Alexandre Ahmad, Olivier Balet, Jesse Himmelstein, Arjen Boin, Maaike Schaap, Paolo Brivio, et al. (2012). Interactive simulation technology for crisis management and training: The INDIGO project. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: To face the urgent need to train strategic and operational managers in dealing with complex crises, we are researching and developing an innovative decision support system to be used for crisis management and interactive crisis training. This paper provides an overview of current decision-support systems, simulation software and other technologies specifically designed to serve crisis managers. These findings inform the design of a new interactive simulation technology system, where a 3D Common Operational Picture (COP) is shared between tactile digital whiteboard in the command center and mobile devices in the field. © 2012 ISCRAM.
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Robert T. Brigantic, David S. Ebert, Courtney D. Corley, Ross Maciejewski, George A. Muller, & Aimee E. Taylor. (2010). Development of a quick look pandemic influenza modeling and visualization tool. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Federal, State, and local decision makers and public health officials must prepare and exercise complex plans to contend with a variety of possible mass casualty events, such as pandemic influenza. Through the provision of quick look tools (QLTs) focused on mass casualty events, such planning can be done with higher accuracy and more realism through the combination of interactive simulation and visualization in these tools. If an event happens, the QLTs can then be employed to rapidly assess and execute alternative mitigation strategies, and thereby minimize casualties. This can be achieved by conducting numerous “what-if” assessments prior to any event in order to assess potential health impacts (e.g., number of sick individuals), required community resources (e.g., vaccinations and hospital beds), and optimal mitigative decision strategies (e.g., school closures) during the course of a pandemic. In this presentation, we overview and demonstrate a pandemic influenza QLT, discuss some of the modeling methods and construct and visual analytic components and interface, and outline additional development concepts. These include the incorporation of a user selectable infectious disease palette, simultaneous visualization of decision alternatives, additional resource elements associated with emergency response (e.g., first responders and medical professionals), and provisions for other potential disaster events.
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