This study was developed in the urban area of Governador Valadares, a reemerging focus of intense transmission of visceral leishmaniasis (VL) in Brazil, presenting 86 human cases of VL from 2008 to 2011. The disease prevailed in males (73.2%) with most patients between 0 and 9 years (44.1%) and a lethality rate of 16.2%. A canine survey was carried out on 16,529 domestic dogs in 35 districts in the area and it showed that 30.2% of them (4,992 dogs) were positive for VL by serum assays. Prevalence ratios for canine VL varied between 13.6% and 53.4%. The clinical exam of 343 seropositive dogs showed that 49.9% of them were considered symptomatic, with larger prevalence of canine VL being in short-furred animals (90%). The entomological survey was performed in eight districts, where 2,539 phlebotomines were captured, preferentially in the peridomicile (84.5%). Lutzomyia longipalpis was the predominant species (90%) suggesting its participation in the VL transmission in the area. The correlation between canine prevalence and L. longipalpis density was evaluated.

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The prevalence of drugs use in children was high, indicating the need for formulating educational programs aiming at the awareness of caregivers regarding rational use.

BackgroundThe Prospective Space-Time scan statistic (PST) is widely used for the evaluation of space-time clusters of point event data. Usually a window of cylindrical shape is employed, with a circular or elliptical base in the space domain. Recently, the concept of Minimum Spanning Tree (MST) was applied to specify the set of potential clusters, through the Density-Equalizing Euclidean MST (DEEMST) method, for the detection of arbitrarily shaped clusters. The original map is cartogram transformed, such that the control points are spread uniformly. That method is quite effective, but the cartogram construction is computationally expensive and complicated.ResultsA fast method for the detection and inference of point data set space-time disease clusters is presented, the Voronoi Based Scan (VBScan). A Voronoi diagram is built for points representing population individuals (cases and controls). The number of Voronoi cells boundaries intercepted by the line segment joining two cases points defines the Voronoi distance between those points. That distance is used to approximate the density of the heterogeneous population and build the Voronoi distance MST linking the cases. The successive removal of edges from the Voronoi distance MST generates sub-trees which are the potential space-time clusters. Finally, those clusters are evaluated through the scan statistic. Monte Carlo replications of the original data are used to evaluate the significance of the clusters. An application for dengue fever in a small Brazilian city is presented.ConclusionsThe ability to promptly detect space-time clusters of disease outbreaks, when the number of individuals is large, was shown to be feasible, due to the reduced computational load of VBScan. Instead of changing the map, VBScan modifies the metric used to define the distance between cases, without requiring the cartogram construction. Numerical simulations showed that VBScan has higher power of detection, sensitivity and positive predicted value than the Elliptic PST. Furthermore, as VBScan also incorporates topological information from the point neighborhood structure, in addition to the usual geometric information, it is more robust than purely geometric methods such as the elliptic scan. Those advantages were illustrated in a real setting for dengue fever space-time clusters.