Human Risk Perception Research Articles

Efficiency of Group Movement within Human Risk Perception

A braking index that incorporates the risk perception of human drivers has been developed to estimate how many drivers would brake in a given situation. We used agent simulations to verify whether incorporating the braking index can improve the efficiency of the agents’ movement in the whole space. The completion time and the number of collisions were measured to compare the simple avoidance algorithm without the braking index and the proposed algorithm with it. While a simple avoidance algorithm showed a strong trade-off between the completion time and the number of collisions, the proposed algorithm resulted in an efficient movement with a shorter time and fewer collisions. More efficient movement could be achieved by incorporating human risk perception because the risk of collision with others was individually evaluated according to others’ position and direction, and only as much avoidance as necessary was performed.

Changes in perceived risk and ecosystem services after herbicide use on an aquatic invader

ABSTRACT Biodiversity conservation can entail socially controversial management interventions such as herbicide applications to eradicate aquatic invasive plants from highly productive native ecosystems. This study used a case example of the successful eradication of Alaska’s first aquatic invasive plant, Elodea spp. from two lakes surrounded by waterfront homes with the objective to measure perceived changes in the use of the lakes by local residents. A household survey was conducted with homeowners before and after the application of herbicides to measure public attitudes and human behavior changes related to the use of herbicide. We found fears and subjective expectations of survey respondents did not match the eventually collected objective scientific data on water quality. Also, we measured a significant negative change in lake-related activities over the duration of the management intervention that is smaller compared to the reduced activity level lake residents anticipated before the application of herbicide. Swimming and the consumption of fish caught in the lakes were the most negatively affected ecosystem services. The study showed the indirect and often hidden effects of management interventions on human risk perceptions that can translate to unintended human behavior changes and a reduction in related ecosystem service use. To account for complex social dimensions of controversial resource management interventions, resource managers require information on broad public value trade-offs and perceived risk beyond that which public meetings can provide. In this context, household surveys before and after resource management interventions can offer insights few other approaches can. The potential for more advanced outreach methods is discussed.

Risk assessment based on fault tree analysis and analytic hierarchy process in rural areas of Thailand

Introduction The importance of understanding the factors contributing to road accidents at schools cannot be overstated. This study aims to determine the risk of accidents in situations that could lead to accidents near schools. Methods A total of 10 kindergarten to junior high schools were selected for the study. The research used the Haddon Matrix to classify factors at risk of accidents, risk assessment through fault tree analysis, and the analytic hierarchy process (FTA-AHP) techniques. Fourteen sub-criteria were defined for risk identification, risk probability analysis, and risk assessment of the 10 roads. The likelihood of each event was analyzed using the AHP technique for all schools with an expert choice program. RI (random index) was calculated, and CR (consistency ratio) < 0.10 was considered satisfactory. Results The possibility of human accidents ranked highest in three areas: 1) Risk perception in SC 01, 03, and 02, with probabilities of 69.30%, 61.90%, and 57.4%, respectively. 2) The likelihood of accidents from vehicles/equipment, with the highest probabilities in a) Handling (SC01) at 64.70%, b) Braking (SC07) at 61.90%, and c) Lighting (SC03) at 57.80%. 3) The likelihood of accidents from the environment, with the highest probabilities in 1) driving at excessive speeds in areas SC01, 06, 03, and 09, which were 43.60%, 40.90%, and 40.00%, respectively. Conclusions The impacts of all three main factors were as follows: a) humans had the highest impact in the SC01 area (77.90%), b) vehicles/equipment had the highest impact in the SC01 area (75.90%), and c) the highest environmental impact in the SC01 area was 69.90%. The accident risk assessment revealed the highest risk score in three areas: 1) human risk perception, 2) environment with driving at excessive speeds, and 3) vehicle/equipment, including lighting, braking, and handling.

