Modeling cumulative evidence for freedom from disease with applications to BSE surveillance trials

Article

Abstract

This investigation deals with the question of when a particular population can be considered to be disease-free. The motivation is the case of BSE where specific birth cohorts may present distinct disease-free subpopulations. The specific objective is to develop a statistical approach suitable for documenting freedom of disease, in particular, freedom from BSE in birth cohorts. The approach is based upon a geometric waiting time distribution for the occurrence of positive surveillance results and formalizes the relationship between design prevalence, cumulative sample size and statistical power. The simple geometric waiting time model is further modified to account for the diagnostic sensitivity and specificity associated with the detection of disease. This is exemplified for BSE using two different models for the diagnostic sensitivity. The model is furthermore modified in such a way that a set of different values for the design prevalence in the surveillance streams can be accommodated (prevalence heterogeneity) and a general expression for the power function is developed. For illustration, numerical results for BSE suggest that currently (data status September 2004) a birth cohort of Danish cattle born after March 1999 is free from BSE with probability (power) of 0.8746 or 0.8509, depending on the choice of a model for the diagnostic sensitivity.

Key Words

Design prevalence heterogeneity Diagnostic accuracy Freedom of disease Geometric waiting time Power function 

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Copyright information

© International Biometric Society 2006

Authors and Affiliations

  1. 1.Applied Statistics, School of Biological SciencesUniversity of ReadingReadingUK
  2. 2.International EpiLabDanish Institute for Food and Veterinary ResearchDenmark
  3. 3.Federal Institute for Risk Assessment (BfR)BerlinGermany

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