Every community must prepare for and respond to hazardous events, whether a natural disaster like a tornado or disease outbreak, or a human-made event such as a harmful chemical spill. A number of factors, including poverty, lack of access to transportation, and crowded housing may weaken a community’s ability to prevent human suffering and financial loss in a disaster. These factors are known as social vulnerability.Link to this page: https://www.atsdr.cdc.gov/placeandhealth/svi/interactive_map.html

The interactive maps are visual representations of the Social Vulnerability Index (SVI). Data were extracted from the US Census and the American Community Survey.

OverviewThis map visualizes the 2022 overall SVI for U.S. counties and tractsSocial Vulnerability Index (SVI) indicates the relative vulnerability of every U.S. county and tract16 social factors grouped into four major themesIndex value calculated for each county for the 16 social factors, four major themes, and the overall rankWhat is CDC/ATSDR Social Vulnerability Index?ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) has created the Social Vulnerability Index (SVI) to help emergency response planners and public health officials identify and map the communities that will most likely need support before, during, and after a hazardous event.SVI uses U.S. Census data to determine the social vulnerability of every county and tract. CDC SVI ranks each county and tract on 16 social factors, including poverty, lack of vehicle access, and crowded housing, and groups them into four related themes:Socioeconomic StatusHousehold CharacteristicsRacial & Ethnic Minority StatusHousing Type & TransportationVariablesFor a detailed description of variable uses, please refer to the full SVI 2022 documentation.RankingsWe ranked counties and tracts for the entire United States against one another. The feature layer can be used for mapping and analysis of relative vulnerability of counties in multiple states, or across the U.S. as a whole. Rankings are based on percentiles. Percentile ranking values range from 0 to 1, with higher values indicating greater vulnerability. For each county and tract, we generated its percentile rank among all counties and tracts for 1) the sixteen individual variables, 2) the four themes, and 3) its overall position.Overall Rankings:We totaled the sums for each theme, ordered the counties, 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.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 are:Socioeconomic Status - RPL_THEME1Household Characteristics - RPL_THEME2Racial & Ethnic Minority Status - RPL_THEME3Housing Type & Transportation - RPL_THEME4FlagsCounties and tracts in the top 10%, i.e., at the 90th percentile of values, are given a value of 1 to indicate high vulnerability. Counties and tracts below the 90th 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 county as the total number of all variable flags.SVI Informational VideosIntroduction to CDC Social Vulnerability Index (SVI)More Questions?CDC SVI 2022 Full DocumentationSVI Home PageContact the SVI Coordinator

This is the Social Vulnerability Index (SVI) developed by the U.S. Centers for Disease Control (CDC) Agency for Toxic Substances and Disease Registry (ATSDR) [1]. This is often used by the emergency response community to anticipate areas where social support systems are weaker, and residents may be more likely to need help. A map viewer for the national database can be found here [2].

November 2023 updates: at the time of Hurricane Harvey, the latest SVI was based on 2014 census data. The CDC SVI website and feature services have since changed. See the current (updated) links for more details.

Subsets of CDC's 2014 SVI for the Hurricane Harvey and Hurricane Irma hydrologic study areas can be downloaded from the contents list below.

[1] SVI web site [https://www.atsdr.cdc.gov/placeandhealth/svi/index.html [2] SVI interactive map [https://www.atsdr.cdc.gov/placeandhealth/svi/interactive_map.html]

This is the Social Vulnerability Index (SVI) developed by the U.S. Centers for Disease Control (CDC) [1]. This is often used by the emergency response community to anticipate areas where social support systems are weaker, and residents may be more likely to need help. A map viewer for the national database can be found here [2]. Documentation is available here [3] which is also included for download below.

Subsets of the national coverage for the Hurricane Harvey and Hurricane Irma hydrologic study areas can be downloaded below.

[1] SVI web site [http://svi.cdc.gov] [2] CDC’s Social Vulnerability Index (SVI) – 2014 overall SVI, census tract level (web feature layer) [http://cuahsi.maps.arcgis.com/home/item.html?id=f951e0df78604cf0ab1fda61a575be6b] [3] SVI Documentation [https://svi.cdc.gov/Documents/Data/2014_SVI_Data/SVI2014Documentation.pdf] [4] ArcGIS Online feature service (CONUS) [https://services3.arcgis.com/ZvidGQkLaDJxRSJ2/arcgis/rest/services/Overall_2014_Tracts/FeatureServer]

