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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.

Lovell-Read, F. et al. (2020) “Interventions targeting nonsymptomatic cases can be important to prevent local outbreaks: SARS-CoV-2 as a case-study”, p. 2020.11.06.20226969.
Riley, S. et al. (2020) “High prevalence of SARS-CoV-2 swab positivity and increasing R number in England during October 2020: REACT-1 round 6 interim report”, p. 2020.10.30.20223123.
Hawryluk, I. et al. (2020) “Inference of COVID-19 epidemiological distributions from Brazilian hospital data”, Journal of The Royal Society Interface, 17(172), p. 20200596.
Hawryluk, I. et al. (2020) “Inference of COVID-19 epidemiological distributions from Brazilian hospital data: Inference of COVID-19 epidemiological distributions from Brazilian hospital data”, Journal of the Royal Society Interface, 17(172).
Radhakrishnan, S. et al. (2020) “Rabies as a public health concern in India – a historical perspective”, Tropical Medicine and Infectious Disease, 5(4).
O’Driscoll, M. et al. (2020) “A comparative analysis of statistical methods to estimate the reproduction number in emerging epidemics with implications for the current COVID-19 pandemic”, Clinical Infectious Diseases, 73(1), pp. e215 - e223.
Riley, S. et al. (2020) “High and increasing prevalence of SARS-CoV-2 swab positivity in England during end September beginning October 2020: REACT-1 round 5 updated report”, p. 2020.10.12.20211227.
Watson, J. et al. (2020) “A cautionary note on the use of unsupervised machine learning algorithms to characterise malaria parasite population structure from genetic distance matrices”, PLoS Genetics, 16(10).
Riley, S. et al. (2020) “High prevalence of SARS-CoV-2 swab positivity in England during September 2020: interim report of round 5 of REACT-1 study”, p. 2020.09.30.20204727.
O’Cathail, S. et al. (2020) “NRF2 metagene signature is a novel prognostic biomarker in colorectal cancer”, Cancer Genetics, 248, pp. 1–10.