Address ranges describe a label given to a unique collection of addresses that fall along a road or path. Address ranges provide a way of locating homes and businesses based on their street addresses when no other location information is available.Using a house number, street name, street side and ZIP code, address ranges can locate the address to the geographic area associated to that side of the street. Once geocoded, the U.S. Census Bureau can assign the address to a field assignment area or tabulate the data for that address. In addition, academics, researchers, professionals and government agencies outside of the Census Bureau use MAF/TIGER address ranges to transform tabular addresses into geographical datasets for decision-making and analytical purposes.Address ranges must be unique to geocode addresses to the correct location and avoid geocoding conflicts. Multiple elements in MAF/TIGER are required to make an address range unique including street names, address house numbers and street feature geometries, such as street centerlines. The address range data model is designed to maximize geocoding matches with their correct geographic areas in MAF/TIGER by allowing an unlimited number of address range-to-street feature relationships.The Census Bureau’s Geography Division devises numerous operations and processes to build and maintain high quality address ranges so that:Address ranges accurately describe the location of addresses on the ground.Address All possible city-style addresses are geocoded.Address ranges can handle all known address and street name variations.Address ranges conform with current U.S. Postal Service ZIP codes.Address ranges are reliable and free from conflicts.Automated software continually updates existing address ranges, builds new address ranges and corrects errors. An automated operation links address location points and tabular address information to street feature edges with matching street names in the same block to build and modify address ranges.Many business rules and legal value checks ensure quality address range data in MAF/TIGER. For example, business rules prevent adding or modifying address ranges that overlap another house number range with the same street name and ZIP code. Legal value checks verify that address ranges include mandatory attribute information, valid data types and valid character values.Some of the TIGER/Line products for the public include address ranges and give the public the ability to geocode addresses to MAF/TIGER address ranges for the user’s own purpose. The address range files are available for the nation, Puerto Rico and the U.S. Island Areas at the county level. TIGER/Line files require geographic information system (GIS) software to use.The Census Bureau Geocoder Service is a web service provided to the public. The service accepts up to 1,000 input addresses and, based on Census address ranges, returns the interpolated geocoded location and census geographies. Users can access the service a web interface or a representational state transfer (REST) application program interface (API) web service. See the Census Geocoder for more information on this process. Directions on how to use the Census Geocoder available: Geocoding Services Web Application Programming Interface (API)Download: https://www2.census.gov/geo/tiger/TGRGDB24/tlgdb_2024_a_us_addr.gdb.zip

Big “p” policy changes at the state and federal level are certainly important to health equity, such as eligibility for and generosity of Medicaid benefits. Medicaid expansion has significantly expanded the number of people who are eligible for Medicaid and the creation of the health insurance exchanges (Marketplace) under the Affordable Care Act created a very visible avenue through which people can learn that they are eligible. Although many applications are now submitted online, physical access to state, county, and tribal government Medicaid offices still plays a critical role in understanding eligibility, getting help in applying, and navigating required documentation for both initial enrollment and redetermination of eligibility. However, as more government functions have moved online, in-person office locations and/or staff may have been cut to reduce costs, and gentrification has shifted where minoritized, marginalized, and/or low-income populations live, it is unclear if this key local connection point between residents and Medicaid has been maintained. Our objective was to identify and geocode all Medicaid offices in the United States for pairing with other spatial data (e.g., demographics, Medicaid participation, health care use, health outcomes) to investigate policy-relevant research questions. Three coders identified Medicaid office addresses in all 50 states and the District of Columbia by searching state government websites (e.g., Department of Health and Human Services or analogous state agency) during late 2021 and early 2022 for the appropriate Medicaid agency and its office locations, which were then reviewed for accuracy by a fourth coder. Our corpus of Medicaid office addresses was then geocoded using the Census Geocoder from the US Census Bureau (https://geocoding.geo.census.gov/geocoder/) with unresolved addresses investigated and/or manually geocoded using Google Maps. The corpus was updated in August through December 2023 following the end of the COVID-19 public health emergency by a fifth coder as several states closed and/or combined offices during the pandemic. After deduplication (e.g., where multiple counties share a single office) and removal of mailing addresses (e.g., PO Boxes), our dataset includes 3,027 Medicaid office locations. 1 (December 19, 2023) – original version 2 (January 25, 2024) – added related publication (Data in Brief), corrected two records that were missing negative signs in longitude 3 (February 6, 2024) – corrected latitude and longitude for one office (1340 State Route 9, Lake George, NY 12845) 4 (March 4, 2024) – added one office for Vermont after contacting relevant state agency (280 State Road, Waterbury, VT 05671)

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

Abstract

A crosswalk table from US postal ZIP codes to geo-points (latitude, longitude)

Documentation

Data source: public.opendatasoft.

The ZIP code database contained in 'zipcode.csv' contains 43204 ZIP codes for the continental United States, Alaska, Hawaii, Puerto Rico, and American Samoa. The database is in comma separated value format, with columns for ZIP code, city, state, latitude, longitude, timezone (offset from GMT), and daylight savings time flag (1 if DST is observed in this ZIP code and 0 if not).

