Alexander Garcia-Aristizabal, Maria Polese, Giulio Zuccaro, Miguel Almeida, & Christoph Aubrecht. (2015). Improving emergency preparedness with simulation of cascading events scenarios. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Natural or man-made disasters can trigger other negative events leading to tremendous increase of fatalities and damages. In case of Low Probability ? High consequences events, decision makers are faced with very difficult choices and the availability of a tool to support emergency decisions would be very much beneficial. Within EU CRISMA project a concept model and tool for evaluating cascading effects into scenario-based analyses was implemented.This paper describes the main concepts of the model and demonstrates its application with reference to two earthquake-triggered CE scenarios, including (the first) the falling of an electric cable, ignition and spreading of forest fire and (the second) the happening of a second earthquake in a sequence. Time dependent seismic vulnerability of buildings and population exposure are also considered for updating impact estimation during an earthquake crisis.
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Axel Dierich, Katerina Tzavella, Neysa Jacqueline Setiadi, Alexander Fekete, & Florian Neisser. (2019). Enhanced Crisis-Preparation of Critical Infrastructures through a Participatory Qualitative-Quantitative Interdependency Analysis Approach. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Critical Infrastructure (CI) failures are aggravated by cascading effects due to interdependencies between
different infrastructure systems and with emergency management. Findings of the German, BMBF-funded
research project ?CIRMin? highlight needs for concrete assessments of such interdependencies. Driven by
challenges of limited data and knowledge accessibility, the developed approach integrates qualitative
information from expert interviews and discussions with quantitative, place-based analyses in three selected
German cities and an adjacent county.
This paper particularly discusses how the mixed methods approach has been operationalized. Based on
anonymized findings, it provides a comprehensive guidance to interdependency analysis, from survey and
categorization of system elements and interrelations, their possible mutual impacts, to zooming into selected
dependencies through GIS mapping. This facilitates reliably assessing the need for maintenance of critical
functionalities in crisis situations, available resources, auxiliary powers, and optimization of response time.
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Gonzalez, J. J., & Eden, C. (2023). Devising Mitigation Strategies With Stakeholders Against Systemic Risks in a Pandemic. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 1000–1013). Omaha, USA: University of Nebraska at Omaha.
Abstract: Understanding and managing systemic risk has huge importance for disaster risk reduction in our globally connected world. The COVID-19 pandemic is a prominent case for the global impact of systemic risk. Did so the added urgency of the pandemic systemic risk trigger such paradigm shift? The use of qualitative modelling of systemic risk has progressed the field, particularly when policy makers need support urgently and want to utilize a range of interdisciplinary expertise. We have extended to disaster risk reduction a method for causal mapping for problem solving and strategy development targeting complex project management. Our approach delivers useful, useable, and used mitigation to systemic risk in a pandemic using participatory modelling with practitioners, domain experts and power-brokers.
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Hayley Watson, Kim Hagen, & Tom Ritchey. (2015). Experiencing GMA as a means of developing a conceptual model of the problem space involving understanding cascading effects in crises. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: A complex challenge facing those involved in crisis management relates to how to manage cascading effects in crisis situations. This paper provides a practice-based insight into the use of General Morphological Analysis (GMA), a non-quantified modelling method that can enable a shared understanding of the various interdependencies involved in cascading crises, by creating a conceptual model of a problem space. This insight paper provides an understanding of the nature of the method, and to reveal the project-related experiences of the facilitator and researchers, thereby contributing to an understanding of the benefits and challenges associated with GMA. Authors find that GMA provided a useful means of a multidisciplinary group developing an initial conceptual model for a complex problem. Whilst a challenging experience, the method will be used for conducting gap analyses at a later stage in the project, thus providing benefits to understanding and managing cascading effects in crises.
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Jose J. Gonzalez, Colin Eden, Eirik Abildsnes, Martin Hauge, Monica Trentin, Luca Ragazzoni, et al. (2021). Elicitation, analysis and mitigation of systemic pandemic risks. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 581–596). Blacksburg, VA (USA): Virginia Tech.
Abstract: The Covid-19 pandemic has disrupted the health care system and affected all sectors of society, including critical infrastructures. In turn, the impact on society's infrastructures has impacted back on the health care sector. These interactions have created a system of associated risks and outcomes, where the outcomes of risks are risks themselves and where the resulting consequences are complex vicious cycles. Traditional risks assessment methods cannot cope with interdependent risks. This paper describes a novel risk systemicity approach to elicit and mitigate the systemic risks of a major pandemic. The approach employed the internet-based software strategyfinder[TM] in workshops to elicit relevant risk information from sixteen appropriately selected experts from the health care sector and major sectors impacted by and impacting back on the health care sector. The risk information was processed with powerful analytical tools of strategyfinder to allow the experts to prioritise portfolios of strategies attacking the vicious cycles.
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Kim Hagen, Meropi Tzanetakis, & Hayley Watson. (2015). Cascading effects in crises: categorisation and analysis of triggers. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: The analysis of cascading effects in crisis situations can enhance crisis managers? understanding of how crises unfold and what prominent triggers of cascading effects are. By identifying and categorising triggers of cascading effects, a greater understanding of critical points in crisis situations can be reached, which can contribute to strengthening practices of crisis management, including preparedness and response. Accordingly, this paper provides an insight into triggers of cascading effects, gained through the analysis of six case studies of crises that took place between 1999 and 2014. The analysis produced six categories of triggers, which are discussed here: the disruption of pre-existing relations of information, organisation, and supply, disturbance relations, pre-disaster conditions, and the malfunctioning of legal and regulatory relations. Authors argue that the categorisation of triggers aids anticipating cascading effects, along with predicting risks and planning for potential bottlenecks in crisis management.
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Stefan Schauer, Stefan Rass, Sandra König, Thomas Grafenauer, & Martin Latzenhofer. (2018). Analyzing Cascading Effects among Critical Infrastructures. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 428–437). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In this article, we present a novel approach, which allows not only to identify potential cascading effects within a network of interrelated critical infrastructures but also supports the assessment of these cascading effects. Based on percolation theory and Markov chains, our method models the interdependencies among various infrastructures and evaluates the possible consequences if an infrastructure has to reduce its capacity or is failing completely, by simulating the effects over time. Additionally, our approach is designed to take the intrinsic uncertainty into account, which resides in the description of potential consequences a failing critical infrastructure might cause, by using probabilistic state transitions. In this way, not only the critical infrastructure's risk and security managers are able to evaluate the consequences of an incident anywhere in the network but also the emergency services can use this information to improve their operation in case of a crisis and anticipate potential trouble spots.
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