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  • 标题:El Niño and the shifting geography of cholera in Africa
  • 本地全文:下载
  • 作者:Sean M. Moore ; Andrew S. Azman ; Benjamin F. Zaitchik
  • 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:2017
  • 卷号:114
  • 期号:17
  • 页码:4436-4441
  • DOI:10.1073/pnas.1617218114
  • 语种:English
  • 出版社:The National Academy of Sciences of the United States of America
  • 摘要:The El Niño Southern Oscillation (ENSO) and other climate patterns can have profound impacts on the occurrence of infectious diseases ranging from dengue to cholera. In Africa, El Niño conditions are associated with increased rainfall in East Africa and decreased rainfall in southern Africa, West Africa, and parts of the Sahel. Because of the key role of water supplies in cholera transmission, a relationship between El Niño events and cholera incidence is highly plausible, and previous research has shown a link between ENSO patterns and cholera in Bangladesh. However, there is little systematic evidence for this link in Africa. Using high-resolution mapping techniques, we find that the annual geographic distribution of cholera in Africa from 2000 to 2014 changes dramatically, with the burden shifting to continental East Africa—and away from Madagascar and portions of southern, Central, and West Africa—where almost 50,000 additional cases occur during El Niño years. Cholera incidence during El Niño years was higher in regions of East Africa with increased rainfall, but incidence was also higher in some areas with decreased rainfall, suggesting a complex relationship between rainfall and cholera incidence. Here, we show clear evidence for a shift in the distribution of cholera incidence throughout Africa in El Niño years, likely mediated by El Niño’s impact on local climatic factors. Knowledge of this relationship between cholera and climate patterns coupled with ENSO forecasting could be used to notify countries in Africa when they are likely to see a major shift in their cholera risk.
  • 关键词:cholera ; El Niño Southern Oscillation ; disease mapping ; climate and health ; Bayesian mapping
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