I currently work for Professor Katharina Hauck on DAEDALUS - an integrated epidemic and economic model to evaluate public-health interventions in response to pandemics. Applications include models curated for countries currently making policy decisions to respond to the ongoing COVID-19 pandemic, and assessing the return on investment of preparations made for future pandemics.
Previously, at the MRC Biostatistics Unit, I worked on developing network epidemic models to assess adaptive trial designs for vaccines, and on integrated transport and health-impact modelling (ITHIM). I completed my PhD in the Theoretical Systems Biology group of Imperial College London under the supervision of Professor Michael Stumpf, with thesis title "Probabilistic modelling of noise as a driving force in biological systems".
et al., 2022, Optimizing social and economic activity while containing SARS-CoV-2 transmission using DAEDALUS, Nature Computational Science, ISSN:2662-8457
et al., 2021, A guide to value of information methods for prioritising research in health impact modelling, Epidemiologic Methods, Vol:10, ISSN:2194-9263, Pages:1-22
et al., 2021, Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England, Nature, Vol:593, ISSN:0028-0836, Pages:266-269
et al., 2021, Genetic evidence for the association between COVID-19 epidemic severity and timing of non-pharmaceutical interventions, Nature Communications, Vol:12, ISSN:2041-1723, Pages:1-7