92 datasets found
  1. d

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

    • catalog.data.gov
    • data.cityofchicago.org
    • +2more
    Updated May 24, 2024
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    COVID-19 Cases, Tests, and Deaths by ZIP Code - Historical [Dataset]. https://catalog.data.gov/dataset/covid-19-cases-tests-and-deaths-by-zip-code
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    Dataset updated
    May 24, 2024
    Dataset provided by
    data.cityofchicago.org
    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. 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 State Profile Report - Illinois

    • catalog.data.gov
    • healthdata.gov
    • +3more
    Updated Jul 4, 2025
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    U.S. Department of Health and Human Services (2025). COVID-19 State Profile Report - Illinois [Dataset]. https://catalog.data.gov/dataset/covid-19-state-profile-report-illinois
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    Dataset updated
    Jul 4, 2025
    Dataset provided by
    United States Department of Health and Human Serviceshttp://www.hhs.gov/
    Area covered
    Illinois
    Description

    After over two years of public reporting, the State Profile Report will no longer be produced and distributed after February 2023. The final release was on February 23, 2023. We want to thank everyone who contributed to the design, production, and review of this report and we hope that it provided insight into the data trends throughout the COVID-19 pandemic. Data about COVID-19 will continue to be updated at CDC’s COVID Data Tracker. The State Profile Report (SPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, in collaboration with the White House. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services (HHS), the Centers for Disease Control and Prevention, the HHS Assistant Secretary for Preparedness and Response, and the Indian Health Service). The SPR provides easily interpretable information on key indicators for each state, down to the county level. It is a weekly snapshot in time that: Focuses on recent outcomes in the last seven days and changes relative to the month prior Provides additional contextual information at the county level for each state, and includes national level information Supports rapid visual interpretation of results with color thresholds

  3. C

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

    • data.cityofchicago.org
    • healthdata.gov
    • +1more
    application/rdfxml +5
    Updated May 22, 2024
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    City of Chicago (2024). COVID-19 Daily Rolling Average Case, Death, and Hospitalization Rates - Historical [Dataset]. https://data.cityofchicago.org/Health-Human-Services/COVID-19-Daily-Rolling-Average-Case-Death-and-Hosp/e68t-c7fv
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    application/rssxml, json, csv, xml, tsv, application/rdfxmlAvailable 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.

    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

  4. d

    COVID-19 Vaccination Coverage, ZIP Code

    • catalog.data.gov
    • data.cityofchicago.org
    • +1more
    Updated Jul 26, 2025
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    data.cityofchicago.org (2025). COVID-19 Vaccination Coverage, ZIP Code [Dataset]. https://catalog.data.gov/dataset/covid-19-vaccination-coverage-zip-code
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    Dataset updated
    Jul 26, 2025
    Dataset provided by
    data.cityofchicago.org
    Description

