title: Using Baidu Search Index to Predict Dengue Outbreak in China.
abstract: This study identified the possible threshold to predict dengue fever (DF) outbreaks using Baidu Search Index (BSI). Time-series classification and regression tree models based on BSI were used to develop a predictive model for DF outbreak in Guangzhou and Zhongshan, China. In the regression tree models, the mean autochthonous DF incidence rate increased approximately 30-fold in Guangzhou when the weekly BSI for DF at the lagged moving average of 1-3 weeks was more than 382. When the weekly BSI for DF at the lagged moving average of 1-5 weeks was more than 91.8, there was approximately 9-fold increase of the mean autochthonous DF incidence rate in Zhongshan. In the classification tree models, the results showed that when the weekly BSI for DF at the lagged moving average of 1-3 weeks was more than 99.3, there was 89.28% chance of DF outbreak in Guangzhou, while, in Zhongshan, when the weekly BSI for DF at the lagged moving average of 1-5 weeks was more than 68.1, the chance of DF outbreak rose up to 100%. The study indicated that less cost internet-based surveillance systems can be the valuable complement to traditional DF surveillance in China.
authors.affiliation: School of Public Health, Key Laboratory of Tropical Diseases Control of Ministry of Education, Sun Yat-Sen University, Guangzhou, P. R. China.|Zhongshan Research Institute of Public Health, School of Public Health, Sun Yat-Sen University, Zhongshan, P. R. China.|School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia.
authors.forename: Kangkang
authors.initials: K
authors.lastname: Liu
authors.affiliation: Zhongshan Research Institute of Public Health, School of Public Health, Sun Yat-Sen University, Zhongshan, P. R. China.|Zhongshan Center for Diseases Control and Prevention, Zhongshan, P. R. China.
authors.forename: Tao
authors.initials: T
authors.lastname: Wang
authors.affiliation: Guangzhou Center for Disease Control and Prevention, Guangzhou, P. R. China.
authors.forename: Zhicong
authors.initials: Z
authors.lastname: Yang
authors.affiliation: School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia.
authors.forename: Xiaodong
authors.initials: X
authors.lastname: Huang
authors.affiliation: School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia.|School of Medicine, University of Queensland, Brisbane, Australia.
authors.forename: Gabriel J
authors.initials: GJ
authors.lastname: Milinovich
authors.affiliation: School of Public Health, University at Albany, State University of New York, Albany, United States.
authors.forename: Yi
authors.initials: Y
authors.lastname: Lu
authors.affiliation: School of Public Health, Key Laboratory of Tropical Diseases Control of Ministry of Education, Sun Yat-Sen University, Guangzhou, P. R. China.|Zhongshan Research Institute of Public Health, School of Public Health, Sun Yat-Sen University, Zhongshan, P. R. China.|Guangzhou Center for Disease Control and Prevention, Guangzhou, P. R. China.
authors.forename: Qinlong
authors.initials: Q
authors.lastname: Jing
authors.affiliation: School of Public Health, Key Laboratory of Tropical Diseases Control of Ministry of Education, Sun Yat-Sen University, Guangzhou, P. R. China.|Zhongshan Research Institute of Public Health, School of Public Health, Sun Yat-Sen University, Zhongshan, P. R. China.
authors.forename: Yao
authors.initials: Y
authors.lastname: Xia
authors.affiliation: Guangzhou Center for Disease Control and Prevention, Guangzhou, P. R. China.
authors.forename: Zhengyang
authors.initials: Z
authors.lastname: Zhao
authors.affiliation: School of Public Health, Key Laboratory of Tropical Diseases Control of Ministry of Education, Sun Yat-Sen University, Guangzhou, P. R. China.|Zhongshan Research Institute of Public Health, School of Public Health, Sun Yat-Sen University, Zhongshan, P. R. China.|The School of Food Science, Guangdong Pharmaceutical University, Guangzhou, P. R. China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Yang
authors.affiliation: School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia.
authors.forename: Shilu
authors.initials: S
authors.lastname: Tong
authors.affiliation: School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia.
authors.forename: Wenbiao
authors.initials: W
authors.lastname: Hu
authors.affiliation: School of Public Health, Key Laboratory of Tropical Diseases Control of Ministry of Education, Sun Yat-Sen University, Guangzhou, P. R. China.|Zhongshan Research Institute of Public Health, School of Public Health, Sun Yat-Sen University, Zhongshan, P. R. China.|Institute of Emergency Technology for Serious Infectious Diseases Control and Prevention, Guangdong Provincial Department of Science and Technology; Emergency Management Office, the People's Government of Guangdong Province, Guangzhou, P. R. China.
authors.forename: Jiahai
authors.initials: J
authors.lastname: Lu
mesh_terms: D002681:China / Q000453:epidemiology; D003715:Dengue / Q000453:epidemiology*; D004196:Disease Outbreaks; D006801:Humans; D015233:Models, Statistical; D011159:Population Surveillance; D012044:Regression Analysis