Demonstration of pest freedom is an important part of the phytosanitary processes surrounding global trade, with many countries requiring declarations of pest free areas before accepting commodities from exporting countries. Claims of pest freedom are often not based on physical survey data, but on expert opinion, together with the fact that the pest has not been recorded in the area of interest. These claims, although they may be based on scientific evidence, are generally not transparent and are becoming less acceptable to trading partners. Surveillance data can provide substantial information for supporting claims of freedom. We have applied a quantitative approach to evaluating complex surveillance data (derived from both targeted and general surveillance activities) for the demonstration of pest freedom.
This approach is based on scenario tree analysis of the surveillance systems and utilises Bayesian methods for incorporating prior knowledge of pest status in the analysis. It allows quantitative estimates of confidence in freedom to be derived from surveillance that is targeted for the pest in question and which therefore does not meet the criteria for a representative survey. This method provides transparency in the process of demonstrating pest freedom, providing a clear description of the surveillance system. The applications and limitations of this approach will be discussed.