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

1Citations
Citations of this article
18Readers
Mendeley users who have this article in their library.

This article is free to access.

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.

Cite

CITATION STYLE

APA

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

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free