4 datasets found
  1. f

    Table_1_Predictive factors of coronavirus disease (COVID-19) vaccination...

    • datasetcatalog.nlm.nih.gov
    • frontiersin.figshare.com
    Updated Feb 29, 2024
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    Nakano, Takashi; Hara, Megumi; Hirota, Yoshio; Kobayashi, Takaomi; Tokiya, Mikiko; Matsumoto, Akiko (2024). Table_1_Predictive factors of coronavirus disease (COVID-19) vaccination series completion: a one-year longitudinal web-based observational study in Japan.DOCX [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001279560
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    Dataset updated
    Feb 29, 2024
    Authors
    Nakano, Takashi; Hara, Megumi; Hirota, Yoshio; Kobayashi, Takaomi; Tokiya, Mikiko; Matsumoto, Akiko
    Area covered
    Japan
    Description

    IntroductionAddresing vaccine hesitancy is considered an important goal in management of the COVID-19 pandemic. We sought to understand what factors influenced people, especially those initially hesitant, to receive two or more vaccine doses within a year of the vaccine’s release.MethodsWe conducted longitudinal Web-based observational studies of 3,870 individuals. The surveys were conducted at four different time points: January 2021, June 2021, September 2021, and December 2021. In the baseline survey (January 2021), we assessed vaccination intention (i.e., “strongly agree” or “agree” [acceptance], “neutral” [not sure], and “disagree” or “strongly disagree” [hesitance]), and assumptions about coronavirus disease (COVID-19), COVID-19 vaccine, COVID-19-related health preventive behavior, and COVID-19 vaccine reliability. In subsequent surveys (December 2021), we assessed vaccination completion (i.e., ≥2 vaccinations). To investigate the relationship between predictors of COVID-19 vaccination completion, a multivariable logistic regression model was applied. Adjusted odds ratios (AORs) and 95% confidence intervals (CIs) were calculated while adjusting for gender, age, marital status, presence of children, household income category, and presence of diseases under treatment. In a stratified analysis, predictors were determined based on vaccination intention.ResultsApproximately 96, 87, and 72% of those who demonstrated acceptance, were not sure, or hesitated had been vaccinated after 1 year, respectively. Overall, significant factors associated with COVID-19 vaccine compliance included the influence of others close to the index participant (social norms) (AOR, 1.80; 95% CI, 1.56–2.08; p < 0.001), vaccine confidence (AOR, 1.39; 95% CI, 1.18–1.64; p < 0.001) and structural constraints (no time, inconvenient location of medical institutions, and other related factors) (AOR, 0.80; 95% CI, 0.70–0.91; p = 0.001). In the group of individuals classified as hesitant, significant factors associated with COVID-19 vaccine compliance included social norms (AOR, 2.43; 95% CI, 1.83–3.22; p < 0.001), confidence (AOR, 1.44; 95% CI, 1.10–1.88; p = 0.008), and knowledge (AOR, 0.69; 95% CI, 0.53–0.88; p = 0.003).DiscussionWe found that dissemination of accurate information about vaccines and a reduction in structural barriers to the extent possible enhanced vaccination rates. Once the need for vaccination becomes widespread, it becomes a social norm, and further improvements in these rates can then be anticipated. Our findings may help enhance vaccine uptake in the future.

  2. Dataset and code for "Evaluating the COVID-19 vaccination program in Japan,...

    • zenodo.org
    csv
    Updated Apr 19, 2025
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    Hiroshi Nishiura; Hiroshi Nishiura (2025). Dataset and code for "Evaluating the COVID-19 vaccination program in Japan, 2021 using the counterfactual reproduction number" in Scientific Reports 2023 Oct 18;13(1):17762. doi: 10.1038/s41598-023-44942-6. [Dataset]. http://doi.org/10.5281/zenodo.15244462
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    csvAvailable download formats
    Dataset updated
    Apr 19, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Hiroshi Nishiura; Hiroshi Nishiura
    License

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

    Description

    - The dataset and R-code for the quoted article in Scientific Reports are provided.

