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Science-policy in environmental and health risk assessment: if we cannot do without, can we do better?

National Research Centre for Environmental Toxicology, University of Queensland, Australia

L A Cox, Jr

Cox Associates, 503 Franklin Street, Denver, CO 80218, USA

T R MacDonald

Environmental Science Dept, University of San Francisco, USA

How can empirical evidence of adverse effects from exposure to noxious agents, which is often incomplete and uncertain, be used most appropriately to protect human health? We examine several important questions on the best uses of empirical evidence in regulatory risk management decision–making raised by the US Environmental Protection Agency (EPA)'s science–policy concerning uncertainty and variability in human health risk assessment. In our view, the US EPA (and other agencies that have adopted similar views of risk management) can often improve decision–making by decreasing reliance on default values and assumptions, particularly when causation is uncertain. This can be achieved by more fully exploiting decision–theoretic methods and criteria that explicitly account for uncertain, possibly conflicting scientific beliefs and that can be fully studied by advocates and adversaries of a policy choice, in administrative decision–making involving risk assessment. The substitution of decision–theoretic frameworks for default assumption–driven policies also allows stakeholder attitudes toward risk to be incorporated into policy debates, so that the public and risk managers can more explicitly identify the roles of risk–aversion or other attitudes toward risk and uncertainty in policy recommendations. Decision theory provides a sound scientific way explicitly to account for new knowledge and its effects on eventual policy choices. Although these improvements can complicate regulatory analyses, simplifying default assumptions can create substantial costs to society and can prematurely cut off consideration of new scientific insights (e.g., possible beneficial health effects from exposure to sufficiently low ‘hormetic’ doses of some agents). In many cases, the administrative burden of applying decision–analytic methods is likely to be more than offset by improved effectiveness of regulations in achieving desired goals. Because many foreign jurisdictions adopt US EPA reasoning and methods of risk analysis, it may be especially valuable to incorporate decision–theoretic principles that transcend local differences among jurisdictions.

Key Words: risk assessment • risk management • hormesis decision theory • environmental policy • probabilistic modeling

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