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��ࡱ�>�� u �r�{�bjbj�n�n2��a��a�\ ��""��8�le��ql��p�p�p�p�p�p�p$2s��u<�p��p��4�qwww�f��pw��pwww��l��w�p�q0�qw$v^$vww�0$v�qmt��w��p�pu��q��$v��"qs: risk analysis volume 44, issue 3, march 2024 1. title: i think, therefore i act, revisited: building a stronger foundation for risk analysis authors: joseph �rvai, alex segr� cohen, lauren lutzke, caitlin drummond otten abstract: actively open-minded thinking (aot) is a thinking style in which people engaged in judgment and decision-making actively seek out and then evaluate information in a manner that is intentionally disconnected from their prior beliefs and motivations and in line with self-perceptions of autonomy. actively open-minded thinkers have been observed to make both more accurate judgments about the magnitude of risks and more evidence-based decisions under uncertainty in a wide range of situations such as climate change and politics. in addition, actively open-minded thinkers functioning in domains where they lack a desired level of knowledge are open to �outsourcing� the job of critical reasoning thinking to credible experts; in other words, they are better able to gauge who is trustworthy and then rely on the insights of these trustworthy others to help them reach a conclusion. we report results from a follow-up to research previously published in risk analysis that confirms these tenets in the context of covid-19. we then extend these results to offer a series of recommendations for strengthening the process and outcomes of risk analysis: leveraging the latent norm of autonomy and personal agency that underpins aot, activating or engaging with approaches to reasoning�such as decision structuring�that are in line with aot, and working upstream and downstream of risk analysis to establish aot as a norm of its own. 2. title: exploring public risk perceptions of microplastics: findings from a cross-national qualitative interview study among german and italian citizens authors: robin janzik, severine koch, giorgia zamariola, domagoj vrbos, mathew p. white, sabine pahl, natalie berger abstract: microplastics are receiving growing attention in the public debate, while the scientific assessment of risks of microplastics to ecological and human health is still ongoing. previous studies suggest concerns among the general public with country-specific differences. however, little is known about the reasoning underlying these concerns. by conducting qualitative interviews with german (n = 15) and italian citizens (n = 15), this study adopted a cross-national perspective to investigate which concepts shape citizens� perceptions of microplastics. a qualitative content analysis was used, with coding categories and subcategories developed inductively. results showed that interviewees formed assumptions around microplastics despite own uncertainties, transferred knowledge from macro- to microplastics, and used the concepts of accumulation and dose�response relationship to make sense of the topic. moreover, they saw the domains of human health and the environment as intertwined and expressed helplessness when discussing solutions to the microplastics issue. many themes on the topic were similar in both samples, but there were also some differences. for instance, whereas italian participants talked about marine-related microplastics, german participants talked about airborne sources; also, german participants tended to recognize more strongly the actions their country was putting in place to address the problem. these findings underscore the need for proactive risk communication despite remaining gaps in scientific risk assessment. beyond providing technical information, communicators should consider the reasoning behind risk perception on microplastics and address scientific uncertainty as well as the interconnectedness between the domains of human health and the environment. 3. title: a risk�risk trade-off assessment of climate-induced mortality risk changes authors: irene mussio, susan chilton, darren duxbury, jytte seested nielsen abstract: the impact of climate change on human health was identified as a priority for the un cop26 conference. in this article, we consider climate-induced changes to mortality risks and how to incorporate these formally in the policy appraisal process. in the united kingdom (uk), the value of statistical life (vsl) is used to monetarize the benefits of policies to reduce mortality risks but it remains an open, empirical question as to whether the current vsl (�2.14 million per fatality prevented, december 2021 values) for traffic accidents should be applied in other contexts without any modification and particularly for extreme weather event fatalities. using a representative sample of the uk population, we aim to estimate and better understand the trade-offs people make when comparing mortality risks, drawing on psychological insights from construal level and regulatory focus theories. we design a stated preference survey using a relative valuation framework with nonmonetary, risk�risk trade-off questions between extreme weather event and traffic accident mortality risks. we find evidence of an extreme weather event risk premium of 1.2�1.6 (implying a climate-related vsl of �2.52��3.41 million). we also find that participants who are psychologically close to climate change (based on construal level theory), weigh reducing extreme weather event mortality risks almost two times that of reducing traffic accident mortality risks. 