Examining the Relationship between COVID-19 Vaccinations and Reported Incidence

  1. Enbal Shacham
  2. Stephen Scroggins
  3. Alexander Garza

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Abstract

As COVID-19 has caused significant morbidity and mortality throughout the world, the development and distribution of an effective vaccine have been swift but not without challenges. Earlier demand and access barriers have seemingly been addressed with more free and accessible vaccines now available for a wide variety of ages. While rates of COVID-19 have decreased overall, some geographic areas continue to experience rapid outbreaks. The purpose of this study was to examine the relationship between vaccination uptake and weekly COVID-19 cases throughout locations in the state of Missouri.

Methods

Among all Missouri counties and two cities (n=117), weekly COVID-19 incidence and cumulative proportion of residents fully vaccinated were abstracted from the Missouri Department of Health and Senior Services during a 25-week period from January 4 to Jun 26, 2021. Additional ecological variables known to be associated with COVID-19 incidence and prevalence were collected from the U.S. Census Bureau and integrated into data: total population, proportion of nonwhite residents, annual median household income, proportion of residents working in public facing occupations. Descriptive and inferential statistics were completed which included the calculation of both linear and nonlinear models using repeated measure data to determine the quantitative association between vaccination uptake and reported COVID-19 cases in the presence of location characteristics.

Results

Throughout the 25 weeks of observations, the average weekly number of COVID-19 cases reported was 66.1 (SD=260.8) while the average cumulative proportion vaccinated individuals at the end of the 25 weeks was 25.8% (SD=6.8%) among study locations. While graphing seemed to suggest a more nonlinear relationship between COVID-19 incidence and proportion vaccinated, comparison of crude linear and nonlinear models pointed to the relationship likely being linear during study period. The final adjusted linear model exhibited a significant relationship between COVID-19 cases and proportion vaccinated, specifically every percent increase in population vaccinated resulted in 3 less weekly COVID-19 cases being reported (β -3.74, p<0.001. Additionally, when controlling for other factors, the adjusted model revealed locations with higher proportions of nonwhite residents were likely to experience less weekly COVID-19 cases (β -1.48, p=0.037).

Discussion

Overall, this study determined that increasing the proportion of residents vaccinated decreases COIVD-19 cases by a substantial amount over time. These findings provide insights into possible messaging strategies that can be leveraged to develop more effective implementation and uptake. As the COVID-19 pandemic persists and vaccination numbers begin to plateau, diverse communication strategies become a critical necessity to reach a wider population.

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  1. ScreenIT

    SciScore for 10.1101/2021.06.30.21259794: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: All ethical guidelines were followed according to the Helsinki Declaration and design and protocols was determined exempt by Institutional Review Board.
    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 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.

    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.

  2. Version published to 10.1101/2021.06.30.21259794v1 on medRxiv