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PubMedDate not supplied

Coupling basin- and site-scale inverse models of the Española aquifer.

Large-scale models are frequently used to estimate fluxes to small-scale models. The uncertainty associated with these flux estimates, however, is rarely addressed. We present a case study from the Española Basin, northern New Mexico, where we use a basin-scale model coupled with a high-resolution, nested site-scale model. Both models are three-dimensional and are analyzed by codes FEHM and PEST. Using constrained nonlinear optimization, we examine the effect of parameter uncertainty in the basin-scale model on the nonlinear confidence limits of predicted fluxes to the site-scale model. We find that some of the fluxes are very well constrained, while for others there is fairly large uncertainty. Site-scale transport simulation results, however, are relatively insensitive to the estimated uncertainty in the fluxes. We also compare parameter estimates obtained by the basin- and site-scale inverse models. Differences in the model grid resolution (scale of parameter estimation) result in differing delineation of hydrostratigraphic units, so the two models produce different estimates for some units. The effect is similar to the observed scale effect in medium properties owing to differences in tested volume. More important, estimation uncertainty of model parameters is quite different at the two scales. Overall, the basin inverse model resulted in significantly lower estimates of uncertainty, because of the larger calibration dataset available. This suggests that the basin-scale model contributes not only important boundary condition information but also improved parameter identification for some units. Our results demonstrate that caution is warranted when applying parameter estimates inferred from a large-scale model to small-scale simulations, and vice versa.

Calibration↗
PubMed1996

Investigation of the impact of pharmacokinetic variability and uncertainty on risks predicted with a pharmacokinetic model for chloroform.

A sensitivity and uncertainty analysis was performed on the Reitz et al. (Toxicol. Appl. Pharmacol., 1990: 105, 443) physiologically based pharmacokinetic (PBPK) risk assessment model for chloroform. The analytical approach attempted to separately consider the impacts of interindividual variability and parameter uncertainty on the predicted values of the dose metrics in the model, as well as on liver cancer risk estimates obtained with the model. An important feature of the analytical approach was that an attempt was made to incorporate information on correlation between important parameters, for example, the observed correlation between total blood flow and alveolar ventilation rate. Using the published PBPK model for chloroform, the best estimate of the average population risk based on the preferred pharmacodynamic dose metric (PTDEAD), representing cell death, is 9.2 x 10(-7); this estimate is more than 500-fold lower than the risk estimate of 5.3 x 10(-4) based on an alternative pharmacokinetic dose metric (AVEMMB), which represents tissue adduct formation. However, when interindividual variability was considered the range of individual risks (from the 5th to the 95th percentile of the population) predicted with PTDEAD was extremely broad (from 3.0 x 10(-13) to 3.2 x 10(-4)), while individual risks predicted with AVEMMB only varied over a factor of four (from 1.9 x 10(-4) to 7.4 x 10(-4)). As a result, the upper 95th percentile of the distribution of individual risk estimates based on the preferred cell death metric were within a factor of three of the 95th percentile for the pharmacokinetic alternative. The crucial factor with respect to the much greater variability of chloroform risk estimates based on cell death is that the dose metric, PTDEAD, is exquisitely sensitive to variation of the parameters in the model defining the response of cells to the cytotoxicity of chloroform. Unfortunately, these key parameters are also highly uncertain, as well as strongly correlated. As a result it proved impossible to accurately quantify the additional impact of parameter uncertainty on the dose metrics and risk estimates for chloroform. In general, however, the approach used in this study should be useful for differentiating the impact of interindividual variability and parameter uncertainty on PBPK-based risk assessments of other chemicals where the sensitivity, uncertainty, and correlation of the key parameters are more limited.

Animals↗
PubMed2003

Response surfaces for climate change impact assessments in urban areas.

Assessment of the impacts of climate change in real-world water systems, such as urban drainage networks, is a research priority for IPCC (Intergovernmental Panel of Climate Change). The usual approach is to force a hydrological transformation model with a changed climate scenario. To tackle uncertainty, the model should be run with at least high, middle and low change scenarios. This paper shows the value of response surfaces for displaying multiple simulated responses to incremental changes in air temperature and precipitation. The example given is inflow, related to sewer infiltration, at the Lycksele waste water treatment plant. The range of plausible changes in inflow is displayed for a series of runs for eight GCMs (Global Circulation Model; ACACIA; Carter, 2002, pers. comm.). These runs are summarised by climate envelopes, one for each prediction time-slice (2020, 2050, 2080). Together, the climate envelopes and response surfaces allow uncertainty to be easily seen. Winter inflows are currently sensitive to temperature, but if average temperature rises to above zero, inflow will be most sensitive to precipitation. Spring inflows are sensitive to changes in winter snow accumulation and melt. Inflow responses are highly dependent on the greenhouse gas emission scenario and GCM chosen.

