16 datasets found
  1. Share of population in the U.S. vaccinated against COVID-19, Apr. 26, 2023,...

    • statista.com
    Updated May 15, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). Share of population in the U.S. vaccinated against COVID-19, Apr. 26, 2023, by state [Dataset]. https://www.statista.com/statistics/1202065/population-with-covid-vaccine-by-state-us/
    Explore at:
    Dataset updated
    May 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of April 26, 2023, around 81.3 percent of the U.S. population had received at least one dose of a COVID-19 vaccination. This statistic shows the percentage of the population in the United States who had been given a COVID-19 vaccination as of April 26, 2023, by state or territory.

  2. d

    COVID-19 Vaccinations by Age Group - ARCHIVED

    • catalog.data.gov
    • data.ct.gov
    Updated Jul 12, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    data.ct.gov (2025). COVID-19 Vaccinations by Age Group - ARCHIVED [Dataset]. https://catalog.data.gov/dataset/covid-19-vaccinations-by-age-group
    Explore at:
    Dataset updated
    Jul 12, 2025
    Dataset provided by
    data.ct.gov
    Description

    NOTE: As of 2/16/2023, this table is no longer being updated. For data on COVID-19 Updated (Bivalent) Booster Coverage by Age go to https://data.ct.gov/Health-and-Human-Services/COVID-19-Updated-Bivalent-Booster-Coverage-By-Age-/j2me-7k56. For information on COVID-19 vaccination primary series coverage for people less than 5 years go to https://data.ct.gov/Health-and-Human-Services/COVID-19-Vaccination-Primary-Series-Coverage-Age-L/su9q-qn6e Important change as of June 1, 2022 As of June 1, 2022, we will be using 2020 DPH provisional census estimates* to calculate vaccine coverage percentages for state- and county-level tables (except coverage by CT SVI priority zip code). 2020 estimates will replace the 2019 estimates that have been used. Caution should be taken when making comparisons of percentages calculated using the 2019 and 2020 census estimates since observed difference may result from the shift in the denominator. The age groups in the state-level data tables will also be changing as a result of the switch to the new denominator. DPH Provisional State and County Characteristics Estimates April 1, 2020. Hayes L, Abdellatif E, Jiang Y, Backus K (2022) Connecticut DPH Provisional April 1, 2020 State Population Estimates by 18 age groups, sex, and 6 combined race and ethnicity groups. Connecticut Department of Public Health, Health Statistics & Surveillance, SAR, Hartford, CT. This tables shows the number and percent of people that have initiated COVID-19 vaccination, are fully vaccinated, and addition dose 1 by age group. Age is based on age at the time of administration of the first dose. All data in this report are preliminary; data for previous dates will be updated as new reports are received, and data errors are corrected. Population size estimates are based on 2019 DPH census estimates until 5/26/2022. From 6/1/2022, 2020 DPH provisional census estimates are used. In the data shown here, a person who has received at least one dose of COVID-19 vaccine is considered to have initiated vaccination. A person is considered fully vaccinated if he/she has completed a primary vaccination series by receiving 2 doses of the Pfizer, Novavax or Moderna vaccines or 1 dose of the Johnson & Johnson vaccine. The fully vaccinated are a subset of the people who have received at least one dose. A person who completed a Pfizer, Moderna, Novavax or Johnson & Johnson primary series (as defined above) and then had an additional monovalent dose of COVID-19 vaccine is considered to have had additional dose 1. The additional dose may be Pfizer, Moderna, Novavax or Johnson & Johnson and may be a different type from the primary series. For people who had a primary Pfizer or Moderna series, additional dose 1 was counted starting August 18th, 2021. For people with a Johnson & Johnson primary series additional dose 1 was counted starting October 22nd, 2021. For most people, additional dose 1 is a booster. However, additional dose 1 may represent a supplement to the primary series for a people who is moderately or severely immunosuppressed. Bivalent booster administrations are not included in the additional dose 1 calculations. The percent with at least one dose many be over-estimated, and the percent fully vaccinated and with additional dose 1 may be under-estimated because of vaccine administration records for individuals that cannot be linked because of differences in how names or date of birth are reported. Town-level coverage estimates have been capped at 100%. Observed coverage may be greater than 100% for multiple reasons, including census denominator data not including all individuals that currently reside in the town (e.g., part time residents, change in population size since the census), errors in address data or other reporting errors. Also, the percent with at least one dose many be over-estimated, and the percent fully

  3. Per capita administration of vaccines in Germany 2018, by federal state

    • statista.com
    Updated Jul 10, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Per capita administration of vaccines in Germany 2018, by federal state [Dataset]. https://www.statista.com/statistics/1200054/vaccines-per-capita-administration-by-state-germany/
    Explore at:
    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2019
    Area covered
    Germany
    Description

    In 2019, Saxony saw the highest per capita administration of vaccines among other German states at *** DDD (defined daily dose). Saxony-Anhalt followed closely at **** DDD per capita.

