Income inequality and risk of infection and death by COVID-19 in Brazil
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , |
Tipo de documento: | preprint |
Idioma: | por |
Título da fonte: | SciELO Preprints |
Texto Completo: | https://preprints.scielo.org/index.php/scielo/preprint/view/1117 |
Resumo: | Objective: To assess, through space-time analyses, whether the economic inequality of the Federative Units (FU) in Brazil can be associated with the risk of infection and death by COVID-19. Methods: This was an ecological study, based on secondary data on incidence and mortality rates for COVID-19. Data were analyzed at the state level, having the Gini coefficient as the main independent variable. Records of twelve days were used, spaced one week each, between April 21 and June 07, 2020. The weekly rate variation was calculated through Prais-Winsten regression, aiming measuring evolution of the pandemic in each FU. Spearman correlation test was used to assess correlation between the rates and their weekly evolution and the independent variables. Lastly, a spatial dependence diagnosis was conducted, and a Spatial Regression lag model was used when applicable. Results: Incidence and mortality rates of COVID-19 increased in all Brazilian FUs, being more pronounced among those with greater economic inequality. Association between Gini coefficient and COVID-19 incidence and mortality rates remained even when demographic and spatial aspects were taken into account. Conclusions: Economic inequality can play an important role in the impact of COVID-19 in Brazilian territory, through absolute and contextual effects. Structural policies to reduce inequality are essential to face this and future health crises in Brazil. |
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Income inequality and risk of infection and death by COVID-19 in BrazilDesigualdade econômica e risco de infecção e morte por COVID-19 no BrasilCOVID-19pandemiadesigualdade em saúdedeterminantes sociais da saúdecoeficiente de GiniCOVID-19pandemichealth inequalitysocial determinants of healthGini coefficientObjective: To assess, through space-time analyses, whether the economic inequality of the Federative Units (FU) in Brazil can be associated with the risk of infection and death by COVID-19. Methods: This was an ecological study, based on secondary data on incidence and mortality rates for COVID-19. Data were analyzed at the state level, having the Gini coefficient as the main independent variable. Records of twelve days were used, spaced one week each, between April 21 and June 07, 2020. The weekly rate variation was calculated through Prais-Winsten regression, aiming measuring evolution of the pandemic in each FU. Spearman correlation test was used to assess correlation between the rates and their weekly evolution and the independent variables. Lastly, a spatial dependence diagnosis was conducted, and a Spatial Regression lag model was used when applicable. Results: Incidence and mortality rates of COVID-19 increased in all Brazilian FUs, being more pronounced among those with greater economic inequality. Association between Gini coefficient and COVID-19 incidence and mortality rates remained even when demographic and spatial aspects were taken into account. Conclusions: Economic inequality can play an important role in the impact of COVID-19 in Brazilian territory, through absolute and contextual effects. Structural policies to reduce inequality are essential to face this and future health crises in Brazil.Objetivo: Avaliar, por meio de análise espaço-temporal, se a desigualdade econômica das Unidades Federativas (UF) do Brasil pode estar associada com o risco de infecção e morte por COVID-19. Métodos: Trata-se de um estudo ecológico, a partir de dados secundários das taxas de incidência e mortalidade para COVID-19. Os dados foram analisados em nível estadual, tendo como principal variável independente o coeficiente de Gini. Foram utilizados os registros de doze dias, espaçados em uma semana cada, entre 21 de abril e 07 de julho de 2020. A variação semanal das taxas foi calculada através de regressão de Prais-Winsten, com o objetivo de medir a evolução da pandemia em cada UF. O teste de correlação de Spearman foi utilizado para avaliar a correlação entre as taxas e suas evoluções semanais e as variáveis independentes. Por fim, foi realizado diagnóstico de dependência espacial dos dados, e utilizado modelo de defasagem da Regressão Espacial quando aplicável. Resultados: As taxas de incidência e mortalidade por COVID-19 foram crescentes em todas UFs brasileiras, tendo sido mais acentuada entre aquelas com maior desigualdade econômica. A associação entre coeficiente de Gini e incidência e mortalidade por COVID-19 se manteve mesmo quando levados em consideração aspectos demográficos e espaciais. Conclusões: A desigualdade econômica pode exercer papel importante no impacto da COVID-19 em território brasileiro, através de efeitos absolutos e contextuais. Políticas estruturais para a redução da desigualdade são fundamentais para o enfrentamento desta e de futuras crises sanitárias no Brasil.SciELO PreprintsSciELO PreprintsSciELO