生乳软奶酪中多病原体定量风险评估

IF 3 4区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
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引用次数: 0

摘要

我们提出了一种多病原体微生物定量风险评估(QMRA)模型,用于估算生乳软奶酪中细菌病原体引起食源性疾病的风险。我们的工作扩展了现有的致病性产志贺毒素大肠杆菌(STEC)定量微生物风险评估模型(Basak 等人,审查中;Perrin 等人,2014 年),纳入了沙门氏菌和单增李斯特菌的影响。这种多病原体模型综合了牧场生奶的微生物污染,以及这些细菌在奶酪制作、成熟和储存过程中的生长和存活情况。使用残疾调整寿命年数(DALYs)来评估与生乳奶酪消费相关的多病原体风险对公共健康的影响。该模型评估了收获前和收获后阶段的干预策略,以估算干预成本。此外,该模型还测试了这些策略的各种方案,并优化了干预参数,以最大限度地降低多重病原体风险和相关成本。本文讨论了 QMRA 模型验证所面临的挑战,强调了模型的局限性,并探讨了未来改进的前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multipathogen quantitative risk assessment in raw milk soft cheese

We propose a multipathogen Quantitative Microbiological Risk Assessment (QMRA) model to estimate the risk of foodborne illness from bacterial pathogens in raw milk soft cheese. Our work extends an existing QMRA model for pathogenic Shiga toxin-producing Escherichia coli (STEC) (Basak et al.,under review; Perrin et al., 2014) by incorporating the effects of Salmonella and Listeria monocytogenes. This multipathogen model integrates microbial contamination of raw milk at the farm level, as well as the growth and survival of these bacteria during cheese fabrication, ripening, and storage. The public health impact of multipathogen risk associated with raw milk cheese consumption is assessed using Disability-Adjusted Life Years (DALYs). The model evaluates intervention strategies at both pre- and post-harvest stages to estimate intervention costs. Furthermore, it tests various scenarios of these strategies and optimizes intervention parameters to minimize multipathogen risk and associated costs. This article discusses challenges in QMRA model validation, emphasizes model limitations, and explores future perspectives for improvement.

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来源期刊
Microbial Risk Analysis
Microbial Risk Analysis Medicine-Microbiology (medical)
CiteScore
5.70
自引率
7.10%
发文量
28
审稿时长
52 days
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.
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