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THE USE OF COMPUTER MODELING PACKAGES TO ILLUSTRATE UNCERTAINTY IN RISK ASSESSMENTS: AN EASE OF USE AND INTERPRETATION COMPARISON
Citation:
Rigas, M L. AND D. M. Hassenzahl. THE USE OF COMPUTER MODELING PACKAGES TO ILLUSTRATE UNCERTAINTY IN RISK ASSESSMENTS: AN EASE OF USE AND INTERPRETATION COMPARISON. Presented at ISEA 2000 Exposure Analysis in the 21st Century: Integrating Science, Policy and Quality of Life, Monterey Peninsula, CA, October 24-27, 2000.
Impact/Purpose:
The objectives for the current task are to 1) evaluate the utility of screening survey design and questionnaires for identifying households/individuals with higher exposures; and 2) compare estimates of dietary exposure derived from food consumption and residue databases with direct measurements of dietary exposure obtained in this study. (Results of the environmental, exposure, and biological measurements will be reported in collaboration with the other investigators.)
Description:
Consistent improvements in processor speed and computer access have substantially increased the use of computer modeling by experts and non-experts alike. Several new computer modeling packages operating under graphical operating systems (i.e. Microsoft Windows or Macintosh) make it easier for sophisticated lay individuals and policymakers without modeling backgrounds to exercise and manipulate probabilistic exposure and risk models. It is likely that individuals and communities will increasingly rely on such models as they make environmental exposure and risk decisions. We compare the speed and ease of use of three packages, Modelmaker 4.0 (Cherwell Scientific; Oxford, UK), Crystal Ball (Decisioneering; Denver, CO), and Matlab (The Mathworks; Natick, MA). The packages were used to solve a Monte Carlo exposure model designed to evaluate the risks of exposure to UDMH, a breakdown byproduct of Alar in cooked apple products, and aflatoxin, a naturally occurring contaminant in peanut butter (Kammen, DM and Hassenzahl, DM. (1999) Should we Risk It? Exploring Environmental, Health, and Technological Problem Solving. Princeton University Press; Finkel, AM (1995), Toward Less Misleading Comparisons of Uncertain Risks - the Example of Aflatoxin and Alar. Environmental Health Perspectives 103(4) 376-385). Individuals with little or no previous Monte Carlo experience were asked to manipulate the models and draw conclusions based on the results. While Matlab has numerous built-in powerful mathematical functions, the Excel interface used by Crystal Ball is familiar to many people. The low-cost and graphical interface of ModelMaker 4.0 makes this package an equally attractive option for many risk assessors.
This work has been funded wholly or in part by the United States Environmental Protection Agency and has been approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.