Imperial College London


Faculty of MedicineSchool of Public Health

Research Associate in Mathematical Modelling







Norfolk PlaceSt Mary's Campus





My main interest is the statistical analysis of stochastic compartmental models for epidemics under a Bayesian framework.

Since March 2020 I have been working on the real-time modelling of the COVID-19 pandemic in the UK as part of the Imperial COVID-19 Response Team with Dr Marc Baguelin, Dr Anne Cori and Prof Neil Ferguson.

As part of this work we have been developing analyical and computational tools for use in potential future pandemics as part of the NIHR Health Protection Research Unit in Modelling and Health Economics.

Previous work includes studying contact tracing, household models, and other infectious diseases such as influenza and human African trypanosomiasis.



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 ES, Whittles LK, Lees JA, et al., 2021, Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England, 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

Hogan AB, Winskill P, Watson OJ, et al., 2021, Within-country age-based prioritisation, global allocation, and public health impact of a vaccine against SARS-CoV-2: a mathematical modelling analysis, Vaccine, Vol:39, ISSN:0264-410X, Pages:2995-3006

Crump RE, Huang C, Knock ES, et al., 2021, Quantifying epidemiological drivers of <i>gambiense</i> human African Trypanosomiasis across the Democratic Republic of Congo, Plos Computational Biology, Vol:17, ISSN:1553-734X

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