Seroepidemiological investigation of COVID-19: A cross-sectional study in Jundiai, São Paulo, Brazil

Abstract

The dramatic increase in the number of COVID-19 cases has been a threat to global health and a challenge for health systems. Estimating the prevalence of infection in the population is essential to provide support for action planning. Within this scenario, the aim of the present study was to analyze the seroprevalence and associated factors of COVID-19 Jundiaí, São Paulo, Brazil. This cross-sectional study was conducted from June 1st to June 19th, 2020. The participants were patients with respiratory symptoms who sought Primary Care Units (UBS) (n = 1,181) and subjects recruited from randomly selected households by probability sampling (n = 3,065), as screening strategy. All participants, in both phases, were submitted to SARS-CoV-2 rapid antigen tests (IgG and IgM) and responded to a questionnaire including sociodemographic characteristics based on Behavioural Insights for COVID-19. Total seroprevalence (positive/negative) was the outcome and the independent variables were sociodemographic variables, health behavior and signs/symptoms. The chi-squared test was used for association analysis (p<0.05) and variables with p<0.20 were entered into the logistic regression model (p<0.05). A total of 1,181 subjects from the UBS and 3,065 from the selected households participated in the study. The seroprevalence was 30.8% in the UBS and 3.1% in the households. The adjusted logistic regression identified that lower educational level (OR 2.68; 95%CI 1.59-4.54), household member testing positive (OR 1.67; 95%CI 1.16-2.39), presence of anosmia (OR 3.68, 95%CI 2.56-5.28) and seeking UBS (OR 3.76; 95%CI 2.08-6.82) was risk factors to test positive for SARS-CoV-2. Estimating the seroprevalence in the population was important to know the disease extension that was higher than the notified cases. These results showed socioeconomic aspects associated with COVID-19 even adjusted by symptoms. Populational epidemiologic studies that investigate the associated factors of COVID-19 are relevant to plan strategies to control the pandemic.

Fig 1. Data collection procedure in studies conducted at the basic health units and households, Jundiaí, São Paulo, 2020.

The figure shows the steps of collection of the data obtained in the present study.

Fig 2. Households selected for data collection, Jundiaí, São Paulo, Brazil, 2020 (n = 1,333).

The map shows the division of the municipality into neighborhoods and the distribution of the households randomly selected for the study. The base layer of the map is available in the Brazilian Institute of Geography and Statistics: https://www.ibge.gov.br/geociencias/organizacao-do-territorio/malhas-territoriais/15774-malhas.html?edicao=30138&t=downloads.