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Analysis of a Vaping-Associated Lung Injury Outbreak through Participatory Surveillance and Archival Internet Data

Author

Listed:
  • Yulin Hswen

    (Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA 94158, USA
    Bakar Computational Health Sciences Institute, University of California at San Francisco, San Francisco, CA 94143, USA
    Innovation Program, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA)

  • Elad Yom-Tov

    (Microsoft Research Israel, 3 Alan Turing Str., Herzeliya 4672415, Israel
    Faculty of Industrial Engineering and Management, Technion, Haifa 3200000, Israel)

Abstract

The US Centers for Disease Control and Prevention alerted of a suspected outbreak of lung illness associated with using E-cigarette products in September 2019. At the time that the CDC published its alert little was known about the causes of the outbreak or who was at risk for it. Here we provide insights into the outbreak through analysis of passive reporting and participatory surveillance. We collected data about vaping habits and associated adverse reactions from four data sources pertaining to people in the USA: A participatory surveillance platform (YouVape), Reddit, Google Trends, and Bing. Data were analyzed to identify vaping behaviors and reported adverse events. These were correlated among sources and with prior reports. Data was obtained from 720 YouVape users, 4331 Reddit users, and over 1 million Bing users. Large geographic variation was observed across vaping products. Significant correlation was found among the data sources in reported adverse reactions. Models of participatory surveillance data found specific product and adverse reaction associations. Specifically, cannabidiol was found to be associated with fever, while tetrahydrocannabinol was found to be correlated with diarrhea. Our results demonstrate that utilization of different, complementary, online data sources provide a holistic view of vaping associated lung injury while augmenting traditional data sources.

Suggested Citation

  • Yulin Hswen & Elad Yom-Tov, 2021. "Analysis of a Vaping-Associated Lung Injury Outbreak through Participatory Surveillance and Archival Internet Data," IJERPH, MDPI, vol. 18(15), pages 1-17, August.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:15:p:8203-:d:607297
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    References listed on IDEAS

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    1. Lei Wang & Yongcheng Zhan & Qiudan Li & Daniel D. Zeng & Scott J. Leischow & Janet Okamoto, 2015. "An Examination of Electronic Cigarette Content on Social Media: Analysis of E-Cigarette Flavor Content on Reddit," IJERPH, MDPI, vol. 12(11), pages 1-20, November.
    2. Lazer, David & Ryan Kennedy & Gary King & Alessandro Vespignani, 2014. "Google Flu Trends Still Appears Sick: An Evaluation of the 2013?2014 Flu Season," Working Paper 155056, Harvard University OpenScholar.
    3. Smolinski, M.S. & Crawley, A.W. & Baltrusaitis, K. & Chunara, R. & Olsen, J.M. & Wójcik, O. & Santillana, M. & Nguyen, A. & Brownstein, J.S., 2015. "Flu near you: Crowdsourced symptom reporting spanning 2 influenza seasons," American Journal of Public Health, American Public Health Association, vol. 105(10), pages 2124-2130.
    4. Matthew Gentzkow & Jesse M. Shapiro, 2011. "Ideological Segregation Online and Offline," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(4), pages 1799-1839.
    5. Kaitlin L. Costello & John D. Martin III & Ashlee Edwards Brinegar, 2017. "Online disclosure of illicit information: Information behaviors in two drug forums," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(10), pages 2439-2448, October.
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