Risk analysis : an official publication of the Society for Risk Analysis最新文献_第8页

Improving Hurricane Power Outage Prediction Models Through the Inclusion of Local Environmental Factors. 通过纳入局部环境因素改进飓风停电预测模型。

IF 3.8

Risk analysis : an official publication of the Society for Risk Analysis Pub Date : 2018-12-01 Epub Date: 2016-10-25 DOI: 10.1111/risa.12728

D Brent McRoberts, Steven M Quiring, Seth D Guikema

{"title":"Improving Hurricane Power Outage Prediction Models Through the Inclusion of Local Environmental Factors.","authors":"D Brent McRoberts, Steven M Quiring, Seth D Guikema","doi":"10.1111/risa.12728","DOIUrl":"https://doi.org/10.1111/risa.12728","url":null,"abstract":"Tropical cyclones can significantly damage the electrical power system, so an accurate spatiotemporal forecast of outages prior to landfall can help utilities to optimize the power restoration process. The purpose of this article is to enhance the predictive accuracy of the Spatially Generalized Hurricane Outage Prediction Model (SGHOPM) developed by Guikema et al. (2014). In this version of the SGHOPM, we introduce a new two-step prediction procedure and increase the number of predictor variables. The first model step predicts whether or not outages will occur in each location and the second step predicts the number of outages. The SGHOPM environmental variables of Guikema et al. (2014) were limited to the wind characteristics (speed and duration of strong winds) of the tropical cyclones. This version of the model adds elevation, land cover, soil, precipitation, and vegetation characteristics in each location. Our results demonstrate that the use of a new two-step outage prediction model and the inclusion of these additional environmental variables increase the overall accuracy of the SGHOPM by approximately 17%.","PeriodicalId":517072,"journal":{"name":"Risk analysis : an official publication of the Society for Risk Analysis","volume":" ","pages":"2722-2737"},"PeriodicalIF":3.8,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/risa.12728","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39978959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 54

Understanding Fear of Zika: Personal, Interpersonal, and Media Influences. 理解对寨卡病毒的恐惧:个人、人际和媒体的影响。

IF 3.8

Risk analysis : an official publication of the Society for Risk Analysis Pub Date : 2018-12-01 Epub Date: 2018-02-02 DOI: 10.1111/risa.12973

Chun Yang, James Price Dillard, Ruobing Li

引用次数: 46

Communicating Zika Risk: Using Metaphor to Increase Perceived Risk Susceptibility. 传达寨卡病毒风险:使用隐喻增加感知风险易感性。

IF 3.8

Risk analysis : an official publication of the Society for Risk Analysis Pub Date : 2018-12-01 Epub Date: 2018-02-27 DOI: 10.1111/risa.12982

Hang Lu, Jonathon P Schuldt

{"title":"Communicating Zika Risk: Using Metaphor to Increase Perceived Risk Susceptibility.","authors":"Hang Lu, Jonathon P Schuldt","doi":"10.1111/risa.12982","DOIUrl":"https://doi.org/10.1111/risa.12982","url":null,"abstract":"Effectively communicating the risks associated with emerging zoonotic diseases remains an important challenge. Drawing on research into the psychological effects of metaphoric framing, we explore the conditions under which exposure to the \"nation as a body\" metaphor influences perceived risk susceptibility, behavioral intentions, and policy support in the context of Zika virus. In a between-subjects experiment, 354 U.S. adults were randomly assigned to one of four experimental conditions as part of a 2 (severity message: high vs. low) × 2 (U.S. framing: metaphoric vs. literal) design. Results revealed an interaction effect such that metaphoric (vs. literal) framing increased perceived risk susceptibility in the high-severity condition only. Further analyses revealed that perceived risk susceptibility and negative affect mediated the path between the two-way interaction and policy support and behavioral intentions regarding Zika prevention. Overall, these findings complement prior work on the influence of metaphoric framing on risk perceptions, while offering practical insights for risk communicators seeking to communicate about Zika and other zoonotic diseases.","PeriodicalId":517072,"journal":{"name":"Risk analysis : an official publication of the Society for Risk Analysis","volume":" ","pages":"2525-2534"},"PeriodicalIF":3.8,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/risa.12982","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35866884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Chronicling the Risk and Risk Communication by Governmental Officials During the Zika Threat. 记录寨卡病毒威胁期间政府官员的风险和风险沟通。

