Society For Risk Analysis Annual Meeting 2016
Session Schedule & Abstracts
* Disclaimer: All presentations represent the views of the authors, and not the organizations that support their research. Please apply the standard disclaimer that any opinions, findings, and conclusions or recommendations in abstracts, posters, and presentations at the meeting are those of the authors and do not necessarily reflect the views of any other organization or agency. Meeting attendees and authors should be aware that this disclaimer is intended to apply to all abstracts contained in this document. Authors who wish to emphasize this disclaimer should do so in their presentation or poster. In an effort to make the abstracts as concise as possible and easy for meeting participants to read, the abstracts have been formatted such that they exclude references to papers, affiliations, and/or funding sources. Authors who wish to provide attendees with this information should do so in their presentation or poster.
|Chair(s): Amber Jessup|
Sponsored by EBA Specialty Group and Society for Benefit-Cost Analysis
|Quantification of the economic impacts of health policies is challenging. In this symposium, the first presentation considers how to estimate willingness to pay for health information and warnings and the impact of this information on price and quantity demanded. The next three presentations address the quantification of health impacts. The first of these shows the utility of creating a test bed of metrics for relating summary measures of population health to each other. The second discusses using survey experiments to reconsider how to quantify the effects of risk reduction and costs on human welfare. The last presentation addresses the challenge of a lack of willingness to pay estimates for avoiding nonfatal health conditions by using studies that estimate willingness to pay per quality adjusted life year to develop a function that can be used to estimate willingness to pay per quality adjusted life year.Co-sponsored by the Society for Benefit-Cost Analysis|
T3-D.1 1:30 pm The value of enhancing consumer confidence in the food supply. Hammitt JK*, Hoffmann S; Harvard University (Center for Risk Analysis) firstname.lastname@example.org|
Abstract: Conventional estimates of the value of risk reductions are based on the change in probability-weighted consequences. For example, conventional estimates of the value of enhanced food safety multiply the reductions in probability of illness or death by values per statistical case. This model implies the value of a small reduction in the probability of a specific harm is proportional to the change in probability. Moreover, it omits a number of factors that may influence an individualâ€™s valuation of a risk reduction. In the context of programs to enhance the safety of the food supply, we consider whether some of the omitted factors should be considered when evaluating policies, and if so how their magnitudes can be estimated. Examples of omitted factors include nonlinear probability weighting (as in prospect theory), certainty effects (reduction vs. elimination of a risk), ambiguity aversion, anxiety while bearing risk, cognitive dissonance and biasing of beliefs to reduce anxiety, decision costs, flexibility to try new foods, and reductions in precautionary behaviors (e.g., food preparation, avoiding unfamiliar foods). The analysis has implications for valuing risk reductions for other contexts, including other consumer products.
T3-D.2 1:49 pm Exploring Quantitative links between Competing Summaries of Population Health Impact. Brand KP*, Campino-Ferrada E; Telfer School of Management, University of Ottawa email@example.com|
Abstract: A wide spectrum of seemingly disparate metrics have been favored by different disciplinary traditions as the yardsticks against which to "measure off" predicted population health impacts. While the qualitative co-relationships between these competing metrics are arguably well appreciated (e.g., many metrics display understandable a positive rank order co-relationships) the quantitative explication of many of these relationships awaits. To the extent that these competing metrics represent summaries of the same basic data (age-specific population, death, and morbidity incidence counts), algebraic relationships for translating among them (even if only approximate) ought to be obtainable. Moreover such algebraic relationships are bound to be of service; for one thing, enabling estimates to be translated from one metric to another. We have sought out such relationships (often approximate) using theory (e.g., well-worn insights from the Demography literature) and empirical data in tandem. In this paper we augment the existing human mortality data-base with a tool that renders stylized (and readily manipulated) age-patterns of cause specific mortality. Our purpose is to create a large and systematically indexed test-bed (of mortality rate, age, profiles) for examining/refining the behavior of posited algebraic relationships for relating competing summary measures to each other. We demonstrate utility of such a test-bed, applying it to the specific case of relating Health Expectancy and Health Gap based summaries of mortality impacts. A quantitative relationship is revealed and its performance is characterized with careful attention given to its contingency upon age patterns in mortality.
T3-D.3 2:10 pm Benefits of air pollution abatement across gender and socioeconomic position. Cifuentes LA*, Borchers N; Pontificia Universidad Católica de Chile firstname.lastname@example.org|
Abstract: Social benefits from air pollution abatement are often used as a justification for emission control measures. In a benefit cost analysis decision framework, these benefits are weighted against the costs of control, with little consideration for distributional issues, i.e. which part of the population bears the costs and which one the benefits. This work looks at the differences in the benefits from reductions in health impacts from air pollution, and their relative importance. We look at the differences across gender and socioeconomic position. We investigate the importance of differences in health effects base incidence rates, of the unit risk, of different exposure reductions, and of differences of willingness to pay to avoid health effects. Data for the analysis comes from analyses of air pollution abatement conducted in four Chilean cities that have different socio-demographic characteristics. The results show that unitary benefits can vary by as much as factor of 2. Without getting into ethical considerations, we discuss the implications of these results for designing air pollution abatement programs and measures.
T3-D.4 2:30 pm Racial Disparities in Access to Community Water Service in Wake County, North Carolina: Public Health Risks and Costs of Interventions. MacDonald Gibson J*, Stillo F; University of North Carolina at Chapel Hill email@example.com|
Abstract: Over the last 100 years, installation of community water systems substantially decreased US waterborne diseases. However, throughout the South, some communities were excluded from these systems as a result of racial segregation, and some of the resulting disparities persist. The magnitude of exclusion risks, water quality in affected areas, health implications, and costs of connecting to nearby municipal water utilities are not well understood. This presentation will summarize four years of research to characterize the locations of affected communities, their drinking water quality, potential health risks, and costs of and barriers to extending municipal water service in Wake County, NCâ€™s second-largest county by population and location of the state capital. The research has included analysis of tax parcel and census data, water quality testing, population intervention modeling using hospital emergency department data, development of preliminary engineering plans for extending municipal water pipes, and open-ended interviews. Overall, our analysis has documented significant and persistent exclusion from municipal water service with associated negative health consequences. Odds of exclusion from municipal water service increase by 4% for every 10% increase in a census blockâ€™s African American population proportion. Water testing in 57 affected homes found 49% tested positive for total coliform bacteria. Our population intervention model estimated that 21% (95% CI 14-31%) of 110 annual emergency department visits for acute gastrointestinal illness among approximately 3,800 affected county residents are attributable to exclusion from municipal water service. Cost is a major barrier to extending water service, with per-household costs of approximately $20,000 and disagreements over who should bear those costs. Overall, our research suggests the need for interventions to improve water quality and protect health in these communities.
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