The presence of Salmonella in rivers, lakes, or beaches in South America represents a challenge to public health and aquatic ecosystems. This review explores the distribution, prevalence, and the main factors contributing to the survival and spread of Salmonella, including wastewater discharge, agricultural runoff, and climatic variables such as high temperatures and precipitation. These factors also facilitate the distribution of multidrug-resistant strains in water. The review is based on bibliographic searches in various databases, focusing on Salmonella species, South American countries, and types of water bodies. Predominant serovars include S. Enteritidis and S. Typhimurium, with S. Typhi and S. Panama frequently detected in Chile, S. Enteritidis in Argentina, and S. Typhimurium in Brazil. Less common serovars, including S. Dublin and S. Paratyphi B, were identified, along with subspecies such as diarizonae and houtenae. These findings highlight the role of environmental, physicochemical, and anthropogenic factors influencing Salmonella dynamics. The review identifies research gaps, advocating for further studies to better understand the interactions between Salmonella, climate change, and human activity. Strengthening surveillance and mitigation strategies is crucial to protect water resources and public health in South America.

Waterborne illnesses, including those caused by Salmonella, 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. Salmonella 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 Salmonella 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 Salmonella, were used to develop a predictive model. Predicting Salmonella 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 Salmonella. 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 Salmonella presence. NDWI and AWEI were most strongly correlated with Salmonella 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.