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Haraguchi M, Klaassen F, Cohen T, Salomon JA, Menzies NA. Statistical Relationship Between Wastewater Data and Case Notifications for COVID-19 Surveillance in the United States From 2020 to 2023: Bayesian Hierarchical Modeling Approach. JMIR Public Health Surveill 2025; 11:e68213. [PMID: 40402554 DOI: 10.2196/68213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2024] [Revised: 02/17/2025] [Accepted: 02/18/2025] [Indexed: 05/23/2025] Open
Abstract
Background During the COVID-19 pandemic, several US jurisdictions began to regularly report levels of SARS-CoV-2 in wastewater as a proxy for SARS-CoV-2 incidence. Despite the promise of this approach for improving COVID-19 situational awareness, the degree to which wastewater surveillance data agree with other data has varied, and better evidence is needed to understand the situations in which wastewater surveillance data track closely with traditional surveillance data. Objective In this study, we quantified the statistical relationship between wastewater data and traditional case-based surveillance data for multiple jurisdictions. Methods We collated data on wastewater SARS-CoV-2 RNA levels and COVID-19 case reports from July 2020 to March 2023 for 107 counties representing a range in terms of geographic location, population size, and urbanicity. For these counties, we used Bayesian hierarchical regression modeling to estimate the statistical relationship between wastewater data and reported cases, allowing for variation in this relationship across counties. We compared different model structural approaches and assessed how the strength of the estimated relationships varied between settings and over time. Results Our analyses revealed a strong positive relationship between wastewater data and COVID-19 cases for the majority of locations, with a median correlation coefficient between observed and predicted cases of 0.904 (IQR 0.823-0.943). In total, 23/107 counties (21.5%) had correlation coefficients below 0.8, and 3/107 (2.8%) had values below 0.6. Across locations, the COVID-19 case rate associated with a given level of wastewater SARS-CoV-2 RNA concentration declined over the study period. Counties with greater population size (P<.001) and higher levels of urbanicity (P<.001) had stronger concordance between wastewater data and COVID-19 cases. Measures of model fit, and relationships with urbanicity and population size, were robust to sensitivity analyses in which we varied the time period of analysis and the sample of counties used for model fitting. Conclusions In a sample of 107 US counties, wastewater surveillance had a close relationship with COVID-19 cases reported for the majority of locations, with these relationships found to be stronger in counties with greater population size and urbanicity. In situations where routine COVID-19 surveillance data are less reliable, wastewater surveillance may be used to track local SARS-CoV-2 incidence trends.
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Affiliation(s)
- Masahiko Haraguchi
- Department of Global Health and Population, Harvard T H Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, United States, 1 6174321046
| | - Fayette Klaassen
- Department of Global Health and Population, Harvard T H Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, United States, 1 6174321046
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, United States
| | - Joshua A Salomon
- Department of Health Policy, Stanford University, Stanford, CA, United States
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T H Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, United States, 1 6174321046
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2
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Costa SM, Simas MCDC, da Costa LJ, Silva R. Dynamics of SARS-CoV-2 Mutations in Wastewater Provide Insights into the Circulation of Virus Variants in the Population. Int J Mol Sci 2025; 26:4324. [PMID: 40362561 PMCID: PMC12072199 DOI: 10.3390/ijms26094324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2025] [Revised: 04/23/2025] [Accepted: 04/25/2025] [Indexed: 05/15/2025] Open
Abstract
SARS-CoV-2 high transmission and genomic mutations result in the emergence of new variants that impact COVID-19 vaccine efficacy and virus transmission by evading the host immune system. Wastewater-based epidemiology is an effective approach to monitor SARS-CoV-2 variants circulation in the population but is a challenge due to the presence of reaction inhibitors and the low concentrations of SARS-CoV-2 in this environment. Here, we aim to improve SARS-CoV-2 variant detection in wastewater by employing nested PCR followed by next-generation sequencing (NGS) of small amplicons of the S gene. Eight SARS-CoV-2 wastewater samples from Alegria Wastewater Treatment Plant, in Rio de Janeiro, Brazil, were collected monthly from February to September 2021. Samples were submitted to virus concentration, RNA extraction and nested PCR followed by NGS. The small amplicons were used to prepare libraries for sequencing without the need to perform any fragmentation step. We identified and calculated the frequencies of 29 mutations matching the Alpha, Beta, Gamma, Delta, Omicron, and P.2 variants. Omicron matching-mutations were detected before the lineage was classified as a variant of concern. SARS-CoV-2 wastewater sequences clustered with SARS-CoV-2 variants detected in clinical samples that circulated in 2021 in Rio de Janeiro. We show that sequencing of selected small amplicons of SARS-CoV-2 S gene allows the identification of SARS-CoV-2 variants matching mutations and their frequencies' calculation. This approach may be expanded using customizing primers for additional genomic regions, in order to differentiate current variants. Approaches that allow us to learn how variants emerge and how they relate to clinical outcomes are crucial for our understanding of the dynamics of virus variants circulation, providing valuable data for public health management.
