University of Kansas, Lawrence, KS, USA.
Stonybrook University, NY, USA.
Risk Anal. 2020 Dec;40(12):2675-2695. doi: 10.1111/risa.13576. Epub 2020 Aug 6.
Housing recovery is an unequal and complex process presumed to occur in four stages: emergency shelter, temporary shelter, temporary housing, and permanent housing. This work questions the four-stage typology and examines how different types of shelter align with multiple housing recovery stages given different levels of social vulnerability. This article also presents a Markov chain model of the postdisaster housing recovery process that focuses on the experience of the household. The model predicts the sequence and timing of a household going through housing recovery, capturing households that end in either permanent housing or a fifth possible stage of failure. The probability of a household transitioning through the stages is computed using a transition probability matrix (TPM). The TPM is assembled using proposed transition probability models that vary with the social vulnerability of the household. Monte Carlo techniques are applied to demonstrate the range of sequences and timing that households experience going through the housing recovery process. A set of computational rules are established for sending a household to the fifth stage, representing a household languishing in unstable housing. This predictive model is exemplified on a virtual community, Centerville, where following a severe earthquake scenario, differences in housing recovery times exceed four years. The Centerville analysis results in nearly 5% of households languishing in unstable housing, thereby failing to reach housing recovery. These findings highlight the disparate trajectories experienced by households with different levels of social vulnerability. Recommendations are provided at the end for more equitable postdisaster recovery policies.
住房恢复是一个不平等且复杂的过程，被认为分为四个阶段：紧急避难所、临时避难所、临时住房和永久性住房。这项工作对四阶段分类提出了质疑，并研究了在不同社会脆弱性水平下，不同类型的住房如何与多个住房恢复阶段相匹配。本文还介绍了一个灾后住房恢复过程的马尔可夫链模型，该模型侧重于家庭的体验。该模型预测了家庭经历住房恢复的顺序和时间，捕捉到最终进入永久性住房或第五个可能的失败阶段的家庭。使用转移概率矩阵（TPM）计算家庭通过各个阶段的概率。TPM 是使用针对家庭社会脆弱性的拟议转移概率模型组装而成的。蒙特卡罗技术被应用于演示家庭在经历住房恢复过程时的各种序列和时间。建立了一套将家庭发送到第五阶段的计算规则，代表家庭在不稳定住房中苦苦挣扎。该预测模型以一个虚拟社区 Centerville 为例，在经历了一场严重地震场景后，住房恢复时间的差异超过四年。Centerville 的分析结果显示，近 5%的家庭在不稳定的住房中苦苦挣扎，从而无法实现住房恢复。这些发现突显了不同社会脆弱性水平的家庭所经历的不同轨迹。最后提供了一些建议，以制定更公平的灾后恢复政策。
