Modeling dynamics of post-disaster recovery

Natural disasters result in loss of lives, damage to existing facilities, and interruption of businesses. The losses are not instantaneous, but rather continue to occur until the community is restored to a functional socio-economic entity. Hence, it is essential that policy makers recognize this dynamic aspect of the incurred losses and make realistic plans to enhance recovery. However, this cannot take place without understanding how homeowners react to recovery signals. These signals can come in different ways: from policy makers showing their strong commitment to restore the community by providing financial support and/or restoration of lifeline infrastructure; or from the neighbors showing their willingness to reconstruct. The goal of this research is to develop a model that can account for neighbors' dynamic interactions by incorporating their signals in a spatial domain. A multi-agent framework is used to capture emergent behavior such as formation of clusters. The results from the model confirm the important role of spatial externality in agents' decision-making and the process of recovery. The results further highlight the significant impact of discount factor and the accuracy of the signals on the percentage of reconstruction. Finally, cluster formation was shown to be an emergent phenomenon during the recovery process.