Topic-specific atlases relating to a range of topics are presented below.
Further information on topic-specific atlases including the associated data workbooks, maps and graphs can be viewed and accessed by selecting the links within each of the following topics.
PHIDU content is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Australia licence (CC BY-NC-SA 3.0 AU) and these data can only be used for non-commercial purposes. PHIDU must be attributed according to the attribution policy under the CC BY-NC-SA 3.0 AU license. For further copyright information, refer to the licensing and attribution of PHIDU content section of the website.
For a full list of revised indicators refer to the latest releases.
COVID-19 and related topics
The Australian Government Department of Health and Aged Care releases vaccination rates each two weeks. PHIDU publishes these data in atlases (including a selection of demographic and socioeconomic status indicators from the Social Health Atlas of Australia), graphs (showing variatons by socioeconomic status) and datasheets; these are updated from time to time.
The atlases are presented for the following:
COVID-19 cases by selected demographic and socioeconomic status indicators
This atlas at the link above use publicly-available data of Total case and Active case counts of COVID-19 as at late January 2022 to-date February 2023 to show patterns of distribution by Local Government Area (LGA) across those States with sufficient cases to map. A commentary is also provided on the correlation between the data for cases and selected demographic and socioecomonic status indicator.
COVID-19 vaccinations by LGA show the successes, hide the challenges to come
Dr Kerry Chant, Chief Health Officer, NSW Health said there needs to be a "strong equity focus" in order to achieve the 90 per cent target . The extent of the challenge to achieve a high vaccination rate across all population groups is highlighted by the variations between LGAs across Greater Sydney and Regional New South Wales. However, of greater concern are the marked variations within many LGAs, pointing to the need to have a strong population health focus if equity in vaccination and returning to a more open way of life is to be achieved.
COVID-19 impact on unemployment benefits (October 2020): supplemented with Emergency Department (ED) presentations for mental health-related conditions (February 2021)
One of the greatest impacts of the coronavirus (COVID-19) in Australia has been on jobs – in fact, the loss of jobs, as businesses have scaled down or closed. A major indicator of the impact of loss of jobs is the increase in the number of people receiving an unemployment benefit. In June 2019 there were just over three quarters of a million people receiving an unemployment benefit; by June 2020 this figure had more than doubled, to over one and a half million (the numbers are 769,555 and 1,614,412, respectively).
The associations at the suburb level between unemployment payments and socioeconomic disadvantage in capital cities are very strong, as shown in the chart below. However, correlations between ED presentations for mental health-related conditions and socioeconomic disadvantage are weaker, ranging from moderate to strong, indicating the more widespread nature of these conditions in the population. There are similar associations for other age groups.
In this report we provide maps, graphs and data that show the major changes in unemployment payments in the capital cities and regional areas, based on data from the Department of Social Services, and presentations to emergency departments by people with mental health-related consitions. Using the double map you can view the correlations, as described above, for different geographical areas.
Socioeconomic disadvantage, as measured by the Index of Relative Socio-economic Disadvantage (click here for further information).
Population group atlases
Child and Youth Social Health Atlas of Australia
Being healthy in childhood and as young people provides an important foundation for later life. This Child and Youth Social Health Atlas of Australia draws together data from other Social Health Atlases and unpublished data for those aged from 0 to 24 years. As such, it seeks to set the data on health status, use of health services and health outcomes alongside the demographic, social and economic characteristics of this population group in the communities where they live across Australia.
Social Health Atlas of Older people in Australia
The Social Health Atlas of Older People in Australia (version 2), presents data on a range of population characteristics, including demography, socioeconomic status, health status and risk factors, and use of health and welfare services. This is available by Population Health Areas (PHA), Local Government Areas (LGA), Primary Health Networks (PHN), Aged Care Planning Regions (ACPR), Remoteness Area and Quintiles of Socioeconomic Disadvantage of Area.
Adequate and affordable housing is an important determinant of health. This report explores the housing circumstances of different population groups, drawing on small area geographic data from the 2016 Census of Population and Housing, health surveys, income support payment datasets, and administrative health datasets (e.g., perinatal statistics, potentially preventable hospitalisations, mortality) to examine area-level associations between the housing circumstances of different population groups and between housing circumstances and health outcomes.
