Quantitative Risk Assessment for Listeria monocytogenes in Selected Categories of Deli Meats: Impact of Lactate and Diacetate on Listeriosis Cases and Deaths

Abstract

Foodborne disease associated with consumption of ready-to-eat foods contaminated with Listeria monocytogenes represents a considerable pubic health concern. In a risk assessment published in 2003, the U.S. Food and Drug Administration and the U.S. Food Safety and Inspection Service estimated that about 90% of human listeriosis cases in the United States are caused by consumption of contaminated deli meats. In this risk assessment, all deli meats were grouped into one of 23 categories of ready-to-eat foods, and only the postretail growth of L. monocytogenes was considered. To provide an improved risk assessment for L. monocytogenes in deli meats, we developed a revised risk assessment that (i) models risk for three subcategories of deli meats (i.e., ham, turkey, and roast beef) and (ii) models L. monocytogenes contamination and growth from production to consumption while considering subcategory-specific growth kinetics parameters (i.e., lag phase and exponential growth rate). This model also was used to assess how reformulation of the chosen deli meat subcategories with L. monocytogenes growth inhibitors (i.e., lactate and diacetate) would impact the number of human listeriosis cases. Use of product-specific growth parameters demonstrated how certain deli meat categories differ in the relative risk of causing listeriosis; products that support more rapid growth and have reduced lag phases (e.g., turkey) represent a higher risk. Although reformulation of deli meats with growth inhibitors was estimated to reduce by about 2.5- to 7.8-fold the number of human listeriosis cases linked to a given deli meat subcategory and thus would reduce the overall risk of human listeriosis, even with reformulation deli meats would still cause a considerable number of human listeriosis cases. A combination of strategies is thus needed to provide continued reduction of these cases. Risk assessment models such as that described here will be critical for evaluation of different control approaches and to help define the combinations of control strategies that will have the greatest imp–ct on public health.