ArticleEpidemiology and infection2014
Emergency department and 'Google flu trends' data as syndromic surveillance indicators for seasonal influenza.
Article in Epidemiology and infection, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 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
- Influenza surveillance systems using traditional and alternative sources of data: A scoping review.Influenza and other respiratory viruses · 2022Article
- Social Media Surveillance for Outbreak Projection via Transmission Models: Longitudinal Observational Study.JMIR public health and surveillance · 2019Article
- Forecasting respiratory infectious outbreaks using ED-based syndromic surveillance for febrile ED visits in a Metropolitan City.The American journal of emergency medicine · 2019Observational
- What Did You Google? Describing Online Health Information Search Patterns of ED patients and Their Relationship with Final Diagnoses.The western journal of emergency medicine · 2017Article
- Dengue Baidu Search Index data can improve the prediction of local dengue epidemic: A case study in Guangzhou, China.PLoS neglected tropical diseases · 2017Article
- A look back: investigating Google Flu Trends during the influenza A(H1N1)pdm09 pandemic in Canada, 2009-2010.Epidemiology and infection · 2017Article
- News trends and web search query of HIV/AIDS in Hong Kong.PloS one · 2017Article
- Google Flu Trends Spatial Variability Validated Against Emergency Department Influenza-Related Visits.Journal of medical Internet research · 2016Article
- Geographical and Temporal Correlations in the Incidence of Lyme Disease, RMSF, Ehrlichiosis, and Coccidioidomycosis with Search Data.The Journal of investigative dermatology · 2015Article
- Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems.Spatial and spatio-temporal epidemiology · 2015Review
- Leading Indicators and the Evaluation of the Performance of Alerts for Influenza Epidemics.PloS one · 2015Article
- Surveillance for emerging respiratory viruses.The Lancet. Infectious diseases · 2014Review
- Characterizing Influenza surveillance systems performance: application of a Bayesian hierarchical statistical model to Hong Kong surveillance data.BMC public health · 2014Article
- Measuring Global Disease with Wikipedia: Success, Failure, and a Research Agenda.CSCW : proceedings of the Conference on Computer-Supported Cooperative Work. Conference on Computer-Supported Cooperative WorkArticle
- A Practitioner-Driven Research Agenda for Syndromic Surveillance.Public health reports (Washington, D.C. : 1974)Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We evaluated syndromic indicators of influenza disease activity developed using emergency department (ED) data - total ED visits attributed to influenza-like illness (ILI) ('ED ILI volume') and percentage of visits attributed to ILI ('ED ILI percent') - and Google flu trends (GFT) data (ILI cases/100 000 physician visits). Congruity and correlation among these indicators and between these indicators and weekly count of laboratory-confirmed influenza in Manitoba was assessed graphically using linear regression models. Both ED and GFT data performed well as syndromic indicators of influenza activity, and were highly correlated with each other in real time. The strongest correlations between virological data and ED ILI volume and ED ILI percent, respectively, were 0·77 and 0·71. The strongest correlation of GFT was 0·74. Seasonal influenza activity may be effectively monitored using ED and GFT data.
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