14 datasets found
  1. Chicago COVID-19 Dataset

    • kaggle.com
    zip
    Updated Jul 20, 2022
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    Ryan Park (2022). Chicago COVID-19 Dataset [Dataset]. https://www.kaggle.com/datasets/ryandpark/chicago-covid19-dataset
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    zip(12812 bytes)Available download formats
    Dataset updated
    Jul 20, 2022
    Authors
    Ryan Park
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    Chicago
    Description

    Description Source data: https://www.chicago.gov/city/en/sites/covid-19/home/latest-data.html.

    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)

  2. COVID-19 Daily Rolling Average Case, Death, and Hospitalization Rates -...

    • healthdata.gov
    • data.cityofchicago.org
    • +1more
    csv, xlsx, xml
    Updated Apr 8, 2025
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    data.cityofchicago.org (2025). COVID-19 Daily Rolling Average Case, Death, and Hospitalization Rates - Historical [Dataset]. https://healthdata.gov/dataset/COVID-19-Daily-Rolling-Average-Case-Death-and-Hosp/sd6k-dtx6
    Explore at:
    xlsx, xml, csvAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    data.cityofchicago.org
    Description

    NOTE: This dataset has been retired and marked as historical-only.

    This dataset is a companion to the COVID-19 Daily Cases and Deaths dataset (https://data.cityofchicago.org/d/naz8-j4nc). The major difference in this dataset is that the case, death, and hospitalization corresponding rates per 100,000 population are not those for the single date indicated. They are rolling averages for the seven-day period ending on that date. This rolling average is used to account for fluctuations that may occur in the data, such as fewer cases being reported on weekends, and small numbers. The intent is to give a more representative view of the ongoing COVID-19 experience, less affected by what is essentially noise in the data.

    All rates are per 100,000 population in the indicated group, or Chicago, as a whole, for “Total” columns.

    Only Chicago residents are included based on the home address as provided by the medical provider.

    Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted based on the date the test specimen was collected. Deaths among cases are aggregated by day of death. Hospitalizations are reported by date of first hospital admission. Demographic data are based on what is reported by medical providers or collected by CDPH during follow-up investigation.

    Denominators are from the U.S. Census Bureau American Community Survey 1-year estimate for 2018 and can be seen in the Citywide, 2018 row of the Chicago Population Counts dataset (https://data.cityofchicago.org/d/85cm-7uqa).

    All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects cases and deaths currently known to CDPH.

    Numbers in this dataset may differ from other public sources due to definitions of COVID-19-related cases and deaths, sources used, how cases and deaths are associated to a specific date, and similar factors.

    Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, U.S. Census Bureau American Community Survey

  3. C

    COVID-19 Daily Cases, Deaths, and Hospitalizations - Historical

    • data.cityofchicago.org
    • healthdata.gov
    • +1more
    csv, xlsx, xml
    Updated May 22, 2024
    + more versions
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    City of Chicago (2024). COVID-19 Daily Cases, Deaths, and Hospitalizations - Historical [Dataset]. https://data.cityofchicago.org/Health-Human-Services/COVID-19-Daily-Cases-Deaths-and-Hospitalizations-H/naz8-j4nc
    Explore at:
    csv, xml, xlsxAvailable download formats
    Dataset updated
    May 22, 2024
    Dataset authored and provided by
    City of Chicago
    Description

    NOTE: This dataset has been retired and marked as historical-only.

    Only Chicago residents are included based on the home ZIP Code, as provided by the medical provider, or the address, as provided by the Cook County Medical Examiner.

    Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted on the date the test specimen was collected. Deaths are those occurring among cases based on the day of death. Hospitalizations are based on the date of first hospitalization. Only one hospitalization is counted for each case. Demographic data are based on what is reported by medical providers or collected by CDPH during follow-up investigation.

    Because of the nature of data reporting to CDPH, hospitalizations will be blank for recent dates They will fill in on later updates when the data are received, although, as for cases and deaths, may continue to be updated as further data are received.

    All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects data currently known to CDPH.

    Numbers in this dataset may differ from other public sources due to definitions of COVID-19-related cases, deaths, and hospitalizations, sources used, how cases, deaths and hospitalizations are associated to a specific date, and similar factors.

    Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office

  4. Coronavirus COVID-19 Cases By US County

    • kaggle.com
    Updated Jul 23, 2020
    + more versions
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    John Wackerow (2020). Coronavirus COVID-19 Cases By US County [Dataset]. https://www.kaggle.com/datasets/johnwdata/coronavirus-covid19-cases-by-us-county/suggestions
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 23, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    John Wackerow
    Area covered
    United States
    Description

    Context

    The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. They are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

    Content

    As described on the NYTimes Github page.

    For each date, we show the cumulative number of confirmed cases and deaths as reported that day in that county or state. All cases and deaths are counted on the date they are first announced.

    In some instances, we report data from multiple counties or other non-county geographies as a single county. For instance, we report a single value for New York City, comprising the cases for New York, Kings, Queens, Bronx and Richmond Counties. In these instances the FIPS code field will be empty. (We may assign FIPS codes to these geographies in the future.) See the list of geographic exceptions.

    Cities like St. Louis and Baltimore that are administered separately from an adjacent county of the same name are counted separately.

    “Unknown” Counties Many state health departments choose to report cases separately when the patient’s county of residence is unknown or pending determination. In these instances, we record the county name as “Unknown.” As more information about these cases becomes available, the cumulative number of cases in “Unknown” counties may fluctuate.

    Sometimes, cases are first reported in one county and then moved to another county. As a result, the cumulative number of cases may change for a given county.

    Geographic Exceptions New York City All cases for the five boroughs of New York City (New York, Kings, Queens, Bronx and Richmond counties) are assigned to a single area called New York City.

    Kansas City, Mo. Four counties (Cass, Clay, Jackson and Platte) overlap the municipality of Kansas City, Mo. The cases and deaths that we show for these four counties are only for the portions exclusive of Kansas City. Cases and deaths for Kansas City are reported as their own line.

    Joplin, Mo. Joplin is reported separately from Jasper and Newton Counties.

    Chicago All cases and deaths for Chicago are reported as part of Cook County.

    Acknowledgements

    Thanks to the New York Times for providing this data. The Gitbub repository can be found here: https://github.com/nytimes/covid-19-data

  5. COVID-19 Hospital Capacity Metrics - Historical

    • healthdata.gov
    • data.cityofchicago.org
    • +1more
    csv, xlsx, xml
    Updated Apr 8, 2025
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    data.cityofchicago.org (2025). COVID-19 Hospital Capacity Metrics - Historical [Dataset]. https://healthdata.gov/dataset/COVID-19-Hospital-Capacity-Metrics-Historical/7znp-3pfk
    Explore at:
    xlsx, csv, xmlAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    data.cityofchicago.org
    Description

    NOTE: This dataset is historical-only as of 5/10/2023. All data currently in the dataset will remain, but new data will not be added. The recommended alternative dataset for similar data beyond that date is  https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/anag-cw7u. (This is not a City of Chicago site. Please direct any questions or comments through the contact information on the site.)

    During the COVID-19 pandemic, the Chicago Department of Public Health (CDPH) required EMS Region XI (Chicago area) hospitals to report hospital capacity and patient impact metrics related to COVID-19 to CDPH through the statewide EMResource system. This requirement has been lifted as of May 9, 2023, in alignment with the expiration of the national and statewide COVID-19 public health emergency declarations on May 11, 2023. However, all hospitals will still be required by the U.S. Department of Health and Human Services (HHS) to report COVID-19 hospital capacity and utilization metrics into the HHS Protect system through the CDC’s National Healthcare Safety Network until April 30, 2024. Facility-level data from the HHS Protect system can be found at healthdata.gov.

    Until May 9, 2023, all Chicago (EMS Region XI) hospitals (n=28) were required to report bed and ventilator capacity, availability, and occupancy to the Chicago Department of Public Health (CDPH) daily. A list of reporting hospitals is included below. All data represent hospital status as of 11:59 pm for that calendar day. Counts include Chicago residents and non-residents.

    ICU bed counts include both adult and pediatric ICU beds. Neonatal ICU beds are not included. Capacity refers to all staffed adult and pediatric ICU beds. Availability refers to all available/vacant adult and pediatric ICU beds. Hospitals began reporting COVID-19 confirmed and suspected (PUI) cases in ICU on 03/19/2020. Hospitals began reporting ICU surge capacity as part of total capacity on 5/18/2020.

