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Activity Number: 244
Type: Contributed
Date/Time: Monday, August 4, 2014 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #313037
Title: Hidden Markov Modeling of Oral Fluid Detection of PRRSV Antibody in Swine Herds
Author(s): Yaxuan Sun*+ and Chong Wang
Companies: Iowa State University and Iowa State University
Keywords: Diagnostic test ; Hidden Markov Model ; logistic regression ; transition rate ; Bayesian analysis ; disease surveillance
Abstract:

The use of oral fluid in veterinary research and diagnostics has been the focus of recent investigations. Diagnostic tests based on oral fluid samples are known to have imperfect sensitivity and specificity, which introduces uncertainty in determination and modeling of the true disease status among animals. The object of the present study is to model the underlying true disease status progression by using multivariate Hidden Markov Models(HMM). The disease transition rate is modeled using a logistic regression /Markov chain(LRMC) model and the regression parameters are estimated using Bayesian Method. Priors are assumed for the parameters and samples are simulated from posterior distributions using Gibbs sampling with Metropolis-Hastings algorithm. The estimated disease transition parameters will further be used to answer design questions in animal disease surveillance regarding sampling sizes and frequencies required to achieve desired power of detection.


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