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.

Wymant, C. et al. (2021) “The epidemiological impact of the NHS COVID-19 app”, Nature, 594(7863), pp. 408–412.

Charniga, K. et al. (2021) “Descriptive analysis of surveillance data for Zika virus disease and Zika virus-associated neurological complications in Colombia, 2015–2017”, PLoS ONE, 16(6).

Speidel, L. et al. (2021) “Inferring population histories for ancient genomes using genome-wide genealogies”, Molecular Biology and Evolution, 38(9), pp. 3497–3511.

Marks, C. et al. (2021) “Identifying counties at risk of high overdose mortality burden throughout the emerging fentanyl epidemic in the United States: a predictive statistical modeling study”, Lancet Public Health, 6(10), pp. e720 - e728.

Parag, K., Thompson, R. and Donnelly, C. (2021) “Are epidemic growth rates more informative than reproduction numbers?”, medRxiv [Preprint].

Davies, R. et al. (2021) “Rapid genotype imputation from sequence with reference panels”, Nature Genetics, 53(7), pp. 1104–1111.

Lovell-Read, F. et al. (2021) “Interventions targeting non-symptomatic cases can be important to prevent local outbreaks: SARS-CoV-2 as a case study”, Journal of the Royal Society Interface, 18(178).

Nicholson, G. et al. (2021) “Local prevalence of transmissible SARS-CoV-2 infection: an integrative causal model for debiasing fine-scale targeted testing data”, p. 2021.05.17.21256818.

Ward, H. et al. (2021) “Prevalence of antibody positivity to SARS-CoV-2 following the first peak of infection in England: serial cross-sectional studies of 365,000 adults”, Lancet Regional Health - Europe, 4.

Christen, P. et al. (2021) “The J-IDEA Pandemic Planner”, Medical Care, 59(5), pp. 371–378.