Published on in Vol 22, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19483, first published .
Regional Infoveillance of COVID-19 Case Rates: Analysis of Search-Engine Query Patterns

Regional Infoveillance of COVID-19 Case Rates: Analysis of Search-Engine Query Patterns

Regional Infoveillance of COVID-19 Case Rates: Analysis of Search-Engine Query Patterns

Journals

  1. Tu B, Wei L, Jia Y, Qian J. Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu index. BMC Infectious Diseases 2021;21(1) View
  2. Pulido-Polo M, Hernández-Santaolalla V, Lozano-González A. Uso institucional de Twitter para combatir la infodemia causada por la crisis sanitaria de la Covid-19. El profesional de la información 2021 View
  3. Huynh Dagher S, Lamé G, Hubiche T, Ezzedine K, Duong T. The Influence of Media Coverage and Governmental Policies on Google Queries Related to COVID-19 Cutaneous Symptoms: Infodemiology Study. JMIR Public Health and Surveillance 2021;7(2):e25651 View
  4. Bellaire C, Rutland J, Sayegh F, Pesce R, Tijerina J, Taub P. Going Viral: A Systematic Review of Google Trends in Plastic Surgery and a Recommended Framework for Its Use. Aesthetic Surgery Journal 2021;41(12):NP2034 View
  5. Rotter D, Doebler P, Schmitz F. Interests, Motives, and Psychological Burdens in Times of Crisis and Lockdown: Google Trends Analysis to Inform Policy Makers. Journal of Medical Internet Research 2021;23(6):e26385 View
  6. Paramita M, Orphanou K, Christoforou E, Otterbacher J, Hopfgartner F. Do you see what I see? Images of the COVID-19 pandemic through the lens of Google. Information Processing & Management 2021;58(5):102654 View
  7. Husnayain A, Chuang T, Fuad A, Su E. High variability in model performance of Google relative search volumes in spatially clustered COVID-19 areas of the USA. International Journal of Infectious Diseases 2021;109:269 View
  8. Saegner T, Austys D. Forecasting and Surveillance of COVID-19 Spread Using Google Trends: Literature Review. International Journal of Environmental Research and Public Health 2022;19(19):12394 View
  9. Lamba J, Jain E. A review on unprecedented influence of COVID-19 on stock market: what communities should know?. Journal of Enterprising Communities: People and Places in the Global Economy 2023;17(6):1088 View
  10. Pulido-Polo M, Jiménez-Marín G, Pérez Curiel C, Vázquez-González J. Twitter como herramienta de comunicación institucional: la Casa Real Británica y la Casa Real Española en el contexto postpandémico. Revista de Comunicación 2022;21(2):225 View
  11. Yang Y, Fan Y, Jiang L, Liu X. Search query and tourism forecasting during the pandemic: When and where can digital footprints be helpful as predictors?. Annals of Tourism Research 2022;93:103365 View
  12. Lamsal R, Harwood A, Read M. Twitter conversations predict the daily confirmed COVID-19 cases. Applied Soft Computing 2022;129:109603 View
  13. Pulido Polo M, Sánchez González M, Mesa Göbel J, Vázquez-González J. La Moncloa en Twitter: un análisis cuantitativo en la era post COVID. Revista Latina de Comunicación Social 2023;(81) View
  14. Zhang T, Lv L, Yang C, Huang C. Communication Efficiency of Local Governments in China: Measurements and Influencing Factors in Public Emergencies. SSRN Electronic Journal 2022 View
  15. Zayed B, Talaia A, Gaaboobah M, Amer S, Mansour F. Google Trends as a predictive tool in the era of COVID-19: a scoping review. Postgraduate Medical Journal 2023;99(1175):962 View
  16. García-García S, Rodríguez-Díaz R. Official Information on Twitter during the Pandemic in Spain. Societies 2023;13(4):91 View
  17. Li J, He Z, Zhang M, Ma W, Jin Y, Zhang L, Zhang S, Liu Y, Ma S. Estimating Rare Disease Incidences With Large-scale Internet Search Data: Development and Evaluation of a Two-step Machine Learning Method. JMIR Infodemiology 2023;3:e42721 View
  18. Clark E, Neumann S, Hopkins S, Kostopoulos A, Hagerman L, Dobbins M. Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review. JMIR Public Health and Surveillance 2024;10:e49185 View
  19. Kaur M, Cargill T, Hui K, Vu M, Bragazzi N, Kong J. A Novel Approach for the Early Detection of Medical Resource Demand Surges During Health Care Emergencies: Infodemiology Study of Tweets. JMIR Formative Research 2024;8:e46087 View