Aboriginal and Torres Strait Islander population
Indigenous Status Comparison: Social Health Atlas of Australia
The Indigenous Status Comparison: Social Health Atlas of Australia, presents selected topics and compares indicators between Indigenous and non-Indigenous populations in Australia. This is available by Indigenous Areas, including total for the Greater Capital City Statistical Areas/Rest of States/NT; and States/Territories.
Closing the Gap Time Series Atlas
Closing the Gap seeks to improve the lives of all Aboriginal and Torres Strait Islander Australians. This Time Series Atlas focuses on the Closing the Gap targets (targets as at February 2018) for the Aboriginal population, with comparisons with the non-Indigenous population, at the Indigenous Area (IARE) level.
Note: the rates for premature mortality have been revised using improved population data. The new rates were released in July 2021.
Regional Centres Atlas
The Centre for Aboriginal Economic Research Policy has developed the concept of Regional Centres, as an ‘important but often overlooked set of areas with particular policy and population dynamics.’ These 46 areas have a total population of between 10,000 and 250,000 with at least 1,000 Aboriginal and Torres Strait Islander usual residents.
Regional centres tend to have a relatively young Indigenous population when compared to the non-Indigenous population in those centres and to the Indigenous population in the rest of Australia. In addition, Regional Centres contain significantly more Indigenous Australians overall than remote Indigenous communities and make up a greater share of the population than in Australia’s major cities. In spite of this, policy interest is very rarely devoted to individual regional centres or to regional centres as a separate geographic grouping.
Using data previously published in the Aboriginal and Torres Strait Islander Social Health Atlas, this atlas expands on the demographic, mobility and socioeconomic measures used in CAEPR's paper to further include indicators under the following themes, ‘Demographic and social indicators’, Health status, disease prevention, disability and deaths, and ‘ Use and provision of health and welfare services’.
Hot spot analysis: showing persistent inequality over time
Emergency Department Presentations: identifying hotspots of inequality
Public hospital emergency departments are a key element of the Australian health system, providing care to people who need it urgently. Mapping of emergency department presentations over time in areas where patients live enables us to geographically examine the degree and persistence of the demand for, and, supply of, this essential health service across Australia. This new evidence can inform policy makers to help strengthen current health care models or help deliver alternative care options, providing pathways and solutions that are tailored and targeted to meet the needs and preferences of the underlying populations.
Causes of premature and potentially avoidable death; identifying hotspots of inequality
The number of deaths in general and by specific cause are indicators of a population’s health and safety. As a population health measure, areas with consistently higher death rates demonstrate areas of inequality and this phenomenon can be deeply entrenched over time. The availability of a long-term archive of death records and the consistent recording of the residential location within these files has meant that the degree of geographic and temporal variation in the causes of death can now be examined at the small area level across Australia.
Potentially Preventable Hospitalisations: Identifying hotspots of inequalities
Justin Beilby, a health services researcher and general practitioner for over 30 years provides his insights on the usefulness of PHIDU’s hot spot analysis of potentially preventable hospitalisations for health care decision making.
The level of Potentially Preventable Hospitalisations (PPHs) is an accepted measure of health system performance and, despite its limitations, can geographically highlight areas of concern where rates of hospitalisation are high or to investigate why in other instances rates are low.
This study identifies the geographic and temporal persistence of PPHs across Australia for Aboriginal and Torres Strait Islander people. It follows on from work by Duckett and Griffiths (2016) published as “Perils of Place: identifying hotspots of health inequalities”. These studies provide a framework to identify the existence of areas with persistently high PPH rates over time known as “PPH hotspots” and provide core principles to highlight areas where interventions can be targeted. We hope that these new analyses, and their presentation in geographical maps, heat map graphs and data sheets, will provide information that is useful to the various levels of the health system, from state and territory health agencies to local and regional health networks and boards, PHNs and primary care practitioners, in working together with an aim to reducing the level of PPHs through improved primary health care outcomes at the local area level.