This database was composed using ZIP code gazetteers from the US Census Bureau from 1999 and 2000, augmented with additional ZIP code information The database is believed to contain over 98% of the ZIP Codes in current use in the United States. The remaining ZIP Codes absent from this database are entirely PO Box or Firm ZIP codes added in the last five years, which are no longer published by the Census Bureau, but in any event serve a very small minority of the population (probably on the order of .1% or less). Although every attempt has been made to filter them out, this data set may contain up to .5% false positives, that is, ZIP codes that do not exist or are no longer in use but are included due to erroneous data sources. The latitude and longitude given for each ZIP code is typically (though not always) the geographic centroid of the ZIP code; in any event, the location given can generally be expected to lie somewhere within the ZIP code's "boundaries".The ZIP code database contained in 'zipcode.csv' contains 43204 ZIP codes for the continental United States, Alaska, Hawaii, Puerto Rico, and American Samoa. The database is in comma separated value format, with columns for ZIP code, city, state, latitude, longitude, timezone (offset from GMT), and daylight savings time flag (1 if DST is observed in this ZIP code and 0 if not). This database was composed using ZIP code gazetteers from the US Census Bureau from 1999 and 2000, augmented with additional ZIP code information The database is believed to contain over 98% of the ZIP Codes in current use in the United States. The remaining ZIP Codes absent from this database are entirely PO Box or Firm ZIP codes added in the last five years, which are no longer published by the Census Bureau, but in any event serve a very small minority of the population (probably on the order of .1% or less). Although every attempt has been made to filter them out, this data set may contain up to .5% false positives, that is, ZIP codes that do not exist or are no longer in use but are included due to erroneous data sources. The latitude and longitude given for each ZIP code is typically (though not always) the geographic centroid of the ZIP code; in any event, the location given can generally be expected to lie somewhere within the ZIP code's "boundaries".

The database and this README are copyright 2004 CivicSpace Labs, Inc., and are published under a Creative Commons Attribution-ShareAlike license, which requires that all updates must be released under the same license. See http://creativecommons.org/licenses/by-sa/2.0/ for more details. Please contact schuyler@geocoder.us if you are interested in receiving updates to this database as they become available.The database and this README are copyright 2004 CivicSpace Labs, Inc., and are published under a Creative Commons Attribution-ShareAlike license, which requires that all updates must be released under the same license. See http://creativecommons.org/licenses/by-sa/2.0/ for more details. Please contact schuyler@geocoder.us if you are interested in receiving updates to this database as they become available.

The Street_and_Address_Composite will return a geographic coordinate when a street address is entered. A user can enter an address either manually or by bulk input from a database or other source.The geocoder returns a coordinate pair and standardized address for each input address it is able to match. The NYS ITS Geospatial Services geocoder uses a series of combinations of reference data and configuration parameters to optimize both the likelihood of a match and the quality of the results. The reference data supporting the geocoder is stored in Federal Geographic Data Committee (FGDC) standard.The first composite locator (Street_and_Address_Composite) is made up of the following set of locators which are most likely to return a high quality hit. The locators are listed in the order in which they will be accessed along with a brief description of the locator's source data. These six locators will generate the majority of the results when geocoding addresses.Locator NameSource DataDescription1A_SAM_AP_ZipNameSAM Address PointsSAM address points using the postal zip code name for the city name in the locator.1B_SAM_AP_CTNameSAM Address PointsSAM address points. The city or town name is used for the city name in the locator.1C_SAM_AP_PlaceNameSAM Address PointsSAM address points. The city name is populated using the NYS Villages and Indian Reservations, the Census Designated Places and Alternate Acceptable Zip Code Names from the USPS. These names do not exist everywhere so there will be a limited number of points in this locator.3A_SS_ZipNameNYS Street SegmentsNYS Street Segments dataset using the postal zip code name for the city name in the locator. The location is interpolated from an address range on the street segment. The city name can be different for the left and right sides of the streets.3B_SS_CTNameNYS Street SegmentsNYS Street Segments using the city or town name for the city name in the locator. The location is interpolated from an address range on the street segment.3C_SS_PlaceNameNYS Street SegmentsNYS Street Segments using an alternate place name for the city field. This field is populated using the NYS Villages and Indian Reservations, the Census Designated Places and Alternate Acceptable Zip Code Names from the USPS. These areas do not exist everywhere so there will be a limited number of segments with this attribute. The location is interpolated from an address range on the street segment.For more information about the geocoding service, please visit: https://gis.ny.gov/address-geocoder.For documentation on how to add these locators to ArcGIS, please reference Adding the Statewide Geocoding Web Service. If you would like these locators to be your default locators in ArcGIS, copy DefaultLocators.xml to C:\Users<username>\AppData\Roaming\ESRI\Desktop10.X\Locators, where

