Summary
I am an MRC career development award fellow at Imperial College London and an honorary lecturer at the University of Bristol. My background is in control and information engineering but I have increasingly worked on statistical and methodological problems in phylodynamics and epidemic modelling.
My research programme focuses on adapting and leveraging concepts from engineering to obtain a sharper and more rigorous understanding of biological processes. My current interests lie in (i) probing the explainability and predictability limits of statistical models across disease transmission scales and (ii) designing new algorithms and tools for improving infectious disease outbreak surveillance and suppression by using feedback control strategies.
See the links below for more information and find me on twitter @krisparag1.
Publications
Journals
Bhatia S, Parag KV, Wardle J, et al., 2023, Retrospective evaluation of real-time estimates of global COVID-19 transmission trends and mortality forecasts, Plos One, Vol:18, ISSN:1932-6203
Parag K, Cowling B, Lambert B, 2023, Angular reproduction numbers improve estimates of transmissibility when disease generation times are misspecified or time-varying, Proceedings of the Royal Society B: Biological Sciences, Vol:290, ISSN:0962-8452
Policarpo JMP, Ramos AAGF, Dye C, et al., 2023, Scale-free dynamics of COVID-19 in a Brazilian city, Applied Mathematical Modelling: Simulation and Computation for Engineering and Environmental Systems, Vol:121, ISSN:0307-904X, Pages:166-184
Pakkanen MS, Miscouridou X, Penn MJ, et al., 2023, Unifying incidence and prevalence under a time-varying general branching process, Journal of Mathematical Biology, Vol:87, ISSN:0303-6812
Parag KV, Obolski U, 2023, Risk averse reproduction numbers improve resurgence detection, Plos Computational Biology, Vol:19, ISSN:1553-734X