    Acute non-ICU bed counts include burn unit, emergency department, medical/surgery (ward), other, pediatrics (pediatric ward) and psychiatry beds. Burn beds include those approved by the American Burn Association or self-designated. Capacity refers to all staffed acute non-ICU beds. An additional 500 acute/non-ICU beds were added at the McCormick Place Treatment Facility on 4/15/2020. These beds are not included in the total capacity count. The McCormick Place Treatment Facility closed on 05/08/2020. Availability refers to all available/vacant acute non-ICU beds. Hospitals began reporting COVID-19 confirmed and suspected (PUI) cases in acute non-ICU beds on 04/03/2020.

    Ventilator counts prior to 04/24/2020 include all full-functioning mechanical ventilators, with ventilators with bilevel positive airway pressure (BiPAP), anesthesia machines, and portable/transport ventilators counted as surge. Beginning 04/24/2020, ventilator counts include all full-functioning mechanical ventilators, BiPAP, anesthesia machines and portable/transport ventilators. Ventilators are counted regardless of ability to staff. Hospitals began reporting COVID-19 confirmed and suspected (PUI) cases on ventilators on 03/19/2020. CDPH has access to additional ventilators from the EAMC (Emergency Asset Management Center) cache. These ventilators are included in the total capacity count.

    Chicago (EMS Region 11) hospitals: Advocate Illinois Masonic Medical Center, Advocate Trinity Hospital, AMITA Resurrection Medical Center Chicago, AMITA Saint Joseph Hospital Chicago, AMITA Saints Mary & Elizabeth Medical Center, Ann & Robert H Lurie Children's Hospital, Comer Children's Hospital, Community First Medical Center, Holy Cross Hospital, Jackson Park Hospital & Medical Center, John H. Stroger Jr. Hospital of Cook County, Loretto Hospital, Mercy Hospital and Medical Center, , Mount Sinai Hospital, Northwestern Memorial Hospital, Norwegian American Hospital, Roseland Community Hospital, Rush University M

  6. M

    COVID-19 Cases, Tests, and Deaths by ZIP Code

    • catalog.midasnetwork.us
    Updated Nov 3, 2025
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    Chicago Department of Public Health (2025). COVID-19 Cases, Tests, and Deaths by ZIP Code [Dataset]. https://catalog.midasnetwork.us/collection/80
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    Dataset updated
    Nov 3, 2025
    Dataset provided by
    MIDAS COORDINATION CENTER
    Authors
    Chicago Department of Public Health
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Area covered
    Postal code
    Variables measured
    Viruses, disease, COVID-19, pathogen, Homo sapiens, host organism, mortality data, Population count, diagnostic tests, infectious disease, and 4 more
    Dataset funded by
    National Institute of General Medical Sciences
    Description

    Dataset of testing, cases, and death in the city of Chicago divided by ZIP code of residency. The dataset is weekly updated and only Chicago residents are included in the dataset. For privacy reasons, totals for ZIP codes are not shown until a ZIP code includes at least five cases. Included population counts for ZIP codes are from the 2020 Census.

  7. d

    COVID-19 Outcomes by Vaccination Status - Historical

    • datasets.ai
    • healthdata.gov
    • +2more
    23, 40, 55, 8
    Updated Feb 14, 2022
    + more versions
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    City of Chicago (2022). COVID-19 Outcomes by Vaccination Status - Historical [Dataset]. https://datasets.ai/datasets/covid-19-outcomes-by-vaccination-status
    Explore at:
    55, 40, 8, 23Available download formats
    Dataset updated
    Feb 14, 2022
    Dataset authored and provided by
    City of Chicago
    Description

    NOTE: This dataset has been retired and marked as historical-only.

    Weekly rates of COVID-19 cases, hospitalizations, and deaths among people living in Chicago by vaccination status and age.

    Rates for fully vaccinated and unvaccinated begin the week ending April 3, 2021 when COVID-19 vaccines became widely available in Chicago. Rates for boosted begin the week ending October 23, 2021 after booster shots were recommended by the Centers for Disease Control and Prevention (CDC) for adults 65+ years old and adults in certain populations and high risk occupational and institutional settings who received Pfizer or Moderna for their primary series or anyone who received the Johnson & Johnson vaccine.

    Chicago residency is based on home address, as reported in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE) and Illinois National Electronic Disease Surveillance System (I-NEDSS).

