Caprine arthritis encephalitis and caseous lymphadenitis in goats: use of bulk tank milk ELISAs for herd-level surveillance.

The objective of this study was to evaluate the diagnostic performance of two ELISA tests applied to bulk tank milk (BTM) as the first part of a two-step test scheme for the surveillance of caprine arthritis encephalitis (CAE) and caseous lymphadenitis (CLA) infections in goats. The herd-level BTM tests were assessed by comparing them to the test results of individual serological samples. The potential for refining the cut-off levels for BTM tests used as surveillance tools in a population recently cleared of infection was also investigated. Data was gathered on serum (nCAE =9702 and nCLA=13426) and corresponding BTM (nCAE=78 and nCLA=123) samples from dairy goat herds enrolled in the Norwegian disease control and eradication programme 'Healthier Goats'. The results showed that the sensitivity and specificity of the CAE ELISA BTM test with respect to detecting ≥2 per cent within-herd prevalence were 72.7 per cent and 86.6 per cent, respectively. For the CLA ELISA BTM the sensitivity and specificity were 41.4 per cent and 81.7 per cent, respectively, for the same goal of detection. The results suggest that BTM testing can be applied as a cost-effective first step for early detection of CAE and CLA infection.

The Norwegian Healthier Goats program--modeling lactation curves using a multilevel cubic spline regression model.

In 2001, the Norwegian Goat Health Service initiated the Healthier Goats program (HG), with the aim of eradicating caprine arthritis encephalitis, caseous lymphadenitis, and Johne's disease (caprine paratuberculosis) in Norwegian goat herds. The aim of the present study was to explore how control and eradication of the above-mentioned diseases by enrolling in HG affected milk yield by comparison with herds not enrolled in HG. Lactation curves were modeled using a multilevel cubic spline regression model where farm, goat, and lactation were included as random effect parameters. The data material contained 135,446 registrations of daily milk yield from 28,829 lactations in 43 herds. The multilevel cubic spline regression model was applied to 4 categories of data: enrolled early, control early, enrolled late, and control late. For enrolled herds, the early and late notations refer to the situation before and after enrolling in HG; for nonenrolled herds (controls), they refer to development over time, independent of HG. Total milk yield increased in the enrolled herds after eradication: the total milk yields in the fourth lactation were 634.2 and 873.3 kg in enrolled early and enrolled late herds, respectively, and 613.2 and 701.4 kg in the control early and control late herds, respectively. Day of peak yield differed between enrolled and control herds. The day of peak yield came on d 6 of lactation for the control early category for parities 2, 3, and 4, indicating an inability of the goats to further increase their milk yield from the initial level. For enrolled herds, on the other hand, peak yield came between d 49 and 56, indicating a gradual increase in milk yield after kidding. Our results indicate that enrollment in the HG disease eradication program improved the milk yield of dairy goats considerably, and that the multilevel cubic spline regression was a suitable model for exploring effects of disease control and eradication on milk yield.