Research Progress on the Transmission Characteristics and Risk Assessment of Norovirus in the Food Chain

Norovirus is one of the primary pathogens causing acute gastroenteritis worldwide, and its highly contagious nature through the food chain poses a serious threat to public health. Norovirus is commonly transmitted through food such as shellfish, vegetable, and fruit during production, processing, and consumption. Traditional detection methods struggle to fully reveal the associated risks. Microbiological quantitative risk assessment combines data and mathematical models to systematically quantify the risk of pathogen transmission, providing a scientific tool for controlling foodborne viruses. This paper focuses on the transmission characteristics of norovirus in the food chain of shellfish, vegetable, and fruit, systematically outlined the contamination pathways and key risk points from production to consumption, and reviews the progress of quantitative risk research. The contamination of shellfish primarily originated from water body, and depuration and thermal processing could significantly reduce the viral load. The contamination of vegetable and fruit primarily stemmed from irrigation water and cross-contamination during manual harvesting. Thermal treatment and novel decontamination technologies could effectively reduce the viral load. Different dose-response models exhibited variations in risk assessment, and a comprehensive analysis of multiple models could enhance accuracy. In the future, interdisciplinary collaboration should be strengthened to utilize big data and machine learning to construct multidimensional risk assessment models, enhancing predictive and early warning capabilities. This will provide precise support for global food safety governance and promote the development of risk management toward systematization and intelligence.

诺如病毒（Norovirus）是全球范围内引发急性胃肠炎的主要病原体之一，其经食物链传播的极强传染性对公共卫生构成严重威胁。诺如病毒通常在生产、加工及消费环节，通过贝类、蔬菜与水果等食品实现传播。传统检测方法难以全面揭示其相关传播风险。微生物定量风险评估（Microbiological Quantitative Risk Assessment）整合数据与数学模型，系统量化病原体传播风险，为食源性病毒防控提供了科学工具。本研究聚焦诺如病毒在贝类、蔬菜与水果食物链中的传播特征，系统梳理了从生产到消费全流程的污染路径与关键风险点，并综述了定量风险研究的进展。贝类污染主要源自水体，净化处理与热处理可显著降低病毒载量（Viral Load）。蔬菜与水果的污染主要源于灌溉水及人工采收过程中的交叉污染。热处理与新型消毒技术可有效降低病毒载量。不同剂量反应模型（Dose-Response Models）在风险评估中存在差异，综合分析多模型可提升评估准确性。未来应加强跨学科协作，借助大数据与机器学习构建多维风险评估模型，提升预测与预警能力。这将为全球食品安全治理提供精准支撑，并推动风险管理向系统化、智能化方向发展。