80 datasets found
  1. Number of COVID-19 cases among young people in the U.S. from Mar. to Dec....

    • statista.com
    Updated Feb 24, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2021). Number of COVID-19 cases among young people in the U.S. from Mar. to Dec. 2020 by age [Dataset]. https://www.statista.com/statistics/1211937/number-of-young-persons-who-tested-positive-for-covid-19-by-age/
    Explore at:
    Dataset updated
    Feb 24, 2021
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    From March to December 2020, around 2.9 million children and adults aged 0 to 24 years tested positive for COVID-19 in the United States. This statistic illustrates the number of persons aged 0 to 24 years who tested positive for COVID-19 in the United States from March to December 2020, by age.

  2. Risk of death following COVID-19 vaccination or positive SARS-CoV-2 test in...

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Mar 27, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Office for National Statistics (2023). Risk of death following COVID-19 vaccination or positive SARS-CoV-2 test in young people, England [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/riskofdeathfollowingcovid19vaccinationorpositivesarscov2testinyoungpeopleengland
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Mar 27, 2023
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England
    Description

    Estimates of the risk of all-cause and cardiac death in the 12 weeks after vaccination or positive SARS-CoV-2 test compared with subsequent weeks for people aged 12 to 29 years in England using two sources of mortality data: ONS death registrations and deaths recorded in Hospital Episode Statistics. 8 December 2020 to 25 May 2022. Experimental Statistics.

  3. f

    DataSheet2_Attitudes Toward COVID-19 Vaccination Among Young Adults in...

    • frontiersin.figshare.com
    • datasetcatalog.nlm.nih.gov
    pdf
    Updated May 30, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Cesar Leos-Toro; Denis Ribeaud; Laura Bechtiger; Annekatrin Steinhoff; Amy Nivette; Aja L. Murray; Urs Hepp; Boris B. Quednow; Manuel P. Eisner; Lilly Shanahan (2023). DataSheet2_Attitudes Toward COVID-19 Vaccination Among Young Adults in Zurich, Switzerland, September 2020.PDF [Dataset]. http://doi.org/10.3389/ijph.2021.643486.s001
    Explore at:
    pdfAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Frontiers
    Authors
    Cesar Leos-Toro; Denis Ribeaud; Laura Bechtiger; Annekatrin Steinhoff; Amy Nivette; Aja L. Murray; Urs Hepp; Boris B. Quednow; Manuel P. Eisner; Lilly Shanahan
    License

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

    Area covered
    Zürich, Switzerland
    Description

    Objectives: Young adults are essential to the effective mitigation of the novel coronavirus (SARS-CoV-2/COVID-19) given their tendency toward greater frequency of social interactions. Little is known about vaccine willingness during pandemics in European populations. This study examined young people’s attitudes toward COVID-19 vaccines in Fall 2020.Methods: Data came from an ongoing longitudinal study’s online COVID-19-focused supplement among young adults aged 22 in Zurich, Switzerland (N = 499) in September 2020. Logistic regressions examined young adults’ likelihood of participating in COVID-19 immunization programs.Results: Approximately half of respondents reported being unlikely to get vaccinated against COVID-19. Compared to males, females were more likely to oppose COVID-19 vaccination (p < 0.05). In multivariate models, Sri Lankan maternal background and higher socioeconomic status were associated with a greater likelihood of getting vaccinated against COVID-19 (p < 0.05). Respondents were more likely to report a willingness to get vaccinated against COVID-19 when they perceived 1) an effective government response (p < 0.05) and 2) their information sources to be objective (p < 0.05).Conclusion: This study communicates aspects important to the development of targeted information campaigns to promote engagement in COVID-19 immunization efforts.

