India’s Covid-19 fatality rates — low in south India, high among migrants
When the coronavirus disease (Covid-19) arrived in India, many feared that the health indicators of the population and under-resourced health care facilities would lead to high Covid-19 mortality. More than a year later, India is among the countries with lower than expected mortality rates from Covid-19, despite infection rates of over 50% in many parts of the country.
In a new study, we set out to use the best available data to measure the infection fatality rate from Covid-19 and how it varied across the country. Notably, most popular claims about India’s mortality rate have relied on an imperfect statistic called the case fatality rate (CFR). The CFR divides the number of positive Covid-19 tests by the number of Covid-19 deaths — but this measure almost always overstates the actual infection fatality rate, because so many people with mild symptoms are never even tested. Instead, we set out to measure the Infection Fatality Rate (IFR) — the probability that an individual who gets the coronavirus at a given age will die — which is a key input in thinking about vaccine planning and activity restriction.
But even such a basic statistic is not easily measured. Measuring IFR requires carefully designed studies that test for Covid-19 antibodies in random samples of thousands of people. Such seroprevalence studies have primarily been run in richer countries, but India has run a number of its own since the pandemic began. We combined data from major serostudies in Mumbai, Karnataka, and Tamil Nadu, and matched these to administrative reports of Covid-19 deaths in each location. We also used records from random samples of migrants returning to Bihar on special trains in response to the national lockdown; positively tested individuals were tracked, and we know how many of them died.
We focused in particular on age-specific fatality. It is widely known that Covid-19 is more severe for the elderly. We wanted to know how fatality in India compares with fatality in other countries, at the same age. This isolates anything special about the susceptibility of Indians to severe infection or access to healthcare.
Our calculations suggested that infection fatality rates were lower in many parts of India than in richer countries. Middle-aged men infected with Covid-19 were half as likely to die in Mumbai than in a sample of high-income countries, 88% less likely in Karnataka, and 96% less likely in Tamil Nadu.
It must be noted that under-reporting of Covid-19 deaths in India can explain some of this gap, but is very unlikely to explain all of it. Excess mortality in Mumbai was twice as high as the number of reported Covid-19 deaths — enough to close the IFR gap with richer countries. But in Tamil Nadu, Covid-19 deaths would have to be undercounted by a factor of 30 to explain the gap, suggesting that undercounting cannot be the whole story.
When we looked at migrants returning to Bihar, we found a starkly different story. The fatality rates among older positive-testing migrants was twice as high as in richer countries. Among younger migrants, it was even worse: over 1% of Covid-19-positive migrant men under the age of 49 died in the followup period, an age group with negligible mortality in other countries. The severe economic and physical distress during the arduous return journey, piled on top of their poorer baseline health may have made migrants highly vulnerable to death after infection. The same phenomenon could explain why mortality was higher in Mumbai than in the southern states — because Mumbai’s outbreak was concentrated among a poor slum population with poor health and worse access to care.
A final striking finding that emerged from our study was that the elderly in India faced a smaller relative mortality disadvantage than in other countries. Most of India’s mortality advantage occurred among those over the age of 60. Our study cannot explain why this was the case, but one explanation likely has to do with the types of people who make it to old age in India relative to in other countries. Many of the most vulnerable may already have died, leaving a relatively robust group of elderly survivors, who further may have immune systems strengthened by a lifetime of viral exposure.
We also do not know the exact reasons for the terrible mortality rates among returning migrants. After a year of economic crisis, it is crucial to identify patterns of economic distress that could raise vulnerability to severe infection. Another key puzzle is why infection fatality rates were so different in Mumbai, Karnataka, and Tamil Nadu.
As vaccines are disseminated, the end of this pandemic is hopefully in sight. Research on patterns of infection and mortality will be essential not only for current vaccination planning, but also to understand and prepare for the future pandemics that will surely emerge.
Paul Novosad is associate professor of economics at Dartmouth College. Rebecca Cai is a research associate at Development Data Lab. Anup Malani (University of Chicago), Vaidehi Tandel (IDFC Institute), and Sam Asher (Johns Hopkins University) also worked on this article.
The views expressed are personal.