Abstract
Extreme rainfall, intensified by climate change, elevates the risk of infectious diseases. The connection between extreme rainfall and common respiratory diseases remains unclear. Here we used a probabilistic approach to detect extreme rainfall events with different return periods for 30 cities across four East Asian countries and regions, including mainland China, Taiwan, South Korea and Japan, from 1980 to 2020. Significant associations were found between respiratory deaths and extreme rainfall events with 5 or 10 year return periods, but not for the events with a 1 or 2 year return period. The cumulative relative risks of respiratory mortality were found to be 1.29 (95% confidence interval: 1.09–1.51) and 1.33 (95% confidence interval: 1.02–1.65) for extreme rainfall events with 5 and 10 year return periods, respectively. The associations were strongest for asthma, followed by chronic obstructive pulmonary disease, but not significant for pneumonia. In cities across South Korea and Japan, no significant differences in the relative risks were detected before 2010. This multi-city study presents compelling evidence that extreme rainfall events could elevate mortality risks for respiratory diseases, especially for asthma and chronic obstructive pulmonary disease, emphasizing the multiple and complex consequences of extreme natural phenomena.
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Data availability
The time-series rainfall data for each city in this study were extracted from three databases: ERA5-Land, MSWEP and IMERG. These databases are publicly accessible and can be downloaded from their respective websites. Specifically, data from ERA5-Land are available at https://cds.climate.copernicus.eu, those from MSWEP at https://www.gloh2o.org/mswep/, and those from IMERG at https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGHHL_06/summary. In addition, the Dartmouth Flood Observatory database can be accessed at https://floodlist.com/. Due to restrictions imposed by the data owners, the daily mortality data for each city of this study cannot be publicly released. They are only available upon request from the corresponding author and other relevant authors. Source data are provided with this paper.
Code availability
The primary code used in this study, including the Python code for calculating the threshold values for extreme rainfall events across different return periods and the R code for estimating the impact of extreme rainfall events on respiratory mortality, can be found in GitHub (https://github.com/chenghe1130/Extreme-rainfall-East-Asia/tree/main).
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Acknowledgements
This study was supported by the National Natural Science Foundation of China (82030103), the National Key Research and Development Program of China (2022YFC3702701), the Shanghai International Science and Technology Partnership Project (21230780200), the Shanghai Committee of Science and Technology (21TQ015) and the Alexander von Humboldt Foundation for the Humboldt Research Fellowship.
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C.H., R.C. and H. Kan contributed to study conceptualization. C.H., R.C. and H. Kan contributed to the study methods. C.H., Y.Z. and L.Z. did the formal analysis. R.C., H. Kan, H. Kim, M.H., W.L., Y.H., S.E.K. and Y.L.G. contributed to data curation and collection of the mortality database. C.H., Y.Z. and L.Z. contributed to the making of all the figures and tables. C.H., R.C. and H. Kan contributed to the study draft preparation. C.H., R.C., H. Kan, H. Kim, M.H., W.L., Y.H., S.E.K., Y.L.G. and A.S. contributed to the study revision preparation. R.C. and H. Kan supervised all the data analysis and paper writing. All authors reviewed and edited the paper and approved its submission.
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He, C., Kim, H., Hashizume, M. et al. The overlooked health impacts of extreme rainfall exposure in 30 East Asian cities. Nat Sustain 7, 423–431 (2024). https://doi.org/10.1038/s41893-024-01294-x
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DOI: https://doi.org/10.1038/s41893-024-01294-x