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“Jay Bhattacharya on Health Economics and Coronavirus” (Two Think Minimum)

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Scott:

Hello and welcome to the Technology Policy Institute’s podcast: Two Think Minimum. Today is July 23rd, 2020, and I’m Scott Wallsten, president and senior fellow at TPI here with my cohost, TPI Senior Fellow and President Emeritus, Tom Lenard. Today, we’re excited to be talking with Jay Bhattacharya. Jay is a professor of medicine at Stanford university. He is a research associate at the National Bureau of Economics Research, a Senior Fellow at the Stanford Institute for Economic Policy Research and at the Stanford Freeman Spogli Institute. He holds courtesy appointments as professor in economics and in health research and policy. He directs the Stanford Center on the Demography of Health and Aging. Dr. Bhattacharya’s research focuses on the economics of healthcare around the world with a particular emphasis on the health and wellbeing of vulnerable populations. His peer reviewed research has been published in economic, statistics, legal, medical, public health, and health policy journals. He holds an MD and PhD in economics from Stanford University. Jay, thanks for being with us.

Jay:

My pleasure, Scott, thanks for inviting me.

Scott:

I should also note, I think we overlapped at Stanford doing our degrees. And so while I was struggling to do my PhD, you were making all the rest of us look bad by doing an MD and a PhD. So never was a slacker by comparison.

Jay:

Yeah, it took me longer to finish than you Scott.

Scott:

So you’ve been doing a lot of work on COVID, obviously, that being the crisis everyone’s, we’re facing now, but why don’t we start off maybe talking a little bit about baseball, cause it finally resumed this week and it was one thing that seemed to be making some people happy aside from there being no fans in the stadium, but you did some work with major league baseball early on, not well somewhere, you know, a couple of months ago on infection rates and transmission, you know, tell us a little bit about that study and what you learned and how you think it applies now to they’re starting back at the season. 

Jay:

Sure. So the study was on, was an antibody prevalence study in Major League Baseball. The idea was to measure what fraction of the employee population, employee Major League Baseball, not, we didn’t actually have that many athletes that are participating in the study. What fraction showed evidence of antibody response to having had a COVID infection? What we found was that about 0.7% of that population had some antibody evidence. And in many cases that was lower than what we’ve now seen for seroprevalence studies that were that have been done in the same community. It’s interesting. So I like, I think it has, that study has more public health implications than it does for the opening of Major League Baseball. So first, I think 0.7 sounds like a small number. It is a small number. It’s suggested that in mid-April or like third week of April, when we did the study that the epidemic hadn’t really gone very far along, like a relatively small fraction of the population had been infected with it. In places where there were overlapping community seroprevalence studies an employee population had lower prevalence.

Jay:

So for instance, in the San Francisco Bay Area, I think one of the teams had zero prevalence and in New York it was, you know, a fraction of the seroprevalence estimates. So that also points to an interesting fact, which is that this is a, you would think this disease doesn’t respect class boundaries, but in fact it does. Richer people, people that have stable jobs that can work from home, which is true for much of MLB population and for me too, of course, you can, you get much lower rates of COVID, exposed less than poorer people who have to basically have to, they still have to work, they still have to go out in public and get exposed. So I think that second lesson is an important one for thinking about COVID policy. A third lesson I drew from this is that there was a very substantial fraction of the people who tested positive with antibody evidence that reported no symptoms in the previous two weeks or two months.

Jay:

None, zero symptoms whatsoever. And this confirms what a lot of other antibody studies have been finding, which is that there are a large number of people who have been exposed, got the disease, got better and had zero or minimal symptoms and they don’t get tested because they don’t even know that they’re sick, or sick enough to warrant getting tested.

Tom:

Is part of the reason for that, that the, the antibody tests don’t, I mean there are several variants of COVID. Of the 0.7%, I mean many of them may have had not the one we’re concerned about right now, is that correct?

