Should I Stay or Should I Go Now? Or Should I Wait and See? Influences on Wildfire Evacuation Decisions

As climate change has contributed to longer fire seasons and populations living in fire‐prone ecosystems increase, wildfires have begun to affect a growing number of people. As a result, interest in understanding the wildfire evacuation decision process has increased. Of particular interest is understanding why some people leave early, some choose to stay and defend their homes, and others wait to assess conditions before making a final decision. Individuals who tend to wait and see are of particular concern given the dangers of late evacuation. To understand what factors might influence different decisions, we surveyed homeowners in three areas in the United States that recently experienced a wildfire. The Protective Action Decision Model was used to identify a suite of factors previously identified as potentially relevant to evacuation decisions. Our results indicate that different beliefs about the efficacy of a particular response or action (evacuating or staying to defend), differences in risk attitudes, and emphasis on different cues to act (e.g., official warnings, environmental cues) are key factors underlying different responses. Further, latent class analysis indicates there are two general classes of individuals: those inclined to evacuate and those inclined to stay, and that a substantial portion of each class falls into the wait and see category.     

Factors Affecting Hurricane Evacuation Intentions

Protective actions for hurricane threats are a function of the environmental and information context; individual and household characteristics, including cultural worldviews, past hurricane experiences, and risk perceptions; and motivations and barriers to actions. Using survey data from the Miami‐Dade and Houston‐Galveston areas, we regress individuals’ stated evacuation intentions on these factors in two information conditions: (1) seeing a forecast that a hurricane will hit one's area, and (2) receiving an evacuation order. In both information conditions having an evacuation plan, wanting to keep one's family safe, and viewing one's home as vulnerable to wind damage predict increased evacuation intentions. Some predictors of evacuation intentions differ between locations; for example, Florida respondents with more egalitarian worldviews are more likely to evacuate under both information conditions, and Florida respondents with more individualist worldviews are less likely to evacuate under an evacuation order, but worldview was not significantly associated with evacuation intention for Texas respondents. Differences by information condition also emerge, including: (1) evacuation intentions decrease with age in the evacuation order condition but increase with age in the saw forecast condition, and (2) evacuation intention in the evacuation order condition increases among those who rely on public sources of information on hurricane threats, whereas in the saw forecast condition evacuation intention increases among those who rely on personal sources. Results reinforce the value of focusing hurricane information efforts on evacuation plans and residential vulnerability and suggest avenues for future research on how hurricane contexts shape decision making.     

Individual Actual or Perceived Property Flood Risk: Did it Predict Evacuation from Hurricane Isabel in North Carolina, 2003?

Individual perception of risk has consistently been considered an important determinant of hurricane evacuation in published studies and reviews. Adequate risk assessment is informed by environmental and social cues, as well as evacuation intentions and past disaster experience. This cross‐sectional study measured perceived flood risk of 570 residents of three coastal North Carolina counties, compared their perception with actual risk determined by updated flood plain maps, and determined if either was associated with evacuation from Hurricane Isabel in 2003. Census blocks were stratified by flood zone and 30 census blocks were randomly selected from each flood zone. Seven interviews were conducted at random locations within selected blocks. Bivariate and multivariable analyses were conducted to produce crude and adjusted risk differences. Neither the designated flood zone of the parcel where the home was located nor the residents' perceived flood risk was associated with evacuation from Hurricane Isabel in the bivariate analysis. In the multivariable analysis, intention to evacuate and home type were important confounders of the association between actual risk and evacuation. The belief that one is at high risk of property damage or injury is important in evacuation decision making. However, in this study, while coastal residents' perceived risk of flooding was correlated with their actual flood risk, neither was associated with evacuation. These findings provide important opportunities for education and intervention by policymakers and authorities to improve hurricane evacuation rates and raise flood risk awareness.     

