2009
DOI: 10.3201/eid1508.090299
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More Diseases Tracked by Using Google Trends

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Cited by 225 publications
(179 citation statements)
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“…The recently developed the Google Insights for Search Application has been effectively applied to analyze large numbers of Google search queries aiming to track infl uenza-like illness in different populations [ 8 ] . The application has also been applied in the assessment of outbreaks of salmonella and gastroenteritis and for predicting the annual incidence of Dengue fever [ 13,14 ] . More recently, the application has been effectively utilized to record increases in Internet search activity for the term ' breast cancer ' every October in concordance with breast cancer awareness campaigns that occur during this month annually [ 9 ] .…”
Section: Discussionmentioning
confidence: 99%
“…The recently developed the Google Insights for Search Application has been effectively applied to analyze large numbers of Google search queries aiming to track infl uenza-like illness in different populations [ 8 ] . The application has also been applied in the assessment of outbreaks of salmonella and gastroenteritis and for predicting the annual incidence of Dengue fever [ 13,14 ] . More recently, the application has been effectively utilized to record increases in Internet search activity for the term ' breast cancer ' every October in concordance with breast cancer awareness campaigns that occur during this month annually [ 9 ] .…”
Section: Discussionmentioning
confidence: 99%
“…Johnson et al [93], Pelat et al [67], and Jia-xing et al [64] identified no reliable leading signals. On the other hand, Polgreen et al [68] used lag analysis with a shift granularity of one week to forecast positive influenza cultures as well as influenza and pneumonia mortality with a horizon of 5 weeks or more (though these indicators may trail the onset of symptoms significantly).…”
Section: Author Summarymentioning
confidence: 99%
“…When appropriately trained, these methods can be quite accurate; for example, many of the cited models can produce near real-time estimates of case counts with correlations upwards of r = 0.95. The collection of disease surveillance work cited above has estimated incidence for a wide variety of infectious and noninfectious conditions: avian influenza [52], cancer [55], chicken pox [67], cholera [81], dengue [50,53,84], dysentery [76], gastroenteritis [56,61,67], gonorrhea [64], hand foot and mouth disease (HFMD) [72], HIV/AIDS [75,76], influenza [34,36,54,57,59,62,63,65,67,68,71,74,[77][78][79][80]82,83,[85][86][87][88][89][90][91][92][93], kidney stones [51], listeriosis [70], malaria [66], methicillin-resistant Staphylococcus aureus (MRSA) [58]<...>…”
Section: Author Summarymentioning
confidence: 99%
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“…Google trends analyses can be either retrospective or cross-sectional; these are highly accurate, as they are based on extrapolation of data from millions of users of the web (surface web). Furthermore, extrapolations can be geographically mapped (geo-mapped) for a particular region of the world (Carneiro et al, 2009;Pelat et al, 2009;Seifter et al, 2010). For instance, geo-mapping of surface web users' interest in relation to amphetamines and ATS; the attentiveness of surface web users can be analysed, using Google Trends, in connection with phenethylamine, amphetamine, and ATS, and in retrospect to provide an accurate inference on the electronic epidemiology (e-epidemiology) on the Internet (Carneiro et al, 2009;Seifter et al, 2010).…”
Section: Google Trends Analyses: Amphetamine and Amphetamine-type Stimentioning
confidence: 99%