Professor Graham Medley

Professor of Infectious Disease Modelling

Background

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.
 

Affiliation

Centres

Teaching

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.

Research

I am currently involved in research projects on leprosy, visceral leishmaniasis, RSV and UK vaccination policy.

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?

Research areas

  • Diagnostics
  • Disease control
  • Immunisation
  • Infectious disease policy
  • Modelling
  • Public health

Disciplines

  • Epidemiology
  • Mathematical modelling

Disease and Health Conditions

  • HIV/AIDS
  • Human papillomavirus (HPV)
  • Infectious disease
  • Leishmaniasis
  • Leprosy
  • Neglected Tropical Diseases (NTDs)
  • Respiratory disease

Countries

  • India
  • United Kingdom

Other interests

  • Centre for the Mathematical Modelling of Infectious Diseases
  • Interdisciplinary research
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