SoVI (trademark) is an algorithm for measure the social vulnerability of places and the people who live there to hazards and extreme events

Description:

Reference #: 00860

The University of South Carolina is offering licensing opportunities for this technology

Potential Applications:

• Determine differential recovery from disasters

• Plan infrastructure upgrades necessary to reduce disaster damage

• Plan disaster response based on which communities are at highest risk from environmental hazards

Advantages and Benefits:

The index synthesizes 42 socioeconomic and built-in environmental variables, which research literature suggests contribute to reduction in a community’s ability to prepare for, respond to, and recover from hazards.

Invention Description:

SOVI™ (Social Vulnerability Index) measures the social vulnerability of U.S. counties to environmental hazards. The index is a comparative metric that facilitates examination of the differences in social vulnerability among counties. SOVI™ is a valuable tool for policy makers and practitioners. It graphically illustrates the geographic variation in social vulnerability, shows where there is uneven capacity for preparedness and response and where resources might be used most effectively to reduce the pre-existing vulnerability, and is also useful as an indicator in determining the differential recovery from disasters. The data was culled from national data sources, primarily those from the United States Census Bureau.

The socioeconomic and built environment data were compiled and geo-referenced by the Hazards Research Lab at the University of South Carolina. The socioeconomic and built environment variables were standardized and input into a principal components analysis to reduce the number of variables into a smaller set of indicators. Adjustments were made to the component’s directionality (negative, positive) to insure that positive loadings were associated with increasing vulnerability, and negative loadings with decreasing vulnerability. Once the directions of the loadings were determined, the components were added together to determine the numerical social vulnerability score for each county. For SOVI™ 2000, there are 11 significant components and these explain 78% of the variance in the data. Among them are socioeconomic status, elderly and children, development density, rural agriculture, race, gender, ethnicity, infrastructure employment, and county debt/revenue.

Patent Information:
For Information, Contact:
Technology Commercialization
University of South Carolina
technology@sc.edu
Inventors:
Susan Cutter
Keywords:
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