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A location-allocation model for casualty response planning during catastrophic radiological incidents

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  • Caunhye, Aakil M.
  • Li, Mingzhe
  • Nie, Xiaofeng

Abstract

A radiological incident is an event whereby the release of radioactive material leads to significant consequences to people, the environment, and facilities. It has the potential of being catastrophic. We seek to analyze casualty response to such an event by addressing issues such as the creation of surge capacity, casualty prioritization, and the incorporation of self-evacuees in planning. We develop a location-allocation model that locates alternative care facilities and considers triage and the movement of self-evacuees in devising a casualty allocation plan for catastrophic radiological events. The model minimizes the total weighted transportation time of casualties and uses triage results to tactically prioritize casualties, while considering resource limitations. We apply the model to the case study of a radiological dispersal device situation in Los Angeles. With analysis of the resulting optimal plan and sensitivity analyses on the budget of alternative care facilities and on medical center triage capacities, we come up with several rules of thumb for casualty response planning. Our model aims to help central planners respond effectively to radiological incidents and better understand the response supply chain. It can thus help avert deaths and reduce suffering, especially in the current climate, where the increasing threat of terrorism is raising concerns over the next radiological attack being more in the offing than ever.

Suggested Citation

  • Caunhye, Aakil M. & Li, Mingzhe & Nie, Xiaofeng, 2015. "A location-allocation model for casualty response planning during catastrophic radiological incidents," Socio-Economic Planning Sciences, Elsevier, vol. 50(C), pages 32-44.
  • Handle: RePEc:eee:soceps:v:50:y:2015:i:c:p:32-44
    DOI: 10.1016/j.seps.2015.02.001
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    5. Alizadeh, Morteza & Amiri-Aref, Mehdi & Mustafee, Navonil & Matilal, Sumohon, 2019. "A robust stochastic Casualty Collection Points location problem," European Journal of Operational Research, Elsevier, vol. 279(3), pages 965-983.
    6. 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.
    7. Liu, Yang & Cui, Na & Zhang, Jianghua, 2019. "Integrated temporary facility location and casualty allocation planning for post-disaster humanitarian medical service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 1-16.
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    9. Caunhye, Aakil M. & Zhang, Yidong & Li, Mingzhe & Nie, Xiaofeng, 2016. "A location-routing model for prepositioning and distributing emergency supplies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 90(C), pages 161-176.

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