Evacuation Decision Research Articles

Assessment of Protective Action Decision Making during Nuclear Power Plant Biennial Exercises.

Radiological emergency preparedness for commercial nuclear power plants provides planning for implementing predetermined, prompt protective actions such as evacuation and shelter-in-place. In the event of a significant radiological release, onsite emergency response organizations will notify offsite response organizations and provide a protective action recommendation. The cognizant offsite authority will then make a protective action decision and inform the public of the need to act. Both the protective action recommendation and decision are driven by US Environmental Protection Agency protective action guides. Protective action strategies contain conservatisms and are intended to balance protection against other factors to ensure that actions result in more benefit than harm. But added conservatism can potentially shift the risks to those inherent to the protective action with no added benefit of protection. Protective action recommendations and protective action decisions made during biennial exercises were analyzed to assess how well they comport with the protective action guides. Trends in precautionary actions and the use of potassium iodide were also investigated. The analysis shows that protective action decisions typically exceed the protective action recommendation, resulting in an increase in the number of potential evacuees. However, exercise dose projection data do not appear to support such extensive initial evacuation decisions based on consideration of the protective action guides.

Diverse Uses of Multi-Purpose Cyclone Shelters In India

India employs a strategy to reduce the probability of tropical cyclones and ready for them through placing Multi-Purpose Cyclone Shelters across its coastline. These shelters are meant to safeguard vulnerable populations throughout storms and to function as school, community halls, etc. while not really in use. This describes in detail purpose of these multi-use cyclone shelters, which also include providing safe shelter for inhabitants of cyclone-affected areas in addition to individuals who are unable evacuate for a wide range of reasons, such like infrastructure problems. In India as well as other south Asian nations, like that as Bangladesh, a vulnerable region is evacuated by transferring at-risk populace into built specifically outdoor structures called as "cyclone shelters." This is frequently discovered in or adjacent to one's neighbourhood, though sometimes they may be a significant distance away. In short, it was initially created in Bangladesh, then adopted in India, and now we'll take a closer look at Odisha, which now has constructed these cyclone shelters for cyclone mitigation. A primary goal of the National Cyclone Risk Mitigation Project is to make sure that each and every home within 10 kilometres of the coastline has accessibility to a cyclone shelter that is no more than 2.5 kilometres away, and that total number of cyclone shelters matches to the area's in need of accommodation. The thought of a "horizontal evacuation" is hardly a possibility for nations with huge populations, inadequate road infrastructure, and lacking transportation services. Instead, it is considered essential to relocate to specifically constructed cyclone shelters located within the neighbourhood. The decision maker sees the particular strategy much more interesting since it takes less time for clearance or to finish an evacuation. In these circumstances, approval is essential because evacuation decisions are often postponed. Construction of the cyclone shelters was a wise move because it is entangled with other aspects, including the accuracy of meteorological forecasts, public willingness to cooperate with mandatory evacuations inside the lack of weather warnings, dissatisfaction in the event of a non-strike, etc.

The multistability of predictive technology in nuclear disasters.

Postphenomenological studies have explored technological mediation between the human body and the world by analysing the bodily experience of the world. Applying this analytical perspective to predictive technology requires some expansions because humans cannot directly experience the future world. I conceptualize pre-spectival focus, which refers to how human attention is directed to the making-future-present process, and which features or aspects of its process are foregrounded or backgrounded. Through the concept of pre-spectival focus and actor-network theory (ANT), this article examines the case of System for the Prediction of Environmental Emergency Dose Information (SPEEDI), a Japanese technology used to simulate the atmospheric dispersion of radionuclides released from nuclear reactors. SPEEDI provides prediction maps representing radiological consequences and was expected to support evacuation decisions during nuclear emergencies. However, this was not the case with the Fukushima disaster, which led to a socio-technical controversy regarding SPEEDI's usage. Based on bibliographic surveys and several interviews, I encapsulate four multistable uses of SPEEDI: prediction as supporting advice, prediction as a tool for evacuation drills, prediction as self-protection, and prediction as a source of misunderstanding. Relevant actors perceive the predictions of a nuclear disaster in each stability depending on the diversity of their pre-spectival foci, which is also related to the forms of life nourished through their professional and daily lives. A distinct rivalry can be observed between the two actor-networks around nuclear emergency management in which SPEEDI is differently enrolled: the social control network and self-determination network. In the former, the residents are constituted as passive selves who obediently follow governmental instructions; in the latter, residents are included as autonomous subjects who can actively decide protective actions. Moreover, I discuss future postphenomenology-ANT studies on predictive technologies based on these analyses.

