Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN, United States.
Department of Teaching and Learning, Vanderbilt University, Nashville, TN, United States.
Risk Anal. 2020 Sep;40(9):1795-1810. doi: 10.1111/risa.13508. Epub 2020 Jun 24.
The concepts of vulnerability and resilience help explain why natural hazards of similar type and magnitude can have disparate impacts on varying communities. Numerous frameworks have been developed to measure these concepts, but a clear and consistent method of comparing them is lacking. Here, we develop a data-driven approach for reconciling a popular class of frameworks known as vulnerability and resilience indices. In particular, we conduct an exploratory factor analysis on a comprehensive set of variables from established indices measuring community vulnerability and resilience at the U.S. county level. The resulting factor model suggests that 50 of the 130 analyzed variables effectively load onto five dimensions: wealth, poverty, agencies per capita, elderly populations, and non-English-speaking populations. Additionally, the factor structure establishes an objective and intuitive schema for relating the constituent elements of vulnerability and resilience indices, in turn affording researchers a flexible yet robust baseline for validating and expanding upon current approaches.
脆弱性和弹性的概念有助于解释为什么类似类型和规模的自然灾害会对不同的社区产生不同的影响。已经开发了许多框架来衡量这些概念，但缺乏一种明确和一致的方法来比较它们。在这里，我们开发了一种数据驱动的方法来协调一类称为脆弱性和弹性指数的流行框架。具体来说，我们对一组来自已建立的衡量美国县一级社区脆弱性和弹性的指数的综合变量进行了探索性因子分析。结果表明，在分析的 130 个变量中，有 50 个变量可以有效地加载到五个维度上：财富、贫困、人均机构数量、老年人口和非英语人口。此外，该因子结构为脆弱性和弹性指数的组成要素建立了一个客观和直观的模式，从而为研究人员提供了一个灵活而强大的基准，用于验证和扩展当前的方法。
