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.

Naidoo, R. et al. (2022) “A multistage mixed-methods evaluation protocol for the national testing response during the COVID-19 pandemic in England”, medRxiv.

Venkatesh, S. et al. (2022) “Genetic architecture of longitudinal obesity trajectories in primary care electronic health records”, in HUMAN HEREDITY, pp. 21–22.

Whitaker, M. et al. (2022) “Variant-specific symptoms of COVID-19 among 1,542,510 people in England”, medRxiv.

Clivio, O. et al. (2022) “Neural Score Matching for High-Dimensional Causal Inference”, in Proceedings of Machine Learning Research, pp. 7076–7110.

Eales, O. et al. (2022) “Quantifying changes in the IFR and IHR over 23 months of the SARS-CoV-2 pandemic in England”, medRxiv.

Eales, O. et al. (2022) “Appropriately smoothing prevalence data to inform estimates of growth rate and reproduction number”, medRxiv.

Parag, K., Donnelly, C. and Zarebski, A. (2022) “Quantifying the information in noisy epidemic curves”, medRxiv.

Penn, M. and Donnelly, C. (2022) “Optimality of Maximal-Effort Vaccination”, medRxiv.

Hillis, S. et al. (2021) “COVID-19-Associated Orphanhood and Caregiver Death in the United States”, arXiv.

McCrone, J. et al. (2021) “Context-specific emergence and growth of the SARS-CoV-2 Delta variant”, p. 2021.12.14.21267606.