A landscape-scale test of the predictive ability of a spatially explicit model for population viability analysis

1. Although population viability analysis (PVA) is widely employed, forecasts from PVA models are rarely tested. This study in a fragmented forest in southern Australia contrasted field data on patch occupancy and abundance for the arboreal marsupial greater glider Petauroides volans with predictions from a generic spatially explicit PVA model. This work represents one of the first landscape-scale tests of its type. 2. Initially we contrasted field data from a set of eucalypt forest patches totalling 437 ha with a naive null model in which forecasts of patch occupancy were made, assuming no fragmentation effects and based simply on remnant area and measured densities derived from nearby unfragmented forest. The naive null model predicted an average total of approximately 170 greater gliders, considerably greater than the true count (n = 81). 3. Congruence was examined between field data and predictions from PVA under several metapopulation modelling scenarios. The metapopulation models performed better than the naive null model. Logistic regression showed highly significant positive relationships between predicted and actual patch occupancy for the four scenarios (P = 0.001-0.006). When the model-derived probability of patch occupancy was high (0.50-0.75, 0.75-1.00), there was greater congruence between actual patch occupancy and the predicted probability of occupancy. 4. For many patches, probability distribution functions indicated that model predictions for animal abundance in a given patch were not outside those expected by chance. However, for some patches the model either substantially over-predicted or under-predicted actual abundance. Some important processes, such as inter-patch dispersal, that influence the distribution and abundance of the greater glider may not have been adequately modelled. 5. Additional landscape-scale tests of PVA models, on a wider range of species, are required to assess further predictions made using these tools. This will help determine those taxa for which predictions are and are not accurate and give insights for improving models for applied conservation management.

Does health service utilisation vary by remoteness? South Australian population data and the Accessibility and Remoteness Index of Australia

Objective: To compare rates of self-reported use of health services between rural, remote and urban South Australians. Methods: Secondary data analysis from a population-based survey to assess health and well-being, conducted in South Australia in 2000. In all, 2,454 adults were randomly selected and interviewed using the computer-assisted telephone interview (CATI) system. We analysed health service use by Accessibility and Remoteness Index of Australia (ARIA) category. Results: There was no statistically significant difference in the median number of uses of the four types of health services studied across ARIA categories. Significantly fewer residents of highly accessible areas reported never using primary care services (14.4% vs. 22.2% in very remote areas), and significantly more reported high use ( greater than or equal to6 visits, 29.3% vs. 21.5%). Fewer residents of remote areas reported never attending hospital (65.6% vs. 73.8% in highly accessible areas). Frequency of use of mental health services was not statistically significantly different across ARIA categories. Very remote residents were more likely to spend at least one night in a public hospital (15.8%) than were residents of other areas (e.g. 5.9% for highly accessible areas). Conclusion: The self-reported frequency of use of a range of health services in South Australia was broadly similar across ARIA categories. However, use of primary care services was higher among residents of highly accessible areas and public hospital use increased with increasing remoteness. There is no evidence for systematic rural disadvantage in terms of self-reported health service utilisation in this State.

Acute care surgeon South American model

Background In the World Health Organization book by Murray and Lopez (The Global Burden of Disease), the authors make the point that there are major regional differences across the world for death from injury. In the European market economies, injuries accounted for 6% of all deaths, of which the majority were the result of road traffic accidents. In stark contrast, in Latin America and the Caribbean, injuries account for 12-13% of all deaths, and most of these are the result of violence. An estimated 30% of all male deaths are from external causes, and road traffic accidents are the number two cause of death. Within South American countries, trauma is the second most common cause of death in Columbia, Venezuela, Ecuador, and Brazil. In other South American countries, it is the third or fourth most common cause of death. If one examines the Disability Adjusted Life Years, South America is the third highest in the world. Death from injury primarily affects people in the middle- and low-income group. Traffic accidents and suicide are the main causes of trauma in the high-income population. South America is made up of developing and poor countries that have trauma as a very important cause of death and disability. Methods The author has reviewed information on injury from the World Health Organization, Pan American Health Organization, and Brazilian Health Ministry. In addition, a search of injury was performed through MEDLINE. Results and Conclusions The results of this review show that trauma is a major public health problem in South America. At the present time, there is a lack of statewide system development. In addition, there are difficulties in training surgeons to cope with these problems.

