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��ࡱ�>�� u �r�h�bjbj�n�n2��a��a_[ ��""��8�le��ql��p�p�p�p�p�p�p$s��u<�pi��p��4tqooo�.��po��pooo��]"m��(o�pjq0�qo�uj�uoo�0�u�imh��o��p�pu��q��u��"qs: risk analysis volume 43, issue 7, july 2023 1. title: multilevel causal attributions on transboundary risk: effects on attributions of responsibility, psychological distance, and policy support authors: hye kyung kim, yungwook kim abstract: this study used two randomized experiments in a prospective design (study 1 n = 297, study 2 n = 296) to examine how multilevel causal attribution dimensions (internal vs. external to an individual or a country) shape domestic and foreign policy support to counter transboundary risk. results from study 1 and 2 showed that external-country (vs. internal-country) causal attribution reduced perceptions of internal-country attributions of responsibility, which had a cross-lagged effect on support for domestic-industry policies to mitigate the risk. in contrast, perceptions of external-country attributions of responsibility increased support for foreign policies in a 2-week follow up. this study offers theoretical insights into the demarcation of multilevel causal attribution dimensions in studying media framing effects. it also highlights some important causal mechanisms of how media frames shape public support for policies aimed at transboundary risk mitigation. 2. title: reliability but not bias: developing a scale to measure preferred channels for risk information during the covid pandemic authors: kenneth a. lachlan, christine gilbert abstract: to develop a new measure of preferred sources for risk information, two studies asked respondents to indicate what channels they were reliant on for information about covid-19, from 25 news channels ranging across the political spectrum. unexpectedly, dependencies clustered around level of reliability rather than the political orientation of the news channel. in other words, each cluster included media channels from both the left and right side of the political spectrum, while dependencies clustered into sources that varied by the degree to which their content is reliable. participants who turned to lower reliability channels indicated lower risk perceptions, less accurate probability estimations, reduced vaccination intentions, and lower protective behavioral intentions. those inclined to use higher reliability channels indicated higher risk perceptions, more accurate probability estimations, increased vaccination intentions, and higher protective behavioral intentions. these relationships are discussed in terms of implications for our understanding of source reliance and risk perception, information sufficiency, and implications for both future research and public health interventions. 3. title: trust, confidence, familiarity, and support for land-based recirculating aquaculture facilities authors: branden b. johnson, laura n. rickard abstract: surveys in three u.s. localities (n = 523) with proposed or existing land-based aquaculture facilities probed trust's relationship with perceived net benefits and public intentions to cooperate with siting of this novel technology. the trust, confidence, and cooperation (tcc) model posits that shared values shape willingness to be vulnerable to others (trust), while past performance shapes certainty that others will behave as expected (confidence). trust affects confidence given moral outweighs performance information, possibly varying by familiarity. other research suggests that trust shapes benefit and risk perceptions, which drive cooperation (defined here by potentially observable behavior: voting on siting, trying to influence government decisions directly or through citizen groups, and buying or eating facility fish). confirmatory factor analyses suggested that a two-factor model fit the trust/confidence measures better than a one-factor model or a two-factor model without inter-factor correlation, indicating (despite a strong association of trust and confidence) that they are empirically distinct. path analyses suggested that trust had stronger direct effects on cooperation than did confidence, reflecting the tcc notion that moral information underlying trust judgments is more influential, and stronger indirect effects through benefit-risk judgments. model fit was better than if the benefit-risk mediator was omitted. trust in government had a small direct effect on cooperation and confidence, but a large effect on trust in the corporation, and model fit was much worse if any of these paths was omitted. low familiarity with the project lowered both model fit and trust�confidence association. we discuss implications for risk analysis theory and practice. 