Protection or Peril of Following the Crowd in a Pandemic-Concurrent Flood Evacuation

The decisions of whether and how to evacuate during a climate disaster are influenced by a wide range of factors, including emergency messaging, social influences, and sociodemographics. Further complexity is introduced when multiple hazards occur simultaneously, such as a flood evacuation taking place amid a viral pandemic that requires physical distancing. Such multihazard events can necessitate a nuanced navigation of competing decision-making strategies wherein a desire to follow peers is weighed against contagion risks. To better understand these trade-offs, we distributed an online survey during a COVID-19 pandemic surge in July 2020 to 600 individuals in three midwestern and three southern states in the United States with high risk of flooding. In this paper, we estimate a random parameter discrete choice model in both preference space and willingness-to-pay space. The results of our model show that the directionality and magnitude of the influence of peers’ choices of whether and how to evacuate vary widely across respondents. Overall, the decision of whether to evacuate is positively impacted by peer behavior, while the decision of how to evacuate (i.e., ride-type selection) is negatively impacted by peer influence. Furthermore, an increase in flood threat level lessens the magnitude of peer impacts. In terms of the COVID-19 pandemic impacts, respondents who perceive it to be a major health risk are more reluctant to evacuate, but this effect is mitigated by increased flood threat level. These findings have important implications for the design of tailored emergency messaging strategies and the role of shared rides in multihazard evacuations. Specifically, emphasizing or deemphasizing the severity of each threat in a multihazard scenario may assist in: (1) encouraging a reprioritization of competing risk perceptions; and (2) magnifying or neutralizing the impacts of social influence, thereby (3) nudging evacuation decision-making toward a desired outcome.

Predicting and Assessing Wildfire Evacuation Decision-Making Using Machine Learning: Findings from the 2019 Kincade Fire

Predicting and Assessing Wildfire Evacuation Decision-Making Using Machine Learning: Findings from the 2019 Kincade Fire

Development and Psychometric Properties of Decision-Making Scale for Emergency Hospital Evacuation in Disasters.

The evidence shows that the need for emergency evacuation in hospitals has arisen. Designing an emergency evacuation decision making tool increases the confidence of hospital managers in the decision made. Therefore, this study was aimed at the development, and the psychometric properties, of the decision-making scale for emergency hospital evacuation in disasters. This study was done in 2 phases of qualitative study and literature review and designing and psychometric properties of the instrument. After development of the primary item pool, the psychometric properties of the questionnaire were evaluated. In this regard, face and content validity, internal consistency (Alpha's Cronbach), reliability (ICC), and stability were assessed. In the validity stage of the instrument, 4 items were removed. Also, 4 items were modified and 2 items were merged. The number of items was thus decreased to 64. After CVI calculation, 5 items were removed, 4 items were modified, and 2 items were merged. As a result of this, the number of items decreased to 58 items. The scale has good reliability and stability. It seems that the instrument could be useful in decision-making for emergency hospital evacuation in disasters.

A Spatio-Temporal Cognitive Framework for Individual Route Choice in Outdoor Evacuation Scenarios

Route choice is a complex issue in simulating individual behaviors and reproducing collective phenomena during evacuations. A growing concern has been given to the individual cognitive mechanism to investigate how routing decisions are made in specific situations. However, the essential role of multiple spatio-temporal scales has not been completely considered in the current cognitive frameworks, which leads to the inaccuracy of cognition representation in evacuation decisions. This study proposes a novel spatio-temporal cognitive framework integrated with multiple spatio-temporal scales for individual route choice. First, a complete spatio-temporal cognitive mechanism is constructed to depict the individual evacuation cognition process. Second, a spatio-temporal route choice strategy that emerges from agent-based simulation and extends into the spatio-temporal potential field is designed to represent the overall time-varying cost along routes in individual subjective estimation. Finally, a spatio-temporal A* algorithm is developed for individual optimal route planning in complex outdoor evacuation scenarios. The experimental results show that the proposed framework outperformed the conventional potential field model in evacuation performance, in both objective crowd evacuation evaluation metrics and individual subjectively estimated evacuation cost in cognition, and may provide more insights on crowd evacuation management and guidance.