The mixed evacuation problem

A dynamic network introduced by Ford and Fulkerson is a directed graph with capacities and transit times on its arcs. The quickest transshipment problem is one of the most fundamental problems in dynamic networks. In this problem, we are given sources and sinks. Then the goal of this problem is to find a minimum time limit such that we can send the right amount of flow from sources to sinks. In this paper, we introduce a variant of this problem called the mixed evacuation problem. This problem models an emergent situation in which people can evacuate on foot or by car. The goal is to organize such a mixed evacuation so that an efficient evacuation can be achieved. In this paper, we study this problem from the theoretical and practical viewpoints. In the first part, we prove the polynomial-time solvability of this problem in the case where the number of sources and sinks is not large, and also prove the polynomial-time solvability and computational hardness of its variants with integer constraints. In the second part, we apply our model to the case study of Minabe town in Wakayama prefecture, Japan.     

Possibilistic scheduling routing for short-notice bushfire emergency evacuation under uncertainties: An Australian case study

This paper aims to develop a capacitated vehicle routing solution to evacuate short-notice evacuees with time windows and disruption risks under uncertainties during a bushfire. A heuristic solution technique is applied to solve the triangular possibilistic model to optimise emergency delivery service. The effectiveness of the proposed algorithm is evaluated by comparing it with a designed genetic algorithm on sets of 20 numerical examples. The model is then applied to the real case study of 2009 Black Saturday bushfires in Victoria, Australia. The results show that it is possible to transfer the last-minute evacuees during the Black Saturday bushfires under the hard time window constraint. Network disruptions however have impact on resource utilisation. The modelling outputs will be useful in the development of emergency plans and evacuation strategies to enhance rapid response to last-minute evacuation in a bushfire emergency.     

Evacuating People with Mobility‐Challenges in a Short‐Notice Disaster

In past disasters, arrangements have been made to evacuate people without their own transportation, requiring them to gather at select locations to be evacuated. Unfortunately, this type of plan does not help those people who are unable to move themselves to the designated meeting locations. In the United States, according to the Post‐Katrina Emergency Management Reform Act of 2006, state or local governments have the responsibility to coordinate evacuation plans for all populations. These include those with disabilities. However, few, if any, have plans in place for those who are mobility‐challenged. The problem of evacuating mobility‐challenged people from their individual locations in a short‐notice disaster is a challenging combinatorial optimization problem. In order to develop the model and select a solution approach, we surveyed related literature. Based on our review, we formulate the problem and develop an Ant Colony Optimization (ACO) algorithm to solve it. We then test two different versions of the ACO algorithm on five stylized datasets with several different parameter settings.     

考虑灾民痛苦感知的应急避难所选址与物资分配优化

大规模灾害发生初期，应急物资往往不能及时供应，受灾群众因缺乏物资和服务产生痛苦感知。针对该问题，设计数值评定量表（NRS）构建痛苦函数，刻画灾民痛苦感知成本，将灾民感知因素纳入应急总成本的决策考量。提出以总社会成本（物流成本和痛苦心理成本之和）最小为应急救援目标，构建了一个考虑灾民疏散与重新安置、临时避难所选址和物资分配的集成优化模型。设计经典混合整数规划方法和改进的遗传算法对所构模型进行求解，并应用于海南威马逊台风案例。案例分析表明，模型和算法能有效解决考虑灾民痛苦的避难所选址与物资分配问题，揭示了随着受灾规模的增加和疏散时间的减少，遗传算法的求解结果优于经典求解方法。     

Flood Risk Acceptability and Economic Value of Evacuation

The economic value of evacuation and its relationship with flood risk acceptability in Japan were studied by applying the contingent valuation method (CVM). Flood risk acceptability here refers to the extent to which people accept the occurrence of floods, in terms of scale and frequency. The economic value of evacuation refers to people's willingness to pay (WTP) for avoiding evacuation inconvenience because of its inconvenience and the potential for certain losses as a result of evacuation. Our main finding was that over half of the people (56%) who actually evacuated in a real flood situation reported inconvenience. The greatest inconveniences were the shortages of information and food. Evacuation inconvenience can be regarded as an important factor causing the low rate of evacuation in Japan. The WTP for avoiding current inconvenience was approximately half of the estimated economic value of evacuation, implying that the current budget for evacuation is too small and should be increased to improve the conditions of evacuation sites. The economic value of evacuation can be taken into consideration in the risk assessment process in order to evaluate the efficiency of risk reduction measures. Flood risk acceptability and home ownership are two major statistically significantly determinants of the WTP. Considering that those who accept flood risk have a lower WTP for flood risk control (ex ante measures) than those who reject it, it is reasonable to think that there may be a tradeoff between the public WTPs for ex ante or ex post measures.     

