Modeling the Impact of Between-lot and Within-lot Variability in Listeria monocytogenes Contamination on Risk Reduction From Sampling Ready-to-eat Foods
IF 2.1 4区 农林科学Q3 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
{"title":"Modeling the Impact of Between-lot and Within-lot Variability in Listeria monocytogenes Contamination on Risk Reduction From Sampling Ready-to-eat Foods","authors":"Yuhuan Chen , Régis Pouillot , Jane M. Van Doren","doi":"10.1016/j.jfp.2025.100478","DOIUrl":null,"url":null,"abstract":"<div><div>Microbiological sampling and testing are widely utilized in food safety risk management. We developed risk assessments to quantify the impact of various sampling plans on the risk of invasive listeriosis to consumers. We used the FDA-iRISK® tool and adapted available process, consumption, and dose-response modules of published <em>L. monocytogenes</em> risk assessments to predict cases per billion servings from consumption of ready-to-eat foods. We also developed an <em>ad hoc</em> quantitative risk assessment application using R (the “FDA-LmQRA App”) to evaluate more complex scenarios and provide additional metrics. Data and model inputs included the prevalence and levels of <em>L. monocytogenes</em>, sampling plan parameters, and operating characteristic curve data. We derived prevalence and between-lot distributions from data from market basket surveys of <em>L. monocytogenes</em> in ready-to-eat foods in the U.S. and examined two assumptions for the within-lot contamination: a lognormal distribution, or a heterogeneous distribution with a defined proportion of exceptional (higher level) contamination in addition to a single lognormal distribution. We found that testing each lot using 2-class plans (e.g., <em>n</em> = 5 or 10, <em>m</em> = 0/25 g or 0/5 g, and <em>c</em> = 0) or 3-class mixed plans (e.g., <em>n</em> = 5 or 10, <em>m</em> = 0/25 g or 0/5 g, <em>M</em> = 20 CFU/g or 100 CFU/g, and <em>c</em> = 1) and replacing positive lots by noncontaminated lots predicted quantifiable, but relatively low, risk reduction. The risk estimates were highly influenced by the variability of the between-lot concentration distribution as well as the presence of exceptional contamination for the within-lot contamination. In the presence of exceptional contamination, a 3-class mixed plan (<em>c</em> = 1) was predicted to have comparable performance based on risk estimates to a 2-class plan (corresponding <em>n</em> and <em>m</em> but <em>c</em> = 0). Results from this study may inform the choice of sampling plans to optimize sampling and testing strategies for reducing listeriosis associated with ready-to-eat foods.</div></div>","PeriodicalId":15903,"journal":{"name":"Journal of food protection","volume":"88 5","pages":"Article 100478"},"PeriodicalIF":2.1000,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of food protection","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0362028X25000304","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Microbiological sampling and testing are widely utilized in food safety risk management. We developed risk assessments to quantify the impact of various sampling plans on the risk of invasive listeriosis to consumers. We used the FDA-iRISK® tool and adapted available process, consumption, and dose-response modules of published L. monocytogenes risk assessments to predict cases per billion servings from consumption of ready-to-eat foods. We also developed an ad hoc quantitative risk assessment application using R (the “FDA-LmQRA App”) to evaluate more complex scenarios and provide additional metrics. Data and model inputs included the prevalence and levels of L. monocytogenes, sampling plan parameters, and operating characteristic curve data. We derived prevalence and between-lot distributions from data from market basket surveys of L. monocytogenes in ready-to-eat foods in the U.S. and examined two assumptions for the within-lot contamination: a lognormal distribution, or a heterogeneous distribution with a defined proportion of exceptional (higher level) contamination in addition to a single lognormal distribution. We found that testing each lot using 2-class plans (e.g., n = 5 or 10, m = 0/25 g or 0/5 g, and c = 0) or 3-class mixed plans (e.g., n = 5 or 10, m = 0/25 g or 0/5 g, M = 20 CFU/g or 100 CFU/g, and c = 1) and replacing positive lots by noncontaminated lots predicted quantifiable, but relatively low, risk reduction. The risk estimates were highly influenced by the variability of the between-lot concentration distribution as well as the presence of exceptional contamination for the within-lot contamination. In the presence of exceptional contamination, a 3-class mixed plan (c = 1) was predicted to have comparable performance based on risk estimates to a 2-class plan (corresponding n and m but c = 0). Results from this study may inform the choice of sampling plans to optimize sampling and testing strategies for reducing listeriosis associated with ready-to-eat foods.
期刊介绍:
The Journal of Food Protection® (JFP) is an international, monthly scientific journal in the English language published by the International Association for Food Protection (IAFP). JFP publishes research and review articles on all aspects of food protection and safety. Major emphases of JFP are placed on studies dealing with:
Tracking, detecting (including traditional, molecular, and real-time), inactivating, and controlling food-related hazards, including microorganisms (including antibiotic resistance), microbial (mycotoxins, seafood toxins) and non-microbial toxins (heavy metals, pesticides, veterinary drug residues, migrants from food packaging, and processing contaminants), allergens and pests (insects, rodents) in human food, pet food and animal feed throughout the food chain;
Microbiological food quality and traditional/novel methods to assay microbiological food quality;
Prevention of food-related hazards and food spoilage through food preservatives and thermal/non-thermal processes, including process validation;
Food fermentations and food-related probiotics;
Safe food handling practices during pre-harvest, harvest, post-harvest, distribution and consumption, including food safety education for retailers, foodservice, and consumers;
Risk assessments for food-related hazards;
Economic impact of food-related hazards, foodborne illness, food loss, food spoilage, and adulterated foods;
Food fraud, food authentication, food defense, and foodborne disease outbreak investigations.