AI 中文总结
该研究构建整合多尺度模型，结合气候、人口与流动性数据，分析21世纪欧洲登革热风险，发现最坏排放情景下风险向环境驱动过渡，需将流动性与人口再分布纳入温带虫媒病预测模型。
AI 中文摘要
近几十年虫媒病毒暴发增多表明，受气候变化影响，欧洲本地虫媒病毒暴发风险预计会上升。欧洲历史上非地方流行，因此确定哪些人群可能暴露、在何种条件下暴露，对构建真正可靠的流行病防范能力至关重要。我们提出一种整合多尺度模型，将机械传播引擎与媒介丰度框架融合，嵌入由人类、媒介及航空交通运动驱动的流动性介导的集合种群系统。为此，我们结合气候与人口预测及流动性数据，估算并绘制21世纪欧洲登革热出现风险图。此外，我们引入专用迁移模型，探究气候驱动的人口再分布如何改变该风险。若气候未出现重大临界点，在多数排放情景下，模型推导的风险指标将大幅上升。时空风险仍主要由输入病例驱动，但结果表明将逐步向环境驱动机制过渡，尤其在最坏排放情景下。为更好预测和管理反复出现的虫媒病毒暴发，研究结果强调需将流动性路径与气候驱动的人口再分布纳入温带地区虫媒疾病出现预测模型。
英文摘要
The risk of local arbovirus outbreaks in Europe is expected to increase due to climate change, as suggested by the multiplication of arbovirus outbreaks in the last decades. Europe has historically been a non-endemic region, making it vital to pinpoint which populations are potentially exposed -and under which conditions- so we can build truly robust epidemic preparedness capabilities. We introduce an integrated, multi-scale model that fuses a mechanistic transmission engine with a vector abundance framework, all embedded in a mobility-driven metapopulation system capturing human, vector, and air-traffic movement. To this end, we combine climate and population projections with mobility data to estimate and map dengue emergence risk in Europe throughout the 21st century. Additionally, we introduce a dedicated migration model that explores how climate-driven population redistribution could alter these risk estimates.Assuming the climate avoids major tipping points, model-derived risk indicators increase substantially under most emissions scenarios. While the spatio-temporal risk will remain largely driven by importation, our results indicate a gradual transition toward an environment-driven regime, particularly under the worst-case emissions scenario. To better anticipate and manage recurrent arbovirus outbreaks, our findings highlight the need to integrate mobility pathways and climate-driven population redistribution into predictive models of vector-borne disease emergence in temperate regions.
Comments36 pages, 25 figures
