ArticlePLoS neglected tropical diseases2023
The relative importance of key meteorological factors affecting numbers of mosquito vectors of dengue fever.
Article in PLoS neglected tropical diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Spatiotemporal patterns and meteorological associations of mosquito density: insights from mosquito surveillance in Chengdu, China.Frontiers in cellular and infection microbiology · 2026Article
- How technologies are driving digital innovation in mosquito surveillance systems: a global scoping review over the past decade.BMJ public health · 2026Article
- A novel approach to quantify the optimal range and causal effect of rainfall on vector-borne diseases: a case study of dengue epidemics.Journal of the Royal Society, Interface · 2025Article
- Assessing the influencing factors of dengue fever in Chinese mainland based on causal analysis.Scientific reports · 2025Article
- Article
- Spatial and temporal characterization of Aedes albopictus oviposition activity in candidate urban settings for sterile insect technique testing in La Reunion Island.Infectious diseases of poverty · 2024Article
- Integrating dynamic models and neural networks to discover the mechanism of meteorological factors on Aedes population.PLoS computational biology · 2024Article
- Article
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Abstract
Although single factors such as rainfall are known to affect the population dynamics of Aedes albopictus, the main vector of dengue fever in Eurasia, the synergistic effects of different meteorological factors are not fully understood. To address this topic, we used meteorological data and mosquito-vector association data including Breteau and ovitrap indices in key areas of dengue outbreaks in Guangdong Province, China, to formulate a five-stage mathematical model for Aedes albopictus population dynamics by integrating multiple meteorological factors. Unknown parameters were estimated using a genetic algorithm, and the results were analyzed by k-Shape clustering, random forest and grey correlation analysis. In addition, the population density of mosquitoes in 2022 was predicted and used for evaluating the effectiveness of the model. We found that there is spatiotemporal heterogeneity in the effects of temperature and rainfall and their distribution characteristics on the diapause period, the numbers of peaks in mosquito densities in summer and the annual total numbers of adult mosquitoes. Moreover, we identified the key meteorological indicators of the mosquito quantity at each stage and that rainfall (seasonal rainfall and annual total rainfall) was more important than the temperature distribution (seasonal average temperature and temperature index) and the uniformity of rainfall annual distribution (coefficient of variation) for most of the areas studied. The peak rainfall during the summer is the best indicator of mosquito population development. The results provide important theoretical support for the future design of mosquito vector control strategies and early warnings of mosquito-borne diseases.
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