  4. Vaccination against coronavirus among young people in Nigeria 2021, by area

    • statista.com
    Updated Jan 24, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2023). Vaccination against coronavirus among young people in Nigeria 2021, by area [Dataset]. https://www.statista.com/statistics/1259668/willingness-to-be-vaccinated-among-young-people-in-nigeria/
    Explore at:
    Dataset updated
    Jan 24, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2021 - May 2021
    Area covered
    Nigeria
    Description

    As of May 2021, about 89 percent of people interviewed in Nigeria declared to be willing to be vaccinated against coronavirus (COVID-19). The percentage of people willing to get a COVID-19 vaccine was higher in rural Nigeria than in urban areas.

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

    • data.virginia.gov
    • healthdata.gov
    • +1more
    csv, json, rdf, xsl
    Updated Jul 20, 2023
    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 Vaccination Status [Dataset]. https://data.virginia.gov/dataset/rates-of-covid-19-cases-or-deaths-by-age-group-and-vaccination-status
    Explore at:
    rdf, csv, xsl, jsonAvailable download formats
    Dataset updated
    Jul 20, 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 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

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

    • healthdata.gov
    • odgavaprod.ogopendata.com
    • +2more
    application/rdfxml +5
    Updated Jun 16, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    data.cdc.gov (2023). Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status and Booster Dose [Dataset]. https://healthdata.gov/w/pifi-rn2z/default?cur=dU-uRhCR4oE
    Explore at:
    xml, csv, application/rdfxml, tsv, json, application/rssxmlAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset provided by
    data.cdc.gov
    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

  7. f

    Data_Sheet_1_COVID-19 Vaccine Hesitancy Among Older Adolescents and Young...

    • frontiersin.figshare.com
    docx
    Updated Jun 2, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Panpan Zhang; Yan Li; Huanchun Wang; Liyan Luo; Ping Wang; Huimin Wang; Qing Li; Zejing Meng; Hui Yang; Yuanhong Liu; Shiyue Zhou; Nan Li; Shengnan Zhang; Jianzhong Bi; Jiewen Zhang; Xiaolei Zheng (2023). Data_Sheet_1_COVID-19 Vaccine Hesitancy Among Older Adolescents and Young Adults: A National Cross-Sectional Study in China.docx [Dataset]. http://doi.org/10.3389/fpubh.2022.877668.s001
    Explore at:
    docxAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    Frontiers
    Authors
    Panpan Zhang; Yan Li; Huanchun Wang; Liyan Luo; Ping Wang; Huimin Wang; Qing Li; Zejing Meng; Hui Yang; Yuanhong Liu; Shiyue Zhou; Nan Li; Shengnan Zhang; Jianzhong Bi; Jiewen Zhang; Xiaolei Zheng
    License

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

    Description

    BackgroundWith promotion of COVID-19 vaccinations, there has been a corresponding vaccine hesitancy, of which older adolescents and young adults represent groups of particular concern. In this report, we investigated the prevalence and reasons for vaccine hesitancy, as well as potential risk factors, within older adolescents and young adults in China.MethodsTo assess these issues, an online survey was administered over the period from March 14 to April 15, 2021. Older adolescents (16–17 years old) and young adults (18–21 years old) were recruited nationwide from Wechat groups and results from a total of 2,414 respondents were analyzed. Socio-demographic variables, vaccine hesitancy, psychological distress, abnormal illness behavior, global well-being and social support were analyzed in this report.ResultsCompared to young adults (n = 1,405), older adolescents (n = 1,009) showed higher prevalence rates of COVID-19 vaccine hesitancy (16.5 vs. 7.9%, p < 0.001). History of physical diseases (p = 0.007) and abnormal illness behavior (p = 0.001) were risk factors for vaccine hesitancy among older adolescents, while only a good self-reported health status (p = 0.048) was a risk factor for young adults. Concerns over COVID-19 vaccine side effects (67.1%) and beliefs of invulnerability regarding infection risk (41.9%) were the most prevalent reasons for vaccine hesitancy. Providing evidence on the vaccine reduction of COVID-19 infection risk (67.5%), ensuring vaccine safety (56.7%) and the low risk of side effects (52.7%) were the most effective persuasions for promoting vaccinations.ConclusionIn China, older adolescents showed a higher prevalence for vaccine hesitancy than that of young adults. Abnormal illness behavior and history of physical diseases were risk factors for vaccine hesitancy among these older adolescents, while social support represents an important factor which could help to alleviate this hesitancy.

