Bayesian spatial statistics for small area estimation of HIV

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This research aims to develop Bayesian methods for sub-national modelling and inference of HIV in sub-Saharan Africa.Accurate sub-national estimates are needed to inform the targeted policy interventions required to reduce HIV disease burden and end the epidemic.There are three key objectives of this research.The first is to create models for spatial random effects which take a more realistic view of space.The second objective is to develop new inference methods which extend the integrated nested Laplace approximation to models outside the latent Gaussian class.Lastly, this research aims to advance a Bayesian approach to survey design which will make use of the small area estimation model to achieve greater sample efficiency.This project falls within the healthcare technologies and mathematical sciences EPSRC research areas.