Optimizing Bulk Milk Dioxin Monitoring Based on Costs and Effectiveness

Introduction: Dioxins are environmental pollutants present in the agri-food chains. The negative consequences associated with their presence in food are not only related to human health but also to the food businesses operators embedded in the food chains. Food and feed dioxin-monitoring programs aiming to detect, control and reduce the presence of dioxins in food chains have been implemented. However, to date, the costs and effectiveness of such programs have not been assessed.

Purpose: This study aims to quantify the costs and effectiveness of bulk milk dioxin monitoring to optimize the sampling and pooling strategies for a selected set of contamination scenarios.

Methods: Two different optimization models were built using a linear programming methodology. The first model aims to minimize the monitoring costs subject to a minimum required effectiveness, while the second model aims to maximize the effectiveness of monitoring for a given monitoring budget. 

Results: The study shows that a higher level of effectiveness is possible but at higher costs. Monitoring programs with 95% effectiveness aiming to detect a single contaminated farm with a tank milk concentration equal to the EC legal action limit (i.e., 2 pg TEQ/g fat) would cost €2.6 million per month. A large reduction in monitoring costs (at the same level of effectiveness) is possible at intermediate incident sizes (i.e., 73% reduction when two farms are contaminated at 3 pg TEQ/g fat), which is close to the smallest incident aimed to be detected.

Significance: Both models enable the analysis of the costs and the effectiveness of bulk milk dioxin monitoring programs, offering quantitative support to risk managers of the food industry and the food safety authority. Additionally, this study proves that the effectiveness of monitoring depends not only on the performance of the detection tests but also on the number of samples collected.