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Monte Carlo Techniques for Quantitative Uncertainty Analysis in Public Health Risk Assessments
Author(s) -
Thompson Kimberly M.,
Burmaster David E.,
Crouch Edmund A.C.
Publication year - 1992
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/j.1539-6924.1992.tb01307.x
Subject(s) - monte carlo method , risk assessment , health risk , computer science , probability density function , econometrics , statistics , risk analysis (engineering) , mathematics , environmental health , medicine , computer security
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).