Christoph Aubrecht, Klaus Steinnocher, & Hermann Huber. (2014). DynaPop – Population distribution dynamics as basis for social impact evaluation in crisis management. 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. 314–318). University Park, PA: The Pennsylvania State University.
Abstract: In this paper ongoing developments regarding the conceptual setup and subsequent implementation logic of a seamless spatio-temporal population dynamics model are presented. The DynaPop model aims at serving as basic input for social impact evaluation in crisis management. In addition to providing the starting point for assessing population exposure dynamics, i.e. the location and number of affected people at different stages during an event, knowledge of spatio-temporal population distribution patterns is also considered crucial for a set of other related aspects in disaster risk and crisis management including evacuation planning and casualty assessment. DynaPop is implemented via a gridded spatial disaggregation approach and integrates previous efforts on spatio-temporal modeling that account for various aspects of population dynamics such as human mobility and activity patterns that are particularly relevant in picturing the highly dynamic daytime situation.
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Arif Cagdas Aydinoglu, Elif Demir, & Serpil Ates. (2011). Designing a harmonized geo-data model for Disaster Management. 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: There are problems for managing and sharing geo-data effectively in Turkey. The key to resolving these problems is to develop a harmonized geo-data model. General features of this model are based on ISO/TC211 standards, INSPIRE Data Specifications, and expectations of Turkey National GIS actions. The generic conceptual model components were defined to harmonize geo-data and to produce data specifications. In order to enable semantic interoperability, application schemas were designed for data themes such as administrative unit, address, cadastre/building, hydrographic, topography, geodesy, transportation, and land cover/use. The model, as base and the domain geo-data model, is a starting point to create sector models in different thematic areas. Disaster Management Geo-data Model model was developed as an extension of base geo-data model to manage geo-data collaborate on disaster management activities. This model includes existing geo-data special for disaster management activities and dynamic data collecting during disaster.
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Catherine Lowry Campbell, Fadi Deek, Murray Turoff, & Bartel A. Van De Walle. (2004). Measuring consensus and conflict among stakeholders in emergency response information system requirements negotiations. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2004 – 1st International Workshop on Information Systems for Crisis Response and Management (pp. 121–126). Brussels: Royal Flemish Academy of Belgium.
Abstract: This paper introduces the experimental design we developed for the analysis of asynchronous negotiations among five different stakeholders as they work towards consensus on the functional system requirements that are needed for a common emergency response information system. We present three analytical preference models to measure the evolving consensus and conflict among the stakeholders as they modify their preferences during the negotiation. We illustrate the use of these techniques for obtaining a detailed understanding of the negotiation dynamics among the stakeholders. © Proceedings ISCRAM 2004.
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Jean-François Gagnon, Martin Rivest, François Couderc, & Sébastien Tremblay. (2012). Capturing the task model of experts in emergency response using SYnRGY. 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: The need for better team measurement in realistic environments has been recognized as one of the key challenges that characterize the field of team work studies (Salas, Cooke, & Rosen, 2008). This challenge is particularly hard to address in the context of emergency response, due to the inherent complexity and dynamism of the domain. Emergency response is part of the emergency management cycle, and refers to the mobilization of the adequate actors and resources to mitigate the impact of an incident on the public and on the environment (Abrahamsson, Hassel, and Tehler, 2010). Emergency response often requires the cooperation of multiple agencies such as police, medical, and fire services, consequently increasing the complexity of such operations. We report of how SYnRGY – a human-centered emergency response technological tool – is embedded with extensive measurement and simulation capabilities to allow tracing of experts' task models in a silent and reliable way. We describe how these capabilities; combined with an innovative modeling technique – dynamic cognitive task modeling – can be used to extract experts' representations of the task. We discuss the importance of such a model for training, improvement of emergency response procedures and development of emergency response tools. © 2012 ISCRAM.
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Sigmund Kluckner, Johannes Sautter, Matthias Max, Wolf Engelbach, & Tina Weber. (2012). Impacting factors on human reactionsto alerts. 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: Crisis response authorities have to deal with the unpredictability of their population's behavior. One of the complex challenges is to understand the people's reaction after an official alert in a crisis situation has been issued. This paper elaborates a knowledge base to describe impacting factors on human reactions in alerting situations. For this purpose, a literature review in the theme of human behavior after warnings was conducted and augmented with information gathered in a series of interviews in German-speaking countries. The outcome is phrased as factors that might impact the human reaction to a warning. This knowledge base shall support crisis management practitioners in the elaboration of alerting strategies as well as allow researchers to systematically structure human behavior aspects for the purpose of modeling and simulating alert effects. © 2012 ISCRAM.
