100+ datasets found
  1. Rate of COVID-19 hospitalizations in the U.S. as of September 26, 2020, by...

    • statista.com
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    Statista, Rate of COVID-19 hospitalizations in the U.S. as of September 26, 2020, by age group [Dataset]. https://www.statista.com/statistics/1122354/covid-19-us-hospital-rate-by-age/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 1, 2020 - Sep 26, 2020
    Area covered
    United States
    Description

    As of September 26, the hospitalization rate in the United States due to COVID-19 was highest for those aged 85 years and older. This statistic shows the cumulative rate of laboratory-confirmed COVID-19-associated hospitalizations in the U.S. as of September 26, 2020, by age group.

  2. Share of U.S. COVID-19 cases resulting in hospitalization from...

    • statista.com
    Updated Jul 27, 2022
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    Statista (2022). Share of U.S. COVID-19 cases resulting in hospitalization from Feb.12-Mar.16, by age [Dataset]. https://www.statista.com/statistics/1105402/covid-hospitalization-rates-us-by-age-group/
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    Dataset updated
    Jul 27, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 12, 2020 - Mar 16, 2020
    Area covered
    United States
    Description

    In the United States between February 12 and March 16, 2020, the percentage of COVID-19 patients hospitalized with the disease increased with age. Findings estimated that up to 70 percent of adults aged 85 years and older were hospitalized.

    Who is at higher risk from COVID-19? The same study also found that coronavirus patients aged 85 and older were at the highest risk of death. There are other risk factors besides age that can lead to serious illness. People with pre-existing medical conditions, such as diabetes, heart disease, and lung disease, can develop more severe symptoms. In the U.S. between January and May 2020, case fatality rates among confirmed COVID-19 patients were higher for those with underlying health conditions.

    How long should you self-isolate? As of August 24, 2020, more than 16 million people worldwide had recovered from COVID-19 disease, which includes patients in health care settings and those isolating at home. The criteria for discharging patients from isolation varies by country, but asymptomatic carriers of the virus can generally be released ten days after their positive case was confirmed. For patients showing signs of the illness, they must isolate for at least ten days after symptom onset and also remain in isolation for a short period after the symptoms have disappeared.

  3. Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status and...

    • data.cdc.gov
    • healthdata.gov
    • +1more
    csv, xlsx, xml
    Updated Feb 22, 2023
    + more versions
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    CDC COVID-19 Response, Epidemiology Task Force (2023). Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status and Second Booster Dose [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/ukww-au2k
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    xlsx, xml, csvAvailable download formats
    Dataset updated
    Feb 22, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    CDC COVID-19 Response, Epidemiology Task Force
    Description

    Data for CDC’s COVID Data Tracker site on Rates of COVID-19 Cases and Deaths by Vaccination Status. Click 'More' for important dataset description and footnotes

    Dataset and data visualization details: These data were posted on October 21, 2022, archived on November 18, 2022, and revised on February 22, 2023. These data reflect cases among persons with a positive specimen collection date through September 24, 2022, and deaths among persons with a positive specimen collection date through September 3, 2022.

    Vaccination status: A person vaccinated with a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. Additional or booster dose: A person vaccinated with a primary series and an additional or booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after receipt of an additional or booster dose of any COVID-19 vaccine on or after August 13, 2021. For people ages 18 years and older, data are graphed starting the week including September 24, 2021, when a COVID-19 booster dose was first recommended by CDC for adults 65+ years old and people in certain populations and high risk occupational and institutional settings. For people ages 12-17 years, data are graphed starting the week of December 26, 2021, 2 weeks after the first recommendation for a booster dose for adolescents ages 16-17 years. For people ages 5-11 years, data are included starting the week of June 5, 2022, 2 weeks after the first recommendation for a booster dose for children aged 5-11 years. For people ages 50 years and older, data on second booster doses are graphed starting the week including March 29, 2022, when the recommendation was made for second boosters. Vertical lines represent dates when changes occurred in U.S. policy for COVID-19 vaccination (details provided above). Reporting is by primary series vaccine type rather than additional or booster dose vaccine type. The booster dose vaccine type may be different than the primary series vaccine type. ** Because data on the immune status of cases and associated deaths are unavailable, an additional dose in an immunocompromised person cannot be distinguished from a booster dose. This is a relevant consideration because vaccines can be less effective in this group. Deaths: A COVID-19–associated death occurred in a person with a documented COVID-19 diagnosis who died; health department staff reviewed to make a determination using vital records, public health investigation, or other data sources. Rates of COVID-19 deaths by vaccination status are reported based on when the patient was tested for COVID-19, not the date they died. Deaths usually occur up to 30 days after COVID-19 diagnosis. Participating jurisdictions: Currently, these 31 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Arkansas, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (New York), North Carolina, Philadelphia (Pennsylvania), Rhode Island, South Dakota, Tennessee, Texas, Utah, Washington, and West Virginia; 30 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 72% of the total U.S. population and all ten of the Health and Human Services Regions. Data on cases among people who received additional or booster doses were reported from 31 jurisdictions; 30 jurisdictions also reported data on deaths among people who received one or more additional or booster dose; 28 jurisdictions reported cases among people who received two or more additional or booster doses; and 26 jurisdictions reported deaths among people who received two or more additional or booster doses. This list will be updated as more jurisdictions participate. Incidence rate estimates: Weekly age-specific incidence rates by vaccination status were calculated as the number of cases or deaths divided by the number of people vaccinated with a primary series, overall or with/without a booster dose (cumulative) or unvaccinated (obtained by subtracting the cumulative number of people vaccinated with a primary series and partially vaccinated people from the 2019 U.S. intercensal population estimates) and multiplied by 100,000. Overall incidence rates were age-standardized using the 2000 U.S. Census standard population. To estimate population counts for ages 6 months through 1 year, half of the single-year population counts for ages 0 through 1 year were used. All rates are plotted by positive specimen collection date to reflect when incident infections occurred. For the primary series analysis, age-standardized rates include ages 12 years and older from April 4, 2021 through December 4, 2021, ages 5 years and older from December 5, 2021 through July 30, 2022 and ages 6 months and older from July 31, 2022 onwards. For the booster dose analysis, age-standardized rates include ages 18 years and older from September 19, 2021 through December 25, 2021, ages 12 years and older from December 26, 2021, and ages 5 years and older from June 5, 2022 onwards. Small numbers could contribute to less precision when calculating death rates among some groups. Continuity correction: A continuity correction has been applied to the denominators by capping the percent population coverage at 95%. To do this, we assumed that at least 5% of each age group would always be unvaccinated in each jurisdiction. Adding this correction ensures that there is always a reasonable denominator for the unvaccinated population that would prevent incidence and death rates from growing unrealistically large due to potential overestimates of vaccination coverage. Incidence rate ratios (IRRs): IRRs for the past one month were calculated by dividing the average weekly incidence rates among unvaccinated people by that among people vaccinated with a primary series either overall or with a booster dose. Publications: Scobie HM, Johnson AG, Suthar AB, et al. Monitoring Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Status — 13 U.S. Jurisdictions, April 4–July 17, 2021. MMWR Morb Mortal Wkly Rep 2021;70:1284–1290. Johnson AG, Amin AB, Ali AR, et al. COVID-19 Incidence and Death Rates Among Unvaccinated and Fully Vaccinated Adults with and Without Booster Doses During Periods of Delta and Omicron Variant Emergence — 25 U.S. Jurisdictions, April 4–December 25, 2021. MMWR Morb Mortal Wkly Rep 2022;71:132–138

