COVID-19: More Widespread Than Estimated?

Are we testing enough people to know the spread of the virus or are we missing out on the asymptomatic people? Moreover, are we overstating what a lockdown can result in? To discuss these questions BOOM's Govindraj Ethiraj spoke to Dr. Jay Bhattacharya, Professor of Medicine at the Stanford University.

Here are a few points that Dr. Jay Bhattacharya made -

- Epidemic Is More Widespread Than We Believe

- Hypothesis Needs To Be Tested Everywhere

- Missing Out On Asymptomatic People

- Economic Depression Will Kill People

- Deaths On Both The Sides Of The Policy

Watch the episode to know more. Read the transcription of the interview below -

Over 21,700 cases have now been detected as positive in India and about 686 people have died. Now, on the 3 rd of May the lockdown as it stands across India will be lifted and obviously there will be far freer movement of people, goods and services than it has been so far. But whether that will actually happen, we do not know for sure. So, what if we were not to have a lockdown in the first place? Or if we were to lift the lockdown regardless of what the numbers are? What if we did not have quarantines and lockdowns to start with? What happens then—would the casualty numbers be higher, lower or would they be the same? We do not know. But there is an interesting theory that is doing the rounds, which questions whether we are indeed over stating the case. It all began with an article on The Wall Street Journal on the 24 th of March by my guest Dr Jay Bhattacharya, Professor of Medicine, at the Stanford University. Also, a senior fellow at the Stanford Institute for Economic Policy Research, he argued that essentially the projections were too high and we needed to revisit these numbers or relook at them differently.

Govindraj Ethiraj: Before, I ask you all the questions that I am obviously keen to ask you, tell us...you are a Professor of Medicine at Stanford (you did an MD) and did a PhD in Economics. Tell us what made you go into Economics after doing medicine?

Dr. Jay Bhattacharya: I was always been interested in medicine—I loved science, in school I contacted? economics and I was amazed to find that you could use the tools of economics to understand questions in medicine. They were very sort of different but a very effective way. And that is why I picked both.

Govindraj Ethiraj: And you follow/focus on the economics of healthcare as a keen, around the world. And that I am assuming is what lead you to form the conclusions you did. So tell us, why is that you fundamentally believe that we are overstating what can happen, if we were not to have a, in India we have as we are calling it a lockdown, in the US you are calling it a Shelter in Place Order or a quarantine.

Dr. Jay Bhattacharya: I want to correct the record slightly—I actually believe that the epidemic is more widespread than we believe, not less widespread. That is my hypothesis. I would like to see that hypothesis tested, basically, everywhere. And the reason I believe that hypothesis is that there are many people—we are seeing this from studies around the world—who have been infected with the virus, cleared it (sometimes with no symptoms, sometimes with mild symptoms) and never were tested to find the virus positive. So those case numbers you said, around 20000 in India, those are all cases where there has been a test done to check whether the virus is active in you.

Govindraj Ethiraj: And in India, we are testing only if there are symptoms to start with...

Dr. Jay Bhattacharya: Right, that system works all around the world...because why would you go get a test if you have no symptoms, right? But that means that we are missing, most likely, large numbers of people who have not had symptoms and not been tested and yet have had the virus. The only way to check for that is by doing the antibody testing. Antibodies form in response to the virus and provide evidence that you had been previously been infected. Only by doing that kind of testing, do we understand how far along in the epidemic we are. And as I said, my hypothesis is that, we are very far along, much further along, than just what we can tell from the case reports. I will agree with you one aspect, ….. correctly, if you want to understand the death rate from the virus, we need to understand the size of the number of cases. We have some sense of the number of people who died in the numerator, we also need to know how many people have been infected in the denominator. And that is the piece we do not know. If my hypothesis is right, and that number is much larger than we realize, then the death rate per case might also be lower than the we realize.

Govindraj Ethiraj: I do not if that really helps, if we know that the fatalities as a percentage of people infected is lower as per your hypothesis...we will come to that in a moment. How are you even concluding—we are talking of Coronavirus which has essentially come from Wuhan in China and then spread all over the world. Why would you assume that there are far more people either in the United States or elsewhere carrying this virus already or for a much longer period of time...

