Professor Graham Medley
of Infectious Disease Modelling
15-17 Tavistock Place
I joined the Social and Mathematical Epidemiology group at LSHTM in April 2015, after 21 years at the University of Warwick, and 10 years at Imperial College before that. I moved to the faculty of Public Health and Policy and the Department of Global Health and Development because I have become fascinated by the interaction between infectious disease and the economic, social and political spheres.
My interest is the transmission dynamics of infectious disease, and I have published on many different pathogens and hosts - see [Google] or [ORCID] or [ResearcherID] for a full list. I am particularly interested in understanding how interventions are and should be designed to control infectious disease; and my definition of "interventions" includes both the biological (e.g. immune response) and societal action (e.g. immunisation).I am on the Board of Reviewing Editors for Science, a handling editor for Mathematical Biosciences, and a Joint Editor for Epidemics.
I am involved in teaching on two MSc modules: Analytical Models for Decision Making and Applied Communicable Disease Control. I teach on the Infectious Disease Modelling short course.
I am currently involved in research projects on leprosy, visceral leishmaniasis, RSV and UK vaccination policy.
- The leprosy research is part of the NTD Modelling Consortium project to develop back-calculation approaches to estimate transmission rates.
- The visceral leishmaniasis research is part of the NTD Modelling Consortium project to develop quantitative frameworks to guide policy towards elimination. I am part of the SPEAK India consortium to develop research that supports the attainment and maintenance of elimination of VL in India.
- I have been collaborating with Professor D. James Nokes on the epidemiology of respiratory syncytial virus (RSV) for many years, and more recently with the Virus Epidemiology and Control research group in Kilifi, Kenya.
- The UK vaccination policy is to develop quantative models that can be used to predict the cost-effectiveness of different vaccination strategies. The project, MEMVIE, is based at the University of Warwick.
As part of my new role, I will be developing research that crosses disciplinary boundaries, and in particular, brings in social sciences to mathematical models of infectious disease. I am deputy director of CMMID.
It is intriguing that, currently, most models of infectious disease transmission dynamics assume that all hosts are identical, when we know that they are not. For some infections, such as measles, it is probably adequate to consider that everybody is average when predicting the impact of immunisation. However, such models result in policy decisions that have "assuming that everybody is equal" as an unwritten assumption. For other infections, such as HIV, assuming that everybody is average is known to be inadequate; the commonest model structures assume that the population is divided into discrete groups, where everybody within the group is average for that group. But how should the groups be chosen, and how do they interact?