Vector-borne diseases, such as those transmitted by mosquitoes, pose a significant public
health concern in many countries worldwide. In this thesis, I explored the role of a number of
risk factors defined at multiple scales on vector-borne disease prevalence, focusing on malaria
and arboviral infections in several regions of North-Eastern Tanzania, with the principal aim of
improving the overall diagnosis of febrile illness in this region.
First, I investigated the influence of household-wealth on prevalence of malaria and arboviral
infections using principal component analysis (PCA), and then described the methodological
challenges associated with this statistical technique when used to compute indices from smaller
datasets. I then employed a multilevel modelling approach to simultaneously incorporate
household-level anthropogenic factors and village-level environmental characteristics to
investigate key determinants of Anopheles malaria vector density among rural households.
These analyses provided methodologically rigorous approaches to studying vector-borne
diseases at a very fine-scale and also have significant public health relevance as the research
findings can assist in guiding policy decisions regarding surveillance efforts as well as inform
where and when to prioritize interventions.