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Flu near you: Crowdsourced symptom reporting spanning 2 influenza seasons

Author

Listed:
  • Smolinski, M.S.
  • Crawley, A.W.
  • Baltrusaitis, K.
  • Chunara, R.
  • Olsen, J.M.
  • Wójcik, O.
  • Santillana, M.
  • Nguyen, A.
  • Brownstein, J.S.

Abstract

Objectives. We summarized Flu Near You (FNY) data from the 2012?2013 and 2013?2014 influenza seasons in the United States. Methods. FNY collects limited demographic characteristic information upon registration, and prompts users each Monday to report symptoms of influenzalike illness (ILI) experienced during the previous week. We calculated the descriptive statistics and rates of ILI for the 2012?2013 and 2013?2014 seasons. We compared raw and noise-filtered ILI rates with ILI rates from the Centers for Disease Control and Prevention ILINet surveillance system. Results. More than 61 000 participants submitted at least 1 report during the 2012?2013 season, totaling 327 773 reports. Nearly 40 000 participants submitted at least 1 report during the 2013?2014 season, totaling 336 933 reports. Rates of ILI as reported by FNY tracked closely with ILINet in both timing and magnitude. Conclusions. With increased participation, FNY has the potential to serve as a viable complement to existing outpatient, hospital-based, and laboratory surveillance systems. Although many established systems have the benefits of specificity and credibility, participatory systems offer advantages in the areas of speed, sensitivity, and scalability.

Suggested Citation

  • 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.
    • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2015.302696_9
    DOI: 10.2105/AJPH.2015.302696
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    Cited by:

    1. William E. Allen & Han Altae-Tran & James Briggs & Xin Jin & Glen McGee & Andy Shi & Rumya Raghavan & Mireille Kamariza & Nicole Nova & Albert Pereta & Chris Danford & Amine Kamel & Patrik Gothe & Evr, 2020. "Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing," Nature Human Behaviour, Nature, vol. 4(9), pages 972-982, September.
    2. Silke Schwarz & David D. Martin & Arndt Büssing & Olga Kulikova & Hanno Krafft & Moritz Gwiasda & Sara Hamideh Kerdar & Ingo Fingerhut & Ekkehart Jenetzky, 2021. "Sociodemographic Characteristics and Interests of FeverApp Users," IJERPH, MDPI, vol. 18(6), pages 1-13, March.
    3. Florence Neymotin, 2021. "Risky behaviour and non-vaccination," Journal of Bioeconomics, Springer, vol. 23(2), pages 151-161, July.
    4. Andrew Perrault & Marie Charpignon & Jonathan Gruber & Milind Tambe & Maimuna Majumder, 2020. "Designing Efficient Contact Tracing Through Risk-Based Quarantining," NBER Working Papers 28135, National Bureau of Economic Research, Inc.
    5. Kennedy, Ryan & Mahajan, Aseem & Urpelainen, Johannes, 2020. "Crowdsourcing data on the reliability of electricity service: Evidence from a telephone survey in Uttar Pradesh, India," Energy Policy, Elsevier, vol. 145(C).
    6. Kuchler, Theresa & Russel, Dominic & Stroebel, Johannes, 2022. "JUE Insight: The geographic spread of COVID-19 correlates with the structure of social networks as measured by Facebook," Journal of Urban Economics, Elsevier, vol. 127(C).
    7. Sasikiran Kandula & Jeffrey Shaman, 2019. "Reappraising the utility of Google Flu Trends," PLOS Computational Biology, Public Library of Science, vol. 15(8), pages 1-16, August.
    8. 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.
    9. Jingwei Li & Choon-Ling Sia & Zhuo Chen & Wei Huang, 2021. "Enhancing Influenza Epidemics Forecasting Accuracy in China with Both Official and Unofficial Online News Articles, 2019–2020," IJERPH, MDPI, vol. 18(12), pages 1-13, June.
    10. David C Farrow & Logan C Brooks & Sangwon Hyun & Ryan J Tibshirani & Donald S Burke & Roni Rosenfeld, 2017. "A human judgment approach to epidemiological forecasting," PLOS Computational Biology, Public Library of Science, vol. 13(3), pages 1-19, March.
    11. Salvatore Pirri & Valentina Lorenzoni & Gianni Andreozzi & Marta Mosca & Giuseppe Turchetti, 2020. "Topic Modeling and User Network Analysis on Twitter during World Lupus Awareness Day," IJERPH, MDPI, vol. 17(15), pages 1-18, July.

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