Optimizing bulk milk dioxin monitoring based on costs and effectiveness

Abstract

Dioxins are environmental pollutants, potentially present in milk products, which have negative consequences for human health and for the firms and farms involved in the dairy chain. Dioxin monitoring in feed and food has been implemented to detect their presence and estimate their levels in food chains. However, the costs and effectiveness of such programs have not been evaluated. In this study, the costs and effectiveness of bulk milk dioxin monitoring in milk trucks were estimated to optimize the sampling and pooling monitoring strategies aimed at detecting at least 1 contaminated dairy farm out of 20,000 at a target dioxin concentration level. Incidents of different proportions, in terms of the number of contaminated farms, and concentrations were simulated. A combined testing strategy, consisting of screening and confirmatory methods, was assumed as well as testing of pooled samples. Two optimization models were built using linear programming. The first model aimed to minimize monitoring costs subject to a minimum required effectiveness of finding an incident, whereas the second model aimed to maximize the effectiveness for a given monitoring budget. Our results show that a high level of effectiveness is possible, but at high costs. Given specific assumptions, monitoring with 95% effectiveness to detect an incident of 1 contaminated farm at a dioxin concentration of 2 pg of toxic equivalents/g of fat [European Commission's (EC) action level] costs €2.6 million per month. At the same level of effectiveness, a 73% cost reduction is possible when aiming to detect an incident where 2 farms are contaminated at a dioxin concentration of 3 pg of toxic equivalents/g of fat (EC maximum level). With a fixed budget of €40,000 per month, the probability of detecting an incident with a single contaminated farm at a dioxin concentration equal to the EC action level is 4.4%. This probability almost doubled (8.0%) when aiming to detect the same incident but with a dioxin concentration equal to the EC maximum level. This study shows that the effectiveness of finding an incident depends not only on the ratio at which, for testing, collected truck samples are mixed into a pooled sample (aiming at detecting certain concentration), but also the number of collected truck samples. In conclusion, the optimal cost-effective monitoring depends on the number of contaminated farms and the concentration aimed at detection. The models and study results offer quantitative support to risk managers of food industries and food safety authorities.

Optimization of the Aflatoxin Monitoring Costs along the Maize Supply Chain

“…A few earlier studies have used optimization modeling to optimize monitoring plans for various types of hazards in food and feed products (Ferrier & Buzby, ; Lascano‐Alcoser et al., ; Lascano‐Alcoser, Velthuis, van der Fels‐Klerx, Hoogenboom, & Oude Lansink, ; St‐Pierre & Cobanov, ). In this study, a single‐objective constrained optimization problem, solved by linear approximation, was applied to the case of mycotoxin monitoring along the cereal chain.…”

Systematic Review of Methods to Determine the Cost‐Effectiveness of Monitoring Plans for Chemical and Biological Hazards in the Life Sciences

“…Linear programming was used, for example, by Lascano‐Alcoser, Velthuis, van der Fels‐Klerx, Hoogenboom, and Oude Lansink () to determine the optimal level of monitoring activities for dioxins in milk. Linear programming requires the specification of a linear objective function to be minimized or maximized by changing decision variables, given some constraints (for example, limited resources).…”

“…Monitoring schemes in the field of food safety tend to focus only on accuracy and not on costs. Including the costs in the design of the monitoring plan may improve accuracy at the same cost, or it may lead to cost savings while achieving the same accuracy (Lascano‐Alcoser et al., ). To assess the cost‐effectiveness of monitoring hazards in food, adequate methods to determine cost‐effectiveness are needed.…”

Cost-effective monitoring of dioxins in agri-production chains

“…This is caused by the dilution of the dioxin-concentration of feed ingredients in compound feeds, which is determined by the inclusion rate of the feed ingredient in the compound feed. The same dilution effect in dioxin monitoring is seen in the milk production chain, when dioxins are monitored in milk trucks (Lascano-Alcoser et al, 2013).…”

“…Designing cost-effective monitoring schemes is therefore needed to optimally allocate monitoring resources along the chain. Studies on cost-effective dioxin monitoring have been carried out for bulk milk and the pork chain (Lascano-Alcoser et al, 2014, Lascano-Alcoser et al, 2013. To date, studies on designing cost-effective strategies for monitoring dioxins, focusing exclusively on the feed industry have not been performed.…”