Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

The contribution of major depression to the global burden of ischemic heart disease : a comparative risk assessment

Background Cardiovascular disease and mental health both hold enormous public health importance, both ranking highly in results of the recent Global Burden of Disease Study 2010 (GBD 2010). For the first time, the GBD 2010 has systematically and quantitatively assessed major depression as an independent risk factor for the development of ischemic heart disease (IHD) using comparative risk assessment methodology. Methods A pooled relative risk (RR) was calculated from studies identified through a systematic review with strict inclusion criteria designed to provide evidence of independent risk factor status. Accepted case definitions of depression include diagnosis by a clinician or by non-clinician raters adhering to Diagnostic and Statistical Manual of Mental Disorders (DSM) or International Classification of Diseases (ICD) classifications. We therefore refer to the exposure in this paper as major depression as opposed to the DSM-IV category of major depressive disorder (MDD). The population attributable fraction (PAF) was calculated using the pooled RR estimate. Attributable burden was calculated by multiplying the PAF by the underlying burden of IHD estimated as part of GBD 2010. Results The pooled relative risk of developing IHD in those with major depression was 1.56 (95% CI 1.30 to 1.87). Globally there were almost 4 million estimated IHD disability-adjusted life years (DALYs), which can be attributed to major depression in 2010; 3.5 million years of life lost and 250,000 years of life lived with a disability. These findings highlight a previously underestimated mortality component of the burden of major depression. As a proportion of overall IHD burden, 2.95% (95% CI 1.48 to 4.46%) of IHD DALYs were estimated to be attributable to MDD in 2010. Eastern Europe and North Africa/Middle East demonstrate the highest proportion with Asia Pacific, high income representing the lowest. Conclusions The present work comprises the most robust systematic review of its kind to date. The key finding that major depression may be responsible for approximately 3% of global IHD DALYs warrants assessment for depression in patients at high risk of developing IHD or at risk of a repeat IHD event.

The global epidemiology and contribution of cannabis use and dependence to the global burden of disease: results from the GBD 2010 study

Aim Estimate the prevalence of cannabis dependence and its contribution to the global burden of disease. Methods Systematic reviews of epidemiological data on cannabis dependence (1990-2008) were conducted in line with PRISMA and meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Culling and data extraction followed protocols, with cross-checking and consistency checks. DisMod-MR, the latest version of generic disease modelling system, redesigned as a Bayesian meta-regression tool, imputed prevalence by age, year and sex for 187 countries and 21 regions. The disability weight associated with cannabis dependence was estimated through population surveys and multiplied by prevalence data to calculate the years of life lived with disability (YLDs) and disability-adjusted life years (DALYs). YLDs and DALYs attributed to regular cannabis use as a risk factor for schizophrenia were also estimated. Results There were an estimated 13.1 million cannabis dependent people globally in 2010 (point prevalence0.19% (95% uncertainty: 0.17-0.21%)). Prevalence peaked between 20-24 yrs, was higher in males (0.23% (0.2-0.27%)) than females (0.14% (0.12-0.16%)) and in high income regions. Cannabis dependence accounted for 2 million DALYs globally (0.08%; 0.05-0.12%) in 2010; a 22% increase in crude DALYs since 1990 largely due to population growth. Countries with statistically higher age-standardised DALY rates included the United States, Canada, Australia, New Zealand and Western European countries such as the United Kingdom; those with lower DALY rates were from Sub-Saharan Africa-West and Latin America. Regular cannabis use as a risk factor for schizophrenia accounted for an estimated 7,000 DALYs globally. Conclusion Cannabis dependence is a disorder primarily experienced by young adults, especially in higher income countries. It has not been shown to increase mortality as opioid and other forms of illicit drug dependence do. Our estimates suggest that cannabis use as a risk factor for schizophrenia is not a major contributor to population-level disease burden.

