My research is highly multidisciplinary and uses ideas from statistics and control engineering to obtain a sharper and more rigorous understanding of biological processes. In particular, I have applied stochastic, information, queueing, estimation and control theory to uncover new insights into molecular biology, epidemiology and invertebrate neuroscience. My current work looks at developing new models for epidemic transmission and control, which justifiably trade complexity with reliability.
Parag K, Donnelly C, Using information theory to optimise epidemic models for real-time prediction and estimation, Plos Computational Biology, ISSN:1553-734X
et al., Potential impact of the COVID-19 pandemic on HIV, TB and malaria in low- and middle-income countries: A Modelling Study, The Lancet Global Health, ISSN:2214-109X
et al., 2020, Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe, Nature, ISSN:0028-0836