Predicting spatio-temporal distribution for eastern Australian birds using birds Australia's atlas data : survey method, habitat and seasonal effects

Faunal atlases are landscape-level survey collections that can be used for describing spatial and temporal patterns of distribution and densities. They can also serve as a basis for quantitative analysis of factors that may influence the distributions of species. We used a subset of Birds Australia’s Atlas of Australian Birds data (January 1998 to December 2002) to examine the spatio-temporal distribution patterns of 280 selected species in eastern Australia (17–37°S and 136–152°E). Using geographical information systems, this dataset was converted into point coverage and overlaid with a vegetation polygon layer and a half-degree grid. The exploratory data analysis involved calculating species-specific reporting rates spatially, per grid and per vegetation unit, and also temporally, by month and year. We found high spatio-temporal variability in the sampling effort. Using generalised linear models on unaggregated point data, the influences of four factors – survey method and month, geographical location and habitat type – were analysed for each species. When counts of point data were attributed to grid-cells, the total number of species correlated with the total number of surveys, while the number of records per species was highly variable. Surveys had high interannual location fidelity. The predictive values of each of the four factors were species-dependent. Location and habitat were correlated and highly predictive for species with restricted distribution and strong habitat preference. Month was only of importance for migratory species. The proportion of incidental sightings was important for extremely common or extremely rare species. In conclusion, behaviour of species differed sufficiently to require building a customized model for each species to predict distribution. Simple models were effective for habitat specialists with restricted ranges, but for generalists with wide distributions even complex models gave poor predictions.

Is phase-specific, community-oriented treatment of early psychosis- an economically viable method of improving outcome?

Objective: The Early Psychosis Prevention and Intervention Centre (EPPIC) provides a comprehensive 'real-world' model of early intervention to young people experiencing an emerging psychotic disorder. A prospective study has already provided evidence of improved clinical outcome at 12 months after entry. The present study examined whether the service was also cost-effective.

Method: A cost-effectiveness analysis compared EPPIC with its immediate precursor service, from the perspective of the government funding agency. Only direct costs were included.

Results: EPPIC proved to be more cost-effective. The weighted average cost per patient for the first 12 months was cheaper (by äD 7110 per patient), while treatment outcomes were superior. The savings were due to the marked reduction in in-patient costs outweighing substantial increases in the costs of community care.

Conclusion: These results, while encouraging in terms of the further development of integrated, phase-specific intervention programmes for early psychosis, are not conclusive, and further research is required.

A hazardous substance exposure prevention rating method for intervention needs assessment and effectiveness evaluation: the small business exposure index

Aims This paper describes the refinement and adaptation to small business of a previously developed method for systematically prioritizing needs for intervention on hazardous substance exposures in manufacturing worksites, and evaluating intervention effectiveness. Methods We developed a checklist containing six unique sets of yes/no variables organized in a 2 × 3 matrix of exposure potential versus exposure protection at three levels corresponding to a simplified hierarchy of controls: materials, processes, and human interface. Each of the six sets of indicator variables was reduced to a high/moderate/low rating. Ratings from the matrix were then combined to generate an exposure prevention 'Small Business Exposure Index' (SBEI) Summary score for each area. Reflecting the hierarchy of controls, material factors were weighted highest, followed by process, and then human interface. The checklist administered by an industrial hygienist during walk-through inspection (N = 149 manufacturing processes/areas in 25 small to medium-sized manufacturing worksites). One area or process per manufacturing department was assessed and rated. A second hygienist independently assessed 36 areas to evaluate inter-rater reliability. Results The SBEI Summary scores indicated that exposures were well controlled in the majority of areas assessed (58% with rating of 1 or 2 on a 6-point scale), that there was some room for improvement in roughly one-third of areas (31% of areas rated 3 or 4), and that roughly 10% of the areas assessed were urgently in need of intervention (rated as 5 or 6). Inter-rater reliability of EP ratings was good to excellent (e.g., for SBEI Summary scores, weighted kappa = 0.73, 95% CI 0.52–0.93). Conclusion The SBEI exposure prevention rating method is suitable for use in small/medium enterprises, has good discriminatory power and reliability, offers an inexpensive method for intervention needs assessment and effectiveness evaluation, and complements quantitative exposure assessment with an upstream prevention focus.

An exposure prevention rating method for intervention needs assessment and effectiveness evaluation

This article describes a new method for (1) systematically prioritizing needs for intervention on hazardous substance exposures in manufacturing work sites, and (2) evaluating intervention effectiveness. We developed a checklist containing six unique sets of yes/no variables organized in a 2 × 3 matrix of exposure potential versus protection (two columns) at the levels of materials, processes, and human interface (three rows). The three levels correspond to a simplified hierarchy of controls. Each of the six sets of indicator variables was reduced to a high/moderate/low rating. Ratings from the matrix were then combined to generate a single overall exposure prevention rating for each area. Reflecting the hierarchy of controls, material factors were weighted highest, followed by process, and then human interface. The checklist was filled out by an industrial hygienist while conducting a walk-through inspection (N = 131 manufacturing processes/areas in 17 large work sites). One area or process per manufacturing department was assessed and rated. Based on the resulting Exposure Prevention ratings, we concluded that exposures were well controlled in the majority of areas assessed (64% with rating of 1 or 2 on a 6-point scale), that there is some room for improvement in 26 percent of areas (rating of 3 or 4), and that roughly 10 percent of the areas assessed are urgently in need of intervention (rated as 5 or 6). A second hygienist independently assessed a subset of areas to evaluate inter-rater reliability. The reliability of the overall exposure prevention ratings was excellent (weighted kappa = 0.84). The rating scheme has good discriminatory power and reliability and shows promise as a broadly applicable and inexpensive tool for intervention needs assessment and effectiveness evaluation. Validation studies are needed as a next step. This assessment method complements quantitative exposure assessment with an upstream prevention focus.