Livestock movements are essential for the economic success of the industry. However, these movements come with the risk of long-range spread of infection, potentially bringing infection to previously disease-free areas where subsequent localized transmission can be devastating. Mechanistic predictive models usually consider controls that minimize the number of livestock affected without considering other costs of an ongoing epidemic. However, it is more appropriate to consider the economic burden, as movement restrictions have major consequences for the economic revenue of farms. Here, using mechanistic models of foot-and-mouth disease, bluetongue virus and bovine tuberculosis in the UK, we compare the economically optimal control strategies for these diseases. We show that for foot-and-mouth disease, the optimal strategy is to ban movements in a small radius around infected farms; the balance between disease control and maintaining ‘business as usual’ varies between regions. For bluetongue virus and bovine tuberculosis, we find that the cost of any movement ban is greater than the epidemiological benefits due to the low within-farm prevalence and slow rate of disease spread. This work suggests that movement controls need to be carefully matched to the epidemiological and economic consequences of the disease, and that optimal movement bans are often of far shorter duration than allowed under existing policy.
- Population dynamics
- Stochastic modelling