Modeling Evacuate versus Shelter-in-Place Decisions in Wildfires

Cova, Thomas J.; Dennison, Philip E.; Drews, Frank A.

doi:10.3390/su3101662

Cited by 62 publications

(22 citation statements)

References 48 publications

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“…1 -Evacuation Phases (Source: adapted from Lindell, 1995) In the event of bushfire, residents' responses can be categorised into three groups; those who leave early; those who stay at their properties (Shelter in Refuge) and those who decide to shelter in the refuge. Cova et al (2011) referred these decision-choices as the 'protective actions' (Figure 2). Bushfire evacuation can be mandatory, recommended, or voluntary.…”

Section: Literature Reviewmentioning

confidence: 99%

“…France a stay or go choice is given to residents except in the case of a severe bushfire (Arnol 2007 Cova et al, 2011) In Australia, the "Stay or Go" policy transfer the responsibility and decision of staying and protecting the property or leave early to individuals. The current Australian 'Stay or Go' policy, which is a replacement of previous plan 'prepare', stay and defend, or leave early', has strategically design to reduce risk to government agencies by making people responsible for their actions (Paveglio et al 2008).…”

Section: Multi-objective Decision Analyticsmentioning

confidence: 99%

“…Thus, the decision to stay or leave early in a bushfire is a critical to community safety. People those expose to fire risk may decide to leave early, or take shelter-in-home or shelter-in-refuge (Cova et al 2011). Obviously, early evacuation is the safest option to protect life.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Objective Decision Analytics for Short-Notice Bushfire Evacuation: An Australian Case Study

Shahparvari

Chhetri

Abareshi

et al. 2015

AJIS

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Late evacuation in a bushfire is a crucial stage of emergency response, which requires a quick response under life-threatening conditions. Lack of operational intelligence and decision support system to execute evacuation of residents within a 10 minutes time window were among key factors, which contributed to the loss of 119 lives (68 percent of total fatalities) during the Black Saturday 2009 bushfire in Victoria. Hard constraints of the limited time window, the uncertainty of bushfire spread, road disruptions and elderly and disabled late evacuees pose multiple challenges for fire agencies. An application of analytics and decision support system, capable of computing Just-in-time allocation of resources, can enhance the capacity of fire services agencies. Using the multi-objective analytics, this paper therefore develops optimal resource allocation models to enhance emergency response to improve the efficiency of late evacuation response.Three key operational challenges are tackled including timely evacuation, shelter assignment and routing. Three bushfire scenarios are constructed to incorporate constraints of restricted time-window and potential road disruptions. Capacity and number of rescue vehicles and shelters are other constraints. This mathematical model is solved by the application of theconstraint approach. Objective functions are simultaneously optimised to maximise the total number of evacuees while minimise the number of assigned rescue vehicles and shelters. We argue that this model provides a scenario-based decision-making tool to aid maximise the resource utilisation and coverage of late evacuees. The analytics based insights drawn from various disruption scenarios could help emergency services agencies in identifying appropriate strategies to improve the efficiency of late evacuation response.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Multi-objective Decision Analyticsmentioning

confidence: 99%

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Multi-Objective Decision Analytics for Short-Notice Bushfire Evacuation: An Australian Case Study

Shahparvari

Chhetri

Abareshi

et al. 2015

AJIS

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“…Historical record of hospital evacuation clearly reveals that uncertainty affects all aspects of emergency evacuation decisionmaking. Factors affecting the selection of decisions are dynamic and have an uncertain nature (60). Conducting the emergency evacuation following a disaster requires fast and correct decisions (61).…”

Section: Thematic Analysismentioning

confidence: 99%

Decision-making on Hospital Emergency Evacuation in Disasters and Emergencies: Findings From a Systematic Review

