Institut Pasteur of New Caledonia, Nouméa, New Caledonia.
HydroSciences Montpellier, University of Montpellier, CNRS, IRD, Nouméa, New Caledonia.
Sci Total Environ. 2024 Feb 10;911:168700. doi: 10.1016/j.scitotenv.2023.168700. Epub 2023 Nov 20.
Leptospirosis is a zoonosis caused by Leptospira bacteria present in the urine of mammals. Leptospira is able to survive in soils and can be resuspended during rain events. Here, we analyzed the pathogenic Leptospira concentration as a function of hydrological variables in a leptospirosis hot spot. A total of 226 samples were collected at the outlet of a 3 km watershed degraded by ungulate mammals (deer and feral pigs) and rats which are reservoirs for leptospirosis. Water samples collected at the beginning of a rain event following a dry period contained high concentrations of pathogenic Leptospira. The concentration was generally correlated with the water level and the suspended matter concentration (SMC) during the main flood event. A secondary peak of pathogenic Leptospira was sometimes detected after the main flood and in slightly turbid waters. Lastly, the pathogenic Leptospira concentration was extremely high at the end of a wet season. The pathogenic Leptospira concentrations could not be explained by a linear combination of hydrological variables (e.g. the rainfall, water level, SMC and soil moisture). However, nonlinear machine learning models of rainfall data only provided a fair fit to the observations and explained 75 % of the variance in the log-transformed pathogenic Leptospira concentration. A comparison of identical machine learning models for the water level, SMC and pathogenic Leptospira concentration showed that the residual error in the Leptospira concentration was due to not only the small dataset but also the intrinsic characteristics of the signal. Our results support the hypothesis whereby pathogenic Leptospira survive at different depths in soils and superficial river sediments (depending on their water saturation) and are transferred to surface water during erosion. These results might help to refine leptospirosis warnings given to the local population. Future research should be focused on larger watersheds in more densely populated areas.
钩端螺旋体病是一种由存在于哺乳动物尿液中的钩端螺旋体细菌引起的人畜共患病。钩端螺旋体能够在土壤中存活，并在降雨事件中被重新悬浮。在这里，我们分析了一个钩端螺旋体热点地区的水文变量与致病性钩端螺旋体浓度的关系。总共在一个被有蹄类哺乳动物（鹿和野猪）和作为钩端螺旋体宿主的老鼠退化的 3 公里流域的出口处收集了 226 个样本。在干旱期后降雨开始时收集的水样中含有高浓度的致病性钩端螺旋体。浓度通常与洪水期间的水位和悬浮物浓度（SMC）相关。在主洪峰之后，有时会检测到致病性钩端螺旋体的二次峰值，并且在稍浑浊的水中。最后，在雨季结束时，致病性钩端螺旋体的浓度非常高。致病性钩端螺旋体浓度不能用水文变量（例如降雨、水位、SMC 和土壤湿度）的线性组合来解释。然而，降雨数据的非线性机器学习模型仅对观测结果提供了较好的拟合，解释了对数转换后的致病性钩端螺旋体浓度的 75%的方差。对水位、SMC 和致病性钩端螺旋体浓度的相同机器学习模型的比较表明，钩端螺旋体浓度的残差不仅由于数据集较小，而且还由于信号的固有特性。我们的结果支持这样的假设，即致病性钩端螺旋体在土壤和浅层河沉积物中（取决于其水饱和度）的不同深度存活，并在侵蚀过程中转移到地表水。这些结果可能有助于为当地居民提供更精确的钩端螺旋体病预警。未来的研究应集中在人口更密集的更大流域。