    Outcomes: • Cases: People with a positive molecular (PCR) or antigen COVID-19 test result from an FDA-authorized COVID-19 test that was reported into I-NEDSS. A person can become re-infected with SARS-CoV-2 over time and so may be counted more than once in this dataset. Cases are counted by week the test specimen was collected. • Hospitalizations: COVID-19 cases who are hospitalized due to a documented COVID-19 related illness or who are admitted for any reason within 14 days of a positive SARS-CoV-2 test. Hospitalizations are counted by week of hospital admission. • Deaths: COVID-19 cases who died from COVID-19-related health complications as determined by vital records or a public health investigation. Deaths are counted by week of death.

    Vaccination status: • Fully vaccinated: Completion of primary series of a U.S. Food and Drug Administration (FDA)-authorized or approved COVID-19 vaccine at least 14 days prior to a positive test (with no other positive tests in the previous 45 days). • Boosted: Fully vaccinated with an additional or booster dose of any FDA-authorized or approved COVID-19 vaccine received at least 14 days prior to a positive test (with no other positive tests in the previous 45 days). • Unvaccinated: No evidence of having received a dose of an FDA-authorized or approved vaccine prior to a positive test.

    CLARIFYING NOTE: Those who started but did not complete all recommended doses of an FDA-authorized or approved vaccine prior to a positive test (i.e., partially vaccinated) are excluded from this dataset.

    Incidence rates for fully vaccinated but not boosted people (Vaccinated columns) are calculated as total fully vaccinated but not boosted with outcome divided by cumulative fully vaccinated but not boosted at the end of each week. Incidence rates for boosted (Boosted columns) are calculated as total boosted with outcome divided by cumulative boosted at the end of each week. Incidence rates for unvaccinated (Unvaccinated columns) are calculated as total unvaccinated with outcome divided by total population minus cumulative boosted, fully, and partially vaccinated at the end of each week. All rates are multiplied by 100,000.

    Incidence rate ratios (IRRs) are calculated by dividing the weekly incidence rates among unvaccinated people by those among fully vaccinated but not boosted and boosted people.

    Overall age-adjusted incidence rates and IRRs are standardized using the 2000 U.S. Census standard population.

    Population totals are from U.S. Census Bureau American Community Survey 1-year estimates for 2019.

    All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. This dataset reflects data known to CDPH at the time when the dataset is updated each week.

    Numbers in this dataset may differ from other public sources due to when data are reported and how City of Chicago boundaries are defined.

    For all datasets related to COVID-19, see https://data.cityofchic

  8. I

    Spatial accessibility of COVID-19 healthcare resources in Illinois, USA

    • databank.illinois.edu
    Updated Mar 14, 2021
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    Jeon-Young Kang; Alexander Michels; Fangzheng Lyu; Shaohua Wang; Nelson Agbodo; Vincent L Freeman; Shaowen Wang; Padmanabhan Anand (2021). Spatial accessibility of COVID-19 healthcare resources in Illinois, USA [Dataset]. http://doi.org/10.13012/B2IDB-6582453_V1
    Explore at:
    Dataset updated
    Mar 14, 2021
    Authors
    Jeon-Young Kang; Alexander Michels; Fangzheng Lyu; Shaohua Wang; Nelson Agbodo; Vincent L Freeman; Shaowen Wang; Padmanabhan Anand
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States, Illinois
    Dataset funded by
    U.S. National Science Foundation (NSF)
    Description

    This dataset contains all the code, notebooks, datasets used in the study conducted to measure the spatial accessibility of COVID-19 healthcare resources with a particular focus on Illinois, USA. Specifically, the dataset measures spatial access for people to hospitals and ICU beds in Illinois. The spatial accessibility is measured by the use of an enhanced two-step floating catchment area (E2FCA) method (Luo & Qi, 2009), which is an outcome of interactions between demands (i.e, # of potential patients; people) and supply (i.e., # of beds or physicians). The result is a map of spatial accessibility to hospital beds. It identifies which regions need more healthcare resources, such as the number of ICU beds and ventilators. This notebook serves as a guideline of which areas need more beds in the fight against COVID-19. ## What's Inside A quick explanation of the components of the zip file * COVID-19Acc.ipynb is a notebook for calculating spatial accessibility and COVID-19Acc.html is an export of the notebook as HTML. * Data contains all of the data necessary for calculations: * Chicago_Network.graphml/Illinois_Network.graphml are GraphML files of the OSMNX street networks for Chicago and Illinois respectively. * GridFile/ has hexagonal gridfiles for Chicago and Illinois * HospitalData/ has shapefiles for the hospitals in Chicago and Illinois * IL_zip_covid19/COVIDZip.json has JSON file which contains COVID cases by zip code from IDPH * PopData/ contains population data for Chicago and Illinois by census tract and zip code. * Result/ is where we write out the results of the spatial accessibility measures * SVI/contains data about the Social Vulnerability Index (SVI) * img/ contains some images and HTML maps of the hospitals (the notebook generates the maps) * README.md is the document you're currently reading! * requirements.txt is a list of Python packages necessary to use the notebook (besides Jupyter/IPython). You can install the packages with python3 -m pip install -r requirements.txt