    The datasets that are described either in the main text or supplemantary material and are the following:

    File 1. Vaccination coverage by age and time (from vaccine registration system)

    File 2. See below (not available)

    File 3. Next generation matrix from fouth wave in Osaka prefecture

    FIle 4 Google mobility data

    File 5. Time series proportion of Delta variant out of screened SARS-CoV-2 viruses.

    File 6. Consecutive holidays (dummy variables)

    File 7. Cumulative vaccination coverage by age and time (with 7-day moving average)

    File 8. Parameters for describing File 7 using a logistic curve.

    Files 9, 10 and 11. Scenarios of vaccination program (i.e., early, late and young; described as the absolute numbers vaccinated)

    -According to our national law, it is not accepted to share the surveillance data (raw data) other than the way that is publicly shared via periodicals published by the National Institute of Infectious Diseases such as Infectious Disease Weekly Reports (IDWR) which follows the Infectious Disease Control Law. The epidemiological dataset for research use is granted following the scheme of data sharing for third persons adhering to Infectious Disease Control Law. This would allow recovering File 2 by the audience. For that purpose, people need to obtain an approval by submitting an application document to the National Institute of Infectious Diseases, Japan Institute for Health Security.
    To access to the epidemiological data, we advise interested audience to apply for the sharing via above quoted link.
  3. f

    Table_1_Potential Triggers for Thrombocytopenia and/or Hemorrhage by the...

    • figshare.com
    • frontiersin.figshare.com
    xlsx
    Updated May 30, 2023
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    Yusuke Okada; Ryota Sakai; Marie Sato-Fitoussi; Marika Nodera; Shoichi Yoshinaga; Akiko Shibata; Takahiko Kurasawa; Tsuneo Kondo; Koichi Amano (2023). Table_1_Potential Triggers for Thrombocytopenia and/or Hemorrhage by the BNT162b2 Vaccine, Pfizer-BioNTech.XLSX [Dataset]. http://doi.org/10.3389/fmed.2021.751598.s002
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    xlsxAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Frontiers
    Authors
    Yusuke Okada; Ryota Sakai; Marie Sato-Fitoussi; Marika Nodera; Shoichi Yoshinaga; Akiko Shibata; Takahiko Kurasawa; Tsuneo Kondo; Koichi Amano
    License

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

    Description

    Immune thrombocytopenia is an autoimmune disease that can cause bleeding in severe cases. Although available published data do not associate the BNT162b2 vaccine (Pfizer-BioNTech) with the risk of developing thrombocytopenia, the ChAdOx1 nCov-19 vaccine has raised concerns about its potential link with thrombosis and thrombocytopenia. We would like to clarify whether the BNT162b2 vaccine administration may interfere with pre-existing conditions and whether it may cause a risk of thrombocytopenia. Herein, we report three cases of post-vaccine thrombocytopenia among patients with rheumatoid arthritis (RA); one case in which a causal relationship cannot be ruled out with the BNT162b2 vaccine was officially announced. Furthermore, we reviewed reports of adverse events and death cases with a focus on thrombocytopenia and hemorrhages, following vaccination with BNT162b2 in Japan between February 17, 2021 and July 16, 2021, as reported by the Ministry of Health, Labour, and Welfare within the general population. The three cases in this report share the common features of old age, RA, chronic renal failure or hypertension, and pre-existing mild thrombocytopenia at baseline. A total of 746 death cases were reported during this time period, with death by bleeding accounting for 8.8% of the total deaths, of which 84.8% were cranial and statistically higher in young women than among elderly women. The risk-benefit ratio of the vaccine needs to be reconsidered based on high- and low-risk population types and ethnicity. To do so, the expansion of the pharmacovigilance system for BNT162b2 vaccination is urgently required worldwide.

