Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/77770
Title: HIERARCHICAL MODELLING FOR INFECTIOUS DISEASES
Authors: ZHENG XIAOHUI
Keywords: Bayesian, hierarchical model, infectious diseases, evidence synthesis, optimal design, temporal trend,
Issue Date: 19-Mar-2014
Citation: ZHENG XIAOHUI (2014-03-19). HIERARCHICAL MODELLING FOR INFECTIOUS DISEASES. ScholarBank@NUS Repository.
Abstract: Hierarchical modelling is a Bayesian approach to pool information from related datasets to provide more accurate estimates of key parameters. In this thesis, we build hierarchical models for three infectious disease applications. First, hierarchical models are fitted to clinical temporal data from patients infected by Dengue and Chikungunya to infer differences in these two similar diseases over time, to guide clinical management and diagnosis. Next, we develop a hierarchical model of the 2009 H1N1 pandemic in a basket of countries. Bayesian evidence synthesis combines information from various data types to infer accurate severity metrics more rapidly. Lastly, a hierarchical model summarising past seroepidemological studies of Enterovirus 71 (EV71) in Asian countries is used to design Bayesian optimal experimental studies for future studies of EV71 in other Asian population.
URI: http://scholarbank.nus.edu.sg/handle/10635/77770
Appears in Collections:Ph.D Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
ZhengXH.pdf3.55 MBAdobe PDF

OPEN

NoneView/Download

Page view(s)

140
checked on Oct 20, 2018

Download(s)

59
checked on Oct 20, 2018

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.