JSM 2004 - Toronto

Abstract #300570

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Activity Number: 56
Type: Contributed
Date/Time: Sunday, August 8, 2004 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #300570
Title: Bayesian Analysis of Negative Binomial Models applied to Lyme Disease in New York State
Author(s): Haiyan Chen*+ and Howard H. Stratton
Companies: SUNY, Albany and NYSDOH and SUNY, Albany
Address: SPH, R632, ESP, Corning Tower, Albany, NY, 12237,
Keywords: Bayesian ; incidence rate ; Lyme disease ; Markov chain Monte Carlo ; Poisson ; negative ninomial
Abstract:

Lyme disease (LD) occurrence in New York State (NYS) appears as an emerging public health problem; however, few studies have investigated its epidemic and spatial dynamics in great detail. Using data from NYS Department of Health Lyme Registry Surveillance System, the authors studied epidemic and spatial characteristics of LD in NYS for the 11-year time period from 1990 through 2000. Because of both overdispersion and excess zeros presented in the NYS LD data related to a Poisson model, a Bayesian negative binomial models (NB) was constructed in order to give a foundation for future state and local health funding plans and education programs. Joint posteriors and predictive densities of future observations are obtained using Markov chain Monte Carlo methods, and performance of the method is evaluated.

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