Skip to main content

Research Repository

Advanced Search

All Outputs (2)

Reconstructing transmission trees for communicable diseases using densely sampled genetic data (2016)
Journal Article
Worby, C. J., O'Neill, P. D., Kypraios, T., Robotham, J. V., De Angelis, D., Cartwright, E. J., …Cooper, B. S. (2016). Reconstructing transmission trees for communicable diseases using densely sampled genetic data. Annals of Applied Statistics, 10(1), https://doi.org/10.1214/15-AOAS898

Whole genome sequencing of pathogens from multiple hosts in an epidemic offers the potential to investigate who infected whom with unparalleled resolution, potentially yielding important insights into disease dynamics and the impact of control measur... Read More about Reconstructing transmission trees for communicable diseases using densely sampled genetic data.

Bayesian non-parametric inference for stochastic epidemic models using Gaussian Processes (2016)
Journal Article
Xu, X., Kypraios, T., & O'Neill, P. D. (2016). Bayesian non-parametric inference for stochastic epidemic models using Gaussian Processes. Biostatistics, 17(4), 619-633. https://doi.org/10.1093/biostatistics/kxw011

This paper considers novel Bayesian non-parametric methods for stochastic epidemic models. Many standard modeling and data analysis methods use underlying assumptions (e.g. concerning the rate at which new cases of disease will occur) which are rarel... Read More about Bayesian non-parametric inference for stochastic epidemic models using Gaussian Processes.