Spatiotemporal expansion of Aedes aegypti and the dengue fever epidemic under climate change in China
PLOS Neglected Tropical Diseases·
- DOI
- 10.1371/journal.pntd.0013702
- PMID
- —
- PMCID
- —
- OpenAlex
- W4416572702
- Study type
- Mathematical modelling
- Publisher
- Public Library of Science (PLoS)
- Article type
- journal-article
- Integrity
- current
Why this research matters now
The projections are framed as a basis for anticipating dengue outbreaks and for guiding proactive, targeted vector and public health control strategies in China.
Structured evidence summary
Research question
The study asks how climate change may alter the geographic distribution, seasonal activity, and population dynamics of Aedes aegypti, and consequently dengue transmission risk, across China under different emissions pathways.
Study design
A modelling study combining a phenological model with a dynamical mathematical model, applied at the municipal level across China and in six representative cities under SSP1-2.6, SSP3-7.0, and SSP5-8.5 scenarios.
Population and setting
Geographic setting is China, assessed at the municipal level, with detailed simulations of mosquito population dynamics and dengue transmission in six representative cities (Guangzhou cited as an example).
Main findings
Climate warming is projected to accelerate Aedes aegypti development, with greatest risk under SSP5-8.5. By the 2090s, southern coastal cities may average about 26 life-cycle completions per year, around 90% of Chinese cities may sustain at least one annual generation, and the mosquito's range is expected to shift northward with peak abundance in September–October. The authors also project higher dengue incidence peaking later in the year (October–November), with Guangzhou peaks of up to 11,000 daily cases under a high-emission scenario.
Public-health relevance
The projections are framed as a basis for anticipating dengue outbreaks and for guiding proactive, targeted vector and public health control strategies in China.
Important limitations
This summary is limited to the supplied single-article abstract and bibliographic metadata; explicit limitations are not reported here, and the original paper is required for decision-grade interpretation.
GIDS interpretation
Indexed under dengue, China, climate and environment, outbreak investigation, and transmission dynamics; the abstract provides contextual modelling evidence relevant to vector-range and dengue-risk discovery, but no link to a live surveillance signal is made.
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 9 auditable classifier relationships to diseases, places, topics, and study design.