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The efficacy of various types of intervention measures intended to facilitate post‐earthquake housing recovery can be evaluated ahead of time by using simulation models to quantify their benefits and tradeoffs. Towards this end, this paper presents a conceptual framework comprised of three components for modeling post‐earthquake housing recovery. The modeling framework starts with a probabilistic assessment of building‐level damage using recovery‐based limit states that characterize post‐earthquake functionality, inhabitability, and repairability. These limit states are the basis for the second component, which includes two different utility‐based models for representing post‐earthquake household decision making. Stochastic models to probabilistically quantify building‐level recovery trajectories comprise the third and final component of the framework. Collectively, these alternative models can integrate the effect of building states, available resources, household decisions, and endogenous factors such as lifeline restoration. The modeling framework can be scaled to model spatiotemporal scenarios of housing recovery to inform jurisdictional‐level policies, plans, and interventions to increase residential community resilience.
Burton et al. (Thu,) studied this question.