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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.

Rivera, L. et al. (2024) “Characteristics of Madariaga and Venezuelan equine encephalitis virus infections, Panama”, Emerging Infectious Diseases, 30(14S), pp. S94 - S104.
Bajaj, S. et al. (2024) “COVID-19 testing and reporting behaviours in England across different sociodemographic groups: a population-based study using testing data and data from community prevalence surveillance surveys”, The Lancet Digital Health, 6(11), pp. e778 - e790.
Bajaj, S. et al. (2024) “COVID-19 testing and reporting behaviours in England across different sociodemographic groups: a population-based study using testing data and data from community prevalence surveillance surveys”, The Lancet Digital Health, 6(11), pp. e778 - e790.
Bajaj, S. et al. (2024) “COVID-19 testing and reporting behaviours in England across different sociodemographic groups: a population-based study using testing data and data from community prevalence surveillance surveys”, The Lancet Digital Health, 6(11), pp. e778 - e790.
Liley, J. et al. (2024) “Publisher Correction: Development and assessment of a machine learning tool for predicting emergency admission in Scotland”, npj Digital Medicine, 7(1), p. 302.
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).