Jay:

So this, the antibody tests, the antibody specifically we were testing for is common to all of the variants of COVID that make people sick. So there’s a protein on the that’s coated by the RNA virus, called the spike protein and the spike protein has a region that binds to the receptor that allows the COVID virus into your cells.

Jay:

And so that’s the one we’re testing for. Every single COVID variant that makes you sick has that variant. Now, but there is something for sure in what you say, because there’s increasing evidence that there are other antibody responses to COVID that are not specific to COVID. Right. So if you like, there’s some evidence that just came out today and in a preprint bi-archive, for instance, suggesting that if you’ve had other coronaviruses non-COVID coronaviruses because, you know, Coronavirus is just is a common cold virus before COVID, that might offer some protection. And so there’s this, that explains partly why kids seem to be less affected by it, cause they’re readers of these colds as any parent can tell you that has had little kids. But I mean, so I think in a sense we underestimated the prevalence because we are asking, we are checking for the specific antibody specifically to COVID and there may have been other antibodies that we didn’t measure that were extant in the population.

Scott:

So what are the results suggest we should be doing that we’re not currently doing? I mean, we know that poorer people are more likely to be in what we’re considered calling essential jobs, but it’s often because they don’t. I mean, like you said, they don’t have the option of staying home. What do we do about that?

Jay:

This is one of these heartbreaking things. I mean, I think it’s going to, it’s COVID and this and that our policy response to COVID-19 is going to intensify inequality, not just in work and in health, but also in education and a whole variety of other things. Your question is difficult, partly because, I mean, it may just start to say, I mean, my understanding of the epidemic is a little different than I think then a lot of the public health folks. So I’ll start with a premise and the premise is based on the seroprevalence work. I think it’s too widespread to eradicate. We just have to live with it. I’ve thought this now for months, if that’s true, then the policy that we adopt should take that as a starting point. We shouldn’t be aiming at eradicating it because the policies that one adopts to eradicate are enormously costly and may not even be possible.

Jay:

I think it’s not possible even no matter how much cost we pay at this point, absent a vaccine coming around. So the right question is how do we manage it? How do we manage our lives with the fact that COVID is here? And I think you start with a good understanding of what the risk actually is to people from getting infected. That’s the most important number if we’re going to start to think about policy and the thing is it’s not one number, it’s a whole host of numbers, depending on both the host and the virus and the circumstances of treatment available to you. Right? So for instance, if you’re over, let’s say you’re under 50. The risk of dying for the virus is less than one in a thousand, the risk of dying, if you will get infected. If you’re under 20, it’s almost, I mean, I won’t say zero, but it’s like one in a hundred thousand, 1 in ten thousand, on that order.

Jay:

Whereas if you’re over 65 and you have multiple chronic conditions, your risk of dying is much higher. So the first lesson for policy is we absolutely have to distinguish the risk and the response based on that risk. So for instance, I think nursing homes should be absolutely quarantined. I’ve faced this myself with a friend of mine who passed away during the COVID epidemic in a nursing home where, or I can just see him over the fence with both of us would mass on 12 feet away. There’s a fence between us, it is heartbreaking to not be able to say goodbye to him, really. I mean, I think that policy is absolutely wise because we know that when people that are older with multiple chronic conditions get the disease, they die at much higher rates. We should protect them. Schools on the other hand are a good example of where we should do the exact opposite thing.

Jay:

In schools the rate at which kids die from COVID is lower than the flu. We don’t close schools down for the flu. There’s evidence from a study that was done in Iceland, an absolutely fascinating study published in New England journal where what they did is they randomly sampled Icelandic population. I think 12, 13, 14% of it. They isolated virus strains from the entire population, every single virus, person that turned positive, they pulled the virus strain out and then they sequenced the genome. And so then they checked to see, okay, suppose I get the, I had a virus and I got mutation A and you get the virus, you get mutation A and B. Well, that means that I might’ve passed the virus to you because you know, you just added on an additional mutation when you got it. But it’s very unlikely you pass the virus onto me.