  4. Crude and adjusted odds ratios of having no intention to vaccine their child...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 8, 2023
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    Sayaka Horiuchi; Haruka Sakamoto; Sarah K. Abe; Ryoji Shinohara; Megumi Kushima; Sanae Otawa; Hideki Yui; Yuka Akiyama; Tadao Ooka; Reiji Kojima; Hiroshi Yokomichi; Kunio Miyake; Takashi Mizutani; Zentaro Yamagata (2023). Crude and adjusted odds ratios of having no intention to vaccine their child (N = 1,200). [Dataset]. http://doi.org/10.1371/journal.pone.0261121.t003
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    xlsAvailable download formats
    Dataset updated
    Jun 8, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Sayaka Horiuchi; Haruka Sakamoto; Sarah K. Abe; Ryoji Shinohara; Megumi Kushima; Sanae Otawa; Hideki Yui; Yuka Akiyama; Tadao Ooka; Reiji Kojima; Hiroshi Yokomichi; Kunio Miyake; Takashi Mizutani; Zentaro Yamagata
    License

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

    Description

    Crude and adjusted odds ratios of having no intention to vaccine their child (N = 1,200).

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Nakano, Takashi; Hara, Megumi; Hirota, Yoshio; Kobayashi, Takaomi; Tokiya, Mikiko; Matsumoto, Akiko (2024). Table_1_Predictive factors of coronavirus disease (COVID-19) vaccination series completion: a one-year longitudinal web-based observational study in Japan.DOCX [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001279560

Table_1_Predictive factors of coronavirus disease (COVID-19) vaccination series completion: a one-year longitudinal web-based observational study in Japan.DOCX

Explore at:
Dataset updated
Feb 29, 2024
Authors
Nakano, Takashi; Hara, Megumi; Hirota, Yoshio; Kobayashi, Takaomi; Tokiya, Mikiko; Matsumoto, Akiko
Area covered
Japan
Description

IntroductionAddresing vaccine hesitancy is considered an important goal in management of the COVID-19 pandemic. We sought to understand what factors influenced people, especially those initially hesitant, to receive two or more vaccine doses within a year of the vaccine’s release.MethodsWe conducted longitudinal Web-based observational studies of 3,870 individuals. The surveys were conducted at four different time points: January 2021, June 2021, September 2021, and December 2021. In the baseline survey (January 2021), we assessed vaccination intention (i.e., “strongly agree” or “agree” [acceptance], “neutral” [not sure], and “disagree” or “strongly disagree” [hesitance]), and assumptions about coronavirus disease (COVID-19), COVID-19 vaccine, COVID-19-related health preventive behavior, and COVID-19 vaccine reliability. In subsequent surveys (December 2021), we assessed vaccination completion (i.e., ≥2 vaccinations). To investigate the relationship between predictors of COVID-19 vaccination completion, a multivariable logistic regression model was applied. Adjusted odds ratios (AORs) and 95% confidence intervals (CIs) were calculated while adjusting for gender, age, marital status, presence of children, household income category, and presence of diseases under treatment. In a stratified analysis, predictors were determined based on vaccination intention.ResultsApproximately 96, 87, and 72% of those who demonstrated acceptance, were not sure, or hesitated had been vaccinated after 1 year, respectively. Overall, significant factors associated with COVID-19 vaccine compliance included the influence of others close to the index participant (social norms) (AOR, 1.80; 95% CI, 1.56–2.08; p < 0.001), vaccine confidence (AOR, 1.39; 95% CI, 1.18–1.64; p < 0.001) and structural constraints (no time, inconvenient location of medical institutions, and other related factors) (AOR, 0.80; 95% CI, 0.70–0.91; p = 0.001). In the group of individuals classified as hesitant, significant factors associated with COVID-19 vaccine compliance included social norms (AOR, 2.43; 95% CI, 1.83–3.22; p < 0.001), confidence (AOR, 1.44; 95% CI, 1.10–1.88; p = 0.008), and knowledge (AOR, 0.69; 95% CI, 0.53–0.88; p = 0.003).DiscussionWe found that dissemination of accurate information about vaccines and a reduction in structural barriers to the extent possible enhanced vaccination rates. Once the need for vaccination becomes widespread, it becomes a social norm, and further improvements in these rates can then be anticipated. Our findings may help enhance vaccine uptake in the future.

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