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Bovine respiratory disease (BRD) is the leading cause of morbidity in feedlot cattle. The ability to accurately identify the expected BRD risk of cattle would allow managers to detect high-risk animals more frequently. Five classification models were built and evaluated towards predicting the expected BRD risk (high/low) of feedlot cattle within the first 45 days on feed (DOF) and incorporate an economic analysis to determine the potential health cost advantage when using a predictive model compared with standard methods. Retrospective data from 10 U.S. feedlots containing 1733 cohorts representing 188,188 cattle with known health outcomes were classified into high- (≥15% BRD morbidity) or low- (&lt;15%) BRD risk in the first 45 DOF. Area under the curve was calculated from the test dataset for each model and ranged from 0.682 to 0.789. The economic performance for each model was dependent on the true proportion of high-risk cohorts in the population. The decision tree model displayed a greater potential economic advantage compared with standard procedures when the proportion of high-risk cohorts was ≤45%. Results illustrate that predictive models may be useful at delineating cattle as high or low risk for disease and may provide economic value relative to standard methods.

Predicting Bovine Respiratory Disease Risk in Feedlot Cattle in the First 45 Days Post Arrival