论文标题
通过为模拟模型创建保证案例来增强COVID-19的决策
Enhancing Covid-19 Decision-Making by Creating an Assurance Case for Simulation Models
论文作者
论文摘要
模拟模型一直在告知COVID-19的决策过程。因此，这些模型对社会危害风险有重大影响。但是，基本建模的假设和局限性如何清楚地传达，以便决策者可以轻松理解它们？在对安全至关重要的系统中提出风险的索赔时，常见的做法是产生保证案例，这是一个结构化的论点，该论点是由证据支持的，目的是评估我们在基于风险的决策中应该有多么自信。我们认为，用于指导关键政策决策的任何COVID-19模拟模型都将受益于这种情况的支持，以解释如何以及在何种程度上依靠模拟的证据来证实政策结论。这将使对建模的隐性假设和固有的不确定性进行批判性审查，并使整体决策过程更大。
Simulation models have been informing the COVID-19 policy-making process. These models, therefore, have significant influence on risk of societal harms. But how clearly are the underlying modelling assumptions and limitations communicated so that decision-makers can readily understand them? When making claims about risk in safety-critical systems, it is common practice to produce an assurance case, which is a structured argument supported by evidence with the aim to assess how confident we should be in our risk-based decisions. We argue that any COVID-19 simulation model that is used to guide critical policy decisions would benefit from being supported with such a case to explain how, and to what extent, the evidence from the simulation can be relied on to substantiate policy conclusions. This would enable a critical review of the implicit assumptions and inherent uncertainty in modelling, and would give the overall decision-making process greater transparency and accountability.
