Effects of human mobility, temperature and mosquito control on the spatiotemporal transmission of dengue

登革热 传输(电信) 爆发 可预测性 埃及伊蚊 地理 环境卫生 载体(分子生物学) 登革热病毒 人口学 生物 生态学 病毒学 医学 计算机科学 统计 数学 基因 社会学 电信 幼虫 生物化学 重组DNA
作者
Guanghu Zhu,Tao Liu,Jianpeng Xiao,Bing Zhang,Tie Song,Yonghui Zhang,Lifeng Lin,Zhiqiang Peng,Aiping Deng,Wenjun Ma,Yuantao Hao
出处
期刊:Science of The Total Environment [Elsevier BV]
卷期号:651 (Pt 1): 969-978 被引量:87
标识
DOI:10.1016/j.scitotenv.2018.09.182
摘要

Dengue transmission exhibits evident geographic variations and seasonal differences. Such heterogeneity is caused by various impact factors, in which temperature and host/vector behaviors could drive its spatiotemporal transmission, but mosquito control could stop its progression. These factors together contribute to the observed distributions of dengue incidence from surveillance systems. To effectively and efficiently monitor and response to dengue outbreak, it would be necessary to systematically model these factors and their impacts on dengue transmission. This paper introduces a new modeling framework with consideration of multi-scale factors and surveillance data to clarify the hidden dynamics accounting for dengue spatiotemporal transmission. The model is based on compartmental system which takes into account the biting-based interactions among humans, viruses and mosquitoes, as well as the essential impacts of human mobility, temperature and mosquito control. This framework was validated with real epidemic data by applying retrospectively to the 2014 dengue epidemic in the Pearl River Delta (PRD) in southern China. The results indicated that suitable condition of temperature could be responsible for the explosive dengue outbreak in the PRD, and human mobility could be the causal factor leading to its spatial transmission across different cities. It was further found that mosquito intervention has significantly reduced dengue incidence, where a total of 52,770 (95% confidence interval [CI]: 29,231–76,308) dengue cases were prevented in the PRD in 2014. The findings can offer new insights for improving the predictability and risk assessment of dengue epidemics. The model also can be readily extended to investigate the transmission dynamics of other mosquito-borne diseases.
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