A Systematic Development of Uncertainty Modeling in the Assessment of Health Risk to Environmental Contaminants

Abstract

The objective of science-based risk assessment is to protect public health by providing profound decisions. Health risk analysis involves various uncertainties and highly variable parameters like multiple routes (ingestion, dermal, and inhalation), complex environmental contaminants, various pathways, and different exposure to population; which makes the risk estimation procedure extremely challenging and rigorous. The uncertainties in risk assessment majorly result from two reasons, firstly, the lack of knowledge of input variable (mostly random), and secondly, data obtained from an expert judgment or subjective interpretation of available information (non-random). The NRC (1994) states that to ignore the uncertainty in any step of risk assessment process is almost as likely as to leave critical parts of the process has been left incompletely examined and therefore increase the probability of generating a risk estimate that is incorrect, incomplete, or misleading. Each step of the risk assessment process involves various assumptions, both quantitative and qualitative, must be evaluated through uncertainty analysis. However, it is necessary that risk process of evaluation must treats uncertainty and variability scientifically and robustly. Moreover, addressing uncertainties in health risk assessment is a critical issue while evaluating the effects of environmental contaminants on public health. The uncertainty propagation in health risk can be assessed and quantified using probability theory, possibility theory, or a combination of both. This chapter will systematically report the development of various methodologies and frameworks to address the uncertainties that are intrinsic to health risk estimation.