4. title: risk heatmaps as visual displays: opening movie studios after the covid-19 shutdown authors: victor l. rodriguez, baruch fischhoff, alexander l. davis abstract: upon shutting down operations in early 2020 due to the covid-19 pandemic, the movie industry assembled teams of experts to help develop guidelines for returning to operation. it resulted in a joint report, the safe way forward, which was created in consultation with union members and provided the basis for negotiations with the studios. a centerpiece of the report was a set of heatmaps displaying sars-cov-2 risks for a shoot, as a function of testing rate, community infection prevalence, community transmission rate (r0), and risk measure (either expected number of cases or probability of at least one case). we develop and demonstrate a methodology for evaluating such complex displays, in terms of how well they inform potential users, in this case, workers deciding whether the risks of a shoot are acceptable. we ask whether individuals making hypothetical return-to-work decisions can (a) read display entries, (b) compare display entries, and (c) make inferences based on display entries. generally speaking, respondents recruited through the amazon mturk platform could interpret the display information accurately and make coherent decisions, suggesting that heatmaps can communicate complex risks to lay audiences. although these heatmaps were created for practical, rather than theoretical, purposes, these results provide partial support for theoretical accounts of visual information processing and identify challenges in applying them to complex settings. 5. title: media exposure, threat processing, and mitigation behaviors in gulf coast residents facing the co-occurring threats of covid-19 and hurricanes authors: dana rose garfin, rebecca r. thompson, gabrielle wong-parodi abstract: the 2020 hurricane season threatened millions of americans concurrently grappling with covid-19. processes guiding individual-level mitigation for these conceptually distinct threats, one novel and chronic (covid-19), the other familiar and episodic (hurricanes), are unknown. theories of health protective behaviors suggest that inputs from external stimuli (e.g., traditional and social media) lead to threat processing, including perceived efficacy (self- and response) and perceived threat (susceptibility and severity), guiding mitigation behavior. we surveyed a representative sample of florida and texas residents (n = 1846) between april 14, 2020 and april 27, 2020; many had previous hurricane exposure; all were previously assessed between september 8, 2017 and september 11, 2017. using preregistered analyses, two generalized structural equation models tested direct and indirect effects of media exposure (traditional media, social media) on self-reported (1) covid-19 mitigation (handwashing, mask-wearing, social distancing) and (2) hurricane mitigation (preparation behaviors), as mediated through perceived efficacy (self- and response) and perceived threat (susceptibility and severity). self-efficacy and response efficacy were associated with social distancing (p = .002), handwashing, mask-wearing, and hurricane preparation (ps < 0.001). perceived susceptibility was positively associated with social distancing (p = 0.017) and hurricane preparation (p < 0.001). perceived severity was positively associated with social distancing (p < 0.001). traditional media exhibited indirect effects on covid-19 mitigation through increased response efficacy (ps < 0.05), and to a lesser extent self-efficacy (p < 0.05), and on hurricane preparation through increased self-efficacy and response efficacy and perceived susceptibility (ps < 0.05). social media did not exhibit indirect effects on covid-19 or hurricane mitigation. communications targeting efficacy and susceptibility may encourage mitigation behavior; research should explore how social media campaigns can more effectively target threat processing, guiding protective actions. 6. title: do actions reduce perceived risk? a longitudinal analysis of the relationship between risk perception and actions in response to forest disturbance in colorado authors: hua qin, jamie vickery, hannah brenkert-smith, barituka bekee, yanu prasetyo abstract: as residents living in hazard-prone areas face on-going environmental threats, the actions they take to mitigate such risks are likely motivated by various factors. whereas risk perception has been considered a key determinant of related behavioral responses, little is known about how risk mitigation actions influence subsequent perceived risk. in other words, do actions to prevent or mitigate risk reduce risk perception? this longitudinal study considers the dynamic relationships between