  4. Covid Vaccinations in United States🇺🇸💉

    • kaggle.com
    Updated Feb 20, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Berkay Alan (2022). Covid Vaccinations in United States🇺🇸💉 [Dataset]. https://www.kaggle.com/berkayalan/vaccinations-in-united-states/metadata
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 20, 2022
    Dataset provided by
    Kaggle
    Authors
    Berkay Alan
    License

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

    Area covered
    United States
    Description

    Context

    This dataset provides State-by-state data on United States COVID-19 vaccinations between 20 December of 2020 and 12 January of 2022. Data is taken daily by the United States Centers for Disease Control and Prevention

    Columns

    us_vaccinations File

    - location: State name.

    - date: date of the case.

    - total_vaccinations: total number of doses administered. This is counted as a single dose, and may not equal the total number of people vaccinated, depending on the specific dose regime (e.g. people receive multiple doses). If a person receives one dose of the vaccine, this metric goes up by 1. If they receive a second dose, it goes up by 1 again.

    - total_vaccinations_per_hundred: total_vaccinations per 100 people in the total population of the state.

    - daily_vaccinations_raw: daily change in the total number of doses administered. It is only calculated for consecutive days. This is a raw measure provided for data checks and transparency, but we strongly recommend that any analysis on daily vaccination rates be conducted using daily_vaccinations instead.

    - daily_vaccinations: new doses administered per day (7-day smoothed). For countries that don't report data on a daily basis, we assume that doses changed equally on a daily basis over any periods in which no data was reported. This produces a complete series of daily figures, which is then averaged over a rolling 7-day window. An example of how we perform this calculation can be found here.

    - daily_vaccinations_per_million: daily_vaccinations per 1,000,000 people in the total population of the state.

    - people_vaccinated: total number of people who received at least one vaccine dose. If a person receives the first dose of a 2-dose vaccine, this metric goes up by 1. If they receive the second dose, the metric stays the same.

    - people_vaccinated_per_hundred: people_vaccinated per 100 people in the total population of the state.

    - people_fully_vaccinated: total number of people who received all doses prescribed by the vaccination protocol. If a person receives the first dose of a 2-dose vaccine, this metric stays the same. If they receive the second dose, the metric goes up by 1.

    - people_fully_vaccinated_per_hundred: people_fully_vaccinated per 100 people in the total population of the state.

    - total_distributed: cumulative counts of COVID-19 vaccine doses recorded as shipped in CDC's Vaccine Tracking System.

    - total_distributed_per_hundred: cumulative counts of COVID-19 vaccine doses recorded as shipped in CDC's Vaccine Tracking System per 100 people in the total population of the state.

    - share_doses_used: share of vaccination doses administered among those recorded as shipped in CDC's Vaccine Tracking System.

    Data as of: May 18, 2021

  5. d

    COVID-19 Vaccination by Town and Race/Ethnicity - ARCHIVED

    • catalog.data.gov
    • data.ct.gov
    • +1more
    Updated Sep 15, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    data.ct.gov (2023). COVID-19 Vaccination by Town and Race/Ethnicity - ARCHIVED [Dataset]. https://catalog.data.gov/dataset/covid-19-vaccination-by-town-and-race-ethnicity
    Explore at:
    Dataset updated
    Sep 15, 2023
    Dataset provided by
    data.ct.gov
    Description