  4. COVID-19 hospitalization rates in the U.S. from March 1 to 28, 2020, by age...

    • statista.com
    Updated Apr 20, 2020
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    Statista (2020). COVID-19 hospitalization rates in the U.S. from March 1 to 28, 2020, by age group [Dataset]. https://www.statista.com/statistics/1111368/covid-hospitalization-rates-age-us/
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    Dataset updated
    Apr 20, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 1, 2020 - Mar 28, 2020
    Area covered
    United States
    Description

    The COVID-19–associated hospitalization rate among patients aged 85 years and older identified through COVID-NET for the 4-week period ending March 28, 2020, was 17.2 per 100,000 population. This statistic shows laboratory-confirmed COVID-19 associated hospitalization rates per 100,000 population from March 1 to 28, in the 14 U.S. states under surveillance by COVID-NET.

  5. Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status

    • data.cdc.gov
    • data.virginia.gov
    • +2more
    csv, xlsx, xml
    Updated Feb 22, 2023
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    CDC COVID-19 Response, Epidemiology Task Force (2023). Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/3rge-nu2a
    Explore at:
    xlsx, xml, csvAvailable download formats
    Dataset updated
    Feb 22, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    CDC COVID-19 Response, Epidemiology Task Force
    Description

    Data for CDC’s COVID Data Tracker site on Rates of COVID-19 Cases and Deaths by Vaccination Status. Click 'More' for important dataset description and footnotes

    Dataset and data visualization details: These data were posted on October 21, 2022, archived on November 18, 2022, and revised on February 22, 2023. These data reflect cases among persons with a positive specimen collection date through September 24, 2022, and deaths among persons with a positive specimen collection date through September 3, 2022.

