Developing statistical models for spatial epidemiology, with applications in disease modelling in the UK and developing nations. Working with health agencies to add value to data and provide practical solutions.
The occurrence of diseases in a population forms a complex pattern in space and time. Our knowledge of that pattern comes to us in incomplete form, via surveys or reports from health agencies. Statistics is essential to understanding and predicting the patterns of disease incidence.
At Lancaster I work with a small group developing and using statistical methods in spatial, and increasingly spatio-temporal, epidemiology. Current projects include predicting meningitis outbreaks in sub-Saharan Africa, looking at socio-economic factors affecting the 2009 H1N1 (Swine flu) outbreak in the UK, and working on a real-time anomaly detection system based on NHS Direct/111 telephone reporting data.
Since most of our work is spatial, I do a lot of mapping and GIS work. Producing informative map graphics can be a challenge - I work with open-source mapping systems such as Quantum GIS, and develop plugins
for it. For my web systems I use OpenLayers to deliver easy-to-use maps of things such as predictions and incidence to partner organisations. This way we can produce spatial dashboards of statistical analytics enabling rapid management decisions.
I'm an active member of the UK section of the Open Source Geospatial Foundation, currently planning the FOSS4G 2013 conference in Nottingham.