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Estimates of people who were experiencing homelessness or marginally housed as calculated from the Census of Population and Housing. Measures to help reduce the spread of COVID included: restrictions to international travel and migration; border control measures for some states and territories; stay at home orders; limits on gatherings; and social distancing rules.
A number of state and territory governments also worked with service providers to give temporary accommodation to people sleeping rough - or in crisis situations - to protect them, and the community, from the virus. The homelessness estimates presented in this publication reflect the unique accommodation circumstances of those experiencing homelessness at the time of the Census.
More information on state and territory government responses to the pandemic and how Census data was collected during the pandemic is in the Methodology and COVID and the Census. The rate of homelessness decreased to 48 people per 10,, from 50 in The rate of homelessness for males decreased in to 55 males per 10, from 58 in , while the rate for females increased in to 42 females per 10, from 41 in Cells in this table containing data have been randomly adjusted to avoid the release of confidential data.
Discrepancies may occur between sums of the component items and totals. The ABS uses six operational groups for presenting estimates of people experiencing homelessness on Census night. These groups are:. The ABS also compiles estimates from Census data for the following three groups of people who may be marginally housed but are not classified as homeless:.
Estimates for these groups are not included in the analysis below but can be found in the data downloads. The decrease in people living in improvised dwellings, tents, or sleeping out and the increase in people in other temporary lodgings may be partly associated with measures put in place by local and state governments in response to COVID The increases in people living in boarding houses and people in other temporary lodging are also partly associated with improvements in data quality through greater use of administrative data.