Abstracts (PDF file, 1.8MB) - Society for Risk Analysis

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SRA 2013 Annual Meeting Abstracts M4-F.2 Jardine, CG*; Driedger, SM; UNIVERSITY OF ALBERTA; cindy.jardine@ualberta.ca Communicating Environmental Health Risk Uncertainty: A Systematic Review of the Literature Communicating the uncertainty associated with environmental health risks is a continuing challenge within risk communication theory and practice. A systematic review of quantitative and qualitative empirical research published between 1985 and 2008 was conducted to consolidate and integrate the knowledge currently available in this area. The review involved searching more than 30 databases, representing various health-related and communication disciplines, using multiple combinations of keywords and synonyms. In addition, a search was made of key journals (such as Risk Analysis and Journal of Risk Research) and 109 key risk communication authors. Of the initial 29,499 potential articles identified, 28 met the inclusion criteria (22 of which were empirical evaluations conducted since the year 2000). Lessons learned for best practice include: (1) the importance of describing the nature, source, and consequences of the uncertainty; (2) the need to avoid vague or ambiguous descriptions of uncertainty; (3) the influence of different risk communication formats on understanding and uptake of uncertainty information; (4) the importance of the spokesperson; (5) how to work with the media to avoid inaccurate information being put ‘into the information void’; and (6) the critical importance of communicating risk uncertainty at the beginning of a developing risk issue. Notable gaps in the literature include the lack of research on different cultural understandings of uncertainty and the impact of new channels and sources of information (such as social media) on communicating uncertainty. The findings from this review will provide insights on needs for risk communication research in this area that will help guide new paths forward. T4-G.4 Jenkins, F*; Rowan, KE; George Mason University; jenkins.fred@epa.gov Ecological risk communication and environmental values: Predicting public interest in participating in federal rulemaking concerning pesticide risk Two impediments to public participation in regulatory decision making regarding ecological risks may be complex findings and frequent failure to make ecological risk relevant to the public’s concerns. Consequently, this study used the mental models approach to risk communication to develop pesticide ecological risk assessment materials accessible to lay audiences. Thirty-six university students were interviewed to determine their understanding of a pesticide’s risk to non-target plants and animals. Their understanding was compared to scientific characterizations of this hazard. Results showed participants were not familiar with 21 of 29 elements found in characterizations of pesticide ecological risk from scientific literature. These results were used to design an account of pesticide effects accessible to lay audiences. Participants (180) were randomly assigned to a treatment or control conditions and asked to complete an environmental attitudes survey. Those in the treatment condition received a more accessible account of a pesticide’s ecological risk than did those in the control group. Results showed those who endorsed pro-environmental attitudes were likely to be interested in participating in a hypothetical US EPA rule-making effort concerning a pesticide’s ecological risks. This association was significant at the .05 level; however, there was no association between condition assignment and interest in participating in US EPA rule making. This set of findings suggests that environmental values guide interest in participating in environmental rule-making but leaves open the question of whether knowledge about ecological pesticide risk is associated with interest among stakeholders in participating in rule making about ecological risk. The authors discuss factors that may affect lay interest in managing ecological risks, especially hazards apt to have implications for plants and animals near dwellings. T3-E.4 Jensen , E; Bellin, C; Embry, M*; Gaborek, B; Lander, D; Tanir, JY; Wolf, D; Zaleski, R; Dow Corning Corporation ; membry@hesiglobal.org Water Chemicals Case Study Using the RISK21 Tiered Exposure Framework As part of the approach for advancing risk assessment in the 21st century, the HESI RISK21 project considered a case study focused on health risk assessment for chemicals that may be found in surface water, and therefore raise the potential for human exposure. The problem was formulated such that a risk manager would have ONE year to decide whether risk management is required for any or all chemicals on a large list of potential drinking water contaminants. For simplicity, the only route of exposure considered was via consumption of drinking water. This case study highlighted rapid screening methods for risk prioritization, identifying readily available sources of suitable data for use in risk assessment, and challenges in considering cumulative exposure assessment. The RISK21 case study participants identified key questions to address and parameters to inform the assessment, and described assessment results progressing through the tiers with increasing levels of complexity. Another important