Monte Carlo Techniques for Quantitative Uncertainty Analysis in Public Health Risk Assessments

Kimberly M. Thompson, David E. Burmaster and Edmund A.C. Crouch3

Risk Analysis, 1992, vol. 12, issue 1, 53-63

Abstract: Most public health risk assessments assume and combine a series of average, conservative, and worst‐case values to derive a conservative point estimate of risk. This procedure has major limitations. This paper demonstrates a new methodology for extended uncertainty analyses in public health risk assessments using Monte Carlo techniques. The extended method begins as do some conventional methods—with the preparation of a spreadsheet to estimate exposure and risk. This method, however, continues by modeling key inputs as random variables described by probability density functions (PDFs). Overall, the technique provides a quantitative way to estimate the probability distributions for exposure and health risks within the validity of the model used. As an example, this paper presents a simplified case study for children playing in soils contaminated with benzene and benzo(a)pyrene (BaP).

Date: 1992
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https://doi.org/10.1111/j.1539-6924.1992.tb01307.x

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Persistent link: https://EconPapers.repec.org/RePEc:wly:riskan:v:12:y:1992:i:1:p:53-63

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