Identification

Author

Ginsberg J, Mohebbi MH, Patel RS, Brammer L, Smolinski MS, et al.

Title

Detecting influenza epidemics using search engine query data

Year

2009

Publication type

Article

Journal

Nature

Modified

2016-07-13 19:22:39.919988+00:00

Details

Volume

457

Number

7232

Pages

1012-1014

Access

Language

English

URL http://www.ncbi.nlm.nih.gov/pubmed/19020500
DOI

10.1038/nature07634

Accessed

2016-05-10

Extended information

Abstract

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.