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Integrative Modeling of Housing Recovery as a Physical, Economic, and Social Process

Published

Author(s)

Elaina Sutley, Sara Hamideh, Maria Dillard, Donghwan Gu, Kijin Seong, John W. van de Lindt

Abstract

This paper presents a set of four simultaneous housing recovery states: RS0 no recovery progress; RS1 repair completion; RS2 re-occupancy; RS3 restored stability; RS4 restored accessibility. The recovery states are aimed at capturing the complex measurement of recovery that involves social, economic, and physical variables. Two least squares regression models analyzed post-disaster data to measure the causal factors on RS1 and RS2. These results were used to develop recovery-based fragility functions. Severe damage and receiving recovery funds from non- government organizations were the most influential predictors in longer repair and re-occupancy times, both resulting in months' worth of differences in timing, demonstrating the need for multi-disciplinary teams and analyses in analyzing resilience and recovery.
Proceedings Title
13th International Conference on Applications of Statistics and Probability in Civil Engineering
Conference Dates
May 26-30, 2019
Conference Location
Seoul, KR

Keywords

recovery, disaster, housing, community resilience, engineering, social science

Citation

Sutley, E. , Hamideh, S. , Dillard, M. , Gu, D. , Seong, K. and van de Lindt, J. (2019), Integrative Modeling of Housing Recovery as a Physical, Economic, and Social Process, 13th International Conference on Applications of Statistics and Probability in Civil Engineering, Seoul, KR, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=927170 (Accessed June 25, 2024)

Issues

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Created May 26, 2019, Updated January 11, 2024