  8. Reasons for COVID-19 vaccine refusal among younger U.S. adults, Mar-May 2021...

    • statista.com
    Updated Nov 29, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2023). Reasons for COVID-19 vaccine refusal among younger U.S. adults, Mar-May 2021 [Dataset]. https://www.statista.com/statistics/1251264/reasons-for-covid-19-vaccine-refusal-among-younger-adults/
    Explore at:
    Dataset updated
    Nov 29, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 5, 2021 - May 2, 2021
    Area covered
    United States
    Description

    As of May 2021, over half of adults aged 18-39 who said they probably or definitely will not get a COVID-19 vaccination said it was because they were concerned about possible side effects. Moreover, 57 percent also said it was because they do not trust COVID-19 vaccines. This statistic depicts the percentage of adults 18-39 years who gave select reasons for not getting vaccinated against COVID-19 in the United States from March-May 2021, by vaccination intent.

  9. Risk of death following COVID-19 vaccination or positive SARS-CoV-2 test in...

    • gov.uk
    Updated Mar 27, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Office for National Statistics (2023). Risk of death following COVID-19 vaccination or positive SARS-CoV-2 test in young people, England: 8 December 2020 to 25 May 2022 [Dataset]. https://www.gov.uk/government/statistics/risk-of-death-following-covid-19-vaccination-or-positive-sars-cov-2-test-in-young-people-england-8-december-2020-to-25-may-2022
    Explore at:
    Dataset updated
    Mar 27, 2023
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Office for National Statistics
    Area covered
    England
    Description

    Official statistics are produced impartially and free from political influence.

  10. f

    Table_1_Age- and sex-specific differences in immune responses to BNT162b2...

    • frontiersin.figshare.com
    • datasetcatalog.nlm.nih.gov
    bin
    Updated Oct 23, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Cecilia Jay; Emily Adland; Anna Csala; Nicholas Lim; Stephanie Longet; Ane Ogbe; Jeremy Ratcliff; Oliver Sampson; Craig P. Thompson; Lance Turtle; Eleanor Barnes; Susanna Dunachie; Paul Klenerman; Miles Carroll; Philip Goulder (2023). Table_1_Age- and sex-specific differences in immune responses to BNT162b2 COVID-19 and live-attenuated influenza vaccines in UK adolescents.xlsx [Dataset]. http://doi.org/10.3389/fimmu.2023.1248630.s007
    Explore at:
    binAvailable download formats
    Dataset updated
    Oct 23, 2023
    Dataset provided by
    Frontiers
    Authors
    Cecilia Jay; Emily Adland; Anna Csala; Nicholas Lim; Stephanie Longet; Ane Ogbe; Jeremy Ratcliff; Oliver Sampson; Craig P. Thompson; Lance Turtle; Eleanor Barnes; Susanna Dunachie; Paul Klenerman; Miles Carroll; Philip Goulder
    License

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

    Description

    IntroductionThe key to understanding the COVID-19 correlates of protection is assessing vaccine-induced immunity in different demographic groups. Young people are at a lower risk of COVID-19 mortality, females are at a lower risk than males, and females often generate stronger immune responses to vaccination.MethodsWe studied immune responses to two doses of BNT162b2 Pfizer COVID-19 vaccine in an adolescent cohort (n = 34, ages 12–16), an age group previously shown to elicit significantly greater immune responses to the same vaccine than young adults. Adolescents were studied with the aim of comparing their response to BNT162b2 to that of adults; and to assess the impacts of other factors such as sex, ongoing SARS–CoV–2 infection in schools, and prior exposure to endemic coronaviruses that circulate at high levels in young people. At the same time, we were able to evaluate immune responses to the co-administered live attenuated influenza vaccine. Blood samples from 34 adolescents taken before and after vaccination with COVID-19 and influenza vaccines were assayed for SARS–CoV–2-specific IgG and neutralising antibodies and cellular immunity specific for SARS–CoV–2 and endemic betacoronaviruses. The IgG targeting influenza lineages contained in the influenza vaccine were also assessed.ResultsRobust neutralising responses were identified in previously infected adolescents after one dose, and two doses were required in infection-naïve adolescents. As previously demonstrated, total IgG responses to SARS–CoV-2 Spike were significantly higher among vaccinated adolescents than among adults (aged 32–52) who received the BNT162b2 vaccine (comparing infection-naïve, 49,696 vs. 33,339; p = 0.03; comparing SARS-CoV–2 previously infected, 743,691 vs. 269,985; p

