Detecting influenza epidemics using search engine query data

Jeremy Ginsberg, Matthew H. Mohebbi (), Rajan S. Patel, Lynnette Brammer, Mark S. Smolinski and Larry Brilliant
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Jeremy Ginsberg: Google Inc., 1600 Amphitheatre Parkway, Mountain View, California 94043, USA
Matthew H. Mohebbi: Google Inc., 1600 Amphitheatre Parkway, Mountain View, California 94043, USA
Rajan S. Patel: Google Inc., 1600 Amphitheatre Parkway, Mountain View, California 94043, USA
Lynnette Brammer: Centers for Disease Control and Prevention, 1600 Clifton Road, NE, Atlanta, Georgia 30333, USA
Mark S. Smolinski: Google Inc., 1600 Amphitheatre Parkway, Mountain View, California 94043, USA
Larry Brilliant: Google Inc., 1600 Amphitheatre Parkway, Mountain View, California 94043, USA

Nature, 2009, vol. 457, issue 7232, 1012-1014

Abstract: Google-driven epidemiology This paper - first published on-line in November 2008 - draws on data from an early version of the Google Flu Trends search engine to estimate the levels of flu in a population. It introduces a computational model that converts raw search query data into a region-by-region real-time surveillance system that accurately estimates influenza activity with a lag of about one day - one to two weeks faster than the conventional reports published by the Centers for Disease Prevention and Control.

Date: 2009
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DOI: 10.1038/nature07634

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