Just How Big Could India’s True Covid Toll Be?


The official Covid-19 figures in India grossly understate the true scale of the pandemic in the country. Last week, India recorded the largest daily death toll for any country during the pandemic — a figure that is most likely still an undercount.


Even getting a clear picture of the total number of infections in India is hard because of poor record-keeping and a lack of widespread testing. Estimating the true number of deaths requires a second layer of extrapolation, depending on the share of those infected who end up dying.


In consultation with more than a dozen experts, The New York Times has analyzed case and death counts over time in India, along with the results of large-scale antibody tests, to arrive at several possible estimates for the true scale of devastation in the country.


Even in the least dire of these, estimated infections and deaths far exceed official figures. More pessimistic ones show a toll on the order of millions of deaths — the most catastrophic loss anywhere in the world.


India’s official Covid statistics report 26,948,800 cases and 307,231 deaths as of May 24.


Even in countries with robust surveillance during this pandemic, the number of infections is probably much higher than the number of confirmed cases because many people have contracted the virus but have not been tested for it. On Friday, a report by the World Health Organization estimated that the global death toll of Covid-19 may be two or three times higher than reported.

因为许多人感染了病毒,但没有进行病毒检测,所以即使在本次大流行期间有严格监测的国家,感染人数也可能远远高于确诊病例的数量。上周五,世界卫生组织发布的一份报告 指出全球新冠的死亡人数可能是报道的两到三倍。

The undercount of cases and deaths in India is most likely even more pronounced, for technical, cultural and logistical reasons. Because hospitals are overwhelmed, many Covid deaths occur at home, especially in rural areas, and are omitted from the official count, said Kayoko Shioda, an epidemiologist at Emory University. Laboratories that could confirm the cause of death are equally swamped, she said.

由于技术、文化和后勤方面的原因,印度病例和死亡人数不足的情况很可能更加明显。埃默里大学的流行病学家Kayoko Shioda说,由于医院人满为患,许多冠状病毒导致的死亡发生在家里,特别是农村地区,这些在官方统计中不会被记录。她说,能够确认死因的实验室同样疲于应对。
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Additionally, other researchers have found, there are few Covid tests available; often families are unwilling to say that their loved ones have died of Covid; and the system for keeping vital records in India is shaky at best. Even before Covid-19, about four out of five deaths in India were not medically investigated.


To arrive at more plausible estimates of Covid infections and deaths in India, we used data from three nationwide antibody tests, called serosurveys.


In each serosurvey, a subset of the population (about 30,000 of India’s 1.4 billion people) is examined for Covid-19 antibodies. Once researchers have figured out the share of those people whose blood is found to contain antibodies, they extrapolate that data point, called the seroprence, to arrive at an estimate for the whole population.


The antibody tests offer one way to correct official records and arrive at better estimates of total infections and deaths. The reason is simple: Nearly everyone who contracts Covid-19 develops antibodies to fight it, leaving traces of the infection that the surveys can pick up.


Even a wide-scale serosurvey has its limitations, said Dan Weinberger, an associate professor of epidemiology at the Yale School of Public Health. India’s population is so large and diverse that it’s unlikely any serosurvey could capture the full range.

耶鲁大学公共卫生学院(Yale School of Public Health)流行病学副教授丹·温伯格(danweinberger)说,即使是大规模的血清调查也有其局限性。印度的人口如此庞大和多样化,任何血清调查都不可能捕捉到全部范围。

Still, Dr. Weinberger said, the surveys provide a fresh way to calculate more realistic death figures. “It gives us a starting point,” he said. “I think that an exercise like this can put some bounds on the estimates.”


Even in the most conservative estimates of the pandemic’s true toll, the number of infections is several times higher than official reports suggest. Our first, best-case scenario assumes a true infection count 15 times higher than the official number of recorded cases. It also assumes an infection fatality rate, or I.F.R. — the share of all those infected who have died — of 0.15 percent. Both of these numbers are on the low end of the estimates we collected from experts.


The result is a death toll roughly double what’s been reported to date.


The latest national seroprence study in India ended in January, before the current wave, and estimated roughly 26 infections per reported case. This scenario uses a slightly lower figure, in addition to a higher infection fatality rate of 0.3 percent — in line with what has been estimated in the United States at the end of 2020. In this scenario, the estimated number of deaths in India is more than five times the official reported count.

印度最新的全国血清阳性率研究于今年1月结束,也就是本次疫情爆发前,估计每个报告病例约有26例感染。这预测使用了一个略低的数字,除了0.3%的较高感染死亡率外,——与美国2020年底的估算值一致 。在这种情况下,印度估计的死亡人数是官方报告的五倍多。

“As with most countries, total infections and deaths are undercounted in India,” said Dr. Ramanan Laxminarayan, director of the Center for Disease Dynamics, Economics & Policy. “The best way to arrive at the most likely scenario would be based on triangulation of data from different sources, which would indicate roughly 500 to 600 million infections.”