IF 3.8

Risk analysis : an official publication of the Society for Risk Analysis Pub Date : 2018-12-01 Epub Date: 2018-11-12 DOI: 10.1111/risa.13232

Marin Pearson Allen

引用次数: 6

Erratum. 勘误表。

IF 3.8

Risk analysis : an official publication of the Society for Risk Analysis Pub Date : 2018-12-01 DOI: 10.1111/risa.13237

引用次数: 0

Differences Between Florida and the Rest of the United States in Response to Local Transmission of the Zika Virus: Implications for Future Communication Campaigns. 佛罗里达州与美国其他地区在应对寨卡病毒本地传播方面的差异:对未来传播活动的影响。

IF 3.8

Risk analysis : an official publication of the Society for Risk Analysis Pub Date : 2018-12-01 Epub Date: 2018-05-08 DOI: 10.1111/risa.13010

Kenneth M Winneg, Jo Ellen Stryker, Daniel Romer, Kathleen Hall Jamieson

{"title":"Differences Between Florida and the Rest of the United States in Response to Local Transmission of the Zika Virus: Implications for Future Communication Campaigns.","authors":"Kenneth M Winneg, Jo Ellen Stryker, Daniel Romer, Kathleen Hall Jamieson","doi":"10.1111/risa.13010","DOIUrl":"https://doi.org/10.1111/risa.13010","url":null,"abstract":"For those at risk for Zika virus infection, prevention requires an approach that includes individual, interpersonal, and community-level support for behavior change. In August 2016, the announcement of local Zika transmission in Florida provided an opportunity to determine whether Zika-related knowledge, attitudes, and behaviors might be affected differentially in Florida compared to the rest of the nation. From August 8-October 3, 2016, we conducted nationally representative weekly surveys (N = 12,236), oversampling Florida residents, measuring Zika virus news exposure, knowledge about transmission and prevention of the infection, and attitudes and behaviors toward prevention. We tested two classes of models: those focused on individual Zika risk perceptions (e.g., protection motivation theory) and one focused on community action beyond those directly at risk (social consensus model). Analyses assessed differences between Florida and the rest of the nation by survey week. Consistent with both models, Floridians demonstrated significantly higher levels of perceived susceptibility and knowledge, more positive attitudes toward Zika virus prevention, and higher likelihood of engaging in protective behavior than non-Floridians. Consistent with theories of individual risk perception, response was greater among respondents who saw themselves at risk of infection. However, consistent with the SCM, irrespective of personal risk, response was greater among Floridians. Nevertheless, more than half of the public took no direct action to prevent the spread of Zika. Communities at increased risk for a novel infection such as Zika may quickly acquire Zika-related knowledge, attitudes, and behavior, but large-scale community-wide response might be difficult without further community-level public education.","PeriodicalId":517072,"journal":{"name":"Risk analysis : an official publication of the Society for Risk Analysis","volume":" ","pages":"2546-2560"},"PeriodicalIF":3.8,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/risa.13010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36082059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Retweeting Risk Communication: The Role of Threat and Efficacy. 转发风险沟通:威胁和有效性的作用。

IF 3.8

Risk analysis : an official publication of the Society for Risk Analysis Pub Date : 2018-12-01 Epub Date: 2018-08-06 DOI: 10.1111/risa.13140

Sarah C Vos, Jeannette Sutton, Yue Yu, Scott Leo Renshaw, Michele K Olson, C Ben Gibson, Carter T Butts