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Affiliation(s)
- Sara Mesquita Costa
- Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-902, RJ, Brazil; (S.M.C.); (M.C.d.C.S.)
- Instituto de Microbiologia Paulo de Góes, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-902, RJ, Brazil;
| | - Maria Clara da Costa Simas
- Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-902, RJ, Brazil; (S.M.C.); (M.C.d.C.S.)
| | - Luciana Jesus da Costa
- Instituto de Microbiologia Paulo de Góes, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-902, RJ, Brazil;
| | - Rosane Silva
- Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-902, RJ, Brazil; (S.M.C.); (M.C.d.C.S.)
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3
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Ramachandran P, Kayikcioglu T, Walsky T, Judy K, Amirzadegan J, Bias CH, Tesfaldet B, Balkey M, EppSchmidt D, Rand H, Pettengill J, Tallent S, Brown E, Pfefer T, Timme R, Windsor A, Grim C, Hoffmann M. Harnessing methods, data analysis, and near-real-time wastewater monitoring for enhanced public health response using high throughput sequencing. ENVIRONMENTAL RESEARCH 2025; 278:121633. [PMID: 40254239 DOI: 10.1016/j.envres.2025.121633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2024] [Revised: 04/14/2025] [Accepted: 04/15/2025] [Indexed: 04/22/2025]
Abstract
Wastewater-based analysis has emerged as a pivotal method for monitoring SARS-CoV-2 (SC2). Leveraging high-throughput sequencing on wastewater samples facilitates a comprehensive, population-level assessment of circulating and emerging SC2 variants within a community. This study meticulously evaluates the detection performance, variant calling accuracy, and the time taken from sample collection to public data release for wastewater SC2 monitoring. Two different SC2 target enrichment panels were employed, Illumina MiSeq and Oxford Nanopore Technologies (ONT) GridION sequencing platforms for a robust analysis. Daily collection of routine raw grab and composite samples took place at a wastewater treatment plant (WWTP) site in Maryland, USA (MD) from mid-January 2022 to the end of June 2022. Total Nucleic Acid (TNA) was extracted from samples and target enrichment was executed using QIAseq DIRECT and NEBNext VarSkip Short amplicon kits, with subsequent sequencing on MiSeq or ONT GridION platforms, respectively. Obtained sequences was analyzed using custom CFSAN Wastewater Analysis Pipeline (C-WAP). Raw sequence data and detailed metadata were submitted to NCBI (BioProject PRJNA757291) as it became available. Wastewater data successfully detected the onset of new variants BA.2, BA.2.12, BA.4.6, and BA.5 to the observed population. Notably, Omicron sub-variants were identified approximately a week ahead of publicly available clinical data at the MD ZIP-code level. Variation in quality metrics paralleled the rise and fall of BA waves, underscoring the impact of viral load on sequencing quality. Regular updates of estimated variant proportions were made available on the FDA-CFSAN "Wastewater Surveillance for SARS-CoV-2 Variants" website. In contrast to the median 28-day turnaround, the lead time from sample collection to public release of raw sequence data via NCBI was remarkably swift, accomplished within a mere 57 h in this specific exercise. Processing, sequencing, and analysis methods empowered the swift and accurate detection of SC2 trends and circulating variants within a community, offering insights for public health decision-making.