    NOTE: This dataset replaces a previous one. Please see below. Chicago residents who are up to date with COVID-19 vaccines by ZIP Code, based on the reported home address and age group of the person vaccinated, as provided by the medical provider in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE). “Up to date” refers to individuals who meet the CDC’s updated COVID-19 vaccination criteria based on their age and prior vaccination history. For surveillance purposes, up to date is defined based on the following criteria: People ages 5 years and older: · Are up to date when they receive 1+ doses of a COVID-19 vaccine during the current season. Children ages 6 months to 4 years: · Children who have received at least two prior COVID-19 vaccine doses are up to date when they receive one additional dose of COVID-19 vaccine during the current season, regardless of vaccine product. · Children who have received only one prior COVID-19 vaccine dose are up to date when they receive one additional dose of the current season's Moderna COVID-19 vaccine or two additional doses of the current season's Pfizer-BioNTech COVID-19 vaccine. · Children who have never received a COVID-19 vaccination are up to date when they receive either two doses of the current season's Moderna vaccine or three doses of the current season's Pfizer-BioNTech vaccine. This dataset takes the place of a previous dataset, which covers doses administered from December 15, 2020 through September 13, 2023 and is marked as historical: - https://data.cityofchicago.org/Health-Human-Services/COVID-19-Vaccinations-by-ZIP-Code/553k-3xzc. Data Notes: Weekly cumulative totals of people up to date are shown for each combination ZIP Code and age group. Note there are rows where age group is "All ages" so care should be taken when summing rows. Coverage percentages are calculated based on the cumulative number of people in each ZIP Code and age group who are considered up to date as of the week ending date divided by the estimated number of people in that subgroup. Population counts are obtained from the 2020 U.S. Decennial Census. For ZIP Codes mostly outside Chicago, coverage percentages are not calculated reliable Chicago-only population counts are not available. Actual counts may exceed population estimates and lead to coverage estimates that are greater than 100%, especially in smaller ZIP Codes with smaller populations. Additionally, the medical provider may report a work address or incorrect home address for the person receiving the vaccination, which may lead to over- or underestimation of vaccination coverage by geography. All coverage percentages are capped at 99%. Weekly cumulative counts and coverage percentages are reported from the week ending Saturday, September 16, 2023 onward through the Saturday prior to the dataset being updated. 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. The Chicago Department of Public Health uses the most complete data available to estimate COVID-19 vaccination coverage among Chicagoans, but there are several limitations that impact our estimates. Individuals may receive vaccinations that are not recorded in the Illinois immunization registry, I-CARE, such as those administered in another state, causing underestimation of the number individuals who are up to date. Inconsistencies in records of separate doses administered to the same person, such as slight variations in dates of birth, can result in duplicate records for a person and underestimate the number of people who are up to date. For all datasets related to COVID-19, please

  5. United States SB: Illinois (IL): COVID-19 Impact: Large Negative Effect

    • ceicdata.com
    Updated Apr 23, 2022
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    CEICdata.com (2022). United States SB: Illinois (IL): COVID-19 Impact: Large Negative Effect [Dataset]. https://www.ceicdata.com/en/united-states/small-business-pulse-survey-by-state-midwest-region/sb-illinois-il-covid19-impact-large-negative-effect
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    Dataset updated
    Apr 23, 2022
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 27, 2021 - Apr 11, 2022
    Area covered
    United States
    Description

    United States SB: Illinois (IL): COVID-19 Impact: Large Negative Effect data was reported at 25.000 % in 11 Apr 2022. This records a decrease from the previous number of 25.500 % for 04 Apr 2022. United States SB: Illinois (IL): COVID-19 Impact: Large Negative Effect data is updated weekly, averaging 24.900 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 27.400 % in 21 Feb 2022 and a record low of 21.200 % in 27 Dec 2021. United States SB: Illinois (IL): COVID-19 Impact: Large Negative Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S047: Small Business Pulse Survey: by State: Midwest Region: Weekly, Beg Monday (Discontinued).

  6. d

    מאגר COVID-19 - מאגרי מידע - Government Data

    • data.gov.il
    Updated May 31, 2023
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    (2023). מאגר COVID-19 - מאגרי מידע - Government Data [Dataset]. https://data.gov.il/dataset/covid-19
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    Dataset updated
    May 31, 2023
    Description

    31.5.2023: נוספה טבלה חדשה - נבדקים על פי סטטוס חיסוני. טבלה זו מציגה את הנבדקים על פי תאריכים וקטגוריות גיל וכמו כן, על פי הסטטוס החיסוני של הנבדקים. בנוסף, עודכנה טבלת המאומתים. 17.5.2023: עודכנה טבלת המחלימים עם מספר מנות החיסון טרם המחלה הראשונה 3.5.2023: נעשו עידכונים בטבלאות הבאות: - טבלת נפטרים - התווספה עמודה המציינת את מספר מנות החיסון שהתקבלו טרם הפטירה. - טבלת גילאי המתחסנים - התווספה עמודה המכילה נתונים על מנת חיסון חמישית בקרב בני 18 - טבלת האוכלוסייה הצעירה - התווספה עמודה מנה רביעית אנא קראו היטב את קבצי ה- readme הרלוונטיים המתארים את השינויים בטבלאות. 25.1.2022 - מעתה יפורסמו רק טבלת הישובים וטבלת האזורים הסטטיסטיים לפני השימוש במאגר, יש לקרוא את COVID-19.PDF ו-DISCLAIMER.PDF. יש בקבצי ה-README מידע חיוני, שיעזור בהבנת הנתונים. צוות תמנ"ע במשרד הבריאות ישמח לשמוע על התובנות שלכם בכתובת מייל המחבר שמופיע בתחתית העמוד.

