Raices Cruz Ivette, Troffaes Matthias C M, Sahlin Ullrika
Centre for Environmental and Climate Science, Lund University, Lund, Sweden.
Department of Biology, Lund University, Lund, Sweden.
Risk Anal. 2022 Feb;42(2):239-253. doi: 10.1111/risa.13871. Epub 2022 Jan 10.
An honest communication of uncertainty about quantities of interest enhances transparency in scientific assessments. To support this communication, risk assessors should choose appropriate ways to evaluate and characterize epistemic uncertainty. A full treatment of uncertainty requires methods that distinguish aleatory from epistemic uncertainty. Quantitative expressions for epistemic uncertainty are advantageous in scientific assessments because they are nonambiguous and enable individual uncertainties to be characterized and combined in a systematic way. Since 2019, the European Food Safety Authority (EFSA) recommends assessors to express epistemic uncertainty in conclusions of scientific assessments quantitatively by subjective probability. A subjective probability can be used to represent an expert judgment, which may or may not be updated using Bayes's rule to integrate evidence available for the assessment and could be either precise or approximate. Approximate (or bounded) probabilities may be enough for decision making and allow experts to reach agreement on certainty when they struggle to specify precise subjective probabilities. The difference between the lower and upper bound on a subjective probability can also be used to reflect someone's strength of knowledge. In this article, we demonstrate how to quantify uncertainty by bounded probability, and explicitly distinguish between epistemic and aleatory uncertainty, by means of robust Bayesian analysis, including standard Bayesian analysis through precise probability as a special case. For illustration, the two analyses are applied to an intake assessment.
对感兴趣的数量的不确定性进行如实沟通，可提高科学评估的透明度。为支持这种沟通，风险评估者应选择合适的方法来评估和描述认知不确定性。对不确定性进行全面处理需要采用能够区分偶然不确定性和认知不确定性的方法。认知不确定性的定量表达在科学评估中具有优势，因为它们明确无误，能够以系统的方式对个体不确定性进行描述和合并。自2019年以来，欧洲食品安全局（EFSA）建议评估者在科学评估结论中通过主观概率对认知不确定性进行定量表达。主观概率可用于表示专家判断，该判断可能会或可能不会使用贝叶斯法则进行更新，以整合评估可用的证据，并且可以是精确的或近似的。近似（或有界）概率可能足以用于决策，并且当专家难以指定精确的主观概率时，可使他们就确定性达成一致。主观概率的下限和上限之间的差异也可用于反映某人的知识强度。在本文中，我们展示了如何通过有界概率对不确定性进行量化，并通过稳健贝叶斯分析明确区分认知不确定性和偶然不确定性，其中包括将通过精确概率进行的标准贝叶斯分析作为一种特殊情况。为便于说明，将这两种分析应用于摄入量评估。
