Hybrid Modeling-Based Approach for Assessing and Enhancing Seismic Resilience of Healthcare Systems

Fig 3. Research framework

Fig 2. System dynamics model of the post-earthquake in-hospital functionality (overall structure)

Fig 1. Interactions of the components of healthcare systems for pre-hospital functionality after earthquakes

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Research Overview

Healthcare systems play an important role in the response and recovery of earthquake-hit regions. However, healthcare systems themselves likely subject to earthquake impacts, which hinders medical service continuity. The enhancement of resilience to earthquakes is crucial for healthcare systems to maintain their functionality during earthquakes and recover in a timely manner in the aftermath of earthquakes. Nevertheless, the lack of an effective approach to assess the seismic resilience of a healthcare system makes it challenging for devising and benchmarking appropriate resilience enhancement measures. To address this gap, this dissertation proposes a hybrid modeling-based approach for assessing and enhancing the seismic resilience of healthcare systems.

Firstly, the study constructs an agent-based model of the post-earthquake pre-hospital functionality of a single hospital. Secondly, the study constructs a system dynamics model of the post-earthquake in-hospital functionality of a single hospital. Thirdly, the study proposes a hybrid modeling-based approach for assessing and enhancing the seismic resilience of a healthcare system. Finally, a case study is conducted in Mianzhu City of Sichuan Province, China, which was one of the worst-hit cities in the 2008 Sichuan Earthquake.

The proposed approach contributes to analyzing the evolution of a healthcare system functionality after an earthquake and assessing the seismic resilience of a healthcare system. Moreover, the approach can serve as a decision-making tool to identify the weakness in the healthcare system seismic resilience and compare the effectiveness of different resilience enhancement measures so as to propose scientific and effective solutions.


Research Team

Li Zaishang

Funding

NFSC, No. 71974106,2020.01-2023.12