Use of scenario tree modelling to plan freedom from infection surveillance: Mycoplasma bovis in New Zealand

•The New Zealand Ministry of Primary Industries (MPI) is operating an eradication program for an incursion of Mycoplasma bovis in cattle.•The program is expensive for industry and should be ceased as soon as practical after eradication has been achieved.•We have used stochastic scenario tree modelling (STM) to plan the freedom surveillance program to demonstrate disease has been eradicated.•Current surveillance components could demonstrate freedom in 2–4 years, but surveillance intensity could be reduced. Herd specificity will need to be perfect.•STM can be used to analyse simulation models of a national herd to plan freedom surveillance and has the capacity to lead to more efficient programs. Since mid-2018, the New Zealand (NZ) Ministry for Primary Industries (MPI) has been operating an eradication program for an incursion of Mycoplasma bovis. Although NZ is still delimiting the outbreak, consideration is being given to how freedom from M. bovis will be demonstrated. Rapid demonstration of freedom will minimise the length of the program, significantly reducing its financial burden. This collaborative research was undertaken to help inform planning of surveillance to demonstrate freedom after M. bovis is believed eradicated. Scenario tree modelling (STM) involves assimilating multiple surveillance system components to determine whether disease is absent. STM has infrequently been used to plan appropriate surveillance but this was the approach used here. A stochastic simulation model was implemented in R. The model represented the NZ commercial dairy and non-dairy cattle industries and the current surveillance components that are also planned to be used to gather evidence of absence of M. bovis once it is eradicated. Different surveillance intensities and risk based versus random surveillance were simulated and compared for probability of freedom, financial cost of sampling and testing and the time to demonstrate freedom. The results indicate that the current surveillance components will enable demonstration of freedom. Surveillance components included bulk tank milk testing, herd testing and testing at meat processing plants, predominantly using an imperfect ELISA. Several combinations of surveillance components appeared most efficient achieving >95 % confidence of freedom over 2–4 years, whilst sampling 4–7 % of the non-dairy herds and less than 25 % of dairy herds annually. The results indicate that surveillance intensity can be lower than is currently