Jay:

And they combine this with contact tracing information and what they found was that there was not one single instance of a child passing the virus onto an adult. Let’s say a child is like 10, 10 and under, 10 to 15, have very, very low rates of transmission. We’re learning is that the children actually have, are more likely to have some of this innate T cell mediated immunity than adults. But that has really important implications for schools. It is entirely safe to open schools up physically. 

Scott:

So you think it’s a mistake that schools are being closed preemptively now for the fall? 

Jay:

Yeah, I think, I think it’s an enormous mistake, an enormous policy mistake that we’ll pay for for a generation. Our kids will pay for for a generation because human capital is very, very difficult to replace. 

Tom:

I’m gonna ask a question, going back to the nursing home thing. So, since this is not going to be over real soon. Are you suggesting that nursing homes should basically be isolated for a year or, I mean, that’s kind of pretty sad to think about, that these people will not be able to see their kids. Their grandkids, you know.

Jay: 

I mean, I think there will be technologies that will make that isolation easier to manage so it’s not less complete. So for instance, rapid antigen testing to see if I’m not positive then I should be allowed to go in. Right now, the virus test takes a long time, like a day or two or sometimes a week to get back that makes it very unwieldy to break the quarantine. But if you had a rapid engine to test, you just test me. If I’m negative, then I’m allowed to go in. If I’m positive, I’m not. I’d still have to wear masks and all that just to make sure. Cause you know, a lot of it’s not just symptoms. Like people use the barometer on the head. Most people that have it don’t have a fever. It’s not enough just to do that. You need something more specific. But so I think some of the isolation could be relaxed with better technology.

Tom:

Do you have an idea how soon those technologies could be available?

Jay:

I mean like some of them are kind of already available. Like rapid engine testing I know that there’ve been several companies that have put some out, The FDA is still considering them. They’re not as accurate as the PCR test for the virus, but they may not need to be right. So if you’re in a low prevalence area, which is still a much increasingly smaller fraction of the country, but still a lot of the country, you know, a negative is really a negative. I mean so even though the test may have scenarios, it’s really good, it’s likely to be right. So in that case, even though you have a test with, you know, 80% or 85% sensitivity, it’s fine, you know, negatives a negative. So I think that kind of like regulatory decision about what the threshold should be used to allow the test to be in the population shouldn’t just be a epidemiologic thing where they have to have it meet some arbitrary standard for how good the test has to be. It should be tied to the policy decisions about what usage you’re going to use the test. 

Scott:

Do you think the massive testing strategy that Paul Romer has been advocating is a productive way to go? Assuming we had the capacity to test at the levels that he’s talking about. 

Jay:

I mean, I followed what some of his suggestions are. My sense is that he’s emphasizing a PCR test. And the kind of thing he’s talking about is a massive one day or two day let’s test, literally the census of the Americans and then isolate just the people that test positive. It seems really unrealistic to me to do anything like that, just because there’s large populations that are hard to reach even with a multi month census, how you would get homeless populations, how you would get large numbers of people who are difficult to reach, actually that are isolating. They’re just not going to answer the door. I don’t practice. I mean, it’s great, I think in theory, but I don’t know how you do in practice. 

Tom:

You would isolate the more vulnerable populations, particularly older people, particularly people in nursing homes or people with other conditions and then kind of let the rest of society go on relatively normally, is that right?

Jay:

I think that’s the right policy tone cause I don’t see any alternative. Not, what I’ve heard and I’m sympathetic is that you’re going to get some excess deaths in those populations. That’s absolutely true. But you have to balance that against the deaths that I know that we’re already getting from the shutdown. Suicides are up among kids and not just among kids. We’re seeing people that are delaying or not getting chemotherapy or radiation therapy for cancer. The rate at which people are getting screened for cancer is an all time. Low people are delaying vaccination for their children because of fear of COVID, your fear of like going to the, to see the doctor with COVID, we’re going to see, there are gonna be health effects that have nothing directly to do with COVID, but indirectly having to do with the lockdown policies for a long time now.

