Seroprevalence Study in Mumbai: In Conversation with TIFR Scientists -- Part 3



Part 3: Discussion of Findings and Other Studies


Meena Kharatmal: How did the studies conducted in other parts of India influence the Mumbai seroprevalene study? What are they indicating? What are your thoughts on similar studies conducted elsewhere in the country or in the world?
Ullas Kolthur: I will talk about general studies, and I think Sandeep is better in talking about what would it mean about the reports that have come out. When we decided to do the serosurveillance, there were not many studies which were done. In fact, even the ICMR (Indian Council of Medical Research) study was not on the cards, at least based on our knowledge, back then. Those were really early days, I mean this was back in April -- beginning April or mid-April. There were no real reports of seroprevalence. So we designed it more or less on our own and the choice was whether to do a longitudinal study or a cross sectional study. There were considerations of whether we want to get a number for the city or whether we want to get all the other attributes that we just elaborated on gender, age, population etc. So in that sense, I would say, our study still stands out probably as one of the largest cross-sectional studies with high density of information, which provides high confidence data in terms of statistical analysis. That was an unique feature.
If you compare our study with other studies in India, they have largely looked at broader populations, but in terms of sampling, the number of samples, the number that have been collected in any given area or Ward are not as dense as ours. So there is unique value in our study, where we get a deep-dive perspective of the spread across these geographical locations. Other studies do not answer the kind of question that we have asked, about population density and crowding. Our study gives that kind of information, where you can now form many more hypotheses in terms of factors that could drive the disease. But our study does not give you a broad, big number for the city. So there is value in both types of study design. We chose to do a cross sectional study, therefore numbers can be compared in terms of prevalence, but you have to keep in mind what those numbers mean and how they came about. I will leave it to Sandeep, as there are numbers that are coming out of Spain,  New York and other places.
Sandeep Juneja: I do not have much to add. But it is true that when we started discussing this in mid-April and the discussion went on in May. The studies that were available to us were the London survey (the UK survey), New York city survey, and the numbers by and large were lower. In New York city, they began to see 23% prevalence at the height of it, when the infection was actually winding down there. London was also at 21% (or 17.5%), when the infection was winding down. So those numbers were available to us, but it was not clear to us whether in Mumbai it was winding down. At least we did not expect these kind of numbers.
As Ullas mentioned, there were unique structures about Mumbai that we wanted to capture. So we knew, that it has to be tackled separately. The Delhi study was actually conducted around same time as ours. So we really could not learn anything from that because it was simultaneous. But I believe the Pune study is influenced by what we did and probably other studies in the country are influenced by the results that they saw in our study. We were certain the Mumbai's slum numbers have got the whole world's attention. So most of the population is showing almost near to herd immunity. It was not clear whether this was possible, whether we would likely to see this happening, and then our study shows it happening to such an extent.
Fortunately, it was not leading to that kind of calamity that one would  have anticipated. Because with these numbers you expect to see many more deaths. That is the most surprising fact that has come out of here. You can imagine, that if indeed when the infection took off in the slums when it began to happen if indeed it was causing severe consequences health wise, or  people were dying, then we all would have known at that time. We would have even chose to take corrective action.  As we did not see all of that and hence we did not expect the prevalence to be so much. But now that we have seen the prevalence to be so much, mild number case fatalities coming from slums, that is raising all kinds of interesting questions, such as why is that the prevalence has been so low (fatality rate) health affect have been so low. One thing that is mentioned is that the population there is younger. Even if you correct for this, we still see a lower number of fatality cases coming from slums. This makes you wonder if there is some kind of immunity that already exists. So lots of interesting questions that are coming out of the survey and hopefully as other surveys happen in  India, we will have a better sense of these questions.
Uma Ramakrishnan: It is very nice to hear you say that you feel this is a positive result. Often media sensationalize these things. So its 50%, and people are shocked and surprised that it is so high. But its very nice that your understanding of it is that it is 50% but it still has no huge impacts on morbidity and mortality. I was just wondering, for example about cities in Africa or South-East Asia. Can we think of ways to inform preparedness or policy based on your studies?
Ullas Kolthur: It highlights the importance of non-homogeneous populations in mega cities. This could even be true of New York and other cities which could impact prevalence. In fact, now some neighborhoods in New York have higher prevalence than others, which points out that we need to understand how the disease spread happens. The factors that could drive us could be very local. But the fact that if there could be differences, we need to be cognizant.