    Vaccination status: A person vaccinated with a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. Additional or booster dose: A person vaccinated with a primary series and an additional or booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after receipt of an additional or booster dose of any COVID-19 vaccine on or after August 13, 2021. For people ages 18 years and older, data are graphed starting the week including September 24, 2021, when a COVID-19 booster dose was first recommended by CDC for adults 65+ years old and people in certain populations and high risk occupational and institutional settings. For people ages 12-17 years, data are graphed starting the week of December 26, 2021, 2 weeks after the first recommendation for a booster dose for adolescents ages 16-17 years. For people ages 5-11 years, data are included starting the week of June 5, 2022, 2 weeks after the first recommendation for a booster dose for children aged 5-11 years. For people ages 50 years and older, data on second booster doses are graphed starting the week including March 29, 2022, when the recommendation was made for second boosters. Vertical lines represent dates when changes occurred in U.S. policy for COVID-19 vaccination (details provided above). Reporting is by primary series vaccine type rather than additional or booster dose vaccine type. The booster dose vaccine type may be different than the primary series vaccine type. ** Because data on the immune status of cases and associated deaths are unavailable, an additional dose in an immunocompromised person cannot be distinguished from a booster dose. This is a relevant consideration because vaccines can be less effective in this group. Deaths: A COVID-19–associated death occurred in a person with a documented COVID-19 diagnosis who died; health department staff reviewed to make a determination using vital records, public health investigation, or other data sources. Rates of COVID-19 deaths by vaccination status are reported based on when the patient was tested for COVID-19, not the date they died. Deaths usually occur up to 30 days after COVID-19 diagnosis. Participating jurisdictions: Currently, these 31 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Arkansas, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (New York), North Carolina, Philadelphia (Pennsylvania), Rhode Island, South Dakota, Tennessee, Texas, Utah, Washington, and West Virginia; 30 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 72% of the total U.S. population and all ten of the Health and Human Services Regions. Data on cases among people who received additional or booster doses were reported from 31 jurisdictions; 30 jurisdictions also reported data on deaths among people who received one or more additional or booster dose; 28 jurisdictions reported cases among people who received two or more additional or booster doses; and 26 jurisdictions reported deaths among people who received two or more additional or booster doses. This list will be updated as more jurisdictions participate. Incidence rate estimates: Weekly age-specific incidence rates by vaccination status were calculated as the number of cases or deaths divided by the number of people vaccinated with a primary series, overall or with/without a booster dose (cumulative) or unvaccinated (obtained by subtracting the cumulative number of people vaccinated with a primary series and partially vaccinated people from the 2019 U.S. intercensal population estimates) and multiplied by 100,000. Overall incidence rates were age-standardized using the 2000 U.S. Census standard population. To estimate population counts for ages 6 months through 1 year, half of the single-year population counts for ages 0 through 1 year were used. All rates are plotted by positive specimen collection date to reflect when incident infections occurred. For the primary series analysis, age-standardized rates include ages 12 years and older from April 4, 2021 through December 4, 2021, ages 5 years and older from December 5, 2021 through July 30, 2022 and ages 6 months and older from July 31, 2022 onwards. For the booster dose analysis, age-standardized rates include ages 18 years and older from September 19, 2021 through December 25, 2021, ages 12 years and older from December 26, 2021, and ages 5 years and older from June 5, 2022 onwards. Small numbers could contribute to less precision when calculating death rates among some groups. Continuity correction: A continuity correction has been applied to the denominators by capping the percent population coverage at 95%. To do this, we assumed that at least 5% of each age group would always be unvaccinated in each jurisdiction. Adding this correction ensures that there is always a reasonable denominator for the unvaccinated population that would prevent incidence and death rates from growing unrealistically large due to potential overestimates of vaccination coverage. Incidence rate ratios (IRRs): IRRs for the past one month were calculated by dividing the average weekly incidence rates among unvaccinated people by that among people vaccinated with a primary series either overall or with a booster dose. Publications: Scobie HM, Johnson AG, Suthar AB, et al. Monitoring Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Status — 13 U.S. Jurisdictions, April 4–July 17, 2021. MMWR Morb Mortal Wkly Rep 2021;70:1284–1290. Johnson AG, Amin AB, Ali AR, et al. COVID-19 Incidence and Death Rates Among Unvaccinated and Fully Vaccinated Adults with and Without Booster Doses During Periods of Delta and Omicron Variant Emergence — 25 U.S. Jurisdictions, April 4–December 25, 2021. MMWR Morb Mortal Wkly Rep 2022;71:132–138. Johnson AG, Linde L, Ali AR, et al. COVID-19 Incidence and Mortality Among Unvaccinated and Vaccinated Persons Aged ≥12 Years by Receipt of Bivalent Booster Doses and Time Since Vaccination — 24 U.S. Jurisdictions, October 3, 2021–December 24, 2022. MMWR Morb Mortal Wkly Rep 2023;72:145–152. Johnson AG, Linde L, Payne AB, et al. Notes from the Field: Comparison of COVID-19 Mortality Rates Among Adults Aged ≥65 Years Who Were Unvaccinated and Those Who Received a Bivalent Booster Dose Within the Preceding 6 Months — 20 U.S. Jurisdictions, September 18, 2022–April 1, 2023. MMWR Morb Mortal Wkly Rep 2023;72:667–669.

  6. Hospitalizations due to the coronavirus (COVID-19) in Switzerland in 2023,...

    • statista.com
    Updated Jan 13, 2025
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    Statista (2025). Hospitalizations due to the coronavirus (COVID-19) in Switzerland in 2023, by age [Dataset]. https://www.statista.com/statistics/1110045/coronavirus-covid-19-hospitalizations-number-age-group-switzerland/
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    Dataset updated
    Jan 13, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2023
    Area covered
    Switzerland
    Description

    Switzerland is battling the coronavirus (COVID-19) outbreak. As of January 2023, patients aged 80 years and older have been hospitalized most often due to being infected with the virus, followed by the 70-79 age group.

  7. Rates of COVID-19 Cases or Deaths by Age Group and Updated (Bivalent)...

    • data.cdc.gov
    • healthdata.gov
    • +1more
    csv, xlsx, xml
    Updated May 30, 2023
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    CDC COVID-19 Response, Epidemiology Task Force (2023). Rates of COVID-19 Cases or Deaths by Age Group and Updated (Bivalent) Booster Status [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/54ys-qyzm
    Explore at:
    xlsx, csv, xmlAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    CDC COVID-19 Response, Epidemiology Task Force
    Description

    Data for CDC’s COVID Data Tracker site on Rates of COVID-19 Cases and Deaths by Updated (Bivalent) Booster Status. Click 'More' for important dataset description and footnotes

    Webpage: https://covid.cdc.gov/covid-data-tracker/#rates-by-vaccine-status

    Dataset and data visualization details:

    These data were posted and archived on May 30, 2023 and reflect cases among persons with a positive specimen collection date through April 22, 2023, and deaths among persons with a positive specimen collection date through April 1, 2023. These data will no longer be updated after May 2023.

    Vaccination status: A person vaccinated with at least a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. A person vaccinated with a primary series and a monovalent booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably receiving a primary series of an FDA-authorized or approved vaccine and at least one additional dose of any monovalent FDA-authorized or approved COVID-19 vaccine on or after August 13, 2021. (Note: this definition does not distinguish between vaccine recipients who are immunocompromised and are receiving an additional dose versus those who are not immunocompromised and receiving a booster dose.) A person vaccinated with a primary series and an updated (bivalent) booster dose had SARS-CoV-2 RNA or antigen detected in a respiratory specimen collected ≥14 days after verifiably receiving a primary series of an FDA-authorized or approved vaccine and an additional dose of any bivalent FDA-authorized or approved vaccine COVID-19 vaccine on or after September 1, 2022. (Note: Doses with bivalent doses reported as first or second doses are classified as vaccinated with a bivalent booster dose.) People with primary series or a monovalent booster dose were combined in the “vaccinated without an updated booster” category.

