The burden of mental disorders: a comparison of methods between the Australian burden of disease studies and the Global Burden of Disease study

The national and Victorian burden of disease studies in Australia set out to examine critically the methods used in the Global Burden of Disease study to estimate the burden of mental disorders. The main differences include the use of a different set of disability weights allowing estimates in greater detail by level of severity, adjustments for comorbidity between mental disorders, a greater number of menta I disorders measured, and model ling of substance use disorders, anxiety disorders and bipolar disorder as chronic conditions. Uniform age-weighting in the Australian studies produces considerably lower estimates of the burden due to mental disorders in comparison with age-weighted disability-adjusted life years. A lack of follow-up data on people with mental disorders who are identified in cross-sectional surveys poses the greatest challenge in determining the burden of mental disorders more accurately.

Small area population disease burden

Small area health statistics has assumed increasing importance as the focus of population and public health moves to a more individualised approach of smaller area populations. Small populations and low event occurrence produce difficulties in interpretation and require appropriate statistical methods, including for age adjustment. There are also statistical questions related to multiple comparisons. Privacy and confidentiality issues include the possibility of revealing information on individuals or health care providers by fine cross-tabulations. Interpretation of small area population differences in health status requires consideration of migrant and Indigenous composition, socio-economic status and rural-urban geography before assessment of the effects of physical environmental exposure and services and interventions. Burden of disease studies produce a single measure for morbidity and mortality - disability adjusted life year (DALY) - which is the sum of the years of life lost (YLL) from premature mortality and the years lived with disability (YLD) for particular diseases (or all conditions). Calculation of YLD requires estimates of disease incidence (and complications) and duration, and weighting by severity. These procedures often mean problematic assumptions, as does future discounting and age weighting of both YLL and YLD. Evaluation of the Victorian small area population disease burden study presents important cross-disciplinary challenges as it relies heavily on synthetic approaches of demography and economics rather than on the empirical methods of epidemiology. Both empirical and synthetic methods are used to compute small area mortality and morbidity, disease burden, and then attribution to risk factors. Readers need to examine the methodology and assumptions carefully before accepting the results.

ANNA: A new prediction method for bioassessment programs

1. Cluster analysis of reference sites with similar biota is the initial step in creating River Invertebrate Prediction and Classification System (RIVPACS) and similar river bioassessment models such as Australian River Assessment System (AUSRIVAS). This paper describes and tests an alternative prediction method, Assessment by Nearest Neighbour Analysis (ANNA), based on the same philosophy as RIVPACS and AUSRIVAS but without the grouping step that some people view as artificial. 2. The steps in creating ANNA models are: (i) weighting the predictor variables using a multivariate approach analogous to principal axis correlations, (ii) calculating the weighted Euclidian distance from a test site to the reference sites based on the environmental predictors, (iii) predicting the faunal composition based on the nearest reference sites and (iv) calculating an observed/expected (O/E) analogous to RIVPACS/AUSRIVAS. 3. The paper compares AUSRIVAS and ANNA models on 17 datasets representing a variety of habitats and seasons. First, it examines each model's regressions for Observed versus Expected number of taxa, including the r(2), intercept and slope. Second, the two models' assessments of 79 test sites in New Zealand are compared. Third, the models are compared on test and presumed reference sites along a known trace metal gradient. Fourth, ANNA models are evaluated for western Australia, a geographically distinct region of Australia. The comparisons demonstrate that ANNA and AUSRIVAS are generally equivalent in performance, although ANNA turns out to be potentially more robust for the O versus E regressions and is potentially more accurate on the trace metal gradient sites. 4. The ANNA method is recommended for use in bioassessment of rivers, at least for corroborating the results of the well established AUSRIVAS- and RIVPACS-type models, if not to replace them.

