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.

Tan, Y. et al. (2021) “Enhanced Recovery Pathways for Flap-Based Reconstruction: Systematic Review and Meta-Analysis”, Aesthetic Plastic Surgery, 45(5), pp. 2096–2115.

Nicholson, G. et al. (2021) “Interoperability of statistical models in pandemic preparedness: principles and reality”, arXiv.

Forna, A. et al. (2021) “Comparison of machine learning methods for estimating case fatality ratios: an Ebola outbreak simulation study”, PLoS One, 16(9).

Lissenden, N. et al. (2021) “Review and Meta-Analysis of the Evidence for Choosing between Specific Pyrethroids for Programmatic Purposes”, Insects, 12(9), p. 826.

Parag, K. and Donnelly, C. (2021) “Fundamental limits on inferring epidemic resurgence in real time using effective reproduction numbers”, p. 2021.09.08.21263270.

Bhatia, S. et al. (2021) “Estimating the number of undetected COVID-19 cases among travellers from mainland China”, Wellcome Open Research, 5, p. 143.

Davies, B. et al. (2021) “Altering the binding properties of PRDM9 partially restores fertility across the species boundary”, Molecular Biology and Evolution, 38(12), pp. 5555–5562.

Siejka-Zielinska, P. et al. (2021) “Cell-free DNA TAPS provides multimodal information for early cancer detection”, Science Advances, 7(36).

Lushasi, K. et al. (2021) “Reservoir dynamics of rabies in south-east Tanzania and the roles of cross-species transmission and domestic dog vaccination”, Journal of Applied Ecology, 58(11), pp. 2673–2685.

Jiang, X., Holmes, C. and McVean, G. (2021) “The impact of age on genetic risk for common diseases”, PLOS Genetics, 17(8).