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Dr Sam Lycett

I am a Chancellor’s Fellow in the Infection & Immunity Division of the Roslin Institute, University of Edinburgh, and research the evolution and epidemiology of viral and  bacterial pathogens with the large quantity of sequence data now available using  computational methods. Pathogen genomes accumulate mutations over time and this information can be used to infer transmission patterns between locations and species.

My expertise is in developing fast computational methods, mathematical and statistical models, and applying machine learning techniques and Bayesian phylodynamics in  livestock disease systems such as avian influenza, bovine viral diarrhoea, foot-and-mouth  disease and bovine tuberculosis.

For EPIC 3, I am contributing to Topic 2, particularly `Animal Movement Networks and Epidemiology with Genetic Data`; and Topic 3, especially `Phylodynamic analysis to identify high-risk paths of disease incursion`. In both of these Topics, pathogen sequence data will be used together with other data sources, including animal movements, to quantify and predict disease spread. The focus of the work in Theme 2 is on existing diseases in Scotland, whereas Topic 3 looks further afield and aims to help inform risk prediction.

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