TY - JOUR
T1 - Excess Mortality and its Determinants During the COVID-19 Pandemic in 21 Countries
T2 - An Ecological Study from the C-MOR Project, 2020 and 2021
AU - Rahmanian Haghighi, Mohammad Reza
AU - Pallari, Chryso Th
AU - Achilleos, Souzana
AU - Quattrocchi, Annalisa
AU - Gabel, John
AU - Artemiou, Andreas
AU - Athanasiadou, Maria
AU - Papatheodorou, Stefania
AU - Liu, Tianyu
AU - Cernuda Martínez, José Antonio
AU - Denissov, Gleb
AU - Łyszczarz, Błażej
AU - Huang, Qian
AU - Athanasakis, Kostas
AU - Bennett, Catherine M.
AU - Zimmermann, Claudia
AU - Tao, Wenjing
AU - Nganda Mekogo, Serge
AU - Hagen, Terje P.
AU - Le Meur, Nolwenn
AU - Pinto Lobato, Jackeline Christiane
AU - Ambrosio, Giuseppe
AU - Erzen, Ivan
AU - Binyaminy, Binyamin
AU - Critchley, Julia A.
AU - Goldsmith, Lucy P.
AU - Verstiuk, Olesia
AU - Ogbu, Jideofor Thomas
AU - Mortensen, Laust H.
AU - Kandelaki, Levan
AU - Czech, Marcin
AU - Cutherbertson, Joseph
AU - Schernhammer, Eva
AU - Vernemmen, Catharina
AU - Leal Costa, Antonio José
AU - Maor, Tamar
AU - Alekkou, Dimos
AU - Burström, Bo
AU - Polemitis, Antonis
AU - Charalambous, Andreas
AU - Demetriou, Christiana A.
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - COVID-19
KW - Excess mortality
KW - Governance
KW - Public health measures
KW - Vaccination rate
U2 - 10.1007/s44197-024-00320-7
DO - 10.1007/s44197-024-00320-7
M3 - Journal article
C2 - 39527396
AN - SCOPUS:85208926669
VL - 14
SP - 1650
EP - 1661
JO - Journal of Epidemiology and Global Health
JF - Journal of Epidemiology and Global Health
SN - 2210-6006
ER -