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Longitudinal variability in mortality predicts COVID-19 deaths
Within Europe, death rates due to COVID-19 vary greatly, with some countries being severely hit while others to date are almost unaffected. This has created a heated debate in particular regarding how effective the different measures applied by the governments are in limiting the spread of the disea...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254667/ https://www.ncbi.nlm.nih.gov/pubmed/34218343 http://dx.doi.org/10.1007/s10654-021-00777-x |
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author | Lundberg, Jon O. Zeberg, Hugo |
author_facet | Lundberg, Jon O. Zeberg, Hugo |
author_sort | Lundberg, Jon O. |
collection | PubMed |
description | Within Europe, death rates due to COVID-19 vary greatly, with some countries being severely hit while others to date are almost unaffected. This has created a heated debate in particular regarding how effective the different measures applied by the governments are in limiting the spread of the disease and ultimately deaths. It would be of considerable interest to pinpoint the factors that determine a country’s susceptibility to a pandemic such as COVID-19. Here we present data demonstrating that mortality due to COVID-19 in a given country could have been predicted to some extent even before the pandemic hit Europe, simply by looking at longitudinal variability of death rates in the years preceding the current outbreak. The variability in death rates during the winter influenza seasons of 2015–2019 correlates to excess mortality in 2020 during the COVID-19 outbreak (Spearman’s ρ = 0.68, 95 % CI = 0.40–0.84, p < 0.001). In contrast, there was no correlation with age, population density, latitude, GNP, governmental health spending, number of intensive care beds, degree of urbanization, or rates of influenza vaccination. These data suggest an intrinsic susceptibility in certain countries to excess mortality associated with viral respiratory diseases including COVID-19. |
format | Online Article Text |
id | pubmed-8254667 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-82546672021-07-06 Longitudinal variability in mortality predicts COVID-19 deaths Lundberg, Jon O. Zeberg, Hugo Eur J Epidemiol Covid-19 Within Europe, death rates due to COVID-19 vary greatly, with some countries being severely hit while others to date are almost unaffected. This has created a heated debate in particular regarding how effective the different measures applied by the governments are in limiting the spread of the disease and ultimately deaths. It would be of considerable interest to pinpoint the factors that determine a country’s susceptibility to a pandemic such as COVID-19. Here we present data demonstrating that mortality due to COVID-19 in a given country could have been predicted to some extent even before the pandemic hit Europe, simply by looking at longitudinal variability of death rates in the years preceding the current outbreak. The variability in death rates during the winter influenza seasons of 2015–2019 correlates to excess mortality in 2020 during the COVID-19 outbreak (Spearman’s ρ = 0.68, 95 % CI = 0.40–0.84, p < 0.001). In contrast, there was no correlation with age, population density, latitude, GNP, governmental health spending, number of intensive care beds, degree of urbanization, or rates of influenza vaccination. These data suggest an intrinsic susceptibility in certain countries to excess mortality associated with viral respiratory diseases including COVID-19. Springer Netherlands 2021-07-04 2021 /pmc/articles/PMC8254667/ /pubmed/34218343 http://dx.doi.org/10.1007/s10654-021-00777-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, 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 changes were made. 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/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Covid-19 Lundberg, Jon O. Zeberg, Hugo Longitudinal variability in mortality predicts COVID-19 deaths |
title | Longitudinal variability in mortality predicts COVID-19 deaths |
title_full | Longitudinal variability in mortality predicts COVID-19 deaths |
title_fullStr | Longitudinal variability in mortality predicts COVID-19 deaths |
title_full_unstemmed | Longitudinal variability in mortality predicts COVID-19 deaths |
title_short | Longitudinal variability in mortality predicts COVID-19 deaths |
title_sort | longitudinal variability in mortality predicts covid-19 deaths |
topic | Covid-19 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254667/ https://www.ncbi.nlm.nih.gov/pubmed/34218343 http://dx.doi.org/10.1007/s10654-021-00777-x |
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