Alexander Gabriel, Florian Brauner, Andreas Lotter, Frank Fiedrich, & Ompe Aimé Mudimu. (2018). The determination of critical components of European Rail Traffic Management systems towards cyber-attacks. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 291–303). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: “Recent events have shown the vulnerability of IT systems of companies, organizations or even governments to hacker attacks. At the same time, information technologies are becoming increasingly established and important in various industries (digitalization). With a view to the modern development of terrorism, cyber-attacks can be used to physically damage critical infrastructures (CI). This leads to a new dimension of cyber-attacks, which are called terrorist cyber-attacks. The following research contributes to the identification of weak information technology components of railway operating systems and thus improves the safety of public transportation in the context of the European railway traffic management system (ERTMS). The core of this paper is an extended literature research on security flaws in the ERTMS. The future introduction of a methodology for evaluating the criticality of information technology system components will build on this using cyber threats and public transportation as examples.”
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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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Amelie Grangeat, Floriane Brill, Stephane Raclot, & Emmanuel Lapebie. (2016). Mapping of Areas Presenting Specific Risks to Firefighters due to Buried Technical Networks. 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: Vehicles or freight cars on fire below a bridge or inside a tunnel are exceptional events and imply difficult intervention conditions for firefighters. A buried technical network like high voltage electricity line, gas or steam pipeline around such a fire causes additional specifics risks. Vulnerability areas for firefighters are defined as zones where both factors exist: a difficult incident area – like tunnels or bridges over roads/railway lines ? together with a specific risk like buried networks. These areas require intervention teams with specific emergency response capabilities. The present paper proposes a method developed for the Paris Fire Brigade for vulnerability mapping. Results aim at being used by their decision support system dedicated to the mobilization of intervention teams. On the long term, it could improve the allocation of specific responses capabilities intervention teams as soon as the emergency call is treated. Results are debated from an operational point of view.
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Anmol Haque, Duygu Pamukcu, Ruixiang Xie, Mohsen Zaker Esteghamati, Margaret Cowell, & Jennifer L. Irish. (2021). Cascading Effects of Mass Gatherings on COVID-19 Infections from a Multi-hazard Perspective: A Case Study of New York City. 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. 218–227). Blacksburg, VA (USA): Virginia Tech.
Abstract: The devastating economic and societal impacts of COVID-19 can be substantially compounded by other secondary events that increase individuals' exposure through mass gatherings such as protests or sheltering due to a natural disaster. Based on the Crichton's Risk Triangle model, this paper proposes a Markov Chain Monte Carlo (MCMC) simulation framework to estimate the impact of mass gatherings on COVID-19 infections by adjusting levels of exposure and vulnerability. To this end, a case study of New York City is considered, at which the impact of mass gathering at public shelters due to a hypothetical hurricane will be studied. The simulation results will be discussed in the context of determining effective policies for reducing the impact of multi-hazard generalizability of our approach to other secondary events that can cause mass gatherings during a pandemic will also be discussed.
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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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Gonçalo Caiado, Rosário Macário, & Carlos Sousa Oliveira. (2011). A new paradigm in urban road network seismic vulnerability: From a link-by-link structural approach to an integrated functional assessment. 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: Other than the direct exposure of a seismic event, the interruption of the transportation network causes an indirect exposure of the population living in stricken areas. In spite of such evidences, current planning practices rarely address road network seismic risk concerns beyond the typical structural link-by-link approach. The underlying hypothesis of the current research work is that, when facing a major earthquake, the impacts on road networks performance for emergency response functions can be minimized namely by the introduction of measures, not only in terms of infra-structural reinforcement but also in terms of network connectivity and activities location. Potential applications of this work include urban planning micro and macro scale solutions to be included in specific instruments (such as urban master plans or emergency plans). Additionally, the proposed method may be integrated in loss estimation models, which still do not include earthquake losses due to inaccessibility.
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Tina Comes, & Bartel A. Van De Walle. (2014). Measuring disaster resilience: The impact of hurricane sandy on critical infrastructure systems. 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. 195–204). University Park, PA: The Pennsylvania State University.
Abstract: Modern critical infrastructure (CI) systems are tightly coupled, resulting in unprecedented complexity and difficulty to predict, limit and control the consequences of disruptions caused by hazards. Therefore, a paradigm shift in disaster risk management is needed: instead of focusing on predicting events, resilience needs to be improved as a basis for adequate response to any event. This paper starts from a definition of CI resilience that provides a basis for quantitative and qualitative decision support. For the quantitative modelling approach, which aims at measuring the resilience of individual CIs, we focus on two CIs of fundamental importance for disaster response: transportation and power supply. The qualitative framework details relations between CIs. The results of this research are illustrated by a case study that analyses the impact of Hurricane Sandy. The findings highlight the need for a framework that combines qualitative and quantitative information from heterogeneous sources to improve disaster resilience.
