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Andrew Arnette, Christopher W. Zobel, & Duygu Pamukcu. (2020). Post-Impact Analysis of Disaster Relief Resource Pre-Positioning After the 2013 Colorado Floods. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 237–243). Blacksburg, VA (USA): Virginia Tech.
Abstract: Pre-positioning of supplies is important to facilitate disaster relief operations, however it is only after a disaster event occurs that the effectiveness of the pre-positioning strategy can be properly assessed. With this in mind, this paper analyzes a risk-based pre-positioning algorithm, developed for the American Red Cross, in the context of its actual performance in the 2013 Colorado Front Range floods. The paper assesses the relative effectiveness of the pre-positioning approach with respect to historical asset placements, and it discusses changes to the model that are necessary to support such comparisons and allow for further model extensions.
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Josey Chacko, Loren P Rees, & Christopher W. Zobel. (2014). Improving resource allocation for disaster operations management in a multi-hazard context. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 85–89). University Park, PA: The Pennsylvania State University.
Abstract: The initial impact of a disaster can lead to a variety of associated hazards. By taking a multi-hazard viewpoint with respect to disaster response and recovery, there is an opportunity to allocate limited resources more effectively, particularly in the context of long-term planning for community sustainability. This working paper introduces an approach for extending quantitative resource allocation models to consider multiple interrelated hazards. The discussion is motivated by a literature review of existing models and then focuses on changes necessary to take the multiplicity of hazards into consideration in the context of decision support systems for disaster operations management.
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Christophe Viavattene, Simon McCarthy, Michelle Ferri, Martina Monego, & Maurizio Mazzoleni. (2016). Evaluation of emergency protocols using agent-based approach. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Integrated flood risk management involves a large portfolio of options for mitigating risks that includes hard and soft structural, non-structural, and recovery responses. Non-structural responses include flood warnings, emergency services supported by individuals, collective actions and the use of resistance and resilience measures. Sufficient flood warning time, appropriate actions at desired locations and time are essential for effective and beneficial responses. From this perspective beside the management of the crisis itself, the level of preparedness including the evaluation of plans involving such responses (e.g. emergency protocols) also needs to be sufficient and, thus in the context of various event scenarios.
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Christopher W. Zobel. (2011). Representing the multi-dimensional nature of disaster resilience. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Although quantitative analytical information systems are an important resource for supporting decision-making in disaster operations management, not all aspects of a disaster situation can be easily quantified. For example, although the concept of the disaster resilience of a community has a technical dimension within which one can measure the resistance of the infrastructure against, and the speed of its recovery from, a disaster event, it also has social, organizational, and economic dimensions within which these characteristics may be more difficult to measure. This work-in-progress paper introduces a quantitative framework within which the multi-dimensional nature of such disaster resilience can be represented in a concise manner. This can help to improve understanding of the complexities associated with the concept, and thus directly support decision-making in disaster operations planning and management.
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