Suchergebnisse

AbstractIn this article we consider the unweighted m‐center problem with rectilinear distance. We preent an O(nm–2 log n) algorithm for the m‐center problem where m ≥ 4.

There is increasing interest in the integration of quantitative risk analysis with benefit‐cost and cost‐effectiveness methods to evaluate environmental health policy making 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. A principal issue in integrating risk and economic analysis is the lack of common performance metrics, particularly when conducting comparative analyses of regulations with disparate health endpoints (e.g., cancer and noncancer effects or risk‐benefit analysis) and quantitative 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 analyses of health risks and policies. We review existing and proposed risk and health‐impact 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 comparative risk and policy analysis framework. Case studies are presented to demonstrate applications of this framework with risk‐benefit and air pollution risk analyses. Through this analysis, we hope to generate discussions regarding the data requirements, analytical approaches, and assumptions required for general models to be used in comparative risk and policy analysis.