{"title":"Retweeting Risk Communication: The Role of Threat and Efficacy.","authors":"Sarah C Vos, Jeannette Sutton, Yue Yu, Scott Leo Renshaw, Michele K Olson, C Ben Gibson, Carter T Butts","doi":"10.1111/risa.13140","DOIUrl":"https://doi.org/10.1111/risa.13140","url":null,"abstract":"Social media platforms like Twitter and Facebook provide risk communicators with the opportunity to quickly reach their constituents at the time of an emerging infectious disease. On these platforms, messages gain exposure through message passing (called \"sharing\" on Facebook and \"retweeting\" on Twitter). This raises the question of how to optimize risk messages for diffusion across networks and, as a result, increase message exposure. In this study we add to this growing body of research by identifying message-level strategies to increase message passing during high-ambiguity events. In addition, we draw on the extended parallel process model to examine how threat and efficacy information influence the passing of Zika risk messages. In August 2016, we collected 1,409 Twitter messages about Zika sent by U.S. public health agencies' accounts. Using content analysis methods, we identified intrinsic message features and then analyzed the influence of those features, the account sending the message, the network surrounding the account, and the saliency of Zika as a topic, using negative binomial regression. The results suggest that severity and efficacy information increase how frequently messages get passed on to others. Drawing on the results of this study, previous research on message passing, and diffusion theories, we identify a framework for risk communication on social media. This framework includes four key variables that influence message passing and identifies a core set of message strategies, including message timing, to increase exposure to risk messages on social media during high-ambiguity events.","PeriodicalId":517072,"journal":{"name":"Risk analysis : an official publication of the Society for Risk Analysis","volume":" ","pages":"2580-2598"},"PeriodicalIF":3.8,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/risa.13140","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36372071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 42

Sequential Refined Partitioning for Probabilistic Dependence Assessment. 概率依赖性评估的顺序精细划分。

IF 3.8

Risk analysis : an official publication of the Society for Risk Analysis Pub Date : 2018-12-01 Epub Date: 2018-08-08 DOI: 10.1111/risa.13162

Christoph Werner, Tim Bedford, John Quigley

{"title":"Sequential Refined Partitioning for Probabilistic Dependence Assessment.","authors":"Christoph Werner, Tim Bedford, John Quigley","doi":"10.1111/risa.13162","DOIUrl":"https://doi.org/10.1111/risa.13162","url":null,"abstract":"Modeling dependence probabilistically is crucial for many applications in risk assessment and decision making under uncertainty. Neglecting dependence between multivariate uncertainties can distort model output and prevent a proper understanding of the overall risk. Whenever relevant data for quantifying and modeling dependence between uncertain variables are lacking, expert judgment might be sought to assess a joint distribution. Key challenges for the use of expert judgment for dependence modeling are over- and underspecification. An expert can provide assessments that are infeasible, i.e., not consistent with any probability distribution (overspecification), and on the other hand, without making very restrictive parametric assumptions an expert cannot fully define a probability distribution (underspecification). The sequential refined partitioning method addresses over- and underspecification while allowing for flexibility about which part of a joint distribution is assessed and its level of detail. Potential overspecification is avoided by ensuring low cognitive complexity for experts through eliciting single conditioning sets and by offering feasible assessment ranges. The feasible range of any (sequential) assessment can be derived by solving a linear programming problem. Underspecification is addressed by modeling the density of directly and indirectly assessed distribution parts as minimally informative given their constraints. Hence, our method allows for modeling the whole distribution feasibly and in accordance with experts' information. A nonparametric way of assessing and modeling dependence flexibly in such detail has not been presented in the expert judgment literature for probabilistic dependence models so far. We provide an example of assessing terrorism risk in insurance underwriting.","PeriodicalId":517072,"journal":{"name":"Risk analysis : an official publication of the Society for Risk Analysis","volume":" ","pages":"2683-2702"},"PeriodicalIF":3.8,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/risa.13162","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36382509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Frequency of Risk-Related News Media Messages in 2016 Coverage of Zika Virus. 2016年寨卡病毒报道中与风险相关的新闻媒体信息频率。

IF 3.8

Risk analysis : an official publication of the Society for Risk Analysis Pub Date : 2018-12-01 Epub Date: 2018-01-03 DOI: 10.1111/risa.12961

Tara Kirk Sell, Crystal Watson, Diane Meyer, Marissa Kronk, Sanjana Ravi, Laura E Pechta, Keri M Lubell, Dale A Rose

