Indian Ocean temperature anomalies predict long-term global dengue trends

• 成果类型: Article
• 署名作者: Chen, Yuyang; Xu, Yiting; Wang, Lin; Liang, Yilin; Li, Naizhe; Lourenco, Jose; Yang, Yun; Lin, Qiushi; Wang, Ligui; Zhao, He; Cazelles, Bernard; Song, Hongbin; Liu, Ziyan; Wang, Zengmiao; Brady, Oliver J.; Cauchemez, Simon; Tian, Huaiyu
• 署名单位: Beijing Normal University; China Three Gorges Corporation; Beijing Normal University; University of Cambridge; Universidade Catolica Portuguesa; China Meteorological Administration; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Biology (INSB); Universite PSL; Ecole Normale Superieure (ENS); Sorbonne Universite; University of London; London School of Hygiene & Tropical Medicine; University of London; London School of Hygiene & Tropical Medicine; Centre National de la Recherche Scientifique (CNRS); Pasteur Network; Universite Paris Cite; Institut Pasteur Paris
• 刊物名称: SCIENCE
• ISSN/ISSBN: 0036-11636
• DOI: 10.1126/science.adj4427
• 发表日期: 2024-05-10
• 页码: 639-646
• 关键词: sea-surface temperature; CLIMATE-CHANGE; pacific; transmission; infection; drivers; burden

摘要

Despite identifying El Ni & ntilde;o events as a factor in dengue dynamics, predicting the oscillation of global dengue epidemics remains challenging. Here, we investigate climate indicators and worldwide dengue incidence from 1990 to 2019 using climate-driven mechanistic models. We identify a distinct indicator, the Indian Ocean basin-wide (IOBW) index, as representing the regional average of sea surface temperature anomalies in the tropical Indian Ocean. IOBW is closely associated with dengue epidemics for both the Northern and Southern hemispheres. The ability of IOBW to predict dengue incidence likely arises as a result of its effect on local temperature anomalies through teleconnections. These findings indicate that the IOBW index can potentially enhance the lead time for dengue forecasts, leading to better-planned and more impactful outbreak responses.