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 KV, Pybus OG, Wu C-H, 2021, Are skyline plot-based demographic estimates overly dependent on smoothing prior assumptions?, Systematic Biology, ISSN:1063-5157
Parag KV, Thompson RN, Donnelly CA, 2021, Are epidemic growth rates more informative than reproduction numbers?
et al., 2021, Reduction in mobility and COVID-19 transmission, Nature Communications, Vol:12, ISSN:2041-1723
et al., 2021, Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK, Science, Vol:371, ISSN:0036-8075, Pages:708-+
et al., 2021, Resurgence of COVID-19 in Manaus, Brazil, despite high seroprevalence, Lancet, Vol:397, ISSN:0140-6736, Pages:452-455