Abstract
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.
Highlights
Each year, there are an estimated 250,000–500,000 deaths worldwide that are attributed to seasonal influenza [1], with anywhere between 3,000–50,000 deaths occurring in the United States of America (US) [2]
Influenza is largely avoidable through vaccination, between 3,000–50,000 deaths occur in the United States each year that are attributed to this disease
The Centers for Disease Control and Prevention continuously monitor the amount of influenza that is present in the American population and compiles this information in weekly reports
Summary
There are an estimated 250,000–500,000 deaths worldwide that are attributed to seasonal influenza [1], with anywhere between 3,000–50,000 deaths occurring in the United States of America (US) [2]. In the US, the Centers for Disease Control and Prevention (CDC) continuously monitors the level of influenza-like illness (ILI) circulating in the population by gathering information from sentinel programs which include virologic data as well as clinical data, such as physicians who report on the percentage of patients seen who are exhibiting influenza-like illness [2]. The most notable of these attempts to date has been Google Flu Trends (GFT), a proprietary system designed by Google, which uses Google search terms that are correlated with ILI activity in the US to make a estimation of the current level of ILI [12]. Google Flu Trends was initially quite successful in its estimation of ILI activity, but was shown to falter in the face of the 2009 H1N1 swine influenza pandemic (pH1N1) due to much-increased levels of media attention surrounding the pandemic [13]. In the face of these obstacles, Google has continued to update and re-evaluate its models [15,16,17]
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