Quantitative Methods for Comparative Risk and Policy Analysis.* E. Y. Wong, R. A. Ponce, S. Farrow, S. M. Bartell, R. C. Lee, and E. M. Faustman; University of Washington, Carnegie Mellon University, University of California, Davis, and University of Calgary
There is increasing interest in the use of quantitative risk analysis with benefit-cost and cost-effectiveness methods to evaluate environmental health policymaking and perform comparative analyses. However, the combined use of these methods has revealed deficiencies in the available methods, and the lack of useful analytical frameworks currently constrains the utility of comparative risk and policy analyses (President’s Commission on Risk Assessment, 1997). A principal issue in comparative risk analysis is the lack of common performance metrics, particularly when performing comparative analyses of regulations across health endpoints (e.g., cancer and non-cancer effects or risk-benefit analysis) and estimation of cumulative risk, whether from exposure to single agents with multiple health impacts or from exposure to mixtures. We propose a general quantitative framework and examine assumptions required for performing comparative analysis. We also review existing and proposed metrics for evaluating policies designed to protect public health from environmental exposures and identify their strengths and weaknesses with respect to their use in a general framework. Case studies will be presented that highlight the importance of appropriate age specific measures and methods to accurately reflect potential impacts across life stages. A significant emphasis of the presentation will be in how measures of uncertainty, variability, and irreversibility are expressed in each metric. Through this analysis, we hope to generate discussion regarding the data requirements, analytical approaches, and assumptions required for general models to be used in comparative risk and policy analysis.
Supported by the Center for the Study and Improvement of Regulation at Carnegie Mellon University and University of Washington and U.S. Department of Energy Award No. DE-FG26 00NT40938.
*Best paper semifinalist.
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