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COVID-19's intra-urban inequalities and social vulnerability in a medium-sized city

BACKGROUND: Social conditions are related to the impact of epidemics on human populations. This study aimed to investigate the spatial distribution of cases, hospitalizations, and deaths from COVID-19 and its association with social vulnerability. METHODS: An ecological study was conducted in 81 urb...

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Autores principales: Nogueira, Mário Círio, Leite, Isabel Cristina Gonçalves, Teixeira, Maria Teresa Bustamante, Vieira, Marcel de Toledo, Colugnati, Fernando Antonio Basile
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sociedade Brasileira de Medicina Tropical - SBMT 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9009887/
https://www.ncbi.nlm.nih.gov/pubmed/35416871
http://dx.doi.org/10.1590/0037-8682-0445-2021
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author Nogueira, Mário Círio
Leite, Isabel Cristina Gonçalves
Teixeira, Maria Teresa Bustamante
Vieira, Marcel de Toledo
Colugnati, Fernando Antonio Basile
author_facet Nogueira, Mário Círio
Leite, Isabel Cristina Gonçalves
Teixeira, Maria Teresa Bustamante
Vieira, Marcel de Toledo
Colugnati, Fernando Antonio Basile
author_sort Nogueira, Mário Círio
collection PubMed
description BACKGROUND: Social conditions are related to the impact of epidemics on human populations. This study aimed to investigate the spatial distribution of cases, hospitalizations, and deaths from COVID-19 and its association with social vulnerability. METHODS: An ecological study was conducted in 81 urban regions (UR) of Juiz de Fora from March to November 2020. Exposure was measured using the Health Vulnerability Index (HVI), a synthetic indicator that combines socioeconomic and environmental variables from the Demographic Census 2010. Regression models were estimated for counting data with overdispersion (negative binomial generalized linear model) using Bayesian methods, with observed frequencies as the outcome, expected frequencies as the offset variable, and HVI as the explanatory variable. Unstructured random-effects (to capture the effect of unmeasured factors) and spatially structured effects (to capture the spatial correlation between observations) were included in the models. The models were estimated for the entire period and quarter. RESULTS: There were 30,071 suspected cases, 8,063 confirmed cases, 1,186 hospitalizations, and 376 COVID-19 deaths. In the second quarter of the epidemic, compared to the low vulnerability URs, the high vulnerability URs had a lower risk of confirmed cases (RR=0.61; CI95% 0.49-0.76) and a higher risk of hospitalizations (RR=1.65; CI95% 1.23-2.22) and deaths (RR=1.73; CI95% 1.08-2.75). CONCLUSIONS: The lower risk of confirmed cases in the most vulnerable UR probably reflected lower access to confirmatory tests, while the higher risk of hospitalizations and deaths must have been related to the greater severity of the epidemic in the city’s poorest regions.
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spelling pubmed-90098872022-04-26 COVID-19's intra-urban inequalities and social vulnerability in a medium-sized city Nogueira, Mário Círio Leite, Isabel Cristina Gonçalves Teixeira, Maria Teresa Bustamante Vieira, Marcel de Toledo Colugnati, Fernando Antonio Basile Rev Soc Bras Med Trop Major Article BACKGROUND: Social conditions are related to the impact of epidemics on human populations. This study aimed to investigate the spatial distribution of cases, hospitalizations, and deaths from COVID-19 and its association with social vulnerability. METHODS: An ecological study was conducted in 81 urban regions (UR) of Juiz de Fora from March to November 2020. Exposure was measured using the Health Vulnerability Index (HVI), a synthetic indicator that combines socioeconomic and environmental variables from the Demographic Census 2010. Regression models were estimated for counting data with overdispersion (negative binomial generalized linear model) using Bayesian methods, with observed frequencies as the outcome, expected frequencies as the offset variable, and HVI as the explanatory variable. Unstructured random-effects (to capture the effect of unmeasured factors) and spatially structured effects (to capture the spatial correlation between observations) were included in the models. The models were estimated for the entire period and quarter. RESULTS: There were 30,071 suspected cases, 8,063 confirmed cases, 1,186 hospitalizations, and 376 COVID-19 deaths. In the second quarter of the epidemic, compared to the low vulnerability URs, the high vulnerability URs had a lower risk of confirmed cases (RR=0.61; CI95% 0.49-0.76) and a higher risk of hospitalizations (RR=1.65; CI95% 1.23-2.22) and deaths (RR=1.73; CI95% 1.08-2.75). CONCLUSIONS: The lower risk of confirmed cases in the most vulnerable UR probably reflected lower access to confirmatory tests, while the higher risk of hospitalizations and deaths must have been related to the greater severity of the epidemic in the city’s poorest regions. Sociedade Brasileira de Medicina Tropical - SBMT 2022-04-08 /pmc/articles/PMC9009887/ /pubmed/35416871 http://dx.doi.org/10.1590/0037-8682-0445-2021 Text en https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License
spellingShingle Major Article
Nogueira, Mário Círio
Leite, Isabel Cristina Gonçalves
Teixeira, Maria Teresa Bustamante
Vieira, Marcel de Toledo
Colugnati, Fernando Antonio Basile
COVID-19's intra-urban inequalities and social vulnerability in a medium-sized city
title COVID-19's intra-urban inequalities and social vulnerability in a medium-sized city
title_full COVID-19's intra-urban inequalities and social vulnerability in a medium-sized city
title_fullStr COVID-19's intra-urban inequalities and social vulnerability in a medium-sized city
title_full_unstemmed COVID-19's intra-urban inequalities and social vulnerability in a medium-sized city
title_short COVID-19's intra-urban inequalities and social vulnerability in a medium-sized city
title_sort covid-19's intra-urban inequalities and social vulnerability in a medium-sized city
topic Major Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9009887/
https://www.ncbi.nlm.nih.gov/pubmed/35416871
http://dx.doi.org/10.1590/0037-8682-0445-2021
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