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Malla B, Shrestha S, Sthapit N, Hirai S, Raya S, Rahmani AF, Angga MS, Siri Y, Ruti AA, Haramoto E. Beyond COVID-19: Wastewater-based epidemiology for multipathogen surveillance and normalization strategies. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 946:174419. [PMID: 38960169 DOI: 10.1016/j.scitotenv.2024.174419] [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: 04/27/2024] [Revised: 06/29/2024] [Accepted: 06/29/2024] [Indexed: 07/05/2024]
Abstract
Wastewater-based epidemiology (WBE) is a critical tool for monitoring community health. Although much attention has focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a causative agent of coronavirus disease 2019 (COVID-19), other pathogens also pose significant health risks. This study quantified the presence of SARS-CoV-2, influenza A virus (Inf-A), and noroviruses of genogroups I (NoV-GI) and II (NoV-GII) in wastewater samples collected weekly (n = 170) from July 2023 to February 2024 from five wastewater treatment plants (WWTPs) in Yamanashi Prefecture, Japan, by quantitative PCR. Inf-A RNA exhibited localized prevalence with positive ratios of 59 %-82 % in different WWTPs, suggesting regional outbreaks within specific areas. NoV-GI (94 %, 160/170) and NoV-GII (100 %, 170/170) RNA were highly prevalent, with NoV-GII (6.1 ± 0.8 log10 copies/L) consistently exceeding NoV-GI (5.4 ± 0.7 log10 copies/L) RNA concentrations. SARS-CoV-2 RNA was detected in 100 % of the samples, with mean concentrations of 5.3 ± 0.5 log10 copies/L in WWTP E and 5.8 ± 0.4 log10 copies/L each in other WWTPs. Seasonal variability was evident, with higher concentrations of all pathogenic viruses during winter. Non-normalized and normalized virus concentrations by fecal indicator bacteria (Escherichia coli and total coliforms), an indicator virus (pepper mild mottle virus (PMMoV)), and turbidity revealed significant positive associations with the reported disease cases. Inf-A and NoV-GI + GII RNA concentrations showed strong correlations with influenza and acute gastroenteritis cases, particularly when normalized to E. coli (Spearman's ρ = 0.70-0.81) and total coliforms (ρ = 0.70-0.81), respectively. For SARS-CoV-2, non-normalized concentrations showed a correlation of 0.61, decreasing to 0.31 when normalized to PMMoV, suggesting that PMMoV is unsuitable. Turbidity normalization also yielded suboptimal results. This study underscored the importance of selecting suitable normalization parameters tailored to specific pathogens for accurate disease trend monitoring using WBE, demonstrating its utility beyond COVID-19 surveillance.
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Affiliation(s)
- Bikash Malla
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Sadhana Shrestha
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Niva Sthapit
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Soichiro Hirai
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Sunayana Raya
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Aulia Fajar Rahmani
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Made Sandhyana Angga
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Yadpiroon Siri
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Annisa Andarini Ruti
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan.
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2
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Islam G, Gedge A, Ibrahim R, de Melo T, Lara-Jacobo L, Dlugosz T, Kirkwood AE, Simmons D, Desaulniers JP. The role of catchment population size, data normalization, and chronology of public health interventions on wastewater-based COVID-19 viral trends. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 937:173272. [PMID: 38763190 DOI: 10.1016/j.scitotenv.2024.173272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 04/28/2024] [Accepted: 05/13/2024] [Indexed: 05/21/2024]
Abstract
The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic presented the most challenging global crisis in recent times. A pandemic caused by a novel pathogen such as SARS-CoV-2 necessitated the development of innovative techniques for the monitoring and surveillance of COVID-19 infections within communities. Wastewater surveillance (WWS) is recognized as a non-invasive, cost-effective, and valuable epidemiological tool to monitor the prevalence of COVID-19 infections in communities. Seven municipal wastewater sampling sites representing distinct sewershed communities were selected for the surveillance of the SARS-CoV-2 virus in Durham Region, Ontario, Canada over 8 months from March 2021 to October 2021. Viral RNA fragments of SARS-CoV-2 and the normalization target pepper mild mottle virus (PMMoV) were concentrated from wastewater influent using the PEG/NaCl superspeed centrifugation method and quantified using RT-qPCR. Strong significant correlations (Spearman's rs = 0.749 to 0.862, P < 0.001) were observed between SARS-CoV-2 gene copies/mL of wastewater and clinical cases reported in each delineated sewershed by onset date. Although raw wastewater offered higher correlation coefficients with clinical cases by onset date compared to PMMoV normalized data, only one site had a statistically significantly higher Spearman's correlation coefficient value for raw data than normalized data. Implementation of community stay-at-home orders and vaccinations over the course of the study period in 2021 were found to strongly correspond to decreasing SARS-CoV-2 wastewater trends in the wastewater treatment plants and upstream pumping stations.
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Affiliation(s)
- Golam Islam
- Faculty of Science, Ontario Tech University, 2000 Simcoe St N, Oshawa, ON L1G 0C5, Canada.
| | - Ashley Gedge
- Faculty of Science, Ontario Tech University, 2000 Simcoe St N, Oshawa, ON L1G 0C5, Canada
| | - Reeta Ibrahim
- Faculty of Science, Ontario Tech University, 2000 Simcoe St N, Oshawa, ON L1G 0C5, Canada
| | - Tomas de Melo
- Faculty of Science, Ontario Tech University, 2000 Simcoe St N, Oshawa, ON L1G 0C5, Canada
| | - Linda Lara-Jacobo
- Faculty of Science, Ontario Tech University, 2000 Simcoe St N, Oshawa, ON L1G 0C5, Canada
| | - Thomas Dlugosz
- Faculty of Science, Ontario Tech University, 2000 Simcoe St N, Oshawa, ON L1G 0C5, Canada
| | - Andrea E Kirkwood
- Faculty of Science, Ontario Tech University, 2000 Simcoe St N, Oshawa, ON L1G 0C5, Canada
| | - Denina Simmons
- Faculty of Science, Ontario Tech University, 2000 Simcoe St N, Oshawa, ON L1G 0C5, Canada
| | - Jean-Paul Desaulniers
- Faculty of Science, Ontario Tech University, 2000 Simcoe St N, Oshawa, ON L1G 0C5, Canada
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3
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Li Y, Ash K, Alamilla I, Joyner D, Williams DE, McKay PJ, Green B, DeBlander S, North C, Kara-Murdoch F, Swift C, Hazen TC. COVID-19 trends at the University of Tennessee: predictive insights from raw sewage SARS-CoV-2 detection and evaluation and PMMoV as an indicator for human waste. Front Microbiol 2024; 15:1379194. [PMID: 38605711 PMCID: PMC11007199 DOI: 10.3389/fmicb.2024.1379194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 03/19/2024] [Indexed: 04/13/2024] Open
Abstract
Wastewater-based epidemiology (WBE) has become a valuable tool for monitoring the prevalence of SARS-CoV-2 on university campuses. However, concerns about effectiveness of raw sewage as a COVID-19 early warning system still exist, and it's not clear how useful normalization by simultaneous comparison of Pepper Mild Mottle Virus (PMMoV) is in addressing variations resulting from fecal discharge dilution. This study aims to contribute insights into these aspects by conducting an academic-year field trial at the student residences on the University of Tennessee, Knoxville campus, raw sewage. This was done to investigate the correlations between SARS-CoV-2 RNA load, both with and without PMMoV normalization, and various parameters, including active COVID-19 cases, self-isolations, and their combination among all student residents. Significant positive correlations between SARS-CoV-2 RNA load a week prior, during the monitoring week, and the subsequent week with active cases. Despite these correlations, normalization by PMMoV does not enhance these associations. These findings suggest the potential utility of SARS-CoV-2 RNA load as an early warning indicator and provide valuable insights into the application and limitations of WBE for COVID-19 surveillance specifically within the context of raw sewage on university campuses.
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Affiliation(s)
- Ye Li
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
| | - Kurt Ash
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | | | - Dominique Joyner
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
| | - Daniel Edward Williams
- Center for Environmental Biotechnology, University of Tennessee, Knoxville, TN, United States
| | - Peter J. McKay
- Battelle Memorial Institute, Columbus, OH, United States
| | - Brianna Green
- Department of Microbiology, University of Tennessee, Knoxville, TN, United States
| | - Sydney DeBlander
- College of Natural Science, Michigan State University, East Lansing, MI, United States
| | - Carman North
- Student Health Center, University of Tennessee, Knoxville, TN, United States
| | - Fadime Kara-Murdoch
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
- Battelle Memorial Institute, Columbus, OH, United States
- Center for Environmental Biotechnology, University of Tennessee, Knoxville, TN, United States
| | - Cynthia Swift
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
- Center for Environmental Biotechnology, University of Tennessee, Knoxville, TN, United States
| | - Terry C. Hazen
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
- Department of Microbiology, University of Tennessee, Knoxville, TN, United States
- Department of Earth and Planetary Sciences, University of Tennessee, Knoxville, TN, United States
- Institute for a Secure and Sustainable Environment, University of Tennessee, Knoxville, TN, United States
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4
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Chen C, Kaur G, Adiga A, Espinoza B, Venkatramanan S, Warren A, Lewis B, Crow J, Singh R, Lorentz A, Toney D, Marathe M. Wastewater-based Epidemiology for COVID-19 Surveillance: A Survey. ARXIV 2024:arXiv:2403.15291v1. [PMID: 38562450 PMCID: PMC10984000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology (WBE) for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding WBE for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.
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Affiliation(s)
- Chen Chen
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Gursharn Kaur
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Aniruddha Adiga
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Baltazar Espinoza
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Srinivasan Venkatramanan
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Andrew Warren
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Bryan Lewis
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Justin Crow
- Virginia Department of Health, Richmond, 23219, United States
| | - Rekha Singh
- Virginia Department of Health, Richmond, 23219, United States
| | - Alexandra Lorentz
- Division of Consolidated Laboratory Services, Department of General Services, Richmond, 23219, United States
| | - Denise Toney
- Division of Consolidated Laboratory Services, Department of General Services, Richmond, 23219, United States
| | - Madhav Marathe
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
- Department of Computer Science, University of Virginia, Charlottesville, 22904, United States
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5
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Parkins MD, Lee BE, Acosta N, Bautista M, Hubert CRJ, Hrudey SE, Frankowski K, Pang XL. Wastewater-based surveillance as a tool for public health action: SARS-CoV-2 and beyond. Clin Microbiol Rev 2024; 37:e0010322. [PMID: 38095438 PMCID: PMC10938902 DOI: 10.1128/cmr.00103-22] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2024] Open
Abstract
Wastewater-based surveillance (WBS) has undergone dramatic advancement in the context of the coronavirus disease 2019 (COVID-19) pandemic. The power and potential of this platform technology were rapidly realized when it became evident that not only did WBS-measured SARS-CoV-2 RNA correlate strongly with COVID-19 clinical disease within monitored populations but also, in fact, it functioned as a leading indicator. Teams from across the globe rapidly innovated novel approaches by which wastewater could be collected from diverse sewersheds ranging from wastewater treatment plants (enabling community-level surveillance) to more granular locations including individual neighborhoods and high-risk buildings such as long-term care facilities (LTCF). Efficient processes enabled SARS-CoV-2 RNA extraction and concentration from the highly dilute wastewater matrix. Molecular and genomic tools to identify, quantify, and characterize SARS-CoV-2 and its various variants were adapted from clinical programs and applied to these mixed environmental systems. Novel data-sharing tools allowed this information to be mobilized and made immediately available to public health and government decision-makers and even the public, enabling evidence-informed decision-making based on local disease dynamics. WBS has since been recognized as a tool of transformative potential, providing near-real-time cost-effective, objective, comprehensive, and inclusive data on the changing prevalence of measured analytes across space and time in populations. However, as a consequence of rapid innovation from hundreds of teams simultaneously, tremendous heterogeneity currently exists in the SARS-CoV-2 WBS literature. This manuscript provides a state-of-the-art review of WBS as established with SARS-CoV-2 and details the current work underway expanding its scope to other infectious disease targets.
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Affiliation(s)
- Michael D. Parkins
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- O’Brien Institute of Public Health, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Bonita E. Lee
- Department of Pediatrics, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Nicole Acosta
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Maria Bautista
- Department of Biological Sciences, Faculty of Science, University of Calgary, Calgary, Alberta, Canada
| | - Casey R. J. Hubert
- Department of Biological Sciences, Faculty of Science, University of Calgary, Calgary, Alberta, Canada
| | - Steve E. Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Kevin Frankowski
- Advancing Canadian Water Assets, University of Calgary, Calgary, Alberta, Canada
| | - Xiao-Li Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
- Provincial Health Laboratory, Alberta Health Services, Calgary, Alberta, Canada
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6
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Rezaeitavabe F, Rezaie M, Modayil M, Pham T, Ice G, Riefler G, Coschigano KT. Beyond linear regression: Modeling COVID-19 clinical cases with wastewater surveillance of SARS-CoV-2 for the city of Athens and Ohio University campus. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169028. [PMID: 38061656 DOI: 10.1016/j.scitotenv.2023.169028] [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: 05/05/2023] [Revised: 11/20/2023] [Accepted: 11/29/2023] [Indexed: 01/18/2024]
Abstract
Wastewater-based surveillance has emerged as a detection tool for population-wide infectious diseases, including coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infected individuals shed the virus, which can be detected in wastewater using molecular techniques such as reverse transcription-digital polymerase chain reaction (RT-dPCR). This study examined the association between the number of clinical cases and the concentration of SARS-CoV-2 in wastewater beyond linear regression and for various normalizations of viral loads. Viral loads were measured in a total of 446 wastewater samples during the period from August 2021 to April 2022. These samples were collected from nine different locations, with 220 samples taken from four specific sites within the city of Athens and 226 samples from five sites within Ohio University. The correlation between COVID-19 cases and wastewater viral concentrations, which was estimated using the Pearson correlation coefficient, was statistically significant and ranged from 0.6 to 0.9. In addition, time-lagged cross correlation was applied to identify the lag time between clinical and wastewater data, estimated 4 to 7 days. While we also explored the effect on the correlation coefficients of various normalizations of viral loads accounting for procedural loss or amount of fecal material and of estimated lag times, these alternative specifications did not change our substantive conclusions. Additionally, several linear and non-linear regression models were applied to predict the COVID-19 cases given wastewater data as input. The non-linear approach was found to yield the highest R-squared and Pearson correlation and lowest Mean Absolute Error values between the predicted and actual number of COVID-19 cases for both aggregated OHIO Campus and city data. Our results provide support for previous studies on correlation and time lag and new evidence that non-linear models, approximated with artificial neural networks, should be implemented for WBS of contagious diseases.