This feature layer visualizes the 2018 overall SVI for U.S. counties and tractsSocial Vulnerability Index (SVI) indicates the relative vulnerability of every U.S. county and tract15 social factors grouped into four major themesIndex value calculated for each county for the 15 social factors, four major themes, and the overall rankWhat is CDC Social Vulnerability Index?ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) has created a tool to help emergency response planners and public health officials identify and map the communities that will most likely need support before, during, and after a hazardous event.The Social Vulnerability Index (SVI) uses U.S. Census data to determine the social vulnerability of every county and tract. CDC SVI ranks each county and tract on 15 social factors, including poverty, lack of vehicle access, and crowded housing, and groups them into four related themes:SocioeconomicHousing Composition and DisabilityMinority Status and LanguageHousing and Transportation VariablesFor a detailed description of variable uses, please refer to the full SVI 2018 documentation.RankingsWe ranked counties and tracts for the entire United States against one another. This feature layer can be used for mapping and analysis of relative vulnerability of counties in multiple states, or across the U.S. as a whole. Rankings are based on percentiles. Percentile ranking values range from 0 to 1, with higher values indicating greater vulnerability. For each county and tract, we generated its percentile rank among all counties and tracts for 1) the fifteen individual variables, 2) the four themes, and 3) its overall position. Overall Rankings:We totaled the sums for each theme, ordered the counties, 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. 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 are: Socioeconomic theme - RPL_THEME1Housing Composition and Disability - RPL_THEME2Minority Status & Language - RPL_THEME3Housing & Transportation - RPL_THEME4FlagsCounties in the top 10%, i.e., at the 90th percentile of values, are given a value of 1 to indicate high vulnerability. Counties below the 90th 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 county as the total number of all variable flags. SVI Informational VideosIntroduction to CDC Social Vulnerability Index (SVI)Methods for CDC Social Vulnerability Index (SVI)More Questions?CDC SVI 2018 Full DocumentationSVI Home PageContact the SVI Coordinator

Purpose: This is an ArcGIS Pro template that GIS Specialists can use to identify vulnerable populations and special needs infrastructure most at risk to flooding events.How does it work?Determine and understand the Place Vulnerability (based on Cutter et al. 1997) and the Special Needs Infrastructure for an area of interest based on Special Flood Hazard Zones, Social Vulnerability Index, and the distribution of its Population and Housing units. The final product will be charts of the data distribution and a Hosted Feature Layer. See this Story Map example for a more detailed explanation.This uses the FEMA National Flood Hazard Layer as an input (although you can substitute your own flood hazard data), check availability for your County before beginning the Task: FEMA NFHL ViewerThe solution consists of several tasks that allow you to:Select an area of interest for your Place Vulnerability Analysis. Select a Hazard that may occur within your area of interest.Select the Social Vulnerability Index (SVI) features contained within your area of interest using the CDC’s Social Vulnerability Index (SVI) – 2016 overall SVI layer at the census tract level in the map.Determine and understand the Social Vulnerability Index for the hazard zones identified within you area of interest.Identify the Special Needs Infrastructure features located within the hazard zones identified within you area of interest.Share your data to ArcGIS Online as a Hosted Feature Layer.FIRST STEPS:Create a folder C:\GIS\ if you do not already have this folder created. (This is a suggested step as the ArcGIS Pro Tasks does not appear to keep relative paths)Download the ZIP file.Extract the ZIP file and save it to the C:\GIS\ location on your computer. Open the PlaceVulnerabilityAnalysis.aprx file.Once the Project file (.aprx) opens, we suggest the following setup to easily view the Tasks instructions, the Map and its Contents, and the Databases (.gdb) from the Catalog pane.The following public web map is included as a Template in the ArcGIS Pro solution file: Place Vulnerability Template Web MapNote 1:As this is a beta version, please take note of some pain points:Data input and output locations may need to be manually populated from the related workspaces (.gdb) or the tools may fail to run. Make sure to unzip/extract the file to the C:\GIS\ location on your computer to avoid issues.Switching from one step to the next may not be totally seamless yet.If you are experiencing any issues with the Flood Hazard Zones service provided, or if the data is not available for your area of interest, you can also download your Flood Hazard Zones data from the FEMA Flood Map Service Center. In the search, use the FEMA ID. Once downloaded, save the data in your project folder and use it as an input.Note 2:In this task, the default hazard being used are the National Flood Hazard Zones. If you would like to use a different hazard, you will need to add the new hazard layer to the map and update all query expressions accordingly.For questions, bug reports, or new requirements contact pdoherty@publicsafetygis.org

