Infodemiology

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Infodemiology was defined by Gunther Eysenbach in the early 2000s as information epidemiology. [1] It is an area of science research focused on scanning the internet for user-contributed health-related content, with the ultimate goal of improving public health. [1] [2] [3] It is also defined as the science of mitigating public health problems resulting from an infodemic. [4]

Contents

Origin of term

Eysenbach first used the term in the context of measuring and predicting the quality of health information on the Web (i.e., measuring the "supply" side of information). [1] He later included in his definition methods and techniques which are designed to automatically measure and track health information "demand" (e.g., by analyzing search queries) as well as "supply" (e.g., by analyzing postings on webpages, in blogs, and news articles, for example through GPHIN) on the Internet with the overarching goal of informing public health policy and practice. In 2013, the Infovigil Project was launched in an effort to bring the research community together to help realize this goal. It is funded by the Canadian Institutes of Health Research. [5]

Eysenbach demonstrated his point by showing a correlation between flu-related searches on Google (demand data) and flu-incidence data. [2] The method is shown to be better and more timely (i.e., can predict public health events earlier) than traditional syndromic surveillance methods such as reports by sentinel physicians.[ citation needed ]

Application

Researchers have applied an infodemiological approach to studying the spread of HIV/AIDS, [6] SARS [7] and influenza, [8] [9] [10] vaccination uptake, [11] [12] antibiotics consumption, [13] the incidence of multiple sclerosis, [14] [15] patterns of alcohol consumption, [16] the efficacy of using the social web for personalization of health treatment, [17] [18] the contexts of status epilepticus patients, [19] [20] factors of Abdominal pain and its impact on quality of life [21] and the effectiveness of the Great American Smokeout anti-smoking awareness event. [22] Applications outside the field of health care include urban planning [23] and the study of economic trends and voter preferences. [24] Infodemiology plays a role in understanding how people seek out health-related information online and how this impacts public health outcomes. As technologies that people use continues to advance, it will becomes relevant for researchers to utilize infodemiological approaches in order to stay informed about emerging health trends in the digital world. One of the main goals of infodemiology is to provide real-time information about public health trends and behaviors. By analyzing user-generated content on the internet, researchers can gain insights into people's attitudes towards health issues and track the spread of diseases or outbreaks. This information can then be used to inform public health policies and interventions. There are also challenges associated with infodemiology. One major concern is the reliability and accuracy of online information. With the rise of fake news and misinformation on the internet, it is important for researchers to carefully evaluate the data sources. [25] [26] [27]

Methods

Infodemiology utilizes a variety of methods and techniques, including data mining, natural language processing, machine learning, and social network analysis. It also involves collaboration between different disciplines such as public health, computer science, sociology, and psychology. [25] [26] [27]

