Publications by Statistical Genetics and Epidemiology

Our research spans areas of statistical genetics, in particular the development of powerful statistical approaches to analyse genetic data, as well as studying infectious diseases.

Riley, S. et al. (2021) “REACT-1 round 8 final report: high average prevalence with regional heterogeneity of trends in SARS-CoV-2 infection in the community in England during January 2021”, p. 2021.01.28.21250606.

Riley, S. et al. (2021) “REACT-1 round 8 interim report: SARS-CoV-2 prevalence during the initial stages of the third national lockdown in England”, p. 2021.01.20.21250158.

Lyons, J. et al. (2021) “Protocol for the development of the Wales Multimorbidity e-Cohort (WMC): data sources and methods to construct a population-based research platform to investigate multimorbidity”, BMJ Open, 11(1).

Lehmann, B. et al. (2021) “Optimal strategies for learning multi-ancestry polygenic scores vary across traits”, p. 2021.01.15.426781.

Unwin, H. et al. (2021) “More than 5.2 Million Children Affected by Global Surges in COVID-Associated Orphanhood and Caregiver Death: New Evidence for National Responses”, SSRN Electronic Journal.

Mullins, E. et al. (2021) “Tracking the Incidence and Risk Factors for Sars-Cov-2 Infection in North West London by Detection of Antibody in Historical Maternal Booking Serum Samples”, SSRN Electronic Journal.

Hillis, S. et al. (2021) “Under the Radar: Global Minimum Estimates for COVID-19-Associated Orphanhood and Deaths Among Caregivers During 2020”, SSRN Electronic Journal.

Mo, Y. et al. (2021) “Transmission dynamics of SARS-CoV-2 in the hospital setting”, medRxiv.

Fong, E. and Holmes, C. (2021) “Conformal Bayesian Computation”, in Advances in Neural Information Processing Systems, pp. 18268–18279.

Wilde, H. et al. (2021) “Foundations of Bayesian Learning from Synthetic Data”, in Proceedings of Machine Learning Research, pp. 541–549.