Is homelessness increasing or decreasing? Are certain subgroups overrepresented in the population of people experiencing homelessness in a particular community? How has homelessness changed over time? Has a certain policy or strategy been successful at reducing homelessness? What is needed in the way of resources to effectively end homelessness?

Knowing the answers to these questions is essential for those concerned with addressing homelessness. In order to be able to answer these questions, communities must measure and produce usable data on homelessness by way of reliable enumeration methodologies appropriate to their local context. Having access to timely, high quality data empowers policymakers, service providers, and advocates alike to make informed decisions on several important issues related to homelessness.

Communities across the world have adopted several different enumeration and data-gathering approaches for measuring homelessness, including the following:

• Point-in-Time Counts: a cross-sectional snapshot of the homeless population in a region at a particular point in time, usually involving a street count and shelter survey.
• Registry Weeks: a data-gathering approach often used alongside point-in-time counts where personal information is collected that can in turn be used to assess and prioritize housing and services for individuals experiencing homelessness.
• Administrative Data: data collected by service providers or government agencies as part of their standard operations that is then leveraged for enumeration purposes.
• Census & General Population Data: data collected during the administration of general population censuses.
• Capture-Recapture: an enumeration technique that uses the overlap in two or more datasets or lists to estimate the size of the population of people experiencing homelessness.

Each of these approaches to homelessness measurement has strengths and weaknesses and some may be better suited to some contexts than others. For example, administrative data can be a cost-effective way to estimate the size and composition of the homeless population and provide valuable information on service usage, but it may be less effective at capturing information on those who are not in contact with services or live in rural areas where service coverage may be less comprehensive. Alternatively, point-in-time counts are often labor- and resource-intensive undertakings that require significant planning and rely heavily on volunteers. Yet despite these drawbacks, point-in-time counts are widely used in and easily adaptable to regions without the capacity to conduct enumerations via administrative data.

A United Nations resolution adopted by the General Assembly in December 2021 underscored the importance of data and measuring homelessness, calling upon member states to:

“…collect disaggregated data on demographics, such as by age, sex and disability, related to homelessness and establish categories of homelessness, accompanying the existing measurement tools, and…harmonize the measurement and collection of data on homelessness to enable national and global policymaking.”

Building on this momentum, the Institute of Global Homelessness and UN-Habitat have teamed up to spearhead the Global Homelessness Data Initiative. The purpose of this initiative is to increase understanding of the importance of homelessness measurement and improve the quality of homeless enumerations internationally. By doing so, the initiative will allow those working on the issue of global homelessness to have a more accurate sense of the scale and nature of the problem, in turn empowering the sector with the information it needs to effectively address homelessness internationally.

Links:

UN Resolution adopted by the General Assembly

link: https://documents-dds-ny.un.org/doc/UNDOC/LTD/N21/284/09/PDF/N2128409.pdf?OpenElement

Homelessness, SDG 1, and Sustainable Recovery from COVID-19

link: https://unhabitat.org/homelessness-sdg-1-and-sustainable-recovery-from-covid-19