Cities↗
PubMedDate not supplied

Effects of uncertainty on perceived health status in patients with atrial fibrillation.

The nursing discipline has focused on uncertainty as a main theme of research as well as an area needing assessment in clinical practice because the concept of uncertainty can be applied across diagnostic categories and may be worthwhile in explaining responses to illness. This study aimed to examine the effects of uncertainty on perceived health status including physical health, mental health, and general health within the theoretical framework of uncertainty in illness. This descriptive correlational and cross-sectional survey study included 81 subjects with atrial fibrillation using a face-to-face interview method. Individuals with greater symptom severity perceived more uncertainty and uncertainty was appraised as a danger rather than opportunity, thus those with greater uncertainty appraised a greater danger. While there was no relationship between danger appraisal and physical health, the significant relationships were shown between danger appraisal and mental health (r = -0.68) and between danger appraisal and general health (r = -0.39) respectively. The symptom severity had a significant direct effect on general health rather than having indirect effects through uncertainty and appraisal. Uncertainty had a significant impact on the perception of mental health through danger appraisal, identifying an area for nursing interventions. The mediating model of uncertainty with mental health as an outcome variable was supported by the empirical data of this study. In order to expand the present body of knowledge on uncertainty in illness model, recommendations for the future nursing studies and nursing practice were included.

Adult↗
PubMed1995

Methods for displaying macromolecular structural uncertainty: application to the globins.

Most molecular graphics programs ignore any uncertainty in the atomic coordinates being displayed. Structures are displayed in terms of perfect points, spheres, and lines with no uncertainty. However, all experimental methods for defining structures, and many methods for predicting and comparing structures, associate uncertainties with each atomic coordinate. We have developed graphical representations that highlight these uncertainties. These representations are encapsulated in a new interactive display program, PROTEAND. PROTEAND represents structural uncertainty in three ways: (1) The traditional way: The program shows a collection of structures as superposed and overlapped stick-figure models. (2) Ellipsoids: At each atom position, the program shows an ellipsoid derived from a three-dimensional Gaussian model of uncertainty. This probabilistic model provides additional information about the relationship between atoms that can be displayed as a correlation matrix. (3) Rigid-body volumes: Using clouds of dots, the program can show the range of rigid-body motion of selected substructures, such as individual alpha helices. We illustrate the utility of these display modalities by the applying PROTEAND to the globin family of proteins, and show that certain types of structural variation are best illustrated with different methods of display.

Animals↗
PubMed2006

Cancer in the mass print media: fear, uncertainty and the medical model.

Cancer is increasing in incidence and prevalence in North America and around the world. The mass print media play an important role in information provision about prevention, diagnosis and treatment of this disease, as well as informing health policy and personal experience. This paper reports on a content analysis of the portrayal of cancer in the highest circulating magazines available in Canada and published in Canada or the USA in 1991, 1996, 2001. It includes both manifest and latent analysis of the framing and content of cancer stories. Manifest analysis documented the dominance of the medical as compared to the lifestyle and political economy frames and the predominance of articles on breast as compared to other cancers. Latent themes included: an emphasis on fear of cancer in that: (1) cancer and fear are frequently conflated; cancer is said to grow outside of awareness; cancer is portrayed as (almost) inevitable; cancer is associated with normal experiences; early detection is associated with diagnosis; and scary statistics are emphasized; (2) contradictions and confusion exist within and between articles; and (3) metaphors of war and battle are used frequently. The paper concludes with a discussion of the implications of the linking of fear with cancer in the context of medicine as the solution.

Fear↗
PubMed1998

Topics in microbial risk assessment: dynamic flow tree process.

Microbial risk assessment is emerging as a new discipline in risk assessment. A systematic approach to microbial risk assessment is presented that employs data analysis for developing parsimonious models and accounts formally for the variability and uncertainty of model inputs using analysis of variance and Monte Carlo simulation. The purpose of the paper is to raise and examine issues in conducting microbial risk assessments. The enteric pathogen Escherichia coli O157:H7 was selected as an example for this study due to its significance to public health. The framework for our work is consistent with the risk assessment components described by the National Research Council in 1983 (hazard identification; exposure assessment; dose-response assessment; and risk characterization). Exposure assessment focuses on hamburgers, cooked a range of temperatures from rare to well done, the latter typical for fast food restaurants. Features of the model include predictive microbiology components that account for random stochastic growth and death of organisms in hamburger. For dose-response modeling, Shigella data from human feeding studies were used as a surrogate for E. coli O157:H7. Risks were calculated using a threshold model and an alternative nonthreshold model. The 95% probability intervals for risk of illness for product cooked to a given internal temperature spanned five orders of magnitude for these models. The existence of even a small threshold has a dramatic impact on the estimated risk.

Analysis of Variance↗
PubMed2002

A concept analysis of uncertainty in illness.

