Background Countries confronting the COVID-19 pandemic are implementing different social distancing strategies. We evaluated the impact of small-area lockdowns in Chile, aimed to reduce viral transmission while minimizing the population disrupted. The effectiveness of this intervention on the outbreak control is unknown. Methods A natural experiment assessing the impact of small-area lockdowns between February 15th and April 25th, 2020. We used mobility data and official governmental reports to compare regions with small-area lockdowns versus regions without. The primary outcome was the mean difference in the effective reproductive number (Re) of COVID-19. Secondary outcomes were changes in mobility indicators. We used quasi-experimental methods for the analysis and examined the impact of other concurrent public health interventions to disentangle their effects. Results Small-area lockdown produced a sizable reduction in human mobility, equivalent to an 11.4% reduction (95%CI -14.4% to -8.38%) in public transport and similar effects in other mobility indicators. Ten days after implementation, the small-area lockdown produced a reduction of the effective reproductive number (Re) of 0.86 (95%CI -1.70 to -0.02). School and university closures, implemented earlier, led to a 40% reduction in urban mobility. Closure of educational institutions resulted in an even greater Re reduction compared with small-area lockdowns. Conclusions Small-area lockdowns produced a reduction in mobility and viral transmission, but the effects were smaller than the early closures of schools and universities. Small-area lockdowns may have a relevant supporting role in reducing SARS-CoV-2 transmission and could be useful for countries considering scaling-down stricter social distancing interventions.
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.
We address the problem of long-term dynamics of tuberculosis (TB) and latent tuberculosis (LTB) in semiclosed communities. These communities are congregate settings with the potential for sustained daily contact for weeks, months, and even years between their members. Basic examples of these communities are prisons, but certain urban/rural communities, some schools, among others could possibly fit well into this definition. These communities present a sort of ideal conditions for TB spread. In order to describe key relevant dynamics of the disease in these communities, we consider a five compartments SEIR model with five possible routes toward TB infection: primary infection after a contact with infected and infectious individuals (fast TB), endogenous reactivation after a period of latency (slow TB), relapse by natural causes after a cure, exogenous reinfection of latently infected, and exogenous reinfection of recovered individuals. We discuss the possible existence of multiple endemic equilibrium states and the role that the two types of exogenous reinfections in the long-term dynamics of the disease could play.
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