output was a graphical presentation of exposure and hazard that could be useful in communicating risk to decision makers. M2-A.4 Jessup, A*; Sertkaya, A; Morgan, K; Department of Health and Human Services/OASPE; amber.jessup@hhs.gov A novel approach to attributing illness to food using consumption data and expert elicitation Policy analysts are often asked to answer questions where there are no published studies or published studies are only peripherally related to the policy question. Often, the policy questions are complex and data needed to provide a useful answer are limited, conflicting, unavailable, or (as is sometimes the case) unobtainable. Further, seldom are analysts given large budgets in time or money to find answers. Meta-analysis and systematic reviews are methods to combine results from a body of established studies. Expert elicitation synthesizes expert opinions when data are lacking, but is typically limited to characterizing uncertainty around generally accepted parameters. Where data and studies are completely lacking, however, innovative methods must be applied. Information linking foodborne illness (FBI) cases to the source of the illness and/or specific food vehicle with sufficient specificity to guide policy is one such area. Previous food attribution research has used microbiological approaches (e.g., microbial sub-typing), epidemiological approaches (e.g., the analysis of outbreak and other surveillance data), and expert elicitation approaches (Pires et al., 2009). None of these studies, however, appear to have produced sufficiently detailed information to produce groupings of foods that are homogenous with respect to risk. We examine the challenges of answering scientific questions needed for policy analysis, moving beyond characterizing uncertainty. First, we discuss the applicability of different research methods (i.e., expert elicitation [EE], meta-analysis, and systematic reviews to the objective of generating FBI attribution rates by highly disaggregated food categories. Next, we develop and apply a hybrid novel method combining EE and food consumption data to estimate FBI cases by highly disaggregated food categories. December 8-11, 2013 - Baltimore, MD
SRA 2013 Annual Meeting Abstracts M3-E.2 Jiao, W; Frey, HC*; North Carolina State University; frey@ncsu.edu Measurement and Comparison of PM2.5 AND CO Microenvironmental Exposure Concentrations for Selected Transportation Modes Daily commutes may contribute disproportionately to overall daily exposure to urban air pollutants such as fine particulate matter (PM2.5) and carbon monoxide (CO). The on-road and near-road microenvironments are of concern because of proximity to on-road traffic emissions. A field data collection study design was developed based on factors that may affect variability in in-transit concentration, including transportation mode, time of day, traffic volume, weather, vehicle ventilation conditions, road geometry and traffic control, traffic vehicle mix, and proximity to intersections. PM2.5 and CO concentrations were measured and compared across pedestrian, bus, and car modes during lunchtime and afternoon rush hour within a three-week time period on pre-selected round trip routes in Raleigh, NC. Variability in the transportation mode concentration ratios of PM2.5 and CO is quantified. Factors affecting variability in PM2.5 and CO concentrations are identified. The average pedestrian concentration is compared with fixed site monitor (FSM) data to determine if FSM is an appropriate surrogate for near-road concentration. Preliminary results indicate that on-road or near-road microenvironmental concentrations are sensitive to transportation mode, traffic volume, and proximity to onroad emission sources. In general, pedestrians experienced the highest PM2.5 concentrations among all measured transportation modes. Peaks in pedestrian PM2.5 concentration are typically associated with a passing truck. In comparison, the average PM2.5 concentration in-car is the lowest because the selected ventilation conditions helped to prevent ingress of particles. A positive association was found between traffic counts and average CO concentrations. Field studies such as this are needed to develop data for input to population-based stochastic exposure simulation models to more accurately predict transportation mode exposure concentrations. M3-E.1 Jiao, W*; Frey, HC; North Carolina State University; wjiao@ncsu.edu Comparison of predicted exposures versus ambient fine particulate matter concentrations Persons 65 and older are particularly susceptible to adverse effects from PM2.5 exposure. Using the Stochastic Human Exposure and Dose Simulation model for Particulate Matter (SHEDS-PM), distributions of inter-individual variability in daily PM2.5 exposures are estimated for Bronx, Queens and New York Counties in the New York City area for the years 2002 to 2006 based on ambient concentration, air exchange rate, penetration factor, deposition rate, indoor emission sources, census data, and activity diary data. Three research questions are addressed: (1) how much is variability in estimated daily average exposure to ambient air pollution influenced by variability in ambient concentration compared to other exposure factors?; (2) what is the inter-annual variation in daily average exposure?; and (3) what key factors and values of these key factors lead to high exposure? In comparison