Pairwise summation as a method for the additive combination of probabilities in qualitative risk assessments.

IF 3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Risk Analysis Pub Date : 2024-11-01 Epub Date: 2024-05-22 DOI:10.1111/risa.14323
Matteo Crotta, Eleonora Chinchio, Vito Tranquillo, Nicola Ferrari, Javier Guitian
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Abstract

Qualitative frameworks are widely employed to tackle urgent animal or public health issues when data are scarce and/or urgent decisions need to be made. In qualitative models, the degree of belief regarding the probabilities of the events occurring along the risk pathway(s) and the outcomes is described in nonnumerical terms, typically using words such as Low, Medium, or High. The main methodological challenge, intrinsic in qualitative models, relates to performing mathematical operations and adherence to the rule of probabilities when probabilities are nonnumerical. Although methods to obtain the qualitative probability from the conditional realization of n events are well-established and consistent with the multiplication rule of probabilities, there is a lack of accepted methods for addressing situations where the probability of an event occurring can increase, and the rule of probability P(AUB) = P(A) + P(B) - P(A∩B) should apply. In this work, we propose a method based on the pairwise summation to fill this methodological gap. Our method was tested on two qualitative models and compared by means of scenario analysis to other approaches found in literature. The qualitative nature of the models prevented formal validation; however, when using the pairwise summation, results consistently appeared more coherent with probability rules. Even if the final qualitative estimate can only represent an approximation of the actual probability of the event occurring, qualitative models have proven to be effective in providing scientific-based evidence to support decision-making. The method proposed in this study contributes to reducing the subjectivity that characterizes qualitative models, improving transparency and reproducibility.

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配对求和法作为定性风险评估中概率加法组合的一种方法。
在数据稀缺和/或需要紧急决策时,定性框架被广泛用于解决紧急动物或公共卫生问题。在定性模型中,对风险路径上发生的事件和结果的概率的相信程度用非数字术语来描述,通常使用低、中或高等词。定性模型所固有的主要方法论挑战是,当概率是非数字时,如何进行数学运算和遵守概率规则。虽然从 n 个事件的条件实现中获得定性概率的方法已经得到公认,并且符合概率的乘法规则,但在事件发生的概率可能增加的情况下,还缺乏公认的方法来处理这种情况,而概率规则 P(AUB) = P(A) + P(B) - P(A∩B) 应该适用。在这项工作中,我们提出了一种基于成对求和的方法来填补这一方法空白。我们的方法在两个定性模型上进行了测试,并通过情景分析与文献中的其他方法进行了比较。由于模型的定性性质,无法进行正式验证;然而,当使用成对求和法时,结果始终与概率规则更加一致。即使最终的定性估计只能代表事件发生的实际概率的近似值,但定性模型已被证明可以有效地为决策提供科学依据。本研究提出的方法有助于减少定性模型的主观性,提高透明度和可重复性。
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来源期刊
Risk Analysis
Risk Analysis 数学-数学跨学科应用
CiteScore
7.50
自引率
10.50%
发文量
183
审稿时长
4.2 months
期刊介绍: Published on behalf of the Society for Risk Analysis, Risk Analysis is ranked among the top 10 journals in the ISI Journal Citation Reports under the social sciences, mathematical methods category, and provides a focal point for new developments in the field of risk analysis. This international peer-reviewed journal is committed to publishing critical empirical research and commentaries dealing with risk issues. The topics covered include: • Human health and safety risks • Microbial risks • Engineering • Mathematical modeling • Risk characterization • Risk communication • Risk management and decision-making • Risk perception, acceptability, and ethics • Laws and regulatory policy • Ecological risks.
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