How does your viewing perspective matter for decision-making with flood risk maps?*

ABSTRACT The globally increasing frequency of flood events highlights the importance of effective flood risk communication. The influence of the viewing perspective of mapped flood events on human risk perception has not yet been a research focus of the geovisualization community. This empirical study aims to fill this gap by investigating how the viewing perspective of flood risk maps, that is, 2D orthographic vs. 2.5D oblique views, influence human flood risk perception and decision-making. Results on how viewing perspective might influence measured risk perception are in line with prior inconclusive research on the utility and usability of adding a third viewing dimension on static maps. Unlike prior research would have suggested, we find that the individual risk attitude of our participants had no direct influence on their risk ratings in the context of this study. With additional empirical evidence on how static 2D and oblique 2.5D hazard maps might influence the public’s risk perception and decision-making, we hope to further inform policy and decision makers on the critical importance of well-designed cartographic displays for effective and efficient hazard and risk communication. We also provide an open-source code repository for making reproducible experiments with our static maps.

Modeling the Impact of Agricultural Mitigation Measures on the Spread of Sharka Disease in Sweet Cherry Orchards.

Sharka is a disease affecting stone fruit trees. It is caused by the Plum pox virus (PPV), with Myzus persicae being one of the most efficient aphid species in transmitting it within and among Prunus orchards. Other agricultural management strategies are also responsible for the spread of disease among trees, such as grafting and pruning. We present a mathematical model of impulsive differential equations to represent the dynamics of Sharka disease in the tree and vector population. We consider three transmission routes: grafting, pruning, and through aphid vectors. Grafting, pruning, and vector control occur as pulses at specific instants. Within the model, human risk perception towards disease influences these agricultural management strategies. Model results show that grafting with infected biological material has a significant impact on the spread of the disease. In addition, detecting infectious symptomatic and asymptomatic trees in the short term is critical to reduce disease spread. Furthermore, vector control to prevent aphid movement between trees is crucial for disease mitigation, as well as implementing awareness campaigns for Sharka disease in agricultural communities that provide a long-term impact on responsible pruning, grafting, and vector control.

Numerical and Visual Representations of Uncertainty Lead to Different Patterns of Decision Making.

Although visualizations are a useful tool for helping people to understand information, they can also have unintended effects on human cognition. This is especially true for uncertain information, which is difficult for people to understand. Prior work has found that different methods of visualizing uncertain information can produce different patterns of decision making from users. However, uncertainty can also be represented via text or numerical information, and few studies have systematically compared these types of representations to visualizations of uncertainty. We present two experiments that compared visual representations of risk (icon arrays) to numerical representations (natural frequencies) in a wildfire evacuation task. Like prior studies, we found that different types of visual cues led to different patterns of decision making. In addition, our comparison of visual and numerical representations of risk found that people were more likely to evacuate when they saw visualizations than when they saw numerical representations. These experiments reinforce the idea that design choices are not neutral: seemingly minor differences in how information is represented can have important impacts on human risk perception and decision making.

Modeling the drivers of oscillations in COVID-19 data on college campuses

PurposeIncorporating human behavior in a disease model can explain the oscillations in COVID-19 data which occur more rapidly than can be explained by variants alone on college campuses. MethodsDampened oscillations emerge by supplementing a simple disease model with a risk assessment function, which depends on the current number of infected individuals in the student population and the institutional public health policies. After accounting for a rapid disease impulse due to social gatherings, we achieve sustained oscillations that follow the trend of 2020/2021 COVID-19 data as reported on the COVID-19 dashboards of US post-secondary institutions. ResultsThis adjustment to the epidemiological model can provide an intuitive way of understanding rapid oscillations based on human risk perception and institutional policies. More risk-averse communities experience lower disease-level equilibria and less oscillations within the system, while communities that are less responsive to changes in the number of infected individuals exhibit larger amplitude and frequency of the oscillations. ConclusionsCommunity risk assessment plays an important role in COVID-19 management in college settings. Improving the ability of individuals to rapidly and conservatively respond to changes in community disease levels may help assist in self-regulating these oscillations to levels well below thresholds for emergency management.

Collateral Effects of Insecticide-Treated Nets on Human and Environmental Safety in an Epidemiological Model for Malaria with Human Risk Perception.