  7. Lake County, IL Coronavirus Data Hub

    • data.amerigeoss.org
    esri rest, html
    Updated Aug 7, 2020
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    ESRI (2020). Lake County, IL Coronavirus Data Hub [Dataset]. https://data.amerigeoss.org/pt_PT/dataset/lake-county-il-coronavirus-data-hub
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    html, esri restAvailable download formats
    Dataset updated
    Aug 7, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Description
    Lake County's priority is the health and safety of our residents, and we continue to use every available resource to prepare our communities for the spread of COVID-19. This dashboard provides data and resources for our county.

    For the latest updates and resources for Lake County, visit lakecountyil.gov/coronavirus.
  8. United States SB: IL: COVID-19 Impact: Moderate Negative Effect

    • ceicdata.com
    Updated Apr 11, 2022
    + more versions
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    CEICdata.com (2022). United States SB: IL: COVID-19 Impact: Moderate Negative Effect [Dataset]. https://www.ceicdata.com/en/united-states/small-business-pulse-survey-by-state-midwest-region/sb-il-covid19-impact-moderate-negative-effect
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    Dataset updated
    Apr 11, 2022
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 27, 2021 - Apr 11, 2022
    Area covered
    United States
    Description

    United States SB: IL: COVID-19 Impact: Moderate Negative Effect data was reported at 41.900 % in 11 Apr 2022. This records a decrease from the previous number of 43.300 % for 04 Apr 2022. United States SB: IL: COVID-19 Impact: Moderate Negative Effect data is updated weekly, averaging 43.400 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 50.400 % in 28 Feb 2022 and a record low of 39.200 % in 22 Nov 2021. United States SB: IL: COVID-19 Impact: Moderate Negative Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S047: Small Business Pulse Survey: by State: Midwest Region: Weekly, Beg Monday (Discontinued).

  9. O

    Open Data Covid19

    • dati.toscana.it
    • data.europa.eu
    csv
    Updated Oct 4, 2020
    + more versions
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    Ars (2020). Open Data Covid19 [Dataset]. https://dati.toscana.it/dataset/open-data-covid19
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    csv(1606041)Available download formats
    Dataset updated
    Oct 4, 2020
    Dataset provided by
    Ars
    License

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

    Description

    Il dataset contiene: i numeri totali dell’ultimo aggiornamento giornaliero disponibile e la variazione percentuale rispetto alla giornata precedente.

    Le info messe a disposizione: geografia, giorno, data, totale casi positivi, andamento dei casi positivi x1000 abitanti, deceduti, incremento deceduti rispetto alla giornata precedente x100, letalità, totale dei ricoveri, incremento ricoveri rispetto alla giornata precedente x100, attualmente positivi, dimessi, tamponi effettuati, incremento tamponi rispetto alla giornata precedente x100 suddivisi per provincia, AUSL (quando possibile). I dati saranno aggiornati entro le ore 20 di ogni giorno.

    ****** ATTENZIONE!! Dal 24 giugno 2022, il Ministero della Salute ha modificato il sistema di rilevazione dei dati sulla diffusione del Covid-19. I casi positivi non sono più indicati secondo la provincia di notifica bensì in base alla provincia di residenza o domicilio.

