Published on in Vol 16, No 12 (2014): December

Cumulative Query Method for Influenza Surveillance Using Search Engine Data

Cumulative Query Method for Influenza Surveillance Using Search Engine Data

Cumulative Query Method for Influenza Surveillance Using Search Engine Data

Journals

  1. Choo H, Kim M, Choi J, Shin J, Shin S. Influenza Screening via Deep Learning Using a Combination of Epidemiological and Patient-Generated Health Data: Development and Validation Study. Journal of Medical Internet Research 2020;22(10):e21369 View
  2. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  3. Lee D, Lee H, Choi M. Examining the Relationship Between Past Orientation and US Suicide Rates: An Analysis Using Big Data-Driven Google Search Queries. Journal of Medical Internet Research 2016;18(2):e35 View
  4. Woo H, Cho Y, Shim E, Lee J, Lee C, Kim S. Estimating Influenza Outbreaks Using Both Search Engine Query Data and Social Media Data in South Korea. Journal of Medical Internet Research 2016;18(7):e177 View
  5. Zhang Y, Bambrick H, Mengersen K, Tong S, Hu W. Using Google Trends and ambient temperature to predict seasonal influenza outbreaks. Environment International 2018;117:284 View
  6. Menachemi N, Rahurkar S, Rahurkar M. Using Web-Based Search Data to Study the Public’s Reactions to Societal Events: The Case of the Sandy Hook Shooting. JMIR Public Health and Surveillance 2017;3(1):e12 View
  7. Kagashe I, Yan Z, Suheryani I. Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data. Journal of Medical Internet Research 2017;19(9):e315 View
  8. Qin L, Sun Q, Wang Y, Wu K, Chen M, Shia B, Wu S. Prediction of Number of Cases of 2019 Novel Coronavirus (COVID-19) Using Social Media Search Index. International Journal of Environmental Research and Public Health 2020;17(7):2365 View
  9. Seo D, Shin S. Methods Using Social Media and Search Queries to Predict Infectious Disease Outbreaks. Healthcare Informatics Research 2017;23(4):343 View
  10. Yom-Tov E, Borsa D, Hayward A, McKendry R, Cox I. Automatic Identification of Web-Based Risk Markers for Health Events. Journal of Medical Internet Research 2015;17(1):e29 View
  11. Kamiński , Łoniewski , Misera , Marlicz . Heartburn-Related Internet Searches and Trends of Interest across Six Western Countries: A Four-Year Retrospective Analysis Using Google Ads Keyword Planner. International Journal of Environmental Research and Public Health 2019;16(23):4591 View
  12. Barros J, 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 View
  13. Zhang Y, Bambrick H, Mengersen K, Tong S, Feng L, Zhang L, Liu G, Xu A, Hu W. Association of sociodemographic factors and internet query data with pertussis infections in Shandong, China. Epidemiology and Infection 2019;147 View
  14. 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
  15. Brownstein J, Chu S, Marathe A, Marathe M, Nguyen A, Paolotti D, Perra N, Perrotta D, Santillana M, Swarup S, Tizzoni M, Vespignani A, Vullikanti A, Wilson M, Zhang Q. Combining Participatory Influenza Surveillance with Modeling and Forecasting: Three Alternative Approaches. JMIR Public Health and Surveillance 2017;3(4):e83 View
  16. Zhang Y, Bambrick H, Mengersen K, Tong S, Feng L, Zhang L, Liu G, Xu A, Hu W. Using big data to predict pertussis infections in Jinan city, China: a time series analysis. International Journal of Biometeorology 2020;64(1):95 View
  17. Venkatesh U, Gandhi P. Prediction of COVID-19 Outbreaks Using Google Trends in India: A Retrospective Analysis. Healthcare Informatics Research 2020;26(3):175 View
  18. Shin S, Seo D, An J, Kwak H, Kim S, Gwack J, Jo M. High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea. Scientific Reports 2016;6(1) View
  19. Shin S, Kim T, Seo D, Sohn C, Kim S, Ryoo S, Lee Y, Lee J, Kim W, Lim K, Olson D. Correlation between National Influenza Surveillance Data and Search Queries from Mobile Devices and Desktops in South Korea. PLOS ONE 2016;11(7):e0158539 View
  20. Agarwal V, Zhang L, Zhu J, Fang S, Cheng T, Hong C, Shah N. Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis. Journal of Medical Internet Research 2016;18(9):e251 View

Books/Policy Documents

  1. Qazi S, Ahmad S, Raza K. Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis. View