Migrant workers move in packed buses | Photo: Praveen Jain | ThePrint
Migrant workers move in packed buses | Photo: Praveen Jain | ThePrint
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As the brouhaha over the supposed dangers of the coronavirus reaches fever pitch, it is necessary to put things into perspective. There are too many alarmist global projections about Indian deaths due to Covid-19. But these ignore several factors that are unique to India.

My intention is to use information, particularly through data, to produce some reassuring insights with respect to India. I am propelled by the fact that many people, especially those on social media, have begun to collectively express a great deal of anxiety, centered on the rising number of infected cases and even deaths.


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Model vs model 

First and foremost we need to debunk much of what the mathematical models are telling us. Models often do not agree with each other even when it comes to a small-sized country such as the UK where some experts at Oxford University are challenging the predictions of the Imperial College model.

In any case, Imperial College had to revise its model within two weeks of making it public. If this is what happens in the context of the UK, a country with a comparatively very small population, I am not sure as to how we can be so confident about a complex scenario like the one that exists in India.

The Center For Disease Dynamics, or the CDDEP model seems to predict that in a worst-case scenario, India may be headed for at least millions of infections, and a large number of deaths. Even if a model were to somehow take into account the need to incorporate corrections along the way, it shall necessarily fail–at least in the Indian context–for some glaring reasons.

Hence, I am staking my reputation as a mathematician, howsoever modest it be, when I state that no model can predict the outcome in India or the US in accurate fashion.


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Why no prediction qualifies for India

In the Indian context, the number of variables is so large, that a one-size-fits-all model shall not work.

For instance, I have not seen a single model that could anticipate the huge outbreak of migrant movements that have suddenly taken place in the last few days in India. I cannot see how this migration shall necessarily lead to an exponential growth in the number of infections. By all accounts, these migrants are young and have moved out from largely rural areas or slums where the carriers of the infection, were not present in any significant numbers.

This could be due to the fact that the first wave of infections into India happened through travellers returning from abroad. They would not be frequenting habitats that are peculiar to the migrants of Uttar Pradesh and Bihar. So, for all that we know, the migrants may not even have been infected much. But, if they are carrying infected numbers in a significant way, it may lead to herd immunity amongst them. This, simply put, means that a significant majority of the migrants could become immune to the virus altogether. This possible result will then be due to them having been infected in very large numbers during the stage when they were congregating in such close proximity to each other. In that event they shall reach a stage of immunity in the days to come.

In any case it is not clear how their sudden and unhindered intermingling in large numbers shall affect the rate of infection of the general population.


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Demographic dividend for India

Another reason why a western model shall likely fail in the Indian context is due to India’s demographic distribution. All data worldwide clearly indicates that the coronavirus infection hits the elderly in a truly virulent manner. The young, too, have been infected in Italy where 25.7 per cent of the infected population is in the 19-50 years age bracket, and in France, where 30 per cent of the infected population is in the 15-44 years age group.

Yet, the deaths in both these badly-affected nations have occurred in overwhelming numbers in the elderly. In Italy, 74.2 per cent of the deaths are in the age group of 70 years and above and in France, 79 per cent of the deaths are in the age group of 75 and above. In other words, even if the young get infected, their survival rate is much higher.


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India’s lessons from Iran

Let us look at some data on Iran. I find that none of the so-called mathematical models have even ventured to model the situation on Iran. Although Iran has suffered much, there are several valuable lessons and insights from Iran for India.

Let me first assert that Iran, which has been badly handicapped because of the sanctions, has actually fared far better than France, Italy and Spain. This is despite the fact that Iran’s population is a little larger than that of the above three European nations and health facilities in the country by far much poorer than in any of these three nations. The number of deaths in Iran is way below these nations. At the time of writing, Iran has had a death rate of 6.5 per cent as opposed to 11.3 per cent for Italy and 6.8 per cent for France.

An even more important measure of Iran’s situation not being as grim as is being made out is the fact that the death curve has been quite similar–for comparable timelines–to that of China, and it is beginning to reach the point where China had begun to control the deaths. Actually, for the last four days, the number of deaths in Iran has been steadily declining.

Let me also add that Iran had not implemented the severe lockdown measures that China had put in place. It has consistently allowed its citizens more freedom for social movements and has only recently started debating a lockdown.

This brings us to the important: what is it that is working for Iran? And it is here that I venture to make a claim. Iran’s demographic distribution is working in its favour. It has a fairly young population. Its median age is 32 years and 38 per cent of its population is below 24 years of age. Actually, almost 49 per cent of its population is in the age group of 25-54 years. This has worked to the advantage of Iran. I must add that this does not take away from the heroic work that health care workers in Iran, Italy, France and other nations are doing.


