Wenxi Ruan, Yinglin Liang, Zhaobin Sun, Xingqin An
{"title":"Climate warming and influenza dynamics: the modulating effects of seasonal temperature increases on epidemic patterns","authors":"Wenxi Ruan, Yinglin Liang, Zhaobin Sun, Xingqin An","doi":"10.1038/s41612-025-00968-3","DOIUrl":null,"url":null,"abstract":"<p>The underexplored impact of climate change on influenza outbreak severity and duration hampers our understanding of how climate-driven changes affect transmission dynamics. Our study employs the SIRS (Susceptible-Infectious-Recovered-Susceptible) model to simulate incremental temperature rises (2.5 °C, 5 °C, 7.5 °C, and 10 °C) in winter and summer. Results show warming significantly influences infections across seasonal, interannual, and decadal scales. Higher temperatures significantly impact infection rates, especially in autumn and winter, with long-lasting effects extending 5-6 years. Sustained warming lowers the total infection numbers compared to pre-warming levels. When winter and summer experience simultaneous warming, infection fluctuations during the warming period are mainly driven by winter warming. Winter warming also lowers the peak-to-trough infection ratio, reducing epidemic intensity fluctuations. Additionally, parameter choices can significantly affect the impact of warming on infection rates. Warming of varying intensity and duration can significantly impact influenza outbreaks, potentially altering their seasonal patterns in a global warming context.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"141 1","pages":""},"PeriodicalIF":8.5000,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Climate and Atmospheric Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1038/s41612-025-00968-3","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The underexplored impact of climate change on influenza outbreak severity and duration hampers our understanding of how climate-driven changes affect transmission dynamics. Our study employs the SIRS (Susceptible-Infectious-Recovered-Susceptible) model to simulate incremental temperature rises (2.5 °C, 5 °C, 7.5 °C, and 10 °C) in winter and summer. Results show warming significantly influences infections across seasonal, interannual, and decadal scales. Higher temperatures significantly impact infection rates, especially in autumn and winter, with long-lasting effects extending 5-6 years. Sustained warming lowers the total infection numbers compared to pre-warming levels. When winter and summer experience simultaneous warming, infection fluctuations during the warming period are mainly driven by winter warming. Winter warming also lowers the peak-to-trough infection ratio, reducing epidemic intensity fluctuations. Additionally, parameter choices can significantly affect the impact of warming on infection rates. Warming of varying intensity and duration can significantly impact influenza outbreaks, potentially altering their seasonal patterns in a global warming context.
期刊介绍:
npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols.
The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.