PURPOSE: To examine the concept of uncertainty in illness and to propose an alternate model of uncertainty in the illness experience. ORGANIZING CONSTRUCT AND METHODS: Following a review of the literature, Morse's description of concept analysis by critically appraising the literature was used as a guideline in examining the concept of uncertainty. FINDINGS: Characteristics of the illness situation--ambiguity, vagueness, unpredictability, unfamiliarity, inconsistency, and lack of information--underlie the process of uncertainty. Three attributes of the concept of uncertainty were identified as probability, temporality, and perception. Loss of personal control is often erroneously equated with uncertainty. CONCLUSIONS: Uncertainty is a multidimensional concept that in its purest form is a neutral cognitive state and should not be mistaken for its emotional outcomes. To clarify the concept of uncertainty, further research is needed to determine the relationship of uncertainty to loss of control and psychosocial outcomes.

Attitude to Health↗
PubMed1992

Principles of pharmacoeconomic analysis of drug therapy.

Economic analyses have become increasingly important in healthcare in general and with respect to pharmaceuticals in particular. If economic analyses are to play an important and useful role in the allocation of scarce healthcare resources, then such analyses must be performed properly and with care. This article outlines some of the basic principles of pharmacoeconomic analysis. Every analysis should have an explicitly stated perspective, which, unless otherwise justified, should be a societal perspective. Cost minimisation, cost-effectiveness, cost-utility and cost-benefit analyses are a family of techniques used in economic analyses. Cost minimisation analysis is appropriate when alternative therapies have identical outcomes, but differ in costs. Cost-effectiveness analysis is appropriate when alternative therapies differ in clinical effectiveness but can be examined from the same dimension of health outcome. Cost-utility analysis can be used when alternative therapies may be examined using multiple dimensions of health outcome, such as morbidity and mortality. Cost-benefit analysis requires the benefits of therapy to be described in monetary units and is not usually the technique of choice. The technique used in an analysis should be described and explicitly defended according to the problem being examined. For each technique, the method of determining costs is the same; direct, indirect, and intangible costs can be considered. The specific costs to be used depend on the analytical perspective; a societal perspective implies the use of both direct and indirect economic costs. A modelling framework such as a decision tree, influence diagram, Markov chain, or network simulation must be used to structure the analysis explicitly. Regardless of the choice of framework, all modelling assumptions should be described. The mechanism of data collection for model inputs must be detailed and defended. Models must undergo careful verification and validation procedures. Following baseline analysis of the model, further analyses should examine the role of uncertainty in model assumptions and data.

Costs and Cost Analysis↗
PubMed1976

[The use of rating scales for the study of diagnostic models: recognition of the uncertainties in classification principles].

In a cross cultural comparison of diagnostic concepts, we obtained from 45 expert italian psychiatrits symptom rating profiles, in terms of B.P.R.S., of the 12 most used diagnostic categories. While for 11 diagnostic concepts agreement was reasonably good, for cycloïd psychosis the variability of results supported the conclusion that this diagnostic concept is rather non specific among italian psychiatrists.

Cross-Cultural Comparison↗
PubMed2005

Spatial variability and uncertainty in ecological risk assessment: a case study on the potential risk of cadmium for the little owl in a Dutch river flood plain.

This paper outlines a procedure that quantifies the impact of different sources of spatial variability and uncertainty on ecological risk estimates. The procedure is illustrated in a case study that estimates the risks of cadmium for a little owl (Athene noctua vidalli) living in a Dutch river flood plain along the river Rhine. A geographical information system (GIS) was used to quantify spatial variability in contaminant concentrations and habitats. It was combined with an exposure and effect model that uses Monte Carlo simulation to quantify parameter uncertainty. Spatial model uncertainty was assessed by the application of two different spatial interpolation methods (classification and kriging) and foraging ranges. The results of the case study show that parameter uncertainty is the main type of uncertainty influencing the risk estimate, and to a lesser extent spatial variability, while spatial model uncertainty was of minor importance. Compared to the deterministically calculated hazard index for the little owl (0.9), inclusion of spatial variability resulted in a median hazard index that can vary between 0.8 and 1.4. It is concluded that a single estimator for a whole flood plain may over- or underestimate risks for specific parts within the flood plain. Further research that expands the procedure presented in this paper is necessary to improve the incorporation of spatial factors in ecological risk assessment.

Animals↗
PubMed2001

Response surface modelling and kinetic studies for the experimental estimation of measurement uncertainty in derivatisation.

