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使用最大模型对人类白病发病率的时空建模

Reza Shirzad¹, Ali Asghar Alesheikh², Mojtaba Asgharzadeh¹

¹Department of Geospatial Information System, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran.

BMC public health

|December 16, 2023

概括

在伊朗,特别是吉兰省,发现了白螺杆菌菌群. 高度和降水是影响疾病患病率的关键因素,指导有针对性的公共卫生干预.

科学领域:

环境流行病学环境流行病学
空间分析是一种空间分析.
疾病建模疾病建模

背景情况:

莱普陀螺杆菌病是伊朗热带地区的一个重要的动物传染病,发病率为每10,000人中有2.33人.
了解时空模式对于公共卫生政策和有针对性的干预至关重要.

研究的目的:

为了分析伊朗莱普托螺旋病的时空聚类.
利用环境因素开发一种疾病流行模型.

主要方法:

雇员 SaTScan 和最大 (MaxEnt) 建模.
使用了高分辨率 (1公里x1公里) 的环境共变量,包括DEM,斜率,水体,土地覆盖,NDVI,降水量和温度.
使用接收器操作特征曲线 (AUC) 下面的面积来评估模型准确性.

主要成果:

在吉兰省西部确定了一个重要的初级集群 (2013年7月至2015年7月).
在Someh Sara,Neka,Gorgan和Rudbar附近发现了四个额外的集群.
风险测绘表明疾病可能扩散到西部/西北部地区. AUC值为0.956 (训练) 和0.952 (测试) 的情况.
高度和降水是主要决定因素;坡度和距离水体的距离的影响最小.

结论:

生成的风险地图可以提高公众意识,并为有效的白病控制政策提供信息.
地图有助于追踪疾病发病率,并将干预措施指向高风险地区.

关键词:

莱普托斯皮罗斯病的发生率马克斯恩特马克斯恩特在 SaTScan 中进行扫描.时间空间建模.

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