Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/91990
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Type: Journal article
Title: Predicting local dengue transmission in Guangzhou, China, through the influence of imported cases, mosquito density and climate variability
Author: Sang, S.
Yin, W.
Bi, P.
Zhang, H.
Wang, C.
Liu, X.
Chen, B.
Yang, W.
Liu, Q.
Citation: PLoS One, 2014; 9(7):e1027550-1-e1027550-10
Publisher: Public Library of Science
Issue Date: 2014
ISSN: 1932-6203
1932-6203
Statement of
Responsibility: 
Shaowei Sang, Wenwu Yin, Peng Bi, Honglong Zhang, Chenggang Wang, Xiaobo Liu, Bin Chen, Weizhong Yang, Qiyong Liu
Abstract: INTRODUCTION: Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF), a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue's control and prevention purpose. METHODOLOGY AND PRINCIPAL FINDINGS: Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA) was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC) and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8%) imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags. CONCLUSIONS: Imported DF cases and mosquito density play a critical role in local DF transmission, together with weather variables. The establishment of an early warning system, using existing surveillance datasets will help to control and prevent dengue in Guangzhou, China.
Keywords: Animals; Humans; Culicidae; Dengue; Risk Factors; Humidity; Temperature; Climate; Disease Outbreaks; Population Density; Geography; Principal Component Analysis; Forecasting; China
Description: Published: July 14, 2014
Rights: © 2014 Sang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
RMID: 0030014963
DOI: 10.1371/journal.pone.0102755
Appears in Collections:Public Health publications

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