利用遥感和环境因素对时空疟疾风险进行建模
Modeling Spatio-temporal Malaria Risk Using Remote Sensing and Environmental Factors.
作者信息
Mazher Muhammad Haris, Iqbal Javed, Mahboob Muhammad Ahsan, Atif Iqra
机构信息
Institute of Geographic Information Systems, School of Civil and Environmental Engineering, National University of Sciences and Technology, Islamabad, Pakistan.
出版信息
Iran J Public Health. 2018 Sep;47(9):1281-1291.
BACKGROUND
Remote sensing have been intensively used across many disciplines, however, such information was limited in spatial epidemiology.
METHODS
Two years (2009 & 2010) Landsat TM satellite data was used to develop vegetation, water bodies, air temperature and humidity criterion maps to model malaria risk and its spatiotemporal seasonal variation. The criterion maps were used in weighted overlay analysis to generate final categorized malaria risk map.
RESULTS
Overall, 25%, 68%, 18% and 16% of the total area of Rawalpindi region was categorized as danger zone for Jun 2009, Oct 2009, Jan 2010 and Jun 2010, respectively. The malaria risk reached at its peak during the monsoon season whereas air temperature and relative humidity were the main contributing factors in seasonal variation.
CONCLUSION
Malaria risk maps could be used for prioritizing areas for malaria control measures.
背景
遥感技术已在许多学科中得到广泛应用，然而，此类信息在空间流行病学中的应用有限。
方法
利用两年（2009年和2010年）的陆地卫星TM卫星数据绘制植被、水体、气温和湿度标准图，以模拟疟疾风险及其时空季节变化。这些标准图用于加权叠加分析，以生成最终的分类疟疾风险图。
结果
总体而言，拉瓦尔品第地区总面积的25%、68%、18%和16%分别在2009年6月、2009年10月、2010年1月和2010年6月被归类为危险区域。疟疾风险在季风季节达到峰值，而气温和相对湿度是季节变化的主要影响因素。
结论
疟疾风险图可用于确定疟疾控制措施的优先区域。
Zotero 插件