Biography
Alex conducts mathematical and statistical analyses for the Vaccine Confidence Project. His background lies in physics (MSci, Imperial College) and mathematical and statistical modelling (PhD, Imperial College; MSc, University of Oxford) and harnessing tools from these fields to model vaccine confidence data. Alex holds a doctorate from Imperial College London, where he was also an EPSRC Prize Fellow, with the PhD thesis: “A mathematical assessment of the global state of vaccine coverage and confidence.”
Alex’s research focuses on using (mainly) Bayesian statistical methods to solve problems at the intersection of public health and vaccine confidence and vaccine acceptance. His particular interest lies in using novel methods to infer vaccine confidence at national and sub-national levels; estimating and forecasting vaccine coverage rates for COVID-19 vaccines and routine childhood immunisation programmes; the social and demographic determinants of vaccine confidence and acceptance, and the large-scale inference of vaccine attitudes in the absence of survey data
Alex has worked extensively on large-scale surveys at global, national, and – more recently – sub-national scales, with his recent research seeking to understand local heterogeneities in vaccine acceptance.
