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Armenta-Castro A, de la Rosa O, Aguayo-Acosta A, Oyervides-Muñoz MA, Flores-Tlacuahuac A, Parra-Saldívar R, Sosa-Hernández JE. Interpretation of COVID-19 Epidemiological Trends in Mexico Through Wastewater Surveillance Using Simple Machine Learning Algorithms for Rapid Decision-Making. Viruses 2025; 17:109. [PMID: 39861898 PMCID: PMC11768489 DOI: 10.3390/v17010109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2024] [Revised: 12/19/2024] [Accepted: 12/30/2024] [Indexed: 01/27/2025] Open
Abstract
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 representative of all cases within the catchment area, whether they are clinically reported or not. However, analysis and interpretation of WBS datasets for decision-making during public health emergencies, such as the COVID-19 pandemic, remains an area of opportunity. In this article, a database obtained from wastewater sampling at wastewater treatment plants (WWTPs) and university campuses in Monterrey and Mexico City between 2021 and 2022 was used to train simple clustering- and regression-based risk assessment models to allow for informed prevention and control measures in high-affluence facilities, even if working with low-dimensionality datasets and a limited number of observations. When dividing weekly data points based on whether the seven-day average daily new COVID-19 cases were above a certain threshold, the resulting clustering model could differentiate between weeks with surges in clinical reports and periods between them with an 87.9% accuracy rate. Moreover, the clustering model provided satisfactory forecasts one week (80.4% accuracy) and two weeks (81.8%) into the future. However, the prediction of the weekly average of new daily cases was limited (R2 = 0.80, MAPE = 72.6%), likely because of insufficient dimensionality in the database. Overall, while simple, WBS-supported models can provide relevant insights for decision-makers during epidemiological outbreaks, regression algorithms for prediction using low-dimensionality datasets can still be improved.
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Affiliation(s)
- Arnoldo Armenta-Castro
- School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, Mexico; (A.A.-C.); (O.d.l.R.); (A.A.-A.); (M.A.O.-M.); (A.F.-T.)
| | - Orlando de la Rosa
- School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, Mexico; (A.A.-C.); (O.d.l.R.); (A.A.-A.); (M.A.O.-M.); (A.F.-T.)
- Institute of Advanced Materials for Sustainable Manufacturing, Tecnologico de Monterrey, Monterrey 64849, Mexico
| | - Alberto Aguayo-Acosta
- School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, Mexico; (A.A.-C.); (O.d.l.R.); (A.A.-A.); (M.A.O.-M.); (A.F.-T.)
- Institute of Advanced Materials for Sustainable Manufacturing, Tecnologico de Monterrey, Monterrey 64849, Mexico
| | - Mariel Araceli Oyervides-Muñoz
- School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, Mexico; (A.A.-C.); (O.d.l.R.); (A.A.-A.); (M.A.O.-M.); (A.F.-T.)
- Institute of Advanced Materials for Sustainable Manufacturing, Tecnologico de Monterrey, Monterrey 64849, Mexico
- Virology & Microbiological Preparedness, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Antonio Flores-Tlacuahuac
- School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, Mexico; (A.A.-C.); (O.d.l.R.); (A.A.-A.); (M.A.O.-M.); (A.F.-T.)
- Institute of Advanced Materials for Sustainable Manufacturing, Tecnologico de Monterrey, Monterrey 64849, Mexico
| | - Roberto Parra-Saldívar
- Biomolecular Innovation Group, Facultad de Agronomía, Universidad Autónoma de Nuevo León, Francisco Villa S/N, Col. Ex Hacienda El Canadá, General Escobedo 66415, Mexico;
- Magan Centre of Applied Mycology (MCAM), Faculty of Engineering and Applied Sciences, Cranfield University Cranfield, Cranfield, Bedford MK43 0AL, UK
| | - Juan Eduardo Sosa-Hernández
- School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, Mexico; (A.A.-C.); (O.d.l.R.); (A.A.-A.); (M.A.O.-M.); (A.F.-T.)
