ReviewAntimicrobial stewardship & healthcare epidemiology : ASHE2021
Social media: A new tool for outbreak surveillance.
Review in Antimicrobial stewardship & healthcare epidemiology : ASHE, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis 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
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Internet-based Surveillance Systems and Infectious Diseases Prediction: An Updated Review of the Last 10 Years and Lessons from the COVID-19 Pandemic.Journal of epidemiology and global health · 2024Pooled it
- Multilingual Disparities in Large Language Model-Based Symptom Detection for Global Disease Surveillance: Evaluation Study.JMIR AI · 2026Article
- Advances in mosquito-borne disease surveillance using machine learning.New microbes and new infections · 2026Article
- Review
- Digital epidemiology: Utilizing big data for public health surveillance and disease outbreak prediction.Journal of public health research · 2026Review
- Advances in Animal Disease Surveillance and Information Systems and Their Role in Disease Control and Prevention: Implications in Ethiopia.Veterinary medicine and science · 2025Review
- CoViNAR: a context-aware social media dataset for pandemic severity level prediction and analysis.Frontiers in artificial intelligence · 2025Article
- Birds of a feather? Mis- and dis-information on the social media platform X related to avian influenza.Antimicrobial stewardship & healthcare epidemiology : ASHE · 2025Article
- Article
- Unconventional data, unprecedented insights: leveraging non-traditional data during a pandemic.Frontiers in public health · 2024Article
- Is Tree-of-Thought Prompting Strategy Better than Chain-of-Thought? Vaping Cessation Analysis Using Large Language Models.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Spatio-temporal evaluation of social media as a tool for livestock disease surveillance.One health (Amsterdam, Netherlands) · 2023Article
- The Voice of the Patient and the Electronic Health Record.Applied clinical informatics · 2023Article
- Reaching Populations at Risk for HIV Through Targeted Facebook Advertisements: Cost-Consequence Analysis.JMIR formative research · 2023Article
- Australasian Institute of Digital Health Summit 2022-Automated Social Media Surveillance for Detection of Vaccine Safety Signals: A Validation Study.Applied clinical informatics · 2023Article
- Automated classification of lay health articles using natural language processing: a case study on pregnancy health and postpartum depression.Frontiers in psychiatry · 2023Article
- The Politicization of Ivermectin Tweets During the COVID-19 Pandemic.Open forum infectious diseases · 2022Article
- Analyzing COVID-19 disinformation on Twitter using the hashtags #scamdemic and #plandemic: Retrospective study.PloS one · 2022Article
- Managing epidemics in the digital age: the crucial role of social media in information dissemination.Pathogens and global healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Social media platforms allow users to share news, ideas, thoughts, and opinions on a global scale. Data processing methods allow researchers to automate the collection and interpretation of social media posts for efficient and valuable disease surveillance. Data derived from social media and internet search trends have been used successfully for monitoring and forecasting disease outbreaks such as Zika, Dengue, MERS, and Ebola viruses. More recently, data derived from social media have been used to monitor and model disease incidence during the coronavirus disease 2019 (COVID-19) pandemic. We discuss the use of social media for disease surveillance.
Identifiers
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.