Hand, foot, and mouth disease (HFMD) is highly prevalent in China, and more efficient methods of epidemic detection and early warning need to be developed to augment traditional surveillance systems. In this paper, a method that uses Baidu search queries to track and predict HFMD epidemics is presented, and the outbreaks of HFMD in China during the 60-month period from January 2011 to December 2015 are predicted. The Pearson correlation coefficient (R) of the predictive model and the mean absolute percentage errors between observed HFMD case counts and the predicted number show that our predictive model gives excellent fit to the data. This implies that Baidu search queries can be used in China to track and reliably predict HFMD epidemics, and can serve as a supplement to official systems for HFMD epidemic surveillance.