In terms of policies, one of the key features is at least the infection fatality rate is as low as what we are seeing in the Indian context. The other key thing that we found is that there is likelihood that there would be more asymptomatic people. In that situation, I think efforts to ensure that symptomatic people are traced, later their primary contacts and their high risk contacts are being isolated, seems to be one of the best ways to tackle the situation. On the other hand, since you will never know who is asymptomatic, there is little you can do in terms of isolating and identifying them. Instead providing better healthcare for symptomatic people seems to be the best approach, also to ensure economic activities.  I think again Sandeep will actually say more things about that.
So it is a fine balance between what is the cost and what is the benefit. Measures during early infection will not give you high rewards, as later periods in pandemic. Particularly, measures like lockdown at 5% or 10% of prevalence may not be very useful as at 50% or 60% of prevalence. So our study actually highlights the need to take informed decisions about what kind of measures we want to bring in to tackle the disease and its spread, specifically emphasizing more on healthcare than anything else. I think Sandeep will add.
Meena Kharatmal: Right
Uma Ramakrishnan: I think its very concrete, thanks Ullas
Sandeep Juneja: So let me say a few things. So Uma, we knew already what was happening in  slums and non-slums in terms of severe cases in terms of  fatalities. In fact high prevalence is better news than low prevalence. We have already seen the nasty aspect of the disease and learning that more people are infected is actually good news. That is the right way to think  about this.
In terms of Africa, I am not following very closely. But it is true that by and large Africa seems to have escaped infection so far. Infection happens only when you have infected people going around. Until sufficient infectious people show up in a country, you will not see the epidemic spread there.  We will have to wait and watch. But I guess your point is that maybe, the rate of infection that we are seeing in India is reflecting on what we might see in Africa. There is some kind of immunity, for example that we might see people in slums here, would also translate to similar effects in Africa. I think those are difficult things for us to comment on right away with the data we have, since those are the things we need to examine as we go forward.
Uma Ramakrishnan: I drew the parallel with Africa because of the demography, and population size. Particularly, this is also true for South America about its high concentration of people in certain mega cities, like in Lima. Ten percent of Peru lives in Lima. So in that sense compared to say in the New York city, which is crowded, but it is still nowhere as crowded as our mega cities. What is interesting to me is how such studies bear implications in the future?  Do we want to continue living in the same way,  in these mega cities in the future? Do we want to change how our cities' scape for more distributed living spaces? I mean this is a big question of course, but something to wonder about and to think about. I think there are implications, as far reaching as land planning from a study like this.  I am glad you brought it out that  the study has got a very far reaching implications. This is what I was trying to say.
Sandeep Juneja: Certainly, exactly to your point, Mumbai's life line is the trains, because people travel everyday here. There are eight million people traveling  everyday very close together and that is where all the mixing happens. Until you get the trains going, the city cannot really come back. But if you get the trains going, you will see lot of new infections coming up. That is the worry that is occupying people. One solution could have been that people actually stay/live nearby so they do not have to travel so much. Another solution is we are all working from home or wherever we can. But redesigning our lives so that we do not have to travel so much would be one way to go about this. I guess there are other constraints that come into play. So we have to see how that plays out.
Personal perspectives, risks and challenges during the study, and about public private partnership, continued in Part 4.
About the People:
Dr. Ullas Kolthur is a Professor at the Department of Biological Sciences of the Tata Institute of Fundamental Research, Mumbai. His research interest is in the area of cellular metabolism and energetics.
Dr. Sandeep Juneja is a Professor and Dean at the School of Technology and Computer Science, Tata Institute of Fundamental Research, Mumbai. His research interests lie in applied probability including in sequential learning, mathematical finance, Monte Carlo methods, and game theoretic analysis of queues.
Dr. Uma Ramakrishnan is a Professor at the National Centre for Biological Sciences (TIFR), Bangalore. Her research investigates population genetics and evolutionary history of mammals in the Indian subcontinent, including work to save India’s tigers.
Ms. Meena Kharatmal is a Scientific Officer at the Homi Bhabha Center for Science Education (TIFR), Mumbai. Currently she is contributing articles, resources for the CovidGyan. She is also trying to complete her PhD in the area of Biology Education.
This interview was recorded on 19th August 2020. Since then, the preprint on the findings of the Mumbai seroprevalance study is available as a report published on TIFR website.