NOTE: As of 2/16/2023, this page is not being updated. For data on updated (bivalent) COVID-19 booster vaccination click here: https://app.powerbigov.us/view?r=eyJrIjoiODNhYzVkNGYtMzZkMy00YzA3LWJhYzUtYTVkOWFlZjllYTVjIiwidCI6IjExOGI3Y2ZhLWEzZGQtNDhiOS1iMDI2LTMxZmY2OWJiNzM4YiJ9 This table shows the number and percent of people that have initiated COVID-19 vaccination and are fully vaccinated by CT census tract (including residents of all ages). It also shows the number of people who have not received vaccine and who are not yet fully vaccinated. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. A person who has received at least one dose of any vaccine is considered to have initiated vaccination. A person is considered fully vaccinated if they have completed a primary series by receiving 2 doses of the Pfizer, Novavax or Moderna vaccines or 1 dose of the Johnson & Johnson vaccine. The fully vaccinated are a subset of the number who have received at least one dose. The percent with at least one dose many be over-estimated and the percent fully vaccinated may be under-estimated because of vaccine administration records for individuals that cannot be linked because of differences in how names or date of birth are reported. Population data obtained from the 2019 Census ACS (www.census.gov) Geocoding is used to determine the census tract in which a person lives. People for who a census tract cannot be determined based on available address data are not included in this table. DPH recommends that these data are primarily used to identify areas that require additional attention rather than to establish and track the exact level of vaccine coverage. Census tract coverage estimates can play an important role in planning and evaluating vaccination strategies. However, inaccuracies in the data that are inherent to population surveillance may be magnified when analyses are performed down to the census tract level. We make every effort to provide accurate data, but inaccuracies may result from things like incomplete or inaccurate addresses, duplicate records, and sampling error in the American Community Survey that is used to estimate census tract population size and composition. These things may result in overestimates or underestimates of vaccine coverage. Some census tracts are suppressed. This is done if the number of people vaccinated is less than 5 or if the census population estimate is considered unreliable (coefficient of variance > 30%). Coverage estimates over 100% are shown as 100%. Connecticut COVID-19 Vaccine Program providers are required to report information on all COVID-19 vaccine doses administered to CT WiZ, the Connecticut Immunization Information System. Data on doses administered to CT residents out-of-state are being added to CT WiZ jurisdiction-by-jurisdiction. Doses administered by some Federal entities (including Department of Defense, Department of Correction, Department of Veteran’s Affairs, Indian Health Service) are not yet reported to CT WiZ. Data reported here reflect the vaccination records currently reported to CT WiZ. Caution should be used when interpreting coverage estimates in towns with large college/university populations since coverage may be underestimated. In the census, college/university students who live on or just off campus would be counted in the college/university town. However, if a student was vaccinated while studying remotely in his/her hometown, the student may be counted as a vaccine recipient in that town. As part of continuous data quality improvement efforts, duplicate records were removed from the COVID-19 vaccination data during the weeks of 4/19/2021 and 4/26/2021. As of 1/13/2021, census tract level data are provider by town for all ages. Data by age group is no longer available.

Context

Federal Superfund sites are some of the most polluted in the United States. This dataset contains a multifaceted view of Superfunds, including free-form text descriptions, geography, demographics and socioeconomics.

Content

The core data was scraped from the National Priorities List (NPL) provided by the U.S. Environmental Protection Agency (EPA). This table provides basic information such as site name, site score, date added, and links to a site description and current status. Apache Tika was used to extract text from the site description pdfs. The addresses were scraped from site status pages, and used to geocode to latitude and longitude and Census block group. The block group assignment was used to join with the Census Bureau's planning database, a rich source of nationwide demographic and socioeconomic data. The full source code used to generate the data can be found here, on github.

I have provided three separate downloads to explore:

• priorities_list_full.json: the NPL containing all geographic, site information, text descriptions, and Census Bureau data from the relevant block groups.
• pdb_tract.csv: the planning database aggregated on the tract level with an additional indicator (has_superfund) noting whether or not the tract contains the address of a Superfund site.
• pdb_block_group.csv: the planning database aggregated on the block group level with an additional indicator (has_superfund) noting whether or not the block group contains the address of a Superfund site.

Some caveats:

1. The planning database contains 300+ columns. For a full description of these columns, please see the documentation here.
2. Since the Google geocoder is relatively aggressive in providing address matches, geocoding was done through a hierarchy of queries (full address, city-state-zip, and zipcode only) to prevent gross errors. The address string used to geocode is noted through the 'geocode_source' column.
3. While this data is linked to demographic and socioeconomic data based on either the block group (tract for pdb_tract.csv), the impacts of a particular site's pollution may extend beyond these geographic regions.

Acknowledgements

I would like to thank the EPA and the Census Bureau for making such detailed information publicly available. For relevant academic work, please see Burwell-Naney et al. (2013) and references, both to and therein.

Please let me know if you have any suggestions for improving the dataset!