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Tina Comes, Valentin Bertsch, & Simon French. (2013). Designing dynamic stress tests for improved critical infrastructure resilience. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 307–311). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: This paper outlines an approach to support decision-makers in designing resilient critical infrastructure (CI) networks. As CIs have become increasingly interdependent disruptions can have far-reaching impacts. We focus on the vulnerability of CIs and the socio-economic systems, in which they are embedded, independent from any initial risk event. To determine which disruptions are the most severe and must be avoided, quantitative and qualitative assessments of a disruption's consequences and the perspectives of multiple stakeholders need to be integrated. To this end, we combine the results of consequence models and expert assessments into stress test scenarios, which are evaluated using multi-criteria decision analysis techniques. This approach enables dynamic adaption of the stress tests in the face of a fast changing environment and to take account of better information about interdependencies or changing preferences. This approach helps make trade-offs between costs for resilient CIs and potential losses of disruptions clearly apparent.
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Diana Contreras, Thomas Blaschke, Stefan Kienberger, & Peter Zeil. (2011). Spatial vulnerability indicators: Measuring recovery processes after earthquakes. 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: In order to analyze and evaluate any post-disaster phases it is necessary to address the pre-existent vulnerability conditions. The methodology consists of four steps: the first step comprises of a review of vulnerability and recovery indicators; the second step is to identify indicators based on spatial variables; the third step is to find the common variables among the subsets of spatial variables from vulnerability and recovery indicators; and the fourth step more pragmatic, is an investigation of the availability of data. The initial results are the set of vulnerability and recovery indicators. Reducing the set of indicators to the indicators represented in a spatial context and the indicators with common features of vulnerability and recovery indices bears the risk to ignore some important single indicators; nevertheless, the added value of the on-going research is to show the advantages of using indicators based on spatial variables.
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Derya Ipek Eroglu, Duygu Pamukcu, Laura Szczyrba, & Yang Zhang. (2020). Analyzing and Contextualizing Social Vulnerability to Natural Disasters in Puerto Rico. 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. 389–395). Blacksburg, VA (USA): Virginia Tech.
Abstract: As the third hurricane the U.S. experienced in 2017, Hurricane María generated impacts that resulted in both short term and long term suffering in Puerto Rico. In this study, we aim to quantify the vulnerability of Puerto Ricans by taking region and society specific characteristics of the island into account. To do this, we follow Cutter et al.'s social vulnerability calculation, which is an inductive approach that aims to represent a society based on its characteristics. We adapted the Social Vulnerability Index (SoVI) for Puerto Rico by using data obtained from the U.S. Census Bureau. We analyzed the newly calculated SoVI for Puerto Rico and compared it with the existing deductive approach developed by the Center for Disease Control (CDC). Our findings show that the new index is able to capture some characteristics that the existing vulnerability index is unable to do.
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Dunn, M. M. (2023). Aphorme: An Intralingual Translation Tool for Emergency Management and Disaster Response. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 1033–1041). Omaha, USA: University of Nebraska at Omaha.
Abstract: While multilingual translation needs (from one or more language(s) to one or more others) in disaster events are a “perennial issue” among responders in crisis-affected communities (Crowley & Chan, 2011) and calls are being made to consider the access to (and translation of) information during crisis a human right (Greenwood et al., 2017), the literature that deals with intralingual translation in disaster is limited in places where it should thrive, such as crisis communication, translation studies, and rhetoric. Intralingual translation is of increasing relevance in disaster not only because of potential variability in literacy levels among those affected (O’Brien, 2020) but because responding to/planning for disaster requires an understanding of the ‘operational’ terms used (but not always shared) by other responding agencies in the field. This paper calls for increased attention to intralingual translation needs in disaster and introduces a translation technology (“Aphorme”) designed to mitigate those needs.
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Florian Brauner, Thomas Münzberg, Marcus Wiens, Frank Fiedrich, Alex Lechleuthner, & Frank Schultmann. (2015). Critical Infrastructure Resilience: A Framework for Considering Micro and Macro Observation Levels. 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 resilience mechanisms of Critical Infrastructures (CIs) are often hard to understand due to system complexity. With rising research interest, models are developed to reduce this complexity. However, these models imply reductions and limitations. According to the level of observation, models either focus on effects in a CI system or on effects in a single CI. In cases of limited resources, such limitations exclude some considerations of crisis interventions, which could be identified in combining both observation levels. To overcome these restrictions, we propose a two-step framework which enables to analyze the vulnerability of a CI and as well in comparison to other CIs. This enhances the understanding of temporal crisis impacts on the overall performance of the supply, and the crisis preparations in each CI can be assessed. The framework is applied to the demonstrating example of the functionalities of hospitals that are potentially suffering from a power outage.
