Abstract

In coastal cities, the damage stemming from hurricanes and severe tropical storms may reduce housing stock. Accelerating the reconstruction of housing stock becomes crucial in minimizing the time that residents are displaced. It is critical to understand how to better coordinate all available resources for an effective and balanced reconstruction where nongovernmental organizations (NGOs), government agencies, volunteers, and many other complex resources converge. This study combines Monte Carlo and beta models to assess supply, costs, and recovery times. The models capture the immediate and long-term costs of reconstruction activities under highly uncertain conditions using embedded stochastic components on projected materials, labor, and equipment flows. The model identifies possible hurdles in acquiring likely material and labor and prospective thresholds that might affect the housing recovery process. This research addresses gaps in strategic humanitarian recovery decision-making by modeling housing damage costs through granular-level housing reconstruction activities. In addition, these models provide constructive insight into how cost and completion time are dependent upon supply uncertainties.

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