    NOTE: As of 2/16/2023, this page is no longer being updated. This table shows the number and percent of people that have initiated COVID-19 vaccination and are fully vaccinated by race / ethnicity and town. It includes people of all ages. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. A person who has received at least one dose of any vaccine is considered to have initiated vaccination. A person is considered fully vaccinated if they have completed a primary series by receiving 2 doses of the Pfizer, Novavax or Moderna vaccines or 1 dose of the Johnson & Johnson vaccine. The fully vaccinated are a subset of the number who have received at least one dose. Race and ethnicity data may be self-reported or taken from an existing electronic health care record. Reported race and ethnicity information is used to create a single race/ethnicity variable. People with Hispanic ethnicity are classified as Hispanic regardless of reported race. People with a missing ethnicity are classified as non-Hispanic. People with more than one race are classified as multiple race. A vaccine coverage percentage cannot be calculated for people classified as NH Other race or NH Unknown race since there are not population size estimates for these groups. Data quality assurance activities suggest that NH Other may represent a missing value. Vaccine coverage estimates in specific race/ethnicity groups may be underestimated as result of the exclusion of records classified as NH Unknown Race or NH Other Race. Town of residence is verified by geocoding the reported address and then mapping it a town using municipal boundaries. If an address cannot be geocoded, the reported town is used. Town-level coverage estimates have been capped at 100%. Observed coverage may be greater than 100% for multiple reasons, including census denominator data not including all individuals that currently reside in the town (e.g., part time residents, change in population size since the census) or potential data reporting errors. The population denominators for these town- and age-specific coverage estimates are based on 2014 census estimates. This is the most recent year for which reliable town- and age-specific estimates are available. (https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Town-Population-with-Demographics). Changes in the size and composition of the population between 2014 and 2021 may results in inaccuracy in vaccine coverage estimates. For example, the size of the Hispanic population may be underestimated in a town given the reported increase in the size of the Hispanic population between the 2010 and 2020 censuses resulting in inflated vaccine coverage estimates. The 2014 census data are grouped in 5-year age bands. For vaccine coverage age groupings not consistent with a standard 5-year age band, each age was assumed to be 20% of the total within a 5-year age band. However, given the large deviation from this assumption for Mansfield because of the presence of the University of Connecticut, the age distribution observed in the 2010 census for the age bands 15 to 19 and 20 to 24 was used to estimate the population denominators. This table does not included doses administered to CT residents by out-of-state providers or by some Federal entities (including Department of Defense, Department of Correction, Department of Veteran’s Affairs, Indian Health Service) because they are not yet reported to CT WiZ (the CT immunization Information System). It is expected that these data will be added in the future. Caution should be used when interpreting coverage estimates for towns with large college/university populations since coverage may be underestimated. In the census, college/university students who live on or just off campus would be counted in the college/university town. However, if a student was vaccinated while study

  6. COVID-19 vaccination rate in European countries as of January 2023

    • statista.com
    Updated Jul 9, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). COVID-19 vaccination rate in European countries as of January 2023 [Dataset]. https://www.statista.com/statistics/1196071/covid-19-vaccination-rate-in-europe-by-country/
    Explore at:
    Dataset updated
    Jul 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Europe
    Description

    As of January 18, 2023, Portugal had the highest COVID-19 vaccination rate in Europe having administered 272.78 doses per 100 people in the country, while Malta had administered 258.49 doses per 100. The UK was the first country in Europe to approve the Pfizer/BioNTech vaccine for widespread use and began inoculations on December 8, 2020, and so far have administered 224.04 doses per 100. At the latest data, Belgium had carried out 253.89 doses of vaccines per 100 population. Russia became the first country in the world to authorize a vaccine - named Sputnik V - for use in the fight against COVID-19 in August 2020. As of August 4, 2022, Russia had administered 127.3 doses per 100 people in the country.

    The seven-day rate of cases across Europe shows an ongoing perspective of which countries are worst affected by the virus relative to their population. For further information about the coronavirus pandemic, please visit our dedicated Facts and Figures page.

  7. COVID-19 vaccination rate in Latin America & the Caribbean 2024, by country

    • statista.com
    • ai-chatbox.pro
    Updated Jun 30, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). COVID-19 vaccination rate in Latin America & the Caribbean 2024, by country [Dataset]. https://www.statista.com/statistics/1194813/latin-america-covid-19-vaccination-rate-country/
    Explore at:
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    LAC, Latin America
    Description

