COVID-19's intra-urban inequalities and social vulnerability in a medium-sized city
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista da Sociedade Brasileira de Medicina Tropical |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822022000100309 |
Resumo: | ABSTRACT 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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COVID-19's intra-urban inequalities and social vulnerability in a medium-sized cityCOVID-19Spatial analysisSocial inequalityUrban healthABSTRACT 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 - SBMT2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822022000100309Revista da Sociedade Brasileira de Medicina Tropical v.55 2022reponame:Revista da Sociedade Brasileira de Medicina Tropicalinstname:Sociedade Brasileira de Medicina Tropical (SBMT)instacron:SBMT10.1590/0037-8682-0445-2021info:eu-repo/semantics/openAccessNogueira,Mário CírioLeite,Isabel Cristina GonçalvesTeixeira,Maria Teresa BustamanteVieira,Marcel de ToledoColugnati,Fernando Antonio Basileeng2022-04-06T00:00:00Zoai:scielo:S0037-86822022000100309Revistahttps://www.sbmt.org.br/portal/revista/ONGhttps://old.scielo.br/oai/scielo-oai.php||dalmo@rsbmt.uftm.edu.br|| rsbmt@rsbmt.uftm.edu.br1678-98490037-8682opendoar:2022-04-06T00:00Revista da Sociedade Brasileira de Medicina Tropical - Sociedade Brasileira de Medicina Tropical (SBMT)false |
dc.title.none.fl_str_mv |
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 |
spellingShingle |
COVID-19's intra-urban inequalities and social vulnerability in a medium-sized city Nogueira,Mário Círio COVID-19 Spatial analysis Social inequality Urban health |
title_short |
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_sort |
COVID-19's intra-urban inequalities and social vulnerability in a medium-sized city |
author |
Nogueira,Mário Círio |
author_facet |
Nogueira,Mário Círio Leite,Isabel Cristina Gonçalves Teixeira,Maria Teresa Bustamante Vieira,Marcel de Toledo Colugnati,Fernando Antonio Basile |
author_role |
author |
author2 |
Leite,Isabel Cristina Gonçalves Teixeira,Maria Teresa Bustamante Vieira,Marcel de Toledo Colugnati,Fernando Antonio Basile |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Nogueira,Mário Círio Leite,Isabel Cristina Gonçalves Teixeira,Maria Teresa Bustamante Vieira,Marcel de Toledo Colugnati,Fernando Antonio Basile |
dc.subject.por.fl_str_mv |
COVID-19 Spatial analysis Social inequality Urban health |
topic |
COVID-19 Spatial analysis Social inequality Urban health |
description |
ABSTRACT 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. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822022000100309 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822022000100309 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0037-8682-0445-2021 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Medicina Tropical - SBMT |
publisher.none.fl_str_mv |
Sociedade Brasileira de Medicina Tropical - SBMT |
dc.source.none.fl_str_mv |
Revista da Sociedade Brasileira de Medicina Tropical v.55 2022 reponame:Revista da Sociedade Brasileira de Medicina Tropical instname:Sociedade Brasileira de Medicina Tropical (SBMT) instacron:SBMT |
instname_str |
Sociedade Brasileira de Medicina Tropical (SBMT) |
instacron_str |
SBMT |
institution |
SBMT |
reponame_str |
Revista da Sociedade Brasileira de Medicina Tropical |
collection |
Revista da Sociedade Brasileira de Medicina Tropical |
repository.name.fl_str_mv |
Revista da Sociedade Brasileira de Medicina Tropical - Sociedade Brasileira de Medicina Tropical (SBMT) |
repository.mail.fl_str_mv |
||dalmo@rsbmt.uftm.edu.br|| rsbmt@rsbmt.uftm.edu.br |
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1752122163029082112 |