Estimating the burden of disease attributable to physical inactivity in South Africa in 2000

Objectives. To quantify the burden of disease attributable to physical inactivity in persons 15 years or older, by age group and sex, in South Africa for 2000. Design. The global comparative risk assessment (CRA) methodology of the World Health Organization was followed to estimate the disease burden attributable to physical inactivity. Levels of physical activity for South Africa were obtained from the World Health Survey 2003. A theoretical minimum risk exposure of zero, associated outcomes, relative risks, and revised burden of disease estimates were used to calculate population-attributable fractions and the burden attributed to physical inactivity. Monte Carlo simulation-modelling techniques were used for the uncertainty analysis. Setting. South Africa. Subjects. Adults ≥ 15 years. Outcome measures. Deaths and disability-adjusted life years (DALYs) from ischaemic heart disease, ischaemic stroke, breast cancer, colon cancer, and type 2 diabetes mellitus. Results. Overall in adults ≥ 15 years in 2000, 30% of ischaemic heart disease, 27% of colon cancer, 22% of ischaemic stroke, 20% of type 2 diabetes, and 17% of breast cancer were attributable to physical inactivity. Physical inactivity was estimated to have caused 17 037 (95% uncertainty interval 11 394 - 20 407), or 3.3% (95% uncertainty interval 2.2 - 3.9%) of all deaths in 2000, and 176 252 (95% uncertainty interval 133 733 - 203 628) DALYs, or 1.1% (95% uncertainty interval 0.8 - 1.3%) of all DALYs in 2000. Conclusions. Compared with other regions and the global average, South African adults have a particularly high prevalence of physical inactivity. In terms of attributable deaths, physical inactivity ranked 9th compared with other risk factors, and 12th in terms of DALYs. There is a clear need to assess why South Africans are particularly inactive, and to ensure that physical activity/inactivity is addressed as a national health priority.

Estimating the burden of disease attributable to high cholesterol in South Africa in 2000

Objectives To estimate the burden of disease attributable to high cholesterol in adults aged 30 years and older in South Africa in 2000. Design World Health Organization comparative risk assessment (CRA) methodology was followed. Small community studies were used to derive the prevalence by population group. Population-attributable fractions were calculated and applied to revised burden of disease estimates for the relevant disease categories for each population group. The total attributable burden for South Africa in 2000 was obtained by adding the burden attributed to high cholesterol for the four population groups. Monte Carlo simulation-modelling techniques were used for uncertainty analysis. Setting South Africa. Subjects Black African, coloured, white and Indian adults aged 30 years and older. Outcome measures Mortality and disability-adjusted life years (DALYs) from ischaemic heart disease (IHD) and ischaemic stroke. Results Overall, about 59% of IHD and 29% of ischaemic stroke burden in adult males and females (30+ years) were attributable to high cholesterol (≥ 3.8 mmol/l), with marked variation by population group. High cholesterol was estimated to have caused 24 144 deaths (95% uncertainty interval 22 404 - 25 286) or 4.6% (95% uncertainty interval 4.3 - 4.9%) of all deaths in South Africa in 2000. Since most cholesterol-related cardiovascular disease events occurred in middle or old age, the loss of life years comprised a smaller proportion of the total: 222 923 DALYs (95% uncertainty interval 206 712 - 233 460) or 1.4% of all DALYs (95% uncertainty interval 1.3 - 1.4%) in South Africa in 2000. Conclusions High cholesterol is an important cardiovascular risk factor in all population groups in South Africa.

Estimating the burden of disease attributable to urban outdoor air pollution in South Africa in 2000

Objectives To quantify the mortality burden attributed to urban outdoor air pollution in South Africa in 2000. Design The study followed comparative risk assessment (CRA) methodology developed by the World Heath Organization (WHO). In most urban areas, annual mean concentrations of particulate matter (PM) with diameters less than 10 μum (PM10) from monitoring network data and PM with diameters less than 2.5 μm (PM2.5) derived using a ratio method were weighted according to population size. PM10 and PM2.5 data from air-quality assessment studies in areas not covered by the network were also included. Population-attributable fractions calculated using risk coefficients presented in the WHO study were weighted by the proportion of the total population (33%) in urban environments, and applied to revised estimates of deaths and years of life lost (YLLs) for South Africa in 2000. Setting South Africa. Subjects Children under 5 years and adults 30 years and older. Outcome measures Mortality and YLLs from lung cancer and cardiopulmonary disease in adults (30 years and older), and from acute respiratory infections (ARIs) in children aged 0 - 4 years. Results Outdoor air pollution in urban areas in South Africa was estimated to cause 3.7% of the national mortality from cardiopulmonary disease and 5.1% of mortality attributable to cancers of the trachea, bronchus and lung in adults aged 30 years and older, and 1.1% of mortality from ARIs in children under 5 years of age. This amounts to 4 637 or 0.9% (95% uncertainty interval 0.3 - 1.5%) of all deaths and about 42 000 YLLs, or 0.4% (95% uncertainty interval 0.1 - 0.7%) of all YLLs in persons in South Africa in 2000. Conclusion Urban air pollution has under-recognised public health impacts in South Africa. Fossil fuel combustion emissions and traffic-related air pollution remain key targets for public health in South Africa.

