A systematic review of methods of uncertainty analysis and their applications in the assessment of chemical exposures, effects, and risks
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Methods of uncertainty analysis are being included increasingly in regulatory chemical risk assessment. Although best practices have been established by several safety agencies in Europe and the United States, they exist only in the grey literature – there has been no comprehensive analysis of the scientific, peer-reviewed literature on these methods. We therefore conducted a systematic review of the recent peer-reviewed literature (2007–2013) on uncertainty analysis relevant to chemical risks. The main objective was to determine whether current methods are robust enough for regulatory use, because the methods used to protect public health must meet the most stringent scientific standards. Based on 297 papers, we concluded that the peer-reviewed literature is much more critical about the disadvantages of those methods, compared to the grey literature. Furthermore, uncertainty analyses can be influenced significantly by subjective expert judgment. As a suggested improvement, we developed guidelines for transparent reporting of uncertainty assessment results.