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Estimates of excess mortality during the COVID-19 pandemic strongly depend on subjective methodological choices.
Kowall, Bernd; Stang, Andreas.
  • Kowall B; Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, Hufelandstr. 55, 45147, Essen, Germany. bernd.kowall@uk-essen.de.
  • Stang A; Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, Hufelandstr. 55, 45147, Essen, Germany.
Herz ; 48(3): 180-183, 2023 Jun.
Article in English | MEDLINE | ID: covidwho-2316226
ABSTRACT
Excess mortality is often used to assess the health impact of the COVID-19 pandemic. It involves comparing the number of deaths observed during the pandemic with the number of deaths that would counterfactually have been expected in the absence of the pandemic. However, published data on excess mortality often vary even for the same country. The reason for these discrepancies is that the estimation of excess mortality involves a number of subjective methodological choices. The aim of this paper was to summarize these subjective choices. In several publications, excess mortality was overestimated because population aging was not adjusted for. Another important reason for different estimates of excess mortality is the choice of different pre-pandemic reference periods that are used to estimate the expected number of deaths (e.g., only 2019 or 2015-2019). Other reasons for divergent results include different choices of index periods (e.g., 2020 or 2020-2021), different modeling to determine expected mortality rates (e.g., averaging mortality rates from previous years or using linear trends), the issue of accounting for irregular risk factors such as heat waves and seasonal influenza, and differences in the quality of the data used. We suggest that future studies present the results not only for a single set of analytic choices, but also for sets with different analytic choices, so that the dependence of the results on these choices becomes explicit.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Influenza, Human / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Herz Year: 2023 Document Type: Article Affiliation country: S00059-023-05166-6

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Influenza, Human / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Herz Year: 2023 Document Type: Article Affiliation country: S00059-023-05166-6