  11. Deaths Involving COVID-19 by Vaccination Status

    • ouvert.canada.ca
    • datasets.ai
    • +2more
    csv, docx, html, xlsx
    Updated Jul 30, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Government of Ontario (2025). Deaths Involving COVID-19 by Vaccination Status [Dataset]. https://ouvert.canada.ca/data/dataset/1375bb00-6454-4d3e-a723-4ae9e849d655
    Explore at:
    xlsx, html, docx, csvAvailable download formats
    Dataset updated
    Jul 30, 2025
    Dataset provided by
    Government of Ontariohttps://www.ontario.ca/
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Time period covered
    Mar 1, 2021 - Nov 12, 2024
    Description

    This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool Data includes: * Date on which the death occurred * Age group * 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster ##Additional notes As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm. As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category. On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON. “Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.

  12. Data from: Let's talk about COVID-19 vaccination: relevance of conversations...

    • zenodo.org
    • data.niaid.nih.gov
    bin, csv
    Updated Jul 12, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Aylin Wagner; Aylin Wagner; Sibylle Juvalta; Sibylle Juvalta; Camilla Speranza; L. SuzanneSuggs; L. SuzanneSuggs; Julia Drava; Julia Drava; COVIDisc study group; Camilla Speranza; COVIDisc study group (2023). Let's talk about COVID-19 vaccination: relevance of conversations about COVID-19 vaccination and information sources on vaccination intention in Switzerland [Dataset]. http://doi.org/10.5281/zenodo.8134399
    Explore at:
    bin, csvAvailable download formats
    Dataset updated
    Jul 12, 2023
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Aylin Wagner; Aylin Wagner; Sibylle Juvalta; Sibylle Juvalta; Camilla Speranza; L. SuzanneSuggs; L. SuzanneSuggs; Julia Drava; Julia Drava; COVIDisc study group; Camilla Speranza; COVIDisc study group
    License

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

    Description

    Data to replicate the publication "Let's talk about COVID-19 vaccination: relevance of conversations about COVID-19 vaccination and information sources on vaccination intention in Switzerland?". This publication examines how public information sources and conversations about COVID-19 are associated with COVID-19 vaccination intention. Multivariable logistic regression and mediation analysis using generalized structural equation modeling were applied.

  13. f

    Table_1_Influencing Canadian young adults to receive additional COVID-19...

    • frontiersin.figshare.com
    docx
    Updated Oct 4, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Rachita Batra; Ovidiu Tatar; Patricia Zhu; Samara Perez; Ben Haward; Gregory Zimet; Zeev Rosberger (2024). Table_1_Influencing Canadian young adults to receive additional COVID-19 vaccination shots: the efficacy of brief video interventions focusing on altruism and individualism.DOCX [Dataset]. http://doi.org/10.3389/fpubh.2024.1414345.s001
    Explore at:
    docxAvailable download formats
    Dataset updated
    Oct 4, 2024
    Dataset provided by
    Frontiers
    Authors
    Rachita Batra; Ovidiu Tatar; Patricia Zhu; Samara Perez; Ben Haward; Gregory Zimet; Zeev Rosberger
    License