Estimating the burden of disease attributable to lead exposure in South Africa in 2000

Objectives To estimate the burden of disease attributable to lead exposure in South Africa in 2000. Design World Health Organization comparative risk assessment (CRA) methodology was followed. Recent community studies were used to derive mean blood lead concentrations in adults and children in urban and rural areas. Population-attributable fractions were calculated and applied to revised burden of disease estimates for the relevant disease categories for South Africa in the year 2000. Monte Carlo simulation-modelling techniques were used for the uncertainty analysis. Setting South Africa. Subjects Children under 5 and adults 30 years and older. Outcome measures Cardiovascular mortality and disability-adjusted life years (DALYs) in adults 30 years and older and mild mental disability DALYs in children under 5 years. Results Lead exposure was estimated to cause 1 428 deaths (95% uncertainty interval 1 086-1 772) or 0.27% (95% uncertainty interval: 0.21 - 0.34%) of all deaths in South Africa in 2000. Burden of disease attributed to lead exposure was dominated by mild mental disability in young children, accounting for 75% of the total 58 939 (95% uncertainty interval 55 413 - 62 500) attributable DALYs. Cardiovascular disease in adults accounted for the remainder of the burden. Conclusions Even with the phasing out of leaded petrol, exposure to lead from its ongoing addition to paint, paraoccupational exposure and its use in backyard 'cottage industries' will continue to be an important public health hazard in South Africa for decades. Young children, especially those from disadvantaged communities, remain particularly vulnerable to lead exposure and poisoning.

Estimating the burden of disease attributable to low fruit and vegetable intake in South Africa in 2000

Objectives To estimate the burden of disease attributed to low fruit and vegetable intake by sex and age group in South Africa for the year 2000. Design The analysis follows the World Health Organization comparative risk assessment (CRA) methodology. Populationattributable fractions were calculated from South African prevalence data from dietary surveys and applied to the revised South African burden of disease estimates for 2000. A theoretical maximum distribution of 600 g per day for fruit and vegetable intake was chosen. Monte Carlo simulationmodelling techniques were used for uncertainty analysis. Setting South Africa. Subjects Adults ≥ 15 years. Outcome measures Mortality and disability-adjusted life years (DALYs), from ischaemic heart disease, ischaemic stroke, lung cancer, gastric cancer, colorectal cancer and oesophageal cancer. Results Low fruit and vegetable intake accounted for 3.2% of total deaths and 1.1% of the 16.2 million attributable DALYs. For both males and females the largest proportion of total years of healthy life lost attributed to low fruit and vegetable intake was for ischaemic heart disease (60.6% and 52.2%, respectively). Ischaemic stroke accounted for 17.8% of attributable DALYs for males and 32.7% for females. For the related cancers, the leading attributable DALYs for men and women were oesophageal cancer (9.8% and 7.0%, respectively) and lung cancer (7.8% and 4.7%, respectively). Conclusions A high intake of fruit and vegetables can make a significant contribution to decreasing mortality from certain diseases. The challenge lies in creating the environment that facilitates changes in dietary habits such as the increased intake of fruit and vegetables.

Microalgal growth characteristics and subsequent influence on dewatering efficiency

Dewatering of microalgal culture is a major bottleneck towards the industrial-scale processing of microalgae for bio-diesel production. The dilute nature of harvested microalgal cultures poses a huge operation cost to dewater; thereby rendering microalgae-based fuels less economically attractive. This study explores the influence of microalgal growth phases and intercellular interactions during cultivation on dewatering efficiency of microalgae cultures. Experimental results show that microalgal cultures harvested during a low growth rate phase (LGRP) of 0.03 d-1 allowed a higher rate of settling than those harvested during a high growth rate phase (HGRP) of 0.11 d-1, even though the latter displayed a higher average differential biomass concentration of 0.2 g L-1 d-1. Zeta potential profile during the cultivation process showed a maximum electronegative value of -43.2 ± 0.7 mV during the HGRP which declined to stabilization at -34.5 ± 0.4 mV in the LGRP. The lower settling rate observed for HGRP microalgae is hence attributed to the high stability of the microalgal cells which electrostatically repel each other during this growth phase. Tangential flow filtration of 20 L HGRP culture concentrated 23 times by consuming 0.51 kWh/m3 of supernatant removed whilst 0.38 kWh/m3 was consumed to concentrate 20 L of LGRP by 48 times.

