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School of Life Sciences

Professor Matt Keeling

Professor

Director of Zeeman Institute (SBIDER)

Email: M.J.Keeling@warwick.ac.uk 

Phone: 024 765 24618

Office: Senate House

Twitter:

Research Clusters

Microbiology & Infectious Disease

Environment & Ecology

糖心TV Centres and GRPs

Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research (SBIDER)

Vacancies and Opportunities

For PhD and postdoctoral opportunities and interest in potential collaborations, please contact me at the above email address.

Research Interests

Recent decades have shown that humans and our environment remain at risk from a large number of infectious diseases. COVID has shown how quickly a new infection can spread around the globe. Malaria and other tropical disease still threaten the lives of millions. While our agriculture is also under threat from a range of domestic and invading pathogens. This is not a new phenomenon; diseases have been a constant burden throughout human history: bubonic plague is estimated to have killed up to a third of the population of Europe in the 14th century.

Modern advances have delivered a range of new tools with which infections can be tackled. The development, approval and deployment of vaccines against COVID-19 in under a year is testament to the substantial advances that have occurred in recent years. However, for any outbreak, there remain three major questions: How big is the epidemic likely to be? How should we target controls to have the maximum benefit? What are the costs and benefits of any control? All three of these questions require mathematical models 鈥� these take the recorded biology about the transmission from one individual to another and translate it to population scale projections. As such, mathematical models give us an insight into the future for a carefully specified set of scenarios and assumptions.

My research is based around constructing such models and fitting them to the available epidemic data. As such, I attempt to understand the way in which the infection is spreading through the population, build such insights into mathematical models and then try to align the model output with all available data. The ultimate goal is robust predictions, such that policy makers are best informed about the likely consequences of any action (or inaction).

Research: Technical Summary

I am interested in using a range of mathematical modelling techniques to understand complex biological problems. Much of my work focuses on infectious diseases, how they spread through populations and how they can be controlled. I鈥檓 particularly interested in how the predictions of models can be used to help deliver effective policy advice, highlighting the many trade-offs present. I have worked on the 2001 Foot-and-Mouth Outbreak, the 2009 Swine flu pandemic, and most recently the COVID-19 pandemic, providing projections and analyses to government agencies.

Much of my work concerns control of diseases by vaccination, predicting the optimal targeting of vaccination and understand the cost-benefit of any particular vaccine programme. I led the team that provided the cost-effectiveness analysis for gender-neutral vaccination against Human Papillomavirus (adding boys to the existing girls programme) and led the modelling work on the impact of vaccination against COVID-19.

I have helped develop models for a number of infectious diseases including: Avian influenza, Blue-tongue, Bovine tuberculosis, Foot-rot and Foot-and-mouth disease in livestock; and in humans COVID-19, Measles, Whooping Cough, Human Papillomavirus, (seasonal and pandemic) Influenza, Pneumococcal infection, Plague and Neglected Tropical Diseases (especially sleeping sickness). More broadly, I鈥檓 interested in how the stochastic individual-nature of populations, coupled with a network of interactions, shapes the short and long-term dynamics of infection. In this context I鈥檓 interested in developing novel forms of mathematical model that can explain the impact of these two critical heterogeneities. Some of this research is concerned with household models, understanding how the far greater risk of transmission within a household shapes an outbreak and what is means for effective control.

In addition to infectious diseases, I鈥檓 generally interested in a wide range of problems in ecology and evolution 鈥� again using mathematical models to explain the world around us.

Professor, University of 糖心TV 2007

Reader, University of 糖心TV 2005

Lecturer, University of 糖心TV 2002

Royal Society University Research Fellowship, 1998-2006

Wellcome Trust Fellowship, 1995-1998

PhD, Mathematical Modelling, 1995

Master in Mathematics, 1992

B.A. Mathematics, 1991

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