  9. d

    COVID-Like Illness (CLI) and COVID-19 Diagnosis Emergency Department Visits...

    • catalog.data.gov
    • data.cityofchicago.org
    • +1more
    Updated Oct 25, 2024
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    data.cityofchicago.org (2024). COVID-Like Illness (CLI) and COVID-19 Diagnosis Emergency Department Visits - Historical [Dataset]. https://catalog.data.gov/dataset/covid-like-illness-cli-and-covid-19-diagnosis-emergency-department-visits
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    Dataset updated
    Oct 25, 2024
    Dataset provided by
    data.cityofchicago.org
    Description

    NOTE: This dataset is no longer being updated but is being kept for historical reference. For current data on respiratory illness visits and respiratory laboratory testing data please see Influenza, COVID-19, RSV, and Other Respiratory Virus Laboratory Surveillance and Inpatient, Emergency Department, and Outpatient Visits for Respiratory Illnesses. 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/reopening-chicago.html#reopeningmetrics. For all datasets related to COVID-19, see https://data.cityofchicago.org/browse?limitTo=datasets&sortBy=alpha&tags=covid-19. The National Syndromic Surveillance Program (NSSP), a collaboration among CDC, federal partners, local and state health departments, and academic and private sector partners, is used to capture information during an Emergency Department (ED) visit. ED data can include information that are collected before cases are diagnosed or laboratory results are confirmed, providing an early warning system for infections, like COVID-19. This dataset includes reports of COVID-19-Like illness (CLI) and COVID-19 diagnosed during an ED visit. CLI is defined as fever and cough or shortness of breath or difficulty breathing with or without the presence of a coronavirus diagnosis code. Visits meeting the CLI definition that also have mention of flu or influenza are excluded. This dataset also includes ED visits among persons who have been diagnosed or laboratory confirmed to have COVID-19. During the initial months of the COVID-19 pandemic COVID-19 diagnoses counts are artificially low, due to varying eligibility requirements and availability of testing. Over the course of the COVID-19 pandemic, public health best practices migrated from focusing on CLI to focusing on diagnosed cases. This dataset originally contained only CLI columns. In June 2021, the diagnosis columns were added, back filled to the start of the pandemic but with the caveat noted above. Roughly simultaneously, updating of the CLI columns was discontinued, although previously existing data were kept. Reflecting the new columns, the name of the dataset was changed from “COVID-Like Illness (CLI) Emergency Department Visits” to “COVID-Like Illness (CLI) and COVID-19 Diagnosis Emergency Department Visits” at the same time. Data Source: Illinois Hospital Emergency Departments reporting to CDPH through the National Syndromic Surveillance Project (NSSP)

  10. C

    Covid 60655

    • data.cityofchicago.org
    Updated May 23, 2024
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    City of Chicago (2024). Covid 60655 [Dataset]. https://data.cityofchicago.org/widgets/mxmg-zkv6?mobile_redirect=true
    Explore at:
    kml, csv, xml, kmz, xlsx, application/geo+jsonAvailable download formats
    Dataset updated
    May 23, 2024
    Authors
    City of Chicago
    Description

    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".

    Confirmed 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 confirmed cases based on the week of death.

    For tests, each individual is counted once, based on the week the test specimen was collected. Tests performed prior to 3/1/2020 are not included. Test counts do not include multiple tests for the same person or some negative tests not reported to CDPH.

    The “Percent Tested Positive” columns are calculated by dividing the corresponding Cases and Tests columns. Because of the data limitations for the Tests columns, as well as strict criteria for performing COVID-19 tests, these percentages may vary in either direction from the actual disease prevalence in the ZIP Code. Of particular note, these rates do not represent population-level disease surveillance.