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Felix Wex, Guido Schryen, & Dirk Neumann. (2012). Operational emergency response under informational uncertainty: A fuzzy optimization model for scheduling and allocating rescue units. 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: Coordination deficiencies have been identified after the March 2011 earthquakes in Japan in terms of scheduling and allocation of resources, with time pressure, resource shortages, and especially informational uncertainty being main challenges. We suggest a decision support model that accounts for these challenges by drawing on fuzzy set theory and fuzzy optimization. Based on requirements from practice and the findings of our literature review, the decision model considers the following premises: incidents and rescue units are spatially distributed, rescue units possess specific capabilities, processing is non-preemptive, and informational uncertainty through linguistic assessments is predominant when on-site units vaguely report about incidents and their attributes, or system reports are not exact. We also suggest a Monte Carlo-based heuristic solution procedure and conduct a computational evaluation of different scenarios. We benchmark the results of our heuristic with results yielded through applying a greedy approach. The results indicate that using our Monte Carlo simulation to solve the decision support model inspired by fuzzy set theory can substantially reduce the overall harm. © 2012 ISCRAM.
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Michael R. Bartolacci, Christoph Aubrecht, & Dilek Ozceylan Aubrecht. (2014). A portable base station optimization model for wireless infrastructure deployment in disaster planning and management. 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. 50–54). University Park, PA: The Pennsylvania State University.
Abstract: Disaster response requires communications among all affected parties including emergency responders and the affected populace. Wireless telecommunications, if available through a fixed structure cellular mobile network, satellites, portable station mobile networks and ad hoc mobile networks, can provide this means for such communications. While the deployment of temporary mobile networks and other wireless equipment following disasters has been successfully accomplished by governmental agencies and mobile network providers following previous disasters, there appears to be little optimization effort involved with respect to maximizing key performance measures of the deployment or minimizing overall 'cost' (including time aspects) to deploy. This work-in-progress does not focus on the question of what entity will operate the portable base during a disaster, but on optimizing the placement of mobile base stations or similar network nodes for planning and real time management purposes. An optimization model is proposed for the staging and placement of portable base stations to support disaster relief efforts.
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Louise K. Comfort, Milos Hauskrecht, & Jeen-Shang Lin. (2008). Dynamic networks: Modeling change in environments exposed to risk. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 576–585). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Modeling the interaction between interdependent systems in dynamic environments represents a promising approach to enabling communities to assess and manage the recurring risk to which they are exposed. We frame the problem as a complex, adaptive system, examining the interaction between transportation and emergency response as a socio-technical system. Using methods of spatial and statistical analysis, we overlaid the engineered transportation system on the organizational emergency response system to identify the thresholds of fragility in each. We present a research design and preliminary results from a small-scale study conducted in the Pittsburgh Metropolitan Region that examined the interaction between the transportation and emergency response systems. These results informed the design of a Situational Assessment Module for emergency managers, currently under development at the University of Pittsburgh.
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Kelli de Faria Cordeiro, Maria Luiza M Campos, & Marcos R. S. Borges. (2014). Adaptive integration of information supporting decision making: A case on humanitarian logistic. 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. 225–229). University Park, PA: The Pennsylvania State University.
Abstract: There is an urgent demand for information systems to gather heterogeneous information about needs, donations and warehouse stocks to provide an integrated view for decision making in humanitarian logistics. The dynamic flow of information, due to the unpredicted events, requires adaptive features. The traditional relational data model is not suitable due to its schema rigidity. As an alternative, Graph Data models complemented by semantic representations, like Linked Open Data on the Web, can be used. Based on both, this research proposes an approach for the adaptive integration of information and an associated architecture. An application example is discussed in a real scenario where relief goods are managed through a dynamic and multi-perspective view.
