Keke Liu1, Xiang Hou2, Zhoupeng Ren3, Rachel Lowe4, Yiguan Wang5, Ruiyun Li6, Xiaobo Liu7, Jimin Sun8, Liang Lu7, Xiupin Song7, Haixia Wu7, Jun Wang7, Wenwu Yao8, Chutian Zhang9, Shaowei Sang10, Yuan Gao7, Jing Li11, Jianping Li12, Lei Xu13, Qiyong Liu14. 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, 102206, China; Shandong Academy of Clinical Medicine, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, China. 2. Shaanxi Key Laboratory for Animal Conservation, Shaanxi Institute of Zoology, Xi'an, 710032, China. 3. State Key Laboratory of Resources and Environmental Information System (LREIS), Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China. 4. Centre for Mathematical Modelling of Infectious Diseases and Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, United Kingdom; Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain. 5. School of Biological Sciences, University of Queensland, QLD, 4072, Australia. 6. MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London, W2 1PG, United Kingdom. 7. 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, 102206, China. 8. Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China. 9. College of Natural Resources and Environment, Northwest A&F University, Yangling, 712100, China. 10. Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, China. 11. Division of Environmental Health, School of Public Health and Management, Weifang Medical University, Weifang, 261053, Shandong Province, PR China. 12. Frontiers Science Center for Deep Ocean Multispheres and Earth System (FDOMES), Key Laboratory of Physical Oceanography, Institute for Advanced Ocean Studies, Ocean University of China, Qingdao 266100, China; Laboratory for Ocean Dynamics and Climate, Pilot Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China. Electronic address: ljp@ouc.edu.cn. 13. 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, 102206, China. Electronic address: xulei@icdc.cn. 14. 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, 102206, China. Electronic address: liuqiyong@icdc.cn.
Abstract
OBJECTIVE: To investigate the relationship between climate variables, East Asian summer monsoon (EASM) and large outbreaks of dengue in China. METHODS: We constructed ecological niche models (ENMs) to analyse the influence of climate factors on dengue occurrence and predict dengue outbreak areas in China. Furthermore, we formulated a generalised additive model (GAM) to quantify the impact of the EASM on dengue occurrence in mainland China from 1980 to 2016. RESULTS: Mean Temperature of Coldest Quarter had a 62.6% contribution to dengue outbreaks. Southern China including Guangdong, Guangxi, Fujian and Yunnan provinces are more vulnerable to dengue emergence and resurgence. In addition, we found population density had a 68.7% contribution to dengue widely distribution in China using ENMs. Statistical analysis indicated a dome-shaped association between EASM and dengue outbreak using GAM, with the greatest impact in the South-East of China. Besides, there was a positive nonlinear association between monthly average temperature and dengue occurrence. CONCLUSION: We demonstrated the influence of climate factors and East Asian summer monsoon on dengue outbreaks, providing a framework for future studies on the association between climate change and vector-borne diseases.
OBJECTIVE: To investigate the relationship between climate variables, East Asian summer monsoon (EASM) and large outbreaks of dengue in China. METHODS: We constructed ecological niche models (ENMs) to analyse the influence of climate factors on dengue occurrence and predict dengue outbreak areas in China. Furthermore, we formulated a generalised additive model (GAM) to quantify the impact of the EASM on dengue occurrence in mainland China from 1980 to 2016. RESULTS: Mean Temperature of Coldest Quarter had a 62.6% contribution to dengue outbreaks. Southern China including Guangdong, Guangxi, Fujian and Yunnan provinces are more vulnerable to dengue emergence and resurgence. In addition, we found population density had a 68.7% contribution to dengue widely distribution in China using ENMs. Statistical analysis indicated a dome-shaped association between EASM and dengue outbreak using GAM, with the greatest impact in the South-East of China. Besides, there was a positive nonlinear association between monthly average temperature and dengue occurrence. CONCLUSION: We demonstrated the influence of climate factors and East Asian summer monsoon on dengue outbreaks, providing a framework for future studies on the association between climate change and vector-borne diseases.
Authors: Muhammad Mazhar Iqbal; Irfan Abid; Saddam Hussain; Naeem Shahzad; Muhammad Sohail Waqas; Muhammad Jawed Iqbal Journal: Sci Total Environ Date: 2020-06-09 Impact factor: 7.963