Investigating the epidemiological impact of the spread of insecticide resistance in malaria vectors

Insecticide resistance is fast becoming one of the major challenges in controlling malaria. With a limited range of insecticide classes available for vector control, it is important to better understand the current levels of resistance present in different regions across sub-Saharan Africa and their potential impact in order to avoid reversing the progress made by vector control tools in the past 50 years. There is an urgent need for new analytical tools to track resistance and understand its public health impact. This thesis presents a novel framework for the analysis of intensity assay data and investigates how different summary metrics can be used to support vector control. I demonstrate how this framework can be applied to explore variability between insecticides and species, with the goal of determining and evaluating the detection value of new discriminating doses. This framework is then applied to better understand the novel insecticide chlorfenapyr and investigates factors impacting its operational use. Additionally, the framework is adapted to explore temporal changes in resistance and generate metrics to summarise mosquito population heterogeneity. The operational impact of heterogeneity in resistance is also assessed using a mathematical model of malaria transmission, showing that insecticide-treated nets will likely be less efficacious the more the mosquito population has mixed levels of insecticide resistance. Together, this thesis provides a new rigorous method of analysing intensity assay data, showing how different statistical frameworks could be used to test different hypotheses and demonstrates the complexity of predicting the epidemiological impact of phenotypic insecticide resistance on malaria control.