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

Infodemiology and Infoveillance (1349)

Published on in Vol 14, No 5 (2012): Sep-Oct

FluBreaks: Early Epidemic Detection from Google Flu Trends

FluBreaks: Early Epidemic Detection from Google Flu Trends

FluBreaks: Early Epidemic Detection from Google Flu Trends

Authors of this article:

Fahad Pervaiz1 ;   Mansoor Pervaiz1 ;   Nabeel Abdur Rehman1 ;   Umar Saif1
Article Authors Cited by (72) Tweetations (32) Metrics

Journals

  1. Sharpe J, Hopkins R, Cook R, Striley C. Evaluating Google, Twitter, and Wikipedia as Tools for Influenza Surveillance Using Bayesian Change Point Analysis: A Comparative Analysis. JMIR Public Health and Surveillance 2016;2(2):e161 View
  2. Joshi A, Karimi S, Sparks R, Paris C, Macintyre C. Survey of Text-based Epidemic Intelligence. ACM Computing Surveys 2020;52(6):1 View
  3. Wiwanitkit V. Google Trends (GT) related to influenza. Cadernos de Saúde Pública 2015;31(6):1334 View
  4. Samson S, Konty K, Lee W, Quisel T, Foschini L, Kerr D, Liska J, Mills H, Hollingsworth R, Greenberg M, Beal A. Quantifying the Impact of Influenza Among Persons With Type 2 Diabetes Mellitus: A New Approach to Determine Medical and Physical Activity Impact. Journal of Diabetes Science and Technology 2021;15(1):44 View
  5. Szmuda T, Ali S, Hetzger T, Rosvall P, Słoniewski P. Are online searches for the novel coronavirus (COVID-19) related to media or epidemiology? A cross-sectional study. International Journal of Infectious Diseases 2020;97:386 View
  6. Zhang Z, Zheng X, Zeng D, Leischow S. Tracking Dabbing Using Search Query Surveillance: A Case Study in the United States. Journal of Medical Internet Research 2016;18(9):e252 View
  7. Pardon B. Developing an early warning system for bovine respiratory disease. Veterinary Record 2014;175(14):349 View
  8. Einav S, O’Connor M. Does Only Size Matter or Is There Still a Place for Single-Center Studies in the Era of Big Data?. Anesthesia & Analgesia 2016;123(6):1623 View
  9. Timpka T, Spreco A, Dahlström Ö, Eriksson O, Gursky E, Ekberg J, Blomqvist E, Strömgren M, Karlsson D, Eriksson H, Nyce J, Hinkula J, Holm E. Performance of eHealth Data Sources in Local Influenza Surveillance: A 5-Year Open Cohort Study. Journal of Medical Internet Research 2014;16(4):e116 View
  10. Hanson C, Cannon B, Burton S, Giraud-Carrier C. An Exploration of Social Circles and Prescription Drug Abuse Through Twitter. Journal of Medical Internet Research 2013;15(9):e189 View
  11. Tana J, 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 View
  12. Seo D, Jo M, Sohn C, Shin S, Lee J, Yu M, Kim W, Lim K, Lee S. Cumulative Query Method for Influenza Surveillance Using Search Engine Data. Journal of Medical Internet Research 2014;16(12):e289 View
  13. Gesser-Edelsburg A, Shir-Raz Y, Walter N, Mordini E, Dimitriou D, James J, Green M. The Public Sphere in Emerging Infectious Disease Communication: Recipient or Active and Vocal Partner?. Disaster Medicine and Public Health Preparedness 2015;9(4):447 View
  14. Mccallum M, Bury G. Google search patterns suggest declining interest in the environment. Biodiversity and Conservation 2013;22(6-7):1355 View
  15. Won M, Marques-Pita M, Louro C, Gonçalves-Sá J, Ferrari M. Early and Real-Time Detection of Seasonal Influenza Onset. PLOS Computational Biology 2017;13(2):e1005330 View
  16. 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
  17. Li E, Tung C, Chang S. The wisdom of crowds in action: Forecasting epidemic diseases with a web-based prediction market system. International Journal of Medical Informatics 2016;92:35 View