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Affiliation(s)
- Fatemeh Rezaeitavabe
- Ohio University, Russ College of Engineering, Department of Civil and Environmental Engineering, Athens, OH 45701, USA
| | - Mehdi Rezaie
- Kansas State University, Department of Physics, Manhattan, KS 66506, USA
| | - Maria Modayil
- Ohio University, Division of Diversity and Inclusion, Athens, OH 45701, USA; Ohio University, College of Health Sciences and Professions, Department of Interdisciplinary Health Studies, Athens, OH 45701, USA
| | - Tuyen Pham
- Ohio University, Voinovich School of Leadership and Public Service, Athens, OH 45701, USA
| | - Gillian Ice
- Ohio University, College of Health Sciences and Professions, Department of Interdisciplinary Health Studies, Athens, OH 45701, USA; Ohio University, Heritage College of Osteopathic Medicine, Department of Social Medicine, Athens, OH 45701, USA
| | - Guy Riefler
- Ohio University, Russ College of Engineering, Department of Civil and Environmental Engineering, Athens, OH 45701, USA
| | - Karen T Coschigano
- Ohio University, Heritage College of Osteopathic Medicine, Department of Biomedical Sciences, Athens, OH 45701, USA.
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Farkas K, Kevill JL, Adwan L, Garcia-Delgado A, Dzay R, Grimsley JMS, Lambert-Slosarska K, Wade MJ, Williams RC, Martin J, Drakesmith M, Song J, McClure V, Jones DL. Near-source passive sampling for monitoring viral outbreaks within a university residential setting. Epidemiol Infect 2024; 152:e31. [PMID: 38329110 PMCID: PMC10894896 DOI: 10.1017/s0950268824000190] [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: 08/10/2023] [Revised: 01/18/2024] [Accepted: 01/24/2024] [Indexed: 02/09/2024] Open
Abstract
Wastewater-based epidemiology (WBE) has proven to be a powerful tool for the population-level monitoring of pathogens, particularly severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). For assessment, several wastewater sampling regimes and methods of viral concentration have been investigated, mainly targeting SARS-CoV-2. However, the use of passive samplers in near-source environments for a range of viruses in wastewater is still under-investigated. To address this, near-source passive samples were taken at four locations targeting student hall of residence. These were chosen as an exemplar due to their high population density and perceived risk of disease transmission. Viruses investigated were SARS-CoV-2 and its variants of concern (VOCs), influenza viruses, and enteroviruses. Sampling was conducted either in the morning, where passive samplers were in place overnight (17 h) and during the day, with exposure of 7 h. We demonstrated the usefulness of near-source passive sampling for the detection of VOCs using quantitative polymerase chain reaction (qPCR) and next-generation sequencing (NGS). Furthermore, several outbreaks of influenza A and sporadic outbreaks of enteroviruses (some associated with enterovirus D68 and coxsackieviruses) were identified among the resident student population, providing evidence of the usefulness of near-source, in-sewer sampling for monitoring the health of high population density communities.
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Affiliation(s)
- Kata Farkas
- School of Environmental and Natural Sciences, Bangor University, Bangor, UK
| | - Jessica L. Kevill
- School of Environmental and Natural Sciences, Bangor University, Bangor, UK
| | - Latifah Adwan
- School of Environmental and Natural Sciences, Bangor University, Bangor, UK
| | | | - Rande Dzay
- School of Environmental and Natural Sciences, Bangor University, Bangor, UK
| | - Jasmine M. S. Grimsley
- Data Analytics & Surveillance Group, UK Health Security Agency, London, UK
- The London Data Company, London, UK
| | | | - Matthew J. Wade
- Data Analytics & Surveillance Group, UK Health Security Agency, London, UK
- School of Engineering, Newcastle University, Newcastle-upon-Tyne, UK
| | - Rachel C. Williams
- School of Environmental and Natural Sciences, Bangor University, Bangor, UK
| | - Javier Martin
- Division of Vaccines, Medicines and Healthcare Products Regulatory Agency, Hertfordshire, UK
| | - Mark Drakesmith
- Communicable Disease Surveillance Centre, Public Health Wales, Cardiff, UK
| | - Jiao Song
- Communicable Disease Surveillance Centre, Public Health Wales, Cardiff, UK
| | - Victoria McClure
- Communicable Disease Surveillance Centre, Public Health Wales, Cardiff, UK
| | - Davey L. Jones
- School of Environmental and Natural Sciences, Bangor University, Bangor, UK
- Food Futures Institute, Murdoch University, Murdoch, WA, Australia
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8
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Marin-Ramirez A, Mahoney T, Smith T, Holm RH. Predicting wastewater treatment plant influent in mixed, separate, and combined sewers using nearby surface water discharge for better wastewater-based epidemiology sampling design. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167375. [PMID: 37774884 DOI: 10.1016/j.scitotenv.2023.167375] [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: 07/07/2023] [Revised: 08/28/2023] [Accepted: 09/24/2023] [Indexed: 10/01/2023]
Abstract
For wastewater sample collection approaches supporting public health applications, few high hydrologic activity normalizing guidelines currently consider readily available environmental flow data that may earlier capture information regarding periods of influent mixing and dilution of wastewater with groundwater and runoff. This study aimed to identify wastewater sampling rules for high hydrological activity events, allowing for an earlier decision point in the control of dilution before sample collection. We defined the sampling rules via data-driven models (Random Forest and linear regression) using environmental data (i.e., wastewater treatment facility influent rates, nearby stream discharge flow, and precipitation). These models were applied to five treatment plants in Jefferson County, Kentucky (USA) in mixed, separate, and combined sewers with different population sizes. We proposed cutoffs of 10 %, 25 %, and 50 % flow conditions for orientation towards public health samples. The results showed a strong nonlinear relationship between nearby stream discharge and treatment facility flow rates, which was used to infer the hydrological conditions that produce high volumes of diluted wastewater in the sewer system. Accumulated Local Effects and SHapley Additive exPlanations aided in deciphering the relationship between the predictors and response variables of the Random Forest models. The influent rate to the treatment plant from the previous day and two USGS stream gages were needed to adequately predict the degree of infiltration and inflow mixing on a given day. Surface water discharge data can be used to provide an earlier workflow decision point during wet weather periods to improve understanding of flow conditions for wastewater-based epidemiological studies to inform laboratory analysis and data interpretation. Not only total flow, but also the specific proportions of infiltration and inflow to wastewater volume in influent should be considered when analyzing data for normalization purposes, and our method provides a starting point for doing so rapidly and at low cost.
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Affiliation(s)
- Arlex Marin-Ramirez
- Department of Civil and Environmental Engineering, J. B. Speed School of Engineering, University of Louisville, 132 E. Pkwy., Louisville, KY 40202, United States
| | - Tyler Mahoney
- Department of Civil and Environmental Engineering, J. B. Speed School of Engineering, University of Louisville, 132 E. Pkwy., Louisville, KY 40202, United States
| | - Ted Smith
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, 302 E. Muhammad Ali Blvd., Louisville, KY 40202, United States
| | - Rochelle H Holm
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, 302 E. Muhammad Ali Blvd., Louisville, KY 40202, United States.
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9
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Baz Lomba JA, Pires J, Myrmel M, Arnø JK, Madslien EH, Langlete P, Amato E, Hyllestad S. Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic. JOURNAL OF WATER AND HEALTH 2024; 22:197-234. [PMID: 38295081 PMCID: wh_2023_279 DOI: 10.2166/wh.2023.279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.
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Affiliation(s)
- Jose Antonio Baz Lomba
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway E-mail:
| | - João Pires
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway; ECDC fellowship Programme, Public Health Microbiology path (EUPHEM), European Centre for Disease Prevention and Control (ECDC), Solna, Sweden
| | - Mette Myrmel
- Faculty of Veterinary Medicine, Virology Unit, Norwegian University of Life Science (NMBU), Oslo, Norway
| | - Jorunn Karterud Arnø
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Elisabeth Henie Madslien
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Petter Langlete
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Ettore Amato
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Susanne Hyllestad
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
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10
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Wiesner-Friedman C, Brinkman NE, Wheaton E, Nagarkar M, Hart C, Keely SP, Varughese E, Garland J, Klaver P, Turner C, Barton J, Serre M, Jahne M. Characterizing Spatial Information Loss for Wastewater Surveillance Using crAssphage: Effect of Decay, Temperature, and Population Mobility. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:20802-20812. [PMID: 38015885 DOI: 10.1021/acs.est.3c05587] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2023]
Abstract
Populations contribute information about their health status to wastewater. Characterizing how that information degrades in transit to wastewater sampling locations (e.g., wastewater treatment plants and pumping stations) is critical to interpret wastewater responses. In this work, we statistically estimate the loss of information about fecal contributions to wastewater from spatially distributed populations at the census block group resolution. This was accomplished with a hydrologically and hydraulically influenced spatial statistical approach applied to crAssphage (Carjivirus communis) load measured from the influent of four wastewater treatment plants in Hamilton County, Ohio. We find that we would expect to observe a 90% loss of information about fecal contributions from a given census block group over a travel time of 10.3 h. This work demonstrates that a challenge to interpreting wastewater responses (e.g., during wastewater surveillance) is distinguishing between a distal but large cluster of contributions and a near but small contribution. This work demonstrates new modeling approaches to improve measurement interpretation depending on sewer network and wastewater characteristics (e.g., geospatial layout, temperature variability, population distribution, and mobility). This modeling can be integrated into standard wastewater surveillance methods and help to optimize sewer sampling locations to ensure that different populations (e.g., vulnerable and susceptible) are appropriately represented.
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Affiliation(s)
- Corinne Wiesner-Friedman
- Oak Ridge Institute for Science and Education, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States
| | - Nichole E Brinkman
- Office of Research and Development, U.S. Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States
| | - Emily Wheaton
- Office of Research and Development, U.S. Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States
| | - Maitreyi Nagarkar
- Office of Research and Development, U.S. Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States
| | - Chloe Hart
- Office of Research and Development, U.S. Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States
| | - Scott P Keely
- Office of Research and Development, U.S. Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States
| | - Eunice Varughese
- Office of Research and Development, U.S. Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States
| | - Jay Garland
- Office of Research and Development, U.S. Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States
| | - Peter Klaver
- LimnoTech, 501 Avis Drive, Ann Arbor, Michigan 48108, United States
| | - Carrie Turner
- LimnoTech, 501 Avis Drive, Ann Arbor, Michigan 48108, United States
| | - John Barton
- Metropolitan Sewer District of Greater Cincinnati, 1081 Woodrow Street, Cincinnati, Ohio 45204, United States
| | - Marc Serre
- Gillings School of Global Public Health, Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Michael Jahne
- Office of Research and Development, U.S. Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States
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11
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Barnes KG, Levy JI, Gauld J, Rigby J, Kanjerwa O, Uzzell CB, Chilupsya C, Anscombe C, Tomkins-Tinch C, Mbeti O, Cairns E, Thole H, McSweeney S, Chibwana MG, Ashton PM, Jere KC, Meschke JS, Diggle P, Cornick J, Chilima B, Jambo K, Andersen KG, Kawalazira G, Paterson S, Nyirenda TS, Feasey N. Utilizing river and wastewater as a SARS-CoV-2 surveillance tool in settings with limited formal sewage systems. Nat Commun 2023; 14:7883. [PMID: 38036496 PMCID: PMC10689440 DOI: 10.1038/s41467-023-43047-y] [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: 04/11/2023] [Accepted: 10/30/2023] [Indexed: 12/02/2023] Open
Abstract
The COVID-19 pandemic has profoundly impacted health systems globally and robust surveillance has been critical for pandemic control, however not all countries can currently sustain community pathogen surveillance programs. Wastewater surveillance has proven valuable in high-income settings, but less is known about the utility of water surveillance of pathogens in low-income countries. Here we show how wastewater surveillance of SAR-CoV-2 can be used to identify temporal changes and help determine circulating variants quickly. In Malawi, a country with limited community-based COVID-19 testing capacity, we explore the utility of rivers and wastewater for SARS-CoV-2 surveillance. From May 2020-May 2022, we collect water from up to 112 river or defunct wastewater treatment plant sites, detecting SARS-CoV-2 in 8.3% of samples. Peak SARS-CoV-2 detection in water samples predate peaks in clinical cases. Sequencing of water samples identified the Beta, Delta, and Omicron variants, with Delta and Omicron detected well in advance of detection in patients. Our work highlights how wastewater can be used to detect emerging waves, identify variants of concern, and provide an early warning system in settings with no formal sewage systems.
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Affiliation(s)
- Kayla G Barnes
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi.
- Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Vector Biology and Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, UK.
| | - Joshua I Levy
- Department of Vector Biology and Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, UK
| | - Jillian Gauld
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Jonathan Rigby
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Oscar Kanjerwa
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Christopher B Uzzell
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK
| | - Chisomo Chilupsya
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Catherine Anscombe
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Christopher Tomkins-Tinch
- Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, MA, USA
- Medical Research Council Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Omar Mbeti
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | | | - Herbert Thole
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Shannon McSweeney
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Marah G Chibwana
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Philip M Ashton
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Blantyre District Health Office, Blantyre, Malawi
| | - Khuzwayo C Jere
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Blantyre District Health Office, Blantyre, Malawi
- Department of Clinical Infection, Microbiology and Immunology, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - John Scott Meschke
- NIHR Health Protection Research Unit in Gastrointestinal Infections, University of Liverpool, Liverpool, UK
| | - Peter Diggle
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, USA
| | - Jennifer Cornick
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Blantyre District Health Office, Blantyre, Malawi
| | - Benjamin Chilima
- CHICAS, Lancaster Medical School, Lancaster University, Lancaster, UK
| | - Kondwani Jambo
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
- Public Health Institute of Malawi, Lilongwe, Malawi
| | - Kristian G Andersen
- Department of Vector Biology and Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, UK
- Scripps Research Translational Institute, La Jolla, CA, USA
| | - Gift Kawalazira
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | | | - Tonney S Nyirenda
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Nicholas Feasey
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
- School of Medicine, University of St Andrews, St Andrews, UK
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12
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Williams BB, Newborn A, Karamat A, Zamcho F, Salerno JL, Gillevet PM, Farris D, Wintermeyer SF, Van Aken B. Detection of SARS-CoV-2 RNA in wastewater from dormitory buildings in a university campus: comparison with individual testing results. WATER SCIENCE AND TECHNOLOGY : A JOURNAL OF THE INTERNATIONAL ASSOCIATION ON WATER POLLUTION RESEARCH 2023; 88:2364-2377. [PMID: 37966188 PMCID: wst_2023_348 DOI: 10.2166/wst.2023.348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
Abstract
Wastewater-based epidemiology (WBE) for monitoring COVID-19 has been largely used to detect the spread of the disease at the community level. From February to December 2022, we collected 24-h composite sewage samples from dormitory buildings in George Mason University (Fairfax, Virginia, USA) housing approximately 5,200 resident students. SARS-CoV-2 RNA extraction was achieved using an automated system based on magnetic nanoparticles. Analysis of SARS-CoV-2 RNA was performed using reverse transcription quantitative PCR based on the Centers for Disease Control and Prevention (CDC) N1 and N2 assays. From the 362 samples collected, 86% showed positive detection of SARS-CoV-2 RNA. Wastewater monitoring was able to detect SARS-CoV-2 RNA in 96% of the samples from buildings housing students with COVID-19. Over the period of study, we observed significant correlations between the SARS-CoV-2 concentration (copy number mL-1) in wastewater and the number of positive cases on campus based on individual saliva testing. Although several reports have been published on the wastewater monitoring of COVID-19 in university campuses, our study is one of the very few that provides results that were obtained during the last phase of the pandemic (roughly the year 2022), when the large majority of students were vaccinated and back on campus.
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Affiliation(s)
- Brandi B Williams
- Department of Chemistry & Biochemistry, George Mason University, Fairfax, Virginia, USA E-mail:
| | - Aaron Newborn
- Department of Chemistry & Biochemistry, George Mason University, Fairfax, Virginia, USA
| | - Ayesha Karamat
- Department of Environmental Science and Policy, George Mason University, Fairfax, Virginia, USA
| | - Fanella Zamcho
- Department of Chemistry & Biochemistry, George Mason University, Fairfax, Virginia, USA
| | - Jennifer L Salerno
- Department of Environmental Science and Policy, George Mason University, Fairfax, Virginia, USA
| | | | - David Farris
- Environmental Health and Safety, George Mason University, Fairfax, Virginia, USA
| | | | - Benoit Van Aken
- Department of Chemistry & Biochemistry, George Mason University, Fairfax, Virginia, USA
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13
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Bohrerova Z, Brinkman NE, Chakravarti R, Chattopadhyay S, Faith SA, Garland J, Herrin J, Hull N, Jahne M, Kang DW, Keely SP, Lee J, Lemeshow S, Lenhart J, Lytmer E, Malgave D, Miao L, Minard-Smith A, Mou X, Nagarkar M, Quintero A, Savona FDR, Senko J, Slonczewski JL, Spurbeck RR, Sovic MG, Taylor RT, Weavers LK, Weir M. Ohio Coronavirus Wastewater Monitoring Network: Implementation of Statewide Monitoring for Protecting Public Health. JOURNAL OF PUBLIC HEALTH MANAGEMENT AND PRACTICE 2023; 29:845-853. [PMID: 37738597 PMCID: PMC10539008 DOI: 10.1097/phh.0000000000001783] [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] [Indexed: 09/24/2023]
Abstract
CONTEXT Prior to the COVID-19 pandemic, wastewater influent monitoring for tracking disease burden in sewered communities was not performed in Ohio, and this field was only on the periphery of the state academic research community. PROGRAM Because of the urgency of the pandemic and extensive state-level support for this new technology to detect levels of community infection to aid in public health response, the Ohio Water Resources Center established relationships and support of various stakeholders. This enabled Ohio to develop a statewide wastewater SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) monitoring network in 2 months starting in July 2020. IMPLEMENTATION The current Ohio Coronavirus Wastewater Monitoring Network (OCWMN) monitors more than 70 unique locations twice per week, and publicly available data are updated weekly on the public dashboard. EVALUATION This article describes the process and decisions that were made during network initiation, the network progression, and data applications, which can inform ongoing and future pandemic response and wastewater monitoring. DISCUSSION Overall, the OCWMN established wastewater monitoring infrastructure and provided a useful tool for public health professionals responding to the pandemic.
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Affiliation(s)
- Zuzana Bohrerova
- Ohio Water Resources Center (Drs Bohrerova, Lenhart, and Weavers), Civil, Environmental and Geodetic Engineering (Drs Bohrerova, Hull, Lenhart, and Weavers), Infectious Diseases Institute (Drs Faith and Lee and Ms Savona), Sustainability Institute (Dr Hull), Department of Food Science & Technology (Dr Lee), and Center for Applied Plant Sciences (Dr Sovic), The Ohio State University, Columbus, Ohio; Office of Research and Development, US Environmental Protection Agency, Washington, District of Columbia (Drs Brinkman, Garland, Jahne, Keely, and Nagarkar); Departments of Physiology and Pharmacology (Dr Chakravarti) and Medical Microbiology and Immunology (Drs Chattopadhyay and Taylor), University of Toledo College of Medicine and Life Sciences, Toledo, Ohio; LuminUltra Technologies Inc, Hialeah, Florida (Mr Herrin and Dr Quintero); Department of Civil and Environmental Engineering, University of Toledo, Toledo, Ohio (Dr Kang); Divisions of Environmental Health Sciences (Drs Lee and Weir) and Biostatistics (Drs Lemeshow and Malgave and Ms Miao), The Ohio State University College of Public Health, Columbus, Ohio; Department of Biological Sciences, Bowling Green State University, Bowling Green, Ohio (Ms Lytmer); Health Outcomes and Biotechnology Solutions, Battelle Memorial Institute, Columbus, Ohio (Ms Minard-Smith and Dr Spurbeck); Department of Biological Sciences, Kent State University, Kent, Ohio (Dr Mou); Department of Geosciences and Department of Biology, The University of Akron, Akron, Ohio (Dr Senko); and Department of Biology, Kenyon College, Gambier, Ohio (Dr Slonczewski)
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14
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Dhiyebi HA, Abu Farah J, Ikert H, Srikanthan N, Hayat S, Bragg LM, Qasim A, Payne M, Kaleis L, Paget C, Celmer-Repin D, Folkema A, Drew S, Delatolla R, Giesy JP, Servos MR. Assessment of seasonality and normalization techniques for wastewater-based surveillance in Ontario, Canada. Front Public Health 2023; 11:1186525. [PMID: 37711234 PMCID: PMC10499178 DOI: 10.3389/fpubh.2023.1186525] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 08/04/2023] [Indexed: 09/16/2023] Open
Abstract
Introduction Wastewater-based surveillance is at the forefront of monitoring for community prevalence of COVID-19, however, continued uncertainty exists regarding the use of fecal indicators for normalization of the SARS-CoV-2 virus in wastewater. Using three communities in Ontario, sampled from 2021-2023, the seasonality of a viral fecal indicator (pepper mild mottle virus, PMMoV) and the utility of normalization of data to improve correlations with clinical cases was examined. Methods Wastewater samples from Warden, the Humber Air Management Facility (AMF), and Kitchener were analyzed for SARS-CoV-2, PMMoV, and crAssphage. The seasonality of PMMoV and flow rates were examined and compared by Season-Trend-Loess decomposition analysis. The effects of normalization using PMMoV, crAssphage, and flow rates were analyzed by comparing the correlations to clinical cases by episode date (CBED) during 2021. Results Seasonal analysis demonstrated that PMMoV had similar trends at Humber AMF and Kitchener with peaks in January and April 2022 and low concentrations (troughs) in the summer months. Warden had similar trends but was more sporadic between the peaks and troughs for PMMoV concentrations. Flow demonstrated similar trends but was not correlated to PMMoV concentrations at Humber AMF and was very weak at Kitchener (r = 0.12). Despite the differences among the sewersheds, unnormalized SARS-CoV-2 (raw N1-N2) concentration in wastewater (n = 99-191) was strongly correlated to the CBED in the communities (r = 0.620-0.854) during 2021. Additionally, normalization with PMMoV did not improve the correlations at Warden and significantly reduced the correlations at Humber AMF and Kitchener. Flow normalization (n = 99-191) at Humber AMF and Kitchener and crAssphage normalization (n = 29-57) correlations at all three sites were not significantly different from raw N1-N2 correlations with CBED. Discussion Differences in seasonal trends in viral biomarkers caused by differences in sewershed characteristics (flow, input, etc.) may play a role in determining how effective normalization may be for improving correlations (or not). This study highlights the importance of assessing the influence of viral fecal indicators on normalized SARS-CoV-2 or other viruses of concern. Fecal indicators used to normalize the target of interest may help or hinder establishing trends with clinical outcomes of interest in wastewater-based surveillance and needs to be considered carefully across seasons and sites.
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Affiliation(s)
- Hadi A. Dhiyebi
- Department of Biology, University of Waterloo, Waterloo, ON, Canada
| | - Joud Abu Farah
- Department of Biology, University of Waterloo, Waterloo, ON, Canada
| | - Heather Ikert
- Department of Biology, University of Waterloo, Waterloo, ON, Canada
| | | | - Samina Hayat
- Department of Biology, University of Waterloo, Waterloo, ON, Canada
| | - Leslie M. Bragg
- Department of Biology, University of Waterloo, Waterloo, ON, Canada
| | - Asim Qasim
- Regional Municipality of York, Newmarket, ON, Canada
| | - Mark Payne
- Regional Municipality of York, Newmarket, ON, Canada
| | - Linda Kaleis
- Regional Municipality of York, Newmarket, ON, Canada
| | - Caitlyn Paget
- Regional Municipality of York, Newmarket, ON, Canada
| | | | | | - Stephen Drew
- Regional Municipality of Waterloo, Waterloo, ON, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, ON, Canada
| | - John P. Giesy
- Department of Biomedical Sciences and Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada
- Department of Environmental Science, Baylor University, Waco, TX, United States
| | - Mark R. Servos
- Department of Biology, University of Waterloo, Waterloo, ON, Canada
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15
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Ciannella S, González-Fernández C, Gomez-Pastora J. Recent progress on wastewater-based epidemiology for COVID-19 surveillance: A systematic review of analytical procedures and epidemiological modeling. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 878:162953. [PMID: 36948304 PMCID: PMC10028212 DOI: 10.1016/j.scitotenv.2023.162953] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/13/2023] [Accepted: 03/15/2023] [Indexed: 05/13/2023]
Abstract
On March 11, 2020, the World Health Organization declared the coronavirus disease 2019 (COVID-19), whose causative agent is the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a pandemic. This virus is predominantly transmitted via respiratory droplets and shed via sputum, saliva, urine, and stool. Wastewater-based epidemiology (WBE) has been able to monitor the circulation of viral pathogens in the population. This tool demands both in-lab and computational work to be meaningful for, among other purposes, the prediction of outbreaks. In this context, we present a systematic review that organizes and discusses laboratory procedures for SARS-CoV-2 RNA quantification from a wastewater matrix, along with modeling techniques applied to the development of WBE for COVID-19 surveillance. The goal of this review is to present the current panorama of WBE operational aspects as well as to identify current challenges related to it. Our review was conducted in a reproducible manner by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. We identified a lack of standardization in wastewater analytical procedures. Regardless, the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach was the most reported technique employed to detect and quantify viral RNA in wastewater samples. As a more convenient sample matrix, we suggest the solid portion of wastewater to be considered in future investigations due to its higher viral load compared to the liquid fraction. Regarding the epidemiological modeling, the data-driven approach was consistently used for the prediction of variables associated with outbreaks. Future efforts should also be directed toward the development of rapid, more economical, portable, and accurate detection devices.
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Affiliation(s)
- Stefano Ciannella
- Department of Chemical Engineering, Texas Tech University, Lubbock 79409, TX, USA.
| | - Cristina González-Fernández
- Department of Chemical Engineering, Texas Tech University, Lubbock 79409, TX, USA; Departamento de Ingenierías Química y Biomolecular, Universidad de Cantabria, Avda. Los Castros, s/n, 39005 Santander, Spain.
