1
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Williams RC, Farkas K, Garcia-Delgado A, Adwan L, Kevill JL, Cross G, Weightman AJ, Jones DL. Simultaneous detection and characterization of common respiratory pathogens in wastewater through genomic sequencing. WATER RESEARCH 2024; 256:121612. [PMID: 38642537 DOI: 10.1016/j.watres.2024.121612] [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: 11/28/2023] [Revised: 04/11/2024] [Accepted: 04/12/2024] [Indexed: 04/22/2024]
Abstract
Genomic surveillance of SARS-CoV-2 has given insight into the evolution and epidemiology of the virus and its variant lineages during the COVID-19 pandemic. Expanding this approach to include a range of respiratory pathogens can better inform public health preparedness for potential outbreaks and epidemics. Here, we simultaneously sequenced 38 pathogens including influenza viruses, coronaviruses and bocaviruses, to examine the abundance and seasonality of respiratory pathogens in urban wastewater. We deployed a targeted bait capture method and short-read sequencing (Illumina Respiratory Virus Oligos Panel; RVOP) on composite wastewater samples from 8 wastewater treatment plants (WWTPs) and one associated hospital site. By combining seasonal sampling with whole genome sequencing, we were able to concurrently detect and characterise a range of common respiratory pathogens, including SARS-CoV-2, adenovirus and parainfluenza virus. We demonstrated that 38 respiratory pathogens can be detected at low abundances year-round, that hospital pathogen diversity is higher in winter vs. summer sampling events, and that significantly more viruses are detected in raw influent compared to treated effluent samples. Finally, we compared detection sensitivity of RT-qPCR vs. next generation sequencing for SARS-CoV-2, enteroviruses, influenza A/B, and respiratory syncytial viruses. We conclude that both should be used in combination; RT-qPCR allowed accurate quantification, whilst genomic sequencing detected pathogens at lower abundance. We demonstrate the valuable role of wastewater genomic surveillance and its contribution to the field of wastewater-based epidemiology, gaining rapid understanding of the seasonal presence and persistence for common respiratory pathogens. By simultaneously monitoring seasonal trends and early warning signs of many viruses circulating in communities, public health agencies can implement targeted prevention and rapid response plans.
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Affiliation(s)
- Rachel C Williams
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd LL57 2UW, UK.
| | - Kata Farkas
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd LL57 2UW, UK
| | - Alvaro Garcia-Delgado
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd LL57 2UW, UK
| | - Latifah Adwan
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd LL57 2UW, UK
| | - Jessica L Kevill
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd LL57 2UW, UK
| | - Gareth Cross
- Science Evidence Advice Division, Health and Social Services Group, Welsh Government, Cathays Park, Cardiff, CF10 3NQ, UK
| | - Andrew J Weightman
- School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3AX, UK
| | - Davey L Jones
- School of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd LL57 2UW, UK; Food Futures Institute, Murdoch University, Murdoch WA 6150, Australia
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2
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Harrington A, Vo V, Moshi MA, Chang CL, Baker H, Ghani N, Itorralba JY, Papp K, Gerrity D, Moser D, Oh EC. Environmental Surveillance of Flood Control Infrastructure Impacted by Unsheltered Individuals Leads to the Detection of SARS-CoV-2 and Novel Mutations in the Spike Gene. ENVIRONMENTAL SCIENCE & TECHNOLOGY LETTERS 2024; 11:410-417. [PMID: 38752195 PMCID: PMC11095249 DOI: 10.1021/acs.estlett.3c00938] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 02/09/2024] [Accepted: 02/12/2024] [Indexed: 05/18/2024]
Abstract
In the United States, the growing number of people experiencing homelessness has become a socioeconomic crisis with public health ramifications, recently exacerbated by the COVID-19 pandemic. We hypothesized that the environmental surveillance of flood control infrastructure may be an effective approach to understand the prevalence of infectious disease. From December 2021 through July 2022, we tested for SARS-CoV-2 RNA from two flood control channels known to be impacted by unsheltered individuals residing in upstream tunnels. Using qPCR, we detected SARS-CoV-2 RNA in these environmental water samples when significant COVID-19 outbreaks were occurring in the surrounding community. We also performed whole genome sequencing to identify SARS-CoV-2 lineages. Variant compositions were consistent with those of geographically and temporally matched municipal wastewater samples and clinical specimens. However, we also detected 10 of 22 mutations specific to the Alpha variant in the environmental water samples collected during January 2022-one year after the Alpha infection peak. We also identified mutations in the spike gene that have never been identified in published reports. Our findings demonstrate that environmental surveillance of flood control infrastructure may be an effective tool to understand public health conditions among unsheltered individuals-a vulnerable population that is underrepresented in clinical surveillance data.
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Affiliation(s)
- Anthony Harrington
- Laboratory
of Neurogenetics and Precision Medicine, College of Sciences, Neuroscience Interdisciplinary
Ph.D. program, Department of Brain Health, Department of Internal Medicine, Kirk Kerkorian
School of Medicine at UNLV, University of
Nevada Las Vegas, Las Vegas, Nevada 89154, United States
| | - Van Vo
- Laboratory
of Neurogenetics and Precision Medicine, College of Sciences, Neuroscience Interdisciplinary
Ph.D. program, Department of Brain Health, Department of Internal Medicine, Kirk Kerkorian
School of Medicine at UNLV, University of
Nevada Las Vegas, Las Vegas, Nevada 89154, United States
| | - Michael A. Moshi
- Laboratory
of Neurogenetics and Precision Medicine, College of Sciences, Neuroscience Interdisciplinary
Ph.D. program, Department of Brain Health, Department of Internal Medicine, Kirk Kerkorian
School of Medicine at UNLV, University of
Nevada Las Vegas, Las Vegas, Nevada 89154, United States
| | - Ching-Lan Chang
- Laboratory
of Neurogenetics and Precision Medicine, College of Sciences, Neuroscience Interdisciplinary
Ph.D. program, Department of Brain Health, Department of Internal Medicine, Kirk Kerkorian
School of Medicine at UNLV, University of
Nevada Las Vegas, Las Vegas, Nevada 89154, United States
| | - Hayley Baker
- Laboratory
of Neurogenetics and Precision Medicine, College of Sciences, Neuroscience Interdisciplinary
Ph.D. program, Department of Brain Health, Department of Internal Medicine, Kirk Kerkorian
School of Medicine at UNLV, University of
Nevada Las Vegas, Las Vegas, Nevada 89154, United States
| | - Nabih Ghani
- Laboratory
of Neurogenetics and Precision Medicine, College of Sciences, Neuroscience Interdisciplinary
Ph.D. program, Department of Brain Health, Department of Internal Medicine, Kirk Kerkorian
School of Medicine at UNLV, University of
Nevada Las Vegas, Las Vegas, Nevada 89154, United States
| | - Jose Yani Itorralba
- Laboratory
of Neurogenetics and Precision Medicine, College of Sciences, Neuroscience Interdisciplinary
Ph.D. program, Department of Brain Health, Department of Internal Medicine, Kirk Kerkorian
School of Medicine at UNLV, University of
Nevada Las Vegas, Las Vegas, Nevada 89154, United States
| | - Katerina Papp
- Southern
Nevada Water Authority, P.O. Box 99954, Las Vegas Nevada 89193, United States
| | - Daniel Gerrity
- Southern
Nevada Water Authority, P.O. Box 99954, Las Vegas Nevada 89193, United States
| | - Duane Moser
- Division
of Hydrologic Sciences, Desert Research
Institute, Las Vegas, Nevada 89119, United States
| | - Edwin C. Oh
- Laboratory
of Neurogenetics and Precision Medicine, College of Sciences, Neuroscience Interdisciplinary
Ph.D. program, Department of Brain Health, Department of Internal Medicine, Kirk Kerkorian
School of Medicine at UNLV, University of
Nevada Las Vegas, Las Vegas, Nevada 89154, United States
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3
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Wang Y, Ni G, Tian W, Wang H, Li J, Thai P, Choi PM, Jackson G, Hu S, Yang B, Guo J. Wastewater tiling amplicon sequencing in sentinel sites reveals longitudinal dynamics of SARS-CoV-2 variants prevalence. WATER RESEARCH X 2024; 23:100224. [PMID: 38711798 PMCID: PMC11070618 DOI: 10.1016/j.wroa.2024.100224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 04/17/2024] [Accepted: 04/19/2024] [Indexed: 05/08/2024]
Abstract
The ongoing evolution of SARS-CoV-2 is a significant concern, especially with the decrease in clinical sequencing efforts, which impedes the ability of public health sectors to prepare for the emergence of new variants and potential COVID-19 outbreaks. Wastewater-based epidemiology (WBE) has been proposed as a surveillance program to detect and monitor the SARS-CoV-2 variants being transmitted in communities. However, research is limited in evaluating the effectiveness of wastewater collection at sentinel sites for monitoring disease prevalence and variant dynamics, especially in terms of inferring the epidemic patterns on a broader scale, such as at the state/province level. This study utilized a multiplexed tiling amplicon-based sequencing (ATOPlex) to track the longitudinal dynamics of variant of concern (VOC) in wastewater collected from municipalities in Queensland, Australia, spanning from 2020 to 2022. We demonstrated that wastewater epidemiology measured by ATOPlex exhibited a strong and consistent correlation with the number of daily confirmed cases. The VOC dynamics observed in wastewater closely aligned with the dynamic profile reported by clinical sequencing. Wastewater sequencing has the potential to provide early warning information for emerging variants. These findings suggest that WBE at sentinel sites, coupled with sensitive sequencing methods, provides a reliable and long-term disease surveillance strategy.
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Affiliation(s)
- Yu Wang
- Australian Centre for Water and Environmental Biotechnology, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Gaofeng Ni
- Department of Microbiology, Biomedicine Discovery Institute, Monash University, Melbourne, Victoria, Australia
| | - Wei Tian
- MGI Australia Pty Ltd, 300 Herston Road, Herston, Brisbane, QLD 4006, Australia
| | - Haofei Wang
- MGI Australia Pty Ltd, 300 Herston Road, Herston, Brisbane, QLD 4006, Australia
| | - Jiaying Li
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Brisbane, Queensland, Australia
| | - Phong Thai
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Brisbane, Queensland, Australia
| | - Phil M. Choi
- Water Unit, Health Protection Branch, Queensland Public Health and Scientific Services, Queensland Health, Brisbane, Queensland, Australia
| | - Greg Jackson
- Water Unit, Health Protection Branch, Queensland Public Health and Scientific Services, Queensland Health, Brisbane, Queensland, Australia
| | - Shihu Hu
- Australian Centre for Water and Environmental Biotechnology, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Bicheng Yang
- MGI Australia Pty Ltd, 300 Herston Road, Herston, Brisbane, QLD 4006, Australia
| | - Jianhua Guo
- Australian Centre for Water and Environmental Biotechnology, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
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4
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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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5
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Ahuja S, Tallur S, Kondabagil K. Simultaneous microbial capture and nucleic acid extraction from wastewater with minimal pre-processing and high recovery efficiency. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 918:170347. [PMID: 38336063 DOI: 10.1016/j.scitotenv.2024.170347] [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: 10/12/2023] [Revised: 12/22/2023] [Accepted: 01/19/2024] [Indexed: 02/12/2024]
Abstract
The COVID-19 pandemic accelerated research towards developing low-cost assays for automated urban wastewater monitoring assay that can be integrated into an environmental surveillance system for early warning of frequent disease outbreaks and future pandemics. Microbial concentration is one of the most challenging steps in wastewater surveillance, due to the sample heterogeneity and low pathogen load. Keeping in mind the requirements of large-scale testing in densely populated low- or middle-income countries (LMICs), such assays would need to be low-cost and have rapid turnaround time with high recovery efficiency. In this study, two such methods are presented and evaluated against commercially available kits for pathogen detection in wastewater. The first method utilizes paper dipsticks while the second method comprises of a PTFE membrane filter (PMF) integrated with a peristaltic pump. Both methods were used to concentrate and isolate nucleic acids from different microbes such as SARS-CoV-2, pepper mild mottle virus (PMMoV), bacteriophage Phi6, and E. coli from wastewater samples with minimal or no sample pre-processing. While the paper dipstick method is suitable for sub-milliliter sample volume, the PMF method can be used with larger volumes of wastewater sample (40 mL) and can detect multiple microbes with recovery efficiency comparable to commercially available kits.
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Affiliation(s)
- Shruti Ahuja
- Centre for Research in Nanotechnology & Science (CRNTS), IIT Bombay, Powai, Mumbai 400076, Maharashtra, India.
| | - Siddharth Tallur
- Department of Electrical Engineering, IIT Bombay, Powai, Mumbai 400076, Maharashtra, India.
| | - Kiran Kondabagil
- Department of Biosciences and Bioengineering, IIT Bombay, Powai, Mumbai 400076, Maharashtra, India.
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6
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Toribio-Avedillo D, Gómez-Gómez C, Sala-Comorera L, Galofré B, Muniesa M. Adapted methods for monitoring influenza virus and respiratory syncytial virus in sludge and wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 918:170636. [PMID: 38331285 DOI: 10.1016/j.scitotenv.2024.170636] [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: 11/30/2023] [Revised: 01/10/2024] [Accepted: 01/31/2024] [Indexed: 02/10/2024]
Abstract
Wastewater-based surveillance constitutes a valuable methodology for the continuous monitoring of viral circulation, with the capacity to function as an early warning system. It holds particular significance in scenarios where respiratory viruses exhibit overlapping clinical presentations, as occurs with SARS-CoV-2, influenza virus (IV), and respiratory syncytial virus (RSV), and allows seasonal virus outbreaks to be distinguished from COVID-19 peaks. Furthermore, sewage sludge, given it harbors concentrated human waste from a large population, serves as a substantial reservoir for pathogen detection. To effectively integrate wastewater-based epidemiology into infectious disease surveillance, the detection methods employed in wastewater samples must be adapted to the distinct characteristics of sludge matrices. In this study, we adapted and applied protocols for the detection of IV and RSV in sewage sludge, comparing their performance with the results obtained in wastewater. To assess the efficiency of these protocols, sludge and wastewater samples were spiked with IV and RSV RNA, either free or incorporated in lentiviral particles. Samples were concentrated using the aluminum hydroxide adsorption-precipitation method before viral RNA extraction. Absolute virus quantification was carried out by RT-qPCR, including an internal control to monitor potential inhibitory factors. Recovery efficiencies for both free IV and RSV RNA were 60 % in sludge, and 75 % and 71 % respectively in wastewater, whereas the values for IV and RSV RNA in lentiviral particles were 16 % and 10 % in sludge and 21 % and 17 % in wastewater respectively. Additionally, the protocol enabled the quantification of naturally occurring IV and RSV in wastewater and sludge samples collected from two wastewater treatment plants during the winter months, thus affirming the efficacy of the employed methodologies.
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Affiliation(s)
- Daniel Toribio-Avedillo
- Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Diagonal 643 Annex, Floor 0, E-08028 Barcelona, Spain
| | - Clara Gómez-Gómez
- Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Diagonal 643 Annex, Floor 0, E-08028 Barcelona, Spain
| | - Laura Sala-Comorera
- Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Diagonal 643 Annex, Floor 0, E-08028 Barcelona, Spain
| | - Belén Galofré
- Aigües de Barcelona, Empresa Metropolitana de Gestió del Cicle Integral de l'Aigua, General Batet 1-7, Barcelona 08028, Spain
| | - Maite Muniesa
- Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Diagonal 643 Annex, Floor 0, E-08028 Barcelona, Spain.
