{"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":2,"journal":{"name":"ACS Applied Bio Materials","volume":"7 1","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/biomethods/bpae031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications.
The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.