Evaluating Multi-level Risk Factors for Malaria and Arboviral Infections in Regions of Tanzania

Abstract

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.