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16
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Schill R, Nelson KL, Harris-Lovett S, Kantor RS. The dynamic relationship between COVID-19 cases and SARS-CoV-2 wastewater concentrations across time and space: Considerations for model training data sets. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 871:162069. [PMID: 36754324 PMCID: PMC9902279 DOI: 10.1016/j.scitotenv.2023.162069] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 02/01/2023] [Accepted: 02/02/2023] [Indexed: 06/18/2023]
Abstract
During the COVID-19 pandemic, wastewater-based surveillance has been used alongside diagnostic testing to monitor infection rates. With the decline in cases reported to public health departments due to at-home testing, wastewater data may serve as the primary input for epidemiological models, but training these models is not straightforward. We explored factors affecting noise and bias in the ratio between wastewater and case data collected in 26 sewersheds in California from October 2020 to March 2022. The strength of the relationship between wastewater and case data appeared dependent on sampling frequency and population size, but was not increased by wastewater normalization to flow rate or case count normalization to testing rates. Additionally, the lead and lag times between wastewater and case data varied over time and space, and the ratio of log-transformed individual cases to wastewater concentrations changed over time. This ratio decreased between the Epsilon/Alpha and Delta variant surges of COVID-19 and increased during the Omicron BA.1 variant surge, and was also related to the diagnostic testing rate. Based on this analysis, we present a framework of scenarios describing the dynamics of the case to wastewater ratio to aid in data handling decisions for ongoing modeling efforts.
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Affiliation(s)
- Rebecca Schill
- TUM School of Engineering and Design, Technical University of Munich, Germany
| | - Kara L Nelson
- Civil and Environmental Engineering, University of California, Berkeley, CA, USA
| | | | - Rose S Kantor
- Civil and Environmental Engineering, University of California, Berkeley, CA, USA.
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17
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Tang L, Wu J, Liu R, Feng Z, Zhang Y, Zhao Y, Li Y, Yang K. Exploration on wastewater-based epidemiology of SARS-CoV-2: Mimic relative quantification with endogenous biomarkers as internal reference. Heliyon 2023; 9:e15705. [PMID: 37124340 PMCID: PMC10122556 DOI: 10.1016/j.heliyon.2023.e15705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 04/18/2023] [Accepted: 04/20/2023] [Indexed: 05/02/2023] Open
Abstract
Wastewater-based epidemiology has become a powerful surveillance tool for monitoring the pandemic of COVID-19. Although it is promising to quantitatively correlate the SARS-CoV-2 RNA concentration in wastewater with the incidence of community infection, there is still no consensus on whether the viral nucleic acid concentration in sewage should be normalized against the abundance of endogenous biomarkers and which biomarker should be used as a reference for the normalization. Here, several candidate endogenous reference biomarkers for normalization of SARS-CoV-2 signal in municipal sewage were evaluated. The human fecal indicator virus (crAssphage) is a promising candidate of endogenous reference biomarker for data normalization of both DNA and RNA viruses for its intrinsic viral nature and high and stable content in sewage. Without constructing standard curves, the relative quantification of sewage viral nucleic acid against the abundance of the reference biomarker can be used to correlate with community COVID-19 incidence, which was proved via mimic experiments by spiking pseudovirus of different concentrations in sewage samples. Dilution of pseudovirus-seeded wastewater did not affect the relative abundance of viral nucleic acid, demonstrating that relative quantification can overcome the sewage dilution effects caused by the greywater input, precipitation and/or groundwater infiltration. The process of concentration, recovery and detection of the endogenous biomarker was consistent with that of SARS-CoV-2 RNA. Thus, it is necessary to co-quantify the endogenous biomarker because it can be not only an internal reference for data normalization, but also a process control.
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Affiliation(s)
- Langjun Tang
- Department of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Jinyong Wu
- Department of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Rui Liu
- Department of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Zhongxi Feng
- Department of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Yanan Zhang
- Department of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Yingzhe Zhao
- Department of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Yonghong Li
- Department of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Kun Yang
- Department of Pharmaceutical & Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China
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18
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Joung MJ, Mangat CS, Mejia EM, Nagasawa A, Nichani A, Perez-Iratxeta C, Peterson SW, Champredon D. Coupling wastewater-based epidemiological surveillance and modelling of SARS-COV-2/COVID-19: Practical applications at the Public Health Agency of Canada. CANADA COMMUNICABLE DISEASE REPORT = RELEVE DES MALADIES TRANSMISSIBLES AU CANADA 2023; 49:166-174. [PMID: 38404704 PMCID: PMC10890812 DOI: 10.14745/ccdr.v49i05a01] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Wastewater-based surveillance (WBS) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) offers a complementary tool for clinical surveillance to detect and monitor coronavirus disease 2019 (COVID-19). Since both symptomatic and asymptomatic individuals infected with SARS-CoV-2 can shed the virus through the fecal route, WBS has the potential to measure community prevalence of COVID-19 without restrictions from healthcare-seeking behaviours and clinical testing capacity. During the Omicron wave, the limited capacity of clinical testing to identify COVID-19 cases in many jurisdictions highlighted the utility of WBS to estimate disease prevalence and inform public health strategies; however, there is a plethora of in-sewage, environmental and laboratory factors that can influence WBS outcomes. The implementation of WBS, therefore, requires a comprehensive framework to outline a pipeline that accounts for these complex and nuanced factors. This article reviews the framework of the national WBS conducted at the Public Health Agency of Canada to present WBS methods used in Canada to track and monitor SARS-CoV-2. In particular, we focus on five Canadian cities-Vancouver, Edmonton, Toronto, Montréal and Halifax-whose wastewater signals are analyzed by a mathematical model to provide case forecasts and reproduction number estimates. The goal of this work is to share our insights on approaches to implement WBS. Importantly, the national WBS system has implications beyond COVID-19, as a similar framework can be applied to monitor other infectious disease pathogens or antimicrobial resistance in the community.
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Affiliation(s)
- Meong Jin Joung
- National Microbiology Laboratory, Public Health Risk Sciences Division, Public Health Agency of Canada, Guelph, ON
- Dalla Lana School of Public Health, University of Toronto. Toronto, ON
| | - Chand S Mangat
- National Microbiology Laboratory, Wastewater Surveillance Unit, Public Health Agency of Canada, Winnipeg, MB
| | - Edgard M Mejia
- National Microbiology Laboratory, Wastewater Surveillance Unit, Public Health Agency of Canada, Winnipeg, MB
| | - Audra Nagasawa
- Statistics Canada, Centre for Direct Health Measures, Ottawa, ON
| | - Anil Nichani
- National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON
| | | | - Shelley W Peterson
- National Microbiology Laboratory, Wastewater Surveillance Unit, Public Health Agency of Canada, Winnipeg, MB
| | - David Champredon
- National Microbiology Laboratory, Public Health Risk Sciences Division, Public Health Agency of Canada, Guelph, ON
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19
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Rainey AL, Liang S, Bisesi JH, Sabo-Attwood T, Maurelli AT. A multistate assessment of population normalization factors for wastewater-based epidemiology of COVID-19. PLoS One 2023; 18:e0284370. [PMID: 37043469 PMCID: PMC10096268 DOI: 10.1371/journal.pone.0284370] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 03/29/2023] [Indexed: 04/13/2023] Open
Abstract
Wastewater-based epidemiology (WBE) has become a valuable tool for monitoring SARS-CoV-2 infection trends throughout the COVID-19 pandemic. Population biomarkers that measure the relative human fecal contribution to normalize SARS-CoV-2 wastewater concentrations are needed for improved analysis and interpretation of community infection trends. The Centers for Disease Control and Prevention National Wastewater Surveillance System (CDC NWSS) recommends using the wastewater flow rate or human fecal indicators as population normalization factors. However, there is no consensus on which normalization factor performs best. In this study, we provided the first multistate assessment of the effects of flow rate and human fecal indicators (crAssphage, F+ Coliphage, and PMMoV) on the correlation of SARS-CoV-2 wastewater concentrations and COVID-19 cases using the CDC NWSS dataset of 182 communities across six U.S. states. Flow normalized SARS-CoV-2 wastewater concentrations produced the strongest correlation with COVID-19 cases. The correlation from the three human fecal indicators were significantly lower than flow rate. Additionally, using reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) significantly improved correlation values over samples that were analyzed with real-time reverse transcription quantitative polymerase chain reaction (rRT-qPCR). Our assessment shows that utilizing flow normalization with RT-ddPCR generate the strongest correlation between SARS-CoV-2 wastewater concentrations and COVID-19 cases.
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Affiliation(s)
- Andrew L. Rainey
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Song Liang
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Joseph H. Bisesi
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
- Center for Environmental and Human Toxicology, University of Florida, Gainesville, Florida, United States of America
| | - Tara Sabo-Attwood
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
- Center for Environmental and Human Toxicology, University of Florida, Gainesville, Florida, United States of America
| | - Anthony T. Maurelli
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
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20
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Jarvie MM, Reed-Lukomski M, Southwell B, Wright D, Nguyen TNT. Monitoring of COVID-19 in wastewater across the Eastern Upper Peninsula of Michigan. ENVIRONMENTAL ADVANCES 2023; 11:100326. [PMID: 36471702 PMCID: PMC9714184 DOI: 10.1016/j.envadv.2022.100326] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 11/01/2022] [Accepted: 11/29/2022] [Indexed: 05/12/2023]
Abstract
Wastewater-based epidemiology is being used as a tool to monitor the spread of COVID-19 and provide an early warning for the presence or increase of clinical cases in a community. The majority of wastewater-based epidemiology for COVID-19 tracking has been utilized in sewersheds that service populations in the tens-to-hundreds of thousands. Few studies have been conducted to assess the usefulness of wastewater in predicting COVID-19 clinical cases specifically in rural areas. This study collected samples from 16 locations across the Eastern Upper Peninsula of Michigan from June to December 2021. Sampling locations included 12 rural municipalities, a Tribal housing community and casino, a public university, three municipalities that also contained a prison, and a small island with heavy tourist traffic. Samples were analyzed for SARS-CoV-2 N1, N2, and variant gene copies using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR). Wastewater N1 and N2 gene copies and clinical case counts were correlated to determine if wastewater results were predictive of clinical cases. Significant correlation between N1 and N2 gene copies and clinical cases was found for all sites (⍴= 0.89 to 0.48). N1 and N2 wastewater results were predictive of clinical case trends within 0-7 days. The Delta variant was detected in the Pickford and St. Ignace samples more than 12-days prior to the first reported Delta clinical cases in their respective counties. Locations with low correlation could be attributed to their high rates of tourism. This is further supported by the high correlation seen in the public university, which is a closed population. Long-term wastewater monitoring over a large, rural geographic area is useful for informing the public of potential outbreaks in the community regardless of asymptomatic cases and access to clinical testing.
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Affiliation(s)
- Michelle M Jarvie
- School of Science and Medicine, Lake Superior State University, 650 W. Easterday Ave., Sault Ste, Marie, MI 49783, USA
| | - Moriah Reed-Lukomski
- School of Science and Medicine, Lake Superior State University, 650 W. Easterday Ave., Sault Ste, Marie, MI 49783, USA
| | - Benjamin Southwell
- School of Science and Medicine, Lake Superior State University, 650 W. Easterday Ave., Sault Ste, Marie, MI 49783, USA
| | - Derek Wright
- School of Natural Resources and Environment, Lake Superior State University, 650 W. Easterday Ave., Sault Ste. Marie, MI 49783, USA
| | - Thu N T Nguyen
- School of Science and Medicine, Lake Superior State University, 650 W. Easterday Ave., Sault Ste, Marie, MI 49783, USA
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21
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Saingam P, Li B, Nguyen Quoc B, Jain T, Bryan A, Winkler MKH. Wastewater surveillance of SARS-CoV-2 at intra-city level demonstrated high resolution in tracking COVID-19 and calibration using chemical indicators. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 866:161467. [PMID: 36626989 PMCID: PMC9825140 DOI: 10.1016/j.scitotenv.2023.161467] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 12/17/2022] [Accepted: 01/04/2023] [Indexed: 05/12/2023]
Abstract
Wastewater-based epidemiology has proven to be a supportive tool to better comprehend the dynamics of the COVID-19 pandemic. As the disease moves into endemic stage, the surveillance at wastewater sub-catchments such as pump station and manholes is providing a novel mechanism to examine the reemergence and to take measures that can prevent the spread. However, there is still a lack of understanding when it comes to wastewater-based epidemiology implementation at the smaller intra-city level for better granularity in data, and dilution effect of rain precipitation at pump stations. For this study, grab samples were collected from six areas of Seattle between March-October 2021. These sampling sites comprised five manholes and one pump station with population ranging from 2580 to 39,502 per manhole/pump station. The wastewater samples were analyzed for SARS-CoV-2 RNA concentrations, and we also obtained the daily COVID-19 cases (from individual clinical testing) for each corresponding sewershed, which ranged from 1 to 12 and the daily incidence varied between 3 and 64 per 100,000 of population. Rain precipitation lowered viral RNA levels and sensitivity of viral detection but wastewater total ammonia (NH4+-N) and phosphate (PO43--P) were shown as potential chemical indicators to calibrate/level out the dilution effect. These chemicals showed the potential in improving the wastewater surveillance capacity of COVID-19.
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Affiliation(s)
- Prakit Saingam
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA.
| | - Bo Li
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA
| | - Bao Nguyen Quoc
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA
| | - Tanisha Jain
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA
| | - Andrew Bryan
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Mari K H Winkler
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA.
