An easy-to-use and affordable surveillance system is crucial for paratuberculosis control. The use of environmental samples and milk pools has been proven to be effective for the detection of Mycobacterium avium subsp. paratuberculosis (MAP)-infected herds, but not for monitoring dairy herds certified as MAP non-suspect. We aimed to evaluate methods for the repeated testing of large dairy herds with a very low prevalence of MAP shedders, using different sets of environmental samples or pooled milk samples, collected monthly over a period of one year in 36 herds with known MAP shedder prevalence. Environmental samples were analyzed by bacterial culture and fecal PCR, and pools of 25 and 50 individual milk samples were analyzed by ELISA for MAP-specific antibodies. We estimated the cumulative sensitivity and specificity for up to twelve sampling events by adapting a Bayesian latent class model and taking into account the between- and within-test correlation. Our study revealed that at least seven repeated samplings of feces from the barn environment are necessary to achieve a sensitivity of 95% in herds with a within-herd shedder prevalence of at least 2%. The detection of herds with a prevalence of less than 2% is more challenging and, in addition to numerous repetitions, requires a combination of different samples.

Regionally, the monitoring of paratuberculosis at the herd level is performed by the detection of specific antibodies in pooled milk samples by ELISA. The negative/positive cut-off S/P values applied for pooled milk samples are low and particularly vulnerable to variation in the test performance. In this study, a batch variation in the test performance of two ELISA tests was assessed to identify consequences for sample classification. A total of 72 pooled milk samples (50 from MAP-infected herds, 22 from one MAP-non-infected herd) were analyzed using three different batches, each of two different MAP antibody ELISA tests (A and B). Receiver operating characteristic (ROC) analysis was performed, with the results of each batch, S/P values of the samples and optical density (OD) readings of the negative and positive control samples included in the kits being compared between the batches of one test. ROC analysis revealed a considerable variation in the test performance of the batches of the two individual tests, caused by differences in the S/P values of the samples and resulting in different sensitivities at a specificity of 100%. Major sources of variation originate from the manufacturing processes of test batches. These sources have to be better controlled, and the test performance has to be revisited regularly.

Within paratuberculosis control programs Mycobacterium avium subsp. paratuberculosis (MAP)-infected herds have to be detected with minimum effort but with sufficient reliability. We aimed to evaluate a combination of random sampling (RS) and pooling for the detection of MAP-infected herds, simulating repeated RS in imitated dairy herds (within-herd prevalence 1.0%, 2.0%, 4.3%). Each RS consisted of taking 80 out of 300 pretested fecal samples, and five or ten samples were repeatedly and randomly pooled. All pools containing at least one MAP-positive sample were analyzed by culture and real-time quantitative PCR (qPCR). The pool detection probability was 47.0% or 45.9% for pools of size 5 or 10 applying qPCR and slightly lower using culture. Combining these methods increased the pool detection probability. A positive association between bacterial density in pools and pool detection probability was identified by logistic regression. The herd-level detection probability ranged from 67.3% to 84.8% for pools of size 10 analyzed by both qPCR and culture. Pools of size 10 can be used without significant loss of sensitivity compared with pools of size 5. Analyzing randomly sampled and pooled fecal samples allows the detection of MAP-infected herds, but is not recommended for one-time testing in low prevalence herds.