AnalysisFEMA's National Flood Hazard Layer (NFHL) and the CDC's Social Vulnerability Index (SVI) were cross referenced to produce a Place Vulnerability Analysis for Hudson County, NJ. Using ArcGIS Pro, the location of interest (Hudson County) was first determined and the Flood Hazard and SVI layers were clipped to this extent. A new feature class, intersecting the two, was then created using the Intersect Tool. The output of this process was the Hudson County Place Vulnerability Layer. Additional Layers were added to the map to assess important special needs infrastructure, community lifelines, and additional hazard risks within the most vulnerable areas of the county.LayersWildfire Hazard Potential: Shows the average wildfire hazard potential for the US on a scale of 1-5. The layer was obtained using ESRI's Living Atlas. Source: https://napsg.maps.arcgis.com/home/item.html?id=ce92e9a37f27439082476c369e2f4254 NOAA Storm Events Database 1950-2021: Shares notable storm events throughout the US recorded by NOAA between the years of 1950-2021. The layer was obtained using ESRI's Living Atlas. Source: https://gisanddata.maps.arcgis.com/home/item.html?id=88cc0d5e55f343c28739af1a091dfc91 Category 1 Hurricane Storm Surge: Includes the expected Inundation Height of areas within the US should a Category 1 Hurricane hit the area. The layer was obtained using the ArcGIS Online Portal. Source: https://gisanddata.maps.arcgis.com/home/item.html?id=49badb9332f14079b69cfa49b56809dc Category 2 Hurricane Storm Surge: Includes the expected Inundation Height of areas within the US should a Category 2 Hurricane hit the area. The layer was obtained using the ArcGIS Online Portal. Source: https://gisanddata.maps.arcgis.com/home/item.html?id=b4e4f410fe9746d5898d98bb7467c1c2 Category 3 Hurricane Storm Surge: Includes the expected Inundation Height of areas within the US should a Category 3 Hurricane hit the area. The layer was obtained using the ArcGIS Online Portal. Source: https://gisanddata.maps.arcgis.com/home/item.html?id=876a38efe537489fb3bc6b490519117f U.S. Sea Level Rise Projections: Shows different sea level rise projections within the United States. The layer was obtained via ESRI's Living Atlas. Source: https://gisanddata.maps.arcgis.com/home/item.html?id=8943e6e91c304ba2997d83b597e32861Power Plants: Includes all New Jersey power plants about 1 Megawatt capacity. The layer was obtained via the NJDEP Bureau of GIS website. Source: https://njdep.maps.arcgis.com/home/item.html?id=282eb9eb22cc40a99ed509a7aa9f7c90Solid & Hazardous Waste Facilities: Includes hazardous waste facilities, medical waste facilities, incinerators, recycling facilities, and landfill sites within New Jersey. Obtained via the NJDEP Bureau of GIS website. Source: https://njdep.maps.arcgis.com/home/item.html?id=896615180fb04d8eafda0df9df9a1d73Solid Waste Landfill Sites over 35 Acres: Includes solid waste landfill sites in New Jersey that are larger than 35 acres. Obtained via the NJDEP Bureau of GIS website. Source: https://gisanddata.maps.arcgis.com/home/item.html?id=2b4eab598df94ffabaa8d92e3e46deb4NJ Transit Rail Lines: A layer showing segments of the NJ Transit Rail System and terminals. Data was obtained via the NJ Transit GIS Department. Source: https://www.arcgis.com/home/item.html?id=e6701817be974795aecc7f7a8cc42f79Medical Emergency Response Structures: Contains emergency response centers within the U.S. based off National Geospatial Data Asset data from the U.S. Geological Survey. The layer was obtained using ESRI's Living Atlas. Source: https://gisanddata.maps.arcgis.com/home/item.html?id=2c36dbb008844081b017da6fd3d0d28bSchools: Shows the location of New Jersey schools, including public, private and charter schools. Obtained via the New Jersey Office of GIS. Source: https://njdep.maps.arcgis.com/home/item.html?id=d8223610010a4c3887cfb88b904545ffChild Care Centers: Shows the location of active child care centers in New Jersey. The layer was obtained via the NJ Bureau of GIS website. Source: https://njdep.maps.arcgis.com/home/item.html?id=0bc9fe070d4c49e1a6555c3fdea15b8aNursing Homes: A layer containing the locations of nursing homes and assisted care facilities in the United States. Obtained via the HIFLD website. Source: https://gisanddata.maps.arcgis.com/home/item.html?id=78c58035fb3942ba82af991bb4476f13cCDC's Social Vulnerability Index (SVI) - ATSDR's Geospatial Research, Analysis & Services Program (GRASP) has created a tool to help emergency response planners and public health officials identify and map the communities that will most likely need support before, during, and after a hazardous event. The Social Vulnerability Index (SVI) uses U.S. Census data to determine the social vulnerability of every census tract. The SVI ranks each census tract on 15 social factors, including poverty, lack of vehicle access, and crowded housing, and groups them into four related themes. Source: https://gisanddata.maps.arcgis.com/home/item.html?id=05709059044243ae9b42f469f0e06642

