Modelling, Bayesian inference, and model assessment for nosocomial pathogens using whole‐genome‐sequence data

Cassidy, Rosanna; Kypraios, Theodore; O'Neill, Philip D.

Abstract

Whole genome sequencing of pathogens in outbreaks of infectious disease provides the potential to reconstruct transmission pathways and enhance the information contained in conventional epidemiological data. In recent years there have been numerous new methods and models developed to exploit such high-resolution genetic data. However, corresponding methods for model assessment have been largely overlooked. In this paper we develop both new modelling methods and new model assessment methods, specifically by building on the work of Worby et al. 1 Although the methods are generic in nature, we focus specifically on nosocomial pathogens, and analyse a data set collected during an outbreak of MRSA in a hospital setting.

Citation

Cassidy, R., Kypraios, T., & O'Neill, P. D. (2020). Modelling, Bayesian inference, and model assessment for nosocomial pathogens using whole‐genome‐sequence data. Statistics in Medicine, 39(12), 1746-1765. https://doi.org/10.1002/sim.8510

• Journal Article Type: Article
• Acceptance Date: Jan 31, 2020
• Online Publication Date: Mar 6, 2020
• Publication Date: May 30, 2020
• Deposit Date: Feb 4, 2020
• Publicly Available Date: Mar 7, 2021
• Journal: Statistics in Medicine
• Print ISSN: 0277-6715
• Electronic ISSN: 1097-0258
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 39
• Issue: 12
• Pages: 1746-1765
• DOI: https://doi.org/10.1002/sim.8510
• Keywords: Statistics and Probability; Epidemiology
• Public URL: https://nottingham-repository.worktribe.com/output/3881573
• Publisher URL: https://onlinelibrary.wiley.com/doi/full/10.1002/sim.8510