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Age is a key factor

Of course, I am at no stage implying that age is the sole factor. However, from all of the above data for France, Italy and Iran, I do believe that the age distribution of a population can be a very important factor if not the most important factor.

And this brings me to India. As things stand, India has a very young population. Its median age is 28.4 years. The actual data runs somewhat like this: 44.7 per cent of the population is below 25 years of age and 41.24 per cent of the population is in the age group of 25-54 years. So altogether, more than 85 per cent of India’s population is below 54 years of age.

Based on the data as analysed for France, Italy and Iran, India’s young are likely to act as a bulwark against the virus. It seems likely that this shall keep the death rates very, very, low indeed. India, with its young population coupled with the lockdown, shall come out of the crisis sooner and better than many European nations.

This does not mean that the infection rates shall necessarily be low. We may get fairly high infection rates. I must also mention that there is no reliable data for infection rates at the global level.

What seems clear is that the death rates for India shall be very low and to my mind that is the most important parameter that should be used to gauge the situation.

However, I am compelled to add, based on the considerable data that I have—a small but well-distributed random, anecdotal sample—that even the infection rates are, as yet, way below most nations.

I urge the Modi government to keep testing small, random samples through well-designed experiments to keep getting regular inputs on what is happening in the nation. The government ask everyone to wear masks whenever they step out. If high quality masks are not available, let people wear homemade masks. There are many reasons for that and one of them is that people may stop spitting.

I end with the fond hope and fervent prayer that India shall do well.

The author is the former vice-chancellor of University of Delhi, a distinguished mathematician and an educationist. Views are personal.

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8 COMMENTS

  1. A very balanced, well researched and logical article.
    Although I am reading this piece almost a fortnight after it was written, I would tend to agree on most points, though only time will endorse the accuracy of this prediction.
    And yes, while I have noticed a distinct bias or slant in several articles in The Print, I must admit that this is one of those rare and notable exceptions and the author deserves my respect and commendation.

  2. Mr Dinesh Singh has compared the death rate of European nations with that of Iran and China. This reasoning seems very logically but should have a caveat. While its very difficult to fake or suppress data in developed countries its always questionable when it comes to theocratic, dictatorial and communist regimes.

  3. It cannot be predicted But yes the actions taken by the PM Mr. Narender Modi and followed by almost all Chief Minsters is really commendable which will help the country to come out of this Corona Virus problem. I also worked on the data so far, as per me the number of patients would be under control after 8th of April provided Lockdown is adhered properly by all Vertically & Horizontally & behave like Indian Citizens.
    Some Muslim groups, those who believe that they cannot be victim is a big risk factor, many deaths would happen of them particularly above the 55 years of age-group.
    We all must behave properly till 14th of April and should maintain distance and all possible precautions as suggested by the Govt. After 14th April no school & colleges should be opened for first two weeks & elderly people should also stay at home only. Only basic needs related and essential items related works should open. Only phase wise opening will help India.
    We all must respect Doctors & Nurses, Police staff, Vendors providing essential goods and all other staff members helping us to maintain the balance at all levels.

  4. No single model can predict complex outcomes of an epidemiological. However incorporating India specific deviations, we can arrive at reasonable predictions which are essential to make a viable response strategy.

  5. “I urge the Modi government to keep testing small, random samples through well-designed experiments to keep getting regular inputs on what is happening in the nation.” <- one of the most savviest approaches; the author is correct.

    However eloquently the author describes the resilience of the younger demographic, they forget that India's socio-cultural milieu is such that those asymptomatic carriers interact more with their parents and grandparents as compared to some other cultures.

    It's also not entirely true that 'young' people are resistant to symptoms. 50 percent of the ICU beds in the US she example are occupied with young people. They will likely survive, but will occupy beds for a long time. What happens when these beds run out? The second or third cohort may not have adequate support.

    No doubt we will find out in due course, but India's resilience may not be just age related. It may have something to do with more resilient immune systems too.

  6. If a forecasting or prediction model can’t be validated using the actual data, it’s a mere deception model often aimed at blowing the propaganda out of proportion. Librandu economists will go to any extent to manufacture fake data and feed their deception models to churn garbage in garbage out. To give respectability to these deception models, it’s easy for librandus to use the seal of famous universities and research institutions. They are so shameless that even after being exposed repeatedly they continue in missionary ways. Time has come to legally disarm them and quarantine their activities.

    • Why so butt hurt Dev? Whole article talks about one thing and you talk about something else altogether? May be if you get your head out of your a$$, you may feel better.

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