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Spatial–temporal distribution of incidence, mortality, and case-fatality ratios of coronavirus disease 2019 and its social determinants in Brazilian municipalities
The COVID-19 pandemic caused impact on public health worldwide. Brazil gained prominence during the pandemic due to the magnitude of disease. This study aimed to evaluate the spatial–temporal dynamics of incidence, mortality, and case fatality of COVID-19 and its associations with social determinant...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009864/ https://www.ncbi.nlm.nih.gov/pubmed/36914858 http://dx.doi.org/10.1038/s41598-023-31046-4 |
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author | Raymundo, Carlos Eduardo Oliveira, Marcella Cini de Araujo Eleuterio, Tatiana de Arruda Santos Junior, Édnei César da Silva, Marcele Gonçalves André, Suzana Rosa Sousa, Ana Inês de Andrade Medronho, Roberto |
author_facet | Raymundo, Carlos Eduardo Oliveira, Marcella Cini de Araujo Eleuterio, Tatiana de Arruda Santos Junior, Édnei César da Silva, Marcele Gonçalves André, Suzana Rosa Sousa, Ana Inês de Andrade Medronho, Roberto |
author_sort | Raymundo, Carlos Eduardo |
collection | PubMed |
description | The COVID-19 pandemic caused impact on public health worldwide. Brazil gained prominence during the pandemic due to the magnitude of disease. This study aimed to evaluate the spatial–temporal dynamics of incidence, mortality, and case fatality of COVID-19 and its associations with social determinants in Brazilian municipalities and epidemiological week. We modeled incidence, mortality, and case fatality rates using spatial–temporal Bayesian model. “Bolsa Família Programme” (BOLSAFAM) and “proportional mortality ratio” (PMR) were inversely associated with the standardized incidence ratio (SIR), while “health insurance coverage” (HEALTHINSUR) and “Gini index” were directly associated with the SIR. BOLSAFAM and PMR were inversely associated with the standardized mortality ratio (SMR) and standardized case fatality ratio (SCFR). The highest proportion of excess risk for SIR and the SMR started in the North, expanding to the Midwest, Southeast, and South regions. The highest proportion of excess risk for the SCFR outcome was observed in some municipalities in the North region and in the other Brazilian regions. The COVID-19 incidence and mortality in municipalities that most benefited from the cash transfer programme and with better social development decreased. The municipalities with a higher proportion of non-whites had a higher risk of becoming ill and dying from the disease. |
format | Online Article Text |
id | pubmed-10009864 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100098642023-03-13 Spatial–temporal distribution of incidence, mortality, and case-fatality ratios of coronavirus disease 2019 and its social determinants in Brazilian municipalities Raymundo, Carlos Eduardo Oliveira, Marcella Cini de Araujo Eleuterio, Tatiana de Arruda Santos Junior, Édnei César da Silva, Marcele Gonçalves André, Suzana Rosa Sousa, Ana Inês de Andrade Medronho, Roberto Sci Rep Article The COVID-19 pandemic caused impact on public health worldwide. Brazil gained prominence during the pandemic due to the magnitude of disease. This study aimed to evaluate the spatial–temporal dynamics of incidence, mortality, and case fatality of COVID-19 and its associations with social determinants in Brazilian municipalities and epidemiological week. We modeled incidence, mortality, and case fatality rates using spatial–temporal Bayesian model. “Bolsa Família Programme” (BOLSAFAM) and “proportional mortality ratio” (PMR) were inversely associated with the standardized incidence ratio (SIR), while “health insurance coverage” (HEALTHINSUR) and “Gini index” were directly associated with the SIR. BOLSAFAM and PMR were inversely associated with the standardized mortality ratio (SMR) and standardized case fatality ratio (SCFR). The highest proportion of excess risk for SIR and the SMR started in the North, expanding to the Midwest, Southeast, and South regions. The highest proportion of excess risk for the SCFR outcome was observed in some municipalities in the North region and in the other Brazilian regions. The COVID-19 incidence and mortality in municipalities that most benefited from the cash transfer programme and with better social development decreased. The municipalities with a higher proportion of non-whites had a higher risk of becoming ill and dying from the disease. Nature Publishing Group UK 2023-03-13 /pmc/articles/PMC10009864/ /pubmed/36914858 http://dx.doi.org/10.1038/s41598-023-31046-4 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 Raymundo, Carlos Eduardo Oliveira, Marcella Cini de Araujo Eleuterio, Tatiana de Arruda Santos Junior, Édnei César da Silva, Marcele Gonçalves André, Suzana Rosa Sousa, Ana Inês de Andrade Medronho, Roberto Spatial–temporal distribution of incidence, mortality, and case-fatality ratios of coronavirus disease 2019 and its social determinants in Brazilian municipalities |
title | Spatial–temporal distribution of incidence, mortality, and case-fatality ratios of coronavirus disease 2019 and its social determinants in Brazilian municipalities |
title_full | Spatial–temporal distribution of incidence, mortality, and case-fatality ratios of coronavirus disease 2019 and its social determinants in Brazilian municipalities |
title_fullStr | Spatial–temporal distribution of incidence, mortality, and case-fatality ratios of coronavirus disease 2019 and its social determinants in Brazilian municipalities |
title_full_unstemmed | Spatial–temporal distribution of incidence, mortality, and case-fatality ratios of coronavirus disease 2019 and its social determinants in Brazilian municipalities |
title_short | Spatial–temporal distribution of incidence, mortality, and case-fatality ratios of coronavirus disease 2019 and its social determinants in Brazilian municipalities |
title_sort | spatial–temporal distribution of incidence, mortality, and case-fatality ratios of coronavirus disease 2019 and its social determinants in brazilian municipalities |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009864/ https://www.ncbi.nlm.nih.gov/pubmed/36914858 http://dx.doi.org/10.1038/s41598-023-31046-4 |
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