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皮肤莱什曼病在伊朗一个超流行大都市地区:通过机器学习进行空间概率建模

Alireza Mohammadi¹, Elahe Pishgar², Robert Bergquist³

¹Department of Geography and Urban Planning, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran.

Journal of medical entomology

|June 27, 2025

概括

伊朗马什哈德的皮肤莱什曼病 (CL) 风险受到社会人口结构,城市发展和地质的影响. 高风险地区需要针对这种寄生虫感染进行有针对性的干预.

科学领域:

流行病学流行病学
环境健康环境健康
医学地理医学地理

背景情况:

皮肤莱什曼病 (CL) 是一种广泛的寄生虫感染.
伊朗的马什哈德是人类感染性和动物感染性CL的高度流行地区.
了解CL的空间分布对于控制至关重要.

研究的目的:

为了评估在马什哈德的CL患病率的空间分布概率.
确定影响CL分布的关键社会人口统计,建筑环境,地质和气候因素.
为 CL. CL 提供有针对性的控制策略.

主要方法:

分析了2013年至2020年期间诊断的3033例CL患者病例.
应用通用线性回归 (GLM) 和最大 (MaxEnt) 模型.
评估社会学,环境和气候变量.

主要成果:

社会人口统计学,建筑环境和地质学显著影响了CL分布.
马克森特模型将42.6%的研究区域确定为CL的高风险地区.
高风险地区与特定的地质,城市化和环境质量有关.

结论:

结核病的患病率与年轻人,低识字率和人口密集地区有关.
风险区域受温度 (20-40°C),湿度,建筑环境和特定岩石类型的影响.
研究结果支持城市规划人员和卫生管理人员针对性干预,以控制CL.

关键词:

皮肤上的莱什曼病.地理信息系统 (GIS) 是一个地理信息系统.最大的最大.进行风险映射.空间分布建模 (SDM) 的应用.

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