Determining the infection status of a herd

  • Timothy E. Hanson
  • Wesley O. Johnson
  • Ian A. Gardner
  • Marios P. Georgiadis
Editor’s Invited Article


This article presents hierarchical models for determining infection status and prevalence of infection within a herd given a hypergeometric or binomial sample of animals that have been screened with an imperfect test. Expert prior information on the infection status of the herd, diagnostic test accuracy, and herd prevalence is incorporated into the model. Posterior probabilities versus prior probabilities of infection are presented in the novel form of a curve, summarizing the probability of infection over a range of possible prior probability values. We demonstrate the model with serologic data for Mycobacterium paratuberculosis (Johne’s disease) in dairy herds.

Key Words

Bayesian approach Gibbs sampling Prevalence Screening test Sensitivity Specificity 


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Copyright information

© International Biometric Society 2003

Authors and Affiliations

  • Timothy E. Hanson
    • 1
  • Wesley O. Johnson
    • 2
  • Ian A. Gardner
    • 3
  • Marios P. Georgiadis
    • 4
  1. 1.Department of Mathematics and StatisticsUniversity of New Mexico
  2. 2.Department of StatisticsUniversity of CaliforniaDavis
  3. 3.Department of Medicine and Epidemiology, School of Veterinary MedicineUniversity of CaliforniaDavis
  4. 4.Laboratory of Clinical Bacteriology, Parasitology, Zoonoses and Geographical Medicine, Faculty of MedicineUniversity of CreteGreece

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