Herd-level interpretation of test results for epidemiologic studies of animal diseases

Abstract

Correct classification of the true status of herds is an important component of epidemiologic studies and animal disease-control programs. We review theoretical aspects of herd-level testing through consideration of test performance (herd-level sensitivity, specificity and predictive values), the factors affecting these estimates, and available software for calculations. We present new aspects and considerations concerning the effect of precision and bias in estimation of individual-test performance on herd-test performance and suggest methods (pooled testing, targeted sampling of subpopulations with higher prevalence, and use of combinations of tests) to improve herd-level sensitivity when the expected within-herd prevalence is low.