Evidence synthesis for estimating epidemiology of chronic diseases

An increasing number of people are living with one or more chronic diseases. To assess public health interventions to prevent diseases, it is important to have good estimates of disease incidence, the risk of death for people with the disease, and how these quantities vary between people and through time. This project will advance Bayesian evidence synthesis methods for investigating the epidemiology of chronic diseases. Multiple routinely-available data sources will be used, such as health surveys, registry data, national mortality statistics and published literature. The aim is to determine the extent of variation in incidence and risk of death over time, between geographical areas and between people of different ages and with different risk factors, for multiple diseases. The statistical challenges include building and computation of models for novel combinations of data of different structures and at different levels of aggregation, with varying definitions of the disease outcome of interest. This work will involve collaboration with Public Health England.