The relative importance of key meteorological factors affecting numbers of mosquito vectors of dengue fever
PLOS Neglected Tropical Diseases·
- DOI
- 10.1371/journal.pntd.0011247
- PMID
- —
- PMCID
- —
- OpenAlex
- W4365457494
- Study type
- Mathematical modelling
- Publisher
- Public Library of Science (PLoS)
- Article type
- journal-article
- Integrity
- current
Why this research matters now
The paper says the model may support future mosquito control strategies and early warning for mosquito-borne disease risk.
Structured evidence summary
Research question
To assess how multiple meteorological factors relate to the population dynamics of Aedes albopictus in dengue outbreak areas of Guangdong Province, China.
Study design
A mathematical modelling study that integrated meteorological data with mosquito-vector association data and used genetic algorithm estimation plus clustering, random forest, and grey correlation analyses.
Population and setting
Aedes albopictus in key dengue outbreak areas of Guangdong Province, China.
Main findings
The abstract reports spatiotemporal heterogeneity in how temperature and rainfall relate to mosquito diapause, summer density peaks, and annual adult mosquito totals. It also states that rainfall-related indicators were more important than temperature-related indicators for most areas, and that peak summer rainfall was the best indicator of mosquito population development.
Public-health relevance
The paper says the model may support future mosquito control strategies and early warning for mosquito-borne disease risk.
Important limitations
No explicit study limitations are stated in the supplied abstract; this summary is therefore limited to the single-article abstract and metadata and should be checked against the full paper for decision-grade interpretation.
GIDS interpretation
This article is contextually discoverable as a dengue, China, climate-and-environment, and transmission-dynamics paper, but the supplied evidence only supports metadata-based interpretation and not any live surveillance signal.
Related GIDS surveillance
Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.
Evidence relationships
This article has 10 auditable classifier relationships to diseases, places, topics, and study design.