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  • 1
    Electronic Resource
    Electronic Resource
    350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.
    Risk analysis 25 (2005), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: Risk analysis (RA) has been proposed as a means of assessing fitness for use of spatial data but is only rarely adopted. The proposal is that better decisions can be made by accounting for risks due to errors in spatial data. Why is RA so rarely adopted? Most geographical information science (GISc) literature stresses educational and technical constraints. In this article we propose, based on decision theory, a number of hypotheses for why the user would be more or less willing to spend resources on RA. The hypotheses were tested with a questionnaire, which showed that the willingness to spend resources on RA depends on the presence of feedback mechanisms in the decision-making process, on how much is at stake, and to a minor extent on how well the decision-making process can be modeled.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.
    Risk analysis 25 (2005), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: This article demonstrates application of sensitivity analysis to risk assessment models with two-dimensional probabilistic frameworks that distinguish between variability and uncertainty. A microbial food safety process risk (MFSPR) model is used as a test bed. The process of identifying key controllable inputs and key sources of uncertainty using sensitivity analysis is challenged by typical characteristics of MFSPR models such as nonlinearity, thresholds, interactions, and categorical inputs. Among many available sensitivity analysis methods, analysis of variance (ANOVA) is evaluated in comparison to commonly used methods based on correlation coefficients. In a two-dimensional risk model, the identification of key controllable inputs that can be prioritized with respect to risk management is confounded by uncertainty. However, as shown here, ANOVA provided robust insights regarding controllable inputs most likely to lead to effective risk reduction despite uncertainty. ANOVA appropriately selected the top six important inputs, while correlation-based methods provided misleading insights. Bootstrap simulation is used to quantify uncertainty in ranks of inputs due to sampling error. For the selected sample size, differences in F values of 60% or more were associated with clear differences in rank order between inputs. Sensitivity analysis results identified inputs related to the storage of ground beef servings at home as the most important. Risk management recommendations are suggested in the form of a consumer advisory for better handling and storage practices.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.
    Risk analysis 25 (2005), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: The establishment and spread of invasive or nonindigenous species has caused concern from stakeholders in affected areas, and has prompted many field and modeling studies. We used stochastic two species, circular three patch dynamic models to investigate the patterns of invasion and impacts upon the affected species. Both persistent and degradable toxicants were incorporated as parts of the model system to act as disturbance regimens. There is a clear series of patterns that result from these simulations. Competition increases population variability, but decreases the number of distinct outcomes possible from the same initial conditions. Isolation of the patch of the introduction was the main determinant of successful establishment through a process we call the beachhead effect. Coexistence of species was often possible in local patches, contrary to the analytical solutions of Lotka-Volterra equations and numerous modeling studies. Contaminants and their resultant disturbances are important as contributors to the stochastic nature of models. The stochasticity leads to a variety of outcomes from some sets of initial conditions. Different outcomes have different probabilities of occurrence and are dependent upon the specific initial conditions of the simulation. A clear pattern that is apparent is the “beachhead effect,” where the invasive establishes a population within a relatively remote patch before migrating to the remainder of the landscape. We make predictions and provide specific research hypotheses as to the causes and effects of invasive species establishment, spread, and impacts.
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  • 4
    Electronic Resource
    Electronic Resource
    350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.
    Risk analysis 25 (2005), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: To avoid interspecies extrapolation in toxicokinetics and drug development, it is convenient to directly develop human data. In that case, exposure dose should pose null or negligible risk to the exposed individual, but still be sufficiently high to allow quantification. We propose to reduce the dose received by human volunteers during exposure, and to compensate for loss of information by exposing the same volunteers to a nontoxic agent. This method was applied to develop 1,3-butadiene (BD) exposure protocols for humans. To study the potential of such a procedure, we worked with simulated data. Three exposure times (20, 10, and 5 minutes) and four exposure concentrations (2, 1, 0.8, and 0.5 ppm) were used to define 12 inhalation exposure scenarios for BD. Isoflurane was used as a probe, with simulated exposure of 20 subjects to 20 ppm isoflurane during 15 minutes. Isoflurane or BD-exhaled air concentrations were supposed to be measured 10 times. A three-compartment physiological toxicokinetic model was used to jointly describe BD and isoflurane data. For each subject, BD data were analyzed, in a Bayesian framework, either alone or together with the isoflurane data. The precision of BD metabolic rate constant or fraction metabolized was increased, and bias reduced, when BD and probe data were considered jointly. An exposure to 10 ppm × min BD and 300 ppm × min isoflurane gave equivalent precision and bias as a unique exposure to 40 ppm × min BD. The BD dose received by volunteers could therefore be at least quartered if BD exposure was supplemented with that of a probe.
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  • 5
    Electronic Resource
    Electronic Resource
    350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.
    Risk analysis 25 (2005), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: Qualitative systems for rating animal antimicrobial risks using ordered categorical labels such as “high,”“medium,” and “low” can potentially simplify risk assessment input requirements used to inform risk management decisions. But do they improve decisions? This article compares the results of qualitative and quantitative risk assessment systems and establishes some theoretical limitations on the extent to which they are compatible. In general, qualitative risk rating systems satisfying conditions found in real-world rating systems and guidance documents and proposed as reasonable make two types of errors: (1) Reversed rankings, i.e., assigning higher qualitative risk ratings to situations that have lower quantitative risks; and (2) Uninformative ratings, e.g., frequently assigning the most severe qualitative risk label (such as “high”) to situations with arbitrarily small quantitative risks and assigning the same ratings to risks that differ by many orders of magnitude. Therefore, despite their appealing consensus-building properties, flexibility, and appearance of thoughtful process in input requirements, qualitative rating systems as currently proposed often do not provide sufficient information to discriminate accurately between quantitatively small and quantitatively large risks. The value of information (VOI) that they provide for improving risk management decisions can be zero if most risks are small but a few are large, since qualitative ratings may then be unable to confidently distinguish the large risks from the small. These limitations suggest that it is important to continue to develop and apply practical quantitative risk assessment methods, since qualitative ones are often unreliable.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.