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Dragos Datcu, & Leon J.M. Rothkrantz. (2007). The use of active appearance model for facial expression recognition in crisis environments. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 515–524). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In the past a crisis event was notified by local witnesses that use to make phone calls to the special services. They reported by speech according to their observation on the crisis site. The recent improvements in the area of human computer interfaces make possible the development of context-aware systems for crisis management that support people in escaping a crisis even before external help is available at site. Apart from collecting the people's reports on the crisis, these systems are assumed to automatically extract useful clues during typical human computer interaction sessions. The novelty of the current research resides in the attempt to involve computer vision techniques for performing an automatic evaluation of facial expressions during human-computer interaction sessions with a crisis management system. The current paper details an approach for an automatic facial expression recognition module that may be included in crisis-oriented applications. The algorithm uses Active Appearance Model for facial shape extraction and SVM classifier for Action Units detection and facial expression recognition.
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Philip Degener, Henning Gösling, & Jutta Geldermann. (2013). Decision support for the location planning in disaster areas using multi-criteria methods. 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. 278–283). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: In this paper, a multi-criteria facility location model is represented. The model is meant to support relief organisations to determine the best warehouse location to stock emergency relief supplies in the pre-disaster phase of a natural disaster. As a result of the prepositioning of the goods the relief organisations are able to respond immediately to an occurring disaster. In consideration of a multiplicity of quantitative and qualitative objectives a criteria hierarchy is developed which can be adapted to any specific disaster area by omitting irrelevant goals. Afterwards the multi-criteria methods PROMETHEE I+II as well as different sensitivity analysis are described and the model is applied on a local level in a flood-prone area in Bangladesh. Small organisations with restrictive financial and personnel resources can especially benefit from the clear structure of the model and the user friendliness and high transparency of the PROMETHE I+II methods.
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Naci Dilekli, & Tarek Rashed. (2007). Towards a GIS data model for improving the emergency response in the Least Developing Countries: Challenges and opportunities. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 57–62). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Over the past few years, several standardized GIS data models have been developed to document “best practices” database designs for various application domains including the domain of emergency management. The majority of such models, however, have been developed in the context of developed countries as in the case of the Homeland Security geodatabase data model by ESRI®. These data models fail to be successful when transferred and used in the context of Least Developing Countries (LDCs) due to significant contextual differences in the domains of information systems and emergency practices. Therefore, developing GIS data models that are specifically designed for emergency response activities in LDCs are needed to improve existing emergency response practices in these countries. This paper reviews the state of development in GIS data models and the potential benefits and applications of building models that are specifically designed to support emergency response activities in LDCs. We first discusses why it is important to differentiate emergency response activities in LDCs from other contexts. We then present some theoretical considerations in developing GIS data models that can overcome contextual difficulties in LDCs in general and in the domain of information systenms. We finally attempt to provide key guidelines that may help designing a GIS Data Model, while is specifically referenced to the LDCs context.
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Gary Eifried. (2005). A model describing a response to a terrorism incident. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 125–127). Brussels: Royal Flemish Academy of Belgium.
Abstract: Understanding how the response to an incident of terrorism involving a Weapons of Mass Destruction (WMD) transpires is essential to understanding the necessary flow of information within that response. A model describing incident response functions overlaid on a realistic timeline is presented.
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Mauro Falasca, Christopher W. Zobel, & Gary M. Fetter. (2009). An optimization model for humanitarian relief volunteer management. 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: One of the challenges of humanitarian organizations is that there exist limited decision technologies that fit their needs. It has also been pointed out that those organizations experience coordination difficulties with volunteers willing to help. The purpose of this paper is to help address those challenges through the development of a decision model to assist in the management of volunteers. While employee workforce management models have been the topic of extensive research over the past decades, no work has focused on the problem of managing humanitarian relief volunteers. In this paper, we discuss a series of principles from the field of volunteer management and develop a multi criteria optimization model to assist in the assignment of volunteers to tasks. We present an illustrative example and analyze a solution methodology where the decision maker exercises his/her preferences by trading-off conflicting objectives. Conclusions, limitations, and directions for future research are also discussed.
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Jose Vargas Florez, Anthony Charles, Matthieu Lauras, & Lionel Dupont. (2014). Designing realistic scenarios for disaster management quantitative models. 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. 180–189). University Park, PA: The Pennsylvania State University.
