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An advanced decision support system for European disaster management: the feature of the skills taxonomy

Author

Listed:
  • Marion S. Rauner

    () (University of Vienna)

  • Helmut Niessner

    (University of Vienna)

  • Steen Odd

    (Lund University)

  • Andrew Pope

    (University College Cork)

  • Karen Neville

    (University College Cork)

  • Sheila O’Riordan

    (University College Cork)

  • Lisa Sasse

    (University of Vienna)

  • Kristina Tomic

    (University of Vienna)

Abstract

Abstract Mankind has faced a huge increase in severe natural and man-made disasters worldwide in the last few years. Emergency responders on a strategic, tactical, and operational level can be assisted by decision support systems (DSS) to enhance disaster preparedness, response, and recovery. Policy makers are in need of an advanced, resilient and integrated incident command and control systems for emergency responders that incorporates health care-related features. To address this need, a DSS was developed in the European Union (EU) project named Securing Health.Emergency.Learning.Planning (S-HELP). Improving the health care delivery process through health care-related DSS features, the identification of key emergency responders and their associated tasks performed in preparedness, response, and recovery-related interventions is absolutely necessary. Thus, we establish a skills taxonomy for the S-HELP DSS Toolset “Decision Making Module” to interlink key emergency interventions/tasks with main national emergency responders supported by international emergency responders with a special focus on the EU. Furthermore, we provide an overview of which key emergency interventions/tasks can be covered by EU Civil Protection Modules by incorporating availability, start of operation, self-sufficiency, and operation time. This skills taxonomy for the S-HELP DSS Toolset “Decision Making Module” improves the interoperability of emergency responders when they cope with major disasters such as mass flooding, chemical spills, and biological-hazards policy scenarios that impact on health care. In the future, operation research models related to fields such as humanitarian logistics or disease control could be incorporated into or benefit from the S-HELP DSS.

Suggested Citation

  • Marion S. Rauner & Helmut Niessner & Steen Odd & Andrew Pope & Karen Neville & Sheila O’Riordan & Lisa Sasse & Kristina Tomic, 2018. "An advanced decision support system for European disaster management: the feature of the skills taxonomy," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(2), pages 485-530, June.
  • Handle: RePEc:spr:cejnor:v:26:y:2018:i:2:d:10.1007_s10100-018-0528-9
    DOI: 10.1007/s10100-018-0528-9
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