    Risk analysis 25 (2005), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: Recent work in the assessment of risk in maritime transportation systems has used simulation-based probabilistic risk assessment techniques. In the Prince William Sound and Washington State Ferries risk assessments, the studies’ recommendations were backed up by estimates of their impact made using such techniques and all recommendations were implemented. However, the level of uncertainty about these estimates was not available, leaving the decisionmakers unsure whether the evidence was sufficient to assess specific risks and benefits. The first step toward assessing the impact of uncertainty in maritime risk assessments is to model the uncertainty in the simulation models used. In this article, a study of the impact of proposed ferry service expansions in San Francisco Bay is used as a case study to demonstrate the use of Bayesian simulation techniques to propagate uncertainty throughout the analysis. The conclusions drawn in the original study are shown, in this case, to be robust to the inherent uncertainties. The main intellectual merit of this work is the development of Bayesian simulation technique to model uncertainty in the assessment of maritime risk. However, Bayesian simulations have been implemented only as theoretical demonstrations. Their use in a large, complex system may be considered state of the art in the field of computational sciences.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.
    Risk analysis 25 (2005), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: Transmissible spongiform encephalopathy (TSE) risk assessments undertaken in the United Kingdom have mainly had the objective of determining the risks posed to humans from exposure to the causal agents associated with bovine spongiform encephalopathy (BSE) and variant Creutzfeld-Jakob disease (vCJD). In this article, I examine 19 of these risk assessments published to date and consider how their results might be influenced by underlying model assumptions and methodology. Three separate aspects common to all the assessments are infective load estimation, exposure pathway identification, and risk estimation. These are each discussed in detail.
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.
    Risk analysis 25 (2005), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: The precautionary principle calls on decisionmakers to take preventive action in light of evidence indicating that there is a potential for harm to public health and the environment, even though the nature and magnitude of harm are not fully understood scientifically. Critics of the precautionary principle frequently argue that unbridled application of the principle leads to unintended damage to health and ecosystems (risk tradeoffs) and that precautious decision making leaves us vulnerable to "false-positive" risks that divert resources away from “real risks.” The 1991 cholera epidemic in Peru is often cited as an example of these pitfalls of the precautionary principle. It has been mistakenly argued that application of the precautionary principle caused decisionmakers to stop chlorinating the water supply due to the risks of disinfection byproducts (DBPs), resulting in the epidemic. Through analyses of investigations conducted in the cities of Iquitos and Trujillo, Peru, literature review, and interviews with leading Peruvian infectious disease researchers, we determined that the epidemic was caused by a much more complex set of circumstances, including poor sanitation conditions, poor separation of water and waste streams, and inadequate water treatment and distribution systems. The evidence indicates that no decision was made to stop chlorinating on the basis of DBP concerns and that concerns raised about DBPs masked more important factors limiting expansion of chlorination. In fact, outside of Peru's capital Lima, chlorination of drinking water supplies at the time of the epidemic was limited at best. We conclude that the Peruvian cholera epidemic was not caused by a failure of precaution but rather by an inadequate public health infrastructure unable to control a known risk: that of microbial contamination of water supplies.
    Type of Medium: Electronic Resource
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  • 9
    Electronic Resource
    Electronic Resource
    350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.
    Risk analysis 25 (2005), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: Microbial food safety has been the focus of research across various disciplines within the risk analysis community. Natural scientists involved in food microbiology and related disciplines work on the identification of health hazards, and the detection of pathogenic microorganisms. To perform risk assessment, research activities are increasingly focused on the quantification of microbial contamination of food products at various stages in the food chain, and modeling the impact of this contamination on human health. Social scientists conduct research into how consumers perceive food risks, and how best to develop effective risk communication with consumers in order to improve public health through improved food handling practices. The two approaches converge at the end of the food chain, where the activities regarding food preparation and food consumption are considered. Both natural and social sciences may benefit from input and expertise from the perspective of the alternative discipline, although, to date, the integration of social and natural sciences has been somewhat limited. This article therefore explores the potential of a transdisciplinary approach to food risk analysis in terms of delivering additional improvements to public health. Developing knowledge arising from research in both the natural and social sciences, we present a novel framework involving the integration of the two approaches that might provide the most effective way to improve the consumer health associated with food-borne illness.
    Type of Medium: Electronic Resource
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  • 10
    Electronic Resource
    Electronic Resource
    350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.
    Risk analysis 25 (2005), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: The appearance of measurement error in exposure and risk factor data potentially affects any inferences regarding variability and uncertainty because the distribution representing the observed data set deviates from the distribution that represents an error-free data set. A methodology for improving the characterization of variability and uncertainty with known measurement errors in data is demonstrated in this article based on an observed data set, known measurement error, and a measurement-error model. A practical method for constructing an error-free data set is presented and a numerical method based upon bootstrap pairs, incorporating two-dimensional Monte Carlo simulation, is introduced to address uncertainty arising from measurement error in selected statistics. When measurement error is a large source of uncertainty, substantial differences between the distribution representing variability of the observed data set and the distribution representing variability of the error-free data set will occur. Furthermore, the shape and range of the probability bands for uncertainty differ between the observed and error-free data set. Failure to separately characterize contributions from random sampling error and measurement error will lead to bias in the variability and uncertainty estimates. However, a key finding is that total uncertainty in mean can be properly quantified even if measurement and random sampling errors cannot be separated. An empirical case study is used to illustrate the application of the methodology.
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