A three-state recursive sequential Bayesian algorithm for biosurveillance

K.D. Zamba, Panagiotis Tsiamyrtzis and Douglas M. Hawkins

Computational Statistics & Data Analysis, 2013, vol. 58, issue C, 82-97

Abstract: A serial signal detection algorithm is developed to monitor pre-diagnosis and medical diagnosis data pertaining to biosurveillance. The algorithm is three-state sequential, based on Bayesian thinking. It accounts for non-stationarity, irregularity and seasonality, and captures serial structural details of an epidemic curve. At stage n, a trichotomous variable governing the states of an epidemic is defined, and a prior distribution for 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 (US) District of Columbia metropolitan area.

Keywords: Bayesian sequential update; Dynamic control; Syndromic surveillance (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167947311001447
Full text for ScienceDirect subscribers only.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:58:y:2013:i:c:p:82-97

DOI: 10.1016/j.csda.2011.04.015

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().