Statistical Local Area Level Research Articles

Spatial and temporal analysis of dengue infections in Queensland, Australia: Recent trend and perspectives.

Dengue is a public health concern in northern Queensland, Australia. This study aimed to explore spatial and temporal characteristics of dengue cases in Queensland, and to identify high-risk areas after a 2009 dengue outbreak at fine spatial scale and thereby help in planning resource allocation for dengue control measures. Notifications of dengue cases for Queensland at Statistical Local Area (SLA) level were obtained from Queensland Health for the period 2010 to 2015. Spatial and temporal analysis was performed, including plotting of seasonal distribution and decomposition of cases, using regression models and creating choropleth maps of cumulative incidence. Both the space-time scan statistic (SaTScan) and Geographical Information System (GIS) were used to identify and visualise the space-time clusters of dengue cases at SLA level. A total of 1,773 dengue cases with 632 (35.65%) autochthonous cases and 1,141 (64.35%) overseas acquired cases were satisfied for the analysis in Queensland during the study period. Both autochthonous and overseas acquired cases occurred more frequently in autumn and showed a geographically expanding trend over the study period. The most likely cluster of autochthonous cases (Relative Risk, RR = 54.52, p<0.001) contained 50 SLAs in the north-east region of the state around Cairns occurred during 2013–2015. A cluster of overseas cases (RR of 60.81, p<0.001) occurred in a suburb of Brisbane during 2012 to 2013. These results show a clear spatiotemporal trend of recent dengue cases in Queensland, providing evidence in directing future investigations on risk factors of this disease and effective interventions in the high-risk areas.

Supply and demand in physician markets: a panel data analysis of GP services in Australia.

To understand the trends in any physician services market it is necessary to understand the nature of both supply and demand, but few studies have jointly examined supply and demand in these markets. This study uses aggregate panel data on general practitioner (GP) services at the Statistical Local Area level in Australia spanning eight years to estimate supply and demand equations for GP services. The structural equations of the model are estimated separately using population-weighted fixed effects panel modelling with the two stage least squares formulation of the generalised method of moments approach (GMM (2SLS)). The estimated price elasticity of demand of -0.19 is comparable with other studies. The direct impact of GP density on demand, while significant, proves almost immaterial in the context of near vertical supply curves. Supply changes are therefore due to shifts in the position of the curves, partly determined by a time trend. The model is validated by comparing post-panel model predictions with actual market outcomes over a period of three years and is found to provide surprisingly accurate projections over a period of significant policy change. The study confirms the need to jointly consider supply and demand in exploring the behaviour of physician services markets.

Epidemiologic patterns of Ross River virus disease in Queensland, Australia, 2001-2011.

Ross River virus (RRV) infection is a debilitating disease that has a significant impact on population health, economic productivity, and tourism in Australia. This study examined epidemiologic patterns of RRV disease in Queensland, Australia, during January 2001–December 2011 at a statistical local area level. Spatio-temporal analyses were used to identify the patterns of the disease distribution over time stratified by age, sex, and space. The results show that the mean annual incidence was 54 per 100,000 persons, with a male:female ratio of 1:1.1. Two space-time clusters were identified: the areas adjacent to Townsville, on the eastern coast of Queensland, and the southeast areas. Thus, although public health intervention should be considered across all areas in which RRV occurs, it should specifically focus on high-risk regions, particularly during summer and autumn to reduce the social and economic impacts of RRV infection.

A new source for high spatial resolution night time images — The EROS-B commercial satellite

City lights present one of humankind's most unique footprints on Earth as seen from space. Resulting light pollution from artificial lights obscures the night sky for astronomy and has negative impacts on biodiversity as well as on human health. However, remote sensing studies of night lights to date have been mostly limited to coarse spatial resolution sensors such as the DMSP-OLS. Here we present a new source for high spatial resolution mapping of night lights from space, derived from a commercial satellite. We tasked the Israeli EROS-B satellite to acquire two night-time light images (at a spatial resolution of 1m) of Brisbane, Australia, and analyzed their radiometric quality and content with respect to land cover and land use. The spatial distribution of night lights as imaged by EROS-B corresponded with night-time images acquired by an airborne camera, although EROS-B was not as sensitive to low light levels. Using land cover and land use data at the statistical local area level, we could statistically explain 89% of the variability in night-time lights. Arterial roads and commercial and service areas were found to be some of the brightest land use types. Overall, we found that EROS-B imagery provides fine spatial resolution images of night lights, opening new avenues for studying light pollution in cities worldwide.

