Estimating the burden of disease attributable to childhood and maternal undernutrition in South Africa in 2000

OBJECTIVES To estimate the disease burden attributable to being underweight as an indicator of undernutrition in children under 5 years of age and in pregnant women for the year 2000. DESIGN World Health Organization comparative risk assessment (CRA) methodology was followed. The 1999 National Food Consumption Survey prevalence of underweight classified in three low weight-for-age categories was compared with standard growth charts to estimate population-attributable fractions for mortality and morbidity outcomes, based on increased risk for each category and applied to revised burden of disease estimates for South Africa in 2000. Maternal underweight, leading to an increased risk of intra-uterine growth retardation and further risk of low birth weight (LBW), was also assessed using the approach adopted by the global assessment. Monte Carlo simulation-modeling techniques were used for the uncertainty analysis. SETTING South Africa. SUBJECTS Children under 5 years of age and pregnant women. OUTCOME MEASURES Mortality and disability-adjusted life years (DALYs) from protein- energy malnutrition and a fraction of those from diarrhoeal disease, pneumonia, malaria, other non- HIV/AIDS infectious and parasitic conditions in children aged 0 - 4 years, and LBW. RESULTS Among children under 5 years, 11.8% were underweight. In the same age group, 11,808 deaths (95% uncertainty interval 11,100 - 12,642) or 12.3% (95% uncertainty interval 11.5 - 13.1%) were attributable to being underweight. Protein-energy malnutrition contributed 44.7% and diarrhoeal disease 29.6% of the total attributable burden. Childhood and maternal underweight accounted for 2.7% (95% uncertainty interval 2.6 - 2.9%) of all DALYs in South Africa in 2000 and 10.8% (95% uncertainty interval 10.2 - 11.5%) of DALYs in children under 5. CONCLUSIONS The study shows that reduction of the occurrence of underweight would have a substantial impact on child mortality, and also highlights the need to monitor this important indicator of child health.

Estimating the burden of disease attributable to diabetes in South Africa in 2000

OBJECTIVES To estimate the burden of disease attributable to diabetes by sex and age group in South Africa in 2000. DESIGN The framework adopted for the most recent World Health Organization comparative risk assessment (CRA) methodology was followed. Small community studies used to derive the prevalence of diabetes by population group were weighted proportionately for a national estimate. Population-attributable fractions were calculated and applied to revised burden of disease estimates. Monte Carlo simulation-modelling techniques were used for uncertainty analysis. SETTING South Africa. SUBJECTS Adults 30 years and older. OUTCOME MEASURES Mortality and disability-adjusted life years (DALYs) for ischaemic heart disease (IHD), stroke, hypertensive disease and renal failure. RESULTS Of South Africans aged >or= 30 years, 5.5% had diabetes which increased with age. Overall, about 14% of IHD, 10% of stroke, 12% of hypertensive disease and 12% of renal disease burden in adult males and females (30+ years) were attributable to diabetes. Diabetes was estimated to have caused 22,412 (95% uncertainty interval 20,755 - 24,872) or 4.3% (95% uncertainty interval 4.0 - 4.8%) of all deaths in South Africa in 2000. Since most of these occurred in middle or old age, the loss of healthy life years comprises a smaller proportion of the total 258,028 DALYs (95% uncertainty interval 236,856 - 290,849) in South Africa in 2000, accounting for 1.6% (95% uncertainty interval 1.5 - 1.8%) of the total burden. CONCLUSIONS Diabetes is an important direct and indirect cause of burden in South Africa. Primary prevention of the disease through multi-level interventions and improved management at primary health care level are needed.

Estimating the burden of disease attributable to iron deficiency anaemia in South Africa in 2000

OBJECTIVES To estimate the extent of iron deficiency anaemia (IDA) among children aged 0 - 4 years and pregnant women aged 15 - 49 years, and the burden of disease attributed to IDA in South Africa in 2000. DESIGN The comparative risk assessment (CRA) methodology of the World Health Organization (WHO) was followed using local prevalence and burden estimates. IDA prevalence came from re-analysis of the South African Vitamin A Consultative Group study in the case of the children, and from a pooled estimate from several studies in the case of the pregnant women (haemoglobin level < 11 g/dl and ferritin level < 12 microg/l). Monte Carlo simulation-modelling was used for the uncertainty analysis. SETTING South Africa. SUBJECTS Children under 5 years and pregnant women 15 - 49 years. OUTCOME MEASURES Direct sequelae of IDA, maternal and perinatal deaths and disability-adjusted life years (DALYs) from mild mental disability related to IDA. Results. It is estimated that 5.1% of children and 9 - 12% of pregnant women had IDA and that about 7.3% of perinatal deaths and 4.9% of maternal deaths were attributed to IDA in 2000. Overall, about 174,976 (95% uncertainty interval 150,344 - 203,961) healthy years of life lost (YLLs), or between 0.9% and 1.3% of all DALYs in South Africa in 2000, were attributable to IDA. CONCLUSIONS This first study in South Africa to quantify the burden from IDA suggests that it is a less serious public health problem in South Africa than in many other developing countries. Nevertheless, this burden is preventable, and the study highlights the need to disseminate the food-based dietary guidelines formulated by the National Department of Health to people who need them and to monitor the impact of the food fortification programme.

