A Probabilistic Framework for Post-Disaster Recovery Modeling of Buildings and Utility Networks in Developing Countries

Abstract

Abstract Post-disaster recovery is a significant challenge, especially in developing countries. Various technical, environmental, socioeconomic, political, and cultural factors substantially influence post-disaster recovery. As a result, 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 and utility networks in developing countries. The proposed framework combines a building-level assessment of individual assets with a community-level assessment of utility networks 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. Similarly, a probabilistic modeling approach is proposed to quantify the utility network’s initial post-disaster outage levels. Specifically, empirical formulations for estimating the recovery time of an electric power network as a function of its initial post-disaster outage levels are calibrated using post-event data from 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.