@article{Ramezankhani_Sajjadi_Nezakati Esmaeilzadeh_Jozi_Shirzadi_2017, title={Spatial analysis of cutaneous leishmaniasis in an endemic area of Iran based on environmental factors}, volume={12}, url={https://www.geospatialhealth.net/gh/article/view/578}, DOI={10.4081/gh.2017.578}, abstractNote={Leishmaniasis is a parasitic disease caused by different species of protozoan parasites. Cutaneous leishmaniasis (CL) is still a great public health problem in Iran, especially in Isfahan Province. Distribution and abundance of vectors and reservoirs of this disease is affected by different factors such as climatic, socioeconomic and cultural. This study aimed to identify the hotspot areas for CL in Isfahan and assess the relations between the climatic and topographic factors with CL incidence using spatial analysis. We collected data on the total number of CL cases, population at risk, vegetation coverage, altitude and climatic data for each district of the province from 2011 to 2015. Global Moran’s Index was used to map clustering of CL cases across districts and the Getis-Ord (Gi*) statistics was used to determine hotspots areas of the disease in Isfahan. We applied overlay analysis to assess the correlation between the climatic and topographic factors with CL incidence. We found the CL distribution significantly clustered (Moran’s Index=0.17, P<0.001) with the Ardestan and Aran va Bidgol (P<0.01) districts along with the Naein and Natanz districts (P<0.05) to be strong hotspot areas. Overlay analysis revealed a high incidence of CL in areas with relative humidity of 27-30%, mean temperature of 15-19°C, mean precipitation of 5-20 mm, maximum wind speed about 12-16 m/s and an altitude of 600-1,800 m. Our study showed that spatial analysis is a feasible approach for identifying spatial disease pattern and detecting hotspots of this infectious disease.}, number={2}, journal={Geospatial Health}, author={Ramezankhani, Roghieh and Sajjadi, Nooshin and Nezakati Esmaeilzadeh, Roya and Jozi, Seyed Ali and Shirzadi, Mohammad Reza}, year={2017}, month={Nov.} }