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

在印度,新冠的真正死亡人数到底有多大?

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.

印度官方发布的新冠数据,严重低估了印度的真实情况。上周,印度创下了大流行期间超越所有国家的最大的每日死亡人数,这一数字很可能仍被低估了。

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.

由于记录保存不佳而且缺乏广泛的测试,因此很难清楚地了解印度的感染总数。估计真实的死亡人数需要第二层推断,这取决于最终死亡的感染者所占的比例。

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.

纽约时报与十多位专家协商,分析了印度的病例和死亡人数,以及大规模抗体测试的结果,得出了几个关于印度糟糕情况的可能估计。

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.

估计中最好的情况,感染和死亡人数也远远超过官方数字。最糟糕的情况显示出数百万死亡人数——这在世界上任何地方都是最灾难性的损失。



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

印度官方发布的新冠统计数据显示,截至5月24日,印度共有26948800例病例和307231例死亡。

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。
原创翻译:龙腾网 http://www.ltaaa.cn 转载请注明出处


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.

另外,其他研究者也发现,人们缺少新冠测试;很多家庭也不愿意说他们所爱的人死于新冠;而印度保存重要记录的制度也非常不稳定。即使在新冠之前,印度也有大约五分之四的死亡病例还没有接受医学调查。

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

为了得出更合理的估算印度新冠病毒感染数和死亡数,我们使用了三个全国性抗体测试的数据,我们称这三个数据为血清调查。

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.

在每一次血清调查中,都需要一部分人(印度14亿人口中约有3万人)接受新冠抗体检测。一旦研究人员计算出那些血液中含有抗体的人群所占的比例,他们就推断出这个被称为血清流行率的数据点,从而得出整个人群的估计值。

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.

抗体测试提供了一种方法来纠正官方记录,可以更好的估计总感染和死亡人数。原因很简单:几乎每个感染了新冠病毒的人都会产生抗体来对抗它,留下调查可以发现的感染痕迹。

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.”

不过,温伯格博士说,这些调查提供了一种新的方法来计算更现实的死亡数字。“这给了我们一个起点,”他说我认为这样的测算可以给估计值设置一些界限。”

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.

即使是对大流行的真实死亡人数最保守的估计,感染人数也比官方报告显示的要高出数倍。我们的第一个最好测算结果是假设真实感染人数是官方记录病例数的15倍。感染致死率,或者说已死亡的感染者的比例为0.15%。这两个数字都在我们从专家那里收集的估计数的最低值。

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

其结果是死亡人数大约是目前报道的两倍。


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.

我们如何估计案例乘数
到目前为止,印度已经在Covid-19大流行期间进行了三次全国血清调查。这三人都发现,真正的感染人数大大超过了当时的确诊病例数。


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.

在每次调查结果公布时,他们都表示感染率比印度在大流行期间报告的病例数高出13.5至28.5倍。自上一次血清学调查完成以来,漏报的严重程度可能有所增加或减少,但如果情况保持稳定,这将表明印度近一半的人口可能感染了该病毒。
原创翻译:龙腾网 http://www.ltaaa.cn 转载请注明出处


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.

Shioda博士说,即使是血清调查中发现的大乘数也可能依赖于对感染真实数量的低估。她说,原因是感染后几个月抗体浓度下降,使其更难检测。她说,如果这些调查能够发现所有事实上已经被感染的人,这个数字可能会更高。

“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.”

“那些不久前被感染的人可能还没有被这个数字抓获,”Shioda博士说:“因此,这可能低估了受感染人数的真实比例。”

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.

然而,与本文联系的几乎所有研究人员一样,Shioda博士说,这一估算方法提供了一个很好的方法,可以了解印度可能死亡人数的广泛范围。

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

我们是怎么估计死亡率的

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.

已经公布的许多感染死亡率估计数是在印度最近一波感染之前计算出来的,因此,在考虑到最近一波感染后,总的感染死亡数可能比实际情况更高。这一比率也因年龄的不同而有很大的差异:通常情况下,这一指标针对的是老年人口。印度的人口偏年轻,平均年龄在29岁左右,这可能意味着印度的人口出生率低于人口老龄化程度较高的国家。

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.

在感染致死率和血清阳性率方面,该国也存在极大的差异。根据收集世界各地血清调查数据的网站SeroTracker的数据,除三个国家级别的血清调查外,印度在地方和地区级也进行了60多次血清调查。

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。”
原创翻译:龙腾网 http://www.ltaaa.cn 转载请注明出处


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.

就像前文所提到的,在印度这样一个大国,感染致死率的微小波动也可能意味着数十万人死亡的差异。

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.

尽管估计数可能随着时间和地区的不同而有所不同,但有一点是毋庸置疑的:印度的新冠感染数比官方数字所显示的要严重得多。