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Results for “Uncertainty modelling”

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PubMed1997

Economics of thromboprophylaxis in total hip replacement surgery.

In 1997, 50,000 hip replacements will be performed in the UK, and over 1 million worldwide. Venous thromboembolism is the most frequent serious complication following joint replacement; its effective and economic management is essential. Antithrombotic prophylaxis can be used to reduce the incidence of venous thromboembolic disease, which presents as either deep vein thrombosis or pulmonary embolism. A number of published studies have shown that prophylaxis against venous thromboembolism is financially beneficial in terms of reduced diagnostic and treatment costs. Cost-effectiveness studies have provided a comparison of the costs and consequences resulting from alternative prophylactic programmes. This article reviews the epidemiology of venous thromboembolism after total hip replacement, prophylaxis against it and a model for cost-effectiveness analysis. Its aim is to highlight inadequacies in the available data and areas of uncertainty within the model that require further research. Pharmacoeconomic studies published to date have all used a similar framework to allow prophylactic options to be compared. However, assumptions made about the frequency of clinical disease have varied widely between studies. This degree of uncertainty calls into question the validity of reported incremental cost savings between treatments. Some studies have also failed to address the cost of complications resulting from the prophylactic method under consideration. Future studies must carefully consider the validity of their models, understand the limitations on current knowledge of outcome rates, and carefully consider all outcomes (both beneficial and detrimental) that result from the intervention.

Cost-Benefit Analysis↗

PubMed2005

Uncertainties in extreme surge level estimates from observational records.

Ensemble simulations with a total length of 7540 years are generated with a climate model, and coupled to a simple surge model to transform the wind field over the North Sea to the skew surge level at Delfzijl, The Netherlands. The 65 constructed surge records, each with a record length of 116 years, are analysed with the generalized extreme value (GEV) and the generalized Pareto distribution (GPD) to study both the model and sample uncertainty in surge level estimates with a return period of 104 years, as derived from 116-year records. The optimal choice of the threshold, needed for an unbiased GPD estimate from peak over threshold (POT) values, cannot be determined objectively from a 100-year dataset. This fact, in combination with the sensitivity of the GPD estimate to the threshold, and its tendency towards too low estimates, leaves the application of the GEV distribution to storm-season maxima as the best approach. If the GPD analysis is applied, then the exceedance rate, lambda, chosen should not be larger than 4. The climate model hints at the existence of a second population of very intense storms. As the existence of such a second population can never be excluded from a 100-year record, the estimated 104-year wind-speed from such records has always to be interpreted as a lower limit.

Computer Simulation↗

PubMed2006

An application of the GLUE methodology for estimating the parameters of the INCA-N model.

The conceptual and parameter uncertainty of the semi-distributed INCA-N (Integrated Nutrients in Catchments-Nitrogen) model was studied using the GLUE (Generalized Likelihood Uncertainty Estimation) methodology combined with quantitative experimental knowledge, the concept known as 'soft data'. Cumulative inorganic N leaching, annual plant N uptake and annual mineralization proved to be useful soft data to constrain the parameter space. The INCA-N model was able to simulate the seasonal and inter-annual variations in the stream-water nitrate concentrations, although the lowest concentrations during the growing season were not reproduced. This suggested that there were some retention processes or losses either in peatland/wetland areas or in the river which were not included in the INCA-N model. The results of the study suggested that soft data was a way to reduce parameter equifinality, and that the calibration and testing of distributed hydrological and nutrient leaching models should be based both on runoff and/or nutrient concentration data and the qualitative knowledge of experimentalist.

Agriculture↗

PubMed2005

Effects of environmental uncertainties on sonar detection performance prediction.

The development of effective passive sonar systems depends upon the ability to accurately predict the performance of sonar detection algorithms in realistic ocean environments. Such environments are typically characterized by a high degree of uncertainty, thus limiting the usefulness of performance prediction approaches that assume a deterministic environment. Here we derive closed-form receiver operating characteristic (ROC) expressions for an optimal Bayesian detector and for several typical suboptimal detectors, based on a statistical model of environmental uncertainty. Various scenarios extended from an NRL benchmark shallow-water model were used to check the analytical ROC expressions and to illustrate the effect of environmental uncertainty on detection performance. The results showed that (1) optimal detection performance in an uncertain environment in diffuse noise depends primarily on the signal-to-noise ratio at the receivers and the rank of the signal matrix, where the rank is an effective representation of the scale of environmental uncertainty; (2) the ROC expression for the optimal Bayesian detector provides a more realistic performance upper bound than that obtained from conventional sonar equations that do not incorporate environmental uncertainty; and (3) detection performance predictions can be performed much faster than with commonly used numerical methods such as Monte Carlo performance evaluations.

