Browsing by Author "Moreno Switt, Andrea Isabel"
Now showing 1 - 7 of 7
Results Per Page
Sort Options
- ItemChallenges and Potential of Remote Sensing for Assessing Salmonella Risk in Water Sources: Evidence from Chile(MDPI, 2025) Palharini, Rayana Santos Araujo; González Reyes, Makarena Sofía; Ferreira Monteiro, Felipe; Mendoza Villavicencio, Lourdes Milagros; Adell, Aiko D.; Toro, Magaly; Moreno Switt, Andrea Isabel; Undurraga, Eduardo A.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.
- ItemDevelopment of a robust FT-IR typing system for Salmonella enterica, enhancing performance through hierarchical classification(American Society for Microbiology, 2025) Fredes García, Diego Antonio; Jiménez Rodríguez, Javiera Alejandra; Piña Iturbe, Luis Alejandro; Caballero Díaz, Pablo Ignacio; González Villarroel, Tamara Nicol; Dueñas, Fernando; Wozniak Banchero, Aniela; Adell, Aiko D.; Moreno Switt, Andrea Isabel; García Cañete, PatriciaSalmonella enterica is a leading cause of foodborne illnesses globally, with significant mortality rates, especially among vulnerable populations. Traditional serotyping methods for Salmonella are accurate but expensive, resource-intensive, and time-consuming, necessitating faster and more reliable alternatives. This study evaluates the IR Biotyper, a Fourier-transform infrared spectroscopy system, in differentiating Salmonella serovars. We assessed 458 isolates of nine Salmonella serovars (Infantis, Enteritidis, Typhimurium, I,4,[5],12:i:-, Montevideo, Agona, Thompson, Panama, and Abony) from diverse sources. The IR Biotyper was used to acquire spectra from these isolates. Machine learning algorithms, including support vector machines, were trained to classify the isolates. The accuracy of classifiers was validated using a validation set to determine sensitivity, specificity, positive predictive value, and negative predictive value. Initial classifiers showed high accuracy for Abony, Agona, Enteritidis, and Infantis serovars, with sensitivities close to 100%. However, classifiers for S. Typhimurium, S. Panama, and S. Montevideo exhibited lower performance. Implementing a hierarchical classification system enhanced the accuracy of serogroup O:4 serovars, demonstrating that this approach offers a robust framework for Salmonella serovar identification. The hierarchical system enables progressive refinement of classification, minimizing misclassifications by focusing on serogroup-specific features, making it adaptable to complex data sets and diverse serovars. The IR Biotyper demonstrates high potential for rapid and accurate Salmonella serovar identification. This study supports its implementation as a cost-effective, high-throughput tool for pathogen typing, enhancing real-time epidemiological surveillance, and guiding treatment strategies for salmonellosis. This method establishes a robust and scalable framework for advancing Salmonella serotyping practices across clinical, industrial, and public health domains by leveraging hierarchical classification.IMPORTANCEEarly and accurate identification of Salmonella serovars is extremely important for epidemiological surveillance, public health, and food safety. Traditional serotyping is very successful but is laborious and costly. In this study, we demonstrate the promise of Fourier-transform infrared spectroscopy together with machine learning as a means for Salmonella serotyping. Using hierarchical classification, we attain optimal serovar identification accuracy, particularly for challenging-to-type serogroups. Our findings recognize the IR Biotyper as a high-throughput, scalable pathogen typing solution that offers real-time data that can enable enhanced outbreak response and prevention of foodborne disease. The approach bridges the gap between traditional microbiological practice and sophisticated analytical technology, the path to more effective, cost-saving interventions in the clinical, industrial, and regulatory settings. Application of these technologies can significantly improve Salmonella surveillance-control and Public Health outcomes.
- ItemExtended-spectrum beta-lactamases belonging to CTX-M group produced by Escherichia coli strains isolated from companion animals treated with enrofloxacin(2008) Moreno Switt, Andrea Isabel; Bello, Helia; Guggiana, Drago; Dominguez, Mariana; Gonzalez, Gerardo
- ItemSalmonella enterica Serovar Abony Outbreak Caused by Clone of Reference Strain WDCM 00029, Chile, 2024(Centers Disease Control & Prevention, 2025) Piña Iturbe, Luis Alejandro; Fredes García, Diego Antonio; García Cañete, Patricia; Porte, Lorena; Johnson, Timothy J.; Singer, Randall S.; Toro, Magaly; Munita, Jose M.; Moreno Switt, Andrea IsabelA Salmonella enterica serovar Abony outbreak occurred during January–April 2024 in Chile. Genomic evidence indicated that the outbreak strain was a clone of reference strain WDCM 00029, which is routinely used in microbiological quality control tests. When rare or unreported serovars cause human infections, clinicians and health authorities should request strain characterization.
- ItemSalmonella in Raptors and Aquatic Wild Birds in Chile(2020) Tardone, R.; Rivera, D.; Duenas, F.; Sallaberry Pincheira, Nicole; Hamilton West, C.; Adell, A. D.; Moreno Switt, Andrea Isabel
- ItemThe COVID-19 Pandemic and Global Food Security(2020) Mardones, Fernando O.; Rich, K. M.; Boden, L. A.; Moreno Switt, Andrea Isabel; Caipo, M. L.; Zimin Veselkoff, Natalia; Alateeqi, A. M.; Baltenweck, I.
- ItemWidespread dissemination of ESBL-producing Salmonella enterica serovar Infantis exhibiting intermediate fluoroquinolone resistance and harboring blaCTX-M-65-positive pESI-like megaplasmids in Chile(bioRxiv, 2023) Piña Iturbe, Luis Alejandro; Díaz Gavidia, Constanza Paz; Álvarez Rojas, Francisca Pía; Barron Montenegro, Rocío Nicole; Álvarez Espejo, Diana Claudia Marcela; García Cañete, Patricia; Solís, Doina; Constenla-Albornoz, Rodrigo; Toro Parada, Magaly Rosana; Olivares-Pacheco, Jorge; Reyes-Jara, Angélica; Meng, Jianghong; Bell, Rebecca L.; Moreno Switt, Andrea Isabel