4. title: from believing in climate change to adapting to climate change: the role of risk perception and efficacy beliefs authors: anne m. van valkengoed, goda perlaviciute, linda steg abstract: are people more inclined to adapt to climate change if they believe that climate change is real, caused by human behavior, and/or brings negative consequences? previous studies provided inconclusive results on the relationship between climate change perceptions and adaptation behavior. using a longitudinal approach, we examined whether risk perception, self-efficacy, and outcome efficacy play a role in how and when climate change perceptions are associated with adaptation to pluvial flooding and heat stress in the netherlands. as expected, stronger climate change perceptions were associated with stronger perceptions of climate-related risks, which in turn lead to stronger intentions to implement adaptation measures. yet, neither climate change perceptions nor risk perception were associated with whether people had actually implemented adaptation measures during a 1-year period. contrary to common assumptions in the literature, higher levels of perceived self-efficacy and outcome efficacy did not strengthen the relations between climate change perceptions and adaptation intentions and behavior. rather, higher levels of self-efficacy and outcome efficacy were directly related to stronger intentions to take adaptive measures and taking those measures within a period of 1 year. exploratory analyses offered initial support for a sequential model where climate change perceptions lead to higher levels of perceptions of specific climate-related risks, which in turn lead to stronger self-efficacy and outcome efficacy, ultimately increasing adaptation intentions, but not actual behavior. strategies to promote adaptation behavior could aim to remove behavioral barriers to increase self-efficacy, and strengthen outcome efficacy, enabling people to act on their climate change perceptions. 5. title: climate risk and renewable energy technological innovation: an institutional environment perspective authors: jinyu chen, xianfeng luo, qian ding abstract: to explore whether climate risk (cr) affects renewable energy technological innovation (reti) and its boundary conditions, this study examines the relationship between cr and reti as moderated by institutional environment. based on panel data of 60 countries for the period 2000�2019, we show that cr is not conducive to reti, and that its negative marginal impact shows an inverted u-shaped trend with the improvement of reti. heterogeneity analysis shows that floods and storms have the greatest negative impacts on reti, and that innovations in solar and wind energy technologies are more vulnerable to the adverse shocks of cr. furthermore, cr has a greater adverse effect on reti in developing countries than in developed countries. however, the institutional environment, especially the economic institutional environment, can work to mitigate the negative effect of cr on reti. our findings not only enrich the research on the economic consequences of cr but also provide effective ways to mitigate the adverse impact of cr on reti from the perspective of institutional environment. 6. title: evolutionary game analysis for multi-level collaborative governance under public crisis in china: from a value perception perspective authors: yingxin chen, xin liu, pandu r. tadikamalla, mingming qu, yiting wang abstract: in a risk society, the survival and development of humans are facing threats of complex and severe public crisis events. public participation in collaborative governance (cg) of public crisis events is increasingly recognized as an important direction for the reform of the current and future emergency management system. previous studies of cg have mainly focused on the macro level and ignored to address micro-level discussions of the behavioral strategy evolution of stakeholders. from a fresh value perception perspective, this study constructs an evolutionary game model to clarify the evolution mechanism of multi-level emergency cg. first, the value perception model is built based on prospect theory and mental accounting to optimize the traditional game matrix. second, the evolutionary stability is analyzed to solve the system evolution law. finally, numerical simulation is conducted in the case of heilongjiang province, a main region of food and energy supply in china. results showed that (1) the cg game system has a complex evolutionary path; (2) the behavior of game players is affected by perceived incomes and perceived costs; (3) compared with the reference value and the risk aversion coefficient of income accounts, game players are more sensitive to that of cost accounts; (4) enhancing the perceived value of public psychological satisfaction and government reputation is helpful for the long-term construction of cg. overall, this study aims to highlight the potential utility of value perception in promoting effective implementations of cg and to provide new insights for the development of cg in china and other countries. 7. title: epidemic propagation risk study with effective fractal dimension authors: fuzhong nian, fangfang li abstract: in this article, the risk of epidemic transmission on complex networks is studied from the perspective of effective fractal dimension. first, we introduce the method of calculating the effective fractal dimension db${d}_b$ of the network by taking a scale free network as an example. second, we propose the construction method of administrative fractal network and calculate the db${d}_b$. using the classical susceptible exposed infectious removed (seir) infectious disease model, we simulate the virus propagation process on the administrative fractal network. the results show that the larger the db${d}_b$ is, the higher the risk of virus transmission is. later, we proposed five parameters p, m, b, f, and d, where p denotes population mobility, m denotes geographical distance, b denotes gdp, f denotes db${d}_b$, and d denotes population density. the new epidemic growth index formula i=(p (1"m) b)(f d)$i = {({p ({1 - m}) b})}^{({f d})}$ was obtained by combining these five parameters, and the validity of i in epidemic transmission risk assessment was demonstrated by parameter sensitivity analysis and reliability analysis. finally, we also confirmed the reliability of the seir dynamic transmission model in simulating early covid 19 transmission trends and the ability of timely quarantine measures to effectively control the spread of the epidemic. 