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The predictors of COVID-19 mortality among health systems parameters: an ecological study across 203 countries

BACKGROUND: Health systems responsiveness is the key to addressing infectious disease threats such as pandemics. The paper outlines an assessment of health systems resilience by exploring the association of health systems and Global Health Security (GHS) parameters with case load and mortality resul...

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Autores principales: Neogi, Sutapa Bandyopadhyay, Pandey, Shivam, Preetha, G. S., Swain, Sumant
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9235072/
https://www.ncbi.nlm.nih.gov/pubmed/35761378
http://dx.doi.org/10.1186/s12961-022-00878-3
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author Neogi, Sutapa Bandyopadhyay
Pandey, Shivam
Preetha, G. S.
Swain, Sumant
author_facet Neogi, Sutapa Bandyopadhyay
Pandey, Shivam
Preetha, G. S.
Swain, Sumant
author_sort Neogi, Sutapa Bandyopadhyay
collection PubMed
description BACKGROUND: Health systems responsiveness is the key to addressing infectious disease threats such as pandemics. The paper outlines an assessment of health systems resilience by exploring the association of health systems and Global Health Security (GHS) parameters with case load and mortality resulting from COVID-19 across 203 countries using an ecological design. METHODOLOGY: Correlation analysis was performed to assess the relationship of each of the indicators with COVID 19 cases and deaths per million population. Stepwise multiple regression models were developed to determine the predictors of COVID-19 cumulative cases and deaths per million population separately. RESULTS: Global health security indicators seemed to have a strong association when analyzed individually but those did not necessarily translate into less burden of cases or deaths in the multivariable analysis. The predictors of cumulative deaths per million population included general government expenditure on health as a proportion of general government expenditure, responsiveness of the system to prevent the emergence and release of pathogens and governance related voice and accountability. CONCLUSION: To conclude, health financing parameters and preventive activities with regard to emergence of pathogens were better predictors of cumulative COVID-19 cases and deaths per million population compared to other health systems and global health security indicators.
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spelling pubmed-92350722022-06-28 The predictors of COVID-19 mortality among health systems parameters: an ecological study across 203 countries Neogi, Sutapa Bandyopadhyay Pandey, Shivam Preetha, G. S. Swain, Sumant Health Res Policy Syst Research BACKGROUND: Health systems responsiveness is the key to addressing infectious disease threats such as pandemics. The paper outlines an assessment of health systems resilience by exploring the association of health systems and Global Health Security (GHS) parameters with case load and mortality resulting from COVID-19 across 203 countries using an ecological design. METHODOLOGY: Correlation analysis was performed to assess the relationship of each of the indicators with COVID 19 cases and deaths per million population. Stepwise multiple regression models were developed to determine the predictors of COVID-19 cumulative cases and deaths per million population separately. RESULTS: Global health security indicators seemed to have a strong association when analyzed individually but those did not necessarily translate into less burden of cases or deaths in the multivariable analysis. The predictors of cumulative deaths per million population included general government expenditure on health as a proportion of general government expenditure, responsiveness of the system to prevent the emergence and release of pathogens and governance related voice and accountability. CONCLUSION: To conclude, health financing parameters and preventive activities with regard to emergence of pathogens were better predictors of cumulative COVID-19 cases and deaths per million population compared to other health systems and global health security indicators. BioMed Central 2022-06-27 /pmc/articles/PMC9235072/ /pubmed/35761378 http://dx.doi.org/10.1186/s12961-022-00878-3 Text en © The Author(s) 2022 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Neogi, Sutapa Bandyopadhyay
Pandey, Shivam
Preetha, G. S.
Swain, Sumant
The predictors of COVID-19 mortality among health systems parameters: an ecological study across 203 countries
title The predictors of COVID-19 mortality among health systems parameters: an ecological study across 203 countries
title_full The predictors of COVID-19 mortality among health systems parameters: an ecological study across 203 countries
title_fullStr The predictors of COVID-19 mortality among health systems parameters: an ecological study across 203 countries
title_full_unstemmed The predictors of COVID-19 mortality among health systems parameters: an ecological study across 203 countries
title_short The predictors of COVID-19 mortality among health systems parameters: an ecological study across 203 countries
title_sort predictors of covid-19 mortality among health systems parameters: an ecological study across 203 countries
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9235072/
https://www.ncbi.nlm.nih.gov/pubmed/35761378
http://dx.doi.org/10.1186/s12961-022-00878-3
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