SARS-CoV-2 infection prevalence and associated factors: a serial population-based study in Espírito Santo, Brazil, May to June 2020. / Prevalência e fatores associados à infecção por SARS-CoV-2: estudo de base populacional seriado, no Espírito Santo, de maio a junho/2020.

OBJECTIVE: To analyze SARS-CoV-2 seroprevalence and association of sociodemographic and clinical aspects in the state of Espírito Santo, Brazil. METHODS: This was a serial cross-sectional study carried out in four phases, using households as the unit of analysis, from May to June 2020. Eleven municipalities were surveyed, with a sample of 4,500 households in each phase. RESULTS: Prevalence ranged from 2.1% (95%CI 1.7;2.5) on May 10 (first phase) to 9.6% (95%CI 8.8;10.4) on June 21 (fourth phase). In the Greater Vitória Metropolitan Region, the prevalence were 2.7% (95%CI 2.2;3.3) in the first phase, and 11.5% (95%CI 10.5;12.6) in the fourth phase; in the interior region of the state, prevalence ranged from 0.4% (95%CI 0.1;0.9) to 4.4% (95%CI 3.2;5.5) between the two phases. CONCLUSION: The increase in SARS-CoV-2 seroprevalence found in the fourth phase highlighted the high transmission of the virus, information that can support management of the pandemic.

Living conditions, seroprevalence and symptoms of COVID-19 in slums in the Metropolitan Region of Vitória (Espírito Santo).

OBJECTIVES: to estimate the prevalence of SARS-CoV-2 infection in residents of the Greater Vitória region living in subnormal and non-subnormal agglomerates, and to compare sociodemographic and clinical characteristics of total residents (infected and not infected with SARS-CoV-2) between them. METHODS: Population-based prevalence study conducted by serological testing in 2020, with a study unit in households in Greater Vitória, grouped into census tracts classified as sub-normal agglomerates and non-sub-normal agglomerates. The two groups were compared in terms of prevalence and associated factors. The significance level adopted was 5%. RESULTS: The prevalence found in the sub-normal clusters was 12.05% (95%CI 9.59-14.50), and in the non-sub-normal clusters 10.23% (95%CI 7.97-12.50) 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 sub-normal clusters, a higher percentage of illiterates and people with only elementary education, greater number of residents per household, longer stay in public transportation, sharing a bathroom with another household, fewer bedrooms per residence and higher frequency of irregular water supply when compared to non-sub-normal clusters (p < 0.05). CONCLUSIONS: The epidemiological characteristics of sub-normal clusters' residents show the social inequalities that can hinder control measures in a pandemic situation.