Infodemiology: Tracking Flu-Related Searches on the Web for Syndromic Surveillance

By Gunther Eysenbach. American Medical Informatics Association Annual Symposium, 2006

441 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d85525ce93c3f04c6e9f8e792c22c0b311f01784

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Citations in the corpus

Using internet searches for influenza surveillance. (2008, background): “Eysenbach [13], unable to get access to search engine query logs, demonstrated that the number of clicks on a “sponsored link” from Google Adsense, which was triggered by persons in Canada who entered “ﬂu” or “ﬂu symptoms” as search terms, accurately anticipated the Flu Watch reports collected by…”
Surveillance Sans Frontières: Internet-Based Emerging Infectious Disease Intelligence and the HealthMap Project (2008, background): “The use of click-stream data and individual search queries is also a promising new surveillance source [24] .”
Infodemiology and Infoveillance: Framework for an Emerging Set of Public Health Informatics Methods to Analyze Search, Communication and Publication Behavior on the Internet (2009, methodology): “…used in the context of analyzing the “supply side” (what is being published on the Web) [9], the scope of infodemiology now also includes “demand-based” infodemiology (ie, analyzing what people need and monitoring their health information seeking behavior) [1], because similar methods are employed.”
Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak (2010, background): “New ‘‘infoveillance’’ methods such as mining, aggregating, and analysing online textual data in real-time are becoming available [7,8].”
Towards detecting influenza epidemics by analyzing Twitter messages (2010, background): “A similar correlation was found in flurelated queries submitted to search engines [12, 6, 22, 8].”
Predicting consumer behavior with Web search (2010, background): “…Cooper et al. (6) found that search activity for specific cancers during 2001 – 2003 correlated with their estimated incidence; and Eysenbach (7) found a high correlation between clicks on sponsored search results for flu-related keywords and epidemiological data from the 2004 – 2005…”
Google Trends in Infodemiology and Infoveillance: Methodology Framework (2019, result): “Despite this and considering the increasing internet penetration, previous studies have suggested that Web-based data have been empirically shown to provide valuable and valid results in exploring and predicting behavior and are correlated with actual data [61-66].”
Reassessing Google Flu Trends Data for Detection of Seasonal and Pandemic Influenza: A Comparative Epidemiological Study at Three Geographic Scales (2013, background): “In parallel, novel approaches based on influenza-related internet search queries have been reported to yield faster detection and estimation of the intensity of influenza epidemics [10–16].”
Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact (2011, background): “…in public health [17,18] and a wide range of other areas [19]—it has, for example, been shown that search engine queries predict influenza [20,21], that tweets during the H1N1 pandemic correlated with incidence rates [22], and that tweets about a movie accurately predict its box-office…”
Sparse Vector Autoregressive Modeling (2012, background): “(2008); Eysenbach (2009); Hulth et al. (2009). Based on this fact, a group of researchers at Google applied logistic regression to select the top 45 Google user search terms that are most indicative of the influenza activity.”
Separating Fact from Fear: Tracking Flu Infections on Twitter (2013, background): “Twitter is a fantastic data resource for many tasks: measuring political (O’Connor et al., 2010; Tumasjan et al., 2010), and general sentiment (Bollen et al., 2011), studying linguistic variation (Eisenstein et al., 2010) and detecting earthquakes (Sakaki et al., 2010).”