8. title: social power and perceived risk of contagious disease: high power leads to lower risk estimation of catching covid-19 authors: heng li abstract: an accurate estimation of covid-19 contagion risk is important in terms of understanding the dynamic of disease transmission and health behavior. previous research has documented that many health-related variables influence the risk estimation of communicable diseases. we expanded the current understanding by investigating whether health-irrelevant factors�such as one's sense of power�can have a systematic and consequential impact on perceived risks of catching the coronavirus. based on the social distance theory of power, we propose that people in a higher power position develop a greater sense of social distance than those in a lower power position, which may in turn predispose the former to think that they are less likely to catch contagious diseases from other people. in study 1, we provided correlational evidence that the personal sense of power was associated with the underestimation of contagion probability in chinese university students. in study 2, we established the causal relationship between power and concerns for contagious diseases in nonstudent adults and revealed the mediating role of social distance in the observed effect. overall, these results, for the first time, indicate that power can elevate perceived social distance, exerting downstreaming effects on health cognition during the covid-19 pandemic. 9. title: does the exponential wells�riley model provide a good fit for human coronavirus and rhinovirus? a comparison of four dose�response models based on human challenge data authors: amar aganovic, edin kadric abstract: the risk assessments during the covid-19 pandemic were primarily based on dose�response models derived from the pooled datasets for infection of animals susceptible to sars-cov. despite similarities, differences in susceptibility between animals and humans exist for respiratory viruses. the two most commonly used dose�response models for calculating the infection risk of respiratory viruses are the exponential and the stirling approximated �-poisson (bp) models. the modified version of the one-parameter exponential model or the wells riley model was almost solely used for infection risk assessments during the pandemic. still, the two-parameter (� and �) stirling approximated bp model is often recommended compared to the exponential dose response model due to its flexibility. however, the stirling approximation restricts this model to the general rules of � k" 1 and � j" �, and these conditions are very often violated. to refrain from these requirements, we tested a novel bp model by using the laplace approximation of the kummer hypergeometric function instead of the conservative stirling approximation. the datasets of human respiratory airborne viruses available in the literature for human coronavirus (hcov-229e) and human rhinovirus (hrv-16 and hrv-39) are used to compare the four dose�response models. based on goodness-of-fit criteria, the exponential model was the best fitting model for the hcov-229e (k = 0.054) and for hrv-39 datasets (k = 1.0), whereas the laplace approximated bp model followed by the exact and stirling approximated bp models are preferred for both the hrv-16 (� = 0.152 and � = 0.021 for laplace bp) and the hrv-16 and hrv-39 pooled datasets (� = 0.2247 and � = 0.0215 for laplace bp). 10. title: trends in reported illness due to poultry- and nonpoultry associated salmonella serotypes; united states 1996�2019 authors: mark r. powell abstract: retrospective review is a key to designing effective food safety measures. despite the reported reduction of salmonella prevalence in poultry products, there has not been a concomitant reduction of the overall incidence of salmonella illnesses reported to the us foodborne diseases active surveillance network (foodnet) since 1996. however, there have been significant annual trends among salmonella serotypes. this analysis examines trends in the reported incidence of illness due to poultry- and nonpoultry associated salmonella serotypes. overall, the findings indicate declining trends in illness due to the poultry-associated serotypes and increasing trends in illness due to salmonella serotypes not associated with poultry. 11. title: to profile or not? authors: yael deutsch, arieh gavious abstract: developing effective inspection processes at border crossings in order to identify violators within large groups of mostly innocent people is an important and difficult task. passenger profiling is a tool used to deal with this task, but it raises many public concerns and ongoing debates about its usefulness. in this article, we study whether profiling is helpful, how it should be used to maximize its effectiveness, and how social utility is affected by its use. we consider two game models that take place at a crowded border crossing, where passengers are divided into different groups based on their risk profile. the models involve three players: the defender, the attacker, and the passenger recruited to engage in a violation. the defender decides on an inspection policy for every group of passengers. the attacker decides from which group to recruit a single passenger as a violator. the recruited passenger has private knowledge about the likelihood that she/he will engage in the violation or not. we solve the game models and compare their solutions with those of a no-profiling inspection policy. we then study a model with four players, including a social planner who is concerned about social utility, and chooses the defender's inspection resources and policy. we show that the announced profiling policy provides the highest payoffs to the defender. regarding social utility, profiling is always better than no profiling. however, there are cases where the unannounced profiling policy provides the most social utility. 