Does relative remoteness affect chronic disease outcomes? Geographic variation in chronic disease mortality in Australia, 2002–2006.

To examine the variation of chronic disease mortality by remoteness areas of Australia, including states and territories. Australian Bureau of Statistics (ABS) death registration data, by Statistical Local Area (SLA), were used to identify chronic disease mortality by remoteness category for states and territories and Australia. The analysis used multiple cause of death for six common chronic diseases: diabetes, ischaemic heart disease, stroke, hypertension, chronic obstructive pulmonary disease and renal disease. ABS correspondence files were used to adjust the SLA level death records and population. The chronic disease mortality rate for Australian residents living in a very remote area (512 per 100,000 persons) was respectively 1.3, 1.4, 1.5, and 1.6 times higher than Remote, Outer Regional, Inner Regional and Major Cities categories. This pattern was consistent for the two age groups of 35–64 years and 65 years and over, all six chronic diseases and all states and territories except Victoria. This study shows that chronic disease mortality increases with increasing relative remoteness. The results highlight the importance and opportunity to redress poorer health outcomes for rural and remote area populations. The study is limited by absence of reliable Indigenous identification in national death data.

Patterns and trends in Australian agriculture: a consistent set of agricultural statistics at small areas for analysing regional changes

ABARES has produced a consistent set of agricultural statistics at scales smaller than Australian States for the period 1982–83 to 2008–09. Every year is available at Statistical Division level, but only the census years of 1986, 1991, 1996, 2001 and 2006 are available at Statistical Local Area level. Although based on statistics collected by the Australian Bureau of Statistics, they are less accurate because of compromises in concording the data to the Australian Standard Geographical Classification spatial boundaries for 1996, 2001 and 2006 and to a common set of agricultural items. However, they provide comprehensive agricultural data for recent time series at scales smaller than states. From this data set, we give some examples of patterns and trends, which indicate considerable regional variation in Australia over time between major industries.

Spatial clusters of suicide in Australia

BackgroundUnderstanding the spatial distribution of suicide can inform the planning, implementation and evaluation of suicide prevention activity. This study explored spatial clusters of suicide in Australia, and investigated likely socio-demographic determinants of these clusters.MethodsNational suicide and population data at a statistical local area (SLA) level were obtained from the Australian Bureau of Statistics for the period of 1999 to 2003. Standardised mortality ratios (SMR) were calculated at the SLA level, and Geographic Information System (GIS) techniques were applied to investigate the geographical distribution of suicides and detect clusters of high risk in Australia.ResultsMale suicide incidence was relatively high in the northeast of Australia, and parts of the east coast, central and southeast inland, compared with the national average. Among the total male population and males aged 15 to 34, Mornington Shire had the whole or a part of primary high risk cluster for suicide, followed by the Bathurst-Melville area, one of the secondary clusters in the north coastal area of the Northern Territory. Other secondary clusters changed with the selection of cluster radius and age group. For males aged 35 to 54 years, only one cluster in the east of the country was identified. There was only one significant female suicide cluster near Melbourne while other SLAs had very few female suicide cases and were not identified as clusters. Male suicide clusters had a higher proportion of Indigenous population and lower median socio-economic index for area (SEIFA) than the national average, but their shapes changed with selection of maximum cluster radii setting.ConclusionThis study found high suicide risk clusters at the SLA level in Australia, which appeared to be associated with lower median socio-economic status and higher proportion of Indigenous population. Future suicide prevention programs should focus on these high risk areas.

Reappraising the Role of Suburban Workplaces in Darwin’s Creative Economy

Traditionally, suburbs have been conceived as dormitory – in binary opposition to the inner-city (Powell). Supporting this stereotypical view have been gendered binaries between inner and outer city areas; densely populated vs. sprawl; gentrified terraces and apartment culture vs. new estates and first home buyers; zones of (male) production and creativity against (female) sedate, consumer territory. These binaries have for over a decade been thoroughly criticised by urban researchers, who have traced such representations and demonstrated how they are discriminatory and incorrect (see Powell; Mee; Dowling and Mee). And yet, such binaries persist in popular media commentaries and even in academic research (Gibson and Brennan-Horley). In creative city research, inner-city areas have been bestowed with the supposed correct mix of conditions that may lead to successful creative ventures. In part, this discursive positioning has been borne out of prior attempts to mapthe location of creativity in the city

Use of measures of socioeconomic deprivation in planning primary health care workforce and defining health care need in Australia

