Cutaneous leishmaniasis (CL) is one of the most significant vector-borne diseases in Iran, whose spatial distribution is strongly influenced by climatic, environmental, and anthropogenic factors. Isfahan Province, as one of the active foci of this disease, requires identification of high-risk areas to optimize prevention and control programs. This study aimed to model, predict, and map the spatial sensitivity of CL occurrence at the county level in Isfahan Province during 2021–2023 using machine learning algorithms. The dependent variable in this study was confirmed cases of CL. Independent variables included climatic factors (minimum, maximum, and mean temperature, precipitation, relative humidity, wind speed, sunshine hours, and soil moisture), vegetation indices (NDVI and EVI), topographic variables (elevation, slope, and slope aspect), distance to watercourses, land use, and population density. Data were pre-processed and integrated in ArcGIS 10.8.2 and subsequently modeled using LightGBM and CART algorithms in RStudio. Seventy percent of the data were used for training and 30% for testing. Model performance was evaluated using ROC curves and the AUC index. The CART model achieved over 96% accuracy with a Kappa coefficient of 0.93, outperforming Light GBM in distinguishing infected from non-infected areas. Sensitivity mapping revealed that 93.6% of the province falls within the very low-risk class, while only about 3.4% is classified as high and very high risk, mainly concentrated in the central and northwestern counties,.
Abbasi, F. , Zakerinejad, R. and Seif, A. (2026). Modeling and Predicting the Spatial Distribution of Cutaneous Leishmaniasis in Isfahan Province Using Machine Learning Algorithms. Spatial Planning, (), -. doi: 10.22108/sppl.2026.148536.1880
MLA
Abbasi, F. , , Zakerinejad, R. , and Seif, A. . "Modeling and Predicting the Spatial Distribution of Cutaneous Leishmaniasis in Isfahan Province Using Machine Learning Algorithms", Spatial Planning, , , 2026, -. doi: 10.22108/sppl.2026.148536.1880
HARVARD
Abbasi, F., Zakerinejad, R., Seif, A. (2026). 'Modeling and Predicting the Spatial Distribution of Cutaneous Leishmaniasis in Isfahan Province Using Machine Learning Algorithms', Spatial Planning, (), pp. -. doi: 10.22108/sppl.2026.148536.1880
CHICAGO
F. Abbasi , R. Zakerinejad and A. Seif, "Modeling and Predicting the Spatial Distribution of Cutaneous Leishmaniasis in Isfahan Province Using Machine Learning Algorithms," Spatial Planning, (2026): -, doi: 10.22108/sppl.2026.148536.1880
VANCOUVER
Abbasi, F., Zakerinejad, R., Seif, A. Modeling and Predicting the Spatial Distribution of Cutaneous Leishmaniasis in Isfahan Province Using Machine Learning Algorithms. Spatial Planning, 2026; (): -. doi: 10.22108/sppl.2026.148536.1880
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