“和大多数国家一样,印度的总感染率和死亡人数被低估了,”疾病动力学、经济与政策中心主任Ramanan Laxminarayan博士说:得出最有可能发生的情况的最佳方法是基于来源不同的数据进行三角测量,这表明大约有5亿至6亿人感染。”

This scenario uses a slightly higher estimate of true infections per known case, to account for the current wave. The infection fatality rate is also higher — double the rate of the previous scenario, at 0.6 percent — to take into account the tremendous stress that India’s health system has been under during the current wave. Because hospital beds, oxygen and other medical necessities have been scarce in recent weeks, a greater share of those who contract the virus may be dying, driving the infection fatality rate higher.

这种情况使用了一个稍微高一点的估计值来解释当前的流行趋势。考虑到印度卫生系统在当前这波浪潮中承受的巨大压力,感染致死率也更高,是前一种情况的两倍,为0.6%。因为医院的病床、氧气等医疗必需品都被抢购一空 ,感染病毒的人中有更大的一部分可能会死亡,从而导致感染致死率更高。

Because there are two different unknowns, there is a wide range of plausible values for the true infection and death counts in India, Dr. Shioda said. “Public health research usually provides a wide uncertainty range,” she said. “And providing that kind of uncertainty to readers is one of the most important things researchers do.”
Explore possible scenarios for yourself in the interactive above.

“因为有两个不同的未知因素,所以在印度,真实的感染和死亡人数有很多合理的数值。”Shioda 博士说:“公共卫生研究通常有很大的不确定性范围。”向读者提供这种不确定性是研究人员所做的最重要的事情之一。”

How we estimated case multipliers
So far, India has conducted three national serosurveys during the Covid-19 pandemic. All three have found that the true number of infections drastically exceeded the number of confirmed cases at the time in question.


At the time the results of each survey were released, they indicated infection prence between 13.5 and 28.5 times higher than India’s reported case counts at those points in the pandemic. The severity of underreporting may have increased or decreased since the last serosurvey was completed, but if it has held steady, that would suggest that almost half of India’s population may have had the virus.

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Dr. Shioda said that even the large multipliers found in the serosurveys may rely on undercounts of the true number of infections. The reason, she said, is that the concentration of antibodies drops in the months after an infection, making them harder to detect. The number would probably be higher if the surveys were able to detect everyone who has, in fact, been infected, she said.


“Those people who were infected a while ago may have not been captured by this number,” Dr. Shioda said. “So this is probably an underestimate of the true proportion of the population that has been infected.”


Like nearly all researchers contacted for this article, however, Dr. Shioda said the estimator provided a good way to get a sense of the wide range of possible death tolls in India.


Jeffrey Shaman, an epidemiologist at Columbia University, said that the “slider,” or sliding calculator, is useful for “exploring the consequences” of different values for the infection fatality ratio and the ratio of the real number of infections to confirmed cases. Those are “the two measures that need to be estimated,” Dr. Shaman said.

哥伦比亚大学的流行病学家Jeffrey Shaman说,“滑动计算器”有助于“探索”感染致死率和实际感染人数与确诊病例之比不同值的后果。Shaman说,感染致死率和实际感染人数是“需要估计的两个指标”。

How we estimated death rates


Many of the infection fatality rate estimates that have been published were calculated before the most recent wave in India, so it could be that the overall I.F.R. is actually higher after accounting for the most recent wave. The rate also varies greatly by age: Typically, the measure rises for older populations. India’s population skews young — its median age is around 29 — which could mean I.F.R. is lower there than in countries with larger older populations.


There is also extreme variability within the country in terms of both infection fatality rate and seroprence. In addition to the three national serosurveys, there have been more than 60 serosurveys done at the local and regional level, according to SeroTracker, a website that compiles serosurvey data from around the world.


In a paper examining infection rates using serosurvey data from three locations in India, Dr. Paul Novosad, an associate professor of economics at Dartmouth College, found huge variability depending on the population being sampled. “We found that age-specific I.F.R. among returning lockdown migrants was much higher than in richer countries,” he said. “In contrast, we found a much lower first-wave I.F.R. than richer countries in the Southern states of Karnataka and Tamil Nadu.”

在 一篇论文 达特茅斯学院(Dartmouth College)经济学副教授保罗诺沃萨德(Paul Novosad)博士利用印度三个地区的血清学调查数据研究了感染率,发现根据抽样人群的不同,感染率存在巨大的差异他说:“我们发现,在返回后被封锁的居民中,印度特定年龄段的感染死亡率比富裕国家高得多。 我们又发现,南部卡纳塔克邦和泰米尔纳德邦的第一波感染死亡率比富裕国家低得多。”
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In a country as large as India, even a small fluctuation in infection fatality rates could mean a difference of hundreds of thousands of deaths, as seen in the estimates above.


While estimates can vary over time and from region to region, one thing is clear beyond all doubt: The pandemic in India is much larger than the official figures suggest.