Social Vulnerability Index

Social Vulnerability Index (SoVI) for Gulf Coast counties

Synopsis of Social Vulnerability

The concept of social vulnerability is theoretically framed by a multi-disciplinary litany of case studies and research on specific hazard events, their impacts, and outcomes. Social vulnerability to hazards refers specifically to a lack of ability for individuals and communities to adequately prepare for, respond to, and rebound from environmental hazards. The science of vulnerability is relatively recent, but theoretical links between pre-event socio-economics and general adverse outcomes date back decades. One of the first operational measures of social vulnerability, Maloney’s (1973) Social Vulnerability of Indianapolis linked underlying social characteristics with adverse health outcomes. Subsequently, scholars at the University of South Carolina and the University of Central Florida have driven development of vulnerability science, empirical measurement of social vulnerability, and use of social vulnerability metrics for decision making, planning, and all phases of emergency management practice.

Current SoVI Model

The Social Vulnerability Index (SoVI®) measures the social vulnerability of U.S. counties to environmental hazards. The index is a comparative metric that facilitates the examination of the differences in social vulnerability among counties. SoVI® is a valuable tool for policy makers and practitioners because it graphically illustrates the geographic variation in social vulnerability. It shows where there is uneven capacity for preparedness and response and where resources might be used most effectively to reduce the pre-existing vulnerability. SoVI® also is useful as an indicator in determining the differential recovery from disasters using empirically-based information. The index synthesizes 29 socioeconomic variables, which the research literature suggests contribute to reduction in a community’s ability to prepare for, respond to, and recover from hazards. SoVI® data sources include primarily those from the United States Census Bureau.

Raw Input Variables Used to Construct SoVI

Variable Definition
QASIAN Percent Asian
QBLACK Percent Black
QHISP Percent Hispanic
QNATAM Percent Native American
QAGEDEP Percent Population under 5 Years or 65 and Over
QFAM Percent Children Living in 2-Parent Families
MEDAGE Median Age
QSSBEN Percent Households Receiving Social Security Benefits
QPOVTY Percent Poverty
QRICH Percent Households Earning over $200,000 Annually
PERCAP Per Capita Income
QESL Percent Speaking English as a Second Language with Limited English Proficiency
QFEMALE Percent Female
QFHH Percent Female Headed Households
QNRRES Nursing Home Residents Per Capita
QNOHLTH Percent of Population without Health Insurance
QED12LES Percent with Less than 12th Grade Education
QCVLUN Percent Civilian Unemployment
PPUNIT People per Unit
QRENTER Percent Renters
MDHSEVAL Median Housing Value
MDGRENT Median Gross Rent
QMOHO Percent Mobile Homes
QEXTRCT Percent Employment in Extractive Industries
QSERV Percent Employment in Service Industry
QFEMLBR Percent Female Participation in Labor Force
QNOAUTO Percent of Housing Units with No Car
QUNOCCHU Percent Unoccupied Housing Units
QHSEBRDN Percent of All Households Spending More than 40% of Their Income on Housing Expenses