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.

Longini, I. et al. (2022) “A platform trial design for preventive vaccines against Marburg virus and other emerging infectious disease threats”, Clinical Trials, 19(6), pp. 647–654.

Creswell, R. et al. (2022) “A Bayesian nonparametric method for detecting rapid changes in disease transmission”, medRxiv.

Elliott, P. et al. (2022) “Twin peaks: The Omicron SARS-CoV-2 BA.1 and BA.2 epidemics in England”, Science, 376(6600), p. eabq4411.

Chadeau-Hyam, M. et al. (2022) “Breakthrough SARS-CoV-2 infections in double and triple vaccinated adults and single dose vaccine effectiveness among children in Autumn 2021 in England: REACT-1 study”, EClinicalMedicine, 48, p. 101419.

Lambert, B. and Vehtari, A. (2022) “R*: A Robust MCMC Convergence Diagnostic with Uncertainty Using Decision Tree Classifiers”, Bayesian Analysis, 17(2), pp. 353–379.

Benedetto, U. et al. (2022) “Machine learning improves mortality risk prediction after cardiac surgery: Systematic review and meta-analysis”, Journal of Thoracic and Cardiovascular Surgery, 163(Int Stat Rev 80 2012), pp. 2075 – 2087.e9.

Parag, K., Thompson, R. and Donnelly, C. (2022) “Are epidemic growth rates more informative than reproduction numbers?”, Journal of the Royal Statistical Society: Series A, 185(S1), pp. S5 - S15.

Penn, M. and Donnelly, C. (2022) “Analysis of a double Poisson model for predicting football results in Euro 2020”, PLoS One, 17(5).

van der Vegt, S. et al. (2022) “Learning transmission dynamics modelling of COVID-19 using comomodels”, Mathematical Biosciences, 349.

Madge, O. et al. (2022) “The COVID-19 pandemic is associated with reduced survival after pancreatic ductal adenocarcinoma diagnosis: A single-centre retrospective analysis”, Journal of Clinical Medicine, 11(9).