Detecting influenza epidemics using search engine query data
Open accessAbstract
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.
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The web has complemented conventional surveillance systems rather than replaced them.
“This is not to assert that web-based or online methods of surveillance have replaced the conventional surveillance systems, but that the web has complemented the conventional systems of surveillance.8”
From Purpose-oriented review of public health surveillance systems: use of surveillance systems and recent advances (2024) · cites this paper as [8]
Google Trends is a valuable tool for investigating the level of interest of the general public in a specific topic.
“Google Trends is a valuable tool for investigating the level of interest of the general public in a specific topic.”
From Public and Research Interest in Telemedicine From 2017 to 2022: Infodemiology Study of Google Trends Data and Bibliometric Analysis of Scientific Literature (2024) · cites this paper as [23]
In 2009, a team of Google researchers reported in Nature that by analyzing flu-related queries, it can accurately detect flu outbreaks quicker than the CDC.
“In 2009, a team of Google researchers reported in the journal Nature 29 that by analyzing flu-related queries coming into its search engine, it can accurately detect flu outbreaks quicker than the Centers for Disease Control and Prevention.”
From A Big Data Guide to Understanding Climate Change: The Case for Theory-Guided Data Science (2014) · cites this paper as [29]
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- Authors
- Ginsberg, J., Mohebbi, M. H., Patel, R. S., Brammer, L., Smolinski, M. S., & Brilliant, L.
- Affiliations
- Google (United States) (US)
- Centers for Disease Control and Prevention (US)
- Corresponding author
- Mohebbi, Matthew H.
- Venue
- Nature
- Published
- 2009-02
- Volume
- 457
- Issue
- 7232
- Pages
- 1012-1014
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2117239687
- Cited by
- 4,295
- References
- 11
- Citations by year
- 2026: 120 · 2025: 113 · 2024: 141 · 2023: 185 · 2022: 265 · 2021: 335 · 2020: 393 · 2019: 278 · 2018: 298 · 2017: 299 · 2016: 355 · 2015: 334 · 2014: 375 · 2013: 278 · 2012: 192
- FWCI
- 81.33
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (publishedVersion)
- Topics
- Health Sciences › Medicine › Epidemiology › Data-Driven Disease Surveillance
- Health Sciences › Medicine › Epidemiology › Influenza Virus Research Studies
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Keywords
- influenza surveillance, influenza-like illness, Google Flu Trends, search engine query data, real-time disease surveillance, health-seeking behavior, internet search data, pandemic influenza
- MeSH terms
- Centers for Disease Control and Prevention, U.S., Health Education, Humans, Influenza, Human, Office Visits, Population Surveillance, Seasons, Time Factors, United States, User-Computer Interface, Reproducibility of Results, Health Behavior, Linear Models, Databases, Factual, Internet, Internationality
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