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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) |
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