Malaria remains a major health problem in many parts of the world, including Sub-Saharan Africa. Insecticide-treated nets, in combination with other control measures, have been effective in reducing malaria incidence over the past two decades. Nevertheless, there are concerns about improper handling and misuse of nets, producing possible health effects from intoxication and collateral environmental damage. The latter is caused, for instance, from artisanal fishing. We formulate a model of impulsive differential equations to describe the interplay between malaria dynamics, human intoxication, and ecosystem damage; affected by human awareness to these risks and levels of net usage. Our results show that an increase in mosquito net coverage reduces malaria prevalence and increases human intoxications. In addition, a high net coverage significantly reduces the risk perception to disease, naturally increases the awareness for intoxications from net handling, and scarcely increases the risk perception to collateral damage from net fishing. According to our model, campaigns aiming at reducing disease prevalence or intoxications are much more successful than those creating awareness to ecosystem damage. Furthermore, we can observe from our results that introducing closed fishing periods reduces environmental damage more significantly than strategies directed towards increasing the risk perception for net fishing.

A novel fuzzy framework for technology selection of sustainable wastewater treatment plants based on TODIM methodology in developing urban areas

Optimal technology selection of wastewater treatment plants (WWTPs) necessitates the adoption of data-driven scientific approaches that satisfy the sustainability requirements of the urban ecosystem. Such approaches should be able to provide actionable insights to decision makers constrained by factors such as population growth, land scarcity, and loss of functionality of wastewater treatment plants. The framework in this study proposes a hybrid fuzzy multi-criteria decision making (MCDM) model consisting of the analytical hierarchy process (AHP) and the TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) by using alpha cut series which takes into account the risk aversion of decision makers (DMs) to overcome uncertainties of environmental conditions. The literature to date indicates that the study is the first to presents how a systematic decision-making process is approached by interpreting the interaction of criteria for the selection of wastewater treatment technology through the membership function of Prospect Theory. The proposed methodology reveals that the prominent reference criterion manipulates other sub-criteria according to the function of risk-aversion behavior. The fuzzy sets based on alpha cut series are employed to evaluate both the criteria weight and the rank of the alternatives in the decision-making process to obtain compromise solutions under uncertainty. The dominance degrees of the alternatives are achieved by fuzzy TODIM integrated with the fuzzy analytic hierarchy process (FAHP) which deals with the uncertainty of human judgements. According to the ranking results determined by the dominance degree of alternatives, anaerobic–anoxic–oxic (A2O) without pre-clarification was the most effective process in relation to the sludge disposal cost (C25) calculated as reference criteria. The ranking of four full-scale WWTPs in a metropolitan city of an EMEA country based on 24 sub-criteria listed under the four main criteria, namely the dimensions of sustainability, is used as a case study to verify the usefulness of the fuzzy approach. Motivated by the literature gap related to the failure to consider the psychological behavior of DMs in technology selection problem for wastewater treatment, it is discussed how the proposed hybrid MCDM model can be utilized by reflecting human risk perception in wastewater treatment technology selection for developing urban areas.

Features of human perception of risk of infection in a COVID-19 pandemic situation

Современное общество находится на стадии трансформаций, которые в первую очередь основаны на внедрении информационных технологий в нашу жизнь. Они затрагивают абсолютно все аспекты, но хотелось бы рассмотреть влияние информатизации на формирование отношения к здоровью и болезни. Важно понимать, что изучение отношения к здоровью и болезни интересовало ученых на протяжении десятилетий. В настоящее время информационные технологии проникли во все стороны нашей жизни, и, конечно же, затронули такой важный аспект, как отношение к болезни. Эпидемиологическая ситуация сложилась таким образом, что можно было проследить влияние информационных технологий на восприятие человеком угрозы заражения вирусной инфекцией с вероятным летальным исходом. В период самоизоляции, основным официальным источником информации для людей были СМИ. Социальные сети и мессенджеры также внесли значительный вклад в формирование картины мира в восприятии людей. Целью данного исследования было изучение восприятия человеком угрозы заражения вирусной инфекцией с вероятным летальным исходом в период ухудшения эпидемиологической ситуации. В статье приведены данные исследования, проведенного в первый месяц карантинного периода на территории Российской Федерации. Выявлено, что часть населения посредством коммуникации сформировала представление о коронавирусной инфекции COVID-19 как о заболевании, требующем физической дистанции в социальной среде или полной изоляции. При этом треть респондентов не доверяют имеющейся информации, что влечет за собой переживание тревожной неуверенности, дестабилизации эмоционального и соматического состояния в целом.

