Spatial pattern of congenital toxoplasmosis incidence and its relationship with vulnerability and national health indicators in Brazil.

There is a gap in evidence regarding spatial clusters of the congenital toxoplasmosis (CT) and its association with social and health indicators in the Brazilian territory. Thus, we aimed herein to identify CT risk areas in Brazil and its association with social vulnerability and health indicators. An ecological and population-based study was conducted.

Pre-Exposure Prophylaxis to Prevent Hematophagous Bat-Mediated Rabies Outbreaks in Remote Amazon Communities: Lessons from a Pilot for Public Health Policy.

In 2018, an outbreak of human rabies caused by the hematophagous bat hit the Brazilian Amazon Basin community of Melgaço, Brazil, resulting in the death of 10 people, 9 of them children. The incidence of rabies has been on the rise among populations in conditions of vulnerability in this ecosystem due to human expansion into sylvatic environments and limited access to public health services. To address this issue, in September 2019, a collaborative effort from national, local, and international institutions promoted and executed a pilot for pre-exposure prophylaxis of a population in high-risk areas for hematophagous bat-mediated rabies.

Temporal trend, spatial analysis and spatiotemporal clusters of infant mortality associated with congenital toxoplasmosis in Brazil: Time series from 2000 to 2020.

Objective: To analyse the spatial, temporal and spatial-temporal patterns of infant mortality associated with congenital toxoplasmosis in Brazil between the years 2000 and 2020.

Methods: Ecological study of time series, with spatial analysis and spatiotemporal scan of infant mortality associated with congenital toxoplasmosis from the records of deaths of the Mortality Information System of the Brazilian Ministry of Health. The rates were smoothed by the Local Empirical Bayesian model.

Information differences across spatial resolutions and scales for disease surveillance and analysis: The case of Visceral Leishmaniasis in Brazil.

Nationwide disease surveillance at a high spatial resolution is desired for many infectious diseases, including Visceral Leishmaniasis. Statistical and mathematical models using data collected from surveillance activities often use a spatial resolution and scale either constrained by data availability or chosen arbitrarily. Sensitivity of model results to the choice of spatial resolution and scale is not, however, frequently evaluated.

Revisiting area risk classification of visceral leishmaniasis in Brazil.

Background: Visceral leishmaniasis (VL) is a neglected tropical disease of public health relevance in Brazil. To prioritize disease control measures, the Secretaria de Vigilância em Saúde of Brazil's Ministry of Health (SVS/MH) uses retrospective human case counts from VL surveillance data to inform a municipality-based risk classification. In this study, we compared the underlying VL risk, using a spatiotemporal explicit Bayesian hierarchical model (BHM), with the risk classification currently in use by the Brazil's Ministry of Health.