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PreprintCited by 42COVID-19 epidemiological studiesData-Driven Disease SurveillanceStatistical Methods in Epidemiology

Robustness and bias of European excess death estimates in 2020 under varying model specifications

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Schöley, Jonas·2021·medRxiv
DOI 10.1101/2021.06.04.21258353
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Abstract

Various procedures are in use to calculate excess deaths during the ongoing COVID-19 pandemic. Using weekly death counts from 20 European countries, we evaluate the robustness of excess death estimates to the choice of model for expected deaths and perform a cross-validation analysis to assess the error and bias in each model’s predicted death counts. We find that the different models produce very similar patterns of weekly excess deaths but disagree substantially on the level of excess. While the exact country ranking along percent excess death in 2020 is sensitive to the choice of model the top and bottom ranks are robustly identified. On the country level, the 5-year average death rate model tends to produce the lowest excess death estimates, whereas high excess deaths are produced by the popular 5-year average death count and Euromomo-style Serfling models. Cross-validation revealed these estimates to be biased under a causal interpretation of “expected deaths had COVID-19 not happened.”

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Crossref · 10.1101/2021.06.04.21258353

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  • The completeness of observed deaths and the consistency in quality as well as construct validity for covariates used in the regression model impact the accuracy of empirical estimates of excess and the robustness of the predictive model.

    “The completeness of observed deaths and the consistency in quality as well as construct validity for the various covariates used in the regression model, impact the accuracy of the empirical estimates of excess and the robustness of the predictive model for deriving excess for countries in which deaths have not been observed16.”

    From The WHO estimates of excess mortality associated with the COVID-19 pandemic (2023) · cites this paper as [16]

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Authors
Schöley, J.
Affiliations
University of Southern Denmark (DK)
Corresponding author
Schöley, Jonas
ORCID
Schöley, Jonas
Venue
medRxiv
Publisher
openRxiv
Published
2021-06-09
DOI
10.1101/2021.06.04.21258353
OpenAlex
W3169577509
Cited by
42
References
23
Citations by year
2026: 4 · 2025: 3 · 2024: 12 · 2023: 12 · 2022: 11
Type
posted content
Language
en
Open access
Licence
cc-by
Locations
medRxiv (acceptedVersion, cc-by)
Topics
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Health Sciences › Medicine › Epidemiology › Data-Driven Disease Surveillance
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords
excess mortality, COVID-19 pandemic, model robustness, estimation bias, cross-validation, European countries

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