ON THE EFFECT OF PROBABILITY-DISTRIBUTIONS OF INPUT VARIABLES IN PUBLIC-HEALTH RISK ASSESSMENT

A central part of probabilistic public health risk assessment is the s election of probability distributions for the uncertain input variable s. In this paper, we apply the first-order reliability method (FORM)(( 1-31)) as a probabilistic tool to assess the effect of probability dis tributions of the input random variables on the probability that risk exceeds a threshold level (termed the probability of failure) and on t he relevant probabilistic sensitivities. The analysis was applied to a case study given by Thompson et al.((4)) on cancer risk caused by the ingestion of benzene contaminated soil. Normal, lognormal, and unifor m distributions were used in the analysis. The results show that the s election of a probability distribution function for the uncertain vari ables in this case study had a moderate impact on the probability that values would fall above a given threshold risk when the threshold ris k is at the 50th percentile of the original distribution given by Thom pson et al.((4)) The impact was much greater when the threshold risk l evel was at the 95th percentile. The impact on uncertainty sensitivity , however, showed a reversed trend, where the impact was more apprecia ble for the 50th percentile of the original distribution of risk given by Thompson et al.((4)) than for the 95th percentile. Nevertheless, t he choice of distribution shape did not alter the order of probabilist ic sensitivity of the basic uncertain variables.