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.

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!

This dataset denotes ZIP Code centroid locations weighted by population. Population weighted centroids are a common tool for spatial analysis, particularly when more granular data is unavailable or researchers lack sophisticated geocoding tools. The ZIP Code Population Weighted Centroids allows researchers and analysts to estimate the center of population in a given geography rather than the geometric center.

This dataset is the primary transportation layer output from the CAMS application and database. This file is a street centerline network in development by Los Angeles County to move toward a public domain street centerline and addess file. This dataset can be used for two purposes:Geocoding addresses in LA County – this file currently geocodes > 99.5% of the addresses in our test files (5,000 out of 8 million addresses) using the County’s geocoding engines.This last statement is important – the County splits the street names and addresses differently than most geocoders. This means that you cannot just use this dataset with the standard ESRI geocoding (US Streets) engine.

© US Census Bureau, TIGER, LA County, RRCC