Analyzing Evacuation Versus Shelter‐in‐Place Strategies After a Terrorist Nuclear Detonation

We superimpose a radiation fallout model onto a traffic flow model to assess the evacuation versus shelter‐in‐place decisions after the daytime ground‐level detonation of a 10‐kt improvised nuclear device in Washington, DC. In our model, ≈80k people are killed by the prompt effects of blast, burn, and radiation. Of the ≈360k survivors without access to a vehicle, 42.6k would die if they immediately self‐evacuated on foot. Sheltering above ground would save several thousand of these lives and sheltering in a basement (or near the middle of a large building) would save of them. Among survivors of the prompt effects with access to a vehicle, the number of deaths depends on the fraction of people who shelter in a basement rather than self‐evacuate in their vehicle: 23.1k people die if 90% shelter in a basement and 54.6k die if 10% shelter. Sheltering above ground saves approximately half as many lives as sheltering in a basement. The details related to delayed (i.e., organized) evacuation, search and rescue, decontamination, and situational awareness (via, e.g., telecommunications) have very little impact on the number of casualties. Although antibiotics and transfusion support have the potential to save ≈10k lives (and the number of lives saved from medical care increases with the fraction of people who shelter in basements), the logistical challenge appears to be well beyond current response capabilities. Taken together, our results suggest that the government should initiate an aggressive outreach program to educate citizens and the private sector about the importance of sheltering in place in a basement for at least 12 hours after a terrorist nuclear detonation.     

Why Near‐Miss Events Can Decrease an Individual's Protective Response to Hurricanes

Prior research shows that when people perceive the risk of some hazardous event to be low, they are unlikely to engage in mitigation activities for the potential hazard. We believe one factor that can lower inappropriately (from a normative perspective) people's perception of the risk of a hazard is information about prior near‐miss events. A near‐miss occurs when an event (such as a hurricane), which had some nontrivial probability of ending in disaster (loss of life, property damage), does not because good fortune intervenes. People appear to mistake such good fortune as an indicator of resiliency. In our first study, people with near‐miss information were less likely to purchase flood insurance, and this was shown for both participants from the general population and individuals with specific interests in risk and natural disasters. In our second study, we consider a different mitigation decision, that is, to evacuate from a hurricane, and vary the level of statistical probability of hurricane damage. We still found a strong effect for near‐miss information. Our research thus shows how people who have experienced a similar situation but escape damage because of chance will make decisions consistent with a perception that the situation is less risky than those without the past experience. We end by discussing the implications for risk communication.     

EvacuAid: A Probabilistic Model to Determine the Expected Loss of Life for Different Mass Evacuation Strategies During Flood Threats

Evacuation of people in case of a threat is a possible risk management strategy. Evacuation has the potential to save lives, but it can be costly with respect to time, money, and credibility. The consequences of an evacuation strategy depend on a combination of the time available, citizen response, authority response, and capacity of the infrastructure. The literature that discusses evacuations in case of flood risk management focuses, in most cases, only on a best‐case strategy as a preventive evacuation and excludes other possible strategies. This article introduces a probabilistic method, EvacuAid, to determine the benefits of different types of evacuation with regards to loss of life. The method is applied for a case study in the Netherlands for preventive and vertical evacuation due to flood risk. The results illustrate the impact of uncertainties in available time and actual conditions (e.g., the responses of citizens and authorities and the use of infrastructure). It is concluded that preparation for evacuation requires adaptive planning that takes preventive and vertical evacuation into account, based on a risk management approach.     

Predicting Emergency Evacuation and Sheltering Behavior: A Structured Analytical Approach

We offer a general approach to predicting public compliance with emergency recommendations. It begins with a formal risk assessment of an anticipated emergency, whose parameters include factors potentially affecting and affected by behavior, as identified by social science research. Standard procedures are used to elicit scientific experts' judgments regarding these behaviors and dependencies, in the context of an emergency scenario. Their judgments are used to refine the model and scenario, enabling local emergency coordinators to predict the behavior of citizens in their area. The approach is illustrated with a case study involving a radiological dispersion device (RDD) exploded in downtown Pittsburgh, PA. Both groups of experts (national and local) predicted approximately 80-90% compliance with an order to evacuate workplaces and 60-70% compliance with an order to shelter in place at home. They predicted 10% lower compliance for people asked to shelter at the office or to evacuate their homes. They predicted 10% lower compliance should the media be skeptical, rather than supportive. They also identified preparatory policies that could improve public compliance by 20-30%. We consider the implications of these results for improving emergency risk assessment models and for anticipating and improving preparedness for disasters, using Hurricane Katrina as a further case in point.     