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7
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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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8
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Carducci A, Federigi I, Lauretani G, Muzio S, Pagani A, Atomsa NT, Verani M. Critical Needs for Integrated Surveillance: Wastewater-Based and Clinical Epidemiology in Evolving Scenarios with Lessons Learned from SARS-CoV-2. FOOD AND ENVIRONMENTAL VIROLOGY 2024; 16:38-49. [PMID: 38168848 DOI: 10.1007/s12560-023-09573-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 11/28/2023] [Indexed: 01/05/2024]
Abstract
During the COVID-19 pandemic, wastewater-based epidemiology (WBE) and clinical surveillance have been used as tools for analyzing the circulation of SARS-CoV-2 in the community, but both approaches can be strongly influenced by some sources of variability. From the challenging perspective of integrating environmental and clinical data, we performed a correlation analysis between SARS-CoV-2 concentrations in raw sewage and incident COVID-19 cases in areas served by medium-size wastewater treatment plants (WWTPs) from 2021 to 2023. To this aim, both datasets were adjusted for several sources of variability: WBE data were adjusted for factors including the analytical protocol, sewage flow, and population size, while clinical data adjustments considered the demographic composition of the served population. Then, we addressed the impact on the correlation of differences among sewerage networks and variations in the frequency and type of swab tests due to changes in political and regulatory scenarios. Wastewater and clinical data were significantly correlated when restrictive containment measures and limited movements were in effect (ρ = 0.50) and when COVID-19 cases were confirmed exclusively through molecular testing (ρ = 0.49). Moreover, a positive (although weak) correlation arose for WWTPs located in densely populated areas (ρ = 0.37) and with shorter sewerage lengths (ρ = 0.28). This study provides methodological approaches for interpreting WBE and clinical surveillance data, which could also be useful for other infections. Data adjustments and evaluation of possible sources of bias need to be carefully considered from the perspective of integrated environmental and clinical surveillance of infections.
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Affiliation(s)
- Annalaura Carducci
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy
| | - Ileana Federigi
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy.
| | - Giulia Lauretani
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy
| | - Sara Muzio
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy
| | - Alessandra Pagani
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy
| | - Nebiyu Tariku Atomsa
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy
| | - Marco Verani
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy
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9
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Dehghan Banadaki M, Torabi S, Rockward A, Strike WD, Noble A, Keck JW, Berry SM. Simple SARS-CoV-2 concentration methods for wastewater surveillance in low resource settings. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168782. [PMID: 38000737 PMCID: PMC10842712 DOI: 10.1016/j.scitotenv.2023.168782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 11/18/2023] [Accepted: 11/20/2023] [Indexed: 11/26/2023]
Abstract
Wastewater-based epidemiology (WBE) measures pathogens in wastewater to monitor infectious disease prevalence in communities. Due to the high dilution of pathogens in sewage, a concentration method is often required to achieve reliable biomarker signals. However, most of the current concentration methods rely on expensive equipment and labor-intensive processes, which limits the application of WBE in low-resource settings. Here, we compared the performance of four inexpensive and simple concentration methods to detect SARS-CoV-2 in wastewater samples: Solid Fraction, Porcine Gastric Mucin-conjugated Magnetic Beads, Calcium Flocculation-Citrate Dissolution (CFCD), and Nanotrap® Magnetic Beads (NMBs). The NMBs and CFCD methods yielded the highest concentration performance for SARS-CoV-2 (∼16-fold concentration and ∼ 41 % recovery) and require <45 min processing time. CFCD has a relatively low consumable cost (<$2 per four sample replicates). All methods can be performed with basic laboratory equipment and minimal electricity usage which enables further application of WBE in remote areas and low resource settings.
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Affiliation(s)
| | - Soroosh Torabi
- Department of Mechanical Engineering, College of Engineering, University of Kentucky, United States
| | - Alexus Rockward
- Department of Biomedical Engineering, College of Engineering, University of Kentucky, United States
| | - William D Strike
- Department of Biomedical Engineering, College of Engineering, University of Kentucky, United States
| | - Ann Noble
- Department of Mechanical Engineering, College of Engineering, University of Kentucky, United States
| | - James W Keck
- WWAMI School of Medicine, University of Alaska Anchorage, United States
| | - Scott M Berry
- Department of Mechanical Engineering, College of Engineering, University of Kentucky, United States; Department of Biomedical Engineering, College of Engineering, University of Kentucky, United States.
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10
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Haskell BR, Dhiyebi HA, Srikanthan N, Bragg LM, Parker WJ, Giesy JP, Servos MR. Implementing an adaptive, two-tiered SARS-CoV-2 wastewater surveillance program on a university campus using passive sampling. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168998. [PMID: 38040360 DOI: 10.1016/j.scitotenv.2023.168998] [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: 10/13/2023] [Revised: 11/27/2023] [Accepted: 11/28/2023] [Indexed: 12/03/2023]
Abstract
Building-level wastewater-based surveillance (WBS) has been increasingly applied upstream from wastewater treatment plants to conduct targeted monitoring for SARS-CoV-2. In this study, a two-tiered, trigger-based wastewater surveillance program was developed on a university campus to monitor dormitory wastewater. The objective was to determine if passive sampling with cotton gauze as a sampling medium could be used to support institution-level public health action. Two nucleocapsid gene targets (N1 and N2) of SARS-CoV-2 as well as the endogenous fecal indicator pepper mild mottle virus (PMMoV) were quantified using RT-qPCR. >500 samples were analyzed during two contrasting surveillance periods. In the Fall of 2021 community viral burden was low and a tiered sampling network was able to isolate individual clinical cases at the building-scale. In the Winter of 2022 wastewater signals were quickly elevated by the emergence of the highly transmissible SARS-CoV-2 Omicron (B.1.1.529) variant. Prevalence of SARS-CoV-2 shifted surveillance objectives from isolating cases to monitoring trends, revealing both the benefits and limitations of a tiered surveillance design under different public health situations. Normalization of SARS-CoV-2 by PMMoV was not reflective of upstream population differences, suggesting saturation of the material occurred during the exposure period. The passive sampling method detected nearly all known clinical cases and in one instance was able to identify one pre-symptomatic individual days prior to confirmation by clinical test. Comparisons between campus samplers and municipal wastewater influent suggests that the spread of COVID-19 on the campus was similar to that of the broader community. The results demonstrate that passive sampling is an effective tool that can produce semi-quantitative data capable of tracking temporal trends to guide targeted public health decision-making at an institutional level. Practitioners of WBS can utilize these results to inform surveillance program designs that prioritize efficient resource use and rapid reporting.
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Affiliation(s)
- Blake R Haskell
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada.
| | - Hadi A Dhiyebi
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada.
| | - Nivetha Srikanthan
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada
| | - Leslie M Bragg
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada.
| | - Wayne J Parker
- Department of Civil and Environmental Engineering, University of Waterloo, 200 University Ave. W, Waterloo, ON N2L 3G1, Canada.
| | - John P Giesy
- Toxicology Centre, University of Saskatchewan, 44 Campus Dr., Saskatoon, Saskatchewan S7N 5B3, Canada; Department of Environmental Science, Baylor University, 1 Bear Trail, Waco, TX 76798, USA
| | - Mark R Servos
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada.
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11
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Rishan ST, Kline RJ, Rahman MS. New prospects of environmental RNA metabarcoding research in biological diversity, ecotoxicological monitoring, and detection of COVID-19: a critical review. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:11406-11427. [PMID: 38183542 DOI: 10.1007/s11356-023-31776-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 12/26/2023] [Indexed: 01/08/2024]
Abstract
Ecosystems are multifaceted and complex systems and understanding their composition is crucial for the implementation of efficient conservation and management. Conventional approaches to biodiversity surveys can have limitations in detecting the complete range of species present. In contrast, the study of environmental RNA (eRNA) offers a non-invasive and comprehensive method for monitoring and evaluating biodiversity across different ecosystems. Similar to eDNA, the examination of genetic material found in environmental samples can identify and measure many species, including ones that pose challenges to traditional methods. However, eRNA is degraded quickly and therefore shows promise in detection of living organisms closer to their actual location than eDNA methods. This method provides a comprehensive perspective on the well-being of ecosystems, facilitating the development of focused conservation approaches to save at-risk species and uphold ecological equilibrium. Furthermore, eRNA has been recognized as a valuable method for the identification of COVID-19 in the environment, besides its established uses in biodiversity protection. The SARS-CoV-2 virus, which is accountable for the worldwide epidemic, releases RNA particles into the surrounding environment via human waste, providing insights into the feasibility of detecting it in wastewater and other samples taken from the environment. In this article, we critically reviewed the recent research activities that use the eRNA method, including its utilization in biodiversity conservation, ecological surveillance, and ecotoxicological monitoring as well as its innovative potential in identifying COVID-19. Through this review, the reader can understand the recent developments, prospects, and challenges of eRNA research in ecosystem management and biodiversity conservation.
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Affiliation(s)
- Sakib Tahmid Rishan
- Biochemistry and Molecular Biology Program, School of Integrative Biological and Chemical Sciences, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Richard J Kline
- Biochemistry and Molecular Biology Program, School of Integrative Biological and Chemical Sciences, University of Texas Rio Grande Valley, Brownsville, TX, USA
- School of Earth, Environmental, and Marine Sciences, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Md Saydur Rahman
- Biochemistry and Molecular Biology Program, School of Integrative Biological and Chemical Sciences, University of Texas Rio Grande Valley, Brownsville, TX, USA.
- School of Earth, Environmental, and Marine Sciences, University of Texas Rio Grande Valley, Brownsville, TX, USA.
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12
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Gholipour S, Shamsizadeh Z, Halabowski D, Gwenzi W, Nikaeen M. Combating antibiotic resistance using wastewater surveillance: Significance, applications, challenges, and future directions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 908:168056. [PMID: 37914125 DOI: 10.1016/j.scitotenv.2023.168056] [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] [Received: 07/05/2023] [Revised: 10/19/2023] [Accepted: 10/21/2023] [Indexed: 11/03/2023]
Abstract
The global increase of antibiotic resistance (AR) and resistant infections call for effective surveillance methods for understanding and mitigating (re)-emerging public health risks. Wastewater surveillance (WS) of antibiotic resistance is an emerging, but currently under-utilized decision-support tool in public health systems. Recent years have witnessed an increase in evidence linking antibiotic resistance in wastewaters to that of the community. To date, very few comprehensive reviews exist on the application of WS to understand AR and resistant infections in population. Current and emerging AR detection methods, and their merits and limitations are discussed. Wastewater surveillance has several merits relative to individual testing, including; (1) low per capita testing cost, (2) high spatial coverage, (3) low requirement for diagnostic equipment, and (4) detection of health threats ahead of real outbreaks. The applications of WS as an early warning system and decision support tool to understand and mitigate AR are discussed. Wastewater surveillance could be a tool of choice in low-income settings lacking resources and diagnostic facilities for individual testing. To demonstrate the utility of WS, empirical evidence from field case studies is presented. However, constraints still exist, including; (1) lack of standardized protocols, (2) the clinical utility and sensitivity of WS-based data, (3) uncertainties in relating WS data to pathogenic and virulent bacteria, and (4) whether or not AR in stools and ultimately wastewater represent the complete human resistome. Finally, further prospects are presented, include knowledge gaps on; (1) development of low-cost biosensors for AR, (2) development of WS protocols (sampling, processing, interpretation), (3) further pilot scale studies to understand the opportunities and limits of WS, and (4) development of computer-based analytical tools to facilitate rapid data collection, visualization and interpretation. Therefore, the present paper discusses the principles, opportunities, and constraints of wastewater surveillance applications to understand AR and safeguard public health.
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Affiliation(s)
- Sahar Gholipour
- Department of Environmental Health Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Zahra Shamsizadeh
- Department of Environmental Health Engineering, School of Health, Larestan University of Medical Sciences, Larestan, Iran
| | - Dariusz Halabowski
- University of Lodz, Faculty of Biology and Environmental Protection, Department of Ecology and Vertebrate Zoology, Lodz, Poland
| | - Willis Gwenzi
- Universität Kassel, Fachbereich Ökologische Agrarwissenschaften Fachgebiet Grünlandwissenschaft und Nachwachsende Rohstoffe, Steinstr. 19, 37249 Witzenhausen, Germany; Leibniz-Institut für Agrartechnik und Bioökonomie e.V. Max-Eyth-Allee 100, D-14469 Potsdam, Germany.
| | - Mahnaz Nikaeen
- Department of Environmental Health Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran; Environment Research Center, Research Institute for Primordial Prevention of Non-Communicable Diseases, Isfahan University of Medical Sciences, Isfahan, Iran.
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13
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Rao G, Capone D, Zhu K, Knoble A, Linden Y, Clark R, Lai A, Kim J, Huang CH, Bivins A, Brown J. Simultaneous detection and quantification of multiple pathogen targets in wastewater. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.23.23291792. [PMID: 37425908 PMCID: PMC10327253 DOI: 10.1101/2023.06.23.23291792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Wastewater-based epidemiology has emerged as a critical tool for public health surveillance, building on decades of environmental surveillance work for pathogens such as poliovirus. Work to date has been limited to monitoring a single pathogen or small numbers of pathogens in targeted studies; however, few studies consider simultaneous quantitative analysis of a wide variety of pathogens, which could greatly increase the utility of wastewater surveillance. We developed a novel quantitative multi-pathogen surveillance approach (35 pathogen targets including bacteria, viruses, protozoa, and helminths) using TaqMan Array Cards (TAC) and applied the method on concentrated wastewater samples collected at four wastewater treatment plants in Atlanta, GA from February to October of 2020. From sewersheds serving approximately 2 million people, we detected a wide range of targets including many we expected to find in wastewater (e.g., enterotoxigenic E. coli and Giardia in 97% of 29 samples at stable concentrations) as well as unexpected targets including Strongyloides stercoralis (a human threadworm rarely observed in the USA). Other notable detections included SARS-CoV-2, but also several pathogen targets that are not commonly included in wastewater surveillance like Acanthamoeba spp., Balantidium coli, Entamoeba histolytica, astrovirus, norovirus, and sapovirus. Our data suggest broad utility in expanding the scope of enteric pathogen surveillance in wastewaters, with potential for application in a variety of settings where pathogen quantification in fecal waste streams can inform public health surveillance and selection of control measures to limit infections.
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Affiliation(s)
- Gouthami Rao
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Drew Capone
- Department of Environmental and Occupational Health, School of Public Health, Indiana University, Bloomington, IN, USA
| | - Kevin Zhu
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Abigail Knoble
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yarrow Linden
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ryan Clark
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amanda Lai
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Juhee Kim
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Ching-Hua Huang
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Aaron Bivins
- Department of Civil & Environmental Engineering, Louisiana State University, Baton Rouge, LA, USA
| | - Joe Brown
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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14
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Babler KM, Sharkey ME, Amirali A, Boone MM, Comerford S, Currall BB, Grills GS, Laine J, Mason CE, Reding B, Schürer S, Stevenson M, Vidović D, Williams SL, Solo-Gabriele HM. Expanding a Wastewater-Based Surveillance Methodology for DNA Isolation from a Workflow Optimized for SARS-CoV-2 RNA Quantification. J Biomol Tech 2023; 34:3fc1f5fe.dfa8d906. [PMID: 38268997 PMCID: PMC10805363 DOI: 10.7171/3fc1f5fe.dfa8d906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2024]
Abstract
Wastewater-based surveillance (WBS) is a noninvasive, epidemiological strategy for assessing the spread of COVID-19 in communities. This strategy was based upon wastewater RNA measurements of the viral target, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The utility of WBS for assessing the spread of COVID-19 has motivated research to measure targets beyond SARS-CoV-2, including pathogens containing DNA. The objective of this study was to establish the necessary steps for isolating DNA from wastewater by modifying a long-standing RNA-specific extraction workflow optimized for SARS-CoV-2 detection. Modifications were made to the sample concentration process and included an evaluation of bead bashing prior to the extraction of either DNA or RNA. Results showed that bead bashing reduced detection of RNA from wastewater but improved recovery of DNA as assessed by quantitative polymerase chain reaction (qPCR). Bead bashing is therefore not recommended for the quantification of RNA viruses using qPCR. Whereas for Mycobacterium bacterial DNA isolation, bead bashing was necessary for improving qPCR quantification. Overall, we recommend 2 separate workflows, one for RNA viruses that does not include bead bashing and one for other microbes that use bead bashing for DNA isolation. The experimentation done here shows that current-standing WBS program methodologies optimized for SARS-CoV-2 need to be modified and reoptimized to allow for alternative pathogens to be readily detected and monitored, expanding its utility as a tool for public health assessment.
