MODIFIED INDIVIDUAL-LEVEL MODELS OF INFECTIOUS DISEASE

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MODIFIED INDIVIDUAL-LEVEL MODELS OF INFECTIOUS DISEASE

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Title: MODIFIED INDIVIDUAL-LEVEL MODELS OF INFECTIOUS DISEASE
Author: Fang, Mingying
Department: Department of Mathematics and Statistics
Program: Mathematics and Statistics
Abstract: Infectious disease models can be used to understand mechanisms of the spread of diseases and thus, may effectively guide control policies for potential outbreaks. Deardon et al. (2010) introduced a class of individual-level models (ILMs) which are highly flexible. Parameter estimates for ILMs can be achieved by means of Markov chain Monte Carlo (MCMC) methods within a Bayesian framework. Here, we introduce an extended form of ILM, described by Deardon et al. (2010), and compare this model with the original ILM in the context of a simple spatial system. The two spatial ILMs are fitted to 70 simulated data sets and a real data set on tomato spotted wilt virus (TSWV) in pepper plants (Hughes et al., 1997). We find that the modified ILM is more flexible than the original ILM and may fit some data sets better.
URI: http://hdl.handle.net/10214/3016
Date: 2011-09-15


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