Editors,
The recent paper on Using Google Trends (GT) to Estimate the Incidence of Influenza-Like Illness in Argentina 1 is very interesting. Orellano et al. studied Google Flu Trends (GFT) and GT with a conclusion regarding “the utility of GT to complement influenza surveillance”. Indeed, the usefulness of GFT and GT has been mentioned in some earlier reports 2,3. However, as a computational model, there are several things to be considered in the simulation 4. Under- or over-estimation can be expected and this is still the present problem in using the Google system for predicting influenza 4. There is a need for modifications of GT and GFT into a more specific tool that is appropriate for each context. A good example of this is the development of FluBreaks by Pervaiz et al. 5.
References
- 1Orellano PW, Reynoso JI, Antman J, Argibay O. Uso de la herramienta Google Trends para estimar la incidencia de enfermedades tipo influenza en Argentina. Cad Saúde Pública 2015; 31:691-700.
- 2Araz OM, Bentley D, Muelleman RL. Using Google Flu Trends data in forecasting influenza-like-illness related ED visits in Omaha, Nebraska. Am J Emerg Med 2014; 32:1016-23.
- 3Malik MT, Gumel A, Thompson LH, Strome T, Mahmud SM. “Google flu trends” and emergency department triage data predicted the 2009 pandemic H1N1 waves in Manitoba. Can J Public Health 2011; 102:294-7.
- 4Wiwanitkit V. Google Flu for forecasting influenza-like illness. Am J Emerg Med 2014; 32:1417.
- 5Pervaiz F, Pervaiz M, Abdur Rehman N, Saif U. FluBreaks: early epidemic detection from Google flu trends. J Med Internet Res 2012; 14:e125.
