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Adaptive capability-based functionality assessment for post-disaster response in urban regional healthcare system incorporating demand uncertainty

Author

Listed:
  • Huang, Yuhan
  • Xu, Longhe
  • Li, Jun
  • Xie, Xingsi
  • Zhang, Ge

Abstract

A reliable assessment method is critical for capturing emergency behaviors and determining the functionality of urban healthcare system exposed to disasters. However, existing functionality-centered methods often pay limited attention to the uncertainty and dynamics of healthcare demand. Common global disaster scenario modelling approaches also offer limited flexibility in decision-making. To fill these gaps, an adaptive capability-based assessment method is proposed to assess the healthcare functionality adapting to dynamic demands. A stochastic computing approach is developed for dynamic demand generation by combining rescue characteristic functions with uncertainty, and dynamic behaviors are simulated using a multi-phase programming-based approach with a pseudo dispatch mechanism. The method is demonstrated on an urban regional healthcare system. Parametric runs show that: (i) adaptive capability initially rises then collapses as population density and disaster intensity grow; (ii) enhancing disaster resistance on the demand side reliably safeguards system performance; (iii) after a maximum considered earthquake the system cannot match a full early rescue work with gamma rescue characteristic pattern. These findings further confirm the importance and effectiveness of the proposed method to track dynamic and uncertain demand. It provides an approach for regional functionality assessment, risk identification, and phased decision-making in healthcare systems during disaster scenarios.

Suggested Citation

  • Huang, Yuhan & Xu, Longhe & Li, Jun & Xie, Xingsi & Zhang, Ge, 2026. "Adaptive capability-based functionality assessment for post-disaster response in urban regional healthcare system incorporating demand uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 269(C).
    • Handle: RePEc:eee:reensy:v:269:y:2026:i:c:s0951832025013262
    DOI: 10.1016/j.ress.2025.112127
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    References listed on IDEAS

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