Questionnaire Survey of Tracheostomy Patients at Home in the Event of a Large-scale Disaster

Patients with disabilities and those receiving medical care at home may be vulnerable to disasters, as they may not be able to evacuate quickly in the event of a large-scale disaster. A questionnaire survey was conducted among patients and their families under home tracheostomy management regarding preparedness for a major disaster, evacuation, and equipment needed in evacuation centers with the aim of identifying current conditions and problems in the event of a major disaster. A total of 34% of respondents answered that “family members can evacuate by themselves,” while 33% answered that “assistance is necessary,” and 33% answered that “evacuation is not possible,” indicating that most patients could not evacuate by themselves should a disaster occur. Although 87% had prepared the supplies necessary for tracheal cannula management in case of a disaster, respirator batteries were the most frequently reported equipment needed in evacuation centers. Evacuation decisions and methods were major concerns faced by patients and families. In terms of disaster preparedness, a community-wide effort involving not only medical institutions and local governments but also providers of medical services is considered important.

Evaluation of Hurricane Evacuation Order Plans: Hurricane Florence Case Study

This paper introduces an approach to evaluate the performance of a previously implemented or proposed hurricane evacuation plan that describes where and when official evacuation orders are issued. The approach involves use of the new integrated scenario-based evacuation (ISE) decision support tool to define a best track evacuation plan as a reference point and measure the performance of other plans in relation to that according to their ability to meet multiple stated objectives: minimizing risk to the population, travel time, and time people are away from their homes. Using North Carolina in Hurricane Florence (2018) as a case study, we demonstrate the process by evaluating performance of both the actual set of orders as executed and the orders that would have been recommended if the new ISE decision support tool had been used during the event. All three plans were evaluated for two cases—assuming the hurricane unfolds as it actually did, and if the hurricane had instead evolved like one of 21 other realistic scenarios. Results suggest the actual evacuation was quite good, and the ISE tool could have resulted in improved evacuation performance.

Understanding levels of compliance with emergency responder instructions for members of the Public involved in emergencies: Evidence from the Grenfell Tower fire

Purpose– It is essential to understand how members of the public make decisions during emergencies. Such understanding is crucial in order to understand how emergency services can best influence positive protective behaviours. Previous research in this area has indicated that members of the public will respond both to the threat from an incident such as a fire as well the way the threat is managed by emergency responders and that this management will be crucial in increasing public willingness to comply with emergency services instructions. AimsThe study aimed to identify factors that affected the way in which those involved in the Grenfell Tower Fire behaved and develop the understanding of factors that affect public behaviour during large scale emergencies. Design/methodology/approachThis paper used 72 transcripts from the Grenfell Tower Inquiry to examine how members of the public make decisions during emergencies. The study utilised a Framework Analysis to identify themes relating to how members of the public made decisions regarding protective actions and what factors influenced these decisions. FindingsThe study identifies several key factors which influenced individuals' decision making concerning protective actions:- Uncertainty and Anxiety.- Environmental Factors in Evacuation Decision Making.- Trust.- Helping and Co-Operative Behaviours in Emergencies. Originality/valueData involving real life emergencies is extremely useful in providing support to the development of emergency procedures and training for emergency services.The research identifies several key factors which can inform a better understanding of public behaviour during emergencies.

