Professor Graham Medley
of Infectious Disease Modelling
15-17 Tavistock Place
My overall 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 how models relate to policy development. The interaction of transmission with societal and political processes is of particular interest to me, and the focus of my work on HIV/AIDS.I am on the Board of Reviewing Editors for Science, on an expert group in the Infected Blood Inquiry, and am chair of SPI-M, and am currently attending SAGE as part of the UK COVID-19 response.
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 visceral leishmaniasis, schistosomiasis, RSV, HIV and UK vaccination policy.
- The visceral leishmaniasis research is part of the SPEAK India Consortium to develop quantitative frameworks to guide policy towards elimination and sustaining elimination. A key part of this work is the "operational imperative" - we only do research of immediate and direct use to the elimination effort.
- The schistosomiasis and visceral leishmaniasis research is part of the NTD Modelling Consortium.
- 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.
- I am involved in the OPTIONS modelling team to develop frameworks to evaluate the impact of PrEP for adolescent girls and young women in sub-Saharan Africa.
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?