Abstract: Disaster Management has received a lot of attention over the last twenty years, and can now be considered a full research area. But a gap exists between research work proposals and their applications on the field. This is particularly true regarding quantitative approaches. One of the main issues is that the scenarios used to design and validate the proposals are often not accurate and/or too simple compared to the complexity of real situations. Designing realistic scenarios is of prime importance to be able to propose relevant quantitative models which could be implemented by practitioners. This paper tackles this problem by proposing a structured methodology which aims at defining realistic disaster scenarios. The case of earthquakes management in Peru is used to illustrate the consistency of our proposal.
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Franclin Foping, & Ioannis M. Dokas. (2013). A saas-based early warning information fusion system for critical infrastructure safety. 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. 156–165). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Maintaining the critical infrastructures, such as Drinking Water Treatment Plants (DWTP), transportation, power generation and communications systems, in a safe state is a complex problem. The effective collaboration, as well as the collection aggregation and dissemination of early warning information among the stakeholders of the Safety Management System (SMS) responsible for the safety of these critical infrastructures are some of the challenges that need to be addressed. This paper argues that the Software as a Service (SaaS) deployment model can offer new ways of enhancing the fusion of early warning information during the operation phase of critical infrastructures. It presents the requirements, the architecture and a number of features of a working prototype SaaS-based early warning information fusion system for DWTP safety issues in the Republic of Ireland. It is the first time that a SaaSbased working prototype system is reported of providing early warning information fusion services in the literature.
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Arthur H. Hendela, Murray Turoff, & Starr Roxanne Hiltz. (2010). Cross impact security analysis using the HACKING Game. 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: Security of network assets is a high priority with little traditional return on investment. Increasingly, cyber attacks are being used by both terrorist and unfriendly government organizations. The HACKING Game, a Cross Impact Analysis planning tool, can be used to plan security resource allocation in computer networks. Cross Impact Analysis provides a mathematical basis to determine the interrelationships of one event with a set of other events. Output from the HACKING Game's Cross Impact Analysis model can be used to help justify security expenditures, with an added benefit of being a training tool for employees learning to protect networks. This paper presents details of the Hacking Game's design and its capabilities. Cross impact modeling can be used to develop games for any situation characterized by a set of offense and defense events to produce an individual or collaborative model for such things as natural and man-made disasters.
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Cindy Hui, Mark Goldberg, Malik Magdon-Ismail, & William A. Wallace. (2008). Micro-simulation of diffusion of warnings. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 424–430). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper presents a unique view of modeling the diffusion of warnings in social networks where the network structure may change over time. Since the characteristics and actions of people in a community have significant influence on the flow of information through a network, we present an axiomatic framework for modeling the diffusion process through the concept of trust. This ongoing work provides a micro level view of the behavior of individuals and groups in a community. Preliminary experiments were made to explore how model parameters such as trust and the social network structure affect warning message belief and evacuation.
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Soumia Ichoua. (2010). Humanitarian logistics network design for an effective disaster response. 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: In this paper we address the problem of pre-positioning emergency supplies prior to a disaster onset. The goal is to ensure a fast and effective response when the disaster strikes. Pre-positioning of emergency supplies is a strategic decision aimed at determining the number and location of local distribution centers as well as their inventory levels for emergency supplies. These decisions must be made in a highly disruption-prone environment where a timely response is vital and resources are scarce. We present and discuss a scenario-based model that integrates location, inventory and routing decisions.
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Syed Imran, Franclin Foping, Ioannis M. Dokas, & John Feehan. (2010). Towards domain specific modeling approach in early warning system. 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: It is of practical significance and great value to design and develop a novel Early Warning System (EWS), which will be used by the personnel of institutions involved in the drinking water delivery governance model of Ireland. In order to help the users of our EWS in representing and codifying their knowledge on the complex coincidences that may drive Water Treatment Plants (WTP) to failures or to hazardous states we propose in this paper a novel approach of using Domain Specific Modeling (DSM) in the domain of EWS for Water Treatment Plants. The novelty of our DSM approach also lies in providing a standalone open source software application rendering profiling of the water utilities, early warning signals, monitoring mechanisms of signals along with capability of assessing the “tendency” of a WTP towards failure, given a set of observed early warning signals.
