I’m an epidemiologist and biostatistician with specialised interests in emerging infectious diseases and zoonotic viruses.
My research aims to better understand the complex patterns behind pathogen transmission from one host species to another and ultimately, pandemic potential in humans. Using EID2, a large data resource of host-pathogen associations, I'm exploring how machine learning methods can take advantage of ecological and genomic information to make better epidemiological predictions. I'm also developing automated data mining algorithms to capture clinical characteristics of RNA viruses from published texts, which has traditionally been challenging as data is often poor-quality.
I obtained my PhD within the Institute of Evolutionary Biology, University of Edinburgh, where I used various statistical approaches to investigate the ecology and evolution of human-to-human transmissibility and virulence of RNA viruses. I then completed a six-month postdoctoral biostatistician role, developing longitudinal models for a range of clinical outcomes from e-health records.
I also have professional interests in teaching methods and pedagogy within statistical sciences; I recently completed a lectureship in statistics with the sigma Mathematics and Statistics Support Centre at Coventry University. Finally, I'm also interested in alternative routes of science outreach and as an Ambassador for the Royal Statistical Society, I advise on ways we can better present statistics and risks to the public.