Biesiada M
Department of Health Risk Assessment, Institute of Occupational Medicine and Environmental Health, Sosnowiec, Poland.
Int J Occup Med Environ Health. 2001;14(4):397-402.
Health risk assessment procedure provides a clear and systematic form of quantitative (or semi-quantitative) description of environmental health impact. It is well known that this approach is burdened with various types of uncertainties of different origin and nature. Therefore, the results of risk assessment should always contain both the "number" and the "measure of uncertainty". The problem is that even if one does attempt to take account of the uncertainty, one does not know a priori what is the probability of getting a given risk value within the specified range of uncertainty. A promising tool for the assessment of risk which provides a means of describing the sensitivity with respect to different exposure factors and evaluating different intervention scenarios is the technique of Monte Carlo simulation. In this probabilistic approach all variables and parameters used in risk assessment may be regarded as distributions throughout the analysis. A process of repeated simulations is then used, during which the estimated quantity (risk in this case) is calculated many times (usually 10,000 or more) with randomly chosen values of variables and parameters, covering their range of variability and reproducing the assumed distribution density. The final result is given in the form of a probability distribution of risk. The idea of Monte Carlo simulations in health risk assessment concerning the exposure to heavy metals in drinking water is illustrated in the population living in the vicinity of the "Lubna" waste site, taken as an example.
健康风险评估程序提供了一种清晰且系统的定量(或半定量)形式,用于描述环境健康影响。众所周知,这种方法存在各种不同来源和性质的不确定性。因此,风险评估的结果应始终同时包含“数值”和“不确定性度量”。问题在于,即使有人试图考虑不确定性,也无法事先知道在指定的不确定性范围内获得给定风险值的概率是多少。蒙特卡罗模拟技术是一种很有前景的风险评估工具,它提供了一种描述对不同暴露因素的敏感性以及评估不同干预方案的方法。在这种概率方法中,风险评估中使用的所有变量和参数在整个分析过程中都可视为分布。然后使用重复模拟过程,在此期间,通过随机选择变量和参数的值多次(通常为10000次或更多)计算估计量(在这种情况下为风险),涵盖其变异性范围并再现假定的分布密度。最终结果以风险的概率分布形式给出。以居住在“卢布纳”垃圾场附近的人群为例,阐述了蒙特卡罗模拟在饮用水中重金属暴露健康风险评估中的应用。