ArticleJournal of medical Internet research2016
Google Flu Trends Spatial Variability Validated Against Emergency Department Influenza-Related Visits.
Article in Journal of medical Internet research, 2016. 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.
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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.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.
- The Application of Internet-Based Sources for Public Health Surveillance (Infoveillance): Systematic Review.Journal of medical Internet research · 2020Pooled it
- The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19.Scientific reports · 2023Article
- How do El Niño Southern Oscillation (ENSO) and local meteorological factors affect the incidence of seasonal influenza in New York state.Hygiene and environmental health advances · 2022Article
- A Pipeline to Understand Emerging Illness Via Social Media Data Analysis: Case Study on Breast Implant Illness.JMIR medical informatics · 2021Article
- Examining the Correlation of Google Influenza Trend with Hospital Data: Retrospective Study.Journal of multidisciplinary healthcare · 2021Article
- Nowcasting Sexually Transmitted Infections in Chicago: Predictive Modeling and Evaluation Study Using Google Trends.JMIR public health and surveillance · 2020Article
- Assessment of the Impact of Media Coverage on COVID-19-Related Google Trends Data: Infodemiology Study.Journal of medical Internet research · 2020Article
- Using Application Programming Interfaces to Access Google Data for Health Research: Protocol for a Methodological Framework.JMIR research protocols · 2020Article
- Article
- Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study.Journal of medical Internet research · 2020Article
- Infodemiology and Infoveillance: Scoping Review.Journal of medical Internet research · 2020Article
- Improved forecasts of influenza-associated hospitalization rates with Google Search Trends.Journal of the Royal Society, Interface · 2019Article
- The use of technology to promote vaccination: A social ecological model based framework.Human vaccines & immunotherapeutics · 2018Review
- Neurology and the Internet: a review.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2018Review
- Syndromic Surveillance Models Using Web Data: The Case of Influenza in Greece and Italy Using Google Trends.JMIR public health and surveillance · 2017Article
- Combining Participatory Influenza Surveillance with Modeling and Forecasting: Three Alternative Approaches.JMIR public health and surveillance · 2017Article
- Article
- Observational
- Tracking Dabbing Using Search Query Surveillance: A Case Study in the United States.Journal of medical Internet research · 2016Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundInfluenza is a deadly and costly public health problem. Variations in its seasonal patterns cause dangerous surges in emergency department (ED) patient volume. Google Flu Trends (GFT) can provide faster influenza surveillance information than traditional CDC methods, potentially leading to improved public health preparedness. GFT has been found to correlate well with reported influenza and to improve influenza prediction models. However, previous validation studies have focused on isolated clinical locations.
objectiveThe purpose of the study was to measure GFT surveillance effectiveness by correlating GFT with influenza-related ED visits in 19 US cities across seven influenza seasons, and to explore which city characteristics lead to better or worse GFT effectiveness.
methodsUsing Healthcare Cost and Utilization Project data, we collected weekly counts of ED visits for all patients with diagnosis (International Statistical Classification of Diseases 9) codes for influenza-related visits from 2005-2011 in 19 different US cities. We measured the correlation between weekly volume of GFT searches and influenza-related ED visits (ie, GFT ED surveillance effectiveness) per city. We evaluated the relationship between 15 publically available city indicators (11 sociodemographic, two health care utilization, and two climate) and GFT surveillance effectiveness using univariate linear regression.
resultsCorrelation between city-level GFT and influenza-related ED visits had a median of .84, ranging from .67 to .93 across 19 cities. Temporal variability was observed, with median correlation ranging from .78 in 2009 to .94 in 2005. City indicators significantly associated (P<.10) with improved GFT surveillance include higher proportion of female population, higher proportion with Medicare coverage, higher ED visits per capita, and lower socioeconomic status.
conclusionsGFT is strongly correlated with ED influenza-related visits at the city level, but unexplained variation over geographic location and time limits its utility as standalone surveillance. GFT is likely most useful as an early signal used in conjunction with other more comprehensive surveillance techniques. City indicators associated with improved GFT surveillance provide some insight into the variability of GFT effectiveness. For example, populations with lower socioeconomic status may have a greater tendency to initially turn to the Internet for health questions, thus leading to increased GFT effectiveness. GFT has the potential to provide valuable information to ED providers for patient care and to administrators for ED surge preparedness.
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