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Predicting the Current and Future Potential Distributions of Lymphatic Filariasis in Africa Using Maximum Entropy Ecological Niche Modelling

机译:利用最大熵生态位模型预测非洲淋巴丝虫病的当前和未来潜力分布

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摘要

Modelling the spatial distributions of human parasite species is crucial to understanding the environmental determinants of infection as well as for guiding the planning of control programmes. Here, we use ecological niche modelling to map the current potential distribution of the macroparasitic disease, lymphatic filariasis (LF), in Africa, and to estimate how future changes in climate and population could affect its spread and burden across the continent. We used 508 community-specific infection presence data collated from the published literature in conjunction with five predictive environmental/climatic and demographic variables, and a maximum entropy niche modelling method to construct the first ecological niche maps describing potential distribution and burden of LF in Africa. We also ran the best-fit model against climate projections made by the HADCM3 and CCCMA models for 2050 under A2a and B2a scenarios to simulate the likely distribution of LF under future climate and population changes. We predict a broad geographic distribution of LF in Africa extending from the west to the east across the middle region of the continent, with high probabilities of occurrence in the Western Africa compared to large areas of medium probability interspersed with smaller areas of high probability in Central and Eastern Africa and in Madagascar. We uncovered complex relationships between predictor ecological niche variables and the probability of LF occurrence. We show for the first time that predicted climate change and population growth will expand both the range and risk of LF infection (and ultimately disease) in an endemic region. We estimate that populations at risk to LF may range from 543 and 804 million currently, and that this could rise to between 1.65 to 1.86 billion in the future depending on the climate scenario used and thresholds applied to signify infection presence.
机译:对人类寄生虫物种的空间分布进行建模对于理解感染的环境决定因素以及指导控制计划的规划至关重要。在这里,我们使用生态位模型来绘制非洲大寄生虫病,淋巴丝虫病(LF)的当前潜在分布图,并估算未来气候和人口变化如何影响其在整个非洲大陆的分布和负担。我们使用从公开文献中收集的508个特定于社区的感染状况数据,结合五个预测性环境/气候和人口统计学变量,以及最大熵生态位建模方法,来构建描述非洲LF的潜在分布和负担的首个生态位图。我们还针对由HADCM3和CCCMA模型在A2a和B2a情景下对2050年做出的气候预测运行了最佳拟合模型,以模拟未来气候和人口变化下LF的可能分布。我们预测非洲的LF分布范围广泛,从非洲的西部到东部,横跨非洲大陆的中部地区,与在中等概率的大区域散布在中部的小概率区域相比,西部非洲的发生概率较高和东非以及马达加斯加。我们发现了预测因子生态位变量与LF发生概率之间的复杂关系。我们首次表明,预测的气候变化和人口增长将扩大地方病地区的LF感染(最终导致疾病)的范围和风险。我们估计,目前受到LF威胁的人群可能在543至8.04亿之间,并且根据所使用的气候情景和所采用的表示感染存在的阈值,未来可能会增加到1.65到18.6亿之间。

著录项

  • 作者

    Slater, Hannah; Michael, Edwin;

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  • 年度 2012
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  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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