Key points are not available for this paper at this time.
A spatial analysis was carried out to identify factors related to geographic differences in infant mortality risk in Mali by linking data from two spatially structured databases: the Demographic and Health Surveys of 1995-1996 and the Mapping Malaria Risk in Africa database for Mali. Socioeconomic factors measured directly at the individual level and site-specific malaria prevalence predicted for the Demographic and Health Surveys' locations by a spatial model fitted to the Mapping Malaria Risk in Africa database were examined as possible risk factors. The analysis was carried out by fitting a Bayesian hierarchical geostatistical logistic model to infant mortality risk, by Markov chain Monte Carlo simulation. It confirmed that mother's education, birth order and interval, infant's sex, residence, and mother's age at infant's birth had a strong impact on infant mortality risk in Mali. The residual spatial pattern of infant mortality showed a clear relation to well-known foci of malaria transmission, especially the inland delta of the Niger River. No effect of estimated parasite prevalence could be demonstrated. Possible explanations include confounding by unmeasured covariates and sparsity of the source malaria data. Spatial statistical models of malaria prevalence are useful for indicating approximate levels of endemicity over wide areas and, hence, for guiding intervention strategies. However, at points very remote from those sampled, it is important to consider prediction error.
Armin Gemperli (Wed,) studied this question.