What can digital disease detection learn from (an external revision to) Google flu trends?

American Journal of Preventive Medicine

Volumn 47, Issue 3, 2014, Pages 341-347

  Santillana, Mauricio ^a   Zhang, D Wendong ^a   Althouse, Benjamin M ^b   Ayers, John W ^c  

^a HARVARD UNIVERSITY   (United States)

^b SANTA FE INSTITUTE   (United States)

^c SAN DIEGO STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ARTICLE; CASE STUDY; CORRELATION COEFFICIENT; DISEASE SURVEILLANCE; FLU LIKE SYNDROME; GOOGLE FLU TREND; INFLUENZA A (H1N1); INFLUENZA VIRUS A H1N1; INFORMATION PROCESSING; METHODOLOGY; PANDEMIC INFLUENZA; PREDICTION; EPIDEMIC; HEALTH SURVEY; HUMAN; INFLUENZA A VIRUS (H1N1); INFLUENZA, HUMAN; INTERNET; ISOLATION AND PURIFICATION; PROCEDURES; SEARCH ENGINE; SEASON; 2009 H1N1 INFLUENZA; AUTOMATION; DIAGNOSTIC ACCURACY; MAJOR CLINICAL STUDY; PUBLIC HEALTH; ROOT MEAN SQUARED ERROR; STATISTICAL PARAMETERS; WEB BROWSER;

DISEASE OUTBREAKS; HUMANS; INFLUENZA A VIRUS, H1N1 SUBTYPE; INFLUENZA, HUMAN; INTERNET; POPULATION SURVEILLANCE; SEARCH ENGINE; SEASONS;

EID: 84906354517     PISSN: 07493797     EISSN: 18732607     Source Type: Journal    
DOI: 10.1016/j.amepre.2014.05.020     Document Type: Article

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