Vose D J
David Vose Risk Analysis Services, Wincanton, Somerset, United Kingdom.
J Food Prot. 1998 May;61(5):640-8. doi: 10.4315/0362-028x-61.5.640.
Quantitative risk assessment (QRA) is rapidly accumulating recognition as the most practical method for assessing the risks associated with microbial contamination of foodstuffs. These risk analyses are most commonly developed in commercial computer spreadsheet applications, combined with Monte Carlo simulation add-ins that enable probability distributions to be inserted into a spreadsheet. If a suitable model structure can be defined and all of the variables within that model reasonably quantified, a QRA will demonstrate the sensitivity of the severity of the risk to each stage in the risk-assessment model. It can therefore provide guidance for the selection of appropriate risk-reduction measures and a quantitative assessment of the benefits and costs of these proposed measures. However, very few reports explaining QRA models have been submitted for publication in this area. There is, therefore, little guidance available to those who intend to embark on a full microbial QRA. This paper looks at a number of modeling techniques that can help produce more realistic and accurate Monte Carlo simulation models. The use and limitations of several distributions important to microbial risk assessment are explained. Some simple techniques specific to Monte Carlo simulation modelling of microbial risks using spreadsheets are also offered which will help the analyst more realistically reflect the uncertain nature of the scenarios being modeled. simulation, food safety.
定量风险评估（QRA）作为评估食品微生物污染相关风险的最实用方法，正迅速获得认可。这些风险分析大多在商业计算机电子表格应用程序中进行，并结合蒙特卡洛模拟插件，以便能够将概率分布插入电子表格。如果能够定义合适的模型结构，并合理量化该模型中的所有变量，QRA将展示风险严重程度对风险评估模型中每个阶段的敏感性。因此，它可为选择适当的风险降低措施提供指导，并对这些提议措施的收益和成本进行定量评估。然而，在这一领域，很少有解释QRA模型的报告提交发表。因此，对于那些打算开展全面微生物QRA的人来说，几乎没有可用的指导。本文探讨了一些建模技术，这些技术有助于生成更现实、准确的蒙特卡洛模拟模型。解释了几种对微生物风险评估很重要的分布的使用和局限性。还提供了一些使用电子表格进行微生物风险蒙特卡洛模拟建模的特定简单技术，这将有助于分析师更现实地反映所建模场景的不确定性。模拟，食品安全。
