This paper applies a Bayesian geo-additive generalized linear model to describe the spatial variation, at the district level, on the prevalence of diarrhea, fever and cough among children under 5 years of age using the 1992 Demographic and Health surveys (DHS) from Malawi and Zambia. The modelling technique employed here may be applicable to other research questions in the DHS data sets. The range of observed childhood diarrhea, fever and cough were dichotomized into high or low districts in Malawi and Zambia. We mapped the residual districts spatial effects of these three ailments and explored the clustering of high or low diarrhea, fever and cough rates districts across space after controlling for all other confounding factors. We find visual evidence that high or low morbidity districts spatially cluster together within each country. This evidence suggests that relatively high or low childhood morbidity persist within a spatial region and population, suggesting that research efforts may be focused on these clusters to assess local causes (environmental, cultural etc...) of high or low childhood morbidity.