title: Statistical and simulation modelling for enhanced understanding of hospital pathogen and related health issues
creator: Lee, Xing Ju
subject: approximate Bayesian computation
subject: data-augmentation
subject: environmental contamination
subject: Markov chain Monte Carlo
subject: max-stable models
subject: methicillin-resistant Staphylococcus aureus
subject: model choice
subject: non-homogeneous Poisson process
description: This thesis investigated the temporal occurrence and transmission of within hospital pathogens using appropriate statistical and simulation models applied to imperfect hospital data. The research provides new insights into the transmission dynamics of methicillin-resistant Staphylococcus aureus within a hospital ward to assist infection control and prevention efforts. Additionally, appropriate statistical methods are identified to analyse hospital infection data which take into account the intricacies and potential limitations of such data.
publisher: Queensland University of Technology
date: 2017
type: Thesis
format: application/pdf
relation: https://eprints.qut.edu.au/103762/1/Xing%20Ju_Lee_Thesis.pdf
relation: DOI:10.5204/thesis.eprints.103762
relation:    Lee, Xing Ju   (2017)   Statistical and simulation modelling for enhanced understanding of hospital pathogen and related health issues.  PhD  by Publication,   Queensland University of Technology.   
id_number: https://eprints.qut.edu.au/103762/
identifier: Faculty of Health; Institute of Health and Biomedical Innovation; School of Mathematical Sciences; Science & Engineering Faculty; School of Public Health & Social Work