    Deaths: A COVID-19–associated death occurred in a person with a documented COVID-19 diagnosis who died; health department staff reviewed to make a determination using vital records, public health investigation, or other data sources. Per the interim guidance of the Council of State and Territorial Epidemiologists (CSTE), this should include persons whose death certificate lists COVID-19 disease or SARS-CoV-2 as the underlying cause of death or as a significant condition contributing to death. Rates of COVID-19 deaths by vaccination status are primarily reported based on when the patient was tested for COVID-19. In select jurisdictions, deaths are included that are not laboratory confirmed and are reported based on alternative dates (i.e., onset date for most; or date of death or report date, where onset date is unavailable). Deaths usually occur up to 30 days after COVID-19 diagnosis.

    Participating jurisdictions: Currently, these 24 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Colorado, District of Columbia, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (NY), North Carolina, Rhode Island, Tennessee, Texas, Utah, and West Virginia; 23 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 48% of the total U.S. population and all ten of the Health and Human Services Regions. This list will be updated as more jurisdictions participate.

    Incidence rate estimates: Weekly age-specific incidence rates by vaccination status were calculated as the number of cases or deaths divided by the number of people vaccinated with a primary series, overall or with/without a booster dose (cumulative) or unvaccinated (obtained by subtracting the cumulative number of people vaccinated with at least a primary series and partially vaccinated people from the 2019 U.S. intercensal population estimates) and multiplied by 100,000. Overall incidence rates were age-standardized using the 2000 U.S. Census standard population. To estimate population counts for ages 6-12 months, half of the single-year population counts for ages <12 months were used. All rates are plotted by positive specimen collection date to reflect when incident infections occurred.

    Continuity correction: A continuity correction has been applied to the denominators by capping the percent population coverage at 95%. To do this, we assumed that at least 5% of each age group would always be unvaccinated in each jurisdiction. Adding this correction ensures that there is always a reasonable denominator for the unvaccinated population that would prevent incidence and death rates from growing unrealistically large due to potential overestimates of vaccination coverage.

    Incidence rate ratios (IRRs): IRRs for the past one month were calculated by dividing the average weekly incidence rates among unvaccinated people by that among people vaccinated without an updated (bivalent) booster dose) or vaccinated with an updated (bivalent) booster dose.

    Archive: An archive of historic data, including April 3, 2021-September 24, 2022 and posted on October 21, 2022 is available on data.cdc.gov. The analysis by vaccination status (unvaccinated and at least a primary series) for 31 jurisdictions is posted here: https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/3rge-nu2a. The analysis for one booster dose (unvaccinated, primary series only, and at least one booster dose) in 31 jurisdictions is posted here: https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/d6p8-wqjm. The analysis for two booster doses (unvaccinated, primary series only, one booster dose, and at least two booster doses) in 28 jurisdictions is posted here: https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/ukww-au2k.

    References

    Scobie HM, Johnson AG, Suthar AB, et al. Monitoring Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Status — 13 U.S. Jurisdictions, April 4–July 17, 2021. MMWR Morb Mortal Wkly Rep 2021;70:1284–1290.

    Johnson AG, Amin AB, Ali AR, et al. COVID-19 Incidence and Death Rates Among Unvaccinated and Fully Vaccinated Adults with and Without Booster Doses During Periods of Delta and Omicron Variant Emergence — 25 U.S. Jurisdictions, April 4–December 25, 2021. MMWR Morb Mortal Wkly Rep 2022;71:132–138

    Johnson AG, Linde L, Ali AR, et al. COVID-19 Incidence and Mortality Among Unvaccinated and Vaccinated Persons Aged ≥12 Years by Receipt of Bivalent Booster Doses and Time Since Vaccination — 24 U.S. Jurisdictions, October 3, 2021–December 24, 2022. MMWR Morb Mortal Wkly Rep 2023;72:145–152

  8. Case-fatality rates and characteristics of countrywide population...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 13, 2023
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    Marc Souris; Jean-Paul Gonzalez (2023). Case-fatality rates and characteristics of countrywide population vulnerability to COVID-19. [Dataset]. http://doi.org/10.1371/journal.pone.0243606.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Marc Souris; Jean-Paul Gonzalez
    License

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

    Description

    Case-fatality rates and characteristics of countrywide population vulnerability to COVID-19.

  9. Coronavirus hospitalization rate in the Netherlands as of September 2020, by...

    • statista.com
    Updated Nov 30, 2023
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    Statista (2023). Coronavirus hospitalization rate in the Netherlands as of September 2020, by age [Dataset]. https://www.statista.com/statistics/1129037/coronavirus-hospitalization-by-age-in-netherlands/
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    Dataset updated
    Nov 30, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 27, 2020 - Sep 29, 2020
    Area covered
    Netherlands
    Description

    As of September 29, 2020, the coronavirus (COVID-19) pandemic in the Netherlands resulted in over 12.7 thousand hospitalizations. However, the distribution of hospital admissions differed greatly by age. To this day, most hospitalizations occurred with older patients. In the Netherlands, roughly 70 percent of hospitalized patients were notably aged 60 years old and over. Children have also been admitted to Dutch hospitals due to the coronavirus, although to a much lesser extent.

  10. M

    Rates of COVID-19 - Associated Hospitalizations

    • catalog.midasnetwork.us
    csv
    Updated Sep 1, 2025
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    Centers for Disease Control and Prevention (CDC) (2025). Rates of COVID-19 - Associated Hospitalizations [Dataset]. https://catalog.midasnetwork.us/collection/162
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    csvAvailable download formats
    Dataset updated
    Sep 1, 2025
    Dataset provided by
    MIDAS COORDINATION CENTER
    Authors
    Centers for Disease Control and Prevention (CDC)
    License

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

    Area covered
    State, Country
    Variables measured
    Viruses, disease, COVID-19, pathogen, Homo sapiens, host organism, age-stratified, Population count, infectious disease, hospital stay dataset, and 5 more
    Dataset funded by
    National Institute of General Medical Sciences
    Description

    Data gathered by the Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET) are used to estimate age-specific hospitalization rates per 100,000 population of laboratory confirmed COVID-19 hospitalizations on a weekly basis and describe characteristics of persons hospitalized with COVID-19. Laboratory confirmation is dependent on clinician-ordered SARS-CoV-2 testing.