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Zeno Franco, Syed Ahmed, Craig E. Kuziemsky, Paul A. Biedrzycki, & Anne Kissack. (2013). Using social network analysis to explore issues of latency, connectivity, interoperability & sustainability in community disaster response. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 896–900). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Community-based disaster response is gaining attention in the United States because of major problems with domestic disaster recovery over the last decade. A social network analysis approach is used to illustrate how community-academic partnerships offer one way to leverage information about existing, mediated relationships with the community through trusted actors. These partnerships offer a platform that can be used to provide entré into communities that are often closed to outsiders, while also allowing greater access to community embedded physical assets and human resources, thus facilitated more culturally appropriate crisis response. Using existing, publically available information about funded community-academic partnerships in Wisconsin, USA, we show how social network analysis of these meta-organizations may provide critical information about both community vulnerabilities in disaster and assist in rapidly identifying these community resources in the aftermath of a crisis event that may provide utility for boundary spanning crisis information systems.
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Gah-Kai Leung. (2021). Reducing Flood Risks for Young People in the UK Housing Market. 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. 481–487). Blacksburg, VA (USA): Virginia Tech.
Abstract: Flooding is one of the most serious natural hazards faced in the UK. The Environment Agency estimates that in England alone, about 5.2 million properties are at risk of flooding, or roughly one in six (2009: 3). Flooding imposes significant financial, psychological and social burdens on households and these may be especially acute for young people in the property market, such as renters and first-time buyers. This paper examines how housing-related policy can help alleviate the burdens of flooding on young people in the housing market. First, it canvasses the kinds of damage inflicted when flooding affects properties. Second, it discusses the financial burdens imposed by such damage. Third, it enumerates the financial burdens and benefits of measures to protect against flooding. Fourth, it considers the non-monetary burdens of flooding, in the form of psychological and social burdens. Finally, the paper offers some policy recommendations in light of the preceding discussion.
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Haitao Sun, Zhiru Wang, Guofeng Su, & Jianguo Chen. (2016). Topological Structure Vulnerability Assessment of Shanghai Urban Metro Networks. 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: Topological structure vulnerability assessment approach for Urban Metro Networks (UMNS) was proposed in order to decrease the impact caused by incidents. Failure scale of stations and sections random failure and target attacks was evaluated. The results show that UMNS is more vulnerable to target attacks on stations than random failure on stations. But UMNS is less vulnerable to target attacks on sections than random failure on sections. Additionally, UMNS is more vulnerable to station failure than sections. It could be concluded as more resources should be put on big transfer stations in UMNS operation management to avoid large scale impacts. The proposed methodology is not intended to predict the occurrence of events but rather to be used a management tool. Results from the evaluation are valuable elements in planning UMNS. They can be used for network planning, further detailed hazard studies, deciding on the arrangement of emergency resources.
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Michael Hiete, & Mirjam Merz. (2009). An indicator framework to assess the vulnerability of industrial sectors against indirect disaster losses. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Natural and man-made hazards may affect industrial production sites by both direct losses (due to physical damage to assets and buildings) and indirect losses (production losses). Indirect losses, e.g. from production downtimes, can exceed direct losses multiple times. Thus, the vulnerability of industrial sectors to indirect losses is an important component of risk and its determination is an important part within risk analysis. In this paper a conceptual indicator framework is presented which allows to assess the indirect vulnerability of industrial sectors to different types of disasters in a quantitative manner. The results are useful for information sharing and decision making in crisis management and emergency planning (mitigation measures, business continuity planning), since the developed indicator system helps to take the complex phenomenon of industrial vulnerability and the underlying interdependencies into account. Besides the identification and conceptual motivation of the indicators, methodical aspects such as standardization, weighting and aggregation are addressed.
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Ivar Svare Holand, Peter Mozelius, & Trond Olav Skevik. (2021). A structured and dynamic model for emergency management exercises. 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. 186–197). Blacksburg, VA (USA): Virginia Tech.