- Institute of Advanced Materials for Sustainable Manufacturing, Tecnologico de Monterrey, Monterrey 64849, Mexico
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Aguayo-Acosta A, Oyervides-Muñoz MA, Rodriguez-Aguillón KO, Ovalle-Carcaño A, Romero-Castillo KD, Robles-Zamora A, Johnson M, Parra-Saldívar R, Sosa-Hernández JE. Omicron and Delta variant prevalence detection and identification during the fourth COVID-19 wave in Mexico using wastewater-based epidemiology. IJID REGIONS 2024; 10:44-51. [PMID: 38149263 PMCID: PMC10750064 DOI: 10.1016/j.ijregi.2023.11.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 11/03/2023] [Accepted: 11/06/2023] [Indexed: 12/28/2023]
Abstract
Objectives To identify the SARS-CoV-2 variants Delta and Omicron during the fourth wave of the COVID-19 pandemic in Mexico using samples taken from 19 locations in 18 out of the 32 states. Methods The genetic material concentration was done with PEG/NaCl precipitation, SARS-CoV-2 presence was confirmed by reverse transcriptase-quantitative polymerase chain reaction assay, the variant detection was carried out using a commercial mutation detection panel kit, and variant/mutation confirmation was done by amplicon sequencing of receptor-binding domain target region. The study used 41 samples. Results The Delta variant was confirmed in two samples during August 2021 (Querétaro and CDMX) and in three samples during November 2021 (Aguascalientes, Ciudad Juárez campuses, and Nuevo Leon). In December 2021, another sample with the Delta variant was confirmed in Nuevo Leon. Between January to March 2022 only the presence of Omicron was confirmed, (variant BA.1). Additionally, in this period six samples were identified with the status "Variant Not Determined". Conclusion To our knowledge, this study is one of the first to identify Omicron and Delta variants with polymerase chain reaction in Mexico and Latin America and its distribution across the country with 56% Mexican states making it a viable alternative for variant detection without conducting a large quantity of sequencing of clinical tests.
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Affiliation(s)
- Alberto Aguayo-Acosta
- Tecnologico de Monterrey, Institute of Advanced Materials for Sustainable Manufacturing, Monterrey, Mexico
- Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, Mexico
| | - Mariel Araceli Oyervides-Muñoz
- Tecnologico de Monterrey, Institute of Advanced Materials for Sustainable Manufacturing, Monterrey, Mexico
- Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, Mexico
| | - Kassandra O. Rodriguez-Aguillón
- Tecnologico de Monterrey, Institute of Advanced Materials for Sustainable Manufacturing, Monterrey, Mexico
- Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, Mexico
| | - Antonio Ovalle-Carcaño
- Tecnologico de Monterrey, Institute of Advanced Materials for Sustainable Manufacturing, Monterrey, Mexico
- Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, Mexico
| | | | | | - Marc Johnson
- Department of Molecular Microbiology and Immunology, University of Missouri School of Medicine, Columbia, USA
| | - Roberto Parra-Saldívar
- Tecnologico de Monterrey, Institute of Advanced Materials for Sustainable Manufacturing, Monterrey, Mexico
- Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, Mexico
| | - Juan Eduardo Sosa-Hernández
- Tecnologico de Monterrey, Institute of Advanced Materials for Sustainable Manufacturing, Monterrey, Mexico
- Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, Mexico
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Cohen JH, Mitchel AP, Montiel Ishino FA. Evaluating the indigenous response to COVID-19 in rural Oaxaca, Mexico. J Glob Health 2023; 13:03051. [PMID: 37792892 PMCID: PMC10550196 DOI: 10.7189/jogh.13.03051] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/06/2023] Open
Affiliation(s)
- Jeffrey H Cohen
- Department of Anthropology, The Ohio State University, Columbus, Ohio, USA
| | - Andrew P Mitchel
- Department of Anthropology, The Ohio State University, Columbus, Ohio, USA
| | - Francisco A Montiel Ishino
- National Institute of Environmental Health Sciences, Epidemiology Branch, Division of Intramural Research, National Institutes of Health, RTP, North Carolina, USA
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De La Cruz-Hernández SI, Álvarez-Contreras AK. Omicron BA.5 Subvariant Provokes the Fifth COVID-19 Wave in Mexico: Closer to the End of This Pandemic. Disaster Med Public Health Prep 2023; 17:e344. [PMID: 36628619 PMCID: PMC10019927 DOI: 10.1017/dmp.2023.14] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Affiliation(s)
- Sergio Isaac De La Cruz-Hernández
- Department of Virology, Institute of Epidemiological Diagnosis and Reference (InDRE), Mexico City, Ministry of Health of Mexico, Mexico
- Corresponding author: Sergio Isaac De La Cruz-Hernández,
| | - Ana Karen Álvarez-Contreras
- Department of Microbiology, National School of Biological Science, National Polytechnic Institute, Mexico City, México
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