Evolução E Periferização Da Covid-19 Na Área Urbana De Santa Maria, Rs: Traçando Padrões Espaciais

Rizzatti, Maurício; Spode, Pedro Leonardo Cezar; Batista, Natália Lampert; Erthal, Douglas Bouvier; Faria, Rivaldo Mauro de

doi:10.14393/hygeia0054554

Cited by 4 publications

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“…Some studies in Brazilian municipalities have found results similar to those presented here. A study carried out in the city of Santa Maria/RS found that at the beginning of the epidemic, there was a greater concentration of confirmed cases of COVID-19 in more central neighborhoods, and during the epidemic, there was a peripheralization of the epidemic to neighborhoods with greater social deprivation 13 . A study conducted in the districts of São Paulo municipality found that the incidence of COVID-19 was concentrated in clusters of districts with a higher proportion of slums and lower salaries 14 .…”

Section: Discussionmentioning

confidence: 99%

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

Nogueira

Leite

Bustamante-Teixeira

et al. 2022

Rev. Soc. Bras. Med. Trop.

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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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Section: Discussionmentioning

confidence: 99%

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

Nogueira

Leite

Bustamante-Teixeira

et al. 2022

Rev. Soc. Bras. Med. Trop.

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“…The higher prevalence in the urban area can be attributed to the greater circulation of people and availability of services. Also, in these regions, the occupational density of residences is higher when compared to rural areas, and https://doi.org/10.1017/dmp.2022.195 Published online by Cambridge University Press measures of social isolation and quarantine become more difficult tasks to be carried out, which may contribute to the emergence of new cases 29 .…”

Section: Discussionmentioning

confidence: 99%

“…Also, in these regions, the occupational density of residences is higher when compared to rural areas, and measures of social isolation and quarantine become more difficult tasks to be carried out, which may contribute to the emergence of new cases. 29 In Tupãssi, the first positive case in the rural area occurred on May 21. In Assis Chateaubriand, June 5.…”

Section: Discussionmentioning

confidence: 99%

COVID-19 (SARS-CoV-2) in Patients Treated in The Unified Health System (SUS) with Flu and Respiratory Symptoms from Three Brazilian Municipalities in the Border Region

Sereno

Sousa²,

Gimenes³

et al. 2022

Disaster med. public health prep.

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Objective: The objective of this study was to investigate the prevalence and carry out epidemiology using sociodemographic data from patients with symptoms suggestive of COVID-19 (SARS-CoV-2) in three bordering Brazilian municipalities. Methods: An epidemiological survey of positive cases of COVID-19 through RT-PCR was carried out in 1874 patients, seen in the Unified Health System (SUS), aged between 0-99 years, who had symptoms suggestive of COVID-19, from the cities of Assis Chateaubriand, Tupãssi, and Formosa do Oeste. Results: It was possible to observe that of the 1874 patients seen in the public health network of the three municipalities, 354 were diagnosed as positive. The predominance of cases was in female patients (51.97%) and in patients who lived in urban areas (93.50%), and the predominant age group was 20-29 years (19.78%). Conclusion: The result of this study demonstrated the epidemiological profile of patients with respiratory and flu-like symptoms, positive for COVID-19, in three municipalities bordering Paraguay and Argentina. It was evident that the age group has its specificities regarding the susceptibility of the infection. Although the borders are closed, there was probably a spread of the virus in this region, due to the diversion, which showed an increase during the pandemic period.

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“…Vários artigos têm ressaltado, desde a progressão inicial da doença, a importância de compreender a relação e a magnitude da associação entre variáveis demográficas, socioeconômicas, ambientais e assistenciais e os padrões de morbimortalidade e disseminação espacial da COVID-19. 4,5 Os principais fatores relacionados à incidência, mortalidade e letalidade da COVID-19 na literatura podem ser agrupados nas seguintes categorias: demográficos, tais como a densidade populacional e a composição étnica; 1,[6][7][8][9][10][11][12][13] educacionais, como o grau de escolaridade da população; 9,10,[13][14][15][16] habitacionais, como a porcentagem de domicílios localizados em áreas de pobreza; 6,[9][10][11][12]14,[16][17][18] emprego, como o grau de informalidade do trabalho; 6,10,12 renda, como a renda média per capita e a proporção de domicílios em extrema pobreza; 6,[9][10][11][13][14][15][16] assistência à saúde, como a disponibilidade de médicos, leitos de Unidade de Terapia Intensiva (UTI) e respiradores. [6][7][8]12 Além destas variáveis citadas, alguns estudos utilizaram, também, indicadores compostos em suas análises, como o Índice de Vulnerabilidad...…”

Section: Introductionunclassified

“…[6][7][8]12 Além destas variáveis citadas, alguns estudos utilizaram, também, indicadores compostos em suas análises, como o Índice de Vulnerabilidade Social (IVS) e o Índice de Desenvolvimento Humano Municipal (IDHM). 6,10,[12][13][14][15][16][17][18] Em estudo realizado no estado de São Paulo, Isso mostra a importância do planejamento em saúde regionalizado, que leve em conta as características do território e as interdependências assistenciais e econômicas dos municípios.…”

Section: Introductionunclassified

COVID-19 nos municípios de uma macrorregião de Minas Gerais e fatores associados

Nogueira

Paula

Leite

et al. 2022

hu rev

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Introdução: No Brasil, a epidemia de COVID-19 teve início nos grandes centros urbanos e se disseminou para os demais municípios ao longo dos meses seguintes. Objetivo: Descrever a distribuição espacial da incidência de casos notificados e da mortalidade por COVID-19 nos municípios da macrorregião de saúde Sudeste de Minas Gerais segundo a tipologia de municípios do Instituto Brasileiro de Geografia e Estatística (IBGE). Material e Métodos: Estudo ecológico que teve os municípios da macrorregião de saúde Sudeste de Minas Gerais como unidades de análise. Foram obtidos os dados de COVID-19 de plataforma virtual da Universidade Federal de Viçosa e calculadas as taxas de incidência e de mortalidade para cada um dos municípios da macrorregião entre março de 2020 e fevereiro de 2021. Também foram obtidas variáveis socioeconômicas (provenientes do Censo 2010) e assistenciais (provenientes do site do DATASUS) referentes a esses municípios. Foram feitas comparações entre as variáveis epidemiológicas, socioeconômicas e assistenciais, por tipos de município, por meio do teste não-paramétrico de Kruskal-Wallis. Resultados: A distribuição dos indicadores socioeconômicos e epidemiológicos entre os municípios que compõem a macrorregião mostrou-se heterogênea. Os municípios predominantemente urbanos apresentaram maior incidência e mortalidade por COVID-19 do que os rurais adjacentes. Contudo, os municípios rurais adjacentes apresentaram, em geral, piores indicadores socioeconômicos quando comparados aos predominantemente urbanos. Não houve diferença significativa entre os intermediários adjacentes e os demais tipos no que tange aos indicadores avaliados. Conclusão: Embora a epidemia de COVID-19 tenha atingido primeiro os municípios maiores, mais urbanizados e com maior comunicação com grandes centros urbanos, ao longo do tempo foi se interiorizando e acabou por atingir todos os municípios da região.

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Evolução E Periferização Da Covid-19 Na Área Urbana De Santa Maria, Rs: Traçando Padrões Espaciais

Cited by 4 publications

References 0 publications

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

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

COVID-19 (SARS-CoV-2) in Patients Treated in The Unified Health System (SUS) with Flu and Respiratory Symptoms from Three Brazilian Municipalities in the Border Region

COVID-19 nos municípios de uma macrorregião de Minas Gerais e fatores associados

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