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

    Area covered
    Canada
    Description

    Younger adults, aged 18–39 years, exhibit low COVID-19 additional vaccine (i.e., vaccination beyond the original 2-dose series) uptake recommended in Canada. No study has examined how altruistic and individualistic messaging can influence COVID-19 additional dose intentions. The present study aimed to estimate the efficacy of altruism and individualism-based videos on vaccine intentions and to explore the multivariable associations between vaccine related individual psychosocial factors and intention to receive the COVID-19 vaccine. Using a web-based survey in a three-arm, pre-post randomized control trial design, we recruited Canadians aged 18–39 years in both English and French. Participants were randomly allocated in a 1:1:1 ratio to receive the active control (COVID-19 general information), control + altruism or control + altruism + individualism. The video interventions were developed with a media company, based on results of a focus group study conducted previously. The measurement of COVID-19 additional dosage intentions before and after completing the interventions was informed by the multistage Precaution Adoption Process Model. The McNemar Chi-square was used to evaluate within-group changes, and the Pearson Chi-square test was used to evaluate between-group changes post-intervention. The measurement of various psychosocial factors was informed by use of validated scale and self-report questions. We employed a generalized Structural Equation Model to evaluate the associations between COVID-19 vaccine intentions and the psychosocial factors. Analyses were performed on 3,431 participants (control: n = 1,149, control + altruism: n = 1,142, control + altruism + individualism: n = 1,140). Within-group results showed that participants transitioned significantly in all three groups in the direction of higher intentions for receiving additional COVID-19 vaccine doses. The between-group differences in post intervention vaccine intentions were not significant. We found that psychosocial factors that include, collectivism, intellectual humility, intolerance to uncertainty, religiosity, identifying as gender diverse, and being indigenous were associated with higher vaccine intentions, whereas pandemic fatigue was associated with lower vaccine intentions. Our study highlighted that a short video that includes altruism and individualism messaging or general COVID-19 information can increase intentions to vaccine among young adults. Furthermore, we gained a comprehensive understanding of various psychosocial factors that influence ongoing COVID-19 vaccination. Our findings can be used to influence public health messaging around COVID-19 vaccination.

  14. f

    Table_7_Concerns and Challenges Related to Sputnik V Vaccination Against the...

    • frontiersin.figshare.com
    • datasetcatalog.nlm.nih.gov
    docx
    Updated Jun 17, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Anna V. Vasileva; Tatiana A. Karavaeva; Dmitriy S. Radionov; Alexander V. Yakovlev; Igor N. Mitin; Emanuele Caroppo; Sergey I. Barshak; Kirill S. Nazarov (2023). Table_7_Concerns and Challenges Related to Sputnik V Vaccination Against the Novel COVID-19 Infection in the Russian Federation: The Role of Mental Health, and Personal and Social Issues as Targets for Future Psychosocial Interventions.docx [Dataset]. http://doi.org/10.3389/fpsyt.2022.835323.s007
    Explore at:
    docxAvailable download formats
    Dataset updated
    Jun 17, 2023
    Dataset provided by
    Frontiers
    Authors
    Anna V. Vasileva; Tatiana A. Karavaeva; Dmitriy S. Radionov; Alexander V. Yakovlev; Igor N. Mitin; Emanuele Caroppo; Sergey I. Barshak; Kirill S. Nazarov
    License

