Interorganizational Information Exchange and Efficiency: Organizational Performance in Emergency Environments

Achieving efficiency in coordinated action in rapidly changing environments has challenged both researchers and practitioners. Emergency events require both rapid response and effective coordination among participating organizations. We created a simulated operations environment using agent-based modeling to test the efficiency of six different organizational designs that varied the exercise of authority, degree of uncertainty, and access to information. Efficiency is measured in terms of response time, identifying time as the most valuable resource in emergency response. Our findings show that, contrary to dominant organizational patterns of hierarchical authority that limit communication among members via strict reporting rules, any communication among members increases the efficiency of organizations operating in uncertain environments. We further found that a smaller component of highly interconnected, self adapting agents emerges over time to support the organization\'s adaptation in changing conditions. In uncertain environments, heterogeneous agents prove more efficient in sharing information that guides coordination than homogeneous agents.Agent-Based Simulation, Emergency Management, Network Evolution, Performance

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

AGENT-BASED DISCRETE EVENT SIMULATION MODELING AND EVOLUTIONARY REAL-TIME DECISION MAKING FOR LARGE-SCALE SYSTEMS

Computer simulations are routines programmed to imitate detailed system operations. They are utilized to evaluate system performance and/or predict future behaviors under certain settings. In complex cases where system operations cannot be formulated explicitly by analytical models, simulations become the dominant mode of analysis as they can model systems without relying on unrealistic or limiting assumptions and represent actual systems more faithfully. Two main streams exist in current simulation research and practice: discrete event simulation and agent-based simulation. This dissertation facilitates the marriage of the two. By integrating the agent-based modeling concepts into the discrete event simulation framework, we can take advantage of and eliminate the disadvantages of both methods.Although simulation can represent complex systems realistically, it is a descriptive tool without the capability of making decisions. However, it can be complemented by incorporating optimization routines. The most challenging problem is that large-scale simulation models normally take a considerable amount of computer time to execute so that the number of solution evaluations needed by most optimization algorithms is not feasible within a reasonable time frame. This research develops a highly efficient evolutionary simulation-based decision making procedure which can be applied in real-time management situations. It basically divides the entire process time horizon into a series of small time intervals and operates simulation optimization algorithms for those small intervals separately and iteratively. This method improves computational tractability by decomposing long simulation runs; it also enhances system dynamics by incorporating changing information/data as the event unfolds. With respect to simulation optimization, this procedure solves efficient analytical models which can approximate the simulation and guide the search procedure to approach near optimality quickly.The methods of agent-based discrete event simulation modeling and evolutionary simulation-based decision making developed in this dissertation are implemented to solve a set of disaster response planning problems. This research also investigates a unique approach to validating low-probability, high-impact simulation systems based on a concrete example problem. The experimental results demonstrate the feasibility and effectiveness of our model compared to other existing systems

User Interface Design And Forensic Analysis For DIORAMA, Decision Support System For Mass Casualty Incidents

In this thesis we introduces the user interface design and forensic analysis tool for DIORAMA system. With an Android device, DIORAMA provides emergency personnel the ability to collect information in real time, track the resources and manage them. It allows the responders and commanders to mange multiple incidents simultaneously. This thesis also describes the implementations of commander app and responder app, as well as two different communication strategies used in DIORAMA. Several trials and simulated mass casualty incidents were conducted to test the functionalities and performance of DIORAMA system. All responders that participated in all trials were very satisfied with it. As a result, DIORAMA system significantly reduced the evacuation time by up to 43% when compared to paper based triage systems

A Framework for Developing and Integrating Effective Routing Strategies Within the Emergency Management Decision-Support System, Research Report 11-12

This report describes the modeling, calibration, and validation of a VISSIM traffic-flow simulation of the San José, California, downtown network and examines various evacuation scenarios and first-responder routings to assess strategies that would be effective in the event of a no-notice disaster. The modeled network required a large amount of data on network geometry, signal timings, signal coordination schemes, and turning-movement volumes. Turning-movement counts at intersections were used to validate the network with the empirical formula-based measure known as the GEH statistic. Once the base network was tested and validated, various scenarios were modeled to estimate evacuation and emergency vehicle arrival times. Based on these scenarios, a variety of emergency plans for San José’s downtown traffic circulation were tested and validated. The model could be used to evaluate scenarios in other communities by entering their community-specific data

