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<p>The Mobility Vulnerability Index (MVI) introduces a dynamic, adaptive framework for quantifying community vulnerability to disasters through the analysis of real-time mobility behavior. It is designed to be cross-culturally adaptive, handle data sparsity, and evolve with disaster events as they unfold. Inspired by the FEMA Social Vulnerability Index and other resilience-based models, the MVI captures dynamic aspects of risk by integrating changes in mobility behavior across both the pre-disaster and post-disaster phases, thereby reflecting vulnerability related to preparation and recovery. The MVI is derived from anonymized population movement patterns, incorporating 12 sub-indices across the preparation and recovery phases to detect disruptions in accessibility, service availability, and mobility resilience. Validation using multiple hurricanes in Florida (Michael, Dorian, Sally) and typhoons in Japan (Hagibis, Haishen) demonstrates that the MVI sub-indices exhibit high internal stability (mean Pearson <i>r</i> &gt; 0.94) and robustness to weighting perturbations (±10% → mean Pearson <i>r</i> ≈ 0.997), with significant external correlations to NOAA property loss for Michael and Sally (<i>p</i> &lt; 0.05). The MVI’s modular design allows it to operate under varying data availability, while offering interpretable, high-resolution insights into evolving disaster vulnerabilities. Our framework supports near-real-time monitoring and evidence-based prioritization for emergency response and long-term resilience planning.</p>

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Mobility vulnerability index for community vulnerability assessment in disaster response

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月29日

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  • Jainil Anilkumar Patel,
  • Mohammadreza Akbari Lor,
  • Puneet Jeph,
  • Renhe Jiang,
  • Steven Luis,
  • Ryosuke Shibasaki,
  • Mei-Ling Shyu,
  • Shu-Ching Chen

摘要

The Mobility Vulnerability Index (MVI) introduces a dynamic, adaptive framework for quantifying community vulnerability to disasters through the analysis of real-time mobility behavior. It is designed to be cross-culturally adaptive, handle data sparsity, and evolve with disaster events as they unfold. Inspired by the FEMA Social Vulnerability Index and other resilience-based models, the MVI captures dynamic aspects of risk by integrating changes in mobility behavior across both the pre-disaster and post-disaster phases, thereby reflecting vulnerability related to preparation and recovery. The MVI is derived from anonymized population movement patterns, incorporating 12 sub-indices across the preparation and recovery phases to detect disruptions in accessibility, service availability, and mobility resilience. Validation using multiple hurricanes in Florida (Michael, Dorian, Sally) and typhoons in Japan (Hagibis, Haishen) demonstrates that the MVI sub-indices exhibit high internal stability (mean Pearson r > 0.94) and robustness to weighting perturbations (±10% → mean Pearson r ≈ 0.997), with significant external correlations to NOAA property loss for Michael and Sally (p < 0.05). The MVI’s modular design allows it to operate under varying data availability, while offering interpretable, high-resolution insights into evolving disaster vulnerabilities. Our framework supports near-real-time monitoring and evidence-based prioritization for emergency response and long-term resilience planning.