An Analysis of the Socio-Demographic and Spatial Determinants of under-Five Mortality in Zambia

Brian Munkombwe, University of Texas at San Antonio

Many sub-Saharan countries are confronted with persistently high levels of neonatal mortality because of the impact of a range of biological and social determinants. High neonatal mortality levels have been contributing significantly to the high levels of under-five mortality in Zambia. The geographic distribution of health problems and their relationship to potential risk factors can be invaluable for effective intervention planning. The objective of this study is to determine the spatial nature of neonatal mortality in Zambia, at a sub district level,as well as identify and map the high risk clusters in the country. We use a Bayesian approach to quantify the spatial risk of neonatal mortality and estimate semiparametric regression models of the effects of the socio-economic and biological determinants. We model small scale sub-district specific effects using flexible spatial priors. Inference is fully Bayesian, using the Integrated Nested Laplace Approximation (INLA), which uses Markov chain Monte Carlo techniques.

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Presented in Poster Session 7