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

    Description

    BackgroundVaccine hesitancy causes serious difficulties in vaccination campaigns in many countries. The study of the population’s attitude toward vaccination and detection of the predictive important individual psychological and social factors defining the vaccination necessity perception will allow elaborating promoting vaccination adherence measures.ObjectivesThe aim of this research was to study COVID-19 threat appraisal, fear of COVID-19, trust in COVID-19 information sources, COVID-19 conspiracy beliefs, and the relationship of sociodemographic variables to COVID-19 preventive behavior.MethodsWe carried out a cohort cross-sectional study of the population’s attitude toward vaccination against the novel COVID-19 coronavirus infection, using a specially designed questionnaire for an online survey. Totally, there were 4,977 respondents, ranging in age from 18 to 81 years. Statistical assessment was carried out using the SPSS-11 program.ResultsThere were different attitudes toward vaccination. Among respondents, 34.2% considered vaccination to be useful, 31.1% doubted its effectiveness, and 9.9% considered vaccination unnecessary. The survey indicated that 7.4% of respondents were indifferent to the vaccine, while 12.2% deemed it to be dangerous. Nearly one-third (32.3%) of respondents indicated that they did not plan to be vaccinated, while another third (34.0%) would postpone their decision until more comprehensive data on the results and effectiveness of vaccination were available. Only 11.6% of the respondents were vaccinated at the time of the study. Young people were less focused on vaccination compared to middle-aged and elderly people. Receiving information concerning COVID-19 vaccination from healthcare workers and scientific experts was associated with greater vaccination acceptance.ConclusionThe study results showed that vaccination attitudes interacted with individuals’ mental health and various sociodemographic factors. Insofar as reports of physicians and experts are essential for shaping attitudes to vaccination, the study results inform the selection of target groups in need of particular psychosocial interventions to overcome their vaccine hesitancy.

  15. f

    Recommendations for policy and practice.

    • plos.figshare.com
    xls
    Updated Mar 18, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Marisa Casale; Oluwaseyi Somefun; Genevieve Haupt Ronnie; Joshua Sumankuuro; Olagoke Akintola; Lorraine Sherr; Lucie Cluver (2025). Recommendations for policy and practice. [Dataset]. http://doi.org/10.1371/journal.pgph.0003795.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Mar 18, 2025
    Dataset provided by
    PLOS Global Public Health
    Authors
    Marisa Casale; Oluwaseyi Somefun; Genevieve Haupt Ronnie; Joshua Sumankuuro; Olagoke Akintola; Lorraine Sherr; Lucie Cluver
    License

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

    Description

    Covid-19 vaccine hesitancy among young people can be seen as an acute – but not isolated – phenomenon within an alarming longer-term trend of broader vaccine distrust in Africa. Yet there are still considerable knowledge gaps in relation to the scope and drivers of low vaccine acceptability among young people. Moreover, better frameworks and tools are needed to conceptualise and better understand acceptability in this population group. We applied the recently published Accelerate Framework for Young People’s Acceptability to guide qualitative research with young people living in South Africa and Nigeria. We aimed to investigate their overall acceptability of the Covid-19 vaccine, and explore factors shaping this acceptability and willingness to be vaccinated. In collaboration with seven community-based organisation partners, we conducted 12 in-person focus groups and 36 remote interviews with 163 individuals aged 15-24. Through a collaborative, iterative process we conducted thematic analysis, incorporating aspects of both deductive and inductive approaches. Our findings show how vaccine acceptability is shaped by a multiplicity of inter-related factors. They also provide a more in-depth perspective of some of these phenomena, their relative importance and their connections in this group of young people. Limited vaccine understanding, conflicting information and distrust, the influence of others, and fear of side effects were key inter-related drivers of low vaccine acceptability. Factors promoting Covid-19 vaccine acceptability were instead: positive perceptions of vaccine safety and efficacy, protection from disease, protection of others, and a desire to return to normal activity. We discuss implications of these findings for policy and practice, both to increase acceptability of Covid-19 vaccination among young people, and more broadly promote vaccination as a critical component of public health programs. Lastly, we reflect on this first application of theAccelerate Framework, and implications for its use in future studies.

  16. Vaccines for children: COVID-19

    • open.canada.ca
    • ouvert.canada.ca
    html
    Updated Aug 31, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Public Health Agency of Canada (2021). Vaccines for children: COVID-19 [Dataset]. https://open.canada.ca/data/dataset/79aa046a-a49f-4c76-a744-5e715fc006bd
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Aug 31, 2021
    Dataset provided by
    Public Health Agency Of Canadahttp://www.phac-aspc.gc.ca/
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    Vaccines are essential to help end the pandemic. It's important for everyone to get vaccinated against COVID-19 when it's their turn. Vaccines help lower your child's risk of infection. They work with the body's natural defenses to develop protection against a disease. Being vaccinated will prevent the disease or lessen its impact. Health Canada has authorized the Pfizer BioNTech COVID-19 vaccine for youth aged 12 and older. People aged 12 to 17 may receive the same 2-dose schedule recommended for adults.

