Research Group
Research Overview
My research is focused on large scale predictions for disease spread and management. My current projects involve modelling the spread of the Ramorum disease epidemic (also known as Sudden Oak Death, caused by P. ramorum) in the UK, working with regulators to provide outputs including predictions of disease spread and the effect of management strategies. I am also involved in predicting the potential for future spread of Sudden Oak Death on the east coast of the USA, and looking at the effects of spread of citrus diseases at the state scale in Florida.
I am part of the production and deployment of a web based interactive utility to demonstrate the effect of control in realistic landscapes and additionally the development of a generic computational framework for stochastic simulation of spatial models of epidemics and developing a flexible, computationally-efficient suite of models for the analysis of disease spread and control in heterogeneous environments.
Previous Positions
- 2010-Present Postdoctoral Research Associate, Department of Plant Sciences, University of Cambridge
- 2009-2010 Research Assistant, Epidemiology and Modelling Group, Department of Plant Sciences, University of Cambridge
Qualifications
- 2008-2009 MMath, Girton College, University of Cambridge
- 2005-2008 MA Hons (Cantab), Mathematics, Girton College, University of Cambridge
Key Publications
An integrated model for pre- and post-harvest aflatoxin contamination in maize. https://www.nature.com/articles/s41538-023-00238-7
A modelling framework to assess the likely effectiveness of facemasks in combination with ‘lock-down’ in managing the COVID-19 pandemic. https://royalsocietypublishing.org/doi/10.1098/rspa.2020.0376
Time-Dependent Infectivity and Flexible Latent and Infectious Periods in Compartmental Models of Plant Disease. https://apsjournals.apsnet.org/doi/10.1094/PHYTO-12-10-0338
Teaching
Supervisions for Maths A, Mathematical Biology and demonstrations for Mathematical Biology for Natural Sciences Tripos students (Part IA)