  11. I

    Data from: Reduced COVID-19 hospitalizations among New York City residents...

    • data.niaid.nih.gov
    url
    Updated Jul 25, 2024
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    (2024). Reduced COVID-19 hospitalizations among New York City residents following age-based SARS-CoV-2 vaccine eligibility: Evidence from a regression discontinuity design [Dataset]. http://doi.org/10.21430/M3MORBFJTU
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    urlAvailable download formats
    Dataset updated
    Jul 25, 2024
    License

    https://www.immport.org/agreementhttps://www.immport.org/agreement

    Area covered
    New York
    Description

    Background: In clinical trials, several SARS-CoV-2 vaccines were shown to reduce risk of severe COVID-19 illness. Local, population-level, real-world evidence of vaccine effectiveness is accumulating. We assessed vaccine effectiveness for community-dwelling New York City (NYC) residents using a quasi-experimental, regression discontinuity design, leveraging a period (January 12-March 9, 2021) when ≥ 65-year-olds were vaccine-eligible but younger persons, excluding essential workers, were not. Methods: We constructed segmented, negative binomial regression models of age-specific COVID-19 hospitalization rates among 45-84-year-old NYC residents during a post-vaccination program implementation period (February 21-April 17, 2021), with a discontinuity at age 65 years. The relationship between age and hospitalization rates in an unvaccinated population was incorporated using a pre-implementation period (December 20, 2020-February 13, 2021). We calculated the rate ratio (RR) and 95% confidence interval (CI) for the interaction between implementation period (pre or post) and age-based eligibility (45-64 or 65-84 years). Analyses were stratified by race/ethnicity and borough of residence. Similar analyses were conducted for COVID-19 deaths. Results: Hospitalization rates among 65-84-year-olds decreased from pre- to post-implementation periods (RR 0.85, 95% CI: 0.74-0.97), controlling for trends among 45-64-year-olds. Accordingly, an estimated 721 (95% CI: 126-1,241) hospitalizations were averted. Residents just above the eligibility threshold (65-66-year-olds) had lower hospitalization rates than those below (63-64-year-olds). Racial/ethnic groups and boroughs with higher vaccine coverage generally experienced greater reductions in RR point estimates. Uncertainty was greater for the decrease in COVID-19 death rates (RR 0.85, 95% CI: 0.66-1.10). Conclusion: The vaccination program in NYC reduced COVID-19 hospitalizations among the initially age-eligible ≥ 65-year-old population by approximately 15% in the first eight weeks. The real-world evidence of vaccine effectiveness makes it more imperative to improve vaccine access and uptake to reduce inequities in COVID-19 outcomes.

  12. Percentage of agents hospitalized with COVID-19 by subgroup in NC synthetic...

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Emily Hadley; Sarah Rhea; Kasey Jones; Lei Li; Marie Stoner; Georgiy Bobashev (2023). Percentage of agents hospitalized with COVID-19 by subgroup in NC synthetic population when an overall hospitalization rate (single point estimate) or age group and comorbidity-specific hospitalization rates (Bayesian method) were used. [Dataset]. http://doi.org/10.1371/journal.pone.0264704.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Emily Hadley; Sarah Rhea; Kasey Jones; Lei Li; Marie Stoner; Georgiy Bobashev
    License

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

    Area covered
    North Carolina
    Description

    Percentage of agents hospitalized with COVID-19 by subgroup in NC synthetic population when an overall hospitalization rate (single point estimate) or age group and comorbidity-specific hospitalization rates (Bayesian method) were used.

  13. COVID-NET Hospitalization Rates

    • kaggle.com
    zip
    Updated Apr 10, 2020
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    Karl Weinmeister (2020). COVID-NET Hospitalization Rates [Dataset]. https://www.kaggle.com/kweinmeister/covidnet-hospitalization-rates
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    zip(12845 bytes)Available download formats
    Dataset updated
    Apr 10, 2020
    Authors
    Karl Weinmeister
    License

    https://www.usa.gov/government-works/https://www.usa.gov/government-works/

    Description

    Content

    The Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET) data are preliminary and subject to change as more data become available. COVID-NET conducts population-based surveillance for laboratory-confirmed COVID-19-associated hospitalizations in children (less than 18 years of age) and adults.

    COVID-NET covers nearly 100 counties in the 10 Emerging Infections Program (EIP) states (CA, CO, CT, GA, MD, MN, NM, NY, OR, TN) and four Influenza Hospitalization Surveillance Project (IHSP) states (IA, MI, OH, and UT).

    Incidence rates (per 100,000 population) are calculated using the National Center for Health Statistics' (NCHS) vintage 2018 bridged-race postcensal population estimates for the counties included in the surveillance catchment area. The rates provided are likely to be underestimated as COVID-19 hospitalizations might be missed due to test availability and provider or facility testing practices.

    Acknowledgements

    COVID-NET: COVID-19-Associated Hospitalization Surveillance Network, Centers for Disease Control and Prevention. WEBSITE. Accessed on 04/09/2020.

  14. f

    Hospital bed number per 100,000 people, per regions in France.