risk perception and risk-mitigating behavior in the context of forest disturbance in north-central colorado. based on panel survey data collected in 2007 and 2018, the results provide a first look at changes in perceived forest risks as they relate to individual and community actions in response to an extensive mountain pine beetle outbreak. analysis revealed that the perception of direct forest risks (forest fire and falling trees) increased, whereas indirect forest risk perception (concern on broader threats to local community) decreased across the two study phases. higher individual or community activeness (level of actions) was associated with subsequent reductions in perceived forest fire risk, smaller increases in direct risk perception, and larger decreases in indirect risk perception. these findings contribute insights into the complex risk reappraisal process in forest hazard contexts, with direct implications for risk communication and management strategies. 7. title: designing optimal food safety monitoring schemes using bayesian network and integer programming: the case of monitoring dioxins and dl-pcbs authors: z. wang, h. j. van der fels-klerx, a. g. j. m. oude lansink abstract: efficient food safety monitoring should achieve optimal resource allocation. in this article, a methodology is presented to optimize the use of resources for food safety monitoring aimed at identifying noncompliant samples and estimating background level of hazards in food products. a bayesian network (bn) model and an optimization model were combined in a single framework. the framework was applied to monitoring dioxins and dioxin-like polychlorinated biphenyls (dl-pcbs) in primary animal-derived food products in the netherlands. the bn model was built using a national dataset with monitoring results of dioxins and dl-pcbs in animal-derived food products over a 10-year period (2008�2017). these data were used to estimate the probability of detecting suspect samples with dioxins and dl-pcbs levels above preset thresholds, given certain sample conditions. the results of the bn model were then inserted into the optimization model to compute an optimal monitoring scheme. model estimates showed that the probability of dioxins and dl-pcbs exceeding threshold limits was higher in laying hen eggs and sheep meat than in other animal-derived food (except deer meat). compared with the monitoring scheme used in the netherlands in 2018, the optimal monitoring scheme would save around 10,000 eur per year. this could be obtained by reallocating monitoring resources from products with lower probability of dioxin and dl-pcbs exceeding threshold limits (e.g., pig meat) to products with higher probability (e.g., bovine animal meat), and by shifting sample collection from the last quarter of the year toward the first three quarters of the year. 8. title: does federal flood hazard mitigation assistance affect community rating system participation? authors: eugene frimpong, allison c. reilly, deb niemeier abstract: with the inexorable march of climate change, increased flooding is inevitable. understanding the feedback between federal flood mitigation policies and the ways in which local governments build flood resilience is a significant gap in the literature. in particular, the effect that federal flood mitigation grants have on the intensity of local flood mitigation is nonexistent. this work measures flood risk mitigation by using the level of participation in fema's community rating system (crs). communities that participate in the crs and undertake mitigation are awarded points; more points imply a higher level of participation. since its inception in 1990, crs communities have received considerably more federal pre-disaster flood mitigation grants compared to non-crs communities. this study assesses the effect of federal pre-disaster flood mitigation grants on the level of participation in the crs program. we use data on hazard mitigation assistance programs and crs participation data between 2010 and 2015. we link these data to flood risk and socioeconomic information. our results indicate (i) federal pre-disaster flood mitigation grants do not appear to significantly influence the level of crs participation, (ii) the effect of flood risk and socioeconomic factors on the level of crs participation are mixed, and (iii) the current level of crs participation is influenced by the previous level of crs participation, which is not tied to federal pre-disaster flood mitigation grant. these findings add to the growing discussions on the drivers and barriers of local flood risk mitigation. 