Sensitivity and uncertainty analyses for burden of disease and risk factor estimates

Epidemiological studies report confidence or uncertainty intervals around their estimates. Estimates of the burden of diseases and risk factors are subject to a broader range of uncertainty because of the combination of multiple data sources and value choices. Sensitivity analysis can be used to examine the effects of social values that have been incorporated into the design of the disability–adjusted life year (DALY). Age weight, where a year of healthy life lived at one age is valued differently from at another age, is the most controversial value built into the DALY. The discount rate, which addresses the difference in value of current versus future health benefits, also has been criticized. The distribution of the global disease burden and rankings of various conditions are largely insensitive to alternate assumptions about the discount rate and age weighting. The major effects of discounting and age weighting are to enhance the importance of neuropsychiatric conditions and sexually transmitted infections. The Global Burden of Disease study also has been criticized for estimating mortality and disease burden for regions using incomplete and uncertain data. Including uncertain results, with uncertainty quantified to the extent possible, is preferable, however, to leaving blank cells in tables intended to provide policy makers with an overall assessment of burden of disease. No estimate is generally interpreted as no problem. Greater investment in getting the descriptive epidemiology of diseases and injuries correct in poor countries will do vastly more to reduce uncertainty in disease burden assessments than a philosophical debate about the appropriateness of social value

Population pharmacokinetics of lamotrigine

The present study estimated the population pharmacokinetics of lamotrigine in patients receiving oral lamotrigine therapy with drug concentration monitoring, and determined intersubject and intrasubject variability. A total of 129 patients were analyzed from two clinical sites. Of these, 124 patients provided spare data (198 concentration-time points); nine patients (four from a previous group plus five from the current group) provided rich data (431 points). The population analysis was conducted using P-PHARM (TM) (SIMED Scientific Software, Cedex, France), a nonlinear mixed-effect modeling program. A single exponential elimination model (first-order absorption) with heteroscedastic weighting was used. Apparent clearance (CL/F) and volume of distribution (V/F) were the pharmacokinetic parameters estimated. Covariate analysis was performed to determine which factors explained any of the variability associated with lamotrigine clearance. Population estimates of CL/F and V/F for lamotrigine generated in the final model were 2.14 +/- 0.81 L/h and 78.1 +/- 5.1 L/kg. Intersubject and intrasubject variability for clearance was 38% and 38%, respectively. The covariates of concomitant valproate and phenytoin therapy accounted for 42% of the intersubject variability of clearance. Age, gender, clinic site, and other concomitant antiepileptic drugs did not influence clearance. This study of the population pharmacokinetics of lamotrigine in patients using the drug clinically provides useful data and should lead to better dosage individualization for lamotrigine.

Direction selectivity in the retina

The neuronal circuitry underlying the generation of direction selectivity in the retina has remained elusive for almost 40 years. Recent studies indicate that direction selectivity may be established within the radial dendrites of 'starburst' amacrine cells and that retinal ganglion cells may acquire their direction selectivity by the appropriate weighting of excitatory and inhibitory inputs from starburst dendrites pointing in different directions. If so, this would require unexpected complexity and subtlety in the synaptic connectivity of these CNS neurons.

Segmenting the market of West Australian senior tourists using an artificial neural network

Measuring perceptions of customers can be a major problem for marketers of tourism and travel services. Much of the problem is to determine which attributes carry most weight in the purchasing decision. Older travellers weigh many travel features before making their travel decisions. This paper presents a descriptive analysis of neural network methodology and provides a research technique that assesses the weighting of different attributes and uses an unsupervised neural network model to describe a consumer-product relationship. The development of this rich class of models was inspired by the neural architecture of the human brain. These models mathematically emulate the neurophysical structure and decision making of the human brain, and, from a statistical perspective, are closely related to generalised linear models. Artificial neural networks or neural networks are, however, nonlinear and do not require the same restrictive assumptions about the relationship between the independent variables and dependent variables. Using neural networks is one way to determine what trade-offs older travellers make as they decide their travel plans. The sample of this study is from a syndicated data source of 200 valid cases from Western Australia. From senior groups, active learner, relaxed family body, careful participants and elementary vacation were identified and discussed. (C) 2003 Published by Elsevier Science Ltd.