Estimating the under-reporting of road crash injuries to police using multiple linked data collections

The reliance on police data for the counting of road crash injuries can be problematic, as it is well known that not all road crash injuries are reported to police which under-estimates the overall burden of road crash injuries. The aim of this study was to use multiple linked data sources to estimate the extent of under-reporting of road crash injuries to police in the Australian state of Queensland. Data from the Queensland Road Crash Database (QRCD), the Queensland Hospital Admitted Patients Data Collection (QHAPDC), Emergency Department Information System (EDIS), and the Queensland Injury Surveillance Unit (QISU) for the year 2009 were linked. The completeness of road crash cases reported to police was examined via discordance rates between the police data (QRCD) and the hospital data collections. In addition, the potential bias of this discordance (under-reporting) was assessed based on gender, age, road user group, and regional location. Results showed that the level of under-reporting varied depending on the data set with which the police data was compared. When all hospital data collections are examined together the estimated population of road crash injuries was approximately 28,000, with around two-thirds not linking to any record in the police data. The results also showed that the under-reporting was more likely for motorcyclists, cyclists, males, young people, and injuries occurring in Remote and Inner Regional areas. These results have important implications for road safety research and policy in terms of: prioritising funding and resources; targeting road safety interventions into areas of higher risk; and estimating the burden of road crash injuries.

Estimating link-dependent origin-destination matrices from sample trajectories and traffic counts

Origin-Destination matrices (ODM) estimation can benefits of the availability of sample trajectories which can be measured thanks to recent technologies. This paper focus on the case of transport networks where traffic counts are measured by magnetic loops and sample trajectories available. An example of such network is the city of Brisbane, where Bluetooth detectors are now operating. This additional data source is used to extend the classical ODM estimation to a link-specific ODM (LODM) one using a convex optimisation resolution that incorporates networks constraints as well. The proposed algorithm is assessed on a simulated network.

A method for estimating intrinsic noise in electroretinographic (ERG) signals

Purpose To develop a signal processing paradigm for extracting ERG responses to temporal sinusoidal modulation with contrasts ranging from below perceptual threshold to suprathreshold contrasts. To estimate the magnitude of intrinsic noise in ERG signals at different stimulus contrasts. Methods Photopic test stimuli were generated using a 4-primary Maxwellian view optical system. The 4-primary lights were sinusoidally temporally modulated in-phase (36 Hz; 2.5 - 50% Michelson). The stimuli were presented in 1 s epochs separated by a 1 ms blank interval and repeated 160 times (160.16 s duration) during the recording of the continuous flicker ERG from the right eye using DTL fiber electrodes. After artefact rejection, the ERG signal was extracted using Fourier methods in each of the 1 s epochs where a stimulus was presented. The signal processing allows for computation of the intrinsic noise distribution in addition to the signal to noise (SNR) ratio. Results We provide the initial report that the ERG intrinsic noise distribution is independent of stimulus contrast whereas SNR decreases linearly with decreasing contrast until the noise limit at ~2.5%. The 1ms blank intervals between epochs de-correlated the ERG signal at the line frequency (50 Hz) and thus increased the SNR of the averaged response. We confirm that response amplitude increases linearly with stimulus contrast. The phase response shows a shallow positive relationship with stimulus contrast. Conclusions This new technique will enable recording of intrinsic noise in ERG signals above and below perceptual visual threshold and is suitable for measurement of continuous rod and cone ERGs across a range of temporal frequencies, and post-receptoral processing in the primary retinogeniculate pathways at low stimulus contrasts. The intrinsic noise distribution may have application as a biomarker for detecting changes in disease progression or treatment efficacy.

Exploring accuracy factors in cost estimating practice towards implementing Building Information Modelling (BIM)

Cost estimating has been acknowledged as a crucial component of construction projects. Depending on available information and project requirements, cost estimates evolve in tandem with project lifecycle stages; conceptualisation, design development, execution and facility management. The premium placed on the accuracy of cost estimates is crucial to producing project tenders and eventually in budget management. Notwithstanding the initial slow pace of its adoption, Building Information Modelling (BIM) has successfully addressed a number of challenges previously characteristic of traditional approaches in the AEC, including poor communication, the prevalence of islands of information and frequent reworks. Therefore, it is conceivable that BIM can be leveraged to address specific shortcomings of cost estimation. The impetus for leveraging BIM models for accurate cost estimation is to align budgeted and actual cost. This paper hypothesises that the accuracy of BIM-based estimation, as more efficient, process-mirrors of traditional cost estimation methods, can be enhanced by simulating traditional cost estimation factors variables. Through literature reviews and preliminary expert interviews, this paper explores the factors that could potentially lead to more accurate cost estimates for construction projects. The findings show numerous factors that affect the cost estimates ranging from project information and its characteristic, project team, clients, contractual matters, and other external influences. This paper will make a particular contribution to the early phase of BIM-based project estimation.