Yaghoubi¹,

Ardalan²,

Zavareh³

et al. 2017

Iran Red Crescent Med J

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Context: Disasters are increasing worldwide, with more devastating effects than ever before. Hospitals must maintain their normal functions or have an evacuation plan due to the rate of damages at the time of a sudden disaster. The present study was conducted to determine the effective determinants and components in hospital evacuation decision-making.Evidence Acquisition: In this systematic review study, which was conducted in 2016, bibliographies, citation databases, and other available records such as international guidelines, documents and reports of organizations and academic dissertations were used to find an answer to the following question: What are the effective components in hospital evacuation decision-making? Finally, 34 articles were included in this systematic review. This systematic review article was checked with PRISMA checklist. Results:The common factors affecting hospital emergency evacuation decision-making were classified into 4 general categories and 40 subcategories, which have been explored during thematic analysis. These 4 categories included hospital infrastructure consequences, threat, internal factors, and external factors. Level of risk was the most important component of threat category and it was mentioned in most of the reviewed literature. Loss of electricity and water, communication and transportation, resources such as staff, and removing patient devices were the most mentioned factors in hospital infrastructure consequences, external factors, and internal factors, respectively. Conclusions:Different variables affect the process of hospital emergency evacuation decision-making. Thus, further studies are needed to develop a decision-making tool for hospital emergency evacuations in Iran.Keywords: Hospital Evacuation, Decision-Making, Disasters, Emergencies ContextThe percentage of disasters and their devastating concerns is increasing worldwide. It was reported that 3.3 million people died in disasters globally from 1970 to 2010 (1, 2). Despite advances in science and technology, it is not yet possible to forecast unexpected events such as earthquakes. In the critical situations following disasters, mortality and morbidity as well as the demand for health care services suddenly increase (3).Health system has a special place among other organizations involved in crisis management because it is the first and foremost need at the time of crises during disasters and unexpected circumstances (4). Hospitals, as key elements in providing preparedness in emergency situations, must remain fully functional at the time of disasters and major incidents (5). They are fundamental resources for successful management of disasters (6).The vulnerability of hospitals in disasters results in instabilities in providing health care (7). Hundreds of hospitals and other health care facilities are destroyed or lose their function in natural disasters worldwide every year Yaghoubi T et al. centers have been evacuated urgently due to fire, incidents related to Hydro-meteorological changes, ter...

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“…By this, the expansion of the fire (heat source) and the amount of smoke generated can be minimized [1][2][3][4]; consequently, safety of life can be secured [5]. A fire in an enclosed space, such as a room in a building, is generally called a compartment fire.…”

Section: Introductionmentioning

confidence: 99%

Effects of a Sprinkler on Evacuation Dynamics in Fire

2015

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Abstract:A fire in an enclosed space, such as a room in a building, is generally called a compartment fire. To prevent the compartment fire, a sprinkler for first-aid fire-fighting is installed in rooms. However, it is difficult to determine the degree to which smoke generation and the fire spreading will be inhibited when sprinklers are on. In particular, demonstrating evacuation behavior assuming an actual fire is impossible. In this study, we evaluated an effectiveness of the sprinkler by numerical simulations. To consider evacuation dynamics, a real-coded cellular automata (RCA) was used, where we can freely set the direction and velocity of an evacuee based on a floor field model. To consider the situation in the room fire, we used a simulator called Fire Dynamics Simulator (FDS). Two cases with and without the sprinkler were compared to see the validity of the sprinkler on evacuation dynamics. The effect of smoke and the expansion of the fire-spreading region were discussed. Results show that, since the fire-spreading region disappears when the sprinkler is actuated, the evacuation time decreases. Even though the sprinkler is actuated, the smoke generated at the beginning of a fire diffuses inside the whole room. However, the duration of evacuees being overwhelmed by smoke is less, because the amount of smoke generated by the pyrolysis reaction is much decreased.

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Modeling Evacuate versus Shelter-in-Place Decisions in Wildfires

Cited by 62 publications

References 48 publications

Multi-Objective Decision Analytics for Short-Notice Bushfire Evacuation: An Australian Case Study

Multi-Objective Decision Analytics for Short-Notice Bushfire Evacuation: An Australian Case Study

Decision-making on Hospital Emergency Evacuation in Disasters and Emergencies: Findings From a Systematic Review

Effects of a Sprinkler on Evacuation Dynamics in Fire

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