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

Submitted: 19 December 2017
Accepted: 30 March 2018
Published: 8 May 2018
Abstract Views: 1505
PDF: 704
HTML: 154
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

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.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

Citations

How to Cite

Ramezankhani, R., Sajjadi, N., Nezakati Esmaeilzadeh, R., Jozi, S. A., & Shirzadi, M. R. (2018). Application of decision tree for prediction of cutaneous leishmaniasis incidence based on environmental and topographic factors in Isfahan Province, Iran. Geospatial Health, 13(1). https://doi.org/10.4081/gh.2018.664