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. 2017 Jun;145(8):1699-1707.
doi: 10.1017/S0950268817000231. Epub 2017 Feb 22.

Tracking and predicting hand, foot, and mouth disease (HFMD) epidemics in China by Baidu queries

Q Y Xiao  1 , H J Liu  2 , M W Feldman  2
Affiliations

Tracking and predicting hand, foot, and mouth disease (HFMD) epidemics in China by Baidu queries

Q Y Xiao et al. Epidemiol Infect. 2017 Jun.

Abstract

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.

Keywords: Epidemics; HFMD; prediction; search query.

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Conflict of interest statement

None.

Figures

Fig. 1.
Fig. 1.
Tracking and predicting outbreaks of HFMD epidemics in China during 60 months. (a–f) Describe the tracking and prediction of HFMD epidemics in Mainland China by Baidu queries during 60 months (from January 2011 to December 2015). (a) Predicts HFMD cases from the 25th to the 36th month, (c) predicts HFMD cases from the 37th to the 48th month, and (e) predicts HFMD cases from the 49th to the 60th month. (b, d, f) Compare the predicted and actual number within the corresponding period.
See this image and copyright information in PMC

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