    ****** ATTENZIONE!! DA giugno 2023 avremo un solo aggiornamento settimanale.

  10. United States SB: IL: COVID-19 Impact: Moderate Positive Effect

    • ceicdata.com
    Updated Apr 23, 2022
    + more versions
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    CEICdata.com (2022). United States SB: IL: COVID-19 Impact: Moderate Positive Effect [Dataset]. https://www.ceicdata.com/en/united-states/small-business-pulse-survey-by-state-midwest-region/sb-il-covid19-impact-moderate-positive-effect
    Explore at:
    Dataset updated
    Apr 23, 2022
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 27, 2021 - Apr 11, 2022
    Area covered
    United States
    Description

    United States SB: IL: COVID-19 Impact: Moderate Positive Effect data was reported at 9.100 % in 11 Apr 2022. This records an increase from the previous number of 6.500 % for 04 Apr 2022. United States SB: IL: COVID-19 Impact: Moderate Positive Effect data is updated weekly, averaging 6.950 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 9.100 % in 11 Apr 2022 and a record low of 5.200 % in 03 Jan 2022. United States SB: IL: COVID-19 Impact: Moderate Positive Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S037: Small Business Pulse Survey: by State: Midwest Region: Weekly, Beg Monday (Discontinued).

  11. United States SB: IL: COVID-19 Impact: Large Positive Effect

    • ceicdata.com
    Updated Feb 15, 2025
    + more versions
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    CEICdata.com (2025). United States SB: IL: COVID-19 Impact: Large Positive Effect [Dataset]. https://www.ceicdata.com/en/united-states/small-business-pulse-survey-by-state-midwest-region/sb-il-covid19-impact-large-positive-effect
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    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 6, 2021 - Apr 11, 2022
    Area covered
    United States
    Description

    United States SB: IL: COVID-19 Impact: Large Positive Effect data was reported at 0.700 % in 11 Apr 2022. This records a decrease from the previous number of 1.000 % for 04 Apr 2022. United States SB: IL: COVID-19 Impact: Large Positive Effect data is updated weekly, averaging 1.500 % from Nov 2021 (Median) to 11 Apr 2022, with 14 observations. The data reached an all-time high of 2.400 % in 15 Nov 2021 and a record low of 0.600 % in 10 Jan 2022. United States SB: IL: COVID-19 Impact: Large Positive Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S037: Small Business Pulse Survey: by State: Midwest Region: Weekly, Beg Monday (Discontinued).

  12. C

    COVID-19 Vaccination Coverage, Region (HCEZ)

    • data.cityofchicago.org
    • catalog.data.gov
    Updated Jun 4, 2025
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    Department of Public Health (2025). COVID-19 Vaccination Coverage, Region (HCEZ) [Dataset]. https://data.cityofchicago.org/Health-Human-Services/COVID-19-Vaccination-Coverage-Region-HCEZ-/5sc6-ey97
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    application/rssxml, csv, tsv, application/rdfxml, application/geo+json, xml, kml, kmzAvailable download formats
    Dataset updated
    Jun 4, 2025
    Dataset authored and provided by
    Department of Public Health
    Description

    NOTE: This dataset replaces a previous one. Please see below.

    Chicago residents who are up to date with COVID-19 vaccines by Healthy Chicago Equity Zone (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

    “Up to date” refers to individuals who meet the CDC’s updated COVID-19 vaccination criteria based on their age and prior vaccination history. For surveillance purposes, up to date is defined based on the following criteria:

    People ages 5 years and older:
    ·Are up to date when they receive 1+ doses of a COVID-19 vaccine during the current season.

    Children ages 6 months to 4 years: · Children who have received at least two prior COVID-19 vaccine doses are up to date when they receive one additional dose of COVID-19 vaccine during the current season, regardless of vaccine product. · Children who have received only one prior COVID-19 vaccine dose are up to date when they receive one additional dose of the current season's Moderna COVID-19 vaccine or two additional doses of the current season's Pfizer-BioNTech COVID-19 vaccine. · Children who have never received a COVID-19 vaccination are up to date when they receive either two doses of the current season's Moderna vaccine or three doses of the current season's Pfizer-BioNTech vaccine.

    This dataset takes the place of a previous dataset, which cover doses administered from December 15, 2020 through September 13, 2023 and is marked as historical: - https://data.cityofchicago.org/Health-Human-Services/COVID-19-Vaccinations-by-Region-Age-and-Race-Ethni/n7f2-e2kq.

