Quantitative evaluation of complex surveillance systems for pest and disease detection

Surveillance for disease detection is used primarily for early detection of incursions and to support assertions of freedom from disease.Analytical techniques used to evaluate the efficacy of such surveillance are equally applicable across the domains of invasive species (both plant and animal), diseases and pests of agriculture crops, livestock, and of wildlife. Scenario tree models of surveillance activities may be used to estimate their diagnostic sensitivities, or the probability that the target organism will be detected given that it is present at a defined level. This paper will outline techniques for estimating the sensitivity of both targeted and general surveillance activities, and for the surveillance system as a whole. Probability of freedom from the target organism may be estimated from the surveillance sensitivity, and this Bayesian approach may be extended to estimate current probability of freedom from appropriate use of historical and ongoing surveillance evidence.