Vaccine hesitancy for coronavirus SARS-CoV-2 in Varanasi India

  1. Utkarsh Srivastava
  2. Avanish Kumar Tripathi
  3. Jagjeet Kaur
  4. Sabita Devi
  5. Shipra Verma
  6. Vanya Singh
  7. Debashruti Das
  8. Prajjval Pratap Singh
  9. Rahul Kumar Mishra
  10. Nikhil A. Kumar
  11. Vijaya Nath Mishra
  12. Pradeep Kumar
  13. Vandana Rai
  14. Rakesh Tamang
  15. Prashanth Suravajhala
  16. Rakesh Pandey
  17. Gyaneshwer Chaubey

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Abstract

With the rollout of the world's largest vaccine drive for SARS-CoV-2 by the Government of India on January 16 2021, India had targeted to vaccinate its entire population by the end of 2021. Struggling with vaccine procurement and production earlier, India overcome these hurdles, but the Indian population still did not seem to be mobilizing swiftly toward vaccination centers. The severe second wave has slowed the vaccination pace and was also one of the major contributing factors to vaccine hesitancy. To understand the nature of vaccine hesitancy and its underlying factors, we conducted extensive online and offline surveys in Varanasi and adjoining regions using structured questions. Most respondents were students (0.633). However, respondents from other occupations, such as government officials (0.10), have also participated in the study. Interestingly, most people (0.75) relied on fake news and did not take COVID-19 seriously. Most importantly, we noticed that a substantial proportion of respondents (relative frequency 0.151; mean age 24.8 years) reported that they were still not interested in vaccination. We observed a significant association between vaccine hesitancy and socioeconomic status (χ 2 = 307.6, p < 0.001). However, we failed to detect any association between vaccine hesitancy and gender (χ 2 = 0.007, p > 0.5). People who have neither been vaccinated nor have ever been infected may become the medium for spreading the virus and creating new variants, which may lead to the vaccine-resistant variant. We expect this extensive survey to help the Government upgrade their vaccination policies for COVID-19 in North India.

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  1. Version published to 10.3389/fpubh.2022.892584
  2. ScreenIT

    SciScore for 10.1101/2021.10.24.21265455: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: The study has been approved by the Ethical committees of Banaras Hindu University, Varanasi and VBS Purvanchal University, Jaunpur, India.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.10.24.21265455v1 on medRxiv