Abstract: Federal, State, and local decision makers and public health officials must prepare and exercise complex plans to contend with a variety of possible mass casualty events, such as pandemic influenza. Through the provision of quick look tools (QLTs) focused on mass casualty events, such planning can be done with higher accuracy and more realism through the combination of interactive simulation and visualization in these tools. If an event happens, the QLTs can then be employed to rapidly assess and execute alternative mitigation strategies, and thereby minimize casualties. This can be achieved by conducting numerous “what-if” assessments prior to any event in order to assess potential health impacts (e.g., number of sick individuals), required community resources (e.g., vaccinations and hospital beds), and optimal mitigative decision strategies (e.g., school closures) during the course of a pandemic. In this presentation, we overview and demonstrate a pandemic influenza QLT, discuss some of the modeling methods and construct and visual analytic components and interface, and outline additional development concepts. These include the incorporation of a user selectable infectious disease palette, simultaneous visualization of decision alternatives, additional resource elements associated with emergency response (e.g., first responders and medical professionals), and provisions for other potential disaster events.

Abstract: Due to the increasing danger of terrorist attacks, it is necessary to determine the preventive effects of security measures installed in e.g. public transportation systems. Since, there is no common practice to determine the preventive effects; we developed two different methodologies to analyse those effects, both are suitable for the assessment of security measures. The first method is a semi-quantitative method based on expert-estimations combined with a modelled process of an attack.The second method models the scenarios using a multi-agent-based simulation framework. Simulating a large number of runs, it is possible to derive values for indicators of interest on statistical basis. We show the suitability of both methods by applying them on a practical example of a public transportation system. In this paper we introduce both methodologies, show an exemplary application and present the strengths and weaknesses and how they can be linked to get an increased benefit.

Abstract: Intentional threats including terrorism have become a worldwide catastrophe risk since recent years. To protect the cities from being attacked, the macro-level study of decision analysis should be given more considerations. In this paper, we proposed a model for describing the strategic game between attackers and defenders based on the methodology of matrix game. This model can be employed to determine which target will be selected by attackers and which attacking strategy and defending strategy will be chosen by attackers and defenders respectively. Furthermore, the defenders of the city can use this model to set priorities among their defending strategies. The importance of this work is to establish a reasonable framework for modeling the attacking and defending strategies rather than assessing the real risk of urban targets, so the model is illustrated by using fictitious numbers. The model proposed in this paper can provide scientific basis for macroscopic decision making in responding to intentional threats. © 2012 ISCRAM.

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.

Abstract: In this contribution we evaluate the effectiveness of mobile services for passenger egress of a train station during a large public event using an agent-based simulation approach. For this simulation we built a virtual replica of the Cologne central train station and collected empirical data on passenger numbers and their movements during a large public event. We simulate several different scenarios and compare the results using key performance indicators, such as time for egress. Our results show that dedicated cell broadcast messages under the described circumstances can be used to decrease evacuation time significantly and that the simulation can be used to quickly investigate the relevant key performance indicators needed to asses and evaluate the effectiveness of different notification and evacuation strategies.

Abstract: Results from disaster research suggest that methods for coordination between individual emergency responders and organizations should recognize the independence and autonomy of these actors. These actor features are key factors in effective adaptation and improvisation of response to emergency situations which are inherently uncertain. Autonomy and adaptability are also well-known aspects of a multi-agent system (MAS). In this paper we present two MAS strategies that can effectively handle aircraft deicing incidents. These MAS strategies help improve to prevent and reduce e.g. airplane delays at deicing stations due to changing weather conditions or incidents at the station, where aircraft agents adopting pre-made plans that would act on behalf of aircraft pilots or companies, would only create havoc. Herein each agent using its own decision mechanism deliberates about the uncertainty in the problem domain and the preferences (or priorities) of the agents. Furthermore, taking both these issues into account each proposed MAS strategy outperforms a naive first-come, first-served coordination strategy. The simulation results help pilots and companies taking decisions with respect to the scheduling of the aircraft for deicing when unexpected incidents occur: they provide insights in the impacts and means for robust selection of incident-specific strategies on e.g. deicing station delays of (individual) aircraft.

Abstract: Underground space like subway stations is prone to be flooded which can lead to severe and unpredictable damage and even threaten human lives. In this paper, four groups of contrastive simulation of urban waterlogging at two subway stations' entry-exit platforms in heavy rainstorm are conducted, and emergency response strategies are suggested. A waterlogging simulation method named UPFLOOD based on shallow water equations is proposed considering complex topography. It has been found that the waterlogging at subway station's entry-exit platforms is easily influenced by several factors and the site selection of the subway stations is very important. A disaster process construction method based on PN model is proposed and it has been found that the response strategies including plugging, drainage and evacuation are important for disaster mitigation. This study helps decision makers to response quickly to meet the emergency of the waterlogging disaster at subway stations caused by heavy rainstorm.