{"title":"开发基于代理的李斯特菌传播预测模型,以评估零售店的李斯特菌控制策略。","authors":"YeonJin Jung , Chenhao Qian , Cecil Barnett-Neefs , Renata Ivanek , Martin Wiedmann","doi":"10.1016/j.jfp.2024.100337","DOIUrl":null,"url":null,"abstract":"<div><p>Contamination of fresh produce with <em>Listeria monocytogenes</em> can occur throughout the supply chain, including at retail, where <em>Listeria</em> spp., including <em>L. monocytogenes</em>, may be introduced and spread via various routes. However, limited tools are available for retailers to assess practices that can enhance control of <em>Listeria</em> transmission to fresh produce. Therefore, we developed an agent-based model that can simulate <em>Listeria</em> transmission in retail produce sections to optimize environmental sampling programs and evaluate control strategies. A single retail store was used as a model environment, in which various routes of <em>Listeria</em> introduction into and transmission between environmental surfaces were modeled. Model prediction (i.e., <em>Listeria</em> prevalence) was validated using a published longitudinal study for all surfaces that were included in both the model and the validation data. Sensitivity analysis using the Partial Rank Correlation Coefficient showed that (i) initial <em>Listeria</em> concentration from incoming produce, (ii) transfer coefficient from produce to employee’s hands, and (iii) transfer coefficient from consumer to produce were the top three parameters that were significantly (<em>p</em> < 0.0018) associated with the mean <em>Listeria</em> prevalence across all agents, suggesting that the accuracy of these parameters are important for prediction of overall <em>Listeria</em> prevalence at retail. Cluster analysis grouped agents with similar contamination patterns into six unique clusters; this information can be used to optimize the sampling plans for retail environments. Scenario analysis suggested that (i) more stringent supplier control as well as (ii) practices reducing <em>Listeria</em> transmission via consumer’s hands may have the largest impact on reducing finished product contamination. Overall, we show that an agent-based model can serve as a foundational tool to help with decision-making on <em>Listeria</em> control strategies at retail.</p></div>","PeriodicalId":15903,"journal":{"name":"Journal of food protection","volume":"87 9","pages":"Article 100337"},"PeriodicalIF":2.1000,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0362028X24001212/pdfft?md5=1dd8d30d4ebef3e397e0481d524e3cf1&pid=1-s2.0-S0362028X24001212-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Developing an Agent-Based Model that Predicts Listeria spp. Transmission to Assess Listeria Control Strategies in Retail Stores\",\"authors\":\"YeonJin Jung , Chenhao Qian , Cecil Barnett-Neefs , Renata Ivanek , Martin Wiedmann\",\"doi\":\"10.1016/j.jfp.2024.100337\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Contamination of fresh produce with <em>Listeria monocytogenes</em> can occur throughout the supply chain, including at retail, where <em>Listeria</em> spp., including <em>L. monocytogenes</em>, may be introduced and spread via various routes. However, limited tools are available for retailers to assess practices that can enhance control of <em>Listeria</em> transmission to fresh produce. Therefore, we developed an agent-based model that can simulate <em>Listeria</em> transmission in retail produce sections to optimize environmental sampling programs and evaluate control strategies. A single retail store was used as a model environment, in which various routes of <em>Listeria</em> introduction into and transmission between environmental surfaces were modeled. Model prediction (i.e., <em>Listeria</em> prevalence) was validated using a published longitudinal study for all surfaces that were included in both the model and the validation data. Sensitivity analysis using the Partial Rank Correlation Coefficient showed that (i) initial <em>Listeria</em> concentration from incoming produce, (ii) transfer coefficient from produce to employee’s hands, and (iii) transfer coefficient from consumer to produce were the top three parameters that were significantly (<em>p</em> < 0.0018) associated with the mean <em>Listeria</em> prevalence across all agents, suggesting that the accuracy of these parameters are important for prediction of overall <em>Listeria</em> prevalence at retail. Cluster analysis grouped agents with similar contamination patterns into six unique clusters; this information can be used to optimize the sampling plans for retail environments. Scenario analysis suggested that (i) more stringent supplier control as well as (ii) practices reducing <em>Listeria</em> transmission via consumer’s hands may have the largest impact on reducing finished product contamination. Overall, we show that an agent-based model can serve as a foundational tool to help with decision-making on <em>Listeria</em> control strategies at retail.</p></div>\",\"PeriodicalId\":15903,\"journal\":{\"name\":\"Journal of food protection\",\"volume\":\"87 9\",\"pages\":\"Article 100337\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0362028X24001212/pdfft?md5=1dd8d30d4ebef3e397e0481d524e3cf1&pid=1-s2.0-S0362028X24001212-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of food protection\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0362028X24001212\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of food protection","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0362028X24001212","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}
Developing an Agent-Based Model that Predicts Listeria spp. Transmission to Assess Listeria Control Strategies in Retail Stores
Contamination of fresh produce with Listeria monocytogenes can occur throughout the supply chain, including at retail, where Listeria spp., including L. monocytogenes, may be introduced and spread via various routes. However, limited tools are available for retailers to assess practices that can enhance control of Listeria transmission to fresh produce. Therefore, we developed an agent-based model that can simulate Listeria transmission in retail produce sections to optimize environmental sampling programs and evaluate control strategies. A single retail store was used as a model environment, in which various routes of Listeria introduction into and transmission between environmental surfaces were modeled. Model prediction (i.e., Listeria prevalence) was validated using a published longitudinal study for all surfaces that were included in both the model and the validation data. Sensitivity analysis using the Partial Rank Correlation Coefficient showed that (i) initial Listeria concentration from incoming produce, (ii) transfer coefficient from produce to employee’s hands, and (iii) transfer coefficient from consumer to produce were the top three parameters that were significantly (p < 0.0018) associated with the mean Listeria prevalence across all agents, suggesting that the accuracy of these parameters are important for prediction of overall Listeria prevalence at retail. Cluster analysis grouped agents with similar contamination patterns into six unique clusters; this information can be used to optimize the sampling plans for retail environments. Scenario analysis suggested that (i) more stringent supplier control as well as (ii) practices reducing Listeria transmission via consumer’s hands may have the largest impact on reducing finished product contamination. Overall, we show that an agent-based model can serve as a foundational tool to help with decision-making on Listeria control strategies at retail.
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.