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Application of decision tree for prediction of cutaneous leishmaniasis incidence based on environmental and topographic factors in Isfahan Province, Iran

机译:基于环境和地形因素的决策树在皮肤利什曼病发病率预测中的应用,伊朗伊斯法罕省

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Cutaneous Leishmaniasis (CL) is a neglected tropical disease that continues to be a health problem in Iran. Nearly 350 million people are thought to be at risk. We investigated the impact of the environmental factors on CL incidence during the period 2007- 2015 in a known endemic area for this disease in Isfahan Province, Iran. After collecting data with regard to the climatic, topographic, vegetation coverage and CL cases in the study area, a decision tree model was built using the classification and regression tree algorithm. CL data for the years 2007 until 2012 were used for model construction and the data for the years 2013 until 2015 were used for testing the model. The Root Mean Square error and the correlation factor were used to evaluate the predictive performance of the decision tree model. We found that wind speeds less than 14 m/s, altitudes between 1234 and 1810 m above the mean sea level, vegetation coverage according to the normalized difference vegetation index (NDVI) less than 0.12, rainfall less than 1.6 mm and air temperatures higher than 30°C would correspond to a seasonal incidence of 163.28 per 100,000 persons, while if wind speed is less than 14 m/s, altitude less than 1,810 m and NDVI higher than 0.12, then the mean seasonal incidence of the disease would be 2.27 per 100,000 persons. Environmental factors were found to be important predictive variables for CL incidence and should be considered in surveillance and prevention programmes for CL control.
机译:皮肤利什曼病(CL)是一种被忽视的热带病,仍然是伊朗的健康问题。人们认为有近3.5亿人处于危险之中。我们在伊朗伊斯法罕省的已知流行地区调查了2007-2015年环境因素对CL发病率的影响。在收集了研究区域的气候,地形,植被覆盖率和CL案例的数据之后,使用分类和回归树算法构建了决策树模型。 2007年至2012年的CL数据用于模型构建,2013年至2015年的数据用于模型测试。均方根误差和相关因子用于评估决策树模型的预测性能。我们发现风速小于14 m / s,海拔在平均海平面以上1234至1810 m之间,根据归一化植被指数(NDVI)进行的植被覆盖度小于0.12,降雨量小于1.6 mm,并且气温高于30°C相当于每100,000人163.28的季节性发病率,而如果风速小于14 m / s,高度小于1,810 m且NDVI大于0.12,则该疾病的平均季节性发病率将为2.27 100,000人。发现环境因素是CL发生率的重要预测变量,应在CL控制的监视和预防计划中考虑环境因素。

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