Abstract
BACKGROUND: Seroprevalence studies provide an accurate measure of SARS-CoV-2 spread and the presence of asymptomatic cases. They also provide information on the uneven impact of the pandemic, pointing out vulnerable groups to prioritize which is particularly relevant in unequal societies. However, due to their high cost, they provide limited evidence of spatial spread of the pandemic specially in unequal societies. Our objective was to estimate the prevalence of SARS-CoV-2 antibodies in Chile and model its spatial risk distribution. METHODS: During Oct-Nov 2020, we conducted a population-based serosurvey in Santiago, Talca, and Coquimbo-La Serena (2493 individuals). We explored the individual association between positive results and socio-economic and health-related variables by logistic regression for complex surveys. Then, using an Empirical Bayesian Kriging model, we estimated the infection risk spatial distribution using individual and census information, and compared these results with official records. RESULTS: Seroprevalence was 10.4% (95% CI 7.8-13.7%), ranging from 2% (Talca) to 11% (Santiago), almost three times the number officially reported. Approximately 36% of these were asymptomatic, reaching 82% below 15 years old. Seroprevalence was associated with the city of residence, previous COVID-19 diagnosis, contact with confirmed cases (especially at household), and foreign nationality. The spatial model accurately interpolated the distribution of disease risk within the cities finding significant differences in the predicted probabilities of SARS-CoV-2 infection by census zone (IQR 2.5-15.0%), related to population density and education. CONCLUSIONS: Our results underscore the transmission heterogeneity of SARS-CoV-2 within and across three urban centers of Chile. Socio-economic factors and the outcomes of this seroprevalence study enable us to identify priority areas for intervention. Our methodological approach and results can help guide the design of interdisciplinary strategies for urban contexts, not only for SARS-CoV-2 but also for other communicable diseases.