See also


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References

  1. 1 2 3 Eysenbach, Gunther (Dec 2002). "Infodemiology: The epidemiology of (mis)information". American Journal of Medicine. 113 (9): 763–5. CiteSeerX   10.1.1.8.8283 . doi:10.1016/s0002-9343(02)01473-0. PMID   12517369. S2CID   35788388.
  2. 1 2 Eysenbach, G (2006). "Infodemiology: tracking flu-related searches on the web for syndromic surveillance". AMIA ... Annual Symposium Proceedings. AMIA Symposium. 2006: 244–8. PMC   1839505 . PMID   17238340.
  3. ↑ Eysenbach, G (27 March 2009). "Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet". Journal of Medical Internet Research. 11 (1): e11. doi: 10.2196/jmir.1157 . PMC   2762766 . PMID   19329408.
  4. ↑ "1st WHO Infodemiology Conference". www.who.int. Retrieved 2020-11-14.
  5. ↑ Eysenbach, Gunther. "The Infovigil Project". www.infodemiology.org. Archived from the original on 2017-01-23. Retrieved 2016-11-12.
  6. ↑ Ling, Rebecca; Lee, Joon (2016-10-12). "Disease Monitoring and Health Campaign Evaluation Using Google Search Activities for HIV and AIDS, Stroke, Colorectal Cancer, and Marijuana Use in Canada: A Retrospective Observational Study". JMIR Public Health and Surveillance. 2 (2): e156. doi: 10.2196/publichealth.6504 . PMC   5081479 . PMID   27733330.
  7. ↑ Eysenbach, Gunther (2003-01-01). "SARS and Population Health Technology". Journal of Medical Internet Research. 5 (2): e14. doi: 10.2196/jmir.5.2.e14 . PMC   1550560 . PMID   12857670.
  8. ↑ Hansen, N. D.; Mølbak, K.; Cox, I. J.; Lioma, C. (2018). "Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation". arXiv: 1802.06833 [cs.IR]. Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 1197-1200.
  9. ↑ Woo, Hyekyung; Cho, Youngtae; Shim, Eunyoung; Lee, Jong-Koo; Lee, Chang-Gun; Kim, Seong Hwan (2016-07-04). "Estimating Influenza Outbreaks Using Both Search Engine Query Data and Social Media Data in South Korea". Journal of Medical Internet Research. 18 (7): e177. doi: 10.2196/jmir.4955 . ISSN   1438-8871. PMC   4949385 . PMID   27377323.
  10. ↑ Lampos, Vasileios; Miller, Andrew C.; Crossan, Steve; Stefansen, Christian (2015-08-03). "Advances in nowcasting influenza-like illness rates using search query logs". Scientific Reports. 5: 12760. Bibcode:2015NatSR...512760L. doi:10.1038/srep12760. ISSN   2045-2322. PMC   4522652 . PMID   26234783.
  11. ↑ Hansen, N. D.; Mølbak, K.; Cox, I. J.; Lioma, C. (2017). "Time-Series Adaptive Estimation of Vaccination Uptake Using Web Search Queries". arXiv: 1702.07326 [cs.IR]. Proceedings of the 26th International Conference on World Wide Web, 773-774.
  12. ↑ Hansen, N. D.; Mølbak, K.; Cox, I. J.; Lioma, C. (2016). "Ensemble Learned Vaccination Uptake Prediction using Web Search Queries". arXiv: 1609.00689 [cs.IR]. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, 1953-1956.
  13. ↑ Hansen, N. D.; Mølbak, K.; Cox, I. J.; Lioma, C. (2018). "Predicting Antimicrobial Drug Consumption Using Web Search Data" (PDF). Proceedings of the 2018 International Conference on Digital Health. pp. 133–142. arXiv: 1803.03532 . Bibcode:2018arXiv180303532D. doi:10.1145/3194658.3194667. ISBN   978-1-4503-6493-5. S2CID   3801274. Archived from the original (PDF) on 2018-03-13. Retrieved 2018-03-12. Proceedings of the ACM International Conference on Digital Health 2018.
  14. ↑ Bragazzi, Nicola Luigi (2013-01-01). "Infodemiology and infoveillance of multiple sclerosis in Italy". Multiple Sclerosis International. 2013: 924029. doi: 10.1155/2013/924029 . ISSN   2090-2654. PMC   3762202 . PMID   24027636.
  15. ↑ Brigo, Francesco; Lochner, Piergiorgio; Tezzon, Frediano; Nardone, Raffaele (2014-07-01). "Web search behavior for multiple sclerosis: An infodemiological study". Multiple Sclerosis and Related Disorders. 3 (4): 440–443. doi:10.1016/j.msard.2014.02.005. ISSN   2211-0356. PMID   25877054.
  16. ↑ Chan, Kl; Ho, Sy; Lam, Th (2013-09-02). "Infodemiology of alcohol use in Hong Kong mentioned on blogs: infoveillance study". Journal of Medical Internet Research. 15 (9): e192. doi: 10.2196/jmir.2180 . ISSN   1438-8871. PMC   3785983 . PMID   23999327.
  17. ↑ Fernandez-Luque, Luis; Karlsen, Randi; Bonander, Jason (2011-01-01). "Review of Extracting Information From the Social Web for Health Personalization". Journal of Medical Internet Research. 13 (1): e15. doi: 10.2196/jmir.1432 . PMC   3221336 . PMID   21278049.
  18. ↑ Kim, Yoonsang; Huang, Jidong; Emery, Sherry (2016-02-26). "Garbage in, Garbage Out: Data Collection, Quality Assessment and Reporting Standards for Social Media Data Use in Health Research, Infodemiology and Digital Disease Detection". Journal of Medical Internet Research. 18 (2): e41. doi: 10.2196/jmir.4738 . ISSN   1438-8871. PMC   4788740 . PMID   26920122.
  19. ↑ Bragazzi, Nicola Luigi; Bacigaluppi, Susanna; Robba, Chiara; Nardone, Raffaele; Trinka, Eugen; Brigo, Francesco (2016-02-01). "Infodemiology of status epilepticus: A systematic validation of the Google Trends-based search queries". Epilepsy & Behavior. 55: 120–123. doi:10.1016/j.yebeh.2015.12.017. ISSN   1525-5069. PMID   26773681. S2CID   205757762.
  20. ↑ Brigo, Francesco; Otte, Willem M.; Igwe, Stanley C.; Ausserer, Harald; Nardone, Raffaele; Tezzon, Frediano; Trinka, Eugen (2015-12-01). "Information-seeking behaviour for epilepsy: an infodemiological study of searches for Wikipedia articles". Epileptic Disorders. 17 (4): 460–466. doi:10.1684/epd.2015.0772. ISSN   1950-6945. PMID   26575365.
  21. ↑ Schäfer, Florent; Faviez, Carole; Voillot, Paméla; Foulquié, Pierre; Najm, Matthieu; Jeanne, Jean-François; Fagherazzi, Guy; Schück, Stéphane; Le Nevé, Boris (2020-11-03). "Mapping and Modeling of Discussions Related to Gastrointestinal Discomfort in French-Speaking Online Forums: Results of a 15-Year Retrospective Infodemiology Study". Journal of Medical Internet Research. 22 (11): e17247. doi: 10.2196/17247 . ISSN   1438-8871. PMC   7671840 . PMID   33141087.
  22. ↑ Ayers, John W.; Westmaas, J. Lee; Leas, Eric C.; Benton, Adrian; Chen, Yunqi; Dredze, Mark; Althouse, Benjamin M. (2016-06-01). "Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout". JMIR Public Health and Surveillance. 2 (1): e16. doi: 10.2196/publichealth.5304 . PMC   4869240 . PMID   27227151.
  23. ↑ "Even the most mundane online social commentary can have a purpose". The Irish Times. Retrieved 2016-11-12.
  24. ↑ Blastland, Michael (2010-12-14). "What do Google, Ask and Bing search results mean?". BBC News. Retrieved 2016-11-12.
  25. 1 2 "Infodemic".
  26. 1 2 https://infodemiology.jmir.org/
  27. 1 2 "1st WHO Infodemiology Conference".

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