Dixuan Cai , Jinhan He , Runrun Zhang , Xinyu Liao , Juhee Ahn , Jinsong Feng , Tian Ding
{"title":"家庭厨房在食物处理和准备过程中细菌交叉污染的定量数据和模型","authors":"Dixuan Cai , Jinhan He , Runrun Zhang , Xinyu Liao , Juhee Ahn , Jinsong Feng , Tian Ding","doi":"10.1016/j.mran.2025.100356","DOIUrl":null,"url":null,"abstract":"<div><div>Cross-contamination is a significant factor contributing to outbreaks of foodborne diseases and food spoilage, and is an important component of quantitative microbial risk assessment (QMRA). The domestic environment represents the final stage of exposure assessment, and data underscore that the exposure risk of foodborne pathogens to consumers is closely linked to cross-contamination in household settings. However, transfer rate data and cross-contamination models from previous studies are fragmented and require integration and categorization for more effective utilization within the QMRA framework. This review summarizes the potential impacts of vehicles during bacterial transmission, transfer rate data for common routes, and current models in domestic kitchens, providing valuable support for cross-contamination modeling within the exposure assessment. In the future, the data gap in the household scenario should be further investigated, particularly in water- and glove-mediated processes. The models can be further improved and refined as deeper underlying mechanisms are uncovered, alongside consumer behavior investigations and the application of AI-powered methods.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"30 ","pages":"Article 100356"},"PeriodicalIF":4.0000,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantitative data and models for bacterial cross-contamination in domestic kitchen during food handling and preparation\",\"authors\":\"Dixuan Cai , Jinhan He , Runrun Zhang , Xinyu Liao , Juhee Ahn , Jinsong Feng , Tian Ding\",\"doi\":\"10.1016/j.mran.2025.100356\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Cross-contamination is a significant factor contributing to outbreaks of foodborne diseases and food spoilage, and is an important component of quantitative microbial risk assessment (QMRA). The domestic environment represents the final stage of exposure assessment, and data underscore that the exposure risk of foodborne pathogens to consumers is closely linked to cross-contamination in household settings. However, transfer rate data and cross-contamination models from previous studies are fragmented and require integration and categorization for more effective utilization within the QMRA framework. This review summarizes the potential impacts of vehicles during bacterial transmission, transfer rate data for common routes, and current models in domestic kitchens, providing valuable support for cross-contamination modeling within the exposure assessment. In the future, the data gap in the household scenario should be further investigated, particularly in water- and glove-mediated processes. The models can be further improved and refined as deeper underlying mechanisms are uncovered, alongside consumer behavior investigations and the application of AI-powered methods.</div></div>\",\"PeriodicalId\":48593,\"journal\":{\"name\":\"Microbial Risk Analysis\",\"volume\":\"30 \",\"pages\":\"Article 100356\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2025-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Microbial Risk Analysis\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352352225000167\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microbial Risk Analysis","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352352225000167","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Quantitative data and models for bacterial cross-contamination in domestic kitchen during food handling and preparation
Cross-contamination is a significant factor contributing to outbreaks of foodborne diseases and food spoilage, and is an important component of quantitative microbial risk assessment (QMRA). The domestic environment represents the final stage of exposure assessment, and data underscore that the exposure risk of foodborne pathogens to consumers is closely linked to cross-contamination in household settings. However, transfer rate data and cross-contamination models from previous studies are fragmented and require integration and categorization for more effective utilization within the QMRA framework. This review summarizes the potential impacts of vehicles during bacterial transmission, transfer rate data for common routes, and current models in domestic kitchens, providing valuable support for cross-contamination modeling within the exposure assessment. In the future, the data gap in the household scenario should be further investigated, particularly in water- and glove-mediated processes. The models can be further improved and refined as deeper underlying mechanisms are uncovered, alongside consumer behavior investigations and the application of AI-powered methods.
期刊介绍:
The journal Microbial Risk Analysis accepts articles dealing with the study of risk analysis applied to microbial hazards. Manuscripts should at least cover any of the components of risk assessment (risk characterization, exposure assessment, etc.), risk management and/or risk communication in any microbiology field (clinical, environmental, food, veterinary, etc.). This journal also accepts article dealing with predictive microbiology, quantitative microbial ecology, mathematical modeling, risk studies applied to microbial ecology, quantitative microbiology for epidemiological studies, statistical methods applied to microbiology, and laws and regulatory policies aimed at lessening the risk of microbial hazards. Work focusing on risk studies of viruses, parasites, microbial toxins, antimicrobial resistant organisms, genetically modified organisms (GMOs), and recombinant DNA products are also acceptable.