    Population counts are from the 2010 Decennial Census.

    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

  11. d

    COVID Impact Survey - Public Data

    • data.world
    csv, zip
    Updated Oct 16, 2024
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    The Associated Press (2024). COVID Impact Survey - Public Data [Dataset]. https://data.world/associatedpress/covid-impact-survey-public-data
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    csv, zipAvailable download formats
    Dataset updated
    Oct 16, 2024
    Authors
    The Associated Press
    Description

    Overview

    The Associated Press is sharing data from the COVID Impact Survey, which provides statistics about physical health, mental health, economic security and social dynamics related to the coronavirus pandemic in the United States.

    Conducted by NORC at the University of Chicago for the Data Foundation, the probability-based survey provides estimates for the United States as a whole, as well as in 10 states (California, Colorado, Florida, Louisiana, Minnesota, Missouri, Montana, New York, Oregon and Texas) and eight metropolitan areas (Atlanta, Baltimore, Birmingham, Chicago, Cleveland, Columbus, Phoenix and Pittsburgh).

    The survey is designed to allow for an ongoing gauge of public perception, health and economic status to see what is shifting during the pandemic. When multiple sets of data are available, it will allow for the tracking of how issues ranging from COVID-19 symptoms to economic status change over time.

    The survey is focused on three core areas of research:

    • Physical Health: Symptoms related to COVID-19, relevant existing conditions and health insurance coverage.
    • Economic and Financial Health: Employment, food security, and government cash assistance.
    • Social and Mental Health: Communication with friends and family, anxiety and volunteerism. (Questions based on those used on the U.S. Census Bureau’s Current Population Survey.) ## Using this Data - IMPORTANT This is survey data and must be properly weighted during analysis: DO NOT REPORT THIS DATA AS RAW OR AGGREGATE NUMBERS!!

    Instead, use our queries linked below or statistical software such as R or SPSS to weight the data.

    Queries

    If you'd like to create a table to see how people nationally or in your state or city feel about a topic in the survey, use the survey questionnaire and codebook to match a question (the variable label) to a variable name. For instance, "How often have you felt lonely in the past 7 days?" is variable "soc5c".

    Nationally: Go to this query and enter soc5c as the variable. Hit the blue Run Query button in the upper right hand corner.

    Local or State: To find figures for that response in a specific state, go to this query and type in a state name and soc5c as the variable, and then hit the blue Run Query button in the upper right hand corner.

    The resulting sentence you could write out of these queries is: "People in some states are less likely to report loneliness than others. For example, 66% of Louisianans report feeling lonely on none of the last seven days, compared with 52% of Californians. Nationally, 60% of people said they hadn't felt lonely."

    Margin of Error

    The margin of error for the national and regional surveys is found in the attached methods statement. You will need the margin of error to determine if the comparisons are statistically significant. If the difference is:

    • At least twice the margin of error, you can report there is a clear difference.
    • At least as large as the margin of error, you can report there is a slight or apparent difference.
    • Less than or equal to the margin of error, you can report that the respondents are divided or there is no difference. ## A Note on Timing Survey results will generally be posted under embargo on Tuesday evenings. The data is available for release at 1 p.m. ET Thursdays.

    About the Data

    The survey data will be provided under embargo in both comma-delimited and statistical formats.

    Each set of survey data will be numbered and have the date the embargo lifts in front of it in the format of: 01_April_30_covid_impact_survey. The survey has been organized by the Data Foundation, a non-profit non-partisan think tank, and is sponsored by the Federal Reserve Bank of Minneapolis and the Packard Foundation. It is conducted by NORC at the University of Chicago, a non-partisan research organization. (NORC is not an abbreviation, it part of the organization's formal name.)

    Data for the national estimates are collected using the AmeriSpeak Panel, NORC’s probability-based panel designed to be representative of the U.S. household population. Interviews are conducted with adults age 18 and over representing the 50 states and the District of Columbia. Panel members are randomly drawn from AmeriSpeak with a target of achieving 2,000 interviews in each survey. Invited panel members may complete the survey online or by telephone with an NORC telephone interviewer.