Response surface modelling is proposed as an approach to the estimation of uncertainties associated with derivatisation, and is compared with a kinetic study. Fatty acid methyl ester formation is used to illustrate the approach, and kinetic data for acid-catalysed methylation and base-catalysed transesterification are presented. Kinetic effects did not lead to significant uncertainty contributions under normal conditions for base-catalysed transesterification of triglycerides. Uncertainties for acid-catalysed methylation with BF3 approach significance, but could be reduced by extending reaction times from 3 to 5 min. Non-linearity is a common feature of response surface models for derivatisation and compromised first-order estimates of uncertainty; it was necessary to include higher order differential terms in the uncertainty estimate. Simulations were used to examine the general applicability of the approach and to study the effects of poor precision and of change of response surface model. It is concluded that reliable uncertainty estimates are available only when the model is statistically significant, robust, representative of the underlying behaviour of the system, and forms a good fit to the data; arbitrary models are not generally suitable for uncertainty estimation. Where statistically insignificant effects were included in models, they gave negligible uncertainty contributions.

Journal Article↗
PubMed2001

Assessing the natural attenuation of organic contaminants in aquifers using plume-scale electron and carbon balances: model development with analysis of uncertainty and parameter sensitivity.

A quantitative methodology is described for the field-scale performance assessment of natural attenuation using plume-scale electron and carbon balances. This provides a practical framework for the calculation of global mass balances for contaminant plumes, using mass inputs from the plume source, background groundwater and plume residuals in a simplified box model. Biodegradation processes and reactions included in the analysis are identified from electron acceptors, electron donors and degradation products present in these inputs. Parameter values used in the model are obtained from data acquired during typical site investigation and groundwater monitoring studies for natural attenuation schemes. The approach is evaluated for a UK Permo-Triassic Sandstone aquifer contaminated with a plume of phenolic compounds. Uncertainty in the model predictions and sensitivity to parameter values was assessed by probabilistic modelling using Monte Carlo methods. Sensitivity analyses were compared for different input parameter probability distributions and a base case using fixed parameter values, using an identical conceptual model and data set. Results show that consumption of oxidants by biodegradation is approximately balanced by the production of CH4 and total dissolved inorganic carbon (TDIC) which is conserved in the plume. Under this condition, either the plume electron or carbon balance can be used to determine contaminant mass loss, which is equivalent to only 4% of the estimated source term. This corresponds to a first order, plume-averaged, half-life of > 800 years. The electron balance is particularly sensitive to uncertainty in the source term and dispersive inputs. Reliable historical information on contaminant spillages and detailed site investigation are necessary to accurately characterise the source term. The dispersive influx is sensitive to variability in the plume mixing zone width. Consumption of aqueous oxidants greatly exceeds that of mineral oxidants in the plume, but electron acceptor supply is insufficient to meet the electron donor demand and the plume will grow. The aquifer potential for degradation of these contaminants is limited by high contaminant concentrations and the supply of bioavailable electron acceptors. Natural attenuation will increase only after increased transport and dilution.

Biodegradation, Environmental↗
PubMed2006

[Markov Chain Monte Carlo scheme for parameter uncertainty analysis in water quality model].

Parameter identification plays an important role in environmental model application. Markov Chain Monte Carlo method was introduced to estimate parameter uncertainty, since usual Bayes discrete methods were not applicable to produce posterior distribution of complicated environmental model due to the limit of computation. In order to study the performance and efficiency of MCMC, two case studies were used. Results indicate that, either sampling performance or sampling efficiency, MCMC method both has its special advantages in producing posterior distribution. Moreover, results of Gelman convergence diagnostics indicate that sampling sequence can converge to a stationary distribution. A key finding was that the MCMC scheme presented herein provided a powerful means of parameter identification and uncertainty analysis.

Models, Theoretical↗
PubMedDate not supplied

Uncertainty estimation of pathlines in ground water models.

A method is proposed to estimate the uncertainty of the location of pathlines in two-dimensional, steady-state confined or unconfined flow in aquifers due to the uncertainty of the spatially variable unconditional hydraulic conductivity or transmissivity field. The method is based on concepts of the semianalytical first-order theory given in Stauffer et al. (2002, 2004), which allows estimates of the lateral second moment (variance) of the location of a moving particle. However, this method is reformulated in order to account for nonuniform recharge and nonuniform aquifer thickness. One prominent application is the uncertainty estimation of the catchment of a pumping well by considering the boundary pathlines starting at a stagnation point. In this method, the advective transport of particles is considered, based on the velocity field. In the case of a well catchment, backtracking is applied by using the reversed velocity field. Spatial variability of hydraulic conductivity or transmissivity is considered by taking into account an isotropic exponential covariance function of log-transformed values with parameters describing the variance and correlation length. The method allows postprocessing of results from ground water models with respect to uncertainty estimation. The code PPPath, which was developed for this purpose, provides a postprocessing of pathline computations under PMWIN, which is based on MODFLOW. In order to test the methodology, it was applied to results from Monte Carlo simulations for catchments of pumping wells. The results correspond well. Practical applications illustrate the use of the method in aquifers.

Models, Theoretical↗