Resolution enhancement by subtraction of confocal signals taken at different pinhole sizes

Subtractive imaging in confocal fluorescence light microscopy is based on the subtraction of a suitably weighted widefield image from a confocal image. An approximation to a widefield image can be obtained by detection with an opened confocal pinhole. The subtraction of images enhances the resolution in-plane as well as along the optic axis. Due to the linearity of the approach, the effect of subtractive imaging in Fourier-space corresponds to a reduction of low spatial frequency contributions leading to a relative enhancement of the high frequencies. Along the direction of the optic axis this also results in an improved sectioning. Image processing can achieve a similar effect. However, a 3D volume dataset must be acquired and processed, yielding a result essentially identical to subtractive imaging but superior in signal-to-noise ratio. The latter can be increased further with the technique of weighted averaging in Fourier-space. A comparison of 2D and 3D experimental data analysed with subtractive imaging, the equivalent Fourier-space processing of the confocal data only, and Fourier-space weighted averaging is presented. (C) 2003 Elsevier Ltd. All rights reserved.

Genetic algorithm optimization of adaptive multi-scale GLCM features

We introduce a new second-order method of texture analysis called Adaptive Multi-Scale Grey Level Co-occurrence Matrix (AMSGLCM), based on the well-known Grey Level Co-occurrence Matrix (GLCM) method. The method deviates significantly from GLCM in that features are extracted, not via a fixed 2D weighting function of co-occurrence matrix elements, but by a variable summation of matrix elements in 3D localized neighborhoods. We subsequently present a new methodology for extracting optimized, highly discriminant features from these localized areas using adaptive Gaussian weighting functions. Genetic Algorithm (GA) optimization is used to produce a set of features whose classification worth is evaluated by discriminatory power and feature correlation considerations. We critically appraised the performance of our method and GLCM in pairwise classification of images from visually similar texture classes, captured from Markov Random Field (MRF) synthesized, natural, and biological origins. In these cross-validated classification trials, our method demonstrated significant benefits over GLCM, including increased feature discriminatory power, automatic feature adaptability, and significantly improved classification performance.

Social indicators and comparisons of living standards

Construction of an international index of standards of living, incorporating social indicators and economic output, typically involves scaling and weighting procedures that lack welfare-economic foundations. Revealed preference axioms can be used to make quality-of-life comparisons if we can estimate the representative household's production technology for the social indicators. This method is applied to comparisons of gross domestic product (GDP) and life expectancy for 58 countries. Neither GDP rankings, nor the rankings of the Human Development Index (HDI), are consistent with the partial ordering of revealed preference. A method of constructing a utility-consistent index incorporating both consumption and life expectancy is suggested. (C) 2003 Elsevier Science B.V. All rights reserved.

Purchasing Power Parities for Industry Comparisons Using Weighted Elteto-Koves-Szulc (EKS) Methods

This study has three main objectives. First, it develops a generalization of the commonly used EKS method to multilateral price comparisons. It is shown that the EKS system can be generalized so that weights can be attached to each of the link comparisons used in the EKS computations. These weights can account for differing levels of reliability of the underlying binary comparisons. Second, various reliability measures and corresponding weighting schemes are presented and their merits discussed. Finally, these new methods are applied to an international data set of manufacturing prices from the ICOP project. Although theoretically superior, it appears that the empirical impact of the weighted EKS method is generally small compared to the unweighted EKS. It is also found that this impact is larger when it is applied at lower levels of aggregation. Finally, the importance of using sector specific PPPs in assessing relative levels of manufacturing productivity is indicated.

