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Why India will not see a big second wave of Covid-19

Last August, I estimated that Covid-19 will end its epidemic phase in India by January 2021. It appears that this prediction was not too far off the mark.

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Update: The author admits the estimates were wrong and has put out a clarification here.

There will not be a significant second wave of Covid-19 in India.

Last August, using a Cynically Optimistic Back Of The Envelope, or COBOTE, calculation, I estimated that Covid-19 will end its epidemic phase in India by January 2021. Karthik Shashidhar, my collaborator, used the curve-fitting technique to predict that the pandemic will be over in the country by February 2021. It appears that these predictions were not too far off the mark.

The same COBOTE method suggests that it is unlikely that we will have a significant ‘second wave’ across the country, although there will be small second waves in several cities and districts. This does not mean we can drop our guard and get back to pre-pandemic levels of congregation; rather, it means that if we continue to be careful, we will all be safe a few months down the road.

Let me explain.

Also read: Majority Indians have natural immunity. Vaccinating entire population can cause great harm

How many cases has India really had?

Although I’ve given it a glorified name tongue-firmly-in-cheek, my estimation relies on the fact that there are more real cases than the official tally suggests. How many more? This depends on your level of cynicism: my Cynic-o-Meter starts at 10x and the default level is 20x. So, if the official number of cases across India is just over 10 million, the actual number is likely to be 200 million, or around 15 per cent of the population.

However, the Indian Council of Medical Research (ICMR)’s own seroprevalence studies in August-September 2020 showed that there are 26-32 actual cases for every reported case in the country. If we set the Cynic-o-Meter to 32x, we have had around 320 million cases, corresponding to 25 per cent of the population of the country. In an earlier study, ICMR had proposed a correction factor of 80-100 per reported case, which permits us to dial up the Cynic-o-Meter all the way to 100x, to a billion cases, close to 75 per cent of the population.

Could this be right? Given that new cases are declining across the country, and the herd immunity threshold is estimated to be around 67 per cent, it is possible that close to a billion Indians have antibodies for Covid-19. Possible yes, but not likely.

That’s because the India-wide figures are misleading. As I wrote in an earlier column, we have had hundreds of local epidemics across the country; with densely populated and urban areas being more affected than others. Lockdowns, post-lockdown control measures, and public compliance were more effective in some areas and less in others. What we can say is this: wherever new cases are declining, we know that around 67 per cent of the “exposed” population possibly has immunity to the virus. Exposed population is the fraction that did not isolate itself adequately, the people who were not strict about masks, handwashing, and social distancing. It follows that if the exposed population in any city or district was large and new cases are few and declining, then the chances of a second wave are small. Cynicism will suggest that this indeed has been the case in India, where it is not uncommon to see the nose poking out of the mask, if at all there is a mask on the face.

This, then, is the basis for optimism. The risk of a second wave is small in most places across the country because most people have already been exposed. For the same reason, we might not need to be overly concerned about the new variants either.

Also read: How IISc & TIFR scientists helped Mumbai civic body anticipate Covid spread, make strategy

Risks still remain

There is, of course, a flip side. If you have been scrupulous about masks, handwashing, and social distancing, you are still at risk of contracting the virus. The risk is lower than it was a few months ago, but is still non-zero. The risk of complications and death are the same as they were earlier. So, if you are among those who have not had Covid-19, you should exercise the same caution and care.

The same logic applies for cities and areas that did well to control the spread earlier in the course of the pandemic: they are at a higher risk of a “second wave” as restrictions on movement end, and as schools, offices, and other public places reopen. This is perhaps what is happening in Kerala, Mumbai, and some other places that saw a resurgence in the number of new cases.

How can you tell if there will be a second wave in your city or local area? Here’s a rule of thumb. Set your Cynic-o-Meter to 20x. Multiply the official cumulative case count in your area by 20; if this figure is more than 67 per cent of the local population, you are likely to escape a second wave if the same level of precautions continue. If not, there is a greater risk of resurgence.

Remember, however, that all this is still part of a back-of-the-envelope analysis. It uses the sparse data that we have, and interprets it in oversimplified ways. While it is useful for us to get a sense of where we are in the pandemic, it is not good enough to relax our guard. Individuals and local governments must continue to err amply on the side of caution. The “all clear” signal will only come after a few months, once the majority of India’s vulnerable population has been vaccinated.

Nitin Pai is the director of the Takshashila Institution, an independent centre for research and education in public policy. Views are personal.

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  1. Pseudointellectualism at its best!
    It is easy to run models and give out meaningless predictions.
    Thanks for your back of the envelope calculations… evolutionary biology is much more complicated than that.

  2. So I was Googling to see who predicted in January that India wouldn’t have a second wave, and THIS popped up… seriously, this has to be one of the worst predictions of all time. The irony, though, is that the model was right about one thing: as a whole, the country probably does have a 75% pre-infection rate. But what this really shows is that natural immunity means absolutely nothing against the new variants. This is a stark lesson for the rest of the world. I don’t know if anybody else is paying attention, but I sure am.

  3. This Post didn’t time well. All these Statistical experts and their predictions are no better than roadside astrologers. When we had the burning example of US, Germany, UK, France, Italy, Brazil in front of us etc we should have been much much more careful, it was really a matter of time before the 2nd wave hit us and that’s exactly what happened. Even if we see statistically also, we were supposed to get hit by the 2nd wave a few months later like how it happened in those countries and we did. The pattern is exactly same.

  4. This calculation builds on the premise that people develop long-term immunity from Covid-19 once exposed to SARS Cov-2 virus. This is not true and most research shows that antibody levels significantly drop after the third month. Even with the vaccine, we do not know what is the duration of immunity with estimates ranging from 6-7 months to 2-years. This means asymptomatic cases will not automatically offer immunity to the people. Also, herd immunity? That term is used only in case of vaccination, not asymptomatic infections;

  5. What about the lapse of immunity? The immunity is known to last for about six months after which it wanes. We have had our peak in September so the immunity will start fading in populations starting February. Your model doesn’t factor in this fact. I think the only way to be out of this epidemic is to continue the safety precautions like social distancing and wearing masks. This along with aggressive vaccination of vulnerable populations.

  6. This is bullshit. It is highly concerning that more than a 100M people have contacted the virus. This provides the virus ample amount of opportunity to undergo transformation and develop a more deadly and contagious strain successfully. The author’s model doesn’t seem to capture that, which is the biggest flaw in its approach. You cannot ignore biology when building models to run different scenarios on your model. We might see more than 3-4 waves of Covid due to the mutated strain.

  7. Absolutely don’t believe in this statistical model. I am from Pune, which has a population of 44 lacs and reported cases of 1.83 lacs. If I multiply 1.83 by 20, then the seropositivity in Pune comes to around 83.2% (36.6/44). If it’s true, then Pune shouldn’t be reporting any new cases. But the fact of the matter is that Pune still has a very high positivity rate of 8-9%, which is the highest among any Indian cities, and it’s still reporting 300 cases per day on an average. So better to be safe and get yourself vaccinated whenever a vaccine becomes available for the general public.

  8. All this statistical modelling is based on assumptions. Fact is many people are locked up at home in India. once schools,colleges and corporate workplaces, transport are fully open we will know true picture.

  9. The view is correct. Look at Bihar election and current kishan protest in Delhi. There is no mask, social distance, but still they are there.

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