Published on in Vol 6, No 3 (2020): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19969, first published .
Fluctuation of Public Interest in COVID-19 in the United States: Retrospective Analysis of Google Trends Search Data

Fluctuation of Public Interest in COVID-19 in the United States: Retrospective Analysis of Google Trends Search Data

Fluctuation of Public Interest in COVID-19 in the United States: Retrospective Analysis of Google Trends Search Data

Journals

  1. Hartwell M, Greiner B, Kilburn Z, Ottwell R. Association of Public Interest in Preventive Measures and Increased COVID-19 Cases After the Expiration of Stay-at-Home Orders: A Cross-Sectional Study. Disaster Medicine and Public Health Preparedness 2022;16(1):55 View
  2. Subhash A, Maldonado D, Kajikawa T, Chen S, Stavrakis A, Photopoulos C. Public Interest in Sports Medicine and Surgery (Anterior Cruciate Ligament, Meniscus, Rotator Cuff) Topics Declined Following the COVID-19 Outbreak. Arthroscopy, Sports Medicine, and Rehabilitation 2021;3(1):e149 View
  3. Sulyok M, Ferenci T, Walker M. Google Trends Data and COVID‐19 in Europe: Correlations and model enhancement are European wide. Transboundary and Emerging Diseases 2021;68(4):2610 View
  4. Kardeş S, Kuzu A, Raiker R, Pakhchanian H, Karagülle M. Public interest in rheumatic diseases and rheumatologist in the United States during the COVID-19 pandemic: evidence from Google Trends. Rheumatology International 2021;41(2):329 View
  5. Asgari Mehrabadi M, Dutt N, Rahmani A. The Causality Inference of Public Interest in Restaurants and Bars on Daily COVID-19 Cases in the United States: Google Trends Analysis. JMIR Public Health and Surveillance 2021;7(4):e22880 View
  6. Szilagyi I, Ullrich T, Lang-Illievich K, Klivinyi C, Schittek G, Simonis H, Bornemann-Cimenti H. Google Trends for Pain Search Terms in the World’s Most Populated Regions Before and After the First Recorded COVID-19 Case: Infodemiological Study. Journal of Medical Internet Research 2021;23(4):e27214 View
  7. Post L, Boctor M, Issa T, Moss C, Murphy R, Achenbach C, Ison M, Resnick D, Singh L, White J, Welch S, Oehmke J. SARS-CoV-2 Surveillance System in Canada: Longitudinal Trend Analysis. JMIR Public Health and Surveillance 2021;7(5):e25753 View
  8. Kardeş E, Kardeş S. Google searches for bruxism, teeth grinding, and teeth clenching during the COVID-19 pandemic. Journal of Orofacial Orthopedics / Fortschritte der Kieferorthopädie 2022;83(6):1 View
  9. SeyyedHosseini S, BasirianJahromi R. COVID-19 pandemic in the Middle East countries: coronavirus-seeking behavior versus coronavirus-related publications. Scientometrics 2021;126(9):7503 View
  10. 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
  11. Sato K, Mano T, Iwata A, Toda T. Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity. BMC Medical Research Methodology 2021;21(1) View
  12. Ma M, Ye S. The role of ingroup assortative sociality in the COVID-19 pandemic: A multilevel analysis of google trends data in the United States. International Journal of Intercultural Relations 2021;84:168 View
  13. Ma M. Heightened religiosity proactively and reactively responds to the COVID-19 pandemic across the globe: Novel insights from the parasite-stress theory of sociality and the behavioral immune system theory. International Journal of Intercultural Relations 2022;90:38 View
  14. Shee V, Louis C. Language Barriers to Online Search Interest for COVID-19: A Global Infodemiological Study. Cureus 2022 View
  15. Wang Z, Xiao H, Lin L, Tang K, Unger J. Geographic social inequalities in information-seeking response to the COVID-19 pandemic in China: longitudinal analysis of Baidu Index. Scientific Reports 2022;12(1) View