Journal Article↗

PubMed1993

Uncertainty and health care spending by the poor: the health capital model revisited.

This short theoretical paper examines health care utilization by the poor in the context of Grossman's (1972) health capital model. Earlier work has shown that uncertainty can reduce the attractiveness to the poor of health capital investments. This paper demonstrates that uncertainty can also have precisely the opposite effect. That is, while there may be cases in which it is excessively risky for the poor to invest in their health, there may also be cases in which the poor can ill-afford the risks that arise from not making timely investments in their health.

Attitude to Health↗

PubMed2006

Uncertainty and perceived personal control among parents of children with rare chromosome conditions: the role of genetic counseling.

Little is known about the impact of genetic counseling on parental uncertainty or perceived control regarding the prognosis of a child with a chromosomal disorder. By exploring the parents' concerns and needs surrounding the child's diagnosis, a genetic provider can help to facilitate effective coping. This study tested the association of measures of parental uncertainty and perceived control with the perceived helpfulness of the genetic counselor. A survey was distributed to 875 members of the Chromosome Deletion Outreach (CDO) support group. We hypothesized that parents' perceptions about the helpfulness of the genetic counselor would modify the relationship between perceived uncertainty, perceived control, and coping. Among the 363 respondents, there was a significant negative correlation of the perceived helpfulness of seeing a genetic counselor with the levels of uncertainty (rs = -0.20, P-value < 0.001). Lower perceived helpfulness of the genetic counselor, along with less perceived personal control, less benefit of a diagnosis, and lower parental age were significant predictors of the highest perceptions of uncertainty. The Transactional Model of Stress and Coping was used as a framework for interpreting the relationships between parental uncertainty, perceived control, and outcome variables. There was a significant positive correlation between parents' perceived personal control and their reports of helpfulness of the genetic counselor (rs = 0.20, P-value <0.0006). Genetic counseling can be enhanced for parents faced with rare disorders by using interventions focused on reducing feelings of uncertainty and enhancing feelings of control.

Adaptation, Psychological↗

PubMed2005

Kinetics of peat soil dissolved organic carbon release to surface water. Part 2. A chemodynamic process model.

Temporary water reservoirs built upon peat soil may exhibit water quality impairment from elevated dissolved organic carbon (DOC). Microbiological decay of the organic carbon in the bed with subsequent release produces "tea" colored water which may require treatment prior to use. This paper contains a process-based mathematical model that quantifies the DOC release from the bed and its build-up in the water column. The model elements are based on microbial DOC production rates and bed sediment transport kinetics describing its' release from the organic soil systems. It relies on laboratory data obtained from an experimental study, Part 1, designed to simulate the DOC chemodynamics of aquatic reservoirs built upon peat soils. A two-step DOC release process was structured based on the experimental findings. The model mechanism assumes a quick release fraction that characterizes the upper soil surface layers as a "tea bag" type release process. This is followed by a fraction that is continuously produced and then released at a constant rate overtime by on-going microbial processes within the upper soil layers. The depth of the active layer, selected as h* = 0.3 cm, is the single adjustable parameter in the model. Concentration predictions of the are consistent with the laboratory simulations and field observations. Measured vs. model-calculated DOC concentrations for both in the microcosm bed and water column are used to test critical features of the proposed model. As conceived and structured it appears to be a realistic first step in quantifying the DOC release consequences for the water column of a reservoir sited upon a peat-soil bed. The development ends with an application to a hypothetical reservoir in order to illustrate model strengths and uncertainties.

Algorithms↗

PubMed1998

Physiologically based pharmacokinetic model for chronic inhalation of 2-butoxyethanol.

2-Butoxyethanol (2BE) is used extensively in the production of cleaning agents and as a general solvent. It is primarily metabolized in the liver to 2-butoxyacetic acid (2BAA), which is excreted in urine. The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model describing the toxicokinetic behavior of 2BE and 2BAA in different species following repeated, long-term exposures. The PBPK model was first developed for short-term 2BE exposure to male rats. Allometric scaling was employed to estimate physiological and biochemical model parameters based on body weight. To accommodate differences in 2BE toxicokinetics in female rats, a higher Vmax for 2BE metabolism to 2BAA, higher plasma protein binding sites for 2BAA, and lower Vmax for 2BAA excretion through the kidney were incorporated into the model. For mice, a higher Vmax for 2BE metabolism to 2BAA for both sexes and higher plasma protein binding sites for 2BAA for female mice were also incorporated into the model. Subsequently, the model was expanded to simulate 2BE and 2BAA toxicokinetics for long-term, repeated exposures by incorporating time-dependent changes in model parameters. To reflect physiological/biochemical changes in animals during a chronic exposure, parameters for cardiac output, body composition, metabolic capacity, protein binding, or capacity of renal excretion were adjusted over time depending on species and sex. Sensitivity analysis was performed to better understand how sensitive model responses were to uncertainties in input parameters. The resulting PBPK model was used to simulate toxicokinetic data acquired during a 2-year inhalation toxicity and carcinogenicity study in male and female F344/N rats and B6C3F1 mice.

