Quantitative data and models for bacterial cross-contamination in domestic kitchen during food handling and preparation

Abstract

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.