ProfessorChristl Donnelly, CBE, FRS, FMedSci

In addition to my Imperial role, I am Head of Department and Professor of Applied Statistics in the Department of Statistics at the University of Oxford.

My research programme brings together and develops statistical and biomathematical methods to analyse epidemiological patterns of infectious diseases. I have worked on a variety of diseases. I also have interests in ecology, conservation and animal welfare.

Statistical Epidemiology
I use rigorous parameter estimation and hypothesis testing to gain the robust insights from dynamical models of disease transmission, demography and interventions.

My research programme aims to improve our understanding of (and ability to predict) the effect of interventions on infectious agent transmission dynamics and population structure. The ultimate goal is to make control strategies as effective as they can be. Without good estimates of epidemiological parameters and knowledge of the associated uncertainty in them, control programmes and preventive measures cannot be designed optimally nor evaluated appropriately.

Such research involves the development of new methods due to the complexities of infectious disease systems – but always driven by the need to answer practical questions. For example:

Who is at greatest risk of SAR-CoV-2 infection right now?
Will culling badgers reduce the incidence of bovine TB in cattle? How might cattle vaccination reduce disease risk within a herd?
How can modified mosquitoes help reduce the risks of dengue?
How many MERS (Middle East Respiratory Syndrome) infections have there been been in the Middle East to date?
Through this research, I have provided quantitative scientific advice to government on COVID-19, bovine TB, FMD and TSEs (including BSE, vCJD and scrapie). In this context I served as the deputy chairman of the Independent Scientific Group on Cattle TB (1998-2007) advising government on research and overseeing a large randomized trial of badger culling strategies. I am currently on the Royal Statistical Society's COVID-19 Task Force (2020-).

In addition to providing science-based policy advice, I am interested in promoting the public understanding of epidemiology and statistics – making the conclusions from important results accessible to a wide audience.

I was elected Fellow of the Royal Society (FRS) in 2016 and Fellow of the Academy of Medical Sciences (FMedSci) in 2015. I was an honorary fellow of the ZSL Institute of Zoology.