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Background <p>Dengue risk is increasingly shaped by climate change and rapid urbanization, yet comprehensive, multidimensional risk assessments grounded in a One Health perspective remain scare.</p> Methods <p>We develop a geographically eXplainable artificial intelligence (GeoXAI) model to estimate dengue hazard across China in 2024 (current), 2050, and 2100 under different shared socioeconomic pathway (SSP) scenarios. A hazard-exposure-vulnerability framework is then used to assess dengue risk by integrating dengue hazard, human exposure, and social vulnerability.</p> Results <p>Here we show a northward expansion of high-hazard areas, with the minimum temperature in the coldest month being the dominant driver (27.2% contribution). Moreover, socioeconomic factors such as population density (3.8%) and urbanization level (2.7%) will further amplify dengue hazard. Current dengue risk assessments reveal high-risk clusters in Southwest China and megacities. Dengue risk exhibits spatially heterogeneous escalation in the future, with Southwest and Southeast China facing the steepest growth and Northwest China experiencing disproportionate increases. Compared to the current, dengue risk in SSP585—a high greenhouse gas emission scenario and limited climate policy interventions—increases by 6.01% (2050) and 8.21% (2100), representing the largest escalation among the three SSPs.</p> Conclusions <p>Despite ongoing disease control efforts, our findings underscore the need to intensify integrated surveillance and multidimensional intervention strategies against escalating dengue risk in China, and offers lessons for other prevalent <i>Aedes</i>-borne diseases (e.g., chikungunya).</p>

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Climate and socioeconomic factors drive heterogeneous dengue risk escalation in the Chinese population

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月3日

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  • Xu Guang,
  • Yifei He,
  • Mengjie Geng,
  • Meifang Liu,
  • Jia Wan,
  • Dongfeng Kong,
  • Zhen Zhang,
  • Lanbin Xiang,
  • Liangqiang Lin,
  • Rongxin He,
  • Ning Zhang,
  • Felipe Arley Costa Pessoa,
  • Claudia Maria Ríos Velasquez,
  • Carolina Mercedes Laurent Singh,
  • Pritesh Lalwani,
  • Jie Huang,
  • Haidong Wang,
  • Jue Liu,
  • Bin Zhu

摘要

Background

Dengue risk is increasingly shaped by climate change and rapid urbanization, yet comprehensive, multidimensional risk assessments grounded in a One Health perspective remain scare.

Methods

We develop a geographically eXplainable artificial intelligence (GeoXAI) model to estimate dengue hazard across China in 2024 (current), 2050, and 2100 under different shared socioeconomic pathway (SSP) scenarios. A hazard-exposure-vulnerability framework is then used to assess dengue risk by integrating dengue hazard, human exposure, and social vulnerability.

Results

Here we show a northward expansion of high-hazard areas, with the minimum temperature in the coldest month being the dominant driver (27.2% contribution). Moreover, socioeconomic factors such as population density (3.8%) and urbanization level (2.7%) will further amplify dengue hazard. Current dengue risk assessments reveal high-risk clusters in Southwest China and megacities. Dengue risk exhibits spatially heterogeneous escalation in the future, with Southwest and Southeast China facing the steepest growth and Northwest China experiencing disproportionate increases. Compared to the current, dengue risk in SSP585—a high greenhouse gas emission scenario and limited climate policy interventions—increases by 6.01% (2050) and 8.21% (2100), representing the largest escalation among the three SSPs.

Conclusions

Despite ongoing disease control efforts, our findings underscore the need to intensify integrated surveillance and multidimensional intervention strategies against escalating dengue risk in China, and offers lessons for other prevalent Aedes-borne diseases (e.g., chikungunya).