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22
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Davis A, Keely SP, Brinkman NE, Bohrer Z, Ai Y, Mou X, Chattopadhyay S, Hershey O, Senko J, Hull N, Lytmer E, Quintero A, Lee J. Evaluation of intra- and inter-lab variability in quantifying SARS-CoV-2 in a state-wide wastewater monitoring network. ENVIRONMENTAL SCIENCE : WATER RESEARCH & TECHNOLOGY 2023; 9:1053-1068. [PMID: 37701755 PMCID: PMC10494892 DOI: 10.1039/d2ew00737a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/14/2023]
Abstract
In December 2019, SARS-CoV-2, the virus that causes coronavirus disease 2019, was first reported and subsequently triggered a global pandemic. Wastewater monitoring, a strategy for quantifying viral gene concentrations from wastewater influents within a community, has served as an early warning and management tool for the spread of SARS-CoV-2 in a community. Ohio built a collaborative statewide wastewater monitoring network that is supported by eight labs (university, government, and commercial laboratories) with unique sample processing workflows. Consequently, we sought to characterize the variability in wastewater monitoring results for network labs. Across seven trials between October 2020 and November 2021, eight participating labs successfully quantified two SARS-CoV-2 RNA targets and human fecal indicator virus targets in wastewater sample aliquots with reproducible results, although recovery efficiencies of spiked surrogates ranged from 3 to 75%. When SARS-CoV-2 gene fragment concentrations were adjusted for recovery efficiency and flow, the proportion of variance between laboratories was minimized, serving as the best model to account for between-lab variance. Another adjustment factor (alone and in different combinations with the above factors) considered to account for sample and measurement variability includes fecal marker normalization. Genetic quantification variability can be attributed to many factors, including the methods, individual samples, and water quality parameters. In addition, statistically significant correlations were observed between SARS-CoV-2 RNA and COVID-19 case numbers, supporting the notion that wastewater surveillance continues to serve as an effective monitoring tool. This study serves as a real-time example of multi-laboratory collaboration for public health preparedness for infectious diseases.
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Affiliation(s)
- Angela Davis
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, 1841 Neil Avenue, Columbus, OH 43210, USA
| | - Scott P Keely
- United States Environmental Protection Agency, Office of Research and Development, USA
| | - Nichole E Brinkman
- United States Environmental Protection Agency, Office of Research and Development, USA
| | | | - Yuehan Ai
- Department of Food Science & Technology, The Ohio State University, USA
| | - Xiaozhen Mou
- Department of Biological Sciences, Kent State University, USA
| | - Saurabh Chattopadhyay
- Department of Medical Microbiology and Immunology, College of Medicine and Life Sciences, Department of Biology and Department of Geosciences, University of Toledo, USA
| | - Olivia Hershey
- Department of Geosciences and Biology, University of Akron, USA
| | - John Senko
- Department of Geosciences and Biology, University of Akron, USA
| | - Natalie Hull
- Department of Civil, Environmental and Geodetic Engineering and Sustainability Institute, The Ohio State University, USA
| | - Eva Lytmer
- Department of Biological Sciences, Bowling Green State University, USA
| | | | - Jiyoung Lee
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, 1841 Neil Avenue, Columbus, OH 43210, USA
- Department of Food Science & Technology, The Ohio State University, USA
- Infectious Diseases Institute, The Ohio State University, USA
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23
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Kisand V, Laas P, Palmik-Das K, Panksep K, Tammert H, Albreht L, Allemann H, Liepkalns L, Vooro K, Ritz C, Hauryliuk V, Tenson T. Prediction of COVID-19 positive cases, a nation-wide SARS-CoV-2 wastewater-based epidemiology study. WATER RESEARCH 2023; 231:119617. [PMID: 36682239 PMCID: PMC9845016 DOI: 10.1016/j.watres.2023.119617] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 01/09/2023] [Accepted: 01/15/2023] [Indexed: 06/17/2023]
Abstract
Taking advantage of Estonia's small size and population, we have employed wastewater-based epidemiology approach to monitor the spread of SARS-CoV-2, releasing weekly nation-wide updates. In this study we report results obtained between August 2020 and December 2021. Weekly 24 h composite samples were collected from wastewater treatment plants of larger towns already covered 65% of the total population that was complemented up to 40 additional grab samples from smaller towns/villages and the specific sites of concern. The N3 gene abundance was quantified by RT-qPCR. The N3 gene copy number (concentration) in wastewater fluctuated in accordance with the SARS-CoV-2 spread within the total population, with N3 abundance starting to increase 1.25 weeks (9 days) (95% CI: [1.10, 1.41]) before a rise in COVID-19 positive cases. Statistical model between the load of virus in wastewater and number of infected people validated with the Alpha variant wave (B.1.1.17) could be used to predict the order of magnitude in incidence numbers in Delta wave (B.1.617.2) in fall 2021. Targeted testing of student dormitories, retirement and nursing homes and prisons resulted in successful early discovery of outbreaks. We put forward a SARS-CoV-2 Wastewater Index (SARS2-WI) indicator of normalized virus load as COVID-19 infection metric to complement the other metrics currently used in disease control and prevention: dynamics of effective reproduction number (Re), 7-day mean of new cases, and a sum of new cases within last 14 days. In conclusion, an efficient surveillance system that combines analysis of composite and grab samples was established in Estonia. There is considerable discussion how the viral load in wastewater correlates with the number of infected people. Here we show that this correlation can be found. Moreover, we confirm that an increased signal in wastewater is observed before the increase in the number of infections. The surveillance system helped to inform public health policy and place direct interventions during the COVID-19 pandemic in Estonia via early warning of epidemic spread in various regions of the country.
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Affiliation(s)
- Veljo Kisand
- Institute of Technology, University of Tartu, Estonia.
| | - Peeter Laas
- Institute of Technology, University of Tartu, Estonia
| | | | | | - Helen Tammert
- Institute of Technology, University of Tartu, Estonia
| | | | - Hille Allemann
- Estonian Environmental Research Centre, Tallinn, Estonia
| | | | - Katri Vooro
- Estonian Environmental Research Centre, Tallinn, Estonia
| | - Christian Ritz
- Department of Population Health and Morbidity, National Institute of Public Health, University of Southern Denmark, Denmark
| | - Vasili Hauryliuk
- Institute of Technology, University of Tartu, Estonia; Department of Experimental Medical Science, Lund University, Sweden
| | - Tanel Tenson
- Institute of Technology, University of Tartu, Estonia.
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24
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Helm B, Geissler M, Mayer R, Schubert S, Oertel R, Dumke R, Dalpke A, El-Armouche A, Renner B, Krebs P. Regional and temporal differences in the relation between SARS-CoV-2 biomarkers in wastewater and estimated infection prevalence - Insights from long-term surveillance. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159358. [PMID: 36240928 PMCID: PMC9554318 DOI: 10.1016/j.scitotenv.2022.159358] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 10/06/2022] [Accepted: 10/07/2022] [Indexed: 06/16/2023]
Abstract
Wastewater-based epidemiology provides a conceptual framework for the evaluation of the prevalence of public health related biomarkers. In the context of the Coronavirus disease-2019, wastewater monitoring emerged as a complementary tool for epidemic management. In this study, we evaluated data from six wastewater treatment plants in the region of Saxony, Germany. The study period lasted from February to December 2021 and covered the third and fourth regional epidemic waves. We collected 1065 daily composite samples and analyzed SARS-CoV-2 RNA concentrations using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Regression models quantify the relation between RNA concentrations and disease prevalence. We demonstrated that the relation is site and time specific. Median loads per diagnosed case differed by a factor of 3-4 among sites during both waves and were on average 45 % higher during the third wave. In most cases, log-log-transformed data achieved better regression performance than non-transformed data and local calibration outperformed global models for all sites. The inclusion of lag/lead time, discharge and detection probability improved model performance in all cases significantly, but the importance of these components was also site and time specific. In all cases, models with lag/lead time and log-log-transformed data obtained satisfactory goodness-of-fit with adjusted coefficients of determination higher than 0.5. Back-estimation of testing efficiency from wastewater data confirmed state-wide prevalence estimation from individual testing statistics, but revealed pronounced differences throughout the epidemic waves and among the different sites.
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Affiliation(s)
- Björn Helm
- Institute of Urban and Industrial Water Management, Technische Universität Dresden, Helmholtzstrasse 10, 01069 Dresden, Germany.
| | - Michael Geissler
- Institute of Medical Microbiology and Virology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Robin Mayer
- Institute of Urban and Industrial Water Management, Technische Universität Dresden, Helmholtzstrasse 10, 01069 Dresden, Germany
| | - Sara Schubert
- Institute of Clinical Pharmacology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany; Institute of Hydrobiology, Technische Universität Dresden, Helmholtzstrasse 10, 01069 Dresden, Germany
| | - Reinhard Oertel
- Institute of Clinical Pharmacology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Roger Dumke
- Institute of Medical Microbiology and Virology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Alexander Dalpke
- Institute of Medical Microbiology and Virology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany; University Heidelberg, Institute of Medical Microbiology and Hygiene, Heidelberg, Germany
| | - Ali El-Armouche
- Institute of Clinical Pharmacology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany; Institute of Pharmacology and Toxicology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Bertold Renner
- Institute of Clinical Pharmacology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Peter Krebs
- Institute of Urban and Industrial Water Management, Technische Universität Dresden, Helmholtzstrasse 10, 01069 Dresden, Germany
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25
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Maal-Bared R, Qiu Y, Li Q, Gao T, Hrudey SE, Bhavanam S, Ruecker NJ, Ellehoj E, Lee BE, Pang X. Does normalization of SARS-CoV-2 concentrations by Pepper Mild Mottle Virus improve correlations and lead time between wastewater surveillance and clinical data in Alberta (Canada): comparing twelve SARS-CoV-2 normalization approaches. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 856:158964. [PMID: 36167131 PMCID: PMC9508694 DOI: 10.1016/j.scitotenv.2022.158964] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/13/2022] [Accepted: 09/19/2022] [Indexed: 05/02/2023]
Abstract
Wastewater-based surveillance (WBS) data normalization is an analyte measurement correction that addresses variations resulting from dilution of fecal discharge by non-sanitary sewage, stormwater or groundwater infiltration. No consensus exists on what WBS normalization parameters result in the strongest correlations and lead time between SARS-CoV-2 WBS data and COVID-19 cases. This study compared flow, population size and biomarker normalization impacts on the correlations and lead times for ten communities in twelve sewersheds in Alberta (Canada) between September 2020 and October 2021 (n = 1024) to determine if normalization by Pepper Mild Mottle Virus (PMMoV) provides any advantages compared to other normalization parameters (e.g., flow, reported and dynamic population sizes, BOD, TSS, NH3, TP). PMMoV concentrations (GC/mL) corresponded with plant influent flows and were highest in the urban centres. SARS-CoV-2 target genes E, N1 and N2 were all negatively associated with wastewater influent pH, while PMMoV was positively associated with temperature. Pooled data analysis showed that normalization increased ρ-values by almost 0.1 and was highest for ammonia, TKN and TP followed by PMMoV. Normalization by other parameters weakened associations. None of the differences were statistically significant. Site-specific correlations showed that normalization of SARS-CoV-2 data by PMMoV only improved correlations significantly in two of the twelve systems; neither were large sewersheds or combined sewer systems. In five systems, normalization by traditional wastewater strength parameters and dynamic population estimates improved correlations. Lead time ranged between 1 and 4 days in both pooled and site-specific comparisons. We recommend that WBS researchers and health departments: a) Investigate WWTP influent properties (e.g., pH) in the WBS planning phase and use at least two parallel approaches for normalization only if shown to provide value; b) Explore normalization by wastewater strength parameters and dynamic population size estimates further; and c) Evaluate purchasing an influent flow meter in small communities to support long-term WBS efforts and WWTP management.
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Affiliation(s)
- Rasha Maal-Bared
- Quality Assurance and Environment, EPCOR Water, Edmonton, Alberta, Canada.
| | - Yuanyuan Qiu
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Qiaozhi Li
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Tiejun Gao
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Steve E Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Sudha Bhavanam
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Norma J Ruecker
- Water Quality Services, City of Calgary, Calgary, Alberta, Canada
| | - Erik Ellehoj
- Ellehoj Redmond Consulting, Edmonton, Alberta, Canada
| | - Bonita E Lee
- Department of Paediatrics, University of Alberta, Edmonton, Alberta, Canada
| | - Xiaoli Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada; Public Health Laboratories (ProvLab), Alberta Precision Laboratories (APL), Edmonton, Alberta, Canada
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26
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Lott MEJ, Norfolk WA, Dailey CA, Foley AM, Melendez-Declet C, Robertson MJ, Rathbun SL, Lipp EK. Direct wastewater extraction as a simple and effective method for SARS-CoV-2 surveillance and COVID-19 community-level monitoring. FEMS MICROBES 2023; 4:xtad004. [PMID: 37333441 PMCID: PMC10117872 DOI: 10.1093/femsmc/xtad004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 11/23/2022] [Accepted: 01/11/2023] [Indexed: 10/22/2023] Open
Abstract
Wastewater surveillance has proven to be an effective tool to monitor the transmission and emergence of infectious agents at a community scale. Workflows for wastewater surveillance generally rely on concentration steps to increase the probability of detection of low-abundance targets, but preconcentration can substantially increase the time and cost of analyses while also introducing additional loss of target during processing. To address some of these issues, we conducted a longitudinal study implementing a simplified workflow for SARS-CoV-2 detection from wastewater, using a direct column-based extraction approach. Composite influent wastewater samples were collected weekly for 1 year between June 2020 and June 2021 in Athens-Clarke County, Georgia, USA. Bypassing any concentration step, low volumes (280 µl) of influent wastewater were extracted using a commercial kit, and immediately analyzed by RT-qPCR for the SARS-CoV-2 N1 and N2 gene targets. SARS-CoV-2 viral RNA was detected in 76% (193/254) of influent samples, and the recovery of the surrogate bovine coronavirus was 42% (IQR: 28%, 59%). N1 and N2 assay positivity, viral concentration, and flow-adjusted daily viral load correlated significantly with per-capita case reports of COVID-19 at the county-level (ρ = 0.69-0.82). To compensate for the method's high limit of detection (approximately 106-107 copies l-1 in wastewater), we extracted multiple small-volume replicates of each wastewater sample. With this approach, we detected as few as five cases of COVID-19 per 100 000 individuals. These results indicate that a direct-extraction-based workflow for SARS-CoV-2 wastewater surveillance can provide informative and actionable results.
