As part of a broader control strategy within herds known to be infected with Mycobacterium avium ssp. paratuberculosis (MAP), individual animal testing is generally conducted to identify infected animals for action, usually culling. Opportunities are now available to quantitatively compare different testing strategies (combinations of tests) in known infected herds. This study evaluates the effectiveness, cost, and cost-effectiveness of different testing strategies to identify infected animals at a single round of testing within dairy herds known to be MAP infected. A model was developed, taking account of both within-herd infection dynamics and test performance, to simulate the use of different tests at a single round of testing in a known infected herd. Model inputs included the number of animals at different stages of infection, the sensitivity and specificity of each test, and the costs of testing and culling. Testing strategies included either milk or serum ELISA alone or with fecal culture in series. Model outputs included effectiveness (detection fraction, the proportion of truly infected animals in the herd that are successfully detected by the testing strategy), cost, and cost-effectiveness (testing cost per true positive detected, total cost per true positive detected). Several assumptions were made: MAP was introduced with a single animal and no management interventions were implemented to limit within-herd transmission of MAP before this test. In medium herds, between 7 and 26% of infected animals are detected at a single round of testing, the former using the milk ELISA and fecal culture in series 5 yr after MAP introduction and the latter using fecal culture alone 15 yr after MAP introduction. The combined costs of testing and culling at a single round of testing increases with time since introduction of MAP infection, with culling costs being much greater than testing costs. The cost-effectiveness of testing varied by testing strategy. It was also greater at 5 yr, compared with 10 or 15 yr, since MAP introduction, highlighting the importance of early detection. Future work is needed to evaluate these testing strategies in subsequent rounds of testing as well as accounting for different herd dynamics and different levels of herd biocontainment.
University College Dublin ->