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Mortality in Germany during the COVID-19 Pandemic

Author

Listed:
  • Alois Pichler

    (Faculty of Mathematics, University of Technology Chemnitz, 09111 Chemnitz, Germany
    These authors contributed equally to this work.)

  • Dana Uhlig

    (Faculty of Mathematics, University of Technology Chemnitz, 09111 Chemnitz, Germany
    These authors contributed equally to this work.)

Abstract

Is there sufficient scientific evidence for excess mortality caused by COVID-19? The German population, similar to the population of many other countries, is subject to fluctuations caused by multiple factors, including migration and aging. COVID-19 is one additional factor, superposing natural or seasonal mortality fluctuations. To give scientific evidence for excess mortality caused by COVID-19, it is essential to employ appropriate statistical tools. This study develops a score indicating excess mortality and studies its evolution over time. Applied to data provided by governmental authorities, the indicator discloses, without relating to causes of death explicitly, excess mortality at the end of 2020, in 2021, and in 2022. In addition, the indicator confirms that COVID-19 particularly impacted the elderly segment of the population.

Suggested Citation

  • Alois Pichler & Dana Uhlig, 2023. "Mortality in Germany during the COVID-19 Pandemic," IJERPH, MDPI, vol. 20(20), pages 1-11, October.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:20:p:6942-:d:1263093
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    References listed on IDEAS

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    1. Andrew Cairns & David Blake & Kevin Dowd & Guy Coughlan & David Epstein & Alen Ong & Igor Balevich, 2009. "A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States," North American Actuarial Journal, Taylor & Francis Journals, vol. 13(1), pages 1-35.
    2. Zeng, Hongtao & Lan, Tian & Chen, Qiming, 2016. "Five and four-parameter lifetime distributions for bathtub-shaped failure rate using Perks mortality equation," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 307-315.
    3. Mariantonietta Pisaturo & Antonio Russo & Viraj Pattapola & Roberta Astorri & Paolo Maggi & Fabio Giuliano Numis & Ivan Gentile & Vincenzo Sangiovanni & Annamaria Rossomando & Valeria Gentile & Giosue, 2022. "Clinical Characterization of the Three Waves of COVID-19 Occurring in Southern Italy: Results of a Multicenter Cohort Study," IJERPH, MDPI, vol. 19(23), pages 1-12, November.
    4. Marília R. Nepomuceno & Ilya Klimkin & Dmitri A. Jdanov & Ainhoa Alustiza‐Galarza & Vladimir M. Shkolnikov, 2022. "Sensitivity Analysis of Excess Mortality due to the COVID‐19 Pandemic," Population and Development Review, The Population Council, Inc., vol. 48(2), pages 279-302, June.
    5. Joel E. Cohen & Christina Bohk & Roland Rau, 2018. "Gompertz, Makeham, and Siler models explain Taylor's law in human mortality data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 38(29), pages 773-842.
    6. S. J. Richards, 2012. "A handbook of parametric survival models for actuarial use," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2012(4), pages 233-257.
    7. Trifon Missov & Adam Lenart & Laszlo Nemeth & Vladimir Canudas-Romo & James W. Vaupel, 2015. "The Gompertz force of mortality in terms of the modal age at death," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 32(36), pages 1031-1048.
    8. Juan Blas Pérez-Gilaberte & Natalia Martín-Iranzo & José Aguilera & Manuel Almenara-Blasco & María Victoria de Gálvez & Yolanda Gilaberte, 2023. "Correlation between UV Index, Temperature and Humidity with Respect to Incidence and Severity of COVID 19 in Spain," IJERPH, MDPI, vol. 20(3), pages 1-13, January.
    9. Mohamed El Fatini & Mohamed El Khalifi & Richard Gerlach & Roger Pettersson, 2021. "Bayesian forecast of the basic reproduction number during the Covid-19 epidemic in Morocco and Italy," Mathematical Population Studies, Taylor & Francis Journals, vol. 28(4), pages 228-242, October.
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