Abstract
A stochastic spreadsheet model was developed to obtain estimates of the costs of whole herd testing on dairy farms for Mycobacterium avium subsp. paratuberculosis (Map) with pooled fecal samples. The optimal pool size was investigated for 2 scenarios, prevalence (a low-prevalence herd [≤5%] and a high-prevalence herd [≤5%]) and for different herd sizes (100-, 250-, 500- and 1,000-cow herds). All adult animals in the herd were sampled, and the samples of the individuals were divided into equal sized pools. When a pool tested positive, the manure samples of the animals in the pool were tested individually. The individual samples from a negative pool were assumed negative and not tested individually. Distributions were used to model the uncertainty about the sensitivity of the fecal culture at farm level and Map prevalence. The model randomly allocated a disease status to the cows (not shedding, low Map shedder, moderate Map shedder, and heavy Map shedder) on the basis of the expected prevalence in the herd. Pooling was not efficient in 100-cow and 250-cow herds with low prevalence because the probability to detect a map infection in these herds became poor (53% and 88%) when samples were pooled. When samples were pooled in larger herds, the probability to detect at least 1 (moderate to heavy) shedder was ≤90%. The cost reduction as a result of pooling varied from 43% in a 100-cow herd with a high prevalence to 71% in a 1,000-cow herd with a low prevalence. The optimal pool size increased with increasing herd size and varied from 3 for a 500-cow herd with a low prevalence to 5 for a 1,000-cow herd with a high prevalence.