    By August 2024, Cuba had administered the largest number of vaccines against COVID-19 per 100 inhabitants in the Latin American region, followed by Chile and Peru. According to recent estimates, the Caribbean country applied around 410 doses per 100 population, accounting for one of the largest vaccination rates observed not only in the Latin American region, but worldwide. In comparison, Haiti registered the lowest vaccination rate within the region, with only 5.87 doses administered per 100 inhabitants. Booster shots started To reinforce the immune protection against the fast spread of the SARS-CoV-2, governments began to introduce booster shots in their immunization programs aiming at strengthening people’s immune response against new contagious COVID-19 variants. In Latin America, Cuba was leading on booster shots relative to its population among a selection of countries, with around 88 percent of the population receiving the extra dose. In comparison, these numbers are higher than those for the European Union and the United States. Pharmaceutical research continues As Omicron becomes more prominent worldwide, and recombinant variants emerge, research efforts to prevent and control the disease continue to progress. As of June 2022, there were around 2,700 clinical trials to treat COVID-19 and 1,752 COVID-19 vaccines trials in clinical development. Other studies were focused on mild, moderate and severe COVID-19, complication support, and post-COVID symptoms, among others.For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

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

    • data.virginia.gov
    • healthdata.gov
    • +1more
    csv, json, rdf, xsl
    Updated Jun 1, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Centers for Disease Control and Prevention (2023). Rates of COVID-19 Cases or Deaths by Age Group and Updated (Bivalent) Booster Status [Dataset]. https://data.virginia.gov/dataset/rates-of-covid-19-cases-or-deaths-by-age-group-and-updated-bivalent-booster-status
    Explore at:
    xsl, csv, json, rdfAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    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

  9. Share of adults vaccinated with COVID-19 vaccine Australia at August 2022,...

    • statista.com
    Updated Apr 3, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). Share of adults vaccinated with COVID-19 vaccine Australia at August 2022, by state [Dataset]. https://www.statista.com/statistics/1245798/australia-percentage-adults-vaccinated-with-covid-19-vaccine-by-state/
    Explore at:
    Dataset updated
    Apr 3, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 22, 2022
    Area covered
    Australia
    Description

    As of August 22, 2022, over 80 percent of adults in Western Australia had been vaccinated with three doses of a COVID-19 vaccine. In comparison, less than 60 percent of Queensland population aged 16 years and over and received three doses of a COVID-19 vaccine.

  10. f

    Regional variations in serotype distribution and vaccination status in...

    • plos.figshare.com
    tiff
    Updated Jun 2, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Stephanie Perniciaro; Matthias Imöhl; Christina Fitzner; Mark van der Linden (2023). Regional variations in serotype distribution and vaccination status in children under six years of age with invasive pneumococcal disease in Germany [Dataset]. http://doi.org/10.1371/journal.pone.0210278
    Explore at:
    tiffAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Stephanie Perniciaro; Matthias Imöhl; Christina Fitzner; Mark van der Linden
    License

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

    Description

    OverviewThe protective effect of infant pneumococcal conjugate vaccine (PCV) recommendation can be seen in Germany as a whole and in smaller regional groups. Comparisons between population-normalized geographic regions of Germany show different serotype distributions after program implementation, particularly in non-vaccine serotypes. The prior distinct differences in serotype distribution in children between the former East and former West German federal states have vanished. Children under six remain a vulnerable group, but the occurrence of vaccine-type (VT) invasive pneumococcal disease (IPD) in children correctly vaccinated (using a three-dose primary series plus one booster dose) with PCV13 was low (9 out of 374 cases, 2.4%). However, only 18.4% of children in Germany with IPD were correctly vaccinated with PCV13 according to the recommended schedule. Continued surveillance and better schedule adherence are essential to definitively establish the most effective PCV administration schedule.Vaccination effectsFor all PCV products used in Germany (PCV7, PCV10, and PCV13), vaccination status was the most common statistically significant predictor of infection with a particular serotype: Unvaccinated children old enough to have received at least one dose of vaccine in the PCV7 group had significantly higher odds (OR: 6.84, 95%CI: 2.66–22.06, adjusted for per capita income and residence in the northeastern federal states) of contracting VT IPD. In the PCV10 group, VT IPD had an OR of 4.52 (95% CI: 1.60–15.62, adjusted for year of infection, median household size, and residence in the southern federal states) in unvaccinated children, and in the PCV13 group, unvaccinated children continued to have higher odds (OR: 6.21, 95%CI: 3.45–11.36, adjusted for year of infection, age of child, per capita income, residence in the southern federal states, and percentage of children using public daycare) of getting vaccine-type IPD. Being unvaccinated was the most frequent significant indicator for infection with vaccine-type serotypes for each analysis group, while geographic groupings showed more limited potential to predict serotype of infection in early childhood IPD in Germany.

