My work is at the interface of mathematics and the epidemiology and evolution of pathogens. I hold an EPSRC Fellowship with the broad aim to develop the mathematical tools to connect sequence data for pathogens to pathogen ecology. I also have a long-standing interest on the dynamics of diverse interacting pathogens. For example, how does the interplay between co-infection, competition and selection drive the development of antimicrobial resistance? To answer these questions, my group is building new approaches to analysing phylogenetic trees derived from pathogen sequence data, studying tree space and branching processes, and doing ecological and epidemiological modelling.
I have varied teaching responsibilities including matlab, dynamical systems, project supervision and working with summer undergraduate reseachers.
Michelle Kendall and I have developed an approach to comparing phylogenetic trees (and other branching trees). It uses a novel metric on rooted trees, which can help to tease out different evolutionary stories making up a group of trees.
You can play with the tool online here using the web-based tree comparison tool that Michelle has developed.
We also have an R package: treescape
et al., 2019, Beyond the SNP threshold: identifying outbreak clusters using inferred transmissions., Mol Biol Evol
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et al., 2018, Genome-based transmission modelling separates imported tuberculosis from recent transmission within an immigrant population, Microbial Genomics, Vol:4, ISSN:2057-5858
et al., 2018, Internal migration and transmission dynamics of tuberculosis in Shanghai, China: an epidemiological, spatial, genomic analysis, Lancet Infectious Diseases, Vol:18, ISSN:1473-3099, Pages:788-795
et al., 2018, Estimating Transmission from Genetic and Epidemiological Data: A Metric to Compare Transmission Trees, Statistical Science, Vol:33, ISSN:0883-4237, Pages:70-85