Speaker
Description
Foodborne illnesses have become a growing concern globally, especially for the fresh produce sector. Due to the large demand of fresh produce and the increasing number of foodborne illnesses outbreaks, maintaining safety along the food supply chain has become an important public health policy challenge. Food-related crises in recent years have accelerated the development of new underlying legislation, policies and standards. Previous research shows that food monitoring and traceability have proven to be effective for complying with regulations, meeting food safety and quality requirements, and reducing the cost of product recalls, as well as for increasing consumer confidence and reducing customer complaints and better connecting producers and consumers. It has been widely recognized both by practitioners and academia that it is critical to develop effective and efficient models to address food safety risks.
In response to the increase in outbreaks, the U.S. Food and Drug Administration (FDA) conducted a pilot study to collect samples of raw agricultural commodity (RAC) focusing on romaine lettuce to test for foodborne pathogens in 2019. This was the first national attempt to test fresh produce for the occurrence of foodborne diseases. It intended to help the FDA, Centers for Disease Control and Prevention (CDC) and state public health agencies to identify sources of contamination and factors that may be contributing to foodborne diseases and find ways to address the food safety issues. Despite this important advance, however, questions remain about how to optimally test for contamination across the supply chain to achieve food safety in a cost-effective manner. To date, few studies have comprehensively assessed the role of food testing and traceability for preventing foodborne illness risks in the produce supply chain context.
To address this gap, this work models a nationwide fresh produce supply chain system using a numerical simulation method and examines food safety risks along the system. Based on this, we develop cost effective risk management strategies. This study considers fresh lettuce produced in Western US, a product mostly eaten raw and associated with a number of foodborne illness outbreaks, and shipped to 13 counties in New York State (NYS). NYS heavily relies on lettuce supplies from Western US to meet consumers’ demand, rendering foodborne disease a top food safety issue in the state.
The objective of this study is to identify the testing strategies that most efficiently balance the tradeoff between risk control efforts costs and food contamination risks. There are four potential test points are proposed from field to fork: (1) a test of products in the field; (2) a test at packinghouse; (3) a test at wholesale centers; and (4) a test at retailers. There are four places in the supply chain where a traceability mechanism could be implemented to identify sources of contamination. The tracing locations emerge if contamination is detected at test points 2, 3 and 4 respectively or if there are foodborne illnesses occurrences. If contamination is detected, a traceability mechanism will be implemented to identify sources of contamination. All products with identified contamination problem will be recalled.
Our results suggest that testing at the earlier stage of the supply chain, e.g., field testing and packinghouse testing, is more effective than other testing undertaken hereafter along the supply chain. Given the currently existing foodborne disease risks, the optimal testing strategy is to test products at a rate of approximately 29% at packer house. However, the testing cost has a significant impact on the optimal testing strategy. If the testing cost is 30 percent lower, the optimal test location will change from packinghouse to field and the systematic contamination risks and costs will be lower. In light of this, a rapid and affordable test technology will improve the functional performance and safety of this supply chain. Our results also suggest that a traceability system coupled with a testing mechanism improve the performance of the entire supply chain. Overall, a 15 percent cost savings can be achieved when the supply chain participants can share information to enable traceability along the fresh produce supply chain.
Our model provides practical solutions by which enterprises can systematically assess, track, and trace the contamination risks of supply chains. Our findings have direct implications for the optimal testing, traceability, and recall strategy for risk mitigation under potential foodborne illness risks. The generated data provide critical insight into possible unforeseen consequences of testing schemes coupled with traceability and recall mechanisms within the current fresh produce supply chain system under given levels of contamination risks. In spite of a regional model, the framework and approaches can be flexibly extended for application in other regions to address similar food safety problems elsewhere.