  11. Flu vaccine coverage in the U.S. 2014-2023, by age

    • statista.com
    Updated Jun 23, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Flu vaccine coverage in the U.S. 2014-2023, by age [Dataset]. https://www.statista.com/statistics/861176/flu-vaccine-coverage-by-age-us/
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the United States, influenza vaccination rates differ greatly by age. For example, during the 2022-2023 flu season, around ** percent of those aged 65 years and older received an influenza vaccination, compared to just ** percent of those aged 18 to 49 years. The CDC recommends that everyone six months and older in the United States should get vaccinated against influenza every year, with a few exceptions. Although influenza is mild for most people it can lead to hospitalization and even death, especially among the young, the old, and those with certain preexisting conditions. The impact of flu vaccinations Flu vaccinations are safe and effective, preventing thousands of illnesses, medical visits, and deaths every year. However, the effectiveness of flu vaccines varies each year depending on what flu viruses are circulating that season and the age and health status of the person receiving the vaccination. During the 2022-2023 flu season it was estimated that influenza vaccination prevented almost *********** hospitalizations among those aged 65 years and older. In addition, flu vaccinations prevented ***** deaths among those aged 65 years and older as well as ** deaths among children six months to four years. The burden of influenza The impact of influenza is different from season to season. However, during the 2022-2023 flu season there were around ** million cases of influenza in the United States. Furthermore, there were around ****** deaths due to influenza, an increase from the previous year but significantly fewer than in ********* when influenza contributed to ****** deaths. Most of these deaths are among the elderly. In ********* the death rate due to influenza among those aged 65 years and older was around **** per 100,000 population. In comparison, those aged 18 to 49 years had an influenza death rate of just ** per 100,000 population.

  12. f

    Best fitting linear models (according to AIC) and corresponding parameter...

    • plos.figshare.com
    xls
    Updated Jun 3, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Easton R. White; Laurent Hébert-Dufresne (2023). Best fitting linear models (according to AIC) and corresponding parameter estimates for the doubling time both early (first 7 days since 25 cases) and for the first three weeks. [Dataset]. http://doi.org/10.1371/journal.pone.0240648.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Easton R. White; Laurent Hébert-Dufresne
    License

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

    Description

    A parameter was not included in the table if it was not selected in the best fitting linear model. The overall model included the following parameters (see Methods for more detail): log(Population density), population percent in rural areas, percent of population over age 65, influenza vaccination rate, gross income per capita, expected number of years of schooling, community tightness score, tests per capita (at the end of 7 days or 21 days, respectively), and binary variables for the presence or absence of each social distancing restriction (see Fig 4).

