| Literature DB >> 30360290 |
Guanghu Zhu1, Tao Liu2, Jianpeng Xiao2, Bing Zhang2, Tie Song3, Yonghui Zhang3, Lifeng Lin3, Zhiqiang Peng3, Aiping Deng3, Wenjun Ma4, Yuantao Hao5.
Abstract
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.Entities:
Keywords: Human mobility; Mosquito control; Mosquito-borne disease; Risk factors; Spatiotemporal transmission dynamics
Mesh:
Year: 2018 PMID: 30360290 DOI: 10.1016/j.scitotenv.2018.09.182
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 7.963