  18. Milinovich G, Williams G, Clements A, Hu W. Internet-based surveillance systems for monitoring emerging infectious diseases. The Lancet Infectious Diseases 2014;14(2):160 View
  19. 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
  20. Zou S, Veeravalli V, Li J, Towsley D. Quickest Detection of Dynamic Events in Networks. IEEE Transactions on Information Theory 2020;66(4):2280 View
  21. Cousins H, Cousins C, Harris A, Pasquale L. Regional Infoveillance of COVID-19 Case Rates: Analysis of Search-Engine Query Patterns. Journal of Medical Internet Research 2020;22(7):e19483 View
  22. Mudunuri U, Khouja M, Repetski S, Venkataraman G, Che A, Luke B, Girard F, Stephens R, Aerts J. Knowledge and Theme Discovery across Very Large Biological Data Sets Using Distributed Queries: A Prototype Combining Unstructured and Structured Data. PLoS ONE 2013;8(12):e80503 View
  23. Ali A, Qadir J, Rasool R, Sathiaseelan A, Zwitter A, Crowcroft J. Big data for development: applications and techniques. Big Data Analytics 2016;1(1) View
  24. Liang B, Scammon D. Incidence of Online Health Information Search: A Useful Proxy for Public Health Risk Perception. Journal of Medical Internet Research 2013;15(6):e114 View
  25. Haney N, Kinsella S, Morey J. United States Medical School Graduate Interest in Radiology Residency Programs as Depicted by Online Search Tools. Journal of the American College of Radiology 2014;11(2):193 View
  26. 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 View
  27. Schootman M, Toor A, Cavazos-Rehg P, Jeffe D, McQueen A, Eberth J, Davidson N. The utility of Google Trends data to examine interest in cancer screening. BMJ Open 2015;5(6):e006678 View
  28. Zhang Y, Milinovich G, Xu Z, Bambrick H, Mengersen K, Tong S, Hu W. Monitoring Pertussis Infections Using Internet Search Queries. Scientific Reports 2017;7(1) View
  29. Aslam A, Tsou M, Spitzberg B, An L, Gawron J, Gupta D, Peddecord K, Nagel A, Allen C, Yang J, Lindsay S. The Reliability of Tweets as a Supplementary Method of Seasonal Influenza Surveillance. Journal of Medical Internet Research 2014;16(11):e250 View
  30. Rosenkrantz A, Prabhu V. Public Interest in Imaging-Based Cancer Screening Examinations in the United States: Analysis Using a Web-Based Search Tool. American Journal of Roentgenology 2016;206(1):113 View
  31. Klembczyk J, Jalalpour M, Levin S, Washington R, Pines J, Rothman R, Dugas A. Google Flu Trends Spatial Variability Validated Against Emergency Department Influenza-Related Visits. Journal of Medical Internet Research 2016;18(6):e175 View
  32. Levin-Rector A, Wilson E, Fine A, Greene S. Refining Historical Limits Method to Improve Disease Cluster Detection, New York City, New York, USA. Emerging Infectious Diseases 2015;21(2):265 View
  33. Mahroum N, Bragazzi N, Brigo F, Waknin R, Sharif K, Mahagna H, Amital H, Watad A. Capturing public interest toward new tools for controlling human immunodeficiency virus (HIV) infection exploiting data from Google Trends. Health Informatics Journal 2019;25(4):1383 View
  34. Zheluk A, Quinn C, Hercz D, Gillespie J. Internet Search Patterns of Human Immunodeficiency Virus and the Digital Divide in the Russian Federation: Infoveillance Study. Journal of Medical Internet Research 2013;15(11):e256 View
  35. Herrera J, Srinivasan R, Brownstein J, Galvani A, Meyers L, Salathé M. Disease Surveillance on Complex Social Networks. PLOS Computational Biology 2016;12(7):e1004928 View
  36. Yan S, Chughtai A, Macintyre C. Utility and potential of rapid epidemic intelligence from internet-based sources. International Journal of Infectious Diseases 2017;63:77 View
