Data collection plan

Förplanerat manus för en övning, samt även den stimulation som används för att uppnå övningens prestationsmål.

DRIVER+ kommentar 1: I samband med scenarier med DRIVER+ används begreppet för försök och inte för övningar.

read more

1: No decision support (baseline). Representing a process of the vehicular evacuation without any support. Each agent move to the closest exit defined by the geographical distance. Agent without support uses the route with minimal length and do not take into account information on congestions. Scenario 2: Ordinary navigators. Simple navigation system has a statistical data on a current roads load. Agents with such system installed find optimal routes by minimization of estimated travel time in congested road network. Scenario 3: Learning navigators. the more advanced navigation system is used. This kind of system allows agents to commit their knowledge to the shared storage. When an agent discovers the flooded road all agents using the system discover this too automatically, and they take this new knowledge into account in their further routing. The knowledge sharing capability could be represented in contemporary navigation systems as a capability to declare information about accidents, road closures. Scenario 4: Navigators with full information about flooding. The full information on flood dynamics is accessible for agents who use the navigation system. It means that all the agents discover information on flooded areas at the moment they became flooded. This case can be projected to reality as a system which collects actual data from the sensors.

The discipline of simulation modeling includes giving attention to details of system composition and entity relationships (mathematical and logical). The steps for building a simulator may be outlined as follows:1. Formulate the problem with the following leading questions.a. What operations and functions produce the systems output?b. What procedural elements exist in the systems operation?c. What interactions occur between functional units of the system?d. What information is available to characterize the operations, functions, and procedures of the system?2. Define the project goal, critical performance measures, modeling objectives, and system to be modeled (e.g., scope and level of detail)3. Specify the model.4. Construct the model.a. Define experimental controls (input and context variables)b. Construct the internal interactions (design variablesand alternatives)5. Run, verify and validate the simulation model.6. Use the simulator to produce and analyze solution alternatives.

Simulation

In the qualitative study, in-depth semistructured interviews were conducted with top-level EH (n = 8) and EPR (n = 6) administrators and managers. Participants were selected by nonprobability purposive sampling methods.The key informant interviews were conducted by trained interviewers at EH or EPR administrative offices in June to August 2010. Prior to being interviewed, participants were asked to read and sign an informed consent approved by the Loma Linda University institutional review board. Each interviewer was accompanied by one or two note takers and the interview was audiotaped.

Multiresource dynamic allocation model for emergency rescues is a multigoal optimization model with two goals, maximizing rescue effectiveness and minimizing allocating cost.Maximum of rescue effectiveness. The purpose of rescue resource allocation is to deal with emergencies, so the maximum of rescue effectiveness is the first goal and the maximum of the importance of all the resources could reflect this goal. On the other hand, according to the dynamic change of the threat of the disasters, the rescue period could be divided into several time intervals, and the model seeks the maximum of rescue resource effectiveness during the whole projection period. The so-called “maximum of rescue resource effectiveness” here concerns not only the effectiveness of the resource allocation, but also the maximum of the whole rescue project with the consideration of the whole rescue demands.

The first activity of the 3-hr exercise was the administration of a pretest of knowledge and an attitude scale. Then, the first author (RS) presented a brief lecture with slides emphasizing main points from the prereadings. Afterward, the students divided into their assigned role-playing groups and went to separate work areas. Each work area had a computer, a CD of the prereadings and other reference materials, and an Internet connection. Each group selected a speaker. Then the faculty facilitators gave out three to five injects describing how the

Förplanerat manus för en övning, samt även den stimulation som används för att uppnå övningens prestationsmål.

DRIVER+ kommentar 1: I samband med scenarier med DRIVER+ används begreppet för försök och inte för övningar.

read more

put demands on their role and questions for discussion. These injects were different from the pr-estudy questions. Usually, injects are given out sequentially by exercise facilitators as the group progresses through problem solving. In this exercise all of the injects for each 45-min session were given out at the beginning of each session because the time constraints were tight.For the second role-playing session, the groups reassembled in combinations. For example, the groups of primary care physicians, the school district, and the county health department were combined. Again, they received three to five injects to guide discussion of how their group roles interrelate in a health emergency, either for mutual information needs or for the potential to pool resources to address common problems. An inject for the team described here was, “How can you work together to manage large numbers of people who want medical screening and reassurance without flooding emergency rooms?” Faculty guidance suggested guiding the group toward disseminating information to families through schools and possibly setting up screening sites at schools. This session also lasted 45 min.Following the small-group sessions, all the students and faculty members reconvened for debriefing. Each role group and each combination of groups presented a summary of their discussions. These sessions addressed Objectives 2 and 3, practicing and understanding the various stakeholder roles.

Case 1: Remote work based on video transmission via satellite enabled experts called to Situation Centre to cooperate with rescue personnel on the dam and to remotely evaluate a

Okända faktorers inverkan på objekt.

read more

of total collapse of the damage. The situation was presented to local authorities and decision about evacuation was taken.Case 2:  The field exercise has been conducted with civilians being trapped by flood and requesting evacuation. Space technologies have been merged with advanced ter- restrial solutions to provide the most efficient information environment supporting operation. Satellite navigation has been used to locate calls and to coordinate rescue activities. This has been enhanced by optical images from unmanned aerial vehicle and telemedical systems using GSM network.Case 3: the train transporting hazardous gas crashes with passenger train between stations, in the forest. Satellite navigation system is used to facilitate operations, including exchange of information between different services involved. EO archived images are used to provide information about the neighbourhood of the crash location. Tracking of first units arriving on the scene provides access information for all other forces. EO images present context information about the area.

Various training methods were used: case studies, workshops, tutorials, seminars, group discussions, role playing, drilling, fieldwork

Data were collected by a series of semi-structured interviews conducted by the author (AN Nasrabadi). Permission for taperecording the interviews were obtained from each participant. The interviews lasted from 45 to 90 min. An interview guide was used and this helped to focus the interview. The interview guide was constructed according to the fundamental questions of interest for the study. At the end of each interview session, the researcher asked the participants to talk about anything they considered important in the earthquake situation. This could involve their personal experiences of the disaster or any additional comments about their experiences as a disaster nurse in Bam.

The core of the Emergo Train System1 (ETS) consists of a patient database with specific casualties and typical in-hospital patients that, together with specific staff and other types of resources involved in  emergency/disaster management, can be used to translate local prerequisites into the system. All ETS victims belong to a specific standardized injury category and each victim has a defined medical need within a certain period. The time taken for each measure is calculated according to a defined standard. If a patient’s specific need (e.g. airway intervention, pleural drainage, surgery or intensive care unit (ICU) assessment) is not met within the stipulated period, the patient risks an unfavourable outcome. This

Okända faktorers inverkan på objekt.

read more

is expressed by the system as a risk for preventable death or a risk for preventable complications. Thus, at the end of a simulation exercise, it is possible to calculate and summarize patient outcome and relate the result to the treatment given and to other decisions made. The different injury categories have been developed in a consensus process with national experts within the fields of traumatology and disaster medicine and in accordance with evidence-based best practice of trauma care. The specific burn categories have been developed in consensus and collaboration with national burn experts in Australia and Sweden