Wildfire evacuation decision modeling using GPS data

The threat of wildfires is increasing at an alarming rate due to climate change and the expansion of the wildland–urban interface. It is critical to improve understanding of people’s evacuation decisions during wildfire emergencies. Therefore, this study proposes a novel methodology to model evacuation rates using large-scale GPS data generated by mobile devices. We first overlay socio-demographic and built environment attributes—aggregated at the census-block-group-level—to the inferred home locations of the mobile device users. We then develop a linear regression model to examine how the socio-demographic and built environment variables affect evacuation rates across census block groups. We apply the GPS data (44.2 million signal records from over 5000 devices) collected during the 2019 Kincade Fire in Sonoma County, California to evaluate the proposed methodology. The results of the model are generally consistent with findings of a prior survey of the same fire event. We also include factors in our model that are rarely measured through previous methods and find several built environment factors such as distance to the fire, land parcel size, and residing in a high fire risk area to be correlated with evacuation rates. Another notable finding is that people living in urban block groups, block groups with a higher median age, and block groups with a higher average level of educational attainment are more likely to evacuate. This research shows that the use of GPS data is a valuable complement to existing methods in wildfire evacuation research, and provides new insights to improve evacuation planning.

A novel method for the risk assessment of human evacuation from cruise ships in maritime transportation

In maritime transport, evacuation, escape and rescue play a crucial role in protecting people's lives when a passenger ship is involved in a serious accident. The study aims to develop a new method to identify hazards, quantify and rank the associated risks in the process of Human Evacuation from Passenger Ships (HEPS). Firstly, based on extensive literature review and marine accident investigation reports, the risk factors affecting passenger ship evacuation were analysed and identified, and an analysis framework based on Human, Ship, Environment and Organization (HSEO) for HEPS was proposed. Secondly, a risk assessment model was proposed to quantify and rank risk factors in the process of HEPS. Finally, a large-scale evacuation drill of a cruise ship was taken as a case study to demonstrate the applicability of the proposed evaluation model, and accuracy of the results. The results reveal that (1) evacuation decision, operation of Life-Saving Appliances (LSAs) are the main risks affecting the safety of HEPS; (2) the behaviours of passengers have a relatively lower risk priority; and (3) future HEPS research should focus on the development of a multi-attribute decision system to address the issue on when to evacuate and when to abandon a ship.

Factors Affecting the Cyclone Preparedness Programme Volunteers’ Performance in Early Warning Dissemination in Emergency Response in Bangladesh

Millions of people living along coastal Bangladesh are at risk from cyclones, and timely dissemination and social acceptance of effective early warnings could significantly save their lives. In recent years, the Cyclone Preparedness Programme (CPP) volunteers have gained considerable popularity among local community as the most reliable source for early warning and emergency assistance for evacuation during coastal cyclones. The sustainability of the CPP is threatened not only by limited funding but also by the difficulty of attracting and retaining committed and efficient volunteers. The purpose of this study is to identify factors that affect the activities of Cyclone Preparedness Programme volunteers regarding early warning dissemination during emergency responses. The research design of this study integrated both qualitative and quantitative approaches. The questionnaires were complemented by face-to-face interviews and Focus Group Discussion with 177 residents of the Koyra and Ukhiya sub-districts (Upazila) to investigate the respondents’ responses to early warning information. In addition, a total of 23 CPP volunteers’ opinions were collected through a questionnaire survey, to identify the factors influencing CPP volunteering performance. The obtained results also show that both of the study-area communities did not properly understand the cyclone early warning signal system delivered by CPP volunteers. Approximately 49% of the community said that they could not interpret the warning message. The low level of community contact with CPP volunteers also hinders trust in warning messages and evacuation decisions. The findings also concluded that the factors related to the effectiveness of volunteering were found to be individual volunteer’s experience, training opportunities, lack of equipment and materials due to lack of budget, the social class of individual volunteers and in the absence of proper coordination. Maintainace of CPP volunteers engaged throughout the year is very challenging. These limited engagement features affect the cyclone preparedness and early warning activities of CPP. The government needs to implement policies that enable the mobilization of adequate resources and awareness campaigns to be mobilized toward the volunteers.

Evacuation action during torrential rain considering situation awareness error using protection motivation theory

The torrential rains in July 2018 caused considerable river overflow, flood damage, and landslides, particularly in western Japan. At that time, 232 fatalities and missing persons were recorded, with most human damage caused by delays in evacuation. These delays occur during most torrential rain events, and can presumably be attributed to a situation awareness error in the disaster response of residents. This study analyzed the evacuation decision-making structure by adding a situation awareness error to the protection motivation theory framework. Accordingly, the evacuation actions of residents during torrential rains in Japan in 2018 were surveyed and analyzed using structural equation modeling and logistic regression. Most respondents chose not to evacuate despite showing a high intention to do so. Such respondents evacuated only in response to a trigger such as a dramatic change in their surrounding environment or the receipt of an evacuation appeal. By considering situation awareness errors in protection motivation theory, this study identified active and passive evacuation decisions to clarify the stage at which evacuation delays occurred. The findings provide guidance on the stage of situation awareness that should be promoted and the specific measures required to achieve efficient evacuation.

