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

Special Issue (2017) "Mining Online Health Reports" (Guest Editor: Collier, Cox, Limsopatham, Lampos, Culotta, Conway) (5) Infodemiology and Infoveillance (1349) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infectious Diseases (non-STD/STI) (1575) Influenza and Influenza-Like-Illness (ILI) Surveillance (217) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Mass Media/Social Media Communication and Campaigns (461) Vaccination and Immunization in the Digital Age (374)

Published on in Vol 19, No 12 (2017): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/8184, first published .
Estimating the Population Impact of a New Pediatric Influenza Vaccination Program in England Using Social Media Content

Estimating the Population Impact of a New Pediatric Influenza Vaccination Program in England Using Social Media Content

Estimating the Population Impact of a New Pediatric Influenza Vaccination Program in England Using Social Media Content

Authors of this article:

Moritz Wagner1, 2, 3 Author Orcid Image ;   Vasileios Lampos4 Author Orcid Image ;   Elad Yom-Tov5 Author Orcid Image ;   Richard Pebody1 Author Orcid Image ;   Ingemar J Cox4, 6 Author Orcid Image
Article Authors Cited by (13) Tweetations (24) Metrics

Journals

  1. Seroussi I, Levy N, Yom-Tov E. Multi-season analysis reveals the spatial structure of disease spread. Physica A: Statistical Mechanics and its Applications 2020;547:124425 View
  2. Liang F, Guan P, Wu W, Huang D. Forecasting influenza epidemics by integrating internet search queries and traditional surveillance data with the support vector machine regression model in Liaoning, from 2011 to 2015. PeerJ 2018;6:e5134 View
  3. Wagner M, Lampos V, Cox I, Pebody R. The added value of online user-generated content in traditional methods for influenza surveillance. Scientific Reports 2018;8(1) View
  4. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  5. Huang X, Smith M, Jamison A, Broniatowski D, Dredze M, Quinn S, Cai J, Paul M. Can online self-reports assist in real-time identification of influenza vaccination uptake? A cross-sectional study of influenza vaccine-related tweets in the USA, 2013–2017. BMJ Open 2019;9(1):e024018 View
  6. Hswen Y, Brownstein J, Xu X, Yom-Tov E. Early detection of COVID-19 in China and the USA: summary of the implementation of a digital decision-support and disease surveillance tool. BMJ Open 2020;10(12):e041004 View
  7. Choi J, Tamí-Maury I, Cuccaro P, Kim S, Markham C. Digital Health Interventions to Improve Adolescent HPV Vaccination: A Systematic Review. Vaccines 2023;11(2):249 View
  8. Calabrò G, D’Ambrosio F, Fallani E, Ricciardi W. Influenza Vaccination Assessment according to a Value-Based Health Care Approach. Vaccines 2022;10(10):1675 View
  9. Ziebart C, Kfrerer M, Stanley M, Austin L. A Digital-First Health Care Approach to Managing Pandemics: Scoping Review of Pandemic Self-triage Tools. Journal of Medical Internet Research 2023;25:e40983 View
  10. Tolosa-Kline A, Yom-Tov E, Hoffman C, Walker-Baban C, Lewis F. Trojan Horse: An Analysis of Targeted Advertising to Reduce Sexually Transmitted Diseases Among YMSM. Health Education & Behavior 2021;48(5):637 View