Derivation and external validation of a simple prediction model for the diagnosis of type 2 Diabetes Mellitus in the Brazilian urban population

A risk score model was developed based in a population of 1,224 individuals from the general population without known diabetes aging 35 years or more from an urban Brazilian population sample in order to select individuals who should be screened in subsequent testing and improve the efficacy of public health assurance. External validation was performed in a second, independent, population from a different city ascertained through a similar epidemiological protocol. The risk score was developed by multiple logistic regression and model performance and cutoff values were derived from a receiver operating characteristic curve. Model`s capacity of predicting fasting blood glucose levels was tested analyzing data from a 5-year follow-up protocol conducted in the general population. Items independently and significantly associated with diabetes were age, BMI and known hypertension. Sensitivity, specificity and proportion of further testing necessary for the best cutoff value were 75.9, 66.9 and 37.2%, respectively. External validation confirmed the model`s adequacy (AUC equal to 0.72). Finally, model score was also capable of predicting fasting blood glucose progression in non-diabetic individuals in a 5-year follow-up period. In conclusion, this simple diabetes risk score was able to identify individuals with an increased likelihood of having diabetes and it can be used to stratify subpopulations in which performing of subsequent tests is necessary and probably cost-effective.

Short-Term Effects of Hydroxyethylstarch Resuscitation on Systemic and Regional Hemodynamics and Metabolism in a Brain-Dead Canine Model

Background. Hydroxyethylstarch (HES) is a synthetic polymer of glucose that has been suggested for therapeutic use in long-term plasma expansion. The aim of this study was to test the hypothesis that the infusion of a small volume of HES may provide benefits in systemic and regional hemodynamics and metabolism in a brain-dead canine model compared with large volume crystalloid resuscitation. Methods. Fourteen mongrel dogs were subjected to a brain-death protocol by consecutive insufflations of a balloon catheter in the epidural space. One hour after induction of brain-death, the animals were randomly assigned to two groups: NS (0.9% NaCl, 33mL/kg), and HES (6% HES 450/0.7, 17mL/Kg). Systemic and regional hemodynamics were evaluated using Swan-Ganz, ultrasonic flowprobes, and arterial catheters. Serial blood samples were collected for blood gas, electrolyte, and serum chemistry analysis. Systemic, hepatic, and splanchnic O(2)-derived variables were also calculated. Results. Epidural balloon insufflations induced a significant increase in mean arterial pressure, cardiac output (MAP and CO, respectively), regional blood flow, and systemic vascular resistance. Following the hyperdynamic phase, severe hypotension with normalization of systemic and regional blood flow was observed. Fluid resuscitation induced a prompt increase in MAP, CO, and portal vein blood flow, and a significant reduction in systemic and pulmonary vascular resistance. There were no differences between groups in metabolic indices, liver function tests (LFTs), or renal function tests. HES was more effective than NS in restoring cardiac performance in the first 2h after fluid resuscitation (P < 0.05). Both tested solutions partially and temporarily restored systemic and regional oxygen delivery. Conclusion. Small volumes of 6% HES 450/0.7 improved cardiovascular performance and provided the same regional hemodynamic and metabolic benefits of large volumes of isotonic crystalloid solutions. (C) 2011 Elsevier Inc. All rights reserved.

An adaptive neural-wavelet model for short term load forecasting

This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.