    Data notes:

    Weekly cumulative totals of people up to date 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" and race-ethnicity is “All Race/Ethnicity Groups” so care should be taken when summing rows.

    Coverage percentages are calculated based on the cumulative number of people in each population subgroup (age group by race-ethnicity within an HCEZ) who are up to date, divided by the estimated number of people in that subgroup. Population counts are from the 2020 U.S. Decennial Census. 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%. Summing all race/ethnicity group populations to obtain citywide populations may provide a population count that differs slightly from the citywide population count listed in the dataset. Differences in these estimates are due to how community area populations are calculated.

    Weekly cumulative counts and coverage percentages are reported from the week ending Saturday, September 16, 2023 onward through the Saturday prior to the dataset being updated.

    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.

    The Chicago Department of Public Health uses the most complete data available to estimate COVID-19 vaccination coverage among Chicagoans, but there are several limitations that impact our estimates. Individuals may receive vaccinations that are not recorded in the Illinois immunization registry, I-CARE, such as those administered in another state, causing underestimation of the number individuals who are up to date. Inconsistencies in records of separate doses administered to the same person, such as slight variations in dates of birth, can result in duplicate records for a person and underestimate the number of people who are up to date.

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

    Data Source: Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE), U.S. Census Bureau 2020 Decennial Census

  13. C

    COVID-19 Vaccinations by Age and Race-Ethnicity - Historical

    • data.cityofchicago.org
    • catalog.data.gov
    application/rdfxml +5
    Updated Dec 13, 2023
    + more versions
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    City of Chicago (2023). COVID-19 Vaccinations by Age and Race-Ethnicity - Historical [Dataset]. https://data.cityofchicago.org/Health-Human-Services/COVID-19-Vaccinations-by-Age-and-Race-Ethnicity-Hi/37ac-bbe3
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    tsv, csv, xml, json, application/rssxml, application/rdfxmlAvailable download formats
    Dataset updated
    Dec 13, 2023
    Dataset authored and provided by
    City of Chicago
    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-Citywide/6859-spec.

    COVID-19 vaccinations administered to Chicago residents based on the reported 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).

    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 an original booster dose: Number of people who have a completed vaccine series and have received at least one additional monovalent dose. This includes people who received a monovalent booster dose and immunocompromised people who received an additional primary dose of COVID-19 vaccine. Monovalent doses were created from the original strain of the virus that causes COVID-19.

    • 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. Note that each age group has a row where race-ethnicity 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) 2019 1-year estimates. For some of the age groups by which COVID-19 vaccine has been authorized in the United States, race-ethnicity distributions were specifically reported in the ACS estimates. For others, race-ethnicity distributions were estimated by the Chicago Department of Public Health (CDPH) by weighting the available race-ethnicity distributions, using proportions of constituent age groups.

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

    Actual counts may exceed population estimates and lead to >100% coverage, especially in small race-ethnicity subgroups of each age group. 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 our estimates. Data reported in I-CARE only include 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 underestimated. Inconsistencies in records of separate doses administered to the same person, such as slight variations in dates of birth, can result in duplicate first dose records for a person and overestimate of the number of people with at least one dose and underestimate the number of people with a completed series or booster dose

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

    Data Source: Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE), U.S. Census Bureau American Community Survey

