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Citing this Article

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Published on 28.06.16 in Vol 18, No 6 (2016): Jun

This paper is in the following e-collection/theme issue:

Works citing "Google Flu Trends Spatial Variability Validated Against Emergency Department Influenza-Related Visits"

Joseph Jeffrey Klembczyk, Mehdi Jalalpour, Scott Levin, Raynard E Washington, Jesse M Pines, Richard E Rothman, Andrea Freyer Dugas

J Med Internet Res 2016 (Jun 28); 18(6):e175 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.5585):

(note that this is only a small subset of citations)

  1. Samaras L, García-Barriocanal E, Sicilia M. Syndromic Surveillance Models Using Web Data: The Case of Influenza in Greece and Italy Using Google Trends. JMIR Public Health and Surveillance 2017;3(4):e90
    CrossRef
  2. Chang Y, Chiang W, Wang W, Lin C, Hung L, Tsai Y, Suen J, Chen Y. Google Trends-based non-English language query data and epidemic diseases: a cross-sectional study of the popular search behaviour in Taiwan. BMJ Open 2020;10(7):e034156
    CrossRef
  3. Zepecki A, Guendelman S, DeNero J, Prata N. Using Application Programming Interfaces to Access Google Data for Health Research: Protocol for a Methodological Framework. JMIR Research Protocols 2020;9(7):e16543
    CrossRef
  4. Blasco MA, Svider PF, Tenbrunsel T, Vellaichamy G, Yoo GH, Fribley AM, Raza SN. Recent trends in oropharyngeal cancer funding and public interest. The Laryngoscope 2017;127(6):1345
    CrossRef
  5. Kandula S, Pei S, Shaman J. Improved forecasts of influenza-associated hospitalization rates with Google Search Trends. Journal of The Royal Society Interface 2019;16(155):20190080
    CrossRef
  6. . Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
    CrossRef
  7. Ford MT, Jebb AT, Tay L, Diener E. Internet Searches for Affect‐Related Terms: An Indicator of Subjective Well‐Being and Predictor of Health Outcomes across US States and Metro Areas. Applied Psychology: Health and Well-Being 2018;10(1):3
    CrossRef
  8. Lambrou GI, Hatziagapiou K, Toumpaniaris P, Ioannidou P, Koutsouris D. Computational Modelling in Epidemiological Dispersion Using Diffusion and Epidemiological Equations. International Journal of Reliable and Quality E-Healthcare 2019;8(4):1
    CrossRef
  9. Barros JM, Duggan J, Rebholz-Schuhmann D. The Application of Internet-Based Sources for Public Health Surveillance (Infoveillance): Systematic Review. Journal of Medical Internet Research 2020;22(3):e13680
    CrossRef
  10. Chang Y, Chiang W, Wang W, Lin C, Hung L, Tsai Y, Chen Y. Assessing Epidemic Diseases and Public Opinion through Popular Search Behavior Using Non-English Language Google Trends (Preprint). JMIR Public Health and Surveillance 2018;
    CrossRef
  11. Brownstein JS, Chu S, Marathe A, Marathe MV, Nguyen AT, Paolotti D, Perra N, Perrotta D, Santillana M, Swarup S, Tizzoni M, Vespignani A, Vullikanti AKS, Wilson ML, Zhang Q. Combining Participatory Influenza Surveillance with Modeling and Forecasting: Three Alternative Approaches. JMIR Public Health and Surveillance 2017;3(4):e83
    CrossRef
  12. Kolff CA, Scott VP, Stockwell MS. The use of technology to promote vaccination: A social ecological model based framework. Human Vaccines & Immunotherapeutics 2018;14(7):1636
    CrossRef
  13. . Digitale Medien als Informationsquelle über Umwelt und Gesundheit für Laien. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz 2017;60(6):649
    CrossRef
  14. Burns SM, Turner DP, Sexton KE, Deng H, Houle TT. Using Search Engines to Investigate Shared Migraine Experiences. Headache: The Journal of Head and Face Pain 2017;57(8):1217
    CrossRef
  15. Shen C, Chen A, Luo C, Zhang J, Feng B, Liao W. Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study. Journal of Medical Internet Research 2020;22(5):e19421
    CrossRef
  16. Zhang Z, Zheng X, Zeng DD, Leischow SJ. Tracking Dabbing Using Search Query Surveillance: A Case Study in the United States. Journal of Medical Internet Research 2016;18(9):e252
    CrossRef
  17. Sousa-Pinto B, Anto A, Czarlewski W, Anto JM, Fonseca JA, Bousquet J. Assessment of the Impact of Media Coverage on COVID-19–Related Google Trends Data: Infodemiology Study. Journal of Medical Internet Research 2020;22(8):e19611
    CrossRef
  18. Kapitány‐Fövény M, Ferenci T, Sulyok Z, Kegele J, Richter H, Vályi‐Nagy I, Sulyok M. Can Google Trends data improve forecasting of Lyme disease incidence?. Zoonoses and Public Health 2019;66(1):101
    CrossRef
  19. . Infectious Disease Research in the Era of Big Data. Annual Review of Biomedical Data Science 2020;3(1):43
    CrossRef
  20. Johnson AK, Bhaumik R, Tabidze I, Mehta SD. Nowcasting Sexually Transmitted Infections in Chicago: Predictive Modeling and Evaluation Study Using Google Trends. JMIR Public Health and Surveillance 2020;6(4):e20588
    CrossRef
  21. Arseneau ME, Backonja U, Litchman ML, Karimanfard R, Sheng X, Taylor-Swanson L. #Menopause on Instagram: a mixed-methods study. Menopause 2021;28(4):391
    CrossRef
  22. Dey V, Krasniak P, Nguyen M, Lee C, Ning X. A Pipeline to Understand Emerging Illness Via Social Media Data Analysis: Case Study on Breast Implant Illness. JMIR Medical Informatics 2021;9(11):e29768
    CrossRef
  23. Jabour AM, Varghese J, Damad AH, Ghailan KY, Mehmood AM. Examining the Correlation of Google Influenza Trend with Hospital Data: Retrospective Study. Journal of Multidisciplinary Healthcare 2021;Volume 14:3073
    CrossRef
  24. Said Abasse K, Toulouse-Fournier A, Paquet C, Côté A, Smith PY, Bergeron F, Archambault P. Collaborative writing applications in support of knowledge translation and management during pandemics: A scoping review. International Journal of Medical Informatics 2022;165:104814
    CrossRef
  25. Xiao J, Gao M, Huang M, Zhang W, Du Z, Liu T, Meng X, Ma W, Lin S. How do El Niño Southern Oscillation (ENSO) and local meteorological factors affect the incidence of seasonal influenza in New York state. Hygiene and Environmental Health Advances 2022;4:100040
    CrossRef
  26. Ruan Y, Huang T, Zhou W, Zhu J, Liang Q, Zhong L, Tang X, Liu L, Chen S, Xie Y. The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19. Scientific Reports 2023;13(1)
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.5585):

  1. Lazar J, Feng JH, Hochheiser H. Research Methods in Human Computer Interaction. 2017. :411
    CrossRef
  2. Ram S, Tyagi R. Sustainability. 2020. :627
    CrossRef