CDC SVI Documentation 2014

View print only PDF of CDC SVI 2014 Documentation pdf icon[PDF – 668 KB]

CDC SVI 2014 Documentation – 12/13/2017

Please see data dictionary and SVI 2014-2010 crosswalk below.

Introduction

What is Social Vulnerability?

Every community must prepare for and respond to hazardous events, whether a natural disaster like a tornado or a disease outbreak, or an anthropogenic event such as a harmful chemical spill. The degree to which a community exhibits certain social conditions, including high poverty, low percentage of vehicle access, or crowded households, may affect that community’s ability to prevent human suffering and financial loss in the event of disaster. These factors describe a community’s social vulnerability.

What is the Social Vulnerability Index?

ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) has created a tool to help public health officials and emergency response planners identify and map the communities that will most likely need support before, during, and after a hazardous event.

The Social Vulnerability Index (SVI) indicates the relative vulnerability of every U.S. Census tract. Census tracts are subdivisions of counties for which the Census collects statistical data. The SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking.

In addition to tract-level rankings, SVI 2010 and SVI 2014 also have corresponding rankings at the county level.

How can the SVI help communities be better prepared for hazardous events?

The SVI provides specific socially and spatially relevant information to help public health officials and local planners better prepare communities to respond to emergency events such as severe weather, floods, disease outbreaks, or chemical exposure.

The SVI can be used to:

• Allocate emergency preparedness funding by community need.
• Estimate the amount and type of needed supplies like food, water, medicine, and bedding.
• Decide how many emergency personnel are required to assist people.
• Identify areas in need of emergency shelters.
• Create a plan to evacuate people, accounting for those who have special needs, such as those without vehicles, the elderly, or people who do not understand English well.
• Identify communities that will need continued support to recover following an emergency or natural disaster.

Important Notes on the SVI Database

• For SVI 2000 and 2010, keep the data in geodatabase format. Converting to shapefile changes the field names. SVI 2014 is available for download in shapefile format. The 2014 names have been changed to accommodate shapefiles. A 2014 to 2010 “crosswalk” is included in this documentation.
• For US-wide or multi-state mapping and analysis, use the US database, in which all tracts/counties are ranked against one another. For individual state mapping and analysis, use the state-specific database, in which tracts/counties are ranked only against other tracts/counties in the specified state.
• Starting with SVI 2014, we’ve added a stand-alone, state-specific Commonwealth of Puerto Rico database. Puerto Rico is not included in the US-wide ranking.
• Starting with SVI 2014, we’ve added a database of Tribal Census Tractsexternal icon (https://www.census.gov/glossary/#term_TribalCensusTractexternal icon).
• Tribal tracts are defined independently of, and in addition to, standard county-based tracts. The tribal tract database contains only estimates, percentages, and their respective MOEs, along with the adjunct variables described in the data dictionary below. Because of geographic separation and cultural diversity, tribal tracts are not ranked against each other nor against standard census tracts.
• Tracts with zero estimates for total population (N = 404 for U.S.) were removed during the ranking process. These tracts were added back to the SVI databases after ranking. The TOTPOP field value is 0, but the percentile ranking fields (RPL_THEME1, RPL_THEME2, RPL_THEME3, RPL_THEME4, and RPL_THEMES) were set to -999.
• For tracts with > 0 TOTPOP, a value of -999 in any field either means the value was unavailable from the original census data or we could not calculate a derived value because of unavailable census data.
• Any cells with a -999 were not used for further calculations. For example, total flags do not include fields with a -999 value.
• ArcGIS preserves leading 0s in the FIPS code fields of csv files. To preserve leading 0s in Excel , follow these steps:
  • Open a blank worksheet in Excel.
  • Click the DATA tab and choose to open a file from Text
  • Navigate to the csv file and choose to Import
  • In the Text Import Wizard, choose the Delimited data type, then Next
  • Choose the Comma delimiter, then Next
  • One by one, select fields based on FIPS codes (TRACTCE, ST, STCNTY, FIPS), set the Column data format to Text, then click Finish to open the csv with leading 0s preserved.
• See the Methods section below for further details.
• Questions? Please visit the SVI web site at http://svi.cdc.gov for additional information.

