Integrative modeling of housing recovery as a physical, economic, and social process

This paper presents a novel approach to modeling housing recovery through the formulation of recovery-based fragility functions built on empirical data collected longitudinally after a recent flood disaster. Previous community resilience frameworks have not addressed social and economic considerations in engineering-based recovery modeling. In doing so, this work takes an important step forward, advancing the use of probability and statistics in civil engineering applications and facilitating their role in interdisciplinary analysis of post-disaster recovery. To address community housing recovery after a flood event, two recovery-based limit states were analyzed: repair completion and re-occupancy. Two least squares regression models identified the variables most strongly associated with each limit state. These variables included household race and ethnicity, whether the household received post-disaster financial recovery assistance, and physical damage to the home. The analyses provide evidence of the simultaneous and interconnected social, economic, and physical processes that take place in a community and influence recovery progress, further demonstrating the need for multidisciplinary teams and analytic approaches in modeling resilience and recovery.