I have a background in computing science and mathematics, and am interested in using mathematical and computational methods to understand the risks of disease spread on networks.
In EPIC, I use the networks of livestock trades, geographic adjacencies, and other contacts to model livestock disease and identify key drivers of infection and areas of risk. My work with EPIC includes a variety of network modelling approaches, including characterisation of the network of registered trade links in Scotland and their potential to spread undetected disease, the development of computationally efficient methods to calculate how big an outbreak is likely to be, models to help understand how networks change over time, and game theoretic models of disease that incorporate strategic decision making by farmers.
Going forward, I will work to adapt methods from network theory to build faster and better methods to understand and manage livestock disease in Scotland.
Risk-based strategies for surveillance of tuberculosis infection in cattle for low-risk areas in England and Scotland. LCM Salvador, M Deason, J Enright, PR Bessell, RR Kao
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