Dispersal patterns in a regional koala population in south-east Queensland

Koala dispersal was investigated as part of a detailed ecological study of a nationally significant koala population located 20 km south-east of Brisbane, Queensland. From 1996 to 2000, 195 koalas from three sites were captured and fitted with radio-collars. A total of 40 koalas ( 23 males and 17 females) dispersed from these sites. Most (93%) dispersing individuals were 20 - 36 months of age. Three adult females ( more than 36 months old) dispersed and no adult males dispersed during the study. A significantly higher proportion of young males dispersed than females. Dispersal occurred between June and December, with most dispersal of males commencing in July and August and that of females commencing between September and November prior to, and early in, the annual breeding season. The mean straight-line distance between the natal and breeding home ranges for males and females was similar and was measured at 3.5 km ( range 1.1 - 9.7 km) and 3.4 km ( range 0.3 - 10.6 km) respectively. Dispersing males and females tended to successfully disperse south and west of their natal home ranges and were generally unable to successfully disperse to urban areas within the study area, as a high proportion of the mortality of dispersing koalas was associated with attacks by domestic dogs and with collisions with vehicles on roads. Information from other studies indicates that most young koalas disperse from their natal areas. It is likely that the social behaviour and mating systems of koala populations provide mechanisms for young koalas to disperse. The potential role of dispersal in the dynamics of regional koala populations is discussed.

SPAnDX: a process-based population dynamics model to explore management and climate change impacts on an invasive alien plant, Acacia nilotica

This paper describes a process-based metapopulation dynamics and phenology model of prickly acacia, Acacia nilotica, an invasive alien species in Australia. The model, SPAnDX, describes the interactions between riparian and upland sub-populations of A. nilotica within livestock paddocks, including the effects of extrinsic factors such as temperature, soil moisture availability and atmospheric concentrations of carbon dioxide. The model includes the effects of management events such as changing the livestock species or stocking rate, applying fire, and herbicide application. The predicted population behaviour of A. nilotica was sensitive to climate. Using 35 years daily weather datasets for five representative sites spanning the range of conditions that A. nilotica is found in Australia, the model predicted biomass levels that closely accord with expected values at each site. SPAnDX can be used as a decision-support tool in integrated weed management, and to explore the sensitivity of cultural management practices to climate change throughout the range of A. nilotica. The cohort-based DYMEX modelling package used to build and run SPAnDX provided several advantages over more traditional population modelling approaches (e.g. an appropriate specific formalism (discrete time, cohort-based, process-oriented), user-friendly graphical environment, extensible library of reusable components, and useful and flexible input/output support framework). (C) 2003 Published by Elsevier Science B.V.

Survival Analysis Employed in Predicting Corporate Failure: A Forecasting Model Proposal

In face of the current economic and financial environment, predicting corporate bankruptcy is arguably a phenomenon of increasing interest to investors, creditors, borrowing firms, and governments alike. Within the strand of literature focused on bankruptcy forecasting we can find diverse types of research employing a wide variety of techniques, but only a few researchers have used survival analysis for the examination of this issue. We propose a model for the prediction of corporate bankruptcy based on survival analysis, a technique which stands on its own merits. In this research, the hazard rate is the probability of ‘‘bankruptcy’’ as of time t, conditional upon having survived until time t. Many hazard models are applied in a context where the running of time naturally affects the hazard rate. The model employed in this paper uses the time of survival or the hazard risk as dependent variable, considering the unsuccessful companies as censured observations.

Outpatient health service utilization and associated factors: a population-based study

OBJECTIVE: To identify factors that lead people to visit a doctor in Brazil and assess differences between socioeconomic groups. METHODS: A cross-sectional study comprising 1,260 subjects aged 15 or more was carried out in southern Brazil. Demographic, socioeconomic, health needs and regular source of care data were analyzed concerning visits to a doctor within two months from the interview. Adjusted prevalence ratios and 95% confidence intervals were calculated using Poisson regression. RESULTS: Adjusted PR showed that women having stressful life events, health insurance, and a regular doctor increased the outcome. A dose-related response was found with self-reported health, and the probability of visiting a doctor increased with health needs. Analysis in the chronic disease group revealed that uneducated lower income subjects had a 62% reduction in the chance of visiting a doctor compared to uneducated higher income ones. However, as it was seen a significant interaction between income and education, years of schooling increased utilization in this group. CONCLUSIONS: Results suggest the existence of health inequity in the poorest group that could be overcome with education. Specific measures reinforcing the importance of having a regular doctor may also improve access in the underserved group.

Data analysis model selection for estimating local population size of the Risso’s dolphin (Grampus griseus) in the Azores

27th Annual Conference of the European Cetacean Society. Setúbal, Portugal, 8-10 April 2013.