Abstract
Sensitivity analyses of exposure or risk models can help identify the most significant factors to aid in risk management or to prioritize additional research to reduce uncertainty in the estimates. However, sensitivity analysis is challenged by non-linearity, interactions between inputs, and multiple days or time scales. Selected sensitivity analysis methods are evaluated with respect to their applicability to human exposure models with such features using a testbed. The testbed is a simplified version of a US Environmental Protection Agency's Stochastic Human Exposure and Dose Simulation (SHEDS) model. The methods evaluated include the Pearson and Spearman correlation, sample and rank regression, analysis of variance, Fourier amplitude sensitivity test (FAST), and Sobol's method. The first five methods are known as “sampling-based” techniques, wheras the latter two methods are known as “variance-based” techniques. The main objective of the test cases was to identify the main and total contributions of individual inputs to the output variance. Sobol's method and FAST directly quantified these measures of sensitivity. Results show that sensitivity of an input typically changed when evaluated under different time scales (e.g., daily versus monthly). All methods provided similar insights regarding less important inputs; however, Sobol's method and FAST provided more robust insights with respect to sensitivity of important inputs compared to the sampling-based techniques. Thus, the sampling-based methods can be used in a screening step to identify unimportant inputs, followed by application of more computationally intensive refined methods to a smaller set of inputs. The implications of time variation in sensitivity results for risk management are briefly discussed.
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Acknowledgements
This work was supported by the National Exposure Research Laboratory of the US Environmental Protection Agency via Alion Science and Technology as part of work assignment 2004-206-01. We acknowledge the advice and guidance provided by Luther Smith, Graham Glen, and Kristin Isaacs of Alion in the development of the simplified SHEDS model, design of the case studies, and aspects of the interpretation of results. Jianping Xue and Shi Liu of EPA provided useful guidance and suggestions. This report has not been subject to any EPA or Alion review. Therefore, it does not necessarily reflect the views of the Agency or Alion and no official endorsement should be inferred. The opinions, findings, and conclusions expressed represent those of the authors. Any mention of company or product names does not constitute an endorsement by the EPA or Alion.
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Mokhtari, A., Christopher Frey, H. & Zheng, J. Evaluation and recommendation of sensitivity analysis methods for application to Stochastic Human Exposure and Dose Simulation models. J Expo Sci Environ Epidemiol 16, 491–506 (2006). https://doi.org/10.1038/sj.jes.7500472
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DOI: https://doi.org/10.1038/sj.jes.7500472
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