Exercise Only

This Web Map provides the foundation for a Situational Awareness application for Wilkes Barre, PA that can be used by emergency management staff to identify the impact of a flood on public infrastructure and human populations. The Situational Awareness Viewer is a configuration of Web AppBuilder for ArcGIS that can be used to analyze the impact to people and places within an incident area. The application can be configured within ArcGIS Online or deployed on-premises.This web map is based on a flood hazard assessment of Luzerne County, PA.

Populations along the Susquehanna River Basin, which includes areas of New York, Pennsylvania, and Maryland, reside in one of the most flood prone areas in the United States. Major floods have occurred about every 15 years and flash floods are a consistent threat. Luzerne County, PA communities have long histories of flood emergencies, as the river bisects the county and tributaries are spread throughout. Based on the existing models and historical data, flood protection and management are already high priorities. However, rapidly changing demographics and unpredictable environmental conditions expose the need for more detailed and constantly evolving models for emergency preparedness and response.

This Hazard Analysis of Luzerne County augments the existing flood hazard area models with two additional critical factors for consideration. First, areas with vulnerable populations are identified using the Agency for Toxic Substances and Disease Registry's (ATSDR) 2014 Social Vulnerability Index. This data model incorporates a variety of socioeconomic indicators as part of an analytical matrix that measures the potential resilience of communities facing emergency conditions. All tracts are given a percentile rank (0= Lowest Vulnerability to 1=Highest Vulnerability) for fifteen variables. Four major theme rankings (Socioeconomic, Housing Composition and Disability, Minority Status & Language, and Housing & Transportation) are compiled as a sum of the variables for each theme. An overall percentile ranking is determined for each tract. For the purposes of this study, Natural Breaks classification was used to group tracts with similar overall tract scores. All tracts with overall ratings above .7372 (top 2 of 5 classes) are defined as “High Vulnerability”, with populations that are at the highest risk during crisis level events of any kind. In addition, critical infrastructure locations are identified and mapped.

Given the incalculable value of human life and importance of essential infrastructure to response and recovery, both the “High Vulnerability” areas and critical emergency locations layers are intersected with a layer of flood hazard areas from the FEMA Flood Map Service Center. The Special Flood Hazard Areas (SFHA) that intersect with High Vulnerability areas are defined as “High Hazard Areas”.

The United States National Grid (USNG) for Luzerne County is also available as a comparative layer.

About the SFHA

The land area covered by the floodwaters of the base flood is the Special Flood Hazard Area (SFHA) on NFIP maps. The SFHA is the area where the National Flood Insurance Program's (NFIP's) floodplain management regulations must be enforced and the area where the mandatory purchase of flood insurance applies.

What is the SVI?

Social vulnerability refers to the resilience of communities when confronted by external stresses on human health, stresses such as natural or human-caused disasters, or disease outbreaks. Reducing social vulnerability can decrease both human suffering and economic loss. The Agency for Toxic Substances and Disease Registry's (ATSDR) Social Vulnerability Index uses U.S. census variables at tract level to help local officials identify communities that may need support in preparing for hazards or recovering from disaster.

What is the USNG?

The United States National Grid (USNG) is a point reference system of grid references commonly used in the United States. It provides a nationally consistent language of location in a user-friendly format. It is similar in design to the national grid reference systems used throughout other nations.

