Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
PLoS One. 2012;7(2):e32202. doi: 10.1371/journal.pone.0032202. Epub 2012 Feb 16.
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.
建模人类寄生虫物种的空间分布对于理解感染的环境决定因素以及指导控制规划至关重要。在这里，我们使用生态位模型来绘制非洲淋巴丝虫病（LF）的当前潜在分布，并估计未来气候和人口变化将如何影响其在非洲大陆的传播和负担。我们使用了从已发表文献中收集的 508 个特定社区的感染存在数据，结合五个预测性环境/气候和人口变量，以及最大熵生态位模型方法，构建了第一个描述非洲 LF 潜在分布和负担的生态位地图。我们还根据 HADCM3 和 CCCMA 模型为 2050 年 A2a 和 B2a 情景制作的气候预测，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 LF 在非洲的地理分布范围很广，从西部延伸到东部，穿过大陆中部地区，西非的发生概率较高，而中非和东非以及马达加斯加的大面积地区则为中等概率，小面积地区为高概率。我们发现了预测生态位变量与 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流行地区 LF 感染（最终是疾病）的范围和风险。我们估计，目前处于 LF 风险中的人口可能在 5.43 亿至 8.04 亿之间，根据所使用的气候情景和表示感染存在的阈值，这一数字可能会上升到 16.5 亿至 18.6 亿。
