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Title:Traffic Resilience Modeling and Planning of Emergency Medical Response
Authors:Suren Chen and Yangyang Wu
University:Colorado State University
Publication Date:Jun 2022
Report #:MPC-22-458
Project #:MPC-569
TRID #:01848893
Keywords:bridges, disaster resilience, disasters and emergency operations, emergency medical services, emergency response time, traffic models
Type:Research Report – MPC Publications

 

Abstract

An efficient and timely rescue of injured people by emergency medical services (EMS) is essential to saving as many lives as possible following disasters. Disrupted traffic networks due to the failures of transportation infrastructure (e.g., bridges) following major disasters like earthquakes affect the accessibility and travel time of the disrupted transportation network during the emergency response stage. A rational prediction of the traffic network resilience performance in terms of EMS will help implement an optimized post-disaster medical response plan, and also identify the most cost-effective preventive measures before disasters occur. Post-hazard EMS transportation highly depends on both the medical needs of the vulnerable group and the serviceability of the disrupted traffic network. A framework to assess the resilience performance of a typical traffic network in terms of post-earthquake EMS is developed by considering the complex interactions between building infrastructures, injured people, vulnerable medical centers, EMS vehicles, disrupted traffic networks, and natural hazards. Two resilience performance indicators are introduced to characterize the relative importance of different links in a traffic network and overall EMS resilience for the entire network. A virtual community is selected as the prototype to demonstrate the proposed framework, which is followed by a parametric study of the earthquake magnitude, different types of bridges, location and number of medical centers, and optimal location for a new medical center facility. The proposed framework and resilience performance indicators can help establish a more efficient pre-disaster improvement plan of critical links, prioritize post-disaster recovery, and optimize the strategic placement and resource allocation of an EMS medical center.

How to Cite

Chen, Suren, and Yangyang Wu. Traffic Resilience Modeling and Planning of Emergency Medical Response, MPC-22-458. North Dakota State University - Upper Great Plains Transportation Institute, Fargo: Mountain-Plains Consortium, 2022.

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