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.

Whitaker, M. et al. (2023) “SARS-CoV-2 rapid antibody test results and subsequent risk of hospitalisation and death in 361,801 people”, Nature Communications, 14(1), p. 4957.

Pritchard, M. et al. (2023) “Natural immune boosting leads to synchrony in immunity and cyclic outbreaks of disease for pathogens with rapidly waning immunity”, in.

Tsui, J.-H. et al. (2023) “Genomic assessment of invasion dynamics of SARS-CoV-2 Omicron BA.1”, Science, 381(6655), pp. 336–343.

Lehmann, B. et al. (2023) “Optimal strategies for learning multi-ancestry polygenic scores vary across traits”, Nature Communications, 14(1), p. 4023.

Ter-Minassian, L. et al. (2023) “PWSHAP: a path-wise explanation model for targeted variables”, in Proceedings of the 40th International Conference on Machine Learning. Proceedings of Machine Learning Research, pp. 34054–34089.

Creswell, R. et al. (2023) “Understanding the impact of numerical solvers on inference for differential equation models”, arXiv.

Penn, M. and Donnelly, C. (2023) “Optimality of maximal-effort vaccination”, Bulletin of Mathematical Biology, 85.

Penn, M. et al. (2023) “Intrinsic randomness in epidemic modelling beyond statistical uncertainty”, Communications Physics, 6.

Gallagher, K. et al. (2023) “Identification and attribution of weekly periodic biases in epidemiological time series data.”

Pons-Salort, M. et al. (2023) “Changes in transmission of Enterovirus D68 (EV-D68) in England inferred from seroprevalence data”, eLife, 12, p. e76609.