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Modeling emergency medical response to a mass casualty incident using agent based simulation

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  • Wang, Yu
  • Luangkesorn, K. Louis
  • Shuman, Larry

Abstract

Emergency managers have to develop plans for responding to disasters within their jurisdiction. This includes coordinating multiple independent agencies participating in the response. While much of this is currently done by use of intuition and expert judgment, models can be used to test assumptions and examine the impact of policies and resource levels. The autonomous nature of responders as well as the rapidly changing information during a disaster suggests that agent based models can be especially suited for examining policy questions. In this work, we built an agent based model of a given urban area to simulate the emergency medical response to a mass casualty incident (MCI) in that area. The model was constructed from publicly available geographic information system and data regarding available response resources (such as ambulances, EMS personnel and hospital beds). Three different agent types are defined to model heterogeneous entities in the system. By simulating various response policies, the model can inform emergency responders on the requirements and response protocols for disaster response and build intuition and understanding in advance of facing actual incidents that are rare in the day-to-day operating experiences.

Suggested Citation

  • Wang, Yu & Luangkesorn, K. Louis & Shuman, Larry, 2012. "Modeling emergency medical response to a mass casualty incident using agent based simulation," Socio-Economic Planning Sciences, Elsevier, vol. 46(4), pages 281-290.
    • Handle: RePEc:eee:soceps:v:46:y:2012:i:4:p:281-290
    DOI: 10.1016/j.seps.2012.07.002
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    2. Farahani, Reza Zanjirani & Lotfi, M.M. & Baghaian, Atefe & Ruiz, Rubén & Rezapour, Shabnam, 2020. "Mass casualty management in disaster scene: A systematic review of OR&MS research in humanitarian operations," European Journal of Operational Research, Elsevier, vol. 287(3), pages 787-819.
    3. Aros, Susan K. & Gibbons, Deborah E., 2018. "Exploring communication media options in an inter-organizational disaster response coordination network using agent-based simulation," European Journal of Operational Research, Elsevier, vol. 269(2), pages 451-465.
    4. Glasgow, Simon M. & Perkins, Zane B. & Tai, Nigel R.M. & Brohi, Karim & Vasilakis, Christos, 2018. "Development of a discrete event simulation model for evaluating strategies of red blood cell provision following mass casualty events," European Journal of Operational Research, Elsevier, vol. 270(1), pages 362-374.

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