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Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in the United States in Near Real-Time

Circulating levels of both seasonal and pandemic influenza require constant surveillance to ensure the health and safety of the population. While up-to-date information is critical, traditional surveillance systems can have data availability lags of up to two weeks. We introduce a novel method of es...

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Detalles Bibliográficos
Autores principales: McIver, David J., Brownstein, John S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3990502/
https://www.ncbi.nlm.nih.gov/pubmed/24743682
http://dx.doi.org/10.1371/journal.pcbi.1003581
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author McIver, David J.
Brownstein, John S.
author_facet McIver, David J.
Brownstein, John S.
author_sort McIver, David J.
collection PubMed
description Circulating levels of both seasonal and pandemic influenza require constant surveillance to ensure the health and safety of the population. While up-to-date information is critical, traditional surveillance systems can have data availability lags of up to two weeks. We introduce a novel method of estimating, in near-real time, the level of influenza-like illness (ILI) in the United States (US) by monitoring the rate of particular Wikipedia article views on a daily basis. We calculated the number of times certain influenza- or health-related Wikipedia articles were accessed each day between December 2007 and August 2013 and compared these data to official ILI activity levels provided by the Centers for Disease Control and Prevention (CDC). We developed a Poisson model that accurately estimates the level of ILI activity in the American population, up to two weeks ahead of the CDC, with an absolute average difference between the two estimates of just 0.27% over 294 weeks of data. Wikipedia-derived ILI models performed well through both abnormally high media coverage events (such as during the 2009 H1N1 pandemic) as well as unusually severe influenza seasons (such as the 2012–2013 influenza season). Wikipedia usage accurately estimated the week of peak ILI activity 17% more often than Google Flu Trends data and was often more accurate in its measure of ILI intensity. With further study, this method could potentially be implemented for continuous monitoring of ILI activity in the US and to provide support for traditional influenza surveillance tools.
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spelling pubmed-39905022014-04-21 Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in the United States in Near Real-Time McIver, David J. Brownstein, John S. PLoS Comput Biol Research Article Circulating levels of both seasonal and pandemic influenza require constant surveillance to ensure the health and safety of the population. While up-to-date information is critical, traditional surveillance systems can have data availability lags of up to two weeks. We introduce a novel method of estimating, in near-real time, the level of influenza-like illness (ILI) in the United States (US) by monitoring the rate of particular Wikipedia article views on a daily basis. We calculated the number of times certain influenza- or health-related Wikipedia articles were accessed each day between December 2007 and August 2013 and compared these data to official ILI activity levels provided by the Centers for Disease Control and Prevention (CDC). We developed a Poisson model that accurately estimates the level of ILI activity in the American population, up to two weeks ahead of the CDC, with an absolute average difference between the two estimates of just 0.27% over 294 weeks of data. Wikipedia-derived ILI models performed well through both abnormally high media coverage events (such as during the 2009 H1N1 pandemic) as well as unusually severe influenza seasons (such as the 2012–2013 influenza season). Wikipedia usage accurately estimated the week of peak ILI activity 17% more often than Google Flu Trends data and was often more accurate in its measure of ILI intensity. With further study, this method could potentially be implemented for continuous monitoring of ILI activity in the US and to provide support for traditional influenza surveillance tools. Public Library of Science 2014-04-17 /pmc/articles/PMC3990502/ /pubmed/24743682 http://dx.doi.org/10.1371/journal.pcbi.1003581 Text en © 2014 McIver, Brownstein http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
McIver, David J.
Brownstein, John S.
Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in the United States in Near Real-Time
title Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in the United States in Near Real-Time
title_full Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in the United States in Near Real-Time
title_fullStr Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in the United States in Near Real-Time
title_full_unstemmed Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in the United States in Near Real-Time
title_short Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in the United States in Near Real-Time
title_sort wikipedia usage estimates prevalence of influenza-like illness in the united states in near real-time
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3990502/
https://www.ncbi.nlm.nih.gov/pubmed/24743682
http://dx.doi.org/10.1371/journal.pcbi.1003581
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