Covid-19 in subnormal and non-subnormal cluster areas in Espírito Santo, Brazil
DOI:
https://doi.org/10.1590/SciELOPreprints.2446Keywords:
Coronavirus Infections, Prevalence, Housing, Population spacial distributionAbstract
Objectives: to estimate the prevalence of SARS-CoV-2 infection in residents of the Greater Vitória region living in subnormal and non-subnormal agglomerations; and, compare sociodemographic and clinical characteristics of total residents (infected and not infected with SARS-CoV-2), among these clusters. Method: Population-based prevalence study, through serological testing carried out in 2020, with a study unit in households in Greater Vitória, grouped into census tracts classified as sub-normal clusters (AGSN) and non-sub-normal clusters (AGNSN ). The two groups were compared in terms of prevalence and associated factors. The significance level adopted was 5%. Results: The prevalence found in the AGSN was 12.05% (95% CI from 9.59 to 14.50%), and in the AGNSN group it was 10.23% (95% CI from 7.97% to 12.50% ) this difference was not statistically significant (p = 0.273). Comparing the sociodemographic characteristics, more people who declare themselves to be of mixed race were found in the SGNA, a higher percentage of illiterates and people with only elementary education, greater number of residents per household, longer stay in public transport, sharing a bathroom with another household , fewer bedrooms per residence and higher frequency of irregular water supply when compared to AGNSN(P<0.05). Conclusions: The epidemiological characteristics of the SNGA residents show the social inequalities that can hinder control measures in a pandemic situation.
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Copyright (c) 2021 Ethel Maciel, Pablo Medeiros Jabor , Laylla Ribeiro Macedo, Gilton Luiz Almada, Raphael Lubiana Zanotti , Crispim Cerutti Junior , Cristiana Costa Gomes , Filomena Euridice Carvalho de Alencar , Tania Reuter, Vera Lucia Gomes de Andrade , Orlei Amaral Cardoso , Nésio Fernandes de Medeiros Junior , Whisllay Maciel Bastos , Marlon Neves Bertolani , Leticia Tabachi Silva , Eliana Zandonade

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