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A beta regression analysis of COVID-19 mortality in Brazil

Brazil was one of the countries most impacted by the COVID-19 pandemic, with a cumulative total of nearly 700,000 deaths by early 2023. The country's federative units were unevenly affected by the pandemic and adopted mitigation measures of different scopes and intensity. There was intense conf...

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Detalles Bibliográficos
Autor principal: Cribari-Neto, Francisco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: KeAi Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9988698/
https://www.ncbi.nlm.nih.gov/pubmed/36945696
http://dx.doi.org/10.1016/j.idm.2023.02.005
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author Cribari-Neto, Francisco
author_facet Cribari-Neto, Francisco
author_sort Cribari-Neto, Francisco
collection PubMed
description Brazil was one of the countries most impacted by the COVID-19 pandemic, with a cumulative total of nearly 700,000 deaths by early 2023. The country's federative units were unevenly affected by the pandemic and adopted mitigation measures of different scopes and intensity. There was intense conflict between the federal government and state governments over the relevance and extent of such measures. We build a simple regression model with good predictive power on state COVID-19 mortality rates in Brazil. Our results reveal that the federative units' urbanization rate and per capita income are important for determining their mean mortality rate and that the number of physicians per 100,000 inhabitants is important for modeling the mortality rate precision. Based on the fitted model, we obtain approximations for the levels of administrative efficiency of local governments in dealing with the pandemic.
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spelling pubmed-99886982023-03-07 A beta regression analysis of COVID-19 mortality in Brazil Cribari-Neto, Francisco Infect Dis Model Article Brazil was one of the countries most impacted by the COVID-19 pandemic, with a cumulative total of nearly 700,000 deaths by early 2023. The country's federative units were unevenly affected by the pandemic and adopted mitigation measures of different scopes and intensity. There was intense conflict between the federal government and state governments over the relevance and extent of such measures. We build a simple regression model with good predictive power on state COVID-19 mortality rates in Brazil. Our results reveal that the federative units' urbanization rate and per capita income are important for determining their mean mortality rate and that the number of physicians per 100,000 inhabitants is important for modeling the mortality rate precision. Based on the fitted model, we obtain approximations for the levels of administrative efficiency of local governments in dealing with the pandemic. KeAi Publishing 2023-03-07 /pmc/articles/PMC9988698/ /pubmed/36945696 http://dx.doi.org/10.1016/j.idm.2023.02.005 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Cribari-Neto, Francisco
A beta regression analysis of COVID-19 mortality in Brazil
title A beta regression analysis of COVID-19 mortality in Brazil
title_full A beta regression analysis of COVID-19 mortality in Brazil
title_fullStr A beta regression analysis of COVID-19 mortality in Brazil
title_full_unstemmed A beta regression analysis of COVID-19 mortality in Brazil
title_short A beta regression analysis of COVID-19 mortality in Brazil
title_sort beta regression analysis of covid-19 mortality in brazil
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9988698/
https://www.ncbi.nlm.nih.gov/pubmed/36945696
http://dx.doi.org/10.1016/j.idm.2023.02.005
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