    • plos.figshare.com
    xls
    Updated Jun 13, 2023
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    Marc Souris; Jean-Paul Gonzalez (2023). Hospital bed number per 100,000 people, per regions in France. [Dataset]. http://doi.org/10.1371/journal.pone.0243606.t003
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    xlsAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Marc Souris; Jean-Paul Gonzalez
    License

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

    Area covered
    France
    Description

    Hospital bed number per 100,000 people, per regions in France.

  15. f

    COVID-19 dataset.

    • plos.figshare.com
    • figshare.com
    xlsx
    Updated May 31, 2023
    + more versions
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    Sinan Trabulus; Cebrail Karaca; Ilker Inanc Balkan; Mevlut Tamer Dincer; Ahmet Murt; Seyda Gul Ozcan; Rıdvan Karaali; Bilgul Mete; Alev Bakir; Mert Ahmet Kuskucu; Mehmet Riza Altiparmak; Fehmi Tabak; Nurhan Seyahi (2023). COVID-19 dataset. [Dataset]. http://doi.org/10.1371/journal.pone.0238680.s001
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    xlsxAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Sinan Trabulus; Cebrail Karaca; Ilker Inanc Balkan; Mevlut Tamer Dincer; Ahmet Murt; Seyda Gul Ozcan; Rıdvan Karaali; Bilgul Mete; Alev Bakir; Mert Ahmet Kuskucu; Mehmet Riza Altiparmak; Fehmi Tabak; Nurhan Seyahi
    License

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

    Description

    File containing dataset used for the main analysis. (XLSX)

  16. d

    MD COVID-19 - Confirmed Deaths by Age Distribution

    • catalog.data.gov
    • opendata.maryland.gov
    • +3more
    Updated Sep 20, 2025
    + more versions
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    opendata.maryland.gov (2025). MD COVID-19 - Confirmed Deaths by Age Distribution [Dataset]. https://catalog.data.gov/dataset/md-covid-19-confirmed-deaths-by-age-distribution
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    Dataset updated
    Sep 20, 2025
    Dataset provided by
    opendata.maryland.gov
    Area covered
    Maryland
    Description

    Note: Starting April 27, 2023 updates change from daily to weekly. Summary The cumulative number of confirmed COVID-19 deaths among Maryland residents by age: 0-9; 10-19; 20-29; 30-39; 40-49; 50-59; 60-69; 70-79; 80+; Unknown. Description The MD COVID-19 - Confirmed Deaths by Age Distribution data layer is a collection of the statewide confirmed COVID-19 related deaths that have been reported each day by the Vital Statistics Administration by designated age ranges. A death is classified as confirmed if the person had a laboratory-confirmed positive COVID-19 test result. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Probable deaths are available from the MD COVID-19 - Probable Deaths by Age Distribution data layer. Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

  17. f

    Data_Sheet_1_How to Reduce the Transmission Risk of COVID-19 More...

    • frontiersin.figshare.com
    docx
    Updated May 30, 2023
    + more versions
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    Miaolei Li; Jian Zu; Zongfang Li; Mingwang Shen; Yan Li; Fanpu Ji (2023). Data_Sheet_1_How to Reduce the Transmission Risk of COVID-19 More Effectively in New York City: An Age-Structured Model Study.docx [Dataset]. http://doi.org/10.3389/fmed.2021.641205.s001
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    docxAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Frontiers
    Authors
    Miaolei Li; Jian Zu; Zongfang Li; Mingwang Shen; Yan Li; Fanpu Ji
    License

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

    Area covered
    New York
    Description

    Background: In face of the continuing worldwide COVID-19 epidemic, how to reduce the transmission risk of COVID-19 more effectively is still a major public health challenge that needs to be addressed urgently.Objective: This study aimed to develop an age-structured compartment model to evaluate the impact of all diagnosed and all hospitalized on the epidemic trend of COVID-19, and explore innovative and effective releasing strategies for different age groups to prevent the second wave of COVID-19.Methods: Based on three types of COVID-19 data in New York City (NYC), we calibrated the model and estimated the unknown parameters using the Markov Chain Monte Carlo (MCMC) method.Results: Compared with the current practice in NYC, we estimated that if all infected people were diagnosed from March 26, April 5 to April 15, 2020, respectively, then the number of new infections on April 22 was reduced by 98.02, 93.88, and 74.08%. If all confirmed cases were hospitalized from March 26, April 5, and April 15, 2020, respectively, then as of June 7, 2020, the total number of deaths in NYC was reduced by 67.24, 63.43, and 51.79%. When only the 0–17 age group in NYC was released from June 8, if the contact rate in this age group remained below 61% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC. When both the 0–17 and 18–44 age groups in NYC were released from June 8, if the contact rates in these two age groups maintained below 36% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC.Conclusions: If all infected people were diagnosed in time, the daily number of new infections could be significantly reduced in NYC. If all confirmed cases were hospitalized in time, the total number of deaths could be significantly reduced in NYC. Keeping a social distance and relaxing lockdown restrictions for people between the ages of 0 and 44 could not lead to a second wave of COVID-19 in NYC.

  18. f

    Health care utilization of patients pre and post hospitalization due to...

    • plos.figshare.com
    xls
    Updated Jun 20, 2024
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    Mohammed Zaidan; Daniel Puebla Neira; Efstathia Polychronopoulou; Kuo Yong-Fang; Gulshan Sharma (2024). Health care utilization of patients pre and post hospitalization due to COVID-19,, by medical specialty. [Dataset]. http://doi.org/10.1371/journal.pone.0303509.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Mohammed Zaidan; Daniel Puebla Neira; Efstathia Polychronopoulou; Kuo Yong-Fang; Gulshan Sharma
    License

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

    Description

    Health care utilization of patients pre and post hospitalization due to COVID-19,, by medical specialty.

  19. C

    Covid-19 hospital and intensive care (ICU) admissions in the Netherlands by...

