Abstract
Background: Various geographic information systems (GIS) are now widely used to map the distribution of diseases and mortality. However, the mapping of raw mortality rates has been found to be inappropriate since it does not account for the spatial heterogeneity of the population at risk. Bayesian techniques have therefore been suggested as a solution to the problem. Methods: Annual mortality rates for each of the 39 villages of the study area in the Kossi Province in northwest Burkina Faso were calculated using midyear populations of children under five. Two mapping techniques were then used. Firstly, the GIS software ArcView was used to map the crude mortality rates. Secondly, the data were smoothed by the method of empirical Bayes estimation. The geostatistical prediction method of Kriging was then used to spatially interpolate the data for successive years. Results: No spatial pattern is identifiable from the circles representing mortality rates drawn on the map using ArcView. The circles are scattered over the study area and comparing annual distributions between them is difficult. The maps produced by the Bayesian technique also do not show a clear spatial trend pattern. However, they indicate the tendency of villages in the northeastern region to produce higher incidence or risk values, confirming the results of an earlier study reporting a significant cluster of high childhood mortality in the same area.

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