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Background: Hand foot Mouth Disease (HFMD) is a worldwide Enteroviral infection; severe outbreaks have occurred recently in the US and Asia. Google technology has been shown to predict influenza epidemics and is a potential resource to track epidemics in developed countries where the use of Web-based searches is prevalent.Methods: Google Trends and Google Correlate were used to enumerate Web based search queries related to HFMD in three Asian regions and were compared to known seasonal variations and standard surveillance data to investigate for strong correlation. We also test whether a mathematical model, constructed using Google Correlate, would have been able to predict, in retrospect, an outbreak of HFMD in Singapore.Results:  HFMD-related search queries strongly correlated to known HFMD seasonal variation and standard surveillance data. Our mathematical model of Singaporean HFMD did predict the magnitude and chronology of the summer 2012 outbreak.Conclusions: Given the correlation of Google technology with known HFMD seasonal patterns and surveillance data in select Asian regions, this technology shows enormous potential for HFMD surveillance. Further prospective studies are needed to validate the utility of Google technology in HFMD surveillance.

Hand Foot Mouth Disease (HFMD) is a worldwide Enteroviral infection. Severe outbreaks have recently occurred in the US and Asia. Google technology has been shown to predict influenza epidemics and is a potential resource to track epidemics in developed countries where the use of Web-based searches is prevalent. Google Trends and Google Correlate were used to enumerate Web-based search queries related to HFMD in three Asian regions and were compared to known seasonal variations and standard surveillance data to investigate correlations. We also tested whether a mathematical model, constructed using Google Correlate, would have predicted an outbreak of HFMD in Singapore. HFMD-related search queries strongly correlated to known HFMD seasonal variation and standard surveillance data. Our mathematical model of Singaporean HFMD predicted the magnitude and chronology of the summer 2012 HFMD outbreak. Google technology shows enormous potential for HFMD surveillance. Further prospective studies are needed to validate the utility of Google technology in HFMD surveillance.