12. title: mission risk control via joint optimization of sampling and abort decisions authors: li yang, fanping wei, qingan qiu abstract: information-driven mission abort is an effective way to control the failure risk of safety-critical systems during mission executions. we investigate the optimal sampling and mission abort decisions of partially observable safety-critical systems, where the underlying system health state can only be revealed by sampling. in contrast to previous studies, we employ partial health information to jointly determine: (a) whether to execute sampling, and (b) when to abort the mission in a dynamic manner, so as to minimize the expected total cost incurred by sampling, mission failure, and system malfunction. dynamic sampling and mission abort policies are devised following the belief state, whose optimization model is cast into the framework of a partially observable markov decision process. some structural insights with regard to the value function, control limit selection, and optimality existence are presented. the performance of the proposed sampling and abort policy is tested by numerical experiments, which are proved to outperform other heuristic abort policies in mission loss control. 13. title: power outage prediction using data streams: an adaptive ensemble learning approach with a feature- and performance-based weighting mechanism authors: elnaz kabir, seth d. guikema, steven m. quiring abstract: a wide variety of weather conditions, from windstorms to prolonged heat events, can substantially impact power systems, posing many risks and inconveniences due to power outages. accurately estimating the probability distribution of the number of customers without power using data about the power utility system and environmental and weather conditions can help utilities restore power more quickly and efficiently. however, the critical shortcoming of current models lies in the difficulties of handling (i) data streams and (ii) model uncertainty due to combining data from various weather events. accordingly, this article proposes an adaptive ensemble learning algorithm for data streams, which deploys a feature- and performance-based weighting mechanism to adaptively combine outputs from multiple competitive base learners. as a proof of concept, we use a large, real data set of daily customer interruptions to develop the first adaptive all-weather outage prediction model using data streams. we benchmark several approaches to demonstrate the advantage of our approach in offering more accurate probabilistic predictions. the results show that the proposed algorithm reduces the probabilistic predictions' error of the base learners between 4% and 22% with an average of 8%, which also result in substantially more accurate point predictions. the improvement made by our algorithm is enhanced as we exchange base learners with simpler models. 14. title: a semiautomated risk assessment method for consumer products authors: nohel zaman, david m. goldberg, richard j. gruss, alan s. abrahams abstract: in this study, we develop a model that assesses product risk using online reviews from amazon.com. we first identify unique words and phrases capable of identifying hazards. second, we estimate risk severity using hazard type weights and risk likelihood using total reviews as a proxy for sales volume. in addition, we obtain expert assessments of product hazard risk (risk likelihood and severity) from a sample of high- and low-risk consumer products identified by a computerized risk assessment model we have developed. third, we assess the validity of our computerized product risk assessment scoring model by utilizing the experts� survey responses. we find that our model is especially consistent with expert judgments of hazard likelihood but not as consistent with expert judgments of 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�h�s�5�ojqj^jo(h)w�5�ojqjo(h[h)w�ojqj^jo(h�loh�loojqj^jhih)w�ojqj^jo(h$?�h)w�5�ojqj^jh[h)w�5�ojqj^jo(h[�5�ojqj^jh[hmw�5�ojqj^jh�loh�lo5�ojqj^jhmw�5�ojqj^jo(hmw�hmw�5�ojqj^jh�"�h)w�5�ojqj^jh)w�5�ojqj^jo(�e�e�e�e�}�~��èl�m�n�p�q�s�t�v�w�z�{��ƹ�֝��tf^z^z^z^zfh�bfjh�bfuh#�hj<ojqj^jo(h[�h[�ojqj^jhih)w�ojqj^jo(h$?�h)w�5�ojqj^jh$?�h �5�ojqj^jo(h[�5�ojqj^jhmw�h �5�ojqj^jh[h �5�ojqj^juh[�h[�5�ojqj^jh �5�ojqj^jo(h �h �5�ojqj^jvacuate or social distance? modeling the influence of threat perceptions on hurricane evacuation in a dual-threat environment authors: hao-che wu, haley murphy, alex greer, lauren clay abstract: this study investigates how different risk predictors influenced households� evacuation decisions during a dual-threat event (hurricane laura and covid-19 pandemic). the protective action decision model (padm) literature indicates that perceived threat variables are the most influential variables that drive evacuation decisions. this study applies the padm to investigate a dual-threat disaster that has conflicting protective action recommendations. given the novelty, scale, span, impact, and messaging around covid-19, it is crucial to see how hurricanes along the gulf coast�a hazard addressed seasonally by residents with mostly consistent protective action messaging�produce different reactions in residents in this pandemic context. household survey data were collected during early 2021 using a disproportionate stratified sampling procedure to include households located in mandatory and voluntary evacuation areas across the coastal counties in texas and parishes in louisiana that were affected by hurricane laura. structural equation modeling was used to identify the relationships between perceived threats and evacuation decisions. the findings suggest affective risk perceptions strongly affected cognitive risk perceptions (crps). notably, hurricane and covid-19 crps are significant predictors of hurricane evacuation decisions in different ways. hurricane 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