Jay:

And the death from that is the, we’re going to start reaping those deaths soon. I mean, it’s a, you’ve seen the excess death numbers it’s for sure has caused, COVID itself has caused excess deaths. But I think we’re going to start to see the excess deaths from that, we’re going to find out how important the healthcare system actually is. To a health economist, it’s a, it’s a fantastic experiment, but you know I won’t take any joy in analyzing it.

Scott:

I mean, you’re also, I guess, raising a point, a sort of difference between how epidemiologists look at the pandemic versus how economists look at it. And so do you find yourself at odds with epidemiologists there, the approach that you take

Jay:

I’m writing a book I’m going to call it the denominator war Scott? Yeah. I’ve been in a lot of fights with epidemiologists over some of this work, but I mean, you know, it’s, I guess whenever fields come together, you’re always gonna have some clash of cultures. So it’s, it is what it is. 

Tom:

Economists are supposed to be contrarians aren’t they?

Jay:

That’s true.

Scott:

True. That’s right. But do you think it’s been, I mean, sometimes that debate could be productive and sometimes it isn’t. How do you feel it’s affected our response to the epidemic? Has it been a collaboration or is it just lots of arguments?

Jay:

To some extent, I mean, it’s heterogeneous, right? So like some epidemiologists have been really open and some much less so. I mean, I’ve worked with some fantastic folks who do epidemiology for a living during this crisis. And before who’ve been very open to these, some of these ideas and others who are just, I think I, to be fair, I’ve seen some economists fall into this trap too. I think if you think about policy just as I need to stop COVID, premised on let’s eliminate the disease, you’re going to get, whether you’re an economist or epidemiologist you’re gonna be led to a certain set of policies. If you view this as something we have to live with and we have to have trade offs and we have to figure out how to manage it well now we’re in the economics world. So I think that difference in viewpoint is more important than just the disciplinary epidemiology or economists’ kind of approach to this.

Jay:

And I think part of the problem for me has been just trying to, you know, I think cause overlaid on this is this moral aspect of, it’s very easy to like to pull it and argue when you disagree with someone, to pull an argument and say, well, look, you want these people to die as if you can end the argument about tradeoffs with that, right? We’re always kind of, as economists we often face this as an occupational hazard where we sound callous, when we’re all we’re saying is, look, we don’t want these people to die. We’re just being realistic about the tradeoffs, and there are deaths on both sides, right, of this. So I think that moral frame has to be an overarching thing where we care about all the deaths that come from the lockdown, from COVID, all. I mean, we have to, we have to like put weight on all of them. And if you focus just on COVID and this should come and to anyone who thinks like this way, if you think focused just on COVID, you will end up doing worse for society than you try to let them take a broader view and say, let’s look at all these people who are going to suffer from the different policies one way or the other. Unfortunately, people are going to die. Question is how do we manage that so that we minimize the suffering?

Scott:

I mean, it’s going to be a while before we have all the data on that, but what do you think we should have done differently in managing that? Our response to it?

Jay:

Well I think for, and this is going to sound funny. I think for one, because we didn’t have seroprevalence data early, we shut down too early in most of the country. We shut down when the disease was basically not present in the vast chunks of the country, but now some of the country, it was present. We shut down, but we didn’t fully shut down the places that should have been shut down. So nursing home deaths are a absolute disaster. You know, I think, I mean, I don’t know exact numbers, but it wouldn’t surprise me if a third of all deaths or half, I mean, somewhere in there, of all deaths are nursing home deaths. We should have done a much better job protecting nursing homes. And we knew that older people were vulnerable from the Chinese data that had come in in January and February. That was not a surprise.