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Affiliation(s)
- Kristina M. Babler
- Department of ChemicalEnvironmental and Materials
EngineeringUniversity of MiamiCoral GablesFlorida33124USA
| | - Mark E. Sharkey
- Department of MedicineUniversity of Miami Miller School
of MedicineMiamiFlorida33136USA
| | - Ayaaz Amirali
- Department of ChemicalEnvironmental and Materials
EngineeringUniversity of MiamiCoral GablesFlorida33124USA
| | - Melinda M. Boone
- Sylvester Comprehensive Cancer CenterUniversity of Miami
Miller School of MedicineMiamiFlorida33136USA
| | - Samuel Comerford
- Department of MedicineUniversity of Miami Miller School
of MedicineMiamiFlorida33136USA
| | - Benjamin B. Currall
- Sylvester Comprehensive Cancer CenterUniversity of Miami
Miller School of MedicineMiamiFlorida33136USA
| | - George S. Grills
- Sylvester Comprehensive Cancer CenterUniversity of Miami
Miller School of MedicineMiamiFlorida33136USA
| | - Jennifer Laine
- Environmental Health and SafetyUniversity of MiamiMiamiFlorida33136USA
| | - Christopher E. Mason
- Department of Physiology and BiophysicsWeill Cornell
MedicineNew YorkNew York10065USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Al-Saud
Institute for Computational BiomedicineWeill Cornell MedicineNew
YorkNew York10065USA
- The WorldQuant Initiative for Quantitative PredictionWeill Cornell MedicineNew YorkNew YorkUSA 10065USA
| | - Brian Reding
- Environmental Health and SafetyUniversity of MiamiMiamiFlorida33136USA
| | - Stephan Schürer
- Sylvester Comprehensive Cancer CenterUniversity of Miami
Miller School of MedicineMiamiFlorida33136USA
- Department of Molecular and Cellular PharmacologyUniversity of Miami Miller School of MedicineMiamiFlorida33136USA
- Institute for Data Science & Computing, University of
MiamiCoral GablesFlorida33146USA
| | - Mario Stevenson
- Department of MedicineUniversity of Miami Miller School
of MedicineMiamiFlorida33136USA
| | - Dušica Vidović
- Department of Molecular and Cellular PharmacologyUniversity of Miami Miller School of MedicineMiamiFlorida33136USA
| | - Sion L. Williams
- Sylvester Comprehensive Cancer CenterUniversity of Miami
Miller School of MedicineMiamiFlorida33136USA
| | - Helena M. Solo-Gabriele
- Department of ChemicalEnvironmental and Materials
EngineeringUniversity of MiamiCoral GablesFlorida33124USA
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15
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Chen W, Bibby K. Making waves: Establishing a modeling framework to evaluate novel targets for wastewater-based surveillance. WATER RESEARCH 2023; 245:120573. [PMID: 37688859 DOI: 10.1016/j.watres.2023.120573] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 08/27/2023] [Accepted: 09/02/2023] [Indexed: 09/11/2023]
Abstract
Wastewater-based surveillance (WBS) monitoring of pathogens circulating within a community provides an improved understanding of the occurrence and spread of infectious diseases. However, the potential suitability of WBS for novel disease targets is unclear, including many emerging and neglected diseases. The current ad hoc approach of conducting wastewater detection experiments on novel disease targets to determine their suitability for WBS monitoring is resource intensive and may stall investment in this promising technology. In addition, detections, or non-detections, without the context of disease prevalence and shedding by infected individuals are difficult to interpret upon initial WBS target development. In this paper, we present a WBS feasibility analysis framework to identify which diseases are theoretically appropriate for WBS applications and to improve the initial interpretation of target detections. We then discuss five primary factors that influence the probability of detection in WBS monitoring - genome shedding rate, infection rate, per capita wastewater usage, process limit of detection (PLOD), and the number of PCR replicates. Clarifying the relationships between these factors and the likelihood of detection enhances quantitative insights into applying WBS, guiding researchers and stakeholders into mitigating inherent uncertainties of wastewater monitoring and subsequent improvements in WBS outcomes, thereby supporting future investment and expansion of WBS research, especially in novel disease targets.
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Affiliation(s)
- William Chen
- Department of Civil & Environmental Engineering & Earth Sciences, University of Notre Dame, 156 Fitzpatrick Hall, Notre Dame, IN 46556, United States
| | - Kyle Bibby
- Department of Civil & Environmental Engineering & Earth Sciences, University of Notre Dame, 156 Fitzpatrick Hall, Notre Dame, IN 46556, United States.
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16
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Sharkey ME, Babler KM, Shukla BS, Abelson SM, Alsuliman B, Amirali A, Comerford S, Grills GS, Kumar N, Laine J, Lee J, Lamar WE, Mason CE, Penso J, Reding BD, Schürer SC, Stevenson M, Vidović D, Solo-Gabriele HM. Monkeypox viral nucleic acids detected using both DNA and RNA extraction workflows. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 890:164289. [PMID: 37216988 PMCID: PMC10213602 DOI: 10.1016/j.scitotenv.2023.164289] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 05/15/2023] [Accepted: 05/15/2023] [Indexed: 05/24/2023]
Abstract
Molecular methods have been used to detect human pathogens in wastewater with sampling typically performed at wastewater treatment plants (WWTP) and upstream locations within the sewer system. A wastewater-based surveillance (WBS) program was established at the University of Miami (UM) in 2020, which included measurements of SARS-CoV-2 levels in wastewater from its hospital and within the regional WWTP. In addition to the development of a SARS-CoV-2 quantitative PCR (qPCR) assay, qPCR assays to detect other human pathogens of interest were also developed at UM. Here we report on the use of a modified set of reagents published by the CDC to detect nucleic acids of Monkeypox virus (MPXV) which emerged during May of 2022 to become a concern worldwide. Samples collected from the University hospital and from the regional WWTP were processed through DNA and RNA workflows and analyzed by qPCR to detect a segment of the MPXV CrmB gene. Results show positive detections of MPXV nucleic acids in the hospital and wastewater treatment plant wastewater which coincided with clinical cases in the community and mirrored the overall trend of nationwide MPXV cases reported to the CDC. We recommend the expansion of current WBS programs' methods to detect a broader range of pathogens of concern in wastewater and present evidence that viral RNA in human cells infected by a DNA virus can be detected in wastewater.
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Affiliation(s)
- Mark E Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Kristina M Babler
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL, USA
| | - Bhavarth S Shukla
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Samantha M Abelson
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Bader Alsuliman
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Ayaaz Amirali
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL, USA
| | - Samuel Comerford
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - George S Grills
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Naresh Kumar
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jennifer Laine
- Environmental Health and Safety, University of Miami, Miami, FL, USA
| | - Jisue Lee
- University of Miami Health System, Miami, FL, USA
| | - Walter E Lamar
- Facilities Safety & Compliance, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY, USA
| | - Johnathon Penso
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Brian D Reding
- Environmental Health and Safety, University of Miami, Miami, FL, USA
| | - Stephan C Schürer
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA; Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL, USA; Institute for Data Science & Computing, University of Miami, Coral Gables, FL, USA
| | - Mario Stevenson
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Dušica Vidović
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA; Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL, USA
| | - Helena M Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL, USA.
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17
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Bowes D, Darling A, Driver EM, Kaya D, Maal-Bared R, Lee LM, Goodman K, Adhikari S, Aggarwal S, Bivins A, Bohrerova Z, Cohen A, Duvallet C, Elnimeiry RA, Hutchison JM, Kapoor V, Keenum I, Ling F, Sills D, Tiwari A, Vikesland P, Ziels R, Mansfeldt C. Structured Ethical Review for Wastewater-Based Testing in Support of Public Health. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:12969-12980. [PMID: 37611169 PMCID: PMC10484207 DOI: 10.1021/acs.est.3c04529] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 08/09/2023] [Accepted: 08/10/2023] [Indexed: 08/25/2023]
Abstract
Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of WBT measured biomarkers for research activities and for the pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process, introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary workshop developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11 questions derived from primarily public health guidance. This study retrospectively applied these questions to SARS-CoV-2 monitoring programs covering the emergent phase of the pandemic (3/2020-2/2022 (n = 53)). Of note, 43% of answers highlight a lack of reported information to assess. Therefore, a systematic framework would at a minimum structure the communication of ethical considerations for applications of WBT. Consistent application of an ethical review will also assist in developing a practice of updating approaches and techniques to reflect the concerns held by both those practicing and those being monitored by WBT supported programs.
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Affiliation(s)
- Devin
A. Bowes
- Biodesign
Center for Environmental Health Engineering, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave, Tempe, Arizona 85287, United States
- Center on
Forced Displacement, Boston University, 111 Cummington Mall, Boston, Massachusetts 02215, United States
| | - Amanda Darling
- Department
of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, 415 Durham Hall; Blacksburg, Virginia 24061, United States
| | - Erin M. Driver
- Biodesign
Center for Environmental Health Engineering, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave, Tempe, Arizona 85287, United States
| | - Devrim Kaya
- School of
Chemical, Biological, and Environmental Engineering, Oregon State University, 105 26th St, Corvallis, Oregon 97331, United States
- School of
Public Health, San Diego State University, San Diego and Imperial Valley, California 92182, United States
| | - Rasha Maal-Bared
- Quality
Assurance and Environment, EPCOR Water Services Inc., EPCOR Tower, 2000−10423 101
Street NW, Edmonton, Alberta T5H 0E7, Canada
| | - Lisa M. Lee
- Department
of Population Health Sciences and Division of Scholarly Integrity
and Research Compliance, Virginia Tech, 300 Turner St. NW, Suite 4120 (0497), Blacksburg, Virginia 24061, United States
| | - Kenneth Goodman
- Institute
for Bioethics and Health Policy, Miller School of Medicine, University of Miami, Miami, Florida 33101, United States
| | - Sangeet Adhikari
- Biodesign
Center for Environmental Health Engineering, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave, Tempe, Arizona 85287, United States
| | - Srijan Aggarwal
- Department
of Civil, Geological, and Environmental Engineering, University of Alaska Fairbanks, 1764 Tanana Loop, Fairbanks, Alaska 99775, United States
| | - Aaron Bivins
- Department
of Civil & Environmental Engineering, Louisiana State University, 3255 Patrick F. Taylor Hall, Baton Rouge, Louisiana 70803, United States
| | - Zuzana Bohrerova
- The Ohio
State University, Department of Civil, Environmental
and Geodetic Engineering, 2070 Neil Avenue, 470 Hitchcock Hall, Columbus, Ohio 43210, United States
| | - Alasdair Cohen
- Department
of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, 415 Durham Hall; Blacksburg, Virginia 24061, United States
- Department
of Population Health Sciences, Virginia
Tech, 205 Duck Pond Drive, Blacksburg, Virginia 24061, United States
| | - Claire Duvallet
- Biobot
Analytics, Inc., 501
Massachusetts Avenue; Cambridge, Massachusetts 02139, United States
| | - Rasha A. Elnimeiry
- Public
Health Outbreak Coordination, Informatics, Surveillance (PHOCIS) Office—Surveillance
Section, Division of Disease Control and Health Statistics, Washington State Department of Health, 111 Israel Rd SE, Tumwater, Washington 98501, United States
| | - Justin M. Hutchison
- Department
of Civil, Environmental, and Architectural Engineering, University of Kansas, 1530 W 15th St, Lawrence, Kansas 66045, United States
| | - Vikram Kapoor
- School
of Civil & Environmental Engineering, and Construction Management, University of Texas at San Antonio, 1 UTSA Circle, San Antonio, Texas 78249, United States
| | - Ishi Keenum
- Complex
Microbial Systems Group, National Institute
of Standards and Technology, 100 Bureau Dr, Gaithersburg, Maryland 20899, United States
| | - Fangqiong Ling
- Department
of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, One Brookings Drive, St. Louis, Missouri 63130, United States
| | - Deborah Sills
- Department
of Civil and Environmental Engineering, Bucknell University, Lewisburg, Pennsylvania 17837, United States
| | - Ananda Tiwari
- Department
of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Agnes Sjöberginkatu 2,
P.O. Box 66, FI 00014 Helsinki, Finland
- Expert
Microbiology Unit, Finnish Institute for
Health and Welfare, FI 70600 Kuopio, Finland
| | - Peter Vikesland
- Department
of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, 415 Durham Hall; Blacksburg, Virginia 24061, United States
| | - Ryan Ziels
- Department
of Civil Engineering, The University of
British Columbia, 6250
Applied Science Ln #2002, Vancouver, BC V6T 1Z4, Canada
| | - Cresten Mansfeldt
- Department
of Civil, Environmental, and Architectural Engineering, University of Colorado Boulder, UCB 428, Boulder, Colorado 80309, United States
- Environmental
Engineering Program, University of Colorado
Boulder, UCB 607, Boulder, Colorado 80309, United States
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18
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Phan T, Brozak S, Pell B, Oghuan J, Gitter A, Hu T, Ribeiro RM, Ke R, Mena KD, Perelson AS, Kuang Y, Wu F. Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks. WATER RESEARCH 2023; 243:120372. [PMID: 37494742 DOI: 10.1016/j.watres.2023.120372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 07/10/2023] [Accepted: 07/15/2023] [Indexed: 07/28/2023]
Abstract
Wastewater surveillance has proved to be a valuable tool to track the COVID-19 pandemic. However, most studies using wastewater surveillance data revolve around establishing correlations and lead time relative to reported case data. In this perspective, we advocate for the integration of wastewater surveillance data with dynamic within-host and between-host models to better understand, monitor, and predict viral disease outbreaks. Dynamic models overcome emblematic difficulties of using wastewater surveillance data such as establishing the temporal viral shedding profile. Complementarily, wastewater surveillance data bypasses the issues of time lag and underreporting in clinical case report data, thus enhancing the utility and applicability of dynamic models. The integration of wastewater surveillance data with dynamic models can enhance real-time tracking and prevalence estimation, forecast viral transmission and intervention effectiveness, and most importantly, provide a mechanistic understanding of infectious disease dynamics and the driving factors. Dynamic modeling of wastewater surveillance data will advance the development of a predictive and responsive monitoring system to improve pandemic preparedness and population health.
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Affiliation(s)
- Tin Phan
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA
| | - Samantha Brozak
- School of Mathematical and Statistical Sciences, Arizona State University, AZ 85281, USA
| | - Bruce Pell
- Department of Mathematics and Computer Science, Lawrence Technological University, MI 48075, USA
| | - Jeremiah Oghuan
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Anna Gitter
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Tao Hu
- Department of Geography, Oklahoma State University, Stillwater, OK 74078, USA
| | - Ruy M Ribeiro
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA
| | - Ruian Ke
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA
| | - Kristina D Mena
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Texas Epidemic Public Health Institute, Houston, TX 77030, USA
| | - Alan S Perelson
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA; Santa Fe Institute, Santa Fe, NM 87501, USA
| | - Yang Kuang
- School of Mathematical and Statistical Sciences, Arizona State University, AZ 85281, USA
| | - Fuqing Wu
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Texas Epidemic Public Health Institute, Houston, TX 77030, USA.
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19
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Wannigama DL, Amarasiri M, Hongsing P, Hurst C, Modchang C, Chadsuthi S, Anupong S, Phattharapornjaroen P, Rad S. M. AH, Fernandez S, Huang AT, Vatanaprasan P, Jay DJ, Saethang T, Luk-in S, Storer RJ, Ounjai P, Devanga Ragupathi NK, Kanthawee P, Sano D, Furukawa T, Sei K, Leelahavanichkul A, Kanjanabuch T, Hirankarn N, Higgins PG, Kicic A, Singer AC, Chatsuwan T, Trowsdale S, Abe S, McLellan AD, Ishikawa H. COVID-19 monitoring with sparse sampling of sewered and non-sewered wastewater in urban and rural communities. iScience 2023; 26:107019. [PMID: 37351501 PMCID: PMC10250052 DOI: 10.1016/j.isci.2023.107019] [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: 01/18/2023] [Revised: 03/31/2023] [Accepted: 05/30/2023] [Indexed: 06/24/2023] Open
Abstract
Equitable SARS-CoV-2 surveillance in low-resource communities lacking centralized sewers is critical as wastewater-based epidemiology (WBE) progresses. However, large-scale studies on SARS-CoV-2 detection in wastewater from low-and middle-income countries is limited because of economic and technical reasons. In this study, wastewater samples were collected twice a month from 186 urban and rural subdistricts in nine provinces of Thailand mostly having decentralized and non-sewered sanitation infrastructure and analyzed for SARS-CoV-2 RNA variants using allele-specific RT-qPCR. Wastewater SARS-CoV-2 RNA concentration was used to estimate the real-time incidence and time-varying effective reproduction number (Re). Results showed an increase in SARS-CoV-2 RNA concentrations in wastewater from urban and rural areas 14-20 days earlier than infected individuals were officially reported. It also showed that community/food markets were "hot spots" for infected people. This approach offers an opportunity for early detection of transmission surges, allowing preparedness and potentially mitigating significant outbreaks at both spatial and temporal scales.
