America Addresses Two Epidemics – Cannabis and Coronavirus and their Interactions: An Ecological Geospatial Study

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Abstract

Importance

Covid-19 infection has major international health and economic impacts and risk factors for infection are not completely understood. Cannabis smoking is linked with poor respiratory health, immunosuppression and multiple contaminants. Potential synergism between the two epidemics would represent a major public health convergence. Cigarettes were implicated with disease severity in Wuhan, China.

Objective

Is cannabis use epidemiologically associated with coronavirus incidence rate (CVIR)?

Design

Cross-sectional state-based multivariable study.

Setting

USA.

Primary and Secondary Outcome Measures

CVIR. Multivariable-adjusted geospatially-weighted regression models. As the American cannabis epidemic is characterized by a recent doubling of daily cannabis use it was considered important to characterize the contribution of high intensity use.

Results

Significant associations of daily cannabis use quintile with CVIR were identified with the highest quintile having a prevalence ratio 5.11 (95%C.I. 4.90-5.33), an attributable fraction in the exposed (AFE) 80.45% (79.61-81.25%) and an attributable fraction in the population of 77.80% (76.88-78.68%) with Chi-squared-for-trend (14,782, df=4) significant at P<10 −500 . Similarly when cannabis legalization was considered decriminalization was associated with an elevated CVIR prevalence ratio 4.51 (95%C.I. 4.45-4.58), AFE 77.84% (77.50-78.17%) and Chi-squared-for-trend (56,679, df=2) significant at P<10 −500 . Monthly and daily use were linked with CVIR in bivariate geospatial regression models (P=0.0027, P=0.0059). In multivariable additive models number of flight origins and population density were significant. In interactive geospatial models adjusted for international travel, ethnicity, income, population, population density and drug use, terms including last month cannabis were significant from P=7.3×10 −15 , daily cannabis use from P=7.3×10 −11 and last month cannabis was independently associated (P=0.0365).

Conclusions and Relevance

Data indicate CVIR demonstrates significant trends across cannabis use intensity quintiles and with relaxed cannabis legislation. Recent cannabis use is independently predictive of CVIR in bivariate and multivariable adjusted models and intensity of use is interactively significant. Cannabis thus joins tobacco as a SARS2-CoV-2 risk factor.

Article Summary

Strengths and Limitations of this Study

  • Population level was used for the large datasets employed relating to international travel, Covid-19 rates and drug exposure.

  • Nationally representative datasets were employed for drug use and exposure

  • A Broad range of covariates was considered including socioeconomic, demographic, drug use, Covid-19 incidence and international travel.

  • Advanced geospatial modelling techniques were used to analyze data.

  • Higher resolution geospatial data was not available to this study.

Note

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Key Points

Question

Since cannabis is immunosuppressive and is frequently variously contaminated, is its use associated epidemiologically with coronavirus infection rates?

Findings

Geospatial analytical techniques were used to combine coronavirus incidence, drug and cannabinoid use, population, ethnicity, international flight and income data. Cannabis use and daily cannabis use were associated with coronavirus incidence on both bivariate regression and after multivariable spatial regression with high levels of statistical significance. Cannabis use quintiles and cannabis legal status were also highly significant.

Meaning

Significant geospatial statistical associations were shown between cannabis use and coronavirus infection rates consistent with immunomodulatory mechanistic reports and environmental exposure concerns.

BMJ

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Article activity feed

  1. SciScore for 10.1101/2020.04.17.20069021: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics: This study was approved by the Human Research Ethics Committee of the University of Western Australia on 31st March 2020 (No. RA/4/20/4724).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistics: Data was processed in RStudio version 1.2.1335 based on R version 3.6.1 on 1st April 2020.
    RStudio
    suggested: (RStudio, RRID:SCR_000432)

    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:
    This report has several strengths and limitations. Our study is timely, and uses a current dataset for CVIR. The study uses a well validated nationally representative drug use dataset, which is widely studied and extensively quoted. Importantly we use two metrics of cannabis use including one which provides a measure of daily (or near daily) cannabis use, which has been shown to be the major parameter of American cannabis consumption 27. We use a very large dataset of international flight arrivals into USA which captures the whole population of these events over a 12 month period. US Census Bureau data is used to source state population, income and ethnicity data from the well validated American Community Survey. Our analysis reaches similar conclusions by several different pathways in both bivariate and multivariable analyses. There is good concordance between models utilizing the spml, spgm and spreml geospatial algorithms. All our major results are at very high levels of statistical significance. The limitations of our study relate to its uncontrolled design. Case control studies cannot be considered in such situations since it is unethical to expose patients to a real risk of mortality in the absence of definitive treatment or vaccination (at the time of writing). Moreover our results are spatially restricted to state level data. For example upstate New York is very rural, but Manhattan is one of the most densely populated places on the planet. The broader geospatial leve...

    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.