Administration, Inhalation↗

PubMed2004

Vapor-phase transport of explosives from buried sources in soils.

The fate and transport of explosives in the soil pore vapor spaces affects both the potential detection of buried ordnance by chemical sensors and vadose zone transport of explosives residues. The efficacy of chemical sensors and their potential usefulness for detecting buried unexploded ordnance (UXO) is difficult to determine without understanding how its chemical signatures are transported through soil. The objectives of this study were to quantify chemical signature transport through soils under various environmental conditions in unsaturated soils and to develop a model for the same. Flux chambers, large soil containers, and batch tests were used to determine explosives signature movement and process descriptors for model development. Low signatures were observed for explosives (2,4-dinitrotoluene, 2,6-dinitrotoluene, and 1,3-dinitrobenzene) under all environmental conditions. A diffusion model was used to describe the chemical transport mechanism in the soil pore air. The soil-air partition constant was treated as a fit parameter in the model owing to the uncertainty in its a priori estimation. The model predictions of the trends in experimental fluxes and the soil concentration were only marginal at best. It was concluded that better estimates of the partition constant are required for more accurate estimation of the chemical concentration at the soil-air interface. Chemical sensors will need to be very sensitive because of low signatures. However, this may result in many false alarms because of explosives residues not associated with UXO on firing ranges. Low explosives signatures also should result in insignificant air environmental exposures.

Air Pollutants↗

PubMed2005

The choice of a genetic model in the meta-analysis of molecular association studies.

BACKGROUND: To evaluate gene-disease associations, genetic epidemiologists collect information on the disease risk in subjects with different genotypes (for a bi-allelic polymorphism: gg, Gg, GG). Meta-analyses of such studies usually reduce the problem to a single comparison, either by performing two separate pairwise comparisons or by assuming a specific underlying genetic model (recessive, co-dominant, dominant). A biological justification for the choice of the genetic model is seldom available. METHODS: We present a genetic model-free approach, which does not assume that the underlying genetic model is known in advance but still makes use of the information available on all genotypes. The approach uses OR(GG), the odds ratio between the homozygous genotypes, to capture the magnitude of the genetic effect, and lambda, the heterozygote log odds ratio as a proportion of the homozygote log odds ratio, to capture the genetic mode of inheritance. The analysis assumes that the same unknown genetic model, i.e. the same lambda, applies in all studies, and this is investigated graphically. The approach is illustrated using five examples of published meta-analyses. RESULTS: Analyses based on specific genetic models can produce misleading estimates of the odds ratios when an inappropriate model is assumed. The genetic model-free approach gives appropriately wider confidence intervals than genetic model-based analyses because it allows for uncertainty about the genetic model. In terms of assessment of model fit, it performs at least as well as a bivariate pairwise analysis in our examples. CONCLUSIONS: The genetic model-free approach offers a unified approach that efficiently estimates the genetic effect and the underlying genetic model. A bivariate pairwise analysis should be used if the assumption of a common genetic model across studies is in doubt.

Cardiovascular Diseases↗

PubMed2002

Vapor phase transport of unexploded ordnance compounds through soils.

Unexploded ordnance (UXO) is a source of concern at several U.S. Department of Defense (DOD) sites. Localization of munitions and fate and transport of the explosive compounds from these munitions are a major issue of concern. A set of laboratory experiments were conducted in specially designed flux chambers to measure the evaporative flux of three explosive compounds (2,4-dinitrotoluene, 2,6-dinitrotoluene, and 1,3-dinitrobenzene) from three different soils. The effect of different soil moisture contents, the relative humidity of air contacting the soil surface, and soil temperature on the chemical fluxes were evaluated. A diffusion model was used to describe the chemical transport mechanism in the soil pore air. The soil-air partition constant was treated as a fit parameter in the model because of the uncertainty in the a priori estimation. The model predicts the qualitative trends of the experimental fluxes satisfactorily. Under extremely dry conditions, the flux decreased more rapidly than that predicted by the model. The fluxes from soils at 24 degrees C were higher than those at 14 degrees C, indicating a larger volatilization driving force at the higher temperature.