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Affiliation(s)
- Dhammika Leshan Wannigama
- Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence in Antimicrobial Resistance and Stewardship, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- School of Medicine, Faculty of Health and Medical Sciences, The University of Western Australia, Nedlands, WA, Australia
- Biofilms and Antimicrobial Resistance Consortium of ODA receiving countries, The University of Sheffield, Sheffield, UK
- Pathogen Hunter’s Research Collaborative Team, Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
| | - Mohan Amarasiri
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Kitasato, Sagamihara-Minami, Kanagawa 252-0373, Japan
| | - Parichart Hongsing
- Mae Fah Luang University Hospital, Chiang Rai, Thailand
- School of Integrative Medicine, Mae Fah Luang University, Chiang Rai, Thailand
| | - Cameron Hurst
- Molly Wardaguga Research Centre, Charles Darwin University, Brisbane, QLD, Australia
- Statistics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Charin Modchang
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
- Centre of Excellence in Mathematics, MHESI, Bangkok 10400, Thailand
- Thailand Center of Excellence in Physics, Ministry of Higher Education, Science, Research and Innovation, 328 Si Ayutthaya Road, Bangkok 10400, Thailand
| | - Sudarat Chadsuthi
- Department of Physics, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand
| | - Suparinthon Anupong
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - Phatthranit Phattharapornjaroen
- Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
- Institute of Clinical Sciences, Department of Surgery, Sahlgrenska Academy, Gothenburg University, 40530 Gothenburg, Sweden
| | - Ali Hosseini Rad S. M.
- Department of Microbiology and Immunology, University of Otago, Dunedin, Otago 9010, New Zealand
- Center of Excellence in Immunology and Immune-Mediated Diseases, Chulalongkorn University, Bangkok 10330, Thailand
| | - Stefan Fernandez
- Department of Virology, U.S. Army Medical Directorate, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Angkana T. Huang
- Department of Virology, U.S. Army Medical Directorate, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | | | - Dylan John Jay
- Pathogen Hunter’s Research Collaborative Team, Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
| | - Thammakorn Saethang
- Department of Computer Science, Faculty of Science, Kasetsart University, Bangkok, Thailand
| | - Sirirat Luk-in
- Department of Clinical Microbiology and Applied Technology, Faculty of Medical Technology, Mahidol University, Bangkok, Thailand
| | - Robin James Storer
- Office of Research Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Puey Ounjai
- Department of Biology, Faculty of Science, Mahidol University, Bangkok, Thailand
| | - Naveen Kumar Devanga Ragupathi
- School of Medicine, Faculty of Health and Medical Sciences, The University of Western Australia, Nedlands, WA, Australia
- Department of Chemical and Biological Engineering, The University of Sheffield, Sheffield, UK
- Department of Clinical Microbiology, Christian Medical College, Vellore, India
| | - Phitsanuruk Kanthawee
- Public Health major, School of Health Science, Mae Fah Luang University, Chiang Rai, Thailand
| | - Daisuke Sano
- Department of Frontier Sciences for Advanced Environment, Graduate School of Environmental Studies, Tohoku University, Sendai, Miyagi, Japan
- Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Sendai, Miyagi, Japan
| | - Takashi Furukawa
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Kitasato, Sagamihara-Minami, Kanagawa 252-0373, Japan
| | - Kazunari Sei
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Kitasato, Sagamihara-Minami, Kanagawa 252-0373, Japan
| | - Asada Leelahavanichkul
- Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
- Translational Research in Inflammation and Immunology Research Unit (TRIRU), Department of Microbiology, Chulalongkorn University, Bangkok, Thailand
| | - Talerngsak Kanjanabuch
- Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Center of Excellence in Kidney Metabolic Disorders, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Dialysis Policy and Practice Program (DiP3), School of Global Health, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Peritoneal Dialysis Excellence Center, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - Nattiya Hirankarn
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence in Immunology and Immune-Mediated Diseases, Chulalongkorn University, Bangkok 10330, Thailand
| | - Paul G. Higgins
- Institute for Medical Microbiology, Immunology and Hygiene, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- German Centre for Infection Research, Partner site Bonn-Cologne, Cologne, Germany
| | - Anthony Kicic
- Wal-Yan Respiratory Research Centre, Telethon Kids Institute, University of Western Australia, Nedlands, WA 6009, Australia
- Centre for Cell Therapy and Regenerative Medicine, Medical School, The University of Western Australia, Nedlands, WA 6009, Australia
- Department of Respiratory and Sleep Medicine, Perth Children’s Hospital, Nedlands, WA 6009, Australia
- School of Population Health, Curtin University, Bentley, WA 6102, Australia
| | | | - Tanittha Chatsuwan
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence in Antimicrobial Resistance and Stewardship, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Sam Trowsdale
- Department of Environmental Science, University of Auckland, Auckland 1010, New Zealand
| | - Shuichi Abe
- Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
| | - Alexander D. McLellan
- Department of Microbiology and Immunology, University of Otago, Dunedin, Otago 9010, New Zealand
| | - Hitoshi Ishikawa
- Yamagata Prefectural University of Health Sciences, Kamiyanagi, Yamagata 990-2212, Japan
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20
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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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21
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Bowes DA, Darling A, Driver EM, Kaya D, Maal-Bared R, Lee LM, Goodman K, Adhikari S, Aggarwal S, Bivins A, Bohrerova Z, Cohen A, Duvallet C, Elnimeiry RA, Hutchison JM, Kapoor V, Keenum I, Ling F, Sills D, Tiwari A, Vikesland P, Ziels R, Mansfeldt C. Structured Ethical Review for Wastewater-Based Testing. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.12.23291231. [PMID: 37398480 PMCID: PMC10312843 DOI: 10.1101/2023.06.12.23291231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of the field blurred the boundary between measuring biomarkers for research activities and for pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process (or associated data management safeguards), introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary group developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11-questions derived from primarily public health guidance because of the common exemption of wastewater samples to human subject research considerations. This study retrospectively applied the set of questions to peer- reviewed published reports on SARS-CoV-2 monitoring campaigns covering the emergent phase of the pandemic from March 2020 to February 2022 (n=53). Overall, 43% of the responses to the questions were unable to be assessed because of lack of reported information. It is therefore hypothesized that a systematic framework would at a minimum improve the communication of key ethical considerations for the application of WBT. Consistent application of a standardized ethical review will also assist in developing an engaged practice of critically applying and updating approaches and techniques to reflect the concerns held by both those practicing and being monitored by WBT supported campaigns. Abstract Figure Synopsis Development of a structured ethical review facilitates retrospective analysis of published studies and drafted scenarios in the context of wastewater-based testing.
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Affiliation(s)
- Devin A. Bowes
- Biodesign Center for Environmental Health Engineering, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave, Tempe, AZ, 85287
- Center on Forced Displacement, Boston University, 111 Cummington Mall, Boston, MA, 02215
| | - Amanda Darling
- Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street; 415 Durham Hall; Blacksburg, VA 24061
| | - Erin M. Driver
- Biodesign Center for Environmental Health Engineering, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave, Tempe, AZ, 85287
| | - Devrim Kaya
- School of Chemical, Biological, and Environmental Engineering, Oregon State University, 105 26th St, Corvallis, Oregon 97331
- School of Public Health, San Diego State University, San Diego and Imperial Valley, CA
| | - Rasha Maal-Bared
- Quality Assurance and Environment, EPCOR Water Services Inc., EPCOR Tower, 2000–10423 101 Street NW, Edmonton, Alberta, CA
| | - Lisa M. Lee
- Department of Population Health Sciences and Division of Scholarly Integrity and Research Compliance, Virginia Tech, 300 Turner St. NW, Suite 4120 (0497), Blacksburg, VA 24061
| | - Kenneth Goodman
- Institute for Bioethics and Health Policy, Miller School of Medicine, University of Miami, Miami, Florida
| | - Sangeet Adhikari
- Biodesign Center for Environmental Health Engineering, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave, Tempe, AZ, 85287
| | - Srijan Aggarwal
- Department of Civil, Geological, and Environmental Engineering, University of Alaska Fairbanks, 1764 Tanana Loop, Fairbanks, AK 99775
| | - Aaron Bivins
- Department of Civil & Environmental Engineering, Louisiana State University, 3255 Patrick F. Taylor Hall, Baton Rouge, LA 70803
| | - Zuzana Bohrerova
- The Ohio State University, Department of Civil, Environmental and Geodetic Engineering, 2070 Neil Avenue, 470 Hitchcock Hall, Columbus, OH 43210
| | - Alasdair Cohen
- Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street; 415 Durham Hall; Blacksburg, VA 24061
- Department of Population Health Sciences, Virginia Tech, 205 Duck Pond Drive, Blacksburg, VA 24061
| | - Claire Duvallet
- Biobot Analytics, Inc., 501 Massachusetts Avenue; Cambridge, MA; 02139
| | - Rasha A. Elnimeiry
- Public Health Outbreak Coordination, Informatics, Surveillance (PHOCIS) Office – Surveillance Section, Division of Disease Control and Health Statistics, Washington State Department of Health, 111 Israel Rd SE, Tumwater, WA 98501
| | - Justin M. Hutchison
- Department of Civil, Environmental, and Architectural Engineering, University of Kansas, 1530 W 15th St, Lawrence, KS 66045
| | - Vikram Kapoor
- School of Civil & Environmental Engineering, and Construction Management, University of Texas at San Antonio, 1 UTSA Circle, San Antonio, TX 78249
| | - Ishi Keenum
- Complex Microbial Systems Group, National Institute of Standards and Technology, 100 Bureau Dr, Gaithersburg, MD 20899
| | - Fangqiong Ling
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, One Brookings Drive, St. Louis, MO, 63130
| | - Deborah Sills
- Department of Civil and Environmental Engineering, Bucknell University, Lewisburg, PA, 17837
| | - Ananda Tiwari
- Department of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Agnes Sjöberginkatu 2 P.O. Box 66 FI 00014 Helsinki, Finland
- Expert Microbiology Unit, Finnish Institute for Health and Welfare, Kuopio, Finland
| | - Peter Vikesland
- Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street; 415 Durham Hall; Blacksburg, VA 24061
| | - Ryan Ziels
- Department of Civil Engineering, the University of British Columbia, 6250 Applied Science Ln #2002, Vancouver, BC V6T 1Z4
| | - Cresten Mansfeldt
- Department of Civil, Environmental, and Architectural Engineering, University of Colorado Boulder, UCB 428, Boulder, CO 80309
- Environmental Engineering Program, University of Colorado Boulder, UCB 607, Boulder, CO 80309
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22
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Wang T, Wang C, Myshkevych Y, Mantilla-Calderon D, Talley E, Hong PY. SARS-CoV-2 wastewater-based epidemiology in an enclosed compound: A 2.5-year survey to identify factors contributing to local community dissemination. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 875:162466. [PMID: 36868271 PMCID: PMC9977070 DOI: 10.1016/j.scitotenv.2023.162466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/21/2023] [Accepted: 02/21/2023] [Indexed: 06/18/2023]
Abstract
Long-term (>2.5 years) surveillance of SARS-CoV-2 RNA concentrations in wastewater was conducted within an enclosed university compound. This study aims to demonstrate how coupling wastewater-based epidemiology (WBE) with meta-data can identify which factors contribute toward the dissemination of SARS-CoV-2 within a local community. Throughout the pandemic, the temporal dynamics of SARS-CoV-2 RNA concentrations were tracked by quantitative polymerase chain reaction and analyzed in the context of the number of positive swab cases, the extent of human movement, and intervention measures. Our findings suggest that during the early phase of the pandemic, when strict lockdown was imposed, the viral titer load in the wastewater remained below detection limits, with <4 positive swab cases reported over a 14-day period in the compound. After the lockdown was lifted and global travel gradually resumed, SARS-CoV-2 RNA was first detected in the wastewater on 12 August 2020 and increased in frequency thereafter, despite high vaccination rates and mandatory face-covering requirements in the community. Accompanied by a combination of the Omicron surge and significant global travel by community members, SARS-CoV-2 RNA was detected in most of the weekly wastewater samples collected in late December 2021 and January 2022. With the cease of mandatory face covering, SARS-CoV-2 was detected in at least two of the four weekly wastewater samples collected from May through August 2022. Retrospective Nanopore sequencing revealed the presence of the Omicron variant in the wastewater with a multitude of amino acid mutations, from which we could infer the likely geographical origins through bioinformatic analysis. This study demonstrated that long-term tracking of the temporal dynamics and sequencing of variants in wastewater would aid in identifying which factors contribute the most to SARS-CoV-2 dissemination within the local community, facilitating an appropriate public health response to control future outbreaks as we now live with endemic SARS-CoV-2.
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Affiliation(s)
- Tiannyu Wang
- Water Desalination and Reuse Center, Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Changzhi Wang
- Bioengineering Program, Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Yevhen Myshkevych
- Environmental Science and Engineering Program, Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - David Mantilla-Calderon
- Water Desalination and Reuse Center, Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Erik Talley
- Health, Safety and Environment, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Pei-Ying Hong
- Water Desalination and Reuse Center, Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia; Bioengineering Program, Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia; Environmental Science and Engineering Program, Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.
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23
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Corchis-Scott R, Geng Q, Al Riahi AM, Labak A, Podadera A, Ng KKS, Porter LA, Tong Y, Dixon JC, Menard SL, Seth R, McKay RM. Actionable wastewater surveillance: application to a university residence hall during the transition between Delta and Omicron resurgences of COVID-19. Front Public Health 2023; 11:1139423. [PMID: 37265515 PMCID: PMC10230041 DOI: 10.3389/fpubh.2023.1139423] [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: 01/07/2023] [Accepted: 04/28/2023] [Indexed: 06/03/2023] Open
Abstract
Wastewater surveillance has gained traction during the COVID-19 pandemic as an effective and non-biased means to track community infection. While most surveillance relies on samples collected at municipal wastewater treatment plants, surveillance is more actionable when samples are collected "upstream" where mitigation of transmission is tractable. This report describes the results of wastewater surveillance for SARS-CoV-2 at residence halls on a university campus aimed at preventing outbreak escalation by mitigating community spread. Another goal was to estimate fecal shedding rates of SARS-CoV-2 in a non-clinical setting. Passive sampling devices were deployed in sewer laterals originating from residence halls at a frequency of twice weekly during fall 2021 as the Delta variant of concern continued to circulate across North America. A positive detection as part of routine sampling in late November 2021 triggered daily monitoring and further isolated the signal to a single wing of one residence hall. Detection of SARS-CoV-2 within the wastewater over a period of 3 consecutive days led to a coordinated rapid antigen testing campaign targeting the residence hall occupants and the identification and isolation of infected individuals. With knowledge of the number of individuals testing positive for COVID-19, fecal shedding rates were estimated to range from 3.70 log10 gc ‧ g feces-1 to 5.94 log10 gc ‧ g feces-1. These results reinforce the efficacy of wastewater surveillance as an early indicator of infection in congregate living settings. Detections can trigger public health measures ranging from enhanced communications to targeted coordinated testing and quarantine.
