Higher COVID-19 Vaccination Rates among Unemployed in the United States: State Level Study in the First 100 days of Vaccine Initiation

  1. Ali Roghani
  2. Samin Panahi

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Abstract

Background

Socioeconomic factors may impact the efficiency of COVID vaccine rollout; however, there are limited studies that examine how state socioeconomic status influences the speed of vaccine distribution. This study aimed to demonstrate how employment rates as one of the main socioeconomic factors affect vaccine coverage in 50 states of the United States.

Methods

This study has obtained vaccine data for the 50 states in the United States, available in the electronic online database ourworldindata.org. In addition to employment rates, other socioeconomic determinants including poverty level, uninsured rates, population density, homeownership, educational level, the percentage of the elderly population, and educational level were obtained from ourworldindata.org data platform. Data from these 50 states were used for regression analyses to examine the relationship between socioeconomic and vaccination rates.

Results

Our study revealed a positive linear association between unemployment and vaccine rates, and states with higher unemployment rates were more likely to have higher vaccination rates. However, other socioeconomic measures do not significantly associate with vaccine coverage.

Conclusion

Despite other studies showing that vulnerable populations had lower vaccine rates, this study shows that states with higher unemployment rates are more likely to be vaccinated. However, the finding suggests a need for more research for the states with higher than 5% unemployment rates, as they had a lower vaccine coverage than states with a range of 4% to 5% unemployment rates.

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  1. ScreenIT

    SciScore for 10.1101/2021.04.17.21255668: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    This study has some limitations. First, due to prioritizing a specific population for vaccination, the results might be influenced and prioritized for the elderly, occupational exposures, and people who have higher risks. Second, these associations are based on the overall information of each state, while individual-level data for each state could determine vulnerability in more detail.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    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.

    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.

  2. Version published to 10.1101/2021.04.17.21255668v1 on medRxiv