  16. Song C, Yin H, Shi X, Xie M, Yang S, Zhou J, Wang X, Tang Z, Yang Y, Pan J. Spatiotemporal disparities in regional public risk perception of COVID-19 using Bayesian Spatiotemporally Varying Coefficients (STVC) series models across Chinese cities. International Journal of Disaster Risk Reduction 2022;77:103078 View
  17. Kow R, Mohamad Rafiai N, Ahmad Alwi A, Low C, Rozi N, Nizam Siron K, Zulkifly A, Zakaria@Mohamad Z, Awang M. Malaysian Public Interest in Common Medical Problems: A 10-Year Google Trends Analysis. Cureus 2022 View
  18. Domino K, Miszczak J. Will you infect me with your opinion?. Physica A: Statistical Mechanics and its Applications 2022;608:128289 View
  19. Kwon C. Research and Public Interest in Mindfulness in the COVID-19 and Post-COVID-19 Era: A Bibliometric and Google Trends Analysis. International Journal of Environmental Research and Public Health 2023;20(5):3807 View
  20. 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 View
  21. An L, Russell D, Mihalcea R, Bacon E, Huffman S, Resnicow K. Online Search Behavior Related to COVID-19 Vaccines: Infodemiology Study. JMIR Infodemiology 2021;1(1):e32127 View
  22. Feng J, Li J, Hu W, Li G. Public Interest, Risk, Trust, and Personal Protective Equipment Purchase and Usage: Face Masks Amid the COVID-19 Pandemic. International Journal of Environmental Research and Public Health 2022;19(9):5502 View
  23. Ming W, Huang F, Chen Q, Liang B, Jiao A, Liu T, Wu H, Akinwunmi B, Li J, Liu G, Zhang C, Huang J, Liu Q. Understanding Health Communication Through Google Trends and News Coverage for COVID-19: Multinational Study in Eight Countries. JMIR Public Health and Surveillance 2021;7(12):e26644 View
  24. He S, Shyamsundar S, Chong P, Kannikal J, Calvano J, Balapal N, Kallenberg N, Balaji A, Ankem A, Martin A. Analyzing opioid-use disorder websites in the United States: An optimized website usability study. DIGITAL HEALTH 2022;8:205520762211215 View
  25. Husnayain A, Shim E, Fuad A, Su E. Predicting New Daily COVID-19 Cases and Deaths Using Search Engine Query Data in South Korea From 2020 to 2021: Infodemiology Study. Journal of Medical Internet Research 2021;23(12):e34178 View
  26. Ng Y. A Cross-National Study of Fear Appeal Messages in YouTube Trending Videos About COVID-19. American Behavioral Scientist 2023:000276422311553 View
  27. Springer S, Strzelecki A, Zieger M. Maximum generable interest: A universal standard for Google Trends search queries. Healthcare Analytics 2023;3:100158 View
  28. 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
  29. Porcu G, Chen Y, Bonaugurio A, Villa S, Riva L, Messina V, Bagarella G, Maistrello M, Leoni O, Cereda D, Matone F, Gori A, Corrao G. Web-based surveillance of respiratory infection outbreaks: retrospective analysis of Italian COVID-19 epidemic waves using Google Trends. Frontiers in Public Health 2023;11 View
  30. Cuff J, Dighe S, Watson S, Badell-Grau R, Weightman A, Jones D, Kille P. Monitoring SARS-CoV-2 Using Infoveillance, National Reporting Data, and Wastewater in Wales, United Kingdom: Mixed Methods Study. JMIR Infodemiology 2023;3:e43891 View
  31. Sun J, Shin J, Li Y, Qu Y, Zhen L, Kim H, Yang A, Liu W, Saffer A. Communicating CSR relationships in COVID‐19: The evolution of cross‐sector communication networks on social media. Business Ethics, the Environment & Responsibility 2024 View

Books/Policy Documents

  1. El-Sharif A, Alhamad H, Assab M, Echarif S, Alhayek Y. Artificial Intelligence (AI) and Finance. View