Data Sources

US Homeland Infrastructure Foundation Level Data (HIFLD Open Data Portal)

Emergency Shelters Emergency Services Hospitals Fire Stations Police Stations Colleges and Universities Private Schools Public Schools

ATSDR 2014 Social Vulnerability Index (link)

FEMA Flood Map Service Center (link)

The United States National Grid (USNG) (link)

NMCDC Copy of Living Atlas map. Source: https://www.arcgis.com/home/item.html?id=23ab8028f1784de4b0810104cd5d1c8fIllustration by Brian BrenemanThis layer shows population broken down by race and Hispanic origin. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the predominant race living within an area. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2013-2017ACS Table(s): B03002 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 7, 2018National Figures: American Fact FinderThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This dataset is updated automatically when the most current vintage of ACS data is released each year. The service contains the ACS data as of the current vintage listed. Tabular data is updated annually with the Census Bureau's release schedule. This may alter data values, fields, and boundaries. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -555555...) have been set to null. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small. NOTE: any calculated percentages or counts that contain estimates that have null margins of error yield null margins of error for the calculated fields.

NMCDC Copy of Living Atlas map. Source: https://www.arcgis.com/home/item.html?id=23ab8028f1784de4b0810104cd5d1c8fIllustration by Brian BrenemanThis layer shows population broken down by race and Hispanic origin. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the predominant race living within an area. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2013-2017ACS Table(s): B03002 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 7, 2018National Figures: American Fact FinderThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This dataset is updated automatically when the most current vintage of ACS data is released each year. The service contains the ACS data as of the current vintage listed. Tabular data is updated annually with the Census Bureau's release schedule. This may alter data values, fields, and boundaries. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -555555...) have been set to null. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small. NOTE: any calculated percentages or counts that contain estimates that have null margins of error yield null margins of error for the calculated fields.

The IPUMS National Historical Geographic Information System (NHGIS) provides free online access to summary statistics and GIS files for U.S. censuses and other nationwide surveys from 1790 through the present. NHGIS boundary files are derived primarily from the U.S. Census Bureau's TIGER/Line files with numerous additions to represent historical (1790-1980) boundaries that do not appear in TIGER/Line files. For more recent boundary files (1990 or later), NHGIS typically makes only a few key changes to the TIGER/Line source: (1) we merge files that are available only for individual states or counties to produce new nationwide or statewide files, (2) we project the data into Esri's USA Contiguous Albers Equal Area Conic Projected Coordinate System, (3) we add a GISJOIN attribute field, which supplies standard identifiers that correspond to the GISJOIN identifiers in NHGIS data tables, (4) we rename files to use the NHGIS naming style and geographic-level codes, (5) we add NHGIS-specific metadata, and (6) most substantially, we erase coastal water areas to produce polygons that terminate at the U.S. coasts and Great Lakes shores.NHGIS derived this shapefile from the U.S. Census Bureau's 2023 TIGER/Line Shapefiles.

This layer presents the USA 2020 Census Tract boundaries of the United States in the 50 states and the District of Columbia. It is updated annually as Tract boundaries change. The geography is sourced from US Census Bureau 2020 TIGER FGDB (National Sub-State) and edited using TIGER Hydrology to add a detailed coastline for cartographic purposes. Geography last updated May 2022.Attribute fields include 2020 total population from the US Census PL94 data.This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the 'U.S. Census Bureau' when using this data.Joined to this dataset is the 2020 Social Vulnerability Index from GRASP/CDC.ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) created databases to help emergency response planners and public health officials identify and map communities that will most likely need support before, during, and after a hazardous event.The CDC/ATSDR SVI uses U.S. Census data to determine the social vulnerability of every census tract. Census tracts are subdivisions of counties for which the Census collects statistical data. The CDC/ATSDR SVI ranks each tract on 16 social factors, including poverty, lack of vehicle access, and crowded housing, and groups them into four related themes. Maps of the four themes are shown in the figure below. Each tract receives a separate ranking for each of the four themes, as well as an overall ranking.Please refer to the CDC Social Vulnerability Index for more information.

78744 Zip Code Feature Layer This feature layer represents the 78744 zip code boundary within Travis County and is used in this StoryMap to provide geographic context for Austin Public Health (APH) Community Health Worker (CHW) outreach efforts. On June 8, 2024, APH CHW Strike Teams conducted a targeted West Nile Virus (WNV) education campaign in the 78744 zip code, an area with high social vulnerability and environmental factors that may contribute to increased mosquito activity and disease transmission. This outreach aimed to:

Assess community awareness of WNV transmission and prevention strategies Distribute educational materials on mosquito control and personal protection Engage with residents to encourage proactive public health behaviors

Why the 78744 Zip Code? The 78744 zip code was identified as a priority area for WNV education due to:

Social Vulnerability Index (SVI) Considerations – Populations with higher vulnerability may have limited access to health resources or face greater risks from vector-borne diseases. Environmental Risk Factors – Standing water, dense vegetation, and urban drainage patterns that may support higher mosquito populations. Historical Public Health Needs – Previous outreach efforts have highlighted the importance of continued engagement in this area.

