Using Web Queries for Influenza Surveillance
Author Information
Author(s): Hulth Anette, Rydevik Gustaf, Linde Annika
Primary Institution: Swedish Institute for Infectious Disease Control
Hypothesis
Queries on influenza and influenza-like illness would provide a basis for the estimation of the timing of the peak and the intensity of the yearly influenza outbreaks that would be as good as the existing laboratory and sentinel surveillance.
Conclusion
Web queries can accurately estimate the timing and intensity of influenza outbreaks, similar to traditional surveillance methods.
Supporting Evidence
- Web queries on influenza follow the same pattern as laboratory and sentinel surveillance data.
- Web queries provide access to individuals who may not yet be seeking medical care.
- The study used data from two influenza seasons to validate the models.
- Partial least squares regression was used to handle highly correlated data.
- Web queries can serve as a cost-effective source for syndromic surveillance.
Takeaway
People search for information about the flu online, and this can help predict when flu outbreaks will happen, just like doctors' reports do.
Methodology
Analyzed search logs from a medical website for two influenza seasons and used partial least squares regression to create estimation models.
Potential Biases
The data were aggregated on a national level, which may not represent local outbreaks accurately.
Limitations
The study only analyzed data from a single medical website and did not account for individual user demographics.
Participant Demographics
The majority of visitors to the website were women aged 21-35, primarily from Stockholm County.
Digital Object Identifier (DOI)
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