  17. Coronavirus (COVID-19) vaccination uptake in school pupils, England

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Sep 23, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Office for National Statistics (2022). Coronavirus (COVID-19) vaccination uptake in school pupils, England [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/healthandwellbeing/datasets/coronavirusvaccinationuptakeinchildrenandyoungpeopleengland
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Sep 23, 2022
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England
    Description

    Figures on coronavirus (COVID-19) vaccine uptake in school pupils aged 12 to 17 years attending state-funded secondary, sixth form and special schools, broken down by demographic and geographic characteristics, using a linked English Schools Census and National Immunisation Management System dataset. Experimental Statistics.

  18. Young adults who wanted a COVID-19 vaccination and received it worldwide...

    • statista.com
    Updated Nov 29, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2023). Young adults who wanted a COVID-19 vaccination and received it worldwide 2021 [Dataset]. https://www.statista.com/statistics/1261436/share-of-adults-who-wanted-vaccination-against-covid-and-received-it/
    Explore at:
    Dataset updated
    Nov 29, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Sep 14, 2021 - Sep 20, 2021
    Area covered
    Worldwide
    Description

    As of September 2021, around 62 percent of adults in Australia aged 18 to 34 years who wanted a vaccination against COVID-19 had received one, which is a much lower rate than in Canada where 95 percent of adults who wanted a vaccination had already had one. This statistic illustrates the percentage of adults aged 18 to 34 years who had been vaccinated against COVID-19 among those who wanted to get vaccinated worldwide as of September 2021, by country.

  19. m

    Attitudes of a Sample of Middle Eastern Young Adults toward Different...

    • data.mendeley.com
    Updated Mar 2, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Walid Al-Qerem (2021). Attitudes of a Sample of Middle Eastern Young Adults toward Different Available COVID-19 Vaccines [Dataset]. http://doi.org/10.17632/vpm6m3fkcp.1
    Explore at:
    Dataset updated
    Mar 2, 2021
    Authors
    Walid Al-Qerem
    License

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

    Area covered
    Middle East
    Description

    The attached data were gathered to evaluate the attitudes of a sample of Middle Eastern young adults toward different available COVID-19 vaccines

  20. c

    COVID-19 Vaccine Hesitancy Beliefs and Conspiracy Theory

    • figshare.cardiffmet.ac.uk
    jar
    Updated Jun 3, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Delyth James (2025). COVID-19 Vaccine Hesitancy Beliefs and Conspiracy Theory [Dataset]. http://doi.org/10.25401/cardiffmet.29222120.v1
    Explore at:
    jarAvailable download formats
    Dataset updated
    Jun 3, 2025
    Dataset provided by
    Cardiff Metropolitan University
    Authors
    Delyth James
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Description

    This small study describes the relationships between vaccine beliefs and adherence behaviours in young people aged 18 to 25 years old.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2021). Number of COVID-19 cases among young people in the U.S. from Mar. to Dec. 2020 by age [Dataset]. https://www.statista.com/statistics/1211937/number-of-young-persons-who-tested-positive-for-covid-19-by-age/
Organization logo

Number of COVID-19 cases among young people in the U.S. from Mar. to Dec. 2020 by age

Explore at:
Dataset updated
Feb 24, 2021
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

From March to December 2020, around 2.9 million children and adults aged 0 to 24 years tested positive for COVID-19 in the United States. This statistic illustrates the number of persons aged 0 to 24 years who tested positive for COVID-19 in the United States from March to December 2020, by age.

Search
Clear search
Close search
Google apps
Main menu