The driver of dengue fever incidence in two high-risk areas of China: A comparative study.
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
In China, the knowledge of the underlying causes of heterogeneous distribution pattern of dengue fever in different high-risk areas is limited. A comparative study will help us understand the influencing factors of dengue in different high-risk areas. In the study, we compared the effects of climate, mosquito density and imported cases on dengue fever in two high-risk areas using Generalized Additive Model (GAM), random forests and Structural Equation Model (SEM). GAM analysis identified a similar positive correlation between imported cases, density of Aedes larvae, climate variables and dengue fever occurrence in the studied high-risk areas of both Guangdong and Yunnan provinces. Random forests showed that the most important factors affecting dengue fever occurrence were the number of imported cases, BI and the monthly average minimum temperature in Guangdong province; whereas the imported cases, the monthly average temperature and monthly relative humidity in Yunnan province. We found the rainfall had the indirect effect on dengue fever occurrence in both areas mediated by mosquito density; while the direct effect in high-risk areas of Guangdong was dominated by temperature and no obvious effect in Yunnan province by SEM. In total, climate factors and mosquito density are the key drivers on dengue fever incidence in different high-risk areas of China. These findings could provide scientific evidence for early warning and the scientific control of dengue fever in high-risk areas.
Date Issued
2019-12-20
Date Acceptance
2019-12-06
Citation
Scientific Reports, 2019, 9 (1), pp.1-9
ISSN
2045-2322
Publisher
Nature Publishing Group
Start Page
1
End Page
9
Journal / Book Title
Scientific Reports
Volume
9
Issue
1
Copyright Statement
© The Author(s) 2019. This article is licensed under a Creative Commons Attribution 4.0 International
License, which permits use, sharing, adaptation, distribution and reproduction in any medium or
format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Te images or other third party material in this
article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the
material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the
copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
License, which permits use, sharing, adaptation, distribution and reproduction in any medium or
format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Te images or other third party material in this
article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the
material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the
copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/31862993
PII: 10.1038/s41598-019-56112-8
Subjects
0601 Biochemistry and Cell Biology
0299 Other Physical Sciences
Publication Status
Published
Coverage Spatial
England
Date Publish Online
2019-12-20