ArticleEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin2022
Epitweetr: Early warning of public health threats using Twitter data.
Article in Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled 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
- Infodemiology of West Nile Virus in Greece, 2024-2025, with Descriptive One Health Preparedness Evidence from Crete.Epidemiologia (Basel, Switzerland) · 2026Article
- Climate Change and Autochthonous Vector-Borne Disease Transmission in Europe: Dengue as a Sentinel Signal for Surveillance and Preparedness.Tropical medicine and infectious disease · 2026Article
- Assessing social media platform data access for automated early warning of public health threats.European journal of public health · 2026Article
- Artificial intelligence for coordinating vaccine design, antiviral discovery, and real-world monitoring in the era of emerging and endemic viral threats.Frontiers in pharmacology · 2026Review
- The power of artificial intelligence for managing pandemics: A primer for public health professionals.The International journal of health planning and management · 2025Review
- Use of large language models as a scalable approach to understanding public health discourse.PLOS digital health · 2024Article
- Linking Opinions Shared on Social Media About COVID-19 Public Health Measures to Adherence: Repeated Cross-Sectional Surveys of Twitter Use in Canada.Journal of medical Internet research · 2024Article
- Innovations in public health surveillance: An overview of novel use of data and analytic methods.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2024Article
- Epidemic intelligence in Europe: a user needs perspective to foster innovation in digital health surveillance.BMC public health · 2024Article
- Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review.JMIR public health and surveillance · 2024Article
- The application of artificial intelligence in health policy: a scoping review.BMC health services research · 2023Article
- Open-Source Intelligence for Detection of Radiological Events and Syndromes Following the Invasion of Ukraine in 2022: Observational Study.JMIR infodemiology · 2023Article
- Establishing Infodemic Management in Germany: A Framework for Social Listening and Integrated Analysis to Report Infodemic Insights at the National Public Health Institute.JMIR infodemiology · 2023Article
- Artificial intelligence in public health: the potential of epidemic early warning systems.The Journal of international medical research · 2023Review
- Digital Marketing: A Unique Multidisciplinary Approach towards the Elimination of Viral Hepatitis.Pathogens (Basel, Switzerland) · 2022Review
- Timeliness of online COVID-19 reports from official sources.Frontiers in public health · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BackgroundThe European Centre for Disease Prevention and Control (ECDC) systematically collates information from sources to rapidly detect early public health threats. The lack of a freely available, customisable and automated early warning tool using data from Twitter prompted the ECDC to develop epitweetr, which collects, geolocates and aggregates tweets generating signals and email alerts.AimThis study aims to compare the performance of epitweetr to manually monitoring tweets for the purpose of early detecting public health threats.MethodsWe calculated the general and specific positive predictive value (PPV) of signals generated by epitweetr between 19 October and 30 November 2020. Sensitivity, specificity, timeliness and accuracy and performance of tweet geolocation and signal detection algorithms obtained from epitweetr and the manual monitoring of 1,200 tweets were compared.ResultsThe epitweetr geolocation algorithm had an accuracy of 30.1% at national, and 25.9% at subnational levels. The signal detection algorithm had 3.0% general PPV and 74.6% specific PPV. Compared to manual monitoring, epitweetr had greater sensitivity (47.9% and 78.6%, respectively), and reduced PPV (97.9% and 74.6%, respectively). Median validation time difference between 16 common events detected by epitweetr and manual monitoring was -48.6 hours (IQR: -102.8 to -23.7).ConclusionEpitweetr has shown sufficient performance as an early warning tool for public health threats using Twitter data. Since epitweetr is a free, open-source tool with configurable settings and a strong automated component, it is expected to increase in usability and usefulness to public health experts.
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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.