Abstract: Emergencies are management challenges, and emergency exercises that involve multiple collaborating parties is a means towards mastering them. Such exercises are often conducted in a virtual training environment based on complex disaster scenarios. The reported study was carried out using a requirement-focused design approach. The aim was to describe and discuss a relevant design for lean, dynamic, and cost-efficient emergency management exercise systems. Data were gathered from a literature study and analyses of earlier emergency management projects in which the authors had participated. Despite the complexity of many current emergency management exercises, the scenarios usually involve only the response phases and have a linear structure that hinders both didactic aspects and the software structure. The conclusion drawn from the study is that an emergency management exercise model should focus on managing the activities that correspond to alternatives that unfold from a dynamic scenario. Finally, the authors recommend the principles of alternate reality games as a way towards more dynamic and cost-efficient emergency exercise systems.
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Kevin D. Henry, & Tim G. Frazier. (2015). Scenario-Based Modeling of Community Evacuation Vulnerability. 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: Evacuation models can be used to determine evacuation capacity, by estimating the time required for evacuating populations to leave areas exposed to a hazard. Disaster management practices and evacuation modeling are generally carried out to prepare for ?worst-case? conditions. However, hazard severity is highly variable. Performing evacuation modeling for multiple hazard scenarios may provide flexibility and a comprehensive understanding of evacuation capacity. A case study was undertaken to analyze the merit of scenario-based evacuation modeling. Results demonstrate a difference in clearance time between maximum and historic tsunami scenario modeling. During a smaller-scale event, allowing the maximum scenario population to evacuate can add congestion and inhibit evacuation of at-risk populations. Managing evacuation can improve evacuation efficiency by preventing unneeded congestion. Results show that traditional worst-case-scenario modeling may lead to overestimation of time needed to evacuate. Planning under such a scenario may increase risk to smaller-scale hazards.
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Leire Labaka, Josune Hernantes, Tina Comes, & Jose Mari Sarriegi. (2014). Defining policies to improve critical infrastructure resilience. 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. 429–438). University Park, PA: The Pennsylvania State University.
Abstract: Industrial accidents increasingly threaten society and economy; the increasing exposure and vulnerability of our modern interlaced societies contributes to intensifying their impact. Critical Infrastructures (CIs) have a prominent role, since they are vital for the welfare of the population and essential for the economic growth. As hazards are hard to predict, decision-makers need to implement adequate adaptation and mitigation strategies to improve CI resilience. Although CI resilience has attracted increasing attention, empirical studies are rare. Research on the implementation of policies aiming at identifying a clear sequence of measures to improve CI resilience is lacking. Therefore, we present a framework to identify resilience policies across four dimensions (technical, organizational, economic and social) and to define the temporal order in which the policies should be implemented. This research provides a framework grounded in our empirical work. Future work will aim at developing quantitative approaches to complement our results.
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Laura Szczyrba, Yang Zhang, Duygu Pamukcu, & Derya Ipek Eroglu. (2020). A Machine Learning Method to Quantify the Role of Vulnerability in Hurricane Damage. 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. 179–187). Blacksburg, VA (USA): Virginia Tech.
Abstract: Accurate pre-disaster damage predictions and post-disaster damage assessments are challenging because of the complicated interrelationships between multiple damage drivers, including various natural hazards, as well as antecedent infrastructure quality and demographic characteristics. Ensemble decision trees, a family of machine learning algorithms, are well suited to quantify the role of social vulnerability in disaster impacts because they provide interpretable measures of variable importance for predictions. Our research explores the utility of an ensemble decision tree algorithm, Random Forest Regression, for quantifying the role of vulnerability with a case study of Hurricane Mar\'ia. The contributing predictive power of eight drivers of structural damage was calculated as the decrease in model mean squared error. A measure of social vulnerability was found to be the model's leading predictor of damage patterns. An additional algorithm, other methods of quantifying variable importance, and future work are discussed.
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Lutiane Queiroz de Almeida, Torsten Welle, & Jörn Birkmann. (2016). A Methodological Proposal to Disaster Risk Indicators in Brazil. 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: This article provides a tool to help assess, visualise and communicate different levels of exposure, vulnerability and risk in Brazil. The Disaster Risk Index in Brazil may sensitise public and political decision-makers towards the important topic of disaster risk and climate change adaptation. This article aims to explore the feasibility and usefulness of such a national risk index that considers both natural hazard phenomena and social vulnerability. The results showed that the risk is strongly interwoven with social-economic and cultural conditions and normal everyday life, as well as with the performance of state institutions dealing with Disaster Risk Reduction and Disaster Risk Management, in other words, vulnerability. Spatial trends of disaster risk and vulnerability, products of this research, also have stressed the serious inequalities between and within regions of the country, which result in barriers to the development of the DRR and DRM in Brazil as a whole.
