Infodemiology in Public Health Infoveillance: An Inevitable Necessity in 21st Century

SeyyedHosseini, Shohreh; Asemi, Asefeh; Shabani, Ahmad

doi:10.30473/mrs.2019.38354.1338

Document Type : Research Paper

Authors

¹ Ph. D Department of Knowledge and Information Science, University of Medical Scienses, Bushehr, Iran

² Associate Professor, Department of Knowledge and Information Science, University of Isfahan Isfahan, Iran.

³ Professor, Department of Knowledge and Information Science, University of Isfahan, Isfahan, Iran

https://doi.org/10.30473/mrs.2019.38354.1338

Abstract

Purpose: Infodemiology tend to use internet and web 2.0 services to collect and analyze health-related data on web automatically. The basic assumption is that these data likely represent a high compatibility with health information need of different categories of people. The constant monitoring of information provides a health information-seeking behavior model for policymakers. The current study aimed to investigate the origin of the term “infodemiology” as well as its application in big data area. Also the study focused on the weakness of the traditional health information systems. Finally, this research studied the state of the social networks and internet search as an infodemiological tool.
Methodgy: This research conducted by review study as well as the comprehensive and systematic review related to infodemiology.
Findings: The results showed that policymakers receive critical and useful data about public health as late as possible by the use of traditional methods. So infodemiology design new methods using computers, internet, web-based services, and information technology to improve public healthcare. It could be applied for problem solving in medicine, medical education, and research-based services in electronic media.
Conclusion: Infodemiological methods and measurements could save the common costs of public health infoveillance by constant monitoring of data in digital environment.

Keywords

Main Subjects

Information Management

References

Abroms, L. C. & Maibach, E. W. (2008). The effectiveness of mass communication to change public behavior. Annu. Rev. Public Health, 29( ), 219-234.

Ayers, J. W. (2011). Using aggregate internet search queries for mental health surveillance. Maryland: the Johns Hopkins University.

Barrett-Connor, E؛Ayanian, J. Z., Brown, E. R., Coultas, D. B., Francis, C. K., Goldberg, R. J & Wallace, P. J. (2011). A Nationwide Framework for Surveillance of Cardiovascular and Chronic Lung Diseases [site article]. Retrieved 2015, Dec. 10, from http://works.bepress.com/david_mannino/206/

Brigo, F & Erro, R (2016). Why do people Google movement disorders? An infodemiological study of information seeking behaviors. Neurological Sciences, 37(5), 781-787.

Brigo, F. Igwe, S. C. Nardone, R; Orioli, A & Otte, W. M. (2016). Cancer information disparities on the internet: An infodemiological study. Journal of Cancer Policy, 8, 33-37.

Broadway, S. C. (2005). Health information-seeking behaviors on the internet among diabetic and healthy women (Doctoral dissertation, University of Florida)

Burton, S. H. (2013). Computational Techniques for Public Health Surveillance (Doctoral dissertation, Brigham Young University).

Carneiro, H. A. & Mylonakis, E. (2009). Google trends: a web-based tool for real-time surveillance of disease outbreaks. Clinical infectious diseases, 49(10), 1557-1564.

Chew, C. (2010). Pandemics in the age of twitter: A content analysis of the 2009 h1n1 outbreak (Doctoral dissertation, University of Toronto).

Dugas, A. F., Jalalpour, M; Gel, Y., Levin, S.,; Torcaso, F; Igusa, T. & Rothman, R. E. (2013). Influenza forecasting with Google Flu Trends. PloS one, 8(2), e56176.

Eysenbach, G. (2002). Infodemiology: The epidemiology of (mis) information.The American journal of medicine, 113(9), 763-765.

Eysenbach, G (2006). Infodemiology: tracking flu-related searches on the web for syndromic surveillance. In AMIA Annual Symposium Proceedings (Vol. 2006, p. 244). American Medical Informatics Association.

Eysenbach, G. (2008). Medicine 2.0: Social networking, collaboration, participation, apomediation, and openness. J Med Internet Res, 10(3), e22.

Eysenbach, G. (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.

Ginsberg, J., Mohebbi, M. H., Patel, R. S., Brammer, L., Smolinski, M. S. & Brilliant, L (2009). Detecting influenza epidemics using search engine query data. Nature, 457(7232), 1012-1014.

Hulth, A., Rydevik, G; Linde, A & Montgomery, J. (2009). Web queries as a source for syndromic surveillance. PloS one, 4(2), e4378.

Kuehn, B. M. (2013). Scientists mine web search data to identify epidemics and adverse events. JAMA, 309(18), 1883-1884.

Kwanya, T., Stilwell, C & Underwood, P. G (2013). Intelligent libraries and apomediators: Distinguishing between Library 3.0 and Library 2.0. Journal of Librarianship and Information Science, 45(3), 187-197.

Mullen, S. (2013). Public Health Surveillance of Pediatric Dentistry via Twitter (Doctoral Dissertation, University of California, San Francisco).

Olsen, J. (2013). Infodemiology to improve public health situational awareness: An investigation of 2010 Pertussis outbreaks in California, Michigan and Ohio. (Doctoral dissertation, The University of North Carolina).

Patel, A. G. (2011). Developing a Social Network Web Application for Influenza Surveillance. (Doctoral dissertation, University of California, Davis).

Polgreen, P. M. Chen, Y., Pennock, D. M., Nelson, F. D & Weinstein, R. A (2008). Using internet searches for influenza surveillance. Clinical infectious diseases, 47(11), 1443-1448.

Raghupathi, W & Raghupathi, V (2014). Big data analytics in healthcare: promise and potential. Health Information Science and Systems, 2(1), 1, 1-10.

Sharma, P & Kaur, P. D. (2017). Effectiveness of web-based social sensing in health information dissemination A review. Telematics and Informatics, 34(1), 194-219.

Willard, S. D & Nguyen, M. M. (2013). Internet search trends analysis tools can provide real-time data on kidney stone disease in the United States. Urology, 81(1), 37-42.

Ybarra, M & Suman, M. (2008). Reasons, assessments and actions taken: Sex and age differences in uses of internet health information. Health Education Research, 23(3), 512-21.

Young, J. M. (2014). An Epidemiology of Big Data (Doctoral dissertation, Syracuse University).

Digital and Smart Libraries Researches

Infodemiology in Public Health Infoveillance: An Inevitable Necessity in 21st Century

References

References

Volume 5, Issue 4 - Serial Number 20
February 2020
Pages 49-62

Infodemiology in Public Health Infoveillance: An Inevitable Necessity in 21st Century

References

References

Volume 5, Issue 4 - Serial Number 20February 2020Pages 49-62

Volume 5, Issue 4 - Serial Number 20
February 2020
Pages 49-62