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Gabriel Jakobson, Nandan Parameswaran, John Buford, Lundy Lewis, & Pradeep Ray. (2006). Situation-Aware multi-Agent system for disaster relief operations management. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 313–324). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Natural and human-made disasters create unparalleled challenges to Disaster Situation Management (DSM). One of the major weaknesses of the current DSM solutions is the lack of comprehensive understanding of the overall disaster operational situation, and very often making decisions based on a single event. Such weakness is clearly exhibited by the solutions based on the widely used Belief-Desire-Intention (BDI) models for building the Muiti-Agent Systems (MAS). In this work we present the adaptation of the AESOP situation management architecture to address the requirements of disaster relief operations. In particular, we extend the existing BDI model with the capability of situation awareness. We describe how the key functions of event collection, situation identification, and situation assessment are implemented in MAS architecture suitable to the characteristics of large-scale disaster recovery. We present the details of a BDI agent in this architecture including a skeleton ontology, and the distributed service architecture of the AESOP platform.
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Johan Jenvald, Michael Morin, Toomas Timpka, & Henrik Eriksson. (2007). Simulation as decision support in pandemic influenza preparedness and response. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 295–304). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Outbreak of a destructive pandemic influenza threatens to disrupt societies worldwide. International agencies and national governments have prepared plans and recommendations, but it is often decision-makers with the local authorities that are responsible for implementing the response. A central issue for these decision makers is what interventions are available and effective for the specific local community. The paper presents a simulator architecture and its relation to a workflow for decision support in influenza preparedness and response. The simulator can simulate pandemic scenarios, using localized community models, in the presence of various interventions to support an evaluation of potential response strategies. The architecture includes a customized modeling tool, separated from the simulation engine, which facilitates swift scenario modification and recalculation. This flexibility is essential both to explore alternative solutions in planning, and to adapt to changing requirements, information, and resources in outbreak response. An example simulation, based on actual population data from a reference city, illustrates the approach.
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Michael Klafft, & Ulrich Meissen. (2011). Assessing the economic value of early warning systems. 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: As of today, investments into early warning systems are, to a large extent, politically motivated and “disaster-driven”. This means that investments tend to increase significantly if a disaster strikes, but are often quickly reduced in the following disaster-free years. Such investment patterns make the continuous operation, maintenance and development of the early warning infrastructure a challenging task and may lead to sub-optimal investment decisions. The paper presented here proposes an economic assessment model for the tangible economic impact of early warning systems. The model places a focus on the false alert problematic and goes beyond previous approaches by incorporating some socio-cultural factors (qualitatively estimated as of now). By doing so, it supports policymakers (but also private investors) in their investment decisions related to early warning applications.
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Erkki Kurkinen. (2013). The effect of age on technology acceptance among field police officers. 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. 468–477). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: This paper studies the differences on technology acceptance between two age groups among uniform police forces. The goal was to seek more understanding on the effects of age on technology adaption in the context of mandatory technology use. Data was collected from police officers in field operations. User intentions were measured after subjects had seen a presentation of a pre-prototype of a mobile information system on the video. The results of this study suggest that there is no difference between the old and young age groups. Similarly, the results suggest that the effect of age is similar between the age groups on the effects of the factors in the research model. This suggests that the old police officers are similar to young police officers regarding the acceptance of new technology for their use. The most prominent result was that regression of behavioral intention on perceived usefulness was not statistically important.
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Daniel E. Lane, Tracey L. O'Sullivan, Craig E. Kuziemsky, Fikret Berkes, & Anthony Charles. (2013). A structured equation model of collaborative community 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. 906–911). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: This paper analyses the collaborative dynamic of community in response to urgent situations. Community emergencies arising from natural or man-induced threats are considered as exogenous events that stimulate community resources to be unified around the response, action, and recovery activities related to the emergency. A structured equation model is derived to depict the actions of the community system. The system is described in terms of its resources including the propensity to trigger community action and collaboration among diverse groups. The community is profiled with respect to its ability to respond. The system defines the trigger mechanisms that are considered to be the drivers of collaborative action. A simulation model is presented to enact the system emergencies, community profiles, and collaborative response. The results develop an improved understanding of conditions that engage community collaborative actions as illustrated by examples from community research in the EnRiCH and the C-Change community research projects.
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