Heterogeneity and complexity in collaborative biosecurity schemes
Plant diseases threaten ecosystem and landscape health. When new disease threats emerge, they can cost millions of pounds to contain and eradicate, and their wider social costs can be several times higher. These threats can be addressed with proactive biosecurity measures, such as better hygiene and monitoring.
However, this raises several important questions about how governments can incentivise these actions, and how they can prevent ‘free-riding’, where some agents (such as farms or importers) might benefit from the measures taken by others, but without incurring additional costs themselves.
One approach to this issue has been to establish ‘public-private partnerships’ between governments and agents, where governments both invest in biosecurity measures and offer outbreak compensation to agents who do likewise. Mathematical models have been used to help improve these partnerships by estimating the costs and benefits involved so that biosecurity strategies can be optimised. However, these models have been unable to capture the diverse landscape of agents and networks because they treat all agents as identical and average their interactions.
Project aims
The aim of our project was to help bridge this gap by engaging with stakeholders and applying a range of numerical simulations and statistical analyses. We used these methods to assess the use of public-private partnerships across a range of potential plant disease scenarios and stakeholder groups. This allowed us to evaluate the effects of heterogeneity and landscape complexity in public-private partnerships, identify effective management policies, and better understand how biosecurity coalitions form and when they may provide significant benefits.
Conclusions
Our results provide some important lessons for governments. We were able to predict optimum strategies for establishing collaborative biosecurity schemes. These strategies are based on a careful balance of government investment in biosecurity and compensation schemes for agents in the event of a disease outbreak. We established new mathematical and computational models that can accurately quantify the added value to the overall economy from these strategies.
Project contacts
Jonathan Pitchford
(Principal Investigator)
Project outputs
The project developed the first mathematical and computational models that try to describe how networks of agents (such as farms) might efficiently collaborate through biosecurity.
