Bayesian Risk-based Surveillance Models for Pathogen Detection in Aquaculture

In this discussion, we will focus on a Bayesian model for the assessment of pathogen risk in aquaculture. This model combines information about site-specific historical disease testing, test characteristic and information on biosecurity measures to estimate current probability of disease absence. The discussion will focus on a proposed model form as well as the utility of aggregating expert information on the impact of biosecurity practices in the absence of hard data. This discussion aims to stimulate discussion of practical and methodological considerations that will support a disease testing sample size dependent on biosecurity measures.

Clark Kogan
Clark Kogan
Washington State University