Palharini Rayana Santos Araujo, Reyes Makarena Sofia Gonzalez, Monteiro Felipe Ferreira, Villavicencio Lourdes Milagros Mendoza, Adell Aiko D, Toro Magaly, Moreno-Switt Andrea I, Undurraga Eduardo A
Departamento de Prevención de Riesgos y Medio Ambiente, Universidad Tecnológica Metropolitana, Santiago 8330383, Chile.
Center for Bioinformatics and Integrative Biology, Facultad de Ciencias de la Vida, Universidad Andrés Bello, Santiago 8370186, Chile.
Microorganisms. 2025 Jun 30;13(7):1539. doi: 10.3390/microorganisms13071539.
Waterborne illnesses, including those caused by , are an increasing public health challenge, particularly in developing countries. Potential sources of salmonellosis include fruits and vegetables irrigated/treated with surface water, leading to human infections. causes millions of gastroenteritis cases annually, but early detection through routine water quality surveillance is time-consuming, requires specialized equipment, and faces limitations, such as coverage gaps, delayed data, and poor accessibility. Climate change-driven extreme events such as floods and droughts further exacerbate variability in water quality. In this context, remote sensing offers an efficient and cost-effective alternative for environmental monitoring. This study evaluated the potential of Sentinel-2 satellite imagery to predict occurrence in the Maipo and Mapocho river basins (Chile) by integrating spectral, microbiological, climatic, and land use variables. A total of 1851 water samples collected between 2019 and 2023, including 704 positive samples for , were used to develop a predictive model. Predicting in surface waters using remote sensing is challenging for several reasons. Satellite sensors capture environmental proxies (e.g., vegetation cover, surface moisture, and turbidity) but not pathogens. Our goal was to identify proxies that reliably correlate with . Twelve spectral indices (e.g., NDVI, NDWI, and MNDWI) were used as predictors to develop a predictive model for the presence of the pathogen, which achieved 59.2% accuracy. By spatially interpolating the occurrences, it was possible to identify areas with the greatest potential for presence. NDWI and AWEI were most strongly correlated with presence in high-humidity areas, and spatial interpolation identified the higher-risk zones. These findings reveal the challenges of using remote sensing to identify environmental conditions conducive to the presence of pathogens in surface waters. This study highlights the methodological challenges that must be addressed to make satellite-based surveillance an accessible and effective public health tool. By integrating satellite data with environmental and microbiological analyses, this approach can potentially strengthen low-cost, proactive environmental monitoring for public health decision-making in the context of climate change.
水源性疾病,包括由……引起的疾病,正日益成为公共卫生领域的一项挑战,在发展中国家尤为如此。沙门氏菌病的潜在来源包括用地表水灌溉/处理的水果和蔬菜,从而导致人类感染。……每年导致数百万例肠胃炎病例,但通过常规水质监测进行早期检测既耗时,又需要专门设备,且存在局限性,如覆盖范围不足、数据延迟和获取不便等。气候变化引发的洪水和干旱等极端事件进一步加剧了水质的变异性。在此背景下,遥感技术为环境监测提供了一种高效且具成本效益的替代方案。本研究通过整合光谱、微生物、气候和土地利用变量,评估了哨兵 - 2 卫星图像预测智利迈波和马波乔河流域……发生情况的潜力。2019年至2023年期间共采集了1851份水样,其中包括704份……呈阳性的样本,用于建立预测模型。利用遥感技术预测地表水中的……存在挑战,原因有几个。卫星传感器捕捉环境替代指标(如植被覆盖、地表湿度和浊度),但无法捕捉病原体。我们的目标是识别与……可靠相关的替代指标。使用了12个光谱指数(如归一化植被指数、归一化水指数和改进的归一化水指数)作为预测因子,以建立病原体存在情况的预测模型,该模型的准确率达到了59.2%。通过对……发生情况进行空间插值,可以识别出……存在可能性最大的区域。在高湿度地区,归一化水指数和自动水提取指数与……存在的相关性最强,空间插值确定了高风险区域。这些发现揭示了利用遥感技术识别有利于地表水中病原体存在的环境条件所面临的挑战。本研究强调了要使基于卫星的监测成为一种可获取且有效的公共卫生工具必须解决的方法学挑战。通过将卫星数据与环境和微生物分析相结合,这种方法有可能加强低成本、主动的环境监测,以用于气候变化背景下的公共卫生决策。