Evaluation of surveillance strategies for bovine brucellosis in Japan using a simulation model

Bovine brucellosis is caused by Brucella abortus and induces abortions in female cattle, with other cattle at risk of infection from the aborted fetus or contaminated placenta. In Japan, the number of cases has dramatically reduced due to national surveillance and eradication strategies. Bovine brucellosis is now believed to be eradicated in Japan. Here, we examine the surveillance strategies currently in place for early detection of infected cattle in the event of a future reintroduction of the disease. We compared current serological surveillance for the dairy population with bulk-milk surveillance and abortion surveillance, and used time to detection as the main criterion of surveillance efficacy. A stochastic individual-based model (IBM) was developed to simulate disease transmission within and between farms. Using outputs from the transmission model, a comparison of surveillance strategies was simulated. For evaluation of the robustness of the parameter values used in the transmission model, a sensitivity analysis was conducted. For the purpose of evaluating the direct costs of each surveillance strategy, the annual number of samples to be tested and the annual number of farms to be visited were estimated. Our results indicated that current serological surveillance with 60-month test intervals is not effective enough for rapid detection of a brucellosis outbreak. Bulk-milk surveillance appeared the most effective method based on the early detection of infected cows and a reduced number of samples required. The time to detection for abortion surveillance was greater than that of bulk-milk surveillance but varied widely depending on the reported ratio of abortions. Results from the surveillance model were consistent when alternative scenarios were applied to the transmission model. Although our model cannot exactly replicate an actual brucellosis outbreak, or the results of surveillance, our results may help decision-makers to choose the most effective surveillance strategy.