Oxford university logo and department of statistics logo

To Department of Statistics Site

 Menu

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.

Liley, J. et al. (2024) “Development and assessment of a machine learning tool for predicting emergency admission in Scotland”, npj Digital Medicine, 7(1).
Mills, C. et al. (2024) “The utility of wastewater surveillance for monitoring SARS-CoV-2 prevalence”, PNAS Nexus, 3(10).
Mills, C. et al. (2024) “Renewal equations for vector-borne diseases”, arXiv.
Gallagher, K. et al. (2024) “Ten simple rules for training scientists to make better software”, PLoS Computational Biology, 20(9).
Gallagher, K. et al. (2024) “Ten simple rules for training scientists to make better software”, PLoS Computational Biology, 20(9).
Pigoli, D. et al. (2024) “Assessing the Performance of Machine Learning Methods Trained on Public Health Observational Data: A Case Study From COVID‐19”, Statistics in Medicine [Preprint].
Pigoli, D. et al. (2024) “Assessing the Performance of Machine Learning Methods Trained on Public Health Observational Data: A Case Study From COVID‐19”, Statistics in Medicine [Preprint].
Miles, V. et al. (2024) “Evaluating camera‐based methods for estimating badger ( Meles meles ) density: Implications for wildlife management”, Ecological Solutions and Evidence, 5(3).
Smith, D. et al. (2024) “Health and economic impacts of Lassa vaccination campaigns in West Africa”, Nature Medicine, 30(12).
Mills, C., Woodroffe, R. and Donnelly, C. (2024) “An extensive re-evaluation of evidence and analyses of the Randomised Badger Culling Trial II: In neighbouring areas”, Royal Society Open Science, 11(8).