Assessing urban pluvial flood resilience based on a novel grid-based quantification method that considers human risk perceptions

The growing worldwide threat of urban flooding has stimulated research on flood resilience so that more targeted measures can be implemented in vulnerable areas to mitigate flood losses. During flood events, people generally show different risk perceptions for different inundation areas according to their population density, economic degree, and service function. In this study, the risk perception was quantified into weights and integrated into the resilience calculation to identify areas vulnerable to floods and posing a danger to human life and property. An area in Zhuhai, China, was selected as the research region. With the proposed novel method, the grid-based flood resilience under different rainfall scenarios and different time periods of the day (human work and rest hours) was researched. Moreover, the resilience of different land uses and the impacts of two critical parameters in the resilience equations were also studied. The results indicated that the risk perception related to a given land-use generally changed according to different periods of the day. The overall resilience of the research region was lower when more severe rainstorm occurred in a given time period. The resilience in the work hours was higher than that in the rest hours during the same rainstorm event, indicating that the living/working state of people affected the flood resilience in urban areas. Analyses of the two parameters provided plausibility verification for the parameters and indicated that a slight increase in the height of building doorsills substantially decreased the areas with low and very low resilience. And this decrease effect was more pronounced in the rest hours than the work hours. Results of this study provide an in-depth understanding of urban flood resilience and targeted guidance for engineering construction and flood management.

What People Really Think About Safety around Horses: The Relationship between Risk Perception, Values and Safety Behaviours.

Simple SummaryEquestrians continue to debate what they think, believe, feel and value as superior safety-first principles during human–horse interactions. Some of these varying opinions about how dangerous horses really are; the risk and what actions should be taken to minimise risk, appear to be determined by many different factors. This paper explored what humans say about safety around horses and identified what they perceived as important or less important to stay safe. We examined what elements influence human risk perceptions and behaviours (both positive and negative) during human–horse interactions. Some human safety choices were influenced by financial gain, level of experience, exposure to safety training and disregard for potential human injury as a deterrent for any safety change behavior. A significant percentage of participants accepted risk of human harm around horses with some choosing to take risks for sport achievements and others willing to place their horse’s safety above their own. This paper highlights benefits for the equestrian industry (work or non-work environments) in adopting some safety-first principles and standards, adopted by many high-risk workplaces such as safety training, risk assessment (horse-rider), improved communications and adequate supervision. Moreover, if the equestrian industry chose to implement these tried-and-tested safety principles, this would assist in mitigating risk and potentially reduce human horse-related injury and fatalities.The equestrian industry reports high rates of serious injuries, illness and fatalities when compared to other high-risk sports and work environments. To address these ongoing safety concerns, a greater understanding of the relationship between human risk perception, values and safety behaviours is required. This paper presents results from an international survey that explored relationships between a respondents’ willingness to take risk during daily activities along with, their perceptions of risk and behaviours during horse-related interactions. Respondents’ comments around risk management principles and safety-first inspirations were also analysed. We examined what humans think about hazardous situations or activities and how they managed risk with suitable controls. Analysis identified three important findings. First, safe behaviours around horses were associated with safety training (formal and/or informal). Second, unsafe behaviours around horses were associated with higher levels of equestrian experience as well as income from horse-related work. Finally, findings revealed a general acceptance of danger and imminent injury during horse interactions. This may explain why some respondents de-emphasised or ‘talked-down’ the importance of safety-first principles. In this paper we predominantly reported quantitative findings of respondents self-reported safety behaviours, general and horse-related risk perceptions despite injury or illness. We discussed the benefits of improved safety-first principles like training, risk assessments, rider-horse match with enriched safety communications to enhance risk-mitigation during human–horse interactions.

