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Abstract

Social vulnerability refers to the differential capacity of communities to prepare for, respond to, and recover from adverse events such as natural disasters, public health emergencies, and economic disruptions. While national indices like the CDC/ATS-DR Social Vulnerability Index (SVI) offer standardized frameworks to quantify this concept, their application often overlooks critical intra-county disparities, especially in rural areas. This study applies the 2022 SVI dataset to analyze social vulnerability in Livingston County, New York—a predominantly rural county in upstate New York. We integrate geospatial analysis, correlation matrices, and Lasso-regularized regression to assess how vulnerability varies across census tracts and to identify key structural drivers of elevated risk. Our results reveal that although Livingston County’s average SVI score is lower than the statewide median, specific tracts—including York, Springwater, Geneseo, Mount Morris, and North Dansville—exhibit significantly higher vulnerability, primarily due to limited vehicle access and poverty. Correlation analysis shows strong associations between transportation indicators and other vulnerability domains, while Lasso regression confirms that households without a vehicle are the most significant predictors of overall vulnerability. Based on these findings, we recommend targeted transportation interventions to address rural mobility challenges, including the expansion of fixed-route public transit, implementation of demand-responsive microtransit, and subsidized rideshare programs. These strategies can meaningfully reduce barriers to employment, healthcare, and education, thereby lowering vulnerability in Livingston County’s most at-risk communities. This study demonstrates the value of local-scale SVI analysis and contributes to the broader discourse on equity-driven planning in rural settings.

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