Why They Escape: Mining Prioritized Fuzzy Decision Rule in Crowd Evacuation

For safety planning in crowd evacuation, it is important to predict the evacuation decisions made by different individuals and understand the reasons behind these decisions. To this end, this paper proposes an automated approach that can learn prioritized fuzzy decision rules from crowd data to predict and understand the evacuation decisions of a real human. A coevolutionary fuzzy rule miner based on genetic fuzzy-system is designed to select necessary decision features from available ones and learn both rule structure and associated rule parameters from training data. The learned fuzzy rule contains multiple sub-rules, each of which can represent evacuation strategies of different individuals in a given scenario and the features in the fuzzy condition of the sub-rule are organized and evaluated in a sequential order to reflect the priorities of different features. Based on training and testing on four evacuations scenarios of two real-world datasets, it is shown that our proposed approach can learn decision rules that are competitive to the existing evacuation decision models in terms of prediction accuracy. More importantly, it is also demonstrated that our learned rules complying with the proposed prioritized fuzzy rule representation can facilitate the interpretation of evacuation behaviors, such as “herding under zero visibility of exit” and “diminished importance on the distance to exit”, which are aligned to the field observations from real crowd evacuation.

An Interdisciplinary Approach to Evaluate Public Comprehension of the “Cone of Uncertainty” Graphic

Abstract The accurate interpretation of hurricane risk graphics is expected to benefit public decision-making. To investigate public interpretation and suggest improvements to graphical designs, an interdisciplinary, mixed-methods approach is being undertaken. Drawing on a series of focus groups with Miami residents that focused on understanding interpretations of the National Hurricane Center’s (NHC) track forecast cone or “Cone of Uncertainty,” we developed an online survey targeting a much larger sample of Florida residents (n = 2,847). The findings from this survey are the primary focus of this short article. We attempt to answer three questions: 1) What are the most frequent and trusted sources of information that Florida residents use when they learn that a hurricane is coming their way? 2) How accurately are Florida residents able to interpret risk based on the NHC Cone of Uncertainty graphic? 3) What is the relationship, if any, between the number of correct interpretations and income, age, education, housing location, housing type, or “most trusted” sources of information? Unlike previous public surveys that focused more on evacuation decisions, forecast usage, and perception of hurricane risk, our approach specifically pays attention to the details of design elements of the forecast graphics with the long-term goal of minimizing misinterpretation of future graphics. Our analysis suggests that many residents have difficulty interpreting several aspects, suggesting a rethink on how to graphically communicate aspects such as uncertainty, the size of the storm, areas of likely damage, watches and warnings, and wind intensity categories. Graphical communication strategies need to be revised to better support the different ways in which people understand forecast products, and these strategies should be tested for validity in real world settings.

Hurricanes Laura and Sally: A Case Study of Evacuation Decision-Making in the Age of COVID-19

Abstract This study examines risk perceptions and evacuation planning for those residents affected by Hurricane Laura—the first major hurricane evacuation during the COVID-19 pandemic—and Hurricane Sally, prior to the widespread availability of vaccines. Research on hurricane evacuation behavior and risk perceptions during a pandemic is critical for quantifying the intersect of these compounding threats. Analyses captured how people perceive public shelters and whether evacuation choices changed in light of the pandemic. Many study participants considered themselves vulnerable to COVID-19 (39.4%), and two-thirds believed it would be “very serious” if they or their loved ones contracted COVID-19, but this had no impact on their actual evacuation decision-making. Approximately 75% of the sample stayed at home during Hurricanes Laura or Sally, and, of these, just over 80% indicated that COVID-19 was a somewhat important deciding factor. This reflects the partial role that COVID-19 played in balancing individual and household protective action decision-making during complex disasters, whereas 15.5% wanted to evacuate but waited until it was too late. For those who evacuated to a hotel, many found that staff and guests wore masks and socially distanced in common spaces. Of particular interest is that individuals have a continued negative perception of public shelters’ ability to safeguard against COVID-19 that was coupled with a significant decrease in the number of respondents that would potentially use shelters in 2020 as compared with before the COVID-19 pandemic. These results have informed and will inform future hazard mitigation planning during the current pandemic or future pandemics or infectious disease outbreaks.

