Human and canine visceral leishmaniasis (HVL and CVL, respectively) represent serious public health issues in Brazil. The surveillance and control measures currently employed have had limited effect in impeding the territorial expansion of the disease and in reducing the number of cases. We have investigated the space-time distribution of HVL incidence rates and CVL prevalence in the coverage areas of the 148 primary healthcare units in Belo Horizonte (MG, Brazil) during a 6-year period in order to identify those that should be prioritized for disease control actions. Data were smoothed using the empirical Bayes method and analyzed by space-time scanning and application of univariate global Moran's I index and local indicators of spatial association (LISA) statistics to identify spatial autocorrelations. Point data of CVL were analyzed using the Kernel method. Bivariate global Moran's I and LISA techniques were employed to identify spatial correlations between HVL and CVL. Based on our results, we were able to formulate two proposals for establishing the prioritization of coverage areas, namely: (i) classification of maximum priority areas as identified by bivariate LISA for HVL and CVL, and (ii) combination of maximum priority areas with high priority areas as identified by univariate LISA for HVL. According to our proposals, 27 coverage areas in Belo Horizonte were categorized as maximum priority and a further 13 were classified as high priority. Our proposals, which are based on practical, feasible and inexpensive statistical tools, will contribute to a better understanding of VL distribution in urban settings and improving the efficiency of governmental control programs.
Keywords: Epidemiology; Risk assessment; Spatial analysis; Visceral leishmaniasis; Zoonoses.
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