Exploring the relationship between product testing and risk

Microbiological sampling is one tool available to help ensure product safety, but where and how to sample in terms of the most effective risk-reduction, and efficient use of resources (money, labour, time) is not always clear. To effectively employ sampling as a risk-management strategy, it is essential to have a clear understanding of the (sometimes complex) relationship between sampling activities in the supply chain and the residual consumer risk. Such an understanding can be supported by the quantitative definition of the relationship (i.e. a model), that is employed to explore how the components of the relationship interact to influence the risk. To meet this need, we will develop a sampling-risk model that quantifies the relationship between product testing, lot rejection rates, and risk and perform detailed analyses of the relationship between product sampling variables driving the risk. The results from this work can support risk reduction initiatives by providing analyses that explicitly enable the exploration of risk management options, facilitating selection of actionable sampling strategies that have the biggest impact on risk reduction. This information (combined with feasibility and cost considerations) can be used by industry, facilitating scientifically supported, risk-based decision-making.