Jay:

In China, the older people died at much higher rates and we should have realized that and focused our lockdown efforts in places where the disease was spreading, where the nursing homes were. You remember that I looked at, one of the very earliest things I remember from I think it was February was this nursing home in Washington state that had an outbreak where a really sad number of people died as a result of the outbreak. That should have been a signal to us about what the policy should be.

Tom:

Going back to the, you know, getting back to relatively normal activities for the bulk of the population. Would you, assuming we could get our act together, which is obviously questionable, would you do large scale contact tracing to go along with that? 

Jay:

I mean, I think some contract tracing is probably worthwhile. I think now that the disease is so widespread and the antibody evidence suggested is, it kind of has a limited role, like you’ll end up doing so contact racing the way it works. I have the disease. You check, ask me where I’d been. That’s got, unfortunately, you and I were in the same room once 17 years ago. So now Scott is going to be two weeks quarantined. And then you move in a circle around him. You ask Scott where he’s been and you keep, you keep expanding until I think the social network, given how widespread the diseases is, will cover the entire population, you’ll have to contact trace everybody. Contact tracing is tantamount to checking the entire population more or less at once. So I don’t know about contact, but I do think like social distancing, to some extent mask wearing, those kinds of things. Even if you don’t mandate them, people will do them because don’t people don’t feel safe and they want some agency. And there’s some evidence that that helps, right? So people will do them do those things. And I think that’s completely reasonable.

Scott:

But if we’re going to, if it’s going to spread until there’s some kind of herd immunity, then I guess you would expect even in places that got it under control, if they got it under control before that they’ll see resurgences. Is that what we should be expecting

Jay:

Like I think, I think for instance, we’re seeing that in Australia, Australia sees a resurgence because they had basically locked down everything that it looked like it was under control and it spread again. There’s some places where I think we’ve reached herd immunity actually. I mean, I think I would be very surprised if there was a second resurgence in New York, we might see some blips, like endemic cases might come up, but you know, like I think Bronx, I saw seroprevalence test on the order of 50%, that’s herd immunity, probably even actually there’s, there’s been some theoretical work that suggests herd immunity might be even lower than that. Cell mediated immunity is really, really important. Obviously it’s theoretical. So we’ll see. I mean, in sense, like Sweden, you’re seeing that’s the policy they followed, they opened up, they kept everything basically open.

Jay:

People did social distance there. People did less mask wearing and a lot more social distancing. Elderly people didn’t go out. You saw basically now cases are down at the very low deaths are down very low. They’ve reached herd immunity there. 

Tom:

In the absence of a vaccine, isn’t that, does the whole thing start all over again in the next flu season?

Jay:

I mean, it could, it depends on how long lasting the immunity is. And that’s a big open question, right? It’s a big open, we don’t know the answer to that. 

Tom:

I mean, there’s questions about how long it lasts, but nobody thinks it’s permanent. 

Jay:

I don’t think, I mean the coronavirus, from what I understand, at least the other coronavirus immunity, it’s not forever. It is generally longer than, it could be more than a year. I mean, it really varies from person to person. I’ll give you some bad news and some good news on that front. The bad news is it seems like the specific antibodies that we’ve been measuring, or I’ve been measuring in my work, they disappear relatively quickly, a few months, not for everybody, but for some such hunk of the population. On the other hand, there seems to be this, this sort of induced T cell mediated immunity that some proportion of the population gets that we’re not measuring the very population level very well. So I can’t give you any specific numbers. That does seem to last much longer. So I don’t know. It’s still, I mean, earlier in the epidemic, I was saying, I don’t know what the immunity is going to be like. Cause the people hadn’t really done the studies. The studies are starting to come out. I think there is immunity. We know it lasts at least five months, but that’s all we can say about it.

