Statistical modeling and analysis of malaria risk and child mortality in Tanzania

Sub Saharan African countries are mostly referred to as malaria-endemic countries with high rates of child mortality. In Tanzania, like in other Sub Saharan African countries, malaria is a major public health problem and a leading cause of morbidity and mortality. This study aims at investigating the malaria-mortality relation in Tanzania using available nationwide surveys. The data used, were obtained from the Mapping Malaria Risk in Africa database (2000-2007), the Demographic and Health Survey (2004/05) and remote sensing environmental factors (2000-2007). The study adopts the statistical models that handle cluster effects such as spatial and non-spatial effects, linear and nonlinear effects and univariate and multivariate designs. The parameters were estimated using Bayesian inference implemented in Windows-based Bayesian inference Using Gibbs Sampling (WinBUGS) software. In this thesis, we begin by estimating and mapping malaria risk in Tanzania. We then estimate the malaria risk at Demographic and Health Survey sample points (clusters) by taking into account spatial configuration of the malaria data. We present two studies of mortality using univariate and multivariate case to investigate the malaria-mortality relation in the country. Analysis shows that malaria continues to be an important risk factor for child mortality in Tanzania. Other factors, such as child age, mother’s education level, marital status, household size, preceding birth interval and average rainfall contribute to child mortality. The spatial random component in mapping malaria risk provides a better depiction of the risk factors acting in the population. The need for further studies are recommended along with control strategies and prevailing epidemiological and demographical situations in the country.