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A probabilistic approach to exposure risk assessment

机译:暴露风险评估的概率方法

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The introduction of hazardous substances into the environment has long been recognized as being a cause of several diseases in humans, wildlife, and plants. The damaging character of suspected contaminants is usually assessed via a "reject/retain" design with no explicit link between levels of exposure and intensities of the potential adverse health effects even though this connection may be important for the development of public health regulations that limit exposure to hazardous substances. Here, we propose a probabilistic approach to exposure risk assessment as a way around this typical flaw. We develop a Bayesian model using proximity to the source of an alleged contaminant as a surrogate for exposure. Subsequently, we carry out an experimental study based on simulated data to illustrate the model implementation with real world data. We also discuss a possible way of extending the model to accommodate potential heterogeneity in the spatial distribution of the focal disease.
机译:长期以来,人们一直认为将有害物质引入环境是人类,野生动植物和植物中多种疾病的原因。通常通过“拒绝/保留”设计评估可疑污染物的破坏特性,在接触水平和潜在不良健康影响强度之间没有明确的联系,即使这种联系对于制定限制接触的公共卫生法规可能很重要有害物质。在此,我们提出了一种概率性的暴露风险评估方法,以解决这种典型缺陷。我们开发了一个贝叶斯模型,使用与所谓污染物的来源的接近度作为暴露的替代物。随后,我们基于模拟数据进行了实验研究,以说明实际数据的模型实现。我们还讨论了扩展模型以适应局灶性疾病空间分布中潜在异质性的可能方法。

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