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Country-level predictors of COVID-19 mortality
This study aimed to identify country-level predictors of COVID-19 mortality, after controlling for diverse potential factors, and utilizing current worldwide mortality data. COVID-19 deaths, as well as geographic, demographic, socioeconomic, healthcare, population health, and pandemic-related variab...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10245344/ https://www.ncbi.nlm.nih.gov/pubmed/37286632 http://dx.doi.org/10.1038/s41598-023-36449-x |
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author | Brown, Paul A. |
author_facet | Brown, Paul A. |
author_sort | Brown, Paul A. |
collection | PubMed |
description | This study aimed to identify country-level predictors of COVID-19 mortality, after controlling for diverse potential factors, and utilizing current worldwide mortality data. COVID-19 deaths, as well as geographic, demographic, socioeconomic, healthcare, population health, and pandemic-related variables, were obtained for 152 countries. Continuous variables were examined with Spearman’s correlation, categorical variables with ANOVA or Welch’s Heteroscedastic F Test, and country-level independent predictors of COVID-19 mortality identified by weighted generalized additive models. This study identified independent mortality predictors in six limited models, comprising groups of related variables. However, in the full model, only WHO region, percent of population ≥ 65 years, Corruption Perception Index, hospital beds/100,000 population, and COVID-19 cases/100,000 population were predictive of mortality, with model accounting for 80.7% of variance. These findings suggest areas for focused intervention in the event of similar future public health emergencies, including prioritization of the elderly, optimizing healthcare capacity, and improving deficient health sector-related governance. |
format | Online Article Text |
id | pubmed-10245344 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102453442023-06-08 Country-level predictors of COVID-19 mortality Brown, Paul A. Sci Rep Article This study aimed to identify country-level predictors of COVID-19 mortality, after controlling for diverse potential factors, and utilizing current worldwide mortality data. COVID-19 deaths, as well as geographic, demographic, socioeconomic, healthcare, population health, and pandemic-related variables, were obtained for 152 countries. Continuous variables were examined with Spearman’s correlation, categorical variables with ANOVA or Welch’s Heteroscedastic F Test, and country-level independent predictors of COVID-19 mortality identified by weighted generalized additive models. This study identified independent mortality predictors in six limited models, comprising groups of related variables. However, in the full model, only WHO region, percent of population ≥ 65 years, Corruption Perception Index, hospital beds/100,000 population, and COVID-19 cases/100,000 population were predictive of mortality, with model accounting for 80.7% of variance. These findings suggest areas for focused intervention in the event of similar future public health emergencies, including prioritization of the elderly, optimizing healthcare capacity, and improving deficient health sector-related governance. Nature Publishing Group UK 2023-06-07 /pmc/articles/PMC10245344/ /pubmed/37286632 http://dx.doi.org/10.1038/s41598-023-36449-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 | Article Brown, Paul A. Country-level predictors of COVID-19 mortality |
title | Country-level predictors of COVID-19 mortality |
title_full | Country-level predictors of COVID-19 mortality |
title_fullStr | Country-level predictors of COVID-19 mortality |
title_full_unstemmed | Country-level predictors of COVID-19 mortality |
title_short | Country-level predictors of COVID-19 mortality |
title_sort | country-level predictors of covid-19 mortality |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10245344/ https://www.ncbi.nlm.nih.gov/pubmed/37286632 http://dx.doi.org/10.1038/s41598-023-36449-x |
work_keys_str_mv | AT brownpaula countrylevelpredictorsofcovid19mortality |