Application of techniques for the quantitative analysis of complex surveillance systems to disease and wildlife management

Scenario tree modelling and associated methods provide tools to quantify the combined value of multiple complex surveillance activities over time. The outputs of this analysis are an estimate of the sensitivity of a surveillance system, and the cumulative probability of disease freedom that surveillance provides over time. The ability to quantify the performance of complex surveillance systems provides a number of new opportunities in the design and application of search and detection activities. One of these is the ability to objectively compare alternative detection strategies. The sensitivity of a strategy (the probability that the target biota would be detected, given that they are present at a defined level) may be balanced against cost and practicality considerations to determine the most effective strategy for a given situation. The paper provides an example of the comparison of two surveillance strategies (structured surveys and abattoir surveillance) for disease detection in animal health (Classical Swine Fever). These techniques may also play an important role in the certification of success in pest eradication operations. The ability to use multiple sources of evidence to evaluate success means that a higher level of confidence can often be achieved at lower cost. Examples of the application of scenario tree modelling in plant health and invasive pests are provided to illustrate its use within eradication programs.