Abstract

The impact of the COVID-19 pandemic on excess mortality from all causes in 2020 varied across and within European countries. Using data for 2015–2019, we applied Bayesian spatio-temporal models to quantify the expected weekly deaths at the regional level had the pandemic not occurred in England, Greece, Italy, Spain, and Switzerland. With around 30%, Madrid, Castile-La Mancha, Castile-Leon (Spain) and Lombardia (Italy) were the regions with the highest excess mortality. In England, Greece and Switzerland, the regions most affected were Outer London and the West Midlands (England), Eastern, Western and Central Macedonia (Greece), and Ticino (Switzerland), with 15–20% excess mortality in 2020. Our study highlights the importance of the large transportation hubs for establishing community transmission in the first stages of the pandemic. Here, we show that acting promptly to limit transmission around these hubs is essential to prevent spread to other regions and countries.

In this study, the authors estimate excess mortality at the regional level for five European countries (England, Greece, Italy, Spain, and Switzerland) in 2020. They identify the regions and time periods with highest excess mortality and show how these patterns evolved through different pandemic waves.

Details

Title
Regional excess mortality during the 2020 COVID-19 pandemic in five European countries
Author
Garyfallos, Konstantinoudis 1   VIAFID ORCID Logo  ; Cameletti Michela 2 ; Gómez-Rubio, Virgilio 3   VIAFID ORCID Logo  ; Gómez, Inmaculada León 4 ; Pirani, Monica 1   VIAFID ORCID Logo  ; Baio Gianluca 5 ; Larrauri Amparo 4 ; Riou Julien 6 ; Egger, Matthias 7 ; Vineis Paolo 1 ; Blangiardo Marta 1 

 Department of Epidemiology and Biostatistics, School of Public Health, MRC Centre for Environment and Health, London, UK (GRID:grid.14105.31) (ISNI:0000000122478951) 
 University of Bergamo, Department of Economics, Bergamo, Italy (GRID:grid.33236.37) (ISNI:0000000106929556) 
 Universidad de Castilla-La Mancha, Departamento de Matemáticas, Escuela Técnica Superior de Ingenieros Industriales, Albacete, Spain (GRID:grid.8048.4) (ISNI:0000 0001 2194 2329) 
 Institute of Health Carlos III, National Centre of Epidemiology (CNE), Madrid, Spain (GRID:grid.413448.e) (ISNI:0000 0000 9314 1427); Institute of Health Carlos III, Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain (GRID:grid.413448.e) (ISNI:0000 0000 9314 1427) 
 University College London, Department of Statistical Sciences, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201) 
 University of Bern, Institute of Social and Preventive Medicine, Bern, Switzerland (GRID:grid.5734.5) (ISNI:0000 0001 0726 5157) 
 University of Bern, Institute of Social and Preventive Medicine, Bern, Switzerland (GRID:grid.5734.5) (ISNI:0000 0001 0726 5157); University of Bristol, Population Health Sciences, Bristol Medical School, Bristol, UK (GRID:grid.5337.2) (ISNI:0000 0004 1936 7603) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2622692855
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.