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Thomas Münzberg, Tim Müller, Stella Möhrle, Tina Comes, & Frank Schultmann. (2013). An integrated multi-criteria approach on vulnerability analysis in the context of load reduction. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 251–260). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Load reduction is an emergency measure to stabilize an electrical grid by decoupling some supply areas to balance the demand and supply of electricity in power grids. In the decoupled areas, power outages may cause important consequences, which may propagate further via the network of interdependent infrastructures. Therefore, support is needed to choose the regions to be decoupled. This paper describes an approach to analyze the risk triggered by load reduction that can be used for disaster management and load reduction scheme optimization. The core of our work is the vulnerability assessment that takes into account the consequences of load reduction on economy and society. The approach facilitates participatory decision support by making the vulnerability of regions especially in urban transparent.
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Thomas Münzberg, Marcus Wiens, & Frank Schultmann. (2014). A strategy evaluation framework based on dynamic vulnerability assessments. 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. 45–54). University Park, PA: The Pennsylvania State University.
Abstract: Assessing a system's vulnerability is a widely used method to estimate the effects of risks. In the past years, increasingly dynamic vulnerability assessments were developed to display changes in vulnerability over time (e.g. in climate change, coastal vulnerability, and flood management). This implies that the dynamic influences of management strategies on vulnerability need to be considered in the selection and implementation of strategies. For this purpose, we present a strategy evaluation framework which is based on dynamic vulnerability assessments. The key contribution reported in this paper is an evaluation framework that considers how well strategies achieve a predefined target level of protection over time. Protection Target Levels are predefined objectives. The framework proposed is inspired by Goal Programming methods and allows distinguishing the relevance of time-dependent achievements by weights. This enables decision-makers to evaluate the overall performance of strategies, to test strategies, and to compare the outcome of strategies.
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Maria A. Santos, António Gonçalves, Sandra Silva, Nuno Charneca, & Miguel Gamboa. (2004). Dam break emergency response Information System. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2004 – 1st International Workshop on Information Systems for Crisis Response and Management (pp. 27–32). Brussels: Royal Flemish Academy of Belgium.
Abstract: Although considered of low risk, incidents with dams may cause significant damage both directly and indirectly. Direct losses are usually easier to assess (assuming human lives are quantifiable), but indirect losses are difficult to measure and may take some time before the original situation is restored. Disaster prevention and vulnerability reduction have been topics of major concern in many local, national or international organisations for some years. These can be accomplished through emergency management which begins with hazard identification and planning for disaster mitigation but encompasses other activities as risk analysis, risk response and recovery. Therefore, an emergency management system with capacity to: i) forecast critical situations; ii) warn the population as well as the authorities; and iii) support the civil protection system to deal with an emergency, is a most helpful tool to minimize the impact of an accident. The Information System described herein fulfils mainly the third objective, i.e. it is intended to help the Civil Protection System in Portugal, to respond to an emergency caused by the failure of a dam. It is an Internet-based application, which integrates all relevant data for the implementation of a dam emergency plan. These data include the main characteristics of the dam and its reservoir, the character-isation of the dam downstream valley as well as the response procedures to be followed in an emergency. © Proceedings ISCRAM 2004.
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Savannah Thais, Shaine Leibowitz, Allie Saizan, & Ashay Singh. (2022). Understanding Historical, Socio-Economic, and Policy Contributions to COVID-19 Health Inequities. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 481–494). Tarbes, France.
Abstract: The COVID-19 pandemic has generated unprecedented, devastating impacts across the United States. However, some communities have disproportionately endured adverse health outcomes and socioeconomic injuries. Ascertaining the factors driving these inequities is crucial to determining how policy could mitigate the impacts of future public health crises. We have established research-driven metrics, aggregated as the Community Vulnerability Index (CVI), that quantify vulnerability to public health and economic impacts of COVID-19. We performed two analyses to better understand similarities between communities in terms of the vulnerabilities represented by the metrics. We performed an unsupervised k-means clustering analysis to understand whether communities can be grouped together based on their levels of negative social and health indicators. Our goal for this analysis is to determine whether attributes of the constructed clusters reveal areas of opportunity for potential policy impacts and future disaster response efforts. We also analyzed similarities between communities across time using time-sensitive clustering analysis to discover whether historical community vulnerabilities were persistent in the years preceding the pandemic and to better understand the historical factors associated with disparate COVID-19 impacts. In particular, we highlight where communities should invest based on their historical health and socioeconomic patterns and related COVID impacts. Through extensive interpretation of our findings, we uncover how health policy can advance equity and improve community resilience.
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