  13. COVID-19 Trends in Each Country

    • coronavirus-response-israel-systematics.hub.arcgis.com
    • coronavirus-resources.esri.com
    • +2more
    Updated Mar 28, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Urban Observatory by Esri (2020). COVID-19 Trends in Each Country [Dataset]. https://coronavirus-response-israel-systematics.hub.arcgis.com/maps/a16bb8b137ba4d8bbe645301b80e5740
    Explore at:
    Dataset updated
    Mar 28, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Earth
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.COVID-19 Trends MethodologyOur goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.DOI: https://doi.org/10.6084/m9.figshare.125529863/7/2022 - Adjusted the rate of active cases calculation in the U.S. to reflect the rates of serious and severe cases due nearly completely dominant Omicron variant.6/24/2020 - Expanded Case Rates discussion to include fix on 6/23 for calculating active cases.6/22/2020 - Added Executive Summary and Subsequent Outbreaks sectionsRevisions on 6/10/2020 based on updated CDC reporting. This affects the estimate of active cases by revising the average duration of cases with hospital stays downward from 30 days to 25 days. The result shifted 76 U.S. counties out of Epidemic to Spreading trend and no change for national level trends.Methodology update on 6/2/2020: This sets the length of the tail of new cases to 6 to a maximum of 14 days, rather than 21 days as determined by the last 1/3 of cases. This was done to align trends and criteria for them with U.S. CDC guidance. The impact is areas transition into Controlled trend sooner for not bearing the burden of new case 15-21 days earlier.Correction on 6/1/2020Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020. Revisions added on 4/30/2020 are highlighted.Revisions added on 4/23/2020 are highlighted.Executive SummaryCOVID-19 Trends is a methodology for characterizing the current trend for places during the COVID-19 global pandemic. Each day we assign one of five trends: Emergent, Spreading, Epidemic, Controlled, or End Stage to geographic areas to geographic areas based on the number of new cases, the number of active cases, the total population, and an algorithm (described below) that contextualize the most recent fourteen days with the overall COVID-19 case history. Currently we analyze the countries of the world and the U.S. Counties. The purpose is to give policymakers, citizens, and analysts a fact-based data driven sense for the direction each place is currently going. When a place has the initial cases, they are assigned Emergent, and if that place controls the rate of new cases, they can move directly to Controlled, and even to End Stage in a short time. However, if the reporting or measures to curtail spread are not adequate and significant numbers of new cases continue, they are assigned to Spreading, and in cases where the spread is clearly uncontrolled, Epidemic trend.We analyze the data reported by Johns Hopkins University to produce the trends, and we report the rates of cases, spikes of new cases, the number of days since the last reported case, and number of deaths. We also make adjustments to the assignments based on population so rural areas are not assigned trends based solely on case rates, which can be quite high relative to local populations.Two key factors are not consistently known or available and should be taken into consideration with the assigned trend. First is the amount of resources, e.g., hospital beds, physicians, etc.that are currently available in each area. Second is the number of recoveries, which are often not tested or reported. On the latter, we provide a probable number of active cases based on CDC guidance for the typical duration of mild to severe cases.Reasons for undertaking this work in March of 2020:The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online. Initial older guidance was also obtained online. Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws. Thus, the formula used to compute an estimate of active cases is: Active Cases = 100% of new cases in past 14 days + 19% from past 15-25 days + 5% from past 26-49 days - total deaths. On 3/17/2022, the U.S. calculation was adjusted to: Active Cases = 100% of new cases in past 14 days + 6% from past 15-25 days + 3% from past 26-49 days - total deaths. Sources: https://www.cdc.gov/mmwr/volumes/71/wr/mm7104e4.htm https://covid.cdc.gov/covid-data-tracker/#variant-proportions If a new variant arrives and appears to cause higher rates of serious cases, we will roll back this adjustment. We’ve never been inside a pandemic with the ability to learn of new cases as they are confirmed anywhere in the world. After reviewing epidemiological and pandemic scientific literature, three needs arose. We need to specify which portions of the pandemic lifecycle this map cover. The World Health Organization (WHO) specifies six phases. The source data for this map begins just after the beginning of Phase 5: human to human spread and encompasses Phase 6: pandemic phase. Phase six is only characterized in terms of pre- and post-peak. However, these two phases are after-the-fact analyses and cannot ascertained during the event. Instead, we describe (below) a series of five trends for Phase 6 of the COVID-19 pandemic.Choosing terms to describe the five trends was informed by the scientific literature, particularly the use of epidemic, which signifies uncontrolled spread. The five trends are: Emergent, Spreading, Epidemic, Controlled, and End Stage. Not every locale will experience all five, but all will experience at least three: emergent, controlled, and end stage.This layer presents the current trends for the COVID-19 pandemic by country (or appropriate level). There are five trends:Emergent: Early stages of outbreak. Spreading: Early stages and depending on an administrative area’s capacity, this may represent a manageable rate of spread. Epidemic: Uncontrolled spread. Controlled: Very low levels of new casesEnd Stage: No New cases These trends can be applied at several levels of administration: Local: Ex., City, District or County – a.k.a. Admin level 2State: Ex., State or Province – a.k.a. Admin level 1National: Country – a.k.a. Admin level 0Recommend that at least 100,000 persons be represented by a unit; granted this may not be possible, and then the case rate per 100,000 will become more important.Key Concepts and Basis for Methodology: 10 Total Cases minimum threshold: Empirically, there must be enough cases to constitute an outbreak. Ideally, this would be 5.0 per 100,000, but not every area has a population of 100,000 or more. Ten, or fewer, cases are also relatively less difficult to track and trace to sources. 21 Days of Cases minimum threshold: Empirically based on COVID-19 and would need to be adjusted for any other event. 21 days is also the minimum threshold for analyzing the “tail” of the new cases curve, providing seven cases as the basis for a likely trend (note that 21 days in the tail is preferred). This is the minimum needed to encompass the onset and duration of a normal case (5-7 days plus 10-14 days). Specifically, a median of 5.1 days incubation time, and 11.2 days for 97.5% of cases to incubate. This is also driven by pressure to understand trends and could easily be adjusted to 28 days. Source

  14. COVID-19 cases and deaths per million in 210 countries as of July 13, 2022

    • statista.com
    • ai-chatbox.pro
    Updated Nov 25, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). COVID-19 cases and deaths per million in 210 countries as of July 13, 2022 [Dataset]. https://www.statista.com/statistics/1104709/coronavirus-deaths-worldwide-per-million-inhabitants/
    Explore at:
    Dataset updated
    Nov 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

    The difficulties of death figures

    This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

    Where are these numbers coming from?