An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 1—Decision Support System

This article introduces a new integrated scenario-based evacuation (ISE) framework to support hurricane evacuation decision making. It explicitly captures the dynamics, uncertainty, and human–natural system interactions that are fundamental to the challenge of hurricane evacuation, but have not been fully captured in previous formal evacuation models. The hazard is represented with an ensemble of probabilistic scenarios, population behavior with a dynamic decision model, and traffic with a dynamic user equilibrium model. The components are integrated in a multistage stochastic programming model that minimizes risk and travel times to provide a tree of evacuation order recommendations and an evaluation of the risk and travel time performance for that solution. The ISE framework recommendations offer an advance in the state of the art because they: (1) are based on an integrated hazard assessment (designed to ultimately include inland flooding), (2) explicitly balance the sometimes competing objectives of minimizing risk and minimizing travel time, (3) offer a well-hedged solution that is robust under the range of ways the hurricane might evolve, and (4) leverage the substantial value of increasing information (or decreasing degree of uncertainty) over the course of a hurricane event. A case study for Hurricane Isabel (2003) in eastern North Carolina is presented to demonstrate how the framework is applied, the type of results it can provide, and how it compares to available methods of a single scenario deterministic analysis and a two-stage stochastic program.     

Understanding Cumulative Risk Perception from Judgments and Choices: An Application to Flood Risks

Catastrophic events, such as floods, earthquakes, hurricanes, and tsunamis, are rare, yet the cumulative risk of each event occurring at least once over an extended time period can be substantial. In this work, we assess the perception of cumulative flood risks, how those perceptions affect the choice of insurance, and whether perceptions and choices are influenced by cumulative risk information. We find that participants' cumulative risk judgments are well represented by a bimodal distribution, with a group that severely underestimates the risk and a group that moderately overestimates it. Individuals who underestimate cumulative risks make more risk‐seeking choices compared to those who overestimate cumulative risks. Providing explicit cumulative risk information for relevant time periods, as opposed to annual probabilities, is an inexpensive and effective way to improve both the perception of cumulative risk and the choices people make to protect against that risk.     

Constrained pairwise and center-star sequences alignment problems

This paper considers the minimax regret vertex 2-sink location problem in a dynamic path network with positive edge lengths and uniform edge capacity. Let \(P\) be an undirected path graph of \(n\) vertices, and the weight (initial supply) of every vertex is known as an interval. The problem is to find two vertices \(x\) and \(y\) as two sinks on the path such that all the weights can evacuate to \(x\) and \(y\) with minimum regret of evacuation time in case of an emergency for any possible weight distribution. We present an \(O(n^3\log n)\) time algorithm.     

Risk‐Based Decision Making for Reoccupation of Contaminated Areas Following a Wide‐Area Anthrax Release

This article presents an analysis of postattack response strategies to mitigate the risks of reoccupying contaminated areas following a release of Bacillus anthracis spores (the bacterium responsible for causing anthrax) in an urban setting. The analysis is based on a hypothetical attack scenario in which individuals are exposed to B. anthracis spores during an initial aerosol release and then placed on prophylactic antibiotics that successfully protect them against the initial aerosol exposure. The risk from reoccupying buildings contaminated with spores due to their reaerosolization and inhalation is then evaluated. The response options considered include: decontamination of the buildings, vaccination of individuals reoccupying the buildings, extended evacuation of individuals from the contaminated buildings, and combinations of these options. The study uses a decision tree to estimate the costs and benefits of alternative response strategies across a range of exposure risks. Results for best estimates of model inputs suggest that the most cost‐effective response for high‐risk scenarios (individual chance of infection exceeding 11%) consists of evacuation and building decontamination. For infection risks between 4% and 11%, the preferred option is to evacuate for a short period, vaccinate, and then reoccupy once the vaccine has taken effect. For risks between 0.003% and 4%, the preferred option is to vaccinate only. For risks below 0.003%, none of the mitigation actions have positive expected monetary benefits. A sensitivity analysis indicates that for high‐infection‐likelihood scenarios, vaccination is recommended in the case where decontamination efficacy is less than 99.99%.     

