This dataset contains estimates of the prevalence of homelessness on Census night 2011, derived from the Census of Population and Housing using the Australian Bureau of Statistics (ABS) definition of homelessness. Prevalence is an estimate of how many people experienced homelessness at a particular point-in-time. The ABS uses six homeless operational groups to present the estimates of homelessness. Estimates are also presented for selected groups of people who may be marginally housed and whose living arrangements are close to the statistical boundary of homelessness and who may be at risk of homelessness. Data is by SA4 2011 boundaries. Periodicity: 5 yearly. For more information visit the Australian Bureau of Statistics.

Abstract copyright UK Data Service and data collection copyright owner. A comparative study of the causes of new episodes of homelessness among people aged 50 or more years was undertaken in Boston, Massachusetts (USA), Melbourne, Australia, and four English cities. The aims were to make a substantial contribution to the predominantly American debate on the causes of homelessness, and to make practice recommendations for the improvement of prevention. The study had several objectives. It aimed to collect information about the antecedents, triggers and risk factors for becoming homeless in later life and about the national and local policy and service contexts. Furthermore, the researchers aimed to analyse and interpret the findings with reference to an integrated model of the causes of homelessness that represented structural and policy factors, including housing, health and social service organisation and delivery factors, and personal circumstances, events, problems and dysfunctions. The aim was to do this collaboratively, by drawing on the project partners' experience and knowledge. Finally, it was hoped to develop recommendations for housing, primary health care and social welfare organisations for the prevention of homelessness. This was to be done by identifying the common sequences and interactions of events that precede homelessness and their markers (or 'early warning' indicators) and by holding workshops in England with practitioners and their representative organisations on new ways of working. By the study of contrasting welfare and philanthropic regimes in a relatively homogeneous category of homeless incidence (i.e. recent cases among late middle-aged and older people), it was hoped that valuable insights into the relative contributions of the policy, service and personal factors would be obtained. The study focused on older people who had recently become homeless, purposely to gather detailed and reliable information about the prior and contextual circumstances. To have included people who had been homeless for several years would have reduced the quality of the data because of 'recall' problems. Users should note that data from the Australian sample for the study are not included in this dataset. Main Topics: The data file includes information about the English respondents and those from Boston. It was compiled in two stages. The first stage involved each project partner entering the pre-coded responses into the file. All partners then identified themes and created codes for the open-ended responses, and the resulting variables were added. Data quality-control procedures included blind checks of the data coding and keying. The first 200 variables pertain to information collected from the respondents. They comprise descriptive variables of the circumstances prior to homelessness, including housing tenure during the three years prior to the survey, previous homelessness, employment history, income, health and addiction problems, and contacts with family, friends and formal services. The respondents were asked to rate whether specific factors were implicated in becoming homeless, and where appropriate, a following open-ended question sought elaboration. The remaining variables comprise information collected from the respondents' 'key workers' about their understanding of the events and states that led to their clients becoming homeless. No sampling frame was available. The sample profiles have been compared with those of all homeless people (not just the recently homeless) in the study locations, most effectively in London and Boston. No gross biases were revealed. The samples represent a large percentage of the clients who presented to the collaborating organisations during the study period and who gave their informed consent to participate. Agreed definitions of homelessness were: sleeping on the streets or in temporary accommodation such as shelters; being without accommodation following eviction or discharge from prison or hospital; living temporarily with relatives or friends because the person has no accommodation, but only if the stay had not exceeded six months, and the person did not pay rent and was required to leave. People who had been previously homeless were included in the survey if they had been housed for at least 12 months prior to the current episode of homelessness. Face-to-face interview Self-completion the 'key workers' (case managers) completed questionnaires about their assessments of the respondents’ problems and of the events and states that led to homelessness. Further clarifications and checks were made by telephone.

Note.*p < .05,**p < .01.SS = Self-satisfaction and PIS = Personal Identity Strength. Correlations are based on sample sizes varying from N = 38 to 44.Study 1c: Descriptive statistics and bivariate correlations for homeless adults in Australia.

This dataset presents the number of distinct specialist homeless services clients by client characteristics. The client counts are based on the location where the client resided in the week before their first presentation of the 2018-19 financial year. The data is aggregated to 2016 Australian Statistical Geography Standard (ASGS) Statistical Area Level 4 (SA4).

The Specialist Homelessness Services Collection (SHSC) data accompanies the Specialist Homelessness Services Annual Report 2018-19.

For further information about this dataset, visit the Australian Institute of Health and Welfare - Technical Information.

Notes:

• 'Homeless' status is derived for a client based on the client's housing circumstances at the beginning of their first support period within the reference year. All other clients not meeting these criteria are considered to be at risk of homelessness (excluding clients who did not provide sufficient information to make this assessment).

• Housing circumstances are determined based on the client's type of residence, tenure and conditions of occupancy.

• Rates are crude rates based on the Australian estimated resident population at 30 June of the reference year, as detailed in the online technical information.

• Includes clients from 'Other territories' and those that have not provided location information.

• Data presented have not been adjusted for partial or non-response (unweighted).

• Clients are assigned to a region based on where they lived in the week before presenting to a SHS agency. Clients are assigned to only one region, based on the location details provided in the first support period in the reference year. Regions are defined by the 2016 Australian Statistical Geography Standard (ASGS).

  AURIN has spatially enabled the original data and has excluded data from 'Unknown' SA4s.