Site‐Specific Applications of Probabilistic Health Risk Assessment: Review of the Literature Since 2000

Lester, Richard R.; Green, Laura C.; Linkov, Igor

doi:10.1111/j.1539-6924.2007.00890.x

Cited by 43 publications

(36 citation statements)

References 105 publications

(146 reference statements)

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“…Given the computational power of today's hardware and availability of modern software, Bayesian methods for data analysis are now easily accessible to everyone and getting more and more attention in different scientific disciplines (Kruschke et al, 2012;Lester et al, 2007). In this paper we hope that we have demonstrated their usefulness to radioecological studies.…”

Section: Furthermore As Priors Represent External Insight/informatiomentioning

confidence: 84%

Application of the Bayesian approach for derivation of PDFs for concentration ratio values

Hosseini

Stenberg

Ávila

et al. 2013

Journal of Environmental Radioactivity

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Concentration ratios (CRs) are used to derive activity concentrations in wild plants and animals. Usually, compilations of CR values encompass a wide range of element-organism combinations, extracted from different studies with statistical information reported at varying degrees of detail. To produce a more robust estimation of distribution parameters, data from different studies are normally pooled using classical statistical methods. However, there is inherent subjectivity involved in pooling CR data in the sense that there is a tacit assumption that the CRs under any arbitrarily defined biota category belong to the same population. Here, Bayesian inference has been introduced as an alternative way of making estimates of distribution parameters of CRs. This approach, in contrast to classical methods, is more flexible and also allows us to define the various assumptions required, when combining data, in a more explicit manner. Taking selected data from the recently compiled wildlife transfer database (http://www.wildlifetransferdatabase.org/) as a working example, attempts are made to refine the pooling approaches previously used and to consider situations when empirical data are limited.

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Section: Furthermore As Priors Represent External Insight/informatiomentioning

confidence: 84%

Application of the Bayesian approach for derivation of PDFs for concentration ratio values

Hosseini

Stenberg

Ávila

et al. 2013

Journal of Environmental Radioactivity

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“…MCA methodology, as well as its application to risk analysis, has been reviewed and detailed in Cullen and Frey(1999), Morgan and Henrion (1990), and elsewhere. 3,4) Furthermore two-dimensional Monte Carlo analysis (2D MCA) is a natural extension of one-dimensional Monte Carlo analysis (1D MCA) [5][6][7][8] , which can provide information on uncertainty and variability in the estimates.…”

Section: Introductionmentioning

confidence: 99%

A Probabilistic Risk Assessment for Field Radiography Based on Expert Judgment and Opinion

Jang

Ryu

Kim

et al. 2011

Progress in Nuclear Science and Technology

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A probabilistic approach was applied to assess radiation risk associated with the field radiography using gamma sources. The Delphi method based on the expert judgments and opinions was used in the process of characterization of parameters affecting risk, which are inevitably subject to large uncertainties. A mathematical approach applying the Bayesian inferences was employed for data processing to improve the Delphi results. This process consists of three phases: (i) setting prior distributions, (ii) constructing the likelihood functions and (iii) deriving the posterior distributions based on the likelihood functions. The approach for characterizing input parameters using the Bayesian inference is provided for improved risk estimates without intentional rejection of part of the data, which demonstrated utility of Bayesian updating of distributions of uncertain input parameters in PRA (Probabilistic Risk Assessment). The data analysis portion for PRA in field radiography is addressed for estimates of the parameters used to determine the frequencies and consequences of the various events modeled. In this study, radiological risks for the worker and the public member in the vicinity of the work place are estimated for field radiography system in Korea based on two-dimensional Monte Carlo Analysis (2D MCA).

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“…A comprehensive literature review on probabilistic risk assessment was done by Lester et al (2007). Although the authors focused on probabilistic risk assessment applications in management of contaminated land, they do provide a comprehensive list of methods used in the probabilistic risk assessment of exposure and hazard assessment, risk characterisation and risk management.…”

Section: General Introductionmentioning

confidence: 99%

“…Lester et al (2007) A literature search (8 December 2015) was done using Scopus, an abstract and citation database covering more than 5000 international publishers. Next, only the peer-reviewed articles were selected.…”

Section: General Introductionmentioning

confidence: 99%

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Statistical modelling of variability and uncertainty in risk assessment of nanoparticles

Jacobs

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Engineered nanoparticles (ENPs) are used everywhere and have large technological and economic potential. Like all novel materials, however, ENPs have no history of safe use.Insight into risks of nanotechnology and the use of nanoparticles is an essential condition for the societal acceptance and safe use of nanotechnology.Risk assessment of ENPs has been hampered by lack of knowledge about ENPs, their environmental fate, toxicity, testing considerations, characterisation of nanoparticles and human and environmental exposures and routes. This lack of knowledge results in uncertainty in the risk assessment. Moreover, due to the novelty of nanotechnology, risk assessors are often confronted with small samples of data on which to perform a risk assessment. Dealing with this uncertainty and the small sample sizes are main challenges when it comes to risk assessment of ENPs. The objectives of this thesis are (i) to perform a transparent risk assessment of nanoparticles in the face of large uncertainty in such a way that it can guide future research to reduce the uncertainty and (ii) to evaluate empirical and parametric methods to estimate the risk probability in the case of small sample sizes.To address the first objective, I adapted an existing Integrated Probabilistic Risk Assessment (IPRA) method for use in nanoparticle risk assessment. In IPRA, statistical distributions and bootstrap methods are used to quantify uncertainty and variability in the risk assessment in a two-dimensional Monte Carlo algorithm. This method was applied in a human health (nanosilica in food) and an environmental (nanoT iO 2 in water) risk context. I showed that IPRA leads to a more transparent risk assessment and can direct further environmental and toxicological research to the areas in which it is most needed.For the second objective, I addressed the problem of small sample size of the critical effect concentration (CEC) in the estimation of R = P (E xpC > C EC ), where E xpC is the exposure concentration. First I assumed normality and investigated various parametric and non-parametric estimators. I found that, compared to the non-parametric estimators, the parametric estimators enable us to better estimate and bound the risk when sample sizes and/or small risks are small. Moreover, the Bayesian estimator out-ABSTRACT performed the maximum likelihood estimators in terms of coverage and interval lengths.Second, I relaxed the normality assumption for the tails of the exposure and effect distributions. I developed a mixture model to estimate the risk, R = P (E xpC > C EC ), with the assumption of a normal distribution for the bulk data and generalised Pareto distributions for the tails. A sensitivity analysis showed significant influence of the tail heaviness on the risk probability, R, especially for low risks.In conclusion, to really be able to focus the research into the risks of ENPs to the most needed areas, probabilistic methods as used and developed in this thesis need to be implemented on a larger scale. With these methods,...

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Site‐Specific Applications of Probabilistic Health Risk Assessment: Review of the Literature Since 2000

Cited by 43 publications

References 105 publications

Application of the Bayesian approach for derivation of PDFs for concentration ratio values

Application of the Bayesian approach for derivation of PDFs for concentration ratio values

A Probabilistic Risk Assessment for Field Radiography Based on Expert Judgment and Opinion

Statistical modelling of variability and uncertainty in risk assessment of nanoparticles

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