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Statistical Modeling for Community Recovery after Seismic Events

  • Author(s): Kang, Hua
  • Advisor(s): Wu, Yingnian
  • et al.
Abstract

The vulnerability of residential communities to earthquakes plays a key role in post-earthquake recovery, since all the other functionality of a community rely on residents having healthy living conditions remaining in the affected region. Understanding the time-dependent effects of hazard events on housing is critical for improving post-earthquake trends through policy and planning interventions. The existing approaches on recovery-related simulation and trajectories require excessive knowledge in earthquake engineering, detailed information of earthquake records, the building structures and complex numerical structural models. This study seeks to explore the possibility of predicting the times of two key sequential pre-construction and construction phases using Socio-Economic data collected from a subset of the earthquake-damaged residential buildings and information from the on-site inspection in 2014 Napa earthquake. A series of statistical models are built and the optimal ones are selected by cross-validation. The community recovery process is then simulated by incorporating the predicted recovery paths of individual buildings into a stochastic process and is compared with the observed recovery curves. The proposed recovery model can be used to assist policy-makers, municipal governments and planners in understanding the possible interdependencies, interventions, and tradeoffs associated with housing recovery.

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