  14. Data from: "IL-6 and cfDNA monitoring throughout COVID-19 hospitalization...

    • zenodo.org
    • data.niaid.nih.gov
    Updated Sep 21, 2022
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    Salvador Bello; Ana Belén Lasierra; Lucía López-Vergara; Cristina de Diego; Laura Torralba; Pablo Ruiz de Gopegui; Raquel Lahoz; Claudia Abadía; Javier Godino; Alberto Cebollada; Beatriz Jimeno; Carlota Bello; Antonio Tejada; Antoni Torres; Salvador Bello; Ana Belén Lasierra; Lucía López-Vergara; Cristina de Diego; Laura Torralba; Pablo Ruiz de Gopegui; Raquel Lahoz; Claudia Abadía; Javier Godino; Alberto Cebollada; Beatriz Jimeno; Carlota Bello; Antonio Tejada; Antoni Torres (2022). Data from: "IL-6 and cfDNA monitoring throughout COVID-19 hospitalization are accurate markers of its outcomes". [Dataset]. http://doi.org/10.5281/zenodo.7099678
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    Dataset updated
    Sep 21, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Salvador Bello; Ana Belén Lasierra; Lucía López-Vergara; Cristina de Diego; Laura Torralba; Pablo Ruiz de Gopegui; Raquel Lahoz; Claudia Abadía; Javier Godino; Alberto Cebollada; Beatriz Jimeno; Carlota Bello; Antonio Tejada; Antoni Torres; Salvador Bello; Ana Belén Lasierra; Lucía López-Vergara; Cristina de Diego; Laura Torralba; Pablo Ruiz de Gopegui; Raquel Lahoz; Claudia Abadía; Javier Godino; Alberto Cebollada; Beatriz Jimeno; Carlota Bello; Antonio Tejada; Antoni Torres
    Description

    Data supporting the manuscript title: IL-6 and cfDNA monitoring throughout COVID-19 hospitalization are accurate markers of its outcomes

  15. COVID-19 Data base.csv

    • figshare.com
    txt
    Updated Jul 27, 2021
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    Ryo Saji (2021). COVID-19 Data base.csv [Dataset]. http://doi.org/10.6084/m9.figshare.15059814.v1
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    txtAvailable download formats
    Dataset updated
    Jul 27, 2021
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Ryo Saji
    License

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

    Description

    Clinical data from 102 Japanese patients with COVID-19.

  16. Covid19-Israeli-Data

    • kaggle.com
    Updated Nov 3, 2021
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    Ron Bratslavsky (2021). Covid19-Israeli-Data [Dataset]. https://www.kaggle.com/ronbratslavsky/covid19israelidata/code
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 3, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Ron Bratslavsky
    Area covered
    Israel
    Description

    What's inside?

    This dataset contains data retrieved from Israeli Ministry of Health open database. The source data, as well as descriptions and disclaimers for each dataset can be found at https://data.gov.il/dataset/covid-19, although it's in Hebrew... So why not to use the source data itself? While this is not a problem if you want to conduct a "one off" analysis because all data is available for download in CSV format, or even EXCEL when possible, it is cumbersome when an update is needed. On the other hand getting the data via API calls is limited and takes long time.

    Acknowledgements

    Kudos to the Israeli Ministry of Health for providing this data. Disclaimers aside, it's not without risk for governmental authority to publish updated data which may have to be adjudicated at a later point in time.
    ISR MoH Covid19 Database ISR DataGov

  17. COVID-19 death rates in the United States as of March 10, 2023, by state

    • statista.com
    Updated May 15, 2024
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    Statista (2024). COVID-19 death rates in the United States as of March 10, 2023, by state [Dataset]. https://www.statista.com/statistics/1109011/coronavirus-covid19-death-rates-us-by-state/
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    Dataset updated
    May 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of March 10, 2023, the death rate from COVID-19 in the state of New York was 397 per 100,000 people. New York is one of the states with the highest number of COVID-19 cases.

  18. f

    Table_3_Prediabetes Induces More Severe Acute COVID-19 Associated With IL-6...

    • frontiersin.figshare.com
    docx
    Updated Jun 4, 2023
    + more versions
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    Icaro Bonyek-Silva; Thiago Cerqueira-Silva; Sara Nunes; Antônio Fernando Araújo Machado; Márcio Rivison Silva Cruz; Blenda Pereira; Leilane Estrela; Jéssica Silva; Ananda Isis; Aldina Barral; Pablo Rafael Silveira Oliveira; Ricardo Khouri; C. Henrique Serezani; Cláudia Brodskyn; Juliana Ribeiro Caldas; Manoel Barral-Netto; Viviane Boaventura; Natalia Machado Tavares (2023). Table_3_Prediabetes Induces More Severe Acute COVID-19 Associated With IL-6 Production Without Worsening Long-Term Symptoms.docx [Dataset]. http://doi.org/10.3389/fendo.2022.896378.s005
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    docxAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    Frontiers
    Authors
    Icaro Bonyek-Silva; Thiago Cerqueira-Silva; Sara Nunes; Antônio Fernando Araújo Machado; Márcio Rivison Silva Cruz; Blenda Pereira; Leilane Estrela; Jéssica Silva; Ananda Isis; Aldina Barral; Pablo Rafael Silveira Oliveira; Ricardo Khouri; C. Henrique Serezani; Cláudia Brodskyn; Juliana Ribeiro Caldas; Manoel Barral-Netto; Viviane Boaventura; Natalia Machado Tavares
    License

