A Probabilistic Framework for Post-Disaster Recovery Modeling of Buildings in Developing Countries
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2023Access:
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Eyitayo Opabola, Carmine Galasso, A Probabilistic Framework for Post-Disaster Recovery Modeling of Buildings in Developing Countries, 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland, 2023.Download Item:
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Post-disaster recovery is a significant challenge, especially in developing countries. As a result of various technical, environmental, socioeconomic, political, and cultural factors influencing post-disaster recovery, methodologies relevant in developed nations may not be directly applicable in Global South contexts. This study introduces a probabilistic framework for modeling the post-disaster recovery of buildings in developing countries. The proposed framework combines a building-level assessment of individual assets to evaluate the post-disaster functionality state of a building portfolio. As part of the framework, a stochastic network analysis approach is proposed to estimate the recovery time of damaged buildings while accounting for technical, environmental, socioeconomic, political, and cultural factors, quantified using data gathered from past events in developing countries. A case study is presented to illustrate the application of the proposed framework to model the post-earthquake recovery of a synthetic low-income residential community. The analysis showed that negative technical, environmental, socioeconomic, political, and cultural factors could amplify the reconstruction time of damaged buildings by a factor of almost three. The proposed framework can support decision-makers in disaster planning and management strategies for vulnerable low-income communities.
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14th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP14)Type of material:
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