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Dr Sam Lycett

I am a Group Leader 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 Topic 2 is on existing diseases in Scotland, whereas Topic 3 looks further afield and aims to help inform risk prediction.

Publications

Phylodynamic analysis of an emergent Mycobacterium bovis outbreak in an area with no previously known wildlife infections. G. Rossi, J. Crispell,T. Brough, S.J. Lycett, P.C.L. White, A. Allen, R.J. Ellis, S.V. Gordon, R. Harwood, E. Palkopoulou, E.L. Presho, R. Skuce, G.C. Smith, R.R. Kao

Using machine learning improves predictions of herd-level bovine tuberculosis breakdowns in Great Britain K. Stański, S. Lycett, T. Porphyre & B. M. de C. Bronsvoort

Genesis and spread of multiple reassortants during the 2016/2017 H5 avian influenza epidemic in Eurasia. S.J. Lycett,  A. Pohlmann, C. Staubach, V. Caliendo, M. Woolhouse, M. Beer,  T. Kuiken, and Global Consortium for H5N8, and Related Influenza Viruses

Predicting vaccine effectiveness in livestock populations: A theoretical framework applied to PRRS virus infections in pigs. V Bitsouni, S Lycett, T Opriessnig, A Doeschl-Wilson

A brief history of bird flu. SJ Lycett, F Duchatel, P Digard

Analysis of bovine viral diarrhoea virus: Biobank and sequence database to support eradication in Scotland. CG Russell, DM Grant, S Lycett, C Bachofen, GL Caldow, PD Burr, K Davie, N Ambrose, GJ Gunn, RN Zadoks

Role for migratory wild birds in the global spread of avian influenza H5N8. S Lycett et al

Supersize me: how whole-genome sequencing and big data are transforming epidemiology. RR Kao, DT Haydon, SJ Lycett, PR Murcia

The genesis and source of the H7N9 influenza viruses causing human infections in China. T Lam et al

Modelling the impact of co-circulating low pathogenic avian influenza viruses on epidemics of highly pathogenic avian influenza in poultry. S Nickbakhsh, MD Hall, I Dorigatti, SJ Lycett, P Mulatti, I Monne, A Fusaro, MEJ Woolhouse, A Rambaut, RR Kao

Broadwick: a framework for computational epidemiology. A O'Hare, SJ Lycett, T Doherty, LCM Salvador, RR Kao

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