with CMAQ input ambient concentrations, daily average exposure estimates have more variability. Variation in estimated exposure to pollutants ambient origin is mostly affected by variation in ambient concentration, air exchange rate, and human activity patterns. Estimated daily average exposure to ambient PM2.5 is about 30 to 40 percent less than the ambient concentration. Seasonal differences in estimated exposure are mainly caused by seasonal variation in ACH. There was relatively little estimated inter-annual variation in the daily average exposure to concentration ratio (Ea/C), since factors affecting exposure such as ACH, housing type and activity patterns were assumed to be relatively stable across years. The distribution of inter-individual variability in the Ea/C ratio can be used to identify highly exposed subpopulations to help inform risk management strategies and to provide advisory information to the public. T4-H.3 John, RS*; Rosoff, HR; University of Southern California; richardj@usc.edu Validation of Adversary Utility Assessment by Proxy Most adversaries are not available for or willing to allow for direct elicitation. Such adversaries have a strong interest in countering or foiling others; these instances range from criminal organizations, terrorist organizations, corporations engage seeking to gain a market advantage, political organizations seeking to promote their views and hindering rivals from making progress, and sports rivalries. In such cases it is necessary to construct a representation of preferences using information that is known about adversary motivations, objectives, and beliefs. Such information includes a variety of sources, including past adversary behavior, public statements by the adversary, adversary web sites, and intelligence. An adversary objectives hierarchy and MAU model based on this information can be constructed by proxy, using judgments from an adversary values expert (AVE). The construction of value models by proxy raises the question of whether such models can accurately capture adversary preferences using only secondary and tertiary sources. There is no published research to date on the validity of utility models constructed by proxy. In this paper, we report two validation studies comparing MAU models for two different politically active non-profit organizations that utilize civil disobedience to achieve political objectives. In both cases, we constructed an objectives hierarchy and MAU model using AVEs who have access to publicly available information about the organizations’ motives, objectives, and beliefs, but no direct contact with organization leaders. We then independently compared these MAU model parameters and constructed preferences to those based on direct assessment from a representative of the organization. In both cases, we demonstrate good convergence between the proxy model and the model assessed by direct contact with a decision maker. The proxy MAU models provided a complete and accurate representation of the organizations’ values, including objectives, trade-offs, risk attitudes, and beliefs about consequence impacts. M4-H.3 John, RS*; Scurich, N; University of Southern California and University of California, Irivine; richardj@usc.edu Public perceptions and trade-offs related to randomized security schedules Although there are theoretical advantages to randomized security strategies, and they have been adopted in several major areas, there has been no research evaluating the public’s perception of such measures. Perhaps the most challenging hurdle for randomized security strategies is the potential for perceived unfairness by the public. Randomization is clumpy, and random selections for search will often appear nonrandom to an individual who observes some relatively small number of searches while waiting in line. Individuals observing random searches may exhibit a confirmation bias that magnifies the perception of unfair search patterns in short sequences due to (1) biased observation seeking to confirm hypothesized inequities, and (2) biased interpretation and recollection of observed searches. In short, the perception of safety can be as important as the reality of safety. Likewise, the perception of fairness can weigh as heavily as the reality of fairness. If randomized security schedules are perceived as inefficacious and/or unfair, potential patrons might protest their use and pursue alternatives that actually increase the net societal risk. In the present experiment, over 200 respondents were asked to make choices between attending a venue that employed a traditional (i.e., search everyone) or a random (i.e., a probability of being searched) security schedule. The probability of detecting contraband was manipulated (i.e., 1/10; 1/4; 1/2) but equivalent between the two schedule types. In general, participants were indifferent to either security schedule, regardless of the probability of detection. The randomized schedule was deemed more convenient, but the traditional schedule was considered fairer and safer, suggesting a perceived trade-off between safety, fairness, and convenience. There were no differences between traditional and random search in terms of effectiveness or deterrence. December 8-11, 2013 - Baltimore, MD
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Abstracts (PDF file, 1.8MB) - Society for Risk Analysis

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