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Regional response to large-scale emergency events: Building on historical data

Author

Listed:
  • Romanowski, Carol
  • Raj, Rajendra
  • Schneider, Jennifer
  • Mishra, Sumita
  • Shivshankar, Vinay
  • Ayengar, Srikant
  • Cueva, Fernando

Abstract

A widespread emergency event in the United States triggers the activation of a regional emergency operations center that manages a coordinated response to the disaster. Historically, the time-critical decisions made by emergency managers in the face of incomplete information and inadequate historical emergency event data have been guided primarily by their experience. The learning curve for emergency managers, especially novice managers, is steep, and is exacerbated by the complexity and scope of emergency events. This paper proposes a methodology designed to provide emergency managers with locality-specific information and resource allocation recommendations for large-scale event response, creating the foundation for a decision support system that draws on emergency event data. This work is the first to use locally-specific data for an emergency management decision support system. Two major allocation scenarios that influence the number of resources allocated to an event are considered and solutions are suggested to address them. Although the methodology is developed for a mid-sized region, it is generalizable to any region.

Suggested Citation

  • Romanowski, Carol & Raj, Rajendra & Schneider, Jennifer & Mishra, Sumita & Shivshankar, Vinay & Ayengar, Srikant & Cueva, Fernando, 2015. "Regional response to large-scale emergency events: Building on historical data," International Journal of Critical Infrastructure Protection, Elsevier, vol. 11(C), pages 12-21.
  • Handle: RePEc:eee:ijocip:v:11:y:2015:i:c:p:12-21
    DOI: 10.1016/j.ijcip.2015.07.003
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    1. Dirk Wrede & Annemarie Will & Tim Linderkamp & Johann-Matthias Graf Schulenburg, 2017. "An Urban Crisis Management System for Critical Infrastructures: Participation Possibilities for Insurance Companies," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 42(4), pages 633-656, October.
    2. Shivam Gupta & Sachin Modgil & Samadrita Bhattacharyya & Indranil Bose, 2022. "Artificial intelligence for decision support systems in the field of operations research: review and future scope of research," Annals of Operations Research, Springer, vol. 308(1), pages 215-274, January.

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