01:15:24.120 If you look at Germany, a lot of that was introduced back in Germany from the Italian ski areas. And it

01:15:29.400 was in a younger crowd. If you look at where the illness is, I can tell you right now that it's

01:15:35.080 starting to change. And it's starting to see more transmission in Germany in older populations.

01:15:40.000 And when that happens, case fatality rates go up. It's just like in Korea. When Korea had this

01:15:45.100 predominant case mix of these younger individuals in this religious sect, case fatality rates were

01:15:50.840 one thing. Now look at what's happening in the older populations more involved. Case fatality rates

01:15:55.700 are going up substantially in Korea. I hate to say this, but every week is like a snapshot. It's not

01:16:01.340 the whole movie. And if we could play the whole movie out for the next two to three years,

01:16:05.320 I think there'll be a lot more similar kinds of pictures that will over time bear that out.

01:16:11.740 That where the risk factors were for comorbidity associated severe disease, we're going to see

01:16:16.840 higher case fatality rates. When you age adjust and when you adjust on risk factors,

01:16:22.920 I don't think there's a lot of difference here that we're going to see around the world.

01:16:27.500 Mike, I want to be sensitive to your time. And of course, I want to make sure that you'll agree to

01:16:31.000 come back and talk with us in a week, two weeks, something like that. Because as you said,

01:16:34.840 the rate at which this is changing, I mean, to talk again in two weeks would be

01:16:38.880 like talking over two years outside of the timeframe of an epidemic.

01:16:43.100 But the last question I want to ask you is, is there any of the sort of repurposed

01:16:49.040 drugs that are currently being thrown around in non-RCT manners that you have any optimism around?

01:16:55.900 I mean, as you probably saw the study that was published out of France on Saturday,

01:16:59.600 looking at hydrochloric. I mean, again, I thought the study was impossible to interpret because

01:17:05.360 without randomization, it looked promising, but you could argue that all those patients would have

01:17:10.720 done just fine without the drug. I mean, without a control group, it's very difficult. At the same

01:17:14.260 time, I don't want to be critical of that, that we have to do something in terms of studying this

01:17:18.180 and using case control cohort, if that's the best we can do, so be it. But you gave a great example

01:17:24.300 with Ebola, which said, look, you can be really deceived by these non-randomized trials,

01:17:30.060 and when you put them to the gold standard, they can fail miserably. If you're lucky, they just fail

01:17:36.060 in futility, not harm. Based on that, how much of your energy are you spending looking at the different

01:17:44.320 types of repurposed antivirals, everything from remdesivir to camostat to hydroxychloroquine?

01:17:50.300 Are you looking at these closely enough to comment on your optimism or pessimism?

01:17:55.100 I'm not because I'm not in that part of it. I'm doing much more on the optimiology

01:17:58.700 prevention side, but I think it's a critical question. I actually feel confident, though,

01:18:02.900 that the systems are being set up to actually collect the data in a meaningful way so that

01:18:07.800 we can have answers, and I think you nailed it. I mean, I actually read that same study you're

01:18:11.940 talking about, and I had the exact same conclusions you did. So I think we just have to, as Godspeed,

01:18:17.800 do these as fast as possible, but we have to keep an open mind and let the data take us wherever

01:18:23.320 it's going to and do them. So in that regard, hopefully I can come back in a couple of weeks

01:18:27.640 and we can have more information. I do believe we're going to have much more information on

01:18:31.440 therapies much sooner than vaccines, and that could be a really important response.

01:18:37.560 So I know I said that was my last question. I guess I want to give you one last thing to say.

01:18:41.060 There's people that are going to be listening to this less than 24 hours after we've recorded it,

01:18:45.080 so consider it as current as possible. What's the message you want to deliver to people listening

01:18:49.840 to this who are afraid, who are not afraid? Just assume you're talking to a heterogeneous mix

01:18:55.820 of people. What do you want to communicate to them as far as what steps they should be taking

01:19:00.420 to protect themselves and the people they care about? Well, number one, we throw around a lot

01:19:05.020 of numbers, and we have to never forget these are all people. They're our loved ones. This is real,

01:19:09.880 and more people are going to know somebody in the next couple of weeks that are going to be

01:19:12.920 seriously ill or die. The second thing is I would just say that we're going to get through this. We

01:19:17.860 are going to get through it. The question is, how do we do it? And that's where I think some of us

01:19:22.220 are trying to get the kinds of approaches in place that have a better chance of getting us through

01:19:26.860 than not. I appreciate it. You were wonderful. I would be happy to do this with you again.

01:19:32.000 You're great at it. You're really good at it. I appreciate that, Mike, and we'll get back to you

01:19:35.820 soon. Thank you so much. Bye for now. Bye.

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The Peter Attia Drive - March 31, 2020

#102 - Michael Osterholm, Ph.D.： COVID-19—Lessons learned, challenges ahead, and reasons for optimism and concern

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