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Affiliation(s)
- Ryland Corchis-Scott
- Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, Canada
| | - Qiudi Geng
- Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, Canada
| | - Abdul Monem Al Riahi
- Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, Canada
| | - Amr Labak
- Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, Canada
| | - Ana Podadera
- Department of Chemistry and Biochemistry, University of Windsor, Windsor, ON, Canada
| | - Kenneth K. S. Ng
- Department of Chemistry and Biochemistry, University of Windsor, Windsor, ON, Canada
| | - Lisa A. Porter
- Department of Biomedical Sciences, University of Windsor, Windsor, ON, Canada
| | - Yufeng Tong
- Department of Chemistry and Biochemistry, University of Windsor, Windsor, ON, Canada
| | - Jess C. Dixon
- Department of Kinesiology, University of Windsor, Windsor, ON, Canada
| | | | - Rajesh Seth
- Civil and Environmental Engineering, University of Windsor, Windsor, ON, Canada
| | - R. Michael McKay
- Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, Canada
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24
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Vo V, Harrington A, Chang CL, Baker H, Moshi MA, Ghani N, Itorralba JY, Tillett RL, Dahlmann E, Basazinew N, Gu R, Familara TD, Boss S, Vanderford F, Ghani M, Tang AJ, Matthews A, Papp K, Khan E, Koutras C, Kan HY, Lockett C, Gerrity D, Oh EC. Identification and genome sequencing of an influenza H3N2 variant in wastewater from elementary schools during a surge of influenza A cases in Las Vegas, Nevada. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 872:162058. [PMID: 36758698 PMCID: PMC9909754 DOI: 10.1016/j.scitotenv.2023.162058] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 02/02/2023] [Accepted: 02/02/2023] [Indexed: 05/25/2023]
Abstract
Real-time surveillance of infectious diseases at schools or in communities is often hampered by delays in reporting due to resource limitations and infrastructure issues. By incorporating quantitative PCR and genome sequencing, wastewater surveillance has been an effective complement to public health surveillance at the community and building-scale for pathogens such as poliovirus, SARS-CoV-2, and even the monkeypox virus. In this study, we asked whether wastewater surveillance programs at elementary schools could be leveraged to detect RNA from influenza viruses shed in wastewater. We monitored for influenza A and B viral RNA in wastewater from six elementary schools from January to May 2022. Quantitative PCR led to the identification of influenza A viral RNA at three schools, which coincided with the lifting of COVID-19 restrictions and a surge in influenza A infections in Las Vegas, Nevada, USA. We performed genome sequencing of wastewater RNA, leading to the identification of a 2021-2022 vaccine-resistant influenza A (H3N2) 3C.2a1b.2a.2 subclade. We next tested wastewater samples from a treatment plant that serviced the elementary schools, but we were unable to detect the presence of influenza A/B RNA. Together, our results demonstrate the utility of near-source wastewater surveillance for the detection of local influenza transmission in schools, which has the potential to be investigated further with paired school-level influenza incidence data.
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Affiliation(s)
- Van Vo
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA; Nevada Institute of Personalized Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Anthony Harrington
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Ching-Lan Chang
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Hayley Baker
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Michael A Moshi
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Nabih Ghani
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Jose Yani Itorralba
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Richard L Tillett
- Nevada Institute of Personalized Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Elizabeth Dahlmann
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Natnael Basazinew
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Richard Gu
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Tiffany D Familara
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Sage Boss
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Fritz Vanderford
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Moonis Ghani
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Austin J Tang
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Alice Matthews
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Katerina Papp
- Southern Nevada Water Authority, P.O. Box 99954, Las Vegas, NV 89193, USA
| | - Eakalak Khan
- Department of Civil and Environmental Engineering and Construction, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Carolina Koutras
- R-Zero Systems, Inc., 345 W Bearcat Dr Suite #100, South Salt Lake, UT 84115, USA
| | - Horng-Yuan Kan
- Southern Nevada Health District, Las Vegas, NV 89106, USA
| | | | - Daniel Gerrity
- Southern Nevada Water Authority, P.O. Box 99954, Las Vegas, NV 89193, USA
| | - Edwin C Oh
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA; Nevada Institute of Personalized Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA; Department of Internal Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA.
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25
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Hart JJ, Jamison MN, McNair JN, Szlag DC. Frequency and degradation of SARS-CoV-2 markers N1, N2, and E in sewage. JOURNAL OF WATER AND HEALTH 2023; 21:514-524. [PMID: 37119151 DOI: 10.2166/wh.2023.314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Coronavirus disease 2019 (COVID-19) is an infectious disease that is mainly spread through aerosolized droplets containing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is excreted in feces by infected individuals. Sewage surveillance has been applied widely to obtain data on the prevalence of COVID-19 in whole communities. We used SARS-CoV-2 gene targets N1, N2, and E to determine the prevalence of COVID-19 at both municipal and building levels. Frequency analysis of wastewater testing indicated that single markers detected only 85% or less of samples that were detected as positive for SARS-CoV-2 with the three markers combined, indicating the necessity of pairing markers to lower the false-negative rate. The best pair of markers in both municipal and building level monitoring was N1 and N2, which correctly identified 98% of positive samples detected with the three markers combined. The degradation rates of all three targets were assessed at two different temperatures (25 and 35 °C) as a possible explanation for observed differences between markers in frequency. Results indicated that all three RNA targets degrade at nearly the same rate, indicating that differences in degradation rate are not responsible for the observed differences in marker frequency.
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Affiliation(s)
- John J Hart
- Oakland University, Department of Chemistry, 146 Library Dr, Rochester, MI 48309, USA E-mail: ; Robert B. Annis Water Resources Institute, 740 West Shoreline Dr, Muskegon, MI 49441, USA
| | - Megan N Jamison
- Oakland University, Department of Chemistry, 146 Library Dr, Rochester, MI 48309, USA E-mail: ; The Ohio State University, 281 W Lane Ave, Columbus, OH 43210, USA
| | - James N McNair
- Robert B. Annis Water Resources Institute, 740 West Shoreline Dr, Muskegon, MI 49441, USA
| | - David C Szlag
- Oakland University, Department of Chemistry, 146 Library Dr, Rochester, MI 48309, USA E-mail:
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26
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Dehghan Banadaki M, Torabi S, Strike WD, Noble A, Keck JW, Berry SM. Improving wastewater-based epidemiology performance through streamlined automation. JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING 2023; 11:109595. [PMID: 36875746 PMCID: PMC9970922 DOI: 10.1016/j.jece.2023.109595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 02/02/2023] [Accepted: 02/26/2023] [Indexed: 06/18/2023]
Abstract
Wastewater-based epidemiology (WBE) has enabled us to describe Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections in populations. However, implementation of wastewater monitoring of SARS-CoV-2 is limited due to the need for expert staff, expensive equipment, and prolonged processing times. As WBE increases in scope (beyond SARS-CoV-2) and scale (beyond developed regions), there is a need to make WBE processes simpler, cheaper, and faster. We developed an automated workflow based on a simplified method termed exclusion-based sample preparation (ESP). Our automated workflow takes 40 min from raw wastewater to purified RNA, which is several times faster than conventional WBE methods. The total assay cost per sample/replicate is $6.50 which includes consumables and reagents for concentration, extraction, and RT-qPCR quantification. The assay complexity is reduced significantly, as extraction and concentration steps are integrated and automated. The high recovery efficiency of the automated assay (84.5 ± 25.4%) yielded an improved Limit of Detection (LoDAutomated=40 copies/mL) compared to the manual process (LoDManual=206 copies/mL), increasing analytical sensitivity. We validated the performance of the automated workflow by comparing it with the manual method using wastewater samples from several locations. The results from the two methods correlated strongly (r = 0.953), while the automated method was shown to be more precise. In 83% of the samples, the automated method showed lower variation between replicates, which is likely due to higher technical errors in the manual process e.g., pipetting. Our automated wastewater workflow can support the expansion of WBE in the fight against Coronavirus Disease of 2019 (COVID-19) and other epidemics.
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Affiliation(s)
| | - Soroosh Torabi
- Department of Mechanical Engineering, College of Engineering, University of Kentucky, United States
| | - William D Strike
- Department of Biomedical Engineering, College of Engineering, University of Kentucky, United States
| | - Ann Noble
- Department of Mechanical Engineering, College of Engineering, University of Kentucky, United States
| | - James W Keck
- Department of Family and Community Medicine, College of Medicine, University of Kentucky, United States
| | - Scott M Berry
- Department of Mechanical Engineering, College of Engineering, University of Kentucky, United States
- Department of Biomedical Engineering, College of Engineering, University of Kentucky, United States
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27
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Babler KM, Sharkey ME, Abelson S, Amirali A, Benitez A, Cosculluela GA, Grills GS, Kumar N, Laine J, Lamar W, Lamm ED, Lyu J, Mason CE, McCabe PM, Raghavender J, Reding BD, Roca MA, Schürer SC, Stevenson M, Szeto A, Tallon JJ, Vidović D, Zarnegarnia Y, Solo-Gabriele HM. Degradation rates influence the ability of composite samples to represent 24-hourly means of SARS-CoV-2 and other microbiological target measures in wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 867:161423. [PMID: 36623667 PMCID: PMC9817413 DOI: 10.1016/j.scitotenv.2023.161423] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 12/25/2022] [Accepted: 01/02/2023] [Indexed: 06/17/2023]
Abstract
The utility of using severe-acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA for assessing the prevalence of COVID-19 within communities begins with the design of the sample collection program. The objective of this study was to assess the utility of 24-hour composites as representative samples for measuring multiple microbiological targets in wastewater, and whether normalization of SARS-CoV-2 by endogenous targets can be used to decrease hour to hour variability at different watershed scales. Two sets of experiments were conducted, in tandem with the same wastewater, with samples collected at the building, cluster, and community sewershed scales. The first set of experiments focused on evaluating degradation of microbiological targets: SARS-CoV-2, Simian Immunodeficiency Virus (SIV) - a surrogate spiked into the wastewater, plus human waste indicators of Pepper Mild Mottle Virus (PMMoV), Beta-2 microglobulin (B2M), and fecal coliform bacteria (FC). The second focused on the variability of these targets from samples, collected each hour on the hour. Results show that SARS-CoV-2, PMMoV, and B2M were relatively stable, with minimal degradation over 24-h. SIV, which was spiked-in prior to analysis, degraded significantly and FC increased significantly over the course of 24 h, emphasizing the possibility for decay and growth within wastewater. Hour-to-hour variability of the source wastewater was large between each hour of sampling relative to the variability of the SARS-CoV-2 levels calculated between sewershed scales; thus, differences in SARS-CoV-2 hourly variability were not statistically significant between sewershed scales. Results further provided that the quantified representativeness of 24-h composite samples (i.e., statistical equivalency compared against hourly collected grabs) was dependent upon the molecular target measured. Overall, improvements made by normalization were minimal within this study. Degradation and multiplication for other targets should be evaluated when deciding upon whether to collect composite or grab samples in future studies.
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Affiliation(s)
- Kristina M Babler
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Mark E Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Samantha Abelson
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Ayaaz Amirali
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Aymara Benitez
- Miami-Dade Water and Sewer Department, Miami, FL 33149, USA
| | - Gabriella A Cosculluela
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - George S Grills
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Naresh Kumar
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Jennifer Laine
- Environmental Health and Safety, University of Miami, Miami, FL 33136, USA
| | - Walter Lamar
- Division of Occupational Health, Safety & Compliance, University of Miami Health System, Miami, FL 33136, USA
| | - Erik D Lamm
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Jiangnan Lyu
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY 10021, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA; The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY 10021, USA
| | - Philip M McCabe
- Department of Psychology, University of Miami, Coral Gables, FL 33146, USA; Department of Biomedical Engineering, University of Miami, Coral Gables, FL 33146, USA
| | | | - Brian D Reding
- Environmental Health and Safety, University of Miami, Miami, FL 33136, USA
| | - Matthew A Roca
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Stephan C Schürer
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Institute for Data Science & Computing, University of Miami, Coral Gables, FL, USA
| | - Mario Stevenson
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Angela Szeto
- Department of Psychology, University of Miami, Coral Gables, FL 33146, USA
| | - John J Tallon
- Facilities and Operations, University of Miami, Coral Gables, FL 33146, USA
| | - Dusica Vidović
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Yalda Zarnegarnia
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Helena M Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA.
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28
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Brooks YM, Gryskwicz B, Sidaway E, Shelley B, Coroi L, Downing M, Downing T, McDonnell S, Ostrye D, Hoop K, Parrish G. A case study of a community-organized wastewater surveillance in a small community: correlating weekly reported COVID-19 cases with SARS-CoV-2 RNA concentrations during fall 2020 to summer 2021 in Yarmouth, ME. JOURNAL OF WATER AND HEALTH 2023; 21:329-342. [PMID: 37338313 PMCID: wh_2023_238 DOI: 10.2166/wh.2023.238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
Wastewater surveillance offers a rapid evaluation of SARS-CoV-2 transmission in a community. We describe how a community group, the Yarmouth Wastewater Testing Team (YWTT), in Yarmouth, Maine, (population 8,990) utilized an asset-based community design framework to organize and manage a program to monitor SARS-CoV-2 RNA concentrations. From September 22, 2020 through June 8, 2021, the YWTT disseminated weekly reports of the wastewater results and reported COVID-19 cases within the Yarmouth postal code. After high and increasing SARS-CoV-2 RNA concentrations, the YWTT issued two community advisories to encourage extra care to reduce exposure. Correlations between SARS-CoV-2 RNA concentrations and COVID-19 cases were stronger the week after sampling, and the average of the COVID-19 cases during the week of sampling and the following week, indicating that surveillance provided advance notice of cases. A 10% increase in SARS-CoV-2 RNA concentrations was associated with a 13.29% increase in the average number of weekly reported cases of COVID-19 during the week of sampling and the following week (R2 = 0.42; p < 0.001). Adjusting for viral recovery (December 21, 2020 through June 8, 2021), improved R2 from 0.60 to 0.68. Wastewater surveillance was an effective tool for the YWTT to quickly respond to viral transmission.
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Affiliation(s)
- Yolanda M Brooks
- Department of Sciences, St. Joseph's College of Maine, 278 White's Bridge Rd, Standish, ME 04084, USA E-mail: ;
| | - Bailey Gryskwicz
- Department of Sciences, St. Joseph's College of Maine, 278 White's Bridge Rd, Standish, ME 04084, USA E-mail: ;
| | - Eilidh Sidaway
- Department of Sciences, St. Joseph's College of Maine, 278 White's Bridge Rd, Standish, ME 04084, USA E-mail: ;
| | - Brianna Shelley
- Department of Sciences, St. Joseph's College of Maine, 278 White's Bridge Rd, Standish, ME 04084, USA E-mail: ;
| | - Laura Coroi
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Margaret Downing
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Tom Downing
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Sharon McDonnell
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Dan Ostrye
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Katrina Hoop
- Department of Social Sciences, University of Maine at Augusta, 46 University Drive, Augusta, ME 04330, USA
| | - Gib Parrish
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
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29
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Li Q, Lee BE, Gao T, Qiu Y, Ellehoj E, Yu J, Diggle M, Tipples G, Maal-Bared R, Hinshaw D, Sikora C, Ashbolt NJ, Talbot J, Hrudey SE, Pang X. Number of COVID-19 cases required in a population to detect SARS-CoV-2 RNA in wastewater in the province of Alberta, Canada: Sensitivity assessment. J Environ Sci (China) 2023; 125:843-850. [PMID: 36375966 PMCID: PMC9068596 DOI: 10.1016/j.jes.2022.04.047] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 04/24/2022] [Accepted: 04/27/2022] [Indexed: 05/03/2023]
Abstract
With a unique and large size of testing results of 1,842 samples collected from 12 wastewater treatment plants (WWTP) for 14 months through from low to high prevalence of COVID-19, the sensitivity of RT-qPCR detection of SARS-CoV-2 RNA in wastewater that correspond to the communities was computed by using Probit analysis. This study determined the number of new COVID-19 cases per 100,000 population required to detect SARS-CoV-2 RNA in wastewater at defined probabilities and provided an evidence-based framework of wastewater-based epidemiology surveillance (WBE). Input data were positive and negative test results of SARS-CoV-2 RNA in wastewater samples and the corresponding new COVID-19 case rates per 100,000 population served by each WWTP. The analyses determined that RT-qPCR-based SARS-CoV-2 RNA detection threshold at 50%, 80% and 99% probability required a median of 8 (range: 4-19), 18 (9-43), and 38 (17-97) of new COVID-19 cases /100,000, respectively. Namely, the positive detection rate at 50%, 80% and 99% probability were 0.01%, 0.02%, and 0.04% averagely for new cases in the population. This study improves understanding of the performance of WBE SARS-CoV-2 RNA detection using the large datasets and prolonged study period. Estimated COVID-19 burden at a community level that would result in a positive detection of SARS-CoV-2 in wastewater is critical to support WBE application as a supplementary warning/monitoring system for COVID-19 prevention and control.
