The Social Vulnerability Index
The Social Vulnerability Index (SoVI) is constructed at a county level and analyzes socioeconomic and demographic data of social vulnerability to environmental hazards. A SoVI is created using a factor analytic approach. According to our research and the work of Susan Cutter, one of the leaders of hazards research, some of the leading factors that influence social vulnerability are: Socioeconomic Status, Gender, Race and Ethnicity, Age, Rural/Urban, Renters, Population Growth, and Special Needs Populations. By using these factors in a model, distinct spatial patterns can be seen throughout the country and we can determine which areas are most vulnerable. Using a SoVI, shows us 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.
Some of the Most Important Factors
- Socioeconomic Status
The ability to absorb losses and enhance resilience to hazard impacts. Wealth enables communities to absorb and recover from losses more quickly due to insurance, social safety nets, and entitlement programs. - Gender
Women can have a more difficult time during recovery than men, often due to sector-specific employment, lower wages, and family care responsibilities. - Race and Ethnicity
Imposes language and cultural barriers that affect access to post-disaster funding and residential locations in high hazard areas. - Age
Extremes of the age spectrum affect the movement out of harm's way. Parents lose time and money caring for children when daycare facilities are affected; elderly may have mobility constraints or mobility concerns increasing the burden of care and lack of resilience. - Rural/Urban
Rural residents may be more vulnerable due to lower incomes and more dependent on locally based resource extraction economies (e.g., farming, fishing). High-density areas (urban) complicate evacuation out of harm's way. - Renters
People that rent do so because they are either transient or do not have the financial resources for home ownership. They often lack access to information about financial aid during recovery. In the most extreme cases, renters lack sufficient shelter options when lodging becomes uninhabitable or too costly to afford. - Population Growth
Counties experiencing rapid growth lack available quality housing, and the social services network may not have had time to adjust to increased populations. New migrants may not speak the language and not be familiar with bureaucracies for obtaining relief or recovery information, all of which increase vulnerability. - Special Needs Populations
Special needs populations (infirm, institutionalized, transient, homeless), while difficult to identify and measure, are disproportionately affected during disasters and, because of their invisibility in communities, mostly ignored during recovery.
This information is sourced from Susan Cutter's article Social Vulnerability to Environmental Hazards
Factors used in developing a SoVI
The following table is a list of factors that we will be using when conducting our Social Vulnerability Analysis of Mobile County, Alabama:
| Per capita income | Median value of owner occupied buildings | Percent Healthcare practitioners |
| Percent Native American and Alaska native | Percent international migrations | Percent African Americans |
| Percent Asian | Percent Native Hawaiian and Other | Percent Hispanic |
| Percent of Population > 5yo | Percent of Population < 65yo | Percent unemployed |
| Avg. number of people/household | Percent living in poverty | Percent renter-occupied housing units |
| Percent rural farm population | Percent of housing units that are mobile homes | Percent of population >25yo with no high school diploma or equivalent |
| Number of housing units per square mile | Percent of population participating in labor force | Percent females participating in civilian labor force |
| Percent employed in farming, fishing, forestry, and extraction industries | Percent population 65 years and older in institutionalized group quarters | Percent Urban population |
| Percent females | Percent female-headed households | Per household Social Security recipients |
| Percent employed in construction | Percent employed in manufacturing | Percent employed in Public Administration |
| Percent employed in service industries | Percent employed in transportation and warehousing | Percent population change 2000-2004 |
The information within this table was contributed by Justin Shelton and Will Walker, University of North Alabama