Preventing Homelessness Through Data Analysis

Predictive analytics can help identify vulnerable people early and deliver necessary services before they descend into homelessness.

1 minute read

April 9, 2019, 1:00 PM PDT

By Camille Fink


Skid Row

Neon Tommy / Flickr

Michelle Chen reports on the Economic Roundtable’s new screening tools to target individuals at risk for persistent homelessness and to provide them the most effective interventions. "The aim is to triage services for people at especially high risk of spiraling into persistent homelessness—particularly among youth and the working poor—to deliver the help they need before a temporary crisis becomes a permanent one."

The goal is to connect people to the best resources to address their needs—job training, childcare, or drug treatment, for example. The application of predictive analytics to prevent long-term homelessness is new, since in the past it has mainly been used in policing and criminal justice, says Chen.

The Economic Roundtable predictive models are being tested in Los Angeles. So far, their use has highlighted social and economic factors that make particular groups of people more vulnerable to chronic homelessness. "These homeless subgroups are, at least statistically, primed for becoming ‘stuck’ in a spiral of destabilization, trauma, and displacement—but they can steer clear of that risk if they get help before crisis strikes," notes Chen.

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