To examine whether measures of remoteness areas adequately reveal high need populations, measured against socioeconomic disadvantage and physician to population ratios. Exploratory spatial analysis of relationships between remoteness areas, medical workforce supply and the index of relative socioeconomic disadvantage (IRSD). Bivariate analyses examined associations between remoteness areas and IRSD. From this analysis, a composite score of deprivation was constructed combining measures of remoteness areas, physician to population ratios and IRSD, and validated against health outcome measures. These measures included avoidable mortality per 100,000, risk behaviour rate per 1000, diabetes rate per 1000. All analyses were conducted at the statistical local area level and weighted to be population representative. The percentage of small areas and populations within the most socioeconomically disadvantaged quintile rose with increasing remoteness. However, 12.8% of small areas within major cities and 40.7% of outer regional areas were also within the lowest socioeconomic quintile. There was a strong relationship between our composite score of deprivation and avoidable mortality, risk rate, diabetes rate and per cent Indigenous. Regression analysis examined the relationship between each element of the composite score and health outcomes. This revealed that the association between avoidable mortality and remoteness was lost after controlling for per cent Indigenous. Using remoteness areas alone to prioritize workforce incentive programs and training requirements has significant limitations. Including measures of socioeconomic disadvantage and workforce supply would better target health inequities and improve resource allocation in Australia.

Spatial analysis of heat-related mortality among the elderly between 1993 and 2004 in Sydney, Australia

This study analyzed the geographical patterns of heat-related mortality among the population aged 65 and over within the metropolitan area of Sydney, Australia between 1993 and 2004, and evaluated the role of some physical and socio-demographic risk factors associated with it. The effect of temperature on all-cause mortality during unusually hot days was investigated using spatial analytic techniques, such as cluster analysis and spatial regression analysis. Generalized Linear Models (GLMs) were used to investigate the role of daily average temperature, ozone (O(3)) and particulate matter of diameter less than 10 microm (PM(10)) at the regions that showed a significant increase in mortality on unusually hot days. Spatial variation in mortality on unusually hot days was observed among the population 65 and over. Elderly people living within 5-20 km south-west and west of the Sydney Central Business District (CBD) were found to be more vulnerable. However, analysis using GLMs showed temperature to be a significant modifier of daily mortality in the region to the south-west of the CBD only. O(3) and PM(10) were found to be non-significant factors in the regions where air pollutants were studied. Socio-economic status and the proportion of vegetation or developed land in each Statistical Local Area (SLA) were also not a significant factor explaining the increased mortality. A combination of social and environmental factors may be at play. Our results suggest an effect of temperature on mortality of the elderly population in Sydney Statistical Division at the SLA level. More spatially-based research would be beneficial once climate datasets with improved spatial coverage become available.

Long-term exposure to gaseous air pollutants and cardio-respiratory mortality in Brisbane, Australia

This study examines the association of long-term exposure to gaseous air pollution with cardio-respiratory mortality in Brisbane, Australia, in the period 1996-2004. The pollutant concentrations were estimated using geographical information system (GIS) techniques at the statistical local area (SLA) level. The generalized estimating equations model was used to investigate the impact of nitrogen dioxide (NO2), ozone (O3) and sulphur dioxide (SO2) on mortality due to cardio-respiratory disease after adjusting for a range of potential confounders. An increase of 4.7% (95% confidence interval = 0.7-8.9%) in cardio-respiratory mortality for 1 part per billion (ppb) increment in annual average concentration of SO2 was estimated. However, there was no significant association between long-term exposures to NO2 or O3 and death due to cardio-respiratory disease. The results indicate that the annual average concentration of SO2 is associated with cardio-respiratory mortality at the SLA level and this association appears to vary with the geographical area.

Predicting The Need For Aged Care Services At The Small Area Level: The CAREMOD Spatial Microsimulation Model

Most industrialised societies face rapid population ageing over the next two decades, including sharp increases in the number of people aged 85 years and over. As a result, the supply of and demand for aged care services has assumed increasing policy prominence. The likely spatial distribution of the need for aged care services is critical for planners and policy makers. This article describes the development of a regional microsimulation model of the need for aged care in New South Wales, a state of Australia. It details the methods involved in reweighting the 1998 Survey of Disability, Ageing and Carers, a national level dataset, against the 2001 Census to produce synthetic small area estimates at the statistical local area level. Validation shows that survey variables not constrained in the weighting process can provide unreliable local estimates. A proposed solution to this problem is outlined, involving record cloning, value imputation and alignment. Indicative disability estimates arising from this process are then discussed.