Roghieh Ramezankhani1, Arezoo Hosseini2, Nooshin Sajjadi3, Mostafa Khoshabi4, Azra Ramezankhani5. 1. Center of Disease Control and Prevention, Ministry of Health of Iran, Tehran, Iran; Department of Environment, Islamic Azad University, North Tehran Branch, Tehran, Iran. 2. Department of Geodesy and Geomatics Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran. 3. Department of Environment, Islamic Azad University, North Tehran Branch, Tehran, Iran. 4. Department of Geo-Spatial Information System (GIS), Center of Excellence in GIS, K.N. Toosi University of Technology, Tehran, Iran. 5. Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Science, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Electronic address: ma.ramezankhani@gmail.com.
Abstract
OBJECTIVES: This study was designed to determine the environmental factors associated with cutaneous leishmaniasis (CL) in Isfahan Province, using spatial analysis. METHODS: Data of monthly CL incidence from 2010 to 2013, climate and environmental factors including: temperature, humidity, rainfall, wind speed, normalized difference vegetation index (NDVI), altitude and population density across the Isfahan's cities was used to perform spatial analysis by ordinary least square (OLS) regression and geographically weighted regression (GWR). RESULTS: OLS revealed a significant correlation between CL incidence and five predictors including temperature, population density, wind speed, humidity and NDVI; which explained 28.6% of variation in CL incidence in the province. Considering AICc and adjusted R2, GWR provided a better fit to the data compared with OLS. CONCLUSION: There was a positive correlation between temperature and population density with CL incidence in both local (city) and global (province) level.
OBJECTIVES: This study was designed to determine the environmental factors associated with cutaneous leishmaniasis (CL) in Isfahan Province, using spatial analysis. METHODS: Data of monthly CL incidence from 2010 to 2013, climate and environmental factors including: temperature, humidity, rainfall, wind speed, normalized difference vegetation index (NDVI), altitude and population density across the Isfahan's cities was used to perform spatial analysis by ordinary least square (OLS) regression and geographically weighted regression (GWR). RESULTS: OLS revealed a significant correlation between CL incidence and five predictors including temperature, population density, wind speed, humidity and NDVI; which explained 28.6% of variation in CL incidence in the province. Considering AICc and adjusted R2, GWR provided a better fit to the data compared with OLS. CONCLUSION: There was a positive correlation between temperature and population density with CL incidence in both local (city) and global (province) level.