Interpretation of COVID-19 Epidemiological Trends in Mexico Through Wastewater Surveillance Using Simple Machine Learning Algorithms for Rapid Decision-Making

Detection and quantification of disease-related biomarkers in wastewater samples, denominated Wastewater-based Surveillance (WBS), has proven a valuable strategy for studying the prevalence of infectious diseases within populations in a time- and resource-efficient manner, as wastewater samples are...

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Veröffentlicht in:	Viruses Jg. 17; H. 1; S. 109
Hauptverfasser:	Armenta-Castro, Arnoldo, de la Rosa, Orlando, Aguayo-Acosta, Alberto, Oyervides-Muñoz, Mariel Araceli, Flores-Tlacuahuac, Antonio, Parra-Saldívar, Roberto, Sosa-Hernández, Juan Eduardo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 01.01.2025 MDPI
Schlagworte:	Algorithms Biomarkers Catchment areas Cluster Analysis College campuses COVID-19 COVID-19 - epidemiology COVID-19 vaccines data-based decision-making Datasets Decision Making Epidemiology Genomes Health aspects Health surveillance Humans Immunization Infectious diseases Machine Learning Medical research Medicine, Experimental Methods Mexico - epidemiology Neural networks Public health Regression analysis Risk Assessment SARS-CoV-2 Sentinel health events Severe acute respiratory syndrome coronavirus 2 Social distancing Wastewater Wastewater - virology wastewater surveillance Wastewater treatment Wastewater-Based Epidemiological Monitoring Mexico United States United States > US SARS-CoV-2 machine learning data-based decision-making wastewater surveillance
ISSN:	1999-4915, 1999-4915
Online-Zugang:	Volltext
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