Imperial College London


Faculty of MedicineSchool of Public Health

Senior Lecturer



m.baguelin Website




511School of Public HealthWhite City Campus





I am a Lecturer in Infectious Disease Epidemiology at Imperial College London and Associate Professor at the London School of Hygiene and Tropical Medicine. My group develops inference methods and tools for modelling infectious disease transmission and potential interventions. We are focussing on a Bayesian evidence synthesis approach where multiple data streams can be used to inform parameters of complex mechanistic models in real time applications.

Since January 2020, I have been part of the Imperial College London Covid-19 response team, involved in the Centre’s effort to understand the properties of the emerging virus in the early phase and subsequently leading the UK Real-time modelling team informing the UK government through SPI-M-O.

I am also a member of the Scientific Pandemic Influenza Group on Modelling (SPI-M) and the Commission technique des vaccinations (CTV), France NITAG.

Selected Publications

Journal Articles

Sonabend R, Whittles LK, Imai N, et al., 2021, Non-pharmaceutical interventions, vaccination, and the SARS-CoV-2 delta variant in England: a mathematical modelling study, The Lancet, Vol:398, ISSN:0140-6736, Pages:1825-1835

Knock E, Whittles L, Lees J, et al., 2021, The 2020 SARS-CoV-2 epidemic in England: key epidemiological drivers and impact of interventions, Science Translational Medicine, Vol:13, ISSN:1946-6234, Pages:1-12

FitzJohn RG, Knock ES, Whittles LK, et al., 2021, Reproducible parallel inference and simulation of stochastic state space models using odin, dust, and mcstate [version 2; peer review: 2 approved], Wellcome Open Research, Vol:5, ISSN:2398-502X

Opatowski L, Baguelin M, Eggo RM, 2018, Influenza interaction with cocirculating pathogens and its impact on surveillance, pathogenesis, and epidemic profile: A key role for mathematical modelling, PLOS Pathogens, Vol:14, ISSN:1553-7366

Baguelin M, Flasche S, Camacho A, et al., 2013, Assessing Optimal Target Populations for Influenza Vaccination Programmes: An Evidence Synthesis and Modelling Study, PLOS Medicine, Vol:10, ISSN:1549-1277

Dureau J, Kalogeropoulos K, Baguelin M, 2013, Capturing the time-varying drivers of an epidemic using stochastic dynamical systems, Biostatistics, Vol:14, ISSN:1465-4644, Pages:541-555

Baguelin M, Van Hoek AJ, Jit M, et al., 2010, Vaccination against pandemic influenza A/H1N1v in England: A real-time economic evaluation, Vaccine, Vol:28, ISSN:0264-410X, Pages:2370-2384


Ferguson N, Laydon D, Nedjati Gilani G, et al., 2020, Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand

Imai N, Cori A, Dorigatti I, et al., 2020, Report 3: Transmissibility of 2019-nCoV

More Publications