Dr. Jay Bhattacharya: That is a good question. Obviously, this is a novel virus, there is a lot that we do not know about it. The hypothesis is primarily driven by the work that I did during the H1N1-Flu epidemic in 2009. I am actually just following that literature. In that literature, the early case reports, reported very very high fatality rates and the reason why was—they looked at the identified cases in the denominator just like we have been doing now. And 1-2% of the population that were infected with H1NI in the early days of the epidemic died. A year later, people started doing these antibody tests and found out that very large numbers had been infected and they never knew about that. And the fatality numbers went from 1% of the cases to 0.01 percent. That happened in the H1NI, the transformation of our view of the risk of it, over a year and half period. Now it is not unreasonable to say that the same kind of situation may be happening now. Now, this is a hypothesis—it needs to be tested. It might be wrong; it might be right but the only way to find out is to do widespread population level testing.

Govindraj Ethiraj: Anecdotally, however, if you were to look at New York, or New Jersey—hospitals are flooded with patients. In India, it is the counter. I am talking to a lot of lung specialists, or pulmonologists or critical care specialists and we are not seeing a surge in cases, Even assuming we ignore the data completely. So that did not happen in H1NI—you were not seeing a surge of patients in hospitals.

Dr. Jay Bhattacharya: I am sorry...I should be completely clear. This is different from H1NI, absolutely, behaves differently and it is very clear also that the mortality from this virus...It is not just the biology of the virus but the situation in which the people who get very sick with it are treated. In overwhelmed systems, it seems very likely that the mortality rate will be higher per case than in places where the hospital system is not overwhelmed. It is the both the biology and the health economics are acting together to determine the mortality rate of this virus. And that is why I think it is important not just to say, I have done a study in Santa Clara and we know the numbers everywhere. I need to study in India, to understand the virus, how deadly it is, how wide spread it is in India; we need to study in Sweden, Switzerland, in New York—separate from Santa Clara. These are all very different environments in which people get taken care of and without understanding the denominator we are not going to have any chance of understanding how this virus is behaving and how deadly is it in various situations.

Govindraj Ethiraj: In Santa Clara you study said that the actual number of people infected could be 50-85 times what is presently known. And that seems to be a dramatic number

Dr. Jay Bhattacharya: There are 2 million/3 million people in Santa Clara; our estimates probably range from 2-4%…..…statistical assumptions. The day we did the study, there were roughly 1000 identified cases. At the lower end our numbers suggest something like 50000 cases in Santa Clara, on the higher end, it suggests more. If you look at the low end, it suggests 49000 more people who had the virus in Santa Clara and were never identified with the PCR test.

Govindraj Ethiraj: The other number that one hears including people from the medical profession is for 85% of the people who are infected nothing really happens and it is the 10-15% we are worried about, maybe the 3-4% who go into intensive care unit, need ventilators and then things go south quite dramatically after that. So is your theory in some way reflecting that—the fact that a lot of us may carry it, by now we know people who contracted it, only exhibited mild symptoms or severe symptoms of flu and then it has dissipated.

Dr. Jay Bhattacharya: I can completely agree with that, the only thing I can add is it 85% or what, because we do not know the denominator. But it does seem to have in many cases no symptoms at all. In Chelsea, Massachusetts, there was a study done just a couple of days ago suggesting, very large numbers of people with antibodies, studies now done in prisons, where they find the virus active in people and most of the prisoners do not have any symptoms at all. On the other hand, the virus is also deadly, as you say, in many many cases. It presents a severe viral pneumonia especially in older people or people who are vulnerable. So, it is not that we should take the virus less seriously. We should take it more seriously. We should better understand who is at risk from it, how extensive it is, and then take better decisions as to what to do about it as opposed to, now I think to some extent, we are making decisions in the dark, in fear and in the dark. That is my main call, let us shine the light of science on it. Let us actually get better numbers, so that we make better decisions.

Govindraj Ethiraj: I will come to how to get those numbers. How do you explain some of this—you talked about the study in Massachusetts, and the study from prisons, how people are behaving quite dramatically and differently. What explains that?

Dr. Jay Bhattacharya: As I said earlier, there is obviously a lot we do not understand about the virus. But it is very clear that it is just not the biology of the virus that makes it deadly. The circumstances by which you get it, the circumstances of the healthcare system that are managing people, all also those things combined can determine what happens to people when they get sick with the virus.

Govindraj Ethiraj: So, your path or way forward is to test and then you find out. So how do you test and what is the scale of testing you propose that America should do, or other countries should do too...