Preprints2020-08-19info:eu-repo/semantics/preprintinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://preprints.scielo.org/index.php/scielo/preprint/view/111710.1590/1980-549720200095porhttps://preprints.scielo.org/index.php/scielo/article/view/1117/1666Copyright (c) 2020 Lauro Miranda Demenech, Samuel C. Dumith, Maria Eduarda Centena Duarte Vieira, Lucas Neiva-Silvahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessDemenech, Lauro Miranda Dumith, Samuel C. Vieira, Maria Eduarda Centena Duarte Neiva-Silva, Lucas reponame:SciELO Preprintsinstname:SciELOinstacron:SCI2020-08-19T19:00:19Zoai:ops.preprints.scielo.org:preprint/1117Servidor de preprintshttps://preprints.scielo.org/index.php/scieloONGhttps://preprints.scielo.org/index.php/scielo/oaiscielo.submission@scielo.orgopendoar:2020-08-19T19:00:19SciELO Preprints - SciELOfalse |
dc.title.none.fl_str_mv |
Income inequality and risk of infection and death by COVID-19 in Brazil Desigualdade econômica e risco de infecção e morte por COVID-19 no Brasil |
title |
Income inequality and risk of infection and death by COVID-19 in Brazil |
spellingShingle |
Income inequality and risk of infection and death by COVID-19 in Brazil Demenech, Lauro Miranda COVID-19 pandemia desigualdade em saúde determinantes sociais da saúde coeficiente de Gini COVID-19 pandemic health inequality social determinants of health Gini coefficient |
title_short |
Income inequality and risk of infection and death by COVID-19 in Brazil |
title_full |
Income inequality and risk of infection and death by COVID-19 in Brazil |
title_fullStr |
Income inequality and risk of infection and death by COVID-19 in Brazil |
title_full_unstemmed |
Income inequality and risk of infection and death by COVID-19 in Brazil |
title_sort |
Income inequality and risk of infection and death by COVID-19 in Brazil |
author |
Demenech, Lauro Miranda |
author_facet |
Demenech, Lauro Miranda Dumith, Samuel C. Vieira, Maria Eduarda Centena Duarte Neiva-Silva, Lucas |
author_role |
author |
author2 |
Dumith, Samuel C. Vieira, Maria Eduarda Centena Duarte Neiva-Silva, Lucas |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Demenech, Lauro Miranda Dumith, Samuel C. Vieira, Maria Eduarda Centena Duarte Neiva-Silva, Lucas |
dc.subject.por.fl_str_mv |
COVID-19 pandemia desigualdade em saúde determinantes sociais da saúde coeficiente de Gini COVID-19 pandemic health inequality social determinants of health Gini coefficient |
topic |
COVID-19 pandemia desigualdade em saúde determinantes sociais da saúde coeficiente de Gini COVID-19 pandemic health inequality social determinants of health Gini coefficient |
description |
Objective: To assess, through space-time analyses, whether the economic inequality of the Federative Units (FU) in Brazil can be associated with the risk of infection and death by COVID-19. Methods: This was an ecological study, based on secondary data on incidence and mortality rates for COVID-19. Data were analyzed at the state level, having the Gini coefficient as the main independent variable. Records of twelve days were used, spaced one week each, between April 21 and June 07, 2020. The weekly rate variation was calculated through Prais-Winsten regression, aiming measuring evolution of the pandemic in each FU. Spearman correlation test was used to assess correlation between the rates and their weekly evolution and the independent variables. Lastly, a spatial dependence diagnosis was conducted, and a Spatial Regression lag model was used when applicable. Results: Incidence and mortality rates of COVID-19 increased in all Brazilian FUs, being more pronounced among those with greater economic inequality. Association between Gini coefficient and COVID-19 incidence and mortality rates remained even when demographic and spatial aspects were taken into account. Conclusions: Economic inequality can play an important role in the impact of COVID-19 in Brazilian territory, through absolute and contextual effects. Structural policies to reduce inequality are essential to face this and future health crises in Brazil. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-08-19 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/preprint info:eu-repo/semantics/publishedVersion |
format |
preprint |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://preprints.scielo.org/index.php/scielo/preprint/view/1117 10.1590/1980-549720200095 |
url |
https://preprints.scielo.org/index.php/scielo/preprint/view/1117 |
identifier_str_mv |
10.1590/1980-549720200095 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://preprints.scielo.org/index.php/scielo/article/view/1117/1666 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
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https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
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application/pdf |
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SciELO Preprints SciELO Preprints SciELO Preprints |
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SciELO Preprints SciELO Preprints SciELO Preprints |
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SciELO Preprints |
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SciELO Preprints - SciELO |
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