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Affiliation(s)
- Padmini Ramachandran
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA.
| | - Tunc Kayikcioglu
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA; Joint Institute for Food Safety and Applied Nutrition, University of Maryland, 5825, University Research Ct, Suite 1400, College Park, MD, USA
| | - Tamara Walsky
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - Kathryn Judy
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - Jasmine Amirzadegan
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - Candace Hope Bias
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - Bereket Tesfaldet
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - Maria Balkey
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - Dietrich EppSchmidt
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA; Joint Institute for Food Safety and Applied Nutrition, University of Maryland, 5825, University Research Ct, Suite 1400, College Park, MD, USA
| | - Hugh Rand
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - James Pettengill
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - Sandra Tallent
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - Eric Brown
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - Tina Pfefer
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - Ruth Timme
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - Amanda Windsor
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - Christopher Grim
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
| | - Maria Hoffmann
- Human Foods Program, Food and Drug Administration, HFS-712, 5001 Campus Drive, College Park, 20740, MD, USA
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Farkas K, Williams RC, Hillary LS, Garcia-Delgado A, Jameson E, Kevill JL, Wade MJ, Grimsley JMS, Jones DL. Harnessing the Power of Next-Generation Sequencing in Wastewater-Based Epidemiology and Global Disease Surveillance. FOOD AND ENVIRONMENTAL VIROLOGY 2024; 17:5. [PMID: 39614945 PMCID: PMC11608212 DOI: 10.1007/s12560-024-09616-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2024] [Accepted: 10/29/2024] [Indexed: 12/07/2024]
Abstract
Wastewater-based epidemiology (WBE) has emerged as a valuable surveillance tool for SARS-CoV-2 and other pathogens globally, providing insights into community-level infections, including asymptomatic and pre-symptomatic cases. While most WBE programmes focus on quantitative pathogen assessment, next-generation sequencing (NGS) approaches have enabled more detailed analyses, including variant and recombinant genotype identification for viruses like SARS-CoV-2 and poliovirus. Despite recent NGS advancements allowing for the detection of known and novel viruses in wastewater, many of these tools remain underutilised in routine WBE. This short review critically evaluates the applicability of common NGS tools in routine WBE programmes, assessing their capability for identifying emerging threats with epidemic or pandemic potential. Here, we provide evidence-based recommendations for integrating NGS techniques into WBE and the use of results for informed decision-making within a One Health framework, aiming to enhance global infectious disease surveillance and pandemic preparedness.
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Affiliation(s)
- Kata Farkas
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK.
| | - Rachel C Williams
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK
- Verily Life Sciences LLC., South San Francisco, California, 94080, USA
| | - Luke S Hillary
- Department of Plant Pathology, University of California Davis, Davis, California, 95616, USA
| | - Alvaro Garcia-Delgado
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK
| | - Eleanor Jameson
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK
| | - Jessica L Kevill
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK
| | - Matthew J Wade
- Data, Analytics & Surveillance Group, UK Health Security Agency, London, E14 4PU, UK
| | | | - Davey L Jones
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK
- Verily Life Sciences LLC., South San Francisco, California, 94080, USA
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5
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Chen X, Balliew J, Bauer CX, Deegan J, Gitter A, Hanson BM, Maresso AW, Tisza MJ, Troisi CL, Rios J, Mena KD, Boerwinkle E, Wu F. Revealing patterns of SARS-CoV-2 variant emergence and evolution using RBD amplicon sequencing of wastewater. J Infect 2024; 89:106284. [PMID: 39341403 DOI: 10.1016/j.jinf.2024.106284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2024] [Revised: 09/06/2024] [Accepted: 09/20/2024] [Indexed: 10/01/2024]
Abstract
OBJECTIVES Rapid evolution of SARS-CoV-2 has resulted in the emergence of numerous variants, posing significant challenges to public health surveillance. Clinical genome sequencing, while valuable, has limitations in capturing the full epidemiological dynamics of circulating variants in the general population. This study aimed to monitor the SARS-CoV-2 variant community dynamics and evolution using receptor-binding domain (RBD) amplicon sequencing of wastewater samples. METHODS We sequenced wastewater from El Paso, Texas, over 17 months, compared the sequencing data with clinical genome data, and performed biodiversity analysis to reveal SARS-CoV-2 variant dynamics and evolution. RESULTS We identified 91 variants and observed waves of dominant variants transitioning from BA.2 to BA.2.12.1, BA.4&5, BQ.1, and XBB.1.5. Comparison with clinical genome sequencing data revealed earlier detection of variants and identification of unreported outbreaks. Our results also showed strong consistency with clinical data for dominant variants at the local, state, and national levels. Alpha diversity analyses revealed significant seasonal variations, with the highest diversity observed in winter. By segmenting the outbreak into lag, growth, stationary, and decline phases, we found higher variant diversity during the lag phase, likely due to lower inter-variant competition preceding outbreak growth. CONCLUSIONS Our findings underscore the importance of low transmission periods in facilitating rapid mutation and variant evolution. Our approach, integrating RBD amplicon sequencing with wastewater surveillance, demonstrates effectiveness in tracking viral evolution and understanding variant emergence, thus enhancing public health preparedness.