Dr. Jay Bhattacharya: India should do this too...I think a lot of people when they talk about the testing, they are talking about the active virus— polymerase chain reaction (PCR) test. Actually, the virus is an RNA virus......unclear. That test just checks whether you have it right now. After you clear the virus you will be negative. You need the antibody test—for this kind of population surveillance (survey work?), you do not need to test everybody. You do not need a billion plus people tested in India for this surveillance (survey work?), but you need to do a random sampling of the population. If you look at areas, let us take Mumbai, we divide up Mumbai into various parts and then randomly pick people from those parts and it does not take very large samples,1000, 2000, 3000, 4000, 5000, samples and you can get a very good idea about the spread of the virus in populations of like millions. The test themselves are inexpensive—basically many of them just require a finger prick blood sample. There has been a lot of controversy over the accuracy of these tests. So, there are two kinds of accuracies in these kinds of tests and it is really important to understand the difference. So, the first kind of accuracy is called specificity—what that means is that the rate at which, a negative case (someone who is truly negative) ends up negative. So, it is kind of related to the false positive rate. That has to be very low..............unclear. There is also another number called sensitivity that says if you are positive how likely is it, I am going to find you positive. The cheap tests are very very specific but only somewhat sensitive. But that is fine, as long as you are specific, it is great for.....I will just give you an example. Suppose there is a test that is only 50% sensitive, that means for every positive I see, there is another that I did not see—false positive. But I can adjust that statistically very very easily. So, these tests are ideal—these antibody tests that are cheap, actually inexpensive to do this kind of population survey work relative to/ rather than test higher population or shutdown an economy or something. You should just do these. There are no good reasons not to have these studies basically done everywhere.

Govindraj Ethiraj: And then the economic conclusion—would that be that we should not be there for fretting too much about lockdowns and quarantines and open things up...

Dr. Jay Bhattacharya: I do not know the optimal policy until I know the numbers—it is really hard to say. I think, one outcome I am hoping from this work is, we will quell the fear. I believe that when I get the virus or if I get the virus, I have a 3% chance of death, I am going to be very scared. That is essentially what the WHO said, 3% mortality. On the other hand, if it is 1 out of a 1000, or 2 out of a 1000, I am going to be much less scared. I think making policy in the midst of fear is really really a bad idea. Now, there may be reason to fear, as I said it is hypothesis, we need/read these numbers everywhere. But if you are going to reason and think about policy in fear, it better be well-rounded fear, not fear based on not knowing the number we can very easily get is....

Govindraj Ethiraj: In a way you represent both worlds to answer the next question. In India, the Prime Minister has said it is lives versus livelihood and the same debate everywhere

Dr. Jay Bhattacharya: it is livelihoods though, it is lives on the other side. People talk about economics as if it is a secondary thing. But it is actually lives. Poor countries are deadly actually for the poor people living in them. The deaths from the other side of this policy, shutdown policies, lockdown policies, worldwide, will create, we are already in it, devastating global economic depression. That depression will kill people—large numbers of people. So, who will die relative to the COVID, on both sides of this policy there are deaths. It is not dollars for lives. It is lives for lives.

Govindraj Ethiraj: Are we any closer to knowing in which side the balance is tilting today?

Dr. Jay Bhattacharya: I need numbers. I need.....prevalence numbers. I have been saying this from the beginning—we cannot really answer the questions you are asking me with any confidence until we have those numbers. It is the start of a….policy. If we shut down the world economy, almost certainly save lives from COVID....absolutely, slowdown the rate of growth of the disease. It is probably one reason why the Indian numbers are as low, other nations may sound horrifically high, but as low as they are, they would have been higher if the lockdown may not have happened. Absolutely. So we know there are some benefits of the policy. But we have not made any efforts whatsoever to measure the costs. I am not talking of the economic dollar costs; I am talking about lives costs that the global economic depression is about to head...

Govindraj Ethiraj: This is a novel virus, as you out it and it has crept into our lives, our existence much earlier perhaps, not so easily quantifiable by saying 400 thousand people flew in from mainland China to the United States and therefore that is how it spread. So, what does it tell us about viruses, about pandemics and lives as we will lead them or likely to lead them, in the coming months and years?

Dr. Jay Bhattacharya: We face the risk of death from a vast number of pathogens every single day. It is just the nature of human existence. It is going to be one more, I think at the end of the day. We will just have to cope with it. Hopefully we will learn more about it and treat it better, we will learn how to prevent it, maybe there will be a vaccine. So, I think all those things are good, they are coming. My fellow scientists have been doing amazing work and I look forward to that. But in the meantime, you should not destroy the world economy and kill—I saw a story in the New York Times the other day, half a million deaths from starvation in children worldwide, projected from the global economic loss. I mean do we really want to act so that I can protect myself at the cost of these half a million children without having the numbers—to say—reason about it correctly? That is really the case I am making. Let us get the numbers, the real numbers and then decide what the right thing to do is.

Updated On: 2020-05-03T01:45:29+05:30
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