ArticleScientific reports2019
The driver of dengue fever incidence in two high-risk areas of China: A comparative study.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 25 citations in OpenAlex.
- Dengue transmission dynamics in China's border regions adjacent to Myanmar.Infectious diseases of poverty · 2026Article
- Projecting the impacts of climate and land-use change on avian influenza suitability in Bangladesh.One health (Amsterdam, Netherlands) · 2025Article
- Emergence and expansion of dengue in Paltas: possible implications of the COVID-19 pandemic and climatic variations.Tropical medicine and health · 2025Article
- Improving dengue fever predictions in Taiwan based on feature selection and random forests.BMC infectious diseases · 2024Article
- The epidemiology ofFrontiers in public health · 2023Article
- Article
- Epidemiological Characteristics and the Dynamic Transmission Model of Dengue Fever in Zhanjiang City, Guangdong Province in 2018.Tropical medicine and infectious disease · 2022Article
- Long-Term Effects of Climate Variability on Seed Rain Dynamics of Four Fagaceae Sympatric Species in Qinling Mountains, China.Biology · 2022Article
- Epidemiology of Indigenous Dengue Cases in Zhejiang Province, Southeast China.Frontiers in public health · 2022Article
- Molecular epidemiology of mosquito-borne viruses at the China-Myanmar border: discovery of a potential epidemic focus of Japanese encephalitis.Infectious diseases of poverty · 2021Article
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17 authors at 9 institutions in 3 countries.
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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.
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