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How Community Data can Stabilize Housing During Winter Months

Communities across the United States are currently being impacted by record-setting snowfall and power outages. Storm and snowy conditions introduce not just transportation and mobility issues, but also financial hardships. Even normal winter conditions can create challenges for families on the margins.

Roughly 25 million Americans are forgoing food and medicine expenses in order to pay their heating and energy bills – a number that is likely to rise as experts predict that this winter Americans will be paying the highest rate for heating in 25 years with fuel prices expected to surge nearly 30%. At-risk and low-income households across the country will inevitably face difficult budgeting choices, while their local governments and utilities strive to provide relief services.

When storms hit, they can have long lasting effects on vulnerable communities, putting people at risk of eviction and exposure to the elements. Low-income communities, for example, like many affected by the 2021 freeze in Texas, faced a greater risk of displacement and eviction during and after winter storms.

Governments and nonprofits face multiple challenges when helping low-income and at-risk households. The demand for programs to assist with energy and housing costs is high and growing, but many vulnerable households remain underserved. For example, only 22% of households that apply and qualify for LIHEAP assistance actually receive aid, with low-income households facing multiple barriers to assistance.

Leveraging community vulnerability data and economic burden insights to proactively and efficiently distribute relief for households experiencing energy poverty, as well as optimize service facility locations such as warming and food centers to meet the needs of their constituents.

With the help of granular socio-demographic location data, organizations can more effectively target outreach and increase engagement in these critical programs. In particular, by overlaying estimates of eligible households with data on incoming applications or outgoing disbursements, organizations can understand, in real-time, where the greatest gaps between need and assistance persist. Agencies and their partners can then monitor and adjust their strategies on a near real-time basis.

For example, a person or family who participates in benefits programs such as SNAP, SSI, and TANF, may be automatically eligible for LIHEAP. Using integrated eligibility data, program managers can proactively target these recipients to ensure they are aware of and enrolled for energy assistance.

UrbanFootprint Assist for governments, utilities, and community partners can answer critical questions at the intersection of climate change, social equity, and community resilience.

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