Jay:

Cause it’s only been five months. Right? And then we hope it lasts longer. The question is what will happen? Like let’s, let’s say it lasts less than a year time. Right? So in that case, what we’ll get is people will start to become non-immune they’ll become susceptible and you’ll see outbreaks, little outbreaks, little outbreaks. You will never again see this massive spike because people got immune at different times. They got unimmune, is that a word, unimmune at different times. And so you’ll start to see like this endemic thing. And I mean, that’s what herd immunity looks like. It doesn’t look like zero infections. It looks like this thing. That’s just sort of, endemics floating around all the time. And that’s why you’d have to protect the older population for a long time.

Scott:

Most of your, well your work had focuses on vulnerable populations and the largest groups of vulnerable people are in poor countries. And right now we see if you look at India’s cases, it’s as if somebody wrote an equation and they’re just following it exactly. I mean the exponential epidemic growth is it looks like it just came right out of a textbook. What do you do in a place like that? They locked down originally, but for people who are already so impoverished lockdown is really can kill them. What do you do with, if you’re the Indian government and you’re trying to think of what to do about this, what do you do now? 

Jay:

It’s a, I mean, some sense, a sad thing. I mean, like I I’ve tried to like help get seroprevalence studies started in India, but now there actually have been some seroprevalence work. For instance, Delhi. I think it’s the ICMR study found 25% of Delhi. That’s a, because testing resources are less in India. That’s a bigger multiple than we found in Santa Clara County and in LA County and people are finding what CDC found in the U.S. I mean, even though the cases look like they’re rising rapidly, they’re actually a small, multiple of all the cases, the same in India as it is everywhere else. And the lockdowns themselves in many poor parts of India probably intensified the spread of the disease because many people live in the same house. There were police basically forcing you to stay in the house.

Jay:

You could get imprisoned. I mean, you could, there was like, it was really a sharp lockdown and the disease spreads indoors at very high rates. So one positive person who normally spends most of the day outdoors selling food or something instead spends all day long inside with his elderly mom. And so you’re going to get, you’re going to spread it there more rapidly than if you allow their people to like walk around. I mean, so I think it’s not clear in India that the lockdowns actually did, I mean, it’s pretty clear it didn’t do anything. It certainly didn’t suppress the disease long enough to stop it from spreading. I don’t see any policy in India outside of herd immunity. I really don’t. I think the question is protection of older people. How do you do that in a setting where there’s a lot of intergenerational cohabitation and the striking thing though, is, is the death rates are lower in India, less than in the United States. The infection fatality rate seems like it’s one of the thousand in India. Whereas in the U S it seems like somewhere between two to five in a thousand.

Scott:

Is that because it’s a much younger population?

Jay:

Yeah. That’s why. It’s a much younger population. That plays a big role. Actually that probably explains partly why Italy had it so bad. I mean, a much older population in Italy. Belgium had it so bad. That age specific IFR is something that, I mean, that it’s really important to think about.

Tom:

 What do you think, what do you think are the prospects for a vaccine? 

Jay:

You know, if you’d asked me three weeks ago, I would’ve said bad, but I’ve kind of started to like, there’s this hope that’s springing up inside me. I don’t, I don’t know. I mean, I was looking at some of the new technologies they have, they have this like one technology where they put MRNA snippet that codes for a little bit of the virus, right? And so your body takes up the MRNA, the cells take up the MRNA, produce the snippet yourself, translate this snippet into a DNA fragment, which then produces the immune response.

Jay:

I’ve never seen. I mean, maybe I don’t do molecular biology, really. But I haven’t seen that use of a vaccine before. That’s pretty amazing actually. And there have been, there’s now I think 137 vaccine candidates worldwide, eight in trial or six or seven in trial in the United States alone, China. I mean, I think there’s a lot of hope for this, I mean, it might actually work. And some of the phase one evidence suggests that the vaccines do produce neutralizing antibodies. This could work, and we’ve made an enormous bet, by the way. We basically have said, we’ll pay you, I don’t know, Pfizer or whoever, X billion dollars to start manufacturing these vaccines even before the trials are done so that when, if it turns out the trials turn out good, we don’t fight over who gets it first, everyone will have it.