9. title: risk assessment for handling hazardous substances within the european industry: available methodologies and research streams authors: mirco peron, simone arena, nicola paltrinieri, fabio sgarbossa, georgios boustras abstract: after the seveso disaster occurred more than 40 years ago, there has been an increasing awareness of the potential impacts that similar accident events can occur in a wide range of process establishments, where the handling and production of hazardous substances pose a real threat to society and the environment. in these industrial sites denominated �seveso sites,� the urgent need for an effective strategy emerged markedly to handle hazardous activities and to ensure safe conditions. since then, the main challenging research issues have focused on how to prevent such accident events and how to mitigate their consequences leading to the development of many risk assessment methodologies. in recent years, researchers and practitioners have tried to provide useful overviews of the existing risk assessment methodologies proposing several reviews. however, these reviews are not exhaustive because they are either dated or focus only on one specific topic (e.g., liquefied natural gas, domino effect, etc.). this work aims to overcome the limitations of the current reviews by providing an up-to-date and comprehensive overview of the risk assessment methodologies for handling hazardous substances within the european industry. in particular, we have focused on the current techniques for hazards and accident scenarios identification, as well as probability and consequence analyses for both onshore and offshore installations. thus, we have identified the research streams that have characterized the activities of researchers and practitioners over the years, and we have then presented and discussed the different risk assessment methodologies available concerning the research stream that they belong to. 10. title: online patient feedback as a safety valve: an automated language analysis of unnoticed and unresolved safety incidents authors: alex gillespie, tom w. reader abstract: safety reporting systems are widely used in healthcare to identify risks to patient safety. but, their effectiveness is undermined if staff do not notice or report incidents. patients, however, might observe and report these overlooked incidents because they experience the consequences, are highly motivated, and independent of the organization. online patient feedback may be especially valuable because it is a channel of reporting that allows patients to report without fear of consequence (e.g., anonymously). harnessing this potential is challenging because online feedback is unstructured and lacks demonstrable validity and added value. accordingly, we developed an automated language analysis method for measuring the likelihood of patient-reported safety incidents in online patient feedback. feedback from patients and families (n = 146,685, words = 22,191,427, years = 2013�2019) about acute nhs trusts (hospital conglomerates; n = 134) in england were analyzed. the automated measure had good precision (0.69) and excellent recall (0.98) in identifying incidents; was independent of staff-reported incidents (r = "0.04 to 0.19); and was associated with hospital-level mortality rates (z = 3.87; p < 0.001). the identified safety incidents were often reported as unnoticed (89%) or unresolved (21%), suggesting that patients use online platforms to give visibility to safety concerns they believe have been missed or ignored. online stakeholder feedback is akin to a safety valve; being independent and unconstrained it provides an outlet for reporting safety issues that may have been unnoticed or unresolved within formal channels. 11. title: flood risk mapping and analysis using an integrated framework of machine learning models and analytic hierarchy process authors: quynh duy bui, chinh luu, sy hung mai, hang thi ha, huong thu ta, binh thai pham abstract: in this study, a new approach of machine learning (ml) models integrated with the analytic hierarchy process (ahp) method was proposed to develop a holistic flood risk assessment map. flood susceptibility maps were created using ml techniques. ahp was utilized to combine flood vulnerability and exposure criteria. we selected quang binh province of vietnam as a case study and collected available data, including 696 flooding locations of historical flooding events in 2007, 2010, 2016, and 2020; and flood influencing factors of elevation, slope, curvature, flow direction, flow accumulation, distance from river, river density, land cover, geology, and rainfall. these data were used to construct training and testing datasets. the susceptibility models were validated and compared using statistical techniques. an integrated flood risk assessment framework was proposed to incorporate flood hazard (flood susceptibility), flood exposure (distance from river, land use, population density, and rainfall), and flood vulnerability (poverty rate, number of freshwater stations, road density, number of schools, and healthcare facilities). model validation suggested that deep learning has the best performance of auc = 0.984 compared with other ensemble models of multiboostab ensemble (0.958), random subspace ensemble (0.962), and credal decision tree (auc = 0.918). the final flood risk map shows 5075 ha (0.63%) in extremely high risk, 47,955 ha (5.95%) in high-risk, 40,460 ha (5.02%) in medium risk, 431,908 ha (53.55%) in low risk areas, and 281,127 ha (34.86%) in very low risk. the present study highlights that the integration of ml models and ahp is a promising framework for mapping flood risks in flood-prone areas. 12. title: development and application of a dose�response model for elizabethkingia spp authors: kara dean, natalie coaster, kyana young, jade mitchell abstract: elizabethkingia spp. are common environmental pathogens responsible for infections in more vulnerable populations. although the exposure routes of concern are not well understood, some hospital-associated outbreaks have indicated possible waterborne transmission. in order to facilitate quantitative microbial risk assessment (qmra) for elizabethkingia spp., this study fit dose�response models to frog and mice datasets that evaluated intramuscular and intraperitoneal exposure to elizabethkingia spp. the frog datasets could be pooled, and the exact beta-poisson model was the best fitting model with optimized parameters � = 0.52 and � = 86,351. using the exact beta-poisson model, the dose of elizabethkingia miricola resulting in a 50% morbidity response (ld50) was estimated to be approximately 237,000 cfu. the model developed herein was used to estimate the probability of infection for a hospital patient under a modeled exposure scenario involving a contaminated medical device and reported elizabethkingia spp. concentrations isolated from hospital sinks after an outbreak. the median exposure dose was approximately 3 cfu/insertion event, and the corresponding median risk of infection was 3.4e-05. the median risk estimated in this case study was lower than the 3% attack rate observed in a previous outbreak, however, there are noted gaps pertaining to the possible concentrations of elizabethkingia spp. in tap water and the most likely exposure routes. this is the first dose�response model developed for elizabethkingia spp. thus enabling future risk assessments to help determine levels of risk and potential effective risk management strategies. 13. title: using a grey relational analysis in an improved grunow�finke assessment tool to detect unnatural epidemics authors: mengxuan lin, hui chen, leili jia, mingjuan yang, shaofu qiu, hongbin song, ligui wang, tao zheng abstract: the grunow�finke epidemiological assessment tool (gft) has several limitations in its ability to differentiate between natural and man-made epidemics. our study aimed to improve the gft and analyze historical epidemics to validate the model. using a gray relational analysis (gra), we improved the gft by revising the existing standards and adding five new standards. we then removed the artificial weights and final decision threshold. finally, by using typically unnatural epidemic events as references, we used the gra to calculate the unnatural probability and obtain assessment results. using the advanced tool, we conducted retrospective and case analyses to test its performance. in the validation set of 13 historical epidemics, unnatural and natural epidemics were divided into two categories near the unnatural probability of 45%, showing evident differences (p < 0.01) and an ass "&') 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factors on these outcomes effectively. �nn/ffnċ� 14. title: disaster risk reduction by douglas paton. edward elgar, northampton, ma, usa, 2022. isbn 978 1 80392 047 4, 150 pp., references and index, $23.87 in paperback authors: michael greenberg abstract: the article reviews the book advanced in&�b�d�v��)�*�7�9�:�;�=�>�@�a�c�d�g�h��ŷ��zvzvzvzv�hojhouh�/hj<ojqj^jo(h�14ojqj^juh�14h�14ojqj^jhih)w�ojqj^jo(h$?�h)w�5�ojqj^jh[h)w�5�ojqj^jo(hmw�hmw�5�ojqj^jh[hmw�5�ojqj^jh�14h�145�ojqj^jtroduction to disaster risk reduction� by douglas paton. 01�82p��. ��a!�"�#��$��%��s��s2�� 0@p`p��2(�� 0@p`p�� 0@p`p�� 0@p`p�� 0@p`p�� 0@p`p�� 0@p`p��8x�v~�� 0@�� 0@�� 0@�� 0@�� 0@�� 0@�� 0@�� 0@�� 0@�� 0@�� 0@�� 0@�� 0@�� 0@pj_hmh nhsh thj`��jck�e$1$a$ cjkh_hajmh nhsh th$a ��$؞��k=�w[sobi��bnf�h�&��ŝ�]�6��ҩ��n=��in��a7��qb&>!"�h [�� lx�z)��w�v�og�%�ţ|8mă#�/��8��'��=��q�u*��c�`c�w{�d6��/�[��yl��%�� n� 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