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Europe’s War against COVID-19: A Map of Countries’ Disease Vulnerability Using Mortality Indicators

Author

Listed:
  • Alexandra Horobet

    (Department of International Business and Economics, The Bucharest University of Economic Studies, 010374 Bucharest, Romania)

  • Anca Angela Simionescu

    (Carol Davila University of Medicine and Pharmacy, Department of Obstetrics and Gynecology, Filantropia Hospital, 020021 Bucharest, Romania)

  • Dan Gabriel Dumitrescu

    (Department of International Business and Economics, The Bucharest University of Economic Studies, 010374 Bucharest, Romania)

  • Lucian Belascu

    (Department of Management, Marketing and Business Administration, Lucian Blaga University of Sibiu, 550024 Sibiu, Romania)

Abstract

Specific and older age-associated comorbidities increase mortality risk in severe forms of coronavirus disease (COVID-19). We matched COVID-19 comorbidities with causes of death in 28 EU countries for the total population and for the population above 65 years and applied a machine-learning-based tree clustering algorithm on shares of death for COVID-19 comorbidities and for influenza and on their growth rates between 2011 and 2016. We distributed EU countries in clusters and drew a map of the EU populations’ vulnerabilities to COVID-19 comorbidities and to influenza. Noncommunicable diseases had impressive shares of death in the EU but with substantial differences between eastern and western countries. The tree clustering algorithm accurately indicated the presence of western and eastern country clusters, with significantly different patterns of disease shares of death and growth rates. Western populations displayed higher vulnerability to malignancy, blood-related diseases, and diabetes mellitus and lower respiratory diseases, while eastern countries’ populations suffered more from ischaemic heart, cerebrovascular, and circulatory diseases. Dissimilarities between EU countries were also present when influenza was considered. The heat maps of EU populations’ vulnerability to diseases based on mortality indicators constitute the basis for more targeted health policy strategies in a collaborative effort at the EU level.

Suggested Citation

  • Alexandra Horobet & Anca Angela Simionescu & Dan Gabriel Dumitrescu & Lucian Belascu, 2020. "Europe’s War against COVID-19: A Map of Countries’ Disease Vulnerability Using Mortality Indicators," IJERPH, MDPI, vol. 17(18), pages 1-19, September.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:18:p:6565-:d:411144
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    References listed on IDEAS

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    1. repec:cai:poeine:pope_201_0157 is not listed on IDEAS
    2. Raffaele Palladino & Jordy Bollon & Luca Ragazzoni & Francesco Barone-Adesi, 2020. "Excess Deaths and Hospital Admissions for COVID-19 Due to a Late Implementation of the Lockdown in Italy," IJERPH, MDPI, vol. 17(16), pages 1-6, August.
    3. Fionn Murtagh & Pierre Legendre, 2014. "Ward’s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward’s Criterion?," Journal of Classification, Springer;The Classification Society, vol. 31(3), pages 274-295, October.
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