Cost estimating practice incorporating Building Information Modelling (BIM): Malaysian Quantity Surveyors perspectives

Cost estimating is a key task within Quantity Surveyors’ (QS) offices. Provision of an accurate estimate is vital to ensure that the objectives of the client are met by staying within the client’s budget. Building Information Modelling (BIM) is an evolving technology that has gained attention in the construction industries all over the world. Benefits from the use of BIM include cost and time savings if the processes used by the procurement team are adapted to maximise the benefits of BIM. BIM can be used by QSs to automate aspects of quantity take-off and the preparation of estimates, decreasing turnaround time and assist in controlling errors and inaccuracies. The Malaysian government has decided to require the use of BIM for its projects beginning from 2016. However, slow uptake is reported in the use of BIM both within companies and to support collaboration within the Malaysian industry. It has been recommended that QSs to start evaluating the impact of BIM on their practices. This paper reviews the perspectives of QSs in Malaysia towards the use of BIM to achieve more dependable results in their cost estimating practice. The objectives of this paper include identifying strategies in improving practice and potential adoption drivers that lead QSs to BIM usage in their construction projects. From the expert interviews, it was found out that, despite still using traditional methods and not practising BIM, the interviewees still acquire limited knowledge related to BIM. There are some drivers that potentially motivate them to employ BIM in their practices. These include client demands, innovation in traditional methods, speed in estimating costs, reduced time and costs, improvement in practices and self-awareness, efficiency in projects, and competition from other companies. The findings of this paper identify the potential drivers in encouraging Malaysian Quantity Surveyors to exploit BIM in their construction projects.

Estimating the potential impact of entry fees for marine parks on dive tourism in South East Asia

Marine reserves are increasingly being established as a mechanism to protect marine biodiversity and sensitive habitats. As well as providing conservation benefits, marine reserves provide benefits to recreational scuba divers who dive within the reserve, as well as to recreational and commercial fishers outside the reserve through spill-over effects. To ensure benefits are being realised, management of marine reserves requires ongoing monitoring and surveillance. These are not costless, and many marine reserve managers impose an entry fee. In some countries, dive tourism is major income source to coastal industries, and a concern is that high entry fees may dissuade divers. In this paper, the price elasticity of demand for dive tourism in three countries in South East Asia – Indonesia, Thailand and Malaysia – is estimated using a travel-cost model. From the model, the total non-market use value associated with diving in the area is estimated to be in the order of US$4.5 billion a year. The price elasticity of demand in the region is highly inelastic, such that increasing the cost of diving through a management levy would have little impact on total diver numbers.

Estimating daily and diurnal variations of illicit drug use in Hong Kong: A pilot study of using wastewater analysis in an Asian metropolitan city

The measurement of illicit drug metabolites in raw wastewater is increasingly being adopted as an approach to objectively monitor population-level drug use, and is an effective complement to traditional epidemiological methods. As such, it has been widely applied in western countries. In this study, we utilised this approach to assess drug use patterns over nine days during April 2011 in Hong Kong. Raw wastewater samples were collected from the largest wastewater treatment plant serving a community of approximately 3.5 million people and analysed for excreted drug residues including cocaine, ketamine, methamphetamine, 3,4-methylenedioxymethamphetamine (MDMA) and key metabolites using liquid chromatography coupled with tandem mass spectrometry. The overall drug use pattern determined by wastewater analysis was consistent with that have seen amongst people coming into contact with services in relation to substance use; among our target drugs, ketamine (estimated consumption: 1400–1600 mg/day/1000 people) was the predominant drug followed by methamphetamine (180–200 mg/day/1000 people), cocaine (160–180 mg/day/1000 people) and MDMA (not detected). The levels of these drugs were relatively steady throughout the monitoring period. Analysing samples at higher temporal resolution provided data on diurnal variations of drug residue loads. Elevated ratios of cocaine to benzoylecgonine were identified unexpectedly in three samples during the evening and night, providing evidence for potential dumping events of cocaine. This study provides the first application of wastewater analysis to quantitatively evaluate daily drug use in an Asian metropolitan community. Our data reinforces the benefit of wastewater monitoring to health and law enforcement authorities for strategic planning and evaluation of drug intervention strategies.

Estimating the parameters of stochastic volatility models using option price data

This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

Working covariance model selection for generalized estimating equations

We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice.

Discussion of “Generalized estimating equations: Notes on the choice of the working correlation matrix”

Objective To discuss generalized estimating equations as an extension of generalized linear models by commenting on the paper of Ziegler and Vens "Generalized Estimating Equations. Notes on the Choice of the Working Correlation Matrix". Methods Inviting an international group of experts to comment on this paper. Results Several perspectives have been taken by the discussants. Econometricians have established parallels to the generalized method of moments (GMM). Statisticians discussed model assumptions and the aspect of missing data Applied statisticians; commented on practical aspects in data analysis. Conclusions In general, careful modeling correlation is encouraged when considering estimation efficiency and other implications, and a comparison of choosing instruments in GMM and generalized estimating equations, (GEE) would be worthwhile. Some theoretical drawbacks of GEE need to be further addressed and require careful analysis of data This particularly applies to the situation when data are missing at random.