Bayesian spatiotemporal analysis of foot-and-mouth disease data from the Republic of Turkey

A. J. Branscum, A. M. Perez, W. O. Johnson, Mark Thurmond

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

A flexible hierarchical Bayesian spatiotemporal regression model for foot-and-mouth disease (FMD) was applied to data on the annual number of reported FMD cases in Turkey from 1996 to 2003. The longitudinal component of the model was specified as a latent province-specific stochastic process. This stochastic process can accommodate various types of FMD temporal profiles. The model accounted for differences in FMD occurrence across provinces and for spatial correlation. Province-level covariate information was incorporated into the analysis. Results pointed to a decreasing trend in the number of FMD cases in western Turkey and an increasing trend in eastern Turkey from 1996 to 2003. The model also identified provinces with high and with low propensities for FMD occurrence. The model's use of flexible structures for temporal trend and of generally applicable methods for spatial correlation has broad application to predicting future spatiotemporal distributions of disease in other regions of the world.

Original languageEnglish (US)
Pages (from-to)833-842
Number of pages10
JournalEpidemiology and Infection
Volume136
Issue number6
DOIs
StatePublished - Jun 1 2008

Fingerprint

Spatio-Temporal Analysis
Foot-and-Mouth Disease
Bayes Theorem
Turkey
Stochastic Processes

ASJC Scopus subject areas

  • Epidemiology
  • Infectious Diseases

Cite this

Bayesian spatiotemporal analysis of foot-and-mouth disease data from the Republic of Turkey. / Branscum, A. J.; Perez, A. M.; Johnson, W. O.; Thurmond, Mark.

In: Epidemiology and Infection, Vol. 136, No. 6, 01.06.2008, p. 833-842.

Research output: Contribution to journalArticle

Branscum, A. J. ; Perez, A. M. ; Johnson, W. O. ; Thurmond, Mark. / Bayesian spatiotemporal analysis of foot-and-mouth disease data from the Republic of Turkey. In: Epidemiology and Infection. 2008 ; Vol. 136, No. 6. pp. 833-842.
@article{a04afdba76374c0590004d6054fd88c9,
title = "Bayesian spatiotemporal analysis of foot-and-mouth disease data from the Republic of Turkey",
abstract = "A flexible hierarchical Bayesian spatiotemporal regression model for foot-and-mouth disease (FMD) was applied to data on the annual number of reported FMD cases in Turkey from 1996 to 2003. The longitudinal component of the model was specified as a latent province-specific stochastic process. This stochastic process can accommodate various types of FMD temporal profiles. The model accounted for differences in FMD occurrence across provinces and for spatial correlation. Province-level covariate information was incorporated into the analysis. Results pointed to a decreasing trend in the number of FMD cases in western Turkey and an increasing trend in eastern Turkey from 1996 to 2003. The model also identified provinces with high and with low propensities for FMD occurrence. The model's use of flexible structures for temporal trend and of generally applicable methods for spatial correlation has broad application to predicting future spatiotemporal distributions of disease in other regions of the world.",
author = "Branscum, {A. J.} and Perez, {A. M.} and Johnson, {W. O.} and Mark Thurmond",
year = "2008",
month = "6",
day = "1",
doi = "10.1017/S0950268807009065",
language = "English (US)",
volume = "136",
pages = "833--842",
journal = "Epidemiology and Infection",
issn = "0950-2688",
publisher = "Cambridge University Press",
number = "6",

}

TY - JOUR

T1 - Bayesian spatiotemporal analysis of foot-and-mouth disease data from the Republic of Turkey

AU - Branscum, A. J.

AU - Perez, A. M.

AU - Johnson, W. O.

AU - Thurmond, Mark

PY - 2008/6/1

Y1 - 2008/6/1

N2 - A flexible hierarchical Bayesian spatiotemporal regression model for foot-and-mouth disease (FMD) was applied to data on the annual number of reported FMD cases in Turkey from 1996 to 2003. The longitudinal component of the model was specified as a latent province-specific stochastic process. This stochastic process can accommodate various types of FMD temporal profiles. The model accounted for differences in FMD occurrence across provinces and for spatial correlation. Province-level covariate information was incorporated into the analysis. Results pointed to a decreasing trend in the number of FMD cases in western Turkey and an increasing trend in eastern Turkey from 1996 to 2003. The model also identified provinces with high and with low propensities for FMD occurrence. The model's use of flexible structures for temporal trend and of generally applicable methods for spatial correlation has broad application to predicting future spatiotemporal distributions of disease in other regions of the world.

AB - A flexible hierarchical Bayesian spatiotemporal regression model for foot-and-mouth disease (FMD) was applied to data on the annual number of reported FMD cases in Turkey from 1996 to 2003. The longitudinal component of the model was specified as a latent province-specific stochastic process. This stochastic process can accommodate various types of FMD temporal profiles. The model accounted for differences in FMD occurrence across provinces and for spatial correlation. Province-level covariate information was incorporated into the analysis. Results pointed to a decreasing trend in the number of FMD cases in western Turkey and an increasing trend in eastern Turkey from 1996 to 2003. The model also identified provinces with high and with low propensities for FMD occurrence. The model's use of flexible structures for temporal trend and of generally applicable methods for spatial correlation has broad application to predicting future spatiotemporal distributions of disease in other regions of the world.

UR - http://www.scopus.com/inward/record.url?scp=42149193648&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=42149193648&partnerID=8YFLogxK

U2 - 10.1017/S0950268807009065

DO - 10.1017/S0950268807009065

M3 - Article

C2 - 17612418

AN - SCOPUS:42149193648

VL - 136

SP - 833

EP - 842

JO - Epidemiology and Infection

JF - Epidemiology and Infection

SN - 0950-2688

IS - 6

ER -