Understanding the influence of multiple information sources on risk perception dynamics and evacuation decisions: An agent-based modeling approach

Evacuation is one of the most effective strategies to reduce risk during natural disasters. Although many studies have investigated factors affecting evacuation decisions (e.g., socio-economic, risk forecast, demographic, environmental cues, etc.), how all these factors interplay in forming the overall risk perception and evacuation decision is underexplored. Here, we present an agent-based model that leverages empirical evidence from post-disaster surveys to create evacuation tendencies of the agents (households) and integrates flood-related hazard risk, household socio-demographic factors, social network characteristics and decisions, and neighbors’ decisions to dynamically evolve complex decision-making pattern during hurricane evacuation. We simulate the effect of multiple information sources and their perceived credibility on evacuation participation by separately determining evacuation compliance (defined as evacuation from places where official mandatory evacuation order is issued) and shadow evacuation (defined as spontaneous evacuation from places where a mandatory order is not issued). We use socio-demographic data from U. S. Census Bureau, building footprint data from County Website, run off data from Stormwater Management Model (SWMM) of U.S. Environmental Protection Agency, and all other data were synthetically generated within the model. Our case study based on a community of Miami-Dade County indicates that higher perceived credibility of hazard risk leads to higher evacuation compliance. We have also found that while social networks increase overall evacuation participation, they also increase shadow evacuation and higher trust on neighbor actions reduces evacuation rates. This study gives insights for emergency management to design appropriate strategies for providing hazard forecasts or communicating overall risk during disasters.

An improved optimization model for crowd evacuation considering individual exit choice preference

AbstractGuidance‐assisted crowd evacuation is a process of combining individual exit choice behavior with managers' exit assignment control. The knowledge of individual exit choice preference is of great significance for optimizing global exit assignment planning. This study proposes an improved optimization model for crowd evacuation by integrating the individual‐level exit choice preference analysis with system‐level exit assignment optimization to represent more realistic crowd evacuation decisions. First, the impact factors of individual exit choice behavior are considered in a mixed logit model to predict the probability of each individual choosing each exit in specific situations. Second, a preference‐based exit filtering strategy is designed to analyze the sensible alternative exits for individuals or groups in multi‐scale evacuation cells. Finally, to pursue optimal exit assignment planning, a multi‐objective particle swarm optimization algorithm and an improved social force model are adopted to simulate the process of crowd evacuation and evaluate the performance of the specific exit assignment plans. The case study of an outdoor multiple‐exit scenario in Xi'an, China, indicates that the proposed model can help managers to understand the heterogeneity of individual evacuation behaviors. Furthermore, it will support more reliable and realistic evacuation decisions in real‐life situations than conventional plans that typically implement the top‐n strategy.

Teleconsultation at Sea and Acute Wound Management Onboard.

Introduction: The French Tele-Medical Assistance Service (TMAS) provides medical teleconsultation for any ship at sea. At the end of the consultation, the doctor decides whether the problem can be taken care of onboard or not. In this study, we determined the factors associated with the decision for disembarkation or evacuation in case of wounds. Methods: We conducted a retrospective epidemiological study between 2011 and 2019 from consultations with the French TMAS. The inclusion criterion was the presence of an acute wound. Results: One thousand six patients (n = 1,006) were analyzed and 586 (58%) patients were disembarked or evacuated. Factors associated with disembarkation or evacuation are wound characteristics (severity and location), the onboard staff's medical training, the availability of photography, and the ship's location. Wound severity is a risk factor for disembarkation or evacuation. The availability of photography, staff with advanced training, and being at >1 day of navigation from a harbor are protective factors against being disembarked or evacuated. Conclusion: The added value of photography and an update of medium medical training could increase the number of wounds taken care of onboard.