Diffusion and prediction of Leishmaniasis in a large metropolitan area in Brazil with a Bayesian space-time model

We present results from an analysis of human visceral Leishmaniasis cases based on public health records of Belo Horizonte, Brazil, from 1994 to 1997. The main emphasis in this study is on the development of a spatial statistical model to map and project the rates of visceral Leishmaniasis in Belo Horizonte. The model allows for space-time interaction and it is based on a hierarchical Bayesian approach. We assume that the underlying rates evolve in time according to a polynomial trend specific to each small area in the region. The parameters of these polynomials receive a spatial distribution in the form of an autonormal distribution. While the raw rates are extremely noisy and inadequate to support decisions, the resulting smoothed rates estimates are considerably less affected by small area issues and provide very clear directions to implement public health actions.