    Once all the study data have been made final, an iterative raking process is used to adjust for any survey nonresponse as well as any noncoverage or under and oversampling resulting from the study specific sample design. Raking variables include age, gender, census division, race/ethnicity, education, and county groupings based on county level counts of the number of COVID-19 deaths. Demographic weighting variables were obtained from the 2020 Current Population Survey. The count of COVID-19 deaths by county was obtained from USA Facts. The weighted data reflect the U.S. population of adults age 18 and over.

    Data for the regional estimates are collected using a multi-mode address-based (ABS) approach that allows residents of each area to complete the interview via web or with an NORC telephone interviewer. All sampled households are mailed a postcard inviting them to complete the survey either online using a unique PIN or via telephone by calling a toll-free number. Interviews are conducted with adults age 18 and over with a target of achieving 400 interviews in each region in each survey.Additional details on the survey methodology and the survey questionnaire are attached below or can be found at https://www.covid-impact.org.

    Attribution

    Results should be credited to the COVID Impact Survey, conducted by NORC at the University of Chicago for the Data Foundation.

    AP Data Distributions

    ​To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

  12. g

    Provisional Deaths Due to Respiratory Illnesses

    • gimi9.com
    • data.cityofchicago.org
    • +2more
    Updated Jan 6, 2025
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    (2025). Provisional Deaths Due to Respiratory Illnesses [Dataset]. https://gimi9.com/dataset/data-gov_provisional-deaths-due-to-respiratory-illnesses
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    Dataset updated
    Jan 6, 2025
    Description

    The Chicago Department of Public Health (CDPH) receives weekly deidentified provisional death certificate data for all deaths that occur in Chicago, which can include both Chicago and non-Chicago residents from the Illinois Department of Public Health (IDPH) Illinois Vital Records System (IVRS). CDPH scans for keywords to identify deaths with COVID-19, influenza, or respiratory syncytial virus (RSV) listed as an immediate cause of death, contributing factor, or other significant condition. The percentage of all reported deaths that are attributed to COVID-19, influenza, or RSV is calculated as the number of deaths for each respective disease divided by the number of deaths from all causes, multiplied by 100. This dataset reflects death certificates that have been submitted to IVRS at the time of transmission to CDPH each week – data from previous weeks are not updated with any new submissions to IVRS. As such, estimates in this dataset may differ from those reported through other sources. This dataset can be used to understand trends in COVID-19, influenza, and RSV mortality in Chicago but does not reflect official death statistics. Source: Provisional deaths from the Illinois Department of Public Health Illinois Vital Records System.

  13. COVID-19 - Vaccinations by Region, Age, and Race-Ethnicity - Historical

    • healthdata.gov
    • data.cityofchicago.org
    • +2more
    csv, xlsx, xml
    Updated Apr 8, 2025
    + more versions
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    data.cityofchicago.org (2025). COVID-19 - Vaccinations by Region, Age, and Race-Ethnicity - Historical [Dataset]. https://healthdata.gov/dataset/COVID-19-Vaccinations-by-Region-Age-and-Race-Ethni/gdfz-hxz9
    Explore at:
    xml, csv, xlsxAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    data.cityofchicago.org
    Description

    NOTE: This dataset has been retired and marked as historical-only. The recommended dataset to use in its place is https://data.cityofchicago.org/Health-Human-Services/COVID-19-Vaccination-Coverage-Region-HCEZ-/5sc6-ey97.

    COVID-19 vaccinations administered to Chicago residents by Healthy Chicago Equity Zones (HCEZ) based on the reported address, race-ethnicity, and age group of the person vaccinated, as provided by the medical provider in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE).

    Healthy Chicago Equity Zones is an initiative of the Chicago Department of Public Health to organize and support hyperlocal, community-led efforts that promote health and racial equity. Chicago is divided into six HCEZs. Combinations of Chicago’s 77 community areas make up each HCEZ, based on geography. For more information about HCEZs including which community areas are in each zone see: https://data.cityofchicago.org/Health-Human-Services/Healthy-Chicago-Equity-Zones/nk2j-663f

    Vaccination Status Definitions:

    ·People with at least one vaccine dose: Number of people who have received at least one dose of any COVID-19 vaccine, including the single-dose Johnson & Johnson COVID-19 vaccine.

    ·People with a completed vaccine series: Number of people who have completed a primary COVID-19 vaccine series. Requirements vary depending on age and type of primary vaccine series received.

    ·People with a bivalent dose: Number of people who received a bivalent (updated) dose of vaccine. Updated, bivalent doses became available in Fall 2022 and were created with the original strain of COVID-19 and newer Omicron variant strains.