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Affiliation(s)
- Megan E J Lott
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - William A Norfolk
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - Cody A Dailey
- Department of Epidemiology and Biostatistics, University of Georgia, 101 Buck Road, Athens, GA 30606, United States
| | - Amelia M Foley
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - Carolina Melendez-Declet
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - Megan J Robertson
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - Stephen L Rathbun
- Department of Epidemiology and Biostatistics, University of Georgia, 101 Buck Road, Athens, GA 30606, United States
| | - Erin K Lipp
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
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27
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Hopkins L, Persse D, Caton K, Ensor K, Schneider R, McCall C, Stadler LB. Citywide wastewater SARS-CoV-2 levels strongly correlated with multiple disease surveillance indicators and outcomes over three COVID-19 waves. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 855:158967. [PMID: 36162580 PMCID: PMC9507781 DOI: 10.1016/j.scitotenv.2022.158967] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
Public health surveillance systems for COVID-19 are multifaceted and include multiple indicators reflective of different aspects of the burden and spread of the disease in a community. With the emergence of wastewater disease surveillance as a powerful tool to track infection dynamics of SARS-CoV-2, there is a need to integrate and validate wastewater information with existing disease surveillance systems and demonstrate how it can be used as a routine surveillance tool. A first step toward integration is showing how it relates to other disease surveillance indicators and outcomes, such as case positivity rates, syndromic surveillance data, and hospital bed use rates. Here, we present an 86-week long surveillance study that covers three major COVID-19 surges. City-wide SARS-CoV-2 RNA viral loads in wastewater were measured across 39 wastewater treatment plants and compared to other disease metrics for the city of Houston, TX. We show that wastewater levels are strongly correlated with positivity rate, syndromic surveillance rates of COVID-19 visits, and COVID-19-related general bed use rates at hospitals. We show that the relative timing of wastewater relative to each indicator shifted across the pandemic, likely due to a multitude of factors including testing availability, health-seeking behavior, and changes in viral variants. Next, we show that individual WWTPs led city-wide changes in SARS-CoV-2 viral loads, indicating a distributed monitoring system could be used to enhance the early-warning capability of a wastewater monitoring system. Finally, we describe how the results were used in real-time to inform public health response and resource allocation.
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Affiliation(s)
- Loren Hopkins
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, United States of America; Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX, United States of America
| | - David Persse
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, United States of America; Department of Medicine and Surgery, Baylor College of Medicine, Houston, TX, United States of America; City of Houston Emergency Medical Services, Houston, TX, United States of America
| | - Kelsey Caton
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, United States of America
| | - Katherine Ensor
- Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX, United States of America
| | - Rebecca Schneider
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, United States of America
| | - Camille McCall
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS-519, Houston, TX, United States of America
| | - Lauren B Stadler
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS-519, Houston, TX, United States of America.
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28
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Li X, Zhang S, Sherchan S, Orive G, Lertxundi U, Haramoto E, Honda R, Kumar M, Arora S, Kitajima M, Jiang G. Correlation between SARS-CoV-2 RNA concentration in wastewater and COVID-19 cases in community: A systematic review and meta-analysis. JOURNAL OF HAZARDOUS MATERIALS 2023; 441:129848. [PMID: 36067562 PMCID: PMC9420035 DOI: 10.1016/j.jhazmat.2022.129848] [Citation(s) in RCA: 35] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 08/22/2022] [Accepted: 08/23/2022] [Indexed: 05/26/2023]
Abstract
Wastewater-based epidemiology (WBE) has been considered as a promising approach for population-wide surveillance of coronavirus disease 2019 (COVID-19). Many studies have successfully quantified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater (CRNA). However, the correlation between the CRNA and the COVID-19 clinically confirmed cases in the corresponding wastewater catchments varies and the impacts of environmental and other factors remain unclear. A systematic review and meta-analysis were conducted to identify the correlation between CRNA and various types of clinically confirmed case numbers, including prevalence and incidence rates. The impacts of environmental factors, WBE sampling design, and epidemiological conditions on the correlation were assessed for the same datasets. The systematic review identified 133 correlation coefficients, ranging from -0.38 to 0.99. The correlation between CRNA and new cases (either daily new, weekly new, or future cases) was stronger than that of active cases and cumulative cases. These correlation coefficients were potentially affected by environmental and epidemiological conditions and WBE sampling design. Larger variations of air temperature and clinical testing coverage, and the increase of catchment size showed strong negative impacts on the correlation between CRNA and COVID-19 case numbers. Interestingly, the sampling technique had negligible impact although increasing the sampling frequency improved the correlation. These findings highlight the importance of viral shedding dynamics, in-sewer decay, WBE sampling design and clinical testing on the accurate back-estimation of COVID-19 case numbers through the WBE approach.
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Affiliation(s)
- Xuan Li
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, Australia; Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Shuxin Zhang
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, Australia
| | - Samendrdra Sherchan
- Department of Environmental Health Sciences, Tulane University, New Orleans, LA 70112, USA
| | - Gorka Orive
- NanoBioCel Group, Laboratory of Pharmaceutics, School of Pharmacy, University of the Basque Country UPV/EHU, Paseo de la Universidad 7, Vitoria-Gasteiz 01006, Spain; Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Vitoria-Gasteiz, Spain
| | - Unax Lertxundi
- Bioaraba Health Research Institute; Osakidetza Basque Health Service, Araba Mental Health Network, Araba Psychiatric Hospital, Pharmacy Service, Vitoria-Gasteiz, Spain
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, Kofu, Japan
| | - Ryo Honda
- Faculty of Geosciences and Civil Engineering, Kanazawa University, Kanazawa, Japan
| | - Manish Kumar
- Sustainability Cluster, School of Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India
| | - Sudipti Arora
- Dr. B. Lal Institute of Biotechnology, Jaipur, India
| | - Masaaki Kitajima
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, Hokkaido, Japan
| | - Guangming Jiang
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, Australia; Illawarra Health and Medical Research Institute (IHMRI), University of Wollongong, Wollongong, Australia.
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29
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D'Aoust PM, Tian X, Towhid ST, Xiao A, Mercier E, Hegazy N, Jia JJ, Wan S, Kabir MP, Fang W, Fuzzen M, Hasing M, Yang MI, Sun J, Plaza-Diaz J, Zhang Z, Cowan A, Eid W, Stephenson S, Servos MR, Wade MJ, MacKenzie AE, Peng H, Edwards EA, Pang XL, Alm EJ, Graber TE, Delatolla R. Wastewater to clinical case (WC) ratio of COVID-19 identifies insufficient clinical testing, onset of new variants of concern and population immunity in urban communities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 853:158547. [PMID: 36067855 PMCID: PMC9444156 DOI: 10.1016/j.scitotenv.2022.158547] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 07/10/2022] [Accepted: 09/01/2022] [Indexed: 05/14/2023]
Abstract
Clinical testing has been the cornerstone of public health monitoring and infection control efforts in communities throughout the COVID-19 pandemic. With the anticipated reduction of clinical testing as the disease moves into an endemic state, SARS-CoV-2 wastewater surveillance (WWS) will have greater value as an important diagnostic tool. An in-depth analysis and understanding of the metrics derived from WWS is required to interpret and utilize WWS-acquired data effectively (McClary-Gutierrez et al., 2021; O'Keeffe, 2021). In this study, the SARS-CoV-2 wastewater signal to clinical cases (WC) ratio was investigated across seven cities in Canada over periods ranging from 8 to 21 months. This work demonstrates that significant increases in the WC ratio occurred when clinical testing eligibility was modified to appointment-only testing, identifying a period of insufficient clinical testing (resulting in a reduction to testing access and a reduction in the number of daily tests) in these communities, despite increases in the wastewater signal. Furthermore, the WC ratio decreased significantly in 6 of the 7 studied locations, serving as a potential signal of the emergence of the Alpha variant of concern (VOC) in a relatively non-immunized community (40-60 % allelic proportion), while a more muted decrease in the WC ratio signaled the emergence of the Delta VOC in a relatively well-immunized community (40-60 % allelic proportion). Finally, a significant decrease in the WC ratio signaled the emergence of the Omicron VOC, likely because of the variant's greater effectiveness at evading immunity, leading to a significant number of new reported clinical cases, even when community immunity was high. The WC ratio, used as an additional monitoring metric, could complement clinical case counts and wastewater signals as individual metrics in its potential ability to identify important epidemiological occurrences, adding value to WWS as a diagnostic technology during the COVID-19 pandemic and likely for future pandemics.
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Affiliation(s)
- Patrick M D'Aoust
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Xin Tian
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | | | - Amy Xiao
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America
| | - Elisabeth Mercier
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Nada Hegazy
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Jian-Jun Jia
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Shen Wan
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Md Pervez Kabir
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Wanting Fang
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Meghan Fuzzen
- Department of Biology, University of Waterloo, Waterloo, Canada
| | - Maria Hasing
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Canada
| | - Minqing Ivy Yang
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Canada
| | - Jianxian Sun
- Department of Chemistry, University of Toronto, Toronto, Canada
| | - Julio Plaza-Diaz
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Zhihao Zhang
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Aaron Cowan
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Walaa Eid
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Sean Stephenson
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Mark R Servos
- Department of Biology, University of Waterloo, Waterloo, Canada
| | - Matthew J Wade
- Data, Analytics and Surveillance Group, UK Health Security Agency, London, United Kingdom
| | - Alex E MacKenzie
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Hui Peng
- Department of Chemistry, University of Toronto, Toronto, Canada
| | - Elizabeth A Edwards
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Canada
| | - Xiao-Li Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Canada
| | - Eric J Alm
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America
| | - Tyson E Graber
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada.
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30
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Mitranescu A, Uchaikina A, Kau AS, Stange C, Ho J, Tiehm A, Wurzbacher C, Drewes JE. Wastewater-Based Epidemiology for SARS-CoV-2 Biomarkers: Evaluation of Normalization Methods in Small and Large Communities in Southern Germany. ACS ES&T WATER 2022; 2:2460-2470. [PMID: 37552738 PMCID: PMC9578648 DOI: 10.1021/acsestwater.2c00306] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 09/21/2022] [Accepted: 09/27/2022] [Indexed: 06/18/2023]
Abstract
In the context of the COVID-19 pandemic, wastewater-based epidemiology (WBE) emerged as a useful tool to account for the prevalence of SARS-CoV-2 infections on a population scale. In this study, we analyzed wastewater samples from three large (>300,000 people served) and four small (<25,000 people served) communities throughout southern Germany from August to December 2021, capturing the fourth infection wave in Germany dominated by the Delta variant (B.1.617.2). As dilution can skew the SARS-CoV-2 biomarker concentrations in wastewater, normalization to wastewater parameters can improve the relationship between SARS-CoV-2 biomarker data and clinical prevalence data. In this study, we investigated the suitability and performance of various normalization parameters. Influent flow data showed strong relationships to precipitation data; accordingly, flow-normalization reacted distinctly to precipitation events. Normalization by surrogate viruses CrAssphage and pepper mild mottle virus showed varying performance for different sampling sites. The best normalization performance was achieved with a mixed fecal indicator calculated from both surrogate viruses. Analyzing the temporal and spatial variation of normalization parameters proved to be useful to explain normalization performance. Overall, our findings indicate that the performance of surrogate viruses, flow, and hydro-chemical data is site-specific. We recommend testing the suitability of normalization parameters individually for specific sewage systems.
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Affiliation(s)
- Alexander Mitranescu
- Chair of Urban Water Systems Engineering,
Technical University of Munich, Am Coulombwall 3,
85748Garching, Germany
| | - Anna Uchaikina
- Chair of Urban Water Systems Engineering,
Technical University of Munich, Am Coulombwall 3,
85748Garching, Germany
| | - Anna-Sonia Kau
- Chair of Urban Water Systems Engineering,
Technical University of Munich, Am Coulombwall 3,
85748Garching, Germany
| | - Claudia Stange
- Department of Water Microbiology, TZW:
DVGW-Technologiezentrum Wasser, Karlsruher Straße 84, 76139Karlsruhe,
Germany
| | - Johannes Ho
- Department of Water Microbiology, TZW:
DVGW-Technologiezentrum Wasser, Karlsruher Straße 84, 76139Karlsruhe,
Germany
| | - Andreas Tiehm
- Department of Water Microbiology, TZW:
DVGW-Technologiezentrum Wasser, Karlsruher Straße 84, 76139Karlsruhe,
Germany
| | - Christian Wurzbacher
- Chair of Urban Water Systems Engineering,
Technical University of Munich, Am Coulombwall 3,
85748Garching, Germany
| | - Jörg E. Drewes
- Chair of Urban Water Systems Engineering,
Technical University of Munich, Am Coulombwall 3,
85748Garching, Germany
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31
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Hoar C, McClary-Gutierrez J, Wolfe MK, Bivins A, Bibby K, Silverman AI, McLellan SL. Looking Forward: The Role of Academic Researchers in Building Sustainable Wastewater Surveillance Programs. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:125002. [PMID: 36580023 PMCID: PMC9799055 DOI: 10.1289/ehp11519] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 12/08/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND In just over 2 years, tracking the COVID-19 pandemic through wastewater surveillance advanced from early reports of successful SARS-CoV-2 RNA detection in untreated wastewater to implementation of programs in at least 60 countries. Early wastewater monitoring efforts primarily originated in research laboratories and are now transitioning into more formal surveillance programs run in commercial and public health laboratories. A major challenge in this progression has been to simultaneously optimize methods and build scientific consensus while implementing surveillance programs, particularly during the rapidly changing landscape of the pandemic. Translating wastewater surveillance results for effective use by public health agencies also remains a key objective for the field. OBJECTIVES We examined the evolution of wastewater surveillance to identify model collaborations and effective partnerships that have created rapid and sustained success. We propose needed areas of research and key roles academic researchers can play in the framework of wastewater surveillance to aid in the transition from early monitoring efforts to more formalized programs within the public health system. DISCUSSION Although wastewater surveillance has rapidly developed as a useful public health tool for tracking COVID-19, there remain technical challenges and open scientific questions that academic researchers are equipped to address. This includes validating methodology and backfilling important knowledge gaps, such as fate and transport of surveillance targets and epidemiological links to wastewater concentrations. Our experience in initiating and implementing wastewater surveillance programs in the United States has allowed us to reflect on key barriers and draw useful lessons on how to promote synergy between different areas of expertise. As wastewater surveillance programs are formalized, the working relationships developed between academic researchers, commercial and public health laboratories, and data users should promote knowledge co-development. We believe active involvement of academic researchers will contribute to building robust surveillance programs that will ultimately provide new insights into population health. https://doi.org/10.1289/EHP11519.
