雨量驱动的病原性LeptoSpira在一个LeptoSpirosis热点中的再悬浮
R Thibeaux1, P Genthon2, R Govan3
1Institut Pasteur of New Caledonia, Nouméa, New Caledonia.
The Science of the total environment
|November 22, 2023
概括
在水中的致病性白菌度与降雨和土壤状况有关. 机器学习模型显示,这些细菌可以在降雨事件中重新悬浮,有助于螺旋体风险评估.
科学领域:
- 环境微生物学 环境微生物学
- 水文学的水文学
- 动物传播疾病 动物传播疾病
背景情况:
- 莱普托斯皮罗斯是一种由Leptospira细菌引起的动物性疾病,通常在哺乳动物的尿液中发现.
- 莱普托斯皮拉可以在土壤中持续存在,并在降雨事件期间重新引入水系统.
- 了解水文变量与莱普托斯皮拉度之间的关系对于公共卫生至关重要.
研究的目的:
- 在已知的白病热点中,分析致病性白菌度与水文变量相关.
- 为了研究降雨,水位,悬浮物质度和土壤水分对Leptospira水平的影响.
- 评估机器学习模型在预测LeptoSpira度方面的有效性.
主要方法:
- 从一个占地3公里的流域收集了226个水样,该流域由Leptospira的哺乳动物水库居住.
- 分析了病原性LeptoSpira度与水文数据相比,包括降雨量,水位和悬浮物质度 (SMC).
- 应用非线性机器学习模型,利用降雨数据预测Leptospira度.
主要成果:
- 在干旱时期后降雨事件开始时观察到高致病性Leptospira度.
- 莱普托斯皮拉度与水位和大洪水期间的SMC相关,在水中出现二次峰值.
- 使用降雨数据的非线性机器学习模型解释了log10转换的LeptoSpira度中75%的差异.
结论:
- 在土壤和沉积物中致病性LeptoSpira的生存,以及随后通过侵蚀的转移,解释了观察到的度.
- 水文变量,特别是降雨模式,是表面水中LeptoSpira污染的关键驱动因素.
- 这些发现可以改善对受影响地区人口的白螺旋体风险警告.
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