    • ckan.mobidatalab.eu
    csv, json
    Updated Aug 30, 2023
    + more versions
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    NationaalGeoregisterNL (2023). Covid-19 hospital and intensive care (ICU) admissions in the Netherlands by age group by hospital and IC admission week and reporting week (according to NICE registration) [Dataset]. https://ckan.mobidatalab.eu/mk/dataset/covid-19-hospital-and-intensive-care-ic-admissions-in-the-netherlands-per-age-group-per-hospital
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    json, csvAvailable download formats
    Dataset updated
    Aug 30, 2023
    Dataset provided by
    NationaalGeoregisterNL
    Area covered
    Netherlands
    Description

    For English, see below This file contains: - the number of COVID-19 hospital and IC admissions per age group in the Netherlands, per week of hospital or IC admission and per week on which the data were reported to the NICE registry (https: //www.stichting-nice.nl). The numbers concern COVID-19 hospital and IC admissions since the first report in the Netherlands (27/02/2020) up to and including the most recent complete week of admission. The registration of the number of COVID-19 hospital and IC admissions may be lagging behind. This may result in the date of recording and the date of the report falling in a different calendar week. Hospital or ICU admissions from the most recent complete week of admission may have been reported in the current incomplete week and are therefore shown in this file. Hospital and ICU admissions from the most recent incomplete week are not included in this file but are censored with the value “NaN” (Not a number). The file is structured as follows: - One record per week of statistics for the Netherlands, even if there are no recordings or reports for the week in question. The numbers are then 0 (zero). -The stated date for statistics may relate to a hospital or IC admission date or the date on which the hospital reported a hospital or IC admission to the NICE registry. Description of the variables: Version: version number of the dataset. When the content of the dataset is structurally changed (so not the daily update or a correction at record level), the version number will be adjusted (+1) and also the corresponding metadata in RIVMdata (Https://data.rivm.nl) . Version 2 update (August 9, 2022): - From August 9, 2022, new admissions of persons with a SARS-CoV-2 infection who were also admitted during a previous COVID-19 episode have been added to this open data file. For this reason, the number of withdrawals with retroactive effect is higher than in our previous files. The underestimation of admissions since the start of the pandemic to August 9, 2022 is less than 1%. A recording is counted as a new recording when a person with a SARS-CoV-2 infection has a recording date that is more than 90 days after the previous recording. Version 3 update (September 1, 2022): - From September 1, 2022, the data will no longer be updated every Wednesday, but on Tuesdays. - As of September 1, 2022, this dataset is split into two parts. The first part contains the dates from the start of the pandemic to October 3, 2021 (week 39) and contains "tm" in the file name. This data will no longer be updated. The second part contains the data from October 4, 2021 (week 40) and is updated every Tuesday. Version 4 update (November 24, 2022): - From November 24, 2022, the age group 0-14 years will be split into age groups 0-4, 5-9 and 10-14 years. This will be retroactively updated for the entire pandemic. Version 5 update (April 4, 2023): - From April 4, 2023, this file will be updated weekly on Tuesdays. The data is retroactively updated for the other days. Date_of_report: Date and time on which the data file was created by RIVM. Date_of_statistics_week_start: The date of the Monday - first day of that week - for which the numbers per week are presented. Week of hospital admission (variable Hospital_admission), week of IC admission (variable IC_admission), the week on which the hospital admission (variable Hospital_admission_notification) or IC admission was reported (variable IC_admission_notification) to the NICE registry. Age_group: Age group in years of the admitted or reported patients. Five-year intervals are used with the exception of 90 years and above (90+). Patients with an unknown age are added to 'Unknown'. Hospital_admission_notification: The number of new COVID-19 patients admitted to the NICE registry per age group [Age_group] per week on which the hospital admission was reported [Date_of_statistics_week_start]. Hospital_admission: The number of new COVID-19 patients admitted to hospital per age group [Age_group] per hospital admission week [Date_of_statistics_week_start] reported to the NICE registry. IC_admission_notification: The number of new COVID-19 patients reported to the NICE registry who were admitted to the ICU per age group [Age_group] per week on which the ICU admission was reported [Date_of_statistics_week_start]. IC_admission: The number of new COVID-19 patients reported to the NICE registry who have been admitted to the ICU per age group [Age_group] per ICU admission week [Date_of_statistics_week_start]. A patient can be hospitalized or admitted to ICU multiple times (see version 2 update). RIVM and the NICE registry have aligned the method for determining the most relevant admission date in such cases as much as possible, but the numbers may differ slightly from the data as presented by the NICE registry. A patient admitted to the ICU also counts in the hospital admission figures. Despite the fact that hospitals are asked to register COVID-19 patients several times a day, the registration of the number of patients may lag. As a result, the numbers for the past calendar week may still be incomplete (https://www.stichting-nice.nl). Corrections made in reports in the source system of the NICE registration by employees of hospitals can also lead to corrections in this database. In that case, numbers published by RIVM in the past may deviate from the numbers in this database. At the time of creation and publication, this file therefore always contains the most up-to-date data according to the source system of the NICE registration after processing by RIVM. -------------------------------------------------- --------------------------------------------- Covid-19 hospital and intensive care unit (ICU) admissions in the Netherlands by age group by hospital and ICU admission week and reporting week (according to NICE registration) This file contains: - the number of COVID-19 hospital and ICU admissions by age group in the Netherlands, per week of hospitalization or ICU admission and per week on which the data were reported to the NICE registry (https://www.stichting-nice.nl). The numbers concern COVID-19 hospital and ICU admissions since the first report in the Netherlands (27/02/2020) up to and including the most recent complete week of admission. The registration of the number of COVID-19 hospital and ICU admissions may be lagging behind. This may result in the date of recording and the date of the report falling in a different calendar week. Hospital or ICU admissions from the most recent complete week of admission may have been reported in the current incomplete week and are therefore shown in this file. Hospital and ICU admissions from the most recent incomplete week are not included in this file but are censored with the value “NaN” (Not a Number). The file is structured as follows: - A record per week of statistics for the Netherlands, even if there are no recordings or reports on the week in question. The numbers are then 0 (zero). -The stated date for statistics may relate to a hospital or ICU admission date or the date on which the hospital reported a hospital or ICU admission to the NICE registry. Description of the variables: Version: version number of the dataset. When the content of the dataset is structurally changed (so not the daily update or a correction at record level), the version number will be adjusted (+1) and also the corresponding metadata in RIVMdata (Https://data.rivm.nl ). Version 2 update (August 9, 2022): - From August 9, 2022, new admissions of persons with a SARS-CoV-2 infection who were also admitted during a previous COVID-19 episode have been added to this open data file. For this reason, the number of withdrawals with retroactive effect is higher than in our previous files. The underestimation of admissions since the start of the pandemic to August 9, 2022 is less than 1%. A recording is counted as a new recording when a person with a SARS-CoV-2 infection has a recording date that is more than 90 days after the previous recording. Version 3 update (September 1, 2022): - From September 1, 2022, the data will no longer be updated every Wednesday, but on Tuesdays. - As of September 1, 2022, this dataset is split into two parts. The first part contains the dates from the start of the pandemic till October 3, 2021 (week 39) and contains "tm" in the file name. This data will no longer be updated. The second part contains the data from October 4, 2021 (week 40) and is updated every Tuesday. Version 4 update (November 24, 2022): - From November 24, 2022, the age group 0-14 years will be split into age groups 0-4, 5-9 and 10-14 years. This will be retroactively updated for the entire pandemic. Version 5 update (April 4, 2023): - From April 4, 2023, this file will be updated weekly on Tuesdays. The data has been retroactively updated for the other days. Date_of_report: Date and time on which the data file was created by the RIVM. Date_of_statistics_week_start: The date of the Monday - first day of that week - for which the numbers per week are presented. Week of hospital admission (variable Hospital_admission), week of ICU admission (variable IC_admission), the week on which the hospital admission (variable Hospital_admission_notification) or ICU admission was reported (variable IC_admission_notification) to the NICE registry. Age_group: Age group in years of the admitted or reported patients. Five-year intervals are used with the exception of 90 years and above (90+). Patients with an unknown age are added to 'Unknown'. Hospital_admission_notification: The number of new COVID-19 patients admitted to the NICE registry per age group [Age_group] per week on which the hospital admission was reported [Date_of_statistics_week_start]. Hospital_admission: The number of new COVID-19 patients admitted to hospital per age group [Age_group] per hospital admission week [Date_of_statistics_week_start] reported to the NICE registry. IC_admission_notification: The

