Climate Change and Variation on Malaria Transmission in Tanzania

Malaria remains one of the most severe infectious diseases afflicting humans globally. This is true despite significant global reductions in the number of reported cases and associated mortality over the last decade as a result of the expansion and intensification of control programs. In Tanzania, the disease remains a leading cause of morbidity and mortality, accounting for over 30% of the country’s disease burden. This thesis aims to develop and apply an integrated spatially-explicit risk assessment framework that would quantify the community vulnerability and risk to malaria transmission as a result of climate variability and change, taking into account both climatic and non-climatic risk factors. A spatial mapping approach was implemented to model the community vulnerability to malaria. Next, I applied the species distribution modeling - ensemble based approach to predict the potential distribution of malaria. A Bayesian spatial modelling approach was used to map the prevalence of malaria and to estimate the number of people infected. Finally, I assessed how climate change and development scenarios, will impact future malaria transmission in the various districts of Tanzania