Dr Marc Baguelin BSc MSc PhD

Assistant Professor


I am a mathematical modeller working at the Immunisation department at Public Health England and at the London of Hygiene and Tropical Medicine with Prof. John Edmunds on models of influenza transmission, immunisation and control.

After graduating from the Ecole Centrale de Lille with a MSc in Control engineering from the University of Lille in 2000, I completed a PhD in 2003 on modelling the co-evolution of populations of bacteria and phages. In 2004, I took a position as Research Associate to work in collaboration with the Animal Health Trust, Newmarket, analysing data from equine influenza. I first joined the department of zoology at the University of Cambridge and subsequently the Cambridge Infectious Diseases Consortium in the Department of Veterinary Medicine, following its creation in 2005. I developed a model of transmission of equine influenza including new techniques to infer parameter estimation from sparse data. The model helped to understand the role of compulsory vaccination in changing the dynamics of the equine influenza viruses following the introduction of compulsory vaccination for racehorses in 1981.

In January 2009, I joined the Health Protection Agency (now Public Health England), UK to work with Profs Miller and Edmunds on the modelling and economical evaluation of immunisation policies in the United Kingdom. During the outbreak of pandemic influenza virus in the United Kingdom, I was part of the team of scientists who provided early results to assess the transmission in the United Kingdom. In particular we developed algorithms to integrate epidemiological information with the temporal dynamics of the virus in order to improve estimation of the effective reproduction ratio of the disease. In order to inform vaccination policy decisions with the newly developed pandemic vaccine, I developed with colleagues a model to assess in real time the impact of vaccination strategies. This model incorporates a transmission model fitted to the epidemiological data with health care costs and savings applied to the disease burden. This model was developed and published in real time during the outbreak.

I am also an enthusiastic photographer. Some of my recent work can be seen on my personal website.




I teach on the "Modelling and the Dynamics of Infectious diseases" module offered by the LSHTM as part of the LSHTM MSc courses and on the eponymous short-course held during the summer. 


I am interested in how processes at different levels (social contacts, immune response, molecular sequences of the virus) can interact together and how they impact on the dynamics of infectious diseases. I believe that a more holistic approach to infectious disease modelling can greatly enhance our understanding of disease control mechanisms. I am currently working on the following projects: developing methods to use sequential serological samples to derive incidence using likelihood based method and adapt it to inform robust real time model of transmission, understanding the impact of changing social contacts during a calendar year and the possible impact on social distancing measures, evaluation of the long term effect of vaccination on seasonal influenza.

As part of Public Health England I am part of the evaluation of immunisation campaigns in the UK. With a team from Public Health England, the London School of Hygiene and Tropical Medicine and the Athens University of Economics and Business, we conducted a study about the efficiency of potential extensions of the current influenza vaccination programme. Our study resulted in a change of policy at the national level with an extension of the programme to 2-16 year old children.

Research areas

  • Bayesian Analysis
  • Disease control
  • Economic evaluation
  • Health care policy
  • Immunisation
  • Infectious disease policy
  • Modelling
  • Statistical methods
  • Surveillance
  • Vaccines


  • Economics
  • Epidemiology
  • Mathematical modelling
  • Molecular epidemiology
  • Statistics
  • Vaccinology

Disease and Health Conditions

  • Dengue
  • Infectious disease
  • Influenza
  • Pandemic diseases


  • United Kingdom

Other interests

  • Evidence synthesis
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