Agent-based model for post-earthquake housing recovery

A framework of agent-based models for housing recovery is presented and used to investigate post-earthquake recovery in the City of Vancouver, Canada. Housing recovery is modeled for a portfolio of buildings, contrasting with the practice of assessing the reconstruction of buildings in isolation. Thus, the presented approach better captures the effect of competition for resources, infrastructure disruptions, and socioeconomic factors on recovery. The analyses include models for damage, inspection, financing, power infrastructure, and labor/materials for repairs. The presented approach is applied to simulate the recovery of 114,832 residential buildings in 22 neighborhoods in Vancouver. Results indicate that recovery after a strong earthquake will take more than three years. The density of old and rented buildings, and the income and immigration status of the homeowners are shown to be good predictors of the speed of recovery for a neighborhood. Mitigation measures are compared and it is shown that retrofitting the most physically vulnerable buildings or doubling the available workforce are effective at reducing housing recovery times. It is demonstrated that the equity in recovery between low and high socioeconomic status homeowners is improved if mitigation measures are implemented. The results presented in this article can inform disaster recovery plans and mitigation actions in Vancouver and similar communities.

Automated summary

A study using an agent-based model framework investigated housing recovery post-earthquake in Vancouver, identifying the density of old and rented buildings, as well as homeowner income and immigration status as predictors of recovery speed. Simulation results showed that retrofitting vulnerable buildings or increasing workforce can effectively reduce housing recovery times.