Quantitative risk analysis uncertainty

Our assignment for EPA was to apply quantitative risk analysis methods to the determination of risk for a particular chemical. The health risks for perchloroethylene turned out to be highly uncertain, but by using decision analysis concepts we were able to display this uncertainty in terms of alternative assumptions about the dose response relationship. Similar methods might be used to characterize uncertainties about human exposure to a chemical agent or about the costs to producers and consumers of a restriction on chemical use. 

In addition to the risk reduction benefits, the costs of risk mitigation options need to be evaluated. Due to the uncertainties associated with semi-quantitative and quantitative risk analysis results, a relative risk comparison, as compared to absolute measures of risk and benefits, is recommended. To conduct this type of relative comparison, incremental risk analysis can be used to evaluate the cost effectiveness of risk mitigation options, or determine the optimal combination of risk mitigation options. Figure 7.4 illustrates example results of this type of analysis, and uses the options from the F-N curve in Figure 7.3 as the basis for comparison. 

Thanks in large part to work done in several of the programs in technology and policy, today modern policy analytic work is much improved, both in terms of the way in which problems are framed and the analytical tools that are employed, than was the case 30 years ago. For example, techniques such as decision analysis, the systematic characterization and analysis of uncertainty, and methods in quantitative risk analysis, that were pioneered in several of these programs, are now almost ubiquitous. 

Flage, R. Aven, T. (2009) Ejqjressing and communicating uncertainty in relation to quantitative risk analysis. Reliability Risk Analysis Theory Application, to appear. 

Uncertainty assessments in a semi-quantitative risk analysis, with application to health care... 

Monte Carlo simulation is one of the most commonly used method of analyzing parameter uncertainty in the quantitative risk analysis research (Coxl 1996, Chen Liao 2006, Sassi et al. 2007). The USEPA has put a Monte Carlo simulation method as the basic methods of risk analysis in risk... 

What risk means in a security context and how the risk can be expressed and managed, is a contested topic in the scholar literature (Bier Von Winterfeldt, 2007 Deisler Jr, 2002 Jore Nja, 2010 Willis, 2007). Traditional quantitative risk analysis calculates risk based on the probability of an incident multiplied with the consequences. Newer perspectives often include uncertainties not captured in the probability or the background knowledge that the traditional risk estimates are based on (Aven, 2011). According to Aven (2013), in the area of security, application of probabilities is commonly avoided it is said that they are impossible to determine and that they are of little interest as a tool to support the decision making. Often qualitative assessments are performed on the basis of judgments of actors intentions and capacities, without references to a probability scale. 

Melnick, Edward L, og Brian S. Ever. Encyclopedia of quantitative risk analysis and assessment. Wiley, 2008. Merkhofer, Miley W. Quantifying Judgemental Uncertainty Methodology. IEEE transactions on systems, man and cybernetics, 1987 741-752. 

Expressing and communicating uncertainty and bias in relation to Quantitative Risk Analysis... 

Section 18.2 Risk Cliaracterization Section 18.3 Cause-Consequence Analysis Section 18.4 Qualitative Hazard Risk Analysis Section 18.5 Quantitative Hazard Risk Analysis Section 18.6 Uncertainties/Limihitions Section 18.7 Public Perception of Risk Section 18.8 Risk Communication... 

In the final phase of risk analysis—risk characterization—one integrates outputs of effects and exposure assessments. Risk is expressed in qualitative or quantitative estimates by comparison with reference values (e.g., hazard quotient). The severity of potential or actual damage should be characterized with the degree of uncertainty of risk estimates. Assumptions, data uncertainties and limitations of analyses are to be described clearly and reflected in the conclusions. The final product is a report that communicates to the affected and interested parties the analysis findings (Byrd and Cothern, 2000). 

Risk evaluation methods should use data that is relevant to the facility under examination. Where other data is used an explanation should be provided to substantiate it s use, otherwise inaccurate assumptions will prevail in the analysis. Where highly accurate data is available, the findings of a quantitative risk evaluation will generally only be within an order of magnitude of 10 of the actual risk levels since some uncertainty of the data to the actual application will always exist. 

Monte Carlo—A statistical technique commonly used to quantitatively characterize the uncertainty and variability in estimates of exposure or risk. The analysis uses statistical sampling techniques to obtain a probabilistic approximation to the solution of a mathematical equation or model. 

Morgan MG, Henrion M. 1990. Uncertainty a guide to dealing with uncertainty in quantitative risk and policy analysis. Cambridge (UK) Cambridge University Press. 

Both qualitative and quantitative evaluations of uncertainty provide useful information in a risk assessment. The techniques of quantitative uncertainty analysis are evolving rapidly. An approach was recently proposed for estimating distribution of uncertainty in noncancer risk assessments (Baird et al., 1996). 

Zheng J, Frey HC (2005) Quantitative analysis of variability and uncertainty with known measurement error Methodology and case study. Risk Analysis, 25(3) 663-676. 

Thompson KM, Burmaster DE, and Crouch EAC (1992) Monte Carlo techniques for quantitative uncertainty analysis in public health risk assessments. Risk Analysis 12 53-63. 

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