Integrating uncertainty and interindividual variability in environmental risk assessment.
An integrated, quantitative approach to incorporating both uncertainty and interindividual variability into risk prediction models is described. Individual risk R is treated as a variable distributed in both an uncertainty dimension and a variability dimension, whereas population risk I (the number of additional cases caused by R) is purely uncertain. I is shown to follow a compound Poisson-binomial distribution, which in low-level risk contexts can often be approximated well by a corresponding compound Poisson distribution. The proposed analytic framework is illustrated with an application to cancer risk assessment for a California population exposed to 1,2-dibromo-3-chloropropane from ground water.
Bogen
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Environmental Sciences Division, Lawrence Livermore National Laboratory, California 94550.
Spear
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D002140:California; D004782:Environmental Health; D006801:Humans; D007306:Insecticides / Q000633:toxicity; D008962:Models, Theoretical; D009369:Neoplasms / Q000139:chemically induced; D011336:Probability; D011407:Propane / Q000031:analogs & derivatives / Q000633:toxicity; D012307:Risk Factors; D014874:Water Pollutants, Chemical / Q000633:toxicity
D007306:Insecticides; D014874:Water Pollutants, Chemical; C007318:1,2-dibromo-3-chloropropane; D011407:Propane