Stochastic simulation modeling to determine time to detect Bovine Viral Diarrhea antibodies in bulk tank milk

A stochastic simulation model was developed to estimate the time from introduction ofBovine Viral Diarrhea Virus (BVDV) in a herd to detection of antibodies in bulk tank milk(BTM) samples using three ELISAs. We assumed that antibodies could be detected, after afixed threshold prevalence of seroconverted milking cows was reached in the herd. Differentthresholds were set for each ELISA, according to previous studies. For each test, antibodydetection was simulated in small (70 cows), medium (150 cows) and large (320 cows)herds. The assays included were: (1) the Danish blocking ELISA, (2) the SVANOVIR®BVDV-Ab ELISA, and (3) the ELISA BVD/MD p80 Institute Pourquier. The validation of the modelwas mainly carried out by comparing the predicted incidence of persistently infected (PI)calves and the predicted detection time, with records from a BVD infected herd. Resultsshowed that the SVANOVIR, which was the most efficient ELISA, could detect antibodiesin the BTM of a large herd 280 days (95% prediction interval: 218; 568) after a transientlyinfected (TI) milking cow has been introduced into the herd. The estimated time to detectionafter introduction of one PI calf was 111 days (44; 605). With SVANOVIR ELISA the incidenceof PIs and dead born calves could be limited and the impact of the disease on the animalwelfare and income of farmers (before detection) could be minimized. The results from thesimulation modeling can be used to improve the current Danish BVD surveillance programin detecting early infected herds.