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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Sociedade Brasileira de Medicina Tropical - SBMT
2022
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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. |
format | Online Article Text |
id | pubmed-9009887 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Sociedade Brasileira de Medicina Tropical - SBMT |
record_format | MEDLINE/PubMed |
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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