Using Household Rosters from Survey Data to Estimate All-cause Mortality during COVID in India

A. Malani, Sabareesh Ramachandran
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引用次数: 8

Abstract

Official statistics on deaths in India during the COVID pandemic are either incomplete or are reported with a delay. To overcome this shortcoming, we estimate excess deaths in India using the household roster from a large panel data set, the Consumer Pyramids Household Survey, which reports attrition from death. We address the problem that the exact timing of death is not reported in two ways, via a moving average and differencing monthly deaths. We estimate roughly 4.5 million (95% CI: 2.8M to 6.2M) excess deaths over 16 months during the pandemic in India. While we cannot demonstrate causality between COVID and excess deaths, the pattern of excess deaths is consistent with COVID-associated mortality. Excess deaths peaked roughly during the two COVID waves in India;the age structure of excess deaths is right skewed relative to baseline, consistent with COVID infection fatality rates;and excess deaths are positively correlated with reported infections. Finally, we find that the incidence of excess deaths was disproportionately among the highest tercile of income-earners and was negatively associated with district-level mobility.
利用调查数据中的住户名册估计印度COVID期间的全因死亡率
关于印度在COVID大流行期间死亡人数的官方统计数据要么不完整,要么报告延迟。为了克服这一缺点,我们使用来自大型面板数据集“消费者金字塔家庭调查”的家庭名册来估计印度的超额死亡人数,该调查报告了死亡减员。我们解决了没有以两种方式报告确切死亡时间的问题,即通过移动平均和差异月度死亡。我们估计,在印度大流行期间的16个月内,大约有450万(95%置信区间:280万至620万)额外死亡。虽然我们无法证明COVID与超额死亡之间存在因果关系,但超额死亡的模式与COVID相关的死亡率是一致的。在印度的两次COVID浪潮期间,超额死亡人数大致达到峰值;超额死亡人数的年龄结构相对于基线右倾斜,与COVID感染死亡率一致;超额死亡人数与报告的感染人数呈正相关。最后,我们发现,在收入最高的人群中,超额死亡的发生率不成比例,并且与地区一级的流动性呈负相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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