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Post-earthquake allocation approach of medical rescue teams

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  • Xiang Chu
  • QiuYan Zhong

Abstract

Earthquakes result in overwhelming demand for medical resources at once, and affected areas requires reinforcement from neighbor cities. An effective allocation approach of medical rescue teams in early stage of disaster relief can improve rescue performance significantly. To find optimal allocation strategy, an integer nonlinear programming model is established, following utility principle. To construct the optimization model, stochastic transition probability of triage levels is introduced. Meanwhile, function from allocation scheme to fatalities of areas is established. Next, we design algorithm based on Lingo software to find solution of utility model. Finally, numerical experiments based on real data in 2008 Sichuan earthquake in China are used to compare utility approach with existing approaches in practice. The results of experiments indicate that: (1) to save more lives, a support team should preferentially be allocated to a worse and nearer affected area. When the worst area is not the nearest, the team also may be sent to an area with moderate severity and moderate distance. (2) Compared with severity strategy and distance strategy, utility strategy improves rescue efficiency significantly. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Xiang Chu & QiuYan Zhong, 2015. "Post-earthquake allocation approach of medical rescue teams," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(3), pages 1809-1824, December.
  • Handle: RePEc:spr:nathaz:v:79:y:2015:i:3:p:1809-1824
    DOI: 10.1007/s11069-015-1928-y
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    References listed on IDEAS

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    1. Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.
    2. Wilson, Duncan T. & Hawe, Glenn I. & Coates, Graham & Crouch, Roger S., 2013. "A multi-objective combinatorial model of casualty processing in major incident response," European Journal of Operational Research, Elsevier, vol. 230(3), pages 643-655.
    3. Xiang Chu & Qiu-Yan Zhong & Shahid G. Khokhar, 2015. "Triage Scheduling Optimization for Mass Casualty and Disaster Response," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 32(06), pages 1-20, December.
    4. Hui Cao & Simin Huang, 2012. "Principles of Scarce Medical Resource Allocation in Natural Disaster Relief," Medical Decision Making, , vol. 32(3), pages 470-476, May.
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    Cited by:

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    2. Ghazaleh Ahmadi & Reza Tavakkoli-Moghaddam & Armand Baboli & Mehdi Najafi, 2022. "A decision support model for robust allocation and routing of search and rescue resources after earthquake: a case study," Operational Research, Springer, vol. 22(2), pages 1039-1081, April.
    3. Pingping Cao & Jin Zheng & Mingyang Li, 2023. "Post-Earthquake Scheduling of Rescuers: A Method Considering Multiple Disaster Areas and Rescuer Collaboration," Sustainability, MDPI, vol. 15(15), pages 1-22, July.
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    5. ShiYang Tang & XueMing Shu & ShiFei Shen & ZhangHua Li & SiYang Cao, 2017. "Study of portable infrastructure-free cell phone detector for disaster relief," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 86(1), pages 453-464, March.

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