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Affiliation(s)
- Catherine Hoar
- Department of Civil and Urban Engineering, New York University Tandon School of Engineering, Brooklyn, New York, USA
| | - Jill McClary-Gutierrez
- School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
| | - Marlene K. Wolfe
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Aaron Bivins
- Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, Louisiana, USA
| | - Kyle Bibby
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Indiana, USA
| | - Andrea I. Silverman
- Department of Civil and Urban Engineering, New York University Tandon School of Engineering, Brooklyn, New York, USA
| | - Sandra L. McLellan
- School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
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32
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Silva CS, Tryndyak VP, Camacho L, Orloff MS, Porter A, Garner K, Mullis L, Azevedo M. Temporal dynamics of SARS-CoV-2 genome and detection of variants of concern in wastewater influent from two metropolitan areas in Arkansas. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 849:157546. [PMID: 35914602 PMCID: PMC9338166 DOI: 10.1016/j.scitotenv.2022.157546] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 07/14/2022] [Accepted: 07/17/2022] [Indexed: 06/15/2023]
Abstract
Although SARS-CoV-2 can cause severe illness and death, a percentage of the infected population is asymptomatic. This, along with other factors, such as insufficient diagnostic testing and underreporting due to self-testing, contributes to the silent transmission of SARS-CoV-2 and highlights the importance of implementing additional surveillance tools. The fecal shedding of the virus from infected individuals enables its detection in community wastewater, and this has become a valuable public health tool worldwide as it allows the monitoring of the disease on a populational scale. Here, we monitored the presence of SARS-CoV-2 and its dynamic genomic changes in wastewater sampled from two metropolitan areas in Arkansas during major surges of COVID-19 cases and assessed how the viral titers in these samples related to the clinical case counts between late April 2020 and January 2022. The levels of SARS-CoV-2 RNA were quantified by reverse-transcription quantitative polymerase chain reaction (RT-qPCR) using a set of TaqMan assays targeting three different viral genes (encoding ORF1ab polyprotein, surface glycoprotein, and nucleocapsid phosphoprotein). An allele-specific RT-qPCR approach was used to screen the samples for SARS-CoV-2 mutations. The identity and genetic diversity of the virus were further investigated through amplicon-based RNA sequencing, and SARS-CoV-2 variants of concern were detected in wastewater samples throughout the duration of this study. Our data show how changes in the virus genome can affect the sensitivity of specific RT-qPCR assays used in COVID-19 testing with the surge of new variants. A significant association was observed between viral titers in wastewater and recorded number of COVID-19 cases in the areas studied, except when assays failed to detect targets due to the presence of particular variants. These findings support the use of wastewater surveillance as a reliable complementary tool for monitoring SARS-CoV-2 and its genetic variants at the community level.
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Affiliation(s)
- Camila S Silva
- Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA.
| | - Volodymyr P Tryndyak
- Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
| | - Luísa Camacho
- Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
| | - Mohammed S Orloff
- Department of Epidemiology, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Center for the Studies of Tobacco, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Austin Porter
- Department of Health Policy and Management, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Arkansas Department of Health, Little Rock, AR, USA
| | - Kelley Garner
- Department of Epidemiology, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Arkansas Department of Health, Little Rock, AR, USA
| | - Lisa Mullis
- Division of Microbiology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
| | - Marli Azevedo
- Division of Microbiology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
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33
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Bitter LC, Kibbee R, Jiménez GC, Örmeci B. Wastewater Surveillance of SARS-CoV-2 at a Canadian University Campus and the Impact of Wastewater Characteristics on Viral RNA Detection. ACS ES&T WATER 2022; 2:2034-2046. [PMID: 37552746 PMCID: PMC9128010 DOI: 10.1021/acsestwater.2c00060] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/25/2022] [Accepted: 04/27/2022] [Indexed: 05/28/2023]
Abstract
Because of the increased population density, high-risk behavior of young students, and lower vaccination rates, university campuses are considered hot spots for COVID-19 transmission. This study monitored the SARS-CoV-2 RNA levels in the wastewater of a Canadian university campus for a year to provide actionable information to safely manage COVID-19 on campus. Wastewater samples were collected from the campus sewer and residence buildings to identify changes, peaks, and hotspots and search for associations with campus events, social gatherings, long weekends, and holidays. Furthermore, the impact of wastewater parameters (total solids, volatile solids, temperature, pH, turbidity, and UV absorbance) on SARS-CoV-2 detection was investigated, and the efficiency of ultrafiltration and centrifugation concentration methods were compared. RT-qPCR was used for detecting SARS-CoV-2 RNA. Wastewater signals largely correlated positively with the clinically confirmed COVID-19 cases on campus. Long weekends and holidays were often followed by increased viral signals, and the implementation of lockdowns quickly decreased the case numbers. In spite of online teaching and restricted access to campus, the university represented a microcosm of the city and mirrored the same trends. Results indicated that the centrifugation concentration method was more sensitive for wastewater with high solids content and that the ultrafiltration concentration method was more sensitive for wastewater with low solids content. Wastewater characteristics collected from the buildings and the campus sewer were different. Statistical analysis was performed to manifest the observations. Overall, wastewater surveillance provided actionable information and was also able to bring high-risk factors and events to the attention of decision-makers, enabling timely corrective measures.
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Affiliation(s)
- Lena Carolin Bitter
- Department of Civil and Environmental Engineering,
Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S
5B6, Canada
| | - Richard Kibbee
- Department of Civil and Environmental Engineering,
Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S
5B6, Canada
| | - Gabriela C. Jiménez
- Department of Civil and Environmental Engineering,
Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S
5B6, Canada
| | - Banu Örmeci
- Department of Civil and Environmental Engineering,
Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S
5B6, Canada
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34
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Vadde KK, Al-Duroobi H, Phan DC, Jafarzadeh A, Moghadam SV, Matta A, Kapoor V. Assessment of Concentration, Recovery, and Normalization of SARS-CoV-2 RNA from Two Wastewater Treatment Plants in Texas and Correlation with COVID-19 Cases in the Community. ACS ES&T WATER 2022; 2:2060-2069. [PMID: 37552728 PMCID: PMC9128005 DOI: 10.1021/acsestwater.2c00054] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/12/2022] [Accepted: 05/04/2022] [Indexed: 05/18/2023]
Abstract
The purpose of this study was to conduct a correlative assessment of SARS-CoV-2 RNA concentrations in wastewater with COVID-19 cases and a systematic evaluation of the effect of using different virus concentration methods and recovery and normalization approaches. We measured SARS-CoV-2 RNA concentrations at two different wastewater treatment plants (WWTPs) in the Bexar County of Texas from October 2020 to May 2021 (32 weeks) using reverse transcription droplet digital PCR (RT-ddPCR). We evaluated three different adsorption-extraction (AE) based virus concentration methods (acidification, addition of MgCl2, or without any pretreatment) using bovine coronavirus (BCoV) as surrogate virus and observed that the direct AE method showed the highest mean recovery. COVID-19 cases were correlated significantly with SARS-CoV-2 N1 concentrations in Salitrillo (ρ = 0.75, p < 0.001) and Martinez II (ρ = 0.68, p < 0.001) WWTPs, but normalizing to a spiked recovery control (BCoV) or a fecal marker (HF183) reduced correlations for both treatment plants. The results generated in this 32-week monitoring study will enable researchers to prioritize the virus recovery method and subsequent correlation studies for wastewater surveillance.
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Affiliation(s)
- Kiran Kumar Vadde
- School of Civil & Environmental Engineering, and
Construction Management, University of Texas at San Antonio,
San Antonio, Texas 78249, United States
| | - Haya Al-Duroobi
- School of Civil & Environmental Engineering, and
Construction Management, University of Texas at San Antonio,
San Antonio, Texas 78249, United States
| | - Duc C. Phan
- School of Civil & Environmental Engineering, and
Construction Management, University of Texas at San Antonio,
San Antonio, Texas 78249, United States
| | - Arash Jafarzadeh
- School of Civil & Environmental Engineering, and
Construction Management, University of Texas at San Antonio,
San Antonio, Texas 78249, United States
| | - Sina V. Moghadam
- School of Civil & Environmental Engineering, and
Construction Management, University of Texas at San Antonio,
San Antonio, Texas 78249, United States
| | - Akanksha Matta
- Department of Chemistry, University of
Texas at San Antonio, San Antonio, Texas 78249, United
States
| | - Vikram Kapoor
- School of Civil & Environmental Engineering, and
Construction Management, University of Texas at San Antonio,
San Antonio, Texas 78249, United States
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35
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Martins RM, Carvalho T, Bittar C, Quevedo DM, Miceli RN, Nogueira ML, Ferreira HL, Costa PI, Araújo JP, Spilki FR, Rahal P, Calmon MF. Long-Term Wastewater Surveillance for SARS-CoV-2: One-Year Study in Brazil. Viruses 2022; 14:v14112333. [PMID: 36366431 PMCID: PMC9692902 DOI: 10.3390/v14112333] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/26/2022] [Accepted: 10/05/2022] [Indexed: 02/01/2023] Open
Abstract
Wastewater-based epidemiology (WBE) is a tool involving the analysis of wastewater for chemicals and pathogens at the community level. WBE has been shown to be an effective surveillance system for SARS-CoV-2, providing an early-warning-detection system for disease prevalence in the community via the detection of genetic materials in the wastewater. In numerous nation-states, studies have indicated the presence of SARS-CoV-2 in wastewater. Herein, we report the primary time-course monitoring of SARS-CoV-2 RNA in wastewater samples in São José do Rio Preto-SP/Brazil in order to explain the dynamics of the presence of SARS-CoV-2 RNA during one year of the SARS-CoV-2 pandemic and analyze possible relationships with other environmental parameters. We performed RNA quantification of SARS-CoV-2 by RT-qPCR using N1 and N2 targets. The proportion of positive samples for every target resulted in 100% and 96.6% for N1 and N2, respectively. A mean lag of -5 days is observed between the wastewater signal and the new SARS-CoV-2-positive cases reported. A correlation was found between the air and wastewater temperatures and therefore between the SARS-CoV-2 viral titers for N1 and N2 targets. We also observed a correlation between SARS-CoV-2 viral titers and media wastewater flow for the N1 target. In addition, we observed higher viral genome copies within the wastewater samples collected on non-rainy days for the N1 target. Thus, we propose that, based on our results, monitoring raw wastewater may be a broadly applicable strategy that might contribute to resolving the pressing problem of insufficient diagnostic testing; it may represent an inexpensive and early-warning method for future COVID-19 outbreaks, mainly in lower- and middle-income countries.
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Affiliation(s)
- Renan Moura Martins
- Laboratory of Genomic Studies, Institute of Biosciences, Letters and Exact Sciences (IBILCE), São Paulo State University (UNESP), São José do Rio Preto 15054-000, SP, Brazil
| | - Tamara Carvalho
- Laboratory of Genomic Studies, Institute of Biosciences, Letters and Exact Sciences (IBILCE), São Paulo State University (UNESP), São José do Rio Preto 15054-000, SP, Brazil
| | - Cintia Bittar
- Laboratory of Genomic Studies, Institute of Biosciences, Letters and Exact Sciences (IBILCE), São Paulo State University (UNESP), São José do Rio Preto 15054-000, SP, Brazil
| | - Daniela Muller Quevedo
- Institute of Exact and Technological Sciences (ICET), University Feevale, Novo Hamburgo 93525-075, RS, Brazil
| | - Rafael Nava Miceli
- SeMAE-Autonomous Municipal Water and Sewage Service, São José do Rio Preto 15048-000, SP, Brazil
| | - Mauricio Lacerda Nogueira
- Virology Research Laboratory (LPV), Faculty of Medicine of São José do Rio Preto (FAMERP), São José do Rio Preto 15090-000, SP, Brazil
| | - Helena Lage Ferreira
- Applied Preventive Veterinary Medicine Laboratory, Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering (FZEA), University of São Paulo (USP), Pirassununga 13635-900, SP, Brazil
| | - Paulo Inácio Costa
- Department of Clinical Analysis, School of Pharmaceutical Sciences, São Paulo State University (UNESP), Araraquara 14801-360, SP, Brazil
| | - João Pessoa Araújo
- Biotechnology Institute, São Paulo State University (UNESP), Botucatu 18607-440, SP, Brazil
| | - Fernando Rosado Spilki
- Molecular Microbiology Laboratory, University Feevale, Novo Hamburgo 93525-075, RS, Brazil
| | - Paula Rahal
- Laboratory of Genomic Studies, Institute of Biosciences, Letters and Exact Sciences (IBILCE), São Paulo State University (UNESP), São José do Rio Preto 15054-000, SP, Brazil
| | - Marilia Freitas Calmon
- Laboratory of Genomic Studies, Institute of Biosciences, Letters and Exact Sciences (IBILCE), São Paulo State University (UNESP), São José do Rio Preto 15054-000, SP, Brazil
- Correspondence:
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36
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Mercier E, D'Aoust PM, Thakali O, Hegazy N, Jia JJ, Zhang Z, Eid W, Plaza-Diaz J, Kabir MP, Fang W, Cowan A, Stephenson SE, Pisharody L, MacKenzie AE, Graber TE, Wan S, Delatolla R. Municipal and neighbourhood level wastewater surveillance and subtyping of an influenza virus outbreak. Sci Rep 2022; 12:15777. [PMID: 36138059 DOI: 10.1101/2022.06.28.22276884] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/08/2022] [Indexed: 05/27/2023] Open
Abstract
Recurrent influenza epidemics and pandemic potential are significant risks to global health. Public health authorities use clinical surveillance to locate and monitor influenza and influenza-like cases and outbreaks to mitigate hospitalizations and deaths. Currently, global integration of clinical surveillance is the only reliable method for reporting influenza types and subtypes to warn of emergent pandemic strains. The utility of wastewater surveillance (WWS) during the COVID-19 pandemic as a less resource intensive replacement or complement for clinical surveillance has been predicated on analyzing viral fragments in wastewater. We show here that influenza virus targets are stable in wastewater and partitions favorably to the solids fraction. By quantifying, typing, and subtyping the virus in municipal wastewater and primary sludge during a community outbreak, we forecasted a citywide flu outbreak with a 17-day lead time and provided population-level viral subtyping in near real-time to show the feasibility of influenza virus WWS at the municipal and neighbourhood levels in near real time using minimal resources and infrastructure.