Automated counting of the Northern Pacific Sea Star in the Derwent using shape recognition

A novel shape recognition algorithm was developed to autonomously classify the Northern Pacific Sea Star (Asterias amurenis) from benthic images that were collected by the Starbug AUV during 6km of transects in the Derwent estuary. Despite the effects of scattering, attenuation, soft focus and motion blur within the underwater images, an optimal joint classification rate of 77.5% and misclassification rate of 13.5% was achieved. The performance of algorithm was largely attributed to its ability to recognise locally deformed sea star shapes that were created during the segmentation of the distorted images.

A follow up sample of first time drink driving offenders : how many drink drive post offence?

Background Drink driving remains an important issue to address in terms of health and injury prevention even though research shows that over time there has been a steady decline in drink driving. This has been attributed to the introduction of countermeasures such as random breath testing (RBT), changing community attitudes and norms leading to less acceptance of the behaviour and, to a lesser degree, the implementation of programs designed to deter offenders from engaging in drink driving. Most of the research to date has focused on the hard core offenders - those with high blood alcohol content at the time of arrest, and those who have more than one offence. Aims There has been little research on differences within the first offender population or on factors contributing to second offences. This research aims to fill the gap by reporting on those factors in a sample of offenders. Methods This paper reports on a study that involved interviewing 198 first offenders in court and following up this group 6-8 months post offence. Of these original participants, 101 offenders were able to be followed up, with 88 included in this paper on the basis that they had driven a vehicle since the offence. Results Interestingly, while the rate of reported apprehended second offences was low in that time frame (3%), a surprising number of offenders reported that they had driven under the influence at a much higher rate (27%). That is a large proportion of first offenders were willing to risk the much larger penalties associated with a second offence in order to engage in drink driving. Discussion and conclusions Key characteristics of this follow up group are examined to inform the development of a evidence based brief intervention program that targets first time offenders with the goal of decreasing the rate of repeat drink driving.

ACE research vignette 039: The Ineffectiveness of Enterprise Policy : Is Policy Formulation to Blame?

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepreneurship researchers. This vignette, written by Dr Norin Arshed, Professor Sara Carter and Professor Colin Mason examines whether the ineffectiveness of enterprise policy can be attributed to the formulation of the enterprise policy itself.

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

From certificate chasing to genuine engagement : the contribution of curriculum design to students' career intent in a subfield

Many students enter business degrees without a defined career goal beyond working in the business world and adopt a scattergun approach to employability by accumulating certifications accessed through individual subjects. Yet, space and time limitations commonly prevent extended exposure to rewarding and interesting career subfields within main specialisations. This case study draws on student feedback collected over three years exploring students’ career interest following an elective human resource development subject in the final stage of a human resources major. Project-based curriculum provided students with scaffolded learning while undertaking key multiphase human resource development tasks. Subsequently, students reported human resource development career interest and intent, attributed to more realistic appreciation of human resource development’s activities, scope, and values. The paper makes an important contribution illustrating how curriculum design can transform instrumentalism into logically, emotionally, and intuitively based career engagement. Further, human resource development is a study and career area little mentioned in higher education or careers literature.

Learning the learning rate for prediction with expert advice

Most standard algorithms for prediction with expert advice depend on a parameter called the learning rate. This learning rate needs to be large enough to fit the data well, but small enough to prevent overfitting. For the exponential weights algorithm, a sequence of prior work has established theoretical guarantees for higher and higher data-dependent tunings of the learning rate, which allow for increasingly aggressive learning. But in practice such theoretical tunings often still perform worse (as measured by their regret) than ad hoc tuning with an even higher learning rate. To close the gap between theory and practice we introduce an approach to learn the learning rate. Up to a factor that is at most (poly)logarithmic in the number of experts and the inverse of the learning rate, our method performs as well as if we would know the empirically best learning rate from a large range that includes both conservative small values and values that are much higher than those for which formal guarantees were previously available. Our method employs a grid of learning rates, yet runs in linear time regardless of the size of the grid.