A stochastic model to assess the risk of introduction of bovine viral diarrhea virus to beef cow-calf herds.

Abstract

A spreadsheet model using Monte Carlo simulation was designed to evaluate the introduction of bovine viral diarrhea virus (BVDV) to cow-calf farms and the effect of different testing strategies. Risks were modeled to include imports to the cow-calf herd and stocker calves imported to adjacent pastures. The number of persistently infected (PI) animals imported and the probability of BVDV introduction were monitored for three herd sizes, four import profiles, and six testing strategies. Importing stockers and importing pregnant heifers were the biggest risks for introduction of BVDV. Testing for PI animals in stockers decreased the risk they posed, but testing pregnant heifers was not sufficient to decrease risk unless their calves were also tested. Test sensitivity was more influential than PI prevalence on the likelihood of BVDV introduction, when all imports were tested. This model predicts the risk of BVDV introduction for individual herds based on management decisions, and should prove to be a useful tool to help cow-calf producers in controlling the risk of importing BVDV to a naïve herd.