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  • 标题:Limiting global-mean temperature increase to 1.5–2 °C could reduce the incidence and spatial spread of dengue fever in Latin America
  • 本地全文:下载
  • 作者:Felipe J. Colón-González ; Ian Harris ; Timothy J. Osborn
  • 期刊名称:Proceedings of the National Academy of Sciences
  • 印刷版ISSN:0027-8424
  • 电子版ISSN:1091-6490
  • 出版年度:2018
  • 卷号:115
  • 期号:24
  • 页码:6243-6248
  • DOI:10.1073/pnas.1718945115
  • 语种:English
  • 出版社:The National Academy of Sciences of the United States of America
  • 摘要:The Paris Climate Agreement aims to hold global-mean temperature well below 2 °C and to pursue efforts to limit it to 1.5 °C above preindustrial levels. While it is recognized that there are benefits for human health in limiting global warming to 1.5 °C, the magnitude with which those societal benefits will be accrued remains unquantified. Crucial to public health preparedness and response is the understanding and quantification of such impacts at different levels of warming. Using dengue in Latin America as a study case, a climate-driven dengue generalized additive mixed model was developed to predict global warming impacts using five different global circulation models, all scaled to represent multiple global-mean temperature assumptions. We show that policies to limit global warming to 2 °C could reduce dengue cases by about 2.8 (0.8–7.4) million cases per year by the end of the century compared with a no-policy scenario that warms by 3.7 °C. Limiting warming further to 1.5 °C produces an additional drop in cases of about 0.5 (0.2–1.1) million per year. Furthermore, we found that by limiting global warming we can limit the expansion of the disease toward areas where incidence is currently low. We anticipate our study to be a starting point for more comprehensive studies incorporating socioeconomic scenarios and how they may further impact dengue incidence. Our results demonstrate that although future climate change may amplify dengue transmission in the region, impacts may be avoided by constraining the level of warming.
  • 关键词:climate change impacts ; disease modeling ; Latin America
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