Feature Layer Use This feature layer helps visualize the geographic scope of the CHW outreach efforts and supports public health decision-making by aligning intervention strategies with spatial data and community needs. Future applications of this layer may include:

Mapping mosquito surveillance data and environmental risk factors Overlaying additional public health data for targeted outreach Informing response strategies for future vector-borne disease outbreaks

By incorporating geographic data into public health initiatives, Austin Public Health can ensure a more data-driven, equitable, and effective approach to disease prevention and community engagement.

Public Information Requests If you cannot locate the information or records you need online, Section 552.234 of the Texas Public Information Act allows you to submit a written request using the following methods:

Online submission: City of Austin Public Records Request | Mail: P.O. Box 689001, Austin, Texas, 78768

DescriptionExercise OnlyA Situational Awareness application for Wilkes Barre, PA that can be used by emergency management staff to identify the impact of a flood on public infrastructure and human populations. The Situational Awareness Viewer is a configuration of Web AppBuilder for ArcGIS that can be used to analyze the impact to people and places within an incident area. The application can be configured within ArcGIS Online or deployed on-premises.This web map is based on a flood hazard assessment of Luzerne County, PA.Populations along the Susquehanna River Basin, which includes areas of New York, Pennsylvania, and Maryland, reside in one of the most flood prone areas in the United States. Major floods have occurred about every 15 years and flash floods are a consistent threat. Luzerne County, PA communities have long histories of flood emergencies, as the river bisects the county and tributaries are spread throughout. Based on the existing models and historical data, flood protection and management are already high priorities. However, rapidly changing demographics and unpredictable environmental conditions expose the need for more detailed and constantly evolving models for emergency preparedness and response.This Hazard Analysis of Luzerne County augments the existing flood hazard area models with two additional critical factors for consideration. First, areas with vulnerable populations are identified using the Agency for Toxic Substances and Disease Registry's (ATSDR) 2014 Social Vulnerability Index. This data model incorporates a variety of socioeconomic indicators as part of an analytical matrix that measures the potential resilience of communities facing emergency conditions. All tracts are given a percentile rank (0= Lowest Vulnerability to 1=Highest Vulnerability) for fifteen variables. Four major theme rankings (Socioeconomic, Housing Composition and Disability, Minority Status & Language, and Housing & Transportation) are compiled as a sum of the variables for each theme. An overall percentile ranking is determined for each tract. For the purposes of this study, Natural Breaks classification was used to group tracts with similar overall tract scores. All tracts with overall ratings above .7372 (top 2 of 5 classes) are defined as “High Vulnerability”, with populations that are at the highest risk during crisis level events of any kind. In addition, critical infrastructure locations are identified and mapped.Given the incalculable value of human life and importance of essential infrastructure to response and recovery, both the “High Vulnerability” areas and critical emergency locations layers are intersected with a layer of flood hazard areas from the FEMA Flood Map Service Center. The Special Flood Hazard Areas (SFHA) that intersect with High Vulnerability areas are defined as “High Hazard Areas”.The United States National Grid (USNG) for Luzerne County is also available as a comparative layer.About the SFHAThe land area covered by the floodwaters of the base flood is the Special Flood Hazard Area (SFHA) on NFIP maps. The SFHA is the area where the National Flood Insurance Program's (NFIP's) floodplain management regulations must be enforced and the area where the mandatory purchase of flood insurance applies.What is the SVI?Social vulnerability refers to the resilience of communities when confronted by external stresses on human health, stresses such as natural or human-caused disasters, or disease outbreaks. Reducing social vulnerability can decrease both human suffering and economic loss. The Agency for Toxic Substances and Disease Registry's (ATSDR) Social Vulnerability Index uses U.S. census variables at tract level to help local officials identify communities that may need support in preparing for hazards or recovering from disaster.What is the USNG?The United States National Grid (USNG) is a point reference system of grid references commonly used in the United States. It provides a nationally consistent language of location in a user-friendly format. It is similar in design to the national grid reference systems used throughout other nations.Data SourcesUS Homeland Infrastructure Foundation Level Data (HIFLD Open Data Portal)Emergency SheltersEmergency ServicesHospitalsFire StationsPolice StationsColleges and UniversitiesPrivate SchoolsPublic SchoolsATSDR 2014 Social Vulnerability Index (link)FEMA Flood Map Service Center (link)The United States National Grid (USNG) (link)