02716nas a2200433   4500000000100000008004100001653001600042653002100058653000900079653001700088653002400105653000900129653001500138653002500153653000900178653001800187653000900205653000900214653001100223653003500234653001200269653001600281653001400297653001100311653001300322653001600335100001500351700001100366700001700377700001500394700001600409700001600425700001700441245014800458300000900606490000800615520164500623022001402268       2016                            d10aTemperature10aSpatial analysis10aSoil10aRisk Factors10aRegression Analysis10aRain10aPrevalence10aPoisson Distribution10aNTDs10aLeishmaniasis10aIraq10aIran10aHumans10aGeographic Information Systems10aForests10aEnvironment10aCutaneous10aCities10aAltitude10aAgriculture1 aMokhtari M1 aMiri M1 aNikoonahad A1 aJalilian A1 aNaserifar R1 aGhaffari HR1 aKazembeigi F00aCutaneous leishmaniasis prevalence and morbidity based on environmental factors in Ilam, Iran: Spatial analysis and land use regression models.  a90-70 v1633 a<p>The aim of this study was to investigate the impact of the environmental factors on cutaneous leishmaniasis (CL) prevalence and morbidity in Ilam province, western Iran, as a known endemic area for this disease. Accurate locations of 3237 CL patients diagnosed from 2013 to 2015, their demographic information, and data of 17 potentially predictive environmental variables (PPEVs) were prepared to be used in Geographic Information System (GIS) and Land-Use Regression (LUR) analysis. The prevalence, risk, and predictive risk maps were provided using Inverse Distance Weighting (IDW) model in GIS software. Regression analysis was used to determine how environmental variables affect on CL prevalence. All maps and regression models were developed based on the annual and three-year average of the CL prevalence. The results showed that there was statistically significant relationship (P value≤0.05) between CL prevalence and 11 (64%) PPEVs which were elevation, population, rainfall, temperature, urban land use, poorland, dry farming, inceptisol and aridisol soils, and forest and irrigated lands. The highest probability of the CL prevalence was predicted in the west of the study area and frontier with Iraq. An inverse relationship was found between CL prevalence and environmental factors, including elevation, covering soil, rainfall, agricultural irrigation, and elevation while this relation was positive for temperature, urban land use, and population density. Environmental factors were found to be an important predictive variables for CL prevalence and should be considered in management strategies for CL control.</p>
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