Data availability
The data generated in this study are available under restricted access for regulations imposed by the ethics committee, and the raw datasets used in this study are not publicly accessible. However, researchers can contact the corresponding author (litiantian@nieh.chinacdc.cn) to request access to the data for reproducibility analysis or collaborative research. Requests will be answered within 12 weeks. The exposure data for air pollution used in this study was available from the National Urban Air Quality Real-Time Release Platform (https://air.cnemc.cn:18007/); the meteorological exposure data used in this study were sourced from the ERA5-Land reanalysis dataset released by European Center for Medium-Range Weather Forecasts ...
Data availability
The data generated in this study are available under restricted access for regulations imposed by the ethics committee, and the raw datasets used in this study are not publicly accessible. However, researchers can contact the corresponding author (litiantian@nieh.chinacdc.cn) to request access to the data for reproducibility analysis or collaborative research. Requests will be answered within 12 weeks. The exposure data for air pollution used in this study was available from the National Urban Air Quality Real-Time Release Platform (https://air.cnemc.cn:18007/); the meteorological exposure data used in this study were sourced from the ERA5-Land reanalysis dataset released by European Center for Medium-Range Weather Forecasts (https://cds.climate.copernicus.eu/datasets/reanalysis-era5-land?tab=overview). Source data are provided in this paper.
Code availability
Code used in this study is available online at (https://github.com/Zhangjingwei-cdc-tj/Stroke_heat_risk_grading_prediction_model_NatureComm), under the MIT license. The specific version of the code associated with this publication is archived in Zenodo and is accessible via https://doi.org/10.5281/zenodo.1771830743.
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Acknowledgements
This study was supported by the Capital’s Funds for Health Improvement and Research (CFH2024-1G-4231, T.L.), National Natural Science Foundation of China (82425051, T.L.; 82241051, T.L.) and the National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (2024NITFID601, T.L.).
Author information
Authors and Affiliations
National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
Jingwei Zhang, Mengxue Zhang, Qinghua Sun, Runmei Ma, Can Zhang, Kailai Lu, Qixuan Dong & Tiantian Li 1.
Institute of Environmental Health, Tianjin Centers for Diseases Control and Prevention, Tianjin, China
Jingwei Zhang
Authors
- Jingwei Zhang
- Mengxue Zhang
- Qinghua Sun
- Runmei Ma
- Can Zhang
- Kailai Lu
- Qixuan Dong
- Tiantian Li
Contributions
T.L. designed the study, guided analysis, revised and reviewed the manuscript. J.Z. performed data cleaning, data analysis, and manuscript writing. M.Z. and Q.D. conducted data curation. Q.S., R.M., C.Z., and K.L. reviewed and edited the manuscript. All authors contributed to the manuscript. All authors have given approval to the final version of the manuscript.
Corresponding author
Correspondence to Tiantian Li.
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Competing interests
The authors declare no competing interests.
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Nature Communications thanks Ewout Steyerberg and Jun Yang for their contribution to the peer review of this work. A peer review file is available.
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Cite this article
Zhang, J., Zhang, M., Sun, Q. et al. Interventional applications of a Stroke Heat Risk Prediction Model produce health benefits. Nat Commun (2026). https://doi.org/10.1038/s41467-026-68815-4
Received: 24 January 2025
Accepted: 16 January 2026
Published: 27 January 2026
DOI: https://doi.org/10.1038/s41467-026-68815-4