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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.

Parag, K. et al. (2020) “An exact method for quantifying the reliability of end-of-epidemic declarations in real time”, p. 2020.07.13.20152082.
Investigators, R. et al. (2020) “Community prevalence of SARS-CoV-2 virus in England during May 2020: REACT study”, p. 2020.07.10.20150524.
Miguel, E. et al. (2020) “A systemic approach to assess the potential and risks of wildlife culling for infectious disease control”, Communications Biology, 3.
Parag, K. and Donnelly, C. (2020) “Using information theory to optimise epidemic models for real-time prediction and estimation”, PLOS Computational Biology, 16(7), p. e1007990.
Thompson, R. et al. (2020) “Key Questions for Modelling COVID-19 Exit Strategies”, arXiv.
Bhatia, S. et al. (2020) “Estimating the number of undetected COVID-19 cases among travellers from mainland China”, Wellcome Open Research, 5, p. 143.
Okell, L. et al. (2020) “Have deaths from COVID-19 in Europe plateaued due to herd immunity?”, Lancet, 395(10241), pp. e110 - e111.
Kim, E. et al. (2020) “The end game – A quantitative assessment tool for anastomosis in simulated microsurgery”, Journal of Plastic Reconstructive & Aesthetic Surgery, 73(6), pp. 1116–1121.
Foster, T. et al. (2020) “Model Evidence with Fast Tree Based Quadrature”, arXiv.
Amimo, F., Lambert, B. and Magit, A. (2020) “What does the COVID-19 pandemic mean for HIV, tuberculosis, and malaria control?”, Tropical Medicine and Health, 48(1).