Objective—To develop a mathematical model to simulate infection dynamics of Mycobacterium bovis in cattle herds in the United States and predict efficacy of the current national control strategy for tuberculosis in cattle.
Design—Stochastic simulation model.
Sample—Theoretical cattle herds in the United States.
Procedures—A model of within-herd M bovis transmission dynamics following introduction of 1 latently infected cow was developed. Frequency- and density-dependent transmission modes and 3 tuberculin test–based culling strategies (no test-based culling, constant [annual] testing with test-based culling, and the current strategy of slaughterhouse detection–based testing and culling) were investigated. Results were evaluated for 3 herd sizes over a 10-year period and validated via simulation of known outbreaks of M bovis infection.
Results—On the basis of 1,000 simulations (1,000 herds each) at replacement rates typical for dairy cattle (0.33/y), median time to detection of M bovis infection in medium-sized herds (276 adult cattle) via slaughterhouse surveillance was 27 months after introduction, and 58% of these herds would spontaneously clear the infection prior to that time. Sixty-two percent of medium-sized herds without intervention and 99% of those managed with constant test–based culling were predicted to clear infection < 10 years after introduction. The model predicted observed outbreaks best for frequency-dependent transmission, and probability of clearance was most sensitive to replacement rate.
Conclusions and Clinical Relevance—Although modeling indicated the current national control strategy was sufficient for elimination of M bovis infection from dairy herds after detection, slaughterhouse surveillance was not sufficient to detect M bovis infection in all herds and resulted in subjectively delayed detection, compared with the constant testing method. Further research is required to economically optimize this strategy.