Operations research in disaster preparedness and response: The public health perspective

Operations research is the scientific study of operations for the purpose of better decision making and management. Disasters are defined as events whose consequences exceed the capability of civil protection and public health systems to provide necessary responses in a timely manner. Public health science is applied to the design of operations of public health services and therefore operations research principles and techniques can be applied in public health. Disaster response quantitative methods such as operations research addressing public health are important tools for planning effective responses to disasters. Models address a variety of decision makers (e.g. first responders, public health officials), geographic settings, strategies modelled (e.g. dispensing, supply chain network design, prevention or mitigation of disaster effects, treatment) and outcomes evaluated (costs, morbidity, mortality, logistical outcomes) and use a range of modelling methodologies. Regarding natural disasters the modelling approaches have been rather limited. Response logistics related to public health impact of disasters have been modelled more intensively since decisions about procurement, transport, stockpiling, and maintenance of needed supplies but also mass vaccination, prophylaxis, and treatment are essential in the emergency management. Major issues at all levels of disaster response decision making, including long-range strategic planning, tactical response planning, and real-time operational support are still unresolved and operations research can provide useful techniques for decision management.-JRC.G.2-Global security and crisis managemen

Evaluation of medical response in disaster preparedness : with special reference to full-scale exercises

Background: Disaster exercises and simulations serves as teaching and training tool for improving medical response in disaster preparedness. Rapid and effective medical response in major incidents is known as a “key phase” to optimise resources, and this requires that management systems have an “all hazards” approach. Decision-making at all levels of management is based on available information and involves allocation of medical resources and triage decisions. Aim: The overall aim of this thesis was to increase our knowledge of the impact of quantitative evaluation of medical response on disaster preparedness. The specific aims were: to increase the ability to learn from full-scale exercises by applying quality indicators at two levels of command and control (I, II); to identify key indicators essential for initial disaster medical response registration (III); to explore ambulance staff attitudes towards practising triage tagging (IV); and to increase our knowledge of the applicability of a technical support system and its potential to provide real-time, overall situation awareness available to those overseeing the medical management of the operation. Methods: Study I, II and V were observational studies based on data collections from full-scale exercises. Templates with measurable performance indicators for evaluation of command and control were used in Study I and II and the same performance indicators combined with outcome indicators was also included in Study II. A consensus method, the Delphi technique, with 30 experts was used in Study III. Study IV used mixed methods, a pre-and post web survey answered by ambulance nurses and physicians (n=57 respectively 57) before and after a time limited strategy with triage tags and three focus groups interviews comprising 21 ambulance nurses and emergency medical technicians. Study V used major two incidents simulations to test the applicability of Radio Frequency Identification (RFID tags) technology and compare it with traditionally paper-based triage tags (n= 20 respectively 20). The quantitative data were analysed using descriptive statistics, and content analysis was used for the qualitative data. Results: The evaluation model exposed several problems occurring in the initial decision-making process that were repeatedly observed (I, II). These results in study II also demonstrated to have a major impact on patient outcome.Out of 17 severely injured patients five respectively seven were at risk for preventable death. A total of 97 statements were generated, of these 77 statements reached experts consensus, and 20 did not (III). Ambulance staffs believe in the usefulness of standardised triage methods, but the sparse application of triage tags at the scene indicates that the tags are not used frequently. Infrequent use in daily practice prevents participants from feeling confident with the triage tool (IV).The Radio Frequency Identification system improved situational awareness in disaster management. Triage information was available at least one hour earlier compared to a paper-based triage system (V). Conclusions: The presented evaluation model can be used in an objective, systematic and reproducible way to evaluate complex medical responses, which is a prerequisite for quality assurance, identification of problems, and the development of disaster preparedness

Understanding the Humanitarian Consequences and Risks of Nuclear Weapons : New findings from recent scholarship

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Smart Shelter: A Sustainable Power System Design Using Micro-Energy Harvesting Techniques

This paper is about the novel design of a Smart Shelter, which is a shelter that is powered using power harvesting techniques