Motivation -- Designing distributed training systems for crisis management (CM) requires an approach with the ability to address a great variety of needs and goals. Crisis responses involve multiple agents, each with different backgrounds, tasks, priorities, goals, responsibilities, organizations, equipment, and approaches. Identifying the different user training needs and translating these into user and functional requirement therefore poses great challenges.

Research approach -- In this paper we present experiences of how to enable the collaboration between multiple stakeholders and partners when creating and adapting ideas throughout the design phase. The techniques have been used in a European project aimed at developing an interactive Virtual Reality (VR) environment for training crisis management.

Findings/Design -- The focus of the paper is on the initial storyboard iterations and lo-fi prototypes, as this is a crucial stage for expressing ideas in a perceivable way without having to spend too much time and effort on creating detailed prototypes.

Take away message -- Experiences using low-cost commercial software for creating storyboards are presented, as these provided the means to create, share, present, adapt and circulate ideas, facilitating the fusing of ideas, shared understanding and distributed working.

Simulation of outbreaks of infectious disease is an important tool for understanding the dynamics of the outbreak process, the impact of disease and population properties, and the potential effect of interventions. However, the interpretation of the simulation results requires a clear understanding of the assumptions made in the underlying model. Typical simulation tasks, such as exploring the space of different scenarios for population and disease properties, require multiple runs with varying model parameters. For such complex tasks, the management of the assumptions made becomes a daunting and potentially error-prone undertaking. We report explicit assumptions management as an approach to capture, model, and document the assumptions for simulator runs. It was found possible to extend ontology-based simulation, which uses an ontological model to parameterize the simulator, to incorporate an assumptions model in the ontology. We conclude that explicit assumptions modeling should be part of any infectious disease simulation architecture from start.

Using time geographic theory for representation of population mixing, we set out to analyze the relative impact from precautionary behaviors on outbreaks of pandemic influenza in Europe and Asia. We extended an existing simulator environment with behavioral parameters from a population survey to model different behaviors. We found that precautionary behaviors even among a minority of the population can have a decisive effect on the probability of the outbreak to propagate. The results also display that assumptions strongly influences the outcome. Depending on the interpretation of how many "children" are kept from "school", R(0) changes from a range where outbreak progression is possible to a range where it is improbable in both European (R(0)=1.77/1.23) and Asian (R(0)=1.70/1.05) conditions. We conclude that unprompted distancing can have a decisive effect on pandemic propagation. An important response strategy can be to promote voluntary precautionary behavior shown to reduce disease transmission.

Computer simulations have emerged as important tools in the preparation for outbreaks of infectious disease. To support the collaborative planning and responding to the outbreaks, reports from simulations need to be transparent (accessible) with regard to the underlying parametric settings. This paper presents a design for generation of simulation reports where the background settings used in the simulation models are automatically visualized. We extended the ontology-management system Protégé to tag different settings into categories, and included these in report generation in parallel to the simulation outcomes. The report generator takes advantage of an XSLT specification and collects the documentation of the particular simulation settings into abridged XMLs including also summarized results. We conclude that even though inclusion of critical background settings in reports may not increase the accuracy of infectious disease simulations, it can prevent misunderstandings and less than optimal public health decisions.

Computer-based simulation of influenza outbreaks in local communities can help researchers, epidemiologists, and decision makers better understand the impact of the community structure on the reproduction rate of disease, and the relative benefits of different types of prevention and interventions. The goal of scenario modeling is to develop a description of scenario components, such us the disease, the community and interventions. An ontology-based representation of the scenario model together with a modeling tool, which is based on an extension to Protege assist scenario developers in formulating simulation specifications. This approach allows the exploration of new ideas by rapidly formulating and reconstructing scenarios from novel components.

Emerging web-based technologies enable information sharing within and among rescue agencies and organisations. This development can facilitate education, training and development through effective distribution of documentation, models and lessons learned from training exercises and rescue operations. We discuss central aspects of this enterprise such as the need for domain-specific data models, methodologies for detailed exercise documentation, and the design of presentation and visualisation tools. Based on this investigation, we present a framework that supports modelling, documentation and visualisation of rescue operations for web-based distribution. We briefly describe the implementation of the components of the framework. Finally, we discuss how to apply the methodology and framework to training of first responders and university-level education of emergency managers and officials.