EVALUATING THE HEALTH-STATUS OF HERDS BASED ON TESTS APPLIED TO INDIVIDUALS

The effects of test sensitivity and specificity, and the impact of true prevalence of disease, on test results at the individual level are well known. When individuals are tested to ascertain if an aggregate of animals (e.g. a herd) is affected by a condition of interest, the number of animals tested and the critical number of reactors used to decide the health status of the herd become very important in influencing the herd-level sensitivity and specificity. If the test specificity is less than 100%, as the number of animals tested increases, the probability of at least one false-positive animal increases-thus the herd specificity decreases. The herd sensitivity, herd negative predictive value and herd apparent prevalence increase directly with the number of animals tested, but the herd positive predictive value decreases. Herd sensitivity can be increased by using a test that is less than 100% specific. These features should be borne in mind when interpreting the natural history of disease, as well as when conducting disease surveys or disease-control campaigns based on surrogate tests.