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Affiliation(s)
- Qiaozhi Li
- School of Public Health, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Bonita E Lee
- Department of Pediatrics, University of Alberta, Edmonton, AB T6G 1C9, Canada
| | - Tiejun Gao
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada
| | - Yuanyuan Qiu
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada
| | - Erik Ellehoj
- University of Alberta Central Receiving, Edmonton, Alberta, T6G 2R3, Canada
| | - Jiaao Yu
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada
| | - Mathew Diggle
- Provincial Laboratory for Public Health, Edmonton, Alberta, Canada
| | - Graham Tipples
- Provincial Laboratory for Public Health, Edmonton, Alberta, Canada
| | | | - Deena Hinshaw
- Department of Medicine, University of Alberta, Edmonton, AB T6G 2G3, Canada
| | - Christopher Sikora
- Department of Medicine, University of Alberta, Edmonton, AB T6G 2G3, Canada
| | - Nicholas J Ashbolt
- Faculty of Science and Engineering, Southern Cross University, East Lismore NSW 2480, Australia
| | - James Talbot
- Department of Medicine, University of Alberta, Edmonton, AB T6G 2G3, Canada
| | - Steve E Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada
| | - Xiaoli Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada; Provincial Laboratory for Public Health, Edmonton, Alberta, Canada.
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30
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Sangsanont J, Rattanakul S, Makkaew P, Precha N, Rukthanapitak P, Sresung M, Siri Y, Kitajima M, Takeda T, Haramoto E, Puenpa J, Wanlapakorn N, Poovorawan Y, Mongkolsuk S, Sirikanchana K. Wastewater monitoring in tourist cities as potential sentinel sites for near real-time dynamics of imported SARS-CoV-2 variants. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 860:160317. [PMID: 36436629 PMCID: PMC9691270 DOI: 10.1016/j.scitotenv.2022.160317] [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] [Received: 08/20/2022] [Revised: 10/29/2022] [Accepted: 11/16/2022] [Indexed: 05/05/2023]
Abstract
Wastewater-based epidemiology (WBE) complements the clinical surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants' distribution in populations. Many developed nations have established national and regional WBE systems; however, governance and budget constraints could be obstacles for low- and middle-income countries. An urgent need thus exists to identify hotspots to serve as sentinel sites for WBE. We hypothesized that representative wastewater treatment plants (WWTPs) in two international gateway cities, Bangkok and Phuket, Thailand, could be sentineled for SARS-CoV-2 and its variants to reflect the clinical distribution patterns at city level and serve as early indicators of new variants entering the country. Municipal wastewater samples (n = 132) were collected from eight representative municipal WWTPs in Bangkok and Phuket during 19 sampling events from October 2021 to March 2022, which were tested by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) using the US CDC N1 and N2 multiplex and variant (Alpha, Delta, and Omicron BA.1 and BA.2) singleplex assays. The variant detection ratios from Bangkok and Phuket followed similar trends to the national clinical testing data, and each variant's viral loads agreed with the daily new cases (3-d moving average). Omicron BA.1 was detected in Phuket wastewater prior to Bangkok, possibly due to Phuket's WWTPs serving tourist communities. We found that the Omicron BA.1 and BA.2 viral loads predominantly drove the SARS-CoV-2 resurgence. We also noted a shifting pattern in the Bangkok WBE from a 22-d early warning in early 2021 to a near real-time pattern in late 2021. The potential application of tourist hotspots for WBE to indicate the arrival of new variants and re-emerging or unprecedented infectious agents could support tourism-dependent economies by complementing the reduced clinical regulations while maintaining public health protection via wastewater surveillance.
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Affiliation(s)
- Jatuwat Sangsanont
- Department of Environmental Science, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand; Water Science and Technology for Sustainable Environmental Research Group, Chulalongkorn University, Bangkok 10330, Thailand
| | - Surapong Rattanakul
- Department of Environmental Engineering, Faculty of Engineering, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand
| | - Prasert Makkaew
- Department of Environmental Health and Technology, School of Public Health, Walailak University, Nakhon Si Thammarat 80160, Thailand; One Health Research Center, Walailak University, Nakhon Si Thammarat 80160, Thailand
| | - Nopadol Precha
- Department of Environmental Health and Technology, School of Public Health, Walailak University, Nakhon Si Thammarat 80160, Thailand; One Health Research Center, Walailak University, Nakhon Si Thammarat 80160, Thailand
| | - Pratchaya Rukthanapitak
- Department of Environmental Science, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Montakarn Sresung
- Research Laboratory of Biotechnology, Chulabhorn Research Institute, Bangkok 10210, Thailand
| | - Yadpiroon Siri
- Environmental, Safety Technology and Health Program, School of Public Health, Walailak University, Thaiburi, Thasala, Nakhon Si Thammarat 80160, Thailand
| | - Masaaki Kitajima
- Division of Environmental Engineering, Hokkaido University, Hokkaido 060-8628, Japan
| | - Tomoko Takeda
- Department of Earth and Planetary Science, The University of Tokyo, 113-0033, Japan
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, Yamanashi 400-8511, Japan
| | - Jiratchaya Puenpa
- Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Nasamon Wanlapakorn
- Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Yong Poovorawan
- Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Skorn Mongkolsuk
- Research Laboratory of Biotechnology, Chulabhorn Research Institute, Bangkok 10210, Thailand; Center of Excellence on Environmental Health and Toxicology (EHT), OPS, MHESI, Bangkok 10400, Thailand
| | - Kwanrawee Sirikanchana
- Research Laboratory of Biotechnology, Chulabhorn Research Institute, Bangkok 10210, Thailand; Center of Excellence on Environmental Health and Toxicology (EHT), OPS, MHESI, Bangkok 10400, Thailand.
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31
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Early detection of local SARS-CoV-2 outbreaks by wastewater surveillance: a feasibility study. Epidemiol Infect 2023; 151:e28. [PMID: 36722251 PMCID: PMC9990400 DOI: 10.1017/s0950268823000146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Wastewater surveillance and quantitative analysis of SARS-CoV-2 RNA are increasingly used to monitor the spread of COVID-19 in the community. We studied the feasibility of applying the surveillance data for early detection of local outbreaks. A Monte Carlo simulation model was constructed, applying data on reported variation in RNA gene copy concentration in faeces and faecal masses shed. It showed that, even with a constant number of SARS-CoV-2 RNA shedders, the variation in concentrations found in wastewater samples will be large, and that it will be challenging to translate viral concentrations into incidence estimates, especially when the number of shedders is low. Potential signals for early detection of hypothetical outbreaks were analysed for their performance in terms of sensitivity and specificity of the signals. The results suggest that a sudden increase in incidence is not easily identified on the basis of wastewater surveillance data, especially in small sampling areas and in low-incidence situations. However, with a high number of shedders and when combining data from multiple consecutive tests, the performance of wastewater sampling is expected to improve considerably. The developed modelling approach can increase our understanding of the results from wastewater surveillance of SARS-CoV-2.
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32
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Gagliano E, Biondi D, Roccaro P. Wastewater-based epidemiology approach: The learning lessons from COVID-19 pandemic and the development of novel guidelines for future pandemics. CHEMOSPHERE 2023; 313:137361. [PMID: 36427570 PMCID: PMC9678975 DOI: 10.1016/j.chemosphere.2022.137361] [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] [Received: 08/30/2022] [Revised: 11/20/2022] [Accepted: 11/21/2022] [Indexed: 05/05/2023]
Abstract
Wastewater-based epidemiology (WBE) provides a comprehensive real-time framework of population attitude and health status. This approach is attracting the interest of medical community and health authorities to monitor the prevalence of a virus (such as the severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) among a community. Indeed, WBE is currently fine-tuning as environmental surveillance tool for coronavirus disease 2019 (COVID-19) pandemic. After a bibliometric analysis conducted to discover the research trends in WBE field, this work aimed to side-by-side compare the conventional method based on clinical testing with WBE approach. Furthermore, novel guidelines were developed to apply the WBE approach to a pandemic. The growing interest on WBE approach for COVID-19 pandemic is demonstrated by looking at the sharp increase in scientific papers published in the last years and at the ongoing studies on viral quantification methods and analytical procedures. The side-by-side comparison highlighted the ability of WBE to identify the hot-spot areas faster than the conventional approach, reducing the costs (e.g., rational use of available resources) and the gatherings at medical centers. Contrary to clinical testing, WBE has the surveillance capacity for preventing the virus resurgence, including asymptomatic contribution, and ensuring the preservation of medical staff health by avoiding the exposure to the virus infection during clinical testing. As extensively reported, the time in collecting epidemiological data is crucial for establishing the prevention and mitigation measures that are essential for curbing a pandemic. The developed guidelines can help to build a WBE system useful to control any future pandemic.
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Affiliation(s)
- Erica Gagliano
- Department of Civil Engineering and Architecture, University of Catania, Catania, Italy; Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, Italy
| | - Deborah Biondi
- Department of Civil Engineering and Architecture, University of Catania, Catania, Italy
| | - Paolo Roccaro
- Department of Civil Engineering and Architecture, University of Catania, Catania, Italy.
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33
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Barber C, Crank K, Papp K, Innes GK, Schmitz BW, Chavez J, Rossi A, Gerrity D. Community-Scale Wastewater Surveillance of Candida auris during an Ongoing Outbreak in Southern Nevada. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:1755-1763. [PMID: 36656763 PMCID: PMC9893721 DOI: 10.1021/acs.est.2c07763] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 12/21/2022] [Accepted: 12/22/2022] [Indexed: 05/29/2023]
Abstract
Candida auris is an opportunistic fungal pathogen and an emerging global public health threat, given its high mortality among infected individuals, antifungal resistance, and persistence in healthcare environments. This study explored the applicability of wastewater surveillance for C. auris in a metropolitan area with reported outbreaks across multiple healthcare facilities. Influent or primary effluent samples were collected over 10 weeks from seven sewersheds in Southern Nevada. Pelleted solids were analyzed using an adapted quantitative polymerase chain reaction (qPCR) assay targeting the ITS2 region of the C. auris genome. Positive detection was observed in 72 of 91 samples (79%), with higher detection frequencies in sewersheds serving healthcare facilities involved in the outbreak (94 vs 20% sample positivity). Influent wastewater concentrations ranged from 2.8 to 5.7 log10 gene copies per liter (gc/L), and primary clarification achieved an average log reduction value (LRV) of 1.24 ± 0.34. Presumptive negative surface water and wastewater controls were non-detect. These results demonstrate that wastewater surveillance may assist in tracking the spread of C. auris and serve as an early warning tool for public health action. These findings provide the foundation for future application of wastewater-based epidemiology (WBE) to community- or facility-level surveillance of C. auris and other high consequence, healthcare-associated infectious agents.
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Affiliation(s)
- Casey Barber
- School
of Public Health, University of Nevada Las
Vegas, 4700 S. Maryland Parkway, Las Vegas, Nevada 89119, United States
- Southern
Nevada Water Authority, P.O. Box 99954, Las Vegas, Nevada 89193, United States
| | - Katherine Crank
- Southern
Nevada Water Authority, P.O. Box 99954, Las Vegas, Nevada 89193, United States
| | - Katerina Papp
- Southern
Nevada Water Authority, P.O. Box 99954, Las Vegas, Nevada 89193, United States
| | - Gabriel K. Innes
- Yuma
Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8th Street, Yuma, Arizona 85364, United States
| | - Bradley W. Schmitz
- Yuma
Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8th Street, Yuma, Arizona 85364, United States
| | - Jorge Chavez
- Utah
Department of Health and Human Services, Utah Public Health Laboratory, 4431 South 2700 West, Taylorsville, Utah 84129, United States
| | - Alessandro Rossi
- Utah
Department of Health and Human Services, Utah Public Health Laboratory, 4431 South 2700 West, Taylorsville, Utah 84129, United States
| | - Daniel Gerrity
- Southern
Nevada Water Authority, P.O. Box 99954, Las Vegas, Nevada 89193, United States
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34
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Phan T, Brozak S, Pell B, Gitter A, Xiao A, Mena KD, Kuang Y, Wu F. A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159326. [PMID: 36220466 PMCID: PMC9547654 DOI: 10.1016/j.scitotenv.2022.159326] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 09/15/2022] [Accepted: 10/05/2022] [Indexed: 06/12/2023]
Abstract
Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor SARS-CoV-2 transmission. However, epidemiological inference from WBS data remains understudied and limits its application. In this study, we have established a quantitative framework to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission through integrating WBS data into an SEIR-V model. We conceptually divide the individual-level viral shedding course into exposed, infectious, and recovery phases as an analogy to the compartments in a population-level SEIR model. We demonstrated that the effect of temperature on viral losses in the sewer can be straightforwardly incorporated in our framework. Using WBS data from the second wave of the pandemic (Oct 02, 2020-Jan 25, 2021) in the Greater Boston area, we showed that the SEIR-V model successfully recapitulates the temporal dynamics of viral load in wastewater and predicts the true number of cases peaked earlier and higher than the number of reported cases by 6-16 days and 8.3-10.2 folds (R = 0.93). This work showcases a simple yet effective method to bridge WBS and quantitative epidemiological modeling to estimate the prevalence and transmission of SARS-CoV-2 in the sewershed, which could facilitate the application of wastewater surveillance of infectious diseases for epidemiological inference and inform public health actions.
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Affiliation(s)
- Tin Phan
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, NM, USA
| | - Samantha Brozak
- School of Mathematical and Statistical Sciences, Arizona State University, AZ, USA
| | - Bruce Pell
- Department of Mathematics and Computer Science, Lawrence Technological University, MI, USA
| | - Anna Gitter
- The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA 77030
| | - Amy Xiao
- Center for Microbiome Informatics and Therapeutics; Department of Biological Engineering, Massachusetts Institute of Technology
| | - Kristina D Mena
- The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA 77030
| | - Yang Kuang
- School of Mathematical and Statistical Sciences, Arizona State University, AZ, USA.
| | - Fuqing Wu
- The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA 77030.
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35
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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: 3] [Impact Index Per Article: 3.0] [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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36
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Prasek SM, Pepper IL, Innes GK, Slinski S, Betancourt WQ, Foster AR, Yaglom HD, Porter WT, Engelthaler DM, Schmitz BW. Variant-specific SARS-CoV-2 shedding rates in wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159165. [PMID: 36195153 PMCID: PMC9527179 DOI: 10.1016/j.scitotenv.2022.159165] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 09/23/2022] [Accepted: 09/28/2022] [Indexed: 05/21/2023]
Abstract
Previous studies show that SARS-CoV-2 waste shedding rates vary by community and are influenced by multiple factors; however, differences in shedding rates across multiple variants have yet to be evaluated. The purpose of this work is to build on previous research that evaluated waste shedding rates for early SARS-CoV-2 and the Delta variant, and update population level waste shedding rates for the more-recent Omicron variant in six communities. Mean SARS-CoV-2 waste shedding rates were found to increase with the predominance of the Delta variant and subsequently decrease with Omicron infections. Interestingly, the Delta stage had the highest mean shedding rates and was associated with the most severe disease symptoms reported in other clinical studies, while Omicron, exhibiting reduced symptoms, had the lowest mean shedding rates. Additionally, shedding rates were most consistent across communities during the Omicron stage. This is the first paper to identify waste shedding rates specific to the Omicron variant and fills a knowledge gap critical to disease prevalence modeling.
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Affiliation(s)
- Sarah M Prasek
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Ian L Pepper
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Gabriel K Innes
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8th St., Yuma, AZ 85364, USA
| | - Stephanie Slinski
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8th St., Yuma, AZ 85364, USA
| | - Walter Q Betancourt
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Aidan R Foster
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Hayley D Yaglom
- The Translational Genomics Research Institute (TGen), 445 N. Fifth Street, Phoenix, AZ 85004, USA
| | - W Tanner Porter
- The Translational Genomics Research Institute (TGen), 445 N. Fifth Street, Phoenix, AZ 85004, USA
| | - David M Engelthaler
- The Translational Genomics Research Institute (TGen), 445 N. Fifth Street, Phoenix, AZ 85004, USA
| | - Bradley W Schmitz
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8th St., Yuma, AZ 85364, USA.
