Modelling and predicting temporal frequency of foot-and-mouth disease cases in countries with endemic foot-and-mouth disease

Young Ku Choi, Wesley O. Johnson, Geoff Jones, Andres Perez, Mark Thurmond

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

Foot-and-mouth disease (FMD) is a highly contagious viral disease that affects a variety of cloven-hoofed animals. It spreads rapidly and results in considerable economic loss for agriculture in regions where the disease occurs. The main objective of this study is to develop statistical models that will reasonably predict temporal FMD case counts in endemic regions or countries, and which will also perform well under sporadic epidemic phases that increase FMD counts beyond background endemic circumstances. We used FMD data from Iran to develop correlated data models for predicting the number of FMD cases at future times and to assess the statistical importance of risk factors for increased frequency of FMD. Model selection and validation are accomplished by using the deviance information criterion and the mean absolute prediction error.

Original languageEnglish (US)
Pages (from-to)619-636
Number of pages18
JournalJournal of the Royal Statistical Society. Series A: Statistics in Society
Volume175
Issue number2
DOIs
StatePublished - Apr 1 2012

Keywords

  • Auto-regressive structure
  • Bayesian method
  • Foot-and-mouth disease
  • Iran Veterinary Organization
  • Longitudinal data
  • Office Internationale des Epizooties
  • Ornstein
  • Random-effects model
  • Threshold model
  • Uhlenbeck process

ASJC Scopus subject areas

  • Statistics and Probability
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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