Data Tool Mapping Neighborhoods with the Highest Risk of Housing Instability and Homelessness
Updated data help show where to prioritize emergency rental assistance and other housing resources to support renters most in need
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Rental assistance that stabilizes residents when they experience a financial crisis is crucial to helping people avoid losing their homes. But to have the biggest impact, this assistance needs to reach the people most at risk of housing instability and homelessness.

Our Emergency Rental Assistance Priority (ERAP) Index helps local decisionmakers identify neighborhoods with the greatest need for rental assistance and apply an equity lens when allocating these resources. Search for your county to see data that, when layered with other local information, can help you prioritize neighborhoods for housing resources. You can also read the technical appendix for more information about the index and its limitations and download the data to dig in further.




To determine census tract–level values for our Emergency Rental Assistance Priority Index and its subindexes (Housing, Household Characteristics, and Income), we use data from the American Community Survey (2017–2021) and the Comprehensive Housing Affordability Strategy (2015-2019). Detailed descriptions of the indicators and data sources are provided in the technical appendix, and brief definitions of each indicator are provided below:

Housing Subindex

  • Median monthly housing cost: the median monthly housing cost of all occupied housing units with monthly housing costs
  • Share of renter-occupied units: the share of all occupied units that are occupied by renters
  • Share of renter-occupied units in multiunit buildings: the share of all renter-occupied units that are in structures with more than one unit

Household Characteristics Subindex

  • Average renter household size: the number of people in renter households divided by the number of renter households
  • Share of Black individuals: the share of all people who identify as Black and do not identify as Hispanic or Latino
  • Share of Asian individuals: the share of all people who identify as Asian and do not identify as Hispanic or Latino.
  • Share of Latine individuals: the share of all people who identify as Hispanic or Latino
  • Share of Indigenous, Pacific Islander, or multiracial individuals: the share of all people who identify as Indigenous, Pacific Islander, or multiracial and do not identify as Hispanic or Latino

Income Subindex

  • Share of cost-burdened renter households: the share of renter households with incomes less than $35,000 that are paying 50 percent or more of their incomes on rent
  • Share of extremely low-income renter households: the share of all renter households with incomes at or below 30 percent of the HUD area median family income

Each census tract’s index percentile is based on its state (for example, if a tract is in the 95th percentile, its index value is higher than the values of 95 percent of tracts in its state). For this reason, the data in this tool and in the data download should not be used to compare census tracts from different states.

Our index and its subindexes are built on historical census data and estimates that may not capture the current need in each neighborhood. We recommend using this tool in conjunction with a community-based process that includes examining local homelessness data and engaging stakeholders from groups and neighborhoods that local data show are disproportionately represented in evictions and homelessness.


This data tool was funded by the Conrad N. Hilton Foundation. It builds on foundational work completed with funding from the Melville Charitable Trust, Funders for Housing and Opportunity, the John D. and Catherine T. MacArthur Foundation, and the Schultz Family Foundation and in partnership with the Framework for an Equitable Homelessness Response partners. We are grateful to them and to all our funders, who make it possible for Urban to advance its mission. The views expressed are those of the authors and should not be attributed to the Urban Institute, its trustees, or its funders. Funders do not determine research findings or the insights and recommendations of our experts.

RESEARCH Samantha Batko, Will Curran-Groome, Judah Axelrod, Brendan Chen, and Lynden Bond

DESIGN Brittney Spinner


EDITING Lauren Lastowka


WRITING Emily Peiffer

View this project and the code used to generate the data on GitHub.

Research Areas Housing
Tags Homelessness Evictions Rental housing
Policy Centers Metropolitan Housing and Communities Policy Center