SynthesisThe Milbank quarterly2014
Social media and internet-based data in global systems for public health surveillance: a systematic review.
Synthesis in The Milbank quarterly, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 111 papers, 15 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
111 citing papers in PubMed, 15 syntheses or guidelines pooled it.
- Unveiling Patient-Level Harms and At-Risk Clinical Groups During Hospital Cyberattacks: Systematic Review of Global Case Studies and Social Media Data.Journal of medical Internet research · 2026Pooled it
- Acute respiratory infections prediction through social media data and machine learning: a systematic review.BMC medical informatics and decision making · 2026Pooled it
- Innovating health prevention models in detecting infectious disease outbreaks through social media data: an umbrella review of the evidence.Frontiers in public health · 2024Pooled it
- Pooled it
- Data-driven methods for dengue prediction and surveillance using real-world and Big Data: A systematic review.PLoS neglected tropical diseases · 2022Pooled it
- Web-Based Apps for Responding to Acute Infectious Disease Outbreaks in the Community: Systematic Review.JMIR public health and surveillance · 2021Pooled it
- Digital Data Sources and Their Impact on People's Health: A Systematic Review of Systematic Reviews.Frontiers in public health · 2021Pooled it
- Social media based surveillance systems for healthcare using machine learning: A systematic review.Journal of biomedical informatics · 2020Pooled it
- A systematic literature review of machine learning in online personal health data.Journal of the American Medical Informatics Association : JAMIA · 2019Pooled it
- Public Health Surveillance Studies of Alcohol Industry Market and Political Strategies: A Systematic Review.Journal of studies on alcohol and drugs · 2019Pooled it
- Does locally relevant, real-time infection epidemiological data improve clinician management and antimicrobial prescribing in primary care? A systematic review.Family practice · 2018Pooled it
- Systematic review of surveillance by social media platforms for illicit drug use.Journal of public health (Oxford, England) · 2017Pooled it
- Digital disease detection: A systematic review of event-based internet biosurveillance systems.International journal of medical informatics · 2017Pooled it
- Twitter as a Tool for Health Research: A Systematic Review.American journal of public health · 2017Pooled it
- Web-based infectious disease surveillance systems and public health perspectives: a systematic review.BMC public health · 2016Pooled it
- Utilizing Machine Learning for Predicting PrEP Use Status Among Sexual and Gender Minority Young Adults.Prevention science : the official journal of the Society for Prevention Research · 2026Article
- Artificial intelligence and infodemic management: a governance framework for digital public health decision-making.Frontiers in digital health · 2026Article
- Surveillance of Twitter Data on COVID-19 Symptoms During the Omicron Variant Period: A Sentiment Analysis.JMIR formative research · 2025Article
- Decoding HIV Discourse on Social Media: Large-Scale Analysis of 191,972 Tweets Using Machine Learning, Topic Modeling, and Temporal Analysis.Journal of medical Internet research · 2025Article
- Advocating for a community-centred model for responding to potential information harms.Nature human behaviour · 2025Review
51 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextThe exchange of health information on the Internet has been heralded as an opportunity to improve public health surveillance. In a field that has traditionally relied on an established system of mandatory and voluntary reporting of known infectious diseases by doctors and laboratories to governmental agencies, innovations in social media and so-called user-generated information could lead to faster recognition of cases of infectious disease. More direct access to such data could enable surveillance epidemiologists to detect potential public health threats such as rare, new diseases or early-level warnings for epidemics. But how useful are data from social media and the Internet, and what is the potential to enhance surveillance? The challenges of using these emerging surveillance systems for infectious disease epidemiology, including the specific resources needed, technical requirements, and acceptability to public health practitioners and policymakers, have wide-reaching implications for public health surveillance in the 21st century.
methodsThis article divides public health surveillance into indicator-based surveillance and event-based surveillance and provides an overview of each. We did an exhaustive review of published articles indexed in the databases PubMed, Scopus, and Scirus between 1990 and 2011 covering contemporary event-based systems for infectious disease surveillance.
findingsOur literature review uncovered no event-based surveillance systems currently used in national surveillance programs. While much has been done to develop event-based surveillance, the existing systems have limitations. Accordingly, there is a need for further development of automated technologies that monitor health-related information on the Internet, especially to handle large amounts of data and to prevent information overload. The dissemination to health authorities of new information about health events is not always efficient and could be improved. No comprehensive evaluations show whether event-based surveillance systems have been integrated into actual epidemiological work during real-time health events.
conclusionsThe acceptability of data from the Internet and social media as a regular part of public health surveillance programs varies and is related to a circular challenge: the willingness to integrate is rooted in a lack of effectiveness studies, yet such effectiveness can be proved only through a structured evaluation of integrated systems. Issues related to changing technical and social paradigms in both individual perceptions of and interactions with personal health data, as well as social media and other data from the Internet, must be further addressed before such information can be integrated into official surveillance systems.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.