Tehran University of Medical Sciences Journal of Arthropod-Borne Diseases 2322-1984 13 3 2019 08 03 310 323 Elham Jahanifard Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran AND Department of Medical Entomology and Vector Control, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran Ahmad Ali Hanafi-Bojd Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran Hossein Nasiri Faculty of Geography, University of Tehran, Tehran, Iran Hamid Reza Matinfar Department of Soil Science, Collage of Agriculture, Lorestan University, Khoramabad, Iran Zabihollah Charrahy Open Training Center, School of Geography, Tehran University, Tehran, Iran Mohammad Reza Abai Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran Mohammad Reza Yaghoobi-Ershadi Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran Amir Ahmad Akhavan Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran 2019 09 30 Background: Cutaneous leishmaniasis due to Leishmania major is an important public health problem in the world. Khuzestan Province is one of the main foci of zoonotic cutaneous leishmaniasis (ZCL) in the southwest of Iran. We aimed to predict the spatial distribution of the vector and reservoir(s) of ZCL using decision-making tool and to pre­pare risk map of the disease using integrative GIS, RS and AHP methods in endemic foci in Shush (plain area) and Khorramshahr (coastal area) counties of Khuzestan Province, southern Iran from Mar 2012 to Jan 2013. Methods: Thirteen criteria including temperature, relative humidity, rainfall, soil texture, soil organic matter, soil pH, soil moisture, altitude, land cover, land use, underground water depth, distance from river, slope and distance from human dwelling with the highest chance of the presence of the main vector and reservoir of the disease were chosen for this study. Weights of the criteria classes were determined using the Expert choice 11 software. The pres­ence proba­bility maps of the vector and reservoir of the disease were prepared with the combination of AHP method and Arc GIS 9.3. Results: Based on the maps derived from the AHP model, in Khorramshahr study area, the highest probability of ZCL is predicted in Gharb Karoon rural district. The presence probability of ZCL was high in Hossein Abad and Benmoala rural districts in the northeast of Shush. Conclusion: Prediction maps of ZCL distribution pattern provide valuable information which can guide policy mak­ers and health authorities to be precise in making appropriate decisions before occurrence of a possible disease out­break. https://jad.tums.ac.ir/index.php/jad/article/view/1181 https://jad.tums.ac.ir/index.php/jad/article/download/1181/466