The article discusses a novel approach by the Los Angeles County Homelessness Prevention Unit, utilizing predictive statistical models to identify individuals most at risk of homelessness. Through a recent call to resident Jocelyn Escanuela, the program reached out to offer financial assistance, demonstrating its proactive method. Experts stress the importance of targeted assistance as funds are allocated through initiatives like the ULA mansion tax and Measure A sales tax. Effective prediction of homelessness is crucial to optimize limited resources and enhance intervention strategies to ultimately reduce homelessness in the city.
Attaining that elusive precision will be increasingly important as both the city's ULA "mansion tax" and the countywide Measure A sales tax begin to direct millions of dollars into homelessness prevention.
Steve Berg highlighted that "with limited prevention resources to work with, there are real consequences to not getting them to the people who need them most."
Research has shown that only a small percentage would become homeless without the help, making the identification of this group critical to effective prevention.
Despite evidence that services can prevent homelessness, knowing who will actually need that help after the fact has been a challenge.
Collection
[
|
...
]