ArticleScientific reports2017
Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Application of Internet-Based Sources for Public Health Surveillance (Infoveillance): Systematic Review.Journal of medical Internet research · 2020Pooled it
- Infodemiology of Influenza-like Illness: Utilizing Google Trends' Big Data for Epidemic Surveillance.Journal of clinical medicine · 2024Article
- Text mining for disease surveillance in veterinary clinical data: part two, training computers to identify features in clinical text.Frontiers in veterinary science · 2024Article
- Measuring concordance of data sources used for infectious disease research in the USA: a retrospective data analysis.BMJ open · 2023Article
- Inferring global-scale temporal latent topics from news reports to predict public health interventions for COVID-19.Patterns (New York, N.Y.) · 2022Article
- Understanding Health Communication Through Google Trends and News Coverage for COVID-19: Multinational Study in Eight Countries.JMIR public health and surveillance · 2021Article
- Enhancing Influenza Epidemics Forecasting Accuracy in China with Both Official and Unofficial Online News Articles, 2019-2020.International journal of environmental research and public health · 2021Article
- Infectious disease outbreak prediction using media articles with machine learning models.Scientific reports · 2021Article
- Using topic modelling for unsupervised annotation of electronic health records to identify an outbreak of disease in UK dogs.PloS one · 2021Article
- Characterizing News Report of the Substandard Vaccine Case of Changchun Changsheng in China: A Text Mining Approach.Vaccines · 2020Article
- The essential inner membrane protein YejM is a metalloenzyme.Scientific reports · 2020Article
- Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach.Journal of medical Internet research · 2020Article
- Development of a global infectious disease activity database using natural language processing, machine learning, and human expertise.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Project Tycho 2.0: a repository to improve the integration and reuse of data for global population health.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Big Data's Role in Precision Public Health.Frontiers in public health · 2018Review
- Harnessing Big Data for Communicable Tropical and Sub-Tropical Disorders: Implications From a Systematic Review of the Literature.Frontiers in public health · 2018Article
- A Platform for Crowdsourced Foodborne Illness Surveillance: Description of Users and Reports.JMIR public health and surveillance · 2017Article
- Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis.Journal of medical Internet research · 2016Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
In retrospective assessments, internet news reports have been shown to capture early reports of unknown infectious disease transmission prior to official laboratory confirmation. In general, media interest and reporting peaks and wanes during the course of an outbreak. In this study, we quantify the extent to which media interest during infectious disease outbreaks is indicative of trends of reported incidence. We introduce an approach that uses supervised temporal topic models to transform large corpora of news articles into temporal topic trends. The key advantages of this approach include: applicability to a wide range of diseases and ability to capture disease dynamics, including seasonality, abrupt peaks and troughs. We evaluated the method using data from multiple infectious disease outbreaks reported in the United States of America (U.S.), China, and India. We demonstrate that temporal topic trends extracted from disease-related news reports successfully capture the dynamics of multiple outbreaks such as whooping cough in U.S. (2012), dengue outbreaks in India (2013) and China (2014). Our observations also suggest that, when news coverage is uniform, efficient modeling of temporal topic trends using time-series regression techniques can estimate disease case counts with increased precision before official reports by health organizations.
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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.