Using GIS Mapping to Help Address Disparities in Homelessness Assistance
Over the past 20 years, my career has afforded me the opportunity on many occasions to combine both my professional and personal passions. Professionally, I have a passion for policy and data analysis. Personally, I have a strong love for technology. I’m a “techie” at heart. During my tenure with the City of Philadelphia’s Office of Homeless Services, I had the opportunity to combine these passions by using Geographic Information Systems (GIS) as a tool to map data in order to help us better understand homelessness in Philadelphia, and develop policies for programs, Continuum of Care operational guidelines, and funding priorities.
GIS is a powerful software tool that uses data to assist communities in mapping patterns and trends to understand relationships. For example, GIS can be used to help communities better understand the racial disparities that exist amongst those who are affected by homelessness. Once understood, communities can develop policies and operational guidelines that ensure that their homelessness crisis response system is being attentive and responsive to these disparities.
National data clearly shows that African-Americans and Native Americans are disproportionately affected by homelessness. While African-Americans make up only 12% of the U.S. population, they comprise an estimated 41% of all sheltered people experiencing homelessness. And while we do not yet have good data on homelessness on tribal lands, the data that we do have indicates that Native Americans make up 1.2% of the general population, but an estimated 2.3% of people who experience sheltered homelessness off of tribal lands.
There are many systemic issues that lead to this inequity that require solutions that are beyond the control of the homelessness services system alone. However, Continuums of Care can use GIS to analyze local demographic patterns in homelessness and system performance trends in order to see if their system is further worsening this disproportionate impact, to inform local conversations about the disparities that exist, and to partner with others to address the larger, systemic forces that help create those disparities. As Continuums of Care seek to address the racial disparities that exist within homelessness, GIS technology in conjunction with HMIS and other data sources can be used to:
- Map race and zip code of last permanent address in order to understand if people are entering the crisis response system disproportionately from certain areas. Continuums of Care, in conjunction with other local partners, can then seek to understand the macro factors causing this disproportionality.
- Map race, destination, and permanent housing placement type (e.g., PSH, RRH) over a specified time period to see where clients are being placed within the community in order to understand placement rates by race and whether or not people of color are being concentrated in certain neighborhoods.
- Overlay permanent housing destination on top of housing quality data to see if people of color are being disproportionately placed into permanent housing of a lesser quality.
These are just a few examples of the power and strength of using technology like GIS to drive decisions at the local level. And it has other benefits, as well. GIS is a great way to develop and/or strengthen collaborative partnerships, since it requires data from multiple sources, like HMIS data, housing quality data, and data on neighborhood rents, that must be obtained from city departments, universities, and local housing/apartment associations. And mapping and analyzing this data on an ongoing basis can create lasting partnerships, thus strengthening the overall capacity of the local homelessness crisis response system.
You don’t have to be an avowed “techie” to recognize the benefit that technology can bring to social solutions. We should be deploying it more often to inform local efforts to address and eliminate disparities.
Resources
ESRI (developers of ArcGIS software)
GIS Lounge (free resources for learning GIS)