Analysis of heterogeneous dengue transmission in Guangdong in 2014 with multivariate time series model.
Guangdong experienced the largest dengue epidemic in recent history. In 2014, the number of dengue cases was the highest in the previous 10 years and comprised more than 90% of all cases. In order to analyze heterogeneous transmission of dengue, a multivariate time series model decomposing dengue risk additively into endemic, autoregressive and spatiotemporal components was used to model dengue transmission. Moreover, random effects were introduced in the model to deal with heterogeneous dengue transmission and incidence levels and power law approach was embedded into the model to account for spatial interaction. There was little spatial variation in the autoregressive component. In contrast, for the endemic component, there was a pronounced heterogeneity between the Pearl River Delta area and the remaining districts. For the spatiotemporal component, there was considerable heterogeneity across districts with highest values in some western and eastern department. The results showed that the patterns driving dengue transmission were found by using clustering analysis. And endemic component contribution seems to be important in the Pearl River Delta area, where the incidence is high (95 per 100,000), while areas with relatively low incidence (4 per 100,000) are highly dependent on spatiotemporal spread and local autoregression.
Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, 410073 Changsha, China.|College of Information System and Management, National University of Defense Technology, 410073 Changsha, China.
Qing
Q
Cheng
College of Information System and Management, National University of Defense Technology, 410073 Changsha, China.|Flowminder Foundation, 17177 Stockholm, Sweden.|Department of Public Health Sciences, Karolinska Institutet, 17177 Stock-holm, Sweden.|Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing 102206, P. R. China.
Xin
X
Lu
School of Public Health, Li Kashing Faculty of Medicine, Hong Kong University, Hong Kong Special Administrative Region, China.
Joseph T
JT
Wu
Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, 410073 Changsha, China.|College of Information System and Management, National University of Defense Technology, 410073 Changsha, China.
Zhong
Z
Liu
Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, 410073 Changsha, China.|College of Information System and Management, National University of Defense Technology, 410073 Changsha, China.
Jincai
J
Huang
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