Objective-To investigate the epidemiologic and financial impacts of targeted sampling of subpopulations of cows, compared with random sampling of all cows, for classification of dairy herd infection status for paratuberculosis. Animals-All cows from 4 infected herds with a low-to-moderate prevalence of paratuberculosis and from 1 noninfected herd in California. Procedure-The infection status of each cow was classified on the basis of results of an ELISA or combined ELISA and fecal culture results. Thirteen sampling schemes designed to randomly sample cows on the basis of lactation number, stage of lactation, and milk production were evaluated. Sampling without replacement was used to obtain a probability of herd detection of paratuberculosis for each evaluated sampling method and for simulated sample sizes between 30 and 150 cows. Marginal cost-effectiveness analysis was used to determine the cost increase relative to the increase in detection probability. Results-Sampling cows in the third or higher lactation and greater than or equal to 200 days into lactation yielded the highest detection probability in most instances, resulting in a detection probability that was 1.4 to 2.5 times that obtained by sampling 30 cows in the second or higher lactation. Costs of testing via the alternative method with a 95% detection probability were approximately $300 lower in a high-prevalence herd (31 %) and $800 lower in a low-prevalence herd (9%), compared with use of the reference method. Conclusions and Clinical Relevance-Detection of herds with paratuberculosis could be improved, and costs of testing substantially reduced by sampling targeted groups of cows.

Objective-To evaluate various sampling strategies for potential use in measuring prevalence of antimicrobial susceptibility in cattle. Sample Population-500 isolates of non-type-specific Escherichia coli (NTSEC) isolated from the feces of 50 cows from 2 dairy farms (25 cows/farm and 10 isolates/cow). Procedures-Diameters of inhibition zones for 12 antimicrobials were analyzed to estimate variation among isolates, cows, and farms and then used to determine sampling distributions for a stochastic simulation model to evaluate 4 sampling strategies. These theoretic sampling strategies used a total of 100 isolates in 4 allocations (1 isolate from 100 cows, 2 isolates from 50 cows, 3 isolates from 33 cows, or 4 isolates from 25 cows). Results-Analysis of variance composition revealed that 74.2% of variation was attributable to isolates, 18.5% to cows, and 7.3% to farms. Analysis of results of simulations suggested that when most of the variance was attributable to differences among isolates within a cow, culturing 1 isolate from each of 100 cows underestimated overall prevalence, compared with results for culturing more isolates per cow from fewer cows. When variance was not primarily attributable to differences among isolates, all 4 sampling strategies yielded similar results. Conclusions and Clinical Relevance-It is not always possible to predict the hierarchical level at which clustering will have its greatest impact on observed susceptibility distributions. Results suggested that sampling strategies that use testing of 3 or 4 isolates/cow from a representative sample of all animals better characterize herd prevalence of antimicrobial resistance when impacted by clustering.