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The Brazilian vaccine divide: How some municipalities were left behind in the Covid-19 vaccine coverage

This study aims to assess the progress of geographic, socioeconomic, and demographic disparities in Covid-19 vaccination coverage in Brazil over the first two years of the vaccination campaign. Data from the National Immunization Program Information System were used to estimate covid-19 vaccine cove...

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Autores principales: Boing, Antonio Fernando, Boing, Alexandra Crispim, Barberia, Lorena, Borges, Marcelo Eduardo, Subramanian, Sankaran Venkata
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637645/
https://www.ncbi.nlm.nih.gov/pubmed/37948353
http://dx.doi.org/10.1371/journal.pgph.0002493
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author Boing, Antonio Fernando
Boing, Alexandra Crispim
Barberia, Lorena
Borges, Marcelo Eduardo
Subramanian, Sankaran Venkata
author_facet Boing, Antonio Fernando
Boing, Alexandra Crispim
Barberia, Lorena
Borges, Marcelo Eduardo
Subramanian, Sankaran Venkata
author_sort Boing, Antonio Fernando
collection PubMed
description This study aims to assess the progress of geographic, socioeconomic, and demographic disparities in Covid-19 vaccination coverage in Brazil over the first two years of the vaccination campaign. Data from the National Immunization Program Information System were used to estimate covid-19 vaccine coverage. Brazilian municipalities were divided into two groups based on their vaccine coverage for the booster dose. The first group comprised 20% of municipalities with the lowest coverage, while the second group (80% of municipalities) had higher coverage. The analysis was conducted separately for four age groups: 5–11, 12–17, 18–59, and 60+. Explanatory variables included socioeconomic and health services indicators. Crude and adjusted logistic regression models were used to estimate the probability of a municipality being among those with the worst vaccination coverage according to the categories of exploratory variables. Between January/2021 and December/2022, Brazil administered 448.2 million doses of the covid-19 vaccine. The booster vaccination coverage varied from 24.8% among adolescents to 79.7% among the elderly. The difference between the group with the highest and lowest coverage increased during the national vaccination campaign. Municipalities with lower education levels, higher proportion of Black population, higher Gini index, and worse health service indicators had a greater likelihood of having lower vaccination coverage. High and increasing levels of inequality in Covid-19 vaccination were observed in Brazil across all age groups during the vaccination campaign in 2021–2022.
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spelling pubmed-106376452023-11-11 The Brazilian vaccine divide: How some municipalities were left behind in the Covid-19 vaccine coverage Boing, Antonio Fernando Boing, Alexandra Crispim Barberia, Lorena Borges, Marcelo Eduardo Subramanian, Sankaran Venkata PLOS Glob Public Health Research Article This study aims to assess the progress of geographic, socioeconomic, and demographic disparities in Covid-19 vaccination coverage in Brazil over the first two years of the vaccination campaign. Data from the National Immunization Program Information System were used to estimate covid-19 vaccine coverage. Brazilian municipalities were divided into two groups based on their vaccine coverage for the booster dose. The first group comprised 20% of municipalities with the lowest coverage, while the second group (80% of municipalities) had higher coverage. The analysis was conducted separately for four age groups: 5–11, 12–17, 18–59, and 60+. Explanatory variables included socioeconomic and health services indicators. Crude and adjusted logistic regression models were used to estimate the probability of a municipality being among those with the worst vaccination coverage according to the categories of exploratory variables. Between January/2021 and December/2022, Brazil administered 448.2 million doses of the covid-19 vaccine. The booster vaccination coverage varied from 24.8% among adolescents to 79.7% among the elderly. The difference between the group with the highest and lowest coverage increased during the national vaccination campaign. Municipalities with lower education levels, higher proportion of Black population, higher Gini index, and worse health service indicators had a greater likelihood of having lower vaccination coverage. High and increasing levels of inequality in Covid-19 vaccination were observed in Brazil across all age groups during the vaccination campaign in 2021–2022. Public Library of Science 2023-11-10 /pmc/articles/PMC10637645/ /pubmed/37948353 http://dx.doi.org/10.1371/journal.pgph.0002493 Text en © 2023 Boing et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Boing, Antonio Fernando
Boing, Alexandra Crispim
Barberia, Lorena
Borges, Marcelo Eduardo
Subramanian, Sankaran Venkata
The Brazilian vaccine divide: How some municipalities were left behind in the Covid-19 vaccine coverage
title The Brazilian vaccine divide: How some municipalities were left behind in the Covid-19 vaccine coverage
title_full The Brazilian vaccine divide: How some municipalities were left behind in the Covid-19 vaccine coverage
title_fullStr The Brazilian vaccine divide: How some municipalities were left behind in the Covid-19 vaccine coverage
title_full_unstemmed The Brazilian vaccine divide: How some municipalities were left behind in the Covid-19 vaccine coverage
title_short The Brazilian vaccine divide: How some municipalities were left behind in the Covid-19 vaccine coverage
title_sort brazilian vaccine divide: how some municipalities were left behind in the covid-19 vaccine coverage
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637645/
https://www.ncbi.nlm.nih.gov/pubmed/37948353
http://dx.doi.org/10.1371/journal.pgph.0002493
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