Are Vapers More Susceptible to COVID-19 Infection?

  1. Dongmei Li
  2. Daniel P. Croft
  3. Deborah J. Ossip
  4. Zidian Xie

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Abstract

Background

COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was declared a global pandemic in March 2020. Electronic cigarette use (vaping) rapidly gained popularity in the US in recent years. Whether electronic cigarette users (vapers) are more susceptible to COVID-19 infection is unknown.

Methods

Using integrated data in each US state from the 2018 Behavioral Risk Factor Surveillance System (BRFSS), United States Census Bureau and the 1Point3Acres.com website, generalized estimating equation (GEE) models with negative binomial distribution assumption and log link functions were used to examine the association of weighted proportions of vapers with number of COVID-19 infections and deaths in the US.

Results

The weighted proportion of vapers who used e-cigarettes every day or some days ranged from 2.86% to 6.42% for US states. Statistically significant associations were observed between the weighted proportion of vapers and number of COVID-19 infected cases as well as COVID-19 deaths in the US after adjusting for the weighted proportion of smokers and other significant covariates in the GEE models. With every one percent increase in weighted proportion of vapers in each state, the number of COVID-19 infected cases increase by 0.3139 (95% CI: 0.0554 –0.5723) and the number of COVID-19 deaths increase by 0.3705 (95% CI: 0.0623 – 0.6786) in log scale in each US state.

Conclusions

The positive associations between the proportion of vapers and the number of COVID-19 infected cases and deaths in each US state suggest an increased susceptibility of vapers to COVID-19 infections and deaths.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.05.20092379: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Outcomes and Covariates: The outcomes used in current analysis are the number of COVID-19 infected cases and deaths
    Covariates
    suggested: None
    All statistical analyses were conducted using statistical analysis software SAS version 9.4 (SAS Institute Inc.
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    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: We detected the following sentences addressing limitations in the study:
    There are several limitations in current study. One limitation is that the weighted proportions of vapers, smokers, and other demographic and chronic diseases are from the 2018 BRFSS data, which might differ from the 2020 estimates. The reported COVID-19 infected cases and deaths obtained from 1Point3Acres.com website could be subject to some reporting errors as we noticed some negative number of COVID-19 infected cases and deaths, which we excluded from further analysis. However, we compared the COVID-19 data obtained from 1Point3Acres.com website with the COVID-19 data from the New York Times 36 and Centers for Disease Control and Prevention (CDC) website 37 and found consistent numbers of COVID-19 infections and deaths, which increased the robustness and reliability of the data sources. Another limitation is that our current analysis is on state level instead of individual level. We don’t know the individual status of vaping and COVID-19 infections or deaths, thus estimated coefficients of association could be different from epidemiological or clinical studies on individual subjects.

    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 10.1101/2020.05.05.20092379 on medRxiv