    The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

  15. Number of U.S. tetanus cases from 1980 to 2022, by year

    • statista.com
    Updated Sep 12, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). Number of U.S. tetanus cases from 1980 to 2022, by year [Dataset]. https://www.statista.com/statistics/1122819/tetanus-cases-us-by-year/
    Explore at:
    Dataset updated
    Sep 12, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2022, there were around 28 cases of tetanus in the United States. The annual number of tetanus cases in the United States has decreased steadily over the past few decades, and in the years 2018 and 2019 there were no reported cases. The decrease in tetanus cases in the United States and around the world is mostly due to high rates of vaccination.

    What is tetanus? Tetanus is an infection caused by bacteria that live in the environment. Spores of tetanus bacteria are often found in soil and dust and enter the body through broken skin, such as puncture wounds. Tetanus cannot be spread from one person to another. One of the most common symptoms of tetanus is a tightening of the jaw muscles, leading tetanus to often be called "lockjaw". Other symptoms include muscle spasms, muscle stiffness, trouble swallowing, seizures, headache, and fever. Like in the United States, cases of tetanus have decreased since the year 1980 for every region around the world. In 2022, there were a total of 6,651 cases of tetanus worldwide. The highest number of cases was found in Africa, however the year prior the Eastern Mediterranean reported the most cases.

    Tetanus vaccination Vaccination is the best way to protect against tetanus and most cases of tetanus in the United States are among people who have not been vaccinated. There are multiple vaccinations that protect against tetanus as well as other diseases such as DTap, DT, Tdap, and Td. Tetanus vaccinations are safe and effective and recommended for people of all ages, with children receiving multiple vaccinations and adults recommended to get vaccinated every 10 years. As of 2022, around 94 percent of one-year-olds in the United States had received the recommended three doses of the combined diphtheria, tetanus toxoid, and pertussis (DTP3) vaccine.

  16. COVID-19 deaths worldwide as of May 2, 2023, by country and territory

    • statista.com
    • ai-chatbox.pro
    Updated May 22, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). COVID-19 deaths worldwide as of May 2, 2023, by country and territory [Dataset]. https://www.statista.com/statistics/1093256/novel-coronavirus-2019ncov-deaths-worldwide-by-country/
    Explore at:
    Dataset updated
    May 22, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 2, 2023
    Area covered
    Worldwide
    Description

    As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had spread to almost every country in the world, and more than 6.86 million people had died after contracting the respiratory virus. Over 1.16 million of these deaths occurred in the United States.

    Waves of infections Almost every country and territory worldwide have been affected by the COVID-19 disease. At the end of 2021 the virus was once again circulating at very high rates, even in countries with relatively high vaccination rates such as the United States and Germany. As rates of new infections increased, some countries in Europe, like Germany and Austria, tightened restrictions once again, specifically targeting those who were not yet vaccinated. However, by spring 2022, rates of new infections had decreased in many countries and restrictions were once again lifted.

    What are the symptoms of the virus? It can take up to 14 days for symptoms of the illness to start being noticed. The most commonly reported symptoms are a fever and a dry cough, leading to shortness of breath. The early symptoms are similar to other common viruses such as the common cold and flu. These illnesses spread more during cold months, but there is no conclusive evidence to suggest that temperature impacts the spread of the SARS-CoV-2 virus. Medical advice should be sought if you are experiencing any of these symptoms.

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

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2024). Share of population in the U.S. vaccinated against COVID-19, Apr. 26, 2023, by state [Dataset]. https://www.statista.com/statistics/1202065/population-with-covid-vaccine-by-state-us/
Organization logo

Share of population in the U.S. vaccinated against COVID-19, Apr. 26, 2023, by state

Explore at:
5 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
May 15, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

As of April 26, 2023, around 81.3 percent of the U.S. population had received at least one dose of a COVID-19 vaccination. This statistic shows the percentage of the population in the United States who had been given a COVID-19 vaccination as of April 26, 2023, by state or territory.

Search
Clear search
Close search
Google apps
Main menu