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Affiliation(s)
- Elisabeth Mercier
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Patrick M D'Aoust
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Ocean Thakali
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Nada Hegazy
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Jian-Jun Jia
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Zhihao Zhang
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Walaa Eid
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Julio Plaza-Diaz
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Md Pervez Kabir
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Wanting Fang
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Aaron Cowan
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Sean E Stephenson
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Lakshmi Pisharody
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Alex E MacKenzie
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Tyson E Graber
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Shen Wan
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada.
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37
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Mercier E, D'Aoust PM, Thakali O, Hegazy N, Jia JJ, Zhang Z, Eid W, Plaza-Diaz J, Kabir MP, Fang W, Cowan A, Stephenson SE, Pisharody L, MacKenzie AE, Graber TE, Wan S, Delatolla R. Municipal and neighbourhood level wastewater surveillance and subtyping of an influenza virus outbreak. Sci Rep 2022; 12:15777. [PMID: 36138059 PMCID: PMC9493155 DOI: 10.1038/s41598-022-20076-z] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/08/2022] [Indexed: 11/22/2022] Open
Abstract
Recurrent influenza epidemics and pandemic potential are significant risks to global health. Public health authorities use clinical surveillance to locate and monitor influenza and influenza-like cases and outbreaks to mitigate hospitalizations and deaths. Currently, global integration of clinical surveillance is the only reliable method for reporting influenza types and subtypes to warn of emergent pandemic strains. The utility of wastewater surveillance (WWS) during the COVID-19 pandemic as a less resource intensive replacement or complement for clinical surveillance has been predicated on analyzing viral fragments in wastewater. We show here that influenza virus targets are stable in wastewater and partitions favorably to the solids fraction. By quantifying, typing, and subtyping the virus in municipal wastewater and primary sludge during a community outbreak, we forecasted a citywide flu outbreak with a 17-day lead time and provided population-level viral subtyping in near real-time to show the feasibility of influenza virus WWS at the municipal and neighbourhood levels in near real time using minimal resources and infrastructure.
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Affiliation(s)
- Elisabeth Mercier
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Patrick M D'Aoust
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Ocean Thakali
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Nada Hegazy
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Jian-Jun Jia
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Zhihao Zhang
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Walaa Eid
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Julio Plaza-Diaz
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Md Pervez Kabir
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Wanting Fang
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Aaron Cowan
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Sean E Stephenson
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Lakshmi Pisharody
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Alex E MacKenzie
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Tyson E Graber
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Shen Wan
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada.
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38
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McGowan J, Borucki M, Omairi H, Varghese M, Vellani S, Chakravarty S, Fan S, Chattopadhyay S, Siddiquee M, Thissen JB, Mulakken N, Moon J, Kimbrel J, Tiwari AK, Taylor RT, Kang DW, Jaing C, Chakravarti R, Chattopadhyay S. SARS-CoV-2 Monitoring in Wastewater Reveals Novel Variants and Biomarkers of Infection. Viruses 2022; 14:2032. [PMID: 36146835 PMCID: PMC9503862 DOI: 10.3390/v14092032] [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: 07/27/2022] [Revised: 09/06/2022] [Accepted: 09/09/2022] [Indexed: 12/02/2022] Open
Abstract
Wastewater-based epidemiology (WBE) is a popular tool for the early indication of community spread of infectious diseases. WBE emerged as an effective tool during the COVID-19 pandemic and has provided meaningful information to minimize the spread of infection. Here, we present a combination of analyses using the correlation of viral gene copies with clinical cases, sequencing of wastewater-derived RNA for the viral mutants, and correlative analyses of the viral gene copies with the bacterial biomarkers. Our study provides a unique platform for potentially using the WBE-derived results to predict the spread of COVID-19 and the emergence of new variants of concern. Further, we observed a strong correlation between the presence of SARS-CoV-2 and changes in the microbial community of wastewater, particularly the significant changes in bacterial genera belonging to the families of Lachnospiraceae and Actinomycetaceae. Our study shows that microbial biomarkers could be utilized as prediction tools for future infectious disease surveillance and outbreak responses. Overall, our comprehensive analyses of viral spread, variants, and novel bacterial biomarkers will add significantly to the growing body of literature on WBE and COVID-19.
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Affiliation(s)
- Jenna McGowan
- Physiology and Pharmacology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Monica Borucki
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Hicham Omairi
- Department of Civil and Environmental Engineering, University of Toledo College of Engineering, Toledo, OH 43607, USA
| | - Merina Varghese
- Medical Microbiology and Immunology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Shahnaz Vellani
- Physiology and Pharmacology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Sukanya Chakravarty
- Medical Microbiology and Immunology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Shumin Fan
- Medical Microbiology and Immunology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Srestha Chattopadhyay
- College of Pharmacy and Pharmaceutical Sciences, University of Toledo, Toledo, OH 43606, USA
| | - Mashuk Siddiquee
- Department of Civil and Environmental Engineering, University of Toledo College of Engineering, Toledo, OH 43607, USA
| | - James B Thissen
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Nisha Mulakken
- Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Joseph Moon
- Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Jeffrey Kimbrel
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Amit K Tiwari
- College of Pharmacy and Pharmaceutical Sciences, University of Toledo, Toledo, OH 43606, USA
- Center for Medical Bio-Allied Health Sciences Research, Ajman University, Ajman P.O. Box 346, United Arab Emirates
| | - Roger Travis Taylor
- Medical Microbiology and Immunology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Dae-Wook Kang
- Department of Civil and Environmental Engineering, University of Toledo College of Engineering, Toledo, OH 43607, USA
| | - Crystal Jaing
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Ritu Chakravarti
- Physiology and Pharmacology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Saurabh Chattopadhyay
- Medical Microbiology and Immunology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
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39
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Lu E, Ai Y, Davis A, Straathof J, Halloran K, Hull N, Winston R, Weir MH, Soller J, Bohrerova Z, Oglesbee M, Lee J. Wastewater surveillance of SARS-CoV-2 in dormitories as a part of comprehensive university campus COVID-19 monitoring. ENVIRONMENTAL RESEARCH 2022; 212:113580. [PMID: 35671797 PMCID: PMC9167806 DOI: 10.1016/j.envres.2022.113580] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 05/20/2022] [Accepted: 05/26/2022] [Indexed: 05/05/2023]
Abstract
Wastewater-based epidemiology is an effective tool for monitoring infectious disease spread or illicit drug use within communities. At the Ohio State University, we conducted a SARS-CoV-2 wastewater surveillance program in the 2020-2021 academic year and compared results with the university-required weekly COVID-19 saliva testing to monitor COVID-19 infection prevalence in the on-campus residential communities. The objectives of the study were to rapidly track trends in the wastewater SARS-CoV-2 gene concentrations, analyze the relationship between case numbers and wastewater signals when adjusted using human fecal viral indicator concentrations (PMMoV, crAssphage) in wastewater, and investigate the relationship of the SARS-CoV-2 gene concentrations with wastewater parameters. SARS-CoV-2 nucleocapsid and envelope (N1, N2, and E) gene concentrations, determined with reverse transcription droplet digital PCR, were used to track SARS-CoV-2 viral loads in dormitory wastewater once a week at 6 sampling sites across the campus during the fall semester in 2020. During the following spring semester, research was focused on SARS-CoV2 N2 gene concentrations at 5 sites sampled twice a week. Spearman correlations both with and without adjusting using human fecal viral indicators showed a significant correlation (p < 0.05) between human COVID-19 positive case counts and wastewater SARS-CoV-2 gene concentrations. Spearman correlations showed significant relationships between N1 gene concentrations and both TSS and turbidity, and between E gene concentrations and both pH and turbidity. These results suggest that wastewater signal increases with the census of infected individuals, in which the majority are asymptomatic, with a statistically significant (p-value <0.05) temporal correlation. The study design can be utilized as a platform for rapid trend tracking of SARS-CoV-2 variants and other diseases circulating in various communities.
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Affiliation(s)
- Emily Lu
- Environmental Science Graduate Program, The Ohio State University, Columbus, OH, USA
| | - Yuehan Ai
- Department of Food Science and Technology, The Ohio State University, Columbus, OH, USA
| | - Angela Davis
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, USA
| | - Judith Straathof
- Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, Columbus, OH, USA
| | - Kent Halloran
- Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, Columbus, OH, USA; Facilities Operations and Development, Environmental Health and Safety, The Ohio State University, Columbus, OH, USA
| | - Natalie Hull
- Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, Columbus, OH, USA; Sustainability Institute, The Ohio State University, Columbus, OH, USA
| | - Ryan Winston
- Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, Columbus, OH, USA; Department of Food, Agricultural, and Biological Engineering, The Ohio State University, Columbus, OH, USA; Sustainability Institute, The Ohio State University, Columbus, OH, USA
| | - Mark H Weir
- Department of Food Science and Technology, The Ohio State University, Columbus, OH, USA; Sustainability Institute, The Ohio State University, Columbus, OH, USA; Infectious Diseases Institute, The Ohio State University, Columbus, OH, USA
| | | | - Zuzana Bohrerova
- Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, Columbus, OH, USA
| | - Michael Oglesbee
- Department of Veterinary Biosciences, The Ohio State University, Columbus, OH, USA; Infectious Diseases Institute, The Ohio State University, Columbus, OH, USA
| | - Jiyoung Lee
- Department of Food Science and Technology, The Ohio State University, Columbus, OH, USA; Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, USA; Infectious Diseases Institute, The Ohio State University, Columbus, OH, USA.
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40
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Tanimoto Y, Ito E, Miyamoto S, Mori A, Nomoto R, Nakanishi N, Oka N, Morimoto T, Iwamoto T. SARS-CoV-2 RNA in Wastewater Was Highly Correlated With the Number of COVID-19 Cases During the Fourth and Fifth Pandemic Wave in Kobe City, Japan. Front Microbiol 2022; 13:892447. [PMID: 35756040 PMCID: PMC9223763 DOI: 10.3389/fmicb.2022.892447] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 05/20/2022] [Indexed: 12/14/2022] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of the current coronavirus disease 2019 (COVID-19) pandemic and associated respiratory infections, has been detected in the feces of patients. Therefore, determining SARS-CoV-2 RNA levels in sewage may help to predict the number of infected people within the area. In this study, we quantified SARS-CoV-2 RNA copy number using reverse transcription quantitative real-time PCR with primers and probes targeting the N gene, which allows the detection of both wild-type and variant strain of SARS-CoV-2 in sewage samples from two wastewater treatment plants (WWTPs) in Kobe City, Japan, during the fourth and fifth pandemic waves of COVID-19 between February 2021 and October 2021. The wastewater samples were concentrated via centrifugation, yielding a pelleted solid fraction and a supernatant, which was subjected to polyethylene glycol (PEG) precipitation. The SARS-CoV-2 RNA was significantly and frequently detected in the solid fraction than in the PEG-precipitated fraction. In addition, the copy number in the solid fraction was highly correlated with the number of COVID-19 cases in the WWTP basin (WWTP-A: r = 0.8205, p < 0.001; WWTP-B: r = 0.8482, p < 0.001). The limit of capturing COVID-19 cases per 100,000 people was 0.75 cases in WWTP-A and 1.20 cases in WWTP-B, respectively. Quantitative studies of RNA in sewage can be useful for administrative purposes related to public health, including issuing warnings and implementing preventive measures within sewage basins.
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Affiliation(s)
- Yoshihiko Tanimoto
- Department of Infectious Diseases, Kobe Institute of Health, Kobe City, Japan
| | - Erika Ito
- Department of Infectious Diseases, Kobe Institute of Health, Kobe City, Japan
| | - Sonoko Miyamoto
- Department of Infectious Diseases, Kobe Institute of Health, Kobe City, Japan
| | - Ai Mori
- Department of Infectious Diseases, Kobe Institute of Health, Kobe City, Japan
| | - Ryohei Nomoto
- Department of Infectious Diseases, Kobe Institute of Health, Kobe City, Japan
| | - Noriko Nakanishi
- Department of Infectious Diseases, Kobe Institute of Health, Kobe City, Japan
| | - Naohiro Oka
- Planning Division, Sewage Works Department, Public Construction Projects Bureau, Kobe City, Japan
| | - Takao Morimoto
- Planning Division, Sewage Works Department, Public Construction Projects Bureau, Kobe City, Japan
| | - Tomotada Iwamoto
- Department of Infectious Diseases, Kobe Institute of Health, Kobe City, Japan
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