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, Donnelly CA, 2021, Fundamental limits on inferring epidemic resurgence in real time
Parag KV, 2021, Improved estimation of time-varying reproduction numbers at low case incidence and between epidemic waves, Plos Computational Biology, ISSN:1553-734X, Pages:e1009347-e1009347
et al., 2021, Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence, Science, Vol:373, ISSN:0036-8075, Pages:889-895
Parag K, 2021, Sub-spreading events limit the reliable elimination of heterogeneous epidemics, Journal of the Royal Society Interface, Vol:18, ISSN:1742-5662, Pages:1-10
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