Extreme Precipitation Mortality Prediction Model

Quantifies Future Excess Deaths

A prediction model integrating climate scenarios and socioeconomic pathways to project spatially resolved excess deaths.

Ban, Jie · Lu, Kailai · Liu, Yuanyuan · Zang, Jiawei · Zhou, Zhen · Zhang, Can · Huang, Jianbin · Chen, Yidan · Xuejie, Gao · Xu, Ying · Wang, Can · Cai, Wenjia · Gong, Peng · Luo, Yong · Li, Tiantian

The Lancet Planetary Health 2024

Specifications

Accidental mortality risk increase (%)

{'zh': '13.0', 'en': '13.0'} %

Annual average excess deaths (accidental)

{'zh': '2644', 'en': '2644'}

Circulatory disease mortality risk increase (%)

{'zh': '4.3', 'en': '4.3'} %

Respiratory disease mortality risk increase (%)

{'zh': '6.8', 'en': '6.8'} %

Increase in excess deaths by 2030s (RCP2.6-SSP2-S2)

{'zh': '1244', 'en': '1244'}

Advantages

Nationwide county-level coverage

The study includes 280 Chinese counties across different climate zones, providing high-spatial-resolution estimates of excess deaths, whereas previous studies were often limited to single cities or regions.

Future scenario projections

The model integrates three RCP emission scenarios and three SSP population scenarios to project excess deaths up to the 2090s, supporting long-term planning.

Disentangles climate and population contributions

The study quantifies the contributions of climate and population factors to changes in future excess deaths across climate zones, helping identify key drivers and target interventions.

Applications

• Public Health Planning：The model projects scenario-specific excess deaths from extreme precipitation, helping health authorities plan medical resources in advance.
• Climate Change Adaptation：Projections of future risks under different climate scenarios provide quantitative evidence for designing climate adaptation strategies.
• Disaster Risk Management：Identifies high-risk climate zones and regions to support disaster risk management and resource allocation.
• Health Early Warning Systems：Quantified health risks from extreme precipitation can be integrated into early warning systems to issue timely alerts and reduce deaths.