伊朗一个流行地区皮肤利什曼病发病率的环境风险因素：基于地理信息系统的方法。
Environmental risk factors for the incidence of cutaneous leishmaniasis in an endemic area of Iran: A GIS-based approach.
作者信息
Ramezankhani Roghieh, Hosseini Arezoo, Sajjadi Nooshin, Khoshabi Mostafa, Ramezankhani Azra
机构信息
Center of Disease Control and Prevention, Ministry of Health of Iran, Tehran, Iran; Department of Environment, Islamic Azad University, North Tehran Branch, Tehran, Iran.
Department of Geodesy and Geomatics Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.
出版信息
Spat Spatiotemporal Epidemiol. 2017 Jun;21:57-66. doi: 10.1016/j.sste.2017.03.003. Epub 2017 Mar 23.
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 R, 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.
目的
本研究旨在通过空间分析确定与伊斯法罕省皮肤利什曼病（CL）相关的环境因素。
方法
利用2010年至2013年CL月发病率数据、气候和环境因素，包括温度、湿度、降雨量、风速、归一化植被指数（NDVI）、海拔高度以及伊斯法罕各城市的人口密度，通过普通最小二乘法（OLS）回归和地理加权回归（GWR）进行空间分析。
结果
OLS显示CL发病率与五个预测因子之间存在显著相关性，这五个预测因子包括温度、人口密度、风速、湿度和NDVI；它们解释了该省CL发病率变化的28.6%。考虑到AICc和调整后的R，与OLS相比，GWR对数据的拟合效果更好。
结论
在地方（城市）和全球（省份）层面，温度和人口密度与CL发病率之间均存在正相关。
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