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

    Description

    AimsPre-existing conditions, such as age, hypertension, obesity, and diabetes, constitute known risk factors for severe COVID-19. However, the impact of prediabetes mellitus (PDM) on COVID-19 severity is less clear. This study aimed to evaluate the influence of PDM in the acute and long-term phases of COVID-19.Materials and methodsWe compared inflammatory mediators, laboratory and clinical parameters and symptoms in COVID-19 patients with prediabetes (PDM) and without diabetes (NDM) during the acute phase of infection and at three months post-hospitalization.ResultsPatients with PDM had longer hospital stays and required intensive care unit admission more frequently than NDM. Upon hospitalization, PDM patients exhibited higher serum levels of interleukin 6 (IL-6), which is related to reduced partial pressure of oxygen (PaO2) in arterial blood, oxygen saturation (SpO2) and increased COVID-19 severity. However, at three months after discharge, those with PDM did not exhibit significant alterations in laboratory parameters or residual symptoms; however, PDM was observed to influence the profile of reported symptoms.ConclusionsPDM seems to be associated with increased risk of severe COVID-19, as well as higher serum levels of IL-6, which may constitute a potential biomarker of severe COVID-19 risk in affected patients. Furthermore, while PDM correlated with more severe acute-phase COVID-19, no long-term worsening of sequelae was observed.

  19. Z

    Dataset: Interleukin (IL)-1 blocking agents for the treatment of COVID-19 A...

    • data.niaid.nih.gov
    • explore.openaire.eu
    Updated Jan 17, 2022
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    Hróbjartsson, Asbjørn (2022). Dataset: Interleukin (IL)-1 blocking agents for the treatment of COVID-19 A living systematic review [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_5853926
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    Dataset updated
    Jan 17, 2022
    Dataset provided by
    Tovey, David
    Meerpohl, Joerg J
    Ravaud, Philippe
    Evrenoglou, Theodoros
    Boutron, Isabelle
    Davidson, Mauricia
    Cogo, Elise
    Chaimani, Anna
    Hróbjartsson, Asbjørn
    Villanueva, Gemma
    Kapp, Philipp
    Rada, Gabriel
    Grasselli, Giacomo
    Devane, Declan
    Henschke, Nicholas
    Graña, Carolina
    Moran, Conor
    Menon, Sonia
    Bonnet, Hillary
    Ferrand, Gabriel
    Ghosn, Lina
    Riveros, Carolina
    License

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

    Description

    This dataset is used in the analyses reported in the review entitled "Interleukin (IL)-1 blocking agents for the treatment of COVID-19 A living systematic review"

    IL-1 blockers are beneficial in inflammation-associated pathologies, such as rheumatoid arthritis (Mertens 2009) and possibly also in the subgroup of patients with severe sepsis where the inflammasome pathway is involved (Shakoory 2016). Similar benefits were reported in children with secondary macrophage activation syndrome, including cases triggered by viral infections (Mehta 2020b).

    In this review we aimed to assess the effectiveness of IL-1 blocking agents compared to placebo, standard of care or no treatment on outcomes in patients with COVID-19.

    This review is part of a larger project: the COVID-NMA project. We set-up a platform (https://covid-nma.com) where all our results are made available and updated bi-weekly.

