Vector-borne diseases are among the leading causes of morbidity and mortality in humans and animals. In the Afrotropical region, some are transmitted by Culicoides, such as Akabane, bluetongue, epizootic haemorrhagic fever and African horse sickness viruses. Bluetongue virus infection has an enormous impact on ruminant production, due to its high morbidity and mortality rates. A nationwide Culicoides trapping campaign was organized at the end of the 2012 rainy season in Senegal. A Maximum Entropy approach (MaxEnt), Boosted Regression Tree (BRT) method and Ecological Niche Factor Analysis (ENFA) were used to develop a predictive spatial model for the distribution of Culicoides, using bio-climatic variables, livestock densities and altitude. The altitude, maximum temperature of the warmest month, precipitation of the warmest quarter, mean temperature of the wettest quarter, temperature seasonality, precipitation of the wettest quarter and livestock density were among the most important factors to predict suitable habitats of Culicoides. Culicoides occurrences were, in most of the cases, positively correlated to precipitation variables and livestock densities; and negatively correlated to the altitude and temperature indices. The Niayes area and the Groundnut basin were the most suitable habitats predicted. We present ecological niche models for different Culicoides species, namely C. imicola, C. oxystoma, C. enderleini and C. miombo, potential vectors of bluetongue virus, on a nationwide scale in Senegal. Through our modelling approach, we were able to determine the effect of bioclimatic variables on Culicoides habitats and were able to generate maps for the occurrence of Culicoides species. This information will be helpful in developing risk maps for disease outbreaks.

中文翻译：

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生态位模型估计塞内加尔蓝舌病病毒潜在载体库蠓的分布

媒介传播疾病是人类和动物发病和死亡的主要原因之一。在非洲热带地区，有些是由库蠓病毒传播的，例如赤羽病毒、蓝舌病病毒、流行性出血热病毒和非洲马瘟病毒。蓝舌病毒感染因其高发病率和死亡率而对反刍动物生产产生巨大影响。2012 年雨季结束时，塞内加尔组织了一场全国性的库蠓昆虫诱捕活动。使用最大熵方法 (MaxEnt)、增强回归树 (BRT) 方法和生态位因子分析 (ENFA)，利用生物气候变量、牲畜密度和海拔高度，开发库蠓分布的预测空间模型。海拔高度、最暖月最高气温、最暖季降水量、最湿季平均气温、温度季节、最湿季降水量和牲畜密度是预测库蠓适宜栖息地的重要因素。在大多数情况下，库蠓的出现与降水变量和牲畜密度呈正相关；与海拔和温度指数呈负相关。尼亚耶斯地区和花生盆地是预测的最合适的栖息地。我们提出了塞内加尔全国范围内不同库蠓属物种的生态位模型，即 C. imicola、C. oxystoma、C. enderleini 和 C. miombo（蓝舌病病毒的潜在载体）。通过我们的建模方法，我们能够确定生物气候变量对库蠓栖息地的影响，并能够生成库蠓物种出现的地图。这些信息将有助于制定疾病爆发的风险图。