Adsorption↗

PubMed2000

A tiered approach to deterministic models for indoor air exposures.

There are a number of deterministic mathematical approaches available for modeling indoor air pollution concentrations. These models range in complexity from simple saturation vapor pressure models to models using computational fluid dynamics, with many in between these extremes. This range reflects the variety of ways pollutant generation, transport, and mixing are treated in the different models. In selecting which model to use, a tiered approach is useful. The tiered approach considers the goal of the modeling, the availability of model inputs, and the degree of uncertainty that is acceptable. The simpler models are easy to use and the inputs are often readily available. However, they usually have an inherently high degree of uncertainty which requires conservative assumptions that may result in overestimates of concentrations. The more complex models are more difficult to use and require more precise inputs. However, they have the potential to allow the modeler to reduce or quantify uncertainty. This ability to address uncertainty may be limited by the understanding of and the availability of the model inputs. An application example of the tiered approach using a completely mixed space model, a two-zone model, and a turbulent diffusion model illustrates the selection criteria for model use and the model performances. Ultimately, an understanding of the principles behind the models and their inherent strengths and weaknesses is required for their appropriate application to exposure assessment.

Air Movements↗

PubMed2004

A TCP-NTCP estimation module using DVHs and known radiobiological models and parameter sets.

Radiotherapy treatment plan evaluation relies on an implicit estimation of the tumor control probability (TCP) and normal tissue complication probability (NTCP) arising from a given dose distribution. A potential application of radiobiological modeling to radiotherapy is the ranking of treatment plans via a more explicit determination of TCP and NTCP values. Although the limited predictive capabilities of current radiobiological models prevent their use as a primary evaluative tool, radiobiological modeling predictions may still be a valuable complement to clinical experience. A convenient computational module has been developed for estimating the TCP and the NTCP arising from a dose distribution calculated by a treatment planning system, and characterized by differential (frequency) dose-volume histograms (DDVHs). The radiobiological models included in the module are sigmoidal dose response and Critical Volume NTCP models, a Poisson TCP model, and a TCP model incorporating radiobiological parameters describing linear-quadratic cell kill and repopulation. A number of sets of parameter values for the different models have been gathered in databases. The estimated parameters characterize the radiation response of several different normal tissues and tumor types. The system also allows input and storage of parameters by the user, which is particularly useful because of the rapidly increasing number of parameter estimates available in the literature. Potential applications of the system include the following: comparing radiobiological predictions of outcome for different treatment plans or types of treatment; comparing the number of observed outcomes for a cohort of patient DVHs to the predicted number of outcomes based on different models/parameter sets; and testing of the sensitivity of model predictions to uncertainties in the parameter values. The module thus helps to amalgamate and make more accessible current radiobiological modeling knowledge, and may serve as a useful aid in the prospective and retrospective analysis of radiotherapy treatment plans.

Body Burden↗

PubMed2006

Estimating the abundance of mouse populations of known size: promises and pitfalls of new methods.

Knowledge of animal abundance is fundamental to many ecological studies. Frequently, researchers cannot determine true abundance, and so must estimate it using a method such as mark-recapture or distance sampling. Recent advances in abundance estimation allow one to model heterogeneity with individual covariates or mixture distributions and to derive multimodel abundance estimators that explicitly address uncertainty about which model parameterization best represents truth. Further, it is possible to borrow information on detection probability across several populations when data are sparse. While promising, these methods have not been evaluated using mark-recapture data from populations of known abundance, and thus far have largely been overlooked by ecologists. In this paper, we explored the utility of newly developed mark-recapture methods for estimating the abundance of 12 captive populations of wild house mice (Mus musculus). We found that mark-recapture methods employing individual covariates yielded satisfactory abundance estimates for most populations. In contrast, model sets with heterogeneity formulations consisting solely of mixture distributions did not perform well for several of the populations. We show through simulation that a higher number of trapping occasions would have been necessary to achieve good estimator performance in this case. Finally, we show that simultaneous analysis of data from low abundance populations can yield viable abundance estimates.

Animals↗

PubMed2001

Estimates of the distributions of forest ecosystem model inputs for deciduous forests of eastern North America.

Techniques for evaluating uncertainties in process-based, computer simulation models are evolving in response to the proliferation of such models and the demand for their use in the management of forest ecosystems. Many evaluation techniques require precise statements of the uncertainties associated with each model input. Statements of uncertainty are typically formulated as probability density functions (pdfs). Here, pdfs are developed for 29 inputs of the process-based, forest ecosystem, computer simulation model PnET-II, many of which are inputs to other well-known forest ecosystem models. The inputs considered describe vegetation characteristics of forests typical of the Eastern Deciduous Forest biome of North America. Data were compiled largely from published literature to estimate pdfs. The compiled distributions can be used to conduct various model evaluations including uncertainty assessment, calibration, and sensitivity analysis.