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Affiliation(s)
- Xingwen Chen
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA; Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | | | - Cici X Bauer
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA; Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Jennifer Deegan
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA; Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Anna Gitter
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA; Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Blake M Hanson
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA; Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Anthony W Maresso
- TAILOR Labs, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Michael J Tisza
- The Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Catherine L Troisi
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA; Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Janelle Rios
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA; Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Kristina D Mena
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA; Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Eric Boerwinkle
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA; Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Fuqing Wu
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA; Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA.
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6
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Tierney BT, Foox J, Ryon KA, Butler D, Damle N, Young BG, Mozsary C, Babler KM, Yin X, Carattini Y, Andrews D, Lucaci AG, Solle NS, Kumar N, Shukla B, Vidović D, Currall B, Williams SL, Schürer SC, Stevenson M, Amirali A, Beaver CC, Kobetz E, Boone MM, Reding B, Laine J, Comerford S, Lamar WE, Tallon JJ, Wain Hirschberg J, Proszynski J, Al Ghalith G, Can Kurt K, Sharkey ME, Church GM, Grills GS, Solo-Gabriele HM, Mason CE. Towards geospatially-resolved public-health surveillance via wastewater sequencing. Nat Commun 2024; 15:8386. [PMID: 39333485 PMCID: PMC11436780 DOI: 10.1038/s41467-024-52427-x] [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: 06/23/2024] [Accepted: 09/05/2024] [Indexed: 09/29/2024] Open
Abstract
Wastewater is a geospatially- and temporally-linked microbial fingerprint of a given population, making it a potentially valuable tool for tracking public health across locales and time. Here, we integrate targeted and bulk RNA sequencing (N = 2238 samples) to track the viral, bacterial, and functional content over geospatially distinct areas within Miami Dade County, USA, from 2020-2022. We used targeted amplicon sequencing to track diverse SARS-CoV-2 variants across space and time, and we found a tight correspondence with positive PCR tests from University students and Miami-Dade hospital patients. Additionally, in bulk metatranscriptomic data, we demonstrate that the bacterial content of different wastewater sampling locations serving small population sizes can be used to detect putative, host-derived microorganisms that themselves have known associations with human health and diet. We also detect multiple enteric pathogens (e.g., Norovirus) and characterize viral diversity across sites. Moreover, we observed an enrichment of antimicrobial resistance genes (ARGs) in hospital wastewater; antibiotic-specific ARGs correlated to total prescriptions of those same antibiotics (e.g Ampicillin, Gentamicin). Overall, this effort lays the groundwork for systematic characterization of wastewater that can potentially influence public health decision-making.
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Affiliation(s)
- Braden T Tierney
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.
| | - Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Krista A Ryon
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Daniel Butler
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Namita Damle
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Benjamin G Young
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Christopher Mozsary
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Kristina M Babler
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL, USA
| | - Xue Yin
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL, USA
| | - Yamina Carattini
- Department of Pathology and Laboratory Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - David Andrews
- Department of Pathology and Laboratory Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Alexander G Lucaci
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | | | - Naresh Kumar
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Bhavarth Shukla
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Dušica Vidović
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL, USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Benjamin Currall
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Sion L Williams
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Stephan C Schürer
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL, USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
- Institute for Data Science & Computing, University of Miami, Coral Gables, FL, USA
| | - Mario Stevenson
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Ayaaz Amirali
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL, USA
| | - Cynthia Campos Beaver
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Erin Kobetz
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Melinda M Boone
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Brian Reding
- Environmental Health and Safety, University of Miami, Miami, FL, USA
| | - Jennifer Laine
- Environmental Health and Safety, University of Miami, Miami, FL, USA
| | - Samuel Comerford
- Environmental Health and Safety, University of Miami, Miami, FL, USA
| | - Walter E Lamar
- Division of Occupational Health, Safety & Compliance, University of Miami Health System, Miami, FL, USA
| | - John J Tallon
- Facilities and Operations, University of Miami, Coral Gables, FL, USA
| | | | | | | | - Kübra Can Kurt
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Mark E Sharkey
- Department of Pathology and Laboratory Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - George M Church
- Harvard Medical School and the Wyss Institute, Boston, MA, USA
| | - George S Grills
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Helena M Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL, USA.
