Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/142813
Title: STATISTICAL MODELLING OF UPPER RESPIRATORY TRACT INFECTIONS
Authors: ZHAO XIAHONG
Keywords: Influenza, Vaccination Effectiveness, Hemagglutination Inhibition Titers, Influenza Seasonality, Attack Rate, Bayesian Hierarchical Model
Issue Date: 12-Jan-2018
Citation: ZHAO XIAHONG (2018-01-12). STATISTICAL MODELLING OF UPPER RESPIRATORY TRACT INFECTIONS. ScholarBank@NUS Repository.
Abstract: Influenza affects 5%–30% of the global population every year, causing substantial health and economic burden. It is widely agreed that vaccination is the most effective method for preventing influenza infections and its complications. Understanding the effectiveness, timing and optimal implementation of vaccination is important for public health decision makers in planning vaccination campaigns and allocating limited resources. This thesis discusses and develops statistical models for evaluating the effectiveness of influenza vaccine in various settings. Bayesian statistical models were developed to estimate influenza attack rates and to characterize the dynamics of infection-induced influenza immunity. Simulations were also conducted, and the findings indicate that the dynamics of herd immunity against influenza infections correlated with influenza seasonality in the tropics. This provides new insights for better understanding of the influenza seasonality, and the models developed provide a simple template for more accurate estimation of influenza vaccine effectiveness and attack rate.
URI: http://scholarbank.nus.edu.sg/handle/10635/142813
Appears in Collections:Ph.D Theses (Open)

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