Haghighi, MRR;
Pallari, CT;
Achilleos, S;
Quattrocchi, A;
Gabel, J;
Artemiou, A;
Athanasiadou, M;
Papatheodorou, S;
Liu, T;
Cernuda Martínez, JA;
et al.
Haghighi, MRR; Pallari, CT; Achilleos, S; Quattrocchi, A; Gabel, J; Artemiou, A; Athanasiadou, M; Papatheodorou, S; Liu, T; Cernuda Martínez, JA; Denissov, G; Łyszczarz, B; Huang, Q; Athanasakis, K; Bennett, CM; Zimmermann, C; Tao, W; Mekogo, SN; Hagen, TP; Le Meur, N; Pinto Lobato, JC; Ambrosio, G; Erzen, I; Binyaminy, B; Critchley, J; Goldsmith, LP; Verstiuk, O; Ogbu, JT; Mortensen, LH; Kandelaki, L; Czech, M; Cutherbertson, J; Schernhammer, E; Vernemmen, C; Costa, AJL; Maor, T; Alekkou, D; Burström, B; Polemitis, A; Charalambous, A; Demetriou, CA
(2024)
Excess Mortality and its Determinants During the COVID-19 Pandemic in 21 Countries: An Ecological Study from the C-MOR Project, 2020 and 2021.
Journal of Epidemiology and Global Health.
ISSN 2210-6006
https://doi.org/10.1007/s44197-024-00320-7
SGUL Authors: Critchley, Julia
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Abstract
Introduction The COVID-19 pandemic overwhelmed health systems, resulting in a surge in excess deaths. This study clustered countries based on excess mortality to understand their response to the pandemic and the influence of various factors on excess mortality within each cluster. Materials and Methods This ecological study is part of the COVID-19 MORtality (C-MOR) Consortium. Mortality data were gathered from 21 countries and were previously used to calculate weekly all-cause excess mortality. Thirty exposure variables were considered in five categories as factors potentially associated with excess mortality: population factors, health care resources, socioeconomic factors, air pollution, and COVID-19 policy. Estimation of Latent Class Linear Mixed Model (LCMM) was used to cluster countries based on response trajectory and Generalized Linear Mixture Model (GLMM) for each cluster was run separately. Results Using LCMM, two clusters were reached. Among 21 countries, Brazil, the USA, Georgia, and Poland were assigned to a separate cluster, with the mean of excess mortality z-score in 2020 and 2021 around 4.4, compared to 1.5 for all other countries assigned to the second cluster. In both clusters the population incidence of COVID-19 had the greatest positive relationship with excess mortality while interactions between the incidence of COVID-19, fully vaccinated people, and stringency index were negatively associated with excess mortality. Moreover, governmental variables (government revenue and government effectiveness) were the most protective against excess mortality. Conclusion This study highlighted that clustering countries based on excess mortality can provide insights to gain a broader understanding of countries' responses to the pandemic and their effectiveness.
Item Type: | Article | ||||||
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Additional Information: | © The Author(s) 2024 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. | ||||||
Keywords: | 1108 Medical Microbiology, 1117 Public Health and Health Services | ||||||
SGUL Research Institute / Research Centre: | Academic Structure > Population Health Research Institute (INPH) | ||||||
Journal or Publication Title: | Journal of Epidemiology and Global Health | ||||||
ISSN: | 2210-6006 | ||||||
Dates: |
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Publisher License: | Creative Commons: Attribution-Noncommercial-No Derivative Works 3.0 | ||||||
URI: | https://openaccess.sgul.ac.uk/id/eprint/116931 | ||||||
Publisher's version: | https://doi.org/10.1007/s44197-024-00320-7 |
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