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COVID-19 in unequally ageing European regions

Author

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  • Kashnitsky, Ilya

    (Statistics Denmark)

  • Aburto, José Manuel

Abstract

The map presented in this brief note summarizes regional differences in population age structures between the NUTS-3 regions of Europe in the context of unequal age- and sex-specific death risks associated with the spread of the COVID-19 pandemic. Since older people are exposed to much higher death risks, older populations are expected to face much more difficult challenges coping with the pandemic. The urban/rural dimension turns out to be very important as the remote rural areas are also the oldest. In the map NUTS-3 regions of Europe are colored according to the deviation from European pooled estimate of the proportion of population at risk of death due to COVID-19. We assume that 5/6 of the populations get infected and experience age-specific infection-fatality ratios (IFRs) modelled by the Imperial College COVID-19 Response Team. We adjust IFRs by sex ratios of age-specific case-fatality ratios observed in the European countries that are included in the COVerAGE-DB. Thus, we effectively introduce a summary measure of population age structures focused on the most vulnerable to the pandemic. Such an estimate for the total European population is 1%. The map reflects the unequal population age structures rather than the precise figures on COVID-19 fatality. It is a case-if scenario that highlights the possible effect of the population age structures, a demographic perspective. This analysis clearly shows the contribution of regional differences in population age structures to the magnitude of the pandemic -- other things equal, we expect to see a four-fold variation in average regional infection-fatality ratios across Europe due only to differences in the population structures.

Suggested Citation

  • Kashnitsky, Ilya & Aburto, José Manuel, 2020. "COVID-19 in unequally ageing European regions," OSF Preprints abx7s_v1, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:abx7s_v1
    DOI: 10.31219/osf.io/abx7s_v1
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    Cited by:

    1. Bart Roelofs & Dimitris Ballas & Hinke Haisma & Arjen Edzes, 2022. "Spatial mobility patterns and COVID‐19 incidence: A regional analysis of the second wave in the Netherlands," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S1), pages 21-40, November.
    2. Marcos Díaz Ramírez & Paolo Veneri & Alexander C. Lembcke, 2022. "Where did it hit harder? Understanding the geography of excess mortality during the COVID‐19 pandemic," Journal of Regional Science, Wiley Blackwell, vol. 62(3), pages 889-908, June.
    3. Isaac Sasson, 2021. "Age and COVID-19 mortality: A comparison of Gompertz doubling time across countries and causes of death," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(16), pages 379-396.
    4. David A. Sánchez-Páez, 2022. "Effects of income inequality on COVID-19 infections and deaths during the first wave of the pandemic: Evidence from European countries," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 20(1), pages 85-106.
    5. Elkomy, Shimaa & Jackson, Tim, 2024. "WHO non-communicable diseases Global Monitoring Framework: Pandemic resilience in sub-Saharan Africa and Low-income Countries," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    6. Zaiga Krisjane & Maris Berzins & Janis Krumins & Elina Apsite‐Berina & Sindija Balode, 2023. "Uneven geographies: ageing and population dynamics in Latvia," Regional Science Policy & Practice, Wiley Blackwell, vol. 15(4), pages 893-908, May.
    7. Margarete Redlin, 2022. "Differences in NPI strategies against COVID-19," Journal of Regulatory Economics, Springer, vol. 62(1), pages 1-23, December.
    8. Shimaa Elkomy & Tim Jackson, 2024. "Health resilience and the global pandemic: The effect of social conditions on the COVID‐19 mortality rate," Journal of International Development, John Wiley & Sons, Ltd., vol. 36(5), pages 2342-2371, July.

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