A new study describes how Google Flu Trends (GFT) harnesses the power of the search engine to detect influenza outbreaks in near-real time, by monitoring public Internet queries.

Researchers at Johns Hopkins University (JHU; Baltimore, MD, USA) and George Washington University (GWU; Washington, DC, USA) collected weekly data from January 2009 through October 2010, to assess the temporal correlation of GFT data to cases of influenza and standard crowding indices from an emergency department (ED) in Baltimore (MD, USA). The data collected included influenza-like illness (ILI) data; laboratory-confirmed influenza data; and ED crowding indices (patient volume, number of patients who left without being seen, waiting room time, and length of stay for admitted and discharged patients). Both pediatric and adult data were analyzed separately using cross-correlation with GFT.

The results showed that city-level GFT data has a strong correlation with influenza cases and ED ILI visits, as well as several pediatric ED crowding measures such as total ED volume and leaving without being seen; the same was true for low-acuity adult patients. On the other hand, other adult crowding measures for low-acuity patients, such as waiting room time and length of stay for discharged patients, had only moderate correlation with GFT. The study was published ahead of print on January 8, 2012, in Clinical Infectious Diseases.

“EDs must be able to respond to a surge in medical need for both seasonal and pandemic influenza. Because many EDs already operate at or near capacity, accurate and timely surveillance, coupled with planned response measures, is essential,” concluded lead author Andrea Freyer Dugas, MD, of the JHU department of Emergency Medicine, and colleagues. “The study highlights the potential usefulness of Internet-based search data on ED-based strategies to better match the supply of ED resources to surges in demand that occur during influenza outbreaks.”

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