{"title":"超额死亡率 \"的含义和预测:1965年至2021年欧盟统计局31个国家Covid死亡率数据与Covid前死亡率数据的比较","authors":"Bernhard Gill, Theresa Kehler, Michael Schneider","doi":"10.1093/biomethods/bpae031","DOIUrl":null,"url":null,"abstract":"\n Determining \"excess mortality\" makes it possible to compare the burden of disasters between countries and over time, and thus also to evaluate the success of mitigation measures. However, the debate on Covid-19 has exposed that calculations of excess mortalities vary considerably depending on the method and its specification. Moreover, it is often unclear what exactly is meant by \"excess mortality\". We define excess mortality as the excess over the number of deaths that would have been expected counter-factually, ie without the catastrophic event in question. Based on this definition, we use a very parsimonious calculation method, namely the linear extrapolation of death figures from previous years to determine the excess mortality during the Covid-19 pandemic. But unlike most other literature on this topic, we first evaluated and optimised the specification of our method using a larger historical data set in order to identify and minimise estimation errors and biases. The result shows that excess mortality rates in the literature are often inflated. Moreover, they would have exhibited considerable excess mortalities in the period before Covid-19, if this value had already been of public interest at that time. Three conclusions can be drawn from this study and its findings: 1) All calculation methods for current figures should first be evaluated against past figures. 2) To avoid alarm fatigue, for mass media and policy communication thresholds should be introduced which would differentiate between \"usual fluctuations\" and \"remarkable excess\". 3) Statistical offices could provide more realistic estimates.","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Meaning and prediction of \\\"excess mortality\\\": A comparison of Covid- and pre-Covid mortality data in 31 Eurostat countries from 1965 to 2021\",\"authors\":\"Bernhard Gill, Theresa Kehler, Michael Schneider\",\"doi\":\"10.1093/biomethods/bpae031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Determining \\\"excess mortality\\\" makes it possible to compare the burden of disasters between countries and over time, and thus also to evaluate the success of mitigation measures. However, the debate on Covid-19 has exposed that calculations of excess mortalities vary considerably depending on the method and its specification. Moreover, it is often unclear what exactly is meant by \\\"excess mortality\\\". We define excess mortality as the excess over the number of deaths that would have been expected counter-factually, ie without the catastrophic event in question. Based on this definition, we use a very parsimonious calculation method, namely the linear extrapolation of death figures from previous years to determine the excess mortality during the Covid-19 pandemic. But unlike most other literature on this topic, we first evaluated and optimised the specification of our method using a larger historical data set in order to identify and minimise estimation errors and biases. The result shows that excess mortality rates in the literature are often inflated. Moreover, they would have exhibited considerable excess mortalities in the period before Covid-19, if this value had already been of public interest at that time. Three conclusions can be drawn from this study and its findings: 1) All calculation methods for current figures should first be evaluated against past figures. 2) To avoid alarm fatigue, for mass media and policy communication thresholds should be introduced which would differentiate between \\\"usual fluctuations\\\" and \\\"remarkable excess\\\". 3) Statistical offices could provide more realistic estimates.\",\"PeriodicalId\":36528,\"journal\":{\"name\":\"Biology Methods and Protocols\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biology Methods and Protocols\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/biomethods/bpae031\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biology Methods and Protocols","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/biomethods/bpae031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
Meaning and prediction of "excess mortality": A comparison of Covid- and pre-Covid mortality data in 31 Eurostat countries from 1965 to 2021
Determining "excess mortality" makes it possible to compare the burden of disasters between countries and over time, and thus also to evaluate the success of mitigation measures. However, the debate on Covid-19 has exposed that calculations of excess mortalities vary considerably depending on the method and its specification. Moreover, it is often unclear what exactly is meant by "excess mortality". We define excess mortality as the excess over the number of deaths that would have been expected counter-factually, ie without the catastrophic event in question. Based on this definition, we use a very parsimonious calculation method, namely the linear extrapolation of death figures from previous years to determine the excess mortality during the Covid-19 pandemic. But unlike most other literature on this topic, we first evaluated and optimised the specification of our method using a larger historical data set in order to identify and minimise estimation errors and biases. The result shows that excess mortality rates in the literature are often inflated. Moreover, they would have exhibited considerable excess mortalities in the period before Covid-19, if this value had already been of public interest at that time. Three conclusions can be drawn from this study and its findings: 1) All calculation methods for current figures should first be evaluated against past figures. 2) To avoid alarm fatigue, for mass media and policy communication thresholds should be introduced which would differentiate between "usual fluctuations" and "remarkable excess". 3) Statistical offices could provide more realistic estimates.