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37
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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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38
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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: 15] [Impact Index Per Article: 15.0] [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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39
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SARS-CoV-2 RNA levels in Scotland’s wastewater. Sci Data 2022; 9:713. [PMID: 36400814 PMCID: PMC9674653 DOI: 10.1038/s41597-022-01788-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 10/18/2022] [Indexed: 11/21/2022] Open
Abstract
Nationwide, wastewater-based monitoring was newly established in Scotland to track the levels of SARS-CoV-2 viral RNA shed into the sewage network, during the COVID-19 pandemic. We present a curated, reference dataset produced by this national programme, from May 2020 to February 2022. Viral levels were analysed by RT-qPCR assays of the N1 gene, on RNA extracted from wastewater sampled at 162 locations. Locations were sampled up to four times per week, typically once or twice per week, and in response to local needs. We report sampling site locations with geographical coordinates, the total population in the catchment for each site, and the information necessary for data normalisation, such as the incoming wastewater flow values and ammonia concentration, when these were available. The methodology for viral quantification and data analysis is briefly described, with links to detailed protocols online. These wastewater data are contributing to estimates of disease prevalence and the viral reproduction number (R) in Scotland and in the UK. Measurement(s) | RNA viral genome | Technology Type(s) | quantitative reverse transcription polymerase chain reaction assay | Factor Type(s) | Geographical coordinate - Lat • Geographical coordinate - Long • Flow rate • Human population • Ammonia concentration • Sample collection date | Sample Characteristic - Organism | SARS Coronavirus 2 | Sample Characteristic - Environment | wastewater treatment plant • sewage | Sample Characteristic - Location | Scotland |
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40
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Gerrity D, Papp K, Pecson BM. Pathogen Peak "Averaging" in Potable Reuse Systems: Lessons Learned from Wastewater Surveillance of SARS-CoV-2. ACS ES&T WATER 2022; 2:1863-1870. [PMID: 37566355 PMCID: PMC8791031 DOI: 10.1021/acsestwater.1c00378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 11/19/2021] [Accepted: 11/29/2021] [Indexed: 05/10/2023]
Abstract
This study describes wastewater concentrations of SARS-CoV-2 at seven different sampling locations in Southern Nevada (ranging from 4.2 to 8.7 log10 gc/L) and highlights several key variables affecting those concentrations, including COVID-19 incidence, sample type, and service area population. This information is important for implementing wastewater-based epidemiology, but it also provides insight relevant to the design and regulation of potable reuse systems. Specifically, smaller systems may be more prone to influent concentration spikes that can drive enteric pathogen risk during disease outbreaks. It may be possible to leverage reactor hydraulics to achieve peak "averaging" in these scenarios, although it then becomes important to consider how elevated risks at the lower percentiles potentially offset benefits at the upper percentiles. Informed by SARS-CoV-2 concentration dynamics, the current study simulated relative risk for a hypothetical enteric pathogen. Simulated reactor hydraulics (i.e., dispersion) increased pathogen concentrations by up to 2.6 logs at lower percentiles but also decreased concentrations by up to 1.1 logs at the upper percentiles that sometimes drive public health risk. Collectively, these data highlight the importance of considering outbreak conditions, pathogen spikes, and peak "averaging" in the design and operation of treatment systems and in the development of regulatory frameworks.
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Affiliation(s)
- Daniel Gerrity
- Applied Research and Development Center,
Southern Nevada Water Authority, Las Vegas, Nevada 89193,
United States
| | - Katerina Papp
- Applied Research and Development Center,
Southern Nevada Water Authority, Las Vegas, Nevada 89193,
United States
| | - Brian M. Pecson
- Trussell Technologies,
Inc., Oakland, California 94612, United States
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41
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McMahan CS, Lewis D, Deaver JA, Dean D, Rennert L, Kalbaugh CA, Shi L, Kriebel D, Graves D, Popat SC, Karanfil T, Freedman DL. Predicting COVID-19 Infected Individuals in a Defined Population from Wastewater RNA Data. ACS ES&T WATER 2022; 2:2225-2232. [PMID: 37406033 PMCID: PMC9331160 DOI: 10.1021/acsestwater.2c00105] [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: 02/27/2022] [Revised: 06/27/2022] [Accepted: 06/29/2022] [Indexed: 06/04/2023]
Abstract
Wastewater surveillance of SARS-CoV-2 RNA has become an important tool for tracking the presence of the virus and serving as an early indicator for the onset of rapid transmission. Nevertheless, wastewater data are still not commonly used to predict the number of infected individuals in a sewershed. The main objective of this study was to calibrate a susceptible-exposed-infectious-recovered (SEIR) model using RNA copy rates in sewage (i.e., gene copies per liter times flow rate) and the number of SARS-CoV-2 saliva-test-positive infected individuals in a university student population that was subject to repeated weekly testing during the Spring 2021 semester. A strong correlation was observed between the RNA copy rates and the number of infected individuals. The parameter in the SEIR model that had the largest impact on calibration was the maximum shedding rate, resulting in a mean value of 7.72 log10 genome copies per gram of feces. Regressing the saliva-test-positive infected individuals on predictions from the SEIR model based on the RNA copy rates yielded a slope of 0.87 (SE=0.11), which is statistically consistent with a 1:1 relationship between the two. These findings demonstrate that wastewater surveillance of SARS-CoV-2 can be used to estimate the number of infected individuals in a sewershed.
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Affiliation(s)
- Christopher S. McMahan
- School of Mathematics & Statistical Sciences, Clemson University, Clemson, SC 29634, USA
| | - Dan Lewis
- Clemson Computing and Information Technology (CCIT), Clemson University, Clemson, SC 29634, USA
| | - Jessica A. Deaver
- Department of Environmental Engineering and Earth Sciences, Clemson University, Clemson, SC 29634, USA
| | - Delphine Dean
- Department of Bioengineering, Clemson University, Clemson, South Carolina 29634, USA
| | - Lior Rennert
- Department of Public Health Sciences, Clemson University, Clemson, SC 9634, USA
| | - Corey A. Kalbaugh
- Department of Public Health Sciences, Clemson University, Clemson, SC 9634, USA
| | - Lu Shi
- Department of Public Health Sciences, Clemson University, Clemson, SC 9634, USA
| | - David Kriebel
- Lowell Center for Sustainable Production and Department of Public Health, University of Massachusetts, Lowell, MA 01854, USA
| | | | - Sudeep C. Popat
- Department of Environmental Engineering and Earth Sciences, Clemson University, Clemson, SC 29634, USA
| | - Tanju Karanfil
- Department of Environmental Engineering and Earth Sciences, Clemson University, Clemson, SC 29634, USA
| | - David L. Freedman
- Department of Environmental Engineering and Earth Sciences, Clemson University, Clemson, SC 29634, USA
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Cohen A, Maile-Moskowitz A, Grubb C, Gonzalez RA, Ceci A, Darling A, Hungerford L, Fricker R, Finkielstein CV, Pruden A, Vikesland PJ. Subsewershed SARS-CoV-2 Wastewater Surveillance and COVID-19 Epidemiology Using Building-Specific Occupancy and Case Data. ACS ES&T WATER 2022; 2:2047-2059. [PMID: 37552724 PMCID: PMC9128018 DOI: 10.1021/acsestwater.2c00059] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/25/2022] [Accepted: 04/27/2022] [Indexed: 08/10/2023]
Abstract
To evaluate the use of wastewater-based surveillance and epidemiology to monitor and predict SARS-CoV-2 virus trends, over the 2020-2021 academic year we collected wastewater samples twice weekly from 17 manholes across Virginia Tech's main campus. We used data from external door swipe card readers and student isolation/quarantine status to estimate building-specific occupancy and COVID-19 case counts at a daily resolution. After analyzing 673 wastewater samples using reverse transcription quantitative polymerase chain reaction (RT-qPCR), we reanalyzed 329 samples from isolation and nonisolation dormitories and the campus sewage outflow using reverse transcription digital droplet polymerase chain reaction (RT-ddPCR). Population-adjusted viral copy means from isolation dormitory wastewater were 48% and 66% higher than unadjusted viral copy means for N and E genes (1846/100 mL to 2733/100 mL/100 people and 2312/100 mL to 3828/100 mL/100 people, respectively; n = 46). Prespecified analyses with random-effects Poisson regression and dormitory/cluster-robust standard errors showed that the detection of N and E genes were associated with increases of 85% and 99% in the likelihood of COVID-19 cases 8 days later (incident-rate ratio (IRR) = 1.845, p = 0.013 and IRR = 1.994, p = 0.007, respectively; n = 215), and one-log increases in swipe card normalized viral copies (copies/100 mL/100 people) for N and E were associated with increases of 21% and 27% in the likelihood of observing COVID-19 cases 8 days following sample collection (IRR = 1.206, p < 0.001, n = 211 for N; IRR = 1.265, p < 0.001, n = 211 for E). One-log increases in swipe normalized copies were also associated with 40% and 43% increases in the likelihood of observing COVID-19 cases 5 days after sample collection (IRR = 1.403, p = 0.002, n = 212 for N; IRR = 1.426, p < 0.001, n = 212 for E). Our findings highlight the use of building-specific occupancy data and add to the evidence for the potential of wastewater-based epidemiology to predict COVID-19 trends at subsewershed scales.
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Affiliation(s)
- Alasdair Cohen
- Department of Population Health Sciences,
Virginia Tech, Blacksburg, Virginia 24061, United
States
- Department of Civil and Environmental Engineering,
Virginia Tech, Blacksburg, Virginia 24061, United
States
| | - Ayella Maile-Moskowitz
- Department of Civil and Environmental Engineering,
Virginia Tech, Blacksburg, Virginia 24061, United
States
| | - Christopher Grubb
- Department of Statistics, Virginia
Tech, Blacksburg, Virginia 24061, United States
| | - Raul A. Gonzalez
- Hampton Roads Sanitation
District, Virginia Beach, Virginia 23455, United
States
| | - Alessandro Ceci
- Molecular Diagnostics Laboratory, Fralin Biomedical
Research Institute, Virginia Tech, Roanoke, Virginia 24016,
United States
| | - Amanda Darling
- Department of Population Health Sciences,
Virginia Tech, Blacksburg, Virginia 24061, United
States
- Department of Civil and Environmental Engineering,
Virginia Tech, Blacksburg, Virginia 24061, United
States
| | - Laura Hungerford
- Department of Population Health Sciences,
Virginia Tech, Blacksburg, Virginia 24061, United
States
| | - Ronald
D. Fricker
- Department of Statistics, Virginia
Tech, Blacksburg, Virginia 24061, United States
| | - Carla V. Finkielstein
- Molecular Diagnostics Laboratory, Fralin Biomedical
Research Institute, Virginia Tech, Roanoke, Virginia 24016,
United States
- Integrated Cellular Responses Laboratory, Fralin
Biomedical Research Institute at VTC, Roanoke, Virginia 24016,
United States
- Department of Biological Sciences,
Virginia Tech, Blacksburg, Virginia 24061, United
States
| | - Amy Pruden
- Department of Civil and Environmental Engineering,
Virginia Tech, Blacksburg, Virginia 24061, United
States
| | - Peter J. Vikesland
- Department of Civil and Environmental Engineering,
Virginia Tech, Blacksburg, Virginia 24061, United
States
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43
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Zhan Q, Babler KM, Sharkey ME, Amirali A, Beaver CC, Boone MM, Comerford S, Cooper D, Cortizas EM, Currall BB, Foox J, Grills GS, Kobetz E, Kumar N, Laine J, Lamar WE, Mantero AM, Mason CE, Reding BD, Robertson M, Roca MA, Ryon K, Schürer SC, Shukla BS, Solle NS, Stevenson M, Tallon Jr JJ, Thomas C, Thomas T, Vidović D, Williams SL, Yin X, Solo-Gabriele HM. Relationships between SARS-CoV-2 in Wastewater and COVID-19 Clinical Cases and Hospitalizations, with and without Normalization against Indicators of Human Waste. ACS ES&T WATER 2022; 2:1992-2003. [PMID: 36398131 PMCID: PMC9664448 DOI: 10.1021/acsestwater.2c00045] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in wastewater has been used to track community infections of coronavirus disease-2019 (COVID-19), providing critical information for public health interventions. Since levels in wastewater are dependent upon human inputs, we hypothesize that tracking infections can be improved by normalizing wastewater concentrations against indicators of human waste [Pepper Mild Mottle Virus (PMMoV), β-2 Microglobulin (B2M), and fecal coliform]. In this study, we analyzed SARS-CoV-2 and indicators of human waste in wastewater from two sewersheds of different scales: a University campus and a wastewater treatment plant. Wastewater data were combined with complementary COVID-19 case tracking to evaluate the efficiency of wastewater surveillance for forecasting new COVID-19 cases and, for the larger scale, hospitalizations. Results show that the normalization of SARS-CoV-2 levels by PMMoV and B2M resulted in improved correlations with COVID-19 cases for campus data using volcano second generation (V2G)-qPCR chemistry (r s = 0.69 without normalization, r s = 0.73 with normalization). Mixed results were obtained for normalization by PMMoV for samples collected at the community scale. Overall benefits from normalizing with measures of human waste depend upon qPCR chemistry and improves with smaller sewershed scale. We recommend further studies that evaluate the efficacy of additional normalization targets.
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Affiliation(s)
- Qingyu Zhan
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Kristina M. Babler
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Mark E. Sharkey
- Department
of Medicine, University of Miami Miller
School of Medicine, Miami, Florida 33136, United States
| | - Ayaaz Amirali
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Cynthia C. Beaver
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Melinda M. Boone
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Samuel Comerford
- Department
of Medicine, University of Miami Miller
School of Medicine, Miami, Florida 33136, United States
| | - Daniel Cooper
- DataGrade
Solutions, LLC, Miami, Florida 33173, United
States
| | - Elena M. Cortizas
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Benjamin B. Currall
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Jonathan Foox
- Department
of Physiology and Biophysics, Weill Cornell
Medical College, New York
City, New York 10021, United States
| | - George S. Grills
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Erin Kobetz
- Department
of Medicine, University of Miami Miller
School of Medicine, Miami, Florida 33136, United States
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Naresh Kumar
- Department
of Public Health Sciences, University of
Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Jennifer Laine
- Environmental
Health and Safety, University of Miami, Miami, Florida 33146, United States
| | - Walter E. Lamar
- Facilities
Safety & Compliance, University of Miami
Miller School of Medicine, Miami, Florida 33136, United States
| | - Alejandro M.A. Mantero
- Department
of Public Health Sciences, University of
Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Christopher E. Mason
- Department
of Physiology and Biophysics and the WorldQuant Initiative for Quantitative
Prediction, Weill Cornell Medical College, New York City, New York 10021, United States
| | - Brian D. Reding
- Environmental
Health and Safety, University of Miami, Miami, Florida 33146, United States
| | - Maria Robertson
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Matthew A. Roca
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Krista Ryon
- Department
of Physiology and Biophysics, Weill Cornell
Medical College, New York
City, New York 10021, United States
| | - Stephan C. Schürer
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
- Department
of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, Florida 33136, United States
- Institute
for Data Science & Computing, University
of Miami, Coral Gables, Florida 33146, United
States
| | - Bhavarth S. Shukla
- Department
of Medicine, University of Miami Miller
School of Medicine, Miami, Florida 33136, United States
| | - Natasha Schaefer Solle
- Department
of Medicine, University of Miami Miller
School of Medicine, Miami, Florida 33136, United States
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Mario Stevenson
- Department
of Medicine, University of Miami Miller
School of Medicine, Miami, Florida 33136, United States
| | - John J. Tallon Jr
- Facilities
and Operations, University of Miami, Coral Gables, Florida 33146, United States
| | - Collette Thomas
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Tori Thomas
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Dušica Vidović
- Department
of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, Florida 33136, United States
| | - Sion L. Williams
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Xue Yin
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Helena M. Solo-Gabriele
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
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Cutrupi F, Cadonna M, Manara S, Postinghel M, La Rosa G, Suffredini E, Foladori P. The wave of the SARS-CoV-2 Omicron variant resulted in a rapid spike and decline as highlighted by municipal wastewater surveillance. ENVIRONMENTAL TECHNOLOGY & INNOVATION 2022; 28:102667. [PMID: 35615435 PMCID: PMC9122782 DOI: 10.1016/j.eti.2022.102667] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 05/12/2022] [Accepted: 05/12/2022] [Indexed: 05/10/2023]
Abstract
This paper highlights the extraordinarily rapid spread of SARS-CoV-2 loads in wastewater that during the Omicron wave in December 2021-February 2022, compared with the profiles acquired in 2020-21 with 410 samples from two wastewater treatment plants (Trento+suburbs, 132,500 inhabitants). Monitoring of SARS-CoV-2 in wastewater focused on: (i) 3 samplings/week and analysis, (ii) normalization to calculate genomic units (GU) inh-1 d-1; (iii) calculation of a 7-day moving average to smooth daily fluctuations; (iv) comparison with the 'current active cases'/100,000 inh progressively affected by the mass vaccination. The time profiles of SARS-CoV-2 in wastewater matched the waves of active cases. In February-April 2021, a viral load of 1.0E+07 GU inh-1 d - 1 corresponded to 700 active cases/100,000 inh. In July-September 2021, although the low current active cases, sewage revealed an appreciable SARS-CoV-2 circulation (in this period 2.2E+07 GU inh-1 d-1 corresponded to 90 active cases/100,000 inh). Omicron was not detected in wastewater until mid-December 2021. The Omicron spread caused a 5-6 fold increase of the viral load in two weeks, reaching the highest peak (2.0-2.2E+08 GU inh-1 d-1 and 4500 active cases/100,000 inh) during the pandemic. In this period, wastewater surveillance anticipated epidemiological data by about 6 days. In winter 2021-22, despite the 4-7 times higher viral loads in wastewater, hospitalizations were 4 times lower than in winter 2020-21 due to the vaccination coverage >80%. The Omicron wave demonstrated that SARS-CoV-2 monitoring of wastewater anticipated epidemiological data, confirming its importance in long-term surveillance.
