Spatiotemporal patterns and determinants of dengue at county level in China from 2005-2017

Keke Liu; Jimin Sun; Xiaobo Liu; Ruiyun Li; Yiguan Wang; Liang Lu; Haixia Wu; Yuan Gao; Lei Xu; Qiyong Liu

doi:10.1016/j.ijid.2018.09.003

Spatiotemporal patterns and determinants of dengue at county level in China from 2005-2017

Int J Infect Dis. 2018 Dec:77:96-104. doi: 10.1016/j.ijid.2018.09.003. Epub 2018 Sep 12.

Authors

Keke Liu¹, Jimin Sun², Xiaobo Liu¹, Ruiyun Li³, Yiguan Wang⁴, Liang Lu¹, Haixia Wu¹, Yuan Gao¹, Lei Xu⁵, Qiyong Liu⁶

Affiliations

¹ State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
² State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China; Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
³ Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, N-0316 Oslo, Norway.
⁴ School of Biological Sciences, University of Queensland, QLD 4072, Australia.
⁵ State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China; Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, N-0316 Oslo, Norway. Electronic address: lei.xu@ibv.uio.no.
⁶ State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China. Electronic address: liuqiyong@icdc.cn.

PMID: 30218814
DOI: 10.1016/j.ijid.2018.09.003

Abstract

Objective: To identify the high risk spatiotemporal clusters of dengue cases and explore the associated risk factors.

Methods: Monthly indigenous dengue cases in 2005-2017 were aggregated at county level. Spatiotemporal cluster analysis was used to explore dengue distribution features using SaTScan9.4.4 and Arcgis10.3.0. In addition, the influential factors and potential high risk areas of dengue outbreaks were analyzed using ecological niche models in Maxent 3.3.1 software.

Results: We found a heterogeneous spatial and temporal distribution pattern of dengue cases. The identified high risk region in the primary cluster covered 13 counties in Guangdong Province and in the secondary clusters included 14 counties in Yunnan Province. Additionally, there was a nonlinear association between meteorological and environmental factors and dengue outbreaks, with 8.5%-57.1%, 6.7%-38.3% and 3.2%-40.4% contribution from annual average minimum temperature, land cover and annual average precipitation, respectively.

Conclusions: The high risk areas of dengue outbreaks mainly are located in Guangdong and Yunnan Provinces, which are significantly shaped by environmental and meteorological factors, such as temperature, precipitation and land cover.

Keywords: China; Dengue; Ecological niche models; Spatiotemporal distribution.

MeSH terms

China / epidemiology
Cluster Analysis
Dengue / diagnosis
Dengue / epidemiology*
Disease Outbreaks*
Humans
Meteorological Concepts
Risk Factors
Socioeconomic Factors
Spatio-Temporal Analysis