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.
- The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA.
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7
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Deák G, Prangate R, Croitoru C, Matei M, Boboc M. The first detection of SARS-CoV-2 RNA in the wastewater of Bucharest, Romania. Sci Rep 2024; 14:21730. [PMID: 39289536 PMCID: PMC11408638 DOI: 10.1038/s41598-024-72854-6] [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: 05/01/2024] [Accepted: 09/11/2024] [Indexed: 09/19/2024] Open
Abstract
Wastewater-based epidemiology (WBE) has been previously used as a tool for pathogen identification within communities. After the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) outbreak, in 2020, Daughton proposed the implementation of a wastewater surveillance strategy that could determine the incidence of COVID-19 (coronavirus disease 2019) nationally. Individuals in various stages of SARS-CoV-2 infection, including presymptomatic, asymptomatic and symptomatic patients, can be identified as carriers of the virus in their urine, saliva, stool and other bodily secretions. Studies using this method were conducted to monitor the prevalence of the virus in high-density populations, such as cities but also in smaller communities, such as schools and college campuses. The aim of this pilot study was to assess the feasibility and effectiveness of wastewater surveillance in Bucharest, Romania, and wastewater samples were collected weekly from seven locations between July and September 2023. RNA (ribonucleic acid) extraction, followed by dPCR (digital polymerase chain reaction) analysis, was performed to detect viral genetic material. Additionally, NGS (next generation sequencing) technology was used to identify the circulating variants within the wastewater of Bucharest, Romania. Preliminary results indicate the successful detection of SARS-CoV-2 RNA in wastewater, providing valuable insights into the circulation of the virus within the community.
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Affiliation(s)
- György Deák
- National Institute for Research and Development in Environmental Protection, Splaiul Independenţei 294, 060031, Bucharest, Romania
| | - Raluca Prangate
- National Institute for Research and Development in Environmental Protection, Splaiul Independenţei 294, 060031, Bucharest, Romania.
| | - Cristina Croitoru
- National Institute for Research and Development in Environmental Protection, Splaiul Independenţei 294, 060031, Bucharest, Romania
| | - Monica Matei
- National Institute for Research and Development in Environmental Protection, Splaiul Independenţei 294, 060031, Bucharest, Romania
| | - Mădălina Boboc
- National Institute for Research and Development in Environmental Protection, Splaiul Independenţei 294, 060031, Bucharest, Romania
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8
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Zhang Z, He F, Yi L, Deng Z, Wang R, Shen L, Fu S. Wastewater surveillance together with metaviromic data revealed the unusual resurgence of infectious diseases after the first wave of the COVID-19 outbreak. JOURNAL OF HAZARDOUS MATERIALS 2024; 473:134635. [PMID: 38772110 DOI: 10.1016/j.jhazmat.2024.134635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 04/01/2024] [Accepted: 05/15/2024] [Indexed: 05/23/2024]
Abstract
How to address public health priorities after COVID-19 is becoming a critical task. To this end, we conducted wastewater surveillance for six leading pathogens, namely, SARS-CoV-2, norovirus, rotavirus, influenza A virus (IAV), enteroviruses and respiratory syncytial virus (RSV), in Nanchang city from January to April 2023. Metaviromic sequencing was conducted at the 1st, 4th, 7th, 9th, 12th and 14th weeks to reveal the dynamics of viral pathogens that were not covered by qPCR. Amplicon sequencing of the conserved region of norovirus GI and GII and the rotavirus and region encoding nonstructural protein of RSV was also conducted weekly. The results showed that after a rapid decrease in SARS-CoV-2 sewage concentrations occurred in January 2023, surges of norovirus, rotavirus, IAV and RSV started at the 6th, 7th, 8th and 11th weeks, respectively. The dynamics of the sewage concentrations of norovirus, rotavirus, IAV and RSV were consistent with the off-season resurgence of the above infectious diseases. Notably, peak sewage concentrations of norovirus GI, GII, rotavirus, IAV and RSV were found at the 6th, 3rd, 7th, 7th and 8th weeks, respectively. Astroviruses also resurge after the 7th week, as revealed by metaviromic data, suggesting that wastewater surveillance together with metaviromic data provides an essential early warning tool for revealing patterns of infectious disease resurgence.
