The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Abstract Details
Activity Number:
|
620
|
Type:
|
Contributed
|
Date/Time:
|
Thursday, August 4, 2011 : 8:30 AM to 10:20 AM
|
Sponsor:
|
Section on Quality and Productivity
|
Abstract - #302525 |
Title:
|
A Recursive Bayesian Approach in Biosurveillance
|
Author(s):
|
Gideon Zamba*+
|
Companies:
|
University of Iowa
|
Address:
|
Department of Biostatistics, Iowa City, ,
|
Keywords:
|
Dynamic Control ;
Bayesian Sequential Update ;
Syndromic Surveillance
|
Abstract:
|
We developed a three-state recursive sequential Bayesian method for signal detection in biosurveillance. The method accounts for non-stationarity, irregularity, seasonality, and captures the serial structural details of an epidemic curve. At stage n, a trichotomous variable governing the states of an epidemic dynamic is defined, and a prior distribution for the time-indexed serial readings is set. The technicality consists of finding a posterior state probability based on the observed data history, using the posterior as a prior distribution for stage n + 1 and sequentially monitoring surges in posterior state probabilities. A sensitivity analysis for validation is conducted and analytical formulas for the predictive distribution are supplied for error management purposes. The method is applied to syndromic surveillance data gathered in the United States (U.S.) District of Columbia metropolitan area.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2011 program
|
2011 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.