Spatio-temporal modelling and analysis of bacterial and viral infections

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This project will begin with investigating a practical question on Legionnaires disease, a relatively rare but well documented disease. Seasonal trends in surveillance data will be considered building on previous work in area (Rickketts Weather patterns and Legionnaires' disease: a meteorological study | Epidemiology & Infection | Cambridge Core and Sansom et al Cluster Detection tool, A case-association cluster detection and visualisation tool with an application to Legionnaires' disease - PubMed (nih.gov)) using different statistical techniques and up to date epidemiological and meteorological data. Limited attention has been drawn to the process of infection or the impact of weather beyond convenient/easy to access data sets. In tandem with a review of statistical methods and data science techniques, mathematical modelling work will consider the mechanisms of infection should inform the weather variables to consider. Building on this the project will consider application to alternative diseases and specific question on surveillance around case definitions.