{"title":"Frequency of Risk-Related News Media Messages in 2016 Coverage of Zika Virus.","authors":"Tara Kirk Sell, Crystal Watson, Diane Meyer, Marissa Kronk, Sanjana Ravi, Laura E Pechta, Keri M Lubell, Dale A Rose","doi":"10.1111/risa.12961","DOIUrl":"https://doi.org/10.1111/risa.12961","url":null,"abstract":"News media plays a large role in the information the public receives during an infectious disease outbreak, and may influence public knowledge and perceptions of risk. This study analyzed and described the content of U.S. news media coverage of Zika virus and Zika response during 2016. A random selection of 800 Zika-related news stories from 25 print and television news sources was analyzed. The study examined 24 different messages that appeared in news media articles and characterized them using theories of risk perception as messages with characteristics that could increase perception of risk (risk-elevating messages; n = 14), messages that could decrease perception of risk (risk-minimizing messages; n = 8), or messages about travel or testing guidance (n = 2). Overall, 96% of news stories in the study sample contained at least one or more risk-elevating message(s) and 61% contained risk-minimizing message(s). The frequency of many messages changed after local transmission was confirmed in Florida, and differed between sources in locations with or without local transmission in 2016. Forty percent of news stories included messages about negative potential outcomes of Zika virus infection without mentioning ways to reduce risk. Findings from this study may help inform current federal, state, and local Zika responses by offering a detailed analysis of how news media are covering the outbreak and response activities as well as identifying specific messages appearing more or less frequently than intended. Findings identifying the types of messages that require greater emphasis may also assist public health communicators in responding more effectively to future outbreaks.","PeriodicalId":517072,"journal":{"name":"Risk analysis : an official publication of the Society for Risk Analysis","volume":" ","pages":"2514-2524"},"PeriodicalIF":3.8,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/risa.12961","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35720045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 28

Rethinking Social Amplification of Risk: Social Media and Zika in Three Languages. 重新思考风险的社会放大:三种语言的社交媒体和寨卡病毒。

IF 3.8

Risk analysis : an official publication of the Society for Risk Analysis Pub Date : 2018-12-01 Epub Date: 2018-11-08 DOI: 10.1111/risa.13228

Christopher D Wirz, Michael A Xenos, Dominique Brossard, Dietram Scheufele, Jennifer H Chung, Luisa Massarani

{"title":"Rethinking Social Amplification of Risk: Social Media and Zika in Three Languages.","authors":"Christopher D Wirz, Michael A Xenos, Dominique Brossard, Dietram Scheufele, Jennifer H Chung, Luisa Massarani","doi":"10.1111/risa.13228","DOIUrl":"https://doi.org/10.1111/risa.13228","url":null,"abstract":"Using the Zika outbreak as a context of inquiry, this study examines how assigning blame on social media relates to the social amplification of risk framework (SARF). Past research has discussed the relationship between the SARF and traditional mass media, but the role of social media platforms in amplification or attenuation of risk perceptions remains understudied. Moreover, the communication and perceptions of Zika-related risk are not limited to discussions in English. To capture conversations in languages spoken by affected countries, this study combines data in English, Spanish, and Portuguese. To better understand the assignment of blame and perceptions of risk in new media environments, we looked at three different facets of conversations surrounding Zika on Facebook and Twitter: the prominence of blame in each language, how specific groups were discussed throughout the Zika outbreak, and the sentiment expressed about genetically engineered (GE) mosquitoes. We combined machine learning with human coding to analyze public discourse in all three languages. We found differences between languages and platforms in the amount of blame assigned to different groups. We also found more negative sentiments expressed about GE mosquitoes on Facebook than on Twitter. These meaningful differences only emerge from analyses across the three different languages and platforms, pointing to the importance of multilingual approaches for risk communication research. Specific recommendations for outbreak and risk communication practitioners are also discussed.","PeriodicalId":517072,"journal":{"name":"Risk analysis : an official publication of the Society for Risk Analysis","volume":" ","pages":"2599-2624"},"PeriodicalIF":3.8,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/risa.13228","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36659507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 62