Capturing expert knowledge for threatened species assessments: a case study using NatureServe conservation status ranks

Assessments for assigning the conservation status of threatened species that are based purely on subjective judgements become problematic because assessments can be influenced by hidden assumptions, personal biases and perceptions of risks, making the assessment process difficult to repeat. This can result in inconsistent assessments and misclassifications, which can lead to a lack of confidence in species assessments. It is almost impossible to Understand an expert's logic or visualise the underlying reasoning behind the many hidden assumptions used throughout the assessment process. In this paper, we formalise the decision making process of experts, by capturing their logical ordering of information, their assumptions and reasoning, and transferring them into a set of decisions rules. We illustrate this through the process used to evaluate the conservation status of species under the NatureServe system (Master, 1991). NatureServe status assessments have been used for over two decades to set conservation priorities for threatened species throughout North America. We develop a conditional point-scoring method, to reflect the current subjective process. In two test comparisons, 77% of species' assessments using the explicit NatureServe method matched the qualitative assessments done subjectively by NatureServe staff. Of those that differed, no rank varied by more than one rank level under the two methods. In general, the explicit NatureServe method tended to be more precautionary than the subjective assessments. The rank differences that emerged from the comparisons may be due, at least in part, to the flexibility of the qualitative system, which allows different factors to be weighted on a species-by-species basis according to expert judgement. The method outlined in this study is the first documented attempt to explicitly define a transparent process for weighting and combining factors under the NatureServe system. The process of eliciting expert knowledge identifies how information is combined and highlights any inconsistent logic that may not be obvious in Subjective decisions. The method provides a repeatable, transparent, and explicit benchmark for feedback, further development, and improvement. (C) 2004 Elsevier SAS. All rights reserved.

The price elasticity of the Euro to movements in foreign reserves through European Central Bank intevention

The Euro has been used as the largest weighting element in a basket of currencies for forex arrangements adopted by several Central European countries outside the European Union (EU). The paper uses a new time-series approach to examine the relationship between the Euro exchange rate and the level of foreign reserves. It employs Zero-no-zero (ZNZ) patterned vector error-correction (VECM) modelling to investigate Granger causal relations among foreign reserves, the European Monetary Union money supply and the Euro exchange rate. The findings confirm that foreign reserves may influence movements in the Euro's exchange rate. Further, ZNZ patterned VECM modelling with exogenous variables is used to estimate the amount of foreign reserves currently required in order to again achieve a targetted Euro exchange rate

Investigations into a wideband spatial beamformer employing a rectangular array of planar monopoles

This paper presents a rectangular array antenna with a suitable signal-processing algorithm that is able to steer the beam in azimuth over a wide frequency band. In the previous approach, which was reported in the literature, an inverse discrete Fourier transform technique was proposed for obtaining the signal weighting coefficients. This approach was demonstrated for large arrays in which the physical parameters of the antenna elements were not considered. In this paper, a modified signal-weighting algorithm that works for arbitrary-size arrays is described. Its validity is demonstrated in examples of moderate-size arrays with real antenna elements. It is shown that in some cases, the original beam-forming algorithm fails, while the new algorithm is able to form the desired radiation pattern over a wide frequency band. The performance of the new algorithm is assessed for two cases when the mutual coupling between array elements is both neglected and taken into account.

A wideband array antenna with beam-steering capability using real valued weights

This article presents an array antenna with beam-steering capability in azimuth over a wide frequency band using real-valued weighting coefficients that can be realized in practice by amplifiers or attenuators. The described beamforming scheme relies on a 2D (instead of 1D) array structure in order to make sure that there are enough degrees of freedom to realize a given radiation pattern in both the angular and frequency domains. In the presented approach, weights are determined using an inverse discrete Fourier transform (IDFT) technique by neglecting the mutual coupling between array elements. Because of the presence of mutual coupling, the actual array produces a radiation pattern with increased side-lobe levels. In order to counter this effect, the design aims to realize the initial radiation pattern with a lower side-lobe level. This strategy is demonstrated in the design example of 4 X 4 element array. (C) 2005 Wiley Periodicals. Inc.