Ecosystem↗

PubMed2004

Probabilistic uncertainty analysis of the European Union system for the evaluation of substances multimedia regional distribution model.

The European Union System for the Evaluation of Substances (EUSES) is a computerized model system to facilitate and harmonize health and environmental risk assessment of previously notified and new substances. For calculation of regional background exposure, a multimedia distribution model is used. In the present study, the uncertainty of this regional model is analyzed. Environmental parameters were collected for North Rhine Westphalia (Germany), which resembles the standard region of EUSES. Probability distribution functions of various types (uniform, triangular, normal, log normal) depending on data availability were derived for environmental input parameters, including geometric parameters. Generic log-normal distribution functions with fixed standard deviations were chosen for solubility in air, water, and n-octanol as well as for degradation half-lives. Monte Carlo simulations were carried out for 10 reference substances having different properties. Contribution of environmental parameter uncertainty to total output uncertainties is higher than that of substance parameters. Range of output uncertainty, defined as the ratio of the logarithms of the 90th and 10th percentiles of the cumulative probability distribution function, shows an increase from air and water to soil. The highest-occurring range is 1.4 orders of magnitude, which means that total uncertainty of the regional model is relatively low and, usually, is lower than the range of measured values. The median of output probability distributions lies above the point estimate. Influence of input parameters was estimated as their rank correlation coefficients to output uncertainty. Substance and environmental parameters contribute differently to output variance depending on individual substance properties and environmental compartment. Hence, the present study underlines the need to perform uncertainty analyses instead of either using a set of simple rules or just looking at certain parameters.

Environment↗

PubMed2006

A weighted bootstrap method for the determination of probability density functions of freshwater distribution coefficients (Kds) of Co, Cs, Sr and I radioisotopes.

The objective of the study was to provide global probability density functions (PDFs) representing the uncertainty of distribution coefficients (Kds) in freshwater for radioisotopes of Co, Cs, Sr and I. A comprehensive database containing Kd values referenced in 61 articles was first built and quality scores were affected to each data point according to various criteria (e.g. presentation of data, contact times, pH, solid-to-liquid ratio, expert judgement). A weighted bootstrapping procedure was then set up in order to build PDFs, in such a way that more importance is given to the most relevant data points (i.e. those corresponding to typical natural environments). However, it was also assessed that the relevance and the robustness of the PDFs determined by our procedure depended on the number of Kd values in the database. Owing to the large database, conditional PDFs were also proposed, for site studies where some parametric information is known (e.g. pH, contact time between radionuclides and particles, solid-to-liquid ratio). Such conditional PDFs reduce the uncertainty on the Kd values. These global and conditional PDFs are useful for end-users of dose models because the uncertainty and sensitivity of Kd values are taking into account.

Cesium↗

PubMed1991

Interstitial adenosine concentration during norepinephrine infusion in isolated guinea pig hearts.

This study determined the effect of norepinephrine (NE) on cardiac interstitial fluid adenosine concentration [( ADO]isf). Isolated guinea pig hearts were perfused with a Krebs-Henseleit buffer solution. Radiolabeled albumin, sucrose, and adenosine were injected under control conditions and after 3 and 20 min of NE infusion to obtain multiple indicator dilution curves that were used to determine capillary transport parameters for adenosine. These parameters together with venous adenosine concentrations were used in a mathematical model to a calculate [ADO]isf. Capillary transport parameters were not changed significantly by NE infusion. Because of uncertainty regarding two model parameters, two sets of [ADO]isf values were calculated. One set used best-fit values obtained from indicator dilution curves, and a second set used parameters chosen to provide the highest [ADO]isf values consistent with indicator dilution curves. Venous adenosine concentrations were 1.9 +/- 0.4 nM under control conditions and 243 +/- 110 and 45 +/- 25 nM after 3 and 20 min of NE infusion, respectively. Calculated [ADO]isf was 2.6-9.4, 591-1,288, and 166-324 nM, respectively, under these same conditions. We conclude that NE infusion greatly increases [ADO]isf, and adenosine is responsible for most of the vasodilation at 3 min. The subsequent fall in venous concentration is due to a fall in [ADO]isf rather than to decreased capillary permeability. Vascular resistance remained low while [ADO]isf fell, which suggests that additional vasodilators are important during maintained NE infusion.

Adenosine↗