  20. COVID-19 Post-Vaccination Infection Data (ARCHIVED)

    • data.chhs.ca.gov
    • data.ca.gov
    • +4more
    csv, xlsx, zip
    Updated Aug 30, 2024
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    California Department of Public Health (2024). COVID-19 Post-Vaccination Infection Data (ARCHIVED) [Dataset]. https://data.chhs.ca.gov/dataset/covid-19-post-vaccination-infection-data
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    csv(38212), xlsx(11056), csv(90508), csv(78921), zipAvailable download formats
    Dataset updated
    Aug 30, 2024
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    Description

    Note: This dataset is no longer being updated due to the end of the COVID-19 Public Health Emergency.

    The California Department of Public Health (CDPH) is identifying vaccination status of COVID-19 cases, hospitalizations, and deaths by analyzing the state immunization registry and registry of confirmed COVID-19 cases. Post-vaccination cases are individuals who have a positive SARS-Cov-2 molecular test (e.g. PCR) at least 14 days after they have completed their primary vaccination series.

    Tracking cases of COVID-19 that occur after vaccination is important for monitoring the impact of immunization campaigns. While COVID-19 vaccines are safe and effective, some cases are still expected in persons who have been vaccinated, as no vaccine is 100% effective. For more information, please see https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/COVID-19/Post-Vaccine-COVID19-Cases.aspx

    Post-vaccination infection data is updated monthly and includes data on cases, hospitalizations, and deaths among the unvaccinated and the vaccinated. Partially vaccinated individuals are excluded. To account for reporting and processing delays, there is at least a one-month lag in provided data (for example data published on 9/9/22 will include data through 7/31/22).

    Notes:

    • On September 9, 2022, the post-vaccination data has been changed to compare unvaccinated with those with at least a primary series completed for persons age 5+. These data will be updated monthly (first Thursday of the month) and include at least a one month lag.

    • On February 2, 2022, the post-vaccination data has been changed to distinguish between vaccination with a primary series only versus vaccinated and boosted. The previous dataset has been uploaded as an archived table. Additionally, the lag on this data has been extended to 14 days.

    • On November 29, 2021, the denominator for calculating vaccine coverage has been changed from age 16+ to age 12+ to reflect new vaccine eligibility criteria. The previous dataset based on age 16+ denominators has been uploaded as an archived table.

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Statista, Rate of COVID-19 hospitalizations in the U.S. as of September 26, 2020, by age group [Dataset]. https://www.statista.com/statistics/1122354/covid-19-us-hospital-rate-by-age/
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Rate of COVID-19 hospitalizations in the U.S. as of September 26, 2020, by age group

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4 scholarly articles cite this dataset (View in Google Scholar)
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Mar 1, 2020 - Sep 26, 2020
Area covered
United States
Description

As of September 26, the hospitalization rate in the United States due to COVID-19 was highest for those aged 85 years and older. This statistic shows the cumulative rate of laboratory-confirmed COVID-19-associated hospitalizations in the U.S. as of September 26, 2020, by age group.

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