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Affiliation(s)
- Francesca Cutrupi
- Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, 38123 Trento, Italy
| | - Maria Cadonna
- ADEP, Agenzia per la Depurazione (Wastewater Treatment Agency), Autonomous Province of Trento, via Gilli 3, 38121 Trento, Italy
| | - Serena Manara
- Department of Cellular Computational and Integrative Biology-CIBIO, Via Sommarive 9, 38123 Trento, Italy
| | - Mattia Postinghel
- ADEP, Agenzia per la Depurazione (Wastewater Treatment Agency), Autonomous Province of Trento, via Gilli 3, 38121 Trento, Italy
| | - Giuseppina La Rosa
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy
| | - Elisabetta Suffredini
- Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Rome, Italy
| | - Paola Foladori
- Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, 38123 Trento, Italy
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45
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Prasek SM, Pepper IL, Innes GK, Slinski S, Ruedas M, Sanchez A, Brierley P, Betancourt WQ, Stark ER, Foster AR, Betts-Childress ND, Schmitz BW. Population level SARS-CoV-2 fecal shedding rates determined via wastewater-based epidemiology. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 838:156535. [PMID: 35688254 PMCID: PMC9172256 DOI: 10.1016/j.scitotenv.2022.156535] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 05/14/2022] [Accepted: 06/03/2022] [Indexed: 05/21/2023]
Abstract
Wastewater-based epidemiology (WBE) has been utilized as an early warning tool to anticipate disease outbreaks, especially during the COVID-19 pandemic. However, COVID-19 disease models built from wastewater-collected data have been limited by the complexities involved in estimating SARS-CoV-2 fecal shedding rates. In this study, wastewater from six municipalities in Arizona and Florida with distinct demographics were monitored for SARS-CoV-2 RNA between September 2020 and December 2021. Virus concentrations with corresponding clinical case counts were utilized to estimate community-wide fecal shedding rates that encompassed all infected individuals. Analyses suggest that average SARS-CoV-2 RNA fecal shedding rates typically occurred within a consistent range (7.53-9.29 log10 gc/g-feces); and yet, were unique to each community and influenced by population demographics. Age, ethnicity, and socio-economic factors may have influenced shedding rates. Interestingly, populations with median age between 30 and 39 had the greatest fecal shedding rates. Additionally, rates remained relatively constant throughout the pandemic provided conditions related to vaccination and variants were unchanged. Rates significantly increased in some communities when the Delta variant became predominant. Findings in this study suggest that community-specific shedding rates may be appropriate in model development relating wastewater virus concentrations to clinical case counts.
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Affiliation(s)
- Sarah M Prasek
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Ian L Pepper
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Gabriel K Innes
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8(th) St., Yuma, AZ 85364, USA
| | - Stephanie Slinski
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8(th) St., Yuma, AZ 85364, USA
| | - Martha Ruedas
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8(th) St., Yuma, AZ 85364, USA
| | - Ana Sanchez
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8(th) St., Yuma, AZ 85364, USA
| | - Paul Brierley
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8(th) St., Yuma, AZ 85364, USA
| | - Walter Q Betancourt
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Erika R Stark
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Aidan R Foster
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Nick D Betts-Childress
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Bradley W Schmitz
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8(th) St., Yuma, AZ 85364, USA.
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46
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Welling CM, Singleton DR, Haase SB, Browning CH, Stoner BR, Gunsch CK, Grego S. Predictive values of time-dense SARS-CoV-2 wastewater analysis in university campus buildings. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 835:155401. [PMID: 35469858 PMCID: PMC9026951 DOI: 10.1016/j.scitotenv.2022.155401] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 04/15/2022] [Accepted: 04/16/2022] [Indexed: 05/14/2023]
Abstract
Wastewater-based SARS-CoV-2 surveillance on college campuses has the ability to detect individual clinical COVID-19 cases at the building-level. High concordance of wastewater results and clinical cases has been observed when calculated over a time window of four days or longer and in settings with high incidence of infection. At Duke University, twice a week clinical surveillance of all resident undergraduates was carried out in the spring 2021 semester. We conducted simultaneous wastewater surveillance with daily frequency on selected residence halls to assess wastewater as an early warning tool during times of low transmission with the hope of scaling down clinical test frequency. We evaluated the temporal relationship of the two time-dense data sets, wastewater and clinical, and sought a strategy to achieve the highest wastewater predictive values using the shortest time window to enable timely intervention. There were 11 days with clinical cases in the residence halls (80-120 occupants) under wastewater surveillance with 5 instances of a single clinical case and 3 instances of two clinical cases which also corresponded to a positive wastewater SARS-CoV-2 signal. While the majority (71%) of our wastewater samples were negative for SARS-CoV-2, 29% resulted in at least one positive PCR signal, some of which did not correlate with an identified clinical case. Using a criteria of two consecutive days of positive wastewater signals, we obtained a positive predictive value (PPV) of 75% and a negative predictive value of 87% using a short 2 day time window for agreement. A conventional concordance over a much longer 4 day time window resulted in PPV of only 60%. Our data indicated that daily wastewater collection and using a criteria of two consecutive days of positive wastewater signals was the most predictive approach to timely early warning of COVID-19 cases at the building level.
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Affiliation(s)
- Claire M Welling
- Center for Water, Sanitation, Hygiene and Infectious Disease (WASH-AID), Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States of America
| | - David R Singleton
- Department of Civil and Environmental Engineering, Duke University, Durham, NC, United States of America
| | - Steven B Haase
- Departments of Biology and Medicine, Duke University, Durham, NC, United States of America
| | - Christian H Browning
- Office of Information Technology, Duke University, Durham, NC, United States of America
| | - Brian R Stoner
- Center for Water, Sanitation, Hygiene and Infectious Disease (WASH-AID), Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States of America
| | - Claudia K Gunsch
- Department of Civil and Environmental Engineering, Duke University, Durham, NC, United States of America
| | - Sonia Grego
- Center for Water, Sanitation, Hygiene and Infectious Disease (WASH-AID), Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States of America.
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47
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Long term detection and quantification of SARS-CoV-2 RNA in wastewater in Bahrain. JOURNAL OF HAZARDOUS MATERIALS ADVANCES 2022. [PMID: 37520797 PMCID: PMC9088096 DOI: 10.1016/j.hazadv.2022.100082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Wastewater-based epidemiology is a corroborated environmental surveillance tool in the global fight against SARS-CoV-2. The analysis of wastewater for detection of SARS-CoV-2 RNA may assist policymakers to survey a specific infectious community. Herein, we report on a long-term quantification study in Bahrain to investigate the incidence of the SARS-CoV-2 RNA in wastewater during the COVID-19 pandemic. The ∼260,000 population of Muharraq Island in Bahrain is served by a discrete sewerage catchment, and all wastewater flows to a single large Sewage Treatment Plant (STP) with a capacity of 100,000 m3/day. The catchment is predominately domestic, but also serves several hospitals and Bahrain's international airport. Flow-weighted 24-h composite wastewater samples for the period February 2020 to October 2021 were analyzed for the presence of SARS-CoV-2 N1, N2 and E genes. A Spearman rank correlation demonstrated a moderate correlation between the concentration of SARS-CoV-2 N1, N2 and E genes in the wastewater samples and the number of COVID-19 cases reported on the same day of the sampling. SARS-CoV-2 viral genes were detected in wastewater samples shortly after the first cases of COVID-19 were reported by the health authorities in Bahrain by reverse transcription-polymerase chain reaction (RT-qPCR). The viral genes were detected in 55 of 65 samples (84.62%) during the whole study period and the concentration range was found to be between 0 and 11,508 RNA copies/mL across the viral genes tested (in average N1: 518.4, N2: 366.8 and E: 649.3 copies/mL). Furthermore, wastewater samples from two COVID-19-dedicated quarantine facilities were analysed and detected higher SARS-CoV-2 gene concentrations (range 27-19,105 copies/mL; in average N1: 5044, N2: 4833 and E: 8663 copies/mL). Our results highlight the potential use of RT-qPCR for SARS-CoV-2 detection and quantification in wastewater and present the moderate correlation between concentration of SARS-CoV-2 genes with reported COVID-19 cases for a specified population. Indeed, this study identifies this technique as a mechanism for long term monitoring of SARS-CoV-2 infection levels and hence provides public health and policymakers with a useful environmental surveillance tool during and after the current pandemic.
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48
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El-Malah SS, Saththasivam J, Jabbar KA, K K A, Gomez TA, Ahmed AA, Mohamoud YA, Malek JA, Abu Raddad LJ, Abu Halaweh HA, Bertollini R, Lawler J, Mahmoud KA. Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance. ENVIRONMENTAL TECHNOLOGY & INNOVATION 2022; 27:102775. [PMID: 35761926 PMCID: PMC9220754 DOI: 10.1016/j.eti.2022.102775] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 05/30/2022] [Accepted: 06/19/2022] [Indexed: 05/06/2023]
Abstract
The apparent uncertainty associated with shedding patterns, environmental impacts, and sample processing strategies have greatly influenced the variability of SARS-CoV-2 concentrations in wastewater. This study evaluates the use of a new normalization approach using human RNase P for the logic estimation of SARS-CoV-2 viral load in wastewater. SARS-CoV-2 variants outbreak was monitored during the circulating wave between February and August 2021. Sewage samples were collected from five major wastewater treatment plants and subsequently analyzed to determine the viral loads in the wastewater. SARS-CoV-2 was detected in all the samples where the wastewater Ct values exhibited a similar trend as the reported number of new daily positive cases in the country. The infected population number was estimated using a mathematical model that compensated for RNA decay due to wastewater temperature and sewer residence time, and which indicated that the number of positive cases circulating in the population declined from 765,729 ± 142,080 to 2,303 ± 464 during the sampling period. Genomic analyses of SARS-CoV-2 of thirty wastewater samples collected between March 2021 and April 2021 revealed that alpha (B.1.1.7) and beta (B.1.351) were among the dominant variants of concern (VOC) in Qatar. The findings of this study imply that the normalization of data allows a more realistic assessment of incidence trends within the population.
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Affiliation(s)
- Shimaa S El-Malah
- Qatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar
| | - Jayaprakash Saththasivam
- Qatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar
| | - Khadeeja Abdul Jabbar
- Qatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar
| | - Arun K K
- Qatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar
| | - Tricia A Gomez
- Qatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar
| | - Ayeda A Ahmed
- Genomics Laboratory, Weill Cornell Medicine-Qatar (WCM-Q), Cornell University, Doha, Qatar
| | - Yasmin A Mohamoud
- Genomics Laboratory, Weill Cornell Medicine-Qatar (WCM-Q), Cornell University, Doha, Qatar
| | - Joel A Malek
- Genomics Laboratory, Weill Cornell Medicine-Qatar (WCM-Q), Cornell University, Doha, Qatar
| | - Laith J Abu Raddad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
| | - Hussein A Abu Halaweh
- Drainage Network Operation & Maintenance Department, Public Works Authority, Doha, Qatar
| | | | - Jenny Lawler
- Qatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar
| | - Khaled A Mahmoud
- Qatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar
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Multifaceted Assessment of Wastewater-Based Epidemiology for SARS-CoV-2 in Selected Urban Communities in Davao City, Philippines: A Pilot Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19148789. [PMID: 35886640 PMCID: PMC9324557 DOI: 10.3390/ijerph19148789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 05/26/2022] [Accepted: 05/28/2022] [Indexed: 02/04/2023]
Abstract
Over 60 countries have integrated wastewater-based epidemiology (WBE) in their COVID-19 surveillance programs, focusing on wastewater treatment plants (WWTP). In this paper, we piloted the assessment of SARS-CoV-2 WBE as a complementary public health surveillance method in susceptible communities in a highly urbanized city without WWTP in the Philippines by exploring the extraction and detection methods, evaluating the contribution of physico-chemical–anthropogenic factors, and attempting whole-genome sequencing (WGS). Weekly wastewater samples were collected from sewer pipes or creeks in six communities with moderate-to-high risk of COVID-19 transmission, as categorized by the City Government of Davao from November to December 2020. Physico-chemical properties of the wastewater and anthropogenic conditions of the sites were noted. Samples were concentrated using a PEG-NaCl precipitation method and analyzed by RT-PCR to detect the SARS-CoV-2 N, RdRP, and E genes. A subset of nine samples were subjected to WGS using the Minion sequencing platform. SARS-CoV-2 RNA was detected in twenty-two samples (91.7%) regardless of the presence of new cases. Cycle threshold values correlated with RNA concentration and attack rate. The lack of a sewershed map in the sampled areas highlights the need to integrate this in the WBE planning. A combined analysis of wastewater physico-chemical parameters such as flow rate, surface water temperature, salinity, dissolved oxygen, and total dissolved solids provided insights on the ideal sampling location, time, and method for WBE, and their impact on RNA recovery. The contribution of fecal matter in the wastewater may also be assessed through the coliform count and in the context of anthropogenic conditions in the area. Finally, our attempt on WGS detected single-nucleotide polymorphisms (SNPs) in wastewater which included clinically reported and newly identified mutations in the Philippines. This exploratory report provides a contextualized framework for applying WBE surveillance in low-sanitation areas.
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Phan T, Brozak S, Pell B, Gitter A, Mena KD, Kuang Y, Wu F. A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.07.17.22277721. [PMID: 35898336 PMCID: PMC9327624 DOI: 10.1101/2022.07.17.22277721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor SARS-CoV-2 transmission. However, epidemiological inference from WBS data remains understudied and limits its application. In this study, we have established a quantitative framework to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission through integrating WBS data into an SEIR-V model. We conceptually divide the individual-level viral shedding course into exposed, infectious, and recovery phases as an analogy to the compartments in population-level SEIR model. We demonstrated that the temperature effect on viral losses in the sewer can be straightforwardly incorporated in our framework. Using WBS data from the second wave of the pandemic (Oct 02, 2020 â€" Jan 25, 2021) in the Great Boston area, we showed that the SEIR-V model successfully recapitulates the temporal dynamics of viral load in wastewater and predicts the true number of cases peaked earlier and higher than the number of reported cases by 16 days and 8.6 folds ( R = 0.93), respectively. This work showcases a simple, yet effective method to bridge WBS and quantitative epidemiological modeling to estimate the prevalence and transmission of SARS-CoV-2 in the sewershed, which could facilitate the application of wastewater surveillance of infectious diseases for epidemiological inference and inform public health actions.
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Affiliation(s)
- Tin Phan
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, New Mexico, USA
| | - Samantha Brozak
- School of Mathematical and Statistical Sciences, Arizona State University, Arizona, USA
| | - Bruce Pell
- Department of Mathematics and Computer Science, Lawrence Technological University, MI, USA
| | - Anna Gitter
- The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, USA 77030
| | - Kristina D. Mena
- The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, USA 77030
| | - Yang Kuang
- School of Mathematical and Statistical Sciences, Arizona State University, Arizona, USA
| | - Fuqing Wu
- The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, USA 77030
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