  37. Sugrue R, Carthy E, Kelly M, Sweeney K. Science or popular media: What drives breast cancer online activity?. The Breast Journal 2018;24(2):189 View
  38. Stevens K, Pfeiffer D. Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems. Spatial and Spatio-temporal Epidemiology 2015;13:15 View
  39. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  40. Abbas M, Morland T, Hall E, EL-Manzalawy Y. Associations between Google Search Trends for Symptoms and COVID-19 Confirmed and Death Cases in the United States. International Journal of Environmental Research and Public Health 2021;18(9):4560 View
  41. Zhang Y, Bambrick H, Mengersen K, Tong S, Hu W. Using internet-based query and climate data to predict climate-sensitive infectious disease risks: a systematic review of epidemiological evidence. International Journal of Biometeorology 2021;65(12):2203 View
  42. Brick J, Andrews W, Foster J. A Review of Nonprobability Sampling Using Mobile Apps for Fishing Effort and Catch Surveys. Transactions of the American Fisheries Society 2022;151(1):42 View
  43. Chu L, Chen H. Sequential Change-Point Detection for High-Dimensional and Non-Euclidean Data. IEEE Transactions on Signal Processing 2022;70:4498 View
  44. Niu Q, Liu J, Zhao Z, Onishi M, Kawaguchi A, Bandara A, Harada K, Aoyama T, Nagai-Tanima M. Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study. BMC Infectious Diseases 2022;22(1) View
  45. Dai S, Han L, Rashid T. Influenza surveillance with Baidu index and attention-based long short-term memory model. PLOS ONE 2023;18(1):e0280834 View
  46. Ito T. Global monitoring of public interest in preventive measures against COVID-19 via analysis of Google Trends: an infodemiology and infoveillance study. BMJ Open 2022;12(8):e060715 View
  47. Strawbridge J, Meer E, Singh P, Rootman D. Google Searches for Thyroid Eye Disease After Regulatory Approval of Teprotumumab. JAMA Ophthalmology 2022;140(6):639 View
  48. Rolnick D, Donti P, Kaack L, Kochanski K, Lacoste A, Sankaran K, Ross A, Milojevic-Dupont N, Jaques N, Waldman-Brown A, Luccioni A, Maharaj T, Sherwin E, Mukkavilli S, Kording K, Gomes C, Ng A, Hassabis D, Platt J, Creutzig F, Chayes J, Bengio Y. Tackling Climate Change with Machine Learning. ACM Computing Surveys 2023;55(2):1 View
  49. Chen H, Chu L. Graph-Based Change-Point Analysis. Annual Review of Statistics and Its Application 2023;10(1):475 View
  50. Quinn J, Frias‐Martinez V, Subramanian L. Computational Sustainability and Artificial Intelligence in the Developing World. AI Magazine 2014;35(3):36 View
  51. Thakur N, Cui S, Patel K, Azizi N, Knieling V, Han C, Poon A, Shah R. Marburg Virus Outbreak and a New Conspiracy Theory: Findings from a Comprehensive Analysis and Forecasting of Web Behavior. Computation 2023;11(11):234 View
  52. Ning S, Hussain A, Wang Q, Kaderali L. Incorporating connectivity among Internet search data for enhanced influenza-like illness tracking. PLOS ONE 2024;19(8):e0305579 View

Books/Policy Documents

  1. Nawaz M, Mustafa R, Lali M. Applying Big Data Analytics in Bioinformatics and Medicine. View
  2. Fan S, Garg S, Yeom S. AI 2016: Advances in Artificial Intelligence. View
  3. Goodman K, Meslin E. Public Health Informatics and Information Systems. View
  4. Staegemann D, Volk M, Daase C, Pohl M, Turowski K. Proceedings of Sixth International Congress on Information and Communication Technology. View
  5. Burr T, Kaufeld K. Time Series Analysis - New Insights. View
  6. Makinde O. Health and Medical Geography in Africa. View
  7. Walter G. Effective Use of Social Media in Public Health. View
  8. Jillahi K, Thandekkattu S. Designing Sustainable Internet of Things Solutions for Smart Industries. View