A radically simple way to monitor life expectancy

Ilya Kashnitsky, Alexei Raksha, J. Aburto, Jonas Schöley, J. Vaupel
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Abstract

NOTE: this is an early registration of the research idea and findings in form of slides for a talk presented at EAPS Mort workshop on 2021-09-22 (video: https://youtu.be/rOndHnuajH4?t=2370)Period Life Expectancy is the key summary measure of current mortality. Elimination of the direct influence of population age structure allows to meaningfully compare mortality levels and changes across the populations and over time. Calculation of life expectancy demands high quality detailed data on death and population counts disaggregated by sex and age. Such data is only available for the more developed countries. Moreover, even in the most developed countries, it becomes available with a considerable time lag. And for the majority of countries across the world timely and high quality deaths statistics is not available. In situations of mortality shocks such as the COVID–19 pandemic near real time mortality level comparisons are crucial.Building on the studied regularities of human mortality, we offer a method of reliable life expectancy short-casting based only on the time series of its previous values and the time series of total deaths counts observed in the population, not disaggregated by sex and age. The radical simplicity of the method allows to monitor changes in life expectancy in near real time, if time disaggregated (daily, weekly, or monthly) total death counts are available.
一个非常简单的方法来监测预期寿命
注:这是研究理念和发现的早期注册,以幻灯片的形式呈现在EAPS Mort研讨会上,20121-09-22(视频:https://youtu.be/rOndHnuajH4?t=2370)Period)预期寿命是当前死亡率的关键总结指标。消除人口年龄结构的直接影响,可以有意义地比较不同人口和不同时期的死亡率水平和变化。计算预期寿命需要关于死亡和按性别和年龄分列的人口数量的高质量详细数据。只有较发达的国家才有这种数据。此外,即使在最发达的国家,也有相当长的时间滞后。对于世界上大多数国家来说,没有及时和高质量的死亡统计数据。在COVID-19大流行等死亡率冲击的情况下,近乎实时的死亡率水平比较至关重要。在研究人类死亡率规律的基础上,我们提供了一种可靠的预期寿命短铸方法,该方法仅基于其先前值的时间序列和在人群中观察到的总死亡人数的时间序列,而不是按性别和年龄分类。如果有按时间分类(每日、每周或每月)的总死亡人数,该方法极为简单,可以近乎实时地监测预期寿命的变化。
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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