  20. Data from: A Complement Atlas identifies interleukin 6 dependent alternative...

    • zenodo.org
    • data.niaid.nih.gov
    csv, txt
    Updated Aug 8, 2023
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    Karel F.A. Van Damme; Karel F.A. Van Damme; Levi Hoste; Levi Hoste; Jozefien Declercq; Jozefien Declercq; Elisabeth De Leeuw; Elisabeth De Leeuw; Bastiaan Maes; Bastiaan Maes; Liesbet Martens; Liesbet Martens; Roos Colman; Roos Colman; Robin Browaeys; Robin Browaeys; Cédric Bosteels; Cédric Bosteels; Stijn Verwaerde; Stijn Verwaerde; Nicky Vermeulen; Nicky Vermeulen; Sahine Lameire; Sahine Lameire; Nincy Debeuf; Nincy Debeuf; Julie Deckers; Julie Deckers; Patrick Stordeur; Patrick Stordeur; Pieter Depuydt; Pieter Depuydt; Eva Van Braeckel; Eva Van Braeckel; Linos Vandekerckhove; Linos Vandekerckhove; Martin Guilliams; Martin Guilliams; Sjoerd T.T. Schetters; Sjoerd T.T. Schetters; Filomeen Haerynck; Filomeen Haerynck; Simon J. Tavernier; Simon J. Tavernier; Bart N. Lambrecht; Bart N. Lambrecht (2023). A Complement Atlas identifies interleukin 6 dependent alternative pathway dysregulation as a key druggable feature of COVID-19. [Dataset]. http://doi.org/10.5281/zenodo.8192092
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    csv, txtAvailable download formats
    Dataset updated
    Aug 8, 2023
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Karel F.A. Van Damme; Karel F.A. Van Damme; Levi Hoste; Levi Hoste; Jozefien Declercq; Jozefien Declercq; Elisabeth De Leeuw; Elisabeth De Leeuw; Bastiaan Maes; Bastiaan Maes; Liesbet Martens; Liesbet Martens; Roos Colman; Roos Colman; Robin Browaeys; Robin Browaeys; Cédric Bosteels; Cédric Bosteels; Stijn Verwaerde; Stijn Verwaerde; Nicky Vermeulen; Nicky Vermeulen; Sahine Lameire; Sahine Lameire; Nincy Debeuf; Nincy Debeuf; Julie Deckers; Julie Deckers; Patrick Stordeur; Patrick Stordeur; Pieter Depuydt; Pieter Depuydt; Eva Van Braeckel; Eva Van Braeckel; Linos Vandekerckhove; Linos Vandekerckhove; Martin Guilliams; Martin Guilliams; Sjoerd T.T. Schetters; Sjoerd T.T. Schetters; Filomeen Haerynck; Filomeen Haerynck; Simon J. Tavernier; Simon J. Tavernier; Bart N. Lambrecht; Bart N. Lambrecht
    License

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

    Description

    Improvements in COVID-19 treatments, especially for the critically ill, require deeper understanding of the mechanisms driving disease pathology. The complement system is a crucial component of innate host defense, but can also contribute to tissue injury. Although all complement pathways have been implicated in COVID-19 pathogenesis, the upstream drivers and downstream effects on tissue injury remain poorly defined. We demonstrate that complement activation is primarily mediated by the alternative pathway, and we provide a comprehensive atlas of the complement alterations around the time of respiratory deterioration. Proteomic and single-cell sequencing mapping across cell types and tissues reveals a division of labor between lung epithelial, stromal, and myeloid cells in complement production, in addition to liver-derived factors. We identify IL-6 and STAT1/3 signaling as an upstream driver of complement responses, linking complement dysregulation to approved COVID-19 therapies. Furthermore, an exploratory proteomic study indicates that inhibition of complement C5 decreases epithelial damage and markers of disease severity. Collectively, these results support complement dysregulation as a key druggable feature of COVID-19.

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COVID-19 Cases, Tests, and Deaths by ZIP Code - Historical [Dataset]. https://catalog.data.gov/dataset/covid-19-cases-tests-and-deaths-by-zip-code

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

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Dataset updated
May 24, 2024
Dataset provided by
data.cityofchicago.org
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. 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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