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Citing this Article

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Published on 20.11.17 in Vol 3, No 4 (2017): Oct-Dec

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

Works citing "Syndromic Surveillance Models Using Web Data: The Case of Influenza in Greece and Italy Using Google Trends"

Loukas Samaras, Elena García-Barriocanal, Miguel-Angel Sicilia

JMIR Public Health Surveill 2017 (Nov 20); 3(4):e90 

According to Crossref, the following articles are citing this article (DOI 10.2196/publichealth.8015):

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

  1. 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
  2. Mavragani A, Sampri A, Sypsa K, Tsagarakis KP. Integrating Smart Health in the US Health Care System: Infodemiology Study of Asthma Monitoring in the Google Era. JMIR Public Health and Surveillance 2018;4(1):e24
    CrossRef
  3. 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
  4. Schneider PP, van Gool CJ, Spreeuwenberg P, Hooiveld M, Donker GA, Barnett DJ, Paget J. Using web search queries to monitor influenza-like illness: an exploratory retrospective analysis, Netherlands, 2017/18 influenza season. Eurosurveillance 2020;25(21)
    CrossRef
  5. 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
  6. Tana JC, Kettunen J, Eirola E, Paakkonen H. Diurnal Variations of Depression-Related Health Information Seeking: Case Study in Finland Using Google Trends Data. JMIR Mental Health 2018;5(2):e43
    CrossRef
  7. Lansdall-Welfare T, Lightman S, Cristianini N. Seasonal variation in antidepressant prescriptions, environmental light and web queries for seasonal affective disorder. British Journal of Psychiatry 2019;215(2):481
    CrossRef
  8. . Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
    CrossRef
  9. Bragazzi NL, Gianfredi V, Villarini M, Rosselli R, Nasr A, Hussein A, Martini M, Behzadifar M. Vaccines Meet Big Data: State-of-the-Art and Future Prospects. From the Classical 3Is (“Isolate–Inactivate–Inject”) Vaccinology 1.0 to Vaccinology 3.0, Vaccinomics, and Beyond: A Historical Overview. Frontiers in Public Health 2018;6
    CrossRef
  10. 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
  11. 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
  12. Brkic FF, Besser G, Schally M, Schmid EM, Parzefall T, Riss D, Liu DT. Biannual Differences in Interest Peaks for Web Inquiries Into Ear Pain and Ear Drops: Infodemiology Study. Journal of Medical Internet Research 2021;23(6):e28328
    CrossRef
  13. Satpathy P, Kumar S, Prasad P. Suitability of Google Trends™ for Digital Surveillance During Ongoing COVID-19 Epidemic: A Case Study from India. Disaster Medicine and Public Health Preparedness 2023;17
    CrossRef
  14. Simonart T, Lam Hoai X, de Maertelaer V. Worldwide Evolution of Vaccinable and Nonvaccinable Viral Skin Infections: Google Trends Analysis. JMIR Dermatology 2022;5(4):e35034
    CrossRef
  15. Cai O, Sousa-Pinto B. United States Influenza Search Patterns Since the Emergence of COVID-19: Infodemiology Study. JMIR Public Health and Surveillance 2022;8(3):e32364
    CrossRef
  16. Simonart T, Lam Hoai X, De Maertelaer V. Epidemiologic evolution of common cutaneous infestations and arthropod bites: A Google Trends analysis. JAAD International 2021;5:69
    CrossRef
  17. Ravkin HD, Yom-Tov E, Nesher L. The Effect of Nonpharmaceutical Interventions Implemented in Response to the COVID-19 Pandemic on Seasonal Respiratory Syncytial Virus: Analysis of Google Trends Data. Journal of Medical Internet Research 2022;24(12):e42781
    CrossRef
  18. Feng Y, Cui X, Lv J, Yan B, Meng X, Zhang L, Guo Y, Peng L. Deep learning models for hepatitis E incidence prediction leveraging meteorological factors. PLOS ONE 2023;18(3):e0282928
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/publichealth.8015):

  1. Samaras L, García-Barriocanal E, Sicilia M. Innovation in Health Informatics. 2020. :39
    CrossRef