Multiple Health Risk Perception and Information Processing Among African Americans and Whites Living in Poverty

We investigated the risk‐information‐processing behaviors of people living at or near the poverty line. Because significant gaps in health and communication exist among high‐ and low‐income groups, increasing the information seeking and knowledge of poor individuals may help them better understand risks to their health and increase their engagement in health‐protective behaviors. Most earlier studies assessed only a single health risk selected by the researcher, whereas we listed 10 health risks and allowed the respondents to identify the one that they worried about most but took little action to prevent. Using this risk, we tested one pathway inspired by the risk information seeking and processing model to examine predictors of information insufficiency and of systematic processing and extended this pathway to include health‐protective action. A phone survey was conducted of African Americans and whites living in the southern United States with an annual income of ≤$35,000 (N= 431). The results supported the model pathway: worry partially mediated the relationship between perceived risk and information insufficiency, which, in turn, increased systematic processing. In addition, systematic processing increased health‐protective action. Compared with whites and better educated respondents, African Americans and respondents with little education had significantly higher levels of information insufficiency but higher levels of systematic processing and health‐protective action. That systematic processing and knowledge influenced health behavior suggests a potential strategy for reducing health disparities.     

The Dynamics of Occupational Choice: Theory and Evidence

In this paper we provide new empirical and theoretical insights into the dynamics of occupational choice. In the empirical part of the paper we analyse West German time series data on the number of first‐year students in more than 50 fields. We show that this number is cyclical in many fields so that occupational choice is cyclical in many professions. In the theoretical part we develop a model that explains cycles in occupational choice. Unlike other models, it is not based on the unrealistic assumption that occupational choice is independent of the risk of unemployment associated with each occupation.     

Risk of Large‐Scale Evacuation Based on the Effectiveness of Rescue Strategies Under Different Crowd Densities

Crowd density is a key factor that influences the moving characteristics of a large group of people during a large‐scale evacuation. In this article, the macro features of crowd flow and subsequent rescue strategies were considered, and a series of characteristic crowd densities that affect large‐scale people movement, as well as the maximum bearing density when the crowd is extremely congested, were analyzed. On the basis of characteristic crowd densities, the queuing theory was applied to simulate crowd movement. Accordingly, the moving characteristics of the crowd and the effects of typical crowd density—which is viewed as the representation of the crowd's arrival intensity in front of the evacuation passageways—on rescue strategies was studied. Furthermore, a “risk axle of crowd density” is proposed to determine the efficiency of rescue strategies in a large‐scale evacuation, i.e., whether the rescue strategies are able to effectively maintain or improve evacuation efficiency. Finally, through some rational hypotheses for the value of evacuation risk, a three‐dimensional distribution of the evacuation risk is established to illustrate the risk axle of crowd density. This work aims to make some macro, but original, analysis on the risk of large‐scale crowd evacuation from the perspective of the efficiency of rescue strategies.     

Mental Models in Risk Assessment: Informing People About Drugs

One way to communicate about the risks of drugs is through the use of package inserts. The problems associated with this medium of informing patients have been investigated by several researchers who found that people require information about drugs they are using, including extensive risk information, and that they are willing to take this information into account in their usage of drugs. But empirical results also show that people easily misinterpret the information given. A conceptual framework is proposed that might be used for better understanding the cognitive processes involved in such a type of risk assessment and communication. It is based on the idea that people develop, through experience, a mental model of how a drug works, which effects it might produce, that contraindications have to be considered, etc. This mental model is "run" when a specific package insert has been read and a specific question arises such as, for example, whether certain symptoms can be explained as normal or whether they require special attention and action. We argue that the mental model approach offers a useful perspective for examining how people understand package inserts, and consequently for improving their content and design. The approach promises to be equally useful for other aspects of risk analysis that are dependent upon human judgment and decision making, e.g., threat diagnosis and human reliability analysis.