    Weekly cumulative totals by vaccination status are shown for each combination of race-ethnicity and age group within an HCEZ. Note that each HCEZ has a row where HCEZ is “Citywide” and each HCEZ has a row where age is "All" so care should be taken when summing rows.

    Vaccinations are counted based on the date on which they were administered. Weekly cumulative totals are reported from the week ending Saturday, December 19, 2020 onward (after December 15, when vaccines were first administered in Chicago) through the Saturday prior to the dataset being updated.

    Population counts are from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-year estimates.

    Coverage percentages are calculated based on the cumulative number of people in each population subgroup (age group by race-ethnicity within an HCEZ) who have each vaccination status as of the date, divided by the estimated number of people in that subgroup.

    Actual counts may exceed population estimates and lead to >100% coverage, especially in small race-ethnicity subgroups of each age group within an HCEZ. All coverage percentages are capped at 99%.

    All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects data currently known to CDPH.

    Numbers in this dataset may differ from other public sources due to when data are reported and how City of Chicago boundaries are defined.

    CDPH uses the most complete data available to estimate COVID-19 vaccination coverage among Chicagoans, but there are several limitations that impact its estimates. Data reported in I-CARE only includes doses administered in Illinois and some doses administered outside of Illinois reported historically by Illinois providers. Doses administered by the federal Bureau of Prisons and Department of Defense are also not currently reported in I-CARE. The Veterans Health Administration began reporting doses in I-CARE beginning September 2022. Due to people receiving vaccinations that are not recorded in I-CARE that can be linked to their record, such as someone receiving a vaccine dose in another state, the number of people with a completed series or a booster dose is underesti

  14. C

    Inpatient, Emergency Department, and Outpatient Visits for Respiratory...

    • data.cityofchicago.org
    • healthdata.gov
    • +1more
    csv, xlsx, xml
    Updated Nov 28, 2025
    + more versions
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    Chicago Department of Public Health (2025). Inpatient, Emergency Department, and Outpatient Visits for Respiratory Illnesses [Dataset]. https://data.cityofchicago.org/Health-Human-Services/Inpatient-Emergency-Department-and-Outpatient-Visi/7ce8-bpr6
    Explore at:
    xlsx, xml, csvAvailable download formats
    Dataset updated
    Nov 28, 2025
    Dataset authored and provided by
    Chicago Department of Public Health
    Description

    This dataset includes aggregated weekly data on the percent of emergency department visits and the percent of hospital inpatient admissions due to influenza-like illness (ILI), COVID-19, influenza, RSV, and acute respiratory illness. The Illinois Department of Public Health (IDPH) collects data for Emergency Department visits to all 185 acute care hospitals in Illinois. The data are submitted from IDPH to the CDC’s BioSense Platform for access and analysis by health departments via the ESSENCE system.

    The CDC National Syndromic Surveillance Program (NSSP) utilizes diagnostic codes and clinical terms to create definitions for diagnosed COVID-19, influenza, RSV, and acute respiratory illness. For more information on diagnostic codes and clinical terms used, visit: https://www.cdc.gov/nssp/php/onboarding-resources/companion-guide-ed-data-respiratory-illness.html

    The data is characterized by selected demographic groups including age group and race/ethnicity.

    The dataset also includes percent of weekly outpatient visits due to ILI as reported by several outpatient clinics throughout Chicago that participate in CDC’s Influenza-like Illness Surveillance Network (ILINet).

    For more information on ESSENCE, see https://www.dph.illinois.gov/data-statistics/syndromic-surveillance

    For more information on ILINet, see https://www.cdc.gov/fluview/overview/index.html#cdc_generic_section_3-outpatient-illness-surveillance

    All data are provisional and subject to change. Information is updated as additional details are received. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources.

  15. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Ryan Park (2022). Chicago COVID-19 Dataset [Dataset]. https://www.kaggle.com/datasets/ryandpark/chicago-covid19-dataset
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Chicago COVID-19 Dataset

COVID-19 Cases, Tests, and Deaths by ZIP Code!

Explore at:
zip(12812 bytes)Available download formats
Dataset updated
Jul 20, 2022
Authors
Ryan Park
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Area covered
Chicago
Description

Description Source data: https://www.chicago.gov/city/en/sites/covid-19/home/latest-data.html.

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)

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