一个集成的机器学习框架,以了解在人类修改的景观中出现动物性传染病的溢出
Yinsheng Zhang1,2, Jinchen Wang1, Luqi Wang1
1School of Environmental Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, P.R. China.
Environmental health perspectives
|May 21, 2025
概括
人类对土地的修改,特别是在中间层面,增加了动物传染病溢出风险. 牲畜分布和作物强度是全球这些高风险地区的关键指标.
科学领域:
- 环境健康 环境健康
- 流行病学 流行病学
- 生态生态学 生态生态学
背景情况:
- 人为土地改造对人类-牲畜-野生动物的相互作用和动物传染病的出现产生重大影响.
- 要了解这种影响的全部程度,需要先进的分析工具和有关动物传染病溢出事件的全面数据.
研究的目的:
- 开发和评估一个集成的建模框架,用于预测和解释动物传染病溢出模式.
- 利用最新的数据集和人类修饰指数来分析人类对动物传染病出现的压力.
主要方法:
- 扩展了历史数据集,包括最近的动物病溢出事件和广泛的预测因素.
- 采用堆叠算法和结构方程建模,对报告充足性的全球变化进行核算.
- 利用人类修饰指数,将土地修饰梯度与三十年来动物性传染病溢出发生联系起来.
主要成果:
- 综合模型展示了增强的预测和解释能力.
- 人类压力的中间水平被发现有助于动物传染病的溢出.
- 人类压力的间接影响,以作物强度为媒介,与动物病的出现有很强的相关性;牲畜分布表明溢出热点.
结论:
- 在全球范围内发现了高度的动物传染性溢出风险,不仅限于热带地区,特别是在人类显著修饰的地区.
- 这些发现支持在高风险或不确定的地区进行有针对性的监测.
- 动物传播的溢出被证明是对人类与环境相互作用的复杂反应.
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