Composite risk index: the new Safety Performance Indicator of risk exposure

Conceptually, all safety programmes desire accurate safety risk quantification in order to provide a meaningful expression of risk. As there are typically, multiple safety risks associated with a system or event, the quantification of total safety risk is a major challenge. One possible way to define and accept the total safety risk of any system is using the concept of a composite risk estimate. This paper represents development of the new safety performance indicator and overall methodology that could be used to measure the performance of European ATM systems as a whole and its individual entities. It describes the computation of the Composite Risk Index (CRI), logic behind it, its use (on the example EUROCONTROL Member States) and limitations and areas of potential improvement. CRI represents a cumulative risk value calculated aggregating all reported, assessed and severity classified key safety-related incidents to form an index. This measure of risk exposure is based on probability and severity that considers the human perception of equivalent risk. Overall idea behind CRI is that the performance of safety system can be analysed within three important broad categories: the quality of reporting system with reporting entity, measured risks within the system, and human perception of risk.

Content Analysis of Media Reports on Predator Attacks on Humans: Toward an Understanding of Human Risk Perception and Predator Acceptance

GB was funded by the Museo delle Scienze di Trento (Muse), Italy. MMD was funded by a Spanish “Ramon y Cajal” contract (no. RYC-2014-16263). VP was financially supported by the Excellence Project (no. CGL2017-82782-P, financed by the Spanish Ministry of Economy, Industry and Competitiveness, MINECO; the Agencia Estatal de Investigacion; and the Fondo Europeo de Desarrollo Regional of the European Union).

Urban Area Response to Flash Flood–Triggering Rainfall, Featuring Human Behavioral Factors: The Case of 22 October 2015 in Attica, Greece

Abstract Over the past several decades, flash floods that occurred in Attica, Greece, caused serious property and infrastructure damages, disruptions in economic and social activities, and human fatalities. This paper investigated the link between rainfall and flash flood impact during the catastrophic event that affected Attica on 22 October 2015, while also addressing human risk perception and behavior as a response to flash floods. The methodology included the analysis of the space–time correlation of rainfall with the citizens’ calls to the emergency fire services for help, and the statistical analysis of people’s responses to an online behavioral survey. The results designated critical rainfall thresholds associated with flash flood impact in the four most affected subareas of the Attica region. The impact magnitude was found to be associated with the localized accumulated rainfall. Vulnerability factors, namely, population density, geographical, and environmental features, may have contributed to the differences in the impact magnitudes between the examined subareas. The analysis of the survey’s behavioral responses provided insights into peoples’ risk perception and coping responses relative to the space–time distribution of rainfall. The findings of this study were in agreement with the hypothesis that the more severe the rainfall, the higher peoples’ severity assessment and the intensity of emotional response. Deeper feelings of fear and worry were found to be related to more adjustments to the scheduled activities and travels. Additionally, being alert to the upcoming rainfall risk was found to be related to decreased worry and fear and to fewer changes in scheduled activities.

Network-Based Modeling for Characterizing Human Collective Behaviors During Extreme Events

Modeling and predicting human dynamic behaviors in the face of stress and uncertainty can help understand and prevent potential irrational behavior, such as panic buying or evacuations, in the wake of extreme events. However, in terms of the types of events and the distinct human psychological factors, such as risk perception (RP) and emotional intensity (EI), human dynamic behaviors exhibit heterogeneous spatiotemporal characteristics. For example, we can observe different collective responses to the same events by people in different regions, with distinct trends unfolding over time. To provide a computational means for understanding the spatiotemporal characteristics of human behaviors during different types of extreme events, here we present a network-based model that enables us to characterize dynamic behaviors. This model assumes the perspective of a dynamic system, whose behavior is driven by human psychological factors and by the network structure of interactions among individuals. By making use of the available data from Twitter and GoogleTrends, we conduct a case study of human dynamic behavioral and emotional responses to the Japanese earthquake in 2011 in order to examine the effectiveness of our proposed model. With this model, we further assess the impacts of an event by evaluating the interrelationships of human RP and levels of EI in terms of observed collective behaviors. The results demonstrate that human behaviors are subjected to personal observations, experiences, and interactions, which can potentially alter perceptions and magnify the impacts of an event.

