Risk Analysis: An International Journal
This article presents a public value measure that can be used to aid executives in the public sector to better assess policy decisions and maximize value to the American people. Using Transportation Security Administration (TSA) programs as an example, we first identify the basic components of public value. We then propose a public value account to quantify the outcomes of various risk scenarios, and we determine the certain equivalent of several important TSA programs. We illustrate how this proposed measure can quantify the effects of two main challenges that government organizations face when conducting enterprise risk management: (1) short-term versus long-term incentives and (2) avoiding potential negative consequences even if they occur with low probability. Finally, we illustrate how this measure enables the use of various tools from decision analysis to be applied in government settings, such as stochastic dominance arguments and certain equivalent calculations. Regarding the TSA case study, our analysis demonstrates the value of continued expansion of the TSA trusted traveler initiative and increasing the background vetting for passengers who are afforded expedited security screening.
Influence of Distribution of Animals between Dose Groups on Estimated Benchmark Dose and Animal Welfare for Continuous Effects
The benchmark dose (BMD) approach is increasingly used as a preferred approach for dose–effect analysis, but standard experimental designs are generally not optimized for BMD analysis. The aim of this study was to evaluate how the use of unequally sized dose groups affects the quality of BMD estimates in toxicity testing, with special consideration of the total burden of animal distress. We generated continuous dose–effect data by Monte Carlo simulation using two dose–effect curves based on endpoints with different shape parameters. Eighty-five designs, each with four dose groups of unequal size, were examined in scenarios ranging from low- to high-dose placements and with a total number of animals set to 40, 80, or 200. For each simulation, a BMD value was estimated and compared with the “true” BMD. In general, redistribution of animals from higher to lower dose groups resulted in an improved precision of the calculated BMD value as long as dose placements were high enough to detect a significant trend in the dose–effect data with sufficient power. The improved BMD precision and the associated reduction of the number of animals exposed to the highest dose, where chemically induced distress is most likely to occur, are favorable for the reduction and refinement principles. The result thereby strengthen BMD-aligned design of experiments as a means for more accurate hazard characterization along with animal welfare improvements.