Tom:

Given the amount of money we’re throwing at other things, that’s seems almost a small amount of money.

Jay:

No, I mean I think it’s a good bet. I mean, like if, if the vaccine works and the data looks good, we should absolutely spread it out to the entire population instantly. As far as I’m concerned.

Tom:

I’m thinking we can afford to spend a few billion dollars on vaccines that may ultimately not prove out [inaudible]

Jay: 

We can find some other use for a whole bunch of MRNAs that, you know, segments that code for a virus that someone will find, even if it doesn’t work for the vaccine. Some, you know, who knows.

Scott:

If a vaccine does not come about in the next, by the, by the end of the year, at what point is, are we close enough to herd immunity in general? That you’d say, all right, well, let’s just get back to life as normal as we can. And you said we have it somewhere. Maybe some places already.

Jay:

Like some of the places that have had it, the worst are, I mean, again, there’s a lot of uncertainties there’s scientific uncertainty still about this, but I think like New York, you know, New Jersey increasingly, it looks like now maybe Arizona, Texas, the places that are in the news as like they’re in the worst shape in a month or two, will be in the best shape. We’ve already seen this with New York where everyone was telling the success story and they’ve forgotten the vast mountain of deaths we had. It’s not a success story. What it is is just the story, right? We don’t have a way to manage this illness. We don’t have a way to treat it. There are some success stories. And I think partly what explains New York is I’ve already, we’ve already talked about the nursing home, but also partly it’s that they were, unfortunate because they were early on in the epidemic. Medically we’ve learned better how to manage the condition when you’re in the hospital, you’re seeing less of the ventilator mediated, I mean, the, the people on ventilators are the first they’re getting on ventilators at lower rates and they’re coming off ventilators and surviving at higher rates. I think I saw a study in England. Like I think the mortality rate inside the hospital is a quarter of what it was at the beginning of the epidemic inside the UK in 

Scott:

Can that paradoxically create more crowding in the hospital or do they get to go home earlier too?

Jay:

Earlier. Yeah, there seems to be, I mean, partly it’s also there are younger people in the hospital you know. There’s also like this development, some new therapeutics with old medicines, like dexamethazone, which is a steroid, like one of the mechanisms by which people get sick with this, what they get it in the lung and they have this it’s called cytokine release syndrome where they essentially your immune system, because it’s overwhelmed with the virus reacts with this nasty immune response. And that it’s the immune response that kills you rather, as opposed to the virus itself directly. So managing that with steroids turned out to be useful. There are technologies like ECMO, which is this essentially you oxygenate the blood directly as opposed to through ventilation through the lung. That seems to be useful in some cases like various, very severe cases, especially ones where the lungs, so, I mean, I think we’ve learned how to treat the disease better than the folks knew in February. So getting it now is safer, not safe, safer than it was back then. So, I mean, I think that probably explains New York also.

Scott:

So we’re, I mean, we’re, we’re running out of time, but I’d like to know. I mean, there are, there are many, many sites that are tracking data and lots of people like me who look at them obsessively. What are the statistics that you think best show the state of the disease? I mean, we focus on cases, but cases are just the tests times positive.

Jay:

Great. Yeah. This is our misleading statistic. Scott. I regret that that’s the number one thing that everyone seems to track. If they want to track anything, I focus on two things. One is cases in the elderly and two, I focus on deaths. How many deaths there are. Those two numbers to me, if I’m going to pick two numbers, I’ll pick those two number. Beyond that I’ll want to know the prevalence, but that prevalence is based on seroprevalence studies. Those are sporadically released as opposed to like tracked continuously day to day. But yeah, if you’re, if you’re trying to follow along, I would look for percent sort of the, how many elderly people get the disease and how many people die from the disease.

Scott:

Okay. Well on that note, I guess we should wrap up. So Jay thanks so much for talking with us.

Jay:

Yeah. It’s my pleasure Scott.

Tom:

Thanks a lot.