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Affiliation(s)
- Ziqiang Zhang
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Medicine, Northwest University, Xi'an 710069, China
| | - Fenglan He
- The Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang 330038, Jiangxi, China
| | - Liu Yi
- The Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang 330038, Jiangxi, China
| | - Zhiqiang Deng
- The Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang 330038, Jiangxi, China
| | - Rui Wang
- Key Laboratory of Environment Controlled Aquaculture (KLECA), Ministry of Education, Dalian Ocean University, Dalian 116023, China
| | - Lixin Shen
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Medicine, Northwest University, Xi'an 710069, China.
| | - Songzhe Fu
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Medicine, Northwest University, Xi'an 710069, China.
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Chen X, Balliew J, Bauer CX, Deegan J, Gitter A, Hanson BM, Maresso AW, Tisza MJ, Troisi CL, Rios J, Mena KD, Boerwinkle E, Wu F. RBD amplicon sequencing of wastewater reveals patterns of variant emergence and evolution. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.12.24310301. [PMID: 39040200 PMCID: PMC11261926 DOI: 10.1101/2024.07.12.24310301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
Rapid evolution of SARS-CoV-2 has resulted in the emergence of numerous variants, posing significant challenges to public health surveillance. Clinical genome sequencing, while valuable, has limitations in capturing the full epidemiological dynamics of circulating variants in the general population. This study utilized receptor-binding domain (RBD) amplicon sequencing of wastewater samples to monitor the SARS-CoV-2 community dynamics and evolution in El Paso, TX. Over 17 months, we identified 91 variants and observed waves of dominant variants transitioning from BA.2 to BA.2.12.1, BA.4&5, BQ.1, and XBB.1.5. Our findings demonstrated early detection of variants and identification of unreported outbreaks, while showing strong consistency with clinical genome sequencing data at the local, state, and national levels. Alpha diversity analyses revealed significant periodical variations, with the highest diversity observed in winter and the outbreak lag phases, likely due to lower competition among variants before the outbreak growth phase. The data underscores the importance of low transmission periods for rapid mutation and variant evolution. This study highlights the effectiveness of integrating RBD amplicon sequencing with wastewater surveillance in tracking viral evolution, understanding variant emergence, and enhancing public health preparedness.
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Affiliation(s)
- Xingwen Chen
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - John Balliew
- El Paso Water Utility, El Paso, TX, United States
| | - Cici X Bauer
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Jennifer Deegan
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Anna Gitter
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Blake M Hanson
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Anthony W Maresso
- TAILOR Labs, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Michael J Tisza
- The Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Catherine L Troisi
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Janelle Rios
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Kristina D Mena
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Eric Boerwinkle
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
| | - Fuqing Wu
- School of Public Health, University of Texas Health Science Center at Houston, TX, USA
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, USA
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Srikrishna D. Pentagon Found Daily, Metagenomic Detection of Novel Bioaerosol Threats to Be Cost-Prohibitive: Can Virtualization and AI Make It Cost-Effective? Health Secur 2024; 22:108-129. [PMID: 38625036 DOI: 10.1089/hs.2023.0048] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/17/2024] Open
Abstract
In 2022, the Pentagon Force Protection Agency found threat agnostic detection of novel bioaerosol threats to be "not feasible for daily operations" due to the cost of reagents used for metagenomics, cost of sequencing instruments, and cost of labor for subject matter experts to analyze bioinformatics. Similar operational difficulties might extend to many of the 280,000 buildings (totaling 2.3 billion square feet) at 5,000 secure US Department of Defense military sites, 250 Navy ships, as well as many civilian buildings. These economic barriers can still be addressed in a threat agnostic manner by dynamically pooling samples from dry filter units, called spike-triggered virtualization, whereby pooling and sequencing depth are automatically modulated based on novel biothreats in the sequencing output. By running at a high average pooling factor, the daily and annual cost per dry filter unit can be reduced by 10 to 100 times depending on the chosen trigger thresholds. Artificial intelligence can further enhance the sensitivity of spike-triggered virtualization. The risk of infection during the 12- to 24-hour window between a bioaerosol incident and its detection remains, but in some cases it can be reduced by 80% or more with high-speed indoor air cleaning exceeding 12 air changes per hour, which is similar to the rate of air cleaning in passenger airplanes in flight. That level of air changes per hour or higher is likely to be cost-prohibitive using central heating ventilation and air conditioning systems, but it can be achieved economically by using portable air filtration in rooms with typical ceiling heights (less than 10 feet) for a cost of approximately $0.50 to $1 per square foot for do-it-yourself units and $2 to $5 per square foot for high-efficiency particulate air filters.
