Predicting Disease Vector Distributions Through Space and Time Using Environmental and Vector Control Data

Abstract

Within this thesis, I performed a systematic review of approaches to broad-scale modelling of disease vector distributions and determined the most widely used methods predict current species niches and project the models forward under future climate scenarios without temporal validation. I then provided a forward-looking summary of emerging techniques to improve the reliability and transferability of those models, including historical calibration. I then predicted Anopheles mosquito distributions across Tanzania in 2001 (before large-scale ITN distributions) and compared this model with countrywide ITN use by 2012 to assess where the most suitable mosquito habitats were located and whether ITN rollouts in Tanzania ensured coverage of such areas. I concluded that ITNs in Tanzania did not optimally target areas most at risk of malaria. In doing so, I provided a new approach to monitoring and evaluating vector control interventions across large spatial scales.