Modelling,Bayesian inference,and model assessment for nosocomial pathogens using whole-genome-sequence data |
| |
Authors: | Rosanna Cassidy Theodore Kypraios Philip D. O'Neill |
| |
Affiliation: | School of Mathematical Sciences, University of Nottingham, Nottingham, UK |
| |
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 article, we develop both new modelling methods and new model assessment methods, specifically by building on the work of Worby et al. Although the methods are generic in nature, we focus specifically on nosocomial pathogens and analyze a dataset collected during an outbreak of MRSA in a hospital setting. |
| |
Keywords: | antimicrobial resistance Bayesian methods MCMC MRSA whole-genome sequences |
|
|