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Bayesian methodology for the analysis of spatial-temporal surveillance data

Publication ,  Journal Article
Zou, J; Karr, AF; Banks, D; Heaton, MJ; Datta, G; Lynch, J; Vera, F
Published in: Statistical Analysis and Data Mining
June 1, 2012

Early and accurate detection of outbreaks is one of the most important objectives of syndromic surveillance systems. We propose a general Bayesian framework for syndromic surveillance systems. The methodology incorporates Gaussian Markov random field (GMRF) and spatio-temporal conditional autoregressive (CAR) modeling. By contrast, most previous approaches have been based on only spatial or time series models. The model has appealing probabilistic representations as well as attractive statistical properties. Based on extensive simulation studies, the model is capable of capturing outbreaks rapidly, while still limiting false positives. © 2012 Wiley Periodicals, Inc.

Duke Scholars

Published In

Statistical Analysis and Data Mining

DOI

EISSN

1932-1864

ISSN

1932-1872

Publication Date

June 1, 2012

Volume

5

Issue

3

Start / End Page

194 / 204

Related Subject Headings

  • 4905 Statistics
  • 4605 Data management and data science
  • 0104 Statistics
 

Citation

APA
Chicago
ICMJE
MLA
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Zou, J., Karr, A. F., Banks, D., Heaton, M. J., Datta, G., Lynch, J., & Vera, F. (2012). Bayesian methodology for the analysis of spatial-temporal surveillance data. Statistical Analysis and Data Mining, 5(3), 194–204. https://doi.org/10.1002/sam.10142
Zou, J., A. F. Karr, D. Banks, M. J. Heaton, G. Datta, J. Lynch, and F. Vera. “Bayesian methodology for the analysis of spatial-temporal surveillance data.” Statistical Analysis and Data Mining 5, no. 3 (June 1, 2012): 194–204. https://doi.org/10.1002/sam.10142.
Zou J, Karr AF, Banks D, Heaton MJ, Datta G, Lynch J, et al. Bayesian methodology for the analysis of spatial-temporal surveillance data. Statistical Analysis and Data Mining. 2012 Jun 1;5(3):194–204.
Zou, J., et al. “Bayesian methodology for the analysis of spatial-temporal surveillance data.” Statistical Analysis and Data Mining, vol. 5, no. 3, June 2012, pp. 194–204. Scopus, doi:10.1002/sam.10142.
Zou J, Karr AF, Banks D, Heaton MJ, Datta G, Lynch J, Vera F. Bayesian methodology for the analysis of spatial-temporal surveillance data. Statistical Analysis and Data Mining. 2012 Jun 1;5(3):194–204.

Published In

Statistical Analysis and Data Mining

DOI

EISSN

1932-1864

ISSN

1932-1872

Publication Date

June 1, 2012

Volume

5

Issue

3

Start / End Page

194 / 204

Related Subject Headings

  • 4905 Statistics
  • 4605 Data management and data science
  • 0104 Statistics