Detecting influenza epidemics using search engine query data.
Seasonal influenza epidemics are a major public health concern, causing tens of millions of respiratory illnesses and 250,000 to 500,000 deaths worldwide each year. In addition to seasonal influenza, a new strain of influenza virus against which no previous immunity exists and that demonstrates human-to-human transmission could result in a pandemic with millions of fatalities. Early detection of disease activity, when followed by a rapid response, can reduce the impact of both seasonal and pandemic influenza. One way to improve early detection is to monitor health-seeking behaviour in the form of queries to online search engines, which are submitted by millions of users around the world each day. Here we present a method of analysing large numbers of Google search queries to track influenza-like illness in a population. Because the relative frequency of certain queries is highly correlated with the percentage of physician visits in which a patient presents with influenza-like symptoms, we can accurately estimate the current level of weekly influenza activity in each region of the United States, with a reporting lag of about one day. This approach may make it possible to use search queries to detect influenza epidemics in areas with a large population of web search users.
Ginsberg
Jeremy
J
Google Inc., 1600 Amphitheatre Parkway, Mountain View, California 94043, USA.
Mohebbi
Matthew H
MH
Patel
Rajan S
RS
Brammer
Lynnette
L
Smolinski
Mark S
MS
Brilliant
Larry
L
D002487:Centers for Disease Control and Prevention, U.S.; D016208:Databases, Factual; D015438:Health Behavior; D006266:Health Education / Q000706:statistics & numerical data*; D006801:Humans; D007251:Influenza, Human / Q000175:diagnosis / Q000453:epidemiology* / Q000635:transmission / Q000821:virology; D038622:Internationality; D020407:Internet / Q000706:statistics & numerical data*; D016014:Linear Models; D009819:Office Visits / Q000706:statistics & numerical data; D011159:Population Surveillance / Q000379:methods*; D015203:Reproducibility of Results; D012621:Seasons; D013997:Time Factors; D014481:United States; D014584:User-Computer Interface