Can Data Analytics Be Used to Solve the Homeless Epidemic?
Published: February 13, 2019
Big DataCommunity DevelopmentHealth CareInformation TechnologyLOS ANGELES, CITY OF (LOS ANGELES) (CALIFORNIA)NEW YORK, CITY OF (NEW YORK) (NEW YORK)SAN DIEGO, CITY OF (SAN DIEGO) (CALIFORNIA)Social Services
As homelessness levels continue to rise across the U.S., cities should turn to data-driven solutions for answers.
With temperatures dropping to record-breaking low levels this winter, many U.S. cities must face the reality that homelessness is an ever-growing problem. Across the country, homelessness levels are rising and some cities, like Los Angeles and New York, have reached crisis levels. Yet, the government, private sector, charitable organizations, academia, and many others have devoted significant time and money to this issue. So, why are homeless populations in the U.S. growing?
Countless programs, initiatives, and investments have been dedicated to solving the homeless epidemic. Some of these solutions are even driven by data and technology. For instance, local communities use Homeless Management Information Systems to track homeless persons as they access shelters and services. Some organizations have developed interactive maps of the U.S. that capture the extent of the epidemic. The City of San Diego is even planning to monitor its homeless population with drones.
Despite their ingenuity, these and other solutions tend to operate separately from each other. The data and information collected are not usually shared with other entities either. These solutions also tend to address a singular aspect of homelessness, rather than tackling the issue from multiple sides. Individually, these solutions collect valuable data, but their isolated nature has resulted in a more limited understanding of the homeless epidemic and how it can be resolved.
This is where data analytics can play a key role. Experts agree that an analytics-based approach would allow cities to methodically track and measure homelessness. A city of any size, complexity, and geography would be able to view data on a broad level, as well as at the neighborhood and individual levels. Cities would be able to visualize all the programs, organizations, technologies, and people at play in an urban ecosystem, enabling them to know which strategies are successful, where resources are needed, and how different programs can work together, among other insights. Furthermore, data analytics would bring together information on multiple aspects of homelessness, including affordable housing, unemployment, poverty, physical and mental health, substance abuse, family and relationships, domestic abuse, and interactions with law enforcement.
A data-driven holistic solution would help lawmakers, city administrators, and many more understand the underlying factors and challenges associated with homelessness, allowing them to not only mitigate the epidemic, but prevent it altogether. Yet, such a solution, as well as the methodology behind it, still needs to be developed. With homelessness levels rapidly increasing in many U.S. cities, it is more important than ever for this to happen and, ultimately, for the resulting data to be converted into action.
Source: Data-Smart City Solutions