Tracking Epidemics With Google Flu Trends Data and a State-Space SEIR Model

In this article, we use Google Flu Trends data together with a sequential surveillance model based on state-space methodology to track the evolution of an epidemic process over time. We embed a classical mathematical epidemiology model [a susceptible-exposed-infected-recovered (SEIR) model] within t...

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Bibliographic Details
Published inJournal of the American Statistical Association Vol. 107; no. 500; pp. 1410 - 1426
Main Authors Dukic, Vanja, Lopes, Hedibert F, Polson, Nicholas G
Format Journal Article
LanguageEnglish
Published Alexandria Taylor & Francis Group 01.12.2012
Taylor & Francis Ltd
Subjects
algorithms
Applications and Case Studies
Disease models
Disease transmission
Emergency preparedness
Epidemics
Epidemiology
Flu
Google correlate
Google insights
Google searches
Google trends
H1N1
health services
Infectious Diseases
Influenza
Information services
IP surveillance
Mathematical models
monitoring
Nowcasting
Online surveillance
pandemic
Pandemics
Particle filtering
Search engines
Sequential analysis
Sequential learning
Statistical discrepancies
Statistics
Surveillance
Trends
U.S.A
United States
United States > US
USA
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Summary:In this article, we use Google Flu Trends data together with a sequential surveillance model based on state-space methodology to track the evolution of an epidemic process over time. We embed a classical mathematical epidemiology model [a susceptible-exposed-infected-recovered (SEIR) model] within the state-space framework, thereby extending the SEIR dynamics to allow changes through time. The implementation of this model is based on a particle filtering algorithm, which learns about the epidemic process sequentially through time and provides updated estimated odds of a pandemic with each new surveillance data point. We show how our approach, in combination with sequential Bayes factors, can serve as an online diagnostic tool for influenza pandemic. We take a close look at the Google Flu Trends data describing the spread of flu in the United States during 2003–2009 and in nine separate U.S. states chosen to represent a wide range of health care and emergency system strengths and weaknesses. This article has online supplementary materials.
Bibliography:http://dx.doi.org/10.1080/01621459.2012.713876
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ISSN:1537-274X
0162-1459
1537-274X
DOI:10.1080/01621459.2012.713876