Methods

Variables Used

American Community Survey (ACS), 2010-2014 (5-year) data for the following estimates:

Text version of overall vulnerability image:

• Socioeconomic Status
  • Below Poverty
  • Unemployed
  • Income
  • No High School Diploma
• Household Composition & Disability
  • Aged 65 or Older
  • Aged 17 or Younger
  • Civilian with a Disability
  • Single-Parent Households
• Minority Status & Language
  • Minority
  • Speaks English “Less than Well”
• Housing Type & Transportation
  • Multi-Unit Structures
  • Mobile Homes
  • Crowding
  • No Vehicle
  • Group Quarters

For SVI 2014, we included two adjunct variables, 1) 2010-2014 ACS estimates for persons without health insurance, and 2) an estimate of daytime population derived from LandScan 2012 estimates. These adjunct variables are excluded from the SVI rankings.

Raw data estimates and percentages for each variable, for each tract, are included in the database. In addition, the margins of error (MOEs) for each estimate, at the Census Bureau standard of 90%, are also included. Confidence intervals can be calculated by subtracting the MOE from the estimate (lower limit) and adding the MOE to the estimate (upper limit). Because of relatively small sample sizes, some of the MOEs are high. It’s important to identify the amount of error acceptable in any analysis.

Rankings

We ranked Census tracts within each state and the District of Columbia, to enable mapping and analysis of relative vulnerability in individual states. We also ranked tracts for the entire United States against one another, for mapping and analysis of relative vulnerability in multiple states, or across the U.S. as a whole. Tract rankings are based on percentiles. Percentile ranking values range from 0 to 1, with higher values indicating greater vulnerability.

For each tract, we generated its percentile rank among all tracts for 1) the fifteen individual variables, 2) the four themes, and 3) Its overall position.

Theme rankings:  For each of the four themes, we summed the percentiles for the variables comprising each theme. We ordered the summed percentiles for each theme to determine theme-specific percentile rankings. The four summary theme ranking variables, detailed in the Data Dictionary below, are:

• Socioeconomic theme – RPL_THEME1
• Household Composition and Disability – RPL_THEME2
• Minority Status & Language – RPL_THEME3
• Housing & Transportation – RPL_THEME4

Overall tract rankings:  We summed the sums for each theme, ordered the tracts, and then calculated overall percentile rankings. Please note; taking the sum of the sums for each theme is the same as summing individual variable rankings. The overall tract summary ranking variable is RPL_THEMES.

Flags

Tracts in the top 10%, i.e., at the 90^th percentile of values, are given a value of 1 to indicate high vulnerability. Tracts below the 90^th percentile are given a value of 0.

For a theme, the flag value is the number of flags for variables comprising the theme. We calculated the overall flag value for each tract as the number of all variable flags.

For a detailed description of SVI variable selection rationale and methods, see A Social Vulnerability Index for Disaster Management pdf icon[PDF – 2 MB].

SVI 2014 Data Dictionary

Variables beginning with “E_” are estimates. Variables beginning with “M_” are margins of error for those estimates. Values of -999 represent “null” or “no data.”

The four summary theme ranking variables, detailed in the Data Dictionary below, are:

• Socioeconomic theme – RPL_THEME1
• Household Composition and Disability – RPL_THEME2
• Minority Status & Language – RPL_THEME3
• Housing & Transportation – RPL_THEME4

The overall tract summary ranking variable is RPL_THEMES.

SVI 2014 – SVI 2010 Crosswalk

 

Variables beginning with “E_” are estimates. Variables beginning with “M_” are margins of error for those estimates. Values of -999 represent “null” or “no data.”

All variables for CDC SVI 2014 came from ACS 2010-2014.

The blue text with a ‘*’ after indicates CDC SVI 2010 data from the 2010 decennial census.

American Community Survey field names that changed between 2010 and 2014 are marked ‘Yes’ or  ‘No’ in the ‘Field Name Changed Since 2014?’ column.

View print only PDF of CDC SVI 2014 Documentation pdf icon[PDF – 496 KB]