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Kuroita T, Yoshimura A, Iwamoto R, Ando H, Okabe S, Kitajima M. Quantitative analysis of SARS-CoV-2 RNA in wastewater and evaluation of sampling frequency during the downward period of a COVID-19 wave in Japan. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:166526. [PMID: 37647962 DOI: 10.1016/j.scitotenv.2023.166526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 08/06/2023] [Accepted: 08/22/2023] [Indexed: 09/01/2023]
Abstract
Wastewater-based epidemiology (WBE) is a practical approach for detecting the presence of SARS-CoV-2 infections and assessing the epidemic trend of the coronavirus disease 2019 (COVID-19). The purpose of this study was to evaluate the minimum sampling frequency required to properly identify the COVID-19 trend during the downward epidemic period when using a highly sensitive RNA detection method. WBE was conducted using the Efficient and Practical virus Identification System with ENhanced Sensitivity for Solids (EPISENS-S), a highly sensitive SARS-CoV-2 RNA detection method, at nine neighboring wastewater treatment plants (WWTPs). These WWTPs were in the same prefecture in Japan, and they had different sewer types, sampling methods, and sampling frequencies. The overall detection rate of SARS-CoV-2 RNA was 97.8 % during the entire study period when the geometric means of new COVID-19 cases per 100,000 inhabitants were between 3.3 and 7.7 in each WWTP. The maximum SARS-CoV-2 RNA concentration in wastewater was 2.14 × 104 copies/L, which corresponded to pepper mild mottle virus (PMMoV)-normalized concentrations of 6.54 × 10-3. We evaluated the effect of sampling frequencies on the probability of a significant correlation with the number of newly reported COVID-19 cases by hypothetically reducing the sampling frequency in the same dataset. When the wastewater sampling frequency occurred 5, 3, 2, and 1 times per week, these results exhibited significant correlations of 100 % (5/5), 89 % (8/9), 85 % (23/27), and 48 % (13/27), respectively. To achieve significant correlation with a high probability of over 85 %, a minimum sampling frequency of twice per week is required, even if sampling methods and sewer types are different. WBE using the EPISENS-S method and a sampling frequency of more than twice a week can be used to properly monitor COVID-19 wave epidemic trends, even during downward periods.
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Affiliation(s)
- Tomohiro Kuroita
- AdvanSentinel Inc., 3-1-8, Doshomachi, Chuo-ku, Osaka 541-0045, Japan; Shionogi & Co., Ltd., 3-1-8, Doshomachi, Chuo-ku, Osaka 541-0045, Japan
| | - Akimasa Yoshimura
- Shionogi & Co., Ltd., 3-1-8, Doshomachi, Chuo-ku, Osaka 541-0045, Japan
| | - Ryo Iwamoto
- AdvanSentinel Inc., 3-1-8, Doshomachi, Chuo-ku, Osaka 541-0045, Japan; Shionogi & Co., Ltd., 3-1-8, Doshomachi, Chuo-ku, Osaka 541-0045, Japan
| | - Hiroki Ando
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan
| | - Satoshi Okabe
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan
| | - Masaaki Kitajima
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan.
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