Bio
My work focuses on the development of complex statistical models for epidemics designed to estimate disease burden and transmission and to predict their impact on healthcare services. In particular, I'm interested in using such models for real-time Bayesian statistical inference and the computational algorithms that can make improve the timeliness of this task and permit greater modelling complexity/detail. Throughout the SARS-CoV-2 pandemic I was the UKHSA (then PHE) lead on a real-time modelling collaboration between UKHSA and the MRC Biostatistics Unit at the University of Cambridge, contributing results to the estimation of R (https://www.gov.uk/guidance/the-r-value-and-growth-rate), infection incidence and medium-term projections (https://www.mrc-bsu.cam.ac.uk/now-casting), and was an academic collaborator in the development of the ONS Coronavirus Infection Survey. In addition I have developed related methods to uncover incidence of HIV infection and the prospects of its elimination as a public health threat to gay and bisexual men and to carry out seasonal influenza forecasting.
My work with the Alan Turing Institute will resolve around improving the tractability of real-time inference from mechanistic models for infectious disease transmission using Julia and the probabilistic programming language Turing.jl.