Department of Vector Biology and Control, Rajendra Memorial Research Institute of Medical Sciences, Indian Council of Medical Research, Agamkuan, Bihar, India.
Mem Inst Oswaldo Cruz. 2013 Apr;108(2):197-204. doi: 10.1590/0074-0276108022013012.
Visceral leishmaniasis, or kala-azar, is recognised as a serious emerging public health problem in India. In this study, environmental parameters, such as land surface temperature (LST) and renormalised difference vegetation indices (RDVI), were used to delineate the association between environmental variables and Phlebotomus argentipes abundance in a representative endemic region of Bihar, India. The adult P. argentipes were collected between September 2009-February 2010 using the hand-held aspirator technique. The distribution of P. argentipes was analysed with the LST and RDVI of the peak and lean seasons. The association between environmental covariates and P. argentipes density was analysed a multivariate linear regression model. The sandfly density at its maximum in September, whereas the minimum density was recorded in January. The regression model indicated that the season, minimum LST, mean LST and mean RDVI were the best environmental covariates for the P. argentipes distribution. The final model indicated that nearly 74% of the variance of sandfly density could be explained by these environmental covariates. This approach might be useful for mapping and predicting the distribution of P. argentipes, which may help the health agencies that are involved in the kala-azar control programme focus on high-risk areas.
内脏利什曼病,又称黑热病,在印度已被确认为一个严重的新出现的公共卫生问题。本研究使用环境参数,如地表温度(LST)和归一化植被差异指数(RDVI),来描绘印度比哈尔邦一个典型流行地区环境变量与白蛉属(Phlebotomus argentipes)丰度之间的关联。于 2009 年 9 月至 2010 年 2 月,使用手持吸气器技术收集成年白蛉属(Phlebotomus argentipes)。分析了 LST 和高峰期和贫瘠期的 RDVI 与白蛉属(Phlebotomus argentipes)分布之间的关系。使用多元线性回归模型分析了环境协变量与白蛉属(Phlebotomus argentipes)密度之间的关系。白蛉属(Phlebotomus argentipes)密度在 9 月达到最大值,而在 1 月达到最小值。回归模型表明,季节、最低地表温度、平均地表温度和平均 RDVI 是白蛉属(Phlebotomus argentipes)分布的最佳环境协变量。最终模型表明,这些环境协变量可以解释白蛉属(Phlebotomus argentipes)密度变异的近 74%。这种方法可能有助于绘制和预测白蛉属(Phlebotomus argentipes)的分布,这可能有助于参与黑热病控制计划的卫生机构关注高风险地区。