DrMarc Baguelin

I am a Senior Lecturer in Infectious Disease Epidemiology at Imperial College London and an Associate Professor at the London School of Hygiene and Tropical Medicine. I am also a member of the Scientific Pandemic Influenza Group on Modelling (SPI-M), an advisory group to the UK Department of Health and Social Care, providing advice on infectious disease modelling and epidemiology since 2010. Since 2020, I have also been a member of the Comité Technique des Vaccinations of the Haute Autorité de la Santé, an expert committee advising French policymakers on vaccine-related matters.

During the 2009 influenza pandemic, the 2014 Ebola outbreak, and the SARS-Cov-2 pandemic, my models have played a significant role in influencing substantial changes in national vaccination policies, particularly in seasonal influenza paediatric vaccination in 2012.

From February 2020 to spring 2022, I led the UK Real-time Modelling (RTM) team at Imperial College, establishing a robust modelling pipeline for collaborative analysis. The team provided weekly estimates and projections, supporting UK government decision-making during the Covid pandemic. This effort resulted in the development of 'dust' and 'mcstate' R packages, enhancing our toolkit alongside 'odin' and 'orderly'.

In 2021, Imperial College London was awarded The Queen’s Anniversary Prize for Higher and Further Education for “world-class expertise in data modelling and real-time analysis, supporting a holistic response to Covid-19 in the UK and internationally,” recognising the work of the Imperial College COVID-19 Response Team.

In 2022, I received the SPI-M-O Award for Modelling and Data Support (SAMDS) and shared the Weldon Memorial Prize from Oxford University with other SPI-M members for contributions to biological modelling methods.

Additionally, in 2023, the Imperial College London Faculty of Medicine received the 25th Anniversary Staff Award for Outstanding Achievement through Collaborative Research was awarded to the MRC Centre for Global Infectious Disease Analysis.

My research focuses on advancing mathematical models to inform and enhance public health policy decisions. I believe that improving methodological and computational tools has the power to leverage science for better decision-making. My contributions span assessing the impact of immunisation campaigns, integrating serological data into models for understanding transmission, and modelling outbreak responses. I am a vocal advocate for open data and transparent coding in public health decision-making.
My group develops inference methods and tools for modelling infectious disease transmission and potential interventions, focusing on a Bayesian evidence synthesis approach where multiple data streams can be used to inform parameters of complex mechanistic models in real-time applications.

Selected Grants:
- UK Research and Innovation (UKRI) COVID-19 rolling scheme - Co-Investigator: “Multiresolution predictive dynamics of COVID-19 risk and intervention effects” (Sep 2020 - Feb 2022) - £550,702.42
- NIHR (Global Health Research Groups) Co-Investigator and Work Package Leader: Modelling and cost-effectiveness “Evidence to Policy pathway to Immunisation in China” (2017-2021) - £1.81 million
- European Commission (Horizon 2020) Work Package Leader: Modelling and cost-effectiveness “Integrated Monitoring of Vaccines in Europe” (I-MOVE+) (2015-2018) - £2.5 million
- MRC (Infection and Immunity Board) Co-Investigator: "Historical serology and herd immunity of influenza viruses" (2013-2016) - £1.1 million
- Wellcome Trust (Project Award) Principal Investigator: "Coupling epidemiological and genetic using mathematical modelling" (2012-2014) - £262,342