The Transit Availability Index (formerly known as the Transit Accessibility Index) is an index measuring access to transit. The index is made up of 4 sub-indices: transit frequency, transit connectivity, sidewalk density, and transit proximity. The focus of the index is on examining how well the transit system as a whole serves the region. The index is not intended to reflect the actual transit service conditions one may encounter on a specific transit trip. It is also not intended as a means to evaluate the performance of the various transit operators nor is it a suitable tool for such an evaluation. For this analysis, transit service attributes are summed at the subzone-level geography for the seven-county region. Subzones are quarter-section sized geographies that CMAP uses for household and employment forecasting; generally they are ½ mile by ½ mile square throughout the region. Subzones in the Chicago Central Business District (CBD) are generally ¼ mile by ¼ mile square due to the densities of activities and the street network in that area.The original index was created in 2010 for the GO TO 2040 plan update. "In anticipation of the GO TO 2040 plan update, CMAP staff developed a new method of measuring access to transit as a means of determining the percentage of regional population and jobs with access to transit, one of the plan’s indicators for measuring the progress of plan implementation. This new method, the Transit Accessibility Index, severed as a uniform measure of transit level of service available during an average week. It permits us to track changes in transit level of service over time and present the results in an intuitive fashion. It also offers a universal comparison of the different service levels offered across the region. The inherent loss of some of the nuances in localized service is balanced against the ability of the index to provide a relatively simple way to compare transit service over a large area over time. This index also adheres to a number of tenets CMAP staff used in developing a revised set of performance measures for the GO TO 2040 plan update: principally that the indicator use actual observed data rather than modeled values, that it is widely comprehensible and that the data are updated with sufficient frequency for the index to serve as a reasonable access to transit index benchmark for measuring progress.”The 2023 update of transit availability is a continuation of these efforts using 2019 data. One notable change is that the Pedestrian Environment Factor is no longer used as a measurement of transit availability. Rather, we have replaced this sub-index with sidewalk density. Another notable change is that the 2017 subzones were used for this analysis, whereas previous iterations used the 2009 subzones. As such, it is not suggested to directly compare the new transit availability index with previous versions of transit availability/accessibility.Transit Availability Index, Indicator Methodology Excerpt

Analysis of ‘COVID-19 Cases, Tests, and Deaths by ZIP Code’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/04f6ebfb-8a04-45ff-9335-984cd5a4e200 on 13 February 2022.

--- Dataset description provided by original source is as follows ---

This is the place to look for important information about how to use this dataset, so please expand this box and read on!

This is the source data for some of the metrics available at https://www.chicago.gov/city/en/sites/covid-19/home/latest-data.html.

For all datasets related to COVID-19, see https://data.cityofchicago.org/browse?limitTo=datasets&sortBy=alpha&tags=covid-19.

Only Chicago residents are included based on the home ZIP Code as provided by the medical provider. If a ZIP was missing or was not valid, it is displayed as "Unknown".

Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted based on the week the test specimen was collected. For privacy reasons, until a ZIP Code reaches five cumulative cases, both the weekly and cumulative case counts will be blank. Therefore, summing the “Cases - Weekly” column is not a reliable way to determine case totals. Deaths are those that have occurred among cases based on the week of death.

For tests, each test is counted once, based on the week the test specimen was collected. Tests performed prior to 3/1/2020 are not included. Test counts include multiple tests for the same person (a change made on 10/29/2020). PCR and antigen tests reported to Chicago Department of Public Health (CDPH) through electronic lab reporting are included. Electronic lab reporting has taken time to onboard and testing availability has shifted over time, so these counts are likely an underestimate of community infection.

The “Percent Tested Positive” columns are calculated by dividing the number of positive tests by the number of total tests . Because of the data limitations for the Tests columns, such as persons being tested multiple times as a requirement for employment, these percentages may vary in either direction from the actual disease prevalence in the ZIP Code.

All data are provisional and subject to change. Information is updated as additional details are received.

To compare ZIP Codes to Chicago Community Areas, please see http://data.cmap.illinois.gov/opendata/uploads/CKAN/NONCENSUS/ADMINISTRATIVE_POLITICAL_BOUNDARIES/CCAzip.pdf. Both ZIP Codes and Community Areas are also geographic datasets on this data portal.

Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, Illinois Vital Records, American Community Survey (2018)

--- Original source retains full ownership of the source dataset ---

CottonGen (https://www.cottongen.org) is a curated and integrated web-based relational database providing access to publicly available genomic, genetic and breeding data to enable basic, translational and applied research in cotton. Built using the open-source Tripal database infrastructure, CottonGen supersedes CottonDB and the Cotton Marker Database, which includes sequences, genetic and physical maps, genotypic and phenotypic markers and polymorphisms, quantitative trait loci (QTLs), pathogens, germplasm collections and trait evaluations, pedigrees, and relevant bibliographic citations, with enhanced tools for easier data sharing, mining, visualization, and data retrieval of cotton research data. CottonGen contains annotated whole genome sequences, unigenes from expressed sequence tags (ESTs), markers, trait loci, genetic maps, genes, taxonomy, germplasm, publications and communication resources for the cotton community. Annotated whole genome sequences of Gossypium raimondii are available with aligned genetic markers and transcripts. These whole genome data can be accessed through genome pages, search tools and GBrowse, a popular genome browser. Most of the published cotton genetic maps can be viewed and compared using CMap, a comparative map viewer, and are searchable via map search tools. Search tools also exist for markers, quantitative trait loci (QTLs), germplasm, publications and trait evaluation data. CottonGen also provides online analysis tools such as NCBI BLAST and Batch BLAST. This project is funded/supported by Cotton Incorporated, the USDA-ARS Crop Germplasm Research Unit at College Station, TX, the Southern Association of Agricultural Experiment Station Directors, Bayer CropScience, Corteva/Agriscience, Dow/Phytogen, Monsanto, Washington State University, and NRSP10. Resources in this dataset:Resource Title: Website Pointer for CottonGen. File Name: Web Page, url: https://www.cottongen.org/ Genomic, Genetic and Breeding Resources for Cotton Research Discovery and Crop Improvement organized by :

Species (Gossypium arboreum, barbadense, herbaceum, hirsutum, raimondii, others), Data (Contributors, Download, Submission, Community Projects, Archives, Cotton Trait Ontology, Nomenclatures, and links to Variety Testing Data and NCBISRA Datasets), Search options (Colleague, Genes and Transcripts, Genotype, Germplasm, Map, Markers, Publications, QTLs, Sequences, Trait Evaluation, MegaSearch), Tools (BIMS, BLAST+, CottonCyc, JBrowse, Map Viewer, Primer3, Sequence Retrieval, Synteny Viewer), International Cotton Genome Initiative (ICGI), and Help sources (User manual, FAQs).

Also provides Quick Start links for Major Species and Tools.