A Systematic Review of the Factors Affecting the Cyclone Evacuation Decision Process in Bangladesh

Researchers are investigating a broad spectrum of factors affecting positively and/or negatively the evacuation decision-making process occurring after people at risk receive cyclone warnings and advisories. Previous studies suggest that early warnings themselves do not propagate evacuation processes to be investigated but, rather, that human risk perceptions do so. This in turn encourages the sociopsychological dimensions of risk perception to be evaluated, which must be done within a country’s own cultural context. In applying content analysis here, we review the literature on evacuation decision-making processes during rapidonset hazards, i.e., tropical cyclones, in coastal Bangladesh. We focus on three broad overlapping themes – early warning, risk perception, and evacuation decision-making. Major content-analysis findings suggest that two things – a lack of credibility in early warning messages and an inefficient dissemination process – tend to affect the risk perception of people at risk and are likely to eventually determine the success of evacuation decision-making. Findings also show that different socioeconomic and socio-cultural issues related to risk perception appear to be more influential than formal warning messages in propagating decisions to evacuate during a cyclone. Based on these results, we suggest specific policy recommendations for improving local evacuation efficiency.

Charting unknown waters—On the role of surprise in flood risk assessment and management

AbstractUnexpected incidents, failures, and disasters are abundant in the history of flooding events. In this paper, we introduce the metaphors of terra incognita and terra maligna to illustrate unknown and wicked flood situations, respectively. We argue that surprise is a neglected element in flood risk assessment and management. Two sources of surprise are identified: (1) the complexity of flood risk systems, represented by nonlinearities, interdependencies, and nonstationarities and (2) cognitive biases in human perception and decision making. Flood risk assessment and management are particularly prone to cognitive biases due to the rarity and uniqueness of extremes, and the nature of human risk perception. We reflect on possible approaches to better understanding and reducing the potential for surprise and its adverse consequences which may be supported by conceptually charting maps that separate terra incognita from terra cognita, and terra maligna from terra benigna. We conclude that flood risk assessment and management should account for the potential for surprise and devastating consequences which will require a shift in thinking.

Coxiella burnetii infections in sheep or goats: an opinionated review

Q fever is an almost ubiquitous zoonosis caused by Coxiella burnetii, which is able to infect several animal species, as well as humans. Cattle, sheep and goats are the primary animal reservoirs. In small ruminants, infections are mostly without clinical symptoms, however, abortions and stillbirths can occur, mainly during late pregnancy. Shedding of C. burnetii occurs in feces, milk and, mostly, in placental membranes and birth fluids. During parturition of infected small ruminants, bacteria from birth products become aerosolized. Transmission to humans mainly happens through inhalation of contaminated aerosols. In the last decade, there have been several, sometimes large, human Q fever outbreaks related to sheep and goats. In this review, we describe C. burnetii infections in sheep and goats, including both advantages and disadvantages of available laboratory techniques, as pathology, different serological tests, PCR and culture to detect C. burnetii. Moreover, worldwide prevalences of C. burnetii in small ruminants are described, as well as possibilities for treatment and prevention. Prevention of shedding and subsequent environmental contamination by vaccination of sheep and goats with a phase I vaccine are possible. In addition, compulsory surveillance of C. burnetii in small ruminant farms raises awareness and hygiene measures in farms help to decrease exposure of people to the organism. Finally, this review challenges how to contain an infection of C. burnetii in small ruminants, bearing in mind possible consequences for the human population and probable interference of veterinary strategies, human risk perception and political considerations.

Perception of risk of natural hazards: a hazard mitigation plan framework

A new approach is presented for policy makers to incorporate sociological aspects of human risk perception into their hazard mitigation plans. Previous methods for creating these plans generally used equivalent dollar losses from natural hazard events as the statistic by which to make decisions. Such an approach fails to take into consideration how people view natural hazards, possibly leading to lack of public support and compliance with emergency plans. Such a situation could exacerbate the consequences of a disaster. In this paper, new graphs are presented that combine the typical risk assessment factors, such as death, injury and economic loss, with human perception of risk. The framework includes risk perception by graphing natural hazards on the axes of dread and familiarity. These two variables have been shown in previous studies by social psychologists to explain the largest variance of an individual’s risk perception. Understanding how the public perceives the risk for various natural hazards can assist decision makers in developing and communicating policy decisions.