Scenario-based:No preparednessPre-positioning of inventoryInvestment in disaster management capabilitiesSystems dynamics model; single disaster, single country, and single organization

Cross-sectional survey where the Disaster Preparedness Evaluation Tool (DPET) was distributed to Jordanian RNs who work in three randomly selected Ministry of Health hospitals and two university hospitals.

The designed questionnaire was pretested by involving the data collectors as part of their practical training

Informant selection, then InterviewsThe interviews consisted of open-ended questions and individually adapted follow-up questions covering the following themes:individual role and task during the hostage episodeexperience of individual actions during the hostage episodeexperience of own and others’ emotions during the hostage episodeexperience of organizational actions during the hostage episodeexperience of collaboration between the authorities and the organization duringthe hostage episodestress and demanding conditions during the hostage episode.

Workshop phase divided in 4 main steps:Briefing of objectivesScenario sessionsDebriefing (reflection)Evaluation

In this paper, we suggest a solution to this problem using earthquake disaster emergency response (EDER) knowledge.We present a computer-based modeling and representation method for EDER knowledge, which is a foundation for computer-aided knowledge use.

the coupled OODA framework is built to analyze the interaction between the emergency response units. In order to demonstrate the emergency response mechanism in theoretic way, the simulation theory of DEVS (Discrete Event System Specification) is adopted to build up the simulator model of the basic OODA process framework.With this scenario: “In the year 20XX, in the city Y in province X of southwest China, suddenly suffering to a Richter 8.0 degree earthquake disaster. This earthquake disaster has caused severe damage to the local city, with a large number of houses collapsed, casualties serious, road and transformation, electricity and other basic infrastructure paralyzed. State and government at all levels immediately launched the emergency response plans, organize and command the emergency response departments and their team units to carry out emergency rescue operations. Considering the disaster zone in the dangerous mountain area with less information, it is very difficult to make emergency response to rescue refugees in the disaster area.” (p. 535)Simulation, in STAGE (‘a scenario developing system’): (1) Edit the scenario database of the emergency environment(2) Edit the mission scripts(3) Edition of the emergency response plans(4) (4) Run the simulation (pp. 538-9)

Stage 1: the occupants evacuate the rooms and arrive at the exit of the floor. The  evacuation time is obtained by dividing the distance between the floor exit and the nearest room exit by the walking speed.Stage 2: the exit flow enters the stairwell and the stagnation occurs at the floor exit when the summed flow rates of all room exits in a single floor exceed the flow rate of that floor exit. The evacuation time is not measured until the occupants descended to the next floor.Stage 3: when the stair entry flow arrives at the lower floor and meets with the sources of exiting occupants, it is called ‘‘merge flow’’ (i.e. merge stage). This stage is assumed that the summed merge flow capacity of the n + 1th floor’s stair flow and the nth floor’s exit flow islarger than the maximum stair capacity. Stage 4: the simulation entered stage 4 when the number of the occupants of a single floor approaches the floor capacity. The maximum number of the occupants a floor can be obtained by two components: stair landing area (m2) multiplied by maximum crowd density of the stair landing (people/m2), and stairwell area (m2) multiplied by maximum crowd density of the stairwell (people/m2). The descending flow is consisted of both stair entry flow and the outflow of the floor. When the occupants fully load the stairwell, the stair entry flow between ground floor and second floor will keep the maximum stair flow.Stage 5: Formula 5 and 6 demonstrate that the higher the floor the smaller the flow rate of the floor when the value of the merge flow ratio is lower than a certain constant and the number of the stagnating occupants in the stairwell reaches the maximum. As a result, the occupants on the second floor take the lead in arriving at the ground floor and yet finish the escape behind others. On the contrary, when the value of the merge flow ratio exceeds a certain constant, the occupants of the roof floor take the lead in entering the stairwell.

We carry out our computational tests on an emergency evacuation network G=(V,E) with 20 nodes.Suppose an accident of ammonia spill happens in a chemical plant at node 2, the safety area is at node 20, and the starting point of the evacuees is at node 1.

Literature Review firstStage 1: Development of a 3-D data model; Stage 2: Integration with gaming technology; Stage 3: Testing in different scenarios to demonstrate potentiality.Three scenarios are presented in which the technology was applied: flooding, riots /protests, and terrorist events.The model was demonstrated at face-to-face sessions over a 12- month period with feedback given via workshops and one-to-one meetings, depending on the sector.j