Literature DB >> 32167477

The Application of Internet-Based Sources for Public Health Surveillance (Infoveillance): Systematic Review.

Joana M Barros1,2, Jim Duggan2, Dietrich Rebholz-Schuhmann3.   

Abstract

BACKGROUND: Public health surveillance is based on the continuous and systematic collection, analysis, and interpretation of data. This informs the development of early warning systems to monitor epidemics and documents the impact of intervention measures. The introduction of digital data sources, and specifically sources available on the internet, has impacted the field of public health surveillance. New opportunities enabled by the underlying availability and scale of internet-based sources (IBSs) have paved the way for novel approaches for disease surveillance, exploration of health communities, and the study of epidemic dynamics. This field and approach is also known as infodemiology or infoveillance.
OBJECTIVE: This review aimed to assess research findings regarding the application of IBSs for public health surveillance (infodemiology or infoveillance). To achieve this, we have presented a comprehensive systematic literature review with a focus on these sources and their limitations, the diseases targeted, and commonly applied methods.
METHODS: A systematic literature review was conducted targeting publications between 2012 and 2018 that leveraged IBSs for public health surveillance, outbreak forecasting, disease characterization, diagnosis prediction, content analysis, and health-topic identification. The search results were filtered according to previously defined inclusion and exclusion criteria.
RESULTS: Spanning a total of 162 publications, we determined infectious diseases to be the preferred case study (108/162, 66.7%). Of the eight categories of IBSs (search queries, social media, news, discussion forums, websites, web encyclopedia, and online obituaries), search queries and social media were applied in 95.1% (154/162) of the reviewed publications. We also identified limitations in representativeness and biased user age groups, as well as high susceptibility to media events by search queries, social media, and web encyclopedias.
CONCLUSIONS: IBSs are a valuable proxy to study illnesses affecting the general population; however, it is important to characterize which diseases are best suited for the available sources; the literature shows that the level of engagement among online platforms can be a potential indicator. There is a necessity to understand the population's online behavior; in addition, the exploration of health information dissemination and its content is significantly unexplored. With this information, we can understand how the population communicates about illnesses online and, in the process, benefit public health. ©Joana M Barros, Jim Duggan, Dietrich Rebholz-Schuhmann. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 13.03.2020.

Entities:  

Keywords:  chronic diseases; infectious diseases; infodemiology; infoveillance; medical informatics; public health; public health informatics

Year:  2020        PMID: 32167477     DOI: 10.2196/13680

Source DB:  PubMed          Journal:  J Med Internet Res        ISSN: 1438-8871            Impact factor:   5.428


  29 in total

1.  How to Fight an Infodemic: The Four Pillars of Infodemic Management.

Authors:  Gunther Eysenbach
Journal:  J Med Internet Res       Date:  2020-06-29       Impact factor: 5.428

2.  Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study.

Authors:  Cuihua Shen; Anfan Chen; Chen Luo; Jingwen Zhang; Bo Feng; Wang Liao
Journal:  J Med Internet Res       Date:  2020-05-28       Impact factor: 5.428

3.  Correlations of Online Search Engine Trends With Coronavirus Disease (COVID-19) Incidence: Infodemiology Study.

Authors:  Thomas S Higgins; Arthur W Wu; Dhruv Sharma; Elisa A Illing; Kolin Rubel; Jonathan Y Ting
Journal:  JMIR Public Health Surveill       Date:  2020-05-21

4.  What triggers online help-seeking retransmission during the COVID-19 period? Empirical evidence from Chinese social media.

Authors:  Chen Luo; Yuru Li; Anfan Chen; Yulong Tang
Journal:  PLoS One       Date:  2020-11-03       Impact factor: 3.240

5.  Online Information Exchange and Anxiety Spread in the Early Stage of the Novel Coronavirus (COVID-19) Outbreak in South Korea: Structural Topic Model and Network Analysis.

Authors:  Wonkwang Jo; Jaeho Lee; Junli Park; Yeol Kim
Journal:  J Med Internet Res       Date:  2020-06-02       Impact factor: 5.428

6.  Evaluation of Korean-Language COVID-19-Related Medical Information on YouTube: Cross-Sectional Infodemiology Study.

Authors:  Hana Moon; Geon Ho Lee
Journal:  J Med Internet Res       Date:  2020-08-12       Impact factor: 5.428

7.  The use of internet analytics by a Canadian provincial chiropractic regulator to monitor, evaluate and remediate misleading claims regarding specific health conditions, pregnancy, and COVID-19.

Authors:  Greg Kawchuk; Jan Hartvigsen; Stan Innes; J Keith Simpson; Brian Gushaty
Journal:  Chiropr Man Therap       Date:  2020-05-11

8.  Systematic analysis of the scientific literature on population surveillance.

Authors:  Gregorio González-Alcaide; Pedro Llorente; José-Manuel Ramos-Rincón
Journal:  Heliyon       Date:  2020-10-01

9.  Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index.

Authors:  Xue Gong; Yangyang Han; Mengchi Hou; Rui Guo
Journal:  JMIR Public Health Surveill       Date:  2020-10-22

10.  Dynamic Panel Estimate-Based Health Surveillance of SARS-CoV-2 Infection Rates to Inform Public Health Policy: Model Development and Validation.

Authors:  James Francis Oehmke; Theresa B Oehmke; Lauren Nadya Singh; Lori Ann Post
Journal:  J Med Internet Res       Date:  2020-09-22       Impact factor: 5.428

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